GEOMATE 2017 TSU MIE JAPANGEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENTiPROCEEDINGS OF SEVENTH INTERNATIONAL CONFERENCE – GEOMATE 2017
GEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENT, TSU MIE JAPAN
21-24 NOVEMBER 2017

Geotechnique, Construction
Materials and Environment
Edited byProf. Dr. Zakaria Hossain
Department of Environmental Science and Technology
Graduate School of Bioresources
Mie University, JapanTHE 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: 978-4-9905958-8-3 C3051

iii

Seventh International Conference on Geotechnique, Construction Materials andEnvironment Tsu Mie Japan, 21-24 Nov. 2017 ISBN: 978-4-9905958-8-3 C3051

Table of Contents

xiv
xv

PrefaceOrganization

1

ID Keynote Papers
1k

FLY ASH GEOPOLYMER STABILIZED RECYCLED ASPHALT PAVEMENT AS A SUSTAINABLE BASE
MATERIAL
Suksun Horpibulsuk, Menglim Hoy, Runglawan Rachan and Arul Arulrajah

2

2k

EVALUATION OF SLOPE STABILITY BASED ON MONITORING OF RESIDUAL LOADS ON GROUND ANCHORSUSING THE SAAM SYSTEM

10

3k

USING PERMEABLE PAVEMENTS TO REDUCE THE ENVIRONMENTAL IMPACTS OF URBANISATION
Terry Lucke

19

4k

ENVIRONMENTALLY GREEN IDEAS FOR SOIL STABILIZATION
Bujang B.K.Huat and Afshin Asadi

28

Toshinori Sakai and Yu Fujiwara

34

Technical Papers
ID

Geotechnique

35

7105

CHARACTERIZATION OF ENVIRONMENT FRIENDLY GEOTEXTILES EMBEDED IN SOIL UNDERPULLOUT TEST
Md. Aminul Islam, Zakaria Hossain, Jim Shiau and Siti Hanggita Rachmawati

36

7108

THE EFFECT OF VOID RATIO, MOISTURE CONTENT AND VERTICAL PRESSURE ON THE
HYDROCOMPRESSION SETTLEMENT OF COPPER MINE TAILING
Mary Ann Q. Adajar and Miller DL. Cutora

43

7109

SOIL-STRUCTURE INTERFACE BEHAVIOR OF CEMENTED-PASTE BACKFILL MATERIAL MIXED WITHMINING WASTE
Mary Ann Q. Adajar and Wincent Nicole K. Pabilona

49

7114

A NEW TESTING APPARATUS TO EXCAVATE RECTANGULAR SECTION FOR UNDERPASS TUNNELCONSTRUCTION
Yota Togashi , Takashi Nakayama , Sohei Itaya , Takatoshi Hondo and Noriyuki Okano

55

7115

INFLUENCE OF MATRIC SUCTION ON INSTABILITY OF UNSATURATED SILTY SOIL IN UNCONFINEDCONDITIONS
Ali Murtaza Rasool and Jiro Kuwano

60

iv

7117

PROPERTIES OF RAW AND PROCESSED BUKIT GOH BAUXITE IN KUANTAN, PAHANG IN
ACCORDANCE WITH IMSBC CODE
Muzamir Hasan, Ahmad Amirul Faez, M. Azizul Moqsud, Tam Weng Long and Phang Biao Yu

66

7121

TEMPERATURE CHANGE AND THE TOTAL STRESS ANOMALY IN PASTE BACKFILL
Alsidqi Hasan, Ting Wee Kiet, Fauzan Sahdi, Siti Noor Linda Taib, Norsuzailina Mohamed Sutan,
Badhrulhisham Abdul Aziz and Andy Fourie

72

7122

7132

7133

3-D NUMERICAL STUDY ON COASTAL LEVEE REINFORCEMENT USING DOUBLE SHEET-PILES WITH
PARTITION WALLS
Kousuke Takahama, Yuta Yamanaka, Atsushi Yashima3 and Kakuta Fujiwara
LANDSLIDES AND PRECIPITATION CHARACTERISTICS DURING THE TYPHOON LIONROCK IN IWATE
PREFECTURE, JAPANThapthai Chaithong, Daisuke Komori, Yoshiya Touge, Yuta Mitobe, Yuto Sukegawa,and Satoshi Anzai
SATURATED SHEAR STRENGTH PARAMETERS OF COMPACTED KHON KAEN LOESS BY DIRECT SHEAR
TEST
Atchariya Saengthongthip, Ratamanee Nuntasarn and Jutaporn Tanok

78

84

90

7134

UTILISATION OF ALKALINE ACTIVATED INDUSTRIAL BY-PRODUCTS IN DEEP SOIL MIXING
Mohammadjavad Yaghoubi, Arul Arulrajah, Mahdi Miri Disfani, Suksun Horpibulsuk, Myint Win Bo
and Melvyn Leong

96

7135

DEEP FOUNDATION REFERENCE FOR METRO MANILA, PHILIPPINES
Jonathan R. Dungca, Noel Lester C. Gozum, Jon Arnel S. Telan, Victor Carlo F. Torres and Timothy
Scott Y. Uytengsu

102

7143

AN ATTEMPT TO DETERMINE A SUITABLE STABILIZER FOR EXPANSIVE SOILS OF VOLCANIC ORIGIN
Rajeshwar Goodary, Avirut Chinkulkijniwat,Vatanavongs Ratanavaraha, Roodheer Beeharry, Anoop
Aujayeb

108

7146

LINEAR OPTIMIZATION OF SOIL MIXES IN THE DESIGN OF VERTICAL CUT-OFF WALLS
Joenel Galupino, Charlle Sy , Jonathan Dungca, and Anthony Shun Fung Chiu

114

7147

EFFECTS OF CUTTING FACE BOLTS IN THE UNCONSOLIDATED SANDY TUNNEL
Yoshifumi Taguchi

121

7149

PHYSICAL MODELING OF PROPOSED POROUS DRAINAGE SYSTEM TO SOLVE INUNDATIONPROBLEM
Ahmad Rifa’I and Noriyuki Yasufuku

127

7153

EFFECT OF HEATING-WETTING CYCLES ON ROCK PERMEABILITY
Ivan Gratchev, Jeremy Stephens and Dong Hyun Kim

133

7154

A SIMPLIFIED METHOD FOR ESTIMATING COEFFICIENT OF EARTH PRESSURE AT REST (K0) IN
COHESIVE SOILS
Premkamol Thuennadee and Kritika Trakoolngam

137

7167

A STUDY ON PERMEATION CHARACTERISTICS OF MICRO PARTICLES INTO SAND
Yukoh Hasunuma, Kentaro UemuraTakamitsu Sasaki, Koichi Nagao, Shunsuke Shimada
Tsuyoshi Tanaka, Naoaki Suemasa

142

7168

OPTIMUM USE OF GEOGRID IN THE UNBOUND GRANULAR LAYER FOR THE PAVEMENTCONSTRUCTIONAUNG AUNG SOE, Jiro KUWANO, Ilyas AKRAM and Takaya KOGURE

148

7175

LONG-TIME STRENGTH PREDICTION METHOD OF CHEMICAL GROUT SPECIMEN WITH HEATCURING
Shunsuke Takiura, Naoaki Suemasa and Kazuya Itoh , Takamitsu Sasaki and Shunsuke Shimada

154

v

7181

FLY-ASH-BASED GEOPOLYMER AS STABILIZER FOR SILTY SAND EMBANKMENT MATERIALS
Jonathan R. Dungca, Edward Ephrem T. Codilla II

160

7182

LONG-TERM STRENGTH OF BUBBLE-MIXED SOLIDIFIED SOIL MADE FROM VOLCANIC ASH
Atsuko Sato1 and Toshihiro Hayashi

167

7199

DEVELOPMENT OF CEMENT-BENTONITE MIXED SOILS BY MIXINGSODIUM CARBONATE
Ko Hashimoto, Shuichi Kuwahara, Yukio Uchida, Tadaomi Eguchi, Shinya Inazumi

172

7200

7206

DEVELOPMENT OF REAL-TIME CHECKING SYSTEM FOR GROUND IMPROVEMENT WORKS BY
HIGH PRESSURE INJECTION
Gicheol Lee, Shinya Inazumi, Hiroyuki Hashida, Tadashi Chuman, Keiji Okumura and Kazuhiro
Ishimaru
THREE-DIMENSIONAL NUMERICAL STUDY OF THE EFFECT OF TUNNELING ON THE SETTLMENT OF
PILE FOUNDATION
Mohammad Reza Atrchian, MiladGhannadzadehKermani, Ali Nisari Tabrizi and HamidTeennejad

178

184

7208

BEHAVIOR OF MODEL GROUP PILES SUBJECTED TO LATERAL SOIL MOVEMENT IN SAND
Saad Farhan Ibrahim, Mohammed Khachi Hatem

188

7215

CHANGE OF DEBRIS FLOW CHARACTERISTICS DUE TO DIFFERENCES IN PHYSICAL CONDITIONS OFLANDSLIDE DAM
Naomasa Honda

194

7218

EXPERIMENTAL STUDY ON SOIL BASED SEALING MATERIAL FULFILLING DEFORMATIONFOLLOWABILITY AND UNDERWATER PLACEABILITY
Yusuke Tadano, Seiichi Ishida and Masanori Shimomura

200

7227

SEISMIC RESPONSE ANALYSIS OF A REINFORCED EARTH WALL USING THE REINFORCEMENTS
INCORPORATING BOTH FRICTION RESISTANCE AND BEARING RESISTANCE
Hirohisa Muto, Takeshi Kodaka and Akihiko Naganuma

206

7230

EFFECT OF CEMENT TYPES ON STRENGTH DEVELOPMENT OF CEMENT-TREATED SOILS
Lanh Si Ho, Kenichiro Nakarai, Kenta Eguchi, Takashi Sasaki, Minoru Morioka

212

7235

ADDITIONAL BEARING CAPACITY OF PILES DUETO TIME DELAY OF INJECTION
Abdul Hakam, M Sofian Asmirza and Heka P Andriani

218

7236

INVESTIGATION ON THE EFFECTS OF PLANT VARIETY AND SOIL SEDIMENT TO THE COASTALABRASION IN WEST SUMATRA
Abdul Hakam, Bambang Istijono and Taufika Ophiyandri

222

7238

PRELIMINARY STUDY OF LIFT-OFF TEST AND PERFORMANCE EVALUATION FOR ANCHORS ON
FREEWAY SLOPES
Sao-Jeng Chao, Chia-Yun Wei and Hong-Da Chou

228

7243

INFLUENCE OF LIQUEFACTION ON SOIL-FOUNDATION-STRUCTURE INTERACTION
Ryohta Takatoku, Kentaro Uemura, Barrios Gonzalo, Naotaka Kikkawa, Nobutaka Hiraoka,
Kazuya Itoh, Naoaki Suemasa, Nawawi Chouw, Thomas Larkin and Rolando Orense

234

7249

ULTIMATE BEARING CAPACITY OF CLAYEY FOOTING UNDER SQUEEZE BREAKDOWN USINGRIGID-PLASTIC FINITE ELEMENT METHOD
Kazuhiro Kaneda, Masamichi Aoki, Tomohiro Tanikawa and Satoru Ohtsuka

240

7257

CORRELATION AMONG THE SOIL PARAMETERS OF THE KARNAPHULI RIVER TUNNEL PROJECT
Khondoker Istiak Ahmad, Masnun Abrar, Hossain Md. Shahin, Sultan Al Shafian and Soumik Nafis
Sadeek246

7258

A STUDY ON COMPRESSION AND SOLIDIFICATION CHARACTERISTICS OF VOLCANIC SAND
Katsuhiro Shibano, Naoaki Suemasa, Kazuya Itoh, Tsuyoshi Tanaka, Hiroto Akimoto
Yoshitaka Yanagihara, Yuan Zhang, Kiyoshi Numakami, Yasushi Furugaichi

249

vi

Katsuya Suzuki, Shun Habara

7264

NUMERICAL ANALYSIS ON MECHANISM OF LIQUEFACTION NOT ONLY IN MAIN EARTHQUAKE BUT
ALSO IN AFTER SHOCK
Yukihiro Morikawa, Hide Sakaguchi, Akihiko Taira and Ho Cho

255

7265

EVALUATION OF HEAVING RESISTANCE FOR DEEP SHAFT USING NODULAR DIAPHRAGM WALL
Koji Watanabe, Akira Mitsumori, Hidetoshi Nishioka and Masayuki Koda

263

7268

RESEARCH OF DAMAGED CONDITION BY THE 2016 KUMAMOTO EARTHQUAKE AND GROUNDINVESTIGATION ON STONE WALLS AND ERATH STRUCTURES IN KUMAMOTO CASTLE
Satoshi Sugimoto, Minoru YAMANAKA, Hideki Maeda, Naozo Fukuda and Yuuya Katsuda

269

7283

ESTIMATION OF INITIAL GROUND CONDITIONS UNDER STUPAS BASED ON ONE-DIMENSIONALCONSOLIDATION THEORY
Yuko Ishida, Ayaka Oya, Chaweewan Denpaiboon, Masamitsu Fujimoto and Ryoichi Fukagawa

275

7285

AN EXACT FINITE ELEMENT MODEL FOR AXIAL LOADED PILE IN MULTILAYERED SOIL
Chinnapat Buachart, Chayanon Hansapinyo, Piti Pratomkhum and Worsak Kanok-Nukulchai

281

7287

STABILITY ANALYSIS FOR AN AIRPORT EMBANKMENT, EVALUATING SHORT AND LONG TERMTECHNIQUES
Ignacio Fructuoso Solís Quispe, José Carlos Solís Tito and Mario Edisson Quilli Apaza

287

7291

DISPLACEMENT OF DIAPHRAGM WALL FOR VERY DEEP BASEMENT EXCAVATION IN SOFT BANGKOK
CLAY
Wanchai Teparaksa and Jirat Teparaksa

293

7300

THE INFLUENCE OF SOLAR RADIATION ON PAVEMENT PERFORMANCEJohn Yeaman and Adrian McCallum

298

7301

THE INFLUENCE OF SOLAR RADIATION AND SUBGRADE MOISTURE CONTENT ON PAVEMENTPERFORMANCEJohn Yeaman and Adrian McCallum

304

7302

THE EFFECT OF LIVE TRAFFIC ON PAVEMENT PERFORMANCEJohn Yeaman and Adrian McCallum

315

7308

LIQUEFACTION SIMULATION FOR THE OSAKA GULF COAST
USING THE LIQCA PROGRAM
Tetsuya Okano, Keita Sugito and Ryoichi Fukagawa

321

7320

NUMERICAL SIMULATION OF LIQUEFACTION AND RELATED BEHAVIOR OF UNDERGROUNDSTRUCTURE ON OSAKA GULF COAST
Keita Sugito, Tetsuya Okano and Ryoichi Fukagawa

327

7322

ROBUST POSITIONING OF DRONES FOR LAND USE MONITORING IN STRONG TERRAIN RELIEF
USING VISION-BASED NAVIGATION
Oleg Kupervasser, Vitalii Sarychev , Alexander Rubinstein and Roman Yavich

333

7329

DEGRADATION OF CEMENT TREATED SOIL DUE TO SULFATE ATTACK
Cynthia Debby Heriyani, Sumiyati Gunawan, John Tri Hatmoko, and Luky Handoko

339

7330

CHARACTERIZATION OF PHYSICAL, CHEMICAL, AND COMPACTION PROPERTIES FOR BURIED
MUNICIPAL SOLID WASTE AT THREE DUMPING SITES IN SRI LANKA
A.B.K.T. Piumali, T. Saito, N.H Priyankara, A.M.N Alagiyawanna, and K. Kawamoto

345

7332

STRESS-STRAIN-DILATANCY RELATIONSHIPS OF NORMALLY CONSOLIDATED DHAKA CLAY
Muhammad Abdur Rahman, Hossain Md Shahin and Teruo Nakai

351

vii

7336

MECHANISTIC BEHAVIOR OF OPEN AND DENSE GRADED UNBOUND GRANULAR MATERIALSUNDER TRAFFIC LOADSAli Alnedawi, Kali Prasad Nepal and Riyadh Al-Ameri

355

7337

STRUCTURAL NUMERICAL ANALYSIS ON AN OPEN-WING-TYPE GROUND ANCHOR
Kota Kono, Akihisa Nakahashi , Dong Daicho , Nobuo Fukushima and Ryoichi Fukagawa

361

7340

H/V SPECTRAL RATIO STUDY FOR ESTIMATION OF LOCAL SITE EFFECTS IN VISHAKHAPATNAM CITY
Swathi Priyadarsini Putti and Neelima Satyam D

367

7349

STUDY OF GROUND PENETRATIN RADAR(GPR) EXPLORATION FOR CAVITY UNDER THE GROUNDUSING FIELD TEST EXECUTION OF SEWER
Daeyoung Lee and Dongmin Kim

373

7359

EFFECT OF CONFINING STRESS AND INCLINATION ANGLE ON THE STRENGTH BEHAVIOUR OF SAND
Navid Khayat

377

7363

7365

INVESTIGATIONS OF INTERACTION OF JOINT PILES WITH PROBLEMATICAL SOIL GROUND IN
KAZAKHSTAN
Askar Zhussupbekov, Abdulla Omarov, Asemgul Moldazhanova, Asel Tulebekova, Karlygash
Borgekova and Gulshat Tleulenova
THE UTILIZATION OF WATER FOOTPRINT TO ENHANCE THE WATER SAVING AWARENESS: CASESTUDY OF A CERAMIC PRODUCTKarin Kandananond

383

389

ID

Construction Materials

394

7106

MECHANICAL PROPERTIES OF FLY ASH GEOPOLYMER MORTAR CONTAINING RECYCLED GLASSNattapong Damrongwiriyanupap, Yue Huang, Sangsan Wongchairattana, Sakonwan Hanjitsuwan,
Tanakorn Phoo-ngernkham and Prinya Chindaprasirt

395

7116

DEMONSTRATION OF LINER INTEGRITY MONITORING SYSTEM IN A GYPSUM WASTE
CONTAINMENT
H.B. Ng and Y.Y. Zheng

399

7129

THE USE OF STEEL FIBER EXTRACTED FROM WASTE TYRE AS REINFORCEMENT IN CONCRETE
CONTAINING RICE HUSK ASH
Fauzan, Febrin Anas Ismail, Rio Sandi and Claudia Lovina A N

405

7141

AN INVESTIGATION ON THE STRENGTH OF AXIALLY LOADED COLD-FORMED STEEL Z-SECTIONSJames Matthew L. De Jesus and Bernardo A. Lejano

411

7142

INVESTIGATION OF THE EFFECTS OF DIFFERENT NATURAL FIBERS ON THE STRENGTH OFCOMPRESSED STABILIZED EARTH BLOCKS (CSEB)
Kyle Solomon D. Pineda and Bernardo A. Lejano

417

7144

USEFULNESS OF ARTIFICIAL BEACHROCK AND GEOTEXTILE TUBE TECHNOLOGY
Md. Al Imran, Kazunori Nakashima and Satoru Kawasaki

423

7152

SHEAR BOND STRENGTH OF FA-PC GEOPOYLMER UNDER DIFFERENT SAND TO BINDER RATIO AND
SODIUM HYDROXIDE CONCENTRATION
Tanakorn Phoo-ngernkham, Sakonwan Hanjitsuwan , Satakhun Detphan , Jaksada Thumrongvut,
Cherdsak Suksiripattanapong, Nattapong Damrongwiriyanupap, Prinya Chindaprasirt andShigemitsu Hatanaka

429

viii

7158

INFLUENCE OF SEAWATER ON THE STRENGTH OF RC BEAMS AND CORROSION BEHAVIOR OF STEEL
Bernardo A. Lejano and Cheryl Lyne C. Roxas

435

7170

A COMPARATIVE SETTLEMENT PREDICTION OF LIMESTONE BLENDED MATERIALS USING ASAOKAAND HYPERBOLIC METHOD
Erica Elice Saloma Uy and Jonathan Rivera Dungca

441

7171

HYPERBOLIC MODEL PARAMETERS OF PHILIPPINE COAL ASH
Erica Elice Saloma Uy and Jonathan Rivera Dungca

447

7172

EXPERIMENTAL STUDY ON MECHANICAL BEHAVIOUR OF CONCRETE BEAMS WITH SHREDDED
PLASTICSRichard M. De Jesus, Emmanuel Bastian Pelaez and Moises Carl Caneca

453

7174

PARAMETRIC STUDY OF RESPONSE OF BRICK MASONRY WALL TO OUT-OF-PLANE LOADING
Miroslav Mynarz and Lucie Mynarzova

458

7176

MACROCELL CORROSION ASSESSMENT OF STEEL IN COLD-JOINTED CONCRETE MIXED AND CUREDIN SEAWATER
Cheryl Lyne C. Roxas and Bernardo A. Lejano

464

7192

7194

INFLUENCE OF PRECURSORS AND ACTIVATOR ON STRENGTH AND POROSITY OF ALKALI ACTIVATEDBINDERS
Nurulhuda Nadziri, Idawati Ismail and Sinin Hamdan
CURRENT SITUATION OF CONSTRUCTION AND DEMOLITION WASTE IN VIETNAM: CHALLENGESAND OPPORTUNITIES
Nguyen Van Tuan, Tong Ton Kien, Dang Thi Thanh Huyen, Tran Thi Viet Nga, Nguyen Hoang Giang,
and Ken Kawamoto

470

477

7214

IRREPARABLE COMPRESSIVE CREEP DEFORMATION OF CHLOROPRENE BEARING PAD
Hidenori TANAKA

483

7221

FE ANALYSIS FOR LATERAL STRENGTH OF CONCRETE WALLS WITH AGGREGATE SEDIMENTATION
Mamoru Kawasaki, Tetsuya Ohmura and Ryota ISHII

488

7232

FERROCEMENT - BRICK SANDWICH WALL APPLIED TO NON-ENGINEERED HOUSES
Febrin A Ismail, M Sofian Asmirza, Abdul Hakam and Fauzan

494

7305

EXPERIMENTAL STUDY ON MASONRY BUILDING STRENGTHENED WITH FERROCEMENT LAYERS
Fauzan, Febrin Anas Ismail, Abdul Hakam, Sindy Harvi Amalia and Siska Apriwelni

499

7310

BIODEGRADEBLE POLY(L-LACTIC ACID) MICROCAPSULE CONTAINING HEAT STORAGE MATERIAL:
INFLUENCE OF POLYMER MOLECULAR WEIGHT ON ENCAPSULATION EFFICIENCY
Primprapa Sangjun and Amorn Chaiyasat

505

7312

COMPOSITE MATERIALS WITH PARTICULAR REFERENCE TO CONCRETE
K. K. Ganguly Gangopadhyay

511

7328

ASSESSMENT OF ANTI-RUTTING ABILITIES OF WARM MIX MODIFIED MIXTURES
Ivan Syed, Md Amanul Hasan and Rafiqul A. Tarefder

525

7360

LATERAL CYCLIC LOAD TEST AND SEISMIC DESIGN OF PRECAST CONCRETE COLUMNS USING STEELBOX CONNECTION
Nutchanon Siri, Chayanon Hansapinyo and Chinnapat Buachart

531

ix

ID
7110

7112

7119
7120
7125

7126

Environment
UTILIZATION OF BUCKLEY-LEVERET THEORY IN BAZARKAMI OIL FIELD IN NORTHERN OF
AFGHANISTAN
Zabihullah Mahdi and Shigeo Honma
THE BEHAVIOR OF WASTE PULLING BY PILE DRIVING THROUGH THE BARRIER CLAY LAYER ON
CONTROLLED COASTAL LANDFILL SITE
Takayuki Hirao, Yoshiaki Kikuchi Taichi Hyodo Masatsugu Kiko Kouta Katagishi Shohei Namiki
Satoshi Matsumura and Makoto Takemoto
TOXICITY AND BIOEFFICACY OF WEED ESSENTIAL OILS AGAINST COWPEA BRUCHIDS AND THEIREFFECT ON MUNGBEAN SEEDS
Ruchuon Wanna and Perayos Khangkhun
GEOPHYSICAL TOMOGRAPHY BASED ON SPARSE ESTIMATION
Takayuki Shuku and Hongyang Cheng
LESSONS AND ACHIEVEMENTS FROM THE MERSEY FOREST BY NETWORKING PARTNERSHIP FOR
TWENTY YEARSTomoko Miyagawa, Clare Olver, Noriko Otsuka, Takefumi Kurose and Hirokazu Abe
IMPACT OF INCREASE IN SIKA DEER (CERVUS NIPPON) ON INFILTRATION RATE AND SOIL EROSION
ON FORESTED HILLSLOPE
Taijiro Fukuyama, Shinya Hiramatsu, Keisuke Kase, Masato Kikuchi, Shusaku Shiiba, Hideto Ohmori,
Masaaki Hanaoka

537

538

546

552

558

564

571

7127

TSUNAMI RISK MAPPING USING INTEGRATED REMOTE SENSING AND GEOSPATIAL ANALYSIS
Abu Bakar Sambah, Fusanori Miura, Guntur, Fuad, and Defrian Marza Arisandi

577

7128

SAFETY AND EFFICIENCY FOR WEEDING WORK AND LEVEE SLOPE’S FORM REQUIRED FOR
MOWING MACHINES ON PADDY FIELDS IN STEEP SLOPING AREAS IN JAPAN
Yoshiyuki Uchikawa, Masami Matsui, Teruo Arase and Takahiro Tamura

584

7130

OPTIMAL RESTORATION STRATEGY OF A WATER PIPELINE NETWORK IN SURIGAO CITY, PHILIPPINES
Agnes Garciano, Lessandro Estelito Garciano, Renan Ma. Tanhueco and Taze Jared Abubo

588

7137

FOREST ROADS CAUSE EDGE EFFECTS ON PLANT SPECIES DIVERSITY IN ARTIFICIAL FORESTS
Hiroki Kohmori, Tetsuoh Shirota, Tetsuo Okano and Teruo Arase

593

7138

DRIFTWOOD ACCUMULATION AND FLOOD DAMAGE AREA IN BLOCKED RIVER
Takaaki Okamoto, Hiroshi Takebayashi Masato Takenaka Yoshinobu Kashihara and Keiichi Toda

599

7145

7148

PERMEABILITY CHARACTERISTICS OF ROAD BASE MATERIALS BLENDED WITH FLY ASH AND
BOTTOM ASH
Jonathan R. Dungca and Joenel G. Galupino
REVIEWS ON THE APPLICABILITY OF CONSTRUCTION AND DEMOLITION WASTE AND ITS RECYCLED
MATERIALS AS LOW-COST ADSORBENTS TO REMOVE HEAVYMETALS IN WASTEWATER
G.M.P. Kumara, Takashi Saito, Shingo Asamoto, and Ken Kawamoto

605

611

7150

STUDY ON EXTRACTION AND ADSORPTION OF CESIUM FROM VERMICULITE MIXTURE SAND
Shota Nishioka , Keiichiro Shibata, Hidenori Yoshida

617

7156

THE ORIGIN OF GROUNDWATER IN THE KIONOKAWA RIVER CATCHMENT
Hiroki Kitagawa, Takuma Kubohara and Hiroyuki Ii

623

x

7164
7166

7169

STUDY ON THE REMOVAL METHOD FOR CESIUM IN SOIL OF SLOPE
Keiichiro Shibata, Hidenori Yoshida and Naomichi Matsumoto
NUMERICAL ASSESSMENT OF THE IMPACT OF STRONG WIND ON THERMAL STRATIFICATION IN
LAKE BIWA
Jinichi Koue, Hikari Shimadera, Tomohito Matsuo, Akira Kondo
IMPROVED EFFICIENCY AND FEASIBILITY IN DEVELOPING REGIONAL SCALE OPTIMAL MULTIPLEOBJECTIVE SALTWATER INTRUSION MANAGEMENT STRATEGIES IN COASTAL AQUIFERS UTILIZINGNEW SURROGATE MODELS
Alvin Lal and Bithin Datta

628

634

640

7173

WATER POLLUTION OF KAMATANI-RIVER BASIN IN YOKKAICHI
Sachie Takeuchi. Masaaki Takahashi, Yukimasa Takemoto, Maki Oyagi and Satoshi Chiba

647

7177

COMPARISON OF DIFFERENT VEGETATION INDICES FOR ASSESSING MANGROVE DENSITYUSING SENTINEL-2 IMAGERY
Firman Farid Muhsoni, A.B Sambah, M. Mahmudi and D.G.R Wiadnya

653

7178

ESTIMATING THE ENVIRONMENTAL EFFECTS OF THE CAR SHIFTING BEHAVIOR ALONG EDSA
Nicanor R. Roxas, Jr, Alexis M. Fillone, and Krister Ian Daniel Roquel

660

7179

EFFECTIVENESS OF PERMEABLE REACTIVE BARRIER (PRB) ON HEAVY METAL TRAP IN AQUIFER AT
SOLID WASTE DUMPSITE: A SIMULATION STUDY
Udayagee Kumarasinghe, Y. Sakamoto, T. Saito, M. Nagamori, C. S. Kalpage4. G.B. Herath, M.I.M.
Mowjood, and Ken Kawamoto

666

7188

ARTIFICIAL PAPER FROM PUTTARAKSA (CANNA INDICA LINN.) AND PLUBPLUENG (CRINUM
ASIATICUM)
Kanokwan Rudisirisak and Nittaya Ngowattana

672

7193

CRUSTAL THICKNESS OF NORTH-WEST PENINSULAR MALAYSIA REGION INFERRED FROM RECEIVER
FUNCTION ANALYSIS
Abdul Halim Abdul Latiff and Amin Esmail Khalil

678

7196

7201

ARSENIC CONCENTRATION AND STABLE ISOTOPIC RATIOS OF OXYGEN AND HYDROGEN FOR
GROUNDWATER AND RIVER WATER AROUND THE MIDORO AND SHINDENHIGASHISAMI TUNNELSIN GOSE CITY, NARA, CENTRAL JAPAN
Hiroyuki Ii, Hiroshi Kono, Yuji Yamashita, Jyunji Uno, Hiroyuki Shimogaki, Sota Ikeda and Toshiki
Nishimura
GENETIC DIVERSITY OF PSEUDOLABRUS SIEBOLDI, USUAL FISH SPECIES IN A WESTERN JAPAN
COASTAL AREA
Michiko Masuda, Wataru Kawase and Fumitake Nishimura

684

690

7207

THE INTEGRATION OF OUTDOOR HUMAN THERMAL COMFORT IN TROPICAL CLIMATE CAMPUS
LANDSCAPE: CHULALONGKORN UNIVERSITY, BANGKOK, THAILAND
Ariya Aruninta, Yoshihito Kurazumi, Kenta Fukagawa, and Jin Ishii

694

7210

ANALYSIS OF TSUNAMI IMPACT TO COASTAL VEGETATION AND GEOLOGICAL LANDSCAPE AT KUALATERENGGANU
Nurfarhana Aisya Anuar and Abdul Halim Abdul Latiff

700

7212

FISH CATCH QUOTA ASSESSMENT FOR SUSTAINABLE MARINE FISHERIES RESOURCES IN EAST JAVA
AlfanJauhari, DefrianMarzaArisandi, Abu Bakar Sambah and WildanAlfarizi

706

7213

USE OF INSECTICIDE-TREATED NETS AMONG PIG OWNERS LIVING IN JAPANESE ENCEPHALITISENDEMIC AREAS OF NORTHERN MYANMAR
Aung Kyaw Soe, Cheerawit Rattanapan, Somsak Wongsawass and Orapin Laosee

713

7223

EFFECT OF ORGANIC BIOPOLYMER ON THE MICROBIALLY INDUCED CARBONATE PRECIPITATION
AND ITS MORPHOLOGY
Thiloththama Hiranya Kumari Nawarathna, Kazunori Nakashima and Satoru Kawasaki

719

xi

7228
7229

7231

7242

7246

PREDICTION OF SALTWATER INTRUSION PROCESSES USING A WAVELET-FCM-ANFIS HYBRID
MODEL
Dilip Kumar Roy and Bithin Datta
LINKED SIMULATION-OPTIMIZATION MODEL FOR OPTIMUM HYDRAULIC DESIGN OF WATERRETAINING STRUCTURES CONSTRUCTED ON PERMEABLE SOILS
Muqdad Al-Juboori and Bithin Datta
JOINT BENMARKING AND ECO-EFFCIENCY FOR THE SUSTAINABLE PERFORMANCE OF SWINEPRODUCTION IN THAILAND
Weerawat Ounsaneha Punthila Janthaphat Thunwadee Tachapattaworakul Suksaroj, Cheerawit
Rattanapan
EVALUATION OF ATTENUATION OF ULTRASONIC DURING PROPAGATION THE AIR TO MEASURE
CONCRETE SURFACE ROUGHNESS BY THE AERIAL ULTRASONIC SENSOR
Nagaoka Seiya, Islam Mohammad Raihanul, Okajima Kenji, Ishiguro Satoru, Ito Ryoei, Watanabe
Ken and Ito Tetsu
A STUDY OF PUBLIC OPINION ON GREEN SPACES USING DATA FROM FREE-TEXT DESCRIPTIVERESPONSES - A CASE STUDY OF REGIONAL CITY IN JAPAN Shinya Tsukada and Tetsuo Morita

725

732

738

744

750

7251

IMPACT OF AGRICULTURAL WATER ALLOCATION ON THE ECOSYSTEMS IN THE INNER NIGER RIVER
DELTA
Barry Kassambara, Homayoon Ganji and Takamitsu Kajisa

755

7254

A STUDY ON SELECTION FACTORS OF RESIDENCE FOCUSING ON PERSONAL ATTRIBUTES AND
DISTRICT CHARACTERISTICS - A CASE STUDY OF REGIONAL CITY IN JAPAN Tetsuo Morita and Shinya Tsukada

764

7256

REMOVAL OF RADIOACTIVE CESIUM FROM OCEAN SULUDGE BY THE BACTERIUM USING
PURIFICATION SYSTEM OF CIRCULATION TYPE
Tomoe Komoriya, Kyoichi Okamoto and Takashi Toyama

770

7260

GEOCHEMICAL REACTIVE MODELING OF FLOW AND TRANSPORT PROCESS AT A MINE SITE INNORTHERN TERRITORY, AUSTRALIA
Michael S. Hayford and Bithin Datta

775

7267

IMPACT OF LAND LEVELING ON THE WATER BALANCE FOR AGRICULTURE IN EASTERNAFGHANISTAN
Shakerullah Hashimi, Pervaiz Ahmad Naseri , Najumuddin Anjum and Takamitsu Kajisa

782

7277

PREDICTORS OF BEHAVIOR INTENTION TO DEVELOP GREEN UNIVERSITY: A CASE OF
UNDERGRADUATE UNIVERSITY IN THAILAND
Weerawat Ounsaneha, Nahathai Chotklang, Orapin Laosee and Cheerawit Rattanapan

790

7279

GIS BASED IDENTIFICATION OF WATER BORNE DISEASES
Hania Arif and Shahid Iqbal

794

7282

ANALYSIS OF RAINFALL IN THE EASTERN THAILAND
Wonlee Nounmusig

800

7284

CHANGES IN THE ZOOPLANKTON COMMUNITY BEFORE AND AFTER NUTRIENT DIVERSION AND
REVETMENT CONSTRUCTION IN LAKE FUKAMI-IKE, JAPAN
Hiromi Suda, Masaaki Tanaka, Maki Oyagi and Akihiko Yagi

805

7286

SPATIAL ASSESSMENT ON THE IMPACT OF FLOOD TO MELAKA’S ECONOMY
Rosilawati Zainol, Hanan Elsawahli and Wan Suzita Wan Ibrahim

810

7304

PROPOSAL OF A FLOATING-TYPE ENVIRONMENTAL PURIFICATION FACILITY INCORPORATING THE
FUNCTION OF TIDELAND
Sato Shinji and Yuji Yamakage

815

xii

7306
7309

7311

WALL OPENINGS AND ITS ABILITY TO MINIMIZE FLOOD INDUCED FORCES ON RESIDENTIAL
BUILDINGS
Nur Aqilah Ahmad Faisal, Abdul Naser Abdul Ghani and Nuzaihan Aras Agus Salim
APPLICATION OF A HYDROLOGICAL LAND SURFACE MODEL TO WATER RESOURCES ASSESSMENT INPENINSULAR MALAYSIA
Chee-Loong Wong , Zulkifli Yusop , Tarmizi Ismail and Raymond Venneker
BIFUNCTIONAL MICROCAPSULE FOR HEAT STORAGE AND AITIBACTERIAL PROPERTIES PREPAREDBY MICROSUSPENSION IODENE TRANSFER POLYMERIZATION
Amorn Chaiyasat, Siriluk Namwong, Boontida Uapipatanakul, Warayuth Sajomsang, Preeyaporn
Chaiyasat

821

827

839

7314

KONDO THEORY FOR SPHERICAL SHELL TECTONICS
Kazuhei Kikuchi and Hiroyuki Nagahama

845

7315

PHOTOELECTROCATALYTIC CONVERSION OF CO2 INTO VALUE-ADDED ORGANIC COMPOUNDSUSING Cu2O PHOTOCATHODE
Pattranit Thongthep and Chatchai Ponchio

849

7316

DEVELOPMENT AND DESIGN OF PHOTOELECTROCATALYTIC REACTOR FOR DYE REMOVAL FROM
INDUSTRIAL SYSTEMS
Watcharapong Nareejun and Chatchai Ponchio

854

7317

IMPROVEMENT THE BIVO4 PHOTOANODE FABRICATED FOR WATER OXIDATION BY
ELECTRODEPOSITION TECHNIQUE
Nuanlaor Kiama and Chatchai Ponchio

858

7318

PHOTOELECTROCATALYTIC DETERMINATION OF CHEMICAL OXYGEN DEMAND USING WO3/BIVO4
PHOTOELECTRODE
Niphawarn Kangkun and Chatchai Ponchio,

863

7326

THE PERFORMANCE RAINFALL DURING RAINY SEASONAL OVER THAILAND BY USING PRELIMINARYREGIONAL COUPLED ATMOSPHERIC AND OCEANIC (WRF-ROMS) MODEL
Pramet Kaewmesri, Usa Humphries, Boonlert Archevarapuprok and Sirapong Sooktawee

866

7335

THE LONG TERM CHANGE OF FORM OF NITROGEN IN YAMATO RIVER BASIN
Masanobu Taniguchi and Hiryuki Ii

872

7338

HEAVY METAL CONCENTRATION OF SEAWEED BY INFLUENCE ON COPPER MINE AT SADAMISAKIPENINSULA
Erika Ueno and Hiroyuki Ii

878

7343

EVALUATION OF IMBIBITION PROCESS IN POROUS MEDIA BY INVADED PERCOLATION PROBABILITY
Junichiro Takeuchi and Masayuki Fujihara

884

7351

MEASUREMENT METHOD OF HEAVY METAL CONCENTRATION IN SOIL OF OSAKA PREFECTURE
USING CICADA SHELL
Satoru Ueda and Hiroyuki Ii

890

7352

PRECIPITATION AMOUNT ON TOPOGRAPHY AT BETWEEN THE OSAKA PLAIN AND THE SOUTH
IKOMA MOUNTAINS, OSAKA PREFECTURE, JAPANHiroki Nishiwaki and Hiroyuki Ii

896

7353

INFLUENCE OF WASTE LOADING RATE ON BIOGAS GENERATION FROM MUNICIPAL SOLID WASTE
Sartaj M., Kennedy K. and Nair A

902

7356

7357

ASSESSING URBAN WATER SUPPLY SYSTEM IN NORTHEASTERN IN THAILAND: WATER QUALITY AND
AUTHORITY ORGANIZATION
Oranee Roongrueang, Pensupa Wirikitkhul, Jareeya Yimrattanabavorn and Sudjit Karuchit
COMBINATION COAGULATION AND ADSORPTION PROCESSES FOR TREATING TEXTILEWASTEWATER IN HOUSEHOLD INDUSTRY
Tharika Kaenjun, Watcharapol Wonglertarak, Boonchai Wichitsathein and Jareeya
Yimrattanabavorn

xiii

906

912

7361

7362

A COMPREHENSIVE METHOD OF EROISON RESISTANCE AND GROWTH PROMOTION FOR PISHASANDSTONE
Zhishui Liang, Zhiren Wu, Caiqian Yang, Mohammad Noori, Xiangyang Wu, Hanbin Ge, Wenyi Yao
and Peiqing Xiao
PREARATION AND EVALUTION BY ARTIFICIAL AGING TEST OF SIO2 / FLURINATED
POLY-STYRENE-ACRYLATE COMPOSITE MATERIAL
Xiaoying Zhang, Dongya Yang, Wenya Wen, Hanqiang Yu, Xiangyang Wu, Jicheng Xu and Qian Chen

918

924

7364

STUDY ON OUTDOOR THERMAL ENVIRONMENT OF CAMPUS BASED ON GIS
Minxue Zheng, Shanwei Li and Hongxiao Liu

929

7367

DEGRADATION OF FAMOTIDINE IN WATER WITH Ag-ZnO UNDER UV LIGHT IRRADIATION
Md. Ashraful Islam Molla, Ikki Tateishi, Mai Furukawa, Hideyuki Katsumata, Tohru Suzuki and
Satoshi Kaneco

934

7225

ACCELERATING METHANE PRODUCT IN REACTION OF METHANOGENS ARCHAEA WITH COAL IN
MUARA ENIM FORMATION
Ildo Muhary Putra, Muhammad Ihsan , T.J.L Tobing, Dio Rizqi Irawan and D.A.A. Putri

939

7261

A POST-LIQUEFACTION STUDY AFTER THE 2014 CHIANG RAI EARTHQUAKE AT TUNG-FAH-PAH
VILLEGE IN CHIANG RAI, THAILAND
Sethapong Sethabouppha, Suriyah Tongmunee, Chollachai Kamtawai and Jittanan Kawilanan

945

7183

PRESENCE STATE OF TRACE ELEMENTS IN THE OHTAKIGAWA RIVER WATERSHED FROM THE FOOTOF Mt. ONTAKE
Akiko Usami, Megumi Nobori, Akihiko Yagi and Eiji Iwatsuki

951

7239

ASSESSMENT ON THE AEROSOLS VARIATION DURING THE INTENSE HAZE EVENT OF JUNE 2013
OVER MALAYSIA BY UTILIZING THE SATELLITE REMOTE SENSING AND GROUND-BASEDMEASUREMENT Nur Atiqah Aainaa Abd Latiff and Takashi Machimura

956

7136

MAT FOUNDATION DESIGN REFERENCE FOR METRO MANILA, PHILIPPINES
Jonathan R. Dungca, Raynold Y. Pua and Raynold, Nelson Que

962

7762

PERFORMANCE OF ANN MODEL IN PREDICTING THE BEARING CAPACITY OF SHALLOW FOUNDATIONS
Mozaher Ul Kabir, Syed Shadman Sakib, Istiakur Rahman, Md. Sirajul Arefin and Hossain Md. Shahin

968

7180

DEVELOPMENT OF THE TRADITIONAL LOCAL WISDOM INNOVATION USING COCONUT SHELL FOR
STRESS RELAXING MASSAGE
Peerada Damapong, Pongmada Damapong, Wichai Eungpinichpong and Thanarat Sripongngam

972

7185

SHORT-TERM EFFECTS OF THE AROMATHERAPY TO REDUCE STRESS IN THE ELDERLY
Pongmada Damapong, Peerada Damapong and Kanyamanee Koomhangsung

976

7187

IMMEDIATE EFFECTIVENESS OF TRADITIONAL THAI MASSAGE ON CERVICAL RANG OF MOTION WITH
CHRONIC TENSION-TYPE HEADACHE
Chamiporn Kongmong and Peerada Damapong

Authors index

xiv

979

Seventh International Conference on Geotechnique, Construction Materials andEnvironment Tsu Mie Japan, 21-24 Nov. 2017 ISBN: 978-4-9905958-8-3 C3051

PrefaceOn behalf of the GEOMATE 2017 Organizing Committee, we would like to welcome you in attending theInternational Conference on Geotechnique, Construction Materials and Environment held at the Miyako
Hotel, Tsu Mie Japan in conjunction with the Japan Geotechnical Society, GEOMATE International Society,
Mie University Research Center for Environmental Load Reduction, AOI-Engineering, Useful Plant SpreadSociety, HOJUN, Cosmo Winds, and Glorious International, JapanOn Friday 11 March 2011, at 14:46 Japan Standard Time, the north east of Japan was struck and severely
damaged by a series of powerful earthquakes which also caused a major tsunami. This conference was first
dedicated to the tragic victims of the Tohoku-Kanto earthquake and tsunami disasters. The Geomate 2017conference covers three major themes with 17 specific themes including:
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Advances in Composite Materials
Computational Mechanics
Foundation and Retaining Walls
Slope Stability
Soil Dynamics
Soil-Structure Interaction
Pavement Technology
Tunnels and Anchors
Site Investigation and Rehabilitation
Ecology and Land Development
Water Resources Planning
Environmental Management
Public Health and Rehabilitation
Earthquake and Tsunami Issues
Safety and Reliability
Geo-Hazard Mitigation
Case History and Practical Experience

This year we have received many paper submissions from different countries all over the world, including
Algeria, Australia, Austria, Bangladesh, Brazil, Canada, China, Czech Republic, France, India, Indonesia,
Iran, Iraq, Japan, Jordan, Kazakhstan, Libya, Malaysia, Mauritius, Nigeria, Oman, Pakistan, Peru, Philippines,
Russia, South Korea, Taiwan, Tanzania, Thailand, Tunisia, Turkey, United Kingdom, United States, Vietnam.
The technical papers were selected from the vast number of contributions submitted after a review of theabstracts. The final papers in the proceedings have been peer reviewed rigorously and revised as necessary by
the authors. It relies on the solid cooperation of numerous people to organize a conference of this size. Hence,
we appreciate everyone who support as well as participate in this 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 GEOMATE 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. Md. Zakaria Hossain, Conference Chairmanxv

Seventh International Conference on Geotechnique, Construction Materials andEnvironment Tsu Mie Japan, 21-24 Nov. 2017 ISBN: 978-4-9905958-8-3 C3051

Organization
Conference Honorary Chairmen:
Dr. Sohji Inoue, E/Prof., Mie University, Japan
Dr. Teruo Nakai, E/Prof., NIT, Japan
Dr. Fusao Oka, E/Prof. Kyoto University, Japan
Conference Chairman:
Dr. Zakaria Hossain, Prof. Mie University, Japan
General Secretary:
Dr. Shinya Inazumi, A/Prof. Shibaura Ins. of Tech., Japan
Conference Organizing Committee:
Dr. Zakaria Hossain, Prof. Mie University, Japan (Chair)Dr. Satoshi Kaneco, Prof., Mie University, Japan (Co-Chair)
Dr. Toshinori Sakai, Prof. Mie University, Japan (Co-Chair)
Dr. Takamitsu Kajisa, Prof. Mie University, Japan (Co-Chair)Dr. Masaaki Kondo, A/Prof. Mie University, Japan (Co-Chair)Dr. Shinya Inazumi, A/Prof. A/Prof. Shibaura Ins. of Tech. (GS)National & International Advisory Committee:
Dr. Sittisak Uparivong, Prof. Khon Kaen University, Thailand
Dr. Jirayut Suebsuk, A/Prof. Rajamangala Uni of Tech., Thailand
Dr. Phacharaporn B., A/Prof., Kasetsart Uni., Thailand
Dr. Dolrerdee Hormdee, A/Prof., Khon Kaen Uni, Thailand
Dr. Vanchai Sata, A/Prof., Khon Kaen University, Thailand
Dr. Chinapat Buachart, A/Prof. Chiang Mai University, Thailand
Dr. Mark Jaksa, Prof., University of Adelaide, 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. M. Bouassida, Prof. National Sch. of Engg. of Tunis
Dr. L.R. Austriaco, Prof. Angles Univ. Found. Philippines
Dr. A.S.M. Abdul Awal, Prof. Univ. Technology Malaysia
Dr. M. Ibn Ibrahimy, Prof. Int. Islamic Univ., Malaysia
Dr. 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
GEOMATE Technical Program Committee (TPC):
Prof. Sai Vanapalli, University of Ottawa, Canada
Prof. Alaa Masoud, Tanta University, Egypt
Prof. Aly Ahmed, Beni-Suef University, Egypt
Prof. Aminaton Marto, Universiti Teknologi Malaysia, Malaysia

xviProf. Bandari Shankar, Osmania University, India
Prof. Bashir Ahmed Mir, National Institute of Technology, India
Prof. Hamidi Abdul, Aziz, Universiti Sains Malaysia (USM), Malaysia
Prof. Hussein Elarabi, University of Khartoum, Sudan
Prof. M. Shohidullah Miah, International Univ. of Business Agriculture &Tech., Bangladesh
Prof. Michele, Casagrande, Pontifical University Catholic of Rio De Janeiro, Brazil
Prof. Radim Cajka, Technical University of Ostrava, Czech RepublicProf. Rajaraman Jambunathan, AMET University, India
Prof. Reshma Chandran T., Global Institute of Architecture, India
Prof. Roslan Hashim, University of Malaya, Malaysia
Prof. Seyed Naser Moghaddas Tafreshi, K.N. Toosi University of Technology, IranProf. Valeriy Perminov, Tomsk Polytechnic University, Russia
Prof. Quanmei Gong, Tongji University, China
A/ Prof. Abdoullah Namdar, Sichuan University, China
A/ Prof. Abdul Naser Abdul Ghani, Universiti Sains Malaysia, Malaysia
A/ Prof. Alaeddinne Eljamassi, Islamic University of Gaza, Palestine
A/ Prof. Alina Paranina, Herzen State Pedagogical University of Russia, Russia
A/ Prof. Ashraf Elmoustafa, Ain Shams Univeristy, Egypt
A/ Prof. Bindu C S, Cochin University of Science& Technology, India
A/ Prof. Chee-Ming Chan, Universiti Tun Hussein Onn Malaysia, Malaysia
A/ Prof. Chidanand Naik, Anjuman Instistute of Technology and Management, India
A/ Prof. Dahlia Hafez, Cairo University, Egypt
A/ Prof. Deepa G Nair, Isfahan University of Technology, India
A/ Prof. Dolrerdee Hormdee, Khon Kaen University, Thailand
A/ Prof. Farhad Behnamfar, Isfahan University of Technology, Iran
A/ Prof. Gabriela B. Cazacu, Geotech Dobrogea, Romania
A/ Prof. Hadi Khabbaz, University of Technology, Sydney (UTS), Australia
A/ Prof. Homayoon Ganji, Herat Univercity Badghis, Afghanistan
A/ Prof. Hudson Jackson, US Coast Guard Academy, United States
A/ Prof. Inazumi Shinya, National Institute of Technology, Akashi, Japan
A/ Prof. John Smith, RMIT University, Australia
A/ Prof. Kasinathan Muthukkumaran, National Institute of Technology, India
A/ Prof. Lindrianasari Lindrianasari, Universitas Lampung, Indonesia
A/ Prof. Mahdi Karkush, Baghdad University, Iraq
A/ Prof. Mohamed Redha Menani, Batna University, Algeria
A/ Prof. Navid Khayat, Ahvaz Branch, Islamic Azad University, Iran
A/ Prof. Salam, Bash AlMaliky, AlMustansiriya University, Iraq
A/ Prof. Shailesh Kumar Jha, Indian Institute of Technology, India
A/Prof. Teodor Lucian Grigorie, University of Craiova, Romania
A/Prof. Paresh Dalal, Shri Vitthalrao Shankarrao Naik Arts, Commerce and Science College, India
A/Prof. Muhammad Qasim, Abdul Wali Khan University Mardan, Pakistan
A/Prof. R. S. Ajin, GeoVin Solutions Pvt. Ltd., India
Dr. Abdul Karim M. Zein, University of Khartoum, Sudan
Dr. Abdull Halim Abdul, Universiti Teknologi MARA, Malaysia
Dr. Afshin Asadi, University Putra Malaysia, Malaysia
Dr. Ahmad Safuan A Rashid, Univeristi Teknologi Malaysia, Malaysia
Dr. Ahmad Safuan Bin A Rashid, Univeristi Teknologi Malaysia, Malaysia
Dr. Akindele Okewale, Federal University of Petroleum Resources, Nigeria
Dr. Akinola Johnson Olarewaju, Federal Polytechnic Ilaro, Nigeria
Dr. Ali Sobhanmanesh, Universiti Teknologi Malaysia (UTM), Malaysia
Dr. Alireza Bahiraie, Semnan University, Iran
Dr. Allan Manalo, Centre of Excellence in Engineered Fibre Composites, Australia
Dr. Aniza Ibrahim, National Defence University of Malaysia, Malaysia
Dr. Arif Ali Baig Moghal, King Saud University, Saudi Arabia
Dr. Aslan S. Hokmabadi, University of Technology, Sydney (UTS), Australia
Dr. Ather Ashraf, PUCIT, Old Campus Punjab University, Pakistan
Dr. Atsuko Sato, Cicil Engineering Research Institute for Cold Region, Japan
Dr. Ben-Hur Silva, Military Institute of Engineering, United Statesxvii

Dr. Choy Soon Tan, Univeristi Teknologi Malaysia, Malaysia
Dr. David Thorpe, University of Southern Queensland, Australia
Dr. Delsye Ching Lee Teo, Universiti Malaysia Sarawak, Malaysia
Dr. Domenico Lombardi, University of Manchester, United Kingdom
Dr. Ehsan, Jorat Newcastle University, United Kingdom
Dr. Ganesh Kumar Shanmugam, National Institute of Ocean Technology, India
Dr. Helsin Wang, Institute of Bridge Engineering, Taiwan
Dr. Hossein Moayedi, Kermanshah University of Technology, IranDr. Hossein MolaAbasi, Babol University of Technology, Iran
Dr. James Hambleton, University of Newcastle, Australia
Dr. James Hambleton, University of Newcastle, Australia
Dr. Janaka Kumara, Tokyo University of Science, Japan
Dr. Jirayut, Suebsuk Rajamangala University of Technology Isan, Thailand
Dr. Juhyung Lee, Korea Institute of Civil Engineering and Building Technology, South Korea
Dr. Jun Sugawara, Advision - WorleyParsons Group, Australia
Dr. Lamia Touiti Bouebdellah, Ecole Nationale d'Ingénieurs de Gabes, Tunisia
Dr. Luky Handoko, Universitas Atma Jaya Yogyakarta, Indonesia
Dr. M. Mohammad Ali, California Public Utilities Commission, United States
Dr. Marfiah Ab.Wahid, Universiti Technologi Mara, Malaysia
Dr. Maryam Naeimi, Semnan University, Iran
Dr. Mehdi Mokhberi, Islamic Azad University, Shiraz, Iran
Dr. Mohd Hairy Ibrahim, Sultan Idris Education University, Malaysia
Dr. Neelima Satyam, International Institute of Information Technology, India
Dr. Nor Zurairahetty Mohd Yunus, Univeristi Teknologi Malaysia, Malaysia
Dr. Siavash Zamiran, Southern Illinois University Carbondale, United States
Dr. Subha Vishnudas, Cochin University of Science and Technology, India
Dr. Sunggi Jin, SK E&C, South Korea
Dr. Sunil Pusadkar, Govt. College of Engineering, Amravati, India
Dr. Teresa Lopez-Lara, Universidad Autonoma De Queretaro, Mexico
Dr. Usama Juniansyah Fauzi, University of Tokyo, Japan
Dr. Yusep Muslih Purwana, Sebelas Maret University, Indonesia
Dr. Ana Almerich-Chulia, Universitat Politecnica de Valencia, Spain
Dr. Khor Shing Fhan, Universiti Malaysia Perlis, Malaysia
Dr. Afshin Asadi, International College of Auckland, New ZealandConference Correspondence:Prof. Dr. Zakaria Hossain, Conference Chairman,
Dept. of Env. Sci. & Tech., Mie University, Japan,
A/Prof. Dr. Shinya Inazumi, General Secretary
Shibaura Institute of Technology, Japan
E-mail: conference@geomate.org
Tel & Fax: +81-59-231-9578
Editorial Committee and Executive Committee:
Dr. Zakaria Hossain
Dr. Jim Shiau
Dr. Sinya Inazumi
Ms. Siti Hanggita Rachmawati
Mr. Md. Aminul Islam
Mr. Alex Otieno Owino

xviii

List of Universities:
ASEAN Institute for Health Development, Mahidol University
Azad University Of Tehran
Abdul Wali Khan University Mardan, Pakistan
Abubakar Tafawa Balewa University, Bauchi
Acharya Shrimannarayan Polytechnic
Aichi Institute of Tecnology
Al-Mustansiriayah University
Andalas University
Ariel University/Transist Video LLC (Skolkovo)
Bangladesh Agricultural Research Institute
Batna 2 University
Brawijaya University
Can tho university, vietnam
Central building research institute
CHUDEN Engineering Consultants Co.,Ltd.
CMR College of Engineering and Technology
Cal Poly, San Luis Obispo
Centre for Infrastructure Engineering, Western Sydney University
Chiang Mai University
China University of geosciences
Chulalongkorn University
Curtin University
De La Salle University - Manila
Deakin University
Diponegoro University
Disaster Prevention Research Institute Kyoto University
Eastern Mediterranean University
Eurasian National University
GSE Lining Technology Co. Ltd.
Gabes University Tunisia
Geophysical Institute of Vladikavkaz Scientific Center of the Russian Academy of Sciences
Gifu University
Govt. Higher Eduication Department J&K India
Griffith University
Gunma National College of Technology
Hakeem Water Business Links Nigeria Limited
Hiroshima University
Hokkaido University
Ibaraki University
Indiana University
International Islamic University Bangladesh
Iran University of Science and Technology
Islamic Azad University, Ahvaz, Iran
Isra University,Amman,Jordan
James Cook University, Australia.
Jiangsu University
Kagawa University
Kansai University
Kasetsart University
Khairun University
Khon Kaen University
Kilimanjaro Christian Medical University College
Kindai University Technical College
King Mongkut's University of Technology Thonburi
Kingston University, London
Korea Institue of Civil Engineering and Building Technology

xixKyoto University, Japan
Kyushu University
L.N.Gumilyov Eurasian National University
Ladoke Akintola University of Technology, Ogbomoso
Mahasarakham University
Maebashi City Office
Maebashi Institute of Technology
Mahasarakham University
Mahidol University
Meijo University
Mie University, Japan
Military Institute of Science and Technology
Misurata University
National Institute Of Technology, Calicut, India
Nagasaki University
Nagoya Institute of Technology
National Agronomic Institute of Tunisia
National Ilan University, Taiwan
National Institute of Technology, Akashi College
Nihon University College of Science and Technology
Nihon University, CST
Obayashi Corporation, Technical Research InstituteOkayama University
Osaka Institute of Technology
Osaka University
Pontifical University of Rio de Janeiro
Pontifícia Universidade Católica do Rio de Janeiro
Prince of Songkla University, Faculty of environmental management
Qazvin Islamic Azad University IranRailway Technical Research Institute Japan
Rajamangala University of Technology Isan, Nakhon Ratchasim, Thailand
Rajamangala University of Technology Thailand
Ritsumeikan University
Roi Et Rajabhat University
Sungkwang lti. Inc
Saitama University
Shinshu University
Shridevi Institute of Engineering and Technology
Sriwijaya University
Suan Sunandha Rajabhat University
Suranaree University of Technology
Swinburne University of Technology
Syiah Kuala University
TOKAI UNIVERSITY
Taisei Corporation
Takenaka Corporation
Texas Tech University
The University of Nottingham Malaysia Campus
Tohoku University
Tokushima University
Tokyo City University
Tokyu University of Agriculture
Tomsk Polytechnic University
Universidad Nacional de San Antonio Abad del Cusco, Peru
Universidade Federal Fluminense , Instituto de Fisica ,Niteroi , RJ, Brazil,
Universitas Atma Jaya Yogyakarta
Universitas Gadjah Mada
Universiti Malaysia PahangxxUniversiti Malaysia Sarawak
Universiti Sains Malaysia
Universiti Teknologi Malaysia
Universiti Teknologi PETRONAS
Universiti Tun Hussein Onn Malaysia
University Normandy
University of Canberra
University of Malaya
University of Msila
University of New Mexico
University of Ottawa
University of Phayao
University of Sriwijaya
University of the Punjab
University of the Philippines
University of the Sunshine Coast, Australia
Université des Mascareignes, Mauritius
VSB - Technical University of Ostrava
Valaya Alongkorn Rajabhat University
Wakayama University
Yahagi Construction Co., Ltd.
Yashwantrao Chavan College of Engineering
Yokkaichi University
Zandjan Azad Slamic Uni, Iranxxi

Keynote Papers

1Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

FLY ASH GEOPOLYMER STABILIZED RECYCLED ASPHALTPAVEMENT AS A SUSTAINABLE BASE MATERIAL
Suksun Horpibulsuk1, Menglim Hoy2, Runglawan Rachan3, Arul Arulrajah4
School of Civil Engineering and Center of Excellence in Innovation for Sustainable Infrastructure
Development, Suranaree University of Technology, Thailand
2
School of Civil Engineering, Suranaree University of Technology, Thailand
3
Department of Civil Engineering, Mahanakorn University of Technology, Thailand
4
Department of Civil and Construction Engineering, Swinburne University of Technology, Australia
1

ABSTRACTThis paper presents the results of laboratory evaluation of recycled asphalt pavement (RAP) – fly ash (FA)geopolymer as a base material. A mixture of NaOH and Na2SiO3 was prepared as an alkali activator to synthesis
FA-geopolymer, while RAP-FA with water (RAP-FA blend) prepared as control material. The strength
development and the strength against wet-dry cycles were determined by unconfined compression strength (UCS)
test, then the microstructural properties were examined by scanning electron microscopy (SEM) and X-Ray
Diffraction (XRD) analysis, while the leachability of heavy metal was measured by Toxicity Characteristic
Leaching Procedure (TCLP) test. The results show both RAP-FA blend and geopolymer can be used as a based
course as its UCS values meet the minimum strength required specified by Department of Highway, Thailand. The
durability test results show the UCS of these materials increase with increasing the number of wet-dry cycles,
reaching its peak at 6 wet-dry cycle. The XRD and SME analyses indicate strength development of RAP-FA blend
occurs due to a chemical reaction between a high Calcium in RAP with a high Silica and Alumina in FA led to
produce calcium aluminate (silicate) hydration formation, while geopolymerization reaction is observed in RAPFA geopolymer. After 6 wet-dry cycles, the development of the macro- and micro crack propagations caused astrength reduction for both RAP-FA blend and geopolymer samples. The TCLP results demonstrate there is noenvironmental risk of these stabilized materials. In addition, FA-geopolymer can reduce the leachability of heavy
metal in RAP-FA blend.
Keywords: Recycled asphalt pavement, Geopolymer, Durability, Heavy metals, Microstructure.
strength development of these materials were studied,then the durability against wetting-drying (w-d)
cycles was undertaken. The strength developmentwith and without w-d cycles process were determinedby unconfined compression strength (UCS) test.
Scanning electron microscopy (SEM) and X-Ray
Diffraction (XRD) analyses were used as a tool to
examine those strength changes. Finally, anenvironmental assessment was carried out by theleachate test to estimate the heavy metal
concentration from the RAP-FA blend andgeopolymer and compared with international
standard. The outcomes of this research will have apositive impact on construction guidelines andspecification for using RAP-FA blend andgeopolymer in road construction.

