SEE 2017 USQ SPRINGFIELD BRISBANE, AUSTRALIASCIENCE, ENGINEERING AND ENVIRONMENTiPROCEEDINGS OF THIRD INTERNATIONAL CONFERENCE – SEE 2017
SCIENCE, ENGINEERING & ENVIRONMENT USQ SPRINGFIELD BRISBANE, AUSTRALIA
13-15 November, 2017

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

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

THE GEOMATE INTERNATIONAL SOCIETYii

Copyright @ 2017 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: 978-4-9905958-9-0 C3051

iii

Third International Conference on Science, Engineering & Environment,
USQ Springfield Brisbane, Australia, Nov.21-23, 2017, ISBN: 978-4-9905958-9-0 C3051

Table of Contents
Prefacexi

Organization

xii

ID

Keynote Papers

1

1k

MECHANICS OF GEOSYNTHETICS SUBJECTED TO CHEMICAL EXPOSURE: EXPERIMENTS,
CONSTITUTIVE MODELS AND COMPUTATIONS
A.P.S. Selvadurai

2

2k

MEETING THE CHALLENGES OF ENGINEERING A SUSTAINABLE FUTURE
David Thorpe

123k

STATISTICS FOR EVIDENCE-BASED DECISIONS – USE, MISUSE AND ABUSE
Shahjahan Khan and M Ashraf Memon

22

Technical Papers

31

ID

32

Science3522

SEA LEVEL IN A CHANGING CLIMATEMaria McCrann, Dr John Russell, Dr Daniela Ionescu and Dr Bandita Mainali

33

3534

EBOLA VIRAL PROTEIN 24 (VP24) INHIBITOR DISCOVERY BY IN SILICO FRAGMENT-BASEDDESIGN
Syafrida Siregar, Erwin Prasetya Toepak, Usman Sumo Friend Tambunan

39

3535

FRAGMENT-BASED LEAD COMPOUND DESIGN TO INHIBIT EBOLA VP35 THROUGHCOMPUTATIONAL STUDIES
Atika Marnolia, Erwin Prasetya Toepak, Usman Sumo Friend Tambunan

45

3547

DEVELOPMENT OF SPECIFIC ELECTROCHEMICAL BIOSENSOR BASED ON CHITOSAN MODIFIEDSCREEN PRINTED CARBON ELECTRODE FOR THE MONITORING OF CAPTAN FUNGICIDE
Porntip Wongkaew, Buddhapala Wongkaew, Suwita Saepaisan, and Panupong Thanutong

51

3548

A BASIC STUDY ON FLUID PREDICTION OF MORTAR WITH VARIOUS POWDERS
Yuki takagi, Koji Takasu, Hidehiro Koyamada and Hiroki Suyama

57

3549

PHYTOCHEMICALS AND ANTIOXIDANT ACTIVITIES OF THAI RED RICE SEEDS FROM DIFFERENTCULTIVATED AREAS
Muntana Nakornriab, Jiraporn Krasaetep, Maratree Plainsirichai and Sisikka Wannajun

62

3550

A STUDY ON PROPERTIES OF MORTAR WITH FLY ASH REMOVEDFLOTATION METHOD
Rika Oie, Koji Takasu, Hidehiro Koyamada and Hiroki Suyama

67

iv

UNBURNED CARBON BY

3551

A STUDY ON PROPERTIES OF WITH FLY ASH REMOVED UNBURNED CARBON BY FLOTATIONMETHOD
Yuto Murakami, Koji Takasu, Hidehiro Koyamada and Hiroki Suyama

72

3559

CHARACTERIZATION OF CERIUM OXIDE-CHITOSAN NANOCOMPOSITE–MODIFIED SCREEN
PRINTED CARBON ELECTRODE AND APPLICATION IN MELATONIN DETERMINATION
Pachanuporn Sunon, Porntip Wongkaew, Jeffrey Johns, Nutjaree Johns

77

3564

COMPARISON OF HEART RATE VARIABILITY BETWEEN PATIENTS WITH MAJOR DEPRESSIVEDISORDER AND NORMAL SUBJECTS
Warangkana Chompoopan, Sipanut Silaket, Wichai Eungpinichpong, Suwanna
Arunpongpaisal and Niramol Patjanasoontorn

83

3566

EFFECT OF ARM SWING EXERCISES ON CARDIOVASCULAR RESPONSE AND BALANCE OF
OLDER WOMEN
Worawut Chompoopan, Piyathida Kuhirunyaratn

87

3578

PLASTIC FLOW HETEROGENEITY AND FAILURE OF BIMETAL MATERIAL
Svetlana Barannikova, Lev Zuev1and Yulia Li

91

3606

SEARCHING OF NEW ANTIVIRAL COMPOUNDS OF SUDAN EBOLAVIRUS GLYCOPROTEIN BASEDON FLAVONOID COMPOUNDS USING IN SILICO METHODS
Rendy Pramuda Putra, Ahmad Husein Alkaff, Mochammad Arfin Fardiansyah Nasution andAgustinus C. B. Kantale, and Usman Sumo Friend Tambunan

97

3622

NEW ESTIMATION IN AR MODELS WITH EXPONENTIAL WHITE NOISE BY USING REVERSIBLE
JUMP MCMC ALGORITHM
Suparman

103

3623

ECOLOGY AND CONSERVATION OF INDIAN HORNBILLS WITH PARTICULAR REFERENCE TO
NARCONDAM HORNBILL (ACEROS NARCONDAMI) OCCURRING ON NARCONDAM ISLAND OF
ANDAMAN& NICOBAR ISLAND ARCHIPELAGO
Hafiz S.A. Yahya

107

3630

THE IMMEDIATE EFFECTS OF FOOT MASSAGE WITH COCONUT SHELL ON PRESSURE PAIN
THRESHOLD AND FOOT GRIP STRENGTH IN HEALTHY SUBJECTS: A PILOT STUDY
Laojeenwong P, Eungpinichpong W

113

3633

MOCAF TEMPEH DATES BISCUIT FOR THE IMPROVEMENT NUTRITIONAL STATUS OF
UNDERWEIGHT CHILDREN
Fatmah117

3637

SPATIAL VARIATION OF WATRBIRDS IN PALLAI AND THADDUVANKODDY IN THE NORTHERNPROVINCE, SRI LANKA
G. Kandasamy, D. K. Weerakoon, and A. Sivaruban

124

3645

FACTORS RELATED TO SELF-CARE ABILITY AMONG ELDERLY WOMEN IN SEMI-URBANCOMMUNITIES, KHON KAEN, THAILAND.
Kanchana Nimsuntorn, Piyathida Kuhirunyaratn and Kanaporn Tansriprapasiri

130

3646

IMMEDIATE EFFECTS OF THAI MASSAGE ON GAIT PARAMETERS IN NORMAL ADULTS: A PILOTSTUDY Nutthanun Tatchananusorn, Wichai Eungpinichpong, Uraiwan Chatchawan and
Donlaya Promkaew

136

3648

THAI MASSAGE COMBINED WITH MUSCLE ENERGY AND PASSIVE STATIC STRENGTHINGTECHNIQUE COULD IMPROVE HEIGHT OF SEPAKTAKRAW SERVES
Apichat Deeminoi, Dr.Wichai Eungpinichpong, Dr.Maitree Pakarasang, Dr.Thanarat
Sripongngam

140

3652

A STUDY OF THE CORRELATION BETWEEN FOUR CLINICAL TRIALS FOR THE MEASUREMENTOF HAMSTRING MUSCLE FLEXIBILITYApichat Deeminoi, Dr.ThanaratSripongngam

146

3665

EFFECTS OF KAEMPFERIA PARVIFLORA ON PHYSICAL AND PSYCHOLOGICAL STRESSES IN
ADULTS
Wichai Eungpinichpong, Uraiwan Chatchawan, Bung-orn Sripanidkulchai Suwanna
Arunpongpaisal

150

v

3673

DEVELOPMENT OF POLY (D, L-LACTIC ACID) WITH POLYBENZOXAZINE VIA SOLUTIONBLENDING
Kansiri Pakkethati and Yodthong Baimark

154

3677

BIOCHEMICAL CHANGES IN CHEMICAL INGRADIENTS OF SILK COCOONS UNDERENVIRONMENTAL FACTORS
H.N.P. Singh, Sunita Kumari and M.M. Prasad

159

3711

ACUTE EFFECTS OF TRADITONAL THAI MASSAGE ON HEART RATE VARIABILITY, HEART RATEAND SALIVARY ALPHA AMYLASE
Jaruk Keawsod Wichai Eungpinichpong

163

ID

Engineering

166

3503

SHEAR STRENGTH OF SOIL BY USING SHELL HUSKS WASTE AS RECYCLE AGGREGATE
Siti Hanggita Rachmawati, Zakaria Hossain

167

3504

ANALYTICAL STUDY ON SINGLE PILE DESIGN FOR SOLAR FOUNDATIONS FOR SLOPING LAND.
Alex Otieno Owino, Hossain, M.Z., Ojiro C., Ozumi, S., Harada, H. and Okuyama, S.

172

3510

EXPERIMENTAL BEHAVIORAL INSPECTION OF COMPOSITE CONCRETE-OPEN WEB EXPANDEDSTEEL BEAMS EXPOSED TO STATIC LOADING
Nazar K. Oukaili and Seezar Sh. Abdullah

178

3512

RESIDENTIAL CUSTOMER DEMAND RESPONSE PROGRAM IN MICROGRID SYSTEM: A SURVEY
LITERATURE
Ignatius Rendroyoko, and Ngapuli I Sinisuka

184

3514

CRACKING AND DEFORMABILITY OF BONDED AND UNBONDED PRESTRESSED CONCRETE
BEAMS UNDER MONOTONIC STATIC LOADING
Nazar K. Oukaili and Mohammed M. Khattab

190

3515

DISTRIBUTED MODEL OF HYDROLOGICAL AND SEDIMENT TRANSPORT PROCESS IN
MEKONG RIVER BASIN
Zuliziana Suif, Chihiro Yoshimura, Nordila Ahmad and Sengheng Hul

196

3516

EVALUATION OF PIER-SCOUR PREDICTIONS FOR WIDE PIERS USING FIELD DATA
Nordila Ahmad, Bruce W. Melville, Thamer Mohammad, Zuliziana Suif

202

3521

MECHANICAL CHARACTERISTICS OF ARTIFICIAL STONE MADE FROM WASTE OF SILICEOUS
TUFF
Hiroaki Shigematsu and Shogo Hashimoto

208

3528

3 DIMENSION REAL TIME IMAGES OF RAINFALL INFILTRATION INTO UNSATURATED SOIL
SLOPE
Aniza Ibrahim, Irfana Kabir Ahmad, Hapsa Husen, Jestin Jelani1and Mohd. Raihan Taha

214

3529

STEREO ECHO CANCELLATION USING ADAPTIVE NON-LINEAR NETWORK FILTER FOR HOMETHEATRE ROOM
Sunisa Kunarak

219

3530

FINITE ELEMENT ANALYSIS OF EWECS COLUMNS WITH VARYING SHEAR SPAN RATIO
Fauzan, Ruddy Kurniawan and Zev Al Jauhari

224

3538

EXPERIMENTAL INVESTIGATION ON BOX-UP COLD-FORMED STEEL COLUMNS IN FIRE
Fadhluhartini Muftah, Mohd Syahrul Hisyam Mohd Sani, Ahmad Rasidi Osman, Shahrin
Mohammad, Shek Poi Ngian

231

vi

3539

EXPERIMENTAL INVESTIGATION OF COLD-FORMED STEEL CHANNEL SECTION WITH NOTCH
Mohd Syahrul Hisyam Mohd Sani, Fadhluhartini Muftah, Muhammad Isha Ismail

237

3542

A REVIEW OF UNEXPECTED LARGE SLOPE FAILURES
Marthinus Sonnekus and John Victor Smith

243

3563

THE EFFECT OF STEEL FIBERS EXTRACTED FROM WASTE TYRE ON CONCRETE CONTAINING
PALM OIL FUEL ASH
Fauzan, Febrin Anas Ismail and Rio Sandi

249

3574

ACCURACY OF CENTRALIZED AND DECENTRALIZED MANUFACTURING SYSTEMS TOWARDS AN
INDUSTRY 4.0’S PERSPECTIVE
Poonpakdee, P. , Koiwanit, J., Yuangyai, C.

254

3576

NUMERICAL ANALYSIS OF NONLINEAR MODEL OF SFRC SLAB AND NONLINEAR SUBSOIL
MODEL IN INTERACTION
Jana VASKOVA, Radim CAJKA

260

3583

AN OVERVIEW OF THE IMPACTS OF SUSTAINABLE HOUSING DESIGN ON ENERGY EFFICIENCYOF THE AUSTRALIAN HOUSING
Javad Asad Poor , David Thorpe, Yong Goh

266

3590

VULNERABILITY ASSESSMENT OF SURIGAO METRO WATER DISTRICT UNDER SEISMIC HAZARD
Sheena I. Better and Lessandro Estelito O. Garciano

276

3591

A COMPARISON OF ESTIMATED SHEAR STRENGTH OF SOUTH-EAST QUEENSLAND RESIDUAL
SOIL USING FIELD AND LABORATORY TESTING
Darren Newell and Choo Yong

283

3593

STUDY ON LANDSLIDE CATEGORY BASE ON TEMPORAL– SPATIAL CHARACTERISTIC
DISTRIBUTION IN NORTHERN VIETNAM USING SATELLITE IMAGES
Thuy Thi Thanh LE and Seiki KAWAGOE

287

3597

THE QUALITY ANALYSIS OF BICYCLE ROUTES FOR SUSTAINABLE URBAN MOBILITY IN THE
WESTERN ZONE OF RIO DE JANEIRO
Guilherme Marins Pessanha, Jaime Massaguer Hidalgo Jr

293

3599

COMPARATIVE ANALYSIS OF PAVEMENT FRICTION PREDICTION MODELS
Luciana Omar, Karim Ismail and Abd El Halim O. Abd El Halim

299

3608

APPLICATION OF MEMETIC ALGORITHM FOR SOLVING THE VEHICLE ROUTING PROBLEM
WITH TIME WINDOWS
Chaowalit Hamontree , Jiraporn Chuenjai and Nawaporn Chamnanketgorn

305

3614

THE EFFECT OF MODEL DOMAIN SIZE FOR UNSUPPORTED PLAIN STRAIN TUNNEL HEADINGSIN UNDRAINED CLAY
Jim Shiau, Fadhil Al-Asadi

309

3656

APPLICATION OF HEC-RAS AND ARC GIS FOR FLOODPLAIN MAPPING IN SEGAMAT TOWN,
MALAYSIA
Noor Suraya Romali, Zulkifli Yusop and Ahmad Zuhdi Ismail

315

3658

EFFECT OF SATURATION ON STRENGTH BEHAVIOR OF SOAPSTONE
Ravikant R Singh, Darga Kumar Nandyala and Faijal Ali

321

3659

MEASUREMENT ACCURACY OF ORIENTATION CODE MATCHING FOR SLOPE DEFORMATIONMONITORING
Takeshi YAMAMOTO, Keigo KOIZUMI, Kazuhiro ODA, and Yoshio FUKUDA

327

vii

3670

3672

3683

NANOSTRUCTURAL CHARACTERIZATION OF GLUTATHIONE-S-TRANSFERASE IMMOBILIZINGCHITOSAN MODIFIED SCREEN PRINTED CARBON ELECTRODE BY ATOMIC FORCE MICROSCOPY
Buddhapala Wongkaew, Porntip Wongkaew, Panupong Thanutong and Chitsanuphong
Thanutong
COLUMN BASED INFILTRATION EXPERIMENT FOR CONSIDERING INITIAL QUASI-SATURAETEDVOLUMETRIC WATER CONTENT DUE TO DEFFERENCES OF WATER SPRAY INTENSITY AND
GRAIN SIZE DISTRIBUTION
Hiroshi Kita, Keigo Koizumi and Kazuhiro Oda and Mitsuru Komatsu
ENVIRONMENTAL RISK ASSESSMENT AND MANAGEMENT OF BIOMASS POWER PLANTS FORSUSTAINABILITY IN THAILAND Manutchanok Jongprasithporn, Adisak Martsri, Supapat
Phuangkaew, Wannapong Yeamma,
and Nantakrit Yodpijit

332

338

342

3686

THE DESIGN OF AN ALTERNATIVE ENERGY DATABASE IN THAILAND
Manutchanok Jongprasithporn,Supapat Phuangkaew, Siravitch Atipatha, and Nantakrit
Yodpijit

348

3691

NUMERICAL INVESTIGATION OF 2D TRAPDOOR STABILITY
Jim Shiau, Mohammad Mirza Hassan

354

3695

INSTALLATION CONSTRAINTS OF SUCTION ASSISTED FOUNDATIONS AND ANCHORS FOR
OFFSHORE ENERGY DEVELOPMENT
Kingsley Osezua Akeme, Alireza Rezagholilou and Meysam Banimahd

360

3706

DIFFERNTIAL THERMAL ANALYSIS OF PMMA (POLY METHYL METHACRYLATE) EXPERIMENTAL CONCERNSSam M Dakka

368

3717

INVESTIGATION OF CURING PERIOD OF CEMENTITIOUS ADHESIVE AND PERFORMANCE OF
RUST PREVENTION
YoichiMimura, Vanissorn Vimonsatit and Isamu Yoshitake

373

3721

REGIONAL DEPOSITION CHARACTERISTICS OF NANOPARTICLES IN A RAT NASAL CAVITY
Yidan Shang, Jingliang Dong, Kiao Inthavong and Jiyuan Tu

379

3733

SEGMENTATION OF PAP SMEAR IMAGES TO IDENTIFY AND DETECT CERVICAL CANCER
Vasundhara Acharya, Preetham Kumar

383

ID

Environment

390

3506

NUTRIENT LOADS AND SELF-REMEDIATION ASSESSMENT IN KHLONG RUNGSIT TAI, PATHUM
THANI PROVINCE, THAILAND
Boontarika Thongdonphum, Kittima Vanichkul, Saming Champasri and Jirapon Kulkham

391

3517

INFLUENCE OF ABIOTIC STRESS FACTORS ON BLACKCURRANT RESISTANCE TO PESTS
I.V. Mashkova, T.G. Krupnova, A.M. Kostryukova

395

3518

USING BIRCH LEAVES TO INDICATE AIR POLLUTION
T.G. Krupnova, I.V. Mashkova and A.M. Kostryukova

399

3519

STUDY OF SYNANTHROPIC PLANTS OF THE SOUTH URAL
A.M. Kostryukova, I.V. Mashkova, T.G. Krupnova and E.E. Shchelkanova

405

3531

A STUDY ON THE EFFECTIVENESS OF LIQUID SMOKE PRODUCED FROM PALM KERNEL SHELLSIN INHIBITING BLACK POD DISEASE IN CACAO FRUIT IN VITRO
M. Faisal, Tjut Chamzurni, Hiroyuki Daimon

411

viii

3543

HEAVY METALS IN MICROALGAE BIOMASS ADDED WITH DIFFERENT CONCENTRATION OF
WET MARKET WASTEWATER
Radin Maya Saphira Radin Mohamed, Najeeha Apandi, Siti Nor Hidayah Arifin, A.A.S.
Al-Gheethi and Amir Hashim Mohd Kassim

417

3546

INFLUENCING PARAMETER OF SELF PURIFICATION PROCESS IN THE URBAN AREA OFCIKAPUNDUNG RIVER, INDONESIA
Yonik Meilawati Yustiani, Mia Nurkanti, Neneng Suliasih and Annisa Novantri

422

3562

THE PHYSICAL MICROHABITAT REQUIREMENTS OF FRESHWATER MUSSEL, WESTRALUNIOCARTERI, (BIVALVIA: HYRIIDAE) IN SOUTH-WESTERN AUSTRALIALe Ma1, Alan Lymbery, Stephen Beatty and David Morgan

426

3567

EVALUATING THE EFFECTIVENESS OF VIRGINIA BUTTONWEED FOR EROSION CONTROL OF
DAM RESERVOIR SLOPES IN JAPAN.
Taizo Uchida, Yuya Imamura, Yoshifumi Kochi, Mamoru Yamada, Kunihiko Fukaura, Aki
Matsumoto, William T. Haller and Lyn A. Gettys

432

3577

NANOCOMPOSITE WITH DUAL FUNCTIONALITY IN SIMULTANEOUS REMOVAL OF HEAVYMETALS, DYE AND ANIONIC SURFACTANT FROM MULTICOMPONENT WASTEWATERMaria Visa, Nicoleta Popa, Andreea Maria Chelaru

437

3600

EFFECT OF WATER ACTIVITY ON ENZYMES ADSORBED ON BIOMASS CHARCOAL IN ORGANIC
MEDIA
Hidetaka Noritomi, Jumpei Nishigami, Nobuyuki Endo, Satoru Kato and Katsumi Uchiyama

443

3602

EVALUATION OF ENERGY EFFICIENCY AND ENVIRONMENTAL PERFORMANCE IN LOBLAWCOMPANIES LIMITED IN CANADA
Koiwanit, J., Chan, V. K., Piewkhow, L., Katipelly, N. D.

449

3611

AN EVALUATION FOR EFFECTIVE PUBLIC PARTICIPATION IN EIA IN THAILAND
Chutarat Chompunth

455

3649

ACHIEVING WATER SENSITIVE CITY CONCEPT THROUGH MUSRENBANG MECHANISM IN
SURABAYA CITY, INDONESIA
Eddy Setiadi Soedjono, Nurina Fitriani, Rifda Rahman, I Made Wahyu Wijaya

462

3651

THE STUDY ON MITIGATION METHOD OF BEACH EROSION USING THE CORAL CELLS
Sang Kil Park, Hong Bum Park, Kyeong Mo Lim

467

3662

THE DESCRIPTION OF LIGHTING ENVIRONMENTAL ON THE URBAN STREET
Shuto Takeuchi, Kazunari Tanaka and Shin Yoshikawa

473

3684

SOCIAL AND ENVIRONMENTAL RESPONSIBILITY IN DEVELOPING COUNTRIES: A THEORETICALAPPROACH OF REGULATION
Lindrianasari, Mahatma Kufepaksi, Yuztitya Asmaranti, and Agrianti Komalasari

477

3688

ASSESSMENT OF URBAN CLIMATE CHANGE IN IPOH CITY, PERAK, MALAYSIA
Mohd Hairy Ibrahim, Mazlini Adnan, Nor Kalsum Mohd Isa & Kamarul Ismail,

482

3707

TREND OF DAILY RAINFALL AND TEMPERATURE IN PENINSULAR MALAYSIA BASED ON
GRIDDED DATA SET
Chee-Loong Wong, Zulkifli Yusop, Tarmizi Ismail

488

3708

SPATIO-TEMPORAL ANALYSIS OF LAND USE AND LAND COVER CHANGES IN ARID REGION OF
SAUDI ARABIA
Eman Albalawi, Ashraf Dewan and Robert Corner

496

ix

3718

COMPARISON OF LUNG DAMAGES DUE TO PETROL AND DIESEL CAR SMOKE EXPOSURES:HISTOLOGICAL STUDY
Wardoyo, Arinto Y.P.a, Juswono, Unggul P., Noor, Johan A. E.

502

3723

SPATIAL VARIATIONS OF SURFACE WATER QUALITY AND POLLUTION SOURCES IN KHLONGU-TAPAO RIVER BASIN
Saudee Maprasit, Chaisri Suksaroj, Vichit Rangpan, and Rotchanatch Darnsawasdi

508

3724

DIVESIRY AND POLLEN MORPHOLGY OF IMPORTANT TREE SPECIES OF RANIKOT FORT, SINDH,
PAKISTAN.
Nabila Shah Jilani, S.S Hassney, Muhammad Tahir Rajput and Feroza shar Baloch

514

3727

RELATIONSHIP BETWEEN PAVEMENT TEXTURE AND MOVEMENT
Yuki OGIMOTO,Kazunari TANAKA and shin YOSHIKAWA

517

3728

REMOVAL AMMONIA FROM LANDFILL LEACHATE USING ULTRASONIC IRRADIATION PROCESS
Sartaj M., Tobalt A., and Kennedy K.

521

3729

THE IMPLEMENTATION OF WATER SENSITIVE CITY AT DEPOK -MIDDLE CITY IN INDONESIA
Firdaus Ali, Irene Sondang, Esty Suyanti and Ahmad Zubair

524

3730

RISK MAPPING STUDIES OF HYDRO-METEOROLOGICAL HAZARD IN DEPOK MIDDLE CITY
R. Jachrizal Soemabrata, Ahmad Zubair, Irene Sondang and Esty Suyanti

528

3698

ROLE OF GOVERNMENT AND PRIVATE SECTOR IN MARINE ECOTOURISM RELATED TOCONSERVATION OF BIODIVERSITY IN SERIBU ISLANDS
Lily Surayya Eka Putri and Kristiyanto

534

3689

SEISMIC MICROZONATION FOR URBAN PLANNING AND VULNERABILITY ASSESSMENT OFNON-ENGINEERED STRUTURE IN EARTHQUAKE PRONE AREA, PADANG, INDONESIA
Rusnardi Rahmat Putra, Junji Kiyono, Ganefri Fahmi Rijal and Syahril

540

3545

RAINWATER HARVESTING STUDY AT MASJID JAMEK RIYAHDUS SOLIHIN, PINTASPUDING, BATU PAHAT JOHOR MALAYSIA
Amir Hashim Mohd Kassim, Siti Mariam Sulaiman, Radin Maya Saphira Radin Mohamed
and Adel Ali Saeed Al Gheethi
Authors Indexx549

Preface

Third International Conference on Science, Engineering & Environment,
USQ Springfield Brisbane, Australia, Nov.13-15, 2017, ISBN: 978-4-9905958-9-0

On behalf of the SEE 2017 Organizing Committee, it is our great pleasure to welcome you to the Third
International Conference on Science, Engineering & Environment, held at the USQ Springfield Brisbane
Australia organized in conjunction with University of Southern Queensland, Mie University Research Center
for Environmental Load Reduction, The GEOMATE International Society, Useful Plant Spread Society,
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

This year we have received many submissions over 50 universities of different countries all over the world
including Australia, Brazil, Canada, Czech Republic, Fiji, India, Indonesia, Iraq, Japan, Malaysia, Philippines
Romania, Russia, South Korea, Sri Lanka and Thailand. The technical papers were selected from the vast
number of contributions submitted after a review of the abstracts. The final papers in the proceedings havebeen peer reviewed rigorously and revised as necessary by the authors. It relies on the solid cooperation ofnumerous 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 2017. 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, Conference Chairman (General)
Dr. Jim Shiau, Conference Chairman (Program)xi

Organization

Third International Conference on Science, Engineering & Environment,
USQ Springfield Brisbane, Australia, Nov.13-15, 2017, ISBN: 978-4-9905958-9-0

Scientific Committees:
Conference Honorary Chairmen:
Dr. John Yeaman, Professor, Univ. of the S/Coast, Australia
Dr. Sohji Inoue, Emeritus Professor, Mie University, Japan
Conference Chairmen:
Dr. Jim Shiau, Senior Lecturer, USQ, Australia (Program Chair)Dr. Zakaria Hossain, Prof. Mie Univ., Japan (General Chair)Conference Organizing Committee:
Dr. Jim Shiau, S./Lec. Univ. of Southern Queensland, Australia
Dr. Stephen Buttling, Principal, National Geo. Cons., Australia
Dr. Karu Karunasena, Prof. USQ, Australia
Dr. David Thorpe, A/Prof., USQ, Australia
Dr. Toshinori Sakai, Prof. Mie University, Japan
Dr. Zakaria Hossain, Prof. Mie University, Japan
National & International Advisory Committee:
Dr. Allan Manalo, Senior Lecturer, USQ, Australia
Dr. Soma Somasundaraswaran, Lecturer, USQ, Australia
Dr. John Smith, A/Prof. RMIT University, Australia
Dr. Arul Arulrajah, Prof. Swinburne Univ. of Tech., Australia
Dr. Robert Evans, A/Prof., Swinburne Univ. of Tech., Australia
Dr. Chaminda Gallage, A/Prof, Queensland Uni. of Tec, Australia
Dr. Iyad Alkroosh, A/Prof., Curtin University, Australia
Dr. Sammy Kwok, Geo. Eng. Cardno Bowler, Australia
Dr. Jun Sugawara, S/Eng. Golder Associates Pty Ltd, Australia
Dr. N. Sivakugan, A/Prof. James Cook Univ., Australia
Dr. Erwin Oh, Senior Lecturer, Griffith University, Australia
Dr. Fumio Tatsuoka, Prof. Tokyo University of Science, Japan
Dr. Jing-Cai Jiang, Prof. University of Tokushima, Japan
Dr. Toshihiro Morii, Prof. Niigata University, Japan
Dr. Kimitoshi Hayano, Prof. Yokohama National Univ., 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., UTHM, Malaysia
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. Hj. Ramli Bin Hj. Nazir, A/Prof.. UTM, Malaysia
Dr. Aly Ahmed, A/Prof.. Beni-Suef University, Egypt
Dr. Chang-Yu Ou, Prof. National Taiwan Univ. of Sci. &Tech.
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

xii

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, Poland
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, Egyptxiii

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, Thailand
Dr. Hamidreza Namazi, Nanyang Technological University, Singapore
Dr. Parichat Phumkhachorn, Ubon Ratchathani University, Thailand
Dr. Subhasis Roy, University of Calcutta, India

Conference Correspondence:
Dr. Jim Shiau, Senior Lecturer, USQ, Australia, Program Chair
Dr. Zakaria Hossain, General Chair,Prof. Graduate School of Bioresources,
Mie University 1577 Kurima Machiya-cho, Tsu-city,xivMie 514-8507 Japan, E-mail: editor@geomate.org
Tel & Fax: +81-59-231-9578
Conference History:
SEE-Mie, Japan, Nov. 19-21, 2015
Chairman: Prof. Dr. Satoshi Kaneco, Mie University, Japan
SEE-Osaka, Japan, Nov. 21-23, 2016
Chairman: Prof. Dr. Zakaria Hossain, Mie University, Japan
Editorial and Executive Committee:
Prof. Dr. Zakaria Hossain
Dr. Jim Shiau
Ms. Siti Hanggita Rachmawati
Mr. Md. Aminul Islam
Mr. Alex Otieno Owino
Note- A: Associate, E-Emeritus

xv

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

Keynote Papers

1Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

MECHANICS OF GEOSYNTHETICS SUBJECTED TO CHEMICALEXPOSURE: EXPERIMENTS, CONSTITUTIVE MODELS ANDCOMPUTATIONS
A.P.S. Selvadurai
Department of Civil Engineering and Applied Mechanics
McGill University, Canada.

ABSTRACTThis article is a review of recent research related to the development of advanced mathematical models fordescribing the behaviour of strain rate sensitive materials such as geosynthetics that are used extensively as
barriers to the migration of contaminants and other hazardous materials. The important finding of the research isthat the leaching of the plasticizer from the geosynthetic can lead to a loss of hyperelasticity of the material,
which is a key functional requirement for a geosynthetic. It is also shown that constitutive models can be
developed to describe the mechanical behaviour of the geosynthetic in its virgin state and upon direct exposure
to pure ethanol for thirteen months. The mathematical models developed using results of uniaxial tests can beincorporated in a general purpose finite element code. This computational approach is used to evaluate theresults of separate laboratory experiments involving transverse indentation of geosynthetic membranes that are
fixed along a circular boundary and tested in either its untreated state or after prolonged exposure to ethanol. The
computational predictions compare very accurately with experimental results in the loading mode of both treatedand untreated geosynthetics. The irreversible deformations of the geosynthetic subjected to transverse loading issatisfactory and can be further improved by re-examining the rate-sensitive plasticity model used in themodelling.
Keywords: Geosynthetics, Chemical exposure, Loss of elasticity properties; Embrittlement, Computationalmodelling, Rate-sensitive materials, Indentation tests for membranesinteraction of the geosynthetic with chemicals suchas acetone and ethanol leads to the loss ofplasticizers that contribute to the hyperelasticity ofthe material. The flexibility of a geosynthetic isderived largely from plasticizers incorporated into
its chemical composition. Recent research has shownthat the exposure of the geosynthetic membranes tochemicals such as acetone and ethanol can lead toembrittlement of the membrane through the leachingof the plasticizer. The longevity of the containment
provided by PVC geosynthetics can be influenced bythese factors, specifically in situations involving thethermal desiccation of clay. Desiccation cracking
can be caused by moisture depletion in the clay
barrier following exothermic processes associatedwith the decay of organic matter in the landfill. A
cracked clay barrier provides a pathway forcontaminants to come into direct contact with ageosynthetic barrier. The direct exposure of theplasticized PVC membrane to chemical action is aproblem of major concern. The exposure of the PVC
to chemicals can result in mechanical alterations in
the material, largely as a result of leaching of theplasticizer, which contributes to the flexibility of the
PVC [2]. Exposure to commonly occurring
chemicals such as acetone and ethanol can lead to aloss of hyperelasticity in the geosynthetics [3,4].
Uniaxial experiments (Figure 1) conducted inconnection with this research also show an alteration

INTRODUCTION
Polyvinyl chloride (PVC) membranes, also
referred to as geosynthetics or geomembranes, areused quite extensively in geoenvironmental
endeavours in order to prevent groundwatercontamination due to leakage of leachates fromlandfill and from hazardous waste sites such as minetailings ponds. PVC membranes constitute animportant component of multi-barrier containment
systems that also consist of alternate layers ofimpermeable clay and collection systems.
Geosynthetic membranes used as landfill liners canbe exposed to adverse environments, including heat,ultra-violet light (prior to commissioning of alandfill site), bacteria and chemicals [1]. Althoughgeosynthetics are widely used in geoenvironmental
engineering practice, the assessment of the long term
effectiveness of these materials under exposure tochemicals, ultra-violet light, radiation, etc., stillneeds concerted attention. The chemical properties
and other details of the untreated PVC material are
given in [1].
A primary requirement of a geosynthetic relates
to its ability to undergo large deformations and tomaintain its integrity, thereby impeding the
migration of hazardous chemicals and contaminants
to the environment. Experiments conducted inconnection with this research indicate that the2SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

in the mechanical properties of a PVC membranes
during exposure to pure ethanol. These alterations
include a progressive loss of large strain flexibility,
embrittlement, the development of a distinct initial
linear elastic modulus and the development of ayield point (Figure 2). The initial linear elastic
modulus and the yield stress of the material
continuously increase over an exposure period of 2
months after which there is a slight decrease in thepeak yield value, which remains unaltered during
further exposure.

convenient model for the examination of theconstitutive behaviour of a geosynthetic both in its
untreated state and after prolonged exposure toethanol.

Fig. 1 Uniaxial testing of specimens of PVC
membranes
The rapid alteration in the mechanical propertiesof the geosynthetic membrane in the first twomonths correlates well with the X-Ray fluorescenceevidence, which also indicates a loss of plasticizer
during this period. The plasticizer content is
identified through the weight ratio RO / Cl of theoxygen element and chloride element in thegeosynthetic specimen that has been originallyplasticized with 25-35% weight content of aphthalate plasticizer. The loss of plasticizer after a
two-month exposure to pure ethanol leads to (i) areduction in the flexibility of the geosynthetic, (ii) an
increase in the failure stress and (iii) the
development of a strain-hardening regime in the
stress-strain response (Figure 2).
For PVC geosynthetics that have been exposed toethanol for a period of 13 months, the stress-strain
behaviour of the specimen exhibits a mechanicalresponse similar to a PVC material containing a very
low content of DOP (Dioctyl phthalate) plasticizer(less than 15%) [2]. With significant loss ofplasticizer from the specimen, the PVC geosynthetic
subjected to a 13-month chemical exposure shows
only moderate deformability with a failure strain of
about 20%. For a specimen that is loaded at a lower

Fig. 2 Behaviour of PVC specimens during exposure
to pure ethanol.
CONSTITUTIVE MODELLING
Purely hyperelastic rubber-like materials exhibit
virtually no irreversible phenomena in terms ofpermanent deformations and energy dissipation
during quasi-static load cycling [6-11]. In contrast,
glassy polymeric materials exhibit appreciable
irreversible effects including development of
permanent strains during loading-unloading cycles
and strain-rate effects [12]. The constitutive
modelling of such materials can be approached at avariety of levels ranging from elementary power law
creep models to generalized continuum models
applicable to non-linear viscoelastic materials. The
This paper presents constitutive models that firstdescribe the hyperelastic behaviour of a geosynthetic
material in it’s as supplied condition. The modelling
accounts for both reversible and irreversible
components of hyperelastic behaviour andincorporates strain rate dependency in thestrain-rate (e.g. 0.05 min −1 ), however, the large
strain deformability of a PVC material with a low
content of plasticizer can be recovered [5]. The
results of the computational simulations arecompared with the experimental results. We observethat the constitutive models that use a basic
hyperelastic constitutive relationship of the MooneyRivlin form, where the parameters are strain rateand chemical exposure-dependent, provides a3

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

constitutive response. The constitutive modelling isthen extended to include the loss of hyperelasticity
as a result of exposure to pure ethanol. The
constitutive parameters were determined fromuniaxial tests and constrained tests conducted at
different strain rates. The constitutive models were
implemented in a general purpose finite element
code to examine the mechanics of a membrane fixedalong a circular boundary and loaded by a hemispherical indenter. chemical action on thesematerials is to leach out the plasticizer that provides
large strain capability without initiation of fracture
and/or damage. This paper presents the results ofexperiments conducted on PVC in its as suppliedstate and subjected to chemical treatment, in order todetermine the constitutive relationships that govern
hyperelastic behaviour as well as loss of
hyperelasticity during chemical action (Selvadurai
and Yu [13-15]; Yu and Selvadurai [1,16]). The
constitutive
modelsdeveloped,
take
into
consideration strain-rate sensitivity and large strain
effects in the untreated material and distinct yieldand strain-rate sensitivity in the chemically treatedmaterial. The modelling uses forms of constitutive
potentials that are derived from hyperelastic
rubberlike materials undergoing moderately large
strains. We consider the deformation such that theposition of a generic particle in the deformed
configuration is denoted by xi (i = 1,2 ,3) and the

The invariants of B e , Bu areI1h = (λ1h ) 2 + (λ2h ) 2 + (λ3h ) 2
I 2h =

+

1

+

1

(5)

(λ1h ) 2 (λ2h ) 2 (λ3h ) 2(h e,u )I 3h λ1h λ2h=
λ3h 1;==eu
and λi and λi (i = 1,2 ,3) are, respectively, theprincipal stretches of the elastic and irreversible
components. In this research, the general
constitutive model for both the untreated andchemically treated PVC has been selected toconform to a single generic form (Figure 3). The
large elastic deformation can be modelled throughthe introduction of a strain energy function W e(component C) of a modified Mooney-Rivlin form,
which is considered to be a satisfactory form of astrain energy function for hyperelastic materials thatexperience moderately large strains [17-26]. The
irreversible deformation can be characterized by avisco-plastic model, which can be visualized asconsisting of an elastic component A of the finite
strain contributing to the elastic recovery, in parallelwith a visco-plastic component B that accounts forthe rate-dependent effects during unloading. The
finite strain component A, which is similar tocomponent C, can be characterized by a strain

coordinates of the same particle in the reference
configuration are denoted by X A (A = 1,2 ,3) .

energy function W u of the Mooney-Rivlin form.
The component C is sufficient to characterize theconstitutive behaviour of an untreated material
during monotonic loading without unloading or achemically treated material experiencing strains
prior to the yield point. In this case, there are noirreversible effects and the total deformation
gradient F is the same as the elastic deformation

Restricting attention to an incompressible materials(for which det F = 1 ), the deformation gradienttensor is given byF =∂xi / ∂X A

1

(1)

As suggested by Lee [17] and others, the total
deformation gradient tensor F can be decomposed
into its elastic (e) and irreversible (u) components,
i.e.

gradient Fe .

F = F e Fu

function of elastic strain tensor B e and takes theform

The stress TC associated with the component C,
which is the total Cauchy stress T of the untreatedor chemically treated material, is an isotropic(2)

Strain tensors in terms of B e and Bu are definedby

B = F (F )
e

e

e T

; B = F (F )
u

u

u T

( )

− p e I + ψ 1e B e + ψ 2e B eT=TC = ∂W e∂W e 
2  e + I1e
ψ 1e =
; ∂I∂I 2e 
 1

(3)

2

(6)
∂W e
e
ψ2 =
−2 e
∂I 2

where p e is a scalar pressure. Following theapproach proposed by Sweeny and Ward [12] toaccount for the influence of the strain rate on thestrain energy function, we adopt the following typeof strain energy function for the untreated material:

and the strain-rate is defined (Spencer, [18]) by −1 =D + W =F e (F e )−1 + F e [F u (Fu )−1 ](F e )−1
L =FF
1
=
Lu F u (Fu )−1 ; =Du [Lu + (Lu )T ]2
(4)4

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

(

)

(

e
e
e
W e (I1e ,I =2 ) C1′ I1 − 3 + C2′ I 2 − 3)rate effects are disregarded. For a chemically treatedmaterial,
aclassical
Hookeanisotropic
incompressible elastic model, without theconsideration of large strain effects, can adequately
describe its initial elastic behaviour prior to the yield
point. To conform to the description of the model forthe untreated material, we adopt a neo-Hookean
form of the strain energy function, which can bederived from a Mooney-Rivlin form of strain energyfunction (7) with C2′ independent of the strain-rate

(7)
where

κ1 ln ( γ0 / γc ) ; ( γ0 ≥ γc )′1 C1 + C=; ( γ0 < γc )0κ 2 ln ( γ0 / γc ) ; ( γ0 ≥ γc )C=
2′ C2 + 
; ( γ0 ≥ γc )
0

(8)

T = T A + TB

and always equal to zero, i.e., C2′ = 0 . Whenexamining the untreated material during unloadingor the chemically treated material experiencing
strains beyond the yield point, permanent strains
ensue. Therefore, the additional visco-plastic modelcharacterized by an elastic recovery component A inparallel to a visco-plastic component B should be
added in series to the component C. The component
A is described by a further conventional finite strain

TB

approach with a strain energy function W u of aMooney-Rivlin form:

Rate-dependent elastic constitutive component CWe= C 1′ (γ 0 )( I 1 − 3 ) + C 2′ (γ 0 )( I 2 − 3 )
e

e

TA

Elastic recovery component A
W u (I1u , I 2u ) = E1′(I1u − 3) + E 2′ (I 2u − 3)

T = T A + TB

Molecular chain network

Visco-plastic component B

TA =− p u I + ψ 1u Bu + ψ 2u (Bu ) 2ζ = g (t B )Fig. 3 Schematic representation of the constitutive
components ∂W u ∂I 1

In (8), γ0 is a generalized form of a combined
stretch-rate that depends only on the in-plane
principal stretches λi (i = 1,2) , such that→ ∞ ; ( γ0 ≥ −γcv )
E1′ = v
0 ; ( γ0 < −γc )(13)and E2′ is a constant. The choice of E1′ in (13) isintended to take into account the non-symmetricbehaviour of the elastic recovery component A
during the loading-unloading response, where, at theloading stage, γ0 ≥ 0 , and at the extremely low(1,2); (λi ≥ 1) ; i =( λi < 1) ;

∂I 2

(12)
In (12), E1′ has the conditional constraint for an
untreated material: i.e.

consideration either the stretching or the unloading
response: i.e.

;

(11)

) E1′ (I1u − 3) + E2′ (I 2u − 3)
W u (I1u ,I 2u=

dγ 0; γ 0 = [(λ1 − 1)α + (λ 2 − 1)α ]1/ α (9)dtwhere, λi have a conditional dependence on the
total principal stretches λi to take into

1

∂W u

where p u is a scalar pressure and

γ0 =

λ
λi =  i∂W u 
∂I 2 

−2 u
ψ 1u =; ψ 2u =2  u + I1u
u 

(1,2)
i=

(10)
and α is a material (combination) parameter.
When the geosynthetics specimen is subjected to auniaxial stretch, the principal stretches in the otherdirection are less than unity and therefore thedefinition of γ 0 reduces to that of the uniaxial

loading rate γ0 ≤ γcv (where γcv is viscousthreshold strain-rate). The visco-plastic deformationthat applies to components A and B is restricted dueto the choice of an infinite value for E1′ . As a result,only the elastic deformation of component C isapplicable for the untreated material. Upon
unloading, however, the visco-plastic deformation is
fully released due to the zero value of E1′ chosen in(13). All three components A, B and C take effectduring the unloading of the untreated material. For achemically treated specimen, E1′ must also takestrain ε 0 . In (8), C1′ and C2′ are the modified

Mooney-Rivlin parameters, κ1and κ 2 areparameters that define the strain-rate sensitivity andγc is defined as the rate-independent thresholdstrain-rate. At loading rates γ0 ≤ γc , the strain-

5

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

dependency of ζ on the strain-rate γ 0 is neglected;
therefore, the parameter q can be interpreted as thestatic yielding stress of the material. It should also

into consideration the yield of the material and has
the formγ0 ≥ −γcv

and γ 0 ≤ ζ yγ0 ≥ −γcv

and γ 0 > ζ y

E1′ → ∞ ;=E1′ E ′y;=E1′ 0 ;

be noted that when s ≈ 0 , the value of γcv isinapplicable and the response of the material reduces
to a pure plastic response.
The stress states in the elastic recovery responses,
denoted by TA and the visco-plastic responses,(14)γ0 < −γcv

where ζ y is the yield strain and E ′y is the postyield hardening modulus. Prior to the yield point,
the visco-plastic deformation is restricted; beyond
the yield point, however, the visco-plastic
deformation is released due to the finite value ofE ′y . This leads to the deviation of the material

denoted by TB , are added to generate the Cauchy
stress: i.e.

behaviour from an initial linear elastic behaviour toa softening behaviour followed by hardening
behaviour at larger strains. The possibility of ratedependency of the hardening modulus E ′y is also

In summary, a single generalized form of aconstitutive model intended for describing large
strain hyperelastic behaviour, strain-rate effects andmoderately large irreversible plastic strains has been
adopted for modelling both the untreated andchemically treated materials. The mechanicalresponse of the untreated material, however, has todistinguish between loading and unloading through aselective treatment of the elastic parameter of theelastic recovery component. During loading, thevisco-plastic deformation of the untreated material
is restricted and the only deformation is attributed toelastic effects; upon unloading, however, the viscoplastic component is fully released and theunloading behaviour is accompanied by irreversible
deformations. For the chemically treated material,
the material responses also have to take into accountthe yield point. Prior to yield, the visco-plastic
deformation is restricted; beyond the yield point,
however, the visco-plastic component is released,
which accounts for further softening and hardening
behaviour. The equations used to describe thegeneral form of the constitutive model for both theuntreated and chemically treated material, can besummarized as follows:

considered; i.e.

(κ ln γ / γ v
0c
 y′y E y + E=0) ; ( γ ≥ γ )
0

v
c

=
T T=
TA + TBC(15); ( γ0 < γcv )where κ y is the rate sensitivity, E y is the rateindependent hardening modulus, and, at γ0 ≤ γcv ,the viscous effect is omitted.
The stress TB in component B is defined in termsof the finite plastic strain-rate Du , which isassumed to be related to the deviatoric component of
the normalized effective stress tensor N B . In thecomponent B, the visco-plastic effects are modelled
through a relationship of the form
1/ 2

1
2 
1
=
TB′ ; t B  tr ( Te′ )  


2
2t B


=
Du ζ=
NB ; NB(16)

and TB′ is the deviatoric component of the Cauchy(18)

stress tensor TB applicable to visco-plastic
phenomena, as depicted in Figure 2. Also, in (16)Constitutive Equations used for modelling theUntreated Material
Loading:

the visco-plastic strain-rate ζ is generally assumed

Deformation Gradient: F = Fe

to be a function of the effective stress τ B and theComponent A ( TA ): Deformation restrictedstrain-rate γ0 , i.e.
1− s

τ 
ζ =  B  q 

Component B ( TB ): Deformation restricted; ( γ0 ≥ γcv )v sγ0  γ0 / γ c; ( γ0 < γcv )
 1

(

1

)

Component C ( TC ): Eq. (6), (7), (8), (9), (10)Unloading:Deformation Gradient: F = Fe Fu(17)

Component A ( TA ): Eq. (11), (12) with E1′ = 0
Component B ( TB ): Eq. (16), (17)In (17), s is the viscous sensitivity to the rate effect.

Component C ( TC ): Eq. (6), (7), (8), (9), (10)Also at extremely low loading rates γ0 ≤ γcv , the6

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017( ∆ ) to a rigid spherical indentor (with a diameter
50.8mm ) that interacts with a membrane fixedalong a circular boundary. All tests were conducted
on PVC specimens that had been exposed to ethanol
for a period of 9 months. The rate of indentation ∆is set constant during a test. The test facility has
provisions for securing a plane membrane specimen
in a fixed condition along a circular boundary of
diameter 250mm (see Figure 4b). The fixedboundary condition is achieved by clamping of the
PVC specimen between two aluminum plates ( 5mmin thickness) using eight 4mm screws. To reduce thepossibility of slippage at the clamped boundary, arubber sheet of thickness 3mm with an opening ofdiameter 250mm was bonded to the PVC specimen,
using a non-reactive instant adhesive. During
axisymmetric indentation, the contacts were initiatedat the center of the circular membrane (Figure 5a).
The indentation response was prescribed through theapplication of the indentation displacement in an
incremental manner up to a maximum displacementof ∆ max = 50.8 mm . During axisymmetric loading of
the chemically-treated PVC, the ratio of the
maximum axial displacement to the membrane
diameter reached approximately 0.20. This
corresponds to a maximum strain of 8% in the radial
direction. The load (P)-indentor displacement ( ∆ )response during axisymmetric indentation and thedisplaced profiles of the membrane are shown in
Figure 5a.

Constitutive Equations used for modelling theChemically Treated Material
Loading prior to Yield Point:
Deformation Gradient: F = Fe
Component A ( TA ): Deformation restricted
Component B ( TB ): Deformation restricted
Component C ( TC ): Eq. (6) with C2′ = 0 , (7), (8),(9), (10)Loading beyond Yield Point:
Deformation Gradient: F = Fe Fu
Component A ( TA ): Eq. (11), (12) with E1′ = E ′y ,and (15)
Component B ( TB ): Eq. (16), (17)Component C ( TC ): Eq. (6) with C2′ = 0 ,(7), (8),(9), (10)Unloading:Deformation Gradient: F = Fe Fu
Component A ( TA ): Eq. (11), (12) with E1′ = 0
Component B ( TB ): Eq. (16), (17)Component C ( TC ): Eq. (6) with C2′ = 0 , (7), (8),(9), (10)The material properties required to model theuntreated and chemically treated PVC geosynthetics
are determined from uniaxial tests. The experiments
were conducted at strain-rates of ε0 = 4% / min

MotorElectronic-mechanicallinear actuatorand ε0 = 40% / min with a peak strain of 140% ,followed by unloading. The specific material
parameters applicable for untreated PVC material
are as follows:

C1 ≈ 0.23 MPa ;Load cell
To data acquisition system

Unit containing PVC
membrane specimen

C2 ≈ 0.53 MPa ;κ1 =κ 2 =≈
κ 0.13; γc ≈ 5.67 × 10−7 sec−1 ;q ≈ 2.0 MPa; s ≈ 0; E2′ ≈ 0.5 MPa

To computer control system
Control & power supplier(a) Schematic view of the test frame−1

C1 ≈ 9.0 MPa ; κ1 ≈ 12.6;γc ≈ 5.6 × 10 sec

q ≈ 2.64 MPa;γcv ≈ 3.2 × 10−10 sec−1 ; (20)s ≈ 0.1;

Camera mounting base
Scale

(19)
Similarly, the constitutive parameters applicable tothe chemically treated material are summarized
below:−7

Indentor with different
geometries

Emergency
shut-off breaker

250mm

κy =
κ ≈ 0.13; E y ≈ 1.13 MPa ; E2 ≈ 1.2 MPa(b) Clamped plate assembly

MEMBRANE INDENTATION EXPERIMENTS
Fig. 4 Apparatus used for membrane indentation
tests
The results show a good repeatability between
the sets of experiments. The visual images of the

The membrane indentation test facility shown in
Figure 4 is designed to apply a controlled movement
7

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

deflected shapes were recorded using a highprecision (5 Mega pixels) digital camera, which was
positioned 1.5m from the test specimen. The digital
camera was mounted on the test frame in such a waythat the image plane was parallel to the plane of thesymmetry of the indentation of the membrane. The
chemically-treated
PVC
material
exhibited
pronounced irreversible deformations after aloading-unloading cycle. During asymmetricindentation, the contacts were initiated at a distanceof 42mm from the central axis of the circularmembrane (Figure 5b) The indentation responses
were examined up to a maximum displacement of∆ max = 38.1 mm , which gave rise to a maximum
strain of approximately 10%. In comparison to thecase of the axisymmetric indentation, larger forces
are needed to induce the same indentational
displacement (Figure 8b).

implemented,

theupdating

γ0ofrequiresinformation on the material configuration at t + dt .
The updated value of γ 0 will have a direct influenceon the elasticity parameters for the component C in
the chosen constitutive model, with the result thatthe computations will exhibit non-convergence.
P (N )
1000∆ = 0.318 mm / sec

900
800
700
600
500

1st loadingunloading cycle

400
300

2nd loadingunloading cycle

200
100
0
0

10

20

30

40

50

60

( mm )
Profile of irreversible shape(immediately after unloading)Profile of irreversible shape after
1st loading-unloading cycle ( 0 )COMPUTATIONAL MODELLING∆ = 0.318 mm / sec

P (N )

The constitutive models for both untreated andchemically treated polymeric materials can be
implemented in computational approaches to
examine the mechanical behaviour. In this research
program attention focused on membranes that were
fixed along a circular boundary and subjected toaxisymmetric and asymmetric indentation using a
spherical rigid indenter. The computational code used
for this purpose was the general purpose finite
element code ABAQUS/ Standard™ and the material
sub-routine U-MAT was used to implement theconstitutive relationships within the computationalalgorithm. The computational modelling takes into
account the rate-sensitive constitutive models andfrictional contact between the spherical indenter and
the PVC membrane (See also [1], [13-15], [27]). In
the nonlinear analysis of frictional contact
performed using the ABAQUS™ code, each step isdivided into iteration increments. The size of thedisplacement increment is first chosen and the
ABAQUS/Standard™ code automatically assigns
the size of subsequent increments. During eachincrement, the code employs a Newton–Raphson
algorithm to perform the iterations and theequilibrium is determined through consideration of
the principle of virtual work. The ABAQUS/Standard™ further utilizes a Backward-Euler
scheme as a default finite difference scheme to
update variables. Those variables determined fromprevious iterations that do not change during theiteration between [t, t + dt ] can be defined as statevariables. The state variables adopted in the analysis
include the components of the irreversible(a) Axisymmetric indentation

700
600
500

1st loadingunloading cycle

400
300
200

2nd loadingunloading cycle

100
0
0

10

20

30

40

( mm )
Profile of irreversible shape(immediately after unloading)Profile of irreversible shape after
1st loading-unloading cycle ( 0 )(b) Asymmetric indentation

Fig. 5 Load-displacement responses of the treated
PVC membrane (exposed to pure ethanol for 9
months): (a) subjected to axisymmetric indentationand (b) asymmetric indentation (symbols represent
experimental scatter)
The value of γ 0 is thus assumed to remainunchanged during iterations and is taken as a further
state variable. For the problems examined here, thePVC membrane only experiences incrementalloading during the initial stage where irreversible
deformations are absent; the initial values of thestate variables can, therefore, be obtained by treating
the material as fully elastic. The state variables are
updated only when the iteration converges. Both aquadratic triangular membrane element (3M6) and alinear solid triangular prism element (C3D6) wereused in the computational modelling. The results
indicated no noticeable differences between the two
types of elements. The computations presented in
the paper were developed using the solid triangularprism element. Figure 6 shows the meshdiscretization used in the computational simulation of

deformation gradient Fu at time t and the stresstensors at time t in the visco-plastic component
included in models A and B. When a fully backwardEuler finite difference scheme in time is8

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

the axisymmetric indentation problem for the circularmembrane. Figure 7 illustrates the comparison ofdeflection profiles during loading and unloading ofan as supplied membrane obtained from theexperiments and the computational simulations.
Corresponding results for the asymmetric indentationof the edge supported, as supplied circular membrane

are shown in Figures 8 and 9. Further details of thecomputational procedures and results of comparisons
between computational estimates and experimental
results can be found in [13-16].
CONCLUDING COMMENTS∆ = ∆ max00(a) Mesh configuration andboundary conditions (total
number of elements: 2086)(b) Deformed shape during
maximum indentation(c) Irreversible shape after aloading-unloading cycle

Fig. 6 Computational simulations of the untreated PVC membrane-symmetric indentation
0

50

100

150

200

250

x (mm )

0

0

0

10

10

20

20

30
∆ = 25 .4 mm (1 inch ); loading

40

50

50

∆ = 50.8 mm(2inches); loading

100

150

200

250

x (mm)

30

40

60

50

60

∆ = 25.4 mm (1inch); unloading

Irreversible deformed
profile (zero load)∆ = 50.8 mm (2 inches); unloading70

70∆ = 76.2 mm (3 inches); loading80

80

z (mm)∆ = 76.2 mm (3 inches); loadingz (mm)(a) During loading(b) During unloading

Fig. 7 Deflected shapes of untreated membrane during symmetric loading and unloading∆ = ∆ max00(a) Mesh configuration andboundary conditions (Total
number of elements: 1246)(c) Irreversible shape after aloading-unloading cycle(b) Deformed shape during
maximum indentation

Fig. 8 Computational simulations of the untreated PVC membrane-non-symmetric indentation

x (mm)
-150
0

-100

-50

0

50

100

150

x (mm)
-150
0

10

10

20

20

30

-100

-50

0

50

100

150

30

40

P

35N ; loading

40

50

50

60

60

P 160N; loading70

P 45N ; unloading

Irreversible deformed
profile (P=0)

7080w( x,0) (mm)P

360N ; loading(a) During loading80

w( x,90) (mm)P

360N ; loading(b) During unloading

Fig. 9 Deflected shapes of untreated membrane during asymmetric loading and unloadingSEE - USQ, Brisbane, Australia, Nov.13-16, 2017[3] Haedrich T, 1995, The Effect of Chemical
Exposure on the Burst Strength of aGeomembrane, Master’s Thesis, Carleton
University, Ottawa (Canada).
[4] Contamin B, Debeauvais V, 1998, The Effect ofEthanol Exposure on Burst Strength of aGeomembrane, Research Report, McGill
University, Montreal (Canada).
[5] Pezzin G, Ajroldi T, Casiraghi T, Garbuglio C,
Vittadini G, 1972, Dynamic-mechanical andtensile properties of poly (vinyl chloride).
Influence of thermal history and crystallinity,
Journal of Applied Polymer Science, 16, 18391849.
[6] Treloar LRG, 1943, Stress-strain data forvulcanized rubber under various types ofdeformation, Transactions of the Faraday
Society, 39, 59-70.
[7] Rivlin RS, 1948, Large elastic deformations ofisotropic materials. IV. Further developments ofthe general theory. Philosophical Transactionsof the Royal Society, A 241, 379-397.
[8] Green AE, Adkins JE, 1970, Large Elastic
Deformations, Oxford University Press, London.
[9] Spencer AJM, 1970, The static theory of finite
elasticity, Journal of the Institute ofMathematics and its Applications, 6,164-200.
[10] Selvadurai APS, 2002, Second-order elasticity
for axisymmetric torsion: a spheroidal
coordinates formulation. In Croitoro., E. (Ed.),
Proceedings of the 2nd Canadian Conf. on
Nonlinear Solid Mechanics, Vancouver, 1, 2749.
[11] Selvadurai APS, Suvorov AP, 2016, Coupledhydro-mechanical effects in a poro-hyperelastic
material, Journal of the Mechanics and Physics
of Solids, 91, 311-333.
[12] Sweeney J, Ward IM, 1995, Rate dependent andnetwork phenomena in the multi-axial drawingof poly (vinyl chloride), Polymer, 36, 299-308.
[13] Selvadurai APS, Yu Q, 2006, On the
indentation of a polymeric membrane,
Proceedings of the Royal Society, Mathematics
and Physics Series A, 462, 189-209.
[14] Selvadurai APS, Yu Q, 2006, Constitutive
modelling of a polymeric material subjected tochemical exposure, International Journal of
Plasticity, 22, 1089-1122.
[15] Selvadurai APS, Yu Q, 2008, Mechanics ofpolymeric membranes subjected to chemical
exposure, International Journal of Non-Linear
Mechanics, 43, 264-276.
[16] Yu Q, Selvadurai APS, 2007, Mechanics of arate-dependent polymer network, Philosophical
Magazine, 87, 3519-3530.
[17] Lee EH, 1969. Elastic-plastic deformation at
finite strains, Journal of Applied Mechanics,
Transactions of the ASME, 36, 1-6.

The loss of hyperelasticity during exposure tochemicals that can leach out the plasticizer in PVC
membranes is a further factor that needs to beaccounted for in the development of the constitutive
models. In this study we have considered a unified
model that can accommodate the large strain andstrain-rate sensitive responses of a PVC membrane in
an untreated and chemically treated state. The
validity of the modelling can be assessed either
through predictions of uniaxial test results conducted
at different strain rates or through predictions ofexperiments
involving
three-dimensional
deformations of membranes subjected to transverse
loading. The latter approach is the more general andrequires the implementation of the constitutive
models developed in a suitable computational
approach. The paper summarizes the results ofprevious research that involved the implementationof the constitutive models in a general purpose
computational code. The computational results
accurately predict the response of the transverse
deflections of the symmetrically and asymmetricallyloaded PVC membranes composed of either
untreated or ethanol treated PVC particularly in theloading mode. The irreversible deformations during
unloading of both the untreated and ethanol- treatedunloading of both the untreated and ethanol-treatedcircular membranes show that while the trends areaccurate, the computational modeling generally
underestimates the experimental data. Both theconstitutive modelling and the computational
approach can be considered as useful for examining
the mechanics of hyperelastic rate-sensitive
polymeric materials used in geoenvironmental
applications.

ACKNOWLEDGEMENTS
The work described in this paper was supported by
an NSERC Discovery Grant, the 2003 Max Planck
Research Prize in the Engineering Sciences awarded
by the Max Planck Gesellschaft, Berlin, Germany
and the James McGill Research Chairs program. The
author is grateful to Dr. Qifeng Yu for his important
contributions to the research work.
REFERENCES[1] Yu Q, Selvadurai APS, 2005, Mechanicalbehaviour of a plasticized PVC membrane
subjected to ethanol exposure, Polymer
Degradation and Stability, 89, 109-124.
[2] Pita VJRR., Sampaio EEM, Monteiro EEC,
2002, Mechanical properties evaluation of
PVC/plasticizers
and
PVC/thermoplastic
polyurethane blends from extrusion processing,
Polymer Testing, 21, 545-550.
10

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[18] Spencer AJM, 2004, Continuum Mechanics, 3rdEd., Dover Publications, Longman Group,
London.
[19] Mooney M, 1940, A theory of large elastic
deformation, Journal of Applied Physics, 11,583-593.
[20] Rivlin RS, 1960, Some topics in finite elasticity,
Structural Mechanics: Proceedings of the 1st
Symposium on Naval Structural Mechanics,(J.N. Goodier & N.J. Hoff, Eds.), 169-198,
Pergamon Press, New York.
[21] Selvadurai APS, Spencer AJM, 1972, Second
order elasticity with axial symmetry. I. General
theory, International Journal of Engineering.
Science, 10, 97-114.
[22] Selvadurai APS, 1974, Second-order effects inthe torsion of a spherical annular region,
International Journal of Engineering Science,
12, 295-310.
[23] Selvadurai APS, 1975, Distribution of stress ina rubber-like elastic material bounded internallyby a rigid spherical inclusion subjected to acentralforce,
Mechanics
Research
Communications, 2, 99-106.
[24] Selvadurai APS, 2006, Deflections of a rubber
membrane, Journal of the Mechanics andPhysics of Solids, 54, 1093-1119.
[25] Selvadurai APS, Spencer AJM, Rudgyard MA,
1988, Second order elasticity with axial
symmetry. II. Spherical cavity and sphericalrigid inclusion problems, International Journalof Engineering Science, 26, 343-360.
[26] Selvadurai APS, Shi M, 2012, Fluid pressureloading of a hyperelastic membrane,
International Journal of Non-Linear Mechanics,
47, 228-239.
[27] Selvadurai APS, Yu Q, 2005, Mechanics of adiscontinuity in a geomaterial, Computers andGeotechnics, 32, 92-106.

11

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

MEETING THE CHALLENGES OF ENGINEERING A SUSTAINABLE
FUTUREDavid Thorpe
School of Civil Engineering and Surveying, University of Southern Queensland, Australia
ABSTRACTEngineers have a significant role in the sustainable development and management of resources. This
responsibility encompasses the three generally accepted dimensions of sustainability – environment,
economic and social - and applies to engineering projects throughout their life cycle. Sustainableengineering practice is supported by professional engineering associations, such as Engineers
Australia, which includes the promotion of sustainability as one of the four principles of its Code of
Ethics, and which has recently published position statements on infrastructure and energy that support
sustainable engineering management positions. It has also been given impetus by the recent Paris
Agreement on climate change. However, while there has been considerable progress and many
advances in this field, such as recycling, use of innovative materials and the use of renewable
resources in energy production, there is much work required to achieve a truly sustainable future.
While industry has a major role in promoting and encouraging sustainable practices in engineering
projects, educators also have a significant role in this process through developing and fostering theknowledge and skills of sustainability in engineers. At the undergraduate level, this task is normally
undertaken through the offer of courses that teach the principles of sustainable engineering practice. A
major challenge for educators, however, is the ongoing development of the knowledge and skills ofsustainable engineering taught in such courses. While postgraduate study in engineering management
topics that incorporate sustainable practices can achieve this objective, the majority of practising
engineers are unlikely to study them at a formal level. Meeting this gap between sustainableengineering knowledge and its implementation in order to better achieve a sustainable future therefore
presents challenges to educators. Possible options proposed to achieve this goal include an ongoingcommitment by government and society to sustainability in engineering projects, ongoing
implementation of innovative sustainable engineering practices, and lifelong learning in sustainableengineering practices by professional engineers through educational providers, professional
associations and personal study.
Keywords: sustainability, life cycle management, resilience, education, professional development
temperatures to below 2 °C, and preferably to no
more than 1.5 °C [3].
While there is increasing commitment tosustainable engineering practices, both locally andglobally, there are significant challenges indeveloping engineering and other professionals who
have the requisite knowledge, skills andcommitment to implement such practices. Whilesome of this work can be accomplished by the
University sector, much of its success relies oncontinued acceptance of the need for sustainability,
implementation of sustainable practices by industry,
and a commitment to practicing sustainability byindividual professionals such as engineers andscientists.
One approach to addressing these challenges is
to engineer the future in a sustainable manner. Thistask will require commitment by all parties in major
engineering and other projects to exercising andimplementing
sustainable
practices,andunderstanding the issues involved. This paper

INTRODUCTION
Professional engineers are responsible forplanning, designing, delivering and maintaining
significant public and private works. Increasingly, in
undertaking this role, they are expected to undertake
sustainable engineering practices and adhere tosustainable management principles. Such practices
are supported by professional engineeringorganizations, such as Engineers Australia [1] [2].
Sustainable
management
practiceshaveincreasingly gained acceptance by both thecommunity and the corporate sector, resulting in a
number of global initiatives with respect tosustainability, including the United Nations Paris
Agreement of 2015, which recognizes the urgency
of managing climate change, a task that requires
wide cooperation and participation by all countries
in a global response aimed at accelerating the
reduction of global greenhouse gas emissions, with agoal of containing the increase in global average
12SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

discusses the issues and challenges in this process
through a review of the principles of sustainability,
discussing approaches to managing the futuresustainably, providing examples of current
sustainability initiatives, discussing the developmentof a sustainable future, outlining the role ofprofessional engineers in sustainable practices,
discussing the development of sustainability skills in
professional engineers, providing examples ofteaching sustainable engineering skills anddiscussing the opportunities for meeting thechallenges of engineering a sustainable future.

A related concept to sustainability is resilience,
which can be described in terms of systems thinking.
The resilience of the socio-ecological-economic
system, which is the focus of this discussion, islargely underpinned by the following concepts• We live within socio-ecological systems inwhich changes in one domain of the system
impact other domains.
• Socio-economic systems are complex adaptive
systems that do not change in a predictable way
and can be driven across a threshold into a
different regime• Resilience can be defined as “the capacity of asystem to absorb disturbance, to undergochange and still retain essentially the samefunction, structure, and feedbacks” or “thecapacity to undergo some change withoutcrossing a threshold to a different system
regime—a system with a different identity” [7].
A resilient system therefore can be subject tosignificant change, such as in natural disasters, andreturn to its previous function, provided that it does
not cross a threshold. From this point of view,
resilience can be considered as being defined by thecharacteristics of the amount of disturbance that asystem can absorb and still remain within the samestate, the degree to which the system can selforganize and the ability to build and increase its
capacity for learning and adaptation. This
characteristic of persistence connects resilience withsustainability, as sustainable development can also
be considered as having the goal of not only creating
but also maintaining well-performing social,economic and ecological systems. This persistence iscommon to both concepts. Resilience thinking canprovide a framework for viewing the threecomponents of sustainability as one system
operating over linked scales of time and space; and afocus on the change of a system with time anddisturbance [8].
Thus, a resilient social-ecological system has agreater capacity to avoid problems as a result of
disturbances external to the system, and so has agreater capacity to continue providing us with those
goods and services that support our quality of life [9].
A further consideration of this point of view is that if
it is accepted that there will be a certain amount ofclimate change over time as a result of the emissions
to date and in the future of greenhouse gases, aresilient engineering installation will be one that isdesigned and installed in such a way that it will
maintain or fairly quickly return to its function
should the intensity of a climatic event increase as aresult of further climate change. A related argument
for a link between sustainability and resilience isthat persisting in the achievement of a sustainable
world will result in the development of resilientsystems of engineering works.

THE PRINCIPLES OF SUSTAINABILITY
Sustainable Development and Practices
Sustainable development, on which theprinciples of sustainable practices are based, isnormally defined as “development that meets theneeds of the present, yet does not compromise future
generations from having the ability to meet theirown needs” [4]. It is commonly described asbalancing economic development, social equity andenvironmental protection. Some views of sustainable
development add the political dimension. For
example, the United Nations Educational, Scientificand Cultural Organization (UNESCO) viewssustainable development as having natural,
economic, social and political dimensions [5].
The United Nations has developed a list of 17
sustainable goals to be achieved by 2030, These
goals relate to social areas (for example, poverty,
hunger, health, education, gender equality, reducing
inequality, safe cities); resources (such as water,energy, sustainable consumption and production, themarine environment), resilience, climate change,sustainable ecosystems and building global
partnerships for sustainable development [6].
Sustainability affects all engineering projects andprocesses. For example, energy efficiency isimportant in any engineering undertaking that uses
power, such as in transportation activities and thelighting and air-conditioning in buildings. Similarly,
it is increasingly necessary to consider recycling,
and the use of recycled products, in the design andimplementation of infrastructure and building
projects. Project development using lean principles
that save waste will be less wasteful of natural
resources. Using extensive community consultation
with respect to the planning of engineering projects
and considering the views of the community in the
final implementation decision is likely to positively
impact on the social aspects of projects. Sustainable
practices are important in both smaller engineering
projects and processes, and larger systems (such asenergy delivery) that affect significant populations.
Resilience
13

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

which may be either positive and/or negative.
Objectives can have different aspects (such as
financial, health and safety, and environmental
goals), and can apply at different levels (such as
strategic, organization-wide, project, productand process).
• Risk is often characterized by reference topotential events and consequences, or their
combination. It can be positive or negative.
• Uncertainty is the state, even partial, of
deficiency of information relatedto,understanding or knowledge of an event, itsconsequence, or likelihood.
Risk is often expressed in terms of a combinationof the consequences of an event and the associatedlikelihood of occurrence. It is managed through asystem that is based on a number of principles; uses
a framework based on mandate and commitment andthat uses a continual improvement approach; anduses a process of seven steps consisting ofcommunication and consultation, establishing thecontext, risk assessment (risk identification, analysis
and evaluation), risk treatment, and monitoring andreview [13].
An alternative view of risk is to distinguish
unfavourable or favourable outcomes by using theword “risk” for possible unfavourable outcomes and“opportunity” for possible favourable outcomes [14].
This approach to risk management is both
rigorous and collaborative. Properly applied, a goodrisk management approach like that described willassess and make provision to take advantage of thebenefits and minimize the adverse effects arisingfrom the sustainability risks in a system. It will
therefore provide a basis for managing the benefits
and issues from the risks in the sustainability andresilience of a given engineering system, and aid in
the developing solutions to understanding, designingand implementing measures to manage and improve
the sustainability and resilience of the system.
In summary, the concepts of sustainability,
resilience and managing uncertainty through a risk
management process are closely linked, and requireconsideration at all levels of engineering systems if
an ongoing sustainable future is to be achieved.
The
relationshipbetweensustainability,
uncertainty/risk and resilience is shown in Figure 1,
which is based on a similar figure in a paper on foodsystem resilience [15]. In this figure, factors insustainability, like global warming, lead to
uncertainty in the global environment which resultsin the uncertainty and risk of increased instability inthe weather and climate, which in turn may lead to
disruption of and damage to the infrastructure andservices system. This simplified picture can beextended to a considerable number of events andrisks, all of which may jointly interact with theresilience of the world system. Therefore, themanagement of sustainability is highly desirable if

Resilience may also be understood through theconcepts of threshold (the magnitude or intensitythat must be exceeded for a particular result not to
occur), the adaptive cycle (how an ecosystemorganizes itself and responds to a changing world)and panarchy (a conceptual framework of systems
and their linkages) [10].
A resilient system will therefore have an upperbound to the intensity of a particular event, will be
adaptable and be composed of a number of linked
sub-systems, or alternatively form part of a larger
integrated resilient system. For example, atransportation system of roads could be considered
resilient if, during or immediately after a disasterthere is a system of key transportation routes (suchas roads) available that will enable assistance to begiven to a community to evacuate as required, besustained during the disaster, and return to normallife as quickly as possible after the disaster. These
key transportation routes would be supported bysub-systems of other routes that would return tonormal service as soon as possible after the disaster,and by other transportation facilities such as sea andair transport.
A further perspective on the concept of resiliencefrom an engineering point of view is that ofrobustness, or “designed resilience,” of anengineering system. This approach assumes bounded
uncertainty, in which the types and ranges of
uncertainty are known, and the system is designed tobe resilient to the shocks from them. This
engineering to approach to resilience is different
from that of other professions, such as psychologists,
who deal with the resilience of individuals andsocieties; ecologists, who consider both the speed atwhich a system can recover or if it can recover; andmilitary or disaster focused personnel, who also
consider speed and ability to recover [11].

•Uncertainty and Risk
The uncertainty in the sustainability andresilience of a system arises because many eventsaffecting the system have limited predictability, andin some cases cannot be anticipated with certainty.
Such uncertainty arises from the limited
predictability of the events on a global scale, such as
weather conditions, the economy, wars, seismic
activity and the extent of rise in sea level as a resultof global warming. It is incumbent on theengineering profession to limit the extent of such
uncertainty. One approach for working withuncertainty and managing it is managing risk [12].
This process is discussed in the Risk Management
Standard AS/NZS ISO 31000:2009, “Riskmanagement­ Principles and guidelines.” According
to this Standard, risk may be defined as the “effectof uncertainty on objectives”, where:• An effect is a deviation from the expected,
14

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017industry sectors, contributes up to 30 per cent of
global greenhouse gas emissions per year andconsumes up to 40 per cent of all energy, a figure
which between 1971 and 2004 had been growing at
2.5 per cent per year for commercial buildings and1.7 per cent per year for residential buildings [20].
The Paris Agreement is complemented by theUnited Nations’ 17 sustainable development goals tobe achieved by 2030 [6].
The Paris Agreement of 2015 also has a numberof technological goals, and notes the role oftechnology
research,development
anddemonstration; andthe development
andenhancement of endogenous capacities andtechnologies. It also establishes a process fortechnology development and transfer to support its
long-term vision. Some of the technology initiatives
include technology needs assessments and theirimplementation, technology action plans and projectideas; provision of financial and technical support
for the implementation of the results of thetechnology needs assessments; the assessment oftechnologies that are ready for transfer; and enabling
environments for addressing barriers to thedevelopment and transfer of technologies that meetsocial and environmental requirements [21].
The above requirements recognize the role ofengineering in the sustainable development process.
Examples of such initiatives could include, as wellas the initiatives of energy efficiency, recycling andwaste management, other initiatives like the use ofadvanced materials, nanotechnology, managementof the natural environment including lessdependence on non-renewable resources and a rangeof other initiatives. Sustainable processes might
includesmart design for sustainability andresilience, sustainable asset management, recycling,lean manufacturing and construction that reduces
waste, rehabilitation rather than replacement, designof materials to match the expected product life cycle,
and reuse of waste materials in other applications
and products. Further insight into some of theseprocesses are provided by Allwood and Cullen, whohave discussed, in addition to energy efficiency,
ways to achieve efficiency in the use of material,
including re-using metal components, longer life
products and achieving a sustainable material future
through business activity evaluation, the influence ofpolicy and the actions of individuals [22].
In summary, there is global recognition of theexisting and potential future consequences ofclimate change and other components of asustainable future, and a commitment by many
governments to address these issues, and inparticular global warming. The challenge that now
faces the world, and the engineering profession inparticular, is how to address the positively andsustainably manage climate change and othersustainability
initiatives
throughpositivethe risk of negative impacts on the global
environmental, societal and economic systems is to
successfully managed.

Fig 1 Sustainability, Resilience, Uncertainty
MANAGING A SUSTAINABLE FUTURE
The 2015 Paris Agreement recognizes thatclimate change represents an urgent and potentiallyirreversible threat to human society and the Earth,which requires cooperation by all countries in aninternational response aimed at accelerating the
reduction of global greenhouse gas emissions, andthat significant reductions are required in global
emissions to achieve the emissions reduction of theAgreement. It also recognizes that climate change is
a common concern of the human race, and thatparties should, when implementing climate change,
respect human rights, health and related matters,
including indigenous rights. The need to promote
access to sustainable energy in developing countries
through the enhanced deployment of renewableenergy is acknowledged [3]. As an example of thecommitment to climate change by many world
governments, the Australian Government has a goal
to reduce carbon emissions by 26 per cent to 28 percent over 2005 levels by 2030 [16].
The importance of managing climate change isunderscored by the significant increase ingreenhouse gas emissions and other climate
indicators. Data from the World Bank indicates thatworld greenhouse gas emissions rose by 40 per centfrom 1990 to 2012 [17], with the main industry
sectors responsible for carbon dioxide emissions in2013 being electricity and heat production (49.4 percent), manufacturing industries and construction(19.7 per cent) and transport (20.2 per cent [18].
Overall, the World Bank estimated that total world
carbon dioxide emissions in 2013 were 34,848.6
million metric tonnes [19]. This position iscomplemented by the United Nations Environment
Programme (UNEP) Sustainable Buildings &Climate Initiative (SBCI), which have stated that thebuilding sector, which would span a number of15

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

The use of lean design and construction
principles, which aim at reducing waste throughout
the production or construction process [24],similarly aim to optimize the use of both materials
and energy in these processes.
Recycling is also used in a range of engineering
processes. For example, achieving sustainability inroad design, construction and management requires
the use of not only sound environmental
management, but also practices like water sensitive
urban design, use of advanced and recycledmaterials, and environmentally responsible project
management and construction, subject to precautions
being taken to ensure that recycled materials are freefrom contaminants. An alternative approach inroadworks is to stabilize existing materials rather
than obtain new materials, using materials likecement, lime, or powdered polymers [25].

management of emissions, waste, resources andglobal infrastructure. Achieving this goal willachieve a more livable future world, conserve ourresources for the future, improve global resilience tothe effects of climate change by infrastructure andbuildings and, through positive risk management,
reduce the uncertainty of the future. This process
should also deliver global social and economic
benefits. Engineers have a significant role inplanning, designing, developing and managing thissustainable future.
EXAMPLES OF CURRENT SUSTAINABILITY
INITIATIVESEngineering a sustainable future presents many
challenges to the engineering profession. It also
provides many opportunities. Areas in which
engineers can play an active role in developing asustainable future include planning and designinginfrastructure and other installations that not only
meet the needs of society, but also use sustainable
materials and methods, waste minimization,
developing and implementing systems and processes
to minimize greenhouse gas emissions, undertaking
renewable energy projects, improving the
manufacture and use of engineering material
including developing and implementing advanced
and green materials, minimizing waste, recycling
and designing installations to maximize resilienceand minimize the adverse impacts of climate change.
These challenges and opportunities can beillustrated through considering three areas ofengineering practice – the use of advanced designand development including material reuse, thedevelopment and use of advanced engineering andconstruction materials, and the challenges in theenergy sector.

Developments in engineering and construction
materials
Modern Engineering uses a range of traditionaland new materials. Such materials are used acrossthe engineering spectrum, and in buildings,
infrastructure, machinery and electrical applications.
In the construction area, for example, there has been
considerable research in low carbon concrete
applications in buildings and other engineering
projects.
There have been enhancements to the physicaland mechanical properties of concrete, a stronger
focus on more efficient use of resources and the useof smart concretes in building energy efficiency [26].
For example, geopolymers, which result from thereaction of amorphous aluminosilicates with alkalihydroxide and silicate solutions, have been claimed
to be used in concrete of up to 70 MPa compressive
strength and have been used in applications likeretaining walls, water tanks, precast bridge decks
and precast beams [27].
Alternative materials may have both advantages
and disadvantages over traditional materials. Thus,
while cement made with fly ash cementitious
additives uses waste from coal-fired power stations
and can have useful properties fitting it for a range
of uses like mass structures its relatively slow rate ofstrength development can make it not suitable forhigh early strength applications. Similarly, concrete
made from recycled aggregate may have lower
densities than concrete made from naturally
occurring aggregate because some mortar remains
attached to it and resulting larger water absorption
than naturally occurring material [28]. There is also
the risk that fly ash may become less readily
available as the world moves away from coal fired
power stations.
Finally, research into the use of advanced andgreen materials by the small and medium sector ofAdvanced engineering design and development
Advanced engineering design and development
processes, including the application of advanced
software, can be a significant contributor tosustainable and resilient engineering practices.
One example of using advanced engineering to
improve efficiency in material usage, by Allwood
and Cullen, has previously been discussed [22]. A
further example is research into the use of
bioclimatic design principles, which tend to mimic
natural approaches and aim to both enable buildings
to function satisfactorily in existing and futureclimatic conditions and reduce building energy use
and greenhouse gas emissions. Such principles aim
at minimizing energy consumption in mining andmanufacturing,
minimizing
transportation;
optimizing resource use through material reuse andrecycling, and maximizing the use of renewableenergy [23].
16SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

electricity generation in Australia [2].

industry has indicated that there may be challenges
in using some building materials, such as advanced
concrete materials, materials using native earth suchas adobe and rammed earth, advanced timber
products, green roof and pervious concrete. These
challenges included whether the firm had previously
had experience with using the material, cost of thematerial and the availability of standards and codesof practice [29].
In summary, while there will continue to beconsiderable research into the development andapplication of both advanced and sustainableengineering materials, there are likely to be somechallenges with their acceptance by the broader
engineering and construction community. It is
probable that a number of these challenges arise
from the novelty of some of the material, and thereluctance of industry to use new materials until they
are proven to be reliable, durable, safe and costeffective. This may take time, given the innovation
decision process of knowledge of the innovation,
persuasion of its use through its perceived
characteristics, a decision to use it, implementationof the innovation and confirmation of its value orotherwise [30].

DEVELOPING A SUSTAINABLE FUTURE
Developing a sustainable, resilient future is achallenging task. It is a process subject toconsiderable uncertainty, which requires the
management of the negative risks involved andpresents many opportunities. The goal of this task is
to develop a rewarding and livable future for both
ourselves and our descendants, in which global
warming is contained and cities and otherinfrastructure quickly recovers from disasters.
Achieving this target requires assessment of thecurrent position and balance of the environmental,
economic and social state of the world; evaluation of
the options in managing climate change and theongoing use of resources; and development ofsolutions that not only achieve a sustainable future
but also ensures resilience of key infrastructure andproductive facilities in times of challenges anddisasters.
Fundamental to this process is an understandingof the options and initiatives that can result in much
more sustainable world. Examples have been givenof such initiatives in engineering design anddevelopment, improved and new engineering andconstruction materials and significant advances inenergy production and management. Thesedevelopments can be considered as part of a muchwider focus on building a sustainable future, andlinking us, through the lens of resilience, with awider systems approach in understanding not only
the immediate impact of sustainability, but also its
longer-term evaluation.
Because of the increasing role of sustainable
practices in the engineering profession, theeffectiveness of teaching these practices toengineering students, and of the use of thesepractices in professional engineering, is developingwith the passage of time. Such teaching should not
only encourage students to understand the principles
of sustainable development, but also should provide
them with the understanding, knowledge and skillsin this area to motivate them to make sustainableengineering practices a significant component of
their professional career. The first step in discussing
this process is to review the role of the professional
engineer in these practices.

Energy production and management
The figures estimated by the World Bank in its
2017 World Development Indicators publication
included a global electricity production figure in2014 of 23,869.3 billion kilowatt hours, and an
energy use per capita of 1,929 watts [19]. Given thisongoing demand for energy, and an increasing
demand for energy, one area in which to improve thetotal carbon emissions is through improved
management of energy, such as electricity, boththrough managing demand and moving away fromfossil fuel production.
In Australia, a review of the future security of thenational electricity market was undertaken by Chief
Scientist Alan Finkel. In summary, the report on thereview recommended increased security, future
reliability, rewarding consumers and lower
emissions. [31].
The Engineers Australia organization, which
represents professional engineers in Australia, hasrecently released an energy position paper, which
discusses energy productivity, transport energy andelectricity generation. Among its recommendations
are that the Australian government adopts an energy
efficiency target of 30 per cent by 2030 as the means
to drive progress under the Australian Government
National Energy Productivity Plan, that theAustralian government introduces policies andprograms that lead to energy efficiency in thetransport sector, including active integration of more
efficient transport modal mixes, and that all levels ofgovernment proactively develop plans to restructure

THE ROLE OF PROFESSIONAL ENGINEERS
IN SUSTAINABLE PRACTICES
Professional engineers have a significant role inproviding a sustainable, resilient future. As an
example of the recognition of this role byprofessional engineering member organizations,
Engineers Australia, of which many Australian
professional engineers are members, states that
17

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

increasingly recognized by professional engineeringand other organizations, and are increasingly
required by industry. There is however a challenge
to develop the skills in engineering students by botheducational institutions and industry so that they
become not only part of their undergraduate
education, but are also embedded in theirprofessional practice.

professional Engineers are “responsible for bringing
knowledge to bear from multiple sources to develop
solutions to complex problems and issues, for
ensuring that technical and non-technicalconsiderations are properly integrated, and for
managing risk as well as sustainability issues.”
Engineers Australia prescribes two levels ofengineering practice competency. Stage 1
competencies qualify students as graduate engineers,
at which they are expected to understand sustainableengineering practice in their discipline, anddemonstrate commitment to sustainable engineering
practices and the achievement of sustainableoutcomes [32]. The second stage of competencies,
Stage 2 competencies, is the Chartered Professional
Engineer level, for which graduates must haveminimum of at least three years of professional
experience and are required to show competencies inpersonal commitment, obligation to community,
value in the workplace and technical proficiency.
These competencies include the sustainability
related skills of developing safe and sustainable
solutions; engaging
with community andstakeholders; communication and risk assessment[33].
These competencies are supported by the Codeof Ethics of Engineers Australia, which contains
guidelines to professional conduct that is based on
ethical engineering practice that requires judgment,interpretation and balanced decision-making incontext. Engineers in their course of professional
practice are required to demonstrate integrity,
practice competently, exercise leadership andpromote sustainability. As part of promoting
sustainability, professional engineers are required toengage responsibly with the community and otherstakeholders; practise engineering to foster thehealth, safety and wellbeing of the community andthe environment; and balance the needs of thepresent with the needs of future generations [1].
These ethics, combined with required
engineering competencies, provide a strong focus onsustainable practice within the engineering
profession. At the same time, there are someengineering related disciplines, such as construction,
which do not rate sustainable management skills as
highly as some other skills. For example, a survey ofrecruiters for over 100 construction companies
located in the eastern United States of America
found that they rated environmental awareness,along with communication skills, lowest among 14
key competencies, while other skills like ethicalissues, problem-solving skills, and interpersonal
skills were rated highly [34]. On the other hand, anAustralian survey noted both the connections anddifferences between educational and professional
employment requirements with respect to education
for sustainability [35].
In summary, sustainable management skills are

DEVELOPMENT OF SUSTAINABILITYSKILLS IN PROFESSIONAL ENGINEERS
The support of sustainable engineering practices
byprofessional
engineeringorganizations,
government and industry has resulted in sustainableengineering practice is increasingly being taught toengineering students. Such teaching would be likely
to consider the principles of the United Nations
Scientific and Cultural Organization (UNESCO) in
the education of sustainable development (ESD)
These competencies include that such education:• is based on the principles and values that
underlie sustainable development• promotes life-long learning• is locally relevant and culturally appropriate• is based on local needs but acknowledges theirinternational consequences• engages formal, non-formal and informal
education• accommodates the evolving nature ofsustainability addresses content• builds civil capacity• is interdisciplinary and promotes participatory
learning and higher-order thinking skills [36].
In engineering, sustainability teaching tends tofollow one of three models – integration ofsustainability into traditional courses, stand-alone
sustainable engineering, and embedding sustainableengineering modules within the framework ofexisting courses. Challenges in sustainableengineering education include a full curriculum, theengineering educational structure and a focus on theenvironmental aspects of sustainability, with lessemphasis on its social and cultural aspects [37].
Thus, there is an opportunity to improve the learningof engineering students in the social dimension ofsustainability [38]. This need for a seamless
interface between engineering and society has been
reinforced by other studies, once of which
considered the link between science, technology andsociety courses and engineering, and whichhighlighted the three categories of participation,
politics and policy, and citizenship, which werereflected themes that were not discussed often inengineering curricula, but were significant in science,technology and society [39].
In conclusion, while teaching in sustainableengineering practices is undertaken in universities,
there is a still a gap in teaching the social and
18

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

The University also incorporates sustainableengineering management principles included as partof other courses, including postgraduate study up toDoctor of Professional Engineering level. For
example, Technological Impact and its Management
is a stand- alone sustainable management focusedcourse that reviews current technologicaldevelopment and evaluates its impact on the world
on we live. There are also courses offered at the
University postgraduate level that integratesustainability with the course material. Such courses
include:• Asset Management in an Engineering
Environment, which discusses the strategic life
cycle management of engineering asset systems• Advanced Engineering Project Management,
which is designed to teach higher level projectand program management knowledge and skills• Whole of Life Facilities Management, whichteaches the life cycle operations, maintenanceand renewal of engineering facilities [43].
In addition, the University offers a postgraduate
courses Management of Technological Risk course[43]. This course teaches risk management
principles based on the Australian Standard for Risk
Management [13], and the applications of risk
management principles in engineering projects andprocesses. A text on managing project opportunity
and risk [14] supports the course.
These courses place a strong emphasis on
assignments that are designed to challenge students
to demonstrate their competencies in problems
similar to those of professional practice, and which
are assessed using the principles of authentic
assessment [44]. Similarly, students are also
encouraged to apply experiential learning principles[45] through applying practical examples in
examinations in those courses with examinations
and applying marking feedback from a firstassignment to a second, more complex assignment
in those courses, like Advanced Engineering ProjectManagement, that are assessed solely byassignments. There is also an increasing use of guest
lecturers from industry.

cultural aspects of sustainability as outlined in the
UNESCO competencies for sustainable education.
.
EXAMPLES OF TEACHING SUSTAIBALEENGINEERING SKILLSOne of the main expected outcomes of teachingsustainable engineering skills is the development ofengineers who can practice, on an ongoing basis, thesustainable design and management of engineering
projects and processes as expected by society andprofessional engineering organizations. As an
example of such teaching, the University ofCambridge, in recognition of the increasing
recognition by the United Kingdom construction andcivil engineering industries, and their professional
bodies, of sustainable engineering practice, engaged
with sustainable development issues.
This
approachrecognized
that
many
sustainability problems requires a systems view ofthe world that accounted for complexity, interdisciplinary understanding and a broader view ofsystem performance. This process requires not only
the use of mathematics, but also making judgments
and understanding of differences.
As a result, a number of initiatives were
undertaken in the Cambridge University Engineering
Department. Such initiatives focused on embedding
sustainable development within the Department.
Initiatives have included:• introduction of sustainable development
thinking into undergraduate teaching• the development of a Master of Philosophy in
Engineering for Sustainable Development• formalizing sharing of sustainable development• developing sustainable development as a key
theme of departmental strategy.
This approach required achieving a quantitativeand qualitative balance, dealing with pedagogicalissues, and initiating change. It has been successful.
Lessons were also learnt in managing change [40].
It is also noted that the Engineering Departmentof Cambridge University is undertaking research inmodelling, simulation and analysis of complex
systems. This research is aimed at better managing
their uncertainties through absorbing variations
naturally. Part of this research is in developing a
new understanding of uncertainty and risk [41].
The University of Southern Queensland offers
the Technology, Sustainability and Society course,
an example of a stand-alone sustainable engineeringcourse, to all Engineering and Built Environment
students studying a three or four year undergraduate
degree program. This course, which discusses topics
like the history of technology, sustainability
including environmental impact management,
politics and power, the economy, models of society,cultural impacts, law and regulation andmanagement concepts, has been successful [42].

OPPORTUNITIESCHALLENGESFORMEETINGTHE

As shown above, there is a developing emphasison teaching sustainable engineering practices in bothundergraduate and postgraduate engineering
programs. Such teaching tends, however, not to be alarge component of the engineering curriculum. It istherefore desirable that graduate engineers further
develop the knowledge and skill of sustainability
during their professional practice. One way in whichsuch ongoing development could be addressed
would be for industry to lead this development
through initiatives like providing environments in
19

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

infrastructure and services, and which can quickly
be restored to functionality following such events.
While current engineering education would be
expected to should provide them with a basic
understanding of these principles, it is consideredthat such education be further reinforced throughgovernment and industry support of sustainable
practices, postgraduate education and training.

which these skills can be enhanced. Further formal
education in sustainable engineering practice is also
desirable. Because most professionals are very busy,
this approach may only be suitable for thoseengineers who have the time to undertake additional
study.
Another possible opportunity for both the tertiary
education sector and industry to have a role indeveloping sustainable engineering knowledge andskills this area is for industry to be develop links
with universities with respect to teaching sustainableengineering practice. This approach would benefit
those industries that are becoming more sustainable
in their outlook and practices, and would therefore
benefit by having a positive role to play insustainable engineering education. This process has
the potential to elevate the profile of sustainability toengineering students. A further option could be foruniversities to develop links with industry partners
and professional associations in encouraging
sustainable practices and offering short courses inthem, along with the related areas of risk andresilience, to both students and practicing
professionals.
The amount of teaching in sustainableengineering at an undergraduate level could be
reviewed to see if it can be better incorporated into
theengineering
curriculum,
perhapsbyincorporating an increased number of components of
it in selected courses in each year of the engineering
curriculum. Engineering teaching could also benefit
from more emphasis on the social aspects ofsustainability.
There is also an opportunity for further
understanding between sustainability, the risks of
not using sustainable practices, and the impact at asystems wide level on resilience, or the ability tobetter withstand and more quickly recover from theimpacts of more extreme and frequent events inareas like the weather, or economic or social
conditions resulting from increased risk.

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CONCLUSION
While there has been considerable progress inthe teaching and practice of sustainability inengineering, there is still much work to beundertaken to make it a part of day to day
professional practice and thereby minimize theimpacts of climate change, as well as to optimize thesocial and economic aspects of a sustainable future.
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environment, of not managing this future well.
Engineers have a significant role in sustainable
management and in designing, developing, operating
and maintaining infrastructure sustainably and withthe resilience to minimize the effect of negative
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Education, 2010, vol. 11, no. 4, pp. 391-403.
[37] Allenby B, Murphy CF, Allen, D & Davidson, C,“Sustainable engineering education in the UnitedStates”, Sustainability Science, 2009, vol.4, no.7.
[38] Valdes-Vasquez R & Klotz L, “Incorporating theSocial Dimension of Sustainability into Civil
Engineering Education”, 2011, Journal ofProfessional Issues in Engineering Education andPractice, vol. 137, pp. 189-197.
[39] Pritchard J. & Baillie C, “How can engineering
education contribute to a sustainable future?”,European Journal of Engineering Education, 2006,
Vol. 31, No. 5, pp. 555-565.
[40] Fenner RA, Ainger CA, Cruickshank HJ &Guthrie PM, “Embedding sustainable development
atCambridge
Engineering
Department”,
International Journal of Sustainability in Higher
Education, 2005, vol. 6, no. 5, pp. 229-241.
[41] Cambridge University, Complex, Resilient andIntelligent Systems, viewed 1 September 2017,
http://www.eng.cam.ac.uk/research/strategicthemes/complex-resilient-and-intelligent-systems,
2017.
[42] University of Southern Queensland, Course
Specification:
ENG2002
Technology,
Sustainability and Society, 2017, Toowoomba,
Australia.
[43] University of Southern Queensland, Doctor ofProfessional Engineering, 2017, Toowoomba,
Australia.
[44] Gulikers JTM, Bastiaens ThJ, & Kirschner PA, ”
Perceptions of authentic assessment: Fivedimensions of authenticity”, Second biannual
Northumbria/EARLI SIG assessment conference,
2004, Bergen.
[45] Kolb DA Experiential Learning: Experience as the
Source of Learning and Development, 1984
Englewood Cliffs, N.J.: Prentice-Hall.

21

SEE -International
USQ, Brisbane,
Australia,onNov.13-16,
2017
Third
Conference
Science, Engineering& Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

STATISTICS FOR EVIDENCE-BASED DECISIONS –USE, MISUSE AND ABUSE
1

Shahjahan Khan1 and M Ashraf Memon1,2,3,4
Faculty of Health, Engineering and Sciences, University of Southern Queensland, Australia
2
Faculty of Medicine, University of Queensland, Australia
3
Faculty of Health Sciences and Medicine, Bond University, Australia
4
Faculty of Health and Social Science, Bolton University, UK
ABSTRACT

Increasingly decision-makers are relying on an evidenced-based approach, using results extracted byanalysing exponentially growing data. Statistical methods have become an integral part of analysing andinterpreting simple or complex data to make valid and accurate decisions for society and science in the face of
uncertainty. Because of its power to uncover, otherwise unavailable, valuable information from data, statistics isincreasingly being applied for both private and public benefit including business and trade, not to mention its
crucial role in research and innovative technologies. The key role of statistics is engraved in the planning anddevelopment of every successful nation and international agency. In fact, the scope of statistics is not confinedby borders as it disseminates through regional and international organisations and agencies driving social,economic, environmental, health, poverty elimination, education and other agendas for planned development.
Obviously statistical methods are capable of analysing data to determine various indices, indicators, predictions,estimates, and perform tests to help identify any problems and take appropriate measures to remedy them.
Because of the obvious power of statistics it has been used, misused and abused by those who are in authorityand power.
Keywords: Evidence-based decision, Analysis of data, Estimation and test, P-value, Society and Science
recognition of statistics at the highest level ofadministration.
Not surprisingly statistical literacy is gradually
becoming an essential component of this basic skill
set in today’s modern world. Every society is
increasingly embracing statistical information as aneffective means of communication, reasoning, andevidence representation. With the exponential
growth of data due to its never ending mass
production on the internet and elsewhere, more indepth understanding of statistics, and its power isbecoming inevitable. Statistical literacy, if notexpertise, is an essential skill for policy makers,
government officials, business executives, scientificresearchers and ordinary citizens.
In the past, there was lack of data, but now, there
is an influx and oversupply of data in many ways.
However, there is no value or real use of this raw
data until and unless it is properly scrutinized andanalysed, only then highly precious information canbe retrieved and presented in lay terms to informmass population of its value. Statistics has themeans to unlock the secret of data and reveal
important information to make it beneficial for reallife applications. Thus, the tremendous power ofstatistics has started to get due recognition frommany fair-minded professionals and decisionmakers in research, business, management, andgovernment and non-government agencies.

INTRODUCITON
In recent years, statistics is receiving growing
attention, acknowledgement, recognition andappreciation from the key decision makers in every
corner of the globe due its incredible power toreveal, otherwise unavailable, precious informationfrom various databases for the benefit of mankind.
Even the Secretary General of the United Nations(UN) and it’s General Assembly have highlighted
the crucial role of statistics in the modern world byadopting a resolution in the UN General Assemblyto celebrate World Statistics Day in 2015. As in [1],the theme of the celebration ‘Better data. Better
lives’ impresses upon the importance of quality
data to better lives in a very wide sense
encompassing every aspect of life and society. A
UN Economic and Social Affairs video on betterdata is found at [2].
The increasing popularity of statistics isunderpinned by its widespread use and the growing
awareness of its public benefit whether that be ineveryday work, business strategy and decision
making process. Recent global interest in evidence
based decision-making practice has also broughtstatistics to the spotlight. The emergence of ‘Big
Data’ and Data Science have further expanded theapplications and benefits of statistics. The
appointment of the Chief Data Scientist by the
President of the USA is clear evidence of the22

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

Although, the power of statistics is often nothighlighted, statistical information is an excellent
way to create awareness, and change the perception,in the community and society on crucial nationaland global issues. It can send the strongest possible
message to shake up views and opinions of thepeople, and inspire/convince them to do things
differently. Two recent examples of how statistics
have impacted on the ordinary people and decision
makers are presented below. The first example
pertains to statistics on the unemployment rate andits power to impact on the choice of voters in theUSA. The second example is relates to vitalstatistics in the area of public health sector inAustralia.
In the recent past, the power of statistics has
been reflected in the presidential election campaignof the USA. In the 2012 re-election campaign ofPresident Barack Hussein Obama the number one
issue was the unemployment rate. Just one month
before the November election, on 5 October the
Bureau of Labor Statistics released that the official
unemployment rate [3] had dropped from 8.1
percent to 7.8 percent in September (see Table 1).
Although the drop was only 0.3 percent,undoubtedly, this was not a simple ‘rate’ or‘number’ for President Obama and his opponent(Mitt Romney). It was make or break information,and most likely the most powerful statistic in
dictating the 2012 presidential election result.

unemployment rate in the USA before and after the
re-election of President Obama.
For the second example, we consider a statistic
on cancer from the ‘authoritative information andstatistics to promote better health and wellbeing’(AIHW), Australia report [5], “In Australia 1 in 3
men and 1 in 4 Australian women will bediagnosed by cancer before the age of 75.” This is achilling statement, not just some figures, but a stern
warning about the very high risk of cancer for real
people. This simple statistic sends a very powerful
message to society on how extensive the risk is ofgetting cancer. This statistic also demands policy
from the decision makers, to be proactive in saving
lives.
The chart in Figure 1 shows that the incidence ofcancer in Australia is still increasing over the years
with some fluctuations for both male and female
population.

Table 1 Unemployment rate by Labor Force
Statistics from the Current Population Survey
Year

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

2008

5.0

4.9

5.1

5.0

5.4

5.6

5.8

6.1

6.1

6.5

6.8

7.3

2009

7.8

8.3

8.7

9.0

9.4

9.5

9.5

9.6

9.8

10.0

9.9

9.9

2010

9.8

9.8

9.9

9.9

9.6

9.4

9.4

9.5

9.5

9.4

9.8

9.3

2011

9.1

9.0

9.0

9.1

9.0

9.1

9.0

9.0

9.0

8.8

8.6

8.5

2012

8.3

8.3

8.2

8.2

8.2

8.2

8.2

8.1

7.8

7.8

7.7

7.9

2013

8.0

7.7

7.5

7.6

7.5

7.5

7.3

7.3

7.3

7.2

6.9

6.7

2014

6.6

6.7

6.7

6.2

6.2

6.1

6.2

6.2

6.0

5.7

5.8

5.6

2015

5.7

5.5

5.5

5.4

5.5

5.3

5.3

5.1

5.1

5.0

5.0

5.0

2016

4.9

4.9

5.0

5.0

4.7

Fig. 1 Incidence and mortality of all cancers
combined, 1982-2016

Obviously, the Republican camp claimed thatthe drop of the unemployment rate was ‘cooked’ by
the influence of the administration. Steve Haugen,an economist at the Bureau of Labor Statistics,"flatly dismissed the idea that there was any way
the White House or Obama campaign could have
had a hand in how the numbers turned out." "Thedata is not manipulated for political reasons. I’ve
been involved in the process myself for almost
three decades. There’s never been any politicalmanipulation of the data, period,” Haugen told
CBSNews [4]. Table 1 shows the statistics on theFig. 2 Incidence of breast cancer by age forAustralian women in 2010
Another statistical fact presented in a simple bar
chart in Figure 2 reveals the incidences of breast
cancer in Australian women [6]. Clearly, a large
number of women above the age of 40 years arereported to have breast cancer. This statistic sends
alarm bells to the health authorities and otherrelevant policy makers to tackle this serious health

23

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

problem with appropriate policy and measures,
particularly for middle and older age women.

model error, judgement error and so on.
Unfortunately, we can’t avoid or ignore error,
because this is a reality of life. Therefore, we needto learn how to deal with error, and how to preventor reduce it. Statistical methods such as regression
model and analysis of variance model include error
in the model as a way of representing the reality oflife. The most commonly used normal distribution
introduced by Gauss [7] is related to measurementof errors. In fact normal distribution is also known
as the law of error, the law of facility of errors,
Laplace's second law, Gaussian law etc. By the endof the 19th century some authors had started using
the name normal distribution, where the word
"normal" was used as an adjective – the term now
being seen as a reflection of the fact that this
distribution was seen as typical, common – and thus
"normal".
Certainly, we live in a world that is full of
uncertainty, variability, and errors of various kinds.
Needless to say that these three realities of life –variation, error and uncertainty - are everywhere
and in everything, and hence the use of statistics is
unavoidable, rather inevitable. Life becomes more
complicated and challenging if the three factors act
simultaneously or in combination leading to further
complexities, demanding further sophistication of
statistical methods. This obvious and ongoingchallenge has helped develop statistics faster thanany other scientific discipline in the last several
decades. Often statistical methods evolved on theway of solving problems in other disciplines, andlater it has found applications in many new areas ofmodern life.
According to the LinkedIn [8] statistics
graduates were the most in-demand skill in 2014
and it is the second most-in-demand in 2017.
Among the hottest skill for jobs in 2016 were
statistical analysis with data mining listing second.
LinkedIn blog reports, “Our top skill category lastyear, statistical analysis and data mining, is still
sitting comfortably at #2. It is the only skill
category that is consistently ranked in the top 4
across all of the countries we analyzed. We still live
in an increasingly data-driven world, andbusinesses are still aggressively hiring experts indata storage, retrieval and analysis.”
Statistics is among the fastest-growing
disciplines of for jobs in the USA. The McKinsey
Global Institute predicts a shortage of up to 190,000
people with the data analysis skills to work withBig Data. Statistics is ranked by Fortune as the top
graduate degree based on salary, growth and job
satisfaction. The starting salaries for statistics
graduates are among the highest in the USA. No
wonder demand for statisticians is very high.

WHY STATISTICS IS ESSENTIAL?
What makes statistics so important in life? Why
is it so relevant in so many aspects of society? The
answer to these questions requires understanding
and appreciation of three crucial realities of life i.e.
uncertainty, variability and error.
Uncertainty
Life is full of uncertainties. The weather is
uncertain, the gender of the conceived baby isuncertain, the amount of sale/income is uncertain,
the profit/loss is uncertain, the list goes on and on.
There is no certainty in almost every natural
phenomena and human behaviour. In this world
uncertainty is the only certainty. Like it or not,uncertainty is here to stay for ever. Is there any way
to measure the degree of uncertainty? Fortunately,
statistical methods are capable of dealing withuncertainty and it relies on the laws of probability
and statistical distributions. Actually, statisticalmethods make use of the magnitude of uncertainty
to create models and enables us to find and study
different attributes of uncertain phenomenon.
Measuring uncertainty has important economic
consequences for calibration and measurement
activities. In calibration reports, the magnitude of
uncertainty is often taken as an indication of thequality of the laboratory, and smaller uncertainty
values generally are of higher value and of higher
cost.
Variability
We live in a world of variables. People vary ingender, age, height, weight, income, education,
ethnicity, hair colour, nationality, size of shirt/shoe,type of car, and so on. Society varies in household,dwelling, population, culture, language, religion,
standard of life, quality of life, health care, welfare
system etc. Business vary in size, sale, profit, type,customer base, product, staff, marketing, wage,
commission/bonus, location, and so on. Almost
everything around us varies and that is the reality oflife and society. Statistical methods utilise themeasure of variability in describing and analysing
the nature and characteristics of the variable. In fact,
variables are the key raw materials of statisticalmethods.
Error
The world is full of errors. Error is everything
and everywhere. We always refer to measurement
error, assessment error, human error, machine error,

DEVELOPMENT OF STATISTICS
24

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

makers and researchers both in the private andpublic sectors. Often, the contribution of statistics is
not fully understood, realised or recognised due tolack of understanding the depth and extent of its
impact on the society and appreciation of its value
and importance in real life. Some of the major
contributions of statistics are highlighted below.
Big Data: The recent emergence of big data haschanged the way people look at statistics, and how
it could extract the hidden information in the messof huge data for their business and other needs.
The analysis of big data involves a number ofcomputing tools in addition to statistical techniquessuch as factor analysis, principal component
analysis, support vector machine, artificial neuralnetworks, multiple regression, analysis of variance,
k-means, prediction analysis etc.

The development of statistics to its current state
as a scientific discipline is relatively recent. But theancient rulers - kings and emperors - used statistics
to take an account of the state of affairs of theirterritory; population, soldiers, horses, food stock,etc. As far back as the Bible, God ordered Prophet
Moses to conduct a census of all males over the ageof 20, and he did it. So the history of census, anintegral part of modern statistics, is at least as old as
the Bible.
In the pre-twentieth century statistics wasviewed as a branch of mathematics dealing withdata. As a discipline lacking rigorous scientificvalidity, at that time, its main emphasis was oncollection,
analysis,
andexplorationofobservational data. After Kolmogorov [9] proposed
his famous Axioms of Probability, and its English
translation published by Morrison [10], statistics
received a boost as a scientific discipline. This laid
the much needed scientific foundation of statisticaltheory and methods enabling the use of various
probability distributions and sampling distributionsof sample statistics for making valid inferences.
The introduction of high power computers hasdone a tremendous service making statisticalcomputing easy and quick, and thus helped
popularise statistics and widen its applications. In
fact, this is what the statistics community was
waiting for; the full manifestation of what statistics
could offer to humanity (see Nolan and Lang, [11]).
In addition to performing different analyses of awide range of observational and experimental data
in a very short time, computer technology has
provided a way to easily prove and illustrate many
complicated statistical results (cf. Klemens [12]).
Furthermore, it enables statisticians to conduct
Monte
Carlo
simulations
andnumerical
computations in a variety of statistical setups whenanalytical methods are unavailable.
Statistics is a science that enables making
reliable decisions in the face of uncertainty. It
provides methods to minimise the risk, and predicts
the value of a response variable for given values ofrelated explanatory variables. Statistics is like amirror of society that reflects the true state ofdifferent aspects of the society and theircharacteristics. To know the attributes of a society,one needs to know the relevant statistics.
Florence Nightingale said, “To understand God's
thoughts we must study statistics, for these are themeasure of His purpose.”

CensusPopulation census is an ancient statisticalmethod to collect data on every household andindividual residing in a country. Normally census isconducted every 5 or 10 years to gather information
on vital demographic, social and economic
variables. The census data is used by governments
and other development/welfare agencies todetermine the vital needs of the communities
including infrastructure, education, welfare,
healthcare, recreation etc. In many countries,
regular census is also conducted on agriculture andindustry sectors.
Sample Survey
Introduction of random sample is a remarkable
contribution of statistics for the mankind. The
random sampling techniques not only reduces thecost, time and resources of data collection, but also
ensures scientific validity of results derived fromthe sample data by avoiding selection bias. This
allows studies to collect data from a very small
representative part of a population to make valid
conclusion or inference on the characteristics of thewhole population. The frequently used sample
survey is the most convenient, timely, cost effective
and popular way of collecting data.
Design of Experiment
Properly conducted experiments following theprinciple of random allocation of treatments toexperimental units, introduction of control, blockand replications enable the experimenters to isolate
out the effect of the treatment of interest from manypotential latent and confounding factors.
Controlled experiment is the only way to establish‘cause and effect’ relationship between variables.

MAJOR CONTRIBUTIONS OF STATISTICS
Statistics has been widely used for different
reasons by people from all walks of life. Among thefrequent users of statistics are the policy/decision25

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

This is extensively used in the agricultural,industrial and engineering problems.

modelling exercises, regression analysis plays acrucial role for prediction or estimation or test. The
regression model is used in varieties of forecasting
and analytical problems.

Randomised Controlled Trial
In a study in which subjects are allocatedat random (by chance alone) to receive one ofseveral clinical interventions including one control
in the form of a standard practice, a placebo, or nointervention at all. The aim is to compare the effectof the intervention (treatment) with that of thecontrol to find out if the intervention effect issignificant. No new drug is allowed to be in themarket for the use of the patients without
undergoing clinical trials and proving its
effectiveness through statistical test. This isregularly used in the health and medical studies.

Total Quality Management

Estimation and Hypothesis Test

Opinion Poll

Point and interval estimations allow people tocompute the value of the sample counterpart of any
relevant unknown parameter/characteristic of the
population at large without knowing the population
data. The confidence interval is a very popular way
to estimate unknown parameter with a preselectedlevel of confidence. Test of hypothesis is the only
way to check manufacturer’s claim on the quality ofa product or any statement about specific value ofparameters of a population. This is frequently usedby the researchers in many different fields to findout if the observational or experimental results are
statistically significant. Introduction of any new
drug in the market requires compulsory clinical
trials and results must be supported by statisticaltest. The sampling distribution of the underlying
statistic is in the centre of both interval estimationand test of hypothesis. These methods are widelyused in business, education, and all branches ofsciences.

This statistical tool allows collection of data on
different issues and problems faced by the society
or nation. It is more popular in checking the level of
popular support for political parties and government
plans and programs. It is equally useful to find theviews of the people on different crucial andcontroversial issues of the day. Often politicians
assesse, review and revise their party policies andprograms based on the outcome of opinion polls.

The quality control is a routine statisticalpractice in manufacturing industries to ensure theeffectiveness of the production system. Various
types of control charts are used to detect any
problems in the quality of the final products, so thatthe underlying defects are rectified to resume
normal production before it is too late. The groundbreaking work of Taguchi and Deming has changed
the way manufacturing industry used to work in thepast.

Research Methodology
After determining the research questions themain concern of every researcher is to gather
relevant data following an appropriate survey
design along with a properly constructedquestionnaire or controlled experiment, analyse thedata at hand, and then interpret the results to answer
the questions. Statistics is an integral part of manysuccessful research projects starting from the initialplanning stage to finally publishing the outcomes in
professional journals.
There are many disciplines taught at various
tertiary levels all over the world that are either
statistics in disguise or highly dominated bystatistical contents including, but not limited to, (1)Actuarial Science, (2) Bioinformatics, (3) Biometry,(4) Biostatistics, (5) Climatology, (6) Data Mining,(7) Data Science, (8) Demography, (9)Econometrics,(10)
Epidemiology,(11)
Environmetrics, (12) Forecasting, (13) Image
Processing,(14)(Bio)Informatics,(15)
Management Science, (16) Meta-analysis, (17)Quality/Process Control, (18) Quantitative Methods,(19) Queuing Methods, (20) Reliability Analysis,(21) Risk Analysis, (22) Research Methods, (23)Survival Analysis, (24) Stochastic Process, (25)Time Series Analysis etc. Further details on

Analysis of VarianceThis is a very frequently used statisticaltechnique by many people who wish to compare themeans of several treatments or populations. The
underlying mechanism is to use the between
treatment variance in determining if there issignificant difference among the treatment means.
It is popularly known as ANOVA. Its multivariate
version, MANOVA is used for multivariate data
analysis.
Regression Model
The linear (and nonlinear) regression analysis isa method to establish relationship between a
response/dependent variable and one or more
explanatory/predictor variables. In most of the26

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

are serious issues in the reported statistical results
due to oversight or lack of statistical knowledge on
the part of the authors. No wonder, many reputed
journals mandate checking of statistical contents ofmanuscripts by statistics reviewer/editor. Even then,there are many published articles with questionablestatistical content. This is because some authors opt
to use dishonest statistics as a way to get theirpapers published without having proper statisticalunderstanding and clearly any insight into its
adverse consequences.
One highly controversial issue relating tostatistical contents in research papers intended to
publish in high impact journals, is the inappropriate
use of the p-value in the context of test of
hypotheses. One of the well reputed psychology
journals decided not to publish any articles with pvalue. Although, the p-value can be misused and its
use as a means to make an acceptance or rejection
decision on the null hypothesis can be problematic,
it can still be used as a statistical tool under thecorrect conditions and with appropriate caution, if
the context is clarified. A better option is to provide
the confidence interval, rather than suggesting
acceptance or rejection of the null hypothesis, sothat the readers can see a wider picture on the
tenability of the parameter of interest. Instead of
depending on the p-value of a single study,
combining results from many studies on the same
topic by conducting meta-analysis may be a way toincrease statistical power through increased sample
size and a void the danger of misusing p-value.

importance and use of statistics is found in Khan
[13].
IMPACT OF STATISTICS ON RESEARCH
AND SCIENCE
Would it be too much to say, ‘No researchwithout statistics’? Not really, as it is almost correct
for any research involving collection, analysis andinterpretation of data with the very small exceptionof some qualitative researches in some disciplines.
Many research projects are highly dependent on
statistics in many different ways. There is hardly
any research that does not involve data and hence
require some form of statistical support. In fact,
statistics has changed the way people used to lookat and conduct research.
Every credible quantitative research requires
some kind of data handling. This varies fromplanning and implementation of collection or
production of data to screening and analysis of data,
and the interpretation of results. In the heart of anysocial and scientific research there is data of one
kind or another. The question is how is this datacollected? What sampling or experimental design isused to collect the data? How is the questionnaire
prepared or how are the experimental treatments
allocated? Answers to these fundamental questions
are crucial in determining if the data at hand meetsthe requirements to be scientifically valid, andhence the results derived from them are accurate.
The quality of data is the key into producing any
credible statistics. Inappropriate or invalid or
defective data can’t produce any valid or usefulstatistics, regardless of what or how sophisticatedmethods are used. Statisticians must be involved in
the planning stage of any project involving data to
make sure that the data is collected scientificallyand it captures all information on relevant variablesof interest and whether to conduct planned or post
hoc analyses.
In many research studies the main objective is tofind confidence intervals for unknown parametersor perform test of hypotheses, or both. The validityof the sampling distribution of the underlying
statistic in both cases is crucial, and hence checking
the assumptions of normality, random samples,
equality of variances etc are essential. The
commonly used z, t, chi-squared, and F statistics
are based on the assumption of normal population.
Blind use of these procedures, without properly
checking the data on the validity of the underlying
assumptions, is likely to produce inappropriate andmisleading results and therefore lead to the wrong
conclusions.
Inclusionofstatisticalanalysesinresearch/scientific papers prepared for possible
publication in international journals has become auniversal practice in almost every field. Often there

STATISTICS IN SHAPING SOCIETY
Planning is the core mechanism of thegovernment to direct and manage programs andactivities through allocation of funds to ensurebalanced and targeted development. The intention
is to come up with a budget that helps achieve
desired progress and development in priority
sectors of economy and society. Statistical data is
the back bone and plays a key role in directing
resources to priority areas of every contemporary
planning and allocation of budget. Limited
resources and competing demands in various
sectors, the challenge is to determine the areas ofpriority for investment, and statistical evidence
provides the necessary guidance to rationalise theallocation. Further explanations on the role ofstatistics in planning and development is found in
Khan [14].
The strategic use of statistics in decision-making
by governments, welfare agencies, researchscientists,
internationalorganisations
andbusinesses are making a huge impact on reshaping
societies in several ways. Allocation of resources
for various directed development programs,
focussed interventions, priority engagements,
27

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017targeted human development and management,
universal health and education strategies etc are
based on population statistics.
We are living in a global information society
where the flow of information is ever increasing.
Statistics plays a major role in shaping andproviding scientific information that are useful inalmost every aspect of human life, and beyond. It
has successfully made its mark on as diverse areas
as from astronomy to administration, from businessto biology, from housing to health, fromengineering to environment, from commerce tocommunity, from manufacturing to ministry, frommarketing to management, from industry to
infrastructure, from politics to policy, from tourism
to trade-union, from sports to strategy. Modern
decision-making, be it for an individual or abusiness or any national government or aninternational agency, is increasingly using statisticalmethods to improve the quality of information
and/or decision.
Some of the important features of modern
statistics are highlighted in the following quotation:“Statistics have a key role to play in opening up
government because of the role they play to holding
the Government to account. They used to be called
the `Government’s statistics’ – now they will be thepublic’s.” Jack Straw.
Statistics is used to solve many complex real life
problems which directly contribute to planning anddevelopment. Among popular applications, it isused to (1) prove the effectiveness of a new drug,(2) assess the effect or impact of air or waterpollution on living creatures, (3) measure thedemographic or economic growth, (4) forecast
economic outlook or growth of different types ofcrops and produce, (5) create awareness on national
or global issues, (6) judge popularity of agovernment, party or leader, (7) determine theneeds for doctors, engineers and other professionals,(8) plan for traffic flow on roads and highways, (9)analyse contributions of different sectors of theeconomy on the gross national product, (10)formulate/adopt appropriate population and humandevelopment programs, (11) highlight the state ofunemployment, (12) estimate agricultural andnatural resources, (13) evaluate performance andefficiency gains of the labour force, (14) find theconsumers’ price index, (15) study the performanceof the stock market, (16) enhance the use of theinformation highway, (17) compare among nations
and regions, (18) decide on bank/interest rates, (19)make insurance profitable, (20) evaluate the crimerate, (21) improve the quality of industrial products,(22) settle claims of insurance and pay rises for
employees etc.
The Millennium Development Goal (MDG)
2015 of the UN was planned, monitored,
assessed/evaluated and compared by using relevant

statistics and indices on the specific eight different
areas of health, education, and social status ofpeople globally. See [15] the MDG Report for
details.
The power of statistics is highly dependent on its
quality and absolute public trust in the offices that
produce statistics. As such, one of the main tasks of
any Statistics Office is to earn and maintain theabsolute confidence of the users of statistics and thegeneral public. Public perception of statistics is key
to the success of official statistics. Keeping theclients satisfied is absolutely essential for the
producers of statistics. This is achieved byobserving some fundamental principles of official
statistics and promoting them. Any government
statistics office must (1) retain users’ trust using
strictly professional considerations for decisions on
methodology, terminology and data presentation;(2) establish accountability and transparency bymaking sources and methods used to compile
statistics readily available to users so that they canjudge the fitness of use of the data; (3) addresserroneous interpretation and preventing misuse ofstatistics by explaining
perceived erroneousinterpretation and misuse of statistics; (4) safeguard
the confidentiality of individual’s data; and (5)strictly adhere to the legislation by following laws,
regulations and measures under which the statisticalsystems operate for public benefit.
The importance of statistics in economic
development has been recognised by theGovernment of Japan [16] via observing 18
October as 'the Statistics Day' every year. This day
was fixed on 3 July 1973 by the Japanese Cabinet
for the purpose of strengthening the national
concern and understanding of the importance ofstatistics and promoting their cooperation insurveys held by the central and local governments.
Interestingly, 18 October is the day when theJapanese Government proclaimed the order tocompile its first modernistic statistics, 'Fuken
Bussan-hyo’ in 1870. The day was converted fromthe lunar calendar day, 24 September, to the solar
calendar day, 18 October (see Statistics Day inJapan). The United Nations Statistical Commissionin collaboration with the International Statistical
Institute (ISI) celebrated the second World
Statistics Day [17] on 20 October 2015 to raiseawareness of the many achievements of official
statistics premised on the core values of service,professionalism, and integrity. The event wascelebrated in various ways in over 130 countries.
Details on this are found on the World of Statistics
website.
MISUSE AND ABUSE OF STATISTICS
In spite of world-wide recognition of statistics
and its benefits, the vast majority of ordinary
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

citizens are not well versed with the statistics andwhat it has done for them. Worse even is thedeliberate abuse of statistics for unfair benefit andignorantly spreading misgivings on statistics. Thisis a challenge for all statisticians as well as the
producers and users of statistics to reach out topeople in the community and to remove
misconceptions and present statistics to them in a
way that is easily understood and appreciated andthereby removing any misconception.
To undermine statistics and it phenomenal
contribution to humanity, some ignorant people andlearned sceptics call upon a quote falsely attributed
to the American author and humourist Mark Twain(actual name Samuel Langhorne Clemens), "There
are three kinds of lies: lies, damned lies andstatistics". Stephen Goranson wrote on the MarkTwain Forum on 31 July 2002: Twain's
Autobiography attribution of a remark about lies
and statistics to a former Prime Minister of the UK,
Benjamin Disraeli is generally not accepted.
However, the phrase appeared in 1895 in an article
by Leonard H. Courtney [18] suggests that theorigin of the phrase is still uncertain, but suspected
to be from another British politician Sir Charles
Dilke (The Bristol Mercury, 19 October 1891) who
said, false statements might be arranged according
to their degree under three heads, fibs, lies, andstatistics. It may not be at all wrong to replace theword ‘statistics’ in the above quote with ‘politics’.
Regardless of the source, the inclusion of theterm ‘statistics’ in the phrase is misleading, at leastin the modern sense of the word, and as a key
scientific discipline. Should we then be blaming theperson behind the abuse or the discipline being
abused? Isn’t it, then, synonymous with rewarding
the criminal and punishing the victim?
Unfortunately, the so called quote is not goingaway anytime soon. So we have to live with it not
only preserving the innocence of statistics but also
promoting its enormous goodness to society. It is
worth remembering the fact, ‘figures don'tlie, but liars can figure’ or ‘figures fool, when fools
figure’.
The abuse of statistics is not new, and has been
occurring as a result of ignorance or deliberate actsof dishonest people, as noted by Josefina Mota,“There are two ways of lying. One, not telling thetruth and the other, making up statistics.” And“There are two kinds of statistics, the kind you lookup and the kind you make up” Rex Stout. The
problem is with the ‘make up’ and the one who is‘making up’, but not with statistics as a discipline.
Stephen Leacock stated, “In ancient times they had
no statistics so they had to fall back on lies.” In thecontemporary word statistics is being used even in
the courts to identify and punish the criminals.
Controversial Canadian psychology professor
John Philippe Rushton [19] at the University ofWestern Ontario claimed in the early nineties that
the Whites tend on average to score higher than test
takers of African ancestry on IQ tests, andsubsequent findings that test takers of East
Asian background tend to score higher than whites.
Rushton's controversial work was heavily criticizedby the scientific community for the questionable
quality of its research based on highly biased
convenience sampling with many alleging that itwas conducted under a racist agenda. Since 2002,
he was head of the Pioneer Fund, a researchfoundation that has been widely accused of being
racist.
Flaherty [20] wrote, “In 1998, Dr Andrew
Wakefield, a British gastroenterologist, described a
new autism phenotype called the regressive autismenterocolitis syndrome triggered by environmental
factors such as measles, mumps, and rubella(MMR) vaccination. The speculative vaccinationautism connection decreased parental confidence inpublic health vaccination programs and created apublic health crisis in England and questions about
vaccine safety in North America. After 10 years ofcontroversy and investigation, Dr Wakefield wasfound guilty of ethical, medical, and scientificmisconduct in the publication of the autism paper.
Additional studies showed that the data presented
were fraudulent. The alleged autism-vaccine
connection is, perhaps, the most damaging medical
hoax of the last 100 years.” (c.f. DOI:
10.1345/aph.1Q318).
In November 2015, the republican Presidential
Candidate in the USA, Donald Trump tweeted“Whites killed by blacks – 81%”, citing “Crime
Statistics Bureau – San Francisco”. The US factchecking site Politifact says – “Bureau” did notexist, and the true figure is around 15%. Whenconfronted, Trump shrugged and said, “Am I going
to check every statistic?” During the recent Brexit
movement in the UK, Boris Johnson’s campaign
bus slogan was “We send the EU £350m a week.”
This is another political abuse of statistics as theUK’s net contribution is more like £250m a week
when rebates are taken into account – and aftersubsidies and grants the figure reduces to£136m. Once again the people of power know thepower of statistics and hence they conveniently
abuse statistics to their benefit, even if it
compromises their honesty and knowledge, and at
the end blame the victim.
CONCLUSDING REMARKSThe best sellers of statistics are the main users ofstatistics. Among them are the policy makers in thegovernment departments, business executives in theprivate sector, research communities, andinternational agencies. Everyone who is part ofthese agencies should take responsibility to produce
29

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017high quality statistics to ensure its appropriateness,accuracy, and expected benefits. All goodjournalists use statistics to prepare reliable reports
on various socio-economic and administrative
issues. The value and power of good statistics arewell known to them. They play a key role inpromoting and popularising statistics to the public.
Media related people should have sound knowledge
and understanding of statistics to ensure correctinterpretation and avoid its unintentional misuse orabuse. There are many users of statistics engaged in
the consultancy business as administrators orexperts. These people could directly promote theuse and benefits of statistics in industry andbusiness.
As a continuingly growing subject, statistics isalways in search of better methods to improve on
the existing ones, and introducing new methods for
emerging problems. The researchers and producersof statistics must be abreast all the time so that theusers get the best results possible. This is equallyapplicable to everyone engaged in providing crucial
information for planning and development for
public or private institutions. In this context thegoals of World Statistics Day, “Official statistics
help decision makers develop informed policies that
impact millions of people. Improved data sources,
sound statistical methods, new technologies andstrengthened statistical systems enable better
decisions that eventually result in better lives for allof us” is absolutely important to the statistics
community everywhere. The old rule ‘use it or lose
it’ applies.

https://blog.linkedin.com/2016/01/12/the-25skills-that-can-get-you-hired-in-2016[9] Kolmogorov AN, Grundbegriffe derWahrscheinlichkeitsrechnung. Berlin, Springer,
1933.
[10] Morrison N. Foundations of the Theory ofProbability. New York, Chelsea, 1950.
[11] Nolan, D and Lang, TD, "Computing in theStatistics Curricula", The American
Statistician, 64 (2), 2010, pp.97-107.
[12] Klemens B. Modeling with Data: Tools andTechniquesfor
StatisticalComputing,Princeton
University Press, 2008.
[13] Khan S, “Statistics on Spotlight: World
Statistics Day 2015”, 2015. World of Statistics
Website,http://www.worldofstatistics.org/files/2015/10/
Article-WSD-2015-2.pdf[14] Khan S, “Statistics in planning anddevelopment”, Pakistan Journal of Statistics,
29 (4), 2013, pp. 513-524.
[15] MDG Report 2015,
http://www.un.org/millenniumgoals/2015_MD
G_Report/pdf/MDG%202015%20rev%20(July%201).pdf[16] MDG Report 2015,
http://www.un.org/millenniumgoals/2015_MD
G_Report/pdf/MDG%202015%20rev%20(July%201).pdf[17] Hoss Statistics Day in Japan,
http://www.stat.go.jp/english/index/seido/8i166.htm[18] World Statistics Day,
http://unstats.un.org/unsd/wsd/[19] Courtney LH, 1895,
http://www.york.ac.uk/depts/maths/histstat/lies.htm[20] Rushton, J P.
https://en.wikipedia.org/wiki/J._Philippe_Rushton[21] Flaherty DK, “The Vaccine-Autism
Connection: A Public Health Crisis Caused by
Unethical Medical Practices and Fraudulent
Science”, Annals of Pharmacotherapy, 45(10),2011, pp.1302-4.

REFERENCES[1] UN Better Data,
http://www.un.org/en/development/desa/news/
statistics/better-data-better-lives.html[2] UN Economic and Social Affairs video,
https://www.youtube.com/watch?v=TIpF3iyiT2g[3] S Unemployment Rate,
https://data.bls.gov/timeseries/LNS14000000[4] CBS News
http://www.cbsnews.com/news/jobs-reportunemployment-rate-drops-to-78-percent/[5] Australian Institute of Health and Welfare(AIHW).
http://www.aihw.gov.au/cancer/cancer-inaustralia-overview-2014/appendixb/#t1[6] Breast Cancer Network Australian (BCNA).
https://www.bcna.org.au/understanding-breastcancer/#sthash.ijyB2HVg.dpuf[7] Gauss CF, Theoria motus corporum
coelestium in sectionibus conicis solem
ambientium, 1809.
[8] LinkedIn Blog,

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

Technical Papers

31

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

Science32

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SEA LEVEL IN A CHANGING CLIMATEMaria McCrann1, Dr John Russell2, Dr Daniela Ionescu3 and Dr Bandita Mainali4
1,2,3,4 School of Engineering and Mathematical Sciences, La Trobe University, Australia

ABSTRACTThe rise of the oceans level could have devastating consequences for coastal settlements and it can easily be one of
the most critical effects of Climate Change. Thus, all factors affecting sea level need to be considered. One of thesefactors discussed in this paper is the natural variability originated in the oscillation of the planets and solar activity. The
effect of Sun’s activity on Earth’s climate has been identified since the eighteen hundreds. However, there are still many
unknowns regarding the mechanisms connecting the Earth’s climate to the variation in solar irradiance. Climate
modelling implementing the solar sciences is a novel approach that accounts for the considerable effect that natural
factors has on the climate especially at regional level. This paper discusses the noticeable effect that the planets
oscillations have on the Sun’s activity, which is in very good correlation with the observed patterns in global surface
temperatures, rainfall records, and sea levels. In agreement with many studies that identified a 60-years cycle in thevariation of Earth’s temperature, it is expected that the surface temperatures will reach a trough of the cycle around2030-2040. Furthermore, considering the influence of the Solar Inertial Motion, a solar slowdown is predicted for Solar
Cycles 24 and 25, which will create a weak grand minimum. It is anticipated that this weak grand minimum to bereflected in a dampening effect of global temperatures and a subsequent moderation in the rate of sea level rise.
Keywords: Solar Activity, Sea Level Rise, Planetary Oscillations, 60-years Cycle
gauges examined, believed to be related to wind forcing
and currents variation [14]. As such, they are notspatially uniform and are directly associated withatmospheric oscillations such as the PDO, AMO and
ENSO, and they influence sea surface temperatures,pressure levels and surface winds [15]. Moreover, Reid[16] compared the long term trend of Sea Surface
Temperature (SST) with the corresponding trend of solar
activity and found a significant correlation especiallyduring the minima periods.
Numerous studies reported that the Sun’s activity ismoderated by the planets oscillation on the Solar system,
modifying so the relative location of the Barycenter tothe Sun’s centre of mass [10], [17], [18]. These studies
also noted that the oscillations of the planets have a close
link with the variations of Earth’s global averagetemperatures, sea temperatures, and sea levels.
Church and Zhang [19] suggested that coastal
regions are mainly impacted by the combined effect oflong term sea-level rise and natural variability. The factthat sea-level rise is not uniform across the worldwide
oceans, makes it difficult to separate natural variability
from the signal of climate change at a regional scale. In
agreement with the Intergovernmental Panel for Climate
Change (IPCC) physics-based projections models,
Church and Zhang [20] indicated that sea-level changes
are likely to show over 80% of the world’s oceans by2030. However, Lyu et al. [21] suggested that, in thenext 20 years, at a regional scale, the signature of naturalvariability is likely to exceed the effect of theanthropogenic climate change on the rise of sea level formany areas of the globe.
In spite of the general agreement that Solar activity
affects the Earth’s climate, opinion that is supported by
the broad data and re-emerging theories, the solar effects
on climate are not yet well defined. Jones et al. [22] useda simple climate model to assess the potential

INTRODUCTION
There is abundant evidence of large changes in sea
level during the Earth’s past history. For example, about
120,000 years ago during the warm period, the average
global temperature was about 2 degrees Celsius higher
than today and the sea level exceeded 5 meters above
present levels. Then, 22,000 years ago during the Ice
Age, sea level was 120 meters lower than today [1].
Paleoclimate reconstructions based on climate
proxies such as ice cores, tree rings, and lake sediments,
enable links between the Earth’s warm and cool periods
with the Sun’s activity. Most reconstructions of the solar
activity are based on the sunspot number, and the solar
cycles’ length or frequency. Eddy [2] noted a correlation
between periods of significant change in the number ofsunspots in the past millennium and large changes in the
climate of the Earth. Hence, many studies reported thatduring periods of low solar activity, lower than average
European temperatures were recorded [3]–[7]. Such
periods of low solar activity are, the Maunder minimum(1645-1715), Dalton minimum (1800-1820), 1900
minimum (1880-1900), and a slight decrease between
1940 and 1970. Also, a sharp maximum in the global
temperatures around 1830 is connected to high solar
activity. Superimposed on these long-term trends ofminima and maxima are short-term fluctuations causedby the Schwabe cycle [8], [9]. Furthermore, other studies
suggest that the climate and atmospheric oscillations
such as the Pacific Decadal Oscillation (PDO), theAtlantic Multi-decadal Oscillation (AMO) and El Nino
Southern Oscillation (ENSO) are synchronized to thenatural oscillations of the Solar System, which are
driven by the movements of the planets around the Sun
and lunar gravitational tides [7], [10]–[12]. In addition,
Chambers et al. [13] identified multi-decadaloscillations of about 60-years in most of the ocean tide

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

implications for future climate projections for a range ofsolar radiance scenarios. However, this study was basedon Total Solar Irradiance (TSI) variations and concluded
that the use of TSI may not capture the net effect of solar
variability as it fails to incorporate UV variability and‘top-down’ influences through stratospheric changes.
Even though the solar influence shows small effects on
global temperatures when compared with the modelledanthropogenic effects, the regional and seasonalvariations around the globe have a closer link to the solar
activity. Hence, modelling regional climate needs toconsider a larger forcing due to solar and naturalvariability [4], [23]. Subsequently, it is expected that theregional sea level changes will be closely related to thenatural variability and solar forcing.
Van Loon and Meehl [7] found that when thesunspots peak and the North Atlantic Oscillation (NAO)
are in phase, there is an intensified positive NAO withnegative Sea Level Pressures (SLP) anomalies in the
North Atlantic greater than 6 hPa and positive anomaliesof about 3 hPa in the subtropical North Atlantic. This is
likely to have a considerable effect in ocean’s basins
given that under a positive NAO index (NAO+), the'inverse barometer effect' is observed on regional basis,
where the reduction in atmospheric pressure creates aregional rise in sea level. This effect is important to boththe interpretation of historic sea level records and thepredictions of future sea level trends, as mean pressure
fluctuations of the order of few hectopascals can lead tosea level fluctuations of the order of centimetres [24].
There are various factors contributing to sea levelrise, though the thermal expansion of water in the oceans
is the most influential and accounts for about 35% of thepredicted sea level rise [25]. Thermal expansion of theoceans is complex and depends on the watertemperature, the global surface temperature, and theoceans thermal inertia. Therefore, observing the trends
and oscillations of global temperature can serve as a
guide on how oceans will behave.
Some studies [26], [27], reported that the average
global temperature records are characterised by decadal
and bi-decadal oscillations. In general, these oscillations
are in good correlation with the 11-years Schwabe andthe 22-years Hale Solar cycles, with higher global
temperatures related to higher solar activity. Current
predictions on the Solar activity show that we are in alow sunspot cycle similar to that of the 1900 Minimum
and the subsequent cycles are predicted to present evenlower Solar activity, therefore a drop in global
temperatures is expected [28]–[30]. Considering thesignificant influence of the thermal expansion of theoceans, it is predicted that the sea level will follow the
global temperature oscillations (with a lag due tothermal inertia), resulting in a subsequent moderation in
the rate of sea level rise, as it happened in 2010-2011
due to an exceptionally strong La Nina event [31].

between 1993 and 2015 by the satellite
TOPEX/Poseidon, Jason-1, and Jason-2, which shows alinear trend and a rate of increase of 3.4±0.4 mm/yr [32].

Fig. 1 Satellite altimetry time series 1993-2016 [32]
It is important to note that there are many methods
used to review the sea level rise, employing different
trend approaches and assumptions, which at times leadto contradictory acceleration – deceleration inferences.
This aspect has been reviewed in detail by Visser et al.
[33]. They explored the sea level trends using more than
one method in addition to cyclic or additional
information such as the SOI or PDO to provide a better
trend description. Furthermore, Watson [34] developed
a methodology to provide a consistent transparent
appraisal of acceleration in mean sea level records using
the Singular Spectrum Analysis (SSA). This techniquereadily separates the trend of sea level from the 60 years
dynamic ocean oscillations and noise.
The limitation of Satellite data (Fig. 1) is that spans
only over 20 years, hence cannot encapsulate anddescribe larger multi-decadal scale natural oscillations.
In contrast, tide gauges on offer a long term view of thechanges in mean sea level. Though, the tide gauges arelocated in the Northern Hemisphere (Europe, Japan, theUnited States), providing poor sampling. Additionally,tide gauge records do not cover the same time period[35]. Therefore, it is useful to define sea level variation
on a regional base considering a wide range of local
processes to eliminate misleading estimates that global
ocean level average could introduce. Furthermore, theeffects of natural variability are likely to influence oceanlevels without adding to the volume.
FUNDAMENTAL DRIVERS FOR NATURAL
CLIMATE CHANGE VARIABILITY
Fluctuations in the oceans levels are common andthis paper investigates their relationship with naturalvariability and oscillations. These natural oscillations
have drivers such as the solar variations, the planetaryforces, and Earth’s orbital changes. It is suggested thatthese three natural drivers for climate variability havenoticeable influence in surface temperature patterns andconsequently sea level rise. Other natural drivers such as
volcanic eruptions and regular, repeatable lunar motions
are excluded from this paper [36].

SEA LEVEL
There are two main data sources for global sea level
namely satellite altimeters and tide gauges. Figure 1
presents the Global Mean Sea Level (GMSL) monitored

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

The variations in the sunspot number reflects the solar
activity and therefore is related to the changes in TSI.
The monitored values of TSI since the beginning of the
1990s shows a decline and the last value measured for
Cycle 24 was 1361.53 W/m2.
According to research undertaken by Hathaway [38],it is expected that Solar Cycle 25, peaking around 2022,
be the weakest one [30]. It is anticipated that the
reduction in Sun’s activity to result in temperature drops
due to reduced energy received. These changes in TSI
would be level out by the thermal inertia of the ocean.
However, low TSI for two or more consecutive cycles
will cause temperatures drop and delayed sea level rise
decline due to the thermal inertia of the ocean. It is worth
noting that the variation of the TSI might be increasedby feedback mechanisms that amplify the solar
variations generating large weather effects. It is believedthat some of these mechanisms are radiative forcing,cosmic rays, the stratospheric solar vortex, cloud coverand albedo, cosmic rays related to changes of the ozone
layer, etc. [39], [40]. However, these mechanisms areoutside the scope of this paper.

Solar Variation
In 1843, astronomer Henrich Schwabe was the firstto demonstrate the 11-years cycle of the sunspots.
English astronomer Walter Maunder reported that from1645 to 1715 sunspots had been generally absent. Such
period with a minimum number of sunspots is now
known as the Maunder Minimum and was accompanied,in Europe and other regions, by the most severe
temperature dip for several millennia [37].
Eddy [2] noted a correlation between periods ofsignificant change in the number of Sunspots in the pastmillennium and large changes in the climate of the Earth.
Figure 2 illustrates the correlation between the Sunspots
activity and the drops of temperature registered inhistory. It is clear the periods of minimum temperature
occurred when the number of sunspots registered wasconsiderably lower than for other periods.

Planet forces
In addition to the findings reported earlier, manystudies indicated that the Sun’s activity is moderated by
the Solar System planets oscillations which shift thelocation of the Solar System Center of Mass (SSCM) or
the Solar System Barycenter (SSB) [29], [41]–[43].
Furthermore, it has been noted a close link between
planetary oscillations and Earth’s global averagetemperatures variation, thus with the sea temperatures
and the sea levels.
Charvátová [44] reviewed work by Paul Jose who
was one of the first researcher to link solar modulation
with planetary movements. Jose observed that the Sun
oscillates around the center of mass of the Solar System(Barycenter), in order to balance the variation in planets
position, hence the center of gravity remains at rest. The
Solar Inertial Motion (SIM) and Solar variability studies
found that the planets returned to roughly the same
position every 178.8 years or 172 years as suggested byothers, a frequency that is similar to that of sunspots
activity [53].
The extent of Sun oscillation around the Solar
System Barycenter is affected by the relative mass of theplanets as displayed in Fig. 4. Figure 4(a) shows the
positon of the center of gravity of the Solar System.
Figure 4(b) simulates the significant shift in the positionof Barycenter when Jupiter is removed from the Solar
System. Figure 4(c) presents the change in the locationof the center of gravity if both Jupiter and Saturn are
removed. Once Neptune is removed, the effect of theremaining planets is barely noticeable. Hence, Jupiterhas the highest effect on SIM due to its largest mass [10],[29].
The gravitational forces between planet and Sun
affect the Solar System dynamics causing harmonicresonances that also modify magnetic and electricalforces. According to Sharp [29], these harmonic drivers
can be separated into three levels.

Fig. 2 Sunspots numbers and the periods of reduced
Solar activity (after [8], [45]).
The solar activity alternates between active and quiet
phases with a frequency of 11 years known as the
Schwabe cycle. Figure 3 presents the 11-years cycles ofsolar activity. It shows a maximum of 150 sunspots for
Cycle 24, contrasting with 81.9 sunspots reported
NOAA in April 2014. This is the cycle with the lowest
maximum of sunspots since Cycle 14, which had amaximum of 64.2 sunspots in February of 1906. Cycle
14 coincides with the 1900 Minimum [30].

Fig. 3 Projected and observed sunspots [38].

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

(a)

(b)

uniform. Although, Baldwin and Dunkerton [15] founda direct correlation between these atmospheric factors
and the atmospheric oscillations (PDO, AMO, ENSO),
which have a significant effect on the sea surface
temperatures, pressure levels pressure, and the surface
winds.
Merrifield et al. [49] reviewing several studies foundthat on decadal to multi-decadal time scales, variationsof up to 1 cm in the level of the Pacific Ocean, believed
to be caused by a combination of Pacific trade winds.
There is a consensus regarding the sea level fluctuationsin the Western Pacific Ocean with the PDO index,
finding based on tide gauge observations that provide a60-years long record. Also, Van Loon and Meehl [7]stated that the decadal time scale climate variability in
the Pacific region was due to external forcing fromvariations in the solar irradiance and the internal climate
variability associated with the PDO. Therefore,
Chambers [14] concluded that the regional variability
and strong effects of wind stresses in the Pacific Ocean
could be the reason why there was no 60-years
oscillation found in his analysis for the Central/Eastern
North Pacific. Furthermore, Chambers et al. [13] pointed
out that incorporating the 60-years oscillation in themean sea level variation, did not change the overall
conclusion that sea levels have been rising on averageby 1.7mm/yr over the last 110 years. It simply shows anatural oscillation that permeates into the sea levelmeasurements [13]. Therefore, this natural oscillation
should be considered when estimating future sea level
rise as proved to be directly related to the planetary
orbits and solar activity, which in time modulates
atmospheric variables such as PDO, AMO, ENSO, etc.
Figure 5 presents Chambers et al. [13] findings,(c)Fig. 4 Sun’s path around the Barycenter (not to scale)when: (a) including all planets; (b) removing
Jupiter; (c) removing Jupiter and Saturn [45].
Level 1 includes the Ice Age Cycles due to orbitalchanges as stated by Sharp, reporting on work by
Milankovitch [36]. These cycles are very long and affectlong term climate variations such as glacial andinterglacial periods.
Level 2 comprises of Solar Grand Minimum andSolar Modulation Cycles. This level is governed by the
SIM theory, which states that the Sun follows akaleidoscope like pattern orbit around the SSB [46] asshown in Fig. 4. The wobble of the Sun generates
changes in its Angular Momentum (AM), velocity,
acceleration, and torque. Several studies have found acorrespondence between the Grand Minima and thevariations of the position of the Sun relative to the
Barycenter [29], [43], [47], [48]. Sharp [29] stated that
this level is modulated by the 172 years conjunction of
Neptune and Uranus and suggested a spacing of 172-179
years between Grand Minima. Based on the influence of
the Solar Inertial Motion a solar slowdown is expected
for Solar Cycles 24 and 25 that will create a weak grandminimum expected to trough around 2030. The
implications of this predicted weak grand minimum canbe expected to be observed in a decline in global
temperatures and a subsequent moderation in the rate ofsea level rise.
Level 3 refers to the well-known 60-years cycle in
the Earth’s temperature record that seems to align with
the PDO/ENSO records. There is significant evidence[11], [26] showing a coincidence between the global
temperature record and two Solar System harmonic
patterns, the Solar velocity 60-years cycle and theJupiter/Saturn synodic harmonic cycle along with Lunarharmonics.
THE 60-YEARS OSCILLATION AND SEA LEVEL
Chambers et al. [13] identified a significant
oscillation of about 60-years in the majority of the tidegauges examined. Using the average of tide gauges infive ocean regions, Chambers team found similar phaseand amplitude for North Atlantic, Western North Pacificand Indian Oceans, while for the Western South Pacificthere was a 10 years lag in the monitored tide gauges.
Though, the mean sea level measured in theCentral/Eastern North Pacific region did not show a 60
years fluctuation. As mentioned earlier, Chambers [14]suggested that these fluctuations are related to wind
forcing and currents variation, which are not spatiallyFig. 5 Sixty-year cycle in Mean Sea Level for world’s
oceans [13].

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

Ganopolski A, González Rouco J, Jansen E, Lambeck
K, Luterbacher J, Naish T, Osborn T, Otto-Bliesner B,
Quinn T, Ramesh R, Rojas M, Shao X, andTimmermann A, “Information from paleoclimate
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Basis. Contrib. Work. Gr. I to Fifth Assess. Rep.
Intergov. Panel Clim. Chang., Cambridge University
Press, 2013.
[2] Eddy JA, “The Maunder Minimum”, Science, Vol.
192, No. 4245, 1976, pp. 1189–81202.
[3] Ineson A, Scaife AA, Knight JR, Manners JC,
Dunstone NJ, Gray LJ, and Haigh JD, “Solar forcingof winter climate variability in the northernhemisphere”, Nat. Geosci., Vol. 4, No. 11, pp. 753–
757, 2011.
[4] Lockwood M, “Solar influence on global and regional
climates”, Surv. Geophys., Vol. 33, No. 3–4, 2012, pp.
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which shows a 60-year cycle in the sea level data,smoothed with a 5-years running mean. The North
Atlantic variation has an optimal period of 64-years.
However, this 64-years oscillation is not evident in theCentral Eastern Pacific gauges (Fig. 5). The Western
North Pacific and Indian Ocean levels seem to be inphase, whilst the North Atlantic gauges are slightly
delayed. The minimum level is around 1915–25, with apeak around 1950–60, and another minimum around
1980–90. The phase of the South Pacific gauges around
Australia/New Zealand lags by about 10 years (Fig. 5.b).
Concerns were raised by Chambers et al. [13] inusing sea level records shorter than two cycles of 60years, as at this point it is not fully understood if there is
a 60 year oscillation present in the GMSL. Highhesitation was articulated by some researchers in lieu
with the interpretation of acceleration in GMSL basedon only 20-years record from satellite altimetry [13].
Chambers and his team’s research (particularly
findings presented in Fig. 5), supports the theory of anatural variability underlining the changes in sea level.
On the other hand, assuming that thermal expansion may
be a key factor contributing to the sea level rise andbased on the premise of the effects of solar activity, it islogical to predict that a reduction in the global averagetemperatures might manifest in a consequent slowing of
the rate of sea level rise.
CONCLUSION
The oscillations of the planets have a noticeable
effect on the Sun’s activity and shows a good correlation
with the observed patterns in global surface
temperatures and sea levels.
Based on the influence of the Solar Inertial Motion asolar slowdown is expected for Solar Cycles 24 and 25
that will create a weak grand minimum which combinedwith the 60-years cycle is likely to dip around 20302040. The implications of this weak grand minimum canbe expected to be reflected in a dampening effect of
global temperatures and a subsequent slowing in the rateof sea level rise. This dampening effect is expected to be
more noticeable when assessing climate variability on aregional scale for decadal and multi-decadal projections.
The combination of natural forces andanthropogenic effects is paramount when analyzing our
climate, as the natural variability has a larger effect at aregional scale. Therefore, the inclusion of solar andplanetary influences in regional models is
recommended.
ACKNOWLEDGEMENTS
The authors would like to thank Phil Watson fromthe University of New South Wales, Nicola Scafetta,
Don Chambers and Geoff Sharp, for clarification andcomments. This work is sponsored by the Australian
Postgraduate Award (APA).
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38

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EBOLA VIRAL PROTEIN 24 (VP24) INHIBITOR DISCOVERY BY IN
SILICO FRAGMENT-BASED DESIGN

1

Syafrida Siregar1, Erwin Prasetya Toepak1, Usman Sumo Friend Tambunan1*
Bioinformatics Research Group, Department of Chemistry, Faculty of Mathematics and Natural Science,
Universitas Indonesia, Kampus UI Depok, West Java 16424, Indonesia
ABSTRACT

Ebola hemorrhagic fever (EHF) is a fatal disease caused by Ebolavirus that can potentially lead to death. The
number of fatalities reached 11.000 of the 28.000 reported cases. A serious concern should be taken because neither
drug nor treatment to cure this disease has been found until now. Recent studies show that viral protein 24 (VP24) is
one of the structural protein that plays a key role in EBOV proliferation and viral life cycle. In this study, we tried tofind the potential inhibitor for EBOV VP24 through in silico experiment. About 242.520 compounds from ZINC15 In
Vitro Database were obtained and screened according to the Rules of Three and pharmacological properties to get aproper lead-like fragment compounds. These compounds were docked into the active site of VP24 using MOE 2014.09
software. The potential fragment compounds were linked to generate potential inhibitor ligands. These ligands werescreened earlier based on Lipinski’s Rule of Five and toxicity prediction, then they were docked once again to obtainthe favourable ligand. Furthermore, the dynamics simulation of best ligand, namely L833, L217 and L595, were
performed to predict the ligand-enzyme complex stability. In the end, we conclude that L595 is the best ligand.
Moreover, the pharmacological and toxicity prediction also confirm that L595 can be developed as the potential
inhibitor for EBOV VP24.

Keywords: Ebolavirus, Viral Protein 24, Molecular Docking, Pharmacological, Toxicity Prediction
replication process of the Ebolavirus genome. The
direct association of the ribonucleoprotein complex
in the infected cells occurs in both processes [9].
In silico study has been used for several years by
researchers. This study provides efficient andeffective results, as it provides accelerated
identification and optimization of drug discovery.
Not only researchers, but the pharmaceuticalindustry has also utilized In silico analysis in theirdrug design pipeline because it can recommend
affinity selectivity to a small number of compounds.
Study In silico utilizes the 3D structure of theprotein as the starting point of the pharmacologicaltest, and this structure provides a visualization of
the interaction occurring in proteins. Vincent Zoete
et al. 2009 reported that there are more than 50
compounds of In silico study results that haveentered the clinical trial stage and some of them
have been approved by The Food and Drug
Administration (FDA) [10].
The fragment-based design is one of the drug
discovery approaches in Silico study. In a fragmentbased approach, the small-molecule formed fromlow molecular fragments from the molecule period
is different from the high throughput screening(HTS) approach. HTS is not yet clear which part ofthe molecule is heavily involved in the binding
energy even though HTS hit binding is obtained bythis approach [11].

INTRODUCTION
Ebolavirus is a part of Filoviridae family that cancause a fatal disease like Ebola hemorrhagic fever [1].
The virus is endemic and deadly in humans andnonprimate [2]. Fever, sore throat, muscle aches, andheadache are symptoms of Ebola hemorrhagic fever[3]. The spread of this virus has occurred from one
country to another such as in West Africa. Liberia,
Guinea, Sierra Leone was attacked by Ebolavirus in
2014-2015. This disease causes up to 11.297 deaths asreported by WHO [4].
RNA of the Ebolavirus genome encodes sevenstructural protein and one non-structural protein [5].
The encoded structural proteins are transmembrane
glycoprotein (GP), nucleoprotein (NP), four viralprotein (VP24, VP30, VP35, and VP40) and RNA
polymerase (L) [4,5]. VP40 is known to be theprincipal protein matrix and the most abundant viralprotein. It contributes to the proliferation process of
EBOV. The viral maturation involves VP40 that joins
the cell membrane. The process of viral maturation of
infected cells by inducing virion assembly in theplasma membrane [7]. VP24 is the second protein
matrix and a minor portion of the viral protein [8]. The
VP24 function as viral protein is not known certainly[6,7]. However, as a structural protein, VP24 may playa role in the virion assembly process [8]. Other
supporting statements are put forward by Shinji
Watanabe et al., 2007. They reported that VP24 canreduce transcription and

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

METHOD

Hits Determination, Fragment
Linking, And Screening

Preparation Of Protein VP24
In the initial stage, we determined the fragmentthat bound to an amino acid. Then, we searched for a
fragment that did not overlap to the first fragment.
Both of these fragments were linked by using linker
database in MOE 2014.09 to generate potential
inhibitor ligands. The results are screened using
Lipinski’s Rule of Five (RO5). RO5 was applied
because it can predict drug-like feature closely related
to the efficacy of the drug in clinical trials [18]. Thenwe performed molecular docking and redocking withthe same retain as the previous molecular docking
parameter. The results obtained from the simulation
were saved in mdb format.

The 3D structure of the target protein become a
new approach to structure-based drug design [12].
In this study, the 3D structure of VP24 was
obtained from the Protein Data Bank(http://www.rcsb.org/pdb), water molecules, andheteromolecules that attached to the protein
structures were removed [13]. Lig X function in
MOE 2014.09 was applied to viral protein for
designing optimized process of VP24.
Preparation Of Fragment
Fragment database was obtained by downloading
the molecules from ZINC15. ZINC15 is a databasedevelopedbycombining
biologyandchemoinformatics together. With this database,researchers can access ready-made compounds forvirtual screening, ligand discovery [14]. Compounds
from the database then screened using RO3 (rule ofthree). The main purpose of the screening process is to
get molecules that have the desired properties so that it
becomes a more efficient sample [15]. The rule ofthree was applied by using Osiris DataWarrior
software,(www.openmolecules.org/datawarrior/).
MOE 2014.09 software was applied to get energy
minimize and also the partial charge with the same
software in an MMFF94x force field software.

Analysis Of Protein-Ligand Interaction,
Pharmacological And Toxicity Prediction
We determined the protein-ligand interaction byfinding the active site of VP24 that bound with low
binding energies ligand. At this step, we also
applied Toxtree, Osiris DataWarrior VEGA, andexperiment to predict pharmacological and toxicity
characteristic.
Molecular Dynamics
In this study, we performed dynamic simulation
using MOE 2014.09 as the final step. The first stage inthe simulation is ligand preparation. Energy
minimization and geometry optimization are applied indynamics simulation. The process of minimizing
energy and optimization is almost similar to thedocking simulation stage as well as the parameter
except for Generalized Born solvation is applied to
dynamics simulation consisting of initialization,equilibration, production. At the initialization, theheating process was performed for 10 ps from 300 K
to 312 K. At the equilibration stage was done for 100
ps at 312 K, while in the production phase was set to
20,000 ps at 312 K.

Molecular Docking Simulation Of Oleuropein,
Ouabain, And Fragment DatabaseIn this step, we did molecular docking simulation
by applying MOE 2014.09 [16] in oleuropein, ouabain
and fragment database. Oleuropein is one of phenolic
compound in olive leaves. It has been proved by
Sebastian Pleśko et al. 2015 that oleuropein can act as
an inhibitor of VP24 [6]. Edwige Picazo, 2015
reported that ouabain has the possibility to inhibit theactivity of VP24 [17]. Molecular docking is toprophesy the natural position, orientation, andconformation of the small-molecule ligand within thebinding site of a targeted molecule [10]. The firstmolecular docking use retains 30. It means 30 times ofplacement pose as parameters.

RESULTS AND DISCUSSION
Set Up Protein VP24
The protein used in this study was obtained fromProtein Data Bank (PDB ID 4U2X) as reported by
Sebastian Pleśko (2015) [6] and Wei Xu (2014) [19]with some modification. The interaction between
ligand and one of amino acid residues wasconsidered as a potential inhibitor candidate for
EBOV VP24. We minimized the structure of VP24
when RMS Gradient structure of this protein is 0.05
kcal/mol/ Å2 by using ligX in MOE 2014.09 in
Amber10:EHT force field.

Molecular Redocking Of Oleuropein,
Ouabain, And Fragment Database
In addition, redocking also to validate the resultsfrom the previous docking simulation. To validate thedocking retain 30, we continued redocking retain 100.
Redocking was done by using MOE 2014.09 software.
The ligands with root mean square deviation (RMSD)
values lower than 2.0 and Gibbs binding energy(Δԍbinding) lower than standards will be selected as thebest ligand [10].

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

Set Up Fragment Libraries
Molecular Docking Simulation
Of
Oleuropein, Ouabain, And Fragment Database

From ZINC15, we obtained 242.520 compounds.
Osiris DataWarrior was used to screen and create thefragment libraries. The rule of three (RO3) wasapplied for ensuring that fragment libraries contained
fragment-like properties and only consisted of simple
molecules that can be easy to elaborate [9,12]. The
molecule properties in the Rule of Three were applied
to screen compounds, and it resulted in 6662
fragments. The criteria of Rule of Three (RO3) follow
rules such as [20]:the value of molecular weight areless than 300g/mol; the amount of hydrogen bondacceptor and donor are less than or equal three; thevalue of cLogP is 3, and have less than or equal withthree hydrogen bond donor.

Molecular docking simulation to oleuropein,ouabain, as ligand standards and the fragment
database as a sample by using MOE 2014.09
software produced 1285 ligands and delivered ascore of binding energy (ΔGbinding) from each ligand.
Gibbs free energy binding energy (∆Gbinding) is used to
predict which ligand-protein conformation that binds
stronger. We also obtained the active site of VP24 at
asparagine and tryptophan (Asn130, Asn132, andTrp38). Moreover, we acquired interactions among
VP24 with ligands. The first, among asparagine(N130) with fragment number 30 as shown in Figure
1. This residue in line with what has been reported by
Sebastian Pleśko, 2015 [21]. The other with fragment
number 300 as shown in Figure 1. These fragments
are the candidate that would be linked to the next
phase and each fragment has RMSD value of 0,8359
and 1,4322, respectively.

Besides that, some rules are added in RO3,
which is the number of rotatable bonds is less thanor equal to three and the value of the polar surface
area is 60 Å2. The construction of fragment
libraries used Osiris DataWarrior. Toxicity
parameters, such as mutagenic, tumorigenic, irritantand developmental toxicity were applied. We
obtained 1285 ligands after toxicity screening
assay.

Prediction Of Linking Fragment And MolecularDocking Of Ligands And Potential Fragment

In this step, we linked fragments that resulted
from the previous step. Both of fragments werelinked with residue amino acids to form a linking
fragment. It was expected that all of the linked
fragments will produce higher affinity [20]. The
linking process was done by using Link Multiple
Fragments features in MOE 2014.09 software. The
result of linked fragments was screening according
to energy minimized and partial charge.
Molecular docking was applied twice withdifferent retain. The docked ligands were given
code L and followed by mseq number. In this study,
we chose three ligands for selecting. The redocking
process was applied to get root mean squaredeviation (RMSD) score lower than 2.0 Å [10]. The
best ligand is L595, 3-amino-N-((S)-1-(4-((E)-1-(6((S)-2-amino-2-(furan-2-yl)ethyl)pyridin-2-yl)-4hydoxybut-2-en-2-yl)phenyl)ethyl)benzamide
which has ∆Gbinding -54,2638, pKi (inhibition
constants) 39,5304 and RMSD 1.5134. Scores∆Gbinding, RMSD, pKi and Osiris DataWarior for
three ligands and standard ligands were shown in
Table 1 below.

Fig. 1. Molecular interaction of the protein EBOVVP24 with fragment 30 (top) and fragment 300(bottom)

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

Table 1. ∆Gbinding energy, pKi, RMSD scores from the selected linked compounds and standard ligands

Polar
LigandLinker∆Gbinding(RMSD)

L833-54,8520
kcal/mol
1.7644

L217-54,8511
kcal/mol
1.9861-54,2638
kcal/mol
1.5134-44,1153
kcal/mol
2,8153

L595

Oleuropein*-41,2201
kcal/mol
1,1113Ouabain*

Molecular
weightHDonor

HAcceptor

C logP

496,6334

72,9530123,78495,5853

91,8767135,13496,6094

7

2,9814

127,4032,1373

540,5166

13

0,3124

201,6730,0282584,6568

12

1,4423

206,60pKi

39,9986

39,9582

39,5304

Surface
Area

Note: * standard ligand
Prediction Drug Scan

DataWarrior analysis is shown in Table 2 below.
Parameters developmental/reproductive toxicity,
potential S Typhimurium TA100 mutagen based on
QSAR, potential carcinogen based on QSAR in
VEGA analysis are showed in Toxtree. The result
from VEGA analysis is shown in Table 2 below.

We predicted toxicity and drug likeness for allof ligands and standards ligands by using Osiris
DataWarrior, VEGA and Toxtree analysis [22].
Parameters mutagenicity, tumorigenic, irritanteffect, and developmental toxicity are showed in
Osiris DataWarrior analysis. The result from Osiris

Table 2. Toxicity prediction by Toxtree and VEGA
No

LigandMutagenic

Tumorigenic

Irritant

1
2
3
4
5

L833
L217
L595
oleuropein*ouabain*

None
Low
None
None
None

None
High
None
None
None

None
None
None
None
None

Developmental
Toxicity
None
High
None
None
None

Reproductive
Toxicity
No
No
No
No
No

Mutagenicity(S.Thypium)
No
No
No
No
No

QSAR
Carcinogenicity
No
No
No
No
No

Note: * standard ligand
considered as potential inhibitor candidates.The
molecular weight (MW) of the ligands is less than 500
g/mol, clogP is less than 5.0, have less than 5hydrogen bond donor and no more 10 hydrogen bondacceptor. The parameters of Veber rules are different
with Lipinski’s RO5. Veber rules only have 2
characteristics for candidate inhibitor. The first

The results toxicity prediction by OSIRIS
DataWarrior, Toxtree and Vega analysis showed,
L595 has same characteristics with ligands standard
oleuropein,ouabain.
The
drug-likenesscharacteristics according to Lipinski’s RO5 andVeber rules. Lipinski’s RO5 has several
parameters[23]. Ligands have these parameters are

42

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

parameter is no more 10 rotatable bonds. The last,polar surface area is equal to or less than 140 Å.

∆Gbinding and RMSD smaller than 2 (table is shown
below). Another consideration in choosing the best
ligand is the change in RMSD value of not more than3Å every 1 nanosecond (ns). The meaning of thischange value indicates the stability of the ligand

Dynamics Simulation
From dynamic simulation of the production
stage, we obtained interactions with amino acidresidues from three ligands with lowest[24]. The change of RMSD value of dynamic
simulation result is shown in Figure 2.

Table 3. Interaction L833, L217, L595 with amino acid residues

Moleculer docking

MD simulation

L833
Q33, W38, N132, V31,
L91, W92, L127, K218,
L201, E88, T128, S89, l87,
T129, N130

L217
L201, K218,L127, S89,
L91, W92,T128, T129,
N130, E88,V31, N132,
Q33, W38

L595
L201, K218, L127, S89,
L91, W92,T128, T129,
N130, E88,V31, N132,
Q33, W38

N30, E88, K218, T86,
T129, T128, l87, S85,
P216, K61, P83, N82, N84

E88, K218,L201, T28,
S89, W92,N130, T129,
L127,L91,W38, Q33
V31, N132

E88, W92, L201, L127,
K218, T128,L91, N130,
V31, N132,S89, l87,
W38, Q33

Note: red color is amino acid residues that found in the binding site of the protein. Bold font is residues thatfound in the protein.

Fig. 2. Graph of RMSD (Å) against time (ps)International Terindeks untuk Tugas Akhir
Mahasiswa No: 693/UN2.R3.1/HKP.05.00/2017.
USFT designed the study and supervised thisresearch, while EPT and SS were performed theexperimental details. We also would like to thankMr. Mochammad Arfin Fardiansyah Nasution for
helping us to proofread this paper.

CONCLUSION
We concluded that L595 is the best ligand from
L833 and L217. The L595 have ΔGbinding -54.2638
kcal/mol, and RMSD 1.5134. Toxicity prediction
by Osiris Data Warrior, Toxtree, and VEGA
showed that L595 can be developed to be a
promising lead candidate for inhibiting Ebolavirus
and more stable than L833 and L217 which havesmaller ΔG binding. It is expected that this research
will be continued in vitro and in vivo experiments.

REFERENCES[1]

CONFLICT OF INTEREST[2]

We declare that there is no conflict of interest in
this research for publication
ACKNOWLEDGEMENTS
We would like to thank Directorate of Researchand Community Engagement of Universitas
Indonesia (DRPM UI) for funding the research andpublication of this article through Hibah Publikasi

[3]

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Zwiers, J. Paragas, and R. N. Harty,“BiochemicalandFunctional
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Butygin, O. Y. Butygina, and A. B.
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Virtual Screening and Molecular Docking
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2015.
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Conjugated to HIV-1 Tat Peptide as
Inhibitor of N-Terminal Heptad Repeat
Glycoprotein-2 Ectodomain Ebola Virus
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Third International Conference on Science, Engineering & Environment (SEE), USQ,
Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

FRAGMENT-BASED LEAD COMPOUND DESIGN TO INHIBITEBOLA VP35 THROUGH COMPUTATIONAL STUDIES
Atika Marnolia1, Erwin Prasetya Toepak2, Usman Sumo Friend Tambunan3
Research Group, Departement of Chemistry, Faculty of Mathematics and Natural
Science, Universitas Indonesia, Kampus UI Depok, West Java 16424, Indonesia

1 Bioinformatics

ABSTRACT
Ebola virus (EBOV) is a virus that is classified under Filoviridae family as a pathogenic organism.
On March 2016, World Health Organization (WHO) reported that 28.646 cases caused by EBOV. Thus, it
is important to find the antiviral drug for this disease because it can create the epidemic around the world.
EBOV VP35 is a potential drug target because it has the component of the viral RNA polymerase complex
that will hamper the host interferon (IFN) production. In this research, about 6.662 fragments were obtained
from ZINC15 Biogenic Database after the Rules of Three, and pharmacological properties parameters wereapplied. After that, these fragments were docked into the active side of EBOV VP35 using MOE 2014.09
software. The potential fragments from previous docking simulations were linked each other, resulting 91
ligands in the process. Furthermore, the docking simulation was conducted again, and we discovered thebest three ligands that have lower Gibbs free binding energy than the standards. Moreover, thepharmacological prediction tests were also done to find the ligand with excellent molecular properties. The
best three ligands from these tests were continued into molecular dynamics simulation. In the end, weconclude that the LEB 31 ligand can be the new drug candidate as EBOV VP35 inhibitor based onmolecular docking, pharmacological prediction test, and molecular dynamic.
Keywords: Fragment-Based Drug Design, Ebola Virus, VP35, Molecular Docking, Pharmacological
Prediction
silico biogenic fragment database. Fragmentbased has been widely used in thepharmaceuticals and biotechnology industry as it
is easy to synthesize and show good results inchemical properties analysis [8]. We used themolecular docking to know the VP35-ligan dinteraction [9]. To docking fragment database,we used MOE 2014.09 software [10]. In thisreseach, we tried to the design a potential VP35
inhibitor using fragment-based drug methods.
We expected the outcome from this study could
provide a promising drugs for Ebola virus
infection.

INTRODUCTION
The Ebola virus (EBOV) is pathogenic, singlestranded RNA virus of Filoviridae family
causing fatal hemorrhagic fever in human andnon-human primates [1],[2]. Ebola virus wasfound in Africa for the first time in 1976. On July
2015, there are 11,268 people deaths from 27,621
cases reported. In Africa, this case is an
epidemic, but Ebola virus may develop andinfected populations in other parts of the world[3].
There are seven codes of protein for EBOVsuch as RNA-polymerase (L), nucleoprotein(NP), glycoprotein (GP), VP24, VP30, VP35 and
VP40 [2]. In this study, we focused on VP35.
Viral protein (VP) 35 is the important host for
EBOV infection that has functions in the filoviral
replication cycle and an essential cofactor of theviral RNA polymerase complex [4]-[6]. The
EBOV VP35 is a potential drug target because it
has the component of the viral RNA polymerase
complex that will hamper the transcription oftype I interferon (IFN) and the production of IFN
will decrease [2],[7]. Initial studies said that thevirus target the RIG-I signal pathway inhibit theactivation of IRF-3 and production of interferonfrom infected cells [6].
Raj et al. (2015) used the flavonoid as an
inhibitor for EBOV [2]. In this study, we
designed EBOV VP35 inhibitor based on in

METHODS
Protein Structure
In this study, we used the three-dimensional
structure of EBOV VP35 with PDB ID: 3FKE [2]that available in Protein Data Bank(http://www.rcsb.org/pdb).
Beforeproteinpreparation process, the water molecules were
removed [11]. We used MOE 2014.09 tominimized and optimized the 3D structure ofprotein [10].

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

Construction of Fragment Database

RESULT AND DISCUSSION

Biogenic
compounds database were
downloaded from ZINC15 database [8]. All of
the fragment was created based on Rule of Threeand toxicity prediction using Osiris Data Warrior[5]. The energy minimized and partial charge ofboth fragments used the MOE 2014.09 with
MMFF94x as a forcefield [11].

Protein Structure
In this study, we used EBOV VP35 chain A(Fig. 1) as potential protein target because thisprotein has a function to protective immun e
responses to EBOV [13]. This protein has theinteraction with Gln244, one of the key aminoacid residues in the protein [2]. We used LigX in
MOE 2014.09 to prepare the protein with
AMBER 10: EHT as a forcefield.

Molecular Docking of Fragment Databaseand Standart Compound
Three-dimensional structure of standard
ligands were obtained from ChemSpider..
Molecular docking simulation for the standard
and fragment database was performed using
MOE 2014.09 software. We used Triangle
Matcher as placements methods, London dG asscoring function and 30 to 100 times ofplacement retain as parameters. The otherparameters were set according to MOE 2014.09
default parameters with AMBER10: EHT as aforcefield [11].

Fig.1 Structure of EBOV VP35
Fragment Linking

Construction of Fragment Database

Potential fragments were linked in MOE
2014.09 to generated new ligands. These newligands were docked with the EBOV VP35.
Three of new ligands that have low binding
energy were used to the pharmacologicalprediction test.
Analysis of Ligand Interactions
Pharmacological Properties

We got 246.244 compounds from biogenic
database. We used the Rule of Three to reduce
the amount of the compounds to find thepotential fragment in Osiris Data Warrior. Threethings must be followed in Rule of Three: (1)molecules have a mass less than 300Da, (2)molecules has the hydrogen donor, and acceptor
up to three, and (3) the value of clogP is 3 [14].
Toxicity screening could also be used to reduce
the risk of toxicity or metabolic instability [11].
We used mutagenic, tumorigenic, irritant andreproductive prediction as a parameter in Osiris
Data Warrior. We got 6.662 fragments after
toxicity and Rule of Three screening. In thisstudy, we used the chloroquine as a ligand
standard [9], [13]. The energy minimizes, andpartial charges of both fragments were applied
using the MOE 2014.09 with MMFF94x as aforce field.

andThree new ligand and standard ligand wereanalyzed their interaction with the active side of
EBOV VP35. In this study, we used Osiris Data
Warrior, VEGA and Toxtree to predict the druglikeness and the toxicity.
Molecular Dynamics Simulation
In this study, we chose the best three ligands
from molecular docking and pharmacologicalproperties prediction. The heating process was
conducted for ten picoseconds (ps) at 300 K and
312 K in the first step. After that, equilibriu m
step simulation was conducted for 100 ps at 312
K and production in 20000 ps at 312 K. For thelast step, cooling simulation is conducted in 10
ps at 300 K [12]. The result for this simulation
was analyzed.

Molecular Docking and Linking Process
Molecular docking is the way to predict theposition, orientation, and conformation of theprotein target binding the ligand [15]. We used
the MOE 2014.09 to performed moleculardocking of 6.662 fragments into the active site of
VP35. We docked 6.662 fragments towards
VP35.
After docking, we search two potential
candidates of the fragment for the linker.
Fragment 1 is the fragment that has interaction

46

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

value of ∆Gbinding , but the RMSD score is higher
than 2.0 Å in LEB 31 (3.26920 Å). In general, adocking pose would be acceptable if the value of
RMSD that generated during the docking
simulation is lower than 2.0 Å [16]. Because ofthis reason, we re-docked the fragment into
rescoring 100, and the result showed that the
RMSD of LEB 31 decrease to 1.0642 Å.
In this step, we found three best ligands thathave potential as a drug for EBOV VP35 basedon the value of ∆Gbinding , inhibition constant(pKi) and RMSD. The ligand with the code LEB
31 is the best ligand that showed the ∆Gbinding 50.5453 kcal/mol with an inhibition constant(pKi) of 36.8215 and RMSD is 1.0642 Å. The
value of ∆Gbinding , inhibition constant (pKi) and
RMSD of the three best ligands and standard
ligands that used in our work showed in Table 1.

with Gln244 residue [2]. Fragment 1 has the root
mean square deviation (RMSD) 1.4186 Å (Fig.
2). Fragment 2 is another ligand that not overlap
with fragment 1. Fragment 2 has the value of
RMSD 1.5146 Å (Fig. 3). Interaction of key
amino acid residues and ligands is important toinhibiting the protein activity.

Pharmacological Analysis
The toxicity and drug-likeness analysis of thebest ligands were performed using Osiris Data
Warrior, VEGA and Toxtree [17], [18]. The
parameter of toxicity like as mutagenic,
tumorigenic, toxicity and irritant was predictedusing Osiris Data Warrior, while development or
reproductive toxicity using VEGA and potential
S. typhimurium TA100 mutagen and potential
carcinogen using Toxtree (Table 2). In Table 2.,
chloroquine as standard ligand shows that it has
a high mutagenic and irritant than another ligand
when using Osiris Data Warrior in toxicity test.
Toxicity prediction test using VEGA and Toxtree
show that all of the ligands have not toxicity
properties in three parameters.
The bioavailability properties prediction
based on Lipinski and Veber rules such as
rotatable bonds, clogP, hydrogen bond donor andacceptor and also the polar surface area. These
parameter was determined using Osiris Data
Warrior (Table 3).
Table 3. show that all of ligands give thegood result based on Lipinski rules: the value of
clogP less than 5, have five hydrogen donors andten hydrogen acceptors and also Veber rules: (1)ligand have a number of rotatable bonds no morethan 10 and (2) polar surface area equal or lessthan 140 Å [19].

Fig. 2 The interaction between Fragment 1 withthe binding site of EBOV VP35

Fig. 3 The interaction between Fragment 2 with
EBOV VP35 at its active site
We linked two fragments using Link Multiple
Fragments feature in MOE 2014.09 to generated
higher affinity binding compounds that haveinteraction with the active site of VP35. We got
91 ligands as result of linked, and then we docked
these ligands. After docking simulation withrescoring 30, we found ligands with the low

47

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

Table 1. ∆G energy, pKi, and RMSD value from the selected linked compounds and standard ligands

2
1
ΔG (kcal/mol)

pKi

RMSD (Å)-50.5453

36.8215

1.0642

LEB 39-47.8037

34.8243

1.3152

LEB 89-47.4118

34.5388

1.5913

Ligands

LinkerLEB 31*Chloroquine-29.021221.1415
1.9169Note: * Standard Ligand; the blue circle in linker is linking with the blue circle in fragment 1 while thered circle is linking with the red circle in another fragment.
Table 2. Toxicity test using Osiris Data Warrior, VEGA and Toxtree
Mutagenic

Parameters
Tumorigenic Irritant

Toxicity

Developmental/Reproductive
Toxicity

None
None
None
None

NO
NO
NO
NO

Ligands

LEB 31None
LEB 39None
LEB 89None*ChloroquineHigh*
Note: Standard Ligand

None
None
None
None

None
None
None
High

Potential S.
typhimurium
TA100
mutagen
NO
NO
NO
NO

Potential
carcinogen

Table 3. The molecular properties using Osiris DataWarrior
Parameters
Ligands

Molecular
WeightLEB 31495.594
LEB 39497.586
LEB 89495.641*Chloroquine
321.894
Note: *Standard Ligand

Numberof HDonor
3
3
3
1

Number of
H-Acceptor

cLog P

82
7
30.6552
1.08682.44324.2018Polar
SurfaceArea
111.33120.56134.5328.16

Number of
Rotatable
bonds
9
9
10
8

protein target. The result shows that some of theamino acid residues in molecular docking arealso found in molecular dynamics. This result
indicated the complex ligan-protein is quit stable.
RMSD score is also the parameter that show thestability of protein-ligand interaction because theMolecular Dynamics Simulation
The best three ligands was analyzed withmolecular dynamics simulation to observe
protein-ligand complex stability. Table 4.
showed the amino acid residues that interact with

48

NO
NO
NO
NO

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

distance of the particular atom in the complex
can indicate from this value. Protein-ligand
complex is stable when the changes in the valueof RMSD does not exceed 3 Å in a reach of 1

nanosecond (ns) [12]. In Fig.4, all of the ligands
have RMSD low than 3 Å. LEB 31 is the moststable than another ligand and standard.

Table 4. Amino acid residues based on molecular docking and dynamics simulation
LigandMolecular
docking

LEB 31
Q241, Q244, K248,
K251, R225, A221,
W229, K222, F235,
P304

LEB 39H240, K248, Q244,
G236, F235, K251,
C247, K222, A221,
N226, R225, Y229

LEB 89
K248, Q244, F235,
R225, N226, Y229,
A221, K222,
K251,C247

Chloroquine
R225, Q241, Q244,
V245, I295, K248,
P293, L249, Vl294

P239, Q244, K251,
K248, Q244, Q241,
R225, A221, L249,
F328, I295, D302, P304, K248, PP293, H296,
Q241, K248,
R225, A221, K222,
I295, L249, V249
I295,V249
K251
Note: amino acid residues in red color are the residues found in the binding site of protein . Residues in bold
font are the residues that can be found in molecular docking and dynamics simulation.

Molecular
dynamics

K222, R225, Q244,
A221, K251, K248,
Cs247

3

RMSD (Å)

2.5

2
LEB31
LEB39
LEB89
Chloroquine

1.5

1
0.5
0

0

5000

10000
15000
20000
Time (ps)Fig. 4 Graph of RMSD (Å) Vs time (ps)25000

through Hibah Publikasi Internasional Terindeks
Untuk Tugas Akhir Mahasiswa (PITTA) No:
693/UN2.R3.1/HKP.05.00/ 2017. Usman Sumo
Friend Tambunan supervised this study, while
Atika Marnolia and Erwin Prasetya Toepak did
the experimental and wrote the manuscript. We
also would like to thank Mr. Mochammad Arfin
Fardiansyah Nasution for helping proofread thispaper.

Conclusion
In this research, we constructed fragment
database and docked it into the active site of
VP35. After docked, we linked the two potential
fragment and then docked again with VP35. We
obtained 91 ligands from this fragment linking
process. In the next step of the study, we used
three best ligands from molecular docking
simulation to analyzed in molecular dynamics
simulation. In generally, all of the ligands showed
the good pharmacological properties and gave thevalue of RMSD lower than 3 Å in molecular
dynamics. Among all ligands, LEB 31 is the best
inhibitor based on result of molecular docking,pharmacological properties prediction, andmolecular dynamics simulation.

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Acknowledgements[2]This research has been supported and funded
by Directorate of Research and Communit yEngagement (DRPM) Universitas Indonesia

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profile and identify potential therapeutictargets of fusarochromanone, a novelanti-cancer agent.,” silico Pharmacol.,vol. 3, no. 1, p. 6, 2015.
S. J. Enoch, M. Hewitt, M. T. D. Cronin,
S. Azam, and J. C. Madden,“Classification of chemicals according tomechanism of aquatic toxicity: An
evaluation of the implementation of the
VerhaarschemeinToxtree,”
Chemosphere, vol. 73, no. 3, pp. 243–
248, 2008.
D. F. Veber, S. R. Johnson, H. Cheng, B.
R. Smith, K. W. Ward, and K. D.
Kopple, “Molecular Properties That
Influence the Oral Bioavailability ofDrug Candidates,” pp. 2615–2623, 2002.

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

DEVELOPMENT OF SPECIFIC ELECTROCHEMICAL BIOSENSORBASED ON CHITOSAN MODIFIED SCREEN PRINTED CARBON
ELECTRODE FOR THE MONITORING OF CAPTAN FUNGICIDE
1

Porntip Wongkaew1*, Buddhapala Wongkaew2, Suwita Saepaisan3, and Panupong Thanutong4
Division of Plant Pathology, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand;
2

Metropolitan Waterworks Authority, Bangkok 10210, Thailand.
ABSTRACT
Harmful chemicals predominantly used in modern agriculture for pest control have raised a longterm accumulation in environment and serious problems concerning food safety and health. Excellent detection
tools for environmental monitoring are thus urgently needed. The recent biosensor technology is proposed tofulfill this purpose. In this study, an expedient biosensor for captan fungicide determination has been fabricatedusing its specific reacting enzyme glutathione-s-transferase (GST) covalently immobilized on natural biopolymer
chitosan (Chi). The screen printed carbon electrode (SPCE) has been selected as a basal platform for thebiosensor development. Modification of SPCE was made by self-assembled deposition of 1% chitosan in 1%
acetic acid solution onto the basal SPCE. Progressive characteristics of the assembled SPCE-Chi-GST have beenclearly approved by atomic force microscopy, impedance spectroscopy and cyclic voltammetry (CV). Twosequential oxidation peak currents were arisen in the electrochemical behavior analysis of captan in the presenceof GST substrate electrolyte solution by CV and linear sweep voltammetry (LSV). Dose response to various
captan concentrations was investigated in the range 0 – 20 µg/ml by LSV and a similar good linear relationshipbetween peak current and concentration of captan could be obtained by both oxidation steps with the limit ofdetection (LOD) at 0.2 µg/ml. Thus the sensitive, rapid, inexpensive and miniature quantitative system forcaptan monitoring could now be successfully achieved by this proposed biosensor.
Keywords: Electrochemical biosensor · Screen printed electrode · Captan · Chitosan · Glutathione-stransferase · Voltammetryelectrophilic substrates via glutathione (GSH)
conjugation. This principal role of GST in
xenobiotic-GSH conjugation especially in thereaction with transient thiophosgene to form a
product thiazolidine‐2‐thione‐4‐carboxylic acid
(TTCA) thus has been considered as a basis forcaptan determination using high performance liquid
chromatography (HPLC), in coupled with mass
spectrometry (MS) but these systems are very
sophisticated, highly expensive, laborious and timeconsuming. Electrochemical sensor using enzyme
reaction is one among advanced effective tools
alternative to such conventional methods. A fieldbased and in situ environmental monitoring is
expected to handle easily on site with several order
lower cost by this novel approach.
Our previous studies presented an approved
effective and afford able electrochemical implement
by a combination of a screen printed carbon
electrode (SPCE) and biopolymer chitosan [3]. In
this present study, the chitosan modified screen
printed carbon electrode (SPCE-Chi) was employed
for a novel fabrication of GST based biosensor.
Characterization of the prepared electrodes was
carried out using atomic force microscopy (AFM),

INTRODUCTION
The fungicide captan is one of the mostfrequently applied pesticides due to its broad actions.
It has been widely used in a variety of crop
production at every growing stage of plant and invarious industries including household applications.
It is highly toxic to very highly toxic to livestock,
poultry, and fish. The evidence of human cardiotoxic
effects has also been reported in a rare case ofcaptan ingestion by skinny person [1]. Overuse ofcaptan has several drawbacks including pollution inenvironment and water ecosystem electrochemical
technique. The toxicity of captan is primarily due toan inhibitory effect on enzymes and essential amino
compounds production according to several
toxicokinetic studies [2]. In captan metabolism, amajor functional group, trichloromethylthio (SCCl3)
is generally metabolized to the reactive
thiophosgene (S=CCl2) along with a relatively stable
1,2,3,6-tetrahydrophthalimide (THPI) in thepresence of exposed thiol group. While a cellulardetoxification response against this xenobiotic is
activated through an enzyme glutathione-stransferase (GST) that metabolizes a broad range of51

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

electrochemical impedance spectroscopy (EIS), andcyclic voltammetry (CV). Statistics calibration was
subsequently explored by linear sweep voltammetry(LSV) with varying captan concentration. The
present issue also firstly demonstrates catalytic
ability of this SPCE-Chi-GST in the oxidation of
captan that liberated significant two sensing
mechanisms owning to the simultaneous formationof two different electrophillic complexes from a
distinct function of xenobiotic-GSH conjugation.

Electrochemical characterization studies
Electrochemical inspections were done at room
temperature on a 50 l droplet of an electrolyte
solution at the working electrode surface area. A
solution of 0.05 M PBE containing 1.0 mM
K3Fe(CN)6 at pH 6.5 was used as the basal
electrolyte reagent throughout all experiments.
Electrochemical impedance spectroscopy (EIS)
measurements were performed in potentiostatic state
as a single sine wave at a frequency range of 0.01–
105 Hz and a frequency number of 50 with theamplitude of 10 mV and estimated duration of 6
minutes. Cyclic voltammetric (CV) profiles wereobtained over the potential scan range from − 0.6 to+ 0.6 V at a scan rate of 25, 50, 100, 150 and 200
mVs−1. Linear sweep voltammetry (LSV) was
carried out at similar potential scan range at a scanrate of 50 mVs−1.

MATERIALS AND METHODS
Materials and apparatus
Chitosan (85% degree of deacetylation) with amolecular weight of 0.28 kDa was obtained from
Bioline Lab, Co., Thailand. Glutathione-Stransferase from equine liver, glutathione (GSH) andcaptan were purchased from Sigma-Aldrich Co.
LLC, USA. Other chemicals for reagent preparation
were purchased from Ajax Finechem Pty, Ltd.,
Australia. All solutions and reagents were preparedusing high purity deionized water of 18.2 MΩ from
Milli-Q RG system (Millipore Corporation, MA,
USA.). Screen printed carbon electrode DRP-150
was provided by DropSens, ParqueTecnológico de
Asturias, S.L. Llanera (Asturias) Spain. An XE-120
Atomic force microscope (Park Systems Corp.,
Suwon, Korea) was acquired for electrode surface
observation and a PGSTAT 302N ECoChemie
Autolab (Metrohm Autolab B.V., Utrecht, The
Netherlands) was used for electrochemical analyses.
Modification of working electrodefabrication of GST enzyme based biosensor

Enzyme activity determination
The GST enzyme activity was determined inaccordance of an approved procedure [4] using asubstrate solution containing 1 mM reduced GSH
and 1 mM CDNB in 0.05 M PBE at pH 6.5 as anelectrolyte for electrochemical sensing of the
prepared SPCE-Chi-GST biosensor. Standard
calibration of captan was acquired by fortifying
authentic captan at various concentrations ranged
from 0 - 20 g/ml and reacting with the substratesolution by 1:1 ratio. The enzyme sensing activity
was assessed before and after captan accretion withan incubation period of 15 minutes. Inhibition of
enzyme activity was calculated from the rest of
current peak obtained by the equation, Inhibition(%) = ((Ipe – Ipf) / Ipe) × 100, where Ipe and Ipf
represent the peak height current of GSH-CDNB
reaction product on the SPCE-Chi-GST before andafter the addition of captan fungicide, respectively.

andModification of working electrode was
performed by self assembled deposition of chitosan
onto a SPCE as previously developed [3].
Fabrication of the enzyme biosensor was executed
following an immobilization of GST enzyme (3 U)
on SPCE-Chi via theincorporation of
glutaraldehyde covalent attachment to ensure thestability of GST as previously described [4].

RESULTS AND DISCUSSION
Morphological characteristics of the preparedelectrode working surfaces

Atomic force microscopic observation
The surface morphology of each working
electrode type could be manifested directly by their
topographic inspection under atomic force
microscope. Typical AFM images in three
dimensions from the nanoscale surface scanning are
as shown in Fig. 1 which representing the original
SPCE in image A, the chitosan modified electrode(SPCE-Chi) in image B and the SPCE-Chi that was
immobilized with GST enzyme (SPCE-Chi-GST) in
image C. It appears that the chitosan nanoparticle
layer is thoroughly covered onto SPCE basement
upon this surface modification (Fig. 1B). On theMorphological characteristics at nanoscale oforiginal SPCE, SPCE-Chi and SPCE-Chi-GST
working surfaces were allocated by a true noncontact mode AFM with a PPP-NCHR siliconcantilever of < 10 nm tip radius baring a spring
constant of 42 N/m force constant and 320 kHz
resonant frequency (Nanosensors TM, Neuchâtel,Switzerland). Inspection of the surface profile wascarried out on an x-y accessible 1×1 μm area at 0.5
Hz scan rate with XEP and XEI software for dataacquisition and image processing.
52

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

other hand, a prominent distinction can be realized
followingtheelectrodeworkingsurfacetransformation and a conspicuous layer of the GST
enzyme bound to the surface after immobilization
was apparently formed as shown in image C in Fig.
1. Therefore a successful immobilization of GST
enzyme can be stated according to thesecircumstantiated images.

probably informs the presence of a barrier that
resulted from negative charges repulsion of the
enzymewhich
retardedtheelectrolyte[K3Fe(CN)6]3−/4− redox action and detained the ion
charges associated to a successful GST
immobilization on SPCE-Chi surface.

Fig. 2 Impedance spectra of SPCE, SPCE-Chi and
SPCE-Chi-GST revealed by nyquist plots(A) and the enlarge view (B).

Fig. 1 Three-dimensional AFM surface micrographs
at nanoscale of (A) original bare SPCE, (B)
SPCE-Chi, and (C) SPCE-Chi-GST

Cyclic votammetric characterization
Electrochemical impedance spectroscopy (EIS)
Typical peak curve of the reductive and reverse
oxidative current vs. electrode potential indicating
ideal reversible reaction governed by freely
diffusion of Fe+3/Fe+2 to the planar surface wasgained in each electrode at about 0.09 to 0.21 V withthe peak separation around 0.1 V at 100 mV s-1 scanrate and a potential window of −0.6 to 0.6 V asshown in Fig. 3. The oxidation/reduction peakcurrents of SPCE-Chi and SPCE-Chi-GST were
almost 2-3 times bigger than that of original bare
SPCE (curve a) as a successive superb improvement
in electroactive response due to the surface
furnishing by an enriched cationic chitosan
biopolymer [6, 7]. A high rate of electron transfer
process was thus accelerated via this highly
conductive chitosan composing as demonstrated by
the curve b for SPCE-Chi and curve c for SPCEChi-GST. Even though a bit smaller peak current
curves were appeared due to a small electrontransfer deducted by subsequent GST enzyme
immobilization stepwise. Graphical plots in Fig. 4
illustrate the representative cyclic voltammogram ofan electrochemical responding to scan rate effectincluding their linear regression relationship from
SPCE-Chi-GST that implies for good diffusion
effect.
The results from cyclic voltammetry on theconfirmation of self assembled layers were inagreement with those from EIS that inferred anefficient electrochemical catalytic activity after the
stepwise preparation. Therefore this prepared SPCEChi-GST is capable to use for the further study on
captan detection.

An EIS assay is exploited to estimate theelectrocatalytic properties of original bare SPCE,
SPCE-Chi and SPCE-Chi-GST as shown in Fig. 2A
with an enlarge view of them at high frequency
region in Fig. 2B. The spectral character of each
could be obviously distinguished and thus signifies
the alteration upon stepwise manipulation according
to the assumption of Warburg impedance for a semiinfinite diffusion on smooth surface [5]. In thisfigure, a broad semicircle at high frequency range
has been arisen in the spectra of SPCE as typicalcharacteristic for a high electron transfer resistance.
Notable plot from SPCE-Chi is evident by its almost
straight line which indicates an extremely fastelectron transfer phenomenon due to numerous
positive charges holding quality of the chitosan.
While a distinct small semicircle has derived in the
spectrum of SPCE-Chi-GST which implied for adeceleration of electron transfer after GST
immobilization. The reference impedance modelusing a modified Randles equivalent circuit in thisrelationship can be written as Rs(Cdl(Rct(W)))
where Rs is the cell resistance, Rct is the chargetransfer resistance, Cdl is double-layer capacitanceand W is the Warburg element. The charge transfer
resistance (Rct) values could be approximated 4,697,
395 and 483 Ωcm-2 for bare SPCE, SPCE-Chi and
SPCE-Chi-GST, respectively. It seems that the Rctof SPCE-Chi appears to decrease down to almost 12
folds in corresponding to an expedite activity of the
Fe3+/Fe2+ redox couple by the influence of chitosan
assembly onto the original SPCE surface. A bit
raised up in Rct value than the basal SPCE-Chi has
been observed after an immobilization of GST
enzyme to make the SPCE-Chi-GST. This incidence53

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

reduction peaks as seen in Fig. 5 curve d, suggestinga differentiation due to captan catalytic reaction in
the system. The first oxidation peak at Epa of 0.12 V
and the second oxidation peak at Epa of 0.27
altogether with the other two prominent reduction
peaks at Epc of -0.078 V and 0.145V were emerged.

Fig. 3Cyclic voltammograms of (a) bare SPCE,(b) SPCE-Chi and (c) SPCE-Chi-GST in
Fe3+/Fe2+ redox probe at 100 mV s-1 scanrate.

Fig. 5

Fig. 4Cyclic voltammograms of SPCE-Chi-GST
in Fe3+/Fe2+ probe accounted by curves
from inner to outer corresponding to 25, 50,
100, 150 and 200 m∙Vs−1 scan rates,
respectively, with their coordinate linear
relationship of anodic and cathodic peakcurrent vs. square root of scan rate on theright plots.

Cyclic voltammograms at 100 mV s-1 scanrate of (a) bare SPCE, (b) SPCE-Chi-GST,(c) SPCE-Chi-GST in 0.1 M PBE (pH 6.5)
containing 1.0 mM [K3Fe(CN)6]3−/4− with 1
mM reduced GSH and 1 mM CDNB
analysis buffer as a blank GST enzyme
substrate; and of (d) SPCE-Chi-GST in 2.5
g/ml captan included analysis buffer.

The effect of scan rate on the peak currents andthe peak potentials in the presence of captan by the
GST immobilized electrodes is illustrated in Fig. 6.
A linear relationship between the peak currents andsquare root of the scan rates with the correlation
coefficient R2 around 0.99 of each could be assumed
as an evidence for diffusion controlled process.
According to the postulation of captan reaction
mechanism [2, 9], this fungicide reacts extremely
rapidly with thiol-containing compounds such as
glutathione to produce THPI (1,2,3,6-tetrahydrophthalimide) and reactive thiophosgene by theequation:
Captan + GSH → Thiophosgene + THPI +HCl. The
thiophosgene immediately undergoes further
reaction by GST catalysis to form thiazolidine-GSH
complex that is spontaneously transformed to anelectroactive
thiazolidine
ringcompound,thiazolidine-2-thione-4-carboxylic acid (TTCA).
The last oxidation step is proposed by the equation:

Electrochemical sensing mechanisms of SPCEChi-GST
The CV profiles of the GST immobilizedworking electrode, SPCE-Chi-GST, as well as theircorresponding bare SPCE and SPCE-Chi were
gained in the absence and presence of 2.5 g/ml
captan in 0.1 M PBE (pH 6.5) containing 1.0 mM[K3Fe(CN)6]3−/4− with 1 mM reduced GSH and 1
mM CDNB as analytic substrate buffer with scanrate of 100 mV s−1 as shown in Fig. 5. In the sole
substrate buffer, almost obvious one oxidation and
one reduction charging current peaks were appearedat Epa of 0.27 V and Epc of 0.16 V owning to the
traditional GSH-CDNB conjugation reaction by
GST catalysis [8] that can be summarized as

𝐺𝑆𝑇

Thiophosgene + GSH → TTCA+2HCl.
Considering the GSH oxidation catalysed by GST,
the two separated oxidation peaks emergence
following the CV measurement in the presence of
captan altogether with universal substrate CDNB
thus could be presumed as the occurrence of two
different xenobiotic-GSH conjugation complexes
from the reaction of GSH with thiophosgene
intermediate of captan at the Epa of 0.12 V and fromthe reaction of GSH with CDNB at the Epa of 0.27 V.

𝐺𝑆𝑇

CDNB + GSH → GS-DNB + HCl . The peakseparation between them was about 0.1 V indicating
profuse diffusion behaviour of the analytic substrate
toward the electrode surfaces (Fig. 5 curve a-c). An
explicit CV current response was generated in thepresence of captan containing analysis buffer in
SPCE-Chi-GST with two oxidation and two
54

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

Fig. 6

0.071𝑥 with R2 = 0.984 for the second range, wherey represents the peak current in e-5 ampere (A) and x
represents the captan concentration in µg/ml as seenin Fig 8A segment p1a and p1b. The detection limit(LOD) for captan in this case is estimated to be
0.225µg/ml based on the formula: LOD = 3S/b
where S is the blank standard deviation (n=15) and b
is the slope of the regression. In case of the p2
currents, their two linear regression equations are
𝑦 = 5.066 − 1.205𝑥 with R2 = 0.995 in the ranges
0-1.25µg/ml and 𝑦 = 2.492 − 0.102𝑥 with R2 =0.977 in the ranges 2.5-15µg/ml. The LOD of
0.198µg/ml can be acquired in this p2 current case.
Notable differences between the slopes of thecalibration plots from the first range and the second
range of captan concentrations in both p1 and p2
currents are probably due to kinetic limitation at theconfine electrode surfaces. The slope obtained fromthe first concentration range is apparently higher
because the active sites number containing on theworking surface still be excess in relation to the total
number of lower analyte molecules. Statisticalanalysis between the p1 and p2 current
measurements has yielded the value of texp at 0.69
and Fexp at 1.03 in comparison to the null hypothesis
student t-test of 1.96 critical value and F-test of 1.00
critical value (n = 16) at 95% confidence level. As
the texp value was lower than the student t-test criticalvalue hence their population means are notsignificantly different. This result also showed an
accuracy of the system. While the Fexp gained wasaround the Fcritical that should be considered
acceptable for the null hypothesis in the population
variance. Therefore both the p1 and p2 current
delivery cases could be similarly accepted.

Cyclic voltammograms of SPCE-Chi-GST
in analysis buffer containing 2.5 g/ml
captan accounted by curves from inner toouter corresponding to 25, 50, 100, 150 and
200 m∙Vs−1 scan rates, respectively, withthe coordinate linear relationship of their
two anodic (Ipa1 and Ipa2) and two
cathodic peak (Ipc1 and Ipc2) currents vs.
square root of scan rate.

Linear detection range of captan
Linear sweep voltammetry (LSV) method was
employed to determine the sensing performance of
SPCE-Chi-GST and the resulting voltammograms
were recorded at 0 up to 20 µg/ml captan
concentration in 0.1 M PBE (pH 6.5) containing 1.0
mM [K3Fe(CN)6]3−/4− with 1 mM reduced GSH and1 mM CDNB. Similar electrochemical behaviour to
the CV profile was arisen by the appearance of two
step oxidation peaks around the potential position
0.04 to 0.12 V for the first peak that continued
growing and around 0.2 to 0.27 V for the second
peak that continued decreasing in the presence ofvarying up captan concentrations as shown in Fig. 7.
As the first peak currents or peak 1 (p1) gradually
increased with an increase of captan concentration,
this behaviour could be assumed as a result from thereaction of GSH with thiophosgene intermediate ofcaptan. While the response in the second peakcurrents or peak 2 (p2) were gradually decreased bytypical reaction of GST inhibition.
Calibration plot and detection limit were thus
comparatively calculated from either p1 or p2
current against captan concentration. Fig. 8
demonstrates a linear relationship between thecurrent response of SPCE-Chi-GST and captan
concentration in two dynamic ranges of 0-1.25µg/ml
and 2.5-15µg/ml in both cases. The growing p1
currents gradually increased with an increase incaptan concentration and the linear regression
equations can be expressed as 𝑦 = 1.613 + 0.99𝑥
with R2 = 0.974 for the first range, and 𝑦 = 2.93 +Fig. 7

LSV performance of SPCE-Chi-GST withsimultaneous peak 1 (p1) and peak 2 (p2)currents corresponding to different captan
concentrations.

The detection range in every regression
performance is comparably more competent than theprevious reports based on GST activity that werecarried through 0.25 to 16 ppm using
aminopropyltriethoxysilane-modified gold electrode[4] and 0 to 2 ppm using optical biosensor system
55

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

University’s Division of Research and Technology
Transfer Affair for partial funding to both individual
and research group (KKU-56-57) and the KKU
Research Instrument Center for instrument facilities.

[10]. These repetitive measurement series withdifferent concentrations of captan in all cases gave acorrelation coefficient over 0.9 and a relative
standard deviation within 3% (n =30), thus
demonstrating a high reliability and good
repeatability of the measurements including a

REFERENCES[1] Gottzein AK, Musshoff F, Madea B,“Systematic toxicological analysis revealing arare case of captan ingestion”, J. of Forensic
Sciences, Vol. 58, Jul. 2013, pp. 1099-1103.
[2] Gordon EB, “Captan and folpet”, Handbook of
Pesticide Toxicology, Krieger RI, Ed. New
York: Elsevier, 2010, pp. 1915–1949.
[3] Wongkaew P, Poosittisak S, “Atomic force
microscopic
andelectrochemical
characterization of the modified screen printed
carbon electrode by self assembled depositionof chitosan and activated carbon”, Int. J. of
GEOMATE,Vol. 11, Aug. 2016, pp. 2356-2362.
[4] Singh RP, Kim YJ, Oh BK, Choi JW,“Glutathione-s-transferase
basedelectrochemical biosensor for the detection of
captan”, Electrochemistry Communications,Vol. 11, Jan. 2009, pp.181–185.
[5] Orazem ME, Tribollet B, Electrochemical
Impedance Spectroscopy. New York:Wiley,2008, pp. 1-459.
[6] Wongkaew P, Poosittisak S, “Electro-affinity of
SCWL-dsDNA on different high deacetylation
degree chitosans deposited glassy carbon
electrode”, Advances in Developing Affordable
In-Vitro Molecular Diagnostics, Puri CP, Abidi
N, Bhanushali, P, Pere A, Gupta SK, Eds.
Mumbai: Yashraj Research Foundation, 2012,
pp. 249-258.
[7] Wongkaew P, Poosittisak S, “Diagnosis ofsugarcane white leaf disease using the highly
sensitiveDNA
based
voltammetricelectrochemical determination” Amer. J. of
Plant Sciences, Vol.5, Jul. 2014, pp. 2256-2268.
[8] Van der Aar EM, de Groot MJ, Bouwman T,
Bijloo GJ, Commandeur JN, Vermeulen NP. “4Substituted 1-chloro-2-nitrobenzenes: structureactivity relationships and extension of thesubstrate model of rat glutathione S-transferase
4-4”, Chem. Res. of Toxicology, Vol. 10, Apr.
1997, pp. 439-449.
[9] Wolfe NL, Zepp RG, Doster JC, Hollis
RC,“Captan hydrolysis”, J. of Agricultural andFood Chemistry, Vol. 24, May 1976, pp. 1041–
1045.
[10] Choi JW, Kim YK, Oh BK, Song SY, Lee WH,“Optical biosensor for simultaneous detection of
captan and organophosphorus compounds”,
Biosensors and Bioelectronics, Vol. 18, May,
2003, pp. 591-597.

reproducibility of the SPCE-Chi-GST fabrication.
Fig. 8Linear regression relationships from LSV
performance of SPCE-Chi-GST between
peak 1 current (A) vs. captan concentration
ranged from 0-1.25µg/ml (p1a), and from
2.5-15µg/ml (p1b); and between peak 2
current (B) vs. the range from 0-1.25µg/ml(p2a), and from 2.5-15µg/ml (p2b).

CONCLUSION
In this present study, a facile electrochemical
biosensor has been developed based on themodification of SPCE with chitosan andimmobilization of GST enzyme for specific andpractical monitoring of captan fungicide. Twosensing mechanisms from this system has been
proposed with reference to an occurrence of two
simultaneous oxidation peak occurrences in CV and
LSV analyses by the formation of two different
xenobiotic-GSH conjugation complexes in thereaction system. Quantitative measurements werecarried out by their converse concomitance, the peak
1 growing current and the peak 2 decreasing current.
A good progressive linear relationship between peakcurrent and captan concentration could be seen inboth cases with the LOD around 0.2 µg/ml. All
calibrations were attested to be high reliability andreproducibility with the RSD lower than 3% and thecorrelation coefficient above 0.9. Therefore thedetection and quantification of captan are enabled by
newly proposed peak 1 current as well as the
traditional peak2 current providing suitableconfirmation of the gaining results in parallel.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge Khon Kaen

56

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

A BASIC STUDY ON FLUID PREDICTION OF MORTARWITH VARIOUS POWDERS
1

Yuki takagi1, Koji Takasu2, Hidehiro Koyamada3 and Hiroki Suyama4
The University of Kitakyushu Graduate School of Environmental Engineering, Japan
2
The University of Kitakyushu Faculty of Environmental Engineering, Japan
ABSTRACTIn the field of concrete, Fly ash and crushed stone powder which are by-product powders and limes stone
powder are used as admixture materials for concrete from the viewpoint of environmental load. Then we should
use by-product powders as materials of the concrete as a substitute of fine aggregate. Therefore it is necessary to
predict fluidity of the concrete with powders in large quantities. In this study, we tried a fluid evaluation ofmortar with various by-products powders and a fluid prediction by grasping a fluid tendency of mortar withvarious powders as a part of fine aggregate, and adopted the thickness of a surplus water film theory and therelative flow area ratio as an evaluation index. We clarified when used by-product powders as a part of fineaggregate, we can use excess water film for an index. But the value of the relative flow area ratio was different
because of the same thickness of a surplus water film depending on the kind of the powder. It was thought thatthe fluidity of mortar was able to predict by applying the correction value proposed by this study in various
mixtures that used the by-product powder.
Keywords: Excess Water Film Thickness, Fresh Properties, Fly Ash, Crashed Stone Sand
(m3/mortar m3), “ G ” is solid content in aggregate of
the thing which mixed fine aggregate with powders(%), “ Gs ” is the volume of powders and fineaggregate ratio in the mortar volume (%), “ Sp ” issurface area of powders in mortar 1m3 (cm2/m3), “ Ss ”
is surface area of fine aggregates in mortar 1m3(m2/m3), “  ” is excess water film thickness (µm).
Further, in order to eliminate the influence ofparticle size distribution, Miyake et al. performed
analyses with a dimensionless value δ/d, where δ isfound from the excess water film and d is the volumesurface average particle size of the solid. The
calculation of δ/d is described below.

INTRODUCTION
In late years, measures to depletion of natural
resources and realization of the low-carbon society
are problems in the field of Japanese concrete. So thetechnique that using by-products powders such as fly
ash and crush stone powder or the limestone fine
powder as a concrete material is considered assolution to these problems. Therefore a fluid
evaluation and prediction of the concrete using byproduct powders are required. In this study, We
confirm a fluid tendency of mortar which mixed
several kinds of powders as a substitute for fineaggregate and evaluated fluidity using excess water
film thickness (δ) and the relative flow area ratio
(Γ) .

Acs 

EXCESS WATER FILM THICKNESS∴ d  6  10 
4

In this study, excess water thickness was used as anindex to show how the composition of mortar andbyproduct-based powders influences fluidity. The
excess water theory of Miyake et al.1) used in thisstudy considers the liquid phase as water and the solid
phase as powder and fine aggregate; the correlation
with liquidity was reported, assuming that the excesswater forms a uniform water film on each particle.
The following formula proposed by Miyake et al.2)
was used to calculate the thickness of the excess water
film.
(1)
Wexc  102  (G  Gs )

  10 4 

Wexc
G  Gs 108 Sp  Ss
Sp  Ss

Sp  Ss 6   (106  d ) 2 (106  d )3
102  Gs
Gs
Sp  Ss(3)

Refer to “ Acs ” is mean ratio surface area of
cement and fine aggregate per volume (cm2/m3), “d”
is average particle size of cement and fine aggregate(µm).
It is expressed by equation (4) by dividing equation(2) in equation (3)dG  Gs6  Gs(4)

I found the ratio surface area of fine aggregate in
the following equations.

Ssu  6  (2)Refer to “ Wexc ”is excess quantity of waterXi
100  ai

(5)

Refer to “ Ssu ” is the ratio surface area of fine57

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

aggregate (mm2/mm3), “ X i ” is Capacity percentage

the notation method of the compounding sign, "FA""LP" "CSP" shows a use powders name followed by
the written number shows a substitution rate.
In addition, the "S" "CS" of the end expresses sandname which I used, and the number of the end of thestandard compounding expresses a water cement ratio.
"P" in the compounding list means powders, and"W/P" expresses water powders mass ratio. I worked
it out using a mortar mixer and mixed mortar. I
measured a mortar flow and mini-slump, the solid
content in aggregate of the thing which mixed fineaggregate with powders. For deriving the solid
content concentration in the mixture, a steel mortar
form (⌀50 mm, height 100 mm) was filled with thebetween sieve opening l i and l i 1 (%), “ a i ” isaverage particle size by the geometric mean between
sieve opening l i and l i 1 (mm)  (li  li 1 ) 0.5 .
THE RELATIVE FLOW AREA RATIOThe relative flow area ratio (Γ) is a thing used for aself-filling-related index, and fluidity is high so that avalue is big.
2(d1  d 2  d 0 )
2
d0

(6)

Refer to “ d 0 ” is the inside diameter of the lower

Table1: Used materials

flow corn, “ d1 and d 2 ” is I do it with the value thatmeasured the direction that is a right angle in greatest
dimension and that of mortar after the transformation.

Item

Type

Properties

Mark

CementOrdinary portland cement

Water

Tap water

Density3.16g/cm3-

W

SUMMARY OF THE EXPERIMENT

Density2.43g/cm3
Ignition loss1.67%

Fly ash(JIS Ⅱclass)

Used materials showed in table 1. I used fly ash of
the prescribed II class equivalency for JIS A 6201,
crush stone powder of the prescribed for JIS A 5041,
crash sand of the prescribed for JIS A 5005. In
addition, I kept it more than 24 hours and used thesematerials for a constant temperature room of 20
degrees Celsius.
Compounding showed in table 2. The admixturefree mixes NS and N-CS were the standard
formulations, and the three byproduct components—
fly ash powder, limestone fine powder, and crushedstone powder—mixed to a concentration of 5, 7.5, 10
or 15% by volume were used as partial replacementof fine aggregate. In the experiment, mixing was
carried out with the formulation in Table 2. The CSPs
10 and 15 are excluded from the formulation tablebecause they could not be mixed with either sea sandor crushed sand. In contrast, FA/LP15-CS, which was
also impossible to mix, is listed in the formulationtable because it could be mixed with sea sand. As for

Admixture

Blain's specificsurfacearea4270cm2/g

Blain's specificsurfacearea2975cm2/g

N-S30
N-S40
N-S50
N-S(CS)60
N-S70
FA5-S(CS)FA7.5-S(CS)FA10-S(CS)FA15-S(CS)
LP5-S(CS)LP7.5-S(CS)
LP10-S(CS)
LP15-S(CS)CSP5-S(CS)
CSP7.5-S(CS)

(%)
30
40
50
60
70
60
60
60
60
60
60
60
60
60
60

(%)
30
40
50
60
70
43
37
33
27
41
35
31
25
41
36

W
280
280
280
280
280
269
264
259
250
269
264
259
250
269
264

C
934
701
560
467
400
449
440
432
416
449
440
432
416
449
440

FA
0
0
0
0
0
182
267
350
505
0
0
0
0
0
0

LP
0
0
0
0
0
0
0
0
0
207
305
399
576
0
0

CSP
0
0
0
0
0
0
0
0
0
0
0
0
0
206
303

LP

Density2.70g/cm3

Crush stone powder

Blain's specificsurfacearea4624cm2/g

CSP

Surface dry
density2.59g/cm3
Water absorption0.76%

Sea sandBlain's specificSsurfacearea55.9cm2 /g
Fineness modulus2.4
Solid content61.5％

Fine
aggregate

Surface dry
density2.66g/cm3
Water absorption1.96%
Crush Sand

Blain's specificsurfacearea33.6cm2 /g
Fineness modulus3.1
Solid content57.1％

Unit content(kg/m3 )W/C W/PFA

Density2.74g/cm3
Limestone powder

Table2: Mix proportions and Experimental
SymbolC

S (CS)
917
1109
1223
1300(1360)
1355
1157(1211)
1090(1140)
1025(1072)
902(944)1157(1211)
1090(1140)
1025(1072)
902(944)1157(1211)
1090(1140)

58

G(%)

Gs(%)

δ(µm)

Flow(mm)mini-slump
Ms(cm)

70.7
75.8
76.7
77.9（78.2）
75.9
75.2（74.1）
74.2（73.8）
72（73.4）
71.3
73.4（73.4）
72.6（71.0）
70.7（69.1）
70.6
74.4（75.3）
74.3（73.8）

65.0
65.0
65.0
65(65)
65.0
66.4(66.4)
67(67)
67.6(67.6)
68.8
66.4(66.4)
67(67)
67.6(67.6)
68.8
66.4(66.4)
67(67)

0.18
0.45
0.60
0.79(0.82)
0.77
0.38(0.33)
0.27(0.26)
0.15(0.19)
0.07
0.32(0.32)
0.23(0.17)
0.12(0.06)
0.06
0.32
0.25

142
185
189
190(189)192
204(183)
176(154)
180(152)
175
184(167)
166(163)150(142)
121
153
119

1.9
6.2
7.6
7.3(7.7)
6
10(6.2)6(3.2)
5.7(3.2)
6.6
4.8(3.6)
3.4(3.1)
1.7(2.0)
0.4
2.7(2.0)
0.6(0.6)

CS

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

RESULT AND CONSIDERATION
Excess water film thickness and fluidity

3.5

The relative flow area ratio

mix in a mixer and tapped using a flow table of once
per second, and then the volume was derived from thesinking depth of the material in the container; thisvolume is divided by the container volume to derive
the solid content in aggregate. The number fortapping was set at 500 times on the basis of apreliminary test.

3
2.5
2
1.5

N-S
FA-S
LP-S
CSP-S
N-CS
FA-CS
LP-CS
CSP-CS1
0.5
0From the results of preceding section, it can beinferred that it is difficult to predict fluidity from only
water film thickness when comparing between
processes that use different powders. We consider
whether it is possible to predict the fluidity using
water film thickness by applying a correction value
for each powder, assuming that the way the uniqueproperties of each powder influences fluidity can beevaluated from its water film thickness. To do so, weneed an intermediary indicator that correlates withboth water film thickness and relative flow area. It has
been confirmed in a previous study1) that the unit
amount of water relative to the total surface area ofthe powder is correlated with fluidity. In this, Water
volume per total surface area was used as an index toevaluate both water film thickness and relative flow
area. Even within this experiment, in each powder,
the water volume per total surface area was correlatedwith the ratio between water film thickness andrelative flow area, as shown in Fig. 3.

0.2

0.4

0.6

0.8

1

Excess water film thickness[μm]Fig.1 Water film thickness and Relative flow area ratio
12

mini-slump[cm]

10

8

6

N-S
FA-S
LP-S
CSP-S
N-CS
FA-CS
LP-CS
CSP-CS

4

2

0
0

0.2

0.4

0.6

0.8

1

Excess water film thickness[μm]Fig.2 Water film thickness and Mini-slump
42

y = -0.47239 + 0.7589x R = 0.98
2
y = -1.2323 + 2.7719x R = 0.84

0.87753.5

0.7312

3

0.585

2.5

N-S δ
FA-S δ
LP-S δ
CSP-S δapproximation straight lineδ0.43870.29250.1462

2
1.5

N-S Γ
FA-S Γ
LP-S Γ
CSP-S Γapproximation straight lineΓ

01

The relative flow area ratio

FLUID PREDICTION
Examination by Excess water film thickness

0

Excess water film thickness[μm]Figs.1,2 showed a water film thickness andrelations of the relative flow area ratio,mini-slump.
In both Figs. 1 and 2, there was a tendency in all
formulations for the relative flow area and the minislump to increase as the excessive water film became
thicker. This is taken to indicate that the change in theexcess water film thickness influences the fresh state,such as the relative flow area and the mini-slump ofmortar. However, when comparing the powders in
Figs. 1 and 2, it can be seen that there is a large
difference in relative flow area and mini-slump
between them, even when the water film thicknesses
are the same. This seems to indicate the influence ofthe properties of the powders. A possible influencing
factor is the difference in particle shape. Whereas fly
ash has a smooth spherical shape, it is reported thatfor crushed powder with fine surface irregularities,
the BET-specific surface area is larger than for othertypes of powders2). That is, we assume that thedifference in particle shape influenced fluidity. Also,in the process using fly ash, the relative flow area andmini-slump were differed sharply between sea sandand crushed sand, while in the standard formulation,
little fine aggregate choice had little influence.

0.5-0.1462

0
0.6

0.8

1

1.2

1.4

1.6

1.8

2

The volume of the water per total surface area[ml/㎡]

Fig.3 volume of the water per total surface area andδ ,ΓIn order to evaluate the characteristics peculiar to thepowder, the y-axis was adjusted on the graph so thatthe reference formulation is approximately a straightline. Figure 3 shows the fitted curves. Here, a linear
approximation was found for the cases N-S 30, 40,
and 50; in these, a linear relationship was clearlyobserved. It is assumed from this that the differences
between the curves of water film thickness andrelative flow area for each powder (Fig. 3) are due tothe characteristics peculiar to the powder. Therefore,
approximately straight lines were drawn for the
curves of water film thickness and relative flow area
for the powders, and the correction value wasobtained by averaging the difference between thestraight lines and converting it into water film
59

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

3.5

12

3

10

2

2.5

Mini-slump [cm]The relative flow area ratio

y = -0.28224 + 12.21x R = 0.81

2

1.5
2

y = 0.3038 + 3.9163x R = 0.82
1Standard compounding
Before correct
After correct
After correct
approximation straight line

0.5

8

6

4
Standard compounding
Before correct2

After correct
After correct
approximation straight line

0

0
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0

0.8

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Excess water film thickness[μm]Excess water film thickness[μm]Fig.4 Before and after correct-δ, Γ

Fig.5 Before and after correct-δ, Ms

thickness; the water film thickness calculated using
the correction value was taken as the corrected water
film thickness.
A similar technique was also used for the minislump. By correcting the water film thickness for eachpowder using the correction value, it was possible toexpress the relation between water film thickness andrelative flow area and mini-slump as a straight line.
In other words, it is assumed that fluidity can beapproximately evaluated and predicted using bothcorrection values and straight-line approximations, asseen in Figs. 4 and 5. Looking at the correction values
in Table 3, siginificant differences were observed
according to powder. The correction value of fly ash
is larger than that of other types of powders. This
seems to be due to the ball-bearing effect caused by
the smooth and round shape of the fly ash, which
improves the fluidity such that the fluidity becomestheoretically large against the water film thickness. In
contrast, with the crushed powder, the correction
value for the relative flow area and mini slump is
negative. This is interpreted as being because fineirregularities on the particle surface of the crushedstone powder decrease the fluidity, and so the fluidity
becomes theoretically small against the water film
thickness.

Table3: Water film correction value
Powder
FA
LP
CSP

Fine
Water film correction
aggregatevalue Γ(µm)

Water film correction
value Ms(µm)

S

2.62×10-2

3.50×10-2

CSS

7.72×10-3
1.07×10-2
1.12×10-2－1.12×10-2

7.65×10-3
1.90×10-2
4.62×10-3－1.52×10-2

CS－1.85×10-2－1.93×10-2

S
CS

0.8

Table4: δ/d correction value
Powder
FA
LP
CSP

Fine
δ/dcorrection value Γ
aggregate(µm)

δ/dcorrection valueMs(µm)

S

1.62×10-2

1.83×10-2

CS

3.59×10-3

2.80×10-3

S

6.37×10-3

8.50×10-4

CS-3

2.76×10-3

SCS

7.46×10-3－7.59×10-3-2－1.37×10-2－8.71×10－1.30×10

correction values in Table 4, the correction value of
fly ash was large, and the correction value of thecrushed powder was negative, a result similar to theresult for water film thickness; therefore, δ/d seems
adequate to use as an index of fluidity.
CONCLUSION

Examination by δ/d1 － 1)Even when a byproduct-based powder ismixed as a water film thickness as an index of fluidity,
though the properties of the powders must be taken
into account when doing so.
2－1)The correction value was given as a converted
water film thickness to indicate the influence of thecharacteristics of the powder on the fluidity, and thecorrected water film was obtained by adding thecorrection value to the theoretical water film
thickness. By using the corrected value for the water
film, the relation the between corrected water film
and relative flow area and mini-slump, which serves
as an index of fluidity, can be given by a straight line.
From this, it seems that the liquidity can beapproximately evaluated and predicted simply byusing water film thickness, even for a process using
byproduct-based powders.