INTRODUCTION
There is increasing global interest to use recycledmaterials as a construction and rehabilitation material
in infrastructure sectors. Recycled Asphalt Pavement(RAP), a waste material is obtained from spentasphalt extracted from roads that have reached theend of their design life [1]. It was becoming a popularmaterial for pavement application due to its low costof construction. Though RAP was successful can bereused as pavement material when it mixed withcement, its negative impact on environment due to the
product of Portland cement produce a huge amount ofcarbon dioxide [2], [3]. Exploring alternative green
binder material is on attempt. Fly ash (FA)geopolymer is an environmentally friendly additive,
which potentially produce suitable mechanicalproperties for stabilized material [4].
The RAP stabilized with FA-geopolymer forpavement applications is currently limited due to thelack of laboratory and field evaluation. Therefore, thisresearch aims to study the possibility of using FAgeopolymer stabilized RAP as a pavement material.
The laboratory experimental programs were carriedout and divided into three main parts. First, theMATERIALS
In this research, RAP samples were collected froma mill asphalt pavement stockpile in Nakhon
Ratchasima province, Thailand. The gradation andshown in Figure 1 and Table 1, respectively. The
chemical and mineral composite of RAP, obtained by
X-Ray Fluorescence (XRF) and XRD analyses, are2

GEOMATE - Mie, Japan, Nov. 21-24, 2017presented in Table 2 and Figure 2, respectively.
FA, obtained from the largest lignite power plantin the northern region of Thailand, was used in thisstudy. The grain size distribution curve of FA,
obtained by a laser particle analyzer, is shown in
Figure 1. Table 2 summarizes the chemicalcomposition of FA using XRF analysis. The XRD
pattern of FA is also shown in Figure 2.
Liquid alkaline activator (L) is a mixture of
sodium silicate (Na2SiO3) and sodium hydroxide(NaOH) solution with a 10 M concentration.

60:40, and 50:50. The RAP-FA blend, which is a
mixture of RAP, FA, and water, was prepared as acontrol material to investigate the effect of L onstrength development. FA replacement ratios are 10,20, and 30% by weight to RAP.
Compaction and UCS test
The mixtures were compacted in a cylindricalmold (101.6 mm in diameter and 116.3 mm in height)
under the modified Proctor energy [7] to determine
the optimum water content (OWC) and optimum
liquid alkaline activator content (OLC). The sample
at the OWC and OLC were prepared for UCS test
following the ASTM D1633 [8]. The samples after 7
and 28 days of curing at room temperature (RT), were
soaked in water for 2 hours and then were air-driedfor 1 hour prior to UCS test according to thespecification of the Department of Highway,
Thailand [9].

100
RAP

Percent finer (%)

80

FA

60
40
20

Table 1. Engineering properties of RAP.

00.0001

0.001

0.01
0.1
1
Particle Diameter (mm)

10

100

Fig. 1 Grain size distribution of RAP and FA.
Cm

Cm = Calcite-magnesium
D = Dolomite
A = Calcium Sulfate
C = Calcite
Q = Quart
M = Mulite
H = Hematite

Cm
D

Cm

D

Cm

Cm

Cm D

RAP

Cm

M

A

10

A

QC

M

H
C

20

M

Fly ashH

30
40o
2 Theata ( )M

50

ValuesASTM

UCS classification
Cu
Cc
Specific gravity
CBR (%)
Water absorption (%)
Swelling ratio (%)ϒdmax (kN/m3)
OWC (%)

SP
2.44
1.16
2.70
10-15
6.80
0.20
17.50
4.10

D2487-11
D1883-07
D557-12
D1557-12
D1557-12

Table 2. Chemical composition of RAP and FA.

Q
M

Parameter

60

Chemical formula

RAP

FA

SiO2
Al2O3
FeO3
CaO
MgO
SO3
K2O
LOI

3.15
4.78
0.10
41.93
36.18
0.89
0.04
-

40.13
20.51
5.83
12.45
3.11
0.42
1.61
0.40

Durability test
The standard wetting-drying (w-d) method forcompacted soil-cement mixture [10] was adopted forthis study. The samples at 28-day of curing were
submerged in water for 5 hours then dried in an ovenat 70oC for 42 hours and air-dried for 1 hour. Thiscounted for 1 cycle. The UCS of the samples were
measured at 1 to 20 w-d cycles and compared withthat of the samples without w-d cycle to investigate
the effect of w-d cycles on the UCS changes.

Fig. 2 XRD patterns of RAP and FA.
EXPERIMENTAL PROGRAM
Sample preparation
The RAP-FA geopolymer is a combination of
RAP, FA and L (NaOH+Na2SiO3). The
NaOH/Na2SiO3 ratios studied were 100:0, 90:10,
3

GEOMATE - Mie, Japan, Nov. 21-24, 2017

L = 100:0 and 50:50 increases sharply after the firstw-d cycle and is much higher than that of
RAP+20%FA blend for all C tested. Although the
RAP+20%FA geopolymer sample at L = 50:50
possesses higher UCS than the sample with L = 100:0
within the first 3 w-d cycles, it has lower UCS whenC > 6.
The effect of cyclic w-d cycles on the externalsurface of the RAP+20%FA blend and RAP+20%FA
geopolymer at L = 100:0, and 50:50 is evident in
Figure 5a, b, and c, respectively at a particular C = 20.
Large macro-cracks and surface deterioration on the
RAP+20%FA blend are clearly observed, whichleads to strength loss. On the other hand, Figure 5b
obviously shows the minimum cracks on the surfaceof RAP+20%FA geopolymer at L = 100:0, whilemore cracks are observed for the sample at L =50:50(Figure 5c).

Microstructure analysis
UCS development of the samples before and after
w-d cycles test were examined by using XRD and
SEM analyses, which performed on the small
fragments taken from the broken portion of the UCS
samples to investigate the mineralogical andmicrostructural changes, respectively.
Environmental assessment
The Toxicity Characteristic Leaching Procedure(TCLP) test is the method prescribed by the U.S. EPA
guidelines (method 1311) to determine if the solid
waste is hazardous. The TCLP test were carried out
on 100% RAP, RAP-FA blend and geopolymers forvarious heavy metal concentrations.
RESULTS AND DISCUSSION
Figure 3 summarizes the UCS results of the RAPFA blend and RAP-FA geopolymers for various
NaOH/Na2SiO3 ratios curing for 7 and 28 days at RT.
It is noted that the UCS values of both RAP-FA
blends and geopolymers increase with increasing
curing time. This result is similar to that reported inprevious study on the strength development of
cement-stabilized RAP and FA-treated RAP [3].
7-day UCS value of both RAP+20%FA blend and
RAP+30%FA blend are greater than the strength
requirement specified by the Thailand national roadauthorities in which UCS > 1,723 kPa and UCS >2,413 kPa for both low and high volume roads,
respectively [9, 11]. The UCS of RAP-FA
geopolymer at NaOH/Na2SiO3 < 10:90 is higher thanthat of RAP-FA blends and the UCS values of RAPFA geopolymers increase when NaOH/Na2SiO3 ratio
is decreased. However, the UCS of RAP-FA blend
and geopolymer improves insignificantly when the
FA replacement ratios exceeds 20% indicating this tobe the optimal ratio. Hence, the RAP+20%FA blend
and geopolymer samples curing at 28 days wereselected for durability test.
The UCS of RAP+20%FA blend and
RAP+20%FA geopolymer at various number of w-d
cycles, C is presented in Figure 4. The UCS of
RAP+20%FA blend and geopolymer increases withincreasing C, up to C = 6 and then decrease when C >6. Previous research on effect of w-d cycles on
strength development of FA-stabilized with lime andgypsum indicated that the strength increase due to thedevelopment of cementitious compounds during w-d
process [12]. The UCS of RAP+20% geopolymer at

10000

RAP+20%FA: 7Days
RAP+20%FA: 28Days
RAP+30%FA: 7Days
RAP+30%FA: 28Days

Curing at RT

UCS (kPa)

8000
6000
4000

Base line 2(2413 kPa)
Base line 1(1724 kPa)

2000
0
WC

100:0

90:10

60:40

50:50

L (NaOH/Na2SiO3)

Fig. 3 UCS of RAP-FA blends and RAP-FA
geopolymers cured for 7 and 28 days.
16

Curing: 28-days at RT, (L=NaOH/Na2SiO 3)
RAP+20%FA Blend
RAP+20%FA (L=100:0)
RAP+20%FA (L=50:50)

14
UCS (MPa)

12
10
8
6
4

Base line 2 (2.413 MPa)
Base line 1 (1.724 MPa)

2
0

0

3

6

9
12
15
Number of cycles, C

18

21

Fig. 4 Relationship between strength and number of
w-d cycles of RAP+20%FA and geopolymers.

4

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(a)

(b)

(c)

Fig. 5 Photos of (a) RAP+20%FA blend, (b) RAP+20%FA geopolymer at L = 100:0, and (c) RAP+20%FA
geopolymer at L = 50:50 at C = 20.
This imply that the samples at L = 100:0 has
stronger bonding structure than the sample at L =50:50. From the cyclic w-d results and the photos, it
is evident that RAP+20%FA blend provides a fairly
good durability when subjected to w-d cycles. FAgeopolymer can enhance the durability of RAP-FA
material, especially for the sample at L = 100:0.
The XRD patterns of RAP+20%FA blend at
various C are shown in Figure 6. Without w-d cycle(C = 0), the RAP+20%FA blend (Figure 6a) contains
the amorphous phases of calcium-magnesium as the
predominant minerals (silica- and alumina- products),
such as Anorthite, Diopsite, Ladradorite, andEttringite. These new minerals are formed when RAP
is mixed with FA (RAP-FA blend). In other words,
the chemical reaction between the high amount ofcalcium of RAP and high amount of silica andalumina of FA results in the formation of Calcium
Silicate Hydrate (C-S-H) and Calcium Aluminate
Hydrate (C-A-H), or Calcium Aluminate Silicate
Hydrate (C-A-S-H), similar to the hydration ofPortland cement [13], that can enhance the strength
development.
The increase in peaks corresponded to Anorthite,
Diopsite, and Ladradorite with increasing C up to 6 isobserved by comparing Figure 6b (C = 1) with Figure
6c (C = 6), that indicates the increase of C-A-S-H gel.
Drying at 70oC for w-d test evidently enhances the
cementitious products (C-A-S-H gel) [14]; i.e., anincrease temperature results in a faster moisturediffusivity of the cementitious materials and hence
cement hardening [15]. The same is however not true
for C > 6. The temperature affects the water physicalproperties (density and surface tension) [16] andcauses the coarsening of the pre-structure in relation
to Ettringite dissolution and C-A-S-H alteration [14].
Figure 6d indicates the presence of Ettringite and thedecreased intensity of Anorthite and Diopsite
minerals when the samples are subjected to 12 w-dcycles. Ettringite is a hydrous mineral that exhibits
expensive behavior upon wetting [17] and makes the
RAP-FA blend volumetrically unstable [18].
Besides the XRD results, SEM images of

RAP+20%FA blend at various C are illustrated in
Figure 8. The growth of C-A-S-H gel inner and on thespherical surface of FA with increasing C (C = 0 to 6,
see Figure 7a-c) is observed while reduction in
cementitious gel at the C = 12 (Figure 7d) is detected,
which confirms the XRD results.
An = Anorthite
Cm = Calcite-magnesium
D = Dolomite
Di = Diopsite
E = Ettringite
L = Ladradorite

Cm

Cm
Di
D L
Cm E An Di
D Cm
L

D Cm Cm

(d)

Cm
Cm

Cm E An

L

Di

D
Di
L

D

Cm

D

Cm

D Cm D

Cm

D Cm

D

Cm

50

60

Cm

L
Cm E An

Cm
Di L
Di
D

(c)

(b)

Cm
Di
D

L
Cm E An Di

10

20

L

30
40
o
2 Theata ( )(a)Fig. 6 XRD patterns of RAP+20%FA blend samples
at (a) C = 0, (b) C = 1, (c) C = 6, and (d) C =12.
5

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(a)

(b)

(c)

(d)

Fig. 7 SEM images of RAP+20%FA blend samples at (a) C = 0, (b) C = 1, (c) C = 6, and (d) C =12.
Figure 8 and 9 presents the XRD patterns of
RAP+20%FA geopolymer at L = 100:0 and 50:50 andat various w-d cycles, respectively. As a result of thealkaline activation, new geopolymerization products
inclusive of Albite, Nepheline, and Analcime areobserved at the broad hump between 22-33o2θ in the
XRD pattern of the sample at L = 100:0 (Figure 8a)
and at L = 50:50 (Figure 9a) for C = 0. A good
performance of geopolymer was observed when the
precursor was in contact with alkali activator at
curing temperature of around 40 – 75oC [19].
Therefore, the C-A-S-H from RAP-FA blend co-exist
with the geopolymer products and contribute to theadditional strength development of RAP+20%FA
geopolymer in the first 6 w-d cycles.
Cm

Ac = Analcime
Al = Albite
An = Anorthite
Cm = Calcite-magnesium
D = Dolomite
Di = Diopsite
E = Ettringite
L = Ladradorite
N = Nepheline

Cm

N
Al L
Cm E An Di
Cm

Cm E

D Cm Cm

Cm D

D Di
Ac
L

Di

N
Al L
An
Di
Cm E

Cm (d)

Cm

E

D Cm

Cm

Cm

An
Cm
E
10

20

Cm

Cm

Cm

Ac T
Cm
D Cm Cm

Cm

(d)

D

Di
Ac
T Cm Cm
D
Cm
Cm
D

(c)
N
Al
L
An
Di
Cm
E

D Cm

Cm

Cm

(b)

D Cm

30
40
o
2 Theata ( )

Cm
50

Cm

(c)

Di

(b)

Cm

N

Cm
Di
L
D
Ac L
Di

Cm
D

Cm

T

Al N
An L
Cm E
Di

D Di
Ac L

Di = Diopsite Ac = Analcime
L = Ladradorite An = Anorthite
N = Nepheline Al = Albite
T = Thomsonite D = Dolomite
E = Ettringite
Cm = Calcite-magnesium

Cm

Cm
Al

Ac

Cm

Cm Cm
Al N
An L
Di

Di

Cm

Cm

Al N
An L

Di Ac
D L

The silica presents in sodium silicate is highly
soluble and consequently incorporated immediately
into the N-A-S-H gel, hence more geopolymer
products are detected in the XRD patterns of thegeopolymer sample at L = 50:50 (Figure 9b and c)compared with those at L = 100:0 (Figure 8b and c).
consequently, the UCS values of RAP+20%FA
geopolymer sample at L = 50:50 are higher than thoseof sample at L = 100:0 within the first 6 w-d cycles(see Figure 4).
The SEM images of RAP+20%FA geopolymer at
L = 100:0 and 50:50 (Figure 10 and 11) were
examined to support the XRD results.

N
Al L
Di
An
Cm
E

(a)

60

10

20

Cm Di
D
Ac CmD Cm
30
40o
2 Theata ( )

Cm
50

Cm

(a)

60

Fig. 9 XRD patterns of RAP+20%FA geopolymer at
L = 50:50 samples at (a) C = 0, (b) C = 1, (c) C = 6,
and (d) C =12.

Fig. 8 XRD patterns of RAP+20%FA geopolymer at
L = 100:0 samples at (a) C = 0, (b) C = 1, (c) C = 6,
and (d) C =12.
6

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(a)

(b)

(a)

(b)

(c)

(d)

(c)

(d)

Fig. 10 SEM images of RAP+20%FA geopolymer at
L = 100:0 samples at (a) C = 0, (b) C = 1, (c) C = 6,
and (d) C =12.

Fig. 11 SEM images of RAP+20%FA geopolymer at
L = 50:50 samples at (a) C = 0, (b) C = 1, (c) C = 6,
and (d) C =12.

The geopolymerization products in the sample at
L = 50:50 are more than those in the sample L = 100:0
for C < 6. For C > 6, at a particular C = 12, the microcracks are clearly observed in RAP+20%FA
geopolymer samples (Figure 10d and 11d) due to theloss of moisture content result in external surface
cracks leading to a strength loss.
It is noted that the sample at L = 50:50 (Figure11d) has more micro-cracks than the sample at L =100:0 (Figure 10d). Consequently, the rate of strength
reduction of the sample at L = 50:50 is higher thanthat of the sample at L = 100:0 when C > 6. This
indicates that the RAP+20%FA geopolymer sample
at L = 100:0 has higher durability against w-d cycles
than that sample at L = 50:50. This high durability is
attributed to the formation of stable cross-linked
alumino-silicate polymer structure.
Table 3 shows the leachate analysis of 100% RAP
and RAP+20%FA blend and geopolymers using
acetic leachate extraction. According to benchmark
mandated by the U.S. EPA for storm-water sampling,
pH values should in the range of 6 to 9 [20].
Leachate results show that pH level in 100% RAP
is 5.12 and 5.59 for RAP+20%FA blend, which arewithin allowable limits. Table 4 presents theprescribed limits for drinking water and the thresholdfor hazardous waste defined by the U.S. EPA.
Wartman et al. [21] reported that a material isdesigned as a hazardous waste in according to U.S.
EPA if any detected metal is present in concentration
larger than 100 times the drinking water standards.
Based on this criterion, the comparison of TCLP
results between Table 3 and 4 indicated that all metal
contaminates are within acceptable limits.
From a geotechnical engineering prospectively,
the research results indicate that RAP is mechanicallyand economically viable for using in pavement baseapplication when it stabilized with FA. Besides
having a high UCS, the RAP-FA blend exhibits good
durability against w-d cycles, which can be attributed
to the growth of C-A-S-H.

FA-geopolymer can significantly improve thestrength and durability of RAP-FA blend.
Furthermore, these materials provide a positiveenvironmental impact as environmental test results
show no significant risk to the ground water.
CONCLUSION
The present study investigated the possibility ofusing RAP-FA blend and geopolymer as a sustainable
pavement material. The 7-day UCS of the compacted
RAP-FA blend at OWC for both 20% and 30%FA
meets the strength requirement for base course
specified by national road authorities, Thailand. The
UCS improved insignificantly when the FA
replacement ratio exceeds 20%, indicating this to be
the optimal content. FA-geopolymer can significantly
improves the UCS and durability of RAP-FA blend.
The XRD and SEM analyses of RAP-FA blends
indicate the growth of C-A-S-H formation, hence its
UCS increase over time. The co-exist of C-A-S-H
from RAP-FA blend with the N-A-S-H from RAPFA geopolymer can enhance the durability of RAPFA blend remarkably.
The TCLP results indicate that RAP-FA blends
and geopolymers can be safely used as a sustainable
pavement base application as these materials pose no
significant environmental and leaching hazard into
soil and ground water sources. In addition, FAgeopolymer used can reduce the leachability of met
concentration from RAP-FA blend. This study canconfirm the utilization of these recycle and wastematerials in pavement application results in energy
saving and reduction in greenhouse gas emission.
ACKNOWLEDGEMENTS
This work was financially supported by theThailand Research Fund under the TRF SeniorResearch Scholar program, Suranaree University ofTechnology.
7

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 3. Leachate analysis results
Sample of acid leachate extraction (mg/L)

Parameter
100% RAP
pH
Arsenic
Cadmium
Chromium
CopperLead
Mercury
Nickel
Zinc

5.12
<0.01
BDL
<0.05
BDL
BDL
BDL
<0.05
1.348

Note: BDL = Below Detection Limit.

RAP-FA blend
5.59
<0.01
BDL
<0.05
BDL
BDL
BDL
<0.051
0.657

RAP-FA geopolymer
L=100:0

L=50:50

7.59
BDL
BDL
<0.05
BDL
BDL
BDL
<0.05
BDL

7.44
BDL
BDL
<0.05
BDL
BDL
BDL
<0.05
BDL

Table 4. Comparison of TCLP data analysis with U.S. EPA requirements.
Contaminant
Arsenic
BariumCadmium
Chromium
Lead
Mercury
Selenium
SilverDrinking water standard(EPA, 1999) (mg/L)
0.05
2.0
0.005
0.1
0.015
0.002
0.05
0.05

Threshold for solid waste (EPA,2009) (mg/L
0.35
35.0
0.1
2.5
0.5
0.05
0.5
5.0

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[12] P. V. Sivapullaiah and A. A. B. Moghal, "Roleof gypsum in the strength development of fly
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[13] N. Cristelo, S. Glendinning, L. Fernandes, andA. T. Pinto, "Effect of calcium content on soil
stabilisation
withalkaline
activation,"
Construction and Building Materials, vol. 29,
pp. 167-174, 4// 2012.

REFERENCES[1] A. Arulrajah, J. Piratheepan, and M. Disfani,"Reclaimed asphalt pavement and recycledconcrete aggregate blends in pavement
subbases: laboratory and field evaluation,"
Journal of Materials in Civil Engineering, vol.
26, pp. 349-357, 2013.
[2] A. J. Puppala, L. R. Hoyos, and A. K. Potturi,"Resilient moduli response of moderately
cement-treated reclaimed asphalt pavement
aggregates," Journal of Materials in Civil
Engineering, vol. 23, pp. 990-998, 2011.
[3] R. Taha, A. Al-Harthy, K. Al-Shamsi, and M.
Al-Zubeidi, "Cement stabilization of reclaimed
asphalt pavement aggregate for road bases andsubbases," Journal of Materials in Civil
Engineering, vol. 14, pp. 239-245, 2002.
[4] M. A. Salih, A. A. A. Ali, and N. Farzadnia,"Characterizationofmechanicalandmicrostructural properties of palm oil fuel ash
geopolymer cement paste," Construction and
Building Materials, vol. 65, pp. 592-603, 2014.
[5] M. M. Allam and A. Sridharan, "Effect ofwetting and drying on shear strength.," Journalof the Geotechnical Engineering Division, vol.
107, pp. 421-438, 1981.

8

GEOMATE - Mie, Japan, Nov. 21-24, 2017[18] A. Aldaood, M. Bouasker, and M. Al-Mukhtar,"Impact of wetting–drying cycles on the
microstructure and mechanical properties oflime-stabilized gypseous soils," Engineering
Geology, vol. 174, pp. 11-21, 5/23/ 2014.
[19] P. Sukmak, S. Horpibulsuk, S.-L. Shen, P.
Chindaprasirt, and C. Suksiripattanapong,"Factors influencing strength development inclay–fly ash geopolymer.," Construction and
Building Materials, 47, 1125-1136. , 2013b.
[20] EPA, "Benchmarks for storm-water sampling.
Business Environmental Resource Center, Cityof Sacramento, California.," ed, 2005.
[21] J. Wartman, D. G. Grubb, and A. Nasim, "Selectengineering characteristics of crushed glass,"
Journal of Materials in Civil Engineering, vol.
16, pp. 526-539, 2004.

[14] F. Brue, C. A. Davy, F. Skoczylas, N. Burlion,
and X. Bourbon, "Effect of temperature on thewater retention properties of two highperformance concretes," Cement and Concrete
Research, vol. 42, pp. 384-396, 2// 2012.
[15] Y. Wang, M. Fall, and A. Wu, "Initial
temperature-dependenceofstrengthdevelopment and self-desiccation in cemented
paste backfill that contains sodium silicate,"
Cement and Concrete Composites, vol. 67, pp.
101-110, 3// 2016.
[16] M. Wu, B. Johannesson, and M. Geiker, "A
study of the water vapor sorption isotherms ofhardened cement pastes: Possible pore structurechanges at low relative humidity and the impact
of temperature on isotherms," Cement andConcrete Research, vol. 56, pp. 97-105, 2//
2014.
[17] E. Celik and Z. Nalbantoglu, "Effects of groundgranulated blastfurnace slag (GGBS) on theswelling properties of lime-stabilized sulfatebearing soils," Engineering Geology, vol. 163,
pp. 20-25, 8/19/ 2013.

9

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EVALUATION OF SLOPE STABILITY BASED ON MONITORING OF
RESIDUAL LOADS ON GROUND ANCHORS USINGTHE SAAM SYSTEM
Toshinori Sakai1 and Yu Fujiwara2
Graduate School of Bioresources, Mie University, Japan
2
Nippon Expressway Research Institute Company Limited, Japan
1

ABSTRACT
Ground anchors are constructed every year as a way to stabilize cutting slopes and prevent landslides. After
construction, maintenance of ground anchors on a slope is generally conducted on only a portion of anchors.
Since anchors are arranged in groups on the slope, it is necessary to evaluate the distribution of tensile loads on
the slope. Methods used to determine the tensile loads on anchors are lift-off testing and monitoring using loadcells. In the present study, we propose a new method for evaluating slope stability based on monitoring of tensileloads using the SAAM system. The SAAM system is compact and has high test accuracy. This system can beused to easily evaluate the residual load distribution on the slope and makes it easy to attach or detach load-cells
to working anchors. Based on the results, tensile loads on anchors do not converge to a constant level affected by
the geological features of the ground. However, the correlation between the measured tensile load obtained byload-cell and temperature is high in stable slopes and low in unstable slopes. It is possible to evaluate slope
stability based on monitoring of the correlation between the tensile loads on load-cells and temperature.
Keywords: Ground anchor, Tensile load, Temperature, Correlation, Slope stabilityor 10% anchors in a slope1),2). As shown in Figure 1,
a slope may contain numerous anchors, whichmeans that a large number of anchors must be
evaluated during maintenance.
We developed a small, lightweight hydraulicjack (SAAM jack) for use in the SAAM system3).
The SAAM system enables evaluation of the
distribution of tensile loads on an anchor in a slope4)
and to attach or detach the load-cells to working
anchors. In the present study, we propose a new
method for evaluating slope stability using the
SAAM system.

INTRODUCTION
The ground anchoring system was introduced in1957 in Japan. A number of anchors are constructed
every year as a way to stabilize cutting slopes andprevent landslides. Anchors are constructed innatural ground and have complicated structures.
Anchor maintenance following construction isimportant. The tensile loads on an anchor are notconstant after introducing the initial tension to theanchor at fixation. The tensile loads on the anchor
are reduced due to the effects of soil creep orrelaxation of the anchor tendon in a stable slope. On
the other hand, when a slope becomes unstable,
during a landslide, for example, the tensile loads on
the anchor may increase. The anchor has a sensor
function, similar to that of a borehole inclination
tester or a pipe strain meter.
Anchor inspection is important in order tomaintain the stability of the slope. One anchor
inspection method involves measuring the tensile
load on the anchor. Tensile loads on anchors aremeasured by lift-off tests or using load-cells. A liftoff test is conducted by pulling the tendon with ahydraulic jack, and conventional hydraulic jacks arelarge and heavy. Since load-cells must be installed
during construction, they are difficult to replace or
newly attach to working anchors. For the above
reasons, lift-off testing or monitoring using loadcells are typically conducted on approximately 5%

Figure 1 Ground anchors in a retaining wall.
THE SAAM SYSTEM

10GEOMATE - Mie, Japan, Nov. 21-24, 2017

The SAAM system was developed in order toproperly maintain ground anchors using a SAAM
jack, which is comprised of a small, lightweight
hydraulic jack, a tension bar, a chair, and a fix-nut.
Figure 2 shows the components of the SAAM jack.
The SAAM jack is lightweight and compact and has
high test accuracy.
There are many anchoring methods. Fixedanchor heads are classified as wedge-fixed,
combination wedge-nut-fixed, and nut-fixed anchor.
The SAAM system supports all of the anchoring
methods and fixation types shown in Fig. 3. The liftoff test is performed by attaching a hydraulic jack to
the extra tendon (tension-bar) length of the anchor
head.
Chair

completely released. If the working anchor is in a
hypertonic state, the tendon may be drawn into theground as the tension released, and the original
condition may be difficult to recover. As such, themethod used to attach a load-cell may depend on theconditions of the study site. In contrast, the SAAM
system makes it easy to attach or detach load-cells toworking anchors.

(a) Attach the tension-bar (b) Attach the load-cell

Fix-natTension-bar(c) Attach the nut(d) Completed installation

Figure 4 Procedure for load-cell installation in the
SAAM system.

Hydraulic jackFigure 2 Components and installation of the SAAM
jack.

(a) Nut type(c) Wedge type(b) Combination wedgenut typeFigure 5 Results of the lift-off test.
Figure 5 shows the typical load-displacement
curve obtained by the lift-off test. The initialdisplacement of the anchor head is small. The slopeof the load-displacement curve then increases
sharply. When the load increases and becomes equal
to the tensile load on the anchor, the anchor headstarts to lift away from the bearing plate. Thisphenomenon is called lift-off. The slope of the loaddisplacement curve decreases after lift-off because
the load is transferred to the long free anchor length.
The residual load is defined as the load atintersection of the linear gradients of the loaddisplacement curve before and after lift-off (point
C)6). After the residual load is determined, the(d) Old anchoring typeFigure 3 Anchoring methods.
Figure 4 shows the procedure used to attach aload-cell to a nut-fixed anchor5). When a load-cell is
attached to a working anchor using the conventional
procedure, the tension load on the anchor must be
11

GEOMATE - Mie, Japan, Nov. 21-24, 2017

unloading process is performed. Residual
displacement sometimes occurs during the firstloading. The residual displacement of the first cycle
is greater than in subsequent cycles. When the liftoff test is performed, preloading should be
performed during the first cycle. Actual loading
should be performed after confirming theconvergence of the small residual displacement in
subsequent cycles.
The SAAM system has high test accuracy andcan be used to investigate residual loads on anchorsin slopes. Figure 6 shows the distribution of residual
tensile loads on anchors in a slope obtained by the
SAAM system7). The distribution in this figure wasobtained by determining the residual tensile loads onof the anchors in the slope. Although numerous
anchors are usually installed in a slope, it is difficult
to investigate the residual loads on all of the anchorsin the slope. Figure 7 shows the distributions ofresidual tensile loads obtained by determining theresidual tensile loads on fewer anchors, specifically
1/20, 1/10, 1/4, and 1/2 the total number of anchors.
The distributions obtained using 1/4 and 1/2 the total
number of anchors were similar to that obtainedusing all of the anchors.

curves obtained by load-cell and SAAM jack. In Fig.
8(a), the values obtained by both load-cell and the
SAAM jack were almost identical after lift-off,which indicates that the load-cell is functioning
properly. The results in Fig. 8(b) indicate that theload-cell was not operating properly. In Fig. 8(c), thevalues obtained using the SAAM jack are slightly
higher than those obtained using the load-cell, but
the results have similar tendencies. Figure 9 shows
the relationship between the loads obtained using the
SAAM jack and the load-cell. The primary
regression equation after lift-off can be obtained.

(a) Taking the identical path(b) Taking the differences path

Figure 6 Distribution of residual loads.

抑止杭(c) Taking the same path
Figure 8 Load-displacement curves obtained by theload-cell and the SAAM jack.

抑止杭(a) 1/2(b) 1/4(c) 1/10(d) 1/20

Figure 7 Distributions of residual loads obtainedusing fewer anchors.
The SAAM system can be used to check thefunction of load-cells attached to working anchors5).
Figures 8(a) and 8(b) shows the load-displacement

Figure 9 Relationship between the load on the jackand the load on the load-cell.
12

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The values obtained using the load-cell are 1.06
times those obtained using the SAAM jack. Figure
10 shows the results of multiplying the load cellvalues by 1/1.06. These are referred to as the revised
results. The revised results are almost identical to theresults measured after lift-off.

Figure 14 shows the variations in tensile load andtemperature8). The variations reveal that the tensile
load changes with the temperature. A difference intemperature of 22ºC and a difference in tensile loadof 13 kN are observed over the course of a day.
Figure 15 shows the relationship between
temperature and tensile load throughout the entire
measurement period. A very high correlation wasobserved between temperature and tensile load.
Since the measured tensile load is affected bytemperature, temperature correction of the tensile
load may be performed based on the correlational
relationship between the temperature and the tensileload. The corrected load is obtained using thefollowing equation:

Figure 10 Revised results.

(1)

CORRELATION BETWEEN TEMPERATURE
AND TENSILE LOAD

where
: Temperature corrected load at time i: Load measured at the start time
: Temperature measured at time i: Temperature measured at the start time
: Slope of the temperature-tensile load curve

The correlation between temperature and tensile
load is high in a stable slope. Figure 11 shows
anchors in a stable slope. A total of 77 anchors were
installed in this slope. The load-cell was attached toa working anchor using the SAAM system, as shownin Fig. 12. A temperature sensor was attached to thesurface of the load-cell, as shown in Fig. 13.

Figure 14 Variations in tensile load and temperature.

Figure 11 Study site.

Figure 15 Relationship between temperature andtensile load.
Figure 12 Load-cellattached to a working
anchor.

Figure 13 Temperature
sensor attached to aload-cell

Figure 16 shows the variations in the measured
and corrected tensile loads. The measured values areaffected by temperature and are not constant. A
13

GEOMATE - Mie, Japan, Nov. 21-24, 2017

difference in tensile load of 25 kN was observed
throughout the entire measurement period. The
corrected results are approximately constant, and adifference in tensile load of 3 kN is observed
throughout the entire measurement period.

Figure 18 Damage at the site.

Figure 16 Variations in the measured and corrected
tensile loads.
EXPERIMENTAL RESULTS
Figure 19 Variations in strain and precipitation.

Study site
Figure 17 shows the study site. A landslide
occurred over a wide area at this site, and anchors
were installed at the edge of the landside site9). The
geological feature is formed from mudstone. A totalof 88 anchors were installed in three regions: 33 in
the upper region (A3), 30 in the middle region (A2),and 23 in the lower region (A1). The anchor was of
the SFL type, and the design load was Td = 414.5 kN.
The lock-off load was equal to approximately half
the design load (Pt = 161 kN to 220 kN). Typhoon
12 struck Japan in September 2011 and caused
significant damage. Figure 18 shows the damage tothe site and the anchor system. A number of slope
deformations appeared on the south side of the slope.
The anchor cap of the anchor at A1-13 was broken,
and the bearing plate was deformed. At this site, thedeformation of the ground was observed using apipe strain meter at GL -8.5 m, and precipitation fora period of one hour was measured using a rain
gauge, and the results are shown in Fig. 19. A
landslide occurred at this site after over 400 mm oftotal precipitation.

Distribution of residual load
Figure 20 shows the distribution of residual load
obtained by the SAAM system. The number ofanchors investigated was 31, which is over to 1/4(35%) of the total number of anchors installed in theslope. The tensile load was found to exceed 90% of
the yield load (0.9Tys) at the south side of the site,
and the lift-off condition could not be confirmed tohave occurred in this region. Lift-off was found tooccur on the north side of the site, and the residualloads fell below the design loads. In a stable state,
the tensile load on the anchor decreases due to theeffects of creep, relaxation, and weathering of the

Figure 17 Study site.

Figure 20 Distribution of residual load.
14

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ground. Based on these results, the landslide appears
to have occurred at the south side of the site, where
measured tensile loads exceeded 0.9Tys.

pipe strain meter at GL -8.5 m. Changes in the loadand strain occur at the same time. Based on theseresults, the anchor functions as a sensor, in the samemanner as the pipe strain meter.
Figure 24 shows the variations in tensile loads on
load-cells and precipitation for one-hour periods.

Monitoring of tensile load
The SAAM system can be used to easily attachload-cells to working anchors. Four load-cells wereattached to anchors, as shown in Fig. 2110). The
relationship between landslide deformation andtensile loads on anchors obtained by load-cells wasevaluated. Figure 22 shows the load-cell attached tothe anchor at A3-14. Figure 23 shows the variationsin tensile load as determined by load-cell and pipe
strain meter. A large change was measured by theRain gauge

Figure 24 Variations in tensile loads on load-cells
and precipitation.

A3
A2
A1

Table 1 List of broken anchors
pipe strain mater
Load-cell

Figure 21 Observation locations.

Figure 22 Load-cell attached to the anchor at A3-14.

Figure 25 Photograph of a jumped out anchor
Landslide deformation was caused by theaccumulation of 667 mm of precipitation on 16-17
July 2015, during which time the tensile loads on theanchors increased. Table 1 lists the results of a

Figure 23 Variations in tensile load as determined byload-cell and pipe strain meter.

15

GEOMATE - Mie, Japan, Nov. 21-24, 2017

survey of the anchor conditions. The number ofbroken anchors increased after the heavy rain of 1617 July 2015. Anchors were confirmed to have“jumped out” for a distance of more than 50 m, as
shown in Figure 25. Figure 26 shows the locationsof broken anchors. All of the broken anchors arelocated on the south side, where the measured tensileloads exceeded 0.9 Tys.

A3

Figure 28 Relationship between temperature andtensile load (during the stable period of November2015).

A2

A1

Figure 29 Relationship between temperature andtensile load (during the unstable period of July 2015).
A very high correlational relationship was observed
between temperature and tensile load, and R2 wasdetermined to be 0.98. Figure 29 shows therelationship between temperature and tensile load
during the unstable period of July 2015. There wasno correlation for this period, during which thelandslide occurred.
Figure 30 shows the relationship between tensile
load and temperature for one-month periods from
October 2014 to October 2015. No correlation
appeared for A1-11, A2-12, and A3-14 in 16-17 July.
A landslide occurred during this period. The
landslide could be evaluated based on the correlation
between tensile load and temperature. The
correlation between temperature and tensile load is
not clear for the anchor at A1-23 during all periods.
Figure 31 shows a plan view of the anchors alongline A1. Figure 32 shows a cross-sectional view of
L22 line shown in Figure 21. The anchor at A1-23
was located at the edge of south side of the site. The
landslide clearly spread over this area. A slope
failure line appears along anchors of fixed length.
Based on these results, the correlation is not clear

Figure 26 Locations of broken anchors.
Relationship between tensile load and temperature
Figure 27 shows the variations in tensile load andtemperature in the anchor at A3-14. The tendency
reveals that the tensile load changes withtemperature during stable periods. Figure 28 shows
the relationship between temperature and tensile
load during the stable period of September 2015.

Figure 27 Variations in tensile load and temperature.
16

GEOMATE - Mie, Japan, Nov. 21-24, 2017(a) A1-11 anchor(b) A1-23 anchor(c) A2-12 anchor(d) A3-14 anchor

Figure 30 Relationship between tensile load and temperature.

Figure 31 Plan view of anchor locations along line
A1.

Figure 32 Cross-sectional view of L22 line.
2) The SAAM system can be used to easily attach or
detach load-cells to working anchors.
3) The SAAM system can be used to confirm thefunctionality of load-cells attached to working
anchors.
4) There is very high correlational relationshipbetween temperature and tensile load for a stableslope. However, there is no correlation for an
unstable slope. A landslide can be evaluated basedon the correlation between temperature and tensileload.

and the tensile load variation in the anchor is
unstable at A1-23.

CONCLUSION
We proposed a new method for evaluating slope
stability based on monitoring of residual loads using
the SAAM system. In the present paper, we obtained
the following results.
1) The SAAM system has high test accuracy andcan be used to easily investigate the residual loads
on numerous anchors and the residual load
distribution of a slope.

ACKNOWLEDGEMENTS

17

GEOMATE - Mie, Japan, Nov. 21-24, 2017[5] Fujiwara, Y. and Sakai, T., "A study of amonitoring method for residual tensile load ofground anchor", Journal of JSCE, Vol68(3),pp.547-563, 2012.
[6] Fujiwara, Y. and Sakai, T., "A study of a lift-off
test method for ground anchors", Journal of
JSCE, Vol.67(4), pp.558-568, 2011.
[7] Fujiwara, Y. and Sakai, T., "A study of amonitoring method for residual tensile load ofground anchor", Journal of JSCE, Vol68(3),pp.547-563, 2012.
[8] Sakai, T. and Kawashima, N., "Influence ofsetting position of thermometer for evaluatingof correlation between anchor load andtempreture", Proceeding of 50th Symposium ofJapanese Geotechnical Society, pp.1387-1388,
2016.
[9] Sakai, T., Tsunekawa, Y., Taguchi, K.,
Sakaguchi, K., Fujiwara, Y. and Ichihashi, Y.,"Maintenance method of ground anchor using
tensile load and temperature of anchor", J. of theJapan Landslide Soc., Vo;.51(6), pp.19-24.
[10] Sakai, T., Tsunekawa, Y., Sakaguchi, K.,
Isojima, Y. and Yano, M., "Relationshipbetween load of anchor and temperature on theslope confirmed deformation, Proceeding of
28th Symposium of Japanese GeotechnicalSociety Cyubu Branch, 2016, pp.23-28.

The present study was supported in part by theJapan Society for the Promotion of Science (JSPS)
through a Grant-in-Aid for Scientific Research (No.
26450341). The authors are very grateful to Mr.
Kawashima and the members of society of the
SAAM for their co-operation.
REFERENCES[1] Public Works Research Institute and JAPA
Anchor
Association,
Inspection
andMaintenance Manual for Ground Anchor,
pp.24-25, 2008.
[2] Japanese Geotechnical Society, Design andconstruction standards for ground anchor,
pp.122-125, 2012.
[3] Sakai, T., "Manual of lift off test with SAAM
jack for maintenance of ground anchor", Japan
Geotechnical Consultants Association, pp.1-72,
2008.
[4] Sakai, T., "Inspection manual for working
ground anchor evaluated by distribution oftensile load using SAAM jack", Committee of
maintenance of ground anchor using SAAM
jack, pp.1-111, 2010.

18

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

USING PERMEABLE PAVEMENTS TO REDUCE THE
ENVIRONMENTAL IMPACTS OF URBANISATION
Terry Lucke
Stormwater Research Group, School of Science and Engineering, University of the Sunshine Coast,
Australia
ABSTRACT
Permeable interlocking concrete pavements (PICPs) are being increasingly utilised in urban developments
globally to promote stormwater infiltration, reduce catchment runoff volumes and to improve the quality ofdownstream receiving waters. Increased interest in permeable pavements from planners, designers and stormwater
managers has led to an increase in permeable pavement research to try to address some of the common
misconceptions and to investigate new research areas. This paper summarises the results of an international
literature review that was undertaken to identify and examine the current state of permeable pavement researchworldwide. The study found that the stormwater management and environmental benefits of permeable pavements
are irrefutable and they clearly reflect the principals of low impact development. However, there are also
misconceptions and barriers to their more widespread implementation which need to be addressed to ensure their
future as an effective LID solution. More targeted research is required to address some of the outstanding issues
with permeable pavements.
Keywords: Low impact development, Permeable pavements, Stormwater pollution, Urban runoff
runoff and finding solutions to integrated water cycle
management. Pezzaniti et al. [5] defined theseprinciples as being:•
Reducing portable water demand throughwater efficient appliance, rainwater and grey
water reuse;•
Minimising wastewater generated andtreatment of wastewater to a standard
suitable for efficient reuse opportunities
and/or release to receiving waters;•
Treating urban stormwater to meet water
quality objectives for reuse and/or discharge
to surface waters; and•Using stormwater in the urban landscape tomaximise the visual and recreational
amenity of developments.
LID is a relatively recent concept that brings
together new technologies, with an increasing interestin urban regeneration, to rethink urban water
management and apply solutions to make towns andcities more sustainable.
As part of the LID stormwater management
principle, a number of stormwater treatment devices
have been developed to improve water quality, suchas swales, bioretention basins, settlement ponds andwetlands. However, these treatment devices canrequire significant land uptake. Highly urbanised
areas are often restricted in space, and potential
stormwater treatment measures should ideally fit into

INTRODUCTION
Low Impact Development
Altering the natural characteristics of a drainage
basin through urbanisation can impose dramaticchanges on the movement and storage of water within
the catchment. Impervious surfaces such as roofs andpavements can prevent precipitation from reaching
the soil and this can reduce infiltration andgroundwater recharge, while increasing stormwaterrunoff volumes and flowrates from the catchment.
Increasing impervious areas in urban catchments canalso cause flooding during periods of heavy rainfall
when stormwater drainage systems are operating at
capacity. Increased stormwater runoff can also causesignificant reductions in downstream water quality [1,2]. With approximately 50% of the world’s
population now living in urban environments
impervious surface areas and their associatedenvironmental problems are set to increase [3].
Low impact development (LID) in the USA andJapan is similar to water sensitive urban design(WSUD) in Australia and sustainable urban drainage
systems (SUDS) in Europe [4]. All of these initiatives
embrace the concept of integrated land and water
management and in particular, integrated urban water
management [5]. The principles of LID focus on
mitigating the adverse effects of urban stormwater
19

GEOMATE - Mie, Japan, Nov. 21-24, 2017

An integral aspect of conventional pavement design
involves preventing the entry of water into thepavement, via the seal or the paving joints, to protect
the integrity of the underlying basecourse and subgrade [12].
Permeable pavements are a relatively newtechnology and have quite different objectives anddesign requirements to conventional pavements.
They can be used as an alternative to conventional
impervious hard surfaces, such as roads, carparks,
footpaths and pedestrian areas [13]. Permeable
pavements are specifically designed to promote theinfiltration of stormwater through the paving andstructure where it is filtered through the various
pavement layers. The filtered stormwater is theneither harvested for later reuse or released slowly into
the underlying soil or stormwater drainage system[13]. This results in many stormwater management
and environmental benefits. The most common typeof permeable pavement is the permeable interlocking
concrete paving (PICP) system shown in Fig. 1 [2].

the urban area without further land uptake.
Permeable pavements are one type of LID
treatment device that is becoming increasingly
popular globally due to the many stormwater
management and environmental benefits they provide.
These will be discussed in the next section.
Permeable Pavements
Pavements are an everyday part of the urban
landscape and are rarely thought about yet they havea significant environmental impact. However, fordevelopers and local authorities who have to address
stormwater flooding and water quality issues, they arevery much at the forefront of the planning process [6].
This is because impervious surfaces such aspavements have such a major impact on downstream
flooding, receiving water quality and on the health ofnatural ecosystems.
Pavements are the most ubiquitous structures built
by man and they generally occupy twice the area ofbuildings. Pavements currently account for
approximately 25% of impervious areas within urban
environments [7]. Two-thirds of all the rain that falls
on potentially impervious surfaces in urban
catchments is falling on pavements (Ferguson, 2005)[6]. Pavements are responsible for the generation ofexcess runoff which is often contaminated with heavy
metals and hydrocarbons [8, 9]. They also prevent
groundwater recharge and this can result in local
water shortages.
The increase in impervious surface accompanying
urban development over recent decades has increased
both the volume of stormwater runoff, and the amountof pollution flowing downstream to receiving waters[1, 2]. However, the problems associated withpavements are not restricted to water-related issues.
They reduce biodiversity by displacing flora andfaunal habitats and they cause localised andregionalised
temperature
increases,
known
commonly as the “urban heat island" effect [10].
Impermeable pavements also cause street trees toextend their roots in search of water to relievemoisture stress which can result in significant damage
to infrastructure. Consequently, the management ofstormwater in urban areas has become a priority issue
for those responsible for planning and construction of
new developments, and maintenance of existingstormwater infrastructure [11].
Conventional pavements designed for use by
vehicular traffic typically consist of a sub-grade, one
or more overlying basecourses of compacted
pavement material and an impervious surface seal.

Permeable Pavers

Infiltration through Paving Joints(Typical Thickness: 50 - 80 mm)

2-5 mm Bedding Aggregate(Typical Depth: 30 - 50 mm)

20-63 mm Sub-base Aggregate(Depth Dependent on Structural
and/or Storage Requirements)

Geofabric or Impermeable Liner(If Required)Sub-gradeFig. 1 – Typical PICP Schematic
Even for PICP systems not designed for
harvesting and reuse, the storage capacity in thebasecourse layers (Fig. 1) can be designed to intercept
significant rainfall events. PICPs can therefore reducerunoff volumes and discharge rates from paved
surfaces [14-17]. These reductions result in asignificantly reduced risk of downstream flooding.
PICPs also provide considerable water quality
improvements by treating and trapping stormwaterpollutants [18 20].
PICPs are one LID treatment option that do not
require any increase in land area. They help increase
infiltration in urbanised areas and help reducepressure on existing stormwater infrastructure. They
are commonly used as part of a treatment train or as asource control measure [5]. Permeable pavements ingood working order have infiltration rates, from 130
mm/h up to several thousand mm/h [2, 21, 27] andcan manage the runoff of rainfall events in excess ofa 1 in 100-year storm event [22]. However, theperformance of a PICP system also depends on thelocal site conditions. For example, if underlying soils
20GEOMATE - Mie, Japan, Nov. 21-24, 2017contains significant concentrations of suspended
sediments and gross pollutants [2, 9, 14, 27, 31].
There is a perception that permeable pavements thatare used as source control devices, and designed toinfiltrate runoff, will tend to clog quickly and resultin high maintenance and replacement costs. This
perception has led to a steady increase in the numberof research studies into the clogging processes thattake place in permeable pavements [4, 5, 9, 28, 31, 32,
33, 34].
Much of the earlier clogging research was
conducted on porous concrete materials which havedifferent clogging processes to PICPs [35-38]. The
research tended to show that porous pavement
materials were more susceptible to clogging, andmore difficult to maintain than other systems andtheir popularity has declined over the last decade.
However, new pavement designs presented by
Dierkes et al. [39] demonstrated success with adouble layer concrete paver with an impermeable top
layer and a porous base layer. The study found thatthe new pavers could temporarily store water close to
the surface which helped promote evaporation of thewater back into the atmosphere. This process could
help reduce heat island effects. The new paver design
was found to be less prone to clogging and theimpermeable top layer was also found to be moreresistant to damage than typical porous layers.
Further research is currently underway to evaluate thenew paving design under operational conditions.

have low permeability a collection pipe is often
needed in the base of the system to divert infiltrated
water to the underground drainage network.
Permeable paving provides multiple benefits for
managing stormwater runoff at source [2]. They help
to reinstate the infiltration capabilities and restore thenatural hydrological cycle of urban areas which
reduces runoff volumes and the risk of flooding. They
filter and treat the infiltrating runoff by trapping
pollutants that might otherwise contaminate
groundwater and stormwater [7, 23]. It is also thoughtthat permeable pavements can reduce the urban heatisland effect and can contribute to a wider range ofsustainable water management objectives throughrainwater harvesting [13, 24]. Recent research [25,26] has also shown that the ability of permeable
pavements to allow water and air to infiltrate throughto the root zone can significantly improve street tree
health and minimize pavement damage.
However,
there
are
some
commonmisconceptions associated with the use of permeable
pavements systems. These include the belief that theycannot be used in clay soils, that they clog easily
which hinders infiltration, and that they do not work
well in cold climates due to damage caused by freeze
and/or frosting [22]. There are also numerous
permeable pavement design guidelines in use
worldwide and that the information contained in these
design guidelines is often unclear and occasionallyconflicting. These issues may have hampered themore widespread implementation of permeable
pavement systems.
Increased interest in permeable pavements fromplanners, designers and stormwater managers has led
to an increase in permeable pavement research to try
to address some of the common misconceptions [2, 4,
5, 27, 28]. It has also initiated new research areas suchas using permeable pavement for stormwater
harvesting and reuse and to promote street tree health[13, 25, 26, 29, 30].
This paper summarises the results of aninternational literature review that was undertaken to
identify and examine the current state of permeable
pavement research worldwide. It is intended as apractical resource for designers and researchers of
permeable pavement systems.

PICPs
A significant amount of research has now havebeen published on the clogging processes that takeplace in PICPs and the subsequent effects these haveon hydraulic performance and how these processeschange over time [2, 4, 5, 27, 28, 33]. The key
mechanisms that govern clogging in different systems
are also now better understood than they were adecade ago.
Pratt [40] undertook a laboratory investigation on
small scale, full-size pavement models to investigate
pollutant retention within the permeable pavement
structure. This study appears to be the first to use an
accelerated stormwater sediment dosing program tosimulate the long-term performance of PICPs due toclogging. Pratt [40] found that most of the sedimentand organic materials tends to get trapped in the upper
layers of the bedding aggregate and on the geofabricfilter and this prevents them migrating through to thebasecourse materials. Pratt predicted that this willlead to eventual total clogging of the system but heconceded that it is difficult to accurately predict thetime to failure. Pratt did, however, suggest an

INTERNATIONAL PERMEABLE PAVEMENTRESEARCH
Clogging
Porous Pavements
Research has shown that urban stormwater runoff
21

GEOMATE - Mie, Japan, Nov. 21-24, 2017

potentially occur in PICPs. This finding suggests that
results from simulated long-term sediment loading
studies that do not include drying cycles, may not beapplicable to prototype PICP field installations.
Lucke and Beecham [2] undertook a forensic
investigation on a clogged eight-year-old PICP
system to determine how sediment had accumulated
within the pavement structure. They found that mostof the sediment was trapped in the gaps between thepaving blocks and on top of the bedding aggregate
directly below the gaps. The sediment accumulation
pattern that took place on the bedding aggregate
beneath pavers is shown Fig. 2. This clearly
demonstrates the effectiveness of the bedding
aggregate as a filter medium to remove sediment fromstormwater runoff.

effective life span of between 15 and 20 years inservice [40].
Borgwardt [31] reported on the long-term, in-situ
infiltration performance of PICPs and presented
infiltration test results for over 80 test locations.
Borgwardt [31] maintained that the infiltration
performance of PICPs decreases significantly withina few years of service due to the entrainment ofmineral and organic sediment material retained in theupper 20 mm of the pavement joint material.
Comparisons of PSD analyses showed that there were26% (by mass) more fine particles (less than 63 µm
in diameter) trapped in the upper 20 mm of the jointmaterial than in the lower 20 mm. Borgwardt [31]predicted that in practice, the permeability of PICP
systems reduces to approximately 18% of the original
infiltration value after approximately 10 years’service.
Research to improve understanding of the longterm hydraulic conductivity and the clogging
processes in permeable pavements was undertaken by
Pezzaniti et al. [5]. The focus of the study, which
included both laboratory and field work components,
was to quantify the degree of sediment trapping andassociated pollutant retention in order to assess theeffective life of PICPs. For their laboratory
experiments, Pezzaniti et al. [5] applied locallysourced stormwater sediment to PICP testbeds,
similar in construction to those used by Pratt [40], inorder to simulate 35 years of sediment loading. The
study [5] concluded that there are two types ofsediment accumulation involved in the clogging
process of PICPs, namely coarse and fine sediments.
They explained that coarse sediment is retained in a
relatively small upper horizon of the pavement joints
and this can reduce fine sediment migration to thelower layers. This generally supported by previous
research studies [19, 31, 40].
Fassman and Blackbourne [41] investigatedinfiltration rates and clogging of a 200 m2 PICP sitethat was constructed to form part of a main arterial
road in Auckland, New Zealand. The structure wasmade from PICP blocks (with wide gaps) on a 2 to 5
mm aggregate bedding layer. A geofabric layer was
included between the bedding layer and thebasecourse. Sub-surface investigations beneath thepavers revealed that a crust had formed above thegeofabric and that some of the bedding layer had
formed into agglomerated chunks. This in an
important finding [41] and demonstrates thesignificant role that dry periods of no rainfall play inthe sediment retention and clogging processes that

Fig. 2. Sediment Accumulation Pattern on Bedding
Aggregate [2]It is also clear from Fig. 2 that sediment is only
deposited on the bedding aggregate directly below thepaving joints. The rest of the bedding aggregate iseffectively "as new" and has performed no sedimentremoval function at all. This suggests that the PICP
design is not fully utilising the filter medium
properties of the bedding aggregate. Therefore, it was
hypothesised [2] that there may be a more effective
PICP design which makes greater use of the bedding
aggregate area to filter more sediment fromstormwater runoff. This was investigated anddescribed in the following sections [28].
The studies outlined above demonstrate thevariability of findings from previous research into theclogging processes that occur in permeable
pavements and the effects that these processes haveon the long-term viability of these systems. While anumber of the studies have examined the sediments
accumulated in the paving layers in some detail, mostof this research did not examine the clogging
processes experienced by sediment particle sizes lessthan 63 µm in diameter. Those studies that did look atparticle sizes of less than 63 µm in diameter wereconducted on laboratory models and these results may
not be applicable to prototype PICP field installations.
Further research is required to better understand thisprocess.
22

GEOMATE - Mie, Japan, Nov. 21-24, 2017

over one full square metre (1 m2) of paving (Fig. 4).
They also found that different areas of the PICP wereaffected by blockage by fine soli particle and theyclassified the different areas as either, Fully Blocked(FB), Medium Blocked (MB) or Unblocked (UB).

Infiltration
Adequate infiltration through PICPs is critical totheir hydraulic and stormwater treatment
performance. Infiltration is affected by clogging
caused by the trapping of fines in the PICP surface,which, over time, reduces treatment performance. It
has been shown that clogging can be reduced byperiodic maintenance such as vacuum sweeping
and/or pressure washing. It has also been suggested
that a PICP’s maintenance requirements can be
identified by measuring reduced infiltration rates.
This section examines some of the previous researchon PICP infiltration.
Bean et al. [16] evaluated the surface infiltration
rates of 40 permeable pavement sites in North
Carolina, USA. They measured the surface
infiltration rates of different permeable pavement
types and tried to relate the infiltration performance
to paver type. They used both the Single-ring
infiltrometer test method [42] and the Standard test
method for infiltration rate of soils in field using
double-ring infiltrometer [43] in their study (Fig. 3).

Fig. 4 Double-ring Infiltration Testing Apparatus
Developed by [2]They [2] found the average infiltration rates forthe pavement to be 11 mm/h for the FB areas, 165
mm/h for the MB areas, and 8,530 mm/h for the UB
areas. They found that although there was only amaximum difference of 56% in the mass of sediments
retained in the paving layers, the infiltration rates
varied by five orders of magnitude. These results
reinforced previous research findings on how
important it is to maintain PICPs to ensure surface
infiltration rate performance remains effective.
Due to the difficulty and inconsistencies
experienced with PICP infiltration testing using
traditional methods, two new experimental test
procedures were developed and evaluated [34] tomore accurately determine the surface infiltration rateof PICPs. The two new methods were the falling headfull-scale (FHFS) method and the constant head fullscale (CHFS) method. Both of the new methods
involved inundating a large area of the pavement inorder to determine the infiltration rate through thepavement surface (Fig. 5). Double ring infiltrometer
tests were also performed to enable a comparison of
the results to traditional methods.
While the new infiltration testing methods [34]were found to be more reliable and consistent than
traditional methods, there was still a large variation in
the results during the testing. It was found thatmoisture levels in the soil underneath the PICP
installation significantly affected test results. Thiswas particularly apparent when multiple tests were
performed at the same site as infiltration rates
decreased as more tests were performed. Overall, theFig. 3. Modified Ring Infiltrometers for Permeable
Pavement Testing with Waterproof Sealant(a) Single Ring; (b) Double Ring [34]The study [16] measured infiltration rates
between 1,000 mm/h and 40,000 mm/h for PICPs thatwere not blocked with fine particles. However, theinfiltration rate of PICPs that were partially filled byfine soil particles reduced to between 16 mm/h and
2,000 mm/h. They concluded that PICP sites installed
for infiltration purposes should not be locatedadjacent to areas with disturbed soils asaccumulations of fine particles can dramaticallydecrease surface infiltration rates. They also foundthat higher surface infiltration rates could besustained by using a vacuum sweeper at regularintervals for maintenance [16].
Lucke and Beecham [2] investigated theinfiltration performance of a PICP system that has
been in service for over eight years. They developed
a new type of double ring infiltration testing
apparatus that measured the surface infiltration rate
23

GEOMATE - Mie, Japan, Nov. 21-24, 2017

demonstrated that sediment is only deposited on thebedding aggregate directly below the paving joints.
The rest of the bedding aggregate is effectively "asnew" and has performed no sediment removal
function at all. This suggested that current PICP
designs were not fully utilising the filter medium
properties of the bedding aggregate. It was therefore
hypothesised that there may be a more effective PICP
design which makes greater use of the bedding
aggregate area to filter more sediment fromstormwater runoff.

study [34] found that the new falling head full-scaletesting method produced the most accurate results.
This study is continuing the new method has been
applied to numerous sites across Europe. It is
anticipated that the full results of this study will be
published in the near future.

Fig. 5 - Full-scale Infiltration Testing in the
Netherlands [34]Fig. 7 – Sediment Slots Being Cut into Underside of
PICP blocks [28]Lucke et al. [44] compared infiltration results
using the standard test (C1781M-14a – Fig. 3a) withthe results of a new stormwater infiltration field test
(SWIFT – Fig. 6) developed in Australia to evaluate
the maintenance requirements of PICPs. A strong
correlation was found between results using the two
methods. The study found that the SWIFT was areliable method for estimating the degree of clogging
of PICPs while successfully overcoming some of the
problems with the more technical existing test
methodology such as horizontal water leakage (use of
sealant), unrealistic pressure heads, speed of test, andportability. The SWIFT test [44] is a simple, fast andinexpensive way for asset managers and local
government employees to quickly assess themaintenance requirements of PICP installations in thefield.

A proof of concept study [28] was performed toinvestigate more efficient use of the bedding
aggregate used in PICP systems. Lateral drainage
channels (sediment slots) were cut into the undersideof PICP blocks (Fig. 7) to allow sediment-laden
stormwater to access, and be treated by, a greater
surface area of bedding aggregate. Eight different slot
designs (Fig. 8) were trialled in the study [28].
Specially fabricated PICP models were tested in thelaboratory using semi-synthetic stormwater todetermine which of the slot designs made the mostefficient use of the bedding aggregate to filter the
sediment from the stormwater.

Fig. 8 - Eight Different Drainage Slot Designs
Trialled in Study [28]Fig. 6. Stormwater infiltration field test (SWIFT)
Infiltrometer used in this study. (a) SWIFT
in use; (b) SWIFT dimensions [44].

The study [28] results (Fig. 9) clearly
demonstrated that the eight drainage slot designs
deposited between 25% and 366% more sediment
beneath the pavers than the control pavement (Design9). The results of the study [28] strongly suggest that
PICP systems with drainage slots cast into their bases

Sediment Slots
Previous

PICP

clogging

research[2]
24

GEOMATE - Mie, Japan, Nov. 21-24, 2017

would take much longer to clog than unmodified
pavers, thereby proving the initial concept of thisstudy. However, more research would be required toverify this fully. More research is also required to
optimise the drainage slot designs for use on different
paver bedding materials. Finally, a better method ofquantifying the amount of sediment that is depositedon the bedding aggregate needs to be developed.

CONCLUSION
This review of permeable pavement research has
identified a number of potential solutions to the issues
surrounding clogging and reduced surface infiltration
capacities. These include:• A new PICP design using a double layer concrete
paver construction with an impermeable top layer
and a porous base layer. The new paver design was
found to be less prone to clogging, better at
evaporating water back into the atmosphere, andmore resistant to damage than typical porous
layers.
• PICP sites installed for infiltration purposes should
not be located adjacent to areas with disturbed soils
as accumulations of fine particles can dramaticallydecrease surface infiltration rates.
• Higher surface infiltration rates can be sustainedby using a vacuum sweeper at regular intervals formaintenance.
• Research suggests that PICP’s maintenancerequirements can be identified by measuring
reduced infiltration rates. A number of new
methods for measuring surface infiltration
capacity were examined.
• New infiltration rate testing methods involving
inundating large areas of the pavement were foundto be more reliable and consistent than traditional
methods, although they were more difficult toimplement.
• The SWIFT test is a simple, fast and inexpensive
way for asset managers and local government
employees to quickly assess the maintenancerequirements of PICP installations in the field.
• A proof of concept study to investigate more
efficient use of the bedding aggregate used in PICP
systems was examined. The study results strongly
suggest that PICP systems with drainage slots castinto their bases would take much longer to clog
than unmodified pavers.

Fig. 9. Study Sediment Distribution Patterns
Summary
Altering the natural characteristics of a drainage
basin through urbanisation can impose dramaticchanges on the movement and storage of water within
the catchment. As permeable pavements are
specifically designed to promote the infiltration ofstormwater through the paving and structure they canbe used to promote infiltration and groundwater
recharge, while decreasing stormwater runoff
volumes and flowrates from the catchment. The useof permeable pavements can result in manystormwater management and environmental benefits.
The preceding sections have outlined some of thelatest international permeable pavement researchstudies. While there have been other quality studies
undertaken, the majority of the research tends to focus
on issues to do with surface infiltration and clogging.
The stormwater management and environmental
benefits of permeable pavements are undeniable andthey clearly reflect the principals of low impact
development. Uncertainties surrounding surface
infiltration and clogging are clearly the main barrier
to the more widespread implementation of permeable
pavements. If these issues can be satisfactorily
addressed, the future of permeable pavements will beassured.

While all of the potential solutions listed above
may be able to resolve some of the issues surrounding
surface infiltration and clogging to some extent, moretargeted research is required to explicitly address theuncertainties surrounding permeable pavement
performance. More positive research results that
demonstrate the potential benefits of permeable
pavements will secure their future in the LID
integrated land and water management philosophy.

25

GEOMATE - Mie, Japan, Nov. 21-24, 2017[14] Pratt, C.J., Mantle, J. and Schofield, P. UK
Research into the performance of permeable
pavement, reservoir structures in controllingstormwater discharge quantity and quality, J. of
Water Sci. & Tech., 32(1), 1995, 63-69.
[15] Hunt, B., Stevens, S. and Mayers, D. Permeable
pavement use and research at two sites in eastern
North Carolina, in Proceedings of the 9thInternational Conference on Urban Drainage,Portland, Oregon, 2002, USA.
[16] Bean, E., Hunt, W. and Bidelspach, D. Field
survey of permeable pavement surface
infiltration rates, Journal of Irrigation andDrainage Engineering, 133(3), 2007, 247-255.
[17] Collins, K., Hunt, W. and Hathaway, J.
Hydrologic comparison of four types ofpermeable pavement and standard asphalt ineastern North Carolina, Journal of Hydrologic
Eng., 13(12), 2008, 1146-1157.
[18] Pratt, C.J., Mantle, J. and Schofield, P. Urban
stormwater reduction and quality improvement
through the use of permeable pavements, Journalof Water Sci. and Tech., 21(8), 1989, 769-778.
[19] Dierkes, C., Angelis, G., Kandasamy, J. andKuhlmann, L. Pollution retention capability andmaintenance of permeable pavements, inProceedings of the 9th ICUD Conference, IWA,
Portland, Oregon, 2002, USA.
[20] Brattebo, B. and Booth, B. Long-term
stormwater quantity and quality performance of
permeable pavement systems, Journal of Water
Research, 37(18), 2003, 4369–4376.
[21] Volder, A. Watson, T. and Visawanathan, B.
Potential use of pervious concrete formaintaining existing mature trees during andafter urban development. Urban Forestry and
Urban Greening. 8(4), 2009,249-256.
[22] Shaffer, P., Wilson, S., Brindle, F., BaffoeBonnie, B., Prescott, C., Tarbet, N.
Understanding permeable and impermeablesurfaces-technical report on surfacing options
and cost benefit analysis. 2009, London, Dept.
for Communities and local Government.
[23] Sansalone, J., Kuang, X., Ranieri, V. Permeable
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[24] Frazer, L. Paving paradise-the peril ofimpervious surfaces, Environmental. Health
Perspectives. 113(7), 2005, 457-462.
[25] Mullaney, J., Lucke, T. and Trueman, S.J. A
review of benefits and challenges in growing

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27

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ALKALINE ACTIVATION FOR SOIL STABILIZATION
Bujang B.K.Huat1, Afshin Asadi2
Department of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor,
Malaysia; 2Department of Civil Engineering, International College of Auckland, Auckland, New Zealand1

ABSTRACT
There is a burgeoning interest in the development, characterization and implementation of alternatives to cement
and other cementitious binders in ground improvement. This interest is in part because of the technical advantages
and related environmental and energy issues, particularly in CO2 gas emission. The current paper presents a brief
history and a review of alkaline activation and carbonation as a greener alternative to cement stabilization. Some
recent investigations have been presented in this paper. Alkali-activated binders can constitute interesting materials
to fully eliminate traditional cementitious binder (i.e. cement and lime) usage in soil stabilization projects sincecalcium is not essential in any part of alkali-activated structure. In simple words, alkaline activation binder isgenerally a synthetic alkali aluminosilicate material that is produced from the reaction of a solid aluminosilicate
with a pre-designed concentrated aqueous alkaline hydroxide or silicate solution.
Keywords: Soil improvement, Alkaline activation, Geopolymerisation, Carbonation
technology can be found in the literature. In thisregard, a number of studies were conducted toevaluate the environmental benefits of alkaliactivated binder. Moreover, a large and growing bodyof literature has investigated the mechanism of thealkaline activation (AA) from wide variety ofaluminosilicate source materials, and the potentialityof utilizing various alkaline activators for the
dissolution of Si and Al oxides through alkaline
activation process. A significant body of these studies
validate the proposition that alkaline activation
provides a promising and sustainable alternative tothe use of cement and lime because of (i) the abundant
raw material sources and (ii) its lower energy
consumption and CO2 emission [1].
This current paper presents a brief history and areview of alkali-activated materials (new generationof binders) and recent investigation done at Universiti
Putra Malaysia.

INTRODUCTION
Due to robustness and easy adoptability, cement
and lime are often employed as stabilizing agents incivil engineering applications (i.e. ground
improvement).
However,these
traditional
cementitious binders are not only for their negativeenvironmental effects during manufacture but also for
their cost [1].
In the case of cement, it generates around 7% ofartificial CO2 emissions, because of carbonate
decomposition. It is estimated that every ton of
cement, it produces around one ton of CO2, a major
greenhouse gas implicated in global warming. Besidethe emission of CO2, another by-product of cement
production is NOx. Most of these nitrogen oxides areproduced in cement kilns, which can contribute to thegreenhouse effect and acid rain [1]-[2]-[3]-[4].
Alkali-activated binder may constitute aninteresting option to fully eliminate traditional
cementitous binders usage in civil engineering
projects since calcium is not essential in any part ofalkali-activated structure. Essentially, the synthesis ofalkali-activated binders, which are formed by thereaction of any amorphous aluminosilicate sourcewith alkali (usually Na or K) or alkali earth (Ca)metals, involves the dissolution of mineralaluminosilicates, followed by the hydrolysis andcondensation of the Al and Si components, resulting
in the formation of a three-dimensional, essentiallyamorphous, aluminosilicate gel . The final product isvery much dependent on the calcium availability.
Alkaline activation of low-calcium precursors results
in a N–A– S–H type gel, while as alkaline activationof high-calcium raw materials forms essentially C–
A–S–H gel [1]-[5] .
An abundance of papers on alkaline activation

BACKGROUND
The alkaline activation (also referred as to‘geopolymerisation’) can be described as apolycondensation (a reaction that chemicallyintegrates minerals), consisting of aluminum andsilica alternately tetrahedrally interlinked by sharing
all the oxygen atoms. The process starts when thehigh hydroxyl concentration of the alkaline medium
favors the breaking of the covalent bonds Si–O–Si,
Al–O–Al, and Al–O–Si from the vitreous phase of thesource material, transforming the silica (SiO2) andalumina (Al2O3) ions in colloids and releasing theminto the solution. Under this condition, aluminosilicates are transformed into extremely reactive
28

treated soil after curing times of 7, 28, 90, and 180
days. As can be seen, the AA stabilization induced adrastic increase in strength, either using sodiumhydroxide (NaOH) or potassium hydroxide (KOH) as
the base element of the activator. For the sodium-soilPOFA (NSP) and potassium-soil-POFA (KSP)
mixtures and after 180 days of curing, values of 3,360
and 6,000 kPa were observed, respectively.
Nonetheless, a brittle behavior was registered in thecase of the 90- and 180-day curing specimens, which
was indicated by the sudden drop in strength after aclear peak value was reached. Such behavior waseven more accentuated in the K+ mixtures (KSP)[10].
The loading procedure was conducted using ahydraulic jack under the stress control condition withan increment of 5 kPa per minute, and the procedurecontinued until it reached a normalized verticaldisplacement of nearly 20%, at which small
increments in the applied load result in relatively big
increase in the settlement, which indicates that thesoil has reached the failure condition (Fig. 2) [10]..

materials to form a well-structured alumino-silicate
polymerized framework [1]-[2].
In recent years, a large and growing body ofliterature has investigated the mechanism of alkaline
activation using a wide variety of alumino-silicate
source materials [2], the role of alkaline activators,
which are normally made by mixing a highly alkaline
solution (such as sodium hydroxide) [2]-[4]-[9], andthe environmental benefits of the alkaline activation
method [2].
A significant body of these studies validate theproposition that alkali-activated binders havesuperior performance in comparison withcementitious binders, such as lower energy
consumption, approximately 80% lower carbon
dioxide emissions, higher strength and with theprinciples of sustainable development. Therefore, ina political climate where governments around theworld are taxing carbon dioxide emissions andpromoting sustainable and environmentally friendly
materials, alkali-activated binder can emerge as animportant material of the future [2].
In the light of these advantages, research on thesynthesis of alkali-activated binder and identificationof reaction mechanisms in civil engineering
frameworks has intensified over recent years [2]-[4][9]. However, using this technology in ground
improvement applications is still at the early stage ofdevelopment.
In very limited attempts, some geotechnicalresearchers have investigated the effectiveness ofalkali-activated fly ash as silica and alumina
amorphous sources for soil stabilization [9].

Fig. 2

It can be seen in Fig. 3 that the vertical load in
untreated ground (S) increases rapidly with theincrease of settlement at first and reaches a plateau at
about 0.09 of displacement/footing width. Also, asshown in this figure, the vertical stress–displacement/footing width curve of untreated soil possessed theductile behavior.

RECENT INVESTIGATIONS AT UPM
Alkaline activation with POFAOne of the well-known agro-wastes, palm oil fuelash (POFA), was used as a source binder.

Fig. 3Fig. 1

Loading procedure.

Stress-strain behavior of treated soil samples
using alkali activated POFA (N-KSP) after
7, 28, 90, and 180 days curing.

The relationship between vertical stress anddisplacement in KSP1–3 group.

It can be clearly seen in Fig. 3 that increasing the
replacement area ratio, a, results in more
improvement in the qult of treated columns KSP1
(N=10, α=9.9), KSP2 (N=12, α=11.9) and KSP3

Fig. 1 shows the stress-strain behavior of the AA29

(N=16, α=15.82) (N and α designate number ofcolumns and replacement area ratio). Other than that,as shown in this figure, compared to untreated soil(S), the qult increased sharply in treated cases (KSP1–
3). This behavior is believed to have been due to theuse of alkaline activation process in treated cases(KSP1–3). In this respect, compared to untreated soil(S), higher enhancement was achieved in the case of
the KSP3, for which higher increased values ofbearing capacities up to 192% was observed at
replacement area ratio of 15.82% [5].
From Fig. 3, in treated cases (KSP1–3), thevertical stress increased rapidly at first, and then themodel ground exhibited progressive softening since
the bearing pressure decrease steadily after the peak.

Fig. 4

Alkaline activation with Olivine
Olivine is widely distributed around the world. It
has been found everywhere all over the Earth [8].
Fig. 6 shows the stress-strain behavior of soil (S),alkali-activated soil (AS), and alkali-activated soil
with different percentages of olivine (A5, A10, A15,and A20) after 7, 14, 28, and 90 days of curing.
Untreated soil specimens (S) showed a ductile
behavior with the strength of 103.4 kPa at a failure
strain of approximately 1.8%. Alkali activation
increased the strength of soil to 240.9, 263.0, 370.3,
and 521.7 kPa at 7, 14, 28, and 90 days, respectively.
The slight increase in the strength of soil specimens
observed in the presence of NaOH was attributed to
the role of NaOH in promoting the dissolution of Si
and Al within soil. The increase in the strength of AS
was not significant due to the low reactivity of Si and
Al. A progressive increase in strength was observed
when different amounts of olivine were used. The
strength of samples increased with olivine content (0–20%) and curing time (7–90 days). A20 achieved thehighest strength within all alkali-treated soil samples,
resulting in 850.3, 1,016.9, 1,210.5, and 3,964.8 kPa
at 7, 14, 28, and 90 days, respectively [11].

SEM micrographs of (a) natural soil; (b)KOH-POFA-soil (KSP).

Scanning
electronmicroscopy(SEM)
micrographs of the untreated soil (S) and KSP, after
curing for 90 days, are shown in Figs. 4(a–b). The
more open texture of the untreated soil is clear in Fig.
4(a), whereas the discrete soil particles appear moreclosely bounded in the stabilized material Fig. 4(b),with the voids seemingly filled.
Wollastonite microfibers were chosen as additivefrom a pool of several possibilities, based not only on
the fact that they fulfil the mentioned requirements
but also on their unique chemical composition andmicrostructure (40.0–50.0% of CaO and 40.0–55.0%
of SiO2), having been formed in nature by theinteraction of silica (SiO2) with calcite (CaCO3) underhigh pressure and temperature [5].
Fig. 5 show selected SEM image of the reinforced
AA specimens which shows the interaction between
the fiber surface and the geopolymeric matrix,
contributing to the enhanced behavior of thereinforced mixtures [10].

Fig. 6

Fig. 7

Fig. 5

UCS of alkaline-activated olivine-treatedsoil at curing times of (a) 7; (b) 14; (c) 28;(d) 90 days.

Cell setup for carbonating olivine treatedsoil.
A triaxial reactor was used to carbonate Mix
CPTA20 (P=pressure, T=carbonation time) byallowing pressurized gaseous CO2 (100 and 200 kPa)
to permeate through the olivine-treated soil for 12, 24,

SEM images of the microfibers inclusion in
the stabilized soil mixture.
30

delayed hydration and pozzolanic reaction within thesoil. Fig. 9(d) shows the microstructure of 20%
olivine-treated soil in the presence of 10 M of NaOH
after 90 days of curing. SEM images demonstrate acompact
morphology
withoutany
major
discontinuities, which is consistent with themechanical properties observed. The presence of a
new amorphous phase is evident in Fig. 9(d), which
reveal the formation of a gelatinous structure andcrystals on the surface of the samples and around theparticles of the starting material. SEM images ofsamples subjected to carbonation at a CO2 pressureof 200 kPa for 12, 24, 48, and 168 h shown in Fig. 10(a & d) demonstrate a denser and more homogenous
microstructure with an increase in carbonation
duration [6]-[11].

48, and 168 h. Immediately after molding, samples
were subjected to carbonation under a confiningpressure of 400 kPa, during which CO2 permeated
upward. The CO2 saturation level was detected by theoutflow tube placed underwater (Fig. 7) [11].
Fig. 8 shows the stress-strain behavior of alkaliactivated soil with 20% olivine (A20) after 90 days ofcuring and soil treated with 20% olivine in thepresence of 10-M NaOH subjected to carbonation at
100 and 200 kPa for up to 168 h. An increase in the
UCS was observed with an increase in the
carbonation pressure and duration. Strength rapidly
increased when the CO2 pressure and duration
increased from 100 to 200 kPa and 12 to 168 h,
respectively. When compared with uncarbonatedalkali-activated 20% olivine-treated soils at 90 days,
the corresponding samples subjected to carbonation(C(200;168)A20) achieved higher strengths. The results
show that olivine is a promising candidate for soil
stabilization because alkali-activated olivine treatedsoils were sufficiently carbonated within a few days
to achieve strengths required for ground improvement[11].

Fig. 10 SEM images of (a) C(200;12)A20; (b)C(200;24)A20;(c)
C(200;48)A20;(d)
C(200;168)A20.
Alkaline activation with Fly Ash
Fig. 8UCS of carbonated alkaline-activatedolivine-treated soil subjected to carbonationfor 12, 24, 48, and 168 h at pressures of 100
and 200 kPa.

Fig. 9SEM images of (a) soil; (b) olivine; (c)olivine-treated soil; (d) alkaline-activatedolivine-treated soil after 90 days curing.

Fly ash is a finely divided mineral residue
resulting from the combustion of coal in electric
generating plants. Fly ash was used as a stabilizer
agent to improve gypseous soil. Gypseous soil
demonstrates sudden volumetric changes in wetting
state due to dissolution of gypsum which causes
uneven settlement or collapsing [9].
Fig. 11 illustrates the collapse potentials ofgypseous soil samples stabilized with geopolymer fly
ash at 7, 28, 90 days of curing. As observed from Fig.
1-a, the gypsum content had a significant influence on
the collapse potential of the untreated gypseous soil
samples at early ages of curing. The collapse potential
increased when the gypsum content was elevated to45%. In samples with 13% gypsum (G13: natural soil
contained 13% gypsum), the collapse potential was
2.86 which can be considered as moderate collapse
while for 25% of gypsum content (G25) the collapse
potential was 7.95 (moderately severe) and finally forthe high gypsum content of 45% (G45), the collapse
potential increased to 10.75 and rated as severe. On
the other hand, stabilization of soil with geopolymer
fly ash decreased the collapsibility in all samples. The
increase in the fly ash content from 10 to 30%
declined the collapse potential at different rates. As
can be seen, the collapse potential for the G45

Fig. 9(a) shows that the microstructure of soil
consists of clusters of particles, whereas the irregularshape of olivine particles are seen in Fig. 9(b). Fig.
9(c) illustrates the olivine-treated soil after 90 days ofcuring. A comparison of Figs. 9 (a & c) reveals how
the olivine fills the pores of the soil as a result of its
31M). For the rest of samples, the collapsibility
potential increased by up to 5.7% and 9% in samples
activated with KOH and NaOH, respectively. Basedon the results, it can be concluded that in gypseous
soil samples with low gypsum content thecollapsibility potential maintained at a low level
especially when activated with KOH. However, when
the gypsum content increased to 25% and 45%,higher content of geopolymer fly ash was needed tomaintain the collapsibility potential at a controlled
range. For example, the collapsibility potential ofgypseous soil samples with 25%, 45% of gypsum
content stabilized with 30% fly ash / KOH (12 M)
increased only by 0.06% and 0.11% as soaking
duration increased from 7 to 28 days.
The collapsibility potentials of stabilized soil
samples after 90 days of soaking are shown in Fig.
12-c. As can be seen, only samples with lower
gypsum content and high percentage of geopolymer
fly ash maintained their integrity and the rest
dissolved due to gypsum leach out. However, therecorded results showed that the collapse potentials
for the G13 and G25 stabilized with 30% fly
ash/KOH (12 M) were less affected. The G45 treatedwith 30% KOH activated fly ash showed slightincrease in collapse potential from 1.88 at 28 days to
1.97 at 90 days [9]-[12].
Fig. 13 shows the changes in morphology andmicrostructure of the gypseous soil samples stabilizedwith 30% fly ash/KOH (12 M) and 30% fly
ash/NaOH (12 M) after 28 days soaking in water. As
can be seen, samples activated with KOH (12 M)
showed denser matrix and more intact bonds.
Increasing the content of gypsum in samples,
intensified disintegration of the binder as can be seenfrom Fig. 13-c, d. Besides, soil grains are easily
traceable, though, the presence of the aluminasilicate-hydrate crust cover on the soil particles isobserved. As for samples activated with NaOH (12M), the gaps between the soil grains were greater andthe soil particles were more isolated [9]-[12].

samples was 10.75 and it reduced to 8.96, 5.88, and
3.7 in KOH activated samples with 10%, 20% and
30% fly ash, respectively. The reduction was to 9.09,
6.64, and 4.48 in samples activated with NaOH at 7days when 10, 20, and 30% fly ash was used tostabilize the gypseous soil. The mechanism of
improvement can be explained as follows: As thecontent of binder increased the enveloping effect of
the crust escalated and consequently the collapsibility
potentials declined further [12].
Fig. 12 shows collapsibility potentials of
stabilized soil samples soaked in water for 7, 28 and90 days. It should be noted that the soaking process
in water was carried out on samples cured for durationof 28 days. Furthermore, it was observed that within
the initial 7 days of soaking, untreated samples were
fully dissolved so no data is available. However, therecorded collapse potentials were 4.93, 9.71 and12.46 for G13, G25, and G45 at 3 days, respectively.
In general, the collapse potential for the stabilized
gypseous soil with 10, 20, 30% geopolymerized fly
ash increased as soaking duration prolonged
indicating the vulnerability of soil to wetting.

Fig. 11 Collapsibility potentials of soil samples at a)
7 days b) 28 days, c) 90 days.
As can be seen from Fig. 12-a, minimum levels of
collapsible potentials were recorded when thegypseous soil samples were stabilized with the fly ash
dosage of 30% at 7 days of soaking. However,activation of fly ash with KOH resulted in moreresistant samples in terms of collapsibility in shorttime. The results showed that the collapsibility
potentials of samples with 45% gypsum content werelower by 11.6%, 5.5%, and 1.8% when 10%, 20%,and 30% Fly ash activated with KOH was usedcomparing to its counterparts activated with NaOH.
However, it was observed that samples with highcontent of gypsum (45%) stabilized with 10% fly
ash/NaOH disintegrated at 7 days of saturation.
As soaking duration prolonged to 28 days (Fig.
12-b), more series of samples disintegrated namely,
samples stabilized with 10% and 20% fly ash /NaOH(12 M) and 10% of activated fly ash with KOH (12Fig. 12 Collapsibility potentials of the soaked soil
samples at a) 7 days b) 28 days c) 90 days.
32

with a pre-designed concentrated aqueous alkalinehydroxide or silicate solution.

The microstructure and morphology of thestabilized gypseous soil, G45 with 30% of fly ash
activated with KOH (12 M) and NaOH (12 M) arealso illustrated in Figs. 14. As can be seen from Fig.
14-a, the SEM image shows the formation of the AS-H gel binder with a dense texture and highly strong
matrix in G45 samples stabilized with KOH activated
fly ash. No presence of borders was observed in thegel portion because of the ability of KOH to dissolve
the fly ash and soil components. On the other hand,
this gel surrounded the insoluble soil grains, which
can limit the reactivity of sulfate ions, and their leachout in the gypseous soil. Fig. 14-b shows the SEM
image of the G45 treated with 30% fly ash activatedwith NaOH (12 M). The image is illustrative of a lessdense matrix comparing with the gel formed in the
KOH (12 M) samples. As can be seen, the soil grains
are rather more visible. A denser matrix was also
observed in the paste samples with intensive gel when
fly ash was activated with KOH (12 M) [12].

ACKNOWLEDGEMENTS
The authors sincerely thanks Universiti Putra
Malaysia (UPM) for providing financial assistanceand facilities for this research.
REFERENCES[1] Pourakbar, S. and Huat, B. K., A Review of
Alternatives Traditional Cementitious Binders forEngineering Improvement of Soils. Int. J. Geotech.
Eng., Vol.11, No.2, 2016, pp.206–216.
[2] Pourakbar, S., Asadi, A., Huat, B. B. andFasihnikoutalab, M. H., Soil stabilization with alkaliactivated agro-waste. Environmental Geotechnics,
Vol.2, 2015, pp.359–370.
[3] Pourakbar, S. and Huat, B. K., Laboratory-Scale
Model of Reinforced Alkali-Activated Agro-Waste for
Clayey Soil Stabilization. Advances in Civil Eng. Mat.,
Vol.6, Issue 1, 2017, pp.82–105.
[4] Fasihnikoutalab, M. H., Pourakbar, S., Ball, R. J., andHuat, B. K., The Effect of Olivine Content and Curing
Time on the Strength of Treated Soil in Presence ofPotassium Hydroxide. Int. J. of Geosynth. and GroundEng., 2017, 10.1007/s40891-017-0089-3.
[5] Pourakbar, S., Asadi, A., Huat, B. B., Cristelo, N., andFasihnikoutalab, M. H., Application of AlkaliActivated Agro-Waste Reinforced With Wollastonite
Fibers in Soil Stabilization. J. Mater. Civ. Eng., 2016,10.1061/(ASCE)MT.1943-5533.0001735.
[6] Fasihnikoutalab, M. H., Asadi, A., Huat, B. K.,
Westgate, P., Ball, R. J., and Pourakbar, S.,
Laboratory-scale model of carbon dioxide deposition
for soil stabilization. J. Rock Mech. Geotech. Eng.,
Vol.8, Issue 2, 2016, pp.178–186.
[7] Fasihnikoutalab, M. H., Westgate, P., Huat, B. K.,
Asadi, A., Ball, R. J., Haslinda, N., and Singh, P., Newinsights into potential capacity of olivine in ground
improvement. Electronic Journal of GeotechnicalEngineering, Vol.20, Issue 8, 2015, pp.2137-2148.
[8] Fasihnikoutalab, M. H., Asadi, A., Huat, B. K., Ball,
R. J., Pourakbar, S., Parminder, S., Utilization ofcarbonating olivine for soil stabilization. Environ.
Geotech., 2015, doi:10.1680/ jenge.15.00018.
[9] Alsafi, S., Farzadnia, N., Asadi, A., Huat, B. K.,
Collapsibility potential of gypseous soil stabilizedwith fly ash geopolymer; characterization andassessment. Const. Build. Mat., Vol.137, 2017,
pp.390–409.
[10] Pourakbar, S., The use of alkali-activated palm oil fuelash reinforced by microfibers in deep mixing method,
2015, pp.1-213.
[11] Fasihnikoutalab, M. H., Utilization of olivine for soil
stabilization. PhD Thesis, UPM, 2015, pp.1-133.
[12] Alsafi, S., Gypseous soil stabilization by alkaline
activation method. PhD Thesis, UPM, 2016, pp.1-25

Fig. 13 SEM images of stabilized soil with 30% fly
ash after soaking for 28 days a) G13/KOH(12 M) b) G13/NaOH (12 M) c) G45/KOH(12 M) d) G45/NaOH (12 M).

Fig. 14 SEM images of G45 stabilized with 30% fly
ash activated with a) KOH (12 M) b) NaOH
(12 M).
CONCLUSION
Alkali-activatedbinders
canconstituteinteresting materials to fully eliminate traditional
cementitious binder (i.e. cement and lime) usage insoil stabilization projects since calcium is notessential in any part of alkali-activated structure. In
simple words, alkaline activation binder is generally
a synthetic alkali aluminosilicate material that is
produced from the reaction of a solid aluminosilicate

33Technical Papers

34

Geotechnique

35

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

CHARACTERIZATION OF ENVIRONMENT FRIENDLY
GEOTEXTILES EMBEDED IN SOIL UNDER PULLOUT TEST
Md. Aminul Islam1, Zakaria Hossain1, Jim Shiau2 and Siti Hanggita Rachmawati1
1Faculty of Bioresources, Mie University, Japan,
2
School of Civil Engineering and Surveying, University of Southern Queensland, Australia
ABSTRACT
Characterizing of a geosynthetic is very essential for its effective use in various field application of reinforced
soil structures. The success of reinforced soil structures depends not only on the types of backfill materials but
also on the types of the reinforcements used in the structures. In view of this objective, a new type ofgeosynthetic has been evaluated for its interaction properties for different backfill soils using direct pullout test.
The test results are compared based on the type of soils and interface mechanical properties of thereinforcements. Three backfills soils (sandy, clayey, and pure sand) in combination with four different
geosynthetics were tested at various loading conditions in direct pullout. Based on the analyses of theexperimental data, the pullout strength and the pullout displacement of reinforcements due to the variation of thebackfill soils are examined. Test results reveal that the stress-deformation behaviour of the geotextile interfaces
with all the backfills can be defined as hyperbolic. GT4 also shows the linear curve with hyperbolic
characteristics. Both softening and hardening behavior is found with the pure sand. But with the sandy andclayey soil, no softening behavior is observed. On the contrary; GT1 shows the lowest value of pullout stresswith all the backfill soils. For GT2 and GT3, almost the same interface behavior is observed with clayey andsandy soil. It is found that GT4 produces the maximum of 140 kPa pullout stress with the toyoura sand andsandy soil.
Keywords: Geosynthetic; Toyoura sand; Direct pullout test; Interface pullout strength
propylene (PP), Polyester (PET) yarns coated with
PVC, etc. The present study dealt with a new type ofgeosynthetic which is made from basalt fiber. A
series of direct pullout tests on the geosynthetic
interfaces with different type of backfill soils havebeen conducted in the laboratory. Based on the test
results, the stress-displacement behaviour of theinterfaces along with different mechanicalcharacteristics has been evaluated and discussed
shortly.

INTRODUCTION
The fashion of reinforcing the soil with various
tensile inclusions has been widely practiced in
geotechnical engineering for the last few decades.
For the design and performance of reinforced soil
structures, the interaction between soil andreinforcement is very important, and this interaction
can be very complex depending on the nature andproperties of the reinforcement [9]. Various types ofgeosynthetic materials have been used for soil
reinforcement including geotextiles (woven andnonwoven), geogrids and geocells [6,7,8]. Whatever
the reinforcement and backfill materials are used forthe design of a reinforced soil structure, theinteraction properties of soil- reinforcement interface
play an important role [1]. The interaction
mechanism between the reinforcement and the soil
can be classified into two types; sliding of soil over
the reinforcement and pullout of reinforcement fromthe soil [4,5]. The pullout tests and the direct shear
are widely used methods to study quantitatively
these interaction mechanisms.
To study the interaction between soil andreinforcement, the direct pullout test is a suitable
method because it can simulate the pullout
mechanism along a potential failure plane in
reinforced earth structure [2,3]. The pullout strengthof soil-geosynthetic interfaces has been investigatedusing direct pullout tests by a number of researchers.
They used various types of geosynthetic materials
like High density polyethylene (HDPE), poly

PURPOSE OF THE STUDY
1. To investigate the pullout behavior of a new
type of geosynthetic, made of fiber basalt, withdifferent backfill soils, through a series of directpullout test.
2. Evaluating Soil-Geotextiles interfaces, pullout
stress pullout displacement, vertical displacement,
cohesion & internal friction
3. Characterizing of Geotextiles
MATERIALS AND METHODS
Backfill Materials
Three types of soils were used as backfill
material in this study. Air-dry pure silica sand
named as Toyoura sand, one sandy and one clayeysoil have been used to evaluate the interface
behaviour with the same geosynthetic materials.

36

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Pullout Apparatus
The pullout box is a rectangular shape of size 150
mm in length, 100 mm in width and 100 mm inheight. The box is divided into two parts namely
lower box and upper box both are 50 mm in depth.
For convenience of the readers, the importantcomponents of the testing equipment (Figure 4) are
numbered numerically starting from top-left to rightdown in the increasing way such as, the number
from [1] to [12], where the number [1] is the pullout
stress monitoring display, [2] is the supporting plateof reaction of the applied normal stress, [3] is theupper part of the pullout box, [4] is the electricallyoperated pullout jack, [5] is the pullout stressmeasuring device, [6] is the reinforcement clamping
jack, [7] is the test reinforcement, [8] is theclearance adjusting screw and fixing system of theupper box, [9] is the lower part of the pullout box,
[10] is the horizontal displacement measuring dialgauge, [11] is the vertical displacement measuring
dial gauge and [12] is the applied normal stressmeasuring dial gauge.

Fig.1 Particle size of the backfill soils
The optimum water content of sandy and clayeysoils was 13% and 14%, respectively. Figure 1
represents the gradation curves of the experimental
soils. According to JGS engineering classification
system, the sandy and clayey soils are classified as
SF and CL, respectively. The major physicalproperties of the soils are listed in Table 1.
Table1. Physical properties of the backfil soils
Properties
ClayeySandy
Particle density, ρs
2.7 g/cm3
2.59 g/cm3
Water content, Wopt
14%
13%
Cohesion (c)5.0
1.5Angle of internal
18.5
23.23
friction (φ)
Liquid limit, LL
39%---Plastic limit, PL
26.8%----Plasticity index, PI
12.2%----Sand (75 µm - 2 mm)
45%85%
Silt (5 µm - 75 µm
30%
11%Clay < 5 µm
25%
4%Geosynthetic Specimens
The woven geotextiles used in this study are madeof Basalt fiber. These materials possess good
property of elasticity and stretch tension with good
resistance to acid, alkali, heat and vibration. It has
also nonconductive and non-magnetic resistance.
The physical characteristics of these geosynthetics
are listed in Table 2. For the purpose of discussion,
the geotextile is noted as GT1, GT2, GT3 and GT4
as shown in fig. 2.

GT1

GT2

GT3

Fig.3 Typical schematic diagram of the pull-out
boxes
Setup and procedure
At first, the required amount of soil with desired
water content were poured into the lower part of thepullout box (No.9, Figure 4) and compacted
uniformly by means of a compactor made of same
width as of the pullout box. The lower box was filled
completely and the surface of the soil was leveled
precisely. The geosynthetic of same width was laidon the soil of lower box and fastened with clamping
jack as shown in No. 6 of Figure 4. The upper partof the pullout box (No.3) was placed on thegeosynthetic (No.7), and required clearance between
the geosynthetic and upper box was set by means ofadjusting screw by No.8. In the second stage, thesoil was gradually spread over the geosynthetic
inside the upper box and compacted uniformly topour the soil into the geosynthetic. The tests werecarried out in the way of pulling out the geosynthetic
from the soil with constant speed of 1.0 mm/min bymeans of screw jack (No.4) under electricallyoperated constant pressure. The pullout force wasGT4

Fig.2 Types of geotextiles used in the direct pullout
test
37

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Pullout stress (kPa)

Pullout stress (kPa)measured using a tension load cell (No.5) with aleast count of 5.0 N. The load cell was set between
the geosynthetic and the jack to facilitate direct load
measurement on the cell avoiding any frictional
discrepancy of the machine components. The
displacements were measured at the front of the bymeans of a dial gauge (No.10) with least count of
0.001 mm. The vertical displacement and applied
normal loads were measured by the dial gages asshown in figure by Nos. 11 and 12, respectively.The
direct pullout tests were conducted using four
different normal stresses of 40, 60, 80 and 100 kPa.

160
140
120
100
80
60
40
20
0

160
140
120
100
80
60
40
20
0

40 kPa60 kPa80 kPa100 kPa0 1 2 3 4 5 6 7 8 9 10
Pullout displacement(mm)( GT1 )

40 kPa60 kPa80 kPa100 kPa0 1 2 3 4 5 6 7 8 9 10
Pullout displacement(mm)(GT2 )

Pullout stress, kPa

Fig.4. Pullout testing equipment and its components
RESULTS AND DISCUSSION
Pullout Stress-Displacement RelationshipA series of direct pullout tests were performed toobtain the stress-deformation characteristics of thegeosynthetic interfaces for different backfill soils.
The test results reveal that the relationship between
pullout stress and relative displacement depends on
both the type of backfill and geosynthetics. It is seenthat the stress-displacement relationship ofgeotextile (GT) interfaces is same for all the backfill
soils. The relationship for GT interfaces can be
defined as hyperbolic in nature. Before and after the
peak pullout stress, displacement hardening andsoftening behaviour is clearly observed. Maximum
pullout resistance mobilizes within 4-7 mm ofpullout displacement for geotextiles interfaces withpure sand backfill.

160
140
120
100
80
60
40
20
0

40 kPa60 kPa80 kPa100 kPa0 1 2 3 4 5 6 7 8 9 10

Pullout stress, kPa

Pullout displacement,mm
(GT3)
160
140
120
100
80
60
40
20
0

40 kPa60 kPa80 kPa100 kPa

0

1

2

3

4

5

6

7

8

Pulout displacement,mm(GT4)
Fig.5 Pullout stress-displacement curve for
Toyoura sand
38

9 10

GEOMATE - Mie, Japan, Nov. 21-24, 2017

120
100

40 kPa60 kPa80 kPa100 kPa

60
40
20

Pullout stress, kPa

40 kPa80

60 kPa60

80 kPa40

100 kPa20

0 1 2 3 4 5 6 7 8 9 10
Pullout displacement,mm( GT1 )

120
100

40 kPa80

60 kPa60

80 kPa40( GT1 )
120
100

0 1 2 3 4 5 6 7 8 9 10120

60 kPa100

80 kPa40

100 kPa

20
0

40
20

(GT3)

40 kPa80

Pullout stress,kPa

Pullout stress, kPa

0 1 2 3 4 5 6 7 8 9 10
Pullout displacement,mm
(GT3)

120

100

60 kPa60

80 kPa40

100 kPa

20
0

40 kPa60 kPa80 kPa100 kPa

60

Pullout displacement,mm
120

0 1 2 3 4 5 6 7 8 9 10
Pullout displacement,mm(GT2 )

80

00 1 2 3 4 5 6 7 8 9 10

100 kPa

20

40 kPa60

80 kPa40
0

Pullout stress,kPa

Pullout stress, kPa

80

60 kPa60(GT2 )
100

40 kPa80

Pullout displacement,mm
120

0 1 2 3 4 5 6 7 8 9 10
Pullout displacement,mm

100 kPa

20
0

100

0

Pullout stress,kPa

Pullout stress, kPa

80

0

Pullout stress,kPa

120

0

1

100
60
40
20
0

2 3 4 5 6 7 8 9 10
Pullout diaplacement,mm
(GT4)

40kPa
60kPa
80 kPa100 kPa80

0 1 2 3 4 5 6 7 8 9 10
Pullout displacement,mm(GT4)

Fig.6 Pullout stress-displacement curve for Clayey
soil

Fig.7 Pullout stress-displacement curve for Sandy
soil
39

GEOMATE - Mie, Japan, Nov. 21-24, 2017

cases. But the increasing trend is not the same for all
the geotextiles with the clayey and sandy soils. It isobserved that GT1 produces the lowest rate of
maximum pullout stress with all the soils. In case of
Toyoura sand, it is found in Fig. 8 that the GT2
showed the higher rate while GT3 showed the lower
rate. Among all the four types of geotextiles, GT4
exhibited the highest rate of maximum pullout stress.
On the other hand, in case of clayey and sandy soils,
all the geotextiles maintained the similar trend ofincreasing rate with the increase in normal stress.
Figs. 9 and 10 clearly showed that the increasingrate of maximum pullout stress for GT2, GT3 andGT4 is very close to one another.

Maximum pullout stress

The pullout strength is found increasing with theincrease of normal stress which is a common
phenomenon for all soil-geosynthetic interfaces
tested in this study.
The relationships between the pulling stress andthe displacement of geotextiles under normal stressof 40, 60, 80 and 100 kPa are given in Fig. 5, 6 & 7.
It is observed that the difference of the pullout
stresses under different normal loading conditions
were comparatively smaller at the initial loading till
attaining the peak value as compared to thedifference of the pullout stresses obtained at the final
loading condition after peak value. It is evident thatthe pullout stresses decreased after attaining the peakvalue for all the cases.
The Fig.5 shows that GT4 produces the maximumof pullout stress with The Toyoura sand and Sandy
soil. On the contrary, GT1 shows the lowest value of
Pullout stress with all the backfill soils. For GT2
and GT3, almost the same interface behavior isobserved with clayey and sandy soil. But with the
Toyoura sand, GT2 produces the higher pullout
stress than GT3. The pullout stress mobilizes within
36 kPa to 140 kPa for the applied normal load 40, 60,
80 and 100 kPa. GT1 always shows the straight line
curve for every normal load with all the backfill
soils. For all the applied normal load, no softening
behavior is observed. GT2 shows the fluctuating
characteristics with the Toyoura sand and Sandy soil.
But with the Clayey soil, it shows the linear
behavior. In contrast with GT1, before and after the
peak normal stress, both hardening and softening
behavior is observed. GT3 shows S stripe curve with
the Toyoura sand and linear behavior with the
Clayey and Sandy soil. It shows the hardening
behavior with all the backfills.GT3 shows the
maximum pullout stress with all the backfill soils.
GT4 also shows the linear curve with hyperbolic
characteristics. Both softening and hardening
behavior is found with the pure sand. But with the
sandy and clayey soil, no softening behavior isobserved

Backfill: Toyoura150

y = 1.3002x + 11.8
y = 1.1263x + 15.278
y = 0.9039x + 14.034

100

y = 0.4966x + 26.114

50

0

0

20

40

60

80

Normal stress

GT1
GT3
Linear (GT1)
Linear (GT3)

100

120

GT2
GT4
Linear ( GT2)
Linear (GT4)

Fig.8 Relationships of maximum pullout stress andnormal stress for Clayey-Geotextiles

Backfill: Clayey soil

160
140

y = 0.7342x + 23.621

Maximum pullout

120

Relationships of Maximum Pullout stress andNormal stress for Soil-Geotextiles
Relationships of maximum pullout stress andnormal stress for four types of geotextiles and three
types of soils are shown in Figs. 8 to 10. The graphs
are drawn with the maximum pullout stress obtained
from the applied normal load of 40, 60, 80 and 100
kPa. The angle of the straight line to the X axis
indicating the Phai value and its intersection to the Yaxis indicating the C value.
It is evident that the maximum pullout stressincreases with the increase of normal load in every

y = 0.6262x + 30.571

100

y = 0.6513x + 23.529

80

y = 0.2829x + 26.889

60
40
20
0

0

20

40

60

Normal stress

GT1
GT3
Linear (GT1)
Linear (GT3)

80

100

120

GT2
GT4
Linear (GT2)Linear (GT4)

Fig.9 Relationships of maximum pullout stress andnormal stress for Clayey-Geotextiles
40

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Backfill: Sandy soil

160
140

Internal Friction

y = 0.7126x + 24.401
y = 0.7802x + 20.781
y = 0.7684x + 14.214

120
100

Phai values Toyoura sandPhai values Clayey soil

y = 0.3406x + 22.63

80

60

60
40

Internal friction(°)

Maximum pullout stressGT3 and Clayey- GT4 are 26.8 kPa, 30.5 kPa, 23.5
Kpa and 23.6 kPa respectively

20
0

0

20

40

60

80

100

120

Normal stress
GT1
GT3
Linear (GT1)
Linear (GT3)GT2GT4Linear (GT2)Linear (GT4)

50
40
30
20
10
0

Fig.10 Relationships of maximum pullout stress andnormal stress for Toyoura-Geotextiles

GT1

GT2

Gt3

GT4

Fig.21 Internal friction of the three types backfills
and four types of geosynthetics

Cohesion

20

The pure sand-GT4 interface obtained maximum
friction angle of 52.4⁰ whereas the minimum friction
angle of 15.7⁰ is found for Clayey –GT1 interface.
The maximum internal friction angles of Toyoura
sand-GT1, sand-GT2, sand-GT3 and sand-GT4
interfaces are obtained as 26.4⁰, 48.3⁰, 42.1⁰ and
52.4⁰, respectively. It is observed that among all
sand geosynthetic interfaces, the sand-GT4 interface
develops the highest frictional resistance whereas
sand-GT1 interface develops the lowest frictional
resistance. The frictional resistance of sand-GT2
interface is 6⁰ higher than that of sand-GT3 andlower than GT4 interface.

10

CONCLUSIONS

Cohesion and internal friction obtained from therelationship of maximum pullout and normal
stresses for four types of geotextiles and three typesof backfill soils are drawn in Figs. 20 and 21.
40
Cohesion(kPa)Phai values Sandy soil

30

0

C‐ values Toyoura sandC‐ values Clayey soil
C‐ values Sandy soil

GT1

GT2

Gt3

Finally, it can be concluded that the pullout stressshowed its increasing trend with the increase inapplied normal stress irrespective of variety ofgeosythetics and the different category of backfill
soils. The relationship for GT interfaces is defined as
hyperbolic. Before and after the peak pullout stress,
displacement hardening and softening behaviour is.
It is found that GT4 produces the maximum of
140 kPa pullout stress with the toyoura sand andsandy soil. GT4 also shows the linear curve withhyperbolic characteristics. Both softening andhardening behavior is found with the pure sand. But
with the sandy and clayey soil, no softening
behavior is observed. On the contrary; GT1 shows
the lowest value of pullout stress with all the backfill
soils. GT1 always shows the straight line curve forevery normal load with all the backfill soils. For

GT4

Fig.20 Cohesion of the three types backfills and fourtype of geosynthetics
Soil-geosynthetic interface friction is an
important parameter for designing a reinforced slope(Shukla and Yin, 2006). It is observed in Fig. 4.31
that clayey-GT2 interface obtained the maximum
cohesion of 30.5 kPa with the clayey backfill
whereas the minimum cohesion of 12 kPa isobserved for pure sand-GT4. The maximum
cohesion of Clayey- GT1, Clayey- GT2, Clayey41

GEOMATE - Mie, Japan, Nov. 21-24, 2017of the 1st International Con-ference on
Geotechnique, Construction Materials andEnvironment, Mie, 21-23 November 2011, pp.
191-196.
[2] Jewell, R.A. 1996. Soil strength and bearing
capacity. Soil reinforcement with geotextiles,
CIRIA, Thomas Telford. 55-83.
[3] Gurung, N and Y. IWAO. 1999. Pullout test
analysis for georeinforcement. Geotextiles andGeomembranes. 17: 157-170.
[4] Hossain, M.Z. and Sakai, T.”. A Study on
Pullout Behavior of Reinforcement Due to
Variation of Water Content of Soil”
Agricultural Engineering International: the
CIGR Ejournal. Manuscript LW 07 011. Vol.
IX. December, 2007.
[5] M. B. Hossain, M. Z. Hossain and T. Sakai,Interaction Properties of Geosynthetic withDifferent Backfill Soils” International Journalof Geosciences, 2012, 3, 1033-103.
[6] Shamsher, F.H. (1992). Ground Improvementwith Oriented Geotextiles and Randomly
Distributed Geogrid Micro-Mesh. PhD Thesis
submitted to Indian Institute of Technology
Delhi, New Delhi, India.
[7] Shukla, S.K. (1997). A study on causes oflandslides in Arunachal Pradesh. Proceedings ofIndian Geotechnical Conference, Vadodara,
India, 1, 613-616.
[8] Shukla, S.K. (2002). Slopes-stabilization. In
Geosynthetics and Their Applications, Shukla,
S.K., Ed., Thomas Telford, London, 237-257.
[9] Shukla, S.K. (2004). Discussion of Applicationsof geosynthetics for soil reinforcement by
M.I.M. Pinto, Ground Improvement, 7(2), 61-72

GT2 and GT3, almost the same interface behavior isobserved with clayey and sandy soil. pure sand.
It is observed that clayey-GT2 interface
obtained the maximum cohesion of 30.5 kPa withthe clayey backfill whereas the minimum cohesionof 12 kPa is observed for pure sand-GT4. The
maximum cohesion of Clayey- GT1, Clayey- GT2,
Clayey- GT3 and Clayey- GT4 are 26.8 kPa, 30.5
kPa, 23.5 Kpa and 23.6 kPa
It is also noticed that the pure sand-GT4
interface obtained maximum friction angle of 52.4⁰
whereas the minimum friction angle of 15.7⁰ isfound for Clayey –GT1 interface. The maximum
internal friction angles of Toyoura sand-GT1, sandGT2, sand-GT3 and sand-GT4 interfaces are
obtained as 26.4⁰, 48.3⁰, 42.1⁰ and 52.4⁰,
respectively. It is observed that among all sandgeosynthetic interfaces, the sand-GT4 interface
develops the highest frictional resistance whereas
sand-GT1 interface develops the lowest frictional
resistance. The frictional resistance of sand-GT2
interface is 6⁰ higher than that of sand-GT3 andlower than GT4 interface.
Based on the obtained results of the importantparameters for reinforced slope stability like thepullout stress-displacement, vertical-horizontal
displacement, cohesion and frictional resistance ofthe four categories of geotextiles, GT4 can berecommended for the field application.
REFERENCES[1] M. B. Hossain, M. Z. Hossain and T. Sakai,Interface Behaviour of Basalt Geosynthetic with
Sand Using Direct Shear Device, Proceedings42Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE EFFECT OF VOID RATIO, MOISTURE CONTENT AND
VERTICAL PRESSURE ON THE HYDROCOMPRESSIONSETTLEMENT OF COPPER MINE TAILING
Mary Ann Q. Adajar1 and Miller DL. Cutora2
Faculty, De La Salle University, Manila, Philippines
2
Graduate student, De La Salle University, Manila, Philippines
1

ABSTRACT
Copper mine tailing (CMT) has the potential to be used as embankment material but this waste material
contains plasticity. Soils containing plasticity are highly reactive to any form of liquid and considered to havegreater compressibility when exposed to water. As an embankment material, CMT is susceptible to different
environmental condition which can cause significant settlement. One possible cause of volume loss is thecompression due to wetting or hydrocompression. This study aims to determine the consolidation properties
and hydrocompression settlement of waste materials with plasticity like copper mine tailing when used asembankment material. One-dimensional consolidation tests were performed on reconstituted specimens. The
obtained consolidation properties indicate that CMT is very slightly compressible under over-consolidated
condition to moderately compressible under normally consolidated condition. The hydrocompression settlementof CMT in relation to initial void ratio, moisture content and preloaded vertical pressure was investigated. The
hydrocompression settlement increases with increasing pressure until the preconsolidation pressure is reached,then decreases with pressure beyond the preconsolidation pressure. Samples with lower density and watercontent less than its optimum exhibit greater hydrocompression settlement. The determined hydrocompression
strain in every condition is less than 5% which means that CMT has a degree of collapsibility classified as low tonegligible despite of having plasticity. CMT when used as embankment materials should be prepared with initialmoisture content slightly more than its optimum, it should be in its very dense condition and preloaded withvertical stress more than its preconsolidation pressure to make hydrocompression strain negligible.
Keywords: Copper Mine Tailings, Embankment Material, Hydrocompression Settlement, Consolidation
Propertiesof condition where significant settlement can rapidly
occur. One possible cause of volume loss is thecompression due to wetting or termed as“hydrocompression” or “hydrocollapse”. Some soils
can swell, collapse, shrink or experienced extreme
settlement if exposed to water or any fluid.
Investigation about the hydrocompression of gold
mine tailings and wastes from aggregate quarry in
the Philippines with non-plastic fines was discussed
in previous study [1]. Findings of the study showedthat these wastes materials which are non-plastic areless susceptible to hydrocompression.
Copper mine tailing has the potential to be usedas embankment material [4] but this waste material
contains plasticity, a property prevalent in clay
minerals. Soils containing clay minerals are highly
reactive to any form of liquid and considered to havegreater compressibility when exposed to water.
Several studies proved that compressibility andcollapsibility of embankment materials are
dependent on several factors like amount of moisture,clay mineralogy, density and applied pressure.
Increasing the moisture content affects thecompaction behavior and compressibility of

INTRODUCTION
The disposal of the enormous amount of wastes
regularly produced from mining processes is one of
the most common environmental issues associated in
the operation. One possible option to address
disposal problem is to utilize these waste materials
that do not contain deleterious components asembankment materials. To evaluate the suitabilityof solid wastes as embankment materials, itsgeotechnical characteristics have to be established.
The determination of the consolidation properties
that describe the compressibility and the onedimensional settlement of mining wastes whensubjected to vertical stresses had been covered in the
study of some researchers [1]–[3].
However,compressibility and settlement of embankment
materials are not only caused by vertical stresses
imposed to the earth structure. During service life ofembankment or fill materials, environmental
changes can lead to an increase in its moisture
content which can affect the compressibility andsettlement behavior. Waste materials, when use asembankment materials, are susceptible to this kind43

GEOMATE - Mie, Japan, Nov. 21-24, 2017

soft consistency.

municipal solid wastes used as embankment. Its
compaction period shortens while compressibility
increases when water was added [5]. Claymineralogy affects the coefficient of consolidation(Cv). The increase or decrease of Cv which describes
the compressibility in clays is governed by themechanical and physicochemical factors [6]. The
study of Langroudi and Jefferson [7] investigates thecontribution of hydraulic and stress history incollapsibility of excavated calcareous clayey loessre-used as embankment materials. The findings
showed that controlled stress-hydraulic paths canguarantee the long-term response of embankments
made of excavated calcareous clayey loess.
This research study aims to determine theconsolidation properties and hydrocompression
settlement of waste materials with plasticity likecopper mine tailings through one-dimensional
consolidation test.
This study verifies if theplasticity of the material is one factor that will leadto greater hydrocompression settlement. It is also
the objective of this study to investigate the effect of
initial moisture content, initial void ratio in terms of
relative density and pre-loaded vertical pressures tothe hydrocompression settlement of copper minetailings. The determination of consolidation
properties and hydrocompression settlement are
essential steps to completely evaluate the suitabilityof copper mine tailings for geotechnical application.

Determination of Consolidation Properties
The consolidation properties of the tailingsamples were determined through one-dimensional
consolidation test using the procedure described in
ASTM D2435. Reconstituted specimen was
prepared with a target relative density slightly closed
to 90% to simulate the very dense condition of theembankment. Load increments that applied stressesof 12.5, 25, 50, 100 and 200 kPa were used. The
tests were conducted with specimen fully submergedin water for the entire duration of the tests. This is tosimulate the condition where embankment materials
are expected to be at its most compressible state.
Consolidation properties such as compression index(Cc), recompression index (Cr) and preconsolidationpressure (σ’p) were determined using the Modified
Strain Energy method [8]. The coefficient ofconsolidation (Cv) was determined using Taylor’s
square root of time method [9].
Determination of Hydrocompression Settlement
Variations in initial relative density, initialmoisture content, and predetermined vertical stresswere incorporated in the experimentation to verify
the effect of these factors on the hydrocompression
settlement of CMT. Reconstituted specimens wereprepared at initial relative density of 60%, 80% and100% to simulate the medium dense, dense, andvery dense conditions of embankment, respectively.
Three variations in water content at start of test wereused; the dry phase where water content is slightly
less than the optimum moisture content (wopt), theoptimum phase where water content is equal to wopt ,and the wet phase where water content is slightly
more than the wopt. Four (4) preloaded verticalstresses (25, 50, 100 and 200 kPa) were used. The
preloaded stress simulates the overburden pressure
imposed to embankment. A total of thirty six (36)test runs was performed.
To evaluate thehydrocompression settlement, the introduction ofwater to the specimen was delayed until the
preloaded stress was reached. At the desired
preloaded stress, the specimen was flooded by fillingthe consolidometer reservoir with distilled water.
Hydrocompression strain was observed and recordedfor 24 hours, after which, specimen was unloaded
and reloaded to complete the consolidation process.
Observation was being prolonged when the
deformation was still significant. The values ofvertical strain of each test samples were plotted in astrain vs. elapsed time graph. Then, the intersectionof tangent lines to the curve where flatter slope isobserved and to the curve at early stages of plot isdetermined. The amount of hydrocompression strain(εh) is then graphically measured [1].

EXPERIMENTAL PROGRAM
Preliminary investigation was done to determine
the physical properties of copper mine tailing(CMT). The main experimental program consistedof determination of consolidation properties andhydrocompression
settlementof
CMT.
Reconstituted specimen, 50 mm in diameter and 17
mm in height was prepared by moist tamping
method to achieve the desired density. An amountof the dry CMT sample that provided the desireddensity for the specimen was mixed with the small
amount of water to produce water content closed to
optimum water content. The sample was then stored
overnight before being tamped into theconsolidometer mold to obtain the desired density.
The Copper Mine Tailing
The waste material used in this study is coppermine tailing (CMT) obtained from Barrio Maglinao,
Municipality of Basay, Negros Oriental, Central
Visayas in the Philippines. Mine tailing is produced
after separating the important ore, which is copper,in open pit mining where blasting and crushing are
performed. The copper tailings obtained fromtailing dam were somewhat dry. Through visualinspection, dry CMT is grayish brown in color andresemble that of fine sand; when moist, CMT has
44

GEOMATE - Mie, Japan, Nov. 21-24, 2017

recompression index, Cr, is used to classify thecompressibility of soils which are over-consolidated.
The stress at σp’ delineates the region of semielastic behavior corresponding to over-consolidated
states from the region of primarily plastic behavior
which is associated with normal consolidation.
Hence, if overburden stresses are below σp’, the soil
is considered as over-consolidated and theirrecoverable deformation is considered to be
negligible. If the overburden pressure is quite near of
σp’, it is classified as normally consolidated and thestrain-deformation in this region is somehow
tolerable, while far beyond σp’, the irrecoverable
deformation is expected to be more significant.
The compression ratio and recompression ratio werealso computed to classify the compressibility of
CMT. Copper mine tailing is classified asmoderately compressible when it is normallyconsolidated and very slightly compressible when
over-consolidated.

RESULTS AND DISCUSSION
Physical Properties
The values of soil constants of CMT determinedfrom the tests are presented in Table 1. The value of
specific gravity showed that CMT has heavier grains
as compared to conventional soil. This is because thesample is waste material and found to contain sometraces of chemical elements like copper and titanium
which are not usually found in conventional soil.
Copper mine tailing from this study is considered tohave low plasticity based on qualitative manner ofplasticity index [10].
Table 1 Soil Constants of CMT [4]Soil ConstantsSpecific Gravity, Gs
Liquid Limit, LL (%)
Plasticity Index, PI (%)
Minimum dry density, ρdmin(kg/m3)
Maximum dry density, ρdmax(kg/m3)
Maximum void ratio, emax
Minimum void ratio, emin
D10 (mm)
D50 (mm)
Maximum dry unit weight(kN/m3)
Optimum moisture content,
wopt (%)

2.82
32
6

Table 2 Consolidation parameters of CMT

1,155.42
1,436.15
1.441
0.964
0.003
0.15
15.70

Compression Index, Cc

0.3416

Recompression Index, Cr

0.0263

Preconsolidation Pressure, σp’ (kPa)58.3

To predict the time rate of settlement, theconsolidation characteristics as described bycoefficient of consolidation (Cv) was evaluated. It isapparent from test results that values of Cv depend
on whether the preconsolidation pressure ( σp’) has
been exceeded or not. Values of Cv for each verticalstresses are summarized in Table 3. The typicaltrend exhibited by the sample is that Cv values arehigher in the early stages of over consolidated range
specifically at stress near the preconsolidationpressure (σp’) and showed a relatively rapid decrease
for stresses beyond σp’. Lower values of Cv areobserved at vertical stresses that exceed σp’.

19.47

Consolidation Properties
The relationship between vertical effective stressand vertical strain as expressed by the change invoid ratio for the copper mine tailing samples was
obtained to determine the consolidation behavior
and to measure the eventual magnitude of settlementthat sample will experience when they are subjected
to one-dimensional compression. Soil exhibiting
excessive settlement is not suitable as fill orembankment material because this can be
detrimental to the integrity of the supported structure.
Consolidation parameters which indicate thecompressibility and the amount of settlement that
copper mine tailing will experience are presented inTable 2. The preconsolidation stress (σp’) of finegrained materials is related to its stress history andsignificantly affects settlement calculations. The
compression index, Cc, and recompression index, Cr,
are index values required for primary consolidation
settlement predictions. The compression index, Cc isused to classify the compressibility of soils which
are normally consolidated. Likewise, theTable 3 Values of Coefficient of consolidation, Cv
Vertical Effective
Stress, σ (KPa)
5
12.5
25
50
100
150
200

45

Cv (cm2/sec) x 10-3
Copper Mine Tailings (CMT)
3.9465
7.867112.4034
15.7816
11.21296.77775.7404

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Hydrocompression Settlement
Copper mine tailings like soil have uniquegeotechnical characteristics including its behavior
when saturated. Consolidation tests were performedon reconstituted specimens to determine thecollapsibility of copper mine tailings due to intrusionof water or termed as hydrocompression settlement.
This study presents the influence of relative density
in terms of void ratio, moisture content andpreloaded vertical stress on the hydrocompression
settlement behavior of CMT. The influence ofinitial moisture content, wi (dry phase: wi < wopt;
optimum phase: wi ≈ wopt; and wet phase: wi > wopt),
and the degree of denseness in terms of relative
density, Dr (medium dense, Dr ≈ 60%; dense, Dr ≈80%; and very dense, Dr ≈ 100%) together with thepreloaded vertical stress (Low = 25 kPa, 50 kPa; andHigh = 100 kPa, 200 kPa) to vertical strain uponsaturation were investigated by using varying
amount of these factors in the experimentation. The
collapsibility behavior of CMT was evaluatedaccording to the amount of hydrocompression strain
attained during inundation.
Figure 1 shows theinfluence of these factors to hydrocompression strain.

c.) Wet Phase
Fig. 1 Effect of preloaded vertical pressure andrelative density to hydrocompression strain
when moisture content is at dry phase,
optimum phase and wet phase
Effect of Preloaded Vertical Stress Prior toInundation
The typical soil response when subjected tostresses lower than the preconsolidation pressure is
to exhibit minimal deformation. Preloading thesample with lower stresses before inundation
resulted to minimal deformation. However, after
the preloading stage and when the sample wasinundated with water, it resulted to greater verticalcompressive strain.
Rearrangement of particles
was easily achieved with pressures lower than σp’.
When the sample experienced sudden flow of water,
the dry particles became very responsive due to its
plasticity. The inter-assemblage pore spaces allow
water to pass through easily that softens the bonds
between particles, thus resulted to verticalcompressive strain. The water serves as lubricant
for the particles to easily rearrange into a denser
configurationas
manifested
bygreaterhydrocompression strain. When the sample waspreloaded with vertical stresses beyond thepreconsolidation pressure, the hydrocompression
strain decreased even for samples with Dr near 60%.
The sample has already achieved its denser andstable condition before the intrusion of water. Whenthe sample was inundated with water, thecollapsibility potential was reduced and thehydrocompression strain became negligible.

a.) Dry Phase

Effect of Initial Relative Density
The arrangement of the soil skeleton influenced
the deformation of CMT due to sudden intrusion ofwater. During inundation, specimens with greater
void ratio (Dr near 60%, medium dense condition)
caused the water to easily penetrate the void spaces
and increased the collapse potential. At lower
relative density, the hydrocompression strain is moresignificant. As the void ratio decreases (Dr nearb.) Optimum Phase46

GEOMATE - Mie, Japan, Nov. 21-24, 2017

100%, very dense condition), the rate of flow ofwater into the sample also decreases, thus causing
minimal disturbance on the particles and thehydrocompression strain became almost negligible.

wi = initial moisture content (e.g. wi = 0.10 for 10%
moisture content)
 = vertical stress before inundation in KPa
To verify the predictive capability of the
proposed model, the hydrocompression strain (εh)
calculated using the proposed model was comparedwith the measured values from experimentation.
Statistical analysis using T-test for paired samples
was performed to determine if there is a significant
difference between the measured values and thepredicted values. The null hypothesis for the T-teststates that there is no significant difference between
the measured and predicted hydrocompression
strain. The results for 36 number of observations
with a level of significance equals to 0.05 ( = 0.05)
showed a tstat value (1.211) is less than tcritical (1.689)
and the p-value is greater than 0.05. This means thatthe null hypothesis should be accepted. It can bestated at 95% confidence level that that there is no
significant difference between the measured εh andthe predicted εh.
The strength of association
between measured εh and the predicted εh was
verified using the Pearson’s correlation coefficientand the data are presented in a scatter plot as shownin Fig. 2. The scatter of data points is nearer to astraight line which means that there is a linear
positive correlation between the measured andpredicted εh. The statistical analysis yielded aPearson correlation value of 0.82 indicating a verystrong association between the two variables(measured and predicted εh). It can be concluded thatthe proposed model (Eq. 1) can be used to predict
the amount of hydrocompression strain as a functionof initial void ratio, initial moisture content and thevertical stress prior to inundation.