In comparison with the excess water film thickness,
which is derived by dividing excess water volume bytotal surface area, and so depends on the surface area,
the index δ/d proposed by Miyake et al.1) excludes theinfluence of the particle size distribution and is moreconcise than the water film thickness, which does notinclude the surface area in the derivation. Therefore,
a consideration similar to that made for water film
thickness was also made for the index δ/d. Before thecorrection, the relative flow area ratio and mini-slump
increased with δ/d, as in the case of the water film
thickness, but when comparing different powders forthe same value of δ/d, variations were observed frompowder to powder. However, we could derive a linear
relationship between δ/d and relative flow area andmini-slump through corrections. Also, looking at the60

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

ACKNOWLEDGMENTS
The experiment was supported by Eiji Mikura, Saori
Itanami, Irie Akira. We show gratitude to them.
REFERENCES[1]Miyake Jyunichi, Matsushita Hirotsugu , Torii
Tsuyoshi “Consideration about the fresh time
property of different mortar of paste levels and thepowders classification”, Concrete engineering
annual memoirs,Vol.2，No.1,2005,pp997~1002[2]Fukuyama Tomohiro, “Study on use as mixture
materials for high flow concrete of the crush stone
powder”, Concrete engineering annual memoirs,
Vol.25，No.1，pp977~982，2003.7

61

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

PHYTOCHEMICALS AND ANTIOXIDANT ACTIVITIES OF THAIRED RICE SEEDS FROM DIFFERENT CULTIVATED AREAS*Muntana Nakornriab1, Jiraporn Krasaetep2, Maratree Plainsirichai3 and Sisikka Wannajun4
1
Faculty of Science, Mahasarakham University, Mahasarakham 44150, Thailand
2
Faculty of Technology, Mahasarakham University, Mahasarakham 44150, Thailand
3
Faculty of Cultural Science, Mahasarakham University, Mahasarakham 44150, Thailand
ABSTRACTThe objectives of this work were to study total phenolic, flavonoid, anthocyanin contents and antioxidant
activities of Thai red rice seed from different 14 areas. Total phenolic, flavonoid and anthocyanin contents
were measured using Folin-Ciocalteu, colorimetric aluminum chloride and pH differential methods
respectively. The antioxidant activities were measured by DPPH and FRAP assay. The results showed thatseed extract from Thai red rice from different areas had total phenolic and flavonoid contents in range of
112.46-278.88 mg GAE/100g sample, 238.55-980.13 mg quercetin/100 g sample, respectively. While theantioxidant activities were found in range of 3.26-8.63 mg/mL and 510.50-2350.41 mM Fe(II)/100 g sample,
respectively. The seed extracts from NET area had significantly higher phytochemicals and antioxidant
activities than other extracts from different areas. In conclusion, the Thai red rice should be proposed as
potential sources of safe natural antioxidants and preservatives for rice industry.
Keywords: Thai red rice, phytochemical, antioxidant activity, different cultivated area

purple or other colors depending on type and ricecomponents. Furthermore, there are important parts
like proteins, cellulose and hemicellulose. Next tofruit pericarp, it is seed pericarp or rice bran. It is
10 % of all seed that contains fat and pigment likefruit pericarp. This causes brown rice has highnutrient substances and fiber [6]. There is the reportthat brown rice or rice with different colors like red,dark purple, and black in inner seed contain higher
important nutrients than rice with has no color for
example polyphenol, betacarotene, anthocyanin,
vitamin E, and gamma oryzanol. These antioxidant
activity substances are very useful and prevent aging,obesity, diabetes, cancer, and cardiovascular disease[7-8].

INTRODUCTION
Rice is an important food of Thai people andforeigners for a long time. Currently, rice products
produce income to Thailand more than otheragricultural products. Rice is cereal which its
scientific name is Oryza sativa L. It is in a family of
Poaceae. Rice grown, in Thailand is an indica type.
Rice is divided into rice and glutinous rice. The
different between rice and glutinous rice is type ofstarch that is combined into the endosperm. Rice
kernels contain amylase flour about 15-30%, while
glutinous rice kernels contain most of amylospectinbut very small amylose content. Thailand has manykind of rice which has many seed colors, indicating
the special properties of rice as the source ofnutrients and special substances. Eighty of seed
riced is flour and 20% of seed rice is bran and rice
germ nutrients [1]. Grain consists of two parts: hullor husk, which is outer most part of seed and fruit orpure rice (true fruit or caryopsis or brown rice)which is inside the cracked kernel.
Brown rice consists of 3 main parts, germ,or embryo (germ) rice seed coat (bran) and ricekernel (endosperm). Germ or embryo is at the baseof large seed shell which. Germ is the source of foodfor growth of seed and it contains high the amountof nutrients such as protein, fat, and vitamin E. In
addition, the germ also contains substances that havedifferent antioxidants including phenolics tocopherol
tocotrienol, oryzanol [2-5]. Seed pericap is the outerlayer of tissue containing pigment mixed with brownrice is made with various colors like brown, russet or

METHODOLOGY
Thai red rice samples (Taptim-Chumphae rice)collected from 18 different areas of Thailand: 3
provinces from North Thailand (NT), 3 province
from Southern Thailand (ST), 3 province from East
Thailand (ET), 3 province from West Thailand (WT),
3 provinces from North East Thailand (NET) and 3
provinces from Central Region Thailand (CRT).
They were from the 2015 of the Chumphae Rice
Research Center in Khon Kaen province and Facultyof Technology, Mahasarakham University, Thailand.
All chemical reagents used were analytical grade.

Extraction of Crude Antioxidants
62

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

was calculated from a calibration curve, and theresult was expressed as mg quercetin equivalent per
100 g of sample

The seeds from Thai red rice at different area weredried in oven at 25 ºC, then ground to a fine powder
in a mechanical blender. Dried seed powder (10.0g)
were extracted by 95% ethanol containing 1.0% HCl(3×100 mL) for 30 min with intermittent shaking atroom temperature. The extracts were combined andfiltered through a 0.45 µm Nylon membrane filter.
After The crude extracts stored at 4 °C in storage
vials for the determination of phytochemicals andantioxidant activities.

Total anthocyanin contents
The total anthocyanin content (TAC) was
determined by the pH-differential method [10].
Pipette crude extracts solution 1 mL into 10 mL
volumetric flask for preparing two dilutions of thesample, one adjust volume with 0.025 M potassium
chloride buffer, pH 1.0, and the other with 0.4 M
sodium acetate buffer, pH 4.5, diluting each. Let
these dilutions equilibrate for 15 min. Measure theabsorbance of each dilution at the 510 and 700 nm,
against a blank cell filled with ethanol. Results are
expressed as micrograms of cyanidin 3-glucosideequivalents (Cy3-GE)/ 100 g of dry weight. The
anthocyanin content was calculated as follows:

Phytochemical screening
Phytochemical screening of Thai red rice seedextracts were carried out on the three extracts, total
phenolic flavonoids and anthocyanin contents.
Total phenolic contents
The total phenolic contents of crude seedextracts from Thai red rice were determined byspectrophotometric method using Folin–Ciocalteu’s
phenol reagent as described earlier with somemodifications [8]. The crude extract in ethanol (0.5mL) was placed in a test tube and was diluted to 5.0
mL with a glass of distilled water. Folin–Ciocalteu’s
phenol reagent (5.0 mL) was added, and the contentsof the test tube were mixed thoroughly. After 3.0
min, 5 mL of 10% sodium carbonate solution wasadded, and the mixture was allowed to stand for 1 h
with intermittent shaking. The absorbance of theblue color was measured in a Shimadzu UV2101PC Spectrophotometer (Bio-Tek Instrument
INC, Canada) at 750 nm. The concentration of total
phenolic compounds was determined using the gallic
acid equation (mg/g extract) obtained from thestandard gallic acid calibration curve. This
experiment was carried out three times, and theresults were averaged for the different fractions in
the Thai red rice varieties.

(1)
Where
MW = molecular mass cyaniding-3-glucoside(449.2)
DF = dilution factor
ε = molar absorptivity of cyanidine-3-glucoside(26,900)

Antioxidant activities
1,1-Diphenyl-2-picryl-hydrazyl (DPPH) assay
The radical scavenging activity of crude seedextracts from Thai red rice measured using the 1,1diphenyl-2-picryl-hydrazyl (DPPH) assay, as
described earlier with some modifications [9]. The
crude extract (0.01-10.0 mg/mL) of 1 mL was placedin a test tube, mixed with 3.0 mL of 0.1 mM DPPH
(2,2-diphenyl-1-picrylhydrazyl) in ethanol. The
mixture was shaken vigorously and was left to standfor 30 min at room temperature in the dark. The
absorbance was measured in a Shimadzu UV2101PC Spectrophotometer (Bio-Tek Instrument
INC, Canada) at 517 nm. The control reaction
contained all reagents except for the crude samples.
The radical scavenging effect was calculated by thefollowing equation:

Total flavonoid contents
The total flavonoid contents of crude seedextracts from Thai red rice were determined byspectrophotometric method using the aluminum
chloride colorimetric method [9]. Pipette crude
extracts in ethanol (250 µL) was placed in a test tube,
mixed with 1.25 mL of distilled water, Shake well.
Add 75.0 µL of 5% NaNO2 solution to shake well.
Then set aside at room temperature for 5 minutes,
and add 150 µL of 10% aluminum chloride (AlCl3).
Shake the mixture well and allowed to stand for
6 min. Afterward, 500 µL of 1 mol/L NaOH solution
were added, and the final volume of the mixture wasbrought to 10 mL with double-distilled water. The
mixture was allowed to stand for 15 min, andabsorbance was measured in a Shimadzu UV2101PC Spectrophotometer (Bio-Tek Instrument
INC, Canada) at 510 nm. The total flavonoid content(2)where Ac is the absorbance of the control at 517 nm,
and As is the absorbance of the extract/standard at
517nm. This experiment was repeated thrice, and theresults were averaged for the different fractions in
the crude extracts.

63

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

Ferric Reducing Antioxidant Power (FRAP)
assay
Ferric Reducing Antioxidant Power FRAP
assay was performed according to the methods of[11] with slightly modification. The FRAP reagent
was freshly prepared by adding 10 mM of 2,4,6-Tris(2-pyridyl)-1,3,5-triazine (TPTZ) (dissolved in 40
mM of HCl), 20 mM of FeCl3 in water and 300 mMof acetate buffer (pH 3.6) in the ratio of 1:1:10. The
crude extract 10mg/mL (100 µL) were mixed with 3
mL FRAP reagent in test tubes, mixed with 300 µL
of distilled water and undergoes vortex. Bothsamples and blank were incubated for 4 minutes at
37oC. The absorbance was measured in a Shimadzu
UV-2101PC spectrophotometer (Bio-Tek Instrument
INC, Canada) at 593 nm. The values obtained wereexpressed as µM of ferrous equivalent Fe (II) per
100 gram of sample.

of quercetin resulted with a linear regression
equation of calibration curve (y=1.939x+0.048, R2=0.975) This linear equation was used to determine
the total flavonoids compounds in the seed extracts
from Thai red rice at different area. Flavonoids arepolyphenolic which are the most numerous of thephenolic compounds that found throughout the plant
kingdom. The average quantity of the total
flavonoids c compounds found in the seed extracts isshown in Table 1. The amount of total flavonoids
content of the seed extracts were in the range of
238.55 ± 21.83- 980.13 ± 55.93 mg GAE/100g
Sample. Among the seed extract from Thai red riceseeds at, NET 1 present the highest amount of TFC.

Statistical analysis
Results obtained were reported as mean ± SDof triplicate measurements. Significance differences
for multiple comparisons were determined byTurkey's Honest Significant Difference (HSD) at
0.05 probability level.

Red ricefromdifferent
cultivated
areas
CRT 1
CRT 2
CRT 3
NET 1
NET 2
NET 3
ST 1
ST 2
ST 3
ET 1
ET 2
ET 3
WT 1
WT 2
WT 3
NT 1
NT 2
NT 3

Table 1. The total phenolic and flavonoids contentsof Thai red rice seeds from different cultivated areas
by total phenolic and flavonoid contents (n=5)

RESULTS AND DISCUSSION
Phytochemical screening of Thai red rice seeds
from different cultivated areas revealed the presentof total phenolic and flavonoid contents in all theextracts, but no anthocyanin.
Total Phenolic Compounds
Total phenolic content (TPC) of Thai red riceseeds from different cultivated areas was measured
by the Folin-Ciocalteu reagent method using gallic
acid as the standard. A linear calibration curve ofgallic acid resulted with a linear regression equationof calibration curve (y =1.939x+0.048, R2 =0.975)
This linear equation was used to determine the total
phenolic compounds in the seed extracts from Thai
red rice at different area. The average quantity of thetotal phenolic compounds found in the seed extracts
is shown in Table 1. The amount of total phenolics
content of the seed extracts were in the range of
113.04 ± 27.20 - 278.88 ± 58.05mg GAE/100g
Sample. Among the seed extract from rice TáptimChumphae at, NET 1present the highest amount of
TPC. Generally, phenolic compounds are the main
constituents in plants and characterized by having atleast one aromatic ring with one or more hydroxyl
groups attached.

TPC(mg GAE/100g
Sample)TFC(mg Quercetin/100
g Sample)

119.00 ± 19.32
190.50 ± 21.13
226.58 ± 53.13
278.88 ± 58.05
233.82 ±37.44
231.55 ±20.69
117.68 ± 17.74
119.75± 12.32
112.46± 14.78
149.29 ± 24.15
123.03± 26.74
133.56± 19.46
211.68 ± 22.83
199.03± 16.83
208.46± 18.73
113.04 ± 27.20
140.19 ± 27.02
164.85 ± 17.34

871.64 ± 54.64
811.69 ± 60.68
912.30 ± 40.45
980.13 ± 55.93
657.36 ± 74.27
497.98 ± 55.32
727.06 ± 85.61
643.10± 48.29
519.47± 49.21
763.98 ± 11.52
713.49± 27.83
737.58± 39.45
829.95 ± 49.79
774.05± 28.91
805.89± 40.06
238.55 ± 21.83
278.79 ± 21.33
303.06 ± 79.04

NT means Northern Thailand, NET means
Northeastern Thailand, CRT means Central Region
Thailand, ET means Eastern Thailand, ST means
Southern Thailand, WT means West Thailand
Antioxidant Activities
Antioxidant activity of the seed extracts fromThai red rice at different area were measured by
DPPH-radical-scavenging and FRAP assay (Table 2).
The radical-scavenging activity of each crude seedextracts were measured by using the DPPH assay.
When the DPPH radical was scavenged by anantioxidant through the donation of H• to form thereduced DPPH-H, the color changed from purple toyellow. In this study, the scavenging activity wasamplified with the increased concentration of all the

Total Flavonoids Compounds
Total flavonoids content of Thai red rice seeds
from different cultivated areas was determined by
the aluminum chloride colorimetric method using
quercetin as the standard. A linear calibration curve64SEE-USQ, Brisbane, Australia, Nov.13-16, 2017

rice antioxidants in the range of 0-40 mg/mL, and it
was constant at concentration above 15 mg/mL. In
theDPPH
radical-scavenging
assay,
theconcentrations of BHA, ascorbic acid and seedextract of Thai red rice at different area, at which
the DPPH radicals were scavenged by 50 % (IC50),
the lower the IC50, the higher the antioxidant
activity. The average quantity of the DPPH and
FRAP value in the seed extracts were shown in
Table 2. The NET 1 extract showed the highest
activity (IC50 = 3.26 ± 0.23mg/mL). In addition, theNET 1 had the highest of FRAP value (2350.41 ±360.42 mM Fe(II)/100 g Sample), too.

cultivated areas is a potential source of antioxidative phytochemicals and is a useful ingredientfor nutraceutical, food industry, health products orfunctional food products.
ACKNOWLEDGEMENTS
The authors wish to thanks to Mr. Ronnachai
Changsri, The Chumphae Rice Research Center inKhon Kaen province, Thailand for supporting theThai red rice seeds from different cultivated areas,
Department of Chemistry, Faculty of Science,
Department of Agricultural Technology, Faculty ofTechnology,
Mahasarakham
University,
Mahasarakham
44150, Thailand for a partial
support of some chemicals.

Table 2. The antioxidant activities of Thai red riceseeds from different cultivated areas by FRAP and
DPPH assay (n=5)
Red rice fromdifferent
cultivatedareas different
area

FRAP
(mM Fe(II)/100 g
Sample)AUTHOR’S CONTRIBUTIONS
IC50(mg/mL)The experiments were conducted in majority of
the conception, design, acquisition, analysis andinterpretation of data and drafting the article by
Muntana Nakornriab. Critical reviewing and final
approval of the version to be submitted were
supported by Jiraporn Krasaetep, Maratree
Plainsirichai and Sisikka Wannajun.

CT11200.56 ± 124.07
4.41 ± 0.18
CT21324.03 ± 198.69
5.08 ± 0.18
CT31731.05 ± 113.44
4.45 ± 0.15
NET12350.41 ± 360.42
3.26 ± 0.23
NET2
1902.42 ± 121.45
3.31 ± 0.07
NET3
2002.78 ± 196.82
3.57 ± 0.46
ST1
658.04 ± 79.97
5.72 ± 0.32
ST2
712.39± 84.69
5.32 ± 0.31
ST3
729.04± 85.14
5.41± 0.28ET1510.50 ± 74.16
8.63 ± 0.59
ET2
521.40 ± 76.39
7.95 ± 0.48
ET3
553.08 ± 75.99
8.23 ± 0.44
WT1
1497.69 ± 283.80
4.66 ± 0.17
WT2
1538.95 ± 249.56
4.75 ± 0.22
WT3
1501.58 ± 263.01
4.72 ± 0.23
NT11089.65 ± 113.77
4.66 ± 0.28
NT21219.52 ± 208.10
4.20 ± 0.08
NT31352.20 ± 127.11
3.91 ± 0.32
BHA
0.0085 ± 0.00
Ascorbic acid
0.0071 ± 0.00
NT means Northern Thailand, NET means
Northeastern Thailand, CRT means Central Region
Thailand, ET means Eastern Thailand, ST means
Southern Thailand, WT means West Thailand

ETHICSThis article is original work and not underconsideration for publication in any other journal.
There are not conflict interests on this paper.
REFERENCES[1] Juliano, B. O., Rice in Human Nutrition. The
International Rice Research Institute (IRRI),
Laguna, and Food and Agriculture Organizationof the United Nations (FAO); Rome; (FAO
Food and Nutrition Series; Vol 26). 1993.
[2] Artht, K., Apichart, N., Somdej, I. Lek, C.
Evaluation of Nutritional Values in Colored
Rice. Agric Sci. J. 40: 1 (Suppl.), 2009, pp.
345-348.
[3] Suttajit, M., Immark, S., Teerajan, S., Suttajit,
S., Chiyasut, C., Antioxdative activity andpolyphenol content in different varieties ofThai rice grains. Proceedings of Asia Pacific
Clinical Nutrition Society. Joint 8th ISCN and
5th APCNS conference 2006. [Online],
http://www.healthy eating club.com/APJCN/
Volume15/Vol15 apcns.htm. [June 21, 2007].
[4] Sookwong P., Nakagawa K., Murata K.,
Kojima Y. and Miyazawa T, Quantitation of
Tocotrienol and Tocopherol in various rice

CONCLUSION
The results presented in this study showed that
Thai red rice seeds from different cultivated areas is
one of good sources of phytochemical compounds
and antioxidant activities. The Thai red rice seeds
from Northeastern Thailand had the highest amountof nutrients. It may be from soil, fertilizer, air etc.
Therefore, the Thai red rice seeds from different
65

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017brans. J. Agric. Food Chemistry. 55, 2007, pp.
461- 466.
[5] Shen Y., Jin L., Xiao P. and Bao, J., Total
phenolics, flavonoids, antioxidant capacity inrice grain and their relation to grain color, size
and weight. Cereal Science. 49, 2009, pp. 106111.
[6] Waltera M., Marchesana E., Sachet Massonia
P.F., Silvab .PL., Sarzi Sartoria G.M. andFerreiraa R.B., Antioxidant properties of ricegrains with light brown, red and black pericarp
colors and the effect of processing Food
Research International. 50, 2013, pp. 698–703[7] Ling, W. H., Wang , L. L., Ma, J.,
Supplementation of the black rice outer layer
fraction to rabbits decreases atherosclerotic
plaque formation and increases antioxidant
status. J. Nutr. 132, 2002, pp. 20-26.
[8] Kotsaeng, N., Nakornriab, M. Total phenoliccontents and antioxidant activity of some fresh

Thai curry.
International
Journalof
GEOMATE, 28, 2016, pp.2906-2909[9] Krasaetep, J., Total Phenolic Contents andAntioxidant Activities from Thai Glutinous
Rice Leaves Extracts. Master’s thesis of
Science degree in Chemistry, Department ofChemistry, Faculty of Science, Mahasarakham
University. Mahasarakham, 2012.
[10] Giusti, M.M.,Wrolstad, R.E. in Current
protocols in food analytical chemistry,
Anthocyanins: Characterization andmeasurement with UV-visible spectroscopy,
ed Wrolstad R.E. (Wiley, New York), 2001, pp.
F1.2.1–1.2.13.
[11] Benzie I.F.F. and Szeto Y.T., Total antioxidant
capacity of teas by the ferric derucing/antioxidant power assay. Agricultural andFood Chemistry. 47, 1999 ,pp. 633-636.

66

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

A STUDY ON PROPERTIES OF MORTAR WITH FLY ASH REMOVEDUNBURNED CARBON BY FLOTATION METHOD
Rika Oie1, Koji Takasu2 , Hidehiro Koyamada3 and Hiroki Suyama4
The University of Kitakyushu Graduate School of Encironmental Engineering, Japan
2
The University of Kitakyushu Faculty of Encironmental Engineering, Japan

1

ABSTRACTIn study of the past, we developed the device removing unburned carbon from the fly ash by flotation method
and examined the performance of the device by experiments. In this study, we divided a modifying class of the fly
ash into five. The loss on ignition of class 1 is the lowest. For various fly ash, such as fly ash conformed JapaneseIndustrial Standards (JIS) and Japanese Industrial non-Standards (non-JIS) are targeted, we confirmed theproperties of mortar with fly ash controlled the modifying levels. As a result, quantity of AE agent addition tosatisfy target air content decreased by increase modifying levels. The correlation was confirmed between themortar flow value and the BET specific surface area. The BET specific surface area was able to reduce by flotation
method. Thus, it was confirmed that it led to the improvement of the mortar flow level. It was thought that it wascause of cleaning effect of particle for the fine grain. It tended to compressive strength was to improve by increase
modifying levels, but compressive strength of mortar with class 2 was the highest in. It was thought it was causeof that fine particle content had been extremely lost.
Keywords: Fly Ash, Slurry, Flotation Method,Unburned Carbon

Table 1INTRODUCTION

Properties of fly ash

BET specific Blaine's specific
Specific
Modified Ignition
Densitysurface area
surface area
Fly ash Modification strength
loss
surface area[g/cm3]2[Class][%][cm²/g][m /g][cm²/cm3]
×
11.78
2.27
13.54
3890
10509

In study of the past, when we use fly ash as
admixture for concrete, the chemical admixture suchas AE agents was adhered to Unburnt Carbon which
fly ash contains, and a problem to adversely affect air
entraining and a fresh property has it pointed out.
Therefore we examined a quality improvement by
floatation method and the development of the quality
stabilization technique to make the low quality fly ash
admixture for concrete and to do the use expansion,and developed the device removing Unburned
Carbon. However, it is necessary to repeat
examination because there are few examination data
which used fly ash modified by flotation method asadmixture. In this study, the mortar properties of themodified fly ash were compared, and the influence ofthe change in the modifying level on the fresh andmechanical properties was confirmed.

FA-A

10

9.64

2.24

8.45

4150

11262

8

8.48

2.25

7.56

4180

17053

6

6.42

2.26

6.55

4220

16924

4

3.61

2.27

4.54

4560

18087

2

2.04

2.26

5.27

4280

20027

Max

0.49

2.23

3.27

4830

22205

-

11.95

2.13

17.52

3320

10438

10

10.14

2.18

11.10

3390

14957

8

8.33

2.19

8.57

3330

16246

6

5.64

2.18

8.21

3410

12817

4

4.18

2.21

5.67

3800

21161

2

2.38

2.20

5.86

3740

17505

Max

0.62

2.20

5.01

3640

17699

[10]

9.16

2.29

6.22

3190

7461

8

8.28

2.26

7.46

3260

8440

6

6.24

2.29

6.59

3240

14367

4

3.93

2.27

5.78

3370

15056

2

1.80

2.28

4.88

3480

13417

Max

0.70

2.28

5.23

3690

17937

[4]

3.37

2.25

3.44

3480

7867

2

2.24

2.22

1.71

3560

7878

Max

0.56

2.24

1.54

3610

9663

×

[2]

1.32

2.36

2.42

4910

17891

〇

Max

1.01

2.33

2.17

4700

12328

〇

×

FA-B

〇

×

FA-C

〇

×
FA-D

EXPERIMENTAL PROGRAM
Materials and Mix proportions

FA-E

Table 1 shows the physical properties of the flyash. Table 2 shows the physical properties of thematerials. For the admixture, the fly ash prepared inthis report 1 was used. The mix proportions are shownin Table 2. For fly ash of Class 8 or higher, the effectof the AE agent was not obtained and it was
impossible to secure the target air volume. Therefore,a total of 18 mixture up to Class6 were tested. The
unit water amount was set to 180 kg/m3, and the water〇

Table 2

67

Item
CementWater

Type
Ordinary Portland cement
Tap waterFine
aggregate

Sea sand(Kitakyushu Iwataya
offshore)

AE agent

AE
Water reducing agent

Materials
Properties
Density 3.16g/cm3
Surface dry density
2.60g/cm3
Water absorption rate
1.36%
Actual rate 61.5%
Coarse particle fraction
2.4
Alkyl ether type anionicsurfactant

Mark
C
W

S

AE

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

SymbolWaterCement
ratio

FA-A6
FA-A4
FA-A2
FA-AMax
FA-B6
FA-B4
FA-B2
FA-BMax
FA-C6
FA-C4
FA-C2
FA-CMax
FA-D4
FA-D2
FA-DMax
FA-E2
FA-EMax

50

Table 3 Mix proportions and Experimental
resultWater- sand-total
Compressive
Modulus of static
Unit Content kg/m³
Fresh test
Powder aggregate
strength N/mm² elasticity ×10⁴/mm²
W
C FA
S
G Flow Value cm Air value％
7days 28days 7days
28daysratio
ratio
693 883
15.2
5.3
38.2
49.6
2.16
2.83
693 884
15.4
5.3
38.5
51.7
2.42
2.87
693 883
15.9
7.2
38.1
52.8
2.26
2.45
692 882
18.2
7.1
34.6
44.7
2.07
2.57
690 880
14.8
5.3
32.9
47.3
2.04
2.35
691 881
14.9
6.2
38.5
48.8
2.67
2.78
691 880
15.4
5.2
38.6
52.0
2.08
2.61
691 880
18.6
7
35.7
48.6
2.01
2.38
35
45
180 360 150 694 884
16.2
6
30.1
45.5
1.78
2.41
693 884
16.35
5.2
34.3
48.0
2.65
2.58
694 884
17.3
6
37.0
49.4
2.11
2.56
694 884
18.35
8
32.2
41.8
1.90
2.40
693 883
18.35
6.6
35.6
49.0
2.30
2.62
692 881
18.45
7
41.0
56.4
2.56
2.61
692 882
20.4
7.2
33.3
45.0
2.68
2.54
696 887
19.85
6.4
39.3
54.0
2.53
2.59
695 886
19.9
7.1
31.3
44.6
1.97
2.31

0.15

0.1

0.05

19

FA-B

FA-C

FA-D

FA-E

Fig.1 AE agent addition amount

20
19

18
17

17
16

15

15
14

6

4
2
Modifying Levels

Fig.2 Flow value

cement ratio was kept constant at 50% for all mixture.
As part of fine aggregate, fly ash amount was 150
kg/m3. In addition, when the modified fly ash is used
as an admixture in a slurry state. The concentration ofslurry fly ash adjust 50-60%. Fly ash slurry wasstirred in speed 400rpm in ten minutes. For mixing, amortar mixer was used.
In the specimen preparation method, after mixing
cement, water and fly ash slurry for 30 seconds, sea
sand was added and mixing was carried out in therange of 4 -6 minutes. When adding fly ash slurry, theshortage of water was added so as to satisfy the unit
water quantity. We adjusted quantity of AE agent
addition with target of 6% of air volume.

1_u

1

2

3

4

5

6

7

2

8

Fig.3 Relationships between Flow valueand BET specific surface area

Fig. 1 shows a graph of the amount of AE agent
added in each ash. In FA-A,B,C, the amount of AE
agent that must be added changes greatly between
Class 6 and Class 4. It was found that the unburned
carbon in the fly ash adsorbs a large amount of AE
agent if the ignition loss is about 6% or more;
therefore, in performing the modification treatment
by flotation, the amount of additional AE agent canbe greatly reduced by reducing the ignition loss to 4%
or less. The amount of additional AE agent generally
decreases as the modification level is increased, but it
was confirmed that there was no marked difference
between Class 2 and Class 1_utherefore, the amountof additional AE agent can be minimized by bringing
the ignition loss down to less than 2%.Fig.2 shows therelationship between the reforming level and the flow
value. Flow values tended to increase as modifying
levels increased in all ashes. It is believed that the

RESULTS

68

9

BET specific surface area m /g

Fresh properties

Test methods
Compressive strength tests, modulus of static
elasticity and drying shrinkage were done according
to JIS for each test.
EXPERIMENTAL

18

16

14
FA-A

FA-A
FA-B
FA-C
FA-D
FA-E

Flow Value cm

20

Flow Value cm

AE agent additon amount[C+FA]%

Class6Class4
Class2
Class1_u

0.2

0

21

21

0.25

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

60

60
FA-A
FA-B
FA-C
FA-D
FA-E

40
30
20
10

FA-E2
FA-E1_u

FA-D1_u

FA-D4
FA-D2

FA-C2

FA-C1_u

FA-C6
FA-C4

FA-B4

FA-B2
FA-B1_u

FA-B6

FA-A2
FA-A1_uFA-A4

028days
7days

Compressive strength N/mm

2

50

FA-A6

Compressive strength N/mm

2

55
50
45
40
35
30
25
20

6

4
2
1_u
Modyfing Levels (class)Fig.4 Compressive strength

28days

FA-A
FA-B
FA-C
FA-D
FA-E

55
2

7days

Compressive strength N/mm

60

50
45
40
35
30
25
20

6

4
2
1_u
Modyfing Levels (class)Fig.5 Compressive strength and modyfing levels
material age of 28 days, just as at a material age of 7days, the Class 2 formulation showed the highest
compressive strength in all ashes. Also, except for
FA-B, Class 1 _u showed the lowest compressive
strength in all Classes. The change in observed trend
between Class 2 and Class 1_u is similar to thatobserved in the mortar flow, and the ability toevaluate the compressive strength through thepresence or absence of the fine particle component,
mentioned before, was confirmed. In this experiment,
we expected that the compressive strength of the fly
ash fully modified by flotation would decrease due tothe excessive loss of fine particles in the case of the
fly ash substitution of 150 kg/m3 of fine aggregate.
Different amounts of substitution are to be studied in
the future.

flow value is increased by the flotation method
because unburned carbon is removed and the particle
surface is cleaned. Regarding the mortar flow value,
FA-A,FA-B,FA-C tended to be low, and FA-D,FA-E
tended to increase. It was confirmed that the flow
value could not be simply evaluated by the ignition
loss. Except for with ash E, the increase of flow value
from Class 2 to Class 1_u was the largest. In
modifying the fly ash by flotation, the primarydifference between maximum modification and othermodification levels is that unburned carbon may
possibly be reduced to the limit. This suggests that aclassifying effect is produced by the maximum
modification, because fine particles are separated
from the fly ash (since fly ash contains unburned
carbon and other fine particle components).
Therefore, it is considered that the flow value fromClass 2 to Class 1-u has greatly improved. FIG. 3
shows the relationship between the BET specificsurface area and the flow value. It has been reported1)
that in fly ash with a BET specific surface area of 3.60
m2/g or more, the greater the BET specific surface
area, the more strongly adverse effects on fluidity are
exhibited. Similar results were also obtained in thisexperiment, and this tendency was observed evenwhen the BET specific surface area was 3.60 m2/g or
less. It was confirmed in the previous section that the
BET specific surface area decreases as themodification level is increased, indicating that ahigher modification level leads to an improved flow
value.

Modulus of static elasticity
Fig. 6 shows the relationship between the removing
level and the modulus of static elasticity at 7 days and
28 days of age. At a material age of seven days, FAA,B,C showed the largest static elastic modulus inClass 4, while the static elastic modulus became
smaller beyond Class 4, and Class 1_u and Class 6
showed similar values. In addition, the static elastic
modulus of ash D increased with modifying level,
while the static elastic modulus of ash E tended todecrease with modification level. At 28 days ofmaterial age, the static elastic modulus of Class 4
tended to be the largest, just as at 7 days of material
age. As for ash C, the static elastic modulus tended todecrease as the modification level became stronger, at
28 days of material age. Comparing the material agesof 7 days and 28 days, it was confirmed that the static
elastic modulus varies to a lesser extent when thematerial is 28 days of age.Fig.7 shows therelationship between the compressive strength andthe static elastic modulus at 7 days and 28 days of age,
NEW-RC formula2). In the relational expression in
the figure, the coefficient k1 is set to 1.0, k2 is set to
1.1, and the unit volume mass r is assumed to be 2.27.
This tended the coefficient k1 is set to 1.0, k2 is set toCompressive strength
Fig. 4 shows the temporal change in compressive
strength. Compressive strength tended to increase
with progress of age in all preparations. Fig. 5 shows
the relationship between the removing level andcompressive strength at 7 days and 28 days of age. In
FA-A FA-D of up to Class 2, the compressive
strength increased somewhat at the material age of7days, and decreased from Class 2 to Class 1_u. At a
69

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

4

2.5
2
1.5
1

6

4
2
1_u
Modifying levels (class)

3 .5

28days

3.5
3
2.5
2
1.5
1

7days
28days

2
4

2

FA-A
FA-B
FA-C
FA-D
FA-E

Modulus of static elasticity×10 N/mm

3

3.5

4

4

3.5

4

Modulus of static elasticity×10 N/mm

2

FA-A
FA-B
FA-C
FA-D
FA-E

Modulus of static elasticity×10 N/mm

7days

NEW RC式

3

3

2.5
2 .5

2

2

1.5
30
1 .5

6

4
2
1_u
Modifying levels (class)Fig.6 Removing class and Modulus of static elasticity
1.1, and the unit volume mass r is assumed to be 2.27.
This tended to be lower than the value of the NEWRC formula in all formulations used in thisexperiment. This experiment was carried out usingmortar; when using concrete, the static elastic
modulus should be evaluated appropriately.

30

40

35

40

35

45
45

55

50

55

50

FA-B1_u
FA-C1_u
FA-D1_u
FA-E1_u
FA-A2
FA-B2
FA-C2
FA-D2
FA-E2

Length change μ-500Fig. 8 shows the change over time of drying
shrinkage. At approximately 28 days of material age,
Class 6 fell below (and Class 2 surpassed) the level ofapproximately -1500µ of the length change rate. It
became clear that strengthening the modificationlevel has the effect of suppressing drying shrinkage.
Focusing on Class 6 and Class 4, the length change
rate is larger in Class 4. In contrast, between Class 2
and Class 1_u, the length change rate is generally
smaller in Class 1_u. This is thought to be due to theadsorption of water by unburned carbon, suggestingthat drying contraction has a strong influence due tounburned carbon. One possibility is that dry
shrinkage can be evaluated by the modification level
only when the ignition loss is 4% or less. Though d4
ash has not undergone a modification treatment, as
mentioned earlier, it can be evaluated formodification level by using ignition loss as an index,
as in the case of the modified fly ash. In thisexperiment, differences dependent on ash species
were not found.

60

Fig.7 Relationships between theCompressive strength andModulus of static elasticity
elasticdielastelasticitCompressive
strength and Modulus of static elasticit
FA-A1_u0

Drying shrinkage

60

2Compressive strength N/mm

-1000

-1500

-2000

0

5

10

15

20

25

30

Days
0
FA-A6
FA-B6
FA-C6
FA-A4
FA-B4
FA-C4
FA-D4

Length changeμ

-500

-1000

-1500

-2000

0

5

10

15

20

25

30

Days

Fig.8 Drying shrinkage
between BET specific surface area and mortar flow,
indicating that strengthening the modification level
reduced the BET specific surface area, leading to theimproved flow value.
1－2) The compressive strength of Class 2 was thehighest in all ashes, while Class 1_u showed thelowest compressive strength among the 28-day
strengths. This is thought to be due to the excessive
reduction of the fine particle component at the
maximum modification level of fly ash.
1－3）In the moduls of static elasticity, a moduls of
static elasiticity of Class4 showed the tendency that
became highest with all fly ash class.

CONCLUSIONS
The findings obtained below are shown.
1－1) For fresh mortar, the amount of additional AE
agent needed to achieve the target air volume
decreased sharply between Class 6 and Class 4. As
for mortar flow, the amount became larger as themodification level was increased. The rise rate wasgreatest between Class 2 and Class 1_u, possibly due
to the detachment of fine particles and the cleaning
effect of particles at the maximum modification level.
In addition, a negative correlation was observed

70

SEE - USQ, Brisbane, Australia, Nov.13-16, 20171－4）In terms of drying shrinkage, we confirmedthat modification intensified suppression of drying
shrinkage due to modification.
ACKNOWLEDGMENTS
The materials were provided by Nippon Steel and
Sumitomo Metal Corporation. The experiment was
supported by Eiji Mikura, Saori Itanami,
YutoMurakami, Yuta Nimura. We show gratitude tothem.
REFERENCES[1]Akira Yoshino, The influence that a property of the
fly ash gives to quantity of addition of the additive
Vol.27，No.1，pp.175-180，2005.6[2] Architectural Institute of Japan: Building works
standard specifications, 5 commentary JASS steel
reinforced concrete construction[3] Japan Standards Association: 2009 JIS handbook
soft concrete71Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

A STUDY ON PROPERTIES OF WITH FLY ASH REMOVEDUNBURNED CARBON BY FLOTATION METHOD
1Yuto Murakami1, Koji Takasu2, Hidehiro Koyamada2 and Hiroki Suyama2
The University of Kitakyushu Graduate School of Environmental Engineering, Japan
2
The University of Kitakyushu Faculty of Environmental Engineering, Japan

ABSTRACTIn study of the past, when we use fly ash as admixture for concrete, the chemical admixture such as AE agentswas adhered to Unburnt Carbon which fly ash contains, and a problem to adversely affect air entraining and a fresh
property has it pointed out. Therefore we examined a quality improvement by floatation method and thedevelopment of the quality stabilization technique to make the low quality fly ash admixture for concreate and to
do the use expansion, and developed the device removing Unburned Carbon. However, it is necessary to repeat
examination because there are few examination data which used fly ash modified by flotation method as admixture.
We had changed the loss on ignition of modified fly ash for an index at degree of the modifying by flotation
method and confirmed the change of fly ash properties. The fly ash did not conform to the demand value of theJapanese Industrial Standardized class 1 only by removing Unburnt Carbon by flotation method. We were revealed
that it influenced other properties by the characteristic of the fly ash.
Keywords: Fly Ash, Slurry, Flotation Method,Unburned Carbon

INTRODUCTION

Table 1: Fly ash
BET specific Blaine's specific
Specific
Modified Ignition
Densitysurface area
surface area
Fly ash Modification strength
loss
surface area[g/cm3][Class][%][cm²/g][m2/g][cm²/cm3]
×
11.78
2.27
13.54
3890
10509

In study of the past, when we use fly ash as
admixture for concrete, the chemical admixture suchas AE agents was adhered to Unburnt Carbon which
fly ash contains, and a problem to adversely affect air
entraining and a fresh property has it pointed out.
Therefore we examined a quality improvement by
floatation method and the development of the quality
stabilization technique to make the low quality fly ash
admixture for concreate and to do the use expansion,and developed the device removing Unburned
Carbon. However, it is necessary to repeat
examination because there are few examination data
which used fly ash modified by flotation method asadmixture. In this study, we had changed the loss on
ignition of modified fly ash for an index at degree ofthe modifying by flotation method and confirmed thechange of fly ash properties. The degree of modifying
by fly ash flotation method was changed by using loss
on ignition as an index, and the change of fly ash
physical properties was confirmed.

FA-A

10

9.64

2.24

8.45

4150

11262

8

8.48

2.25

7.56

4180

17053

6

6.42

2.26

6.55

4220

16924

4

3.61

2.27

4.54

4560

18087

2

2.04

2.26

5.27

4280

20027

Max

0.49

2.23

3.27

4830

22205

-

11.95

2.13

17.52

3320

10438

10

10.14

2.18

11.10

3390

14957

8

8.33

2.19

8.57

3330

16246

6

5.64

2.18

8.21

3410

12817

4

4.18

2.21

5.67

3800

21161

2

2.38

2.20

5.86

3740

17505

Max

0.62

2.20

5.01

3640

17699

[10]

9.16

2.29

6.22

3190

7461

8

8.28

2.26

7.46

3260

8440

6

6.24

2.29

6.59

3240

14367

4

3.93

2.27

5.78

3370

15056

2

1.80

2.28

4.88

3480

13417

Max

0.70

2.28

5.23

3690

17937

[4]

3.37

2.25

3.44

3480

7867

2

2.24

2.22

1.71

3560

7878

Max

0.56

2.24

1.54

3610

9663

×

[2]

1.32

2.36

2.42

4910

17891

〇

Max

1.01

2.33

2.17

4700

12328

〇

×

FA-B

〇

×

FA-C

〇

×
FA-D

FA-E

〇

measurement of the particle size distribution, theSEM image analysis and the BET specific surface
area, all the fly ash had raw powder and 24 hours ormore fly ash dried in an 105℃ electric furnace wasused. The flow value ratio and the activity index were
performed in accordance with JIS A 6201 Annex 2"Test method of flow value ratio and activity index bymortar of fly ash". Table 1 shows the properties of the
fly ash used. In this experiment, we use five types of
fly ash A supplied from different producers. FAA,B,C,D is ash from a power generation plant. FA-E

EXPERIMENTAL DETAILS
Materials
The particle size distribution was measured usinga laser diffraction / scattering type particle size
distribution measuring apparatus. For SEM image
analysis, an SEM image was taken using a probe
electron microscope. For the BET specific surface
area, the BET specific surface area was measured
using an automatic specific surface area pore
distribution measuring apparatus, and for the72

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

20

4
2
1_u

3000

2000

1000

0

FA-A

FA-B

FA-C

FA-D

FA-E

Fig.1: Blaine's specific surface area

15

10

5

0

FA-A

FA-B

FA-C

FA-D

FA-E

Fig.2: Specific surface area

is JIS-II certified. As a method of preparing thesesamples, when modifying raw ash with a device, themodification level (Preprocessing time, Amount of
foaming agent, Flotation method time, Amount oftrapping agent) was weakened or strengthened bycontrolling the processing level, and multiple types ofmodified ashes with different ignition loss were madefrom one kind of raw ash; additionally, themodification level was set more finely by mixing,
using the ignition loss to characterize the modified
ash. As a measure of the modification level of eachash (using ignition loss as an indicator), themodification level of FA-A~C was varied in steps of
2%, and FA-D in steps of 1%, with minimum
modification levels of 10% for FA-A, 10% for FA- B,
8% for FA-C, and 2% for FA-D. The error in theindex of ignition loss of each sample was ± 0.5% for
FA-A~C and ± 0.25% FA-D. Note that Class10_o of
FA-A, Class10_o of ash B, Class10 of FA-C, Class4of FA-C, and Class2 of FA-E are all raw powders, andare not subjected to modifying treatment.

20

10_o
10
8
6
4
2
1_u

2

2

3

10_o
10
8
6

BET specific surface area [m /g]

25

3

4000

4
2
1_u

Specific surface area [×10 cm /cm ]

10_o
10
8
6

2

Blaine's specific surface area [cm /g]

5000

15

10

5

0

FA-A

FA-B

FA-C

FA-D

FA-E

Fig.3: BET specific surface area

specific surface area when modification was carriedout by flotation. For FA-A(11.78%) in which theignition loss of the raw powder was high, when the
maximum modification(0.49%) was carried out, achange of about 1000 cm2/g (from 3890 cm2/g to4830 cm2/g) was observed in the Blaine specificsurface area. In contrast, for FA-B(11.95%) in which
the ignition loss of the raw powder was high, a changeof only about 300 cm2/g (from 3320 cm2/g to 3640
cm2/g) in the Blaine specific surface area wasobserved in the case of the maximum
modification(0.62%). Also, in the case of the FAD(3.37%), in the case with a low ignition loss of raw
powder, a change of only about 500 cm2/g (from 3190
cm2/g to 3690 cm2/g) was observed in the Blaine
specific surface area, even in the case of the
maximum modification(0.56%). It was found that therelation between the decrease in ignition loss and theimprovement in Blaine specific surface area variedwith the ash species.
Fig. 2 shows the raw ash powder and the specificsurface area for each reforming level.The specificsurface area for FA-A changed by about 12000
cm²/cm3 (from 10509 cm²/cm3 to 22205 cm²/cm3)
when the maximum modification of the raw powder
was made, but the change for FA-B was only about
7000 cm²/cm3 (from 10438 cm²/cm3 to 17699
cm²/cm3) after the modification of the raw powder. In
FA-D as well, a change of only about 2000 cm²/cm3(from 7461 cm²/cm3 to 9663 cm²/cm3) was observed.
Fig. 3 shows the values of BET specific surface
area for each ash raw powder and each reforming
level. The value of BET specific surface area
decreases if any ash type, except FA-C, is modified
by flotation, and tends to decrease as ignition loss
decreases. In the case of FA-C, the BET specificsurface area was higher than that of the raw powder
when it was modified to Class10, and the BET
specific surface area tended to decrease as themodification level was strengthened. In Fig. 4, a
positive correlation was confirmed, with a coefficientof determination of 0.73 in the relationship between
BET specific surface area and ignition loss. With ahigh ignition loss of the base ash powder, the BET

Measurement
Samples in which the 25 reforming levels shownin Table 1 were operated were used to confirm theirproperties. In order to decrease the influence of
precipitated fly ash when the modified slurry ash is
cast as an admixture, a fly ash slurry is prepared witha fly ash concentration of 65%; for the samples that
did not become slurry, water was further added toincrease the concentration to 50% or more, and a prestirring procedure was used for 10 min, using a stirrer
rotating at 400 times per minute. After casting the fly
ash slurry, the lack of water was compensated so as
to satisfy the unit water quantity of the preparation
before mixing.
RESULTS AND DISCUSSION
Fresh properties
Fig. 1 shows the raw powder of each ash and theBlaine's specific surface area for each reforming level.
Every ash, except for ash E, resulted in high Blaine's
73

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

specific surface area of FA-A and FA-B show
relations that differ from the aforementioned relation:
the BET specific surface area of the raw powder was
not consistent with the assumption of a correlation
between ignition loss and BET specific surface area.
Also, no clear correlation was found for the relation
with the BET specific surface area when the ignition
loss was 4% or less, and the BET specific surface areavaried within the range of 5.0 m²/g or less.
Photo 1 shows SEM images of raw powder of FAA, B, C ash and fly ash at maximum reforming.
Relative to the original powder, in all the fly ash,unburned carbon adhering to the fly ash particles ispeeled off from the tail ash, indicating that the particle
surface is cleaned; specifically, while the particle
surface is completely cleaned in FA-A when thechange in the Blaine’s specific surface area is large,
complete cleaning is not achieved in FA-B and FA-D,
in which the change in the Blaine specific surface area
is small. Although it has been reported in earlier
studies that unburned carbon cleaning is apparent
despite the increase in ignition loss, this experimentshows that residual substances remain in FA-B, as
seen in the SEM image, and cannot be removed fromthe particle surface despite the ignition loss of 0.62%
at the maximum modification. Horiuchi et al. reported
that immersing and leaving fly ash in water for 1 day
decreased strength decreased and generated reactantson the particle surface. Because we measured thesamples dipped in water (except for the raw powders),
reaction products may have been created in water.
Reaction products other than unburned carbon are
generated, adhering to the fly ash surface during themodification by flotation, and there are ash types thatcan be cleaned and those that cannot. It is possiblethat the cleaning condition influences the Blaine
specific surface area and the specific surface area;
therefore, detailed study is necessary in future.
Fig. 5 shows the change in the particle size
distribution of raw FA-A,B,C raw powder andsamples with different reforming levels. FA-A shows
median diameters of modified ash smaller than thoseof the raw powders; it is thought that the fly ash
particle diameter is decreased by flotation. As for FAD, there was hardly any difference in particle size
between the raw powder and the modified ash. If themost common particle size of the raw material wasaround 10 μm, then the most common particle
diameter was hardly changed from that of the raw
powder, even with modification by flotation. Thisclarifies the removal of unburned carbon by flotation
has an influence on the particle size distribution, andthat this influence varies with the fly ash. In all ashes
except for FA-D, ash modified by flotation has a peakat a particle diameter of about 10 μm, and thefrequency in the vicinity of 10 μm intensifies as themodification level is raised or the ignition loss isdecreased. It is considered that there is a classification
effect in reforming fly ash by flotation method, so it

20
2

2

BET specific surface area [m /g]

y = 2.2 + 0.83x R = 0.73

15

10

5

0
0

2

4
6
8
Ignition loss [%]10

12

Fig4: BET specific surface area and Ignition loss

FA-A

FA-B

FA-E
※ Left: Raw powder Right: maximum modified

Photo1: SEM images (magnification:5000 times)
is necessary to verify in detail in the future.
Flow value ratio and Activity index
Fig. 6 shows the results of the flow value
ratio.Comparing the raw powder and the ashes ofvarious modification levels, a tendency can be seen:
the flow value ratio rises sharply as the modificationlevel is strengthened for FA-A and FA-C. FA-A with
an ignition loss of 4% or less and FA-C with anignition loss of 2% or less meet the JIS-I reference
value of 105% for flow value ratio. For FA-D and FA74

SEE - USQ, Brisbane, Australia, Nov.13-16, 20176Frequency [%]

8

10_o
10
8
6
4
2
1_u

5

FA-B

7
6

4
3

8

10_o
10
8
6
4
2
1_u

5
4
3

5
4
3

2

2

1

1

1

1

10
100
Particle size [μ m]

1000

0
0.1

1

10
100
Particle size [μ m]

4
2
1_u

6

2

0
0.1

FA-D

7

Frequency [%]

FA-A

7

Frequency [%]

8

1000

0
0.1

1

10
100
Particle size [μ m]1000

Fig5: Particle size distribution
120
10_o
10
8
6

110

2

y = 1e+02 - 1.5x R = 0.49

110

Flow value ratio [%]Flow value ratio [%]

115

115

4
2
1_u

105
100
95

105
100
95
90

90
85

85
80

80

FA-A

FA-B

FA-C

FA-D

FA-E

0

Fig6: Flow value ratio

68
Ignition loss [%]10

12

Fig7: Flow value ratio and Ignition loss
4
2
1_u

FA-B
2

y = 2.2 + 0.83x R = 0.73
2

10_o
10
8
6

105

4

20

BET specific surface area [m /g]

Activity index at 28 days of age [%]

110

2

100
95
90
85
80

FA-A

15

10

5

75
0

70
FA-A

FA-B

FA-C

FA-D

FA-E

0

2

4

6
8
Ignition loss [%]10

12

Fig8: Activity index at 28 days of age

Fig9: Activity index at 28 days of age
and BET specific surface area

E, the raw powders satisfied the reference values of
JIS-II and JIS-I, at 95% and 105% for flow value ratio,
respectively; note that the flow value ratio tended tobe equal to or lower than that of the raw powder after
the modification. FA-B did not show any remarkabletendency and did not satisfy the flow value ratio of
95%—the reference value of JIS-II for both raw
powder and modified ash. With the flow value ratios
in this experiment, most of the ash with an ignition
loss of 4% or less satisfies the JIS-II reference valueof 95%; however, because unburned carbon is an
influence on ash with an ignition loss of 4% or more,
it is recommended the ignition loss be brought down
to 4% or less to improve the flow value ratio.
Fig. 8 shows the results of the activity index at 28

days of age. In the cases of FA-A and FA-C, the flow
value ratio clearly increased as the modification level
was strengthened. FA-A with an ignition loss of 4%or less and FA-C with an ignition loss of 2% or lessmeet the flow value ratio of the JIS-I reference valueof 105%. For FA-D and FA-E, the flow value ratiosof 95% and 105%, which are the reference values of
JIS-II and JIS-I, respectively, were satisfied in theraw powders; note that the flow value ratio tended tobe equal to or lower than that of the raw powder after
the modification. The FA-B did not show a clear
tendency and did not satisfy the flow value ratio of
95%, the reference value of JIS-II, for both raw
powder and modified ash. In the flow value ratio in
this experiment, most of the ash with an ignition loss
75

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

of 4% or less satisfies the JIS-II reference value of
95%. Because unburned carbon in ash with anignition loss of 4% or more seems to influence theoutcome, it is recommended that the ignition loss bebrought down to 4% or less to improve the flow value
ratio by modification.

ACKNOWLEDGMENTS
The materials were provided by Nippon Steel &Sumitomo Metal Corporation. The experiment was
supported by Eiji Mikura, Saori Itanami, Rika Oie,
Yuta Imuran and Shoma Takegawa. We show
gratitude to them.

CONCLUSIONSREFERENCES
The findings obtained below are shown.
1-1) Regarding the BET specific surface area, there
was a correlation between ignition loss and BET
specific surface area, except that the BET
specific surface area converged to a value ofabout 5 m2/g or less when the ignition loss was
4% or less.
1-2) As the modification level was increased, theBlaine specific surface area and the specificsurface area increased, but the rise rate depended
on ash species. Furthermore, even when theignition loss was low, there were areas in thescanning electron microscope images where thesubstances were not well separated.
1-3) For ash with a frequency peak at a particle sizefor the raw powder of larger than 10 μm, thefrequency peak drops to around 10 μm after themodification. Meanwhile, for ashes in which thepeak frequencies are around 10 μm in the raw
powder, the frequency peak remains at around 10
μm even after the modification. Taken together,in all ashes, the modified ash tended to have afrequency peak at a particle diameter of 10 μm,
with the peak becoming more pronounced as themodification level is strengthened. The
classification effect is made more apparent bymodification of the fly ash by flotation.
1-4) The flow value ratio tended to increase and thefluidity improved when the modification level
was strengthened.
1-5) In ash A, the 28-day activity index surpassed theJIS-I reference value of 90% when the ignition
loss was 10% or less. As for ash B, the JIS-I
reference value of 90% was met when modified,
except at the maximum modification level.

[1] Koji Takasu, Experimental Study on Removal of
Unburnt Carbon in Fly Ash by Flotation Method
and Properties of Concrete with the Fly Ash
Slurry, Architectual Institute of Japan, pp331340, Japan(2014)[2] Yosuke Tihara, A Basic Study on Removing
Unborn Carbon in Fly Ash by Ore Flotation,
Part7 The Change in The Composition andPhysical Properties Between The Original Fly
Ash and The Removed Fly Ash, Architectual
Institute of Japan, (52), pp33-36, 2013.3[3] Sumiob Horiuti, A Study on strengthcharacteristics of fly ash, Shimizu Corporation
Research Report (39)，pp.1-9，1984.4

76

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

CHARACTERIZATION OF CERIUM OXIDE-CHITOSANNANOCOMPOSITE–MODIFIED SCREEN PRINTED CARBON
ELECTRODE AND APPLICATION IN MELATONIN
DETERMINATION
Pachanuporn Sunon1, Porntip Wongkaew2*, Jeffrey Johns1, Nutjaree Johns1
1Division of Clinical Pharmacy, Faculty of Pharmaceutical Science,
Khon Kaen University, Khon Kaen 40002, Thailand
2
Division of Plant Pathology, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand

ABSTRACT
A simple and effective modification of the working screen printed carbon electrode (SPCE) surface has beendeveloped with a mixture of chitosan biopolymer and nano cerium oxide at 1:1 composition for the detection ofmelatonin, a circadian rhythm regulation hormone. The fabricated electrode was characterized by scanningelectron microscopy (SEM), energy dispersive X-ray spectrophotometer (EDS), electrochemical impedance
spectroscopy (EIS) and cyclic voltammetry (CV). Electro-oxidation behaviors of melatonin were extensively
observed by differential pulse voltammetric(DPV) analysis. The experimental results demonstrated that themodified cerium oxide-chitosan screen printed carbon electrode (SPCE-Chi-CeO2) exhibited satisfactorily
improvement in the electrochemical current sensitivity.Alinear calibration curve for melatonin was obtained in
the concentration range from 0-10 µg/ml with a detection limit of 0.18 µg/ml based on DPV measurement. Good
selectivity was also obtained in an interference study with some other closely structural related compounds suchas tryptophan and serotonin. Thus this modification strategy was proved to be a suitable tool for the simple, fast,sensitive and selective determination of melatonin.
Keywords: SPCE-Chi-CeO2, SEM and EDS, EIS and CV, melatonin, DPV analysis
radioimmunoassay (RIA),high-performance liquid
chromatography(HPLC)
andcapillaryelectrophoresis; but they are expensive and time
consuming methods and are confined to thelaboratory. ELISA and RIA provide a stablecalibration curve, reasonable speed and small sample
volume with specificity, sensitivity and precision [2],but they have some limitations and disadvantages by
their high cost and laborious time requirement.
Moreover, a special lab in radiochemistry is neededin RIA analysis and the radioactive tracer is toxic as
well. Recently, electrochemical biosensors have
expanded their attractive attributions that offer new
challenges of analytical methodology and apossibility of miniaturization and portability,
sensitivity, selectivity, a wide linear range, energy
saving, minimal space, and cost effective usage.
Screen printed carbon electrode (SPCE) in
combination with suitable surface modification anda proper electrochemical technique has been shown
applicable in various electrocatalytic studies.
Previous works on the fabrication of an effective andaffordable electrochemical implement via a route ofthis SPCE modification have provided a possibility
for the development of a potent biosensor [3]. The
versatile chitosan biomaterial has been employed as
main structural scaffold for a wide variety ofbiosensor due to its robust properties especially anionic binding of biomolecules including DNA andINTRODUCTION
Melatonin (N-acetyl-5-methoxytryptamine) is an
important hormone that is synthesized in the pineal
gland.It is also recognized as ubiquitous amongliving organisms, including humans, animals, plants,
bacteria, fungi, and algae [1]. It is responsible forregulating sleep and circadian rhythms in mammals,
and is used to counteract the effects of jet-lag or toaid sleep. Principally, it is used for the diagnosis andremedy of insomnia, hypomnesia and of thecerebrum and is used to treat some diseases such as
Alzheimer and cancer. Melatonin is biomarker ofcircadian dysregulation, and measurement melatoninlevels in saliva and blood, and the melatonin
metabolite 6‐sulphatoxymelatonin in urine are usefulto evaluate problems related to circadian rhythms
and sleep. The development of rapid, simple, easy touse, real-time detection, low cost and portabledetection of melatonin in animal tissues and fluids
emerges as imperative. The biosensor ismethodologies employed for qualitative andquantification detection of melatonin in cells,
animals and human products.
Although many methods have been applied in
the qualitative and quantitative determination of lowlevels of melatonin in samples such as enzyme
linked immunosorbent assay (ELISA) and77

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

proteins [3, 4, 5]. In addition, many types ofnanoparticles such as metals and metal oxides haveprovided an ideal remedy for enhancing the sensing
performance of the sensors. Cerium oxide (CeO2) is
one among the metal oxides mostly introduced forbiosensor fabrication due to its excellent properties,
including a good biocompatibility, high chemical
stability, excellent electronic conductivity and hugeelectroactive surface. A composite matrix
construction based on chitosan and CeO2 for animmobilization of single stranded DNA probehasalso been reported for effective sensing of cancer
gene [6].
In the present study, modification of SPCE witha combination of chitosan and CeO2 is organized tofabricate an electrochemical sensor for melatonin
determination via differential pulse voltammetry(DPV). Techniques in scanning electron microscopy(SEM), energy dispersive X-ray spectrophotometer(EDS), electrochemical impedance spectroscopy(EIS) and cyclic voltammetry (CV) are utilized toinvestigate the modified SPCE performance. An
appreciable sensitivity of SPCE-Chi-CeO2 in thedetection of melatonin is expected from theinheritance of advantageous chitosan and CeO2
properties as well.

Modification of working electrodes
Fabrication of the modified SPCE-Chi-CeO2
electrode was done using a DS-150 screen printed
carbon electrode (SPCE) as the basal platform. The
0.25 cm2 working surface area of the SPCE wascleaned by ultrapure water rinsing for 3 times prior
to a modification. Chitosan solution was made by amixing of chitosan powder with 1% acetic acid at
1% by weight per volume. Afterward, the nanocerium oxide (CeO2) particles were added up at 1 %(w/v) and sonicated for 15 min at room temperature.
Later, a 5 μL of this Chitosan-CeO2 solution wasembedded onto the 0.25 cm2 SPCE working surface
and left drying in clean air environment overnight.
Then it was rinsed with ultrapure water and allowed
to dry again for the ready use.
Structural and electrochemical characterization
Surface morphological characteristics of themodified SPCE-Chi-CeO2 in comparison to its basal
SPCE were acquired through scanning electron
microscopy (SEM). Three replicates of each weresputter coated with gold and 0.25 cm2 working
electrode areas were investigated using 10,000
magnifications. A structural profiling of theelements was consequently investigated by energy
dispersive X-ray spectrophotometer (EDS) in couple
with the SEM. Electrochemical performance weredone via Autolab PGSTAT 302N controlled with the
Autolab Nova software. An electrolyte 0.1 M
phosphate buffer saline (PBS) at pH 7.0 solution
containing 1.0 mM of K3Fe(CN)6as a model
electrochemical probe was employed for theelectrochemical characterization. Electrochemical
impedance spectroscopy (EIS) was carried out by
applying a potentiostatic state of 0.01 V AC
potential and 0.17 V bias potential with 10 mV
amplitude in the frequency range from 0.01 to 105
Hz. Cyclic voltammograms were obtained over the
potential scan range from -0.6 to 1.2 V at a varied
scan rate of 25, 36, 81, 144 and 255 mV/s.
Subsequent measurement of electrochemical
response of SPCE-Chi-CeO2 to a function ofmelatonin concentration (0-10 µg/ml) was set up
using differential pulse voltammetric (DPV)
technique at 50 mV/s scan rate.

MATERIALS AND METHODS
Materials and instruments
Chitosan (85% degree of deacetylation) with amolecular weight of 0.28 kDa was obtained from
Bioline Lab, Co., Thailand. Cerium oxide (CeO2)
nanoparticles (50 nm), tryptophan and serotoninwere gained from Sigma-Aldrich Co. LLC,
USA.Melatonin (GMP 99.96%) was acquired from
HuanggangSaikang Pharmaceutical Co., Ltd, Hubal,
China. Other chemicals for reagent preparation werepurchased from Ajax Finechem Pty, Ltd., Australia.
Buffer solutions and reagents were made up usingorganic free ultrapure water from an Elga DV25
Purewater OptionQ system with resistivity (25 °C)>18.18 MΩ•cm. Screen printed electrode DS-150
strip made of carbon as working area (4 mmdiameter) with a counter electrode made of platinum,a reference electrode made of silver and an electriccontact made of silver was provided by DropSens,
ParqueTecnológico de Asturias, S.L. Llanera(Asturias) Spain. A scanning electron microscope(SEM) LEO1450VP was from Hurley, UK andanenergy dispersive X-ray spectrophotometer (EDS)
was from Technai G2 20,FEI; Thermo Fisher
Scientific,
Oregon,USA.
Electrochemical
performanceswere
acquired
withapotentiostat/gulvanostat model PGSTAT 302N of
ECoChemieAutolab(MetrohmAutolab
B.V.,
Utrecht, The Netherlands) incorporated with Nova
system software.

RESULTS AND DISCUSSION
Morphological and structural characterization ofmodified SPCE-Chi-CeO2
The surface morphologies and atomic
components of SPCE-Chi-CeO2 in comparison to thebasal SPCE at different mixing molar percentage
were characterized by SEM and EDS. The SEM
image in Fig. 1A presents homogeneous carbon
platelets containing in SPCE working surface,78

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

whereas the modified SPCE-Chi-CeO2 surface has
uniform granular porous morphology attributed tothe homogeneous dispersion of CeO2 nanoparticles
in chitosan network as seen in Fig. 1B. Seemingly, astable surface cover could be obtained following themodification by this highly adhesive nanocomposite.
Fig. 2 represents atomic fingerprints from EDS
investigation that signify the differences between
SPCE (Fig. 2A) and SPCE-Chi-CeO2 (Fig.2 B). The
bare SPCE has shown its dominant containing
elements as carbon, chlorine and oxygen. The
carbon is presented as the major constituent of SPCE,
and chlorine is present as a constituent of the binderor solvent, whereas the presence of oxygen is due toany hydrophobic contamination.

Fig. 1

Fig. 2

Atomic fingerprints of bare SPCE (A) and
SPCE-Chi-CeO2 (B) components by EDS
analysis.

Table 1 Percentage of atomic and weight byelement and total compound in SPCE-ChiCeO2 from EDS analysis.
Components
Atom (%)
Weight(%)
Elements
C
57.60
O
29.40
19.82
F
2.27
1.81
Ni
2.42
5.99
Na
1.09
1.06
Tc
0.37
1.54
Ce
6.81
40.18
Gd
0.07
0.47
Compounds
Total chitosan
molecules
3.95
12.77
CeO2 molecules
20.42
73.35
C in chitosan
23.68
C in SPCE basement 33.92
8.50

SEM images observed from working
surface of bare SPCE (A) and SPCE-ChiCeO2 (B).

In view of the modified SPCE-Chi-CeO2, many
more types of atoms are presented such as fluorine,
nickel, sodium, technetium, gadolinium and gold aswell as cerium component in Chi-CeO2 matrix. The
carbon in this case is assumed as a constituent of thechitosan and electrode, the presence of oxygen isdue to any hydrophobic contamination and from
chitosan, fluorine, nickel, sodium and technetium
maybe from electrode plastic basement andcontamination, while gold is from gold coating
electrode for EDS in couple with SEM analysis. The
percentage of atomic and weight by element andtotal compound in SPCE-Chi-CeO2 are as displayedin Table 1. The atomic percentage of carbon ispresent as 23.68% in chitosan constituent and33.92% in the electrode basement. While the atomic
percentage of CeO2 molecules and total chitosan
molecules are 20.42 and 3.95, respectively.
Considering the weight percentage by compound, it
has been stated that the carbon content is about 8.5%,
the CeO2 molecules are 73.35% and total chitosan
molecules are 12.77%. Thus, it can be concluded
that in SPCE-Chi-CeO2 the major constituent byatomicpercentage
iscarbonandbyweight percentage is cerium.

Electrochemical characterization of modified
SPCE-Chi-CeO2
EIS analysis has provided information about thechanges on interface properties between the basal
SPCE and the modified SPCE-Chi-CeO2 as
illustrated by Nyquist plots in Fig. 3. The semicircle
diameter represents the electron charge-transfer
resistance (Rct) character which controls the electrontransfer kinetics of the redox probe (K3Fe(CN)63−/4−in this experiment) at the electrode interface [7]. The
bare SPCE showed a large semicircle diameter with
Rct value about 8,000 Ω/cm2 (Fig.3 curve a),whereas the modified SPCE-Chi-CeO2 produced
almost half size smaller with the Rct value down toabout 3,000Ω/cm2 (Fig.3 curve b) implying lesscharge transfer resistance and hence about 2.7 times
better electron transfer ability. An extreme faster inelectron transfer obtained following the modificationof SPCE with CeO2-chitosan nanocomposite
probably due to the robust positive charges
containing in this composite that offer electrostatic
anchors for negative charges of the probe toaccelerate the electron transfer at the interface. The
fast electron transfer property of SPCE-Chi-CeO2
79

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

could also be affirmed by CV testing, as shown in
Fig. 4. It can be seen that typical current peak curves
for the oxidation and reduction versus potential
applied were arisen in all performing scan rate of 25,
36, 81, 144 and 255mV/s. The current peaks slide
apart a bit with increasing scan rate as acharacteristic of quasi-reversible reaction of theelectrode against the K3Fe(CN)63−/4− redox probe(Fig. 4A). The peak potential (Ep) of oxidative andreductive currents was about 0.2 and 0.04 V,
respectively. The peak separation was about 0.09 Vwith a potential window from -0.2 to 1.2 V, while
the anodic and cathodic peak currents responses
were linearly proportional to the square root of theinvestigated scan rate with the regression coefficient
about 0.9 (Fig. 4B). Thus the modified SPCE-ChiCeO2 is certified satisfactory efficient for further use
in electrochemical sensing according to its approved
linear diffusion control mechanism and fast electrontransfer ability [8].

Fig. 3

Electrochemical oxidation of melatonin
An electrochemical oxidation of melatoin on thescreen printed carbon electrode before and after
surface modification with cerium oxide-chitosan
nanocomposite was investigated using DPV analysis.
Fig. 5 shows the DPV of bare SPCE in the absence(curve a) and the presence (curve b) of melatonin at
1 µg/ml in 0.1 M PBS pH 7.0 electrolyte as a sample
at the scan rate of 50 mV/s, meanwhile the DPV of
SPCE-Chi-CeO2 in this absence and presence of
melatonin is shown up by curve c and d, respectively.
The current curves in the presence of melatonin
produce one oxidation peak at Ep around 0.5-0.6 V
with peak height (Ip) about 0.1µA from bare SPCE
and 1.6 µA from SPCE-Chi-CeO2, whereas almost
none peak current is exhibited in the absence of
melatonin. Obviously higher response and welldefined melatonin oxidation peak has been obtainedin the case of SPCE-Chi-CeO2 indicating anefficiently improvement by this working surface
modification.

Nyquist plot of electrochemical impedance
spectra from bare SPCE (a) and SPCE-ChiCeO2 (b).
Fig. 5Differential pulse voltammetric responsesof bare SPCE and modified SPCE-ChiCeO2: (a) bare SPCE at 0 µg/ml melatonin,(b) bare SPCE at 1.0 µg/ml melatonin, (c)SPCE-Chi-CeO2 at 0 µg/ml melatonin, and(d) SPCE-Chi-CeO2 at 1.0 µg/ml melatonin,
all in PBS pH 7.0 based electrolyte.

Quantitative determination of melatonin

Fig. 4

Quantitative
melatonin
determination
performance of the SPCE-Chi-CeO2 was further
examined by DPV with reference to its high current
sensitivity and a small noise contribution fromprevious experiment. The peak current tended toincrease with the increase of melatoninconcentration. A linear relationship between peakcurrent and melatonin concentration was obtained in
the range from 1 to 10µg/ml in measurement by bare
SPCE with the regression equation of
y = 2.067 + 0.44x
where y = Ip in µA, x = concentration in µg/ml,

Cyclic voltammograms of SPCE-Chi-CeO2
in response to an electrochemical probe
K3Fe(CN)63−/4−accounted by curves frominner to outer corresponding to 25, 36, 81,
144 and 255 mV/s scan rates, respectively(A),with theircoordinate
linearrelationship of anodic and cathodic peakcurrent vs. square root of scan rate (B).

80

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017and a correlation coefficient (R2) = 0.99 (Fig. 6A).
Much lower concentration range down to 0.1 to 1.0µg/ml could be measured by the SPCE-Chi-CeO2
with the regression equation of
y = 1.484x - 0.074, and R2 = 0.96 (Fig. 6B).
The limit of detection, calculated by three times
the standard deviation of the linear regression (Sy/x)
divided by the slope value (b), was 1.07µg/ml fromthe use of SPCE and 0.18µg/ml from SPCE-ChiCeO2. Much higher sensitivity was achieved with
SPCE-Chi-CeO2 in consideration of the slope valueand LOD results due to a better affinity of CeO2chitosan nanocomposite for melatonin moleculesthat enhanced an electrochemical response
performance. The relative standard deviation (RSD)of each calibration experiments was less than 10%
indicating acceptable reproducibility. Although it
seems that this LOD is not as low as some otherrecent reports such as the LOD of 0.02µM (0.005µg/ml) by CV measurement with multi-walledcarbon nanotube (MWCNT) modified glassy carbon
electrode [9], the LOD of 0.1µM (0.025 µg/ml) bysquare wave voltammetry (SWV) with boron-doped
diamond microelectrode [10], and the LOD of
0.004µM (0.001µg/ml) by DPV on carbon ionicliquid electrode modified with MWCNT and cobalt
hydroxide nanoparticles [11], but the ease of
preparation and a facile operation for the prompt use
with considerable lower cost in comparable tosatisfactory detection range for the onsite practicaluse has made the SPCE-Chi-CeO2 enduring
attraction.

Fig. 6

Selectivity in terms of interference study
To examine the relative reactivity and selectivityof the fabricated SPCE-Chi-CeO2 toward melatonin
detection, the electrochemical DPV were performed
with 0.1 M PBS (pH 7.0) supporting electrolyte
containing a fixed amount of 10µg/ml melatonin in
the presence of other two closely structural related
biological indoles as tryptophan and serotonin,
adding at similar concentration. Usually, direct
measurement of melatonin in presence of indole
compounds especially of tryptophan would be
impossible due to the proximity of the potentials of
their oxidation peaks [12]. However, successful
discrimination among them has been testified with
SPCE-Chi-CeO2 as displayed in Fig.7 by the DPV
response in a mixture of melatonin with tryptophan(curve a), and the mixture of melatonin, tryptophan,and serotonin (curve b). A well separate oxidation
peak of melatonin from that of tryptophan can beobserved as shown in curve a, in which the typicaloxidation peak of melatonin occurs at Ep around0.53 V (peak 1), whereas the tryptophan’s peak has
placed at the next Ep of 0.65 V (peak 2). Slightly
shift in Ep is apparent in the mixture of melatonin
and its two precursors, tryptophan and serotoninwhich probably due to the competition in the
diffusion rate to the electrode surface. The current
peak concerning to melatonin exhibits at Ep of
0.56V and tryptophan originated peak appears at Ep
around 0.69 V, meanwhile the oxidation peakcorresponding to serotonin at Ep of 0.23 V is evident(peak 3). This phenomenon suggests that melatonin
could still be selectively determined in the presenceof both indolic precursors. In addition, the modified
SPCE-Chi-CeO2 has also allowed feasibility for
effective simultaneous detection of these compounds.

Calibration
plots
for
melatonin
determination from DPV responses withbare SPCE (A) and with SPCE-Chi-CeO2(B).

Fig. 781

Differential pulse voltammograms of
SPCE-Chi-CeO2 in 0.1 M PBS (pH 7.0)
supporting electrolyte containing melatoninin the presence of tryptophan (a), and in thepresence of tryptophan and serotonin (b) at
10µg/ml of each compound.

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

characterization of the modified screen printed
carbon electrode by self assembled depositionof chitosan and activated carbon”, Int. J. of
GEOMATE,Vol. 11, Aug. 2016, pp. 2356-2362.
[4] Wongkaew P, Poosittisak S, “Electro-affinity of
SCWL-dsDNA on different high deacetylation
degree chitosans deposited glassy carbon
electrode”, Advances in Developing Affordable
In-Vitro Molecular Diagnostics, Puri CP, Abidi
N, Bhanushali, P, Pere A, Gupta SK, Eds.
Mumbai: Yashraj Research Foundation, 2012,
pp. 249-258.
[5] Wongkaew P, Poosittisak S, “Diagnosis ofsugarcane white leaf disease using the highly
sensitiveDNA
based
voltammetricelectrochemical determination”, Amer. J. of
Plant Sciences, Vol.5, Jul. 2014, pp. 2256-2268.
[6] Feng KJ, Yang YH, Wang ZJ, Jiang JH, Shen
GL, Yu RQ, “A nano-porous CeO2/chitosan
composite film as the immobilization matrix forcolorectal cancer DNA sequence-selective
electrochemical biosensor”, Talanta, Vol.70,
Oct. 2006, pp. 561–565.
[7] Orazem ME, Tribollet B, Electrochemical
Impedance Spectroscopy. New York: Wiley,2008, pp. 1-459.
[8] Nicholson RS, “Theory and Application of
Cyclic Voltammetry for Measurement ofElectrode Reaction Kinetics”, Analytical
Chemistry, Vol. 37, Apr. 1965, pp.1351-1355.
[9] Qu W, Wang F, Hu S,Cui D, “Electrocatalytic
properties and voltammetric determination ofmelatonin at a nanostructured film electrode”,
MicrochimicaActa, Vol. 15, Jun. 2005, pp. 150109.
[10] Levent A, “Electrochemical determination ofmelatonin hormone using a boron-doped
diamond electrode”, Diamond & RelatedMaterials, Vol. 21, Jan. 2012, pp. 114–119.
[11] Babaeia A, Taheria AR, Farahanic IK,“Nanomolar simultaneous determination oflevodopa and melatonin at a new cobalt
hydroxide nanoparticles and multi-walledcarbon nanotubes composite modified carbon
ionic liquid electrode”, Sensors and Actuators
B: Chemical, Vol. 183. Jul. 2013, pp. 265-272.
[12] Radi A,Bekhiet GE, “Voltammetry of melatonin
at carbon electrodes and determination in
capsules”,
Bioelectrochemistry
andBioenergetics, Vol. 45, May 1998, pp. 275-279.

CONCLUSION
An effective working electrodeSPCE-Chi-CeO2
was fabricated based on a combination of SPCE andcerium oxide-chitosan nanocomposite for rapid
detection of a circadian rhythm regulation hormone,
melatonin. Signified characteristics of the fabricatedelectrodes
weremorphologicallyandelectrochemically manifested through SEM, EDS,
EIS and CV analyses. A prominent improvement inelectrochemical response signal was obtained incomparison to the original bare SPCE. Satisfactory
working performances in melatonin inspection with
rapid response and considerably low detection limit
and reproducibility as well as good selectivity havealso been verified by quantitative DPV andinterference testing with its structural related
tryptophan and serotonin. Melatonin detection by
this electrode via DPV has shown simple and easy tooperate, providing great potential application forpractical use. Moreover, this system has allowed
simultaneous speciation analysis of these three
related indole compounds within the same time, as
well as a tool extensible for elaboration of an easy
and direct electrochemical determination ofmelatonin and other hormones in pharmaceuticalpreparations.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge Khon Kaen
University’s Division of Research and Technology
Transfer Affair for partial fundingto both individual
and research group (KKU-56-57) and KKU
Research Instrument Center for laboratory facilities.
REFERENCES[1] Tan DX, Zheng X, Kong J, Manchester LC,
Hardeland R, Kim SJ, Xu X, Reiter RJ,“Fundamental issues related to the origin ofmelatonin and melatonin isomers during
evolution: relation to their biological functions”
Int. J of Molecular Sciences, Vol.15, Sep. 2014,
pp. 15858-15890.
[2] Chegini S, Ehrhart-Hofmann B, Kaider A,
Waldhauser F, “Direct enzymelinked
immunosorbent assay and a radioimmunoassay
for melatonin compared”, Clinical Chemistry,
Vol. 41, Mar. 1995, pp. 381-386.
[3] Wongkaew P, Poosittisak S, “Atomic force
microscopic
andelectrochemical82

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

COMPARISON OF HEART RATE VARIABILITY BETWEENPATIENTS WITH MAJOR DEPRESSIVE DISORDER AND NORMALSUBJECTS
Warangkana Chompoopan 1 , Sipanut Silaket2, Wichai Eungpinichpong3 , Suwanna Arunpongpaisal4 andNiramol Patjanasoontorn5
1
Sirindhorn College of Public Health, Khon Kaen, Thailand 2Faculty of Associated Medical Sciences, Khon
Kaen University, Khon Kaen, Thailand; 3Research Center in Back, Neck, Other Joint Pain and Human
Performance, Khon Kaen University, Thailand; 4 Faculty of Medicine, Khon Kaen University, Khon Kaen,
Thailand

ABSTRACT
Major Depressive Disorder is one of major mental health problems that affect quality of life of the patients.
The reduced heart rate variability (HRV) and elevated heart rate that associated with depression have been foundas risk factors for cardiac mobility and mortality. These patients should be assessed regularly on HRVparameters and compare with those of normal subjects. This study aimed to compare heart rate variability
between patients with major depressive disorder and normal subjects. This study was conduct at a psychiatricdepartment in Khon Kaen University, Srinagarind hospital, Khon Kaen province, Thailand. A cross sectional
analytic study design was used. Forty patients diagnosed with major depressive disorder (who had been treatedwith antidepressants) were matched according to age, gender with 40 normal subjects participated. They wereassessed on HRV for time domain (standard deviation normal to normal: SDNN, and the root mean square of
successive differences: RMSSD) and frequency domain (High frequency: HF, low frequency: LF, and LF/HF
ratio) using SA 3000P Digital. The results shown that The HRV in the patients and in the normal subjects were
found with SDNN 28.60, 31.44; RMSSD 23.78, 26.73; HF 4.70, 5.04; LF 4.46, 5.01; and LF/HF 1.16, 1.35
respectively. However, No significant difference in the HRV variables between MDD and normal subjects
except LF. Findings in this study show that HRV in the treated patients with major depressive disorder seem tobe a little lower than the normal subjects. This may be due to the effects of well treated with antidepressants. It issuggested that HRV may be one of outcome measures for this patient population.

Keywords: Major depressive disorder, Heart rate variability, Time domain, Frequency domain
and elevated sympathetic activity, which may lead to
cardiovascular dysregulation.
Interactions of central nervous system increased
sympathetic tone, decreased parasympathetic tone tothe heart will also reduce heart rate variability.
However, the effects of sympathetic andparasympathetic activities on interaction between
stress and depression of the autonomic nervous
system remains were unclear. [7] HRV is anelectrocardiograph-based technique developed toassess the relative influences of sympathetic andvagal branches over heart’s beat-to-beat activity. [8]It may be a trait – maker for MDD which can beused for evaluating and classifying the severity ofsymptoms in these patients. This study aimed tocompare heart rate variability between patients withmajor depressive disorder and normal subjects.
METHODSINTRODUCTION
Major depressive disorder (MDD) is the mostcommon illness psychiatric problem and will be oneof the most disabling medical conditions by 2020. It
has a large prevalence worldwide, with an estimated
350 million people affected. [1] MDD has beenfound around 2.4% in Thai population fromepidemiological study of Mental Disorders National
Survey in 2008. [2] It could be one of the risk
factors for developing ischemic heart disease andhas been found to elevate mortality rate ofcardiovascular diseases that sudden death can occur
after cardiac infarction. [3] Depression and stresswere initially associated with the sympathetic
activities and then were found to correlate withparasympathetic activity. [4] The reducing heart ratevariability (HRV) and elevated heart rate wereassociated with Depression [5] which have been
known to be risk factors for cardiac mobility andmortality. [6] Several evidence also suggest that
depression is associated with altered brain function

Design and setting
A cross-sectional analytical design was used inthis study.
83

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

Statistical analyses
Participants
Data were performed using IBM SPSS 19.0
software (IBM Corp. Released 2010. IBM SPSS
Statistics for Windows, Version 19.0. Armonk, NY:
IBM Corp) (Licensed of Khon Kaen University).
Frequency (percent), mean, and standard deviation
were presented for quantitative variables, respectively.
The Kolmogorov-Smirnov test was tested to verify
normal distribution of the data. For analysis of HRV
data that exhibit non-normal distribution of the data,
the median (with Quartile 1 and Quartile 3) waspresented. All HRV variable were then compared
between sex and age-matched groups.

Forty patients, aged 18-64 years, who werediagnosed with MDD, were recruited at thepsychiatry outpatient clinic of Srinagarind hospital,
Khon Kaen University, Khon Kaen province,
Thailand.
Procedure
The study proposal was approved by the Khon
Kaen University Ethics Committee for Human
Research with reference number HE581192. The
objective and design of the study were explained to
all participants before they gave informed consent at
the psychiatric clinic of Khon Kaen University,
Srinagarind hospital. Diagnostic and Statistical
Manual of Mental Disorders, Fifth Edition (DSM-5)
was conducted to ensure the diagnosis of MDD by alicensed psychiatrist.
The process of data collection consisted of threesteps. The first step included demographic data (sex,age). The second step included physician-assessment
measure were assess by the Hamilton rating scale fordepression and structured clinical interview for Mini
International Neuropsychiatric Interview (MINI). It
was used to determine depression and to rule out
other similar psychiatric disorders such as bipolar
disorder, schizophrenia, and psychotic disorder. The
third step, all subjects were asked to have early mealat least 2 hours prior to participate in themeasurements. They were also instructed to refrainfrom alcohol or caffeinated consumption 24 hours
before participation. To control for diurnal variation,
HRV was measured between 10.00 a.m. and 2 p.m.
by using SA-3000P (Medi-core, Seoul, Korea). Eachof the subject was comfortably seated on a chair,then the probe was placed on his/her left index
finger to measure HRV for 3 minutes. During HRV
measurement the subject was guided to breathe
naturally in order to obtain accurate HRV data.

RESULTS
Demographic features
The demographic variables based on age, sex
were balanced between the case (MDD) group andthe control group. Forty depression patients [11males and 29 Female; Mean age (SD) = 43.35(14.37) years] participated.
For the control group, age and sex matchedhealthy volunteers were recruited from university
students, teacher, hospital workers, and people in thecommunity. They were chosen after excluding thosewith psychiatric and physical disorder by apsychiatrist (Table 1).
Table 1 Demographic data between patients withmajor depression and normal controls
Depression

NormalPatients

Control(n=40)(n=40)

Male

11(27.50)

11(27.50)

Female29(72.50)

29(72.50)

18-30

9(22.50)9(22.50)31-40

5(12.50)

5(12.50)41-50

11(27.50)

11(27.50)

51-60

10(25.00)

10(25.00)

Parameters
Sex

Age

Measurement equipment
All variables were calculated as indicators of
ANS function. Time domain variables included: (1)the standard Deviation of all normal to normalintervals (SDNN) as an estimate of overall HRV,and (2) the Root Mean Square successive differencesof normal to normal interval (RMSSD) whichindicate mostly parasympathetic activity.
Frequency domain variables included: (1) HighFrequency power expressed as normalized units (HFnu; 0.15-0.4 Hz); (2) Low Frequency power
expressed in normalized units (LF nu; 0.04-0.15
Hz). The LF- band is associated with both
sympathetic and parasympathetic activity, while the
HF band can be interpreted as a specific measure ofparasympathetic control; and (3) LF/HF display for
sympathovagal balance of HRV.

+

61

5(12.50)

5(12.50)

Total

40(100.00)

40(100.00)

Mean

43.35

43.10

S.D.

14.37

14.50

No significantly differences in the demographic variables (sex,age) between the control and depression groups were observed.

The comparison between the frequency domain
and time domain of HRV in the two group wasshown in Table 2. The Mean and standard deviationof HR, SDNN, RMSSD, LF, HF and LF/HF ratio in
the depression patients were 79.40(12.62) beat/min,
28.60(15.84)ms2 , 23.78(15.87)ms2 , 4.46(1.50) ms2 ,84

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

4.70(1.37)ms2 , 1.16(1.01) and in the normal subjects
were 79.32(13.79) beat/min, 31.44(16.58) ms2 ,26.73(15.28)ms2 , 5.01(1.10) ms2 , 5.04(0.91)ms2 ,1.35(1.09) respectively.
No significant difference in the HRV variables
between MDD and normal subjects except LF.
However, it was noted that mean of all variables in
the MDD group seemed to be lower than those innormal group.

(p-value 0.008) and LF/HF (p-value 0.02).
According for the results on anti-depressants,
patients treated with TCA has relatively low HRV as
compared with other antidepressants (Table 4).

Table 4. Comparison of HR, HRV and difference ofDrug
SNRI: Serotonin and norepinephrine reuptake inhibitor
SSRIs: Selective serotonin reuptake inhibitors
TCA: Tricyclic antidepressantsTable 2 Comparison on HRV data between
MDD and the control groups.
MDD (n=40)

Control (n=40)

Parameters

Mean (S.D.)

Mean (S.D.)

p-valueHR

79.40(12.62)

79.32(13.79)

0.98

SDNN

28.60(15.84)

31.44(16.58)

0.37

RMSSD

23.78(15.87)

26.73(15.28)

0.40

LF

4.46(1.50)

5.01(1.10)

0.01

HF

4.70(1.37)

5.04(0.91)

0.14

1.16(1.01)

1.35(1.09)

0.43

HRV

LF/HF

Mild
Depression
Median(n=9)

Less than
MDDMedian(n=10)Mild
MDDMedian(n=10)

SevereMDDMedian
(n=3)

HR

76.50
(23.50)

74.00
(17)

90.00
(15)

86.00
(12.5)

78.5(12.5)

0.49

SDNN

21.40
(15.83)24.75(17.20)30.98(24.79)16.71(10.48)31.05(15.80)

0.37

RMSSD

16.61
(12.01)

20.18(16.83)19.87(23.81)

13.59(14.54)18.39(12.25)

0.44

LF

3.60
(2.22)

4.74(1.57)

4.96(2.89)

3.57(2.06)

4.70(1.60)

0.16

HF

3.74
(1.40)

5.18(2.33)

5.23(3.42)

4.04(1.72)

4.92(1.07)

0.22

LF/HF

1.68
(1.56)

1.00(1.40)

0.56(1.30)

0.44(0.66)

0.84(0.85)

0.79

noMedian(IQR)Median(IQR)p-valueYesnoMedian(IQR)Median
(IQR)

78
(20)

0.56

76
(20)

84.5
(18)

0.09

93
(9)

76
(15)

0.003

26.33
(25.85)
19.47(10.32)4.69(2.20)
4.74(1.31)
0.84(1.35)

0.91

26.33(15.96)20.02(19.19)4.69(1.92)
4.81(1.47)
0.64(1.38)

18.42(24.17)
16.57(9.27)
3.91(2.93)
3.65(2.16)
1.34(1.41)

0.10

11.11(0.05)
10.59(2.15)
2.23(1.05)
3.05(.077)
0.5(0.35)

26.93(15.96)19.87(17.99)4.70(1.97)
4.85(1.82)
1.09(1.50)

0.0009

0.82
0.84
0.93
0.69

0.09
0.26
0.06
0.20

DISCUSSION
Depression is an affective disorder of patients
who are suffering to daily life.
Prolonged
depression they may lead to the risk of have heartdiseases. Previous studies, MDD patients were
found to have a decreased in HRV as compared to
the non-depressed group. [9]-[10] Conversely, ourfindings did not find significant difference in HRV
between MDD and normal subjects except Low
frequency (LF). This could be due to small sample
size of the current study. With a trend of having
lower HRV in the MDD as compare to the normal
indicate that a large sample size may show a larger
power for statistical analysis. Another reason may bethat the patients in the MDD group of this study
have been on medication for a while where theirconditions may be getting near normal. Further
study on new case of MDD that have not started any
medication may provide a clearer result.

p-value

Kruskal-Wallis equality-of-population rank test
No depression (0-7), Mild (8-12), Less than MDD (13-17)
MDD (18-29) and severe (30+)

CONCLUSION
HRV and HR data were also compared by meanof different medications for treatment. The only
TCA was significant difference in HRV.
Furthermore, we found no difference on Serotonin
and norepinephrine reuptake inhibitor (SNRI),
Selective serotonin reuptake inhibitors (SSRIs) andthere was significant increase on HR and decrease
HRV associated with Tricyclic antidepressants(TCA) (p-value 0.003), SDNN (p-value 0.0009),
RMSSD (p-value 0.008), LF (p-value 0.0009), HF

Based on the results of the study, HRV
variables in the treated patients with MDD seemed
to be a little lower than those in the normal subjects
but no statistical significance. This may be due tothe effects of well treated with antidepressants andsmall sample size of the study. Further study with alager sample size is needed to explore the different
in HRV between the MDD and normal subjects.

85

p-value

75.5
(15)

LF/HF

Table 3. HR, HRV in patients with depression
LevelNo
depression
Median(n=8)

Median
(IQR)

TCA

yes

23.04
(20.73)19.03(19.47)4.42(1.85)
4.49(2.95)
0.82(1.50)HF

HRVMedian(IQR)p-value

HRLF

HRV variables in patients with different degreeof depression were also compared. No statisticallysignificant difference in median HR, frequency
domain and time domain (Table 3).

SSRIs
no

SDNN
RMSSD

.

SNRI
Yes

0.008
0.00090.008
0.02

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

finger temperature, and respiratory rate:
sympathetic-parasympathetic hypothesis ofstress and depression. Journal of ClinicalPsychology. 2011; 67(10):1080-91.
[5] van der Kooy KG, van Hout HP, van Marwijk
HW, de Haan M, Stehouwer CD, Beekman AT.
Differences in heart rate variability between
depressedandnon‐depressed
elderly.
International journal of geriatric psychiatry.
2006; 21(2):147-50.
[6] Robert M, Carney P, Kenneth E. Freedland, andRichard C. Veith, Depression, the Autonomic
Nervous System, and Coronary Heart Disease.
Psychosomatic Medicine 67. 2005;1: 529-33.
[7] Shinba T, Kariya N, Matsui Y, Ozawa N,
Matsuda Y, Yamamoto K-i. Decrease in heart
rate variability response to task is related toanxiety and depressiveness in normal subjects.
Psychiatry Clin Neurosci. 2008; 62(5):603-9.
[8] Foerce T. Heart rate variability standards ofmeasurement, physiologic interpretation, andclinical use. Circulation. 1996; 97(5):1043-65.
[9] Carney RM, Blumenthal JA, Stein PK, Watkins
L, Catellier D, Berkman LF, et al. Depression,
Heart Rate Variability, and Acute Myocardial
Infarction. Circulation. 2001;104(17):2024-8.
[10] Yiming Wang XZ, Adrienne O'Neil, Alyna
Turner, Xingde Liu and Michael Berk. Alteredcardiac autonomic nervous function in
depression. BMC psychiatry. 2013; 13.

ACKNOWLEDGEMENTS
This study would not have been possible withoutkind cooperation of Khon Kaen University,
Srinagarind hospital and the 80 participants. More
importantly, the Research Center in Back, Neck,
Other Joint Pain and Human Performance, Khon
Kaen University as well as Sirindhorn College of
Public Health where have funded this study.
REFERENCES[1] World Health Oraganization, Sixty-fifth world
Health:http://www.who.int/mediacentre/factshe
ets/fs369/en/. assrmbly 2012.
[2] Kongsuk T, Pengjuntr W, Kittirattanapaiboon P,
Kenbubpha K, Arunpongpaisan S, Sukawaha S.
The prevalence of major depressive disorders in
Thailand: results from the Epidemiology of
Mental Disorders National Survey 2008. 2013.
[3] Glassman AH, Bigger J, Jr, Gaffney M.
Psychiatric characteristics associated with longterm mortality among 361 patients having anacute coronary syndrome and major depression:
Seven-year follow-up of sadhart participants.
Archives of general psychiatry. 2009;
66(9):1022-9.
[4] Lin H-P, Lin H-Y, Lin W-L, Huang AC-W.
Effects of stress, depression, and theirinteraction on heart rate, skin conductance,

86Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EFFECT OF ARM SWING EXERCISES ON CARDIOVASCULARRESPONSE AND BALANCE OF OLDER WOMEN
Worawut Chompoopan1, Piyathida Kuhirunyaratn2
Faculty of Medicine, Khonkaen University, Thailand.
2
Research Center in Back, Neck, Other Joint Pain and Human Performance,
Khon Kaen University, Thailand.
1

ABSTRACTThe purpose of this study was to assess the effect of arm swing exercises (ASE) on cardiovascularresponse and dynamic body balance of older women. 4 villages were randomly selected. The total population
was 128 participants divided into 63 older women from two villages in the experimental group, another 65 older
women from another two villages in the control group. The experimental group participated in the evening ASE
program, five days a week, lasted for six months. The ASE program began with warming up for 5 minutes,
swinging arms for 30 minutes, and gradually cooling down for another 5 minutes. Data collection consisted of
pre and post-data collection before and after six months of the ASE program exercise. The collected data werevalidated by the experienced researcher. An independent t-test was used to compare the mean of both groups
before participating in the ASE program. An intention-to-treat analysis was used for last observation carriedforward missing data. Analysis of Covariance (ANCOVA) was used to compare the mean of both groups andPaired t-test within the group. After 6 months of exercising, the cardiovascular response and body balancing ofboth groups were measured. The results showed that the systolic blood pressure and diastolic blood pressure ofparticipants in the experimental group were declined at 5.64 and 6.72 mmHg. respectively while there was only
slightly changed in the control group of which statistically was not significant. In addition, the resting heart ratesof the participants in the experimental group declined to 6.76 beats /minute and their body balancing has
improved. Therefore, the ASE program can be effective to improve BP, HR, and body balancing of older
women.

Keywords: Older, Arm-swing exercise, Blood pressure, Resting heart rate, Balance.

Regular exercises have benefit towards cardiovascular health, increase cardiovascular endurance,
decrease heart disease, or any factors associated toheart diseases. [6]
In China, Arm-swing exercise (ASE) has been
performed and very popular among older people formore than thousand years and has been proved verysafe for them. [7] It is non-equipment involved. No
cost is concerned. People can do everywhere andany circumstances. It is very easy to remember. The
only condition is that it has to be done continuously
at certain period of time.
The study involving Arm-swing exercise (ASE)
related to the effect of cardiovascular system andbody balancing of older people has been limited.
This study aims to assess the effect of Arm-swing
exercise on cardiovascular response and balance ofolder women.

INTRODUCTION
An increase of ageing society has globally been
an issue of discussion and challenges for many
countries. More than a half of the ageing population(414 million) is in Asia and Europe (161 million).
China was reported to have the most older people(209.24 million), India was the second (116.55
million) and Japan had 41.85 million. Indonesia andBrazil had almost the same amount (21.19 and 24.39
million). [1]Thailand is one of the countries where the ageing
population has increased to 10.73 million and has atendency to increase each year. [2] Health problems
also occur. These older people have to encounter not
only their health problems, but also the other aspectsof their living like high blood pressure, chronic
diseases, unexpected non-communicable diseases,
more dangerously body balancing. [3] Physiologicalchanges in the older people can be very dangerous,
particularly cardiovascular system. For instance, thereduction of Cardiac function, the inflexibility ofblood vessel. [4] These can cause hypertension andheart disease. [5]METHODS
Participants
Four villages were randomly selected and divided
into an experimental and a control group. 128 healthyolder women, age more than 60 years old from the87

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017four villages were randomly recruited and grouped
accordingly to the inclusive criteria (have been living in
the village more than a year and have to live in thevillage more than a year) to participate in the study.
The exclusive criteria include regular exercise,disability, and having dynamic body balance problems.

Normally, the exercise was performed in the village
meeting point center nearby where was convenientand older people had fun.
Village health volunteers and Health Promoting
Hospital officers followed up whether the ASE
program had been regularly performed. All theparticipants were encouraged to regularly participate
accordingly to the study design. The researcher andresearch assistants regularly visited and interviewed
the participants. After 6 months of the ASE program,
another appointment was made at the Health Promoting
Hospital in the morning to measure blood pressure(BP), resting heart rate (HR), and dynamic bodybalance.

Design and settingThis study employed a parallel two-arm cluster
randomized control trial (CRT). A Block of 2 wasused for randomization. (4 villages were equallydivided.) The size of each village was required tohave similar geographically characteristics such as
similar number of older women, similar size of thecommunity, and each village has to be a distanceapart. The study was conducted at one of the
districts in Khon kaen province, from October 2014
to March 2015.

Measurement equipments
Blood pressure (BP) and resting heart rate (HR)were measured by a digital sphygmomanometer(Omron® Japan) at the right arm. The participant
rested for 10 minutes after the arrival at the Health
Promoting Hospital. The measurement was repeated
3 times for each participant and recorded. If the results ofthe systolic or diastolic blood pressure varied moreor less than 10% of the previous measurement, theparticipant was advised to sit down for a 10 minutes
rest. All the three times measurement was averaged.
A timed up and go test (TUG) was used to measure
the dynamic body balance (Podsiadlo & Richardson,
1991) purposely to assess the balance, walking ability,and fall risk in older women. Participants weresuggested to wear their regular footwear. The
procedure of TUG measurement began with theadvice for the participants to sit on a chair, waited
for the signal from the researcher to get up and walkalong the three meters line, then went back to theirseat. The duration of this performance was timed
and recorded.

Intervention
All 63 participants from the two selected villages
in the experimental group followed the ASE program in
the evening, five days a week lasted for six months.
All participants from each village did the exercise
together at the same time. The ASE program started
by warming up for five minutes, after that they
followed the steps of the ASE program by standing
on feet as wide as their shoulder width, swinging
both arms forwards at thirty degrees and backwards
at sixty degrees in a second. They had to repeatedly
do this sixty times per minute, lasted for thirty minutes
each day. Since the exercise had taken a bit of time,to avoid the boringness, local music was included
throughout the exercise. All participants wereallowed to walk or dance while swinging their arms.
The exercise was gradually cooled down for fiveminutes.
All participants were suggested not to perform
any other exercises apart from the ASE program
during the period of this study.

STATISTICAL ANALYSES
Shapiro-Wilk test was used to verify the normal
distribution of continuous variables. Data wereanalyzed through using SPSS Version 19 (IBMCorp. Released 2010. IBM SPSS Statistics for
Windows, Version 19.0. Armonk, NY: IBM Corp.)
Under licensed by Khon Kaen University. An
intention-to-treat analysis was also used for last
observation carried forward missing data. The
Independent t-test was used to compare the averaged
results from blood pressure, resting heart rate anddynamic body balance of both groups before
participating in the ASE program. The intention-totreat analysis for last observation carried forward
missing data was also used. Subsequently, ananalysis of covariance (ANCOVA) was employed tocompare the averaged results from blood pressure,resting heart rate, and dynamic body balance of bothgroups after the ASE program, followed by a paired

ProcedureFirstly, the research proposal was required to beapproved by the Khon Kaen University Ethics
Committee. Eventually the research was registeredfor Human Research, coded HE571237. The
objectives and the study design were described to all
the participants for both the experimental andcontrol groups. The consent form was read andsigned at the Health Promoting Hospital. The
appointment was arranged right after the consent
form was acknowledged and signed for self-risk
assessment. Those who were initially screened, thesteps of the program were introduced. Every
participant was provided with a recording-book tosign every time participated in the exercise.

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

SBP
DBP
HR
Balancet-test to compare the mean within the experimental
and control group. A difference at the level of
p<0.05 was considered statistically significant.

The results of the ASE program for older womenin the villages could help reduce blood pressure andresting heart rate, similarly to several studies. Vitro
reported that 12 weeks of low intensity exercise inolder men and women found affected the reductionof resting heart rate. [8] Similarly to the study ofhealthy older men and women, after 6 months of low
and high intensity exercise, it was found that the low
intensity exercise group developed lower bloodpressure comparing to the high intensity exercisegroup. [9] Another study of borderline diabetic
mellitus older people, after 12 weeks of low
intensity exercise training, their blood pressure wasalso reduced. [10]The potential based on mechanism of reducing
the blood pressure can be explained by the effect of
sympathetic nerve activity. During the exercise
recovery period, the sympathetic nerve activity isdecreased. This also happens to the signaltransduction from sympathetic nerve activation into
vasoconstriction. The local vasodilator mechanisms
decrease the arterial blood pressure, apparently
found after the exercise. [11]As far as the dynamic body balance is concerned,
the results of the ASE program affected similarly toseveral studies. A home exercise program for 78
years old people, the results showed that theirdynamic body balance has improved. [12] Similarly
to another study done on three month exercise
program for older men and women and followed up
after12 months, the finding demonstrated that theexercise program significantly improved theirdynamic body balance measurement of which thesame type of tool used for this study (timed up andgo test (TUG). [13] Consequently, the potential
based on mechanism increased the dynamic bodybalance due to the peripheral sensation improved by
the ASE program.

Table 1 Base line characteristics before experimentASE
67.32±5.95
124.23±12.82
75.76±10.05
79.10±10.59
9.60±3.34

CON
67.94±6.58
125.19±14.15
70.98±8.9477.22±8.1110.45±3.11p-value
0.58
0.81
0.01
0.26
0.14

Present Mean±SD., Independence t-test

After 6 months of the ASE program, the results ofsystolic blood pressure (SBP), diastolic bloodpressure (DBP), resting heart rate (HR), anddynamic body balance of the experimental groupwere improved more than the control group. (Asshown in Table 2)
Table 2 Comparison between ASE and CON groupASE
118.60
67.71
71.75
8.78

CON
123.12
71.87
75.86
10.62

p-value
0.005
0.003
0.005
<0.001

Present Mean, ANCOVA mean adjust baseline as covariate

A comparison within the experimental group
after 6 months of the ASE program, the results ofsystolic blood pressure and (SBP) diastolic bloodpressure (DBP), and resting heart rate (HR) werereduced, while the dynamic body balance wassignificantly improved. (As shown in Table 3)
Table 3 Comparison with in ASE group
Variables
SBP
DBP
HR
Balance

Before124.23±12.82
75.18±10.05
79.10±10.59
9.60±3.34

After
118.59±12.47
68.46±6.41
72.34±7.70
8.75±2.40

p-value
0.001<0.001<0.001
0.028

CONCLUSION

Present Mean±SD., paired t-test

Regular exercising of older women in thevillages by Arm-swing, 5 times a week lasted for 6
months, may reduce blood pressure, resting heart rateand improve the dynamic body balance. This kind ofactivity can contribute a lot to the communities
where there are a lot of older people in terms ofhealth promotion, opportunities for social gathering,
having fun as well as no-money costing. Any older
people with any social status can perform thisexercise program. More importantly older people
could use their leisure time worthwhile for their

A comparison within the control group after 6
months of the ASE program, the results of systolicblood pressure and (SBP) and resting heart rate (HR)were reduced, but statistically no difference, while there
were no significantly changes for dynamic body balanceand diastolic blood pressure (DBP) (As shown in
Table 4)
Table 4 Comparison with in CON group
Variables

0.436
0.974
0.070
0.179

DISCUSSION

Before participating in the ASE program, allparticipants ages, systolic blood pressure (SBP),
diastolic blood pressure (DBP), resting heart rate,(HR), and dynamic body balance were compared to findout any obvious differences. There was not statisticallydifferent except the systolic blood pressure of theexperimental group was higher than the control groupand it was statistically significant. (As shown in Table 1)

Variables
SBP
DBP
HR
Balance123.83±11.54
71.02±9.6275.33±9.04
10.72±3.32

Present Mean±SD., paired t-test

RESULTS

Variables
Age
SBP
DBP
HR
Balance125.19±14.15
70.98±8.9477.22±8.1110.45±3.11

BeforeAfterp-value89

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

lives. This activity can certainly economicallyreduce the medication cost of the country.

science and medicine in sport / Sports Medicine
Australia. 2011;14(4):331-7. Epub 2011/03/29.
[7] Ladawan S. Effects of arm swing exercise on
metabolism and heart rate variability in type 2
diabetes mellitus: Khon Kaen University; 2008.
[8] De Vito G, Hernandez R, Gonzalez V, Felici F,
Figura F. Low intensity physical training inolder subjects. The Journal of sports medicine
and physical fitness. 1997;37(1):72-7.
[9] Seals DR, Hagberg JM, Hurley BF, Ehsani AA,
Holloszy JO. Endurance training in older men
and women. I. Cardiovascular responses to exercise.
Journal of applied physiology: respiratory,
environmental
andexercisephysiology.
1984;57(4):1024-9. Epub 1984/10/01.
[10] Hua LP, Brown CA, Hains SJ, Godwin M,
Parlow JL. Effects of low-intensity exercise
conditioning on blood pressure, heart rate, andautonomic modulation of heart rate in men andwomen with hypertension. Biol Res Nurs.
2009;11(2):129-43. Epub 2009/01/20.
[11] Floras JS, Sinkey CA, Aylward PE, Seals DR,
Thoren PN, Mark AL. Postexercise hypotension
and sympathoinhibition in borderline hypertensive
men. Hypertension. 1989;14(1):28-35. Epub
1989/07/01.
[12] Brown M, Sinacore DR, Ehsani AA, Binder EF,
Holloszy JO, Kohrt WM. Low-intensity exercise asa modifier of physical frailty in older adults.
Archives of physical medicine and rehabilitation.
2000;81(7):960-5.
[13] Arai T, Obuchi S, Inaba Y, Shiba Y, Satake K.
The relationship between physical condition andchange in balance functions on exercise intervention
and 12-month follow-up in Japanese communitydwelling older people. Archives of gerontology
and geriatrics. 2009;48(1):61-6.

ACKNOWLEDGEMENTS
This study would not have been possible without
the generous cooperation of the Health Promotion
hospital officers, community health care volunteers,
and the 128 participants. The researcher is thankful
for Siridhorn College of Public Health, Khon Kaen
to provide proportion of study funding and thefinancial support from the Research Center in Back,
Neck, Other Joint Pain and Human Performance,
Khon Kaen University for paper publication.
REFERENCES[1] United Nations. Department of Economic andSocial Affairs. Population Division. Current Statusof the Social Situation, Wellbeing, Participationin Development and Rights of Older People
Worldwide. New York2011.
[2] United Nations. Department of Economic Social
Affairs. Population Division. World population
prospects the 2015 revision. New York: United
Nations; 2015.
[3] World Health Organization. Global health andaging. Bethesda, MD: National Institute on Aging;
2011.
[4] Strait JB, Lakatta EG. Aging-associated cardiovascular changes and their relationship to heart
failure. Heart Fail Clin. 2012;8(1):143-64. Epub
2011/11/24.
[5] Lakatta EG, Levy D. Arterial and cardiac aging:major shareholders in cardiovascular disease
enterprises part ii: the aging heart in health: links
to heart disease. Circulation. 2003;107(2):346-54.
[6] Williams AD, Almond J, Ahuja KD, Beard DC,
Robertson IK, Ball MJ. Cardiovascular andmetabolic effects of community based resistancetraining in an older population. Journal of90Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

PLASTIC FLOW HETEROGENEITY AND FAILURE OF BIMETAL
MATERIAL
1

Svetlana Barannikova1, Lev Zuev2and Yulia Li3
Institute of Strength Physics and Materials Science, SB RAS, 2/4 Academicheskii Ave., Tomsk, 634055,
RussiaABSTRACTThe aim of this paper was to display the kinetics of Lüders band (LB) propagation of bimetallic material on
the yield plateau at the microscale level. The localization patterns of plastic deformation in the process ofuniaxial tension were obtained by noncontact method of recording the fields of displacement vectors.
Microstructure of the interfaces with the using results of optical, atomic force and scanning microscopy showedthat in the direction of the pearlite steel to the austenitic form there are structural components: the weakened
zone of the ferrite layer; hardened section of the ferrite layer dark-pickling layer from the side of austenitic steel.
Plastic deformation of a bimetal began from the nucleation of the Lüders band on the boundaries of the bimetal
on stress raisers with higher hardness due to the diffusion effect. In the main layer the Lüders band was limited
to a pair of fronts moving in opposite directions along the bimetal axis with different velocities. The cladding
layer did not suppress the formation of Lüders bands, leaded to an increase in the propagation velocity of Lüders
band fronts in the base layer.
Keywords: Lüders band, localization of plastic deformation, DIC, steel, bimetal
obtained three-layer sheet at t = 1200 ÷ 1400°C.
Along the outer edge of the sample on bothsides ≈ 750 microns thick cladding layer of 321
AISI steel is located; in the center ≈ 6.7 mm thicklayer of the base metal of A 283 Grade C.
Sample preparation of the bimetal for
metallographic studies and visualization of zones oflarge deformation localization was carried out
according to the standard procedure for steels andalloys: grinding on abrasive cloths of various grades:50Н 865, М50 L219, Р120; polishing using diamondpaste ACM 1/0 on a felt base. Chemical etching of
the sample was carried out with reagents to reveal
structures of stainless and low-carbon steels.
Pre-prepared samples in the form of a double dog
bone with the dimensions of the working section
42×8×2 mm were extended at T = 300K at a rate of
6,67×10-5с-1 on LFM-125 test machine.
Visualization of the localized plastic deformation
bands and registration of their proliferation kinetics
was carried out at the working portion of the sample
by the length of 42 mm by two non-contact methods:
the method of digital image speckle correlation andthe method of digital statistic speckle photography[11,12]. When these methods were implemented, theextended sample was illuminated with coherent lightof a semiconductor laser with a wavelength of
635nm and a power of 15W. The strained sample
images obtained in this light and superimposed withspeckle patterns were recorded with PixelLink PLB781 digital video camera at the frequency of 10Hz
and the resolution of 15.114 microns/pixel, digitizedand stored as files. The idea of the method of digitalcorrelation of speckle images is in possibility to

INTRODUCTION
Unstable plastic deformation of metals and alloys
at the macroscopic level is manifested in the form ofa sharp yield point, neck formation anddiscontinuous deformation [1-3]. The bands ofmacrolocalized deformation accompanying jumps ofdeformation and/or stresses impair the industrial
products surface quality, cause their premature
corrosion and increase the probability of sudden
destruction. Studies of the nonuniformity ofmaterials deformation had been previously made in
detail on specimens of pure metals and alloys [4-6].
This paper considers the deformation behavior of acorrosion-resistant bimetal – carbon steel - stainlesssteel – which is used in chemical engineering for the
manufacturing of reaction columns, autoclaves,reactors and heat exchangers [7-10]. The main
requirement for a bimetal is to ensure the strengthand ductility of the compound, its continuity andstability of its properties over the entire contact
surface. In this connection, it is necessary to
improve knowledge about the processes of joining
dissimilar metals and their joint deformation on
micro-, meso- and macroscale levels.
RESEARCH MATERIALS AND METHODS
The studied samples of bimetallic compounds
were cut from a strip produced according to thefollowing procedure: between the sheets of cladding
metal put into the mold box - 321 AISI as a parent
metal steel of A 283 Grade C was poured(t = 1500°C), followed by hot rolling of the91

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

stainless steel at the depth of 10 μm from theconjugation boundary between the two metals has
showed an increase of 0.32 (wt.%). At the same
distance and less than 10 μm from the conjugation
boundary, carbides are formed as a result ofdiffusion of alloying elements from steel A 283
Grade C into 321 AISI, which explains the increased
hardness of structural steel in the conjugation area.
The results of the investigation of the
microhardness distribution along the thickness of thebimetallic compound are shown in Fig. 2. Thus, themicrohardness at the conjugation was significantly
higher than the microhardness of the base metal (321
AISI) and the cladding layer (A 283 Grade C)
outside the conjugation area. Such a change in the
microhardness along the width of the conjugation
zone can be explained by the manifestation of twocompeting effects due to the presence of directedflows: carbon from low-carbon steel 321 AISI into
stainless steel A 283 Grade C, and alloying elements
Cr and Ni in the opposite direction. The first stream
leads to softening and formation of a ferrite structurein the border sections of 321 AISI, which originally
had a perlite structure, and the second, on thecontrary, leading to their hardening.

determine displacement fields with a high accuracy
by tracking changes in the material surface andcomparing the digital images recorded during
stressing. In the method of digital statistical speckle
photography, a count sequence for each picture pointof a speckle image structure was formed
characterizing the time course of its brightness,variance and the expectation were calculated and theratio between them was used for mapping zones ofplastic deformation localization.
RESULT AND DISCUSION
The study of the microstructure by optical
metallography has allowed to establish that after
rolling of a three-layer sample, the interfaces ofdissimilar materials are clear and thin, pores andnonmetallic inclusions are absent, which indicatescontinuity and high quality of the engagement.
Examination of the bimetal conjugation area
using the LEO EVO 50 scanning electron
microscope (Carl Zeiss, Germany) with the Oxford
Insruments attachment for X-ray dispersion
microanalysis (NANOTEH Center of the Institute ofTheoretical and Experimental Physics affiliated withSB RAS) yielded data on the quantitative content ofelemental composition of steels in the conjugation
area in the course of a step-by-step approximation to
the boundary, as, for instance, shown in Fig. 1.

Fig. 2Distribution of microhardness in thearea of conjugation of steels 321 AISI and A 283
Grade C.

Fig. 1
Bimetalareas
fordispersive
microanalysis (5 μm distance to the conjugation
boundary).

In steel 321 AISI the basis is ferrite, and in steel
A 283 Grade C it is austenite (Fig. 3) [3].

The results of the study of the quantitative
elemental composition of steels in the conjugation
area showed a chromium content in steel of 321
AISI, the concentration of which increases from 0.18
to 0.39 (wt.%) in the direction of the conjugation
boundary between 25 and 5 μm. At the same time, inthe stainless steel, in the direction of the conjugation
boundary between the two steels, the chromium
content decreases, due to the diffusion of chromiumfrom stainless steel in 321 AISI. Since carbon
belongs to chemical elements with a low sequencenumber, in this case, only its qualitative assessment
is possible. Analysis of the carbon content in

Fig. 3
Optical metallography of bimetal in the
conjugation area: (1) – the decarburized layer – the92

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

conjugation area; (2) – the zone of partial
decarburization; (3) – structure of the base metal(321 AISI).

(c)

Fig. 4 (a-c) shows atomic force microscopy scan
images taken when examining the structure of thebase metal of 321 AISI, with successive
approximation to the boundary of conjugation withthe cladding layer of stainless steel on an atomic
force microscope. Thus in Fig. 4a the image of thestructure of the base metal 321 AISI is obtained at
the distance of ≈ 2 mm from the conjugation
boundary and represents a matrix of ferrite withperlite colonies, which is a typical picture for lowcarbon steels. A successive approximation to the
conjugation boundary at a distance of about 200 μm
makes it possible to detect an area of partial
decarburization, which is transitional from thestructure of the base metal to the ferrite structure(see Fig. 4b).
Further in Fig. 4c directly shows the conjugation
boundary between the two metals. It is clearly seenthat a decarburized layer consisting entirely of ferrite
grains is formed on the side of the base metal of 321
AISI That means that a structure of pure ferrite wasformed.
(a)Fig. 4An atomic-force image of the bimetal
structure in the conjugation area: (a) the base metal
structure; (b) the zone of partial decarburization; (c)the decarburized layer - the conjugation area.
Let us consider in more detail the zone of partial
decarburization of the structure of 321 AISI steel inthe case of the AFM analysis. From the scan images(Fig. 5a) it follows that along the boundaries of theferrite grains there are small spots of perlite, which
is located between the grains of ferrite in the form of
separate inclusions or interlayers. Studies haveshown that the perlite cementite in 321 AISI isrepresented with thin, parallel plates, alternatingwith ferrite plates. Fig. 5b shows the fragmented
structure of a pearlitic grain. It is shown that thecementite plates have an intermittent appearance,
which may indicate a heterogeneous release of
cementite within a single grain, and they can beunequal in thickness and curved.
(a)

(b)

93

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017(b)increase in the strength limit, and a decrease in theductility of the base metal (321 AISI). For complete
coverage of the processes of nucleation anddevelopment of Lüders bands (LB) in the bimetal,
during the experiments, the registration of speckle
images began at a voltage lower than the yieldstrength and ceased at the completion of the yieldplateau and transition to the stage of strain hardening.
As the experiment showed, the large deformationin the bimetal sample is localized first in the form of
a LB nuclei, which appears on the yield drop (point
A in the inset of Figure 6), i.e., at the stage of
microlarge deformation. Fig. 7a shows that the
Lüders band front (1) arises at the upper conjugation
boundary of the cladding layer, the main layer of thebimetal, and germinates in the base layer of 321
AISI. Along with this (Fig. 7b), at the lower
conjugation boundary of the cladding layer (themain layer of the bimetal) the second Lüders band
front (2) is generated (point B in the inset of Figure6). At the bimetal flow plateau (inset of Fig. 6), thegrowth of the embryo of the strip across the sample
corresponds to the formation of the ascending
branches of the BC for the front of the Lüders band
(1) and the CD for the Lüders bands (2). At the
moment when both embryos cross the entire sectionof the bimetal, the formation of the Lüders bandends and its expansion begins. In the bimetal
expansion diagram, this process corresponds to the
DE area of the yield plateau. The generated Lüders
band is limited by a pair of fronts moving in
opposite directions along the axis of the sample atvelocities ± Vf, and gradually transferring thebimetal from the elastic to the plastic state.

Fig. 5 An atomic-force image of the bimetal
structure in the zone of partial decarburization;(a) a
3D image; (b) features of perlite structure.
It should be noted that the results shown in Fig.
3-4 were obtained directly by observing the surface
of a metallographic section made by means of
traditional methods without the manufacture of
special preparations (foils) required for electron
microscopy by the method of AFM [13].
Loading curves of flat samples of bimetal, andthe samples equal in size made separately fromsteels 321 AISI and A 283 Grade C are presented in
Figure 6.

(a)(b)
Fig. 6
Loading curves: 1 - A 283 Grade C; 2 bimetal; 3 – 321 AISI; 2' is the yield surface of curve
2 for the bimetal.
They cover the areas of elastic and large
deformations, and the area of fracture. The bimetal
curve after the yield point in the area of large
deformations is located between the curves for its
components (20 samples from each material were
tested). On the loading curves for 321 AISI and thebimetal, the pronounced tooth and the yield plateau
are visible, on which the oscillations of thedeforming stress are noticeable (Fig. 6). The
presence of a cladding layer of stainless steel leads
to a reduction in the duration of the yield plateau, an(c)Fig. 7 Origin of the Lüders band fronts of thebimetal at the plateau: (a) ε = 0.0081; (b) ε = 0.0084;(c) ε = 0,0099.
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

An important characteristic of the process is the
speed of motion of the LB fronts. It was found outthat when the LB starts, its two fronts move in themain layer of 321 AISI in opposite directions withdifferent velocities V1 = 0.8 • 10-4 m/s and V2 = 2.3 •10-4 m/s (Fig. 8a). Since the deformation is due tothe more complex resistance of the bimetal to theloading compared to its components, the plastic flowat the initial stage is effected by means ofpropagation of the LB front in the basic soft metal,
while the stronger cladding layer of stainless steel isdeformed even more elastically. Then, the base layer
and the cladding layer of the bimetal are deformed
plastically. As a result, in the upper cladding layer ofthe material A 283 Grade C only the Lüders band
front (2) propagates with velocity V2 = 2.4 • 10-4 m /s (Figure 8b), and two Lüders band fronts (1) and (2)propagate in the lower cladding layer (A 283 GradeC) in opposite directions with velocities V1 = 0.7 •10-4 m/s, V2 = 2.3 • 10-4 m/s (Fig. 8c).

To compare the data, note that when analyzing
the patterns of localization of large deformation ofsamples of 321 AISI low-carbon steel under tension,
the following was revealed. The generation of LB
fronts corresponds to the stress of the upper yielding
tooth and occurs in the area of the base stressconcentrator near the mobile gripper of the test
machine (Fig. 9a). As a result, one LB front
propagates throughout the yield plateau with thevelocity V2 = 1.1 • 10-4 m/s (Fig. 9b).
(a)

(b)

(a)

(b)

Fig. 9Origin of the Lüders band front at theyield plateau of 321 AISI: (a) ε = 0.008 and ε =0.028;(b) propagation of the CLB front at the yieldplateau of of 321 AISIThe parabolic reveals plastic flow localization in
the form of a stationary system of the plastic flow
centers through the specimen length with the
distance λ = 4 mm between them (Fig. 10).

(c)Fig. 10The distribution of local elongation εxx
along the axis of extension during of parabolic work
hardening stage.

Fig. 8 Propagation of Lüders bands fronts in thebimetal at the yield plateau: (a) in the main layer of
321 AISI (ML), (b) in the upper cladding layer (CL),(c) in the lower cladding layer of A 283 Grade C.

At the prefracture stage, the immobile zones ofplastic strain localization started moving consistently
95

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[1] Orlova D, Barannikova S, Zuev L, “On the
kinetics of localized plasticity domains
emergent at the pre-failure stage of deformation
process”, AIP Conf. Proc. 2016, Vol.1783, pp.
020168.
[2] Danilov V.I, Barannikova S.A, Zuev L.B,
“Localized strain autowaves at the initial stageof plastic flow in single crystals”, Tech. Phys.
2003, Vol. 48, pp. 1429-1435.
[3] Zuev L. B, Barannikova S. A, “Experimental
study of plastic flow macro-scale localization
process: Pattern, propagation rate, dispersion”,
2014, Int. J. Mec. Sci. Vol. 88, pp. 1-7.
[4] Acarer M, Gulenc B, Findik F, “Investigation of
explosive welding parameters and their effects
on microhardness and shear strength”, 2013,
Mater.Des. Vol. 24, pp. 659-664.
[5] Venkateswara N, Madhusudhan G, Nagarjuna
S, “Weld overlay cladding of high strength low
alloy steel with austenitic stainless steel –Structure and properties”, 2011, S. Mater. Des.
Vol. 32, pp. 2496-2506.
[6] Findik F, Yilmaz R, Somyurek T, “The effect ofheat treatment on the microstructure andmicrohardness of explosive welding”, 2011,
Acad. J. Vol. 6, pp. 4141-4151.
[7] Guobin L, Jianjun W, Xiangzhi L. Guiyun L,“The properties and application of bi-metal hotforging die”, 1998, J. Mater. Proc. Technol.
Vol. 75, pp. 152-156.
[8] Mehnen L, Pfutzner H, Kaniusas E,“Magnetostrictive amorphous bimetal sensors”,
2000, J. Magn.Magn. Mater. Vol. 215, pp. 779781.
[9] Nakano J, Miwa Y, Tsukada T, Kikuchi M, Kita
S, Nemoto Y, Tsuji H, Jitsukawa S,“Characterization of 316L(N)-IG SS joint
produced by hot isostatic pressing technique”,
2002, J. Nucl. Mater. Vol. 307, pp. 1568-1572.
[10] Akramifarid H.R, Mirzadeh H, Parsa M.H,
“Cladding of aluminum on AISI 304L stainlesssteel by cold roll bonding: Mechanism,microstructure, and mechanical properties”,
2014, Mater. Sci. Eng. Vol. A 613, pp. 232-239.
[11] Sozen S, “Determination of displacement
distributions in welded steel tension elements
using Digital image techniques”, Steel Comp.
Str. Int. J., Vol. 18, pp. 1103-1117.
[12] Sokoli D, Shekarchi W, Buenrostro. E, Wassim
M, “Advancing behavioral understanding anddamage evaluation of concrete members using
high-resolution digital image correlation data”,
2014, Earthquakes and Structures An Int'l
Journal,Vol.7, pp.609-626.
[13] Barannikova S., Shlyakhova G., Zuev L.,
Malinovskiy
A.
“Microstructureofsuperconducting cable components”, Int. J.
Geomate, 2016, Vol. 10, Is. 21, pp. 1906-191.

with a tendency to merge into a high-amplitude
focus of localized straining, where a neck-likenarrowing of the sample cross section was formed.
This maximum forms at the place of occurring
damage. The peculiarity of damage of the bimetal isrelated to the heterogeneity of plastic deformation in
the intermediate layer of the metal.
Fragmentation of the specimen determines thefracture pattern of bimetal composite. Two macrobands of localized plastic deformation are formed at
the stage of the shoulder effect in the area of stressmacro concentrator. They propagate along
conjugated directions of maximum shear stressacross the whole section of the sample, forming
trihedral prisms on the macro level on the bondinterface of the bimetal. The cracks are nucleated in
the area of parent metal at the trihedral prism tip,
gradually merged passing across the whole sectionof the metal sample (Fig. 11).

Fig. 11Bimetalfracture
patterns
anddistribution of local extensions at the prefracture
stage under deformation 0.24.
CONCLUSION
The research conducted allowed to identify themain patterns of proliferation of LB in the main
layer material. It is revealed that the LB is limited toa pair of fronts moving in opposite directions along
the bimetal axis with different propagation
velocities. The cladding layer does not suppress theformation of LB, leading to an increase in the
propagation speed of the LB fronts in the main layer.
Metallographic studies have shown that at extensionof bimetallic samples of A 283 Grade C + 321 AISIa decarbonized layer is formed in bimetal at the sideof A 283 Grade C steel, and at the side of 321 AISI
steel a carburized layer is formed. On the boundaryof conjugation of bimetal layers an intermediate
layer (carbide) is found, by the depth of up to 50μm.
ACKNOWLEDGEMENTS
The work was supported by the Russian Science
Foundation (project No. 16-19-10025).
REFERENCES

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SEARCHING OF NEW ANTIVIRAL COMPOUNDS OF SUDAN EBOLAVIRUS
GLYCOPROTEIN BASED ON FLAVONOID COMPOUNDS USING IN SILICOMETHODS
Rendy Pramuda Putra1, Ahmad Husein Alkaff2, Mochammad Arfin Fardiansyah Nasution3 andAgustinus C. B. Kantale4, and Usman Sumo Friend Tambunan5*
1

Bioinformatics Research Group, Department of Chemistry, Faculty of Mathematics and Natural Science,
Universitas Indonesia, Indonesia.

ABSTRACT
Ebola hemorrhagic fever is a viral disease from Ebolavirus genus and lethal to primates, including humans. The
case fatality rate is 30%-90%. Until now, no vaccines nor drugs that could effectively combat Ebola hemorrhagic
fever. Sudan ebolavirus (SEBOV), which is classified into Ebolavirus genus, is the second deadliest species after
Zaire ebolavirus, with a fatality rate of SEBOV is 50-70%. In Ebola life cycle, glycoprotein (GP) is crucial for
mediating Ebolavirus entry into the host cell. Thus, molecules that could inhibit glycoprotein activity has apotential to become an ideal therapeutic compound of Ebola hemorrhagic fever. Flavonoid compounds arepotential because of its antiviral properties. In this research, we utilized in silico method to investigate the potencyof flavonoid compounds as an inhibitor of SEBOV GP through molecular docking and computational ADME test.
Moreover, the oral bioavailability and toxicity prediction of the flavonoid compounds were performed as well to
get the best flavonoid compounds. In this research, about 1479 flavonoid compounds and 3D structure of EBOVGP were retrieved from ZINC15 database and RCSB PDB, respectively. Moreover, MOE 2014.09 software wasused as the main operating software. Furthermore, we utilized Toxtree v2.6.13, Osiris Data Warrior, and SwissADME as the software for conducting computational ADME test. In the end, we found Cyanidin-3-(p-Cuomaro)
and Prurin 6’’-O-gallate have the potential as an inhibitor of EBOV GP because they have the best binding affinity
to SEBOV GP and have the excellent ligand properties.
Keywords: Sudan ebolavirus, glycoprotein, in silico, molecular docking, ADME test
INTRODUCTION

the protein existed in SEBOV. The most important
protein for penetration of host cells is a glycoprotein.
Glycoprotein core is GP1-GP2 [1]. Glycoprotein
mechanism to penetrate host cell is attached to hostcell surface, open its core by changing conformation,and penetrate by endocytosis pathway. The inhibitor
can disrupt conformation change [3]. Any disruption
in glycoprotein core could devastate Ebola life cycle[1].
Flavonoid is the biggest phytonutrient group ina natural product. It is very abundant in various
plants, fruits, and vegetables. It has low toxicity,
high bioavailability, antioxidant activity, free radical
activity [4]. They have the potential to become
therapeutical medicine of SEBOV by inhibiting
glycoprotein [5].

Ebolavirus is a genus of virus that causes thedeadly Ebola hemorrhagic fever (EHF). Case fatality
rate of EHF is between 30-90% [1]. Ebola isclassified in group V ((-) ssRNA), Mononegavirales
order, Filoviridae family, and Ebolavirus genus.
There are five species of Ebolavirus: Ebola virus(Zaire ebolavirus, EBOV), Sudan virus (Sudan
ebolavirus, SEBOV), Taï Forest virus (Taï Forest
ebolavirus,
once Côte
d’Ivoire
ebolavirus,
CIEBOV), Bundibugyo
virus (Bundibugyo
ebolavirus, BEBOV), and Reston virus (Reston
ebolavirus, REBOV). Reston ebolavirus only infects
primate nonhuman. Until now, no medicine nor
vaccine can effectively cure EHF.
SEBOV outbreak occurred for the first time in1976 at Nzara and Maridi, Sudan with 284 people isbeing infected and 153 people lost their life. The
species got it is from the country it first identified.
The biggest outbreak occurred in 2000-2001 at Gulu,
Masindi, and Mbarara, Uganda which infected 425
people and 224 people died. Another case of Sudan
Ebolavirus happened in England at 1976; Uganda at
2011, 2012, and 2013, Sudan at 1979 and 2004 [2].
Look at the long list of the outbreak; it is importantto find a therapeutical compound for treating
SEBOV infection.
Glycoprotein (GP), nucleoprotein (NP), RNApolymerase (L), VP35, VP30, VP40, and VP24 are

RESEARCH METHODOLOGYThis research utilized some online and offline
software such as Molecular Operating Environment(MOE) 2014.09, Osiris DataWarrior, Toxtree
v2.6.13, and Swiss ADME. Additionally, the
ChEMBL database, RCSB PDB (Research
Collaboratory for Structural Bioinformatics Protein
Data Bank) and NCBI BLAST (National Center for
Biotechnology Information Basic Local Alignment
Search Tool) were used as the primary sources of ourexperimental data. The general pipeline in thisresearch referred to the previous research that has

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

placement method. The function of the ‘Triangle
Matcher’ is orienting ligand to the active site basedon charge group and spatial fit. The role of ‘London
dG’ scoring is to calculate Gibbs energy for bindingfor certain conformation or pose to allow orientation
analyzing and ligand position as an inhibitor of theprotein [13], [15].
A toxicology test is needed to accurate measuredata such as ADME (Absorption, Distribution,
Metabolism, Excretion) and Carcinogenicity forevery compound that will be tested to human. Before
going to in vitro test, flavonoid will be tested bythree software. They are Osiris Data Warrior,
Toxtree v2.6.13, and Swiss ADME. Osiris Data
Warrior and Toxtree v2.6.13 are offline software,
but SwissADME is online software.

been validated and approved [6]–[8].
First, the flavonoid compounds were retrieved
from ChEMBL database [9], [10]. Thus, a total of1358 flavonoid compounds were obtained and saved
in .sdf file format. RCSB PDB (Research
Collaboratory for Structural Bioinformatics Protein
Data Bank) is the source for Sudan Ebolavirus
glycoprotein database. NCBI BLAST (National
Center for Biotechnology Information Basic Local
Alignment Search Tool) is used to sequence theglycoprotein. Molecular Operating Environment(MOE) 2014.09 [11], [12] software was used toperform molecular docking simulation.
Before glycoprotein is ready, we need to look at
glycoprotein similarity with standard Ebola
Glycoprotein. Next unwanted amino acid chain,solvent, and ligand should be removed. Protonate 3D
is important to add explicit hydrogen. Energy
minimization to lowering glycoprotein local energy.
AMBER99 is chosen for forcefield because of it iscompatible with protein and nucleic acid. Solvation
is a gas phase which means the simulation does notinclude solvent solvation for calculation. Root meansquare gradient is 0,05 kcal/Å.mol, which meanenergy minimization will be stopped when RMS
Gradient is below 0,05 kcal/Å.mol since it iscompatible with protein [13]. In chase of the active
site, number two is chosen because of its similarity
with Endosomal Receptor Niemann-Pick C1 [14].
Tether function is to limit atom shifting from theoriginal position.
In preparation of flavonoid database need toscreen up to make sure there is no same ligand to be
calculated in docking phase. Wash is to repair
flavonoid imperfect structure such as strong aciddeprotonation, strong basic protonation, and add
explicit hydrogen. MMFF94 (modified) method ischosen specifically for its compatible with smallorganic molecule when selecting ligand partial
charge. RMS Gradient value is 0,001 kcal/Å.mol
since its compatible with a small molecule.
In this study, ‘Triangle Matcher’ was used as the

RESULT AND DISCUSSION
Before docking can be started the flavonoids
and glycoprotein must be prepared. We used 1358
flavonoid ligands. In addition, the selected SEBOV
glycoprotein was obtained by employing Swiss
Model. The result itself can be seen in Figure 1.
Glycoprotein from the database does not attach withany unwanted amino acid, solvent, or watermolecule.
Docking flavonoid-glycoprotein complexes
process resulting in the seven best ligand that has apotential to become an alternative medicine for
Ebola. Then the result is selected to become 553
by removing all ligand with rms_define above 2.
Then selected again by stronger than standard
attachment to the glycoprotein. The result is sevenligand.
Based on the interaction of flavonoidglycoprotein complexes, the flavonoid is attachedstrongly to a polar group such as a hydroxyl groupwith aspartate. In this research, we utilized
neplanocin A, 3-deazaneplanocin A, toremifene, andclomiphene 1 as the standard ligands [16].

Figure 1. Similarity of Sudan Ebolavirus with standard Ebolavirus (99,6%)

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

a)

b)

c)

Figure 2. Binding pattern of SEBOV GP and (a) cyanidin-3-(p-coumaroyl)-rutinoside-5-glucoside, (b)myrciatrin V, and (c) 7-O-(6-feruoylglucosyl)isoorientin

The molecular docking simulation was performed byusing MOE 2014.09 software. This simulation
determines the binding affinity of the selected
ligands in the binding site of the protein/enzyme byknowing the Gibbs free binding energy (∆Gbinding)value, inhibition constants, molecular interaction in
the respective binding site. Moreover, the interaction
between the ligand and the key residues that play a
crucial role in the protein/enzyme is also observed.
If the selected ligand has lower ∆Gbinding value andhigher inhibition constants than the standard ligand
and may bind with the key residues at the bindingsite of the protein/enzyme, then the selected ligand
has better chance to be a drug candidate than thestandard ligand. In this study, about 1358 flavonoid
compounds underwent docking simulation against
SEBOV GP. After the docking simulation was
conducted, we found out that there were sevenligands, namely monardaein, cyanidin-3-(pcoumaroyl)-rutinoside-5-glucoside, cyanidin 3glucoside 5-caffeoylglucoside, myrciatrin V, prurin
6’’-O-gallate, 7-O-(6-feruoylglucosyl)isoorientin,
and petunidin 3-O-(6-O-(E)-4-coumaroyl-beta-Dglucoside), which have lower ∆Gbinding value than thefour standards that we tested in the simulation as
well. Moreover, we also figured out that cyanidin-3(p-coumaroyl)-rutinoside-5-glucoside has the lowest∆Gbinding value among all with -8,5716 kcal/mol.
Followed by myrciatrin V and 7-O-(6feruoylglucosyl)isoorientin, with a ∆Gbinding value of-9,1728 kcal/mol and -9.0058 kcal/mol, respectively.
These are much lower than the lowest ∆Gbinding value
among all of the standard ligands (clomifane), which
has a ∆Gbinding value of -7.5146 kcal/mol. The resultsof molecular docking simulation in this study are
shown in Table 1.
In addition, we also take molecular interaction
between the ligands and the protein into account indetermining the best ligand. Cyanidin-3-(p-coumaroyl)-rutinoside-5-glucoside forms threehydrogen bond interactions, two with Ile285 and one
with Arg136. In addition, the positively charged
oxygen from the ligand forms an ion contact with theside chain of Glu71. 19 residues from the protein
interact with the ligands through van der Waals
interaction. On the other hand, myrciacitrin V, theligand with the second lowest ∆Gbinding, interact with
Glu71 and Gly72 through side chain hydrogen bondand Trp104 through backbone hydrogen bond.
Moreover, the ligand also interacts with 18 protein
residues by van der Walls interaction. 7-O-(6feruoylglucosyl)isoorientin forms three hydrogeninteractions with a backbone of Trp104 and Ala283,
also side chain of Asn107. In term of van der Waals
interaction, this ligand interacts with 24 residues.
From the molecular interaction, we can assume that
7-O-(6-feruoylglucosyl)isoorientin has the finest
interaction. The molecular interaction of the selectedflavonoid ligands with SEBOV GP is displayed in
Figure 2.
Finally, the root mean square deviant (RMSD)
score is also considered for determining whether theligand pose that created during the docking
simulation is acceptable and can be replicated during
the real interaction when the ligand acts as the drugor inhibitor for the respective protein. The
acceptable value for each docking pose is below 2.0
Å [17]. In this research, we found out that four outof the seven best ligands have RMSD score below
2.0 Å, namely monardaein (1,6116 Å), myrciatrin V(1.8359 Å), Prurin 6’’-O-gallate (1.8922 Å), 7-O-(6feruoylglucosyl)isoorientin (1.8618 Å). It meansthat these ligands pose which were generated during
the docking process is acceptable and can beconsidered as a model for the real interaction that
may happen during the inhibition process of therespective ligands into the SEBOV GP.

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No
1

2

3

4

5

6

7

S1
S2
S3
S4

Table 1. Molecular docking simulation result∆Gbinding
Molecule Name (with Molecular Structure)(kcal/mol)
Monardaein

RMSD-8,5716

1,6116-9,6941

3,1720-8,14072,3497-9,1728

1,8359-8,4739

1,8922-9,0058

1,8618-8,6197

2,1168-6.0057-7.5146-6.1226-7.3515

1,24941.60391.7294
1.6344

Cyanidin-3-(p-coumaroyl)-rutinoside-5-glucoside

Cyanidin 3-glucoside 5-caffeoylglucoside

Myrciatrin V

Prurin 6’’-O-gallate

7-O-(6-feruoylglucosyl)isoorientin

Petunidin 3-O-(6-O-(E)-4-coumaroyl-beta-D-glucoside)

3-deazaneplanocin A
Clomifane
Neplanocin A
Toremifene

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Table 2. Molecular properties of the selected ligands by Osiris DataWarrior
Ligand
1
2
3
4
5
6
7
S1
S2
S3
S4

MW
903,813598,555
786,690625,557
911,749
586,500
773,671
262,268
406,975
263,256
406,975

clogP-4,9096-1,3391-0,7744
2,0912
1,0577-0,5711
1,4906-0,8991
3,7701-1,1785
3,5829DruglikenessH-acceptor
H-Donor
23
8
22
13
19
12
13
7
14
8
19
11
14
8
7
4
2
1
8
4
2
1

clogS
-5,286-4,887-4,384-4,202-3,218-3,531-4,812-0,433-4,147-1,069-4,798In this research, we also conducted thecomputational ADMET prediction to determine themolecular properties of the best ligands and also
predict their toxicity potency. Two software were
deployed to calculate their properties, namely Osiris
DataWarrior and SwissADME. These software wereused to calculate the toxicity potency based on the
structure and the fragments that contained in therespective ligands.
The molecular properties, druglikeness, andtoxicity of the ligands and the standards are
predicted using Osiris DataWarrior. Following the
Lipinski’s Rule of Five, all the ligands havemolecular weight more than 500 g/mol, H-acceptor
more than 10, H-donor more than 5, and TPSA
greater than 140 Å2 [18]. However, the Lipinski’s
rule of five doesn’t take into account because it
cannot be applied to the natural product compound[19]. On the other hand, the standards have themolecular properties which mostly acceptableaccording to Lipinski’s Rule of Five. The result of
druglikeness score showed that only ligand 4, ligand

PSA (Å2)357,92
344,67305,98
212,67232,9312,05
215,83
219
353
215
356

Druglikeness-16,498-11,851-9,7867
0,79392
0,76076-3,3256-5,5318
1,7618-2,5935
1,7618-3,4787

5, standard 1, and standard 3 that have the scorebelow zero. It means the four molecules have a better
potential to act as a a drug. In the toxicity test, theligands perform well in all parameters, i.emutagenic, tumorigenic, reproductive effective, andirritant, while two standards showed a highprobability to have tumorigenic and reproductive
effective probability. Only standard 2 demonstrated
a high probability of being mutagenic.
In SwissADME test, all flavonoid ligands have
low GI absorption. On the other hand, three out offour standards have high GI absorption, except
neplanocin A. Only cyanidin-3-(p-Cuomaro) andprurin 6’’-O-gallate, flavonoid have zero PAINS
alert. All standards also have zero PAINS alert.
Brenk prediction shows that only ligand 2 and 6
produced one alert. Overall, based on the result of
our computational ADMET tests, it is possible to
make flavonoid compound as a drug that orally
available for the body.

Table 3. Toxicity and absorption prediction by Swiss ADME and OSIRIS DataWarrior
LigandMutagenic

LE & Tox
Reproductive
Tumorigenic
Effective
No
No

Pharmacokinetics

Medicinal Chemistry

Irritant

GI Absorption

PAINS

Brenk

No

Low

1 alert:catechol_A

No
No

No
No

Low
Low

No

No

No

Low

0 alert1 alert:catechol_A
1 alert:catechol_A

No

No

No

No

Low

0 alert

6

No

No

No

No

Low

7

No

No

No

No

Low

1 alert:catechol_A
1 alert:catechol_A

3 alerts: catechol,charged_oxygen_sulfur,
michael_acceptor_1
1 alert: hydroquinone
2 alert : cathecol,
Michael_acceptor_1
3 alerts: catechol,charged_oxygen_sulfur,
michael_acceptor_1
4 alerts: beta_keto_anhydride,
charged_oxygen_sulfur,
michael_acceptor_1,
more_than_2_esters
1 alert: catechol

S1
S2
S3
S4

No
High
No
Low

No
High
No
High

No
High
No
High

No
No
No
No

High
High
Low
High

1

No

2
3

No
No

No
No

4

No

5

101

0 alert0 alert0 alert0 alert3 alerts: catechol,charged_oxygen_sulfur,
michael_acceptor_1
1 alert: isolated_alkene
1 alert: stilbene
1 alert: isolated_alkene
2 alert: alkyl_halide, stilbene

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

CONCLUSIONS
The result of the current study shows flavonoid
is still potential impressive for combating SEBOVby inhibiting its glycoprotein. Flavonoid such as
Cyanidin-3-(p-Cuomaro), myrciatrin V, and 7-O-(6feruoylglucosy) have the lowest Gibbs energy
binding (ΔGbinding), but when looking at SwissADME test myrciatrin V, and 7-O-(6feruoylglucosy) resulting alert in PAINS (false
alarm). However, it can be said that all best sevenligand is still relatively safe, look at data such as
carcinogenicity,
mutagenic,
tumorigenic,
reproductive effective, and irritant.

[8]

[9]

ACKNOWLEDGEMENTS
Usman Sumo Friend Tambunan supervised thisstudy, Agustinus C.B. Kantale and Rendy Pramuda
Putra worked on the experimental details and wrote
the research reports, while Mochammad Arfin
Fardiansyah Nasution and Ahmad Husein Alkaff
wrote the manuscript and analyzed the experimental
data. The authors would like to thank Directorate of
Research and Community Engagement (DRPM)
Universitas Indonesia for granting us Hibah
Publikasi Internasional Terindeks Untuk Tugas
Akhir Mahasiswa (Hibah PITTA) 2017 with No:
693/UN2.R3.1/HKP.05.00/2017. Moreover, theauthors declare that there is no conflict of interestsand competing financial interests.

[10]

[11]

[12]

[13]

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[4]
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[6]

[7]

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E. H. Miller et al., “Inhibition of Ebola virus
entry by a C-peptide targeted to endosomes,”
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15861, May 2011.
P. M. Dewick, Medicinal Natural Products: A
Biosynthetic Approach: Third Edition. 2009.
U. Raj and P. K. Varadwaj, “Flavonoids asmulti-target inhibitors for proteins associatedwith Ebola virus: in-silico discovery using
virtual screening and molecular docking
studies.,” Interdiscip. Sci., pp. 1–10, 2015.
U. S. F. Tambunan, A. A. Parikesit, Y. C.
Unadi, and D. Kerami, “Designing
Cyclopentapeptide Inhibitor of Neuraminidase
H5N1 Virus Through Molecular andPharmacology Simulations,” Tsinghua Sci.
Technol., vol. 20, no. 5, pp. 431–440, 2015.
U. S. F. Tambunan, R. Bakri, A. A. Parikesit,
T. Ariyani, R. D. Puspitasari, and D. Kerami,“In silico modification of Zn 2+ binding groupof suberoylanilide hydroxamic acid (SAHA)

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U. S. F. Tambunan, A. A. Parikesit, V. C.
Adam, M. A. F. Nasution, R. D. Puspitasari,and D. Kerami, “Virtual Screening ofCommercial Cyclic Peptides as β­-OG Pocket
Binder Inhibitor in Dengue Virus Serotype 2,”Int. J. GEOMATE, vol. 13, no. 37, pp. 60–68,
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A. Gaulton et al., “ChEMBL: A large-scalebioactivity database for drug discovery,”
Nucleic Acids Res., vol. 40, no. D1, pp. 1100–
1107, 2012.
A. P. Bento et al., “The ChEMBL bioactivity
database: An update,” Nucleic Acids Res., vol.
42, no. D1, 2014.
S. Vilar, G. Cozza, and S. Moro, “Medicinal
chemistry and the molecular operating
environment (MOE): application of QSAR andmolecular docking to drug discovery.,” Curr.
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1572, Jan. 2008.
“Molecular Operating Environment (MOE)2014.09.” Chemical Computing Group Inc.,
Montreal, QC, Canada, 2015.
D. D. Ben, M. Buccioni, C. Lambertucci, A.
Thomas, and R. Volpini, “Simulation andcomparative analysis of binding modes ofnucleoside and non-nucleoside agonists at the
A 2B adenosine receptor,” Silico Pharmacol.,vol. 1, no. 24, pp. 1–14, 2013.
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B.W.;
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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

NEW ESTIMATION IN AR MODELS WITH EXPONENTIAL WHITENOISE BY USING REVERSIBLE JUMP MCMC ALGORITHM

1Suparman1
Department of Mathematics Education, Ahmad Dahlan University, Indonesia

ABSTRACT
A white noise in an autoregressive (AR) model is often assumed to be normally distributed. In application,
the white noise usually does not follow a normal distribution. This paper aims to estimate a parameter of AR
model that has an exponential white noise. A Bayesian method is adopted. A prior distribution of the parameterof AR model is selected and then this prior distribution is combined with a likelihood function of data to get aposterior distribution. Based on this posterior distribution, a Bayesian estimator for the parameter of AR model isestimated. Because the order of AR model is considered a parameter, this Bayesian estimator cannot be
explicitly calculated. To resolve this problem, a method of reversible jump Markov Chain Monte Carlo (MCMC)
is adopted. The result is an estimation of parameter AR model that can be simultaneously calculated.
Keywords: AR Model, Exponential White Noise, Bayesian, Reversible Jump MCMC

independently and identically exponential randomvariables with parameter  , written z t ~ Exp () .

INTRODUCTION
Autoregressive (AR) with normally white noise
is a time series model that is often used in many
fields. For example, it is used in the field of
economics [1]. But there are so many applications
where white noise is not normally distributed. A
LSE of AR model with heavy-tailed G-GARCH(1,1)
noises is studied [1]. A class of non parametric tests
on the Pareto tail index of the innovation distribution
in the linear autoregressive model is proposed [2]. A
study of the autoregressive model with exponential
white noise can be found in the literature (see [3][8]). A form of time series models where marginal
distributions are in fact exponential distributions ispresented in [3]. A Bayesian analysis of threshold
AR model with exponential noise is developed in [4].
A robust of the bayesian estimation of an AR modelwith exponential innovation to obtain optimal
bayesian estimator is analyzed [5]. A bayesian
method to estimate the coefficient of the AR(1)model is proposed [6]. Generally, the order of theautoregressive is known and must be estimated by
the data.
If the AR model with white noise is fitted to thedata, the order and coefficient of model will be

For example, Figure 1 shows the graph of theautoregressive model with and   5.
80
60
40
20
0
-20
-40
-60
-80

0

50

100

150

200

250

300

350

400

450

500

Figure 1 AR(3) with exponential white noise
Suppose that ( p)  (1 ,, p ) is coefficient
vector.
Let  be the above autoregressive model. Then
this parameter  can be written as

generally unknown. Let x t be a time series with  (p, ( p) , )t  1,2, , n and n be a number of samples. An
AR(p) with exponential white noise can be
expressed as:
p
(1)
x 
 x zSuppose that is a data. This data is taken from a
population having a autoregressive model withexponential white noise. Based on this data, themain problem is how to estimate the parameter  .
This paper aims to estimate this parameter  .

t



i 1

i

t i

t

where p < n and thez t ( t  1, , n ) are
103

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

METHOD

Prior Distribution

The parameter  is estimated by using Bayesian
method. For this, a likelihood function is determined.

Before obtaining a posterior distribution, a priordistribution must be selected. The prior distribution
is taken as follows. A binomial distribution ischoosenforanumberoforder

Likelihood Functionp ( p  1, 2, , p max )Because the random variabel z t( p )  C pp max  p (1  ) p max  p

has anwhere p max is a maximum of p and  is an
hyperparameter. A uniform distribution is choosen

exponential distribution with parameter  fort  1,2, , n , the density function of z t isf (z t )   exp z t

for a coefficient vector r

(2)

used.

z t  x t  i 1 i x t i
p

Then

dz t
1 .
dx t

Let

and

Furthermore, a hyperprior distribution for  is a
uniform distribution.
Let (, ) be a prior distribution for (, ) .

x  (x1 , x 2 ,, x n ) be arealization vector of AR(p) with exponential error.

Because the distribution ofThus, the density function of x t isf ( x t )   exp  ( x t  i 1 i x t i )p

( ) 

(4)

that

y0  (x1, x 2 ,, x p )np

Posterior Distribution
Let (, (5)Sp be a stationary region and ry) be a posteriori distribution for(, ) . According to the Bayesian Theorem theposterior distribution for (, ) is given as follows(6)

(,  y)  f ( y )(, )

for t  p  1,2, , n , with a initial value y 0 . Let
( p)

(12)

and

where

g( t , p, ( p ) )  x t  i 1 i x t i(, ), the prior distribution for()(, )  ( )()y  ( x p 1 , x p  2 , , x n ) . Then the likelihood
function of x can be approximated by:L( y )  n p exp t p1 g(t, p, ( p) ) given  is(, ) can be written as follows:

for t  1,2, , n .
Suppose(10)

Also, a uniform distribution is choosen for aparameter (11)( )  U (0,1)

(3)

p

is

( p)

(r ( p) p)  U(0,1)p

The variable transformationx t  i 1 i x t i  z t(9) f ( y )(, ) ( )() (r1, r2 ,, rp )(13)

Unfortunately, the Bayesian estimator cannot be
determined analytically because the posterior
distribution of parameter θ has a complicated form.
To overcome these problems, reversible jump
MCMC Algorithm [9] is used.

be a sample partial autocorrelation vector. By using
a transformation(7)
F : ( p )  S  r ( p )  [1,1]ppthen the AR(p) model is stationary if and only ifr ( p) [1,1]p . Finally, the approximated likelihood
function of the x can be written by:(8)
L( y )  n  p exp  ni p 1

Reversible Jump MCMC
Suppose that M  (, ) . An MCMC method forthe simulation of a distribution (, g(t, p, F1 (r ( p) ))where   (p, r ( p) , ) andy) is amethod producing an ergodic Markov chainF1 is a inverse

M1, M2 ,, Mm whose stationary distribution(,  y) . This Markov chain M1, M2 ,, Mm

transformation of F .

104

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

can be considered as a random variable whose(,  y) .

distribution iscurrent point and   (p  1, r*

Furthermore, thepoint.

Markov chain M1 , M2 ,, Mm is used to estimate
the parameter M. To realize this, the Gibbs samplingalgorithm is adopted. It consists of five steps:
Simulate  ~ B(p  1, p max  p  1)

Simulate  ~ G (, ) with   n  p  1and  (p  1, (p)point   (p, r* p and create a new

*

(p )

) withprobability of acceptance for birth of order and deathof order. The probability of acceptance for birth is asfollows:* ( , y) q(* , ) 
a n (,  )  min 1,*  ( , y) q(,  ) *While the probability of death is as follows:
1a d (, * )  min 1,* a n ( , ) 

algorithm [9] is adopted.

) be an actual point of) is defined in

Suppose that a n and a d are respectively a(p, r ( p) y, , ) . Here, reversible jump MCMC
( p)

from

r  r1 , ..., rp**  rp

not an explicit form. The exact simulation is notpossible to be done. Since the value p is not known,
the MCMC algorithm cannot be used to simulate

Let   (p, rorder( p* )*
1y, , ) is( p)) is a updated

the) to   (p, rthe following way. Set p) ~ (p, r ( p ) y, , )

Unfortunely, the distribution (p, r

of
*

*

p

Simulate ( p, rdeath
( p1)  t p1 (x t  i1 F1 (ri )x t i )nThe

( p* )

thewhere

Markov chain. There are 3 types of transformations
are used, namely: a birth of the order, a death of theorder and a change of the order. Furthermore, let
N p be the probability of transformation from p to p(* , y)( , y)* n pD k 1 ( )p 1
1n  p 1Nk n  p p max  pandq (* , ) 1
q (, * )+ 1, let D p be the probability of transformation fromp + 1 to p, and let C p be the probability oftransformation from p to p.

Change of the Coefficients
Birth/Death of the Order
The transformation of the change of order will notchange the number of coefficients. Thistransformation makes to change the value ofA transformation of the birth of the order willchange a number of coefficients, from p to the p + 1.
Suppose that   (p, r*  (p  1, r
the

order

*  (p  1, r
Set

( p* )( p)*  (p  1, r*

  (p, ( p) )

Next,

a

new

*  (p, r

point

*

) to

) is defined in the following way. Set( p* )) is created withr1*  r1 ,.., ri*1  ri 1 , ri*  u , ri*1  ri 1 , rp**  rp

Otherwise, the transformation of the death of theorder will change the number of coefficients, from
Suppose that   (p  1, r

( p* )

new point   (p, r) withr1*  r1 , ..., rp** 1  rp , rp**  

p+1 to p.

) is a updated point. The

p*  p , choose a random point i  1,2,, p ,and choose a random point u ~ U ( 1,1) . Then a

*

(p )

) is a current( p1)

choose a random point
create( p* )( p)change of the coefficient from   (p, to) is defined in the following way.

p*  p  1 and ~ U (1,1) .

point and   (p, r) is a updated point. The birth offrom( p* )

coefficients. Suppose that   (p, r) is a current point and( p 1)

Let a p be a probability of acceptance to a changeof coefficient. Then the probability of acceptance forchange is as follows:) is a105

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017* ( , y) q(* , ) a p (, * )  min 1,*  ( , y) q(,  ) 

of research strenghthening and development,Indonesian Ministry of Research and Higher
Education (Kemenristekdikti), that has given the
grant to present in this international conference. The
author would also like to thank the Ahmad Dahlan
University (UAD) that has supported the grant forthis research.

where *  
( , y)   (* , y)

andREFERENCES

q (* , )1q (, * )[1] Zhang R and Ling S, Asymptotic Inference for
AR Models with Heavy-Taliled G-GARCH
Noises, Econometric Theory, 2015, 880-890.
[2] Jureckova J, Koul HL, and Picek J, Testing thetail index in autoregressive models, Annals of
the Institute of Statistical Mathematics, 2009,579-598.
[3] Novkovic M, On Exponential Autoregressive
Time Series Models, J. Math, 1999, 97-101.
[4] Pereira IMS and Amaral-Turkman MA,
Bayesian prediction in threshold autoregressivemodels with exponential white noise, Test, 2004,
45-64.
[5] Larbi L and Fellag H, Robust Bayesian Analysisof an Autoregressive Model with Exponential
Innovations, Afr. Stat., 2016, 955-964.
[6] Ibazizen M and Fellag H, Bayesian Estimationof an AR(1) precess with exponential white
noise, A Journal of Theoretical and Applied
Statistics, 2003, 365-372.
[7] Suriyakat W, Areepong Y, Sukparungsee S, andMititelu G. On EWMA Procedure for AR(1)Observations with Exponential White Noise.
International Journal od Pure and Applied
Mathematics, 2012, 73-83.
[8] Shi Z and Aoyama H, Estimation of theExponential Autoregressive Time Series Modelby Using The Genetic Algorithm, Journal ofSound and Vibration, 1997, 309-321.
[9] Green
PJ,
Reversible
Jump
MCMC
Computation
andBayesian
Model
Determination, Biometrika, 1995, 711-732.

RESULTS AND DISCUSSIONSThe transformation in equation (7) is used in orderto get a stationary conditions for AR model. First
result of this paper is a AR model that is obtained isalways stationary. The hierarchical Bayesian isadopted to estimate the order of AR model, thecoefficient of AR model, the variance of the white,
and its hyper parameter. The second result of thispaper is both the order of AR model and thecoefficient of AR model can be estimatedsimultaneously.
CONCLUSION
The purpose of this paper was to estimate theparameters of AR model with exponential white
noise when the order is unknown. The parameters
cannot be estimated by Markov chain Monte Carloalgorithm, because the order of AR model is
unknown.
The reversible jump Markov chain Monte Carloalgorithm is one of the new methods that can beused to estimate the parameters of AR models
although an order of AR is unknown. The advantageof this method is both the order of AR and thecoefficient of AR can be estimated simultaneously.

ACKNOWLEDGEMENTS
The author would like to thank the program offoreign seminar aid (BSLN), the General Directorate

106Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

ECOLOGY AND CONSERVATION OF INDIAN HORNBILLS WITH
PARTICULAR REFERENCE TO NARCONDAM HORNBILL (ACEROSNARCONDAMI) OCCURRING ON NARCONDAM ISLAND OF
ANDAMAN& NICOBAR ISLAND ARCHIPELAGO
Hafiz S.A. Yahya
Department of Wildlife Sciences, A.M.U. Aligarh, India
E-mail: has.yahya@gmail.com
ABSTRACT
Hornbills are old world birds with pan tropical distribution. Out of 54 species of hornbills found indifferent parts of the world, only two species of South Africa are ground dwellers. Hornbills are mainly fruit
eating birds but during breeding season feed varieties of animal matters to their nestlings and to the confined
females inside the natural tree holes, entrance of which is sealed by the pair all along except a thin slit throughwhich males provide food and females drop out the fecal matter. On account of rapid decline of their suitable
foraging and nesting habitats, most Indian species of hornbills are facing various categories of threats. During
my almost four decades of observations on avian communities in India I have opportunities of studying thehornbills at various sites, more particularly on ecology and biology of Narcondam Hornbills occurring only ona small island (6.8 sq. km)in the Andaman archipelago. Although their present population density is good, they
are quite vulnerable to any anthropogenic or natural catastrophe such as tsunami. This paper entails accounts ofecology, distribution and conservation issues of Indian hornbills with especial reference to Narcondam Hornbill.

Key words: Indian Hornbills, Narcondam Island, Ecology and Avian Conservation

INTRODUCTION
By virtue of encompassing large tract ofland, diversified bio-geographical zones and varied
climates, India’s biodiversity vis-à-vis avian
diversity is very rich. The hornbills are a prominentgroup of birds well adapted in variety of habitats
and providing immense ecological services. Out of
54 species found in Asia and sub-Saharan Africa(el Hoyo et al 2001), 10 species are found in India.
According to Kemp (1995), the hornbills are mostrecognizable group of all birds belonging to Order
Coraciiformes under the Family Bucerotideae with
14 Genera, 54 species and 78 Taxa. Although their
phylogeny is rather established, according to new
taxonomic arrangement some changes innomenclature and arrangement may be inevitablein many avian groups of birds (Jente et al 2016) as
well as in hornbills. The Hornbills are largely
arboreal birds (Sub-Family Bucerotineae) but a few
African species are ground dwelling too (SubFamily Bucorvineae). The hornbills chiefly
consume fruits and berries and help in seeddispersal; they also eat variety of animal matters insects, small vertebrates and a few even scavenge

on large animal carcass. Most hornbills possesslarge bills with remarkable casque that makes themunique in the avian community. Only toucans ofSouth America possess such massive bills.
Hornbills are mostly sedentary, move only locallyin search of food, at times to considerable distances.
The breeding habits of the hornbills are also unique.
They nest in natural tree holes and the femalesconfined themselves by plastering the opening of
the hole. Only a small slit is left through which themales keep feeding the female and the nestlings.
After the nestlings are able to fly, the opening isbroken for fledging of the occupants.
DISTRIBUTION OF INDIAN HORNBILLS
Indian Hornbills are widely distributed(Table 1). Being large and conspicuous birds theirmorphology, distribution, general habits and habitat
have been described variously (Ali 1941, Ali &Ripley 1974, Mundappa 2000, Baker 1927, Datta
2000, Kannan& Douglas 1997, Grimmettet al 1998,
Ranjit et all 2011, etc.).
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Narcondam Hornbill

RESULTS AND DISCUSSION

Narcondamis a small island in Bay of
Bengal (130.27 N& 94.17 E; Fig.1) comprising
about 6.8 sq.km; 114 KM from Port Blair towards
Myanmar; the Coco Island of Myanmar is only
about 40 KM from Narcondam. From defense pointof view, the Island is quite strategic and hence a
party of 15 policemen camp on the island while theIndian Coast Guard keep constant vigil in thevicinity. The Island is lofty peak rising out ofdeep waters of the sea with the highest peak of
about 900 meters. Generally, it is an evergreen typeof forest lashed by heavy rains during two
monsoons (SW & NE), temperature varying 22 to
27 degree Celsius. It was declared as Narcondam
Bird Sanctuary under Wildlife Protection Act 1972
and an Important Bird Area in 2004 by Birdlife
International.

Among other 23 avian species recorded on
this Island, Narcondam Hornbill is the mostpopulous and vociferous bird. The second mostcommonspeciesisAndamanKoel(Eudynamisscolopaceadolosa) but it is an
intrigue that how this brood parasitic bird isflourishing on this island where none of the 23
resident birds (Yahya & Zarri 2000) look likeappropriate host for the Koel; neither any suchspecies can visit the Island for breeding due to its
remoteness and inaccessibility.
In comparison to other hornbills, theNarcondam Hornbill has been least observed
because of the inaccessibility to the Narcondam
Island and difficulties in obtaining the permission
to visit the island. Therefore, so far only a few
ornithologists have contributed meaningfully on
ecology and biology of Narcondam Hornbills(Abdul Ali 1976, Cory 1902, Hussain 1984,
RaviSankar&Vijayan, 1998, Vivek&Vijayan 2003,
Yahya&Zarri,.2000 & 2002 and Yahya 2012).
Details of our observations as given in Reference
section; a summary is given below:

METHODS OF STUDY
Observations on feeding habits, groupstructure, nest feeding, population density andother behavioral aspects of the Narcondam
Hornbill were made in Feb- March 2000. Linetransect and point count methods were adopted toestimate population density and program
TRANSECT was used for the analysis of data. Nest
feeding by breeding males (Fig. 2 & Fig. 3) wereobserved in 3 shifts of 4 hours daily to cover theentire day at three nests. Foods items wereidentified directly on the fruiting trees andindirectly by collecting the debris of the seeds
thrown down by the females. Density of fruiting
and nesting trees were estimated by Point Circular
Quadrate
method.
The
vegetationatNarcondamisland is quite thick comprising large
trees, thorny bushes and climbers. A herbarium of
main trees and shrub were collected and identified
with the help of botanists at the Botanical Surveyof India Office at Port Blair.

As per our observation the population of
the N. Hornbill was 423, whereas Vivek andVijayan (2003) estimated their number about 300.
Such number is though stable considering the smallarea, it is not viable in long term survival becauseof possible inbreeding and confinement to a single
habitat. We collected considerable qualitative andquantitative data on nest feeding, foraging andother behavioral traits of the hornbills (Table 2). A
total of 20 pairs were recorded nesting while detailobservations were carried out at 3 nests. Naturallarge holes in tall trees were preferred between 5
and 35 m heights. Nest feeding started as early as
0440 hours and with an average of 2.5 visits perhour continued until late afternoon (1840 hrs.).
Most feeding was recorded in morning session. The
males carry 45 to 70 fruits in its throat and feed thefemale and nestling by regurgitation. It is alaborious work, especially during raining whenclinging to nest opening is very difficult.

Active nests were located by following thebreeding male hornbills and by checking tall trees
with natural tree holes. Like the study of breeding
biology of barbets (Megalaimaspp; Yahya 2001), attimes food begging calls of the nestlings whilefeeding by male hornbills also helped in locating
active nests. A lofted hide was made at nest
number 2 for regular observations and photography.
Feeding and other activities of the group of nonbreeding hornbills were also recorded during thestudy period (Table 1).

The non-breeding hornbills often gather inlarge numbers on fruit trees and besides feeding,
perform a number activities such as calling,fighting, chasing, preening and aerodynamics(Table 2). The Narcondam hornbills roosted infoliage of large trees and various pre- and postroosting activities such as loud calling andmovement in group on fixed route were performed.
The breeding males were often observed chasing108

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the White-bellied Sea eagle (Haliaeetus
leucogaster), that could be a potential predator of
fledgling hornbills. Watching hornbills performing
aerodynamics mostly in overcast weathers was
spectacular scenes. So far I have not observed such
behavior in other Indian hornbills.

Department and cooperation of the Police party
deputed at Narcondma Island during the study.
REFERENCES[1] Abdul Ali, H. 1976. “The fauna of
Narcondam Island.Part 1 Birds.” JBNHS
71(3): 496-505[2] Ali
Salim.
1941.“Bookof
IndianBirds”.Bombay Natural History Society.
[3] Ali, S. &Ripely, S.D. 1970. “Handbook of the
Birds of India and Pakistan .”Vol 4. Oxford
University Press, Bombay, London[3] Baker, E.C. 1927.“Fauna of British
India.Birds.”Vol. 4. Taylor and Francis
London[4] Cory, C.P. 1902. “Some further notes on
Narcondam Hornbill.” JBNHS 14(2): 372[5[ Datta, A. 2000.“Seed dispersal by Hornbillsin tropical forest in Arunachal Pradesh.”
Report XIV. Wildlife Institute of Indai,
Dehradun, India.
[6] Jente, Ottenburhs, Pim van Hooft, Spike E.
van, Ronal C Yenberg and Herbert, H.T.
Prins.“Birds in a bush: Toward an avian
phylogenetic network.”The Auk: 133. 2016,
Pp577-582.
[7] Kanan, R.an, R. & A.J. Douglas. 1997.
“Breeding biology of Great Pied Hornbill(Bucerosbicornis) in the Anamali Hills ofsouth India.”JBNHS 94 (3)[8] Kemp, A C. 1995.“The Hornbills”. Oxford
University Press, Oxford.
[9] Mundapa, D. 2000. “Breeding biology ofMalabar Grey Hornbill, in Southern Western
Ghats, India.” JBNH 97(1): 15-24.
[10] delHoyo, J., Elliott, A. and Sargatal, J.
(2001) “Handbook of the Birds of the World.
Vol. 6: Mousebirds to Hornbills.” Lynx
Edicions, Barcelona[11] Ranjeet, M., J.C. Daniel & Nikhil
Bhopale.“Birds of the Indian Subcontinent.”AFioeldGuide.Bombay Natural History Society& Oxford University Press, New Delhi.
[12] Sankar, R. andLalith, V. 1993. “The avifaunaof Andaman & Nicobar islands.” In A.
Verghese, S. Sridhar and A.K. Chakarvarthy(eds). Bird Conservation and Strategies in the
Ninetees and Beyond. Ornithological Societyof India, Bangalore.
[13] Yahya, H.S.A. &Zarri, A. A. 2000. “Status
and Behavior of Narcondam Hornbill at
NarcondamIsland.”Technical Report. 58 Pp.

CONCLUSION
Conservation of Indian Hornbills
Owing to rapid decline in content andquality of habits, like other groups of birds, thepopulation of most hornbills is declining in the
country except the Narcondam Hornbill. However,the future of this endemic and endangered species
is also quite vulnerable because about 300-400
birds occur only on a small island and any
catastrophe, such as a tsunami, may be detrimental
to their survival. The Narcondam Island is close toIndonesia which falls in severe seismic zone.
During 2004 earthquake and subsequent tsunami
biodiversity of several islands of Andaman andNicobar archipelago has been dented. I have given
somespecific
recommendationsfor
theconservation of Narcondam Hornbill earlier (Yahya2012): Besides other measures, the most important
step to safeguard the future of this important bird is
captive breeding and introduction of the species tosome ecologically similar and uninhabited island sothat alternate population is established.
To restore the habitat and reduceincreasing anthropogenic pressures, it is desirable
that a long term study is conducted to ascertain
present status of all Indian hornbills. Based on thedata thus gathered, the conservation efforts could
be prioritized. Forming a separate project – SAVEINDIAN HORNBILLS – should be launched by
the Ministry of Environment, Forests and Climate
Change with the collaboration of Birdlife
International. For sustainable future of Indian
biodiversity vis-à-vis avian diversity increase fromonly 4% land to at least 14% land under Protected
Area coverage is imperative.
ACKNOWLEDGEMENTS
While information on other hornbills weregathered during my several ornithological
expeditions, for the study on NarcondamHornbill I
am grateful to the British Ecological Society, U.K.
for funding. I am also indebted to officials of
Ministry of Defense, Ministry of Home Affairs,
Ministry of Environment & Forests and Inspector
General of Police, Port Blair for the needed
permissions. I am obliged for the assistance of Dr.
Ashfaq Zarri, the then research scholar of our109Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051[16] Yahya, H.S.A. 2012, “Ecology andConservation of Narcondam Hornbill,
Acerosnarcondamiin Andaman & Nicobar
Islands. In Ecology of Faunal Communities
on the Andaman & Nicobar Island.” Editedby : K. Vendataraman, C. Raghunathan W&
C. Sivaperuman, Springer Heidelberg, New
York, London. Pp.263 - 272

Dept. of Wildlife Sciences, A. M.U. Aligarh,
India.
[14] Yahya, H. S. A..& Zarri, A. A. 2002.“Status,
ecology andbehaviour of Narcondam Hornbill(Acerosnarcondami) in Narcondam Island,Andaman and Nicobar Islands, India.” J
BNHS Bombay 99(3): 418-433.
[15] Yahya, H.S.A. 2001.“Biology of Indian
Barbets.”Authorspress, New Delhi, The
Netherlands.
Table 1: Distribution of Indian Hornbills

SN
1

Common Name
Indian Grey Hornbill

Scientific Name
Ocycerosbirostris

Distribution
Widely spread, forests andgardens; almost throughout
subcontinent

2

Malabar Grey Hornbill

Ocycerosgriseus

Endemic to Western Ghats

3

Great Hornbill

Bucerosbiornis

4

Brown Hornbill

Anorrhinustickelli

5

Rufous-necked Hornbill

Acerosnepalensis

Mainly from Uttrakhand east
through
Himalayas
toArunachal Pradesh, N E
India & Western Ghats
North east India; mainly
upper Barhamputra valleys,also in Bangladesh
North east India, east Nepal
to Arunachal Pradesh, alsoin Bangladesh

6

Wreathed Hornbill

Acerosundulates

Locally fairly common in
low foothills west Bengal to
Arunachal Pradesh

7

Narcondam Hornbill

Acerosnarcondami

Endemic
Island.

8

Plain-pouched Hornbill

Acerossubruficollis

9

Oriental Pied Hornbill

Anthracocerosalbiros
tris

10

Malabar Pied Hornbill

Anthracoceroscorona
tus

EarliercommoninMargherita area in Assam,
now rare.
Residentfrom
Nepal
foothills
toArunachal
Pradesh,BhutanandBangladesh
Resident, subject to local
movement.

110

toNarcondam

RemarkSeen individually or insmall groups. Population
declining due to loss ofhabitatPopulation declining due
to habitat loss
Sporadically common inforests and well wooded
areas
Populations
declining
due to local poaching
and loss of forests
Locally common in
Bhutan; occasional in
Chittagong Hill tracts;
rare in Nepal
Population stable inIndian territories but
declining in earths whilerangesFlagship species on the
Island.
423
birds
estimated in 2000. See
text.
Globally threatened.

Locally common; keeps
in small groups and pairs

Common;use same nest
holes’ year after year; attimes fly in large groups;
flightfrighteningly
noisy.

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Table. 2. Group structure and activities of Norcondum Hornbill, March 2000

Date
March
2000

Time of observation
Start

End

Total
(min)

09
10
11
12
13
14
15
15
15
16
18
20
22
23
24
25
25
25
26
26
26
27
27
28
28
29
30

1650
0510
1200
1437
1645
1103
0600
0725
1517
0940
1610
1615
1530
1530
1612
0615
1215
1515
0542
0905
1150
0545
1340
0900
1600
1500
0555

1726
0543
1500
1705
1121
0645
0728
1529
0945
1700
1633
1610
1700
1620
0620
1230
1542
0724
0910
1203
0630
1445
0910
1630
1620
0558

36
33
23
20
18
45
03
12
05
50
08
40
90
08
05
15
37
96
10
13
45
65
10
30
80
03

NumberMale

Female

32
15
04
14
50
04
06
04
05
04
37
05
06
22
05
07
19
19
18
06
11
48
16
18
34
22
04

19
08
02
05
24
03
05
02
02
19
02
14
03
10
05
22
09
20
12
02

13
07
02
09
26
01
01
02
03
18
03
08
02
09
06
26
07
14
10
02

111

Activity

Calling preening moving
branch to branch (HopHop-Move)
Post-roosting feeding &displaysFlew across the valley
Actively feeding
Pre-roosting displays
frequent movements lessfeeding calling
Feeding actively
Feeding & aerial displays
Aerial displays
Active calling + Feeding
Flying high across valley
Pre-roosting activities
Pre-roosting activities
Parachute like dropping in
mid air about 60-70m
high
Aerodynamics +Preroosting activities
Mobbing the WhiteBellied Sea Eagle
Mobbing the WhiteBellied Sea Eagle
Aerial Movements
Feeding & Aerodynamics
Feeding & Aerodynamics
Crossed valley after rain
Active Feeding
Feeding + aerial
movements
Feeding + calling
Flew across valley
Pre-roosting activities
Pre-roosting activities
Aerodynamics

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Fig. 1. An enchanted view of Narcondam Island, eastern side

Fig.2. A male NH about to feed

Fig.3. A Male NH removing fecal matter from the rim of the nest.

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THE IMMEDIATE EFFECTS OF FOOT MASSAGE WITH COCONUT
SHELL ON PRESSURE PAIN THRESHOLD AND FOOT GRIP
STRENGTH IN HEALTHY SUBJECTS: A PILOT STUDY
Laojeenwong P1, Eungpinichpong W 2*
Division of Exercise and Sport Sciences, Graduate School, KhonKaen University.
Muang, KhonKaen 40002, Thailand
2
Back,Neck,and other Joint Pain and Human Performance Research Center, KhonKaen University.
Muang, KhonKaen 40002, Thailand,*e-mail wiceun@yahoo.com
1

ABSTRACT
Feet are very important parts of the body because they carry almost all of the body weight and contribute on
human locomotion. Daily works in prolonged standing position may cause foot pain and fatigue easily. Currently,
foot massage with coconut shells has been practiced in some eastern countries to relieve foot pain and fatigue forlong time without sufficient scientific evidence. This study aimed to preliminarily determine the immediate
effects of a foot massage with coconut shell on pressure pain threshold and foot grip strength in healthy subjects.
Thirteen healthy volunteers, who worked in standing position mostly, participated in the study and received a 5minute session of foot massage using coconut shells. Pressure pain threshold and foot grip strength were
measured before and 2 minutes after the foot massage. The results showed that foot massage with coconut shells
could increase pressure pain threshold and foot grip strength significantly (P<0.05). We suggested that footmassage with coconut shells may raise pressure pain threshold of the feet and provide better effort on footmuscles contraction. Further study with a randomized controlled trial was recommended to verify these effects.
Keywords: Coconut shells, Foot massage, Pressure pain threshold, Grip strength
threshold and foot grip strength in healthy subjects.
Methodology
Sampling site
Subjects who met the criteria were recruitedfrom students and staff at Prince of Songkhla
University, Thailand
Inclusion criteria
Subjects were included if they were healthy andaged between 20-35 years.
Exclusion criteria
Subjects were excluded if they met one of the
exclusion criteria:●Physical fatigue or fever●Pregnant women●Having menstruation●Hyper sensitive to pressure massage●An open wound in the footINTRODUCTION
Feet are major organs of the body that support
the weight of the whole body. They are always tiredor fatigue and pain after long hours of working inweight bearing positions such as standing andwalking. A study found prolonged standing may
decrease pressure pain threshold of the feet (Messing
K, Kilbom A, 2001). Untreated foot discomfort andpain may lead to abnormal gait and prone to have
injury and falls especially in the elderly people. Footmassage is one of commonly used treatments forrelieving foot fatigue and pain. Moreover, based on
the theory of foot reflexology, foot massage on
specific zone on the feet may reflect to normalize thefunctions of the remote organs on the body such asheart and brain. It has been found that foot massage
may be helpful in maintaining health by reducing
muscle fatigue (Kim OJ and Kim IS, 2012) andbalancing the autonomic nervous system (Guan L etal., 2014). Some studies found foot massage may
have a positive effect on type 2 diabetes and exert abeneficial effect on lowering blood pressure andincontinence (Song, 2015), (McCullough, 2014)
Foot massage using coconut shells has beenpracticed in many countries in Asia for relieving
foot fatigue and reduce pain in lower extremities.
However, the effects of foot massage using coconut
shells haves not been reported.
The current study aimed to preliminary
determine study on the immediate effects of the footmassage using coconut shell on pressure pain

Measurement instruments and procedures●Pressure pain threshold (PPT)A calibrated pressure algometer (WE Algometer,
Thailand) was used to measure PPT of the feet. A
research assistant marked the ten locations onplantar surface of the feet for measurement of the
PPT. (figure 1). Each of the subjects was rested inprone lying position and carried a control switch of
PPT in a hand. Then, the research assistant carried
the handle of the algometer and gradually applied

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After the baseline were measured each subject
received 5 minutes of self-foot massage using
coconut shells and followed by 2 minutes rest on achair. To perform self-foot massage, the subject
stood on one foot while placing another foot of aprepared half-sized coconut shell and gradually
increasing pressure to the plantar surface of the footuntil he/she felt a little discomfort then releases thepressure. This procedure of self-foot massage had
been repeated for 2.5 minutes and ensures to cover
the whole area of plantar surface of the foot and thenswabbed to massage on another foot for 2.5 minutes.
After 2 minutes of rest on a chair, the subject wasmeasured again. The procedure of data collection
was summarized in figure 2.

perpendicular pressure through the probe on eachmarked location. When the subject had a sensationof pain distinct from pressure or discomfort (Fischer
AA, 1987) on the applied pressure location, he/she
pushed the stop button and got the reading of PPT.
At this point, the algometer pressure wasimmediately released. The measurement was done
twice and the average of the readings was recorded.

A

13Eligible subjects (N=13)

B
Fig. 1 Measurement of PPT. (A). Plantar surface ofthe foot with the 10 marked at the locations formeasurement of PPT10 test locations (B).

Health assessment and informed

Pre –test☻Pressure pain threshold☻foot grip strength●Foot grip strength
Isometric measurement of foot grip strength was
performed using a Toe Grip Dynamometer (TAKEISCIENTIFIC INSTRUMENTS CO., LTD, Japan).
Each of the Subjects was instructed to stand uprighton the measuring plate where both feet were placedshoulder-width apart. The handle of the force meteror grip bar was set underneath the 1st
metatarsophalangeal joint and the heel stopper was
adapted to fit the heel of the participant. When, thesubject was ready to start, the dynamometer was set
to zero. Then the subject was asked to squeeze andpull the grip bar with the toes as hard as possible andget the reading. After the adequate number ofpractice and rest, the actual toe grip strength wasmeasured twice, each time maintained the maximal
force about 3 seconds and rested 10 seconds
between times, the mean value of the foot grip
strength was calculated (Uritani et al., 2014; Uritani
et al., 2015). Using this method of measurement,
Uritani et al. (2012) reported that the interrater
reliability of foot grip strength was high in young
adult and middle-age adult (ICC=0.76-0.95).

Standing on the coconut shell
5 min/Rest 2 min
Post –test☻Pressure pain threshold☻foot grip strength
Figure 2 A diagrammatic representation of datacollection procedure.
Data analysis
All data were expressed using descriptive
statistics as the means and the standard deviation(mean ± SD). Pair t-test was used to compare
outcome measures between baseline and after thetreatment. All p-values were two-tailed, and thelevel of significance was set at 0.05. All statisticalanalysis was performed with IBM SPSS statistics 20
software (SPSS Inc., Chicago, IL, USA)RESULTS AND DISCUSSION
Demographic data of the subjects was presented inTable 1. Most of the subjects were females, aged
ranged 20-30 years, and had normal range of bodymass index.

Procedure
After the participants underwent screening
procedures by interview, they gave inform consent.
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Table 1 Characteristics of healthy subjects.
Item
Sex
Age

Weight (Kg)

Height (cm)Body massindex(kg/cm2)

FemaleMale
20 – 25
26 - 30
41 -50
51-60
61-70
71-80
81-90
91-100141-150
151-160
161-170
171-180< 18
18.5– 23.4
23.5– 28.4
28.5– 34.9
35.0– 39.9
> 40

N=13

Percentage

8
5
3
10
5
3
3
1
1
1
8
2
2
1
8
3
1
-

62
38
23
77
38
23
23
8
8
8
62
15
15
8
62
22
8
-

reading and well calibrated, it was unlikely that thesmall effect sizes were due to the instrumental error.
Table 2 Pressure pain threshold (PPT) measured
on the plantar surface of the foot with at the 10 test
locations.
Mean PPT (kg/cm2)
Baseline

Post

Difference

p-value

5.44 ±

5.12± 1.67

-0.32

0.001*

4.55±1.96

0.1

0.001*

4.16± 1.83

-0.33

0.001*

4.71± 1.78

-0.19

0.001*

4.82± 1.72

0.05

0.001*

5.25± 1.98

0.21

0.001*

5.29± 1.95

0.22

0.001*

5.28± 1.99

0.11

0.001*

5.13± 2.02

0.32

0.001*

5.23± 1.95

0.24

0.001*

6.25± 1.99

0.65

0.003*

5.29± 1.92

0.24

0.005*

4.86± 1.74

0.28

0.008*

5.38± 1.53

0.2

0.004*

5.21± 1.59

0.18

0.082

5.59± 1.94

0.35

0.021*

5.74± 2.03

0.44

0.001*

5.70± 2.18

0.39

0.001*

5.53± 2.04

0.37

0.002*

5.80± 2.05

0.33

0.006*

Location
P1

1.98
P2

4.45±
1.70

P3

Left
(Kg/
cm2)

4.49±
1.89

P4

4.90±
1.91

P5

4.77±
1.58

P6

5.04±
2.04

P7

5.07±
2.29

P8

5.17±
2.42

The results of the paired t-test revealed asigniﬁcant changes in PPT mostly after the treatment(P < 0.05) (Table 2). PPTs of the left leg wereincreased at Seven out of ten locations (p≤0.5)
whereas three locations were decreased. The low
PPT at location P1, P3, P4 after foot massage may
be due to over pressure during procedure of applying
foot massage using the coconut shells. For the rightfoot, almost all the locations (9 out of 10) were
found with significantly increased in PPT after
having foot massage. It was noted that at P5 the
PPTs were not significantly increased for both feet.
This may be due to the location of P5 that wasunderneath the first metatarsal joint and has lessmuscle mass than the others. The response to footmassage was lower than the locations with relatively
more muscle mass in the foot. The intrinsic musclesof the feet that were prone to get fatigue during
stance may respond to massage quicker than the areawith less muscles. Although, the results of thecurrent study were in line with those of previous
studies, it was also noted that the overall changes in
PPT after foot massage were less than 1 kg/cm2.
The effect size was relatively small which may be
due to a single session of foot massage may provide
small effect. If more sessions of foot massage wereadministered, more effect size may be occurred. The
algometer being used to measure (PPT) in this study
had high precision with two decimals of digital

P9

4.81±
2.21

P10

4.99±
2.20

P1

5.60±
2.19

P2

5.05±
2.39

Right
(Kg/
cm2)

P3

4.58±
1.94

P4

5.18±
2.21

P5

5.03±
1.84

P6

5.24±
2.11

P7

5.30±
2.12

P8

5.31±
2.35

P9

5.16±
2.31

P10

5.47±
2.31

*sig p<0.05
The result from paired t –test of foot grip strength
revealed significantly different after foot massage.
(p<0.05) (Table 3). The higher score of foot grip
strength after foot massage reflected that less fatigue
115

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

ACKNOWLEDGEMENTS

so that the subjects could exert more forces thanthose of baseline.

This project is supported by Traditional Thai
Medicine Hospital, Faculty of Traditional Thai
Medicine, Prince of Songkla University, Thailand.

Table 3 Foot grip strength.
Mean foot grip strength
Location

Baseline

Post

Difference

REFERENCES

pvalueLeft

12.74±4.32

13.79±2.80

1.040.001*

Right

13.12±4.4215.54±4.572.330.001*[1] Messing K, Kilbom A. Standing and very slow
walking: foot pain-pressure threshold,subjective pain experience and work activity.
Appl Ergon. 2001 Feb;32(1):81-90[2] Kim JO, Kim IS. [Effects of aroma self-footreflexology massage on stress and immune
responses and fatigue in middle-aged women inrural areas]. J Korean Acad Nurs. 2012
Oct;42(5):709-18.
[3] Guan L, Collet JP, Yuskiv N, Skippen P, Brant
R, Kissoon N. The effect of massage therapy on
autonomic activity in critically ill children. Evid
Based Complement Alternat Med.
2014;2014:656750[4] Fischer AA (1987) Pressure algometry overnormal muscles. Standard values, validity, andreproducibility of a pressure threshold.
Pain.30:115–126.
[5] McCullough JE, Liddle SD, Sinclair M, Close C,
Hughes CM (2014) The physiological andbiochemical outcomes associated with areflexology treatment: a systematic review. Evid
Based Complement Alternat Med.2014:502123.
[6] Song HJ, Choi SM, Seo HJ, Lee H, Son H, Lee
S (2015) Self-administered foot reflexology forthe management of chronic health conditions: asystematic review. J Altern Complement Med.,
21(2), 69-76.
[7] Uritani D, Fukumoto T, Matsumoto D, Shima
M (2015) Associations between toe grip
strength and hallux valgus, toe curl ability, andfoot arch height in Japanese adults aged 20 to79 years: a cross-sectional study. J Foot
Ankle Res 8(1): 1-6[8] Uritani D, Fukumoto T, Matsumoto D (2012)
Intrarater and interrater reliabilities for a toe
grip dynamometer. J Phys Ther Sci 24: 639–43.
[9] Uritani D, Fukumoto T, Matsumoto D, Shima
M (2014) Reference values for toe grip strength
among Japanese adults aged 20 to 79 years: acrosssectional study. J Foot Ankle Res
7: 1-6.
[10] Eungpinichpong W, Montri N(1999) Basicphysiological effects of modified foot massage.
J Med Tech Phys Ther 11: 98-105.

*sig p<0.05
The purposes of this study preliminarily
determined the immediate effect of a foot massage
with coconut shell on pressure pain threshold andfoot grip strength in healthy subjects. To ourknowledge, this is the ﬁrst study on f the effect of afoot massage with coconut shell on plantar surface
muscles after immediate. This study showed asigniﬁcant increase in pressure pain threshold, andfoot grip strength after treatment compared withscore. The increase in nearly PPT after foot massage
may be a sign of recovery from muscle fatigue andlet the subject exert more muscle power thanbaseline and have more foot grip strength on bothfeet. The findings of this study were consistent withthe study of Eungpinichpong W et al (1999) whichfound that foot massage increased blood circulation,
reduce the tension and pain of the muscles, andincreases the skin temperature in area being
massaged. Some limitations of this study were noted.
First, this was only a pilot study in 13 healthy
volunteers. Small sample size may provide
limitation on conclusion. Second, the pre-post study
design in this study could not provide a definite
conclusion. However, results of this study could
provide a clue that foot massage with coconut shell
may result in immediately increased pressure pain
threshold, and foot grip strength. Finally, we also do
not know the long-term effects.
CONCLUSION
Based on the results of this study, we conclude
that the foot massage with coconut shells may
increase the (PPT) and foot grip strength. Further
study with a larger sample size and randomized
controlled trial is needed.

116

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

MOCAF TEMPEH DATES BISCUIT FOR THE IMPROVEMENTNUTRITIONAL STATUS OF UNDERWEIGHT CHILDREN
1

Fatmah1
Public Health Nutrition Department, Faculty of Public Health, Universitas Indonesia, Depok City, West Java
Province, Indonesia

ABSTRACTThe prevalence of PEM (Protein Energy Malnutrition) in toddlers in Indonesia has increased due to lower macronutrient intake and exposure to infectious diseases. Therefore, it is necessary to intervene with supplementary
feeding in the form of highly nutritious food products, such as biscuits made from flour enriched from mocaf fromsoybean and date jam. The effects of mocaf tempeh dates biscuits were investigated in villages within the Cinere
District and the Pancoran Mas District in Depok City. The study was conducted to assess the effects of consumptionof mocaf tempeh dates biscuits with the nutritional status of KEP toddlers. Approach: Randomized Controlled Trial(RCT) with pre-post tests were used with 70 subjects, divided into 3 groups: 27 subjects in the treated group (mocaf
tempeh dates biscuits), 26 subjects of control group 1 (tempeh dates biscuits), and 17 subjects in control group 2(placebo biscuits). The intake of energy, protein, and fat, along with haemoglobin (Hb) examination and blood
albumin were collected pre-post intervention. Results: A change in weight of 0.4 kg was found in the intervention
group. The highest increase in height was found in control group 1 (1.7 cm). An increase in blood hemoglobin levelsof 0.1 points were found in the intervention group and the control group 1. The albumin was decreased by 0.3 points
in the intervention group. Weight gain in the intervention group was influenced by macro-nutrient intake. Intake ofvitamin A, Fe, and Zn affected blood hemoglobin levels in post-intervention with the intervention group.
Conclusion: Mocaf tempeh dates biscuits can be consumed by underweight children as an alternative food of
Nutritional Supplementation Program.
Keywords: Mocaf Tempeh Dates Biscuits, Weight, Height, Hemoglobin, Albuminheight of 0.7 kg and 1.7 cm, and 0.4 kg and 2.4 cm,
respectively [9-10]. Further, there are significant
differences between the consumption of biscuits inthe study that spanned six weeks in Ease Jakarta on
the change of weight and height of toddlers.
Referring to the findings of the above study, it isclear that a study of the development of local foodproducts in Indonesia that are easily available ataffordable prices is warranted. One possibility is theuse of the base material of mocaf biscuits since it is
widely used as an additional food product in PMT for
malnourished toddlers in Indonesia. This study has
developed a biscuit made from a flour mixture ofmocaf with tempeh and date jam. Mocaf is derived
from extracts/cassava extract, which is chosen as thebase material of biscuits because it has become afavorite food of Indonesian people, especially in Java.
Tapioca processed foods from cassava (one of thestaple food in Indonesia) should be consumed withcomplimentary foods due to its lower protein content
and the presence of phytic acid that inhibits iron (Fe)and zinc (Zn) absorption. Excessive consumption oftapioca without consuming other nutrients will cause

INTRODUCTION
The lack of energy/calories and protein in the
nutrition of toddlers increases morbidity andmortality and is a significant public health concern inIndonesia. In developing countries, approximately
60% of deaths occur in children under five years’ old
due to malnutrition [1]. In general, KEP in toddlers
presents higher levels of hemoglobin (Hb) and lower
albumin due to a decrease in protein content in the
blood and body tissues [2]. One of the preventive
efforts is through supplementary feeding recovery(PMT). The PMT food form preferred by children isa biscuit and PMT for toddlers in this from proved tobe quite effective and significantly improve
nutritional status [3-7]. Other studies have also
shown an increase in the nutritional status of children
under five with an increase in weight and height of
1.3 kg and 0.7 cm, respectively over four weeks
through the supplementation of tempeh dates biscuits[8]. Similar studies on malnutrition in children underfive who suffered from Tuberculosis (TB) in Depok
and in East Jakarta show an increase of weight and117

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

the body to become deficient in several nutrients [11].
Therefore, tapioca must be balanced with other foods
that are high in protein, such as soybean flour, andiron and zinc, such as dates, in order to prevent
severe anemia in KEP toddlers. Malnourishedtoddlers generally have low hemoglobin levels so that
there is an interaction between the low nutrient status
with infectious diseases [12]. This study was
conducted in the district and sub-district of Cinere
and Pancoran Mas, Depok City, which have thelargest PEM toddler prevalence in Depok (10.6%). A
prevalence of greater than 10% is considered asignificant public health issue [13] Moreover, theproportion of children under five (KEP toddlers) inthis district in Depok has exceeded 5.31% [14]. It
was hypothesized that there would be effect of
supplementation with protein-enriched mocaf biscuits
from soybean flour and iron and vitamin C levels
from date jam to changes in anthropometry
weight/age (W/A) and the biochemistry of blood(hemoglobin and albumin) in KEP toddlers threemonths post-intervention.

A total of 70 samples were divided into three groups(mocaf tempeh date biscuits, tempeh dates biscuits,
placebo biscuits). 75 samples were originally enrolled
at the beginning of the study; however, five did notcontinue in the second week of the study for a varietyof reasons, including the toddler not wanting to eat
the biscuits, out of town travel or moving without
providing a forwarding address. he use of indicatorsof weight/age (W/A) in this study was based on theindicators of malnutrition status. Each subject
received 50 grams of biscuits per day for 12 weeks.
The children were differentiated into three groups:
the treatment group (mocaf tempeh dates biscuits)
and two control groups (tempeh dates biscuits andplacebo biscuits, respectively). Height and weight aswell as any presence of illness were monitored every
two weeks. Anthropometric measurements werecollected twice and daily recordings of foodconsumption were collected by enumerators throughhome visits as many as 24 times during the study.
Nutritional counseling was conducted twice byinvestigators with the mothers of the sample in thevillage office simultaneously with posyandu with themonitoring of the nutritional status in the form ofanthropometric measurements of samples. The
distribution of mocaf tempeh dates biscuits, tempeh
dates biscuits, and placebo biscuits were achieved
through home visits by a team of researchers andtoddlers cadres every three days at which time daily
food record forms (24 hours food recall) were alsocollected. At the end of the intervention, weight,
height, and blood samples were taken again. Weight
anthropometric data were measured using a digitalscale (SECA) by trained field workers. An indicator
Z-score of weight/age of less than −2 SD was used todetermine the status of children under five who had
malnutrition [13]. Basic data (baseline survey) werecollected at the beginning and at the end of the study
through direct interviews with a structured
questionnaire administered with the mothers. The
independent variables were toddlers’ weight before
research and the dependent variable was their weightafter the intervention. Confounding variables in thisstudy included demographic characteristics ofmothers and toddlers, mothers’ knowledge about
nutrition and intake of macro and micro nutrients.
The measurements for independent and confounding
variables were obtained once before the study. The
mothers’ knowledge of nutrition and height wereassessed before and after the study based upon meanscores. The educational background of mothers weredivided into categories of low and moderately long,an indicator of being educated for at least nine years
Weight anthropometric data samples were analyzed
by WHO Anthroplus software Version 02 of 2009

MATERIALS AND METHODS
A Randomized Clinical Trial (RCT) was used in thisstudy with 70 samples in Depok that have aprevalence of PEM (W/A) in toddlers, of which thelargest was in Depok with 10.6% [14]. Nutritional
interventions were conducted for three months from
May-July 2014. Ethical Clearance was obtained fromthe Research Ethics Committee of Research andDevelopment Agency for Health Care Ministry of
Health of the Republic of Indonesia. Initial screeningof nutritional status was done through anthropometricmeasurements of body weight (BW) in 100 KEP
toddlers based on the integrated health post
(posyandu) data of toddlers in April 2014. The
sample size was determined by the formula meandifference test two independent groups with weightgain samples from a previous study of 0.4 kg [8];significance level (Zα) by 1.96; and strength test (Zβ)
of 0.84. The minimum sample in each group wastherefore determined to be 15 toddlers. Participants
were selected through appropriate data from calendar
notes of posyandu cadres of the weighing resultsfrom the previous month. Inclusion criteria for the
study were male and female children aged between
12–56 months, a status of malnutrition (W/A) with aZ-score between −3 to −2 SD, not suffering from achronic or acute infectious disease and not currently
participating in the (PMT) Recovery and Counseling
Program either from the government (posyandu,
community health center, hospitals, and others),
private organizations, or local or international NGOs.
118

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

based upon indicators of W/A [13].Food
consumption data to assess the adequacy of intake ofenergy and protein with Nutri Survey were analyzed
and then compared to Nutritional Adequacy Rate in
toddlers aged 12–59 months (14). Univariate andbivariate data analyses were performed using SPSS
version 13. Test paired t-tests were used to assesschanges in the mean intake of energy, protein, fat,vitamin A, vitamin C, calcium (Ca), zinc (Zn),ferrous (Fe), weight, height, albumin and Hb pre- andpost-intervention in each group. ANOVA test wasused to assess the mean differences between variables
based on the group (among groups).

groups, except the control group 2 (p = 0.142).
Further, the mean measurement of Hb increased by
0.1 at the end of the intervention in the intervention
group and the control group 1. The albumin inintervention group decreased by 0.3 after threemonths of ingesting mocaf tempeh dates biscuits. The
toddlers in control group 1 did not show increased
levels of albumin and the toddlers in control group 2
showed an increase of 0.1 at the end of the study.
Mean albumin levels is significantly different in allgroups, unlike the case with the mean change in Hblevel. A significant difference in nutrient intake at theend of the study was found in the intervention groupand control group 1. Table 3 illustrates thedifferences in nutrient intake of macro andmicronutrients among groups. There are significant
differences in both macro-nutrient intakes of energy,
carbohydrate, fat, and protein and micronutrients.
This is in contrast with the current post-study inwhich the intake of energy and carbohydrates aredifferent among groups (p < 0.05). The intervention
group has energy intake, fat, protein, andcarbohydrate levels that are large compared with thecontrol groups. Whereas, the intake of Fe, vitamin A,
and zinc were the most widely consumed by thecontrol group 2. The intake of energy andcarbohydrate were significantly different at all thegroups after the intervention (p < 0.05).

RESULTS
Contents of Nutrition of Three Types of Biscuits
Table 1 describes the contents of macro-nutrients(energy, carbohydrates, protein, and fat) andmicronutrients (Na, Zn, Fe, and vitamin A) in threekinds of biscuits. Mocaf tempeh dates biscuits
contain the most energy, fat, and vitamin A comparedwith the other types of biscuits. The placebo biscuits
contained the highest amount of carbohydrates.
Tempeh dates biscuits contained protein, Fe, and Zn
in larger amounts than the mocaf tempeh dates
biscuits and placebo biscuits. By consuming 50
grams of mocaf tempeh dates biscuits per day, theenergy sufficiency of a toddler aged 1–3 years would
be met with a fat content of between 22 % and 27%.

The Knowledge of Toddlers’ Mother about
Nutrition
The mothers’ knowledge concerning nutrition wasassessed by the following indicators: the compositionof a healthy diet; the benefits of eating a variety offood sources, including carbohydrates, protein, andfruit; the definition of healthy food; the meaning ofbalanced nutrition; the meaning of weight of toddlersthat remains the same or decreases and understanding
its cause; and the efforts that should be made by themother to increase the toddler’s weight. Most
mothers could describe the composition of a healthy
diet, which consists of a source of protein, vitamins
and minerals, but only few mention sources ofcarbohydrates, such as rice, noodles, bread, etc. aspart of a healthy diet composition. The mother's
knowledge about the meaning of balanced nutrition isstill very low as 17% of respondents rate that the “4healthy 5 perfect” (4 sehat 5 sempurna) as the slogan
of healthy food wa the same as balanced nutrition.
When asked whether or not mothers weighed theirbabies regularly every month, almost all said it was
important (95.7%). However, 25% of women statedthat the cause of their toddler’s static weight orweight loss was because the toddlers were often ill

Toddler Nutritional Status Change
Gender distribution of toddlers involved in this study
was almost equal between males and females, 54.3%
and 45.7%, respectively. The largest number ofchildren were between the ages of 12–23 months(38.6%) followed by 24-25 months of age (28.6%).
Changes in nutritional status of toddlers inanthropometric and biochemical are illustrated inTable 2. The increase in weight of toddlers was
slightly larger in the intervention group (0.4 kg) thanthe other two control groups (0.2 kg for control group
1 and 0.3 kg for control group 2). Weight before andafter the intervention showed significant differencesin all three groups (p = 0.05). Changes in body heightof 1.7 cm in toddlers who consumed the tempeh dates
biscuits and the placebo biscuits group are slightly
higher than the toddlers who consumed mocaf
tempeh dates biscuits (1.3 cm). Toddlers in theintervention and control group 1 initially had lower
nutrition status at the end of the normal nutritional
intervention based upon Z-score of W/A. Significant
differences were found on these indicators in both119

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017and had low food intake. Approximately one-third of
the mothers (37.1%) gave their child vitamins or anappetite enhancer when their toddlers’ weight was
low or did not increase. Therefore, this study
concluded low levels (58.6%) and sufficient levels(41.4%) of nutritional knowledge of mothers at theend of the KEP study. Upon further analysis, noeffect of changes in anthropometric and biochemical
nutritional status with the level of nutrition
knowledge of mothers was found at the end of thestudy (p > 0.05). Nonetheless, mothers with toddlers
who had sufficient levels of nutritional knowledge inall three groups were more likely to see theirunderweight children reach a normal weight after the
study intervention. Changes in the nutritional statusof children under five in the intervention group werebased on the indicators of weight/age which wasaffected by the intake of energy, protein, and fat (p <0.05). This indicator changed for toddlers in control
group 1, which was affected by the intake ofcarbohydrates and Fe (p < 0.05) and in control group2, which was affected by the intake of vitamin A, Fe,and Zn. Further, the intake of vitamin A, Fe, and Zn
affected the hemoglobin levels post-intervention in
the intervention group (p < 0.005). Meanwhile, aninfluence on the intake of macro and micro nutrientson changes in Hb levels at the end of the study incontrol groups 1 and 2 was not found (p > 0.05). The
same is also found concerning the influence of intake
of macro and micronutrients to changes in blood
albumin levels post- intervention (p > 0.05).

biscuits groups (control group 1) is affected by theincrease mothers’ knowledge on nutrition and TB
disease. Mothers’ knowledge on nutrition and TB
may be affected the level of tempeh dates biscuits
consumption, which affect on the height of the most
rapid increase in this group. This latter finding is
consistent with a similar study conducted in East
Jakarta [10] and studies in Sragen [15] and Ghana[16]. Mothers’ knowledge about nutrition was
significantly associated with the nutritional status ofher children. Specifically, the intervention ofnutrition education with families with children
underfive has shown to change the behavior of themother and the family in terms of feeding the childresulting in improvements in the nutritional status ofchildren [17]. The highest weight gained in the groupof mocaf tempeh dates biscuits in this study is in linewith the three previous studies [18-19, 10]. The firststudy proved that there are significant differences inweight and height through the provision of biscuits
from potato flour for undernourished children in
India over the course of months. The second study
was conducted with children underfive years’ old
who had malnutrition in Depok, which found aweight gain of 1.3 kg in the group consuming tempeh
dates biscuits over four weeks. The third study
proved that a multi-micronutrient in toddlers who had
malnutrition can improve the weight of toddler infour months.

DISCUSSION

The greatest weight gain (0.4 kg) was found in
toddlers who consumed mocaf tempeh dates biscuits,
while the largest increase in height (1.7 cm) was
found in toddlers who consumed tempeh dates
biscuits. It is recommended that mocaf tempeh dates
biscuits can be consumed by toddlers as analternative
food
for
PMT
recoveryforundernourished children in Depok.

CONCLUSION AND RECOMMENDATION

The total energy needs of children aged 1-3 years canbe fulfilled by 24.25%, 20% of carbohydrates
nutritional adequacy rate and 16.9% of protein
nutritional adequacy rate, if the toddlers consume 50
grams of tempeh dates biscuits per day. The most
rapid change in weight was experienced by thechildren who consumed tempeh dates biscuits(control group 1). The rapid increase in weight in theintervention group of mocaf tempeh dates biscuits
was caused by the intake of carbohydrates, which
was the greatest in this group compared to the twocontrol groups. The high intake of carbohydrates canbe obtained from the content of glucose and fructosein the dates that can be digested by the body anddirectly changed into energy. Fulfilling the needs ofcarbohydrates by 20% is derived from dates jam
consumption in toddlers 1 years’ old and 15%
carbohydrates in toddlers 4–5 years’ old. The
toddlers who consumed mocaf tempeh dates biscuits
showed an increase in height greater than the othertwo groups. The height increase in tempeh dates

ACKNOWLEDGEMENT
Our appreciation is extended to DP2M Higher
Education of Ministry of Education and Culture(DIKTI KEMENDIKBUD) for the funding of these
activities through the Research Grants of PUPT 2014
and also for Program Overseas Seminar of
Directorate General of Research and Development
Reinforcement 2017.

120

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

World Health Organization. PhysicalStatus:Uses
andInterpretationof
Anthropometry. WHO Technical Report
Series, Report No. 854. Geneva, Switzerland:World Health Organization, 1995
[14] Depok District Health Office. Report of The
Nutritional Status of Children Underfive Year
Depok: Depok DHO, 2011[15] Munthofiah S., 2008. The association between
knowledge, attitude, and practice of motherswith the nutritional status of children
underfive. Thesis. Solo: Postgraduate Facultyof Sebelas Maret University.
[16]Appoh LY, Krekling S. Maternal nutritional
knowledge and child nutritional status in the
Volta region of Ghana. Maternal Child
Nutrition 1(2), 2005: 100-10.
[17]Frost MB, Forste R, Haas DW.Maternal
education and child nutritional status in
Bolivia: finding the links. Soc Sci Med 60(2),2005: 395-407.
[18]Vasantha M, Gopi PG & Subramani R. Weightgain in patients with tuberculosis treatedunder directly observed treatment shortcourse (DOTS). The Indian Journal of
Tuberculosis, 56 (1), 2009: pp.5-9.
[19]Mursalim, Juffrie M., Sri Mulyani N.
Multimicronutrient fortification affecting the
growth of poor family chilren underfive. The
Indonesian Journal on Clinical Nutrition 8 (2),2011: 69-80.

REFERENCES[1] Faruque et al. Nutrition: basis for healthy children
and mothers in Bangladesh. Health Popul
Nutr. 26 (3), 2008: 325–339.
[2] Muller O. & Krawinkel M. Malnutrition andhealth in developing countries. CMAJ 173 (3),2005: 279-286.
[3] Fitriyanti. et al. Effect of recovery supplementary
feeding
forundernourishedchildrenunderfive.Scription. Semarang: Public HealthFaculty, University of Diponegoro, 2012.
[4] Kandarina J.I. et al. Effectivity of Giving Cassava
Flour fortified with ferrous among
elementary school children at Bantul District:effort to overcome micronutrient deficiency
local food based. Final report of National
Strategic Fund Year 2010. Yogyakarta:
LPPM UGM, 2010[5] Kurnia P. et al. Ferrous and zinc fortification
effect on biscuits made from tempeh and bran
combination to increase albumin level ofanemic and undernourished childen underfive
Explanation 5 (2), 2010: 10-23.
[6] Rivera J.A. & J.P. Habitch. Recovery of
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supplementary feeding. Am J Public Health 86(10), 1996: 1430-1434.
[7] Maleta et al. Feeding patterns of underweightchildren in rural Malawi given Supplementary
fortified spread at home. Matern Child Nutr 4(1), 2008: 65-73[8] Fatmah et al. Tempeh-dates biscuits effect on thegained weight of moderate underweightchildren. International Journal of Medicine
and Medical Sciences 2 (8), 2012: 165-172[9] Fatmah. The intervention of tempeh dates biscuiton the improved nutritional status of
tuberculosis preschoolers patients. The
Indonesian Journal on Clinical Nutrition 9 (4),2013: 147-154[10]Fatmah. Effect of tempeh dates biscuit on
nutritional status of preschool children withtuberculosis. Malaysian Journal of Nutrition
19 (2), 2013: 173-184[11] Astawan M. Cassava flour, benefit, and its
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[12] Sulaeman A., Deddy Muchtadi. The nutrient
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enriched with fish flour and tempeh flourMedia Gizi dan Keluarga 27(2), 2003: 77-85.
121SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Inclusion criteria:
New TB patients of children
underfive and or treated by TB
drugs at least 4 months, aged 12 59 bulan, having undernourishedstatus ( W/A z score < -2 SD), andmothers want to participate in the
study.

100 subjects candidates

80 subjects

Exclusion citeria:
TB patients children underfive
who have special diets and or
sufferingfromcertainchronical disesase. kronik
tertentu.

Purposive sampling

Intervention group
Mocaf tempeh dates biscuit(n=25)

Control group 1
Tempeh dates biscuit(n=25)

Control group 2:
Placebo biscuit (n= 25)

Baseline survey: sociodemography characteristic, nutrition
knowledge of mothers)
24 h food recal
Hb and albumin examination

Biscuits distribution @ 50 gr per day/subject
for 12 weeks
Nutrition education twice / month
Weighing twice / month

Drop-out of 8 subjects due to moving
out, went hometown, get bored, andmothers resigned from the study

Intervention group
Mocaf tempeh dates biscuit(n=25)

Control group 1
Tempeh dates biscuit(n=25)

Data analysis
Analisis data

122

Control group 2
Placebo biskuit (n=17)

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

Figure 1. Research scheme

Table 1. Nutrient value per 100 gr biscuit
Type

Energy(cal)

Tempeh dates
Mocaf tempeh dates
Placebo

490
495
462

Carbohydrate
(gr)
61.8
61.8
70.4

Protein(gram)

Fat(gram)

Na
(mg)

Fe
(mg)

Zn Vitamin A
(mg)
(IU)

9.62
5.80
5.03

22.7
23.8
17.8

267
460
-

1.9
1.3
0.6

1.9
0.9
1.3

139
155
< 0,5 IU

Source: BBIA Laboratory, 2014

Table 2. Mean change of subject’s antropometric and biochemical assessment
Indicator

Intervention (n=26)
Pre
Post

p

Group
Control 1 (n=25)
Pre
Post

p

Control 2 (n=17)
Pre
Post

p

Weight (kg)11.0 + 2.1 11.4 + 2.2 *0.001 9.1 + 1.0 9.3 + 1.6 0,001 9.3 + 1,6 9.6 + 1.5 *0.013
Height (cm)86.1+ 8.3 87.4 + 8.1 *0.001 76.7 + 4.3 78.4+ 4.3 0,001 81.0 + 8,3 82.7 + 7.9 *0.001
W/A (kg/m2) - 2.0 + 1.3 -1.5 + 1.4 *0.007 - 2.1 + 1.4 -1.4 + 0.8 0.001 -2.5 + 0.9 -1.9 + 0.9
0.142
Hb11.8 + 1.1 11.9 + 1.0 *0.001 11.9 + 0.9 12.0 + 0.9 0.001 11.6 + 0.7 11.5 + 0.9
0.114
Albumin
4.4 + 0.3 4.1+ 0.3 *0.003 4.3 + 0.4 4.3 + 0.4 0.036 4.2 + 0.2 4.3 + 0.3
0.013*p < 0,05

Table 3. Mean macro-micronutrients intake of subject
Group
Type of nutrient

Intervention
Mean + SD

Control 1
Mean + SD

Pre-intervention:
Energi (cal)Karbohidrat
Protein (gr)Fat(gr)
Vitamin A (IU)
Fe (mg)
Zinc (mg)1360.3 + 335.2
187.7 + 50.2
43.5 + 13.2
47.8 + 18.7
1027.9 + 515.1
14.5 +7.7
10.0 + 6.5

932.2 + 420.6
122.5 + 58.7
35.1 + 14.7
33.6 + 15.8
1172.8 + 1270,5
13.1 + 9.1
8.4 + 7.7

1184.1 + 426.3
144.1 + 50.1
40.9 + 17.9
48.9 + 20.8
939.5 + 541.4
12.0 + 9.6
9.9 + 6.8

*0.000*0.000*0.003*0,000
0.757
0.468
0.179

Post-intervention:
Energy (cal)Carbohydrate (gr)Protein (gr)Fat (mg)
Vitamin A (IU)
Fe
(mg)
Zinc
(mg)

1755.7 + 479.4
231.1 + 61.1
58.2 + 17.9
66.4 + 26.2
1076.6 + 682.7
18.2 + 13.9
13.7+ 7.3

1081.9 + 381.2
144.4 + 47.8
37.3 + 15.5
38.5 + 17.2
1301.5 + 1242.2
16.2 + 15.7
9.8 + 7.4

1258.2 + 351.1
160.4 + 64.5
43.0 + 13.5
52.1 + 18.2
1183.6 + 59.9
14.3 + 9.7
11.0 + 7.0*0.032*0.025
0.265
0.053
0.557
0.828
0.843

123

Control 2
Mean + SDpThird International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SPATIAL VARIATION OF WATRBIRDS IN PALLAI AND
THADDUVANKODDY IN THE NORTHERN PROVINCE, SRI LANKA
1

G. Kandasamy1*, D. K. Weerakoon2, and A. Sivaruban3
Department of Zoology,University of Jaffna 2Department of Zoology,University of Colombo,Sri Lanka
vadhana.gk@gmail.com
ABSTRACTThe Jaffna Peninsula is one of the main entry and exit points for migratory birds that use the Central Asian
Flyway. However, ornithological studies and Avitourism have been rare in the Jaffna Peninsula as the study area
was inaccessible for three decades due to the armed conflict. The present study was done to determine spatial
variation of water birds in two selected locations, Pallai wind farm in the Pachchilappalli DS division and
Thadduvankoddy in the Kandavalai DS division in the Kilinochchi district, Sri Lanka. Thadduvankoddy area lies
close to Chundikulam National park (24 km). The bird counting was done once a month, by walking along three
counting blocks of approximately 500 m x 500 m in each study site. Altogether 50 bird species belonging to 15
families were recorded in the study area, of which 47 species were recorded in Thadduvankoddy while 35
species recorded in Pallai. Out of the 50 bird species recorded, 32 species were shared between the two sites, 15
species were recorded only in Thadduvankoddy while three were recorded only in Pallai. A higher water bird
diversity was found in Pallai (Shannon Diversity Index: 2.41; Shannon Evenness Index: 0.68) compared toThadduvankoddy (Shannon Diversity Index: 2.13; Shannon Evenness Index: 0.55). A high number of Anas
penelope (1682 individuals) and Phoenicopterus ruber (1567 individuals) were observed in Thadduvankoddy
while Calidris minuta (303 individuals) and Phoenicopterus ruber (120 individuals) were the dominant species
recorded in Pallai during the study period. It can be concluded that Thadduvankoddy is an excellent place for thedevelopment of Avitourism in the Northern Province, Sri Lanka due to the presence of large number of migrantbird species.
Keywords: Spatial, Pallai, Thadduvankoddy, waterbirds
migrate from northern latitude, during winter in thenorthern hemisphere [26]. Most of the ducks, birdsof prey, and waders, reach southern tip of the India
along the eastern coastline, cross Indian Ocean andenter Sri Lanka [14]. Certain pelagic species migratefrom southern regions, during their winters, to theIndian Ocean, within the oceanic limits of thecountry [26]. Six species of off-shore bird species
are summer visitors in Sri Lanka [12].

INTRODUCTION
Waterbirds play an important role in energy
fluxes between aquatic and terrestrial ecosystem[05]. According to the Ramsar convention on
Wetlands, the term “waterbirds” is defined as
species of birds that are ecologically dependent on
wetlands [4] for variety of activities such as foraging,nesting, resting and roosting [22]. Migratorywaterbirds are important indicators of the ecologicalcondition and productivity of wetland ecosystem[16]. Sri Lanka is blessed with 441 species of birds
including 239 resident and 202 migratory birds, ofwhich,155 (35 %) are waterbirds [26]. According to
Wetland International, 21 out of 33 families ofwaterbirds are represented in Sri Lanka [6].

The high environmental heterogeneity ofcoastal lagoons provide habitats for waterbirds. In
Sri Lanka, most of the coastal waterbirds are
migrants [26]. The numerically largest migratorygroups are the waders, ducks and coastal birds [14],where 42 of 47 species belonging to Family
Charadridae, 11 of 14 species belonging to Family
Anatidae and 15 of 19 species belonging to Family
Laridae are migrants in Sri Lanka [14]. Altogrther,
54 species of seabird species belonging to OrderCiconiiformes were recorded in Sri Lanka [12].
Northern coastline is the longest coastline in Sri
Lanka, which extends from Mannar to Mullaitivu[23] and consists of rich habitat heterogeneity,mangroves, marshland, sand dunes, tidal flats andcoastal lagoons[28], which provide stopover habitats
for migratory water birds.

Sri Lanka is divided into six avifaunalzones based on the distribution of the resident bird
species. The Northern avifaunal zone shares many
similarities with south Indian Avifauna [27].
Migratory birds that use the Central Asian flyway,
use five main entry and exit points, of which three
are located n the Northern Province of Sri Lanka
namely, the Jaffna Peninsula, the Adam’s
Bridge/Mannar region and the Devil’s Point [14]. As
Sri Lanka is located in the Central Asian Flyway, itis the final destination point for majority of birds

124

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

Tropical coastal lagoons are the mostthreatened ecosystem due to multiple disturbances
including, habitat fragmentation, habitat alterations,climate change and various forms of anthropogenic
activities [25]. Although wind power is an ideal
alternative renewable energy option in Sri Lanka, it
negatively impacts migrant bird population arriving
the country in many ways, including collision,
displacement and disbursement, barrier effect andhabitat change and loss [9] [15] [18] [20]. This maylead to disruption of ecological links between
feeding, breeding and roosting sites [15].
Fig. 01: Location of two study sites

However, a few ornithological studies havebeen done in the Northern Province of Sri Lanka dueto three decades of armed conflict [21] [29] [10] [11].
Long term monitoring of waterbirds provide crucial
information on conservation of waterbirds and theirwetland habitats [4]. The present study was done to
explore habitats which were inaccessible for several
decades and to determine spatial variation ofwaterbird species in two selected locations, Pallai
wind farm and Thadduvankoddy located in the
Northern Province, Sri Lanka.

Fig. 01: Pallai windfarm
Fig. 02: Thadduvankoddy
Thadduvankoddy (Fig. 02) situated in the
Kandavalai DS division in Kilinochchi district,
Northern Province, Sri Lanka (9 0 30’ 0” N and 80 0
25’ 0”) and it lies close to the Chundikulam National
Park (24 km away from the NP). The site can be
described as a marsh with salt marsh species such as
Suaeda maritima along with other plant species such
as Volkameria inermis, Dopatrium cinerea,
Heliotropium supinum, Ipomoea pes-caprae,
Calotropis gigantea etc.

MATERIALS AND METHODS
Study Area
Pollupallai wind farm (Figure 01) is located in the
Pachchilapalli DS division in Kilinochchi District,
Northern Province of Sri Lanka (9 0 35’ 59” N and
80 0 18’ 60”). This wind farm consists of 16 turbines
which are placed 400 m apart in a single row, facing
the Jaffna lagoon. This is the first-ever windfarm
constructed in the Northern Province [30]. Pallai
wind farm is surrounded by true mangrove species
such as Exoecaria aggalocha, Pemphis acidula andLumnitzera racemosa, and other plant species, salt
marshy vegetation such as Sueda maritima,
mangrove associate Pandanus sp., and Dry and arid
species such as Aloe vera, Borassus flabillifer,
Annua sp. Opuntia sp. etc.

A line transect was established in eachstudy site, the entire transect belt was divided into
three counting blocks of 500 m x 500 m, each block
was separated at least by 500 m to avoid double
counting as most were open areas. Three blocks
established in Pallai site are designated 1, 2 and 3
while
the
three
blocksestablishedin
Thadduvankoddy are designated as 4, 5 and 6.
Counting of waterbirds was done during dawn, noonor dusk on alternate months to capture temporalvariations, by walking along the transect line of eachblock. Waterbirds were identified and counted using
binoculars (10 x 50) and telescope (60 x) in the three
counting blocks in each study site, once a monthfrom December, 2016 to February, 2017.

125

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

Altogether 50 species of waterbirds
belonging to 15 families were recorded in the study
area, of which 47 species were recorded in
Thadduvankoddy which 35 species recorded in
Pallai. Out of the 50 bird species recorded, 32
species were shared between the two sites, 15
species were recorded only in Thadduvankoddy
while three were recorded only in Pallai.

DATA ANALYSISDiversity Indices such as Shannon’s diversity Index,
Shannon Evenness Index, Inverse of Simpson’s
Index, Margalef’s richness index and Berger-Parker
Index were used to compare the two study sites. The
percent occurrence was compared for families ofwaterbirds recorded in the study area.

According to Shannon Wiener diversity
Index, a higher waterbird diversity was recorded in
Pallai compared to Thadduvankoddy (Table. 01).
Shannon Evennes was higher in Pallai compared toThadduvankoddy. Thadduvankoddy was dominatedby Eurasian Wigeon, Anas penelope (1682
individuals) and Greater flamingoes, Phoenicopterus
ruber (1567 individuals). However, Species richness
and Margalef’s Richness Index were higher in
Thadduvankoddy compared to Pallai (Table 01).
That might be due to habitat heterogeneity andavailability of food in Thadduvankoddy. In general,
wetland birds are heterogeneous in their feeding
habits [1]. Birds might be displaced into lessfavourable feeding areas due to the development of
windfarm [24].

Defining the Foraging Guilds
The foraging guild is a group of waterbirds that
exploit the same set of food resources in similar way
but not necessarily closely related taxonomically[22]. In this study, Waterbird species werecatergorised into 10 main guilds according tomorphological characteristics, taxonomic groupings
based on different habitat requirements, following[2][3][17][19].
1.
2.
3.
4.
5.

6.

7.
8.
9.

Dabbling: ducks and gallinules;
Stalking: comprising herons, egrets andbitterns.
Fishing: pelicans
Diving waterbirds: comprising cormorants,
darters and grebes
Coots: Common coot, Common moorhen,
white-breasted Waterhen and Purple
Swamphen
Flamingoes,storksandspoonbills:
comprising flamingoes, storks, ibises andspoonbills
Terns
Gulls
Shorebirds: The Shorebird guild wasfurther subdivided on the basis of theshorebird’s sensory mechanism of fooddetection, and feeding style.
a. Visualsurfaceforaging
shorebirds: Thick-knee, Plovers,
Lapwings, Common Sandpiper,
Whimbrel, Wood sandpiper andCommon Redshankb. Tactile
surfaceforaging
shorebirds: Curlews, Godwits andStintsc. Pelagic foraging shorebirds: Stilts
and Marsh Sandpipers

Table 01: Comparison of species richness anddiversity indices in two study sites

Species Richness
Shannondiversity
index
Shannon
Evenness
Index
InverseSimpsonIndex
Margalef’s Richness
Index
Berger Parker Index

Pallai35
2.41

Thadduvankoddy
47
2.13

0.68

0.55

5.27

4.77

5.11

5.38

0.39

0.32

Of all, family Scolopacidae was dominatedwith nine waterbird species, representing 47.61 % ofpercent occurrence in Pallai and Thadduvankoddy
was dominated by Anatidae with five waterbird
species, representing 43.88 % of percent occurrence.
Thadduvankoddy is an excellent place to observe
Greater Flamingo (Phoenicopterus ruber) and
Migratory ducks such as Northern Pintail (Anasacuta), Eurasian Wigeon (Anas penelope), Northern
Shoveller (Anas clypeata) and Garganey (Anasquerquedula) during the migratory season.

Euclidean distances were measured for abundance ofwaterbird communities for each foraging guild tocreate dendrogram to find similarities among threeblocks in Pallai and three blocks in Thadduvankoddy
using Minitab, version 17.

Table 02: Status of families of waterbirds recorded
in Pallai and Thadduvankoddy
Sr.
N
o.

RESULTS AND DISCUSSION

126

Family Name

No
of
Spec

Percent
occurrence

Percent
occurrence
Thadduvank

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

01
02
03
04
05
06
07
08
09
10
11
12
13
14
15

Podicipedidae
Pelicanidae
Phalocrocoracidae
Anhingidae
ArdeidaeCiconiidae
Threskiornithidae
Phoenicopteridae
Anatidae
Rallidae
Recurvirostridae
Burhinidae
Charadriidae
Scolopacidae
Laridae

ies
01
01
02
01
09
02
03
01
05
04
01
01
07
09
02

Pallai
0.78
1.55
1.42
0
8.54
0.13
2.07
15.52
1.68
0
1.94
0.78
14.75
47.61
4.01

oddy
0
0.27
6.16
0.15
1.85
0.10
1.37
30.19
43.88
0.06
3.06
0.06
3.02
6.67
3.01

When Euclidean distance based on theabundance of waterbirds is considered, samplingsites, Block 04 in Thadduvankoddy was distinct
from other sampling sites (Fig. 03) due to thepresence of unique species with relatively highabundance. This site was dominated by Family
Anatidae and Phoenicopteridae. This Block in
Thadduvankoddy is close to Chundikulam Bird
sanctuary, (around 24 km), in the Northern Province,
Sri Lanka. It seems that is an excellent place for bird
watching during migratory season. Further studies
are important to confirm this observation in
Thadduvankoddy in the Northern Province. Other
two blocks in Thadduvankoddy were clustered
together due to the habitat homogeneity near thecauseway. However, Block 05 was dominated byfamily Anatidae while Block 06 was dominated by
Family Phalacrocoracidae. Block 01 was distinct
from Block 02 and 03 in Pallai at about 20.83 %level of similarity due to the presence of uniqueshorebird species in the other side of the turbines
near the shoreline. However, Block 02 and 03 show
similarity at about 57.99 % due to habitat
homogeneity near wind turbines.

and 6 represent Blocks 01, 02, 03 in Pallai andBlocks 04, 05 and 06 in Thadduvankoddy
respectively).
Table 03: Checklist of waterbird species recorded in
the study
Family name
Podicipedidae
Pelicanidae
Phalocrocora
cidae
Phalocrocora
cidae
Anhingidae
Ardeidae
Ardeidae
Ardeidae
Ardeidae
Ardeidae
Ardeidae
Ardeidae

Ardeidae
ArdeidaeCiconiidae
Ciconiidae
Threskiornith
idae
Threskiornith
idae
Threskiornith
idae
Phoenicopteri
daeAnatidae

Figure 03: Dendrogram of the Euclidean distanceshowing similarity among three blocks in Pallai site
and three blocks in Thadduvankoddy, based on theabundance of waterbird communities in each
foraging guild. (In the Figure, Numbers, 1, 2 3, 4, 5

AnatidaeAnatidaeAnatidae
127

CommonName
LittleGrebeSpot-billed
PelicanIndianCormorant
LittleCormorant
Oriental
DarterGrey Heron
PurpleHeron
Great Egret
Intermediat
e EgretLittle Egret
CattleEgret
IndianPond
Heron
Striated
Heron
Yellow
Bittern
PaintedStork
AsianOpenbill
Blackheaded Ibis
Glossy Ibis
Eurasian
Spoonbill
Greater
Flamingo
LesserWhistling
Duck
EurasianWigeon
Northern
Shoveller
Northern

Scientific
Name
Tachybaptus
ruficollis
Pelecanus
philippensis
Phalacrocora
x fuscicollis
Phalacrocora
x nigerAnhingamelanogasterArdea
cinereaArdea
purpurea
Casmerodius
albus
Mesophoyx
intermedia
Egrettagarzetta
Bubulcus
coromandus
Ardeolagrayii

Guild

Butorides
striatus
Ixobrychussinensis
Mycteria
leucocephalaAnastomus
oscitansThreskiornis
melanocephalus
Plegadis
falcinellus
Platalea
leucorodia
Phoenicopter
us ruber
Dendrocygna
javanica2

Anas
penelope
Anas clypeata

1

Anas acuta

1

4
3
4
4
4
2
2
2
2
2
2
2

2
6
6
6

6
6
6
1

1

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

Anatidae
Rallidae

Rallidae
Rallidae
Rallidae
Recurvirostri
dae
Burhinidae
Charadriidae

Charadriidae

Charadriidae

Charadriidae

Charadriidae
Charadriidae
Scolopacidae

Scolopacidae

Scolopacidae
Scolopacidae
Scolopacidae

Scolopacidae
Scolopacidae
Scolopacidae
Scolopacidae
Laridae

Laridae

Pintail
Garganey
Whitebreasted
WaterhenPurpleSwamphenCommoncoot
CommonMoorhenBlackwinged
Stilt
Great
Thick-knee
Yellowwattled
Lapwing
Redwattled
Lapwing
Pacific
GoldenPloverCommonRingedPloverKentishPlover
Monglian
PloverBlacktailed
GodwitWhimbrelEurasian
Curlew
CommonRedshank
CommonGreenshank
MarshSandpiper
Wood
Sandpiper
CommonSandpiper
Little Stint
Great
Blackheaded
Gull
Brown-

headedGull
WhiskeredTern
Gull-billed
TernCaspianTern
Little Tern

brunnicephalus
Chlidonias
hybridus
Gelochelidon
nilotica
Hydroprogne
caspiaSternaalbifrons
Chlidonias
leucopterusAnasquerquedula
Amaurornis
phoenicurus

1

Porphyrio
porphyrio
Fulica atra

5

Laridae5LaridaeGallinulachloropus
Himantopus
himantopus

5

LaridaeEsacusrecurvirostris
Vanellusmalabaricus

10aVanellus
indicus10a

Pluvialis
fulva

10a

Charadrius
hiaticula

10a

RECOMMONDATION

Charadrius
alexandrinus
Charadrius
mongolus
Limosalimosa10aFurther studies are needed to know about thetemporal variation and the ecological requirementsof waterbirds in both study sites.

Numenius
phaeopus
phaeopus
Numenius
arquataTringatetanusTringanebularia

10a

Tringastagnatilis
Tringaglareola
Actitishypoleucos
Calidris
minutaLarus
ichthyaetus

10c

Larus

8

Laridae5Laridae10cLaridaeWhitewinged
Tern
LesserCrested
Tern

Thalasseus
bengalensis

7
7
7
7
7

7

CONCLUSION
10a
It can be concluded Thadduvankoddy is an excellent
place for the development of bird-related tourism in
the Northern Province, Sri Lanka due to the presenceof large number of migrant bird species while Pallai
wind farm has comparatively lower abundance anddiversity of waterbirds might be due to the impact ofnoise and motion of the wind turbines.

10a
ACKNOWLEDGEMENTS
10b
Financial assistance provided by the University
GrantsCommission(GrantNo.
UGC/DRIC/PG/2015(iii)/UJA/01) to carryout
this study is gratefully acknowledged. And welike to thank Mr. A. Sumanapala and Mr. H.
Jayasinghe for field survey and identification ofvegetation and Miss. N. Mohanachandran forher support during field survey.

10b
10a

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Conservation Status of the Fauna and Flora.
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[29] Wijesundara CS, Chathuranga D, Hettiarachchi
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[30] www. Renewgen.lk, Jan, 2017.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

FACTORS RELATED TO SELF-CARE ABILITY AMONG ELDERLY WOMENIN SEMI-URBAN COMMUNITIES, KHON KAEN, THAILAND.
Kanchana Nimsuntorn1, Piyathida Kuhirunyaratn2 and Kanaporn Tansriprapasiri3
1, 2Faculty of Medicine, Khon Kaen University, Thailand
3
Kanchanabhishek Institute of Medical and Public Health Technology, Nonthaburi, Thailand
ABSTRACTThis research study aims to describe factors related to self-care ability among elderly women insemi-urban communities around Khon Kaen, Thailand. A cross-sectional study was conducted on individuals
elderly woman who were over 60 years old in the Banped Municipality of Khon Kaen, Thailand. The total ofelderly woman 268 valid questionnaires were received from 317 participants who were recruited by a simple
random sampling method. Study measurements or interview questionnaire constructs included self-care ability,
demographics, chronic disease, health status and mental health. Descriptive statistics i.e., frequency, percentage,mean, standard deviation (S.D.), median and inter quartile range (IQR) were conducted to describe initial results.
Furthermore, inferential statistics for bivariate analysis: chi-square, odds ratio and multivariate analysis using
multiple logistic regression were performed. The self-care ability level of all individual participants was assessedby Self-care Ability Scale for the Elderly (SASE). The individual’s mental health level was assessed by Thai
Geriatric Depression Scale-15 (TGDS-15). After analyzing the results with the SASE, 166 elders were found tohave a high level of self-care ability while 102 elders had the low level of self-care ability. Self-care ability was
found to be highly associated with demographics, chronic disease, health status and mental health. Factors thatwere statistically proven to be related to a high level of self-care ability included age, chronic disease, perceived
health status and mental health: depression (p-values < 0.05).
Keywords: Factors, Self-care ability scale for the elderly, Elderly women, Semi-urban communities
them were a health status in a moderate level. The
most common disorders were back pain, rheumatoid
arthritis, high blood pressure, gastritis and heartdisease.
Furthermore, these health problems
resulted in the lower income of these elders.
Specifically, most of these elders had to live alone orapart from their couple due to this lower income [5].
Many people in Thai society consider those
who enter their aging period to have a poor health orto be commonly ill with a little contribution to theircommunity and should not work. This tends to be a
result from a Buddhism-based belief about gratitude,
particularly for parents, grandparents including elderfamily members. In other words, descendants haveto take care of older people in their family. With
this ideology, even some elders who have an ability
to take care of themselves expect their descendants
to take care of them in order to avoid the criticism
from the society. This lack of support for self care
may be a major cause of self-care ability declining insome elders.
There are few studies focus on self-care ability
in elderly. The study found that studying abroad ismainly a study of Self-care ability among homedwelling older people.[6] Self - care ability Scale forthe elderly (SASE) [7] In international the level ofself - care ability was categorized by group of age
65 – 74 years equal 73.89 75- 84 years equal 66.55
85 years above equal [8] and a mean SASE score of
78.[9] Those who had higher self-care ability had amean SASE score of 77.8 and those who had lower

INTRODUCTION
Global aging situation is arisen. The number ofworld population aged 65 and older is projected to
grow from an approximately 524 million in 2010 tonearly 1.5 billion in 2050, with most of the incretionin developing countries [1]. In Asia, over the next
30-year period, this number will increase very fast.
For instance, the proportion of Chinese aged 60 andover is estimated to be sharply increased from 12.4
to 28.1 percent [2].
Thailand has a faster growing aged population
rate than other countries in South East Asia. As thegrowing rate of Thai elders rapidly increase, Thai
society is rapidly becoming an aging society. The
proportion of elderly in Thailand has risen from
10.5% in 2005 to 11.2% in 2009 and will be close to
30% in 2050. Additionally, Thailand’s oldest aged
population group (> 80 years old) will sharply
increase from approximately 12.7 percent to almost
20 percent in 20 [3].
This rapid aging population is changing thesocial structure from socio-economic and healthstatus to the labor force, the employment sector andthe dependency of the senior population on theworking age group due to the social conditionchange and decreased family size [4].
Several studies found that the growing rate ofelder population could become both social andpublic health problems. Almost half of the elders
had an insufficient income and only two third of130

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017self-care ability had a mean SASE score of 57.4.[10]In Thailand not found a study about increasing
Self-care ability in elderly. Unable to assess selfcare ability. Therefor this study than to identify levelof the SASE and factor related among community
elderly In addition most of study show only self care behavior [11]. There is no study self-careassessment. For that reason. A study was conducted
to assess the self-care ability of the elderly among
the elderly women. This reason show the elderly
should have self -care ability.

Research instrument
Study measurements or interview
questionnaire constructs included self-care ability,
demographics, chronic disease, health status andmental health. The self-care ability level of all
individual participants was assessed by Self-care
Ability Scale for the Elderly (SASE) [6]. Whereas
the individual’s mental health level was assessed byThai Geriatric Depression Scale-15 (TGDS-15).
Data collection

OBJECTIVE
Data were collected by trained interviewers
between February and March, 2015. Face-to-faceinterviews were conducted in a comfortableenvironment for each individual participant, mostly
at their home.
.
Data analysis

The aim of this study was to describe factors
related to self-care ability among elderly women insemi-urban communities of Khon Kaen, Thailand.
METHODS
DesignAfter collecting the data, all forms and data
were checked for completeness. All data wasentered twice and validated in EPI INFO for DOS
before transferring in to SPSS application for
Windows as a preparation for data analysis. Data
were analyzed through using SPSS version 19 ( IBM
Corp. Released 2010. IBM SPSS for Windows
version 19.0. Armon, NY:IBM Corp. Under
Liciensed by Khon Kaen University). Descriptive
statistics i.e., frequency, percentage, mean, standard
deviation (S.D.), median and inter quartile range(IQR) were conducted to describe initial results.
Furthermore, inferential statistics for bivariate
analysis: chi-square, odds ratio and multivariate
analysis using multiple logistic regression were
performed. Only a probability (p-value) less than
0.05 was considered to be a statistically significant.

A cross-sectional study was conducted on
individuals who were over 60 year-old in Banped
Municipality of Khon Kaen, Thailand.
.
Population and Sample size
The total number of elder women in target
population from all twenty-three villages was 3000
people. A simple random sampling method wasused to select 350 elder women who registered for
healthcare at Banped Health Promoting Hospitalwere from the four villages of the twenty-threevillages under the supervision of Banped
Municipality; Moo 1, Moo 2, Moo 3, and Moo 18 in2014 to be a research participant . Sample size ofelder women calculate by WinPepi. Assumed
proportion = 0.79 [10] . Required sample size 317(Inflate to compensate for a loss of 15% of subject).
Response rate was 268/317 = 84.50 %. Total ofsample size was 268 elder women.

Ethical issues
An ethical approval for this study was issued byKhon Kaen University, Thailand. Participants gave
a written consent prior to their participation in the
study.

Total of elder woman from
4 villages who registered for
healthcare at Banped Health
Promoting Hospital 350 persons.

RESULTS
Sample size of elder women
calculate by Win Pepi.
Required sample size 317
Assumed proportion = 0.79
(Inflate to compensate for aloss of 15% of subject).
Total of sample size was 268 elder
women. Response rate was268/317 = 84.50 %.

Study sample
The study sample included 268 elder women(n= 268), ranging in age between 60 and 95 years
old, with a median age of 67 years old.

48 elderwomen
notresponse

Demographic characteristics
This study response rate was 84.50 %. A
median age of participants was 67 years old (IQR +11). The highest education of most participants wasFig. 1 Sample size Diagram.
131

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017a primary school. The majorities of participants
were widows (48.9%) and married (42.9%). Most
participants worked, had a caregiver, stayed
connected with close friend(s) and joined religious
activities. More than half of participants received
home visits.(As shown in Table1)

102 participants (38.10%) had a low level of selfcare ability and 166 (61.90%) had a high level ofself-care ability. The low-level self-care ability
group (with scores ranged from 50 to 85 points) had
a statistically significant relationship with moreadvanced age participants. (As shown in Table 2)

Table 1 Demographic characteristics of the sample.

Table 2 Proportion of SASE among the elderly

Characteristics
Age
60 – 69
70 – 79
80 aboveMedianIQR
Max – Min
Education
Bachelor
SecondaryschoolPrimary school
No school
Marital status
SingleMarriedWidow
Working
Yes
No
Caregiver
Yes
No
Close friend
Yes
No
Joined religious
activities
Yes
No
Home visitsYesNo(n= 268)

Percentages
(100)

157
80
31
67
11
95 - 60
1
1
10

58.6
29.9
11.6

264
6

91.8
2.2

22
115
131

8.2
42.9
48.9

196
72

73.1
26.9

223
45

83.2
16.8

233
35

86.9
13.1

SASE

(n = 268)

Low level
High level

102
166

Percentages
(100)
38.10
61.90

Mean score = 71.82

95%CI

70.5073.64

SD = 10.94

Self-care ability and health-related variables
Results showed that self-care ability levels
were related to many health variables i.e., Age 70-79
y.o., Age 80 y.o. and above, Marital status, Having
caregiver, Living arrangement, Having close friend,
Joining religious activities, Received home visits,
Having professional care, Perceived good health,
Perceived poor health, Having chronic disease, Hada fall (in the last 6 months), Time Up & Go (TUG)
test, and Thai Geriatric Depression (TGD) test
(suspected depression). (As shown in Table 3)

0.4
0.4
3.7

223
45

83.2
16.8

153
115

57.1
42.9

Table 3 Factors related to SASE
Factors
related SASE

Age
60-69
70-79
80 above
Education
In school
No school
Marital status
SingleMarriedWorking
Yes
No
Caregiver
Yes
No
Livingarrangement
Yes

Self-care ability
After measuring the self-care ability ofparticipants using a SASE, the results indicated thatan average score of the total 268 study participants
was 72.4 points (S.D. = 10.9). When dividing theparticipants into two groups, this study showed that132

Higher
SASE
Scores > 69
(n = 102)

Low
SASE
Scores <69(n = 166)P

46(45.1)
38(37.3)
18(17.6)111(66.9)42(25.3)13(7.8)101(99.0)1(1.0)

161(97.0)
5(3.0)

0.280

67(65.7)
35(34.3)

86 (51.8)80(48.2)

0.026

31(30.4)
71(69.6)

41(24.7)
125(75.3)

0.307

70(68.6)32(31.4)

153(92.2)13(7.8)<0.01

66(64.7)

153(92.2)

<0.01

0.006
0.002

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

Factors
related SASE

Higher
SASE
Scores > 69
(n = 102)No
Close friend
Yes
No
Joinedreligious
activities
Yes
No
Home visit
Yes
No
Professional
care
Yes
No
Exerciseadequate
Yes
No
SmokingYes

36(35.3)

Low
SASE
Scores <69(n = 166)
13(7.8)75(73.5)27(26.5)

158(95.2)8(4.8)

No

P

<0.01

76(74.5)26(25.5)

147(88.6)
19(11.4)

0.003

68(66.7)
34(33.3)

85(51.2)
81(48.8)

0.013

155(93.4)11(6.6)<0.01

80 (78.4)
22 (21.6)

126 (75.9)
40 (24.1)

0.634

3 (2.9)4 (2.4)

0.791

99(97.1)

162(97.6)

50 (49.0)42(41.2)10(9.8)95 (57.2)
66 (39.8)5(3.0)

0.470
0.014

88 (86.3)

29 (17.5)

<0.01

No

14 (13.7)

137 (82.5)

Fall (last 6months)Yes

38(37.3)

28(16.9)No64(62.7)

138(83.1)

91(89.2)
11(10.8)

74(44.6)
92(55.4)

26 (25.5)
65 (63.7)
11(10.8)

161(97.0)
4 (2.4)1(0.6)

TUG
Yes
No
TGDs
NormalSuspect
Depress

Among several health variables, five predictors
emerged in this study’s logistic regression equation.
These five predictors included Age 70-79 y.o.,Having chronic diseases, and Thai GeriatricDepression (TGD) test (suspected depression). (Asshown in Table 4)
Table 4 Summary of multiple regression analyses
for variables predicting SASE

45(44.1)
57(55.9)

Perceivegood healthGood
Moderate
Poor
Chronic
diseaseYes

Predictors for self-care ability

Variable
Age
70-79
Chronic
disease
TGDs

P

COR

AOR

95%CI

0.03
<0.01

0.46
0.03

0.42
0.04

0.20 - 0.93
0.02 – 0.09

Suspect

<0.01

0.01

0.01

0.00 - 0.03

Depression

0.01

0.01

0.01

0.00 - 0.18

The summarize of this result shows people inNorth East Thailand appreciate and interest in
elderly care. The average score of the sample
regarding self-care was high level, which shows thatthe woman people at average age of 67 years arecapable to take care of their selves. There waspredictors for self-care ability included Age 70-79
y.o., Having chronic diseases, and Thai GeriatricDepression (TGD) test (suspected depression).
DISCUSSION
This research study aimed to describe factors
related to self-care ability among elderly women insemi-urban communities. The outcome of thedemographic data study confirmed the results ofprevious researches in Khon Kaen study [18] whichshows that the main caregiver of the older people
sample was a higher number than that of three ago.
This result shows people in North East Thailand
appreciate and interest in elderly care.
The results of the factors related to self-careability among elderly women program in the villages,
similarly to several studies. An SASE average scoreof this study’s participants who resided in Khon
Kean’s semi-urban communities was in a high level
which indicated that the participants, in general,

<0.01

<0.01

manage well in performing self-care ability andrelate to age average 67 years and exclude
criteria older people with an acute or current
medical or being confused and unable toprovide information. This result was close toprevious study Self-care ability among homedwelling older people in Norway people.[10][9]

<0.01
<0.01

This corresponds with a study regarding self-care
133

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

behaviors of Thai elders that showed most elders
perceived their own health status in a high level as aresult from a decade of Thailand’s health promotion
policies under the healthcare reform following theenactment of the 2002 National Health Security Act
and the 2003 National Senior Act [12].
This comparable result also appeared in among
the seniors in the other country who used the same
SASE instrument to assess elder self-care ability,
Norway. In Norway, an average high level of selfcare ability was 83.3% while an average low level ofself-care ability was 16.7% with an overall averagescore of 78.2 points which was comparable with an
overall average score of 78.4 points of the Banped
Municipality’s elders.
The slight differences
between these numbers may result from different
demographic characteristics e.g., average life
expectancy and a higher chronic illness rate ofdeveloped countries [13]. Additionally, Norwegianelders were received a regular health promotion thatthey could practically apply to their lifestyle. The
same study showed that Norwegian 65 y.o. andabove elders had enhanced their learning skills andappropriately adapted their lifestyle to be inharmony with their surrounding environment andsocial conditions.
Although Thai elders yielded a comparable
result in terms of an overall average score, a highlevel self-care ability proportion representing by the
SASE scores of Thai elders was less than the same
proportion of Norwegian elders.
This lower
proportion reveals that Thailand still has difficulties
in enhancing senior learning ability to diminish therising healthcare costs and challenges of aging
population who tends to be a burden for their family.
Therefore the development of a model for enhancing
senior learning skills for increasing self-care ability
is needed for Thai senior citizens.
Factors related to enhancing self-care ability inthe over seventy years old group had a higher
statistically effect as an obstacle for enhancing selfcare ability than the same effect in the 60-70 years
old group (OR= 0.42, 95% CI = 7 – 80, p-value <0.05). This result can be interpreted as this higher
age affects elder deteriorate body and lessening elder
capacity during the progression of their aging
process [14]. This supposition corresponds with theother two studies in 2001 and 2003 [15], [16].
Additionally, the self-care ability of elders is
gradually decreased by emergent age numbers.
Therefore, aging is a statistically significant
impediment factor in maintaining self-care ability(OR = 0.946, 95% CI = 0.901– 0. 993 in 2012[13]and R2 = 0.18, p-value < 0.001 in 2001 [16].
For elders with chronic diseases, having
chronic diseases was a higher impediment factor for
maintaining their self-care ability than those without
chronic diseases (OR = 0.04, 95% CI = 0.02 – 0.09

, p-value < 0.001). This result was influenced by thelack of self-confidence in their own health fromanxiety caused by physical illnesses and possible
disease complications. As a result, these elders tend
to overlook or lessen their own healthcare. Together
with their dementia or partially skipping
medications, elders with chronic diseases are more
likely to have their illnesses worsening ordeveloping into more complications and become
more dependent on their caregiver than healthyelders. This corresponded with a study in 2009
which indicated that individuals in a good heath who
has no inherited disorders or chronic diseases arelikely to have a high level of self-care ability (R2 =0.356, p-value < 0.001) [17].
Furthermore, the results also showed thatstatistically depression was the worse significant
impediment factor for elders with chronic diseases
than for those without any (OR= 0.01,95% CI= 0.00
- 0.03, p-value < 0.001). This corresponded with theother two studies in China and Sweden whichconcluded that depression caused by isolation was
an impediment factor in maintain a proper self-careability (r = -0.299, p-value < 0.001 in 2009 [17]. andR2 = 0.25, p-value < 0.001 in 2000) [8]. In otherwords, the loss of the loved one might be asignificant cause of sorrow, self isolation, lack ofsocial interaction, resulting in separation anxiety anddepression and ultimately diminished self-careability of individual elders.
CONCLUSION
The findings of the study show that age, chronic
disease, perceived health status and mental healthi.e., depression had a greater impact on female elder
self-care ability. Therefore more public awarenesssuch as culturally appropriate policies and programs
is needed to support senior women in coping with
their challenges. Policies and programs should
focus on preventing chronic diseases in this age
group and address the methods for increasing selfcare ability. In communities for basic information on
health promotion. Strengthen and empowering theelderly to self-reliance. To reduce the cost of healthcare and reduce the burden of reliance on others. In
addition control this factor can certainly
economically reduce the medication cost of thecountry.
ACKNOWLEDGEMENTS
We wish to acknowledge Ole and Ulrika
Soderhamn, Professors at the Faculty of Health andSport Sciences, University of Agder, Grimstad,
Norway for a permission to use the SASE scale andthe Faculty of Medicine, Khon Kean University for
their financial support. We would like to thankBanped Health Promoting Hospital’s staff members
134

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017and participants for their excellent support andcooperation.

[10] Bjorg Dale, Ulrika Soderhamn and Olle
Soderhamn. Self-care ability among homedwelling older people in rural areas inSouthern Norway. Scand J Caring Sci., 2012
26, pp. 113- 122.
[11] Klainin, P., & Ounnapiruk, L. A
meta-analysis of self-care behavior researchon elders in Thailand: an update. Nurs Sci
Q, 2010, 23(2), pp. 156-163.
[12] Jittapunkul, S., Wivatvanit, W.
Panyacheewin, J., & Kangkanpanich,P.(2003).OlderPopulation and Health System:
A profile of Thailand In World HealthOrganization (Ed.), Developing Integrated
Response of Health Care Systems to Rapid
Population Ageing (INTRA) Thailand Survey
Report (Draft 1) Bangkok. Thailand: World
health organization. 2003.
[13] World population ageing 1950-2050
Population Division. DESA. [2013 Feb 10].
Available from:http./www.un/esa/population/
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[14] Nordenfelt, L. On the nature of health. An
action-theoretic approach. Second revised andenlarged edition. Kluwer Academic Publishers;
1995.
[15] Haveman-Nies, A., de Groot, L.C.P.G.M., vanStaveren, W.A. Relation of dietary quality,
physical activity and smoking habits to 10year changes in health status in older
Europeans in the SENECA study. American
Journal of Public Health, 2003, 93, pp.318323.
[16] Soderhamn Olle and Christina Cliffordson.
The Structure of Self-Care in a Group ofElderly People. Nurs Sci Q, 2001, pp. 55-58.
[17] Yu-Ling Bai, Chou-Ping Chiou and YongYuan Chang. Self-care behavior and related
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Journal of Clinical Nursing, 2009, 18(23), pp.
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[18] Kuhirunyaratn, P., Prasomrak, P., &Jindawong, B. Factors related to falls amongcommunity dwelling elderly. Southeast Asian
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[8] Soderhamn O, Lindencrona C, Ek AC. Ability
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135

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

IMMEDIATE EFFECTS OF THAI MASSAGE ON GAIT PARAMETERS INNORMAL ADULTS: A PILOT STUDY
Nutthanun Tatchananusorn1, Wichai Eungpinichpong2, Uraiwan Chatchawan3 and Donlaya Promkaew4
1
Faculty of Associated Medical Sciences, Khon Kaen University.
2
Research Center of Back, Neck, Other Joints Pain and Human Performance (BNOJPH), Khon Kaen University.
3
Improvement of Physical Performance and Quality of Life (IPQ) research group, Khon Kaen University.

ABSTRACTThe purpose of this study was to determine the short-term effects of Thai massage on gait parameters including
stride length, step length, step width, and gait speed, and hamstring flexibility, trunk flexibility, and hip, knee and ankle
range of motion while walking in normal adults aged 19-25 years. A randomized crossover trial was used. Thirty
healthy subjects (17 females and 13 males) with tightness of hamstring muscles as indicated by a straight-leg-raising(SLR) ranged between 40 to 70 degrees participated. Each of them received a session of 1-hour Thai massage and acontrolled condition of 1-hour resting on a bed with a 2-day washout period. Changes in the gait and flexibility
parameters were assessed before and immediately after both conditions and analyzed using paired t-test. Crossoverstatistical analysis was performed by independent t-test. Significantly differences were found between-groupcomparison in hamstring flexibility (4.88º; 95%CI, -8.23 to -1.52), trunk flexibility (2.35 cm.; 95%CI, -3.45 to – 1.25),
step length (1.94 cm.; 95%CI, -3.47 to -0.40), and stride length (4.77 cm.; 95%CI -7.41 to -2.12) (p<0.05). However, nodifferences were found in changes of gait speed, range of motion of hip, knee, and ankle. We concluded that one sessionof Thai massage could provide immediate effects for improving some of the gait parameters, body flexibility andhamstring flexibility.
Key words: Thai Massage, Gait, Walk, Flexibility, Pilot Study1

INTRODUCTION
flexibility and range of motion that is important forwalking performance. However, there is no evidence
on the effects of Thai massage to walking performancein normal adults. The present study aimed toinvestigate the effects of Thai massage tospatiotemporal gait parameters in normal adults.

Walking is ambulatory function of activity in daily
life. There are many benefits of walking. A 30-minutewalking affects to improve mental health and physicalhealth. It may increase endorphin production to easingstress, tension, anger, fatigue, and confusion andimprove sleep quality and cognitive performances [1].
Walking is also one of the best choices of physicalactivity to decrease and prevent risks of noncommunicable diseases such as diabetes, heart diseases,
osteoporosis, Alzheimer disease and cancer [2].
According to the lifestyle of people nowadays, they
will easily have the abnormal sign of musculoskeletal
systems such as muscle tightness and decreased offlexibility, by prolonged abnormal postures [3].
Furthermore, prolonged abnormal posture may lead todecrease walking performances because of somemuscle get tightness and decreased flexibility. Muscles
that mostly to be activated while walking are
Hamstrings, Quadriceps, Gastrocnemius, Soleus,
Tibialis Anterior, Hip Flexors and Hip extensors.
Therefore, if these muscles become tightness, they will
decrease the flexibility and affect walking performancesuch as short step length, decreased step width,
decreased walking speed, and abnormal posture [4].
Recently, Thai massage has become a populartreatment of massage therapy for Thai people. Somestudies suggested that Thai massage help improve body

METHOD
Design and setting
A crossover design study was conducted at the
Department of physical therapy, Khon Kaen University,
Thailand. The study was approved by the ethicalcommittee of Khon Kaen University.
Participants
Healthy participants with tightness of Hamstring
muscle, aged 19-25 years, were recruited through flyers
posted around Khon Kaen University. These
recruitment announcements called for individuals who
had experienced tightness in legs to volunteer to takepart in the study. Participants for inclusion in this study
were selected by a physical therapist who conducted adetailed physical examination and collected baseline
data. Participants must not have evidence of underlying
136

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

disease or anatomical abnormalities. (e.g. malignancy,
osteoporosis, spondylolisthesis, scoliosis, herniatednucleus pulposus, and spondylosis)

width. Reliability of data obtained with footprint was
found to be high (r = 0.92) [5].
Body flexibility

Intervention
A Sit-and-reach box was used to measure body
flexibility. Body flexibility was measured three times.
Reliability of data obtained with sit-and-reach box isreported to be moderate (r = 0.46-0.67) [6].

A session of whole body of Thai Massage used asintervention in this study. The 1-hour Thai massage
protocol consisted of deep pressure massage andstretch on major muscles of the body. Firstly, therapist
applied gently and deep thumb pressure massage along
the meridian lines that covered head, neck, back, andupper and lower extremity consequently. Thumbpressure massage was maintained at each point on themeridian lines for 5-10 seconds per point and repeated
3 times. The intensity of thumb pressure was notexceeded pressure pain threshold of participants andwas adjusted by the therapist. After massage session,
the therapist applied gentle stretch for those muscles
including calf, hamstring and quadriceps.

Range of motion and gait speed
Range of motion of the hip, knee, and ankle were
measured by recording the video while walking. Prior
to walking, markers were placed at shoulder joint,
greater trochanter, lateral epicondyle, lateral malleolus
and middle phalange of the participants. Kinovea
program (version 0.8.15) was used to measure bothparameters.
STATISTICAL ANALYSESPROCEDURE

Changes in spatiotemporal parameters for both Thai
massage session and control session results wereanalyzed by paired t-test. Crossover statistical analysis
was performed by independent t-test. All statisticalanalyses was calculated by Stata 10 software(StataCorp LP, 4905 Lakeway Drive College station,
Texas 77845, USA), assuming no carryover effects. A
P-value of less than 0.05 was considered statisticallysignificant.

Randomization
Thirty participants who met the above
inclusion/exclusion criteria were recruited andrandomly allocated into one of the 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 15 participants per group.

RESULTS
Treatment
Thirty-five potential participants responded toflyers, or word-of-mouth; 5 were excluded after
screening for eligibility. A total of 30 adults met theinclusion /exclusion criteria and were randomly
assigned to the treatment group and to the control
group. A flow chart of participant progression throughthe trial is presented in Figure.1
Table 1. demonstrates the characteristic of the study
population. There were 17 females and 13 males. The
mean age was 21 ± 1 years. The mean weight andheight was 57 ± 9 kilograms and 166.10 ± 9.26
centimeters respectively
Outcome measures were found to be similarly
distributed in both groups at baseline (Table 2)
Step length and stride length test showed significant
improvement after Thai massage session, whereas only
ankle plantar flexion ROM of toe off period showed
improvements in the control period. SLR test showedsignificant improvement after both sessions; however,Thai massage session gave better results. (Table 2)
Independent t-test showed significant differences in
Step length (P=0.015), Stride length (P<0.001), SLR(P=0.006) and Sit and Reach (P<0.001) test between
groups. (Table 3)Participants in group A received an hour Thai
massage and took a rest in supine lying position after
taking Thai massage 2 days later. Whereas, participantsin group B took an hour rest in supine lying position
and 2 day after they took a rest, they received one-hour
Thai massage. The same pre-assessments and postassessments were conducted on both groups.
In keeping with the recommendation of Khon Kaen
University’s ethical committee, all gave informed
consent before participation in the study.
ASSESSMENT
Prior to and following Thai massage and control
sessions, all outcome measures were assessed by one
physical therapist. Details of outcome measures andassessments are described below.
Gait parameters
Gait parameters were assessed by inkmat footprint.
Outcomes consisted stride length, step length and step137

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

Table 2. Evaluation of outcome measures (Mean±SD).
Variables showing a significant interaction effects
between groups have been signed with *,** and *** (pvalue is 0.015, 0.006 and <0.001 respectively).
Parameters
Pre-A
Post-A
Pre-B
Post-B
Step length
65.51
65.41
65.34
67.18
(cm.) *
±5.53
±5.45
±5.23
±5.17
Parameters
Pre-A
Post-A
Pre-B
Post-B
Stride length
131.41130.84129.89 134.09(cm.) ***
±10.93±10.50±9.83±10.29
Step width
6.38
6.26
6.58
6.66
(cm.)
±1.86
±2.40
±2.33
±2.33
SLR (Degree)
54.83
59.11
54.45
63.60
**
±5.83
±8.49
±6.38
±9.80
Sit and reach
-1.56
-2.20
-1.79
-0.07
(cm.) ***
±8.73
9.28
±9.32
±9.32
Heel strike (ROM)Hip Flexion
22.66
22.37
22.50
23.14
(Degree)
±2.88
±3.17
±3.46
±3.87
Knee Flexion
4.68
4.22
3.82
4.89
(Degree)
±3.37
±3.39
±3.81
±4.56
Ankle Plantar
10.32
10.56
10.20
10.16
Flexion
±2.38
±2.30
±2.40
±4.60
(Degree)Toe off (ROM)Hip Flexion
-7.57
-7.81
-8.41
-8.13
(Degree)
±3.38
±3.54
±3.03
±3.31
Knee Flexion
41.62
41.62
40.44
41.03
(Degree)
±4.30
±4.26
±3.36
±4.17
Ankle Plantar
24.92
27.09
24.70
26.01
Flexion
±3.48
±4.97
±3.47
±3.69
(Degree)
1.30
1.29
1.29
1.31
Speed (m/s)
±0.15
±0.14
±0.13
±0.13
A: control session, B: Thai massage session

Assessed for eligibility (n=30)

Randomized(n=30)First period
Control (resting)(n=15)First period
Thai massage(n=15)

Washout
1 weekWashout
1 weekSecond period
Thai massage(n=15)

Second period
Control (resting)(n=15)

Data analysis (n = 30)
Figure 1. Diagram of study design and participants

Table 1 Characteristics of the study population
Participant Data
Sex (Female/Male)
17/13
Age (year)
21 ± 1
Weight (kilogram)
57 ± 9Height (centimeter)
166.10 ± 9.26

DISCUSSION
This study showed that one session of whole bodyThai massage could provide improvements on walking
performance and flexibility, including step length,
stride length, SLR and Sit and Reach, in normal adults
with muscle tightness of hamstring muscles. Our result
are consistent with previous studies reporting that Thai
massage is able to improve lumbar flexibility andhamstring muscle length which tested by Sit and Reach
and SLR test. This was because Thai massage, using
deep pressure, followed by passive stretching, isapplied along the meridian lines covers all taut bandsof whole body. The potential of Thai massage arestimulation of Golgi tendon organ and send to thespinal cord. Within the spinal cord, an inhibitory
interneuron will releases the neurotransmitter glycine
than inhibits alpha motor neuron to inhibit stretch
reflex and relieve muscle with tension, thus it affects to
reduce pain, release the taut band in the tissues andhelp increase muscle length. This provides the muscles
to have more flexibility [7], [8], [9]. Moreover,flexibility help improve step length and stride length[10].

Table 3. Comparison of the mean change between
control session and Thai massage session by
independent t-test, where a significant interaction
effects was found.
ParaWithin-group
Between-group p-value
metersdifference
difference(95%CI)
Control Massage
Step
-0.10
1.84
-1.94
0.015
length(-3.47 to -0.40)
Stride
-0.57
4.20
-4.77
0.001
length(-7.41 to -2.12)
SLR
4.28
9.16
-4.88
0.006
(-8.23 to -1.52)
Sit and
-0.63
1.71
-2.35
0.001
Reach
(-3.45 to -1.25)
Although changings of range of motion while walkingof hip, knee and ankle were not significant. Thai
massage still provided little effects that relate to thedue to Thai massage helps improve flexibility andlengthen muscle. [11], [12]. Moreover, when muscles
were lengthen and reached the optimal resting length, it
138SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

could produce the maximal force and improve mobility[13].
Due to some unclear results, investigating theimmediate effects could be the limitation of this study.
Thus, further study should determine the effects oflong-term treatment with follow-up.

(Thai) Thesis for Bachelor Degree of Science(Physical Therapy), Khon Kaen University. Khon
Kaen: Khon Kaen University; 2003
[8] Hongsuwan C, Eungpinichpong W, Chatchawan U,
Yamauchi J. “Effects of Thai massage on physicalfitness in soccer players”. Journal of Physical
Therapy Science. Volume 27 No.2, 2015, pp.505508.
[9] Barlow A. et al. “Effects of Massage of the
Hamstring Muscle Group on Performance of the
Sit and Reach Test”. British Journal of Sports
Medicine. Volume 38, 2004, pp.349-351.
[10] Christiansen C. “The Effects of Hip and Ankle
Stretching on Gait Function of Older People”.
Archives of Physical Medicine and Rehabilitation
August. Volume 89, 2008 pp.1421-1428.
[11] Zajac FE, Neptune RR, Kautz SA. “Biomechanics
and muscle coordination of human walking. Part I:
introduction to concepts, power transfer, dynamics
and simulations”. Gait Posture. Volume 16 No.3,
Dec 2002, pp.215-32.
[12] Brunner R, Rutz E. “Biomechanics and muscle
function during gait”. Journal of Children’s
Orthopaedics. Volume 7 No.5, 2013, pp.367-371.
[13] Rassier DE, MacIntosh BR, Herzog W. “Length
dependence of active force production in skeletal
muscle”. Journal of Applied Physiological (1985).
Volume 86 No.5, May 1999, pp.1445-57.

CONCLUSION
According to the results of this pilot study, we
concluded that 1-hour Thai massage session may
provide some improvement of spatiotemporalparameters and flexibility parameters, especially forstep length, stride length, SLR and Sit-and-reach. Infurther study, a randomized controlled trial and a longterm treatment with follow-up are suggested. The othertype of participants such as older adults also aresuggested
ACKNOWLEDGEMENT
The authors would like to thank the subjects who
participated in this study. The study was supported by
the Research Center of Back, Neck, Other Joint Pain
and Human Performance of Khon Kaen University.
REFERENCES[1] Johansson M., Hartig T. and Staats H.
“Psychological benefits of walking: moderation bycompany and outdoor environment” Applied
Psychology: Health and Well‐being. Volume 3
No.3, 2011, pp. 261–80.
[2] Cooper K. and Hancock C. “The Benefit ofRegular Walking for Health, Wellbeing and theEnvironment – a review document by C3”. C3
Collaborating for Health [serial online] 2012: [48screens] Available from: http://www.c3health.org/
wp-content/uploads/2009/09/C3-report-on-walking-v-1-20120911.pdf. Accessed June 8, 2015[3] DeLisa J. “Gait Analysis in the Science ofRehabilitation Industrial Biofouling”. District ofColumbia: Department of Veterans Affairs; 1998
[4] Wilkinson MJ., Menz HB. “Measurement of gaitparameters from footprints: a reliability study” The
Foot. Volume 7, 1997, pp.19-23.
[5] Mayorga-Vega D., Merino-Marban E., Viciana J.
“Criterion-Related Validity of Sit-and-reach testfor estimation hamstring and lumbar extensibility:
a meta-analysis” Journal of Sports Science andMedicine. Volume 13, 2014, pp.01-14[6] Buttagat V., Eungpinichpong W., Chatchawan U.,
Kharmwan S. “The Immediate Effects of
Traditional Thai Massage on Heart Rate
Variability and Stress-related Parameters inPatients with Back Pain Associated with
Myofascial Trigger Points” Journal of Bodywork
and Movement Therapies. Volume 15 No.1,
January 2011, pp. 15-23.
[7] Srionla C. and Thong-iam R. “Effect of Thai
Massage on Running Performance in Runner.”

139

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THAI MASSAGE COMBINED WITH MUSCLE ENERGY ANDPASSIVE STATIC STRENGTHING TECHNIQUE COULD IMPROVEHEIGHT OF SEPAKTAKRAW SERVES
Apichat Deeminoi1, *Dr.Wichai Eungpinichpong2, Dr.Maitree Pakarasang3, Dr.Thanarat Sripongngam4
1

Exercise and Sport Sciences Program, Graduate School, Khon Kaen University, Thailand;
Department of Physical Therapy, Faculty of Associated Medical Science, Khon Kaen University, Thailand;
3
Department of clinical microbiology, Faculty of Associated Medical Science, Khon Kaen University, Thailand;
4
Department of Health and Sport Science, Faculty of Education, Mahasarakham University, Thailand
2

ABSTRACT
Flexibility of hamstring muscles is very important in the height of Sepaktakraw serves. The most beneficial
type of stretching of lower limb muscles for this sport has not been verified. This study aimed to evaluate theeffects of applied Thai massage combined with muscle energy technique (ATMMET) versus passive static
stretching technique (PSST) on hamstring flexibility and the height of a Sepaktakraw serve. One hundred andeight healthy Sepaktakraw amateur athletes were randomly allocated to 3 comparison groups. Subjects in the
ATMMET group and the PSST group received a 10 min session of corresponding intervention, whereas the
subjects in the control group sat on a chair without intervention for the same period of time. Passive straight leg
raise test (PSLR) and the height of Sepaktakraw serves were measured at 3 consecutive periods, consisting of
pre-test, post-test, and 24 hour after intervention. An analysis oftwo-way repeated measures ANOVA found that
there was a statistically significant difference in hamstring flexibility and the height of Sepaktakraw serves inboth intervention groups but not in the control group. However, no significant differences were found between
the three groups (p >0.05). We conclude that both ATMMET and PSST may improve hamstring flexibility andthe height of a Sepaktakraw serve immediately.
Keywords: Applied Thai massage, Muscle energy technique, Static stretching, Hamstring flexibility,
Sepaktakraw serves
the exposed balls was correlates with the
Sepaktakraw serve speed [5]. Therefore, theflexibility of lower limb muscles is an importantfactor for increasing the efficiency of the serve.
Massage is one of the treatments used in sport
medicine to increase the performance of the athlete
through its mechanical, physiological, andpsychological effects. Massage has been used inmany cultures and has been employed in sports for along time [6]. Techniques of massage therapy
include acupressure, rubbing, friction, kneading andmuscle stretching [7]. In Thailand, Traditional Thai
massage (TTM) has been used for heal and relax thebody since ancient times. TTM has the appearanceof deep massage, with brief sustained pressure on
the muscles. The TTM therapist use body weight topress down on the muscles through thumbs, palms,
elbows, knees, and feet [8]. The therapist often uses
feet to press on large muscles, such as the gluteus
muscle group, gastrocnemius muscles, andhamstring muscles.
Moreover, muscle energy technique (MET) is
another method that can be used in the treatment ofshortened muscle, restricted joints, and weakened
muscles [9]. Ballantyne et al. showed that 32
seconds of MET produced a significant immediate
increase in passive knee extension. The prominent

INTRODUCTION
Sepaktakraw is a popular sport in Southeast Asia.
This sport has been competed in both the SEA
Games and the Asian Games [1]. There are 5 players
in each team (3 players on the court and 2
substitutes), and each player in the team has adifferent role, depending on their position. First, “thestriker” is responsible for kick, jump kick, or head
the Sepaktakraw ball over the net, to fall into the
opponent’s area. Second, “the feeder” is responsible
for set the Sepaktakraw ball near the net in theirteam’s area for the striker. Finally, “the server” has aduty to serve or kick the Sepaktakraw ball to go overthe net and fall into the opponent’s area [2].
Serving skill is very important in the modern
game of Sepaktakraw, as it is the main reason for
attacking and scoring points. Serving with highefficiency helps towin the game easily which thisrequires the greatest flexibility of lower limb
muscles. The main anatomical motion for theserving highest kicking consist of hip flexion, hip
abduction, and knee extension [3]. In an earlier
study, Rezaei et al. investigated lower limb motion
in Sepaktakraw elite athletes, they found that theserver players had a greater range of hip motion than
did strikers and feeders [4]. In addition, the height of140

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

point of TTM is that it provides muscle relaxation
resulting from deep massage or pressure on muscle,
whereas the prominent point of MET is to lengthen
muscle within a short period of time. Therefore, thecombination of two techniques may provide a betterway to increase the flexibility of muscle as much as
possible without any injury [10].
The most common technique is used to increase
muscle flexibility is the static stretch. Rosario andFeletto compared 4 different static stretchingtreatments: 10 minutes of passive static stretching
performed in 3 sessions over 3 consecutive days; 20
minutes’ walking combined with 30 seconds ofpassive stretching; 10 minutes’ warming of thehamstrings by microwave diathermy combined with30 seconds of passive static stretching; and 30
seconds of passive static stretching. The results
showed that 10 minutes of passive stretching
performed in 3 sessions over 3 consecutive days was
the most effective. However, there are relatively few
studies on the acute effects of passive static
stretching for 10 min in only 1 stretching session[11].
While static stretching has also been found to bean effective method to increase muscle flexibility
but there is no scientific evidence about the mosteffective method for this purpose. Therefore, we aim
to compare the effect of Thai massage incombination with muscle energy technique(ATMMET) with the passive static stretching
technique (PSST) on both hamstring flexibility andthe height of the Sepaktakraw serve.

The remaining participants were randomly divided
into3
groups(usingsoftwareat
http://randomizer.org.),36 people in each group. The
measurers were unaware about the groups’
assignment to reduce bias (Fig. 1).

MATERIAL AND METHODInterventions

Design and Setting

Applied Thai massage (ATM)The research design of this study was arandomized controlled trial with a blinded measurer,
approved by the Khon Kaen University Ethics
Committee for Human Research (approval number
582221).

The participants received 8-minutes of the ATM byusing moderate foot pressure on the calf, the rearlegs and the bottom area on both sides in the prone
position by the experienced massage trainers which
trained by professional Thai massage therapists andreceive a certificate

Procedure
On the first day, all participants warm up before
testing begins about 5 minutes by jogging without
any stretch to prevent injuries. After that, they under
took the passive straight leg raise test (PSLR) [12]for measuring hamstring flexibility followed by theheight of Sepaktakraw serve test (pre-test), which
was recorded by a digital video camera and using a
movement analysis program (Kinovea version
0.8.15) [13].
On the second day, the participants in ATMMET
group received 8 min of ATM from an experienced
trainer and then received 2 min of MET. The
participants in PSST group received 10 min of PSST
on both sides of their legs. And the participants incontrol group carried out activities of daily living
without intervention. They sat on a chair for 10 min.
Participants in all groups were received PSLR test
and the height of Sepaktakraw serve test
immediately after intervention (post-test1).
On the third day, 24 hours after intervention(post-test2), all participants were tested as well as
pre- and post-test for determining chronic effects.
All measurements were done at the same time of day
between 08.00 AM and 12.00 PM.

Participants
Muscle energy technique (MET)One hundred and sixty healthy college students
aged between 18 - 25 years from Roi Et province,
Thailand, were recruited in this study. Firstly, theparticipants had to complete a questionnaire
providing general information, experience inSepaktakraw sport, and history of injuries. After
that, all the participants received a passive straightleg raise test (PSLR) [12]. The remaining
participants consisted of one hundred and eight
healthy college students because of 5 participants
had played Sepaktakraw for less than 1 year,
10 participants had incurred hamstring muscle
injuries within the last 3 months, and 37participants
had PSLR tests of equal or greater than120 degree.

MET was performed in the supine position andhamstring muscles were stretched to the point of
discomfort. And then they were instructed tocontract muscles with moderate isometriccontraction (approx. 75% of maximal) for 5 secondin each 4 repetition and rest between repetition for 3
second [10].

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

Fig. 1 Flow chart for study participation
normality of the data. Kruskal Wallis test or oneway analysis of variance (ANOVA) statistics wereused to compare outcome variables between thethree groups in baseline characteristics. Friedman
test or two-way repeated measures ANOVA byusing the Bonferroni test were used to compare
outcome variables within group and between
groups. Significance level was set at the p ≤ 0.5.

Passive static stretching technique (PSST)
The subjects were placed in the supine
position and hamstring muscles were stretched at
below the pain threshold level by lifting one leg
for 10 minutes [11].
Outcome Measurements

RESULTS
The height of the Sepaktakraw serve wasmeasured by digital video camera recording andanalyzed by using the software Kinovea version
0.8.15 [13] (Fig. 2). The reliability and criterionrelated validity of the software are 0.95 and 0.99,
respectively [14].
Hamstring flexibility was measured by PSLR
[12]. The subjects were placed supine on the bed,
and they raised one leg with knee extension andheld it for 3 s. Subsequently, the goniometer pro
application (trial version) on a smart phone wasused to measure ROM of hip flexion (Fig. 3). Inhouse tests have shown tolerances of ± 0.2° and ±0.3° depending on device [15].
Height of Sepaktakraw serves and hamstring
flexibility were measured before, immediately
after intervention, and 24 hours after intervention.

Kolmogorov test - Smirnov test showed that thedata are distributed normally. There was no
significant difference between the three groups inbaseline characteristics. None of the subjects had
sustained hamstring injuries in last 3 months. Foursubjects in each group were excluded from thisstudy because of data collection errors (Table 1).
So, the remaining ninety six participants were used
to analyze the data.
Within-groups comparison of the means
between pre-test and post-test1 found that
hamstring flexibility and height of Sepaktakraw
serves were significantly increased in PSST and
ATMMET groups (p<0.05). Comparison of themeans between pre-test and post-test2 found that
hamstring flexibility was significantly increasedin PSST and ATMMET groups (p<0.05). Only
height of Sepaktakraw serves was significantly
increased in ATMMET group (p<0.05). But theseparameters were not changed in the control group.

Statistical Analysis
The data were presented as mean ± SD.
Kolmogorov - Smirnov test was used to verify the142SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

However, all parameters showed no significantly
different between groups comparison (Table 2).

Some previous study demonstrated that MET
could increase hamstring flexibility [9], [21]-[22].
They concluded that MET affects shortened
muscle, restricted joints, and weakened muscles.
From this reasons, it can be concluded that both
PSST and ATMMET could increase hamstring
flexibility. Furthermore, this study found that bothtechniques could maintain hamstring flexibility for
24 hours after intervention (Fig. 4).
This study demonstrated that both techniques
could increase the height of the Sepaktakraw serve
as a result of increasing hamstring flexibility. After
24 hours post-intervention, the height of the
Sepaktakraw serve with both techniques decreased
continuously but only the ATMMET group still
maintained the performance of the Sepaktakraw
serve. It could be concluded that the ATMMET
technique for 10 minutes could maintain theperformance of the Sepaktakraw serve (Fig. 5).
However, there were no significant differences
between the three groups in hamstring flexibility
and the height of the Sepaktakraw serve. Thismight be because the subjects received only 1intervention session, which may not be enough.
Our suggestion for further research is to add up
the intervention session, increase the duration ofintervention, and use more than one test formeasuring hamstring flexibility and the height of
the Sepaktakraw serve.

Fig. 2 TheSepaktakraw serve test by using thesoftware Kinovea.

CONCLUSION
In summary, the ATMMET and the PSST
treatment could immediately significantly increase
hamstring muscle flexibility. Moreover, 24 h postintervention, both techniques could maintainhamstring flexibility.
Furthermore, the ATMMET and the PSST
treatment could immediately significantly increase
the height of the Sepaktakraw serve. At 24 h postintervention, only ATMMET could maintain theheight of theSepaktakraw serve. No significant
differences were found in the control group, bothin hamstring muscle flexibility and the height of
the Sepaktakraw serve.

Fig. 3 Passive straight leg raise test (PSLR)DISCUSSIONACKNOWLEDGEMENT
The study showed that treatment with PSST and
ATMMET for 10 min could increase hamstring
flexibility and height of Sepaktakraw serves.
The findings of this study correspond to previous
studied, they found that stretching of soft tissue
could increase tissue elasticity [7], [9], [11]-[12],[16]-[17] leading to increased hamstring
flexibility. The effect of using multiple massage
techniques on flexibility was studied. It found that
Thai massage, deep massage and hand massage
could increase the muscles flexibility [16]-[20].
Table 1 Baseline characteristics

The authors would like to thank the ResearchCenter in Back, Neck, Other Joint Pain and Human
Performance, KhonKaen University, Thailand,and Graduate School, KhonKaen University,
Thailand for Financial supported. Special thanks to
Assoc. Prof. Dr. NaruemonLeelayuwat for helpfulcomments

143

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

Control Group(n=36)
21.28(0.70)
64.69(11.95)
168.64(7.01)
2.56(1.48)
111.00(12.25)

PSST Group(n=36) a
21.67(0.86)
64.93(10.16)
170.94(6.55)
2.75(1.48)
106.56(11.23)

ATMMET Group(n=36) b
21.89(1.63)
64.71(10.45)
170.69(7.22)
2.89(1.43)
108.83(10.49)

p-Values cAge (years)
Weight (kg)Height (cm)
Playing Sepaktakraw (years)
SLR test (degree)
Past hamstring000
injuries (number)
Data collection
4
4
4
error (number)
Note: a PSST, passive static stretching technique.
b
ATMMET, applied Thai massage combined with muscle energy technique.
cOne-way ANOVA

.076
.994
.305
.626
.256

Table 2 Mean and Standard Deviation of PSLR test and Sepaktakraw serve test.

Group

Control

PSST

ATMMET

Note:

Time

Sepaktakraw
serve test

Pre-test
Post-test1
Post-test2
Pre-test
Post-test1
Post-test2
Pre-test
Post-test1

175(2.26)
174(2.12)
174(2.14)
178(2.26)
180(2.12)*
179(2.14)
176(2.26)
179(2.12)*

PSLR test
ROM
Torque(Degrees)(N.m)
115(2.13)
12.87(4.49)
116(2.01)
12.87(4.49)
116(2.01)
12.87(4.49)
109(2.13)
12.22(4.73)
115(2.01)*
12.30(4.85)
113(2.01)*,**
12.25(4.71)
113(2.13)
11.87(3.88)
120(2.01)*
12.70(3.79)

Post-test2

178(2.14)*

119(2.01)*,**

12.17(3.78)* The mean is significantly different compared between pre-test and post-test1 (P<0.05).
**The mean is significantly different compared between pre-test and post-test2(P<0.05).

Fig. 5 Change in the height of Sepaktakrawserve(cm.) during pre-test, post-test1, and posttest2.

Fig. 4 Change in hamstring flexibility (degrees) by
the PSLR test during pre-test, post-test1,
and, post-test2.

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study," in International Conference 2016
"Ergogenic Aids and Nutritional Supplement for
Health and Sports", Centara Hotel & Convention
Centre, Khon Kaen, Thailand, 2016.

REFERENCES[1] P. Mutalai. (February 19, 2014). History of
Sepaktakraw. Available:
http://www.sepaktakrawworld.com/index.php/201
4-01-17-04-10-40[2] O. Sepaktakraw. (2014, 04 August). How to Playthe Game. Available:
http://www.sepaktakraw.org/about-istaf/how-toplay-the-game/#.VAeRbfmSwgM[3] K. I.-o. Suwat Sidthilaw, Chatchadaporn
Pitaksathienkul, , "Biomechanical Analysis of
Sepak Takraw Serves in 24th SEA GAMES,"
journal of Bureau of Sport Science, Office ofSport and Recreation Development, 2009.
[4] M. Rezaei, M. Paziraei, M. Haghani, and S. Hariri,"The Comparison of some lower limb’s motion
range parameters in Sepaktakraw elite athleteswith an emphasis on talent identification,"International Journal of Sport Studies, vol. 4, pp.
1462-1465, 2014.
[5] E. S. a. B. W. Nadzrin Hamdan, "Factors
Correlated With Sepak Takraw Serve Speed " in30th Annual Conference of Biomechanics inSports, Melbourne, Australia, 2012 pp. 413-416.
[6] B. J. Hemmings, "Physiological, psychologicaland performance effects of massage therapy insport: a review of the literature," Physical
Therapy in Sport, vol. 2, pp. 165-170, 2001.
[7] A. Calder. (1998, Recovery: Restoration andRegeneration as Essential Components within
Training Programs. Available:
https://swimmingcoach.org/recovery-restorationand-regeneration-as-essential-components-withintraining-programs/[8] S. Tapanya, Traditional Thai Massage. Bangkok,
Thailand: Duang Kamol, 1993.
[9] G. Fryer, "Muscle energy technique: An
evidence-informed approach," International
Journal of Osteopathic Medicine, vol. 14, pp. 3-9,
Mar 2011.
[10]G. F. F Ballantyne, P McLaughlin, "The effect ofmuscle energy technique on hamstring
extensibility: the mechanism of alteredflexibility," Journal of Osteopathic Medicine, vol.
6, pp. 59-63, 2003.
[11]J. L. Rosario and A. Foletto, "Comparative studyof stretching modalities in healthy women:
heating and application time," J Bodyw Mov Ther,
vol. 19, pp. 3-7, Jan 2015.
[12]A. C. Toby M. Hall, Catherine McNee, Jeremy
Walsh, "Effects of the mulligan traction straightleg raise technique on range of movement,"
Journal of Manual and Manipulative Therapy, vol.
9, pp. 128-133, 2001.
[13]Kinovea. (2016, 3 August). Kinovea. Available:
http://www.kinovea.org/[14]A. Deeminoi, "Reliability and criterion-related
validity of 2d motion analysis system: Kinovea
computer program for measuring the height ofsepaktakraw serves in amateur athletes. A pilot[15]5fuf5. (2015). Goniometer Pro (trial version) Android app on Google Play.
Available:https://play.google.com/store/apps/deta
ils?id=com.FiveFufFive.GoniometerProPreviewAndroid&hl=th[16]V. Buttagat, W. Eungpinichpong, U. Chatchawan,
and S. Kharmwan, "The immediate effects oftraditional Thai massage on heart rate variability
and stress-related parameters in patients withback pain associated with myofascial trigger
points," J Bodyw Mov Ther, vol. 15, pp. 15-23,
Jan 2011.
[17]J. Forman, L. Geertsen, and M. E. Rogers,"Effect of deep stripping massage alone or witheccentric resistance on hamstring length andstrength," J Bodyw Mov Ther, vol. 18, pp. 139-44,
Jan 2014.
[18]D. Hopper, M. Conneely, F. Chromiak, E. Canini,
J. Berggren, and K. Briffa, "Evaluation of theeffect of two massage techniques on hamstring
muscle length in competitive female hockey
players," Physical Therapy in Sport, vol. 6, pp.
137-145, Aug 2005.
[19]C. Uraiwon, "Therapeutic effectiveness of deepmassage (Traditional Thai massage) on patientswith back pain associated with myofascial trigger
points," Thesis (Ph D ), Public Health, Graduate
School, Khon Kaen University, 2005., 2005.
[20]U. Chatchawan, B. Thinkhamrop, S. Kharmwan,
J. Knowles, and W. Eungpinichpong,"Effectiveness of traditional Thai massage versus
Swedish massage among patients with back pain
associated with myofascial trigger points,"
Journal of Bodywork and Movement Therapies,
vol. 9, pp. 298-309, 10// 2005.
[21]F. Ballantyne, G. Fryer, and P. McLaughlin, "Theeffect of muscle energy technique on hamstring
extensibility: the mechanism of alteredflexibility," Journal of Osteopathic Medicine, vol.
6, pp. 59-63, 2003/10/01 2003.
[22]R. Mehdikhani and F. Okhovatian, "Immediate
effect of muscle energy technique on latent
trigger point of upper trapezius muscle," Clinical
Chiropractic, vol. 15, pp. 112-120, 12// 2012.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

A STUDY OF THE CORRELATION BETWEEN FOUR CLINICAL
TRIALS FOR THE MEASUREMENT OF HAMSTRING MUSCLEFLEXIBILITYApichat Deeminoi1, Dr.ThanaratSripongngam2
1

2

Department of Physical Education, Faculty of Education, Roi Et Rajabhat University, Thailand;
Department of Health and Sport Science, Faculty of Education, Mahasarakham University, Thailand

ABSTRACT
Flexibility of hamstring muscles is very important in sports which can be measured in many tests. The
relationship of each test for measuring on the hamstring muscles flexibility has not been verified. The aim of thisstudy was to examine the correlation between the four tests. Ninety six participants were received four methodsof hamstring muscles flexibility tests consist of sit and reach test (SR), stand and reach test (ST), passive knee
extension test (PKE), and passive straight leg raise test (PSLR). Pearson product-moment correlation analysis
was used to analyze relationship between four tests. This study demonstrated the high significant correlation
between SR and ST (r=0.87), moderate significant correlation between SR and PSLR (r=0.50), moderatesignificant correlation between ST and SLR (r=0.46), and low significant correlation between PKE and SLR(r=0.33). We conclude that SR and ST were a high correlation in the measurement of hamstring muscle
flexibility which can be used interchangeably.

Keywords: Hamstring flexibility, Sit and reach test, Stand and reach test, Passive knee extension test, Passive
straight leg raise test

athletes than non-athletes when measured by PSLR
test. That is hamstring flexibility could measureachievement by using PSLR test than ST test.
It can be seen that, using different instruments
to measure hamstring flexibility achieved different
results. Relationship of each test for measuring on
the hamstring muscles flexibility has not beenverified. The knowledge from this study can help
the interested people choosing the appropriate
measurement method.

INTRODUCTION
Flexibility of hamstring muscles is very
important in sports which the reduction of
hamstring flexibility is a risk factor for muscle
injury [1]. Sit and reach test (SR), stand and reachtest (ST), passive knee extension test (PKE), andpassive straight leg raise test (PSLR) [2-5] wereusually use to measured hamstring flexibility in thefield test.
The previous study, Hopper et al. studied about
the effect of two massage techniques on hamstring
muscle length in competitive female hockey players
by using PKE test and PSLR test for measured
hamstring flexibility. The result showed that
hamstring muscle length was significantly
increased by using the PKE test but not the PSLR
test [6].
Moreover, Chu, et al. [7] studied about EMG
activities between the SR test and the ST test: apilot study. The results showed that hamstring andlow back muscles activities higher in ST test thanSR test, but found no significant difference between
the tests.
Furthermore, Bakirtzoglou, et al. [8] studied
about hamstring flexibility by using two different
measuring instruments, SR test and PSLR test, inathletes and non-athletes. They found that
hamstring flexibility score was significant greater in

MATERIAL AND METHOD
Design and Setting
The research design of this study was theanalytical research, one group with four parameters.
Participants
Ninety six healthy college students aged
between 18 - 25 years from Roi Et province,
Thailand, were recruited in this study. Each of themsigned an informed consent and completed aquestionnaire to provide general information andhistory of injuries before participating in this study.

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

Procedure

Passive knee extension (PKE) test

All participants warmed up before the test
begins for 5 minutes by jogging to prevent injuries
but not received stretching the muscles. After that,all participants received the SR test [4], the ST test[3], the PKE test [2], and the PSLR test [5] which
rest between the tests for 20 minutes. All tests were
examined on the same day.

The participants lay supine on the bed, bend one
side of hip and knee joint 90º degree. Then, theexaminer raised the tested leg straight up to thepoint of feeling tight and hold for 3 s.,
3 repetitions [2]. The test used goniometer pro (trial
version) program on smart phone, which wasplaced above the ankle for measured hamstring
flexibility. Record the values in centimeters which
the highest value was used to statistical analysis. Inhouse tests have shown tolerances of the device
between ± 0.2° and ± 0.3°. [10] (Fig. 3).

Outcome Measurements
Sit and reach (SR) test
The participants sit with straight leg, soles of thefeet against the box, bent hip about 90 degrees, andthen, the participants bent forward, without bending
the knee and tried to reach out as much as possible
and hold for 3 s., 3 repetitions. After that, record thevalues in centimeters which the highest value wasused to statistical analysis. [4] (Fig. 1).

Fig. 3 Passive knee extension test (PKE)
Passive straight leg raise (PSLR) test
The participants lay supine on the bed and thenraised the one leg without bending the knee to thepoint of feeling tight and hold for 3 s.,
3 repetitions. The testing done by the examiners [5].
Hamstring flexibility was measured by using thegoniometer pro (trial version) program on smart
phone as same as PKE test [10] (Fig. 4).

Fig. 1 Sit and reach test (SR)Stand and reach (ST) test
The participants stood on a box, which is placedon a chair. Then bend down, straight leg, without
bending the knee and tried to reach the hands
downward as much as possible and hold for 3 s., 3
repetitions. After that, record the values incentimeters which the highest value was used tostatistical analysis [4] (Fig. 2).

Fig. 4 Passive straight leg raise test (PSLR)

Statistical Analysis
The data were presented as mean ± SD.
Kolmogorov - Smirnov test was used to verify thenormality of the data. Pearson product moment
correlation coefficient was used to analyze
relationship between four tests. Significance level
was set at the p ≤ 0.5.

Fig. 2 Stand and reach test (ST)147

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

but PKE test performed by bend the hip joint at 90
degrees. The PSLR test could bend the hip joint
more than 90 degrees until it feels tight which it
involved lower back muscles as same as SR and ST
tests.

RESULTS
Ninety six participants (74 men, 22 women)
aged average 21.61 ± 1.06 years, weight average
64.78 ± 10.85 kg., and height average 170.09 ± 6.93
cm. None of them had sustained hamstring injuries
in last 3 months. All participants were tested for all
tests. In each test, the participants repeated 3 times
and the highest value was used to statisticalanalysis. Mean and standard deviation of each tests
showed in table 2.
The results of this study showed that the highest
correlation was between SR and ST (r=0.87,
p<0.001), the relationship between SR and PSLR
(r=0.50, p<0.001), ST and SLR (r=0.46, p<0.001)
found moderate correlation and low correlation was
found between PKE and SLR (r=0.33, p=0.001).
This study showed no correlation between SR and
PKE (r=0.14, p=0.17), and ST and PKE (r=0.14,
p=0.19) (Table 2).

CONCLUSION
This study showed that SR and ST weresignificant relationships in a high correlation. The
tests can be used interchangeably. PKE and PSLR
were significant relationships in a low correlation.
The moderate correlations were found between SR
and PSLR, and ST and PSLR. PSLR had acorrelated with all tests.
ACKNOWLEDGEMENT
The authors would like to thank Department of
Physical Education, Faculty of Education, Roi Et
Rajabhat University, Thailand, and Department of
Health and Sport Science, Faculty of Education,
Mahasarakham University, Thailand, for financial
supporting this study. Special thanks to Assoc. Prof.
Dr. Wichai Eungpinichpong for helpful comments.

Table 1 Mean and standard deviation of four tests
Test
SR (Cm.)ST (Cm.)PKE (Degrees)
PSLR (Degrees)

Mean ± SD
14.32 ± 6.33
13.81 ± 5.35
89.34 ± 1.85
112.32 ± 12.19

REFERENCES[1] Witvrouw E, Danneels L, Asselman P, D’Have
T, Cambier D, “Muscle flexibility as a risk
factor for developing muscle injuries in male
professional soccer players”, Am J Sports
Med, Vol. 31(1), 2003, pp. 41-46,[2] Gajdosik R, Lusin G, “Hamstring muscle
tightness. Reliability of an active-kneeextension test”, Phys Ther, Vol. 63(7), Jul.
1983, pp. 1085-1090.
[3] Rich BSE, “ACSM's Health-Related PhysicalFitness Assessment Manual”, Med Sci Sports
Exerc, 2004, pp. 1657.
[4] Wells KF, Dillon EK, “The sit and reach—atest of back and leg flexibility”, Research
Quarterly of the American Association for
Health, Physical Education and Recreation,
Vol. 23, 1952, pp. 115-118.
[5] Hall T, Cacho A, McNee C, Riches J, Walsh
J, “Effects of the mulligan traction straight leg
raise technique on range of movement”, J Man
Manip Ther, vol. 9, 2001, pp. 128-133.
[6] Hopper D, Conneely M, Chromiak F, Canini
E, Berggren J, Briffa K, “Evaluation of theeffect of two massage techniques on hamstring
muscle length in competitive female hockey
players”, Phys Ther Sport, Vol. 6(3), Aug.
2005, pp. 137-145.

Table 2 Correlation between four tests
SR
ST
PKE
PLSR
SR
1.00
ST
0.87*
1.00
PKE
0.14
0.14
1.00
PSLR
0.5*
0.46*
0.33*
1.00
Note: SR=sit and reach test, ST=stand and reachtest, PKE=passive knee extension test, PSLR=
passive straight leg raise test
DISCUSSION
This study found that SR and ST tests were themost correlated probably due to the both tests
required flexibility of back and leg muscles which
can be used interchangeably. However, Chu et al.
[7] demonstrated that hamstring (semitendinosus
and biceps femoris) and lumbar erector spinae hadhigher activity in ST test than in SR test. Therefore,
ST test may not be suitable for some individuals,
such as the elderly or who had a problem of thelower back muscle.
PKE test was only correlated with PSLR test
because of the participants were similar in the test
posture (hip flexion) which was an isolate the joint
measurement.
PSLR test was correlated to all tests. May be
due to the test posture was similar with PKE test

[7]

148

Chu DPK, Luk TC, Hong Y, “EMG activities
between sit-and-reach and stand-and-reach: apilot study”, Proceedings of the 20th annual

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017conference of the IEEE engineering inmedicine and biology society, Vol. 20(5),1998, pp. 2448-2451.
[8] Bakirtzoglou P, Ioannou P, Bakirtzoglou F,“Evaluation of Hamstring flexibility by using
two
different
measuring
instruments”,
Sportlogia, Vol. 6, 2010, pp. 28-34.
[9] Barlow A, Clarke R, Johnson N, Seabourne B,
Thomas D, Gal J, “Effect of massage of thehamstring muscle group on performance of thesit and reach test”, Br J Sports Med, Vol. 38,
Jun. 2004, pp. 349-351.
[10] 5fuf5. (2015, 3 August). Goniometer Pro (trial
version) - Android app on Google Play.
Available:
https://play.google.com/store/apps/details?id=
com.FiveFufFive.GoniometerProPreviewAndr
oid&hl=th149

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EFFECTS OF KAEMPFERIA PARVIFLORA ON PHYSICALAND PSYCHOLOGICAL STRESSES IN ADULTS
Wichai Eungpinichpong1, Uraiwan Chatchawan2, Bung-orn Sripanidkulchai3
Suwanna Arunpongpaisal3
1
Faculty of Associated Medical Sciences, Khon Kaen University
2
Faculty of Pharmaceutical Sciences, Khon Kaen University
3
Faculty of Medicine, Khon Kaen University, Thailand.

ABSTRACT
Although Kaempferia parviflora (K. parviflora) has been known as one of health promoting herbs, a clinical
trial is needed to confirm its beneficial effect on stress reduction. The aim of this study was to determine theeffects of Kaempferia parviflora on the physiological and psychological stresses. Healthy adult participants withmoderate stress level were divided into two groups; either ingested with Kaempferia parviflora at doses of 360
mg/day for 14 days (intervention group) or placebo tablets (control group). The results indicated both groups had
significantly decreased stress based upon Hamilton Anxiety Rating Scale (HAM-A) and Suanprung Stress Test20 (SPST-20). Heart rate variability measures exhibited non-significant between-group comparison, except HF,
SDNN, RMSSD and LF of which the control group had significantly lower than the experimental group. This
study suggests that Kaempferia parviflora may be useful for both physiological and psychological stress
reduction.
Keywords: Kaempferia Parviflora, Stress, Clinical Trial, Heart Rate Variability

that consuming optimum dose of extracted
Kaempferia parviflora may reduce physical andpsychological stresses in adult subjects.

INTRODUCTION
Currently, stress has been one of the healthproblems in the society and its consequences haveaffected daily living in a great deal, such as peptic
ulcer, depressive syndrome, diabetes, and high bloodpressure. The reaction of stress does affect not only
physically, but also psychologically wellbeing, likehaving fears and trembling, obvious symptoms
reacted by the autonomic nervous system; feeling aterrible headache, fatigue, nausea, vomiting, increased
heart rate, and muscle tightness. [1] The long term
physical stresses can arouse the sympathetic nervous
system, increase blood pressure, heart rates, salivary
cortisol secretion, and decrease heart rate variability.
Kaempferia parviflora (Thai Ginseng) is an
herbaceous plant in the family Zingiberaceae, nativein Thailand. It has been believed that it might
contain substance that increases libido when
consumed. A study found that it has inhibiting effecton the growth of microorganisms. In addition, it also
be found to have beneficial effect for health such as
anti-inflammatory effect. [2] reduce of blood sugar
levels and lipid levels in mice, increase physicalfitness, and reduce oxidative stress inelderlypeople, [3] increase blood flow to the muscles. [4][5] Since persistent stress affects the body cells to
produces excessive oxidants which destroy
biomolecules in cells and cause tissue cell
degradation [6] and because of antioxidant
mechanism of Kaempferia parviflora, we propose

METHODS
Design and ParticipantsThis study was a randomized controlled trial in
40 volunteers aged 25-45 years who had mild tomoderate degree of psychological stress were screened
by a psychiatrist to rule out for anxiety. The selfassessment form for anxiety symptoms was used forvolunteers who were identified having slightly low
level of anxiety. The exclusion criteria were as follows:
Volunteers with a history of psychiatric illnesses, suchas depression, schizophrenia, bipolar mood, or having
taken any type of stress medication, have had
musculoskeletal pain, postmenopausal women,functional abnormalities of liver and kidneys, lack ofunderstandable communication, unable to follow the
instructions, or having a disease that requires
continuous treatment.
Research Setting
The data collection procedures were obtained at
research room, Faculty of Associated Medical
Sciences where is very quiet, no noise disturbing.
Room temperature was controlled at 25 degrees
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SEE-USQ, Brisbane, Australia, Nov.13-16, 2017

Salivary α-amylase levels (Salivary α-amylase
levels) were measured by inserting a test strip into
the mouth and left underneath the tongue for 2
minutes. Then the strip results were read by Human
Cocoa Meters (Nipro Co., LTD., Japan). The
readings were interpreted as follows: 0-30 KU/L
Normal, 30-45 KU/L High, 46-60 KU/L High,> 60
KU/L very high.
Psychological stress level was assessed by
Suanprung Stress Test with 20 questions (SPST 20), recommended by the Department of Mental
Health. The Cronbach's alpha reliability coefficient
was greater than 0.7.
The level of anxiety was assessed by Thai
version of Hamilton Anxiety Rating Scale (HAM-A).

Intervention and Procedure
All qualified volunteers were informed on
research objectives and how they were expected toperform while participating in the study. Then they
sign the consent form as well as answering thequestionnaire relating to general information. Selfstress level was subsequently self-evaluated while
the anxiety was assessed by the psychiatrist.
Volunteers were randomly allocated either in theexperimental group to take the extracted Kaempferia
parviflora or in the placebo group.
The randomized volunteers took either extracted
Kaempferia parviflora or placebo which were containedin similar capsules. The data collector did not know
which group each volunteer belonged to until thedata collection process was finished. The volunteers
received either extracted Kaempferia parviflora (360
milligrams/day according to human-equivalentsafety dose in a previous study [7]) or placebo after
having blood test for assessing liver enzymes andkidney function (AST, ALT, ALK, BUN, Creatinine: Cr) to
identify the normality. After that each volunteer took 2
tablets at a time before meal in the morning andevening meal lasted for 7 days. The blood test was
repeated again after 7 and 14 days of taking thetablets to ensure that liver enzymes and kidneys
function were within normal range. At the end of thestudy, the anxiety of all the volunteers were assessedby the Psychiatrists and self-assessment was also
performed.

STATISTICAL ANALYSES
Descriptive statistics was used to describe thecharacteristics of the volunteers. The results of all
the continuous variables were compared within thegroup by using the Sign test statistic providing thatthe data were not normally distributed. To compare
between the groups, the Wilcoxon Rank Sum
statistic was used. Statistically significant was set at
α < 0.05. All statistics were analyzed using SPSS
version 19 (Armonk, NY: IBM Corp. Under licensed
by Khon Kaen University)
RESULTS
Recruited participants were 80 volunteers (13males and 67 females), aged 24-36 years, who met
the inclusive criteria. The demographic data werebalance between the Kaempferia parviflora and theplacebo groups. (Table 1)

Measurement Equipment
Variables used for stress assessment in the study
were as follows. The first four variables reflected
more physical than psychological stress whereas thelast two reflected more psychological stress.
Stress index is a measure, sensitive to changes
and reliable. It can be measured by a HRV detector.
The results are as follows: 50-70 excellent, 71-90
good, 91-110 normal, 111-130 stressed (poor), 131150 stressed (very bad)Stress resistance refers to the adaptation of the
body towards stress, used to evaluate the functioningof the autonomic nervous system. The same tools
and methods of measurement were used as stressindex, the results are as follows: 50-70 Bad, 71-90
Poor, 91-110 Normal, 111-130 Good, 131-150 Very
goodHeart rate variability: heart rate variability includes
the values of heart rate (HR), standard deviation of
normal-to-normal intervals (SDNN), root of themean squared of successive difference of normal RR
intervals (RMSSD), high frequency (HF), lowfrequency; LF) and low frequency per high frequency
ratio (LF/HF ratio).

Table 1 Demographic data of the Kaempferia parvifloraand control groups
Characteristics
GenderMale
Female
Age
<36
36-45
>45
Mean ± SD

Kaempferia
parviflora (n=40)

Placebo(n=40)

33(82.50)
7(17.50)34(85.00)
6(15.00)

24(60.00)
15(37.50)
1(2.50)34.50±6.1220(50.00)
20(50.00)0(0.00)34.15±6.93

Note: n(%)

Results of volunteer at baseline demonstrate thatall stress variable were not significantly different
between the two groups (Table 2).

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Table 2 Comparison of stress variables at baseline
between the two groups.
Stressvariables
Stress index
Stressresistance
SDNN
RMSSD
HF
LF
LF/HF
AMYLESS
HAM-A
SPST – 20

Kaempferia
parviflora
Median(IQR)
95(10.50)
97(11.50)
39.86(22.24)
30.02(21.75)
5.79(1.55)
5.44(1.60)
0.81(1.58)
74.50(55.00)
19(10.00)
57(10.50)

PlaceboMedian(IQR)

pvalue98(18.00)
93(21.50)

0.065
0.109

32.74(24.10)
24.52(18.69)
5.29(1.44)
5.44(0.99)
1.21(1.81)
83.00(46.50)
18(15.00)
60(13.50)

0.175
0.194
0.155
0.870
0.051
0.299
0.751
0.287

the groups was not statistically significant. As far as
the value of RMSSD was concerned, the vagal tone
was increased and denoted stress relief. This study
also found that the group taken the extracted the
Kaempferia parviflora, the stress was statistically
better than the placebo. The results of changing, theAlpha-amylase and HAM-A show similarity pattern
as the others. Volunteers from the Kaempferia
parviflora taken group had a significantly lower
stress and anxiety than those in the placebo groupalthough no statistically significant differences.
The results from other variables of HRV did notdetect any differences after the completion of 14days, except RMSSD, and LF only. Even though theplacebo group showed a significant stress reduction
compared with the Kaempferia parviflora taken
group (Table 3), and the size of the difference wasvery small. This might be due to a relatively shortperiod of taking extracted Kaempferia parviflorathat exhibited small stress reduction effects. Further
study might consider a longer period of intervention
and higher dose of taking extracted Kaempferia
parviflora so that the differences between the groups
may be obviously shown. The results of this study
correspond to the past research which found that the
Kaempferia parviflora was effective in reducing thevolunteers stress in older subjects. [3]The volunteers in the current study did not dropout or quit. No serious adverse reactions were foundduring taking the extracted Kaempferia parviflora. It
was reported that only one volunteer from theextracted Kaempferia parviflora taken groupdeveloped flatulence which was a slight symptom.
This shows that the amount of the extracted
Kaempferia parviflora taken is safe and suitable forthe volunteers’ ages.

Stress variables after 14 days of taking either
extracted Kaempferia parviflora or placebo werecompared. The results demonstrate that most of thestress variables were not significantly different
between the two groups except the RMSSD and
LF/HF ratio (Table 3). Liver enzyme and kidney
function were found to be normal for every
volunteer even after 14 days of taking the tablets.
Table 3 Comparison of stress variables after 14days of taking either extracted Kaempferia
parviflora or placebo tablets
Stressvariables
Stress index
Stressresistance
SDNN
RMSSD
HF
LF
LF/HF
AMYLESS
HAM-A
SPST – 20

Kaempferia
parviflora
Median(IQR)
95.5(14.50)
96(13.00)

PlaceboMedian(IQR)

p-value

101.50(18.50)
91(20.00)

0.117
0.119

38.16(17.19)
29.30(17.41)
5.43(0.88)
5.36(1.31)
0.88(0.91)
63(47.00)
9.5(8.00)
48(16.50)

30.25(19.58)
22.90(15.98)
5.12(1.70)
5.08(1.50)
1.28(1.71)
69(53.50)
9.50(11.00)
44.50(13.00)

0.090
0.033
0.084
0.403
0.036
0.528
0.647
0.158

CONCLUSION
Based on the results of the study, we conclude
that the extracted Kaempferia parviflora may reducestress and anxiety in adults aged 25-45 years.

DISCUSSIONACKNOWLEDGEMENTS

The purpose of the study was to determine theclinical effects of extracted Kaempferia parvifloraon physical and mental stress in adults. Forty
volunteers without any contra-indication underwent
the randomized controlled trial although most of thestress variables were not significantly different
between the two groups at the end of the trial,
RMSSD was higher, and LF/HF ratio was lower inthe treatment group than the control (Table 3). The
results of these two variables revealed that 14 daysof 360 mg/day of extracted Kaempferia parviflora
could reduce physical and psychological stresses.
The results from Table 3, when compared on
the stress index, the level of stress in the Kaempferia
parviflora taken group was lower than the placebogroup by about 6%. However, the difference between

The authors would like to thank the Agricultural
Commercial Research Project where provided a support
with research funding. More importantly, good
cooperation from the volunteers is always valued.
This research project was grateful from the help ofvarious sources contributed their valuable time toenhance a better living of people in the communities.
REFERENCES[1] Selhub EM, “Stress and distress in clinicalpractice: a mild-body approach” NutrClin Care,Vol. 5, 2002, pp. 182-190.

152

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017ethanolic extract in isolated rat organ studies”
Fitoterapia, Vol. 79, 2008. pp. 214-216.
[5] Chaturapanich G, Chaiyakul S, Verawatnapakul
V, Pholpramool C, “Effects of Kaempferia
parviflora extracts on reproductive parametersand spermatic blood flow in male rats” Reproduction,
Vol. 136, Oct. 2008, pp. 515-22.
[6] Pansarasa O, Bertorelli L, Vecchiet J, Felzani G,
Marzatico F, “Age-dependent changes of antioxidant
activities and markers of free radical damage inhuman skeletal muscle,” Free Radical Biology
and Medicine, Vol. 27, 1999, pp. 617–622.
[7] Chivapat S, Chavalittumrong P, Attawish A,
Rungsipipat A, “Chronic Toxicity Study of
Kaempferia parviflora Wall ex. Extract”, Thai
J. Vet. Med, Vol. 40, 2010, pp. 377-383.

[2] Rujjanawate C, Kanjanapothi D, Amornlerdpison D,
Pojanagaroon S. “Anti-gastric ulcer effect of
Kaempferia parviflora” Ethnopharmacology,
Vol. 102, 2005, pp. 120–122.
[3] Wattanathorn J, Muchimapura S, Tong-Un T,
Saenghong S, Thukhum-Mee W, Sripanidkulchai B.
“Positive modulation effect of 8-weekconsumption of Kaempferia parviflora on
health-related physical fitness and oxidative status
in healthy elderly volunteers” Evid BasedComplement Alternat Med, Vol. 2012, Jul. 2012
Article ID 732816.
[4] Wattanapitayakul S,
Chularojmontri L.,
Herunsalee A, Charuchongkolwongse S,
Chansuvanich
N.
“Vasorelaxation
andantispasmodic effects of Kaempferia parviflora

153

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USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

DEVELOPMENT OF POLY (D, L-LACTIC ACID) WITH
POLYBENZOXAZINE VIA SOLUTION BLENDING
1

Kansiri Pakkethati1 and Yodthong Baimark2
Biodegradable Polymer Research Unit, Department of Chemistry, Faculty of Science,
Mahasarakham University,Thailand

ABSTRACT
Polybenzoxazine was synthesized by using bisphenol A, formaldehyde and diamine as precursor via
condensation reaction. Triethylenetatraamine was used as dianmine precursor. Polybenzoxazine wascharacterized by FTIR technique in order to confirm the obtained polybenzoxazine. The ratio of poly(D,L-lacticacid)/polybenzoxazine (Mw=10,000 and 20,000 g/mol) was 0:100, 1:99, 3:97 and 5:95, respectively. Thepoly(D,L-lactic acid)/polybenzoxazine films was characterized by using Scanning Electron Microscope (SEM).
The results showed homogenous and smooth films. Thermal stability of poly(D,L-lactic acid)/polybenzoxazine
films was better than pure polybenzoxazine film. Moreover, 3:97 ratio of polybenzoxazine mixed with poly(D,Llactic acid) (Mw = 20,000 g/mol) film showed good tensile strength,becuse the stress at break was 24.06 ± 7.99
when determined by Universal Tenting Machine. It was concluded that poly(D,L-lactic acid) improved theproperty of the polybenzoxazine film.

Keywords: Biodegradable polymers, polybenzoxazine, poly(D,L-lactic acid)and formaldehyde. Accordingly, phenol and amine
could be varied and this is one of the mostadvantages of polybenzoxazine in excellent
molecular design flexibility. The preparation of
polybenzoxazine is also easy and low cost.
Moreover, polybenzoxazine has good properties inhigh glass-transition temperature (Tg), high thermal
stability, good mechanical properties, and low
shrinkage upon polymerization thermal stability [3].
Polybenzoxazine
precursors
have
been
synthesized from various aromatic/aliphatic amines,
mono/diphenols, and formaldehyde [3,4]. One
approach was to synthesize polybenzoxazine from alowmolecular
weightmonomer,using
monofunctional amine, phenol, and formaldehyde asreactants [4] However, polybenzoxazines obtained
via this approach usually suffered from brittleness.
Another method was the preparation of
polybenzoxazine from high molecular weightoligomers from diamine, bisphenol-A, andformaldehyde [5]. The properties of the
polybenzoxazines derived from these high molecularweight oligomers, especially brittleness, have been
greatly improved when compared with cured films
from the typical low molecular weight precursors.
This enables polybenzoxazine to be an excellent
candidate for flexible film applications. Therefore,
combination of polybenzoxazine with poly(D,Llactic acid) could improve the film properties whencompare to the pure polymer.

INTRODUCTION
The research of biodegradable polymers has
gained considerable momentum in latest years withthe growing public attention to environment
problems. Poly(lactic acid), a biodegradable polymer
which can also be produced from annually
renewable resources, has extended recently an
increasing attention [1].
Lactic acid (2-hydroxy propanoic acid) is ahydroxyl acid containing an asymmetric carbon
atom. The lactic acid exists in two optically active
configurations: D- and L-lactic acids. These lactic
acids are produced by fermentation using bacterial
systems. However chemical process was used to
produce a racemic or D,L-lactic acid. The poly(Llactic acid) and poly(D-lactic acid) are semicrystalline, while the poly(D,L-lactic acid) is
amorphous. The mechanical and thermal propertiesof poly(D,L-lactic acid) are usually lower thanpoly(lactic acid) [2] Moreover below T g in the rangeof 50 – 60 °C, amorphous poly(D,L-lactic acid) is
rigid and brittle having the elastic modulus about 33.5 GPa and low ability to plastic deformation. The
transition from brittle to ductile behavior in theplasticized polylactide occurs when Tg is shifted to
35°C.
Polybenzoxazine is a new class of phenolic
resins which is very accepted and useful in polymer
research. There are three common types of chemical
needed to synthesize polybenzoxazine, including
various aromatic/aliphatic amines, mono/diphenols,
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MATERIALS AND METHOD
Materials
Analytical grade 1,4-dioxane (99%) was
purchased from Sigma-ALDRICH. Bisphenol-A(BPA, 97 % purity) and Triethylenetetramine(TETA, 60% w/w) were obtained from Aldrich,Germany. Formaldehyde was gained from Ajax
Finechem. D,L-lactic acid was purchased fromAcros Organics. All chemicals were used asreceived.
Synthesis of poly(D,L-lactic acid)
In a typical synthesis experiment in this work,
approximately 200 g of D,L-lactic acid were added
into a 500 mL round-bottomed flask whichcontained about 2 g of p-toluene sulfonic acid(PTSA) as catalyst (1% by weight). The flask wasthen heated at 170 °C in a conventional short-path
distillation apparatus for 4 hours. The pressure ofsystem was reduced (ca. -25 inch Hg) for 2 hours tofacilitate further removal of water and to increase
the polymer yield. The molecular weight of products
was consisting of 10,000 and 20,000 g/mol.
Fig.1 Synthesis of polybenzoxazine
Synthesis of polybenzoxazine
Characterization of poly(D,L-lactic acid)/
polybenzoxazine

The polybenzoxazine precursors were preparedby mixing bisphenol-A, TETA, and formaldehyde ata mole ratio of 1:1:4, respectively [6,7]. Firstly,bisphenol-A (6.84 g, 30 mmol) was dissolved in 1,4dioxane (15 mL) in a 50 mL glass bottle and wasstirred until a clear solution was obtained. A
formaldehyde solution (9.73 g, 324 mmol) was thenadded to the bisphenol-A solution. The temperature
was kept under 10 °C by using an ice bath. TETA
was then added dropwise into the mixture while
continuously stirring for approximately 1 hour until
a transparent yellow viscous liquid was obtained [8].
The process of chemical precursor was shown in
Fig.1

FTIR results were obtained by using Thermo
Nicolet Nexus 670 (Vacuell55) used to determine
the chemical structure. The sample was mixed with
KBr powder then it was compressed in sample
preparation equipment to obtain the thin plate. The
measurement wavelength was 500-4000 cm-1.
Morphological observations of poly(D,L-lacticacid)/polybenzoxazine films were performed using a
JEOL JSM-6460LV scanning electron microscopy.
The samples were sputter-coated with gold to
produce a conductive coating and to prevent
charging.
The thermal transition properties of thepoly(D,L-lacticacid),
polybenzoxazineandpoly(D,L-lactic acid)/polybenzoxazine films were
determined with a Perkin-Elmer Pyris Diamonddifferential scanning calorimeter (DSC) under anitrogen flow. For DSC, samples of 5 – 10 mg inweight were heated at 10 °C/min over a temperature
range of 0 to 250 °C to observe their melting
temperature (Tm) and glass transition temperature(Tg). Thermogravimetric analyses (TGA) were doneon TA-Instrument (TG SDT Q600) instrument from30 to 800 °C using nitrogen. The heating rate was
10 °C /min.
Mechanical properties including stress at break,percentage Strain at Break and initial Young’s
modulus,ofthepoly(D,L-lacticacid),

Preparation of poly(D,L-lactic acid)/
polybenzoxazine films
The benzoxazine precursors were mixed withpoly(D,L-lactic acid) (Mw=10,000 and 20,000
g/mol) with 100:0, 99:1, 97:3, 95:5 and 0:100 ratio
cast on glass plates at room temperature. The
membranes were dried at room temperature in air for
one day, followed by drying at 80 °C in an aircirculating oven for 24 hours to remove excess
solvent.

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

the asymmetric stretching of C–O–C (1234 cm-1),
the asymmetric stretching of C–N–C (1180 to 1187
cm-1), the CH2 wagging of oxazine (1325to 1328 cm1), the tri-substituted benzene ring (1502 to 1511 cm1), and the out-of-plane bending vibrations of C–H(1502 to 1511 cm-1 and 937 to 943 cm-1). The bandof O-H and C=O of poly(D,L-lactic acid) was
observed at around 3500 cm-1 and 1725 cm-1,
respectively as shown in Fig 5.

polybenzoxazineandpoly(D,L-lacticacid)/
polybenzoxazine films were determined at 25 °C and
65% relative humidity with a Lloyds LRX+
Universal Mechanical Testing Machine. The film
samples (80 x 10 mm) were tested with a gauge
length of 25 mm and a crosshead speed of 10
mm/min. The mechanical properties were
determined from the average of three measurements
for each sample.
RESULTS AND DISCUSSION
The photographs of poly(D,L-lactic acid)(Mw=10,000 and 20,000 g/mol), polybenzoxazine
and poly(D,L-lactic acid)/polybenzoxazine films
were shown in Fig.2-3.

Fig. 4 The FTIR spectrum of polybenzoxazine

a

b

c

d

e

Fig. 2 The photographs of poly(D,L-lactic acid)(Mw=10,000g/mol)/polybenzoxazine films
a=0PDLLA/100PBZ, b=1PDLLA/99PBZ,
c=3PDLLA/97PBZ, d=5PDLLA/95PBZ
and e =100PDLLA/0PBZ

Fig. 5 The FTIR spectrum of poly(D,L-lactic acid)
Morphology
a
b
c
d
e
Fig. 3 The photographs of poly(D,L-lactic acid)(Mw=20,000 g/mol)/polybenzoxazine films
a=0PDLLA/100PBZ, b=1PDLLA/99PBZ,
c=3PDLLA/97PBZ, d=5PDLLA/95PBZ and
e=100PDLLA/0PBZ

Morphology of the blend films was studied from
SEM images. Figure 6 and 7 show SEM images ofpoly(D,L-lactic acid)/polybenzoxazine films with
(Mw=10,000 g/mol) and (Mw=20,000 g/mol),respectively. The blend films show smooth surface.
The increasing ratio of poly(D,L-lactic acid) show
the higher rough surface.

The chemical structure of the prepared poly(D,Llactic acid), polybenzoxazine and poly(D,L-lacticacid)/polybenzoxazine films were also confirmed
using FTIR technique. The band of N-H stretchingof the TETA was observed at around 3400 cm-1. Theband at 1502 cm-1 represents the stretching of the trisubstituted benzene ring. The out-of-plane bending
vibration of C-H was observed at 932 cm-1. In
addition, bands assigned to the asymmetricstretching of C-O-C and C-N-C were found at 1233
and 1128 cm-1, respectively. Furthermore, the CH2
wagging of the oxazine ring was also observed at1378 cm-1. These FTIR results are in agreement withthe study of Ning and Ishida [3], who also observed

Thermal transition properties
The thermal transition properties of the blend
films were obtained from DSC thermograms to
obtain melting temperature (Tm) glass transition
temperature (Tg) as shown in Fig. 8-9. The Tg of theblend films were around 30-29 °C. The raising Tg
was gained with high molecular weight because thepolymer chain was more disorder. Addition ofpoly(D,L-lactic acid) was also increase Tg. The
formation of polymer chain affected to the thermaltransition properties. The blend films with
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

3PDLLA/97PBZ and 5PDLLA/95PBZ show the Tm
at around 117-143 °C according to some part ofpolymer chain was order formation to get
crystallinity. The thermal stability of the poly(D,Llactic acid), polybenzoxazine and poly(D,L-lacticacid)/polybenzoxazine was investigated using TGA
as shown in Fig. 10-11. The blend films show 3
steps of degradation, 150-200 °C, 250-400 °C and400-450 °C
Fig. 9 The DSC results of polybenzoxazine (a),poly(D,L-lactic acid)(Mw=20,000 g/mol)/polybenzoxazine 99:1 (b), 97:3 (c), 95:5 (d) andpoly(D,L-lactic acid) (e)
a

c

b

d

e

Fig. 6 The SEM results of polybenzoxazine (a),poly(D,L-lactic acid)(Mw=10,000 g/mol)/polybenzoxazine 99:1 (b), 97:3 (c), 95:5 (d) andpoly(D,L-lactic acid) (e)acFig. 10 The TGA results of poly(D,L-lacticacid)(Mw=10,000 g/mol), polybenzoxazine andpoly(D,L-lactic acid)/polybenzoxazine.

b

d

e

Fig. 7 The SEM results of polybenzoxazine (a),poly(D,L-lactic acid)(Mw=20,000 g/mol)/polybenzoxazine 99:1 (b), 97:3 (c), 95:5 (d) andpoly(D,L-lactic acid) (e)Fig. 11 The TGA results of poly(D,L-lacticacid)(Mw=20,000 g/mol), polybenzoxazine andpoly(D,L-lactic acid)/polybenzoxazine.
Mechanical properties
The mechanical properties, stress at break,percentage strain at break and Young’s modulus, ofpoly(D,L-lacticacid),
polybenzoxazineandpoly(D,L-lacticacid)/polybenzoxazine
weredetermined from tensile testing. The results ofmechanical properties of the blend films werecompared in Table 1-2 for stress at break, percentage
strain at break and Young’s Modulus, respectively.
It can be seen that Young’s modulus of blend films
significantly increased as the poly(D,L-lactic acid)ratio increased. Especially 3PDLLLA:97PBZ ratio
showed high stress at break and good flexibility.

Fig. 8 The DSC results of polybenzoxazine (a),poly(D,L-lactic acid)(Mw=10,000 g/mol)/polybenzoxazine 99:1 (b), 97:3 (c), 95:5 (d) andpoly(D,L-lactic acid) (e)157

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

This due to the poly(D,L-lactic acid) can increase
free volume of polybenzoxazine molecules. The
tensile results suggested that poly(D,L-lactic acid)showedgood
potential
for
mix
with
polybenzoxazine.

ratio with poly(D,L-lactic acid) Mw = 20,000 g/mol
show the best flexibility compare with other ratio. It
was concluded that a mixture of poly(D,L-lacticacid) with polybenzoxazine improved theperformance of the blend film.

Table 1 Tensile properties of poly(D,L-lacticacid)(Mw=10,000 g/mol), polybenzoxazine andpoly(D,L-lactic acid)/polybenzoxazine.

ACKNOWLEDGEMENTS

SamplePDLLA :PBZ

Stress at
Break
(MPa)
12.69
0:100
± 3.9710.52
1:99± 5.839.05 ±
3:97
6.96
19.18
5:95
± 6.25100:0
ndnd = not detected

Percentage
Strain at
Break
77.82
± 25.8345.90± 84.58
2.59± 1.5527.15± 37.06
nd

This research was financially supported by
Mahasarakham University, Mahasarakham, Thailand.

Young’s
Modulus(MPa)
374.53± 95.61352.49± 114.93
581.90± 128.10
588.80± 153.21
nd

REFERENCES[1] Jacobsen, S.; Degee, Ph.; Fritz, H.G.; Dubois,
Ph.; Jerome, R. Polym. Eng. Sci., 39, 1999,
pp.1311-1319.
[2] Celi, A. Scandolat, M. Polymer, 33, 1992, pp.
2699-2703[3] Ning, X., and Ishida, H., J. Polym. Sci., 32,
1994, pp. 1121-1129.
[4] T. Takeichi, T. Kano, T. Agag, Polymer, 46,2005, pp. 12172-12180.
[5] T. Agag, T. Takeichi, J. Polym, Sci. Part A:
Polym. Chem. 45, 2007, pp. 1878-1888.
[6] P. Lorjai, T. Chaisuwan, S. Wongkasemjit, J.
Sol-Gel Sci. Technol. 52, 2009, pp. 56-64.
[7] P. Lorjai, T. Chaisuwan, S. Wongkasemjit,
Mater. Sci. Eng., A 527, 2009, pp. 77-84.
[8] T. Takeichi, T. Agag, High Perform. Polym. 18,
2006, pp. 777-797.
[9] Y. Ikada, K. Jamshidi, H. Tsuji, S. H.
Macromolecules, 20, 1987, pp. 904-906.
[10] Z. Kulinski, E. Piorkowska, K. Gadzinowska,
M. Stasiak, Biomacromolecules, 7, 2006, pp.
2128-2135.
[11] H. Tsuji, S.H. Hyon, Y. Ikada, 1991.
Macromolecules, 24, 1991, pp. 5651-5656.
[12] G. Theryo, F. Jing, L. M. Pitet, M. A. Hillmyer,
Macromolecules, 43, 2010, pp. 7394-7397.
[13] Y. Hu, Y.S. Hu, V. Topolkaraev, A. Hiltner, E.
Baer, Polymer, 44, 2003, pp. 5711-5720.
[14] E. Piorkowska, Z. Kulinski, A. Galeski, R.
Masirek, Polymer, 47, 2006, pp. 7178-7188.
[15] H. Xu, C. Teng, M. Yu, Polymer, 47, 2006, pp.
3922-3928.

Table 2 Tensile properties of poly(D,L-lacticacid)(Mw=20,000 g/mol), polybenzoxazine andpoly(D,L-lactic acid)/polybenzoxazine.
SamplePDLLA :
PBZ
0:100
1:99
3:97
5:95
100:0

Stress at
Break
(MPa)
12.69
± 3.9712.37± 6.4424.06± 7.9915.29± 2.7915.56± 4.89Percentage
Strain at
Break
77.82
± 25.83
2.83± 1.366.04± 3.7234.16± 17.49
7.03± 2.98Young’s
Modulus(MPa)
374.53± 95.61668.92± 106.60
657.23± 137.45
466.33± 67.39491.29± 81.41

CONCLUSIONSIn conclusions, it was successfully synthesized ofpoly(D,L-lactic acid) (Mw=10,000 and 20,000
g/mol), polybenzoxazine and poly(D,L-lacticacid)/polybenzoxazine with 0PDLLA/100PBZ,
1PDLLA/99PBZ,3PDLLA/97PBZ, 5PDLLA/95PBZ
and 100PDLLA/0PBZ. It was found that the blend
films showed better thermal properties than the purepolymer due to the good formation of polymer blend.
The SEM images were confirmed well blending
poly(D,L-lactic acid)/polybenzoxazine. Increasing
the amount of poly(D,L-lactic acid) gave the film amore smooth and homogeneous. It was also
approved by mechanical properties using tensile
testing. The 5PDLLA/95PBZ ratio with poly(D,Llactic acid) Mw = 10,000 g/mol and 3PDLLA/97PBZ
158

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BIOCHEMICAL CHANGES IN CHEMICAL INGRADIENTS OF SILKCOCOONS UNDER ENVIRONMENTAL FACTORS
H.N.P. Singh1, Sunita Kumari2 and M.M. Prasad3
1&3
1

Post. Graduate Department of Biotechnology

T.M. Bhagalpur University Bhagalpur-812007, Bihar, (India)
2

S.M. Inter Girls School, Mirjanhat Bhagalpur
ABSTRACT

Environmental factors like temperature, light and relative humidity greatly influence the damage andspoilage of agricultural, horticultural and sericultural products. Subsequently the quality of these sericultural
products depend on temperature and relative humidity of storage centers at which they are stored. The healthy
as well as infested lots of tasar and mulberry by three test fungi viz Fusarium moniliforme, Aspergillus
flavus and Penicillium citrinum were stored under different RH i.e. 33, 55, 75, and 96 per cent. The results
show that storage of infested tasar and mulberry cocoons at various RH for different intervals had pronounced
effect on total protein and carotenoid contents. In general, there was an increase in the rate of degradation ofchemicals with increase in RH values and incubation period. The results show that at all the relative
humidities, maximum degradation in the chemical constituents was recorded in 60 days by all the infested
fungi. Out of four variables (33, 55, 75, 96%), maximum degradation was observed at 96% RH in 60 days ofstorage period in tasar as well as mulberry cocoons. However minimum reduction was noted in 20 days of
incubation in both types of tasar and mulbery cocoons in all test fungi.
Keyword : Biochemical, Silk Cocoons, Environmental Condition

chemical changes in tasar and mulberry cocoons
under infestation, 5gm of each healthy cocoons
were surface sterilized by 0.1% mercuric
chloride and followed by two successive
washing with sterilized distilled water. Thesesamples were infested separately and asepticallyby the spore, suspension of fungi in sterilized
distilled water. Standardization of spore
suspension was done by dilution technique(about 200 – 250 spores / 0.5 ml)

INTRODUCTION
The history of silk dates back to the originof civilization. It has been named in legends,
folklores. The superiority of silk as textile fibrehas been recognized since time immemorial. The
luxurious look, sleek feel, fine lusture andtextiles of silk fabrics are unquestionaly
inimitable. However the chemical constituents ofsilk fibre changes due to fungi underenvironmental factors like RH. So the present
investigation aims to study the biochemicalchanges in chemical constituent of silk cocoons
under different relative humidities during fungal
infestation.

Infested as well as control lots wereincubated at room temperature (25±20C) for 20days, 40 and 60 days under various relative
humidities. At the end of each incubation period
sample were washed then oven dried andpowdered. The powdered samples were taken
for the estimation of total protein [4] andcarotenoid and then estimated [1].

MATERIAL METHODSThe effect of different relative
humidifies was studied following the method of[10]. To maintain different relative humidities
viz, 33%, 55%, 75% and 96%, saturated solutionofMagnesiumchloride(MgCl26H2O),
Magnesium nitrate Mg(NO3)2 Sodium chloride(NaCl) and Potassium nitrate (KNO3)
respectively were prepared and placed insterilized desiccators. In order to study the bio

RESULTS
Protein
The total protein (8.52%) of controlled
tasar cocoons showed little fluctuation in theirconcentration during storage at various RH for

159

different intervals (Table-I) Infestation by all thefungi caused a gradual fall in the amount of total
protein. The maximum decline in the amount of
the total proteins were recorded at 96% RH by F.
moniliforme (88.14%) followed by A. flavus(86.66%) and P. citrinum (85.18%), respectively
in 60 days in case of tasar cocoons.

0

20

40

60

20

40

60

days

days

days

days

days

Control

8.52 8.52

8.52

8.10
6.12

6.48

6

5.52

F. moniliforme

6.96

6.66

% Loss18.3

21.83 24.44

23.94

29.57 1.85

A. flavus

7.32

6.96

6.48

6.66

6.12

% Loss

14.08

18.3

20

21.83

28.16 28.87

P. citrinum

7.5

7.14

6.66

6.84

6.48

% Loss

11.97

16.19 17.77% Loss

20.55

25.14

26.37

32.83 40.25 38.20

P. citrinum

10.66

10.23

10

10.10 9.79

29.37

28.67 30.86 34.28

24.71 27.75

9.51

40

60

20

40

60

days

days

days

days

days

days

6.4

5.85

5.28

4.74

4.40

4.10

54.80

56.07

62.71

66.52

68.92

71.04

7.18

7.80

6.22

6.86

6.40

5.90

49.29

44.91

56.07

5.55

54.88

58.33

8.93

8.52

7.50

7.00

6.50

5.58

36.93

39.83

47.03

50.56

54.09

60.59

5.64

33%
0

20

40

55%
60

20

40

60

days

days

days

FUNGI

day days days

days

19.71 23.94 0.37

Control

0.112 0.112 0.112

0.102

96%

F. moniliforme 0.111 0.111

0.171 0.068% Loss

4.375 39.307 41.696

1.508 0.892

0.065 0.058

47.946

40

60

20

40

60

A. flavus

0.112

days

days

days

days

days

days

% Loss

0.354 0.714

4.56

1.44

1.08

2.04

1.32

0.96

34.464

46.47

83.09

86.66

76.05

84.50

88.14

P. citrinum

4.68

1.92

1.32

2.46

1.74

1.08

45.07

77.46

83.70

71.12

79.57

86.66

5.04

2.34

1.44

2.88

2.16

1.20

40.84

72.53

82.22

66.19

74.64

85.18

0.111 0.111 0.870

0.082 0.073

0.714 22.448 26.696

0.111 0.111 0.111 0.101

0.090

0.064
% Loss
42.5891.419 0.535 0. 803

10.204 19.642

Contd. Table III
75%

Table II Level of total protein (mg/100 mg) inmulberry cocoons under infestation at
different RH

20

9.32

20

20

0

8.75

96%

5.64

33%

8.46

Table III Level of carotenoid (mg/100 mg) intasar cocoons under infestation at different
RH

Contd. Table I
75%

10

75%

55%

day days

10.60

Contd. Table II

Table I Level of total protein (mg/100 mg) intasar cocoons under infestation at different
RH

FUNGI

11.25

% LossMulberry cocoons exhibited the similar
trend. The maximum degradation of total protein
was noted at 96% RH due to all the three fungi
where as minimum was observed at 33% RH in
20 days of storage (Table-II)

33%

A. flavus

55%

96%

20

40

60

20

40

60

days

days

days

days

days

days

0.050

0.043

0.035

0.031

0.023

0.012

55.45660.80368.39272.31579.10788.750

40

60

20

40

60

0.057

0.051

0.040

0.048

0.043

0.031

FUNGI

day days

days

days

days

day days49.15754.28564.01756.69961.42871.964Control

14.10 14.16

14.16 13.95

0.054

0.049

0.036

0.041

0.025

0.011

51.28655.53567.50

62.82176.96490.178F. moniliforme

10.53

9

8.48

8.59

7.46

6.90

% Loss

25.63

36.44

40.11

8.89

7.46 51.27

160

Table IV Level of carotenoid (mg/100 mg) inmulberry cocoons under infestation at
different RH
33%
0

20

40

20

40

60

days

days

days

F. moniliforme 0.141 0.12

0.109 0.116 0.11

0.10

% Loss

11.87 20

25.62 27.50 31.25 37.50

A. flavus

0.15% Loss6.25 12.50

P. citrinum

0.138 0.127 0.118

0.12

0.109

0.10

% Loss

13.75 20.62 26.29

25

31.87

37.50

FUNGI

day days days

days

Control

0.16 0.16

0.16

0.14

The present findings indicate thatstorage of infested tasar and mulberry cocoonsat various relatives humidities for different
intervals had pronounced effect on their total
protein and carotenoid contents. In general,
there was an increase in the rate of degradationof protein and carotenoid with the increase inrelative humidity as well as period intervals.
The maximum loss in the concentration ofprotein and carotenoid was recorded in 60 daysby F. moniliforme at 96% RH, howeverminimum degradation was observed at 33%
relative humidity value in 20 days of storage.
Greater loss in chemical constituents upon 96
percent relative humidity in the present
investigation is supported by the results of [2, 3,
5, 7 and 9]. Such loss in cocoons could befirstly due to luxuriant growth of fungi between
75-96% relative humidity resulting into moreutilizations of chemical constituents of silk
fibres for growth and development of fungi.
Secondly, it might be due to greater enzymatic
activity by the colonizing fungi [6&8].

55%
60

0.16

DISCUSIONS

0.13

0.139 0.128

18.75 13.12 20

0.119
25.62

Contd. Table IV
75%

96%

20

40

60

20

40

60

days

days

days

days

days

days

0.111

0.10

0.091

0.102

0.09

0.072

30.62

37.50

43.12

36.25

43.75

55

0.128

0.116

0.108

0.12

0.10

0.082

20

27.50

32.50

25

36.25

51.25

0.112

0.102

0.096

0.101

0.097

0.08

30

0.363

40

36.80

43.12

50

CONCLUSIONS
On the basis of present findings we conclude
that the environmental factor i.e. relative
humidity is very important factors for the
degradation of chemical constituents of silk
cocoons due to different fungi and storage
period. The relative humidity value of 96% aswell as 60 days of incubation period are mostsuitable condition for growth and developmentof fungi and their metabolic activities. However
maximum degradation was observed due tofungi so the farmers and tribal people of theseregions are suggested to control the spoilage of
cocoons by keeping the cocoons in safe andscientific storage centre in scientific way so thatsilk thread quality remains maintained alongwith good market value.

CAROTENOID
It is obvious from the results (Table-III)that infestation of tasar cocoons by F.
moniliforme, A. flavus, P. citrinum caused a
considerable change in the carotenoid contents
with the increase in the storage period as well as
RH values. The maximum fall was recorded by P.
citrinum (90.17%) which was subsequently
followed by F. moniliforme (88.75%) A. flavus(71.96%) respectively in 60 days at 96% RH.

ACKNOWLEDGEMENTS

The controlled mulberry cocoons
contained 0.162% of carotenoid under infestationby all the three test fungi was reduced to varying
extent at different relative humidifies. Maximum
reduction of carotenoid was noticed at 96% RH
due to F. moniliforme (55.00%) which in turnwas followed by A. flavus (51.05%) and P.
citrimum (50.00%) respectively in 60 days ofstorage. However the losses were observed
minimum at 33 percent RH in 20 days of
incubation by all the three test fungi (Table-IV).

I am highly thankful to P.G. Dept. of
Botany and Biotechnology, T.M Bhagalpur
University, Bhagalpur – 812007, Bihar (INDIA)
for laboratory and library facilities as well as
U.G.C, Government of INDIA for Financial
supports. I am also grateful to my teacher Prof.
A. K. Roy Vice Chancellor B. N. Mandal
University Madhepura Bihar India for continous
inspirational supports.

161

REFERENCES[1]

Davis, B.H. (1976). Carotenoids. In
Goodwin, T.W. ed. Chemistry andBiochemistry of plant pigments Vd-2
London : Academic Press. 38-165.

[2]

Jolly, Dr. M.S., S.K. Sen., T.N. Sonwalkar
and G.K. Prasad (1981). Non Mulberrysilk Food & Agriculture Organization ofUnited Nations, Rome, Italy.

[3]

Kumari Vineeta and A.K. Roy (1990).
Biodegradation of embelia ribus seeds
under the influence of different relative
humilities. Nat. Acad Sai. Letters 13 (5)167-169.

[4]

Lowry, O.H., N.J. Rosebrough, A.L. Farr
andR.R. Randall (1951). Protein
measurement with the folin phenol
reagent J. Biol. Chem 193, 265-275.

[5]

Prasad, M.M. and H.N.P. Singh (1995).
Biodegradationonofchemicalconstituents in silk cocoons by somestorage fungi. National academy Science
letters Vol. 18, (9&10), 163-164.

[6]

Prasad, M.M. and H.N.P. Singh (1995).
Biodegradation of chemical constituentsin tasar silk cocoons after infection withfungi Letters in Applied Microbiolgy. Vol.
21, 235-236.

[7]

Prasad, M.M. and HNP. Singh (1998).
Screening of silk cocoons under storage
for Microbial damage. Proceeding volume
phytodiversification and Human welfare(Eds A.K. Roy J.V.V. Dogra & S.K.
Verma) M.D. Publications. New Delhi
Page 47-51.

[8]

Prasad, M.M., HNP. Singh, A.K. Roy and
R.K. Sinha (1995). Microbial spoilage ofsilk cocoons in storage centres of Biharand their control. Final Technical Report
UGC, Code No. F. 3-22/91 (RBB-I),
Research Project Govt. of India, New
Delhi.

[9]

Roy, A.K and Nilamy Choubey (1984).
Changes in protein contents of bitter
gourd at different relative humilities by
two pathogenic fungi. Indian Phytopath.
37, 179-181.

[10]

Wink, S.A. and G.R. Sears (1950)
Instrumentation studies LVii equilibrium
related humilities above saturated salt
solutions at various Tappi 39 (9): 96 A-97.

162

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

ACUTE EFFECTS OF TRADITONAL THAI MASSAGE ON HEARTRATE VARIABILITY, HEART RATE AND SALIVARY ALPHAAMYLASE
Jaruk Keawsod1 Wichai Eungpinichpong2
1. Graduate schlool, Khon Kaen University, Thailand;
2 Research and Training Center for Enhancing Quality of Life of Working Age People, Khon Kaen
University, Thailand;*Corresponding Author, Received: 00June 2017, Revised: 00 June 2017, Accepted: 00 0000 2017
ABSTRACT: Prolonged stresses always lead to autonomic nervous system (ANS) imbalance that causes
physical and mental disorders. A session of 60 minute of Tradition Thai massage (TTM) can reduce stressand heart rate as well as improve heart rate variability (HRV). However changes in the HRV, an indicator of
ANS balance during TTM has not been explored. The purposes of this study are to investigate the effects of
TTM on HRV and other stress parameters including heart rate (HR) and Salivary alpha amylase (sAA).
Across-over design was carried out in 18 healthy subjects who were recruited and randomly allocated into
two groups receiving either TTM or Control (CT) for 60 minute in each session. HRV and HR were recorded
every 5 minute while sAA was recorded at baseline and post-intervention sessions. The results showed thathigh frequency (HF) component of HRV was increased significantly at 20, 55 minutes and maintained until
the end of session within TTM group (P<0.05). Within the CT group, HF was significantly increased at 15,
20 and 40 minutes (p<0.05), however it was significantly decreased close to baseline at post session.
Between group comparison revealed that HF was significantly increased at 35, 55, 60 minutes and post
session (P<0.05). The HR within TTM group was decreased significantly at the first 5 minutes of having
TTM and maintained until post session (p<0.01) whereas within CT group, the HR was decreased
significantly only at the first 15 minutes of session. The HR was also decreased significantly in TTM at 10 to
50 minutes when compared to CT. Salivary alpha amylase (sAA) level at post-session in TTM was slightly
decreased as compare to baseline. However, it was decreased significantly at post session in TTM whencompared to CT (p<0.01). The results suggest that a session of 60 minutes of whole body TTM could
increase HF, and thus improve HRV and decrease HR. A short duration of 20 minutes of TTM is sufficient toimprove autonomic nerves system activity (ANS). Therefore, for the purpose of improving ANS activity or
stress reduction in healthy individuals by mean of TTM, we suggest that practitioner may use a shorter
duration (20 minutes) than 60 minutes.
Keywords: Massage, Stress, Heart Rate Variability, Salivary alpha amylase
1. INTRODUCTION
Sufficient stress can be effective against
challenge such as competitive stress for athlete.
It may drive someone to complete their goal in
an excellent standard [1]. But if prolonged
stresses persisted, for example over train
athlete or over stressed office workers, SNS
becomes over stimulated (even in the rest timethat PNS should be more activated) and leads
to ANS imbalance. This not only drop on
performance of the athlete but also cause many
health problems such as insomnia, anxiety,fatigue, headache and constipation [2]. In longterm, expose to chronic stresses can increase
cardiovascular risk [3].
Traditional Thai Massage (TTM) is one
type of manual therapies using the hand or
thumb to apply pressure to muscles of limbs
and back along meridian lines and combinewith stretching. TTM is a non-invasive andnon-pharmacological treatment that has beenshown to reduce stress, pain, anxiety, increase
blood circulation and muscle flexibility andpromote relaxation [4]-[6]. A 30-minitues
session of TTM in patients with back pain
associated with myofascial trigger points canalso increase HRV and improve stress-relatedparameters [7]. Although touch massage (TM)
could lower the stress level and increase HRV
using full therapy of 80 minutes, the researcher
found that just only 5 minutes of TM could
significantly increase HRV [8]. Similarly,
duration of application using TTM always be
1-2 hours per session for promote relaxation or
stress reduction.
A shorter period on
application using TTM has not been studied on
this regard. The duration of time that affects
the change in HRV resulting from TTM has notbeen investigated.
163

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

participant’s right finger). When the TTM insupine lying position was completed (40minutes) the participant changed to prone
position and rest for 5 minutes before starting
the massage for lower back and upper back(included neck) parts for 20 minutes. HRV
were measured every 5 minutes during the 60minute massage session. After the massage
session was over, the participant was asked torest in supine for another 5 minutes. Then the
HRV and Salivary alpha-amylase were
measured for post session data. The pressing
technique employed in TTM was done bytransferring the body weight of the massage
therapist to apply gentle, gradually increasing,pressure through the therapist thumb, palm or
elbow. The amount of pressure used wascontrolled by the therapist to be within thepressure pain threshold. Each of the pressure
was maintained for 5 second. [9]. Massage
session was performed by a 7-year experience
full time physiotherapist. who has beencertified and had good skills in performing
Thai massage. For control group, theparticipants were received the same protocol as
TTM group without massage.

2. MATERIAL AND METHODThis study was a crossover randomized
controlled trial, approved by the EthicalCommittee of Khon Kaen University, Thailand(HE592306). eight teen participants wererecruited in this study but two of them dropped
out during the washout period due to unable tocome for data collection on the second visit
second visit. The remaining participantsconsisted of six teen healthy participants
including 16 with the average age of 25.4±4.8
years who completed all the procedures. They
were randomly allocated into either aTraditional Thai massage group (TTM) groupor a Control (CT) group after which they were
swabbed to the other one with 2 weeks washed
out period. Each of them gave written informed
consent to participate in this study. The
participants were excluded from the study if A
history of having disease or disorder which
may affect on heart rate variability (HRV),such as heart diseases, and hypertension or
having disease or disorder that met
contraindication to Thai massage, regularsmoking or drinking alcohol within the past
one year or regularly drinking coffee orbeverage that contained caffeine more than 2times per week.

2.3 Outcome measurements
2.3.1 Heart rate variability (HRV)
All participants were asked to refrainfrom talking, falling asleep, exaggerated body
movements and intentionally altering their
respiration. They were carefully monitored toensure there were no significant respiratory or
postural changes during the session [10].After
resting in supine position for 5 minutes,
baseline HRV was measured in a supine
position with the APG UbioMacpa (HPLAN
Co., Ltd., Busan, Busan-Gwangyeokshi). HRV
data were measured every 5 minutes with aprobe attached to the tip of the participant’s left
finger. This measurement was performed by
the research assistant. Time domain analysis of
HRV and power spectral analysis using the fast
Fourier transformation were performed. Test
measurements were taken in a temperature
controlled room (25°C). During the massage
HRV parameters were determined for every
successive 5-min segment. HRV were
calculated using frequency domains by APG
UbioMacpa software, and the following
parameters were calculated to yield highfrequency power (HF) and mean heart rate. In
this study, HF was the main parameter since it
reflected the sole parasympathetic activity.

2.1 Procedure and Protocol
After
the
participants
underwent
screening procedures using interview andsubjective examination, they were asked togive inform consent and followed by having
the sequence of the following interventions.
2.1.1 Traditional Thai massage group
The participant was asked to rest insupine for 5 minutes then Salivary alphaamylase baseline was collect by theparticipants put the edge of the test strip(saliva-collecting paper) into the mouth, andleft it underneath the tongue (sublingual) for 2
minutes. After that HRV 5-min measurements
were taken with a probe attached to the tip of
the participant’s left finger to collect the HF
baseline. Then the participant received TTM
session for 60 minutes in supine lying position.
The session was divided into 10-minute subsessions for each of the body parts including
the right leg, the left leg, the right arm, and theleft arm (when massage the left arm part; theprobe was attached to the tip of the

2.3.2
164

Salivaryalpha-amylase(sAA)

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

significantly from 5 minutes to post session ascompare to baseline (P –value <0.05)
For mean heat rate (Mean HR), paired Ttest comparing mean HR in CT and TTM ateach time point revealed that there weresignificantly lower mean HR in TTM compare
to CT from 10 to 60 minute
Salivary alpha-amylase (sAA) was foundsignificantly increased in CT, whereas in TTM,
it slightly decreases but no statisticalsignificance. When compare sAA between
TTM and CT group, the sAA at post session
significantly lower (P-value <0.01)

Each of the participants was chewing
cotton wool for 1 minute to induce excretion ofsaliva, participants put the edge of the test strip(saliva-collecting paper) into the mouth, andleft it underneath the tongue (sublingual) for 2
minutes. After that, the test strip was fit into
the handle sleeve and slid into the Cocoro
meter (NiproCo., LTD., Japan).
2.4 Statistical Analysis
That data were present as mean ± SD.
Shapiro-Wilk test was used to test for normal
distribution of each variable. ANOVA withrepeated measures was used to analyze each of
the variables before, during intervention, andfollow up measurements. Paired sample t-test
was used to test for differences in each measure
between the groups. The statistical analyses
were performed with SPSS software (version
17.0, SPSS Inc., Chicago IL, USA). And
Statistical significance was set a p<0.05.

4. DISCUSSION

3. RESULTS
High frequency (HF) was used as the main
outcome measure for HRV. Paired T-test revealed
that there were significantly higher HF values in
TTM compare to CT at 35, 65 minute and post
session (P –value <0.01) and at 70 minute (P –value <0.05) the data were present in Table 1
Table 1 Changes of High frequency (HF) between
CT and TTM group at each time point (Mean ±SD)
Repeated ANOVA was used to analyze theTime point
High Frequencychange of HF within groups,
For TTM, HF(minutes)increased significantly at 20 minute (P –value<0.05) and from 55 minute until post session
TTM in figure
P valuecompare toCTbaseline as shown
1,
whereas;forCT,
HF
increasedsignificantlyatBaseline
6.31 ± 0.59
6.26 ± 0.34
0.629
15minute,20
minuteand40
minutecompare56.30 ± 0.50
6.29 ± 0.81
0.933
tobaseline.,
However
there
was
no
10
6.38 ± 0.35
6.48 ± 0.74
0.482
significantly
changefrom45
minuteuntil
to15
6.68 ± 0.29
6.36 ± 0.68
0.103
post
session
For
mean
heat
rate
(Mean
HR),
20
6.66 ± 0.34
6.53 ± 0.73
0.459
pairedT-testcomparing
mean
HR
in
CT
and
25
6.37 ± 0.63
6.33 ± 0.75
0.778
TTM at each time point revealed that there30
6.38 ± 0.61
6.56 ± 0.84
0.109
were significantly lower mean HR in TTM
35 **6.23 ± 0.65
6.49 ± 0.55
0.001
compare to CT from 10 to 60 minute. Data40
6.74 ± 0.54
6.39 ± 0.75
0.114
were present in Table 255
6.69 ± 0.68
6.71 ± 0.81
0.913
Repeated ANOVA was used to analyze
60
6.67 ± 0.63
6.61 ± 0.68
0.598
the change of Mean HR in within groups. In
65 ** CT group; 6.34
0.73was significant
6.73 ± 0.68increased
0.002
Mean±HR70 * at 15 minutes
6.51as±compare
0.65
6.80
± 0.50 whereas
0.019
tobaseline,
Post session**
6.39
±
0.68
6.89
±
0.37
0.001
n TTM group the Mean HR decreased
Note: CT is control group, TTM is traditional Thai massage
group, .* = p<0.05, **=p<0.01
165

In the present study, TTM to whole bodyfor 60 minutes is effective in increasing
parasympathetic activity in healthy participant(Table 1). Even though the data in figure 1
revealed that HF began to change significantly
at 35 minute of session, it increased slightly
from 5 to 15 minute compare to baseline (6.29,
6.48 respectively). The change in HF as
biphasic curve and tended to increase until theend of session. In control state at 15 and 20
minutes, the increase in HF might be due to therelaxation from resting position. Then it
decreased to nearly close to baseline. However
HF it became a peak again at 40 minute. Thismay be because of changing the probe sitefrom an index finger of one hand to anotherone at 30 to 40 minutes of investigationaccording to the preset protocol. Changing theprobe from left to right finger may affect the
HRV recordings [11]. A decreasing in HR inthis study also was in accordance with thestudy of Lindgren et al.,[8] that HR decreasesignificantly after 5 minutes of massage andlasting for 65 minutes. In the present study, HR
decreased significantly after 5 minutes andlasted until post session of TTM. Even though
the context of these study were different suchas pressure, form of massage, and the durationof treatment or the control environment, theresults showed a similar trend. These results
support the theory that massage has an effectonparasympathetic
nervoussystem[12].Salivary alpha-amylase (sAA) was foundsignificantly increased in CT, whereas itslightly decreased but no statistical significancein TTM. When compare sAA between TTM
and CT group, The sAA at post session
significantly lower. This finding supported theresult of Sripongngam et al.,[13] that TTM
could lower stress as indicated by the lower
level of Salivary alpha-amylase in healthy

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017individual. Since we do not have stressor onto
the participants, the changes in sAA might not
be significantly different. Our protocol requiredthat participants had to change position at 40
minute, and they laid in a certain position inorder to measure the HRV correctly. This maylead to a decrease level of Salivary alphaamylase (sAA) at post session in control group.
Even though APG Ubiomacpa can givethe real time HRV data with only finger probe
attach to participants’ fingertips duringassessment, the participant had to be carefully
monitored to ensure there were no significant
respiratory or postural changes during thesession [10]. Thus we have to modify TTM tominimize the movement of body part when
TTM was performed and even pause theassessment when change position to prone to
wait for HRV to be stable and continue to theend of the protocol. This prolonged constrained
condition may affect the feeling of theparticipants and the HRV results.

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5. CONCLUSION
The results of this study suggested that asession of 60 minutes whole body TTM could
increase HF, thus improve HRV and decreasemean HR. A short duration of 20 minutes of
TTM was sufficient to improve autonomic
nerves system activity (ANS). Therefore, wesuggest that practitioner may use a shorter
duration of TTM (20 minutes) for improving
ANS in healthy individual.
6. ACKNOWLEDGEMENTS
The authors would like to thank thevolunteers who participated in the study. Our
special thanks go to Research and Training
Center for Enhancing Quality of Life ofWorking Age People, Khon Kaen University
for financially supporting this study.
6. REFERENCES[1] Yerkes RM, Dodson JD. "The relation ofstrength of stimulus to rapidityofhabitformation". J comp neurolpsychol 1908; 18:
459–482.
[2] Carlson, Neil. Physiology of Behavior. Pearson
2013; 602–606.
[3] Blascovich J., Spencer S. J., Quinn D. M.,
Steele C. M. "African Americans and high166

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Engineering

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SHEAR STRENGTH OF SOIL BY USING SHELL HUSKS WASTE ASRECYCLE AGGREGATE
1

Siti Hanggita Rachmawati1, Zakaria Hossain2
Graduate School of Bioresources, Mie University, Japan

ABSTRACT
Every year in Japan, a large amount of shell husks waste is generated due to industry and household
consumption. This amount of shell husk plays a negative impact not only on environmental but also on theeconomic problem because the disposal process costs. To solve this problem, the abandon shell husks are
generally used as recycle aggregate for ground improvement and for protection of the natural resources ofaggregates. In this study, shell husks are used as recycle aggregate for ground improvement. Soil is mixed withshell husk percentages of 0% (control), 10%, 20%, and 30% respectively. Specimens of soil-shell husk
composite were tested under the triaxial consolidated-drained tests (CD tests). Test results in terms of deviatoricstress and axial strain are depicted. Results obtained showed that the addition of shell husk in soil leads to anincrease in the deviatoric stress. The shear strength parameters were quantified in terms of cohesion andfrictional resistances. It was observed that the angle of internal friction of soil-shell husks composite increased
up to 30% shell husks. Interestingly, the cohesion of soil-shell husk composite was conspicuously increased
with the increase of shell husk of up to 20% then decreased at 30% shell husk. Further addition of shell husk(30%) in soil altered the behavior of the composite leading to a reduction of shear strength.
Keywords: Shell husks waste, Ground improvement, Principal stress difference, Axial strain shear strength

test, the result showed that certain amount of shellhusk increased the shear strength of soil [5]In this study, the abandon shell husks also arebeing used as the recycle aggregate for ground
improvement. Ground improvement techniques areprovided to increase the soil strength, reducing
compressibility and enhance the performance under
the load. The triaxial test has been performed toevaluate the shear strength of soil-shell husk
composite with 0% (control), 10%, 20% and 30%
shell husks percentage. The triaxial test is the mostreliable methods available for determining shear
strength parameters under different drainage
condition [6]. The triaxial test provides informationon the stress-strain behavior of the soil that the direct
shear test does not. It also provides more uniform
stress condition than the direct shear test does with itits stress concentration along the failure plane [7].

INTRODUCTION
Annually,enormous volume
Seashell-ByProducts (SBP) are produced in all over world.
Burning and burying are most common way to treat
those kinds of waste [1]. All those disposal process
affected a serious problem in environment, andeconomic perspective. For example in Japan, an
example of SBP is abandon shell husks which has
total amount about 151,000 tons/year and nearly 32
million US$ are being used for disposal. That budget
is not expected event for developed country like
Japan. In developing country, many illegally
dumped are happened due to high cost of disposal
waste. In long time, if this waste is untreated, could
be causing the air pollution and other environmental
problems. These circumstances motivate thedevelopment of technologies that using abandoned
shell husk [1], [3].
Recently, the abandon shell husks areinvestigated widely as recycle aggregate inconstruction field. The utilization of abandon shellhusk is expected solving mainly two environmental
and economic aspects, such as: 1) waste storage
problem and 2) protection of limited natural
resources of aggregates [2]. From point of view thepotency of shell husks, generally clam shell iscomposed mainly 95-99% (by weight) of CaCO3
that potentially convert to CaO for reinforcing thesoil or binding the material[1], [4]. In previous study
the shell husk is had been used as recycle aggregate
for ground improvement. By using the direct shear

MATERIALS AND METHOD
Properties of Soil
The soil sample was collected from Shiratsuka
port, Tsu, Mie Prefecture, Japan. From thelaboratory test which are based on Unified
Classification System, revealed that sand has thehighest part of this soil. Figure 1 illustrates theparticle size distribution of sandy soil.
Approximately 7 % is coarse gravel, 19% is pebble,
7% is granule, 10% is fine sand, 29% is medium

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sand, 13% is coarse sand, 11% is silt and 4% is clay.

Fig. 2

Shell size distribution

Fig. 1 Particle size distribution curve

Methodology

The other properties of soil are shown in Table 1.
It is revealed from plasticity chart shown in Figure 2,
that this soil contains silt which caused higher
permeability, higher compressive strength, higher
dry density and low toughness.

The specimens were manually compacted inside
the mold with 12.5cm in height and 5.0cm indiameter. The mixtures of soil-shell husk-cement
were compacted in three layers using 4.9cm
diameter hand-rammer with rammer mass 1.0 kg andfalling height of 30 cm. Each layer was compacted
by 20 blows.
The consolidated-drain (CD) test triaxial
compression test was conducted using soil with shellhusk percentages (0%, 10%, 20% and 30%). The
triaxial chamber is assembled after soil specimen
sealed by the rubber membrane. In the baseplategroove, the chamber cylinder is installed andthereafter the top plate is positioned on it. The threecomponents of the triaxial chamber (i.e., baseplate,chamber cylinder and top plate) are clamped
together by tightening the tie bars. The specimen cap
has a circular indentation at the center and theposition of loading piston should be aligned. It is
achieved by pushing down the loading piston andverified precisely into the center of the specimen
cap. Then the chamber is filled by the fluid fromwater channel and in the same time air release valve
on top cap kept open. An axial stress (△σ) is applied
through the loading piston and during the process
the dial gauge which connected with piston andspecimen recording vertical deformation. The
hydrostatic chamber pressure is applied using the air
channel on the top cap while the air release valve on
top cap closed. The confining pressures in thisresearch are 50kPa, 100kPa, 150kPa, 200kPa.
During the test, water valve is kept oven due todrained condition requirement in CD test.

Table 1.Properties of soilParameters

ValuesDry density (ρd)
Optimum Water Content (W opt)
Specific gravity (ρs)
Cohesion (c)Angle of internal friction (φ)
Sand > 75 μm
Silt >5-75 μm
Clay <5 μm
Liquid limit
Plastic limit
Plasticity Index

1.80g/cm3
13.29%
2.589
1.52
23.23
85.00%
11.00%
4.00%
39.00%
26.80%
12.20%

Properties of Shell Husk
The Mactridae shell husk waste was collectedfrom the seashore closed to Mie University, Tsu city,
Mie Prefecture, Japan. Then the shell husks were
graded by performing sieve analysis. The finenessmodulus and the maximum size of the abandon shellhusks were 4.35 and 4.76 mm, respectively. The
shell size distribution curve is shown in Figure 2 andthe physical properties are given in Table 2.
Table 2. Physical properties of shell husk
Physical Properties
Values obtained
Water absorption
7.28%
Specific Gravity
1.75
Unit Weight (g/cm3)
1.57

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RESULT AND DISCUSSION

20% shell husk

Relationship Between Differential Stress (σa-σr)
and Axial Strain (ℇa)

As shown in Fig. 5, under different confiningpressure, for soil composite with 20% shell husk
when the axial strain (ℇa) getting higher, theprincipal stress difference (σa-σr) also increasing.
Initially, axial strain 0-2%, between the principal
stress under confining pressure 150 kPa and 200kPa
are slightly different. The ultimate principal stressdifference under confining pressure 150 kPa and
200kPa are decided at maximum 15% of axial strain.
Then for maximum principal difference stress underconfining pressure 100kPa and 50 kPa are obtained
between 3.0%-4.9% axial strain.

0% shell husk
In Fig. 3, the relationship between axial strain(ℇa) and principal stress difference (σa-σr) of soil
composite with 0% shell husk are illustrated. Thisgraph shows the increasing of axial strain (ℇa) alsoenhance the principal stress differences (σa-σr). For
confining pressure 200kPa, the 15% axial strain was
define as the ultimate principal stress difference
because the peak value has not achieved. On theother hand, under confining pressure 150kPa,
100kPa, and 50kPa the peak value was recognized ataxial stress (ℇa) 7.05, 4.25, 3.8% respectively.

Fig. 5 Differential stresses versus axial strain (20%shell husk)
Fig. 3 Differential stresses versus axial strain (0%shell husk)

30% shell husk

10% shell husk
Fig. 4 depicts the axial strain (ℇa) and principal
stress difference (σa-σr) of soil composite with 10%
shell husk. For confining pressure 200kPa and
150kPa, the ultimate peak value is 15% of axial
strain. However, the principal stress difference underconfining pressure 100kPa and 50kPa have peakvalue. For 100kPa the peak value at 3.5% axial
stress. Then for 50kPa the peak value at 2.1% axial
stress. From the graph also known that before peakvalue on 100kPa, the principal stress difference
between 100kPa and 150kPa are slightly different.

The curves of principal stress difference (σa-σr)
versus axial strain (ℇa) of composite with 30% shellhusk under several confining pressure are given in
Fig. 6. From this curve, could be seen only theultimate principal stress difference under confiningpressure 150kPa that decided until 15% axial stress.
For the ultimate principal stress difference underconfining pressure 200kPa is achieved at 10% axial
stress then decreased. Then the maximum principal
stress difference under confining pressure 50kPa and
100kPa are reached at axial stress 2.0% and 3.7%
respectively.

Fig. 4 Differential stresses versus axial strain (10%shell husk)

Fig. 6 Differential stresses versus axial strain (30%shell husk)

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Shear Strength of Soil Composition with Shell
Husk Percentages
The shear strength of soil from triaxial test,
internal friction (φ) and cohesion (C) are obtainedusing the Mohr-Coulomb failure criterion. The
triaxial test has failure surface that reflected the realstress-strain characteristic of samples compared todirect shear test. In triaxial test different conditions(drained,undrained,
consolidation,andunconsolidated) can be simulated. It could beunderstood that the triaxial compression test has
choose as the accurate and reliable method by many
researcher [8].
The shear strength (τf) of a soil is combination ofsoil cohesion (c) and internal friction angle (φ). The
calculations are obtained by Mohr-Coulomb
criterion as a linear function of the normal stress (σf)
on the plane at the same point which following by
the equation [9]:τf = c + σf tan φ

Fig. 8 Mohr-Coulomb failure envelop for soil with
10% shell husk

(1)Fig. 9 Mohr-Coulomb failure envelop for soil with
20% shell husk

The Mohr-Coulomb circles as representation ofsoil-shell husk composite according to triaxial testare presented on Fig. 7-Fig. 10. Internal friction is
the measure of the shear strength of soils due tofriction. Friction is attributed to displacement
between soil particles and materials which combine
soil and reinforcing materials together [8]. Theinternal friction comparison between percentages ofsoil-shell husks composite are shown in Fig. 11.
This graph shows additional shell husk percentages
increased the internal friction. The enhancement ofinternal friction along with the shell husk percentage
increasing is assumed due to the irregular shape ofshell husk particle which develop the frictional
resistance between particles. The internal friction ofsoil composite with 0, 10, 20, and 30% shell husk
are 35o, 37o, 38o, and 40o respectively.

Fig. 10 Mohr-Coulomb failure envelop for soil with
30% shell husk
Cohesion holds the particles of the soil together in asoil mass and independent of the normal stress [6].
In Fig. 12 could be seen the cohesion of shell husks
composite increasing up to 20% shell husk
percentages then decrease at 30% shell husk
percentage. The increasing of cohesion is assumed
due to the interlocking mechanism between soil andshell husks particles. On the other hand, decreasingcohesion at 30% shell husk is assumed due to theintegration limit between soil and shell husk
particles. The cohesion (c) of soil composite with 0,
10, 20, and 30% shell husk are 75, 90, 100, and 85.5
respectively. The trend of internal friction andcohesion were also occurred on previous researchwhich observed the shear strength of soil with shellhusk reinforcement using direct shear test [5].

Fig.7 Mohr-Coulomb failure envelop for soil with
0% shell husk

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Internal Friction (o)40These types of behavior were attributed with soilshell husk mixture under direct shear test. Moreresearch is needed to clarify this type of behavior ofsoil-shell husk mixture.

30

20

ACKNOWLEDGEMENTS
This research was supported by Mie University,
Japan and Sriwijaya University, Indonesia. Our
gratitude also to Mr. Ito for assistance during the
research.

10

0
0

10

20

30

REFERENCES

Shell husk (%)

Fig. 11 Internal
composite

frictionofsoil-shellhusks[1] Motamedi S, Shamshirband S, Hashim R,
Petkovic D, Roy C, ”Estimating unconfinedcompressive strength of cockle shell-cementsand
mixturesusing
softcomputingmethodologies”, April. 2015, pp: 49-58.
[2] Hossain, MZ, “Waste shell husks concrete:
durability, permeability and mechanicalproperties”. J. of Building Construction and
Planning Research. Vol. 1, Sept. 2013 pp. 61-66.
[3] Yoon G L, Yoon YW, Chae, KS, “Shearstrength and compressibility of oyster shell-sandmixtures”, J. Environmental Earth Science. Vol.
60, Oct. 2009, pp. 1701-1709.
[4] Park K., Jun S, Kim D, “Effect of strength
enhancement of soil treated with environmentfriendly calcium carbonate powder”, The
Scientific World Journal, Feb. 2014, pp. 1-11.
[5] Rachmawati SH, Zakaria MZ, “Utilization ofwaste shell husks for ground improvement”,
International Agricultural Engineering J., Vol.
26, March 2017, pp. 11-18.
[6] Arora KR, Soil Mechanics and Foundation
Engineering. Nai Sarak-Delhi: Standard
Publishers Distributors. 1978, Ch. 13.
[7] Das BM, Fundamentals of GeotechnicalEngineering, Third Edition, United States: SI
Cencage Learning, 2007, Ch: 3.
[8] Zhang CB, Chen LH, Liu YP, Ji XD, Liu XP,“Triaxial compression test of soil-root
composites to evaluate influence of roots on soil
shear-strength”, Ecological Engineering, Vol.
36, 2010, pp. 19-26.
[9] Mouazen A M, Ramon H, Baerdemaker JD,“Effects of Bulk Density and Moisture Content
on Selected Mechanical Properties of Sandy
Loam Soil”, Biosystem Engineering, Vol. 83,
2002, pp: 217-224.

Cohesion (kPa)

100
80
60
40
20
0
0

10
20
Shell husk (%)

30

Fig. 12 Cohesion of soil shell husks composite

CONCLUSION
The maximum differential stress (σa-σr) of soilshell husks composite were taken at 15% axial strain(ℇa) when there was not any softening behavior. It
was observed that differential stress (σa-σr)
increased with the increasing of the confiningpressure. Soil-shell husk composite with 20% shellhusk percentages under confining pressure of 200
kPa showed the highest differential stress ascompared to others.
From the triaxial tests, the shear strengths (τf) of
soil-shell husks composite were quantified in termsof internal friction (φ) and cohesion (c). It wasobserved that the shear strength of soil increased
along with the shell husk percentage increasing up to
20% shell husk then decreased at 30% shell husk.

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ANALYTICAL STUDY ON SINGLE PILE DESIGN FOR SOLAR
FOUNDATIONS FOR SLOPING LAND.
Alex Otieno Owino1, Hossain, M.Z.2, Ojiro C.3, Ozumi, S.4, Harada, H.5 and Okuyama, S.6
1
Graduate School of Bioreseouces, Mie University, Japan2
Cosmowinds Company Ltd., Nagoya, Aichi, Japan3
Beppu Construction Company Ltd., Yokkaichi, Japan
ABSTRACTIn accordance to rising queries in the global environmental concerns, such as climate change, environmental
sustainable development have become handy so as to rescue the environment from further degradation. Most
researches being done today focus mostly on the development of solar cells, architectural design of various typesof solar cells, reduction in size of the solar panels while improving the operation and energy tapping efficiency.
This paper therefore focuses on the main framework on the installation process which is the foundation. Thisconsists of a single pile composite foundation made from hollow steel pipe bonded to the ground by a thin layerof cement and sand mortar. The experiments done here aims at establishing the bearing capacity of single pilecomposite foundation with respect to pull out forces (uplift tension), compression (axial) forces and lateral forces
acting upon the structure upon full foundation installation and loading setup. The tests show the analysis of theinteraction of the forces. The tests include the axial compression test and the pullout test. The results shows thatthe pull out and the compressions loads applied are capable to hold the entire structure subject to naturalenvironmental condition.
Keywords: Solar Panels, Single Pile Foundation, Pullout/ Lateral/Compression Load –Deflection Relationship,
The most conventional way of laying the foundation
have been the use of steel reinforced concrete as
seen in most of the construction companies
worldwide not bearing in mind the financial
implications and cost- performance relations.
Nevertheless, foundations are designed so as towithstand extreme environmental condition such as
earthquakes, typhoons, cyclones, soil cohesion
variability and any other natural or artificial calamitythat may lead to structural failure.
This paper shows a simple composite foundation
design taking in to account cost-performance
relation, made from a hollow steel pipe andanchored to the ground by a cement- sand mortar.
The steel pile channels the entire load to the ground
while the sand – cement mortar improves the soil
bearing capacity as well as bonding the foundation
to the immediate soil structure thus provides
adequate frictional resistances and improved
cohesion owing to its relatively greater surface area
and roughness as compared to conventionalfoundation. The objective of this paper is todetermine the optimum permissible loading that thefoundation can withstand with respect to tensional(pullout) loading, axial (compression) loading,lateral loading and load displacement tests. The
failure modes of the tests are used to determine thefoundation strength and the optimal structureloading specifications.

INTRODUCTION
Energy demand is at growing level worldwide by
production industries and governments. With the
influx in the commodity demand most of theattention is being driven in the production of green
energy sources. Solar energy is a green energy
source that utilizes the radiant heat from the sun andis harnessed using different technologies like solar
heaters, photovoltaic cells, solar thermal energy
absorbers and solar architecture innovations.
The large magnitude of solar energy available tothe earth surface makes it a highly appealing andefficient source of energy. During the United
Nations Development Program in 2000 based on
World Energy Assessment, it was found that theannual potential of solar energy ranged from 1,575
to 49,837 exa-joules (EJ). This range was muchhigher than the total world energy consumption,
which was 559.8 EJ in 2012. [1][2]As at now much of the research being conducted
are based on the innovation on a wide variety of thesolar cells and the architectural design of different
size, shape and structure of the solar harnessing
material. In addition to the design parameters,
Somekawa et al has done the research on the effectsof the wind loading on the solar panels. This aims at
establishing a strong foundation that will resist any
horizontal loading subject to fluctuating wind speeds.
With reference to Japan Architectural Society andAihara et al. [3][4] the coefficients of wind loadpressures can be obtained to design the foundation.
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METHODOLOGY

PillarWind Load Calculations

H

Wind is one of the major forces that require loadtransmission to the ground. The maximum wind load
is assumed to act at an angle of 45°, [6] when withpressure is applied to the panel surface. Wind speed
is 40m/slope 10°.

Foundation

Ground Rebound

θ

h/2

M

δ

Pmax

h

L

Table 1 Wind load calculations
D
Item
Effective
projection area
Wind load(kg/m2)

Formula(Length *Width)

Wind load on
effective area
Horizontal wind
load
Right angle windload
Horizontal windload Force(Effective projection area *Wind load)(Wind load on effective
area* Sin 45°)(Wind load on effective
area* Cos 45°){(Horizontal wind load*
Sin 10°) + (Right angle
wind load* Cos 10°)}Kh{1/16 *(wind speed m/s)2 *Resistance coefficient }Passive EarthFig. 1 Moment diagram
Pressure

Engel method [8] shows that the root penetration
length if the foundation is determined when the
maximum ground reaction force (Pmax) is less than orequal to the Passive soil pressure strength (Pp).
Considering a rigid foundation, taking into accountthe depth, bottom surface resistance and an increaseof horizontal ground reaction force coefficient, Kh
by first order then the rotation angle (θ) and thecenter depth (h) is obtained by the following
formula;Rotational angle (θ) =Pillar Root Length Calculation Using Extreme
Ground reaction Force Method

Rotational center depth h =Ground reaction force (GRF) encompasses thetoleration of the force exerted by the ground to thefoundation pillar in contact with it. This acts as abaseline parameter in the calculation of foundation
strength taking in to account the overhead load to betransmitted, the bending moment of the pile
extension above the ground and the soil parameters
as shown in Table 2 below.

GroundCondition

horizontal force, H
Moment Bending, M
Width of column, D
Unit vol. weight, γInternal friction angle,
φWall friction angle, δAdhesive force, C

Kh

L.(4M+3H.L)
2.(3M+2H.L)

(1)
(2)

Maximum Ground reaction force occurs at h/2,
hence;
1

Pmax = 𝛿Kh = (h.θ).Kh. (h/2L)2

1

Pp = 2 .h.Kp.γ + 2.C.√(Kp)

Table 2 Forces and ground conditions
Item
Working
Load;
AppliedLoad
Pile dim.

12.(3M+2H.L)(4)

Cos 2 φ

Kp =

Value
3.28
kN
3.28
kN.m
0.13 m
18kN/
m3
30

(3)

Cos δ { 1 − √sin(φ + δ) sin(𝜑 + 𝛽)cosδcosβ

When Pmax is equal to Pp;
𝟏𝟏.h.Kp.γ + 2.C.√ (Kp) = 0
𝟐 (h.θ).Kh. (h/2L) - 𝟐(5)

Substituting equation 1 and 2 into equation 5;
3.Kpγ.D.H.L4 + 4.D. (Kp.γ.M + 4.C.√(Kp).H).L3 –3(9.H2 – 8.C.√(Kp).D.M).L2 - 72.M.H.L – 48.M2 = 0(6)Resistance width of the pile is considered to be,
D=3D according to Broms Method and theanalytical method of piles, Eq. (6) becomes,

10
0kN/m

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3.Kpγ.D.H.L4 + 4.D. (Kp.γ.M + 4.C.√(Kp).H).L3 (9.H2 – 24.C.√(Kp).D.M).L2 - 24.M.H.L – 16.M2 =0(7)
Replacing the coefficients of L with C1, C2, C3, C4
and C5 we have;
C1.L4 + C2.L3 – C3.L2 - C4.L – C5 = 0(8)ground level. The allowable empirical horizontal
displacements 10mm in normal situations and 15mm
in the areas prone to seismic process such as
earthquakes. Okahara et al [13] also states that thepermissible horizontal displacement is the larger
value of 1% of the pile diameter or 15mm in bothareas of normal conditions and seismic activity
prone areas. This was derived from the examinationof piles subjected to horizontal loads and theobservation of the elastic limits displacements on theload displacement curves.
The pile head displacement is a function of;y= {Qg, M, z, L, T, EI, kh}. Where T is the relative
stiffness factor, EI is the product of Modulus ofelasticity and the Moment of Area of the pilematerial, Kh is the Unit modulus ofsubgrade reaction. Hence the following equations.
y= {(Qg T^3)/EI} Ay
T= √ (5&EI/kh)
Ay is the displacement coefficient at the top of thepile, 2.435

Solution and Graph of the Quartic Polynomial
From Eq. (8) the fourth order polynomial can besolved to obtain four values of L3 ranging between 1.3 to 1.4 with the most positive number as thedesired value for pillar root length as shown in Fig. 2
below

Construction Material and Methods
The pillar supporting material used was a
76.3mm diameter steel pipe measuring 2m and sandcement mortar mixed at a ratio of 2.1 with watercement ratio of 2.1. The steel section was thenanchored into the ground at a depth of 1.3m. A
burrow was drilled using a precision drillingmachine set at right angles to the ground. An
additional 10cm was drilled to allow for thecomplete anchoring of the steel pipe to the ground as
shown in Fig. 4 below.

Fig. 2 Graphical representation of Pillar support
insertion length
By solving the fourth order equation, L = 1.4m [14]Foundation Depth versus Pile Shaft Diameter

length of pilefoundation,mFrom Eq. (7), a relationship between thefoundation depth and the pile shaft diameter can beanalyzed.

L1

2.5
2

L2

1.5
1
0.5

L3

0
0

2
diameter of pile section, m4

L4

Fig. 3 Pile Shaft Diameter against Pile Length

D1
D2
Fig. 4 Foundation set-up

Pile Displacement Calculation; Theoretical Value
With reference to previous analytical models [4],horizontal pile bearing capacity can be analyzed
with respect to the displacement that occurs at theWork Flow Diagram
A comprehensive

174

working

procedureisSEE - USQ, Brisbane, Australia, Nov.13-16, 2017displacement increases with an increase in the
pullout load. The graph is of a curvilinear shape withslow displacement from 3kN to 9kN for pile 2 thenfollowed by a more linear relationship up to 15kN
recording a displacement of 0.38mm. In Pile 1 thehighest permissible load gives a displacement of
0.85mm, this is due to the cohesiveness variabilityof the soil [9].

illustrated in the flowchart inn Fig. 5 below.

Site Survey
Allocation

Soil Analysis
Equipment and Material Preparation

Pullout Load,kN

Site Allocation; Boring, Pouring
mortar, Pile Insertion
CuringChecking
installation angle
and insertion length

Mortar Quality
Test

16
14
12
10
8
6
4
2
0

pile 1
pile2
0

Testing; Pullout Test,
Compression Test, Lateral
Displacement Test

1

Fig. 7 Pullout load-pile displacement relationshipThe result of compression loading shows anonlinear relationship with both piles showing an
increase in displacement as the compression loadincreases. Maximum displacement was recorded at
20kN with a minimal displacement of 0.7mm and
0.75mm for pile 2 and pile 1 respectively. This is
more so evident in the theoretical value which shows
linearity in the trend with minimum variations fromthe test data as shown in Fig. 8

Fig. 5 Working procedure flow chat.
Foundation Testing Methods
Once the foundation was fully cured it was
subjected to pullout (tensile) test, axial compression
test and the lateral displacement test. All the tests
were carried out in accordance to the Japanese
Geotechnical Society (JGS), 2014. Monitoring wasdone using the Linear Displacement Transducers(LDT) and readings recorded automatically withrespect to loading variations. Experimental setup is
as shown the Fig. 4 below.

Compression Load, kN

25
20

Chain
block

LVDT

0.5
Pile Head Displacement, mm

Load cell

15

pile 1

10

pile 2

5

pile
ref

0

Steel pipe

0

0.5
1
Pile Head Displacement, mm

1.5

Fig.8 Compression load –pile displacement
relationship
In Fig. 9, two phases of load- displacements
relationship is evident. The first phase is a slow
displacement phase from 0mm to 10mm as the loadincreases from 3kN to 13kN. The second phaseshows a linear relationship of rapid displacement

Fig. 6 Testing experimental setup.
RESULTS AND DISCUSSIONS
From Fig. 7 it is evident that the pile
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Lateral Load,kN

from 13mm to 30 mm with 2kN increase in loading.
Failure point is recorded at 14kN lateral loading.

16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
0.00

Fig.9

M
Kp
γ
φ
C
δ
β
L1
D2
L4
L2

deflection
curve
def ref

REFERENCES
10.00
20.00
30.00
Deflection, mm

40.00[1] Somekawa D., Koizumi T., Taniguchi T. andTaniike Y.: Wind loads acting on thephotovoltaic panels arrayed near ground， The
22nd Wind Engineering Symposium, pp.157160, 2012
[2] An Elastomeric Insole For 3-Axis Ground
Reaction Force Measurement. 1st ed.
Washington, D.C.: United States. National
Nuclear Security Administration, 2012.
[3] Engel, Michael W. Evaluation Of Barnes'
Method And Kriging For Estimating The Low
Level Wind. 1st ed.: Biblioscholar, 2012.
[4] Honjo, Y. Foundation Design Codes And Soil
Investigation In View Of International
Harmonization And Performance Based Design.
1st ed. Lisse [u.a.]: Balkema, 2002.
[5] Hamada, Masanori, and Takeshi Koike.
Critical Urban Infrastructure Handbook. 1st ed.
Boca Raton, Fla: CRC Press, 2015.
[6] Reese, Lymon C, and W. F Van Impe. Single
Piles and Pile Groups under Lateral Loading.
1st edition.
[7] Okahara, M., Nakatani, S., & Matsui, K. 1991a.
A study on vertical and horizontal bearing
characteristics of piles, JSCE J. of Struct.
Engrg. 37, 1453-1466. In Japanese.
[8] Okahara, M., Takagi, S., Nakatani, S., &Kimura, Y. 1991b. A study on the bearing
capacity of single piles and design method ofcolumn shaped
foundations.
Technical
Memorandum of PWRI (2919), Public Works
Research Institute. In Japanese.
[9] Cosmo
WindsCompany
Limited,http://cosmowinds.jp/solar/studio/[10] Beppu Construction Company Limited,
http://www.o-beppu.co.jp/[11] "2014 Key World Energy Statistics" (PDF).
iea.org. IEA. 2014. pp. 6, 24, 28. Archived

Lateral load- pile displacement relationship

CONCLUSION
This research study shows that the design ofcomposite foundation can be achieved using very
simple techniques in the construction industry taking
in to consideration the economic factors such as
minimum cost evaluation and minimum material
usage. The foundation is of high strength as it canwithstand loads up to 20kN as evident during
compression loading. This is with reference to thedesign loading of 3.28kN.
The Inclusivity of seismic loads to the working
load in the foundation length design gives a clear
indication of strength as it can withstand the design
load of 3.28 kN and an additional 16kN. The pullout
loading, compression loading and the lateral loading
bearing capacity of the foundation shows that thefoundation is able to withstand the wind loads at 40m/s inclusive of the solar panels installation design
weights without any risks of failure.
ACKNOWLEDGEMENTS
I express my thanks to Japan International
Cooperation Agency (JICA) for the financial
assistance and cooperation in the entire design
process.
APPENDIX
D1
L3
Kh
H

Working Bending Moment.
Passive earth pressure coefficient
Unit volume weight of soil (kN/m3)
Internal friction
Viscosity (kN/m2)
Wall friction angle
Ground surface inclination angle (degrees)
Solar panel length
Foundation diameter.
Pile - wall clearance
Pile height above ground

Width of strut, pile diameter.
Pillar support insertion length
Horizontal ground reaction coefficient
Horizontal action force, Bending Moment.
176

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017from the original on 5 May 2014.
[12] "Energy and the challenge of sustainability"(PDF).
UnitedNations
Development
Programme and World Energy Council.
September 2000. Retrieved 17 January 2017.
[13] JIS C8955: Japanese Industrial Standards,
Design guide on structures for photovoltaic
array, 2004．
[14] JIS C8917: Japanese Industrial Standards,
Environmental and endurance test methods forcrystalline solar PV modules, 2005．
[15] Aihara T., Asami Y., Nishimura H., Takamori
K., Asami R. and Somekawa D.: An area
correct factor for the wind pressure coefficientfor cladding of hip roof －The case of squareplan hip roof with roof pitch of 20 degrees－
The 22nd Wind Engineering Symposium,
pp.339-344, 2008．
[16] AIJ2004: Architectural Institute of Japan,
Recommendations for Loads on Buildings,
2004．

177

SEE-USQ 2017, Brisbane, Australia. Third International Conference on Science,
Engineering and Environment (SCOPUS & ESCI Journal)

EXPERIMENTAL BEHAVIORAL INSPECTION OF COMPOSITE
CONCRETE-OPEN WEB EXPANDED STEEL BEAMSEXPOSED TO STATIC LOADING

1,2

Nazar K. Oukaili1 and Seezar Sh. Abdullah2
College of Engineering, University of Baghdad, Iraq

ABSTRACTThe behavior of composite concrete – open expanded steel beams (castellated and cellular) under effect of
flexure was studied experimentally. Two strengthening technics were implemented (strengthening by adding
intermediate stiffeners only or strengthening by both external prestressing and intermediate stiffeners). The
experimental program was designed in such way that six composite concrete- open web expanded steel
specimens were tested, which are simply supported over a span of 2900 mm and divided to two main groups.
Each group has three specimens, which designated according to the type of the strengthening technics, (reference
specimens without strengthening, specimens with intermediate stiffeners, and specimens with externalprestressing in addition to intermediate stiffeners). The bending moment was created by exposing theexperimental specimens to two-point loads. Carrying capacity, load-deformation responses, and strain in both
concrete and steel were recorded and analyzed. The experimental results show that the first strengthening
technique improved the load carrying capacity by 26% for castellated specimens and 21.8% for cellularspecimens, respectively. Meanwhile, the second strengthening technique enhanced the load carrying capacity by
186 % for castellated specimens and 134.3% for cellular specimens, respectively. It is worth to mention that, thefirst technique reduced the mid span deflection under service loads by 25% and 22% for castellated and cellularspecimens, respectively. While the second technique decreased, the mentioned values by 56% and 61% forcastellated and cellular specimens respectively.
Keywords: Castellated, Cellular, Composite , Flexure, Strengthning, External Prestressing

widely in multi-story buildings, hospitals, industrial,commercial, warehouse buildings and any structurewith suspended floor, where the web-openings used
for passage of the services, resulting in saving theheight of the structure [3].
The existence of opening in the web alters thestress distribution within the member and influences
its collapse behavior. Accordingly, the strength ofthese beams may be governed by the plastic
deformation that occur due to moment and shear
effects at openings.
The load carrying capacity of these types ofbeams will be reduced at the opening because of the
reduction in the contribution of web to the moment
capacity. This is not very significant, as usually thecontribution of the web to the moment capacity isvery limited. However, the reduction in shear
capacity at the opening can be significant. Therefore
the ultimate capacity under the combined action of
moment and shear at the section where there is an
opening will be less compared to that at the normal
cross section without opening.
To restore the strength lost, strengthening withintermediate steel stiffeners, which should be weldedto the web between openings, could be used.
However, compared to such scheme, the use of post-

INTRODUCTION
Open web expanded steel beam is a namecommonly used for a specific type of standard hotrolled steel I-beam sections. It is made by cutting the
web of the original steel beams in a regular pattern,
separating into two halves, and rejoined by welding,(after offsetting one portion), to create a regularholes shape in the web such as castellated andcellular shapes [1].
The advantage of open web expanded steel
beams coming from improving the strength due toincreasing the section depth without increasing theself-weight. In some instances, the depth isincreasing as much as 50%, and by these increasing,strong axis bending strength and stiffness is
improving as the strong axis moment of inertia Ix,
section modulus Sx, are increasing, more holes also
allow plumbing pipelines and electrical conduits
pass through them ultimately reducing the elevationof floor level [2].
With the development of buildings construction
and the desire to make them capable to resist theapplied loading with low cost, composite concrete –open web expanded steel beams have been use invarious designs of structural buildings. They used178

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

tensioned external tendons to strengthen thesegirders is relatively simple technique and economic
method to employ also.
Few studies have been conducted on the
behavior of composite concrete-open web expanded
steel beams under flexure with or without
strengthening technique. In the current study, thecircular, and hexagonal castellation has been chosen
to show the effect of different strengthening
techniques on the global behavior of suchconfiguration under the flexural effect.
The objective of this investigation was to
examine experimentally the benefits of steel
stiffeners and external prestressing as used instrengthening of composite concrete – open web
expanded steel beams and to evaluate their effect on
both the service load behavior and nominal carrying
capacity.

The length of the channel was chosen as 50 mm
centered above the upper ﬂange. The concrete deckslab above the steel beam was 60 mm in thickness
and 500 mm in width. It was reinforced in both
directions by mild steel rods of 6 mm diameter
which spaced 150 mm c/c.
For specimens subjected to external prestressing,
two low - relaxation seven - wire steel strands, with12.7 mm diameter, (Grade 270), were used andlocated at symmetrical distances of 100 mm fromeither sides relative to the longitudinal axis of thecomposite beam. The two strands were tensioned
simultaneously from one end. Special care was
exercised to balance the prestressing force in thestrands to avoid biaxial bending of the specimens.
The wedge anchored prestressing strands were
supported directly on an 200 mm wide x 300 mm
deep x 20 mm thick bearing plate attached to theends of the beam, where two holes were formed tofacilitate the application of the prestressing. Draped
external tendon profile was adapted for the test
specimens. Two deviators around the third points ofthe span consisted of 25 mm diameter cylindricalrod welded to the bottom surface of the steel section.
The steel strands were stretched and anchored to thevertical steel bearing plate using Supreme Productanchorage chucks (grips). The prestressing force wastransferred to the steel strand through the use of
hydraulic jack of 20 tons capacity and a stroke of
150 mm. The target effective prestress fpe in theexternal prestressing steel was 40% of the ultimate
strength of the strand fpu. The corresponding stress
was monitored accurately using readings of thestrain gauges attached to the surface of theprestressing strands along with the readings of thepressure gauge of the hydraulic jack used in theprestressing operation. Figure 1 shows details of thesections after castellation process. The longitudinalprestressing steel strands, welded wire fabric of slab
reinforcement, and steel for web, ﬂanges, stiffeners,
and shear connectors had different mechanicalproperties which are summarized in Table 1.
The concrete mix was prepared using Type I
cement, crushed stone of 10 mm maximum
aggregate size and fine river sand. By weight thecement: sand: aggregate proportion was 1:1.5:3 withwater/cement ratio of 0.45.
The concrete compressive strength was
determined from three standard 150 x 150 x 150 mm
cubes taken from each specimen, where the target
value was 32 MPa. The concrete deck for all
specimens was cast horizontally in wooden forms.

EXPERIMENTAL PROGRAM
Six composite concrete – open web expanded
steel specimens divided into two groups according tocastellation shape (cellular (CEB) and castellated(CB)) were fabricated and tested as simply
supported over an effective span of 2900 mm. All
specimens had the same cross – sectional
dimensions where the total height of the beam was
360 mm, which divided into 60 mm concrete deckslab and 300 mm hot-rolled I-beam as the steel
section.
The steel IPEA - section with overall height of
200 mm was chosen to fabricate the cellular andcastellated steel section. Electric cutting was thenused to split the web into two parts where one partwas shifted half a pitch to obtain the shape ofcastellation. Finally, the steel section was assembled
using continuous electric welding of 3 mm thickness
on both sides, the end of the beam was then polishedand the extra parts of castellation were cut to obtaina castellation section of total height of 300 mm andtotal length of 3000 mm.
The success of composite action depends on theshear resistance at the interface between the steel
beam and the cast-in-place deck to allow fulltransfer of stresses. Thus, a good connection
between the two components of the composite
system is essential. To achieve full connection
between the steel cellular or castellated I-section andthe concrete deck slab, rigid shear connectors wereused in form of channel section of total height of 40
mm and ﬂange width of 30 mm. The thickness of thechannel was constant for both web and ﬂange andwas equal to 3 mm, while its spacing was 150 mm
perpendicular to the longitudinal axis of the beam.
179

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

posts. While the third specimens, (CEBP and CBP),
were subjected to external prestressing in addition tousing vertical intermediate steel stiffeners. All
specimens were strengthened at the end zone byﬁlling the ﬁrst castellation.
It should be mentioned that, the externalprestressing was applied to the steel cellular Isection before pouring the concrete of the deck slab.
All specimens were loaded in four-point bending
using two symmetrical concentrated loads applied at
one-third the span length. The test was conductedusing closed loop ram with 50 ton capacity actuator.
Specimens were subjected to a monotonicallyincreasing load to failure using a load control test.
All measurements, such as beam deflections,strains in concrete, steel strands and steel section
were recorded twice, immediately after theapplication of the load and after 10 minutes later.
EXPERIMENTAL RESULTS

Fig. 1

Detailed analysis and comparison among the twogroups have been conducted considering thefollowing: mode of failure; carrying capacity; loaddeformation responses.
Eight failure modes for castellated and cellularbeams are known [4]: flexural mechanism; lateral
torsional buckling; distortional buckling; web-post
buckling due to shear force; web-post buckling due
to compression force; Vierendeel or shear
mechanism; rupture of welded joints; and ultimate
deflection.
In the current investigation, the failure due tolateral torsional buckling was not happened due tothe stiffness achieved by the concrete deck slab. As
for the rupture of welded joints, this mode of failure
was excluded as the welded joints were properly
designed. Also, failure due to ultimate deﬂection
could not have been possible to observe since thetested specimens were loaded until the complete
collapse had occurred.
For the control cellular specimen (CEBR), thefailure was characterized by local buckling of webpost, at section located directly under theconcentrated load, due to shear force and Vierendeel
mechanism, The remaining specimens (CEBS and
CEBP) failed by a combination of failure modes
such as flexural mechanism and Vierendeel or shear
mechanism. In the same manner, for the control
castellated specimen CBR, the failure was web post
buckling, while specimens strengthening by adding
intermediate stiffener (CBS) failed by flexural
mechanism, finally specimen strengthening byexternal prestressing was failed by flexural
mechanism caused compressive failure of concrete
deck slab. Table 2 and Plate.1 show failure modes of
all tested specimens.

Details of experimental specimens.

One day after casting, the standard cubes and thesides of the deck slab were stripped from the molds
and covered in wet material. The deck slabs werecovered until the seventh day, when the wet material
was removed and the specimen allowed air-drying
until testing.
Table 1 Mechanical properties of steel components
Component

Thickness
(mm)
5.6
8.0

Yield
Stress(MPa)0397.870378.95

Ultimate
Stress(MPa)0520.520519.80

Plate for web
Plate for top
and bottom
flanges
Plate forstiffeners
Plate for shear
connectors
Welded wire
fabricPrestressing
steel strand

6.0

0394.710520.523.00246.140332.79

Φ = 06.0

0456.620615.60

Φ = 12.7

1675.00

1862.00

Each group has three specimens, which
designated according to the type of the strengthening
techniques used. The ﬁrst specimen of each groups,(CEBR and CBR), has no strengthening andconsidered as a control specimen. The second
specimen of each groups, (CEBS and CBS), wascharacterized by strengthening using verticalintermediate steel stiffeners at both sides of all web180

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

Table 2 Failure modes of experimental specimens
Specimen
designation

Pu
(kN)

Mode of failure

CEBR

160.0

CEBS

195.0

Web-post buckling due toshear force plus Vierendeel
mechanism
Flexural mechanism

CEBP

375.0

CBR

115.0

CBS

145.0

CBP

330.0

a

decreased, the mentioned values by 61% and 56%
for cellular and castellated specimens, respectively.
It was noted that, using these strengthening
systems excluded certain failure modes, which arecommonly happened with open web expanded
beams. Figure 3 show load – deflection diagram oftested specimens.

Vierendeel or shear
mechanism
Web-post buckling
Combined flexural andshear mechanisms
Vierendeel or shear
mechanism
b

c

d

e

f

Fig. 2

Ultimate
capacityof
specimens according totechniques.

experimental
strengthening

Fig. 3

Load -midspan deflection of all specimens.

The strain of the steel section and concrete deckslab were measured at each loading stage using
different strain gages. These electrical strain gages
were installed at different levels of the steel web,steel flanges, and at the extreme top and bottom
concrete fibers of the deck slab, Fig. 4 – Fig. 9 show
variations of strain across the section depth inconcrete and steel beam depending on the applied
load level. The experimental results of cellularreference specimen (CEBR) show that strain in
concrete fibers varied across the thickness of thedeck slab from compression to tension which
increased with the increasing of the applied load
level approaching -1300x10-6 in extreme top fiberand +169x10-6 in extreme bottom fiber as the load
attained the ultimate level. Meanwhile, the tensile
strain values in extreme fibers of the bottom flangeof the steel section reached +1248x10-6 at ultimate
load. It is noted that, using intermediate stiffeners
produced rising of the load carrying capacity anddecreasing of strains in concrete by 4.5% in extreme
top fibers and 18% in extreme bottom fibers,

Plate 1 Failure modes of experimental specimens,(a) CEBR, (b) CEBS, (c) CEBP, (d) CBR,(e) CBS, and (f) CBP.
In term of ultimate load carrying capacity, it canbe seen that, adding stiffeners to the web section as afirst strengthening technique led to improve the load
carrying capacity by 21.8% for cellular specimens,
and 26% for castellated specimens, respectively. In
the same manner, using external prestressing withintermediate stiffeners as a second strengthening
technique enhanced the load carrying capacity by
134.3 % for cellular specimens and 186 % forcastellated specimens, respectively. Figure 2 showsthe effect of strengthening techniques on ultimate
capacity of the tested specimens.
It is worth to mention that, the first techniquereduced the midspan deflection under service loads
by 22% and 25% for cellular and castellated
specimens, respectively. While the second technique181

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

respectively, while the tensile strain in extreme
fibers of the bottom flange increased by 16.5% incomparison with the above mentioned value of thereference beam. While for the specimen subjected toexternal prestressing with stiffeners, it was observed
that, the strain decreased in extreme top and bottom
concrete fibers by 24% and 34%, respectively.
Meanwhile, the strain in the extreme fibers of thebottom flange was decreased by 9% in comparison
with the reference beam (CEBR).
Moreover, results of castellated reference
specimen (CBR) show that the strain in concrete
fibers followed the same manner of changing acrossthe thickness of deck slab with the excessive
increasing of the applied load. Accordingly, atultimate load the concrete strain attained -1225x10-6
and +179x10-6 in extreme top and bottom fibers,
respectively. Also, the tensile strain in extreme
fibers of the bottom flange approached +1560x10-6.
For the castellated specimen strengthened byintermediate stiffeners (CBS), strain in top andbottom concrete fibers of the deck slab decreased by
51% and 35%, respectively. While, strain in steel ofthe bottom flange decreased by 24%, in comparison
with reference castellated specimens (CBR). In thesame manner, for the specimen subjected to externalprestressing with intermediate stiffeners, it was
found that, the strain decreased in extreme top andbottom concrete fibers by 18% and 10%,respectively. Also, the strain in the extreme bottom
flange fibers was decreased by 7.5% in comparison
with the reference beam (CBR).

Fig. 6

Strain across section level of CEBP.

Fig. 7

Strain across section level of CBR.

Fig. 4

Strain across section level of CEBR.

Fig. 8Strain across section level of CBS.

Fig. 5Strain across section level of CEBS.

Fig. 9Strain across section level of CBP.

182

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

The strain increment in the external prestressed
strands due to applied loads in cellular specimen(CEBP) and castellated specimen (CEBP) was
indicated in Fig. 10, where these values attained at
failure 1526 x 10-6 and 1416 x 10-6, respectively.

Fig. 10REFERENCES[1] Erdal, F. and Saka, M. P. “Ultimate load
carrying capacity of optimally designed steel
cellular beams” Journal of Constructional Steel
Research, Vol. 80, No. 1, 2013, pp. 355–368.
[2] Hosain, M., Cheng, W. and Neis, V. “Deflection
analysis of expanded open-web steel
beams” Computers & Structures, Vol. 4, No. 2,
1974, pp. 327–336.
[3] Lorenc, W. and Kubica, E. “Behavior ofcomposite beams prestressed with externaltendons: experimental study” Journal ofConstructional Steel Research, Vol. 62, No. 12,
2006, pp. 1353–1366.
[4] Kerdal, D. and Nethercot, D. “Failure modes forcastellated beams” Journal of Constructional
Steel Research, Vol. 4, No. 4, 1984, pp. 298–
315.

Load – strand strain increment diagram.

CONCLUSIONS
Based on the studied configuration of strengthening
the composite castellated and cellular beams
subjected to incremental monotonic static loading,the following conclusions can be drawn:
1. Adding vertical stiffeners at all web posts leads
to increasing the ultimate capacity by 26% forcastellated specimens and 21.8% for cellularspecimens, respectively.
2. Using external prestressing in addition to vertical
stiffeners leads to increase the ultimate load
capacity by 186% for castellated specimens and134.3% for cellular specimens, respectively.
3. The first technique reduced the midspandeflection under service loads by 25% and 22%
for castellated and cellular specimens,
respectively. While the second techniquedecreased, the mentioned values by 56% and61%, respectively.
4. Applying external prestressing technique withintermediate stiffeners, led to more ductility inperformance of specimens comparing withreference beams by decreasing strain overconcrete and steel section with respect of highultimate load carrying capacity.

183

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

RESIDENTIAL CUSTOMER DEMAND RESPONSE PROGRAM IN
MICROGRID SYSTEM: A SURVEY LITERATURE
Ignatius Rendroyoko1, and Ngapuli I Sinisuka2
School of Electrical Engineering and Information Technology - Institute Technology of Bandung,Indonesia; 2 2Smart Grid Team PT PLN (Persero), Indonesia

1

ABSTRACTElectricity supply in microgrid power systems often faces limited power supply constraints. Besides to add
more power generation, efforts to provide sufficient power in the power system can be made by controllingelectricity load. A demand-side management (DSM) program can be done to regulate energy consumption andlimit peak loads. The demand response (DR), as one of the DSM program, can be implemented to regulate theelectric load to balance supply and demand. Residential customers demand response is a program that aims to
reduce peak load by shifting or shedding residential electricity loads. This load reduction method has been used
to control the peak load to be able to adjust to power supply conditions. This paper presents a literature survey ofpapers that address the application of DR for residential customers. The study uses the assumption that majorityof electrical loads in microgrid systems are residential customers. It is expected that a balance between supply
and demand for electricity in the power system can be achieved through demand response activities forresidential customers. Here, a review of effective demand response methods is performed to precisely andaccurately regulate the use of electricity by residential customers to limit peak load and control electrical energy
consumption. In the end, this paper also discusses the possible implementation of demand response method forresidential customers on a microgrid system.
Keywords: Residential customers demand response, Load and power supply balancing, Electricity price,
Incentives, Efficiency, Home energy management system

Charles River Associates (2005) mentioned that the
DSM has two main categories: energy efficiency anddemand response (DR) [1]. The purpose of energy
efficiency is a reduction of energy consumption, andthe implementation of the DR refers to load profile
adjustment, by implementing load shifting, shaving,and shedding, driven by market incentives [5].
DR scheme is an ability of an electric customer
to reduce kWh usage or kW demand over a period or
shift the usage to another period, in response to priceor financial incentives [1]. Considering that thebiggest part of electricity customers consist ofresidential customers, then DR program forresidential customers may have a huge potential inelectrical load controlling [6]. In electric powersystems in remote areas or islands such as inIndonesia, where electricity supply is limited, DR
schemes can be one of the appropriate ways tomanage electricity loads, to be adapted to the electric
power supply capability.
The proper design and scenario of DR
implementation for residential customers will
determine the successful implementation of
intelligent electricity demand management to change
the customer load profile. Therefore, some types oftechnology schemes, business models, and methodsof implementation of the DR program for residential
customers must be mastered and identified for the
successful implementation of the program.

INTRODUCTION
In the development of micro grid power system
to provide electricity supply for customers, often
encountered constraints of a limited power supply ofelectricity. These problems are generally overcome
by adding capacity of power plants, including RE
generators, which is integrated into existing powersystems to increase power capacity. Besides adding
power generation, efforts to create a balance
between supply and demand in power systems bycontrolling the electrical load. Here, the balance
between the supply of electric power and variableload must be regulated and maintained [1].
On the demand side of a power system,
controlling electrical loads and load scheduling canbe done by using demand side management (DSM)
method, with the aim to balance the load andelectricity power supply. DSM is a method toregulate customer’s demand load intelligently byreforming the load profile through efforts to change
energy consumption patterns of electricity customers[2], [3]. Peter Palensky and D. Dietrich (2011) stated
DSM could be used to intelligently influence theload, rather than building a new power plant [4]. The
concept of DSM was first developed by utility withan aim to influence the customer's use of electricity[2]. In the report of EPRI (1993), utilities have load
control programs that encourage the DSM programs.
184

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

 DR Scheme based on the electricity price
Changes in the use of power and kWhconsumption refer to electricity prices paid bycustomers, which consist of real-time pricing (RTP),
critical peak pricing (CPC) and the time of use(TOU). When prices change, customer will react toadjust to changes in electricity rates according to thetime so their consumption patterns will change.
Peter Palensky (2011) describes that residential
customers may join on DR activities by looking on
real-time pricing and price signals [4]. P.T. Baboliet.al (2012) find that if the price gap between time
periods are significant, customers will adjust thetiming of their flexible loads to take advantage oflower price periods. Customers’ reaction against
implementing price-based DR is much important [8].

This paper presents a literature review of papers
discussing the development, and implementation of
DR program for residential customers. In general,
discussions address the objectives, general concepts
and technology schemes that are applied toresidential customers. In particular, the review will
focus on residential customer demand response
optimization
algorithms,
controlschememechanisms, program scheduling, and types ofoffers provided to motivate residential customers toparticipate in DR programs. Finally, it is discussed
the implementation of DR schemes for residential
customers on a microgrid power system to create abalance between demand and supply.
DEMAND RESPONSE CONCEPTThe concept of demand response (DR) for
residential customers can be described as a program
to reduce peak load of electricity usage of residential
customers by shifting or shedding electricity
consumption, in response to power supply
conditions.

 DR schemes based on incentives
This scheme is provided by the utility or network
operator. Here, customers will receive an incentive
for any reduction in electricity usage. Some utilities
also impose penalties when there are customers whoalready have a contractual obligation reduction in
consumption but fail to comply. In their research on
incentive-based DR program (IBDRP), James C
Holyhead (2015) suggests that in the implementationof DR, especially on the incentive-based, optimal
selection of customers must be performed, and betargeted to customers whose expected behavior leads
to a reduction in the cost to the supplier [9].

Main Objectives of the DR Scheme
Residential DR program refers directly todemand side management (DSM) which has main
purposes as follows:
The first main purpose is the reduction ofdemand peaks of electricity usage in residential
customers. Rajasekhar B. and Naran M. P. (2015)
stated that the purpose of residential DR program is
the reduction of electricity consumption by shifting,shaving and shaping electricity usage for residential
customers, both individuals and customer groups [7].
The next purpose is to change the behavior ofresidential customers, so the load profile ofresidential customers may be modified into more
adaptable load profile to electrical power system
condition. Robin Roche (2012), mentioned thatchanges in residential customer load profiles could
be done using new technologies and the function of
DR aggregator [6]. As the load profile changes, DR
can also reduce the possibility of overload
conditions. Another important purpose isencouraging the reduction of large-capacity power
generation [3]. When the load reduction can be
carried out by DR scheme, it will directly reduce theneed to operate the expensive power plants
Work Mechanism of Demand Response
In implementing the DR scheme, one of theimportant things is how to make customers
interested in participating in the program. This
review on numbers of the mechanism of DR
implementation will be a good reference for its
practice on microgrid power system. Here, DR
schemes can be classified according to themechanism offered so that customers can beinterested or willing to participate.

 DR programs imposed by state or utility
The implementation of DR is done by requiring aparticular group of residential customers toparticipate. In this way, the percentage ofparticipation will be high, and the effect on theelectrical system will be very influential.
Based on the above discussion, it is understoodthat the method to implement DR programs forresidential customers will largely determine its
success. Especially on how to give an explanation on
residential customers about the importance offollowing the DR program with the option ofcompetitive electricity prices or incentives offered.
Here, the mindset change is required, whereknowledge and awareness about energy management
and efficiency also depend on customer engagement.
In the implementation of DR for residential
customers, Rajasekhar B. and Naran M. P. (2015),
states that residential customers tend to follow DR
schemes based on the price offered. Depending on
pricing scheme used, DR programs may operate inreal-time, while others may work on a daily/hourlyscheduling basis. For individual residential
customers coordination of day-ahead scheduling andreal-time DR need to be focused on optimization
strategy of usage time. At the group of residentials
level, cooperative methods will result in greater
impact on efficient and economical distribution
network operations [7].
185SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Meanwhile, P.T. Baboli et.al (2012), state thatthe successful implementation of the above two DR
schemes depends on customer behavior. The resultsof research that have been implemented on a single
customer and multi-customer give results thatincentive-based DR schemes can be successful witha formation of customers habits. This is dependent
on proper education and publicity programs [8].
Amir and Alberto (2010) presented on theirstudy that although the price-based DR scheme has
several advantages, it’s limited due to the lack ofautomation systems (HEMS) and real-time pricing
scheme cannot be executed manually. Therefore,scheduling the consumption of electrical energy forresidential customers is proposed to be done
automatically to provide more optimal results [10].
On coordination between systems and equipment
in demand response, Bingnan Jiang and Yunsi Fei(2011), expressed about the concept of dynamic
demand response and management of distributed
generation (DG) for the implementation of DR in a
residential community [11]. With conditions
dynamically update mechanism, the DR will operate
automatically according to the latest condition.
Results show the effectiveness of this management
system on the energy consumption cost reduction.

concept of HEM system, proactively and effectively,
able to control and manage the operation ofhousehold appliances to maintain overall electricalenergy consumption to keep them under a certain
limit. Here, HEMS has operated with priorities ofboth the load and customer comfort level settings.

Figure 2 Architecture of HEM system
Both of the concepts above discuss thearchitectural scheme of DR for residential customersof an individual home. The resource management
electricity of individual customer is managed
separately by separating the operational plans ofhome appliances, energy storage systems, andrenewable energy resources, as well as manage
energy deals with the electricity system network.
DR Method Based on the Decision Variable
DR methods can also be grouped by decisionvariables into two main groups: the first group refers
to the DR program that decides when to activate therequested electrical load, while the DR program in
the second group determines the amount of energythat can be allocated for each consumer, Vardakaset.al. (2015). In the method of DR with load
scheduling, the most important thing is controllingthe activation time of requested load [14]. In here,
the load is divided into two types:
1. The type of load that must be operable andnot allowed any failure or delay time of theentry load (such as lights and refrigerators).
2. Type of load that can be scheduled and may
be discontinued, adjusted, or can be shifted toanother time slot.

Architecture and Components Framework DR
SchemeArchitecture and components of the scheme ofDR, described by Antimo Barbato and Antonio
Capone (2014). Specifically, individual user
methods are designed to manage users' electricalresources individually, while for cooperative
consumers, users collaborate in determining theiroperating plans [12]. The frameworks for DSM aredesigned to be able to adjust its user’s power source
optimally, as shown in Figure 1 below.

In the implementation of DR with decision variable,
James C. Holyhead et.al. (2015) stated that thesuccess of the program of acceptance of customers
demand reduction could be improved by targeting acertain group of customers in the program.
Evaluation of the algorithm against a classicalapproach that sees all customers within a group istargeted at reduced demand for a period with the useof maximum demand and indicates that solutions
with targeting customers show greater peak
reductions and increased cost savings [9].
Mohammad Rastegar et.al (2012), suggested in
an article, an optimal framework for the
implementation of commitments and an automatic

Figure 1 Frameworks architecture of DR
Figure 1 shows the basic components of DSM. It
consists of power generation, power monitoring
system, sensors, energy storage, and energy
management unit (EMU). The EMU works as adevice to exchange information with other devices inthe system and manage resources electricity of theuser based on demand response mechanism [12].
In another paper, M. Pipattanasomporn, Murat
Kuzlu, and Saifur Rahman [13] states that the186SEE - USQ, Brisbane, Australia, Nov.13-16, 2017load of residential customers [15]. Here, the issue ofload commitment (LC) is formulated with a purpose
to determining the status on/off for responsive
equipment. This formulation expanded to combine
the capabilities of direct load control (DLC).
The importance of decision-making in thescheduling of operating equipment is also discussed
by Alessandro et.al (2011), mentioned that inresidential home, the problem occurs at the time ofscheduling the operation of equipment, to be able toadjust with goals of cost savings and convenience
related to the weather, and timeliness [16].
The second DR method is based on energy
management by limiting or decreasing power
consumption of specific loads, so the total power
consumption in the peak load period will go down.
This is implemented by controlling operation ofdomestic electrical appliances that will consume lesspower when the power capacity limitations in the
power system [17].

facilities. Therefore, the potential of DR scheme forvarious home appliances needs to be assessed as aconsideration in designing DR algorithms.
Adam Taylor et.al. (2014) delivered on theevaluation of several algorithms have been designed
to include a variety of conditions on the applicationof DR [18]. It was concluded that the algorithm
residential DR should be following the structure of
the electricity network so that the compliance
between the data acquisition and dissemination ofcontrol commands can be synchronized without any
significant delay time.
In specific about the load profile, Sara Ghaemi
and Gunther Brauner (2010) presented the results ofan analysis of the stochastic model for generating
customer load profile [19]. This model can allow for
the assessment of potential energy savings throughthe replacement of energy-saving devices andchanging the customer’s behavior.
OPTIMIZATION MODEL FOR RESIDENTIAL
CUSTOMER DEMAND RESPONSE
In this section, a review of the optimization ofseveral DR schemes : for single houses, and for agroup of houses or communities. The optimization
process is defined as a process of discovering theconditions that provide a maximum benefit orminimal cost of a process [7]. The research which is
conducted on optimizing the DR program aimed atminimizing power consumption while maintaining alevel of customer comfort.

RESIDENTIAL DEMAND RESPONSE AND
HOME ENERGY MANAGEMENT SYSTEM
In performing the DR scheme for residential
customers, the key to successful implementation of
the program may depend on the willingness ofcustomers to participate in the program. For
residential customers who are willing to follow the
program this DR scheme, customers should also beable to implement energy management in eachresidential home (home energy management) [7].
Implementation of HEM can be done manually
and automatically using auxiliary equipment ofenergy management. For manual implementation,
HEM can be conducted by always informing
customers not to operate household electricalappliances at peak periods. The implementation of
HEMS can be done automatically by the algorithmic
programming operation. Figure 3 shows the DR
algorithm for residential smart home [7].

Optimization of DR Model for Single home
The problem of optimization of a DR model is to
manage electricity consumption, generation, andcustomer’s energy storage over a period, which is
divided into some time slots from a few minutes tohour periods. The purposes of DR model
optimization are as follows:
1) Minimizing the total cost of electricity
2) Minimize the discomfort experienced bycustomer of delay operation time3) Maximizing network’s power resources withelectricity transactions from/to the network
4) Peak load reduction and ratio of PAR
An optimization model for the above purpose canbe provided by the following formula [7]:1) To minimize the cost of electrical power
Focus on reducing the cost of electricity
𝒎𝒊𝒏 ∑(𝒄𝒕 . 𝒚𝒕 − 𝒅𝒕 . 𝒛𝒕 )Figure 3 DR Algorithm for Smart Home Residential
Formulation of algorithms DR and load control
strategies depending on the characteristics of theload consisting of types of loads, usage patterns, theduty cycle, consideration of the uncertainty,
modeling behavior, technical obstacles andrenewable energy generation and energy storage𝒕∈𝑵

When the reward parameter included in thecalculation, then the formula becomes:
𝑼
𝑳 𝑳
𝒎𝒊𝒏 ∑𝒕∈𝑵(𝒄𝒕 . 𝒚𝒕 − 𝒅𝒕 . 𝒛𝒕 − (𝑹𝑼𝒕 . 𝒂𝒕 + 𝑹𝒕 . 𝒂𝒕 ))Where ct, dt are buying, selling cost of energy and yt,
zt are energy brought and injected into the grid at

187

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

time t. 𝑹𝑼
𝒕 can be reward paid/penalty collected
depending on demand request satisfaction.
2) To minimize the inconvenience that perceived
by customer. Here, the focus is on minimizing
the inconvenience experience

scheme will be developed. The system has limited
power supply, high electrical load during peak loads
and loads, are dominated by residential customers.
Referring to an article from Tongam (2008),
numbers of factors that may influence the demandfor electrical energy in the residential sector arehousehold income, prices or tariffs of electricity,
electrical appliances, load characteristics, and otherrelevant variables [20]. These factors will affect load
characteristics of the microgrid system, which isdominated by residential customers.
Characteristics of the electrical load in a
microgrid system will greatly determine thestrategies used to balance between the load profileand generation capacity.

𝑪𝑩𝒎𝒊𝒏 ∑(𝜶 ∑ 𝒇𝑺𝒔𝒕 . 𝒙𝒔𝒕 + 𝜷 ∑ 𝒇𝜺𝒆𝒕 )
𝒕∈𝑵

𝒔∈𝑺

𝒆∈𝜺𝑪𝑩

3) To maximize the energy from local generation∑𝒏∈𝑵(𝝅𝑹,𝑷𝑽− 𝝅𝒏𝒆𝒕
𝒕 )
𝒕
𝒎𝒂𝒙
𝑻𝑶𝑻
𝝁. 𝒑𝒕
is energy that generated by the PV
Where 𝝅𝑹,𝑷𝑽𝒕panel at time t and 𝒑𝑻𝑶𝑻
is total power and 𝝅𝒏𝒆𝒕
is𝒕𝒕
nett generation.
In the single home model, customers have four typesof equipment that are distinguished by their control
functions: fixed/critical, time and power shiftable,
comfort base and local renewable energy generationand energy storage.

Load Curve of Timor Eectricity Sistem
60000

55000

50000

45000

40000

Optimization of DR Model for group of homes orcommunity Tables

35000

30000

MondayIn this condition, a group of individual residential
customers will cooperate with an aggregator orCommunity Energy Management System (CEMS) to
conduct electricity transaction management withelectricity company or power system grid [7], [12].
The main purpose is to reduce total cost ofelectricity from a group of homes or communities by
setting the schedule for the time allowed. The
formula for calculating cost minimization is:

Tuesday

WednesdayThursdayFridaySaturday

SundayFigure 4 Load Curve of Timor Power System
Figure 4 shows the daily load curve of the Timor
power system, in the period of 4 - 10 April 2016
(Monday-Sunday). It is shown a gap between peakload and off-peak load, about 23% of total power
capacity in Timor electric power system.
At single residential homes in Timor electricity
system, loading curve with details of energy
consumption per equipment can be seen in Figure 5.
It has a similar pattern to a study on residential
demand response scheduling [20].

𝑚𝑖𝑛 ∑ ∑(𝑐𝑡 . 𝑦𝑡𝑢 − 𝑑𝑡 . 𝑧𝑡𝑢 )𝑢∈𝑈 𝑡∈𝑇

Where 𝑐𝑡 𝑦𝑡𝑢 is energy received from system grid,and 𝑑𝑡 . 𝑧𝑡𝑢 is selling cost of energy. The challenge
remains the total peak load of users cannot exceed atotal aggregate peak load customers. Cooperative
methods of multiple residential homes have thepotential to provide a greater influence on theefficiency of the system, when the settings are donewith system-wide perspective.
Some papers also discuss the DR relationshipwith the electricity market. The influence of DR
scheme can result from electricity price and optionsof incentive offered so that customers are interested
in participating in the DR program. Several types of
the tariff are available for determining the price ofelectricity : time of use (TOU), critical peak pricing(CPP) and real-time pricing (RTP) [12].

Figure 5 Energy consumption per hour for every
household electrical appliances
The demand for electricity with characteristics,
as shown in Figure 5 above, supplied by existing
power plants, including renewable energy power
plants that have intermittent characteristics. To
maintain a balance between the power supply andthe load, the implementation of demand response forresidential customers need to be performed on the
microgrid system such as in Timor power system.

LOAD CHARACTERISTICS IN INDONESIANISLAND MICROGRID SYSTEM
In this chapter, it is discussed load characteristics
of microgrid systems in the island where the DR
188

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

Demand Response Programmes,” in the ACM
International Conference on Future Energy
Systems, Bangalore, India, 14 - 17 Jul 2015.
[10] Amir-Hamed M., and Alberto L. G., “Optimal
Residential Load Control with Price Prediction
in Real-Time Electricity Pricing Environments
Demand Response in an Isolated System withhigh Wind Integration,” in IEEE Transactions
on Smart Grid, Volume: 1, Issue: 2, Sept. 2010.
[11] Bingnan Jiang and Yunsi Fei, “Dynamic
Residential Demand Response and Distributed
Generation Management in Smart Microgrid
with Hierarchical Agents,” in Procedia ICSGCE
2011: 27–30 September 2011, Chengdu, China.
[12] Antimo Barbato and Antonio Capone,“Optimization Models and Methods for
Demand-Side Management of Residential
Users: A Survey,” Energies 2014.
[13] Manisa Pipattanasomporn, M. Kuzlu, and S.
Rahman, “An Algorithm for Intelligent Home
Energy Management and Demand Response
Analysis,” in IEEE Transactions on Smart Grid,
Vol. 3, No. 4, December 2012.
[14] John S. Vardakas, Nizar Zorba, and Christos V.
Verikoukis, “A Survey of Demand Response
Programs in Smart Grids: Pricing Methods andOptimization
Algorithms”,
IEEE
Communication Surveys & Tutorials, Vol. 17(No. 1), 152-178.
[15] M. Rastegar, M. Fotuhi-Firuzabad, and F.
Aminifar, “Load commitment in a smart home,”
Appl. Energy, vol. 96, pp. 45–54, Aug. 2012.
[16] Alessandro
Agnetis,et.al.,“Appliance
Operation
SchedulingforElectricity
Consumption Optimization,” in 50th IEEE CDC- ECC, Orlando, FL, USA, December, 2011.
[17] Q. Dong, L. Yu, W. Z. Song, L. Tong, and S.
Tang, “Distributed demand and response
algorithm for optimizing social-welfare in smart
grid,” in Proc. 26th IEEE IPDPS, Shanghai,
China, May 21–25, 2012, pp. 1228–1239.
[18] Adam Taylor, Ivana D., C. Harris, A. Marinescu,
Edgar G.L., Fatemeh G., Siobhan C., and Vinny
Cahill, “Self-Organising Algorithms for
Residential Demand Response,” in IEEE
Conference on Technologies for Sustainability(SusTech), 2014, Portland, USA, 24-26 July
2014, pp. 55–60[19] S. Ghaemi, and Günther Brauner, “Stochastic
Model For Household Load Profile,” in 11.
Symposium Energieinnovation, 10-12 February
2010, Graz/Austria[20] Tonggam Sihol Nababan, “Household Electrical
Energy Demand (Case Study on Domestic
Electricity Consumer Group Electrical PT PLN(Persero) in Medan), Ph.D. Dissertation,
Doctoral Studies Program in Economics,
University of Diponegoro, Indonesia, 2008.

CONCLUSIONS
From discussions in the preceding paragraph,several conclusions can be drawn as a reference andvaluable lesson that can be used to conduct further
research in the future :1) In general, the purpose of applying the demand
response is to reduce the peak load, and it
directly impacts the reduction of generating
capacity to be operated and changes the customer
behavior so that the load profile can be improved.
2) Optimization of DR scheme implementation areclassified into individual customers and groupsof customers that will define the architecture of
the program and the success rate of
implementation
3) Residential demand response has great potential
to be used as a method of load balancing andpower supply in microgrid systems in Indonesia
REFERENCES[1] Charles River Associates, “Primer on DemandSide Management”, Tech. Rep. February, The
World Bank, 2005
[2] Gellings CW, “The concept of demand-side
management for electric utilities”, Proceedingsof the IEEE 73(10):1468–1470, 1985
[3] Barakat & Chamberlin, Inc. “Principles andPractice of Demand-Side Management”, EPRI
TR-102556, Palo Alto, California, August 1993
[4] Peter Palensky, and Dietmar Dietrich, “Demand
Side
Management:
DemandResponse,
Intelligent Energy Systems, and Smart Loads”,
IEEE Transaction on Industrial Informatics, Vol.
7, No. 3, August 2011[5] Qi Zhang and Ignacio E. Grossmann, “Planningand Scheduling for Industrial Demand SideManagement: Advances and Challenges”,
Alternative Energy Sources and Technologies,
pp 383-414, Springer, March 2016
[6] Robin Roche, “Agent-Based Architectures andAlgorithms for Energy Management in Smart
Grids: Application to Smart Power Generation
and Residential Demand Response,” Ph.D.
dissertation, Abbrev. Dept., UTBM, Belfort,
France 2012.
[7] Rajasekhar Batchu and Naran M. Pindoriya,“Residential Demand Response Algorithms:
State-of-the-Art, Key Issues and Challenges,” in
7th EAI International Conference on Wireless
and Satellite Systems, Breadfort, Great Britain,
6-7 July 2015, pp. 18–32.
[8] P.T. Baboli, M. Eghbal, dan M. Parsa
Moghaddam and H. Aalami, "Customer
behavior based demand response model," Powerand Energy Society General Meeting, 2012
IEEE, San Diego, California, USA, Juli 2012[9] James C. Holyhead, Sarvapali D.R. and, Alex
Rogers, “Consumer Targeting in Residential
189Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

CRACKING AND DEFORMABILITY OF BONDED AND UNBONDED
PRESTRESSED CONCRETE BEAMS UNDER MONOTONIC STATICLOADING
Nazar K. Oukaili1 and Mohammed M. Khattab2
Professor, University of Baghdad, Iraq; 2Ph.D. Candidate, University of Baghdad, Iraq

1

ABSTRACTThis paper presents outcomes of the study undertaken on partially prestressed concrete beams with bonded
and unbonded prestressing strands. In order to investigate the cracking and deformability of partially prestressed
concrete beams, an experimental program has been conducted on 10 full-scale simply supported beams over aspan of 3000 mm. The objective of this investigation was to examine experimentally the effect of varying partial
prestressing ratio (PPR) and type of bond development between prestressing steel and surrounding concrete(bonded or unbonded) on cracking and deflection values. Accordingly, two specimens were fully reinforced
concrete, three partially prestressed concrete with bonded strands, three partially prestressed concrete withunbonded strands and the remaining two were fully prestressed with bonded strands. All specimens were loaded
up to failure in four-point bending using two symmetrical concentrated monotonic static loads applied at onethird of the span length. Measurements were made for strains in prestressed, nonprestressed steel and concrete,
midspan deflections, crack spacing and crack widths at different loading stages.
Theoretical analysis was also carried out using ACI Code to predict the cracking load, deformability, stress at
failure in prestressing steel, and ultimate load of the specimens. Results of the theoretical analysis according tocode methods have been found to be consistent with the experimental data.
Keywords: Partial Prestressing, Bonded, Unbonded, Flexure, Deflection, Cracking
INTRODUCTION𝑃𝑃𝑅 =In the last few decades, prestressed concrete has
been widely used due to enormous development in
the construction techniques. Now more than 50
percent of bridges in the world are constructed usingprestressed girders [1].The major disadvantages ofusing conventionally reinforced concrete beams isthe corrosion of reinforcement which occurs due tothe effects of cracks in the tension zone. In the other
hand, the major defect of fully prestressed concretebeams, where no flexural tension allowed in theconcrete under service load, is the low ductility. The
ductility of fully prestressed concrete beams could
be enhanced with the presence of nonprestressedreinforcement. Partial prestressing describes
prestressed beams wherein limited cracking ispermitted through the use of additional mild
nonprestressed reinforcement to control the extent
and width of cracks and to contribute with part of
the ultimate flexural moment strength. Partiallyprestressed concrete beams, therefore occupies thecomplete spectrum between the two extremes. It
permits cracking under service loads, but to satisfy
the serviceability requirements, the maximum crack
width and the maximum deflection should notexceed the code recommended limits on crack widthand deflection.
The term Partial Prestressing Ratio (PPR) is theratio of ultimate resisting moment due to theprestressing steel to the ultimate resisting moment
due to the total tensile steel [2]:𝐴𝑝𝑠 𝑓𝑝𝑠 𝑑𝑝
𝐴𝑝𝑠 𝑓𝑝𝑠 𝑑𝑝 + 𝐴𝑠 𝑓𝑦 𝑑𝑠(1)

Where:
𝐴𝑝𝑠 = area of prestressing steel;𝐴𝑠 = area of nonprestressed steel;
𝑓𝑝𝑠 = stress in prestressing steel at ultimate behavior;
𝑓𝑦 = yield strength of nonprestressed steel;
𝑑𝑝 = distance from extreme compressive fiber ofconcrete to centroid of prestressing steel;𝑑𝑠 = distance from extreme compressive fiber ofconcrete to centroid of nonprestressed steel.
Reinforced concrete beams always have to be
designed as underreinforced to ensure ductile failureby yielding of the steel reinforcement. Prestressed
beams can be either underreinforced using relatively
small percentage of mild nonprestressed steel,leading to rupture of the tensile steel at failure, oressentially overreinforced, using a large percentage
of steel, resulting in crushing of the concrete at thecompression top fibers in somewhat less ductile
failure [3].
According to ACI 318-2011 [4], the prestressed
concrete beam sections can be classified into three
types based on the tension – reinforcement area,such that when the beam reaches its nominal flexuralstrength, the net tensile strain in the extreme layer oftensile steel, 𝜀𝑡 , as follow:
Tension - controlled section if 𝜀𝑡 > 0.005
Transition – zone section if 0.002 < 𝜀𝑡 < 0.005
Compression - controlled section if 𝜀𝑡 < 0.002
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

exercised to balance the prestressing force in thestrands to avoid biaxial bending of the specimens.
The corresponding stress was monitored accurately
using readings of the strain gauges attached to thesurface of the prestressing strands along with thereadings of the pressure gauge of the hydraulic jackused in the prestressing operation.

EXPERIMENTAL PROGRAM
The experimental program consists of testing ten
full scale specimens with overall dimensions of(200x300x3300) mm, which were divided into fourgroups. The first group consists of two fully
reinforced concrete specimens (FR). The second andthe third groups, each consists of three partiallyprestressed concrete specimens (PP) with bonded
and unbonded strands, respectively. The fourthgroup consists of two fully prestressed specimens
with bonded strands (FP).
For all specimens concrete mix of target value of
40 MPa, cylinder compression strength at 28 days
age, was used. Deformed steel bars with yield stressof 570 MPa and ultimate strength of 650 MPa wasused for flexural nonprestressed and stirrups. All
specimens were reinforced using closed stirrups of
10 mm diameter with spacing 100 mm c/c in shear
spans of 1000 mm length and 3 stirrups were used in
the pure bending moment zone (Fig. 1). Low relaxation seven - wire steel strands, with 12.7 mm
diameter, (Grade 270), has been used in allprestressed specimens.
To achieve the objective of the study, theexperimental specimens were designed in such a
way that to allow investigate the effect of partial
prestressing ratio and type of bond development
between prestressing steel and the surrounding
concrete on the behavior of these members (Table 1).

PP-B-TC

PP-B-TRPP-U-TC

PP-U-TRPP-B-CC

PP-U-CC

Table 1 Details of experimental specimens
Specimen PPR
𝜔𝑝
𝜔
𝜔′
FR-UN
0.000 0.000 0.043 0.043
1
FR-MAX 0.000 0.000 0.244 0.045
PP-U-TC 0.743 0.157 0.043 0.043
2
PP-U-TR 0.409 0.144 0.172 0.044
PP-U-CC 0.339 0.138 0.224 0.044
PP-B-TC 0.771 0.185 0.043 0.043
3PP-B-TR 0.529 0.178 0.124 0.043
PP-B-CC 0.358 0.169 0.259 0.045
FP-B-TC 1.000 0.187 0.000 0.049
4FP-B-CC 1.000 0.270 0.000 0.000
Note: UN = under - reinforced; MAX = maximum
reinforced ( 𝜌 = 0.75 𝜌𝑏 ); U = unbonded; B =bonded; TC=tension - controlled; TR=transition controlled; CC = compression - controlled;𝜔𝑝 , 𝜔 and 𝜔′ = the reinforcement index for tensile
prestressing, tensile nonprestressed and compression
nonprestressed reinforcement, respectively.
Group

FR-UN

FR-MAX

FP-B-TC

FP-B-CC

Fig. 1 Details of experimental specimens.
TEST SETUP
All specimens were loaded in four-point bending
using two symmetrical monotonic concentrated
static loads applied at one-third of the span length.
The test was conducted using closed loop ram with50 ton capacity actuator. Specimens were subjected
to a monotonically increasing load up to failureusing a load control test. All measurements, such as
beam deflections, strains in steel strands, strains insteel bars and strains in concrete were recorded
twice, immediately after the application of the load
and after 10 minutes later.
Deflection was measured at midspan using dial gageof 0.01 mm accuracy. Electrical strain gauges wereused to measure the strains in prestressing steel,
nonprestressing steel and concrete. Cracks weremonitored along the span of the beams. Maximum
crack width, number of cracks and average crack
spacing were measured sequentially during loading.

In all prestressed concrete specimens, except
specimen (FP-B-CC), two strands were used withtarget initial prestress 𝑓𝑝𝑖 of 0.7 𝑓𝑝𝑢 . For specimen(FP-B-CC), three strands with 0.6 𝑓𝑝𝑢 initialprestress were applied. Strands were tensioned
simultaneously from one end. Special care was
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also noted that, for (PP) specimens, increasing
nonprestressed reinforcement, i.e. decreasing (PPR),
slightly affected the cracking load. In the other hand,for (FP) specimens, increasing the area ofprestressing steel in (FP-B-CC) led to increase thecracking load by about (29%) in comparison with
(FP-B-TC).
Crack width, number of cracks and average crack
spacing at failure were measured and recorded
throughout the test (Table 3).

EXPERIMENTAL RESULTS
Cracking load, Crack Width, Crack Number,and Average Crack Spacing
Flexural cracks in all specimens were initiated at
the location of pure moment zone perpendicularly tothe longitudinal axis of the specimen and extended
up to the location of the tensile nonprestressedreinforcement. Table 2 illustrates experimental andtheoretical cracking load as well as experimental andtheoretical deflection at this loading stage.
Theoretical cracking load was determined according
to the following equations [5]:𝑀𝑐𝑟 = 𝑓𝑟𝐼𝑡𝑐𝑏

+ 𝑓𝑝𝑠 𝐴𝑝𝑠 (𝑒𝑜 +

𝐼𝑡
𝑐𝑏 𝐴𝑡

)

Table 3 Number of cracks, average crack spacing
and crack width for experimental specimens
Specimen

Numberofcracks

FR-UN
FR-MAX
PP-U-TC
PP-U-TRPP-U-CC
PP-B-TC
PP-B-TRPP-B-CC
FP-B-TC
FP-B-CC

24
27
10
22
20
18
20
23
13
14

(2)

Where:
𝑀𝑐𝑟 = cracking moment;
𝑓𝑟 = modulus of rupture;
𝐼𝑡 = transformed moment of inertia;
𝑐𝑏 = distance between centroid of section andbottom fiber of concrete;
𝐴𝑡 = transformed area of concrete section;
𝑒𝑜 = distance between centroid of prestressing
reinforcement and centroid of section.
The following equation was used to calculate
theoretical deflection at cracking load [5]:Averagecrack
spacing,
(mm)
120
100
140
90
110
110
100
100
150
125

Crack
width,
(mm)
1.30
1.20
4.25
1.00
0.95
2.10
0.95
0.95
5.00
2.40

Table 2 Experimental and theoretical cracking loadand deflection

In (FR) specimens, the number of cracks was thehighest among all specimens. For prestressing
specimens with high nonprestressed steel area, i.e.
low level of (PPR), more cracks were propagatedand less crack spacing was observed (Plate 1). Thisis due to the better overall bond achieved by thetensile nonprestressed steel with the surrounding
concrete which led to control the cracks in tension
zone of the element.

Specimen

Load - Deflection Response

∆𝑐𝑟 =

𝑃𝑐𝑟 𝑏
24 𝐸 𝐼𝑡

(3𝑙 2

− 4𝑏

2)

(3)

Where:
𝑙 = span between the supports;
𝑏 = distance from support to point load, (Fig. 1).

FR-UN
FR-MAX
PP-U-TC
PP-U-TRPP-U-CC
PP-B-TC
PP-B-TRPP-B-CC
FP-B-TC
FP-B-CC

Exp.
𝑃𝑐𝑟 ,
(𝑘𝑁)
20.0
22.0
67.0
68.0
72.0
70.0
67.0
73.0
70.0
90.0

Theo.
𝑃𝑐𝑟 ,
(𝑘𝑁)
23.0
24.2
75.0
76.0
76.8
74.3
75.0
77.2
74.9
91.3

Exp.
∆𝑐𝑟 ,
(𝑚𝑚)
1.10
1.70
3.00
3.00
2.88
3.33
2.50
3.25
3.12
4.24

Theo.
∆𝑐𝑟 ,
(𝑚𝑚)
0.75
1.77
2.95
2.58
2.58
2.62
2.70
2.66
2.85
6.30

The load deflection curves for the tested specimens
are shown in (Fig. 2). It can be seen that for
specimens of (FR) and (PP) groups with tension controlled and transition - controlled concrete
sections, three distinctive points could be observed.
These points are characterizing cracking, yielding
and ultimate loads. However, for partially and fully
prestressed compression - controlled concrete
sections, only points which characterized cracking
and ultimate loads can be observed. Thus, clear
yielding point cannot be distinguished. Prior tocracking all specimens behaved in an elastic manner.
After cracking, (FR) and (PP) specimens with low(PPR) developed approximately linear loaddeflection response. All specimens experienced
decreasing of stiffness after cracking, depending on
the level of (PPR) and the reinforcement index.
Increasing the area of tension reinforcement

From Table 2, it was observed that the presence ofprestressing steel has good contribution to delay thecracking appearance and increase the cracking load.
For (FR) specimens, the cracking load was muchless than that for (PP) and (FP) specimens. It was
192

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

produced stiffer specimen which led to low rate ofdeflection versus applied load.

Plate 1 Crack propagation of tested specimens.
It was observed that, specimen with highest stiffness
before cracking suffered from highest stiffness
reduction after cracking. Also, specimens withbonded strand were stiffer than the similar but withunbonded strand. Yielding of the nonprestressedsteel occurred prior to prestressing steel for all the
specimens. This is because of the location ofreinforcing steel relative to neutral axis. (FR)specimens developed a well-defined yield point
followed by a strain hardening stage prior to failure.
Moment Capacity and Strain in Prestressing
Reinforcement
The strain in prestressing strands has beenmeasured using two electrical strain gauges per eachstrand which were fixed at midspan section.
Accordingly, the stress was determined by using theactual stress-strain curve of the strand. This stress
was compared with the stress determined according
to the mentioned below empirical equations, which
adopted by the ACI-318-2011 [4]:For bonded strands
𝛾

𝑓

𝑑𝑠

𝛽1
𝑓𝑦

𝑓𝑐

𝑑𝑝

𝑓𝑝𝑠 = 𝑓𝑝𝑢 [1 − { 𝑝 𝜌𝑝 𝑝𝑢′ +
ω=𝜌

𝑓𝑦
𝑓𝑐′

; 𝜔′ = 𝜌′ ′𝑓𝑐

(𝜔 − 𝜔′ )}](4)(5)
Fig. 2 Load-deflection response of tested specimens.
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017For unbonded strands
𝑓𝑝𝑠 = 𝑓𝑝𝑒 + 70 +

𝑓𝑐′
𝑘𝜌𝑝

≤ 𝑓𝑝𝑒 +c

Table 5 illustrates the experimental and thetheoretical load carrying capacities for eachspecimen.

(6)

Where:
𝑓𝑝𝑠 = stress in prestressing strand at flexural
resistance of the section;
𝑓𝑝𝑢 = specific tensile strength of prestressing strand;
𝑓𝑝𝑒 = effective prestress;
𝑓𝑐′ = specific compressive strength of concrete;
𝛾𝑝 = factor used for type of prestressing steel;𝛽1 = factor relating depth of equivalent rectangularcompressive stress block to depth of neutral axis;
𝜌𝑝 = ratio of 𝐴𝑝𝑠 to 𝑏 𝑑𝑝 ;
𝜌 = ratio of 𝐴𝑠 to 𝑏 𝑑𝑠 ;𝜌′ = ratio of 𝐴′𝑠 to 𝑏 𝑑𝑠 ;k = 100 and c = 414 for span/depth ratio ≤ 35
k = 300 and c = 207 for span/depth ratio > 35

Table 5 Experimental and theoretical ultimate load
capacity

Table 4 shows experimental strain and stress andempirical stresses in prestressing strands for eachprestressed specimens.

Exp.
𝜀𝑝𝑠,𝑒𝑥𝑝

PP-U-TC
PP-U-TRPP-U-CC
PP-B-TC
PP-B-TRPP-B-CC
FP-B-TC
FP-B-CC

0.008200.00730
0.007400.011890.010420.00897
0.00863
0.00777Exp.
𝑓𝑝𝑠,𝑒𝑥𝑝,
(MPa)
1621
1449
1469
1722
1712
1661
1641
1540

Theo.
𝑓𝑝𝑠,𝑡ℎ𝑒𝑜,
(MPa)
1414
1337
1284
1725
1662
1566
1745

𝑓𝑝𝑠,𝑒𝑥𝑝
𝑓𝑝𝑠,𝑡ℎ𝑒𝑜
1.146
1.084
1.144
0.998
1.030
1.061
0.940

The concept of determining experimental ultimate
load varies from one researcher to another. In thisstudy, the load value corresponding to the maximum
load on the load-deflection curve was taken as theultimate load.
The theoretical nominal moment capacity of tension- controlled concrete rectangular section can be
determined by the following equation [5]:
𝑎

𝑎

2

2

𝑀𝑛 = 𝐴𝑝𝑠 𝑓𝑝𝑠 (𝑑𝑝 − ) + 𝐴𝑠 𝑓𝑦 (𝑑𝑠 − ) +𝑎

𝐴′𝑠 𝑓𝑦 ( − 𝑑𝑠′ )2(7)For compression - controlled concrete rectangularsection
𝑀𝑛 = 𝑓𝑐′ 𝑏 𝑑𝑒2 (0.36𝛽1 − 0.08𝛽12 )𝑑𝑒 =𝐴𝑝𝑠 𝑓𝑝𝑠 𝑑𝑝𝑠 + 𝐴𝑠 𝑓𝑦 𝑑𝑠
𝐴𝑝𝑠 𝑓𝑝𝑠 +𝐴𝑠 𝑓𝑦

PPR

FR-UN
FR-MAX
PP-U-TC
PP-U-TRPP-U-CC
PP-B-TC
PP-B-TRPP-B-CC
FP-B-TC
FP-B-CC

0.000
0.000
0.734
0.409
0.339
0.771
0.529
0.358
1.000
1.000

Exp.
𝑃𝑢,𝑒𝑥𝑝,
(𝑘𝑁)
130
210
165
210
320
182
230
310
146
170

Theo.
𝑃𝑢,𝑡ℎ𝑒𝑜,
(𝑘𝑁)
121
199
151
211
212
172
213
209
138

𝑃𝑢,𝑒𝑥𝑝𝑃𝑢,𝑡ℎ𝑒𝑜
1.074
1.055
1.093
0.995
1.509
1.058
1.082
1.483
1.058

The magnitude of ultimate load capacity was varied
depending on the value of the reinforcement index.
Almost experimental ultimate load results weregreater than the theoretical values. The reason of thiscan be interpreted that the calculated stress inprestressing steel, according to equations (4) or (5),was smaller than the experimental values. In general,comparison of these results indicates good
agreement between the experimental and theoreticalresults for all the specimens except the compression- controlled specimens ((PP-U-CC) and (PP-B-CC)).
The experimental results of these specimens gave
approximately 1.5 times the theoretical values. Thus,
the ACI-code equation (Eq. 8) is not considering theimpact of the presence of reinforcing steel on the
moment capacity of compression - controlled
sections. This equation also doesn’t distinguishbetween bonded and unbonded strands in calculating
the moment capacity of compression controlled
sections.
Obviously, two modes of failure have been
observed through the experimental tests. The firstmode of failure is due to the crushing of concrete incompressive zone of the section, which resulted after
yielding and excessive deformation of tension
nonprestressed steel. This type of failure wasoccurred in (FR) and tension - controlled (PP)
specimens. The second mode of failure which wasobserved is the crushing of concrete of the section
compression zone before the yielding of the tension
nonprestressed steel. This is primarily due to an
excessively large quantity of tension reinforcementin the section. This type of failure was observed for(FR) as well as compression - controlled (PP)
specimens. No slip between strand and concrete has
been observed in any specimen through theexperimental tests.

Table 4 Experimental and theoretical strain andstress in prestressing strands
Specimen

Specimen

(8)
(9)
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Table 6 summarizes strains in nonprestressed
tension 𝜀𝑠 and compression 𝜀𝑠′ reinforcement and thestrain at the top extreme concrete fibers𝜀𝑐 . It shows
also, the ultimate deflection ∆𝑢 at midspan of thespecimens. These results indicate that, for tension controlled sections the tensile steel reached yielding
point while for compression - controlled specimens
the strains were below the yielding point.

REFERENCES[1] Collins, M. and Mitchell, D. “Prestressed
Concrete
Structures”,
Prentice
Hall,
Engineering Cliffs (NJN, USA), 199, pp. 4-5.
[2] Harajli, M.H. and Naaman, A. E. “Deformation
and Cracking of Partially Prestressed Concrete
Beams Under Static and Cycles Fatigue
Loading” Report No. UMEE 84R1 Department
of Civil Engineering, the University ofMichigan, College of Engineering, 1984, pp. 21.
[3] Nawy, E. G. “Prestressed Concrete: A
Fundamental Approach”, Prentice Hall, 5th
Edition, 2009, pp. 198 - 201.
[4] ACI Committee 318-2011, “Building CodeRequirements for Structural Concrete andCommentary” American Concrete Institute,
Farmington Hills, Michigan, 2011.
[5] Naaman, A. E., “Prestressed Concrete Analysis
and Design”, 2nd, Techno Press 3000, Ann
Arbor, Michigan, 2004, pp. 235-236.