Effect of Initial Moisture Content
When specimen was prepared with initialmoisture content slightly more than its optimum
value (wet phase), the collapse potential of thespecimen was reduced to negligible value even when
the predetermined vertical stresses were below thepreconsolidation pressure and at medium dense
condition. The hydrocompression strains at wetphase were less than the hydrocompression strains at
optimum and dry phase. The presence of water inthe void spaces reduces the sudden intrusion ofwater. Moreover, the pore water pressure aided insupporting the applied vertical load, thus the stresscarried by the soil skeleton was reduced.
From
test
results,theamountofhydrocompression strain experienced by CMT isaffected by the applied vertical stress prior toinundation, initial relative density and initialmoisture content. To reduce the magnitude ofhydrocompression strain to a negligible value, CMT
when used as embankment materials should be
prepared with initial moisture content slightly morethan its optimum value. If the initial moisture
content is less than or equal to its optimum value,
CMT should be in its very dense condition and it
should be preloaded with vertical stress more thanits
preconsolidationpressuretomakehydrocompression strain negligible. The determinedhydrocompression strains in every condition is lessthan 5% which means that CMT has a degree ofcollapsibility classified as low to negligible despiteofhavingplasticity.
Theamountofhydrocompression strain obtained is higher than thevalues obtained for non-plastic mine tailings [1] andwithin the range of values for mine spoils with low
plasticity [12].
Formulation of Empirical Model to Predict
Hydrocompression Strain
Using the response surface method (RSM), therelationship of the hydrocompression strain withinitial void ratio, eo, initial water content, wi, and thepreloaded vertical stress, σ¸ was formulated. The
hydrocompression strain, εh can be expressed by theequation:.
.

.

Fig. 2 Correlation of Measured εh with Predicted εh.

CONCLUSIONS

(1)

The
consolidation
behaviorandhydrocompression settlement of copper mine tailingwere investigated to determine its suitability as

where:
eo = initial void ratio

47

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Tailings”, Philippine Engineering Journal, 2013,
Vol. 34, No. 1, ISSN: 0117-5564.
[2] Germanov T, “Geotechnical Properties ofIndustrial Waste Deposits in Bulgaria”,
Proceedings of 13th European Conference on
Soil Mechanics and Geotechnical Engineering,
Prague, 2003, 1: 95-100.
[3] Qiu Y and Sego DC, “Laboratory Properties ofMine Tailings”, Canadian Geotechnical Journal,
2001, 38: 183-190.
[4] Uy ES and Adajar MQ, “Assessment of
Critical-State Shear Strength Properties of
Copper Tailings, International Journal of
GEOMATE, April, 2017, Vol. 12, Issue 32,
ISSN: 2186-2990, Japan, pp. 12-18.
[5] Hanson JL, Yesiller N, Von Stockhausen SA
and Wong WW, “Compaction Characteristics ofMunicipal Waste”, Journal of Geotechnical andGeoenvironmental Engineering, 2010, pp. 10951102.
[6] Robinson R. and Allam M., “Effect of Clay
Mineralogy on Coefficient of Consolidation.
Clays and Clay Minerals”, 1998, Vol. 46, No. 5,
pp. 596-600.
[7] Langroudi A and Jefferson I, “Collapsibility in
Calcareous Clayey Loess: A Factor of StressHydraulic History”, Int. J. of GEOMATE, 2013,
Vol. 5, No. 1 (Sl. No. 9), ISSN: 2186-2982(P),Japan, pp. 620-627.
[8] Zarco M, “Modified Strain Energy Method for
Determining
Preconsolidation
Pressures”,
Proceedings: 32nd Phil. Institute of Civil
Engineers National Convention, Iloilo City,
2006.
[9] Buddhu M, Soil Mechanics and Foundations,
2nd ed., John Wiley and Sons, Inc. USA, 2007,
pp 196-197.
[10] Das B and Sobhan K, Principles ofGeotechnical Engineering, 8th ed., Cengage
Learning, USA, 2014, pp. 102.
[11] Prahallada M and Shanthappa B, “Use of
Copper Ore Tailings - As an Excellent
Pozzolana in the Preparation of Concrete”,
International Journal of Advanced Research in
Engineering and Applied Sciences, 2014, 3(3),pp. 1-10.
[12] Kalinski ME, Karem WA, and Little LM,“Estimating Hydro-compression Potential of
Mine Spoils from a Site in Eastern Kentucky
using Dry Unit Weight and Moisture Content”,
International Journal of Mining, Reclamationand Environment, 2010, 24:4, pp. 350 – 362.

embankment material. Based from laboratory test
results, the following conclusions were drawn:
Copper mine tailing is considered to have low
plasticity with heavier grains as compared toconventional soil. Based on values of consolidation
parameters CMT is classified as moderately
compressible when it is normally consolidated andvery slightly compressible when over-consolidated.
Coefficient of consolidation (Cv) values arehigher in the early stages of overconsolidated range
specifically at stress near the preconsolidationpressure (σp’) and showed a relatively rapid decrease
for stresses beyond σp’.
The hydrocompression settlement of CMT
increases with increasing pressure until the
preconsolidation pressure is reached, and thendecreases with pressure beyond the preconsolidationpressure. Samples with lower density and watercontent less than its optimum value exhibit greaterhydrocompression settlement.
The determinedhydrocompression strains in every condition is lessthan 5% which means that CMT has a degree ofcollapsibility classified as low to negligible in spiteof having plasticity.
To reduce the magnitude of hydrocompression
strain to a negligible value, CMT when used asembankment materials should be prepared withinitial moisture content slightly more than its
optimum value. For cases where the initial moisture
content is less than or equal to its optimum value,
CMT should be in its very dense condition and it
should be preloaded with vertical stress more thanits
preconsolidationpressuretomakehydrocompression strain negligible.
Having good compaction behavior, reasonably
stable when dense, with low compressibility and low
collapsibility are indications that copper mine tailing
despite of having plasticity has consolidation andhydrocompression characteristics suitable asembankment material.
ACKNOWLEDGEMENT
This research study was undertaken through the
DLSU-University Research Coordination Officeunder the new PhD research program.
REFERENCES[1] Adajar MQ and Zarco MH, “Estimating
Hydrocompression
Settlement
of
Mine

48

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

SOIL-STRUCTURE INTERFACE BEHAVIOR OF CEMENTED-PASTEBACKFILL MATERIAL MIXED WITH MINING WASTE
Mary Ann Q. Adajar1 and Wincent Nicole K. Pabilona2
1
Faculty, De La Salle University, Manila, Philippines
2
Graduate student, De La Salle University, Manila, Philippines
ABSTRACTThe use of mining wastes as component of cemented paste backfill provides an environmentally acceptable
method of waste disposal at lesser cost as the method does not require tailing dams for storing the large volume
of wastes. This study determines the applicability of cemented-paste backfill materials mixed with aggregate
quarry wastes as ground support to concrete structures. Aggregate quarry waste with varying fine contents wasused as substitute for sand in cemented-paste backfill and the mixture was referred to as cemented-paste tailingbackfill (CPTB). Its micro fabric structure was determined though SEM-EDX tests. Test results showed that
CPTB with 20% and 40% fine contents has acceptable values of strength properties in terms of its unconfinedcompressive strength and interface friction angle. The unconfined compressive strength in relation to its curing
period is in the range of 120 kPa to 150 kPa which can be described as having stiff consistency. The stress-straininterface behavior between CPTB and concrete structure was evaluated through direct shear test using strain
rates that simulate the rapid and slow rates of loading. In both conditions, the stress-strain behavior exhibits
strain softening. The average interface friction angle is 38o which can be associated to its dense condition.
Modified hyperbolic model was applied to evaluate the soil-structure interface behavior of CPTB. Hyperbolic
parameters were formulated to predict the interface shear stress – shear strain behavior of the CPTB when incontact with concretes structure at any value of shear strain and normal effective stress.
Keywords: Cemented-paste Backfill, Unconfined Compressive Strength, Interface Friction Angle, Modified
Hyperbolic Modelmass, is one of the major activities of open-pit minerehabilitation to bring back the mined area into
beneficial use. The use of mining wastes specificallywastes from aggregate quarry, as component of
cemented paste backfill provides an environmentally
acceptable method of waste disposal andrehabilitation process at lesser cost. Waste fromaggregate quarry is proven to be stable when used asembankment material [3]. It is also a feasible
component in concrete mix as substitute for fineaggregates [4]. However, its strength properties
when used as component of cemented-paste backfill
have yet to be determined. Its interface behavior
when in contact with concrete structure has to beevaluated.
Understanding the soil-structure interface
behavior is an important tool for use in analyzing,
designing, and monitoring geotechnical structures.
Several constitutive modeling have been used toobtain accurate solution to many soil-structureinteraction problems. The hyperbolic interface
model developed by Clough and Duncan [5]presented a systematic approach to model the
behavior of the retaining wall-to-soil interfaces in
the primary loading stage. An extended hyperbolicmodel for interfaces was developed that can capture
important aspects of interface response under the

INTRODUCTION
Cemented paste backfill is a cementitious
composite normally made of coarse and fineaggregates mixed with hydraulic binder which istypically Portland cement. It is a means of groundstabilization and for strengthening and solidificationof underground foundation of a building which isdone at early parts of construction activities. It also
provides stable platform and ground support to thestructure sitting on it.
In mining industry, theextraction of valuable ore creates very large voids
which need to be backfilled. The backfill material
makes use of waste rocks or tailings mixed with abinder, usually cement, to form a cemented-paste
backfill. The use of cemented paste backfill is anincreasingly important component of undergroundmining operations and is becoming a standardpractice for use in many cut-and-fill mines aroundthe world [1]. This is an effective means of tailingdisposal because it negates the need for constructing
large tailing dams at the surface [2].
In the Philippines, sustainable solution to
manage wastes being produced by mining industries
is essential. Moreover, an effective open-pit minerehabilitation method is strongly required.
Backfilling, which requires large volume of soil
49

GEOMATE - Mie, Japan, Nov. 21-24, 2017

type of loading expected to occur in a wall-backfill
interface at different stages of construction andoperation of a lock wall [6]. In this study, themodified hyperbolic model which was formulated tocharacterize the stress-strain and volume-change
behavior of tailings determined from direct shear
tests [3] was applied to evaluate the soil-structureinterface behavior of cemented-paste tailing backfill.
This study determines the applicability of
cemented-paste backfill materials mixed withaggregate quarry wastes as ground support toconcrete structures like footings or retaining walls.
The mixture is called cemented-paste tailing backfill(CPTB). Strength properties such as unconfinedcompressive strength at various curing time andinterface friction angle were determined. Hyperbolic
parameters were formulated to predict the interface
shear stress – shear strain behavior of the CPTB
when in contact with concretes structure.

maximum unconfined compressive strength wasused for the direct shear test. The experimental setup simulates a concrete structure resting on CPTB
material. The lower part of the shear box contains
the CPTB mixture while the upper part of the shear
box contains the concrete mortar mix to represent arigid concrete structure. The schematic ofexperimental set-up is shown in Fig. 1. Samples
were subjected to normal stresses of 13.625 kPa,
20.4375 kPa, and 27.25 kPa. Direct shear test wasdone using the fast strain rate of 1.25mm/min. tosimulate the rapid loading condition and slow strain
rate of 0.12mm/min to simulate the long termloading condition. From the plot of shear stress vs.
shear strain behavior obtained from direct shear test,
hyperbolic parameters using the modified hyperbolicmodel technique were determined to predict the soilstructure interface behavior of CPTB at any value ofshear strain and normal effective stress.

MATERIALS AND TEST METHODS

Table 1 Typical mix proportion of CPTB for eachcylindrical sample for UCS test

The material composition of cemented-paste
tailing backfill (CPTB) is waste from aggregate
quarry (WAQ) as sand substitute with Portland
cement as hydraulic binder. WAQ was collectedfrom quarry site in Ternate, Cavite. These quarry
wastes are residues of mountain rocks which went
through crushing processes to produce fineaggregates. The residues, considered as solid wastes,
are produced during the washing of crushed rocks inthe siltation pond through the natural process of
sedimentation. WAQ has specific gravity of 2.57
and classified as fine-grained soil with no plasticity[4].
The aggregate quarry wastes in the CPTB
mixture had varying fine contents ranging from 20%,
40% and 60% by weight. This is done to investigate
the effect of fineness of grains on the strength
properties of CPTB. The fine content for thisexperimentation is defined as percent grain particles
passing the #200 sieves. Cement consists of 5.5
percent by dry mass of WAQ which is equivalent to
3.8 weight percentage of the entire mixture. The
water-cement ratio of 7:1 was used in the mixture.
Table 1 shows a typical mix proportion of CPTB.
To determine the strength properties of CPTB,
unconfined compression strength (UCS) test inaccordance with ASTM D2166 was performed. The
cylindrical sample has 63.5 mm diameter with 158.8mm height. The samples were tested after the 7th,
14th, 28th and 42nd day curing period to determine theeffect of curing time on its strength development.
The 42nd day curing time was intended to observe
the long-term strength of CPTB.
Direct shear test in accordance to ASTM D3080
was performed to determine the interface friction
angle and to describe the soil-structure interface
behavior of CPTB. The mixture that produced the

% of
Fine
Contents
of WAQ

Cement
(g)

Water
(g)

WAQ (g)Passing#4 sieve,
Passingretained#200
on #200
Sieve
Sieve

20%

15.9

111.5

58.3

233.4

40%

15.9

111.5

116.7

175.0

60%

15.9

111.5

175.0

116.7

Normal stress, σ’τConcrete
CPTB

Shear stress, τFig. 1 Schematic of experimental set-up for direct
shear test
RESULTS AND DISCUSSION
Unconfined Compressive Strength, quFigure 2 shows the unconfined compressive
strength development of CPTB with varying finecontents; the average values are tabulated in Table 2.
For CPTB with 20% and 40% fines, the samples
exhibited greater qu at early curing days; however,there is an appreciable decrease in strength beyond
the 7th day curing period followed by an almost
50

GEOMATE - Mie, Japan, Nov. 21-24, 2017

constant value of qu as curing age increases. The
observed higher value of qu at 7th day curing can be
explained from the SEM results as shown in Figs. 3
and 4. The microstructure of samples at 7th day
curing time showed a more flocculated state withminimum void spaces. This results to a decrease in
the total pore volume and a concurrent increase instrength. At 42nd curing day, the micrograph showeda honeycomb structure with intra-assemblage voids
depicting an increase in porosity and thus leads tolower compressive strength. The final amount ofporosity after the hydration of Portland cement paste
depends strongly on the initial water-cement ratio of
the paste [7]. The almost constant value of quranging from 120 KPa to 140 KPa for CPTB with
20% fines and 140 KPa to 150 KPa for CPTB with
40% fines can be considered as the suitable value ofcompressive strength of CPTB that depicts its longterm behavior. The compressive strength iscomparable to clay with stiff consistency. The modeof failure exhibited by the samples is diagonal shear
as seen in Figures 5a and 5b. Meanwhile, CPTB
with 60% fines showed an unpredictable trend in its
strength development with respect to curing period.
The bonding between Portland cement and WAQ
did not work well when the mixture contains morefines. This is further attested from its mode of failureclassified as failure by axial splitting (Fig. 5c). It is
expected that samples which failed by axial splitting
give a lower value of qu than those that failed bydiagonal shear [8].

a.) at 7th day curingb.) at 42nd day curing

Fig. 3 Micrographs of CPTB with 20% finesa.) at 7th day curingb.) at 42nd day curing

Fig. 4 Micrographs of CPTB with 40% finesa.) 20% finesb.) 40% finesc.) 60% fines

Fig. 5 Modes of failure of CPTB subjected tocompressive test a.) and b.) diagonal shear
failure c.) axial split
Fig. 2 Unconfined compressive strength of CPTB

Stress-strain Interface Behavior

Table 2 Average unconfined compressive strength of
CPTB

The stress-strain interface behavior between
CPTB and concrete structure was evaluated throughdirect shear test using strain rates that simulate therapid and slow rates of loading. Specimens with
20% and 40% fines were subjected to shear force
and normal stress after the 28th day curing period
following the experimental set-up described in Fig. 1.
CPTB with 60% fines was no longer included in theexperimentation since the compressive strength test
did not show acceptable results. The typical stressstrain graphs are shown in Figs. 6 to 9. In bothconditions, the stress-strain behavior of CPTB

Curing
Days
7
14
28
42

CPTB
with 20%Fine
229.81200.44121.02139.07

CPTB
with 40%Fine
299.26148.03149.74150.48CPTB
with 60%
Fine
88.32
222.15189.3856.40

51

GEOMATE - Mie, Japan, Nov. 21-24, 2017exhibits strain softening. The specimen showed a
rapid increase in shear stress reaching a peak value
at low shear strains and then decreases withincreasing shear strains indicating strain softening
until the shear stress at failure is attained. This
indicates that specimen failed in brittle manner. The
shear stress at failure is described as the shear stressat which continued shearing occurs without change
in shear stress for a given normal stress.
The stress-strain curve defines the typicalresponse of dense sample. In this experimentation,
the CPTB after 28th days of curing time iscomparable to compacted, dense soil. CPTB with
20% and 40% fines, whether subjected to slow or
fast strain rates, achieved an almost the same shear
stress at failure. The shear stress at failure is greaterfor specimens subjected to greater normal stress (σ’).

Normal stress, σ’

Fig. 8 Shear stress vs. shear strain of CPTB with
40% fines using fast strain rate

Normal stress, σ’

Normal stress, σFig. 9 Shear stress vs. shear strain of CPTB with
40% fines using slow strain rate

Fig. 6 Shear stress vs. shear strain of CPTB with
20% fines using fast strain rate

The shear stress at failure (τf) is plotted against
the normal stress (σ’) on a graph of τ against σ’.
The best fit line joining the τ and σ’ can be describedby equation τ=σ'tanϕ. This line represents thefailure envelope with slope tan ϕ. The angle ϕ isreferred to as the interface friction angle and istabulated in Table 3. This friction angle describes
the frictional resistance of CPTB when in contact
with concrete structure.

Normal stress, σ

Table 3 Interface Friction Angle of CPTB
CPTB with
20% Fines Fast Strain Rate
20% Fines Slow Strain Rate
40% Fines Fast Strain Rate
40% Fines Slow Strain Rate

Fig. 7 Shear stress vs. shear strain of CPTB with
20% fines using slow strain rate

52

Interface Friction Angle, (deg.)
38.8
38.5
37.6
38.7

GEOMATE - Mie, Japan, Nov. 21-24, 2017

limitation of the model is that it cannot capture thepeak shear stress [3], but it can provide a goodprediction of shear stress at failure.

Hyperbolic Parameters
Shear stress vs. shear strain behavior of CPTB as
presented in Figs. 6 to 9 was used to determine thehyperbolic parameters using the modified hyperbolicmodel. The modified hyperbolic model uses theshear stress against shear strain and volumetric strain
against shear strain relations to describe thehyperbolic stress-strain behavior from the direct
shear test. The hyperbolic relation between thechanges in stress and strains is defined in terms of an
initial shear modulus, Gi and the shear strength at
failure, τf . The modified hyperbolic model concepts
and procedure for the determination of hyperbolic
parameters are discussed in the study of Adajar andZarco [3]. Using the modified hyperbolic model, theparameters K (shear modulus number) and n (shear
modulus exponent) describing initial shear modulus(Gi), based on hyperbolic fit to the stress-strain
curve are obtained.
The failure ratio Rf that
relates the asymptotic shear stress with shear stressat failure is also determined. Rf is defined as theratio of τf (Eq. 1) and the shear stress at failure. The
variation of ϕ’ with respect to σ’ is described interms of hyperbolic parameters ϕo and Δϕ. The
summary of hyperbolic parameters is presented inTable 4. Applying these hyperbolic parameters inequations (1) to (3) allows the prediction of theinterface shear stress – shear strain behavior of the
CPTB when in contact with concretes structure atany value of shear strain and normal effective stress.

 f   ' tan  'Hyperbolic
Parameter
K
n
Rf
∅
∆∅

Description
Shear modulus
numberShear modulus
exponent
Failure ratio
Friction angle
parameter
Friction angle
parameter

Value
170.990.98090.997131.021°
5.126°

(1)

 '

 Pa 

 '  o   log Table 4 Hyperbolic parameters of CPTB

Fig. 10 Comparison of stress-strain curve using
modified hyperbolic model and from test
data of CPTB with 40% Fines and normal
stress of 27.25 KPa

(2)


 
 Rf   f  ' K  Pa   Pa 
1n(3)

Where:
τ = shear stress, KPa
γ = shear strainσ’ = normal effective stress, KPa
Pa = atmospheric pressure = 101.325 KPa
Using the determined hyperbolic parameters, themodel’s response to the test data was compared withexperimental data. The comparison of the test data
and the calculated hyperbolic response are shown in
Figs. 10 to 12. The modified hyperbolic model
provides a good approximation of the interface shear
stress – shear strain behavior of the CPTB. The

Fig. 11 Comparison of stress-strain curve using
modified hyperbolic model and from test
data of CPTB with 40% Fines and normal
stress of 20.438 KPa
53

GEOMATE - Mie, Japan, Nov. 21-24, 2017

design criteria are not requiring a high compressive
strength value.
RECOMMENDATION
It is recommended that paste mixture with lower
water-cement ratio and using binder other thanPortland cement be considered in future test design
to verify if the unconfined compressive strength canbe improved.
REFERENCES[1] Landriault DA, Verburg R, Cincilla W, andWelch D, “Paste technology for undergroundbackfill and surface tailings disposal
applications”, Short course notes, Canadian
Institute of Mining and Metallurgy, Technicalworkshop – April 27, 1997, Vancouver, British
Columbia, Canada, p. 120.
[2] Sivakugan N, Rankine RM, Rankine KJ, andRankine KS, “Geotechnical Considerations in
Mine Backfilling in Australia”, Journal of
Cleaner Production, Elsevier, Vol. 14, 2006, pp.
1168 – 1175.
[3] Adajar MQ and Zarco MH, “Predicting thestress-strain behavior of mine tailing using
modified hyperbolic model”, Int.
J. of
GEOMATE, Vol. 10, Issue 21, Japan, May
2016, pp. 1834-1841.
[4] Adajar MQ, De Guzman E, Ho R, Palma C, andSindico D, “Utilization of Aggregate Quarry
Waste in Construction Industry”, Int. J. of
GEOMATE, Vol. 12, Issue 31, Japan, March
2017, pp. 16-22.
[5] Clough GW and Duncan JM, “Finite Element
Analyses of Retaining Wall”, Journal of the Soil
Mechanics
andFoundations
Division,
Proceedings of the American Society of Civil
Engineers, Dec. 1971, 97(SM12): 1657-1673.
[6] Gomez JE, Filz GM and Ebeling RM,“Development of an Improved Numerical
Model for Concrete-to-Soil Interfaces in SoilStructure Interaction Analyses”, US ArmyEngineer Research and Development Center,
Technical Report ITL-99-1, August 2000.
[7] Thomas J. and Jennings H., “The Science ofConcrete: Hydration and Microstructure of
Cement Paste”, Retrieved date: June 17 2016.
http://iti.northwestern.edu/cement/index.html[8] Liu C and Evett J, “An Investigation of the
Uniaxial Compressive Strength of a Cemented
Hydraulic Backfill Made of Alluvial Sand”,
Minerals 2017, Vol. 7, Issue 4, pp. 1-13.

Fig. 12 Comparison of stress-strain curve using
modified hyperbolic model and from test
data of CPTB with 40% Fines and normal
stress of 13.625 KPa
CONCLUSION
Strength properties of cemented-paste tailingbackfill with waste from aggregate quarry as sandsubstitute were determined through unconfinedcompressive strength test and direct shear test. Its
soil-structure interface behavior was evaluated. The
following are the conclusions drawn from test
results:
Cemented-paste tailing backfill with finecontents up to 40% showed acceptable values of
unconfined compressive strength and interface
friction angle suitable as ground support tostructures. The unconfined compressive strength
depicting its long-term behavior is in the range of
120 kPa to 150 kPa comparable to clay with stiff
consistency. The mode of failure exhibited by the
samples is diagonal shear. Its microstructure showed
an increase in porosity as curing age increases. Thiscan be due to the initial water-cement ratio of thepaste mixture.
The stress-strain interface behavior between
CPTB and concrete structure exhibits strainsoftening. The average interface friction angle is 38owhich can be associated to its dense condition.
Modified hyperbolic model was applied andhyperbolic parameters were formulated to predict
the interface shear stress – shear strain behavior of
the CPTB when in contact with concretes structure
at any value of shear strain and normal effective
stress. The modified hyperbolic model provides agood approximation of the interface shear stress –shear strain behavior of the CPTB. The modelcannot capture the peak shear stress, but it provides
a good prediction of shear stress at failure.
The CPTB used in this study can be a goodalternative to the conventional cemented-paste
backfill when used as a free-standing fill if the54Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A NEW TESTING APPARATUS TO EXCAVATE RECTANGULARSECTION FOR UNDERPASS TUNNEL CONSTRUCTION
Yota Togashi 1, Takashi Nakayama 2, Sohei Itaya 2, Takatoshi Hondo 3 and Noriyuki Okano 2
1
Disaster Prevention Technology Division, Railway Technical Research Institute, Japan
2
Structures Technology Division, Railway Technical Research Institute, Japan3
Railway Dynamics Division, Railway Technical Research Institute, Japan

ABSTRACTFor understanding a mechanical behavior of soils during tunnel excavation, various experiments have been
conducted, e.g. trap door test. However, the influence of rectangular shape excavation was not sufficiently
investigated by previous studies. In this study, in order to evaluate ground relaxation during underpass tunnel
construction by non-open cut method, which include rectangular shape excavation for temporally construction ofsquare pipes to prevent ground relaxation, a new testing apparatus to excavate rectangular section is developed.
The testing apparatus is configurated by metal lining scaled down by approximately 1 / 5, drilling and its
operating devices, and it can be movable corresponding to rectangular tunnel face by three-degree of freedom.
For investigate the deformation properties of soils during excavation, jacking and excavation test is conducted bya small sand box using Toyoura soil compacted with water content ratio w = 10%. The results demonstrated thatthe excavation can be stably conducted using the cutter rotated by a motor and the tunnel face observation can bealso stably conducted by a miniature camera. Furthermore, for soil removal amount, the difference between planand measured values finally become less than 2 %.
Keywords: Underpass, Tunnel, Rectangular shape, Excavating test, Surface displacementwith piles were studied by centrifuge model testing
using the equipment of decreasing tunnel diameter[5]. These studies were mainly conducted for tunnel
construction with circular section combining withsome numerical analysis, [e.g. 6, 7]. Furthermore,
although there were some studies focused onmodeling excavation process [8, 9], the influences of
excavating square section were not well studied yet.
In recent years, underpass tunnel, which intersectroad or railroad, is increasingly constructed by non-

INTRODUCTION
For understanding a mechanical behavior of soils
during tunnel excavation, various experiments weredeveloped [1]. For example an earth pressure during
tunnel excavation has been investigated by trap door
tests using aluminum bars [2, 3], soil relaxation
between tunnel face to ground surface were
investigated by pull-out test of duplex tube in soilbox [4] and an interaction of tunnel constructionab

HandleLinear guideMetal lining

Knuckle
Motor
joint

CL

200mm
Knucklejoint

Fig. 1

Rod

Wire
1500mmWire guide
Cutterbit

A new testing apparatus of excavating rectangular section: (a) appearance, (b) cross section
55

GEOMATE - Mie, Japan, Nov. 21-24, 2017

open cut method mainly using jacking method [e.g.
10, 11] and it is strongly important to investigate
mechanical behavior of soils during rectangularshape excavation for temporally construction ofsquare pipes to prevent ground relaxation. Although
Takahashi et al. [12] conducted FE analysis withmodeling of excavating rectangular section inaccordance with tunneling process, there were few
experimental studies to investigate a mechanicalbehavior of soils due to rectangular excavation.
In this study, to evaluate mechanical behaviors ofsoils during underpass tunnel construction, wedeveloped a new laboratory testing apparatus toexcavate rectangular section. The structure of theequipment and excavating test using acryl soil box
for modeling underpass tunnel construction isreported as following chapter.

a

HandleCutterbit

Metal liningb
HandleCutterbit

STRUCTURE OF TESTING APPARATUS
Metal lining

Fig. 1 shows a new testing apparatus of
excavating rectangular section. The apparatus isconfigurated by metal lining scaled down by
approximately 1 / 5, drilling and its operating
devices as shown in Fig. 1 (b). The cutter can be
movable corresponding to rectangular tunnel face by
three-degree of freedom, which can be operated byhandle via wire connected by knuckle joints tocontrol roll, pitch, and yaw angles separately as
shown in Fig. 2. The allowable length of excavationis 20 cm and the maximum inclination angle ofcutter is 30 ° as shown in Fig. 3.
By using this apparatus, tunnel excavation withrectangular section is simulated by a laboratory test.
In next chapter, excavating and jacking test using
soil box is shown.

Handlec
Cutterbit

Metal lining

Fig. 2EXCAVATING AND JACKING TEST

Movement of cutter due to handle
operation: (a) movement to tunnel axis,(b) rotation around tunnel axis, (c)inclination from tunnel axis.
CutterKnuckle
Motor
bit
joint

Test condition
30°
CL

200mm

For underpass tunnel construction using nonopen cut method, steel pipes are propelled by ahydraulic jack after excavating soils. To model thecondition of construction, we conducted excavatingand jacking test as shown in Fig. 4. The excavating
apparatus was fixed on the pedestal, and the soil box
was movable to lateral orientation. The soil box ispartially opened in the lateral side by 20cm square,
and it can be installed the excavating apparatus. The
opening is covered before excavation to prevent a
collapse of tunnel face and drying soil.
For the testing procedure, the box is first moved
to the excavating apparatus and the tunnel face is
opened. Soil box is excavated by 20mm and metallining is installed by lateral movement of acryl soilbox by 20mm. The ground surface condition isvisually observed and the vertical displacement of

250mm

Fig. 3200mm

Structure of the apparatus near tunnel
face.

the center of the surface is measured by laser
displacement meter on each process. Excavated soils
were removed by a vacuum cleaner in each test step,and the weight of soil removal was measured in eachstep. Tunnel face is also observed by a miniaturecamera in each excavation phase.
The soil layer in the box is made by Toyoura
sand, which properties are shown in Table. 1. Water
content w is adjusted by mixing dry sand with water
as shown in Fig. 5, and then the layer is compacted
56

GEOMATE - Mie, Japan, Nov. 21-24, 2017ab
Laser displacement
meter

Metal lining
200mm

Miniaturecamera200mm

Acrylsoil tank

Jacking
lengthLED light

600mm
200mm
PedestalFig. 4

Pipe tovacuumcleaner

600mm
Hand
truck

Excavating and jacking test: (a) settings of equipment, (b) over view.

Table 1 Physical properties of Toyoura sand.
Maximum dry
density

Minimum dry
densityr dmax (g / cm3)
1.65

r dmin (g / cm3)

Optimum watercontent ratio
w opt (%)

Water content ratiow (%)

Degree ofcompaction
D c (%)

1.337

14.3

10

90

by its ratio Dc = 90 % in every 50 mm to 600 mm
height as shown in Fig. 6. As the water content, w =10%, is a little smaller than optimum water content
ratio, it can be expected the stiffest condition of
Toyoura sand.
Test results

Fig. 5Mixing of sand with water.

Fig. 6Compacting sand layer in each 50 mm
height.

Fig. 7 shows the relationship between jacking
length and testing steps. In the test, the soil box was
finally moved laterally by 200 mm. Fig. 8 shows
tunnel face changes due to testing step. Tunnel face
and its changes can be clearly observed by miniaturecamera. It demonstrates that a collapse of tunnel face
and its mechanical behavior are possibly recorded by
the apparatus.
Fig. 9 shows the relationship between soil
removal amounts, surface displacements and testing
steps. As the planned removal amounts got nearlysame values as the excavation test, excavation wasappropriately conducted in accordance with the plan.
The difference between plan and actual test finallybecome less than 2% in step 10. The surface
displacement got very small values, because the soil
condition is very stiffer. Settlements were observed
until step 5, and upheaval were then observed after
the step. It can be demonstrated that, whereas
settlement is occurred in smaller jacking amount due
to ground relaxation, the steel lining was approached
to measurement points in greater jacking amount,and then positive dilatancy may occurred due tostiffer sand.
As stated above, the applicability of the testing57

GEOMATE - Mie, Japan, Nov. 21-24, 2017

apparatus was confirmed. The test using lower watercontent ratio and using bigger soil box will be
conducted and a collapse of tunnel face or relaxationof soils will also be concretely investigated in future.

Jacking length (mm)

200
150

CONCLUSION

100
Excavating0

For understanding a mechanical behavior ofsoils during tunnel excavation, various experiments
were developed. However, the influences of
excavating square section especially for underpass
tunnel construction were not well studied yet.
In this study, to evaluate mechanical behaviors
of soils during underpass tunnel construction, a newlaboratory testing apparatus to excavate rectangularsection was developed. To confirm the applicabilityof the testing apparatus, jacking and excavation test
is conducted. The results of the test using highly
compacted Toyoura sand demonstrated that, tunnel
face changes due to excavation can be clearlyobserved by miniature camera and the mechanicalbehavior of soils during rectangular excavation canbe observed by the tests. Furthermore, for soil
removal amount, the difference between plan andmeasured values finally become less than 2 %.
The test using lower water content ratio andusing bigger soil box will be conducted to evaluatemechanical properties of soils during rectangular
excavation for grasping a mechanism of underpass
tunneling.

Jacking

50

0

1

2

3

4

5

6

7

8

9 10

Testing step
Fig. 7

Relationship between jacking length andtesting steps.

Step 1

Open tunnel face.

ACKNOWLEDGEMENTS
Thanks are given to Mr. Yoshiteru Kawakami,
Japanese Railway Soken Engineering, for
conducting the test.
REFERENCES
Step 5
Fig. 8

Step 10[1] Meguid MA, Saada O, Nunes MA, Mattar J,“Physical modeling of tunnels in soft ground: A
review”, Tunnelling and Underground SpaceTechnology, Vol. 23, 2008, pp. 185–198.
[2] Adachi T, Kimura M, Kishida K, Ito H,“Mechanical behavior of a tunnel and theground around it in consideration of the tunnel
excavation process through the trapdoor
experiments”, J. JSCE, No. 694, 2001, pp. 277 –
296. (In Japanese with English abstract)[3] Kikumoto M, Kimura M, Kishida K, Adachi K,“Three dimensional trapdoor experiments andits numerical analysis on the mechanicalbehavior during tunnel excavation”, J. JSCE,
No. 750, 2003, pp. 145 – 158. (In Japanese withEnglish abstract)[4] Kirsch A, “Experimental investigation of theface stability of shallow tunnels in sand”, Acta
Geotechnica, Vol. 5, 2010, pp. 43 – 62.

Tunnel face changes by miniature camera.

Soil removal
amount (kg)

15
12
9
6

0

Surfacedisplacement (mm)

Plan
Test

3
0

1

2

3

4

5

6

7

8

9

10

0.08
0.06
0.04

Uplift

0.02
0.00
-0.02

Settlement
0

1

2

3

4

5

6

7

8

9

10

Testing step

Fig. 9Relationship between soil removal
amounts, surface displacements andtesting steps.

58

GEOMATE - Mie, Japan, Nov. 21-24, 2017

[5] Loganathan H, Poulos HG, Stewart DP,“Centrifuge model testing of tunneling –induced ground and pile deformation”,
Geotechnique, Vol. 50, No. 3, 2000, pp. 283 –294.
[6] Davis EH, Gunn MJ, Mair RJ, Seneviratne HN,“The stability of shallow tunnels andunderground openings in cohesive materials”,
Geotechnique, Vol. 30, No. 4, 1980, pp. 397 –416.
[7] Komiya K, Soga K, Akagi H, Hagiwara T,
Bolton MD. “Finite element modelling of
excavation and advancement processes of ashield tunnelling machine”, Soils andFoundations, Vol. 39, No.3, 1999, pp. 37 – 52.
[8] Shin JH, Choi YK, Kwon OY, Lee SD, “Modeltesting for pipe-reinforced tunnel heading inagrabular soil”, Tunnelling and UndergroundSpace Technology, Vol. 23, 2008, pp. 241–250.
[9] Champan DN, Ahn SK, Hunt DVL, Chan HC,“The use of model tests to investigate theground displacement associated with multiple
tunnel construction in soil”, Tunnelling andUnderground Space Technology, Vol. 21, No. 3,
2006, pp. 1 – 6.
[10] Nozawa S, “Reduction of the Cost ofConstruction in the Space Above and Below
Rails”, JR EAST Technical Review, No.4, 2003,
pp. 23 – 28.
[11] Zhang D, Liu B, Qin Y, “Construction of alarge-section long pedestrian underpass using
pipe jacking in muddy silty clay: A case study”,
Tunnelling and Underground Space Technology,
Vol. 60, 2016, pp. 151 –164.
[12] Takahashi H, Komiya K, Akagi H, Nakayama T,
Ohashi Y, “Finite element simulation of
construction processes of a mechanized HEP &JES Tunnelling Method”, Proc. EURO:TUN
2009, pp. 31 – 36.

59

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

INFLUENCE OF MATRIC SUCTION ON INSTABILITY OF
UNSATURATED SILTY SOIL IN UNCONFINED CONDITIONS
Ali Murtaza Rasool1,2, Jiro Kuwano1
Dept. of Civil & Environmental Engineering, Saitama University, Japan; 2NESPAK Pvt. Ltd., Lahore, Pakistan

1

ABSTRACT
Rainfall has been recognized as one of the main causes of natural or manmade slope failure in many tropicalareas of the world. In order to reduce and mitigate rainfall-induced slope failures, there is a need to develop anunderstanding of reduction in shear strength of soil due to water infiltration. This research aimed at understanding
the influence of matric suction on water infiltration and transformation of shear strength in unsaturated soil in
unconfined condition. In the present study, two types of test series have been performed using modern triaxial test
apparatus: (1) shear-infiltration test, and (2) pre-wetting shear test. From test results, it was concluded that water
infiltration causes the excessive deformations and softening which decreases the cohesion and hence reduces theshear strength of the soil. The more decrease in shear strength was witnessed in case of pre-wetting shear tests andmaximum reduction observed was 85% against 36cm3 of infiltrated water.
Keywords: Slope failure, Water infiltration, Suction, Shear strength, Unconfined
confining pressure is applied to soil specimen in
unconfined conditions, it is primarily the matricsuction that controls the measured shear strength.
There have been very few studies on unsaturated soils
performed in triaxial test apparatus in unconfinedconditions. Kato et al. (2002), Pineda et al. (2005),
Chae et al. (2010), Kwon et al. (2011) have examined
the behavior of unsaturated soil in unconfinedconditions and tried to interpret the effects of matricsuction and suction stress on shear strength of the soil.
The detailed and fundamental studies on the
instability of unsaturated soils due to matric suction
have seldom been performed in a laboratory using
element test. In the present study, a series of shear
infiltration and the pre-wetting shear test has been
conducted with the main objective of investigating
the mechanical behavior and failure mechanism of
silty soil gradually infiltrated by water. The effects ofdecrease in matric suction on water absorption,
volume deformation and shear strength are discussed,
and finally, the results of two series are compared.

INTRODUCTION
A number of shallow depth slope failures havetaken place during or just after heavy rainfall. Mostof these slope failures are characterized by the factthat they take place in silty and sandy soils. Some ofthem seem to be caused not only by an increase ofpore water pressure in soils resulting from a rise in the
groundwater table, but also by the degradation of thestrength of soil forming the slopes. In view of these
conditions, Yoshida et al. estimated that the cause of
the rain-induced slope failure is largely due to a
reduction in strength of the slope-forming soilmaterials caused by the infiltration of water [11]. The
amount of rainwater that infiltrates the slope is an
important factor. Infiltration of rainwater into a soil
slope may impair slope stability by changing the porewater pressure in the soil which in turn controls thewater content of the soil. It is important to understandthe pore-water pressure changes due to water
infiltration in order to calculate the extent of
reduction of shear strength under certain rainfall
condition. It has implicated that during rainfall,
increased water content in the soil decreases the soil
suction above the ground water table and, thus, theshear strength of the soil [7].
The stress state in natural slope or the surface
layer of an embankment is under very low confiningpressure conditions. A triaxial test performed in
unconfined conditions can simulate this type ofsituations. From a practical standpoint, the test
performed in unconfined conditions can also play animportant role to get a thorough understanding of themechanical behavior of unsaturated soils and to
predict the stability and deformation of the surface
layer in natural slopes or embankments. Since no

TESTING PROGRAMMEDL Clay is the commercial name of the soil usedin this study, it is a fine material without plasticity.
The appearance of freshly and freely deposited DL
clay looks yellowish brown. Dried and powdered DL
clay consists of Kaolinite and silica. Kaolinite andsilica stones are used as agricultural chemicals.
According to the Japanese Geotechnical Society(JGS), it is classified as having Medium-Low
compressibility (ML) and is composed of 90% silt
and 10% clay which show that it is larger in grain size
than average clay. Table 1 shows the physicalproperties of this soil.
60

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Physical properties of DL clay
Properties
Density of soil particle, sConsistency
Maximum dry density, dmax
Optimum water content

Unit
g/cm3
g/cm3
%

Value
2.654
NP
1.538
20

The specimens used in the present study wereprepared using the static compaction method. Prior toperforming the compaction, dry DL clay, with a soil
particle density of 2.654g/cm3, was mixed well withwater to make up 20% of the water content. Then, themixed wet DL clay was compacted statically in acylindrical mold, 5cm in diameter, to obtain auniform density throughout the length of thespecimens. The specimens were compacted in 5
layers, each 2cm thick [10]. The low energy from thestatic compaction can produce a uniform density thatprevents the development of a weaker region in thespecimen [8]. The pre-consolidation pressure on a
specimen during preparation was approximately
300kPa. The void ratio of the specimens was around
1.1 and the initial degree of saturation was 47.5%.
The measured initial matric suction was 1920kPa forall specimens, which means that the preparation
procedure was always followed carefully in order tomaintain a suction state of approximately 20kPa. All
the specimens had a dry density of 1.3g/cm3 and a
degree of compaction 80%.
Two series of experiments with twelve shearing
tests on unsaturated soil specimens were conductedunder stress states as shown in Table 2 to observe theshear strength of soil due to the decrease of matricsuction. The first series involved the infiltration ofwater during the shearing process in drainage
conditions, whereas, in the second series, wetting ofspecimens was performed before the shearing process.

Fig. 1 Variation of suction with degree of saturation
The test apparatus used in this study consists of adouble-walled triaxial cell, an axial loading device,pore-air, pore water and cell pressure transducers asshown in Fig. 1(a). The salient feature of this triaxial
apparatus is that both pore air and water pressures canbe measured separately. The Pore air pressuretransducer is installed in the top cap and is connectedto the air regulator in order to give a continuous
supply of air throughout the test. The change involume of the specimen during the triaxial tests wasmeasured as the change in the water level in the innercell through a Low Capacity Differential Pressure
Transducer (LCDPT). In order to separate the routes
for measurement and control of the pore air pressure
and the pore water pressure, a membrane and a PTFE
sheet were used. The PTFE sheet was placed in the
top cap (Fig. 2(c)) to cut off the flow of water, and themembrane filter was installed in the lower pedestal(Fig. 2(d)) to cut off the flow of air. The thinmembrane filter with pores of 0.45mm has an air
entry value of 420kPa. In addition, a solenoid
controlled valve to control the exhaust air was also
installed in the air drainage line inside the top cap tominimize the air volume (in the air drainage line).

Table 2 Stress state of specimens
Net normal stress(σa - ua) kPa
0
0
20
30

Matric suction (ua - uw) kPa
0
5
10
15
Shear infiltration (SI) test✔

✔

✔

Pre-wetting (PW) test
✔

✔

✔

✔

-

-

✔

(a)
20
-

✔

✔

✔

✔

-

-

The relationship between matric suction andwater content is generally termed as the soil-water
characteristic curve (SWCC). Such curves are usually
measured in laboratory through pressure plate tests or
pF tests, though the current experimental setup wasused to establish the SWCC relation. Several soil
specimens with varying water content were preparedand placed on top of a membrane filter and values of
initial suction were measured, the same technique todraw SWCC was also used by Farooq et al. (2004).
Fig. 1 shows the expected results i.e. the suction
decreases as the saturation ratio increases.

(b)

Infiltrationpressure(c)

Pore air pressure

Air

PTFE

(d)

Water
Air

Membranefilter

Water

Fig. 2 (a) Schematic figure of triaxial cell: (b)external load cell; (c) top cap; (d) bottom pedestal
61

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Since this study focuses more on shallow slope
failure, it was assumed that the pore air pressure
remained atmospheric throughout the test and water
infiltration increased only the pore water pressure [2].
Water in an unsaturated soil specimen was injectedfrom the bottom pedestal which was connected to a
beaker and the pore water pressure transducer throughthe water line. The beaker was placed on an externalload cell and encased in a pressure chamber as shownin Fig. 2(b). The rate of infiltration was controlled byregulating the pressure applied on top of the water
surface in the beaker [2], [8].

infiltration continued until the end of the shearing
process and the amount of water flow into specimen
increases while matric suction decreases. In addition
to this, it was observed that most of the water was
infiltrated up to peak deviatoric stress (represented as), after which water absorption becomes graduallyconstant. The bond between the soil particles broke
after attaining peak strength, which affects the water
infiltration process, it decreases and gradually
becomes constant towards the end of shearing.
(a)

SHEAR INFILTRATION (SI) TEST

InitialsuctionDrained/Controlled pore air
Pressurecontrolσcua
PWP incd. todec. suction

Pressure

A shear infiltration test simulates the condition
and failure mechanisms of slop failures induced bywater infiltration. The schematic representation of thetest procedure is shown in Fig. 3. After measurementof the initial matric suction, pore air and cell pressures
were increased using axis translation technique tokeep pore water pressure above atmospheric [4]. Foursoil specimens were tested in this series, and before
the start of the shearing process each specimen was
brought to a matric suction value of 0kPa, 5kPa,
10kPa, and 15kPa by applying an infiltration pressureof 20kPa, 15kPa, 10kPa, and 5kPa. The pore air was
drained and controlled throughout the test process,whereas, drainage valve for pore water was kept open
during the shear process in order to continuously
supply water to the specimen during the shear process.

uw
Undrained water

(b)

(c)
compression
dilation

Shear

(d)

Time
Infiltration/drained water

Fig. 3 Schematic illustration of shear infiltration test
Fig. 4 shows the results of the shear infiltration
test conducted on unsaturated soil specimens inunconfined conditions. Before the start of theshearing process, an infiltration pressure to individual
specimens was applied and the drainage valve forpore water was opened at the start of the shearing
process to decrease soil suction as shown in Fig. 4(a).
The value of the infiltration pressure was kept thesame therefore no further change in suction wasobserved during the shearing process. Rainfallinduced slope failures are directly related to rainfall
intensity in a specific area. Some part of rain water
penetrates and some flows as surface runoff. A betterparameter to analyze would be the volume ofrainwater infiltrating the soil profile as shown in Fig.
4(b), it shows a more direct relation between moisture
content and deformation. It can be seen that the water

ABCD

A = 1.20%, C = 2.05%
B = 1.40%, D = 2.10%

Fig. 4 Shear infiltration test results: (a) matric suction;(b) water flow; (c) volume change; (d) deviator stress
The volumetric strain response during shearing isimportant to assess or predict the likely field
deformations. Hence the monitoring of volume
changes during shearing becomes crucial. The
volume changes due to water absorption during
shearing process are shown in Fig. 4(c). All the test
specimens showed dilative behavior, however,dilatancy decreased with the increase in water
absorption. The specimen SI-s0 showed first an initial
62

GEOMATE - Mie, Japan, Nov. 21-24, 2017

dilation followed by compression with an increase inaxial strain due to water absorption. As expected,
stress-strain curves in Fig. 4(d) show that deviatoricstress decreases with a decrease in matric suction. The
axial strain corresponding to the peak strength for all
unsaturated specimens ranged between 1.20% to2.10%. Due to water infiltration during the shearing
process, the stress-strain curves showed strain
softening at a higher axial strain of above 6%.
Following Japanese Geotechnical Society Standard“JGS 0527-1998 Method for Triaxial Compression
Test on Unsaturated Soils” the shearing wascontinued to 15% of axial strain. At the end of eachtest, it was observed that all the specimens showed
failure by bulging. All the specimens had an overconsolidation stress history of approximately 300kPa.
The impact of over consolidated stress history andimposed suction is clearly seen in the form of first, apeak failure followed by the post-peak softening typeof stress-strain response and second, in the form of
dilation type of volume change response during theshearing stage.

and failure mechanism of a soil slope after a rainy
period where the soil above the water table
experienced a wetting process. Such kind of situation
has seldom been tested in the laboratory using
unsaturated triaxial test apparatus. Initial suction wasmeasured and matric suction was applied using theaxis-translation technique [4]. The initial phase ofeach test consisted of a wetting stage in which fivesoil specimens were brought to matric suction valuesof 0kPa, 5kPa, 10kPa, 15kPa and 20kPa respectively.
This was achieved by applying an infiltration pressureof 20kPa, 15kPa, 10kPa, 5kPa and 0kPa. The wetting
stage of each test was finished when no further
change in the flow of water into the specimen wasobserved. After the wetting stage, the drainage valve
for pore water was closed and each specimen was
subjected to shear under undrained conditions withmeasurement of pore water pressure. The pore air was
drained and controlled throughout the test process.
Fig. 6 shows the schematic diagram of test procedure.
In this series, three more tests were carried out by
applying low confining stress to make a comparison.
Drained/Controlled pore air
Pressure

M=1.4
(3,4)

InitialsuctionPressurecontrol
σc
ua
uw

(2)

Undrained water

Shear

Pre-wetting(under NO
control)

Infiltration/
drained water

Time
Undrained water

Fig. 6 Schematic illustration of pre-wetting shear test

(1)

Fig. 7 shows the flow of water into the specimen
due to a decrease in matric suction during the wetting
process as a function of time. The volume of water
infiltrating the specimen varied from 0cm3 to 36cm3
for specimens which were brought to a suction of
20kPa to 0kPa. At matric suction value of 20kPa noflow of water occurred which shows that a decreasein suction was required to start the infiltration process,the amount of water flow increases with a decrease insuction. However, by just applying a small net
confining stress of 20 or 30kPa, the amount of waterflowing into the specimen decreases. This is becauseof a decrease in void ratio due to the confining stress.

Ap’ = (σa’ + 2σr’)/3 + s.Sr (kPa)

Fig. 5 Stress paths for shear infiltration tests
The stress paths followed by the soil specimens
during the shear infiltration test are plotted in p’–q
plot as shown in Fig. 5. Since the pore air pressure
was exhausted in this series, the stress paths thus
sloped at a gradient of 1:3 on the p’–q plot. Initially,
the stress path moved towards the left from point “A”
due to a decrease in matric suction. The soil used inthis study was over-consolidated soil, for such soils,
the stress path first crosses the critical state line (CSL)
but eventually reverses its direction and fails on a
critical state line corresponding to critical state
strength (1,2,3,4) and ultimately dropped to residual
strength. The gradient M of CSL was 1.4 andintercept q-axis was 5kPa.

e = 1.10

e = 1.10

e = 1.10

e = 1.10
e = 1.10

σnet = 20kPa
e = 1.08
σnet = 20kPa
e = 1.08
σnet = 30kPa
e = 1.06

PRE-WETTING (PW) SHEAR TESTA pre-wetting shear test simulates the condition

Fig. 7 Flow of water into specimens during wetting
63

GEOMATE - Mie, Japan, Nov. 21-24, 2017(a)between water content, mean net stress and matricsuction at failure is plotted in 3D space as shown in
Fig. 9. It can be seen that mean net stress decrease withincrease moisture content and a decrease in suction,
which shows that moisture content and suction
independently controls the shear strength of soil.

compression
dilation(b)

A =1.80%, C = 3.10%
B = 2.90%, D = 3.30%
E = 3.40%

σnet = 30kPa, s = 10kPa

σnet = 20kPa, s = 5kPa

σnet = 20kPa, s = 0kPa
A

BCDE

Fig. 9 Relationship between water content, mean net
stress, and matric suction

Fig. 8 Pre-wetting shear test results: (a) volume
change; (b) deviator stress

The cohesion of unsaturated soils at a certain levelof matric suction can be estimated more efficiently byusing extended Mohr-Coulomb failure envelope [3].
The Mohr-Coulomb failure envelope for the study
soil was obtained from a series of soil specimen andhas a peak angle of shearing  of 32 and apparent
cohesion c’ (for specimen with 0kPa matric suction)
1.7kPa, shown in Fig. 10(a). The cohesion changed
with matric suction, however,  remained constant.
The angle of the rate of strength due to matric suction
b is shown in Fig. 10(b) which is b 22 for the study
soil. This shows that the cohesion of unsaturated soils
is reduced due to water infiltration from the surface.

The plots of volume change and deviatoric stressversus axial strain relationship for five variable
suction pre-wetting shear test is shown in Fig. 8. It
can be seen that both stiffness and strength decreases
with a decrease in matric suction. This behavior canbe related to the influence of matric suction on interpacket contact forces, which tends to stabilize the soil
structure. Specimens with matric suction value of
5kPa or less showed stress-strain behavior typical of
normally consolidated soils without a marked
reduction of shear strength after attaining peak value,as compared to specimens with matric suction of
more than 5kPa which showed stress-strain behavior
typical of overconsolidated soils. The different shapesof stress-strain curves during shearing can be
explained by looking at how the soil samples wereprepared using static compaction technique. The
compacted soil behavior was similar to theoverconsolidated soil as 300kPa of vertical stress
was applied during sample preparation and tested
under zero net stress. This behavior is attributed todilation of compacted soil [9]. Such specimens showa brittle stress-strain and dilative volume change
behavior at a relatively high matric suction as shownby specimen PW-s20, PW-s15 and PW-s10.
However, with a decrease in suction the volume ofwater flow into specimen increases, as a result, stressstrain behavior becomes typical of ductile materialand compressive soil behavior was observed in
specimen PW-s5 and PW-s0. When specimens with amatric suction of 5kPa and 10kPa were sheared under
net confining stress of 20kPa and 30kPa, no peakcurve was obtained and specimens showed highstrength at the end as compared to unconfinedconditions. However, specimens with 0kPa matricsuction and net confining stress of 20kPa did notshow any remarkable difference. A relationship(σa –σr)/2 (kPa)

(a)

(b)

E
D
C
B
A

For all failure envelops:  = 32
A: (ua-uw) = 0kPa: c = 1.7kPa
B: (ua-uw) = 5kPa: c = 3.9kPa
C: (ua-uw) = 10kPa: c = 6.0kPa
D: (ua-uw) = 15kPa: c = 7.8kPa
E: (ua-uw) = 20kPa: c = 8.3kPa(σa – ua) and (σr – ua) (kPa)b = 22
R2 = 0.967

Fig. 10 Pre-wetting shear test results: (a) failureenvelope; (b) angle indicating the rate of increase in
shear strength with respect to changes in (ua-uw)
64GEOMATE - Mie, Japan, Nov. 21-24, 2017

A series of laboratory element tests wereconducted to examine the instability of unsaturated
soil subjected to water infiltration. It was found that
under the same matric suction, the soil sheared to
failure with pre-wetting condition possessed a lower
shear strength than soil sheared to failure under
infiltration conditions. The maximum reduction inshear strength due to water infiltration observed incase of SI test was 55% and PW test was 85%. The
water infiltration causes excessive deformation
changing the soil behavior from dilatant tocompression. The slope instability problems, whichwere always been treated as a shear strength problem,
also appeared to be a volume change problem. It
seems that a better way of preventing rainfall-induced
slope failures is to limit the excessive development ofsoil deformation rather than just trying to increase theshear strength of slope.

DISCUSSION
The results from the shear infiltration tests arecompared with the results from the pre-wetting shear
tests and are plotted in Fig. 11. Initially, all specimens
have almost the same saturation ratio. In the shear
infiltration test, due to the flow of water into
specimen during shearing process, the saturation ratio
increases till residual stage. Due to this increase in
the degree of saturation a decrease in deviator stress
was observed, the decrease which is small for matricsuction values 15kPa and 10kPa and bigger for 5kPa
and 0kPa, can be seen in Fig. 11(b). The change indeviator stress with matric suction is non-linear. In
the case of pre-wetting shear test the water infiltration
was completed before shearing, therefore, a smallchange in saturation ratio was observed at the start,
peak and residual deviator stress. The amount ofwater absorbed by the specimen at residual deviator
stress stage in shear infiltration test is almost the sameas the pre-wetting shear test wetting stage. Due tothis, the specimens have almost the same watercontent and saturation ratio, as a result almost
identical peak deviator stresses were observed in prewetting shear test as the residual deviator stress in theshear infiltration test, shown in Fig 11(b). The change
in the degree of saturation is not only due to the flowof water but also due to the volume of specimen, at
matric suction of 15kPa and 20kPa the amount ofwater infiltration was very small and specimen
showed dilatant behavior so a decrease in saturation
ratio was observed in both series. When the suction isabout zero or at small value, the saturation ratio is
between 80% and 85%. That means the specimens
could not be fully saturated even at zero suction. The
incompletely full saturation at zero suction may be
attributed to the trapped air in the pores inside soil
specimens or in the testing system.
(a)* Values are water content

20.91%

22.10%
27.68%
25.02%

28.5%
31.70%
34.55%

34.85%

31.92%[1] Chae et al., “Effect of suction on unconfinedstrength in partly saturated soils” KSCE J. of Civil
Engineering, Vol. 14, No. 3, 2010, pp. 281-290.
[2] Farooq et al., “Response of unsaturated sandy
stress under constant shear stress drained
condition” Soils & Found., Vol. 44, 2004, pp.1-13[3] Fredlund DG, Rahardjo H, Soil Mechanics for
Unsaturated Soils. New York: John Wiley andSons Inc., 1993.
[4] Hilf JW, “An investigation of pore water pressure
in compacted cohesive soils” U.S. Dept. InteriorBur. Reclamation tech. Memo. no. 654, 1956.
[5] Kato et al., “Effect of suction on unconfinedcompressive strength and undrained shear
strength of a compacted silty clay” in Proc. of the
3rd Intl. Conf. on Unsat. Soils, 2002, pp. 513-518[6] Kwon et al., “Effect of suction on shear strengthof unsaturated compacted city sand under low
confining pressure” in Proc. of Intl. Symp. on Def.
Charac. of Geomaterials, 2011, pp. 834-840.
[7] Meen WG, Yong MW, “Failure of soil underwater infiltration” Engineering Geology, Vol. 181,
2014, pp. 124-141.
[8] Melinda et al., “Shear strength of compacted soil
under infiltration conditions”, J. of Geotech. Eng.
Div. ASCE, Vol. 130, No. 8, 2004, pp. 807–817.
[9] Pineda JA, Colmenares JE, “Influence of matricsuction on shear strength of compacted kaolin soil
under unconfined condition” in Proc. of Intl.
Symp. Adv. Unsat. Soil Mech., 2005, pp. 221-226.
[10] Rasool AM, Kuwano J, Tachibana S, “Behavior
of compacted unsaturated soil in isotropic
compression, cyclic and monotonic shear loading
sequence in undrained condition”, in Proc. of 6th
Intl. Symp. on Def. Characteristics ofGeomaterials, 2015, pp. 267-274.
[11] Yoshida Y, Kuwano J, Kuwano R, “Effects ofsaturation on shear strength of soils”, Soils andFoundations, Vol. 31, No. 1, 1991, pp. 181-186.

q0
qresidual
qpeak
qresidual

qstartqpeak
qresidual(b)

REFERENCES

25.60%

21.96%

20.00%

21.60%⏹ shear infiltration test (qpeak)⎕

shear infiltration test (qresidual)▲pre-wetting shear test (qpeak) pre-wetting shear test (qresidual)

Fig. 11 Comparison of test results: (a) saturation
ratio; (b) deviator stress
CONCLUSIONS
65

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PROPERTIES OF RAW AND PROCESSED BUKIT GOH BAUXITE INKUANTAN, PAHANG IN ACCORDANCE WITH IMSBC CODE
Muzamir Hasan1,2, Ahmad Amirul Faez1,2, M. Azizul Moqsud3, Tam Weng Long2 and Phang Biao Yu2
1
Centre for Earth Resources Research & Management, Universiti Malaysia Pahang, Malaysia;
2
Faculty of Civil Engineering & Earth Resources, Universiti Malaysia Pahang, Malaysia;
3
Department of Civil and Environmental Engineering, Yamaguchi University, Ube-Shi, Yamaguchi, Japan.
ABSTRACTThis study focus on the differences of geotechnical properties between raw and processed Bukit Goh bauxite.
As bauxite material has high clay content which mostly composed of silicate minerals, it has high risk to cause
cargo liquefaction which in turn causes catastrophic incident. This paper includes the analysis of raw and processedbauxite where its fine particle contents has been minimized using beneficiation method to reduce the risk ofliquefaction by referring to the International Maritime Solid Bulk Cargoes Code (IMSBC Code) standard. To
analyse these characteristics of the bauxite, five samples were selected at Bukit Goh, Kuantan; three of the samples
from the Bukit Goh mine and two samples from stock pile were tested to identify the bauxite geotechnicalproperties by referring to GEOSPEC 3: Model Specification for Soil Testing; particle size distribution, moisture
content, specific gravity, morphological properties as well as its elemental and oxide properties. Laboratory tests
involved including Small Pycnometer test, Dry Sieve test, X-ray fluorescence test (XRF) and Field emission
scanning electron microscopy test (FESEM). The results show that average moisture content of raw bauxite is
24.81% which exceeded the recommended value of maximum 10% while the average moisture content ofprocessed bauxite is only 6.69%. The average fine material for raw bauxite is 38.40% which should not be greaterthan 30% per IMSBC standard while for processed bauxite is 21.40%. In conclusion, the quality and safety ofprocessed bauxite is better than raw bauxite.
Keywords: Bauxite, Beneficiation, Geotechnical Properties, Soil Liquefaction
the cargoes to capsize. Figure 1 shows theclassification of Bauxite in Group C where it isneither liable to liquefy (Group A) nor to possess
chemical hazards (Group B) [6]. If bauxite samples
are complied with the specifications as stated in
IMSBC Code, the samples are allowed be shippedand exported. Thus, this study is carried out todetermine whether Kuantan bauxite samples are inaccordance with the IMSBC Code or not; bycomparing the parameters stated in the code.