Table 6 Strains in nonprestressed reinforcement, top
extreme concrete fibers and ultimate
deflection
Specimen

𝜀𝑠

𝜺𝒄

𝜺′𝒔

FR-UN
FR-MAX
PP-U-TC
PP-U-TRPP-U-CC
PP-B-TC
PP-B-TRPP-B-CC
FP-B-TC
FP-B-CC

0.00550.00530.01230.01570.00240.00630.00520.003830.001400.000690.001540.00179
0.002110.00205
0.001700.001930.001420.001450.000240.000230.000320.001440.002430.00108
0.000850.00195
0.00044

Δ𝑢,
(mm)
41.4
32.8
45.0
35.0
29.0
56.0
32.4
34.0
38.0
30.0

CONCLUSIONS
The following conclusions can be drawn
1For specimens with approximately the same
(PPR), ultimate strain in bonded prestressing strands
is higher than its counterpart of unbonded
prestressing strand. Accordingly, the value of
ultimate load capacity for specimens with bonded
strands is significantly higher than that of thecounterpart specimen with unbonded strands.
2The appearance of first crack in (PP) as
well as in (FP) specimens was delayed incomparison with (FR) specimens. This is due to thepresence of prestressing force.
3The first flexural crack initiated at load
ranged 8.6% to 52.9% of the ultimate load.
4In (FR) and (PP) specimens with small(PPR) value, the crack pattern was distributed along
the pure bending moment zone with small crack
width and large number. This is due to the presenceof nonprestressing steel which controls the cracks intension zone. In the other hand, for (FP) and (PP)
specimens with high (PPR), small number of cracks
were appeared with large crack width.
5Failure modes for (FR) and tension –controlled (PP) specimens were more ductile thanthat of (FP) and compression - controlled (PP)
specimens.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

DISTRIBUTED MODEL OF HYDROLOGICAL AND SEDIMENTTRANSPORT PROCESS IN MEKONG RIVER BASIN
Zuliziana Suif1, Chihiro Yoshimura2, Nordila Ahmad1 and Sengheng Hul3
Department of Civil Engineering, Faculty of Engineering, National Defence University of Malaysia,
Malaysia; 2Department of Civil engineering, Tokyo Institute of Technology, Japan, 3Institute of Technology
Cambodia, Cambodia.
1

ABSTRACT
Soil erosion and sediment transport have been modeled at several spatial and temporal scales, yet few models
have been reported for large river basins (e.g., drainage areas > 100,000 km2). In this study, we propose a processbased distributed model for assessment of sediment transport at a large basin scale. A distributed hydrologicalmodel was coupled with a process-based distributed sediment transport model describing soil erosion andsedimentary processes at hillslope units and channels. The model was tested in Mekong River Basin (795,000
km2). The simulation over 10 years showed good agreement with the observed suspended sediment load in thebasin. The average Nash–Sutcliffe efficiency (NSE) and average correlation coefficient (r) between the simulated
and observed suspended sediment loads were 0.60 and 0.78 respectively. Sensitivity analysis indicated that thesuspended sediment load is sensitive to soil detachability over land (Kf) in the Mekong River Basin. Overall, theresults suggest that the present model can be used to understand and simulate erosion and sediment transport inlarge river basins such as Mekong River Basin.
Keywords: Soil Erosion, Sediment Transport, Hydrological Model, Mekong River Basinproblem, in this study we primarily consider the largebasin scale in developing the process-based sedimenttransport model. Besides, some existing models
application at these scale have borrowed heavily fromsmaller scale application. The existing models areeither in-stream models, land surface models or, insome cases, have both land surface and in-rivercomponents. Basin scale prediction of sediment
generation and transport requires consideration ofland surface processes and in-river processes. The
objectives of this study to check the feasibility ofdeveloped process-based model on simulating of
sediment dynamic considering hillslope sediment andsediment in river system separately. The model wasdeveloped by integrating soil erosion-sedimenttransport process with the distributed hydrologicalmodel to estimate the soil erosion, deposition,transport and sediment yield in large river basin. The
model has been calibrated and validate for MekongRiver basin.

INTRODUCTION
Sediment erosion, transport and deposition arecomplex natural processed strongly affected byhuman activities and leads to environmental damage
through sedimentation, pollution and increased
flooding. The sediment produced by soil erosion
process is transported into rivers, reservoirs andponds resulting in high sediment deposition rates andfrequent dredging operations. Effective managementof sediment in rivers is becoming increasingly
important from an economic, social andenvironmental perspective. Sediment dynamics in ariver basin can be estimate both quantitatively andconsistently by using modeling tools [1]. Currently,
there are many models was developed for a wide
range of applications, over a range of scales from theplot based models to basin scale approaches for
erosion and sediment transport. Basin scale processbased distributed approach is advantageous formodeling sediment delivery processes since eroded
sediments are produced from different sources
throughout a basin.
Despite of the fact that many of process-based
sediment transport models have been developed overthe past four decades, such as Water Erosion
Prediction Project (WEPP) [2], European Soil
Erosion Model (EUROSEM) [3] and Areal Non-point
Sources
Watershed
Environment
Response
Simulation (ANSWER) [4], the application of thesemodels to large basin scales (e.g drainage area > 100000 km2) remained questionable. While to address the

STUDY AREA
The present study focused the Mekong Riverbasin, which covers an area of approximately 795,000
km2 (Fig.1). The basin consists of approximately
33 % of forests. Among major rivers of the world, theMekong ranks 12th with respect to length (4880 km),21st with respect to catchment’s area. The wet season
lasts from May to October when the average rainfall
around 80-90% of the annual total. The dry season
period starts from November and lasts until April.
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

The minimum annual rainfall is 1000 mm/year (NEof Thailand) and the maximum is 4000 mm/year(West of Vietnam).

study is a geomorphology based hydrological model(GBHM) developed at the University of Tokyo [5]. It
solves the continuity, momentum and energy
equations using two modules; hillslope model andriver routing model. The GBHM uses a basin
subdivision scheme, a sub grid parameterization
scheme, a physically based hillslope hydrologicalsimulation, and a kinematic wave flow routing inriver network [6]. Further details can be described asin [5].

The Mekong River Basin is populated withapproximately 60 million people and is considered to
be one of the most culturally diverse regions of theworld. Agriculture, fishing and forestry provide
employment for approximately 85% of the basin’s
residents. In this basin, Acrisols were found thedominant soil type, which are tropical soils that havea high clay accumulation in a horizon and are
extremely
weatheredandleached.
Theircharacteristics include low fertility and highsusceptibility to erosion if used for arable cultivation.
The rest of the areas are mixtures of deciduous andevergreen covers as well as woodland and shrublandwith some undisturbed forest land.

Process based soil erosion and sediment transportmodel
Hillslope erosion process
Hillslope erosion is divided into two systems;
detachment from raindrop and flow. In Eq. (1), soil
eroded by raindrop is calculated with canopy ratio,rain intensity and surface water depth using theequation as follows [7].
𝐷𝑅 = (1 − 𝐶𝑔 )𝑘 𝑟 (𝐾𝐸)𝑒 −𝑧ℎ(1)where, DR is soil detachment by raindrop impact (gm-2 s-1), k is an index of the detachability of the soil(g J-1). KE is the total kinetic energy of the rain (J m2), z is an exponent ranging between 0.9 and 3.1, h is
the depth of the surface water layer (mm), Cg is the
proportion of canopy cover in each grid.
In Eq. (2, 3), soil eroded by sheet flow on thesurface occurs with when hydraulic shear stress islarger than critical hydraulic shear stress using theequation as follows [8].
𝜏𝐷𝐹 = 𝐾𝑓 ( − 1) (𝜏 > 𝜏𝑐 )(2)

(𝜏 < 𝜏𝑐 )(3)

𝜏𝑐

𝐷𝐹 = 0

Fig.1

Where, DF is overland flow detachment (kg m-2 s-1),
Kf is an overland flow detachability coefficient (kg m2 -1s ), here 10 (mg/m2) is used, τc is critical shear stressfor initiation of motion, which is obtained from theShield’s curve (N m–2) and τ is hydraulic shear stress(N m–2).

Mekong river basin map.

METHODOLOGY

Sediment transport process

The important sediment dynamics (soil erosion,
sediment transport and deposition) were modelled
and integrated with a process-based distributedhydrological model (DHM). In sediment module,
sediment dynamics on hillslope and river wasmodelled separately and linked to each othersystematically.

The eroded soil on each hillslope would flow into
the main stream and get dissolved in suspended load.
The detachment or deposition in the river is expressedusing the equation as follows [9]. In Eq. (4), theprocess of deposition to the bed and detachment frombed is calculated by transport capacity concentrationand SS concentration. If it is larger than Cs,
entrainment occurs. If it is smaller than Cs, deposition
occurs. However, bed load was ignored in this case.

Hydrological Modelling
The distributed hydrological model used in this197

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

𝐷𝐹𝑟𝑖𝑣𝑒𝑟 = 𝛽𝑠 𝑤 𝑣𝑠 (𝑇𝐶 − 𝐶𝑆 )(4)𝛽𝑠 = 0.79𝑒 −0.85𝐽(5)measurements. Hence it is acknowledged that thefrequency of sampling does not ensure that all rangesof the flow were sampled. In this study, monthly
observed sediment load was computed from themonthly measured of suspended sedimentconcentration and the measured water discharge.

Where, DFriver is the flow detachment or deposition(m3 s-1 m-1), CS is sediment concentration in eachflow-interval (kg m-3), TC is Transport capacity
concentration (m3 m-3), w is the width of the flow (m),vs is the particle settling velocity (m s-1) and βs is acorrection factor to calculate cohesive soil erosion, J
is soil cohesion (kPa).

Model calibration and validation
The model was simulated for 10 years from 19912000 and three stream gauge along Mekong are used
for calibration and validation. The period of
simulation is selected depends on the data availability.
Taking into account the availability of data, the daily
discharge and sediment data for periods 1991 to 1995
were used to calibrate discharge simulation.
Meanwhile, 1996-2000 data were used for validation.
The six parameters required for calibration were
initialized with empirical values, and then adjusted
according to the observed discharge at different river
sections. The residual soil moisture (wrsd) and thesaturated hydraulic conductivity (ksat1) are the onlyhydrological parameters calibrated by semiautomatic calibration method. While, the twoparameters of soil detachability by raindrop (k) andon overland flow (Kf) and soil cohesion (J) were
initialized by empirical values [9], and then adjusted
according to the observed sediment. Manual
calibration was performed for soil detachment andtransport parameters.

Model setup
The input data for the model include weather data,
topography data, soil properties, land cover. In thisstudy, the GTOPO30, global Digital Elevation Model(DEM) data with a horizontal grid spacing of ~20 km2(grid area: 2  2 min) resolution was used to delineate
the Mekong River Basin. The land cover and soil type
for the basin, obtained from global land cover 2000
(http://edc2.usgs.gov/glcc/eadoc2_0.php) and FAO
soil map of the world [10] respectively. The elevation
data were first aggregated to 3.6 km  3.6 km
resolution, and land cover and soil data were
aggregated by reclassifying the land-use data for nineclasses, and the soil data for eight classes. Daily
precipitation and air temperature data from 65 station
weather stations were obtained from the MekongRiver Commission (MRC) in this river basin.

RESULTS AND DISCUSSION
Annual records of discharge and suspended
sediment concentration in the study are being
extracted from the series of historical record
published by the MRC. The publications tabulated
measurements of water discharge, suspended
sediment concentration (SSC), water quality andother physical characteristics of a series of gauging
stations located along the Mekong River and its
tributaries. In view of this study, flow and SSC
records from three stations (Fig. 1) located in themainstream were identified, of which records threestations were used to calculate the sediment load
(Chiang Saen, Khong Chiam and Phnom Penh). The
stations were selected based on their relative locationfrom one another and the completeness of flow andsediment records for the station. Unlike discharge
which was measured daily, measurements of SSC
were relatively sporadic, sampling frequency ismonthlyandmeasurementsofsediment
concentration were not conducted at several gauging
stations due to the political unrest in some of theseareas. SSC samples were collected near the surface ofthe river (0.3 m depth) in the middle of themainstream [11]. The estimation of suspended
sediment load is challenging in the Mekong River,given that many gauging stations do not document
relatively long-term sedimentconcentration

Suspended sediment concentration simulation
To check the seasonal characteristics of suspended
sediment in the river, the concentration was also
simulated as shown in Fig. 2. Generally, a declining
trend in mean monthly suspended sedimentconcentration (SSC) was observed along the entire
length of the Mekong River since water quality
measurement began in 1985 [12]. Figure 2 shows themonthly SSC simulation at stream gauging station forthe period 1991 to 2000. The result reveals adecreasing trend in the SSC along the three regions
from upstream to the downstream. This decrease
trend was due to the decrease in the main stream watervelocity, which increases the sediment deposition and
the SSC become lower. The average monthly SSC
was highest at the Chiang Saen station was estimatedby 0.9 kg/m3. While, the average SSC at Phnom Penh
were estimated to be 0.25 kg/m3. That was the lowest
among the studied stations due to the sedimentdeposition behaviour in the Delta region, which
decrease the SSC in the water. The model results also
show the SSC was high in the rainy (July, August,
September) season than the dry season at all threestations. That is due to the intensive soil erosion

198

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

coincident with heavier precipitation.

simulation was underestimated at some point but
generally, the suspended sediment load was fairly
well simulated at the three stations. The results also
indicate that the model simulates suspended sedimentload with reasonable accuracy and describing theseasonal of suspended sediment load in the MekongRiver Basin, which can be applied to estimate thefuture suspended sediment load. The lower values of
NSE and r may attribute to limitations in terms of thecontinuity and length of the records. As [19] also
reported the lower NSE and r values for the daily
sediment calibration of the Nam Ou basin in Lao PDR
for a similar reason – a limited number of sediment
samples for calibration. This lack also highlights theneed for further investigation in the quality of theobserved sediment data reflected from the sampling
process and the method of sediment analysis.

Fig. 2 Daily suspended sediment concentration(SSC) simulation at stream gauge stations for 19912000.

Suspended sediment load simulation
The annual sediment loads of the Mekong River
were relatively stable in the past 40 years [13].
However, there is a significant seasonal change in theannual sediment loads among the year seasons.
Changes in sediment loads of the Lower Mekong
Basin have been analysed relying on the existing
sediment data in many literatures [14], [15], [16],[17], [18]. Since the existing sediment data in the
Mekong river basin have been collected byinconsistent method and had a low sampling
frequency [18] studies reported different changing
trends on sediment load in the Mekong River Basin.
Figure 3 shows the simulated results of monthly
suspended
sediment
load
comparedwithmeasurements of upper, middle and lower monitoring
stations cases from 1991-2000. The simulated results
show in good agreement with observations, asreported in Table 1. The NSE result is greater than 0.6;
0.62, 0.62 and 0.64 for upper, middle, and lower
station respectively (1991-1995) except thevalidation period for the Chiang Sean station (NSE =0.51). A relatively highest simulation error at the
Chiang Sean may have been caused by the effect of
the reservoir on the upper basin of Mekong River.
While, the linear correlation coefficient (r) between
simulated and observed values was in the range of
0.80 to 0.86 for all three region stations. The modelFig. 3 Monthly suspended sediment load (SSL)
simulation at stream gauge stations for 1991-2000.
In general, higher sediment load is expectedduring the wet season. The model results reveal that,for the entire period of 1991-2000, the averagesuspended sediment load a highest (76  105 t/day) at
middle region. While the upper region had a lower
average suspended sediment load calculated (27  105
t/day) compared to other study region. Moreover, themonthly suspended sediment load increased withincreasing basin area from Chiang Saen and Phnom
199

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017ha-1 mm ha-1.

Penh. The results reveal the increasing sediment loadin the lower region due to deposition process. Thus,
the suspended sediment load in the upper region of
the Mekong River Basin was lower than the middlelower region.
Table 2 Model performance indicators for daily riversuspended sediment load simulation in Mekong River
Basin from 1991 to 2000
Stations
ID
1
2
3

Name
Chiang
Sean
Khong
Chiam
Phnom
Penh

Performance Indicators
Calibration(1991-1995)
NSE
r

Validation(1996-2000)
NSE
r

0.62

0.85

0.51

0.65

0.62

0.86

0.62

0.83

0.64

0.80

0.64

0.87
Fig. 4 Average suspended sediment (SS) yield (t km2
year-1)

Suspended sediment yield simulation

CONCLUSION

The resulting spatial mean distribution of annual
SS yield was simulated in 1991-2000 as the model
output as shown in Fig. 4. The spatial pattern of SS
yield categories has five ranges of SS yield values.
Three qualitative categories have been chosen for the
output SS yield classes: low (SS yield range, 0.014.36 t km-2 yr-1), moderate (SS yield range, 14.3691.80 t km-2 yr-1), and high SS yield (SS yield range,
91.80-274.52 t km-2 yr-1). This trend can be
determined by coverage of land use, indicating
severely eroded area locates at the region with poor
vegetation cover and topographic of the basin.

In this study, the sediment dynamic process was
successful assessed using integrated process-basedmodel. The main findings were as followed.
1.

2.
Total annual SS yield range from 0.0 to 14.36 t
km-2 yr-1 are scattered in all over the MRB area. This
range occupying 60% of the study area incorrespondence to low steepness slope, range from 0
to 5.98% in lower region Mekong basin, in Thailand
and Cambodia part, and also some part in upper
region. Sand and clay of these parts, have better
permeability and highly resistant to runoff impact.
This total annual SS yield also is related mainly to theprotective role of forest and natural vegetation cover.
While, the SS yield range from 14.36 to 91.80 t km-2
yr-1 class occupying 35% in this study scattered in the
middle region near Vietnam and some parts near
Myanmar and Lao PDR. This is due to cropland coverand higher average annually rainfall distribution.
Furthermore, type of soil is highly contents silt andsand, easy to detach due to runoff. Small parts
occupying 5 % with extremely high value of SS yield,
91.80 to 274.52 t km-2 yr-1 in upper, middle and lower
region especially in the valleys with steep slopes andhigh rainfall-runoff factor between 7986-12,599 MJ

3.

4.

Integrated process-based sediment dynamic
model with targeting large basin in South
East Asia showed the applicability tosimulate sediment dynamic process,indicating the sufficient accuracy for longterm simulation.
The
simulatedsuspended
sediment
concentration is higher in the rainy (July,
August, September) season than the dry
season.
The sediment load in the lower region
Mekong River basin showed an increase due
to deposition process.
The results provide the spatial distribution of
SS yield over the Mekong River basin. SS
yield was the highest close to Vientiane andNakhon Phanom due to highest annual
rainfall records around this area. This canhelp us to identify the severe SS yieldproduced areas which deserve priority
attention in basin management for soil andwater conservation.

ACKNOWLEDGEMENTS
This work was supported by Core-to-Core
Program (B. Asia-Africa Science Platforms) of Japan
Society for the Promotion of Science (JSPS). The part200

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[9] Morgan RPC, Quinton JN, Smith RE, Govers G,
Poesen JWA, Auerswald K, Chisci G, Torri D,
and Styczen ME, “The European soil erosion
model (EUROSEM): a process-based approachfor predicting sediment transport from fields andsmall catchments”, Earth Surface Processes andLandforms 23, 1998, 527-544.
[10] FAO, “The digital soil map of the world andderived soil properties”, version 3.6,
FAO/UNESCO: Rome, Italy, 2003.
[11] Mekong River Commission, “Lower Mekong
Hydrologic
Yearbook”,
MekongRiver
Commission (MRC), 2000.
[12] Lu XX and Siew RY, “Water Discharge andsediment flux changes over the past decades inthe Lower Mekong River: possible impact of theChinese dams”, Hydrol. Earth Syst. Sci., Vol. 10,
2006, pp. 181-195.
[13] Walling DE, “Evaluation and analysis of
sediment data from the Lower Mekong River”,
Report to the Mekong River Commission, 61,
2005.
[14] Fu KD, He DM and Li SJ, “Response ofdownstream sediment to water resource
development in mainstream of the Lancang
River”, Chinese Science Bulletin, Vol. 51, 2006,
pp. 119–126.
[15] Kummu M and Varis O, “Sediment-related
impacts due to upstream reservoir trapping, theLower Mekong River”, Geomorphology, Vol. 85(3–4), 2007, pp. 275–293.
[16] Walling DE, “The Changing Sediment Load of
the Mekong River”, Ambio, Vol. 37, 2008, pp.
150–157.
[17] Walling DE, “Chapter 6 The Sediment Load of
the Mekong River, In: The Mekong: BiophysicalEnvironment of an International River Basin, Ian
C. Campbell (eds.), New York: Elsevier Inc.,
2009, pp. 113-142.
[18] Wang JJ, Lu XX and Kummu M, “Sediment load
estimates and variations in the Lower MekongRiver”, River Res. Appl., Vol. 27, 2011, pp. 33–
46.
[19] Shrestha B, Babel MS, Maskey S, Griensven AV,
Uhlenbrook S, Green A, and Akkharath I,“Impact of climate change on sediment yield in
the Mekong River basin: a case study of the Nam
Ou basin, Lao PDR”, Hydrol. Earth Syst. Sci.,
Vol. 1, 2013, pp. 1-20.

of the modeling work was also supported by AsianCore Program of JSPS and Collaborative Research
Program (CRA) of AUN/SEED-Net.
REFERENCES[1] Bhattarai R and Dutta DUSHMANTA,“Analysis of Soil Erosion and Sediment Yield
using Empirical and Process Based Models,
Proceedings of the MTERM International
Conference, AIT, 2005, pp. 215-226.
[2] Nearing MA, Foster GR., Lane LJ and Finckner,
SC, “A process-based soil erosion model for
USDA-Water Erosion Prediction Projecttechnology”, Transactions of the American
Society of Agricultural Engineers 32, 1989, pp.
1587-1593.
[3] Morgan RPC, Quinton JN and Rickson RJ,“EUROSEM version 3.1 a user guide”, Silsoe
College, Cranfield University, Silsoe, Bedford,
UK., 1993, pp.83.
[4] Beasley DB, Huggins LF and Monke EJ“ANSWERS: A model for watershed planning”,
Transactions of the American Society ofAgricultural Engineers 23, 1980, 938-944.
[5] Yang D, Herath S, Oki T and Musiake K,“Application of distributed hydrological modelin the Asian monsoon tropic region with aperspective of coupling with atmosphericmodels”, Journal of the Meteorological Societyof Japan, 79,1B, 2001, 373-385.
[6] Yang D, Oki T, Herath S and Musiake K, “A
geomorphology-based hydrological model andits applications”, In: Singh, V. P. & Frevert, D.
K. Eds. Mathematical Models of Small
Watershed Hydrology and Applications, Water
Resources Publications, Littleton, Colorado,
USA, Chapter. 9, 2002, pp. 259-300.
[7] Torri D, Sfalanga M and Delsette M, “Splash
detachment: runoff depth and soil cohesion”,
Catena, Vol. 14 (3), 1987, pp. 149-155.
[8] Habib–ur–Rehman DM and Akhtar EMN,
“Development of regional scale soil erosion andsediment transport model; its calibration andvalidations”, Pakistan Engineering Congress,
Vol. 69th Annual Session Proceedings, 2006, pp.
231-245.

201

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EVALUATION OF PIER-SCOUR PREDICTIONS FOR WIDE PIERS
USING FIELD DATA
Nordila Ahmad1, Bruce W. Melville2, Thamer Mohammad3, Zuliziana Suif1
1

Faculty of Engineering, National Defence University, Malaysia; 2Faculty of Engineering, The University of
Auckland, Auckland; 3Faculty of Engineering, Universiti Putra Malaysia, Malaysia

ABSTRACT
Many studies have been conducted and equations developed to predict wide bridge-pier scour equation.
However, most of these equations were developed using laboratory data and very limited equation that had beendeveloped were tested using field data. The purpose of this paper is to evaluate the laboratory wide pier scour
equation that proposed from the previous findings with field data set. Large amount of field data from theliterature were extracted and it consist both live-bed and clear-water scour. A method for assessing the quality ofthe data was developed and applied to the data set. Three other wide pier-scour equations from the literature also
used to compare the performance of each predictive method. Comparisons of computed and observed scour
depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and
RMSE value when compared with the large amount of laboratory and field data.
Keywords— Field Data, Local Scour, Scour Equation, Wide Piers

the main characteristics of the local flow field is theformation of secondary flows called vortices. Many
researchers [12], [13], [7] have proposed that these
vortices are the most important mechanisms of local
scour.

INTRODUCTION
Scour is the lowering of the level of the riverbed
due to water erosion such that there is a tendency to
expose the foundations of a bridge. The extent of
this reduction below an assumed natural level istermed the depth of scour or scour depth. The basic
mechanism that causes local scour around piers isthe downflow at the upstream face of the pier andthe formation of vortices at the base. The flow
moves more slowly as it approaches the pier, coming
to a rest at the face of the pier. The approach flow
velocity is reduced to zero at the upstream side of
the pier and this result in a pressure increase at thepier face. The associated pressures are highest near
the surface, where the rate of decrease in velocity isgreatest, and becomes lower the closer the flow is to
the river bed [17]. As the velocity decreases thecloser the flow is to the river bed, the pressure on theface of the pier also decreases accordingly, forming
a downward pressure gradient. The pressure gradienthence forces the flow down the face of the pier,resembling that of a vertical jet. The resulting
downflow creates an effect on the streambed andcreates a hole in the vicinity of the pier base. The
downflow impinging on the bed is the main scouring
agent [17], [15], [11]. Fig. 1 shows the flow andscour pattern at a circular pier under the action ofcurrents.

Fig. 1 The flow and scour pattern at a circular bridge
pier
PARAMETERS AFFECTING LOCAL SCOURAROUND BRIDGE PIERS
In order to measure the relation between thedepth of local scour at a bridge pier and its
dependent parameters, a detailed discussion of themechanics of local scour at bridge piers waspresented. [6] presented the relation between the

Actually, the flow field surrounding a pierstructure is quite complex, even for simple pierstructures such as piers with a circular shape. One of202

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017depth of local scour at a bridge pier and its
dependent parameters, which can be written as:

involving sediment size cannot be kept constant
between the model and the prototype [1]. If thesediment-to-structure-length scales are not properly
calculated for in the predictive equations, problems
will occur when the equations are used in situations
which differ from the laboratory conditions on
which they are based. The problems will be related
to the model not being able to maintain the properscale between model and prototype sediment as thesize of the prototype structure increases [1]. Thiscondition always occurs in huge gravity structures
such as in the case of large coastal and inland bridgepiers.

ds = f[Flood flow(,, U, y, g), Bed sediment(d50, g,s, Uc), Bridge geometry (b, Sh, Al), Time (t)](1)
where  and  = fluid density and kinematic
viscosity, respectively; U= mean approach flow
velocity; y = flow depth; g = acceleration of gravity;
d50 and g= median size and geometric standard
deviation of the sediment particle size distribution,
respectively; s= sediment density; Uc= criticalmean approach flow velocity for entrainment of bed
sediment; b = pier width; Sh and Al = parametersdescribing the shape (including floating debris) andalignment of the pier, respectively; t = time; and fdenotes “a function of”.

The wide pier problem is usually considered to be aconcern when the relative depth, y/b, is too small toallow the vortices to fully develop. Earlier
investigations of the dependence of scour depth (y/b)
were performed with small piles and very small
water depths [7]. [5] established an upper thresholdat y/b = 3 beyond which the scour depth is relatively
independent of the relative depth. However, [1]conducted tests with large piers which indicate thatthe threshold should be closer to 2, although data(2) included in a number of
below these thresholds are
empirical equations that overestimated prototype
scour depths. There are various researchers who
have attempted to deal with this problem.

By assuming a constant relative density of
sediment, for example by neglecting , and s, and ,
Eq. (2) can be written as:
𝐝𝐬
𝐛

𝐔

𝐲

𝐛

𝐔𝐭 𝐔𝐛

= 𝐟 (𝐔 , 𝐛 , 𝐝 , 𝛔𝐠 , 𝐒𝐡 , 𝐀𝐥, 𝐛 ,  )𝐜

𝟓𝟎

The first three parameters on the right-hand sideof Eq. (2) are flow-related and represent,
respectively, the stage of sediment transport on theapproach flow bed (termed flow intensity), the depthof flow relative to the size of the foundation (termed
flow shallowness), and the foundation size relative
to the sediment median size (termed sedimentcoarseness). The last two terms is a time scale forthe development of scour (Ut/b) and the effect ofviscosity (Ub/) based on the size of the foundation.

HEC-18 [3] is the standard used by mosthighway agencies for evaluating scour at bridges. It
was determined from a plot of laboratory data forcircular piers. In the latest edition of HEC-18 [9], theHEC-18 pier scour equation (based on the CSU
equation) is recommended for both live-bed andclear-water pier scour. The equation predicts
maximum pier scour depths. Basic applications
include simple pier substructure configurations andriverine flow situations in alluvial sand-bed channels.
The new equation of HEC-18 [9] is shown in Eq. (3).

The rational of choosing that dimensionlessparameters in this study is, all of those parameters
were use in piers analyses.
PREVIOUS FORMULAS FOR WIDE PIER
LOCAL SCOURds
 y 2 K1 K 2 K 3  bb

In terms of wide and long skewed piers, mostempirical local scour prediction equations
overestimate scour depths around structures that arewide compared to the water depths where they arelocated. The equations were derived using laboratory
data from steady flow experiments. Due to thecomplexity of the flow and sediment transport
associated with local scour processes, there are anumber of dimensionless groups needed to fully
characterise the scour. Many of these groups, suchas the ratio of water depth to structure diameter (y/b),
can be kept constant between the laboratory modeland the prototype structure. However, as there is alower limit on the sediment particle size before
cohesive forces become important, those groups

where
ds
y

0.35

Fr 0.43= scour depth (m)= flow depth directly upstream of the pier,(m)
K1 = correction factor for pier nose shape
K2 = correction factor for angle of attack offlow
K3 = correction factor for bed conditionb = pier width (m)Fr = Froude Number directly upstream of thepier, U/(gy)1/2, where, U=mean velocity
of flow directly upstream of the pier,
(m/s)

203

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

Jones and Sheppard equations [1] include thestructure-width-to-sediment-size ratio and thus
should be directly applicable to large structures(wide piers). They concluded that the pier width
impacts the equilibrium scour depth in two ways.
First, the pier size to flow depth ratio (y/b) is
important and can best be represented by a
hyperbolic tangent function, which makes the scour
depth primarily a function of the pier size forrelatively slender piers, but a function of the flow
depth for relatively wide piers. Second, the pier size
to sediment ratio (b/d50) can have an even greater
impact on the prediction of scour. Moreover, they
have shown that the maximum relative clear-water
scour occurs when the b/d50 ratio is about 46, andthat scour tends to diminish on both sides of thisvalue for constant values of U/Uc and y/b (Fig 2).
The equation produced by Jones and Sheppard isshown in Eq. (4).

scour equation resulting from their study is acombination of equations developed by [2] and [4],and is referred to as the Sheppard/Melville or S/Mequation. [10] concluded that the predictive methods
have improved in accuracy over the years, withthose developed in recent years demonstrating thebest performance. The Sheppard/Melville (S/M)
method was found to be the most accurate of thosetested and is recommended for use in design. The
S/M equation is shown in Equation 2.27.

ds
 2.5 f1 f 2 f 3
b*

0.4

 y
f1  tanh  *  ,
b 
2

  U  
f 2  1  1.2ln    , and  U c  (4) b* 




d50 



f3  
1.2
 0.13 ** 0.4 b   10 .6 b d   d50  50 

where

k

(5)

where

5  U  ds  1 c1  b
2 Uc  2c1  k3

for 0.4U/Uc1

and
0.66

 y 
tanh 2.18   b  


where




 b 
 log10 
0.78 
 0.279  0.049 e  d 50   
 b 
 
log 10  d 50  b*

 b p x*bbp

= effective pier width;= projected pier width;and= 1.0 for a circular pier;
 0.86  0.97    4


for a skewed pier
EVALUATION OF LABORATORY-DERIVED
CURVE ON FIELD DATA
[16] present the relationship between equilibrium
local scour depth (ds/b) and sediment coarseness forlarge ranges of b/d50. A least-squares regression
analysis using a fitting criterion of mean square error
was applied to all data in their study plus withlaboratory data in the literature, and found the
optimum coefficients which minimised the meansquare error between the experimental and predictedvalues. The best fit relationship between ds/b andb/d50 is described by this laboratory-derived curve in
Eq. (6) and the graph can be shown in Fig. 3.

Fig. 2 Dependence of normalised scour depth on
b/d50 for a circular pier. For the curve shown U/Uc=1
and y/b>2
Based on a recent publication, [10] have made an
improvement in developing the best-performing
equations. The recommended equilibrium local
204

4

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017𝟐𝒅𝒔

= 𝟑. 𝟒 −
𝒃

𝟑𝟎
𝒃
(
)
𝒅𝟓𝟎

equilibrium time. Regardless, it can be consider that
uncertainty occurs during measurement of scour and
it is never known whether the bed has attained anequilibrium stage during scour data measurements.
Similar discrepancies can occur for scour data inlive-bed conditions, but this may be for otherreasons.

𝒃

𝒆𝒙𝒑 [𝟎. 𝟎𝟖𝟖 (𝒍𝒏 (𝒅 )) ]
𝟓𝟎

(6)
3.5

Present study
Yanmaz & Altinbilek (1991)
Mia & Nago (2003)
Chabert & Engeldinger (1956)
Ettema (1980)
Sheppard et al (2004)
Ettema (1976)
Equation (1)

3

ds/b

2.5
2

ds/b

1.5
1
0.5
0
10

100

1000

10000

b/d50

3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

Mueller & Wagner (2005)_clear water
Muell & Wagner (2005)_live bed
Equation (4.1)

10

Fig. 3 Plot of ds/b versus b/d50 from laboratory data
[16]

100

1000

10000

b/d50

Fig. 4 Plot of ds/b versus b/d50 for selected field data.
(Source of data: [14])In this study, the field measurements of [14]were used to test the applicability of Eq. (6) to fielddata. The measurements consist of both clear-waterand live-bed data sets. Before the comparison was
made, the field data were filtered from 493 to 45
data sets. This is because when the full data set isused, there is no relationship obtained between ds/b
and b/d50. Therefore, several steps had been taken inchoosing the field data. First, only a single pier typewas selected. Second, data that b/d50> 50 werechosen [8]. Thirdly, the data points that have d50<
0.1 mm were eliminated in order to consider thecohesive effects from that sediment. Fourth, datathat affected from debris accumulation around thebridge pier were also eliminated due to there being
no definite relationship between the scour depth anddebris accumulation. Fifth, if the scour depth wasmeasured at the upstream and downstream of thebridge pier, only the maximum value of scour depth
was preferred. Finally, if the scour depth wasmeasured around the same bridge pier, only the
maximum scour depth was chosen. This gives 15
data sets from clear-water scour conditions and 30
data sets from live-bed conditions. All of the filtereddata are graphically shown in Fig. 4 along with thebest fit curve from Fig. 3.

Although the recorded scour depth can represent
equilibrium scour conditions for live-bed scour, it ispossible that the recorded scour depth was less thanthe equilibrium value because of the dynamic flow
and sediment transport aspects around a bridge site
like the transition of dunes through the scour hole.
However, the combination of the laboratory-derived
curve with the field data which have been filtered asdemonstrated in Fig. 4 gives evidence that thenormalised scour depth appears to be significantly
reduced for the large values of b/d50 that are
frequently found in the field. It was found that Eq.
(6) can fit both data sets for clear-water and live-bed
conditions. For extra safety, 25% can be added to thevalue obtained from Eq. (6) in order to consider thevalue of the maximum scour depth for the all data
sets used.
EVALUATION OF EXISTING EQUATIONSFOR PREDICTING MAXIMUM LOCALSCOUR DEPTH AT WIDE PIERS
In this section, field data sets were used to validate
the predicted maximum scour depth at wide piersusing equations proposed by [1], HEC-18 [9], and[10]. Statistical analysis was carried out to assess theperformance of each predictive equation. The
discrepancy ratio (r), the standard deviation of thediscrepancy ratio (r), and the root mean squareerror (RMSE) were determined. The formulae forthe statistical analysis are described below:

According to Fig. 4, most of the clear-water fielddata indicate reasonable agreement with thelaboratory-derived curve when it is considered as an
upper envelope curve. For those clear-water scour
data sets below the curve, it may be that pier scour
depth could not attain the equilibrium stage during
the time in which the data were measured because of
the short duration of the flood relative to the205SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Present study
2.54 3.01
0.80𝒓̅ 1= average discrepancy ratio, r2 = standard
deviation of discrepancy ratio, RMSE3 = root meansquare error𝟐∑𝑵𝒊=𝟏(𝒅𝒔 ⁄𝒃𝒑𝒓𝒆𝒅𝒊𝒄𝒕𝒆𝒅,𝒊 −𝒅𝒔 ⁄𝒃𝒎𝒆𝒂𝒔𝒖𝒓𝒆𝒅,𝒊)

𝑹𝑴𝑺𝑬 = √(7)𝑵−𝟏(𝒅𝒔⁄𝒃)𝒓 = (𝒅 ⁄𝒃) 𝒑𝒓𝒆𝒅𝒊𝒄𝒕𝒆𝒅𝒔(8)

𝒎𝒆𝒂𝒔𝒖𝒓𝒆𝒅

3

𝟏

̅ )𝟐
𝝈𝒓 = √𝑵−𝟏 ∑𝑵
𝒊=𝟏(𝒓𝒊 − 𝒓

Jones & Sheppard (2000)(9)2

Where 𝒓̅ is the average of the discrepancy ratio. A
value of unity for 𝒓̅ shows perfect agreement
between the dimensionless scour depths of thepredicted and measured values. r represents anevaluation of the scatter in the predictions relative tothe average value.

1

0
0

1

3

The statistical analysis using the predicted andfield data sets is also shown in Table 1. It was foundthat all the tested equations over-predict the ds/b
values for field conditions. As stated previously, theprobable reasons for this are that the field datacontain non-equilibrium field scour conditions anddiscrete measurements rather than data based on
measurements that were made continuously withtime in the field. The lack of agreement with thefield data sets can be attributed to the difficulty inmeasuring field data using flood-chasing or discretemeasurement in time without being able to take into
account the unsteady development of the scour holeitself. Therefore, it is likely that the proposed
equation will produce the smallest discrepancy ratio
and RMSE value when compared with the large
amount of laboratory and field data. Visualcomparison (scattergrams) is another method thatcan be used to evaluate the predictive equations
using the predicted and measured scour depths atwide piers. Fig. 5 demonstrate the dimensionless
scour depth for field data sets. The plot indicate howmuch the predicted values of normalised scour depth
deviate from the line of perfect agreement. From theobservation, the results obtained from applying Eq.
(6) are found to be in agreement with the results
obtained from applying the selected equations whenfield data sets are used.

2

3

HEC-18 (2012)

2

ds/bpredicted

1

0
0

3

1

2

3

Sheppard et al (2014)

2

1

0
0

1

2

3

3
Present Study
2

1

Table 1. Summary of the discrepancy ratio, r, androot mean square error, RMSE, for each predictive
equation

ds/bmeasured

00Field datar
Jones and Sheppard(2000)
HEC-18 (2012)
Sheppard et al.
(2014)

𝒓̅

r

RMSE

2.75
6.26

3.43
7.95

1.21
4.22

2.68

3.43

0.99

1

2

3

Fig. 5. Comparison of the predicted and measured
normalised scour depths in the field [14] withselected existing scour depth predictive equations
CONCLUSION

206

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

In order to show the effectiveness of the
proposed equation from the previous findings [16]for predicting maximum scour depth around widepiers, several scour prediction equations were
evaluated with field data. It was found that equations
from [1], [9] and [10] mostly over-predict scour
depth, as shown by the statistical analysis with thediscrepancy ratio, r, and RMSE in Table 1. Thisevaluation was also supported by scattergrams,
shown in Fig. 5. Equation (6) produces the smallest
discrepancy ratio, r, and RMSE, and thus can bereliably used to predict scour depth at the prototype
scale. As a factor of safety, 25% can be added to thevalue obtained from Eq. (6) in order to consider thevalue of the maximum scour depth for all data sets
used. Meanwhile, it needs to be stressed that theapplicability of Eq. (6) is limited to values of b/d50
from 50 – 4200, to skewed piers with angle of attack,< 45, to piers in shallow flows and to gradedsediments with g less than 7.

[6] Melville, B.W., Coleman, S.E., 2000. Bridge
Scour. Water Resources Publications,LLC,
Colorado, U.S.A., 550 p.
[7] Ettema, R., 1980. Scour around bridgepiers.Report No. 216, University of Auckland,
Auckland, New Zealand.
[8] Sheppard, D. M. (2004). “Overlooked local
sediment scour mechanism.” Transportation
Research Record: Journal of the Transportation
Research Board, 1890, 107–111.
[9] Arneson, L. A., Zevenbergen, L. W., Lagasse, P.
F., and Clopper, P. E. (2012). Evaluating scour
at bridges, 4th Ed. Hydraulic Engineering
Circular No. 18 (HEC-18), Federal Highway
Administration, Washington, DC[10] Sheppard, D. M, Huseyin, D. Melville. B. W.
(2014). Evaluation of Existing Equations for
Local Scour at Bridge Piers. Journal of
Hydraulic Engineering–ASCE, 140(1), 14–23[11] Ibrahimy M. I. and S. M. A. Motakabber.
Bridge Scour Monitoring by Coupling Factor
Between Reader and Tag Antennas of RIFD
System. International Journal of GEOMATE,
8(2), 1328-1332[12] Shen, H. W., Schneider, V. R., and Karaki, S.
(1966). Mechanics of local scour, U.S. Dept. ofCommerce, National Bureau of Standards,
Institute for Applied Technology, Fort Collins,
CO.
[13] Melville, B. W. (1975) “Local Scour at Bridge
Sites.” Rep. No.117, School of Engineering,
The Univ. of Auckland, New Zealand.
[14] Mueller, D. S., and Wagner, C. R. (2005).
“Field observations and evaluations ofstreambed scour at bridges.” Office ofEngineering Research and Development,
Federal Highway Administration, McLean,
Virginia.
[15] Dey, S. (1996). “Sediment pick-up for evolving
scour near circular cylinders.” Applied
Mathematical Modelling, 20(7), 534-539.
[16]Nordila A., Thamer A. M.and Zuliziana S.
(2017). “Prediction of Local Scour around Wide
Bridge Piers under Clear-water Conditions”.
International Journal of GEOMATE. 12(34),
135-139.
[17] B.W. Melville, A.J. Raudkivi (1977). “Flowcharacteristics in local scour at bridge piers”.
Journal of Hydraulic Research, 15 (4) (1977),
pp. 373-380

ACKNOWLEDGEMENTS
The financial support from the Research University
Grant Scheme (RUGS) given by University Putra
Malaysia (Grant No. 05-01-10-0904RU) for thisproject is acknowledged. The experiments wereconducted in the Hydraulic Laboratory in the
National Hydraulic Research Institute of Malaysia(NAHRIM).
REFERENCES[1] Jones, J. Sheppard, D. 2000, Scour at wide
bridge pier. Building Partnerships, pp. 1–10.
[2] Melville, B. W. (1997). “Pier and abutment
scour: Integrated approach.” Journal of
Hydraulic Engineering–ASCE, 123(2), 125–136.
[3] Richardson, E. V., and Davis, S. R. (2001).
“Evaluating scour at bridges.” Fourth Edition.
Hydraulic Engineering Circular No. 18 (HEC18),
FederalHighway
Administration,
Washington, D.C.
[4] Sheppard, D.M., Miller, W., 2006. Live-bed
local pier scour experiments.Journal of
Hydraulic Engineering, ASCE,132(7), 635–642[5] Melville, B. W., and Sutherland, A. J. (1988).
“Design method for local scour at bridge piers.”
Journal of Hydraulic Engineering–ASCE,
114(10), 1210–1226.

207

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

MECHANICAL CHARACTERISTICS OF ARTIFICIAL STONE MADEFROM WASTE OF SILICEOUS TUFF
1

Hiroaki Shigematsu1 and Shogo Hashimoto2
National Institute of Technology, Ishikawa College, Japan; 2 Taisei Corporation, Japan

ABSTRACTIn this study, in order to clarify the mechanical characteristics of the artificial stone made from waste of thesiliceous tuff, a series of laboratory tests are carried out. The experiments involve unconfined compression test,
bending test and needle penetration test. From experimental results, the in-situ applicability of the artificial stone
as civil engineering materials is discussed. The following conclusions are obtained from present study: (1)Unconfined compressive strength of the artificial stone made from waste of siliceous tuff increases remarkably
by extending the curing period. Also, the higher the density of the artificial stone is, the higher the strength of theartificial stone is due to pozzolanic reaction. (2) As siliceous tuff contains more silica and alumina than other soilmaterials, it has higher pozzolanic reactivity. (3) Unconfined compressive strength of the artificial stone can be
estimated by two parameters of dried density and curing period. (4) By compacting artificial stone densely, thestiffness of the artificial stone becomes higher. (5) Sandy soil is unsuitable for base material of artificial stone.
(6) Even though the flexural strength of the artificial stone is not as high as that of concrete, its strength increases
remarkably by extending the curing period.
Keywords: Siliceous Tuff, Artificial Stone, Strength Development, Deformation, Flexural Strength

the artificial stone into the restoration work ofAngkor heritage.
In this study, in order to clarify the mechanicalcharacteristics of the artificial stone made fromwaste of the siliceous tuff, a series of laboratory tests
were carried out. The strength development
characteristics of the artificial stone are firstly
discussed based on unconfined compression test
results. Secondary, the deformation properties of theartificial stone are explained with attention to themodulus of deformation obtained from unconfinedcompression tests. Finally, the flexural strengthcharacteristics of the artificial stone are describedbased on the results of bending test and needle
penetration test.

INTRODUCTION
Siliceous tuff which belongs to Hokuriku layergroup of Neogene period, around 23 million to 2.6
million years ago, is deposited thickly in Ishikawa
Prefecture facing the Sea of Japan. The siliceous tuff
is light and porous material, so it has been often used
as a filtration material and a remover material forslug in an ore for a long time. However, the size ofthe crushed pieces of the siliceous tuff is required tobe more than 0.25 mm in these uses. Others havebeen thrown away as waste. Therefore, the effective
utilization of the waste discharged in crushingprocess of the siliceous tuff must be considered
quickly. Fortunately, it contains much silica (SiO2)
and alumina (Al2O3) necessary for pozzolanic
reaction in cement or lime soil stabilization. Authors
have decided to use the waste as a base material of
the artificial stone in these situations.
The artificial stone, called "Tataki" in Japanese,
is soil compacted after mixed with lime and antifreezing agent, and has high strength and hardness
comparable to concrete [1], [2]. Being also low
environmental load, its application in a wide rangeof fields will be expected in the future. Recently,
strong points of the artificial stone and Japanesetraditional technique have been reconsidered andreported by researchers and technicians. Tamayama
et al. [3] reported that the artificial stone made byusing the Japanese traditional technique can beutilized as pedestrian pavement materials. Iwasaki[4] introduced the Japanese traditional technique ofKanazawa
City
TsuribeIshikawa Pref.

Fig. 1
208

Sampling site for Siliceous tuff.

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

Table 2 Physical and chemical properties of base materials
Ishikawa-Lite
2.443
1.402
25.7
9.0
74.2
16.8
－
NP
－
6.1
－

3

Density of soil particle, ρs (g/cm )Maximum dry density, ρdmax (g/cm3)
Optimum moisture content, wopt (%)
Sand fraction (%)
Silt fraction (%)
Clay fraction (%)
Liquid limit, wL (%)
Plasticity limit, wP (%)
Plasticity index, IP
Ignition loss, Li (%)
Activity, A (%)
Table 1 Chemical composition of Ishikawa-Lite
Silicon dioxide (Silica), SiO2 (%)
Aluminium oxide (Alumina), Al2O3 (%)
Potassium oxide, K2O (%)
Iron(III) oxide, Fe2O3 (%)
Sodium oxide, Na2O (%)
Calcium oxide, CaO (%)
Magnesium oxide, MgO (%)
Others (%)

Fujinomori soil
2.689
1.601
22.9
12.7
76.9
10.4
43.8
21.0
22.8
5.9
3.93

Ohta soil
2.629
1.698
15.3
62.8
26.4
10.8
30.7
NP
－
3.0
－

now on. Both of them were air-dried and then passed
once through each sieve (Fujinomori soil: 0.425 mm,
Ohta soil: 4.75 mm).
Physical and chemical properties of the basematerials after passed through the sieve are shown in
Table 2. From grain size distribution, both ofIshikawa-Lite and Fujinomori soil contains morethan 70 percent silt, and Ohta soil includes morethan 60 percent sand. Ishikawa-Lite is porous
material, so density of its soil particle shows slightly
lower value than that of Fujinomori and Ohta soils.
This affects the maximum dry density of three basematerials. Ishikawa-Lite and Ohta soil are alsoclassified as “non-plastic” because the plastic limit
could not be obtained.
Hydrated lime (Ca(CH)2) for stabilizer andmagnesium chloride (MgCl2･6H2O) for anti-freezing
agent were used in a series of laboratory tests. Mix
proportion of specimen was decided based on thedried mass of the whole sample with base material a(g), hydrated lime b (g) and magnesium chloride c(g), as shown in Table 3. Amount of water added d(g) was determined by the following equation (1),wopt in it means optimum moisture content for eachbase material.

63.4
17.1
3.34
2.79
2.62
0.86
0.66
9.23

Table 3 Mix proportion of specimen (Dried mass
per 100g)
Base material Hydrated lime Magnesium chloride
a (g)
b (g)
c (g)
65
30
5

MATERIALS AND LABORATORY TESTS
Materials
Base material of the artificial stone used forexperiments are waste of the siliceous tuff and two
kinds of soil samples. The siliceous tuff was taken at
Tsuribe area of Kanazawa city in Ishikawa
Prefecture, Japan, as shown in Figure 1. Based on
the name of this area, the siliceous tuff is called“Ishikawa-Lite” from now on. Ishikawa-Lite wascrushed, air-dried and then passed once through the
0.425 mm sieve. The tuff includes much silica andalumina as shown in Table 1. This means that thelong term pozzolanic reaction increases the strengthof the material. In this study, other two basematerials were used. One is cohesive soil obtained at
Fujinomori area of Kyoto city, Japan, and another issandy soil taken at Ohta area of Tsubata town in
Ishikawa Prefecture, Japan. These soils are named“Fujinomori soil” and “Ohta soil” respectively fromd  a  b  c  

wopt
100

(1)
Laboratory tests
In order to understand the strength development,
deformation and flexural strength characteristics ofthe artificial stone, three different kinds ofexperiments were carried out. Figure 2 shows
preparation method of the specimen for unconfinedcompression test and bending test. The diameter andheight of the specimen used for unconfinedcompression test is 35 mm and 70 mm respectively,
and those of the specimen used for bending test is 50
209

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

mm and 110 mm respectively. Dry density of eachspecimen is decided based on maximum dry density(ρdmax) of each base material as shown in Table 2.
The specimen used for each experiment was
static compacted after mixed with hydrated lime andmagnesium chloride into each base material atpredetermined ratio as shown in Table 3. After that,the cylindrical mold was used to prevent the
expansion of the specimen for 24 hours. The
specimen demolded was wet cured at a constanttemperature for predetermined days. Curing periodsof the specimen used for unconfined compression
test are 1, 3, 7, 14, 28, 56 and 112 days, and those of
the specimen used for bending test are 28, 56, 112
and 225 days.

the result, generates compound with binding ability.
Therefore, Ishikawa-Lite with more silica andalumina than other soil materials indicates higher
pozzolanic reactivity.
The strength qu of the artificial stone can bepredicted by two parameters of dry density (ρd) andcuring period. ρd means the dry density after curing
for predetermined period. This is very useful forpractical use. Figure 5 shows the relationships
between ρd and qu of the artificial stones at eachcuring period for Ishikawa-Lite as base material. ρdof each specimen is slightly lower than ρd0. ρd - qucurve can be approximated by logarithm at eachcuring period. For example, the artificial stone of ρd= 1.43 g/cm3 will reach to qu = 6.5 MN/m2 at 56 daysof curing.

EXPERIMENTAL RESULTS
Strength Development Characteristics

Hydrated lime andMagnesium chloride

Unconfined compression test results of theartificial stones are shown in Figures 3 to 7. ρd0
shown in those figures means the dry density after
static compaction. Figure 3 shows the relationships
between unconfined compressive strength (qu) andcuring period for Ishikawa-Lite as base material.
From experimental results, qu of the artificial stoneincreases remarkably by extending the curing period.
Strength development of lime-stabilized soil isgenerally divided into two phases. The first phase isa short period during which water absorption and ion
exchange reaction take place. The second phase is along period during which the pozzolanic reaction
takes place. Artificial stone is the material that
hardens due to pozzolanic reaction over a long
period of time. Also, the higher the density of theartificial stone is, the higher the strength of theartificial stone is due to pozzolanic reaction asshown in Figure 3.
In order to investigate the influence of thedifference of physical properties of base materials,
Fujinomori and Ohta soils mentioned earlier wereprepared as comparative soils. Figure 4 shows therelationships between qu and curing period of theartificial stones for different base materials. ρd0 ofeach specimen was set to make equal to the value ofthe maximum dry density of each base material. In
the case of Ohta soil as base material, qu is lower
than the case of other base materials. Especially, thestrength increase due to pozzolanic reaction in longterm curing for Ohta soil is much lower than that forother two base materials. qu for Fujinomori soil as abase material is higher than that for Ishikawa-Lite inshort-term curing. On the other hand, qu for
Fujinomori soil as a base material is lower than thatfor Ishikawa-Lite in pozzolanic reaction stage. The
pozzolanic reaction is the phenomenon that the
pozzolan with the silica and alumina as main
components reacts with hydrated calcium slowly, as

Distilledwater

MixingStatic compaction
20℃

Fix the cylindrical moldFig. 2

Wet curing

Preparation method of specimen.

Unconfined compressive strength q u(MN/m2)

18
16
14

ρd0=1.6g/cm 33
ρd0=1.4g/cm 3(=ρdmax )ρd0=1.2g/cm

12
10
8
6
4
2
0
0

Fig. 3210

Ishikawa-Lite

20

40
60
80
Curing period (days)

100

120

Relationships
betweenunconfinedcompressive strength and curing period of
artificial stones for Ishikawa-Lite as base

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

material.
87material gradually. By compacting the material
densely, the stiffness of the artificial stone becomes
higher as shown in Figure 6.
Figure 7 shows the relationships between E50 and
qu of the artificial stones for different base material.
The stiffness of artificial stone for Ohta soil as basematerial is not low as shown in Figure 7. However,the strength development of the artificial stone for
Ohta soil is lower than the artificial stone for
Ishikawa-Lite and Fujinomori soil. Consequently,
sandy soil such as Ohta soil is unsuitable for basematerial of artificial stone.

Ishikawa-Lite, ρd0=1.4g/cm 3(=ρdmax )Fujinomori, ρd0=1.6g/cm 3(=ρdmax )Ohta, ρd0=1.7g/cm 3(=ρdmax )

6
5
4
3
2

Relationships
betweenunconfinedcompressive strength and curing period of
artificial stones for different base materials.

1.7
1d

3d 7d 14d

28d
56d

1.5

35
)

2

R2
=0
.9

=0
.9

u(

u (R

1200

5.
9q
10

1000

)
30

9
0.

↑ 2=
(R
u
7q

800
8.

600

=8

0
E5

400
ρd0=1.6g/cm 3
ρd0=1.4g/cm 33(=ρdmax )ρd0=1.2g/cm

200
0
0

112d

2
4
6
8
10 12 14 16 18
2
Unconfined compressive strength q u(MN/m )1.4

Fig. 6
1.3

Ishikawa-Lite

1.2

ρd0=1.6g/cm 3
ρd0=1.4g/cm 33(=ρdmax )ρd0=1.2g/cm

Deformation Properties
Figure 6 shows the relationships between E50 and
qu of the artificial stones at each dry density ρd0 for
Ishikawa-Lite as base material. Each E50 - qu relation
can be approximated by a linear function. E50
increases roughly proportionally with the increase ofqu at the same dry density ρd0. This tendency meansthat the deformation of the artificial stone becomes
small with the increase of compressive strength.
Consequently, the artificial stone becomes stiffer

800

)
.9
R2
=0

=0
.7

.9

q

u(

u (R 2

05
=1
50

E

E5

3)

96
0.

2 =

(R

qu

4

1.

=9
0

600
400
200
0
0

Fig. 7

211

.5q

1000

35

07

Relationships between dry density andunconfined compressive strength ofartificial stones for Ishikawa-Lite as basematerial.

1200

05

2
4
6
8
10 12 14 16
Unconfined compressive strength q u(MN/m2)

0 =2

Fig. 5

1400

E5

1.0
0

Relationships
betweenmodulusofdeformation and unconfined compressive
strength of artificial stones for IshikawaLite as base material.
)

1.1

Modulus of deformation E 50(MN/m2)

Dry density ρd(g/cm3)

1.6

1400

50
=

120

12
2.
6q

100

50 =

40
60
80
Curing period (days)

E

Fig. 420

Ishikawa-Lite

E

0
0

1600

61
)

1800

1
Modulus of deformation E 50(MN/m2)

Unconfined compressive strength q u(MN/m2)

9

Ishikawa-Lite, ρd0=1.4g/cm3(=ρdmax )Fujinomori, ρd0=1.6g/cm 3(=ρdmax )Ohta, ρd0=1.7g/cm 3(=ρdmax )

2
4
6
8
10
12
14
Unconfined compressive strength q u(MN/m2)

Relationships
betweenmodulusofdeformation and unconfined compressive
strength of artificial stones for different
base materials.

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

Maximum Load
Pmax(N)

Flexural Strength Characteristics

Needle Penetrometer→

Artificial stone is expected to be widely used forconstruction work such as block pavement and theblock for retaining wall in the future. Therefore, inorder to clarify the flexural strength characteristics
of artificial stone, bending tests based on civilengineering material experiment method werecarried out as shown in Figure 8. Flexural strength(σb) was determined by the following equation (2),in which I means moment of inertia.
Fig. 8(2)↑
A piece of specimen
after bending test

Methods of Bending test and needle
penetration test.

3.0

Ishikawa-LiteFigure 9 shows the relationships between σb andcuring period of the artificial stones at each dry
density ρd0 for Ishikawa-Lite as base material. Even
though flexural strength σb of the artificial stones at
each dry density ρd0 is not so high as that of concrete
using ordinary portland cement ( ≓ 7.0MN/m2), it
increases remarkably by extending the curing period.
The values of σb (=1.4 or 2.5 MN/m2) at 225 days ofcuring is found to be obtained nearly three times
higher than σb (=0.5 or 0.9 MN/m2) at 28 days ofcuring as shown in this figure.
In order to investigate σb - compressive strength
relation of the artificial stones, the needle
penetration tests were carried out by using a piece ofspecimens after bending tests as shown in Figure 8.
The conversion unconfined compressive strength qu*is calculated from the penetration resistance (N/mm).
Figure 10 shows the σb - qu* relation of the artificial
stones. The σb and qu* relation can be expressed by
the following equation (3). The needle penetration
test can be easily conducted without worrying timeand place. Therefore, it is very useful for practicalengineers if the flexural strength of the artificial
stones is estimated by using equation (3). However,in order to make the σb - qu* relation clearer, moreexperiments of artificial stones are needed in the
future.

1 b  qu*
5

l
2

l
2

Flexural strength σb(MN/m2)

Pmax l DM22b  y D 4 2
I
64

Diameter: D=50mm
Span: l =80mm

2.5
2.0
1.5
1.0
0.5

ρd0=1.4g/cm 3(=ρdmax )ρd0=1.2g/cm 300Fig. 950

100
150
Curing period (days)

200

250

Relationships between flexural strength andcuring period of artificial stones for
Ishikawa-Lite as base material.

3.0

Ishikawa-Lite
2

Flexural strength σb(MN/m )

2.5

2.0

1.5

1.0

0.5

(3)

←σb=1/5qu*ρd0=1.4g/cm 33(=ρdmax )ρd0=1.2g/cm

0
0
2.5
5.0
7.5
10.0
12.5
15.0
Conversion unconfined compressive strength q u* (MN/m 2)

Fig. 10 Relationships between flexural strength andconversion
unconfinedcompressive
strength of artificial stones for IshikawaLite as base material.
212

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

CONCLUSIONSREFERENCES

The main conclusions obtained in this study aresummarized as follows.
(1) Unconfined compressive strength of theartificial stone made from waste of siliceous tuff
increases remarkably by extending the curing period.
Also, the higher the density of the artificial stone is,the higher the strength of the artificial stone is due topozzolanic reaction.
(2) As siliceous tuff contains more silica andalumina than other soil materials, it has higher
pozzolanic reactivity.
(3) Unconfined compressive strength of theartificial stone can be estimated by two parametersof dried density and curing period.
(4) By compacting artificial stone densely, thestiffness of the artificial stone becomes higher.
(5) Sandy soil is unsuitable for base material of
artificial stone.
(6) Even though the flexural strength of theartificial stone is not as high as that of concrete, its
strength increases remarkably by extending thecuring period.

[1] Yoshida N., “Lime concrete observed at thefoundation of old Osaka prefectural governmentbuilding completed in 1874”, General Building
Research Corporation (GBRC), Vol.37, No.4,
2012, pp.29-37 [in Japanese].
[2] Ishida S, “Research and Conservation on
Industrial Heritage of Artificial Stone''TATAKI''”, Journal of Historical Studies in
Civil Engineering, Vol.11, 1991, pp.309-318 [inJapanese].
[3] Tamayama Y, Iwashita T, Akagi T and Ito T,“The Environmental Properties of Artificial
Stone Developed by Using the Method ofConstruction,''Tataki''”,
The
Japanese
Geotechnical Society, Vol.52, No.11, 2004,
pp.23-25 [in Japanese].
[4] Iwasaki Y., “Authenticity and TechnicalTransfer of Rammed Ground for Restoration
Work of Angkor Heritage”, The Japanese
Geotechnical Society, Vol.62, No.4, 2014, pp.69 [in Japanese].

213

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

3 DIMENSION REAL TIME IMAGES OF RAINFALL INFILTRATION
INTO UNSATURATED SOIL SLOPE
Aniza Ibrahim1, Irfana Kabir Ahmad2, Hapsa Husen3, Jestin Jelani4 and Mohd. Raihan Taha5
1

Faculty of Engineering, National Defense University of Malaysia;2Faculty of Engineering, National
University of Malaysia.

ABSTRACT
Failure of soil slope is mainly due to infiltration of rainfall. The complexity of rain water path infiltrate soil
slope can be predicted using commercial software, and volumetric moisture content at the infiltrated slope area
can be measured by Time-Domain-Reflectometry (TDR). Prediction of rain water path is based on parameters
obtained by laboratory works, and volumetric water content using TDR can only available at the point of insertion.
In this research, an innovative method called Electrical Capacitance Volume Tomography (ECVT) was used in
geotechnical engineering application in determining the real time imaging of rain water infiltration into unsaturated
soil slope. This method also achieves permittivity value through the experiments and converted to volumetric watercontent using equation. A soil sample obtained from slope failure around National Defense University of Malaysia(NDUM) campus during monsoon season were used in the research. The results revealed real time 3 dimension(3-D) images of rain water infiltrated into soil slope were produced through image reconstruction method of ECVT.
Volumetric water content were also achieved using permittivity value attained by ECVT result. Images which
permittivity indicated the infiltration of rain water through soil slope were clearly shown in the results. This
innovative technology is expected to improve the understanding of soil slope behavior especially in for rainfall
infiltration that relates to soil stability.
Keywords: Rainfall, Infiltration, Soil Slope, ECVY.

content was determined by laboratory works andprevious data to simulate rainfall infiltration into soil
slope event.

INTRODUCTION
Slope instability in tropical country such as
Malaysia, normally triggered by the high seasonalrainfall event. [1], [2], [8]. This main reason is also
caused by other activities such as construction
development of hillside, and geological factors. As
rainfall event started and for some times, infiltrate
into unsaturated soil slope, and increase the negative
pore pressure above groundwater table and moisture
content. In the monsoon season, soil slope will
vigorously subjected by high intensity and long
duration of rainfall, and this cause rainfall- induced
slope failure. [6].

This study is to introduce ECVT as a innovativetechnology used in geotechnical engineeringresearch. ECVT is 3 dimensional real- time imaging
system considered as “the most promising techniquefor dynamic flow imaging, which has a relatively hightemporal resolution, up to few milliseconds, withreliable spatial resolution [4].
The used of tomography technique is widely
known for medical field purposes such as Magnetic
resonance imaging (MRI), X-ray micro tomography,
Optical tomography, resistive tomography, Acoustic
tomography, Positron-emission tomography (PET),
Capacitance tomography, and others [11].

The complexity of rainfall infiltration event into
soil slope is due to non-linear of soil water
characteristic and soil permeability [12]. The study ofmain parameters such as initial moisture content, soil
water retention ability, soil porosity and others is vitalfor the understanding of soil behavior when subjected
to various rainfall intensity and duration[3], [5],.

The principle of ECVT is based on forward andinverse problem electrical properties measurement[10].

Current studies on the rainfall- induced involve
laboratory work such as using soil slope flume
equipped of apparatus to measure the parameters. The
images of rainfall infiltration showing the real time
infiltration is not available since all simulations weredone by software. The prediction of soil moistureCollection of capacitance data from electrodes tothe data acquisition system is a forward problem,
which the electrodes act as sensors are located at theperimeter of ECVT wall vessel. Next, inverse
problem will retrieving the capacitance data.

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Consequently, reconstructing the images is obtained
through the measured data capacitance.

Tilted Flume Apparatus
Tilted flume as soil slope model was used and
ECVT sensors system was attached to it. ECVT
system is including the 32 channel sensors and results
were obtained through data requisition system (DAS)
by personal computers.

Earlier studies using ECVT are including gas
distributor of single gas distributor of paraffin liquid,
air, and glass beads as flow media [9] to ensure themoving object is detected by ECVT sensors andproduce real time images. Research by [7] shows the
successfully capturing water seeping in each layer
and producing 3D real images using ECVT.

Through laboratory experiment, DAS will capture
the real time images using MATLAB software.
Schematic diagram of tilted flume apparatus using
ECVT system and sizes is shown in Fig 1 (a) and (b)respectively.

As mentioned earlier, rainfall – induced soil slope
failure mechanism were complex and obtaining
related parameters and images in this area currently
were using previous laboratory studies and prediction
were attained from software.

Simulated rainfall

Therefore, the objective of this study is to capture
3 dimension real-time imaging along the experiment,
and the capacitance data is then converted to evaluate
volumetric water content for soil slope sample. Other
than that the effect of rainfall intensity and duration
to the image developed by ECVT and volumetricmoisture content is also captured during infiltration
process.

ECVT sensors

TiltedFlume

MATERIALS AND METHOD
Samples for the purpose of experiment wereobtained from a sites (Cadet Mess) around NDUM
campus. These two sites experienced soil slope
failure during monsoon season as high intensity andlong duration of rainfall.
Data Acquisition
Systemfor ECVT

Water tank

Basic Soil Properties

Effluent
system(a)

Basic soil properties were obtained fromlaboratory for moisture content, porosity, bulk
density and soil classification.

Experiment Set Up
The experiments were conducted in the laboratory
using flume apparatus and other apparatus wereattached such as water supply system, tilted flumewith ECVT sensors and water effluent system.
(b)

Water Supply system

Figure 1: Schematic diagram of (a) tilted flume
apparatus using ECVT system (b) sensors and sizes.

Water pump to simulate rainfall were used in thisexperiment. Water flow regulator to simulate rainfall
is manufactured by Cole-Parmer, model 07554-80
Masterflex L/S economy with variable-speed console
and the speed are varies from 1 to 10.

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Experiment Schedule

RESULT AND DISCUSSION

Rainfall infiltration tests were conducted withintensity of 50/240 mL/s flow rate, and duration for
30 and 60 minutes for all three samples. Schedule ofexperiments is shown in Table 1.

ECVT 3 D Images
3 D real time images for all samples were obtained
as in Table 3. Selection of images were done throughobservation to present the significant changes to theimages.

Table 1: Experiments schedule
Soil
SampleExperiment
no

CADET
MESS

Calibration(Air)
Calibration(Soil)
1
2

Rainfallduration(second)

The result for the real time images shows thedetection of rainfall infiltration into the soil but there
are many images need to be selected in order to show
the changes.

Dryingduration(second)
300

In this experiment, there are 1800 and 5400
images for experiment 1 and 2 respectively. It is notedthat x frame in this experiment refers to real time
images at the x second.

300
1800
5400

1800
5400

Results shown in Table 3 shows the 3 D Imagesof sample for axis XY, YZ and XZ for slices of 1, 9,
17, and 25, at frame 1, 1000, 3000, and 5000. Eachframe has 32 slice images (for 32 channel sensors).
Images shows the variation of color indication for
permittivity from dark blue (lowest permittivity
value), light blue, yellow, orange to red (highest
permittivity value).

Images Reconstruction
In this research, 3 D real time images wereobtained through images reconstruction after
experiments were done using MATLAB software.
The different script to run the software were used andall saved file will be retrieved and went through theprocess.

The results shows that water infiltration is clearly
indicated though the images but only small variation
shown. This is believed due to the lower intensity andshort duration rainfall applied during the experiment.

Permittivity and Volumetric Moisture Content
Permittivity and Volumetric Moisture Content(ECVT)

Other than real time images, permittivity andvolumetric water content were also obtained in thisstudy. Permittivity data were retrieved from the dataand converted to determine volumetric water content
proposed by [7]. It is noted that the relative
permittivity for air, water, residual soil, and saturated
soil are 1, 80, 2-4, and 23-28 respectively. The
equation is as follows:

After images were obtained, the permittivity data
were retrieved and converted to volumetric watercontent. Sample of average permittivity data andvolumetric moisture content is shown in Figure 2 (a)and (b) for the frame of 5000 respectively.
The result of permittivity in Figure 2(a) indicatedthat the average volumetric moisture content of all
frames during the experiment. The changes andincreasing of permittivity during shows that theincreasing of moisture content throughout theexperiment.

Normalized permittivity,
𝜺𝑵 =𝜺−𝜺𝒓𝒆𝒔(1)𝜺𝒔𝒂𝒕 − 𝜺𝒓𝒆𝒔

Volumetric water content,𝜽 = 𝜼(

𝜺−𝝐𝒓𝒆𝒔𝜺𝒔𝒂𝒕 − 𝜺𝒓𝒆𝒔)

This result are shown by a sample value shown in
the Figure 2(b) which all 32 slices. The successful ofusing equation by [7] is observed for this experiment.

𝟎.𝟓

(2)

where 𝜺𝑵 , 𝜺, 𝜺𝒓𝒆𝒔 , 𝐚𝐧𝐝 𝜺𝒔𝒂𝒕 are normalized, relative,residual, saturated permittivity respectively, and 𝜼 isthe porosity.

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Frame

1

1000

3000

5000

XY
AXIS

(b)
YZ
AXIS

Figure 2: (a) Graph of average permittivity valueand (b) average moisture content for each slice forframe 500.

CONCLUSION
This research study is regarding the using of
ECVT system to detect rainfall infiltration into soil
slope. Through previous studies in geotechnicalengineering field, moisture content can be obtained
through this system but only small scale experiments
were done. This experiment using indicated rainfall
intensity and duration of wetting (rainfall) and drying(after rainfall) clearly shown the images of rainfall
infiltration. Result of permittivity values also shown
the changes of volumetric moisture content andproved that ECVT is appropriate to use to observed
and study in soil slope rainfall infiltration. On theother hand, the small variation and changes in the 3D
images indicate that the rainfall intensity may be too
small. Therefore the author would like to suggest
further experiments with higher rainfall intensity andlonger rainfall duration for future.

XZ
AXIS

Table 3: 3 D Images of sample for axis XY, YZ
and XZ for slices (a) 1 (b) 9 (c) 17 and (d) 25.

ACKNOWLEDGEMENTS

Permittivity value

The authors would like to express theirappreciation to the financial supports provided by
National Defense University of Malaysia throughRACE/F3/TK3/UPNM/10.

REFERENCES(a)[1] B. B.K, Ali F. H and Low T.H, "Water
Infiltration Characteristics of Unsaturated Soil
Slope and its Effect on Suction and Stability,"
Geotechnical amd Geological Engineering, vol.
24, 2006,pp. 1293-1306.
[2] Gofar N, Lee L. M, and Kassim A, "Instrumented
Soil Column Model for Rainfall Infiltration
Study," presented at the GEOTROPIKA 2008.

Frame

217

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[3] Lee L. M, Kassim A, and Gofar N, "Performanceof Two Instrumented Laboratory Models for the
Study of Rainfall Infiltration into Unsaturated
Soils", Engineering Geology, vol. 117, 2011, pp.
78-89.
[4] Marashdeh Q, Fan L.S, Du B, and Warsito W,"Electrical Capacitance Tomography - A
Perspective," Ind. Eng.Chem. Res., vol. 47,
2008, pp. 3708-3719.
[5] Mukhlisin M, Kosugi K, Satofuka Y, andMizuyama T,"Effects of Soil Porosity on Slope
Stability and Debris Flow Runout at a Weathered
Granitic Hillslope",Vadose Zone J, Vol 5,
2006,pp. 283-295.
[6] Mukhlisin, M., and Taha, M.R.,"Numerical
Model of Antecedent Rainfall Effect on Slope
Stability at a Hillslope of Weathered Granitic
Soil Formation", Journal Geological Society ofIndia, Vol 79, 2009, pp.525-531.

[7] Mukhlisin M, Saputra A, El-Shafie A, and Taha
M. R, "Measurement of Dynamic Soil Water
Content Based on Electrochemical Capacitance
Tomography," Int. J. Electrochem. Sci., vol. 7,
2012,pp.5457-5466.
[8] Rahardjo H, Ong T.H, Rezaur R. B, Leong E.C,
and Fredlund D.G, "Response Parameters for
Characterization of Infiltration," Environment
Earth Science, vol. 60, 2010,pp. 1369-1380.
[9] Van Genuchten M.TH,"A Closed-form Equation
for Predicting the Hydraulic Conductivity of
Unsaturated Soils", Soil Sci. Soc. Am. Journal,
vol.44 (5), 1980, pp. 892-898.
[10] Warsito W and Fan L.S, "Dynamics of spiralbubble plume motion in the entrance region of
bubble columns and three-phase fluidized beds
using 3D ECT", Chemical Engineering Science,
vol. 60, 2005,pp.6073-6084.
[11] Warsito W, Marashdeh Q, and Fan L-S,
"Electrical Capacitance Volume Tomography",IEEE Sensors Journal, vol. 7, 2007,pp.525-535.
[12] Willians R. A and Beck M. S., 'Introduction toprocess tomography', Process Tomography:
Principles, Techniques and Applications., 1 ed.:Butterworth-Heinemann, 1995,pp.3-10.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

STEREO ECHO CANCELLATION USING ADAPTIVE NON-LINEARNETWORK FILTER FOR HOME THEATRE ROOM
Sunisa Kunarak
Department of Electrical Engineering, Srinakharinwirot University, Nakhonnayok, Thailand 26120
Email: sunisaku@g.swu.ac.th
ABSTRACTThe Stereo Echo Cancellation (SEC) is a necessary process for reducing undesired noise in order that theaudiences can receive the apparent sound signal. In this paper, we use the Adaptive Non-Linear Network Filter(ANNF) that is an algorithm based on Radial Basis Function Neural Networks (RBFNNs) in order to get rid theunwanted sound signal. The fully ANNF is used to model the room transfer function with the proper activation
function as the Gaussian structure. We obtain the samples of the echo sound in home theater room and apply it as
the input to the adaptive non-linear network filter. Furthermore, this method is implemented in MATLAB program.
To ensure the clarity sound, the simulation results show that our proposed algorithm provided outperform theprevious works as Adaptive Filter with Gain and Time-shift, Wiener Adaptive Filter and Feedforward Network interm of the Echo Return Loss Enhancement (ERLE) and Mean Square Error (MSE), respectively. We observe thatthe proposed approach can improve the ERLE around 10 dB and can reduce the MSE less than 0.001.
Keywords: Adaptive Non-Linear Network Filter, Echo Return Loss Enhancement, Mean Square Error, Radial
Basis Function Neural Networks, Stereo Echo Cancellation
This paper is organized as follows: the adaptive
radial-basis function neural network filter issummarized in the next section. After that, the stereo
echo cancellation using adaptive non-linear network
filter is explained. Next, the simulation environmentand simulation results is presented. The conclusion is
finally given in the last section.

INTRODUCTION
The echo is a phenomenon that is delayed anddistorted of the original signal which is reflected backto the source as the voice signals. Stereo Echo
Cancellation (SEC) is a common approach inremoving the echo and noise path. The normalized
least mean square (NLMS) algorithm is the mostpopular method since this one is a simple structure
and lower computational time complexity. However,the performance of this algorithm is essentiallydeteriorated for correlated input speech signals [1-2].
To overcome in echo cancellation, the affine
projection algorithm (APA) that reuses the input
vector to accelerate the convergence speed in [3].
Unfortunately, the performance of this method isdepend on the step size i.e. if the step size is small,the approach can get a smaller misalignment but hasa slower convergence speed. In the other hand, when
the step size is large, the algorithm can achieve afaster convergence but has a bigger misalignment.
Additionally, the frequency-domain adaptive
filter [4-5] can reduce the distinction between the
expected and actual output filter is also known aserror signal but this method is not suitable for nonstatistical information situation due to unpredictableenvironments. To enhance the performance, we
propose the adaptive non-linear network filter that isbased on radial-basis function neural networks. This
proposed algorithm can control the tendency of meansquare error (MSE) and echo return loss enhancement(ERLE).

ADAPTIVE RADIAL
NETWORK FILTERBASIS

FUNCTION

In this section, the radial-basis function neuralnetworks (RBFNNs) is utilized the stereo echo
cancellation (SEC) process as explained in Fig. 1.
This approach is suitable for abundant non-linear
sound signal. The three layers as input layer, hidden
layer and output layer are gathered in the basic
structure [6]. The speech voice that is direct sound, issampled about 4,096 samples as the input nodes, thenon-linear Gaussian are the transfer function in thehidden layer to connect them to all of the input nodes.
Finally, the output layer consists of one node that is
obtained by a linearly weighted sum of the outputs of
the hidden units that are updated in the training
procedure. The output of this network is the error thatis minimized less than 0.001.
In order to adjust minimized the error, the network
will find the optimal weight, w  w1, w2 ,..., wN T islearned as the following steps [7].
1. Set the initial value of center  ji in the hidden

 

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layer for the i th input node and the j th hidden node

 

x1

and the value of span  j in the j th hidden node,x2

respectively. Also, the initial weight vector which is
distributed uniformly between 0 and 1.
2. Calculate the output of hidden layer as:

w1

w0  b

wN1



wN

   2z  exp  x   ji / 2 2j 



xi 1

(1)

xi

where x  x1 , x2 ,..., xi 1 , x5000 T represents the
input vector.
3. Calculate the output of output layer as:M

yk   wkj z j , k  1; M  10

Fig. 1STEREO ECHO CANCELLATION USING
ADAPTIVE
NON-LINEARNETWORKFILTER

(2)

j 0

4.

When the user speaks into a microphone is called
the direct sound, the surroundings noise as a door,
walls, furniture and so on in the room is added to the
speech signal, and the resultant signal heard byaudience would be of low quality. So, we would liketo obtain a signal that contains the clarity speech
voice, but not the surroundings noise. We can do thisan adaptive non-linear network filter if we get asample of the surroundings noise and apply it as the
input to the adaptive non-linear network.
Here we adaptively train the non-linear network
filter to predict the combined speech voice andenvironment signal as m from a surroundings noise
as n . Notice that the surroundings signal does not tell
the adaptive non-linear network filter anything about
the speech signal contained in m . However, thedirect sound signal does give the adaptive non-linear
network filter information which it can use to predict
the surrounding’s contribution to the speech voice
and environment signal as illustrated in Fig. 2.
The network will do its the best to adaptively
output m . In this case, the network can only predict
the surroundings interference noise in the speech
voice and environment signal. The network error eis equal to m , that means the speech voice andsurroundings signal will be minus the predictedcontaminating surrounding noise signal. Thus, thenetwork error contains only the speech voice. Finally,
the adaptive non-linear network filter adaptively
learns to cancel the surroundings noise.

Calculate the error of this network:ek  d k  yk

(3)

where d k is the desired output.
5. Update the weight as:wkj (n  1)  wkj (n)   w (ek ) z j(4)

where  w is the learning rate of weight.
6. Update the center momentum with the learning
rate of center as: ji (n  1)   j (n)   
7.

zj

j

( xi   ji ) e k wkj(5)

Update the span with the learning rate of span  as:

 j (n  1)   j (n)    z j2j

ln z j  e k wkj

Adaptive radial-basis function structure.

(6)

In our implementation, the training process use
1000 samples of sound and 300 samples are used totest the network. The mean square errors of actual
output and desired output are calculated in eachsimulating epoch.

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Simulation Results

Fig. 2In the simulation results, we observe that the
Adaptive Non-Linear Network Filter (ANNF) which
is a proposed method outperforms the otheralgorithms as the Wiener Adaptive Filter (Wiener)[8], Feedforward Network (FF) [9] and Adaptive
Filter with Gain and Time-shift (AFGT) [11] in Mean
Square Error (MSE) value as illustrated in Figs. 4-7.
Figure 4 shows the speech voice or original signal(top), noise signal (middle) and restored signal(button) of the proposed approach that is nearly the
speech voice. Also, it has a MSE equal to 1.7496 
10-6 which is less than the Adaptive Filter with Gain
and Time-shift, Feedforward and Wiener methods
because the proposed approach is suitable in nonstationary systems and numerous non-linear signal
while the Adaptive Filter with Gain and Time-shift isrelatively stable systems as displayed in Fig. 5. The
Feedforward network is a one type of neural networks
but this algorithm is improper to distinguish the nonlinear sound signal as illustrated in Fig. 6. Finally, theWiener Adaptive Filter depends on the window sizethat is disadvantage of this one as shown in Fig. 7.
Accordingly, the coverage echo return loss
enhancement (ERLE) of the ANNF algorithm isincreased around 10 dB with comparing the othermethods as the adaptive filter with gain and timeshift, feedforward network and Wiener adaptive
filter. Furthermore, the proposed algorithm is not
limited in high power i.e. the ERLE augments despite
the high power owing that it has a recursive structure
while the ERLE of the other algorithms are dropped
at larger than 0.1 watt as depicted in Fig. 8.

Echo cancellation using ANNF process.

SIMULATIONIn this section is explained into 2 sub-section as
the simulation environment and simulation results,
respectively.
Simulation Environment

Amplitude

Amplitude

The main disadvantages of the home theatre arereverberation and echo signal. In order to solve thisproblem, we propose an efficient methodology for get
rid the echo signal. In this paper, the fundamental
home theatre room feature has a width  length height size is equal to 10 meter  16 meter  5
meter and compose 5 loudspeakers and 1 sub-woofer(SW) that is called 5.1. The position of loudspeakers
are fixed in the center (C) of the audience and under
the television, the front loudspeakers in the left handside (FL) is angle 30 degree and the right hand side(FR) is angle 20 degree and finally, surround in theleft hand side (SL) and surround in the right hand side(SR) are arranged in the audience’s axis as shown in
Fig. 3. The sound signal that is generated 30 seconds
of music, is sampled 4,096 points for each input
pattern with 16 kHz sampling frequency and stored tomemory for off-line processing [10].

FR
Amplitude

FL

C

SW

Fig. 4 Restored signal by adaptive non-linear
network filter.
SL

Fig. 3SR

Home theatre room characteristic.

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Speech Voice

5

40

0
-5

35
0

500

1000

1500

2000

2500

3000

3500

4000

4500

30

Samples
Noise Signal

2

25

0
-2

20
0

500

1000

1500

2000

2500

3000

3500

4000

4500

15

Samples
Restored Signal-AFGT

1010
mse = 5.6956e-06

0
-10

ANNF
AFGT
FF
Wiener

5
0

500

1000

1500

2000

2500

3000

3500

4000

4500

0
10 -5

Samples

10 -4

10 -3

10 -2

10 -1

10 0

10 1

Loudspeaker Power (w)Fig. 5 Restored signal by adaptive filter with gain
and time-shift.

Fig. 8Speech Voice5

Coverage ERLE versus loudspeaker power.

REFERENCES

0
-5

0

500

1000

1500

2000

2500

3000

3500

4000

4500

3000

3500

4000

4500

[1] H. H. Qin and L. Zhang, “Adaptive feedback
cancellation based on variable step-size affine
projection for hearing aids”, The Journal of
China
Universities
of
Posts
and
Telecommunications, Vol. 22, Feb. 2015, pp. 610.
[2] F. Strasser, “Adaptive feedback cancellation forrealistic hearing aid applications”, IEEE/ACM
Transactions on Audio, Speech and Language
Processing, Vol. 23, Dec. 2015, pp. 2322-2333.
[3] M. Zhu and L. Zhang, “APA with Evolving
Order and Variable Step-size for Echo
Cancellation”, IEEE Advanced Information
Management, Communicates, Electronic andAutomation Control Conference, 2016, pp. 841844.
[4] N. Praveen, S. Ranjitha and H. N. Suresh, “Afrequency-domain adaptive filter (FDAF)
prediction error method and ARLS for speechecho cancellation”, 2nd International Conference
on Applied and Theoretical Computing andCommunication Technology, 2016, pp. 182-187.
[5] S. Wu, X. Qiu and M.Wu, “Stereo acoustic echo
cancellation
employingfrequency-domain
preprocessing and adaptive filter”, IEEE
Transactions on Speech and Audio Processing,Vol. 19, Jun. 2011, pp. 614–623.
[6] S. Haykin, Neural Networks and Learning
Machines. New York: Prentice Hall, 2008,
pp.68-73.
[7] S. Kunarak, “Vertical Handover Decision basedon RBF Approach for Ubiquitous Wireless
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Platform Technology and Service, 2016, pp. 1-4.
[8] I. J. Dahanayaka, P. K. Y. N. Kulasekara, M. N.
F. Zihra and S. H. G. Chamindu, “Acoustic Echo
Cancellation for Hands-free Applications using
Adaptive Filters”, Annual Technical Conference2010 of IET-YP Sri Lanka, 2010, pp. 1-4.

Samples
Noise Signal

2
0
-2

0

500

1000

1500

2000

2500

Samples
Restored Signal-FF10mse = 6.6297e-06

0
-10

0

500

1000

1500

2000

2500

3000

3500

4000

4500

SamplesFig. 6

Restored signal by feedforward network.
Speech Voice

5
0
-5

0

500

1000

1500

2000

2500

3000

3500

4000

4500

3000

3500

4000

4500

Samples
Noise Signal

2
0
-2

0

500

1000

1500

2000

2500

Samples
Restored Signal-Wiener

20

mse = 2.0221e-05

0
-20

0

500

1000

1500

2000

2500

3000

3500

4000

4500

SamplesFig. 7

Restored signal by Wiener adaptive filter.

CONCLUSION
We proposed the Adaptive Non-Linear Network
Filter (ANNF) that is an algorithm based on Radial
Basis Function Neural Networks (RBFNNs) for hometheatre room in 5.1 characteristic. The simulation
results indicate the proposed algorithm that increases
efficiency compared with the other three approaches
in increasing the coverage echo return loss
enhancement. Also, this algorithm can decrease themean square error, respectively.

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Electronics, Control, Measurement, Signals andtheir Application to Mechatronics, 2017, pp. 1-6.
[11] Z. Zhang and Z. Wu, “An Adaptive Filter with
Gain and Time-Shift Parameters for Echo
Cancellation”, 10th International Symposium on
Chinese Spoken Language Processing, 2016, pp.
1-5.

[9] A. N. Birkett and R. A. Goubran, “Acoustic Echo
Cancellation for Hands-free Telephony using
Neural Networks”, Proceedings of the IEEE
Workshop Neural Networks for Signal
Processing, 2002, pp. 1-11.
[10] M. Müller, J. Janský, M. Boháč and Z.
Koldovský, “Linear Acoustic Echo Cancellation
using Deep Neural Networks and Convex
ReconstructionofIncomplete
Transfer
Function”, IEEE International Workshop of223

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

FINITE ELEMENT ANALYSIS OF EWECS COLUMNS WITH
VARYING SHEAR SPAN RATIO
1

Fauzan1, Ruddy Kurniawan2 and Zev Al Jauhari3
Department of Civil Engineering, Andalas University, Indonesia

ABSTRACTA new hybrid structural column system called Enginering Wood Encased Concrete-Steel (EWECS) was
developed for low and high to sesimic zones. Experimental studies on seismic behavior of EWECS composite
columns with varying shear span to depth ratio (shear-span ratio) have been conducted by one of the authors. To
complement and validate the experimental program, finite element analysis (FEA) on EWECS Columns withvarying shear span ratio ranging 1.0 to 2.0 under constant axial load and lateral load are summarized. This
numerical analysis was used finite element program, ANSYS APDL v.14, to investigate the structural
performance of the EWECS columns, which was compared with experimental results. A detailed threedimensional (3D) non linier FE model of three composite columns were performed. The FEA results showed thatthe shear span ratio was affect to the maximum shear strength and failure mode of the EWECS columns. The
maximum strength of the columns increased with decreasing shear-span ratio. The stress distribution on the FEmodels representing the failure mode of the EWECS column specimens well. More damages on the columns
were observed with decreasing shear-span ratio. Generally, the numerical results was able to accurately simulate
the behaviour of the EWECS composite columns on experimental study.
Keywords: Column, Composite Structure, Finite Element Analysis, ANSYS, and Seismic Performance(TUT), Japan to obtain the effects of shear span todepth ratio on the seismic behavior of EWECS
columns [4]. The results shows that the maximum
flexural strength of the columns increased withdecreasing shear-span ratio. However, moredamages on the columns were observed withdecreasing shear-span ratio.

INTRODUCTION
It has been known that the composite steelconcrete columns such as Steel Reinforced Concrete(SRC) and Concrete Filled Tube (CFT) columns
have been widely used in high-rise and long-spanbuildings. Based on the ideologies of SRC and CFT
composite columns, a new hybrid structural column
system called Engineering Wood Encased ConcreteSteel (EWECS) was developed for low and high toseismic zones [1]. This new composite material
overcomes the limitation of the number of stories
that can be constructed by utilizing wood as amaterial on its own. This column consists ofconcrete encased steel (CES) core wrapped with an
exterior wood panel [2], as shown in Figure 1.
Some benefits of using wood panel as column
cover in EWECS column include the improved
structural behavior through its action to provide coreconfinement and resistance to bending moment,
shear force and column buckling, enviromentallyfriendly, and save time during construction.
Therefore, EWECS column is possible to apply toactual structures as an alternative to SRC
columns, which have weaknesses due to difficulty inconstructing [3].
An experimental study on EWECS columns withvarying shear span to depth ratio ranging from 1.0 to
2.0 under constant axial load and lateral load
reversals was conducted by Fauzan et al. in the
Laboratories of Toyohashi University of Technology

Fig. 1 Specimen Detail of EWECS Column
To complement and validate the experimental
program, a 3D finite element (FE) model of EWECS
composite columns with varying shear span ratio
subjected to axial and lateral cyclic loads using
ANSYS APDL 14.0 software was developed [5].
This software has proven its reliability in many
benchmark studies and was considered suitable forthe current task. The developed model takes into
consideration the nonlinear behavior of material.
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The results of the FEA were compared with theexperimental test results. In this paper, the shear
span to depth ratio hereafter referred to as “shearspan ratio”.

wood panels were modeled as block and solid cubewith an equivalent length representing the total areaof specimen.
Two types of elements are used in the modelingof steel H-section, concrete, and wood panel.
ANSYS solid element, SOLID185 is used tomodelling the steel section and wood panel, while
SOLID65 is used to modelling the concrete of the
EWECS column. The SOLID185 and SOLID65
elements are a 3D hexahedral element defined byeight nodes as shown in Figure 4. The elements havethree translational degrees of freedom at each nodein the nodal x, y, and z directions. The FE model inthis study is considered perfectly-bonded for eachmaterial interfaces (steel-concrete and woodconcrete) in adjacent contact. This assumption isapplied because based on the experimental results,
the effect of slips and separations in each material
are not much influence [6], so the interface
modelling on the FE model is not performed.

THE GEOMETRY AND ELEMENT TYPE OF
3D FE MODEL
A total of three composite column models withvarying shear-span ratios were performed in 3D FE
model. The column cross-section was constant at
400 mm square section for all specimens anddifferent shear-span ratios (1.0, 1.5 and 2.0) wereachieved by varying the column height (800 mm,
1200 mm and 1600 mm). Details and named of the
3D FE models in terms of geometry of steel section,
concrete, and wood panel are generated anddescribed in Figures 2 and 3.

Fig. 2 The 3D FE Model of EWECS Column
Fig. 4

Solid65 and Solid185 ANSYS Elements

MATERIAL PROPERTIES, MESHING, LOAD,
AND BOUNDARY CONDITIONS
Material Properties
Concrete

WC1

WC2

The compressive strength of concrete used inboth specimens was 35 MPa. A peak concrete strainof 0.0025 was used in the analysis [7]. Figure 5
presents the tensile stress–strain curve used for theconcrete. The stress-strain relationship in the risingregion was designed on the model developed by
Saenz [8], which was built in the program. In thesoftening region, the linearly decreasing model was
adopted. The tensile relaxation (softening) waspresented by a sudden reduction of the tensile
strength to 0.6fr upon reaching the tensile cracking
strain εcr. After this point, the tensile response
decreases linearly to zero stress at a strain of 6ε cr asshown in Figure 6.
Additional concrete material data, such as theshear transfer coefficient βt for open cracks and βc
for closed cracks are also needed for the concrete
constitutive material data table. The shear transfer
coefficients βt and βc control the amount of shear

WC3

Fig. 3 Full Models of EWECS Column with Varying
Shear Span Ratio
The steel encased in each column had a single Hsection steel of 300 x 220 x 10 x 15 mm. The FEmodels are developed to accurately represent thegeometrical configuration and dimensions of the test
specimen. The full model EWECS composite
columns with varying shear span ratio are modeled
as illustrated in Figure 3. The concrete, steel, and225

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017transfer across the cracks. Typical shear transfer
coefficients range from 0.0 to 1.0, with 0.0
representing a smooth crack (complete loss of shear
transfer) and 1.0 representing a rough crack (no lossof shear transfer). A shear transfer model developedby Al-Mahaidi [9] was included in the analysis, withvalue of 0.75 and 0.9 was used in the FE model forβt and βc, respectively. The fracture criterion of
concrete was applied with the adoption of the fiveparameter model of William-Warnke [10].

modifications [7]. Stress-strain relationship in therising region was modeled with the linearly
increasing model. The fracture criterion of wood
was adopted following the rule of the five parametermodel of William-Warnke [10] for concrete with the
input of wood material characteristic. The maximum
tensile strength of the wood panel during theanalysis was taken as 5 MPa. This value took into
consideration the lower tensile strength in the
direction perpendicular to the grain. The shear
transfer model for concrete developed by Almahaidi [9] was included with the use of modified
shear transfer coefficient βc of 0.35 for wood.

Fig. 5 Compressive stress-strain curve for concreteFig. 7 Tensile stress-strain curve for steel

Fig. 6 Tensile stress-strain curve for concrete [11]Steel Section
The yield strength of steel used in each models
are 293.6 and 313.3 MPa for flange and web steel,respectively. The constitutive model of the steel
used in this study is a perfectly elastic-plasriccriterion. At first, this curve is elastic, then it
assumed to be perfectly plastic (bilinear isotropic
model), as shown in Figure 7. This curve is suitable
for representing stress-strain characteristics ofnormal and high quality steel section.

Fig. 8 Tensile stress-strain curve for wood
Meshing
The mesh density was chosen so that theelements aspect ratio is nearly equal to one. This
provided adequate accuracy and fair computationaltime in modelling the steel columns. The total
numbers of element used is 5095 elements. This isan adequate refinement for the constructed 3D FE
model.

Wood Panel
The compressive strength and modulus elasticity
of wood are 46.2 MPa and 11200 MPa, respectively.
The constitutive model of engineering wood panel isshown in Figure 8. Owing to the design to allow theforce to be applied in the direction parallel to theannual growth ring of the wood, some existing
concrete models built in the program by many
researchers might be used in the analysis with someBoundary Conditions
The boundary conditions in FE models werecorresponding to the experimental setup. An anchor
Plate (700.700.400 mm) was used in the model at
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the top and bottom of the column. Fixed at thebottom of the column and roller supported at the topof the column.
Restrictions ofdisplacements
on y direction

Fig. 10 Lateral Cyclic Load History
RESULT AND DISCUSSIONS
Hysteresis Characteristics
The comparison of shear versus story drift
relationships between all specimens and FE model
are plotted in Figure 11. The blue dotted and redlines drawn in these figures represent the measured
hysteresis loops of the specimens and FE models of
EWECS column, respectively. The yield andmaximum strengths and the corresponding story
drift for each specimen are listed in Table 1. The
yielding of each specimen was assumed when thefirst yielding of steel flange and/or web at the top
and bottom of the columns was observed, while theyielding of FE model was observed when theprincipal strain in the encased steel was reached byaround 0.002, as seen in Figure 12.

Restrictions ofdisplacements on x,y, and z directions
Fig. 9 Boundary Conditions of FE Model
Nodes at the bottom of the column are restrainedin all translational degrees of freedom, and the top of
the column is restrained in the vertical y direction.
The lateral y direction is restrained since the column
prevent any displacement in this direction. The
nodes at the two edge lines of the column arecoupled in the vertical y direction to ensure all thenodes associated with this line move together. The
nodes located at the middle face of the column along
the direction of the applied displacement are coupledin the horizontal x direction. It should be noted thatthe boundary conditions were the same for all
loading cycles. The final boundary conditions of FE
model is shown in Figure 9.
Loads
The loading in the study was applied as follows:
Constant axial load, approximately 1031 kN was
applied to the top face column. This is represented in
the FE model by applying a point pressure of 1.4 kN
on the upper elements (steel plate) of a total nodal
area of 717. The loading history for the model isbased on story drift and is the one recommended foruse in the experimental study [4]. This is represented
in the FE model by applying the displacement incycles of loading and unloading at the top edge ofthe column. The incremental loading cycles were
controlled by story drift, R, defined as the ratio of
lateral displacements to the column height, /h. The
lateral load sequence consisted of one cycle to eachstory drift, R of 0.5, 1, 1.5, 2, 3 and 4% followed byhalf cycle to R of 5%, as shown in Figure 10.

(a) EWECS Column with SSR = 2(b) EWECS Column with SSR = 1.5

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specimen have a little strength degradation after
attaining the maximum capacity of 771.9 kN at R of
3%. This was approximately 6.8% higher than the
results obtained from the experiment. Good
correlation exists in all stages of lateral cycling
loading. The FE and experimental results are almost
the same in the each stages of cyclic loading, and the
FE results are greater than those of the experimental
results (within 8.4%) in the each stage of loading
cycles. The maximum capacity of Model WC2 washigher than that of Model WC1.
(c) EWECS Column with SSR = 1
Fig. 11 Comparison of Hysteresis Loop between
Experimental and Numerical Results
Table 1 Comparison of measured strength between
experimental specimens and FE models

Model
WC1
WC2
WC3

Study
Exp.
Num.
Exp.
Num.
Exp.
Num.

At Yielding
Qy
Ry
(kN)
(%)
386
0.5
367
0.55
423.1
0.5
454
0.49
666.2
0.64
613
0.58

Max. Capacity
Qmax Rmax
(kN)
(%)
728
5
772
5
771.9
3
951
5
916
3
1022
5

(a) WC1

In Specimen WC1 with a shear-span ratio of
2.0, the first yielding occurred on steel flange
when the applied load was 386 kN and R of 0.5%, while in the FE model, the first yielding occured
on steel flange at R of 0.55%. From Figure 11 (a), it
can be seen that the specimen and FE models
showed ductile and stable spindle-shaped hysteresis
loops without degradation of load-carrying capacity
until R of 5%. The maximum capacity of thespecimen was reached in the last story drift of 725
kN, while the maximum capacity was 778 kN in the
FE model. This was approximately 6.8% higher than
the results obtained from the experiment. Good
correlation exists in all stages of lateral cycling
loading. The FE and experimental results are almost
the same in the each stages of cyclic loading, and the
FE results are greater than those of the experimental
results (within 5.5%) in the each stage of loading
cycles.
For Specimen WC2 with a shear-span ratio of
1.5, the first yielding also occurred on steel flange atshear force of 423.1 kN and R of 0.5%, while in the
FE model, the first yielding occured on steel flange
at R of 0.49%. From Figure 11 (b), it can be seenthat the FE model showed ductile and stable spindleshaped hysteresis loops without degradation of loadcarrying capacity until last story drift with maximum
capacity of 972 kN, while the hysteresis loop of the(b) WC2(c) WC3
Fig. 12 The principal strain at first yielding of the FEmodelsSpecimen WC3 with the smallest shear-span
ratio showed the highest maximum capacity among
the tested specimens. However, the yielding locationof this specimen was different from the other two
specimens. The first yielding of the specimen
occurred on the steel web at shear force of 666.2 kN
at R of 0.64%, while in the FE model, the firstyielding occured on steel web at R of 0.58%. From
Figure 11 (c), it can be seen that the specimen
showed ductile and stable spindle-shaped hysteresis
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loops, while the FE model showed pinching-shaped
hysteresis loops without degradation of loadcarrying capacity until story drift, R of 5%. The
maximum capacity was reached at shear force of
916 kN and R of 3% in the specimen, while themaximum capacity of FE model was 1022 kN at R
of 5%. The maximum capacity of Model WC3 washigher than that of other models. The FEA results
are greater than those of the experimental results(within 11%) in the each stage of loading cycles.

glue, as seen in Figure 13 (a). Cracks also formed at
the opposite side of the column, propagated along
the column height.
For Specimen and Model WC2, the first cracks
of wood panel occurred at R of 3% in the East sideof the column. In FE model, the cracks occurred on
the wood panel of the column at a shear stress ofapproximately 7.8 MPa, as shown in Figure 13 (b).
Subsequently, the cracks extended along the column
height with the increase of story drift.
In Specimen WC3, the first cracks of wood panel
occurred at R of 2% in the East side of the column,
while in the FE model, first cracks occurred at R of
3% as indicated by the principal shear stress in thewood approximately 7.3 MPa. The cracks extended
along the column height with the increase of story
drift.

Failure Mode

: Crushed in flexure

Shear Failure
Mode

Fig. 13 Comparison of failure mode of wood panel
between experimental and FE result
In Specimen WC1, within a drift ratio of 3 %, thefirst cracks in the wood panel occurred in the Northside of the column face at around 30 cm awayfrom the top of the column. This is also seen on the
FE model, that the cracks on the wood is indicatedby the principal shear stress in the wood was higher
than the tangential shear strength of the woodsuggested by Calderoni et al. [12] was averaged at
7.44 MPa at the location where the wood panel ofthe column were assembled together by using wood

Fig. 14 Comparison of failure mode of concrete
between experimental and FE result
From test results, it was found that the shearspan ratio also greatly affected the observed
cracking patterns of the wood panel at the column
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faces. The cracks extended with increasing story
drift. Finally, the wood panel was split along thecolumn height for all specimens. From the figure, it
can be seen that Specimen WC3 with the smallest
shear-span ratio had the most damages in which thecracks of the wood panel occurred in both East andNorth sides of the column. This indicates that thedamage of wood panel becomes dominant withdecreasing the shear-span ratio.
After the test of experimental, the wood panel
was removed from the columns to visually inspect
the damage. It was observed for all specimens andmodels that the in-filled concrete had crushed in
flexure at both the top and bottom of the column,
and no local buckling occurred at the encased steel.
In addition, shear cracks occurred along the column
height in Specimen WC3 and no shear cracks wasobserved for the other two specimens, as shown in
Figure 14.

[2] Fauzan, Kuramoto, H. and Kim, K-H.,“Seismic Performance of Composite EWECSColumns using Single H-steel,” Proceedingsof JCI, Vol.27, No.2, 2005, pp. 307-312.
[3] Fauzan, and Kuramoto, H., “Experimental
andAnalytical
Studyon
Structural
Performance of Engineering Wood Encased
Concrete-Steel
Composite
Columns,”
Proceedings of the Third International
Conference on ASEM, Seoul, Korea,
September, 2004, pp. 1447-1459.
[4] Fauzan, Kuramoto, H., Matsui, T., and Kim, K.H. (2006). “Seismic behavior of composite
EWECS columns with varying shear-span
ratios.” Proceedings of JCI, 28(2), 1357–1362.
[5] ANSYS Version 14.0, User and Theory
Reference Manual, 2004.
[6] Meas, K., Fauzan, Matsui, T., and Kuramoto, H.
(2006). “Seismic behavior of engineering woodencased concrete-steel composite structural
systems, Part I: Effect of shear studs on
behavior of EWECS columns.” Proc.,
Architectural Institute of Japan, AIC, Tokyo,
1181–1182.
[7] Kuramoto, H., Li, B., Meas, K., and Fauzan.
(2011).
“Experimental
andAnalytical
Performance Evaluation of Engineering Wood
Encased Concrete-Steel Beam-Column Joints”.
Journal of Structural Engineering ASCE, pp.
822-833.
[8] Saenz, L. P. (1964). “Discussion of equation forthe stress-strain curve of concrete.” J. Am.
Concr. Inst., 61(9), 1229–1235.
[9] Al-Mahaidi, R. S. H. (1979). “Nonlinear finite
element analysis of reinforced concrete deep
members.” Rep. No. 79-1, Dept. of StructuralEngineering, Cornell Univ., Ithaca, NY[10] William, K. L., and Warnke, E. P. (1975).
“Constitutive model for the triaxial behavior of
concrete.” Int. Association for Bridge andStructural Engineering, Proc., Vol. 19, IABSE,
Zurich, Switzerland.
[11] Hawileh, R.A. (2010). “Nonlinear finite element
analysis and modeling of a precast hybrid beamcolumn connection subjected to cyclic lads”.
Journal Applied Mathematical Modelling
Sciencedirect 34, pp. 2562-2583.
[12] Calderoni, C., Matteis, G. D., Giubileo, C., andMazolani, F. M. (2006). “Flexural and shear
behavior of ancient wood beams: Experimental
and theoretical evaluation.” J. Struct. Eng.,
28(5), 729–744.

CONCLUSION(1) The FE model proved to be effective in
producing results that were in good agreementwith the experimental results in the elastic andplastic ranges.
(2) The response envelope from the FEA correlated
fairly well with experimental results. Good
correlation exists in all stages of cycling loading.
Specifically, the FE results for the peak loads are
smaller than the experimental results within
6.8%; 8.4%; and 11% in the each stages of cyclicloading for FE models WC1, WC2, and WC3,
respectively.
(3) A smaller shear-span ratio led to a higher shear
force for the composite columns. The ultimate
strength of EWECS columns increased withdecreasing the shear-span ratio.
(4) The stress distribution on the FE models
representing the failure mode of the EWECS
column specimens well. The damage of thecolumns in the wood panel and the CES core
became dominant with decreasing the shear-span
ratio.
REFERENCES[1] Fauzan, Kuramoto, H., Shibayama, Y. andYamamoto, T., “Structural Behavior ofEngineering Wood Encased Concrete-Steel
Composite Columns,” Proceedings of JCI,
Vol.26, No.2, 2004, pp. 295-300.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EXPERIMENTAL INVESTIGATION ON BOX-UP COLD-FORMEDSTEEL COLUMNS IN FIRE
Fadhluhartini Muftah1, Mohd Syahrul Hisyam Mohd Sani2, Ahmad Rasidi Osman3, Shahrin Mohammad4,
Shek Poi Ngian51
Faculty of Civil Engineering, Universiti Teknologi Mara Cawangan Pahang, 26400 Bandar Jengka, Pahang,
Malaysia;
2
Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

ABSTRACT
Cold-formed steel (CFS) is a popular material with various advantages. Its easy production and assembly
give engineer an option to speed the construction process. However, thinness relates to the major issue ofbuckling, especially when dealing with high temperature. The unprotected CFS behaviour under fire is expected
to have a little strength as compared to hot-rolled steel. Information on such behaviour is still limited. Fire
resistance testing on built-up box CFS column was presented in this paper. Two fire resistance tests were carriedout under compression load. The Standard ISO 834 Fire Resistance Test under 50% and 70% degree of
utilisation measured the temperatures at several points of the steel column surface by using surface thermocouple
and axial column deformation. For reference purpose, one same static test at ambient temperature was carried out
to assess the load bearing capacity. Results found that the failure temperature of built-up CFS could reach up to
515ºC and 443ºC within 8 minutes and 7 minutes resistant time for 50% and 70% degree of utilisation,
respectively. Based on deformation analysis, buckling temperature of the column was 448ºC and 394ºC withcritical time of 7 minutes for 50% and 70% degree of utilisation, respectively. This concluded that the higher
degree of utilisation result in lower critical temperatures of the columns.
Keywords: Cold-formed steel, Standard ISO 834 fire, buckling temperature, buckling time

research trend happened because the required
information is on the performance of wall made up
with an embedded CFS wall which may be covered
with a fire retention material. Hence, information onelevated temperature is fairly enough. Moreover, thelocal buckling failure was observed as similarly as
failure mode in ambient temperature [9]. Research
on CFS at high temperature were broadly exploredon the material strength models according to various
parameters, such as thickness and steel grade byusing CFS from different countries. Hence, thestrength of CFS structure was predicted based onthese models. Currently, the EN 1993-1-2: 2005 ismeant for hot-rolled steel material is also practiced
for CFS. The section always considered as Class 4
section. Annex E has stated the reduction factor
material property for Class 4 section. The limiting
temperature stated in National Annex is 350ºC for
all degrees of utilisation.
The ISO 834 fire curve is widely used to test thefire resistance of materials under the category "A"fire hazard, i.e. with the fire hazard rating based on
the burning rate of general combustible building
materials and contents. The study of cold-formed
structural column under fire was conducted by [10]using stainless steel material. A fire design
multiplier of 1.37 was used for design buckling
resistance. It was valid for stainless steel hollow

INTRODUCTION
In the event of fire, much loss was identified,such as people injury, huge damage, loss of life, lossof capital, and production. Data from the MalaysianFire and Rescue Department reported that Malaysia
were facing with 5,248 fire cases in 2011. Housing
was recorded as the highest cases at 2,761 and was
dramatically increased from 2001 to 2007 [1].
Efficient method of construction involving innovatebuilding material is the main considerations to
support modern building design requirement. Hence,
the use of cold-formed steel (CFS) as the main
structure, i.e. column, is broadly significant due toits various advantages. The fire safety information
about this material is still limited and somehow still
unavailable in any practical design guideline.
Usually the technical time is 20 minutes for otherstructure type, but it was unsuitable for the CFS typeof structure. Moreover, CFS failure gives little oreven no warning on unlike wood structure withcracking and moaning sounds [2].
Currently, the design of structure on fire isapplied as fire safety factors that proposed based on
fire testing such as for stainless steel column design
under fire condition. Most CFS related research wasdone under elevated temperature, but not under
direct fire, such as real fire stimulation [3] - [8]. This
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column with utilising the buckling resistance design
equation in EC3–1.2. The research on CFS under
ISO 843 standard fire was conducted by [11]. The
column section was open channel and built-up I (2C).
It was loaded under compression and the heat was
generated from an electric furnace. The exposed
temperature was lower temperature from theStandard ISO 834 fire curve in the early fire state,might result column fail at longer duration. The
results show that the CFS had lower resistant time
and temperature and the exposed temperature wasslightly lower. It has produced a conservative
finding. Research conducted by [12] reported thatthe unprotected restrained column for section factor(F/V) of 424.6 m−1 experienced a temperature
increase very quickly, almost the same as theatmosphere temperature. The buckling temperatureis the temperature at which the axial deformation
reaches a maximum value, while the column failure
temperature is defined as the temperature at which
the axial force in restrained column returns to its
initial value.
Previous studies found very limited informationof CFS column exposed to the Standard ISO 834 fire.
This research evolution trend may be due to thethickness of CFS is thin and may fail due to various
buckling modes which are unsuitable for column
structure. However, adopting the current design
guideline, which is mainly used for hot-rolled steel
and has clearly different production method, thispractice is barely inappropriate. A practical solution
for this issue is by conducting a fire test on CFS
column. The test was conducted in the Construction
Research Centre (CRC) at Universiti Teknologi
Malaysia in Skudai, Johor. The test involved a boxup column. Two columns with different degree of
utilisation were studied. The column was supported
on constant constrain. The objective of this study isto evaluate the temperature rise behaviour of CFS
column when exposed with the Standard ISO 834
fire.

plate was used to place the bottom and top end of thecolumn. It is used to ensure the load was uniformly
distributed over the column cross-section. Column
top was attached in the same manner at the bottom.
Meanwhile, fire test support was improved toprevent support expansion due to fire. All steel-end
plates, angle and steel-based, were coated with 3
mm high temperature coating paint. 20 mm ceramic
fibers, which were covered with steel-based andthermocouple were placed at the bottom of column
to monitor the temperature. Temperature measured
was less than 100°C. The rise of temperature data inthe column was captured by a surface type K
thermocouple. The thermocouple position along thelength of the column and in the column section was
according to BS EN 13381-4:2013 (E)recommendation. Figure 1 shows the of thethermocouples position on the column height and at
the cross-section. Since the column is unrestraint,
the axial deformation was allowed during fire
exposure. The axial deformation of column was also
monitored based on the actuator movement. The
ambient and a series of fire tests were conductedunder the same actuator and loading frame. At
ambient test, the CFS column was loaded until it
failed. During the fire test, the column was loaded
till reach a constant load level for 5 to 10 minutes
before the fire was introduced inside the furnace.
The test was stopped until the load dropped, which
was considered that the column had failed. A
hydraulic jack loading system with maximum loadof 1000 kN were used to load the column withloading rate of 0.25 kN/s.

MATERIALS AND METHODS
A channel with lipped column was supplied by alocal manufacturer in Johor, Malaysia. The channel
size is 200 mm depth, 73 mm width of flanges, 17
mm lipped size, thickness is 1.9 mm, round corner is
2.5 mm and centroid is 20.38 mm from the web. The
column height is 3 m. Each column was constructed
as a built-up section by using two identical lippedchannel sections. Two of the channel sections wereconnected at their flanges by using self-drillingscrews, at 400 mm c-c spacing along the length. It
will form a box-up section with a self-drilling screwin the middle of the flange.
The end column was screwed to the two steel
angles at both column webs. It used to restrain
lateral movement of the column. A circular steel

Fig. 1

Location of thermocouple on the column

ISO 834 standard fire curve and 15% percentage
deviation (de) from a standard fire curve, as shownin Fig. 2(a), was according to BS EN 1363-1:2012(E). The graph also plots the furnace averagetemperature curve for all samples during testing. The
furnace consists of six blowers. 3 blowers located atleft and right side of the furnace, which by location
were at the top side, middle side and bottom side of
the furnace. Furnace fire was produced by a gas
furnace which transfers heat to the CFS throughradiation and convection. Convection will cause the232SEE - USQ, Brisbane, Australia, Nov.13-16, 2017air particles (gases) to spread out and become dense,
causing a movement of gases. Cooler gas is dense
and warmer gas is less dense and thus causes
warmer gases to rise up. Radiation does not require a
medium to transfer heat. The CFS shiny surface ispoor in absorbing radiation heat.
The furnace pressure should be approximately
8.5 Pa per-metre height within ± 5 Pa after 5 minutes
during fire, as recommended in BS EN 1363-1:2012(E). Pressure inside the furnace was presented in Fig.
2 (b), which shows that the furnace pressure during
the fire test was within an acceptable range.

exposure was observed. It was found that the CFS
temperature rise was propositional to the fire
exposure time for all stations. Thermocouples
located at 200 mm from top support and loadingwere known as SpTC1–SpTC3. The rise of
temperature at this location was lower the Standard
ISO 834 fire for all degrees of utilisation until thecolumn failed. The rate of temperature rise of 50%
and 70% degree of utilisation was similar for all thethermocouples except for SpTC6. This may happen
due to uneven fire blow during testing. The rate of
temperature rise was also similar for different
degrees of utilisation. It can be concluded that therate of temperature rise of the BU CFS column wasconstant for CFS and independent to the degree of
utilisation. It was found that rise of temperature at
the bottom was faster as compared to the top. Thismay happen because the heat in the furnace waspressured to the bottom of the furnace and may be
due to some heat losses from the ceramic fibre on
top of the furnace. A technician can feel thetemperature around the outer furnace top. The 70%
load utilisation failed at lower temperatures ascompared to the 50% load utilisation. In addition,
the 70% load utilisation had a lower failure
temperature than Standard ISO 834 fire curve incontrast with the 50% load utilisation, was failed
when approaching the ISO 834 fire curve.
SpTC5, SpTC7, SpTC8, and SpTC9 for 50%
degree of utilisation rose up to the Standard ISO 834
fire curve at failure while for 70% degree of
utilisation, the column failed at lower temperatures.
SpTC7, SpTC8, and SpTC9 were temperatures atthe lower column. SpTC5 was the temperature at 2mfrom the bottom, specifically at the web of the boxup CFS. SpTC4 and SpTC6 were located at theflanges which had double thickness, resulting in alower failure temperature. The greater web thickness
and thermal conductance between the two CFS
profiles have caused these respective behaviours
[11].

800
Temperature (°C)

700
600
500
400

Upper limit
ISO 834
Lower limit
50%BU_3m
70% BU_3m

300
200
100
0
0

2

4
Time (min)68Fig. 2(a) Furnace average temperature during testingfor Box-up column
Furnace pressure (Pa)0

Pressure (Pa)

0

5

10
standardpressure (Pa)Upper limit
pressure (Pa)
Lower limit
pressure (Pa)
50% BU_3m-5-10

70% BU_3m-15Time (min)Fig. 2(b) Furnace pressure
3.00
Column height (m)RESULTS AND DISCUSSION
Compression Strength of CFS Column
The strength test of the column at ambient
temperature results that the ultimate compression
load is 170 kN. The calculation ultimate load
prediction from EC3-1.3 is 162.34 kN. Loading for
50% and 70% degree of utilisation were 85 kN and
119 kN, respectively. It was calculated bases on
normal strength test.

t=0 min
t=1 min
t=2 min
t=4 min
t=5 min
t=6 min
t=7 min
t=8 min

2.50
2.00
1.50
1.00
0.50
0.00

0 100 200 300 400 500 600 700 800 900 1000
Temperature (ºC)(a) 50% BU_3m

Temperature Rise in CFS Column
Nine thermocouples gave reliable results,
whereby the steel temperature rise over time of fire
233

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

To select the appropriate mean temperature forthe column, the minimum, maximum and averagetemperature for each level was plotted. Again, thedifference between all values was small, hence theaverage value was selected. Table 1 shows the mean
temperature for each degree of utilisation.

t=0 min
t=1 min
t=2 min
t=3 min
t=4 min
t=5
t=6 min
t=7 min

2.50
2.00
1.50
1.00
0.50
0.00

0 100 200 300 400 500 600 700 800 900 1000
Temperature (ºC)(b) 70% BU_3m
Fig. 3 Temperature evolution along the length of
Box-up column

50% BU_3m

700
600
500
400
300
200
100
0

Temperature (°C)

Column height (m)3.00

Furnace ISO 834
SpTC1
SpTC2
SpTC3
Average TL1
0

1

2

3

4 5 6
Time (min)

7

8

9

(a)
700
600
500
400
300
200
100
0

Temperature (°C)

Fig. 3 shows the temperature evolution of CFS
column due to different load utilisation. At the
beginning of fire exposure until failure time bothcolumns evolved at a uniform temperature andslightly higher temperature at the bottom. The
evolution of temperature was independent to thedegree of utilisation of the column.

50% BU_3m
Furnace ISO 834
SpTC4
SpTC5
SpTC6
0

1

2

3

4 5 6
Time (min)Mean Temperature

7

8

9

(b)

Temperature (°C)

This section explains the analysis of a mean
temperature for the column. The evaluation of mean
temperature along the column was calculated byusing the weightage area methods in which thetemperatures recorded were multiplied to the area ofcolumn surface and divided by the total area of thecolumn. This method was applied to account for thearea coverage near the thermocouple that
represented the flange and web surface temperature.
Figure 6 and Figure 7 shows the temperature for50% and 70% load utilisation, respectively.
Level T1 for 50% load utilisation recorded asimilar value for all surfaces as in Fig 4(a). Hence,
the average is directly determined by a simple
average. As the lower side of the column was high intemperature at, a difference in temperature atrespective levels was found. The temperature at web
was higher than at the flanges due to the thicker
thickness as in Fig 4 (b) and (c). However, thedifference in temperature was less than 10%, hence
the calculated simple average can be accepted. The
analysis was continued with depth detail on the
average TL for each column. TL3 resulted in ahigher average followed by TL2 and TL1 as in Fig.
4(d). This behaviour was similar for the 70% degreeof utilisation. All columns had the same temperaturerise behaviour where the upper thermocouple
registered a lower temperature until column failure.
This may be caused by the thermocouple locatednearer to the ceramic fibre which supported thecolumn end. The heat was shielded by a ceramic
fibre that restricted the conductance of heat to thisposition.

700
600
500
400
300
200
100
0

50% BU_3m
Furnace ISO 834
SpTC7
SpTC8
SpTC9
Average TL3

0

1

2

3

4 5 6
Time (min)

7

8

9

Temperature (°C)(c)
50% BU_3m

700
600
500
400
300
200
100
0

Average TL3
Average TL1
Average TL2
0

1

2

3

4

5

6

7

8

9

Time (min)Temperature (°C)

(d)
700
600
500
400
300
200
100
0

50% BU_3m
Minimum
Maximum
Average
0

1

2

3

4 5 6
Time (min)

7

8

9

(e)
Fig. 4234

Evaluation of mean temperature along thecolumn for 50% degree of utilisation

Maximum temperature (ºC)

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

Table 1 Mean temperature of the column

0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0

30
121
177
224
285
331
395
448
515

30
110
162
233
287
347
394
444
-

600
500

Failure Time and Failure Temperature
The consideration in fire safety design isconcerned about preventing structural failed before
resistant period. The evaluating of the criticaltemperature steel column is characterised as a
uniform temperature all over the column surface.
The critical temperature was determined byevaluating the results of the maximum temperature
gain from the experiment, the highest values of theaverage temperature for each thermocouple level,
and the highest value from the mean temperature.
Figure 5 plots the temperature values against degrees
of utilisation. Furthermore, the safe temperature
value in selecting the critical limiting temperature,
the smallest value was considered. As expected, theresistant time was decreased as the degree of
utilisation was increased. Then, both the initial andaverage heating rates were calculated by using thetemperature at the first 1 minute, meanwhile thevalue of the average heating rate was according to
the temperature and time of the column at failure.
The load applied on the column does not affect theheating rate of the column and this was also reportedby [11]. The heating rate of 60ºC/min was constantfor all box-up columns. The initial heating rate of
84ºC/min is higher at for the column due to rate ofStandard ISO 834 was higher at 329ºC/m at the first
1 minute. The critical temperature for box-up
column was 515.95ºC and 443.77ºC and the criticaltime was 8 and 7 minutes for 50% and 70% degreeof utilisation, respectively. The degree of utilisation
was increased results in decreasing of criticaltemperature and time.

max TCmax level400

max avg
300
0Fig. 5

Axial deformation (mm)Time

Degree of utilisation (%)
50
70

700

16
14
12
10
8
6
4
2
0
-2 0
-4
-6
-8
-10
-12
-14
-16

10

20 30 40 50 60
Degree of utilisation (%)

70

80

Evaluation of critical temperature

100

200

300

400

500

600

700

50% BU
70% BU

Temperature (°C)

Fig. 6

Variation of axial deformation over the
box-up CFS column means temperature.

The axial deformation of the column was
analysed against the mean temperature rise of thecolumn and the results were presented in Fig. 6. The
column had an initial deformation due to load levelapplication of 50% and 70% load utilisation. The
axial deformation was accounted after the column
was fired. According to the buckling temperaturedefinition given by [12], the buckling temperature isconsidered at the maximum axial deformation of thecolumn. It was found that the buckling temperaturesof the column were 448ºC and 394ºC, with criticaltime of 7 minutes for 50% and 70% degree of
utilisation, respectively. This concluded that thehigher degree of utilisation resulted in lower
buckling temperatures of the columns. Both values,
critical temperature and buckling temperature,would be significant in predicting future CFS fire
resistance design. Figure 7 shows the testing
configuration and buckling failure of the CFS
column under Standard ISO 834 fire exposure.

235

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017(a)[3] Chen J and Young B, “Cold-formed steel lippedchannel columns at elevated temperatures”,
Engineering Structures, Vol. 29(10), 2007, pp.
2445–2456.
[4] Feng M, Wang Y and Davies J, “Structural
behaviour of cold-formed thin-walled short steel
channel columns at elevated temperatures. Part 1:
experiments”, Thin-Walled Structures, Vol. 41(6),2003a, pp. 543–570.
[5] Feng M, Wang Y, and Davies J, “Structural
behaviour of cold-formed thin-walled short steel
channel columns at elevated temperatures. Part 2:
Design calculations and numerical analysis”, ThinWalled Structures, Vol. 41(6), 2003b, pp. 571–594.
[6] Feng M, Wang YC and Davies JM, “Axial
strength of cold-formed thin-walled steel channels
under non-uniform temperatures in fire”, Fire
Safety Journal, Vol. 38(8), 2003c, pp. 679–707.
[7] Kaitila O, “Imperfection sensitivity analysis oflipped channel columns at high temperatures”,
Journal of Constructional Steel Research, Vol.
58(3), 2002, pp. 333–351.
[8] Ranawaka T and Mahendran M, “Distortional
buckling tests of cold-formed steel compression
members at elevated temperatures”, Journal ofConstructional Steel Research, Vol. 65(2), 2009,
pp. 249–259.
[9] Kankanamge ND, “Structural behaviour anddesign of cold-formed steel at elevatedtemperature”, Thesis, (2010).
[10] Gardner L, & Ng KT, “Temperature development
in structural stainless steel sections exposed tofire”, Fire Safety Journal, Vol. 41(3), 2006, pp.
185–203.
[11] Craveiro HD, Rodrigues JPC, and Laím L, “Coldformed steel columns made with open crosssections subjected to fire”, Thin-Walled Structures,Vol. 85, 2014, pp. 1–14.
[12] Wang P, Wang YC and Li GQ, “A new design
method for calculating critical temperatures ofrestrained steel column in fire”, Fire Safety
Journal, Vol. 45(6-8), 2010, pp. 349–360.
[13] BS EN 13381-4: Test methods for determining thecontribution to the fire resistance of structuralmembers - Applied passive protection to steel
members.
[14] BS EN 1363-1: Fire resistance tests. General
Requirements.
[15] EN. 1993-1.3: Design of steel structures. Generalrules - Supplementary rules for cold-formed
members and sheeting.
[16] EN. 1993-1.1: Design of steel structures. Generalrules and rules for buildings. Brussels, Belgium:
European Committee for Standardization (CEN);
2005.
[17] EN. 1993-1.2: Design of steel structures. Generalrules. Structural fire design. Brussels, Belgium:
European Committee for Standardization (CEN);
2005.

(b)

Fig. 7 (a) Test set-up (b) buckling of box-up column
CONCLUSION
This paper found that the temperature rise in CFS
is independent to the degree of utilisation for box-up
CFS columns. According to the recorded analysis
for all degrees of utilisation, it can be concluded that
there was a constant rate of temperature rise of thebox-up CFS column. The heating rate was 60ºC/min
and the initial heating rate was 84ºC/min. The
temperature behaviour of BTB column showed bothdegrees of utilisation, the flanges recorded a lower
temperature as compared to the flange due to thegreater thickness. It was found that criticaltemperature was 515.95ºC and 443.77ºC and criticaltime was 8 and 7 minutes for 50% and 70% degreeof utilisation, respectively. While buckling
temperature was 448ºC and 394ºC with critical timeof 7 minutes for 50% and 70% degree of utilisation,
respectively. Thus, findings concluded that thehigher degree of utilisation resulted in lower criticaland buckling temperatures of columns. The buckling
resistance time was not dependent on the degree of
utilisation.
ACKNOWLEDGEMENTS
This research was funded by the Ministry of Higher
Education Malaysia and Universiti Teknologi Mara
(UiTM) through the Fundamental Research Grant
Scheme grants. The technical support from theLaboratory of Structures and Materials, Faculty of
Civil Engineering, Universiti Teknologi Malaysia
and UiTM are greatly appreciated.
REFERENCES[1] Salleh N and Ahmad A, “Fire safety management
in heritage buildings: the current scenario in
Malaysia, 1996 (Table 1)”, (2009). Retrieved fromhttp://irep.iium.edu.my/1085/.
[2] Thompson
KK,(2006),
Retrieveat
http://www.fireengineering.com/articles/print/volu
me-159/issue-6/features/the-dangers-oflightweight-steel-construction.html (3/10/13).

236

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EXPERIMENTAL INVESTIGATION OF COLD-FORMED STEELCHANNEL SECTION WITH NOTCH
1

Mohd Syahrul Hisyam Mohd Sani1, Fadhluhartini Muftah3, Muhammad Isha Ismail4
Faculty of Civil Engineering, Universiti Teknologi Mara Cawangan Pahang, Kampus Jengka, 26400 Bandar
Jengka, Pahang, Malaysia

ABSTRACT
Cold-formed steel (CFS) channel section is a construction material that often been used in the building andstill in the research for utilising in structural element. The advantages of the CFS channel section such as
lightweight, anti-corrosion and etc are becoming so interesting in selecting it as a roof purlin, roof truss systemand storage rack. For having the structure element with strong, safe and stable condition, the study of the CFS
with the notch is carried out to determine the behaviour. The parametric study is taking place to determine thesuitability of notch pattern whether the notch depth and spacing is affecting the ultimate load of the CFS channel
section column and beam. The study of the CFS channel section is divided into two parts, the first part is to
examine the ultimate load of the column in varies of notch depth and the second part is to determine the ultimate
load of the beam in varies of notch spacing. By referring the study of the notch depth on CFS channel column
section, the result of the ultimate load is obtained to have the reduction about 19-80% of variation of notch depth
when compared with normal section. Although, the CFS channel beam section with variation notch depth isinfluenced of approximately 4-14% when compared with CFS channel normal beam section.
Keywords: Cold-formed steel, Notch, Ultimate load, Column, Beamsteel is the main problem that always been
discussed by researchers because of its fatigue
issues. It is happened due to the localised or
restricted changes of the steel structure withproducing the concentration stress on the locationof the notch and lastly growth of cracking.
Reference [2] has explained about the fatigue
design limit for conventional parts are acquired atstress cycles of 107 for determining and designing
the allowable stress.
There are a lot of researchers studied about thenotch which become popular for stopping the
failure of the material and structure. Reference [3]has analysed the fatigue of complex notch that
established from welded joints. Welded joint forindustries purpose such as offshore, oil and gas, andbuilding is used as a joint between structure
member to provide safety and stability of theconstruction [3]. Reference [4] has clarified thetensile residual stresses from the welding activity
for steel assemblies is combined with initial stressfrom steel component is lead to crack initiation.
Others researchers that study on the notch madefrom welded joints are [5] and [6].
Reference [7] has reported the result ofcompression testing of the concrete filled steel
tubular (CFST) short column with notch and theperformance of the column when subjected to thematerial imperfection. So, the notch in the steel
tubes is reacted as the material imperfection
problem which must be solved to obtain the
excellent in the structural integrity and also

INTRODUCTION
Cold-formed steel (CFS) is a structural andbuilding material that has been introduced broadly
in construction such as a roof truss system, wall
panel, storage pallet rack and etc. CFS with a lot ofadvantages in construction such as highest strength
to weight ratio, impervious to termites, rot andmold, recyclable,
non-combustibility, costeffectiveness and anti-corrosion. Currently, CFS isshifted as a structural element rather than before,
for only non-structural element. There iscomprehensive information about the design of the
CFS in the codes especially Eurocode 3 orAmerican Iron and Steel Institute (AISI). However,there are having not clear information and design of
the CFS as structural element, such as a column or
beam with a notch or perforated.
The notch can be referred that steel structure is
discontinuities in cross-sectional geometry as
example v-shape, semi-circle shape square-shapeand etc or non-uniformity of material [1]. Generally
the steel notch is produced to provide some spacing
to mechanical and electrical service activity in thebuilding. The study of the steel notch is significant
to certify the structure is could be utilised back if
there are some failure happened on it. There are two
types of the notch counting of V-notch and U-notchin the previous study. Additionally, fatigue of thesteel structure is existed when the fatigue loading
occurred at plastic strain and produced the surface
defect such as a notch or cracking. The notch of the237

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

extended their service life [7]. Besides, the notch
length, orientation and location are proposed for
determining the column performance and loadstrain response. As the result, the ultimate load of
the CFST short column is decreased with increasingof the notch length. Reference [8] has reported themechanical behaviour of the circular concrete-filledsteel tube short column subjected to axial
concentrated load and also the impact of the steel
tubes due to geometry imperfection.
Reference [9] has explored the crack growthresistance of a sharp notch of the high strength rail
steels for their mechanical properties. There arethree test specimens including smooth, short gauge
and pre cracked single-edged-notched bending
specimen that used in the railway industry [9].
Reference [10] explained the structural integrity ofthe structure is evaluated by assessing the defectcondition or flaw assessment procedures derived
from the mechanics of fracture approaches such asloading and temperature. Furthermore, many
researchers are studied about the notch as a crack
and defects of the section or material such as [11],[12], [13] and [14].
There is no information about CFS with notch
for column and beam in design, standard andprevious study. Besides, there are a lot of studies
about steel notch as an imperfection, welding andcracking effect but no information about the steel
notch as an initial work before being curve of thesteel component. CFS is cut with same notchspacing and width but varieties of notch depth as apreliminary study to form CFS curved section. Cutcurved method is one of the methods that's beenutilised in curving process and other method arecold-curved and hot-curved process. Cut-curved
method is chosen due to the simple way of process
and also avoids using the skill workers, hightechnology machine and high cost equipment. For
producing the CFS curved section, the notch depth
must be studied to determine the physical effect of
the section before being curved, ultimate load andalso the load-deformation behaviour. Reference[15] has stated that the mitred bends by cut-curved
is produced the smooth bends for impracticalcircumstances such as uneconomical and limited
space factor.
Usually, many studies are only emphasized on
the tensile load either flat or coupon tensile
specimen but for column and beam structure in
actual size or small scale is still deficient.
Additionally, there is no standard and experimental
method that's been utilised in evaluating theperformance of the structure with notch. Hence, theobjective of the study is to investigate themechanical behaviour especially the ultimate loadof the CFS column and beam section with a variety
of notch depth under concentrated load. Finally, thepaper determines the behaviour of the CFS with

notch to propose some new information andunderstanding of production of the CFS cut-curved.
SPECIMEN
SETUP

PREPARATION

AND

TEST

A CFS channel section with lipped and doubleintermediate web stiffener is chosen and clean. A
CFS channel section with double intermediate web
stiffener is selected to avoid the local buckling on
early stage and as a reference of the cut limit. The
cross-section and section dimension of the CFS
channel section are tabulated in Fig. 1 and Table 1.
Besides that, the section dimension of the testing
specimen is taken because the section is easy to getfrom construction material suppliers. The initialgeometric imperfection and residual stress of thesection is ignored. The ratio between the sectionand element is tabulated in Table 1 for checking theappropriateness of the section dimension due todeformation ability and allowable stability.

Fig. 1 The cross-section of the CFS channel section
Table 1 The section dimension and properties of
CFS channel section

Notes
Web, D
Lipped, L
Area, AF/t = b/t
D/F = h/b
D/L

Section dimension
Value
Notes
75 mm
Flange, F
8 mm
Thickness, t
148
Yield
mm2
Strength, γs
Ratio
34.0
F/L
2.21
D/t = h/t
9.38
L/t = c/t

Value
34 mm
1 mm
550
MPa
4.25
75.0
8.0

The section is cut by using an electric saw with
notch width of 3 mm and notch spacing whichmeasured centre to centre of 100 mm as a constantvalue. There are two experiments is arranged, thefirst experiment is a column specimen with varies
of notch depth and second experiment is still avariation of notch depth but for beam specimen.
The first experiment is obtained three column
specimens with difference notch depth and profile
is illustrated in Table 2 and Fig. 2. The section iscut according to three parts of notch depth forcolumn and beam specimens. First part, the section
is cut from the bottom flange until bottom
intermediate web stiffeners with 14 mm of notch
238

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017depth from the bottom of the CFS channel section.
Second part, the section is cut to half of the totalheight of the CFS channel section with notch depthof 37.5 mm. The section is cut from the bottom
flange until upper intermediate web stiffeners with
notch depth of 60 mm for the last part. The notch
depth of 14 mm, 37.5 mm and 60 mm are comparedwith an overall depth of the CFS channel section
without notch is roughly about 81.3 %, 50 % and
20 %, respectively. The height of the column is 400
mm and the length of the beam is 250 mm.

The length of the CFS channel beam section isstated of 250 mm. Both specimens are utilised thepace rate of the loading of the UTM is 1 mm/min.
All LVDTs is connected to a data logger to acquire
the value of the web and flange deformation.
Table 3 Specimen profile and label for a CFS
channel section for both experiments
Specimen profile
Label
Experiment One - Column
CFS without notch section
CFS-CC0
CFS with notch depth of 14 mm
CFS-CC1
CFS with notch depth of 37.5 mm
CFS-CC2
CFS with notch depth of 60 mm
CFS-CC3
Experiment Two - Beam
CFS without notch section
CFS-CB0
CFS with notch depth of 14 mm
CFS-CB1
CFS with notch depth of 37.5 mm
CFS-CB2
CFS with notch depth of 60 mm
CFS-CB3

Table 2 The profile of CFS with notch
Notes
Notch width, aNotch spacing, cNotch depth, d
a/t
c/t
d/D

Value Data
3 mm
100 mm
14 mm, 37.5 mm, 60 mm
Ratio
3.0
100
0.19, 0.50, 0.80

Fig. 2 The schematic diagram of CFS channel
section with notch.
Table 3 is represented the specimen profiles andlabels for column and beam specimen. The
compression test of the CFS channel section ofcolumn and beam with the variety of notch depth istested by using the Universal Testing Machine(UTM) with a capacity of 100 kN. The end supportcondition for column specimens are acknowledged
as a semi-rigid end support which utilise the steel
plate 6 mm that attached to the compression steel
jigs. The column specimen is situated on thesurface of the steel plate at the upper and bottomside of the support by using self-drilling screw andmonitored the fixity of the specimen to avoid the
movement. Two of the linear variable deformationtransducers (LVDT) are placed in the middle of thecolumn height of flange and web element, and one
LVDT is located on the steel plate to measure theaxial shortening of the specimen as shown in Figure
3 (a) and (b). The height of the CFS channel
column section is 400 mm.
Meanwhile, the end support condition for beamspecimens are also recognised as a semi-rigid end
support condition. Two plates and one steel rod areused for every end support to avoid the movement.
Two LVDTs are located on mid-span of the web
beam and end of the flange beam. The 50 mm
extensometer is also being used for determining the
mid-span flange deformation as shown in Figure 4.

(a)(b)
Fig. 3 The compression testing arrangement andsetup of the CFS channel section column specimen(a) without notch and (b) with notch.

Fig. 4 The flexural testing arrangement of the
CFS channel section beam specimen.
RESULT AND DISCUSSION
The mechanical behaviour of the column andbeam specimen is calculated and analysed.

239

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017is illustrated in Fig. 5. The initial stiffness of CFSCC0 is higher than other specimens and CFS-CC1
is higher than CFS-CC2 and CFS-CC3. CFS-CC2
and CFS-CC3 is illustrated having the same patternof load-deformation behaviour because the notch
depth is located more than 50% of the web depth
and percentage difference of notch depth between
them is 37.5%. Therefore, the initial stiffness isdecreased when the notch depth is increased. Some
example of the failure of the CFS-CC0 and CFSCC3 is shown in Fig. 6. Circle line in the figure isshown the location of the critical failure which has
proven the local and distortional buckling is existed.
The flange element is more critical to deflect andbuckle when compared to the web element.
However, the CFS-CC channel section with thenotch is capable to avoid the large deformation at
the flange and cause the overall column structure tobend to weak axis.

Mechanical Behaviour of CFS Channel Column
Section with Difference Notch Depth
The result of the compression behaviour of a
CFS channel column section especially ultimate
load, axial shortening and failure mode shape isrepresented in Table 4. From the table, the CFSCC1 is the largest value of ultimate load and lowest
value of axial shortening at ultimate load whencompared with other CFS-CC specimen with notch.
The percentage different of ultimate load between
CFS-CC1 with CFS-CC2 and CFS-CC3 isapproximately 5.51% and 8.52%, respectively. The
ultimate load of the specimen is decreased withincreasing of the notch depth. The ultimate load of
the CFS-CC specimen is not extensively affected
and influenced even if the notch depth in a highpercentage. The percentage difference of the ratio
notch depth over the section web between CFS-CC
without notch and CFS-CC1, CFS-CC2 and CFSCC3 is 19%, 50% and 80%, respectively. 56.85%
of the ultimate load percentage difference between
CFS-CC0 with CFS-CC1 is recorded. Furthermore,
the difference of axial shortening at ultimate load
between CFS-CC0 with CFS-CC1, CFS-CC2 and
CFS-CC3 in percentage is represented roughly
17.44%, 18.08% and 18.39%, respectively. The
axial shortening at ultimate load for CFS channel
section with the notch is not showing significant
changes between all specimens. This is because thespecimen is no longer having the compression
deformation but the specimen is demonstrated tohave the small rotation or known as distortional
buckling. Besides, the notch depth is getting
smaller when compression load is applied and thepeak at both sides of the notch is touching eachother. Lastly, the axial shortening at ultimate load isincreased when the notch depth is increased. Failuremode shape for all specimens is reported having
local and distortional buckling. All specimens isstated to meet the local buckling in early loading
and finally shifted to distortional buckling with the
movement of the both flange from the origin.

Fig. 5(a)Table 4 Compression behaviour testing of CFS
channel section with and without notch depth

Fig. 6

Axial
Failureshortening
mode
(mm)
shape
CFS-CC0 42,410.55
2.13
L&D
CFS-CC1 18,299.17
2.58
L&D
CFS-CC2 17,290.63
2.60
L&D
CFS-CC3 16,739.64
2.61
L&D
Note: L-Local buckling and D-Distortional
buckling
Specimen

Applied load versus compression
deformation graph.

(b)

The schematic diagrams of (a) CFS-CC0(b) CFS-CC3 after fail.

Mechanical Behaviour of CFS Channel Beam
Section with Difference Notch Depth

Ultimate
Load (N)The result of the flexural behaviour of a CFS
channel beam section for instance ultimate load andthe moment is tabulated in Table 5. The ultimate
load of CFS-CB without notch is recorded to have
6,931.42 and the highest value of the ultimate load
among of the CFS-CB with notch is 6,598.15. The
percentage difference between them is expressedaround 4.80%. It showed that the notch depth withless than 50% of the cut along the web depth is not

The detail of the specimen from initial applied
load to failure load with compression deformation

240

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

influenced the ultimate load and the moment of thesection. This is because the beam is categorised as ashort beam with less of deformation and bending
condition when compared to slender beam. 16.93%
and 35.14% of comparison percentage between
CFS-CB1 with CFS-CB2 and CFS-CB3,
respectively is reported. Additionally, thepercentage difference between the CFS-CB0 with
CFS-CB2 and CFS-CB3 is noted having 20.93%
and 38.26%, respectively. Lastly, a summary thatcan be designated is that when the notch depth isincreased, the ultimate load of the beam decreased.
The failure mode shape of the CFS-CB istabulated in Table 5. All specimens are observed
having a local buckling in the early stage of loading
and shifted to distortional buckling in the middle
period of loading. Table 5 also mentioned about theflexural deformation of mid-span flange at ultimate
load and flexural deformation of the overall beam at
mid-span under the applied load. The flexural
deformation of mid-span flange is noted to have
non uniform and uncertain data because of thelocation and depth of the notch. When the notch
depth is not achieved the second web stiffener or
middle of the section, the flexural deformation isstill in a stable condition but if the notch depth isreached the second web stiffener, the beam has lostits stability and strength. The percentage difference
between the CFS-CB0 with CFS-CB1 and CFSCB2 is recorded to meet about 4.14% and 11.90%,
respectively. The load-flexural deformation graphat mid-span flange is illustrated in Fig. 7 andshowed that the initial stiffness and line pattern of
CFS-CB0 and CFS-CB1 is same. Meanwhile, theinitial stiffness and stability of the CFS-CB isdecreased with increasing of the notch depth. The
percentage difference between CFS-CB3 with CFSCB0 is 14.07%. In addition, the flexural
deformation of overall bending at mid-span isincreased when the notch depth is increased. The
percentage difference between the specimen withthe lowest value, CFS-CB3 and the specimen withthe highest value is 99.31%. Fig. 8 is shown applied
load versus the flexural deformation of overallbending at mid-span. From the figure, the initialstiffness of the CFS-CB without notch is higher
when compared with CFS-CB with notch. This isbecause the CFS-CB has lost its stability, strength,
toughness and stiffness if the section is cut
vertically though small by following the directionof the applied load.

Table 5 The result of CFS channel beam section under three pinned bending
Flexural deformation at mid-span (mm)Ultimate
MomentLoad (N)(Nmm)
Flange at ultimate load
Overall bending
CFS-CB0
6,931.42
433,213.75
5.80
0.05
CFS-CB1
6,598.15
412,384.38
5.56
0.85
CFS-CB2
5,480.94
342,558.75
5.11
2.40
CFS-CB3
4,279.27
267,454.38
6.75
7.26
Note: L – Local buckling and D – Distortional bucklingSpecimen

Fig. 7

Applied load versus flexural deformationof mid-span flange under load graph.

Fig. 8

Applied load versus flexural deformationof overall mid-span beam graph.

Failuremode shape
L&D
L&D
L&D
L&D

When the load is applied, the beam with higher
notch depth is able to open in widespread, added
more stress at the end of the notch and eventuallycause the part to be torn. CFS-CB2 and CFS-CB3
are illustrated to have the additional gap of thenotch width to 40-60%. From observation, the CFSCB channel section with the notch is so flexible andelastic when load is applied, and form into large
deformation. But, after the applied load is released,
the beam is capable to form back to original shapewith less deformation. The flange element at top
side is more critical compared with bottom side.
Whilst as, the web element for CFS-CB0 and CFSCB1 are not critical when distinguished with CFSCB2 and CFS-CB3 channel section. The failure of
local and distortional buckling of the CFS-CB isless deformation compared with the CFS-CC
specimen this is due to slenderness.
CONCLUSION AND RECOMMENDATION

241

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[4] Ibrahim OA, Lignos DG and Rogers CA, “Aprobabilistic
approachforassessing
discontinuities in structural steel components
based on Charpy-V-notch test”, Engineering
Structures, Vol. 147, 2017, pp. 1-11.
[5] Berto F and Fergani O, “A review of the notch
rounding approach under in plane mixed modeloading”, International Journal of Fatigue, Vol.
101, 2017, pp. 127-136.
[6] Bilous P and Lagoda T, “Structural notch
effect in steel welded joints”, Materials andDesign, Vol. 30, 2009, pp. 4562-4564.
[7] Ding F, Fu L and Yu Z, “Behaviors of axiallyloaded square concrete-filled steels tube
(CFST) stub columns with notch in steel tube”,
Thin-walled Struct., Vol. 115, 2017, pp. 196204.
[8] Chang X, Fu L, Zhao H-B and Zhang Y-B,
“Behaviors of axially loaded circular concretefilled steel tube (CFT) stub columns with
notch in steel tubes”, Thin-walled Struct., Vol.
73, 2013, pp. 273-280.
[9] Yu F, Ben Jar P-Y and Hendry M, “Fracture
behaviour at the sharp notch tip of highstrength rail steels – influence of stresstriaxiality”, Engineering Fracture Mechanics
Vol. 178, 2017, pp. 184-200.
[10] Horn AJ, Sherry AH and Budden PJ, “Sizeand geometry effects in notched compact
tension specimens”, International Journal ofPressure Vessels and Piping, Vol. 154, 2017,
pp. 29-40.
[11] Torabi AR and Alaei M, “Mixed-mode ductile
failure analysis of V-notched Al 7075-T6 thinsheets”, Engineering Fracture Mechanics, Vol.
150, 2015, pp. 70-95.
[12] Hassan AR and Radhi SH, “Effect of the crack
geometry and notch on stress intensity factors
in bonding of materials”, Academic ResearchInternational, Vol. 4 (4), 2013, pp. 93-103.
[13] Cicero S, Madrazo V and Garcia T, “Thenotch master curve: A proposal of mastercurve for ferrritic-pearlitic steels in notched
conditions”, Engineering Failure Analysis,Vol. 42, 2014, pp. 178-196.
[14] Aratani M and Knott JF, “The growth of shortfatigue cracks ahead of a notch in highstrength steel”, Engineering Failure Analysis,Vol. 17, 2010, pp. 200-207.
[15] Neilson R, Wood J, Hamilton R and Li H, “A
comparison of plastic collapse and limit loads
for single mitred pipe bends under in-planebending”, Int. J. of Pressure Vessels andPiping, Vol. 87, 2010, pp. 550-558.

CFS-CC1 channel section which notch location
below the web stiffener is a specimen that has ahigher value of ultimate load and lower value of
axial shortening at ultimate load when comparedwith other specimen with notch. Besides that,56.85% and 17.44% of ultimate load and axial
shortening at the ultimate load percentage
difference between CFS-CC0 with CFS-CC1 isachieved. Consequently, the notch depth isincreased and the ultimate load of the specimen
decreased.
CFS-CB1 channel section is a specimen withthe highest value of ultimate load among thespecimen with notch and percentage difference
when compared with specimen without notch is
4.80%. The failure mode shape of the specimen isrecorded having local and distortional buckling.
Initial stiffness of the CFS-CB1 is in a good result
when compared with CFS-CB2 and CFS-CB3.
For further study, some experiment for severalof cross-section and section dimension must be
done to get the good relationship between theultimate load and cross-section.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge thefinancial support from Ministry of Higher
Education, Malaysia under the Fundamental
Research Grant Scheme for Universiti Teknologi
Mara (UiTM) Pahang. Thanks are also extended toFaculty of Civil Engineering of UiTM Pahang,
Kampus Jengka and Universiti Teknologi Malaysia(UTM) Skudai, Johor for providing laboratory
equipment.
REFERENCES[1] Bader Q and Kadum E, “Effect of V notch
shape on fatigue life in steel beam made of
AISI 1037”, Qasim Bader Int. J. of
Engineering Research and Applications, Vol.
4 (6), 2014, pp. 39-46.
[2] Akiniwa Y, Miyamoto N, Tsuru H and Tanaka
K, “Notch effect on fatigue strength reductionof bearing steel in the very high cycle regime”,
International Journal of Fatigue, Vol. 28 (11),2006, pp. 1555-1565.
[3] Lagoda T, Bilous P and Blacha L,“Investigation on the effect of geometric andstructural notch on the fatigue notch factor insteel welded joints”, International Journal of
Fatigue, Vol. 101, 2017, pp. 224-231.

242

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

A REVIEW OF UNEXPECTED LARGE SLOPE FAILURES
Marthinus Sonnekus1 and John Victor Smith2

1School of Engineering, RMIT University, Melbourne,

Australia
ABSTRACT
Significant advancements in the application of soil and rock mechanics have been achieved in managing therisk of large scale slope instability. In practice, however, unexpected slope failures do occur, sometimes withsignificant safety and economic implications for nearby communities, public infrastructure or the environment.
This review focus on large slope failure case studies, considering the slope failure mechanisms and theeffectiveness of the controls adopted in managing the geotechnical risk. The role of appropriate data collection
and interpretation in underpinning analysis methods is investigated. The impact of levels of uncertainty of input
data on different methods of analysis is addressed in the paper. In some instances, the slope failure mechanisms
are not understood and can therefore not be incorporated into geotechnical models. It is also found in this review
that the safety implications for communities located in the failure path were not initially evident, in some case,resulting in significant loss of life. A thorough understanding of the failure mechanism and triggers is essential
for assessing slope stability conditions. In addition, reliable stability monitoring, geological and hydrogeological
data are required for determining slope stability conditions. It is also evident from this review that timedependent behavior is likely to result in shear strength reduction and should be considered for long term slope
stability.

Keywords: Slope stability, slope failure, Southern Leyte, Guinsaugon, Vaiont, Yallourn MineINTRODUCTION

Geology

Large landslides can be highly complex in termsof failure mechanisms and movement history [1].
The examples reviewed here include a natural slope
in a remote location, a natural slope in the vicinity ofa large engineering project and a cut slope in an
open pit mine. The role of geology, landforms andgeotechnical conditions related to each failure arereviewed. Geotechnical issues include the failure
mechanism, the role of progressive failure,geotechnical parameters and reliability and failure
triggers. The lessons learned in each case and bycomparison of the cases are identified.

Leyte Island is in the central part of Philippine
islands. The archipelago is in one of the most active
geological settings on earth. The Philippine Fault
Zone, NW-SE orientated 1,200km long fault system
traverses the Leyte Island. The fault is actively
moving with a mean slip rate of 26±10mm/year at an
azimuth of about N130°E [4].
The Geological Map of the Philippines indicatesthat the landslide developed in a succession ofUpper Miocene-Pliocene interbedded sedimentary,
volcanic and volcaniclastic rocks [5]. Field mapping
undertaken in the Guinsaugon landslide area consistof sandstone, breccias and mudstones with faults anddefect infill comprising smectite clay [6].

GUINSAUGON LANDSLIDEA large slope failure occurred on 17 February
2006 at St Bernard, Southern Leyte province in thePhilippines. The failure volume is estimated at
between 20 to 25 million cubic meters with a runout
distance of almost four kilometers [2]. The
maximum velocity of the failure was estimated at
between 120 to 130 m/s [3]. The failure resulted in
the destruction of the Guinsaugon village with morethan 1,000 people being killed and many more
displaced.

Natural landform
The failure is bound at the crest of the 780 ma.s.l Mount Can-abag. This ridge is approximately
30 km long and is a geomorphic expression of theactive Philippine Fault Zone. The pre-landslide
topography was characterized by steeply dipping
slopes that formed a wedge geometry. The slope
release area is approximately 780 to 400 m a.s.l on
the eastern slope of Mount Can-abag [3].

243

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017days before the landslide. Other indications include
cracking and muddy water flow of the Aliho Creek
that flows down the mountain [2].
Geotechnical parameters and reliability

Fig. 1

There is very limited laboratory testing data
available for the Guinsaugon landslide. Intact coredsamples were obtained for Uniaxial Compressive
Strength (UCS) testing with results ranging from
17.9 to 23 MPa [3]. The number of tests, rock typeand reliability of test work are not known.
The calculated rock mass (and defect) cohesion
range between 0.45 and 0.78 MPa and the angle offriction between 22.9° and 32.2° [3].
The shear strength of the clay infill is not known.

Scar of the Guinsaugon landslide above
intensively farmed plains (photograph by
Christian Arnhardt, 2010).

Failure triggers

GeotechnicalNo direct triggers for the Guinsaugon landslide
could be identified [2], [5], [7]. Heavy rainfall
preceded the landslide and two minor earthquakes
occurred the day of the failure.
The Leyte island is characterized by a total
annual rainfall of approximately 3,640 mm. This has
resulted in deep tropical weathering profiles [5].
During February 2006, 970.8 mm rainfall wasrecorded at the Otikon rainfall station. This was
significantly more than the average rainfall of
275 mm for February. The heaviest recorded rainfallof 687.8 mm occurred from 8 to 16 February [2].
This rainfall would have resulted in significant porewater pressure buildup in the rock mass and along
defects. There would have been relatively limited
time for drainage.
Two minor earthquakes were recorded inSouthern Leyte Island on the day of the landslide.
There is uncertainty if the earthquakes induced thelandslide. Some authors believe the magnitudes arewell below the threshold that would be required toinduce the landslide. It is also possible that thelandslide itself could have caused the ground
tremors [2], [5], [7]. It is possible that the occurrenceof the earthquakes may not have any relationshipwith the Guinsaugon landslide.

Failure mechanism
The Guinsaugon failure mechanism wasstructurally controlled with failure on defects thatwere continuous, slickensided and weathered with asmectite clay infill. The Philippine Fault Zone
resulted in the weakening of the rock mass strength.
Kinematic analysis suggests a wedge failure
mechanism with a plunge towards the east [7].
It was proposed by [2] that the Philippine fault
zone may have acted as a release surface i.e. thefailure was initiated along the fault zone.
It is expected that high porewater pressure would
have developed in the rock mass and along thedefects due to heavy rainfall. It was found in a study
by [3] that increasing pore water pressure
significantly affected the calculated Factor of Safety(FoS) of the slope.
At the base of the slope the landslide debris
spread out almost 3 km2 over flooded paddy fields.
The extensive spread is the result of reduced
frictional resistance at the base of the debris mass
sliding on the flat flooded rice paddies [2].
Progressive failure

Lessons Learned
Post-landslide studies indicate that there are noslope movement and groundwater level monitoringdata. There are also no records of inspections to
identify cracks or other signs of slope instability. In
addition, it would have been difficult to locate
tension crack due to the dense tropical vegetationand difficult terrain. The absence of monitoring data
makes it difficult to determine the progressive
failure mechanism and to calibrate stability models.
If movement and piezometric data were available,
it may have indicated the onset of the landslide.
Residents observed small failures a few months andPractical monitoring methods such as theidentification of tension cracks, changes in slope
geometry, changes in creek flows and the reportingof small failures to authorities should be encouraged.
Slope movement and hydrogeological data isimportant in the development and calibration ofstability models. In the case of the Guinsaugonlandslide this data doesn’t exist. There is also very
limited geological, geotechnical and hydrogeologicalinformation available. Most of the data were only
collected after the landslide and this make244

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

geotechnical back analysis work difficult.
In landslide prone areas geotechnical mappingand drilling can be highly beneficial inunderstanding geotechnical conditions and obtaining
samples for geotechnical testing purposes.
With technological advancements, it is possible
to set up a very cost effective and accurate slope
monitoring system. Groundwater levels can bemonitored by drilling observation bores andinstalling piezometers.
Geological mapping of the pre-historic landslides
in the Guinsaugon area will aid in the understandingof failure mechanisms, volumes, triggers andperhaps even the frequency of landslides.
Authorities should continue to develop andimplement a Landslide Risk Management Plan withalert levels for monitoring and evacuation of villages.

still uncertainty on the failure mechanism.
The re-activation of an ancient landslide would
have resulted in very low shear strength along thepre-existing sliding surface. The low shear resistancecould have contributed to the high failure velocity of
20 to 30 m/s [11]. A residual friction angle as low as
5° may even be possible [12].
The presence and influence of clay beds in thelandslide have been widely discussed. Some authors
dismiss the presence of any clay beds while others
have described the presence of these layers in thestratigraphy and even conducted laboratory testingon the clay beds [10], [13].
Some authors propose that sliding occurred along
5 to 15 cm thick bands of clay 100 to 200 m deep
within the limestone mass. The clay layers are subhorizontal near the gorge and further out dip at 35°
towards the valley [9]. It is possible that persistent
rainfall and raising the reservoir level resulted inincreased pore water pressure [9], [10].
If a clay sliding surface is at sufficient depth,then the clay may exhibit brittle type behavior due tothe formation of microscopic cracking. This may
also explain the rapid failure that occurred [9].
Another recent study described a 30 to 60 m
thick shear zone at the base of the landslide [8].

VAIONT LANDSLIDEThe Vaiont valley is situated in the Italian Alps,
approximately 90 km north of the city of Venice.
The Vaiont landslide occurred on 9 October
1963 with approximately 270 to 280 million cubic
meters of material suddenly sliding from thenorthern slope of Mt. Toc into the Vaiont reservoir.
The failure resulted in a 245 m high wave that
overtopped the 260 m high double curved arced dam.
The flood wave destroyed Longarone and nearby
villages. It is estimated that more than 2,000 people
were killed in the disaster [8], [9].

Hydrogeology
Two aquifers are present in the northern slope ofMount Toc. The upper aquifer was mainly
influenced by the reservoir level and the lower
aquifer by both the reservoir and rainfall. The two
aquifers may be separated by a continuous clay layer[12].
Limited groundwater level data was obtained
from three boreholes with open standpipes. The
standpipes only recorded the average groundwaterlevels for the different hydrogeological units
encountered. In addition, the piezometers did notreach down to the sliding surface. The reliability ofgroundwater data is one of the biggest obstacles inunderstanding the effect the reservoir levels may
have had on slope movements [12].
There is also evidence of karstic conditions at Mt.
Toc, suggesting transmission of high groundwaterpressures along a possible clay sliding surface [10].

Geology
The Vaiont valley slopes comprise of middle
Jurassic limestone and overlain by upper Jurassic
limestone with clay and Cretaceous limestone [9].
Multiple clay layers occur near the base of lower
Cretaceous stratigraphic units [10].
Natural landform
The 300 m deep valley was formed by glacialand fluvial action in an asymmetric syncline [9]. The
deep and narrow gorge made it ideal for dam
construction. The dam is located just above thejunction of the Vaiont and Piave rivers.
There is evidence of the existence of an oldlandslide on the northern slope of Mt. Toc. Air photostudies identified evidence of the landslide that
includes drainage pattern changes, bulges anddepressions in the slope geometry [10].

Progressive failure
Three cycles of raising and lowering of thereservoir water commenced in February 1960 until
the landslide occurred. During the first cycles asmall failure occurred on March 1960 and a 2 kmlong tension crack opened up. A second failure of
700,000 m3 occurred on 4 November 1960.
Displacement rates of up to 3.5 cm/day wererecorded. During the third cycle movement
velocities continuously increased with rates of up to

GeotechnicalFailure mechanism
Although numerous geotechnical studies havebeen published since the Vaiont landslide there is245

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

20 cm/day [12].

approximately 150 km east of Melbourne in the stateof Victoria, Australia. The Latrobe Valley forms partof the Gippsland Basin that holds significant brown
coal deposits [15]. The coal is used for power
generation at the Yallourn Power Station.
On 14 November 2007, a large landslide
occurred on the approximately 80 m high North-Eastslope of the Yallourn East Field Mine. The failurevolume was estimated at approximately 6 million
cubic meters. The landslide was sudden with arunout distance of approximately 250 m [14]. The
Latrobe River that is behind the North-East slope
flooded the mine after the landslide. The landslide
resulted in significant damage to the environment
and mine infrastructure. Fortunately, there was noloss of life.

Geotechnical parameters and reliability
Direct shear test results on the clay material
ranged between 5° and 22°. Back analyzed effective
friction angle values calculated by various authors
ranged between 17° to 39°. The back analyzed
values are considerably higher than the direct shear
results. The back analysis was complicated by nothaving reliable groundwater data [10].
Failure triggers
It is possible that rainfall and raising andlowering of the reservoir levels could have acted as
triggers for the landslide [12]. It was difficult tocorrelate the piezometric levels with the rainfall andwater level of the reservoir [11].
Seismic events were recorded from May 1960
until the landslide occurred. However, the seismic
events could not be located with confidence as there
was only one seismometer installed at the Vaiont
dam [9].

Geology
The brown coals of the Gippsland Basin were
deposited during the Eocene to Late Miocene. The
coal forms part of a sequence of non-marine sands,
clays and coals, comprising the Latrobe Valley
Group. The Yallourn seam is mined at the YallournMine. Pliocene sandy clays, sands and gravels form
part of the Haunted Hill Formation. [15].
The Haunted Hill overburden thickness may
range from 10 to 44 m overlying 50 to 88 m of the
Yallourn brown coal seam. Below the Yallournseam there is clay, sand and other coal seams [16].

Lessons Learned
It is very important to incorporate the correct
failure mechanism into slope failure models. In the
Vaiont landslide there still appears uncertainty on
the failure mechanism and hydrogeologicalconditions that could have contributed to thelandslide.
An adequately designed slope monitoring system
can provide valuable insight into the failure
mechanism and early warning of an impending
landslide. Instrumentation such as boreholeextensometers can be used to locate deep seatedsliding surfaces.
Groundwater observation bores should be drilled
to the correct depths and equipped to ensure reliable
and representative readings are obtained for eachhydrogeological unit. Modern grouting techniques
have simplified the installation of vibrating wire
piezometers.
Geological and geotechnical field investigation
may include comprehensive mapping, drilling andlaboratory testing programs. It is important thatexperienced geologists, hydrogeologists andgeotechnical engineers manage these programs.

Natural LandformThe Yallourn Mine is in a relative flat area. The
Morwell river is west of the Yallourn East Field
Mine and flows into the Latrobe river. The Latrobe
river is north of the North-East slope. The Eastern
Highlands is north of the mine and the South
Gippsland Highlands towards the south [17].
GeotechnicalFailure mechanism
The Yallourn coal seam is highly jointed with
continuous sub-vertical joints. The dominant joint
set is striking west-northwest to east-southeast andform an acute angle with the North-East mine slope[14].
Due to the low density of the brown coal, thecoal slopes are prone to movement and can fail if
there is a sufficient increase in the slope
groundwater levels.
The Yallourn landslide is a typical horizontal
block sliding mechanism. The high groundwaterpressure in joints that connected to the Latrobe riverand along the interseam resulted in the failure. The
planned buffer distance between the pit slope andthe Latrobe river was only 150 m [14].

YALLOURN LANDSLIDE
A review and discussion of some of the key
findings of the Mining Warden Yallourn Mine
Batter Failure Inquiry [14] is provided. The authorsof this paper are also familiar with the geotechnicalaspects of the Latrobe Valley brown coal mines.
The Yallourn Mine is in the Latrobe Valley,
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Lessons Learned
There is a long history of the block sliding
failure mechanism in the Latrobe Valley brown coalmines.
The use of horizontal drainholes and deep
aquifer dewatering is required to reducegroundwater pressure in both the coal joints andalong the interseam clays [14]. Removing thesecontrols, and mining very close to the Latrobe river,resulted in a significant increase in the risk of slope
instability.

Hydrogeology
A phreatic groundwater level is present in the
Yallourn coal seam. This groundwater level can beaffected by rivers or rainfall runoff into open joints.
Horizontal drainholes have historically been usedat the Yallourn Mine to dewater and reduce thegroundwater level in the coal slopes. A decision wasmade around 2003 to stop the drilling of horizontal
drainholes [14].
Confined aquifers are present below most ofslopes for the Latrobe Valley Mines. These aquifers
can be very extensive [18].
Deep aquifer dewatering has historically beenrequired at the Yallourn Mine to manage the risk offloor heave. After various studies, it was decided in
2004 to switch off the deep aquifer dewatering bores.
Unfortunately, high porewater pressures remained in
the interseam clays under the North-East slope [14].

CONCLUSION
The three large slope failures reviewed share thefollowing features. (1) The failure mechanisms arecomplex and have required significant detailed
investigation. (2) No single trigger event could be
identified as the ‘cause’ of the landslide. (3)Movement on pre-existing bedrock structures wasinvolved thus generating the large volumes involvedin the landslides. (4) Water movement and related
water pressure was part of the problematicconditions associated with the failures.
Risk management planning is needed in
excavations, engineering projects and forcommunities in the vicinity of slopes. In the case of
excavations such as mining, every slope requires a
management plan to assess stability. All engineering
projects including dams, transport corridors andbuilding construction also require assessment ofslopes in the vicinity. In remote areas it may not bereasonable to assess and monitor the stability of
every natural slope. However, every community
should be aware of slopes that represent a potential
hazard. Risk factors such as heavy rain periods andobservations such as ground cracking or anomalous
surface water behavior together with associatedaction plans should be known by local residents.
Significant advances have been made in regional
assessments of susceptibility to shallow landslides[19] but the potential for larger, deeper landslides tooccur remains difficult to assess on a regional scale.

Progressive failure
The movement monitoring survey pins on the
North-East slope indicated accelerated movement
for years before the landslide occurred.
In general, the piezometer levels on the
North-East slope reduced over time. However, a few
months before the failure there was a significant
increase in some of the bore levels. This sudden
increase may indicate hydrogeological connectivity
being established between the joints that formed thefailure surface and the Latrobe river [14].
In the months before the failure large cracks
started forming between the pit crest and the Latrobe
river. This was followed with significant inflows ofwater from the Latrobe river until the failure
occurred. There were also significant displacementof the conveyers and other infrastructure on the
North-East slope the days and weeks before thefailure.
Geotechnical parameters and reliability
Movement of the North-East slope in the months
and years before the failure would have resulted inresidual shear strength conditions in the interseam
clays below the base of the coal. A residual friction
angle of 16° was used in back analysis / validation
modelling by [14]. Based on experience in the
Latrobe Valley mines the residual friction angle canbe significantly lower than 16°.

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classification of landslide types, an update",
Landslides, Vol. 11, 2014, pp. 167-194.
[2] Orense RP, Gutierrez MS, "2006 large-scale
rockslide-debris avalanche in Leyte Island,
Philippines", Earthquake geotechnical casehistories for performance-based design, 2009,
pp. 31-45.
[3] Catane SG, Cabria HB, Zarco MAH, Saturay
RM, Mirasol-Robert AA, "The 17 February
2006 Guinsaugon rock slide-debris avalanche,
Southern
Leyte,
Philippines:
depositcharacteristics and failure mechanism", Bull

Failure triggers
Various factors contributed to the Yallournlandslide as previously discussed. It is possible that arainfall event on 4 November 2007 could have acted
as a trigger for the landslide to occur.

247

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

Eng Geol Environ, Vol. 67(3), 2008, pp. 305320.
[4] Duquesnoy TH, Barrier E, Kasser M, Aurelio M,
Gaulon R, Punongbayan RS, Rangin C,"Detection of creep along the Philippine Fault:
First results of geodetic measurements on Leyte
Island, central Philippine", GeophysicalResearch Letters, Vol. 21(11), 1994, pp. 975978.
[5] Evans SG, Guthrie RH, Roberts NJ, Bishop NF,"The disastrous 17 February 2006 rockslidedebris avalanche on Leyte Island, Philippines: acatastrophic landslide in tropical mountainterrain", Nat. Hazards Earth Syst. Sci., Vol. 7,
2007, pp. 89–101.
[6] Futalan KM, Biscaro JRD, Saturay RM, Catane
SG, Amora MS, Villaflor EL, "Assessment ofpotential slope failure sites at Mt. Can-abag,
Guinsaugon, Philippines, based on stratigraphy
and rock strength", Bull Eng Geol Environ, Vol.
69, 2010, pp. 517–521.
[7] Guthrie RH, Evans SG, Catane SG, Zarco MAH,
Saturay RM, "The 17 February 2006 rock slidedebris avalanche at Guinsaugon Philippines: asynthesis", Bull Eng Geol Environ, Vol. 68,
2009, pp. 201–213.
[8] Barla G, Paronuzzi P, "The 1963 Vajont
Landslide: 50th Anniversary", Rock Mech RockEng, Vol. 46, 2013, pp. 1267-1270.
[9] Kilburn CRJ, Petley DN, "Forecasting giant,catastrophic slope collapse: lessons from Vajont,
Northern Italy", Geomorphology, Vol. 54, 2003,
pp. 21–32.
[10] Hendron AJ, Patton FD, "The Vaiont slide – A
geotechnical analysis based on new geologicalobservations of the failure surface", Engineering
Geology, Vol. 24, 1987, pp. 475 – 491.
[11] Semenza E, Ghirotti M, "History of the 1963
Vaiont slide: the importance of geologicalfactors", Bull Eng Geol Environ, Vol. 59, 2000,
pp. 87–97.

[12] Genevois R, Tecca PR, "The Vajont Landslide:
State-of the Art", J. Eng. Geol. Environ Vol. 6,
2013, pp. 15-39.
[13] Müller-Salzburg L, "The Vajont Slide",
Engineering Geology, Vol. 24, 1987, pp. 513523.
[14] Sullivan T, "Mining Warden Yallourn Mine
Batter Failure Inquiry", Victorian Government
Printer, No. 156, Session 2006 – 08, 2008.
[15] Barton CM, Gloe CS, Holdgate GR, "Latrobe
Valley, Victoria, Australia: a world class brown
coal deposit", International Journal of Coal
Geology, Vol. 23, 1993, pp. 193-213.
[16] Wood WJ, Dugan K, Coulthard M, Rivalland J,"Deep Aquifer Shutdown Tests at YallournMine", Fifth Large Open Pit Mining Conference,
2003, pp. 205-214.
[17] BlackburnDT,
Sluiter
IRK,"The
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Australia", History of the Australian Vegetation:
Cretaceous to Recent, 1994, p. 329.
[18] Schaeffer J, "Scaling Point Based Aquifer Datafor Developing Regional Groundwater Models:Application to the Gippsland Groundwater
System", University of Melbourne, PhD Thesis,
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[19] Rabonza ML, Felix RP, Lagmay AM, Eco RN,
Ortiz IJ, Aquino DT. “Shallow landslide
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201-210.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THE EFFECT OF STEEL FIBERS EXTRACTED FROM WASTE TYRE
ON CONCRETE CONTAINING PALM OIL FUEL ASH
1

Fauzan1, Febrin Anas Ismail2 and Rio Sandi 3
Engineering Faculty, University of Andalas, Padang City; 2West Sumatera, 3Indonesia

ABSTRACT
Tyre production is increasing every year due to the increase of vehicle sales in the world. In Indonesia, morethan 50 billion waste tyre was generated per year. The generation and disposal of waste are inherent to life itself
and have presented very serious problems to the human community in Indonesia. Recently, some research has
been devoted to the utilization of steel fibers extracted from waste tyre (SFEFWT) in concrete. This study is
focusing on the use of SFEFWT with containing palm oil fuel ash (POFA) in concrete mix. Steel fibers was
extracted from chips of waste tyres by manual cutting process and cut to 1 inch (25.4mm) length. Number ofcylindrical specimen of steel fibers extracted from waste tyre (SFEFWT) with addition of 0%, 0.25%, 0.5%,
0.75%, 1% and POFA with addition 15% by cement weight were used in concrete mix to fabricated and tested.
The experiment has been tested at 28th day. In particular, concrete containing POFA obtain by adding SFEFWT
evidence a satisfactory improvement, mostly in cracking control, compressive strength, flexural strength and also
splitting tensile strength. On the other hand, compressive, flexural and tensile strength was positively affected by
the additions of SFEFWT on POFA concrete. The percentage of SFEFWT on concrete containing POFA will
give high number of bonding in concrete to delay the crack growth.
Keywords: Concrete; Steel Fiber; Waste Tyre; Palm Oil Fuel Ash; Compressive Strength; Flexural Strength;
Splitting Tensile Strength; Cracking Control.

of concrete mix makes it less liable to segregation
due to increased cohesiveness.
The addition of fibers to concrete considerably
improves its structural characteristics such as static
flexural strength, impact strength, tensile strength,
ductility and flexural toughness [1]. The inclusion ofsteel fibers in concrete considerably enhanced theengineering properties of mortar and concrete [2].
Using a little percentage of steel fibers efficiently
improve the load-carrying capability of slabs on
ground and significantly improve the slab ductility[3]. With the inclusion of hooked steel fibers withcut length of 6 cm and aspect ratio of 80 and
replacement of cement with 0.5%, and 1% improved
the mechanical properties of concrete [4]. The
results of ultrasonic pulse velocity revealed that theusing of small percentage of steel fiber in concrete
improved the quality of concrete [5].Sata et al.,(2010) investigated that the strength development of
POFA concretes with w/c ratios of 0.50, 0.55, and0.60 tended to be in the same direction. At earlyages, concretes containing POFA as a cement
replacement of 10, 20, and 30% had lower strength
development than control concretes while at laterage 28 days, the replacement at rates of 10 and 20%
yielded higher strength development [6]. Hussin etal., (2008) discovered that inclusion of 20% POFA
would produce concrete having highest strength ascompared to any other replacement level [8]. Ahmad
et al., (2008) studied that one of the potential

INTRODUCTION
Facts and figures show that concrete is very
common and extensively used for construction as afavorable material all over the world. Even then,there are many deficit characteristics of concrete
which limits its applications, as concrete has a low
stiffness, low ductility and low energy absorption.
Also when concrete is hardened, shrinkage cracks
appears on its surface, therefore to improve these
deficiencies in concrete, now a day’s variety of fiber
materials are being used in concrete to improve its
applications for best services. The fibers such as
steel, glass, polymeric, natural and plastic fibers
mixed with concrete at particular cut length andspecified aspect ratio and randomly distributed, caneffectively be utilized to overwhelm such deficits.
However, in developing countries like Indonesia the
major problem to utilize steel fibers extracted fromwaste tyre (SFEFWT) produced from industry isinherent to life itself. In Indonesia, more than 50
billion waste tyre was generated per year.
The use of steel fibers extracted from waste tyre
(SFEFWT) is day by day increasing in structural
applications because of high stress resistance,
toughness and long term strength. The fibers join
together in a synchronized manner and becomeenmeshed to aggregates and substantially fibers tend
to reduce the workability of mix, this phenomenon249

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

recycles material from palm oil industry is palm oil
fuel ash which contains siliceous compositions andreacted as pozzolans to produce a stronger anddenser concrete [9]. In this paper, the effect of steel
fibers extracted from waste tyre on concrete
containing palm oil fuel ash was studied.
MATERIALS AND METHODS
Materials Used
CementOrdinary Portland Cement
available in market was used.

(OPC)

commonlyFig. 2. Steel Fiber Extracted From Waste Tyre

Fine and Coarse Aggregate
Locally
available aggregates were used; fine aggregate withsize retained on 200 number sieve and passing from4.75 mm. The specific gravity and fineness modulus
of fine aggregate was 2.57 respectively. The coarse
aggregate used was locally available quarry having
two different sizes; one fraction is passing through20 mm sieve and another fraction passing through10 mm sieve. The specific gravity of 20 mm and 10
mm aggregates are 2.70 and 2.60 respectively.
Fig. 3. Steel Fiber in 1 Inch Cut Length

II.1.3 Water
Potable tape water was used in mix preparation.

II.1.5 Palm Oil Fuel Ash
Palm Oil Fuel Ash (POFA) is the product ofburning palm oil husk and palm kernel shell in thepalm oil mill. POFA obtained from PT. Sawit,
Sangir in Dhamasraya was used in the electricalenergy. The specific gravity of palm oil fuel ash was
1.65. The chemical composition of POFA was tested
at Indarung II, PT. Padang Cement Indonesia andthe results is given in Table 1. Figures 4 and 5 show
the Palm Oil Residues and Palm Oil Fuel Ash.

Steel Fiber Extracted From Waste Tyre
Waste tyres in Indonesia are the low-priced,
economical and in abundance available material. In
Indonesia there is a lack of appropriate recycling
industry of waste tyres, manually a huge amount of
Steel fiber are being taken out which includes a little
quantity of rubber particles on their surfaces. In thisstudy, the steel fibers taken out from waste tyres areused in the concrete mix to form a composite fibrousmaterial. Steel fibers waste tyre were extracted fromchips of waste tyres by manual cutting process(Figures 1 and 2) and cut to 1 inch (25.4 mm) length(Figure 3) and average diameter of fiber was 0.28
mm keeping aspect ratio 90. As waste tyres steel
fibers are uniformly and randomly distributed indifferent proportions from (0-1%) with increment of
0.25% by the weight of cement to prepare thedifferent concrete matrix. The chips of waste tyres
available in local market; normally they sell those as
scrap to scarp industry.

Fig. 4. Palm Oil Residues

Fig. 1. Cutting Process From Waste Tyre to Obtained
Steel Fiber Extracted

Fig. 5. Palm Oil Fuel Ash

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Table 1. Chemical Composition of POFA
ChemicalComposition
Silicon Dioxide
Aluminium Trioxide
Iron Oxide
Lime
Magnesium Oxide
Potassium Oxide
Loss of Ignition

Formulae
SiO2
Al2O3
Fe2O3
CaO
MgO
K2O
LOI

Testing of Specimen
Compressive, splitting tensile and flexuralstrength tests were conducted on cylindrical
specimens and beam specimens using Universal
testing machine (UTM) in the concrete laboratory of
PT. Semen Padang as per SNI 1974:2011, ASTM C
496-86 and ASTM C 293-08, respectively. Figures 6,
7 and 8 show the specimens under compressive,
splitting tensile and flexural testing in the laboratory.

Content
(%)
62.84
2.19
0.00
9.57
3.48
-

EXPERIMENTAL STUDY
Mix Proportions of Concrete
The concrete mix is designed as Indonesian
Nasional Standar (SNI) for the normal concrete. The
grade of concrete adopted is M35 with a water
cement ratio of 0.52. Five mixture proportions were
made. First was control mix (with palm oil fuel ash,without steel fiber), and the other four mixes is steel
fiber with percentage of 0.25%, 0.5%, 0.75%, 1%
contained POFA. Cement was replaced with POFA
by weight. The proportions of cement replaced 15%.
The ingredients of concrete were thoroughly mixed
in a mixer machine till uniform consistency wasachieved. Mix proportions are given in Table 2.
Table 2. Mix Proportions
SampleCSF
SF
ID
0% 0.25%Cemen
332 332.
391
t
.35
35
3
(kg/m )
Water
205 205 205(kg/m3)725. 725 725.
F.A.
6
.6
6
(kg/m3)108 108 108
C.A.
8.4
8.4
(kg/m3) 8.4
SFEF
0.97
WT
6
3
(kg/m )
58. 58.6
POFA
650
50
(kg/m3)

SF
0.50
%

SF
0.75
%

SF
1%

332.3
5

332.
35

332
.35

205

205

205

725.
6
108
8.4

725
.6
108
8.4

1.955

2.93
3

3.9
10

58.65
0

58.6
50

58.
650

725.6
1088.
4

Fig. 6. Compressive Test on CylindricalFig. 7. Splitting Tensile Test on Cylindrical

Casting of Specimens
Total 27 cylinders were casted, for compressive,
tensile and flexural strength test. Cylindrical
specimens of length 300 mm and diameter 150 mm
and beam specimens of length 500 mm, wide
100 mm, high 100 mm casted with adding 0%,
0.25%, 0.5%, 0.75% and 1% of used waste tyre steel
fibers extracted.

Fig. 8. Flexural Test on Beam

RESULT AND DISCUSSION
Compressive Strength
The results of the tests for compressive strength
performed on the samples are shown in table 3.
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SEE-USQ, Brisbane, Australia, Nov.13-16, 2017

Table 3. 28 Days Compressive Strength of
Cylinder Specimen
Palm Oil(SFEFWT)
Compressi
Fuel Ash
No.
Content
ve Strength
Content(%)(N/mm2)
(%)
1
15
0
26.40
2
15
0.25
27.60
3
15
0.50
28.40
4
15
0.75
29.10
5
15
1.00
29.70

Splitting Tensile Strength(N/mm2)3

2.5*SFEFWT : Steel Fiber Extracted From Waste Tyre

Compressive Strength(N/mm2)

0.25

0.5

0.75

1

29
Fig. 10. Comparison of Splitting Tensile Strength of
Ordinary and SFEFWT POFA Concrete28
27

The results of splitting tensile strength of POFA
concrete mixes with SFEFWT measured at 28 days
are given in Table 4 and Figures 7 and 10. Test
results indicate that the tensile splitting strength
increases as the percentage of the SFEFWT on
POFA concrete increases from 0% to 0.5%, 0.75%
and 1%. The maximum splitting tensile strengthwith the addition of 1.0% of SFEFWT is 2.85
N/mm2, which is 23% increment as compared toconventional concrete.

26
25
0

0.25 0.5 0.75
SFEFWT (%)

1

Fig. 9. Comparison of Compressive Strength of
Ordinary and SFEFWT POFA ConcreteCompressive strength of POFA concrete mixes
made with SFEFWT was determined at 28 days. The
results presented in Table 3 and Figures 6 and 9, thatthe compressive strength of POFA concrete
reinforced with SFEFWT slightly increases with theincrease of SFEFWT content. The maximum 13%
increase i.e. 29.70 N/mm2 as compared to without
SFEFWT concrete; at addition of 1.0% SFEFWT.

Flexural Strength
The results of the tests for flexural strength
performed on the samples are shown in Table 5.
Table 5. 28 Days Flexural Strength of Cylinder
Specimen
Palm Oil(SFEFWT)
Flexural
Fuel Ash
No.
Content
Strength
Content(%)(N/mm2)
(%)
1
15
0
4.19
2
15
0.25
4.46
3
15
0.50
5.06
4
15
0.75
5.32
5
15
1.00
5.50

Splitting Tensile Strength
The results of the indirect tensile strength tests
performed on the samples are shown in Table 4.
Table 4. 28 Days Indirect Tensile Strength of
Cylindrical Specimen

1
2
3
4
5

0

SFEFWT (%)

30

No.

2

Palm Oil
Fuel AshContent
(%)
15
15
15
15
15

(SFEFWT)
Content
(%)
0
0.25
0.50
0.75
1.00

SplittingTensileStrength(N/mm2)
2.32
2.50
2.61
2.71
2.85

*SFEFWT : Steel Fiber Extracted From Waste Tyre

Flexural strength of POFA concrete mixes madewith SFEFWT was determined at 28 days. The
results presented in Table 5 and Figures 8 and 11,that the flexural strength of POFA concrete
reinforced with SFEFWT increases with the increase
of SFEFWT content. As can be seen that, themaximum 31% increase i.e. 5.50 N/mm2 ascompared to without SFEFWT concrete; at additionof 1.0% SFEFWT on POFA Concrete.

*SFEFWT : Steel Fiber Extracted From Waste Tyre

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

increase compared to the POFA concrete
without SFEFWT.
 Results suggest that 1% SFEFWT on POFA
concrete could be the optimum level for the
maximum flexural strength; 5.50 N/mm2 i.e.
31% increase as compared to POFA concrete
without SFEFWT.

Flexural Strength(N/mm2)

5.5
5
4.5
4

ACKNOWLEDGEMENTS

3.5

The authors wish to acknowledge the staffs of
the Laboratory of Material and Structure in Andalas
University and the Laboratory of Concrete in Padang
Cement Factory for their support.

3
0

0.25

0.5

0.75

1

SFEFWT (%)

REFERENCES
Fig. 11. Comparison of Flexural Strength of Ordinary and
SFEFWT POFA ConcreteFig. 12.

[1] Mohammadi Y, Singh SP, Kaushik SK.
“Properties of steel fibrous concrete containing
mixed fibers in fresh and hardened state”.
Constr
Build
Mater
2006;
doi:10.1016/j.conbuildmat.2006.12.004.
[2] Yet, T.C., Hamid, R. and Kasmuri, M.
“Dynamic Stress-Strain Behavior of Steel Fiber
Reinforced High-Performance Concrete with
Fly Ash”Hindawi Publishing Corporation,
Advances in Civil Engineeringvol. 2012,
Article ID 907431, 6pages. (2012)[3] Luca G. S., Meda, A. and Giovanni, A. P.
“Steel Fiber Concrete Slabs on Ground: A
Structural Matter”ACI Structural Journal, Vol
103. pp 551-558 (2006)[4] Nili, M. Afroughsabet, V. “Combined effect ofsilica fume and steel fibers on the impact
resistance and mechanical properties ofconcrete” International Journal of Impact
Engineering, Vol 37, pp 879-886. (2010)[5] Nataraja, M.C., Nagaraj, T.S. and Basavaraja.
S.B. “Reproportioning of steel fibre reinforced
concrete mixes and their impact resistance”
Cement and Concrete Research, Vol 35, pp
2350 – 2359. (2005)[6] Vanchai Sata., Chai Jaturapitakkul., &Chaiyanunt Rattanashotinunt., “Compressive
Strength and Heat Evolution of Concretes
Containing Palm Oil Fuel Ash”, Journal of
Materials in Civil Engineering, Vol. 22, No. 10,
October 1, 2010. ©ASCE, ISSN 08991561/2010/10-1033–1038.
[7] Mohd Warid Hussin., Mohamed A. Ismail.,
Ahmed Budiea., & Khairunisa Muthusamy.,“Durability of high strength concrete
containing palm oil fuel ash of different
fineness”, Malaysian Journal of Civil
Engineering, Vol.21 (2), 2009, pp.180-194.
[8] Ahmad M. H., Omar R. C., Malek M. A., Noor
N & Thiruselvam S., “Compressive Strength ofPalm Oil Fuel Ash Concrete”, ICCBT 2008 - A- (27) – pp297 – 306.

Crack Growth in Concrete

The results presented in Figure 12 show that thepercentage of SFEFWT on POFA concrete givenhigh number of bonding in concrete to delay thecrack growth.
CONCLUSION
The following conclusions could be arrived atfrom the study: Compressive strength, Splitting tensile
strength and Flexural strength of POFA
concrete specimens with steel fiber extracted
from waste tyre (SFEFWT) were found to bestronger than those of without SFEFWT.
 By inclusion of SFEFWT on concrete
containing palm oil fuel ash, the compressive
strength increases slightly, at addition of
1.0% SFEFWT, maximum compressive
strength, 29.70 N/mm2 i.e. 13% increase ascompared to POFA concrete without
SFEFWT is observed.
 With addition of 1% SFEFWT on POFA
concrete, the maximum splitting tensile
strength was 2.85 N/mm2, which is 23%
253

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

ACCURACY OF CENTRALIZED AND DECENTRALIZEDMANUFACTURING SYSTEMS TOWARDS AN INDUSTRY 4.0’S
PERSPECTIVE

1

Poonpakdee, P. 1, Koiwanit, J.2, Yuangyai, C.3
Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology
Ladkrabang, Bangkok 10520, Thailand

ABSTRACTWith significantly improving the overall manufacturing operations commonly known in smart factory
practices, vertical and horizontal integrations of various components are introduced throughout the entire value
chain. The proliferation of smart factory practices introduce the fourth industrial revolution called Industry 4.0.
Industry 4.0 creates new challenges and the application of networked manufacturing systems is one of theimportant features required to handle the systems in an efficient way by communicating and processing
information to each other. Distributed systems provide coordination to allow the global information to beavailable for a better decision making and consequently achieving high efficiency. This connectivity helps for abetter decision making and therefore achieve high efficiency. However, the evaluation on the accuracy of global
information between different architectures of distributed systems (centralized systems and decentralized
systems) has little work mentioning in the state of current manufacturing systems under the conception ofIndustry 4.0. As a result, this research will fill the gap by providing an accuracy of the decentralized system overthe centralized system together with their sensitivity analysis.
In this study, the decentralized system is built based on the concept of Epidemic protocols or Gossip-based
protocols, while the centralized system is a simple client-server. Epidemic protocol is a bio-inspired
communication paradigm that imitates the behavior of virus when the outbreak is occurred in a community. The
accuracy in both systems has been monitored by mean of simulations. The effects of message loss to theaccuracy of centralized and decentralized systems are studied. By comparing the system accuracy between both
systems, it was found that the accuracy of decentralized system is generally more accurate when the system isused for a long period. The accuracy tends to be lower down especially when the information is not completely
distributed, while the accuracy of centralized system receive an excessive suffer from message loss.
Keywords: Industry 4.0, centralized systems, decentralized system, accuracy

server. A server aims to centralize all function andinformation taken from clients by directly
connecting to the clients. Clients share theirresources by sending and receiving the information
to a server [1]. In contrast, decentralized systems are
similar to peer-to-peer systems where all peers
communicate symmetrically and equally in roles. A
well-known example of decentralized systems is
Gnutella, the practical decentralized systems with
only a centralized function for starting a new host[1]. In this study, Epidemic protocols or Gossipbased
protocols,
which
is
bio-inspired
communication
paradigm
forinformation
dissemination in extreme scale network systems, areused to construct the decentralized system.
In general, the convergence speed of centralized
systems is faster than decentralized systems because
the complete set of data is stored and managed
within a hub that does not exist in decentralized

INTRODUCTION
The proliferation of smart factory practices
introduces the fourth industrial revolution called
Industry 4.0. Industry 4.0 creates new challenges
and the application of networked manufacturingsystems is one of the important features required tohandle the systems in an efficient way bycommunicating and processing information to eachother. Distributed systems provide coordination toallow the global information to be available for abetter decision making and therefore achieve highefficiency.
The basic architecture of distributed systems,
which is a part of smart factory systems, can be
categorized into two major groups: centralized
systems and decentralized systems. The mostfamiliar form of topology is centralized systems,
whose structure is typically similar to the client254

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

systems. However, many circumstances such as
message loss and node failure in centralized systems
can cause data missing which can skew the results ofthe global aggregation. This introduces aninaccuracy in the decision making [2]. Unlike
centralized systems, decentralized systems allow
data from each node to be distributed to its
neighbors [3]. This results in the networked
infection over the whole system as the time goes by.
Several works related to the accuracy of the global
information in distributed systems have beenreviewed. Reference [4] studied on the accuracy offailure detection in distributed system Reference [2]explored the accuracy analysis of data aggregation
for distributed network monitoring. Reference [5]analyzed the convergence in decentralization in a
specific problem. Reference [3] studied the accuracyof the epidemic spreading over a network. However,the literature review reveals that little work has been
done under the concept of Industry 4.0 particularly
focusing on the accuracy of global aggregation
between both systems. As such, this paper presents
how accuracy decentralized systems is evaluatedagainst centralized systems in the context ofmanufacturing.
The rest of the paper is organized as follows.
Section 2 gives the detail of Epidemic aggregation
protocols and some of the related works. Applicationcase study is presented in Sections 3. The
experimental scenario and their results are presented
and analyzed in Section 4 and 5, respectively.
Finally, Section 6 draws some conclusions andprovides possible directions of future work.

to solve data aggregation problems because highly
distributed systems such as P2P or large-scale
network systems have currently become more
popular and enabled for a broad range ofapplications [26],[22]. Due to these systems, theinformation of data aggregation over the network isoften more important than the information of anindividual node [19], so tools that can computesignificant system properties of a network arenecessary [27]. A monitoring system is an example
where the system administrator would be moreinterested in the aggregation information about the
average of measured values from all sensors in anarea than the individual measured value of a single
sensor. More details about the utilizations of
epidemic aggregation protocols are given in the next
section.
APPLICATION CASE STUDY
A case study of the monitoring system using
epidemic aggregation protocol related to urban
environmental aspects is studied to illustrate theiruse of the distributed systems in manufacturing. Theinteresting aspect is the urban flooding that occurs
when an urban drainage system (UDS) becomesoverloaded during an extreme rainy condition. As aresult, the wastewater treatment plant (WWTP) is
not able to treat the wastewater. This problem causes
sewer flooding and combined sewer overflows in an
urban environment, which are a potential risk tohuman life, economic asset, and the environment. In
general, the UDS is managed by a real-time control(RTC) system that requires the network to beembedded with sensors and actuators permitting the
network to be monitored real-time and regulated toadapt to the different rainfall events.
Many previous works of RTC are based on
centralized systems that introduce several problems
due to the large amount of data to be read, managed,
and processed. The drawbacks of centralized
systems include: 1) a complex mathematical modelof network is required, 2) the central unit needs to beconnected with all physical parts, and 3) a single
failure in any part of the system, especially thecentral unit, can compromise the entire system.
In order to solve these drawbacks, adecentralized system is considered Reference [28]developed an urban drainage network of the city ofCosenza in Italy, which adopts the decentralized
real-time control (DRTC) system based on a
distributed agent-based architecture and specificallyan epidemic protocol, which exhibits good
performance, and fault tolerance properties. The
characteristics of the systems are shown as follows:

EPIDEMIC AGGREGATION PROTOCOLS
An epidemic protocol or a gossip-based protocol
aims to solve problems in an extreme-scale
distributed system. The definition of an epidemic
protocol is generally a bio-inspired communicationand computation, which takes over the concepts of avirus-spreading mechanism and the gossip mannersof human. The characteristics of the protocol arerobustness and scalability with respect to a global
communication paradigm based on a deterministic
interconnection network [6]. Epidemic protocols use
randomized communication as the principle
mechanism in order to achieve these characteristics.
A number of applications based on epidemic
protocols have been proposed to serve different
purposes in different environments. Examples ofthese applications are: Peer-to-Peer (P2P) overlay
networks [7], distributed computing [8], mobile ad
hoc networks (MANET) [9]-[11], failure detection[12],[13], exascale high performance computing[14]-[16], data mining [17]-[18], data aggregation[19]-[22], and wireless sensor networks (WSN)[23]-[25].
Several epidemic protocols have been proposed-

255

Autonomy: Each agent is self-aware and has aself-behavior. It observes the environment,cooperates with others, and plans its execution

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

autonomously.
Local views: None of the agents have a fullglobal view of the whole environment. However,its performance is solely based on the quality of
local information.
Decentralization: There is no master agents
controlling the others, but the system is built
from the interaction of peer agents.

from gateways, which are sensors that communicate
with the base station.

The results are generated by using the Strom
Water Management Model (SWMM), an opensource computer model for the simulation ofhydrodynamic water and pollutant transport in sewer
systems. The process to balance the water level
throughout the conduits is simulated as the main
contribution in their work. The water balancing
process consists two tasks: 1) Computing the
average water level in the generated network
accomplished by epidemic protocol and, 2)
Triggering the gate in order to bring the water level
closer to its average value.
Reference [28] confirms that epidemic protocol
is able to support UDS to control water levelsuccessfully, ensuring a full utilization of the actual
storage capacity of the system.

a)Centralized systemsb) Decentralized systems
EXPERIMENTAL SCENARIO
Fig. 1The experiments in this study have adopted thescenario from the case study mentioned in theprevious section. The simulated scenarios are shownin the context of Industry 4.0, specifically in
manufacturing systems under smart factory practices,where all the work units are connected. Machines,
sensors, mobile devices, computers, laptops, andservers are some of the examples of the work units
in smart factory practices. The simulation presents
the activity in the manufacturing systems in terms ofmonitoring the system status in order to performsystem maintenance. The goal of the experiments isto evaluate the accuracy of a global aggregation
computation in different network environments:
decentralized and centralized systems by mean ofsimulation. Fig. 1 presents two different
architectures of simulated scenarios, which include
centralized systems and decentralized systems.
In this study, the systems consist of two classesof work units: a base station and sensors. The basestation’s objective is to monitor the status of thesystem based on the data from the sensors. In
centralized systems, a base station will compute theglobal aggregation by processing all of local data
sent by every sensors in the system. In general, abase station is a hub of data in centralized systems
whereas decentralized systems do not have any hubs.
Each of the sensor is distributing its local data to thesystem while processing the global aggregation
locally. A base station aims to monitor and provide
the global aggregation by obtaining the information

Architectures of simulated scenarios.

In comparison with the case study, each sensor
represents as an agent that maintains the measured
value as local data. The differences between the casestudy and the simulation are that the global
aggregation in the case study is the average of themeasured values, whereas the global aggregation in
the simulation is represented in terms of a maximum
value.
EXPERIMENTAL RESULTS
The experimental results and their analysis arepresented in this section. The simulations have been
completed in PeerSim [29], a discrete-event basedPeer-to-Peer simulator developed in Java. The
simulations are based on an asynchronous networkmodel with a network latency. Each sensor contains
the local data initialized with uniformly distribution
between 1 and 100,000, and the base station will
monitor the system by computing the maximum
value among the local data. Message loss is also
introduced and included as one of the main
parameters in the simulations. The value of theparameter indicates the possibility of message loss inpercent.
For decentralized systems, the global aggregation
is executed by an epidemic aggregation protocol.
The protocol is based on push-only gossip-based
communication modified from the SI model, one of
the epidemic dissemination algorithms [30].
256SEE -USQ, Brisbane, Australia, Nov.13-16, 2017

Algorithm 1 presents the mechanism of epidemic
aggregation protocol where v is local data and j is aremote sensor. Every sensor uses the protocol toestimate and distribute the global aggregation. Whenthe base station requires the global aggregation, it
will send a request message to a gateway of thesystem, and then the gateway will reply its current
estimated maximum value to the base station. In thiswork, the base station will make a request to a single
fixed gateway.
For the centralized systems, the base station willcollect the local data from every sensor to find the
maximum value.

systems. The performance index is presented as theaccuracy of the global aggregation.
Convergence Speed
This section shows how fast sensors candistribute the information across the system whendifferent percentages of message loss occur. The
results were collected from five trials with fivedifferent random seeds to avoid any experimental
biases. The standard deviation of local estimatedmaximum value at each sensor is used to determine
the convergence speed.

The general configuration of a simulation isbased on the evaluation criterion and the objectivesof this study. The total number of work units using
in this study is 1,000, which includes a single basestation and 999 sensors. The initial topology
depends on the models of simulated scenarios. For
centralized systems, the initial topology is similar toa client-server architecture: a server (base station)
contains a completed list of work units while clients(sensors) contain only a connection to the server. In
contrast, the initial topology for decentralized
systems is similar to a random graph that all sensors
are randomly connected while a base station can
only communicate with a gateway.
In decentralized systems, an epidemic
membership protocol is required in this scenario.
Epidemic membership protocols offers mechanisms
intended to maintain the connectivity of the systems
in terms of overlay topology [33]. Each sensor holds
the local cache containing the connections to 20
random sensors. As a result, each sensor willrecognize approximately 2% of other sensors. In
each cycle, one-fourth of the connections in the local
cache will be exchanged with other sensors due tothe mechanism of an epidemic membership protocol.
As a result, the structure of the system is continually
rewired in every cycle. On the other hand,centralized systems are not required rewiring thestructure, thus epidemic membership protocols are
not taken into account.
The results can be categorized in two sets andpresented in the following sections. First, theconvergence speed of epidemic application in
decentralized systems is examined, specifically theintention of the results showing how message loss
affects the convergence speed. Second, theperformance of base station is evaluated in bothFig. 2

Convergence
speed
with
possibility of message loss.

different

The effect of message loss to the convergence
speed can be observed from the results. Fig. 2 shows
the average standard deviation of the local estimatedmaximum over five trials. The y-axis is the standard
deviation and the x-axis is the number of cycles. A
curve in the chart indicates a convergence to thetarget value.
At the beginning of the simulation, it is expectedthat the standard deviation is high because there isno sensors that is able to determine the maximum
value. After the first cycle, the standard deviation isdecreasing which shows that each sensor is startingto generate the maximum value. Different
possibilities of message loss including 0%, 10%,
20%, and 30%, were simulated for the evaluation.
Without message losses in the network, Epidemic
protocol provides the fastest convergence speed andit will be slower with a higher possibility of message
loss.
System Accuracy
This set of simulations aims to evaluate theaccuracy of the systems between decentralized andcentralized systems when message loss occurs. Eachsimulation was run for 100, 300, and 700 cycles andwas repeated five times with different random seeds
in order to compute an average number of257

SEE -USQ, Brisbane, Australia, Nov.13-16, 2017inaccuracies. The base station will compute themaximum for once at a cycle.

Table 2 shows that message loss has a correlation
to the accuracy. The number of inaccurate
estimations is increasing with the higher possibilityof message loss. The best result comes from
centralized systems which claims that the estimationof the base station are seamless regardless tomessage loss; however, the systems also receive agreat suffer when message loss is considered. The
system usage during a long period will lead to higher
number of inaccuracies. In contrast, the long usageof decentralized systems does not affect an increasein the number of inaccuracies because they will only
occur when the system is not completely distributedwith the information. Nonetheless, a delay of
information distribution is a necessary fordecentralized systems. Figure 3 and table 2 showthat there is a relationship between the convergence
speed and the number of inaccuracies indecentralized systems. The systems with the fastest
convergence speed have the lowest number of
inaccuracies.

This work has investigated the effect of systems
architectures, centralized systems and decentralized
systems, to the accuracy of global aggregation. The
characteristics of these architectures are alsomentioned in this study. Epidemic aggregation
protocols are used as the key for information
distribution in the decentralized systems. The maintask of these protocols is to provide a service todisseminate and generate the global information.
The sets of results were produced under message
loss conditions. By evaluating the accuracy of thedecentralized systems over the centralized systems,
the results show that message loss have negative
effect to the accuracy of the system and it isinteresting to notice that the long period of system
usage does cause higher inaccuracies in thecentralized systems when message loss occurs, but
not in decentralized systems. In addition, when there
is no message losses, centralized systems run
perfectly without any such inaccuracies while
decentralized systems still have some error at the
beginning of the simulations. These results can draw
the conclusion that decentralized systems are
suitable under the condition that the messages can be
missing. On the other hand, centralized systems
should be selected when the messages areguaranteed to be delivered.
In order to achieve the practical implications,further study on distributed systems in a real world
manufacturing systems, e.g. node churn, information
retrieval from multiple gateways and sub basestations, are required for future work. Another aspect
to consider is how to improve the convergence speedof epidemic aggregation protocols under the context
of Industry 4.0 with the variety of environmental
conditions and case studies.

CONCLUSIONREFERENCES

Within the Industry 4.0’s context, one of thesmart manufacturing features is to focusing on theestablishment of the high-tech communication
between not only humans but also machines in orderto reach the goal of the smart factory practices.
Industry 4.0 promises increased networking of thesemachines, which can be highly accurate andconsequently customized to manufacture individual
outcomes.
Centralized systems that are currently used in
any industries require a single control center or hub
to collect all required data to create a global
information that can potentially suffer from being
inaccurate, especially when messages are missing.
This consequently results in poor decision making
and most importantly, leading to an organization’s
future irreparably. Decentralized systems, however,redesign the networking system to allow eachworking unit to contain a global information without
using any hubs.

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Table 2 Average number of inaccuracies from thebase station
Centralized Systems
MessageLoss

100
cycles300
cycles700
cyclesDecentralized Systems
100
cycles300
cycles700
cycles

0%

0

0

0

7.6

7.6

7.6

10%

11

30.4

72.2

11.8

11.8

11.8

20%

19.6

61.8

146.6

12.4

12.4

12.4

30%

32.2

92.4

206

16.8

16.8

16.8

258

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

Descent”, in SIAM Journal on Optimization, vol.
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[8] Di S, Wang C L, and Hu D H, “Gossip-based
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[9] Vahdat A, and Becker D, ”Epidemic Routing for
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[10] Ma Y, and Jamalipour A, “An epidemic P2P
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[11] Novotny P, “Fault Localization in ServiceBased Systems hosted in Mobile Ad Hoc”,
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[12] Van Renesse R, Minsky Y, and Hayden M, “A
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[13] Ahn J H, and Kim C Y, “Gossip-Pull Systembased Dissemination Protocol Satisfying
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[14] Strakov H, Niederbrucker G, and Gansterer W
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[15] Soltero P, Bridges P, Arnold D, and Lang M,“A gossip-based approach to exascale systemservices”, in Proc. of the 3rd Int. Workshop on
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[19] Kempe D, Dobra A, and Gehrke J, “GossipBased Computation of Aggregate Information”,
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[26] Bawa M, Garcia-molina H, Gionis A, andMotwani R, “Estimating Aggregates on a Peerto-Peer Network”, Technical Report. Stanford
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259

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

NUMERICAL ANALYSIS OF NONLINEAR MODEL OF SFRC SLAB
AND NONLINEAR SUBSOIL MODEL IN INTERACTION
1, 2Jana VASKOVA1, Radim CAJKA2
Faculty of Civil Engineering VŠB-Technical university of Ostrava, Czech Republic

ABSTRACT
Experimental measurements of concrete slab in interaction with subsoil are compared with numericalanalysis based on Finite Element Method FEM. Experimental measurements are conducted with using ofexperimental device constructed at the Faculty of Civil Engineering VSB – Technical University of Ostrava. In
this article several types of nonlinearities enters into FEM analysis. Subsoil-structure interaction requires aniterative solution procedure - and therefore structural nonlinearity. Material nonlinearity was used in the
numerical model of slab. This model also allows the creation and development of cracks in concrete - similar as
during the experimental load test. Material nonlinearity was also used in the numerical model subsoil - to ensureof apposite subsoil behaviour. The purpose of this paper is to compare resulting deformation of the slab withvalues observed during experimental loading test.
Keywords: Foundation Structure, Experimental Measurement, Soil – Structure Interaction, Interaction Models,
FEM Calculation.

interaction system "subsoil - foundation structure".
However, the question is, how accurate is input dataand parameters entering the calculations. Both, 2D
and 3D finite elements, can be using to solve of
numerical analyzes of the complete interaction
systems and also simplified interaction systems.

INTRODUCTION
With the beginning and subsequent developmentof computer technology, numerical methods havealso been used to solve the interactions between baseand subsoil. The most well-known numericalmethods are Boundary Element Method (BEM) and
Finite Element Methods (FEM). Currently (and also
in the past) many experts have been dealt withnumerical model based on Finite Element Method(FEM) – eg. Zienkiewicz a Taylor [1], Králik,Jendželovský [2], Kolář, Němec [3]. The mostwidely used software, which solve interaction tasks,
are Scia Engineer, Ansys, Trimas, MKPINTER,
RFEM a RF-Soilin and Plaxis. Despite many
commercial software and non-commercial software,
a computational model was not still found toaccurately capture the behavior in interaction of thefoundation structure and subsoil. The difficulty ofdesigning an accurate static design of foundation
structures lies in several aspects, for example theinfluence of physical-nonlinear behavior of thestructure or the uncertainty associated with thedescription of the properties and behavior of thefoundation soil, because it is natural material and its
properties cannot be determined unambiguously.
Despite these uncertainties in input parameters,
Finite Element Method (FEM) is an excellent
computing method for a whole range of tasks,
including interaction tasks. The Finite Element
Method (FEM) allows solution of a so-called
complete interaction system including "subsoil foundation structure - upper structure". Complete
interaction system is more demanding to compute,but provides more accurate results than a simplified

EXPERIMENTAL LOADING TEST
A combination of experimental tests, laboratory
tests, field tests and numerical modelling is optimal
to obtain reliable results of analyses of subsoilstructure interaction. Combination of all theforegoing approaches was also used in this paper. In
2016, experimental loading test of concrete slab was
realized using the experimental facility built incampus of Faculty of Civil Engineering, VŠB Technical University of Ostrava in the Czech
Republic, see Fig. 1. For this experimental loading
test, numerical analyses have been done in the
program Ansys, Plaxis, Scia Engineer, MKPInter, allbased on the finite element method (FEM).

Fig. 1 Experimental equipment, called Stand
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

where
E0 – modulus of deformability at the surfacez – z-coordinate (depth)m – coefficient depending on Poisson's ratio 
Value of modulus of deformability Edef
continuously increases with increasing depth
according to the formula (1) in an inhomogeneous
half-space. When the subsoil model is created asinhomogeneous nonlinear continuum, results are
significantly less affected by the selected geometry
subsoil model than subsoil model created as a linear
homogeneous continuum. Inhomogeneity of thenumerical model of the subsoil was created by
dividing into separate layers (Fig. 3), in which themodulus of deformability growed in layers.

Fig. 2 Experimental loading test
The concrete was mixture of C 25/30 XC2. It
was concrete with consistency S3, with the limit
value of the minimum content of cement (CEM I
42.5 R VL) of 280 kg/m3 and for the maximum grain
size to 16 mm. A modulus of elasticity of concrete
was obtained with laboratory tests, which wereconducted in the day when the slab was loaded. The
modulus of elasticity was E = 19.75 GPa. Poisson's
ratio of concrete was = 0.2. Compressive strengthof concrete fc = 20.03 MPa was also obtained bylaboratory tests. The slab dimensions were 2.00 x
2.00 x 0.15 m. The slab model was loaded byhydraulic press in the slab center, see Fig. 2. The
load area was 400 x 400 mm. The subsoil had theseproperties – Poisson coefficient = 0.35, modulus
of deformability Edef = 12.5 MPa. A load step
method was used at 25 kN/30 minutes. Loading was
carried out up to the load during which theexperimental load test of slab was failed (345 kN). A
load of 345 kN applied on the loading area (400 x
400 mm) was also used in numerical analyses.
NONLINEAR NUMERICAL MODELINHOMOGENEOUS HALF-SPACE

OF

Soil is naturally and heterogeneous material.
Because of it, its properties differ from idealizationof linear elastic, isotropic and homogeneous material.
That's the reason why the calculated values ofsettlement differ from the actual settlement. This canbe appropriately dealt with using the inhomogeneous
half-space [4]. In inhomogeneous half-space themodulus of deformability of the subsoil varies
continuously with the increasing depth. In theinhomogeneous half-space there is a different
concentration of the vertical stress in the axis of thefoundation than that in the homogeneous half-space.
The Equation (1) based on the minimum of
deformation work was derived by Frölich [5].
1
(1)
E def  E0 z m
where m   2
Fig.

3 Homogeneous half-space model andinhomogeneous half-space model, ANSYSNUMERICAL ANALYSES IN ANSYS
3D numerical model was created in ANSYS. The
input data were taken over the experimental loading
test. Subsoil model was created as a threedimensional model using 3D finite element SOLID
45. Subsoil model was created as homogeneous halfspace and also as inhomogeneous half-space, see Fig.
3. Based on a parametric studies [6], [7], [8], area
representing the subsoil was 8.0 x 8.0 x 8.0 m.
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Physical nonlinearity associated with material
properties was used. Nonlinear material model was
performed by Drucker-Prager model. SOLID 65 wasused for spatial modelling of experimentally loadedslab. It was necessary in the numerical model to take
into account the influence of nonlinearities andcracks in concrete (occurring during the continuous
loading of the concrete slab). These were taken into
account by the use of the finite element SOLID 65.
SOLID 65 enables non-linear calculation of concrete
structures by Willam - Warnke criterion. This modelof behavior of quasi-brittle material considers bothtensile damage (forming cracks) and pressuredamage (crushing the material). Fracture propertiesof concrete are also described eg. [9].
If spatial numerical model is created using 3D
finite element, results are largely dependent on thechosen parameters entering into the calculation. It
has been proven by parametric analysis in author´sarticles, eg. [6], [8]. Important parameters
influencing the results of numerical analysis are,among other, the size of the modelled area
representing the subsoil, the choice of boundary
conditions or mesh size.

base of the subsoil model, because it represented theterrain. The boundary conditions in numericalanalysis in ANSYS were the same. The finiteelement mesh was created automatically by 15 nodal
finite elements. The Mohr - Coulomb material
model was used for the subsoil and consequently,
the difference between tensile and compressive
strength can be described.
When the subsoil model was created as ahomogeneous half-space (Fig. 4), the maximum
calculated vertical deformation at the center of theslab was 13.23 mm.

NUMERICAL ANALYSES IN PLAXIS 3D
FOUNDATION

Fig. 4 Homogeneous half-space model, PLAXIS 3D
FOUNDATION

Model in the PLAXIS 3D FOUNDATION
program, despite the title, it is not a full 3D model ofthe subsoil because the spatial model is created bystretching the cut to depth. In PLAXIS 3D
FOUNDATION, therefore, a concrete slab was
created as a 2D linear model, which was also
computed for ANSYS for comparison purposes(above).
PLAXIS 3D FOUNDATION is primarily used tosolve geotechnical problems. In this computing
system is a specialized module designed to analyze
subsoil-structure interaction. The 3D numericalmodel in PLAXIS 3D FOUNDATION was createdwith the same geometry of the subsoil model as innumerical analyses in ANSYS - in order to compare
the results obtained by numerical analysis in
ANSYS. The area representing the subsoil model
was 8.0 x 8.0 x 8.0 m. The subsoil model is createdas a homogeneous half-space and inhomogeneous
half-space, as in ANSYS including the same valuesof the modulus of deformability. All input
parameters are the same as input parameters innumerical analyzes in ANSYS and therefore
according to experimental load test. The boundary
conditions are automatically created in the PLAXIS
3D FOUNDATION and cannot be changed. The
boundary conditions prevent by horizontal shifts of
the nodes in the walls of the subsoil model and thevertical and horizontal shifts of the nodes in thelower base of the subsoil model. No boundary
conditions prevented the nodes shifting in the upper

The deformation measured during theexperiment (using the sensor closest to the slab
center) was 15.05 mm. In the inhomogeneous modelof the subsoil (Fig. 4) the value of the modulus ofdeformability increased with the depth according toformula (1).

Fig. 5 Inhomogeneous half-space model, PLAXIS
3D FOUNDATIONIn the PLAXIS 3D FOUNDATION the subsoil
model was divided into 32 layers (Fig. 5). In theselayers the value of the modulus of deformability
gradually increased with the depth (as in ANSYS).
When the subsoil model was created as theinhomogeneous half-space, the maximum calculated
vertical deformation at the center of the slab was
9.68 mm (Fig. 4).

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

zero, i.e. the influence of the surrounding soil
environment has been taken into account.
The same values were entered in the calculation
as in all previous programs in which this task wasalso solved (ANSYS and PLAXIS 3D
FOUNDATION). Parameters of the geological
profile were defined by the modulus ofdeformability Edef = 12.5 MPa and the Poissoncoefficient . In addition, the soil massdensity γ = 20.0 kN/m3, the structural strength
coefficient m = 0.2 (according to EC 7 [12]) and thelayer thickness (defining the geological profile) h =8.0 m were given. In this model, the maximum
calculated vertical deformation in the center of theslab was 6.26 mm (Fig. 6).

NUMERICAL ANALYSES IN SCIA ENGINEER
Subsoil-structure interaction can also be solved
using the SCIA ENGINEER, commercial software[10]. The results then was compared with the results
obtained by the 3D numerical models created in the
ANSYS, PLAXIS 3D FOUNDATION and with theexperimental values.
In SCIA ENGINEER [10], the so-called standard
model of subsoil according to ČSN 73 1001 [11] isapplied, which is based on the theory of elastic halfspace of modified structural strength of soil. If thedesign in the program is modeled according toEurocode 7 [12], the value of the structural strength
coefficient is automatically m = 0.2 and isunchanged. It is a surface model of the subsoil,
which is characterized by the parameters Cx, Cy, Cz.
The properties of the modeling subsoil are inter alia
entered through the parameters of the subsoil C1x,
C1y, C1z, and C2x, C2y [10]. C1z is the compressibility
parameter of the elastic subsoil in the z-axis
direction, which represents the resistive elastic
resistance against the vertical displacement w. C2x
and C2y are shear deformation parameters that take
into account the shear interaction of the subsoil. C1x
and C1y are parameters of pliability of the subsoil inthe x-axis direction, respectively y-axis direction,
which represent resistance against horizontal
displacement u, resp. v (shifts in the plane of theslab). The SCIA ENGINEER offers calculation
module SOILIN to solve the interaction offoundations with the subsoil. SOILIN calculates theparameters of the subsoil C1z, C2x and C2y.
Parameters C1x, C1y are always specified by the user.
The SOILIN module calculates the settlement basedon the elastic half-space. Then subsoil parameters C
are automatically calculated. Whereas the subsoil
parameters C affect the contact stress, and thisaffects settlement, and all interdependencies arevalid also conversely, it is an iterative calculation.
The iteration cycle is finished when the calculated
value of shift or calculated value of contact stress in
two consecutive cycles is almost unchanged (use ofquadratic norm). In the author's article [10] thedependence of the deformations calculated by the
SOILIN module on the input values of the individual
subsoil parameters was monitored and evaluated.
Differences in deformations occur depending on theparameters C2x and C2y. If C2x = C2y = 0, theseparameters do not enter the SOILIN iterative process
and the influence of the surrounding soil
environment is not taken into account in thecalculations. If the parameters C2x and C2y are nonzero, they enter the iterative calculation and theinfluence of the surrounding soil environment istaken into account [10]. In calculation of theinteraction of the subsoil with the slab loaded during
the experiment, the SOILIN module was used. The
input values of the parameters C2x and C2y are non-Fig. 6 Surface subsoil model, SCIA ENGINEERNUMERICAL ANALYSES IN MKPINTER
To compare the results of the solution of theinteraction of the subsoil with the concrete slab, thistask (with the same input values) was also analyzed
in the non-commercial program MKPINTER [13],[14]. Calculation of the deformations and internal
forces of the slab is done by the finite element
method (FEM) using isoparametric plate elementswith shear effect. The course of contact stress affects
the deformation of the slab and of the subsoil too. To
cause the contact stress of the same deformation of
the slab and subsoil in this nonlinear interaction, thissolution is performed by an iterative method. The
calculation of stress, settlement and contact stress issolved by the universal method of calculation using
Jakobian transformation. In MKPINTER, subsoilstructure interaction is solved using numericalintegration calculations of stress and settlement of
the modified elastic half-space by structural strength.
For more information about MKPINER see [13],[14].
COMPARISON OF RESULTS
This article compares the resulting verticaldeformations calculated in the software based on
FEM - ANSYS, PLAXIS 3D FOUNDATION, SCIA
ENGINEER, MKPINTER FEM, and also verticaldeformations calculated according to recommended
normative procedures.
In the graph (Fig. 7), the vertical deformations
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

calculated by the various computational programs
and procedures are compared. The verticaldeformations calculated by the solution of theinteraction of subsoil with concrete slab in ANSYS,PLAXIS 3D FOUNDATION, SCIA ENGINEER
and MKPINTER are compared. The settlement
calculated according to the normative procedures
recommended in ČSN 73 1001 [11] and Eurocode 7[12] are also included in the chart.
The red full line indicates the slab deformation
measured at the last loading test step, i.e. at a time
when the slab was significantly damaged by cracks.
The graph shows vertical deformation dependence
on the depth of the 3D subsoil models created in
ANSYS (yellow and green) and PLAXIS 3D
FOUNDATION (blue). The light lines indicate
verticaldeformations
calculatedonthehomogeneous model of the subsoil. The dark lines
indicate the vertical deformations calculated on theinhomogeneous model of the subsoil in which thevalue of modulus of deformability increases with thedepth. In tasks where the slab was modeled as a 2D
linear model (without the impact of cracks), there
was a very good accordance in the results fromANSYS (dark and light yellow dashed line) and
PLAXIS 3D FOUNDATION (dark and light blue
dashed lines). Due to the impact of the cracks in theconcrete slab model is not taken into account, thevertical deformations calculated by the above
mentioned models are less than the measured
deformation of the already extensively damaged
concrete slab. This is also valid for verticaldeformation obtained in SCIA ENGINEER (purple)
and MKPINTER (pink), in which the concrete slab
was also created as a 2D linear model without the
impact of cracks. There are the subsoil surface
model based on the elastic half-space of themodified structural strength of soil (according toEC 7 [12], m = 0.2) in programs SCIA ENGINEER
and MKPINTER, in comparison with ANSYS and
PLAXIS 3D FOUNDATION. It is a surface modelof the subsoil and its results do not depend on thechosen depth of the area as it is with 3D models in
ANSYS and PLAXIS 3D FOUNDATION. Using
the procedure according to ČSN 73 1001 [11], thedepth of the deformation zone was 4.15 m and thesettlement was 6.55 mm for m = 0.1 (brown dottedline with a cross). The value of the correction
coefficient of overload m = 0.1 was determinedaccording to the table in ČSN 73 1001 [11].
According to Eurocode 7 [12], it is always m = 0.2,
the depth of the deformation zone is 3.25 m and thesettlement was 5.89 mm (black dotted line with across). For calculations of the depth of active zone
according
to
the
both
above-mentioned
recommended standards, it is clear from the graphthat different models of subsoil and slab models(which are not uniquely specified in the standards)
can obtain a large range of calculated deformation

values.
The calculations whose resulting verticaldeformations were greater than the measured
deformations of the damaged slab are marked bygreen lines. Specifically, this is the deformation
calculated in the ANSYS, in which the concrete slab
was created as a 3D non-linear model with influenceof cracks. The highest values of the calculated
deformations indicate that in the numerical analyzes
performed in this way the influence of the cracks
was taken into account, leading to a reduction of
stiffness of the concrete slab model and its greater
deformations. Of course, these deformations are also
dependent on the subsoil model created as ahomogeneous continuum (light green) and as aninhomogeneous continuum (dark green).
The average difference was of about 66% between the results of the 2D linear slab model
without influence of cracks and the 3D nonlinear
slab model with influence of cracks (in thecomparison the deformations obtained from the
ANSYS). The average difference between thecalculated deformations in the homogeneous andinhomogeneous subsoil models was about 29%. The
3D nonlinear model of the subsoil has always beenretained when comparing.

Fig. 7 Comparison of results – deformations

CONCLUSION
This article compares the resulting verticaldeformations calculated in the software based on
FEM - ANSYS, PLAXIS 3D FOUNDATION, SCIA
ENGINEER, MKPINTER FEM, and also vertical
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

deformations calculated according to recommended
normative procedures.
A very good accordance was in the results fromthe ANSYS and PLAXIS 3D FOUNDATION programs in which 3D finite elements were used,
and from the SCIA ENGINEER and MKPINTER programs, which in which 2D finite elements wereused. A significant difference in the calculated
deformations occurred when comparing the resultsfrom the ANSYS and PLAXIS 3D FOUNDATION
with results from the SCIA ENGINEER and
MKPINTER in which the subsoil-structureinteraction is solved based on the theory of elastic
half-space modified by structural soil strength. A
significant difference in the calculated deformations
occurred when comparing the results from the
ANSYS and PLAXIS 3D FOUNDATION withresults from the SCIA ENGINEER and MKPINTER
in which the subsoil-structure interaction is solved
based on the theory of elastic half-space modified bystructural soil strength.
For calculations of the depth of active zone
according to the recommended standards, it is clearthat different models of subsoil and slab models(which are not uniquely specified in the standards)
can obtain a large range of calculated deformation
values.
Although it has been shown that the resulting
deformation of the interaction of foundation
structure and subsoil created as an inhomogeneouscontinuum model provide deformations to betterdelineate the real deformations, prudence is in placewhen creating a numerical model of subsoil createdby spatial finite elements. By choosing the geometryof the solved area without previous experience withthe aforementioned parameters, a numerical model
can be created that would adversely affect thecalculated deformations and lead to dangerous andunreliable results.

[4] Feda, J., Tenseness of subsoil and calculation
methods for calculation of final subsidence,
ACADEMIA, 152 pages, 1974. (In Czech)[5] Frölich, O. K.: Druckverteilung im Baugrunde,
Mit
Besonderer
Berücksichtigung
derPlastischen Erscheinungen, Vienna, 1934.
[6] Labudkova, J. Cajka, R., Numerical analyses ofinteraction of steel-fibre reinforced concreteslab model with subsoil, Frattura ed Integrita
Strutturale, Volume 11, Issue 39, January 2017,
Pages 47-55, 2017.
[7] Cajka, R., Labudkova, J., Mynarcik, P.,
Numerical solution of soil - foundationinteraction and comparison of results withexperimetal
measurements,
International
Journal of GEOMATE, Volume 11, Issue 1,
2016, pp. 2116-2122.
[8] Labudkova, J., Cajka, R., Application of an
Inhomogeneous Halfspace for the Solution ofFoundation-Subsoil Interaction based on the
Finite Element Method, in Proceedings of theFifteenth International Conference on Civil,
Structural and Environmental Engineering
Computing, Civil-Comp Press, Stirlingshire,
UK, Paper 9, 2015. doi:10.4203/ccp.108.9[9] Sucharda O., Pajak, M., Ponikiewski T.,
Konecny P., Identification of mechanical andfracture properties of self-compacting concretebeams with different types of steel fibres using
inverse analysis, Construction and Building
Materials,
138,
pp.
263-275,
2017,
doi:10.1016/j.conbuildmat.2017.01.077.
[10] Labudkova, J., Cajka, R., Numerical analysis ofinteraction of steel-fibre concrete slab with
subsoil and comparison with values measured
during experimental loading test. Proceedings oftheInternational
Conference
FIBRE
CONCRETE, Volume 2015-January, 2015,
Pages 292-301, 8th International Conference
Fibre Concrete 2015: Technology, Design,
Application, FC 2015; 10 – 11 September 2015,
Prague; Czech Republic;[11] Eurocode 7 - Geotechnical Design, Part 1:
General Rules, European Committee forStandardization. EN 1997-1: 2004, Brussels[12] ČSN 73 1001. Foundation engineering.
Foundation soils under flat foundations, Czech
Standards Institute, Prague (in Czech).
[13] Cajka, R., Analysis of Stress in Half-space
using Jacobian of Transformation and Gauss
Numerical Integration, Advanced Materials
Research, Switzerland, p.178-186, 2013.
[14] Cajka, R., Accuracy of Stress Analysis Using
Numerical
Integrationof
Elastic
Half-Space, Applied Mechanics and Materials,
Trans Tech Publications, ISSN: 16609336,
Switzerland, p.1127-1135, 2013.

ACKNOWLEDGEMENTS
This outcome has been achieved with thefinancial support of the project GACR No. 1608937S „State of stress and strain of fiber reinforced
composites in interaction with the soil environment“.
REFERENCES[1] Zienkiewicz, O. C., Taylor, R. L., The Finite
Element Method, Volume 2: Solid Mechanics,
Oxford, Butterworth-Heinemann, 479 p, 2000.
[2] Kralik, J., Jendzelovsky, N., Contact problem ofreinforced concrete girder and non-linear
Winkler foundations, Geomechanics 93,
Ostrava, Pages 233-236, 1994.
[3] Kolar, V., Nemec, I.: Modelling of Soil
Structure Interactions, Prague, 336 p, 1989.

265

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

AN OVERVIEW OF THE IMPACTS OF SUSTAINABLE HOUSINGDESIGN ON ENERGY EFFICIENCY OF THE AUSTRALIAN
HOUSING
Javad Asad Poor 1,2; David Thorpe 2; Yong Goh 3
Javad.asadpoor@usq.edu.au; david.thrope@usq.edu.au; Yong.Goh@usq.edu.au
Department of Architecture, Mashhad Branch-Islamic Azad University, Mashhad, Iran. 1
School of Civil Engineering and Surveying, Faculty of Health, Engineering, and Sciences, University ofSouthern Queensland, Education City, Sinnathamby Blvd, Springfield Central QLD 4300, Australia. 2
School of Psychology and Counselling, Faculty of Health, Engineering, and Sciences, University of Southern
Queensland, Ipswich Campus, 11 Salisbury Rd, Ipswich, Queensland 4305, Australia

ABSTRACTThe building industry has a substantial potential for short-run and cost-effective greenhouse gases emission
mitigation with long-term positive sustainability impacts. However, the main problematic issue in the building
industry is the existence of large number human-based factors, which makes the operation of the mitigation
action plans very complicated and detracts from the outcomes of the implemented plans in this area of industry.
The impacts of human-based factors are especially important in the area of small size residential buildings,
where a variety of stakeholders play serious roles in the development of the industry. In Australia, the residential
sector is the main component of the building industry and has a substantial responsibility in the energy
consumption of the country. One critical human-based factor in the residential sector is the occupants’
preferences, increasing substantially diversity and complexity of the dwelling units’ physical characteristics.
This paper intends to explain the role of feasibility assessment and design process in improving the energy
performance of the Australian residential sector. In responding to this aim, an overview of spatial, functional,
and physical characteristics of the Australian housing results in addressing the key characteristics of theAustralian housing preferences. The analyses show that the typological monotony, the owner-occupied housing,alongside occupants’ perceptual ability are a number of factors, facilitating the implementation of housing
efficiency plans in the early stages of housing decision making. The direction of other characteristics, e.g. floorarea, number of bedrooms, and number of people per dwelling units are somehow inefficient, stressing thedesigners’ supervisory roles in enhancing the housing preferences toward more efficient choices. According to
the analyses, the feasibility assessment and design process have potential to, directly and indirectly, impact theenergy demand of the Australian housing by enhancing physical characteristics of the units, regulating theoccupants’ housing preferences, and simplifying their daily life activities.
Keywords: Feasibility Assessment and Design Process; End-users’ Environmental Perceptions and Preferences;
Australian Housing; Energy Efficiency.
INTRODUCTION

building sector is responsible for 40 percent of thetotal energy consumptions, and the generation of
one-third of CO2 and GHG emission (United
Nations Environmental Programme, Sustainable
Buildings and Climate Change (UNEP SBCI), 2009).
The sector also has exceptional potentials for costeffective emission mitigation, so that it is possible todecrease up to 29 percent of the emission in the
sector without any financial costs (Allwood et al.,2012; Desmarais, et al. 2013). In small size
residential buildings, typological diversity of the
products, the complexity and diversity of
stakeholders, the direct impacts of occupants’attitudes and preferences, as well as the spread andmagnitude of energy use activities detract from theeffect of the mitigation actions plans (Cheng, 2010;

A successful emission mitigation action planrequires a combination of bottom-up flexibility andtop-down fixed rules, to achieve accountability andambition by means of broad participation (Centre for
Climate and Energy Solutions (C2ES), 2015). Basedon the 2005 target mitigation baseline, Australia has
a responsibility to cut down carbon dioxide (Co2)and greenhouse gas (GHG) emissions 26 percent by
2030 compared with the average global reduction
rate of 36 percent (Hasham, et al., 2015).
However, in achieving the Australian target
baseline, the building industry has a critical role,
because of the responsibility of the industry in theenergy consumption and the carbon emission. The

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regarding the emission mitigation in the residential
sector, the feasibility assessment and design stages
are highly responsible for improving the energy
demands of the buildings for both embodied andoperation energies (Allwood et al., 2012; Nasrollahi,
et al., 2013; Sattary and Thorpe, 2016; UNEP SBCI,2009).
In this regard, the study of Allwood et al. (2012)stressed that environmental sustainability relies
substantially on developing a production process,which is capable of employing the efficient materials
and reducing the demands, while the process has
ability to retain the function and service qualities. In
the housing production process, the decisions about
spatial and physical characteristics, and the function
and service quality are mostly made in the feasibility
assessment and design process.
Sattary and Thorpe (2016) also stressed the necessityof replacing the conventional materials with theenergy efficient materials in the production of the
new houses to decrease the embodied energy of thebuildings. Their study also highlighted thecontribution of feasibility assessment and design
stage in improving the sustainability of the housing
industry. Sattary and Thorpe (2016) revealed that thesustainable usage of the building materials would
make it possible to reduce the embodied energy ofthe buildings by up to 64 percent. Accordingly, thesustainable usage of the materials means theselection of the materials by considering theavailability of the resources, the energy consumptionof the mining and manufacturing process, thetransportation, and the installation, alongside thepossibility of employing reused or recycledmaterials, and the degree of environmentallyfriendly of the selected materials. The process of thematerial selection should be mainly developed in theearly stages of the feasibility assessment and design
process.
It is also evident that the energy-efficientarchitectural techniques and principles, e.g.
orientation, courtyard, window to wall ratios,
geographical location of windows, as well as crossventilation and shading devices have serious
contributions in improving the energy performanceof the residential buildings during the operational
phase (Nasrollahi, et al., 2013). Nasrollahi, et al.,(2013) stated that an efficiently well-designed
residential building is able to cut down the energy
performance of the units up to 65 percent, which issubstantially related to the decisions made during thedesign process.

Levine et al., 2007).
In the residential sector, end-users are, indeed,
the key driving forces in the development of the
housing sector compared with the other industries.
Therefore, improving the energy performance of thesector depends strongly on a proper attention to thebottom-up approach as the key concept inmaximizing the occupants’ participation parallel totaking into account the development of theefficiency rules alongside the investment on thetechnical aspects. This paper intends to explain thecontribution of the housing design process in
improving the energy performance of the Australian
housing sector and in overcoming the challenges.
The
spatial,functional,
andphysicalcharacteristics of the residential buildings influence
substantially the energy performance, and emission
production of the sector (United Nations
Environmental Programme, Sustainable Buildings
and Climate Change (UNEP SBCI, 2009). The
housing design process has a lot to contribute to themitigation, not only by the direct effects on thedwelling units’ physical characteristics, but also by
the indirect effects on the occupants’ environmental
perceptions, attitudes, and housing choice
behaviours (Levermore, 2008, Kwami et al., 2015).
This paper makes initially an overview of theliterature on the effects of the design process on theenergy performance of the residential buildings, thenexplains the capacities of the housing design inenhancing the energy performance of the dwelling
units in Australia.

LITERATURE REVIEW
According to UNEB SBCI (2009), the main factors
in the energy performance of the residentialbuildings are the building spatial and physicalcharacteristics, along with the end-users’ perceptions,attitudes, and behaviours. The study of Bawden &Williams (2015) also revealed that a number ofhousing characteristics, e.g. dwelling type,occupants’ income, and household composition havesubstantial impacts on the energy consumption of
the residential units. Australian Bureau of Statistics(ABS, 2013a) also indicated that the number ofpeople and the number of bedrooms per dwelling
unit affect significantly the energy consumption of
the units. However, Richard (2014) believed that in
the Australian residential sector, the current
benchmark of the energy consumption in theresidential buildings is substantially far from thesustainable level. However, it is believed that

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The remaining question is the impacts of thephysical, functional, and spatial characteristics,
arrangement, structure, and organization, e.g. size,
from, shape, depth, proportions, interconnections,
openness, and interrelationships, flexibility, andcomplexity along with the occupants’ housing
behaviours in improving the energy performance ofthe residential buildings in the total lifecycle of thebuildings including embodied and operation phases.
The feasibility assessment and design stages are
responsible not only for improving the buildings
capacities for employing passive techniques throughthe implementation of the sustainable and efficientmaterials, technologies, and principles, but also forarranging the buildings spatial characteristics,
structure, and organization, alongside regulating theend-users’ choice behaviours toward more efficientenergy consumption actions (Asad Poor 2014, 2012).
Moving beyond this level, housing design has
capability of improving end-users’ sense of place byenhancing the congruity of the physical settings withthe occupants’ motivations; hence has particular rolein improving their pro-environmental behaviours,
enhancing the overall efficiency of the residential
environment (Asad Poor, 2014, 2015; Morrison,
2011; Ramkissoon, 2013).
Although the housing design process has substantial
responsibility for improving the energy performanceof the residential buildings by improving thearrangement of the spatial layouts, and the end-users’
preferences, so far the research works have paid
proper little attention to this area. In the context ofAustralia, the current direction of housingdevelopment and the rapid growth of the number of
new housing units are the main reasons for the rapid
increase in the demands for energy in the residential
sector; hence the direction of the housingdevelopment overrode the outcomes of the
mitigation plans in the building sector (Beyond Zero
Emissions (BZE), 2013). This paper, therefore,
intends in explaining the contribution of thefeasibility assessment and design stages in
improving the energy performance of the Australian
housing sector, possibly obtained by moderating
end-users’ housing preferences and energy demands,
as will be discussed in the next sections.

flexibility of energy efficiency rules is more
beneficial for energy efficiency and emission
mitigation than up-down fixed rules based on meretechnological and engineering approach (BZE, 2013;
C2ES, 2015). This research employs a down-up
analytical model, stressing the potential contributionof individual housing units alongside the substantial
role of occupants’ preferences in enhancing theoverall energy consumption of the residential sector.
In studying human perceptions from their choice
behaviours, two possible methods are to look at
people’s revealed preferences based on their actual
choices (secondary data) or stated preferences basedon their intended choices (Collen & Hoekstra, 2001).
Since the nature of stated preferences is hypothetical,
referring to revealed preferences ensures the validityof analyses and the significance of findings if
reliable actual data would be available (de Vaus,
2002; Opoku & Abdul-Muhmin, 2010). It is also
believed that explaining occupants’ housing
preferences through an overview of the physical,
functional, and spatial characteristics of theirhousing environments is a reliable methodology for
explaining their perceptions (de Vaus, 2002; Asad
Poor, 2014).
In Australia, a number of online databanks, e.g.
Australian Bureau of Statistics (ABS) and Beyond
Zero Emissions (BZE) provide reliable data related
to the Australian housing characteristics, which areappropriate sources for tracking the Australian
housing trends. This research, therefore, employs
revealed preferences model and compiled thesecondary data from these online sources. The
analyses facilitate the representation of key
characteristics of the Australian housing; hence,
make it possible to explain the potential contributionof the design process in enhancing the energy
performance of the residential sector. The analyses
indeed explain the role of feasibility assessment anddesign process in improving spatial layout
arrangements and physical characteristics ofdwelling units, enhancing the energy performance ofthe sector through improving the overall efficiencyof the buildings and facilitating the occupants’s daily
life activities.
Mapping the key characteristics by merging thecompiled data through Microsoft Excel, the next
section initially discusses the critical aspects ofoccupants’ housing preferences. The section thenmakes a comparison between Australian residential
and non-residential sector to explain the substantial
role of energy performance of the housing sector in
overall energy consumption of the building andconstruction industry in Australia. Referring to theAustralian projected population (ABS, 2015b), thesection also calculates a number of future trends of
the Australian housing, representing the impacts ofthe current direction of housing development on
future energy performance of the Australian

RESEARCH METHODOLOGY
It is believed that congruity between theoutcomes of engineering and technological approachand occupants’ choice behaviours alongside the268

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

domestic sector. In final, addressing a previously
conducted research work, a feasibility assessment ismade to briefly estimate the potential contribution of
the design process in enhancing the energy
performance of the Australian housing. The section
ends up with a brief discussion on the different
components of sustainable housing design and thetechniques related to each component.

In this section, the housing characteristics will be
initially explained, and then a discussion on theimpacts of these characteristics on energy
performance improvement in the residential sector
will be discussed. In the discussion, the main effort
is to explain the impacts of end-users’ preferenceson the housing physical characteristics, and theimpacts of these preferences on the housing units
energy performance, and finally the contribution of
the design process and feasibility assessment inenhancing energy performance of the Australian
housing. Table 1 provides a brief picture of the key
characteristics of the Australian housing, which
reveals the rapid and dramatic increase in the
demands for more spacious dwelling units withhigher energy demands during the recent decades.

ANALYSES AND DISCUSSION
In discussing the responsibility of the feasibility
assessment and design stages in facilitating the
mitigation baseline of Australia, it is initiallynecessary to make an overview of the Australian
housing characteristics.

Table 1. Key Characteristics of Australian housing
No
1
2

Key Characteristics
Housing Type
Number of Rooms

3

Housing Size

4
5

Owner-Occupancy
Mortgage

6
7
8
9
10

Average Floor Area per
PersonNumber of Person per
Household
Number of Bedroom per
PersonSpare bedrooms
Proportion
Households

of

Lone

Description
Separate house standing on its own block: 79% (2012).
3 or more bedroom house: 70.3% ((2012)).
The number of rooms have increased from 2.8 to 3.1 (1976 –2014).
Overall average floor area increased from 149 to 207 Square
Metre (1984-2013).
Average floor area of the separate housing increased from 162
to 241 Square Metre (1984-2013).
Average floor area of the apartments increased from 99 to 134
Square Metre (1984-2013).
67% (2013-2014).
31% without mortgage, 36% with mortgage (using low-interest
loan for other financial purposes) (2013-2014).
The decrease in the outright owner-occupied housing from 42%
to 31% (1994-2014).
Almost 90 Square Metre (2012).
Decreased from 3.1 to 2.6 (1976 – 2014).
Increased from 0.9 to 1.2 (1976 – 2014).
Almost 80% of the households have more than 1 spare
bedrooms (2013-2014).
Almost 2,100,000 Households by 2011 (24.3%), estimated to be
increased to almost 3,300,000 households by 2036 (the growth rateof 63% with high demands for separate housing) (2013-2014).

Source: ABS (2012, 2013b, c, 2015a), de Vaus &Qu, (2015)
One of the factors that assist in explaining the
housing characteristics is the housing tenure andownership. 67 percent of the Australian households
live in owner-occupied houses, and from thispopulation, 31 percent are without any mortgages,
and the rest of them (36 percent) mostly uptake themortgage for other financial purposes rather than the
housing purchase (ABS, 2015a). According to ABS(2012), the proportion of owner-occupied houses in
269

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017separate houses is 88 percent of the total owneroccupied houses. This means that the owneroccupied separate houses are the most preferred
accommodation destination of the Australian
population, while they purchase the other housing
types for non-accommodation purposes, e.g. to haveincome from the rental payments or other financial
opportunities. It is also evident that the outrightowner-occupation has been dropped from 42% to
31% in the period of 1994-95 to 2013-2014. The
descending order of outright owner-occupied
housing makes it evident that the current direction of
housing development has been achieved with thecost of loaning and mortgaging.
In other words, an overview of the Australian
housing shows that 3 or more bedroom separate
houses are the most important part of the building
sector in Australia, and has significant responsibility
in the energy performance of the building sector inthis country. However, there are a number ofmultiple barriers that make the implementation of
the mitigation plans in the residential buildings quite
complicated and practically difficult, one of which isthe diversity and complexity of the building types
and characteristics, and the other is the diversity ofthe stakeholders along with the absence of the endusers and the separation of and the distance between
the costs paid by the owners and benefits received
by the occupants (Cheng, 2010; Levine, et al., 2007;
UNEP SBCI, 2009). These factors detract from theleverage of the mitigation action policies; hence,
make it necessary to find out a practical solution forthe problem. The most preferred housing type andtenure provide a suitable platform for eliminating a
number of barriers preventing from theimplementation of energy efficiency action plans in
the Australian residential sector, one of which is thediversity of the stakeholders, the second is theabsence of the end-users’ in early stages of housing
decision-making, and the third is the distance
between costs and benefits.
Looking at the housing type and tenure
characteristics, it is also necessary to consider someother characteristics related to the spatialorganization and physical settings of the residentialbuildings. Monitoring the changes happened to theAustralian housing characteristics over the last few
decades makes it possible to explain the direction of
housing development in the Australian context. Thechanges in the spatial and physical characteristics
makes it evident that the average floor area has
increased from 170m2 to 241m2 from 1985 to 2013
(ABS, 2013c). The average floor area per person has
also increased in the separate houses from 50m2 to
90m2 over the same period. The changes in the
average floor area of the separate dwelling units
from 2003 to 2013 shows a significant increase in
the average floor area of the separate houses (from235m2 to 241m2) comparing with the decrease in the

average floor area in the other housing types (from142m2 to 134m2) (ABS, 2013c). From 1976 to 20132014, the number of bedrooms per dwelling has
increased from 2.8 to 3.14, while the number of
persons per household has decreased from 3 to 2.4(ABS, 2015a). 49.9 percent of 3 or more bedroom
separate houses were occupied by less than two
persons households, 16.9 and 33 percent
respectively for lone person and two persons
households (de Vause & Qu, 2015; ABS, 2012). The
amount of lone person households has grown from11 to 25 percent during the period of 1911 to 2011(de Vause & Qu, 2015). The number of lone personhouseholds is also estimated to significantly increase
from 2’100’000 households in 2011 to more than
3’300’000 households in 2036 (1’300’000
households with growth rate of almost 63% growth)(ABS, 2015b). According to ABS (2012), 79 percent
of households had spare bedrooms.
Accordingly, the households mostly haveenjoyed relatively spacious accommodations, andthe housing units are mostly not fully utilized byaccommodating a reasonable number of people,
even though the spare spaces might be allocated forother functional purposes, e.g. study room, officeroom, play room, and store. The most popular
housing type, the accommodation preferences, thedemographic of lone person households, along withthe average number of people per dwelling in 3 ormore bedroom separate houses are also some piecesof evidence of lack of diversity of the Australian
housing industry market in relation to the different
lifecycle stages of the Australian populations. In thisregards, the diversity and flexibility of the housing
spatial structure have a strong responsibility inmaking the industry more compatible with thelifecycle requirements of the population. The
necessity of paying attention to the flexibility andthe diversity of the new dwelling units is more
obvious when the ascending order in the proportionof lone person in the Australian projected populationin the next two decades (2026 and 2036) would beconsidered (ABS, 2015b).
The most preferred housing type decreases the
problem of housing diversity, as the majority of thehouseholds prefer 3 or more bedroom houses as theirresidential place. The housing tenure is also anevidence of the presences and availability of endusers during housing delivery, and also gives thecosts and benefits to the same person. The presenceof the end-users during the design process increase
the opportunity for making more reliable decisions
about the operation phases of the buildings as well.
The most preferred housing type and tenure, alongwith size and economic performance of the housing
units in Australia, highlight the socio-economic
characteristics of the end-users, their ability,
capacity, and power in joining to the mitigation
action plans, their presence and availability during
270

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

different stages of housing delivery, and thesubstantial decrease in the complexity of decisionmaking provided by stakeholders diversity. These
parameters all together provide higher opportunity
for the implementation of the efficiency policies inthe design stage of the Australian housing.
Some other aspects like the increase in the
average floor area and the number of bedrooms,
compared with the decrease in the number of people
per household are some of the growing inefficient
aspects of the housing preferences in Australia.
However, although these characteristics might besomehow signs of the intensification ofunsustainable attitudes and perceptions, they
meaningfully address the end-users’ level ofperceptual ability and socio-economic characteristics.
These characteristics show the critical responsibilityof the housing design practitioners in enhancing thesituation by a careful consideration of theirsubstantial potential in impacting the people’s daily
life activities, behaviours, preferences, andperceptions.
Regarding the role of residential sector in theenergy performance of the Australian building andconstruction sector, it is necessary to make a brief

comparison between the residential sector and thewhole building sector of Australia. Accordingly, acomparison has been made between the floor areaand energy consumption of the residential buildings
and non-residential buildings to visualise thesubstantial responsibility of the residential sector inenergy performance of the building industry.
The floor area of the Australian residentialbuildings is almost 87 percent (Office 2.3 percent,
Retails 3.3 percent) of the total building sector of thecountry (BZE, 2013, pp. 45-46; ABS, 2013b, c). The
total floor area of separate houses standing on theirown blocks is 79 percent, almost 75 percent of
which are 3 or more bedroom housing units (ABS,2013b, c). Regarding the energy consumption, theresidential sector consume up to 69 percent of thetotal energy (office buildings 8 percent, and retails 9
percent), while most of this amount is consumed in 3
or more bedroom separate houses with theproportion of almost 55 percent of the total energy
consumption of the building sector (Table 2; Figure1) (BZE, 2013, pp. 45-46; ABS, 2013b, c).

Table 2. National residential and non-residential building characteristics
Building Category

Residential

NonResidential

Flor Area(m2)

Percentage(%)

3 or more Bedroom
Separate Houses

1 413 283
000

Other
Residential
Units
RetailOffices
Education&
Universities
Others231 905 000

12.2

National Energy
Use(PJ/Annum)
300(54.5%
375)(68.2%)
75

67 134 855
47 232 731
41 568 034

3.55
2.5
2.2

49.4
46.0
15.1

74.8
1 645 188000

245 311 000

89 457 986
1 890 500 000

87

13

4.75

175
(31.8%)

64.5
100

550

Fig. 1. National residential and non-residential building flat area and energy consumption
14%

9%

12%
4%
2%

8%
3%

55%

2%

Energy (PJ/Annum)

5%

12%
3 or more Bedroom Separate Houses
Other Residential Types
RetailOffices
Education & Universities
Others75%

Source: BZE (2013); ABS (2013)b

271

Floor Area (M2)

3 or more Bedroom Separate Houses
Other Residential Types
RetailOffices
Education & Universities
OthersSEE - USQ, Brisbane, Australia, Nov.13-16, 2017

The energy consumption of the 3 or more
bedroom separate houses is more than 300
PJ/Annum (55% of the total building sector) and 114
PJ/Annum (38%) (The Government of South
Australia: Department of State Development, 2015)
consumes only for heating and cooling purposes.
Addressing the findings of Nasrollahi, et al. (2013)
study, an efficiently well-designed residentialbuilding is capable of improving the energy
performance of the building up to 65%. Therefore,lack of attention to the design of efficient houses
with respect to the energy required for heating andcooling would be substantially responsible for losing
up to 74 PJ/Annum in the Australian housing sector,
which is substantially higher than the total energy
consumption of the non-residential, e.g. retails,
offices, and education and universities.
The number of the Australian households is
projected to be increased from 9’250’000 to
12’600’000 million in 2036 (3’350’000 or around 35
percent increase over the period of 2016-2036),
while the Australia's population is estimated toincrease by 33 percent in the same period, from24’300’000 people to 32’400’000 people (ABS,2015b). The projected population and householdcomposition make evident the future demands forthe new houses and the critical role andresponsibility of the housing design process inenhancing the housing characteristics and regulating
the end-users’ preferences towards more efficienthousing choice behaviours.
According to the projected number of households,
during the next two decades (from 2016 to 2026 and2036) more than 3’000’000 dwelling units should beconstructed (an average of 1’500’000 units for eachperiod) (ABS, 2015b), 2’250’000 (75%) of which
would be from 3 or more bedroom separate houses.
Accordingly, with assuming the average floor areaof 240m2, the floor area of the 3 or bedroom
dwelling units would be up to 550’000’000m2. Theenergy consumption of the projected dwelling units
would be up to 2’300PJ (an average of
115PJ/Annum) over the period of these 20 years.
Regarding the study of Nasrollahi et al. (2013), thepotential the energy consumption reduction throughthe production of efficiently well-designed dwelling
units with employing the bioclimatic architecturalprinciples, just in the area of heating and cooling,
would be up to 570PJ (an average of 28PJ/Annum).
The capacity of the reduction would be even far
greater than this amount if the design process would
be able to decrease the housing energy demands by

implication of bioclimatic architectural principles,e.g. using natural elements, e.g. vegetation and waterfeatures, cross ventilation, window to wall ratio andopenings, shading devices, geographical orientation,
external wall dimensions, building mass and density,height and 3D proportions. The second componentsof the sustainable design is the optimization of thebuilding physical characteristics, e.g. floor area andthe building size, as well as other physicalcharacteristics, e.g. the number bedrooms, and otherlateral facilities of the residential units. The
architectural design is also capable of providing
positive impacts on the occupants’ choice
behaviours by optimizing the spatial and functional
structure and organization, improving the interiorlayouts arrangement of the dwelling units, alongwith enhancing the flexibility of the dwelling units
in respect to the different lifecycle stages of theoccupants, which has capability of reducing theoverall energy demands of the dwelling units. The
design process has also potential in improving theenergy performance by facilitating the sustainableusage of the building construction materials by
reducing the wasted materials, encouraging theconsumption of the reusable and recycled materials
alongside the usage of the materials that areenvironmentally friendly and more compatible withthe climate and are efficient with respect to theavailability of the resources, production andmanufacturing
process,transportation,andinstallation, which are capable of enhancing theembodied energy parallel to the operational energyof the dwelling units. Table 3 overviews briefly theapplication of architectural design in reducing theenergy demands in the residential sector.

Table 3.

designKey components of sustainable housing

Different Components
1

Regarding the housing spatial, physical, andfunctional characteristics and the direction ofprojected housing development, the design process
has strong role and responsibility in enhancing theenergy demands of the occupants, in improving theenergy performance of the buildings, and in
implementing the energy efficiency action plans.
The designers are, also, responsible and havesupervisory roles in improving the people’s
awareness, information, and knowledge, and to
motivate them toward the selection of more efficienthousing spatial and technological options. The
designers should not be passive followers of theirclients' preferences and market trends; they shouldhave an active role in enhancing the sustainability of
theirhousingdesignpractices

Bioclimatic

Architectural

Techniques
Using natural elements, e.g. vegetation andwater features
272

Advantages
Improving the energy

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

Principles

2

Building
Characteristics

3

Interior Layouts Arrangement
and Spatial Organization

4

Sustainable
Building
Materials

PhysicalUsage of theConstruction

Cross ventilation
Window to wall ratio and openings
Shading devices
Orientation
External wall dimensions and materials
Building mass and density
Height and 3D proportions
Optimizing floor area and building size
Number of rooms
Average floor area per person
Spatial and functional structure andorganization
Interior layouts arrangement
Flexibility of the dwelling units in respect tothe different lifecycle stages of occupants
Reducing the waste materials
Consumption of the reusable and recycledmaterials
The material that are environmentally friendly
and more compatible with the climate
Efficient materials with respect to theavailability of the resources, production andmanufacturing process, transportation, andinstallation

demands for heating andcoolingEnhancing the building
energy performance
Improvingtheoccupants’housing
choice behaviours

Reducing the embodied
energy of the residentialbuildings

users’ housing choice behaviours. The housing
design is also responsible for paying higher attention
to the diversity and spatial flexibility of housing
products to improve the compatibility of the
products with the different lifecycle stages of theAustralian population. Improving the flexibility of
the housing spatial structure in relation to theAustralian end-users’ lifecycle requirements andfamily composition changes is also applicable forthe existing dwelling units. In sum, sustainablehousing design has potential to impact the energy
performance of the Australian residential sector
directly through the enhancement of the spatial andphysical characteristics of the housing units andindirectly through improving occupants’ housing
preferences and daily life activities; hence should
gain centrality in the energy efficiency action plans.

Conclusion
Regarding spatial, physical, and functional
characteristics, housing preferences, and direction of
housing development in Australia, the concept ofsustainable housing design has substantial
contributions for improving energy performance of
the Australian housing. The responsibility offeasibility assessment and design process would behighly critical by considering the 2036 projectedhouseholds and the future demands for new
residential units. Although the literature mostly
emphasized the responsibility of sustainable
materials alongside bioclimatic architectural
techniques and principles in improving the buildings
energy performance, there are other components, e.g.
physical characteristics of the buildings alongsideinterior
layouts arrangements and spatialorganization, impacting directly or indirectly theenergy performance of the residential buildings. The
employment of different components of housing
design has direct impact on reducing the energy
demand of the units by improving the physicalcharacteristics of the buildings and has indirect
impact by simplifying occupants’ daily life activities.
The implementation of the different components ofhousing design depends strongly on the interest andinvolvement of end-users. In this regard, the second
level of indirect impacts of housing design is thesupervisory role of the designers in enhancing end-

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275

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

VULNERABILITY ASSESSMENT OF SURIGAO METRO WATER
DISTRICT UNDER SEISMIC HAZARD
Sheena I. Better1 and Lessandro Estelito O. Garciano2
1

Undergraduate student, De La Salle University - Manila, Philippines; 2Associate Professor, De La Salle
University - Manila, Philippines
ABSTRACT

Earlier this year, Surigao Del Norte, a province in the Philippines experienced a 6.7 magnitude earthquake.
The severe ground movement caused some of the buried pipelines to be pulled-out from their supports. This typeof failure occurs when the ground strain during extreme seismic excitation exceeds the strain capacity of theburied pipe. The failure of the pipes resulted to the loss of water that was vital for post-earthquake recovery
efforts. In this regard, there is a need to re-assess the vulnerability of the buried pipes of the water network. In
this paper, a probabilistic seismic hazard analysis (PSHA) was employed to estimate the seismic hazard within
the concession area. Past seismic data that can significantly affect the target structure is used for this purpose.
The buried water lifeline system of Surigao Metro Water District (SMWD) was chosen as the target lifeline. An
appropriate ground motion prediction equation (GMPE) was used to develop the uniform hazard response
spectra for the site. To assess the vulnerability of the pipes three damage states were considered: major, moderate
and minor. The probability of major, moderate and minor damage for each pipe was determined using Monte
Carlo simulation. Subsequently, fragility curves were obtained.
Keywords: Buried Pipelines, PSHA, Damage States, Fragility Curve, Monte Carlo Simulation
INTRODUCTION
Earthquakes are one of the most damaging
natural hazard to a built environment. Countries
located along the “Pacific Ring of Fire” such as thePhilippines experience more earthquakes than any
other part of the world. In recent years, there havebeen three earthquakes in the country that caused
damage to lives and property, e.g. Bohol
Earthquake in 2013, Batangas Earthquake in 2017
and the Surigao Earthquake in 2017. These
earthquakes caused damage to bridges, schools,
hospitals and historical structures (Garciano andTaclibon 2013), and power supply system(Crismundo, 2017).
Aside from potential damage to building andbridges, severe ground movement can trigger
damage to buried utility lifelines that can stop theoperation of the entire lifeline system. Previous
works by Hamada, 2014, Sahoo et. al, 2014
O’Rourke and Liu, 1999, Tromans, 2004 discussed
the seismic risks of buried water lifelines, as well
the behavior of buried water lifelines.
The problems posed by the lack of potablewater supply for post-seismic recovery operations
after a destructive earthquake is therefore an
important issue. Considering the vulnerability ofour buried utility lifelines to extreme
environmental events, there has been a change
from a passive to a more pro-active stance byvarious government agencies to study, document,
design mitigation measures, and to retrofit
structures for the reduction of the effects of these276

hazards. This paper is a contribution to these
efforts. The purpose therefore of this study is toestimate the damage of the buried lifeline networkof the Surigao Metro Water District (SMWD) andprovide additional information on the effect ofseismic ground motion to the buried steel pipes.
The main outputs of this research are fragility
curves of buried main water pipelines during
extreme seismic events that can be used to develop
risk management strategies.
The paper is organized into the following: first,
assessing the site-specific seismic hazard using aprobabilistic approach. In this step the peak groundacceleration (pga) at bedrock as well as theuniform hazard response spectra at the groundsurface is established. Second, the performance
criteria as a function of pipe and ground strains
due to an earthquake are defined as well as thedamage states criteria, i.e. minor, moderate andmajor damage were calculated. The results are
summarized by fragility curves and are developed
based on models developed by Koike (2009).
TARGET AREA
Surigao City is the capital city of Surigao delNorte. It is situated in the northeastern part of
Mindanao, Philippines. It has a total land area of
245.3 square kilometers (PSY 2010) with 17
municipalities and 335 barangays. Surigao City
has a population of about 140,540 and is composedof three barangays namely: Washington, Taft and
San Juan as shown in Figure 1.

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

probability of damage for each pipe.

(source: www.zamboanga.com)

Fig.1 Study area
Water Lifeline of SMWD
A schematic network diagram is shown in Fig.
2. This figure shows the span and location of thenodes of the lifeline system. It covers the whole
city of Surigao with extensions to farther towns
and municipalities. The system is composed of 8
different steel pipes. These pipes make up thetrunk and distribution lines of the system. Theirmain function is to circulate water from one point
to another. Trunk lines have a diameter of 35 cm to40 cm that varied in length. Distribution lines havea diameter of 5 cm to 25 cm. Properties of steel
pipes are considered on the pipe strain analysis.
SMWD have two water sources, several control
facilities that include tanks, reservoirs andpumping systems, and demand nodes. These are allconnected to the distribution and service lifeline
networks.

Fig. 2 SMWD pipe network system
3.1.1 Seismic Sources Identification
Surigao Del Norte is susceptible to frequent
earthquakes due to the geologic setting of theprovince. Large earthquake occur within 150 kmof the province. Three active seismic sources
namely Surigao, Central Leyte and Bohol faults
are within the 150 km radius from the target area.
Surigao fault is the nearest seismic source to thetarget area.
Table I Properties of Seismic Sources near
SMWD
Fault
Tectonics
Style
Length (m)nameSurigao
CrustalStrike153
slip
CentralCrustalStrike116
Leyte
slip
Bohol
CrustalStrike slip
38

METHODOLOGY
Probabilistic Seismic Hazard Analysis (PSHA)
To estimate the seismic hazard at the site a
PSHA was employed in the study as it can capture
uncertainties in the estimation of the pga. The
uncertainties include but not limited to theidentification of the seismic sources that exposes
the area to significant ground motion, uncertainties
in the fault parameters, historical data of theseismic events, distribution of the source-to-site
distances, epicenter approximations, soil thickness
and composition variations, local SPT results andthe choice of an appropriate GMPE.
Uniform hazard response spectra for both
spectral acceleration and velocity are developed
for the estimation of the probability of failure foreach pipe diameter and are followed by theAmong the three seismic source, the Philippine
Fault Zone: Surigao Segment (see Fig. 2) has thehigher potential to cause damage to the target area.
The 6.7 magnitude earthquake that affected
Surigao City last February 10, 2017 is a case inpoint. According to National Disaster Risk

Reduction

andManagement

Council(NDRRMC) site report, 8 persons lost their lives
while 249 were injured. More than 10,645 homes
were damaged, 555 were totally damaged and10,090 were partially damaged. The total cost ofdamage was estimated to be around US$ 14
277

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

million.

M

m +mu) (mu -ml )2

P [Ml ≤ m ≤ mu ]= ∫M u fm (𝑚) ≈ fm( ll(3)

The attenuation model of Fukushima and Tanaka(1990) shown below was used to estimate themean peak horizontal acceleration (PHA) for a
10% in 50 years probability (MRI = 475 years).
log 𝐴 = 0.41𝑀 − log(𝑅 + 0.03𝑥100.41𝑀 ) −0.0034𝑅 + 130(4)

A is the PHA mean value (in g). A summary of the
PSHA process through a total probability theorem(Thenhaus and Campbell , 2003) is shown below.
Fig. 3. Active Faults / Trenches near Surigao𝑀

λ[X≥x]≈ ∑sourcesi vi ∫𝑀 max ∫ 𝑃[X≥x|M,R]fm(m)fR|m (r|m)drdm (5)min

3.1.2 Seismic Events Modeling

Uniform Hazard Response Spectra

Historical data of the past earthquakes within
the 150-km radius were obtained from thePhilippines Institute of Volcanology andSeismology (PHIVOLCS). The records include thedate, location, magnitudes and depths of theseismic events from 1952 to 2014. Only main
shocks were considered in the analysis andaftershocks were removed. Moment magnitudeless than 5.2 were removed as these were assumed
not capable of triggering any damage. Historicalsurface, body and live wave magnitudes were all
converted into moment magnitudes (Giacomo et.
al. 1990) to conform to the GMPEs used. Due tothe scarcity of the data from third-party resources
uncertainties on fault parameters cannot be
avoided.

The estimated acceleration experienced by thewater pipelines during earthquake can be estimatedy determining the spectral acceleration. This study
adapted the GMPE of McGuire (Sen, 2009) toestimate the corresponding spectral acceleration
for the following periods (T) 0.1, 0.2, 0.3, 0.5, 1.0,
2.0, 3.0, and 4.0.
Sa =b' 1 10b2M (R)-b3
Sa is the spectral acceleration value (in g).
Table 2. McGuire’s GMPE values
Period (T)
0.1
0.2
0.3
0.5
1.0
2.0
3.0
4.0

3.1.3 Attenuation models and pga estimation
The Gutenberg-Richter recurrence law was
adapted in the study to determine the distributionof the seismic magnitude for each seismic source.
It conveys the relationship between the number ofearthquakes for each magnitude group interval incomparison to the total number of earthquakes of
the target area.
log(𝜆𝑚 ) = 𝑎 − 𝑏𝑀

(6)

b’1
1610
2510
1478
183.2
6.894
0.974
0.497
0.291

b2
0.233
0.226
0.290
0.356
0.399
0.466
0.485
0.520

b3
1.341
1.323
1.416
1.197
0.704
0.675
0.709
0.788

cov, Sa
0.651
0.577
0.560
0.591
0.703
0.941
1.007
1.191

In conformity with the models of for damage
estimations, spectral acceleration values areconverted to response velocity spectrum, Sv.
(in/sec)(1)

where a and b are constants derived from theregression analysis of the region while M is theearthquake moment magnitude. Total average
exceedance rate for a given period is given by thismodel.

𝑷
SV = 𝟐𝝅 SV(7)Vulnerability Assessment of a Lifeline Network𝑁𝑁
𝑁𝑟
λy*= ∑i=1𝑠 ∑j=1𝑚 ∑k=1
vi P[Y>y*|mj ,rk]P[M = mj ]P[R=rk ]3.3.2 Damage functions
The damage estimation for this study adapted
the models of Ogawa and Koike, 2001. The
damage estimation of pipe is divided into three
categories such as (a) major damage curve wherein(2)
The probability distribution of the magnitude,
P(M) is based on the function shown below(Kramer, 1996).
278

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

the structural reliability of the material considered
exceeds the critical or allowable level for the major
damage state or ultimate limit state under seismic
loading;𝒎𝒂𝒋

P[major damage] = P[𝜺𝒄𝒓 − 𝜺𝒑 < 𝟎](8)(b) moderate damage curve wherein the structuralreliability of the material considered exceeds themoderate damage state seismic loading; andP[moderate damage] = P[𝜺𝒎𝒐𝒅𝒄𝒓 − 𝜺𝒑 < 𝟎]

(9)

Fig. 5. Diagram of Buried Pipelineand (c) minor damage wherein the structuralreliability of the material exceeds the minor
damage state or the serviceability limit state underseismic loading.
P[minor damage] = P[𝜺𝒎𝒊𝒏𝒄𝒓 − 𝜺𝒑 < 𝟎]

The actual pipe strain is the product of the freefield ground strain g and the αo (see Eq. 12)
εp = 𝜶 𝒐 𝜺 𝑮

(10)

𝟐𝝅

𝜺𝑮 = 𝑳 𝑼𝒉

Where e, e , e are the critical strains forthe different damage states and p is the actual pipe
strain.
The models above are used to generate fragility
curves which is expressed as the probability ofdamage occurrence of material conditioned on the
pga as shown in Fig 4.
major
cr

mod
cr

(12)

min
cr

(13)

The conversion factor αo is determined using Eq.
14 below
𝜶𝒐 =

𝟏
𝟏+(

𝟐𝝅 𝟐
)
𝝀𝑳

𝑲

𝝀 = √𝑬𝑨

(14)

(15)

where L is the horizontally travelling wavelength(cm), K is the axial stiffness between thesurrounding soil and pipe (N/m), E is the modulus
of elasticity (Mpa), A is the cross-sectional area ofthe pipe (mm2).
RESULTS AND ANALYSIS
Probabilistic Seismic Hazard Analysis
The result of PSHA is summarized through thegeneration of seismic hazard curve and seismic
hazard map for the province of Surigao Del Norte
where the concession area of SMWD is located.
The generated map provided the probability ofexceedance of each points considered for a Design
Basis Earthquake (DBE).

Fig. 4. Sample Fragility Curve
Pipe Strain and Ground Strain
The seismic response analysis of buried
pipeline is evaluated using ground response
displacement (cm) Uh (JWWA, 1997) as shown in
Eq. 11. The free field displacement of soil particles
is based on spectral velocity, period of the groundsurface, thickness of the ground surface and the
distance of the pipeline to the ground.
2

Uh = π2 Sv T

4.1.1 Distribution of the Radius R
Seismic sources are considered linear sourcewith distance L, based on the notion that point
sources are not capable of generating earthquakes
with magnitude 5.8 and above. The mathematicaltechnique of triangulation is used to determine theshortest distance from any point of linear source.
The calculated distances are divided by 10 km then

(11)

279

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

normalized to
distribution.

determinetheirsource-to-sitewith magnitude 7.6 to 8.1 have distribution ofaround 3%.

Fig 8. Annual Rate of Occurrence of Surigao Fault
Fig. 6. P(R) for 6.4 - 6.9 Mw
4.1.3 Seismic Hazard Curve and Map
It can be seen in figure 6 that the likelihood for aseismic event with a moment magnitude of 6.4 to
6.9 to occur with 3 km away is estimated to bearound 53% from the site.

The seismic hazard curve is based on themean value for all magnitude-distance pairs.
Figure 9 shows that for 0.0021 chance ofoccurrence for a DBE of 0.7g for PFZ: Surigao
Segment. It must be noted that this even is likely tooccur within 5km of the fault itself. The
acceleration for all points considered is plotted on
the map as seen the Figure 10.

4.1.2 Annual Rate of Occurrence and Probability
Distribution of EQ Magnitudes, P(M)The annual rate of occurrence is the likelihoodof an earthquake with a corresponding magnitude
to occur for a year. Values for each seismic source
are plotted to determine the equation and slope ofline. The equation and slope serves as the seismic
constants, a and b, that is used for thedetermination of probability distribution ofearthquake magnitude M, P(M).
0
5

6

7

8

Log N

-0.5
-1
Fig. 9. Probability of Exceedance-1.5
y = 1.854-0.4677M-2

4.1.4 De-aggregation

Moment Magnitude

De-aggregation is the summary of possible
location magnitudes for each mean distance range.
The graph below shows that as the distance range
increases, the probability of each magnitudedecreases that the likelihood of earthquake withmean magnitude of 7.9 has a 0.005 probability ofoccurrence within 5 km of the source.

Fig. 7. Annual Rate of Occurrence of Surigao
Fault

Figure 8 shows the likelihood of the seismic eventswith greater magnitudes to have longer return
periods than events with smaller magnitude.
Earthquakes with magnitude within 5.2 to 5.7 havea distribution of about 49.6% while earthquake
280

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

Fig. 12. Uniform Hazard Response Spectra
Vulnerability Analysis of SMWD
The fragility curves for this study aredeveloped using Monte Carlo Simulation. The
figure below shows the fragility curves for minor,
moderate and major damage states given the pipe
diameter of 10 cm.

Fig. 10. Seismic Hazard Map of Surigao Del Norte

Fig. 13. Fragility curve for Major Damage State

Fig. 11. De-aggregation of PSHA results
Uniform Hazard Response Spectra
Spectral Velocity Curve

andThe figure below provides the uniform hazard
response spectra for Surigao Del Norte. The
spectral acceleration at sudden ground motion
gradually increases until it reaches its peak
movement. It slowly decreases as the period
increases.

Fig. 14. Fragility Curve for Moderate Damage
StateFig. 15. Fragility Curve for Minor Damage State

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

Figure 16 shown below shows the summaryof the probability of damage for major, moderate
and minor damage state of all pipe diameters.
Probability of minor damage is higher for all pipe
sizes in comparison to major damage state.

[3] Hamada, M. Critical Urban Infrastructure
Handbook, 2014, CRC Press.
[4] Sahoo, S., Manna, B., and Sharma, K. G.
Seismic Behaviour of Buried Pipelines: 3D
Finite Element Approach, Journal of
Earthquakes. Vol. (2014), 2014.
[5] O’Rourke, M. and Ayala, G. Pipeline Damage
Due to Wave Propagation. Journal of
Geotechnical Engineering, 119 (9), 1993, pp.
1490 - 1498.
[6] Tromans, I. Behavior of Buried Water Supply
Pipelines in Earthquake Zones. Doctorate
Thesis, Imperial College of Science,
Technology and Medicine, London. 2004.
[7] Koike, T. Seismic Risk Assessment of a Water
Supply Lifeline System in Baku. Conference
Proceedings. In Proc. Reliability Engineering
Conference, Azerbaijan. 2009.
[8] The Philippine Statistical Yearbook (PSY),
National Statistical Coordination Board(NSCB), 2010.
[9] NDRRMC (National Disaster Risk Reduction
and Management Council). SitRep No. 18 re:
Effects of Magnitude 6.7 Earthquake in
Surigao City, Surigao Del Norte. July 3, 2017from http://www.ndrrmc.gov.ph.
[10] PHIVOLCS(Philippines
InstituteofVolcanology and Seismology). Seismicity
Map and Catalogue of Surigao Del Norte
Earthquakes Magnitude 2.0 and above. 19522014.
[11] Giacomo, D., Bondar, I., Storchak, D. A.,
Engdhal, E.R., Bormann, P., Harrus, J., “ISCBEM: Global Instrumental Earthquake
Catalogue (1900-2009), Physics of the Earthand Planetary Interiors, 2014.in of the
Seismological Society of America. 1990.
[12] Kramer,
S.
Geotechnical
Earthquake
Engineering. New Jersey: Prentice Hall. 1996.
[13] Fukushima, Y., & Tanaka, T. A new
attenuation relationship for peak horizontal
acceleration of strong earthquake groundmotion in Japan. Bulletin of the SeismologicalSociety of America. 1990.
[14] Thenhaus, P., & Campbell, K. Seismic Hazard
Analysis. W. Chen Earthquake Engineering
Handbook. 2003.
[15] Sen, T. Fundamental of Seismic Loading on
Structure. PSHA. John Wiley & Sons. 2009.
[16] Ogawa, Y. and Koike, T., Structural Design ofBuried Pipeline for Severe Earthquakes. Soil
Dynamics and Engineering, 2001.
[17] JWWA (Japan Waterworks Association).
Seismic Design Guideline for Waterworks
Pipeline and Facilities, 1997.

Fig. 16. Damage States for all pipe diameters
CONCLUSION
Monte Carlo simulation is used to produce thefragility curves for each damage states. The
fragility curves provided for three different
damage states showed that the probability of
failure for the pipe for period around 0.1 to 0.5
secs are around 0 to 10%. Aside from that, it canbe seen that damage probability increases as period
increases. It proves that the pipe strain is relativewith the ground displacement and period of theseismic event. Major damage state is expected
about 70% for longer earthquake period.
ACKNOWLEDGEMENTS
The authors would like to thank Prof. Takeshi
Koike as well as to SMWD and PHIVOLCS for
their valuable assistance.
REFERENCES[1] Garciano, L. E. and Taclibon, P. The October
15, 2013 Bohol Island, Philippines earthquake
and its damaging effects: An investigative
report, Journal of Disaster Factsheets,
http://committees.jsce.or.jp/disaster/FS2013D-0004, Dec. 2013.
[2] Crismundo, M. Panic grips Surigao; Strong
aftershocks, water shortage keep quakeaffected residents on edge. Manila Bulletin,
2017.

282

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

A COMPARISON OF ESTIMATED SHEAR STRENGTH OF SOUTHEAST QUEENSLAND RESIDUAL SOIL USING FIELD AND
LABORATORY TESTING
Darren Newell1 and Choo Yong2
School of Engineering, Griffith University, Queensland, Australia

1

ABSTRACT
Undrained shear strength of soil is an interpreted value that is typically used when undertaking geotechnicalengineering analyses. There is a suite of laboratory and in situ tests readily available to engineering practitioners
that can be used to estimate undrained shear strength of a soil. This paper compares estimates of the short term
undrained shear strength of a sandy clay using laboratory (undrained triaxial, oedometer) and in situ (conepenetrometer) tests. The interpreted undrained shear strength derived from laboratory and in situ tests displayed
significant variation. These differences in the estimated strength parameters for the subject clay highlight theimportance of not relying on one type of test in isolation when assessing soil strength parameters.
Keywords: Undrained Shear Strength, Triaxial Test, Cone Penetrometer Test, Oedometer Test, Fine Grained Soils,
Over Consolidation Ratio

INTRODUCTION

SITE DESCRIPTION

Laboratory and in situ testing was undertaken ona sandy clay material obtained from a site in Yatala,
Queensland (a suburb of the City of Gold Coast). The
objective of this testing was to characterize thestrength parameters of this material in order toestimate its short term undrained shear strength.
The short term undrained shear strength (su) ofsoils is typically a critical value that must be
interpreted in geotechnical engineering. There is noone value for the undrained shear strength of a soil;
the value depends on various factors including therate of loading, the in situ stress, stress history and test
method. There is a suite of laboratory and in situ tests
readily available to engineering practitioners that canbe used to estimate the undrained shear strength of asoil.
Triaxial tests are widely recognized as an accurate
laboratory test to determine the engineering
properties of a soil, such as the angle of internal
friction and cohesion from which su can be estimated.
There are several variations of the test that relate to
the way in which the sample is consolidated anddrained. In this research, isotropically consolidated,undrained triaxial compression tests (CU) were used
to estimate the strength parameters of the clay underinvestigation.
In situ testing was also undertaken at the site using
the Cone Penetrometer Test (CPT). Since theinception of the CPT in the early to mid-1930s there
has been continuous development and understandingof CPT technology, making it a widely accepted
method for assessing soil strength parameters (see,e.g. [1]).

Regional geological mapping of Yatala, where thesubject clay is located [2], indicates that the area iscomprised of soil and rock of the Neranleigh Fernvale
beds that are typically characterized by greywacke,
argillite, quartzite, chert, shale, sandstone andgreenstone.
Geotechnical investigations on this site have been
undertaken to assess subsurface ground conditions
utilizing undisturbed sampling (rotary wash boring,
52 mm nominal dia.) and CPT techniques. Subsurface
conditions were found to be comprised of three
distinct layers, described as: engineered fill; residual
clay (approx. 2.0 m deep); and meta-siltstone rock.
Ground water was not encountered in any of theboreholes, which is consistent with the surrounding
topography and elevation of the site (approximately
17.75 m AHD).
TEST RESULTS AND INTERPRETATION
Various laboratory tests were conducted on
undisturbed samples of the subject clay obtained from
boreholes at the site. At each borehole, a CPT
sounding was also undertaken. Test results and aninterpretation of the soil strength follow.
Laboratory Testing
Laboratory tests using undisturbed samples froma total of seven boreholes were undertaken to
determine the engineering characteristics of the clay
layer between depths of 1.2 and 2.6 m.

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

These tests included: Atterberg Limit, particle
size distribution, oedometer and triaxial tests.

Based on these results the consistency of thesubject clay can be generally described as Firm.

Atterberg limits and sieve analysis

Table 1: Strength parameters from CU tests

Atterberg Limit tests indicate that the clay layer
has varying plasticity. Of the ten tests performed on
the subject clay, the average liquid limit (LL) andplasticity index (PI) was 46 percent and 30 percent,respectively. Particle size distribution tests show that
more than 50 percent of the material has a particle lessthan 0.075 mm. The tested clay can be generally
categorized as a Sandy Clay with medium plasticity(a CI material under the USCS system).

c’
kPa
12
13
22
20
12
10
20

z
m
1.45
1.59
1.80
2.15
2.25
2.29
2.50

ϕ’
degrees
17
18
23
21
17
24
23

su
kPa
25
27
47
43
31
39
51

Over consolidation ratio from oedometer test
Evaluation of shear strength from laboratory tests

Oedometer tests were carried out on three
undisturbed samples recovered from depths of 1.8,
2.8 and 3.4 m. Using the graphical method proposedby [3] the estimated Over Consolidation Ratio (OCR)
for these samples was 1.0, 2.0 and 2.5, respectively,
indicating a normal to lightly overconsolidated clay.

Due the variability that can be encountered inestimating su there has been considerable research on
the subject, see [6], [7] and [8]. From this publishedresearch an assessment of su can be made throughvarious means. For an overconsolidated soil with a
low to moderate PI, where σ’vc is the effective
preconsolidation stress, the normalized shear strength
can be expressed as [8]:𝑠𝑢
= 0.23 ± 0.04 𝑂𝐶𝑅0.8
(6)
𝜎’𝑣𝑐

Undrained shear strength from triaxial tests
A total of seven CU tests were performed on
undisturbed clay samples (recovered from depths
between 1.2 and 2.6 m) to determine the material’s
effective cohesion (c’) and angle of internal friction(ϕ’) (Table 1). These values were interpreted from
Cambridge p–q plots (critical soil state theory
developed by [4]). Using these values, the in situ su
was estimated using the Mohr-Coulomb criterion,
where for an in situ horizontal stress (σ’ho), thevertical (σ’f) and shear (τf) stress at failure are:2 𝑐 ′ cos 𝜙′ + 𝜎 ′ ℎ𝑜 (1 + sin 𝜙′)
(1)
𝜎’𝑓 =
1 − sin 𝜙′𝑠𝑢 = 𝜏𝑓 =1(𝜎’𝑓 − 𝜎 ′ ℎ𝑜 ) cos 𝜙′
2

Table 2: Normalized shear strength from CU tests(2)

where (𝛾′𝑠 is unit soil weight, z is depth),
𝜎’ℎ𝑜 = 𝐾𝑜 𝜎’𝑣𝑜

(3)

𝜎’𝑣𝑜 = 𝛾′𝑠 𝑧 (effective vertical stress, σ’vo)(4)𝐾𝑜 = (1 − sin 𝜙 ′ )𝑂𝐶𝑅

su
kPa

σ’vc
kPa

su / σ’vc

1.45
1.59
1.80
2.15
2.25
2.29
2.50

25
27
47
43
31
39
51

64
70
79
95
99
101
110

0.39
0.39
0.60
0.45
0.32
0.38
0.46

Upper Lower
Limit
Limit
su / σ’vc su / σ’vc

0.47

0.33

Normalized shear strengths were calculated using
su values from Table 1 and assuming an OCR of 2
(Table 2). Generally, these values fall within thelimits defined by Eq. (6) (Fig. 1). As noted by [9], abetter fit of data can result if the exponent in Eq. (6)is varied between 0.75 and 0.85.

For over consolidated soils the coefficient of earthpressure (Ko) can be estimated using various methods.
One of the most commonly used is that proposed by[5] where:
sin 𝜙′zm

In Situ Testing
CPTs were undertaken close to each borehole sothat a comparison could be made between laboratory
and in situ estimates of soil strength parameters.
Three of the seven CPT soundings were performed
using a piezo-cone (CPTu) so that pore water pressure
measurements could also be taken.

(5)

The estimated su values were calculated using Eqs(1) – (5) at depths corresponding to those from which
the specimens were recovered and assuming OCR=2(Table 1).
284

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[1]. However, published ranges of between 4.5 and 75
have also been reported [11].
Assuming that the clay investigated is a lightly
overconsolidated clay, [12] suggests a value of 19,
which has been used in Eq. (8) to estimate su values(Table 3). When su is normalized by σ’vc the resulting
values (Table 3) exceed the upper limit given by Eq.
(6). When a value of 75 (as in [11]) is chosen for Nkt
normalized values were still found to exceed theupper limit.

Lower Limit-1
Depth (m)Upper Limit-0.5

Upper Test
Depth

-1.5
-2
-2.5

Lower
Test Depth

Table 3: Normalized shear strength from CPT tests

-3
0.2

0.3

0.4

0.5

0.6

0.7

Normalized Strength (su/σ'vc)zmFig. 1 Depth versus normalized shear strength

su
kPa

σ’vc
kPa

su / σ’vc

Upper Lower
Limit
Limit
su / σ’vc su / σ’vc

1.45 168*
64
2.6
1.59
136
70
1.9
1.80
251
79
3.2
2.15
251
95
2.7
0.47
0.33
2.25 267*
99
2.7
2.29 366*
101
3.6
2.50
213
110
1.9
* CPTu test, value adjusted for pore pressure.

Over consolidation ratio from CPTu
A commonly used method to estimate the OCR offine grained soils is outlined in [9] using thenormalized cone resistance (Qt), which is a functionof the cone resistance corrected for pore waterpressure (qt) and, the total (σvo) and effective (σ’vo)vertical stresses, expressed as:
𝑞𝑡 − 𝜎𝑣𝑜
𝑂𝐶𝑅 = 𝑘 𝑄𝑡 = 𝑘
(7)
𝜎′𝑣𝑜

CONCLUSIONS
Comparative estimates of su and OCR for the sameclay are shown to vary substantially between
laboratory and in situ test methods. Laboratory testing
was undertaken by two independent laboratories andgave very similar results. Similarly, CPT soundings
were also undertaken by two independent contractors,
one using CPT and the other using CPTu, yielding
similar results.
With reference to laboratory testing, it is widely
accepted that sample disturbance can influence test
results. This influence is a function of the soil
sensitivity, which is the ratio of the tested su for an
undisturbed and remolded sample. However, [13]notes that sensitivity does not appear to influence
normalized estimates of su.
Whilst sensitivity cannot be ruled out, it appears
unlikely to be the cause of the large variance observed
between the laboratory and in situ tests.
Based on normalized shear strength, CU tests
appear to provide an estimate with the expected su
range using Eq. (6). However, this relies on an
accurate measurement of the OCR. Therefore, itcannot be concluded that the laboratory estimates ofsu are, or are not, accurate from this alone.
Therefore, the discrepancy in the estimated valuesof su from laboratory and in situ tests is likely to hingeon the OCR value for the investigated clay. To resolve
this, additional oedometer tests will be undertaken in
an endeavor to confirm the accuracy of the OCR value
used to derive su for the tested clay.

The variable k in Eq. (7) is a preconsolidationcone factor that [10] suggests can be expected torange from 0.2 to 0.5 with an average value of 0.33.
Higher values of k correspond with aged and heavily
over consolidated clays. According to [10],estimating the OCR using Eq. (7) is not strongly
influenced by soil sensitivity.
CPTu soundings were analyzed across the depth
range where all undisturbed samples were recoveredfrom (1.2 to 2.6 m deep). Using Eq. (7) with k = 0.33
resulted in estimated OCR values greater than 10.
These estimates appear far greater than would be
expected based on laboratory tests and the qualitative
assessment of the clay’s consistency. Similarly,
estimates of the OCR for CPTu soundings over theentire tested depth also resulted in values greater than
10.
Undrained shear strength from CPT and CPTu
CPT soundings were undertaken adjacent to eachborehole that have been used to estimate su using Eq.
(8) [1].
𝑞𝑡 − 𝜎𝑣𝑜
𝑠𝑢 =
(8)
𝑁𝑘𝑡
From Eq. (8) it can be seen that an accurate
estimate of su is limited by the adopted value of theempirical cone factor (Nkt). Research indicates a range
for likely values of Nkt of between 10 and 20 in clays
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Additional su tests (such as direct simple shear andfield vane) may also be undertaken. Finally, testing
information will be sought for similar clays in the area
in order to benchmark estimated values.
The variance in the estimated strength parameters
for the subject clay highlights the importance of not
relying on one type of test in isolation when assessing
soil strength parameters.

[6] Ladd CC and Foott R, New Design Procedure for
Stability of Soft Clays. Massachusetts:
Department of Civil Engineering, Massachusetts
Institute of Technology, 1973.
[7] Mesri G, "A reevaluation of using laboratory
shear tests", Canadian Geotechnical Journal, vol.
26, pp. 162-164, 1989.
[8] Jamiolkowski M, "New development in field andlaboratory testing of soils", in Proceedings of the
11th International Conference on Soil
Mechanics and Foundation Engineering, San
Francisco, 1985, pp. 57-153.
[9] Kulhawy FH and Mayne PW, "Manual on
estimating soil properties for foundation
design", Electric Power Research Inst., Palo
Alto, CA (USA); Cornell Univ., Ithaca, NY(USA). Geotechnical Engineering Group1990.
[10] Robertson P, "Interpretation of cone penetration
tests—aunifiedapproach",
Canadian
Geotechnical Journal, vol. 46, pp. 1337-1355,
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Netherlands: CRC Press, 2014.
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calculation of embankments and foundations on
soft clays", Canadian Geotechnical Journal, vol.
17, pp. 591-602, 1980.

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penetration testing for geotechnical engineering,
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[2] Whitaker WG and Green PM, "Murwillumbah
1:100,000 Geological Series 9541 Geological
Survey of Queensland", ed. Brisbane,
Queensland: Department of Natural Resources
and Mines, 1980.
[3] Casagrande A, "The determination of the preconsolidation
load
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its
practical
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Conference on Soil Mechanics and Foundation
Engineering, 1936, pp. 60-64.
[4] Schofield A and Wroth P, Critical state soil
mechanics. New York: McGraw-Hill, 1968.
[5] Mayne PW and Kulhawy F, "Ko - OCR
Relationships in Soil", Journal of the Soil
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pp. 851-872, 1982.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

STUDY ON LANDSLIDE CATEGORY BASE ON TEMPORAL–SPATIAL CHARACTERISTIC DISTRIBUTION IN NORTHERNVIETNAM USING SATELLITE IMAGES
Thuy Thi Thanh LE1 and Seiki KAWAGOE2
1

Department of Symbiotic Systems Science Fukushima University, JAPANABSTRACT

North Vietnam mountainous area is considered as one of the most landslide generate region in Vietnam.
Landslides in this area often occurs under the influences of heavy rainfall or tropical storms, steep slopes onmountainous sides and human activities such as road or house constructions. Heavy rainfall events are estimatedby climate change in the future. Therefore, it is necessary to understand landslide characteristic due to rainfall
variation. This paper applied Landsat satellite images and calculated Normalized Difference Indexes to evaluate
the condition of vegetation, soil and water and detected 87 landslide points in North Vietnam. As result, three
typical types of landslides are classified as i) landslide caused by rainfall on construction sites, ii) landslidecaused by rainfall on natural slopes, and iii) landslide caused by rainfall and water drawdown on banks ofreservoirs or streams. Considering the Landsat result type 2 and type 3 consist larger proportions (48.3 % and36.8 %) compared to those in historical data (11.7 % and 1.53 %). This means that many landslide would occur inmountainous areas that far from residential or road are-as (type 1). This paper thus would provide initial assessment
for further studies on landslide problems on the bank of water sites such as reservoirs or streams.
Keywords: Landslide type, Landsat 8, Digital geographic information, Climate change
INTRODUCTION

on statistical analysis of landslide groundcharacteristics. However it needs a large amounts ofdata collection and suitable for medium scaleprediction. Deterministic approach requires physicalprocesses. However, since the data availability is oneof the difficulties, the limitation of this approach isshown. Heuristic, which requires long-term landsidedata and causative parameters, estimates potential
landslide from preparatory variables. It is an expert
driven approach that depends on the knowledge andexperiences of scientists in deciding degree and typeof landslide risks. The report of Bui Tien Dieu[4] in2012 also pointed that landslide inventory maps
provide great importance input data in landslide
hazard and susceptibility analysis. The inventories
can be divided into two sub classes including
historical landslide inventories and landslides withtriggering factors. The application of inventory thus
would give information of locations, types andcausative factors of past landslides.
In case of Vietnam, lacking of continuous
information about past occurrences of landslide
hinders the landslide assessment. It also leads todifficulties in data integration with land use plan andmanagement task in landslide hazard regions. As a
one of the most vulnerable nation to climate change,such external hazard risk is estimated to increasesignificantly in Vietnam. It therefore requires
substantial demand in acquiring comprehensive
information of landslide in order to obtain adequately
adaptive measurements and mitigations for landslide
prone areas. Considering the data unavailability(long-term landslide data and its related factors), in

Vietnam is a tropical nation that is often hit byseveral typhoons and tropical cyclones every year. As
the influence of climate change, abnormal weather
phenomenon such as cyclones and severe typhoons
have been occurring with more frequencies andhigher intensities. During the period from 2014-2016
many strong tropical storms and heavy rains occurredin this country and led to disaster in many regions
across Vietnam. According to a national study of theVietnam Geography academy study in 2004[1], North
Vietnam is the most prone region to landslide. Sixteen
out of twenty five provinces there are listed asprovinces obtaining high hazard of landslide
occurrences. In accordance with topographic andgeology condition, landslides in this area often occurs
under the influences of heavy rainfall or tropicalstorms, steep slopes on mountainous sides and humanactivities such as road or house constructions.
Detecting landslides occurrences thus becomes
necessary approach for landslide susceptibility
regions there.
According to Dieu[2] and Metternicht et al[3] , four
major classes for landslide susceptibilities areinventory, statistical, deterministic and heuristic
approaches. Inventory map is based on satellite
images, ground survey and historical data-base oflandslide occurrence. It would give spatial
distribution of past landslides and does not provide
prediction of landslide susceptible areas. Statisticalmethod would provide pre-diction of landslide inregion that might not have landslide in the past basing
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Fig. 2 Average monthly rainfall 1960-2011 in study

Fig. 3 Monthly rainfall 2013-2016 at 3 stations
Fig. 1 Elevation classification in the study area

this paper, we apply the inventory approach to assess
the landslide map based on the satellite images in a
relationship with historical database of landslide
occurrences [3],[5]. We also utilized Landsat satellite
images and calculated Normalized DifferenceIndexes to evaluate the condition of vegetation, soil
and water and detect land degradation in some areasin the North Vietnam. The outcomes would support
further study on the landslide hazard prediction under
the influence of climate change when considering
additional triggering parameters such as heavy
rainfall even and water drawdown.

Fig. 4 Daily rainfall 2015-2016 in four provinces(Spatial average value)

maximum daily rainfall is greater than 100mm [8].
DATASET AND METHODOLOGYSTUDY AREA

DatasetStudy areas are Bac Kan (BK), Thai Nguyen (TN)and Tuyen Quang (TQ), and Ha Giang (HG) in North
Vietnam (Fig 1). These four provinces are considered
as having hazard of landslide occurrence in the North
Vietnam. The elevation in this studied area varies
from 0 to 2958 m covering both mountainous andmidlandregionwithcomplicatedterraincharacteristics. There are two major types of
directions in mountain ranges: northwest to southeast
and arc curve turning eastward Gam mountain ranges
in HG and TQ, and Ngan Son range in BK and TN.
According to report of Vietnam academy of Water
Resources Planning about monthly rainfall [7] from1960 to 2015 in TQ and from 1960 to 2011 in otherprovinces, this area has considerably high annual
rainfall with the ranges from 2467 to 4735 mm in H
G and from 1342 mm (BK) to 1988 mm (TN) inothers. Rainy season in this area often starts in late
April and ends in October with average precipitationfrom 300 to 750 mm in HG and from 150 to 300 mm
in BK, TN and TQ(Fig. 2). June to August is theheaviest rainfall time in rainy season with the

We tried to obtain landslide characteristic torelationshipbetweenlandslidegeomorphic
information and rainfall condition. Therefore, weused actual landslide distribution data as landslide
analysis. Satellite images and Landslide history data
were used to landslide distribution characteristics.
And geomorphic digital information was used toconfirm to landslide factor characteristics. Rainfall
data show timely incitement as temporal event
characteristics.
a)Satellite image
We utilized Landsat 8 satellite images from USGS
website (http://earthexplorer.usgs.gov/) to examine
the land surface changes in area of four given
provinces in northeast Vietnam. The Landsat 8
released the first image in the re-search site on
2013/04/22. It is used as the base image to compare
the changes in surface condition in this area. With the
16-day-circle, from April 2013 to March 2017 among
94 images, the number of good quality images in
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SEE - USQ, Brisbane, Australia, Nov.13-16, 20172013, 2014, 2015 and 2016 are 2, 3, 3 and 2,
respectively. Looking at the rainfall data from 2013
to 2016 in some stations, we found that the year 2015
obtained the heavier monthly rainfall than that in2014 and 2016 (Fig. 3). Comparing daily rainfall datain the last two years, we found that the number ofrainy days in 2015 are higher than those in 2016 (Fig.
4). As rainfall is one of the most important triggeringfactor of landslide occurrence, in this paper, wechoose year 2015 as the computing year to evaluate
the changes of land surface in this studied region.
Regarding to the image quality as well as theoccurrence of heavy rainfall, we select the Landsat 8
data on 2015/07/01 as the comparative image for landdegradation analysis.

describes the greenness of surface throughout thereflection of light waves by land surface. Amongwavelengths of light being gathered from satellite
sensors, the red light’s wave-lengths(VIS) arestrongly absorbed by photo-synthetically active
leaves, and the leaves reflect strongly the nearinfrared (NIR) light’s wave-lengths. In cases of deathor stressed vegetation and non-vegetated surfaces
they reflect less near-infrared light and more red light.
The near-infrared and red light waves thus are applied
to transform raw satellite data into Normalized
Difference Vegetation Index (NDVI) (Equation 1).

NIR  VIS
NIR  VISNDVI 

b) Landslide history data
In 2012, the government released the national
project “Investigation, assessment and zonation oflandslide hazards in mountainous area in Vietnam”.
Phase I (2012-2015) conducted in 13 provinces in thenorth and 1 province in the north central Vietnam.
Twenty-three remaining provinces in the north (4)and other areas (19) will be investigated in the second
phase from 2016-2020. The output of this project isthe landslide occurrences regarding to investigate
time. In this study area, 1049 landslide points in threeprovinces BK, HG and TQ were recorded with brief
information of observed locations, estimated sliding
volume and repeated time. The observation routes
were implemented along road lines and nearresidential areas in 2013

(1)

Unlike vegetation factor, water has stronger
absorption capacity within the NIR wave range. It
also has lower reflectance regarding to the higher
wavelength. The Normalized Difference Water Index(NDWI), which is calculated basing on the NIR and
Short wave infrared (SWIR) in order to evaluate thewater amount in vegetation canopies, can therefore
distinguish the vegetation and water [15] (Equation 2).

NDWI 

VIS  SWIRVIS  SWIR(2)

In addition, the condition of soil moisture on the
ground surface could be observed by applying the
SWIR wavelength. The Normalized Difference Soil
Index (NDSI) therefore would reflect the soil watercontent when using SWIR as a spectral signature in a
relationship with the NIR wavelength (Equation 3)c)Other data
Rainfall data in this paper was adopted from theAcademy of Water Resources Planning [7] (monthly
rainfall from 1960-2011), the Directorate of Water
Resources [11] (daily rainfall 2015-2016) and from theInstitute of Meteorology in Vietnam (daily rainfall
data at some stations). The terrain data was extracted
from a digital elevation model (DEM) from the Open
Mekong Development [6] with the grid cell size of 30m
× 30m. Geology information data was collectedfrom US Geological Survey (USGS). Land use data
was extracted from Japan Aerospace Exploration
Agency (JAXA) [12] with the resolution of 15m ×
15m in north area in 2015.

NDSI VSWIR  NIR
VSWIR  NIR

b)

(3)

Landslide inventory approach
The occurrence of landslide is often in a close
relationship with two main factors namely triggeringand conditioning factors. According to Dieu[4],triggering factors include heavy rainfall events, snow
and earthquakes. States of slope, soil, geology andland use are some examples of conditioning factors.
The former factors could lead to quick changes ofslope condition while the latter factors refer to slowly
processes. In this study, we consider four main
conditioning parameters: slope, elevation, geology
and land use. Historical landslide data and Landsat 8
calculated data are thus mapped and combined with
DEM, slope, geology and land use data.

METHODOLOGYa)Landsat dataset
Basing on the land cover mapping, the Landsat
images would support the inventory of landdegradation. It would visualize and map the pastdegradation of land surface including soil erosion,
landslide, vegetation removal or land use changes [14].
In order to evaluate the changes in vegetation stateand density by the satellite image instruments, avegetation index is often utilized. This index

RESULT
Landsat analysis result

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

With the purpose of determining threshold value
for land use change area, we first calculated the NDVI
in pre event (2013/12/02) and post event (2015/07/01)(Fig. 5) and difference of NDVI between those two
periods. The NDVI differences between pre and post
event are grouped into 11 major land use categories,
which are adopted from USGS database. They are
Evergreen Broadleaf Forest (EBF), Mixed Forests(MF), Closed Shrub lands (CS), Open Shrub lands(OS), Woodley Savannas (WS), Savannas (Sa),Grassland (Gr), Permanent Wetland (PW), Croplands(Cr), Urban and Build-up (UB) and Cropland/Natural
Vegetation on Mosaic (Cr/VM). The average NDVI
value of NDVI in each land use type varies from 0.2223 to -0.1486. Standard deviations and its
multiple values (said 2SD and 3SD) were calculated
and subtracted from average values to obtain
threshold NDVI values. NDVI values that below thegiven base lines are mapped as the first trial of land
surface changes detection in the studied area (Fig. 7).
In case of land degradation, especially in theforest related area, the application of NDSI andNDWI would support the detection of soil-exposedarea in post event. The NDSI thus will increase when
it illustrates the changes in water content (absorptionof SWIR) and chlorophyll of leaves (reflection of
NIR). In addition, NDWI is a vital index that reflects
liquid water content. Positive NDWI values typicallypresent in open water area and negative ones refer tonon-water region. According to Gao[15], most baresoil provides negative NDWI values. Study of
Takeuchi in 2004[16] showed the results of NDVI,NDSI and NDWI values for eleven land covertypes(Fig.6). The results point that NDWI obtains thelowest values in conifers (-0.6), broadleaf forest (0.64) and grass (-0.65) and varies from -0.34 to -0.12
in soil. Water and snow provide positive values.
NDSI increases from vegetation cover type (-0.47 to-0.35) to soil cover group (-0.11 to 0.11). In the studyof Deng et al. in 201517), they tested the potential
band combination of Landsat TM5 to calculate NDSI.
The NDSI output show the critically low value ofaround -0.37 for vegetation surface for the
combination of Shortwave infrared band (SWIR1)and Near Infrared band (NIR) while positive values
are shown in impervious surface area and soil surface
for all other band combinations (0.06 for soil with the
SWIR1 and NIR combination).
In this study, we calculate and set up therelationship between NDVI, NDSI and NDWI in theselected pixels in the first trial map to evaluate thethreshold for landslide detecting areas. In case of deadweak or removal of vegetation during the landslide
occurrence, the soil will be exposed as a result. The
NDSI and NDWI hence would increase comparing to
the case of vegetation cover to the positive or nearpositive values (around zero). The results show theranges of NDSI and NDWI are from -0.5 to -0.1 andfrom -0.38 to 0.14, respectively. Since positiveFig. 5 NDVI calculation in study area
(left:2013/12/02 and right: 2015/07/01)

Fig. 6 NDSI (left) and NDWI (right) on 2015/07/01

Fig. 7 Land use change area and land degradation area
detecting from Landsat calculation

NDWI values come with low NDVI data in post even,it thus may refer to water or impervious surface.
NDWI that less than -0.32 obtains high NDVI
(greater than 0.5) so that it would reflect thevegetation type cover. The threshold of -0.32
therefore is primary set for NDWI value. NDSI
bellowing -0.3 obtains NDVI values of around 0.4
and above. It also refers to vegetation cover area. Low
values of vegetation index (reduction in green surfacearea) locate in the NDSI range from 0 to -0.2. In thiscase, -0.2 is set as NDSI threshold value. We will
locate pixels obtaining NDSI that is higher than -0.2
and NDWI that is higher than -0.32 as landslide
detection area (Fig. 7). In this detecting area, averagevalues of NDVI and NDWI are 0.338 (from -0.04 to0.48) and -0.199 (from -0.32 to 0.14), respectively.
Inventory approach
In this part, we applied the land use map, which
was released by JAXA in September 2016 to290

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

demonstrate land cover situation in North Vietnam in
the year 2015. In this version, land use cover includes
9 categories namely: water site(1), urban and built up(2), rice paddy(3), crops(4), grassland(5), orchards(6),bare land (7), forest (8) and mangrove (9) (Fig. 8).
There are 9 main geology categories in this study
area:Carboniferous/Permian(CP),Cambrian/Ordovician(CmO),Devonian(D),Jurassic/Cretaceous(JK),Ord
ovician/Silurian(OS),Permian/Triassic(PTr),Proteroz
oic/Cambrian(PtCm),Quaternary(undivided) (Q), andSilurian/Devonian(SD) (Fig. 9). The slope angle weredivided into six sub-classes: i) <10 ° ,ii)1020°,iii)20-30°,iv) 30-40°,v) 40-50°,vi) >50°.
The elevation is also grouped into six subclasses: i)<100 m, ii) 100 m- 200 m, iii) 200 m – 300 m, iv) 300
m – 400 m, v) 400 m – 500 m and vi) >500 m.

Fig. 8 Land use map

Historical landslides and its causative factors
We analyse 1049 historical landslide events in2013 when combining with causative factors such as
slope angle, elevation, geology and land use. The
analysis results show that landslide den-sity is thehighest (27.5%) in the slope class iii (20-30 ° ),following by class ii (25.8%) and class iv (21.9%).
The numbers of landslide events decrease when theslope angle increase from group iii (20-30 ° ) togroup 6 (>50°). This overall trend is similar in all
three provinces BK, HG and TQ. In general, landslidedensity concentrates in the elevation range from
100m–300m (48.23%). The most common elevation
class in landslide occurrence site in BK, HG and TQ
is iii (200m-300m), ii (100m-200m) and i (<100m) in
respectively (Fig.10 & Fig.11). The susceptible
geology type in landslide sites in BK area D and PTr
while Devon dominates landslide areas in HG and TQ.
Among 9 land use classes, historical landslides occurs
mainly in forest (BK and HG) and crops (TQ). In allarea, grassland also perform in intermediate level (1626%) (Fig. 12).

Fig. 9 Geology mapa)Fig. 2 Slope classification in historical landslide 2013

Fig.11 Elevation classification in historical landslide

Fig. 2 Land use classification in history landslide 2013b) Landslide classification
According to Chandrasekaran, et al [18]. Internaland external causes are two main types of landslidecauses. Internal causes include seepage erosion,
weathering and progressive failure. Some
illustrations of external causes are slope geometry
changes, slope toe under loading, slope crest loading,water regime changes or drawdown as well as
vibrations and shocks. The external causes can also
be divided into two sub categories: natural cause andhuman cause. For the case of North Vietnam,
regarding to the external mechanism, the naturalcause for landslide often relate to slope undercutting
by wave strength and stream erosion, heavy andprolonged rainfall events, critical groundwaterfluctuation and upper slope loading by dense
vegetation. The human cause can be seen from somemain activities such as slope overloading, slope
cutting activities for houses and road constructions,cultivation activities (vegetation removal) andquarrying or mining activities. Our study in 2016
about the regional precipitation distribution in
Vietnam [8] showed that an average annual rainfall inthe studied site (1975-2006) is about 1997 mm (1762
mm in the North). Rainfall fluctuates significantly
around the year. Approximately 80% of total rainfall
occurs during summer time. This area has high denseof streams and rivers. The main river systems in
North Vietnam [19] appear high density. With regards
to geomorphic condition, mountain regions in thisarea are heavily divided and eroded by thick dense oftributaries so that erosion and sliding activities
become more seriously, especially under the
influence of heavy rainfall the main landslide
triggering factor here. Considering the climatic,hydrological and geomorphic conditions as well as
human-related activities in North Vietnam, in this291

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

TYPE 1
Rainfall on
Construction sites

TYPE 1
Average angle
Average elevation (m)Typical rangeof slope angle
Maximum angle
Minimum angle
Max elevation (m)Min elevation (m)

29
265
Bac
Ha Tuyen
Kan Giang Quang
62
65
63
8
8
3
862 710
580
60
70
28

Original slope
Construction
Embankment

RainfallLand use:
Forest/ Crops

TYPE 2

Rainfall

32
250
Bac
Ha Tuyen
Typical range
Kan Giang Quangof slope angle
54
Maximum angle
63
49
9
8
6
Minimum angle
782 670820
Max elevation (m)808246
Min elevation (m)Average angle

Average elevation (m)TYPE 2
Rainfall on
Natural slope

Slip surface

Slip surface

1

Slope cutPTr (Permian/Triassic)
D (Devonian (unidivided))
Ha Giang: SD (Silurian/Devonian)Tuyen Quang: SD (Silurian/Devonian)

TYPE 3Rainfall and water drawdown onbanks of reservoirs or streams
RainfallSlip surface

High water level

Land use:
Crop
Grass land
Rice paddy

Drawdown
2

Bac Kan:
29 ‹

24
228
Bac
Ha Tuyen
Typical range
Kan
Giang Quangof slope angle
Maximum angle
60
18
8
7
Minimum angle
550
130
Max elevation (m)15284
Min elevation (m)Land use: Forest

GeologySlop features

TYPE 3

Average angle

Average elevation (m)High water level

Geology:
SD (Silurian/Devonian)Slop features

32 ‹Geology:Slop features

24 ‹D (Devonian (unidivided))

Fig. 13 Illustration of three landslide types[3]

Metternicht, G., Hurni, L. and Gogu, R.: Remote sensing oflandslides: An analysis of the potential contribution to geospatial systems for hazard assessment in mountainous
environments, Remote Sens Environ., Vol. 98, No. 2-3, pp.
284-303, 2005.
[4] Dieu, T. B.: Modeling of rainfall-induced landslide hazard for
the Hoa Binh province of Vietnam, Nor Univ Life Sci. , 2012.
[5] Behling, R., Roessner, S., Golovko, D. and Kleinschmit, B.:
Derivation of long-term spatiotemporal landslide activity-A
multi-sensor time series approach, Remote Sens Environ. ,Vol. 186, pp. 88-104, 2016.
[6] ODM.: Digital Elevation Model (DEM) of Vietnam, OpenDev
Mekong.,2016,
Availableathttps://data.opendevelopmentmekong.net/vi/dataset/digitalelevation-model-dem[7] AWRP.: Monthly rainfall in North Vietnam, Acad Water
Resour Planning, Minist Agric Rural Dev Vietnam, 2016.
[8] Thuy, T. T. Le, Kawagoe, S. and Suzuki, K.: Study on thevariation of regional precipitation characteristics based on
meteorological spatial data in Vietnam: Relationship between
GCMs output and historical data, Vietnam-Japan Work
Estuaries, Coasts, Rivers 2016, Ho Chi Minh City, Vietnam,
2016.
[9] RCFEE.: Forest ecological stratification in Vietnam, Res
Cent For Ecol Environ Vietnam., 2011.
[10] USGS.: Landsat 8, US Geol Surv., 2015. Available at
http://landsat.usgs.gov/landsat8.php[11] DWR.: Management of Hydraulic system in Vietnam, Dir
Water Resour Minist Vietnam Agric Rural Dev, 2016.
[12] JAXA.: High- Resolution Land Use and Land Cover Map ofNorthern Region of Vietnam (Released in Sep.2016/Version
16.09), Adv L Obs Satell – ALOS Res Appl Proj EORC,
JAXA.,
Availableat
http://www.eorc.jaxa.jp/ALOS/en/lulc/lulc_vnm.htm[13] Broxton, P. D., Zeng, X., Sulla, M. D. and Troch, P. A.: A
Global Land Cover Climatology Using MODIS Data, J Appl
Meteorol Climatol., Vol. 53, No. 6, pp. 1593-1605, 2014.
[14] Mwaniki, M. W., Agutu, N. O., Mbaka, J. G., Ngigi, T. G.
and Waithaka, E. H.: Landslide scar/soil erodibility mapping
using Landsat TM/ETM+ bands 7 and 3 Normalised
Difference Index: A case study of central region of Kenya,
Appl Geogr., Vol. 64, pp. 108-120, 2015.
[15] Gao, B. C.: NDWI - A normalized difference water index for
remote sensing of vegetation liquid water from space,
Remote Sens Environ., Vol. 58, No. 3, pp. 257-266, 1996.
[16] Takeuchi, W. and Yasuoka, Y.: Development of normalized
Vegetation, soil and water indices derived from satellite
remote sensing data, J Japan Soc Photogramm Remote Sens. ,Vol. 43, No. 6, pp. 7-19, 2004.
[17] Deng, Y., Wu, C., Li, M. and Chen, R.: RNDSI: A ratio
normalized difference soil index for remote sensing ofurban/suburban environments, Int J Appl Earth Obs Geoinf. ,Vol. 39, pp. 40-48, 2015.
[18] Chandrasekaran, S. S., Senthilkumar, V. and Maji, V. B.:
Landslides in Nigiris: Causal factors and remedial measures,
Indian Geotech Conf IGC 2016, 2016.
[19] Hue, T. T.: Research on evaluation of the river bank sliding
hazard in mountainous region in the North Vietnam, Vietnam
Geogr Acad, 2004.
[20] Ko, F. W. Y. and Lo, F. L. C.: Rainfall-based landslide
susceptibility analysis for natural terrain in Hong Kong - A
direct stock-taking approach, Eng Geol. Vol. 215, pp. 95-107,
2016.
[21] VIGMR.: Geology hazard and natural disaster warning
program, Vietnam Inst Geosci Miner Resour, 2014.

study, we divide the landslides into three majorcausing types: i) Type 1: Rainfall on construction
sites, ii) Type 2: rainfall on natural slope, and iii)
Type 3: Rainfall and water drawdown on banks ofreservoirs or streams(Fig.13). Type 1 refers tolandslide on artificial slopes that are resulted mainly
from road and house constructions after heavy or
prolonged rainfall events. Type 2 belongs to the casethat slopes are not significantly modified by humanactivities[20] under the influences of rainfall triggeringfactors. In type 3, water fluctuation especially rapid
drawdown in a relationship with rainfall event thus
are major attributions to landslides that occur on theslope facing water sites such as rivers, ponds andreservoirs. Regarding to historical landslide data in
2013, only 1.34 % and 7.54% of landslide events areclassified in type 3 and type 2, respectively. Type 1
dominates in all three provinces (from 83.7 % in HG
to 94% in BK).
DISCUSSIONS AND CONCLUSIONS
Above discussions lead to our consideration forfurther study on the landslide issues in upper stream
regions in Vietnam. However lacking in-formation oflandslide scales (height, depth and area) throughout
surveys are main limitations of this study. Outputs ofthis paper, which are mainly based on historical data
in a relation-ship with Landsat instrument, would beconsidered as initial assessment results of landslide
is-sue in those four provinces in North Vietnam.
Further studies should be implemented withrequirements of site surveys for position and scaleverification and landslide hazard mapping as well as
training model for rainfall induced land-slide andwater level simulations.
ACKNOWLEDGMENT
This research was supported by the Social
Implementation Program on Climate Change Adaptation
Technology (SI-CAT) of MEXT, Japan.

REFERENCES
[1]

[2]

Hue, T. T.: Research on crack and subsidence hazards inmountainous region in North Vietnam, Vietnam Geogr Acad.,
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Tien. Bui. D, Owe, L., Inge, R. and Dick, O.: Landslide
susceptibility analysis in the Hoa Binh province of Vietnam
using statistical index and logistic regression, Nat Hazards. ,Vol. 59, pp. 1413-1444, 2011.

292

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THE QUALITY ANALYSIS OF BICYCLE ROUTES FORSUSTAINABLE URBAN MOBILITY IN THE WESTERN ZONE OF RIO
DE JANEIRO
Guilherme Marins Pessanha1, Jaime Massaguer Hidalgo Jr2.
Urban and Environmental Engineering1, Pontifícia Universidade Católica do Rio de Janeiro / Technische
Universitat Braunschweig, Brazil

ABSTRACT

In order to be an example of active urban mobility using bicycles, the city of Rio de Janeiro in Brazil, hasdeveloped the program "Rio de Janeiro, urban capital of mobility by bicycle", a program to increase the cycle
infrastructure that preceded the mega events; 2014 World Cup and the 2016 Olympic Games. This article aims toapply bicycle model analysis criteria and to promote the discussion about quality of bicycle facilities in the westof Rio de Janeiro and its structure legacy. The bicycle lanes and cycle paths of the Santa Eugênia Road inPaciência neighborhood and the Padre Guilherme Decaminada avenue in Santa Cruz neighborhood were
measured in order to highlight the real problems that are currently being faced in the specific spaces for bicycleuse. For the analysis of local conditions and the cycle paths, field trips were made by bicycle. The methodology
used has ten benchmarking criteria. The collected results point to good operating conditions but a lack ofcompliance with some minimum requirements for signaling, lighting and maintenance of bicycle ways
pavement. Thus, this study contributes to the analysis of the quality of cycle routes in the city by encouraging
sustainable urban mobility and its urban infrastructure itself.

Keywords: Urban Planning, Bicycle Facilities, Mobility.

Olympic Games. However, a cycling programme is
not only sustained by its extension, and a set ofsocio-spatial criteria is necessary for its
effectiveness. The Mobility Plan for Bicycles inCities, (Ministry of Cities, 2007), states that theconnection with different transport systems is a key
factor for bicycles to be adopted by the population in
their movements, the urban infrastructure of cities
must adapt to modal and adaptations should and canbe made. As a sample of existing bicycle
infrastructure, the Santa Eugênia Road cycle paths
were chosen in the Paciência neighbourhood andPadre Guilherme Decaminada Avenue in the Santa
Cruz neighbourhood, both in the western zone of
Rio de Janeiro. The west zone of Rio de Janeiro isrepresented as AP-5 (planning area 5) and comprises
five administrative regions with 21 districts
distributed in an area of 609.50 km² occupying about
42% of the city's territorial area (IPP, 2013 ). It is anarea of great real estate expansion of the city, where
the land use and occupancy patterns are
predominantly horizontal and the use of the bicycle
is frequent between residents and merchants.

INTRODUCTION
In the last decades, the use of urban mobility
policies by bicycles has gained prominence in theBrazilian scenario, especially in Rio de Janeiro. The
history of the Rio de Janeiro cycle routes began in
1991, when the first cycle routes were built from a
program to redevelop the seafront known as “RioOrla” (Rio Seaboard). The program has built 23 kmof bicycle lanes designed mainly for leisure. Since
1993, and with the influence of ECO92 (United
Nations Conference on Environment andDevelopment), which the city of Rio de Janeiro has
hosted, the Municipal Environment Secretariat was
created. The city government has incorporated theprogram "Rio, urban mobility capital by bicycle"
into the urban mobility plan of the city as analternative transportation and as a modal element oftransport for short distances with the ability tointegrate BRT systems (Bus Rapid Transport), trains
and subway. The bicycle plan of the city of Rio deJaneiro had the goal of expanding its extension from150 km in the year 2009 to 450 km by the end of
2016, a period in which the city received the Mega
events such as World Cup 2014 and the 2016 Rio

Padre Guilherme Decaminada Avenue
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The bicycle system of Av. Padre Guilherme
Decaminada is 3.60 km long (Mobility and Culture,2016), composed of a shared bicycle path in the
sidewalk of the neighbourhood functioning as an
axis between the train station of Santa Cruz andAvenida Brasil, Paracycles, lighting and signage. It
has an intense flow of people due to the services andschools in the surroundings. The flow of cyclists andpedestrians is intense in the cycle path as well as theflow of private vehicles in the neighbourhood.
Santa Eugenia RoadThe cycle path of the Santa Eugenia Road has
similar characteristics, with a 6.00 km extension(Mobility and Culture, 2016) divided between ashared cycle path on the sidewalk and the cycle path.
It is located along the intense chain of services,
schools and hospitals and goes to the train station ofPatience and the station of BRT Santa Eugenia.

Fig. # 1: Padre Guilherme Decaminada Avenue
Designed by co-author

The Santa Eugenia Bus Rapid Transport (BRT)
station is one of the many stations that make up asegregated collective transportation road that runs
through the western zone of Rio de Janeiro
implemented for the 2014 World Cup and 2016
Olympics Games. Bicycle as a means of transport in
the west of Rio de Janeiro is a common practice, due
to local economic conditions and precarious accessto public transportation. For the reasons presented,
the cycling systems cited were chosen for theapplication of the evaluation criteria of a bicycle
system proposed in the “Caderno das Ciclovias”.

Fig. # 2:Santa Eugenia Road. Designed by co-author

METHODOLOGY

Study of the route and section markings

The present article makes a qualitative analysis of
the bicycle paths and bicycle lanes of two importantroutes for the displacement of the local population.
Based on this diagnosis, a critical analysis is carriedout in these two routes and their connections withthe public transport, focusing on the compliancewith the criteria of the Caderno das Ciclovias,
nonconformities and suggestions for improvements.
To do this, maps and photos of the research scopewere compiled. After this survey of documentation,a search was made for bibliographic references thatindicated temporal results of the goals and actions
proposed, from the period of 2013 to 2016 by the
public and private partnerships in the period of theworks.
From the observed references, the total route ofbicycle route was divided into 2 distinct sections
with the objective of a specific evaluation for eachcycleway analysed.
In the figures below, we observe the geographic
maps and studied in this article.

In possession of the aforementioned maps of thetwo avenues, the bicycle paths and their facilities
were marked with a purple and light blue line. Eachextension of the bicycle paths was evaluated as wellas small sections due to different conditions along
the two avenues.
Method and Measurement Criteria’s
Based on the research carried out in thetheoretical references, it was defined that the"Brazilian Bicycle Mobility Program" and its"Reference Notebook for the elaboration of:
Mobility Plan by Bicycle in Cities" indicates thecriteria for the elaboration of the collection table for
Data and metrics appropriate to a bicycle system.
The main purpose of such table is to raise thesituation of these cycle routes following minimum
criteria and suggest improvements to expand theconnectivity and meet the criteria required in theBrazilian Bicycle Mobility Program.

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the conforming and nonconforming conditions ofthat urban space of the city of Rio de Janeiro.
The table was divided into two topics. The first
topic relates the Basic Elements for Projects with the
purpose of detailing the criteria for evaluating thequality of the cycle paths of this research. This topic
was divided into 10 questions with the objective of
evaluating the following criteria: 1 - Geometric
Project; 2 - Cyclist Useful Space; 3 - Traffic
Moderation - measures for the humanization of thecity; 4 - Runs and Tracks of Cyclists; 5 Intersections and Crossings; 6 - Paving; 7 Drainage; 8 - Lighting; 9 - Parking for Bicycles; 10 Bicicletário. The second topic aimed to analyze theintegration of the bicycle with the collective
modalities in the following points: 1 - bicycle andbus; 2 - bicycle and train; 3 - bicycle in BRT;
To measure, the following criteria were adopted:a)b)

Adoption of a Bicycle Conformity Index – BCI
With possession of the notes of each section, by
avenue and relating all evaluation criteria, we
decided to adopt an Index of Compliance with theBrazilian Bicycle Mobility Program with thenecessary adaptations for an adequate assessment.
The adapted weighted average formula was chosen
to facilitate readers' understanding and is also
applied to large works contracts in Brazil and thecity of Rio de Janeiro, and is accepted by fiscal audit
courts.
BCI = {(∑Basic Project Elements Criteria
Applicable) x 8 + (∑ Integration Criteria withcollective modals Applicable) x 2} / 10

The criteria receive a score for each Section
The possible punctuation are : Not
Conformity (zero point up to 0,59 points),
In Conformity, need improvements (0,60
points up to 0,79 points) e In Conformity(0,80 points up to 1,00 point);

The Evaluation Criteria
The selected criteria were taken from theBrazilian Bicycle Mobility Program in chapters 3
and 4. The topic lists the Basic Elements for Projects
has the following criteria:

If the sum of the points attributed to acertain section of cycling route is <0.60 it isconsidered Non-Conforming the use of
bicycles in this place because it does notcontemplate 60% of the analyzed criteria; If
the sum of the points attributed to aparticular section of cycle path is ≥ 0.60
and < 0.80, it is considered Partially
According to the use of bicycles in thissection, since it presents more than 60% of
the analyzed criteria, and in this way, there
is The need for improvements in order tohave the perfect state of use and its
connections with the public transportsystems evaluated; And if the sum of thepoints assigned to a given section of
cycling track is > 0.8 and ≤ 1.00, the use of
bicycles as In Conformity is adopted, since
it can reach 80% to 100% of the criteria
assessed.

Geometric design - the arrangements anddimensions of bicycle spaces will always depend on
five factors, namely: the minimum dimensions
required for the safe circulation of bicycles; Theremnants of spaces or the rearrangements of parts or
all of the existing roads, converting to the bicycles aslice of the road system; The creativity of designers
by combining techniques with existing opportunities
in urban spaces, adapting them to the needs ofcyclists.
Useful space of the cyclist - the standard bicyclein Brazil has a longitudinal dimension of about 1.75
m. The width of 1.00 m results from the width of thehandlebar (0.60 m), plus the space required for the
movement of the arms and legs (0.20 m on eachside). The template to be adopted, however, forsafety measures, shall be higher by 0.25 m in height
and on each side, in order to maintain the cyclists'balance. (Brazilian Bicycle Mobility Program, page99.) See figure 2 the useful space of the cyclist in
centimetres.

These evaluation criteria were applied during themonth of February 2017 in 2 field visits during themorning, afternoon and evening periods. At eachstart and end point, the bicycles were parked for theappropriate notes. With the notes, it was possible tocalculate the BCI (Bicycle-Rate Conformity Index)
of each of the small sections and then add themusing a simple average formula that we will see.
Thus we will have different notes for each shortsection evaluated and a general note for each scopeof each cycle of the survey, giving an overview ofFig. # 3: Cyclist parameters in Brazil
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Source: Programa Brasileiro de Mobilidade Por
Bicicleta, page. 99.

drainage in cycle paths, cycle paths or routes where
there is bicycle traffic. Considering that the size ofadult bicycle wheels is greater than 0.60m, the space
between the closing transverse bars being less than
0.50m will prevent their falling into the drainage
area.

Traffic moderation - measures for humanization of
the city As a measure of moderation of traffic
directed to the circulation of bicycles, it isrecommended to use cycle paths near the bed of thecollecting ways. Corner radius reduction; • Changeof texture and color of the lining of the cycle lane; •Adoption of central islands separating fl ows; •Demarcation of crosswalk;Illumination - When using poles of the existing
electrical network, it is recommended to place metalrods in a lower position than is normally used forillumination of the entire track. The height should be
between 2.60m and 3.20m, making access to theluminaire difficult for anyone without the use ofstairs or other elements that raise their height.

Cycle lanes and lanes - Cycle lanes are dedicated tothe exclusive circulation of bicycles, separated fromthe other runways by embankment, with a minimumof 0,20 m of unevenness, which is usually higher
than the car lane Motorized. In the road system, it
can be located along the central bed or on the
sidewalks. Bicycle lanes is the space destined to thecirculation of bicycles, contiguous to the raceway of
automotive vehicles, being separated of it bypainting and / or devices limited denominated oftacks by the Brazilian Transit Code.

Parking for bicycles - Two bicycles are inscribed ina rectangle of approximately 1.70m x 1.60m.
Bicycles - Bicycles are characterized as long-termparking lots, large number of seats, access control,
whether public or private.
The topic related to the integration of the bicyclewith the collective modes has the following criteria:Intersections and crossings - Will be evaluated in
the crossings: the Circulation Channelized in
Crossings with Ample Side Space, Circulation with
Little Side Space, Shared Circulation, Upper
Crossings. Rotary - Roundabouts are considered bymany experts dangerous for pedestrians and cyclists.
However, this concept has to be relativized,
according to their sizes and positions in the territoryof a city or region. Rotates with inclusion of special
spaces for the bicycle In Brazil it is still notcommon.

Bicycles and buses - bus shelter with paracycle,
containing eight places for bicycle parking. The
project was awarded in competition in Finland at the
National Bicycle Year in that country in 1996. The
project was part of a paper presented by Maija
Rahka at the Velocity Congress in September 1997
in Barcelona.
Bicycles and trains - There are bicycles in thevicinity of the train stations near the section
evaluated.

Paving - The basic requirements for a bicycle lane in
relation to the pavement are as follows: the rollingsurface must be regular, waterproof, non-slip and, if
possible, pleasant in appearance. Due to the close
proximity of the bicycle lane with the pedestrian
walk, it is desirable that the surface of the bicycle
lane and that of the lane be visually differentiated sothat there is no invasion of the bicycle path by thepedestrian as well as the invasion of the ride by thecyclist. Cycle paths are not subjected to great efforts,
Requiring a larger structure than that used forpedestrian routes.
Drainage - The drainage of the bicycle lanes should
be as natural as possible, taking advantage of the
topography of the site, thus avoiding the installationof sophisticated networks for the drainage ofrainwater. When there is greater freedom of tracing(especially on leisure cycle routes), cuts andembankments should be avoided, as soil movements
always create some drainage problems that imply
erosion or need for clearing. The position of thelobes in the mouth of a wolf is an important aspect
regarding the safety of the cyclists, referring to the

Bicycles and BRT - evaluated the existence ofparking for bicycles on weekdays, in the vicinity of
BRT stations near the evaluated section.
EVALUATION OF RESULTS
Cycle routes and cycle routes of the Santa Eugênia
Road in the Paciência neighbourhood, BCI = 0.61
STATUS = In Conformity, with suggestions for
improvements.
Table 1 - BCI Santa Eugenia Road
Santa Eugênia RoadBCI = 0,61
divided into sections
Section 2.1
0,63
Section 2.3-2.5
0,67
Section 2.6-2.13
0,66
Section 2.14
0,67
Section 2.15
0,59
Source: Own authorshipComments and results of the criteria
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. Geometric Design
Average = 1.0 - Conformed
Technical comment: Safe circuits and allow thevisualization of the section to be covered.
. Useful space of the cyclist
Average = 0.75 - Conformity, needs improvement.
Technical comment: The minimum dimensions of
1.20 required for circulation are respected, but insome cases the pedestrian walkway suffers
bottlenecks. Traffic moderation
Average = 0.60 - Conformity, needs improvement.
Technical comment: There is a lack of elements forthe reduction of the turning radius of corners andsignalling on the bicycle lane. As well as a moreobjective demarcation in relation to the pedestrianrange. Cycle tracks and tracks
Average = 0.60 - Conformity, needs improvement.
Technical comment: There are excerpts where theboundary between cyclist and sidewalk lanes are notwell delimited.
. Intersections and crossings
Average = 0.60 - Conformity, needs improvement.
Technical comment: In Brazil it is still not common
crossings with satisfactory safety conditions for the
rider. In the evaluated sections they are restricted tothe end of the pivot radius.
. Paving
Average = 0.65 - Conformity, needs improvement.
Technical Comment: Paving is either precast
concrete or concrete block, both suitable. But theconservation is irregular. Leveling for crossing is themost critical point. Drainage
Average = 0.62 - Conformity, needs improvement.
Due to the irregular state of conservation of thepavement, imperfections and unevenness, the waterflow is compromised creating areas and allowing the
growth of unwanted vegetation.
. Lighting
Average = 0.60 - Conformity, needs improvement.
Technical comment: illumination is interrupted orcompromised by existing vegetation. Bicycle parking
Average = 0.61 Conformity requires improvement.
Technical comment: Bicycle stands are public andcan be found mainly near public buildings or nearcorners. Along the stretches there is no presence ofbicycle lifts. Connectivity to public transport
Average = 0,38 - Not in conformity
Technical comment: Not all train stations areprepared to receive the cyclist, in some of them it isnecessary to go up or down a ladder carrying thebicycle. In the trains the schedules allowed for thebicycles are reduced and there is no such integration
with the BRS.

See in the table below the results found for each
Section of the cycle ranges and an integral
evaluation of the whole cycle cycle:
Table 2 – BCI Padre Guilherme Decaminada
Padre Guilherme
Decaminada Avenue
BCI = 0,67
divided into sections
Section 1.1
0,74
Section 1..2
0,82
Section 1.3
0,77
Section 1.4
0,78
Section 1.5-1.6
0,76
Section 1.7
0,84
Section 1.8
0,77
Section 1.9
0,75
Section 1.10
0,60
Source: Own authorshipComments and results of the criteria. Geometric Design
Average = 1.0 - Conformed
Technical comment: Safe circuits and allow thevisualization of the section to be covered.
. Useful space of the cyclist
Average = 0.78 - Conformity, needs improvement.
Technical comment: The minimum dimensions of
1.20 required for circulation are respected, but insome cases the pedestrian walkway suffers
bottlenecks. Traffic moderation
Average = 0.67 - Conformity, needs improvement.
Technical comment: There is a lack of elements forthe reduction of the turning radius of corners andsignalling in the sections in bicycle-band. Cycle tracks and tracks
Average = 0.65 - Conformity, needs improvement.
. Intersections and crossings
Average = 0.64 - Conformity, needs improvement.
Technical comment: In Brazil it is still not common
crossings with satisfactory safety conditions To thecyclist. In the sections evaluated, they are limited tothe distance at the end of the turning radius of thepavement. Paving
Average = 0.80 - Conformity.
Technical Comment: Paving is either precast
concrete or concrete block, both suitable. But
conservation is irregular.
. Drainage
Average = 1.0 - Conformity.
The blocking paving in some sections works with adrainage element.
. Lighting
Average = 0.75 - Conformity, needs improvement.
Technical comment: Crossings have irregularlighting
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. Bicycle rental
Average = 0.65 In Compliance, you need
improvements.
Technical comment: Bicycle stands are public andcan be found mainly near public buildings or nearcorners. Along the stretches there is no presence ofbicycle lifts. Connectivity to public transport
Average = 0.43 - Nonconforming.

1-2014/2012/lei/l12587.htm>.
Acess
on:
10/03/2017.
[2] BRASIL. Lei nº 9.503 de 1997. Código deTransito
Brasileiro.
Availableon:<www.planalto.gov.br/ccivil_03/leis/L9503.htm>. Acess on: 15/02/ 2017.
[3] Ministério das Cidades (2007) Programa
Brasileiro de Mobilidade por Bicicleta –Bicicleta Brasil. Caderno de referência paraelaboração de plano de mobilidade por
bicicletas nas cidades. Brasília: Ministério das
Cidades. Available on: <www.cidades.gov.br>.
Acess on: 15/02/2017.
[4] Inatti,G “Mobilidade e Cultura de bicicleta no
Rio de Janeiro”,ed.1 Vol. 1, Rio de Janeiro Ed.
Transporte Ativo, 2016[5] IPP-Instituto Pereira Passos “Cadernos do Rio
deJaneiro,2013”.
Availableon:
http://www.armazemdedados.rio.rj.gov.br/arqui
vos/3295_religiao.PDF . Acess on 02/05/2017

CONCLUSION
By the methodology applied, the bicycle system of
the Estrada Santa Eugenia reached an BCI = 0.61
and the Padre Guilherme Decaminada Avenue an
BCI = 0.67. Both are compliant with the applicables
criterias, but need improvements mainly inconnectivity with modal systems and safety ofcrossings. It is necessary to adapt the train stations
for the handling of bicycles, and to create bicycle
stands with an infrastructure that can attend to thecyclist needs and secure the bicycle. The parameters
established for analysis are physical andinfrastructure and establish direct influence on the
choice of the bicycle as an element of mobility. The
results presented in this article highlight the need tobroaden the research on the public policies adopted
in the City of Rio de Janeiro to transform the bicycle
into a complementary system and integrated with theother modes of public transport in the city.

[6] Programa Brasileiro de Mobilidade por
Bicicleta – Bicicleta Brasil; Caderno dereferência para elaboração de Plano de
Mobilidade por Bicicleta nas Cidades. Brasília:Secretaria Nacional de Transporte e da
Mobilidade Urbana, 2007
[7] Programa Cicloviário do Distrito Federal:
Sistema Cicloviário Intermunicipal, Integrado
com outros modais de Transporte e açãoeducativa - ABCP – Associação Brasileira deCimento Portland. Programa Soluções para
Cidades.

REFERENCES[1] BRASIL. Lei nº 12.587 de 2012. Institui as
Diretrizes da Política Nacional de Mobilidade
Urbana.
Availableon:<https://www.planalto.gov.br/ccivil_03/_ato201

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COMPARATIVE ANALYSIS OF PAVEMENT FRICTION
PREDICTION MODELS
Luciana Omar,1, Karim Ismail2 and Abd El Halim O. Abd El Halim3
Faculty of Engineering and Design, Carleton University, Canada

1

ABSTRACT
Pavement friction is an important operational variable that affects the safety and efficient operation of
highways. Pavement friction measurement is a relatively complex and resource-intensive process, thus limiting
data availability. This is especially problematic when studying extensive road networks such as interjurisdictional highways in North America. Other measurements of pavement conditions, however, are readily
available through automated techniques using road analyzer vehicles that can potentially travel at free-flow
speed along highways. This study explores the prediction of pavement skid number measured using a lockedwheel tester on provincial highways in Ontario, Canada. The study compares different model structures:
multivariate regression and structural equation modelling. The explanatory variables available for all sites were:
pavement age, traffic and loads, and macrotexture, which was measured using an instrumented vehicle that laser
scanners pavement surface. A subset of these sites had mix-design information available and is considered in a
separate analysis with more explanatory variables, but a more limited sample size.
Keywords: Skid Resistance, Macrotexture, Multivariate Regression Model, Structural Equation Modelaims to develop and compare multivariate statisticalmodels of pavement friction prediction using fielddata collected by ARAN, mix design and operational
characteristics of the roads. The results willcontribute to a comprehensive knowledge base to
guide transportation agencies in decision-making
regarding maintenance services and highway safety.

INTRODUCTION
Pavement skid resistance, or friction, refers to
the force that resists the relative motion between avehicle’s tire and the pavement surface. Pavement
friction is considered one of the most important
indicators of road safety [1]. In general, drivercontrol is related to the friction available at the tirepavement interface; the higher the levels of friction,
the greater the vehicle control [1]. Pavement friction
is a function of pavement surface texture thatcombines two scales of surface texture properties:
microtexture (texture wavelength range from 1 μm
to 0.5 mm and vertical amplitude less than 0.2 mm)
and macrotexture (texture wavelength range from
0.5 mm to 50 mm and vertical amplitude between
0.1 mm and 20 mm) [1] [2].
In North America, friction field measurements
are usually taken using a device called ASTM E-274
Brake Force Trailer; however, these tests arelaborious, as is the data entry into a Pavement
Management Systems (PMS). As a result, roadagencies may not fully implement and integrate thedata into existing performance models. These
performance models also receive pavement
condition information from field data collected using
a state-of-the-art device called an Automatic Road
Analyzer (ARAN), a high-speed road analyzer.
Despite its strengths, ARAN is not readily used in
conducting a comprehensive evaluation of pavement
surface friction. There is an overall need to explore
alternative approaches to identifying friction
deficiencies. To address this need, the present study

BACKGROUND
Previous studies have suggested that it ispossible to estimate friction using statistical models
that correlate pavement textures with other variables
related to aggregate properties, mix parameters, androad characteristics (e.g., traffic, loads, road design,and environmental conditions). Reference [3]developed a method that can used in models forpredicting changes in asphalt pavement skid
resistance as a function of aggregate texture, mixture
properties, and environmental condition. Reference[4] and [5] developed models for estimating friction
deterioration
that
incorporated
aggregatecharacteristics and mixture gradation. Reference [5],for instance, developed a model that correlated skid
resistance, initial and terminal, for asphalt
pavements based on multiple mix design, aggregatecharacteristics, and traffic level.
Reference [7] developed models for estimating
friction for asphalt concrete pavements using
mixture and aggregate gradation, cumulative Annual
average daily traffic, and equivalent single axle load.
Reference [7] also demonstrated that the percentage
of aggregates passing in different sieves were299

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significant predictors of pavement friction.
Reference [8] developed a model for predicting
skid number (SN) and mean profile depth
macrotexture (MPD) using mix design properties
and aggregate gradation. The results indicated that
SN could be estimated using mix design properties
and macrotexture.
In a recent study, [9] attempted to develop
models to predict SN that correlates MPD
measurements collected using a laser mounted in a
vehicle travelling at high speed (100 km/h). The
models exhibited a positive correlation between SN
and MPD when the MPD was less than 0.75 mm,
and a negative correlation when the MPD was morethan 0.90 mm. The authors also proposed reduction
factors for SN to account for cumulative traffic
volume.

characteristics of each road section were also
obtained from MTO. Pavement and operational
characteristics include information regarding yearsof service of the pavement after the most recent
maintenance or rehabilitation (pavement age),traffic, loads (ESAL), number of lanes, lane
distribution factor, type of asphalt mix, and mix
design parameters. The years of service of the 109
road sections ranged from two to nine years ofservice. Mix design information was available for 68
road segments.
The 109 road sections were divided into seventypes of asphalt surface courses: one road section ofrecycled hot mix 40 (RHM40), one road section of
hot mix HL type 1 (HL1), seven road sections of hotmix HL type 4 (HL4), 11 road sections of Stone
Mastic Asphalt (SMA), 44 road sections ofSuperpave 12.5 (SP 12.5), 23 road sections ofSuperpave 12.5 FC1 (SP 12.5 FC1), and 22 roadsections of Superpave 12.5 FC2 (SP 12.5 FC2).
Skid resistance measurements occurred in thefield using a Locked-Wheel Friction Tester (LWT),ASTM E-274 Brake Force Trailer, ASTM E274-97,
with a standard ribbed tire, ASTM E 501-97. The
weighted trailer was connected to a standard fleet
truck and travelled along wetted surfaces at aconstant speed of 65 km/h. The average of skid
resistance was generated over 20 to 30 meters ofroad

STUDY SITES AND DATA COLLECTION
The datasets used in this research were obtained
from the Ministry of Transportation of Ontario(MTO) for 109 road sections of asphalt surface
course within a variety of functional classes of ruralroads (divided and undivided, single and multiple
lanes) with speed limits of more than 80 km/h. The
field data, skid resistance (SN) and macrotexture(MPD), were collected in the between April andOctober of the years 2012 to 2015.
Information about pavement and operational
segment. The skid tests were performed on theleft wheel path of the outsider lane in both directionsof travel. In total, 1,544 tests were performed indifferent regions of Ontario’s road network. On
average, 14 skid tests were performed per roadsection, within a maximum of 33 tests in the longest
segments and a minimum of four tests in the shortest
segments.
Macrotexture measurements occurred in 87 roadsections using a high-speed road analyzer (ARAN).
ARAN is an example of a multi-purpose and multisensor data collection vehicle that employs cameras,
sensors, and an advanced laser scanner to survey
pavement distress, macrotexture, smoothness, andother relevant attributes. The ARAN laser
measurement system is based on regular contactlessscanning of longitudinal profile that computes
average depths in intervals of 20 meters long of thepavement surface macrotexture. To determine themacrotexture level for each road section themacrotexture measurements were computed as theaverage of the MPD readings for each road section.

Multivariate Regression
Multivariate regression using ordinary leastsquare (OLS) is the most widely and adaptablestatistical technique used to investigate therelationships between a single dependent variable(SN) and several independent variables [10]. The
objective of multivariate regression is to use
independent variables whose values are known topredict the single dependent dependent variable. In
the regression analysis each independent variable isweighted by the regression. The weights (β) denote
the relative contribution of each independent
variable to the overall prediction [10]. For eachvariable added to the model, several measures wereanalysed to determine their contribution to theoverall model fit regarding the increase in thecoefficient of determination (R2), decrease ofstandard error (SE), the significance of the partial
correlation (p-value), and the effects of collinearity.
Usually, the threshold value for excluding variablesfrom the equation is set at a p-value of 0.05 to 0.10.
The effects of multicollinearity were assessed using
the Variance Inflation Factor (VIF) with a thresholdof five [10].

METHODOLOGYFor prediction purposes, this study uses two
approaches: multivariate analysis and structuralmodeling.

Structural Equation Modelling
The structural models involve processing and
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goodness-of-fit of the proposed model
In a PA model, observed variables are
represented as rectangles. Direct effects between
variables are indicated using a single directional
arrow. The single arrow indicates directionality anddoes not imply causality. Curved double-headedlines between variables indicate correlations.
Independent variables are called exogenous anddependent variables are called endogenous. Finally,each endogenous variable has an error term, denotedby a circle pointing towards the specific endogenous
variable. The error term captures the unexplained
variance of the variable, which corresponds to theassumption that the variable was measured withsome degree of error [12].
The goodness-of-fit of the model is based on the
difference between the observed and the modelimplied variance-covariance matrices [13]. The mostcommon indicators are Chi-square, the goodness-of fit (GIF), the adjusted goodness-of-fit index (AGFI),and the root mean square of approximation(RMSEA) [12].
This research employed the software IBM SPSS
23 and IBM SPSS AMOS for multivariate and SEM
analyses, respectivelly.

testing a structural equation model (SEM). The
hypothesized model can be tested statistically in thesimultaneous analysis of the entire system ofvariables to determine if the goodness-of-fit ofmodels is satisfactory for the proposed relations
within the variables [11].
SEM is a statistical technique for multivariate
analysis similar to multivariate regression [10].
Reference [11] listed four main differences between
SEM and other multivariate techniques:
1. SEM takes a confirmatory technique for data
analysis, while other techniques are descriptive
and exploratory in nature.
2. SEM is a technique for testing hypotheses about
relationships among observed and unobserved(latent) variables. Other multivariate techniques
are exclusively based on observed variables.
3. SEM is also capable of dealing withmultivariate relations and estimating direct andindirect effects of variables.
4. SEM gives estimates of error varianceparameters. In other techniques, these errors are
ignored, which may lead to incorrectconclusions due to misleading regression
estimates.
Another important difference between SEM andother multivariate techniques is the impact of sample
size. While in the other multivarite the effects ofsample size are directly related to the probability ofdetecting statistical power (R2) at a specified level ofsignificance, in SEM these parameters are not the
only consideration. SEM requires sufficient numberof cases for the model to converge without improper
estimate parameters [10] [14]. Estimate parameters
include weights, covariances, variances, means, andintercepts.
SEM is more sensitive to sample size than othermultivariate techniques because some statisticalalgorithms used by SEM are unreliable with small
samples [10]. Generally, the more complex themodel the larger sample size is required. Small
sample size affects the ability of the model toestimate correctly error estimation. Larger samples
reduces the variability of the model and increases
the stability of the model. [10] [12].
As with the OLS multiple regression model,
SEM cannot be used to prove causality; rather, SEM
is a model-testing procedure used for evaluating
hypotheses of relationships among variables.
The most common types of structural equation
models are: path analytic models (PA), confirmatory
factor analysis models (CFA), structural regression
models (SR), and latent change models (LC) [12].
The main difference between the models is that PA
models account for observed variables only, while
the other three models account for the relationshipbetween observed and latent variables. This research
focus on development of a PA model for testingcorrelations between observed variables andData preparation
For modelling purposes, all of the independent
variables used in this study were graphicallyanalysed to meet three assumptions: normal
distribution, homoscedasticity, and linearity. The
frequencies of the data were plotted to verify
whether data distribution followed a Gaussian
distribution. Linearity was examined using bivariate
plots. The independent variables that violated theseassumptions were transformed using logarithm
function. Outliers were identified and removed by
calculating the median absolute deviation (MAD).
RESULTSThis section presents the modelling process todevelopfrictionprediction
modelsusing
multivariate regression. The SN was used as thedependent variable and 11 independent variables
that were tested as potential predictors. The 11
predictiors: MPD, a set of variables related tooperational characteristics and a set of variables
related to mix design characteristics.
The set of operational characteristics included
pavement age (Age) and annual ESAL per lane
(AESAL). Addicionally, a variable was created tocapture the effect of accumulated traffic loads overtime by multiplying the age of pavement by theannual ESAL (AgeAESAL). When the variable
AgeESAL was tested in the models, Age and
AESAL were not included.
The variables related to mix design
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characteristics included nominal aggregate size
(NMAS), percentage of voids in the mineralaggregate (VMA), percentage of air voids (VA),
percentage of asphalt content (AC), percentage ofaggregates retained sieve 4.75 mm (Co), percentage
of aggregates passing sieve 4.75 mm (Fi), and thepercentage of aggregates passing sieve 2.36 mm(FFi). In addition, one variable was created to
combine fine and coarse aggregates by dividing thepercentage of the percentage of aggregates passing
sieve 2.36 mm by the percentage of aggregatesretained sieve 4.75 mm (FFi / Co).

Structural Equation Model
Figure 1 shows a diagram of one of several
attempts to specify a PA model. The initial PA
diagram was based on hypothesized relationships
within variables and derived from the same Pearson
correlation matrix used in the multivariate OLS
regression. As in OLS regression analysis, theexogenous variables were assumed to be correlated.
By correlating these variables it was possible toassess the direct influence of exogenous variables(FFi/Co, VMA, NMAS, AESAL, Age, and MPD) on
the endogenous variable (SN). In addition, it waspossible to assess the indirect influence of mix
design and operational characteristics on SN through
MPD by using MPD as a mediator.

Multivariate Regression
The process of selecting variables to build themodel started by selecting the independent variables
that exhibit the highest correlation with SN in thePearson correlation matrix. After testing the 11
variables, only four contributed to the increase of R 2
and remained statistically significant. For models 1
to 3, the first variable entered in the model was the
AESAL because it exhibited the highest bivariate
correlation with the SN. This variable explained
0.349 percent of the variation (R2) of SN. The
second variable added in the model was MPD,
which contributed to an increase of R2 to 0.401. The
third variable added in the model was the FFi/Co
that contributed to an increase of R2 to 0.524.
Unpredictably, the variable Age did not exhibit
statistical significance for inclusion in the regression
model, despite theory stating that friction is affectedby the polishing effect of traffic over time.
Table 1 displays a summary of regression models
and their principal measures of overall fit for
multiple regression analysis using a stepwise
approach. In this approach, independent variables
were added or removed based on their statisticalsignificance. All of the predictor variables in themodels exhibited p-values less than 0.10 and the VIF
was lower than 1.5.

Fig. 1

The initial PA model exhibited an R2 of 0.536
with model fit of Chi–square and degrees of freedom
equal to zero, which indicated that the model issaturated. In other words, the model has too many
parameters and some goodness-of-fit indicators
could not be identified. Thus, the initial PA model
needed to be modified by eliminating non significant
parameters, or parameters that exhibited a p-value
above 0.1.
The correlations between MPD and NMAS,
VMA, FFI/Co, AESAL, and Age did not exhibit
statistical significance. MPD exhibited a statisticallysignificant correlation with SN only. SN exhibited astatistically significant correlation with two
variables, FFi/Co and AESAL.
As in the OLS regression analysis, thecorrelation of Age and SN was not statisticallysignificant. However, Age was kept in the SEM
model for further analyses of its correlation withother variables, and direct and indirect effects on
SN.
Figure 2 displays the modified PA model andregression results after excluding all non-significant
parameters except the variable Age.
In the modified PA model FFi/Co, AESAL,MPD accounted for the variance (R2) of 0.52 of SN.
The goodness-of-fit indexes calculated for themodified model indicated reasonably good fit. The

Table 1 Summary of models
Model
1
2

R2
0.349
0.401

Initial PA model specification

SE
4.929
4.778

Model Specification
β0 - β1 logAESAL
β0 - β1 logAESAL - β2MPD30.524 4.304 β0 - β1 logAESAL - β2
MPD + β3 FF/Co
Note: SE = Standard error of the estimate.
The equation for SN prediction withunstandardized coefficients and intercept is depicted
in Eq. (1).
SN = 75.09 - 4.98 logAESAL - 4.61 MPD +11. 9 FFi/Co(1)
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

model exhibited Chi-square of 1.2, degree of
freedom (df) of 2 and p-value of 0.543, whichindicated
nonsignificant
Chi-square.
Anonsignificant Chi-square is required for the
goodness-of-fit of the model and indicates that thetwo matrices, observed and variance-covariance, aresimilar. In other words, it indicates that thetheoretical model reproduces the sample variancecovariance relationships [13].

covariance determine the weight of direct andindirect effects on SN. The results indicated that
there is a negative relationship between the pairs
FFi/Co and Age, and FFi/Co and AESAL. This
result suggests that the mix design parameters havean influence on the other variables.
Table 3 also displays the variances for eachparameter in the model. The variances, also called
error term, indicate unexplained variance on thevariables due to the influence of factors that were
not contained in the specified model. All thevariables in the model exhibited significant levels ofvariance. The variance related to SN (eS) indicatedthat there is a measurement error of SN that was not
explained by the model.
Table 3 Variance and Covariance
VariableFig. 2Modified PA model

FFi/Co_Age
AESAL_Age
FFi/Co_AESAL

The other indicator (GFI, AGFI and RMSEA)
also performed around the acceptable range ofmodel fit with a GFI of 0.991, AGFI of 0.93, and
RMSEA of 0.000.
Table 2 displays the estimated regression results.
The unstandardized coefficients represent theamount of change in the endogenous and mediatorvariables for each unit in changing in the exogenous
variable. The unstandardized coefficients areequivalent to the OLS regression coefficients. The
standardized coefficients are used to assess thecontribution, or importance, of each predictor
variable to each outcome variable. The value of
unstandardized and standardized coefficients
indicated that the parameter related to mix design(FFi/Co) and the parameter related to the operational
condition of the roads (AESAL) exhibited
significant influence on SN prediction. MPD
exhibited minor influence on SN. Age exhibited apositive and nonsignificant influence.

FFi/Co_Age
AESAL_Age
FFi/Co_AESAL
FFi/Co
AESAL
Age
eM
eS

Estimate
Covariance-0.1430.004-0.041
Correlation-0.3070.003-0.393
Variance
0.038
0.285
5.784
0.054
16.977

0.007
0.056
1.145
0.011
3.362

p-value
0.036
0.984
0.009

0.001
0.001
0.001
0.001
0.001

Table 4 displays the results of the analysis of thetotal, direct, and indirect effects of Age on MPD andSN.
Table 4 Total, direct and indirect effects

Table 2 Regression estimates
Estimate
Coefficients
Unsta.
Stand.
0.411
11.884-0.438-4.987-0.176-4.6140.062
0.152-0.024
0.002

Std.
Error
0.068
0.180
0.016

Total
-0.002
0.163

Indirect
0.000
0.011

Std.
Error

pvalue

3.243
1.180
2.495
0.254
0.014

0.001
0.001
0.070
0.549
0.862

Results indicate that Age exhibited insignificant
direct effect on MPD, and positive direct effect on
SN. Age exhibited a slight indirect effect on SN
using MPD as mediator.

The PA models provided estimates for eachrelationship in the model. These estimates are
displayed in Table 3. The estimated correlation and

The theoretical model included four explanatory
variables that resulted in an R2 of 0.52. The
regression weight for Age was positive andVariable
SN_ FFi/Co
SN_ AESAL
SN_MPD
SN_ Age
MPD_Age

MPD
SN

Age
Direct-0.0020.152

Model Modification

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

statistically nonsignificant. Therefore, Age was
excluded from the model. The model without Age
exhibited fit measures (variances, covariances,
correlations, standard errors, and p-values) similar tothe previous model. The equation for SN prediction
with unstandardized coefficients and intercept is
depicted in Eq. (2).
SN = 75.10 – 4.98 logAESAL – 4.61 MPD +11.88 Fi/Co

REFERENCES[1] W. Hall, K. L. Smith, L. Titus-Glover, J. C.
Wambold, T. J. Yager and Z. Rado, "Guide for
Pavement Friction", National Cooperative
Highway Research Program, Washington, 2009.
[2] AASHTO, Guide for Pavement Friction,
Washington: American Association of State
Highway and Transportation Officials, 2008.
[3] M. A. Ahammed and S. L. Tighe, "Long Termand Seasonal Variations of Pavement Surface
Friction", In Proceeding of the 2008 Annual
Conference of the Transportation Association of
Canada , Toronto, 2008.
[4] D. A. Noyce, H. U. Bahia, J. M. Yambo and G.
Kim, "Incorporating Road Safety into Pavement
Management: Maximizing Asphalt Surface
Friction for Road Safety Improvements",
Midwest Regional University Transportation
Center, Wisconsin, 2007.
[5] E. Kassem, A. Ahmed, E. A. Masad and D. N.
Little, "Development of Predictive Model for
Skid Loss of Asphalt Pavements", Journal of
the Transportation Research Board, vol. 2372,
2013, pp. 83-96.
[6] A. Rezaei, "Development of a prediction model
for skid resistance of asphalt pavements", 2010.
[7] G. S. Awoke, "Estimating The Friction
Performance of Hot Mix Asphalt Pavements
Based on Aggregate Properties and RouteCharacteristics: Analysis, Modelling andValidation," College Park, 2011.
[8] M. Rajaei, N. R. Sefidmazgi and H. Bahia,"Establishment of Relationship Between
Pavement Surface Friction and Mixture Design
Properties", Transportation Research Board,
vol. 2457, 2014, pp. 114-120.
[9] J. N. Meegoda and S. Gao, "Evaluation of
pavement skid resistance using high speed
texture measurement", Journal of Traffic andTransportation Engineering, vol. 2, no. 6, 2015,
pp. 382-390.
[10] J. F. Hair, W. C. Black, B. J. Babin and R. E.
Anderson, Multivariate Data Analysis, New
Delhi: Pearson Educational Limited, 2015.
[11] B. M. Byrne, Structural Equation ModelingWith Amos: Basic Concepts, Applications andProgramming, Ney York: Routledge, 2016.
[12] M. S. Khine, Application of Structural Equation
Modelling in Educational Research andPractice, Rotterdan: Sense Publishers, 2013.
[13] R. E. Schumacker and R. G. Lomax, "A
Beginner's Guide to Structural Equation
Modelling", New York, NY: Taylor & Francis
Group, 2010.
[14] R. B. Kline, Principles and practice of structural
equation modeling, vol. 2, New York: Guilford
Press, 2005.

(2)

CONCLUSION
This study compared two multiple regression
approaches, multivariate regression (OLS) andstructural equation model (SEM), for developmentof models for pavement friction prediction. The
results indicated that OLS and SEM exhibitedcomparable predictive models in terms of coefficientof determination, R2, despite of limited sample sizeused in SEM analysis.
The SEM approach allowed statistical analysis
that could not be measured using OLS. SEM
allowed to assess correlation, covariances of pairs of
predictors, and direct and indirect effects on SN. The
assessment of covariance and correlation analysis
within predictors indicated a negative correlationand covariance between FFi/Co and Age, andbetween FFi/Co and AESAL. Assessment of thedirect and indirect effects of Age on MPD and SN
indicated a positive direct effect of Age on SN and
an insignificant indirect effect on MPD.
The models showed that SN can be predicitedwith a fair coefficient of determination using
variables related to traffic and loads, macrotexture,and mix gradation. The variables AESAL and MPD
exhibited negative correlation with SN, while thevariable FFi/Co exhibited positive correlation with
SN.
This research used limited data to develop themodels; new field data are planned to be acquired tovalidate the models. Further research is needed to
explore the influence of mineral hardness, physicaland geometrical characteristics (e.g., angularity,
shape, and texture), and abrasion of aggregates on
SN. There is also a need to develop models
employing skid resistance measured with LWT andwith a smooth tire, because a smooth tire is moresensitive to macrotexture than a ribbed tire and theresults might differ from those presented in thisstudy.
ACKNOWLEDGEMENTS
This research was supported by the Ministry ofTransportation of Ontario, Highway Infrastructure
Innovation Funding Program and the Natural
Science and Engineering Research Council of
Canada.
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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

APPLICATION OF MEMETIC ALGORITHM FOR SOLVING
THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
Chaowalit Hamontree１, Jiraporn Chuenjai2 and Nawaporn Chamnanketgorn3
1Department of Industrial Engineering, Faculty of Engineering
2King Mongkut’s Institute of Technology Ladkrabang,

Thailand
ABSTRACT
Most importantly, vehicle routing problem is one of logistic problems that impact on the economy which
includes in business and industry. It is very important to manage the transportation system properly. This
research is proposed the Memetic Algorithm (MA) to solve vehicle routing problems with time windows(VRPTW) and also capacity of vehicles constrains. The objective of this research is to find the minimize travel
distance, and number of vehicles. A memetic algorithm has been developed to solve VRPTW by combining a
genetic algorithm based on suitable encoding and genetic operators, with a local search procedure. Therefore,
the experimental result shows that the memetic algorithm contributes a new good solutions and performs better
than genetic algorithm but unable to get to the best results. However, for better analysis of the results, thesensitivity analysis is performed in order to investigate the effect of parameters, which are crossover rate,
mutation rate, and population on the total distance criteria.
Keywords: VRPTW, Memetic Algorithm, Genetic Algorithm, Local Searchalthough they can find near-optimal, or in somecases optimal, solutions much faster.
The main objective of this research is to find aset of routes that will minimize the total travelling
distance of all vehicles in a VRPTW with Memetic
Algorithm (MA). MA is a class of stochastic global
search heuristics in which Evolutionary Algorithms
based approaches are combined with local searchheuristics techniques.
The organization of this paper presents thememetic algorithm for solving the VRPTW. In thefirst section, problem definition is described. In thesecond section, memetic algorithm and local search
are illustrated. Then, computational results are
conducted to evaluate the performances. Finally,
conclusion is explained in the last section.

INTRODUCTION
The Vehicle Routing Problem (VRP) is a generalclass of problems in which a fleet of vehicles basedat one or several depots needs to be routed for acertain number of customers located in different
places to minimize the number of routes, total
travelling time and distance between all vehicles.
VRP with time windows (VRPTW) is a
generalization of VRP with additional restrictions,where each customer must be supplied within a
specific time interval. The delivery of all vehicles
dispatched from the single depot should satisfy thedemand of all customers within their required time.
Vehicle routes should be designed in such a way thateach customer can only be visited once and the total
demand of all customers in any particular routeshould not exceed the capacity of the vehicle.
Meanwhile, each vehicle route must begin and end
at the depot.
VRPTW has already been proven to be an NPhard problem [7]. Many researches proposed exact
methods and heuristics to solve this type of problem.
Kolen et al. [5] developed a branch and boundapproach to solve the VRPTW. Desrochers et al. [1]proposed a column generation approach that solved
the Solomon's benchmark instances. Fisher et al. [2]proposed a K-tree relaxation approach to solve twoof Solomon's benchmark instances. Instead, various
heuristic or metaheuristic methods are applied tothese types of problems. Compared to the traditional
optimization approaches, heuristic and metaheuristic
methods cannot guarantee optimal solutions,

PROBLEM DEFINITIONIn this section, the study focused on the vehicle
routing problem with time windows. The center
node is called the depot with a set of customer N to
be visited. The depot node is denoted as 0. Each arc
in the network represents a connection between two
nodes and also indicates the direction it travels. Each
route starts from the depot, visits customer nodes
and then returns to the depot. The number of routes
in the network is equal to the number of vehicles
used. One vehicle is dedicated to one route. A cost
𝑐𝑖𝑗 and a travel time 𝑡𝑖𝑗 are associated with each arcof the network.
This assumption makes the problem simpler,
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

N V

because numerically the travel cost 𝑐𝑖𝑗 , the travel
time 𝑡𝑖𝑗 and the Euclidean distance between thecustomer nodes equal each other. Each customer in
the network can be visited only once by one of thevehicles. Every vehicle has the same capacity 𝐶 andeach customer demand 𝑑𝑖 , must be equal to thesummation of all demands on the route travelled by
vehicle 𝑘 , which means that no vehicles can beoverloaded. The time windows constraint is denotedby a predefined time interval, given an earliest
arrival time and latest arrival time. The vehicles
must arrive at the customers not later than the latest
arrival time. Each customer also imposes a service
time to the route, taking consideration of loading andunloading time of goods. Moreover, vehicles arealso supposed to complete their individual routes
within a total route time, which is essentially thetime window of the depot. VRPTW can be statedand solved by mathematical programming models[8] as shown in follows.

 xijk  1 𝒇𝒐𝒓 𝒊 ∈ {𝟏, … . , 𝑵},Ni  0 k 1

(4)

ijk

N

N

 x   x  1 𝒇𝒐𝒓 𝒊 = 𝟎, 𝒌 ∈ {𝟏, . . , 𝑽},
j 1

ijk

j 1

ijk

(5)
N

N

i0

j0

 di  xijk  C 𝒇𝒐𝒓 𝒌 ∈ {𝟏, … . , 𝑽},
N

(6)

N

 x (t  f  w )  r 𝒇𝒐𝒓 𝒌 ∈ {𝟏, . , 𝑽},(7)i 0 j 0

ijk

ij

i

i

v

t0  w0  f 0  0, 𝒊 = 𝟎,
V

(8)

N

 x (t  t  f  w )  t
k 1 i  0

ijk

i

ij

i

i

j

𝒇𝒐𝒓 𝒋 ∈ {𝟏, . , 𝑵},(9)ei  (ti  wi )  li 𝒇𝒐𝒓 𝒊 ∈ {𝟏, . , 𝑵},(10)
The objective function of this model is tominimize the total travelling distance by all vehicles
to satisfy the demands of all the customers. The
constraint in Eq. (2) and (3) ensure that exactly one
vehicle enters and departs from each customer aswell as from the depot. For each vehicle, the numberof visits must be equal to the number of departuresfrom each customer. There are at most 𝑉 routes
going out of the depot shown in Eq. (4). The
constraint in Eq. (5) specifies only one vehicle
leaves from and returns to the depot. The constraint
in Eq. 6 imposes an upper bound which is thevehicle’s capacity to the accumulated demand ofeach route. The constraint in Eq. (7) is the maximum
travel time constraint. Finally, constraint in (8) to(10) ensures schedule feasibility and time windows
are respected.
MEMETIC ALGORITHM
The Memetic Algorithm nomination was first
introduced by Moscato [6]. MA belongs to the larger
class of evolutionary algorithms that use techniques
inspired from natural evolution. It is a combinationof genetic algorithm (GA), first introduced byHolland [4], and local search procedures that
intensify the search. GA mimics the natural selection
and natural genetic selection process concurrent withartificial system for optimizing problems. GA isinspired from the biological evolution, whereas MA
mimics cultural transmission based on the meme
concept analogous to the gene in GA. It is also
called hybrid genetic algorithm or genetic local
search algorithm. Since then, MA has been used in

Minimize
N N V

(1)

i0 j0k1

Subject to
N V xijk  1 𝒇𝒐𝒓 𝒋 ∈ {𝟏, … . , 𝑵},V x  V 𝒊 = 𝟎,

Decision Variables:𝑡𝑖= arrival time at customer 𝑖;
𝑤𝑖 = waiting time at customer 𝑖;
𝑋𝑖𝑗𝑘 = if there vehicle 𝑘 travels from customer
𝑖 to customer 𝑗,and 0
otherwise. (𝑖 ≠ 𝑗; 𝑖, 𝑗 = 0, 1, . . . , 𝑁).
Parameters:𝑉= total number of vehicles
𝑁 = total number of customers
𝑐𝑖 , = customer 𝑖 (𝑖 = 1, 2, . . . , 𝑁)
𝑐0 = delivery depot
𝑐𝑖𝑗 = traveling distance between customer 𝑖 tocustomer 𝑗;
𝑡𝑖𝑗 = travel time between customer 𝑖 andcustomer 𝑗;
𝑚𝑖 = demand of customer 𝑖;𝐶= capacity of homogeneous vehicles;
𝑒𝑖 = earliest arrival time at customer 𝑖;𝑙𝑖= latest arrival time at customer 𝑖;𝑓𝑖= service time at customer 𝑖;
𝑟𝑘 = max route time allowed for vehicle 𝑘;   cx
ij ijk(3)i0k1(2)i0k1306

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

several works and has proved its efficiency to solve
VRP. In the following sections, we present theprocedures used in the MA as shown in follows.

Reproduction
For the VRPTW problem, the encoding of acandidate has to deal efficiently with the two level
information of the multiple trip solution. Allocationof routes to vehicles, and the delivery order for eachroute. In the adopted representation, thechromosome (individual) contains several trips; theterm “trip” is used for the genetic representation to
designate a complete journey of a vehicle. Each
route is composed by an ordered subset of customers.

Step 1 Initialize. Construct the first generation ofsolutions. To produce a solution we use aconstructive heuristic.
Step 2 Improve the solutions. We use a local searchmethod to improve the initial solution and eliminate
duplicate solutions.
Step 3 Create the next generation. Use reproduction,
crossover, and mutation from genetic operators to
produce the non-optimized next generation. Each of
the genetic operators selects parent solutions fromthe previous generation. The length of a solution isused as the evaluation function.
Step 4 Improve next generation. Use a local search
procedure to replace each of the current generation
solutions except the reproduced ones by the local
optimum. Eliminate duplicate solutions.
Step 5 Evolute. Repeat Steps 3 and 4 until atermination condition is reached.

CrossoverIn this part, two chromosomes are selected asparents to crossover by means of the crossover rate
which is the probability of crossover. A random
number between 0 and 1 is then generated. If therandom number is smaller than the crossover rate,
two chromosomes will undergo reproduction to
generate new members as offspring that may be
included in the next generation. Otherwise, theoffspring will be the same as the parents.
Mutation
Mutation is another important role, which brings
more variation to the population to explore
diversified solutions and prevent the premature local
convergence. The mutation rate measures theprobability that mutation is applied to a gene in theoffspring. If a randomly generated number between
0 and 1 is smaller than the mutation rate, the gene
undergoes the mutation process. Otherwise, themutation does not take place for that gene.

Fig. 1 Memetic algorithm
Selection

The proposed MA for VRPTW is described in detailand steps as shown in Fig. 1.

In MA, an appropriate selection method should
be applied to select the fittest chromosomes from thecurrent population to the next generation. The
memetic progresses to find the optimal or nearoptimal solution.

Initial population
The initial chromosomes are randomly generated
by randomly assigning customer numbers to thegenes. First, an equal probability is assigned to every
customer. A random number is then created todetermine which customer is chosen for the next
gene in the chromosome. After one customer issettled in the chromosome, all of the remaining
customers are again assigned the same probability
and are selected by generating another random
number.

LOCAL SEARCH
For each solution generated for the initial
population, we use a local improvement procedure.
The proposed local search uses exchange method for
VRPTW. The procedure works as follow:


307

Exchange: swaps one or two consecutive
customers pertaining to one or two trips

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

Table 4 Comparison performance measurement
between the published best solution and oursolution

COMPUTATIONAL RESULTS
There are three data sets from the Solomon’s
VRPTW instances including of customer size 25, 50,
and 100 customers, all distances are represented by
Euclidean distance, and the speed of all vehicles isassumed to be unity. The locations of the stores are
expressed using the (x, y) coordinates on the
Euclidean plane. The problem has been solved byusing two methods including of genetic and memetic
algorithms.
The memetic parameters are very important forthe success of a memetic algorithm, as well as forthe representation of the individuals, the initial
population and the genetic operators. Based on
preliminary computational experiments, we set thefollowing genetic parameters:Problem
R101.25
R101.50
R101.100

CONCLUSION
This work presents a memetic algorithm forsolving the classical vehicle routing problem withtime window. MA provides a very interesting
approach to solve problems where an exact method
cannot be applied. However, it is a bid disappointed
that MA took many generations to find a solution,and unable to get to the best results.

Table 1 The best solution of Solomon’s publishedR101.25
R101.50
R101.100No.
customer
25
50
100(The best solution)
No.
Distance
vehicle
8617.1
121044.0201637.7

REFERENCES[1] Desrochers, M., Desrosiers, J., and Solomon, M.,"A new optimization algorithm for the vehicle
routing problem with time windows,"
Operations Research, vol. 40, 1992.
[2] Fisher, M., Jornsten, K., and Madsen, O.,"Vehicle routing with time windows: Two opt
algorithms," Operations Research, 1997.
[3] Goldberg, D.E. “Genetic algorithms in search,
optimization, and machine learning. Boston”:
Addison-Wesley Pub. Co. 2004.
[4] Holland, John H. “Adaptation in Natural andArtificial Systems. Ann Arbor”: University ofMichigan Press. 1975.
[5] Kolen, A. W. J., Kan, A. H. G.R., andTrienekens, H. W. J. M., "Vehicle routing withtime windows," Operations Research, 1987.
[6] Moscato, P., 1989, On evolution, search,
optimization, genetic algorithms and martial
arts: Towards memetic algorithms, Caltech
Concurrent Computation Program, C3P Report.
[7] Savelsbergh, M. Local search for routing
problems with time windows. Annals of
Operations Research, 1985.
[8] Tan, K. C., Lee, L.H., and Ou, K., "Artificial
intelligence heuristics in solving vehicle routing
problems with time window constraints,"
Engineering
Applicationsof
Artificial
Intelligence, 200l.

Table 2 The result of genetic algorithm
Problem
R101.25
R101.50
R101.100No.
customer
25
50
100

No.
vehicle8
1220

Distance625.481157.1
2001.1

Table 3 The result of memetic algorithm
Problem
R101.25
R101.50
R101.100No.
customer
25
50
100

No.
vehicle81220% Deviation
GA
MA
1.35%
0.19%
10.83%
6.84%
34.40%
16.67%

The computational experiments show thatmemetic algorithm can generated a good solution tominimize the total distance. Table 4 shows thepercentage of deviation of the MA solutions against
the best solutions in the literature. It demonstrates
the position of MA is given a good solutions which
better than GA for all instances. For instance
R101.25, MA can give the good solution near the
optimal solution but slightly different for instance
R101.50 and also far away from the best solution for
instance R101.100. However, it cannot generate thebest solution for all instances.

The population size is set to 1000
individuals that are enough to guarantee alarge search space.
The crossover probability is set to 0.7 andthe mutation probability is set to 0.1.
The maximum number of generations in
our algorithm is set to 50,000.

ProblemPublished best
617.1
1044.01637.7Distance
618.3
1115.51910.8308

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THE EFFECT OF MODEL DOMAIN SIZE FOR UNSUPPORTEDPLAIN STRAIN TUNNEL HEADINGS IN UNDRAINED CLAY
1

Jim Shiau1, Fadhil Al-Asadi2
School of Civil Engineering and Surveying, University of Southern Queensland, Australia

ABSTRACTThis paper examines the effect of model domain size for unsupported plain strain tunnel headings inundrained clay. The tunnel heading models for different soil parameters (depth ratio C/D and strength ratio
Su/γD) are studied using the finite element limit analysis and strength reduction technique to determine the ideal
geometric parameters X/C, L/C, and B/C of established numerical models. The upper and lower bound limit
solutions are presented alongside finite difference results for validation. A thorough comparison between these
two methods finds a very good agreement. Design charts are established for a broad range of practical scenarios
using dimensionless ratios, similar to the traditional slope stability design chart. Typical examples are presented
to illustrate the usefulness for practicing engineers.
Keywords: Model Domain Size, Plain Strain Heading, Undrained Clay, Strength Reduction Method, Limit
Analysis, Design Chart
INTRODUCTION
The research of tunnel heading stability was
initiated with [1] who studied the plastic flow of clay
soil in vertical openings such as sheet pile walls anddrew comparison to the stability of a tunnel heading
face. Following this work, numerous studies werecompleted on centrifuge models by [2]. The work
was culminated by [3] who investigated theexperimental and theoretical undrained collapse of
three-dimensional cylindrical tunnel headings innormal consolidated kaolin under different geometry
and gravity regimes. [4 and 5] built further on thestability ratio by using upper and lower boundsolutions using the classical limit theorems fortunnel collapse in undrained cohesive conditions.

by which the material parameters need to be reduced
in order to attain a state of incipient collapse [14 and15]. A factor greater than one thus implies a stablesystem while a factor less than 1 implies that
additional strength is required to prevent collapse.
For Tresca material in this study, the strength
reduction factor can be viewed as a factor of safety(FoS) value shown in Equation (1).
𝑺

𝑭𝒐𝑺 = 𝑺𝒖𝒄(1)

Where Su is the ultimate undrained shear strengthof the soil, and Sc is the undrained shear strength of
the soil at collapse. This is a similar approach usedin Taylor’s design charts for slope stability analysis[16].
In general, the FE model domain size has to belarge enough to validate the assumption of an
infinite soil, but small enough to obtain accuracy
without large numerical CPU times. Over allowanceof the model domain would decrease the solution
accuracy in any numerical analysis, as moreelements would need to cover the entire soil area
[17-18]. Although this problem is of considerable
analytical interest, particularly in regard to thestability of tunnels, there is no current literature
stating the guideline in preparing the design modelso that the boundary conditions do not affectnumerical solutions.

With the development of computers over the lasttwo decades, numerical modelling has become auseful “must-have” technique for engineering
problem resolution [4]. A number of papers wereachieved in the numerical area of tunnel stability andsettlement prediction by [6-13]. In particular [6]extended the limit analysis theory on tunnel heading
by investigating a three-dimensional multiblock
failure mechanism for frictional and cohesive soil by
the use of a spatial discretization technique. Authorsin [7-9] recently developed a pressure relaxation
method and automatic mesh generation by making
use of FLAC script to conduct parametric studies
conveniently. Besides, both numerical and physicalmodelling have also been introduced recently ingeotechnical education by [10-13].
This paper utilises the finite element limit
analysis (OptumG2) and the strength reduction
method to study the effect of finite element model
domain size. The strength reduction analysis isproceeded by computing a strength reduction factor

This paper presents a comprehensive analysis forthe geometric parameters to generate precise plain
strain heading model in an unsupported excavationin green-field conditions. Based on these modified
geometric parameter ratios, strength reduction
technique using OptumG2 is used to determine thefactor of safety in cohesive soils over a wide309

parametric range. Numerical results are comparedwith the strength reduction technique using FLAC
and stability charts presented for practical uses.

base of the model (B). For any model the geometricparameters (L, X, and B) have to be defined toensure that the analysis results are not affected by
the boundary conditions.
In this paper, numerical result based on strength
reduction technique is represented by factor of safety(FoS) that is a function of the depth ratio (C/D) andstrength ratio (Su/γD).

STATEMENT OF PROBLEM
Figure 1 shows the problem definition of an
idealised tunnel heading. The problem is a twodimensional plane strain tunnel heading. The soil
medium is considered as undrained and is modelled
as a uniform Tresca material, which is the same as a
Mohr-Coulomb material with no internal friction
angle. The undrained shear strength (Su) and thesaturated unit weight (𝛾) are soil properties used,whilst the tunnel has diameter (D) and cover depth(C) above its crown, as shown in Figure 1.

𝑪 𝑺

𝑭𝒐𝑺 = 𝒇 (𝑫 , 𝜸𝑫𝒖 )(2)These dimensionless ratios allow the results ofthis study to be used in scenarios that are physicallydifferent, but where the soil strength ratio and thedepth ratio still fall in the parametric domain. To
cover all possible realistic ranges, the parameters
used in the study include Su/γD = 0.1 - 2 and C/D =1-6. This would ensure that the design charts
produced can be applied to many different tunnel
design and analysis problems, which are useful forpractical design purposes.
Figure 2 shows a typical finite element mesh of
the problem in this study. The boundary conditions
shown in Figure 2 are important to deﬁne thedomain boundary of the model. The smooth rigid
lining above and below the soil excavation isrestrained in the vertical (y) direction to reproduce
the nature of the tunnel linings and mining supports.
The base and sides of the model are restrained in thex and y directions.

Fig. 1 Problem Definition
The other unknown geometric parameters are thedistance away from the face of the tunnel heading(X), the length of the tunnel inside the model (L) andthe depth between the base of the tunnel and theFig. 2 Typical Mesh and Boundary Condition
Stability of plane strain tunnel heading models
were investigated using a factor of safety approach.
Factor of safety values were commuted in OptumG2
using FELA with strength reduction and werecompared with FLAC results. This method has been
widely used for slope stability analysis but is rarely
used for tunnel stability analysis. This strength
reduction technique will yield a factor of safety(FoS), which is not unfamiliar with practicing
designers.
Such a method involving factors of safety has
been described by [19] for slope stability. The factorof safety is defined as a ratio of the strength
necessary to maintain limiting equilibrium with thesoil’s available strength. The shear strength of thematerial is reduced until the limiting condition is
310

found. This can be compared to the studies
originated from [1] where the uniform surchargepressure is increased until the limiting condition isfound. If failure occurs initially, the shear strength of
the soil is increased by amplifying the cohesion andfriction angle until limiting equilibrium or failurestate is reached. Once the actual and critical strength
are known, the factor of safety can then be
calculated.

Fig. 4 Geometric Parameter Ratio L/C
Numerical results of averaged FoS from upperand lower bound solutions are shown in Figures 3-5
for various values of X/C, L/C, and B/C. In general
it can be concluded that the FoS values remain
constant for X/C ≥ 2.5, L/C ≥1.0, and B/C ≥ 0.25.
The constant FoS results indicate an optima domain
size for the problem in hand and ensure theboundary conditions have very little effect on the
results.

PARAMETRIC STUDIESAs shown in Figure 1, X represents the distanceaway from the face of the tunnel heading, L denotes
the length of the tunnel inside the model while B is
the distance between the base of the tunnel and thebase of the model. The effects of dimensionlessratios X/C, L/C and B/C on the obtained results are
examined in this paper.
Using the strength reduction technique within thefinite element limit analysis program OptumG2,
factor of safety (FoS) values were obtained for arange of parameters for an unsupported tunnel
heading in undrained soil. The two dimensionlessparameters used in the studies are the depth ratio(C/D) and the strength ratio (Su/𝛾D). It is important
to compare the finite element limit analysis, upperbound and lower bound with another numericalinvestigation. Using the finite difference technique,factors of safety have been calculated using FLAC
over the same parametric ranges. The numerical
procedures used in OptumG2 are based on the limit
theorems of classical plasticity [15].

Fig. 5 Geometric Parameter Ratio B/C
Dimensionless stability charts showing thenumerical results obtained in this study are presented
in Figures 6 and 7. In Figure 6, FoS increases
linearly as the strength ratio Su/γD increases. The
finite element upper bound solutions OptumG are ingood agreement with the finite difference results
FLAC. Also note that the rate of FoS increase isdifferent for each C/D value. The gradient of the line
is greater for smaller C/D values.

Fig. 3 Geometric Parameter Ratio X/C
Fig. 6 Comparison of FoS results with respect toSu/γD for various values of C/D

311

𝐸/𝐷 = 0.9133(𝐶/𝐷) + 1.297

Fig. 7 Comparison of FoS results with respect toC/D for various values of Su/γD(3)Fig. 8 Surface Failure vs. Depth Ratio

Figure 7 shows that the FoS decreases
nonlinearly with increasing depth ratio C/D for all
strength ratios defined as Su/𝛾D. The finite element
upper bound solutions are in good agreement withthe finite difference results. Note the strength ratio isnormalised with respect to the tunnel excavation
depth (D), and therefore the undrained shear strength(Su) remains constant throughout the increasing
depth ratios. Owing to the increasing overburdenpressure with the increasing of (C/D) and theconstant undrained shear strength (Su), it therefore
results in FoS values decreasing. This is in contrast
to the common belief that an increase to C/D always
results in an increase to FoS.
A simple observation can be made from Figure 1,
where the active force is the weight of soil and theresisting force is given by the shear strength of thesoil. For two proposed tunnels in the same cohesive
soil but at different depths, the tunnel with thesmaller active force (γC) will have a higher
probability of stability. This observation may not betrue in a soil with internal friction angle (ϕ≠0) due tothe additional shear strength (σtanϕ) and geometricalarching effects. In purely cohesive soils, the latterstill occurs, but its effect is not enough to overcomethat subsequent increase in active force.

Example: For an unsupported green-field tunnel,
determine the maximum extent of failure surface.
Parameters are given as C = 10 m, and D = 2.5 m.
1.
2.

For C/D = 4.0, Eq. 3 gives an E value of 12.38
m.
For C/D = 4.0, Figure 8 gives an approximate
E/D of 5.1 and therefore E value of 12.5 m.

Fig. 9 Total displacements and displacement vectors
for C/D= 1 and Su/γD= 2.0

EXTENT OF FAILURE SURFACE
Collapse of unsupported tunnel heading orvertical trapdoor inevitably lead to soil deformationof the ground surface. The extent (E) andmechanism of such failure can be explained byobserving some graphical outputs from OptumG2
such as the plots for power dissipation in shear.
In reality the deformation trough would be three
dimensional, but with the assumptions made, thelargest extent of plastic deformation in the heading
cross-section can be reasonably estimated. This
information of failure extent is important as it willassist practicing engineers in the decision making inmonitoring ground movements.
Figure 8 presents the surface failure ratio plot
where the surface failure ratio is a function of thedepth ratio. Regression of the chart gives thefollowing approximate linear equation.

Fig. 10 Total displacements and displacement
vectors for C/D=3 and Su/γD =2.0

312

continue. Parameters are given as Su = 50 kPa, γ = 18
kN/m3, C = 10 m, and D = 2.5 m.
3.
4.

Using C/D = 4.0, Su/γD = 1.11, Eq. 4 gives a
FoS of 1.62.
Using C/D = 4.0, Su/γD = 1.11, Figure 12 gives
an approximate FoS of 1.66.

Fig.11 Principle elemental stresses at collapse for
C/D= 3 and Su/γD= 2.0

An actual computer analysis of this particular casegives a FoS of 1.64.

Figures 9-10 show that the strength ratios haveminimal effect on the appearance and the area of the
failure, while the extent of the surface failure
increase with large values of depth ratios. Figures
11 shows typical tensor plots for principal stresses.
The blue vectors indicate the major principle stresses,
whilst the red vectors indicate the minor principle
stresses. For all cases, the vector fields are similar.
Vertical stresses are shown in the major external
failure zone just below the surface.

Analysis of a temporary unsupported tunnel heading
During the construction of a tunnel in soft soil, afactor of safety of 3 is targeted for a shallow tunnel
maintenance job. While the machine requires
maintenance, it will be unable to apply pressure to
the tunnel face for a short period. A decision needs
to be made whether stability will be maintained
during this period. Parameters are given as: Su = 30
kPa, 𝛾 = 18 kN/m3, C = 20 m and D = 5 m
1.

USING THE STABILITY CHARTS
2.

The stability design charts are best demonstrated
through a number of examples. The numericalresults have been used to produce design contour
charts for factors of safety in Figure 12. A designer
will use the chart to relate the depth ratio (C/D), soil
strength ratio (Su/𝛾D) and factor of safety for theparticular tunnel heading. This process would
predominantly be used in the initial design
procedure.
Figure 12 presents the design chart where thefactor of safety is a function of the depth ratio andstrength ratio. Regression of the chart gives thefollowing relationship with r2 = 0.99.
𝒔𝑪 −𝟎.𝟓𝟎𝒖
𝑭𝒐𝑺 = 𝟑 (𝜸𝑫) (𝑫)Using C/D = 4.0, Su/γD = 0.33, Eq. 4 gives a
FoS of 0.5.
Using C/D = 4.0, Su/γD = 0.33, Figure 12 gives
an approximate FoS of 0.52.

An actual computer analysis of this particularcase gives a FoS of 0.49. Therefore, in this case, afailure to supply heading pressure would result incollapse. Ground improvement is needed to increase
the soil strength.
Design of an unsupported tunnel heading
The soil properties are known at the tunnel
project site, and the diameter is specified. A target
factor of safety is chosen, and the designers need to
specify a maximum cover depth that will satisfy thetarget FoS.
Parameters are given as: Su = 100 kPa, 𝜸 = 18 kN/m3,
D = 5m, and the target FoS = 2(4)

Examples1.

Using both the design chart and the regressed
design equation, practical examples are presented for
either analysis or design purposes.

2.

Analysis of an existing unsupported tunnel

Using FoS = 2 and Su/γD = 1.11, Eq. 4 gives a C
value of 13.86 m.
Using FoS = 2 and Su/γD = 1.11, Figure 12
gives an approximate C/D value of 3 andtherefore C value of 13.5 m.

An actual computer analysis for this particular case(C value of 13.5 m) gives a FoS of 2.03

An existing mining excavation having no internal
heading pressure and no surcharge pressure,determine the factor of safety for operations to313

Fig.12 Stability chart for FoS with respect to C/D and Su/γD
Geoenvironmental Engineering, Vol: 136, pp.
215-229.
CONCLUSION[7] Shiau, J. S. and Kemp R. J. (2013). Developing
The effect of tunnel heading models for different
a numerical model for the stability design ofparameters (depth ratio C/D and strength ratio
tunnel heading. Third International Conference
Su/γD) were studied in this paper using a factor ofon Geotechnique, Construction Materials andsafety approach with the strength reduction
Environment, Nagoya, Japan, Nov. 13-15, 2013.
technique. It was found that results (FoS results and[8] Shiau, J. S., Sams, M. S., Zhang, J., & Kemp, R.
the extent of surface failure) are the most accurate
J. (2014). Settlement analyses of undergroundwhen the models have the geometric parameters:
circular tunneling in soft clay. In Geotechnical
X/C ≥ 2.5, L/C ≥1.0, and B/C ≥ 0.25.
Aspects of Underground Construction in Soft
Numerical results were obtained using both the
Ground, Seoul, 347-352.
finite element software OptumG2 and the finite[9] Shiau, J. S., Sams, M. S., & Kemp, R. J. (2014).
difference software FLAC. Based on these modified
Physical modelling and PIV analyses of an
results design equation and charts were produced
underground tunnel heading. In Geotechnicalaligned with examples to determine the stability of
Aspects of Underground Construction in Soft
excavated heading depths, such as idealised tunnel
Ground, Seoul, 61-66.
headings and long wall mining excavations as well[10] Shiau, J. S. and Buttling, S. and Sams, M.
as the extent of failure surface. The factor of safety(2016) Developing a project based learning
approach to plain strain heading stability is a usefulassignment for geotechnical engineering.
approach to the initial design stage as it always
Electronic Journal of Geotechnical Engineering,
provides direct information and understanding of20(18): 10113-10121.
tunnel stability.
[11] Shiau, J. S., Sams, M. S., & Lamb B. (2016).
Introducing Advanced Topics in Postgraduate
REFERENCES
Geotechnical Engineering Education – Tunnel
Modelling. International Journal of Geomate,[1] Broms, BB & Bennermark, H 1967, ‘Stability
10(1): 1698-1705.
of clay at vertical openings’, Journal of the Soil
[12] Shiau, J. S., Lamb B., & Sams, M. S.. (2016).
Mechanic & Foundations Division, Proceedings
The use of sinkhole models in advancedof the American Society of Civil Engineers, vol.
geotechnical engineering teaching. International93, pp. 71- 93.
Journal of Geomate, 10(2): 1718-1724.
[2] Atkinson, JH, & Cairncross, AM 1973,[13] FLAC 2003, Fast Lagrangian Analysis of‘Collapse of a shallow tunnel in a Mohr–Continua, Version 5.0, Itasca Consulting Group,
Coulomb material’, In Proceedings of theMinneapolis, Minnesota, USA.
Symposium on the Role of Plasticity in Soil
[14] OptumG2 2016,
Optum Computational
Mechanics, Cambridge, UK, 13–15 September
Engineering, Standard Version, Newcastle,
1973. pp. 202–206.
Australia.
[3] Mair RJ 1979, ‘Centrifugal modelling of tunnel[15] Taylor, DW 1937, ‘Stability of earth slopes.’
construction in soft clay’, PhD thesis,
Journal of the Boston Society of Civil Engineers,
University of Cambridge.
vol. 24, no. 3, pp. 197-246.
[4] Davis, EH, Gunn, MJ, Mair, RJ & Seneviratne,[16] Shiau, J, Sams, M & Chen, J (2016) Stability
HN 1980, ‘The stability of shallow tunnels &design charts for unsupported wide rectangularunderground openings in cohesive material’,tunnels. Electronic Journal of Geotechnical
Geotechnique, vol. 30, pp. 397-416.
Engineering, 21(1): 139-150.
[5] Sloan, SW, Assadi, A 1994, ‘Undrained[17] Shiau, J, Sams, M & Chen, J (2016) Stability
stability of a plane strain heading’, Canadiancharts for a tall tunnel in undrained
Geotehcnical Journal, vol. 31, no. 3, pp. 443clay. Electronic Journal of Geotechnical450.
Engineering, International Journal of Geomate,[6] Mollon, G, Dias, D & Soubra, AH 2010, ‘Face
10(2), Japan: 1764-1769.
stability analysis of circular tunnels driven by a[18] Bishop, AW 1955, ‘The use of slip circle in thepressurized shield’, Journal of Geotechnical &stability analysis of slopes’, Geotechnique, vol.
5(1), pp. 7-17.

314

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

APPLICATION OF HEC-RAS AND ARC GIS FOR FLOODPLAIN
MAPPING IN SEGAMAT TOWN, MALAYSIA
Noor Suraya Romali1, Zulkifli Yusop2 and Ahmad Zuhdi Ismail3
Faculty of Civil Engineering and Earth Resources, Universiti Malaysia Pahang, Gambang, Malaysia;
2
Centre for Environmental Sustainability and Water Security, Universiti Teknologi Malaysia, Skudai,
Malaysia; 3Faculty of Civil Engineering, Universiti Teknologi Malaysia, Skudai, Malaysia.

1

ABSTRACT
Nowadays, a risk-based flood mitigation concept has received more attention rather than the conventional
flood control approach in reducing the impacts of flooding. With the intention to assist in the management offlood risk, flood modeling is useful in providing information on the flood extend and flood characteristics. This
paper presents the application of HEC-RAS model to the development of floodplain maps for urban area in
Segamat town in Malaysia. The analysis used Interferometric Synthetic Aperture Radar (IFSAR) as the mainmodelling input data. Five distribution models, namely Generalized Pareto, Generalized Extreme Value, LogPearson 3, Log-Normal (3P) and Weibull (3P) were tested in flood frequency analysis to calculate extreme flows
with different return periods. Using Kolmogorov-Smirnov (KS) test, the Generalized Pareto was found to be thebest distribution for the Segamat River. The peak floods from frequency analysis for selected return periods were
input into the HEC-RAS model to find the expected corresponding flood levels. Results obtained from HECRAS model were used in ArcGIS to prepare floodplain maps for different return periods. The results indicatedthat most of the inundated areas in the simulated 100 year return period were also affected by 2011 historicalfloods. For 100 years flood simulation, the inundated area was almost 5 times larger than the simulated 10 years’flood.
Keywords: Floodplain Mapping, HEC-RAS, ARC GIS, Frequency Analysis, Segamat

Meanwhile, Cunha et al. [9] applied landmorphology approach to map the flood risk of
mainland Portugal. There is also a considerable
volume of published studies describing the role offlood modeling in the flood vulnerability assessment.
In literatures [12]-[14], flood modeling is used toprovide hydrological and hydraulics information forflood damage modeling.
HEC-RAS is one of the most widely used modelto analyze channel flow and floodplain delineation[10]. Khattak et al. [10] applied HEC-RAS and
ArcGIS in their study to map a floodplain of Kabul
River that lies in Pakistan. Similarly, Ullah et al.
[11] in their flood forecasting study of Kalpani River,
Pakistan used a combination of remote sensing,geographical information system (GIS), HEC-RAS(1D), and HEC-Geo RAS. HEC-RAS model was
found to give good performance where the simulated
results for both studies showed a close agreementwith observed water surfaces. Several otherapplications of HEC-RAS model can be observed in[15]-[17].
In Malaysian, the implementation of flood risk
management approach that is supported by modelingtools is still new [18], [19]. However, several floodmodeling studies have been carried out during thelast few years. Ab. Ghani et al. [19] had developed aflood mapping of 2007 Pahang River flood. In the

INTRODUCTION
In recent years, the conventional flood control
approach that focusing on structural flood mitigation
measures have been shifted to a risk-based flood
mitigation concept [1]-[3]. Flood risk is related totwo elements i.e. flood hazard and flood
vulnerability [4]. Flood hazard is the probability of aflood event to take place, while flood vulnerability is
the potential flooding impacts to community andassets which is normally associated with theassessment of property damages [4]-[5]. In moststudies i.e. [2], [3], [6], [7], the estimation of flood
damage was obtained using the combination of flood
characteristics, flood exposure and flood damage
function curve.
Flood modelling is important for the assessmentof flood hazard to show the magnitude of flood to acertain exceedance probability [4], while its function
in vulnerability assessment is to provide
hydrological characteristics for damage modelling.
The existing literature on flood hazard assessment is
extensive and focuses particularly on flood mapping(for example, [8]-[11]). Montane et al. [8] developed
a numerical floodplain model to map extreme floodof Meurthe River in France. The model usedhydrogeomorphological observations and LiDAR
DEM data to produce water depth mapping.
315

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

study, a digital elevation model (DEM) was
produced using a combination of digital topography
maps and satellite image. A few studies have applied
HEC-RAS and GIS techniques in flood modeling(e.g. [20]-[22]). Shahiriparsa et al. [20], [22] had
applied HEC-RAS to simulate flood zoning in Kota
Tinggi district in Johor state and Maka River districtin Kelantan state.
Flood modeling is an important tool in theassessment of flood risk for both hazard andvulnerability. Hence, this study aimed at developing
a floodplain map showing the extent of flood andproviding related flood characteristics information
for flood risk assessment purpose. The application of
HEC-RAS modeling for the selected study area in
Malaysia is presented.

(TIN). The DEM data used in this study was theInterferometric Synthetic Aperture Radar (ISFAR)
obtained from the Drainage and Irrigation
Department (DID) Malaysia.
Flood frequency analysis

HEC-HMS

Peak flow ofvarious ARI

Flow hydrograph of2011 flood event
HEC-RAS

Cross section
profileBoundary
condition
Hydrograph /Hydraulicparameters

Model set-up(HEC-RAS)
Run flood event

Study Area
The study area is Segamat River Basin, Johorwhich is located in the southern part of Peninsular
Malaysia. The aim is to provide flood mapping for
frequently flood affected areas in the Segamat town.
Segamat town is a medium size town located at thecenter of the Segamat district with an approximate
area of 12,875 hectares and 80,000 residents. The
town center is divided into two, which is Bandar
Atas (uptown) and Bandar Seberang (Crosstown).
Both neighborhoods are separated by Segamat River.
Bandar Atas is the original town center of Segamat
while Bandar Seberang is located at the other side
across Segamat River [23]. Figure 1 shows the
Segamat River that flows through the Segamat town.
Segamat River is located in 102° 49” E and 2° 30.5’
N. With a length of 23 km, the average width of
Segamat River is 40 m and is 14 m above sea level.
Segamat River is the tributary of Sungai Muar thatflow in Segamat town [24].
A series of major floods have occurred in the lastfew decades along the Segamat river. According tohistorical records, Segamat experienced flooding
during the 1950s, 1984 and more recently in 2006
and 2011. The flood disaster had caused severe
damages and inconvenience to the local community.

Floodplain modeling using
ArcGIS/HEC-GeoRAS
No
Flood validation
Run peak flow
ARI
Floodplain maps for various
ARI
Fig. 2

Methodology flowchart of floodplain
mapping

The initial step in developing flood plain maps isto provide peak flows for selected flood event anddifferent return periods [10]. The peak flows for 10,
25, 50, 100, 200, 500 and 1000 average recurrence
interval (ARI) were obtained by conducting flood
frequency analysis. While the peak flood of 2011
flood used in this study is 1238.2 m3/s, obtained
from hydrological modeling analysis using HECHMS. The steps followed with the hydraulics
modeling to translate the discharges into water levels,and the final step is the determination of theinundated extent areas for discharges corresponding
to different return periods.

METHODOLOGY
Flood Frequency Analysis
The research methodology generally follows thesteps shown in Fig. 2. The flood model is acombination of four elements i.e., hydrologic model,
hydraulic model, a tool for floodplain mapping andvisualization and the extraction of geospatial for use
in model [11]. A digital elevation model (DEM) wasapplied to provide the essential information. The
DEM refers to a topographic map which contains
terrain elevation properties. The DEM was used inorder to set up 2D models for processing the resultsof flood progression. DEM can be represented by araster map (grid) or as a triangular model network

EasyFit software was used to select the best
flood distribution model to calculate peak flows ofvarious ARIs. We used 52 annual maximum flow
data of Sg. Segamat gauging station (Site 2528414)
for the water years between 1960 and 2011,provided by DID. Five flood distribution models
were tested, namely Generalized Pareto (GP),Generalized Extreme Value (GEV), Log-Pearson 3(LP3), Log-Normal (LN) (3P) and Weibull (3P). The
goodness of fit test (GOF) of Kolmogorov-Smirnov(K-S) was used to evaluate and estimate the best316

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

fitted distribution. K-S at 5% level of significant(p<0.05) was used to define the best fit ranking. The

detailed description of flood frequency analysis is
described in [25].

Fig. 1 Location of the study area
and GP. The smallest values were obtained by
Weibull distribution.

HEC-RAS Modeling
As illustrated in Figure 2, a schematic geometry
model that consists of river cross section profile andbanks is required in a HEC-RAS model set up. The
hydraulic parameters required manning n values forthe land cover. Then the boundary condition was set
up to a condition of the river. In the next step, theyear 2011 floodplain was simulated in 1D result.
The 1D result was converted into 2D using HECGeoRAS software. The simulated floodplain wasverified with the 15 observed flood marks at various
location. Once the simulated floodplain is verified,the HEC-RAS was applied to simulate floodinundated area for various return periods [26].
In HEC-RAS, the data input requirement
consists of three main parts which are plan data,geometry data and flow data. Those requirements
have to be fulfilled before running the simulation.
The plan data is the first step in performing asimulation. The plan data will identify whichgeometry and flow data to be used as well as provide
a description and short identifier for the simulation.
If the geometry and flow data do not exist, thesimulation will not run. It also includes the flow
regime in the simulation option. Cross sections are
required at representative locations along the stream
and at locations where changes occur in discharge,
slope, shape, and roughness [26].

Table 1 Maximum flood for various return periods
based on GP, GEV, LP3, LN (3P) andWeibull (3P) distributions
ReturnPeriod(Years)
10
25
50
100
200
500
1000

Estimated flood discharge (m3/s)
WeiLN
GP
GEV
LP3
bull
(3P)
(3P)
541
830
616
666
176
943
1415
1099
1375
297
1362 2071
1563
2195
404
1914 2997
2112
3342
523
2642 4308
2755
4917
653
3971 6915 3280
6624
840
5354 9861
4651 10877
993

Table 2 GOF K-S ranking results for GP, GEV, LP3,
LN (3P) and Weibull (3P) distributions
Distributions
GP
GEV
LP3
LN (3P)
Weibull (3P)

RESULT AND DISCUSSION

Kolmogorov Smirnov
p-valueRanking
0.832
1
0.678
2
0.673
3
0.452
4
0.294
5

Table 2 shows the performance ranking based on
K-S GOF test. GP is ranked the first in terms of
performance, followed by GEV, LP3, LN (3P), andthe least for Weibull (3P). The ranking is based on
the p-value. A p-value closer to one indicates a
better-fit distribution. The highest p-value is 0.832
for the Generalized Pareto and the lowest is 0.294
for Weibull (3P). Based on the results, theestimation of peak flows using GP distribution was

Flood Frequency Analysis
The peak flows for 10, 25, 50, 100, 200, 500 and1000 return periods, calculated using GP, GEV, LP3,
LN (3P) and Weibull (3P) distributions are shown in
Table 1. It’s found that the predicted maximum
flood using GEV is the highest, followed by LP3
317

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

m3/s, 1914 m3/s, 2642 m3/s, 3971 m3/s and 5354
m3/s respectively.

used as the input into HEC-RAS model. The
estimated peak flows for 10, 25, 50, 100, 200, 500
and 1000 years ARI are 541 m3/s, 943 m3/s, 1362

Fig. 3 Water surface profile for 2011 flood

Note:= WS PF 1,(a)= Ground,(b)= LOB,= ROB

Fig. 4 Water surface profile for return period (a) 10 years (b) 100 years
flood, 10 and 100 years return period are shown in
Fig. 5, Fig. 6 and Fig. 7 respectively. The blue color
shows the extent of flooded area for depth between
0 to more than 1.2 meters.
Figure 5 shows that almost 45% of Segamat
town was affected during 2011 flood where 66% of
the area is inundated with more than 1.2 meters’
depth (dark blue area). Most of the affected area
were located at Bandar Seberang (crosstown) which
is at the other side across Segamat river. The
residential and commercial properties located at thecenter of the crosstown area i.e. Bandar Seberang,
Jalan Sia Her Yam, Jalan Ros and Jalan Genuang
experienced flood depth up to 2 meters. Kampung
Abdullah and Kampung Jawa were severely
affected during 2011 flood with flood depth morethan 3 meters.
The simulation results for 10 years return period(Fig. 6) indicate that only 7.43 km2 of the Segamat
town area was affected by flood. The most affectedarea with flood depth more than 1.2 meters was

Floodplain Mapping
A HEC-RAS hydraulic modeling set-up was
created to generate the water level due to the 2011
flood and subsequently the flood map for various
return periods. The comparison between thesimulated 2011 flood and the simulated 10 and 100
years return periods are presented. The crosssection of water surface elevation for 2011 flood isshown in Fig. 3. The blue line shows the level ofwater surface (WS), while the dotted black line
indicates the ground level. The purple and blue
dotted line represent the left of bank (LOB) andright of bank (ROB) respectively. The water levelproduced by 2011 flood are higher than thosesimulated for 10 and 100 years return period floods,
as shown in Fig. 4(a) and Fig. 4(b) respectively.
This indicates the extreme situations of 2011 flood.
The results of HEC-RAS model were thenexported to HEC-GeoRAS for flood map
generation. The simulated inundated areas for 2011
318

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

Kampung Chabong, Taman Pawana and Taman
Pemuda. On the other hand, the simulation of 100
years return period (Fig. 7) shows that almost 40
km2 of the area was affected by flood, which is 5
times larger than the simulated 10 years’ flood. The
results also indicate that most of the areas
inundated by the 100 years’ flood were also
affected by 2011 historical floods. Kampung
Abdullah and Kampung Tengah were most affectedwith flood depth more than 4 meters in certain partsof the area.

The results were validated by comparing thesimulated flood against the observed value at 15
stations for 2011 flood event. As shown in the 1:1
graph in Fig. 8, flood simulated flood depths are
acceptable with more than 91% accuracy comparedto the observed values. The simulated floodboundary is also close to actual flood boundary.

Fig. 8 Observed and simulated flood depth of 2011
Segamat flood
CONCLUSION
HEC-RAS model was applied to map theinundated area of Segamat town during the 2011
flood and simulate flood map under various return
periods. The modelling accuracy was validated
against observed flood marks of 2011 event. The
simulated flood depth is acceptable with more than
91% accuracy. It’s found that Generalized Pareto is
the best fit distribution model for peak discharge.
The estimated peak flows of Segamat River for 10,
25, 50, 100, 200, 500 and 1000 ARIs are 541 m3/s,
943 m3/s, 1362 m3/s, 1914 m3/s, 2642 m3/s, 3971
m3/s and 5354 m3/s respectively.
The simulation suggests that most of theinundated areas of 100 years’ flood were also
affected by the 2011 historical floods. For 100
years flood simulation, the inundated area wasalmost 5 times larger than the simulated 10 years’flood.

Fig. 5 Floodplain map of 2011 Segamat flood event

Fig. 6 10 years’ floodplain map of Segamat town

ACKNOWLEDGEMENTS
The authors would like to acknowledge
Universiti Malaysia Pahang and Universiti
Teknologi Malaysia for the financial support
through research grant Institut Inovasi Strategik
Johor (IISJ) Vot 15H00 and Department of
Irrigation and Drainage (DID) Malaysia forproviding data and relevant information.
REFERENCES[1] Merz B, Kreibich H, Schwarze R, and Thieken
A, “Review article “Assessment of economic

Fig. 7 100 years’ floodplain map of Segamat town

319

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

flood damage””, Natural Hazards and Earth
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[2] De Moel H, and Aerts JCJH, “Effect of
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[14] Vozinaki AEK, Karatzas GP, Sibetheros, IA,
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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EFFECT OF SATURATION ON STRENGTH BEHAVIOR OF
SOAPSTONE
Ravikant R Singh1, Darga Kumar Nandyala2 and Faijal Ali3
School of Building and Civil Engineering, College of Engineering Science and Technology,
Fiji National University, Fiji Islands.
ABSTRACT
Soapstone samples of standard size prepared from same location, for unconfined compression stress (UCS)
test are placed in a water tub for one-day saturation and it is seen that these samples had experienced different
failure patterns. Samples 2, 4 and 5 have experienced hairline cracks and samples 3, 6, 7 and 8 have experienced
complete separation diametrically. Sample 1 is not subjected to saturation and it showed 4500 kPa of UCS, i.e.,
4.5 MPa. Whereas the samples failed due to soaking were rejoined with cement coating and air-dried for one day
and tested for UCS showed reduction in UCS. Though these samples were subjected to saturation for 24 hours, it
was noticed that hardly 1 to 2% increase in water content. The liquid limit of soapstone is 55% and its plastic
limit is negligible, i.e., non-plastic. The collapse potential of soapstone under 200kPa effective normal stress is
7.5% and 1% respectively for dry samples in disturbed and natural state. The free swell index is found to be 18%,
which indicates non-swelling nature of soapstone. The dry unit weight of soapstone is 12.5 kN/m3 . The UCS
variations of cracked samples coated with cement and air dried for one-day are presented and discussed.
Keywords: Soapstone, strength, saturation, collapse potential, dry unit weight.

INTRODUCTION
Soapstone encompasses various talc-rich schists
and that the major weathering problems are related
to loss of carved detail along foliation planes at
exposed places, and heavy crumbling when greatamounts of soluble salts are present in sheltered or
partly sheltered locations. There are major gaps inunderstanding of soapstone weathering. The
influence of petrography on weathering at places
exposed to direct precipitation, frost and biologicalagents are not properly understood. Moreover, therelative importance of frost, crystalizing salts andother agents, especially related to weathering atpartly exposed places, should be investigated more
carefully, as should the weathering mechanisms
when soapstone is affected by alkaline salts (PerStoremyr et al, 2000).

Soapstone is a natural metamorphic rock. Fiji is acountry located in the south pacific and has got
abundant soap stone in its land mass. In Fiji,soapstone is used as a backfilling material and also
as subbase in the civil engineering construction.
Soapstone is heat resistant, has high heat capacity
and is very easy to work even with wood carving
tools. The colour of soapstone varies from dull grayto bluish, greenish and brownish or reddish in
general. The qualities of soapstone as is the case forall other stone types depend on those of its basic
components, the minerals. Some minerals are hardand some are soft; some can endure extremely hightemperatures, whereas others remain stable only up
to 100oC.
Soapstone would include a considerable amountof talc, but the proportions and types of otherminerals may vary considerably. In addition to talc,
the main mineral components of the most typicaltypes of soapstone include mica, chlorite, amphibole,pyroxene, and serpentine minerals. Based on its
mineral content, soapstone can be categorized as a
type with mica content, one with chlorite content,
and so on. Variants including magnesite are quiterare as soapstone goes, but magnesite has,nevertheless, a significant role in increasing the heatstorage capacity of the soapstone. The soapstone ischaracterized by intercalating soft carbonate rich andrelatively hard, carbonate poor soapstone (Storemyr,
1996; Heldal and Storemyr, 1997).

Soapstone can be used as a building material
because this was the first rock on the surface to bequarried and used for construction such as churches,roads, retaining walls, masonry walls which werecompletely built of soapstone. Most of the ca.200
Medieval baptismal fonts in Norway were made ofsoapstone (Solhaug, 2001). The use of different
varieties of soapstone is almost universal in different
building tradition. Soapstone artisan workshops
produce a large quantity of powder (approximately
10-15% rock recovery), which is discardedcarelessly, often causing environmental problems(Rodrigues and Lima, 2012). The specific gravity ofsoapstone powder collected from the artisan

321

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

workshop in the Bandeiras region varied from 2.73
to 2.83 (Rodrigues, 2010).
Many rocks show a significant strength decrease
with increasing moisture content. In some cases,
such as montmorillonite clay shales, saturation
destroys the specimens completely. More typically,strength losses of 30-100% occur in many rocks as aresult of chemical deterioration of the cement or clay
binder (Broch [2]). Samples which have been left todry in a core shed for several months, can give amisleading impression of the rock strength.
Laboratory tests should be carried out at moisture
contents which are as close as possible to thosewhich occur in the field (Broch, 1974). Rock Quality
Designation (RQD) based empirical relations aremost commonly employed in determination of rockdeformation modulus and unconfined compressive
strength (Aydan & Dalgic, 1998; Barton, 2002;
Zhang, 2016). The uniaxial compressive strength ofrock mass varies by a factor of about 5, depending
upon the direction of loading. Evidence of the
behaviour of this graphitic phyllite in the fieldsuggests that the rock mass properties are dependent
upon the strength parallel to schistosity rather thanthat normal to it (Salcedo, 1983). Medhurst and
Brown (1996) have reported the results of laboratory
triaxial tests on samples of 61, 101, 146 and 300 mm
diameter samples of a highly cleated mid-brightness
coal from the Moura mine in Australia and showedthat there is a significant decrease in strength withincreasing sample size.

testing them for UCS (Fig.2).
The index properties of soapstone which were
tested in the laboratory are presented in Table.1. The
collapse potential of undisturbed and disturbed
samples is presented in Fig.3. The samples unit
weight maintained during test are 12.5 kN/m3.
Table 1 Properties of Soapstone
Property
LL
PL
FSI
CP1
CP2
γd

Value
55%
NP
18%
7.5 %
1%
12.5 kN/m3

Note: LL = Liquid Limit, PL = Plastic Limit, FSI =Free swell Index, CP1 = Collapse Potential disturbed
sample, CP2 = Collapse Potential undisturbed
sample, γd = dry unit weight.

S3

S4

S6

S5

S7

S8

S2

EXPERIMENTAL INVESTIGATION
Tests Conducted
To understand the behavior of soapstone, a basic
laboratory study is carried out aiming geotechnicalcharacteristics such as plasticity characteristics, freeswell index, unconfined compression stress (UCS)
and collapse potential. A block of soapstone sample
was brought to the laboratory from Derrick campusof Fiji National University, Suva, Fiji. The
soapstone collected was dry and whitish in colour.
The dry unit weight of soapstone is 12.5 kN/m3.
From this block of soapstone, required number ofsamples of standard size 76 mm long and 38 mm
diameter are dressed neatly for UCS test (Figs.1 and
2).

Fig. 1

All the tests are carried out as per the standard
test procedures of testing of soils (AS 1289.0 - 2014).
Soapstone samples of standard dimension wereprepared and tested them for unconfinedcompression strength with one-day saturation andwithout saturation. Samples had gone throughdifferent crack pattern as shown in Fig.1 due to oneday saturation. These cracks were joined withcement paste and air dried for one –day before

Samples cracked under one-day saturation.

S3

Fig. 2
322

S4

S6

S8

S7

S5

Cracked samples joined with cement paste.

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

soapstone can perform better in terms of bearing
stress even after failure, if it had treated or glued
with cement appropriately.
5000

1000

900

Compresssion Stress, kPa

Dial guage reading (div)

1100

800

700

4000

3000

2000

1000
600
10
100
1000
UD
Dist Effective normal stress, kPa
Fig. 3 Collapse Potential for Undisturbed anddisturbed at 200 kPa.

0
0

1
1.5
2
% Strain
Sample 1 UCS test zero day’s saturation.

Fig. 4

0.5

DISCUSSION OF RESULTS
1000

The UCS test results of cement coated soapstone
samples are presented in Figs. 4 to 11 for various
failed samples due to one-day saturation (Fig.1).
Figure 4 presents the compression stress-strain plot
for the soapstone dry sample tested without
subjecting to the one-day saturation. The sample hasreached a peak compression stress at 1% strain andthe corresponding UCS noticed is 4500 kPa. From
this plot it is understood that the soapstone is failingat lower strain and it clearly shows brittle failure.

Compression Stress, kPa

900

Figure 5 presents the stress – strain plot for
sample 2 (Fig.1). Sample 2 is not affected due to 1day saturation and it is almost same as theunsaturated sample as per the size is concerned. But,
due to one-day saturation of sample, it is noticed that
there is an increase in water content by 2%. As the
sample 2 is intact, the specimen is tested without
cement coating and corresponding UCS noticed is
950 kPa. This reduction in UCS as compared to thesample tested without saturation is attributed to theweakening of internal structure because of saturation.

800
700
600

500
400
300
200
100

0
0
Fig. 512
3
4% strain
Sample 2 UCS test one day’s saturation
with cement paste.

Figure 7 presents the compression stressvariation with strain for sample 4 (Figs.1 and 2).
Sample 4 shows the very minute level hairline
cracks diametrically along the periphery of thesample due to 1-day saturation. These minute
hairline cracks are glued with little cement andtested for UCS after one-day drying. The UCS of thesample noticed is about 445 kPa. The sample 2 andsample 4 are not experienced any major cracks, but

Figure 6 presents the compression stressvariation with strain for sample 3 (Figs.1 and 2).
Due to one-day saturation the sample had horizontal
cut at the middle. This sample is joined by gluingwith cement and was kept for one-day air drying
before testing for unconfined compression stress.
From figure 6, the UCS of cement glued sample isnoticed as 1245 kPa corresponding to a strain of
1.5%. From this result, it is noticed that the323

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

there is an influence of saturation towards reduced
UCS.

as 1175 kPa. This higher UCS of the sample isattributed to presence of more glued cement aroundthe failure area of the sample. The sample is failed atabout 2% strain.

1400

1000

1000
Compression Stress, kPa

Compression Stress, kPa

1200

800
600
400
200
0

600

400

200

0
Fig. 6

800

1

2

3

% strain
Sample 3 UCS test one day’s saturation
with cement paste.

00Fig. 8500

1

2
3% strain
Sample 5 UCS test one day’s saturation
with cement paste.

1400
1200
Compression Stress, kPa

Compression Stess, kPa

400

300

200

100

1000

600
400
200

0
0

Fig. 7800

12
3% Strain
Sample 4 UCS test one day’s saturation
with cement paste.

00Fig. 9Figure 8 shows the UCS test plot for sample 5(Fig.1) which has hairline crack diametrically at its
middle portion. This hairline crack was glued withcement and kept for one-day air drying before
testing for UCS (Fig.2). The UCS of sample 5 isnoticed as almost 800 kPa corresponding to a failure
strain of 1.7%.

1

2
3
4
% strain
Sample 6 UCS test one day’s saturation
with cement paste.

Similarly, for sample 7 and sample 8 the stressstrain plots are presented in Figs. 10 and 11. The
sample 7 experienced the failure almost very close
to the edge and sample 8 experienced the failure
diametrically and almost at the middle of the sample
height. The UCS of cement glued sample 7 (Fig.10)
is noticed as 785 kPa and whereas for cement glued
sample 8 (Fig.11), the UCS noticed is 1280 kPa.

Sample 6 (Figs .1 and 2) UCS plot is presented
in Fig.9. The failure pattern due to saturation noticed
is almost similar for the samples 3 and 6. The UCS
of sample 6 when cement glued and tested is noticed

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

well utilized as a building material.
1000

Compression Stress, kPa

800

600

400

200

0
0

1

2
3
4
5
% strain
Fig. 10 Sample 7 UCS test one day’s saturation
with cement paste.

Fig.12 Typical failure of cement joined sample
CONCLUSION

1600
Interesting points are brought out from the above
discussion. The UCS of samples 2, 4 and 5 is 950
kPa, 445 kPa and 800 kPa respectively. The low
value of UCS in case of sample 4 is attributed tomultiple hairline cracks diametrically close to top
and bottom edges and also at the middle. The UCS
of samples 2 and 5 is almost in the same range as it
is evidenced that similar kind of crack pattern. The
samples 3, 6, 7 and 8, though they werediametrically separated, but no hairline cracks are
noticed. The UCS values of samples 3, 6, 7 and 8 are
1245 kPa, 1175 kPa, 785 kPa and 1280 kPa
respectively. Though the failure pattern is same forthe samples 3, 6, 7 and 8, it is noticed that UCS of
sample 7 is low compared to samples 3, 6 and 8. It is
attributed that the failure is occurred diametricallyclose to the edge in sample 7, whereas for the
samples 3, 6 and 8, the failure is occurred at middleof the sample height.

Compression Stress, kPa

1400
1200
1000
800
600
400
200
0
0

1

2

3

% strainAlso it is interesting to note that the soapstone aslong as it is dry, possesses reasonable strength, andwhen subjected to water saturation, its internal
structure gets disturbed causing failure patterns suchas cracks and separation. Cement coating caneffectively join the failed soapstone to make thesystem intact and provide required minimum
strength for serviceability point of view of civilengineering constructions on the soapstone.

Fig. 11 Sample 8 UCS test one day’s saturation
with cement paste.
A typical failure pattern of cement pasted
soapstone sample is presented in Fig.12. From thisfigure, it can be noticed that the most of the failure isconcentrated at the bottom of the sample, where
cement paste was not applied. It means that thesoapstone samples when treated with cement and air
dried can improve the strength and controls thefailure in a sustainable way. Soapstone can be very

Also the collapse potential of undisturbed anddisturbed soapstone samples showed different values.

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

The collapse potential of undisturbed sample was
7.5% and whereas for disturbed sample it is 1%.

[7] Medhurst T. P. and Brown E. T. (1996). Large
scale laboratory testing of coal. In Proc. 7th
ANZ Conf. Geomech. (Edited by Jaksa M. B.,
Kaggwa W. S. and Cameron D. A.), pp. 203208. IE Australia, Canberra.

FUTURE SCOPE OF THE WORK
From the limited work carried out in thelaboratory, it is realized that there is a much scope tofurther carry out research on soapstone. In Fiji, there
are three different varieties of soapstone available
and these are stiff, very stiff to hard in nature. As
most of the constructions are taking place on
soapstone, it is required to understand effect ofsaturation on failure patterns, influence of cement on
strength of joined specimens, physico-chemical
behavior of soapstone and soapstone sustainability
behavior with respect to various loading andenvironmental considerations.

[8] Per Storemyr, Eberhard Wendler & Konrad
Zehnder (2000). Weathering and Conservationof Soapstone and Greenschist used at Nidaros
Cathedral Brief Summary of Investigations
1999-2000, Report Raphael I Nidaros Cathedral
Restoration 98/034198 Project 68.
[9] Rodrigues, M.L.M. (2010). Caracterização
tecnológica de resíduos de pedra-sabão deoficinas de artesanato em pedra-sabão da região
de Ouro Preto. Ouro Preto: Programa de PósGraduação
em
Engenharia
Mineral,
Universidade Federal de Ouro Preto (Master
dissertation). p. 120.

REFERENCES[1] AS 1289.0 - 2014. Methods of Testing Soils forEngineering Purposes, Australian Standard.

[10] Rodrigues, M.L.M & Lima, R.M.F. (2012).
Cleaner production of soapstone in the Ouro
Preto region of Brazil: a case study, Journal of
Cleaner Production, 32, 149-156.

[2] Aydan, O and Dalgic, S (1998). Prediction of
deformation behavior of 3-lanes Bolu tunnels
through squeezing rocks of North Anatolian
fault zone (NAFZ), Proceedings of Regional
Symposium on Sedimentary Rock Engineering,Taipei, China (1998), pp. 228–233.

[11] Salcedo D. A. Macizos Rocosos (1983).
Caracterizaci6n, Resistencia al Corte y
Mecanismos de Rotura. Proc. 25 Aniversario
Conferencia Soc. Venezolana de Mechnica delSuelo e lngenierla de Fundaciones, Caracas.
143-172.

[3] Barton, N (2002). Some new Q-value
correlations to assist in site characterization andtunnel design, International Journal of RockMechanics and Mining Sciences, 39 (2) (2002),
pp. 185–216[12] Solhaug, M. (2001). Middelalderens dopefonter
I Norge, Acta humaniora 89, Ph.D Thesis,
University of Oslo, Unipub, 1999.

[4] Broch E (1974). The influence of water on somerock properties. Proc. 3rd Congress, 1SRM,
Denver 74(2), Part A, 33-38.

[13] Storemyr, P. (1996). A study on the weatheringof Norwegian greenchist, In J.Riederer (ed.), 8 thInternational congress on Deterioration andconservation of Stone: Proceedings, I: 185-200,
Berlin.

[5] Heldal, T and Storemyr, P. (1997). Geologisk
undersokelse og arkeologisk registering av demiddelalderske steinbruddene ved oye, Klungenog Huseby I Sor-Trondelag. NorwegianGeological Survey, Report No.97: 149.

[14] Zhang, L (2016). Determination andapplications of rock quality designation (RQD),
Journal of Rock Mechanics and GeotechnicalEngineering, Volume 8, Issue 3, June 2016,
Pages 389–397.

[6] Kavvadas M., Hewison L. R., Lastaratos P. G.,
Seferoglou C. and Michalis I (1996).
Experience in the construction of the Athens
Metro. Proc. lnt. Symp. Geotechnical Aspects ofUnderground Construction in Soft Ground(Edited by Mair R. J. and Taylor R. N.), 277282. City University, London.

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Third International Conference on Science, Engineering & Environment (SEE),
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MEASUREMENT ACCURACY OF ORIENTATION CODE MATCHINGFOR SLOPE DEFORMATION MONITORING
1

Takeshi YAMAMOTO1, Keigo KOIZUMI2, Kazuhiro ODA3, and Yoshio FUKUDA4
Graduate School of Engineering, Osaka University, Japan; 2Earth Watch Institute, Inc., Japan

ABSTRACT
Orientation code matching (OCM) is an image sensing technique and has already been used for the remote andaccurate measurement of rainfall-induced slope deformation in the laboratory test. However, the influence ofrainfall and differences in target patterns on the measurement accuracy have not yet been verified. In order toverify the influence, the displacement of target panels attached to a height gauge was measured. Comparing themeasurement results of two target panels with different patterns confirmed that the displacement could bemeasured accurately by using a target with the same texture size as the camera pixel size. In addition, comparing
the measurement results under rainfall and non-rainfall conditions confirmed that the displacement could be
detected with an accuracy of 0.1 mm, although rainfall did influence the measurement accuracy. A model slope
experiment was carried out to confirm that accurate measurements could be taken under rainfall conditions.
Measurements could be taken without target panels when the slope surface pattern was the same size as thecamera pixel size.
Keywords: Slope Deformation, Image Sensing, Measurement Accuracy, Slope Failure
INTRODUCTION

INFLUENCE OF THE TARGET PATTERN ON
THE MEASUREMENT ACCURACY

Rainfall-induced slope failure can damage
people and the economy. Therefore, an accurate
remote slope monitoring system is required. A slope
deformation monitoring system that utilizes
orientation code matching (OCM) was developed[1]–[4]. Representations for an object image areconstructed from corresponding gray images suchthat each pixel represents an orientation code that is
obtained by quantizing the orientation angle at thecorresponding pixel position in the gray image. The
orientation code represents the steepest ascentorientation evaluated from the pixel neighborhoods
and is measured with respect to the horizontal axis.
The orientation codes are a function of the texture
and shape of the object. Hence, they are essentiallyinvariant to object translation and the effects ofshading, background, and illumination variations [5].
In a previous study, it was confirmed that apositive correlation between the camera pixel size
and measurement error under non-rainfall conditions
using only one target pattern. However, in order tomonitor the slope deformation, the system needs tobe able to measure displacement under rainfall
conditions. In addition, differences in target patterns
may affect the measurement accuracy.
In this study, in order to verify the influence ofrainfall and differences in target patterns, thedisplacement of two target panels with different
patterns were measured under rainfall and nonrainfall conditions. A model slope experiment was
carried out in order to confirm that the slope surface
displacement can be measured accurately underrainfall conditions.

Target Patterns
When using OCM to measure the displacement,
the influence of noise from low-contrast pixels needs
to be reduced. Therefore, this method ignores lowcontrast pixels.
Figure 1 shows the target pattern (pattern A)
used in the previous study [6]. In this pattern, pixels
except for those around the borders of the black andwhite areas were ignored. Because the number ofignored pixels was high, the influence of noise on
the measurement accuracy should increase. If pixels
can be effectively used over the whole target, themeasurement would be more accurate. Therefore, inorder to verify the influence of differences in target
patterns on the measurement accuracy, thedisplacements of two target patterns were measured
and compared. Figure 1 also shows the new target
pattern (pattern B).

Pattern A

Pattern B

Fig. 1 Target patterns.

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Experimental Outline

Experimental Results

In the laboratory, two target panels with patterns
A and B (Fig. 1) attached to a height gauge(Mitutoyo HD30AX) were set facing the camera(Point Grey, Flea3 1.3M) lens (Edmund Optics, 9–90MM), as shown in Figs. 2 and 3. The instrumental
error of the height gauge was ±0.02 mm. The camera
captured images with a 1280 × 1024 pixel resolution
at an 8-bit grayscale and rate of 50 frames per
second. The lens was adjusted so that the pixel could
be the specified value. The value varied from 0.20 to
1.00 mm/pixel in increments of 0.10 mm/pixel.
After the camera started, target panels were moved
0.10 mm upward in the vertical direction by thehandle drive device of height gauge. After the
movement, OCM was used to measure for 10 s. The
above procedure was carried out for every pixel size.

Generally, the standard deviation 𝝈 or 3𝜎 is used
as an evaluation index of the dispersion when themeasurement results have a normal distribution. In
this experiment, the Shapiro–Wilk test [7] wasperformed to determine if the measurement results
followed a normal distribution. The p-value was
0.05 or more in every case, and the null hypothesis
was rejected. In other words, the, measurement
results followed a normal distribution with asignificance level of 5%. Therefore, 3𝜎 was used as
the evaluation index. The accuracy 𝜺𝝁 was definedas equation (1) and measurement error 𝜺 was definedas equations (2):Height gauge and target panels0𝜺𝝁 = 𝝁 − 𝟎. 𝟏𝟎
𝜺 = |𝜺𝛍 | + 𝟑𝛔

(1)
(2)

where 𝝁 is the mean of the measurement results.
Table 1 presents the measurement results forpatterns A and B at every pixel size. For pattern A,
3σ increased with the pixel size. In addition, εμ was
0.04 mm when the pixel size was 0.80 mm/pixel and0.08 mm when it was 1.00 mm/pixel. This showedthat the displacement could not be accurately
measured. For pattern B, εμ was 0.06 mm or lesswhen the pixel size was from 0.02 to 1.00 mm/pixel
and 0.03 mm or less when it was greater than 0.06
mm/pixel. However, 3σ increased suddenly when
the pixel size was 0.90 mm/pixel or greater. Figure 4
shows the relation between the pixel sizes and ε. ε ofpattern B was less than that of pattern A except
when the pixel size was 0.90 mm/pixel. This
demonstrates that the measurement results weremore accurate with pattern B than with pattern A.

Camera5

15

Fig. 2 Schematic diagram of the experiment.

Table 1 Measurement results of patterns A and B
Pattern A
Pixel size
(mm/pixel)

Fig. 3 Height gauge and target panels.
328

εμ
(mm)

3σ
(mm)

Pattern B
ε
(mm)

εμ
(mm)

3σ
(mm)

ε
(mm)

0.20

0.00

0.01

0.01

0.00

0.02

0.00

0.30

-0.01

0.01

0.02

-0.01

0.01

0.02

0.40

-0.02

0.01

0.03

-0.01

0.01

0.02

0.50

0.01

0.03

0.04

0.00

0.04

0.01

0.60

0.00

0.03

0.04

0.00

0.02

0.02

0.70

0.00

0.09

0.09

-0.02

0.04

0.06

0.80

-0.04

0.05

0.08

0.02

0.03

0.05

0.90

0.00

0.03

0.03

-0.02

0.12

0.14

1.00

-0.08

0.09

0.17

0.03

0.10

0.12

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

The lens was adjusted so that the pixel size could be
the specified value. The value was increased from
0.20 to 0.50 mm/pixel in increments of 0.10
mm/pixel. After water was sprayed (intensity of 180mm/h) from above the target to simulate
measurement under rainfall conditions, the camera
was started. The target panels were moved 0.10 mm
upward in the vertical direction with the handle
drive device of height gauge. After they were moved,
OCM was used to measure for 10 s. The above
procedure was carried out for every pixel size.

0.20
Pattern A
Pattern B

ε (mm)

0.15

0.10

0.05

0.00
0.00

0.50

1.00

Experimental Results

Pixel size (mm/pixel)

Table 2 presents the measurement results forpattern B with every pixel size under non-rainfall
and rainfall conditions. Under the non-rainfall
condition, ε was 0.02 mm or less when the pixel size
was from 0.20 to 0.50 mm/pixel. On the other hand,under the rainfall condition, ε was 0.03 mm when
the pixel size was from 0.20 to 0.40 mm/pixel, and ε
was 0.08 mm when the pixel size was 0.50 mm/pixel.
Figure 6 shows the relation between the pixel sizeand ε. As a result, ε was smaller under the nonrainfall condition than under the rainfall condition.
These results show that rainfall reduced themeasurement accuracy. This may be because there
were water drops between the target and camera,
which changed the target pattern from the initial one.
However, when the pixel size was 0.40 mm/pixel or
less, ε was less than 0.05 mm. This means that ameasurement accuracy with the order of 0.1 mm wasrealized. For the model slope experiment discussed
in the next section, the pixel size was adjusted to0.30 mm/pixel.

Fig. 4 Relationship between the pixel size and ε.
Discussion
The measurement results were more accurate forpattern B than for pattern A except when the pixel
size was 0.90 mm/pixel. Pattern B may be morerobust against noise than pattern A because it has
more effective pixels. In other words, thedisplacement could be measured accurately by using
a target with the same texture size as the camera
pixel size.
For the pattern B results, 3σ increased suddenly
when the pixel size was 0.90 mm/pixel or greater.
Figure 5 shows camera images of the target patterns
when the pixel sizes were 0.20 and 0.90 mm/pixel.
When the pixel size was large, the image of thetarget pattern was unclear, and the contrast was low.
Thus, pattern B was not robust when the pixel size
was greater than the texture size of the target.

Table 2 Measurement results under rainfall
conditions
Non-rainfall
Pixel size
(mm/pixel)

0.20 mm/pixel

0.90 mm/pixel

Fig. 5 Images of target panels.
INFLUENCE OF RAINFALL ON THE
MEASUREMENT ACCURACY
Experimental Outline
In the laboratory, a target panel with pattern B(Fig. 1) was attached to the height gauge (Mitutoyo
HD30AX) at 35° with the horizontal axis. The
height gauge was set facing the camera (Point Grey,
Flea3 1.3M) and lens (Edmund Optics, 9–90MM),
as shown in Figs. 2 and 3. The height gauge’s
instrumental error was ±0.02 mm. The camera
captured images with a 1280 × 1024 pixel resolution,
8-bit grayscale, and rate of 50 frames per second.
329

εμ
(mm)

3σ
(mm)

Rainfall
ε
(mm)

εμ
(mm)

3σ
(mm)

ε
(mm)

0.20

0.00

0.00

0.00

0.11

0.02

0.03

0.30

-0.01

0.01

0.02

0.08

0.01

0.03

0.40

-0.01

0.01

0.02

0.08

0.01

0.03

0.50

0.00

0.01

0.01

0.14

0.04

0.08

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

Top view

0.10

150

Non-rainfall

ε (mm)

Rainfall

A

D

B

E

F
150

C

G

0.05
260

87

87

100
Surface layer

Side view
Camera

0.00

440

0.00

0.10

0.20

0.30

0.40

0.50
Impermeable layer
30°

Pixel size (mm/pixel)

Foundation layer

Fig. 6 Relationship between the pixel size and εunder rainfall conditions.

830
Measurement point

Target panel

MODEL SLOPE EXPERIMENT

Unit：mmFig. 7 Schematic diagram of the model slope.

Experimental Outline

Table 3 Soil sample properties

Figure 7 shows a schematic of the model slope
used in this experiment. It was 30 cm wide, 83 cm
long, and 54 cm high. The surface layer thickness
was 10 cm, and the gradient of the slope was 35°.
The surface layer was made of Masa, as given in
Table 3, The slope was divided into five layers in thevertical direction, and the soil was compressed for avoid ratio of 0.60.
A clay layer was arranged under the surface layer
and acted as an impermeable layer. Measurement
points (A–G) were at the middle of the slope surface,
as shown in Fig. 7. Target panels were at A, C, F
and G, but not at B, D, and E. The sand of the slope
surface was also used as the target. The camera
captured images with a resolution of 1280 × 1024
pixels, 8-bit grayscale, and rate of 10 frames per
second. The lens was adjusted so that the pixel size
could be 0.30 mm/pixel. The measurement started
with rainfall (intensity of 180 mm/h), and stopped
when none of the targets could be recognized in thecamera image.

Masa

Soil samples
Density of soil particles (ρ s )g/cm3

Water content (ω )%5.0

Dry density (ρ d)

g/cm3

1.629

Maximum dry density (ρ dmax )

g/cm3

1.766

Void raito (ρ s )-0.6

Permeability (ρ s )cm/s

1.21×10-2

2.607

Failure(A～E)

45

Disp (mm)Failure(F)
Failure(G)

A (Target panel)
B (Sand)
C (Target Panel)
D (Sand)
E (Sand)
F (Target panel)
G (Target panel)

35
25
15
5
-5

0

100

200

300

400
Time (s)

500

600

700

800

Fig. 8 Displacement time histories.

Experimental Results

3

Figure 8 shows the displacement time histories,
and Fig. 9 shows partially expanded histories
indicating where each measurement point began todisplace. At 580 s after the experiment began, thedisplacement gradually increased at A–E. After 600
s, the displacement rapidly increased, and the slope
finally failed. At F and G, the displacement
gradually increased after 580 s and rapidly increased
after 640 s before the slope finally failed. Figure 10
shows the slope after 640 s. Cracks were confirmed
below F and G. Therefore, the displacement
behaviors at A–E and at F and G were different.

A (Target panel)
B (Sand)
C (Taget panel)
D (Sand)
E (Sand)
F (Target panel)
G (Target panel)

Disp (mm)

2

1

0

-1
560

580

600

620

640

660

Time (s)Fig. 9 Displacement time histories (partiallyexpanded).

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

F(3) In the model slope experiment, the surface
displacement was measured as accurately without
target panels as with them.

G

Crack
D

E

A

B

ACKNOWLEDGMENTS

This research was partially supported by JSPSLIPI Bilateral Research Projects and JSPS
KAKENHI Grant Number 16H03154.

C

REFERENCES[1] F. Ullah and S. Kaneko, Using orientation
codes for rotation-invariant template matching,
Pattern Recognition, Vol. 37, No. 2, pp. 201–
209, 2004.
[2] F. Ullah, S. Kaneko, and S. Igarashi,
Orientation code matching for robust object
search, IEICE Trans. Inf. Syst., Vol. E84-D,
No. 8, pp. 999–1006, 2001.
[3] Y. Li・ H. Takauji・S. Kaneko ・T. Tanaka
and I. Ohmura, Robust focusing usingorientation code matching, Electronic Letterson Computer Vision and Image Analysis, Vol.
7, No. 3, pp. 101–114, 2008.
[4] Y. Narita, Remote and robust displacement
measurement based on picture matching, M.S.
thesis, Hokkaido University, Japan, 2010.
[5] S. Kaneko・I. Murase and S. Igarashi, Robust
image registration by increment sign
correlation, Pattern Recognition, Vol. 35, No.
10, pp. 2223–2234, 2002.
[6] Y. Fukuda, K. Koizumi, T. Yamamoto, S.
Kobashi, K. Oda, K. Sakuradani and M. Feng,
Experimental study on slope deformation
measurement utilizing a image sensing
technology, Kansai Geo-Symposium2016,
pp.243-248, 2016.
[7] S. S. Shapiro and M. B. Wilk, An Analysis of
Variance Test for Normality (Complete
Samples), Biometrika, Vol. 52, No. 3/4,
pp.591-611, 1965

Fig. 10 Slope (after 640 s).
DISCUSSION
At every measurement point, the displacement
behavior could be measured from a small
displacement to slope failure. There were no target
panels at B, D and E, and the sand of the slope
surface was used as the target directly. However, thedisplacement behavior at B was like that at A and C.
If a mass of soil under the crack is displaced in one
body, it is reasonable to assume that thedisplacement behavior at D and E was like that at A
and C.
The displacement could be measured as
accurately without target panels as with them. Thisis because the sand showed a high contrast, and its
pattern was as rough as that of the target panel asshown in Fig.11. However, if sand is used as thetarget, the pattern could change from the initial one
with slope deformation, which may reduce themeasurement accuracy. Therefore, measurements
without target panels must be a supplementary
method.

Fig. 11 Images of sand of surface (at B).
CONCLUSIONSA series of experiments was carried out to verify
influences on the accuracy of measurements with
OCM. The major findings and conclusions arepresented below:(1) The displacement can be measured moreaccurately by using a target with the same texture
size as the camera pixel size.
(2) The displacement can be measured with anaccuracy of the order of 0.1 mm even under therainfall condition.

331

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

NANOSTRUCTURAL CHARACTERIZATION OF GLUTATHIONE-STRANSFERASE IMMOBILIZING CHITOSAN MODIFIED SCREEN
PRINTED CARBON ELECTRODE BY ATOMIC FORCEMICROSCOPY
Buddhapala Wongkaew1, Porntip Wongkaew2, Panupong Thanutong3 and ChitsanuphongThanutong4
1
Metropolitan Waterworks Authority, Bangkok 10210, Thailand;
2
Department of Plant Science and Agricultural resources, Faculty of Agriculture,
KhonKaen University, KhonKaen 40002, Thailand;
3
Office of The Secretary Permanent, Ministry of Digital Economy and Society, Bangkok 10210, Thailand.
ABSTRACT
Immobilization of a bio-recognition element to the surface of a functional working electrode is fundamental
for effective biosensor development. In this study, the enzyme glutathione-s-transferase (GST) that constitutes aprotein superfamily involvingvarious distinct chemical transformations was introduces as a versatile tool for thesensing of environmental toxicants. Functional electrode surface was made by self-assembly of a great
bioscaffold chitosan onto screen printed carbon electrode surface concerning to its excellent covalent bonding
binding of biomolecules. To enhance the enzyme proximity, glutaraldehyde was employed as an assistingbifunctional cross-linker. The self assembled chitosan layer and the GST immobilizing nanostructural features
were explored by morphological imaging andseveral quantitative analyses such assurface grain size anddistribution, power spectrum density (PSD) algorithm, fractal dimension character and other important surface
roughness parametersvia atomic force microscopy (AFM). Vertical aggregation of the successive layer was
clearly verified in all quantitative approaches. Exceedingly, a better understanding in the direction of aggregation
along with the growth mechanism was obtained by PSD analysis and the fractal dimension values gained around2.27 for modified chitosan surface and 2.02 for GST immobilized chitosan modified screen printed carbon
basement could thus implied for the diffusion limited model in this growth mechanism.
Keywords: Immobilization · Glutathione-s-transferase · Chitosan · Biosensor development · Atomic ForceMicroscopy

achieved at mild conditions of temperature, pressure
and pH which makes substantial process energy
savings and reduced manufacturing costs. Moreover
they are natural substance being mostly
biodegradable protein and peptides that can be easily
withdrawn from contaminated environment without
disposal problems.
Immobilization of the enzymes onto suitable
platforms is crucial for maintaining their catalytic
activity and long term stability, and also forbiosensor development. In pesticide determination
studies, the main in use enzymes
areacetylcholinesterase,butyrilcholinesterase,cholinesterase, acid phosphatase, ascorbateoxidase,acetolactate
synthase,urease,aldehydedehydrogenase and glutathione-s-transferase [4]. On
the other hand, it is necessary to choose a suitable
platform that provides good support for demand inboth catalytic and non catalytic activities including
productivity, rapidity, selectivity, separation, control,and down streaming process. A natural material
chitosan is one among nanomatrix choices in ourattention because of its biocompatibility altogether
with its prompt availability and inexpensive
productivity which allows a wide array for
application on environmental engineering [5,6]. Our

INTRODUCTION
Recently, researches based on electrochemical
biosensor have been attractively considered as
potential successors to the development of new
methodologies for economical and real time
monitoring of environmental pollutants and also forprevention of toxic materials in the environment [1]The main functional activity is belonged to theoxidising and reducing ability of the selective biorecognition elements that make a high throughput
screening of analytical target possible in a reliable
manner within a fraction of seconds. Therefore a
critical step for development of biosensor is theselection of a proper bio-recognition element and theimmobilization of this element to the surface of aworking platform. Although there have been a wide
range of bio-molecular recognition elementssuggested, enzymes are historically the firstmolecular recognition elements included informer
biosensors and continue to be the basis to date for
newly biosensor development and application [2, 3].
Enzymes provide several advantages due to their
excellent selectivity for the targeted substrate andhigh catalytic activity. In addition, a relatively highreaction rate with enzyme operation is commonly332

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017previous study on the modification of a screen
printed carbon electrode by surface incorporation
with chitosan has demonstrated one among potent
application for obtaining an effective and affordable
electrochemical implement [1]. With reference tosuch excellent advantages, it was further used toachieve another successfulimmobilization of enzyme
in this present work to gain an effective specificbiosensor.
According to the recent advance innanotechnological science, many more sophisticate
techniques has been developed for the analysis ofinterfacial events at micro and nanoscale. Among
various instrumentations that enable imaging, atomic
force microscopy (AFM) is the only empower
technique for material surface visualizing at subnanometer accuracy. In comparison to standard
scanning (SEM) and transmission Electron (TEM)
microscopy, the AFM not only offers the capacity tovisualize nanometric features in two and three
dimensions but
also the physicochemical
characteristics including its spatial distribution
mapping of surfaces and the permittivity to perform
an observation in several environments for example
in air, vacuum and liquid environments with little oreven no sample preparation requirement. The
correlation between the physicochemical propertiesof biomaterials and the resulting biological response
can also be resolved significantly. Inferably, theAFM allows superlative tool for imaging,quantifying, manipulating and other analyses ofinspection materials at nanometer level without
perturbation of the native characteristics. The factthat nanotopographical surfaces influence charge
density and electric field strength, quantitative
characterization of surface morphology is thus very
important. To date, AFM has been employed
progressively
for
exploringthesurfacemorphological features especially in the researcharea of surface engineering [1, 7].
In the present study, an enzyme glutathione-stransferase (GST) was chosen as a model for
immobilization onto chitosan modified screen
printed carbon electrode (SPCE) prepared according
to our previous report [2]. Accomplishment of thisimmobilization event was then deeply evaluatedthrough high resolution AFM imaging and importantinterfacial parameters analyses.

Ajax Finechem Pty, Ltd., Australia. Solutions andreagents were prepared using high purity deionizedwater of 18.2 MΩ from Milli-Q RG system(Millipore Corporation, MA, USA). Screen printed
carbon electrode DRP-150 was provided by
DropSens, Parque Tecnológico de Asturias,
S.L.Llanera (Asturias) Spain.
Preparation
platformofchitosanmodified

electrode

The chitosan modified electrode platform wasmade by self-assembling onto SPCE according toour previous report [2].
Immobilization ofGSTenzyme
To form a better support condition for enzyme
immobilization, the chitosan modified working
surface was to be activated by an incorporation of
glutaraldehyde (GA) covalent attachment. This
working surface spot was treated with a 5 μl drop of
2.5% glutaraldehyde for 30 minutes at room
temperature and rinsed with deionized water
afterward to remove an excess of its particle.
Preparation of 3 U GST enzyme solution was donein 0.05 M PBE that formulated from 0.05 M
Phosphate buffer saline at pH 6.5 containing 0.05 M
EDTA and 0.1 M KCl [8]. Immobilization of GST
was then performed by adding a 5 μl drop of thisenzyme solution onto the GA-activated chitosan
modified working surface and incubated at room
temperature for 2 hours. It was then washed down
inordinate molecules with deionized water.
AFM imaging and analysis
Nanostructural imaging of surface characteristics
was carried out byan atomic force microscope model
XE-120 (Park Systems Corp., Suwon, Korea)
through a true non contact mode. Observation was
done in non contact mode under ambient conditions
with standard PPP-NCHR silicon cantileverconsisting 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 1×1μm area at 0.5 Hz
scanrate was inspected with XEP software for dataacquisition and XEI software for image processing
and quantitative analysis of the surface topography.
Important parameters such as an average roughness
Ra (nm), root mean square or standard deviation of
the height value Rq (nm), height different or peakto-valley (Rpv), ten point height (Rz), mean spacing
average (Rsm), skewness (Rsk), kurtosis (Rku),
power spectrum density (PSD) algorithm, fractal
dimension and grain aggregation were thensuccessively identified.

MATERIALS AND METHODS
Materials
Chitosan (85% degree of deacetylation) with amolecular weight of 0.28 kDa was obtained from
Bioline Lab, Co., Thailand. Glutathione-Stransferase from equine liver was purchased from
Sigma-Aldrich Co. LLC, USA. Other chemicals forexperimental reagent preparation were bought from333

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

RESULTS AND DISCUSSION

Surface grain profile

AFM imaging of surface morphology

As the AFM nanostructural images have shown awavy surface texture containing various ripples
against a background. These ripples can be detected
as grains by watershed algorithm with a softwarebased image processing. In this observation, theXEI
software of Park System was used in quantitative
analysis of the surface grain profile to provide
comparative information related to the success of
SPCE modification with chitosan and GST
immobilization onto chitosan modified SPCE. Table
1 presents the measured surface grain information in
average of grain area, volume, perimeter and peakto-valley via level 2.5 filter of watershed algorithm
by the XEI software. Differences among the surface
natures could be demonstrated in this grain size
quantification.Much larger in area, length andperimeter but smaller in volume and peak-to-valley
value of the grains from SPCE-Chi and SPCE-ChiGSTthan the original SPCEsurface were obtained inthis determination.With reference to thesevalues, thesurface look after chitosan modification and GST
immobilization became rather slightly wrinkle taper
smear on top of screen printed carbon basement inconsent to our previous report [2].

A creation of GST enzyme immobilization on
working chitosan platform was sighted up by AFM
imaging. Remarkable changing in surface
morphology could be seen following themodification of screen printed carbon spot area of
the SPCE with chitosan and the immobilization of
GST enzyme onto chitosan modified platform withthe aid of GA bifunctional covalent as shown in
Fig.1. Morphological feature at nanometer scale ofthe scanned surface within a projection area of 1 × 1
μm has been revealed in 3D illustration for thescreen printed carbon basement of SPCE in Fig. 1A,
the chitosan modified SPCE (SPCE-Chi) in Fig.1B
and the GST immobilized chitosan modified SPCE(SPCE-Chi-GST) in Fig. 1C, respectively. The
different feature appearance from each other among
these obtaining images, thus, is likely an indicationof a progress in the surface modification.