INTRODUCTION
Bauxite is the principal ore of alumina (Al2O3),
which is used to produce aluminum. Hydrated
aluminum oxides, hydrated aluminosilicates, ironoxides, hydrated iron oxides, titanium oxide, andsilica are the main compound that made a bauxite [1].
Around the globe, approximately 165 million tonnesof bauxite are mined each year and they are usuallytransported to refineries by conveyor, ship, or rail [2].
Bauxite reserve has been found in Kuantan district
and bauxite mining activity has started due to strong
demand from China, Malaysia increases the
production of bauxite. In 2015, a bulk carrier capsizedabout 150 nautical miles off the coast of Vietnam with
18 fatalities and only one survivors which werecarrying 46 400 tonnes of bauxite. Investigation
conducted by International Maritime Organization(IMO) concluded that the loss of the Bulk Jupiter has
uncovered evidence to suggest liquefaction of cargo
led to loss of stability [3][4]. Liquefaction is aphenomenon where soil experience a process bywhich water-saturated sediment temporarily loses
strength and acts as a fluid [5]. There are somestandard and regulation that need to be follow; in thiscase IMSBC Code to determine the safety of bulk
cargoes carrying bauxite and to minimize the risk of

Fig. 1

Bauxite’s Group C Classification [6]Percentages of moisture content of the sample dohave a relationship with particle size distribution
where the presence of fines particles will influence its
water-holding properties [7].

66GEOMATE - Mie, Japan, Nov. 21-24, 2017liquefaction may occur without warning at any time
during the voyage.

Besides identifying the standard quality ofKuantan bauxite, its morphological characteristic alsostudied to determine the particles present and its
effect. If the particles are found to be harmful,prevention and safety measure should be applied anddiscussed.

Table 2 Moisture content of raw and processed Bukit
Goh Bauxite
Moisture Content (%)

MATERIALS AND METHODS

SampleAll laboratory experiments were carried out basedon Geospec 3: Model Specification for Soil Testing(as shown in Table 1). The beneficiation process isdone in small scale with 100g of samples using abottle dispenser on 4.25mm passing sieve.
Table 1 Laboratory tests and standard
Standards

Moisture Content Test

Geospec 3: Part 2; 5Clause 3.2
Geospec 3: Part 2; 7Clause 3.4
Geospec 3: Part 2; 8Clause 3.5
Quantexpress (FullAnalysis) by XRF S8
Tiger

Specific Gravity Test
Particle Size
Distribution
X-Ray Fluorescence(XRF)

Processed

M2L1B1

27.69

7.31

M2L2B1

22.96

6.12

M2L2B2

23.93

6.47

PTSTL1B1

23.51

6.62

PTSTL2B1

25.95

6.94
Raw

Moisture Content (%)

Laboratory Tests

Raw

30 27.69
22.96

25

23.93

Processed

23.51

25.95

20
15
10
5

7.31

6.12

6.47

6.62

6.94

0

RESULTS AND DISCUSSION
Fig. 2

There are FIVE (5) samples selected from Bukit
Goh in Kuantan; THREE (3) samples are in-situ
samples (M2L1B1, M2L2B1 and M2L2B2) andTWO (2) samples are from stockpile (PTSTL1B1
AND PTSTL2B1).

Moisture content of raw and processed Bukit
Goh Bauxite

Based on IMSBC Standard, the allowablemoisture content for deposits to be on a cargo ship is0%-10%. From the comparison in the bar chart, itshows that the moisture content of raw Bukit Gohbauxite is higher compared to processed bauxite
where it has the average of 24.81% over 6.69% only
on the processed bauxite sample. Due to higher
moisture content, it clearly demonstrates that raw
Bukit Goh bauxite have large amount of fine particle
compared to coarse particle. High level of moisture
content causes the liquefaction of mineral ores to beoccurs and this making the cargo loss of stability
during the voyage. If cargoes loaded with too high amoisture content, liquefaction may occur without
warning at any time during the voyage.

Moisture Content
The result shows moisture content of Bukit Gohbauxite is higher compared to recommended
percentage in the IMSBC Code (Table 2). Due tohigher moisture content, it clearly shows that Bukit
Goh bauxite have large amount of fine particle
compared to coarse particle. Based on IMSBCStandard, the allowable moisture content for deposits
to be on a cargo ship is 0%-10%. From thecomparison in the histogram in Figure 2, it shows thatthe moisture content of raw Bukit Goh bauxite ishigher compared to processed bauxite where it has theaverage of 24.81% over 6.69% only on the processedbauxite sample. Due to higher moisture content, it
clearly demonstrates that raw Bukit Goh bauxite havelarge amount of fine particle compared to coarse
particle. High level of moisture content causes theliquefaction of mineral ores to be occurs and thismaking the cargo loss of stability during the voyage.
If cargoes loaded with too high a moisture content,

Specific Gravity Test
The result from Small Pycnometer Test wascollected where there is just a slight difference in
specific gravity for both samples (Figure 3). Based on
previous studies, the specific gravity values obtained
for the bauxites are in the range from 2.70 to 2.87 andspecific gravity of bauxite in India is higher compared67

GEOMATE - Mie, Japan, Nov. 21-24, 2017

to bauxite at Bukit Goh. The specific gravity ofbauxite largely depends on the density of the mineralmaking up the individual soil particle.
Raw

Specific Gravity

2.95
2.9
2.85
2.8
2.75

morphological properties of both raw and processed
Bukit Goh bauxite. The results are shown in Figure 4,
Figure 5, Figure 6 and Figure 7 where magnificationfor each figure is 1000x, 2000x 5000x and 10000x
respectively; for both raw and processed bauxite
samples. Closer inspection of the particles shows alayer of material coating most of the particle surfaces.
The different sizes of particles can be observed withclear image of lump particles and powdery likestructure of fine particles under 2000x magnification.
Clear image of particles started to be seen at 5000x
magnification and under 10000x magnification, fineparticles attached to the bauxite sample are clearlycan be seen. Study on morphological properties of
Bukit Goh bauxite above displays that the fineparticles of raw bauxite is higher than the beneficiatedbauxite. Clearly seen that the lesser fine particle
attached to the processed bauxite ore. This proved thewashing of bauxite can reduce the amount of fineparticle in bauxite lump. Bauxite samples collectedfrom Bukit Goh mine are disturbed sample, hence thetendency for this sample to liquefy is higher thanundisturbed soil because of the shear force of antiliquefaction of undisturbed soil is 1.5 to 2 times
greater than disturbed soil.

Processed

2.935
2.887
2.865 2.845
2.828
2.807 2.823
2.82
2.795
2.755

2.7
2.65

Fig. 3Specific gravity of raw and processed Bukit
Goh Bauxite

Particle Size Distribution
From Table 3, it clearly shows that bauxite sample
that undergo beneficiation process have lesser fineparticles compare to the raw bauxite sample. Particles
that passed through 2.5mm sieve size is consider fineparticles. The percentage passing 2.5mm forprocessed bauxite sample is 20% while for raw
sample is 39%. Therefore, this prove that the particle
size distribution of raw Bukit Goh bauxites is not in
the range of less than 30% fine particle and coarse
particle more than 70% as stated in IMSBC Code.
Due to higher percentage of fine particle in the raw
bauxite, it will cause the moisture content to increase
as fine particles absorb more water. Meanwhile,bauxite of the same sample that has been beneficiatedhas fine particle less than 30% which prove that
beneficiation method can reduce the number of fineparticles in bauxite.

(a)

(b)

Table 3 Percentage of fine particles between raw andprocessed Bukit Goh Bauxite
SamplesRaw (%)

M2L1B1M2L2B1M2L2B2PTSTL1B1PTSTL1B2
Average fine particles

39
38
47
32
36
38.40

Processed
(%)
20
24
18
23
22
21.40
Fig. 4 Magnification of bauxite sample under 1000x
magnification for (a) raw and (b) processedbauxite sample

Morphological Properties of Bauxite
Field Emission Scanning Electron Microscopy(FESEM) Test is carried to determine the68GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 6 Magnification of bauxite sample under 5000x
magnification for (a) raw and (b) processedbauxite sample

(a)

(a)

(b)

(b)

Fig. 5 Magnification of bauxite sample under 2000x
magnification for (a) raw and (b) processedbauxite sample(a)Fig. 7 Magnification of bauxite sample under 10000x
magnification for (a) raw and (b) processedbauxite sample
Elemental and Oxide Properties Test
The test of both raw and processed bauxite
elements and oxide properties is carried out by X-Ray
Fluorescence XFF S8 Tiger machine from the UMP
central Laboratory by bombarding a high-energy
gamma ray on both M2L1B1 samples. The results areshown in Table 4 and 5.
From Table 4, it shows that the quantity of Silicon(Si) is reduced from 0.50% to 0.44% and from Table
3, the amount of Silicon Dioxide (SiO2) or also
known as silica is minimized from 1.07% to 0.94%
after beneficiation process. Unfortunately, the valueof aluminium element also decreases slightly from
7.48% to 7.25% although it has not much effects on
the bauxite products. As mentioned before, the coretarget of washing bauxite is to decrease the amount ofsilica and improve the amount of aluminium. In
addition, along with silica, the insoluble iron andtitanium oxides in red mud will also be removed that

(b)

69

GEOMATE - Mie, Japan, Nov. 21-24, 2017

will abolish lower grade fines and enhance the qualityof bauxite.

Table 6 Comparison table with IMSBC code

Table 4 Raw and processed Bukit Goh Bauxite
elements
Parameters
Iron (FE)Aluminium (AL)
Titanium (Ti)
Silicon (Si)
Phosphorus (P)Calcium (Ca)
Sulphur (S)Chromium (Cr)Manganese (Mn)
Zirconium (Zr)
Strontium (Sr)
Niobium (Nb)
Zinc (Zn)
Gallium (Ga)
Yttrium (Y)

Unit
%
%
%
%
%
%
%
%
%
%
%
%
%
ppm
ppm

Raw
31.38
7.48
3.96
0.50
0.40
0.09
0.09
0.08
0.06
0.05
0.02
0.02
0.01
69
35

PSD (IMSBC: 30% < 2.5mm passing)
SamplePassing (%)

Remarks

Processed

M2L1B1 (R)

39

Fail

26.49
7.25
3.33
0.44
0.41
0.11
0.07
0.09
0.05
0.05
0.02
0.02
0.02
79
48

M2L1B1 (P)

20

Pass

M2L2B1 (R)

38

Fail

Unit

Raw

Processed

Iron (III) Oxide
Aluminium Oxide
Titanium Dioxide
Silicon Dioxide
Phosphorus
Pentoxide
Sulphur Trioxide
Calcium Oxide
Chromium (III)Oxide
Manganese Oxide
Zirconium
DioxideNiobium
Pentoxide
Strontium Oxide
Zinc Oxide

%
%
%
%
%

44.86
14.13
6.60
1.07
0.91

37.88
13.69
5.55
0.94
0.93

%
%
%

0.22
0.13
0.12

0.18
0.15
0.13

%
%

0.08
0.07

0.06
0.06

%

0.03

0.02

%
%

0.02
0.01

0.02
0.02

24

Pass

47

Fail

M2L2B2 (P)

18

Pass

PTSTL1B1 (R)

32

Fail

PTSTL1B1 (P)

23

Pass

PTSTL2B1 (R)

36

Fail

PTSTL2B1 (P)

22

Pass

Moisture Content (IMSBC: 0% to 10%)

Table 5 Raw and processed Bukit Goh Bauxite
oxidesParameters

M2L2B1 (P)M2L2B2 (R)M2L1B1 (R)

27.69

Fail

M2L1B1 (P)

7.31

Pass

M2L2B1 (R)

22.96

Fail

M2L2B1 (P)

6.12

Pass

M2L2B2 (R)

23.93

Fail

M2L2B2 (P)

6.47

Pass

PTSTL1B1 (R)

23.51

Fail

PTSTL1B1 (P)

6.62

Pass

PTSTL2B1 (R)

25.95

Fail

PTSTL2B1 (P)

6.94

Pass

*Raw = (R), Processed = (P)CONCLUSION
The basic geotechnical properties, chemical
properties and morphological properties of Bukit Gohbauxite had been determine based on criteria neededin IMSBC Code that focuses on three basic properties
which are particle size distribution, moisture content
and specific gravity.
The analysis and result from laboratory test showsthat the average fine particle size of Bukit Gohbauxite is 38.40% while the average percentage ofmoisture content is 24.81%. The results obtained wascompared with IMSBC Code where each of thesebasic properties are exceeding the specified value
stated in the code. After comparing the results to
IMSBC Code, Bukit Goh bauxite cannot be
categorized as Group C because the basic properties
obtained are not fulfilling the requirement in thestandard IMSBC Code. Therefore, it is not suitable to
be exported and there will be higher risk in the

Comparison with IMSBC CodeThe comparison between raw and processedbauxite is shown in Table 6 shows that bauxite thatwent through beneficiation procedure pass all therequirements whether in particle size or moisture
content.
70

GEOMATE - Mie, Japan, Nov. 21-24, 2017transportation of bauxite due to the waves of theocean. Meanwhile, for the processed bauxite, theaverage fine particle size is 21.40% which is below
the limit of 30% while the average percentage ofmoisture content is 6.69% which does not exceed the
10% limitation.
In conclusion, the quality of processed bauxite is
better than raw bauxite. Bukit Goh bauxite must go
through beneficiation process at the site to reduce andeliminate fine particle. The bauxite properties should
follow IMSBC Code requirement to preventliquefaction from occurring.

[3]

[4]

[5]

ACKNOWLEDGEMENTS[6]

The authors would like to acknowledge theUniversiti Malaysia Pahang (UMP) for financing thisresearch through the Research University Grant
Scheme, Project Number RDU1603122. The
cooperation given by all parties involved in thisresearch is greatly acknowledged.

[7]

REFERENCES[1] Shakhashiri, BZ, “Chemical of The Week”:
Aluminium.
UniversityofWisconsin:
SciFun.org, 2012.
[2] Donoghue, AM, “Bauxite Mining and Alumina
Refining: Process Description and Occupational

71

Health Risks”, Journal of Occupational andEnvironmental Medicine, Vol. 56, No. 5, 2014.
International Maritime Organization. Retrieved
from
http://www.imo.org/en/MediaCentre/PressBrief
ings/Pages/38-bauxite-CCC.aspx, 2015.
World Maritime News. Retrieved fromhttp://worldmaritimenews.com/archives/17205
9/imo-bauxite-liquefaction-sank-bulk-jupiter/,
2015.
Seed, HB, “Liquefaction of Saturated Sands
During Cyclic Loading”, Journal of the Soil
Mechanics and Foundations Division, pp. 105134, 1966.
IMSBC Code. International Maritime Solid
Bulk Cargoes Code and Supplement.
International Maritime Organization, 2013.
Freyssinet, P. “Ore forming processes related tolateritic weathering”, Economic Geology One
Hundredth Anniversary, Vol. 1, 2005, pp. 681722.

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

TEMPERATURE CHANGE AND THE TOTAL STRESS ANOMALYIN PASTE BACKFILL*Alsidqi Hasan1, Ting Wee Kiet1, Fauzan Sahdi1, Siti Noor Linda Taib1, Norsuzailina Mohamed Sutan1,
Badhrulhisham Abdul Aziz2 and Andy Fourie3
The Department of Civil Engineering, Universiti Malaysia Sarawak, Malaysia; 2Rare Earth ResearchCenter, Universiti Malaysia Pahang, Malaysia; 3School of Civil, Environmental and Mining Engineering,
University of Western Australia, Australia
1

ABSTRACTThis paper presents preliminary results from a laboratory backfill model test in order to explain the effect oftemperature change during the cement hydration on the total stress within cemented paste backfill. It is
conducted via temperature control test in the absence of the cement. This investigation is an attempt toresolve an anomalous behaviour reported in recent full scale monitoring reports, where the total verticalstress at the stope base shows a progressive increase after backfilling is terminated. The result in this paper
shows that the total vertical stress is not affected by the level of the temperature but rather by the temperature
gradient. The empirical relationship between the temperature gradient and the change in the total verticalstress is proposed. The total stress anomaly found in the full scale monitoring of paste backfill could be
explained by the finding.
Keywords: Backfill, Temperature, Arching, Total Stress, Anomaly
the engineers must have a good understanding of
the possible mechanisms within the paste backfill
during and after backfilling, especially on thehorizontal stress exerted by the paste backfill near
the barricade. The conservative design practiceuses the total vertical stress at the base (bottom) of
the stope to estimate the maximum horizontal
stress acting on the barricade wall. This
assumption is reasonable since the total horizontal
stress is equal to the total vertical stress during thebackfilling (i.e, the paste is still in liquid phase)and the highest total vertical stress within the paste
is located at the deepest location (i.e base).

INTRODUCTION
Paste backfill is a type of material used to fillup underground mined-out voids (stopes), which
improves underground general stability condition.
The material has a paste-like consistency madefrom a mixture of tailings, water, and cementbinder to increase the strength of the paste. Figure
1 shows the paste backfill is being tested for its
rheology property. The paste backfill or also called
cemented paste backfill provides significant
advantage in mining production as compared to theother type of backfills (e.g. hydraulic fill), which
can be a self-supporting material. The adjacent orebodies can be mined without the need of leavingsome parts to act as underground pillars. Hence,
the ore production can be maximized. The
cemented paste backfill has been popularly used in
the underground mining operations for the last two
decades. Figure 2 shows a backfilling sequence in
cemented paste backfilling.
During the backfilling, a barricade isconstructed to plug the drawpoint. The barricade
provides a temporary barrier to prevent the backfill
to flow out of the stope until the backfill gains
enough strength as a self-supporting material andable withstand pressure from blasting activity of
the adjacent stope. As a temporary structure, thebarricade has to be cost effective and acceptable instrength. When the barricade fails, a hefty amountof rehabilitation cost has to be spent and more
importantly the safety of the underground workers
is at serious risk.
In order to design an efficient barricade wall,Fig.1 Paste backfill
According to the overburdened stress theory[1], the total vertical stress (v) is equal to:z(1)

where,  is the bulk unit weight of the backfill
72

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(kN/m3) and z is the depth of backfill (m).

order to isolate the strength gain, the cement is
excluded in the paste and the temperature increaseis simulated via temperature controller. Therefore,
the paste backfill in this experiment is uncemented.
The silica flour is sourced from SILVERBOND,
Johor, Malaysia. It is inert material with SiO2
contents of 99.38% and the specific gravity of
2.65.

Fig.2 Cemented Paste Backfilling
The equation 1 is valid for a semi-confinedarea (such as stope) provided that the paste has notbeen consolidated. During the unconsolidated state,
the paste is in liquid phase and the total stress atthe base of the stope is then equal to the geostatic
stress. After the backfilling is terminated the depth
becomes constant and the geostatic stress is also
constant. The plot of geostatic stress with elapsed
time can be illustrated by a thick solid line in
Figure 3. The consolidation appears after thetermination of backfilling at which the effective
stress starts to generate within the paste. During
the consolidation, the interfacial friction between
the paste and the stope side walls increases as theeffective stress increases. The interfacial friction
transfers some of forces in the paste to the sidewalls (called arching) and therefore, the total
vertical stress at base is reduced. The time toconsolidate depends of the material properties andthe length of drainage path [2]. By considering thearching, the plot of the total vertical stress versus
time deviates from the geostatic line as illustrated
by the dash lines in Figure 3.
The general observation in Figure 3 issummarized from several full scale monitoring
reports [3-10]. However, stress anomalies arefound in some reports [3-8], where the total
vertical stress increases during the rest period as
illustrated by dash dot lines in Figure 3. This is
obviously not expected since there is no paste ispoured during the rest period. One of the
hypotheses is attributed to the temperature increaseduring the cement hydration. This paper showssome preliminary results to test the hypothesis.

Fig. 3 General plots of total vertical stress at thebase of the stope versus elapsed time based on fullmonitoring reports [3-10].
The particle size distribution (psd) of the silica
flour is shown in Figure 4. Two additional points
are superimposed to indicate general categories ofmaterials to be used for paste fill and hydraulic fill[12]. The empty square symbol indicates that thepaste material should have at least 15% of particles
finer than 20 m in order to retain the water inorder to achieve reliable paste flow. It is shownthat silica flour has more than 15% (i.e. 38%) ofparticles is finer than 20 m, thus it falls within the
category. On the other hand, a solid square symbol
indicates the category for hydraulic fills material,
where it requires a maximum 10% of particles
finer than 10 m in order achieve adequate
permeability. The silica flour has more than 10%(14.2%) of particles finer than 10 m and therefore
it does not fall in this category.
The paste is mixed using 10L portable flour
mixer with a solid content of 72% and the unit
weight of the paste is 17.5 kN/m3. The solid
content is defined as the mass of the dry silica
flour over the total mass of paste. In mine
operations, the solid content is determined by thetype of the reticulation system. The higher solid
content, the higher energy is needed to transport
the paste backfill through the reticulation pipes andvice versa. In some cases, gravity system without
pump is sufficient. The range of paste backfill
solid content used in some mining paste backfill
operation is between 71-82% [2-11].

EXPERIMENT
Paste Material

Apparatus

The paste is produced from a mixture of waterand silica flour as a replacement of tailings. In

A laboratory backfill model is built to simulate73

GEOMATE - Mie, Japan, Nov. 21-24, 2017

stope backfilling. The apparatus has four mainparts, namely: a narrow wall, sensors, temperature
control system, and data acquisition system. The
complete apparatus is depicted in Figure 5.

It is important to emphasize the connection
between the base plate and the narrow side wall.
The base plate and the narrow side wall work
independently. This is designed to separate themeasurement of force that is transferred to the baseof the box and the force that is transferred to thenarrow side wall. Therefore, the base plate is not
fixed to the narrow side wall. The base plate issimply seats on the load cell and separated by a 3
mm gap from the narrow side wall. In order toprevent flow of paste between the gap, it is closed
and secured with latex membrane.

Fig. 4 Particle size distribution
The narrow wall consists of a rectangularaluminum box, two columns and the platform. The
box is made of 1 cm thick aluminum measures 15
cm inner length (L), 5 cm inner width (W) and 80
cm inner height (H). The box has a base plate but
has no plate at the top. The two columns are madeof threaded steel rods fixed vertically on theplatform. The rods support the box by fixing its
sides via four nuts. The platform is made of thicksteel with four legs. In order to ensure thehorizontalness, the legs can be adjusted with aspirit level as a reference.
There are two types of sensor used: a load celland a thermocouple. The load cell is used tomeasure the weight of the paste transferred to thebase of the narrow wall. It is placed right under thebase plate. The horizontalness of the load cell canbe adjusted. The thermocouple used is type J,
inserted into the paste from the above opening of
the narrow wall. The temperature control system
consists of heating elements and a microprocessor
based temperature process control CN7263
manufactured by Omega Engineering. The heating
elements are attached to the box using special
aluminum holders and connected to the AC 240
volts powerline via temperature controller. The
target temperature can be set using “on-off” mode
upon receiving signal from the thermocouple. The
heating elements will be turned on if thetemperature received is lower than the target
temperature and vice versa.
The measurements from the sensors are sent tothe computer via data acquisition system. The
sensors calibration and trial testing are carried out
prior to actual test to ensure the test accuracy.

Fig. 5 The laboratory backfill model
Backfilling
The paste is filled (poured) into the box using
funnel until about 70 cm in height. The
thermocouple is inserted into the backfill from the
top opening of the narrow wall. The opening of thenarrow wall is then covered with plastic cling wrap
to minimize the evaporation from the paste during
monitoring. The room temperature during thefilling is about 22 oC. At this time, the heating
elements are turned off to minimize the risk fromelectric shock. After the filling is completed, theheating elements are turned on and the temperature
control is set to the target temperature of 30 oC.
RESULTS
Figure 6a shows the full observation of verticalstress denotes as v (kPa) and temperature of thepaste, T (oC) against the elapsed time. The elapsed
time starts from the filling until 78 hours after. The
vertical stress, v (kPa) is computed as:(2)74

GEOMATE - Mie, Japan, Nov. 21-24, 2017

respectively.
The filling event is highlighted in Figure 6b.
The increase in the total vertical stress is as
expected until it is terminated at about 40 seconds.
The total vertical stress increases from 0 (empty)
until about 12 kPa (full). The 12 kPa is equivalent
to about 70 cm in height of paste according toequation 1. The vertical stress is kept constant until
0.1 hours. During the filling, the temperature isabout 22 oC, which indicates the room temperature(not temperature of the paste) since thethermocouple has not been inserted into the paste.

where, F is the downward force measured by theload cell (kN) and A is the base area of the narrow
wall (0.0075 m2). The temperature from thethermocouple is directly registered by the dataacquision in oC, therefore there is no additional
computation is needed.
Figure 6a is decomposed into Figure 6b-6e thatenlarges and highlights specific events in Figure
6a. Figure 6b-6e shows the total vertical stressversus elapsed time during the filling,
consolidation,
constant
temperature
after
consolidation,andtemperature
ramp-up,
(a)

25
20

temperature
increment

filling/pouring

60

15
40

T ( C)
o

20

10
5

v

consolidationv (kPa)

Temperature (oC)

80

0

0
0

10

20

30

40

50

60

70

80

Elapsed time (hours)
(b)

(c)
20
15

v
25

10
temperature
controller
is started

20

5Temperature (oC)

T (oC)
fillingcompletedv (kPa)

Temperature (oC)

30

40

30

0

0.02 0.04 0.06 0.08 0.1

10
86

consolidationis complete

20

0
0

backfill is
v consolidating
temperature ismaintained
constant
T (oC)48

v (kPa)

12

25

12

16

20

Elapsed time (hours)

Elapsed time (hours)

(e)

(d)

30
12

disturbancev is stablearound 6 kPa

8

20

60
40
20

16

temperature isramped up

12
T (oC)

v (kPa)

16

Temperature (oC)temperature is maintained
constant
T (oC)

v (kPa)

Temperature (oC)

80

8

v

0
20

30

40

50

60

68

Elapsed time (hours)

72

76

80

Elapsed time (hours)

Fig. 6 Backfill monitoring: (a) full observation, (b) filling, (c) consolidation, (d) constant temperature after
consolidation, and (e) temperature ramp-up.
75

GEOMATE - Mie, Japan, Nov. 21-24, 2017

About 2.4 minutes after the filling, thethermocouple is inserted into the paste, theheating elements and the temperature control is
set to a target temperature of 30 oC. The
temperature increases from 22 oC to about 30 oC
in about 20 seconds and maintained. There is noeffect in increasing temperature on the verticalstress during this filling period is apparent, except
a small spike in the total vertical stress at the time
the temperature controller starts to ramp up.
Figure 6c depicts the consolidation phase thatstarts from 6 minutes after the filling andcompletes at around 12 minutes. The temperature
is maintained constant throughout this period. The
total vertical stress at base reduces sharply anddiminishes when approaching the completion of
the consolidation. The consolidation in thisprocess is attributed to the dissipation of porewater to the upper part of the paste and the paste
is compressed. The consolidation increases theeffective stress within the paste and the friction
along the side walls are mobilized that leads tothe development of arching.
The archingtransfers some of the stress within the paste to theside wall and onto the platform. The remaining
stress is carried by the base plate. The archingcauses the total vertical stress to reduce from 12
kPa to only 6 kPa (50% reduction) in 6 minutes.
This consolidation phenomenon has also beenfound in the full scale monitoring [3-10].
Figure 6d shows that there is no change in the
total vertical stress after the consolidation iscompleted. During this period the temperature ismaintained constant. The total vertical stress isconstant around 6 kPa. A small disturbance ofabout 1 kPa is shown as a spike in the total
vertical stress, which is located between 26 to 28
hours elapsed time (occurs at daytime). The total
vertical stress goes back to 6 kPa after 28 hours.
Figure 6e shows the effect of increasing thetemperature (gradient) to the total vertical stressat base. The temperature is ramped-up (increase)and soak (maintained constant) in three steplevels. The first step, the temperature is rampedup from 30 to 42 oC and soaked for about 1.5hours. During ramp-up, the temperature increases
linearly with time in 30 minutes. The calculated
temperature rate of increase (T/t) is 0.4
oC/hours. Due to this temperature increase, thetotal vertical stress increases by 4 kPa. It isthought that the increase of the total vertical stressis due to the expansion of the paste. The
volumetric strain caused by the expansion ispartly resisted by the side wall through friction;
hence the arching is reduced and consequently,
the additional stress to the base is generated. At
the soaking period, the data shows interesting
results where the vertical stress decreases anddiminishes to its value before the ramped-up. The

second step, the temperature is ramped-up from42 to 55 oC at the same rate as the first step. The
total vertical stress increases by 4 kPa. At thesoaking period, the same phenomenon happens
where the total vertical stress decreases anddiminishes to the original value. The last step, thetemperature is ramped-up from 55 to 72 oC withthe same rate as the first and the second step. It
increases the total vertical stress by 5.5 kPa.
During the soaking period, it is noticed from
Figure 6e that the temperature slightly drops
down to 68 oC after reaching 72 oC, thetemperature controller tries to maintain thetemperature by heating the narrow wall and thetemperature ramps-up again until 70 oC at which
the monitoring is terminated. Despite slight dropin the temperature during soaking period, thesame phenomenon as the first and the second step
reappear.
The relationship between the temperature andthe vertical stress is shown in Figure 7. It shows anon-linear increase of vertical stress during thetemperature increase. The patterns for the threesteps are similar and the empirical formulation of
the relationship can be established. In contrast
with ramping-up process, soaking process shows
vertical drop in the total vertical stress, whichbrings back the total vertical stress to its
consolidated state. This implies that the change inthe total vertical stress with respect to its
consolidated state equals to zero (v=0) if there
is no change in temperature (T=0).

Fig.7 v versus T
Figure 8 shows the relationship between thechange in vertical stress (v) and the change intemperature (T) for the three steps during thetemperature ramp-up period. Attempts have been
made to curve fit the experimental data points.
The continuous line in Figure 8 represents thebest curve fitting to represent the empirical
relationship between the change in vertical stress(v) and the change in temperature (T). The
following form of equation is proposed:76

GEOMATE - Mie, Japan, Nov. 21-24, 2017 v  A  1  e

BT



[3] Doherty, J., Hasan, A., Suazo, G., and Fourie,
A. An investigation of some controllable
factors that impact the stress state incemented
paste
backfill.
Canadian
Geotechnical Journal, 2015. doi: 10.1139/cgj014-0321[4] Hasan A., Suazo G., & Fourie A, “Full scale
experiments on the effectiveness of adrainage system for cemented paste backfill”,
in Proc. 16th Int. Seminar on Paste andThickened Tailings (Paste2013), Belo
Horizonte, 2013, pp. 381-394. ISBN 978-09870937-6-9.
[5] Hasan A., Suazo G., Doherty J. & Fourie A,“In situ measurements of cemented paste
backfilling in an operating stope at
Lanfranchi Mine”, in Proc. 11th Int.
Symposium on Mining with Backfill(Minefill 2014), Perth, 2014a, pp. 327-336.
ISBN 978-0-9870937-8-3.
[6] Hasan A., Suazo G., Doherty J. & Fourie A,“In-stope measurements at two Western
Australian mine sites”, in Proc. 17th Int.
Seminar on Paste and Thickened Tailings(Paste2014), Vancouver, 2014b, pp. 355-370.
ISBN 978-0-9917905-3-1.
[7] Thompson, B, Bawden, W and Grabinsky,
M, In situ measurements of cemented paste
backfill at the Cayeli Mine’, Canadian
Geotechnical Journal, Vol. 49, 2012, pp. 75572.
[8] Thompson B, Grabinsky M, & Bawden W,“In-situ measurements of cemented paste
backfill in long-hole stopes”, in Proc. 3rd
Canada-US Rock Mechanics Symposium &20th Canadian Rock Mechanics Symposium,
eds. M. Diederichs & G. Grasselli, Universityof Toronto Press, Toronto, 2009, on CDROM.
[9] Belem T, Harvey A, Simon R, & Aubertin M“Measurement and prediction of internal
stresses in an underground opening during its
filling with cemented fill”, in Proc. 5th Int.
Symposium on Ground Support in Mining
and Underground Construction, eds. E.
Villaescusa & Y. Potvin, Balkema,
Rotterdam, 2004, pp. 619-30.
[10] Yumlu, M., Barricade pressure monitoring inpaste backfill. Gospodarka Surowcami
Mineralnymi, Vol. 24, 2003, pp. 233-244.
[11] LeRoux, K., Bawden, W., and Grabisnky M,“Field properties of cemented paste backfill
at the Golden Giant mine”, Mining
Technology (Trans. Inst. Min. Metall. A)
Vol. 114, 2005, pp. A66-A80.
[12] Potvin, Y., Thomas, E., Fourie, A. Handbook
on mine fill. ISBN 9780975675625, Perth:
Australian Centre for Geomechanics, 2005.

(3)

where, A and B are constants. For the curve
fitting in Figure 8, the value of A and B are 5 and
0.15, respectively.

Fig.8 v versus T
CONCLUSIONS
An experiment has been conducted to monitor
the effect of the temperature change (gradient) on
the total vertical stress within paste backfill via
laboratory model. The following conclusions havebeen made: 1) the total vertical stress is notaffected by the level of the temperature, 2) the
increase in temperature causes the increase in the
total vertical stress at the base of the stope, 3) theempirical relationship between the change intemperature and the change in the total verticalstress fits the exponential function, and 4) the
total stress anomaly found in the full scalemonitoring of paste backfill can be explained as
the change in temperature within the backfill.
ACKNOWLEDGEMENTS
The authors would like to acknowledge
financial supports from the Fundamental
Research Grant Scheme (FRGS) of the Malaysian
Ministry of Higher Education, Grant No.
FRGS/TK01(01)/1301/2015(18).
REFERENCES[1] Fenner, R., “Untersuchungen zur Erkenntnis
des Gebirgsdrucks.” Glückauf, Vol. 74, No.
32, 1938, pp. 681–695.
[2] Terzaghi K., Theoretical Soil Mechanics.
New York: Wiley, 1943.
77

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

3-D NUMERICAL STUDY ON COASTAL LEVEE REINFORCEMENTUSING DOUBLE SHEET-PILES WITH PARTITION WALLS
1

Kousuke Takahama1, Yuta Yamanaka2, Atsushi Yashima3 and Kakuta Fujiwara4
Department of Civil Engineering, Gifu University, Japan; 2,3 Gifu University, Japan;
4
Nippon Steel & Sumitomo Metal Corporation, Japan

ABSTRACT
There is fear that coastal levees will sink by liquefaction due to large earthquake such as Nankai TroughEarthquake in Japan. To overcome this damage, as one of major countermeasures, the application of double sheetpiles with partition walls to coastal levees has been proposed. Authors have already carried out 2-D numericalanalyses (code:LIQCA2D15) to investigate the effectiveness of the proposed countermeasure. However, theinfluence of the interval of partition walls has not been discussed in the framework of 2-D analysis. In this study, theapplicability and limitation of the 2-D analysis was discussed based on 3-D analyses (code:LIQCA3D15).
It was found that the wider the interval of partition walls becomes, the larger the bending deformation of sheet
piles as well as the settlement of coastal levee itself become.
Keywords: Coastal levee, sheet-pile, partition wall, liquefaction, three-dimensional numerical analysis
investigate the applicability and limitation of the 2-D
analysis.

INTRODUCTION
The severe seismic damage to coastal levees inJapan’s Tohoku region was caused by the 2011
Tohoku Region Pacific Coast Earthquake [1]. Largeearthquake such as Nankai Trough Earthquake is also
concerned to occur in the near future and there is fearthat coastal levees will sink by liquefaction. As acountermeasure against a large earthquake andtsunami, the double sheet-piles installation methodwith partition walls (Fig.1 and 2) has been proposed
and its effectiveness has been confirmed by model
tests and numerical analyses [2-4]. The more levee
damage is reduced, the quicker it is feasible to recover
the function of the levee, and as a result, personal andphysical damage can be minimized.
Based on the model tests results, the installationof the double sheet-piles in the coastal levee reduced
the settlement of the levee significantly during theliquefaction of the foundation ground. Furthermore,
if the partition walls were installed with anappropriate interval as shown in Fig.2, the settlementof the top of coastal levee was negligible.
The authors carried out 2-D numerical analysis
for the model test with partition walls. The analyticalresults reproduced model test results quantitatively.
In the previous numerical analysis, however, thecoastal levee with partition walls were modelled by
two dimensional mesh system. If the interval of thepartition walls become larger, we have to take into
account three dimensional deformation characteristicof coastal levee along the extension direction of thelevee. In this study, therefore, we are carrying out 3D numerical analyses by using LIQCA3D15 [5] totie-rod

sheet-pileseaward side

partition wall

landward side

Fig.1 Schematic view of reinforced coastal levee.
partition-wall
extention directionof levee（y-direction in this study）

tie-rod

sheet-pile

Fig.2 Double sheet-piles with partition walls.

78

GEOMATE - Mie, Japan, Nov. 21-24, 2017height of the levee is 300mm, the thickness ofliquefiable layer is 320mm, the thickness of
unliquefiable layer is 200mm and the length of the

VERIFICATION OF 3-D ANALYSIS
Outline of Numerical Code, LIQCA
We are discussing about the difference between
results by 2-D analysis and those by 3-D analysis in
this chapter. The model tests carried out by Fujiwara
et. al [4] are targeted for the comparative numericalanalyses. The experimental results have been
reproduced with high accuracy by 2-D analysis [5].
In this study, we are using two-dimensional
effective stress analysis program, LIQCA2D15[6]and three-dimensional program, LIQCA3D15[6].
The governing equations for coupling problems
between the soil skeleton and pore water pressure
were formulated based on two-phase mixture theory[7] and u-p (displacement of solid-phase and porewater pressure) formulation was adopted in both 2and 3-D analysis. The finite element method (FEM)
was employed for spatial discretization of theequation of motion, while the finite difference
method (FDM) [8] was employed for spatial
discretization of pore water pressure in the continuity
equation. In this simulation, a cyclic elastic-plastic
model [9] was applied to the coastal levee andliquefiable layer.

extension direction of the levee is 170mm which is
the half of the model test container due to thesymmetric nature along the extension direction oflevee. The displacements of the bottom boundary are
fixed in all directions. The horizontal displacement ofside boundaries is also fixed.
The joint element is not supported in the numericalcode, LIQCA3D15.Therefore, the sheet-piles and theinterface between sheet-piles and ground are modeledby solid elements. The slipping and separation of theinterface between sheet-piles and ground cannot betaken into account. The levee and liquefiable layer aremodeled by a cyclic elasto-plastic model, and theunliquefiable layer is modeled by Ramberg-Osgoodmodel (R-O model). As no dilatancy is considered in
R-O model, this model is applicable for dense sand or
clay layer which generate little build-up of excess
pore water pressure during cyclic shear.
The material parameters for a cyclic elasticplastic model is summarized in Table 1(a). The
material parameters of solid element for sheet-pile areshown in Table 1(b). The tie-rod and partition wall
are not modeled by the element itself but modeled by
the displacement constraint condition of nodes. Theinterval of tie-rod in the extension direction of thelevee is 113 mm and the location is 113 mm below
the top of levee. The nodes on both side ends of tierod are put on the nodes of the sheet-piles in the same
position and they are given equal displacementboundary conditions in the vertical and horizontal
directions. As far as the movement of the partition
wall concerned, the equal-displacement condition in
all directions are set for all nodes located on partition
wall. Therefore, shear and bending deformations are
not allowed for partition wall.
The levee, liquefiable and unliquefiable layer aremodeled by same constitutive models in both 2-D and
3-D analysis. The sheet-piles are represented bylinear beam elements (see table 1(c)) in 2-D analysis.
A joint element in which the slipping and separation
are taken into account is used between the ground andsheet-pile. The joint element values are set referring

Condition for Numerical Model
The shaking table model tests were carried out under
the gravity field. The model ground consisted of alevee, liquefiable and unliquefiable layers. The heightof the model levee is 300 mm. That condition isapproximately 1/25 geometrical scale to the actual
structure. Three cases of model tests such as CaseA(without contermeasure), Case-B(with double
sheet-piles), Case-C(with double sheet-piles andpartition walls) are examined. The model tests havebeen successfully reproduced by using a twodimensional effective stress analysis program [10,11] .
In order to compare the performance of 3-D
analysis and that of 2-D analysis, 2-D and 3Dnumerical mesh systems are prepared as shown in
Fig.3. In 3-D analysis, the width is 2800mm, the
170mm

tie-rod

originpartition-wall

300mm

2800mmpartition wallz(hight direction)y(extention
direction of levee)x(width direction)

tie-rodlevee(hight)320mm(liquefiable
layer)
200mm(unliquefiable
layer)

sheet-pileliquefiable layer

320 820

unliquefiable layer
810

450

(b)

(a) 3-D model mesh (half model)
Fig.3 Numerical mesh system

79

300

200
280
2800

450

2-D model mesh

810
[unit : mm]

GEOMATE - Mie, Japan, Nov. 21-24, 2017

to example analysis from LIQCA manual (Table
1(d)). The partition wall is modeled by elastic planar
elements and arranged so as to be superimposed on
the ground elements inside double sheet-piles. The
nodes on both side ends of the partition wall are puton the nodes of the sheet-piles in the same position
and they are given equal displacement boundary
conditions in the vertical and horizontal directions. In
the region inside double sheet-piles, thickness of thepartition wall and ground element are converted intothat per meter in the extension direction of levee andinputted in 2-D analysis. The material parameters forthe partition wall are summarized in Table 1(e).
The other boundary conditions are as follows:A) The bottom of the ground are fixed in thehorizontal and vertical direction.
B) The side boundary of model are fixed in thehorizontal direction.
C) The water level are adjusted to the surface of theliquefiable layer.
D) The drainage boundary is set on the surface of theliquefiable layer.
As a large earthquake with high acceleration
amplitudes and a long duration, we refer the wave
recorded at Kamaishi during the 2011 Tohoku Region
Pacific Coast Earthquake (Fig.4). This wave indicatesthat the maximum acceleration is more than 7m/s2,
the duration is approximately 240 seconds. We adjust
as the input earthquake motion for shaking model
tests considering the similarity rule [12], and thenextend time duration three times in order toemphasize the effect of countermeasures.
As for the condition of both 2-D and 3-D analysis ,the incremental time interral is 0.002 seconds, thecoefficient β of the Newmark method is set at
0.3025, and γ is set at 0.6. For Rayleigh damping, a
proportional type to the initial stiffness is used. The
coefficient is set at 0.003 which corresponds to the
3.0% damping factor to the first natural period of 0.3
seconds of the level ground portion.

Table 1 Material Parameters for layer(a) Material Parameters for liquefiable layer
0.813
intial void ratio
0.015
compression index
0.002
swelling index
1000
initial shear modulus ratio
⁄
∗
0.909
phase transformation stress
ratio
failure stress ratio

1.122

∗

reference strain parameter
reference strain parameter
hardening parameter
hardening parameter
hardening parameter

0.01
0.02
7000
50
0

dilatancy parameter
dilatancy parameteranisotropy parameter

3
3
2000

(b) Material Parameters for sheet-pile (3D)
1.8×109
Lame’ constant (kN/m2)
2
1.1×109
Lame’ constant (kN/m )7.8
density (t/m3)(c) Material Parameters for sheet-pile (2D)
2.0×108
Young’s modulus (kN/m2)
3.2×10-3
area of cross section (m2)
2.7×10-9
area moment of inertia (m4)3
7.8
density (t/m )(d) Material Parameters for joint element (2D)
1.0×104
spring stiffness in shear
direction (kN/m2)
1.0×108
spring stiffness in shear2
perpendicular direction (kN/m )0cohesion (kN/m2)
15
friction angle (degree)

input acceleration (m/s2)(e) Material Parameters for partition wall (2D)
2.0×108
Young’ modulus (kN/m2)
7.8×107
shear elastic modulus(kN/m2)
6.6×10-3
thickness (m)3
7.8
density (t/m )
8
6
4
2
0
-2
-4
-6
-8

0

20

40

time(sec)

60

NUMERICAL RESULTS
For Case-A and C, the levee deformation together
with excess pore water pressure ratio distribution(t=80sec.) in both 2-D and 3-D analyses are shown in
Fig.5. In 3-D analysis, the numerical results at theintermediate location of neighboring walls are plottedin Figs.5(a) and (c). It is found that the horizontal
ground, P2, reached the liquefaction state. The
ground beneath the levee, P1, on the other hand, dose
not reach the liquefaction state. Both 2-D and 3-D
analyses successfully reproduce the generation ofexcess pore water pressure observed in the model
tests [9, 10].
For Case-A and C, the time histories of the excess
pore water pressure at points P1 (beneath the levee)and P2 (horizontal ground) in both 2-D and 3-D
analyses are shown in Fig. 6. It is found that time80

Fig.4 Input acceleration80

excess pore water pressure (kN/m2)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

histories of excess pore water pressure at P1 and P2
are almost identical in both 2-D and 3-D analysis. It
is also found that while the foundation grounddeforms due to liquefaction, the settlement of double
sheet-piles themselves and the ground inside sheetpiles as well as partition walls are significantly
reduced both in 2-D and 3-D analyses.
For Case-A ~ C, the time histories of the settlement
at the top of the levee in 2-D and 3-D analyses areshown in Fig. 7. The settlement numericallycalculated in 3-D analyses is a little bit smaller thanthat in 2-D analyses. The slipping between sheet-piles
and ground is not taken into consideration in 3-D
analysis. This is the main reason why the smaller
settlement is predicted in 3-D analysis than in 2-D
analysis.

(a)

(b)

(c)

Case-A (3D)

Case-A (2D)

4
2
0

(d)

Case-C (2D)P1(2D)
P2(2D)

initial vertical effective stress (P2)depth (mm)excess pore water pressure (kN/m2)

initial verticaleffective stress(P1)P1(3D)
P2(3D)

2
0

20

40

60

time (sec)80(b) with countermeasure (Case-C)
Time histories of excess pore water pressure

Fig.7 Time histories of settlement at top of leveeFig.5 Excess pore water pressure distribution
in deformed mesh

40Case-C (3D)

P1

P2

6

initial vertical effective stress (P2)P1(3D)
P2(3D)P1

P2

8

P1(2D)
P2(2D)For Case-B and C, the sheet-pile deformation at
t=80sec. in both 2-D and 3-D analyses are shown in
Fig.8. In 3-D analysis, the numerical results at theintermediate location of neighboring partition walls(at y=170mm) are plotted. In Case-B, 2D and 3D
results almost correspond. In Case-C, it is found that
there is little deformation in 2-D analysis. There is, on
the other hand, a certain horizontal deformation
calculated at the intermediate location of the ofneighboring partition walls. This deformation pattern
can be only predicted in 3-D analysis.
From the above results, 3-D analysis successfully
is found to reproduce 2-D analysis. On the other hand,in Case-C, the longer the distance from the partition
wall, the larger the horizontal deformation of sheetpiles is expected.

P1

P2

6

Fig.6

P1

P2

initial verticaleffective stress (P1)

8

0

20

(a)

40

time (sec)

60

0

0

100

100

200

200

300

300

400

400

500

500

600

600

700

700

800

800

-15 -10 -5 0 5 10 15
horizontal displacement
(mm)

80

(a) 2-D (Case-B)

without countermeasure (Case-A)

81

y=0

-15 -10 -5 0 5 10 15
horizontal displacement
(mm)

(b)

3-D (Case-B)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

200

200

300

300

400

400

500

500

600

600

700

700
-15 -10 -5 0 5 10 15
horizontal displacement(mm)(c) 2-D (Case-C)

800

300

settlement at op oflevee (mm)

3000

4000

5000

6000

y=0
y=1700y=3400

y=43
y=85
‐10

‐5

0

5

10

(a)interval of 170mm

‐10

‐5

0

5

10

horizontal displacement (mm)(b) interval of 6800mm

Fig.10 Horizontal deformation of sheet-piles
8interval 170mm(P1)6interval 340mm(P1)4interval 6800mm(p1)2

P2（almost the same）

0
0

20

40

time (sec)60

80

Fig.11 Time histories of excess pore water pressure at theintermediate location of the interval of partition wall
maximum opening of steel pile
(mm)

15

interval 170mm

12interval 340mm
interval 6800mm

9
6
3
0

0

20

40

60

80

time (sec)Fig.12 Time histories of maximum opening of sheet-piles
7000

The horizontal deformations of sheet-piles atdifferent distance from the partition wall are shown in
Fig.10 for cases of the interval of partition wall with
170mm and 6,800mm, respectively. The value of “y”
in the figure represents the distance from the partition
wall. It is understood that the horizontal deformation
becomes larger if the interval of partition wall
becomes larger by comparing the results shown in
Fig.8(b). It is found that a large vertical displacementof levee is caused by a large horizontal deformationof sheet-pile. A small horizontal deformation of
sheet-pile just beneath the top of levee at y=3,400mm
is due to the existence of tie-rod.
The time histories of excess pore water pressures atpoints P1 (beneath the levee) and P2 (horizontal

‐10
‐20
‐30

Fig.9

y=0

(d) 3-D (Case-C)

interval of partition wall (mm)
2000

600

-15 -10 -5 0 5 10 15
horizontal displaement(mm)

In Case-C, it is expected that the larger the intervalof partition walls is, the more vertical settlement at
top of levee surrounded by sheet-piles and partition
walls in the extension direction of levee will be. We
are changing the interval of partition walls under thecondition in which all other numerical conditions aresame as those employed in the previous chapter. Theintervals employed for parametric studies are 170,
226, 280, 510, 680, 1,360, 3,400 and 6,800mm,
respectively.
The relationship between the settlement of top oflevee at t=80sec. and the interval of partition wall isshown in Fig.9. It is found that the larger the intervalof partition wall becomes, the more settlement of topof levee will be. The sheet-piles themselves do notsettle because the bottom end of sheet-pile is installed
into the unliquefiable layer. The predicted settlementin the present 3-D analysis is thought to be smaller
than that predicted in the analysis in which theslipping and separation of the interface between
sheet-piles and ground is taken into account.
1000

500

800

y=0
y=170

Discussion on Influence of Interval of Partition
Wall

0

400

700

Fig.8 Horizontal displacement of sheet-piles0

maximum
opening200

depth(mm)

100

100

excess pore water pressure (kN/m2)

depth (mm)

100

800

0

0

0

Settlement of levee vs. interval of partition wall82

GEOMATE - Mie, Japan, Nov. 21-24, 2017

and Nagao, N., Experimental study on
reinforcement method of levees by sheet-pile,
Geotechnical Journal, Vol.6, No.1, 2011, pp.1-14.
[3] Fujiwara, K., Koseki, J., Otsushi, K. andNakayama, H., Study on reinforcement methodof levees using steel sheet-piles, Foundation andSoft Ground Engineering Challenges in Mekong
Delta, 2013.
[4] Fujiwara, K., Taenaka, S., Otsushi, K., Yashima,A., Sawada, K., Hara, T., Ogawa, T. and Takeda,
K., Study on coastal levee reinforcement using
double sheet-piles with partition walls,
International Journal of Offshore and Polar
Engineering, 2017, (in print)[5] Fujiwara, K., Taenaka, D., Otsushi, K., Yashima,A., Sawada, K., Hara, T., Ogawa, T. and Takeda,
K., Study on coastal levee reinforcement using
double sheet-piles with partition walls,
Proceeding of ISOPE2016, Rhodes, Greece；
pp.767-774, 2016.
[6] LIQCA Liquefaction Geo-Research Institute(LIQCARI), Manual of LIQCA2D15・
LIQCA3D15, 2015.
[7] Biot, M.A., Mechanics of deformation andacoustic propagation in porous media, Journal ofApplied Physics , 33(4), 1962.
[8] Oka, F., Yashima, A., Shibata, T., Kato., M. andUzuoka, R., FEM-FDM coupled liquefaction
analysis of a porous soil using an elasto-plastic
model, Applied Scientific Research, 52, 1994,
pp.209-245.
[9] Oka, F., Yashima, A., Tateishi, A., Taguchi, Y. andYamashita, A., A cyclic elasto-plastic constitutive
model for sand considering a plastic-strain
dependence of the shear modulus, Geotechnique,49(5), 1999.
[10] Fujiwara, K., Taenaka, S., Otsushi, K., Yashima,A., Sawada, K., Ogawa, T. and Takeda, K., Studyon levee reinforcement using double sheet-piles
with partition walls ， Japanese GeotechnicalSociety Special Publication, Vol.5, No.2, 2017,
pp.11-15.
[11] Fujiwara,K., Taenaka, S., Otsushi, K., Yashima,
A. Sawada,K., Hara, T., Ogawa,T. and Takeda, K.,
Study on coastal levee reinforcement using double
sheet-piles with partition walls, Proceeding of
ISOPE2016, 2016, pp.767-774.
[12] Iai, S., Similitude for shaking table tests on soilstructure-fluid model in 1g gravitational field,
Report of the Port and Harbor Research Institute,27(3), 1988, pp.3-24.

ground) are shown in Fig.11 for cases of the intervalof partition wall with 170mm, 340mm and 6,800mm,
respectively. There is no difference of pore waterpressure generation for all cases at point P2. On theother hand, at P2, while the excess pore waterpressure generations for all cases almost coincideeach other before t=15sec. The dissipation of theexcess pore water pressure for narrower interval caseis faster than that for winter internal case after
t=15sec. The time histories of maximum opening ofsheet-pile at the intermediate location of neighboring
partition walls are plotted in Fig.12. There is nodifference of the increase in the opening of sheet-pile
for all cases before t=15sec. On the other hand, theopening of sheet-pile for wider interval case increases
larger than that for narrower case after t=15sec. The
large opening of sheet-pile induces the expansion of
the soil surrounded by sheet-piles. The fastdissipation of excess pore water pressure is partly due
to the expansion of soil surrounded by sheet-piles.
This typical three dimensional deformation
characteristic can only be explained by 3-D analysis.
CONCLUSIONS
Authors investigated the effect of double sheetpiles with partition wall as coastal levee
reinforcement method. The following conclusions
were obtained by carrying out both 2-D and 3-D
numerical analyses (code: LIQCA2D15 and
LIQCA3D15).
1) It was found that the double sheet-piles withpartition wall significantly reduced leveesettlement compared to the case without
countermeasure.
2) It was confirmed that 3-D analysis successfully
reproduced 2-D analysis for case with narrowinterval of partition walls. It is concluded that 2D analysis is sufficient to predict the
deformation of coastal levee installed by double
sheet-piles and partition walls with a certain
interval.
3) It was found that the larger the interval ofpartition walls was, the larger the difference
between 2-D numerical results and 3-D
numerical ones became.
REFERENCES[1] Oka, F., Yoshida, N., Kai, S., Tobita, T., Higo,
Y., Torii, N., Kagamihara, S., Nakanishi, N.,
Kimoto, S., Yamakawa, Y., Touse, Y., Uzuoka,
R. and Kyoya, T., Reconnaissance Report of
Geotechnical Damage due to the 2011 off the
Pacific coast of Tohoku Earthquake - Northern
Area of Miyagi Prefecture -, Japanese
Geotechnical Journal ， Vol.7, No.1, 2012,
pp.37-55.
[2] Otsushi, K., Koseki, J., Kaneko, M., Tanaka, H.
83

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LANDSLIDES AND PRECIPITATION CHARACTERISTICS DURING
THE TYPHOON LIONROCK IN IWATE PREFECTURE, JAPANThapthai Chaithong 1 , Daisuke Komori2 , Yoshiya Touge 3 , Yuta Mitobe 4 , Yuto Sukegawa 5 ,and Satoshi Anzai6
1,2

Graduate School of Environmental Studies , Tohoku University, Japan;
3,5,6
Graduate School of Engineering, Tohoku University, Japan
4
Faculty of Civil and Environmental Engineering, Tohoku Gakuin University , Japan

ABSTRACTIn August 2016, the typhoon Lionrock made landfall on Japan's northeastern coast and caused floods andlandslides. Lionrock brought heavy precipitation to Japan which Sh imotokusari station (33201) recorded 24-hour
rainfall amount over 200 mm and the peak rainfall intensity was approximately 65 mm/hr. Total cost damage
with in the Iwate prefecture is over 700 million dollar, moreover 20 lives were lost and 4 peoples missing.
Therefore, the objective of this paper is to present the results of post -disaster investigation, including, the backanalysis of landslides and precipitation due to the typhoon Lionrock. The rainfall and landslides relationship is
significantly important for rainfall intensity-duration threshold. In this typhoon, the empirical rainfall intensity duration threshold has been derived as I = 20.24D-0.33 . The slope failure could be broadly categorized into thedebris flow, surficial erosion, and soil slide, moreover, occurred on slopes ranging from 19 to 58 degrees.
Keywords: Typhoon, Tropical Cyclone, Landslides, Rainfall, Intensity–duration threshold, Critical rainfall
near Ofunato city where is a city located in Iwate
prefecture on 30 August 2016. This is a cause offlood, landslides, debris flo w and the other in Iwate
prefecture and vicin ity. As a consequence, there aremany serious infrastructure damages and loss of
lives and property. This study aims to present a postdisaster damage investigation and back analysis oflandslides and rainfall characteristic due to thetyphoon Lionrock in Iwate prefecture, Japan.

INTRODUCTION
Landslides are one of the serious natural hazards
and may lead to the occurrence of the large volumesof rock, wood or the other debris . The mechanis m o fintense rainfall due to the typhoon (tropical cyclone)induced landslides is well understood. Landslides
can be caused by increased pore water pressure or
groundwater table during intense storms [1].
Moreover, there are many contributing factor suchas, geological, geomorphological, or land use [2].
Nu merous studies proposed the model that
depicts the criteria and relationship between rainfall
and landslides occurrence for early warning
development or understanding behavior of rainfallinduced landslide such as emp irical rainfall
threshold, analytical rainfall infiltration-infinite
slope model, and numerical models. The emp iricalrainfall threshold uses correlat ion of crit ical daily
rainfall and three day antecedent rainfall for early
warning system, in addition, finding the correlationof rainfall intensity and duration of rainfall (I-D
critical threshold) [3-6]. The analytical rainfall
infiltrat ion-infinite slope model is applied theinfiltrat ion model for finding rainwater infiltration
volume and also applied the infinite slope model fo ra factor of safety calculation. The numerical model
is a widely used analysis the rainfall seepage
through the hillslope.
In 2016, Iwate prefecture is located in the
Tohoku region of Japan, experienced ext reme eventsof the Typhoon. Typhoon Lionrock made landfall

TYPHOON LIONROCK
Typhoon Lionrock was first observed on 15
August 2016 where it was located about 580 km to
the west of Wake Island in the western Pacific
Ocean. It developed into a tropical depression andwas classified by the Japan meteorolog ical agency(JMA) on 16 August 2017 that the wind speed isabout 45 km/h. Du ring August 20-21, the windspeed is increased to 65 km/h and became a tropicalstorm. The lionrock developed into a severe tropicalstorm on August 23 and tropical storm on August 24.
The highest wind speed is 166 km/h on August 28.
Table 1 shows the information of the typhoon
lionrock. Figure 1 shows the direction of thetyphoon lionrock. JMA reported the typhoon
lionrock made landfall near the city of Ofunato
which this unusual typhoon to directly land in the
Tohoku because of typhoons usually approach Japanfro m the south and southwest before moving
northward across the archipelago.
84

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 The information of the typhoon lionrock
Date
(UTC)
08/21
(12:00)08/22(12:00)08/23(12:00)08/24(12:00)08/25(12:00)08/26(12:00)08/27(12:00)08/28(12:00)08/29(12:00)08/30(12:00)

Lat

Long

29.2

133.3

Winds
(km/h)
65

28.5

134.1

74

26.6

134

111

24.4

131.8

148

Tropical
Storm
TropicalStorm
SevereTropical
Storm
Typhoon

23.5

130.8

157

Typhoon

23.2

132.1

148

Typhoon

24.5

134.6

157

Typhoon

28.5

138.8

166

Typhoon

32.3

143.4

138

Typhoon

41.3

140

111

SevereTropicalstorm

reached 220 mm that was observed at the
Shimotokusari station in Kuji city, Iwate. Figure 2
illustrates the intensity and distribution of rainfall on
August 30 in Iwate prefecture. The Lionrock
typhoon produced the heavy rain covered Iwaizu mi
town, Tanohata city, Miyako city which the amountsof 24-hour rain fall in these areas were between 155
to 220 mm. Th is was a cause of the overflow of theriverbanks of Omoto River and landslides and debris
flows.

Category

Fig. 2 Distribution of rainfall on August 30 in
Iwate prefecture.
Figure 3 shows the hourly rain fall of the five rain
gauges in Iwaizu mi town on August 30. Consideringlandslide triggering factors, the intensity andduration of rainfall are the main factors to consider.

Fig. 1

Direction of the typhoon lionrock [7]CHARACTERISTICS OF RAINFALL AND
LANDSLIDES DURING THE TYPHOON
LIONROCK
Rainfall pattern and intensity
Fig. 3 Hourly rainfall from five rain gauges in
Iwaizumi town on August 30.

There were 50 rain gauges in Iwate prefecture
which were used to measure the amount of rain waterin this the landslides and debris flow event. Rainfall
informat ion for event that triggered the landslides
was collected fro m Automated Meteorological Data
Acquisition system (AMeDAS) by the Japanese
Meteorological Agency and the rain gauges areoperated by Iwate prefecture. The heavy rainfall
started on August 30 and the 24 – hour rainfall was

Therefore, intensity-duration thresholds (I-D criticalthresholds), as the empirical threshold, using therainfall intensity and duration data obtained fromthis landslide event. Intensity-duration thresholds are
the most common type of landslide thresholds andhave a general form as the following:85

GEOMATE - Mie, Japan, Nov. 21-24, 2017I  c  aD  warning as shown in Tab le 2. Figure 4 shows thecomparison of I-D critical thresholds obtained fro mthis event and the literature reviews. Fig 4 shows theintensity and duration for the gauge nearest thelandslide areas.

(1)

where I is the rainfall intensity, D is rainfall
duration, and c, a,  are the parameters obtained
fro m curve. Nu merous researchers developed
several I-D critical thresholds serves the landslide
Table 2 Intensity-duration threshold for landslides
No
1

Area
World

EquationI  14.82D0.39

Range, h0.167 < D < 500

2
3
4
5
6

World
World
World
Japan
Japan

I  30.53D0.57
I  10D0.77
I  0.48  7.2D1.00
I  39.71D0.62
I  2.18D0.26

0.5 < D < 12
0.1 < D < 1000
0.1 < D < 1000
0.5 < D < 12
3 < D < 537

Landslides type
Shallow landslides,
Debris flow
Debris flow
Soil slip
Shallow landslides
Debris flow
Shallow landslides

Reference
6
6
6
6
6
4

but this event was to co mbine shallo w landslides
with debris flo w that were observed and surveyed in
the field by a team. Considering the threshold No. 6
for Japan, the I-D critical threshold is rather
conservative criterion.
In addition to the above mentioned, the relation
between the 24-hour rainfall and cu mulative soil
mo isture are also significantly useful for theestablishment of the critical rainfall envelope. The
24-hour rainfall criterion can reflect a function ofregolith thickness and porosity of soil mass and theantecedent precipitation index, as cu mulative soil
mo isture, can refer a function of interception andevapotranspiration [8]. Figure 5 indicates the plots
between the 24-hour rainfall and antecedent
precipitation index.
Fig. 4 I-D crit ical threshold determined by thisstudy and comparison with other I-D criticalthresholds
According to the rainfall intensity and duration,
the I-D critical threshold for this event can bepresented in Eq. (1). Th is threshold is defined for therainstorm durations range 5 to 24 hours. The type of
failure of the landslide occurrence is to combine
shallow landslides with the debris flows.
I  20.24D0.33(2)

Fig. 5 Critical rainfall envelope obtained fro m thislandslides event

As shown in table 1, the previous researchstudies proposed several I-D critical thresholds forworld scale and country scale. Co mparison theprevious thresholds with the data obtained from thislandslide event, it was found that almost of all
previous thresholds can serve this event, but only thethreshold No. 5 is slightly higher than the one pointof intensity and duration this event. Threshold No. 5
was developed to serve the debris flow failure type,Figure 5 presents the critical zone that is rainfall
triggered landslides. The red dots are the 24-hour
rainfall and the API that collected from the rain
gauges surround the landslide areas. The blue dots
are the 24-hour rainfall and the API in the nonlandslides occurrence time. The minimu m critical
24-hour rainfall is appro ximately 130 mm and theminimum API is 220 mm.
86GEOMATE - Mie, Japan, Nov. 21-24, 2017

Landslides characteristics

showing landslide scars in Iwate. Failure scars
usually stretched fro m the stream banks to uphill at
various distances and the depth of failure scars isabout 0.5-1.5 meters. Consequences of failure
brought the large amounts of debris such as rock,wood, or sediment, into the river or villages and got
stuck on the bridge or a house. Fig 10 shows the
woody debris trapped the rail bridge.