Table 1 Surface grain structure estimation of bare
SPCE, SPCE-Chi and SPCE-Chi-GST at
1x1 m AFM scan size.
Parameters
Area (nm2)

Mean
Std.

2.215
3.385

4.185
1.029

SPCEChiGST
3.165
3.792

Volume
(nm3)

Mean

1.882

0.037

1.063

Std.

2.943

0.089

1.307

Mean

67.54483.85489.109Std.

43.25982.99964.534

Mean

205

273

252

Std.

155

335

179

Mean

10.212

6.942

5.683

Std.

5.995

3.164

3.777

Length(nm)
Perimeter(nm)
Rpv (nm)

Bare
SPCE

SPCEChiNote: Rpv = peak-to-valley, Std = root mean squareor standard deviation

Fig. 1

Statistical information ongroups of these grains
could also be evaluated to define distribution of thegrain size. Quantitative scoring for the grain size
distribution through histogram plots are shown in
Fig. 2. Distinction in grain size distribution is also
manifested among these surfaces, thus exemplify

Three-dimensional AFM nanoscale surface
images of (A) SPCE, (B) SPCE-Chi, and(C) SPCE-Chi-GST.
334

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

asymmetric growth evidence following chitosan
deposition and GST immobilization process.

varied following the modification with chitosan andthe immobilization with GST.

Fig. 3Fig. 2

Power spectral density (PSD) function of
the waveguide analyzed along a line in the
AFM image via 1x1 m scan size: (a) bare
SPCE, (b) SPCE-Chi and (c) SPCE-ChiGST.

Fig. 4 displays 2D isotropic power spectral in a
log-log plot of PSD and frequency of each working
surface in comparison to their relevant slopes for an
estimation of the fractal dimension by triangulation
method included in the XEI software. All the 2D
PSD plots show quite similar in the slope patternthat gradually decreasing from lower to higher
spatial frequenciesbut with a bit different in theirwaviness concerning to their relative waveguide
profile in Fig. 3. These PSD plots also reflect theroughness contribution in their correlative surface.
Moreover a condense description in term of fractal
dimension of the surface can be quantified based on
this PSD function in a more sample-independent
manner according to the inverse power law decay[10]. Generally, the fractal model provides moredetail on rough surface morphology considering theconcepts of scale and the symmetry elements.In
another words, fractal objects can be characterizedby morphological invariance under scale variancein
a restricted range of the spatial scales and allow
determination of surface morphology by scale laws[11]. The calculated fractal dimensions in this study
are 2.12, 2.27 and 2.02 for SPCE, SPCE-Chi and
SPCE-Chi-GST working surface, respectively(Table 2), suggesting a small but markedly
difference among each surface texturein subsequent
to the layer-by-layer deposition process due to their
distinct attribution in the fractal figure occupied
along these investigated 3D images.
The higher value of fractal dimension in SPCEChi working surface represents a higher level offractality and a more continuous irregular feature ofGrain size distribution histogram of SPCE,
SPCE-Chi and SPCE-Chi-GST at 1x1 m
AFM scan size.

Power spectrum density (PSD) and fractality
Further analysis of surface feature was
performed by power spectral density (PSD) which isone of important parameters in surface roughness
representation. PSD of the loaded image is obtained
from Fourier Transform (FT) of the image andreflects the root mean square(Rq) roughness of thesample surface. according to the relation: PSD = FT 2
= Rq2. Information given from PSD graph provides
not only roughness status but also the contribution ofeach frequency components to the total roughness ofthe surface [9]. The curves depicted in Fig. 3 show
the PSD function of the waveguide evaluated along
a line in the AFM image of each working surface
acquired via 1x1 µm scan size.The contribution ofeach spatial frequency to the line profile versus
frequency is represented. The most outstanding peakwith the highest frequency intensity in each curve at
2, 3 and 1 µm-1 was delivered from SPCE, SPCEChi and SPCE-Chi-GST working surface,respectively. In spite of these low spatial values, thecurves indicate thatthe spatial periodicity of resist
molecular aggregates existed in the surfaces is335

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

the surface roughness than the others while thesmaller value represents a smoother top surface [12].
The lowest value obtained in the case of SPCE-ChiGST thus infers a smoothening flow of successive
GST immobilization. This evidence also indicates avertical growing of the filling GST on the basal
chitosan modified screen printed carbon surface.

Fig. 4

figuring surface profiles that is fluctuate from a highplateau of SPCE to a shallow top up layer in SPCEChi and an up level of the dept again in thefollowing SPCE-Chi-GST. In cases of the Rsk andRku representing the shape and sharpness of theheight distribution, on the other hand, the porosityand load carrying capacity, are decreased in SPCEChi from the value of the basal SPCE working
surface thus suggesting a growing of valleys andcavities appropriate to groove the enzyme molecules.
While an increasing of these value are scored in theworking surface of SPCE-Chi-GST, on contrary,suggesting a growing of peaks rather than cavities
by virtue of the fill up GST immobilization process.
Measurement of the Rsm shows values down from
0.39 µm in SPCE to 0.11 and 0.08 µm in SPCE-Chi
and SPCE-Chi-GST. These values similarly indicate
a decreasing of lateral adjacent peak spaces
following a diffusive topping aggregation in thecorresponding stepwise manipulation. All theparameters determined thus definitely assure theprogression of desirable environmental sensor basedon the selective GST enzyme.
Table 2 Surface profile exploration from AFM
micrographs at 1x1 m scan size of bare
SPCE, SPCE-Chi, and SPCE-Chi-GST.

Two dimensional (2D) isotropic power
spectral plots of log PSD and frequency of
the working surface of SPCE, SPCE-Chi
and SPCE-Chi-GST at 1x1 m AFM scansize in comparison to their relevant slopes
for an estimation of the fractal dimension
by triangulation method.

AnalysisSPCE
SPCESPCEparameters
Chi
Chi-GST
Ra (nm)
18.69
21.74
26.72
Rq(nm)
24.49
25.15
33.17
Rpv (nm)157.23 111.62
143.38Rz (nm)155.24 108.88
142.81
Rsk
-0.19
-0.18
0.59
Rku
3.32
1.96
2.67
Rsm (µm)
0.39
0.11
0.09
Fractal
2.14
2.27
2.02
(triangular)
Note: Ra = roughness average, Rq = root meansquare roughness or standard deviation of the heightvalue, Rpv = peak-to-valley, Rz= ten point
height,Rsk = skewness, Rku = kurtosis, Rsm = mean
spacing average.

Surface roughness characteristics
The surface roughness characteristics of thechitosan modified layer both before and after GST
immobilization in comparison to a screen printed
carbon basement layer were measured from theobtained AFM images by important statisticalparameters such as average roughness (Ra), root
mean square roughness (Rq), peak-to-valley (Rpv),
ten point height (Rz), mean spacing average (Rsm),
skewness (Rsk), kurtosis (Rku), and mean spacing
average (Rsm). Table 2 displays the estimated values
which explicitly show trends in their layer by layer
toping relation. The Ra and Rq similarly describe
overall height distribution profile as a result of themean height and the standard deviation of the profile
height hence imply the top surface wavy roughness
characteristics which seem to be remarkably
increase over one order of magnitude in SPCE-Chi
platform, in consent to our previous report [2].
Simultaneously, these surface roughness parameters
appear to be highest in the SPCE-Chi-GST working
surface due to the succession of GST oriented
assembling. The values gained in Rpv and Rz clearly
explain a differentiation in spike depth among the

CONCLUSION
A fundamental step in enzyme biosensor
development is to get success in the immobilizationof a selected enzyme onto suitable platform. In thisstudy, a SPCE was chosen as a convenient basement
for a self assembled modification with
biocompatible chitosan polymer, afterward the
enzyme GST was immobilized onto a working
surface of this SPCE-Chi using glutaraldehyde as acrosslinker. To gain valuable information for a
progress achievement of immobilization, ananoscale imaging and several analysis strategies via
AFM were employed. The obtaining 3D AFM
336

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

images have illustrated a clear distinction inmorphological appearance among SPCE, SPCE-Chi
and SPCE-Chi-GST working surfaces. Statisticalparameters and fractal geometry were used as two
main analysis approaches with an XEI software
assistance for describing the surface roughnessand
complexityofirregular
nanostructures.
Determination of the surface grain size anddistribution has denoted the asymmetric planar
growth in grain area and parameter of SPCE-Chi and
SPCE-Chi-GST working surface. One of the mostimportant parameters as power spectral density(PSD) curves was performed and proved capable toreflect differences among the roughness and its
contribution on these surfaces. Fractal dimension
character of each surface could be calculated withreference to this PSD function and an indicativevalue for diffusion limited manner was gained fromboth SPCE-Chi and SPCE-Chi-GST as a result fromsurface modification with chitosan and subsequentimmobilization with GST. Several other quantitative
statistical roughness parameters were also assessed
and all indicate the complete layer by layer
development in the SPCE-Chi and SPCE-Chi-GST.
The outcome AFM images as well as surface
topographical delineation of these prepared surfaces
have revealed a surface dependent characteristic andconsequently, a successfulness of the proposed
simple direct self assembling stepwise processing
for well done enzyme immobilization. Fabrication ofdesirable biosensor for real time monitoring ofspecific environmental pollutants based on theselective GST enzyme shall be thus possible.

carbon electrode by self assembled depositionof chitosan and activated carbon” Int. J. of
GEOMATE, Vol. 11, Aug.2016, pp. 2356-2362.
[3] Aminea A, Mohammadia H, Bourais I,
PalleschiG,“Enzymeinhibition-based
biosensors for food safetyand environmental
monitoring” Biosens. Bioelectronics, Vol. 21,
Mar. 2006, pp. 1405-1423.
[4] Krajewska B, “Application of chitin- andchitosan-basedmaterialsfor
enzymeimmobilizations: a review”, Enzyme andMicrobial Technology, Vol. 35, Aug. 2004, pp.
126–139.
[5] Wongkaew P, Poosittisak, S, 2012. “Electroaffinity of SCWL-dsDNA on different highdeacetylation degree chitosans deposited glassy
carbon electrode”, Advances in Developing
Affordable In-Vitro Molecular Diagnostics, Puri
CP, Abidi N, Bhanushali P, Pere A, Gupta SK,
Eds., Yashraj Research Foundation, Varun
Enterprises, 2012, pp. 249-258.
[6] Singh RP, “Prospects of Organic Conducting
Polymer Modified Electrodes: Enzymosensors”,
Int. J. of Electrochemistry, Vol. 2012, Jan. 2012,
pp. 1-14.
[7] Variola F, “Atomic force microscopy inbiomaterials surface science”, Phys. Chem.
Chem. Physics, Vol. 17, Feb. 2015, pp. 29502959.
[8] Singh RP, Kim YJ, Oh BK, Choi JW,“Glutathione-s-transferase
basedelectrochemical biosensor for the detection of
captan”, Electrochem. Communications, Vol. 11,
Jan. 2009, pp.181–185.
[9] Gavrila R, Dinescu A, Mardare D, “A power
spectral density study of thin films morphology
based on AFM profiling”, Rom. J. Inform. Sci.
Technology, Vol. 10, Sept. 2007, pp.291–300.
[10] Church EL, “Fractal surface finish”, Appl.
Optics, Vol. 27, Apr. 1988, pp. 1518-1526.
[11] Stach S, Cybo J, “Multifractal description of
fracture morphology: theoretical basis”, Mater.
Characterization, Vol. 51, Aug. 2003, pp. 79-86.
[12] Ţălu S, Stach S, Ikram M, Pathak D, Wagner T,
Nunzi
J-M,
“Surfaceroughnesscharacterization of ZnO: TiO2-organic blended
solar cells layers by atomic force microscopy
and fractal analysis”, Int. J Nanoscience, Vol.
13, Jun. 2014, No. 03, 12 pp.

ACKNOWLEDGEMENTS
The authors gratefully acknowledge the financial
support provided by Division of Research andTechnology Transfer Affair, KhonKaen University(KKU-56-57) and the KKU Research Instrument
Center for technical supports.
REFERENCES[1] Wongkaew P, Poosittisak, S. “Diagnosis ofsugarcane white leaf disease using the highly
sensitiveDNA
based
voltammetricelectrochemical determination”, Amer. J. of
Plant Sciences, Vol. 5, Jul. 2014, pp. 2256-2268.
[2] Wongkaew P, Poosittisak, S.“Atomic force
microscopic
andelectrochemical
characterization of the modified screen printed

337

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

COLUMN BASED INFILTRATION EXPERIMENT FORCONSIDERING INITIAL QUASI-SATURAETED VOLUMETRICWATER CONTENT DUE TO DEFFERENCES OF WATER SPRAYINTENSITY AND GRAIN SIZE DISTRIBUTION
Hiroshi Kita1, Keigo Koizumi2 and Kazuhiro Oda3 and Mitsuru Komatsu4
1
Graduate School of Engineering, Osaka University, Japan;
2
Graduate School of Environmental and Life Science, Okayama University, Japan

ABSTRACT
Rainfall-induced slope failure has been increasing in recent years in Japan. In this study, it was hypothesizedthat displacement on a model slope would not occur unless the initial quasi-saturated volumetric water content
was exceeded. This prediction was based on a slope failure experiment using a scale-down slope model.
However, in order to apply the initial quasi-saturated volumetric water content as an early warning index for
slope failure monitoring, it is necessary to understand the relationship between the initial quasi-saturated
volumetric water content and following two factors that affect water infiltration behavior. One is rainfall
intensity. The other is soil physical properties. As the first try to understand the factors, two types of fundamentallaboratory experiments was conducted; a column experiment for understanding the relationship with the water
intensity; a column experiment for understanding the relationship with grain size distribution. As a result, a
positive correlation between the initial quasi-saturated volumetric water content and a rainfall intensity wasconfirmed through the vertical one-dimensional infiltration experiment using a water spray and a column soiltank. Second, a result of evaluating the relationship between grain size distribution and the initial quasi-saturated
volumetric water content, it was confirmed that the value of the initial quasi-saturated volumetric water content
differed according to grain size distribution. Considering these results, it is expected that the initial quasisaturated volumetric water content can be utilized for a forecast of the rainfall-induced slope failure byidentifying them with multi-monitoring points on the target slope.
Keywords: Volumetric Water Content, Rain Intensity, Grain Size Distribution, Slope Failure

column experiment is the same as the initial quasisaturated volumetric water content in the modelslope when performing the sprinkling-water
experiment on the column and the model slope
under the same physical-property condition [5].
Koizumi et al. (2017) defined the initial quasisaturated volumetric water content as the state at
which the infiltration and drainage in the vicinity ofthe sensor are balanced under the infiltration processfrom the upper part. Based on the fact that
deformation does not occur unless the initial quasisaturated volumetric water content is exceeded,
Koizumi et al. (2017) suggested that an initial quasisaturated volumetric water content will be an index
to forecast rainfall-induced slope failure in advance[6].
However, in order to apply the initial quasisaturated volumetric water content as an early
warning index for slope failure monitoring, it isnecessary to understand the relationship between theinitial quasi-saturated volumetric water content andfollowing two factors that affect water infiltration
behavior. One is rainfall intensity. The other is soil
physical properties. As the first try to understand thefactors, following fundamental relationships were

INTRODUCTION
In recent years, rainfall-induced slope failure has
been frequently occurring in Japan. In order topredict slope failure, on-site monitoring [1],laboratory-scale slope experiment and seepage
analysis etc. are carried out [2]–[4].
The authors clarified the relationship between
volumetric water content and displacement (shear
deformation), as shown in Fig. 1, using a small
model slope as a basic experiment for grasping
rainwater infiltration. As this schematic diagram
indicates, volumetric water content when the rate ofrise initially decrease is defined as the initial quasisaturated volumetric water content. After the initialquasi-saturated state appears, shear deformation thattriggers the slope failure begins. Figure 2 shows thechange in volumetric water content due to sprinklingwater in a column experiment. The soil sample is not
fully saturated by water infiltration from above, andit temporarily equilibrates at a certain volumetricwater content. Owing to the subsequent rise of thesaturation zone from the bottom of the column,
volumetric water content again rises. The volumetricwater content at the time of equilibrium in the338

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

evaluated:
1) Relationship between the water spray
intensity and initial quasi-saturated
volumetric water content
2) Relationship between the grain size
distribution and initial quasi-saturated
volumetric water content

Table 2 details the physical properties of the soil
samples, Table 3 details the grain size fraction foreach soil sample, Fig. 3 shows the grain size
distribution, and Fig. 4 illustrates the column soiltank. The total number of cases in the experiments isthree, which are referred to as Case-60 A, Case-100
A, and Case-100 B, respectively. The numbers 60
and 100 refer to the water spray intensity, whereas A
and B refer to the soil sample. Using an acrylic
column, a soil tank was prepared under theexperimental conditions described in Table 1.
Regarding the B sample, because the soil samples
taken at the site were naturally dried in separate vatsfor the upper and lower parts, the initial watercontent was different. Thirty-two air holes each witha diameter of 2 mm were provided on the side of thecolumn, thereby suppressing the occurrence of pore
air pressure within the column and confirming the
groundwater level via outflow of water from the airholes. However, once confirming the water level atthe bottom of the column, all air holes were sealedwith putty. To measure the volumetric water content,a soil moisture sensor, EC-5 (Decagon Co.;measurement accuracy: ± 3.0%), was installed andimplemented at depths of 50 mm (upper) and 150
mm (lower). The measurement interval was 1 min.,and the sensor was installed horizontally because thesoil moisture sensor should not obstruct the water
path. In all cases, when the water reach the bottom
and groundwater re-rise to the top of the soil tank,the experiment was finished.

Infiltration Behavior

Rainfall Intensity

Initial Quasi-saturated
Volumetric Water Content

Deformation(㎜)Volumetric Water Content(cm3/cm3)

Shear Deformation

Time(min)Volumetric Water Content(cm3/cm3)

Fig. 1 Volumetric water content and slope
deformation on model slope as functions of time
Infiltration Behavior
Rainfall Intensity

Initial Quasi-saturated
Volumetric Water Content

Table 1 Experimental conditions
Case

Case-60A

Water Spray
Intensity(mm/h)

Case-100A

Case-100B

100

100

60

Top

Opening(Water Spray)Side

Impermeable Side(Air Hole)

BottomImpermeable Face

Boundary
Condition

Table 2 Physical properties of soil samples

Time(min)Fig. 2 Volumetric water content observed during
water spray experiment on the column as a functionof time

Case

Case-60A

Case-100A

Case-100B

Samples

A Sample

A Sample

B Sample

2.607

2.607

g/cm3）

Soil Particle Density

COLUMN EXPERIMENT METHODSIn this study, in order to compare and evaluate
the relationship between the water spray intensity
and initial quasi-saturated volumetric water content,
experiments were conducted using a water spray
intensity of 60 mm/h and 100 mm/h. Additionally, inorder to compare and evaluate the relationshipbetween the grain size distribution and initial quasisaturated volumetric water content, we focused on
sandy soil, using sandy soil dominated by sandy
fraction (A sample) and sandy soil dominated by silt
fraction and clay fraction (B sample).
Table 1 outlines the experimental conditions,

Initial Water Content (w)

（％）

S

Upper

Lower

Upper

2.911

Lower

Upper

Lower

11.53

18.25

5.0

5.0

g/cm3）

1.629

1.629

0.970

Maximum Dry
Density()

g/cm3）

1.766

1.766

1.422

Void Ratio(e)

（－）

0.6

0.6

2.0

Hydraulic Conductivity(k)（cm/s）

1.21×10-2

1.21×10-2

4.65×10-3)

Table 3 Soil sample grain size fractions
Samples339

GravelSand
Fraction(%) Fraction(%)

A Sample

24.6

70.2

B Sample

16.8

43.3

Silt
Fraction(%)

Clay
Fraction(%)

5.2
17.6

Soil mark
SG-Cs

22.3

SCsG

100

0.40

90

0.35

Volumetric Water Content（㎝3/㎝3）

Percentage by Passed Mass(%)

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

80
70
60

50
40
30

20

A Sample

10

B Sample00.001■Initial Quasi-saturated Volumetric Water Content
Secondary Equilibrium States

0.30

Experiment was finished

0.25
0.20
0.15

Case-60A Upper Depth
Case-60A Lower Depth
Case-100A Upper Depth
Case-100A Lower Depth
Saturated Volumetric Water Content

0.10
0.05
0.00

0.01

0.1
1
Grain Size(mm)

10

100

0

Fig. 3 Grain size distribution

Initial Quasi-Saturated
Volumetric Moisture Content(cm3/cm3)

200

100
50

Lower Side

60

80

100
120
Time（min）

140

160

180

200

0.25

Upper Side

Air Hole

40

Fig. 5 Volumetric water content for different
water spray intensities at upper and lower depths

50

Acrylic

20

EC-5
200

0.2

0.15

0.1

0.05

Case-60A

Upper Depth

Case-60A

Lower Depth

Case-100A Upper Depth

Fig. 4 Column soil tankCase-100A Lower Depth
00

RELATIONSHIP BETWEEN THE WATERSPRAY INTENSITY AND INITIAL QUASISATURATEDVOLUMETRICWATER
CONTENT

20

40
60
80
Water Spray Intensity(mm/h)

100

120

Fig. 6 Relationship between the water spray
intensity and initial quasi-saturated volumetric watercontent
RELATIONSHIP BETWEEN GRAIN SIZE
DISTRIBUTION AND INITIAL QUASISATURATEDVOLUMETRICWATER
CONTENT

Experimental Results
Fig. 5 show relationships between the volumetricwater contents and the elapsed times of Case-60A
and Case-100A, respectively. After sprinkling water,
the volumetric water content increased in order fromthe upper depths to the lower depth. An equilibrium
state with values between 0.16 and 0.18 was
observed in the case of Case-60A, and values
between 0.19 and 0.20 in the case of Case-100A.
Subsequently, the volumetric water content at thelower depth re-increased before re-increasing at theupper depth. Secondary equilibrium states ofvolumetric water content with values between 0.30
and 0.31 in the case of Case-60A and a value ofapproximately 0.30 in the case of Case-100A wereobserved.

Experimental Results
Fig. 7 shows the time series change in eachvolumetric water content for Case-100A and Case100B which are different grain size distributions.
After sprinkling water, the volumetric water content
increased in order from the upper depths to the lower
depth. An equilibrium state with values between
0.19 and 0.20 was observed in the case of Case100A, and values between 0.37 and 0.40 in the caseof Case-100B. Subsequently, the volumetric watercontent at the lower depth re-increased before reincreasing at the upper depth. Secondary equilibrium
states of volumetric water content with value ofapproximately 0.30 in the case of Case-100A, andvalues between 0.63 and 0.65 in the case of Case100B were observed.

Discussion
Here, the relationship between the water spray
intensity and the initial quasi-saturated volumetricwater content, which is shown in Fig. 6, will be
discussed. This figure shows that a positive
correlation exists between the water spray intensity
and the initial quasi-saturated volumetric watercontent. It indicates that this relationship should beconsidered as a fundamental property when theinitial quasi-saturated volumetric water content is
discussed.

Discussion
Here in Fig.7, the relationship between grain size
distribution and the initial quasi-saturated volumetricwater content will be discussed. It was confirmedthat the value of the initial quasi-saturated
volumetric water content differed according to grain
size distribution. Fig. 8 shows the relationship
340

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

between the initial quasi-saturated volumetric watercontent and the degree of saturation for Case-100A
and Case-100B. The degree of saturation was
calculated fromthe relationship between thesaturated volumetric water content and thevolumetric water content. The saturated volumetricwater content was calculated from the void ratio on
the experimental condition. Although the initialquasi-saturated volumetric water content of eachsample was different, the degree of saturation was
ranging from 50% to 60%.

Considering these results, it is expected that theinitial quasi-saturated volumetric water content canbe utilized for a forecast of the rainfall-induced
slope failure by identifying them with multimonitoring points on the target slope.
ACKNOWLEDGEMENTS
This research was partly supported by Grant-inAid for Scientific Research (17K00615). We express
our gratitude.

Volumetric Water Content(cm3/cm3)

0.70

REFERENCES■Initial Quasi-saturated Volumeric Water Content

0.60
0.50

Secondary Equilibrium States

[1]

0.40

Experiment was finished0.30
Case-100A Upper Depth
Case-100A Lower Depth
Case-100B Upper Depth
Case-100B Lower Depth
Saturated Volumetric Water Content

0.20
0.10

[2]

0.00
0

10

20

30

40

50
60
Time(min)

70

80

90

100

Fig. 7 Change in volumetric water content fordifferent grain size distributions
[3]
100.0
90.0

Degree of Saturation(%)

80.0
70.0
60.0

50.0

[4]

40.0

Case-100A

Upper Depth

30.0

Case-100A

Lower Depth

20.0

Case-100B Upper Depth

10.0

Case-100B Lower Depth

0.0
0

0.05

0.1
0.15
0.2
0.25
0.3
0.35
0.4
Initial Quasi-saturated Volumetric Water Content(cm 3/cm3)

0.45

[5]

Fig. 8 Relationship between initial quasi-saturated
volumetric water content and degree of saturation
CONCLUSIONS[6]First, As a result, a positive correlation between
the initial quasi-saturated volumetric water content
and a rainfall intensity was confirmed through thevertical one-dimensional infiltration experimentusing a water spray and a column soil tank. Second,a result of evaluating the relationship between grain
size distribution and the initial quasi-saturated
volumetric water content, it was confirmed that thevalue of the initial quasi-saturated volumetric watercontent differed according to grain size distribution.

341

Koizumi K, Konishi T, et al.,”Improvementof slope warning system with ubiquitouscommunication environment”, in Proc.
Kansai Geo-Symposium 2014, 2014, pp.
141–144．
Iida T, Fujimoto M, et al., ”A method tojudge slope failures using soil moisturecharacteristics”, International Journal of
GEOMATE, June, 2016, Vol. 10, Issue 22,
pp.2094-2100
Sasahara K, Sakai N, ”Shear deformation
development and the increase of porepressure due to rainfall infiltration in sandymodel slope under different inclination”,
Int. J. of GEOMAT, Oct. 2011, Vol. 1, No. 1(Sl. No. 1), pp., 64-70
Ito S, Oda K, Koizumi K, Usuki Y,“Identification of slopes with higher risk toslope failures based on information
processing techniques”, Int. J. of
GEOMATE, June, 2015, Vol. 8, No. 2 (Sl.
No. 16), pp. 1226-1231
Ohnishi T, Koizumi K, Oda K, Adrin T,“Grasp of water infiltration behavior up to
shallow landslides in miniature slope”, in
Proc. Kansai Geo-Symposium 2014, 2014,
pp. 213–216．
Koizumi K, Sakuradani K, Oda K et al.,“Fundamental research on advancement ofregulation standard for expressway
management
againstrainfall-induced
surface failure”, J. of Japan Society of Civil
Engineers, Ser. C (Geo-engineering), Vol.
73, No. 1, 2017, pp. 93–105.

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

ENVIRONMENTAL RISK ASSESSMENT AND MANAGEMENT OF
BIOMASS POWER PLANTS FOR SUSTAINABILITY IN THAILAND
Manutchanok Jongprasithporn1, Adisak Martsri2, Supapat Phuangkaew3, Wannapong
Yeamma4, and Nantakrit Yodpijit5
1

Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology
Ladkrabang, Thailand
2
Center for Innovation in Human Factors Engineering and Ergonomics, Department of Industrial
Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Thailand

ABSTRACTThe environmental impact of electricity generation is becoming more critical as electricity consumption
continues to increase. It is because the world’s population is growing very fast and modern communities use
large amounts of electric power. This paper presents the assessment and management of environmental risk of
7.5 and 9.9 MW biomass power plants in Thailand. Three environmental factors (air, transportation) have been
examined in this research project. In the environmental analysis, comparisons of measured environmental datafrom the sites and environmental standards by USEPA (United States Environmental Protection Agency) and
Thailand’s PCD (Pollution Control Department) are performed. This research project focuses on sustainability
that impacts economic, social, and environment aspects by communities, companies, and individuals. The
sustainable development of the research project can lead to a coherent and long-term balance between these three
aspects. Recent findings from the environmental monitoring system revealed that quality levels of all threeenvironmental factors are under the standards. It is implied that these two biomass power plants do not
negatively affect the environment and satisfy the essential needs of humanity.
Keywords:Environmental risk, Biomass power plant, Sustainability
future is of importance. Moreover, the power plants
should use renewable resources when generating
electricity.
Renewable energies are becoming very
important to economic development [2,3]. The
thermal power plant and combined-cycle power
plant are the most used in Thailand. Burning fossil
fuels such as coal oil and natural gas has releases
greenhouse gases and other pollutants into theatmosphere [4-6]. So a few renewable energy suchas wind, solar, biogas, biomass energy are now used
to produce electricity instead of fossil fuels and coal.
Because Thailand has a lot of biomass resources,
biomass power plants are a good choice to solve theenergy shortage problem.
Previously, there were a lot of problems whenconstructing a power plant. They were opposed by
the community due to the fear of various power
plant issues which could affect the community.
Especially, the environmental impact from thepower plant was the main problem. The
environmental impact has brought many complaints
and has a negative impact on the surroundings.
Therefore this research analyzes and manages theenvironmental risks of power plants. The risk affects
the power plant safety and the people in the

INTRODUCTION
Today electricity is an important energy.
Electricity is used for daily life, activities andeconomic development. The demand for electricity
in Thailand increases every year due to theeconomic growth and population growth as shown in
Figure 1.

40000

Demand of Electricity in Thalind
(MW)

30000
20000
10000
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

0

Fig. 1

Demand for electricity in Thailand [1]The trend of the demand for electricity in
Thailand is rising. Therefore, increasing theelectrical capacity and constructing more power
plants to solve the energy shortage problem in the342

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

community around the power plant [7]. In addition,risk assessments and opportunities for factor
analysis as well as a recommendation hedging
measure for the future.

Ash

ESP, Multi-cyclone
Feul – Rice husk

Fuel Handling
SystemExhaustfrom
combustion

Steam

BoilerWater

RESEARCH METHODS
Water Treatment
SystemThis research has two steps as follows:
1. Study the power plant processes.
2. Study of environmental conditions andmeasurement of environmental factors in power
plant areas.

Fig. 2

Ash Handling
SystemChimney of power
plant

Turbine andCondenser

Generator

Cooling
Tower

Transmissionline

The biomass power plants process used inthis research

The process of generating electricity from abiomass power plant starts with the rice husk whichis stored in the silo as a combustion fuel to heat theboiler. Until a high pressure steam is sent to thesteam turbine to make the turbine rotate. The
generator is connected to the shaft of the steam
turbine. The generator will then rotate to produce
electricity. The waste gasses from these processes
are sent to the waste gas treatment plant and the ash
removal machine before the gas is discharged
through the plant's waste flue. The steam that goes
through the steam turbine will be sent to the cooling
tower to condense the hot steam into the water forreuse in the boiler. The machines and equipment
found in a biomass power plant are listed in table 1.

Study the Power Plant Processes
The power plants in this research are biomass
power plant with a capacity of 9.9 MW and 7.5 MW.
The fuel for biomass power in this research is ricehusk. The rice husk is used as a combustion fuel togenerate electricity. Location of both biomass power
plants are at Suphan Buri-Uthaithani Road
(Highway 333), U-Thong district, Suphan Buri.The
process of a biomass power plant used in thisresearch are shown in Figure 2.

Table 1 The machine and equipment of the biomass power plant
Number of
MachineMachines

Power

Total Power

(HP)

(HP)

Bucket Elevator
Belt Conveyor

7.5

4

30

7.5

2

15

Belt Conveyor

5.0

4

20

Husk Feeder

7.5

4

30

F.D Fan

125.0

1

125

F.D Fan

75.0

1

75

Spreader Fan

55.0

1

55

I.D Fan

270.0

1

270

Boiler and Pump

270.0

2

540

Electrostatic Precipitator

55.0

1

55

Air Compressor

15.0

2

30

Drum

3.0

1

3

Screw Conveyor Dust Collector

3.0

1

3

Screw Conveyor Dust Collector
Screw Conveyor Under ESP

3.0
2.0

1

3

2

4

Chain Conveyor

7.5

2

15

Pump to Clarify

30.0

2

60

Pump to Softener

20.0

2

40

343

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

Table 1 continued
Number ofPower

Total PowerMachines

(HP)

(HP)

Pump to Sand Filter

20.0

2

40

Pump to R.O

5.0

2

10

Pump to Mixed

5.0

2

10

Pump to De-aerator

7.5

2

15

Pump to Cooling Water

20.0

2

40

Cooling Fan

50.0

4

200

Cooling Fan

270.0

3

810

Condensate Pump

15.0

2

30

Diesel Generator

1,610.01

1,610

Steam Turbine Generator

12,750.0

112,750

Etc.

67.00

1

67

56

16,955

MachineTotal
The Study of Environmental Conditions andMeasurements of Power Plant Area

RESULTSIn this section, the results of the implementation
are covered. The environmental factors are air
quality and transportation. Measurements of value
were collected from both of the biomass power
plants. The area of this research covers 5 km aroundthe biomass power plants. The results ofimplementation are as follows.

In this process, the environmental impacts to thearea of both biomass power plants were studied.
Moreover, air quality and transportation are alsomeasured.
Air quality
The risk of pollution in the air will be assessed toinvestigate if Biomass power plants have negative
impact on the environment or not. The measured
value will be compared with the standard values.
The standard values have been set by environmental
departments such as the United States
Environmental Protection Agency (USEPA) and
Thailand’s Pollution Control Department (PCD)[8,9]. The measured value must not exceed thestandard values, [2,3,7].The air pollution should becomposed of Total Suspended Particulate (TSP),
Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), andCarbon Monoxide (CO). The area around both of thebiomass power plants will be measured.

Air quality
The value of environmental pollutants in theatmosphere were measured and collected. The
results are shown in Tables2 and 3.
The air pollutants measurement was a 1-hour
average of Sulfur Dioxide (SO2), Nitrogen Dioxide(NO2), Carbon Monoxide (CO), and 24-hours
average Total Suspended Particulate (TSP). The
results show the air pollutants in the atmosphere of
two biomass power plants. The quality of air quality
was within the standard. Except total suspended
particulate at the power plant (9.9 MW) in day 1 and
2 because of agency maintenance of the road surface
in those two days. Therefore, total suspended
particulate was higher than the other days.

Transportation

Table 2 Air Monitoring (Power Plant 9.9 MW)
Pollutant Concentration
Measured
SO2
NO2
CO
TSP
Date
(ppm) (ppm) (ppm) (mg/m3)

Transportation is an important factorwhen
developing economically [10]. If the power plant has
a good transportation system, economics of thepower plant are better becausethe transportation
costs would be cheaper[11].Both biomass power
plants in this case study are locate at U-thong district
Suphan-buri province.

344

10.00530.0165

0.58

0.52

2

0.00470.0106

0.62

0.45

3

0.00440.00860.53

0.25

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

Table 2 continued

Dioxide (NO2) and Carbon Monoxide (CO) within
the standards [12]. The removal particular system inboth of biomass power plants used Multi-Cyclone
separators and Electrostatic Precipitator (ESP).
Therefore, total Suspended Particulate (TSP) in thesurrounding area of the biomass power plants were
within the standards. The pollutant from thechimney of the biomass power plant is shown in
Table 4.

Pollutant Concentration
Measured
Date

SO2
(ppm)

NO2
(ppm)

CO
(ppm)

TSP
(mg/m3)40.00280.0057

0.43

0.19

5

0.00300.00610.36

0.20Standard*

0.30

0.17

30

0.33

Table 4 The pollutant from the chimney of thebiomass power plants
NOx
TSP
Pollutant
SO2 (ppm)(ppm)(mg/m3)
power
plant
<0.10
106.41
28.22(9.9MW)
power
plant
<0.10
150.86
20.64(7.5 MW)Standard*
60
200
320
*The standard values. Reference from act oflegislation from the factory Ministry of Industry [13]Table 3 Air Monitoring (Power Plant 7.5 MW)
Pollutant Concentration
Measured
SO2
NO2
CO
TSP
Date
(ppm) (ppm) (ppm) (mg/m3)
10.00240.0149

0.49

0.13

2

0.00210.0132

0.63

0.16

3

0.00250.0129

0.42

0.18

4

0.00350.0136

0.55

0.15

5

0.00290.01400.54

0.13Standard*
0.30
0.17
30
0.33
*The standard values. Reference from criteria air
pollutants USEPA and act of legislation of pollution
control Department [5-6]Transportation
Due to the biomass power plants having ricehusk deliveries every day, it is necessary to consider
the effect of density on the roads. Database of
Bureau of Traffic Safety, Department of Rural
Roads, Ministry of Transport [11,14] shows theaverage daily traffic on the road that are used totransport rice husks. Traffic volumes are 6,40010,000 per day. The detail of traffic volumes on the
highway are shown in Table 5.

Air quality assessment
The result shows that Sulfur Dioxide (SO2) was
low, this is because rice husk have a low sulfur
compound. Controlling the temperature, heat andoxygen in the boiler helped to handle Nitrogen
Table 5 Traffic volumes on highway [11, 14]
VehicleTraffic volumes on highway (per day)No. 321

No. 333

No. 3342

No. 3472

Car< 7 persons

671

3,045

1,298

1,158

Car > 7 persons

1,636

1,001

2,658

789

Small Bus

51

227

424

395

Medium Bus

85

95

156

183

Large Bus

120

238

224

229

Small Truck

1,521

1,027

890

1,766

Medium Truck

522

497

882

1,158

10 Wheel Truck

401

514

658

512

Trailer

376

318

509

210

Hybrid Trailer

30

167

178

95

Motorcycle

964

1,432

2,204

1,817

345

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

Table 5 continued
Traffic volumes on highway (per day)
VehicleNo. 321

No. 333

No. 3342

No. 3472

Total Truck

2,850

2,523

3,117

3,741

Total Vehicle

6,377

8,561

10,081

8,312

From table 5, the traffic volume on the highway
no. 321, 333, 3342 and 3472can calculate theproportion of car volume. Each type of vehicle canadjusted to PCU (Passenger Car Unit)[14]as shownin Table 6.

Table 6 Traffic statistics on highway [14]VehicleCar < 7 persons
Car > 7 persons
Small Bus
Medium Bus
Large Bus
Small Truck
Medium Truck
10 Wheel Truck
TrailerHybrid Trailer
Motorcycle
Total Vehicle

PCU
1
1
1
1.5
2
1.5
2
2
2
2
0.25
-

Expectation of traffic volumes on highway (per day)No. 321
No. 333
No. 3342
No. 3472
671
3,045
1,298
1,158
1,636
1,001
2,658
789
51
227
424
395
127.5
142.5
234
274.5
240
476
448
458
2,281.5
1,540.5
1,335
2,649
1,044
994
1,764
2,316
802
1,028
1,316
1,024
752
636
1018
420
60
334
356
190
241
358
551
454.25
7,906
9,782
11,402
10,128The standard values of traffic capacity in eachtype of road are set by department of highways [14]as shown in Table 7. Four highways (321, 333,
3342, and 3472) have the capability to support 2,000
PCU per hour as follows

The measured values may change for many reasons
such as of the deterioration of a machine in the
power plant when used for a long time or the
expansion of a community near to the power plant.
Therefore, the guidelines and prevention measures tosolve problems that may arise in the future areproposed in this paper.

Table 7 Traffic capability by road type [15]Traffic volumes
Road type(PCU per hours)
2 lanes
2,000
3 lanes
4,000
4 lanes
2,000 per lane

Air Pollution Prevention Measures
1. Define a maintenance schedule to monitor thecondition and operation of machines to reduce thepollution from them.

The traffic capabilities in Table 7 with the traffic
statistics on highway in Table 6 were compared. The
ratio is as follows.
1. Highways No. 321 have the traffic volumes at
40 percent.
2. Highways No. 333 have the traffic volumes at
49 percent.
3. Highways No. 3342 have the traffic volumes
at 57 percent.
4. Highways No. 3472 have the traffic volumes
at 51 percent.
The ratio implies that, the volume of four
highways traffic is moderate and does not affecteither of the biomass power plants.

2. Define regularly measured pollution from thepower plant’s chimney to control the pollutant
within standard values.
3. Use water around the power plant’s area toreduce the dust around the power plant.
4. Preventive maintenance should be used toprevent machine failure in the power plant.
5. Provide protection cloth and glasses to
employees to prevent health problems because of theinternal combustion has a large amount of dust fromthe rice husk processing.
Transportation Performance Measures

Measures to Prevent Environmental Impacts

1. Control the pathway for the power plant’s
trucks.

Environmental factors can change at any time.
346

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

2. The truck’s speed must be limited byregulation. Cover trucks with burlap to prevent dust
from spreading.
3. Avoiding rush hour. (7.00-9.00 am and 4.006.00 pm).
4. Define the traffic lanes in the biomass power
plant and define traffic signs.
5. Set an employee to control the traffic in andout of the biomass power plant.
6. Provide adequate parking.

Progress in Energy and Combustion Science,38(1), 2012, 62-86.
[3] Mishra, U. C. “Environmental impact of coalindustry and thermal power plants in India.”
Journal of environmental radioactivity, 72(1),2004, 35-40.
[4] Singh, G., Kumar, S., Singh, M. K., &Mohapatra, S. K. “Environmental impact
assessment of ash disposal system of a thermal
power plant.” international journal of hydrogenenergy, 41(35), 2016, 15887-15891.
[5] Malek, A. A., Hasanuzzaman, M., Rahim, N. A.,& Al Turki, Y. A. “Techno-economic analysis
and environmental impact assessment of a 10
MW biomass-based power plant in Malaysia.”
Journal of Cleaner Production, 141, 2017, 502513.
[6] Wang, Z., Pan, L., Li, Y., Zhang, D., Ma, J.,
Sun, F., ... & Wang, X. “Assessment of air
quality benefits from the national pollution
control policy of thermal power plants in China:Anumerical
simulation.”
Atmospheric
Environment, 106, 2015, 288-304.
[7] Deborah, P., Francesca, V., & Giuseppe, G.
“Analysis of the environmental impact of abiomass plant for the production of bioenergy.”
Renewable and Sustainable Energy Reviews, 51,
2015, 634-647.
[8] United States Environmental Protection Agency.
Criteria
Air
Pollutants.1(Nov.
2016),,https://www.epa.gov/criteria-airpollutants[9] Thailand’s Pollution Control Department. Act
of legislation for controlling pollutions. 1 (Nov.
2016),http://www.pcd.go.th/info_serv/test_regul
ation5.cfm[10] Leboreiro, J., & Hilaly, A. K. “Biomasstransportation model and optimum plant size forthe production of ethanol.” Bioresource
technology, 102(3), 2011, 2712-2723.
[11] Ben-Iwo, J., Manovic, V., & Longhurst, P.
“Biomass resources and biofuels potential forthe production of transportation fuels in Nigeria.”
Renewable and Sustainable Energy Reviews, 63,
2016, 172-192.
[12] Kanokporn Jangsawang. 1999. Environmental
Impact Assessment. 2nd ed. Thai wattana
panich publisher.
[13] Ministry of Industry. Act of legislation forEnvironmentaloffactory.
25(Nov.
2016),http://www.diw.go.th/hawk/content.php?
mode=laws&tabid=1&secid=3&subid=1[14] Department of Highways. The traffic volumes
on highways in Thailand 2016. 10 (Feb.
2017),http://bhs.doh.go.th/download/traffic

CONCLUSIONSThis research has presented the environmental
impact (air and transportation) from a biomass
power plant. This research was defined into two
steps 1.Study the power plant processes. 2. Study
the environmental conditions and measurement ofenvironmental factors in power plant areas. The air
monitoring points were established for a village andcommunity near the power plants to study the air
quality. The relevant government departments alsocollaborated to study the traffic volume and statistic
relevant to routes for transportation. Results of thisresearch found that the pollutant (Sulfur dioxide,
Nitrogen dioxide, Carbon monoxide and totalsuspended particulate) were within the standards andthe volume of traffic on the four highways (321, 333,
3342, 3472) were at 40, 49, 57 and 51 percent. The
result implies that the impact of both biomass power
plants does not affect air or transportation. Measures
to prevent environmental impacts to air andtransportation were also presented. Although thisresearch did not clearly conclude that the biomass
power plants have an environmental impact or not,in future it would be necessary to study various
environmental impacts such as water noise etc to
fully confirm that the biomass power plant does notaffect the environment.
ACKNOWLEDGEMENTS
Research project was conducted at the Center
for Innovation in Human Factors Engineering and
Ergonomics, Department of Industrial Engineering,
Faculty of Engineering, King Mongkut's Universityof Technology North Bangkok.
REFERENCES[1] Electricity Generating Authority of Thailand.
Electrical Capacity in Thailand.(Nov. 2016),
https://www.egat.co.th/index.php?option=com_
content&view=article&id=80&Itemid=116[2] Koornneef, J., Ramírez, A., Turkenburg, W., &Faaij, A. “The environmental impact and risk
assessment of CO 2 capture, transport andstorage–an evaluation of the knowledge base.”

347

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THE DESIGN OF AN ALTERNATIVE ENERGY DATABASE IN
THAILAND
Manutchanok Jongprasithporn1,Supapat Phuangkaew2, Siravitch
Atipatha3, and Nantakrit Yodpijit4
1

Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology
Ladkrabang, Thailand
2
Center for Innovation in Human Factors Engineering and Ergonomics, Department of Industrial
Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok,
Thailand

ABSTRACTEnergy is a critical factor for the global economy and development. Fossil fuels (ie, coal, oil, and natural gas) are
expensive and linked to health problems. In Thailand, the management of strategic national energy plan is very
challenging, especially for alternative energy. Alternative energy is any energy resource that does not consume
fossil fuels. Recently, the Ministry of Energy in Thailand launched an Energy Efficiency Plan (EEP) 2015
indicating that 30% of total energy used in Thailand must come from alternative energy. As such, energy plans
should rely on informative energy data. The purpose of this research project is to design a database management
system for alternative energy in Thailand. The current design of the database management system focuses onseven resources of alternative energy: biomass, biogas, solar power, hydropower, wind, waste, and bio-fuel. Four
major user sectors of energy sources are determined for national EEP, including industry, transportation,
agriculture, and residential/commercial buildings. However, the use of energy sources for agriculture andtransportation (ground and water) are still unclear. Limitations and future work for this research project are also
discussed.
Keywords: Alternative energy, Database, Energy Efficiency Plan (EEP)INTRODUCTION

system.

Energy is an important factor that directly affects
all people, and fluctuations of energy prices can behigh. Therefore, people are interested in researching
and understanding energy deeply. Fuels used inenergy production are mostly fossil fuels such as oil,natural gas, and coal. Fossil fuels are recognized as
the main source of energy for electricity generation,
but these fuels tend to run out. Therefore, the idea ofsupplying an alternative energy sources has beentaken into considered. Alternative energy inThailand today is of high interest because the royal
Thai government announced a government policy touse more alternative energy: main energy 30:70 by
the year 2070.
Data from alternative energy in Thailand isstored in many departments/offices. Eachdepartment has related data from many missions, butdata of each department sometimes do not matchand finding the central alternative energy databasecan be hard. Therefore, this research aims to create asystem to manage alternative energy databases. The
central alternative energy database will be created bydata from related departments/offices. This researchalso presents a web service for users to modify orchange data in the central alternative energy data

METHODOLOGY
Database system
The database system consists of many
information structures that are used in a variety ofsystems, including a system where users canmanipulate data, such as adding, modifying, deleting
and retrieving information. A reliable database is the
key to reducing operation costs[1,2].
Relationship
Relationship refers to the relationship between
entities which can be divided into three types: [5]1.One-to-One Relationships (1: 1) represents a
relationship of information in an entity that is related
to information in another entity.
2.One-to-Many Relationships (1: M) represents
the relationship of data in one entity that is related tomultiple data in another entity.
3.Many-to-Many(M:M)
represents
therelationship of two entity group data.
Database management system348

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

6.
Management Information Systems [6] are widely
recognized in the globalization era as they facilitate
the rapid, efficient and effective business process.
One of the information systems that will assist indata management is the database management
system [7].The database management system defines
the data in the database and facilitates to record data
into the database. The database management system
also determines user access level.

7.
8.
9.

ResourcesandThe data from 9 ministries was collected tocreate an alternative energy database.
Data structure
The Thai energy sector has five key components.
The five key components are energy source, energy
requirement, regulation and relevant law, related
departments/offices, processed. This research set
uses the five key components as entity and defines
an attribute for each entity. The Entity Relationship
Diagram(ER Diagram) is used to explain structure
and relation of alternative energy database.
Components of ER Diagram are shown in table 1.

Establish energy database
The steps in this research to create an alternative
energy database are shown in Figure 1.

Study of RelatedInformation on alternative
EnergyMinistry of Natural
Environment
Ministry of Industry
Ministry of Interior
Ministry of Energy

Insufficient
data

Table1 Symbol of components in ER diagram
Components
SymbolEntityData structure

Attribute
Relationship

Relational Database
Management System(RDBMS)This research has set the Attribute for each entity inthis study as follows.

Not
appropriate

Establish Database

Fig. 1

Operation diagrams.

Study of Related Information on alternative Energy
Fig. 2This research is incorporation with the royal Thaigovernment ministries to identify all data that related
to alternative energy in Thailand. The ministries ofThailand participated in this research included:
1. Ministry of Defence
2. Ministry of Agriculture and cooperative
3. Ministry of Digital Economy and Society
4. Ministry of Commerce
5. Ministry of FinanceAttribute of energy requirement

Figure 2 shows attribute of energy requirement.
This entity includes seven attributes(Agriculture,
Service, Industry, Transportation, Government,
Household and Fishery).

349

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

Fig. 3Attribute of energy source

Alternative energy sources in Thailand are biofuel, hydro, biomass, solar, waste, wind and biogas
as shown in figure 3. As part of the processes, westudied the process of each department/office andfound that the main activates were setting up a board
and defining a host. Therefore, an attribute forprocesses entity was defined as set up board and hostas shown in figure 4.

Fig. 4

Fig. 5Attribute of related departments/offices

Fig. 6

Attribute of regulation and relevant law

Attribute of processes

Related departments/offices entities have various
departments. The related data from 9 ministries
were studied. The results found that related
departments/offices totaled 29 departments form 9
ministries and state enterprises. Therefore, thisresearch defined attribute as 2 major attributes(Government ministries and State enterprise).
Regulation and relevant law are a difficult part ofthis alternative energy database because this entity
has lots of details. Moreover, each department has aregulation and relevant law, each relevant law wasstudied .Moreover, we also compiled an alternative
energy database. There entity of regulation andrelevant law in this study has two attribute as shownin figure 6.

Relational Database Management System (RDBMS)
The data was collected by the same database insteps 1 and 2. In this step, the relational databasemanagement system (RDBMS) was created [8]. The
entity relationship diagram (ER Diagram) was used
to design the relationship of each entity. Figure 7
shows the relationship between energy requirement
and related departments/offices entity. The
relationship of entities is one to many relationships(1: M).

350

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

Fig. 7

Relationship of entities

Establish Databaseas the primary key in the database management.
The alternative energy database was then created by
dividing this into five groups (alternative energy
source, regulation and relevant law, process, energy
demand and related departments/offices).Details of
the alternative energy database are shown in the ER
Diagram in Figure 8.

The operation in Steps 1-3 is complicatedbecause the data linkage cannot be done directly [9].
Therefore, a registration number is used to identify
data. Moreover, this defines registration number for
all factories [10]. The registration number will be
used

Fig. 8

Entities Relationship Diagram

RESULTS

Alternative energy Database

The results of this research includes analternative energy database and networking for web
services.

This research collected data from every
entities/attributes form the ER diagram in Figure 8tocreate a central alternative energy database. The
351

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

central alternative energy data base collect data form
29

departments from 9 ministries. An example of thedata in the central alternative energy database isshown in figure 9.

Central alternative energy data base
Electricity capacity( kW)
Total electricity capacity
Space of landfill
Dams
Electricity uses
Director Name
Customer list
Importer / exporter list
Location of Waste disposal
Reservoir
Location of power plantFig. 9Customer’s location
Registered Capital
Geometry data
Business type
Quantity of garbage
The amount of waste entering thedisposal site (Incinerator)
The amount of waste entering thedisposal site
Etc.

Example data in energy data basethrough the web service as shown in figure 10. Users
can modify or change data in the central alternative
energy database according to the level of the user.
The level of user is defined by the admin of thecentral alternative energy data base.

Networking for web services
Networks from entities related in figure 8 werelinked to create the web services. Users of thecentral alternative energy data base come from 11
departments/offices. Users can log in to the database

Fig. 10 Web service network diagram.

352

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017of database operations on multicore servers.
Future Generation Computer Systems, 2017.
[3] Hernández, J., Gyuk, I., & Christensen, C.
“DOE global energy storage database—A
platform for large scale data analytics andsystem performance metrics.” In Power System
Technology (POWERCON), 2016 IEEE
International Conference on (pp. 1-6). IEEE.
[4] Haas, S., Arnold, O., Scholze, S., Höppner, S.,
Ellguth, G., Dixius, A., ... & Schiefer, S. “Adatabase accelerator for energy-efficient query
processing and optimization.” In Nordic
Circuits and Systems Conference (NORCAS),
2016 IEEE (pp. 1-5). IEEE.
[5] Amornsinlaphachai, P., & Deejring, K.. “THEPERFORMANCE OF UPDATING XML IN
TRADI-TIONAL DATABASES.” Nakhon
Ratchasima Rajabhat University ,Thailand.
[6] Peeraphatchara, C., & Thalang, S. P. N.
“Competitivetechnological
databasedevelopment project to support technology
transfer on internet: Thai cuisine from four
regions web database.” In 45. Kasetsart
University Annual Conference, Bangkok(Thailand), 30 Jan-2 Feb 2007.
[7] Pho, N., & Prakancharoen, S. “Accuracy
Comparison of Waveform Database Generator
Data Set Imputation Estimation Using
Structural Equation Modeling and Multiple
Regression Analysis.” Information Technology
Journal. 13, 2011, 33-39.
[8] Chutimaskul, W., & Chankham, S. “Distributed
Relational Database Management System on
PVM.” KMUTT Research and Development
Journal, 23(2), 2000, 47-58.
[9] Trumpy, E., & Manzella, A. “Geothopica andthe interactive analysis and visualization of the
updated Italian National Geothermal Database.”
International Journal of Applied Earth
Observation and Geoinformation, 54, 2017, 2837.
[10] McQueen, J., & Boss, R. W. “Sources ofmachine-readable cataloging and retrospective
conversion.” Library technology reports, 21(6),1985, 597-732.

CONCLUSIONSThis research has studied the alternative energy
situation in Thailand. Relevant data was collected
form 9 government ministries and concluded that the
5 core areas are: process, energy demand and related
departments/offices. Therefore, we focused on
studying in detail each core of data and set the coredata as the entities in the database, and also set thedetail in each core data as attribute. Then therelationship of each entity was created by the ER
diagram. This research established the central
alternative energy database by the data from
relationship of each entity. The central alternative
energy database connects to the databases fromvarious departments/offices, which is defined by aregistration number for each part of data. Therefore,
all databases will be matched. This research also
created a web service to access the central database.
The central alternative energy database wasconnected to 11 departments/offices. The users were
given the ability to edit, view, search and modify.
The ability of a user was defined by the central
admin. The result of this research was a databasewhich is always up to date and matches. In
conclusion, the central alternative energy database isan efficient method to manage energy in Thailand
especially for the country's alternative energy
efficiency plan (EEP).
ACKNOWLEDGEMENTS
Research project was conducted at the Center
for Innovation in Human Factors Engineering and
Ergonomics, Department of Industrial Engineering,
Faculty of Engineering, King Mongkut's Universityof Technology North Bangkok.
REFERENCES[1] Lin, M., Wierman, A., Andrew, L. L., &Thereska, E. “Dynamic right-sizing for powerproportional
data
centers.”
IEEE/ACM
Transactions on Networking (TON), 21(5),2013,pp.1378-1391.
[2] Zhou, Y., Taneja, S., Qin, X., Ku, W. S., &Zhang, J.EDOM: Improving energy efficiency

353

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

NUMERICAL INVESTIGATION OF 2D TRAPDOOR STABILITY
1

Jim Shiau1, Mohammad Mirza Hassan2
School of Civil Engineering and Surveying, University of Southern Queensland, Australia

ABSTRACTThis paper investigates numerically the stability of trapdoor problem that is similar to a 2D sinkhole stability
analysis. The shear strength reduction technique in the finite difference element software FLAC is used todetermine factors of safety. The FLAC results are then verified by comparing with rigorous upper and lower
bound limit analysis results using OPTUM G2. Numerical results presented are for various depth ratios indimensionless forms to establish design charts like in Taylor’s slope stability chart. Examples are provided todemonstrate the use of the design chart and table.
Keywords: Sinkhole, Trapdoor, Stability, Strength Reduction Method, FLAC, OPTUM G2, Design Chartthe centrifuge modelling and developed failureenvelope design chart. Broms and Bennermark [7],through the laboratory experiments and the field datacollections, proposed the stability number (N). They
concluded that the opening will be unstable theoverburden pressure γH is greater than 6~8 times ofundrained shear strength of the soil.
Shiau [8] investigated the cause of sinkhole
formation and used strength reduction method toanalyze factor of safety and failure mechanism of
sinkholes by making use of different depth ratios.
Besides, both numerical and physical modelling
have also been introduced recently in geotechnicaleducation by [15-16]. Tao [9] in laboratory
investigated the formation of sinkhole and verified
his work by simulating in FLAC. The importance ofpressure changes in confining layer for sinkhole
prediction were discussed by the authors. Yang [10]developed a simplify method to evaluate the stabilityof the soil in karst and stated that the stability should
evaluated with two different conditions. Augarde[11] used finite element limit analysis to obtain theupper bond and lower bond values for loadingparameters. Shiau [12-14] extensively studied thepressure relaxation method and created automatedmesh generation system using FISH programing
language in FLAC [22-23].
Many researches were conducted on formationand prediction of sinkholes. However, most of thoseresearches are limited to investigation on the causeof formation, failure mechanism or limited to
specific geological site, yet there is little researchdone in producing the dimensionless design chart,
which assist the engineers in field to evaluate thestability of the ground and decide whether it is safe
regardless of the geographical location. This paper
will investigate the stability of the sinkhole by using
strength reduction method and presenting the resultsin form of Factor of Safety. Design charts will bepresented dimensionally, just like in Tylor’s slope

INTRODUCTION
Sinkholes are as old as the age of the earth. The
size of sinkholes can be as large as 100 meter or as
small as meter or less. Whether it is big or small, it
can be deadly and destructive [1]. Office of theinternal auditor reported that the program fund in
Sinkhole Managed Repair Program (SMRP) has
increased from $50 million in 2015 to $250 Million
in 2016, and this budget is only for in the UnitedStates [2].
Sinkholes can be natural or cause by humanactivities. Natural sinkholes can form by rise of theundergroundwater
surface,decrease
theunderground water piezometric level in the rocks
below the surface or frequent fluctuation of thewater table beneath. Human activities such as
mining and drilling can also expedite the formationof the sinkholes [3].

Fig.1 Sinkhole formation [4]It is well known that sinkhole failure is anextremely difficult situation to investigate, such as
the causes of the failure and the actual depth of it [5].
Therefore, researcher are working on the models tosimulate, predict and estimate the stability of thesinkholes.
Abdulla [6] tested stability of 51 model through354

stability design chart [19]. This will simplify the
problem and assist the engineers in making decision
with required parameters in the field.

in slope stability problem; however it has rarely used
to analysis the sinkhole stability. OPTUM G2 hasability to refine the mesh size by using the mesh
adaptively feature or by increase the number of
element in mesh to improve the accuracy of theupper bond and lower bound results.

PROBLEM DEFINITION
Figure 2 shows a schematic diagram of the 2D
sinkhole problem and its associated failure surface.
For simplicity, this study assumes that no surcharge
load acting on the soil surface and the problem canbe stated as a Greenfield unsupported condition as in[15].

FLAC MODELLING
Figure 3 shows a typical half mesh adopted for
all analyses in this paper using FLAC. To allow the
downward movement of soil particles under
overburden pressure (γH), both left and right sideboundaries of the model have been restrained in X
direction. This is particular important for thesymmetrical boundary condition for the left sideboundary.
In lower boundary except where the trapdoor
opening is, both vertical and horizontal movement ofsoil particles are prevented. No surcharge has been
considered in this paper, and therefore failure occurs
only due to overburden pressure.

σ s =0 , No Surcharge
Overburden
PressureFix (x)Fix (x)Unit weight (γ)in kN/m
Su =Undrained Shear

Height(H)

Potenitial
Slip Surface

SymmetricalLine
Fix (x,y)Half Trapdoor
width (H/2)

Fig.2 An idealized sinkhole problem.
The soil structure is modelled as uniform Tresca
Material, which behaves the same as the MoherColumb material when the soil friction angle is zero.
For this material, the shear strength reduction factor
can be represented by a factor of safety that is theratio of ultimate undrained shear strength (Su) overthe undrained shear strength at collapse (Sc). This isshown in equation (1).
𝑺

𝑭𝒐𝑺 = 𝑺𝒖

Fig.3 Typical half mesh and boundary condition
A FISH script has been developed to generate themesh in FLAC environment and solve for thesolution automatically. Using the script, parametricstudies can be conducted efficiently and effectively
with quick change of material input.
To solve the problem numerically, shear strength
reduction method in finite different program FLAC
has implemented to obtain the factor of safety forundrained clay soil. Using this method, the criticalslip failure surface will be located automatically
based on the stress failure in finite elements,
therefore shear strength failure is appropriate to be
used to assist in solving the stability problem [21].
The finite difference FOS results obtained from
FLAC are compared with the rigorous lower boundand upper bond from OPTUM G2.

(1)

𝒄

In Figure 2, W indicates the width of cavity
opening whilst the depth of sinkhole is denoted by H.
The depth ratio is represented by (H/W) and thestrength ratio (SR) of the soil can be defined as(Su/γW). The solutions of factor of safety is therefore
a function of the depth ratio and the soil strength
ratio.
𝑯𝑺𝒖
𝑭𝒐𝑺 = 𝒇 (𝑾 , 𝜸𝑾)

(2)

In addition to the FLAC program, OPTUM G2[20] will be utilized to validate the obtained results.
The finite element program FLAC and the OPTUM
G2 both has built-in shear strength reduction method
to determine the FOS. This technique is widely used

RESULTS AND DISCUSSION
Based on the previous problem definition, thedepth ratio H/W used in this study ranges from 1 to
10 and the strength ratio Su/w used in this paper355

(Su)/(WFOS)

ranges from 0.2 to 2. These parameters will covermost practical cases that practical engineers mightface in field.
H/W=1
H/W=2
H/W=3
H/W=4
H/W=5
H/W=6
H/W=7
H/W=8
H/W=9
H/W=10

4.0
3.5

2.5
2.0

4.5

1.5

4.0

1.0

3.5

0.5

3.0

0.0
0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Su/W
Su/W
Su/W
Su/W
Su/W
Su/W

2.5

Su/W

0.5
0.0
0

1

2

3

4

5

6

7

8

9

10

11

H/W

Fig.6 FOS vs. depth ratio
For a given strength ratio Su/w, Figure 6 showsthat the FOS value decreases nonlinearly as thedepth ratio (H/W) increases. This figure highlights
the effect of over burden pressure (γH) in thesecohesive cases. Given the same strength ratio Su/w,
the larger the depth ratio, the larger (γH) it is. Thereis very little arch support for these cohesive cases.
This finding is in agreement with Shiau’s [22-23],
showing the same effect on FOS.
Figure 7 shows a typical output plot of shear
strain rate (ssr) for H/W=3 and SR= Su/γW=1. The
shear strain rate plot is used to display the possible
collapse mechanism. It represents the zone of plastic
deformation for the soil particle of such a perfectly
elastic-plastic soil model where the actual strain
cannot be determined.

2.0

Failure Envelope FOS=1
1.8
1.6

Su/W

Su/W

1.0

Figure 4 shows the relationship between factor ofsaftey (FOS) and strenght ratio ratio Su/W forvarious depth ratios H/W, ranging from 1 to 10. It
can be seen that the FOS increases linearly as thestrength ratio increases. Note that the rates ofincrease are different for various H/W ratios. The
gradient is much small for the deep case H/W=10
than the shallow case H/W=1. By increasing the soil
strength for deep cases is not as effective as that for(Su)/(W FOS)=0.0922(H/W)+0.3458

1.0

FOS>1

0.8

0.34581.5

Fig.4 FOS vs shear strength ratio

1.2

+

2.0

Su/W

1.4

(H/W)

5.0

FOS

FOS

3.0

0.0922This failure envelope can be represented byequation (3) for practical design purpose. It can beused to determine the critical depth H, as well as tocalculate the critical strength ratio or where the FOS
is 1.

5.0
4.5

=

(3)

FOS<1
0.6
0.4
0.2
0.0
0

1

2

3

4

5

6

7

8

9

10

11

H/W

shallow cases.
Fig.5 Critical strength ratio – failure envelope
Owing to the linear response in Figure 4, thecritical strength ratio (Su)/(WFOS) is shown in
Figure 5 for depth ratios of 1-10. This figure
highlights the failure envelope for FOS of 1. When
FOS=1, it reduces to a chart similar to Taylor’s
slope stability design chart where (Su)/(WFOS) =(Su)/(W). The values below the failure envelope
indicates an unsafe design where FOS <1, whilst
values above the failure envelope categorizes thestable condition which has FOS >1.

Fig.7 Shear strain rate plot for H/W=3 and SR=1
Figure 8 shows a typical vector plot showing thevelocity field. The chosen case is for a depth ratio of3, where the shear strength ratio Su/γW=1.
356

Velocity vector indicates the movement of soil
particles. Vector path shows the direction as well as
the magnitude of particle movements. This velocity
plot can also be used to determine the overall failure
mechanism.

8
9
10

0.878
0.811
0.753

0.906
0.838
0.779

0.92
0.85
0.79

RESULTS VERIFICATION
To improve the confidence in FLAC results, acomparison is made with those obtained fromOPTUM G2 [20] using lower and upper bondanalyses.
Table 1 shows the summarized FOS values
obtained from FLAC and rigorous upper bond andlower bond for the case Su/γW = 1 and H/W= 1 to 10.
Comparison of the two methods reveals that FLAC
produces results that are consistently 3% to 4%
higher than upper bound. These results are also
shown graphically in Figure 10 for better
observation of the comparison trend.
Fig.8 Velocity vector plot for H/W=3 and SR =1
2.2

FLAC
G2 LB
G2 UB

2.0
1.8
1.6
1.4

FOS

1.2
1.0
0.8
0.6
0.4
0.2
0.0
0

1

2

3

4

5

6

7

8

9

10

11

H/W

Fig.9 Plasticity indicator plot for H/W=3 and SR=1

Fig.10 Comparison of FOS value for FLAC and G2
UB and LB

Figure.9 presents a typical plot for plasticity
indicators. This plot is for a depth ratio H/W of 3 andSu/γW=1. The area shown in (*) presents the yieldzones of soil particles, where the area shown in (x)possessed plasticity in the past but is currently in anelastic state. This typical plot can also be used todetermine the likely zones of failure and therefore
can be useful for engineering design.

This comparison has successfully validated theusefulness of FLAC results, and design charts cantherefore be produced with high level of confidence
in the next section.
STABILITY DESIGN CHART

Table.1 FOS results for FLAC, G2 UB and G2 LB(Strength Ratio; SR=1)
H/W

G2 LB

G2 UB

FLAC

1
2
3
4

1.92
1.8
1.546
1.341

1.976
1.846
1.587
1.378

2.05
1.89
1.64
1.41

5
6
7

1.187
1.061
0.964

1.214
1.088
0.988

1.24
1.11
1.01

In addition to Figures 4-6 where the FOS can be
estimated with input values of Su/γW and H/W, adesign chart in form of the contour map is also
provided in Figure 11. This chart can be best
demonstrated practicality through the number ofexamples.
Example of using the stability chart
Example 1. To determine the factor of safety
The following data has been provided togeotechnical engineer: H=10m, W=2m, γ= 18
KN/m3 and Su=50 kPa. It is required from the357

engineer to determine the factor of safety for such agiven system.

with rigorous lower and upper bond using OPTUM
G2. The comparison confirmed the accuracy of thesesolutions and it greatly enhanced the confidence inusing these results.
Both the design charts and equation for the
failure envelope were presented to estimate thestability of sinkholes. Examples were illustrated on
how to use these design charts and equation. It is
recommended that future work be conducted by
implementing three dimension models for better
understanding of failure mechanism. Other further
work such as investigation of surface failure extent
and the effect of surcharge loading would improve
the study.

Given H/W=5, Su/γW = 1.39, Figure 11
returns approximately a value of FOS of
1.74. Using Figure 4, the value is 1.73.
2. Using equation 3, a value of FOS=1.72 is
obtained.
Actual computer analysis of this case returns the
FOS of 1.76. Based on the results of the above
analysis, this trapdoor is potentially stable and nofurther ground improvement requires.
1.

2.0
3.8

1.8

3.2

2.2

2.0

2.8
3.6 3.4

REFERENCES

1.6

2.6

1.6

1.4

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[10] Yang, M. Z. & Drumm, E. C. (2002) Stability
evaluation for the siting of municipal landfills inkarst. Engineering Geology, 65, 185-195

3.0

Su/W

1.4

1.2

1.2

2.4

0.96

1.0
1.8

0.8
0.76

0.6
0.4

0.36

0.56

0.2
1

2

3

4

5

6

7

8

9

10

H/W
Fig.11 Stability design chart
Example 2. Evaluation of the sinkhole depthCouncil requires further investigation after heavy
rain to estimate the depth of a sinkhole. The
following properties are available from previous
investigation: Su= 54 kPa, W=3m, γ= 18 KN/m3 and
FOS = 1.5.
Using Su/γW =1 and FOS=1.5, equation 3 gives
the H/W=3.48, and the resulting depth H = 3.48x 3 =10.44 m.
Example 3. Estimation of Undrained Shear Strength
Geotechnical engineer is required to estimate theundrained shear strength of the soil for a sinkhole.
The following data are available: FOS=1, γ= 18
KN/m3, H=18m and W=3m.
1. Using equation 3 where FOS=1, the criticalstrength ratio (Su)/(WFOS) is 0.622.
2. Undrained shear strength Su can then be
calculated as 33.61 kPa.
CONCLUSION
The shear strength reduction method was usedin this paper to evaluate the stability of trapdoors.
The FOS results produced in FLAC were compared358

[11] Augarde, C. E., Lymin, A. V. & Sloan, S. W.
(2003). Prediction of undrained sinkholecollapse. Journal of Geotechnical andGeoenvironmental Engineering, 129, 197-205.
[12] Shiau, J. S. and Kemp R. J. (2013). Developing
a numerical model for the stability design oftunnel heading. Third International Conference
on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013.
[13] Shiau, J. S., Sams, M. S., Zhang, J., & Kemp, R.
J. (2014). Settlement analyses of undergroundcircular tunneling in soft clay. In GeotechnicalAspects of Underground Construction in SoftGround, Seoul, 347-352.
[14] Shiau, J. S., Sams, M. S., & Kemp, R. J. (2014).
Physical modelling and PIV analyses of anunderground tunnel heading. In GeotechnicalAspects of Underground Construction in SoftGround, Seoul, 61-66.
[15] Shiau, J. S. and Buttling, S. and Sams, M.
(2016) Developing a project based learningassignment for geotechnical engineering.
Electronic Journal of Geotechnical Engineering,20(18): 10113-10121.
[16] Shiau, J. S., Sams, M. S., & Lamb B. (2016).
Introducing Advanced Topics in Postgraduate
Geotechnical Engineering Education – Tunnel

Modelling. International Journal of Geomate,10(1): 1698-1705.
[17] Bishop, AW (1955), ‘The use of slip circle inthe stability analysis of slopes’, Geotechnique,vol. 5(1), pp. 7-17.
[18] FLAC (2003), Fast Lagrangian Analysis ofContinua, Version 5.0, Itasca Consulting Group,
Minneapolis, Minnesota, USA.
[19] Tylor, D.W., (1937). Stability of earth slopes, J
Boston Soc Civil Eng, XXIV (3) (1937), pp.
337-386[20] OptumG2 (2016), Optum Computational
Engineering, Standard Version, Newcastle,
Australia.
[21] Matsui, T. & San, K.-C. 1992. Finite element
slope stability analysis by shear strength
reduction technique. Soils and foundations, 32,
59-70.
[22] Shiau, J, Sams, M & Chen, J (2016) Stability
design charts for unsupported wide rectangulartunnels. Electronic Journal of GeotechnicalEngineering, 21(1): 139-150.
[23] Shiau, J, Sams, M & Chen, J (2016) Stability
charts for a tall tunnel in undrained
clay. Electronic Journal of GeotechnicalEngineering, International Journal of Geomate,10(2), Japan: 1764-1769.

359

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

INSTALLATION CONSTRAINTS OF SUCTION ASSISTEDFOUNDATIONS AND ANCHORS FOR OFFSHORE ENERGYDEVELOPMENT
Kingsley Osezua Akeme1, Alireza Rezagholilou2 and Meysam Banimahd3
Petroleum Engineering Department, Curtin University, Australia; 3Adjunct Research Fellow, University ofWestern Australia, Australia.

1,2

ABSTRACTThe application of suction caissons have been increased over the last two decades for offshore energy
developments. Their installation challenges in different seabed types affect their execution process and load
bearing capacity. Hence, the identification of these challenges and understanding of their root causes are highly
important. As such, this paper aims to review the recorded installation constraints due to different seabed
conditions, discuss the various factors related to each of these constraints, and finally provide some suggestions
to rectify each constraints and/or its relevant factors. To do so, the approach is to evaluate the geological(geophysical and geotechnical) conditions in multiple case studies and analyze the stability of suction caisson
installation in different soil types. Results show that some factors such as: : buckling, plug heave, soil piping,bottom resistance failure and high penetration resistance can exist in both homogeneous and heterogeneous
seabed conditions, and the uncertainties of soil parameters or behavior, add more complexities into the above
factors. Therefore, a good understanding of the seabed conditions and soil parameters before and during
installation, as well as constant monitoring of the induced suction created with respect to the penetration depth isessential to mitigate the likely issues.

anchorage support (M. N. Tran 2007). Some
examples of other suction assisted foundation andanchors include: suction anchor, suction pile,
bucket foundation, skirted foundation and skirt
piles etc.

INTRODUCTION
Definition
Suction assisted caissons have been defined aslarge cylindrical steel structures of 5- 7m diameter
opened at the base and closed by a lid at the top.
The top contains a “valve controlled vent” whichallows the escape of water from the caisson during
installation (T. I. Tjelta 2001; Aubeny, Murf andMoon 2001; El-Sherbiny 2005). However in moredetail, they are defined as foundation structures thatare installed as a result of a differential pressure
created within the caisson compartment through theapplication of a pump attached to the caisson top
which reduces the internal pressure within the
caisson compartment as shown in Fig 1.
Suction caissons are classified into two
categories based on their application and function.
By application, they are classified as: (1)Compression caisson foundations when they areused in shallow water applications as foundation
supports, and as (2) Suction anchors when they areused in deep water applications as mooring andanchoring supports (Cao, et al. 2002; Tran, Aireyand Randolph 2005).
In terms of their function, they are classified
either as (1) an integrated foundation structure
when they are attached to the base of a foundation
structure e.g the Gullfak C platform, or as (2) astandalone structure when used for mooring and

Fig 1 A Cluster of suction anchors (Adapted from
M. N. Tran 2007)
Installation Procedure
In general, suction assisted foundations and anchors
have the same installation principle in which asuction induced force is required for theirpenetration into the seabed. Also, their installation
process occurs in two-stages. In the first stage, they
penetrate into the seabed by virtue of their selfweight. As the process occurs, the water displaced
inside the caisson is evacuated through an open
vent. The velocity of water that can be discharged
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

through the open vent with respect to the overpressure within the suction caisson is given by thefollowing equation:
V=C

2𝑃

√𝜌

𝑆𝜔

when

an

Orificeiswhere the water within the caisson begins tovaporise. This maximum value is equal to sum of
the atmospheric pressure and hydrostatic pressure
outside the caisson. Once the design depth has beenreached, the valve at the top is closed and a passive
suction is generated within the caisson. Thispassive suction increases the holding capacity (pullout resistance) of the caisson by engaging negative
pore pressure from the soil plug inside and at thebottom of the caisson (Cao, et al. 2002; Sukumaran
1999; Cao, et al. 2003; Sparrevik 2002).
Generally, the allowable suction for caisson
penetration before plug failure (Reverse end
bearing failure) occurs can be calculated using thefollowing equation:

used

(1)
V= √𝜌

2𝑃
𝑆𝜔 ∑𝐾𝑖when a piping system (valve) is used(2)
Where V= steady velocity of water flow, C=
Coefficient of discharge (C=0.61 for sharp edged
orifice surface and C= for sharp edged orificesurface with short tube), P= over pressure in thesuction caisson, 𝜌𝑆𝜔 = sea water density, and 𝐾𝑖 =Resistance coefficient for the piping system (∑𝐾𝑖 =1.7 - 1.8 for a 2 ft or 3 ft diameter butterfly valve
system).
However, suction caisson would stop
penetrating under its own weight when the soil
resistance, including external and internal frictional
resistances and tip resistance is equal to the weightof the suction caisson (Huang, Cao and Audibert
2003)
An important phenomenon in this stage is theformation of a seal between the seabed surface andthe caisson. The importance of the seal is to preventthe formation of localized piping and loss ofsuction during penetration. It is thus important thatthe seal formed must be sufficient in order toguarantee suction assisted penetration. However, if
an insufficient seal is formed this would result to
failure of the entire installation process (Cao, et al.
2002; Sukumaran 1999).
The second stage consist of the later part of thepenetration process of arriving at the design depth.
This is achieved by the application of an additional
installation force which is provided in the form ofan under pressure or suction created by pumping
water out of the caisson through a “submersiblepump” attached to the top of the caisson (Cao, et al.
2002; Sukumaran 1999; Housby and Byrne 2005)
as shown in Fig 2. The suction generated, is thetotal pressure difference between the caisson
internal vacuum pressure and the externalhydrostatic pressure. If the pressure difference
created is relatively higher than the externalhydrostatic pressure, the suction caissons may
buckle during installation. Also, an excessive underpressure or suction created within the caissoncompartment could result in the upward movementof the internal soil within the caisson which could
lead to plug failure. Therefore, the amount ofsuction available for penetration ranges from aminimum value when the caisson internal pressure
is at zero absolute pressure to a maximum value(allowable suction) which corresponds to the point

𝑃𝑎𝑙𝑙 = 𝐹𝑖𝑛
(3)

/

𝐴𝑖𝑛

+

𝑄𝑢

/

(𝐴𝑖𝑛

FS)

Where 𝑃𝑎𝑙𝑙 = allowable suction, 𝐹𝑖𝑛 = internal
caisson wall frictional resistance, 𝐴𝑖𝑛 = Caisson
internal crossectional area, 𝑄𝑢 = reverse end
bearing over the all soil plug area at the caisson tip,
FS = factor of safety (Huang, Cao and Audibert
2003).
Once the suction assisted foundation has been
installed, a set up time is allowed to enable thesurrounding soil regain some of its strength lost
during installation before any load attachment isdone. During this period the caisson remains
unloaded. Set up time is mostly observed duringmooring application (Tran, Airey and Randolph2005).

Fig 2 Suction installation process (Adapted fromTran MN 2007)
METHODOLOGY
The
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approachadoptedinachievingtheSEE - USQ, Brisbane, Australia, Nov.13-16, 2017

objectives of this paper is carried out in two parts.
The first part is a review of the geological(geotechnical and geophysical) survey conducted
before and during installation as well as thestability assessment of suction caisson during
installation. While the second part is a comparative
analysis of the installation issues of suction assisted
foundations and anchors obtained from literature
reviews and over 50 case study field reports

more permeable the soil is, the faster the loss ofsuction under sustained tension loads.
The
permeability of the soil is very important especiallyin sand during installation so as to avoid soil piping
and the possibility of having a bottom resistance
failure (Huang, Cao and Audibert 2003).
Soil strength profile
This comprises of the drained and undrained
shear strength profile of the soil from the mud line
down to the seabed. This is very important to know
especially in homogeneous clay soils and in layered
structured soils in order to avoid plug heave andpunch through during penetration (Huang, Cao and
Audibert 2003).

Geological Properties of Soil That Affects the
Installation and Load Bearing Capacity ofSuction Caissons
Prior to the installation of suction caissons, aproper site investigation is conducted in order toselect the right location for installation, and also toestablish the geotechnical installation parameters
needed for a successful installation campaign. To
this end, a geotechnical survey involving in-situ
and laboratory tests is conducted in order to obtain
information about the soil properties such as: soil
index properties, in-situ stresses and stress history,
the soil shear strength profile (undrained andundrained conditions) etc.
The following geotechnical soil attributes
below are considered very important during the
installation of suction caissons at the design stage
in order to accurately predict the likely installation
issues that may be encountered during installation.
These soil attributes are:Seabed topographical irregularities
The uneven nature of the seabed could cause
problem during installation especially for suction
caissons in cluster form where cracks are formed in
the caisson walls during penetration. To overcome
this challenge, an optimal levelling procedure of thesuction caisson should be done immediately after
self-weight penetration process but before thesuction assisted penetration process begins. The
levelling of the uneven section of the caisson
should be carried out in small monitored steps (T. I.
Tjelta 2001; Sukumaran 1999; Sharma 2005)
Penetration resistanceSet up/consolidation effects

This is a measure of the soil shear strength
conditions (drained and undrained conditions). The
soil shear strength increases gradually with depth
depending on the soil density profile. The soil
penetration resistance is the sum total of thepenetration resistance experienced during selfweight and suction assisted penetration(s). It
comprise of the total internal and external caisson
wall resistance and the caisson tip resistancealtogether.
The following Eq. (4) – (7) shows therelationship between penetration resistance and thepenetration depth that could be achieved during
installation in clay and sand soils.

This is a phenomenon due to the timely
dissipation of excess pore water from the soil
particles which results to an increase in the soil
effective stress. The time of soil consolidation, need
to be accurately predicted and monitored during
installation in order to understand the soil strength
conditions during penetration so as to regulate therate at which suction is applied in order to avoid apunch through or plug failure during installation.
For example, the soil strength gained during selfweight penetration takes much longer time than thesoil strength gained during suction assisted
penetration for different soil types. Also, the rate ofsoil strengths gained by soil particles outside thecaisson wall is faster when compared to the soil
strength gained by soil particles inside the caisson
wall due to the differences in their drainage paths(Sukumaran 1999; Sharma 2005).

For self-weight penetration in clay soil
𝑉 ′ = h 𝛼𝑜 𝑆𝑢1 (𝜋𝐷𝑜 ) + h 𝛼𝑖 𝑆𝑢1 (𝜋𝐷1 ) + (𝛾 ′ h +𝑆𝑢2 𝑁𝑐 )
(
𝜋𝐷𝑡)
(4)

Soil permeability profile

For suction assisted penetration in clay soil before
reverse bearing failure (plug failure) occurs

The permeability of the subsurface soil anddrainage paths determines the magnitude of suction
the caisson can accommodate and sustain. The

𝜋𝐷2

𝐷2

𝑉 ′ + 𝑁𝑐∗ 𝑆𝑢2 4 𝑖 = h 𝛼𝑜 𝑆𝑢1 (𝜋𝐷𝑜 ) [1 + (𝐷2 −1𝐷2 )] (𝛾 ′ h
𝑚

362

𝑜

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

𝑆𝑢2 𝑁𝑐

+
(5)

)

(

𝜋𝐷𝑡)

resistance (soil strength) of the soil around thecaisson where it occur. This could lead to punchthrough failure during penetration (Senders,Randolph and Gaudin 2007; Senders and Randolph2009).

For self-weight penetration in sand considering theeffect of stress enhancement along the caisson walls
and tip

Soil stiffness′ℎ∫𝑜 𝜎 ′ 𝑣𝑜 dz(𝐾𝑡𝑎𝑛𝛿 )0 (𝜋𝐷0 ) +𝑉 =′(𝐾𝑡𝑎𝑛𝛿 )𝑖 (𝜋𝐷𝑖 ) + 𝜎𝑒𝑛𝑑
(𝜋𝐷𝑡)ℎ∫𝑜 𝜎 ′ 𝑣1 dz

This parameter is used to analyze the horizontal
displacement of suction caisson under loading
conditions. Fig 3, demonstrates how large
horizontal deflections are generated which alters
the stress state of the soils around the caisson
thereby leading to the formation of soil gaps aroundthe back of the caisson. The gap created around thecaisson could become a channel path for the flow ofseawater into the caisson which could result into
soil piping or boiling failure. Therefore, predicting
accurately the caisson lateral displacement and theassociated moment distribution along the caisson
length is a critical factor in determining the suction
caisson load bearing capacity (Huang, Cao and
Audibert 2003).

(6)

For suction assisted penetration in sand before
reverse bearing failure (plug failure) occurs whileconsidering the effect of stress enhancement along
the caisson walls and tip
𝑉′ + S (
ℎ

𝜋𝐷𝑖2
4

ℎ

) = ∫𝑜 𝜎 ′ 𝑣𝑜 dz (𝐾𝑡𝑎𝑛𝛿 )0 (𝜋𝐷𝑜 ) +∫𝑜 𝜎 ′ 𝑣1 dz (𝐾𝑡𝑎𝑛𝛿 )𝑖 (𝜋𝐷𝑖 ) + (𝜎 ′ 𝑣1 𝑁𝑞 + 𝛾 ′ 𝑡𝑁𝛾 )
(
𝜋𝐷𝑡)
(7)
Where 𝑉 ′ = Effective vertical load, h= installed
depth of caisson, 𝛼𝑜 = adhesion factor on outside
caisson wall, 𝛼𝑖 = adhesion factor inside of caisson
wall, 𝑆𝑢1 = average shear strength over depth ofskirt, 𝑆𝑢2 = shear strength at caisson skirt tip, 𝐷𝑜 =caisson diameter outside, 𝐷𝑖 = caisson diameter
inside, D = caisson diameter, t= caisson wall
thickness, 𝑁𝑐 = Bearing capacity factor (cohesion),
𝜋 = 22/7, 𝑁𝑐∗ = Bearing capacity failure factor, 𝛾 ′ =effective unit weight of soil, 𝐷𝑚 = caisson diameteras a result of enhanced stress, k = factor relating
vertical stress to horizontal stress, 𝜎 ′ 𝑣𝑜 = effective
vertical stress outside the caisson, 𝜎 ′ 𝑣1 = effective′
vertical stress inside the caisson, 𝜎𝑒𝑛𝑑
= effective
vertical stress at the caisson tip, 𝛿 = interface
friction angle, s = suction within the caisson withrespect to the ambient seabed water pressure, 𝑁𝑞 =Bearing capacity factor ( over burden), 𝑁𝛾 =Bearing capacity factor ( self-weight) (Houlsby andByrne 2004).

Fig 3 Failure mechanism and padeye optimization(Adapted from Tran MN 2007)
Load Bearing Capacity Factors
From the review of literatures and practicalresearch works, some key factors that could affectthe load bearing capacity of suction caisson wereidentified. These factors include:

Soil sensitivity
This refers to the soil- stress conditions duringpenetration. It is very important during suction
caisson installation. The sensitivity of the soil iscritical in predicting the self-weight penetration
depth of the caisson; and also in estimating thecaisson’s pull-out capacity immediately after
installation (Huang, Cao and Audibert 2003).

Loading condition
Suction caissons are subjected to vertical,
horizontal and moment loads during installation
which may affect their load bearing capacity. These
loads have different loading duration which
produces different drainage conditions. Thus theyrequire continuous monitoring of the load patterns
during installation especially the hydrodynamic
horizontal and moment loads (Huang, Cao and
Audibert 2003).

Set down scour
This is an uneven seabed condition which could
likely occur very rapidly as the caisson approaches
the seabed during installation. During self-weightpenetration, set down scour decreases the soil
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Suction caisson geometry- (Aspect ratio)
Aspect ratio (L/D) is the limiting factor for the
maximum penetration depth during installation(Sparrevik 2002). Suction caissons with high aspectratios may be prevented from reaching the design
penetration depth during installation when failuresuch as plug heave or buckling occurs. Another areaof concern is the retrieval process where suction
caissons with high aspect ratios are difficult toretrieve. It is therefore very important that during
the installation process, the soil conditions aremonitored and the rate of suction application iscontrolled (T. I. Tjelta 2001).
Table 1 below shows the aspect ratios for
specific foundations systems and anchors withrespect to the water depth, while Table 2 shows therange of Aspect ratios to be applied in different
seabed locations as analyzed from the review ofover 50 case study field reports
Table 1 Suction caissons applications vs aspectratios from case studies reviewed from 1958 – 2014
(M.N Tran 2007, T.I Tjelta 2001)
Foundation
SystemAspectRatio

Foundation

0.3
1.7

Anchoring

0.71 5.3

20 1800

Mooring

1.4
5.6

30 1920

-

-

Water
Depth
(m)
25 220Type of
SuctionCaissonSkirt
foundation,skirt
pile andbucketfoundation
SuctionAnchorsandSuctionPile
SuctionAnchorsandSuctionPile*= Not clearly statedPlatform

Mooring/chain line attachment point (padeye)This is a very critical aspect during the
installation of suction caissons when they are used
as mooring or anchorage support. A mooring
system under tension loads from a floating structuretransfer the tension loads to the suction caisson via
steel chains attached to the padeye. The padeyes arelocated along the caisson wall and they occupy
about 5 to 10% or more of the caisson length.
During installation, the padeyes alongside with thesteel chain creates a groove in the soil as the
suction caisson penetrates deeper into the soil. The
groove created could also be a drainage path forsoil piping failure to occur.
After the design penetration depth has beenreached, the steel chain assumes the shape of areverse catenary as a result of: (1) the tension
loading on the steel chain, (2) the soil bearing
resistance, (3) the frictional resistance along theembedded chain length, (4) the chain angle at the
mud line, and (5) the chain weight duringpenetration.
To ensure that there is no rotational movementof the suction caisson during ultimate loading
conditions, the mooring lines or chains should be
attached to the padeye at the optimal position. Thisis important because, a larger amount of theultimate load (weight of the floating platform +environmental loads) is transferred in the lateral
direction to the caisson. This ensures that thecaisson is operating at full capacity. However, if
they are attached below or above the optimum load
attachment point, the caisson will be operating at
low capacity. This is because, more of the

Fixed

Floaters

Floaters

Table 2 Aspect ratio Vs seabed location from casestudies reviewed from 1958 – 2014 (M.N Tran
2007, T.I Tjelta 2001)

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

foundation loads will be transferred in the verticaldirection resulting in the vertical and rotational
movements of the suction caisson. This would
cause the caisson to buckle, or become unstable
which may eventually reduce its load bearing
capacity as shown in Fig 4 (T. I. Tjelta 2001,
Sharma 2005, Randolph, et al. 1998), Huang, Caoand Audibert 2003).

failure modes experienced during their installation.
Zen (2016) derived the equations to calculate thelimiting suction for plug heave in clay as shown in“Eq. (1)” and also an equation to calculate thecritical suction for piping (boiling) in sand as
shown in “Eq. (2)”.
𝑃𝑠𝑐 = (𝑑 − 𝜕)𝛾 ′(9)𝑃𝑠𝑐 = (2𝑑 − 𝜕)𝛾𝜔 𝑖𝑐(10)Where Psc =Maximum suction or Plug heavesuction, d= Diameter of the suction caisson; 𝜕 =Displacement of the soil surface inside thefoundation; ic= Critical hydraulic gradient (mostlyic=1); 𝛾 ′ ’=Submerged unit weight of soil; and γw =unit weight of water (Zen and Hirasawa 2016).
Tilting/misalignment

Fig 4 Buckling of anchor piles under tension
loading (Adapted from Sharma 2005)

The risk of misalignment of the caisson during
installation could affect the load bearing capacity of
the caisson due to the uneven load distribution as aresult of the either the improper levelling of thecaissons after touch down, buckling of the caisson,or attaching the steel chain or mooring lines to the
padeye above or below the optimal position(Sharma 2005; Randolph and House 2002).
2005; Randolph and House 2002).

The “required suction” for penetration
This is the suction created within the caissonwhen water is pumped out through the pump during
the suction assisted penetration stage. The amountof suction that can be accommodated and sustained
during this process, greatly depends on thepermeability of the sub surface soil and drainage
paths. For example, highly permeable soils
experience a higher suction decrease compared toless permeable soils. Thus, the required suction to
install the caisson to the required depth is given byusing the limit equilibrium equation:

The type of installation used
The type of installation used (e.g. lift installedor launched installed) and their associated failuremodes (e.g. fatigue and corrosion etc.) could reduce
the stiffness and load bearing capacity of suction
caissons (T. I. Tjelta 2001).

𝑃𝑟𝑒𝑞 = (𝑅 − 𝑊𝑝 )/𝐴𝑖𝑛(8)

The pump requirement capacity

Where 𝑃𝑟𝑒𝑞 = required suction, R= soil resistance at
different penetration, 𝑊𝑝 = submerged suction
caisson weight, 𝐴𝑖𝑛 = suction caisson internal top
cross sectional area (Huang, Cao and Audibert
2003).
As a rule of thumb, the required suction for
penetration must be less than the maximum suction
for all soil conditions. For example in soft clay soils,
the ratio between the maximum suction and therequired suction should be equal to at least 1.3
before failure occurs, but when failure occurs, theratio should be greater than 1.3 (Sparrevik 2002).

Identifying the right pump capacity for suction
caisson installation in different soil types is very
important. The pump capacity is very important in
the installation process because it creates the
suction required for penetration and also thepenetration rate limiting factor.
Houlsby and Bryne (2004), proposed a formulafor calculating the pumping requirement for caisson
installation in clay refer to “Eq. (10)” and also insand refer to “Eq. (11)”𝑄=(11)The maximum allowable suction limit
This is a very critical aspect that is responsible
for the installation of suction caissons and the

𝑄=

365

𝜋𝐷𝑖2
4

𝜋𝐷𝑖2
4

𝑉

𝑆𝐾𝐷

𝑉+𝐹 𝛾

𝜔

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017(12)

Penetration Resistance, IS= Insufficient Sealing,
PTF= Plug Through Failure, L = Liquefaction

Where Q= Pump capacity or required flow rate; V=
Vertical penetration velocity; Di= Caisson internal
diameter; D= Caisson outer diameter; F=Dimensionless quantity that depends on h/D (where
h is the penetration depth), K is the sandpermeability; s= suction within the caisson withrespect to the ambient seabed water pressure, andγw = unit weight of water.
The above formula shows that the pumping
requirement for sand is greater than that for clay
due to the high seepage flow generated during
caissonDue to the high seepage flow generated during
caisson installation in sand requirement for sand isgreater than that for clay due to the high seepage
flow generated during caisson installation in sand.

Suction Caisson Installed in Different Seabed
Conditions From 1958 - 2014
Soft Clay2%

Homogenous Stiff
Clay
Layered Clay (SoftClay + Stiff Clay)
Sand

0%
0%0%
7%
9%
47%

9%

Layered- Dense sand+ Stiff Clay
Layered- Clay + Sand
Layered - Sand +
Clay
Silt

11%
15%

Comparative Analysis of Suction Caisson
Installation Issues, Their Causes and Possible
Solutions in Different Seabed Conditions

0%

From the review of suction caisson installationfrom literature reviews and 50 case study fieldreports, the results obtained are summarized inTable 3 and Fig 4.

Carbonate Sand
(Shallow Water)
Carbonate Sand
(Deep Water)
Cemented Soils andhard rocks

Fig. 5 Suction Caisson Installed in Different Seabed
conditions from 1958-2014 (M.N Tran 2007, pp.
112, T.I Tjelta 2001, pp. 3)

Table 3 Suction caisson installation issues indifferent seabed conditions (M.N Tran 2007, pp.
112, T.I Tjelta 2001, pp. 3, Colliat and Dendani
2002, Kolk, et al. 2001, Houlsby and Byrne 2004,
Randolph and House 2002)

These results highlights that, plug heave, soil
piping and bottom resistance failure are the mostcommon failure types amongst suction caissons.
Plug heave contributes about 34% of theinstallation issues in both homogeneous clay soils
and layered clay soils, soil piping and bottom
resistance failure contribute about 24% and 20%
respectively of the installation issues in both sandand layered sand soils, while high penetration
resistance contributes about 27% of installation
issues in layered soils. However, in spite of these
installation issues, suctions caissons are more
widely used in clay soils (47%) among all other soil
types.
CONCLUSION
From the literature reviewed and analysis
conducted, it was observed that the following
installation issues such as: buckling, plug heave,soil piping, bottom resistance failure and highpenetration resistance existed in both homogeneousand heterogeneous seabed conditions. These issues
were caused by the amount of suction induced andthe soil attributes exhibited during penetration. The
amount of suction induced is dependent on theseabed condition and the soil attributes exhibited
during penetration. Therefore, in order for thesechallenges to be mitigated, a good understanding of
the seabed conditions and soil parameters before* = Not clearly stated
PH= Plug Heave, B= Buckling, SP= Soil Piping,
BRF= Bottom Resistance Failure, HPR= High366

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017and during installation, together with constantmonitoring of the induced suction created alongside
the penetration depth is essential.

[12] Sparrevik P. "Suction Pile Technology andInstallation in Deep Waters." Offshore
Technology Conference, 2002

REFERENCES[13] Dendani H. "Suction Anchors: Some criticalaspects for their design and installation in clayeysoils." Offshore Technology Conference, 2003

[1] Tjelta TI. "Suction Piles: Their Position And
Application Today." International Society of
Offshore and Polar Engineers, 2001[14] Sharma PP. "Ultimate capacity of suction caisson
in normally and lightly overconsolidated clays.
“Unpublished work but accepted (Thesis)” 2005.

[2] Aubeny CP, Murf JD, and Moon SK. "Lateral
Undrained Resistance of Suction Caisson
Anchors." International Journal of Offshore andPolar Engineering; ISOPE-01-11-3-211, 2001.

[15] Huang J, Cao J, and Audibert JME.
"Geotechnical Design Of Suction Caisson In
Clay." International Society of Offshore andPolar Engineers, 2003.

[3] El-Sherbiny RM. "Performance of suction caissonanchors in normally consolidated clay
[dissertation]." Austin, TX: The University ofTexas at Austin, 2005
[4] Cao J., Audibert JME , Al-Khafaji Z, Phillips R,
and Popescu R. "Penetration Resistance ofSuction Caissons In Clay." International Societyof Offshore and Polar Engineers, 2002[16] Senders M, and Randolph MF. "CPT-based
Method for the Installation of Suction Caissons in
Sand."
Journalofgeotechnicalandgeoenvironmental engineering 14-25, 2009[17] Senders M, Randolph MF, and Gaudin C.
"Theory For The Installation Of Suction Caissons
In Sand Overlaid By Clay." Society ofUnderwater Technology, 2007

[5] Tran MN., David WA, and Randolph MF. "Studyof Seepage Flow And Sand Plug Loosening In
Installation of Suction Caissons In Sand."International Society of Offshore and Polar
Engineers, 2005.

[18] Randolph MF, O'neill MP, Stewart DP, andErbrich C. "Performance of suction anchors infine-grained
calcareous
soils."
Offshoretechnology conference. Offshore technology
conference, 1998

[6] Tran MN. "Suction Caissons: A New Offshore
Foundation Concept." Australian Geomechanics,
2007.
[7] Sukumaran B. "Suction Caisson Anchors-A
Better Option For Deep Water Applications."
Rowan University, 1999[19] Zen K, and Hirasawa M. "Case History on the
Penetration of Suction Foundation into Seabed."
International Society of Offshore and Polar
Engineers, 2016[8] Solhjell E, Blaker O, Knudsen S, and Rahim A.
Geotechnical Design and Installation of Suction
Anchors for the Goliat FPSO, Offshore Norway.
Offshore Technology Conference, 2014.

[20] Randolph MF, and House AR. "Analysis of
Suction Caisson Capacity in Clay." Offshore
Technology Conference, 2002

[9] Housby GT, and Byrne BW. "Design proceduresfor installation of suction caissons in clay andother materials." Geotech. Eng 75-82, 2005[21] Houlsby GT, and Byrne BW. "Calculation
procedures for installation of suction caissons."
Report No. OUEL2268/04, University of Oxford,
2004[10] Bang S, and Karnoski S. "Field Retrieval of
Suction Piles In Sand." Proceedings of theSeventeenth (2007) International Society of
Offshore and Polar Engineers. International
Society of Offshore and Polar Engineers, 2007[22] Colliat JL, and Dendani H. "Girassol:
Geotechnical Design Analyses And Installation
Of The Suction Anchors." Society of UnderwaterTechnology, 2002[23] Kolk HJ, Kay S, Kirstein A, and Troestler H.
"North Nemba Flare Bucket Foundations."
Offshore Technology Conference, 2001.

[11] Cao J, Phillips R, Popescu R, Audibert JME, and
Al-Khafaji Z. "Numerical analysis of the
behavior of suction caissons in clay."
International Journal of Offshore and Polar
Engineering, 2003

367

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

DIFFERNTIAL THERMAL ANALYSIS OF PMMA (POLY METHYLMETHACRYLATE) - EXPERIMENTAL CONCERNSSam M Dakka1

1Department of Engineering and Mathematics, Sheffield Hallam University, United

Kingdom
ABSTRACT
Experimental concerns related to differential thermal analysis of 0.5mm PMMA particles are discussed withemphasis on experimental factors and sample characteristics impacting DTA trace signals. The experimental
factors affecting recorded DTA signals are the heating rate and the shape of crucible while the major sample
characteristics factors are size distribution, mass and tight packing. PMMA degradation results illustrated fasterheating rate improved sensitivity, however slower heating rate improved resolution. Tight particle packing
demonstrated a shift of PMMA decomposition to a higher temperature due to reduction in diffusion in and out of
the reaction zones of the sample under investigation. The reaction terminated earlier for smaller diameterparticles as compared with larger diameter particles. Furthermore, transformation of the DTA technique from
qualitative to quantitative is illustrated by calibration factor obtained utilizing various melting metals. The results
corroborate that DTA is a powerful investigative tool subject to strict implementation of experimental
procedures and handling.

Keywords: Thermal analysis, PMMA, Experimental concerns, Polymer

INTRODUCTION

AXPERIMENTAL APPARTUS

Thermal degradation of PMMA has attracted
great attention in various scientific fields in generaland in particular in the aerospace industry [1],PMMA is used as a reference material in studies
related to flammability of materials for theinternational space station cockpits and airline
cabins [2]. Thermal degradation of PMMA particles
via differential thermal analysis was investigatedunder various diluting environments ranging frompure Nitrogen to 79% nitrogen and 21% oxygen of
the surrounding gas [2]. The main results revealed
thermal degradation reaction in pure nitrogen can be
described as one step reaction and the reaction isendothermic. As oxygen is introduced in theenvironment the reaction was transformed to
exothermic. Furthermore, the heat of combustion
also was determined in pure nitrogen environment
utilizing a calibration factor. The following sectionsof this paper is focused on the experimental
concerns implemented prior to acquiring thedifferential thermal analysis signals described above[2] in order to demonstrate that DTA is a powerful
technique that should be considered seriously in any
future investigation of thermal degradation samples
subjecttoexperimental
concerns
strictimplementation. While the degradation discussed isfor PMMA particles, the experimental DTA
concerns are valid for any polymer particles

The experimental apparatus consist ofthermogravimetric (TG) device Cahn Instruments,
model 2131 [2, 3], the TG device is shown in Figure
1. The TG main components are a small furnace anda microbalance. A crucible inside the furnace is
attached to the microbalance for weight loss andweight rate degradation studies.

Fig.1 TG device consists of small furnace.
For DTA experiments the crucible is replaced bya small plate with two small pans, a sample pan anda reference pan. This is illustrated in Figure 2 and 3.
A Thermocouple located beneath the pans measured
the temperature difference between the two pans,
368

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

after performing cold junction correction.

completed the sample temperature will increase or
decrease to catch-up with the inert temperaturesample, in this case increases. For melting zinc thereaction is endothermic, the energy consumed topromote the phase transformation will result in a
relative decrease in the temperature of the sample.

Fig. 2 Sample and reference quartz pans or crucibles
utilized in the DTA measurements close view.

Fig.4 Typical DTA trace of melting Zinc
Large experimental factors can affects DTA
curves. The shape, position and number ofendothermic or exothermic curve peaks are crucial
for qualitative analysis. In addition the furnace
heating rate and furnace atmosphere content canalter the shape and position of the curves, therefore
impacting quantitative analysis due to changes in theenclosed curve areas of the peaks. In general the
DTA signal depends on two groups of factors
instrument factor and sample characteristics.

Fig. 3 Sample and reference quartz pans or crucibles
utilized in the DTA measurements, remote view
while the furnace is open (lowered).

RESULTS AND DISCUSSION
EXPERIMENTAL CONCERNSHeating Rate

Differential thermal analysis (DTA) is a methodby which the temperature of a sample is compared tothe temperature of thermally inert material. Thesetemperatures are recorded for sample and inert
material as the furnace is heated or cooled at aconstant heating rate. The inert sample must havethe same thermal mass as the sample underinvestigation with no occurrence of transformation
reaction in the investigative range of temperatures.
When transformation happens, it is either
endothermic or exothermic, heat is absorbed orreleased respectively, Figure 4 illustrates a DTA
signal of melting Zinc, in general, differential
thermal analysis plots, describe the difference oftemperature T as a function of time ortemperature. As the sample undergoes a phasetransformation as illustrated in Figure 4 thetemperature of the sample will lag, since during
melting the temperature holds steady until thetransformation is completed, as compared to an inert
sample, as illustrated the temperature of the sample
is lower than the inert one, as the transformation is

The effect of heating rate on DTA curves issignificant. Figure 5 and 6 illustrate the DTA signal
shape-dependence on whether the horizontal axis isdenoted by temperature or time. Also, the effects ofheating rate on the onset temperature and themagnitude of the peak temperature for Zinc at
2°C/min and 4°C/min in pure nitrogen environment.
By inspection of the curves carefully, the magnitudeof the peak curves is slightly larger or higher for
higher heating rate as compared with lower heating
curves this is due to the fact that during melting theendotherm temperature of the sample is maintained
constant while the reference temperature increases
faster. Since less time is available for increase of one
degree of temperature at higher heating rate, the timeinterval for the phase transformation to advanceshorter, also since the rate of heat flow to the sample
is higher the extent of reaction to proceed isnarrower as illustrated in figure 6. Anotherobservation is the onset of temperature is higher for
higher heating rates due to larger temperaturedeviation between the sample interior and the369

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

thermocouple junction.

temperature. Figure 7 illustrates this effect bycomparing the degradation weight loss rate of tightpacked versus loosely packed PMMA particles as afunction of temperature. As we can observe thetightly packed particle curve exhibit higher
temperature due to reduced diffusion effects and thedegradation curve is slightly broader.

Diff. Temperature [Celsius]-0.5

Zinc 4 C/min
Zinc 2 C/min

-1

-1.5

-2

-2.5

1.4
390

400

410

420

430

440

1.2

450

Mass Loss rate [mg/min]-3
380

Temperature [Celsius]

Fig. 5 The effect of heating rate on the melting
endotherm of Zinc

Light packing
Tight packing

1
0.8
0.6
0.4
0.2
0
-0.2
150

200

250

300
350
400
Temperature [Celsius]

450

500

Fig. 7 The effect of packing on the weight loss rateof PMMA
The impact of the sample particle size was also
considered, assuming spherical PMMA particles, incertain decompositions the surface to volume ratio
increases as the inverse of the particle radius [4],hence the reaction will terminate earlier for smaller
particles as illustrated in Figure 8. It is important tonote, that, since the thermocouple is attached to theunderside of the crucible, the larger the sample size,
the larger the temperature gradients inside thesample, and therefore less sensitivity of themeasurements. For example, for a large amount of
powder, the upper side or the surface might melt
first, while the lower part, in the vicinity of thethermocouple junction, may remain below themelting point. Thus, the melting of the upper surface
will act as a heat sink, and promote endothermic
deviation acquired by the DTA signal. This will
yield a false DTA trace since the detected melting
temperature will be lower. The geometric shape of
the pan is important due to the fact that the transferof heat to the sample should be uniform and efficientin order to reduce the temperature gradients within
the sample. The sample preparation of the PMMA
particles was obtained via shaving from large slab ofPMMA. Packing is a factor that should beconsidered, light packing and tight packing would
affect the TG curve. The maximum mass weight loss
will increase for the tight packing due to lessdiffusion effects. In addition, for low-density
packing the thermal conductivity is low due to the
low conductivity of air between the particles. In
these particular experiments the interest is in dense
packing. For studying ignition of a PMMA slab, theinterest is in relatively large bulk PMMA samples,
therefore, emphasis in sample preparation and

Fig. 6 The effect of heating rate on the shape of the
DTA endotherm
As discussed and illustrated by figure 5 and 6 theheating rate has a large impact on the magnitude of
the reaction peaks and the shape of the curves,
narrow or wide. For example if the heating rate is
too fast then some reaction will not be identified orrecognized, as a peak of more than one reaction canbe identified as one reaction. For accurate
determination of the onset of temperature a slower
heating rate should be exercised, in addition todiscerning close adjacent reactions. On the other
hand, too slow heating rate will cause the magnitudeof the peak to be too small to be identified. Tosummarize the effect of the heating rate on PMMA
degradation curves, slower heating rate yieldedhigher resolution, and faster heating rate higher
sensitivity.
PMMA Sample Characteristics
The reaction rates of the participating gases are
influenced by how the sample particles are placed in
the crucible [4]. Free diffusion in and out of thereaction zones will be reduced if the sample istightly packed, hence heavier molecules such ascarbon dioxide evolving from the sample will be
convected slowly from the surface. To that end, tightpacking will shift the decomposition to a higher
370

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

handling in reducing the diffusion effects. Light
sample packing, is achieved by placement the
PMMA particles into the crucible with no any
external interference. Dense packing involves anexternal procedure to reduce the pockets ofenvironment gas between the particles, once thesample is placed in the crucible.

Figure 8 shows the calibration DTA curves ofdifferent zinc weights as a function of temperature
for the same heating rate of 4C/min. The transition
temperature of 419.47C  1C is consistent withtable 1. In addition, the area and the maximum DTA
trace are higher for larger mass; this is due to thefact that a larger amount of energy is needed to melta larger mass compared to a smaller one. The
differential temperature of the baseline is lower for
24 mgs since the sample experiences lesstemperature gradient inside the particles.
The area under the DTA curve is calculated via
the equation listed in the beginning of this section.
Figures 8 and 9 illustrate the values of thecalibration factor versus temperature, for a variety ofpure metals with different masses, and for 2C/min
and 4C/min respectively.
Figures 9 and 10 indicate that the calibration
factor indeed depends on the temperature; the valueof K is higher for lower temperatures. The
dependence on temperature can be approximated bylinear relationship at 2C/min

Quantitative Aspects- Calibration

Table 1 DTA calibration of pure metals [4].

Indium
Tin
Lead
Zinc
Potassium
Sulphate
Potassium
Chromate

Transition
Point [°C]156.60231.88327.47419.47
585.0

-1
-1.5
-2
-2.5

81 mgs51 mgs24 mgs

-3
-3.5
-4
410

Heat
of
transition [j/g]
28.45
60.46
23.01
108.37
33.26

415

420
425
430
Temperature [Celsius]

435

440

Fig. 8 The effect of packing on the weight loss rateof PMMA

0.8

670.5

0.7

35.56

IndiumLead

0.6

K [J/ C-sec]

Metal Type0-0.5

Diff. Temperature [Celsius]

The ultimate goal is to determine the heat ofreaction or transition or the mass of the reactive
sample, this is accomplished from the area under the
DTA curve by applying the simple relation
H  m  K  A , where H is the heat of reaction ,m is the mass of the sample, K is the calibration
factor and A is the area under the peak. The
application of DTA for determining the heat ofreaction has been reviewed by [5, 6 and 7].
The calibration coefficient K, is determined byusing compounds having a known heat of transition.
These compounds must meet certain requirements
such as chemical stability during transformation, lowvapor pressure so that the heat of vaporization will
be negligible and will not contribute to the heateffect. The melting of pure metals is the mostcommon calibration method in DTA. Table 1
provides the type of metal, the transition temperatureand the latent heat of transformation.

The calibration procedure used in this study
included Indium, Lead and Zinc. These metals werechosen in order to cover the range of thedecomposition reactions of PMMA. Two different
tests were performed, one with emphasis on thedependence of the calibration factor on temperatureand the other, on the effects of the mass of thesample tested on the calibration factor. More overthe impact of the heating rate on the value of K was
also evaluated.

Zinc

0.5
0.4
0.3

m=54 mgs
m=24 mgs
m=84 mgs

0.2
0.1
0
100

150

200

250

300

350

400

450

Temperature [Celsius]

Fig. 9 Calibration factor as a function of temperature
for various mass metals at a heating rate of 2C/min.

371

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

CONCLUSION

0.8

Indium0.7

Lead

K [J/ C-sec]

0.6

Differential thermal analysis experimental
concerns related to 0.5mm PMMA particles
degradation in a TG device was discussed. The main
factors affecting the DTA traces are experimental
factors and sample characteristics. The experimental
factors affecting recorded DTA signals are theheating rate and the shape of crucible while themajor sample characteristics factors are size
distribution, mass and tight packing. PMMA
degradation results illustrated faster heating rate
improved sensitivity, slower heating rate improved
resolution. The shape of the crucible is important inconvection heavier molecules in and out of thesurface of the sample. Tight particle packing shifted
the decomposition to a higher temperature due toreduction in diffusion in and out of the reaction
zones. The reaction terminated earlier for smaller
particles as compared with larger particles. The
larger the particle size or mass, the larger
temperature gradients are experienced within thesample. Transforming the DTA measurements to aquantitative tool was demonstrated via a calibration
factor. The methodology is based on calculating thearea under or enclosed by the DTA trace signal. The
above experimental consideration is vital to achievea good quality and useful DTA traces.

Zinc

0.5
0.4
0.3

m=54 mgs
m=24 mgs
m=84 mgs

0.2
0.1
0
100

150

200

250

300

350

400

450

Temperature [Celsius]

Fig. 10 Calibration factor as a function oftemperature for various mass metals at a heating rateof 4C/min.
K  0.0009T  0.795, at m  54,24,84mgs (1)At higher heating rate 4C/min, K can beapproximated by a single relationship:K  0.0009T  0.8595, at m  54,24,84mgs (2)Both figures imply that for higher heating rates
the magnitude of K increases at lower temperatures.
The suitable calibration factor, which depends on thedecomposition temperature, must be used in thecalculation of the DTA area trace.
Figure 11 shows the DTA trace as a function ofdifferent sample weights at 2C/min and 4C/min.
The important conclusion from this figure is that the
TG device provides more stable data for thecalibration factor for higher temperatures. This iscorroborated by the fact there is almost no scatter ofdata for the zinc, while the amplitude of thescattering for Indium, which melts at a lower
temperature is much higher, and the scatter of lead isin between. This appears to be related to the TG
device or furnace design; therefore, the importanceof the calibration is crucial for obtaining accurate
results to determine the heat of transition.

REFRENCES[1] Friedman R. Risks and Issues in Fire safety on
the Space Station. NASA-TM-106430[2] Dakka SM., “TGA/DTA/MS of Poly(methyl
methacrylate)-The role of the oxidativeenvironment” Journal of Thermal Analysis andCalorimetry, Vol 73, 2003, pp. 17-24[3] Cahn instruments, Inc., Cerritos, CA.
[4] Speyer R. F. Thermal analysis of materials.
New York: Marcel Dekker; 1994
[5] Brochard J. H., and Daniels F., “The applicationof differential thermal analysis to the study ofreaction kinetics1”, Journal of The American
Chemical Society, Vol 79(1), 1957, pp.41-46[6] Bohon, R. L. Proceedings of the First Toronto
symposium on Thermal Analysis. McAdie, H.
G. Chemical Institute of Canada. Toronto; 1965.
pp. 63.
[7] Ozawa T.,” A new method of quantitative
differential Thermal Analysis”, Bull. Chem. Soc.
Japan, Vol 39, 1966, pp. 2071-2078

0.8
0.6

K [J/ Csec]

0.4
0.2

Indium 2 C/min
Zinc 2 C/min
Lead 2 C/min
Indum 4 C/min
Zinc 4 C/min
Lead 4 C/min

0
-0.2
-0.4
-0.6
-0.8
-1
0

20

40
60
Weight [mgs]

80

100

Fig.11 The calibration factor as a function ofdifferent weights of metals
372

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

INVESTIGATION OF CURING PERIOD OF CEMENTITIOUSADHESIVE AND PERFORMANCE OF RUST PREVENTION
Yoichi Mimura1, Vanissorn Vimonsatit2 and Isamu Yoshitake3
Department of Civil and Environmental Engineering, National Institute of Technology, Kure College, Japan;
2
Department of Civil Engineering, Curtin University, Australia;
3
Department of Civil and Environmental Engineering, Yamaguchi University, Japan

1

ABSTRACTA steel-concrete composite structure needs generally mechanical shear connectors such as headed studs toensure efficient load resistances. As an alternative to shear studs, a type of cementitious adhesives has beendeveloped to connect a steel-concrete composite structure. The unique feature of this adhesive is the improved
bond performance with fresh concrete which depends on the curing age of the adhesive. This paper presents theoutcome of fifteen flexural tests of elemental steel-concrete composite beams with various curing ages of theadhesive to investigate the appropriate curing period. Shot blasting steel plate and the un-shot blasting steel plate
were prepared to examine the bond performance from the surface condition of the steel plate. The result of theflexural tests indicates that the bond performance between the steel plate and the concrete is optimum when the
curing periods are 7 - 14 days. The tests with longer curing age produce similar bond performances with the tests
at 7 days. Use of steel plate without shot blasting may be undesirable for the composite structure using theadhesive. In addition to the flexural tests, 8 deformed bars with and without adhesive coating were exposed to a
field condition to investigate the rust preventive performance of the adhesive. The deformed bars without theadhesive had already corroded at 5 days after exposure. The observation showed the deformed bar with theadhesive was hardly deteriorated after 200 days.
Keywords: Cementitious Adhesive, Curing Period, Rust Prevention, Flexural Test, Field Exposure
INTRODUCTION

performance of the adhesive was examined using
coated bars exposed to a field environment for 200
days.

Steel-concrete
composite
structuresareconstructed by connecting concrete and steel, andhave many advantages such as excellent fatigue
durability and a reduced member size compared with
non-composite sections. Interaction between
concrete and steel affects performances (e.g. load
carrying capacities, durability and rigidity) ofcomposite structures. Various shear connectors suchas headed studs, channels and T-connectors are
currently available.
A new composite structural system using acementitious adhesive has been developed inprevious studies. The adhesive has been used invarious structures as rust preventive materials. The
previous study reports the composite beam using theadhesive had sufficient load carrying capacity [1]and fatigue durability [2]-[3]. Herein, it should be
noted that the adhesive needs an appropriate curing
term before casting of concrete. According to theprevious report [1], the steel substrate sprayed withthe adhesive was cured for 2 weeks. However, thecuring period was not discussed sufficiently.
Therefore, flexural tests using elemental composite
beams cured in various terms were performed inorder to investigate an appropriate curing period of
the adhesive. In addition, the rust prevention

MATERIALS
Cementitious Adhesive
The carbon-fibre-blended cementitious adhesive
developed in Japan consists of compound powder
and liquid emulsion, as shown in Fig. 1. Table 1 andTable 2 give the components and properties of theadhesive [4]. The powder and liquid were manually
mixed in the laboratory using a portable mixer at aweight ratio of 2.3 (powder/emulsion), as
recommended by the manufacturer.

Fig. 1

373

Compound powder
emulsion (right)(left)

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

Table 1 Components of the adhesiveplate with shot blasting has rougher surface than the
one without shot blasting, so the surface without
shot blasting was shiny, as shown in Fig. 2. Steelplates were 100 mm width x 300 mm length x 3.2mm thickness. The adhesive after mixing was
sprayed on the steel plates by using a spray gun witha nozzle diameter of 4 mm as shown in Fig. 3. The
amount of the adhesive sprayed on the steel plates
was approximately 1.0 kg/m2. The adhesive wassprayed on all steel plates used in flexural tests at
once as shown in Fig. 3.

Component
Composition
CompoundWhite cement36%
powderQuartz sand54%
Carbon fibre
3%
Additive
7%
LiquidWater
73%
emulsion
Acrylic ester
27%
Additive<1%
Note: The manufacturer is Mighty-kagaku [4]Table 3 Mixture design of expansive concrete

Table 2 Properties of fresh and hardened adhesive
Component
Water-binder ratio
Water
Ordinary Portland cement
Expansive additive
Fine aggregate
Coarse aggregate
Water-reducing admixture

Property
Fluidity
Air permeability

Value>250 mm
476 cm3/m2 (24 h)
1455 cm3/m2 (72 h)
Flexural strength
5.8 MPa (7 days)
6.9 MPa (28 days)
Compressive strength
21.0 MPa (7 days)
36.8 MPa (28 days)
Tensile strength
3.1 MPa (7 days)
4.0 MPa (28 days)
Strain capacity
0.4% (7 days)
0.4% (28 days)
Drying shrinkage
0.08% (7 days)
0.13% (28 days)
Water permeability
0.4% (water pressure:
0.1 MPa)
Note: The manufacturer is Mighty-kagaku [4]Quantity
48.0%
161 kg/m3
316 kg/m3
20 kg/m3
841 kg/m3
980 kg/m3
2.69 kg/m3

Table 4 Strength of expansive concrete at the age of
7 daysCompressive strength
Splitting tensile strength
Flexural strength

Strength39.1 MPa
3.30 MPa
5.58 MPa

Concrete
The Japan Bridge Association recommends theuse of expansive concrete for composite slab toprevent cracks due to concrete contraction [5]. Table
3 gives the mixture proportion of the expansive
concrete. The compressive strength and splitting
tensile strength of concrete were obtained from thetests using the cylindrical specimen (100 mm
diameter x 200 mm height). The concrete prisms(100 mm width x 100 mm height x 400 mm length)were used for the flexural strength. Table 4 provides
the concrete strength at the age of 7 days.

(a) Un-shot blasting steel plate

Fig. 2(b) Shot blasting steel plate
Steel plates

Fig. 3

Steel plates sprayed with the adhesive

Steel Plate and Deformed Bar
Rolled steel for welded structure (Grade
SM400A by JIS G3106 [6]) used in flexural tests
had a yield strength of 245 MPa with Young's
modulus of 200 GPa. The shot blasting steel plate(Type B) and the un-shot blasting steel plate (TypeN) were prepared to examine the bond performancewith a different surface condition of the steel plate.
Fig. 2 shows steel plates used in this study. The steel
374

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

Eight deformed bars with a diameter of 13 mm
were employed for field exposure. All bars (GradeSD345 by JIS G3112 [7]) had a yield strength of 345
MPa with Young’s modulus of 200 GPa. Eachreinforcing bar was 1940 mm long. The adhesive
attached on the deformed bar was approximately
0.83 kg/m2. Fig. 4 shows the surface condition of thecoated and uncoated deformed bars.

crack to the plate edge debonded from the concrete,
as shown in Fig. 6.
Strain gauge (3 mm long)
100mm

100mm
Expansive concrete

300mm
400mm

100mm

Steel plate (t=3.2mm)

Fig. 5(a) Deformed bar without adhesive coating

Fig. 4

Schematic of specimen
condition for flexural test

andloading(b) Deformed bar with adhesive coating
Surface condition of the deformed bar
debonding

FLEXURAL TESTS FOR ADHESIVE CURINGPERIOD
Test DetailFig. 6To examine the effect of curing time for theadhesive, flexural test was conducted by using thespecimen shown in Fig. 5. The curing periods of theadhesive on steel plates (Type B and Type N) were 2,
7, 14, 28, 140 and 168 days before casting concrete.
In addition, the flexural tests using the Type B steel
plates cured for 3, 4 and 5 days were also performed
to further explore the trend of the failure load at theinitial age. After curing of the adhesive to a desiredage, concrete was cast. The concrete formwork wasremoved at the concrete age of 1 day, and theconcrete was cured in the water with a temperatureof 20 degree Celsius. The side of the steel plate
without adhesive was greased in order to prevent therust during the water curing. The test age forconcrete was 7 days for all test cases.
The load by using a universal testing machine
was applied statically to the test specimen. The test
was a 4-point loading system, as shown in Fig. 5.
Two beam specimens were tested at each age. Strainof steel plate was measured at the mid-span of thebeam.

Concrete cracking and debonding of steel
plate

Fig. 7 presents the adhesive remaining on thesteel plate after flexural test with 7 days curing of
the adhesive. Little adhesive remained on un-shot
blasting steel plate (Type N) because the un-shot
blasting steel plate had a smooth surface. The
surface of shot blasting steel plate (Type B) was
rougher than Type N, more adhesive remained on
Type B steel plate.

adhesive

Type N

Experimental Results and Discussion
Fig. 7All specimens had a single line cracking due tothe bending moment occurred at the loading span
regardless the experimental conditions. After
concrete cracking, the steel at the area from theType B

Adhesive remaining on steel plate after testwith curing period of 7 days

Fig. 8 presents a ratio of failure load (failure load
375

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017of elemental composite beam/load carrying capacityof concrete). The ratio of 2 days curing of Type N
beams was almost 1.0, the adhesive cured for 2 days
hardly had the bond performance with the un-shot
blasting steel plate. In the test of Type B, the ratios
at 28, 140 and 168 days were approximately
equivalent to the ratio at 7 days. This result indicatesthat the bond performance between the steel plate
and the concrete is optimum when the curing periods
are 7 - 14 days. This appropriate curing is longer
than one of typical adhesive such as epoxy resin.
However, some procedures for casting concrete areneeded after applying the adhesive, so the curing
period of 7 - 14 days can be acceptable in actual
construction. The tests with longer curing age, suchas 140 or 168 days, produced similar bondperformances with the tests at 7 days. A half year
curing of the adhesive hardly affects the decrease inload carrying capacity of the composite beam. In thetest of Type N, the ratio of the beam with 140 days
curing was definitely smaller than the ratio of theone with 7 days curing. Use of steel plate without
shot blasting may be undesirable for the composite
structure using the adhesive.

Load (kN)

5 daysFig. 950
100
Strain of steel plate (x10-6)

Load - steel strain relationship

70

Type N

1.0
0.8
0.6

Load: 15kN

60
50
40
30
20
10

Load 5kN

0

0.4: average

2

3

0.2
2

3

4
5
7
14 28 140 168
Curing period of adhesive (days)

4
5
7
14 28 140 168
Curing period of adhesive (days)

Fig. 10 Strain of steel plate at the load of 5 kN and
15 kN (Type B)

Type B70

1.4

Strain of steel plate (x10-6)

Ratio of failure load

7 days

10

0

1.2

1.2
1.0
0.8
0.6
0.4

: average

0.2
2

Fig. 8

20

0

1.4

1.6

Type B

30

Strain of steel plate (x10-6)

Ratio of failure load

1.6

smaller than steel strain from the specimen with 7days curing. Such smaller strain was caused by thereleased strain due to the slip between concrete andsteel plate, as evident in Fig. 6. Higher strain such as
the elemental beam with 7 days curing was inducedby the development of the bond performance of theadhesive.

34
5
7
14 28 140 168
Curing period of adhesive (days)

Load: 15kN

60
50
40
30
20
Load 5kN

100
2

Ratio of failure load

7
14
28
140
Curing period of adhesive (days)

168

Fig. 11 Strain of steel plate at the load of 5 kN and
15 kN (Type N)

Fig.9 shows the relationship between load andstrain of steel plate of Type B at the curing period of
5 days and 7 days. Both strain responses weresimilar up to the load of around 10 kN. Under theload of more than 10 kN, the strain of steel plateobtained from the specimen with 5 days curing wasFig. 10 shows the strain of steel plate in Type B
at loads of 5 kN and 15 kN. Strains at 5 kN werefrom 13 x 10-6 to 25 x 10-6, and almost equivalent at
the ages of 2 - 168 days. At the load of 15 kN, thestrains before 5 days and the strains after 7 days
376

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

were approximately 40 x 10-6 and 50 x 10-6,
respectively. Such smaller strains before 5 days
mean a slip between the steel plate and the concrete.
This result also indicates that the adhesive needs thecuring period of more than 7 days.
The strains of the Type N beams are as shown in
Fig. 11. The strain at a load of 15 kN tended toincrease until 14 days of curing but decreased at 28
days of curing period, and at 140 days, the strain
was less than that at 2 days due to the slip between
the steel plate and the adhesive. Such a decrease instrain at these curing days was the same as thetransition of the failure load ratio shown in Fig 8.

Deformed bars were then exposed in a field
condition to confirm the rust preventive effect of theadhesive, as shown in Fig. 13. The field exposure
was performed at a site located 500 m from theseashore.
Table 5 Weight of the adhesive on the deformed bar
Bar
1
2
3
4
Ave.

FIELD EXPOSURE OF DEFORMED BARSCOATED BY ADHESIVE

Bar weight (g)before
after
1836
1899
1830
1897
1827
1892
1840
1910
1833
1899

Adhesive Weight(g)
63 (0.79 kg/m2)
67 (0.84 kg/m2)
65 (0.82 kg/m2)
70 (0.88 kg/m2)
66 (0.83 kg/m2)

Test DetailFor applying the adhesive coating to steel bars, aroller and lysing gun can be used. However, withthese ways, it is difficult to uniformly apply anappropriate amount of adhesive to the reinforcing
bar. Therefore, in this study, a wood formwork withan inner dimension of 50 x 50 x 2000 mm as shownin Fig. 12 was used as a mould to hold the adhesivematerial inside. Reinforcing bars were then coatedby immersing in the adhesive in this wood
formwork. In the present test, each rebar was
immersed for a few seconds, and after taking it out,
it was manually rotated for about 30 minutes so thatthe adhesive was evenly applied to the rebar.

Fig. 13 Field exposure of the deformed bars
Experimental Results and Discussion
Fig. 14 shows the corrosion of the deformed bars
exposed for 0, 5 and 42 days. The deformed bars
without the adhesive had already corroded at 5 days.
The rust at 5 days appeared at some lugs and ribs ofthe deformed bars. After 42 days of exposure, mostlugs and ribs had rusted, and the rust had expanded
further to other areas of the bar. On the other hands,
bars with the adhesive showed no sign of rusting.

Fig. 12 Coating of the adhesive on the deformedbarTable 5 shows the amount of adhesive applied.
As a result of the application, the coating amount
was 0.38 kg/m2, and the adhesive could be applied
only to the extent that a thin film was stretched overthe surface of the reinforcing bar. Therefore, after
the adhesive cured for around 30 minutes, theadhesive was again applied to the rebar with thesame procedure. As a result of measuring the weightof the reinforcing bars after the second applicationof the adhesive, as shown in Table 5, the appliedamount of the adhesive was 66 g on the average of 4bars and the average coated amount per unit area
was 0.83 kg/m2.

0 day
5 days42 daysFig. 14 Corrosion of the deformed bar at 0, 5 and42 days377

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

Fig. 15 shows the corrosion of the deformed bars
exposed for 91, 136 and 200 days. The rust of thedeformed bars without the adhesive expanded as
exposure continued, and the whole of the bars
deteriorated due to the rust when 200 days passed.
The deformed bars coated with the adhesive hadsome minor rust with the size of approximately 1
mm after 91 days exposure, as shown in Fig. 15. Allsuch rust appeared like a pinhole at the lug which
had locally thinner adhesive. The occurrence of thislocalized rust gradually increased with theincreasing exposure period. In this study, although
the bars were rotated until the adhesive hardenedroughly, the uniform adhesive was not entirely
applied around the lugs of the deformed bars. The
application procedure and the amount of theadhesive required on a deformed bar need further
studies to prevent the rust at the lug location.
However, the local rust did not expand, and evenafter 200 days from the start of the exposure, thereinforcing bar was sound and no significant
corrosion occurred.

cementitious adhesive can be recommended as
7 - 14 days based on the ratio of failure loadand steel strain response obtained from flexural
tests. In addition, the adhesive with longer
curing age, such as 140 or 168 days has similarbond performances.
(2) As a result of the field exposure test, thedeformed bars without the adhesive had alreadycorroded at 5 days, and the rust covered almost
the whole surface area of the bar when 200
days passed. The deformed bar coated with theadhesive was sound and no significant
corrosion occurred.
ACKNOWLEDGEMENTS
The authors would like to thank Dr. Watada(Ube Machinery Co., Ltd.), Mr. Ikushima (Maeda
Sangyo Co., Ltd.) and Mr. Shimoda (an advanced
course student of National Institute of Technology,
Kure College).
REFERENCES[1] Yoshitake I., Ogawa A., Kim Y.J. and MimuraY., “Development of a New Composite SlabSystem Using a Carbon Firber-Blended
Cementitious Adhesive”, Journal of StructuralEngineering, Vol.138, No.11, Nov, 2012,
pp.1321-1330.
[2] Yoshitake I., Ogawa A., Kim Y.J. and Ogami
E., “Composite Deck Having Transverse
Stiffeners Bonded with a Cementitious
Adhesive Subjected to Moving-Wheel Fatigue”,
Journal of Bridge Engineering, Vol.18, No.9,
Sep, 2013, pp.848-857.
[3] Yoshitake I., Kuroda Y., Watada Y. and Kim
Y.J., “Fatigue performance of steel–concrete
composite slabs with a cementitious adhesive
subjected to water leakage”, Construction and
Building Materials, Vol.111, Feb, 2016, pp.2229.
[4] Mighty-kagaku, Manufacturer’s data sheet (inJapanese), <www.mighty-kagaku.jp> (accessed
May. 9, 2017)[5] Japan Bridge Association (JBA), 2007. (inJapanese)[6] Japanese Industrial Standards (JIS), JIS G3106:
Japan Standard Association, 2008[7] Japanese Industrial Standards (JIS), JIS G3112:
Japan Standard Association, 2010

136 days
200 days
91 daysFig. 15 Corrosion of the deformed bar at 91, 136
and 200 days
CONCLUSION
This paper presents the investigations of thecementitious adhesive for a steel-concrete composite
structure. Flexural tests using the elemental
composite beams were conducted to obtain theappropriate curing period of the adhesive. Field
exposure testing of deformed bars coated theadhesive was performed to confirm the rustprevention performance. Based on the test results inthis study, it can be concluded as follows:(1) Theappropriate

curingperiod

of

the

378

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

REGIONAL DEPOSITION CHARACTERISTICS OF
NANOPARTICLES IN A RAT NASAL CAVITY
Yidan Shang1, Jingliang Dong2, Kiao Inthavong3 and Jiyuan Tu4
1

School of Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia.
Key Laboratory of Ministry of Education for Advanced Reactor Engineering and Safety, Institute of Nuclear
and New Energy Technology, Tsinghua University, PO Box 1021, Beijing 100086, China.

2

ABSTRACTIn this study, inhalation exposure to nanoparticles in a realistic rat nasal passage was numerically investigated byComputational Fluid-Particle Dynamics (CFPD) approach. The nasal passage was reconstructed from CT imagesof a 400g Sprague-Dawley rat, and moderate breathing condition was applied to produce laminar airflow field.
Nanoparticle trajectories were calculated using Lagrangian one-way coupling method. Nanoparticles in the sizeof 1 to 200 nm were used and the effect of Brownian motion was considered. The simulation results showed thetotal deposition efficiency sharply decreased from 98.8% for 1 nm particles to 2.33% for 200 nm particles. The
regional olfactory deposition efficiency peaked at 9.4% for particle size 5 nm. Particle flux distributions wereplotted to identify the bulk particle flow at different cross-sectional planes. For 1 nm particles, the flux
dominantly concentrated in the centre of the cross-section when exiting the vestibule region and no flux was
shown in the olfactory region, whereas for 10 nm particles the flux was more uniformly distributed when exiting
the vestibule and the particles travelling through the upper part leaded to the deposition in the olfactory region.
This indicates that the rat nasal cavity retains a particle selective feature, which prevents high diffusive particles
from entering the olfactory region but allows low diffusive nanoparticle to deposit in the olfactory region.
Keywords: Rat, Nasal Cavity, Nanoparticle, CFPD

INTRODUCTION

effectively bypass the challenges above withacceptable accuracy.
Previous CFD studies have investigated airflow
characteristics and nanoparticle/gas deposition
efficiencies in rats [6-8]. To estimate regional
nanoparticle uptake, Schroeter, et al. [9] plotted theparticle distribution and found the frontal part of the
rat’s nasal cavity was the major deposition region
and it moved distally as the particle size increased.
Furthermore, Shang, et al. [10] and Dong, et al. [11]revealed the detailed particle deposition patterns
using a novel surface-mapping technique andcompared between the rat and the human models.
The large olfactory to total nasal surface area
ratio makes the rat olfactory region, a portal for
nanoparticle translocation, vulnerable to even low
toxic dosage level. Although the regional particle
deposition in the rat nasal cavity has been
intensively conducted, the exact mechanism ofnanoparticle travelling from nostril to olfactory
region remains unclear.
In this study, we performed 1-200 nm
nanoparticle inhalation simulation under themoderate breathing condition (400 mL/min) in arealistic rat nasal cavity model (RNC01). Both total
and regional (vestibule and olfactory) deposition
efficiencies were calculated. 1 nm and 10 nm
particle flux distributions were plotted on two crosssections located posterior to the vestibule region andmiddle olfactory region. Combined with previous

Concerns about the health effects of inhaled
nanoparticles on respiratory and central nerve
system have been increased in recent years as theprosperity of nanotechnology has increased human’s
exposure to airborne nanoparticles. WHO [1]confirmed that inhalation hazards such as notorious
asbestos cause severe health consequences. Previous
investigations showed inhaled nanoparticles lead toincreased risk of respiratory, cardiovascular andneurological disorders [2].
Recently, emerging evidences indicate theolfactory bulb and olfactory nerve play a vital role inbrain uptake of neuro toxics [3, 4]. Oberdörster, etal. [5] used a confined compartment to study rats’exposure to carbon nanoparticles and found theirtranslocation via neuron routes from olfactory
mucosa to central nerve system.
Experiments on rats have been widely used toevaluate exposure risks to nanoparticles. However, it
has been a challenge to extrapolate the experimental
data from rats to humans due to various
experimental limitations. For example, nanoparticles
tend to agglomerate to micron in size before
depositing and it is difficult to quantitively measureregional particle deposition. With the rapid
development of medical imaging technique andComputational Fluid Dynamics (CFD), simulations
coupled with realistic rat nasal CAD models cost379

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

studies, the cross-sectional particle distribution
provides insights into the interaction between rat
nasal structure and nanoparticle trajectories.

equals to particles passing through the nostrils. The
definition was:𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒𝑠 𝑝𝑒𝑟 𝑢𝑛𝑖𝑡 𝑎𝑟𝑒𝑎
𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒𝑠 𝑝𝑎𝑠𝑠𝑖𝑛𝑔 𝑡ℎ𝑟𝑜𝑢𝑔ℎ 𝑛𝑜𝑠𝑡𝑟𝑖𝑙𝑠
Thus, the particle flux distribution can reveal thebulk movement of nanoparticles, and may shed alight on the mechanism of olfactory deposition.
For cross-sections at nostrils, the integral ofparticle flux is constantly 1,𝑓(𝑟⃑) =METHOD
Nasal Geometry
LocationsandParticle

ReleaseThe CAD model of a Sprague-Dawley rat
labeled as RNC01 (Fig. 1) was reconstructed from
CT-scan and was frequently used in authors’previous studies [10-12]. The model started from the
rat’s face/nostrils and ended at the exit ofnasopharynx. The highly folded olfactory region,
which occupied 52.4% of the total surface area [12],was highlighted at the posterior-dorsal part. Twocross-sections A and B located at the posterior
vestibule and at the middle of olfactory region,
respectively, were generated to reveal the particle
flux patterns.
The particle releasing location, external facial
features plays important roles on determining thefate of particles. Our previous study has
demonstrated that the breathing zone was the key
component that dominated particles trajectory [13].
In this study, nanoparticles were uniformly released
from a spherical surface in front of the nose.
Detailed governing equations of airflow simulationand Lagrangian particle tracking method can befound in the author’s previous study [11].

∫ 𝑓(𝑟⃑)𝑑𝐴 = 1
𝑛𝑜𝑠𝑡𝑟𝑖𝑙𝑠

Due to deposition on the nasal wall, the integralof particle fluxes on cross-section A and B werealways less than 1,∫
𝑐𝑟𝑜𝑠𝑠−𝑠𝑒𝑐𝑡𝑖𝑜𝑛

RESULTS
Total Deposition Efficiency
Fig. 2 shows the total deposition efficiency
against particle size between 1-200 nm. Highdeposition percentage (>80%) was found for particle
smaller than 2 nm. The deposition efficiency sharply
dropped to around 10% for 20 nm particles and thenstabled around 5% for 20-200 nm particles.

Figure 1. The rat nasal cavity with particle releasing
locations. Two characteristic cross-sections, A andB, were used for particle transport analysis.

Figure 2. Particle deposition efficiency in the entire
rat nasal cavity for particles range between 1 to 200nm.

Deposition Efficiency and Particle Flux
The deposition efficiency (DE) was defined as
the ratio of number of particles deposited in a region
to the total number entering the nasal cavity:𝐷𝐸 =𝑓(𝑟⃑)𝑑𝐴 < 1

The data of the deposition curve was consistent
with our previous paper [11]. Close agreements were
found when comparing the trend of the curve to
published relevant rat nasal deposition data [7, 9].

𝑟𝑒𝑔𝑖𝑜𝑛𝑎𝑙 𝑜𝑟 𝑡𝑜𝑡𝑎𝑙 𝑑𝑒𝑝𝑜𝑠𝑖𝑡𝑒𝑑 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒𝑠
𝑡𝑜𝑡𝑎𝑙 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒𝑠 𝑖𝑛ℎ𝑎𝑙𝑒𝑑

Regional Deposition Efficiency

The particle flux (𝑓) was designed to assess thenumber of particles passing through an unit area on
the cross-section. It was normalized by the numberof particles inhaled into the nasal cavity, which

The vestibule region of rats serves a filtration
function to avoid particles entering olfactory region
and lung. The regional deposition efficiencies
against particle size between 1-200 nm were plotted
380

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017for vestibule and olfactory regions in Fig. 3. The rat
nasal vestibule showed strong filtration effect forparticles smaller than 3 nm. It absorbed 20% of
inhaled 3 nm particles and the filtration rate reached
60% for 1 nm particles. While for particles larger
than 5 nm, the deposition in the vestibule region
approached to the same level as in the olfactory,
which kept below 10%.

section had larger chance to deposit. While for the
10 nm case, the resultant particle deposition was
more broad. This is mainly because extremely low
deposition occurred (merely 5%) in the vestibule
region according to Fig. 3 and Table 1.

Figure 3. Regional particle deposition efficiency inthe vestibule and olfactory regions.
Figure 4. 1 nm particle flux on cross-sections A and
B. Particles were concentrated in the middle when
exiting vestibule and concentrated in the lower partof cross-section B without entering olfactory region(upper part).

Particles exited the vestibule region continued
travelling to the deep nasal cavity and part of them
deposited in the olfactory region. Different to thevestibule deposition, the olfactory deposition
efficiency started from 0 and rose up gradually as
the particle size increased. It peaked at 10% whenparticle size reached 5 nm and then smoothly
decreased to 0% for 200 nm particles. This wasconsistent with previous study conducted bySchroeter, et al. [9].
Particle Flux Distribution
Fig. 4 and Fig. 5 displayed the flux distributionsof 1 and 10 nm particles at cross-sections A and B.
The cross-section A was located at the posterior ofvestibule and the cross-section B was located at the
middle of main passage, with the upper part being
included in the olfactory region. To have a complete
view, the relative locations of two cross-sections in
the nasal cavity remained unchanged and 3D-view
was rotated. Nostrils and the exit of nasopharynx
were also plotted.
Obvious preferential particle distributions wereobserved at the cross-section A for both 1 nm and 10
nm particles. Higher particle concentration wereseen in the centre, where the mainstream of air
flowed through as shown in the airflow patterns inShang, et al. [10]’s study.
0 particle flux was observed at the top andbottom of cross-section A for the 1 nm case due tothe strong filtration effect of the vestibule region. As
seen in the Table 1, the integral of particle flux oncross-section A of 0.42 indicated that majority of
inhaled particles were absorbed by the vestibule
region and the particles at the margin of the cross-

Figure 5. 10 nm particle flux on cross-sections A
and B. Particles are more uniformly distributed
when exiting the vestibule and significant amount ofparticles entered the olfactory region.
Table 1. Integrals of particle flux on nostrils, crosssection A and cross-section B.
particle nostrils
crossCrosssize
section A section B
Integralof flux

1 nm
10 nm

1.00
1.00

0.42
0.95

0.03
0.84

Particle size was seen clearly to affect particles

381

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

entering the olfactory region. The Table 1 also
showed merely 3% of inhaled 1 nm particles reached
the cross-section B and they were mostly
concentrated in the lower part (Fig. 4), where thebulk streamlines flowed through. With lessdiffusivity, considerable amount of 10 nm particles
entered the upper part of cross-section B, leading tohigh olfactory deposition. Comparing Fig. 4 and Fig.
5, it is reasonable to infer that the particles depositedin the olfactory region was travelled from the upper
part of cross-section A.

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2010.
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J. D. Schroeter, J. S. Kimbell, B.
Asgharian, E. W. Tewksbury, and M. Singal,"Computational fluid dynamics simulations ofsubmicrometer and micrometer particle deposition in
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CONCLUSION
In this study, numerical results of 1-200 nm
particles deposition in a Sprague-Dawley rat nasal
cavity model under inhalation flow rate 400 mL/min
were reported. The simulation results showed good
agreement with previous experimental andnumerical data.
The research findings demonstrate the particle
size remain the key factor to determine particles’
fate in the rat nasal cavity. The rat vestibule region
posed strong filtration for high diffusive particles (1nm) while it allowed low diffusive particles (10 nm)
to travel through. The particle main mainstream was
located at the centre when it exited vestibule andconverted to the lower part when reaching theolfactory region. The particles exited in the upper
part of the vestibule region may contribute to highdeposition in the olfactory region.
ACKNOWLEDGEMENT
This study was funded by the National Natural
Science Foundation of China (Grant No.: 91643102)
and Australian Research Council (Project ID:
DP160101953).
Corresponding Author: Jiyuan Tu
Email: jiyuan.tu@rmit.edu.au
REFERENCES[1]
I. A. f. R. o. Cancer, I. A. f. R. o. Cancer,
I. A. f. R. o. Cancer, and I. A. f. R. o. Cancer,"Asbestos (chrysotile, amosite, crocidolite, tremolite,
actinolite, and anthophyllite)," IARC Monogr Eval
Carcinog Risks Hum. C, vol. 100, pp. 219-309, 2012.
[2]
K. B. Knudsen, H. Northeved, P. K. Ek,
A. Permin, T. L. Andresen, S. Larsen, et al.,"Differential toxicological response to positively andnegatively charged nanoparticles in the rat brain,"Nanotoxicology, vol. 8, pp. 764-774, 2014.
[3]
R. Bai, L. Zhang, Y. Liu, B. Li, L.
Wang, P. Wang, et al., "Integrated analytical382

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SEGMENTATION OF PAP SMEAR IMAGES TO IDENTIFY AND
DETECT CERVICAL CANCER
Vasundhara Acharya1, Preetham Kumar2
Student, Dept. Of Information &Communication Technology, Manipal Institute of Technology, Manipal
University,Manipal -576104, India.
2
Professor,Dept. Of Information &Communication Technology, Manipal Institute of Technology, Manipal
University,Manipal -576104, India.
1

ABSTRACT
Cervical Cancer arises in the Cervix. It is caused due to Human Papillomavirus. The cancerous cells are locatednear transition area between the vagina and the uterus known as the squamo-columnar junction. Invasive cancer
has the ability to spread to regional lymph nodes, the lungs, the liver, the bladder, the vagina, and the rectum.
The cancer progresses slowly from normal stage to pre-cancerous stage and hence it provides an opportunity todiagnose it and prevent it. Visual inspection of the Pap smear is tedious and time consuming. Commercial
systems for automated analysis are costly which makes it unaffordable for most hospitals. The main aim of thisresearch work is to identify if the cervical cancer is Squamous cell carcinoma or Adenocarcinoma by
segmenting the Pap smear images. Image Segmentation and Boundary detection techniques are utilised toclearly separate the nucleus from the cytoplasm. Automated cropping procedure is implemented to have one cell
per image that allows to extract the cytoplasm features. The work extracts texture, shape and pixel value
measurements to classify the cancer in to its respective categories. It also classifies Squamous cell carcinoma as
Low-grade Squamous intraepithelial lesion (LSIL) or High-grade Squamous intraepithelial lesion (HSIL). It
usually takes 3 weeks for the pathologists to generate the Pap smear results. The proposed work identifies thestage of the cancer within few seconds. It works for images with different stains and images with single cell andmultiple cells. It achieved an accuracy of 98 percent when the results obtained where compared with the clinicalresults.
Keywords: Cervical cancer, Pap smear, Squamous cell carcinoma, Adenocarcinoma. Automated cropping
Cytoplasm is obtained by using automated cropping
technique with coordinates computed using the
INTRODUCTION
nucleus boundary detection. Binary Morphology is
Cervical cancer is a cancer located in ectocervix,
used to determine the cytoplasm area. The N/C ratio
endocervix and transformation zone. Humanalong with the other shape and texture features
Papilloma Virus is the root cause of cervical cancer.
obtained from the image is analyzed using WEKA
A recent survey says that, every seven minutes one
tool. An efficient data mining algorithm is used towoman loses her life because of cervical cancer andclassify the instances in to respective classes and theit is approximated to be one death in every 4.6
stage of cancer is identified. It also intends to predict
minutes by 2025. Initially precancerous changes are
the stage when a new patient data is given as anseen in the normal cells which later become
input based on the knowledge gained from thecancerous cells. Effect of cancer can be warded off
training phase.
if it is detected in early stage since the growth of thecancer cells takes about 10-15 years. Cervical cancer
LITERATURE REVIEW
can be detected by using a Pap smear, also called a
Pap test. It identifies the abnormality present in theIn [1] the author has used two hybrid steps approachcells. Manual processes of analysis incur a lot of
to attain cell segmentation. Waterfall algorithm wastime and it is tiring to visualize millions of cells. The
used to construct the nested hierarchy. A
probability of sampling errors is high in this case.
Segmentation criterion was used to select the mostThe analysis of Pap smear images of cervicalappropriate hierarchy.
region is based on distribution of the cell nuclei ,In [2] the author proposed a technique to classify theshape and texture features of them. The researchelements present in the Pap smear image using thework intends to classify the instances in to two
Color intensity values. Variational Level Set
classes which are Squamous Cell Carcinoma andFormulationofCurveevolution
without
Adenocarcinoma. This approach uses MATLAB toreinitialization was used to determine the range ofanalyze the Pap smear images. N/C ratio plays acolor intensity values of the cells. The normal cells
vital role in diagnosis of cancerous cells. The
had the color intensity between 122-150. The
nucleus is identified using Contrast adjustment and aabnormal cells had in between 80-100.
number of morphological operations. The
In [3] the author proposed an unsupervised

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technique to detect the overlapping cytoplasm of thecell. H-maxima transform was applied and thebinary image was obtained using the regional
maxima of the image. The cytoplasm was obtainedusing the distance regularized level set model.
In [4] the author proposed a technique to separate
the normal cells from the inflammatory cells andclassify them using the J48 algorithm. The algorithm
considered only 8 features out of 11 for theconstruction of the rules. The classifications were
performed along the different directions.

The system development involves preparing thetraining data and classifying the new instances using
the knowledge derived by the classifier from thetraining phase. The different classifiers like Naïve
Bayes, Multinomial Logistic Regression, Decision
tree, Support vector machine and Random Forest
are used in the proposed work and the one withhighest accuracy is chosen for further steps.
C. Segmentation of Nucleus and Cytoplasm of White
blood cell from Blood smear image with normal
dimension and Feature Extraction.
The following steps are followed to achieve the goalof segmentation and feature calculation:

LIMITATIONS IN THE EXISITING SYSTEM
Determination of stage of tumor at the earliest plays
an important role in the field of medicine. Due to thecomplication of the disease it goes undiagnosed.
Invasive cancer has the ability to spread to regional
the lungs, lymph nodes, the bladder, the liver, thevagina, and the rectum. The delay in the diagnosis
leads to further division of the stem cells which
aggravate the condition. The present procedures
incur a lot of cost and time and are imprecise. The
accurate segmentation of the Pap smear images
cannot be achieved using a single algorithm.

1. Image Pre-Processing:
1.1 Convert the Image to Gray scale:"rgb2gray"function is used to convert the image to gray scale.
It eliminates the hue and saturation information
while retaining the luminance. The conversion isdone as gray scale image is required for further
processing.
1.2 Adjust the contrast of the image: In order toobtain accurate results with images stained withdifferent stains like Haemotoxylin and Eosin andPapanicolaou stain, we have used four different
types of contrast enhancement methods. They are
mentioned below:
1.2.1. Using Histogram Equalization: The histogramof the image is equalized using the "histeq" function.
The contrast of the resulting image is enhanced
using the "imadjust" operation.
1.2.2. Using the stretch limits: The contrast of theimage is adjusted using the “imadjust" function.
The stretch limits used in this research falls in therange of 0.1 to 0.7. This step is undertaken toenhance the quality of the image.
1.2.3. Addition of two channels: The Red, Greenand Blue channels of the RGB image are extracted
individually. The contrast of Red and Green channel
is enhanced using the "imadjust" operation withstretch limits in the range 0.3 to 0.5. The resulting
images are added using the "imadd" operation.
Histogram equalization operation is applied to theresulting image.
1.2.4 Using Local Laplacian Filter: The RGB
image is filtered with an edge aware filter.
Amplitude of the edges is given by the sigma andalpha does the controlling of smoothing of thedetails. In the proposed work sigma value is set as
0.2 and alpha is set as 2. Number of levels is set as
10 while applying the filter. The individual channels
are extracted and green component is chosen forfurther processing.

METHODOLOGY
In the proposed work, the data mining technique isapplied in the health sector. It intends to predict thestage of cervical cancer using Pap smear images. It
identifies if the cell is a normal one or the cancer is a
Squamous Cell Carcinoma or Adenocarcinoma. It
further classifies Squamous Cell Carcinoma in to
HSIL and LSIL. The manual procedure of detectionof status of cancer involves a lot of effort and iserror prone. The results will be highly dependent
upon the physician's skills. A computer aided
automated system would prove to be boon in thisfield.
A. Description of Dataset
In this research work the data set ispreparedby extracting
features from theimages using
image segmentation algorithms.
The Pap smear images are collected from public
image database of Herlev University Hospital,
Denmark with 917 images [5] , Kasturba Medical
Hospital, Manipal-India (6 images) , International
Agency for Research on Cancer [6] and DoveMed[7] (remaining images). The analysis is performedon 1000 images collected from the above data
sources. The features extracted from the images isused to build the training data. The trained model isused to predict the stage of tumor in new cases. In
the proposed work, 25 features are extracted. The
features extracted are given in the Feature extraction
section.
B. System Description

2. Image Segmentation
2.1 Convert the image to binary to obtain the
nucleus: Based on the type of contrast adjustment
technique chosen, the method to convert to binary is384

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

opted. Case 1 is opted when the Histogram
Equalization is used for contrast adjustment. Case 2
is opted when contrast is enhanced using the stretch
limits. Case 3 is opted when the channels are added
to improve the contrast. Case 4 is used when Local
Laplacian filter is used to adjust the contrast.
2.1.1 Case 1: The image is converted to binary
for further processing using a level value 0.37. The
image is complemented to highlight the nucleus.
2.1.2 Case 2: The image is converted to binary
using global Otsu's threshold. The image iscomplemented to highlight the nucleus.
2.1.3 Case 3: The image is converted to binary
using a threshold value of 100. The image iscomplemented to highlight the nucleus.
2.1.4 Case 4: The image is converted to binary
using a threshold value of 90. The image iscomplemented to highlight the nucleus.
2.2. Obtain the Cytoplasm:
In the proposed work two types of images are taken
in to consideration. One with single cell per image
and another with many cells. The work intends toextract the cytoplasm from Pap smear images using
an automated approach. Previous works involved themanual cropping of the images to have one cell per
image. But this work overcomes the drawback byautomating the technique.
2.2.1. Extract cytoplasm when one cell exists per
image: The Original image is converted to gray scale.
The resulting image is applied with the contrast
adjustment to enhance the quality. The image isconverted to binary using the Otsu's threshold. The
noise is filtered by applying a median filter value
with 15*15 neighborhood. The unwanted small
particles in the image are separated by choosing avalue of 4000. The values used for filtering of noiseand morphological open operation are chosen after
analyzing over a number of images.
2.2.2. Image with Clustered cells: In this research
work an automated approach for cropping of thecells is specified. The procedure is specified below:

with width and height as .
4.4. Adjust the contrast of the image using the“imadjust” function.
4.5. Equalize the image using the “histeq” function
and convert it to binary with a level value of 0.65.
4.6. Fill the holes and use an area open function
with value of 70.
End For.
Area of extracted cytoplasm is calculated using the“regionprops” function.
3. Image Post-processing:
3.1. Separate the touching objects using theWatershed transform:
The Nucleus extracted from the images will betouching each other. Touching cells if not separated
generate inaccurate results. Watershed transform of
the distance transform is calculated. The ridge lines
obtained are used to segment the binary image. The
existing Watershed algorithm faces the problem ofover segmentation. So, we modify it. Tiny local
minima are eliminated using the function"imextendedmin" . Distance transform is thenmodified so that no minima occur at the filtered out
locations using the function "imimposemin" .
Watershed is applied again to the resulting image.
After the above operation, the touching objects will
be clearly separated.
D. Feature extraction
The texture and shape features are calculated for theobjects in the image using "region props" function.
These features help the doctor to differentiate acancerous cell from a non-cancerous one and also
identify in to which category the tumor falls. The
features extracted are as follows:
1. Shape Features:
1.1 Eccentricity: It specified how much a shape of a
nucleus deviates from being circular. The abnormal
cells will have higher eccentricity due to abnormal
bulging.
1.2 Centroid: Represents the center mass of theregion.
1.3 Orientation: Angle between the x-axis and the
major axis of the ellipse that has the same secondmoments as the region.
1.4 Major Axis length: Gives the length of the
major axis of the ellipse. The normal cells will avalue below 30 and the abnormal cells will have avalue above 30.
1.5 Area: Actual number of pixels in the region.
1.6 Solidity: Ratio between area and convex area.
1.7 Equivalent Diameter: Diameter of a circle withthe same area as the region. The value for normal
cells will be below 20. The cancerous cells will havea value above 20.
1.8 Perimeter: Specifies the distance around theboundary of the region. The perimeter of normal
cells will be below 100. The cancerous cells will

Algorithm 2: Pseudo code for the extraction of
Cytoplasm from Pap smear image
Input: Image of the Pap smear
Output: Extracted Cytoplasm.
1. Convert the RGB image to Gray Scale
2. Obtain the image of the nucleus obtained from thenucleus extraction stage.
3. Obtain the boundary of the image using the“bwboundaries” function.
4. for 1 to NumberOfBlobsdo
4.1. Obtain the X and Y coordinate value.
4.2. Compute the minimum value of x and ycoordinate.
4.3. Use the ”imcrop” function with the cropping
rectangle’s x coordinate as minimum x value minus
10 and y coordinate as minimum value minus 15

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have a value above 100.
1.9 Minor axis length: Gives the length of the minor
axis. The normal cells will a value below 20 and theabnormal cells will have a value above 20.
1.10 Form factor: The ratio between Area andperimeter. The Eq. (1) gives the Form factor value.

4. Fractal Dimension
4.1 Hausdorff Dimension: It is a quantity thatindicates how completely a fractal appears to fillspace. Box counting algorithm is used here. In box
counting algorithms, the number of boxes covering apoint set is a power law function of the box size.
They indicate the roughness of the object. The
Hausdorff dimension of a cancerous cell will be
above 1. Normal cells will have a value below 1.

𝑭𝒐𝒓𝒎 𝑭𝒂𝒄𝒕𝒐𝒓 = (𝟒 ∗ 𝒑𝒊 ∗ 𝑨𝒓𝒆𝒂)/(𝑷𝒆𝒓𝒊𝒎𝒆𝒕𝒆𝒓 ∗𝑷𝒆𝒓𝒊𝒎𝒆𝒕𝒆𝒓) (1)E. Data Pre processing
Data preprocessing plays an important role in thedata mining process. Usually the process ofgathering data involves many errors, resulting in
out-of-range values, impossible values. This stage
plays a very important role in getting the accurate
results.
F. Feature Selection
Feature selection methods can be used to achieve
efficient data reduction. In this research work, thesubset of attributes is assessed using the
InfoGainAttributeEval and the Ranker Searchmethod is used. The attributes such as the cell id
Centroid, Orientation which do not contribute to theclassification are eliminated.
G. Classification and Prediction of unknown classlabel
The classification algorithm is used to classify thedata into groups. At the initial stage the training data
set is used to train the classifier and then the test data
is used to test the accuracy of the classifier algorithm.
In this research work the classification algorithm
classifies the instances of cervical cancer in to
Adenocarcinoma/Squamous carcinoma/Normal cell.
In the proposed work, Random forest algorithm isused for classification. The accuracy of thealgorithms is compared. It was found that Random
forest outperformed other algorithms. It operates byconstructing large number of decision trees attraining time and predicts the unknown class labelsat the prediction stage.

1.11 Roundness: Measure of how closely the shapeof an object approaches that of a circle. Cancerous
cells will have a roundness value above 12.
1.12 Radius: Measures the radius of the cells.
1.13 Elongation: Specifies the lengthening of a cell
during the cell differentiation process. Cancerous
cells will have a elongation value above 2.
1.14 Cytoplasm Area: Measures area of thecytoplasm which is used in calculating the N/C ratio.
1.15 N/C ratio: Specifies the ratio between the areaof the nucleus and cytoplasm.
2. Pixel Value Measurements
2.1. Maximum Intensity: Specifies the value of the
pixel with the largest intensity in the region. Normal
cells will have a value below 200. Abnormal cells
will have a above 200.
2.2 Minimum Intensity: Specifies the value of the
pixel with the smallest intensity in the region.
Normal cells will have a value below 150. Abnormal
cells will have a above 150.
3. Texture Features
3.1 Entropy of the image: It measures therandomness that can be used to identify the textureof the input image. Cancerous cells will have a value
above 1.
3.2 Contrast of the image: Measures the intensity
contrast between a pixel and its neighbor over thewhole image. Normal cells will have a contrast
value below 0.1 and cancerous cells will have avalue above 0.1
3.3 Correlation of the image: Returns a measure of
how correlated a pixel is to its neighbor over thewhole image. Normal cells will have a value above
0.5 and cancerous cells will have a value below 0.5.
3.4 Energy of the image: Specifies the uniformity of
the image. Normal cells will be more uniform than
the abnormal cells. Abnormal cells will be non
uniform due to bulging. It is computed using the Eq.
(2). Pi and Pj represent the marginal probabilities.
𝜮𝜮𝒑(𝒊, 𝒋)2 (2)3.5 Homogeneity: Measures the closeness of the
distribution of elements in the GLCM to the GLCM
diagonal.
3.6 Contrast of the nucleus: It is the measure of theamount of local variations present in the image.
Adenocarcinoma cells will have a value below 0.5
and Squamous cells will have a value above 0.5.
3.7 Difference Entropy: Returns the difference
between the entropy values.

RESULTS & DISCUSSION
The results obtained after the application ofsegmentation algorithm over the Pap smear images
is discussed here. Table 1 shows the confusion
matrix obtained using the Random forest algorithm.
A indicates Adenocarcinoma instances. B indicates
Normal instances. C indicates instances of High
grade Squamous epithelial lesion. D indicatesinstances of Low grade Squamous epithelia lesion.
Each instance indicates the cell present in the image.
The Random forest classified the instances with 100
percent accuracy. Fig.1.–Fig.8. represents theimages used to test the accuracy of the proposed
work. Fig.4. represents the box plot. Test images aredifferent from the images that are used for training.
The features of the cells present in the image were386

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

extracted and were given as input to Random forest
algorithm for prediction. The input file was fed inform of ARFF (Attribute-Relation File Format). The
Random forest algorithm predicted the stage by
utilizing the knowledge gained from training model.
The diagnosis done by the proposed system iscompared with diagnosis done by experts. The
evaluation done by experts is specified by DoveMed
and International Agency for Research and Cancer(IARC). DoveMed is a health portal with medical
content that is trusted by the physicians. IARC
provides the classification of human tumors thathelps in the cancer research. In the proposed work ,a counter is set to count the number of cells fallingunder each category. This counter helps in
identifying the final stage of tumor. The stage oftumor is declared to be in HSIL stage , if even one
cell in the image is predicted as HSIL. It is done toprevent any risks as HSIL is dangerous. Fig.9.
depicts the extraction of Cytoplasm from a normal
Pap smear image when there is one cell per image.
Fig .10. depicts the extraction of cytoplasm from an
instances of High grade intra epithelia lesion byusing the automated cropping technique. Second
object is extracted from the labeled image obtainedusing case 1. Fig.11. Represents the cells extracted
from the normal, Squamous cell carcinoma andAdenocarcinoma category. Significant feature values
that helps in differentiating Normal, SCC andAdenocarcinoma is tabulated in Table 2.

MatrixA
B
C
D

Fig.3. Img_003 Depicts the image of the nucleus
extracted from Squamous cell carcinoma using thecontrast stretch operation with the stretch limits andbinary conversion as in case 2.

Fig.4. A. Box plot of Normal cell. B. Box plot ofCancerous cell

Table 1. Confusion Matrix
A
B
C
D
251
0
0
0
0
888
0
0
0
0
479
0
0
0
0
196

Fig.5.
Img_004 Depicts the image of the nucleus extracted
from Adenocarcinoma using the addition of twochannels and binary conversion as in case 3.

Fig.6. Img_005 Depicts the image of the nucleus
extracted from Squamous cell carcinoma using theFast Laplacian filter and binary conversion as incase 4.

Fig.1. Img_001 A. Input Image, B. Histogram
Equalized Image, C. Binary Image, D. Image having
nucleus after processing and labeling operation.

Fig.2. Imag_002 A. Input image. B. Extracted andlabeled nucleus.
Fig.7. Img_006 Depicts the image of the nucleus
extracted from LSIL (Squamous Cell Carcinoma)

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SEE -USQ, Brisbane, Australia, Nov.13-16, 2017using theaddition of two channels and binary
conversion as in case 3.

3
77
7
49
0
HSIL
HSIL [8]
4
0
0
78
54
Adeno
Adeno [9]
5
12
9
36
0
HSIL
HSIL [8]
6
0
38
2
0
LSIL
LSIL [10]
7A
0
1
1
0
LSIL
LSIL [10]
7B
1
1
2
0
HSIL
LSIL [10]Table 3 gives the count value of the cells present inimages used for testing. The stage predicted by the
Random forest algorithm is compared with theground truth. In the proposed work, one instance of
LSIL is misclassified as HSIL (Img_007B). C andD denote HSIL and LSIL. B and A denote normal
cells and Adenocarcinoma cells. C5 denotes theprediction done by the system. C6 denotes groundtruth. The misclassification is due to the minute error
in the stage of segmentation. The LSIL cells have
low grade changes that make it to look like a normal
cell. In some cases, the LSIL cells will have areactive change, which makes it to look like HSIL.
The accuracy is computed by comparing the results
predicted by the proposed system with the groundtruth. The proposed work achieved an accuracy of
87.5 percent for these test images, as it misclassified
one instance of LSIL as HSIL.

Fig.8. Img_007 Depicts pap smear images of LSIL
(Squamous Cell Carcinoma) .

Fig.9. A. Input image. B. Labeled Nucleus. C.
Contrast adjusted image. D. Extracted cytoplasm.

CONCLUSION
The main aim of this work is to accurately segment
the Pap smear image to obtain its components. After
performing a survey, we identified that accuratesegmentation of the image cannot be done withsingle segmentation algorithm. A combination ofalgorithms is required to achieve precise
segmentation. Texture, shape and visual features are
extracted to differentiate between different
categories of cervical cancer and normal cell. A
comparison is done between supervised learningalgorithms and the one with highest accuracy.
Random Forest was found to outperform otheralgorithms. The work achieved an accuracy of 87.5
percent in successfully
identifying the stage oftumor in new patients when it was compared withclinical results (Ground truth).

Fig.10. A. Input Image. B. Cropped Image. C.
Contrast Adjusted Image. D. Binary Image of the
Cytoplasm.

Fig.11. A. Normal cell. B. Squamous cell. C.
Adenocarcinoma cell.
Table 2. Values of some significant features
Feature
Ncell
Scell
Acell
0.64579
0.620864
0.70152
Eccentricity
Form factor
Elongation
N/C ratio
Diff Entropy
HausdorffI
12

1.00190
1.50555
0.21504
0.165040.51250.534535
2.08796
1.907773
0.37083
1.1492

REFERENCES[1] Mingzhu Zhao, Lei Chen, L. B. J. Z. C. Y. andZhang J., “Feature quantification and abnormal
detection on cervical squamous epithelial cells,”
Computational and Mathematical Methods in
Medicine, vol. 2015, no. 2015, 2014, pp.1–9.
[2] Happy S. L., Chatterjee S., and Sheet D,“Unsupervised segmentation of overlapping cervicalcell cytoplasm,”CoRR, vol. abs/1505.05601, 2015.
[3] Eko Supriyanto, Nur Azureen M. Pista, L. H.
I. B. R. and Mengko,“Automatic detection
system of cervical cancer cells using color

0.86057
4.02783
0.61690
1.024411.2122

Table 3: Count of cells present in the test images.
C
D
B
A
C5
C6
46
6
20
0
HSIL
HSIL [8]0010Normal Normal [5]388SEE -USQ, Brisbane, Australia, Nov.13-16, 2017

intensity classification,” in Proceedings of the 15th
WSEAS Int. conf.on Computers, 2011, pp. 303–307.
[4] Dwiza Riana, D. H. W. and Mengko T. L.,“Extraction
andclassification texture of
inflammatory cells and nuclei in normal pap smear
images, “in 4th Int. Conf. on Instrumentation,
Communications, Information Technology, andBiomedical Engineering, November 2015, pp. 65–69.
[5] Pap Smear dataset. [Online]. Available
http://mde-lab.aegean.gr/index.php/downloads.
[6] Pap Smear images.[Online]. Available:
http://screening.iarc.fr/atlascyto.php?lang=1[7] Pap Smear images. [Online]. Available:
http://www.dovemed.com/diseasesconditions/squamous-cell-carcinoma-of-cervix/[8] Diagnosis done by experts.[Online]. Available:
http://screening.iarc.fr/atlascyto_list.php?cat=F1c2&
lang=1[9] Diagnosis done by experts.[Online]. Available:
http://screening.iarc.fr/atlascyto_detail.php?flag=0&
lang=1&Id=cyto6185&cat=F2b.
[10] Diagnosis done by experts.[Online]. Available:
http://screening.iarc.fr/atlascyto_list.php?cat=F1b&l
ang=1

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Environment

390

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

NUTRIENT LOADS AND SELF-REMEDIATION ASSESSMENT INKHLONG RUNGSIT TAI, PATHUM THANI PROVINCE, THAILAND
1

Boontarika Thongdonphum1, Kittima Vanichkul 2, Saming Champasri3 and Jirapon Kulkham4
Faculty of Agricultural technology, Rajamangala University of Technology Thanyaburi, Thailand

ABSTRACTThe aim of this work was to investigate on the aquatic environmental factors and nutrients transfer patterns.
The aquatic environmental impacts assessment was conducted based on analysis water quality of the Klong
Rungsit Tai, Pathum Thani Province, Thailand of 6 sampling stations surveyed during September 2014 andMarch 2015. The results showed that aquatic environmental factors varied by season. The results indicated thatammonium-nitrogen (NH4+-N), nitrite and nitrate-nitrogen (NO2-+NO3--N), and orthophosphate phosphorus(PO43--P or P) concentration ranged between 10.79-85.35 M, 56.70-135.79 M and 0.74-5.66 M, respectively.
Analysis of the dissolved inorganic nitrogen (DIN) and P transfers patterns showed that self-remediation wererarely found in dry season. Levels of DIN and P load ranged between [5.05 and 0.40 tonne/day] and [5.12 and0.32 tonne/day] in September 2014 and March 2015, respectively. The positive relative remediation efficiency(EFR) for DIN and P were highest in September 2014. The EFR for DIN and P were [39.60%] and [12.82%],
respectively. The negative EFR were found in March 2015, indicating that input loads were higher than output
loads. The whole results have revealed that water mass transfer direction and water drainage affected to selfremediation and accumulation of nutrients in the study area.
Keywords: Nutrient loads, Self-remediation, Aquatic environmental factors, Dissolved inorganic nitrogen,Orthophosphate phosphorus

anthropogenic factors such as land use, urbanization,
sewage discharge, and nonpoint sources like stromwater runoff and runoff from agricultural and urban
areas [9]. Thus, this research aimed to assess theimpacts of nonpoint sources nutrient loads, together
with the nutrient transfer patterns in the impacted
site. The findings could subsequently be used toestablish a better management of water resources inthis area.

INTRODUCTION
Klong Rangsit Tai is the part of Klong Rangsit
Prayurasakdi, as known Klong Rangsit or Rangsit
canal, is located at Rangsit, Pathum Thani Province,in the eastern part of Chao Phraya River, centre ofThailand ]1 [. Runs from Thung Luang, Pathum
Thani Province and flows toward into the Nakhon
Nayok River. Klong Rangsit is approximately 54
kilometre in length [2]. Land utilization have been
discussed as urbanization, agriculture, aquaculture,and industrial purpose [3]. Its has long been known
that changes of river flow could impact biochemicalcomposition, including nutrient loading, in the riverand thereby phytoplankton abundance [4].
Here, the Klong Rangsit supports a resident
population about 1,010,898 people (662.51 people
per square kilometer) that related to the deteriorationof water quality induced mainly by sewage,
domestic discharges, and agricultural utilization [5].
In [6], reported that water quality in the urbanization
area were deterioration. Increasing of urbanization,industrial and agricultural developments, andinadequate sewerage system had contributed
material inputs in to the water resource [7].
Pollution problems can occur according tountreated municipal and industrial wastewater,
eutrophication, trace metals contamination andpetroleum hydrocarbon [8]. River water chemistry iscontrolled by natural factors, rainfall, and

MATERIALS AND METHODS
Sampling sites
The surveys were conducted at 6 samplingstations (stn.) at Klong Rangsit Prayurasakdi,
Rangsit, Pathum Thani Province, the stations ofwhich nearly the residential areas, spanning from
September 2014 to March 2015 (Fig.1). According
to the rainfall patterns, Thailand is under the
influence of monsoon winds [10]. The seasons canthus be divided into rainy season (May-September),
winter season (October-February), and dry season(March-April). In addition, large amounts of water
typically flow into the this area depends on the Chao
Phraya River flows and is the head works of theSouth Rangsit Irrigation Office which diverts anddistributes water to about 0.7 million rai (1 ha = 6.25
rai) [6]. Water samples from the 6 stations werecollected during the two seasonal periods for the 2391

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

year interval such that all possible loading periods
were taken into consideration.

environmental variation comparison, and the level ofconfidence greater than 95% (p0.05) was
considered to indicate a statistically significant
impact. The relative remediation efficiency (EFR) of
each station was approximated using equation (2);
EFR (%) = [(Input-Output)/Input] x 100(2)

where: Input and Output are amounts of DIN or
P that transferred into and out of each section,
respectively.
RESULTS
Fig. 1 Sampling stations (Stn. 1-6) and 3 crosssectioned sites located at Klong Rangsit
Prayurasakdi, Pathum Thani Province, Thailand.

Table 1 tabulates the results of water quality
during study period. Water temperature and salinity
varied slightly with seasons (p0.05) and tend to
decrease in dry season. The pH level was found to
be relatively constant for the entire study area, while
DO varied and markedly decreased to unsuitablelevels (<4 mg/l) in during study period. The levels of
NH4+ and NO2-+NO3- varied significantly (p0.05)
with seasons. The concentrations of NH4+ and NO2+NO3- varied from 10.79 to 85.35 M and 1.87 to
135.79 M, respectively. High of NH4+ levels wererecorded during the survey in September 2014,
while NO2-+NO3- level were found during in March2015. PO43- levels ranged from 0.74 to 5.66 M.

Sample collection and analysis
Temperature, dissolved oxygen (DO), salinity,and pH, were measured with a multi-parameterprobe (YSI-6600 Sonde instrument) at the samplingsites. At each stations, surface water (30 cm deep)
samples for nutrient analysis were pre-filteredthrough GF/F (Whatman) and then stored at 4oC
before transporting to the laboratory. Ammonium(NH4+), nitrite and nitrate (NO2-+NO3-), andorthophosphate (PO43-)
concentrations
weredetermined using a SKALAR segmented flow
analyzer.

Table 1 The water quality (mean±SD) at Klong
Rangsit Prayurasakdi during the study
period.

Nutrient transfer analysis
To assess nutrient transfer was conducted for 3
selected cross-sectioned sites (Fig 1), which were
calculated with a two-dimensional Surfer model.
Water mass and nutrient transfer were determined as
dissolved inorganic nitrogen (DIN; NH4++NO2+NO3-) and orthophosphate phosphorus (P; PO43-)
based on the nutrient balance method. The amountof nutrient loads were estimated using equation (1);Mi = 8.64x10-7[Conc]AiUhiΔti

Parameters
Temp (oC)DO (mg/L)
Salinity (psu)pH
NH4+ (M)
NO2-+NO3- (M)
PO43- (M)

Study period
September 2014
March 201531.43±0.09a
30.07±0.05b
0.75±0.35a
2.90±0.61ba
0.27±0.01
0.17±0.01b
7.40±0.12a
7.50±0.08aa79.99±4.33
27.73±24.66b
5.21±5.08a
90.52±29.42ba3.94±1.37
2.20±1.42a

Note: The mean values in the same row withdifferent superscript letters are significantly different(p0.05).

(1)

where: Mi = amount of each nutrient load
(tonne/day), [Conc] = concentrations of DIN or P
(g/L), Ai = cross-sectional area (m2) of section I,
Uhi = flow velocity (cm/s) passing through section I,
and Δti = time under a focus period (1 day) in sectioni [11].

Nutrient transport analysis was performed in therainy and dry period for representing loading
amounts in the area. Here, the water volume passed
through 3 representative cross-sectioned sites andcurrent velocities are shown in Table 2. The highest
inflow volume and velocity were found at the stn. 4
of 4.84x106 tonne/day and 50.31 cm/s, respectively.
On the contrary, the lowest load and velocity of 0.91
x106 tonne/day and 10.06 cm/s, respectively, were
found at the stn. 2.

Data analysis
Comparisons of water quality in terms oftemperature, salinity, DO, and pH between thesampling periods were performed using descriptive
statistic as average levels and distribution
characteristics. T-test was used for the392

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

Table 2 Water volume (x106 tonne/day) andvelocity (cm/s) of each section during rainy
and dry period at the sampling site.
Section area(m2)

Volume(10 tonne/day)6% remediation efficiency

Station(Sectione
d codes)100.00Velocity(cm/s)

September 2014

Marc
h
2015

September 2014

Marc
h
2015

0.00

-100.00

DIN
P
R2>R1

-200.00

2 (R1)

105.24

2.68

0.91

29.44

10.06

-300.00

4 (R2)
6 (R3)

111.28
98.61

4.84
2.81

1.66
3.49

50.31
32.95

17.28
40.95

-400.00

R3>R2

(a)

R1>R2

(b)

R2>R3

Cross-sectioned site

Fig. 3 The relative remediation efficiency (%) of
DIN and P during (a) September 2014 and (b) March
2015.

Nutrient load estimation in the area indicated that
DIN and P loads varied from 1.48 to 5.12 and 0.05
to 0.40 tonne/day, respectively. The highest of DIN
was found at the R3 sectioned site during March
2015, while the highest of P load was located in R3
sectioned site during September 2014.

DISCUSSION
The general of water quality varied by season.
Results showed the slightly changed of temperature,salinity, and pH, which were almost constant for theentire area. Freshwater inflow and precipitationinduced drainage influenced the level salinity [4].
Dissolved oxygen were low and showed theunsuitable levels (<4 mg/l) for the living of aquatic
animal [12], which was probably the result ofbacterial decomposition of organic waste matter [4].
High nutrients concentration were apparent,
reflected that the anthropogenic contamination
because high population density and land use area
are located near the water bodies. In [13], reported
that nutrient loading in the river is controlled bynatural and anthropogenic sources as runoff fromurban areas, crop cultivation, and inflow throughorganic rich ground. NH4+ is the important factor
for water quality assessment that could be indicatedthe major anthropogenic and natural sources [14]. In[15], reported that NH4+ levels in the water bodies
should detect less than 1 mg/L (71.4 M). Different
nitrogen transformations may permanently occur inriver floodplains and ecotones of the river bed andmay involve several microbiological processes [16].
PO43- levels showed noticeably higher levels than
the recommended level of 1 M that could cause
eutrophication problems [4].
DIN and P loads revealed the impact ofanthropogenic activity, water flow characteristics
affected the water quality in the study area. Basewater flow is a potential source of river nutrient, canprovide dilution and enhance the transportation
process through nutrient in base flow is from land
use through leaching process, its efficiency could besignificant physical function on self-remediation of
the river ecosystem [11],[13]. Changes of land use
could be leading to nitrogen enrichment in the river[17]. Relative remediation efficiency (EFR) analysisof the area were almost negative EFR, indicating that

(a)

(b)
Fig. 2 DIN and P transport (tonne/day) in eachcross-sectioned sites during (a) September 2014 and(b) March 2015.
Analysis of relative remediation efficiency (EFR)
showed positive values only in the sections of R2 to
R1 during rainy season. The EFR in those area for
DIN and P were [39.60%] and [12.82%],
respectively. The other sectioned sites showed thenegative values that reflected the level of Input loads
were higher than the Output loads (Fig.3)

393

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

application of spatially explicit nutrient export
models”, Harmful Algae, Vol. 8, 2008, pp.33-38.
[8] Cheevaporn V & Menasveta P, “Water Pollution and
Habitat Degradation in the Gulf of Thailand”, Marine
Pollution Bulletin, Vol. 47, 2003, pp. 43-51.
[9] David SE, Chattopadhyay M, Chattopadhyay S &Jennerjahn TC, “Impact of human interventions on
nutrient biogeochemistry in the Pamba River, Kerala,
India”, Science of the Total Environment, Vol. 541,
pp. 1420-1430.
[10] TMD, “Climate of Thailand”, Thai Meteorological
Department, Thailand,assessed :https://www.tmd.go.th/info/info.php?FileID=53 (April 4, 2017)[11] Thongdonphum, B, Meksumpun, S & Meksumpun C,“Nutrient Loads and their Impacts on Chlorophyll ain the Mae Klong River and Estuarine Ecosystem: An
Approach for Nutrient Criteria Development”. Water
Science and Technology, Vol. 64(1), 2011, pp. 178188.
[12] Pollution Control Department, “Water quality
standard”, assessed :http://www.pcd.go.th/info_serv/reg_std_water06.html(March 20, 2016)[13] Xia Y, Ti C, She D & Yan X, “Linking river nutrient
concentrations to land use and rainfall in a paddy
agriculture-urban area gradient watershed insoutheast China”, Science of the Total Environment,
Vol. 566-567, 2016, 1094-1105.
[14] Wang S, Lu A, Dang S & Chen F, “Ammonium
nitrogen concentration in the Weihe River, central
China during 2005-2015”. Environmental
Earth Science, Vol. 75, 2016, 512.
[15] PHILMINAQ, “Water quality criteria and standards
for freshwater and marine aquaculture. Mitigating
impact from aquaculture in Philippines”. assessed :https://www.researchgate.net/file.PostFileLoader.htm
l?id=571b93653d7f4b012861d0a1&assetKey=AS%3
A354056255098880%401461424997739. (Mar 2,
2016)[16] Kiedrzyńska E, Kiedrzyński M, Urbaniak M,
Magnuszewski A, Skłodowski M, Wyrwicka A &Zalewski M, “Point source of nutrient pollution in thelowland river catchment in the context of the Baltic
Sea eutrophication”, Ecological Engineering, Vol. 70,
2014, 337-348.
[17] Li R, Liu S, Zhang G, Ren J & Zhang J,“Biogeochemistry of nutrients in an estuary affectedby human activities: the Wanquan River estuary,
eastern Hainan Island”, China, Continental Shelf
Research, Vol. 57, 18-31.
[18] Álvarez-Vázquez MA, Prego R, Ospina-Alvarez N,
Caetano M, Bernárdez P, Doval M, Filgueiras AV &Vale C, “Anthropogenic changes in the fluxes toestuaries: Wastewater discharges compared with riverloads in small rias”, Estuarine, Coastal and Shelf
Science, Vol. 179, 2016, 112-123.
[19] Markogianni V, Varkitzi I, Pagou K & Dimitriou E,“Nutrient flows and related impacts between a
Mediterranean river and the associated coastal area”.
Coastal Shelf Research, Vol. 134, 2017, 1-14.

Input loads were higher than Output loads [11],reflected the high level of anthropogenic inputs fromdispersed sources as fertilizers or point sources as
wastewater facilities have altered the land-sea fluxes[18] and disturb the balance of the water ecosystem[19].
CONCLUSION
The general of water quality, namely dissolved
oxygen could be reflected to water resource
deterioration in this area. Levels 0f DIN and P loads
were high in the rainy season, 5.05 tonne/day and0.40 tonne/day, respectively. Based on EFR
estimation of DIN and P revealed that the level of
Input loads were higher than the Output loads. The
research finding showed that water mass direction
effected to water drainage, nutrient dilution, andnutrient accumulation in the area.
ACKNOWLEDGEMENTS
The authors would like to extend deep gratitude
to the Faculty of Agricultural Technology,
Rajamangala University of Technology, Thanyaburi(RMUTT) for the financial support.
REFERENCES[1] Pathum Thani Office Center, “Development Plan of
Pathum Thani Province”, assessed :http://www2.pathumthani.go.th/551017.pdf. (April 3,
2017)[2] RIO 11, “Data project”. South Rangsit Irrigation
Project, Regional Irrigation Office 11, Royal
Irrigation Department , Ministry of Agriculture andCooperatives, assessed :http://ridceo.rid.go.th/pathum/rangsits/Data.html(Aug22, 2012)[3] Thongkumpow J & Sumpanpanit P, “Water use
patterns of the irrigation area in Klong Rung Sit Tai”,
Environmental research institute, Chulalongkorn
university intellectual repository, 1997.
[4] Thongdonphum B, Meksumpun S, Meksumpun C,
Sawasdee B & Kasemsiri P, “The Predictive Modelfor Biochemical Component of Phytoplankton in theRiver and Estuary System of the Mae Klong River,
Thailand”, International Journal of Environmental
and Rural Development, Vol. 4-1, 2013, pp. 13-18.
[5] REO 6, “Environmental Status in the Western
Report”, 2011, Ministry of Natural Resources andEnvironment, Thailand.
[6] RIO 11, “Data project”. South Rangsit Irrigation
Project, Regional Irrigation Office 11, Royal
Irrigation Department , Ministry of Agriculture andCooperatives,
assessed:
http://ridceo.rid.go.th/pathum/rangsits/Data.html(May 2, 2017)[7] Glibert PM, Mayorga E & Seitzinger S,“Prorocentrum minimum tracks anthropogenic
nitrogen and phosphorus inputs on global basis:394

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

INFLUENCE OF ABIOTIC STRESS FACTORS ON BLACKCURRANTRESISTANCE TO PESTS
I.V. Mashkova1, T.G. Krupnova2, A.M. Kostryukova3

1Chemistry Department, South Ural State University, Russia

ABSTRACTBlackcurrant is one of the valuable berries of a temperate zone. Lampronia Capitalla Cl. is an extremely
dangerous pest of blackcurrant in South Ural. Abiotic stress factors can significantly reduce blackcurrant
resistance to L. capitella Cl. We studied blackcurrant in two areas and in laboratory. The first area isexperimental and belongs to a horticultural selection station. It is situated close to the residential area, and a busy
motorway is just 100 m from the selection station. The second area is presented by 5 private household plots inan environmentally clean area, far from the city and motorways. We noted that, in the horticultural selection
station, L. capitella Cl. population explosion was often in three times more, than in the household plots. We
registered the formation of specific complexes of leaf-eating micro-lepidopterans (entomocomplexes) inanthropogenically polluted air. The study of entomocomplexes is the framework of the research of the influenceof temperature stress factors on blackcurrant resistance to L. capitella Cl. We compared the growth of
L. capitella Cl larvae in nature and in the laboratory at different temperatures. The experiment lasted for 7 days
at +25 °С in the laboratory, and for more than 13 days at daily average temperatures of +9.7 °С, +14 °С,+15.1 °С private household plots. We discovered that larvae’s harmfulness increases at the temperature lower
than +25 °С.
Keywords: blackcurrant, Lampronia Capitella Cl.., Coefficient of Assimilation of Food, Abiotic Stressincreasing crop production for future food security[6]. It was shown [7] that global climate change canaccelerate the breakdown of crop resistance to insect
pests. It is anticipated that global climate change
could lead to increases in the incidence of
blackcurrant through increased overwinteringsurvival and longer seasonal activity L. capitella Cl.
There are scientific studies that allow us toevaluate varieties of black currant in respect of theiryield, the quality of berries and resistance to pests[8]. Moreover, changes in management practices
such as increased cropping densities and machine
harvesting could lead to pest outbreaks throughoptimal microhabitats and increased susceptibility topest colonization. It is important to consider future
management options with an emphasis on integrated
approaches to pest management, including s
biocontrol and plant resistance enhancement throughbreeding [9].
The natural environment for plants is composedof a complex set of abiotic stresses and biotic
stresses. Plant responses to these stresses arecomplex. While it is difficult to get accurate
estimates of the effects of abiotic stress on crop
production, it is evident that abiotic stress continues
to have a significant impact on plants [10, 11].Thelevel and duration of stress (acute vs chronic) canhave a significant effect on the complexity of theplants response [12, 13]

INTRODUCTION
Blackcurrant is rich in vitamins and bioactive
substances [1–4]. It is one of the valuable berries ofa temperate zone. Blackcurrants are an important
berry crop in many European countries [5]. There isincreasing demand for new and economicallyvaluable blackcurrant cultivars suitable for organic
production. In recent years, there have beensignificant changes in the methods of berries crops
in some parts of Europe. Now, most blackcurrants
are concentrated in central, east and south-eastern
Europe where growing method relies on “traditional”
open-field production systems [5].
Blackcurrant are attacked by a wide range ofinsect and mite pests that can reduce quality, yield or
have phytosanitary implications in propagation andplant exports. Many of the insects and mites colonise
specific to them small fruits. So, specific insect
control strategies must be developed [5]. To date,research into insect pests blackcurrants has been
fragmented, with little appreciation of how changes
in climate and agronomic practices affect biology. It
is very important to concentrate on enhancing
natural plant resistance to some of important pests
and diseases.
Lampronia capitalla Cl. is an extremely
dangerous pest of blackcurrant in South Ural.
Predicting how insect crop pests will respond to
global climate change is an important part of395

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

Abiotic stress is defined as environmental
conditions that reduce growth and yield below
optimum levels [14, 15]. With long-term stress,
photosynthesis declines due to stomatal limitations
for CO2 uptake and increased photoinhibition fromdifficulties in dissipating excess light energy [13]Abiotic stress factors can significantly reduce
blackcurrant resistance to L. capitella Cl. There islittle and very old published literatures onblackcurrant pest L. capitella Cl.
The aim of the present paper was to investigate
the influence of abiotic stress on the resistance of
blackcurrant to the pest L. capitella Cl.

experiment did not consider the first larval instars as
they feed in berries, and they have a direct impact on
the black currant crop. For second, third and fourth
instars larvae we studied food assimilation. We
weighed the original amount of food, the remaining
amount of food and excrements. The coefficient offood assimilation, C was calculated according to theequation:C( M f  M e )  100%,
Mf
where Me – larva excrement mass (mg), Mf – massof food eaten (mg).

METHODSRESULTS AND DISCUSSION

The Conditions of Blackcurrant Cultivation
Investigated in the present work, the blackcurrant
were grown under three conditions: (1) laboratory,(2) natural conditions, area 1, (3) natural conditions,area 2. Area 1 is experimental and belongs to ahorticultural selection station. It’s situated close to
the residential area, and a busy motorway is just 100
m from the site. Area 2 is presented by 5 privatehousehold plots in an environmentally clean area far
from the city and motorways.
Examining the Growth of L. Capitella Cl. Larvae
We compared the growth of larvae: (1) in natureand (2) in the laboratory at different temperatures.
In the nature we studied the growth of the larvae
as follows. We made 5 frameless mesh cagesisolators on a branch of a currant, which wascontained some of the kidneys. We placed 2 larvaein each mesh cage-insulator (in total, there are 10
larvae). Mesh cage did not allow the larvae to spread,but larvae could move from the kidneys to thekidney. Larvae took more than 13 days in natural
conditions at the average day temperatures of+9.7 °C, +14.3 °C, +15.1 °C. The larvae were
weighed when they left the buds, and therefore at the
air temperature of +9.7 °C in natural conditions thesecond larval instars were weighed twice, not once,
for the first two days of their development. When
weighing the larvae, biology of L. capitella Cl.,
experimentally confirmed, was taken into account.
In the laboratory, we used 5 Petri dishes for each,and 2 larvae in a Petri dishes (total 10 larvae). The
laboratory experiment was conducted for seven days
at air temperature of +25 °C, air humidity of 70–75 %with a ten-hour daylight.
Food Assimilation by L. Capitella Cl. Larvae
Larvae of L. capitella Cl. have 4 instars.
According to the conventional approach, the numberof instars equal to the number of molts. The
396

The results of five years of research showed thatthe population of L. capitella Cl. increases faster in
Area 1 (the horticultural breeding stations), where
blackcurrant is a monoculture and grows under the
influence of abiotic stress. In laboratory conditions,
populations of L. capitella Cl. behaves the same.
This is because in a laboratory population of
L. capitella Cl. was kept on injured branches currant,
who have reduced defense mechanisms. In Area 2(private farms) the number and activity of the pest
was much smaller than in Area 1, in conjunction
with other types of plants. It is located in an
ecologically clean area far away from cities andhighways.
Insects are poikilothermal with their bodytemperature depending on that of the surroundings.
Insects’ activity rhythm is directly connected withthe changes of the surroundings [16]. Their rhythmof life can differ in different points within the same
space. Since they can differ in microclimaticconditions [17, 18]. For instance, temperaturechange influences the feeding intensity of insects
including Lampronia capitella Cl. Further, feeding
intensity should be researched to give a moredetailed analysis of L. capitella Cl. harmfulness invarious surroundings.
Basing upon the classification of insects
according to their activity rhythm given by [19],Lampronia capitella Cl., according to our data, canrefer to the insects whose feeding habits are equallyintensive throughout the day. Primarily it is due tothe fact that L. capitella Cl. develops in foodabundance (in the food substratum: bud or berry). L.
capitella Cl. nutritional adaptation is very importantfor identifying the researched characteristics.
Numerous studies have shown that voracity of
insects directly depends on the physiological state ofa forage plant [20].
The experiment revealed that in the laboratory
conditions the amount of food eaten by the larvae forthe whole process of their development, i.e. of thesecond, third and fourth instars was 60.44 mg. In theSEE - USQ, Brisbane, Australia, Nov.13-16, 2017

natural conditions at an average decade temperatureof +12.4 °C the amount was 94.4 mg, which is 1.6
times more than in the laboratory.
Studying feeding intensity of the second, thirdand fourth larval instars separately the fourth instars
are revealed to be the most active, and therefore they
are more harmful than the second and third larval
instars.
We understand uredospores as an indicator ofyield reduction per plant is influenced by the life of
one individual pest [21]. The mass of food eaten by
the second instars larvae was 11.8 mg for the entire
period of their development under laboratory
conditions when the air temperature was +25 °C.
Weight of food eaten by fourth instars larvae was
28.96 mg. It is 2.5 times more than in the laboratory.
Similar patterns were observed in natural conditions.
For example, in natural conditions over the period offull development, the second and fourth instars
larvae destroyed 21.7 mg and 39.84 mg food,respectively. The third instars of L. capitella Cl.
consumed 19.68 mg of food in the laboratory. In
contrast, in natural conditions, this value was 33.86
mg when the air temperature was+13.9 °C.
Voracity coefficient for the fourth larval instars
is found out to be 34.5 %; for the third – 25.4 %; forthe second – 12.7 %. These findings suggest that the
fourth larval instars are the most voracious. Table 1
illustrates larval voracity according to their instars in
the natural and laboratory conditions.

Thus, at the air temperature of +25 °C the second
larval instars ate 7 mg of food in average, at +8.3 °C
larvae of the same instars ate 5.7 mg of food daily.
At the air temperature of +25 °C the third instars ate
10.52 mg of buds, while at +15.4 °C the amount offood eaten was 9.5 mg. The fourth larval instars ate
13 mg of food at +25 °C, while at +17.8 °C the massof food eaten daily was 10.2 mg of buds.
Table 2 The mass of food eaten daily of larvae
L. capitella Cl.
Larvae
age

II
III
IV
Total

Ta, °C

+25
–

II
III
IV
Total

+9.7
+14.3
+15.1
–

II
III
IV
Total

+9.7
+14.3
+15.1
–

Mf, mgМе, mgLaboratory
11.80±0.01
7.06±0.01
19.68±0.02 11.26±0.02
28.96±0.03 17.44±0.03
60.44±0.02 35.76±0.02
Nature (Area 1)
32.71±0.01 22.29±0.01
45.76±0.03 31.43±0.02
51.48±0.03 37.13±0.03
129.90±0.02 90.85±0.02
Nature (Area 1)
20.7±0.01
12.29±0.01
33.86±0.03 20.53±0.02
39.84±0.03 27.13±0.03
94.40±0.02 59.95±0.02

II
III
IV

+25

II
III
IV

+8.3
+15.4
+17.8

II
III
IV

+8.3
+15.4
+17.8

Mf, mgМе, mgLaboratory
7.00±0.01
4.47±0.01
10.52±0.02 6.55±0.02
13.00±0.02 7.78±0.02
Nature (Area 1)6.90±0.02
4.68±0.01
11.53±0.01 8.42±0.01
14.22±0.02 10.37±0.01
Nature (Area 1)5.70±0.02
3.48±0.01
9.55±0.01
6.40+0.01
10.20±0.02 7.47±0.01

C, %
36.1
37.7
40.2
32.2
27.0
27.1
38.9
33.0
26.8

The data characterizing the relationship between
the second, third and fourth instars of L. capitella Cl.
and air temperature are presented in Table 2.
When studying the dynamics of the digestion
coefficient it was noted that in the laboratory
conditions at the air temperature of +25 °C, air
humidity of 70–75 % and a 10 hour daylight thedigestion coefficient was slightly changing with theage, accounting for 40.2 % for the second instars,
42.8 % for the third and 39.8 % for the fourth. In thenatural conditions at the average air temperaturefrom 9.7 °C to 15.1 °C the digestion coefficient was
declining from the second larval instars to the fourth
being 40.6 %, 39.4 % and 31.9 % respectively(Tables 1, 2). These results indicate that the second
larval instars digest food better.
In the whole, the digestion coefficient of thelarvae brought up in the permanent laboratory
conditions is higher (40.8 %) than that of thosegrown in varying natural conditions (36.5 %).
Moreover, the digestion coefficient increases withage for the larvae grown in the laboratory conditions.
In the natural conditions the coefficient declines
with age. It means that at the air temperature of+25 °C nutrients are better digested, consequently
the development cycle extends, and the harmfulnessof L. capitella Cl. grows. Tables 1, 2 present how
the digestion coefficient changes for the second,
third and fourth instars daily and during theirdevelopment.
The study of the food chains, voracity andharmfulness of L. capitella Cl. instars showed that

Table 1 Mass of food eaten by L. capitella Cl.
during their development
Larvaeage

Ta, °C

C, %
40.2
42.8
39.8
40.8
31.9
31.1
27.9
30.1
40.6
39.4
31.9
36.5

To monitor the influence of temperature on thevoracity of L. capitella Cl. second, third and fourth
instars, the amounts of food eaten daily by the larval
instars at different air temperatures were compared.
The evidence was found to state that the larvae
feeding intensity increases with increasing
temperatures (Table 2).
397

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

cultivars”, Acta Agriculturae Scandinavica,
Section B: Soil and Plant Science Vol. 59(1), Jan.
2009, pp. 63-69.

the most voracious are the fourth larval instars, thevoracity coefficient is 34.5 %; the second instars areless voracious (12.7 %). But the digestion coefficientfor the fourth instars is the lowest (31.9 %). The
lower the air temperature is, the worse the larvae
digest food.

[9] Mitchell C, Brennan RM, Cross JV, Johnson SN,“Arthropod pests of currant and gooseberry crops in
the U.K.: Their biology, management and future
prospects”, Agricultural and Forest Entomology, Vol.
13(3), Feb. 2011, pp. 221-237.
[10] Cramer GR, Urano K, Delrot S, Pezzotti M,
Shinozaki K, “Effects of abiotic stress on plants: asystems biology perspective”, BMC Plant Biology,
Vol. 11, 2011.
[11] Lobell DB, Schlenker W, Costa-Roberts J, “Climate
trends and global crop production since 1980”,
Science, Vol. 333(6042), 2011, pp. 616-620.
[12] Tattersall EA, Grimplet J, DeLuc L, Wheatley MD,
Vincent D, Osborne C, Ergul A, Lomen E, Blank RR,
Schlauch KA, Cushman JC, Cramer GR, “Transcript
abundance profiles reveal larger and more complex
responses of grapevine to chilling compared toosmotic and salinity stress”, Functional &Integrative Genomics, Vol. 7(4), Oct. 2007, pp. 317333.
[13] Pinheiro C, Chaves MM, “Photosynthesis anddrought: can we make metabolic connections fromavailable data” Journal of Experimental Botany, Jan.
2011, Vol. 62(3), pp. 869-882.
[14] Skirycz A, Inze D, “More from less: plant growthunder limited water”, Current Opinion in
Biotechnology, Vol. 21(2), Apr. 2010, pp. 197-203.
[15] Cramer GR, “Abiotic stress & plant responses fromthe whole vine to the genes”, Australian Journal of
Grape and Wine Research, Vol. 16, Jan. 2010, pp. 8693.
[16] Ваrtе1 G.M., “Effect of temperature on development
and survival ofargentine stem weevel (List
Incurvariidae) ”. Ber. naturwiss – med. Ver.
Innsbruck, 1987, pp. 197-205.
[17] Shchelkanova VY, Mashkova IV, Shchelkanova EE.
“Biotopical distribution of dasyhippus in south forest
division of the Ural state reserve” In the collection:
People. The science. Innovation in the newmillennium The collection of scientific papers of theInternational Youth Scientific and Practical
Conference: in 2 parts, 2015, pp. 103-108.
[18] Mashkova IV., Krupnova TG., Kostryukova AM,
Shchelkanova
VY,“Landscapeecologicaldistribution of diurnal butterflies of mixed forests inSouth forest division of Ilmen state reserve”,
International
Multidisciplinary
Scientific
GeoConference Surveying Geology and Mining
Ecology Management, SGEM, Book 1, Vol. 1, 2016,
pp. 555-562.
[19] Danilevsky AS, Kuznetsova IA, “Intraspecificadaptation of insects to climatic zonality”
Photopsychic adaptations in insects and mites.
Leningrad: Leningrad University, 1968, pp. 5-51.
[20] Kozhanchikov IV, “Nutritional specialization and its
significance in the life of insects” Entomologicalreview Moscow, 1951, Vol.31, Issue. 4, рр. 324-335.
[21] Tanskiy VI.,“Biological basis of harmfulness ofinsects”, Moscow: Agropromizdat, 1988, 182 p.

CONCL.USION
Comparison the conditions of blackcurrant
cultivation is shown that the population of
L. capitella Cl. increases faster in the Area 1(breeding stations), where the blackcurrants are
growing under the influence of abiotic stress. In thelaboratory, population L. capitella Cl. was the same.
In Area 2 (private farms) the number and activity ofthe pest was much smaller than in Area 1.
The food assimilation by L. capitella Cl. larvae
was higher for larvae in constant laboratory
conditions than larvae in a changing natural
conditions.
REFERENCES[1] Manganaris GA, Goulas V, Vicente AR, Terry LA,“Berry antioxidants: Small fruits providing large
benefits”, Journal of the Science of Food andAgriculture, Vol. 94(5), Mar. 2014, pp. 825-833.
[2] Folmer F, Basavaraju U, Jaspars M, Hold G, ElOmar E, Dicato M, Diederich M, “Anticancer
effects of bioactive berry compounds”,
Phytochemistry Reviews, Vol. 13(1), Mar. 2014,
pp. 295-322.
[3] Sava P, Calaras C, Tcaci V, Gherasimova E,
Crivaia P, Vitelaru O, “Nutrients accumulation in
fruits of berry species”, Fruit Growing Research,
Vol. XXXL, 2015, pp. 30-33[4] Kevers C, Pincemail J, Defraigne JO, Dommes J,“Antioxidant capacity of small dark fruits:
Influence of cultivars and harvest time”, Journal ofBerry Research, Vol. 4, Jan. 2014, pp. 97-105.
[5] Gordon SC, “Raspberry and currant entomology The drivers for change in Europe”, Acta
Horticulturae 777, 2008, pp. 301-310.
[6] Johnson SN, Barton AT, Clark KE, Gregory PJ,
Mcmenemy LS, Hancock RD, “Elevatedatmospheric carbon dioxide impairs theperformance of root-feeding vine weevils bymodifying root growth and secondary metabolites”,
Global Change Biology, Vol. 17(2), May 2011, pp.
688-695.
[7] Martin P, Johnson S, “Evidence that elevated CO2
reduces resistance to the European large raspberry
aphid in some raspberry cultivars”, Journal ofApplied Entomology, Vol. 135(3), Jun. 2011, pp.
237-240.
[8] Kahu K, Jänes H, Luik A, Klaas L, “Yield andfruit quality of organically cultivated blackcurrant

398

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

USING BIRCH LEAVES TO INDICATE AIR POLLUTION
T.G. Krupnova1, I.V. Mashkova2 and A.M. Kostryukova3
1Chemistry Department, 2South Ural State University,
RussiaABSTRACTThe present study investigated the utility of Bétula pubéscens L. leaves as a bioindicator of air pollution
within an industrial Russian city. The study focused on the effects of air pollution on fluctuating asymmetry(FA) of leaves. B. pubéscens L. leaves (n=3800) were sampled from 190 trees growing at 38 different sites in
Chelyabinsk. The relationship between the data was determined using Pearson’s test with a significance level of
0.05. Correlations were observed between the integral index of fluctuating asymmetry (IIFA) and air pollutants
such as suspended solids (P=0.527), nitrogen dioxide (P=0.313), sulfur dioxide (P=0.355), inorganic dust SiO 2(P=0.790), and the air pollution index (P=0.607). The correlation was the highest for inorganic dust since dust
clogs the stomata on the leaves of plants, affecting their photosynthesis and respiration. B. pubéscens L. could beconsidered as a bioindicator of air pollution of Chelyabinsk, Russia.
Keywords: Fluctuating Asymmetry (FA), Bioindicator, Air Pollution, Leaves

INTRODUCTIONMETHODS
Fluctuating asymmetry (FA) consists of small,non-directional deviations from perfect symmetry inmorphological characters. FA can be used as ahandy indicator of stress experienced by organisms[1]–[10].
FA has been considered a marker ofdevelopment instability for over half a century. FA
is a nonspecific indicator of the conditions ofdevelopment and a measure of random deviations indevelopment. This gives us the opportunity to use it
to assess the conditions of existence, both naturaland artificial populations. It is believed that thestronger the external influence, than higher the FA[1]–[10].
Despite the fact that this method is widely used,
including for monitoring the state of atmospheric air,it has been repeatedly criticized in the literature[11]–[14]. Recent works [15], [16] recommend thismethod under the following conditions: (1) using theblind method, where the person conducting
measurements is not aware of the origin of samples
being measured; (2) pay utmost attention to adequateand detailed description of data acquisition protocols,
because all characteristics of instruments andmethods need to be controlled to increase the quality
and reproducibility of the data; (3) the measurements
should be conducted with high accuracy fromimages of fresh or press-dried leaves.
Bétula pubéscens L. is most widely used as theobject of FA studies [15].
The aim of the present work is to explore thenature of FA B. pubéscens L. leaves in different
districts of Chelyabinsk and to explore thepossibility of using this parameter to assess air
pollution.

Study Area
38 sampling sites were selected for researchingin different districts of Chelyabinsk (Fig. 1).

Fig. 1399

The locations of sampling and air quality
monitoring sites.

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

Chelyabinsk is a large industrial city. The air in
Chelyabinsk is polluted by traffic, heavy industry(ferrous and nonferrous metallurgy, pulp production)and thermal power stations. The most dangerous
pollutants are benzo(a)pyrene, formaldehyde, andnitrogen dioxide. Air quality is monitored at 24
monitoring sites.
In 2012 [16] the average concentration of
benzo(a)pyrene, formaldehyde, and dioxide nitrogenexceeded the maximum allowable level of 3.9, 3.3,
and 1.1 times, respectively. In addition, in 2012,
disposable excess concentration of substances in the
air was observed for Pb, Mn, Cd, suspended solids,
H2S, NO2, phenol and formaldehyde [17].

from each plant were stored in separate envelope.
We carefully marked envelope, indicating the placeand date of leaf collection and has a number of thetree.
Measurements of the Leaves
We made measurements of each birch leaf twice.
The first time, we measured fresh leaves on the dayof collection or within 2–3 days after collection. The
second time, we measured the press-dried leaves.
The second measurement was performed blindly
with respect to the results of the first measurement.
For each leaf, we measured five parameters on
the left and right sides (Fig. 2, 3):(1) the width of the halves of the leaf;(2) the length of the second order nerve that is
the second from the base of the leaf;(3) the distance between the bases of the first andsecond nerves of the second order;(4) the distance between the ends of these nerves;(5) the angle between the main vein and thesecond from bottom nerve of the second order.

Leaf Collection
We collected birch leaves in July 2012. We
chose July because leaf growth stops at this time.
We collected leaves from 5 trees at each site, 20
leaves from each tree. The total number of leaves
collected at each site was 100. A total of 190
B. pubéscens L. trees were studied. We considered a
few factors when we were selecting trees according
to the recommendations of the literature [1]. First, it
is important to determine that the plant belongs to
the investigated species. B. pubéscens L. is able tointerbreed with other species of birches, and it forms
interspecific hybrids which have characteristics ofboth species. To avoid errors, we chose trees with
distinct characteristics B. pubéscens L. Second,
leaves should be collected from plants located insimilar environmental conditions (it is necessary toconsider the light level, moisture, etc.). We chose
trees growing in open areas, because shading
conditions are stressful for birch and significantly
reduce the stability of plant development. Thirdly,
the age of trees should be considered. We chose
trees which had a generative age state.
We collected leaves from the maximum numberof branches available evenly around the tree fromthe lower part of the crown. The leaves werecollected only from short shoots. Leaf size wassimilar - the average for this plant. Damaged leaves
were not used for the analysis [1].
56 students and teachers of South Ural State
University participated in collecting and measuring
leaves.

Fig. 2

Measurements of five parameters.

Fig. 3

Measurement methodology.

Preparation and Storage of the Leaves
We made measurements of leaf immediately on
the day of collection or kept short leaves 2–3 days in
the refrigerator on the bottom shelf.
In addition, all leaves were dried according tostandard
Botanical
methodsforfurther
measurements of the air-dried leaves blind. For thispurpose the leaves were dried under standard
Botanical press to air-dry state. Further, the leaves

These measurements were performed with theuse of a slide caliper, a ruler, and a protractor.
We used a scale (Table 1) to assess the degree ofviolation and consequently to assess disturbances inthe ecosystem.
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Table 1 Rating scale of comfort for living
environment fluctuating asymmetry [1]IIFA< 0,0400,040–0,044
0,045–0,049
0,050–0,054> 0,054

where Ci is an average i-substance concentration in
mg/m3 ; MPCi – the average daily maximum
permissible concentration of i-substance in mg/m3 ;Ki – dimensionless constant depending on thesubstance hazard category, N – the number ofcontaminants considered.
Ki values are equal to: 0.85 for substance hazard
category 4; 1.0 for substance hazard category 3; 1.3
for substance hazard category 2; 1.5 for substancehazard category 1. The five substances with thehighest index are used.
With an API of ≤ 5, air pollution level isconsidered low. If 5 < API ≤ 7, then air pollution
level is increased. If 7 < API ≤ 14, it is high, and if
API is > 14 it is very high.

Characteristics of theenvironmental condition of theterritory
Conditionally clean
Disturbed
Considerably disturbed
AdverseExtremely adverse

We calculated the integral index of fluctuating
asymmetry (IIFA) using normalized difference
algorithm [1]:A1 

1 m n Lij  R ij,m  n i 1 j1 Lij  R ij

Data Processing
Microsoft Excel 2013, MapInfo Pro 15.0, andSPSS 24.0 software were used to organize andanalyze the data. The Kolmogorov–Smirnov test wasused to test data normality. The relationship between
the data was determined using Pearson’s test with asignificance level of 0.05; the linear regression wasconsidered significant.

(1)

where Lij and Rij are the values of the j-th characterin the i-th leaf to the left and right side of the planeof symmetry and convolution of the functions,
respectively, that in the form of finite sums can be
represented by the following formula [18]:

RESULTS AND DISCUSSIONn

A2  1

m

2 L ij  R ij

1
.
 j1
m i 1 n 2
2
 (Lij  R ij )The values of IIFA for the studied sites arepresented in Table 2 and Figure 4.
(2)

j1

Statistical processing of the experimental data
was performed with N.A. Plohinskiy methods [19]using the Microsoft Excel 2013 software suite.
Air Pollution Index
We used data on service monitoring of urban air
on 11 substances for the assessment of air pollution:suspended solids, carbon dioxide, sulfur dioxide,
nitrogen dioxide, nitrogen monoxide, phenol,
formaldehyde, sulfuric acid, inorganic fluorides, Mn,
and inorganic dust SiO2. We calculated the air
pollution index (API) based on Chelyabinsk air
monitoring by the standard method RD 52.04 18689 [20], RD 52.04.667-2005 [21].
API shows the air pollution level characteristicof chronic, long-term air pollution [22].
API is calculated using the formula:N

Ci K i) ,i 1 MPC i

API   ((3)
Fig. 4401

Integral index of fluctuating asymmetry.

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

Table 2 IIFA in different sites
Site
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

where the highest IIFA was obtained (Fig. 4).

IIFA
0.041±0.011
0.043±0.013
0.060±0.015
0.039±0.010
0.037±0.010
0.048±0.012
0.047±0.011
0.051±0.017
0.049±0.016
0.046±0.014
0.081±0.015
0.058±0.011
0.055±0.011
0.052±0.012
0.053±0.011
0.057±0.012
0.053±0.011
0.047±0.013
0.064±0.011
0.042±0.011
0.047±0.011
0.042±0.015
0.048±0.011
0.056±0.013
0.054±0.011
0.055±0.011
0.053±0.011
0.054±0.012
0.046±0.012
0.047±0.012
0.056±0.011
0.054±0.014
0.052±0.011
0.054±0.011
0.046±0.017
0.048±0.014
0.050±0.011
0.043±0.011

Fig. 5Air pollution index.

Coefficients of correlation between IIFA and air
pollutant were calculated to more accurate estimates(Table 3).
Table 3 Pearson’s tests for different air pollutants
Pollutant
Pearson’s test
Suspended solids
0.527
Carbon dioxide
0.242
Sulfur dioxide
0.355
Nitrogen dioxide
0.313
Nitrogen monoxide–
Phenol0.0006
Formaldehyde
0.203
Inorganic fluorides–
Sulfuric acid
–
Mn
0.155
Inorganic dust sio2
0.790
API
0.607
Blank is insufficient data to calculate
Bold is significant value of correlation

We observed only 2 sites with IIFA < 0.04.
According to Table 1 and Table 2, there were 2 sites
with a conditionally-clean environment, and 5 and 8
sites with disturbed and сonsiderably-disturbed
environment, respectively.
The remaining sites corresponded to the adverse(20 Sites) and the extremely adverse (5 Sites)
environment level. Very high values are observed
along highways that cross the entire central part ofthe city. In the central part of the area, the values ofasymmetry were often higher than the values in theother areas. The maximum achieved value IIFA was
0.081 in Site 11.
A map of the air pollution of the city was built
according to the calculation of API (Fig. 5).
Figure 5 shows that the sites with the greatest air
pollution (maximum API) coincide with the areas

The average value of API in July 2012 was 6.51.
This corresponds to increased air pollution. The low
degree of air pollution was observed only in theoutskirts of the city away from the plants.
The values exceed the critical value of Pearson’s
tests 0.300 (n=38, p=0.05) for suspended solids(P=0.527) nitrogen dioxide (P=0.313), sulfur dioxide

402

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

(P=0.355), inorganic dust SiO2 (P=0.790) and air
pollution index (P=0.607).
Correlation with sulfur and nitrogen dioxides
was significant. Sulfur dioxide penetrates into leaves
primarily in gaseous form through the stomata,although there is evidence for a limited pathway via
the cuticle. Chronic damage results from long-term
exposure to much lower concentrations of the gas
and is essentially cumulative in nature, taking theform of reduced growth and yield and increased
senescence, often with no clear visible symptoms orwith some degree of chlorosis. Sulfur dioxide canalso modify the response of plants to otherenvironmental stresses, both biotic and abiotic, often
exacerbating their adverse impacts. Nitrogen dioxide
is the damaging component of photochemical smog.
In the environment, excessive levels of nitrogendioxide can rapidly inhibit photosynthesis per unit
leaf area [22].
The highest correlation values were observed forsuspended solids - inorganic dust SiO2 and API. It
was found that dust accumulation on leaf surfaces
induces water stress-like conditions, such as a
reduction of stomata conductance, photosynthesis
and transpiration, and increased leaf temperature[23].

applications”, Symmetry, Vol. 2, Mar. 2010, p.
466-540.
[3] Bukharina IL, Povarnitsina TM, Vedernikov KE,“Ecological and biological characteristics oftrees in urban environment”, Izhevsk: State
Agricultural Academy, 2007, pp. 5-215.
[4] Vogel S, “Leaves in the lowest and highest
winds: temperature, force and shape”, New
Phytologist , Vol. 183(1), Jul. 2009, p. 13-26.
[5] Wilsey BJ, Haukioja E, Koricheva J,
Sulkinoja M, “Leaf fluctuating asymmetry
increases with hybridization and elevation intree-line birches”, Ecology, Vol 79(6),Sep. 1998, p. 2092-2099.
[6] Wuytack T, Wuyts K, van Dongen S, Baeten L,
Kardel F, Verheyen K, Samson R, “The effectof air pollution and other environmental
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Environmental Pollution, Vol.
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Vol. 17, Nov. 1986, p. 391-421.
[10] Parsons PA, “Fluctuating asymmetry: abiological monitor of environmental andgenomic stress”, Heredity, Vol. 68, Apr. 1992,
p. 361-364.
[11] Klisarić NB, Miljković D, Avramov S, Živković
U, Tarasjev A, “Fluctuating asymmetry inRobinia pseudoacacia leaves – possible in situ
biomarker?”, Environmental Science and
Pollution Research, Vol. 21(22), Nov. 2014,p. 12928-12940.
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and measurement error”, Systematic Biology ,Vol. 44(1), Mar. 1995, p. 97-101.
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fitness: can we bridge the gap between studies?”,
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[14] Rasmuson M, “Fluctuating asymmetry –indicator of what?”, Hereditas, Vol. 136(3), Sep.
2002, p. 177-183.
[15] Kozlov MV, Zvereva EL, “Confirmation bias instudies of fluctuating asymmetry”, Ecological
Indicators, Vol. 57, Oct. 2015, p. 293-297.

CONCLUSION
Analysis of fluctuating asymmetry of Bétula
pubéscens L. leaves collected in July 2012 in theindustrial city, Chelyabinsk, showed that:- most sites have index deviations from its
conditional standard;- correlation coefficients between the fluctuating
asymmetry and the concentration of pollutants inurban air are greater than the critical value.
In conclusion, it should be noted that, despite
criticism of the method, fluctuating asymmetry of
B. pubéscens L. leaves can be used as a bioindicatorof air pollution
ACKNOWLEDGEMENTS
The authors wish to thank D. Uchaev (SUSU
Nanotechnology ERC) for his XRF quantification
measurements.
REFERENCES[1] Zakharov VM, “Analysis of fluctuating
asymmetry as a method of biomonitoring at the
population level”, Bioindications of chemical
and radioactive pollution, Moscow: Mir
Publishers and Boca Raton: CRC Press, 1990,
p. 187-198.
[2] Graham JH, Raz S, Hel-Or H, Nevo E,“Fluctuating asymmetry: methods, theory, and403

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[20] RD 52.04 186-89, “Guidelines for air pollution”,
Russia, 1991, pp. 24-172.
[21] RD 52.04.667-2005, “Documents on air
pollution in cities for informing government andpublic.
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deposition on physiological behaviors of someselected plant species”, International Journal of
Scientific & Technology Research, Vol. 1(9),Oct. 2012, pp. 98-105.

[16] Kozlov MV, Cornelissen T, Gavrikov DE,
Kunavin MA, Lama AD, Milligan JR, Zverev V,
Zvereva EL, “Reproducibility of fluctuating
asymmetry measurements in plants: sources ofvariation and implications for study design”,
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733-740.
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Chelyabinsk region in 2015”, Chelyabinsk,
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[18] Gelashvili DB, Chuprunov EV, Ludin DI,“Structuralandbioindicativeaspectsoffluctuating asymmetry bilaterally symmetricalorganisms”, Journal of General Biology. Vol.
65(5), 2004, p. 433-441.
[19] Plohinsky NA, “Biometrics”, Moscow: Moscow
State University, 1970, pp. 3-367.

404

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

STUDY OF SYNANTHROPIC PLANTS OF THE SOUTH URAL
A.M. Kostryukova1, I.V. Mashkova2, T.G. Krupnova3 and E.E. Shchelkanova4
1Chemistry Department, South Ural State University, Russia

ABSTRACTThe present study aimed to assess the long-term dynamics of the synanthropic vegetation of the road and path
network of the Ilmen State Reserve. The analysis of the synanthropic species spread among coenofloras of theelements of the road and path network revealed an increasing synanthropization index in the gradient of thestress factor for all forest types. Pine forest is the most resistant to the introduction of synanthropic species. The
paper considers the element composition in the period before seed formation. 10 weeds most common in thecentral regions of Russia were analyzed. The studied weeds can accumulate metals in their green mass. Somewild plants are potentially resistant to metals, as they can grow on heavily dirty substrates. The analysis of thevegetational metals shows that most of the species do not translocate metals into their overground part, so they
act as excluders. Due to the human-made impact on the natural landscape, synanthropic species of plants aretaking a significant place in the structure of biodiversity.
Keywords: Reserve, Synanthropic Plants, Anthropophytes, Apophytes, Metal Concentration

accumulate heavy metals, the nature of soil ischanging [3]. The problem of heavy metal
accumulation by synanthropic plants is of current
interest. Researchers all over the world have come to
study heavy metal concentration in weeds. Somewild plants are potentially resistant to metals, as they
can grow on heavily polluted substrates [4]. Bothclimate diversity and increasing human-made impact
on natural ecosystems explain the high adaptabilityof synanthropic plants [5].
The growing interest of scientists in Russia andformer Soviet republics in studying synanthropic
flora is connected, first of all, to the increased role ofsynanthropic species of plants in the regional floras,
secondly, to the influence of floristic schools ofCentral and Northern Europe that have achievedmuch in the sphere. Adventitious and synanthropic
plants are well-studied in Primorsky Kray and someother regions [6]. There are some open questions
concerning synanthropic species in phytogeography,
ecology and phytocoenology.
The efficiency of monitoring the vegetative
cover and tracking the natural (by anthropophytes)
and cultivated (introduction) enrichment of local
flora depends on working out the theory ofsynanthropization of the vegetative cover.
Investigating these issues in the South Ural region
seems to be important, as the territory is a complex
structure of climatic, ecological, and phytocoenotic
factors with a focus on the high ecological flexibilityof species. This paper is aimed at studying heavy
metal accumulation by the synanthropic vegetationin the road and path network of the Ilmen State
Reserve and finding out the instances of the growthof their ecological and phytocoenotic positions.