The catastrophic landslide in Iwaizu mi town and
Tanohata village are located in Sh imohei District,
Iwate prefecture, Japan, were serious and large
landslide induced Typhoon Lionrock. Geologicalconditions in these areas were formed anaccretionary comp lex (Mesozoic and Palaeo zoic)
and some plutonic rocks [10]. Figure 6 shows the
bedrock layer of the landslide scar.

Fig. 6

Debris flow occurrence in Iwate

Fig. 9Aerial photos showing landslide scars in
Iwate. [11]Bedrock layer of the landslide scar

The landslide scars data were obtained from
Geospatial Information Authority of Japan and
Google Earth website. Figure 7 shows the landslide
distribution and slope angle. The failures occurredon slopes ranging from 19 to 58 degrees.

Fig. 7

Fig. 8Landslide distribution and slope angle.
Fig. 10 Woody debris trapped the rail bridge

Field investigation revealed that the majority ofthe slope failures were of co mplex fo rms that could
be broadly categorized into the debris flow, surficial
erosion, and soil slide. Figure 8 shows the debris
flow occurrence. Figure 9 shows the aerial photos
87GEOMATE - Mie, Japan, Nov. 21-24, 2017

cohesion of soil,   is the effective friction angle,

REGIONAL RAINFALL THRESHOLD

 t is the total soil unit weight, and z is the depth.

As already discuss the characteristic of
precipitation that is the intensity – duration rainfall,
and the antecedent rainfall condition as an empirical
relationship including the characteristic of thelandslide. Hence, the purpose this section is to
discuss the critical rain fall threshold at the regional
scale which considers the physical properties such as
soil permeab ility, soil strength, and failure
mechanis m, using the rainfall in filtration and infinite
slope model. Conceptual of th is crit ical rainfall
threshold is to find the amount of rain that makes thefactor of safety less than 1. The critical rainfall
threshold is based on two main assumptions. The
first assumption is the failure type of landslides is
the infinite slope and the saturation of hillslope
would destabilize a hillslope. The second
assumption is the soil mo isture init ial condition prio r
to rainstorm is equal to the volumetric water content
at field capacity (suction at 33 kPa).
The wetting front of sloping surface is defined
as:

zw 

I

    cos sHence, fro m (5) and (6), the crit ical rainfall
threshold can create a new form as follows:






c
      cos  I cr  sf tan       t sin  cos    1  tan   (7)Reference [13] proposed the range of critical depththat is 2-5 met res for a large debris flow and soil slip
and 0.7-1.2 metres for small soil slip and local
failure. Generally, the crit ical depth is controlled by
the natural soil strata and the other geologicalcondition in each area. Following laboratory results,
the type of soil was classified as a loamsand (LSa),so, the volumetric water content at field capacity is
14% and the volumetric water content at saturation
is 45%. Figure 11 shows the regional crit ical rainfall
threshold for Iwaizu mi town and Tanohata village.
Figure 12 shows the rainfall d istribution in Iwaizu mi
town and Tanohata village.

(3)

f

So,

I  zw s   f  cos (4)So, the critical rainfall threshold is defined as:

I cr  zcr s   f  cos (5)where z w is the wetting front, I is the amount ofrain infiltration,  s is the volu metric water content

Fig. 11 Regional critical rainfall threshold for
Iwaizumi town and Tanohata village.

at saturation,  f is the volu metric water content at
field capacity (33 kPa), I cr is the critical rainfall

threshold, z cr is the critical depth, and  is theslope angle. The volumetric water content at field
capacity and saturation can be estimated using a soil
texture. [12] The soil texture is estimated by the soil
classification and grain size d istribution curve. The
critical depth uses the infin ite slope stability model.
The factor of safety for an infinite slope model isbased on the Mohr-Coulo mb failure criterion isdefined as:Fs tan  c
 t z sin  cos  tan (6)Fig. 12 Rainfall distribution in Iwaizu mi town and
Tanohata village.

where Fs is the safety factor, c  is the effective88

GEOMATE - Mie, Japan, Nov. 21-24, 2017

According to the critical rainfall threshold map,
the landslides occurred in the red and yellow zonethat the critical rainfall is ranging 124 – 192 mm,hence, compared with the rainfall distribution in
those zone, it was found that the amount of rainfall
is high than the critical rainfall and the excess
rainfall is about 5 to 25 mm.

Association of Engineering Geology, Oct. 1993,
pp. 93-100.
[3] Chen CY, “Landslide and debris flo w initiatedcharacteristics after typhoon Morakot in
Taiwan”, Landslides, Vo l. 13,Nov. 2015, pp.
153-164.
[4] Saito H, Nakayama D, and Matsuyama H,“Relat ionship between the initiation of ashallow landslide and rainfall intensity-durationthresholds in Japan”, Geo morphology, Vol. 118,
2010, pp. 167-175.
[5] Godt JW, Bau m RL, and Chleborad AF,“Rain fall characteristics for shallo w landsliding
in Seattle, Washington, USA”, Earth Surf.
Process. Landforms, Vol. 31, 2006, pp. 97-110.
[6] Gu zzetti F, Peruccacci S, Rossi M, and Stark
CP, “Rainfall thresholds for the initiat ion oflandslides in central and southern Europe”,
Meteorol Atmos Phys, Vo l. 98, 2007, pp. 239267.
[7] Kitamoto A, “Typhoon 201610 (LIONROCK)
Detailed
Track
Informat ion”
(Website:
http://agora.ex.nii.ac.jp/digitaltyphoon/summary/wnp/l/201610.html.en)[8] Gabet EJ, Burbank DW, Putkonen JK, PrattSitaula BA, and Ojha T, “Rainfall thresholds forlandsliding in the Himalayas of Nepal”, Vo l. 63,
2004, pp. 131-143.
[9] Ohtsu H, Chaleiwchalard N, Koga H, andSoralu mp S, “A study on landslide early
warning system considering the effect o fantecedent rainfall on slope stability”, The 41th
Symposiu m on Rock Mechanics, Jan. 2012, pp.
252-257.
[10] Araiba K, No zaki T, Jeong B, and Fuku moto y,“Distribution of landslides and their geologicalcharacteristics in Japan-Analysis report basedon the data of nation –wide designatedlandslides-threatened areas”, J. of the Jpn.
Landslide Soc, Vol. 44 No. 5, 2008, pp. 38-43.
[11] Geospatial Information Authority of Japan,
Ministry of Land, Infrastructure, Transport andTourism,(http://www.gsi.go.jp/ BOUSAI/ H28.ta
ihuu10gou.html.)[12] Saxton KE, and Rawls WJ, “Soil water
characteristic estimates by texture and organic
matter for hydrologic solutions ”, Soil science
society of America journal, Vo l. 70, 2006, pp.
1569-1578.
[13] Jotisankasa, A, andVathananukij, H,“Investigation of soil moisture characteristics oflandslide-prone
slopesin
Thailand”,
International Conference on Management ofLandslide Hazard in the Asia-Pacific Region,
Nov. 2008, Sendai, Japan .

CONCLUSION
Typhoon-triggered landslide is a serious natural
disaster. Understanding the characteristics of rainfall
and landslides are a very important method fordeveloping the critical criterion of the landslide early
warning. This study could be concluded that:
The past I-D threshold can be applied in thiscase, except the threshold No. 5 that the rainfall is
considerably higher than the threshold. Moreover,
we create the crit ical rain fall envelope using the 24hour rainfall and antecedent precipitation index.
The majority of the failures were could bebroadly categorized into the debris flow, surficial
erosion, and soil slide, in addition, occurred on
slopes ranging from 19 to 58 degrees. One of theconsequences of landslide is debris such as rocks, o rwoody that is cause of property damage.
The region critical rain fall applies theinfiltrat ion process and the infinite slope analysis
model that can apply in this case.
ACKNOWLEDGEMENTS
This study was supported by Japan Society of
Civil Engineering, The Society for the Pro motion ofConstruction Engineering, and The Social
Implementation Program on Climate Change
Adaptation technology (SI-CAT). The authors
gratefully acknowledge the Geotechnical laboratory,
Depart ment of civil and environ mental engineering,
Graduate School of Engineering, Tohoku University,
Iwate prefecture, and Geospatial Info rmation
Authority of Japan, and National Institute ofInformatics of Japan for informat ion and equipment.
The authors also gratefully thank Mr. Hiroaki
Kabuki for the good suggestion about the laboratory
test.
REFERENCES[1] Tofani V, Dapporto S, Vannocci P, and Casagli
N, “Infiltrat ion, seepage and slope instability
mechanis ms during the 20–21 November 2000
rainstorm in Tuscany, central Italy”, Nat.
Hazards Earth Syst. Sci., Vol. 6, Issue 6, Dec.
2006, pp. 1025-1033.
[2] Phien-wej N, Nutalaya P, Aung Z, and Zh ibin
T, “Catastrophic landslides and debris flows inThailand”, Bulletin of the International89

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

SATURATED SHEAR STRENGTH PARAMETERS OF COMPACTEDKHON KAEN LOESS BY DIRECT SHEAR TEST

Atchariya Saengthongthip1, Ratamanee Nuntasarn2 and Jutaporn Tanok3
1,2,3
Faculty of Engineering, Khon Kaen University, Thailand

ABSTRACTThe aim of this study is to investigate shear strength parameters of compacted Khon Kaen loess from UU, CU
and CD method. These shear strength parameters were determined by direct shear test. The initial dry density of
UU and CU samples was 1.95 t/m3, which was 90% of maximum dry density by modified method. But the initial
dry density of CD samples was 2.0 t/m3, which was the maximum dry density by modified method. The shear rateof UU and CU method was 1 mm/min. The shear rates of CD method was determined from consolidation. However,two samples were tested for CD method. The difference between these two samples was the shear rate, which
was 0.018 and 0.086 mm/min. The test result showed that total cohesion (c) from UU and CU was 0 and 20 kPa,
respectively. Meanwhile, the total friction angle (φ) from UU and CU was 36 and 23.5 degree, respectively. The
residual friction angle (φr) from UU and CU method was 34 and 25 degree, respectively. Moreover, the shear
strength parameters from CD method, which was tested by different strain rate, showed that were a slightly
different. The stress-strain behavior from UU and CU method showed the strain hardening. However, the stressstrain behavior of sample from CD method, which was sheared with a slow rate, showed the strain hardening. The
stress-strain behavior of sample from CD method, which was sheared with a quick rate, showed the strain softening.
Keywords: Direct Shear, Unconsolidated Undrianed, Consolidated Undrianed, Consolidated Drianed, Khon
Kaen Loess

INTRODUCTION

BASIC PROPERTIESIn the present, there are many constructions inKhon Kaen province. Moreover, Khon Kaen soil wasused as construction material for landfill. Therefore
the engineering should know the shear strengthparameters for design the foundation. The shear
strength parameters can be evaluated byunconsolidated undrained method (UU), consolidated
undrained method (CU) and consolidated drained
method (CD). These methods can test by triaxial anddirect shear test. This study used a direct shear test to
determine shear strength parameters of three methods
as mention previously.
In this study, Khon Kaen loess had been
investigated at compacted and saturated condition.
Soil samples for UU and CU method were compacted
at 95% of maximum dry density by modified method.
Moreover, the strain rate of shear for UU and CU
method was 1 mm/min. However, the soil sample for
CD method was prepared at a different initial dry
density from UU and CU. The initial dry density of
CD samples was at the maximum dry density bymodified method. Moreover, the strain rate of shear
CD samples was determined from consolidation test.
For this study, the effect of shear rate on the shear
strength parameters of CD method was considered.
Two strain rate of shears was observed in this study,
which was 0.086 and 0.018 mm/min.

Khon Kaen loess, which was used in this study,
was classified as silty sand (SM) according to [1]. The
results of sieve and hydrometer analysis showed that
Khon Kaen loess consists of 55% sand, 30% silt, and
15% clay [1]. The majority of Khon Kaen sand size
was a fine grain as illustrated in Fig. 1. The naturaldensity of Khon Kaen loess was 1.65 t/m3, which is
the loosed sand. Atterberg’s limit results alsopresented a liquid limit was 16.5% and a non-plastic
limit. The specific gravity was 2.65. The basic
properties of Khon Kaen loess were present in Table1.
100
90

Percent Finer,%

80
70

Silt

Sand

60
50
40
30
20
10
0
10

1

0.1
Particle Size, mm

Fig. 1 Grain Size Distribution
90

0.01

0.001

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Unconsolidated Undrained Method

In addition, the modified compaction was decided
to use in this project because Khon Kaen loess wasused in pavement construction rather than an anotherconstruction. The maximum dry density was 2 t/m3
and the optimum moisture content was 9%.

After specimen was setup, the specimen was soakedfor 24 hr. prior to shear. Then the specimen was shearwith rate 1.0 mm/min. Three different vertical stress
144, 286.5 and 572 kPa was used for this method. The
test result showed that the total cohesion was 0 kPa
and the total friction angle (φ) was 36 degrees. The
residual friction angle (φr) was slightly dropped to 34
degree as shown in Fig 4.

Table 1 Basic Properties of Khon Kaen loess
Properties
16.5
NP
2.65
9
2.0
55
30
15
SM

500
Maximum shear stress400

τmax (kPa)

Liquid limit (LL), %Plastic limit (PL), %Plasticity index (PI), %Specific gravity
Optimum moisture content (OMC), %Maximum dry density (ρd), t/m3
Sand (% )Silt (%)
Clay (%)
USCS classificationy = 0.72x
R² = 0.99
300
200Residual shear stressy = 0.6851x
R² = 0.9785

100
0
0

100

DIRECT SHEAR

200

300
σn (kPa)

400

500

600

Fig. 4 Unconsolidated Undrained Shear Strength

Soil samples were compacted at optimum
moisture content by modified method. Soil samples
were trimmed by cutting ring and taken into direct
shear apparatus as shown in Fig 2 and 3, respectively.

The relationship between horizontal and shear
stress showed a strain hardening except for specimen
no.2, which showed a strain softening as shown in Fig.
5. Besides the relationship between the verticaldisplacement and horizontal displacement presented
a dilatation as shown in Fig. 6.
450400
No.3: Vertical stress = 572 kPa

Shear Stress (kPa)

350
300
250

No.2: Vertical stress = 286.5 kPa

200
150
No.1: Vertical stress = 144 kPa

100

Fig.2 Preparation specimen

50
0
0

2

4
6
Horizontal Displacement (mm)810Fig. 5 The relationship between horizontal
displacement and shear stress of UU sample
Consolidated Undrained Method
After specimen was setup, the specimen was
soaked for 24 hr. and then the specimen had to beconsolidated for 24 hr. prior to shear. The specimen
was shear with rate 1.0 mm/min. Three different
vertical stress 144, 286.5 and 572 kPa was used forthis method. The relationship between the shear stressFig. 3 Direct shear setup91

GEOMATE - Mie, Japan, Nov. 21-24, 2017

and normal stress as shown in Fig. 7 presented thatthe total friction angle of the maximum and residual
shear stress equal to 23.5 degrees. However, theresidual cohesion was dramatically dropped morethan 50% from 20 to 8 kPa.

and OCR was 1.74, which was less than 2. Therefore
the failure time has to determine t50 or t90 as shown in
Eq. 1 and 2, respectively. The shear rate wascalculated from the maximum value of the failure
time as shown in Eq. [3]. This series t50 and t90, which
was determined from the pressure 200 kPa, was 14
and 9 min, respectively. The failure time, which was
calculated from t50 was higher than t90. The shear rateof this series equaled to 0.08571 mm/min.

0.4
No.3: Vertical stress = 572 kPa

Vertical Displacement (mm)

0.35
0.3
0.25
0.2
0.15

t f = 50 t 50

[1]

t 50 = 11.6 t 90

[2]

df
tf

[3]

No.1: Vertical stress = 144 kPa

0.1
0.05
No.2: Vertical stress = 286.5 kPa

0
-0.05

Rd =

-0.1
-0.15
0

1

2
3
4
5
Horizontal Displacement (mm)67Where df equal to 0.2 inches according [2] because
Khon Kaen loess was coarse grain soil. Moreover, tf
is a failure time, which equaled to 60 min.

300
Maximum shear strength

250

200

250
Residual shear strength

Shear Stress (kPa)τmax (kPa)300

y = 0.44x + 19.83
R² = 0.99

150
y = 0.44x + 8.16
R² = 0.9910050

No.3: Vertical stress = 572 kPa

200
150
No.2: Vertical stress = 286.5 kPa

100
50

No.1: Vertical stress = 144 kPa

0

0
0

100

200

300
400
σn (kPa)

500

600

0

700

1

2
3
4
Horizontal Displacement (mm)56Fig. 8 The relationship between horizontal
displacement and shear stress of CU sample

Fig. 7 Consolidated Undrained Shear Strength

0.3

The relationship between horizontal and shear
stress showed the strain hardening as shown in Fig. 8.
Besides the relationship between the verticaldisplacement and horizontal displacement presented
a dilatation as same as UU sample as shown in Fig. 9.

No.3: Vertical stress = 572 kPa

Vertical Displacement (mm)0.25

Consolidated Drained Method

0.2
0.15
0.1
0.05
No.2: Vertical stress = 286.5 kPa

0

After specimen was setup, the specimen was
soaked for 24 hr. and then the specimen had to beconsolidated for 24 hr. prior to shear as same as CU
method. However the shear rate of this method haveto determine from consolidation test. Two series wasstudied in this method. The first series, three verticalstresses 100, 300 and 400 kPa was applied to
specimen. Besides the second series, three verticalstresses 100 200 and 400 kPa was applied to specimen.

Fig. 9 The relationship between horizontal andvertical displacement of CU sample

Consolidation Test
For the first series, the consolidation results foundthat that pre-consolidation pressure (Pc) was 56 kPa

For the second series, the consolidation results
found that that pre-consolidation pressure (Pc) was 40
kPa and OCR was 1.24, which was also less than 2.

-0.05
-0.1
No.1: Vertical stress = 144 kPa

-0.15
0

92

1

2
3
5
4
Horizontal Displacement (mm)67GEOMATE - Mie, Japan, Nov. 21-24, 2017

Then the failure time has to determine t50 or t90.This
series t50 and t90, which was determined from thepressure 100, 200 and 400 kPa as shown in Table 2.
The failure time which was calculated from t50 of 100
kPa vertical stress was highest. Therefore the shear
rate of this series equaled to 0.018 mm/min.

The effective friction angle of the first series and thesecond series was slightly different. The effective
cohesion of the first series was higher than the second
series. The residual friction angle of both series
showed slightly increased 0.5 degrees. However, theresidual cohesion was dropped dramatically.
The relationship between horizontal displacement
and shear stress of the first series showed the strain
softening as shown in Fig. 12. Meanwhile, therelationship between horizontal displacement andshear stress of the second series showed the strain
hardening as shown in Fig. 13.
However, the relationship between verticaldisplacement and horizontal displacement of both
series showed a dilation behavior except sample no.1of the second series, which showed the compression.

Table 2 Failure time of CD series 2
VerticalStress(kPa)

t50(min)tf(min)t90(min)

tf
(min)

100

5.5

275

7.84

90.944

200

2.5

125

3.24

37.584

400

3.6

180

7.29

84.564300

Test Result
The effective friction angle and cohesion of thefirst series was 30.5 degree and 18 kPa, respectively,
as shown in Fig. 10. Moreover, the residual friction
angle and cohesion of the first series was 31 degrees
and 0 kPa, respectively.

Shear Stress (kPa)

250

300

No.3: Vertical stress = 400 kPa

200
No.2: Vertical stress = 300 kPa

150
100
50

τmax (kPa)No.1: Vertical stress = 100 kPa
250

Maximum shear strength200

y = 0.59x + 17.69
R² = 0.99

0
0

150

12

14

Fig. 12 The relationship between horizontal
displacement and shear stress of CD sample (First
Series)Residual shear strengthy = 0.60x
R² = 0.99

100

8
10
4
6
Horizontal Displacement (mm)

2

50

300
No.3: Vertical stress = 400 kPa

250

0
50

100

150

200
250
σn (kPa)

300

350

400

450

Shear Stress (kPa)0

Fig. 10 Consolidated Drained Shear Strength of theFirst Seriesτmax (kPa)

4
6
Horizontal Displacement (mm)810CONCLUSION

100

Residual shear
strength50

y = 0.67x + 3.79
R² = 1.00

All test results were present in Table 3. The
residual friction angle (φr) of all methods was slightly
different from the maximum shear stress. However,the cohesion of the residual stress was dropped
dramatically (more than 50%) from the maximum
shear stress. Moreover, the shear rate has an effect on
the stress-strain behavior rather than the shear

0
50

2

Fig. 13 The relationship between horizontal
displacement and shear stress of CD sample (Second
Series)y = 0.66x + 10.60
R² = 1.00

0

No.1: Vertical stress = 100 kPa

0Maximum shear strength

150

100

0

300

200

No.2: Vertical stress = 200 kPa

150

50

The effective friction angle and cohesion of thefirst series was 33.5 degrees and 11 kPa, respectively,
as shown in Fig. 10. Moreover, the residual friction
angle and cohesion of the first series was 34 degreeand 4 kPa, respectively.
250

200

100 150 200 250 300 350 400 450
σn (kPa)

Fig. 11 Consolidated Drained Shear Strength of theSecond Series
93GEOMATE - Mie, Japan, Nov. 21-24, 2017

strength in term of friction angle. However, the shear
rate was impacted on the cohesion of soil.

ACKNOWLEDGEMENTS
Acknowledgement is given to Faculty ofEngineering, Khon Kaen University for the supportof this re-search.

0.3
No.1: Vertical stress = 100 kPa

Vertical Displacement (mm)

0.25
0.2

REFERENCES

0.15
0.1

[1] ASTM - American Society for Testing Material.
2000. Standard Practice for Classification ofSoils for Engineering Purposes (Unified Soil
Classification System) (ASTM D 2487-00).
West Conshohocken. Pennsylvania.
[2] ASTM - American Society for Testing Material.
2011. Standard Test Method For Direct Shear
Test of Soils Under Consolidated Drained(ASTM D3080/D3080M). West Conshohocken.
Pennsylvania.

No.2: Vertical stress = 300 kPa

0.05
0
-0.05
No.3: Vertical stress = 400 kPa

-0.1
0

2

4

6

8

Horizontal Displacement (mm)Fig. 14 The relationship between horizontal andvertical displacement of CD sample (First Series)
0.3

No.3: Vertical stress = 400 kPa

Vertical Displacement (mm)0.2
No.2: Vertical stress = 200 kPa

0.1

0

-0.1

No.1: Vertical stress = 100 kPa

-0.2

-0.3
0

2

4
6
Horizontal Displacement (mm)810Fig. 14 The relationship between horizontal andvertical displacement of CD sample (First Series)
Table 3 All Test Results
Method
Ini.
Shear
Rate
ρdry
(t/m3) (mm/min)
UU
1.9
1.0
Max. shear
Res. shear
CU
1.9
1.0
Max. shear
Res. shear
CD
2
0.086
Max. shear
Res. shear
CD
2
0.018
Max. shear
Res. shear

φ
(o)

c
(kPa)

36
34

0
0

20
23.5

20
8

30.5
31

18
0

33.5
34

11
4

94

GEOMATE - Mie, Japan, Nov. 21-24, 2017

This page has been keft blank intentionally95

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

UTILISATION OF ALKALINE ACTIVATED INDUSTRIAL BYPRODUCTS IN DEEP SOIL MIXING
Mohammadjavad Yaghoubi1, Arul Arulrajah2, Mahdi Miri Disfani3, Suksun Horpibulsuk4, Myint Win Bo5
and Melvyn Leong6
1,2
Faculty of Science, Engineering and Technology, Swinburne University of Technology, Australia;
3
School of Engineering, The University of Melbourne, Australia; 4Faculty of Engineering, Suranaree
University of Technology, Thailand; 5Bo & Associates Inc., Canada: 6Geofrontiers Group Pty Ltd.,
Australia
ABSTRACTThe use of deep soil mixing (DSM) technique in deep ground improvement projects has increased over the past
decade due to being more cost-effective and easier to implement compared to other techniques such as piling, forstructures subject to low to medium loads. Currently, Portland cement, lime and their combination are being usedas the most common binders in DSM. However, due to the economic and concerning environmental disadvantagesof using these binders, there is a need for new environmentally friendly cementing materials. This researchattempts to find a way to use stockpiles of industrial by-products, such as fly ash (FA) and slag (S), as new green
binders; consequently, reducing the carbon footprint in ground improvement projects. Different contents of FA
and S, activated by liquid alkaline activator (L), were added to a soft marine soil to evaluate the changes in its
behaviour as well as its microstructure. In addition, mixtures with cement (C), lime (Li) and their combination
were prepared and tested for comparison. Binders were added at contents of 10, 20 and 30%, by dry soil mass, andsamples were cured for 7 days. The results revealed that these new binders significantly increased the strength andstiffness of the soft soil, and they can be a suitable replacement for C and Li. The optimum mixture was found to
be CIS+5% FA+15% S, within the range of binder, L and water content studied in this research. Moreover,recycling FA and S would substantially limit the expansion of landfill sites.
Keywords: Fly ash, Slag, Geopolymer, Alkaline activation, Deep soil mixing
compared to the native soil. Cohesive soils with highmoisture contents, such as CIS, are most suited to betreated with the DSM method. Current major binders
being used are cement (C) and/or lime (Li) with thecontents of 100-500 kg/m3 (up to 30% by mass) of
soil [5]-[7]. Due to economic and environmental
concerns such as high energy and natural resource
consumption and CO2 emission during the productionof these binders, attempts are being made to findalternative binders lowering the aforementioned
disadvantages in recent years. There is a great
potential in utilizing industrial by-products such as flyash (FA) and slag (S) as they are available abundantly
in landfills; consequently, eliminating the production
concerns associated with traditional binders.
Moreover, this can be a solution to the mentioned
wastes disposal problems. These efforts in recent
years have led to the introduction of green binders
termed as geopolymers. Geopolymer is an inorganic
product of blending precursors, materials rich inalumina and silica such as FA and S, with liquidalkaline activators (L) [8]. FA is a by-product of coal
combustion in power plants, and S is a by-product ofiron and steel manufacturing.
There has been a great deal of research conductedon the use of DSM method and geopolymers,

INTRODUCTION
In the southern part of the Central BusinessDistrict of Melbourne, Australia, which is located in
the Yarra Delta, a highly compressible soft marinesoil, known as Coode Island Silt (CIS), with highwater contents exists. The vast presence of CIS, withpoor engineering characteristics such as low bearing
capacity (undrained shear strengths up to 80 kPa
depending on the depth), in this area causes
geotechnical constraints in construction projects.
Proper deep ground improvement techniques need to
be implemented to improve these soft soil deposits asthey extend up to 30 m in depth [1]-[3]. In the recent
years, new deep ground improvement technologies
such as deep soil mixing (DSM) have drawn theattention of researchers and engineers. For structures
bearing low to medium loads such as roadembankments, DSM is faster and cheaper with lesspractical restrictions compared to traditional methods
such as piling [2], [4].
In DSM method, an auger-mixing tool is drilled
down to the intended depth while injecting acementitious material, as binder, to mix with thenative soil. The result would be circular columns oftreated soil with improved engineering properties
96

GEOMATE - Mie, Japan, Nov. 21-24, 2017

especially utilizing FA and S, in the constructionindustry [2], [6], [8]-[18]. However, sincegeopolymers are relatively new in civil engineering,
there is limited knowledge on the use of these binders
in ground improvement, especially in the DSM
application. This study investigates utilizing FA andS based geopolymers, as an alternative sustainable
material with low carbon footprint, to improve theproperties of soft soils in DSM application. The main
objective of this research is to study the reliability ofusing geopolymers, as green binders, compared to
traditional binders in implementing the DSM
technology in soft soils with high water contents
through unconfined compressive strength (UCS) andmicrostructure analysis. Utilizing FA and S as
industrial by-products, which are often discarded tolandfills, to produce geopolymeric binders in asustainable manner could lead to finding proper
replacements for traditional binders, both
environmentally and economically.

fine fraction of soil was 90% and the coarse fraction
was 10%, with the maximum particle size (Dmax)
being 0.15 mm. the soil had a liquid limit (LL) of
50.4% and a plastic limit (PL) of 23.4%, resulting ina plasticity index (PI) of 27.0%. From the results ofthese tests, the CIS was classified as a silty clay withhigh plasticity. The FA, S, C and Li were collectedfrom local suppliers in Melbourne.

MATERIALS AND METHODS
Materials
Fig. 1The CIS was collected at depths of approximately 3
to 5 m in field, and samples were then put in plasticbags and transferred to the laboratory. Soilclassification tests, such as Atterberg’s limits tests,
were conducted on the CIS to determine its physicalproperties. Figure 1 presents these characteristics
including particle size distribution of CIS, throughconducting sieve analysis and hydrometer tests. thea)c)Fig. 1

Properties of CIS.

Figure 1 presents the SEM images of CIS, FA, S,
C and Li. It is noted that the CIS particles are almost
clustered with irregular shapes, the C and S particles
are very similar having irregular shapes and sharpedges, the FA particles are in spherical shapes andhave smooth surfaces, and the Li particles show aporous medium.
b)

d)

e)

SEM images of: a) CIS, b) C, c) FA, d) Li and e) S.

A combination of sodium hydroxide (NaOH),
obtained in the form of beads, and sodium silicate(Na2SiO3), obtained as solution, was used as the L.
Following safety and financial factors and previous
recommendations, NaOH was prepared to 8 molarity
and a Na2SiO3:NaOH ratio of 70:30 was used [3], [14],[16], [18].

Sample Preparation and Testing
Following the range of binder content consideredfor DSM [6], [7], binder or precursor contents of 10,
20 and 30 %, based on dry CIS mass, were used inthis study. The mixtures were prepared as presented
in Table 1. For the mixtures where traditional binders,
97

GEOMATE - Mie, Japan, Nov. 21-24, 2017[17]. The ratio of activator to precursor was chosen as
1 based on the recommendations by previous
researchers [3], [14]. The water content of the CIS
was set at its LL, to replicate the field conditions,
before mixing with other materials. Previously, the
LL has been reported as the optimum water content
for stabilization of high water content clays [3], [6],[10], [14].

C and Li, were used, C:Li ratios of 100:0, 50:50 and
0:100 were considered. For the geopolymeric binders,
FA:S ratio was considered as 25:75 since S results inhigher strengths, and in less time, compared to FA.
Nevertheless, FA is needed to achieve a coexistenceof Calcium Silicate Hydrate gel, due to the presenceof Calcium in S, and Sodium Aluminosilicate
Hydrate gel, geopolymer product, for better
improvements of the soil properties [3], [11]-[13],Table 1 Mix designs
10%
C
Li
FA
S
C
CIS+C
10
20
CIS+C+Li
5
5
10
CIS+ Li
10
CIS+FA+S
2.5
7.5
Note: The values are in percent (%) by mass of dry CIS.
MixtureFor preparation of geopolymer-stabilized samples,
first, the CIS and precursors were mixed in amechanical mixer for 2.5 minutes, before L wasadded and mixed for another 2.5 minutes, resulting ina total mixing time of 5 minutes. For the feasibility ofcomparison, traditional binder-treated mixtures wereprepared by adding the binder to CIS and mixed for 5
minutes. After mixing the materials, the mixtures
were placed into PVC split molds to prepare
cylindrical specimens with 38 mm diameter and 76
mm height. Three samples were prepared for eachmix to assure the test results were consistent.
Mixtures were put into the molds in two layers,
each layer tapped 25 times on the table to remove theentrapped air. The unit weight of the specimens of all
mixtures was checked for consistency. The samples
were then wrapped with plastic films, put in a humid
room with constant temperature (23±1 °C),
dismantled the next day, wrapped again, and put inthe humid room again to be cured. The overall curing
time was 7 days.
After the curing period, UCS tests were conductedon samples with a 1-mm/min (1.32%/min) rate ofdisplacement and stopped manually after the
specimens reached a considerable post-peak strength
loss. After conducting the UCS tests, small samples
were taken from the failed specimens for further
analysis by scanning electron microscopy (SEM)
imaging tests. The taken samples needed to be dry
before being gold-coated and put in the SEM device.
Thus, samples were put in the oven at 50 °C overnight
before conducting SEM tests.

Li
10
20
-

20%
FA
5

S
15

C
30
15
-

Li
15
30
-

30%
FA
7.5

S
22.5

RESULTS AND DISCUSSIONUCS Tests
Figure 2 presents the results of UCS tests on
different mixtures of CIS stabilized with various
combinations of binders, C and/or Li, at threecontents of 10, 20 and 30%. Puppala et al. [19]suggested a minimum 7-day UCS value of 100 psi(689.5 kPa) for DSM ground improvement using C,
which is presented in Fig. 2. As noticed, in the
mixtures stabilized with traditional binders, CIS-C
mixtures show the highest strength improvement, andas Li content increases, there is a significant decreasein the UCS, as previously observed [20].
Furthermore, while the strength development isalmost linear with binder content increment in CISC-Li and CIS-Li mixtures, the rate of increase reduces
after addition of 20% binder in CIS-C mixtures. This
demonstrates that the optimum C content for ground
improvement in CIS, with high water content, is 20%,
as reported earlier [2], [6], [10], [15].
The UCS values of CIS stabilized with precursors, FA
and S, are illustrated in Fig. 3. It is noted that there isa significant increase in the UCS of geopolymerstabilized mixtures when the precursor content isincreased from 10% to 20%, followed by a lower rateof strength enhancement when 30% precursor isadded. Previously an increase in strength withprecursor content increment has been reported;
however, 20-25%, by dry mass of soil, has beenreported as the optimum [8], [15]. It can be concluded
that, within the range of precursor contents studied
here, 20% is the optimum content to use.

98

GEOMATE - Mie, Japan, Nov. 21-24, 2017(a)Fig. 3

UCS values for mixtures stabilized with FA
and S.

SEM Tests
To analyze the microstructure of the mixtures, SEM
tests were conducted on the samples after the UCS
tests. The SEM images of CIS stabilized with C
and/or Li and geopolymeric binder, with 20% binderor precursor content, are presented in Fig. 3. Figure 3(a) shows the SEM image of CIS+20% C. It is noticed
that the C particles are almost dissolved in the
mixture, resulting in a dense medium with strong
bonds. As C is gradually being replaced with Li, voids
start to appear in the structure, Figs. 3 (b) and (c), tothe extent that in Fig. 3 (c) where the binder is merely
Li, a completely porous matrix is observed. These
images further confirm the considerably higher UCS
values of CIS+C mixtures compared to those of
CIS+C+Li and CIS+Li mixtures.

(b)

Fig. 2(c)
UCS values for mixtures stabilized with: a)C, b) C+Li and c) Li.

Overall, comparing traditional and geopolymericbinders reveals that, except for 10% binder content,
using geopolymeric binders results in considerably
higher strengths. Moreover, although CIS+10% C
and CIS+10% C+10% Li meet the minimum UCS
requirement, it should be noted these are the values
achieved in the lab, while the values obtained in thefield can be 2 to 3 times lower [9]. Therefore,
CIS+20% C and CIS+5% FA+15% S seem to be theoptimum mixtures in terms of strength. Considering
the economic and environmental factors, mentioned
before, using FA-S-based geopolymeric binder in
DSM ground improvement of CIS is a beneficial
replacement for C and/or Li binders.

a)

b)

c)

d)

Fig. 3

SEM images of: a) CIS+20% C, b)
CIS+10% C+10% Li, c) CIS+20% Li and d)
CIS+5% FA+15% S.

In Fig. 3 (d), reacted FA and S particles are clearly
evident that leads to a compact morphology withstrong geopolymer gel bonds. This strong structure
proves proper activation of FA and S with the used L
99

GEOMATE - Mie, Japan, Nov. 21-24, 2017[4] Porbaha A, “State of the art in deep mixing
technology: part I. Basic concepts and overview”,
Proceedings of the Institution of Civil Engineers- Ground Improvement, Vol 2(2), 1998, pp. 8192.
[5] Arulrajah A, Abdullah A, Bo MW, Bouazza A,“Ground improvement techniques for railway
embankments”, Proceedings of the Institution of
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[6] Horpibulsuk S, Rachan R, Suddeepong A,“Assessment of strength development in blended
cement admixed Bangkok clay”, Construction
and building materials, Vol 25(4), 2011, pp.
1521-1531.
[7] Bruce MEC, Berg RR, Collin JG, Filz GM,
Terashi M, Yang DS, Federal Highway
Administration design manual: deep mixing forembankment and foundation support, FHWAHRT-13-046, Federal Highway Administration,
Washington, DC, 2013.
[8] Pourakbar S, Huat BB, Asadi A, Fasihnikoutalab
MH, “Model Study of Alkali-Activated Waste
Binder for Soil Stabilization”, International
Journal of Geosynthetics and GroundEngineering, Vol 2(4), 2016, pp. 35.
[9] Horpibulsuk S, Miura N, Koga H, & Nagaraj T,“Analysis of strength development in deep
mixing: a field study”, Proceedings of theInstitution
of
Civil
Engineers-Ground
Improvement, Vol 8(2), 2004, pp. 59-68.
[10] Lorenzo GA, Bergado DT, “Fundamental
parameters of cement-admixed clay-new
approach”, Journal of Geotechnical andGeoenvironmental Engineering, Vol 130(10),2004, pp. 1042-1050.
[11] Yip CK, Lukey G, Van Deventer J, “Thecoexistence of geopolymeric gel and calcium
silicate hydrate at the early stage of alkaline
activation”, Cement and Concrete Research, Vol
35(9), 2005, pp. 1688-1697.
[12] Kumar S, Kumar R, Mehrotra S, “Influence ofgranulated blast furnace slag on the reaction,
structure and properties of fly ash based
geopolymer”, Journal of Materials Science, Vol
45(3), 2010, pp. 607-615.
[13] Yang T, Yao X, Zhang Z, Wang, “Mechanicalproperty and structure of alkali-activated fly ash
and slag blends”, Journal of Sustainable CementBased Materials, Vol 1(4), 2012, pp. 167-178.
[14] Cristelo N, Glendinning S, Pinto AT, “Deep soft
soil improvement by alkaline activation”,
Proceedings of the Institution of Civil Engineers- Ground Improvement, Vol 164(2), 2011, pp.
73-82.
[15] Bushra I, Robinson RG, “Effect of Fly Ash on
Cement Admixture for a Low Plasticity Marine
Soil”, Advances in Civil Engineering Materials,
Vol 2(1), 2013, pp. 608-621.

and water content; and accordingly, the high strengthachieved by utilizing geopolymeric binder.
CONCLUSION
A series of UCS and SEM tests were conducted
on a clayey soil, CIS, treated with different contents
of geopolymeric binders, obtained by activation ofindustrial by-products such as FA and S, andtraditional binders, C and/or Li. The aim was toinvestigate the performance of utilizing these byproducts in DSM application and comparing theirreliability with that of the traditional binders.
UCS tests results revealed that increasing thebinder content to 30% increased the strength in all
mixtures. However, the rate of increase was lower
when the binder content was increased from 20% to30%, especially when using the geopolymeric binder.
In terms of strength development, using
geopolymeric binder resulted in the highest
improvement, followed by using C, C+Li and Li as
binders. This was evident from the microstructure of
the mixtures using SEM images.
Overall, CIS+5% FA+15% S was found to be
the optimum mixture, within the range of binder, L
and water content studied in this research. Utilizing
stockpiled FA and S in landfills in ground
improvement technologies will not only reduce thefinancial and environmental consequences of using
traditional binders, but also will be a solution to the
problems regarding the disposal of these wastes.
ACKNOWLEDGEMENTS
This research was supported under Australian
Research Council’s Linkage Projects funding scheme(project number LP150100043). The fourth author is
grateful to the financial support from the Thailand
Research Fund under the TRF Senior Research
Scholar program Grant No. RTA5980005 andSuranaree University of Technology.
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age sediments of the Yarra Delta”, Engineering
Geology of Melbourne, 1992, pp. 245-260.
[2] Bouazza A., Kwan PS, Chapman G, “Strength
properties of cement treated Coode Island Silt by
the soil mixing method”, GeotechnicalEngineering for Transportation Projects ASCE,
2004, pp. 1421-1428.
[3] Phetchuay C., Horpibulsuk S., Arulrajah A.,
Suksiripattanapong C., Udomchai A, “Strength
development in soft marine clay stabilized by fly
ash and calcium carbide residue based
geopolymer”, Applied Clay Science, Vol 127128, 2016, pp. 134-142.

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properties of a soil stabilised with an alkaliactivated cement”, European Journal ofEnvironmental and Civil Engineering, 2017, pp.
1-23.
[19] Puppala A, Madhyannapu R, Nazarian S, Special
specification for deep soil mixing, 0-5179, 2008,
The University of Texas at Arlington, Arlington,
TX.

[16] Nematollahi B, Sanjayan J, “Effect of different
superplasticizers and activator combinations on
workability and strength of fly ash based
geopolymer”, Materials & Design, Vol 57, 2014,
pp. 667-672.
[17] Phoo-ngernkham T, Maegawa A, Mishima N,
Hatanaka S, Chindaprasirt P, “Effects of sodiumhydroxide and sodium silicate solutions oncompressive and shear bond strengths of FA–
GBFS geopolymer”, Construction and Building
Materials, Vol 91, 2015, pp. 1-8.
[18] Rios S, Ramos C, Viana da Fonseca A, Cruz N,
Rodrigues C, “Mechanical and durability[20] Okyay, U, Dias, D, “Use of lime and cement
treated soils as pile supported load transfer
platform”, Engineering Geology, Vol 114(1),2010, pp. 34-44.

101Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEEP FOUNDATION REFERENCE FOR METRO MANILA,
PHILIPPINES
Jonathan R. Dungca1, Noel Lester C. Gozum2, Jon Arnel S. Telan3, Victor Carlo F. Torres4 and Timothy
Scott Y. Uytengsu5
12345
Civil Engineering Department, De La Salle University, Philippines
ABSTRACTThe study focuses on the analysis of the pile capacity and pile length for various cities of Metro Manila.
Standard Penetration Test (SPT) N-values from soil reports were used to compute for the geotechnical parameterssuch as the undrained shear strength and the angle of internal friction which were directly applied in thecomputation of the allowable pile capacity. The estimation of the pile length, on the other hand, was done by meansof determining the depth of the refusal or rock layer. The proposed minimum pile length and the allowable pile
capacity values for each city are plotted to establish a contour map. By means of the collected borehole data, theallowable pile capacity was computed, which was shown in the reference as a series of contour maps. The contour
maps were provided to show an overview of the soil’s pile capacity at various locations in Metro Manila,
Philippines. The contour maps presented vary by means of the design of pile, the size of the pile and the proposed
pile length for a specific city or municipality and for the entire Metro Manila. A Geographic Information System(GIS) database was made so as to have storage for the collected borehole data and their locations. The databasecan be updated for the availability of new data.
Keywords: pile capacity, pile length, deep foundation, foundation referenceof this paper are to estimate the necessary pile lengths
for the different areas of Metro Manila and to
determine the proposed pile capacity in the entire
Metro Manila.

INTRODUCTION
Metro Manila’s buildings are comprised of at least
70% high-rise buildings and skyscrapers, excluding
for the cities of Caloocan, Navotas, Las Piñas, Pateros,and Malabon due to the absence of data [1]. High-risebuildings and skyscrapers, compared to low-risebuildings and residential dwellings, would usuallyrequire pile foundation. With that, soil exploration or
excavation would be needed for every construction.
With such a large amount already allocated to theconstruction of the structure itself, a great sum ofmoney must again be allotted to the necessary soil
explorations, which are not just costly but time
consuming. Reducing the total construction expense
would greatly benefit the structural engineer and theowner.
There have been some similar studies related tothis research [2]-[8], however, there is not one
compiled published or commercially available sourceof data for the entire Metro Manila, just scattered andseparate ones. Due to this, if a structural orgeotechnical engineer desires a second reference forthe soil data of a specific area in Metro Manila, theywould need to acquire them from different sources.
This, in turn, would take tremendous amount of timeand effort. Thus, this paper will try to help structural
engineers by giving them a reference for the pile
capacity and pile length needed for the constructionof a structure in need of pile foundation in any
specific place of Metro Manila. The main objectives

METRO MANILA
Metro Manila, Philippines is bounded by theprovinces of Bulacan in the northern part, Rizal in theeastern part, Cavite and Laguna in the Southern part.
Manila Bay is located on the western part of Metro
Manila, while Laguna de Bay is on the eastern part.
Metro Manila has a total land area of 615.39 square
kilometers. Basing on geographical coordinate
system, the entire Metro Manila lies between 120° 54'
and 121° 9' longitudinally and 14° 20' to 14° 47' along
the latitude direction.
At some geologic past, the Metro Manila wassubmerged underwater, which extends up to themountains in the Eastern part. Intermittent volcanic
activities occurred which resulted to the deposition of
volcanic materials. During intervening period ofinactivity, a layer of sediments are placed on top of
the previously laid out volcanic materials which
resulted to the common characteristic of the geologic
deposit which is alternating beds of tuffaceous
materials and transported sediments.
Majority of the sediments present in the geologic
deposit of Metro Manila are due to the bodies of water
surrounding it which include Manila Bay, Pasig River,and Laguna de Bay. The sediments that were102

GEOMATE - Mie, Japan, Nov. 21-24, 2017transported consist of sands, pebbly gravels, silts andclays with various traces of fossil remains or marine
shells and several organic particles. The presence oforganic particles and fossil remains gives an idea of aswampy environment which prevails during a time
which has a shallow water level.
The Guadalupe Tuff formation, the underlying
rock formation of Metro Manila, was generally wellconsolidated and well-cemented. The tuff formation
extends from Quezon City and Novaliches up to theprovince of Cavite in the south. Majority of its
composition is lithified volcanic ash, lapilli and sands.
When it comes to the thickness of the tuff formation,
it remains to be uncertain. Several areas where thetuff formation is present are overlain by layers of
sediments which generally thicken as it approaches
the west side of Metro Manila, which is Manila Bay.
Overall, the composition of the geologic deposit
can be attributed to its elevation. For highly elevatedlocations, it is composed of dense sands andtuffaceous clays. For low – lying areas of Metro
Manila, it is generally composed of loose sands andsoft clays [9].

The estimation of the pile length and thecomputation of the allowable pile capacity were
performed though an excel program. The soil
properties, SPT N-values and RQD were inputted in
the program to get some vital geotechnical parameterslike the undrained shear strength [10] and the angle ofinternal friction [11]-[14]. The minimum pile length
was estimated depending on the soil condition
whether until the refusal layer (SPT-N 50), rock layer(RQD) or even at the last layer of the borehole log in
the absence of the refusal or rock layer. The SPT N
values that are available in the borehole logs that werecollected are the main components used for thecomputation of the pile capacity. The design of thepiles was limited to a range of sizes and shapes. As
for the proposed length of the piles, the depth of therock formation or refusal layer was used as with a one
meter embedment on the hard layer or the last soil
layer.
The allowable pile capacity, on the other hand,
was computed based on the skin friction and end
bearing resistance which are both dependent on thegeotechnical parameters. The results weresummarized in a form of contour maps for easy
visualization and interpretation per city. Likewise, toprovide a good analysis of the values of the allowablepile capacity, skin-to-tip ratio were also consideredand plotted in the maps. This is to provide a support
which between the skin friction and the end bearing
resistance contributed greater value in the allowablepile capacity, which in turn, describes what kind of
soil does a city, in particular, have and how long thepile length is.
The pile capacity was computed by means of thetheory of the alpha and beta method. The alphamethod is used to estimate the pile capacity especiallyfor clayey soil layers. It uses a factor denoted as inapproximating the value of the skin friction and acoefficient Nc to compute for the end-bearing
capacity. The skin friction for any types of piles using
the alpha method includes the coefficient, theundrained shear strength and the lateral surface areaof the pile [15]:fs= αuSu;(1)

METHODOLOGY
The aim of this study is to create a deep
foundation reference for the district of Metro Manila.
Borehole logs with a ratio of one borehole log per
square kilometer were collected and compiled
accordingly as shown in Figure 1. The borehole logs
were accumulated from the different privatecompanies and government institutions in Metro
Manila. A total of 677 borehole locations werecollected and mapped. For the attained data or soil
reports, it already comprised almost 86% of the total
target. However, this number of data does not yet
include the outskirts of Metro Manila which are from
Rizal, Bulacan, Cavite and Laguna. The outskirt data
were used to provide accurate mapping even at thenear boundaries of Metro Manila. The data are thenanalyzed and calculated for the depth of rockformation and geotechnical parameters.

Qf = ∑ (f )x(perimeter)x(length);s
where:
fs= skin friction stressu= coefficient for skin friction
Su = undrained shear strength .

(2)

Beta Method is similar to alpha method in such a
way that it uses coefficients but this time, it is denoted
as for skin friction and Nq for end bearing resistance.
Unlike alpha method, beta method considers bothsandy and clayey soils. The general equations using
the beta method is quite similar to alpha method but
instead of undrained shear strength, the effective
stress is used.

Fig. 1 Map of Manila with borehole locations
103

GEOMATE - Mie, Japan, Nov. 21-24, 2017

respect to Laguna de Bay, where majority of the datacollected near the said body of water possess thicklayers of alluvial deposits, namely sand, silts and clay.
Generally, the proposed pile length for Metro Manila
ranges from 5 to 15 meters.

The skin friction for any types of piles using thebeta method includes the coefficient, the effective
stress and the lateral surface area of the pile [16].
qf = ∑ (z)x(perimeter)x(length);(3)
where:
= coefficient for skin friction;
’z = effective stress;
qf = skin friction .
Some of the borehole data have rock layers
designated by RQD or Rock Quality Designation.
The computation using the alpha and beta methods
are not applicable to rocks anymore. The pile capacity
is now based on the end bearing resistance of the rockwhich is far greater than the soil. Moreover, the skinfriction is neglected in the computation of the pile
capacity of rock. O’ Neill and Reese [7]approximated the ultimate end bearing resistancethrough the formula:q’t = 4830 (qu)0.51 ;(4)
where:
q’t = end bearing resistance;
qu = unconfined compressive strength of rock’ = drained angle of friction
For a better visualization of the acquired data andcomputed values, the allowable pile capacity values
are then mapped out by means of contour maps,
implementing the kriging method. Verification forboth the data accomplished and the produced contour
maps were done as well. The computed values ofallowable pile capacity were stored in the GIS
database as well.

Fig. 2 Proposed Pile Length
Proposed Skin-to-Tip Ratio
The skin-to-tip Ratio is the ratio between the skinfriction and the tip resistance or the end bearing
resistance. For the skin-to-tip ratio map for Metro
Manila, the values can also be reflected by the type ofsoil present along those areas, as seen in Figures 3 and4. The areas underlain by the Guadalupe Tuff
Formation produces low skin-to-tip ratio whereas ahigh ratio is observed in areas where alluvial deposits
are prevalent. In general, the skin-to-tip ratio haspresented that for a certain type of pile, a particular
resisting force is dominant over the other, that is, skinfriction is greater than the tip resistance, also known
as end-bearing resistance, or vice versa. For driven
piles, skin friction usually contributes greater
resistance than that of the end bearing resistance dueto the larger adhesion factors, α and . Practically, theprocess of driving the piles really induces greater
friction from the soil but the consequence is to use
smaller cross-sections only so that the pressure in
driving the piles is greater, thus, producing small endbearing resistance. For bored piles, end bearing
resistance dominates the skin friction because thecross-sectional area of the type of pile is quite large.
Also, some soil layers are neglected for thecomputation of the skin friction due to the effect ofdrilling that make these particular layers disturbed.

DEEP FOUNDATION REFERENCE
Proposed Pile Length
The proposed pile length map for the entire Metro
Manila can be seen in Figure 2. The map reflects thetype of soil present where majority of the area that isunderlain by the Guadalupe Tuff Formation has a pilelength that ranges from 5 to 10 meters in length. There
are regions, which can be seen as areas shaded withwhite, have pile lengths of 5 meters for the entire
region. These regions are recommended for the use ofshallow foundation due to the shallowness of the rocklayer or refusal layer. For locations composed ofalluvial deposits, the range of pile lengths varies
significantly depending on the location. For thewestern part, the pile length ranges from 10 to 15
meters. Several parts of the region show lengths
ranging from 20 to 25 meters. The effect of theManila Bay, in terms of pile length, is manifested
through these results. For the eastern part of Metro
Manila, the proposed pile length ranges from 10 to 25
meters, which shows the effect of the location with104

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 5 Pile Capacity (Bored Piles Size 1.50 meter)
Fig. 3 Proposed Skin-to-tip Ratio (Bored Pile)

Fig. 6 Pile Capacity (Square Driven Piles Size
0.50 meter)

Fig. 4 Proposed Skin-to-tip Ratio (Driven Pile)
Proposed Pile Capacity
The allowable pile capacity maps presented under
Figures 5, 6 and 7 show consistency in terms of theirdistribution of values. A separated sample pile
capacity map where the division of the type of soil
can be seen under Figure 8 (Guadalupe Tuff
Formation) and Figure 9 (Alluvial Deposits). Higher
values of allowable pile capacity are found in areas
where Guadalupe Tuff Formation is located. On theother hand, areas with alluvial deposits have low
allowable pile capacities. Generally, it shows that thepile capacity depends on the type and quality of soilpresent on a specific area.

Fig. 7 Pile Capacity (Octagonal Driven Piles Size
0.50 meter)
105

GEOMATE - Mie, Japan, Nov. 21-24, 2017

still plays a great contributor over the end-bearing
resistance although in totality, the allowable pile
capacity is still small as compared to other cities.
The cities of Makati, Mandaluyong, Paranaque,
Makati and Quezon are quite remarkable not only due
to the high allowable pile capacities that they produce
but to the short pile lengths as well. Having a shortpile length, in this case, is quite advantageous because
it is really cost-effective. Also, it does not affect too
much the allowable pile capacity because it majorly
relies on the end-bearing resistance. The Guadalupe
Tuff formation is actually the factor which makes theend-bearing resistance greater. These cities haveshallow rock layers and usually, shallow foundationis recommended for most of the areas of theaforementioned cities. Skin-to-tip ratio has proventhat the end-bearing resistance really governs in thesecities.
There are cities in Metro Manila which are notrecommendable for shallow foundation just because
the top layers are weak especially in bearing capacity.
These include Manila, Marikina and Pasay. However,when pile foundation is used for these cities, a large
allowable pile capacity is computed. This is because
a longer pile length is recommended to induce largeskin friction from several soil layers and to reach therefusal or rock layer at great depth. In these particularareas, both the skin friction and end bearing resistancegreatly contribute to the allowable pile capacity. Thismeans that high loadings from the superstructure canbe resisted by piles considering also its length. The
trade-off, however, is that it is not cost effective
anymore due to the long piles that require greatamount of materials.

Fig. 8 Pile Capacity for Bored Pile (Guadalupe
Tuff Formation Area)

REFERENCES[1] Emporis GmbH. (n.d.). Emporis, “In Building
Directory”, Retrieved June 10, 2017, fromhttp://www.emporis.com/city/manilaphilippines.
[2] Dungca J. R., “Liquefaction Potential Map ofManila”, Masteral Thesis, De La Salle
University, Philippines, 1997.
[3] Dungca J. R. and Chua R. A. D., “Developmentof a Probabilistic Liquefaction Potential Map for
Metro Manila”, International Journal of
GEOMATE, Vol. 11, Issue 25, Sep. 2016, pp.
2461-2467.
[4] Dungca J. R., Concepcion I., Limyuen M.C.M,
See T. O. and Vicencio M. R., “Soil Bearing
Capacity Reference for Metro Manila”,
International Journal of GEOMATE, Vol. 12,
Issue 32, Apr 2016, pp. 5-11.
[5] Dungca J. R. and Macaraeg C. J., “Developmentof a Reference for Seismic Amplification: The
Case of Metro Manila”, 19th Congress ofInternational Association for Bridge andFig. 9 Pile Capacity for Bored Pile (Alluvial
Deposits Area)
CONCLUSION
In this paper, the pile length and allowable pile
capacity are determined through borehole logs. For
the cities of Las Piñas, Malabon, Navotas, Pateros andPasig, they have relatively small allowable pile
capacities as compared to the other cities for bothdriven and bored piles. Pile lengths are shorter beause
they have reach the refusal layers at somehow ashallow depth thus, lesser skin friction is induced.
Moreover, based on the skin-to-tip ratio, skin friction
106

GEOMATE - Mie, Japan, Nov. 21-24, 2017

American Society of Civil Engineers, June 1-4,
1975, Vol. Ii, 1975.
[12] Kulhawy, F. H.,And Mayne, P. W.,“Relative
Density,
SPT,
and
CPT
Interrelationships”, Calibration Chamber Testing(Isocct-1), Elsevier, New York, 1991, pp. 197211.
[13] Wolff, T. F, “Geotechnical Judgment inFoundation Design. Foundation Engineering:
Current Principles And Practice”, Vol. 2,
American Society Of Civil Engineers, 1989, pp
903 – 917.
[14] Hatanaka, M. and Uchida, A. “Empiricalcorrelation between penetration resistance andinternal friction angle of sandy soils", J. of Soils
and Foundations, 36(4), pp. 1-9 (1996).
[15] Budhu, M. “Soil Mechanics and Foundations”,
2nd Edition. United States of America: John
Wiley & Sons, Inc., 2007.
[16] O'Neill, M.W. and Reese, L.C., "Drilled Shafts:
Construction Procedures and Design Methods,"
Publication No. FHW A-IF-99-025, U.S. Dept.
of Transportation, Federal Highway Admin.,Washington, D.C., 1999, pp.535.

Structural Engineering, Stockholm, Sweden Sep.
2016.
[6] Saldivar – Sali, A., “An Earthquake Risk
Analysis of Metro Manila from a Foundation
Engineering Perspective”, Journal of theGeological Society of the Philippines, 50, 1992,
pp. 287 – 289.
[7] Guevarra E., Santos, J., Sy, Hazel (1999). Data
Aid for the Design of Foundation in Las Pinas
City. Manila”, Thesis, De La Salle University,
Philippines, 1999.
[8] Mustafa, K. “Evaluation of Soil Bearing
Capacities in San Mateo, Rizal,” Philippines,
1995.
[9] Hosono, T., Siringan, F., Yamanaka, T.,
Umezawa, Y., Onodera, S., Nakano, T., &Taniguchi, M. “Application of multi-isotope
ratios to study the source and quality of urban
groundwater in Metro Manila, Philippines”.
Applied Geochemistry, 25(6), 2010, pp.900–909.
[10] Mesri, G. 1989 “A re-evaluation of su(mob) =0.22’ using laboratory shear tests”, Canadian
Geotechnical Journal, 26(1): 1989, pp.162–164.
[11] Schmertmann, J. H., “Measurement of In-Situ
Shear Strength” Journal of the Proceedings of the107SeventhInternational Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

AN ATTEMPT TO DETERMINE A SUITABLE STABILIZER FOR
EXPANSIVE SOILS OF VOLCANIC ORIGIN
Rajeshwar Goodary1, Avirut Chinkulkijniwat2,Vatanavongs Ratanavaraha2, Roodheer Beeharry1, Anoop
Aujayeb1.
1
Université des Mascareignes
Avenue de la Concorde, Rose Hill, Mauritius
2
Suranaree University of Technology
Nakhon Ratchasima, Thailand
ABSTRACTIn this study, a family of widespread expansive soil, namely Dark Magnesium Clay of volcanic origin,occurring in Mauritius Island, is stabilized with various stabilizers and their combinations. The strength properties
for these mixtures are investigated. The test specimens are prepared at maximum dry density (MDD) value,
obtained from the standard Proctor compaction test, in compliance with BS 1377. Lime, Ordinary Portland Cement(OPC), Fly Ash and Coarse Rock Sand and their combinations, that is, lime-cement, coarse rock sand-cement, fly
ash-cement, lime-fly ash, lime-coarse sand and fly ash-coarse sand, used as partial replacement of the soil, areused as main stabilizers and their effects on the soil mass strength are investigated. Trial mixes with 0%, 2.5%,
5%, 7.5%, 10%, 12.5% and 15% soil replacement are prepared and tested for Unconfined Compressive Strengths.
Specimens 40 mm x 40 mm x 40 mm are prepared in a mold with varying content of stabilizer. The samples aredemolded and allowed to cure in a water-saturated and airtight container for 7 days and eventually in ambientlaboratory conditions. Hardened samples are tested for their dry Unconfined Compressive Strength at the age of
21 days. Results show that an addition of 2.5% of the combined mix of coarse sand-fly ash and 7.5% fly ash yield
acceptable Unconfined Compressive Strengths of 5.2 and 5.5 MPa respectively with a significant decrease in linear
shrinkage value
Keywords: Dark magnesium clay, stabilizer, maximum dry density, curing, compressive strength, linear shrinkage
signs incorporate wide and profound shrinkage cracks
and hard consistency when these soils are in a dry
state and which becomes soft to liquid with additionof water [9].

1. INTRODUCTION
1.1 General
An expansive or swelling soil is defined as one whichchanges volume with change in moisture content of
the soil. These soils contain clay minerals of themontmorillonite family as main clay component andthey undergo excessive volume change with change
in their moisture content, that is from dry to wet state.
Deposits of expansive soils occur mainly in dry tomoderately dry regions of the globe and arehazardous to engineering structures because of theirability to swell during rainy seasons and shrink asmoisture decreases [1]-[5]. Their scattering depends
mainly on the geology and genetic of the original
material, climate, hydrogeology and other prevailingconditions. Literature review on expansive soils
reveal that problems arising are somehow common
for all countries and are quite alarming [2]-[4.
Due to the extensive structural damage caused tobuildings and structures by expansive soils, it isimportant that solution to problems related to such
soils be investigated on a common platform andregrouping engineers worldwide because if notadequately treated these materials may become asevere potential hazard [6] - [8].
There are several indications associated with the soil
behavior that help identifying expansive soils. It may
start with a simple visual examination on site. Visual

1.2 Appropriate additives for stabilization of
expansive soils
Lime Stabilization – This technique for ground
improvement is the most popular method forchemicallychanging
unstablesoils
intofundamentally stable construction foundations. The
utilization of lime in soil stabilization enhancesvarious critical engineering properties of the material,
including compressive strength, imperviousness tocrack and decreased swelling.
The addition of lime may not have much effect inkaolinitic clay soils, but rather it can have asignificant impact in clay soils containing
montmorillonite. Expansive clays have a tendency torespond promptly with lime, losing plasticity
instantly. This is due to the fact that montmorillonite
display a high cation exchange capacity, while
kaolinite has a generally low cation exchange
capacity [11]. The addition of lime to a soil initiates a
two stage reaction namely short-term and long-term
reactions. Short-term reactions show their effect rightafter the addition of lime, while long term reactions
are accompanied by a period of time [12] - [17].
Cement Stabilization - Cement is the most traditionalbinding agent since the origin of soil stabilization
108

GEOMATE-Mie, Japan, Nov. 21-24, 2017

5 to 12% depending upon the soil genetics beyond
which strength decreases for obvious reasons.
Cement reaction does not depend on soil minerals as
the most important is its reaction with water, alreadyexisting in the soil mass, but sometimes the moisture
may not be adequate and water has to be added duringstabilizing process. This can be the reason why
cement is used to stabilize a wide range of soils.

technology in 1960’s. It is considered to be a primarystabilizing agent, as it can be used as a single binder
which yields the desired stabilizing reaction [18].
There are several types of cement available in themarket namely ordinary Portland cement, blast
furnace cement, sulfate resistant cement and highalumina cement. Usually the choice of cement
depends on the type of soil to be treated and thedesired final mechanical property [19].
Generally the amount of cement used is small inquantity but sufficient to improve the engineering
properties of the soil. However, cement increases thestrength but may decrease the cohesiveness andcompressibility of the soil.

2. MATERIALS AND METHODS
Raw expansive soil was collected from the northwestern part of the Island of Mauritius or rather the
Ring Road Phase 1 project site, located at Pailles, aregion which is very well known for problematicsoils. The recent problems that have affected the roadstructures after heavy rainfall justify the choice of thelocation. From the soil map of Mauritius the sample
is classified as Dark Magnesium Clay belonging to
the Lauzun family of the Old Volcanic Series deposit[22], [24].
Locally available lime, ordinary Portland cement,
coal fly ash and sieved coarse rock sand are used asstabilizers in this research.
Lime - White hydrated lime of the brand Gluex
supplied by Cape Lime (PTY) Ltd is used. Table 1
shows the chemical and physical properties of thelime used.

Fly-ash Stabilization - Extensive amount of coal arebeing burnt in thermal power stations to meet thegrowing demand for thermal power. About 80% of
the ash formed after burning is fly ash. To reduce theproblems of disposal of fly ash, expensive and tedious
methods are being used and great efforts are being
made to utilize fly ash alternately. The use of coal fly
ash as a stabilizing agent will on one hand help tomitigate environmental problems associated with fly
ash disposal and on the other hand will be beneficial
for enhancing the engineering properties ofproblematic soils [10], [17].
Fly ash is known for its pozzolanic effect. It is asiliceous or alimino-siliceous material with little or no
cementitious content but if finely ground it will reactwith calcium hydroxide to form compounds
possessing cementitious properties [20], [21].

CaO + MgO
80% min
CaO ignited
45% min
CO2
5% max at work
Melting point
580°C
pH
11.8
Density
2.5 g/cm3
Bulk density
0.55 g/cm3
Table 1: Chemical and physical properties of lime.

Coarse sand Stabilization – Not much research work
has been published on the use of sand as a stabilizer
but from the few available studies, it has been provedthat coarse sand can be used as an additive to modify
the particle size distribution in a soil-cement mix [22].
It has been found that an addition of coarse sand tosoils, which constitute mainly montmorillonite asclay mineral, increases the values of the compressive
strengths at the age of seven days by almost 50 %.

Cement - Ordinary Portland Cement of class 42.5,
supplied by Lafarge (Mauritius) Cement Limited, isused as binder in the present investigation withcompressive strength values of 40.03 and 50.94 MPa
after 7 and 28 days respectively, as indicated insupplier specifications.

1.3 Background of soil stabilization
When fly ash or lime is added to an expansive soil,
the latter reduces its plasticity index and swellpotential due to cation exchange which results in an
agglomeration of fine clay particles into coarser
particles. Furthermore, this activates flocculation ofclay particles. On the other hand, cementation process
within the soil-additive mass increases shear strengthand decreases volume change. Hence, the combined
effect of the short term reaction (cation exchange andflocculation) and long term reaction (pozzolanic
reaction) leads to a general improvement of the soil
behaviour. Generally, the amount of additive required
to stabilize an expansive soil may be in the range from

Fly ash - A high percentage of electricity on the islandof Mauritius is produced by burning fossil coal
imported mainly from South Africa. Though aninsignificant percentage of unburnt coal in the fly ash,the latter is quite responsive when added to soil, as
evidenced by results below. Fly ash was acquired
from local sugar cane factory, engaged in the
production of electricity from fossil coal.
Coarse rock sand - Commercially available rock sandof particle size 0 - 4 mm is sieved through a 2 mm
109

GEOMATE-Mie, Japan, Nov. 21-24, 2017

sieve and as such coarse sand of size 2 - 4 mm is usedin the present investigation.

of water is kept constant with the assumption that thechange in OMC for each mix is insignificant.

2.1 Sample preparation
The test specimens were prepared at maximum dry
density (MDD) and optimum moisture content(OMC) obtained for the adopted soil sample inaccordance with BS 1377:1990 [23]. The raw
material (dark magnesium clay) is sieved using a 2
mm aperture sieve to avoid any inclusion of gravels
and the standard Proctor compaction test method isadopted to determine the compaction properties.
Eventually samples for each mix with specificproportion of binder, described below, is preparedand pressed at MDD and OMC. This is achieved bystatically compacting the soil in the mold withapplication of the right amount of energy needed toachieve MDD at OMC [22].

%additive0

Mass of additiveg0

Mass of dry soil
g
92

2.5

2.3

89.7

5

4.6

87.4

7.5

6.9

85.1

10

9.2

82.8

12.5

11.5

80.5

15
13.8
78.2
Table 2: Mass of additive in each sample.
The samples are demolded and allowed to cure in awater-saturated and airtight container for 7 days atroom temperature. After 7 days, the samples are
removed from the airtight container and allowed tocure at room temperature in ambient conditions. They
are tested for their dry unconfined compressive
strengths at the age of 21 days. Fig 1 shows values of
the unconfined compressive strengths of the samples.
Phase II: The additives are now used in paired
combinations with an aim to investigate the behaviorof the mixtures with respect to the characteristic
unconfined compressive strengths of the samples.
Combinations of 2 additives in the ratio of 1:1 areused. The procedure for sample preparation is kept
same as described in phase I above.

2.2 Mixtures.
Phase I: In the first phase of the investigation, rawlime, fly ash, cement and coarse rock sand acquired
from local suppliers in Mauritius are used to prepare
various trial mixes. These are used as partial
replacement of the soil by 0%, 2.5%, 5%, 7.5%, 10%,
12.5% and 15% additive respectively. The soil istreated with each additive individuallyStrength parameter, namely unconfined compressive
strength (UCS) is used to assess the effect of the
inclusion of each additive in the sample of expansive
soil.
As stated above, the soil is sieved through a 2mmsieve to obtain a uniform and homogeneous mix. The
constituents, i.e. soil, stabilizers/combinations andwater are mixed in a mechanical mortar mixer with afixed rotational speed of the helix, in the following
sequence [22]:1. soil and stabilizers/combinations for aduration of 5 minutes
2. water is then added and mixed for an
additional 10 minutes.
For each mix, a set of three cubical specimens 40 mm
x 40 mm x 40 mm are prepared in a mold withdimensions 40 mm x 40 mm and 40 mm high.
Specimens are prepared at varying additive content,
ranging from 0 to 15 %. The maximum dry density
obtained from the standard Proctor compaction test is1.437 g/cm3, volume of mold is 64 cm3 and the OMC
is 30.5%. The mass of soil mix required to fill themold each time is defined as a function of the
maximum dry density, the optimum moisture content
and the volume of the mold which gives 120 g (i.e. 64
x 1.437 x 1.305 g) of blended mix to be pressed in themold at OMC. Table 2 summarizes the mass of dry
soil required for each increment of additive. The mass

3. Results and discussion
3.1 Soil classification parameters
Table 3 summarizes the physical and classification
parameters of the selected soil sample. The highvalues of liquid limit and linear shrinkage are to be
noted as they are indicative of swelling and shrinkage
behavior.

110

Soil Characteristics
Specific Gravity
2.65
Liquid Limit %53.4
Plastic Limit %27.2
Plasticity Index %26.2
Linear Shrinkage %12.1
Optimummoisture 30.5
content %Maximum dry density 1.437
g/cm3
Table 3: Physical and classification parameters of soil
sample.

GEOMATE-Mie, Japan, Nov. 21-24, 2017

have been insufficient for the free migration of clay
particles into the voids.

3.2 Strength properties
Phase I: Single stabilizers by percentage mass usedas soil replacement, as shown in Table 4 below, does
not show a regular pattern in the strength behavior of
the mixtures. However, it is noted that each binder
reacts specifically with the Dark Magnesium Clayand likewise there is an optimum content of eachstabilizer that yields a maximum characteristic
compressive strength. It is noted that 7.5 % lime gives
a maximum value of Compressive Strength equal to
5.5 MPa which is explained by the affinity of lime tothe montmorillonite clay particles.

Table 5: Strength properties of combinations of 2
additives

Table 4: Strength properties with single stabilizer.

Fig 2: Unconfined compressive strength of samples
blended with paired additives.
4. Conclusions
Based on results of the present investigation, thefollowing conclusions are drawn:
1. Dark magnesium clay of the Lauzun family fromthe ancient lava deposits, sampled from the PortLouis region in Mauritius belongs to the class of
expansive soils with liquid limit and linear
shrinkage values in the range of 53.4 % and 12.1
% respectively.

Fig 1: Variation of strength for samples blended withsingle additives.
Phase II: Combinations of two stabilizers are used toinvestigate the combined effect of the latter on thestrength properties of the trial mixes. As mentioned
earlier, samples are tested at the age of 21 days afteran adopted curing regime, described above. Hereagain there is no regular pattern in the strengthvariation of samples with regards to percentage ofbinders but each combination has a characteristic
maximum compressive strength value as shown in
Table 5 below. As evidenced by the results, acombination of 2.5% of coarse sand/fly ash yields a
maximum compressive strength of 5.2 MPa. This is
explained by the fact that apart from the reactivity
effect of the fly ash on the montmorillonite clay
particles, coarse sand provides an appropriate
skeleton to the overall soil mass. Beyond thisoptimum percentage, the mutual effect of thesebinders decreases the characteristic compressive
strength value which may be explained by the factthat the constant amount of water in the mix might
111

2.

Single stabilizers when blended with the
expansive soil under study, do not show a regularpattern in the strength behavior of the mixtures.
The present investigation nevertheless showsthat each binder reacts variously with the Dark
Magnesium Clay and graphs reveal an optimum
content of each stabilizer that yields a maximum
characteristic compressive strength. An optimum
amount of 7.5 % lime gives a maximum value ofcompressive strength equal to 5.5 MPa. This is
explained by the affinity of lime to react with themontmorillonite clay particles. For cement, fly
ash and coarse sand the maximum strength
values of 4.2 MPa, 4.8 MPa and 4.9 MPa occur
at 4.3%, 10% and 12.4% respectively.

3.

In the second part of the present study, the effectof paired combinations of binders in the
expansive soil sample has been investigated. As

GEOMATE-Mie, Japan, Nov. 21-24, 2017evidenced by the results of the current
investigation, a combination of 2.5% of coarse
sand/fly ash blended with the soil under study
yields a maximum compressive strength of 5.2
MPa. This may explained by simultaneous effectof the reactivity of the fly ash with themontmorillonite clay particles and provision ofan appropriate skeleton to the overall soil massby the coarse sand. Further addition of thesebinders decreases the characteristic compressive
strength value which is explained by the constantamount of water in the mix being insufficient for
the free migration of clay particles into the voids.
4.

10. Goodary R, et al. “Effect of Fly Ash on Strengthand Compressibility of Dark Magnesium Clay”
Proceedings ‘Advances in Civil Engineering for
Sustainable Development’. 27-29 Aug 2014:437-442, Thailand.
11. Ferreira, C., Riberio, A. and Ottosen, L., (2003),“Possible Applications for Municipal Solid
Waste Fly Ash”, Journal of Hazardous Materials,
Vol. B96, pp. 201-216.
12. Bell, F.G., (1996), “Lime Stabilization of Clay
Minerals and Soils”, Engineering Geology, Vol.
42, pp. 223-237.
13. Bell, F.G., (1993), “An Examination of the Useof Lime and Pulverized Fly Ash to Stabilize Clay
Materials”, Bulletin of the Association ofEngineering Geologists, No. 4, pp. 469-479.
14. Hilt, G. H., and Davidson, D. T. (1960) “Limefixation in clayey soils” Highway Res. Board
Bull., v.262, pp.20-32.
15. Rao, K.S.S. and Triphaty, S., (2003), “Effect ofAging on Swelling and Swell-Shrink Behavior ofa Compacted Expansive Soil”, Geotechnical
Testing Journal, Vol. 26, No. 1, pp. 1-11.
16. Kinithua, J.M., Wild, S. and Jones, G.I., (1999),“Effects of Monovalent and Divalent Metal
Sulphates on Consistency and Compaction ofLime- Stabilized Kaolinite”, Applied Clay
Science, Vol. 14, pp. 27-45.
17. Nalbantoğlu, Z. and Güçbilmez, E., (2002),“Utilization of an Industrial Waste in Calcareous
Expansive Clay Stabilization”, Geotechnical
Testing Journal, Vol. 25, No. 1, pp. 78-84.
18. Sherwood, P. (1993) “Soil stabilization withcement and lime” State of the Art Review.
London: Transport Research Laboratory,HMSO.
19. EuroSoilStab. (2002) “Development of Design
and Construction Methods to Stabilize Soft
Organic Soils” Design Guide for soft soil
stabilization.
CT97-0351,
EuropeanCommission,
Industrial
andMaterials
Technologies Programme (Rite-EuRam III)
Bryssel.
20. Al-Tabbaa, A. and Evans, W.C. (2005).
“Stabilization-Solidification Treatment andRemediation” Part I: Binders and TechnologiesBasic Principal. Proceedings of the International
ConferenceonStabilization/Solidification
Treatment and Remediation (pp. 367-385).
Cambridge, UK: Balkerma.
21. ASTM, (1993), “Standard Practice for
Characterizing Fly Ash for Use in Soil
Stabilization”, Annual Book of ASTM
Standards, D 5239-92, Vol. 04-08, pp. 12771279.
22. R. Goodary et al. “Investigation of the strength
properties of cement stabilised soils of volcanic
origin” Construction and Building Materials
2012, 28. Pp. 592-598.

Linear shrinkage is found to decrease from 12.1
% for plain soil to 6.1 % for soil blended withadditives which is due to the fact that fly ash
reduces the soil’s plasticity index and swellpotential due to cation exchange which results inan agglomeration of fine clay particles into
coarser particles.

References
1. Simmons, K.B. (1991) “Limitations ofresidential structures on expansive soils”.
Journal of Performance of Constructed Facilities,
5 (4), 258-270.
2. Fredlund, D.G & Hung, V.Q. (2001)”Predictionof volume change in an expansive soil as a resultof vegetation and environmental changes.
Expansive clay soils and vegetative influence on
shallow foundations” ASCE Geotechnicalspecial publications No.116., 24- 43.
3. Fredlund D.G. and Rahardjo H. (1993) ”Soilmechanics for unsaturated soils” John Wiley &Sons, USA.
4. Hyndman, D. & Hyndman, D. (2009) “Natural
Hazards and Disasters” Brooks/Cole, Cengage
Learning, California
5. Mishra, A.K., Dhawan S., Rao, S.M. “Analysis
of Swelling and Shrinkage Behavior ofCompacted Clays” Geotechnical and GeologicalEngineering, Vol. 26, No. 3, pp. 289-298, 2008.
6. Al-Rawas, A.A., Taha R., Nelson, J.D., Al-Shab,
T.B. and Al-Siyabi, H. “A Comparative
Evaluation of Various Additives Used in the
Stabilization of Expansive Soils” Geotechnical
Testing Journal, Vol. 25, No. 2, pp. 199-209,
2002
7. Jones, D. E., and Holtz, W. G. “Expansive Soils- the hidden disaster”, Civil Engineering, ASCE
43(8), pp. 49-51, 1973
8. Terzaghi, K., Peak R.B. and Mesri, G. “Soil
Mechanics in Engineering Practice” 3rd Edition,
John Wiley and Sons Inc., New York, 1996.
9. Wayne, A.C., Mohamed, A.O. and El-Fatih,
M.A. “Construction on Expansive Soils in
Sudan” Journal of Construction Engineering andManagement, Vol. 110, No. 3, pp. 359-374, 1984112

GEOMATE-Mie, Japan, Nov. 21-24, 201723. British Standards Institution BS1377-4.
“Methods of tests for soils for Civil Engineering
purposes” Part 4; Compaction related tests; 1990;
70 p.
24. Proag V. “The geology and water resources ofMauritius”
MahatmaGandhi
Institute;
Mauritius; 1995

113

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LINEAR OPTIMIZATION OF SOIL MIXES IN THE DESIGN OF
VERTICAL CUT-OFF WALLS
Joenel Galupino1, Charlle Sy2 , Jonathan Dungca1, and Anthony Shun Fung Chiu2
1
Civil Engineering Department, De La Salle University, Manila, Philippines
2
Industrial Engineering Department, De La Salle University, Manila, Philippines
ABSTRACT
In order to prevent the contamination of surrounding groundwater in a landfill, cut-off walls were recommended.
Cut-off walls are walls utilized when there is a need to restrict horizontal movement of liquids. Currently, thefactors in designing cut-off walls are effective permeability, and relatively inexpensive materials in containing
contaminants. It was suggested to provide a mix of 96% soil and 4% bentonite in the design of cut-off walls, but
bentonite is relatively expensive, thus the viability of fly ash as a replacement for bentonite was considered. Soil
mixtures were proposed and rigorous laboratory tests was performed to determine the individual properties.
Tests such as specific gravity, Atterberg limit (liquid limit, plastic limit and plasticity index), relative density
tests, particle size analyses, microscopic characterizations, elemental composition tests and permeability tests
were performed to garner data, and were utilized for the model. A linear optimization model was generated toachieve the least cost with the minimum required permeability. The minimum permeability requirement for the
cut-off wall was achieved by providing various mixtures for soil-bentonite-fly ash.
Keywords: Permeability, Fly Ash, Bentonite, Optimization, Linear Optimization
replacement for bentonite was considered. Becauseof its relatively low permeability, bentonite isusually recommended mixed with non-cohesive soil
like silty sand as an encapsulation material [5],however, the utilization of bentonite has made thecost high that is why bentonite is suggested to be
replaced. It was proposed that fly ash is a viablereplacement for bentonite [5]. It is sustainable, since
power plants discharge large amounts of fly ash as
waste but only half of them are used and theremaining half is trashed to land and sea, its disposal
became an environmental concern. The utilization of
fly ash may be a viable alternative for barrier
containment material [6] but on the contrary, flyashes generally consist of silt-sized particles andconsequently possess high permeability [7].
Permeability refers to the susceptibility of a material
to allow fluid to move through its pores. Tests mustbe performed to determine if fly ash may be viable
for a containment material. The main objective of
the study is to determine the most viable
permeability characteristic of the various soil mixesof soil, fly ash and bentonite for cut-off wall.

INTRODUCTION
Nearly a decade ago, the World Bank found that
the San Mateo Landfill located in Rizal Province
and Carmona Landfill in Cavite Province of thePhilippines containing over 23 million cubic metersof corrupting waste were contaminating the groundwater of their nearby vicinities [1]. In order toprevent the contamination of their groundwater, cutoff walls were recommended. In a waste disposal
system, cut-off walls and clay liners (also known as
contaminant barriers) are used to restrict movementof liquids and gases around waste-disposal facilities
or site remediation projects [2]. Cut-off walls arewalls utilized when there is a need to restrict
horizontal movement of liquids. It is also used toprovide an encapsulation for the waste to limit the
inward movement of clean ground water in areas
where groundwater is being pumped or being treated.
It is also used to provide as long-term barrier toimpede contaminant transport. The difference
between cut-off wall and clay liner is that cut-off
wall reduces the contaminant transport in thehorizontal direction [3] while clay liner reduces therate of contaminant transport in the vertical direction
Currently, one of the factors in designing cut-off
walls is to provide an acceptable permeability ofcontaining contaminant. Permeability generally
relates to the propensity of a soil to allow fluid tomove through its void spaces. Baxter [4] suggested
to provide a mix of 96% soil and 4% bentonite in thedesign of cut-off walls, but bentonite is relatively
expensive, thus the viability of fly ash as a

METHODOLOGY
Varying blends were tested to check their
response on the vertical and horizontal permeability,
shown on Table 1.
Each soil mixture underwent rigorous index tests
such as Specific Gravity Test [8], Atterberg Limit
Tests [9], emax test [10] and emin tests [11] andParticle Size Analysis [12].
114GEOMATE -Mie, Japan, Nov. 21-24, 2017

The scanning electron microscopy (SEM) wasused to evaluate the microfabric of soil, fly ash andbentonite. Scanning electron microscopy (SEM)with energy dispersive X-ray spectroscopy(SEM/EDX) is the best known of the surface
analytical techniques. High resolution images of
surface topography are produced using these tests.
Soil particles were described according to theirshape, texture and size.

k = coefficient of permeability, cm/s; Q=
quantity (volume) of water discharged during test,
cm3; l= length between manometer outlets, cm; A =cross-sectional area of specimen, cm2; h = head(difference in manometer levels) during test, cm; t =time required for quantity Q to be discharged during
test, s.
A Linear Optimization Model was also proposedto achieve the optimized mixture that will give an
acceptable permeability value with the least cost.

Table 1. Soil Mixtures of Fly Ash, Soil, andBentonite
Soil
Fly Ash
Soil
Bentonite
Mixture
(%)
(%)
(%)
100FA
100
0
0
75FA25S75
25
050FA50S5050
025FA75S
25
75
0
100S
0
100
0
100B
0
0
100
96S4B
0
96
4
96S4FA
4
96
0
96S2B2FA2
96
2

Manometer

AirWater
Cylinderk=Ql/Aht

Outflow
Collector

Pump

Energy Dispersive X-ray Spectroscopy (EDX)
was used to determine the chemical composition ofeach soil mixture. It is expected to have Oxygen,
Silicon, and Calcium elements. The elemental
composition was in terms of percent (%).
Permeability of the different soil mixes wasdetermined by the constant head test method andfalling head test methods. The direction of flow ofwater is also important, thus, both the vertical andhorizontal orientations of the permeameter wereused. A proposed set-up for the permeameter wasused and modified to determine the horizontal
permeability [13] of the soil mixtures, shown on Fig.
1. The Eq.1 is also used in the analysis. The
following were also considered:
1. It was suggested by Baxter (2004) to use a relative
density of 90% to provide a very dense soil state,thus, the desired void ratio of each soil mix wasdetermined.
2. It was proposed that the pressure head for constanthead permeability test will vary during theexperiment to check if there were differences inpermeability. Three (3) pressure heads were tested
for statistical difference for each soil mix, 200cm,
150cm and the 50cm.
3. The diameter of the soil sample was follow thediameter of the permeameter 2.5in (6.35cm). The
length of the specimen is 10cm to accommodate
the additional porous stones provided.
4. The standard temperature was 20°C. Results werestandardized once the temperature varied.
where:

Permeameter

Fig. 1: Horizontal Permeability Set-up
RESULTS AND DISCUSSIONS
Index Properties and Chemical Properties
The specific gravity of each soil blend wasdetermined. The summary of the specific gravity ofvarious soil mixtures are shown in Table 2.Thespecific gravity of a particular soil shall be reducedby the addition of fly ash [7] since the usual of thespecific gravity of fly ash is low. The addition of fly
ash reduces the specific gravity of a soil mixture,thus we can agree with the statement of Prabakar[14], this is due to the light weight property of fly
ash. Furthermore, it can be noticed that 100B is theheaviest of all the soils. Bentonite being a highdensity material, an increasing weight by adding
bentonite to a soil mix can be noticed.
Table 2. Specific Gravity of Each Mixture
MixtureGs
100FA
75FA25S
50FA50S
25FA75S
100S
100B
96S4B
96S2B2FA
96S4FA

(1)

115

2.02
2.11
2.31
2.49
2.58
2.75
2.61
2.60
2.52

GEOMATE -Mie, Japan, Nov. 21-24, 2017

technical specifications on soil-bentonite trench cutoff wall, they stated that the cut-off wall must haveat least 15% fines content. Fine materials are
particles that passed through #200 sieve during theparticles size analysis test (ASTM D422). Evans[17] agreed that the cut-off wall mix must contain atleast 15% fines to garner a low coefficient of
permeability (commonly less than 9.9x10-7 cm/s)
because the percentage of fines present affects thehydraulic conductivity [18].
Most of the soil properties and characteristics
like strength, compressibility and permeability are
ascribed by its microfabric or microstructure. The
scanning electron microscopy (SEM) was used toevaluate the microfabric of soil, fly ash andbentonite. Scanning electron microscopy (SEM)with energy dispersive X-ray spectroscopy(SEM/EDX) is the best known of the surface
analytical techniques. High resolution images of
surface topography, are produced using these tests.
Pure soils were initially tested to check theirmicroscopic characteristics, mixed soils were also
tested thereafter. In the Energy Dispersive X-ray
Spectroscopy (EDX), chemical composition of soil
is determined to give information on the elements
present in the soil. Oxygen (O) is very abundant,
followed by Silicon (for Silty Sand) and Calcium(for Fly Ash). Silicon and Calcium are predominant
in the soil elemental composition. Due to thepresence of Oxygen and other dominant elements:
Silica (from Silicon), Lime (from Calcium) andAlumina (from Aluminum) are the dominant
minerals in the soil sample.
As shown in Fig. 2, with 500x magnification for
100S, it is a combination of extremely strandy
grains, large angular grains and abundant silt grains
formed the micro fabric. The silt grains have a roughsurface.
The
particlesarewell-gradedmicroscopically. The smaller particles tend to fill thevoids created by the larger particles shown in the
figure, thus creating a smaller inter-particle void.
Looking closer to magnification of 1000x and5000x, strand-like particles are present, his indicatesthat these elongated particles also fill the voids,
giving small passageways for water to permeate.

ASTM D4253 [10] and ASTM D4254 [11] wereused to determine the maximum and minimum void
ratios of the different mixes. It can be noticed from
Table 3, the Maximum Void Ratio (emax) ranges
from 1.78 to 1.99 because the fine contents of the fly
ash contributed to the percentage of voids. 100S has
the lowest value while 100FA has the highest, also
from Table 3, 100S has the lowest fines content,
while 100FA garners the highest. Their fines content
and microfabric may have contributed to theminimum and maximum void ratio. It can be noticed
that the minimum void ratio is much less that thereference [15], this is due to the meticulous
laboratory execution. The allotted time for thevibratory table exceeded to determine the extent of
the minimum void ratio.
Table 3. Summary of emin and emax
Soil Mixture
emin
100S
0.84
100FA
0.27
100B
0.36
96S4B
0.8
50FA50S
0.47
75FA25S
0.37
25FA75S
0.72
96S4FA
0.76
96S2B2FA
0.78

emax
1.78
1.99
1.98
1.80
1.94
1.98
1.93
1.80
1.81

These minimum and maximum void ratios
together with the target relative density of 90% wereused to determine the void ratio to be utilized for thepermeability specimens.
Summary of results from the particle size analyses
are shown on Table 4. 100FA and 100B have thegreatest percentage of fines compared with otherblends. Both soils are considered fines but theclassification differ, fly ash is silt and Bentonite isplastic. It can also be noticed that mixing fly ashwith other soils increases the fines content.
Table 4. Summary of Particle Size Analysis Results%
Soil
Passing
D10
D30
D60
Mixture
#200
100S
21.84
0.01
0.4
1.2
100F
61.83
0.029
0.03
0.04
100B
58.36
0.0022 0.0055 0.032
96S4B
29.33
0.018
0.043
0.125
50FA50S
29.79
0.032 0.0375
0.12
75FA25S
50.78
0.019
0.032
0.06
25FA75S
25.79
0.015
0.042
0.15
96S4FA
22.27
0.035
0.09
0.13
96S2B2FA 23.82
0.03
0.08
0.25

Fig. 2. Microfabric of 100S (5000x, 1000x and 500x
Magnification)
As shown in Fig. 3, with 500x magnification for
fly ash, it is a combination of larger silt grains andsmaller silt grains to form the micro fabric. Fly ash
is a silt thus normally 0.002-0.05 mm in size. As

All soil mixture followed the suggested fines
content. Geo-con [16] provided the complete
116

GEOMATE -Mie, Japan, Nov. 21-24, 2017

seen on the 500x magnification, particles havealmost similar size, forming larger inter-particle
void, compared with silty sand and bentonite, toallow water to pass through. On the 1000x and5000x magnification, the surface of the particle isnot smooth, this create passageway/voids for water
to pass through.

Permeability
A proposed approach utilized in determining thehorizontal permeability of the various soil mixtures
was referred [13] and was modified. Shown in Table
5 is the range of permeability values gathered for thevertical oriented constant head permeability test.
Table 5. Range of permeability values for verticaloriented permeability test
Soil Mixture
Min K, cm/s
Max K, cm/s
100FA
4.51E-05
5.35E-05
75FA25S
2.93E-05
3.97E-05
50FA50S
2.81E-05
2.98E-05
25FA75S
2.05E-05
2.50E-05
100S
1.66E-05
1.90E-05
100B
6.13E-09
2.48E-08
96S4B
1.16E-07
2.98E-07
96S2B2FA
6.90E-07
7.79E-07
96S4FA
1.93E-05
2.40E-05

Fig. 3. Microfabric of 100FA (5000x, 1000x and
500x Magnification)
As shown in Fig. 4, with 500x magnification for
50FA50S, it is a combination of extremely strandy
grains, large angular grains and abundant larger silt
grains and smaller silt grains formed the micro
fabric. The silt grains have a rough surface. Looking
closer to magnification of 1000x and 5000x, strandlike particles are present but not prevalent comparedwith the pure soil, the soil particles may contributeto the reduction of permeability but the silt grains of
fly ash will counteract to allow water to drain faster.

It is clear that the permeability is increased
when the amount of fly ash is increased. It now
agrees with the study by Prashanth [7] that fly ashes
generally consists of silt-sized particles andconsequently possesses high permeability. Thus, theamount of fly ash increases the permeability of thesoil mixes.
Table 6. Range of permeability values for horizontal
oriented permeability test
Soil Mixture
Min K, cm/s
Max K, cm/s
100FA
6.15E-05
7.29E-05
75FA25S
4.19E-05
5.46E-05
50FA50S
3.70E-05
4.34E-05
25FA75S
3.39E-05
3.49E-05
100S
2.25E-05
2.66E-05
100B
1.30E-08
3.53E-08
96S4B
1.65E-07
2.72E-07
96S2B2FA
8.04E-07
9.87 E-07
96S4FA
2.52E-05
2.70E-05

Fig. 4. Microfabric of 50FA50S (5000x, 1000x and
500x Magnification)
As shown in Fig. 5, with 500x magnification for
96S2F2B, it is a combination of extremely strandy
grains, large angular grains, silt grains and elongatedsmooth grains formed the micro fabric. The particles
are still well-graded microscopically. Looking closer
to magnification of 1000x and 5000x, strand-likeparticles are present, this indicates that theseelongated particles also fill the voids, giving small
passageways for water to permeate. Also the smoothsurface of bentonite particles gave a smaller interparticle-void which the permeability is reduced but
counter-acted by the presence of fly ash’s silt grains
which contributed to additional drainage.

The horizontal permeability of the various soil
mixtures is important, because for cut-off walls, it
can discern how long the contaminated water will
penetrate in the horizontal direction. Shown in Table
6, is the range of permeability values gathered forthe horizontally oriented constant head permeability
test.
Soil is the usual majority component of the soil
mixture since the study followed the suggested mix[6] to reduce its cost, the soil excavated from thecut-off wall trench can be utilized as the soil element
for the backfill. If the soil is contaminated or does
not meet the requirements, the excavated soil can beremoved and treated. 100S is not a viable candidate
for the cut-off wall. 100S’ microfabric having a
combination of extremely strandy grains, large

Fig. 5. Microfabric of 96S2F2B (5000x, 1000x and
500x Magnification)
117

GEOMATE -Mie, Japan, Nov. 21-24, 2017

angular grains and abundant rough-surfaced silt
grains contributed to the drainage.
Fly ash is the recommended addition to the soil
mixtures to form the cut-off wall mix, since wastematerials are aimed to be utilized but the addition of
fly ash to soils changes the inter-particle void ratio[14], which is prevalent to the microscopic
characterization test for 100F. It is a combination oflarger silt grains and smaller silt grains to form themicro fabric. Silt particles have almost similar size,
forming larger inter-particle void, contributing to amuch larger inter-particle voids.
Bentonite has low hydraulic conductivity. Its
microfabric usually composed of a combination ofsmooth elongated grains and smaller grains, thus,
smaller inter-particle voids are present.
Baxter [4], 96% soil is mixed with 4% bentonite
to form the cut-off wall mix. In the study, 96S4B
was used as a control specimen and its permeability
is above the minimum requirement of 9.9x10-7 cm/s
for a cut-off wall. It is a combination of extremely
strandy grains, large angular grains and elongatedsmooth grains formed the micro fabric. In its
microscopic structure, strand-like particles arepresent, this indicates that these elongated particles
also fill the voids, giving small passageways forwater to permeate. Since, the attained permeability is
above the minimum required value, fly ash wasincorporated in the mix. Fly ash may increase thedrainage but a certain amount of fly ash can be
added but still attaining the minimum required
permeability.

0 (7)where:
x1 = Amount of Soil;x2 = Amount of Fly Ash;x3 = Amount of Bentonite.
This proposed linear optimization model wasused to achieve the optimized mixture, x1=38.43%
and x2=62.57%, that will give the permeability value
with the least cost.
In order to validate the model, equations 5 and 6
were used. A plot of residuals was considered,shown on Figs. 6 and 7.
Normal Plot of Residuals
99

Normal % Probability

95
90
80
70
50
30
20
10
5

1

-2.07

-0.97

0.14

1.24

2.35

Internally Studentized Residuals

Fig. 6. Normal Plot of Residuals for Equation 5

Linear Optimization Model
To check the effect of fly ash and bentonitewhen added to soil, the mixtures were tested forspecific gravity, soil index property, relative density,
microscopic
characterizations,
elemental
composition and permeability. Many models may
also be considered [20, 21, 22, and 23]. In theprevious study, their permeability values were used
to generate linear optimization model. Equations 2
to 7 are considered in the constraint.

99

95

Normal % Probability

Objective Function: Min. x3 (Bentonite)

Normal Plot of Residuals

(2)

90
80
70
50
30
20
10
5

Constraints:

1

1,

1,

1(3)

-1.96

1(4)
.

.

∗

∗

∗

0.85

1.79

Fig. 7. Normal Plot of Residuals for Equation 6

(5)
.

.

-0.08

Internally Studentized Residuals

.
.

-1.02

CONCLUSIONS AND RECOMMENDATIONS∗

As a criterion in selecting the viable mixture forthe cut-off wall, Baxter [4] recommended that the

(6)
118

GEOMATE -Mie, Japan, Nov. 21-24, 2017minimum permeability requirement of x10-7 cm/s fora cut-off wall. Also, it was suggested to provide amix of 96% soil and 4% bentonite (96S4B) in thedesign of cut-off walls, but bentonite is relatively
expensive, thus the viability of fly ash as areplacement for bentonite was considered. Fly ash is
the recommended addition to the soil mixtures, sincewaste materials are aimed to be utilized. But theaddition of fly ash to soils changes the inter-particle
void ratio [14], it increases the permeability, thus,
the microscopic characteristics of the soil mixtures
may contribute to the increase in permeability. Since,
96S4B’s attained permeability is above theminimum required value, fly ash was incorporated in
the mix. Fly ash may increase the drainage but acertain amount of fly ash can be added and stillattaining the minimum required permeability.
Given the linear optimization model, theoptimized mixture, x1=38.43% and x2=62.57%, thatwill give the permeability value with the least cost
was achieved.

[7] Prashanth, J., Sivapullaiah, P., &Sridharan, A.
(2001). Pozzolanic fly ash as a hydraulic barrierin land fills. Engineering Geology, 60, 245-252.
[8] American Society for Testing and Materials.
(n.d.). Standard Test Methods for Specific
Gravity of Soil Solids by Water Pycnometer.
ASTM D854. ASTM D854.
[9] American Society for Testing and Materials.
(n.d.). Standard Test Methods for Liquid Limit,
Plastic Limit, and Plasticity Index of Soils.
ASTM D4318.
[10] American Society for Testing and Materials.
(n.d.). Standard Test Methods for Maximum
Index Density and Unit Weight of Soils Using aVibratory Table. ASTM D4253.
[11] American Society for Testing and Materials.
(n.d.). Standard Test Methods for Minimum
Index Density and Unit Weight of Soils andCalculation of Relative Density. ASTM D4254.
[12] American Society for Testing and Materials.
(n.d.). Standard Test Method for Particle-SizeAnalysis of Soils. ASTM D422.
[13] Smith, C. B. (2010). Horizontal Permeameter.
Magna Cum Laude Honors Research Project,
University of Florida, Department of Civil andCoastal Engineering, Gainesville, Florida.
[14] Prabakar, J., Dendorkar, N., & Morchhale, R.
(2004). Influence of fly ash on strength behaviorof typical soils. Construction and Building
Materials, 18, 263-267.
[15] Al-Tabbaa, A., & Wood, D. (1991). Somemeasurements of the permeability of kaolin.
Geotechnique, 499-503.
[16] Geo-con. (n.d.). Technical specification of soilbentonite slurry trench cut-off wall. Retrieved
from
Geo-con:http://www.geocon.net/pdf/sbswtech.pdf[17] Evans, J. C. (1994). Hydraulic conductivity ofvertical cut-off walls. ASTM STP 1142 (pp. 7994). Philadelphia: American Society for Testingand Materials.
[18] D’ Appolonia, D. (1980). Soil-bentonite slurry
trench cut-offs. Journal of GeotechnicalEngineering Division, 106(4), 399-417.
[19] Dungca, J., Galupino, J. (2016). Modelling ofPermeability Characteristics of Soil-Fly AshBentonite Cut-Off Wall using Response Surface
Methodology,
International
Journalof
GEOMATE 10, 2018-2024.
[20] Galupino, J., Dungca, J. (2015). Permeability
characteristics of soil-fly ash mix. ARPN
Journal of Engineering and Applied Sciences,15, 6440-6447.
[21] Dungca, J., Galupino, J. (2017). Artificial neuralnetwork permeability modeling, International
Journal of GEOMATE 12, 77-82.

REFERENCES[1] Caplano, J. (2001, December 30). Closed
landfills contaminating groundwater, WorldBank warns. (Philippine Star) Retrieved
November 2013, from Philippine Star:
http://www.philstar.com/nation/145333/closedlandfillscontaminating-groundwater-worldbank-warns[2] Kansas Health Department. (n.d.). Kansas
Health Department Website. Retrieved October
10, 2013, from Kansas Health Department Waste
Management:http://www.kdheks.gov/waste/techguide/EPA_QAQCforWasteContainmentFaciliti
esCH7.pdf[3] Daniel, D. E., &Koerner, R. M. (2007). Vertical
cut-off walls. In A. Press, Waste containment
facilities: Guidance for construction quality
assurance and construction quality control ofliner and cover system (pp. 281-311). Rexton,
Virginia, USA: ASCE.
[4] Baxter, D. Y. (2000, April 14). Mechanicalbehavior of soil-bentonite cut-off wall. Virginia
Polytechnic Institute and Stat University,
Department of Civil Engineering. Blacksburg,
Va: Virginia Polytechnic Institute and State
University.
[5] Daniel, D. E. (1993). Clay Liners. Geotechnicalpractice for waste disposal, 137- 163.
[6] Yehesis, M. B., Shang, J. Q., &Yanful, E. K.
(2010). Feasibility of using fly ash for mine
waste containment. Journal of environmental
engineering, 682-690.

119

GEOMATE -Mie, Japan, Nov. 21-24, 2017[22] Dungca, J.R., Jao, J.A.L. (2017). Strength andpermeability characteristics of road basematerials blended with fly ash and bottom ash,International Journal of GEOMATE 12, 9-15.

[23] Uy, E.E.S., Dungca, J.R. (2017). Constitutive
modeling of coal ash using modified cam clay
model, International Journal of GEOMATE 12,
88-94.

120

SeventhInternational Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EFFECTS OF CUTTING FACE BOLTS IN THE UNCONSOLIDATEDSANDY TUNNEL
Yoshifumi Taguchi 1
Department of Comprehensive Engineering, Urban Environment Course,
Kindai University Technical College, Japan

1

ABSTRACTIn the tunnel excavating unconsolidated sand layer of urban areas, it is important to stabilize the tunnel
cutting face and to control the surface settlement. Therefore, the long face bolts are used frequently. As the effectof the face bolts for the cutting face stability and the surface settlement control, it is thought that reinforcing
effects are different according to length and the interval. In this study, we changed the length and the interval of
the face bolts by the two-dimensional model test used Toyoura-sand and examined the influence level on theeffect of the face stability and the surface settlement. As a result, when the length of the face bolt is longer than
0.3H（H: cutting face height）, the reinforcing effect of the cutting face becomes higher. It is small in length
0.2H. For the surface settlement, when the length of the face bolt is longer than 0.5H, the reinforcing effectbecomes higher. Moreover the face stabilizing effect is higher better installation interval of the face bolt is small.
In bolt’s installation interval 0.2H, face stabilizing effect and surface settlement control effect is high, but bolt’s
installation interval 0.5H is small. In addition, we examined the reinforcing effect and the mechanism of the facebolts by a numerical analysis using the finite element method.
Keywords: Tunnel, Cutting face bolts, Model test, Numerical analysis, Unconsolidated sandy tunnel
the longitudinal direction taken along the center of
the actual tunnel cross section, a rectangular crosssection of the cutting face model is 15cm in heightand 15cm in width. In this test, a cutting face bolt
modeled with a thin Kent paper thicknesses 0.12mm
of a flat plate shape, was placed at a predeterminedinterval in cutting face, as shown in Fig.2 and Fig.3.
The model test reproduced the excavation bypulling out the tunnel cutting face model by a screw
jack. Upon reaching a predetermined pull-out
amount was measured the load acting on the tunnel
cutting face and the surface settlement. The load
acting on the tunnel cutting face sets the load-cell on

INTRODUCTION
In the tunnel excavating unconsolidated sandy
layer in NATM, it is important to stabilize the tunnel
cutting face and to prevent the surface settlement.
For that purpose, the various auxiliary methods oftunnel construction are used, and it becomes theeffective method to drive the long face bolts recently[1]. As the effect of the face bolts for the cutting
face stability and the surface settlement control, it isthought that reinforcing effects are different
according to length and the interval [2-7].
In this study, we changed the length and theinterval of the face bolts by the two-dimensionalmodel test used Toyoura-sand and examined theinfluence level on the effect of the face stability andthe surface settlement [8-9].
In addition, we evaluated the reinforcing effectand the reinforcement mechanism of the face bolts
by a numerical analysis using the finite element
method[10-11].

Front

view

Displacement
gauge

OUTLINE OF MODEL TEST

Cutting face

Sand

Side
view

Sand

Model Test Equipment
A model test equipment shown in Fig. 1. The
size of the soil tank is 65cm in height, 80cm in width,and 15cm in depth. As shown in Fig. 1, Tunnel partof the model is the two-dimensional cross section of

Load cellFig.1 Model test equipment (unit mm)
121

GEOMATE-Mie, Japan, Nov. 21-24, 2017

パッキン

Packing

1mm up to 10 ～ 15mm was carried out. The
measurement of the surface settlement used a
displacement gauge. It was placed in five locationsin the 10cm interval.

鏡ボルト（３段）
Face
bolt model (Kent-paper)
ケント紙でモデル化

50

Pull-out
スクリュージャッキによる引抜きbyjack

Support
支持板
plate

切羽面
Face
ロードセル

Load cell

50

Ｈ＝150

Overview of the Model Test Results

50

Surface settlement (non-face bolt)

150

Figure 4 shows the change in surface settlement
due to tunnel cutting face pull-out when there is noface bolt. The measurement point just above the face,
and front 10cm, 20cm, 30cm and 40cm from thecutting face just above. It is the point of the rear
10cm from the cutting face just above. The surface
settlement of the point of the cutting face
immediately above and the front 10cm is large. With
the pull-out amount of the cutting face increases, thesurface settlement is increasing linearly.

Fig.2 Cutting face part enlarged view (unit mm)

トンネル引抜量（mm）
Pull-out
amount (mm)

地表沈下量（mm）
Surfacesettlement (mm)0

Fig.3 Model test equipment (Photograph)the back side of the tunnel cutting face, wasmeasured change of the load in accordance with thepull-out.
Table 1 shows the case of the model test. The
length of the face bolt model (Kent paper) waschanged 15cm (1.0H, H: cutting face height ofmodel tunnel), 7.5cm (0.5H) and 3cm (0.2H).
Further, the installation interval was changed 7.5cm(1-stage), 5cm (3-stage) and 3cm (5 -stage), it was
examined the influence.
Test case
1
2
3
4

0
1
2
3
4
5
6
7
8
9
10

5

10

Face backward 10cm

切羽後方10cm
Face just above
切羽直上
Face forward 10cm
切羽前方10cm
Face forword 20cm
切羽前方20cm
Face forword 30cm
切羽前方30cm
Face forword 40cm
切羽前方40cm

Fig.4 Surface settlement due to the pull-out(non-reinforced)

Table 1 Case of model test
length（ℓ）
Installation interval
Non-reinforced
15.0cm (1.0H)
1,3,5-stage
7.5cm (0.5H)
1,3,5-stage
3.0cm (0.2H)
5-stage

Model ground was used Toyoura-sand of the airdried state. The model sand was free-fall from theoutlet of a fixed size at the position of the height
60cm, and the model ground was introduced tooverburden thickness 30cm (2.0H). The density ofthe sand is 1.54g/cm3.
The pull out of the tunnel, one by 0.2mm up to 0～2mm, one by 0.5mm up to 2～10mm, one by

The reason for this surface settlement has
increased because its position is within the range ofthe sliding surface of the ground. The surface
settlement amount at the position of the cutting facebehind 10cm and face forward 20cm~40cm is small
and the surface settlement is not significantly
increased even if the pull-out amount of the cutting
face is increased. The reason is because the surface
settlement is not significantly increased in order tothat position the outside than the range of the sliding
surface.
Surface settlement (using face bolts)
Figure 5 shows the change in surface settlement
due to cutting face pull-out in the case of the facebolt installed 5-stage at the installation interval 3cm
and length 15cm. The settlement measurement
points are the same as described above the non-facebolt case. The surface settlement amount of point of

122

15

GEOMATE-Mie, Japan, Nov. 21-24, 2017settlement of about 2mm, increased sharply
settlement just above the cutting face in the case of
1-stage, there is no reinforcing effect. In addition,from these figures, the range of influence of surface
settlement is about face forward 20 ~ 30cm (1.3 ~2.0H).

the face above and face the front 10cm is slightly
larger. The maximum surface settlement at the timeof pull-out 15mm of tunnel face is about 2 mm, thesurface settlement than non-face bolt is considerably
suppressed.
トンネル引抜量（mm）
Pull-out
amount (mm)
5

0
1
2
3
4
5
6
7
8
9
10

10

15

切羽面からの距離（cm）
Distance fromtunnel cutting face (cm)-10

Face backward 10cm

10

20

30

40

切羽後方10cm
Face just above
切羽直上
Face forward 10cm
切羽前方10cm
Face forword 20cm
切羽前方20cm
Face forword 30cm
切羽前方30cm
Face forword 40cm
切羽前方40cm

2
4

8
10
12

Fig.7 Surface settlement curve(Longitudinal direction, on 15mm pull-out)
Figure8 show the surface settlement of tunnel
longitudinal direction of the case changing the facebolt length 15cm (1.0H), 7.5cm (0.5H) and 3cm(0.2H) in installation interval 5-stages.It shows thesurface settlement when pulled out 15mm (0.1H) the
cutting face. In the case of non-reinforcement areabout 7～8mm settlement at the point of the facefront 10cm. Although the settlement amounts of thesame degree in the face bolt length 15cm and length
7.5cm are about 2mm settlement, the control effectof settlement is high. On the other hand, in the facebolt length 3cm (0.2H), settlement amount has been
increased to about 4mm just above tunnel face, thecontrol effect of the settlement is small.

Surface settlement of the tunnel longitudinal
direction
Figure6 to7 shows the surface settlement of thetunnel longitudinal direction in the case of changing
the installation interval of the face bolt when thecase of face bolt length is 15cm (1.0H). The tunnel
cutting face position as 0cm, at the position of theface front 10cm, 20cm, 30cm, 40cm and facebackward 10cm, shows the surface settlement valueof each case.
Figure6 shows the surface settlement when the
cutting face was pulled out 10mm (0.07H). In thecase of non-reinforced, at the point of the face front
10cm from the face above, it is about 4mm
settlement. On the other hand, in 5-stage and 3-stage
hardly subsidence, about 1mm settlement in the face
just above even 1-stage, the surface settlement
control effect is clearly evident.

切羽面からの距離（cm）
Distance fromtunnel cutting face (cm)
-10

0

10

20

30

2
4
6
8

□ Non-reinforced
無補強△ L=15cm,
1-stageℓ=15cm、1段ℓ=15cm、3段○ L=15cm,
3-stageℓ=15cm、5段◇ L=15cm,
5-stage40

Surface地表沈下（mm）
settlement (mm)

-10

0

10

20

30

40

0

Distance fromtunnel cutting face (cm)
切羽面からの距離（cm）0□ Non-reinforced
無補強△ L=15cm,
1-stageℓ=15cm、1段ℓ=15cm、3段○ L=15cm,
3-stageℓ=15cm、5段◇ L=15cm,
5-stage6

Fig.5 Surface settlement due to pull-out(Bolt length 15cm, 5- stage)

Surface地表沈下（mm）
settlement (mm)00Surface地表沈下（mm）
settlement (mm)Surfacesettlement
地表沈
下 量 （mm）(mm)

0

2
4
6
8

□ Non-reinforced
無補強△ L=15cm,
5-stageℓ=15cm、5段○ L=7.5cm,
5-stageℓ=7.5cm、5段◇ L=3.0cm,
5-stageℓ=3cm、5段

10
12

Fig.8 Surface settlement curve(Longitudinal direction, on 15mm pull-out)

10
12

Fig.6 Surface settlement curve(Longitudinal direction, on 10mm pull-out)Among the model test results, Table 2 shows acomparison of the surface settlement of each case.
The comparison position of the surface settlement isthe value of the position of the front 10cm from thecutting face just above. It is shown in detail inreference [8].

Similarly, Figure 7 shows the surface settlement
when pulled out 15mm (0.1H) the cutting face. In
the case of non-reinforcement is about 6 ～ 7mm
settlement at the point of the face front 10cm.
Although the 5-stage and 3-stage have been123

GEOMATE-Mie, Japan, Nov. 21-24, 2017

Moreover, was changed the face bolt’s installationinterval in the 3-stages and 5-stages.

Table 2 Experimental results(Comparison of surface settlement)№

Test case

１
２
３
４
５

Non-reinforced
length15cm, 5stage
length15cm, 3stage
length7.5cm, 3stage
length3cm, 5stage

Table 3 Material properties

Surface settlement (mm)Pull-out Pull-out Pull-out
1.5mm
4.5mm
15mm
0.7
2.0
6.6
0.1
0.2
1.1
0.1
0.2
2.0
0.3
0.8
2.4
0.2
0.5
3.8

GroundFace bolt

1.0ＭＰa1.0×104MPa

Poisson's
ratio

0.3
－

moment ofinertia of area－
1.0×10-7cm4

Non-face bolts
The displacement mode diagram and contour
diagram of the horizontal displacement of theanalysis results are shown in Fig. 10 to 11. Figure 10
is deformation diagram in the case where there is noface bolt, and Fig.11 is a contour diagram of thehorizontal displacement.
From the figure, the cutting face has swelledlarge, if ground strength is low, is expected to leadto face collapse. In addition, from the contour
diagram of the horizontal displacement, it has spreada large area of the horizontal displacement toward
the surface in the direction of the obliquely upward
45 °.

NUMERICAL ANALYSIS
Analysis Method and Model
The analysis used the two-dimensional planestrain elastic analysis by the finite element method.
The analysis model is shown in Fig.9. Although theanalysis of the tunnel face portion is inherently
three-dimensional, used a two-dimensional crosssection in order to correspond to the model tests
described above.
The materials properties used in the analysis areshown in Table 3. The model ground used aquadrilateral element of the 4-node, the face bolt
used a beam element. The bending rigidity of thebeam element was a small value that can not be
resistance to bending due to the use of Kent paper
model test.
In accordance with the above-mentioned model
test, the tunnel excavation was simulated in a waythat extracting the elements of the shaded portion of
Fig.9. The stress release ratio as 100% was carriedout excavation analysis of the tunnel. For boundary
conditions, the soil tank’s bottom is a fixed bothvertical and horizontal directions, tunnel crown was
fixed condition in accordance with the model test.

300

Deformation
ModulusFig.10 Deformation mode diagram (non-face bolt)

Cutting
face bolt
鏡ボルト

450

150

650

150

Fig.11 Contour diagram of the horizontal
displacement (non-face bolt)

800

Fig.9 Analysis model and boundary conditions

Using face bolts

Analysis Results

Figure 12 is a displacement mode diagram of theface bolt’s length 15cm (1.0H) in installationinterval 5-stages. Figure 13 is a contour diagram ofAnalysis was varied with the length of the facebolts 15cm (1.0H, H: face height) and 7.5cm (0.5H)
in correspondence with model test case of Table 1.
124

GEOMATE-Mie, Japan, Nov. 21-24, 2017the horizontal displacement. From this figure, in theface bolt installation position have been suppressedswelling of the cutting face, the amount of horizontal
displacement is smaller. Moreover, the contour
diagram, a large area of deformation does not extend
toward the ground surface, the cutting face is stable,
it is expected that the surface settlement is reduced.
Figure 14 is a contour diagram of the horizontal
displacement of the face bolt’s length 3cm (0.2H) ininstallation interval 5-stages. From this figure, even
if the face bolt has 5-stages, the bolt length is short,
so the amount of horizontal displacement of the
cutting face is large. The reinforcing effect of the
cutting face is small.
Figure 15 is a contour diagram of the horizontal
displacement of the face bolt’s length 15cm (1.0H)
in installation interval 3-stages. From this figure, inthe face bolt installation position, the swelling of the
cutting face have been suppressed a little. It isalmost similar to the case of the face bolt’s length
15cm (1.0H) in Fig13.
Figure 16 shows the axial force diagram of theface bolt. From the axial force distribution, the axial
force is the largest is near the center of the face bolt,
the face bolts are functioning well as the role of theground anchor. The face bolt does not function as aground anchor, if the face bolt is pulled out, the axial
force distribution dose not become indicating amaximum near the center as shown in the figure, thedistribution shape becomes the largest near the
cutting face.

Fig.14 Contour diagram of horizontal displacement(Bolt’s length 0.2H, installation interval 5-stage)

Fig.15 Contour diagram of horizontal displacement(Bolt’s length 1.0H, installation interval 3-stage)

Fig.16 Axial force mode of face bolts(Bolt’s length 1.0H, installation interval 3-stage)
Fig.12 Deformation mode diagram(Bolt’s length 1.0H, installation interval 5-stage)

Comparison of the Model Test
Table 4 is the surface settlement and the cutting
face’s swelling amount in the numerical analysis
results. Comparing the position of the surface
settlement is the position of the face front 0cm ~15cm, was using the maximum value. In the table isalso shown the ratio of the case of no face bolt inparentheses. Because it is elastic analysis the amountof deformation of the ground is proportional to thedeformation modulus E. Therefore, hereafter we
described using the ratio of the no face bolt’s case.
From the two Table of Table 2(above mentioned)
and Table 4, when inserting the face bolts and thetunnel pull-out amount is small in 1.5mm or 4.5mm,
which is an elastic state, the analysis result of theFig.13 Contour diagram of horizontal displacement(Bolt’s length 1.0H, installation interval 5-stage)125

GEOMATE-Mie, Japan, Nov. 21-24, 2017settlement become larger. The poll-out amountbecomes large as 15 mm, the ground is expected to
become a plastic state, as compared to the model test,
the degree of deformation is well reproducible.
Paying attention to the swelling amount of the
cutting face, in the case that the length of the facebolt is short and installation interval is large, it islarger than the trend of surface settlement. However,
the tendency of the reinforcing effect of the lengthand spacing of the face bolt is able to reproduce.
From these results, the numerical analysis of the facebolt using the elastic analysis can obtain an analysis
result of the safety side with respect to thereinforcing effect of the cutting face bolt.

REFERENCES[1]The Japan Geotechnical Society, “Toconstruction from the design of the mountaintunnel construction method”, 2007, pp.140-141.
(in Japanese)[2]Fukusima S, Mochizuki Y,Kagawa K,
Yokoyama A, “Model test on pre-reinforcementof shallow tunnel in sandy ground ” , Japan
Society of Civil Engineers, No.406, Ⅲ -11 ，JUN.1989,pp.79-86.(in Japanese)[3] Taguchi Y, Kagawa K, Sagara M, Yoshikawa K,“Reinforcing effects of thin flexible pre-lining”, Japan Society of Civil Engineers, No. 645,Ⅲ-50,Mar.2000, pp.125-135. (in Japanese)[4]Mitarasi Y, Matsuo T,Tezuka T,Okamoto
T,Nisimura S,Matsui T,”Evaluation of effect oflong face reinforcement method in tunneling”,
Japan Society of Civil Engineers, No.743,Ⅲ-64，
SEP.2003,pp.213-222.(in Japanese)[5]Miyanomae
S,Morita
A,Sakai
T,MatsuiM,Nasimoto Y,Okubo S, “A proposal of thesimplified model to evaluate the effect of long
bolting”, Journal of Japan Society of Civil
Engineers, Ser. F,vol.62,No. 2,APR.2006,pp258267(in Japanese)[6]Domon T, Seo K, Nishimura K, ”Simplified
design method for face bolting based on thereinforcing effect”, Journal of Japan Society of
Civil Engineers, Ser. F1,Tunnel Engineering, vol.
66, No. 1,NOV.2010,pp.29-39.(in Japanese)[7]Yokota Y,Yamamoto T,Date K, ”Evaluation ofreinforcing effects on new face bolts using steal
checker pipes by centrifuge model tests and 3Dnumerical analysis”, Journal of Japan Society of
Civil Engineers, Ser. F1,Tunnel Engineering, vol.
67, No. 3,2011 ,pp.67-79.(in Japanese)[8] Taguchi Y, Tanaka T,” Model test on the effectof reinforcing the face bolt in unconsolidated
sand tunnel”, Kindai University TechnicalCollege Research Reports, vol.4, JAN.2011,
pp.79-84. (in Japanese)[9] Taguchi Y, Tabira T, ”Model test on tunnel facestabilizing effect of the face bolt”, Kindai
University Technical College Research Reports,
vol.6, MAR.2013,pp.71-76.(in Japanese)[10] Japan Society of Civil Engineers,”Practice ofmodel experiments and numerical analysis in themountain tunnel”, 2006,pp.22-59. (in Japanese)[11] Taguchi Y, ”Model Test and Numerical
Analysis on the Effect of the Length and Intervalof the Face Bolt in Sandy Tunnel”, Proceedingsof Second International Conference on Science,
Engineering & Environment, Nov.2016, pp.328333.

Table4 Result of numerical analysis№

Test case

１
２
３
４
５

Non-reinforced
length15cm, 5stage
length15cm, 3stage
length7.5cm, 3stage
length3cm, 5stage

Result of numericalanalysis (mm)Swelling
Settlementof face0.28(1.0)
3.3(1.0)0.08(0.3)
1.1(0.3)
0.12(0.4)
2.0(0.6)
0.19(0.7)
2.6(0.8)
0.22(0.8)
2.4(0.7)

CONCLUSION
The two-dimensional longitudinal direction of
the model tests using Toyoura -sand, was examined
influence of the surface settlement by changing the
installation interval and the length of the cutting facebolts. Moreover, we examine the reinforcing effectand the reinforcement mechanism of the cutting facebolt using a numerical analysis method by the finite
element method. As a result, it was found that thefollowing.
Compared to the model test results, in theregion where the tunnel pull-out amount is small andthe natural ground seems to be within the elastic
range, an elastic analysis result has a bigger ratio of
the settlement. When the pull-out amount of the
cutting face is as large as 15mm, and the groundbecomes the plastic state, the elastic analysis results
show the same tendency as the model test results.
For the elastic analysis, the swelling amount of the
cutting face is larger in the case that the length of theface bolt is short and installation interval is large.
The numerical analysis of the face bolt using
the elastic analysis can obtained of the safety side
analysis results with respect to reinforcing effect of
the natural ground deformation by the cutting face
bolt.

126

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PHYSICAL MODELING OF PROPOSED POROUS DRAINAGE
SYSTEM TO SOLVE INUNDATION PROBLEM
Ahmad Rifa’i1, Noriyuki Yasufuku2
Faculty of Engineering, Universitas Gadjah Mada, Indonesia; 2, Faculty of Engineering, Kyushu University,
Japan

1

ABSTRACTPost rain inundations that occurred in Prambanan Temple yard interfere the visitor’s mobility and heavyequipment that operated for restoration activities in the temple. A typical porous drainage system was proposedusing waste material from Merapi eruption to reduce the inundations. Research on the characteristics of thewaste material becomes important due to the availability of so many supplies from these materials and it has notbeen utilized optimally. A full scale of physical modeling experimental test, with a modified equipment todetermine the performance of the porous drainage system, was proposed in this study. Physical modeling of theporous drainage system is expected to represent the actual conditions in the field. The ground water level was
designed in two conditions, deep ground water level based on the natural field condition and shallow groundwater level that is an extreme condition that may occur in the field. In this test, rainfall simulator was built toflow the discharge constantly into this physical modeling. The effectiveness of this system amounted to 20% of
the drainage capacity in natural field condition during the rainfall duration of 2.183 hours. In the extreme
condition, the effectiveness of the system amounted to 75% of the drainage capacity during the rainfall durationof 2.383 hours. It shows that the porous drainage system is quite effective when applied at Prambanan Temple
yard that has an average rainfall duration of 2.375 hours. The proposed porous drainage system is expected tosolve the inundation problem in Prambanan Temple yard.
Keywords: Post Rain Inundations, Physical Modeling, Porous Drainage Systemdominated by sandy soil. The water level conditionis on 12 meters under the soil surface. One ofsolution that can be conducted is by creating adrainage system that able to reduce runoff byinfiltration through porous media of a porous
material [1].