INTRODUCTION
There has always been increased interest in
ruderal plants. The structure and composition ofvegetative cover is irreversibly affected by humanactivity. Weeds strangle cultivated plants, absorbing
large amounts of water and nutrients from the soil,
discharging harmful substances from the roots, andblocking light. But the problem has not been studiedcomprehensively. Natural reserves are not thesolution, as phytocoenosis can’t but be affected byhuman activity even in a conservation area [1]. In
economic and scientific activities, the main line used
for preventing fires is connected with the process ofinvasion. The Ilmen State Reserve, which serves as areserve for the gene and coenobank of South Ural
region vegetation and a standard of common
vegetation communities that, as part ofenvironmental monitoring, may be compared withother territories’ phytocoenosis under various humanimpact, is not an exception [1], [2].
The vegetation composition and structure on
paths and roads are different. Species diversity andweed abundance are directly connected to theirusage. Roads and paths are the place where “alien”
species (or anthropophytes) invade the naturalvegetation. As a result, separate species of nativeflora (apophytes), adapting to human-made impact,
alter their coenotic positions. According to someresearchers, these plants become dominant in newcommunities and oust common species [2]. Alongwith these transformations, synanthropization of theReserve’s vegetative cover occurs. The flora isdegrading, derived communities are replacing thenative, and phytocoenosis stability is declining.
Since many synanthropic plants were reported to405

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

The study of adaptability given human-madetransformation of the vegetative cover is crucial for
defining ecological and phytocoenotic positions ofsynanthropic species. It is important to identify thechemical and biological features of ruderal plants ina natural geographic habitat and in the newly
developed territories of the road and path network of
the Ilmen State Reserve.

covering 56 % and 40 % of the territory of theReserve, respectively. The territory of road and pathvegetation is 6.4 % of all the Reserve’s area [1].
Scotch pine (55 %) and European white birch(40 %) mainly constitute forests. Herb-grass, green
moss, green moss-vaccinium (close to the original)and steppificated biotopes are presented in theforests. Peat-bog and bog-moss pine forests are seenin the wetlands. European white birch and European
aspen make young growth with herbs and grass at
logging sites. Grass-pine and sedge-reed-sphagnum
biotopes are seen in valleys, lakesides, and bogs.
Such meadow herbs as various grasses (bluegrass,bentgrass, cocksfoot grass), many legume species,
buttercups, globeflowers, meadow cranesbills,
syndows, etc. are found at the outskirts of the forest.
Being diverse and numerous, bogs don’t coverlarge territories. Almost all of them appear at thesides of “aged” lakes or former bays thereof. Someof them occupied by reed-sedgy formations still
have the character of floating bogs. More developed
bogs are characterized by the presence of sphagnum
moss, bog low shrubs, and herbs specific for taigabogs such as bog rosemary, swamp ledum, bog
cranberry, moorberry, Scheuchzeria palustris,roundleaf sundew, mud sedge, whortleberry willow,
white beak sedge, English sundew, cloudberry, andblueberry. Sometimes trees (birch, suppressed pine)
are seen. Water and coastal water vegetation is richand diverse. There are about 70 species of water
macrophytes [1], [2]. Macrophyte vegetation isdeveloping in shallow water in bays of the littoralzone of open shores.

METHODS
Study Area
The Ilmen State Reserve is located on the easternSouth Ural macroslope between the latitude of
540 degrees 58 minutes – 550 degrees 20 minutes
north and longitude of 600 degrees 07 minutes –600 degrees 21 minutes east. It’s a part of the South
Ural physiographic region of the Ural highlands.
The Reserve is a refuge for many endemic andextinct plants and for rare and protected species.
The complex history of the evolution of theSouth Ural fauna in the Quaternary Period and theIlmen mountains unique borderline location between
mountain (forest) and piedmont (forest-steppe) partsof the region allow the invertebrate animals, diversein species and complex in composition, to evolve. Inthat context, the phenomenon of “rich local
invertebrate fauna of the Ilmen mountains” is worth
mentioning.
In the terrain analysis of Chelyabinsk region, theIlmen State Reserve is a part of the erosion anddenudation landscape of eastern foothills of South
Ural that evolved on the eruptive rocks. The South
forest division is located in the south terminal ridgeof the Ilmen mountains, which is a mild terrace
slope with a steep on the Ilmenskoye lake. The
abundant flora and phytocoenosis diversity of thesite is caused by the borderline location between
steppe and forest-steppe zones, challenging
landscape, various rock formations. The site’slandscape is longitudinal-ridge-steep-sloping (400–300 m above sea level). According to thephytogeographical analysis, the South forest division
is located in mixed forests of the preforest-steppepine and birch forests subzone of the south taiga
forests zone. On the west, the subzone borders on
dark coniferous forests of dividing ridges, on theeast – on forest-steppe of trans-Ural peneplain [7].
The variegated vegetative cover was formed under
the challenging climate and landscape.
The data were gathered in 9 biotopes [7].

Research Methods
The research was conducted in 2015–2016.
Standard methods were used to collect data.
Sampling points were selected based on thelandscape features, vegetation spread and humanmade impact. Expedition trips were planned basedon natural zone analysis, remote sensing of the earth(Landsat/ETM+ satellite images) with a landscapediversity assessment.
Road and path network with complexes ofvegetation communities was chosen for analysis. 6
permanent sampling sites in glague-herb-gramineous
birch forests and pleurocarpous moss herbgramineous pine forests and 3 types of roads(unsurfaced road, forest road, and foot path) were
described (Fig. 1). The coordinates of the samplingsites: site 1 – 55° 0'13.28"N, 60°10'26.98"E; site 2 –54°59'57.00"N,
60°11'30.34"E;
site
3–
54°59'52.91"N, 60° 9'56.01"E; site 4 –54°59'29.69"N,60°10'29.14"E;site
5–54°59'21.32"N,
60°10'46.77"E;
site
6–
54°59'32.52"N, 60°10'54.98"E.
The routes cover 10 km in total. Geo-referenced
data integration and correlation were completed with

Characteristic Features of Vegetation
The Ilmen State Reserve is 90 % covered byforests, which can be classified as South Ural
preforest-steppe pine and leafed-pine forests. The
main forest-forming species are pine and birch,
406

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017a geographic information system (GIS). A total of
about 100 plant samples were described. The area ofthe studied stations was more than 25m2.

patterns were registered in the lab of Education andResearch Center for Nanotechnology at South Ural
State University. A Rigaku SuperMini XRF
Spectrometer was used for XRF analysis. The
relative standard results deviation was not more than
5 %.
RESULTS AND DISCUSSION

Fig. 1The problem of synanthropic species is
becoming more important not only for developed
areas but also for reserves. Synanthropization
significantly influences the flora of conservation
areas. Synanthropic flora is heterogeneous.
According to E.V. Dorogostayskaya [10],anthropophilic flora consists of some local species(apophytes) and species brought by man(anthropochores). The main factor for the growth ofsynanthropic plants is soil microclimate change
made by man both deliberately and indeliberately or
spontaneously. Anthropogenic plants are classified
into native and adventive (anthropochores). Native
species are divided into sedentary, indifferent, andapophytes. Apophytes fall into erosiophilous (infreshly exposed substrates) and nitrophiloushalophilous apophytes (in the dirty anthropogenic
habitat). Adventive species (anthropochores) areclassified
into
unnaturalized(accidental,
permanently brought) and naturalized (growing onlyin the anthropogenic habitat; moving to the natural
habitat). According to common classification [11],synanthropic plants are divided into local (orapophytes) and alien (or anthropophytes). Among
synanthropic flora, S.G. Kudrin [12] distinguishes
the following ecological-phytocoenotic groups:
forest group (ruderal-forest element), meadow group(ruderal-meadow element), ruderal group (ruderal
element with wide environment, brought oradventive element), and the cultivated group (foodelement, decorative element, introduced element).
The modern synanthropic flora of the Ilmen State
reserve has increased by 45 species since 1986 [13],both apothytes (28 species) and anthropophytes (17species). The synanthropization index has grown by
1.6 % (Table 1).
Our research revealed 51 species of synanthropic
flora on the road and path network of the Reserve,
37 of which are apophytes and 14 - anthropophytes.
It has been established that the number ofsynanthropic species has insignificantly increased incomparison with 2014 [14].
In the birch forests, the number of synanthropic
species is larger (42–32) than in the pine forests (25–19), which may be explained by more favourable
conditions for the growth of the herbal andsuffruticose layer in the birch forests. A large
number of published studies do not establish any
differences in the parameters of the ecotopes of pineand birch forests, therefore the increasing number ofSampling sites: 1, 2 – unsurfaced roads, 3, 4
– forest roads, 5, 6 – foot paths.

The number of species, projective cover (%),
species abundance (according to Drude), and shareof synanthropic species were determined for every
10 m2 structural unit of the road.
The level of phytocoenosis synanthropization
was assessed based on the synanthropic species
share (synanthropization index). An assessment
scale of the synanthropization of vegetation
communities [8] was used: I – human-made impact
is low, synanthropic species up to 15 %; II – humanmade impact is considerable, 16 % to 60 %synanthropic species; III – human-made impact islong-term and high, synanthropic species are
dominant - 61 % to 100 %. Species grouped bycoenotic and ecological similarity of ecotopes [9]and forming communities on separate parts of paths
and roads are meant as coenoflora.
Sampling
andConcentration

Determination

of

Metal

Sampling occurred in July 2016, when plants
stopped in growth. To analyze the chemical content
of ruderal plants and to minimize their individual
distinctions, 5 samples of each plant species weregathered and air-dried. The air-dry samples of
5 plants were united into one mixed sample, they
were then ashed at 550 °C for 5 hours. The ashedsamples were ground in a mortar. The finely groundrock powder, mixed with a small amount ofpolyvinyl alcohol dissolved in water, wascompressed using a hydraulic press into a pellet.
In the pellets, Cu, Zn, Mn, and Fe were measured
using X-ray fluorescence (XRF) analysis. XRF
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

species in the synanthropic vegetation of the roadand path network of the Reserve may be attributed tothe anthropogenic factor. The study shows that with
the increase of stress load, microclimate is slightly
changing; humidity, trophicity, acidity, and nitrogengrow; and luminance in the pine and birch forests inall types of the main line is increasing [14].

synanthropization level, the heaviest and mostlasting impact is identified in the coenoflora of birch
forests that belong to all the types of forest roads. In
the pine forests, only unsurfaced and forest roads areaffected.
The most coeno-stable populations were chosen
to study heavy metal concentration in the ruderal
plants of the Ilmen State Reserve species formation.
Such metals as Zn, Mn, Fe, Cu, and Sr were found in
the plants (Table 2).
Cuprum is an essential element playing a keyrole in a range of physiological processessuch as
photosynthesis,
respiration,
carbohydrate
distribution, reducing nitrogen decline and fixation,
protein metabolism, and cell wall metabolism. Many
plants have cuprum. It also influences water
permeability, and thus, governs water relationships.
The most significant practical consequences of
cuprum function for plants are attributed to its
deficit and toxicity. Cuprum is a part of the disease
resistance mechanism. Plant resistance to mycosis
may be explained by an adequate cuprum supply.
There is the evidence that plants with a rich cuprum
concentration are more susceptible to some diseases.
Zinc is an essential microelement playing a keyrole as a specific activator of some ferments, such ascarbonic anhydrase catalyzing the breakage ofcarbonic acid into water and carbon dioxide. It iseasily absorbed as hydrated ion Zn2+. Zn
concentration in plants depends on the age and stateof vegetation. A high concentration of Zn is usuallyseen in young plants, and it reduces with the age as aresult of dilution. In general, plants can in large
amounts of Zn without showing any instances ofrejection with Zn concentration in soil being lessthan 500 mg/kg.
Iron is of great importance for the enzyme
system and necessary for chlorophyll synthesis. It ispart of the redox processes in plants, it can convert
from oxidated form into protoxydic and vice versa.

Table 1 Dynamics of synanthropization of the Ilmen
State Reserve flora according to thereferences

Plants groups
Plants totally
Synanthropic
species totally
Includingapophytes
Includinganthropophytes
Synanthropizationindex %
Apophytizationindex %

References
Gorchakovsky Gorchakovsky
and et al., 2005 and Kozlova,[1]
1998 [13]
953
841
265

220

144

116

121

104

27.8

26.2

54.3

40.0

The quality of soil on the unsurfaced roads islower than on the forest roads. Test planting ischaracterized by more xerophytic conditions, which
may be explained by the drainage properties of thevegetative cover transpiring water surplus fromorganic-mineral substrate. Integrity disturbance ofthe herbal and suffruticose layer results in stagnationin tracks and the space between them, bogging, andacidification; increased nitrate is caused by polluting[14].
Analysis of synanthropic species distribution in
the coenoflora of the elements of the road and path
network revealed an increasing synanthropizationindex in the gradient of stress factor for all theforests. According to the assessment scale ofTable 2 Heavy Metal Concentration in ash residue of ruderal plants, %Plant
Carduus crispus L.
Tanacetum vulgare L.
Trifolium montanum L.
Euphorbia esula L.
Leonurus quinquelobatus GILIB.
Linaria vulgaris MILL.
Artemisia vulgaris L.
Artemisia absinthium L.
Barbarea vulgaris W.T.AITON
Galeopsis ladanum L.
Capsella bursa-pastoris (L.) MEDIK.

Zn
0.62
0.45
1.64
0.49
1.12
0.65
1.98
0.65
0.56
0.48
0.42

Mn
1.12
1.42
1.17
2.04
2.52
1.54
1.32
2.56
1.69
1.23
1.51

408

Fe
1.53
1.65
1.58
2.10
2.13
1.79
1.74
2.03
1.91
1.65
1.78

Cu
0.22
0.24
0.25
0.26
0.21
0.25
0.26
0.21
0.28
0.22
0.26

Sr
0.11
0.12
0.11
0.11
0.10
0.12
0.11
0.11
0.12
0.10
0.12

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

Manganese is a significant element used in the
reduced form of Mn2+. Like cuprum, manganese,being the part of ferments that enable theseprocesses, plays an important role in the redox
reaction in plants.
The most influential factor in the absorption ofstrontium by plants is Ca concentration in soil. Other
factors are pH and organic matter concentration.
Accumulation of strontium by different
organisms depends not only on their species but also
on the interrelations of strontium, calcium andphosphorus in the environment. The total strontium
concentration in soil is 0.035 % (in mass).
Strontium in adequate concentrations isfavourable for plant metabolism [15].
Plant chemical composition reflects soil element
composition. But this is affected by many factors.
Therefore, heavy metal concentration in plants isvery changeable and widely varies. This study foundthat motherwort and wormwood accumulate a highamount of manganese and may be used for drawing
it out from soil in the process of phytoremediation.
Phytoremediation is known as a relatively
inexpensive method of soil reclamation [16, 17].
Clover and thistle accumulate more zinc and may be
used for drawing it out from soil. Other plants
accumulate iron ions and may be used for drawing
out iron from soil.

REFERENCES[1] Gorchakovsky PL, Zolotareva NV, Koroteeva
EV, Podgaevskaya EN, “Phyto-diversity of theIlmen Reserve in the system of protection andmonitoring”.
Ekaterinburg:
Goschitsky
Publishing House, 2005, pp 5-180.
[2] Kulikov PV, “Additions to the flora of Ilmenski
state reserve (South Ural)”, Bulletin of Moscow
Ssociety of Testers of Nature. Department of
Biology, Vol. 108(6), 2003, pp. 68-69.
[3] Liang S-X, Gao N, Li Z-C, Shen S-G, Li J,“Investigation of correlativity between heavy
metal concentration in indigenous plants andcombined pollution soils”, Chemistry andEcology, Vol. 32(9), Jul. 2016, pp. 872-883.
[4] González RC, González-Chávez MCA, “Metal
accumulation in wild plants surrounding mining
wastes”, Environmental Pollution, Vol. 144(1),Nov. 2006, pp. 84-92.
[5] Seledets VP, Mayorov IS, Syritsa MV, “Thepeculiarities of natureuse in the coastal zone of
the Russian far east seas: ecological ranges ofsinanropic plant species”, News of the Samara
Scientific Center of the Russian Academy of
Sciences, Vol. 10(2), 2008, pp. 303-309.
[6] Puzyrev AN, Baranova OG, “The study ofadventive and synanthropic flora in the CIS:
achievements and prospects”, Adventive andSynanthropic Flora of Russia and Neighboring
Countries: State and Prospects, in Materials of
the III International Scientific Conference.
Conference, 2006, pp. 3-4.
[7] Mashkova IV, Krupnova TG, Kostryukova AM,
Shchelkanova VY, “Landscape ecologicaldistribution of diurnal butterflies of mixed forests
in South forest division of Ilmen state reserve”,
in Proc. International Multidisciplinary Scientific
GeoConference Surveying Geology and Mining
Ecology Management, SGEM 16th., Vol. 1,
2016, pp. 555-562.
[8] Gorchakovsky
PL,“Anthropogenictransformation and restoration of productivity of
meadow
phytocenoses”.
Ekaterinburg:
Ekaterinburg Publishing House, 1999, pp. 3-150.
[9] Yurtsev BA, “Monitoring of biodiversity at thelevel of local flora”, Botanical Journal, Vol.
82(6), 1997, pp. 60-70.
[10] Dorogostaiskaya EV, “Weed plants of theextreme North of the USSR”. Leningrad: Science,
1972, pp. 3–170.
[11] Kornas J, “Man’s impact upon the flora:
processes and affects”, Memorabilia zoologica,Vol. 37, 1982, pp.11-30.
[12] Kudrin SG, “Analysis of ecological andphytocenotic elements of the synanthropic part of
the flora of the Hingemsky reserve”, Adventive
and Synanthropic Flora of Russia and

CONCLUSION
The study has identified 51 species ofsynanthropic plants on the road and path network ofsome parts of the Ilmen State Reserve. The plants
cover ditches, quarries, embankments, wastelands,
and the side of the roads. Rapidly growing annuals
and perennials are dominant in such coenofloras, as
they are not demanding of soil and grow well in sites
lacking a humous soil horizon.
The paper analyzes the chemical composition of
the metals Zn, Mn, Fe, Cu, and Sr for the most
coeno-stable species. These elements are essential in
low concentrations for plant metabolism and may be
used for the phytoremediation of soil.
The obtained results indicate declining efficiency
in the use of the current mainlines of the Reserve.
But the road and path network of the birch forests ismore frequently used than that of the pine forests,
which are more resistant to the invasion ofsynanthropic species.
Climate and a growing human-made impact on
the natural ecosystems explain the high adaptabilityof synanthropic plants. This study revealed thenonequivalence of different environmental factors
for forming the adaptability of synanthropic species.
Such parameters of the ecoarea as moisturevariability, drainage, light, and anthropotolerance
are gaining particular importance for increasing theability to settle on various habitats.
409

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[15] Kabata-Pendias A, “Trace Elements in Soils
and Plants”, 4th Edition. Boca Raton, FL: Crc
Press, 2010, ch. 7.
[16] Cuningham SD, Berti WR, “Remediation ofcontaminated soils with green plants: an
overview”, In Vitro Cellular & Developmental
Biology - Plant, Vol. 29(4), Oct. 1993, pp. 2072012.
[17] Cuningham SD, Ow DW, “Promises andprospectsofphytoremediation”,
Plant
Physiology. Vol. 110(3), Mar. 1996, pp. 715-719.

Neighboring Countries: State and Prospects, inMaterials of the III International Scientific
Conference, 2006.
[13] Gorchakovsky
PL,
Kozlova
EV,“Synanthropization of the vegetation cover underprotected regime conditions”, Ecology, Vol. 3,
1998, pp. 171-177.
[14] Koroteeva EV, Kuyantseva NB, Chashchina
OE, “Monitoring the composition and structureof synanthropic vegetation at Ilmen nature
reserve”, News of the Samara Scientific Centerof the Russian Academy of Sciences, Vol. 16(1),2014, рp. 1213-1217.

410

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

A STUDY ON THE EFFECTIVENESS OF LIQUID SMOKE PRODUCEDFROM PALM KERNEL SHELLS IN INHIBITING BLACK POD
DISEASE IN CACAO FRUIT IN VITRO
M. Faisal1, Tjut Chamzurni2, Hiroyuki Daimon3
Department of Chemical Engineering, Syiah Kuala University, Banda Aceh, Indonesia; 2Department ofAgro Technology, Syiah Kuala University, Banda Aceh, Indonesia; 3Department of Environmental and Life
Science, Toyohashi University of Technology, Toyohashi, Aichi, Japan
1

ABSTRACTThe effectiveness of liquid smoke made from palm kernel shells in inhibiting black pod disease (Phytopthorapalmivora) in cacao fruit was studied. Palm kernel shells underwent pyrolysis in a slow-pyrolysis reactor at
280°C–400°C. The resulting liquid smoke was then distilled at a temperature of 200°C. The observed parameters
were incubation period and spotting diameter. The experimental design was completely randomized, with a 4 × 6
factorial pattern having four repetitions and consisting of two factors. Both temperature and concentration
significantly affected the incubation period of the fungi causing black pod disease. Additionally, the liquidsmoke concentration had a strong influence on the spotting diameter. Phenolic compounds and acetic acidcontained in the liquid smoke serve as antimicrobials and are bacteriostatic. Although the maximum phenol level
was found at 280°C, the longest incubation period occurred in liquid smoke produced at a pyrolysis temperatureof 360°C. Thus, 360°C was the optimum temperature for producing liquid smoke to inhibit black pod diseasecaused by P. palmivora in cacao.
Keywords: Liquid smoke, Pyrolysis temperature, Biopesticide, Cacao black pod disease, Phytopthora palmivoraof anthracnose, halting the symptoms created by thedisease. Thus, the use of liquid smoke in inhibiting
plant disease is a step toward supporting the ‘gogreen’ organic program.
Presently, farmers still use chemical/synthetic
pesticides that can harm the environment and are notsuitable for human consumption. The damage
caused by synthetic pesticides to soil microbiology
has been intensively studied in the past [5],[6].
Plant-based pesticides are potential alternatives [7].
Cacao black pod disease is caused by theStraminipile genus of Phytophthora [8]. This fungus
can rot the pods at any age and causes a total
production loss of ~30% [9],[10]. The infected pods
display brownish black spots, usually starting at thestem, middle or end of the pods. Under humid
conditions, the spots spread rapidly on the surfacesof the pods, rendering them black and rotten. This
pathogen’s spores are carried by wind and rain water,
infecting other pods and spreading to other plant
stems and branches.
This disease is difficult to control in a curative
manner; therefore, preventive measures, such as
fungicides, are used to stop its spread. Because of
the phytopathogenic nature of this fungi, several of
the biological agents used to combat its associateddiseases are Trichoderma species, such as T.
asperellum, T. harzianum, T. polysporum, T. viride
and T. virens [11]–[14]. A few effective chemicalcompounds used to control/reduce cacao black pod

INTRODUCTION
A major developing industry in Indonesia is oil
palm, which results in abundant biomass waste,
including kernel shells, fronds and empty bunches.
The potential of these waste products has not beenutilized properly, even though Indonesia is anagricultural country with a large agriculture biomass.
One method to utilize such potential is throughpyrolysis to produce liquid smoke [1],[2].
Technology enables the processing of palm kernel
shells into liquid smoke, which contains oxidizedorganic compounds, such as ketone, aldehyde,
phenol, and carboxylic acid, resulting from thecondensation of the pyrolysis vapor [3]. These
compounds give liquid smoke its antioxidant andantibacterial properties, as well as its specific flavor[4]. Phenol and phenolic compounds possessbactericidal and bacteriostatic properties dependingon the concentration used. Phenol and its derivatives
function to denature proteins in bacterial cells anddestroy cell membranes.
Because of the nature of some of its components,
liquid smoke can also function as a plant-based
insecticide and fungicide to inhibit disease-causing
pathogens in agriculture. Previous studies on theeffectiveness of liquid smoke in inhibiting
anthracnose disease in chili plants have been
conducted [1]. Liquid smoke made from palm kernel
shells significantly influenced the incubation period
411

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

disease are metalaxyl- and copper-based fungicides[11],[15]. Additionally, chemical components
containing essential oils, especially terpene, phenol
and alcohol, are being considered for use as
biopesticides because they have various biologicalactivities [16],[17], such as insecticidal [18]–[20],antifeedant [21], repellent [22],[23], lure [24], insect
growth inhibition [25], and antimicrobial [26],[27].
However, essential oils are mostly volatile, easily
decompose, and are unstable when exposed to lightand heat [28],[29]. Liquid smoke may serve as abetter biopesticide because it is more stable, nonvolatile and inexpensive.
Nonetheless, there has been nearly no in-depth
research on the effectiveness of liquid smoke as abiopesticide. Research related to liquid smoke andits applications in agriculture are required to develop
a sustainable agricultural industry. The utilization ofwaste and organic side products to produce liquidsmoke will create an economic added value and an
added social cultural value. This research studied theeffectiveness of liquid smoke made from palm
kernel shells as a plant-based fungicide against black
pod disease caused by Phytophthora palmivora incacao fruit (Theobroma cacao).

infected cacao pods before it was cultivated onhealthy pods. P. palmivora was then inoculated into
healthy pods by puncturing the surface of the pod
once using a straight pin and then placing these pods
into the mica boxes. The punctured sites were theninoculated with P. palmivora using a small 3-mm
cork borer. These inoculated cacao pods were thenincubated for 24 h before liquid smoke was appliedin 2–10% concentrations.
Liquid Smoke Application
Fungicide in Cacao Pods

as

Plant-based

Liquid smoke was applied one day after P.
palmivora inoculation by spraying the whole surfaceof the pods. The observed variables were (1)Incubation time: observations began one day after
the inoculation of cacao pods with P. palmivora
until the first symptoms appeared. (2) Spot diameter:
Observations began two days after the inoculation of
cacao pods with P. palmivora using a ruler andcontinued for the next five days. The data wasstatistically analyzed using the SPSS program fordata in a completely randomized design, with a 4 × 6
factorial pattern having four repetitions andconsisting of two factors. The first factor wastemperature (T), T1 = 280°C, T2 = 320°C, T3 =360°C and T4 = 400°C. The second factor wasconcentration (C), C0 = control, C2 = 2%, C4 = 4%,C6 = 6%, C8 = 8% and C10 = 10%.

RESEARCH METHODS
Liquid Smoke Production
The slow-pyrolysis reactor made of stainlesssteel was 32 cm in diameter, 50 cm in height, andhad a 5-kg capacity. This reactor was equipped witha tar container and temperature control. The upper
temperature was 500°C. Samples of palm kernel
shells were put in the reactor for a certain period oftime and were pyrolyzed at temperatures ranging
from 280°C to 400°C. The smoke was thencondensed into liquid smoke using a stainless steel
condensation unit (diameter of 50 cm and height of
60 cm), resulting in liquid smoke, Grade 3. Thisliquid smoke was then distilled at 190°C to become
Grade 2. The complete process of liquid smoke
production was previously published [1],[2]. The
chemical compounds within the liquid smoke wereidentified using GC–MS based on a method
developed by Guillen and Ibargoitia [30].

RESULTS AND DISCUSSION
Chemical Composition of Liquid Smoke
Liquid smoke is a compound formed during theburning of cellulose, hemicelluloses and lignin. The
pyrolysis of these component results in phenol andacetic acid, which can have antioxidant andantimicrobial characteristics. Phenolic compounds
have antibacterial and antifungal effects [31] thatcan kill rot-causing bacteria that degrade proteins
into amino acids, thereby preventing the foul smell.
Liquid smoke also possesses strong bacteriostatic
properties that inhibit bacterial growth, as well as
fungicidal properties that inhibit fungal growth.
Phenol itself functions as a bactericide because of its
ability to increase the permeability of cell
membranes, inactivating essential enzymes anddestroying or inactivating functional genetic
materials.
The pyrolysis of cellulose produces acetic acidand carbonyls, such as acetaldehyde, glucose andacrolein. The pyrolysis of lignin results in phenol,
guaiacol and syringol, along with their homologs
and derivatives. The numbers and types ofSampling of Cacao Pods
Cacao pod samples were obtained from thePeople’s Plantation at Pidie Jaya, Aceh, Indonesia.
The media used was 21 × 21-cm mica boxes, eachcontaining one cacao pod and labeled based on thetreatment received.
Isolation and Cultivation of P. palmivora
The P. palmivora inoculum was isolated from412

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

compounds contained in the resulting liquid smoke
depend on the pyrolysis temperature and the raw
materials used [1]. An analysis of the liquid smoke
composition at T3 is shown in Table 1. The phenol
and acetic acid contents of liquid smoke are shownin Table 2. The maximum phenol content occurredat the T1 pyrolysis temperature, while that of acetic
acid occurred at T2.

Incubation Time
Incubation time was observed to establish theeffectiveness of liquid smoke concentrations appliedon the cacao pods to halt the fungal growth thatcauses black pod disease. Incubation periods weremarked by the presence of brownish black spots on
the surface of the pods, which will look clear under amagnifying glass. The application of liquid smoke
produced at various temperatures and concentrations
affected the incubation time differently. However,
the temperatures and concentrations did not havevisible interactions. The average incubation times of
P. palmivora after the application of liquid smoke
produced at different temperatures are shown in
Figure 1.

Tabel 1 Liquid smoke composition at 360ᵒC

2
3
4
5
6

7
8
9
10
11

12
13

14
15

R.
Time
5,70
0
6,11
0
7,05
8
7,32
2
11,8
77
12,6
58

Area
182807746
7451840165
792450881

Conc
.(%)
28.0
2
6.93

632271906

12.1
5
9.69

147795235
4
164876203

22.6
5
2.53

13,0
95
13,6
40
14,2
58
14,8
63
15,1
59

280722335

4.30

103445521

1.59

74541045

1.14153070215

2.3544016691

0.67

15,2
92
15,9
25

67054314

1.03

195663312

3.00

16,7
58
17,8
87

83136367

1.27

175252398

2.69

Name
Acetic acid (CAS)
Ethylic acidAcetic acid (CAS)
Ethylic acid
Propanoic acid (CAS)
Propionic acidAcetic acid (CAS)
Ethylic acid
Benzenamine (CAS)Aniline2-Cyclopenten-1-one,
2-hydroxy-3-methyl(CAS) Corylon
Phenol, 4-methoxy

Incubation time (day)

Pe
ak
1

cis-1,3-Dideuterio-1,3cyclohexandiamine
2-Methoxy-4methylphenol
1,3-Benzenediol(CAS) Resorcin
Phenol, 4-ethyl-2methoxy- (CAS) pEthylguaiacol
3-Methoxypyrocatechol
Phenol, 2,6dimethoxy- (CAS)
2,6-Dimethoxyphenol
1,2,4Trimethoxybenzene
1,6-Anhydro-beta-DGlocopyranose

Acetic acid (%)

Phenol (%)

1

Pyrolysis
temperature
280ᵒC

1.29

0.73

2

320ᵒC

2.06

0.62

3

360ᵒC

1.20

0.31

4

400ᵒC

1.86

0.36

4

3
2
1
0
T1

T2

T3

T4

Treatment (Temperature)
Fig.1 Average incubation time of P. palmivora after
the application of liquid smoke (6%) produced at
different temperatures.
The temperature with the longest incubation timeof 3.88 days was T3. Meanwhile T1, T2 and T4 had
similar incubation times, namely 2.62 days, 3.00
days and 2.96 days, respectively. Thus, T3 waseffective in inhibiting the growth of P. palmivora as
proven by the resulting longer incubation time,
which is a criterion of resistance against pathogen
infection. Longer incubation times mean that thesymptoms are slow to appear because the pathogen’s
growth is inhibited.
The longer T3 incubation time was probably
because of the chemical contents of the liquid smoke
produced at T3. According to Lin et al. [32], liquidsmoke’s antifungal properties were influenced by its
pyrolysis temperature. Similar results were shownon the effectiveness of liquid smoke in inhibiting
anthracnose disease in chilies [1], and temperatures
significantly affected the anthracnose incubation
time.
Figure 2 shows the average incubation time of P.
palmivora after the application of liquid smoke atseveral concentration levels.
The
highestconcentration at C4 produced markedly different
results from C0 and C2, but not significantly
different from C6, C8 and C10, although theTabel 2 The content of phenol and acetic acid inliquid smoke
No.

5

Note : % = gr/100 ml

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

incubation times at C2, C4, C6, C8 and C10 weremarkedly different from that of C0 (control). The
lower incubation time at C0 occurred because no
liquid smoke had been applied, leaving the pathogen
free to infect the surface and the fruit of the cacao
pods, resulting in the rapid display of symptoms.
Thus, C4 should be used to control the diseasebecause it inhibited black pod disease longer incacao.

This pathogen can infect internal tissues of the fruit,causing the cacao seeds to wrinkle and change
colors during infection [34]. An analysis of varianceshowed that several liquid smoke concentrationlevels produced significant effects on the spot
diameter of the fungus that causes cacao black pod
disease.
CONCLUSION

Incubation time (day)5

Different temperatures and concentrations had
significantly different effects on the incubation timeof P. palmivora, the causal agent of black pod
disease, and the concentration had markedly
significant effects on the diameter of the spots. The
phenol and acetic acid compounds contained in theliquid smoke have antimicrobial and bacteriostatic
properties. The optimum conditions for inhibiting
the spread of black pod disease in cacao were 360°C
during liquid smoke preparation and the use of 4%
liquid smoke.

4
3
2
1
0
C0

C2

C4

C6

C8

C10

Treatment (Concentration)
Fig. 2 Average incubation time of P. palmivora after
the application of liquid smoke (from T3) at several
concentration levels.

ACKNOWLEDGEMENTS
The Authors acknowledge the financial support
provided by Syiah Kuala University and theMinistry of Research, Technology and Higher
Education of Indonesia. The authors also thank Ms.
Afriyani for help in the data analysis of this study.

The high content of the functional components,
phenol and organic acid, in C4 was able to destroy
the fungal cell membranes, slowing its growth. The
phenol compound increases the permeability of thefungal cell membranes, leading to the loss of nuclei,
and the functional inactivation of genetic materials
and essential enzymes [33].

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

HEAVY METALS IN MICROALGAE BIOMASS ADDED WITH
DIFFERENT CONCENTRATION OF WET MARKET WASTEWATER
Radin Maya Saphira Radin Mohamed¹, Najeeha Apandi², Siti Nor Hidayah
Arifin³, A.A.S. Al-Gheethi4 and Amir Hashim Mohd Kassim5
1, 2, 3, 4, 5

Department of Water and Environmental Engineering, Faculty of Civil and Environmental Engineering, Universiti
Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia

ABSTRACTThe aim of this study was to assess heavy metals content; arsenic (As), cadmium (Cd), lead (Pb) and mercury(Hg) in microalgae Scenedesmus sp. biomass cultivated with wet market wastewater. Microalgae Scenedesmus
sp. added with wet market wastewater which contain high nutrient level has a potential for fish supplement
product. However, it is depending on the level of heavy metals concentration. Different wet market wastewater
was tested in the dilution of 10% (10SWM), 15% (15SWM), 20% (20SWM), and 25% (25SWM) during thecultivation to measure the potential by-product quality. Heavy metals for As, Cd, Pb and Hg in dry biomass of
Scenedesmus sp. were measured by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Mercury
Analyser. Heavy metals content (ug/kg in ppb) in the Scenedesmus sp. were found in the range of As (182.57.74), Cd (0.985-3.111), Pb (4.95-2.375) and Hg (9.774-1.037). Arsenic was the highest trace metals (182.5 ppb)
found in 25SWM and the lowest (0.311 ppb) was Cd (cadmium) from BBM (Bolt’s Basal Medium) sample. The
level of heavy metals in all microalgae biomass samples did not exceeded the maximum concentration set up by
the European Commission Regulation. Therefore, the biomass from microalgae Scenedesmus sp. cultivated withwet market wastewater has acceptable concentration of As, Cd, Pb and Hg. Thus, make it a great potential for
upcoming bio products such as fish feed and fish supplement.
Keywords: Heavy metals, Scenedesmus sp., Wet market wastewater, Heavy metals concentration
and biomass production [4, 5]. Gani et al., [6] hadstudied the use of microalgae and had successfully
removed up to 93.3% of total organic carbon fromwastewater while the algae became a potential forbiodiesel production. Wastewater treatment by using
microalgae is eco-friendly and offers the advantage
of a cost effective way of nutrient removal andbiomass production [7]. Since microalgae have theability to absorb nitrogen and phosphorus levels [8],instead of the nutrients being wasted; this will
provide nutrients for the microalgae to grow which
in turn become valuable biomass products [910].Since microalgae has been recognized as a very
favorable source of biomass, this can be applied inorder to treat wastewater efficiently without
involving high production cost. Microalgae are also
the best candidate to decrease heavy metals
concentration from ppm to ppb levels and known tobe resilient to the contaminants of high concentrated
wastewater [11].
There are few types of toxic heavy metals that
may impact in human and animal diseases andmortality. The content of toxic heavy metals willlead the effect of the biomass quality. Heavy metals
are dangerous because they tend to bioaccumulate
the concentration of a chemical in a biologicalorganism over time, compared to the chemical
concentration in the environment [12]. Those four
selected toxic heavy metals were Arsenic (As),Cadmium (Cd), Lead (Pb) and Mercury (Hg). To

INTRODUCTION
There are many markets available for buyers to
get fresh foodstuff such as the wet market.
Unfortunately, wet market wastewater which
consists of variety components such as nitrogen andphosphorus commonly discharge directly to thedrainage without any treatment [1]. In Malaysia,
most of the wastewater will be channeled into thedrainage and end up flowing into the river. Thisphenomenon escalates the pollution among
Malaysian rivers. Thus, a river in Perlis, Malaysia,
has been polluted with wastewater mostly comingfrom the effluent of food-based wastewater which
includes wet market with a 58.30 (polluted), 61.87(slightly polluted) and 41.64 (polluted) of water
quality index [2]. Wastewater from wet market
contains nutrient and heavy metals derived from the
fresh foodstuff, waste scraps of seafood and fish
entrails. The wastewater discharged contains various
wastes such as organic materials, suspended solid,
fat, and toxic compound such as heavy metals. The
content of organic matter found in wastewater fromwet market is three times more than in solid waste[3]. Although low concentration of heavy metalmight give no harm to the living organisms, but highlevels of it are potentially toxic.
For the past few years, a lot of research was
carried out to study on the value potential of dual
application of microalgae for wastewater treatment
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

evaluate and remove four toxic heavy metals (As,Cd, Pb and Hg) the process of bioremediation
technology has been applied in this study [13]. The
existence of heavy metals in the wastewater may
affect the characteristic compound on the microalgae
which automatically constitute negative impact tothe main food source for bivalve mollusks at their
growth stages (zooplankton; larvals stages ofcrustacean and fish species) [14]. Furthermore, these
toxic metals in microalgae could be a threat to theecosystem and public health and must be treated.
Therefore, this study is to evaluate the heavy metals(As, Cd, Pb and Hg) contents from biomass thatderived from different concentration of wet market
wastewater.

Onn Malaysia. The inoculum of Scenedesmus sp.
was maintained in Bolt’s basal medium (BBM) prior
to experiment. The experiment was carried out using
2L of Erlenmeyer flask containing 1.5 L ofwastewater and Bolt’s Basal Medium (BBM). BBM
medium was used as control media. Microalgae
were cultivated under outdoor sunlight with
continuous aeration at 3.2 L/min to ensure the
distribution of nutrients using atmospheric air froman aquarium pump through air spurger. The
experiment flask was inoculated with the same
initial microalgae cells of (106 cells/ml) at thestarting day of the experiment. The biomass was
harvested immediately after 12 days bycentrifugation at 4000 rpm for 5 min. The sample
was then kept and stored at -20 °C until further
analysis. The cultivation batches were carried out in
duplicate.

MATERIALS AND METHODS
Wastewater Characterization and Experimental
Procedure

Sample Preparation and Analysis
The frozen microalgae sample was melted
individually and dried at 105°C to a constant weight.
Dried microalgae were then finely crushed andhomogenized using mortar and pestle and about 0.5g
of the homogenized sample was digested in 10 ml of
HNO3 (nitric acid) at 160°. The solution was diluted
with deionized water up to 50ml and analyzed forheavy metals content using Inductively Coupled
Plasma Mass Spectrometry (ICP-MS) for As, Cd, Pb
and Hg and Mercury Analyser for Hg [16].

Untreated wet market wastewater (WM) wascollected from Pasar Borong Rengit, Batu Pahat,
Johor, Malaysia (N 1° 40' 39.5144" E 103° 8'
43.7844"). Wet market wastewater has been taken
by grab sampling according to the standard of
APHA (2002) [15]. The main organic waste fraction
was from seafood and fish entrails and market’s
activities operations. Wastewater was transported to
the laboratory and went under sterilization using
autoclave at 120°c for 15 minutes. Wet market
wastewater sample was filtered with GF/C
(Whatman) filter to remove suspended solids anddiluted with distilled water into four concentrations
10%, 15%, 20% and 25% in triplicate toinvestigating the effect of different concentration inorder to support microalgae growth. Bolt Basal
Medium (BBM) was used as control media. The
experiment was conducted in duplicate for eachconcentration. Physical and chemical parameters
were analyzed according to the standard method
given in APHA (2002) [15]. Samplings forparameters analysis were collected before and after
the treatment. Total parameter removal efficiencies
was calculated accordance with Eq. (1)Removal, % = Initial conc. (mg/L) – Final conc. (mg/L)
Initial conc. (mg/L)

RESULTS AND DISCUSSION
Wastewater Characteristics
Wet market wastewater remediated with
Scenedesmus sp. was evaluated for the pollutants
parameter removal of biochemical oxygen demand(BOD), chemical oxygen demand (COD) andturbidity. The percentage removal efficiency before
and after the microalgae Scenedesmus sp. cultivation
was shown in Table 1. The removal efficiency of
BOD and COD of microalgae Scenedesmus sp.
reached relatively high values; BOD (83.6%) from
25SMW, COD (94.7%) from 15SM.Comparing to
the research data result from other study by Violeta
et al., (2011) [17], this study achieved slightly highremoval of BOD at 94.7% from wet market
wastewater compared with Violeta et al., (2011)
with a BOD removal of 92.12% from Scenedesmus
sp. cultivation using sewage wastewater. The
reduction of BOD and COD by microalgae
cultivation because of the absorption of carbon
dioxide since microalgae has the ability inconverting BOD and COD concentration into theircarbon sources of living [18-19]. As for pH
parameter in each sample was slightly decreased andshowed that the pH levels are not exceeding thex 100

Eq. (1)

Cultivations of Scenedesmus sp. Using Wet
Market Wastewater
Microalgae Scenedesmus sp. was obtained from theculture collection of Faculty of Science, Technology
and Human Development, Universiti Tun Hussein
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standard A & B [20]. Assimilation of photosynthetic
activity reduce the pH levels due to the ammonia
concentration react as a nitrogen source formicroalgae to grow [9, 21].
Heavy Metals Content in Microalgae Biomass± 2.7 ppb) and 10SMW (76.86 ± 10.5 ppb). The
following metal value after mercury is Lead (Pb)with a total of 4.95 ± 4.82 from 15SWM. Next, thelowest metal is Cadmium (Cd) with a total of 0.985± 0.124 from the biomass of 20SMW. For BBM
biomass shows that the total value of all metal arevery low compared to others biomass sample
directly verified that this microalgae Scenedesmus sp.
are non-toxic algae straightly proved that this kindof microalgae are harmless. Low levels of trace
metals in this study could be affected from thedilution due to low parameter content in thewastewater.

According to the Table 2, the highest
concentration mostly dominated by the Arsenic (As)with the value of 182.5 ± 7.18 ppb from the biomassof 25SMW. This amount may due to highconcentration of wastewater medium (25% of wet
market wastewater) during the microalgae
cultivation process, compared to biomass from (7.74

Table 1 Percentage Removal of Wet Market Wastewater Characteristic
10SWM
Parameter

15SWM

After
(MSC)
7.0

%

pH

Before
(MSC)
7.36

BOD

349

COD

574

20SWM

After
(MSC)
6.4

%

-

Before
(MSC)
7.41

74

78.8

375

32

94.4

639

25SWM

After
(MSC)
6.18

%

-

Before
(MSC)
7.49

After
(MSC)
6.79

%

-

Before
(MSC)
7.52

78

79.2

512

87

83

566

93

83.6

34

94.7

647

46

92.9

689

56

91.9

-

*MSC: Microalgae Scenedesmus sp. Cultivation
Table 2 Heavy Metals Content in Microalgae Biomass Compared with the Maximum Content of the European
Commission Regulation (2015)
Remarks
Heavy
MetalsArsenic(As)
Cadmium(Cd)
Lead (Pb)
Mercury(Hg)

BBM(control)
7.74 ±
2.7
0.311 ±
3.9
2.695 ±
5.1
1.44 ±
0.00

Microalgae Biomass Concentration(ug/kg as in ppb)
10SWM
15SWM
20SWM

25SWM

Low

Max. content in ug/kg(ppb)(EU) No 186/2015
25000

76.86 ±
10.5
0.319 ±
3.25
3.36 ±
0.343
9.774 ±
0.00

182.5 ±
7.18
0.413 ±
2.03
2.375 ±
5.59
2.422 ±
0.00

Low

2000

Low

10000

Low

200

Low

25000

107.7 ± 3.68
0.515 ± 3.12
4.95 ± 4.82
3.502 ± 0.00

117 ±
11.98
0.985 ±
0.124
3.195 ±
1.57
1.033 ±
0.00

The tests deduced that the microalgae Scenedesmus
sp. biomass cultivation using four different mediumsof wet market wastewater are harmless and nontoxic where all the values of heavy metal
concentrations are below the limit based on theEuropean Commission Regulation (2015) [22]. In
order to protect public health, it is appropriate torefer the maximum levels of metal that are safe forhuman/animal exposure in foodstuffs [22, 23]. Uponto this achievement of evidence in proving the
production of non-toxic algae biomass cultivatedfrom wet market wastewater, this experiment can begreat potential for upcoming bioproducts such as
fish feed, food supplement for humans and animals
and fertilizer.

Fig 1 Heavy Metal Concentrations in Microalgae
Biomass Sample BBM,
10SMW, 15SMW, 20SMW and 25SMW (ug/kg in
ppb)

419

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

biofuels production,” Applied Energy (88)3411-3424 (2011).
[5] NM Jais, R Mohamed, AA Al-Gheethi,
MKA Hashim, “The dual roles ofphycoremediationofwetmarketwastewater for nutrients and heavy metals
removalandmicroalgae
biomass
production,” Clean Technologies andEnvironmental Policy 19 (1), 37-52 (2017).
[6] P. Gani, Norshuhaila Mohamed Sunar,
Hazel Matias-Peralta, Siti Suhana Jamaian,and Ab Aziz Abdul Latiff, “Effects ofDifferent Culture Conditions on the
Phycoremediation Efficiency of Domestic
Wastewater” Journal of Environmental
Chemical Engineering, 2213-3437 (2016).
[7] Wilkie AC, Mulbry WW, “Recovery ofdairy nutrients by benthic freshwater algae.”
Bioresource Technology, 84:81-91 (2002)[8] Zhang, E., Wang, B., Wang, Q., Zhang, S.,& Zhao, B., “Ammonia-nitrogen andorthophosphate removal by immobilized
Scenedesmus sp. isolated from municipal
wastewater for potential use in tertiary
treatment,”Bioresource Technology, 99(9),3787–3793 (2008).
[9] NM Apandi, RMSR Mohamed, N.A.A.
Latiffi, N.F.M. Roslan, A.A.S. Al-Gheethi,“Protein and lipid content in biomass frommicroalgae Scenedesmus sp. grown in wet
market wastewater,” MATEC Web
Conferences 103, 06011.
[10] E.W Becker, Micro-Algae as a Source ofProtein Biotechnology Advances 25(2):207–10. (2007)[11] Latiffi, Nuratikah Ahmad, Radin Maya,
Saphira Radin Mohamed, Najeeha Mohd
Apandi, and Amir Hashim Mohd Kassim.
“Application of Phycoremediation Using
Microalgae Scenedesmus Sp . as
Wastewater Treatment in Removal of
Heavy Metals from Food Stall Wastewater.”Applied Mechanics and Materials 773,
1168-1172 (2015).
[12] Kulbat, E., Quant, B., Geneja, M., &Haustein, E. Heavy Metals Removal in the
Mechanical-Biological
Wastewater
Treatment Plant “ Wschód ” in Gdańsk,12(5), 635–641 (2003).
[13] Muyssen, B. T. a, & Janssen, C. R. “Zincacclimation and its effect on the zinc
tolerance of Raphidocelis subcapitata andChlorellavulgarisinlaboratory
experiments,” Chemosphere, 45(4-5), 507–
514 (2001).
[14] Wang, Ya et al. “Review of Arsenic
Speciation, Toxicity and Metabolism inMicroalgae.” Reviews in Environmental
Science and Bio/Technology 14(3):427–51

CONCLUSION
The use of microalgae Scenedesmus sp.
cultivation in wet market wastewater treatment is
one of the alternative way in wastewater treatment
before it can be discharged to the drainage. The
result of metal concentration in dry biomass in eachsample mostly acceptable under the regulation which
are beneficial to make father experiment inproducing bioproduct. It can be said that the
microalgae Scenedesmus sp. has potential inabsorbing pollutants that contain in wastewater.
Although, levels of heavy metals in this study were
below than the standard regulation (EU) No
186/2015) (Table 2), monitoring on morecontaminated wet market wastewater should becontinuously necessary since wet market wastewater
has high nutrient and pollutants parameter when thesample is not dilute. Hence, the microalgae
Scenedesmus sp. extracted from wet market
wastewater in this study is non-toxic and risk-free tobe consumed in producing as variety of bio products
such as fish feed, fish supplement and much more.
ACKNOWLEDGEMENTS

This research was funded under the FRGS
(1574) and E-Science Fund project vot no: S029.
Special thanks to Dr. Hazel Monica Matias-Peralta
for providing the microalgae cell and any parties thatinvolved in this project specifically Universiti Tun
Hussein Onn Malaysia for providing the equipment
and research facilities to carry out this project.
REFERENCES[1] AY Maizatul, RMSR Mohamed, AA AlGheethi, MKA Hashim, “An overview of
the utilisation of microalgae biomass
derived from nutrient recycling of wet
market wastewater and slaughterhousewastewater,”International
Aquatic
Research, 1-17 (2017).
[2] W.A.Amneera, N.W.A.Z. Najib, S.R.Mohd
Yusof, S.Ragunathan., “Water quality
index of Perlis river, Malaysia”,
International Journal of Civil&
Environmental Engineering IJCEE-IJENS,
vol:13, no:02, 1312102-9595 (2013)[3] Santos, C., & Robbines, M. Low-CostInnovative Solutions for Treating PublicMarket Wastewater in the Philippines:
Deploying Hybrid Anaerobic/Aerobic
Cocopeat Filtration Systems, 2011.
[4] Rawat, I., Ranjith Kumar, R., Mutanda, T.,& Bux, F, “Dual role of microalgae:
Phycoremediation of domestic wastewaterand biomass production for sustainable
420

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017(2015).
[15] APHA “Standard Methods for the
Examination of Water and Wastewater”,
22th edition. American Public Health
Association American Works Associationand Water Environment Federation USA,(2012).
[16] Ogoyi, D. O., C. J. Mwita, E. K. Nguu, andP. M. Shiundu, “Determination of Heavy
Metal Content in Water, Sediment andMicroalgae from Lake Victoria, East
Africa”,
The
Open
Environmental
Engineering Journal 4:156–61 (2011).
[17] Violeta, Vaida Andrulevičiūtė, Virginija
Skorupskaitė, and Jūratė Kasperovičienė,“Cultivation of Microalgae Chlorella Sp.
and Scenedesmus sp. as a Potentional
Biofuel Feedstock” 57(3): 21–27 (2011)[18] P Gani, N M Sunar, H Matias-Peralta,
RMSR Mohamed, AAA Latiff, UK Parjo,“Extraction Of Hydrocarbons FromFreshwater
Green
Microalgae(Botryococcus
Sp.)
Biomass
after
PhycoremediationofDomestic
Wastewater”, International Journal of
Phytoremediation, Taylors & Francis, 1,
679 (2017).

[19] N.Abdel-Raouf, A.A.Al-Homaidan, I.B.M.
Ibraheem, “Microalgae and wastewater
treatment” Saudi Journal of Biological
Sciences 19, 257-275 (2012)[20] Law of Malaysia Act 127, “Environmental
Quality Act (1974)” (1975).
[21] A Latiffi, N Atikah, R Mohamed, RM
Saphira, NM Apandi, RM Tajuddin,“Experimental Assessment on Effects ofGrowth Rates Microalgae Scenedesmus sp.
in Different Conditions of pH, Temperature,
Light Intensity and Photoperiod,” KeyEngineering Materials 744, 546-551 (2017).
[22] Commission Regulation (EU) 2015/186 of
6th Feb 2015, Official Journal of theEuropean Union L 31/11 (2015).
[23] Radin Mohamed, Radin Maya Saphira,Haritharan Maniam, Najeeha Afandi, Adel
Ali Saeed Al-Gheethi, Mohd Kassim, Amir
Hashim, “Microalgae Biomass Recovery
Grown in Wet Market Wastewater via
Flocculation Method Using Moringa
oleifera,” Key Engineering Materials 744,542-545 (2017).

421

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

INFLUENCING PARAMETER OF SELF PURIFICATION PROCESS IN
THE URBAN AREA OF CIKAPUNDUNG RIVER, INDONESIA
1

Yonik Meilawati Yustiani1, Mia Nurkanti2, Neneng Suliasih3 and Annisa Novantri4
Dept of Environmental Engineering, Engineering Faculty, Pasundan University, Indonesia;2Faculty of
Education, Pasundan University, Indonesia ,3Faculty of Engineering, Pasundan University, Indonesia

ABSTRACTSelf purification process is an important process in the effort of recovering the river condition itself. This
process usually takes place naturally. However, several inhibitions might disturb the process. It was indicated by
the slow deoxygenation rate and unhealthy river condition. This research aims to identify the influenceparameters responsible on the slow of self purification in the Cikapundung River, which is located in the urban
area of Bandung City, Indonesia. The river water samples were taken and analyzed in the laboratory to obtain thewater quality. The deoxygenation rate was also calculated based on the Slope Method after data was acquired
from 10 days daily observation. Research showed that the value of urban river deoxygenation rate is relatively
low. The low value of the rate of deoxygenation led to the difficulty in rivers to purify themselves. Pollutants
inhibiting the process include phenol, detergent, and heavy metals, which are contaminating the river over the
maximum standard. Biologically, the decomposer consists in the river is few. It leads to a slow organic
degradation rate. The condition is representing the low capacity of self purification of the Cikapundung River
which is caused mainly by chemical and biological parameters.
Keywords: Self Purification, Deoxygenation Rate, Urban River, Water Quality

INTRODUCTION

chemically and biologically.
Degradation of organic pollutants is primarily
affected by the river water characteristic.
Contaminants generated from industries can threat toriver capability of self purification. Several
indicators can be used to explain on how the natural
remediation of river cannot be carried out. This
research was conducted to investigate theinfluencing parameter of self purification process inthe urban area of Cikapundung River. The result canbe useful to track the pollutant sources and handle
the issue from the initial causes.
BOD (biochemical oxygen demand) and COD(chemical oxygen demand) are 2 essential parameterof water quality to describe the organic pollutant
condition of rivers. Thus BOD and COD are two
widely used parameters for organic pollution
measurement [4].
BOD (Biochemical Oxygen Demand) has a strong
relationship with DO because it indicates the needfor oxygen to decompose organic matter in thewaters. Therefore, BOD becomes an importantfactor to evaluate the level of pollution of organic
matter in the river [5]. Deoxygenation is the processof decreasing the amount of oxygen that occurs dueto the use of oxygen by microorganisms todecompose pollutants into the aquatic bodies [6].
The deoxygenation process is an important process
in the effort of the river to self purification process,i.e. degradation of bio-degradable organic pollutants
to re-clean the water. The rate of the deoxygenation

Cikapundung River is a river that passes throughBandung. As the capital of West Java Province,
Bandung City is a city with a large population,
which is more than 2.4 million people. The rapid
development of the population stimulates the growthof settlements on the banks of the CikapundungRiver without adequate sanitation facilities.
Cikapundung River becomes a place of disposal ofliquid waste from the activity around the river banks.
Rivers in urban areas, including Cikapundung,
have various functions, such as drinking water
sources, recreational locations and main drainage
canal [1]. The river is the main natural andecological site from a water management
perspective [2]. Some parameters are set in thequality standards to maintain the health of the river.
Organic pollutant can be removed naturally inrivers. The process is performed by microorganisms.
Several physical, chemical and biological activities
involves in the river water organic pollutant
degradation. Many of these physical and chemical
activities are influenced by the biological condition.
The removal of pollutants from a water bodywithout any artificial controls is called self
purification, or natural purification [3].
Many urban rivers in Indonesia suffer with heavy
pollution. Their capabilities to perform self
purification appear relatively low and resulting thedeterioration of the water quality, physically,
422

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

process affects the sooner or later self purification
takes place. The rate of deoxygenation rate is also an
important tribe in the Streeter-Phelps equation whichis always used to model the quality of river water.
The rate of deoxygenation rate can be specific if it isin an area with different temperatures. In addition,
the quality of the river, the presence of matter andpollutants in the river will affect the rate ofdeoxygenation. Research on deoxygenation is veryrare in Indonesia.
The non-optimization of the work of decomposing
microorganisms is also one of the factors that
influence the process of self-purification in the river.
Therefore, in this study the condition of decomposer
microorganisms becomes one of the components tobe studied.

river water. Not only polluted by the untreatedwastewater, the river is also suffering from the solid
waste. Cikapundung River plays a very strategic role
as one source of water supply for Bandung, but its
water quality decreased for several years [8].
Besides that, the Cikapundung river basin is one of
the sub watershed Citarum that serves as the main
drainage channel of Bandung [9].
Data Collection
Data was collected from previous research andalso from the government agency that performperiodic monitoring on the rivers. Measurement ofriver water quality is conducted regularly by theEnvironmental Protection Agency of Bandung City
and West Java Province. Several points wereappointed as sampling locations. The data were thenbeing calculated to have average values.
Primary data was also obtained by laboratory
analysis of the river water samples to investigate thetype of microorganisms living in the water.

METHODOLOGY
Research Location
Cikapundung River is chosen to represent theurban city river. Figure 1 shows the location of the
Cikapundung River.

Parameters
The investigated parameters to determine the self
purification process in the urban river are including
deoxygenation rate, BOD/COD ratio, heavy metals
and surfactant concentration. The deoxygenation rate
will indicate the degradation process of organic
matter. BOD/COD ratio can describe thebiodegradation capacity of the river [3]. Heavy
metals and surfactant were considered as theinhibitorsofdecomposition
processbymicroorganisms.
RESULT AND DISCUSSION
Deoxygenation Rates
Table 1 shows the deoxygenation rate of
Cikapundung River water located in the upstream
and downstream of Bandung City area.

Fig.1

The deoxygenation rate obtained from previous
studies ranged from 0.010 to 0.26 per day. It was
found that deoxygenation rate value was relatively
low. This low rate of deoxygenation causes the slow
recovery of organic pollution in the river. Seasons do
not appear as an influencing factor for the
deoxygenation rate value. Generally, there is no
significant trend that differentiates between dry

Research location and sampling points [10].

The rivers pass through Bandung City's most
crowded area [7]. The Cikapundung river water
quality suffers with the wastewater that being
disposed directly without prior proper treatment.
The condition stimulates the worse quality of the423

Deoxygenation rate (per day)Deoxygenation rate
Upstream
Downstream
Year Dry Season
Rainy Season Dry Season Rainy Season
2011
0.146
0.19
0.023
0.26
2012
0.016
0.1
0.08
0.01
2014
0.24
0.24
0.03
0.37
2015
0.13
0.12
0.19
0.29

Deoxygenation rate (per day)

Table 1 Deoxygenation rates of Cikapundung River

0.600

0.600 0.500

0.500 0.400

0.400 0.300

0.300 0.200
0.200

0.100
0.000

0.100

0.000

0.02

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017season and rainy season [7].
Typical range of the deoxygenation rate for thesurface water is 0.10-0.23 mg/L [11]. As comparison,
the rates of deoxygenation of rivers outside
Indonesia are found in the typical range such as Ravi
River in Pakistan has 0.14-0.27 per day [12], andGomti River in India has 0.45 per day [13].
Low rate of deoxygenation is typically found in
the clean water without organic matter andmicroorganisms. The low of deoxygenation rate canalso be caused by the turbulent condition of river
flow [14].

toxic substances to the mixed culture of
microorganisms responsible for the decompositionof organic matter [18]. The decomposing
microorganisms play an important role in the selfpurification of polluted river, thus heavy metals
pollution might weaken the capability of river topurify itself.
Based on the laboratory analysis for identificationof living decomposer microorganisms in the water, it
was found that the only living bacterium was
Bacillus sp type. This bacterium is the most active
decomposer of organic matter in the river water.
Consortiums of the Bacillus sp can effectively
reducing organic pollutants [19]. Bacillus sp is nonpathogenic organisms [20]. Fungi that were existed
include Penicillium sp, Aspergillus sp and
Cladosporium sp. Several of the species in genus
Penicillium and Aspergillus are known to produce
mycotoxins in other substrates [21]. Those fungi areusually found in the treated and untreated water.
Aspergillus and Penicillium spores are the mostwidespread aeroallergens in the world [22].
Activity of washing can also pollute the river,
especially by the surfactant contaminant. It canaffect the deoxygenation rate. An experimental
substantiation was given to the potential
environmental significance of the effect caused by
the influence of synthetic surfactants on hydrobionts
and the relationship between these effects and thehazard of anthropogenic impact on the processes ofwater self-purification [23]. Surfactants are diverse
and amphiphilic compounds which can reducesurface and interfacial tensions [24].

BOD/COD ratio

BOD/COD Ratio
The Fig. 2 depicts the calculation of BOD/COD
ratio of Cikapundung River water during 2012-2014.
The values were determined based on the periodical
data of the river water quality.
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0

0.678

0.488

0.600
0.395

0.198

2012
AverageFig. 2

0.790
0.738
0.638

0.198

2013
Year
Max

2014
Min

BOD/COD ratio observed.

The range of BOD/COD ratio is 0.198-0.790. A
value of more than 0.5 of BOD/COD ratio indicates
rapid biodegradation; and a range of 0.2-0.4
specifies biodegradation only in favorable thermal
condition [15]. The ratio of Cikapundung River
water mainly denotes the rapid biodegradation
process. It probably occurred in the anaerobic
condition.
Considering the processes indicated by the
deoxygenation rate, i.e. oxidation of organic material
and aquatic plants respiration, the low value of therate can probably denote a non-optimal condition of
the processes. Decomposition of organic matter by
the microorganism can be inhibited by several
conditions, such as toxic material and heavy metals.
The river quality data of Cikapundung show thatseveral heavy metals were detected above theconcentrations standard, i.e. Cr+6, Zn, Mn, Cu, and
Pb. Research on the heavy metals impact on the biodegradation of organic matter are not generally
explained, however the metals has potency on
inhibiting biodegradation of pollutants under both
aerobic and anaerobic conditions [16]. Heavy metals
form complexes with protein molecules that causing
inactivation of cells [17].
In the surface water, heavy metals consider as

CONCLUSION
The deoxygenation rate of Cikapundung is quite
low, indicating the slow process of self purification.
However, the ratio of BOD/COD shows that thewater has potential rapid biodegradation rate. The
The existence of heavy metals, synthetic
surfactant, antimicrobial substances, indicate theunhealthy condition, especially in considering theself purification process. Toxic pollutants fromvarious activities would inhibit the microorganism tolive in the river water and to decompose the organic
pollutants.
ACKNOWLEDGMENT
This research was funded by the Ministry of
Research, Technology, and Higher Education of the
Republic of Indonesia.
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Information System of Modeling andMonitoring of Cikapundung River, Bandung,424

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

Indonesia”, Procedia Engineering 154, 2016, pp.
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Rewicka A, Nowak P, “BOD measuring andmodeling methods – review”, Land Reclamation
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[6] Kumarasamy MV, “Deoxygenation andReaeration Coupled hybrid mixing cells Based
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India”, KSCE Journal of Civil Engineering Vol
12 No.2 March 2008.
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Deoxygenation Rate of Carbon in Upstream
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Esplugas S, “Contribution of the ozonation pretreatment to the biodegradation of aqueous
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425

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THE PHYSICAL MICROHABITAT REQUIREMENTS OF
FRESHWATER MUSSEL, WESTRALUNIO CARTERI, (BIVALVIA:HYRIIDAE) IN SOUTH-WESTERN AUSTRALIA
1

Le Ma1, Alan Lymbery2, Stephen Beatty3 and David Morgan4
Centre for Fish and Fisheries Research, School of Veterinary and Life Science, Murdoch University,
Australia

ABSTRACT
Freshwater mussels (Bivalvia: Unionoida) are important for maintaining the water quality. Carter’sFreshwater Mussel, Westralunio carteri, is the only species of freshwater mussel in the south-west of Australia,
and the only representative of Westralunio in Australia. Eighteen sites from thirteen rivers have been surveyed inthis research for investigating the physical microhabitat requirements of W. carteri. Substrate type, debris size
and water depth are believed to have significant impacts on the microscale occurrence of W. carteri. In channel,
locations with shallow water, fine substrates and relative larger debris are most favored by freshwater mussels.
Shadows of trees or bridges may have a less significant impact. Juvenile mussels are suspected to have a slightly
different microhabitat requirements with adult mussels.
Keywords: Westralunio, Bivalvia, Freshwater mussels, Ecology, Microhabitat

Australia and the sole representative of Westralunio
present on the Australian continent [18]. A
combination of drought, increasing salinity andnitrate-related pollution has led to a >60% decline
in its extent of occurrence (EOO) over the past fifty
years, resulting in its classification as a ‘Vulnerable’
species by both international and local conservation
regulatory bodies [19], [20]. A map of W. carteri’s
presence and distribution has been produced,
however, detail concerning the living quality of thisspecies is remaining unclear [18]. Investigation into
the microhabitat requirements of W. carteri will help
to reduce this knowledge gap and improve theconservation of this species.
This research firstly attempted to determine the
distribution of Westralunio carteri in the rivers ofsouth-western Australia from a microhabitat
perspective. We hypothesized that the occurrence ofW. carteri is affected by several selected stream
characteristics.

INTRODUCTION
Freshwater bivalves (Mollusca: Bivalvia:
Unionoida) play significant roles for the balance ofboth freshwater ecosystems and development of
human cultures [1], [2]. Freshwater mussels act as“ecological generalists” and benefit to the freshwatercommunities through the filter feeding function [3],[4]. Their presence further improves water quality
through reducing the overall nutrient level [5] andthe concentration of several chemicals [6], thereby
reducing the probability of detrimental algal blooms
and eutrophication. Unionoida is also key coupler,
enhancing the links between benthic and pelagic
systems through burrowing the sediment andreleasing biological waste into water [7], [8]. Afterthey dead, their shells may be occupied by otheraquatic organisms as shelters and refuges [9], [10].
Additionally, they can be a source of mother-ofpearl and food for economy values [11], [12].
It is widely recognized that environmental
features, especially stream characteristics, are able toinfluence the distribution of unionid species. [13]believed that microhabitat features are goodpredictors for investigating the distribution ofbivalves. For instance, substrate sediment-type andhydrology are known to strongly influence the
distribution of freshwater bivalves in waterways [14],[15]. Freshwater mussels tend to favor areas ofincreased flow stability, and in flood-periods rely on
areas of reduced particle movement [16], withmicrohabitat preferences similar across life-stages[15], [17].
Carter’s Freshwater Mussel, Westralunio carteri,is the only known Unionoida in the south-western

METHODS AND MATERIALS
Survey sites
Eighteen sites in thirteen rivers were selectedbased on the distribution of Westralunio carteri inprevious records [18]. Gingin Brook, Yalyal Brook,
Marbling Brook, and Ellen Brook, located to thenorth of Perth City, flow through agricultural areasfrom the east to the west. Bennett Brook and the
mid-downstream part of Canning River, in the Perth
Metropolitan Region, are situated in urbanised
regions. To the east of Perth, Helena River and the
upstream reach of Canning River originate in the426SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Darling Scarp, in areas largely covered by native
vegetation. North Dandalup River and Collie Riverlie to the south of Perth in agricultural areas. Finally,
Warren River, Fly Brook, Lefroy Brook and Smith
Brook are located in the south-western corner ofWestern Australia. Sampling occurred between
March and June 2016 (i.e. spring to early winter).
The location of each site was recorded by GPS
handset.

A total number of 604 mussels were recorded
and examined from twelve sites in eight rivers.
Mussel density ranged from 0 to 512 mussels/m2
with half of the investigated quadrats having nomussels. The mean number of mussels/quadrat was
2 (±0.210) for all quadrats, and 3.67 (±0.331) for
those quadrats with mussels present, while themedian number is slightly lower, with 1 mussel per
quadrat for all quadrats or 2 mussels per quadrat for
the quadrats having living mussels. The quadratslevel mussel density distribution did not show
significant difference (unpaired t-test, p=0.9535)
with the transect-level in the analysis results asshown in fig 1. Living mussels were not detected in
the selected reaches at Ellen Brook, Fly Brook,
Lefroy Brook, Marbling Brook and Smith Brook.

Mussel samplingAt each site, four to five transects were selectedby channel accessibility and 10 random quadrats(each 25 cm × 25 cm) were taken at each transect.
For each transect, surveys occurred in a downstream
to upstream direction for a distance of up to 10 m ofstream. Several selected in-stream environmental
characteristics were recorded as shown in table 1.
Mussels in each quadrat were searched by hand.
Substrate was classified following the method usedby [21]. Debris was classified as wood, leaves orother artificial debris. Current velocity wasmeasured by a Hontzsch® HFA 711 series handheld flowing meter at the water surface. Riverbed
slope was measured by magnetic protractor. Finally,
the condition of surrounding channel valley was
roughly assessed following the method in [22] andrecorded.
Table 1 Variables for modelling the micro-habitat
requirements of Westralunio carteri
Variable Name
Mean ± s.e.
Range

Fig. 1

Water Depth (m)0.25±0.009

0.02-0.92

Streambed Slope (º)

7±0.4

0-49

Debris Type

Wood, Leaf and Artificial

Debris Height (cm)

5±0.6

0-166

Debris Cover (%)

38±2.20-100

0.67±0.07

0-1.00

3±0.1

0-10

Macrophytes Cover (%) 33±2.4

0-100

Current Velocity (m/s)
Substrate Grain Size*

Observed mussel density distribution attransect (a) and quadrat (b) level.

Mussels were found among a wide range ofsubstrate types from silt to large rocks, while themajority of population inhabits fine silt. Channel
width ranged from 2-33 m (7.19±0.880 m) withrelatively narrower water width (5.94±0.736 m).
Riverbanks at all selected locations were vegetatedwith grass and trees.
Table 2 Variables for modelling the micro-habitat
requirements of Westralunio carteri
Variable Name
Estimate P value

Distance to riverbank
1.0±0.04
0-3.9*
the substrate grain size is converted to SedimentParticle Index following the method used by [21].
Statics
All collected data was processed by R software.
The habitat requirements were analyzed throughgeneral liner regression model (glm) with binomial
distribution. A decision tree was applied to find themost significant predictors for the occurrence of W.
carteri.

Water Depth (m)

0.465

0.522

Streambed Slope (º)

0.014

0.313

Debris Height (cm)

0.028

0.085

Debris Cover (%)

0.000

0.869

Current Velocity (m/s)
Substrate Grain Size(see methods for scale)*
Macrophytes Cover (%)

0.198

0.844

-0.237<0.001

0.002

0.521

Distance to riverbank-0.138*is the significant variable(s)Italic is the near significant variable(s)RESULTS

427

0.269

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

485
(0.55)

Substrate grain
size <2.85

Substrate grain
size≥2.85

291

194

(0.64)(0.41)

Water depth ≥ Water depth <10.5cm10.5cmFig. 2241

50(0.67)(0.48)

Decision tree for the impacts of substrate
and water depth on the presence of W.
carteri. Rounded rectangles indicate
terminal nodes. See method for the scale ofsubstrates

Fig. 3General liner regression model only illustrated
the significant negative impact of substrate grain
size and a near significant relationship between themussel occurrence and the debris height (Table 2).
The decision tree analysis also indicated that
substrate grain size is the most significant predictor
for mussel occurrence, with water depth as thesecond level predictor (Fig. 2). The range and valueof other variables did not show significant difference
for the quadrats with and without living mussels (Fig.
3).

Mussel presence (Y) and absence (N)coinciding with the water depth (a),riverbed slope (b), debris height (c), debris
cover (d), water flow velocity (e), substrategrain size (f), macrophytes cover (g) anddistance to riverbank (h), see methods forthe scale of substrate grain size.

Transect analysis shown that mussel density was
positively affected by canopy cover (estimate=0.005,
p<0.001), and may be positively influenced by theoccurrence of flat riverbed (estimate=0.327,
p<0.001) and bank tree abundance (estimate=0.013,
p<0.001) as shown in fig 4. No more relationshiphas been detected in this study.

Fig. 4428

The relationship between the transect level
mussel abundance and canopy cover (a), thetree abundance level of riverbank (b) andflat riverbed (c). Scale of bank tree
abundance level: 1 – no trees at the bank, 5– bank is full with trees

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

DISCUSSIONS

is too high. For the conditions above, an appropriate
water depth is also required by freshwater mussels.
The next important microhabitat feature can belarge debris. The debris may be in a relation with thestability of mussel bed as several researches claimed
that the substrate stability is curial for freshwater
mussels [30], [31]. As fine and loose silt is not as
stable as boulders or coarse sands between boulders
or rocks, stability adder may help to reduce theturbulence in water flow. In the south west ofWestern Australia, large pieces of debris (eg. woodlog) may act as stability adders. It is suspected thatseveral certain types of large aquatic vegetation,such as water lily or submerged water plants, mayalso act as the same role in the rivers while thestatistical result did not illustrate a clear relationshipin this study.
Furthermore, shear stress may also have impacts
since a couple of past researches pointed out thatshear stress is one of the most significant predictors
of freshwater mussels [27], [30], [32]. High shear
stress may remove both the suitable substrate andthe mussels. It is believed that shear stress isdetermined by the substrate, riverbed morphology
and water flow velocity [31]. Large pieces ofobjectives may create a shelter and reduce the shear
stress by changing the nearby hydrologicalcircumstance.
In addition, transect assessment suggested thatflat channel bed, trees at the streambank and canopy
cover are also able to positively affect the presenceof mussels. The result can be reasonable. Flatbottom refers a generally stable flow velocity andeven distributed shear stress. Trees at river bank canbring more shadow area in the channel. Canopy
cover also can create shadows. Mussels may preferto stay with shaded area as the temperature insummer is very high. In some very extreme events,
for instance a long drought and the river dried,mussels may survive longer in shadow. However,the sample size of transect assessment is not enoughand the transect assessment is not focused with thisstudy, further research on larger scales might be help
to improve the understanding of mussels’ habitat
requirements.
Finally, although there is no statistical result forjuvenile Westralunio carteri in this study because
the mussel searching method is biased to adultmussels with larger size. A few juvenile mussels
were found in the places where large number ofadult mussels were also found.

The assemblages of Westralunio carteri prefer tostay at the microhabitat with certain characterswhich matches our hypothesis. Locations with finesilt, shallow water and large debris in the rivers arelikely to be preferred by W. carteri. In addition,
shadows of the trees at the riverbank and flat
riverbed may also be favored by the freshwater
mussels.
Overall, substrate, water depth, canopy cover,streambed morphology are able to influence thepresence of freshwater mussels, Westralunio carteri.
The result generally matches other studies onAustralian Hyriidae species and Hyridella menziesi
in New Zealand [23], [24]. Respectively, researches
in Asia [25], Northern America [13], [26] andEurope [17] also performed similar results. Thus, thehypothesis is believed to be true.
Substrate is believed to be the primary
microhabitat environmental character, which
respects the conclusions of almost all other studies
for the same topic [17], [27]. In this study,
Westralunio carteri requires fine and loose silt orsand. This fine substrate preference does not like its
Australian relatives in the east, such as Hyridelladepressa or Hyridella australis, which prefers coarse
sand or sand [24]. Instead, the substrate preferenceof W. carteri is in some way similar with Unio
douglasiae nipponensis, and Lanceolaria grayana inJapan [25]. It is probable because the streams in both
Japan and Western Australia are relatively small, thenormal flow is not able to create much turbulencewith fine and loose substrate so mussels prefer tostay with those easy-burrowed sediments without
being flowed away. In addition, W. carteri may findmore food from fine silt due to the large amount oforganic material within the silt. However, as
indicated in [17], only substratum can never be areliable predictor for mussels presence.
Water depth is the second primary predictor in
the decision tree analysis and this result also
matches a series of researches for other freshwaterbivalves [28], [29]. The water depth must be neither
too shallow nor too deep. The reason behind thisresult is not complicated, adequate water depth canprovide both protection and dissolved oxygen. In the
one hand, mussels will be easily seen and capturedby their predators if the water is very shallow,
especially in clean water. In the other hand, thedissolved oxygen of bottom water will be very low,which is not good for aquatic livings, if water depth

429

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

ecosystems," Freshwater Biology, vol. 46, 2001,
pp. 1431-1446.
[8] Strayer DL, "Understanding how nutrient cycles
and freshwater mussels (Unionoida) affect one
another," Hydrobiologia, vol. 735, 2014/09/01
2014, pp. 277-292.
[9] Seed R, "Patterns of biodiversity in themacroinvertebrate fauna associated with mussel
patches on rocky shores," Journal of the Marine
Biological Association of the United Kingdom,
vol. 76, 1996, pp. 203-210.
[10] Jaramillo PQE & Pino M, "Macroinfaunalassemblages associated with mussel and clam
beds in an estuary of southern Chile.," Estuaries,
vol. 19, 1996, pp. 62-74.
[11] Ray S, Ray M, Chakraborty S & Mukherjee S,"Immunotoxicity of environmental chemicals in
the pearl forming mussel of India - a review," inMussels: Anatomy, Habitat and Environmental
Impact, L. E. McGevin, Ed., ed New york:
Nova Science Publishers Inc., 2011, pp. 429440.
[12] FAO, The State of World Fisheries andAquaculture 2014. Rome, 2014.
[13] Strayer DL, "Macrohabitats of Freshwater
Mussels (Bivalvia: Unionacea) in Stream of theNorthern Atlantic Slope," Journal of the North
American Benthological Society, vol. 12, 1993,
pp. 236-246.
[14] Box JB, Dorazio RM & Liddell WD,"Relationships between stream substratecharacteristics
andfreshwater
mussels(Bivalvia: Unionidae) in Coastal Plain streams,"
Journal of the North American BenthologicalSociety, vol. 21, 2002, pp. 253-260.
[15] McRae SE, Allan JD & Burch JB, "Reach‐andcatchment ‐ scale determinants of the
distribution of freshwater mussels (Bivalvia:
Unionidae) in south‐eastern Michigan, USA,"
Freshwater Biology, vol. 49, 2004, pp. 127-142.
[16] Strayer DL, "Use of Flow Regfues by Unionid
Mussels in Rivers," Journal of the North
American Benthological Society, vol. 18, 1999,
pp. 468-476.
[17] Hastie LC, Boon PJ & Young MR, "Physicalmicrohabitat requirements of freshwater pearl
mussels, Margaritifera margaritifera (L.),"
Hydrobiologia, vol. 429, 2000, pp. 59-71.
[18] Klunzinger MK, Beatty SJ, Morgan DL &Lymbery AJ, "Distribution of Westralunio
carteri Iredale, 1934 (Bivalvia: Unionoida:
Hyriidae) on the south coast of south-western
Australia, including new records of the species,"
Journal of the Royal Society of Western
Australia, vol. 95, 2012, pp. 77-81.
[19] Klunzinger MW, Beatty SJ, Morgan DL, Pinder
AM & Lymbery AJ, "Range decline andconservation status of Westralunio carteri
Iredale, 1934 (Bivalvia: Hyriidae) from south-

CONCLUSION
This study firstly attempt to investigate themicrohabitat of Westralunio carteri in the south
western of Western Australia. Those freshwater
mussels require fine substrate, large piece ofstability adder in the habitat. Tree shadows and flatstreambed may also contribute to the establishmentof mussel bed. Further quantitative investigation on
the mussels’ microhabitat preference can help theconservation management of this endangered species.
ACKNOWLEDGEMENTS
This research is part of PhD project at Murdoch
University, we appreciate to all our volunteers fortheir help in our fieldwork. We thank the Holsworth
Wildlife Research Endowment for funding thefieldwork. Special thanks to Ms. Suzanne Thompson
and Ms Megan Sheehan from WA Department ofParks and Wildlife for her help in surveying
Canning River, Helena River and Serpentine River.
Many thanks to Holly Emery-Butcher, Nathan
Beerkens and Tom J. Dimaline for their kind help indata collection and article editing. We also would
like to thank all landowners for their permissions
and assistances of working in their properties. All
fieldworks are under licenses.
REFERENCES[1] Strayer DL, Freshwater Mussel Ecology: A
Multifactor Approach to Distribution and
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[2] Mackie GL and Claudi R, Monitoring andControl of Macrofouling Mollusks in Fresh
Water Systems, 2nd ed.: CRC Press, 2009.
[3] Caraco NF, Cole JJ & Strayer DL, "Top-down
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[5] Howard JK & Cuffey KM, "The functional roleof native freshwater mussels in the fluvial
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whiting events the cause?," Journal of Great
Lakes Research, vol. 32, 2006, pp. 131-141.
[7] Vaughn CC & Hakenkamp CC, "The functionalrole of burrowing bivalves in freshwater430

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western Australia," Australian Journal of
Zoology, 2015,[20] Klunzinger M & Walker KF, "Westralunio
carteri," in The IUCN Red List of Threatened
Species Version 2014.3, ed, 2014.
[21] Strayer DL, "Use of Flow Refuges by Unionid
Mussels in Rivers," Journal of the North
American Benthological Society, vol. 18, 1999,
pp. 468-476.
[22] Raven PJ, Holmes NTH, Dawson FH, Fox PJA,
Everard M & Fozzard IR, "River Habitat
Quality: the physical character of rivers andstreams in the UK and Isle of Man," Scottish
Environmental
Protection
Agency,Edinburgh1998.
[23] James MR, "Distribution, biomass andproduction of the freshwater mussel, Hyridellamenziesi (Gray), in Lake Taupo, New Zealand,"Freshwater Biology, vol. 15, 1985, pp. 307-314.
[24] Brainwood M, Burgin S & Byrne M, "The roleof geomorphology in substratum patch selection
by freshwater mussels in the HawkesburyNepean River (New South Wales) Australia,"
Aquatic Conservation-Marine and Freshwater
Ecosystems, vol. 18, Nov-Dec 2008, pp. 12851301.
[25] Nagayama S, Harada M & Kayaba Y,"Distribution and microhabitats of freshwater
mussels in waterbodies in the terrestrialized
floodplains of a lowland river," Limnology, vol.
17, 2016, pp. 263-272.

[26] Layzer JB & Madison LM, "Microhabitat use
by freshwater mussels and recommendations fordetermining their instream flow needs,"
Regulated Rivers: Research & Management, vol.
10, 1995, pp. 329-345.
[27] Morales Y, Weber LJ, Mynett AE & Newton TJ,"Mussel dynamics model: A hydroinformatics
tool for analyzing the effects of different
stressors on the dynamics of freshwater mussel
communities," Ecological Modelling, vol. 197,
8/25/ 2006, pp. 448-460.
[28] Johnson PD & Brown KM, "The importance of
microhabitat factors and habitat stability to thethreatened Louisiana pearl shell, Margaritifera
hembeli (Conrad)," Canadian Journal of
Zoology, vol. 78, Feb 2000, pp. 271-277.
[29] Parasiewicz P, Castelli E, Rogers JN & Plunkett
E, "Multiplex modeling of physical habitat forendangered freshwater mussels," EcologicalModelling, vol. 228, 3/10/ 2012, pp. 66-75.
[30] Zigler SJ, Newton TJ, Steuer JJ, Bartsch MR &Sauer JS, "Importance of physical and hydrauliccharacteristics
tounionidmussels:a
retrospective analysis in a reach of large river,"Hydrobiologia, vol. 598, Feb 2008, pp. 343-360.
[31] Morales Y, Weber LJ, Mynett AE & Newton TJ,"Effects of substrate and hydrodynamic
conditions on the formation of mussel beds in alarge river," Journal of the North American
Benthological Society, vol. 25, 2006, pp. 664676.

431

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, !ov.13-16, 2017, ISB!: 978-4-9905958-9-0 C3051

EVALUATI G THE EFFECTIVE ESS OF VIRGI IA BUTTO WEEDFOR EROSIO CO TROL OF DAM RESERVOIR SLOPES I JAPA
Taizo Uchida1, Yuya Imamura2, Yoshifumi Kochi3, Mamoru Yamada4, Kunihiko Fukaura5, Aki
Matsumoto6, William T. Haller7 and Lyn A. Gettys8
1

Graduate School of Engineering, Kyushu Sangyo University, Japan; 2Fukuoka Prefectural Office, Japan;
K's Lab Co., Ltd., Japan; 4SPTEC-YAMADA Inc., Japan; 5Makino Green Corp., Japan; 6Takino Filter Inc.,
Japan; 7Center for Aquatic and Invasive Plants, University of Florida, USA

3

ABSTRACT
Reservoir slopes of dams are typically bare or sparsely vegetated due to their steep inclination, long-term
submergence, marked fluctuation of water levels and impact of waves, which promote soil erosion and cause
water turbidity, deterioration of the landscape, and disrupt ecosystem functioning. Using plants to stabilize
slopes and prevent erosion is difficult, and the introduction of plants for this purpose has been extensively
debated. This study examined the effectiveness of Virginia buttonweed (Rubiaceae: Diodia virginiana L.) forstabilizing the exposed slopes of the Matsubara Dam in western Japan- Diodia virginiana was originallyintroduced to a 0.1-hectare experimental area on the dam slopes from 1994 to 1997. Since that time, D.
virginiana flourished; in 2008 it was widespread around the dam, growing in harsh environments such as steep
slopes and shoreline, and by 2016, the distribution and density of the species increased. These characteristics of
D. virginiana growth mean that the species is well suited for use as a cover plant for preventing erosion on dam
reservoir slopes.
Keywords: Cover plant, Dam, Diodia virginiana, Erosion control, Reservoir slope

Jap

I TRODUCTIO
Dams have a variety of functions, including thestorage of water for drinking and agriculture,generating electricity, and providing habitats forwildlife. In addition, dams are important for
mitigating floods in Japan, particularly in the rainyseason in June and July, and the typhoon season in
August and September. Dams used mainly for flood
control exhibit marked fluctuations in water levels
during the year as the water level of reservoirs istypically lowered artificially approximately twomonths before the onset of the rainy and typhoonseasons. Since these fluctuations in water levels canbe in the order of dozens of meters, extensive
reservoir slopes can be exposed when the water levelis lowered (Photo 1).
These slopes are typically bare or sparsely
vegetated due to their generally steep gradient,extended submergence and impacts of waves as wellas marked fluctuation of water level, which have anegative effect on landscape appearance, ecosystem
integrity and water quality [3], [6], [10], [11], [14],[16] (Photo 1). Although slopes can be stabilizedusing a variety of methods, the artificial introductionof cover plants for purposes of erosion control canbe difficult.
It was previously reported that the reservoir
slopes of some dams on Kyushu Island in western

Photo 1 Reservoir slopes exposed when the waterlevel of dam was lowered before slope
stabilization was attempted (reproduced
from the River Bureau, Ministry of Land,
Infrastructure and Transport [14]).

Japan had spontaneously become covered by
Virginia buttonweed (Rubiaceae: Diodia virginianaL.); for example, Tsuruta Dam, Midorikawa Dam,and Ichifusa Dam [8], [10]. In 1994, therefore, test
areas on the reservoir slopes of Matsubara Damwere stabilized with D. virginiana to prevent erosion
and related problems [6], [10], [16]. Here we
examine the current status of the slopes and discuss
the utility of using D. virginiana as a cover plant for
erosion control on reservoir slopes.
432

SEE - USQ, Brisbane, Australia, #ov.13-16, 2017

130°

sel

140°

280
Full water level

Japan
270

Elevation level (m)40°Midorikawa Dam

35°

Oita Pref.
30°

Kyushu Island
Tsuruta Dam

260
250

Water level

240

Matsubara Dam
Ichifusa Dam

Minimum water level230
1 Jan.

Fig. 1 Location of the study site.

Mar.

May

Jul.

Sept.

Nov.

Fig. 1 Location of the study site, Matsubara Dam,in Oita Prefecture, and some dams thereservoir slopes of which are spontaneously
covered by Diodia virginiana.

Fig. 2 Seasonal change of the average fluctuation inwater level of reservoir of Matsubara Dam inrecent years.

METHODS

selected for analysis in the permitted areas.
A transect was set up along the slope
perpendicular to the dam shore in early July 2008
when the water level was lower than usual (at 237 m,
see Fig. 2). After conducting a topographical survey
along the transect, survey quadrats (1 × 1 m each)were placed on the transect at approximately 2-mintervals. The species composition of the plants ineach quadrat was recorded using the Braun-Blanquet
cover-abundance scale [1]. Vegetation on the slopes
was classified by TWINSPAN calculated using the
PC-ORD statistical software package (ver. 4.0 for
Windows, MjM Software Design, OR). The BraunBlanquet cover-abundance scale (r, +, I, II, III, IV,
and V) was transformed as follows: r and + weretaken as 0.1%; I as 5.0%; II as 17.5%; III as 37.5%;
IV as 62.5%, and V as 87.5%.
In addition, coverage of D. virginiana along thereservoir shoreline was also surveyed and mapped
early in September 2008 and 2016 when the waterlevel was 263 and 265 m, respectively; these surveys
were conducted using a boat and Braun-Blanquet
cover-abundance scale.

Study Site
Matsubara Dam is situated in Oita Prefecture,
Kyushu Island, in western Japan in an area that is
dominated by andesite soils [9] (Fig. 1). This dam islocated in the warm temperature zone where themean annual temperature and annual precipitation
for the last decade (2007-2016) ranged from 15.1 to
16.8°C and 1,561 to 2,481 mm, respectively [4].
Matsubara Dam, which was constructed in 1973
as a multipurpose dam for water supply, flood
control and generation of electricity, is a concrete
gravity-type dam with a wall measuring 83.0 m high(elevation level (meters above sea level): 192.0 275.0 m) and 192.0 m long [9]. The basin area,
reservoir area and gross capacity are 491 km2, 1.9
km2 and 54,600,000 m3, respectively [9]. Seasonal
fluctuations in the water level of Matsubara Dam inrecent years are shown in Fig. 2. The water level
decreases most from the middle of June to the end ofJuly, and the reservoir slopes are highly exposed inthis period.
Introduction of D. virginiana to the reservoir
slope was conducted on three occasions from 1994
to 1997 using seeds, rhizomes and seedlings. A total
area of approximately 0.1-hectare was used for all
trials [6], [10], [16].

RESULTS
Reservoir Slope Vegetation
The reservoir slopes of Matsubara Dam wereextensively vegetated (Photo 2 [A-H]). The
vegetation was classified into six vegetation types (I,II, III, IV, V and VI) using TWINSPAN (Fig. 3);
Types I, II, III and IV were dominated by D.
virginiana, which had been applied to the slopes ascover plant for erosion control, together with
Oenothera laciniata Hill and Cynodon dactylon (L.)
Pers. Types V and VI were dominated by Xanthium
occidentale Bertoloni and C. dactylon. The formergroup was typically found on steep slopes and/or
aaaa

Vegetation Survey
Permission for the study on the reservoir slopesof Matsubara Dam was obtained from the Kyushu
Regional Development Bureau, Ministry of Land,
Infrastructure, Transport and Tourism. The steepest(steep slope) and gentlest (gentle slope) slopes were433

SEE - USQ, Brisbane, Australia, #ov.13-16, 2017

sre

[A]

[B]

[C]

[D]

[E]

[F]

[G]

[H]

[I]

[J]

[K]

[L]

[A-H]: Reservoir slopes when the water level
was lowered; [G, H]: Areas used as rice paddies
before construction of the dam; [I-M]: Diodia
virginiana on the slopes; [I, J]: Flowers; [K]:Seeds and young seedlings; [L, M]: Rhizomes
and adventitious roots, and [N]: Vegetation
survey of reservoir shoreline using a boat.

[L]

[M]

[M]

10 cm

[ ]

[N]

Photo 2 Matsubara Dam from July to September.

near the top of both the steep and gentle slopes,
which is where the shoreline is when the dam is full(Fig. 2), and the latter group was restricted to gentle
slopes (Fig. 4).

serious barriers to the colonization andestablishment of plant species including cover plants[3], [11], [14]. The findings of this study showedthat the stands of D. virginiana (2008) introduced
approximately 10 years previously had expanded
considerably beyond the 0.1 ha study plots to covervast regions of exposed dam shore (Photo 2; Fig. 5),
and that the distribution and density of this species
had increased over time (2016) (Fig. 5). In addition,
most of this growth was observed on steep slopes
and along the shoreline, and the latter is vulnerable
to wave impact (Fig. 4).
It appears that D. virginiana is suitable for use asa cover plant for stabilizing the reservoir slopes ofdams. The success of this species for this purpose isconsidered to be due to the fact that the seeds of D.

Diodia virginiana along the Reservoir Shoreline
Diodia virginiana was observed over most of
the dam slopes around the dam in 2008 (Fig. 5), anddistribution and density of this species increased in
2016.
DISCUSSIO
The effects of fluctuations in water level,
extended submergence and wave action constitute
434

SEE - USQ, Brisbane,
B is a , Australia, #ov.13-16, 2017

AAA

Vegetation types †n = 48aa280
bioaity.
( A ): N57°W

I (n = 2)
a

a

a

a

III (n = 7)aaIV (n = 7)aaV (n = 9)aaElevation level (m)II (n = 12)270( B ): N26°E

260
250

V
VI

240

II

VI (n = 11)
a

1

2

3

4

IV

a

Classification of vegetation on reservoir
slopes by TWINSPAN using species
composition (coverage data, %).
†, on the basis of plant coverage size ineach vegetation type (I-VI), it was defined
as follows: I, Diodia virginiana
vi i ia a Oenothera laciniata; II, Diodia virginiana
vi i ia a;
III, Diodia virginiana - Cynodon
Cynodo dactylon
dactylo ;IV, Cynodon dactylon - Diodia virginiana;
V, Xa
Xanthium
thium occid
occidental
tale - Cynodon
dactylon, and VI, Cy
Cynodoodon dactylon
dactylo Xanthium occidentale.

I( A' )

230

5

-10

0

Division level

Fig. 3

V III ( B' )
III

III

10

20

30

40

50

60

070 5 1080m

距離（ｍ）

Fig. 4 Vegetation type on steep and gentle slopes.
(A)(A) and (B) indicate steep and gentle slopes,
respectively. (A') and (B') indicate vegetation
types on steep and gentle slopes, respectively.
Vegetation types: See Fig. 3.

2008[ Water level: 263 m ]virginiana contain suberin, which causes the seeds
to float and spread widely [6] (Photo 2 [K]), andeven young plants are remarkably resistant toinundation; according to Imamura et al. [3], severalmonth-old seedlings of D. vi
virginia
i ianaa can tolerate
submergence for more than half a year.
It is also considered that the presence of otherplant species, such as O. laciniata, C. dactylon
dactylo and X.
occidentale, on both types of slopes may have been
facilitated by D. virginiana, which effectively boundthe soil of the dam slopes and trapped the seeds ofother grass species (Fig. 4). And furthermore,
succession among species would have beenpromoted on the gentle slopes (Fig. 4).

2016[ Water level: 265 m ]CO CLUSIO S
Matsubara
Dam

Given the importance of conserving landscapesand biodiversity, the application of cover plants for
erosion control on slopes (e.g. Kondo et al. [7];Uchida et al. [15]) has become preferable to civilengineering solutions. Under the circumstances, inthis study it is considered that characteristics of D.
virginiana growth are well suited for use as a coverplant on dam reservoir slopes (Figs. 4, 5). In
addition, the dense carpets, attractive flowers andlong rhizomes produced by this species (Photo 2 [I, J,
L, M]), means it could be used to prevent erosion,increase aesthetic appearance, and promote soil
binding in areas at risk of soil erosion. However,since D. virginiana is an alien species native to"North America", extensive growth of the species

500 m

500 m

: Reservoir slope: D. virginiana coverage (r, +, I, and II): D. virginiana coverage (III, IV, and V)

vi i ia a along the
Fig. 5 Distribution of Diodia virginiana
shoreline of Matsubara Dam.

435

SEE - USQ, Brisbane, Australia, #ov.13-16, 2017

Reveget. Tech. 33, 171-174. In Japanese.
[7] Kondo K., Uchida T., Hayasaka D., Tanaka J.,
Sato A. and Arase T., 2016. Vegetation
succession on cut slopes covered with exotic
grasses for erosion control, Mt. Sakurajima. Int.
J. of GEOMATE 11, 2136-2142.
[8] Konno R., 2003. Revegetation of reservoir slopeof dam for environmental conservation, using
Diodia virginiana. Mizutotuti 132, 29-35. In
Japanese.
[9] Kyushu Regional Development Bureau,
Ministry of Land, Infrastructure and Transport,
2017. Website of the Dam Joint Control Officeof Chikugo-gawa River <http://www.qsr.mlit.
go.jp/toukan/g_shokai/matsubara.html>.
In
Japanese.
[10] Matsumura M. and Fukuda K., 1996.
Conservation of dam reservoir slope by Virginia
buttonweed. Engineering for Dams 124, 42-50.
In Japanese.
[11] Miyake K. and Onishi A., 2005. Study on lake
front planting within water level change area ofdam reservoirs. Bull. of Water Resources
Environment Technology Center, 50-56. In
Japanese.
[12] Ni H., Wehtje G., Walker R.H., Belcher J.L.
and Blythe E.K., 2006. Turf tolerance andVirginia buttonweed (Diodia virginiana) control
with fluroxypyr as influenced by the synergist
diflufenzopyr. Weed Technology 20, 511-519.
[13] Reed T.V., Yu J. and McCullough P.E., 2013.
Aminocyclopyrachlor efficacy for controlling
Virginia buttonweed (Diodia virginiana) andsmooth crabgrass (Digitaria ischaemum) in tallfescue. Weed Technology 27, 488-491.
[14] River Bureau, Ministry of Land, Infrastructure
and Transport, 2006. Draft for revegetaion ofreservoir slope of dam. 96 pp. In Japanese.
[15] Uchida T., Tanaka J., Kondo K., Hayasaka D.,
Tomoguchi Y., Arase T. and Okano T., 2017.
Evaluating the dynamics of alien species(Poaceae) used for erosion control on
Sakurajima volcano. Int. J. of GEOMATE 12,114-120.
[16] Yamamoto T., Makino A. and Yamamoto K.,
1999. Bio-engineering technique with Virginia
buttonweed on dam reservoir slope ( I ).
Abstract of 30th Conference of Jpn. Soc.
Reveget. Tech., 234-237. In Japanese.

could adversely affect ecosystem integrity andbiological diversity. Indeed, D. virginiana isbecoming increasingly troublesome weed even in
the US, particularly in Alabama, Georgia,
Mississippi, North Carolina, etc., where control
using herbicides is currently being investigated [2],[5], [12], [13]. It is therefore necessary to overcome
a trade-off between the application of D. virginiana
as a cover plant and the potential negative effects ofthis species on biological diversity.
ACK OWLEDGEME TS
We thank the Dam Joint Control Office of
Chikugo-gawaRiver,
KyushuRegional
Development Bureau for providing access to theexperimental sites. We also thank Takeshi Goto,
Hayato Yoshitsugu, Ryoji Zenmyou, Syuhei
Yamawaki, Hisae Yonao, Kentaro Kondo and Yuki
Tomoguchi at the Laboratory of Plant Ecology at
Kyushu Sangyo University (KSU) for theirassistance.
REFERE CES[1] Braun-Blanquet J., 1964. Pflanzensoziologie.
Grundzüge der Vegetationskunde, 3rd ed.
Springer-Verlag, Vienna. 865 pp.
[2] Hutto K.C., Brecke B.J. and Unruh J.B., 2008.
Comparison of flazasulfuron to pyridine
herbicides for Virginia buttonweed (Diodia
virginiana) control. Weed Technology 22, 351353.
[3] Imamura Y. and Uchida T., 2011. Seedgermination and seedling growth of Virginia
buttonweed- Diodia virginiana L. (Rubiaceae).
LRJ 74, 479-482. In Japanese.
[4] Japan Meteorological Agency, Ministry of Land,
Infrastructure and Transport, 2017. Website ofthe
AMEDAS<http://www.jma.go.jp/jp/
amedas/>. In Japanese.
[5] Kelly S.T.
and
Coast
G.E.,
2000.
Postemergence herbicide options for Virginia
buttonweed (Diodia virginiana) control. Weed
Technology 14, 246-251.
[6] Kochi Y., Matsumoto A., Mutsunobu K.,
Makino A., Yamada M. and Suzuki M., 2007.
Application of Diodia virginiana L. as therevegetation plant on dam slope. J. Jpn. Soc.

436

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

NANOCOMPOSITE WITH DUAL FUNCTIONALITY IN
SIMULTANEOUS REMOVAL OF HEAVY METALS, DYE AND
ANIONIC SURFACTANT FROM MULTICOMPONENTWASTEWATERMaria Visa1, Nicoleta Popa1, Andreea Maria Chelaru1
1

Transilvania University of Brasov, R&D Center: Renewable Energy Systems and Recycling Romania
ABSTRACT

By means of the hydrothermal method, a new material was obtained from fly ash (FA) and tungsten oxide(WO3) with dual adsorbent and photocatalyst properties, which proved to be effective in removing the pollutantsfrom wastewater. The characterization of the material by means of atomic force microscopy (AFM) analysis
showed that the surface is rougher than that of raw FA and of WO3. The energy dispersive X-ray detector (EDX)and X-ray diffraction (XRD) indicated the existence of nano-WO3 on the FA surface. FT-IR spectroscopy
measurements further illustrated that the alkali hydrothermal method causes not only the generation andanchorage of nano-WO3 on ash surface but also the exposure of more hydroxyl groups on the ash surface; bothproved able to adsorb heavy metals, dye and surfactant via the synergistic effect. Both activities ofnanocomposite WO3-FA were evaluated in the process of removing of Cu2+, Cd2+, Methylene blue (MB) and of
Sodium Dodecylbenzenesulfonate (SDBS) from mixture solutions. The adsorption capacity was improved up to
30.21mg/g cadmium cations and 90.09mg/g of copper cations in the removal process of the cations fromcomplex pollutant systems.
Keywords: WO3, photoctalysis/adsorption, wastewater treatment
This paper reports the synthesis, characterization,
adsorption and photocatalytic activity of thecomposite WO3-FA, obtained by the alkaline fusing
followed by hydrothermal treatment.
The enhanced photocatalytic activity of thenanocomposite was evaluated using synthetic
pollutant systems loaded with Cd2+, Cu2+cations,(MB) and anionic surfactant (SDBS) under UV andVIS light irradiation (hν>Eg), as a new method for
wastewater treatment.

INTRODUCTION
Many branches of industry, especiallythe textile industry, generate great amounts ofwastewater loaded with heavy metals, dyes,
surfactants, which are all refractory and nondegradable. About 1-258 of the total world
production of dyes is lost during the dyeing process
and is released in the textile effluents [1]. Many
physic-chemical methods have been developed forremoving dyes, heavy metals and surfactants, forexample: adsorption [2], coagulation [3], chemical
precipitation, ion-exchange, reverse osmosis andnanofiltration
membranes[4].
Adsorption
technologies have many advantages: inexpensive
equipments, easy operation, efficiency and thepossibility of regenerating the adsorbents for the
next cycle. Suitable adsorbents for dyes and/or
heavy metal removal were reported to be modified
FA, natural zeolite, clay, bentonite [5], [6], [7], [8],resins such as Dowex 11[9] or synthetic adsorbents
represents a possible alternative forthesimultaneous removal of the pollutants fromwastewater. The advanced oxidation processes(AOPs), based on the generation of reactive species(•OH radicals), are recommended for the degradationof organic pollutants [10], [11]. WO3 is thesemiconductor photocatalyst with a band gape of
2.8eV which can be activated by visible light but
only with low photonic efficiency.

EXPERIMENTAL
Materials and the Substrate’s Preparation
Raw FA was collected from CET power plant in
Brasov, Romania. This FA is type F, according to
the ASTM standard C-618-2a [12].
The total percentage of major oxides (SiO2,
Al2O3, Fe2O3)exceeds 70% and this type of FA will
not aggregate during long contact with water, being
suitable as substrate in adsorption of organic andinorganic pollutants [13]. Ti5O9 (1.07%), Fe2O3(8.97%) and MnO2 (0.08%) are important as
possible participants in the photodegradation of dyes
and surfactants. The composite substrate of FA andWO3 was obtained using FA, NaOH pellets andWO3 (99.8% purity) from Across Organics by alkali
fusion at 5000C for 1h. The composite cooled withbi-distillated water was transferred in an autoclave437

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

investigate the crystal structures
composition of the composites, Fig.1.

and stirred (300 rot/min) at atmospheric pressure and1000C for 48h. Afterwards, the solid phase wasfurther washed with ultrapure water until constantpH, followed by filtration and drying at 105-1150C.
The new composite is noted FUS-WO3. Due to thesynergistic effect of functional groups (-OH-), (≡SiO-), (≡AlO-), (≡ SiONa), this composite will
exhibit good adsorption and photocatalytic ability inthe wastewater treatment process.

and

phase

Adsorption and Photocatalytic Experiments
The pollutant systems were synthetically
prepared using ultrapure water with resistivity of
18.23 MI cm-1, CuCl2.2H2O and CdCl2.2.5H2O(Scharlau Chemie S.A., c<983 ), MB (C16H18ClN3S)(Fluka AG, molecular weight (319.85g/mol) andanionic surfactant (SDBS) (C12H25C6H4SO3Na) withlinear carbon chains having 983 purity (SigmaAldrich), with molecular weight (343.48g/mol).
Experiments were done using solutions in theconcentrations of cCd=0..550mg/L,cCu=0..300mg/L,
cMB=0.03125mM and the initial concentration of
SDBS=25mg/L being lower than the critical micelleconcentrations (CMCSDBS =418mg/L), as evaluatedbased on conductivity measurements [14]. A seriesof experimental on adsorption and photocatalysis
were done in solutions containing four pollutants:- Adsorption under mechanical stirring denoted (A)with: Cd2-- Cu2--MB-SDBS;- Photocatalysis under UV irradiation, denoted (FDV): Cd2--Cu2--MB-SDBS;- Photocatalysis denoted with (F-VIS) under VIS
irradiation: Cd2-- Cu2--MB-SDB.
The kinetic adsorption parameters of cations, dyeand surfactant were evaluated from batch
experiments; in each experiment, the 0.1g FUS-WO3
substrate was stirred at 20-230C, with 50ml solution,at initial concentrations. For the kinetic studies,aliquots were taken at fixed moments (10, 15, 30,
45, 60, 90, 120, 150 and 180min.), when stirring wasbriefly interrupted and the supernatant was analyzed
for evaluate the momentary concentration ofpollutants. The concentrations of the metal in the
aqueous solution were analyzed by AAS (analytic
jena, zeenit700), at λCd=228.8nm, λCu=324.75nm,
while MB and SDBS were analyzed by UV-VIS
spectrometry on the calibration curve registered at
the maximum absorption peaks of MB(λ=664nm),
and of SDBS (λ=224 nm), respectively.

Fig.1.X-ray difractograms of (A) FA; (B) FUS-WO3
In the FUS-WO3, the WO3(2) content isestimated at 52.58%, the alkaline tungsten oxides
content at 8.54% and 38.88% aluminosilicates withadsorbent properties, mordenite (NaAlSiO·H2O) (6),faujasite–Na, (Na14Al12Si13O51·6H2O) (8), cancrinite
syn(7), Na8(Al6Si6O24(OH)2,04(H2O)2,66, phillipsite(KNa)2(SiAl)8O16·4H2O (9) and albite Na(AlSi3O8).
On the FUS-WO3 difractogram, the shape of thepeaks (2, 2`, 8) appears as overlapping, meaning that
this substrate contains semiconductor oxides
homogenously dispersed within the composite,which indicates the existence of a high number ofcontact aluminosilicates–WO3, Fig.1. The XRD data
show that the new composite (FUS-WO3) has wellembedded the WO3 phases with crystallite size
132.3-184.4Å. The crystalline modifications areaccompanied by a significant increase in the BET
surface, from 6.14m2/g in FA to 39.753m2/g for
FUS-WO3.Beside the diffraction lines corresponding
to WO3 triclinic, hexagonal and orthogonal, there
appear other lines with high peaks, which wereidentified in crystalline structures of FUS-WO3
proving the chemical restructuration of the FA
together with WO3 during the hydrothermal
treatment. The formation of new compounds, suchas, silicon tungsten (3), aluminum tungsten oxide
silicate (5), sodium tungsten oxide (2*), potassium
tungsten oxide (4), is the consequence of the
dissolution/recrystallization processes followed by
the partial transformation of the main components of
the FA in alkaline media. The incorporation of WO3
in the modified FA structure, along with thepolymorphous transformation from monoclinic WO3 totriclinic is also evidenced in the XRD pattern. The
sharp peak at 2θ =27.203o corresponds to the formationof crystalline (Na6W4O6) and at 2θ=31.66o itcorresponds to the (KW3O9), the specific tungsten
oxide in strong alkaline media. All these processes leadto an increase of the overall crystallinity to 58.8% for
the new synthesized composite.

RESULTS AND DISCUSSIONS
Crystalline Structure of the Substrate
The novel WO3/SiO2Al2O3 (aluminosilicates)
heterojunction was obtained from fine FA and WO3
via alkaline fusion followed by hydrothermal
process. The X-ray diffraction was used in order to
438

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017groups in the adsorbent, which represent the numberof adsorption bonds that identify the type ofchemical bonds (functional groups), indicating thecomplex nature of the adsorbent as shown in Fig.3.

Surface
Morphologyof theSurface
Morphology
ofSububstrate
the S strate
Information on the new substrate morphology/
topography, respectively surface characteristics wereobtained from the SEM micrographs and AFM. The
highest roughness value (112.24nm) corresponds tothe composite (FUS-WO3) which has moreaggregates with different, almost round and stable
shapes. The FA has a rough surface = 91nm withlarge pores, 12.33nm in diameter, while for WO3 thediameter of the pores are 27.76nm, respectively. The
adsorption efficiency depends not only on the pores`
diameter, but also on the surface charge and theaffinity of the pollutants molecules for the substrate.
The contact angles with water were very low(15-20),g ood surface wettability. With glycerol
liquid the polar component was σp = 45.04mN/m
and the dispersive component was σD = 8.69mN/m.
The surface energy is 53.73mN/m such as the FUSWO3 composite has a predominant polar component,
which indicates the hydrophilic character andwettability, thus making them a suitable composite
with dual application (adsorbent and photocatalyst)
in the process of simultaneous removal of pollutantsfrom wastewater. The grains` dimension is affected,
varying from the large domain for FA (27.6…100µm) to narrower grains/agglomerates of 8…60 µm
diameter, for the FUS-WO3, as shown in Fig. 2.

Fig. 3. IR spectrum FUS-WO3 and FA-CETThe FT-IR spectra provided further insight into
the structure of the composite synthesized by thehydrothermal method at 100°C. The peak located at
1648cm-1 is indexed at O-H, bonding the watermolecules associated with ions or molecules. This
peak exists only at FUS-WO3 after treating the FACET. The FT-IR spectrum shows a sharp peak at
909R1 cm-1, which is attrib
attribuuted
the symmetricsymmetric
ted toto the
from
types
stretching mode of terminal WW=O
=O from
allalltypes
of oftungsten trioxide hydratesRTThhe
broad
band
arounde broadband
around610-657 cm-1 is characteristi
characteristiccofofththe stretching of Os rp absorption- W-O modes [10]The shhaarp
absorption bands
bands
recorded at 429R 04 cm
t thhe FUS-WO3
in-1 einFUS
spectrum and at 440 cm-1 in
FA-CEETmay
spectrumC the
T spectrum
resultmay their
resultsuperposition
from their wit
superposition
withhstretch
thefromthe symmetricsymmetric stretchof Al-O
Si-O bonds,
also oO bonds,
als andresentedin the zeolite
ppresented in the zeolite structures [11]ADSORPTION AND PHOTOCATALYSIS(a) AdsorptionRThe poor adadssoorption
rption capacity of the
raw FA and the negative eeffficiency
cadmiumficiency forforcadmium
ined bybythetheformation
removal on WO3 can be exp
expllaained
formation
wol amats, correlated withof new species of meta-wolffrramats,area and,
and, respecttiively,
respec vely, withlow surface areawith low surface
charge [16]Heavy
Heavymetals
metalsatta low concentrations (asin the wastewaters
thee textiles
textilesindustry)
industry)cancantewaters from thadsorption;
however,also be efficiently removed bbyy
adsorption;
however,the efficiency of adsorpti
adsorptio onnprocesses
processesdecreases
decreases
when applied to wastew
rs ers
withwitha complex
wastewa atte
a complex
metalss,,dyes
dyesandandsurfactants),
surfactants),
pollutants load (heavy metal
as concurrent reactions
occur,
thus
decreasing
ctions may occur,
thus
decreasing
efficie enncy
pollutantsR
the overall removal effici
cy of ofthethepollutants.
moreprocesses
processesmay
may
Therefore, the employment oof
f moreea eacchh
processprocess
being highly
represent aafeasible
feasiblepath,
path,
being
highly efficient for one pollutant
typpee [17]ty
The adsorption is implemented in systems withfour pollutants: Cd2++Cu2++MB+SDBS/FUS-WO3,

Fig.2. SEM images of the FUS-WO3
The SEM image of FUS-WO3 shows a highdegree of homogeneity. The elemental EDX analysisof the FUS-WO3 shows a high intensity signal forthe atoms: Si(14.51%), O(59.95%), W(1.09%),
Al(10.13%) before adsorption and confirms theCd(2.46%), S(3.59%), Cl(5.35%) percents on thesurface scanned after the adsorption processes.
3.2.1. FT-IR spectra analysis of the substrate
The FT-IR spectra of FUS-WO3 before and after
adsorption of cations were conducted to investigate
the vibration frequency changes of the functional
439

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

Overall efficiency has increased, since the numberof active centers, the number of pores able to hostions and molecules of pollutants has increased.

the results being presented in Fig.4. The adsorption
efficiency was evaluated based on the initial andequilibrium concentrations c iM / D / S c eM / D / S of themetal (M), dye (D) or surfactant (S), Eq. (1):

100
90

(c

−c
) × 100
cMi / D / S

2+

2+

2+

2+

2+

2+

70

(1)

Cd (Cd +Cu +MB+SDBS)/FUS-WO 3 (A)90

Cu (Cu +Cd +MB+SDBS)/FUS-WO 3 (A)
2+

2+

60
50
40

MB(MB+Cu +Cd +SDBS)/FUS-WO 3 (A)

80

2+

2+

30

Cd (4P)/FUS-WO3 (A)20

Cu (4P)/FUS-WO3(A)MB(4P)/FUS-WO3 (A)SDBS(4P)/FUS-WO3 (A)2+SDBS(SDBS+Cu +Cd +MB)/FUS-WO 3 (A)70

Eficienta [%]80e
M / D/ S

Efficiency [%]η=i
M / D/ S

60

10

50

0

2+

0.0

0.1

0.2

0.3
0.4
masss [g]

40
30

0.5

0.6

Fig.5. Adsorption efficiency vs. mass of substrate.

20
10

The reason may be the higher mobility to poresand the lower volume of the hydrated complexes of
the cations in aqueous solution (hexacomplexes for
Cd and tetra-coordination for Cu), as well as otherprocesses at working pH=8.22.
(b) Photocatalysis. The active species generated byphoto-irradiation will attack the organic pollutants,
provided they are in the very close vicinity of thesubstrate. The most active photocatalytic
components of the composite are WO3 triclinic andsilicon tungsten (Si0.043WO2.839) with band gaps of
2.8 eV, active under both UV and VIS radiation. The
influence of contact time in UV and VIS
decomposition is presented in Fig.6 (a) and (b).

0
0

20

40

60

80

100

120

140

160

180

Timp [min]Fig.4. Adsorption efficiency vs. time forsystem Cd2++Cu2++MB+SDBS
The optimal adsorption time can be estimated as
90min. when the adsorption equilibrium starts tosettle for system and was set at this value in all
further experiments. The adsorption efficiency of
Cd2+ ions (11.73%) and of the MB molecules(11.79%) is very close, see Fig.4; the adsorption of
Cu2+ ions (58.63%) and of SDBS molecules(51.22%) increases, in the same way, Fig. 4. Thisapproach can be explained by interactions between
heavy metal cations and ionic groups of organic
molecules (MB and SDBS).
In systems containing two or more pollutants andthe substrate, several adsorption processes occur:a) The Cd2+ and Cu2+ cations can be absorbed by thesilanol group (Si–OH) of the layer, but with lower
efficiency (eqs.2, 3):

2+

2+

2+

2+
2+

Cu (Cu +Cd +MB+SDBS)/FUS-WO 3 (F-UV)

80

2+

2+

MB(MB+Cd +Cu +SDBS)/FUS-WO 3 (F-UV)
2+

2+

SDBS(SDBS+Cd +Cu +MB/FUS-WO 3 (F-UV)

70

Eficienta [%]2+

Cd (Cd +Cu +MB+SDBS)/FUS-WO 3 (F-UV)

90

60
50
40
30
20

Si–OH+ Cd2+(H2O)n⇔Si–OCd+(H2O)n-x + 2H+(H2O)x (2)Si–OH+Cd2+(H2O)n⇔(Si–O)2Cd(H2O)n-x+2H+(H2O)x (3)

10
0
0

50

100

150

200

250

300

350

Timp [mim](a)b) The adsorption of heavy metals onto NaP1 zeolite
has a cation exchange capacity over 2.7meq/g. Threedifferent stages are observed in the ion + exchange
adsorption of the heavy metals: fast adsorption on
the zeolite microcrystal surfaces during the first 30
min; then the inversion stage has a short+time
prevalence of the desorption process, connected withthe diffusion flow from the zeolite microcrystal’s[18], [19]. The amount of FUS+WO% in adsorption
was optimised, considering the pollutants mixture(Cd2+, Cu2+, MB, SDBS). Based on the experimental
results, the optimal amount is 0.4g FUS+WO% in
50mL solution, Fig.5. By increasing the amount of
substrate, the surface area as well as the number ofthe pores and of the cations+surface interactions will
increase. The adsorption efficiency of the Cu2+
cations is higher than that of the Cd2+cations.

2+

2+

2+

2+

2+

Cd (Cd +Cu +MB+SDBS)/FUS-WO 3(F-VIS)

90

2+

Cu (Cu +Cd +MB+SDBS)/FUS-WO 3(F-VIS)
2+

2+

80

MB(MB+Cd +Cu +SDBS)/FUS-WO3(F-VIS)

70

SDBS(SDBS+Cd +Cu +MB)/FUS-WO3(F-VIS)

Eficienta [min]

2+

2+

60
50
40
30
20
10
0
0

50

100

150

200

250

300

350

Timp [min](b)Fig.6. Photocatalysis efficiency vs. time: (a)(F-UV and (b) F-VIS for system
Under VIS irradiation the efficiency after 6h is440

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017higher than in experiments, where the irradiation
source is UV light, as in Fig. 6(b) (Cd2+= 45.4%;
Cu2+= 52.33%; MB= 20.39% and SDBS= 51.29%.
By coupling two or more semiconductors withsuitable electronic band (SiO2, TiO2, WO3, thephotocatalytic activity under UV or VIS irradiation
can be improved. The composite FUS-WO3 with
Eg= 4.41eV is more active in visible light and it caninvolve other compounds from the substrate atworking pH. This path is also valuable, with a view
to upscaling as, by coupling UV-active with VIS
active semiconductors; the costs of the process canbe reduced.
Once formed the electron-hole pair was formed,
the most common mechanisms involves the holes forhydroxyl radical production. In alkaline media
several other reactions are possible [20], [21]involving the O2/ HO-, O2 / HOO-.

Table 1 Kinetic parameters of the processes
Pseudo-second order
Pollutantk2
qe
processR2[g mg-1min-1][mg/g]
Cd2+/Ads.
0.183
30.21 0.961
Cu2+/Ads.
0.06
90.09 0.999
MB/Ads.
5.384
0.134 0.992
SDBS/Ads
5.619
0.845 0.999
Cd2+/F-UV
3.127
43.67 0.957
Cu2+/F-UV
1.204
70.92 0.981
MB/ F-UV1354.200.007 0.922
SDBS/F10.987
0.786 0.994
UV
For the photocatalysis process, the LangmuirHinshelwood mechanism simplified for low
concentration as a pseudo first order kinetics wastested, Eq. (10):ln c/co= - kt (10)Photocatalist + hν → e− + h•
(4)+h• + H2O(Photocat) → •OH(Photocat) + H (5)The kinetic parameters and the correlation
coefficients calculated from the linear form of the
kinetic laws are presented in Table 1 and kinetic
plots are given in Fig.7.

These are powerful oxidizing species, able todegrade the dye and surfactant molecules Tadsorbedon the catalyst or in solution, near the photocatalyst
surface) to smaller fragments less colored, Eqs.
T6,7), probably with similar dimensions/charges
which can be further by adsorbed onto the active
sites of substrate or can be further degraded up tomineralization [22].

y = -0.0013x - 0.0561

Langmuir -Hinshelw ood
SDBS (SDBS+MB+Cu2+)

R 2 = 0.8468

0
0

50

100

150

200

250

300

350

400

-0.1

logC/Co-0.2

HO• + Dye → oxidation products (OP)(6)
HO•+OP→CO2+H2O+ mineralization products (7)

-0.3

-0.4

-0.5

-0.6

ADSORPTION KINETICS MODELINGt [min]Fig.7. Langmuir – Hinshelwood
Adsorption Kinetics Models Analysis
Parallel kinetic mechanisms may occur,
especially inter-particle scattering, due to bulky
cation adsorption in the pores of the substrate. As inprevious cases, the maximum adsorption capacity
values are associated with the species of cations,while the organic components associated with MB
and SDBS are characterized by low values ofmaximum adsorption capacity.

The amount of pollutants adsorbed, qt [mg/g] attime t was calculated from the following Eq. (8).
(cMi / D / S − cMe / D / S ) × Vsol .
(8)ms
The kinetics models are fitted to experimental
data by nonlinear regression analysis. To determine
the uptake kinetic mechanisms of pollutants (Cd2+,
Cu2+, MB, SDBS) from systems three kinetic models
were investigated: pseudo-first order (Lagergren
equation), pseudo-second order and intraparticle
diffusion. The pseudo-second order kinetic (Eq.9) is
the model which best describes the adsorption of thepollutants on the composite FUS-WO3.
t
1
t
(9)
=
+
2
q t k 2q e q e
qt =CONCLUSIONSThis paper investigates the removal of MB,
SDBS, Cu2+, Cd2+ cations from synthetic solutions
loaded with four pollutants by adsorption andphotocatalysis, using FUS-WO3 nanocomposites
with dual activity.
The tungsten oxide imbedded on fly ash surface
by the alkaline fusing and hydrothermal process,developed the new composite to be more effective insimultaneous processes of adsorption and ofphotocatalysis.

Where:
k2- the equilibrium rate constant for the pseudosecond order adsorption (g·mg-1 min-1), qe- theadsorption capacity (mg·g-1).
441

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017[10] Wols B. A, Hofman-Caris C.H.M, J. Water Res,
Vol. 46. Mar.2012, pp. 2810-2A27.
911] Visa M, Andronic L, Duta A, Environ
Eng Manag J. Vol.8, Jul.2009, pp. 633-63A.
912] Ramme B. W, Tharaniyil M. P,
Coal Combustion Products Utilization Handbook,2nd Ed., of America. 2000.
[13] Duta A, Visa M, J. of Photochem. Photobiol,
Vol. 306, Jun. 2010, pp. 21-30.
914] Visa M, Duta A, J. Chem. Eng, Vol. 223,
May. 2013, pp. 860-A6A.
910] Yaakob Z, Pudukudy M, Rajendran R, J.
Der Pharma Chemica, Vol.0, 2013, pp. 208-2012.
[16] Visa M, Duta A, J.of Optoelectronics andAdvans. Mater., Vol. 12, Feb. 2010, pp. 406-410.
[17] Visa M, Pricop F, Duta A, J. Clean Techn.
Environ. Policy, Vol. 13, Dec. 2011, pp. 800- 861.
[18] Sprynskyy M, Buszewski B, Terzyk A.P,
Namiesnik J, J. Colloid Interf. Sci., Vol. 304, Dec.
2006, pp.21-2A.
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[21] Hsu L.J, Lee L.T, Lin, C.C, Chem. Eng. J. Vol.
173, Apr. 2011, pp. 698-705.
922: Ho Y. S, Mc Kay G., J. Chem. Eng. Vol.
76 1998, pp. 822.

The results show that the adsorption efficiency
significantly depends on the surface properties,
while the process kinetics is mainly influenced by
the type of cations and by the molecular structure of
the surfactant and of MB.
Considering the adsorption processes, the data
indicate that a large volume of MB allows the rapid
adsorption of the cations, leading to higher rate
constants, as compared to cadmium.
The pseudo-second order kinetic is the modelthat governs the entire process of removing
pollutants from complex systems, while the parallelmechanisms of pseudo-first-order kinetics and interparticle diffusion affect the complex processes ofsimultaneous adsorption and photocatalysis to anegligible extent.
The presence of more pollutants in aqueous
solutions may adversely affect the adsorption
process of other pollutants: qe of the cadmium
removal from systems with four pollutants is30.21mg/g, in the case of copper cations removal is
90.09mg/g.
The reason may be the higher mobility andlower volume of the hydrated complexes of thecations in aqueous solutions (hexa-complexes for Cd
and tetra-coordination for Cu).
The photocatalytic experiments proved various
paths for the removal of SDBS and MB:
independent adsorption and photocatalysis.
REFERENCES[1] Konstantinou I. K, Albanis T. A, J. Appl. Catal.
B- Environ, Vol.49, Nov. 2004, pp. 1-14.
[2] Visa M, Duta A., Environ Eng Manag J. Vol. 7,
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2010, pp. 1468-1476.
[4] Bowen R.W, Welfoot J.S, J. of Chem. Eng. Sci,
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[6] Wang S, Boyjoo Y, Choueib A, Zhu Z.H, J.
Water Res, Vol. 39, Jan. 2000, pp. 129-138.
[7] Perić J, Trgo M, Medvidović N.V, J of Water
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[8] Jiang M.Q, Jin X.Y, Lu X.Q, Chen Z.L, J.
Desalination, Vol. 202, Nov. 2010, pp. 33–39.
[9] Munesh, Swati, Sindal R.S., Meena R.C. J.of
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23-30

442

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EFFECT OF WATER ACTIVITY ON ENZYMES ADSORBED ON
BIOMASS CHARCOAL IN ORGANIC MEDIA
Hidetaka Noritomi1, Jumpei Nishigami2, Nobuyuki Endo3, Satoru Kato4 and Katsumi Uchiyama5
Department of Applied Chemistry, Tokyo Metropolitan University, Japan; 2EEN Co., Ltd., Japan

1

ABSTRACT
We have found that the organic solvent-resistance of α-chymotrypsin (α-CT) is enhanced by adsorbing α-CT
onto bamboo charcoal powder (BCP), which is obtained by pyrolyzing bamboo waste under nitrogen atmosphere,
and is markedly dependent on the thermodynamic water activity (aw) in organic solvents. When BCP-adsorbed
α-CT was immersed in acetonitrile at an appropriate water activity, it effectively enhanced the transesterificationof N-acetyl-L-tyrosine ethyl ester (N-Ac-Tyr-OEt) with n-butanol (BuOH) to produce N-acetyl-L-tyrosine butyl
ester (N-Ac-Tyr-OBu), compared to the hydrolysis of N-Ac-Tyr-OEt with water to give N-acetyl-L-tyrosine (NAc-Tyr-OH). When the water activity was 0.28, the initial rate of transesterification catalyzed by BCP-adsorbed
α-CT was about sixty times greater than that catalyzed by free α-CT. Regarding the reaction selectivity which isdefined as a ratio of the initial rate of transesterification to that of hydrolysis, BCP-adsorbed α-CT was muchsuperior to free α-CT. The catalytic activity of BCP-adsorbed α-CT was markedly dependent on the reaction
temperature. Furthermore, concerning the thermal stability at 50 ℃, the half-life of BCP-adsorbed α-CT exhibited
3.8-fold, compared to that of free α-CT.
Keywords: Biomass charcoal, Adsorption, Enzymatic activity, Thermal stability, Water Activity

INTRODUCTION

enzymes onto various carriers has been widely usedfrom the laboratory scale to the industrial scalebecause of the simplest and most economical methodof stabilizing enzymes [8], [9]. The physical andchemical surface properties of carriers strongly affectthe performances of adsorbed enzymes such as thecatalytic activity, the specificity, and the stability.
Thus, it is probably that the stress resistance of
enzymes is enhanced by selecting an appropriate
carrier.
As a part of our ongoing research efforts aimed
at utilizing forestry residues, we have so far examined
the usefulness of biomass charcoal powder, which isprepared from forestry residues by pyrolysis, as a
enzyme carrier. We have found that enzymes are
effectively adsorbed onto biomass charcoal powder[10], [11], and biomass charcoal powder imparts highheat stress resistance to enzymes through theadsorption [12]-[15]. Furthermore, we have reported
that the adsorption of enzymes onto biomass charcoal
powder can sufficiently improve the organic solvent
resistance of enzymes in hydrophilic organic solvents[16]. When solid enzymes are at moist air, thecatalytic activity of enzymes strongly depends on thethermodynamic water activity (aw), which is the ratioof water partial pressure to vapor pressure of purewater [17]. Likewise, since adsorbed enzymes are
solids in hydrophilic organic solvents containing low
water content, it is probably that the catalytic activityof adsorbed enzymes is influenced by the water
activity. However, there have been few reports
regarding the relation between the water activity in

The utilization of biomass wastes, which arecarbon neutral, for energies and functional materials
is one of the most important challenges to reducegreenhouse gas emissions [1], [2]. However, almost
all forestry residues have hardly been used.
Accordingly, the development in the high valueadded application of forestry residues has been
desired to provide the multiple effective utilization
system of forestry residues.
On the other hand, environmentally benign
processes such as biotransformation, biosensor,
biofuel cell, and so on have recently been developedby using enzymes as a kind of proteins, since
enzymes exhibit their outstanding biological activity
under mild conditions [3]-[5]. However, enzymes aregradually denatured and inactivated under various
physical and chemical stresses such as heat, organic
solvents, and so on, although they are generally stable
in a cell [6]. To enhance the stress resistance of
enzymes, enzymes have been modified chemicallyand genetically [3], [7]. As a chemical modification,
enzyme immobilization and stabilizers have beendeveloped, and molecular engineering has been
carried out as a genetic modification. Among these
enzyme modifications, an enzyme immobilization
system has widely been studied due to following
advantages [3]: 1. Concentration of substrate can beincreased. 2. Recycled enzymes can be used manytimes. 3. Separation of the products is straightforward. 4. Stability of the enzyme to change understress is increased. Especially, the adsorption of443

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

phosphate buffer solution at pH 7 containing 300 μM
α-CT and 3 g/L BCP was placed in a 10-mL test tube
with a screw cup, and was incubated at 25 ℃ and 120
rpm for 24 h. After adsorption, the mixture wasfiltrated with a membrane filter (pore size: 0.1 μm,
Millipore Co. Ltd.). The amount of α-CT adsorbed
onto BCP was calculated by subtracting the amountof α-CT included in the supernatant liquid after
adsorption from the amount of α-CT in the aqueous
solution before adsorption. The amount of α-CT was
measured at 280 nm by UV/vis spectrophotometer(UV-1800, Shimadzu Co. Ltd.).

hydrophilic organic solvents and the performance ofadsorbed enzymes.
In our present work, we have assessed how thewater activity affects the organic solvent resistance of
enzymes adsorbed onto biomass charcoal powder inhydrophilic organic solvents. We have used bovinepancreas α-chymotrypsin (α-CT) as a model protein
since it is well investigated regarding its structure,functions, and properties [18].

MATERIALS AND METHODS
Materials

Measurement of
Chymotrypsin

α-Chymotrypsin (EC 3.4.21.1 from bovinepancreas) (type II, 52 units/mg solid)( α-CT) was
purchased from Sigma-Aldrich Co. (St. Louis, USA).
N-Acetyl-L-tyrosine ethyl ester (N-Ac-Tyr-OEt) andN-acetyl-L-tyrosine (N-Ac-Tyr-OH) were also from
Sigma-Aldrich Co. (St. Louis, USA). Acetonitrile ofguaranteed grade was obtained from Kanto Chemical
Co. (Tokyo, Japan). Before acetonitrile was used as areaction solvent, it was dried by storing it over dry 0.3
nm molecular sieves (Wako Chemical Co.) for at least
24 h.

Catalytic

Activityofα-The standard reaction for transesterification was
carried out as follows: Three milliliter of acetonitrile
containing a certain amount of water, 10 mM N-AcTyr-OEt, 1000 mM n-butanol, 1 mM acetanilide, andfree α-CT or BCP-adsorbed α-CT (30 μM) was placedin a 4 mL screw-cap vial, and was incubated at 120
rpm and 25 oC. The amounts of the reaction
components were periodically determined with
HPLC (Shimadzu LC-10A) ( Shimadzu Co., Kyoto,
Japan) using a TSK-GEL ODS-80TM column (Tosoh
Co., Tokyo, Japan) eluted with water-acetonitrile (6:4
by volume) at 0.5 mL/min with detection at 270 nm.
Acetanilide was used as an internal standard.

Preparation of Bamboo Charcoal Powder
To prepare bamboo charcoal, under nitrogen
atmosphere, bamboo waste was dried at 180 ℃ for 2
hr, was pyrolyzed at 450 ℃ for 2 hr, was carbonizedat 350 ℃ for 3 hr, and then was cooled at 100 ℃ for
1 hr by pyrolyzer (EE21 Pyrolyzer, EEN Co. Ltd.,
Japan).
Bamboo charcoal powder (BCP) was
obtained by grinding the resultant bamboo charcoal
with jet mill (100AS, Fuji Sangyo Co. Ltd., Japan).

Measurement of Remaining Activity of αChymotrypsin
In order to assess the thermal stability of free αCT and BCP-adsorbed α-CT, the activity of free α-CTor BCP-adsorbed α-CT was measured at the water
activity of 0.15 after free α-CT or adsorbed α-CT wasstored in acetonitrile at 50 ℃ for appropriate time,
and then was cooled at 25 ℃ for 30 min. The
remaining activity was obtained by Equation (1).

Characterization of Bamboo Charcoal Powder
The SEM micrograph was obtained using ascanning electron microscope (JSM-7500FA, JEOL,Japan) operating at 15 kV. The sample for SEM was
prepared on a carbon tape without vapor deposition.
All samples were outgassed at 300oC for 8 hprior to the nitrogen adsorption measurements. The
specific surface area of BCP was calculated with theuse of the Brunauer-Emmett-Teller (BET) method
using a micropore system (BELSORP-mini II, BEL
JAPAN, INC.).
The surface of BCP was analyzed by X-ray
photoelectron spectroscopy (XPS) (Quantum-2000,
ULVAC-PHI Co. Ltd.) operating at an x-ray beam
size of 100 μm.

Remaining activity (%) =×100

Activity after heat treatment

Activity before heat treatment(1)

Measurement of Fourier Transform Infrared(FTIR) Spectroscopy
FTIR measurements of free α-CT and BCPadsorbed α-CT were carried out using a Jasco FT/IR
spectrometer model FT/IR-4100. A KBr pellet
containing 0.5 mg of free α-CT or BCP-adsorbed αCT powder per 100 mg of KBr was prepared, andthe measurements were performed using 512 scans
under 4.0 cm-1 resolution.

Adsorption of α-Chymotrypsin onto Bamboo
Charcoal Powder

RESULTS AND DISCUSSION

As a typical procedure, 5 mL of 0.01 M
444

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

Fig. 1 SEM images of bamboo charcoal powder(BCP).
Fig. 2 Effect of water activity on the initial rate(Ve) of transesterification and the initial rate(Vh) of hydrolysis in acetonitrile. The enzyme
was added into acetonitrile containing 10 mM
N-Ac-Trp-OEt, 1000 mM n-butanol, and 1 mM
acetanilide at an appropriate water activity, andthe resulting mixture was shaken at 120 rpm and25 oC.

Table 1 Characteristics of BCP.
Textural property
Experimental value
Specific surface area (m2/g)
294
Pore volume (cm3/g)
0.041
Pore diameter peak (nm)Less than 2.6

To estimate the chemical property of the surfaceof BCP, BCP has been measured by X-ray
photoelectron spectroscopy (XPS). As shown in
Table 2, carbon atom was the main element, oxygen
atom was also located on the surface of BCP to someextent, and nitrogen atom was detected at a small ratio.
Furthermore, by the measurement of narrow scan
spectra of XPS, C-C, C-H, C-O, O-C-O, C=O, COOH,
and C-N were detected as a chemical state of carbon.
BCP-adsorbed α-CT was obtained by dispersing
BCP in the buffer solution at pH 7 containing α-CT,and the amount of α-CT adsorbed onto BCP was 9.8μmol/g. The charge of α-CT is positive in the buffer
solution at pH 7 since the isoelectric point of α-CT is
9.1 [18]. On the other hand, the ζ-potential of BCP isnegative at pH 7 in the buffer solution at pH 7 [10].
Accordingly, the electrostatic interaction between αCT molecules and BCP mainly contributes to theadsorption of α-CT onto BCP.

Table 2 Elemental ratio of BCP measured by X-ray
photoelectron spectroscopy.
Element
Atomic percentage (%)
Carbon80.7
Nitrogen
0.8
Oxygen
15.9
Other
2.6
Characterization of Bamboo Charcoal Powder
We have pyrolyzed bamboo waste at low
temperatures under nitrogen atmosphere to producefunctional groups, which were used as a binding site
for the adsorption of enzymes. The fine bamboo
charcoal powder was obtained by grinding theresultant bamboo charcoal with jet mill. The mean
diameter of BCP was 7 μm.
Table 1 shows the characteristics of BCP. The
surface area of BCP was one order of magnitude
lower than that of activated carbon, which is used as
an adsorbent, and was the pore volume of BCP was
low as well. Moreover, the pore diameter peak wasmuch smaller than the size of α-CT since the size ofα-CT is 5.1 x 4.0 x 4.0 nm [18].
Figure 1 shows the scanning electron
micrograph of BCP. The surface of BCP was almost
smooth. It is probably that micropores were notobserved under the magnification measured in thepresent work since the pore size was several
nanometers or less.

Dependence of Catalytic Activity of BCPAdsorbed α-CT on Water Activity in Acetonitrile
An enzymatic reaction in hydrophilic solvents
has the advantage of the solubility of a variety of
substrates, including amino acid derivatives, which
are poorly soluble in hydrophobic solvents [19].
However, when a hydrophilic solvent is used as areaction medium, the enzyme molecule directly
comes in contact with the solvent, and thereby its
catalytic activity is strongly influenced by the natureof the solvent [20], [21]. Moreover, the catalytic
445

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

Table 3 Ratio of the absorbance at 1650 cm-1 tothe absorbance at 1630 cm-1 (ABS1650/ABS1630)
of BCP-adsorbed α-CT provided by the FTIR
measurement.
Water activity (-)
ABS1650/ABS1630 (-)
0.03
1.3
0.28
1.3
0.55
1.3
0.73
1.3
activity of enzymes tends to be reduced sincehydrophilic solvents tear water from enzymes. Water
bound to enzymes is essential for enzymes tomaintain their mobility for catalysis [22].
Accordingly, it is considered that the performance of
enzymes is strongly influenced by the water activity
in hydrophilic solvents. To assess the effect of water
activity on the catalytic activity of BCP-adsorbed αCT in acetonitrile, we have examined the relationshipof initial rates of transesterification and hydrolysis
with the water activity in acetonitrile. The water
activity was prepared by adding an appropriate
amount of water to acetonitrile [23]. Figure 2 shows
the plots of the initial rate (Ve) of transesterificationand the initial rate (Vh) of hydrolysis against the water
activity in acetonitrile at 25 oC. The inherent
enzymatic hydrolysis of N-acetyl-L-tyrosine ethyl
ester (N-Ac-Tyr-OEt) with water was inhibited by
low water activity, while the enzymatictransesterification of N-acetyl-L-tyrosine ethyl ester(N-Ac-Tyr-OEt) with n-butanol (BuOH) was
promoted. The initial rates of transesterification
catalyzed by BCP-adsorbed α-CT and free α-CT werestrongly dependent on the water activity, anddisplayed a bell-shaped curve. The initial rate oftransesterification catalyzed by BCP-adsorbed α-CT
was about sixty times greater than that catalyzed byfree α-CT when the water activity was 0.28, at which
the maximum initial rates of transesterification of freeα-CT and BCP-adsorbed α-CT were obtained. On theother hand, the initial rates of hydrolysis catalyzed byfree α-CT and BCP-adsorbed α-CT increased with anincrease in the water activity. The relationshipbetween the catalytic activity of enzymes and thewater activity in organic solvents tends to exhibit
bell-shaped curve. The optimal water activity resultsfrom the balance between the kinetic rigidity ofenzyme structures and their thermodynamic stability[20], [23]. The kinetic rigidity decreases withincreasing water activity, while the native enzyme
structure gradually changes through thermodynamic
stability. Accordingly, the catalytic activity ofenzymes increases with an increase in the flexibilityof rigid enzyme structures, and then decreases with anincrease in the disturbance of enzyme structures. On
the other hand, since the increase of water activity
results in the increase of overall water concentration,

Fig. 3 Temperature-dependence of the initialrate (Ve) of transesterification and the initial rate(Vh) of hydrolysis in acetonitrile. The enzyme
was added into acetonitrile containing 10 mM
N-Ac-Trp-OEt, 1000 mM n-butanol, and 1 mM
acetanilide, and the resulting mixture wasshaken at 120 rpm and appropriate temperature.
the hydrolysis is enhanced by the increase of water
activity. Regarding the reaction selectivity, which
was the ratio of the initial rate (Ve) oftransesterification to the initial rate (Vh) of hydrolysis,
BCP-adsorbed α-CT was much superior to free α-CT.
Table 3 shows the ratio of the absorbance at1650 cm-1 to the absorbance at 1630 cm-1
(ABS1650/ABS1630) of BCP-adsorbed α-CT. The
bands at ca. 1650 and 1630 cm-1 are assignable to αhelix and intramolecular β-sheet, respectively [24].
The higher absorbance ratio, the higher secondary
structure.
Since
the
absorbanceratio(ABS1650/ABS1630) of BCP-adsorbed α-CT was
independent on the water activity, the secondary
structure of BCP- adsorbed α-CT was not influenced
by the water activity. Thus, the secondary structure of
BCP- adsorbed α-CT is firmly maintained through theadsorption. The absorbance ratio (ABS1650/ABS1630)
of BCP- adsorbed α-CT is higher than that of free αCT [16]. The results indicate that the water activity
effectively affects the catalytic activity of BCPadsorbed α-CT having a high second structure,compared to that of free α-CT.
Temperature Dependence of Catalytic Activity of
BCP-Adsorbed α-CT in Acetonitrile
Figure 3 shows the plots of initial rate (Ve) oftransesterification and the initial rate (Vh) ofhydrolysis in acetonitrile against reaction temperaturewhen the water activity was 0.55 at 25 oC. The initialrate of transesterification catalyzed by BCP- adsorbed
α-CT exhibited a maximum around 35 oC, and thendecreased with an increase in temperature, while thatcatalyzed by free α-CT slightly increased withincreasing temperature. The initial rate oftransesterification catalyzed by BCP- adsorbed α-CT
446

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

state, was unchanged during the heat treatment,
although enzymes dissolved in an aqueous solution
immediately form the aggregation of thermallydenatured enzymes [12]. Likewise, the enzyme
aggregation and the cohesion among BCP- adsorbed
α-CT were not observed in acetonitrile during the heat
treatment. However, the remaining activities of freeα-CT and BCP-adsorbed α-CT gradually decreased
with heat time. As seen in the figure, the relationshipof the remaining activities of free α-CT and BCPadsorbed α-CT with heat time could be correlated byfirst-order and second-order kinetics, respectively.
The half-lives of inactivation of free α-CT and BCPadsorbed α-CT calculated from the fitting curves in
the figure were 33 and 125 min, respectively. Thus,
the half-life of BCP- adsorbed α-CT exhibited 3.8fold, compared to that of α-CT. On the other hand, we
have reported that the half-lives of inactivation of
BCP- adsorbed α-CT is 15 min in an aqueous solution
at 45 ℃ [14]. Thus, the thermal stability of BCPadsorbed α-CT in acetonitrile was much superior tothat of BCP- adsorbed α-CT in water. The result
indicates that the adsorption is strengthened in
acetonitrile by the electrostatic force, which mainly
contributes to the adsorption of α-CT onto BCP, andstabilizes α-CT since the dielectric constant ofacetonitrile is much lower than that of water [27].

Fig. 4 Time course of remaining activities offree α-CT and BCP-adsorbed α-CT through theheat treatment at 50 ℃. The activity of free αCT or BCP-adsorbed α-CT was measured after
free α-CT or adsorbed α-CT was stored in
acetonitrile at 50 ℃ for appropriate time, andthen was cooled at 25 ℃ for 30 min.
exhibited 30-fold, compared to that catalyzed by freeα-CT at 35 oC. On the other hand, the initial rate ofhydrolysis catalyzed by BCP- adsorbed α-CT showeda maximum around 40 oC, and then decreased with anincrease in temperature, while that catalyzed by freeα-CT showed a slight increase with increasing
temperature, as well as the case of transesterification.
The initial rate of hydrolysis catalyzed by BCPadsorbed α-CT was thirteen times greater than thatcatalyzed by free α-CT at 40 oC. Enzymatic reactions
obey the Arrhenius correlation between the reaction
rate constant and the reaction temperature as well as
chemical reactions [25]. Thus, the initial rate becomes
higher at higher temperatures. However, since thethermal denaturation of enzymes proceeds withincreasing temperature due to the disruption of weakinteractions in enzymes including ionic bonds,
hydrogen bonds, and hydrophobic interactions, which
are prime determinants of enzyme tertiary structures.
On the other hand, the water activity is influenced bytemperature [26]. Consequently, it is probably that the
optimal temperature of the catalytic activity of BCPadsorbed α-CT was observed due to these factors. The
result indicated that the catalytic activity of α-CT issufficiently enhanced by adsorbing α-CT onto BCP
since the initial rate of transesterification catalyzed by
BCP- adsorbed α-CT was about fifteen times greaterthan that catalyzed by free α-CT even at 50 oC.

CONCLUSION
We have demonstrated that the water activity
affects the catalytic activity of α-CT in acetonitrile.
The catalytic activity of BCP-adsorbed α-CT was
more effectively enhanced by changing the water
activity than that of free α-CT. The catalytic activityof BCP-adsorbed α-CT was strongly influenced byreaction temperature. The catalytic activity of BCPadsorbed α-CT exhibited the optimum temperature,
and was much greater than that of free α-CT. The
thermal stability of α-CT was markedly improved byadsorbing α-CT onto BCP, and the half-life of BCPadsorbed α-CT exhibited 3.8-fold, compared to thatof α-CT.
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448

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

EVALUATION OF ENERGY EFFICIENCY AND ENVIRONMENTALPERFORMANCE IN LOBLAW COMPANIES LIMITED IN CANADA
1

Koiwanit, J.1, Chan, V. K.2, Piewkhow, L.3, Katipelly, N. D.4
Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
2

Faculty of Engineering and Applied Science, University of Regina, Canada

ABSTRACT
There is growing pressure to limit Global Warming Potential (GWP) as it is the most significant way to
reduce serious threats to people. The increase of average temperature in the atmosphere causes adverse effects on
the environment, and this is changing the way business operates. Loblaw Companies Limited, the largest food
distributors in Canada, has put more concerns on environmental impacts and worked diligently to reducegreenhouse gas (GHG) emissions through actions such as improving energy efficiency reducing refrigerant leaks,
and incorporating renewable energy sources. This study analyzed Loblaw’s energy efficiency and environmental
performance and provided suggestions in the applications of skylight improvement, geothermal, refrigeration
systems, kinetic energy to electricity, and e-grocery shopping. The results showed that the environmental
concerns were substantially decreased. However, types of lights and refrigerators, distance driven, vehicle types,
fuel used in e-grocery shopping results in the different amount of emissions; consequently, the GHG emissions
varied depending on these factors. By integrating more environmentally technology, Loblaw could further
reduce their emissions and waste and become a more sustainable company.
Keywords: Environmental performance; Greenhouse gas emissions; Energy efficiency; TRACI; GaBi 6

All of these showed that they take reducing carbon
emissions and contributing to mitigating climatechange as their priority.
The objective of this study is to analyze energy
used by Loblaw and provide suggestions for
improvement. The GHG impacts on the provided
suggestion was evaluated using the Life Cycle
Assessment (LCA) methodology. The GaBi
software system and databases developed by PE
International, Germany together with TRACI, a life
cycle impact assessment methodology, were appliedin this study to convert existing inventory data into
GHG impacts. The broad range data sets of the GaBi
cover many different industrial sectors including
metals (steel, aluminum and non-ferrous metals),plastics, mineral materials, energy supply (steam,thermal energy, power grid mixes), transport,
disposal, manufacturing, and electronics.

INTRODUCTION
With a supermarket chain of over 2,000 storesoperating under Loblaw and over 17 million
Canadians shopping at the stores every week,
Loblaw is the largest food distributor in Canada [1][2]. For over 50 years, Loblaw has supplied theCanadian market with innovative products andservices through corporate, franchised andassociated stores. These supermarket chains include
Loblaws®, Provigo® and Zehrs® [3]. With
environmental concerns, Loblaw plays a major rolein energy usage over other food distributors. They
have answered with many innovations like theintroduction of the reusable shopping bag, new“green” products and even installing a wind turbine
to generate renewable energy. Regarding power
consumption, Loblaw has worked diligently to
reduce greenhouse gas (GHG) emissions throughimproving energy efficiency, reducing refrigerant
leaks, and other renewable energy initiatives.
According to Loblaw Companies Limited Corporate
Social Responsibility Report in 2015, Loblaw has
been tracking their operations focusing on carbon
emissions since 2010 [4]. The results showed thatthey achieved their target of reducing energy
consumption in stores by 4%, by investing in newlighting, upgrading fleet and building fuelconsumption, refrigerant releases and corporate
travel, and using renewable energy technologies [4].

TECHNOLOGIES TO SAVE ENERGY AND
IMPROVE EFFICIENCY
Supermarkets have reduced their electricity
consumption to improve energy efficiency andreducetheircarbonemissions.
Lighting,
refrigeration system, and heating, ventilation and air
conditioning (HVAC) system are key opportunities
for energy saving upgrades in typical supermarkets
and these are monitored and controlled bycentralized building energy management systems [5]449SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[6]. Example of technologies for energy efficiency
upgrades are shown as follows [5] [7]:evaluated high, medium, and low if Loblaws need tospend a lot of money, not much money, and very
low amount of money for the suggestions,
respectively.
- Knowledge: this knowledge refers to theknowledge required for each suggestion. Advanced
knowledge is required when the criteria is high,intermediate level of knowledge is required for
medium, and low skills are required for low criteria.
- Time to adopt: this is the amount of time spenton implementation. For example, the time to adopt
the new refrigeration systems is for six months; thismeans that six months are required to make changes
on the refrigeration systems.
- Parties involved: this category shows the people
or organizations who are involved or interested ineach suggestion.
- Public perception: this refers to the conscious
understanding that people have of public and official
issues. A high public perception means a high levelof public beliefs in the suggestions, medium means
the majority ofpeople are agree with thesuggestions, low means there are not many people
who support Loblaws for the implementation.
- Ease of implementation: this refers to anassessment required of the ease or difficulty of
implementing the suggestions. The criteria isevaluated high if the suggestions are allowed foreasy to set up, medium if the suggestions are not too
difficult to set up, and low if the suggestions are noteasy to set up.
- Capacity to reduce emissions: this assessment
refers to an ability of suggestions to reduce
emissions. The criteria is evaluated high if thesuggestions have a high capacity in emission
reductions, medium if the suggestions are normal inemission reductions, and low if the suggestions are
low in emission reductions.
- Administrative simplicity: This is to perform thetask of simplification of administrative procedures.
The simplicity criteria is high when the suggestions
are difficult for administration, medium when thesuggestions are in general for administration, andeasy when the suggestions’ determination are easy tounderstand and manage.
The analysis on the environmental performanceof the visited store and suggestions for improvement
is summarized in Table 1.

Lighting- Occupancy sensors installation in the active
storage, restroom, office zones, etc.
- Skylights usage in warm and hot climates
Refrigeration- Using frozen food and ice cream
refrigerated cases with vertical models withdoors
- Using medium-temperature refrigerated
display cases with doors
HAVC- Highest efficiency HVAC installed
throughout corporate offices, stores, etc.
- Using an active HVAC asset performancetracking program- implementing ground source heat pumps,
packaged variable air volume systems,
radiant heating and cooling, etc.
- Solar thermal technologies usage forservice water heating
SUGGESTIONS FOR IMPROVEMENT
Loblaw has put in much effort into improving
their environmental performances in energy
efficiency; however, there is also some room for
improvement. After visiting the Superstore in
Regina East, Saskatchewan, Canada, this study
showed five suggests for Loblaw/Superstore to
become more environmentally friendly. The
suggestions were analyzed based on the follow:- Reliability: the reliability of a suggested ismeasured by the quality of producing stable andconsistent results. A high means the suggestions
produce similar results under consistent conditions,
medium means the suggestions produces somewhat
the same results, and low means it is hard to be
reproduced with similar results.
- Applicability: this indicator refers to a degree ofbeing applied. The applicability criterion isevaluated high if Loblaws have a high potential to
implement the suggestions, medium if Loblaws havepotential to apply them but not immediately, and low
if Loblaws are nearly unable to implement thesuggestions.
- Cost: this refers to all direct and indirect costs
required for the suggestion. The cost criterion is
Table 1 Analysis of Suggestion of Improvement

1

Suggestion
pointsReliability

Applicability

Cost

Know
-ledge

Time
to
adopt

Parties
involved

Publicperception

Ease ofimplementation

Capacity to
reduceemissions

Administrative
simplicity

Skylight

High

High

MediumHigh

Now- Loblaw- Con-

High

Medium

High

Easy

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

improvement
2

Geothermal(for newstore)

High

High

High

High

3–5
years

3

Refrigeration
systems

High

High

Low –
MediumHigh

6months4

Kinetic
energyto electricity
E-grocery
shopping
systemMediumMediumMedium

Low

1–2
years

High

Medium

Low

High

1–2
years

5

structioncompany- City ofRegina- Loblaw- Construction
company- City ofRegina- Loblaw- Construction
company- City ofRegina- Loblaw- Suppliers- Loblaw- Customers

High

Easy

MediumMediumHigh

Easy toMedium

High

Easy

High

Medium

low

Easy

High

MediumHigh

Highenvironment significantly during the day. Anotheroption would be to simply switch off the lights.
The National Association of Rooflight
Manufacturers (NARM) commissioned the Instituteof Energy & Sustainable Development at Leicester’s
De Montfort University to undertake a study toinvestigate the effect skylights have on the annual
CO2 emissions which result from the use of energy
needed to operate a building. Savings fromdaylighting can cut lighting energy use by 50
percent [9]. Based on the average supermarket's
electricity consumption is 5,000 MWh per year [10]and the energy consumption of lighting isapproximately 15% to 25% of the total consumption[11].
It can be seen from the results generated by
TRACI that savings from daylighting could reduce
the energy usage numbers from 1250 to 625 MWh
per year. The main substances that contribute to the
Global Warming Potential (GWP) are CO2, Methane(CH4), and Nitrous oxide (N2O), and the highest
contributor to the GWP comes from CO2. CO2
emissions emitted into the air could be substantiallyreduced by 50% from 789,026.66 to 394,513.33 kg
CO2-equiv. per year. This study covers electricity
produced, but no accounting will be made of the
GHG effects associated with construction,transportation, and operation of the Superstore.

All the above suggestions are explained in moredetails as follows. However, GHG emissions will becalculated using GaBi 6 software tool forsuggestions that show high capacity to reduce
emissions. The GHG impact results are generated
based on the TRACI methodology implemented in
the GaBi 6 software. The users enter all the inputs
and outputs of the two scenarios into the GaBi 6
software. GaBi 6 then generates the GHG emissions
based on the TRACI methodology.
Skylight Improvement
Lighting makes up the second largest share of
the energy use and electricity bill [8]. Based on thisreason, installing skylights can help savesupermarkets’ energy since a well-designed building
with a good spread of natural light will benefit frompassive solar gain and a reduced requirement for
artificial light. The combination of these factors
means that including skylights can offer a dramatic
reduction in a building’s total energy consumption
and the emissions of CO2 associated with this energy
use. A naturally-lit interior will save money, provide
a more pleasant environment where people want tospend time, and contribute to the reduction of CO2
emissions.
The Superstore in Regina (East) has skylights
installed; however, the store also has lights installed
beneath the skylights. During our visit to the store,
there was enough natural light, but Superstore still
kept their lights. An improvement Superstore canmake is to combine the skylight design with anautomated dimming control system will achieve
substantial energy savings and improve the store

Use Geothermal
Geothermal energy is defined as heat from the
Earth. Geothermal energy can be utilized forelectricity production, for commercial, industrial,
and residential direct heating purposes, and for

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

efficient home heating and cooling throughgeothermal heat pumps. Heat pumps are reversibleof refrigerator and can provide either heating or
cooling to almost any space or location. In warm
weather the geothermal unit acts like homerefrigerator. It removes unwanted heat from thespace being cooled and deposits that unwanted heatsomewhere else, in this case to the earth. In cool
weather the geothermal heat pump acts as a reverse
refrigerator because it withdraws heat from the earth
and transfers that earth heat into the space being
heated such as building, home, mall, etc. Heatpumps use a vapor compression cycle to transportheat from one location to another. In heating mode,the cycle starts as the cold liquid refrigerant within
the heat pump which passes through a heatexchanger (evaporator) and then absorbs heat fromthe fluid circulated through the earth connection.
The refrigerant evaporates into a gas as heat isabsorbed from the earth connection heat exchanger(evaporator). The gaseous refrigerant then passes
through a compressor where it is pressurized, raising
its temperature to over 180 degrees F. The hot gas
then circulates through a refrigerant-to-air heatexchanger where the heat is removed and sent
through the air ducts. When the refrigerant loses theheat, it changes back to a liquid. The liquid
refrigerant cools as it passes through an expansion
valve and the process begins again.
This application can achieve very importantenergy savings by decreasing primary energy
consumption by 28% to 32%, energy for cooling byaround 25% and energy for heating by around 40%.
These combined can potentially reduce CO2
emissions by 28% to 32% [12]. However, installing
geothermal energy system would be costly for thecurrent Superstore and would be more applicable to
new stores in the future.

increase comfort for consumers, Loblaw could
consider replacing the open freezer units with units
with doors. This change would not only reduce GHG
emission significantly, it will also save a large
portion of Superstore’s electricity bill. The closed
display cabinets consumed less energy byapproximately 5.46 kWh/m2 per day compared tothe opened display cabinets [14] as summarized inTable 2.
Table 2 Electrical energy consumption of the closed
freezers (modified from [14])Energy consumption (kWh/m2/day)
Saving from closure (kWh/m2/day)Average12.6755.4575The analysis from TRACI showed that the closed
cabinets will cause a reduction of 30.1% in theimpact category of GWP compared to the opened
cabinets. CO2 emissions emitted into the air werereduced from 31,974.74 kg to 22,388.37 kg CO2equiv. per year. However, the analysis covered
electricity produced, but not for the GHG effects
associated with construction, transportation, andoperation of the Superstore.
Another suggestion for Loblaw to reduce theenergy consumption of the refrigeration system isthat the store could have one enclosed area for all of
the refrigerators in the store. By having all of therefrigerators in one area the cold air that escapes therefrigerator will be contained in the zone and will
lower the cost of refrigerating the units in that zone.
In addition, the new innovative refrigeration battery
from Axiom Energy can store energy at night when
it is inexpensive and this can be discharged during
peak hours for electricity demands in the afternoon.
The battery can retrofit to the exiting refrigeration
systems in which any modifications are not required.
This helps the Superstore to be able to turn off theirrefrigeration systems’ compressors and condensers
and save their electricity by up to 40% [15].

Improve Refrigeration
Refrigeration is the largest single energy
consumer in most supermarkets and has very highpotential for savings. According to Loblaw
Corporate Social Responsibility report from 2012,
running the refrigeration system contributes toapproximately 50% of a supermarket’s energy
consumption [1]. The most common practice is tohave open freezers, which causes the following
problems: (1) inefficient energy consumption, (2)cold aisles that causes discomfort to consumers, and(3) gaining temperature of food products more
rapidly than the ones in freezers with doors [13]. To
solve the above problems, supermarkets should
consider installing doors on every refrigerated
cabinet and use glass door displays instead of open
displays.
In the Superstore in Regina East, there are a lotof open freezers. To reduce energy consumption andKinetic Energy to Electricity
Renewable energy options are constantly
replenished and more environmentally friendly
compared to coal, oil, and natural gas for generatingenergy [16]. These options have experienced
explosive growth over the past decade [17]. For
Loblaws, electricity can be generated from thefootsteps of people by installing special piezoelectric
floor tiles. These tiles could be installed in the
supermarket to generate electricity for lights andrefrigerators within the supermarket. Pavegen
System is a company based in the UK and iscurrently the only that sells energy-harvestingpiezoelectric floor tiles. The new Pavegen’s V3 isknown to be generating over 200 times more power
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

than the first version launched in 2009 [18]. Eachfootstep can generate up to 8 Watts of electricity[19].
This study did an observation on people visiting
the Superstore in Regina and the results showed thatduring the busiest time on a Sunday, there areapproximately 200 people entering the store hourly.
Based on this, we can make an assumption that onhourly average of 200 people would enter the store
from 9 am to 9 pm and 100 people would enter thestore other period of times (store hours is 6am to11pm), giving a total of 2,300 people entering thestore daily. Assuming that Superstore has 8 tiles atthe entrance and each person entering the store
would step on 6 of them; that would give a total of
0.139 MWh per day. This gives a total of 50.808
MWh per year, saving 1% of the electricity (basedon the previous assumption that an average
supermarket consumes 5000 MWh of electricity peryear). Based on 2.17 pound of CO2 eq/kWhelectricity generated by lignite [20], the GHG
reduction per year would be approximately 984.3
gCO2 eq.
Although the amount of electricity saved by thetiles is not as high as the wind turbine, the capitalrequired is also much lower, which makes thefeasibility much higher. Wind turbine generating 10
kw costs approximately $48,000 – 65,000 to install[21]. Pavegen’s V3 is easy to install with nomaintenance costs. Even though the cost of thistechnology is currently not released to the media,
cost of a standard square meter of used in a building
would cost approximately $1,170 [22]. Since there
are no regulations and community restrictions on
this project, it is mostly up to the company to
execute this project. From planning to installing andrunning, this project should be able to execute within
a year. This product should be popular among the
public. The tile itself has a LED lighting, whichlights up with it is being stepped on (uses 5% of theelectricity it generates), this is not only visuallyattractive, but can also be a good source of education
to the public about sustainable and clean energy.

groceries are delivered by the Loblaw truck to thecompany at a certain time once or twice a week
(depending on the demand). The coordinators fromthe company are responsible for distributing thegroceries to employees in need.
As employees can take their groceries from theworkplace directly home, the individual trips togrocery stores can be avoided and the vehicles’
emissions can be greatly reduced. The applicabilityof this system should be high in Regina, sincemajority of the people are grouped in limited places
for work and the system has high potential to reduce
GHG emission reduction.
This study assumed that 100 employees from the
University of Regina (U of R) join this program andtheir average traveling distance is 6 km one way (i.e.
12 km return). A typical car is assumed to have aluggage space with around 424 liters [24], whereas acargo van is assumed to have a luggage space with
6,787 liters [25]. In addition, this study assumed that
1 customer will buy goods with their full of luggage
space. As a result, Superstore will need to deliver
their products to 100 customers for 7 rounds in total.
By delivering to the 100 employees to the U of R,
the results from the TRACI method showed a92.9 % reduction of the impact in the GWP category
in the “E-grocery shopping” scenario compared to
the “conventional shopping” scenario. However, thisstudy covers transportation and gas produced, but noaccounting will be made of the GHG effects
associated with construction, operation of theSuperstore.
CONCLUSION
Over the years, supermarkets have been
undergoing changes to be more environmentallyfriendly. Loblaw committed on creating a positive
impact in the community being socially responsible
by respecting the environment. They have taken big
measures to reduce their emissions, such as cutting
discharges
fromrefrigeration
units
and
implementing a new low temperature system, which
reduces greenhouse gas emissions. In addition, thismakes supermarkets substantially cost savings andconsequently high returns of investment. In thisstudy, the energy efficiency and environmental
performance of Loblaw have been analyzed. It canbe shown that Loblaw has put in a lot of effort toenhance their environmental performance.
However, there are some areas of improvement
and this study has presented 5 suggestions for
Loblaw’s further improvement. This study paid avisit to the Superstore in Regina East to inspect theapplicability of our suggestions. The results showedthat the option that is the most reliable, cheap, andeasy for an implementation is the skylight
improvement. However, as online shopping is
becoming more popular these days, e-grocery

E-Grocery Shopping System
An online ordering and delivering service isbecoming increasingly popular in any companies
because of continued increases in mobile adoption
and broadband penetration which result in its service
convenience with time saving [23]. The idea of the
E-Grocery
shopping
systemisthat
Loblaw/Superstore provides an online grocery
shopping system to consumers. However, instead ofdelivering individually to the customers, Superstore
delivers to companies in which the consumers are. In
other words, Superstore would have somearrangement with big companies and customers are“grouped” by the companies they are in. The
453

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[12] Garcia J, Coelho L, Cerdeira R, Sanner B, Lentz ,P, & Frechin N, “Application of ground source
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454

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

AN EVALUATION FOR EFFECTIVE PUBLIC PARTICIPATION IN
EIA IN THAILAND
Chutarat Chompunth1
School of Environmental Development Administration,
2
National Institution of Development Administration, Thailand
1

ABSTRACTIn Thailand, environmental conflicts and problems from project development are increasing vastly. Many
development projects have been delayed or postponed. The public has lost confidence in the environmental
monitoring and mitigation plans of the EIA system. Many ongoing projects cause severe environmental andsocial impacts. To solve this problem, public participation in the EIA system is considered as a vital theme topromote sound management of development projects. Although, public participation has become an essential
element of environmental decision-making and has grown considerably in Thailand, it frequently fails to solve
environmental conflicts. Thus, there is significant to evaluate public participation practice to consider whether
the participation process is effective and what works or does not work in this manner. This research aimed toevaluate the effectiveness of public participation in the Thai EIA system. The evaluation is based on in-depth
interviews with key stakeholders, review of EIA reports as well as observing public hearing forums. The
evaluation of the selected case study presented an overall weakness of public participation practice. It was foundthat the public participation in Thailand was not completely effective when tested against the evaluation criteria.
The affected people had no chance to present any comments at the very beginning. The public participation
process started too late, after a decision had been made and conflicts among stakeholders already occurred.
Public participation is not yet properly established in the Thai context. There is an urgent need to find an
appropriate approach and conditions of public participation in Thailand.
Keywords: Public Participation, Evaluation, EIA, Environmental Conflictparticipation in the implementation of development
projects in Thailand and identifies the critical factors
for effective practice of public participation. The
public participation processes of the Khao Hin Son
power plant was evaluated to provide evidence toanswer the research questions of this study that is:
How effective is public participation for managing
environmental conflict management in development
projects in the Thai contexts?
The research findings and recommendations arevital to improve the public participation practice inThailand and to enable all stakeholders to effectively
participate in the decision-making process.

INTRODUCTION
Thailand’s rapid economic growth andindustrialization over the last five decades have led
to significant environmental crisis. The Thaigovernment recognizes the linkage between
continued economic prosperity and the protection of
the environment. Thus, the concept of public
participation in the environmental decision-making
process through a number of laws and legal
requirements was established, and the public began
to recognize their rights granted by laws. Although afoundation for involvement in the decision-making
process is provided to the public, this is still in theearly stage of implementation [1].
Public participation is a continuing challenge in
Thailand. A number of development projects
initiated either by the government or the private
sectors frequently face strong public opposition andthe public participation process itself is viewed as
unsuccessful practice. The question of how to be
sure that the participation process is effective andresults in desirable outcomes seems to be vital [2]. A
systematic evaluation of public participation isessential as a means to ensure the acceptance of theprocess and outcomes, and, importantly, to develop
knowledge of how to improve the practice [3].
This study is important to Thailand because it
highlights the significance of conducting public

A Conceptual Framework of Public Participation
What is Public Participation?
The term public participation has numerous
different meanings and definitions. Different
academics have different meanings when defining
the term ‘public participation’ depending on who thepeople are and what the setting is [4]. It is always
viewed differently depending on its contexts andpurposes. In the past, public participation wasconsidered as being an opportunity to givecomments in a public hearing, to vote inreferendums, or just being a member of a social
movement society. Frequently, public participation
455

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

related to participation at public hearings only, but,at present, this term refers to a diversity ofprocedures for facilitating members of the public tobe effective participants in deliberations in decisionmaking processes [1], [5].

participation to be effective in any context, it
requires the public to be well informed and kept
aware of the possibility of participation.
Conclusively, the definitions of effectivenessare pretty much influence by individual expectations
and interpretations. Thus, it can be summarized thatthat there is no single definition of effective
participation processes.

Effective Public Participation
When a government or a private agency employs
public participation in their activities, there is a
substantial interest in determining whether or nottheir endeavors have been successful .To begin with,
it is important to clearly verify and define what
successful or effective public participation means. In
general, the effectiveness can define as: “whether
something works as intended an meets the
purpose(s) for which it is designed”. However
indeed, the definition of effectiveness is typicallycomplicated because of a diversity of objectives andexpectations for public participation processes andmechanisms. The definition and interpretation canvary depending on participants’ and stakeholders’perspectives, contexts and situations. Specificpolitical, social and economic contexts in eachcountry typically have an influence on theeffectiveness of public participation. For thesereasons, developing a single universal definition ofeffective public participation is difficult.

A Development of Evaluation Frameworks for
Public Participation
Obviously, the existing evaluation approaches
vary widely with regards to differences in concept,
purpose, focus, scope, methodology and disciplinary
perspective. Besides, different stakeholders may
have different objectives and measurements. As aresult, the evaluations in the participation field havebeen applied from a variety of theories such as
public participation theory, communication theory,and democratic theory [2], [6]. Indeed, theapproaches to public participation evaluations areprimarily developed from the traditional evaluationthat focused on whether public participationachieves either process or outcome goals [6].
Most acknowledged evaluation approaches ofpublic participation are related to the effectivenessof the construction and implementation of theparticipation procedure, and the success of theoutcome. The participatory process-based evaluation
typically measures fairness and competence matters,interchanged
information,
inclusivenessandprocedures. This includes the evaluation for how
effective public participation is in democratic
decision-making. The outcome-based evaluation
uses indicators of how stakeholders influence
decisions, their satisfaction with the final decisions,or an ability to reach a consensus. This approach is
not only based on stakeholders’ or users’ goals, but
it also includes social goals [7].

In terms of process effectiveness, many scholars
indicate that process effectiveness focuses primarily
on means rather than ends [1], [4]. It is therefore, toexamine a variety of procedural aspects of theparticipatory programs that add value to a decision
making process. These factors include; procedural
justice, accessibility to the decision making process,inclusiveness, diversity of views represented,
opportunitiesforparticipation,
informationexchange, identification and integration of concerns,
early involvement of stakeholders, number of
options identified, number/types of participants,
decision maker presence at meetings, availability
and clarity of materials, etc..

In order to make a rigorous evaluation of public
participation processes and build generalizableconclusions, some consistency in theoreticalframeworks is essential and needed. An evaluation
model for the evaluation of the public participation
process of this study is developed which includes
process-based evaluation and outcome-based
evaluation.

For some practitioners, the success of a public
participation endeavor can be judged in terms ofresults or outcomes. They proposed important
outcomes in term of; project/decision acceptability,
mutual learning, improved understanding andconflict resolution [5]. However, in practice, it isdifficult to facilitate public participation processes toachieve all desired elements.

Process-based evaluation of participant activities
aims at evaluating the characteristics of stakeholders
focuses on an identification of stakeholders and theinclusiveness and adequate representativeness of theparticipants. Outcome-based evaluation focuses onan evaluation of impacts and influence of theparticipation process, resolving conflict and an
integration of public values and concerns to thedecision-making process [2], [4].

Effective participation should be perceived as ameans to enhance effective decision making throughan opening-up of the decision process to public
views. Through this approach, public participation
could constitute accountability and transparency tothe decision-making process. These elements should
be used as an outline when the practitioner designs apublic participation program [6]. Thus, for public

It can be seen that this evaluation framework
456

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017attempts to make more explicit the factors thatshould be considered when evaluating both theprocesses and outcomes of a public participation
process. The framework facilitates a balanced
evaluation that indicates not only effectiveness but
also the factors instrumental to that effectiveness.
The evaluation criteria also encompass substantialconsideration of the participation processes andoutcomes [3].

priority to participate in the process to lay people in
the impacted area who were directly impacted fromthe development project.
A similar finding was evident in other research[8], [9]. It was found that it was difficult to engage
an appropriate and inclusive representative crosssection of the entire community in a participation
process. Local villagers and stakeholders who would
be directly affected by, or benefit from the decision
and were closer to the project, should have firstopportunity to participate and present their concerns.
Stakeholders who felt they were excluded from thedecision-making process would mount strong
opposition to the project or policy initiatives which
could delay or cancel the implementation.

METHODOLOGY
A single case study was adopted for thisthesis in order to conduct an in-depth study of the
public participation practices in the Thai context. To
achieve broader and better data and results, mixed
methods of data collection were carried out. The first
method was a review of documents concerning theoperations, activities and concepts of public
participation process. Interviews were selected,
including semi-structured and in-depth interviews
with stakeholders. Stakeholders who held key
positions or played important roles in the public
participation process were identified and selected.
All relevant data were reviewed to build up
knowledge and framework about the case study andpublic participation process. These processes aimed
to provide background on the rationale for public
participation and the Thai EIA system.

Multiple and appropriate participation methods
A number of participation techniques were used
to engage and communicate with the public;
nonetheless, they were not conducted at the earlystage of the project, particularly after the conflictoccurred. These techniques ranged from traditional
methods on an education and information provisionlevel, to a more interactive approach such as public
meetings. However, the majority of them weretraditional. The public did not have more
opportunities to discuss the issue and manipulate thedecision.
The selected participation methods, particularly
a public hearing, seemed not to be appropriate to thesituation and the involved parties. Indeed, thegovernment usually used public hearings to solicit
the public’s opinions and solve conflict among
stakeholders in development projects; however,more often the public hearing was not successful insolving the conflict in Thai society, as clearlypresented in this project. Many affected villagers
were frustrated with the participation process andtheir government because they felt that the process
was not a participation process in which they could
make any change to the decision or create
appropriate dialogue.
Similarly, [10] and [11] found that, althoughtraditional methods were being widely used, they
focused on one-way transmission of informationfrom the developer or the authority to the public, andthe public had less opportunity to input into an earlystage of the decision-making processes.

RESULTS AND DISCUSSION
Process-Based Evaluation
Inclusiveness and adequate representativeness]In this study, inclusiveness of the participants
was not achieved due to some constraints such as
strong opposing ideas of the protestors or unclear
practical guidelines. The authorities and thedevelopers did not try enough to engage
stakeholders, particularly the affected villagers, atthe beginning of the project implementation. Afterthe conflict occurred, a participation process wasthen initiated. Most protestors refused to take part inthese programs run by either the authorities or thedevelopers and made it difficult for the government
to engage all parties in the participation process.
Besides, there were problems in practice whenselecting the right participants due to selection
criteria not being clear. For example, the participantsin the public hearing case were identified andselected by a top-down approach which seemed toengage all stakeholders; however, the authorities did
not make clear who the stakeholders were and whoshould participate in the process. Thus, it was hardto say that the opinions and comments from theparticipation process represented the voice of all
people affected by the project. The finding
suggested that the authorities should give the first

Early Involvement
When the Khao Hin Son power plant was firstinitiated, it was implemented without providing
opportunities for the public to take part early enoughin project development. The affected people had nochance to present any comments at the very
beginning. The public participation process started
too late, after a decision has been made and conflicts
among stakeholders already occurred. Clearly, the457

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

public had little power to influence the decision andnothing could be changed. It could be said that, in
this study, a lack of public participation in the earlystage of project implementation became the criticalproblem.
This issue is a critical problem in practice inmany countries, such as the Czech Republic [12],Spain [13], Bulgaria [14], and Kenya [15]. The
public participation taken place late, particularly
when decisions have already been taken, could be
ineffective and obstructed by the public. This was
because it was too late for the public to makemeaningful contributions and its voice might haveless power to influence the decisions.

many technical terms, such as the EIA report. There
were also some mistakes in the EIA report. This led
to mistrust in other information provided by thegovernment and the developers. Additionally, theparticipation programs, particularly public hearings,
were conducted on workdays which means a numberof people were unable to attend.
From the research findings, it was found thatreceiving, sharing and exchanging precise, correct,
and updated information about the project was
critical for project implementation. The public
required sufficient information which was relevant
and accessible to increase their knowledge andunderstanding, and enable them to meaningfully
participate in the process.
A number of scholars stated that people could
not effectively evaluate the problems andalternatives unless they were provided withappropriate and sufficient information. These
resources are important and must be provided to the
public in order to achieve an effective participation
process [4], [17], [18].

Transparency
In this study, the participation process seemed
not to be open and transparent enough. All decisions
were decided before an involvement of the public;
thus the public could not see how the decisions werebeing made. For example, the contract was alreadysigned and the construction had been approved
before the public had any details about the project.
The affected villagers did not have an opportunity toparticipate through the processes. After the public
hearing, the committee could not clearly explain
how the public input was incorporated into thedecision-making process. The hearing report andconclusion was not widely publicized in order tocommunicate the results back to the participants.
The finding showed that if the participation process
was credible, transparent and legitimate, the project
would be more accepted and increase publicsatisfaction with decisions or even be successfully
implemented
There is considerable empirical evidence of alack of transparency in many studies [8], [16], [17].
This research showed that the decision-making andpublic participation processes failed to betransparent. An integration of public inputs into thedecision-making process was poor and hardly
existed. In particular, the information circulatedback to participants had little evidence of how theparticipation process had an impact on the final
decision.
Resource andaccessibility

information

availability

Outcome-Based Evaluation
Impact and influence of participation
In this study, it was clearly presented that in the
traditional management style of the Thaigovernment, the public was often excluded from thedecision-making process and the public did not haveany power over the decision. The public input hardly
influenced the decision-making process of thegovernment. The public were provided little
opportunity to comment on, or contribute to, any
aspect of the project in any participation programs. It
might be said that the decision-makers did not want
to distribute their power to the local people, or eventhe local government bodies. Importantly, they did
not intend to promote public participation at any
level.
When the impacted villagers found that theirinvolvement was too late and could not impact on
the decision or even make any change to the project,so they preferred not to participate in thegovernment’s or the project owner’s participation
processes and began their protest activities. Clearly,
the public needed to have a genuine opportunity to
be heard and influence the final decisions.
This problem also has been found in many
countries, such as Bulgaria [14], India [17], and theUK [18]. It was found that the outcomes of the
public participation process have failed to bereflected in the decision-making stage and the final
decisions. While the public expected that theyshould have a real influence in decision-making,they had a marginal influence only on what really
happened. Indeed, empowering was not only power
sharing and free access to information, but also anefficient transfer of necessary competency to theandIn this study, provision of resources wasinsufficient and unsatisfactory. Most relevant
information was difficult to access and not available
to the public. The public had difficultly accessing alldata and information related to the project,
maintained either by the government or the project
proponent.
Besides,
thisinformation was
inappropriate and incomprehensible for many
participants since most of it was in English and had
458

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

public.
Incorporation of public values and concerns

make everyone agree with a decision [4], [16].
Importantly, conflicts could not be solved if theprocess of decision making is perceived to be unfair
or biased.

Clearly, in this study, the local villagers tried to
add their knowledge and concerns into the process.
However, there was no obvious evidence that the
public input or the outcomes of the participation
process were brought and soundly integrated into thedecision-making process. The public input hardly
influenced the decision-making process of thegovernment. Although the project was cancelled,there was no official evidence presented that the
public input influenced the final decision. The
decision-making process remained with thegovernment.
Indeed, the public hold specific and valuable
information, particularly local geography, the local
ways of life, environmental conditions or otherrelevant factors that can influence the operation andsafety of the project. This knowledge was potentiallyvaluable to the decision-making process and should
not be overlooked. Integrating this local knowledge
and values into the decision-making processes could
assist in finding consensus which leads to moreaccountability and legitimacy that satisfies a broader
public. Undoubtedly, this study found that the publicneeded to ensure that their viewpoints and concerns
were meaningfully incorporated into the decisionmaking process.
The public participation process needed to be
conducted carefully to ensure that all stakeholders
were given opportunities to voice their ideas andconcerns, and every interest was considered fairly.
This would eventually lead to a better decision andconflict resolution [1], [12].

CONCLUSION AND RECOMMENDATION
To Establish Effective Public Participation in
ThailandPublic participation processes seem to be arational strategy for a developing country with apoor economy and struggling democracy likeThailand. However, in this study, it was found thatpublic participation of Thai people did not comply
with a real concept of public participation; people
who were stakeholders in the project did not have an
opportunity to be informed and to express their ideas
from the very beginning, and their opinions were notconsidered in the decision-making process. It could
be said that the public participation process was not
yet properly established in the Thai context. Thus,
there is an urgent need to find a working model andconditions of public participation which can assist in
resolving environmental problems.
From this study, it is recommended that public
participation should be considered as obligatory inany development project and local communities
should be empowered as equal development partners
who should participate in activities related todevelopment projects, in particular, in the design,
implementation, mitigation, and benefit sharing
aspects. This confirms that public participation was
more than a procedural obligation to comply with indevelopment project implementation [8]. It can
provide extensive advantages to the whole of society
in particular preventing, minimizing and resolving
conflicts, developing trust and co-operation among
stakeholders, increasing acceptance in projects,
establishing democratic involvement, and improving
the environmental decision-making process and its
outcome [5].
Principally, participation processes are highly
influenced by prior experience with participation,
cultural, institutional contexts [18]. According to thespecific and dynamic context of governance in Thai
society, public participation techniques should be
carefully considered to be properly applied in thisspecific context. There is no consensus on a format
for public participation. Different methods are
particularly favored and suitable in different
contexts and vary in their purposes which should be
judged on how well they fulfill a particular purpose.
This research recommends that, in practice, acombination of participation methods could be more
fruitful that an application of only one specifictechnique for the reason that different public
participation techniques can complement the limitsof other(s). These participation mechanisms should
be multiple and rigorously applied case by case in

Resolving conflict
Conflicts of the Khao Hin Son case were serious
which mainly resulted from a lack of public
participation. Evidently, the public was excluded
from the decision from the beginning, so they
thought the project was not transparent and did not
accept it. The public tried to make their voices heard
but they were overlooked. Later, although there had
been an attempt to resolve conflicts between theprotestors and the developer, it proved to be too late.
For example, the public hearing’s function was often
to communicate prior decisions to the attendees
rather than to foster discussion and problem solving
to reach consensus. The developers and the officers
claimed that they tried their best to resolve theconflict while the villagers viewed that they were
not willing to do so. These conflicts were toocomplicated and difficult to handle.
Similar finding was found in other studies thatdifferent stakeholders looked for different tactics toachieve their own concerns and interests. This pointis hard to handle it since it was very difficult to459

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

order to achieve the effectiveness of public
participation.
It could be implied that effective public
participation is not a single event, but a carefully
designed and planned process that applies a
multiplicity of techniques suited to the situations,contexts and the communities involved. To achieveit, it is very important to plan and execute theprocess very carefully, allowing adequate time andresources [19]. The participation issues need to beclearly framed and communicated before theprocesses are commenced. The sessions should be
employed in two-way communication and sufficient
information should be exchanged.
If the development projects are to be effectively
implemented, and the potential to resolve conflicts
from their implementation succeed, the public must
be appropriately involved in the decision-making
process. Public participation is an effective
mechanism for conflict resolution since the public’s
cooperation is fundamental to the successful
implementation of any development projects. A full
involvement of the public in the decision-making
process make the consideration of the project more
efficient and effective than would otherwise would
be the case.
Finally,various assumptions discussed
previously in this study could lead to a conclusionthat public participation is the pre-eminent approachto achieve a balance desired between stakeholders
fromdevelopment
projectsorpolicyimplementation. By providing public participationfrom the beginning through until the end of theprocess, it could: reduce strong opposition since thepublic could be involved before the decision has
been made; resolve conflict and lessen anger fromthe public; and, enhance the trust and credibility of
the authority or developer.

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USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

ACHIEVING WATER SENSITIVE CITY CONCEPT THROUGH
MUSRENBANG MECHANISM IN SURABAYA CITY,INDONESIA
1,3,4

Eddy Setiadi Soedjono1, Nurina Fitriani2, Rifda Rahman3, I Made Wahyu Wijaya4
Faculty of Civil Engineering and Planning, InstitutTeknologiSepuluhNopember, Indonesia;
2
Faculty of Science and Technology, UniversitasAirlangga, Indonesia

ABSTRACT
Water sensitive city is a very important issue for development of future cities. Water sensitiveis a kind way of live for all communities in the city. Cities with low level of environment awarenesswould be difficult to implement the issue of water sensitive city. The aim of this study is to access how
water sensitive city would be implemented in Surabaya. Observations and surveys using focus group
discussion (FGD) and in-depth interview (IDI) were conducted to get real information for eachmusrenbang from kelurahan level, up to kecamatan and city level. The concept of water sensitive city
is likely to be possible to be implemented in Surabaya. It is, however, not easy to be implemented as
human basic needs are not discussed during musrenbang yet as an indicator to further discuss the issueof water sensitive city.
Keywords: communities,e-musrenbang, water sensitive city

INTRODUCTION
Increase of urban water demand forceswater stakeholders like government, academia,
and communities to change their live
especially towards water. One of the modified
system has been introduced in the concept ofwater sensitive city which may change a city,
give best practice to manage water, improve
environment and its relevant institutions(Brown et al., 2008). In the context of water
sensitive city, a city must be resilient, liveable,
productive, and sustainable. The resilientsystem consists of: (1) number of disturbancethat can be absorbed and still remain at samestate, (2) degree of capability to selforganisation, (3) degree of capability andcapacity to learnand adapt (Folke, 2006).
Resiliency of system to disturbance in theenvironment was well understood and basedon the approraches, the ‘hydro-social contract’
was found (Lundqvist et al., 2001). The termof the concept is used to describe thepervading values and often implicit agreements
between communities, governments, andbusiness on how water should be managed.
According to Brown et al. (2009), steps totransform to a water sensitive city were
initiated from a city which could manage its
own water supply system as called watersupply city. Then it would moved forward
subsequently to sewerage city, drainage city,then waterways city before becoming to awater sensitive city. The steps were not fixed
but leap frogging was a leap from whicheverstep to become a water sensitive city. There arethree main supports to come to a water
sensitive city, i.e: stock of water, proper
ecosystem, and community involvement(Wong dan Brown, 2009).
Water management in Indonesia has
already been strongly supported by thegovernment, communities, and academia(Moerwanto, 2011). Water governance isbasically using a top-down approach wherewater policy from the central government must
be implemented for the benefit of all citizens
and communties via provincial and municipal
government, in this case Jawa Timur Provinceand Surabaya City. Even within the city level,
it goes down to Kecamatan (sub-district),
Kelurahan (village-like), Rukun Warga (RW;
community-like), and Rukun Tetangga (RT;neighborhood-like) level (Soedjono et al,2017). Different level of government boards
and institutions which regulates water in thisstudy are Jasa Tirta (central government),
Dinas PU Pengairan (provincial government),
BAPPEKO, Dinas PUBMP, Dinas LH,
DKRTH, and PDAM (municipal government).
In Indonesia, however, water governance may
also introduced using a bottom-up approach
where water related program could be
proposed from the communities to the462

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

municipal, provincial, and central governmentas called MUSRENBANG (Musyawarah
Perencanaan Pembangunan). Musrenbang
would result a annual work plan of city andprovince (RKPD) as the mandate from RPJMD(soedjono et al, 2017, UU 25/2004, PP
23/2014, and Permendagri 54/2010).
Study on Musrenbang in Jawa Timur
Province like in Probolinggo District showedthat water and sanitation was not strongly
discussed during Musrenbang (Rahman andSoedjono, 2016). Musrenbang at the level ofvillage/kelurahan,kecamatan,
district,province, and even at the level of national level
mainly discuss about infrasturctures like road,rain drainage, and other public facilities. Somemunicipalities in Jawa Timur Province like
Bojonegoro District, however, has discussed
water and sanitation in its musrenbang. With
all background has been mentioned before, theaim of this research is to access how water
sensitive city concept can be introduced in themusrenbang (using bottom-up approach) at
different level in Surabaya City: kelurahan,kecamatan, and municipal level.

RESULTS AND DISCUSSIONAs regulated by Regulation of Ministry ofHome Affairs no. 54/2010 regarding
Musrenbang then musrenbang is started from
Kelurahan level, then it is continued tomusrenbang in sub-ditrict, city, province, andeven at national level. The following
musrenbangs are to describe Musrenbang at
KelurahanKenjeran,MusrenbangatKecamatan Bulak and Semampir, Musrenbang
at Surabaya City, and even Musrenbang at
Jawa Timur Province.
MUSRENBANG at Kelurahan Kenjeran
Musrenbang in Surabaya started at RW
level which all proposals could be inputed
onlinethrougha
websiteofbapeko.surabaya.go.id/musrenbang2017. Each
RW in Surabaya was given user id andpassword to log into the website. Surabaya
government called this system as eMusrenbang. RW was not only entitled to
input any next year program into the website,
but was also entitled to give any comments andcritics to the city government (Putri, 2015).
Such system would ease the interaction
between communities and the city government.
Input from RW definitely would accomodate
input from its RT. With this system then any
input from RT, RW, Kelurahan, and finallyfrom kecamatan could be easily known by thecity government. In the system, however, RW
was only allowed to select proposal whichwere already given in the website; not any
proposal could be accomodated in the website.
Each RW was only allowed to propose 2
proposal with 1 reserved proposal toaccomadate future adjustment due to program
priority of the city.
Kelurahan Government was entitled toedit all input from RWs during the KelurahanMusrenbang. That was why the RW speakers
should be properly selected to clarify any
priority within its RW. Website of RW and
Kelurahan was definitely different as
Kelurahan regulated all its RWs. Besides,
Kelurahan had a fixed budget from the city
government for local development using topdown approach. Results of bottom-up
approach of Musrenbang were called
development priorities of kelurahan for next
year program. This top-down must meet thebottom-up approach during Musrenbang.
Development priorities within Kelurahan werethen submitted to Kecamatan through thewebsite as well.

METHODS
Primary data were collected through indepth interview (IDI) and focus group
discussion (FGD). The respondents werecommon people and representatives from local
government officers which conducted theMusrenbang in the kelurahan, kecamatan, andmunicipal level. Secondary data collections
were mainly information regarding relevant
regulations from the central government level
like Indonesia Law or UURI down tokelurahan regulations. Then resuts ofsecondary data was compared with the primarydata. The comparasions were used to improvethecurrent
regulations,especialy
improvements towards water resource
management to achieve water sensitive city
conditions. As Musrenbang Kelurahan was
conducted simultaneously for all kelurahan in
Surabaya, then Kelurahan Kenjeran was
selected to join the MUSRENBANG in
January 2017. Within kecamatan level, thenKecamatan Bulak and Kecamatan Semampir
were selected for the Musrenbang andeventually it was the Musrenbang at the citylevel.

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MUSRENBANG at Kecamatan Bulak andSemampir

Within the city level then BAPPEKO was
the one incharge to collect all online input
from each kecamatan at Surabaya City. City
Musrenbang was usually opened by the mayor
which invited all the kecamatan representatives
and other relevants invitations like NGO,
academia, industries, etc. BAPPEKO and any
agencies within the city would have their own
meeting to determine which priorities wereselected and surveyed. Each agency basically
had its own program priorities and budged(top-down approach) which should be inline
with musrenbang bottom-up approach. Whendecisions were taken, the the rejected
proposals had to be infomed back to thekecamatan and kelurahan via the website as
well. This kind of e-musrenbang was claimedby the city government to give better public
service and transparancy.
As there were different musrenbang levels
like kelurahan, kecamatan, municipalities,
provinces, and national level, the kelurahan
musrenbang was the most important moment
to discuss the issue of water sensitive city. As
musrenbang kelurahan was opened byrepresentative from kecamatan as also amoment to inform any top-down program fromthe central government, issueing water
sensitive sensitive city would be a hugechallenge. With the assumption that water
sensitive city (WSC) is already the national
program, WSC could not only be implemented
through opening ceremony during kelurahan
musrencang, but would be more like way ofliving. Isueing this during musrenbang opening,
however, was also important for next or future
develpment program. There should be otherprogram from the city government to introduce
water sensitive program via other institutes toinform basic human needs especially any
related issues of water to bring this discussion
at kelurahan musrenbang. Water sensitive
issues had to be discussed during premusrenbang at RW level in Surabaya.
Musrenbang had to be attended by women
representatives in order to bring important
issues regarding basic human needs like health,environement, water, and sanitation.
Summary of musrenbang in eachgovernment level is shown in Table 2.

As Kelurahan Kenjeran is located at
Kecamatan
Bulak,
then
KecamatanMusrenbang was at Bulak as well as Semampir.
The condition of Bulak Musrenbang wasbasically typical at any other KecamatanMusrenbang
inSurabaya.
Kelurahan
representatives had to attend the musrenbang
at kecamatan level. Each kecamatan in
Surabaya had its own website as well to submit
its musrenbang development priorities to thecity of Surabaya online. All priorities andreserved proposal from each kelurahan were
evaluated together during Musrenbang
kecamatan. Some priorities were definitely
agreed while some others were rejected. Some
reserved proposal could be accomodated as
this reserved became priorities at several otherkelurahans. All the agreed proposals would
later surveyed by relevant cities agencies(SKPD) to be executed next year.
Probably the biggest challenge within
Kecamatan Musrenbang was the littlenumberof participants. Even the quality of participantsin term of discussing and debating to goal
priority development in each kelurahan was
not strong. Hence the Musrenbang seemed akind of forum to conclude decision without
strong arguments. Example of musrenbang
participations is shown in Table 1 at
Kecamatan Semampir in the last two years(Azhar, 2015).
Tabel 1 Musrenbang participants at Kecamatan
Semampir
Kelurahan

Numberof RW

Pegirian

11

Ujung

14

Wonokusumo

16

Ampel

17

Sidotopo

12

2014

2015

22
persons27
persons39
persons34
persons29
persons23
persons29
persons32
persons37
persons33
persons

According to PTPM (2006), RW
representatives would be 3 persons (one would
be woman) or 5 persons (2 would be women).
Based on Table 1, it showed that the total
participants in each Kelurahan were less thanideal. This was not to discuss the capacity of
the representatives and gender represenative.
MUSRENBANG at Surabaya City

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

Table 2. Summary of Musrenbang
Musrenbang

Results

Kelurahan Input from RT and RW
to online system.
 Top-down meets thebottom-up approach
during Musrenbang.
 The kelurahan
musrenbang is the mostimportant moment todiscuss the issue of water
sensitive city.

Kecamatan

 Each sub-district inSurabaya had its own
website to submit its
musrenbang
development priorities tothe city of Surabaya
online.
 RW representatives
would be 3 persons (onewould be woman) or 5
persons (2 would be
women).

City

 City Musrenbang is
usually opened by themayor which invites all
the kecamatan
representatives.
 BAPPEKO and any
agencies within the city
have their own meeting
to determine whichpriorities to be selected
and surveyed.

mm/year. Although the issue of water supply,
wastewater, and drainage is the issue of city
centred, but the raw water supply of Surabaya
is coming from its neighboors regencies. Thisis obvious that the issue of water sensitive city
is so important for Surabaya. This issue mustbe raised to the provincial musrenbang of Jawa
Timur; eventhough the issue of water in
Surabaya was already mentioned in theregional planning of the Province.
Water sensitive
MUSRENBANG

city

concept

throughMusrenbang is a forum to discussdevelpment priorities in a bottom-up approachin Indonesia development system. As it is abottom-up approach, then the priorities isstarted from the lowest of government level up
to the highest. Within Surabaya City, then it
started from the Kelurahan Government, whichthen to be continued to Sub-district, city, andeventually to provincial level of Jawa Timur
Province.
Within this water sensitive city concept,
then the top-down approach was not discussed
as it was assumed that the government fromthe national to local level was alreadyunderstood the concept of water sensitive city
as it could be assumed that water sensitive city
was already become the policy of thegovernment, at least at Surabaya City
Government. The crucial thing was then how
water sensitive city became the topic ofdiscussion at musrenbang kelurahan in
Surabaya.
Musrenbang
resultswouldthedevelopment plan for next year. Next year
development priorities should be obtained
from the current year of Musrenbang. Hencethe representatives of Musrenbang Kelurahan
were very crusial. According to Soedjono et al(2017) and PTPM (2006), musrenbang had to
be attended by women representatives in order
to discuss at least human rights needs likeeducatiion, health, and water-sanitation. Men
representative would create men dominatedforum which discussed man’s local
development world like development of roads,
irrigation facilities, and other infrastructures
rather than to discuss human right needs. This
is to say that to discuss water sensitive city inMusrenbang Kelurahan is likely possible aslong as the representatives raise the issue.
Again, this is to say that water sensitive city
concept must relates to daily activities ofcommunities. The concept of water sensitive
city is not merely knowledge; it must be
attitude and way of live of communities. Thenthe main issue would be how to bring the issue

MUSRENBANG at Jawa Timur Province
Provincial musrenbang is basically tocontinue the musrenbang results frommunicipalities in Jawa Timur. The musrenbang
is also online. This musrenbang level is so
important when there is develpment priorities
which is cross border among municipalities.
As water related issue is always cross border ininland area like Surabaya City and its
neighboor regencies, then the issue of water
sensitive cities become crusial, especially inthe condition where surabaya water is comingfrom its neighboors regencies. Water security
is becoming a crusial issue for city like
Surabaya with about 3 millions population atarea of 330 km2 with rain intensity of 2200

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of water sensitive city to be widely well knownby public.

[4] Folke, C. 2006. Resilience: the emergenceofaperspectiveforsocialecologicalsystem analysis. Glob. Environ.
Change, 16 (3), pp: 253-267.
[5] Http://bapekko.surabaya.go.id/musrenban
g 2017.
[6] Lundqvist, J., Turton, A., and Narain, S.
2001. Social, institutional, and regulatory
issues. In: Maksimovic, C. and TejadaGulbert, J.A. frontiers in urban water
management: deadlock or hope. IWA
Publishing, London, pp: 344-398.
[7] Peraturan Menteri Dalam Negeri Nomor
54 Tahun 2010 tentang Tahapan, Tata
Cara Penyusunan, Pengendalian dan
Evaluasi
Pelaksanaan
Rencana
Pembangunan Daerah.
[8] Petunjuk
TeknisPenyelenggaraan
Musrenbang (PTPM) Tahun 2006
[9] Putri, N., P. 2015. Studi Eksplorasi
Tentang
VariabelPendukung
Keberhasilan
AplikasiSistem
EMusrenbang di Bappeko Surabaya.
Kebijakan dan Manajemen Pubik, 3 (3),pp: 109-122.
[10] Rahman, R. and Soedjono, E. S. 2016.
Study on achieving sanitation governancethrough musrenbang mechanism inprobolinggo city. Joint workshop global
engineer in asia. 25-30 July 2016, King
Mongkuts University of Technology
Thonbur, Bangkok, Thailand.
[11] Soedjono, E., Rahman, R., Wijaya, W.,
Fitriani, N., 2017. Study on Musrenbang
Mevhanism to Promote Sanitation.
Environmental Engineering Department,
Institut Teknologi Sepuluh Nopember,
Surabaya (unpublished)[12] Undang-undang Nomor 25 Tahun 2004
tentang Sistem Perencanaan Pembangunan
Nasional.
[13] Undang-undang Nomor 23 Tahun 2014
tentang Pemerintahan Daerah.
[14] Moerwanto, A. S., 2011. Strategi
Penelitian dan Pengembangan Sumber
Daya Air dalam mendukung Pengelolaan
Sumber Daya Air berkelanjutan. Pusat
Litbang Sumber Daya Air, Badan
Penelitian dan Pengembangan Kementrian
Pekerjaan Umum.
[15] Wong, T.H.F., and Brown, R.R. 2009. The
water sensitive city: principle for practice.
Water science & technology-WST, 60 (3),pp: 673-682.

CONCLUSIONS
Musrenbang kelurahan was a coordination
forum basically between the Government as
represented by the Kelurahan Government andthe communities. On one hand, theGovernment was mainly using a top-down
approach to implement its development targets.
The communities, on the other hand, proposeddevelopment priorities they need in a bottomup approach. As it was assumed that theconcept of water sensitive city was alreadyunderstood by the government from the central
down to the kelurahan level, then thecommunity representatives who attended themusrenbang kelurahan were very crusial tocome to a water sensitive city discussion.
These representatives had to understand wellabout the water sensitive city. This would be
far beyond ideal as the representatives in the
beginning were not women representation. It
was a male dominated forum while basic
human right were not discussed. Then theconcept water sensitive city would not be
discussed in the musrenbang forum. The
concept of water sensitive city to be discussed
in the musrenbang forum, however, waspossible as long as the proposal from thecommunties must propose anything related towater sensitive city. This to say that thecommunities must fully understand the conceptof water sensitive city. Water sensitive is notenough to be only taught as concept, it must be
attitude of communites on their daily live tobring the city robust for water related issues.

REFERENCES[1] Azhar, F. 2015. Partisipasi masyarakat
dalammusyawarah
perencanaan
pembangunan (musrenbang) di Kelurahan
Pegirian Kecamatan Semampir Kota
Surabaya. Kebijakan dan Manajemen
Pubik, 3 (2), pp: 63-70.
[2] Brown, R., Keath, N., Wong, T. 2008.
Transitioning to water sensitive cities:
historical, current, and future transition
states. 11th international conference on
urban drainage, Edinburgh, Scotland, UK.
[3] Brown, R., Keath, N., and Wong, T. 2009.
Urban water management in cities:
historical, current, and future regimes.
Water sciences & technology, 59, pp: 847855.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THE STUDY ON MITIGATION METHOD OF BEACH EROSIONUSING THE CORAL CELLS
Sang Kil Park1, Hong Bum Park2, Kyeong Mo Lim3
1

Department of Civil Engineering Pusan National University, 2Busan Metro-City Hall
ABSTRACT

Recently, an artificial submerged breakwater method has been installing to prevent the loss of shoreline ateverywhere. Artificial submerged breakwater is made to minimize the loss of sand nourishment of beach erosion.
For this reason, submerged breakwater has been indiscriminately constructed that is planned throughout thecountry. Despite of its purpose to keep the shoreline of the beach, it has a quite a few problems. In addition, thepurpose of utilizing the space of the marine leisure users does not like that because of the disconnection of thesea using sea space. Therefore, in this study, we propose to develop a economical method of Coral cell modelthat can mitigate degree rate of beach erosion and improve costal environments without installing the submerged
breakwater for the maintenance. In the one-dimensional topography variations, hydraulic model experiments bymeasurement of residual rate of nourishment sand and water quality, it demonstrated the effectiveness of
prevention of loss of nourishment sand and improvement of water quality.
Keywords: Nourishment Sand, Water Quality, Mitigation of Beach Erosion, Residual Rate of Nourishment Sand,
Coral-cell Modelout to the deep water until 8 hours, but after 8 hours
the sea bottom topography was very stable. We
defined the residual rate of nourishment sand as theamount of nourishment sand remaining in a certain
space divided by the total amount of sand. Therefore,
the purpose of this study is to propose a Coral cellmethod to prevent coastal erosion without installing asubmerged breakwater for maintenance of thebeaches.

INTRODUCTION
Coastal erosion due to climate change is one of
the world's worst disasters. In order to prevent this,
we are indiscriminately installing submerged
breakwater, ignoring use and environment of thecoast. In Korea, a plan to minimize the erosion ofshoreline was implemented by conducting artificial
nourishment on the coast. At the center of thesubmerged breakwater, the deposition occurs, incontrast, both ends erode. This phenomenon causes
the shoreline to be cusped, which not only provides
inconvenience to the visitors, but also generates
strong rip current and causes safety accidents. Since
access is prohibited to small boats and surfing users,
it is inadequate for marine recreational facilities. We
want to prevent the erosion of the designatedGwangan beaches at Busan City South Korea andutilize the sea level space as a space for marine
leisure. In short speaking, we are trying to prevent
erosion by installing Coral cells on the erosion coasts.
This method is to capture the nourishment sand with
the Coral cells pockets and retain the nourishment
sand in the pockets. The field installation method is
to install Coral cells of a certain size on a wide andlong underwater sea bottom. Two dimension
hydraulic experiments were carried out to investigate
the effects of wave damping and prevention of sandoutflow. Coral cells weakened the rip current andreduced the loss of nourishment sand. We directly
measured the movement of the sand by continuous
wave action for 20 hours. Nourishment sands flowed

HYDRAULIC EXPERIMENT
Fixed Bed Hydraulic Experiment
In order to carry out the two dimension hydraulicmodel experiment, we used the regular and irregularwave generation tank in the coastal laboratory of the
Civil Engineering Department at Pusan National
University. Fig. 1 is simple illustration of a water
wave tank and a wave device. The specification of
the wave tank is shown in Fig. 1, the length is 22.5m,
height is 1.0m, width is 0.6m. Fig. 1 is the positionof the wave gauge after installing the Coral cell. The
wave height was measured at the required point toobserve the effect of the wave reduction. Fig.1’s 5thwave gauge is the point where the incident wave ismeasured, 7th wave gauge measured wave time series
at nature slope where the Coral cell is not installed,
and 8th wave gauge measured wave time series at theslope where the Coral cell is installed. Furthermore.
the 7th and 8th wave gauges measured wave timeseries in which incident waves and reflected waves
467

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

are synthesized at the same depth. In order to checkthe wave attenuation state caused by the Coral cell,
we observed wave series at slope behind the Coralcell. The size of the Coral cell used in the movable
bed hydraulic experiments (the size of the lower sandcapture and the upper wave damp device of the Coralcell) is 3 cm pocket cell (Pocket cell) and 3 cm ripple
cell that forms complex structure. The shape of theCoral cell is circular type with a height of 6cm and awidth of 3cm.

purpose of Cases1 was to perform a hydraulicexperiment to test the pocket function of Coral cell.
In this case, the topographic variation is summarized
as a photograph, and the capture function of the
topographic variation for the Coral cell is confirmedin the hydraulic experiment. The purpose of Cases 2
is to compare and analyze the topographic variability
for Coral cell installation and without installation.
Bottom topography of variation elapsed time wasmeasured at intervals of 4 hours. We tried to verify
the two functions of the Coral cell, the capture rate
and the sea bottom profile rate. Table 1 summarizes
the conditions of the mobile bed hydraulicexperiment.

Manufacture of Subsea Bottom Slope
Sea bottom slope without Coral cell wasconstructed by setting natural beaches with 1/10
slope. The subsea bottom slope with Coral cell was
produced as an 1/10 erosion type of artificial subsea
bottom slope. The natural bottom slope without Coralcell was made of standard grain size sand and thedepth of the sandy beaches was made from 15cm to26cm deep. Of course, a 60cm water tank was
separated by an acrylic plate, 29 cm and 29 cm, inthe same way as the fixed bed. The natural erosion
coast was made on the glass surface, and Coral cell
was installed at the center of the sea bottom slope ofinside the glass surface Both beaches wereconstructed to allow erosion of the shoreline byincident waves.
Irregular Waves of Time Series Group
The time series of irregular wave used in themobile bed experiment is as same as the time series
analyzed in fixed bed model. The incident wave
height is the 14cm of significant wave height, theperiod of wave is 0.98 sec of significant waves
period, and the wave steepness is 0.093.
In mobile bed experiments, we examined the
topography of beaches elapsed time by using
irregular waves. In order to verify the occurrence ofthe sand bars of beaches, Nayak
was used as an evaluation criterion of erosion anddeposit.[1] Iwatani and Noda 's sand bar occurrence
limit formula was used as an evaluation criterion forsandy beaches, and this coastal sandy beach belongs
to Johnson' s storm beach.[2][3] The purpose of themobile bed experiment is to change the erosion coast
to deposit coast. In other words, the nourishment
sand did not flow into the deep sea by Coral cell but
was collected in the pocket of Coral cell. In thisexperiment, we can see that the erosion coastchanges to a stable coast. This phenomenon isthought to be the result of wave height attenuation by
Coral cells in the fixed bed experiment. Experimental
progress of the mobile bed experiment is to verify thevariation of topography according to elapsed time. In
the mobile bed experiment, we focused on thevariation of topography of sea bottom rather than thetrend of the wave experiment. The experimental

Fig. 1 Hydraulic experiment device

Table 1 Condition of mobile bed experiment
Case

Case1

Case2

Coral
cell
6cm
pocket6cm
ripple3cm
pocket3cm
rippleMeasuringTime
Every 2 hours
total 8 hours
Every 4 hours(total 20 hours
passed)Observation

H.W.L.
Height ofsand

Model of Topographic Bed and Coral cell
Installation
As mentioned above, table 1 shows theconditions of the mobile bed hydraulic experiment,
and Case 1 and Case 2 have clearly different
purpose for the mobile bed hydraulic experiment.
For Case 2, we decided to measure the topography

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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017variation and the nourishment sand of capture rateaccording to the elapsed time of hydraulicexperiment. The purpose of estimating the capture
rate is that nourishment sand does not flow into thedeep sea by Coral cell but remains in the pocket tomaintain stable beach of topography. Generally, thewave height is not measured in a two-dimensional
mobile bed hydraulic model test. The geometricscale ratio was 1/20. Scale 1/20 is widely used forhydraulic model tests to show the reproducibility of
the wave and sea bottom of topography variation.
Fig. 2’s (a) shows a natural beach with a constantsea bottom slope for stabilization, and (b) shows a
Coral cell type installed on an eroded beach toprevent erosion. Of course, fig. 2 present thebeaches made of hybrid type of Coral cell with a
3cm pocket and 3cm ripple. Fig. 3 is figure of theCoral cell with a nourishment sand capture and awave attenuator. In this figure, the direction of thearrow indicates the direction of incident wave andthe main direction of nourishment sand out flow.
Fig. 3’s (a) is a 30mm pocket type, (b) is ahybrid type of 30mm pocket and 30 mm ripple.
The pocket is designed to have an elliptical shape,
and the ripple is designed to have a half ellipticalshape. The largest 120mm pocket type and ripple
type is actually designed to have a wave damping
effect and a nourishment sand capture type. The
pocket is designed to have an elliptical shape, andthe ripple is designed to have a half elliptical shape.
Coral cell was made in the petrochemical productsthat are not harmful to the environment. To behonest, the larger the Coral cell of the pocket andripple, the greater the wave reduction and thenourishment sand of capture rate.

(b) Coral cell shape installed on erosion beachFig. 2 Beach with 3cm pocket and 3cm ripple ofCoral cell(a) 3cm pocket cell(b)3cm pocket and 3cm ripple cellFig. 3 Examples for cross-section of Coral cell

EXPERIMENT ANALYSIS
Situation of Nourishment Sand Movement by
Coral cell(a) Unstable beach form before coral cell
installation

The mobile bed experiments were carried out tounderstand the movement of the nourishment sandin accordance with the elapsed time of the wave.
Figure 4 shows the movement of the nourishment
sand along with the elapsed time of wave after
installing the Coral cell. In other words, we can seethat nourishment sand is flowing into the Coral cell
pocket and deposited. Fig. 4 shows the state in469

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

which the Coral cell is buried by the movement of
the sand. This phenomenon shows that thenourishment sand flows into the pocket of Coralcell and accumulates as the shoreline erode. The
red line is the topography of original sea bottom.

Fig. 4hours. The yellow line is nourishment sand surface
after elapsed time of 12 hours, the blue line is thenourishment sand surface after elapsed time of 16hours, and the pale purple line shows nourishment
sand surface after elapsed time of 20 hours. In thispicture, we can see three phenomena. Firstly, theinstallation of Coral cell can prevent thenourishment sand loss more than a certain value.
Secondly, the nourishment sand on the steep slope
can be collected in Coral cell to increase theresidual rate, the sand that flows into the deep sea
area flows into the pocket of Coral cell again and isdeposited from the deep water depth of the Coralcell. Thirdly, the nourishment sand that flows out
into the deep water area flows back into the Coralcell and accumulates from the deepest point.

View of bottom variation with Coral cell

Table 2 Wave condition for Pocket 3cm and ripple 3cm
Coral cell
Maximum wave
heightSignificant wave
height

deep
sea

no
cell

with
cell

deep
sea

no
cell

with
cell

4

26.4

7.2

6.5

14.6

4.3

4.1

8

26.8

7.5

7.0

15.7

4.5

4.3

12

19.0

5.6

5.0

15.7

5.3

4.3

16

26.9

7.2

6.9

15.4

4.5

4.0

20

25.8

7.0

6.8

14.7

4.8

4.0

Mean

25.0

6.9

6.4

15.2

4.7

4.2

Elapsetime(hours)Fig. 5View of bottom variation by elapsed time

Change of Sea Bottom Topography by Coral cell

Outflow Nourishment Sand Volume and Residual
Amount by Coral cellFig. 5 shows the sea bottom topography ofvariation according to elapsed time of wave action.
The vertical axis is depth of the sand as unit of mm,
and the horizontal axis is the length of location ateach point as unit of which is indicating the changeof water depth. In the figure, the upper side of
600mm is the point with the Coral cell and thelower side between 0mm ~ 600mm is the point
without the installation of Coral cell. The thinblack lines is subsea fixed slope, the red line is thesand depth of the initial sea bottom topography.
The black line is the nourishment sand surface after
elapsed time of 4 hours, the green line is thenourishment sand surface after elapsed time of 8

Fig. 5 is a figure for calculating the out flow andresidual amount of nourishment sand. In order tocalculate the amount of sand discharged into the deepsea, we assume that the cross-sectional shape of sandis triangular and rectangular. After calculating thecross-sectional area of the side surface in theseshapes, the total nourishment sand volume wascalculated by multiplying the width. Comparing theobtained values and the measured sand amount, it
corresponded up to 95%. Table 3 and Table 4summarize the residual amount or capture amountand outflow rate.
Table 3 Movement volume of nourishment sand before

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

Coral cell of installation accord to each depth
Elapse time for wave
generation(minute)

Category
240

480

720

960

1200

Erosionquantity of
beach

121.8

132.0

166.0

183.3

208.8

Sediment
quantity oftransition

102.5

111.4

101.2

122.4

139.2

Outflowquantity
at deep sea

19.3

20.6

34.8

60.9

69.6

caught in Coral cell. In this case, the residual rate andthe capture rate were defined to be the same mean.
We found that installing the Coral cells can reliably
capture the nourishment sand that flows into the deep
water. Therefore, the total amount of sand outflow
which eroded by the wave, the elapsed time ,and the amount of deep water outflow
were
calculated by following equation (1).

(1)

The amount of sand outflow rate and residual rateis illustrated form Fig.6 to Fig.10. Fig.6 shows theoutflow of nourishment sand along the depth
before the Coral cell installation

Table 4 Movement volume of nourishment sand after
Coralcell of installation accord to each depth
Elapsed time for wave
generation(minute)
Category
240
480
720
960
1200
Erosionquantity of
Case
Sediment
quantity oftransitionzone
Outflowquantity
at deep sea

37.6

39.4

46.4

52.2

57.9

33.5

32.2

37.0

39.9

43.4

4.1

7.3

9.4

12.3

14.5

Outflow Rate and Residual Rate by Coral cellFig. 6 Nourishment sand outflow amount withwater depth before Coral cell installation
In this figure, we can see that the outflow ofnourishment sand is very serious on the natural
coast. Outflow phenomenon of nourishment sandis most severe in the surf zone.

As a result, the residual amount of nourishment
sand was summarized as shown in Table 5.
Table 5 Residual amount of natural beach with Coral cell

Category

Elapse time(minutes)
240

480

720

960

1200

Erosionquantity
121.8 132.0 136.0 183.3 208.8
without
Erosionquantity
4.1
7.3
9.4
12.3
14.5
with cell
Outflow
3.3
5.5
6.9
6.7
6.9
rate
Residual
96.7
94.5
93.1
93.3
93.1
rate
By installing coral cell, most of nourishment sand isFig. 7 Outflow quantity after installation of Coral cell

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

Fig. 7 shows the nourishment sand amount after
coral cell installation. In this figure, we found that if
the coral cell was installed on the sea bottom slope,the outflow amount would be very small. That is tosay, Coral cells have a great effect of preventing
outflow of nourishment sand.

Fig. 10

Residual rate of sand under Coral cellFig. 9 shows the residual rate of nourishment
sand for before and after the installation of Coral cellby equation (1). The residual rate in the transition
depth is much larger than the residual rate in the deep
water.
CONCLUSION

Fig. 8 Outflow difference between before and after
Coral cell at deep water

It is a very difficult task to stabilize the coast byconducting nourishment sand on the erosive natural
beach. The purpose of this study is to investigate themaintenance strategies to enlarge availability for
artificial nourishment sand in Gwanganri beach in
Busan, South Korea. In other words, this research
proposed an erosion prevention method using Coralcell as a customized method. As a results of the twodimensional hydraulic experimental model, thismethod was able to raise the residual rate ofnourishment sand up to 70%. It is highly expected tohave an economic value since its high residual rate.

Fig. 8 compares with outflow quantity of thenourishment sand for before and after the installationof the Coral cell accord to elapsed time at deep water.
The tendency of the nourishment sand outflow islarger as the elapsed time of the wave becomes
longer.
Fig. 9 shows the residual amount of nourishment
sand for before and after the installation of Coral cellby equation (1). The residual amount of nourishment
sand is increasing as the wave action elapsed time
becomes longer.
Therefore, in this figure, we can say that
installing a Coral cell is much more efficient than notinstalling it.

ACKNOWLEDGEMENT
This researches was supported by research fundof P.N.U. Small Business Incubator Center, Han
Ocean Co.,Ltd and Green Land & Water
Management Research Institute.

REFFERENCE[1] Nayak IV, “Equilibrium profiles of model
beaches”, Proc. 12th Int. Conf. on Coastal Eng.,
1971 pp. 1321-1339.
[2] Noda H, “Initial movement of sea bottom sandinception and generation sand ripples due towaves”, Proc. 11th Conf. on Coastal Eng. inJapan, 1964, pp. 135-141.
[3] Iwagaki Y, “Laboratory study of scale effects in
two dimensional beach process”, Proc. 8th Int.
Conf. on Coastal Eng., 1963, pp. 194-210.

Fig. 9 Residual quantity of nourishment sand Coralcell for before and after installation

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051
Review_Results-SEE-2017.zip

THE DESCRIPTION OF LIGHTING ENVIRONMENTAL ON THE
URBAN STREET

1

Shuto Takeuchi1, Kazunari Tanaka2 and Shin Yoshikawa3
Engineering, Osaka Institute of Technology, Japan; 2 Osaka Institute of Technology, Japan

ABSTRACTThe purpose of this study is to visualize spatial illuminance for the street space at night. In the street space, it isnecessary to consider the illumination effect in three dimensions, such as the direction and size of the light, as
well as brightness and luminance of the surface. For example, depending on the brightness of the pedestrian’sfeet, chest, face, or the difference in the height of the light source, it is conceivable that the place or movement ofpeople walking will affect the lighting. By grasping the characteristics of the light environment of each street, it
is possible to confirm the role and function of the street. Furthermore, this information can be used to support thelighting design for streets at night-time. When designing a city, we should consider not only the implications forday-time, but also night-time. I will analyze the lighting environment of the street space utilizing threedimension representation visuals from various angles.
Keywords: Lightning Environmental, Urban Street, Calculation Method, Flat Surface Sourcesthought that the lighting gives each street uniquecharacteristics at night. In this research, attention is
focused on the features of such streets, collection ofbasic data for surveying and analysis, andexplanation of the results.

INTRODUCTION
In Japan, the landscape law was enforced in 2004
to preserve, protect and create unique landscapes.
Furthermore, night-time street lighting forpedestrians has increased, this includes the distanceof streetlights by the number of pedestrians and soft
light sources such as sodium lamps, and lighting for
traffic direction has increased.
The influence of the light environment onpedestrian behavior and psychology in the nighttime outdoor space is considerable. Various kinds ofoutdoor light exists such as; light for safety purposes
to brighten a road like a street lamps, lights forvisual purposes such as outdoor advertisements orsigns, and indirect light leaking from building
interiors etc.
Illuminating light which is effectively applied toan object such as light up is considered as anelement for creating a nighttime landscape. For
outdoor light, various kinds of light such as light forsafety to brighten a road like a streetlight, light formaking visually conspicuous such as an outdoor
advertisement, light leaking from the indoor space
exists. In addition, the light which is lit foradvertisement such as a signboard light is being
considered as a viewpoint of how easily it isperceived and as a factor interfering with a calm
landscape.
In the commercial areas, stores and shops havetheir own unique designs to attract customers.
Interior lighting is important because it is inviting
and welcoming for potential customers to enter thebuilding; signage also gives visual appeal. It is

PURPOSEIn this research, we aim to grasp the lighting
environment in urban spaces and to concretize themethod of describing and expressing it. This is doneby trying to capture the night-time image in thestreet from the illuminance calculation point of view.
In past studies, research on spatial illuminance in anindoor space and two-dimensional illuminancecalculation in an outdoor space has been conducted,
but there are limited studies for three-dimensional
outdoor space. By expressing and grasping the
spatial illuminance in the street space, we can see
the personality and features of each street[1].
Furthermore, by describing and analyzing the lightenvironment at night, it leads to the effective design
and maintenance of lighting for urban streets.
METHODA special light receiver is required that canmeasure spherical illuminance, hemispheric surface
illuminance, cylindrical surface illuminance and halfcylindrical surface illuminance. Furthermore, as amethod of substituting the illuminance meter for
ordinary planar illuminance measurement, a methodof averaging measured values of illuminance in six
directions or four directions is recommended. When
473

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017considering the light hitting a certain point in space,light is irradiated not only from one direction but
from many directions. Therefore, it is difficult toaccurately measure illuminance on-site (outside)from a single light source because there is light fromvarious sources interfering. Taking this into account,
the author opts to use a model in order to isolate asingle light source, and measure the distance. This isdone by calculating the illuminance corresponding
to a box placed virtually in the street space andconverted to spherical illuminance. As a result, it ispossible to simply depict the nighttime lightenvironment. Finally, the results of the lighting ofeach street are expressed on a map, creating acomprehensive night-time urban street map.

of arbitrary shape and arbitrary inclination via themethod of obtaining horizontal plane illuminance,and can be applied to the calculation of various
spatial illuminances.

Target area
Fig. 2 Picture plane for via-perspective method

Multiple factors were taken into consideration inchoosing a target area such as the various lighting
sources and features. The author chose Osaka-shi
Chuo-ku, as the night-time pedestrian traffic here
was also taken into consideration.

In this research, Autodesk's AutoCAD is used tocreate a simple model to portray the position of thelight source. We then placed a rectangularparallelepiped 1.5 m in height vertically in the centerof the target street, with pedestrians 1.8 m away oneach side. Next, we measure the distance between
the rectangular parallelepiped and the light source
and use it for calculating illuminance.
Calculation of hemispheric surface illuminancefrom horizontal plane light.
If the light source direction is vertical, thehemispheric surface illuminance of the horizontal
surface light source can be obtained.

Fig.1 Chuo-ku, Osaka
Calculation process
To calculate illuminance for this study; 1) Createa simple street model and measure the distance tothe light source and 2) using illuminance calculation,
obtain the value of the illuminance corresponding to
the virtually rendered surface.
Previous studies analyzed the calculation formulaof spatial illuminance from a planar light source of
shapes and every tilted state using the same method;
as in the case of horizontal illuminance by using ananalytical system and applying the mediatedperspective model[2].
In the mediated perspective model, in order toapply it to a stereoscopic light source such as anannular one, a perspective figure viewed from thecalculation point is obtained on the screen, theperspective figure is regarded as a flat light source,
and a deformation formula of boundary integration
is applied. This can be applied to a flat light source

Fig.3 Spherical illuminance by means of a horizontal
surface source𝐋𝐱

𝐄𝐡𝐬 = ∫𝐱 𝟐 {(𝟏 − 𝟐
𝟒
√𝐱
𝟏

𝐲
𝟐√𝐱𝟐 +𝐲𝟐(𝐀)} 𝟐𝐧𝐱 +𝐲𝟐𝐡+𝐲𝟐 +𝐡𝟐)+𝐝𝐱 (1)For example,(𝐀) = 𝐭𝐚𝐧−𝟏

474√𝐱𝟐 +𝐲𝟐𝐡𝐡√𝐱𝟐 +𝐲𝟐− 𝟐

𝐱 +𝐲𝟐 +𝐡𝟐(2)

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

Half cylindrical surface
horizontal plane light.

illuminancefromIn this calculation method, the light irradiatedfrom a lateral direction hits the whole semicylindrical surface uniformly. The semi-cylindricalsurface illuminance “Esc” is the average value of thevertical illuminance distributed on the small semicylindrical surface on the side facing the observation
direction. It does not include illuminance distributed
on top and bottom surfaces of the cylinder.
𝐄𝐬𝐜 =

𝐋

𝐱

𝐲

𝟏

+𝐲

𝟐
∫ (𝟏 + √𝐱𝟐
𝟐𝛑 𝐱) (𝐀) 𝟐
𝟐

𝐧

𝐱 +𝐲

𝟐 𝐝𝐱

Fig.5 Geometrical relationship between an
illuminated range and an observation range on aminute cylindrical surface.

(3)

The Fig.6 shows the output calculated by
inputting the value of the target area into the formula.

Fig.4 illuminated range on the minute cylindricalsurface
Relationship between the illumination range andobservation range on a small cylindrical surface
𝐄𝐬 =

𝐋 𝐱𝟐
∫
𝟒𝛑 𝐱𝟏

𝐲
√𝐱𝟐 +𝐲𝟐 +𝐠𝟐

∗ 𝟐

𝐠

𝐱 +𝐠𝟐

𝐝𝐱

(4)

Fig.6 the output

Fig.7 bird's-eye view

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

Fig.7 shows a depiction of the target area in asimilar manner from a bird's-eye view. Analysis ofstreets by using simplified images as representationsof the night-time landscape.
CONCLUSION
In this research, as a means of better grasping thelighting environment in urban streets, we studied
about modeling the light sources. In this example,
we calculated the planar light source, but to get amore accurate analyzation, calculating the threedimensional light source should be considered.
Furthermore, we will also consider aspects such as
appropriate shapes and sizes for modeling.
References[1] Kamisaka Sho, “Calculation Method for Spacial
Illuminances by means of Flat Surface Sources andConsideration for Rough Calculating Methods”
J.Illum. Engng. Inst. Jpn., Vol.77 No.6 1993[2]Shuto Takeuchi, “Analysis on the Lighting
Environment of the Urban Street Space” The 12th
Conference for Architecture and Infrastructure
Environment, JSCE. Jpn., No.12 2016476

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SOCIAL AND ENVIRONMENTAL RESPONSIBILITY IN
DEVELOPING COUNTRIES: A THEORETICAL APPROACH OF
REGULATION
1

Lindrianasari, 2Mahatma Kufepaksi, 3Yuztitya Asmaranti, and 4Agrianti Komalasari,1
Economics and Business Faculty, 2Universitas Lampung, Indonesia
ABSTRACTThis study aims to analyze and describe the social and environmental responsibility of companies listed on
the stock exchange in three developing countries, namely Indonesia, Malaysia, and Thailand, before and after
2007. In 2007 chosen as the cut-off year of observation as we find in each country was issued significant
environmental policy. By doing a differential test on a sample of 24.626 independent firms / years, the study
found that four variables used in this study, overall showed a significant difference. Environmental costs,
disclosure of environmental, social disclosure, and ESG that observed in three developing countries has
increased significantly after 2007. However, we did not find significant increase in environmental costs inIndonesia. The findings of this study indicate that the theory of regulation, particularly for public interest theory,
can explain clearly the reasons why the four variables research has increased after the environmental regulations
issued.
Keywords: Environmental accounting, accounting and social disclosure, developing countries, regulation.

particularly for public interest theory, can explain
clearly the reasons why the four variables research
has increased after the environmental regulations
issued.

INTRODUCTION
Scheme of government policies related to theenvironment in Indonesia has been demonstrated
with the exclusion of some policies. The government
policy was issued as Republic Act No. 17 Year 2004
on the Kyoto Protocol on Framework Convention of
the United Nations on Climate Change; Republic
Act No. 40 Year 2007 regarding Limited Liability
Company; and Government Regulation No. 47 Year2012 on Social and Environmental Responsibility(Social and Environmental Responsibility - TJSL)Company Limited. Implementation of Corporate
Social Responsibility (CSR) in Indonesia has beenstrengthened and reinforced by the issuance ofGovernment Regulation No. 47 Year 2012.
In other countries, Malaysia and Thailand, we
also found that environmental policy was issued in2007. The findings provide strong reasons for us todetermine that 2007 be the year of the revival
environmental issues in three developing countries,
and then in 2007 became the cut-off on this research.
This study aims to analyze and describe the socialand environmental responsibility of companies listedon the stock exchanges of developing countries. The
three countries intended are Indonesia, Malaysia andThailand.
The study found that the cost of theenvironment, disclosure of environmental, social
disclosure, and ESG observations in the three
countries has increased significantly after 2007.
Only in Indonesia we found no significant increasein environmental costs after 2007. The findings ofthis study indicate that the theory of regulation,

LITERATURE REVIEW AND HYPOTHESISDEVELOPMENT
Theory of legitimacy and stakeholder theory is
regarded as an influential theory in the domain ofsocial and environmental accounting research [5]. In
our previous studies, we also have used both of thetheories ([1], [2], [3]). All of the above study refers
to the opinion of [4] which explains that the theoryof legitimacy and stakeholder theory are twotheories that explain each other (overlapping
theories). Both theories have differences in the levelof perception and settlement, and not the conflicting
theories. In other words, legitimacy theory andstakeholder theory can both explain and predict therelationship between the organization and the social
environment, but with different approaches anddecomposition [5]. However, both have profoundbenefits in providing understanding of the social andenvironmental accounting research.
The theory of legitimacy (introduced by Lindblom
and Suchman) focus on the value system of society[(6], [7]). So that the legitimacy theory predicts if
the value system of an organization are congruent
with the value system in the society around it, thentheorganization
will
survive.
Therefore,
organizations must be able to meet the expectations
and subsequent revenues from the public.
Meanwhile, stakeholder theory (introduced by R.
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Edward Freeman, (see [8]) focused on therelationship between the organization and various
stakeholders that form (affect) the environment.
Stakeholder theory explains that each group of
stakeholders has not the same impact on theenvironment. On the other hand, each stakeholder
expectations are often at odds with each other [5].
This study re-examine whether there is arelationship regulations issued by the government on
the actions of companies in environmental
conservation. Corporate response that reflected theiractions show their firm adherence to the regulator[9]. Although some have been inadequate disclosure
quality and only limited social contract to meet thelegitimacy to people around the company (Deegan,
2002; and O'Dwyer, 2003 in [1]). But the others
research found a significant relationship between theregulations issued by the government toaccountability on the environment by companies inIndonesia ([1], [2]). The findings of those previous
studies indicates that the regulations issued by thegovernment is very effective in encouraging
compliance of company. If in earlier studies we haveconducted investigations of companies in Indonesia
related to compliance with the policies issued inIndonesia, then this study will conduct an empirical
overview of the three developing countries which
are relatively have similar cultures and economies,
namely Indonesia, Malaysia and Thailand.
The management companies that do not havethe basic laws of the government can run but withouta clear direction [10]. Research conducted by Börzel
and Risse also explained the importance of the roleof a state in the making of rules and policies
regarding corporate governance. Mandatory actionin protecting the environment by the company canbe seen as a gesture to the government that it is time
for the regulation of an integrated environment in all
activities seriously formulated.
This would greatly support by the earlier study
in voluntary action taken by the companies (Haufler
2001 in [11]). The research found that the rules
issued by the government for an entity would
increase the compliance of these entities is greaterthan ever before. From the above, we establish thefollowing research questions as below:a) Countries Indonesia issued Law No. 40 of 2007,
which in Article 66 and Article 74 explained thatcompanies are obliged to report on social andenvironmental activities of the company. This
law is very revolutionary and very eagerly by the
public.
b) in 2007-2009 is the year where Malaysia issued a
lot of environmental policies. Department ofEnvironment, Ministry of Natural Resources andEnvironment (http://www.doe.gov.my/eia/ wpcontent/uploads/2012/03/A-Guide-ForInvestors1.pdf).
c) The Kingdom of Thailand passed the B.E.2550
Constitution in 2007. P This Constitution entitles
communities to participate in the prevention andelimination of business acts that could damage
natural resources and pollute the environment.
The data used is secondary data. Observations
focused on the company's response on government
policies related to social and environmental
responsibility. Therefore, this study assesses how
environmental performance before and after theissuance and promulgation of regulations related tothe environment. The variables measured in thisstudy are the environmental costs, the disclosure ofenvironmental, social disclosure, and governance.
Data obtained from Bloomberg database at Gadjah
Mada University in 2016. Data were analyzed using
Independent Sample test.
Data are obtained from Bloomberg database,the companies listed on the stock exchanges inIndonesia, Malaysia, and Thailand. The observation
was conducted for 12 years ie period 2004-2015.
The total sample is 24,626 years old. Table 1 shows
the distribution of research samples.

DISCUSSIONS AND ANALYSIS OF RESULTS
Figure 1 shows that before the Act No. 40 of2007 was issued and applied in Indonesia,
environmental and social performance in Indonesia
is very low, even some variables worth null. But
after it is issued and the enactment of Law No. 40 of
2007, environmental and social performance inIndonesia getting better, although there are stillcompanies that do not respond properly government
regulation. Nevertheless, it is generally seen that theregulations issued by the government have an impact
on the preparation of the purpose of theseregulations. This evidence also indicates that theregulations was issued related to this environmenthas been consistent with the public interest theory
which predicts that the regulation should be madefor the benefit of society

RQ: how adherence of companies in developing
countries on government regulation ofsocial and environmental responsibility.

RESEARCH METHODSThe object of this research is Indonesia, Malaysia
and Thailand. The reason is that these countries areat a relatively similar economic level, and are in thesame region. 2007 became a cut-off because of thatyear in each important country.
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

to 2007, to 0.7278 after 2007. Meanwhile, Indonesia
and Malaysia are in the same relative value changes.
For social disclosure and disclosure of ESG,
Indonesia showed the highest value of disclosure,then Malaysia and Thailand. However, the numberschange in each of these countries reached more than
95%.

2.5
2
1.5

1
0.5
0

Envi
_Cos
t
Before 2007
0

Envi
_Dis
c
0.00

Soc_
Disc
0.01

ESG
_Dis
c
0.01

After 2007

0.47

1.00

1.32

2.23

3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00

Source: Bloomberg, 2016.

Envi Envi Soc ESG_Co _Dis _Dis _Disstccc
Before 2007 0.00 0.01 0.05 0.12

Fig. 1 Environmental and Social Performance
Before and After 2007 in Indonesia

The same condition also occurs in Malaysia
and Thailand [see Fig. 2 and Fig. 3]. In the periodprior to release and promulgation of regulations
related to environmental and social performance ofcompanies in each country do not show a good
performance compared with after the enforcement of
the regulations. From the three countries observed,
changes in the allocation of environmental costs on
average occurs in all countries, with the greatest
increase occurred in Indonesia (relative to the valueof the unit of measure) is from 0 before 2007 to
22270 after 2007. Next is Thailand, of the value

After 2007

Source: Bloomberg, 2016.

Fig. 3 Environmental and Social Performance
Before and After 2007 in Thailand.
Test of performance of Environmental, Social,
and ESGEnvironmental cost
Environmental costs are allocated in Indonesia,
Malaysia, and Thailand on average increased frombefore and after it is issued and the enactment ofregulations on the environment in these countries.
From the test results of independent sample test
found that there were significant differences in the
allocation of environmental funds in Malaysia andThailand, respectively at a significance level of
0.000 and 0.001. However, no significant
differences were found for the allocation ofenvironmental funds in Indonesia (P-value of 0.244)(see Table 1, Panel 1).
Investigations into the findings of theenvironmental cost allocation in Indonesia showsthat no account name can be used to record andreport the costs associated with managing anenvironmental company. The absence of the name ofthis account is suspected as the cause the level oflack environmental cost allocation found in thecompany's financial statements.

1.20
1.00
0.80
0.60
0.40
0.20
0.00

Envi Envi Soc ESG_Co _Dis _Dis _Disstccc
Before 2007 0.00 0.01 0.01 0.03
After 2007

3.24 0.73 0.97 1.27

0.01 0.48 0.98 1.18

Source: Bloomberg, 2016.

Fig. 2 Environmental and Social Performance
Before and After 2007 in Malaysia

Table 1. Test of performance of Environmental,
Social, and ESG
Panel 1. Environmental CostingTo value environmental disclosure, Thailand
experienced the greatest increase, from 0.0072 prior
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

1
2
3

Thailand
Malaysia
Indonesia

Sign.
0,001
0,000
0,244

F-value
10.95618.4311.357

significance obtained from the statistical test result is
0000 for all countries. Malaysia has a value F-value
is higher (which is 533.080) compared withIndonesia and Thailand, with each value of the Fvalue of 406.386 and 274.414. (see Table 1, Panel
4).These results indicate that the government's
policy governing environmental, social andgovernancevery
effectivein
improvingenvironmental awareness by companies.

t-value-1.655-2.144-0.0585

Panel 2. Environmental Disclosure Score
1
2
3

Thailand
Malaysia
Indonesia

Sign.
0,000
0,000
0,000

F-value
128.646230.727
123.284t-value-5.61-7.545-5.505

CONCLUSIONS
By doing independent sample t test on a sample
of 24 626 firms / years, the study found that the costof the environment, disclosure of environmental,social disclosure, and ESG observations in the three
countries has increased significantly after 2007. In
Indonesia was found no significant improvement
only in environmental costs.
The findings of this study indicate that as
predicted the theory of public interest that theexistence of the policy should be aimed at theinterest of the people is confirmed by this study. It isseen from the four variables were observed in thisstudy as a whole showed a significant difference
from before and after the issuance andimplementation of policies in 2007. Each of thecompanies in the three countries that were observedin this study indicate compliance with theregulations issued on each country. In addition, theresults of this study also indicate that the rules aremandatory (regulatory) much more real impact, thanjust voluntary, especially for developing countries.

Panel 3. Social Disclosure Score
1
2
3

Thailand
Malaysia
Indonesia

Sign.
0,000
0,000
0,000

F-value
177.847336.522181.699

t-value-6.561-9.001-.6.617

Panel 4. Environmental, Social, and Governance
Score
1
2
3

Thailand
Malaysia
Indonesia

Sign.
0,000
o,ooo
0,000

F-value274.414533.08406.386t-value-8.117-11.094-9.786

Environmental Disclosure Score
Results of independent sample test showed asignificant difference in the score disclosure of thecompany's concern the environment in Indonesia,
Malaysia, and Thailand (see Table 1, Panel 2). Eachlevel of significance obtained from the statistical test
result is 0000 for all countries. Malaysia has a value
F-value is higher (ie 230.727) compared to Thailand
and Indonesia (which is 127.646 and 123.284).

ACKNOWLEDGEMENTS
The research was funded by using a research grantfrom the indonesian government, through theuniversity of lampung. We would like to thank forthe financial support of this research. In addition, we
would also like to thank our colleagues at the facultyof economics and business, university of gadjahmada, indonesia to access the data.

Social Disclosure Score
On average, social disclosure made by thecompany increased before 2007 and thereafter.
Social disclosure in Indonesia, Malaysia, andThailand experienced a significant increase frombefore and after it is issued and the enactment ofregulations on the environment in these countries.
The test results of independent sample test showedsignificant difference at the level of 0000 in all
countries. Respectively, Malaysia showed thehighest increase, then Indonesia and Thailand (seeTable 1, Panel 3).

REFERENCES[1] Lindrianasari, “Hubungan antara kinerja
lingkungan dan kualitas pengungkapan
lingkungan
dengankinerjaekonomiperusahaan di Indonesia”, Jurnal Akuntansi dan
Auditing Indonesia, Vol. 11, No.2, 2007,
pp.159-172.
[2] Asmaranti, Y. and Lindrianasari, “Comparationof Greenhouse Gas Emission Disclosure
Before and After Establishment of theIndonesian Act No. 17 of 2004’, Issues In
Social and Environmental Accounting (ISEA)

Disclosure ofEnvironmental,
Social andGovernance (ESG) Score
Results of independent sample test, showed asignificant difference in scores ESG disclosure inIndonesia, Malaysia, and Thailand. Each level of480

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017Vol. 8, No. 3, 2014, pp. 225-234.
[3] Lindrianasari and Asmaranti, Y., “Investigative
studies on environmental disclosure and thecosts of R&D as a compliance withgovernment policy on corporate social
responsibility in Indonesia’, International
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5, No.2, 2016, pp. 61-71.
[4] Gray,R., R. Kouhy and S. Lavers, “Corporate
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[5] Chen, J. C. and Roberts, R. W., “Toward a
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651-665.
[6] Lindblom C. K., The of Implications
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stakeholder approach. Boston: Pitman. 1984.
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No. 2, 2005, pp.235–248.

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ASSESSMENT OF URBAN CLIMATE CHANGE IN IPOH CITY,PERAK, MALAYSIA
Mohd Hairy Ibrahim , Mazlini Adnan2, Nor Kalsum Mohd Isa3 & Kamarul Ismail4,
1

1

Department of Geography and Environment, Faculty of Human Sciences, Sultan Idris University of Education,
35900 Tg. Malim, Perak.
2
Department of Mathematics, Faculty of Science and Mathematics, Sultan Idris University of Education, 35900
Tg. Malim, Perak

ABSTRACTThis paper focuses on the variation of changes of the urban climate parameters as a result of rapid
expansion of human habitat in Ipoh City. The study found that long-term temperature trend Ipoh showsthat the temperature has increased significantly between 1968 and 2010. Findings show thattemperature increase in the industrial area has the value of r =0.44, which indicates that the industrial
area experiences temperature change in moderate strength. During all monsoon seasons, the trendsof temperature change increase in low strength in the industrial area. The temperature variation
increases significantly during the southwest monsoon and April monsoon transition seasons comparedwith during the northeast monsoon season. Urban climate change calls for cooperation of all parties inaddressing the temperature change in preserving the urban ecosystem sustainability of Ipoh City.
Urban climate change calls for cooperation of all parties in addressing the temperature change in preserving theurban ecosystem sustainability of Ipoh City.
Keywords: Urban Climate, Human Habitat, Environmental Change, Ecosystem Sustainability

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specifically urban heat island which is a major issue
due to urbanization and industrialization.

INTRODUCTION
Since the mid-1970s, global warming has
accelerated at a rate of 0.150C per decade [24] [14].
Due to rapid urbanization, urban warming has
become a serious problem along with global
warming [26] [27] [29]. Over 100 years ago, theaverage global temperature has increased by 0.30 to
0.60C [14] .The situation arises due to expansion ofhuman habitat via urbanization activities in theurban areas. Before we proceed, we need to discuss
the expansion of human habitat in Malaysia ingeneral.

This paper examines the increasing expansionof human habitat in Ipoh City, which is located in
the Kinta Valley. The rapid expansion involves
urbanization activities which alter the physicallandscape in expanding cities and towns in Kinta
Valley, such as Kampar, Gopeng, Batu Gajah, Seri
Iskandar, Ipoh, Chemor, Bercham, Simpang Pulai,
Lahat and Pengkalan, Kanthan, and Tanjong
Rambutan.
Development
involving
human
activities in these areas has transformed the naturalenvironment of Ipoh into a Kinta Valley
metropolitan. The human activities have altered thelandscape with opening of land for the purpose ofurbanization,
agriculture,miningandindustrialization. From a well-known tin mining
area in the past, Kinta Valley has largely been
reclaimed by humans and transformed into
residential, business and industrial areas. The hills
in the east and north of Kinta Valley have been
quarried for the precious marbles. These activities
and changes have caused temperature change inIpoh. As cities grow over time, the temperature also
tends to increase and become higher [21].

The rapid expansion of human habitat throughurbanization activities takes place mostly in Asian
countries which experience rapid economic growthin the 19th century until 20th century. Malaysia is
one of the fastest growing and urbanizing countries
in Asia [12]. Urban development in terms ofurbanization has cause a number of changes andtransformation, including socio-economic andsignificant climate and weather changes [37].
Environmental changes in fast-growing urban areas
can cause urban climate change, acid rain, and heatisland which lead to increasing temperature anddisruption of people's lives.

DATA AND METHOD

Most current research discusses environmental
issues in relation to the rapid urban development
and industrial factors which tend to alter natural
patterns and temperature trends in urban
environment [33]. As cities grow over time, thetemperature also tends to increase and become
higher [21]. Urban heat island has become a major
problem associated with urbanization andindustrialization of human civilization whereby
temperature increases due to the urban heat island
threaten human health. This makes the urban heatisland a theme among climatologists and is
documented in metropolitan areas around the world[28] [17] [3] [20] [30] [36] [4] [8] [19] [18].

Malaysia's tropical climate is hot and humid.
Data obtained from Malaysian Meteorological
Department of a period of ten years shows that theexternal temperature is relatively uniform with anaverage temperature of between 23.70 C and 31.30
C during the day, with the highest recorded
temperature of 36.90C and an average relative
humidity throughout the day between 67% and95%. Generally, temperature increases in the
rapidly developing cities with buildings andcrowded with vehicles compared with suburban andrural areas.

Cities are vulnerable to climate change due togreenhouse gases and local effects of activities suchas urban heat island. The process of urbanization
definitely affects the urban environment. It is wellknown that urbanization creates a change in themorphology of the city, infrastructure, available
facilities, increase in energy consumption, visible
physical environmental conditions and also thenumber of population being accommodated [15].
Urban areas have different climatic conditions than
the surrounding environment [27]. Urban heatisland has become a major problem associated withurbanization and industrialization in which
temperature increases due to the urban heat island
threatens human health through thermal stress. This
indicates problematic urban atmosphere or climate,

All raw data are obtained from theMeteorological Department, Malaysia from its
database. Meteorological data from the years 1970
to 2000 were gathered from Ipoh Airport
Meteorological Station. Geographically, Ipoh islocated at 4.5975° N, 101.0901° E. Ipoh City is thethird largest city in Peninsular Malaysia, and at aheight of 75 meters above sea level based on theflat landing of both banks of Kinta River. The
topology of the study area is low lands at a heightof less than 180 meters above sea level. In thesouthwest of Ipoh is the Kledang Range, at a heightof 600 meters above sea level acts as a permanent
forest reserves and water catchment areas. In thesouth, the environment is littered with limestone
hills about 160 meters high from Map of Peninsular
Malaysia, Series 1307.

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Time series data of mean maximum
temperature, mean minimum temperature and meanannual temperatures from 1970 to 2000 (30 years)
collected from Ipoh Airport meteorological station
are used to determine the change in temperature of
the metropolitan city of Ipoh. The data wereanalyzed in two parts by conducting linear
regression and noting the anomalies of periods from1968 to 2010. The linear regression is used todetermine temperature changes in Ipoh, Perak.
Temperature is used as a dependent variable, while
the length of time as an independent variable.
Temperature is used as: temperature = f (time) andy = a + bx, where Y + mean temperature(minimum, maximum), X = period of time [31].
The analysis also shows the extent of relationshipbetween the variables. The relationship between theminimum and maximum mean surface temperature,
and annual time series (1968-2010) can assess thestrength of the relationship between two variables
as illustrated in Table 1 [1]. Trend analysis was
carried out to show the mean temperature and time(in years). The trend given by the slope coefficientof the fitted linear regression line is tested forsignificance (95%).

average minimum temperature had aconsiderable increase compared with the average
maximum temperature. Wind velocity had also
undergone dramatic increase. At the same time,
however, relative humidity only increased at a low
level, and did not significantly influence
temperature change.

Figure 1: Trend of average temperature change in
Ipoh from 1968 to 2010
The variation of urban climate parameters in
Ipoh involves two areas, which are urban andindustrial areas where the data of climateparameters from air quality station in Pengkalan
Pegoh represents the urban area, while the air
quality station in Tasek represents the industrial
area. Research findings show that temperature
increase in the industrial area has the value of r
=0.44, which indicates that the temperature change
in the industrial area was positively increasing inmoderate strength. Relative humidity also increasedin moderate strength (Table 2).

Table 1: The strength of relationship between two
variables
The value ofRelationshipcoefficient r
0.00 – 0.20
Nil
0.20 – 0.40
Low
0.40 – 0.60
Moderate
0.60 – 0.80
High0.80 – 1.00
Very highSource: [1] Alias Baba, 1999

Table 2: Result of Regression Analysis of Climate
Parameter Change of Tasek (Industrial Area) in Ipoh

FINDINGS AND DISCUSSION
The temperature increase due to urbanization in
Ipoh received a lot of attention from several
researchers only in the early 1990s, but after 1993,
the attention ceased. Preliminary studies have been
carried out previously to understand changes intemperature [25] [13]. Temperature trends used inmany of the studies is a popular way to assess
trends of urban temperature changes due to urban
warming [16] [9] [10] [5]. Analyzing the linear
trend of change over the years and temperaturechanges in Ipoh had shown significant results (Fig.
1).

* Significance level: 0.0
Urban areas are experiencing temperature change
which increases by 0.0850C per year in moderate
strength, influenced by relative humidity which has
increased in very high strength (Table 3). At thesame time, wind velocity has decreased at moderate
strength (r=0.48). The findings show thattemperature change in the urban area is higher thanin the industrial area.

The study found that in the long-term,
temperature change in Ipoh City shows a moderateand significantly positive temperature trend in the
period between 1968 and 2010 (Table 3). The

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Table 3: Result of regression analysis oftemperature, relative humidity, rainfall and windvelocity in Ipoh (Urban) and Sitiawan (Suburbs)

Table 6: Result of Regression Analysis of
Temperature Change According to Monsoon
Seasons of Urban Area (Pegoh) in Ipoh from 1998
to 2010* Significance level: 0.05
Urban areas were experiencing positive increase of
temperature change in moderate strength,
influenced by an increase of relative humidity invery high strength (Table 6). At the same time,
wind velocity had decreased in moderate strength(r=0.48). The urban areas also experienced higher
temperature change during the southwest monsoon
and April monsoon transition seasons in moderate
strength compared with during the northeast
monsoon and October monsoon transition seasons(Table 6). Obviously, variations in temperature
increase in the long term, but the strength of change
is moderate. The temperature variation increases
considerably during the southwest monsoon and
April monsoon transition seasons compared with
the northeast monsoon season. Urban climatechange calls for cooperation of all parties inaddressing variation of temperature change inpreserving urban ecosystem sustainability of Ipoh
City.

* Significance level: 0.05: MAT Mean Annual
Temperature; MMxT Mean Maximum
Temperature, and MMiT Mean Minimum
Temperature (0C)

Table 4: Result of Regression Analysis of Climate
Parameter Change of Pegoh (Urban) in Ipoh
* Significance level: 0.05

Table 5: Result of Regression Analysis of
Temperature Change According to Monsoon
Seasons of Industrial Area (Tasek) in Ipoh from1998 to 2010

CONCLUSION
In conclusion, the results of trend analysis show apositive temperature change in Ipoh between 1968
and 2000. The research findings are a sign of theneed for feasible measures to protect thesustainability of urban environment so that urban
temperature does not continue to rise and negatively
affect the urban residents in the future. Therefore,
sustainable planning and urbanization should
continue to be strengthened to ensure that Ipoh
becomes a sustainable city.

* Significance level: 0.05
Trends of increasing temperature change during all
monsoon seasons are in low strength in theindustrial area in Ipoh (Table 4). The industrial area
(Tasek) experienced very high increase of relative
humidity during the southwest monsoon (r=0.9),
April monsoon transition (r=0.7), and northeast
monsoon (r=0.9), while it decreased during Octobermonsoon transition (r=0.4) (Table 5).

ACKNOWLEDGEMENTS
Our appreciation to Malaysian Meteorological
Department for generously contributing their data tothis study.

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Universiti Kebangsaan Malaysia: Bangi
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Indications of the urban heat island in
Athens, Greece. Journal of Applied
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1985, pp. 1296–1302.
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26, 1987, pp. 712–716[4] Böhm, R. Urban bias in temperature time series- a case study for the city Vienna, Austria.
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days in the inland of the Kanto Plain and its
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pp. 1041-51.
[11] Grimmond C.S.B, T.S. King, F.D. Cropley,
D.J. Novak & C. Souch. Local-scale fluxesof carbon dioxide in urban environments:
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2002, pp. 243-254.
[12] Hanafiah. N.H & Chan., N.W. The occurrence
Urban Heat Island and its effect humanthermal discomfort in Penang, National
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Environment international Journal Vol. 30,
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December, 2009. pp. 50-60.

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TREND OF DAILY RAINFALL AND TEMPERATURE IN
PENINSULAR MALAYSIA BASED ON GRIDDED DATA SET
Chee-Loong Wong1 , Zulkifli Yusop2 , Tarmizi Ismail3
1

Facultyof Civil Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
2
Department of Irrigation and Drainage, Malaysia, Jalan Sultan Salahuddin 50626 Kuala
Lumpur, Malaysia
3
Centre for Environmental Sustainability and Water Security, Research Institute for
Sustainable Environment, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia

ABSTRACT
A gridded data set with the size of 0.05 degree resolution (approximately 5.5km) which representing groundobservations of daily rainfall and temperature of Peninsular Malaysia has been created over 1975-2006. The
integration and processing of the variety of data sources and data assessment is also presented. The 32-year
period of the daily gridded rainfall and temperature data set were assessed to see how the daily mean rainfall andtemperature have changed over time and space. Northeast monsoon (NEM) contributes more rainfall over thecountry compare to southwest monsoon (SWM). The rainfall trend during NEM is found significantly increased
at the 95% confidence level (7mm/season/year), meanwhile SWM rainfall does not pose any significant trends.
Both NEM and SWM temperature trends show significant increasing trends at 95% confidence level at
0.32oC/decade and 0.31oC/decade, respectively over the 32-year period. A drastic increased of mean temperature(1.20oC) was found in Klang Valley over the 20-year period. The mean decadal temperature was foundconsistently decrease as it approached the northern, east coast and southern part of the country.
Keywords: Rainfall trend, temperature trend, gridded data set, Peninsular Malaysia

as an input in the hydrological models as explainedby many researchers [5-8], particularly in areas withfew rain gauges. However, few shortcomings ofsatellite data were identified e.g. short records ofdata, biases and discontinuities due to thedisruptions of instruments or nature and frequentchanges of algorithms causing lengthy calibration
tasks [9,10]. Although the calibration methods are
improved from time to time [10-12], gauge-based
data remains as a primary data source for anyhydrological and atmospheric models.
To overcome the spatial and temporal problems
with the ground observations, gridded data sets
become essential means for applications inhydrological research and climate studies. For
examples, global and regional studies inhydrological cycles [1,13-17], water resources
assessment in large river basin [15,18], hydrologicalextremes [19,20], flood forecasting [21,22], climate
variability [23,24], climate change scenario
projections [25,26] and high resolution climate
model evaluation [27,28].
Motivated by the availability of long records andgood quality of daily hydrometeorological gridded
data set in Peninsular Malaysia [29], this study
focuses on the trend assessment of the daily rainfall
and temperature data set between 99.5⁰E to 104.5⁰E
and 1⁰N to 7⁰N, with a 0.05⁰ resolution. The study
also covers the spatial and temporal variability

INTRODUCTION
An accurate and complete hydrometeorological
data source plays an important role in large scalemodels to simulate hydrological land surface
conditions, especially in related to climate and water
resources studies. Though the nature of eachindividual model varies due to the applied physics,
the basic requirement is to acquire a complete data
sources in terms of space and time. In many floodmodeling applications, the simulations are
dependent upon the availability of station data andthe distance of the nearest station [1]. Because of thelimited observation coverage, the selected nearest
station data could be a few hundred kilometres awayfrom the research area. The spatial distribution of
stations or stations density in observation networkand erroneous data in temporal aspects are the key
problems for obtaining good hydrometeorological
data within the study area [2]. Besides, thedifferences in customary observation practice, e.g.
for rainfall measurements between countries [3,4],
or differences in measurement methods or reporttiming between variables also limits the researchworks, especially affecting the modelling
simulations (calibrations and verifications).
A current trend in achieving better hydrologicalmodelling results, is turning to remote sensing as apossible means for quantifying e.g. variable rainfall
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analysis of rainfall and temperature in Peninsular
Malaysia.

of three datasets has an average of 122 daily
observations with a maximum of 167 for 2001 and2003. Meanwhile, the average numbers of daily
observations are 32 for temperature. The
temperature records show a very small number ofdays were the number of observations significantly
drops.

DATA COLLECTION
Data Sources and Quality Control
The daily rainfall and temperature observation
data used in this study has been extended from theprevious study by Wong [29] to 2006. The data
sources are based on the ground observations data of
Malaysian Department of Irrigation and Drainage(DID), the publicly accessible Global Summary of
the Day (GSOD) archive compiled from reports
transmitted over the Global Telecommunication
System of the World Meteorological Organisation(WMO-GTS) at the National Climatic Data Centerof the National Oceanic and Atmospheric
Administration (NOAA/NCDC), the Global Energy
and Water Balance Experiment (GEWEX) research
programme Asian Monsoon Experiment (GAME)
archive, and the Malaysian Meteorological
Department (MMD). Table 1 shows the data
sources for the period 1975-2006.
Data sources
DID
MMD
GAME*
WMO-GTS**

Variable
Rainfall Temp
152
5
5
19
19
87
87

Duration
1975-2006
2002-2006
1997-2002
1975-2006* from GEWEX Asian Monsoon Experiment (GAME)** retrieved from NOAA/NCDC

Fig. 1 Locations of the station in the study.

Fig. 1 shows the interpolation domain anddistribution of the stations. For the purpose ofinterpolation, the station data includes several
WMO-GTS stations in Thailand and Sumatra, which
are located just outside of the grid as shown in Fig.
1.
The data quality control procedure follow that
described by Wong [29]. Three levels of screening
and filtering of data were conducted in order toobtain the most reliable and consistent data sources.
The details were highlighted in gridded data set
development by Wong [29]. The long-term MMD
statistics become reference for the quality
monitoring purpose. The quality control of WMOGTS data was based on the quality flags in the data
sources files. There are no additional quality checks
on MMD and GAME data, assuming the data werechecked by MMD.
Fig. 2 presents the number of available daily
observations from the individual data sources andtheir combination for the period from 1975 to 2006.
The total number of rainfall observations isrelatively stable, except the lack of WMO-GTS
observations during short periods. The combination

Fig.2 Number of daily observations during therecord period, the dotted line shows the maximum
number of observations for each variable.
Terrain Data
Static data, i.e. terrain characteristics are constantover time. It is impossible to develop or operate
489

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

large-scale modeling without such data. Elevation
data have been derived from the Shuttle Radar
Topography (STRM 30) 1 km version 2 data set[30], and were averaged into the output grid
resolution.
The dynamic terrain data are associated with theland cover properties in the study area. Land covertype data were obtained from MODIS MOD12Q1
annual V004 1 km data products for the period
2001-2004, using the International GeosphereBiosphere Programme (IGBP) biome classification.
The land cover data are used to obtain the effective
momentum roughness length for wind speed
interpolation by aggregating the roughness length
values of all cover types within a grid box using acover type fraction-weighted averaging scheme [31].
The relations between land cover types androughness length are based on [32] and [33].

distance (CDD) then equals to the distance where
the mean correlation coefficient drops to 1/e.
In order to provide a measure of the expected
accuracy, a jackknife cross-validation analysis has
been carried out by repeated deletion andreplacement of individual stations followed by acomparison of the grid box values with those of thedeleted station. Overall daily error statistics for theentire area are computed in terms of mean absolute
error (MAE) and bias. The results for temperaturefields showed MAE is 0.4 °C with a bias of 0.1 °C.
For rainfall a comparison at jackknifed grid box
level resulted in a MAE of 5.2 mm/d and a bias of−0.1 mm/d (−1.9%). These results show thatinterpolation on a daily basis is significantly moreerror-prone that for the long-term average. On shorttime scales, the largely convective rainfall exhibits alarge amount of spatial variability over shortdistances. In some cases, multiple rainfall stations
located in the same grid box and that are averagedby the interpolation scheme show distinct
differences in daily rainfall.

METHODOLOGY
Data Interpolation
The interpolation scheme is based on an adaptionof Shepard’s [34] angular distance weighting(ADW) procedure covers 32 years (1975 – 2006)
period. Details description of the data set andgridding procedure are given in Wong [29]. In orderto account for orography, interpolation oftemperature are carried out on sea level equivalentvalues and then converted to grid box values using
the derived DEM. Temperature is related toelevation, the temperature lapse rate formulations
applied for the U.S. standard atmosphere [35] isused. There is no additional processing is carried out
for rainfall, which is interpolated directly from point
observation values. Since very few stations areavailable at higher altitude, it is not possible toidentity clear orography effect on rainfall especiallyin daily time series.
The
interpolation
methodrequiresanunderstanding of the spatial correlation structure of
the station data as explained by Wong [29]. Theinter-station correlations were investigated todetermine the distances over which observed climate
variables are related. This allows defining the
distance weighting. The Pearson correlation
coefficients between all pairs of stations for thevariables are interpolated and plotting against
distance. The spatial relationships between stations
vary depending on the density of station coverage. In
order to obtain daily spatial correlation coefficientsfor all pairs of rainfall and temperature stations, they
were binned into separation distance intervals. In
each bin, the mean and standard deviation of thecorrelation coefficient was calculated and an
exponential curve was fitted through the mean
distance-correlation points. The correlation decay

Trend detection
The annual and monsoon time series of rainfallof the climatic regions were analyzed using theMann-Kendall nonparametric trend detection test
[36,37]. The Mann-Kendall method has been widelyused and tested as an effective method to evaluate apresence of a statistically significant trend inclimatological and hydrological time series [18,3840]. In the trend test, the null hypothesis H o is that
there is no trend in the series (the data are
independent and identically distributed).
The
alternative hypothesis H 1 is that a trend exists in thedata. The Kendall S-statistic is obtained fromcomparison between all possible (x, y) pairs of dataand is given byn −1nS = ∑ ∑ sgn( xi − x j ) sgn( y i − y j )(1)

i =1 j =i +1

where, the sign function is defined (for any variableu) as − 1 if u < 0(2)
sgn (u ) =  0 if u = 0
 + 1 if u > 0Under the null hypothesis, the statistic S isapproximately normally distributed with zero mean
and variance are given by
Var ( S ) =n(n − 1)(2n + 5) −∑ t i(i − 1)(2i + 5)ni =1 i(3)18
where t i is the number of ties of extent i in either thex or y data. The summation term in the numerator is490

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017used only if the data series contains tied values. The
standardized test statistic Z is obtained as S +1
if S < 0 Var (S )(4)
if S = 0
Z = 0−1
Sif S > 0 Var (S )mean annual rainfall. The lowest mean monthly
rainfall of 113 mm occurs in February, which
contributes about 5% to the mean annual rainfall. It
is noted that during the NEM from November toMarch both the maximum and minimum monthly
rainfall are observed. A relative high rainfall
variation is observed during the NEM than theSouthwest Monsoon (SWM), which occurs from
May to September. The result agrees with thefindings by Moten [41], where maximum rainfall isobserved near the end of the year during theNortheast Monsoon (NEM). A secondary maximum
is found during the intermonsoon months (April orMay).
Fig. 4 shows the distribution of annual average
rainfall in Peninsular Malaysia. It is noted that therainfall in the east coast region of Peninsular
Malaysia is mostly influenced by the NEM,
particularly during November or December [42,43].
The NEM influence was even reported to have morethan 70% rainfall contribution over most parts of thePeninsular [41]. However, there is only 44% ofannual rainfall throughout 32-year analysis occurred
during the NEM. In this study, both monsoons
contribute 81% of the total annual rainfall over thecountry as shown in Table 2. There is 37% of annual
rainfall which occurred during SWM period. During
the NEM, the dry northeasterly wind becomes wet
during the passage over the South China Sea. Theinteraction between with the land along the east
coast area creates deep convection clouds andrainfall [44].

The test statistic Z is used to measure thesignificance of a trend. In a two sided test, H oshould be accepted if |Z| is greater than Z α/2 , where α
represents the chosen significance level (e.g. 5%
with Z 0.025 = 1.96) then the null hypothesis isrejected implying that the trend is significant. A
positive Z value indicates an upward trend, whereasa negative Z value indicates a downward trend. If asignificant trend is present, the average rate ofincrease or decrease can be obtained from the slopeof a simple linear regression.
DATA SET EVALUATION AND ANALYSIS
Rainfall

400
300
0

100

200

Monthly Rainfall (mm)

500

600

An overview of rainfall distribution of Peninsular
Malaysia as a whole is presented. The gridded data
set at 0.05 degree resolution was used to analyze themonthly rainfall distribution in Peninsular Malaysia.
The mean monthly areal rainfall data for entire
Peninsular Malaysia is shown in Fig. 3.

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Fig. 3 Box and whisker plot of areal average mean
monthly rainfall (1975-2006) in Peninsular
Malaysia. The asterisk denotes the mean value, thesolid line is the median, the height of the box is thedifference between the third and first quartiles(IQR). Any data observation which lies 1.5 IQRlower than the first quartile or 1.5 IQR higher than
the third quartile can considered an outlier inthe statistical sense, indicated by open circles.
The highest mean monthly rainfall of 311 mm isobserved in November, equivalent to 13% of theFig. 4 Peninsular Malaysia rainfall distribution(1975-2006).
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

NAHRIM [24] where the country will be warmer by
about 2oC in the next 50 years. Both NEM andSWM temperature trends show significant
increasing temperature trends at the 95% confidence
level at 0.32oC/decade and 0.31oC/decade,respectively over the 32-year period (as shown in
Fig. 6(b) and 6(c)).

Table 2 Monsoons rainfall contributions in
Peninsular Malaysia.
NEM
SWM
Total
Annual(Nov-Mar)(May-Sep)
Monsoons
RainfallRainfallRainfallRainfall
(mm)
mm %
mm
%
mm
%

2500

(a)

y=5.03x+2265

1500

The inland region received a relatively smaller
amount of mean annual rainfall, i.e. 1950 mm/year
as shown in Fig. 4. The reduction of rainfall amountin the inland is due to Titiwangsa mountain range
forms the backbone of the Peninsula, from southern
Thailand running approximately south-southeast
over a distance of 480 km and separating the easternpart from the western part [42]. It appears to block
the westward progression of the climatic system andtherefore inhibits excessive rainfall over the inland
areas [45]. The rainfall produced in this region ismainly due to local convection caused by intense
heating of the land surface [46].

Annual Rainfall

3500

Annual Rainfall (mm)

81

1975

1980

1985

1990

1995

2000

2005

NEM Rainfall

(b)

1500

2000

NEM Rainfall (mm)

Year

500

1000

y=7.03x+925

1975

1980

1985

1990

1995

2000

2005

1500

y=-1.725x+891

500

The annual and monsoons rainfall trends ofPeninsular Malaysia are presented in Fig. 5. The
mean annual rainfall shows minor increase trend (5mm/year) over 32-year period, however it does notpose any significant increasing trends at the 95%
confidence level under Mann-Kendall analysis.
For the mean NEM rainfall in the Peninsula,increasing trends of rainfall are significantly foundat the 95% confidence level (7mm/season/year). It
was probably due to the accumulation of increasing
trend of other months though they are not significant
at 95% confidence level. During SWM monsoon,
Peninsular Malaysia shows −1.7 mm/season/year of
rainfall declining but it does not pose significant
trends at the 95% confidence level. Generally, thetrends of mean annual and monsoons rainfall areprobably governed by the topographic characteristics
and local or regional conditions that have an effecton the interannual rainfall variability, which issuperimposed on the large-scale weather conditions.

(c)

1000

Rainfall Trends

SWM Rainfall

2000

SWM Rainfall (mm)

Year

1975

1980

1985

1990

1995

2000

2005

Year

Fig. 5 Rainfall trends of Peninsular Malaysia (19752006).
(a)y=0.032x+25.20

24.5

Mean Temp.

o

 C

27.5

Annual Temperature Trend

26.5

1898

25.5

37

1975

1980

1985

1990

1995

2000

2005

Year

(b)

y=0.032x+24.79

24.5

Mean Temp.

o

 C

27.5

NEM Temperature Trend

26.5

864

25.5

44

1975

1980

1985

1990

1995

2000

2005

Year

SWM Temperature Trend

27.5
Mean Temp.

o

 C

TemperatureTrends(c)y=0.031x+25.55

24.5

Fig. 6 shows the annual mean temperature trendof Peninsular Malaysia for 1975-2006. Significant
increasing temperature trend at the 95% confidence
level was found at about 0.32oC/decade for annual
temperature in Peninsular Malaysia. This warming
trend is comparable to those reported by Tangang etal. [47] where their results showed that the warming
trend of between 2.7−4.0 oC/100 years. The warming
trend at 0.30oC/decade agrees with the simulated
temperature increase range by MMD [48] and

26.5

1034

25.5

2343

1975

1980

1985

1990

1995

2000

2005

Year

Fig. 6 Temperature trends of Peninsular Malaysia(1975-2006).

492

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

may be caused by the urbanization andindustrialization in the country [49]. For other partsof the country, the mean temperature is generally on
significant increasing trend as discussed earlier. The
reason for the rise of warming rates in the recent
decade is the higher frequency of El Niño events[47,48].

Temperature Spatial Variation
To analyze the spatial variation of mean
temperatures of Peninsular Malaysia, the 32-year ofmean temperature gridded data was divided into
three decades, i.e. 1975-1984, 1985-1994 and 19952006. The difference between the earlier and later
decade was calculated to explore the spatial
variation of mean monthly temperatures ofPeninsular Malaysia as shown in Fig. 7.

CONCLUSION
A high resolution, 0.05 degree gridded dailyhydrometeorological data set was used to assess therainfall and temperature variability in Peninsular
Malaysia. The rainfall distribution of Peninsular
Malaysia is generally influenced by two monsoons
season, i.e. NEM and SWM. NEM has higher
impact over the Study region compared to SWM. As
most of the important rainfall trends may not be
identified at the coarse time resolutions. A finer
temporal scale is needed to investigate the rainfall
trends in the future study.
Significant increasing trends (0.32oC/decade) at
the 95% confidence level have been found in themean temperature for the whole country. It was inline with the finding by other researchers [24,47,48].
The mean temperature of the country is generally
spatially on increasing mode over the 32-year
period. Klang Valley and west coast of Peninsular
Malaysia encounter higher increase of mean
temperature (the range of 0.95oC to 1.2 oC) between
1975-1984 and 1994-2006. In contrast, the northernand southern parts of the country were on slow
increasing pace (less than 0.35oC/decade) comparedto other regions.
Future studies are likely to include thedelineation of climatic regions using statisticalanalysis over the daily gridded data set in Peninsular
Malaysia. It will be useful to further explore theregional characteristics of rainfall and temperature
distribution through trend analysis and spatial
rainfall and temperature variability analysis on
different temporal resolution for different climatic
regions in the country. It not only provides better
understanding over the spatial and temporal
climatology characteristics of Peninsular Malaysia,
but also serve as the future fundamental forflood/hydrological research development in the
country.

Fig. 7: Decadal temperature (a) differences between
baseline (1975-1984) and intermediate decade(1985-1994) (b) differences between intermediate(1985-1994) and most recent decade (1995-2006) of
Peninsular Malaysia.
The initial decade (1975-1984) was used as thebaseline to compare with the intermediate decade(1985-1994) as shown in Fig. 7(a). It is noted thatthe inland region (especially Klang Valley)encountered higher degree of temperature between
0.35oC/decade to 0.5oC/decade. It dispersed towards
northern and southern part of Peninsular Malaysia.
The most northern part of the country has minima ofdifferences mean temperature (less than 0.05
oC/decade) in terms of decade-to-decade comparison.
Meanwhile, the southern of the country was at therange of 0.3oC/decade - 0.35oC/decade changes over
10 years period. Fig. 7(b) shows the difference ofmean temperature between the intermediate decade(1985-1994) and the most recent decade (19952006). A drastic increased of mean temperature(more than 0.6oC/decade) was noted in Klang Valley
and west coast of Peninsular Malaysia. The mean
temperature differences consistently decrease as it
approached the northern, east coast and southernpart of the country. The northern and southern partshows the approximately 0.35oC/decade or lesser ofmean temperature differences. Majority of country
area has an increased of mean temperature in therange of 0.35oC/decade between 0.6oC/decade overthe latest decade-to-decade comparison. The mean
temperature of Klang Valley areas wasapproximately 1.2oC warmer in 20-year period. This

ACKNOWLEDGEMENTS
The authors thank the Department of Irrigation
andDrainage
Malaysia(DID),
Malaysia
Meteorological
Department(MMD),andNOAA/NCDC for providing the data.

493

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

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SPATIO-TEMPORAL ANALYSIS OF LAND USE AND LAND COVER
CHANGES IN ARID REGION OF SAUDI ARABIA
1, 2, 3

Eman Albalawi1, Ashraf Dewan 2 and Robert Corner 3
Department of Spatial Sciences, Science and Engineering, Curtin University, Australia
1
Department of Geography, Umm Al-Qura University, Makkah, Saudi Arabia.
ABSTRACT

Changes in land use/land cover (LULC), are a major factor driving global environmental change, especiallyin arid and semi-arid regions. As a result, expansion of agriculture and urbanisation is occurring in ecologicallyfragile lands. This study analyses and detects land use/land cover changes in an agricultural centre Tabuk in
Saudi Arabia. For LULC analysis, object-based classification technique using Landsat images for seven years(1985, 1990, 1995, 2000, 2005, 2009, and 2015) have been used. The urban growth type for Tabuk wasmeasured using Urban Growth Analysis Tool (UGAT) within a GIS to analyse the pattern of urban growth thathas occurred during the last three decades. The result showed a high level of accuracy, ranging from 85% to
97 %. The study found a significant increase in urban areas from 48 km2 in 1985 to 315 km2 in 2015. A
remarkable increase of 61% in agricultural area, from the year 1985 (112 km2) to (577 km2) in 2015. Thismassive expansion is occurring at the expense of the bare land, indicating a loss of 768 km2 bare land. The urban
growth for Tabuk showed that 72% was determined to be of extension-type over the study period, with urban
areas expanding in a direction towards the west and north-western areas. The LULC maps would assist
government planners and decision makers to analyse and manage agricultural and urban growth.
Keywords: Change detection; GIS; Land Use /land cover (LULC); OBIA; Remote sensing; Urban Growth Typeecosystem [3].
Migration plays an important role in population
distribution between administrative regions of Saudi
Arabia, and between rural and urban areas within thesame region [6] The imbalance of population
distribution, however, has negative impacts fordemands on resources and space [7].
Urban development together with humanactivities such as unsustainable agricultural practices,
unplanned urbanisation, excessive use ofgroundwater and poor public policies in Tabuk haveresulted in environmental problems across the city.
A modelling study for Michigan USA, on the effects
of urban growth on groundwater, predicted thaturban growth dependent on ground water supply is
not sustainable [8] Such studies highlight the issuesof urban expansion for cities, relying solely on
groundwater. To prevent further damage inenvironment, land use change should be assessed [9].
Temporal and spatial observation of changes
over a specific time period can provide reliable
information for mapping and analysing LULC
change at local, regional and global scales [10]. A
variety of techniques have been used to detectchanges in LULC, including post-classificationcomparisons. The selection of an appropriateclassification method is essential for extracting
reliable information from satellite data. Supervisedand unsupervised classifications are two traditional
pixel-based approaches to image classification [11].

INTRODUCTION
Land use and land cover have been changed
dramatically in Saudi Arabia over the last 30 years
due to the high value of national petroleum revenues
and rapid growth in urban population [1]. The arid
climatic conditions in Saudi Arabia generate low andirregular rainfall, so that agricultural areas are
dependent on groundwater. The Government has
introduced plans and programs to increase
agricultural productivity by augmenting agriculturalareas to ensure consistent development of thecountry [2]. Tabuk is an important agricultural
centre in Saudi Arabia and is highly susceptible toland degradation due to high aridity. An increase inagricultural activities around Tabuk city reflects theimplementation of wheat subsidies, introduced in the
1980s. During that time, the Saudi government
supported and encouraged new agricultural projects[3], with a view to enhance food self-sufficiency.
Reference [4] concluded that Tabuk is exposed
to a high risk of environmental damage from‘desertification’ due to rapid change in LULC as
agricultural land use increased to about 68% over a
20-year period, from 1988 to 2008, into fragile
areas . Inadequate planning, lack of awareness, andmismanagement of natural resources have led tomassive changes in LULC and, therefore,hydrological processes [5]. Such changes haveresulted in the further deterioration of the desert
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Object-Based (or Object-Oriented) image analysis(OBIA) classification introduced by [12] has gained
popularity in recent times. The key to OBIA is toexhibit features such as image textural; spectral andspatial information so an accurate analysis can beobtained [13]. Object-based classification provided
higher accuracy than pixel-based classifications inurban classes. This technique was utilised spatialand spectral information for the mixed urbanagriculture arid region of Arizona [14]–[15].
Previous research applied remote sensing data forassessing and mapping urban sprawl, urban
structures, sprawl direction, and urban growth
pattern [16]–[17]–[18].
There is a need to accurately define LULC
change using geospatial techniques to support
environmental planning. To date, little attention has
been paid to environmental and socio-economic
stability in Tabuk region, which lacks spatial andtemporal information about LULC changes.
Assessing LULC change, therefore, can deliver
essential information to aid environmental
management and planning. The aim of this work is
to assess land use and land cover changes in arid
Tabuk from 1985 to 2015.

2015)
Dataset and Image Pre-processing
Landsat Multispectral Scanner (MSS), Thematic
Mapper (TM), Enhanced Thematic Mapper (ETM+)
and Operational Land Imager (OLI) (path 173 androw 40) for 1985, 1990, 1995, 2000, 2005, 2009 and2015 were downloaded from Earth Explore. Images
were selected during March and April of any given
year to provide uniformity when detecting andassessing LULC change. Images were geometricallycorrected and rectified to the Universal Transverse
Mercator (UTM) coordinate system. Landsat images
acquired at two or more different periods havedifferent amounts of haze and dust in the atmosphereand required atmospheric correction to overcome
these differences [19]. Dark object subtraction(DOS) used to correct Landsat imageries foratmospheric scattering.
Image Segmentation
The land use/cover classification scheme from[20] was modified to account for local fieldknowledge and conditions of the study area to define
four classes of land cover including Bare land,
Urban areas, Agricultural land and Others (Table 1).
ENVI software at scale level 10, merge level 97 andtexture kernel size 3 was used to performsegmentation processes. An overlay procedure doneusing a GIS function with the help of availablereferenced data for all segmented images.

MATERIALS AND METHODS
Study Area
Tabuk has an area of 4212 km2, and is located at
an altitude of 600-800 m above mean sea level:
between 28˚23` to 28˚39 N and 36˚35` to 36˚57 E in
the north-western region of Saudi Arabia (Fig. 1).
The province is considered arid with an annual
rainfall 40 mm, mostly occurring between
Novembers and January with snowfalls every 2-3
years. The primary land use in Tabuk is agriculture.
It is considered being the most important area in the
country for commercial growers. Wheat, fruit, andexport flowers (to Europe) are the main agricultural
products in the study area.

Table 1 Land use/cover classification scheme
NO
1

Class
Bare land

2

Urban areas

3

Agriculturalland

4

OthersDescriptions
Desert sand, mountain,bare exposed rock,
Residential, commercial
and industrial areas;settlements; andtransportation
infrastructure
Cropland and pasture
fields, grassland
greenhouses, and fallow
lands
Dry salt flats and ponds

Change Detection

Fig. 1

Post-classification comparisons were used todetect the nature change of LULC by determining‘from–to’ change by comparing classified images
individually across different dates [21]. The natureof LULC change maps (‘from –to’) were for sevenepochs, namely 1985–1990, 1990–1995, 1995-2000,
2000-2005, 2005- 2009- 2009- 2015, and 1985–

Location of the study area Tabuk, within
Saudi Arabia (Source: Landsat-8 image
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Table 2 Temporal change in land use/land cover for
Tabuk (km2)

Accuracy Assessment

Land Cover Categories

Accuracy assessment measures the degree ofcloseness to true values. Error matrix is a common
method in the accuracy assessment process,including overall accuracy, producer’s accuracy,
user’s accuracy and kappa coefficient (which is a
proportion of pixels that are classified correctly) [22]–[23]. Around 500 points distributed randomly wereidentified on the reference image and attributed to
the four categories. Topographical map, highresolution images, and field data were used as
reference data to assess the image classification
accuracy.
Urban Growth Analysis Tool (UGAT)

Year

Bare

Urban

Agriculture

Others

1985

3986

48.3

112.5

66.1

1990

3927

64.4

152.3

68.8

1995

3840

88.1

226.7

57.3

2000

3652

122.1

357.8

80.3

2005

3465

145

528.3

73.7

2009

3405

203.6

524.4

78.9

2015

3218

315.1

576.6

102.9

The agricultural land for Tabuk in 1985 covered
112 km2, while in 2015 it covered 577 km2, anincrease of 61 %. Urban land increased by 28%(from 48 km2 in 1985 to 315 km2 in 2015) (Table 2).
Both agriculture development and urbanisation
have a similar trend over bare land (Fig. 3). From1985 to 2015, around 767.75 km2 of desert areas
converted to agriculture land and built-up area.
In 2009, agriculture land had slight shrank (from528.3 km2 to 524.4 km2) of the total area, however,an increase in agriculture land by 52.2 km2 wasobserved in 2015.

The dataset of classified images was reclassified
into urban and non-urban areas. Spatial metrics andstatistics technique using UGAT was adopted [18],to analyse urban spatial growth and type of changeover 30-year period. The municipality of Tabuk set
as the Tabuk central area with 1 km2 multi ringbuffer implemented over the study area, using the
average percentage of urban development for all
built-up pixels. The direction of the urban growth for
Tabuk city is presented. The result of urban
development pattern for different periods describedas ‘extension, infill or leapfrog development, overopen space.
RESULTS
LULC maps showed a clear increase in irrigatedagriculture and urban areas over a 30-year period(Fig. 2). Based on the classification results, change
statistics in LULC in Tabuk are summarized (Table
2).

Fig. 3Fig. 2Gain or loss of land use classes acrossseven epochs

Accuracy assessment for LULC classification
generated an overall accuracy of > 92% across all
image years (Table 3), which is the acceptable
standard classification accuracy level of remotelysensed data for LULC [20].
In terms of producer’s accuracy, vegetation andbuilt up classes were over 76 %, and for bare land
were above 97 %. Kappa coefficient of > 0.85 wereobtained from the accuracy assessment for all
images, while for the user’s accuracy all classes
were ranging from 87% to 100 %.

Land use/land cover classification in Tabukfrom 1985 to 2015

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Table 3 User, Producers, Overall accuracy, andKappa coefficient of LULC classification

Table 4 Area of urban growth attributed to eachurban growth typeEpoch1985 to 1990
1990 to 1995
1995 to 2000
2000 to 2005
2005 to 20092009 to 2015

Urban growth type (km2)
Extension
InfillLeapfrog
31.64
4.22
7.33
31.28
9.73
8.73
41.99
6.98
16.09
58.96
7.49
8.82
91.97
3.96
19.97
133.1925.68
30.47

Population Growth and Spatio-Temporal Analysis of
Urban Growth
Urban expansion is based on the relationshipbetween built-up area and population of an area. The
latest demographic survey of Tabuk Province for2016 revealed increase of population from 165 000
in 1985 to 890 922 in 2015 with an annual
population growth rate 2.48.

Fig. 5

Direction of urban growth for each epoch

DISCUSSIONS

Fig. 4

Quantitative results from OBIA classification
allow us to understand spatio-temporal LULC
change pattern. The view of [15], that OBA issuitable for assessing area under mixed urban
agriculture in arid regions, is supported by the
results found in this study. Social and economicchange in Tabuk city over a 30-year period can be
attributed to migration and increases in the militaryforce leading to increased urbanisation that haschanged the demography of the city. Reference [6]showed that migration in the Tabuk region for 1999
was the fourth largest after Riyadh, Makkah (Mecca),
and Eastern regions. Many of the younger
generation choose to leave the Nomadic way of life,
drawn to the city by economic gain and social
benefits [24]. People choose to move to Tabuk togain better health service, education and increased
job opportunities. The continued increase inpopulation leads to a significant impact on thephysical and economic infrastructure, and the spatialand social interaction within Tabuk city. [7].
Increasing population growth through migration
impacts services for urban areas [25], while theadditional pressure on limited natural resources andthe subsequent rise in food insecurity [26].

The urban growth map for 30 years within
15 rings

The major urban growth was noticed in between
time period (2009 to 2015) with around 112 km2 had
gained of built area (Fig. 4).
The urban type result of Tabuk in each epoch
indicated that extension type development in Tabuk
was the main urban growth type by 72%, whereas
infill type growth only 11 %. The leapfrog typegrowth 17 % of total urban land (Table 4). The
growth direction is clearly expanded towards thenorth-west and west of Tabuk city (Fig. 4 and Fig. 5).
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Population size impacts the amount ofagricultural land and water needed to grow food [27].
Rapid
population
growthandresource
mismanagement can result in soil erosion and landdegradation, causing imbalances in the environment[28].
Tabuk considered to be the largest producer ofwheat, olives and grapes in Saudi Arabia, producing
200,000 tonnes of wheat annually [29]. A
considerable increase of agricultural land and builtup areas in Tabuk attributed to increasing demand ofland the growing population. The sharp increase inland use change to agriculture around Tabuk cityreflects the implementation of wheat subsidies
introduced in the 1980s [30]. The Saudi government
encouraged agricultural projects, such as Astra farms
and TADCO, with a view to increasing food selfsufficiency. In 2003, sustainable use of water for
irrigation has been a top priority for Saudi Arabia,
the government restructured agricultural policies toconserve natural resources and increase water use
efficiency [30]. The loss of agricultural areas during
2005 to 2009 epoch coincidence with thegovernment policy.
The trend for agriculture to expand to thenorthwest and southeast of Tabuk city is due to theaccessibility of water from the Saq aquifer.
Increased demand of water for agricultural andurban use coincided with decreasing groundwaterlevels of the Saq aquifer [5]. High demand of
irrigation required for increased area of agriculture
places immense pressure on valuable water reserves,
being the most scarce resources in Saudi Arabia [31].
Agricultural land in Tabuk used pivot irrigation
technique that exhibits relatively low efficiency forwater usage in arid areas using fossil groundwater,which is not sustainable. More than 80% of theusable water for agriculture, industry and daily
consumption is withdrawn annually to total
renewable supply in Saudi Arabia set the country
in extremely high stress on its limited renewable
water resources [32]. Desert climate andunsustainable human activity are creating stress on
and depleting water resources in Saudi Arabia [33].

towards the west and north-western areas of the city,following the location of groundwater aquifer.
Several factors were identified in agricultural andurban area change that can contribute to the
problems of land degradation in Tabuk city.
Intensive crop irrigation of expanding agriculture
across the Tabuk region, increases the risk of landdegradation. Increasing population places additionalpressure on the limited natural resources within thisfragile, arid region. The result of this work would
help government planners and decision makers tomanage agricultural and urban growth in arid
regions. This information is important for further
prediction studies that can indicate potential impacts
on natural resources and provide a spatio-temporal
dynamics of LULC change.
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CONCLUSIONS
Satellite data and GIS are complementary andhave proven to be effective for providing
information of agriculture and urban expansion. The
high accuracy result showed OBIA can be an
accurate LULC extraction method for Saudi Arabia
and in other arid regions. Fast expanding agriculturaland urban areas in Tabuk pose serious
environmental threats that require urgent attention.
Increasing agriculture and urban expansion that
relies solely on groundwater resources isunsustainable and requires diligent management
procedures. The expansion of Tabuk city is more
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[21] D. Lu and Q. Weng, "A survey of image
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[22] G. Rees, The Remote Sensing Data Book.
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[25] S. Eckert, "Urban expansion and its impact onurban agriculture–remote sensing based change
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[28] S. Maisel, Saudi Arabia and the Gulf ArabStates Today: An Encyclopedia of Life in the
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[30] P. Vincent, Saudi Arabia: An Environmental
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[31] F. Gassert, P. Reig, l. Tianyi, and m. Andrew,"Aqueduct country and river basin rankings aweighted aggregation of spatially distincthydrological i," World Resources Institute, ,vol. Working Paper, 2013.
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COMPARISON OF LUNG DAMAGES DUE TO PETROL AND DIESELCAR SMOKE EXPOSURES: HISTOLOGICAL STUDY
Wardoyo, Arinto Y.P.1, Juswono, Unggul P.2, Noor, Johan A. E.3
1Laboratory of Air Quality, Physics Department, Brawijaya University, Indonesia
Jl. Veteran, Malang, Indonesia
ABSTRACT
Background; Motor vehicles have significantly recognized to have a role in air pollution. The emissions
regarding particles and gasses have identified to affect human health depending on the concentration,
constituents, kind of vehicles, and fuels. This study investigated the impacts of the petrol and diesel car smoke
on mice lung. The aims were to observe the mice lung injury caused by the smoke exposures emitted by petroland diesel car. The lung injury was identified by using the histological images. The mice were exposed to thesmoke with a particular concentration conducted by introducing the smoke into the chamber with the dimensionof 30x20x20 cm3 as long as 40 seconds. The mice exposures were carried out daily for eight days. The lunginjury was observed using a Binocular BX-51 Computer Microscope with the 400x magnification to thehistological images. We identified the healthy cells and damage cells to determine the lung damage showed by
the destructive index. The results showed that the mice exposed to diesel cars have higher index rather than thosewith the petrol car exposures.
Keywords: Smoke exposures, Petrol cars, Diesel cars, Lung damage.

assistance that increased the chance of development
cancer [17].
In general, the vehicle smoke exposures haveidentified to affect to a lung damage. Previous
studies showed that particle exposures haveresulted in the respiratory inflammation response[18], alveolar enlargement [19], oxidative stress[20], and alveolar lavage fluids [21]. The allergy
response was the most reported cases [22], [23].
The other circumstances were influenza-like illness[24], alveolar emphysema [25], lung cancer [26],and chronic obstructive pulmonary disease (COPD)[27]. The impacts of the vehicle emissions on lung,there is less information available, especially forthe emissions from the car using a different fuel. In
this study, we tried to observe the effects of the carsmoke exposures on lung damage to better
understanding the impacts of the emissions emitted
by the car operate using diesel and petrol fuel.

INTRODUCTION
The traffic pollutants have significantly
contributed to the air quality and adverse on healtheffects. The car emissions contained somedangerous compounds have triggered healthproblems [1] based on the type of the pollutant
itself [2]. There are two kinds of the fuel used to
run the engine such as diesel and gasoline. The
emissions are in the form of Both types of engine
produced compounds that are in the form of gasses[3] and particles [8]. The emission compounds
consist of polycyclic aromatic hydrocarbon [4],nitro polycyclic aromatic hydrocarbon [5], black
carbon [6], NOx [7], particulate matter in various
size (PM25, PM10, PM2.5, PM1.0, and PM0.1) [8] inthe different concentration depended on theircomposition, blended, driving methods, [9], engine
type [10], and compression ratio [11].
Fine particles (PM2.5) and ultrafine particles(PM0.1) are commonly found in the car smoke [12].
The problem of these particles is due to their size,
made them possible to be in their airborne andinhaled by the human [13]. The result is a healthproblem [2] that has reported mostly in respiratory
diseases because of the particle emissions [14]. The
concentration of fine particle and ultrafine particles
was found high in the area close to Highway [15].
This resulted in the increase of the risk for thepeople living near the highway that had to be
exposed daily [16]. Based on the previous research
about the effect of the vehicles smoke for the traffic

METHODS
General Method
Three different cars were used as the samples
based on their popularity in the Indonesia. The
sample 1 was that the car with the engine capacityof 2000c was operated using petrol fuel. The
sample 2 and 3 were powered using a diesel engine.
To characterize the effect of petrol and diesel car
emission, we prepared 4 groups of mice. The mice
were chosen by their similar characteristic in the502

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With 𝐷𝑒 is destructive index, 𝐷𝑐 is the damage
cell counted, 𝑇𝑐 is total cells counted by adding
the damage cell with the normal once [35].

response of the lungs to reveal the effect of thesmoke with the human respiratory system [28]. The
first group acted as a control that we named thecontrol group. The second group was exposed topetrol car smoke as petrol group, the third labeleddiesel 1 and the fourth called diesel 2 were thesamples overcoming diesel car smoke exposures.
Each of the group excepted control group was
experienced for 100-second exposures with thedose concentration that was set up by introducing
the smoke into a chamber as long as 40 seconds.
The lung of the mice was taken after the 8 exposuredays and observed using a Binocular BX-51
Computer Microscope with the 400x magnification.
Each histological images of the lung were identified
to determine the damage.
To know the concentration of the ultrafine
particles and the fine particles in the smoke, wemeasured the concentration using a P-Track type8525 and a Kanomax model 2443 dust monitor. The
smoke of the car was collected by the airbag; thenthe smoke was injected into the chamber with thedimension of 30x20x20 cm3 with the rate of 2 m/s
for 40 seconds. The total concentration of theparticles in the smoke was calculated by thesumming of the measured particle concentrations.

RESULT AND DISCUSSIONS;
The total concentrations of the ultrafine and fineparticles contained in the smoke presented in Table
1. The particle concentrations are found low for the
petroleum car of (14.88 ± 0.24 x 1011) particles/cm3
for ultrafine and (1.54 ± 0.09) x 10-3 mg/m3 for fineparticles. In the diesel car, the total concentration of
the ultrafine is found much higher than the petrolcar of (60.00 ± 3.20) x 1011 and (102.40 ± 5.60) x
10-11particles/cm3. In case of fine particles, we also
found the similar result by (162.06 ± 6.90) x 10-3
mg/m3 and (376.30 ± 7.73) x 10-3 mg/m3. The
increase of the concentration of ultrafine and fineparticle in the diesel cars was found directly
proportional to the engine capacity. In themeasurement results for both type of particulate,the higher engine capacity resulted in the increaseof the ultrafine and fine particles contained in thesmoke.
Table 1 Total concentrations of ultrafine and fineparticles

Mice Preparation
The mice were treated by following the standardof humane animal care and the guidelines by the
Ethics Committee of Experimental Animal of the
University of Brawijaya. The mice were kept in thequarantine chamber to isolate from any external
pollutant source to avoid the contamination in thestandard light (12:12 dark-light) and standard RHtemperature conditions [29]. To reduce the micestress during exposures, the acclimation processes
were done for 3 days by putting the mice into the
exposure chamber for 100 seconds.

𝐷𝑐𝑐Enginecapacity(cc)

Petrol

2000

14.9

0.2

1.5

0.1

2238

60.0

3.2

162.1

6.9

2500

102.4

5.6

376.3

7.7

In the table, one of the factors that were foundaffecting the smoke ultrafine and fine particle
concentration is the engine capacity. The increaseof the engine size increases both of ultrafine andfine particles in the smoke. However, between the
petrol and the diesel car was found theconcentrations differ in the large number. This
indicates that the engine type affects theconcentration of ultrafine and fine particles in thesmoke [36]. This data are supported by the fact thatthe properties of the fuel used in the combustion
system emitting the significant different amount ofparticles [37], [38]. The diesel engine vehicles had
a more significant contribution in the particulatematter concentration than the petrol onces in theroad.

The histological damage analysis was
conducted by observing the lung sample images byusing the microscope with the magnification of 400
times and were identified by a counting method.
The lung injuries were found as alveolar
geometrical damage [30], loss of alveolar wall [31],hemorrhage [32], and the inflammation responses[33]. The destructive index [34] was used toanalyze the damage level by following the equation(1)
𝐷𝑒 = 𝑇

FPs(x10-3
mg/m3)
Mean
Dv

Fuel
Type

Diesel1
Diesel2

Histological Analysis

Total
Concentration
UFPs (x1011
particles)
Mean
Dv

(1)

503

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

alveolar septum is also found in the image byobserving the loosing of the alveolar wall. The
hemorrhage is also found in the figure by theappearance of the erythrocytes in particular area.

Lung Damage Identification
The lung damages identified in the histologicalimages are found similarly. The alveolus damages(blue dots) that are the geometrical changes boththe shape and size, the inflammation (red circle),and loss of alveolus wall (yellow circle) may as theresult of the oxidative response by the particles [39].

The damages of the lung are analyzed to relate
to the effect engine type. Figure 2 displays the lungdamage indicated by the destructive index for the
car samples. The petrol car has the lowest index
among the samples of 0.45. The diesel car with theengine capacity of 2238 cc has the index of 0.47
and the other diesel car sample with the engine
capacity of 2500 cc causes the lung damage with
the index of 0.46. The different damage of the lung
posed by the diesel car smoke exposure does notshow a significant different.

Destructive Index

1)

Damage Analyst

2)

PetrolDiesel 1

0.45

0.47

Diesel 2
0.46

0.28

Control

2000
2238
Engine capacity

2500

Fig. 2 The destructive lung index for the car
samples.
3)

The lung damage between the control and theexposed samples give a large difference of thedestructive index. This indicates that the car smoke
surely damages the lung tissues. The limitation of
the samples may not show many differences of thelung damage between the petrol and diesel car. The
engine technology may affect the lung damage dueto the particle emission production [47].

4)Fig. 1 The mice lung condition after exposed to thesmoke. (1) Control; (2) Petrol; (3) Diesel 1; (4)Diesel 2
This results in the development of emphysema
in the lung by the work of pro-inflammation
cytokine and anti-inflammation cytokine [40]. The
emphysema is predicted because of the release ofreactive oxygen series (ROS) [41] that loss of thealveolar septum [42], triggered the proinflammatory cytokine [43]. The result is the
inflammation in the lung tissues. However, theinflammation itself has not triggered thedevelopment of alveolar damage [44]. The releaseof anti-inflammation [45] repairs the alveolar andresults in the elaboration of the emphysema. In Fig
1, the alveolar damage can be seen as the irregularshape of alveolar and the enlargement of the area[19]. In the same figure also identified theinflammation area that is believed to trigger theemphysema itself [46]. The depleted of the

CONCLUSION
The different fuel and engine capacity result in
the different concentration of the ultrafine and fineparticles in the smoke. The diesel fuel cars produce
the large particle concentration than the petrol car.
Exposures diesel car smoke to mice cause more thelung damage than petrol car smoke exposures.
ACKNOWLEDGEMENT
All the authors are grateful to Directorate Generalof Higher Education, for providing funding for thisresearch project. The kind hands of Eko Teguh,504

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

Arif Budianto, Mia Anggun, involving in this study
are gratefully acknowledged .

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507

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SPATIAL VARIATIONS OF SURFACE WATER QUALITY AND
POLLUTION SOURCES IN KHLONG U-TAPAO RIVER BASIN
Saudee Maprasit1, Chaisri Suksaroj 2, Vichit Rangpan3, and Rotchanatch Darnsawasdi4
Department of Applied Science, Faculty of Science,Technology and Agriculture,Yala Rajabhat University,
Thailand; 2Faculty of Engineering, 3Faculty of Environmental Management, Prince of Songkhla University,
Thailand1

ABSTRACTMultivariate statistical analysis, cluster analysis, parametric analysis, as well as factor analysis were applied
to analyze water quality dataset including 9 parameters at 21 sites of the Khlong U-Tapao river basin in
Songkhla province, Thailand, from 2007–2015 to investigate spatial variations of water quality and identify
potential sources of pollution. Using cluster analysis to classify the three-periods of water quality variation ineach monitoring site has shown 3 water quality measures: high, moderate and low. Using parametric study todescribe variations of water quality and the significantly identified land use variables affecting water quality,
such as urbanization and industrial land use which are sources of pollution in upstream. However, in midstream,
Economical urbanization is the pollution source while agricultural land use is the pollution source indownstream. Factor analysis identified that the major pollutants in the upstream were turbidity and conductivity
matter from soil erosion in rainy season and industrial wastewater, in the midstream, biochemical oxygen
demand of organic matters from wastewater discharge from domestic settlements were the main pollutants while
in downstream, nutrients from agricultural practices were the major pollutants. From upstream to downstream,bacterial pollutants were the main pollutants from all activities. These results provide fundamental information
for developing better water pollution control strategies for the Khlong U-Tapao river basin.
Key words: Water quality; Spatial variations; Multivariate statistical analysis; Khlong U-Tapao river basin

as season and land use change are considered toinvestigate impact on water quality [6]. Seasonalchange and urban land use change is the impacts on
surface water quality, for example how urban
scenarios encourages in low, normal and commercial
urban growth are impacts on water quality [7].
Furthermore, water quality changes by seasonalchange and nutrients loading from land degradation,
sediment with nutrients from agricultural land use isdamaging to catchment aquatic systems, almost ofpollutants from point source of industrial land use
such as wastewater discharge. Population growth,
unplanned domestic, deforestation, farming andlivestock intension, agriculture expansion andinfrastructure are human activity which differently
impact on water quality.
Land use is the major source of pollution in riverwater basin. All relationship there are the question
what is the affection land use change to water
quality, what is the season factors causing different
land use and transformation and what is theconsequence of the results to water quality. Land use
type, occupation and transformation causing todifferent hydrology and what is the water quality
outcome. Therefore, the study in water quality
management must to know how the relationship ofwater quality by land use change with seasonalchange.

INTRODUCTION
Water, the one fourth natural resources fordevelop human life quality. The drive source ofvarious systems for example socio-politicoeconomical system of human activities. There areurbanization,
agricultures,aquaculturesandindustries. Water quality, the indicator was pointed
suitability which relevant to characteristics ofphysical-chemical-biological properties for use ineach activities of human life execution. A
development is related to water quality degradation[1]. One of the Nation significance natural resource
concern issue is water quality management [2]. The
execution contains various components anduncertainty of qualitative and quantitative
information from the interrelationship in their [3],[4]. The main component influence water quality todegradation is products from point-nonpoint sourceof human life development, a pollution source towater quality. The various land use leachate is amajor issue in study and management [2].
The obstacle of water quality management islarge scale and plenty of factors, including
population growth, land use in each pattern andpractice of urbanization, agriculture, aquaculture andindustry comprehensive all activity in water supply
system [5]. Therefore, to evaluate the state of water
quality, the spatio-temporal influential factors such
508

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

Water quality studies and management in Khlong
U-Tapao river basin for problem solving arecomplex system education that focused on related
factors based on temporal-spatial change. Study inwater quality and management just to study behavior
and trends of dynamic change include relationshipand interaction of variables in the system under
different of spatial and temporal including land usechange and seasonal parameter. The objectives ofthis study are quantified the contributions impact of
spatial-temporal change to water quality andrecognize water quality system. In addition to
discuss and point pollution sources for how to solve
the impact of land use practice and human driven
force on water quality and what feasible actions
should be taken from causing adverse effects in eachseason.
STUDY AREA
Khlong U-tapao is a sub-basin of Songkhla lakebasin located at southern part of Thailand. The basin
is about 60 km long from north to south, and 40 km
wide from west to east, and total coverage is about
2,805 square kilometers [8], [9], [10] (Fig.1). There
are 7 district such as Sadao, Namom, Hatyai, Khlong
hoi kong, Bangklam, Ratpum and Kuanniang.
Pollution sources in Khlong U-Tapao river basin
come from various land use which divided that,
there are; 1) Residential Land Uses which are more
found in plain area or low land for example in
Hatyaimunicipality,
Khohong
sub-district
municipality,
Banprumunicipality,
Sadao
municipality and comprehensive area of sub-district
administrative organization. 2) Agricultural Land
Uses, for example para-rubber plantation, paddy
field, fruit plantation, palm plantation, farm of cows,
buffalos and goats including shrimp farms. The areaof paddy field is on low land of the north or
upstream of basin, para-rubber and palm plantationis on the south or begin from midstream todownstream of basin. Fruit plantation is distribution
around of rural community area. 3) Forestry, which
are area of tropical rain forest, swamp forest, botherpeat swamp and mangrove swamp and deciduous
forest. Almost of tropical rain forest is found on thewest of basin. 4) Industrial land use is a main ofvarious para-rubber process and frozen foods. All isfound most in urban community. 5) Water resources
and 6) Lowland and bare land.

Fig.1 Khlong U-tapao river basin Map and land-use
Table 1 water quality monitoring sites
Geographic Co-System
Location area
Longtitude
Latitude(Easting)(Northing)100.490
6.593
UT01
Samnak Taeo SAO
100.4396.636
UT02
100.4106.599
UT03
100.417
6.632
Sadao TM
UT04
100.396
6.632
UT05
100.430
6.665
UT06
100.436
6.670
UT07
Prik SM
100.4366.702
UT08
100.446
6.776
UT09
Tha Poh SAO
100.4416.820
UT10
Phang La SM
100.466
6.853
UT11
Phatong SM
100.4596.865
UT12
100.4606.881
UT13
100.457
6.897
UT14
Ban Phru TM
100.4426.928
UT15
100.466
6.977
UT16
Khohong SM
100.465
6.984
UT17
Khuan Lang SM
100.455
7.029
UT18
Khlong Hae TM
100.471
7.070
UT19
Mae Tom SAO
100.468
7.105
UT20
Ku Tao SM
100.458
7.124
UT21
Note: SAO: Subdistrict Administration Organization, SM:
Subdistrict Municipality, TM: Town Municipality (Department ofProvincial Administration, Ministry of Interior, 2013).
station509

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

The secondary data of water quality comefrom 21 stations along the Khlong U-Tapo river
basin (Fig.1, table 1) and cover 13 administrative
districts, there are 4 sub-district administration
organization (SAO), 6 sub-district municipality(SM) and 3 town municipalities (TM) [10].
In this basin area was separated in to 3 part suchas upstream part, it started from station UT01 to
UT09,
midstreamfrom UT10-UT17
anddownstream from UT18-UT21.

Table 2 water quality variations in dry and rainy season
Season /parameter

WT

pH

TB

CD

DO

BOD

TCB

FCB

NH3N

Min.

26.6

4.4

4.3

0.18

0.50

0.40

78.00

78.00

0.00

Max.

34.0

9.2

110.0

15064.0

7.00

16.20

1.60E+05

1.6E+05

0.51

Mean

30.0

6.9

50.8

357.26

4.01

4.33

1.19E+04

1.1E+04

0.07

Dry

SD.

1.6

0.7

24.2

1667.67

1.40

3.40

2.73E+04

2.7E+04

0.11

Min.

26.0

4.6

3.0

0.01

0.10

0.50

20.00

20.00

0.00

Max.

33.0

8.9

357.0

10680.0

7.60

32.20

1.60E+05

1.6E+05

0.68

Mean

28.7

6.9

77.3

277.85

3.95

3.78

1.83E+04

1.8E+04

0.06

SD.

1.3

0.9

76.9

987.07

1.36

3.03

4.01E+04

4.0E+04

0.11

Rain

MATERIALS AND METHODS
Data
Water quality parameters was collected fromsecondary data of pH, water temperature (WT),
turbidity (TB), dissolved-oxygen (DO), conductivity(CD), biochemical-oxygen-demand (BOD), TotalColiform-Bacteria( TCB) ,Nitrogen-Ammonia(NH3-N) and Fecal-Coliform-Bacteria (FCB) from
Regional Environmental Office 16, Songkhla from2007-2015. Land use was separated into 3 types ofagriculture, industry and urbanization. Agricultural
data was gathered from Provincial Agricultural
Extension Office, Sadao district, Songkhla.
Industrial data was gathered from Songkhla
Provincial Industry Office. Urbanization was
gatheredfrom
DepartmentofProvincial
Administration, Ministry of Interior,

Allyear

Min.

26.0

4.4

3.0

0.01

0.10

0.40

20.00

20.00

0.00

Max.

34.0

9.2

357.0

15064.0

7.60

32.20

1.60E+05

1.6E+05

0.68

Mean

29.2

6.9

68.2

307.48

3.97

3.99

1.61E+04

1.6E+04

0.06

SD.

1.5

0.9

65.0

1282.40

1.37

3.18

3.62E+04

3.6E+04

0.11

The result showed that WT, pH, DO and NH3-N
in dry season was higher than rainy season. In
another parameter, BOD, CD, TB, TCB and FCB
was higher during rainy than dry season because ofclimatic and hydrologic change [8].

Statistical analysis
A statistical analysis is used for a normal
distribution. Correlation is studied for variable
relationship by multiple independents [11], [12].
Cluster analysis is used to identify variations ofwater quality. Factor analysis is applied to use for
identified pollution factors which related to pollution
sources of river basin and performed this suitable
method by Kaiser-Meyer-Olkin (KMO) and Barlett’s
test [13].
RESULT AND DISCUSSION
Water Quality Variations by Seasonal Change
The variations of water quality by seasonalchange presented in fig.2 and table 2, in all the year,
WT varied from 26.0-34.0 0C, pH from 4.4-9.2, TB
from 3.0-307.48 NTU, CD from 0.01-15,064.0µs/cm, DO from 0.10-7.60 mg/L, BOD from 0.4032.20 mg/L, TCB and FCB from 20.0- 1.60E+05
MPN/100mL and NH3-N from 0.00-0.68 mg/L.

Fig. 2 water quality variations in dry and rainy season

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Clustered water quality variations were
presented in fig.3 and identified site station ofpollution sources that upstream zone was site UT5and UT7, midstream zone was site UT12, UT15 anddownstream was UT19. Follow by table 4.

Cluster Analysis of Water Quality Variations
Two-step Cluster analysis for continuous data
was applied to classify the set of water quality
variations into 3 variations periods follow by fig.3
and table 3, WT, CD, TCB and FCB were classified
into 2 periods but pH, BOD, DO, TB and NH3-N
were classified into 3 periods.

Table 4 pollution source in each zone.
Water
quality

Table 3 Water quality period by cluster analysis
parameters
WT
pH
TB
CD
DO
BOD
TCB
FCB
NH3-N

Water quality variations period
Period 1
Period 2
Period 3
Low
Moderate
High
29.78
28.49
7.02
6.94
6.72
77.10
69.25
30.26
574.34136.30
3.89
4.00
4.80
4.82
3.85
3.03
8497.527977
17607.89
6790.73
0.152
0.070
0.057

Low
Moderate
High

Site station of pollution sources ineach basin zone
upstream midstream downstream
5, 7
12,15
19
3,6,9
13,16,17
18,20,21
8,4
14

Factor Analysis of Water Quality Variations
Factor analysis to identify group of water quality
variation and the main pollution factors whichshowed results in table 5 and table 6;
Table 5 results of KMO and Bartlett’s sphericity
tests

Water quality in period 1 presented low quality
by high value of pH, TB, CD, BOD, TCB, FCB,
NH3-N and low value of DO whereas high water
quality was presented by contrary.

Parameter
WT
pH
TB
CD
DO
BOD
TCB
FCB
NH3-N

Mean

SD.

29.23
7.13
61.12
349.88
4.45
3.38
1.69E+04
1.34E+0
4
0.09

1.48
0.61
58.74
1017.75
1.42
2.54
3.57E+04
3.23E+04
0.16

Bartlett's Test of
Sphericity
Approx. ChiSquare

KMO

586.901

df

36
0.516

Sig.

0.000

In factor analysis, the KMO and Bartlett’s
sphericity test results are 0.516 and 586.901 (df=105,
p<0.001), respectively, showing that this method
was effective in reducing dimensionality [13].
Table 6 water quality factors on rotated component
matrix during dry and rainy season
Variables
TCB
FCB
WT
pH
NH3-N
DO
BOD
CD
TB

Fig. 3 water quality variations in dry and rainyseasonNon-rotated Component
matrix
1
2
3
4
.944
.927
.242
.738
.219
.630
-.328
-.721 .373-.294 -.341
.589
.247
.201
.274
-.485 -.310
.406
.221
.543
.358 -.460.249 -.489
Eigenvalue% of variance

511

Rotated Component matrix
1
.962
.970

2

.729
.707
-.569

1.961
21.789

3

.208

.416
-.766
.657
-.281

1.417
15.742

1.342
14.916

4

.646
-.771
1.217
14.120SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Cumulative %21.78937.53052.44666.566
pollution of organic matter which almost discharge

from large and economical urbanization. This zone
is in Hatyai district where is a tourist attraction.
Some of part are factories of palm-oil, animal-feed
and frozen food.
In downstream, main pollution source was UT19
which factor 2 represents pollution of nutrients inagriculture and aquaculture area. In this area is coverof small urbanization with paddy farm and agropastoral land.
FCB and TCB are bacterial pollution along river
basin. There is problem in many part of river fromupstream to downstream which influenced bywastewater discharge from domestic settlements.
The management should be concentrate in rainyseason more than dry season.
Spatio-temporal pollution sources can conclude
in table 7. In rainy season, upstream should beconsider site 5 and 7 areas, midstream should beconcentrate site 12 and 15 areas and in dry season,
downstream should be intensify site 19 areas.

The first fourth rotated factors witheigenvalue of 1 or greater are extracted using
Varimax with Kaiser normalization, which can
explain the total variance in water quality data set
amount 66.565%.
Factor analysis identified 4 factors such as factor
1, which accounted for 21.8 % of the total variance,
was strong correlation with TCB and FCB. Thisfactor could be interpreted as “bacterial pollutants”
influenced by point sources such as urbanization
with surrounding urban rim and human made areasuch planted forest, agro-pastoral land and barren
land [14]. Factor 2, which implied 15.7 % of thetotal variance with moderate correlation on WT and
pH and primarily negative correlation on NH3-N.
Factor 2 suggests “nutrient pollution and transform”,
It presented natural factors impacted by seasonalchange [8], [15]. The inverse relationship between
temperature and nitrogen forms is natural process ofnitrogen cycle because warmer water is cause of
nitrogen transformation by biological process [14].
Almost of this pollutant could be cause by non-point
sources such as agricultural runoff and or domestic
sewage discharge directly into river basin without
treatment [16].
Factor 3 explained 14.9% of the total varianceand had moderate correlation with BOD and strong
negative loading on DO. This factor represented as“organic pollutants” which influenced by point
source such as municipal and industrial effluents[16], [17] resulting from rapid urbanization as wellas economical area.
The last factor, factor 4 accounted for 14.1% of
the total variance and had moderate correlation with
CD and strong negative correlation on TB which
represented “solids pollutants” and explained byinfluenced pollution originating from industrial
sewage [16], [17].

Table 7 Source and season identification of pollution
Basin zone
upstream
Midstream
downstream

Site
UT05, 07
UT12, 15
UT19

factor4
3
2

Season
Rainy
Rainy
Dry

CONCLUSION
Water quality variations by spatial patterns
could presented various periods of water quality bymultivariate statistical analysis, moreover, thismethod could explain group of water quality
variation in each part of land use. Upstream zone
should be consideration in area of industry andurbanization, midstream zone should be concentratein area of economical urbanization and downstreamzone should be management in area of agriculturalland use as seasonal strategies. Rainy season,
rainfall and level of water are main cause of organic
pollutants from land surface to river surface both ofrural and urban area. Pollutants and waste
controlling in these areas may be could reduce water
quality degradation. For example, sufficiently
construct waste water treatment plant in urbanization,
wastewater discharge controlling from industry andagricultural area restricting.

Pollution Source Identification
In upstream area, main pollution sources werefrom site monitoring UT05 and UT07 which factor 4
reflects the solids pollutants both of dissolved andnon-dissolved solids. Almost turbidity in this area
discharged during rainy season which eroded soil
from land surface to river. Electrical conductivity ishigh by industrial wastewater discharge from manypara-rubber factories including rubber sheet, glove
and latex.
In midstream area, main pollution sources werefrom UT12 and UT15 that factor 3 displays

ACKNOWLEDGEMENTS
The authors are extremely grateful to the Officeof the Higher Education Commission, Thailand’s
ministry of education, Prince of Songkhla University(PSU) and Yala Rajabhat University (YRU). Finally,
we would like to thank to the Songkhla’s state
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Khlong U-Tapao river basin, Thailand”, Int. J.
of GEOMATE, Vol.11, 2016, pp.2763-2770.
[9] Gyawali S, Techato K, Yuangyai C andMonprapussom S, “Assessment of Surface
Water Quality Parameters and Their Variations
for Effective River Monitoring System: A Case
Study of U-Tapao River Basin”, J. of Environ.
Res. Vol.34 (2), 2012, pp. 89-106.
[10] Regional Environmental Office 16, Songkhla,“Water quality in Khlong U-Tapao river basin”,
year reports of 2006-2014.
[11] Ethington B., “Things to know about regression,
EDPR 7/8542, Spring, Retrieved on 07 June2013 from https://umdrive.memphis.edu/yxu/
public/Bunty' s%20REGKNOW.pdf

agency for making available their all data such as
Regional Environmental Office 16, Songkhla
Meteorological department, Regional Irrigation
Office 16, Provincial Agricultural Extension Office,Sadao district, Songkhla, Songkhla Provincial
Industry Office and Department of Provincial
Administration, Ministry of Interior.
REFERENCES[1] Praxeda KM, “Water quality management andsustainability: the experience of Lake Victoria
Environmental Management Project (LVEMP),
Tanzania”, Physics and Chemistry of the Earth,Vol.28, 2003, pp. 1111–1115.
[2] United State Department of Agriculture(USDA), National water quality handbook,
2003, introduction.
[3] UNESCO/WHO/UNEP, “Water Quality
Assessments - A Guide to Use of Biota,
Sediments and Water in Environmental
Monitoring” Second Edition. Published by
E&FN Spon, an imprint of Chapman & Hall,
1992, 1996.
[4] Li YP, and Huang GH, “Two-stage planning forsustainable water-quality management under
uncertainty”, J. of Environmental Management,[12] Patrasinee P, “chapter7: multiple linear
regression analysis”, Statistics for Scientificresearch, 1st ed. Bangkok: Chulalongkorn
University, 2007, pp. 279-302.
[13] Vanichbuncha K, “Statistics for research.
Faculty of commerce and accountancy.
Chulalongkorn University, 2009, pp. 202-228.
[14] Maillard P and Pinheiro Santos NA, “A spatialstatistical approach for modeling the effect of
non-point source pollution on different water
quality parameters in the Velhas riverwatershed-Brazil”, Journal of Environmental
Management, Vol.86, 2008, pp. 158-170.
[15] Singh K P, Malik A and Sinha S, “Water quality
assessment and apportionment of pollution
sources of Gomti river (India) using
multivariate statistical technique: a case study”,
Analytica Chimica Acta, Vol.538, 2005, pp.
355-374.
[16] Mei K, Liao L, Zhu Y, Lu P, Wang Z,
A.Dahlgren R, Zhang M, “Evaluation of spatialtemporal variations and trends in surface water
quality across a rural-suburban-urban interface”,
Environ Sci Pollut Res. Vol.21, 2014, pp. 80368051.
[17] Zhao J, Fu G, Lei K and Li Y, “Multivariate
analysis of surface water quality in the Three
Georges area of China and implications forwater management”, Journal of Environmental
Sciences, Vol.23(9), 2011, pp. 1460-1471.

Vol.8, 2009, pp. 2402–2413.
[5] UNICEF/WHO, “UNICEF Handbook on Water
Quality”, New York, 2008, pp. 1-2.
[6] Kannel PR, Lee S, Lee YS, “Assessment of
spatial-temporal patterns of surface and groundwater qualities and factors influencing
management strategy of groundwater system inan urban river corridor of Nepal”, J. ofEnvironmental Management, Vol.86, 2008, pp.
595-604.
[7] Cyril O, Wilson and Qihao W, “Simulatimg theimpacts of future land use and climate changes
on surface water quality in the Des PlainesRiverwatershed,
ChicagoMetroplitan
Statistical area, Illinois”, Science of the Total
Environment, Vol.409, 2011, pp. 4387–4405.
[8] Maprasit S, Suksaroj C and Darnsawasdi R,“Temporal patterns of water quality variation in

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DIVESIRY AND POLLEN MORPHOLGY OF IMPORTANT TREESPECIES OF RANIKOT FORT, SINDH, PAKISTAN.
Nabila Shah Jilani1, S.S Hassney2, Muhammad Tahir Rajput3 and Feroza shar Baloch4
Institute of Plant Sciences, University of Sindh, Jamshoro, Sindh, Pakistan.

ABSTRACT
Ranikot Fort is a talismanic wonder of Sindh, Pakistan. This fort is one of the largest forts of the world
and approximately of 35 km in length. Visitors and researchers can reach at this beautiful location andhistorical mystery via Hyderabad to Sann by travelling about 90 kilometers north of Hyderabad 30 kilometersfrom town of Sann. All construction in the Ranikot has its own distinctiveness and magnificence. The
exploration for the tree plant diversity of fort area was carried out to find out range of important tree plants
diversification in this fort area because two species reported threatened in my pervious publication. Frequent
survey was conducted throughout the years to record vegetation diversity present in Ranikot fort area. Plant
materials were collected from the site area, herbarium sheets were prepared by using slandered techniques.
Pollen morphology of important tree species has been investigated by Scanning electron microscope.
Considerable pollen diversity has been particularly pollen shape, size, aperture and exine ornamentation.

Key words: Pollen, Diversity, Ranikot Fort.
INTRODUCTION
The exploration for the tree plant diversity andpollen morphology of fort area was carried out tofind out range of tree plants diversification in thisfort area. Experts of archeology and history have an
opinion that Ranikot was built some 500 BC before.
Talpur in 1819 refurbished this fort late on. Settler
used the fresh spring water to irrigate the field for
growing of their food. This is the only fresh water
found in the area. There are very few tree plants
present in Ranikot, main reason is shortage ofwater, local people of Ranikot are totally dependent
on plants for their survival. They cut, chop trees formaking their homes and for fuel. There are very few
threes left. Two of tree species reported threatened
due to extreme use of local people. (Jilani et al.,2014). A large numbers of plants and animal fossils
have been reported by many scholars, historian andplaeobiologist (Khan & Rehmatullah 1968; Khan
and Rajput 1976; Rajput & Khan 1982; Rajput et al1985 & Ahmed et al, 2001).

Figure.2: Ranikot Fort wall showing
resemblance with the great wall of China.

Figure. 3: Tribal people of Ranikot Fort
The people of Ranikot live very simple life
without having any facilities of life. They might
unaware of the advancement of the world. Theirkids don’t get education, no medical facility, noroads no transport is available for them. Theirhomes are made up of four pillars of wood,covered with dry grass roof. They cut trees to getwood for different purposes. This is the reason ofdisappearing trees from Ranikot.

Figure. 1: Beautiful picture showing the view ofRanikot fort entrance.

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Figure.7:

MATERIAL AND METHODSFrequent survey was conducted throughout theyears to record vegetation diversity present in
Ranikot fort area. Plant materials were collectedfrom the site area, herbarium sheets were preparedby using slandered techniques. All the plants were
documented using protocol of plant identification
described in the flora of Pakistan, Nasir & Ali (1970- 1989), Ali & Nasir (1989 – 1993), Ali & Qaiser(1993 – 2008), flora of Karachi, Jafri (1966) andflora of Indian desert, Bhandari (1987). ScanningElectron Microscopic examination of pollen was
carried out by using Jeol (JSM-T-200) microscope.
RESULTS AND DISCUSSIONS

Fig. 8:Fig. 4:

Fig. 9:Fig. 5:

Fig. 10:
Fig. 6:515

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Fig. 11:(Fig 4, Acacia Senegal (Linn.), Fig 5, 6, equatorial
view and exine pattern Prosopus Sineneria(Linn.), Fig 7, 8, 9 Ziziphus nummularia (Burm. f.)
Wight & Arn., Fig10, Tamarix dioica Roxb. ex.
Roth. Fig 11, Salvadora oleoides Decne.)

2.

Jilani. N.S, S. S. Hassney, M.T. Rajput (2015)
Threatened species of Ranikot Fort area a
Historical heritage of Sindh, Pakistan. Sindh
University Research Journal. 149-152.

3.

Ahmed, B, MTM Rajput & K.M. Khan (1989),
Laurinoxylonellipticum Sp. Nov., a new
petrified taxon of lauraceae from Tertiary
deposits of Sindh, Pakistan. Pak. J. Bot.40(1).

5.

Ahmed Sultan & B.B. Steverd. Grasses ofwest Pakistan Lahore 1958.

6.

Ali, S.I. & M. Qaiser (1986) A
phytogeographic
analysisofthePhanerogams of Pakistan and Kashmir.
Proc. Roy. Soc. Edinb; 89B: 89 – 101.

7.

Ali, S.I. & M. Qaiser (Eds), 1993 – 2008,
Flora of Pakistan – Karachi.

8.

Ali, S.I. & Y. J. Nasir (Eds), 1989 – 1993,
Flora of Pakistan – Islamabad, Karachi.

9.

Bhnadari, M.M. (1975), Flora of IndianDesert. Scientific publishers, Jodhpur.

11. http://pakistanpaedia.com/landmarks/
ranikot/ranikot_fort.htm
12. Nasir E, and Ali S.I. (Eds), 1970 – 1989,
Flora of Pakistan.
13. Rajput MTM & K.M. Khan (1984),
AraucarioxylanSp. nov. A new species ofgymnosperm wood from Manchhar
Formation. Pak. J. Bot. 16(1); 53-76.

REFERENCES
Jilani, N., Tahir, S. and Rajput, M. (2014)
Vegetation of Ranikot Fort Area, a Historical
Heritage of Sindh, Pakistan. American Journalof Plant Sciences, 5, 2207-2214.

Akhter R. (2003) A plant guide to National
Park Khirthar and adjoining areas. Premier –Kufpec, Pakistan B.V. 1

10. Jafri S.M.H (1966). The Flora of Karachi –The book corporation, Karachi, Pakistan.

SEM study of five tree species was conducted,
considerable diversity have been observed amongpollen characters particularly type, shape, size andaperture. Acacia Senegal (Linn.), Pollen grain inpolyads 12 celled, 40-45 µm in diameter. Pollen
grains present in polyads, non aperturate, eachpolyads consists of 12 cells. Prosopus Sineneria(Linn.)
Prolate Tricolporate,, 35 µm length,
22µm width. Tricolporate grain with linear, long,narrow colpi. Ziziphus nummularia (Burm. f.)
Wight & Arn., Pollen Sphroidal, tetracolpate,22.2 µm diameter. Grain is spheroidal, tetracolpate,
due to the broad four colpi folds it gives appearance
like a broad rhomboid grain. Tamarix dioica
Roxb. ex. Roth. Prolate, Tricolpate grain 16 µm
long, 6 µm wide. Salvadora oleoides Decne. Grainis prolate to sub-prolate, Tricolpate, 15.2 µm, 8.2µm wide. Tricolpate grain, colpi elongated,tactum reticulate with murate pattern.

1.

4.

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RELATIONSHIP BETWEEN PAVEMENT TEXTURE AND
MOVEMENT
1

Yuki OGIMOTO1,Kazunari TANAKA2and shin YOSHIKAWA3Engineering, Osaka Institute of Technology, Japan; 2,3Osaka Institute of Technology, Japan
ABSTRACTThe purpose of this research is to design pavement taking pedestrians into consideration, especially the elderly,
which is the fastest growing age group in Japan. In recent years, the awareness of street landscape has increased,
and the development of roads taking pedestrians into consideration has become more common. It is consideredthat the walking path of people is changing due to the design of sidewalks and the walking environment. By
analyzing the pavement, we believe that we can utilize this for urban planning, by clarifying the route according
to individual’s age. In previous studies, walkability tests and analysis were performed for each type of pavement.
There are few studies on public spaces. If it is possible to grasp the respective walking route by attributes such as
age group, then this can lead to improve functional design universally. It will potentially allow people to be able
to more easily walk on pavement.
Keywords: stationary people, pavement, open space, public space
INTRODUCTION

Ultimately, we will refine it to detailed analysis
that finds how space design affects pedestrian
influence, we will obtain basic knowledge of analysis
using physical data, while acquiring a large amountof pedestrian behavior data.
In order to grasp the influence of the spatial shapeand the influence range, first, we shoot a moving
image and capture the behavior of the person.
We extract external factors that are appear to beaffecting people. Furthermore, we will calculate
specific figures and analyze them, Analysis is madeon the relationship between the elements of the spatial
shape extracted by the survey and human attributes.
We then express the influence range and influence ofthe grasped space shape on the map, using GIS frompedestrian data.

Designers are trying to create space that various
people can use easily. However, there are actuallyvarious aspects to consider for design.
For example, some people are sitting on the chairor bench, others are leaning walls etc., these actions
are usually performed unconsciously.
A difference arises from how to use the spaceconsidered at the planning stage, stemming fromunconscious behavior. People select places fromspace, at that given time, it is influenced by physicalfactors and human factors. There is a difference ininfluence, depending on number of people, sex andage.
In this research, we focus on human behavior andspace shape for busy places that many people use, andto understand human behavior and grasp the influenceof space shape by classifying attributes such as age
and sex. Therefore, from a human behavior point-ofview it becomes possible to visualize, by discovering
the influence range and influence of people and space
shapes. It would be one of the effective means formaking new town planning.

Target area
For the target area, we wanted to use a space that
had various features common in public places suchas; pillars, walls, stairs, monuments etc.
Also, we wanted to consider the number of users
around the ground, rather than only paying attention
to the design part of the space.
In this research, we will cover a space used mainly
by pedestrians. A preliminary survey was conductedin the open space around Osaka station, and a placeconsidered to be similar was set as the target site. In
addition, this survey is a place with many railway
stations.

Purpose and method of research
We find the relationship between thecharacteristics of space shape and pedestrian features,grasp the relationship with the place of each action
and the shape of the surrounding space. It is
ultimately best to propose a design taking into
consideration human behavior.
In this research, we will quantitatively find theinfluence of invisible design, utilizing physical andpedestrian behavior data obtained from a field survey.

Fig1 An example stationary people
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Investigation

analysis

For the survey, first, we shot video to capture thelocation and constituent elements of the people
standing around, then we plot this on CAD andconsider this place as a place where people are likely
to be stationary, and the hypothesis of the cause fromthe plot (Figure 2). For the flooring surface, it was
concrete tiles, and its pattern consisted of different
colors at equal intervals. Braille guide blocks for thevisual impaired were also present.
What we noticed when plotting is that when one
person arrives and stands in place, they tend to it at awall etc.
On the other hand, when multiple people stood inplace, it was noticed that the distance from any
feature (such as a wall) was far compared to the caseof a solo individual. The surface was not unified, andeach place had different patterns.
We focused on two things here. The first was on theexistence of a feature and the spatial shape of thepavement, and the second was the relationship of thenumber of people at the time of capture and looking
at these two points of interest. As a result, when it
comes to staying in one spot, people decided to stayat a place that they feel "a sense of security".

In order to grasp this "sense of security" from theresults of the survey, two points of interest wereanalyzed and quantified. In the analysis, seven kindsof actions were used; the composition of the numberof people, the time, the distance to the surrounding
features etc. For the attribute information of theperson, I converted the strength of the relationship bycorrelation analysis. The stationary person and the
distance from the wall became the strong correlation
element. A significant correlation is seen. Wegraphed the results, when an individual is stationary
alone, they are often near to the wall compared to thecase when there are two or more people stationary(Fig.3, Fig.4 )From this result, it can be said that when being alone,
the induvial wants a feeling of being “secure”.

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6m

Fig4
Relation between a Stationary
person (individual) and the Nearest
Distance to a feature/object

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 m

Fig.5 Relation between stationary people (two or more)
and the Nearest Distance to a feature/object
Fig2 stationary people(two or more)

Fig.6 The influence for the people by the wall

Fig3 stationary people

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Analysis that replaced walls with people

Floor design

According to the previous analysis, it is assumed
that when a small group of people are standing
together they can feel "relief" similar to standing neara wall.
Therefore, when two or more people were
stationary, we analyzed them with the same layer as awall. As a result, it was possible to obtain a graphshowing the same tendency as in the case of standing
alone by one person. From these results, it waspossible for residents to feel that they feel "secure"
where they are unconsciously standing.

In the previous study, the walking trajectories ofpedestrians were caught. The pavement; the pattern of
the floor surface was not uniform from thephotograph, it was different in section B (Figure 11).
On the other hand, the floor surface of section A andsection C was the same pattern.
Figure 12 is a diagram in which the area shown in
the photograph is meshed with the tile of the floor
surface with the camera angle adjusted to directly
above. The trajectory at this time is caught in 15
seconds. Focusing on the number of trajectories, we
see that the interval of B is smaller than that of A andC. That is, from Figure 12, pedestrians do not walkalong the center of the road relatively. They tend towalk along it in a parallel manner, or across it in aperpendicular manner.
There is a possibility that the pedestrian selects thespace which they like and avoid space which they
don’t unconsciously considering the pattern of thefloor surface from these two figures.

Fig.7 Wall and People

Fig.8

Wall substituted with People

Fig.11 Example: Pavement and Movement inMarket Place

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6m

Fig.9 Relation between a Stationary person(individual) and the Nearest Distance to afeature/object

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6m

Fig.10 Relation between stationary people (twoor more) and the Nearest Distance to afeature/object

Fig.12 The Trajectory of the People
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017[3] Sattoshi AMAGAI Zyun HIROTA Evaluation ofdiversity in walking space Crowd flow and personal
space

Fig.13 Relation of the Movement and Pattern of thePavement

CONCLUSION
In this research, we focused attention onpedestrians in public spaces in the city and observed
and analyzed them. In the analysis, we clarified thetendency of the number of people in stationary
positions and found the selection by conditioning of
being stationary. In addition, with walking they draw
different trajectories for each floor surface, so it isconceivable that the features. The floor surface may
have a psychological influence on route selection at
the time of walking and selection of stationary
position. When creating space for pedestrians, it isnecessary to consider the characteristics of the floor
surface for designing.
REFERENCES[1] Co., Ltd.New construction company: New building July 2011 issue: Osaka station design
drawing[2] Yurika YOGO, Kazuto HAYASHIDA, Hitoshi
WATABE Spatial usage behavior by age in station
concourse pp651 ~ pp652 2012

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

REMOVAL AMMONIA FROM LANDFILL LEACHATE USINGULTRASONIC IRRADIATION PROCESS
1Sartaj M.1, Tobalt A.2, and Kennedy K.3
University of Ottawa, Ottawa, Ont., Canada K1N6N5

ABSTRACT
Landfill leachate could contain high concentrations of ammonia, which results in environmental consequences if
not removed before discharge. Ultrasonic (US) irradiation has been reported to be a promising technology forremoving ammonia from aqueous solution. The main objective of this study was to investigate the efficiency of US
technology for removal of ammonia from landfill leachate. A series of laboratory batch experiments using synthetic
solution (3,000 mg TAN/L) as well as two real landfill leachates (1,730 and 3,440 mg TAN/L) were carried out in
triplicates. Heat only experiments using a hot water bath evaporation tests with samples open to the surrounding
atmosphere were carried out to quantify the contribution of different mechanisms. Statistical analysis of the TAN
removal data showed that there was no significant difference between the two leachate sources tested in this study
for total TAN removals. The contribution from non-thermal effect (US), thermal effect (WB), and volatilization was
estimated to be 61.5%, 36.7%, and 1.8% of total TAN removal respectively.
Keywords: Anaerobic Digestion, Biogas, Municipal Solid Waste, Organic Loading Rate, Leachate.

treatment, microwave radiation, air stripping, chemical
precipitation, adsorption/ion-exchange, and ultrasonicirradiation [2], [3], [9]. Ultrasonic (US) irradiation has
been reported to be a promising technology forremoving ammonia from aqueous solution andcompared to the conventional methods, it can bringseveral benefits such as environmentally friendly, lowcost, selectivity and compact. Contrary to otherprocesses which are negatively affected by presence ofsuspended solids, US efficiency may even improve by
increase of turbidity or suspended solids.
Considering the above, the main objective of thisstudy was to investigate the application of US
technology for removal of ammonia from landfill
leachate under high ammonia concentration in therange of 2,000- 3,000 mg/L where the inhibitory
effects of ammonia in treatment of landfill leachate andanaerobic digestion process has been reported to occur.
Additionally, it was intended to assess the contributionof thermal and non-thermal effects through statisticalanalysis of the data.

INTRODUCTION
Anthropogenic sources of pollution such as
agricultural, industrial, and municipal wastewaters
contribute to the degradation of water resources [1]-[2].
Discharge of such wastewaters with high ammonia–
nitrogen contents can result in eutrophication and algal
blooms, depletion of dissolved oxygen, and toxicity tofish even at low concentrations in receiving water
bodies, and inhibitory effects on microbial activity of
microorganisms responsible for biological treatment ofwastewater [2]-[5]. Total ammonia nitrogen (TAN)
exists in liquid phase either in unionized form (NH3) orionized form (NH4+), with toxicity being mainly
attributed to NH3 form [6]. The NH3/ NH4+ equilibrium(pKa of NH4+ is 9.25 at standard conditions) depends
on temperature and pH; the higher the pH of a solution,
the higher the concentration of NH3 [7].
Landfill leachate varies in strength and composition
depending on several factors such as the age of thelandfill, composition of waste, and design andoperation of landfill [8]. Ammonia is mainly produced
during the anaerobic biodegradation of organic fractionof solid waste and there is no mechanism for its
degradation under methanogenic conditions. This
process, known as ammonification, results inaccumulation of ammonia in leachate, which intensifies
its toxicity. As such, ammonia is considered to be theone of the most significant long-term pollutant found in
landfill leachate [6]. The range of ammonia
concentrations in landfill leachate has been reported tobe very wide, from a few hundreds to more than 10
thousands mg/L.
Conventional treatment processes to remove
ammonia from aqueous solution include biological

MATERIALS AND METHODS
A series of laboratory batch experiments using two
real landfill leachate were carried out. All tests werecarried out in triplicate. Table 1 shows thecharacteristics of the two leachates collected from two
local landfills. While both leachates had high ammonia
nitrogen content they were selected to represent bothold and new leachates – leachate 1 being morecharacteristic of a newer landfill’s leachate andleachate 2 more characteristic of an older landfill’sleachate.

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Table 1. Characteristics of leachates used to assessammonia nitrogen removal by ultrasound irradiation.

BOD5 (mg/L)
Alkalinity(mg CaCO3/L)
COD (mg/L)
TKN (mg N/L)TAN (mg N/L)pH

Leachate 1
18600
6690

Leachate 2
345
15300

55000
3190
1730
5.1

6200
4670
3440
8.2

between the two synthetic solutions (P > 0.05 and F >Fcrit ).

The schematic of the experimental setup is
illustrated in Figure 1. For each test, 165 mL ofleachate was added to a 500 mL beaker, with aremovable lid used during the cooling stage to limit
water loss. The pH of solution was then adjusted to an
initial pH of 10 (above the pKa of NH4+ = 9.25) using a
10 N NaOH solution. The initial TAN, pH, andtemperature of the sample were measured. Afterwards,
the sample was exposed to US irradiation using
Branson digital sonifier 450 with a ½” disruptor hornand ½” disruptor tip for the time duration of 15 minutes.
The US vibration was generated by a 20 kHz ultrasonicconverter and was transferred into the leachate byputting the US probe into it. The power output could be
adjusted from 10 to 100% in 5% increments and ranged
from 0 to 400 W. Temperature was measured
immediately after this stage. The sample was allowed
to cool to room temperature before distilled water wasadded to account for water loss. TAN and pH were
measured again and energy output recorded (KJ).
In order to study the amount of ammonia removed
due to temperature rise during the process, heat only
experiments were conducted. This method involved thesame procedure outlined above; however, instead ofbeing sonicated, the samples were placed into a 20
L/120 V Stable Temp hot water bath set at atemperatures that correlated to the final temperatures
achieved after sonication for the desired durations. The
contribution of evaporation on the ammonia removal
was also investigated by leaving some samples open to
the surrounding atmosphere for the same duration timeof 15 min instead of being heated in water bath orsonicated.

Figure 1 - Schematic of experimental setup.
(1) Synthetic solution or leachate, (2) disruptor horn
and tip, (3) US converter, (4) case, (5) stand.
To determine the contribution of thermal and nonthermal effects of US process the TAN removals
obtained by water bath was subtracted from the total
TAN removal efficiencies. The difference is identified
as non-thermal effect (US) effect. It should be notedthat the TAN removal in water bath samples shows the
combined effect of thermal (due to temperature
increase)andvolatilization.
Bysubtracting
contributions by volatilization from water bath removal,
the net thermal effect contribution was also calculated
and identified as WB. As such, it is possible to estimate
the sonication or non-thermal effect (US), thermal
effect (WB), and volatilization (Volat.) contributions.
These are presented in Figure 2.
Table 2. One-Way ANOVA for TAN removal
efficiencies for two leachate sources
Source of
Variation
BetweenGroupsWithinGroupsTotal

RESULTS AND DISCUSSIONS
The ammonia removal efficiency was calculatedusing the Equation below:
TAN removal (%) = (C0- Ce)/ C0 ×100%

SS

df

MS

F

P

Fcrit

10.98

1

10.98

2.52

0.19

7.71

17.43
28.41

4
5

4.36

The percent removal for Total as well as US, WB
and Volat. contributions were compared using t-Test.
The results for US removal comparison are presented
in Table 3 as an example. As it can be observed, no
significant difference was observed between the twoleachate sources tested, showing the same performanceand removal efficiency. Similar results were obtainedfor comparison of WB and Volat. contributions.

where: C0 and Ce are initial and equilibrium TAN
concentration (mg/L), respectively.
Table 2 shows the results of the one-way ANOVA
tests that compares the total TAN removal efficiencies
for the two leachate sources. Looking at the results inTable 2 it can be seen that there are no significant
differences in the total TAN removal efficiencies

522

REFERENCES[1] Arabgol R., Sartaj M., Asghari K. Predicting Nitrate
Concentration and Its Spatial Distribution in
Groundwater Resources Using Support Vector
Machines (SVMs) Model. Environmental Modeling &Assessment, 21 (2016), 71-82.

Figure 2 - Average TAN removal by non-thermal (US),thermal (WB), volatilization (Volt.) at pH =10 andduration time of 15 min[2]Ozturk E., Bal N. Evaluation of ammonia–nitrogen
removal efficiency from aqueous solutions by
ultrasonic irradiation in short sonication periods.
Ultrasonics Sonochemistry, 26 (2015), 422-427.

[3]

Dong S., Sartaj D. Statistical analysis of thermal andnon-thermal effects of sequential microwave/aeration
process for the removal of ammonia from aqueous
solution. Desalination and Water Treatment, 57(2016),
20005-20015.

[4] Faryadi M., Rahimi M., Moradi N., Safari S. Ammonia
removal using 1.7 MHz high frequency ultrasound inbatch and novel dam-weir falling systems, Desalinationand Water Treatment, 54 (2015), 3412–3421.

Comparing the average contributions from US, WB,
and Volat. processes to Total TAN removals indicatesthat on average 61.5%, 36.7%, and 1.8% of total TAN
removal is contributed to US, WB, and Volat.
mechanisms.

[5]

Table 3. t-Test results for comparisons of Total
TAN removal between the two leachate sources

Lee S.M., Jung J.Y., Chung Y.C. Measurement ofammonia inhibition of microbial activity in biologicalwastewater treatment process using dehydrogenase
assay. Biotechnology Letters, 22(2000), 991-994.

[6]

Nair A., Sartaj M., Kennedy K., Coelho N.M.
Enhancing biogas production from anaerobic
biodegradation of the organic fraction of municipal
solid waste through leachate blending and recirculation.
Waste Management and Research, 32(2014), 939-946.

Mean
Variance
Observations
Pooled Variance
Hypothesized Mean
Differencedft StatP(T<=t) one-tailt Critical one-tailP(T<=t) two-tailt Critical two-tailLeachate 1
38.61
3.81
3
3.04
0

Leachate 2
40.02
2.27
3

4
-0.991477279
0.188787797
2.131846786
0.377575594
2.776445105[7] Ding Y., Sartaj M. Optimization of ammonia removal
by ion-exchange resin using response surface
methodology. International Journal of Environmental
Science and Technology, 13(2016), 985-994.
[8]

Sartaj M., Ahmadifar M., Jashni A.K., Assessment of
in-situ aerobic treatment of municipal landfill leachateat laboratory scale. Iranian Journal of Science andTechnology B. 34(2010), 107-116.

[9]

Dong S., Sartaj M., Statistical analysis and optimizationof ammonia removal from landfill leachate bysequential microwave/aeration process using factorial
design and response surface methodology. Journal ofEnvironmental Chemical Engineering, 4(2016), 10-108.

CONCLUSIONS
The results obtained for laboratory batch
experiments for TAN removal using ultrasonicirradiation indicated that this process is effective in
TAN removal from landfill leachate. The main
mechanisms for TAN removal were non-thermal
effects accounting for approximately 2/3 of total
removal with the remaining 1/3 mainly due to thermal
effects.

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

THE IMPLEMENTATION OF WATER SENSITIVE CITY AT DEPOK MIDDLE CITY IN INDONESIA

1

Firdaus Ali1, Irene Sondang2 Esty Suyanti3 and Ahmad Zubair4
School of Strategic and Global, Universitas Indonesia, Indonesia; 2Center for Urban and Regional Research,
Indonesia

ABSTRACTThe city has increasingly be burdened with the increase of urbanization. The effect of this dynamic is thepressure to urban environment, specifically on the supply of water and the number of water space. The city of
Depok as a middle-city continuously experience infrastructure development as the consequences of the capitalcity, Jakarta’s spill over. It resulted in the diminishing amount and quality of water supply and space. Water
Sensitive Cities is an innovative approach that is based on similar experience in similar surroundings within
Australian cities. The approach integrates the concept of water cycle with urban development dynamics thatconsider to environment equilibrium. To what extent the concept is implemented in one of the middle cities inIndonesia will therefore then be significant for the study of urban developments and water studies in Indonesia.
Specifically for the case of Depok, Water Sensitive City studies will provide a guideline as to what will be
required to be done with regards to current condition of water supply and space in the middle city context. The
research takes advantage of mix-method approach combined with GIS mapping to identify water spacecapacities and supply as well as gauge what can be done from a social economic aspects. The research will
outline the degree of Water Sensitive City implementation in Depok and what still required to be done. The
research will also highlight the extent of which Water Sensitive City as an approach can be applicable in Depok
and Indonesia in general.
Keywords: Water Sensitive City, Water Supply, Water Space, Middle City
To comprehensively examine and provide
effective solutions for the issue of sustainable water
management within a certain urban context, aconcept of an ideal system of urban water
managements will be used. One of this concepts iswater sensitive city, a concept that presents an
integrative approach of urban water managementthat does not only provide sufficient supply for
urban water requirements, but equally provide
numerous other benefits to increase the urban live
ability and resilience of the city [1]. The Water
Sensitive City approach provides a “Leapfrogging”
mechanism that indicates the different stages that acity needs to fulfill in order to achieve Sensitive
Water Management in the urban context.
The implementation of Water Sensitive City inthe urban areas of Indonesia becomes a challenge in
itself due to specific characteristics that tropicalurban context in the case of Indonesia. The
developmental nature of the urban areas, the everincreasing population and the rise of land and water
use issues as well as continuous development of its
governance system provides Indonesian cities aninteresting case for the implementation of Water
Sensitive City concept. As the concept itself has
mainly been implemented in Australian cities, it
serves a valid reference from which Indonesiancities may be able to consult from.
One of cities that implemented WSC in

INTRODUCTION
Since the world’s urban population has
increased rapidly in the past few years,
approximately 54% of the world’s population now
live in urban areas, limitless of resources become an
urban issues. Water is one of the most importantnatural resources and plays an irreplaceable role inhuman survival and in the ecosystem. In urban areas,
many water resources are now facing threats fromnutrient enrichment, organic, and inorganic pollution.
Besides, with the rapid urban expansion andpopulation growth, water resources in urban areas
are also gradually decreasing. With some of themain issues of urbanization in mind, urban entities
will need to take further consideration to maintainbalance between the different spaces in land, air andwater. The numerous dimension that is involved
within urban water management portrays thecomplexities of managing issues in the urban area.
This complexity carries with it a multi-dimensional
issue that involves a large area of solution that
includes the need for technological, urban planningand design, empowerment of urban communities aswell as social and institutional development solution[4]. Urban dynamics will have to be able to provide
a balance between economic and physicaldevelopment with the availability or sources,
management and fresh water space.
524

Australia is Melbourne. This city threatened various
elements not only growth pressure but also climatechanging risk. Drought and flood happened at
Melbourne. 40% reduction in livestock production,
80% reduction in grain production, 10-20%
reduction in rainfall in autumn/winter andMelbourne’s largest reservoir got down to 16%(Thompson Dam). Floods made most region at
Melbourne had inundated. Hence city government
deal it with short term plan like disaster response
unit. They also doing long term plan by implement
10,000 raingardens, planning scheme amendment
and maintaining sport grounds.
The implementation on Water Sensitive City
Concept at Melbourne city that stated before,
become best practice to other city in Indonesia.
Depok is the city for the study case of this research.
The characteristic similar with Melbourne with asmall scale.
We need to know the sustainability of water
management after more than 30 years of rapidlychanging in Depok. Simple question like: “How thewater management to fulfill the needs of the
Depok’s residents?” becoming our aim in doing thisresearch. By asking this question the research tries to
examine the extent of which the concept of Water
Sensitive City (WSC) as has been implemented inAustralia, is applicable in the context of Indonesianurban environment in Indonesian cities. This
investigation is conducted as another effort toachieve an integrated and sustainable urban water
management in Indonesia.

400,000
300,000
200,000
100,000-

Sawangan
Bojongsari
Pancoran…
Cipayung
Sukmajaya
Cilodong
Cimanggis
Tapos
Beji
Limo
CinereSEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Fig.1 Population of Depok City in 2015
Population of Depok City is 2,106, 100 people
with population growth of 3.57 in 2015 [3].
Cimanggis sub-disctrict is the region with thehighest population, about 292,132 people lives in theregion. But the most dense sub-district in Depok
City is Sukmajaya sub-district with population
density of 15,600 people per kilometer square.
Total area of Depok City is 20,029 hectares.
Residential areas dominating land use in Depok City
that reach 58% areas of Depok City. Mixed
agricultural is the second largest land use in Depok
only have 8.95% of total area. Water bodies such as
rivers, lakes and ponds only reach 3% of total area
2%

Primary
Forest

1% 0%
1%

9%
7%

9%

8%

THE POSSIBILITY OF WATER SENSITIVE
CITY CONCEPT WOULD IMPLEMENTED
AT DEPOK58%

Depok is one of middle city in Indonesia thathave changing urbanize rapidly. Since earlier 1970
until now there are massive development, since
many campuses move from Jakarta to the periphery
area. The land use changing made the changing ofwater usage too. It impacted not only by theavailability of fresh water but also the services offresh water per households at Depok.
Depok city, in this sense serves as a perfect
example of a middle city that also serves aswaterway through Ciliwung main river and buffer
city connecting the capitol Jakarta and water
catchment area Bogor city.

5%

Commercial
Area
Farm
Agriculturalarea
Residential

Fig.2 Total Area of Land use in Depok City
Water bodies such as rivers, ponds, lakes andothers in Depok City can’t works well to receive
rainwater or runoff due to insufficient area. This cancause floods in many location in Depok City.
Massive housing development can be a contributing
factor to decrease area of water catchment area.
Increased housing area causes the change of others
landuses to residential area.
Despite their importance in water managements,
land use between Jakarta, Depok and Bogor city also
vary with both urban and rural characteristics
developments constantly providing alterations. As
many of the developments occured within the past 5
years, urban management of the city neglected water
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

management from being integrated to thedevelopment plan. As a result, water supply
demands increased, while water space decreased. If
Depok city government had fully under-stood andimplemented Water Sensitive city concept, this may
be averted effectively. In addition, suchdevelopments have subsequent effects to water
catchment areas in Depok, and particularly Jakarta.
Despite its status as the centre of economic activity
in Indonesia, sustaining close to 10 million residents
of different nationalities, cultural backgrounds andsocial economic power, Jakarta may suffer
diminishing supply of water in the next few years tocome.
The concepts of Water Sensitive Cities are
emerging in response to a general consensus thatexisting water services and planning processes havebeen poorly equipped to support the discussed urban
challenges (projected population growth, andclimate and economic challenges) [2]. Integrated
solutions to deliver services for supply, sewerageand flood protection, as well as green and live ableurban environments, are a requirement for future
cities and towns. In a Water Sensitive City this will
be achieved by:
1. Using the city as water supply catchments:
diversity of sources and diversity ofcentralized and decentralized solutions.
2. Assuring its healthy environments: cleanrivers and ground water, with cool, green
and beautiful urban landscapes.
3. Developing
resilient,
water-conscious
citizens: communities that accept andsupport new water solutions.
While Australian cities are on their (rather slow)
path to transform to water sensitive futures thepossibility exists in Indonesian developing cities toleapfrog certain traditional stages in building theurban water infrastructure. For example, rather thaninvesting in a massive centralized sewerage system,
it may be more practical in some areas to implement
decentralized, efficient and cost-effective treatment
and recycling systems at neighborhood scale,leading to direct development of a water sensitive
city. In this way developing Indonesian cities will
avoid repeating the mistakes that westernized cities
made on sustainability.

Clean water in Depok City provided by PDAM
Tirta Asasta, a company owned by the city. PDAM
Tirta Asasta established in 2013, before 2013 theneeds of clean water provided by PDAM Tirta
Kahuripan that owned by Bogor Municipality. In
2015, PDAM Tirta Asasta has 52,255 customers
with clean water supply of 1,172,883 cubic meters.
The biggest customer of PDAM Tirta Asasta areresidential. The middle residentials are the biggest
with total 26,759 customers and low residential with
18,120 customers.
Needs of drinking water in Depok City is not
only provided by PDAM Tirta Asasta but also fromother sources. Suprisingly, source of drinking waterin Depok City is from ground water pumps withtotal of 51.31%. Water meter from PDAM Tirta
Asasta only supplied 2.96% needs of drinking water.

Bottled Water

6% 0%

Refill Water
28%
Water Meter
51%

12%
3%

Ground water
pump wells
Shielded Well

Fig.3 Graphic Source of Drinking Water
Groundwater used to meet needs of drinking
water in Depok . Local companies such as PDAM
Tirta Asasta was not able to meet the needs of cleanwater, especially drinking water for residents of
Depok city. Excessive use of groundwater can leadto rapid groundwater degradation resulting in an
imbalance in the groundwater flow system.
GAP OF WATER ISSUES AT DEPOK CITY
The issues of water in Depok City are
dominated by flood and clean water issues. Floods inmany areas of Depok City became major issues
especially in the rainy season where rainfall is rising.
This flooding issue is usually accompanied byinformation of clogged waterways caused by
garbage and mud sediment. Siltation andconstriction of water bodies are also the cause offloods in the city of Depok.
The number of settlements increased, causing
an increase in the need for clean water for the peopleof Depok City. The issue of clean water became the

WATER AVAILABILITY AND
MANAGEMENT AT DEPOK CITY
24 rivers cross Depok City with the longest
river are Kali Grogol and Kali Psanggrahan. Lengthof Kali Grogol crossed Depok City is 35.2
kilometers and Kali Psanggrahan is 20.75 kilometers.
But the most important river in Depok City is Ci
Liwung, the river has 14 kilometer length
throughout Depok City.

526

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017second biggest issue after the flood, where the needof clean water supplied by PDAM Tirta Asasta has
not been able to meet all the needs of the people of
Depok City. This causes the use of other sources,
especially groundwater pumps become the main
source of Dpeok City residents to get clean water.

ACKNOWLEDGEMENTS
This article is part of Superior Research of
Universities (Ministry of Research, Technology andHigher Education)

CONCLUSION
Depok city is under pressure from Jakarta's
spillover and the internal development of Depok city
itself. This is evidenced by the increasingly
urbanized landuse rather that rural area. Thiscondition causes water demand to increase but water
availability decreases. Based on the Water Sensitive
indicator, that Depok City is still included in the"Sewered City" stage. Depok City has not been able
to manage the water needs and the availability ofwater in its area. The issue of flooding and cleanwater is still emerging in many parts of Depok City.
Therefore, if the WSC concept wants to be
implemented, leapfrogging is necessary so thatsustainable development of Depok City does nottake a long time to execute.

REFERENCES[1] Brown, R., Keath, N., & Wong, T. (2008).
Transitioning to water sensitive cities: historical,
current and future transition states. Paper
presented at the 11th international conferenceon urban drainage. Edinburgh, Scotland, UK[2] Brown, R. R., & Clarke, J. M. (2007).
Transition to water sensitive urban design: Thestory of Mel-bourne, Australia (Vol. 7): Facility
for Advancing Water Biofiltration, Monash
University Melbourne[3] BPS, 2016. Kota Depok Dalam Angka 2016.
BPS Kota Depok[4] Johnstone, P., Adamowicz, R., de Haan, F. J.,
Ferguson, B., & Wong, T. (2012). Water
Sensitive City.

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RISK MAPPING STUDIES OF HYDRO-METEOROLOGICALHAZARD IN DEPOK MIDDLE CITY
R. Jachrizal Soemabrata1, Ahmad Zubair2, Irene Sondang3 and Esty Suyanti4
1School of Strategic and Global, Universitas Indonesia, Indonesia; 2Center for Urban and Regional
Research, Indonesia
ABSTRACT

Rapid population makes rapid activity at limitation space. It will increase the potential of conflict within naturalor environment resources. Urbanization in Indonesia cities result tight competition of resources between urban
dwellers, especially in satellite city like Depok as the consequences Jakarta’s spill over. Depok more experienceswith flood and landslide since the rapid population pressure. Instead of doing curative action deal with disaster,
this city should do preventive action by doing risk mapping. This research will guideline to identify thevulnerability and capacity of it city in dealing with hydro-meteorological hazard. It will conduct by mix method
approach using GIS technique and statistical analysis to determine the risk mapping. This research will show thespatial variety of risk that (potential) occurred related with hydro-meteorological in Depok City. Through risk
mapping studies, this study will examine the balancing of population growth with the environment acceptances at
middle city in Indonesia.
Keywords: Risk Mapping, Hydro—Meteorological Hazard, Vulnerability, Capacity, Middle City
making maps. Map can give several disaster
information by linking 3 aspects. These aspects are
the potential disasters occurring in the city, thevulnerability of cities and the roles and capacities ofboth communities, NGO and governments.

INTRODUCTION
Geographically, Indonesia is located among threetectonic plates of earth, they are Eurasian, Pacific andIndo-Australian plates. Indonesia is also located in
the ring of fire area. This location causes 62 % of 497
cities in Indonesia have a high risk level of disaster[1]
Since 2011, Indonesia has entered a period ofdevelopment, called urban millennia, a situation
where the number of urban residents is greater thanrural areas. This condition can be seen from the
population in big cities such as Jakarta which
continues to increase every year.
Indonesia's major cities have a strategic role toplay in the development of the region as a service,collection and distribution node, which has abackward relationship with its intermediate andhinterland cities as well as forward relationships withother big cities [2]. Unfortunately, the growth rate andgrowth of middle cities are relatively uneven and tend
to be uncontrolled then causing many problems.
One of the middle cities in Indonesia is Depok.
Depok’s development tends not to look at thecharacteristics of the city itself, consequently thephysical burden that need to be borne by the city evenincreases. If this situation still exists, it will lead tolarge of potential disasters and run down the growth
process that will make the slow pace of urban
development.
Responding to the importance of disaster andurban issues in Indonesia's development, it isnecessary that every city in Indonesia has a tool thatcan measure disaster risks, one of them through

LITERATURE REVIEWDisaster risk assessment is an approach to show
potential negative impacts that may arise from apotential disaster. Disaster risk assessment in theprevious research was conducted on a provincial scaleusing GIS by the government. The disaster threats
experienced by middle cities in Indonesia are hydrometeorological disasters. It is hydro meteorological(i.e., floods, landslides) and climatological disasters(i.e., droughts and heat waves), rather than thegeophysical disasters (i. e., earthquakes and volcanic
eruptions), that have been trending upwards in recent
decades. This rising trend of climate-related hazards
suggests a possible connection between these hazards
and in turn disasters on the one side and climatechange on the other [3].
Hydro meteorological disasters greatly affect theresilience of communities within middle city. The
characteristics and circumstances of a community,
system or asset that make it susceptible to thedamaging effects of a hazard. Figure 1 shows many
aspects of vulnerability, arising from various physical,
social, economic, and environmental factors.
Examples may include poor design and constructionof buildings, inadequate protection of assets, lack ofpublic information and awareness, limited official

528

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017recognition of risks and preparedness measures, anddisregard for wise environmental management. [4]will be followed by a case study conducted in Depok
City. It is hoped that by studying the application in
the case study, some learning outcomes will be usefulfor the improvement of the formulation.
Hazard Assessment
Hydro-Meteorological hazards are caused byextreme meteorological and climate events, such as
floods, droughts, hurricanes, tornadoes, or landslides[7]. The focus of research are floods and landslides.
Flood disaster can be calculated and classified into
Table 1

Fig. 1

Depth
Class
Value
Weight Score
(m)
(%)
<0.76
Low
1
0.3
0.76Mid
2
0.6
100
1.5
>1.5
High
3
1
Source: National Board for Disaster Management

5 Aspects to Assess Vulnerability

Souza [5], stated that potential damage and risk
maps are automatically built up within the GIS (anyother geo processing software may be used), then any
change in environmental characteristics might beeasily updated, allowing that all of the thematic maps
involving the Risk Assessment be rapidly modified
too.
Hydro meteorological disaster risk reduction is
not only done with the construction and managementof facilities and infrastructures, in accordance with
National Law Number 26, 2007 about Spatial
Planning, Republic of Indonesia located in disasterprone areas requires spatial planning based on
disaster mitigation as an effort to improve the safety
and comfort of life and preserve the environment [6].

Landslides can be calculated and classified into:
Table 2

There are 3 components of indicators forcalculating the disaster risk of a region. Those
indicators are hazard, vulnerability and capacity. At
this stage, the study will be conducted to explore therisk assessment methods that used in government
guidelines through the Head of National Board forDisaster Management Regulation No 2/2011 as well
as recommendations from the United Nation
International Strategy for Disaster Reduction(UNISDR).

R
H
V
C

𝐇×𝐕

Vulnerability Assessment
The vulnerabilities that can be identified in thisstudy are economic and social vulnerability.
Indicators used in vulnerability analysis are primarily
exposure and loss information. The sources of
information used for analysis can come from Central
Agency on Statistics data and basic map information.
Economic vulnerability can be calculated
through the following equation:(1)

𝐂

Landslide Classification and Score

ThreatClass
Value Weight Score
Zone
(%)
Low
GroundLow
1
0.3
Movement
MediumGround
Mid
2
100
0.6
Movement
High
GroundHigh
31
Movement
Source: National Board for Disaster Management

METHODOLOGY𝑹=

Flood Classification and Score= Risk= Hazard= Vulnerability= Capacity

Table 3 Economic Vulnerability Classification

Based on National Board for Disaster
Management [8], equation (1) is a risk assessment
method linking potential hazard and vulnerability in
Depok City, then divide by its capacity. The review

Para
meter

529

Weight(%)

Class (Million)
Low Mid High

Score

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

PL

60

DODP
Source: National Board for Disaster Management<5050- >200 Class/
200
Max
GDRP
40 <100 100- >300 Score
300
Source: National Board for Disaster Management

Capacity Index = (1 x Capacity Score)
RADMI

𝑬𝑽 = (𝟎. 𝟔 × 𝑷𝑳 𝒔𝒄𝒐𝒓𝒆) + (𝟎. 𝟒 ×
𝑮𝑫𝑹𝑷 𝑺𝒄𝒐𝒓𝒆) (2)
EV
PL
GDRP

EWS
DE
BRFR
DOP

= Economic Vulnerability= Productive Land
= Gross Domestic Regional ProductHazardFlood

Social Vulnerability Classification

Para Weight
meter
(%)
PD
60

Low
<500

Class
Mid
5001000

High
>100
0

Floods are overflow water that exceeds thecapacity of rivers in their canals that are usually
preceded by high rainfall or high flow water fromupstream areas. Due to its vast territory, flood in
different areas manifest themselves in different types
and with various characteristics [9]. Flood andinundation problems are caused by high rainfall,
modified or disturbed river morphological conditions,poor drainage systems, and other external factors
such as high river sedimentation and landslides.

Score

Class/
SR
Max
PR
<
20>
Score
40
DR
20% 40% 40%
AR
Source: National Board for Disaster Management
𝑺𝑽 = (𝟎. 𝟔 ×

𝑷𝑫
)
𝟎.𝟎𝟏
𝟏𝟎𝟎
𝒍𝒐𝒈(
)
𝟎.𝟎𝟏

𝒍𝒐𝒈(

) + (𝟎. 𝟏 × 𝑺𝑹) + (𝟎. 𝟏 ×

𝑷𝑹) + (𝟎. 𝟏 × 𝑫𝑹) + (𝟎. 𝟏 × 𝑨𝑹)
SV
PD
SR
PR
DR
AR

= Rules and Disaster Management
Institution= Early Warning System= Disaster Education= Basic Risk Factor Reduction= Development of Disaster Preparedness

RESULT AND DISCUSSION

Social vulnerability can be calculated through thefollowing equation [8]:Table 4(4)

(3)

= Social Vulnerability= Population Density= Sex Ratio= Poverty Ratio= Dissabled Ratio= Age Ratio

Capacity Assessment

Fig. 2The capacity index is calculated based on
indicators in the Hyogo Framework for Actions(HFA). The HFA agreed by more than 160 countries
in the world consists of 5 Priority DRR programs.
Achieving these disaster risk reduction priorities ismeasured by 22 indicators of achievement [8].

Some district are potentially affected by flood.
The flooded districts spread throughout Depok Cityand is dominated in the eastern of city. Some areas
prone to flooding tend to be passed by large streams
such as Ciliwung and Pesangerahan River. Average
depth of flood in Depok city is about 50-100 cm, oreven reach 200 cm in certain area.
Floods are indirectly related to so massive land
use changes. Land use / land cover will be given formaking land use monitoring system [10]. It is
understood that floods occur because of theunplanned rapid urbanization, change in land use andpoor watershed management mainly in flood plains
become important issues for consideration as theflood causes [11].

Table 5 Capacity Classification and Score
Para Weight
meter
(%)
RADMI
EWS
100
DE
BRFR

Low
<0.3

Class
Mid
0.30.6High>0.6

Flood Area in Depok City in 2015

Score
Class/
Max
Score
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Flood also affects the availability of water. Studyof the run-off transformation on the land surface isespecially important in built-over areas, where basic
natural landscapes are modified [12]. In addition to
the area being a reservoir of water, many ponds andfish ponds are both consumption and aquaculture thatcan become a water reservoir when heavy rains sothat the overflow of river water can still be handled.

Fig. 3

Factors caused by humans can be in the form ofpiles of garbage and the accumulation of materialcaused by the expansion of settlements so that pilingup the soil around the valley leads to overloaded land,
and there are farms on the slopes.Potentiallylandslide-prone areas are located along large rivers
that have a fairly steep slope. Geological andgeomorphological conditions (e.g., material type,strength and structure, and slope angle) predispose
slopes to failure; knowledge of these conditions canhelp to predict the location, types, and volumes ofpotential failures [15].
Figure 4 shows the landslide prone area in Depok
City is on slope between 8-15% which means that theslope condition is quite steep and has a steep hill orvalley. This region is often found along a large river
flow that has a river width of more than 10 m. The
steeper the slope, the higher the landslide potential,
but this can’t be separated from the type of rock andsoil type in the area.

Flood Areas Percentage by District in 2015

Based on Soemabrata [13], figure 3 shows that
Depok City has a flood prone area of 126.4 Hectares,
Sukmajaya District became the most potentiallyaffected by floods with estimated total area of 32.8
Hectares. In addition, flood-prone areas in Depok
City tend to be located at an altitude of less than 100
meters which includes a declivous area.
Landslide
Landslide in Depok City occurs due to several
factors both from the physical condition of the region
and the natural factors of Depok and human activity
in it. According to Matheus [14], measuring the levelof landslide hazard can be determined based on sevennatural physical parameters consisting of slope, soil,
rocks making up the slope, rainfall, land use,seismicity and fault.

Fig. 5Landslide Areas Percentage by District in2015

Based on Soemabrata [13], figure 5 shows areas
prone to landslides in the city of Depok reach 1807
Hectares in area. The most vulnerable areas oflandslides are Tapos and Cinere Districts with a totalof 7 vulnerable villages. This region has a fairly steep
slope along the stream.
Vulnerability

Fig. 4

Vulnerability can simply be defined as exposurex sensitivity [16]. Vulnerability is considered as aresult of the interactions between physical (territorial)
characteristics and the susceptibility and thecapacities of the socioeconomic system to adapt andcope with a specific hazard, expressed as anondimensional index ranging between 0 and 1 [17].
The vulnerability of Depok City can be divided into
economic, social, physical and environmental
vulnerabilities.

Landslide Area in Depok City in 2015

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Economic Vulnerability
Indicators used for social vulnerability are
population density, sex ratio, poverty ratio, disabled
ratio and age group ratio. Figure 7 illustrates the
distribution of areas with levels of social vulnerability.
Where each indicator of each districts has different
vulnerability lift. Areas with high social vulnerability
are only in Sukmajaya District. This is consistent withthe high population density in the region. In addition
to population density, the more disability and thenumber of vulnerable age groups, the more
vulnerable the Distrct to Hydro-Meteorologicalhazard.
Areas with low social vulnerability are located insome districts located in the suburbs. In addition, in
the region in some indicators also shows are in low
grade. Broadly speaking, it can be said that the more
towards the center of the city, the level of social
vulnerability is increasing. Vice versa, the more
towards the suburbs, the lower the social
vulnerability.

Indicators used to measure the economic
vulnerability of Depok City is the area of productive
land and GDP of the city. The area of productive land
can be obtained from land use maps and district / cityor sub-district books in figures and converted into
rupiah, whereas GRDP can be obtained from sector
or district reports in figures. The weight of the index
of economic vulnerability is almost the same for all
types of threats, except for building fire andresidential and settlement fires.

Capacity

Fig. 6

The policies and regulations on disaster in Depok
City are still overlapping. This is due to the absenceof agencies that focus on disaster management affairs.
Unlike other cities such as Jakarta that already have
Regional Board for Disaster Management (BPBD
DKI Jakarta), BPBD Depok needs to be completed
because the level of disaster threat is increasing every
year. For now, disaster-related policies aredowngraded into several plans and programs can be
identified through urban planning regulation (RDTR
Depok City in City Regulation No.1 Year 2015). The
plans and programs are as follows:

Economic Vulnerability Area in Depok Cityin 2015

Figure 6 shows the area with the highest level of
economic vulnerability is located in the suburbs withtotal area of 629 Hectares. Based on the data and fieldobservations that have been done, there are 8 mostvulnerable districts. One of them is located in the vitalareas of the city.Most of them have productive land(e.g. offices, services and trading area, plantations)that play an important role in economic activity. The
rise of land use change has also become one of thecauses of economic vulnerability index which is still
continuously increasing every year.

Table 6 Flood and Landslide Management Program
Item
Flooded Area
Plan

Social Vulnerability

Landslided Area
Plan

Fig. 7

Social Vulnerability Area in Depok City in
2015
532

Program
Normalization of drainage
channels
Building new channels to theriver
Building embankments
Protecting and building ofriver/lake walls
Normalization of riverbank
and lake with mmud
dredging
anddevelopjogging track
Building an evacuation road
Reforestation by planting
landslide prevention plants
along riverbank
Limit the utilization of spacearound riverbank

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

Source: Urban Planning of Depok City

Coastal Drainage Basins through Multivariate
Analysis within a GIS-Based Model”, J. of
Coastal Research, Vol.1, 2009, pp. 900-904.
[6] M.R. Amri et al, “Resiko Bencana Indonesia”.
Jakarta: Indonesian National Board for Disaster
Management, 2016, ch. 2.
[7] Huan Wu et al, “Hydrometeorological Hazards:
Monitoring, Forecasting, Risk Assessment, andSocioeconomic Responses”, J. of Advances in
Meteorology, Vol. 2016, Aug. 2016, pp. 1-3.
[8] M.R. Amri et al, “Resiko Bencana Indonesia”,
Jakarta:
National
Board
for
DisasterManagement Regulation, 2016 ch 3.
[9] Zhong Guihui et al, “Urban Flood Maping for
Jiaxing City Based on Hydrodynamic Modelingand GIS Analysis”, J. of Coastal Research, Vol.
1, 2014, pp. 168-175.
[10] K. Djaja et al, “The Integration of Geography
Information System (GIS) and Global
Navigation Satelite System-Real time Kinematic(GNSS-RTK) For Land Use Monitoring”,
International Journal of GEOMATE, Vol.13,
Aug, 2017, pp.31-34.
[11] N.F Ibrahim et al, ”Identification of Vulnerable
Areas to Floods in Kelantan River Sub-Basons
By Using Flood Vulnerability Index”,
International Journal of GEOMATE, Vol. 12 ,Jan, 2017, pp. 107-114.
[12] A.V. Bobylev, A.V. Malaev, N.S. Rasskazova,“The Geoecological Modelling of Small Water
Reservoirs and River Catchment Areas as a
Procedure in Urban Development”, Procedia
Engineering, Vol. 150, 2016, pp. 2067-2072.
[13] Soemabrata. J, “Hidro-Meteorological Hazard
Risk Assessment in Slum Area Depok City
through Health Aspects, Community Adaptation
Capacity,
and
AvailabilityofBasic
Infrastructure”, Depok: Universitas Indonesia,
2016, ch 4.
[14] S. Matheus, H. Lilik, H. Gunawan “Landslide
Hazard and Risk Assessment for Ambon City
using Landslide Inventory and GIS”, J. Of
Physics: Conference Series 739, 2016, pp. 1-11.
[15] Samuel T. McColl, “Landslide Causes and
Triggers”, Landslide Hazards, Risk andDisasters. Amsterdam: Elsevier, 2015, pp. 17-42.
[16] R.R Putra, J. Kiyono, A. Furukawa,“Vulnerability Assessment of Non Engineered
Houses Based on Damage Data of The 2009
Padang Earthquake in Padang City, Indonesia”,
Int. J. of GEOMATE, Vol. 7, Dec. 2014, pp.
1076-1083.
[17] Giupponi Carlo et al, “Integrated Risk
Asssessment of Water-Related Disasters”,
Hydro-Meteorological Hazards, Risks, andDisasters. Amsterdam: Elsevier, 2015, pp. 163200.

Several programs can also be identified through aseries of Focus Group Discussions (FGD) with the
Local Government of Depok City and field findings.
CONCLUSION
Depok City based on the identification ofpotential hazard threat variables and have historical
data related to Hydro-Meteorological hazard that are
floods and landslides. Meanwhile, the susceptibility
variable successfully identifies two aspects, those are
economic and social aspect. Two other aspects(environmental and physical vulnerability) have notbeen identified due to data limitation. While thecapacity variables successfully identified that there
have been disaster management programs eventhough the activities that are preventive are still small.
One of them is due to the lack of focus on disastermanagement because it does not have BPBD yet. The
future research should be more focus on themeasuring the risk index. Governments need to workwith communities to build capacity and reduce
vulnerability levels with more planned mitigation
programs. In addition, the establishment of disastermanagement in the city-level is urgently needed.
ACKNOWLEDGEMENTS
This article is part of Superior Research of
Universities (Ministry of Research, Technology andHigher Education) titled “Measuring the Risk ofHydro-Meteorological Disasters on Urban Slums
From Health, Adaptive Capacity of Citizens, andAvailability of Basic Infrastructure Aspects”
REFERENCES[1] State
Ministryfor
Development
Planning,”Disaster
Index
Reduction
inIndonesia”, Jakarta: National Board for Disaster
Management, 2014.
[2] Soemabrata. J, “Hidro-Meteorological Hazard
Risk Assessment in Slum Area Depok City
through Health Aspects, Community Adaptation
Capacity,
and
AvailabilityofBasic
Infrastructure”, Depok: Universitas Indonesia,
2016, ch 1.
[3] Thomas V, “Confronting Climate-Related
Disasters in Asia and Pasific”, Jahrbuch fürWirtschaftswissenschaften
Reviewof
Economics, Vol. 2, 2014, pp. 121-135.
[4] United Nations International Strategy for
Disaster Reduction (UNISDR), “Global Platformfor Disaster Risk Reduction”, 2nd Session,
Geneva, Switzerland, June 2009.
[5] Souza, C.R. de G, “Flood Risk Assessment in533

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

ROLE OF GOVERNMENT AND PRIVATE SECTOR IN MARINE
ECOTOURISM RELATED TO CONSERVATION OF BIODIVERSITY
IN SERIBU ISLANDS
1

Lily Surayya Eka Putri1 and Kristiyanto2
Department of Biology, Faculty of Science and Technology, State Islamic University Syarif Hidayatullah
Jakarta, Indonesia
2
UNINDRA, Indonesia

ABSTRACT
Ecotourism have relation with conservation of biodiversity which recently shows bad condition on marine
ecosystem. This research analyzed how the role of government compared to private sector was conducted in
Pramuka and Air Island based on diversity of marine biota and conformity of ecotourism. Line Intercept
Transect method was used in this study stretched along the parallel 85 m into the coastline with three replications
over 25 m. Interview with local people surrounding islands was also conducted to get the information ofanthropogenic activities. The study showed that coral diversity in Pramuka and Air Island were in moderatelevel (1.00 <H '<3.00), nevertheless live coral coverage in Pramuka Island was 29.17% of 73.44% total coral
coverage lower than Air Island (49% of 55.62%). Sea grass species found in Pramuka Island were 6 species andonly 3 species were found in Air Island whereas mangrove species was lower in Pramuka Island than Air Island.
For ecotourism conformity, Pramuka Island was only suitable for sea grass tourism whereas snorkeling anddiving tourism were more suitable in Air Island. Hence, despite ecotourism in both islands were likely destroyed
the environment, conservation of biodiversity on marine ecosystem seemed ineffectively managed or evenignored by government neither private sector. Education and raise awareness for local people is the main priority
in order to conserve the uniqueness of the ecosystems in Seribu Islands.
Keywords: Marine Biodiversity, Marine Ecotourism Conformity, Seribu Islands
less study is conducted regarding to evaluate role ofgovernment and private sector in conserving
biodiversity related to tourism activities and otheranthropogenic activities in the mainland. Therefore,
this study was conducted at Pramuka and Air Island
representing government and private sector
management in order to analyze the role of bothmanagement in marine diversity conservation andevaluated the impact of ecotourism activities tobiodiversity in the islands. The ecological data wascollected and analyzed as the important informationin monitoring the condition of the ecosystem atboth islands, including diversity of marine (corals
and sea grass) and conformity of ecotourism
assessment.

INTRODUCTION
Indonesia is the largest archipelago country
with more than 17,000 small islands which is called
Seribu Islands. The Seribu Islands has the uniquenatural resources, both in terrestrial and marine
areas providing environmental services for local
people to support economic and social development
sustainably [1], [2].
The richness of biodiversity in Seribu Islands
provides ecotourism activities which serves aninteresting tourism destination, including whitesandy beach, beauty of under water, and uniqueculture. Nevertheless, such ecotourism activities are
conducted so far in Seribu Islands has some
negative impacts on the conservation of
biodiversity, including use of coral for building,destruction of coral as water sport activities,
exploitation sands for building. Many studies havereported the degradation marine diversity, including
corals in Seribu Island [3-6] and sea grass [7].
Most of management of the small islands in
Seribu Islands is run by government and some ofthem are by private. There are 12 islands managed
by government of DKI Jakarta which are in primaryzone and 11 islands in inhabitant zone, while 34
islands managed by private for tourism destinationand no inhabitants in those islands. Unfortunately,

MATERIALS AND METHODSThis research used the qualitative andquantitative methods, including collecting data
through field survey methods, interviews andobservations in Pramuka and Air Islands, Seribu
Islands, Indonesia, from June to November 2013.
Diversity of marine biota was collected including
coral and sea grass, and the analysis was conductedat the Laboratory of Biology, Center for Integrated
Laboratory, State Islamic Unviersity (UIN) Syarif
Hidayatullah Jakarta. The sampling point at
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SEE-USQ, Brisbane, Australia, Nov.13-16, 2017

Pramuka Island was at North, South, and West
(Pier) sites, while Northern sites of Air Island
which coral ecosystem found. Interview with local
people was also conducted to get more information
about the contribution given by government andprivate sector for conservation program in bothislands.
Furthermore, the data of diversity index ofvarious marine species is determined using theformula of Shannon-Wiener index [8].

𝑳=

Description:
L = The percentage of coral cover (%)
Li = Length of life form (intercept colony)
categories
to-i
N = Length of transect (m)Percentage of coral coverage is the area
covered by growing corals which was developed by
Gomez and Yap [13] the criteria as follow:∞

𝐇′ = − ∑ (𝑳𝒊
𝒙 𝟏𝟎𝟎%
𝑵𝒏𝒊𝒏𝒊+ 𝐥𝐧 )𝑵
𝑵

𝒏=𝟏

Table 1 Percentage of live coral coverage

Description:
H '= Shannon-Wiener diversity index
ni = Number of individuals of a species to-i
N = Total number of individuals of all species
The value of Shannon Wiener Diversity Index
has a range of categories is defined as follows:
H '<1.00: Diversity of species is low.
1.00 ≤ H '≤ 3.00 : Diversity of species is moderate.
H '> 3.00: Diversity of species is highFor coral reef monitoring, it was used LIT(Line Intercept Transect) method to collect data
which was made of 3 transects. The length oftransect was each 25 m with 5 m interval between
each transect, so it was about 85 meters length ofline toward the sea. Observation was conducted at
two depths, which were at 3 and 10 meters depth,with 3 replications. The depth of 3 m represented
shallow waters while the 10 m depth for a relatively
deepest water, assuming two conditions represent
the depth of the reef where coral can grow well [9].
Observation was conducted in the morning or
during the day depending on the condition of
weather [10].
Installation of transect was parallel to theshoreline and follow the contours of corals.
Transect is placed on top of the coral colony andrecorded the coral form, live and dead coral, abiotic
form, coral cover, and the form of the substrate(sand, mud and rocks), along 85 m length.
These measurements were performed with anaccuracy approach which always considered thecolony form as a single individual. If a colony of
the same type is separated by one or several parts ofthe dead corals, the living part of each regarded as aseparate individual. If two or more colonies are
growing on top of the other colonies, then eachcolony was still counted as a colony separately [11].
The length of overlapping colonies were recorded
and used to analyze the species richness.
The percentage of coral cover was used toestimate the condition of coral reefs in anenvironment which was obtained from themeasurement of life form of corals using theformula[12] below:

Coverage (%)
75 – 100
50 – 74.9
25 – 49.9
0 – 24.9

Category
Very goodGood
Moderate
Bad

Measurement of physical parameters at eachstation of each transect was also considered. The
physical parameters of water measured were pH,
temperature, and clarity
Data Analysis
The data of this study is the qualitative andquantitative data. Data obtained from this study was
analyzed quantitative descriptively using simple
mathematic formula, so it can provide an overview
of the ecological condition of Pramuka and Air
Island. Furthermore, ecological data from bothstudy sites was analyzed to evaluate the conformity
index of ecotourism, including type of ecotourism
for recreation, snorkeling, diving, and sea grass
tourism. Assessment for conformity of ecotourism
was adapted from Yulianda [14] and Baksir [15].
Based on the results obtained, it can be further
evaluated the role of government and the private
sector in managing the region-based biodiversity
conservation.
RESULT AND DISCUSSIONManagement in Seribu Islands is the importantfactor in determining the condition of biodiversity
in this area. Based on ecological data, there weredifferences between Pramuka Island which wasmanaged by local governments and Air Island
which was managed by private company (Table 2).
The differences were very closely related toconservation activities carried out by the
stakeholders.
The quality of the environment and the level ofdiversity in Air Island as the resort’s island which535

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was run by the private company were relatively
better than Pramuka Island. There was not foundpeople living in this island resulted in little waste
produced which in further lead to better
environmental quality of the surrounding waters.
However, less waste production in the island did
not significantly impact to the quality ofenvironment in Air Island. This assumes that lackof contribution was given by the management inmarine conservation leading to moderate to low
diversity of corals and sea grass (Table 3) whichshould have high diversity as no residential in thisisland.

of the ecosystem, such as research and conservation
activities. Those activities which are often carriedout by the external parties, including universities,
NGO’s and government as governors had a positive
impact on the conservation in Pramuka Island’s
ecosystems. Instead of Air Island, it was very few
and even might not have conservation andeducation programs for the tourists that come to theisland leading to degradation to the ecosystem. It
seems that management of Air Island wasdependent on natural condition instead of giving
proper contribution in conservation.
However, it does not mean that the island run
by the government was better than the private
island. Based on surveys and interviews conductedin Pramuka Island were acquired the informationthat most of the contribution of conservation
programs was from the outsiders such asuniversities, researchers and NGO’s compared to
the local people itself and government. The marine
biota diversity has to be consider as an importantparameter to assess the success of conservation
program in the islands
Regarding to the marine diversity, in recent
study, diversity index of corals decreased to 1.38
(Table 3) compared to the study conducted by
Efrinawati [3] that found diversity index of coralwas 2.07-2.82. This was so bad and it can beassumed that all activities done did not givesignificantly impact to the marine environment,such as coral transplantation. Rifqi [4] observedthat coral transplantation had already conducted in
Pramuka Island since 2005, but live coral coverage
was only 23-50% in 2016 due to water pollution
come from mainland and diesel spill from ships.
This condition was almost the same as reported by
Mujiyanto et al [16] in 2009 that live coral
coverage was 30-50%. More attention for corals
conservation is needed for environmental
sustainability in the future.

Table 2 Comparison of Pramuka and Air Island
profileParameter

Management
Residential
WastesEnvironmental
awareness

Transportation

Exploitation ofnaturalresources
Research

Management
PramukaAir
IslandIslandGovernment
PrivateYes
No
Many
Less domestic
domestic
wastes andwastes andwith treatment
without
treatment- Cleanliness - Cleanlinessbadkeep well
- Low
- Low
awareness
awareness ofofmanagement
government- Low
Awarenessof people
Ships dockShips dockeverydayonly weekend,
prefer big
private ships
Corals forCorals forbuilding
water front
materials
development
on large scale
Many studies Less researchdone bydone
universities,
government,
and NGO’s

Table 3 Comparison of Diversity Index (H’) andNumber of Species at Pramuka and Air
IslandNo
AParameter
H’ index- Corals-

Marine Biodiversity in Pramuka and Air Island
B

Based on ecological quality, level of
biodiversity in Air Island was relatively similar to
Pramuka Island that was in moderate level(1.00<H'<3.00) (Table 3). As resort’s island, thediversity index in Air Island has to have highdiversity index (H’>3). This was suggested that theexternal factor were also contributed to the quality
536

Seagrass

Number ofSpecies- Life form ofcorals- Sea grass- Macroalgae- Coral fish

PramukaIslandAir
Island1,38(moderate)
1,60(moderate)

1,52(moderate)
0,82
(low)

10

6

6
2
<61

3
3
<61

SEE-USQ, Brisbane, Australia, Nov.13-16, 201750%

The low diversity index in Pramuka Island was
also strengthened by the low coverage of live corals
was 29.17%. The coral coverage in Pramuka Island
was 73.44% however 44.27% was dominated bydead coral algae (DCA) (Fig. 1). In Air Island,
49.22% of 55.62 % live coral dominated coral
coverage and only 6.4% of dead corals found.
Nevertheless, there was not any contribution givenby the resort management for marine conservation.
Thus, the good condition of live coral coverage wassolely because of the dynamics of nature. This wasproved by the study conducted by Subhan et al [6]in 2008 and Yosephine et al [5] in 2010 found thatlive coral coverage in Air Island was 27.18%37.88% and 43.16% lower than the recent study in2013.
Regarding to sea grass ecosystems, thediversity index in Pramuka Island was better than
Air Island (Table 3). There were 6 species of sea
grass found in Pramuka Island, including
Cymodoceae rotundata, Cymodoceae serrulata,
Enhalus acoroides, Halodule uninervis, Halophilia
ovalis, dan Thalassia hemprichii, whereas 3 species
in Air Island, Cymodoceae rotundata, Enhalus
acoroides, and Thalassia hemprichii. Enhalus
acoroides (37%-43%) and Cymodoceae rotundatais(31%-58%) were the most dominant species grownin both islands (Fig. 2). Both species are a hardy
species and it is adaptable to marginal conditions.
Just like other intertidal species,% coverage

40%

20%
10%
Thalassia hemprichii

Halophilia ovalis

Halodule uninervis

Enhalus acoroides

Cymodoceae serrulata

Cymodoceae rotundata

Cymodocea serrulata

Cymodocea rotundata

0%

seagrass species
Pramuka island
Air island
Fig. 2 Percentage of sea grass coverage at Pramuka
and Air Island
Enhalus acoroides and Cymodoceae rotundatais
are common and widespread, especially inembayments. Based on criteria of ecology
developed by Salm et al. [17] and Soselisa [18],diversity of sea grass was high (>5 species) in
Pramuka Island, but it was categorized low (1-3species) in Air Island.
Macroalgae was also found in Pramuka and
Air Island, they were Padina sp., Sargassum sp.,and only Halimeda sp. was in Air Island, but insmall quantities due to anthropogenic wastes thathave an impact on water quality degradation. Very
low clarity was observed that was only 1.5 m in
Pramuka Island and 2 m in Air Island (Table 4).
This was resulted in interference of marine biota
including corals, sea grass and macroalgae diversity.
Based on criteria of ecology [17], [18], diversity ofmacroalgae was low (<10 species) in both islands.

80%% coverage

30%

60%
40%
20%
ACB
ACD
ACS
CB
CE
CF
CM
CMR
CS
DCA
SP

0%

Table 4 Physical parametercorals typePramuka island
Air island

Parameter

Pramuka Island

Air Island

8

7.6

29.66
1.5

31.2
2

pH

Fig. 1 Percentage of coral coverage at Pramuka
and Air Island. Note: ACB (Acropora
Branching), ACD (Acropora Digitate), ACS(Acropora Submassive), CB (Branching
Coral), CE (Encrusting Coral), CF (Foliose
Coral), CM (Massive Coral), CMR(Mushroom Coral), CS (Submassive Coral),
DCA (Dead Coral Algae), SP (Sponge)oTemperature ( C)Clarity (m)Conformity of Ecotourism

From the field observation, in general thecondition of Pramuka and Air Island was not ingood condition, however with high awareness andefforts form all stakeholders especially government,
resort management, and local community,
ecotourism in both islands still have good potential
to be developed because of the underwater537

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

uniqueness in both islands. This factor is very
important to attract tourists visiting the islands.
In order to analyze the conformity of Pramuka
and Air Island as ecotourism destination, it isnecessary to use the matrix of conformity [14],[15].
The conformity of ecotourism category is divided
into recreational, snorkeling, diving and sea grass
tourism. The value of matrix is defined as 3
categories: value 1 means not suitable, value 2means suitable, and value 3 means vey suitable.
Analysis of ecotourism conformity on Pramuka
and Air Island was showed at Table 5. The
conformity of Pramuka Island was only suitable forsea grass tourism which was supported by thehigher diversity of

between government, private sector, tourists andlocal communities.
This study has already shown that it is quitedifficult to expect local communities with low
awareness to support and implement conservation.
Hence, it is up to the political will of thegovernment to develop and implement policies thatstrike a balance between economic gains andenvironmental conservation. Clifton [19] suggested
that if the activities do not reflect the needs between
local communities and the environment, local
people will not participate in conservation activities
which finally will not result in environmental
benefits.
The efforts in scientific research activities,
conservation and management, environmental
education, awareness, and community action havedone successfully in Tamar project at Brazil [20], in
Brunei Darussalam [21] and also in South Korea[22]. The high level of interaction develops
awareness about the importance of field researchand the importance of conservation and research in
the islands.

Table 5 The conformity of ecotourism at Pramuka
and Air Island
No Parameter Pramuka Island
Air Island
1
Recreation
1.84
1.46
2
Snorkling
1.63
2.29
3
Diving
1.54
2.29
4
Sea grass
2.12
1.8
sea grass in Pramuka Island than Air Island.
Fortunately, the presence of coral fish in the sea
grass ecosystems was such an attractively scenery
for tourist in shallow water activities as the main
habitat for sea grass. Various types of sea grass canbe found in Pramuka Island at depths between 50100 cm at low tide and 2 m at high tide.
For Air Island, snorkeling and diving tourism
were more suitable to be develop. This was
supported by higher live coral coverage in Air
Island than Pramuka Island. Deep depth water was
also considered which can dive until 18 m deep in
Air Island. Although, diversity of coral fish was
low based on Salm et al. [17] and Soselisa [18], thelive coral coverage still attract tourist to dive or
snorkel. The diversity of fish is closely related tothe quality of the waters and the presence of the
inhabitants in Island. Waste production in Air
Island as a Resort Island with no inhabitants, was
not so many as Pramuka Island with large residents
which could pollute the water if it was disposed
directly to water without treatment.
Recreation tourism was not suitable in bothisland due to muddy sand in the beach and thepresence of sea urchins and lepu fish that can injure
tourists while doing activities on the beach.
In general, ecotourism are not are suitable inPramuka and Air Island and also not meet thecriteria of ecotourism itself of which environmental
protection and biodiversity conservation areimperatively considered. To develop ecotourism
in the islands, the authorities should focus on
consultation and participation between all
stakeholders involved in ecotourism to ensure theeconomic and socio-cultural benefits are shared

CONCLUSION
The role of the private sector and governmentis still limited in conservation of biodiversity in
Pramuka and Air Island. However, if they makegood collaboration with other parties including
university, research centre and NGO’s, and haveopen minded to others, in future, both Islands will
be getting better environment as habitats for marineorganisms.
Meanwhile, the government needs to give
seriously attention in population growth in Pramuka
Island which tends to enhance waste production
resulted in water quality declined. Bad water
quality is related to low-moderate level of marine
diversity in Pramuka and Air Island. This also
results in less conformity of ecotourism. Air Island
was suitable for snorkeling and diving tourism
while Pramuka Island was only suitable forrecreation tourism.
With good efforts and collaboration among all
stakeholders, ecotourism activities will further
provide positive impacts in economic, socio-culture
and environmental benefits in Seribu Islands.
Research and education are the first step concernedin order to develop the ecotourism in small islands,
like Seribu Island. Finally, the quality of marine
environment will increase in between withbiodiversity
conservation
activities,soenvironmental sustainability will be achieved in the
future.

538

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

ACKNOWLEDGEMENTS
Authors would like to thank to State Islamic
University (UIN) Syarif Hidayatullah Jakarta which
had given financial support for this research. We
also thank to students and laboratory staff ofBiology Department who had given technicalsupport in the field and laboratory.

[14]

[15]

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Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

SEISMIC MICROZONATION FOR URBAN PLANNING AND
VULNERABILITY ASSESSMENT OF NON-ENGINEEREDSTRUTURE IN EARTHQUAKE PRONE AREA, PADANG,INDONESIA*Rusnardi Rahmat Putra1,, Junji Kiyono2, Ganefri3 Fahmi Rijal4 and Syahril5
1,4

Civil Engineering, Engineering Faculty, Universitas Negeri Padang, Indonesia, 3Graduate School ofEngineering, Kyoto University, Japan, Elect4Mechanicall Engineering, Engineering Faculty, Universitas
Negeri Padang, Indonesia

Abstract: Padang city is located at earthquake prone area, several powerful earthquakes have struck Padang
during recent years, one of the largest of which was an M 7.6 event that occurred on September 30, 2009
and caused more than 1000 casualties. The basic purpose of seismic microzonation is to produce input for
urban planning and to supply site specific ground motion data to be used for the assessment of thevulnerability of the non-structure houses stock. A very detailed geological and geotechnical studies wereconducted to evaluate the variation of site characterization within the city of Padang. We performed single
observations of microtremors at 110 sites in Padang. The results enabled us to estimate the site-dependent
amplification characteristics of earthquake ground-motion. We also conducted a 12-site microtremor array
investigation to gain a representative determination of the soil condition of subsurface structures in Padang.
Based on soil characteristic in whole Padang, We simulated the recorded ground motion of earthquake 2009
to obtain ground motion whole Padang. This seismic microzonation is a parameter for vulnerability
assessment to non-engineered houses. We conducted vulnerability assessment to non-engineered structureof houses stock to estimate current structure condition to face predicted earthquake event in near future.
About 1400 non-engineered structure were assessed and interviewed. The residents received explanations
for each item on the questionnaire from the interviewers, and answers were filled in directly on the answer
sheets. This survey produced a map of the shaking intensity and houses’ vulnerability distribution in Padang.
From the dispersion curve of microtremor array observations, the central business district of Padang
corresponds to relatively soft soil condition with Vs30 less than 400 m/s, the predominant periods due tohorizontal vertical ratios (HVSRs) are in the range of 2.0 to 4.0 s, and 98% of houses in high risk due topredicted earthquake. These results enable produce clear information to Padang people including local
government of Padang how to create a mitigation system to reduce earthquake risk.
Keywords: array observation, vulnerability assessment, non-engineered structure, seismic microzonation

Indonesian capital, Jakarta, about 923 km from theepicenter. The tremors also were felt in neighboring
countries such as Malaysia and Singapore [2]. The
earthquake caused landslides and collateral debris
flows in the hills surrounding Lake Maninjau. A
major landslide in Gunung NanTigo, Padang
Pariaman completely destroyed some villages andforced road closures.
This 1900-km-long active strike-slip fault
zone that runs along the backbone of Sumatra posesseismic and fault hazards to a dense population
distributed on and around the fault zones [3]. The
Sumatran Fault is highly segmented. It consists of
20 major geometrically defined segments and theslip rate along the fault increase to the northwest,
from about 5 mm/yr [3].
This fault also has generated large
destructive earthquakes, e.g., 1892 (Mw 7.1), 1943
(Mw 7.6) and 2007 (Mw 6.4). These faults are

1. INTRODUCTION
The city of Padang is located on the west
coast of Sumatra in western Indonesia, lies close to
the Sumatran subduction zone that is formed by the
subduction of the Indo-Australian Plate beneath theEurasian Plate. Relative motion of the plates occurs
at a rate of about 50 to 70 mm/year and this is themain source of subduction-related seismicity in thearea [1]. Based on our catalog, several giant
earthquakes have occurred in this region sincerecords began: 1779 (Mw 8.4), 1833 (Mw 9.2),
1861 (Mw 8.3), 2004 (Mw 9.2), 2007 (Mw 7.9 and
8.4), 2009 (Mw 7.6), and 2017 (6.4). The
hypocenter of the Padang earthquake that occurred
on September 30, 2009 was located in the oceanslab of the Indo-Australian Plate at -0.81°S,
99.65°E and at a depth of 80 km. It produced a highdegree of shaking and the tremor was felt in the540

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

Indo-Australian Plate. It produced extensive
shaking and severe damage to houses and buildings
in Padang and Padang Pariaman, because its
epicenter was about 60 km offshore from Padang.
As the Padang earthquake was an intra-slab
earthquake at intermediate depth with a comparable
magnitude, the event did not generate a tsunami ofsignificance [5]. Due to this earthquake, 1117
people were reported killed, 1214 severely injured,1688 slightly injured, and 3 were left missing inWest Sumatra. The earthquake also destroyed many
houses, buildings and infrastructure (heavily
damaged houses numbered 114,797, with 67,198
moderately damaged and 67,837 slightly damaged).
In Padang, 5458 buildings sustained damage [6].
This event occurred at the end of the working day,just 15 minutes after offices and schools closed; if
it had struck earlier, the number of causalities would
definitely have been higher as a result of building
collapses. Several hours after Padang earthquake,
1st October 2009, Sumatran fault line generated
Mw7.1 and 10km depth. Due to this earthquake
destroyed many houses and building (heavily
damaged houses numbered 600, with 550
moderately damaged). Since Padang has highpotential to great earthquake shaking in near futurewith great acceleration too compare with previous
earthquake in 2009 [7]. With great potential shaking
occur in Padang for several return period ofearthquake events, Padang has highest vulnerability
to non engineered structure in Indonesia [8]. Basedon observation in Palu city, Palu its self has thesame soil characteristic as Padang city [9],[10].
There are four accelerometers in Padang.
Three were donated by Engineers Without Borders
Japan (EWBJ) and installed in 2008, and the otherwas installed by the Indonesian Government’s
Bureau of Meteorology, Climatology andGeophysics (BMKG). However, only one groundmotion record is available for the Padang
earthquake. Due to an electric power cut during theearthquake, only the BMKG device recorded thetime history of the earthquake. The observed record
shows about 20 s of strong shaking with a peakground acceleration (PGA) of 0.3 g and a
predominant period of 0.5 s [11]. Response spectraat law period is greater then Indonesia code for rockcondition (0.83g).The location of this station is a
mountainous suburb about 12 km in from the coast.
The subsurface condition at this station is rocky; theaverage shear wave velocity for the upper 30 m ofthe subsurface here, Vs30, is 1200 m/s [10].

capable of generating strong ground motion in the
future that would greatly affect vulnerable
structures. Based on the latest earthquake events
catalogs from USGS (2017) showed the number ofearthquake events with magnitude from 3 to 6 iscreasing within one month for each month in 2017.
It shows how the activity of plate currently is.

Fig.1 Seismicity of Sumatra Island from 2005 to
2010, Mw>6.5, <100km depth of hypocenter, andPadang City

Regional Geology and Recent Earthquake
The city of Padang, with a population of
914,968 people as of 2016, is the capital of West
Sumatra province. The location of the city center is
at 100.38°E, 0.95°S. The main part of Padang issituated on an alluvial plain between the Indian
Ocean and the mountains. For the most part, thecountainous area is formed of Tertiary sedimentaryrocks with outcrops of metamorphic rocks seen insome places. The alluvial plain spreads along thebase of the mountains and is roughly 10 km wide in
the east-west direction and 20 km wide in the northsouth direction.
The topography of the Padang region isvery similar to the tsunami-damaged area of Miyagi
Prefecture in Japan, that was inundated by as muchas 4-5 km from the coast after the March 11, 2011
Mw 9.0 Tohoku earthquake off the east coast of
Honshu. In Padang, about 650,000 people live in the
coastal area (covering about 60 km2). The
population density is very high, about 10,833
people/km2. The city is located on the coast of the
Indian Ocean between the Sumatran Fault and the
Sunda Trench Fault. Both faults are active with slip
rate ranging from 10 to 27 mm/year [3]. According
to our catalog, 3,174 events with a magnitude
greater than 4 occurred in this region from AD 1779
to 2017 [4]. The several giant earthquakes
mentioned previously have all been strongly felt
here. For example, the source of the 2009 Padang
earthquake was located in the ocean slab of the

DAMAGE FROM
EARTHQUAKE

THE

2009

PADANGThe city of Padang covers an area of about
695 km2 and is divided into 11 districts:
B. T. Kabung, K. Tangah, Kuranji, L. Begalung, L.
Kilangan, Nanggalo, P. Barat, P. Selatan, P. Timur,
541

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

where 𝑭𝑵𝑺𝒊 (𝝎) and 𝑭𝑼𝑫𝒊 (𝝎) denote the Fourier
amplitude of the NS, EW and UD components ofeach interval, respectively, and 𝝎 is the frequency.
We performed 140 single site surveys thatsampled every district of the city of Padang. Theseobservations were carried out in November 2008,
September, November, and December 2009 andJanuary 2010. The locations of observations areplotted in Fig.3. Microtremor was measured using aGPL- 6A3P sensor. The two horizontal (NS and
EW) and the vertical (UD) components were

P. Utara, and Pauh. 51.0% of the land is forested,
28.52% is used for farming, 9.54% for housing and7.1% for rice fields [12]. The population of morethan 914.968 is increasing by 1%-2% per year. The
K. Tangah district has the highest population andmost extensive area compared with the other
districts in the city.
The central business area of Padang isclose to the coast and consist of several district:
P. Barat, P. Utara, P. Selatan and P. Timur, B.T.
Kabung, K. Tangah. The downtown area is utilized
as a center of political and commercial activities.
Although the Padang earthquake affected all
districts of the city, the major damage occurred
downtown, because about 80% of population lives
near the coast. The majority of houses in the city areone- and two-storey non-engineered structures.
These structures are typically built of confined
masonry, with reinforced-concrete (RC) frames
acting as confinement for the brick masonry walls.
There are three general categories of houses in
Padang: permanent houses (RC), semi-permanenthouses (mix of RC and wood) and traditional
houses (wood). Unfortunately, no detailed damage
statistics are available for each type of building, so
we cannot classify the category of the house. This
earthquake also affected lifelines in Padang. The
strong ground shaking destroyed public water
distribution pipes leading to 2,906 reported leakage
points in total [13]. Damage to pipelines forced thecessation of water delivery to consumers for several
weeks.
2. SITECHARACTERIZATIONMICROTREMOR OBSERVATION

(a)

BY

Single Microtremor Observation
A microtremor is a very small groundmotion that can be recorded on the ground surface.
It can be produced by a variety of excitations (e.g.,wind, traffic, breaking sea waves). A fullmicrotremor record can be described by one verticaland two horizontal components. Our analysis was
conducted using the recorded microtremor. First,
the horizontal and vertical spectrum ratios (HVSR)
were computed for all sites (Fig. 2). HVSR
(Horizontal-Vertical Spectra Ratio) is consists inestimating the ratio between the Fourier amplitude
spectra of the horizontal (H) to vertical (V)components of ambient noise vibrations recorded at
one single station.
The peak period of the HVSR is known tocorrespond to the resonant period of the site. Thismethod postulates the shape of the Fourier
spectrum . Equation. (1) shows the method used to
calculate HVSR using the observed records.

𝑯𝑽𝑹𝒔 =𝑭√ 𝑵𝑺𝒊(𝝎)𝟐 +𝑭𝑭𝑾𝒊 (𝝎)𝟐
𝑭𝑼𝑫𝒊 (𝝎)𝟐(b)Fig. 2 Observation sites and results of HVSR.(a)Microtremor single observation sites at every
district in Padang, (b) Distributed HVSR ratio.
The recorded simultaneously for 10 minuteswith a 100 Hz sampling frequency. We estimatedthe distribution of the peak periods of the HVSRs
for all sites in Padang using the ordinary kriging
technique. From single observations, we obtained a
predominant period of 2.0 to 4.0 s in the central
business district and less than 1.0 s in the

(𝟏)

542

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

mountainous areas. These results indicate an affectrelated to the thickness of alluvium in the coastal
area of Padang city, which decreases in thickness
inland.
3.

SITE CHARACTERIZATION BY
MICROTREMOR OBSERVATION

Microtremor Aray Observations
The velocity of surface waves is well known tovary as a function of frequency (or period) due todispersion. Since dispersion is a function of
subsurface structure, the substructure can be
estimated from a Rayleigh wave dispersion curve.
We carried out microtremor array investigations
using 12 sites at several districts in Padang (Fig.3).
Dispersion curves were calculated using the SPAC
method [13] to obtain a velocity structure from themicrotremor recordings. An outline of theprocedure follows. It is necessary to simultaneously
record microtremors with an instrument array of atleast three stations. The dispersion of a measured
surface wave is a response to the subsurface
structure directly below the array, and theestimation of the subsurface structure causing thedispersion is determined by means of inversion ofRayleigh waves. The basic principles of the SPAC
method assume that the complex wave motions of
microtremors are stochastic processes in time andspace. A spatial autocorrelation coefficient for acircular array can then be defined when the waves
composing the microtremor (i.e., the surface waves)are dispersive. Hence, the spatial autocorrelation isa function of phase velocity and frequency.
Rayleigh wave records were measured for the 12array observation sites using the SPAC method andinversion analysis was undertaken on the observed
dispersion curves to estimate the soil profiles. In the
inversion analysis, the Particle Swarm Optimization(PSO) algorithm was adopted to solve the nonlinear optimization problem [14]. The basic
procedures of PSO are outlined below. he particle
swarm concept originated as a simulation of
simplified social system. The original intent was tographically simulate the choreography of bird of abird block or fish school. However, it was foundthat particle swarm model can be used as an
optimizer, PSO simulates the behaviors of bird
flocking. Suppose the following scenario: a groupof birds are randomly searching food in an area.
There is only one piece of food in the area being
searched. All the birds do not know where the foodis. But they know how far the food is in each
iteration. So what's the best strategy to find the
food? The effective one is to follow the bird which
is nearest to the food. PSO learned from thescenario and used it to solve the optimization
problems. In PSO, each single solution is a "bird" in

Fig.3 Array observation sites
the search space. We call it "particle". All ofparticles have fitness values which are evaluated by
the fitness function to be optimized, and havevelocities which direct the flying of the particles.
The particles fly through the problem space byfollowing the current optimum particles. PSO is
initialized with a group of random particles(solutions) and then searches for optima by
updating generations. In every iteration, eachparticle is updated by following two "best" values.
The first one is the best solution (fitness) it has
achieved so far. (The fitness value is also stored.)This value is called pbest. Another "best" value thatis tracked by the particle swarm optimizer is the bestvalue, obtained so far by any particle in the
population. This best value is a global best andcalled gbest. When a particle takes part of the
population as its topological neighbors, the bestvalue is a local best and is called lbest.
We estimate the subsurface structure of themodel by solving a nonlinear minimization problem
with the fitness function below.
𝒕
𝒕
𝒕
𝒕
𝒗𝒕+𝟏
𝒊𝒅 = 𝝎 𝒗𝒊𝒅 + 𝒄𝟏 𝒓𝟏 (𝒑𝒊𝒅 − 𝒙𝒊𝒅 ) + 𝒄𝟐 𝒓𝟐 (𝒑𝒈𝒅 −(1)
𝒙𝒕𝒈𝒅 )
𝒕+𝟏(2)
𝒙𝒊𝒅 = 𝒙𝒕𝒊𝒅 + 𝒗𝒕+𝟏
𝒊𝒅
𝑡
where
𝑣𝑖𝑑
is particle velocity of the𝑡
𝑖 𝑡ℎ component in dimension d in the interaction, 𝑥𝑖𝑑
is the particle position of the 𝑖 𝑡ℎ component indimension d in interaction,𝑐1 and 𝑐2 are constantweight factors, 𝑝𝑖 is the best position achieved byparticle 𝑖 , 𝑝 𝑔 is the best position found by theneighbor of particle 𝑖, 𝑟1 and 𝑟2 are random factors
in the [0,1] interval and 𝜔 is the inertia
weight.Before performing the inversion analysis,
the subsurface structure was assumed to consist ofhorizontal layers of elastic and homogeneous media
above a semi-infinite elastic body. The shear wave
velocity and thickness of each layer are theparameters determined by the inversion analysis.
The results enable us to determine the condition of543

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

From the SPAC coefficient ρ(r,ω), the phasevelocity is calculated for every frequency from theBessel function argument of equation. 15 and thevelocity model can be invert. The layer thickness
and the average S-wave velocity in Figure 6 eacharray site. For the average S wave velocity modelobtained by averaging the estimated groundstructure of the array site was to be calculated by aweighted average using a S-wave velocity
structure is estimated as a weighted layer thickness.

shallow subsurface structures (Ono et al., 2010).
The outline of the SPAC method for the phasevelocity calculation of Rayleigh waves follows.

𝟏 ∞∫ 𝒇(𝒕) ∙ 𝒆𝒙𝒑(−𝒊𝝎𝒕) 𝒅
𝟐𝝅 −∞= 𝑨𝒇 (𝝎) ∙ 𝒆𝒙𝒑 (−𝒊∅𝒇 (𝝎)) (𝟑)∞𝟏
𝑮(𝝎) =∫ 𝒈(𝒕) ∙ 𝒆𝒙𝒑(−𝒊𝝎𝒕) 𝒅𝒕
𝟐𝝅 −∞= 𝑨𝒈 (𝝎)𝒆𝒙𝒑 (−𝒊∅𝒈 (𝝎)) (𝟒)𝑭(𝝎) =𝝎𝒓
𝑹𝒆(𝑺𝑷𝑨𝑪(𝝎, 𝒓)) = 𝑱 () (𝟏𝟒)𝒄(𝝎)From the SPAC coefficient 𝝆(𝒓, 𝝎) , the phasevelocity is calculated for every frequency from theBessel function argument of equation. 15 and thevelocity model can be invert. The layer thickness
and the average S-wave velocity in Figure 6 eacharray site. For the average S wave velocity modelobtained by averaging the estimated groundstructure of the array site was to be calculated by aTypeequation
here.using a S-wave velocity structure
weighted
averageis estimated as a weighted layer thickness.

𝑨𝒇 (𝝎) ， 𝑨𝒈 (𝝎) and ∅𝒇 (𝝎) ，are difference
between the amplitude of ∅𝒈 (𝝎), 𝑭(𝝎) ，𝑮(𝝎) respectively. Futher cross correlation in
the frequency region of the two waveforms will
be as follows.
𝑪𝑪𝒇𝒈 = 𝑭(𝝎) ∙ ̅̅̅̅̅̅̅
𝑮(𝝎) = 𝑨𝒇 (𝝎) ∙ 𝑨𝒈 (𝝎) ∙𝒆𝒙𝒑( 𝒊∆∅(𝝎))(𝟓)

It shows the phase difference of∆∅(𝝎)𝝎𝒓∆∅(𝝎) =
𝒄(𝝎)

𝑯
̅̅̅̅
𝑽𝒔 = ∑ 𝑽𝒔𝒊 ∙ 𝒊(6)𝑯𝒄(𝝎) is the phase velocity from the phase

From the dispersion curve, we can produce
an interpretation Vs30 (average shear wave velocity
for the upper 30 m) as show in Table 4, shows thecontours of Vs30 for every 200 m/s increment andsoil characteristic every layer.

difference.
𝑪𝑪𝒇𝒈 = 𝑨𝒇 (𝝎) ∙ 𝑨𝒈 (𝝎) ∙𝒆𝒙𝒑 (𝒊

𝝎𝒓
𝒄(𝝎)

)

(𝟕)

The complex coherence of two waveforms isdefined by the following equation.
𝑪𝑪𝒇𝒈 (𝝎)𝑪𝑶𝑯𝒇𝒈 (𝝎) =𝑨𝒇 (𝝎) ∙ 𝑨𝒈 (𝝎)𝝎𝒓(𝟖)= 𝒆𝒙 𝒑 (𝒊)𝒄(𝝎)𝑹𝒆 (𝑪𝑶𝑯𝒇𝒈 (𝝎)) = 𝐜𝐨𝐬 (𝒊．

𝒄(𝝎, 𝝋) =

𝝎𝒓
𝒄(𝝎)

𝒄(𝝎)

Type equation here.

) (9)
(10)

𝒄𝒐𝒔𝝋
𝟐𝝅
𝝎𝒓
𝑺𝑷𝑨𝑪(𝝎, 𝒓) = ∫𝟎 𝒆𝒙𝒑(𝒊𝒄𝒐𝒔𝝋)𝒅𝝋
𝟐𝝅
𝒄(𝝎)
𝟏

(11)
𝑹𝒆(𝑺𝑷𝑨𝑪(𝝎, 𝒓)) =𝟏 𝟐𝝅
𝝎𝒓∫ 𝐜𝐨𝐬(𝒊 𝒄(𝝎) 𝒄𝒐𝒔𝝋)𝒅𝝋
𝟐𝝅 𝟎

𝑱(

𝝎𝒓
𝒄(𝝎)

)=

𝟏 𝟐𝝅
𝝎𝒓
∫ 𝒆𝒙𝒑(𝒄(𝝎) 𝒄𝒐𝒔𝝋)𝒅𝝋
𝟐𝝅 𝟎

(15)

(a)

(12)
(13)

where 𝑱𝒐(𝒙) is the zero-order Bessel function of thefirst kind of x, and 𝒄(𝝎) is the phase velocity at
frequency 𝝎. The SPAC coefficient 𝝆(𝒓, 𝝎) can beobtained in the frequency domain using the Fouriertransform of the observed microtremors.

544

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

The vulnerability of an element is usually
expressed as a percentage loss (or as a value
between zero and one) for a given hazard severity
level [16]. In a large number of elements, likebuilding stocks, vulnerability may be defined interms of the damage potential to a class of similar
structures subjected to a given seismic hazard.

(b)

Fig.5 Ground motion whole Padang city.
Vulnerability analysis reveals the damageabilityof the structure(s) under varying intensity or
magnitudes of ground motion. Multiple damage
states are typically considered in the analysis. Basedon the data of damaged houses by ground shakingof Padang earthquake in 2009.

(c)

5.

ASSESSMENT
HOUSESTORESIDENTIAL

Survey Outline
The main purpose of assessment of housing has
been used to quantify the structural condition after
giant earthquake based on observed or interviewed
to the owner its self. Since Padang has been
conducted for seismic intensity in 2011 [11]. The
method was originally developed by Japanarchitecture disaster prevention association
earthquake. This method widely applied to assesshouses for preventing future ground shaking due topredicted earthquake. It has been useful for
estimating house condition such as the earthquake
resistant performance and earthquake resistantrepair to improve earthquake-resistant performancethe observed houses by knowing the weak point at
the structural. The original questionnaire sheet was
written in Japanese (juutaku day taishinnshinndan);however, it was translated into Indonesian language
for its application to Padang city. The questionnaire
has 10 items that cover recognition of structural
condition in general, had experience past giant
earthquake and strengthened after struck byearthquake. Some sentences were modified to make(d)
Fig.4 Observation sites, soil profile anddistribution of average shear wave
velocity, (a)Array observationsites, (b) layer 1 (Vs < 400m/s) and (c)layer 2 (Vs >400m/s), (d) Distribution of
Vs30 (m/sec).
4.

VULNERABILITY ASSESSMENT

Vulnerability can simply be defined as thesensitivity of the exposure to seismic hazard(s).
545SEE - USQ, Brisbane, Australia, Nov.13-16, 2017it more relevant to local people while not changing

the city The interviewers explained each item of theFig. 6 Assessment distribution map in Padang

Fig. 7 Survey result show residential condition distribution in Padang cityquestionnaire to residents, discussed the responses
given, and documented the answers on the standard
answer sheets. The results of the questionnaire
survey conducted to estimate the houses condition
distribution in Padang after earthquake in Padang
2009. The interview distribution showed in figure
11 and its result showed in figure 12, the interview
result is indicated 98% of houses in Padang withscore < 8 (Japan architecture disaster prevention
association), its means the houses need to consultand discuss with experts directly soon as possible.

the original topics covered by questionnaire. People
living near the observation points were interviewed
using the questionnaire [17][18]. The questionnaire
survey was conducted from October 2nd to
November 23rd , 2016. The survey was carried out
in all districts of Padang by distributing andcompleting 1235 the questionnaire. People living
near the observation points were interviewed using
the questionnaire. The questionnaire survey was
conducted from October 2nd to November 23rd, 2016.
The survey was carried out in all districts of Padang
by distributing and completing 1235 questionnaires
through a direct interview process with residents of546

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

damage report and verification for West
Sumatra due to Padang
earthquake”,
www.bnpb.go.id.
[7] Rusnardi Rahmat Putra, J. Kiyono, Y. Ono, H
Parajuli. 2012, Seismic Hazard Analysis forIndonesia, Journal of Natural Disaster Science,Vol. 33, No.3 pp.59-70, June 2012.
[8] Rusnardi Rahmat Putra, Junji Kioyono, Aiko
Furukawa, Vulnerability Assessment of Non
Engineering Houses Based on Ddamage Dataof the 2009 Padang Earthquake in Padang
City, International Journal of Geomate, Vol 7,
No.2 (SI.No.14) pp.1076-1083,2014[9] Rusnardi Rahmat Putra, Junji Kiyono, Yusuke
Ono, Yasuo Yoshimoto, Syharil, Determined
Soil Characteristic of Palu in Indonesia byUsing Microtremor Observation, International
Journal of Geomate, Vol. 10, No.2 (SI. No. 20)
1737-1742, 2016.
[10] Rusnardi Rahmat Putra, Estimation of Vs30
Based on Soil Investigation by Using
Microtremor Observation in Padang,Indonesia, International Journal of Geomate,
Oct., 2017, Vol.13, Issue 38, pp.135-140,
2017[11] Rusnardi Rahmat Putra, J. Kiyono, Y. Ono,
Estimation of Earthquake Ground Motion in
Padang City, Indonesia. International Journalof GEOMATE, Vol..1 (S1.No.1), pp.71-77,
October, 2011.
[12] Padang City Statistic Center Agency of Local
Government,www.padangkota.bps.go.id.
2017.
.[13] Aki, K. 1957.”Space and time spectra ofstationary stochastic waves, with specialreference to microtremor”, Bull. Earth. Res.
Inst., Vol. 35, No. 3, 415-456.
[14] Keneddy, J. and Eberhart, R. C. Particle swarm
optimization, Proc. Of IEEE International
Conference on Neural Networks, Vol.4,pp.19421948, 1995
[15] Ono, Y., Kiyono, J., Rusnardi, P. R. andNoguchi, T. 2010. Microtremor Observation in
Padang City, Indonesia to Estimate Site
Amplification of Seismic Ground Motion, Proc.
of International Symposium on a Robust andResilient Society against Natural Hazards andEnvironmental Disasters and the third
AUN/SEED-Net Regional Conference on
Geodisaster Mitigation, pp.386-391.
[16] Baker, Jack W. 2008. “Introduction
Probabilistic Hazard Analysis”, handbook.
Version 1.3 Oct 1st 2008.
[17] Fallahi. A, P. Teymourzadeh, M. Miyajima, T.
Tobita and R. Alaghebandian (2008).
Statistical Study to Determine JMA
Earthquake Intensity by QuestionnaireSurvey
in 2003 Bam (Iran) Earthquake, The 14 World
conference on earthquake engineering,

6. CONCLUSION
According to microtremor observations,
downtown Padang is underlain by soft soil
conditions (Vs30<400 m/s). Consistent results
concerning the soil condition were found based on
predominant period observations.
In both cases, the coastal area was determined
to have a soft soil conditions (Vs30<400 m/s), a
longer predominant period, and a greater seismic
intensity.
Padang has a thick alluvial layer in the coastal
area (with a predominant period between 2.0 and
4.2 s) that thins toward the mountains (with apredominant period less than 2.0 s). The subsurface
geology also changes slowly from soft soil in the
coastal area to rocky conditions in the mountains.
The results show clear information on soil
condition especially at the downtown andresidential houses current condition with 98% ofhouses need to consult to expert as soon as possible
as a way to mitigate future earthquake event.
7. ACKNOWLEDGEMENTS
The author would like to thank to Professor Junji
Kiyono from Kyoto University who provided
strong support throughout the period. Thanks also
go to Professor Yusuke Ono and Professor Noguchi
from Tottori University, Japan for their great
assistance during the field survey. Thanks to Dr.
Safriani from Universitas Negeri Padang as
research partner. Finally would like to thanks
Indonesian government DIKTI who provided
financial support on research schema Penelitian
Unggulan Perguruan Tinggi year 2016.

8.

REFERENCES[1] Prawirodirjo, L., Y. Bock, J.F. 2000, “Onecentury of tectonic deformation along theSumatran fault from triangulation and global
positioning system surveys”, J. of Geophysicalresearch, 105, 28, 343-28,363.
[2] Aislinn Laing, 2009, “More than 1000 feared
deadinSumatraearthquake’,
www.telegraph.co.id.
[3] Natawidjaja and WahyuTriyoso 2007. “The
Sumatran fault Zone-from Source to Hazard”, J.
of Earthquake and Tsunami, Vol. 1 No. 1, 21-47.
[4] Rusnardi Rahmat Putra, J. Kiyono, Y. Ono, H
Parajuli, “Seismic Hazard Analysis For
Indonesia”. Journal of Natural Disaster Science,Vol. 33, No.3 pp.59-70, June 2012.
[5] EERI 2009. “The Mw 7.6 Western Sumatra
Earthquake of September 30, 2009”, Special
report.
[6] BNPB 2009 (National Disaster Management
Agency of Indonesian Government). “Total
547

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

October 12-17, Beijing, China.
[18] Sutrisno, Rusnardi, Ganefri, A Comparative
Study on Structure in Building Using Different
Partition receiving expense earthquake,
International Journal of Geomate, Vol.13,
Issue 37, pp.34-39, 2017.

548

Third International Conference on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017, ISBN: 978-4-9905958-9-0 C3051

RAINWATER HARVESTING STUDY AT MASJID JAMEK RIYAHDUS
SOLIHIN, PINTAS PUDING, BATU PAHAT JOHOR MALAYSIA
Amir Hashim Mohd Kassim1, Siti Mariam Sulaiman2, Radin Maya Saphira Radin Mohamed3 and Adel Ali
Saeed Al Gheethi4
1,2,3,4
Department of Water & Environmental Engineering,Faculty of Civil & Environmental Engineering,
UniversitiTun Hussein Onn Malaysia, 86400 Pt. Raja, Batu Pahat, Johor, Malaysia.
ABSTRACT
Harvesting rainwater contribute towards a sustainable living. It eliminate the wastage and reduce the dependencyof potable water. The demand of potable water increases in accordance to the population. Rainwater harvestingis capable to combat water crisis and serves as an alternative water resources during water shortage. The present
study proposed a rainwater harvesting system for the mosque and obtain the rainfall amount at study area. The
method used for designing the rainwater harvesting system is referred to MSMA 2nd Edition. The system isconsists of downpipe filter (4"/ Ø150 mm), Eaves gutter (16, 000 mm²) first flush diverter 150 mm (63 liter; 1.78
length) and: taper tank (600 liters). Rainfall data for study area was recorded by HOBO tipping rain gauge forfour months. Rainwater was calculated and harvested 116.7% yield to the water demand for the study area. The
rainfall for four months at the study area showed that the rainwater demand was sufficient to be collected andused for the mosque activities. The highest rainfall data collected was 75.2 mm. This study would help to initiate
a starting point to create a green mosque concept into reality. Furthermore, this system applied the concept ofgreen building that create environmental friendly surrounding as a stepping stone to educate and at the same timesave the environment and minimize the energy wastage.
Keywords: Design of rainwater harvesting system, MSMA, Rainfall data
problem of water quality. Urban development,
human activities and industrialization deteriorate thequality of water and, in some cases, make it unsafe
for consumption [3]. Some effort has been made toreuse ablution water from mosques (masjid), which
it has low contaminant and consist of high volume
from the cleansing ritual [4] [5]. However, theutilization of the rainwater harvesting in mosque has
not widely discussed in the case study.
Developing of region increase the water
demand and reduce capability of drainage area tomaintain overland flow judging the increasing of
runoff coefficient. Fast growing development in
Parit Raja especially at Pintas Puding area now has
begun to increase of the water demand due to therapid urbanization and dependence on main watersupply.
In order to overcome the water crisis, domestic
rainwater harvesting has been carried out which isan alternative solution for these problem. Rainwater
harvesting is a simple ancient technique of collectwater and storage. This technique has been practiced
in Sri Lanka to meet the growing water demand on
water supply; a good example is the sophisticatedrainwater cum reservoir system in 5th century
Sigiriya fortress complex. In Malaysia, a study on
rainwater harvesting and utilization system (for non
potable household use), coupled with detention
storage (to reduce peak storm runoff), for double
storey terrace house at Taman Wangsa Melawati,
Kuala Lumpur was carried out. Therefore, all of theadvantages of using rainwater harvesting will be

INTRODUCTION
The rainwater is a precious gift for us by nature.
Since the creation of the Earth, rain has helped
nourish the growth of myriad of flora and fauna andhas provided precious drinking water for all
creatures. Rainwater harvesting is as old as mankind.
About 4,000 years ago in Rome, the Romans havebeen used rainwater for domestic purposes. Roman
villages and cities of that time planned to takeadvantage of rainwater for drinking [1]Clean water is a valuable and important source.
Since clean water is important, it is seen as a waste
for it to be used for flushing of toilets and watering
plants. Rainwater is one of reliable source of cleanwater it can be used as a substitute by collecting andutilize it rather than let it go to waste. A part from
that, by collecting rainwater from roof, flash flood
affect can be reduced as few percentage of rainfall isretained and thus reduce the volume of surface
runoff. Besides, by using rainwater as an alternative,
clean water can be saved and used for otherpurposed and simultaneously decrease of demand ofclean water resulted in lower cost of water bill andcost of operation in the water treatment plants. The
use of untreated rainwater for non – potable uses thatwould otherwise be supplied by potable water
ultimately conserves municipally supplied potablewater [2].
Water shortage is becoming the number one
problem in the world today. Moreover, the problemof water scarcity is strongly connected to the549

SEE-USQ, Brisbane, Australia, Nov.13-16, 2017combined in this further study to overtake the watercrisis besides reducing water bills for the mosque.
Rainwater harvesting is a technology used forcollecting and storing rainwater from rooftops, theland surface of rock catchments using simple
techniques such as jars and pots as well as more
complex techniques such as underground checkdams and ponds. Commonly used systems areconstructed of three principal components; which
are the catchments area, the collection device andthe conveyance system. The captured rainwater
could be used for domestic usage such as drinking,cooking, toilet flushing, and other public facilities.
This study was conducted to propose arainwater harvesting system at the study area withthe collected data.

study. Rooftop dimension such as width, base andslope was taken by measure at the study area. The
total catchment area can be determined by using Eq
2.
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐ℎ𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 = 𝐴𝐴ℎ × 𝐴𝐴𝐴𝐴
Where,
Ah= plan area (m2)
Ar= rise vertical area (m2)

(Eqn. 2)Gutter and RWDP Sizing

METHODOLOGY

Gutter and downpipe size was determined byreferring to the design chart from MSMA 2nd
Edition (Chapter 6) [6]. The size determine byconsidering the rooftop gradient and the total flow of
the rainfall.

Design of Rainwater Harvesting System

First Flush Diverter

The study area is located at Masjid Jamek
Riyahdus Solihin in Batu Pahat, Johor, Malaysia.
This mosque is located nearby to Sekolah
Kebangsaan Pintas Puding, and Kolej Jururawat
Masyarakat Batu. Rainwater harvesting is atechnique of collecting rainfall as a source of watersupply for household, commercial and industrial
premises. The planning and development ofrainwater harvesting system shall be carried out
adhering to the principles and guideline describes in
MSMA (Urban Stormwater Management). The
value of rainwater as the primary source of cleanwater is always ignored. Rainwater harvesting usingroof catchments is the easiest and most common
method.

First flush diverter is a must component in rainwater
harvesting. It separate debris from entering thestorage tank to control the quality of the rainwater.
First flush diverter was determined according tostandard as stated in MSMA 2nd Edition (Chapter 6)[6]. First flush volume requirement are based on theroof area or the catchment area. Figure 1 shows theillustration of the first flush diverter.

Determine Average Rainfall Intensity
Average rainfall intensity determined by referring to
the intensity – duration – frequency (IDF) curves atstudy area city or the nearest. Basically, to obtain themost accurate amount of the rainfall intensity, Eq.
(1) can be used.

Fig 1 Illustration of first flush diverter
Tank size Estimation

3(Eqn. 1)
Where,
i = Average rainfall intensity (mm/hr);
T = Average recurrence interval–ARI (0.5 ≤ T ≤ 12month and 2 ≤ T ≤ 100 years)
d = Storm duration (hours), 0.0833 ≤ d ≤ 72; andλ, K, θ and Ƞ = Fitting constants dependent on therain gauge location

There are various types of rainwater harvesting tank.
In general, the rainwater tank can be divided intoeither above – ground tank or below – tank. The tankshapes can be circular, or rectangular. The tanksizing was determined based on the Yield Before
Spillage (YBS) model. Tank size of 1 m3 is for roof
area of 100 m2. Tank size (m3) can be determinedaccording to Eq. 3.
𝑺𝑺𝑺𝑺 = 𝟎𝟎. 𝟎𝟎𝟎𝟎 𝑨𝑨𝑨𝑨
(Eqn. 3)

Determine the Catchment Area

Where,
St = Tank Size (m3)
Ar = Rooftop Catchment Area (m2).

The rooftop act as the catchment area for this550

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

Determine the Water Demand
Water demand was determined based on the average
consumption, and average total rainwater demand at
the study area. Total use per day and the annual
rainwater demand need to be determined in unit of
m3 and in percentage. Water demand determination
is important to determine whether the rainwatersupplied is sufficient to fulfill the water demand at
study area. Table 1 shows the estimation amount ofwater used for different application.

Johor

Λ

κ

θ

η

Stor JPS Johor

59.972

0.163

0.121

0.793

54.265

0.179

0.1

0.756

Johor Silica

59.06

0.202

0.128

0.66

Balai Polis Kg.

50.115

0.191

0.099

0.763

SM Bukit Besar

50.554

0.193

0.117

0.722

Setor JPS

64.099

0.174

0.201

0.826

55.864

0.166

0.174

0.81

61.562

0.191

0.103

0.701

Emp. Semberong

60.568

0.163

0.159

0.821

Pintu Kaw. Tg.

80.936

0.187

0.258

0.89

JPS Kluang

54.428

0.192

0.108

0.74

Ladang Chan

57.188

0.186

0.093

0.777

Ladang Kekayaan

53.457

0.18

0.094

0.735

Ibu Bekalan

52.177

0.186

0.055

0.652

56.966

0.19

0.144

0.637

Bahru
Pusat Kem. Pekan
Nenas

Seelong

Table 1 Amount of Water Uses for Different
Applications (DID, 2009)

BatuPahat
Ladang Ulu
Remis
Simpang Masai
K. SediliAgasCollection of Rainfall Data

Wing

Collection of rainfall data at the study area is taken
for almost four months at the study area. The rainfall
data collected using the rain gauge that was installeda few meters from the location of the RWH system.
The rainfall data and temperature for every 3
minutes from 28th August 2016 were recorded until
20th November 2016 using HOBO tipping rain gauge.

KahangJalanKluang–
Mersing
LadangLabis

45.808

0.222

0.012

0.713

RESULTS AND ANALYSIS

Rmh. Tapis

45.212

0.224

0.039

0.711

Average Rainfall Intensity

Segamat
59.5

0.185

0.129

0.623

62.04

0.215

0.103

0.592

Kg Peta Hulu Sg

In order to maximize the error in estimating theamount of rainfall intensity values from the IDF
curves, the empirical equation 1 was applied. The
fitting constants dependent on the rain gauge
location (Table 2)

Endau
Setor JPS Endau

Table 2 Fitting constants dependent on the rain
gauge (MSMA 2nd Edition)

The system designed using the average
recurrence interval – ARI, T is for 10 years with 10
minutes of storm duration, d.

Catchment Area
Plan area, Ah= 25 m×22 m= 550m2
Rise Vertical area, Ar =25×0.5 m=12.5m2

551

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

the contaminants and debris collected from the roof
surface from entering the storage tank.

Total catchment area

= Ah×Ar (Eqn. 2)= 550 + (12.5/2)=556.3m2
Calculation of Gutter and Downpipe Size

Table 4 First Flush Requirement According To RoofArea (DID, 2009)

As the gradient of the rooftop surface is flatter than
1:500, with the calculated value of average rainfall
intensity and total catchment area, the sizing of theeaves gutter is able to be identified as 15.75 m2 with
4.0L/s total flow. Therefore, 150 mm diameter ofcircular downpipe was taken from Table 3.

Minimum Nominal Size ofSize(mm2)

Downpipe (mm)Circular

4,000
4,200

75

4,600
4,800
5,900
6,400
6,600
6,700
8,200
9,600
12,80016,00018,40022,000Less than 100

0.025 – 0.05

100 – 4356

0.05 – 2.5
2.5
3

Note: Adopt first flush of 5 m if surface contains
excessive soil, dust or debris.
Tank Size Estimation
Based on the Yield Before Spillage (YBS) model
suggested for the procedures in estimating the
rainwater availability, the estimation of the Average
Annual Rainwater Yield (AARY) was carried out by
using the water balance model for the selected towns
in Malaysia and summarize that tank size for
Malaysia regardless of location is 1m3 for roof areaof 100m2. With the 10 mm of rainfall is equivalent
to be stored from 100 m2 of rooftop area. The tanksize was determined by using Equation 3.

Rectangular
65 x 5075 x 5085
100 x 50

St = 0.01Ar

90
75 x 70

100 x 75
125

150

Not
applicable(Eqn. 3)

Where,
St = Tank Size (m3); andAr = Rooftop Catchment Area (m2).
St = 0.01 (556.3)
St = 5.563m3

100

19,20020,000First Flush Volume (m3)Greater than 4356

Table 3 Required Size of Downpipe for Eaves
Gutter (AS/NZS 3500.3, 2003)
Eaves Gutter

Roof Area (m2)

100 x 100
125 x 100

Water Demand

150 x 100

The rainwater demand depends on the number ofpeople using the water, average consumption andalso the range of uses by the consumer. The water
demand for the rainwater influences theeffectiveness and availability of designed rainwater
storage tank.

125 x 125
150 x 125

This study determines the size of the down pipe byusing the size of the gutter. However, it is different
for other researcher. Study by Villarreal and Dixon(2005)[7] determine the size of the downpipe byreferring to the material of the downpipe itself.
Villarreal and Dixon (2005) [7] use concrete pipewith diameter of 300 mm compare to otherresearcher with the use PVC pipe with diameter of
65 mm. The pipe size for this study is within therange from the previous study which shows that thesize is suitable to be used.

Table 5 Rainwater Demand for Domestic
Application (DID, 2009)
Use

Type

(Application)

Average

Average Total

Consumption

Rainwater
DemandToiletGeneralwashing

Single9 litres per

120 litres per

Flush

flush

day

-

10-20 litres

150 litres per

per minuteday

First Flush Volume
Total use per day = 120 l/day + 150 L/day= 270 l/day

The first flush need to install with suitable volume
according to its standard as suggested in the MSMA
2nd Edition (Chapter 6). This is important to prevent552

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

The annual rainwater demand = 365 days × 300
L/day=98.55 m
Compute the Average Annual Rainwater Yield fortown (m3)
From Table 5, take the nearest Kluang, The AARY
for 1m3 tank size = 1 x 115 = 115m3
Compute the percentage of water yield overrainwater demand
Percentage of rainwater yield over rainwater demand= (115/98.55) x 100 = 116.7%
Rainfall Data
Fig. 3 Recorded rainfall data from infokemarau(2017)The rainfall data was collected for almost fourmonths (August until November) using the rain
gauge that installed few meters from the location of
the RWH system. The rainfall data and temperaturefor every 3 mins from 28th August 2016 wererecorded until 20th November 2016 using HOBO
tipping rain gauge. Figure 6 shows the rainfall
amount and temperature collected at study area.

CONCLUSION
From the study, it is promising if the rainwater
harvesting is practices in mosque, it serves as a
substitution for non – potable water usage fordomestic activities such as flushing and irrigationand supplying freshwater in the face of increasingwater scarcity and escalating demand. The
component that needs to be used for this RWH
system is design based on the MSMA 2nd Edition.
The components proposed Downpipe filter (4"/
Ø150mm), Eaves gutter (16, 000mm²), First flush
diverter 150mm (63 liter; 1.78 length), : taper tank
(600liters) and Outgoing Distributions Pipe fromRWH Tank Main Discharge Point to Nearest
Irrigation Tap or Usage Points (Ø35mm). The
rainwater is calculated 116.7% yield to the water
demand for the study area. The rainfall for fourmonths at the study area shows that the rainwater
demand is sufficient to be collected and used for themosque activities. The highest rainfall collect isrecorded to be 75.2 mm.
By using rainwater, many benefits can be seen
economically and environmentally where water canbe saved and can reduce impacts from flash flood
phenomena respectively. It is important that mosquewould take rainwater harvesting system seriously inrealizing its objectives to become a green mosquethat creates an environmental friendly surroundings
and the same time save the environment andminimize the energy usage.

Fig. 2 Rainfall amount and temperature collected
According to website from the Department of
Irrigation
andDrainage
Malaysia(DID),
http://infokemarau.water.gov.my/realtime.cfm,2017), the rainfall data that were recorded at SriMedan show that the highest rainfall data recorded is77.00 mm which is the same as the rainfall data in
Figure 3. The data are comparable due to Malaysia’s
equatorial climate. Equatorial climate can be definedas the climate where there is a constant temperature,high moisture content and generally high rainfall
intensity. Figure 3 shows the rainfall amounts thatwere obtained from infokemarau website
http://infokemarau.water.gov.my/realtime.cfm,2017),ACKNOWLEDGEMENT
We wish to thank research grant FRGS 1453 and
IGSP vot U682 for ﬁnancial assistance during thestudy.
REFERENCES[1] Amir Hashim Mohd Kassim (2006),
Improvement of Rainwater Quality using the Bio–sand Filtration, Department of Water Resources andEnvironmental Engineering, Faculty of Civil and553

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

Environmental Engineering, Kolej Universiti
Teknologi Tun Hussein Onn (KUiTTHO).
[2] Persyn R., Russell A., Porter D. O. and Silvy
V.A.,(2004).RainwaterHarvesting,
Texas
Cooperative Extension, Texas agricultural andMechanical University System.
[3] Nazahiyah Rahmat, Zarina Md Ali, SabariahMusa (2008), Treatment of Rainwater Quality Using
Sand Filter. Departmentof Water andEnvironmental Engineering, Faculty of Civil andEnvironmental Engineering University Tun Hussein
Onn Malaysia (UTHM, Malaysia).
[4] RMSR Mohamed, MN Adnan, MA Mohamed,
AHM Kassim Conventional Water Filter (Sand andGravel) for Ablution Water Treatment, Reuse
Potential, and Its Water Savings, Journal of
Sustainable Development 9 (1), 35 (2016).
[5] RMSR Mohamed, AA Al-Gheethi, JA Rahman,
AHM Kassim, S Musa, Reuse of Ablution Water to
Improve Peat Soil Characteristics for Ornamental
Landscape Plants Cultivation, MATEC Web ofConferences 103, 05003 (2017).
[6] Manual Mesra Saliran Alam (MSMA) 2nd
Edition (Chapter 2 to 6), Department of Irrigation
and Drainage Malaysia.
[7] Villarreal, E. L. and Dixon, A. (2005). Analysis
of a rainwater collection system for domestic watersupply in Ringdansen, Norrköping,
Sweden. Building and Environment, 40(9), 11741184.

554

Authors Index

A

ChitsanuphongThanutong

332

A. Sivaruban

124

Choo Yong

283

A.A.S. Al-Gheethi

417

Chutarat Chompunth

455

A.M. Kostryukova

395,399,405

Abd El Halim O

299

DAdisak Martsri

342

D. K. Weerakoon

124

Agrianti Komalasari

477

Daniela Ionescu

33

Agustinus C. B. Kantale

97

Darga Kumar Nandyala

321

Ahmad Husein Alkaff

97

Darren Newell283

Ahmad Rasidi Osman

231

David Morgan

426

Ahmad Zubair

524,528David Thorpe

12,266

Ahmad Zuhdi Ismail

315

Donlaya Promkaew

136

Aki Matsumoto

432

Dr Bandita Mainali

33

Alan Lymbery

426

Dr.Maitree Pakarasang

140

Alex Otieno Owino

172

Dr.Thanarat Sripongngam

140,146

Alireza Rezagholilou

360

Dr.Wichai Eungpinichpong

140

Amir Hashim Kassim

417

Andreea Maria Chelaru

437

E

Aniza Ibrahim

214

E.E. Shchelkanova

405

Annisa Novantri

422

Eddy Setiadi Soedjono

462

Apichat Deeminoi

140,146

Eman Albalawi

496

Ashraf Dewan

496

Environment

390

Ashraf Memon

22

Erwin Prasetya Toepak

39,45

Atika Marnolia

45

Esty Suyanti

524,528

Eungpinichpong W

113

B
Boontarika T.

391

F

Bruce W. Melville

202

Fadhil Al-Asadi

309

Buddhapala Wongkaew

51,332

Fadhluhartini Muftah

231,237

Bungorn Sripanidkulchai

150

Faijal Ali

321

Fatmah117

C
Chaisri Suksaroj

508

Fauzan224,249

Chan V. K.

449

Febrin Anas Ismail

249

Chaowalit Hamontree

305

Feroza shar Baloch514

Chee-Loong Wong

488

Firdaus Ali

524

Chihiro Yoshimura

196

Authors Index

G

Jiraporn Chuenjai

305

G. Kandasamy

124

Jiraporn Krasaetep

62

Guilherme Marins Pessanha

293

Jiyuan Tu

379

John Russell

33

John Victor Smith

243

H
H.N.P. Singh

159

Jongprasithporn

342

Hafiz S.A. Yahya

107

Jumpei Nishigami

443

Hapsa Husen

214

Juswono Unggul P.

502

Harada, H.

172

Hidehiro Koyamada

57,67,72

K

Hidetaka Noritomi

443

Kamarul Ismail

482

Hiroaki Shigematsu

208

Kanaporn Tansriprapasiri

130

Hiroki Suyama

57,67,72

Kanchana Nimsuntorn

130

Hiroshi Kita

338

Kansiri Pakkethati

154

Hiroyuki Daimon

411

Karim Ismail

299

Hong Bum Park

467

Katipelly, N. D.

449

Hossain

172

Katsumi Uchiyama

443

Kazuhiro ODA

327,338

Kazunari TANAKA

473,517I
I Made Wahyu Wijaya

462

Keigo KOIZUMI

327,338

I.V. Mashkova

395,399,405

Kennedy K.

521

Ignatius Rendroyoko

184

Kiao Inthavong

379

Irene Sondang

524,528

Kingsley Osezua Akeme

360

Irfana Kabir Ahmad

214

Kittima Vanichkul

391

Isamu Yoshitake

373

Koiwanit, J.

254,449

Koji Takasu

57,67,72

Kristiyanto

534

J
Jaime Massaguer Hidalgo Jr

293

Kunihiko Fukaura

432

Jana VASKOVA

260

Kyeong Mo Lim

467

Jaruk Keawsod

163

Javad Asad Poor

266

L

Jeffrey Johns

77

Laojeenwong P

113

Jestin Jelani1

214

Le Ma1426

Jim Shiau

309,354

Lessandro Estelito O. Garciano

276

Jingliang Dong

379

Lev Zuev1and Yulia Li

91

Jirapon Kulkham

391

Lily Surayya Eka Putri

534

Authors Index

Lindrianasari

477

Ngapuli I Sinisuka

184

Luciana Omar

299

Nicoleta Popa

437

Lyn A. Gettys

432

Niramol Patjanasoontorn

83

Nobuyuki Endo

443

Noor Suraya Romali

315

M
M. Faisal

411

Noor, Johan A. E.

502

M.M. Prasad

159

Nor Kalsum Mohd Isa

482

M.Z.

172

Nordila Ahmad

196,202

Mahatma Kufepaksi

477

Nurina Fitriani

462

Mamoru Yamada

432

Nutjaree Johns

77

Manutchanok Jongprasithporn

348

Nutthanun Tatchananusorn

136

Maratree Plainsirichai

62

Maria McCrann

33

OMaria Visa

437

Ojiro C.

172

Marthinus Sonnekus

243

Okuyama, S.

172

Mazlini Adnan

482

Ozumi, S.

172

Meysam Banimahd

360

Mia Nurkanti

422

P

Mitsuru Komatsu

338

Pachanuporn Sunon

77

Mochammad Fardiansyah

97

Panupong Thanutong

51,332

Mohammad Mirza Hassan

354

Piewkhow L.

449

Mohammed M. Khattab

190

Piyathida Kuhirunyaratn

87,130Mohd Hairy Ibrahim

482

Poonpakdee P.

254

231,237

Porntip Wongkaew

51,77,332

Mohd. Raihan Taha

214

Preetham Kumar

383

Muhammad Isha Ismail

237

Muhammad Tahir Rajput

514

R

Muntana Nakornriab

62

R. Jachrizal Soemabrata

528

Radim CAJKA

260

Radin Maya S. Mohamed

417

MohdSyahrul Hisyam Sani

N
Nabila Shah Jilani

514

Ravikant R Singh321

Najeeha Apandi

417

Rendy Pramuda Putra

97

Rifda Rahman

462

305

Rika Oie

67

Nazar K. Oukaili

178,190

Rio Sandi

249

Neneng Suliasih

422

Robert Corner496

Nantakrit Yodpijit
Nawaporn Chamnanketgorn

342,348

Authors Index

Rotchanatch Darnsawasdi

508

T

Ruddy Kurniawan

224

T.G. Krupnova

395,399,405

Taizo Uchida

432

SS.S Hassney

514

Takeshi YAMAMOTO

327

Sam M Dakka

368

Tarmizi Ismail

488

Saming Champasri

391

Thamer Mohammad

202

Sang Kil Park

467

Thuy Thi Thanh LE

287

Sartaj M.

521

Tjut Chamzurni

411

Satoru Kato

443

Tobalt A.

521

Saudee Maprasit

508

Seezar Sh. Abdullah

178

U

Seiki KAWAGOE

287

Uraiwan Chatchawan

136,150

Sengheng Hul

196

Usman Sumo Tambunan

39,45,97

Shahjahan Khan

22

Shahrin Mohammad

231

V

Sheena I. Better

276

Vanissorn Vimonsatit

373

Shek Poi Ngian

231

Vasundhara Acharya

383

Vichit Rangpan

508

Shin YOSHIKAWA

473,517

Shogo Hashimoto

208

Shuto Takeuchi

473

W

Sipanut Silaket

83

Wannapong Yeamma

342

Siravitch Atipatha

348

Warangkana Chompoopan

83

Sisikka Wannajun

62

Wardoyo Arinto Y.P.

502

Siti Hanggita Rachmawati

167

Wichai Eungpinichpong

Siti Nor Hidayah Arifin

417

William T. Haller

432

Stephen Beatty

426

Worawut Chompoopan

87

Sunisa Kunarak

219

Sunita Kumari

159

Supapat Phuangkaew
Suparman
Suwanna Arunpongpaisal

342,348
103
83,15083,136,150,163

Y
Yidan Shang

379

Yodthong Baimark

154

Suwita Saepaisan

51

YoichiMimura

373

Svetlana Barannikova

91

Yong Goh

266

Syafrida Siregar

39

Yonik Meilawati Yustiani

422

Yoshifumi Kochi

432

Yoshio FUKUDA

327

Authors Index

Yuangyai, C.

254

Yuki OGIMOTO

517

Yuki takagi

57

Yuto Murakami

72

Yuya Imamura

432

Yuztitya Asmaranti

477

Z
Zakaria Hossain

167

Zev Al Jauhari

224

Zuliziana Suif

196,202

Zulkifli Yusop

315,488

Science, Engineering & Environment

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