INTRODUCTION
Prambanan Temple yard is divided into threestages, with the main stage of Prambanan temple
complex is located on the first yard. The first yard of
Prambanan Temple is the main destination for
tourists to enjoy the beautiful view. But in these last
few years, the convenience of the tourism activity inthe first yard of Prambanan Temple was quite
disturbed due to the water inundations that always
occur during the rainy season. Inundation thatappears after rainfall in certain parts in the first yardof Prambanan Temple, as shown in Fig. 1, is one ofissues that must be solved. Cultural Heritage
Institution of Prambanan Temple attempted toreduce the inundation problem by adding a special
soil above the original soil layer, so that the groundis not expected to quickly become saturated, free of
dust, and it is not a growing medium of grass.
Moreover, some drainage channels have added on
Prambanan Temple yard to reduce the potential
inundations of water occurrences, but this treatment
is still not effective. To preserve this cultural site
and keep the convenience of visitor’s mobility, itneeded some solution to organize and improve thedrainage systems to reduce the inundated area.
According to the soil stratification data, as shownin Fig. 2, the soil layer in Prambanan temple yard isFig. 1 Inundation that occurs in the yard of
Prambanan Temple.
127

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 2Stratification of soil layer [2].

In addition, to obtain the high permeability
material, a porous medium in the drainage system
also serves to reduce the water pressure, prevent
erosion, and prevent soil particles transported by thewater flow. An alternative porous medium
application is the utilization of porous drainage
channels and porous paving block as an access roadfor visitors which considered to solve theinundations. Both of these alternatives are used inthis study to optimize the drainage system and tosolve the inundations problem. In this study,
physical modeling of drainage system based on field
condition parameter was conducted. This study
focused on the effectiveness of the proposed
drainage system with a physical model that has
adapted to the conditions in Prambanan Temple yard.
Reference [3] has conducted research on
utilization of low strength aggregate or Bantak andvolcanic ash for drainage porous. Bantak andvolcanic ash are used in no fine concrete as the main
substituting material. The materials are used as abasic calculation of the total requirement of drainage
material for producing of porous concrete samples.
A numerical analysis model of the drainage channel
was conducted and the distance between the nearest
channels is 7.48 m. In addition to the distance
between the channels, a typical channel model was
proposed and shown in Fig. 3.
In addition to the porous drainage channels, toreduce inundation that caused by lack of water
infiltration into the soil, porous paving blocks can be
an alternative construction for pavement, especiallyfor sidewalks, open parking area, etc. Reference [4]has conducted research on utilizing Bantak andvolcanic ash to porous paving block in the handlingof drainage at Prambanan temple page. The test
results of the characteristics of porous paving blocks
can be seen in Table 1. In [4], the model testing
was conducted in an acrylic box with an area of 50
cm by 50 cm to get the value of the original soil
permeability coefficient and porous paving block.
This modeling was also performed on the normal
paving block as a comparison. The calculation resultof infiltration based on the data modeling results canbe seen in Table 2.

Fig. 3

Proposed drainage system by [3].

Table 1 Characteristics of the porous paving blockusing volcanic ash [4].
Characteristic
Specific gravity (kN/m3)
Compressive strength (MPa)
Porosity (%)
Permeability (m/s)

Value
16.80
5.72
28.40
1,93 x 10-2

Table 2 Hydraulic properties of the soil and paving
block [4]Parameter

Soil

Normalpavingblock

Porouspavingblock

Permeability(m/s)
Infiltration
capacity (m)Infiltration
velocity (m/s)
Runoff (m)Inundations
time (hour)

5.8 x 10-6

1.3 x 10-5

1.1 x 10-4

4.2 x 10-2

1.1 x 10-1-

7.5 x 10-6

1.4 x 10-5-

8,8 x 10-2

1,6 x 10-2

-

3,2

0,3

-

RESEARCH MATERIALS AND METHODS
Three-dimensional physical modeling was
conducted in this study to validate theoretical resultsthat have obtained through a mathematical
calculation. In the physical modeling, detailed
planning with analytical calculations is needed inorder to build a physical modeling that represents
the actual conditions in the field. Physical modelingcan use the full scale or can be scaled from theactual conditions taking into account the scale factor.
Detailed figure of a porous drainage system was
proposed by [3]. Typical porous drainage channels
that have been made by previous researchers thenmodified into a physical model in a scale of 1:1, thatshown in Fig. 4.

128GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 4

Physical modeldrainage system.

ofproposeda layer of impermeable because the water does notflow out and the water that seeps through thephysical modeling test stuck in the bottom layer.
Meanwhile, to simulate actual field conditions, thewater valve at the bottom of the box was opened andthe flow rate is set in accordance with the soil
conditions in the field. Permeable layer conditions
on the bottom of the porous drainage are made bymaking a puddle in advance at the box support ashigh as the bottom limit of the soil layer, then open
the valve outlet of 8.7 ml/sec with assumption thatthe value of the discharge that comes out of thevalve outlet is the same discharge in the modelingtest. At the same time simulation of rain still running.
The observations focused on the direction ofwater flow and time to achieve the highest
inundation level at 75% of the drainage capacity insaturated soil conditions. Changes of water content
to determine the saturated condition was maintainedby using soil moisture sensor devices. Groundwaterflow direction can be visually seen when conducting
this physical modeling. When the rain simulationequipment conducted, the time monitoring start.
Furthermore, every inundation of 2 cm in porous
drainage, the elapsed time is recorded until thealtitude target. The simulation equipment was
stopped when rain inundation on a porous drainage
has reached 75% of the porous drainage height, thenthe elapsed time is recorded.

porousRESULTS AND DISCUSSIONS

Fig. 5In the shallow ground water level conditions,when rainwater simulation equipment was
conducted and the surface of the soil in physicalmodeling start to wet, at that time the rain time
calculation begins. The valve is opened by setting a
constant flow of 14 ml/sec. This value is obtained
from the calculation using 5 times of the rain
intensity on the field that is equal to 70 mm/hour (>60 mm/hour) and classified as the category of very
heavy rain [5]. It used 5 times of the normal
intensity because the intensity of rainfall simulationequipment was limited, so it used the higher rain
intensity that can be seen visually and the represent
the rain in the field. The process of physicalmodeling test is executed when the soil reaches thesaturated condition and based layers as deep as 20
cm below the drainage porous consideredimpermeable. This impermeable layer is aninterpretation of extreme field conditions where thesoil is saturated with a high water level.
The results of the physical modeling test are time
and water level contained in porous drainage.
Observation of the water level in porous drainage
every 2 cm to 26 cm, obtained from the 75% of thedrainage capacity. The observations are then madein the form of a graph as shown in Fig. 6.

Experimental test apparatus.

Physical modeling testing of the porous drainage
process begins with regulating the flow of rain
simulation equipment, water discharge arranged
until approaching rainfall conditions in the first yardof Prambanan Temple as shown in Fig. 5. Water
discharge released from the rain simulationequipment is 14 ml/sec assuming the typical heavy
rain. This water discharge represents the rain
intensity about 70 mm/hour where it is 5 times
higher than normal intensity obtained from the fielddata that equal to 14 mm/hour. Water discharge flow
through a pipe that has been hollowed and the slopeof the pipe needs to be taken to ensure that water canflow as expected. There are two conditions in thistest, shallow ground water table for the criticalcondition and deep ground water table that
represents actual field conditions.
Conditions of shallow ground water table can bemodelled using an impermeable layer on the bottomof the porous drainage. It is made by letting an
empty space at the bottom of the modeling box filledwith water. The condition is considered to represent

129GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 6

Recapitulation of physical modelingobservations with impermeable layer

Fig. 7

Recapitulation of physical modelingobservations with permeable layer

Fig. 8

Testing results of the decreasing water levelin porous drainage with permeable layer

From Fig. 6, it can be seen that the time required
for the water level every 2 cm is not constant. It
appears there was a decrease in significant time
when the water level of 6 cm to 8 cm and shows thewater flowing into the drainage porous faster. Afterthe water level height above 8 cm time required
every 2 cm relatively constant, although there are up
and some going down but not too significantly. The
test data obtained from the time required for porous
drainage inundation heights of 26 cm for 2 hours 23
minutes or 2.383 hours with rainfall intensity 5 times
the normal intensity that is equal to 70.55 mm/hour.
Data on the average duration of rainfall that
occurred in the first yard of Prambanan Temple
based on previous research that is over 2,375 hours.
Thus the porous drainage system can be said to beeffective for the treatment of inundation occurred in
the first yard of Prambanan Temple despite heavy
rain conditions (intensity of> 60 mm/hour).
On the deep ground water level condition, after
the rainwater discharge valve is opened to dischargeof 14 ml/sec with the intensity of 72 mm/hour
interval of ± 10 minutes the water had penetrated theupper surface of porous drainage. With the soil
conditions in the experimental test equipment weresaturated and the water level at the bottom has been
setting the limit as high as the bottom layer of soil,
the results showed after waiting 1.5 hours, groundwater level touches the bottom of the porous
drainage. After the water reached the base of theporous drainage, then did a calculation of increasing
inundation over time as shown in Fig. 7.
Based on Fig. 7, it can be seen every change oftime elevation of inundation rose by 2 cm, and thenaveraged summed it takes about 20 minutes perincrement inundation of 2 cm on porous drainage.
So the speed of inundation in porous drainage was
0.1 cm/min. Of the total duration of the rain occurs
about 2 hours 11 minutes gained inundation heighton drainage pore of 7.5 cm from the inner surface
drainage. So, in a case of rain with an intensity of 72
mm/hour for 2 hours 11 minutes, the condition isstill very efficient drainage as a reservoir andseepage of rain. It is shown at an inundation height
still 20% of the total of the level.
Decreasing water level is only performed on apermeable layer, which assumed that the water could
flow down. Water level decreasing test in porous
drainage, simulating when the rain was stopped but
the discharge outlet remains open in accordanceflow of water in the soil is 8 ml/sec and the positionof the state remain saturated soil conditions. The test
results can be seen in the graph shown in Fig. 8
below concluded that the rate of decreasing waterlevel per 0.5 cm takes 1.203 minutes. From theresults of this study concluded drainage catchment
speed is 0.416 cm/min.
In decrease testing inundation in the porous
drainage, rain simulation was stopped but the130

GEOMATE - Mie, Japan, Nov. 21-24, 2017

discharge outlet remains open in accordance
groundwater flow that is 8 ml/sec and the position of
the state remain saturated soil conditions. The test
results can be seen in the graph below, inundation
concluded that the decrease rate every 0.5 cm takes
1.203 minutes. It can be concluded from the speed ofthe drainage catchment is 0.416 cm/min.
Fig. 9 shows in the direction of flow that occurs
in the physical modeling of the porous drainage
system. Running physical modeling to determine
groundwater flow direction was made during a field
dry conditions up to saturated soil conditions. Basedon visual observations, the direction of flow on
physical and mathematical modeling there is no
significant difference, with it can be assumed thatthe input and output physical modeling andnumerical modeling is correct. Conditions on
groundwater flow above using rain discharge of 20
ml/sec to the direction of flow as shown above. In
the picture, shown in number 1-6 as the change inshape of the flow of time. The initial condition isshown in number 1 and number 6 shows the final
condition. In numerical modeling using Finite
Element Method is modeled with the same soil
conditions such as conditions on the modeling ofphysical test equipment. Results of running thesoftware SEEP/W is shown in Fig. 10. It was
concluded from a comparison of both models show
the direction of flow which is not much different
shape.

constant and even tends to decrease. This is possible
because of the influence of the horizontal flow ofwater coming into the porous drainage increased.
Comparison of flow direction on physical modelingwith Finite Element Method is not too significant.

Fig. 9Pictures direction of flow in modeling tools
experimental test

CONCLUSIONS
After testing on modeling of porous drainage
system with the condition of the ground water levelin accordance with the conditions of the field, theresults obtained by 7 cm water level from lower
surface drainage within 139 minutes. This showsthat the porous drainage system used is quite
efficient in streaming and storage of rain waterrunoff intensity 5 times the average rainfall intensity
in the field. The time required for each increase of
the water level in the drainage porous 1 cm nearly
constant. This is possible because of the influence
horizontal water flow coming into the porous
drainage changed and influenced also by the alreadysaturated ground conditions. The duration for thedecrease in drainage porous inundation with a heightof 0.5 cm takes 1.203 minutes. This is possible
because the permeability of the non-sand concretedrainage density is very high and the soil densitythat is not so dense.
On the condition of the shallow ground watertable below the drainage system obtained results
height of inundation by 26 cm within 2.383 hours of
this suggests that the drainage system is porous
enough used effectively in reservoir drainage andwater runoff. The time required for each increase of
the water level in the drainage of 2 cm is not

Fig. 10 Vector direction of water seepage on
numerical modeling
REFERENCE[1] Bhutta MR, Tsuruta K, Mirza J, “Evaluation ofHigh-Performance Porous Concrete Properties”,
Construction and Building Materials, Vol. 31,
Jun. 2012, pp. 67-73.
[2] Rifa'i A, “Sifat Teknis Tanah dan Struktur
Fondasi Candi Wisnu dalam Tinjauan
Geoteknik, in Proc. PIT-XIII HATTI
Development of Geotechnical Engineering in
Civil Construction, 2009, pp. 45-53. (InIndonesian Language)[3] Rifa’i A, Lestari NP, Yasufuku N, “Drainage
System of Prambanan Temple Yard Using Nofine Concrete of Volcanic Ash and Bantak
131

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Merapi”, International Journal of GEOMATE,
Vol. 11, Sept. 2016, pp. 2499-2505.
[4] Rifa’i A, Yasufuku N, “Utilization of Bantak
and Merapi Volcanic Ash for Porous Paving
Block as Drainage Control in The Prambanan
Temple Yard”, International Journal of
GEOMATE, Vol. 12, Mar. 2017, pp. 141-146.
[5] Sosrodarsono S, Takeda K, “Hidrologi untuk
Pengairan”, 9th ed. Pradnya Paramita, 2003, pp.
7-8. (In Indonesian Language)

132

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EFFECT OF HEATING-WETTING CYCLES ON ROCKPERMEABILITY
1

Ivan Gratchev1, Jeremy Stephens 2 and Dong Hyun Kim 3
Griffith School of Engineering, Griffith University, Australia; 2,3 Griffith University, Australia
ABSTRACTHigh temperatures that exist in rock mass can affect the properties of rocks, resulting in the formation of new
discontinuities or expansion of the existing cracks. Such changes in the rock structure would likely influence thewater flow in rock mass, which may undermine the rock storage capacity. This study seeks to investigate the effectof high temperatures on rock permeability. Fresh and weathered rock samples of argillite were subjected to heating
and wetting cycles under the laboratory conditions to simulate the impact of high temperatures on rock mass. Aftereach cycle the rock permeability was determined and compared with its initial value. It was found that as thenumber of heating-wetting cycles increased the coefficient of permeability of rock specimens also increased.
However, this change depended on the initial rock properties and the number of heating-wetting cycles. The
observed increase in permeability was attributed to the changes in the rock structure caused by the heating-wetting
process.
Keywords: Rock permeability, Heating-wetting procedure, Laboratory testing, Argillite(diameter 50 mm) (Fig. 1) from the Neranleigh–Fernvale Beds formation [5-6], Gold Coast, Australia
were used in this research. Two fresh specimens (F1and F2) and two slightly weathered specimens (W1and W2) were subjected to the same testing procedurethat consisted of 3 heating and wetting cycles.

INTRODUCTION
Variations in temperature and moisture content
tend to affect the mechanical properties of rocks
through the initiation of new or developing alreadyexisting cracks [1]. It is already known that 1) heating
and cooling of rock can generate fractures through thethermal expansion and contraction [2], and 2) thisprocess can close or open the existing fractures [3]. A
better understanding of the effect of temperature onrock material is extremely important for underground
waste repositories including nuclear waste. It is vitalto contain the waste by preventing any leakage ofhazardous material that can contaminate thesurrounding environment. Although rocks are
generally considered hard material with very low
permeability, it can increase or decrease dependingon the behavior of fractures under high temperatures.
For example, recent studies [4] indicate that
extremely high temperatures of 800-900C resulted inlower values of permeability (by nearly four orders ofmagnitude) as the thermal stresses closed the existing
fractures.
It is clear that temperature-induced changes in therock structure would likely influence the fluid flow inrock mass, which may affect the rock storage
capacity. This study seeks to better understand theeffect of high temperatures on rock permeability.

Fresh rock

Weathered rockFig. 1

A view of the fresh and slightly weatheredrock used in this study.

Before testing, each specimen was enclosed in a
concrete mould (diameter 150 mm) with fiber
reinforcement as shown in Fig. 2. Silicone sealant
was used to separate the rock from the concrete mould
to ensure that the specimen permeability is notaffected by the concrete.
Rock permeability tests

TESTING PROCEDURE

To conduct a permeability test, the permeability
apparatus with a 50-mm diameter O-ring was
positioned on top of the specimen and clamped down
to the specimen as shown in Fig. 3. To begin the test,

Rock specimens used
Four borehole core specimens of argillite
133

GEOMATE - Mie, Japan, Nov. 21-24, 2017

the data recorded after each heating-wetting cycle. As
can be seen in Fig. 4, the initial permeability of therock was relatively low; that is, about 1x10-6 m/s forF1 and 5x10-7 m/s for F2. It is also clear from Fig. 4that the heating-wetting process resulted in higher
values of permeability for each specimen. It isinteresting to note that for F1, a change in thepermeability was much greater compared to F2. It isalso evident from this figure that the coefficient of
permeability of both specimens (F1 and F2) tends toincrease with an increasing number of heatingwetting cycles.

a pressure of 500 mBar was applied and the volume
of water permeated through the rock specimen wasmeasured every minute. The test continued for 15 minwhen only limited variation in pressure (less than 1%)
was observed.

Rock

Silicone sealantFig. 2

Coefficient of permeability, m/s

Concrete mould
Specimen preparation for the permeability
tests.

Permeability
apparatus
Clamp

Fig. 3

Coefficient of permeability, m/s

Rock specimen
Experimental setup used for a series ofpermeability tests.

Heating-wetting cycles
After the initial permeability test was conducted,
the specimen was left to dry before starting the firstheating cycle. The specimen was placed in an ovenfor 24 h at a temperature of 105C. The specimen wasthen taken out of the oven and left in a controlledenvironment to cool before being submerged in
distilled water (at a room temperature) for 24 h. The
final stage of the heating cycle was to remove thespecimen from the distilled water and let it dry for 24
h under controlled temperature (20C) conditions.
After each heating-wetting cycle, a permeability test
was conducted to investigate the effect of the heatingwetting process on rock permeability. In addition,
visual observations of the rock surface were
performed after each cycle to study the influence ofhigh temperatures on the crack formation anddevelopment.

Fig. 42.0E-05(a) Specimen F1

1.8E-05

Initial
Cycle 1
Cycle 2
Cycle 3

1.6E-05
1.4E-05
1.2E-05
1.0E-05
8.0E-06
6.0E-06
4.0E-06
2.0E-06
0.0E+00

03

1.4E-05

6

9Time (min)12

Initial
Cycle 2

1.2E-05
1.0E-05

15

Cycle 1
Cycle 38.0E-06
6.0E-06
4.0E-06
2.0E-06
0.0E+00(b) Specimen F2
0

3

6

9

Time (min)12

Results from a series of permeability tests on
the fresh specimens of argillite: (a) specimen
F1, and (b) specimen F2.

A similar tendency was observed for the slightly
weathered rock specimens (W1 and W2). The initial
permeability was as low as the one observed for the
fresh specimens: W1 – 1.4x10-7 m/s, and W2 –3.5x10-7 m/s. In addition, the coefficient of
permeability of both specimens increased as theheating-wetting procedure continued. It is noted thatfor W1, a significant increase in the permeability
occurred after the third heating-wetting cycle while
for W2, the increase appeared to be more gradual.

RESULTS AND DISCUSSIONS
Permeability test results
Three heating-wetting cycles were performed andthe obtained results for the fresh specimens of F1 andF2 are given in Fig. 4 as the variation of coefficientof permeability with time. This figure also presents
134

15

Coefficient of permeability, m/s

GEOMATE - Mie, Japan, Nov. 21-24, 2017

8.0E-06

6.0E-06

Coefficient of permeability, m/s

Cycle 1
Cycle 3

5.0E-06
4.0E-06(a) Specimen W1

3.0E-06
2.0E-06
1.0E-06

0.0E+00

Fig. 5Initial
Cycle 2

7.0E-060

3.0E-0 6

3

6

9

12

Time (min)(b) Specimen W2

2.5E-0 6

Initial
Cycle 215

Cycle 1
Cycle 32.0E-0 6

New cracks

1.5E-0 6
1.0E-0 6

Surface breakage

5.0E-0 7
0.0E+0 0

(a)
0

3

6

9

12

Time (min)Coefficient of permeability, m/s

(b)

15

Results from a series of permeability tests on
the slightly weathered specimens of argillite:(a) specimen W1, and (b) specimen W2.

Crackdevelopment

The summary of all permeability tests is given in
Fig. 6 as changes in the coefficient of permeability
with increasing heating-wetting cycles. It can beinferred from this figure that the initial coefficient of
permeability of all specimens (both fresh and slightly
weathered) was similar (about 1-3x10-7 m/s), and it
increased after each heating-wetting cycle.

Fig. 6

examined after each cycle. The surface of F1 (thespecimen that exhibited the largest increase in thecoefficient of permeability) is shown in Fig. 7a(before the heating procedure) and Fig. 7b (after thethird heating-wetting cycle). The change in the rocksurface was quite pronounced and can be described asfollows: a) a central part of the surface was chipped
due to the heating process, b) some minor cracks
appeared on the surface as well. Such changes were
believed to lead to a higher coefficient of
permeability which was observed for F1. For theslightly weathered rock W2 (Fig. 7c), discolorationand some increase in the crack length were observed
as a result of heating-wetting (Fig. 7d).

Discolouration

2.0E-06
F1

F2

W1

W2

1.0E-06

5.1E-070

1

2

Number of cycles(d)Fig. 7

A view of the specimen surface. F1: a)before the heating-wetting cycles, and b)
after the third heating-wetting cycle. W2: c)before the heating-wetting cycles, and d)after the third heating-wetting cycle.

CONCLUSION

1.5E-06

1.0E-08(c)

3

Summary of permeability tests for the freshand slightly weathered specimens ofargillite.

Visual observations of rock surface
To better understand the effect of the heatingwetting process on the permeability of the tested
rocks, the surface of each specimen was visually135

A series of permeability tests were performed oncore specimens of argillite which were subjected tothree cycles of heating and wetting. The following
conclusions can be drawn:- The permeability of the tested rocks,
regardless of their weathering degree (freshor slightly weathered), was found to be low,in the range of 1 to 3x10-7 m/s.
- The heating-wetting process caused someincreaseinrockpermeability(approximately by one order of magnitude).
This increase was observed for all tested
rocks.
- The increase in the coefficient of
permeability was mainly attributed to theformation of new cracks or extension of theexisting ones. These cracks were observedon the surface of each tested specimen.

GEOMATE - Mie, Japan, Nov. 21-24, 2017[4] Gaunt H, Sammonds P, Meredith P, Chadderton
A, “Effect of temperature on the permeability oflava dome rocks from the 2004–2008 eruption of
Mount St. Helens”, Bulletin of Volcanology, Vol.
78 (4), 2016.
[5] Kim DH, Gratchev I, Balasubramaniam A,“Determination of joint roughness coefficient(JRC) for slope stability analysis: a case study
from the Gold Coast area, Australia”, Landslides,
Vol. 10 (5), 2013, pp. 657-664.
[6] Shokouhi A, Gratchev I, Kim DH, “Rock slope
stability problems in Gold Coast area, Australia”
International Journal of GEOMATE, Vol. 14,
2013, pp. 501-505.

REFERENCES[1] Takarli M, Prince W, Siddique R, “Damage in
granite under heating/cooling cycles and water
freeze–thaw condition”, International Journal ofRock Mechanics and Mining Sciences, Vol. 45(7), 2008, pp.1164-1175.
[2] Fredrich J, Wong T, “Micromechanics ofthermally induced cracking in three crustal
rocks”, J. Geophys. Res., Vol. 91(B12), 1986, pp.
12743-12764.
[3] Cooper H, Simmons G, “The effect of cracks on
the thermal expansion of rocks”, Earth andPlanetary Science Letters, Vol. 36 (3), 1977,
pp.404-412.

136

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A SIMPLIFIED METHOD FOR ESTIMATING COEFFICIENT OF
EARTH PRESSURE AT REST (K0) IN COHESIVE SOILS
Premkamol Thuennadee and *Kritika Trakoolngam
Faculty of Technology, Khon Kaen University, Thailand
ABSTRACT
Various geotechnical engineering problems require the value of coefficient of earth pressure at rest (K0) for
determining the in situ stress and designing engineering structures. At present, most available empiricalmethods for estimating this value are based either on the plasticity index or friction angle. These methods arewidely used and proven to be quite accurate. In this paper, we propose a more simplified method to estimate
K0. The parameters of basic physical properties that influence the value of K0 were statistically analyzed using
data from 3,900 cohesive soil samples. An empirical formula was developed based on the water content,
specific gravity, and bulk density. The finalized relationship shows that the value of K0 is a function of thespecific volume. Values of K0 resulting from the new equation were compared to that from the equation
proposed by Massarsch (1979) which is based on the plasticity index. The maximum, minimum, and average
error is 5.00%, 0.00%, and 2.00%, respectively. In conclusion, this new empirical method can estimate K0
values in a much simpler way using the soil’s specific volume without the need to determine the plasticity
index or the friction angle.
Keywords: Coefficient of lateral earth pressure, Cohesive soil, Empirical method
variations using the Rankine active earth pressure
coefficient [9] and the Poisson’s ratio [10].
Interestingly, very few solutions were proposedfor determining K0 of normally consolidated
cohesive soils. The first was proposed by Brooker
and Ireland in 1965 [3] based on the Plasticity Index(PI) asINTRODUCTION
The coefficient of lateral earth pressure at rest
(K0) is a parameter required for determining the insitu lateral earth pressure which is necessary fordesigning many underground engineering works.
The values of K0 can be obtained from laboratory
tests, in situ tests, theoretical analysis, or empiricalmethod. The latter is the most popular approachsince it is most convenient and inexpensive.
Theoretically, the value of K0 can be determinedfrom an elastic solution based on the Poisson’s ratio(  ) as in

K0 


1 

K 0 = 0.04 + 0.007 (PI) ; PI = 0 - 40%(2)

K 0 = 0.64 + 0.001 (PI) ; PI = 40 - 80%(3)

Later in 1979, Massarsch [11] proposed a more
widely accepted formula which was able todetermine K0 at all ranges of PI(1)

K 0  0.44  0.42  PI 

The first empirical solution for determining thevalue of K0 was proposed for cohesionless soils by
Jaky [1] in 1944 which was then simplified,allowing for some loss in accuracy, in 1948 [2].
Both solutions are based on the friction angle of thematerial. To date, Jaky’s simplified solution is still
the most widely used although there have been
several authors presenting solutions based on thefriction angle of the soil as well [3]-[7].
For overconsolidated clays, the first solution
was presented by Schmidt in 1966 [8] which was
based on the Overconsolidation Ratio (OCR), thefriction angle, and the K0 in its normallyconsolidated state. Later on, other formulas were
proposed based on the OCR as well but with some

(4)

RATIONALE

Good predictions of K0 for cohesionless soils
are obtained from solutions based on the friction
angle. However, formulas that use friction angles
are accurate for only cohesionless soils and thosethat are accurate for cohesive soils use the plasticity
index which are inapplicable to cohesionless soils.
A formula that can solve for both cohesive andcohesionless soils accurately would be preferable.
Furthermore, being able to account for OCR would
be ideal. This leads to finding a solution that is notdependent on the friction angle nor the plasticity
index.
OBJECTIVE AND SCOPE
137

GEOMATE - Mie, Japan, Nov. 21-24, 2017

soil sample.

Our long term goal is to develop a formulawhich can solve K0 for both cohesive andcohesionless soils accurately and is based on basic
physical properties (independent of friction angle
and plasticity index).
In this paper we focus on obtaining a solution
for cohesive soils first. The concept is to use
Massarsch’s 1979 solution as a model and derive aformula that is comparable.

Soil type
Unit
1 Moisture Content%
2 Particle Density
kg/m3
3 Bulk Density
kg/m3
Dry
Density
4
kg/m3%
5 Plasticity Index%
6 Clay%7 SiltSand%
8%
9 Gravel
Note: Parameters not relevant to this study are notlisted.

APPROACH
Data Acquisition and Filtering

Secondary data consisting of laboratory tests
results were collected from the GeotechnicalEngineering Department, Mae Moh Mine,
Electricity Generating Authority of Thailand. The
data consisted of various soil types, therefore, it had
to be filtered to obtain cohesive soil samples. The
initial criteria being samples consisting of clay andsilt fraction more than 50%. A total of 3,900 records
of cohesive soil samples were obtained. According
to the USDA soil texture triangle [12] the samples
can be classified into 6 types as shown in Table 1.
Each sample comprises of laboratory test results
which consist of 9 individual parameters as shownin Table 2.

RESULT
Proposed Simplified Solution

The resulting formula for determining K0 ofcohesive soils is found to be based on the bulk
density (Db), water content (w), and specific gravity(GS) as follow

 G 1  w  
K 0  0.38  0.102  S

Db



Table 1 Types of soil samples classified according
to the USDA texture triangle
Soil type
1. Clay
2. Clay loam
3. Loam
4. Silty clay
5. Silty clay loam
6. Silt loam
Total

(5)

The above equation can be written in the formof the specific volume (V) or void ratio whicheveris preferred

Number of samples
2,358
95
153
1,137
105
52
3,900

K 0  0.38  0.102V 

K 0  0.38  0.102 1  e 

(6)
(7)

Analysis of the Proposed Solution

Values of K0 from the new solution is comparedto that of Massarsch’s solution as shown in Fig.1
The maximum, minimum, and average error ofK0 from the new solution is 5.00%, 0.00%, and
2.00%, respectively. In order to confirm theaccuracy of the solution, an analysis of the error was
conducted. The dependent variables are plottedagainst the error of K0 as shown in Figs.2 to 5.
It can be seen that samples with specific volume
between 1.20 and 2.00 do not affect the error of K0.
However, specific volume values are limited due tothe nature of the soil samples, therefore, it cannot
yet be concluded that specific volume values higher
than 2.00 would result differently. Bulk density,
water content, and specific gravity also do not show
any influence on the error of K0. However, errors
may increase at high water content (more than 30%)
but this is inconclusive with the available data.

Data Analysis

Each parameter listed in Table 2 wasstatistically analyzed compared to the plasticity
index which is Massarsch’s main variable fordetermining K0.
Three parameters were found to strongly
influence the values of plasticity index and K0, theseare, bulk density (Db), water content (w), andparticle density (used as an alternative to thespecific gravity, GS).

Table 2 Available laboratory test result for each138

GEOMATE - Mie, Japan, Nov. 21-24, 2017

0.650
0.600

K0

0.550
0.500
0.450
0.400

K0 Thuennadee, 2017
K0 Massarsch, 1979

Various data points

Fig.1 Comparison between values of K0 obtained
from Massarsch’s formula and that of the new
proposed formula.

Fig.4 Values of water content and the resulting errorof K0 compared to Massarsch’s solution.

Fig.2 Values of specific volume and the resulting
error of K0 compared to Massarsch’s solution.

Fig.5 Values of specific gravity and the resulting
error of K0 compared to Massarsch’s solution.

Fig.3 Values of bulk density and the resulting errorof K0 compared to Massarsch’s solution.

Fig.6 Values of total clay and silt fractions and theresulting error of K0 compared to Massarsch’ssolution.

Limitations of the Proposed Solution

5.3.2 Activity

5.3.1 Particle Size

The activity of the clays according to Skempton[13] was calculated fromThe effects of the amount of clay and silt on theerror of K0 is presented in Figs.6 to 8. Fig.6 showsthat the error of K0 is not influenced by the amountof clay and silt of more than 50%. However, Fig.7
and 8 show that error increases with clay fraction
less than 20% and silt fraction more than 60%.

A

139

PI
%Clay fraction (weight)(7)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The samples were found to have activity below
1.25. Therefore, the soil samples are categorized as
normal clays.
ACKNOWLEDGEMENTS
The authors are truly grateful for the valuable
data given by the Geotechnical Engineering
Department, Mae Moh Mine, Electricity Generating
Authority of Thailand.
REFERENCES[1] Jaky J, "The coefficient of earth pressure atrest", Journal of the Society of Hungarian
Architects and Engineers, Vol. 7, 1944, pp.
355-358.
[2] Jaky J, "Pressure in soils", in Proc. 2nd
International Conference on Soil Mechanics
and Foundation Engineering, Vol. 1, 1948, pp.
103–107.
[3] Brooker EW and Ireland HO, "Earth pressuresat rest related to stress history", Canadian
Geotechnical Journal, Vol. 2(1), 1965, pp. 1-15.
[4] Feda J, "K0-coefficient of sand in triaxial
apparatus",
Journalof
GeotechnicalEngineering-Asce, Vol. 110(4), 1984, pp. 519524.
[5] da Fonseca AV and Sousa JAE, "At rest
coefficient of earth pressure in saprolitic soils
from granite", in Proc. Fifteenth International
Conference on Soil Mechanics andGeotechnical Engineering, 2001, pp. 397-400.
[6] Guo PJ and Stolle DFE, "Fabric and particle
shape influence on K-0 of granular materials",
Soils and Foundations, Vol. 46(5), Oct 2006,
pp. 639-652.
[7] Wanatowski D and Chu J, "K-0 of sandmeasured by a plane-strain apparatus",
Canadian Geotechnical Journal, Vol. 44(8),Aug 2007, pp. 1006-1012.
[8] Schmidt B, "Discussion of ‘Earth pressures atrest related to stress history’ by Brooker &Ireland (1965)", Canadian Geotechnical
Journal, Vol. 3(4), 1966, pp. 239-242.
[9] Pruska MJ, "Effect of initial stress on the
stress-strain relation", in Proc. 8th International
Conference on Soil Mechanics and Foundation
Engineering, Vol. 4, Moscow, 1973, pp. 26-28.
[10] Wroth CP, "In situ measurement of initialstresses and deformation characteristics", inProc. In Situ Stress Measurement of Soil
Properties, North Carolina State University,
Geotechnical Engineering Division, 1975, pp.
181-230.

Fig.7 Values of total clay fraction and the resulting
error of K0 compared to Massarsch’s solution.

Fig.8 Values of total silt fraction and the resulting
error of K0 compared to Massarsch’s solution.
CONCLUSION
A simplified formula for determining the valueof coefficient of lateral earth pressure at rest (K0) ispresented in Eq.6. The solution is dependent on thespecific volume which can be easily determined in
the laboratory. Since it is not dependent on theplasticity index, the application of this formula canbe extended to cohesionless soils and especiallysoils that are ambiguous in its cohesiveness. There
are several important notes to be made:(1) The maximum, minimum, and average errorof K0 from the new solution is 5.00%, 0.00%, and
2.00%, respectively. The accuracy is assumed tocorrespond with the accuracy of Massarsch’ssolution and currently applies to cohesive soils.
(2) The formula is applicable to soils withnormal clays. Active clays are expected to result
differently, therefore, using this formula is notrecommended.
(3) Although K0 values are comparable to thoseobtained by Massarsch’s solution, validation
against laboratory or in situ data is necessary and isan ongoing process.
(4) The applicability of this solution tocohesionless soils is still under investigation.
140

GEOMATE - Mie, Japan, Nov. 21-24, 2017[11] Massarsch KR, "Lateral Earth Pressure inNormally Consolidated Clay", in Proc. Seventh
European Conference on Soil Mechanics andFoundation Engineering (Design parameters ingeotechnical engineering), Vol. 2, Brighton:
British Geotechnical Society, 1979, pp. 245249.
[12] United States Department of Agriculture,"Texture Triangle and Particle-Size Limits of
AASHTO, USDA, and Unified Classification
Systems", National soil survey handbook, title

430-VI. USA: United States Department ofAgriculture, 2016.
[13] Skempton AW, "The Colloidal Activity ofClays", in Proc. Third International Conference
on Soil Mechanics and Foundation
Engineering, Vol. 1, Switzerland, 1953, pp. 5761.

141

Seventh International Conference on Geotechnique, Construction Materials and

GEOMATE- Mie, Japan,
Nov. 21-24,
2017 2017, ISBN: 978-4-9905958-8-3 C3051
Environment,
Mie, Japan,
Nov. 21-24,

A STUDY ON PERMEATION CHARACTERISTICS OF
MICRO PARTICLES INTO SAND
Yukoh Hasunuma1, Kentaro Uemura1
Takamitsu Sasaki2, Koichi Nagao3, Shunsuke Shimada4
Tsuyoshi Tanaka1, Naoaki Suemasa1
1
Tokyo City University Graduate Division, Japan; 2Kyokado Engineering co.,Ltd, Japan;
3
Sato Kogyo, Japan; 4 Kyokado co.,Ltd, Japan
ABSTRACTIn this study, Bubble White was proposed as a new grouting material for a chemical grouting method, which
is a mixture of silica micro-particles and micro bubble water. By injecting the Bubble White into ground, it was
expected to increase the effectiveness of preventing ground from liquefaction. However, it is not common to
improve granular soil by injecting a suspended grout solution containing micro particles since it is difficult tosecure a sufficient improved diameter by this method. Therefore, the penetration properties of micro particles to
the ground have not yet been sufficiently clarified. In the previous research, the permeability characteristics undera constant pressure were investigated by the injection experiments using unprepared sand specimens. In this report,
therefore, we examined the penetration characteristics when injected at a constant rate. As a result of theexperiments, it was confirmed that the permeability of micro particles depended on both injection rate and injection
volume.
Keywords: Micro-particles, Micro bubble, Liquefaction countermeasures
INTRODUCTION
previous studies, injection experiments wereconducted to investigate the injection properties,
where silica micro particles were injected into
saturated sand specimens at a constant pressure [2].
According to the test results, it was found that when
the injection pressure was high, the micro particles
flowed in the voids of the soil particles and permeatedthroughout the specimen, and the concentration
distribution became substantially uniform. On theother hand, when the injection pressure was low, themicro particles tended to clog in the voids resulting in
an increase in the concentration of the micro particles
near the injection port. In addition, it was also
revealed that the liquefaction strength improved byinjecting Bubble White increased compared to theunimproved case [3]. Since a constant pressure wasset for the previous injection experiment, this study
focused on the injection rate.
In this report, therefore, a constant rate wasprovided during the injection experiments to get moredetailed information about the permeability.

Since approximately 75% of Japan is mountains
and forests, the Japanese economy has beendeveloped mainly around the coastal areas andlandfill was used to supplement lacking developable
plains. However, liquefaction strength of the landfill
is low. By the Pacific coast of Tohoku Earthquake that
occurred in 2011, the landfill such as Urayasu city,
Chiba Prefecture suffered from large-scaleliquefaction damage and it became a social problem.
Liquefaction has been a serious problem in Japanfor a long time and many technical countermeasuremethods have been developed until now. However,since most of the methods generally used forliquefaction countermeasures need large-scaleconstruction machinery, it is difficult to improve thegrounds in narrow places such as residential land. In
addition, the construction in a narrow place requires
a high cost per unit area in comparison with that in alarge place [1]. Accordingly, it has been demanded todevelop a method with a low cost and better
operability. In this study, Bubble White is proposed asa new grouting material for a chemical grouting
method, which is obtained by mixing silica micro
particle and micro bubble water.
It is not common to improve granular soil byinjecting a suspended grout solution containing micro
particles since it is difficult to secure a sufficient
improved diameter by this method. For that reason, it
is essential to clarify the injection characteristics of
micro particles and the liquefaction strength in sandspecimen improved by the micro particles. In the

NEW GROUTING MATERIAL BUBBLE WHITE
Photo. 1 shows micro bubbles pouring in a beaker.
As the characteristics of the micro bubbles, thesurface area of micro bubbles is quite large incomparison with that of a normal air bubble with thesame volume. Also, the bubbles have an advantagethat they tend to rise slower and accordingly diffuse
horizontally. The micro bubbles can reduce both
142

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ONE-DIMENSIONAL INJECTION EXPERIMENT
Conditions of Experiment
A series of experiments were carried out with theaim of confirming the difference in injection behavior
when different void ratios and different injection rates
were provided. During the experiments, silica micro
particles were injected into saturated sand specimens
at a constant rate. Fig.2 and Fig.3 show the schematicof injection experiment, and grain size accumulation
curves of micro particles and silica sand #5. Table 13 show the physical properties of silica sand #5, theconditions of specimens and the conditions ofexperiments, respectively. The specimens wereprepared by an air-pluviation method so as to become
50 cm in height and 5.0 cm in diameter, and the void
ratios of Case 1 and Case 2 were 0.84, and those of
Case 3 and Case 4 were 0.80, respectively.
In order to prevent from clogging of micro
particles in pipes of experimental equipment, filter
media were installed at the top and the bottom of thespecimen, which are constituted of a plurality of glass
beads having a diameter of about 1 cm and a plate
having a large number of holes with a diameter ofabout 1.5 mm.
Additionally, the specimens were completely
saturated by permeating CO 2 and degassed water into
the specimens.

Photo. 1 Micro bubbles
saturation degree and pore water pressure in the
ground during an earthquake [4].
The silica micro particles are white and powdery,
containing silicon dioxide as a main component. The
micro particles used for this experiment wereindustrially produced amorphous silica and classified
so that the average particle diameters became about
20μm. By injection of the silica particles, the densityof ground increases. In addition, the silica particles
are viscous enough to stay in the voids of ground.
They can increase the density of ground efficiently.
Fig.1 shows an image of the improvement effect of
bubble white. By combining these excellent
materials: the micro-bubble water and the silica
micro-particles, it was expected to increase theeffectiveness of preventing ground from liquefaction[5].

Fig. 1 Improvement effect of bubble white
As described above, although constant pressures
were applied to the specimens and the injection
behavior was investigated through the previous
experiments, the injection characteristics of the micro
particles have not yet been sufficiently clarified. Thistime, therefore, focusing on the injection rate, thepurpose of the experiments was set to confirm theinjection behavior when the injection rate wasconstant.
Fig. 2 Schematic of injection experiment143

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The injection material was a suspended grout
solution whose concentration of silica fine particles
dissolved in water was adjusted to 6% by weight.
Here, the injection rate in Table 2 shows the flow rateof water when draining directly from the injection
device. In addition, in order to measure the change ofwater pressure with time elapsed, water pressuregauges were installed at two places; one was theconnection part between the injection device and thespecimen and the other was the drain part of thespecimen. Columns of the specimens can be divided
by 10cm each and concentration distributions of fineparticles in pore water were measured after injection
experiment was completed.

Results of Experiment(1) Comparison of cases with low injection rate
Fig. 4 shows the relationship between injection
volume and pressure head in case of a low injection
rate. The chain line shown in the figure is a line drawn
to obtain a gradient of the injection volume at theinitial stage of injection. At first, the two cases with
low injection rates were compared. The comparison
between Case 1 and Case 3 showed very similartendencies, while their void ratios were different. In
Case 1, although the pressure increased immediately
after injection started, the increase in pressure began
to decrease after the injection volume became 300
cm 3. The previous studies showed that the injectedparticles tended to clog more at a low injection
pressure rather than at a high injection pressure [2].
Therefore, it was assumed that the micro particles
adhered to the voids of the soil particles were swept
away due to the high injection pressure at the initialstage in Case 1. As the increase in pressure was also
suppressed after the injection volume reached 300
cm 3 in Case 3, it was presumed that Case 3 has asimilar tendency to Case 1. However, a largepressure fluctuation was seen even after that point inCase 3. It was likely that since the void ratio of Case
3 was smaller than that of Case 1, the particles tended
to clog in the voids and flowed intermittently. After
that, the pore water was completely replaced with theinjection material and the injection behavior became
temporarily stabilized. Meanwhile, the micro
particles were continuously accumulated andaccordingly the pressure kept on increasing until thecompressor of the injection device stopped working.
Fig. 5 shows the relationship between
concentration ratio and permeation distance in caseof low injection rate. In this figure, the index C / C0
is the ratio of C; the concentration of pore water to
C0; the initial concentration of material in injected
mixture. From the comparison between Case 1 andCase 3, it was confirmed that the concentration ratioof Case 3 was lower than that of Case 1. However,almost no difference was seen in the final injection
volume between Case 1 and Case 3. Therefore, thisresult seems to be caused by the fact that the void
was small and tended to be clogged by micro
particles in Case 3. That is, there is a possibility thatthey could neither flow through the voids nor
sufficiently accumulate in some parts of thespecimens because the fine particles clogged in thevoids. In addition, high concentration of pore waterin the vicinity of the injection port of the specimen
was likely to be caused by clogging of the fineparticles because the permeability of the micro
particles appeared to greatly changed influenced by
the characteristics of the experimental apparatus.

Table. 1 Physical properties of silica sand #5

ρssilica sand #5

ρ max

ρ min

(g/cm )

3(g/cm )

(g/cm )

2.640

1.555

1.300

3

3

Table. 2 Conditions of specimens
case

case1

case2

case3

case4

silica sand #5

samplediameter (cm)5.0height (cm)50.0void ratio
3

void volume (cm )e=0.84e=0.80448.19438.58

Table. 3 Conditions of experiments
case

case1

case2

case3

injection material

silica micro particles

concentration of
injection material

6.0%

3

injection rate (cm /sec)

4.35

22.21

4.35

case4

22.21

Fig. 3 Grain size accumulation curves of micro particles
and silica sand #5
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

injection volume approximately constant. The total
volume of injected material was about 2.7 times asmuch as the volume of pore water in the specimen ofCase 2. In Case 4, on the other hand, sudden pressure
fluctuation was seen before replacing the pore waterof the specimen and the compressor of the injection
device stopped when the pore water was replacedwith injected material. According to the result of Case2, it can be seen that the pressure rose almost
constantly until the injected material completely
replaced the pore water of the specimen. Thereafter,
the pressure fluctuation became large. The pressure
fluctuation was likely to be caused by the repeatedphenomenon in which injected micro particles were
temporarily clogged between sand skeletons, and thenremoved and transported to another place due to highpressure injection.

(a) case1(b) case3

Fig. 4 Relationship between injection volume andpressure head in case of low injection rate(a) case2

Fig. 5 Relationship between concentration ratio andpermeation distance in case of low injection rate(b) case4(2) Comparison of cases with high injection rate

Fig. 6 Relationship between injection volume andpressure head in case of high injection rate

Fig. 6 shows the relationship between injection
volume and pressure head in case of high injection
rate. The injection pressure changed after replacing
pore water with injected material in Case 2. After thechange of the pressure, although the injection volume
decreased slightly, it was possible to keep the145

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 7 Relationship between concentration ratio andpermeation distance in case of high injection rate

Fig. 8 Relationship between injection volume andcoefficient of permeability k’

Fig. 7 shows the relationship between
concentration ratio and permeation distance in case ofhigh injection rate. As shown in the figure, thevariation was large compared with the case where theinjection rate was low. In the case where the injection
rate was high, it was presumed that the skeleton of thesoil particle was disturbed by the flow of the injection
material because the injection pressure was high. The
tendency of accumulation of micro particles changed
due to minute turbulence of the soil particle skeleton
and therefore the concentration of pore water became
varied. However, it was confirmed that the micro
particles penetrated into the specimens sufficiently
since the concentration ratios were distributed ataround 1.0 as a whole.

CONCLUSIONSIn order to investigate the penetrability of micro
particles, a series of one-dimensional injection
experiments with a constant injection rate was carriedout in this paper. The following conclusions wereobtained from the experiments.
1) Since the pressure increased almost constantly
when the injection rate was constant, it is presumed
that the micro particles were continuously
accumulated.
2) It was suggested that the permeability of micro
particles varies depending on the injection amountsince an increasing tendency was seen in the pressure
at the time when the injection volume reached thevoid volume of the specimen.

(3) Comparison of permeability of injection material
Fig. 8 shows the relationship between injection
volume and a coefficient of permeability k’. In thisfigure, the index k’ is defined as the injection rate of
the injection material divided by the hydraulicgradient. Since this value is different from the actual
coefficient of permeability for water, it is denoted ask’. As shown in the figure, k’ tended to depend on
injection rate and injection volume. k’ tended to behigher as its injection rate became higher. The
tendency is considered to be due to the fact that the
micro particles are more likely to become clogged
because the injection pressure becomes lower as theinjection rate is lower. The comparison between Case
1 and Case 3 showed a small difference immediately
after the start of injection. However, the two cases
showed similar behavior, and the k’ value almost
agreed with each other. Similarly to the case with low
injection rate, the two cases with high injection rate
showed similar behaviors. In case 4, however, after k’fluctuated largely, the injection became impossible. It
is thought that the pressure fluctuation showed thatclogging occurred.

3) Although the concentration of injection material
showed a slightly higher tendency near the injection
port, the specimens were uniformly improved in thecases the flow rates were constant throughout theexperiments and a sufficient amount of injection
material was injected into the specimens.
4) It was suggested that there is a possibility that thesoil skeleton of specimen could be broken by
injection with a high rate.

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REFERENCES[1] The commission related to earthquake proof
countermeasure of residential development in Kanto
Branch of The Japanese Geotechnical Society (2013)“The briefing session relate to earthquake proof
countermeasure of residential development -a
guideline to protect residence from liquefaction-,”
Kanto Branch of The Japanese Geotechnical Society,84-85[2] Uemura K, Naoaki S, Takamitu S, Koichi N(2016)” The Injection experiment on penetration
characteristics of micro particles” Proceedings of the71th Annual Conference of the Japan Society of Civil
Engineers, 479-480[3] Hasunuma Y, Kentaro U, Naoaki S, Takamitu S,
Koichi N (2016)” A study on injecting micro bubble
water mixed with crushed silica” Sixth International
Conference on Geotechnique , Construction
Materials and Environment, Bangkok, GEOMATE,
162-167[4] Koichi N, Naoaki S, Tosiyuki K, Saeka
Y(2015),‘‘Applicability of soil improvement withusing Micro-Bubbles mixing water against soilliquefaction’’ Proceedings of the 70th Annual
Conference of the Japan Society of Civil Engineers,395-406.
[5] Shota M, Kentaro U, Naoaki S, Takamitu S,
Koichi N(2015), ‘‘Ultrafine particles of silica
grouting method for liquefaction countermeasure ’’
Proceedings of the 50th Annual Conference of The
Japanese Geotechnical Society, 307-308.

147

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

OPTIMUM USE OF GEOGRID IN THE UNBOUND GRANULARLAYER FOR THE PAVEMENT CONSTRUCTIONAUNG AUNG SOE1, Jiro KUWANO2, Ilyas AKRAM3 and Takaya KOGURE4
Department of Civil and Environmental Engineering, Saitama University, Japan

1,2,3,4

ABSTRACTThe benefits of using geogrid for the pavement construction have been reported by many researchers. The wellknown benefits are base course reduction and rut-depth reduction. Currently, the available information is still
limited for the geogrid-stabilized pavement construction. In this study, the benefits of geogrid stabilization were
investigated through series of laboratory test. Base-course thickness and reinforcement position of geogrid wereconsidered as the control parameters and their influences were analyzed on the surface and subgrade deformations.
The tests were performed in a rigid square-tank, and the subgrade and base course were modelled by using the fineand coarse silica sands. Triangular geogrid was used for the reinforcement. Cyclic loading was applied with thevariable steps of loading ranging from 100 kPa to 550 kPa. From the test results, it was realized that the surface
deformation was mainly contributed from the subgrade deformation in the thin base-course sections. In contrast,
the base-course deterioration dominated and resulted in severe surface deformation in the thick base-course
sections. This severe deformation was effectively reduced when geogrid location was shifted to the upward
position inside base course layer. However, this geogrid position has negligible influence on the subgrade
deformation, which is considerably affected by the base-course thickness. In all test cases, a progressive loss inbase course thickness was noticed under high footing pressure. This loss is smaller in the thin section, comparedto thick one. Test results revealed that the benefit of geogrid stabilization is more obvious in the thin section.
Keywords: Pavement, Base Course, Subgrade, Deformation, Geogrid Position

INTRODUCTION

size of aggregate material become important for thelateral restraint mechanism.
Since there are several types of geogrid, such asuniaxial geogrid, biaxial geogrid and triangulargeogrid (also called multiaxial geogrid), lateral
restraint mechanism will be different depending on
the geogrid type. For the recently developed
triangular geogrid, there is limited information
regarding the reinforcement mechanisms. Therefore,
it becomes necessary to know the reinforcement
behavior of this triangular geogrid. In this study, acommercially available triangular geogrid (TX160)
was selected and its reinforcement behavior was
examined by conducting large scale laboratory model
test. Regarding the reinforcement position in basecourse layer, the optimal placement position of thegeosynthetic depends on the thickness of the basecourse layer and the applied load magnitude,according to S. W. Perkins [4]. Thus, current study
also focused on the reinforcement position in the
granular layer in order to know the optimum use ofgeogrid in the unbound granular layer, together withdifferent base-course thicknesses under the cyclicloading of variable load magnitudes.

Geosynthetic materials have been widely used in
the geotechnical engineering applications due to theirbeneficial improvements. Depending on theapplications and purposes, there are several types ofgeosynthetic materials, such as geocell, geotextile
and geogrid. Among them, geotextile and geogrid aremainly applied in the flexible pavement constructions
in order that the design service life of pavement could
be extended and/or the amount of base course
materials could be reduced.
The key functions of geotextiles in improving
flexible pavement performance are separation,
reinforcement, and filtration [1]. Unlike geotextile,
the reinforcement function is the main function ofgeogrid for the flexible pavement. Reinforcement
refers to the mechanism(s) by which the engineering
properties of the composite soil/aggregate aremechanically improved [2]. Geogrid reinforcement
mechanisms can be distinguished into lateral restraint,
improved bearing capacity and tensioned membrane
effect [3]. From these mechanisms, the lateral
restraint, also known as “confinement”, has been
identified as the primary reinforcement mechanismsof geogrid [2] [3]. This is the ability of the aperture
geometry of a grid to confine the aggregate particles
within the plane of the material [3]. Hence, thegeometry of geogrid aperture and the average particle

EXPERIMENTAL PROGRAM
In this study, seven cyclic loading tests were
performed, considering base-course thickness,
148GEOMATE - Mie, Japan, Nov. 21-24, 2017

geogrid reinforcement position in base-course layer
and the applied stress levels. For no reinforcement,
base-course thicknesses were 10 cm, 20 cm and 30
cm. In geogrid-reinforced tests, base course
thicknesses were 10 cm and 20 cm. For 20 cm thickbase course, the reinforcement positions wereconsidered as the reinforcement depth ratios (a/h) of
1.0, 0.75 and 0.5 which were obtained when the depthof reinforcement (a) was divided by the base-course
thickness (i.e. h = 20 cm). Test conditions are
summarized in Table 1.

sands are presented in Fig. 1.
Reinforcement Material
In this study, the commercially available
triangular geogrid (trade name TX160, product ofTensar) was used for the reinforcement purpose. This
geogrid has the tensile strength of 10 kN/m in the
cross-machine direction and diagonal directions,pitch length of 40 mm along each side of triangularaperture, and unit weight of 245 g/m2. The
dimensions of TX160 geogrid are illustrated in Fig. 2.

Table 1 Test conditions
100
Subgrade**a/hPercent Finer (%)*BC
Test ID
thickness
Reinforcement
(cm)
10X
10
Non
20X
20
Non
30X
30
Non
10T
10
TX160
20T1.020
TX160
20T0.75
20TX160
20T0.520
TX160* base course** reinforcement depth ratio

1.0
1.0
0.75
0.5

80

Base Course

60
40
20
0
0.01

0.1

1

10

Particle Size (mm)Remarks:
1) Subgrade was modelled by fine uniform sandand prepared by sand raining method.
2) BC was modelled by coarse uniform sand andprepared by compaction.
3) In each test, cyclic load was applied withvarying magnitudes ranging from 100 kPa to
550 kPa (500 cycles for each loading step).

Fig. 1

Particle size distribution curves

MATERIALS
Subgrade and Base Course
Fig. 2
Silica Sand No.5 and No.1 were used for themodel subgrade and base course preparation. Thesesands are commercially available in Japan. Thesesands were selected because they have uniform
gradation, and, hence, there would be minimum
variation in the particle size distribution in each test.
The model subgrade sand has the following index
properties: the specific gravity Gs = 2.675, theaverage particle size D50 =0.488 mm, coefficient of
uniformity Cu = 1.98, coefficient of curvature Cc =0.943, maximum dry density ρmax = 1.628 g/cm3,
minimum dry density ρmin = 1.338 g/cm3. Model basecourse has the average particle size D50 of 3.735 mm,
uniformity coefficient Cu of 1.904 and curvature
coefficient Cc of 0.879. Since Cu and Cc values of bothsands are not in the range (Cu > 6 and 1 < Cc < 3)
specified by Unified Soil Classification System(USCS), they can be regarded as poorly graded sand(SP) [5]. The particle size distribution curves of these

Dimensions of triangular geogrid (TX160)

EXPERIMENTAL SETUP AND TESTING
In this experimental study, a large squarecontainer (100 cm x 100 cm x 80 cm) was used forthe preparation of model pavement sections. A rigid
circular steel plate, diameter = 17.5 cm, was used asa model footing. Since the total depth of subgrade andbase course was greater than 70 cm in each test, theboundary influence from the tank base would be
negligible according to Boussinesq StressDistribution Analysis. In addition to this, theinfluences from the tank walls would be minimal on
the test data because the size ratio between tank andfooting diameter is considerably large (100/17.5 ≈ 6)
[6] [7].
In order to model the subgrade soil, the sandraining method was adopted and used in accordancewith the literatures [8] [9] [10]. A large raining box
149

GEOMATE - Mie, Japan, Nov. 21-24, 2017

was developed so that the sand raining area covered
over the plan area of tank. By using this raining
method, the relatively high density was achieved ineach test, ranging from 1.54 g/cm3 to 1.66 g/cm3.
These densities were calculated from the total massof sand and the obtained average thickness.
After subgrade layer was prepared, a small plastic
plate was placed at the predefined location where
subgrade deformation was monitored, directly
beneath the footing. Then, a small aluminum tube wasset above this plate and was hold in vertical position
with the help of supporting system. After that, coarse
silica sand was spread over the subgrade layer in caseof no reinforcement, while geogrid was placed in caseof reinforcement. After the mass of 80 kg coarse sandhave been filled, the compaction was manuallyconducted through the wooden plate in order tominimize the breakage of material. The obtained
thickness was about 5 cm as an average after
compaction. The same procedure was continued until
the desired base-course thickness was obtained. The
experimental layout is shown in Fig 3.

frequency of 0.1 Hz was applied with the help offunction generator, E-P transducer and pneumaticpressure via Bellofram cylinder. The generated
voltage from function generator and the resulting load
pulse are shown in Fig. 3. In each test, cyclic load wasapplied with variable amplitudes ranging from 100
kPa to 550 kPa. Each loading step was allowed until
500 load cycles. Load and deformations at the surface
and subgrade were recorded by the data acquisition
system at every 1 second.
RESULTS AND DISCUSSION
Influence of Base Course Thickness
The influence of base-course thickness wasanalyzed on the surface and subgrade deformations ofgeogrid-stabilized sections and non-stabilized
sections. These are shown in Fig.4 and Fig.5, in which
the legends represent the test conditions, as presented
in Table 1.

100

0

Surface deformation (mm)Load (kN)

3
2
1
0
0

5

10 15 20 25 30

Time (Sec)200

Pressure (kPa)
300
400

550

10
20
30
10X
20X
30X
10T
20T1.0

40
50
60
70

0

500

1000

1500

2000

2500

Load cycle

Fig.4 Influence of base-course thickness on surface
deformation

100

Fig.3

Surface deformation (mm)0Experimental layout and test setup

The model footing was set after the preparation ofsubgrade and base course layers. One linear variabledisplacement transducer was set on the footing tomonitor surface deformation, while anothertransducer was used to monitor subgrade deformation
through the small aluminum tube. To simulate
trafficked loading, a trapezoidal load pulse with a

200

Pressure (kPa)
300
400

550

10
20
30
10X
20X
30X
10T
20T1.0

40
50
60
70

0

500

1000

1500

2000

2500

Load cycle

Fig.5 Influence of base-course thickness on subgrade
deformation
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

As seen in Fig.4, the largest surface deformation
was observed in the 10cm thick non-stabilized section(10X) since initial loading. Under 300 kPa pressure,
this section suddenly failed just after few load cycles.
This sudden deformation attributed to the bearing
capacity failure of subgrade layer, shown in Fig.5. For
10 cm thick geogrid-stabilized section (10T), thesignificant improvement was observed under all
loading stages, and this became more obvious with
the increase in the stress levels. Though the surface
deformation of 10T was much smaller than that of thecorresponding non-stabilized section 10X, thesubgrade deformations were similar to each other
under 100 kPa pressure. For this test section, thereduction in subgrade deformation was started noticeunder 200 kPa pressure together with load cycles,
shown in Fig.5. Thus, it can be assumed that thereinforcement action of geogrid might not have been
fully mobilized under 100 kPa. However, the smaller
surface deformation in 10T revealed that thisimprovement would have been contributed from thelateral confinement action of geogrid. This also
implied that the confinement action of geogrid first
appeared as soon as load was applied, and the full
reinforcement mobilization would have beenachieved with increasing load magnitudes. For 10 cm
thick base-course, the benefit of geogrid stabilization
was more significant with the increase in pressure andwith load cycles.
When base-course thickness was increased to 20
cm, the improvement was noticed in case of nonstabilized sections (10X and 20X in Fig.4). However,this improvement was negligible when the basecourse was further increased to 30 cm (30X), in whicha slight improvement was observed under 300 kPa
pressure. Then, this 30cm thick section suddenly
failed due to the lateral flow of aggregate materials
under 400 kPa pressure. For the geogrid-stabilized
sections, there was no obvious improvement when thebase course was increased from 10 cm to 20 cm (10Tand 20T1.0). Similar to 30X test, the sudden failure
was found in 20T1.0 test. That might be due to thelateral flow of aggregate materials under 400 kPa
pressure, before the reinforcement action of geogrid
was fully mobilized.
Regarding the behavior of subgrade deformation,
the deformations were minimal in thick base-course
sections: 20X, 30X and 20T1.0, regardless ofgeogrid-stabilized conditions. Though base-thickness
was increased to 30 cm in non-stabilized section,
there was no obvious reduction in subgrade
deformation, compared to 20 cm thick section (20X).
This might be due to the nature of uniformity ofaggregate. Because of uniform characteristic of thisaggregate, the internal friction angel would be smalland, the resulting stress distribution angle might also
be small. Qian et al. also reported that the stress
distribution angle became smaller with the number ofload cycle [11]. Hence, the influence of base-course

thickness might have been smaller with the increasingload cycles.
Interestingly, the geogrid-stabilized section
20T1.0 behaved like 30 cm thick non-stabilized one(30X) in both surface and subgrade deformation
characteristics. For the 10cm thick geogrid-stabilized
section, it showed even better performance than thatof 20X section, especially after 200 kPa stage. Hence,
it was realized that the effect of geogrid inclusion in
base-course layer was equivalent to the 10cm
thickness of the given type of aggregate material.
Thus, the required amount of aggregate could be
reduced by mean of geogrid stabilization. Due to thisaggregate uniformity, however, geogrid stabilization
could be effective only in thin base course if geogrid
was placed at the boundary between subgrade andbase course (10T in Fig.4).
Effect of Geogrid Position in Base-Course Layer

Subgrade deformation (mm)Since a flow-type deformation was observed in 20
cm thick geogrid-stabilized base course, thisthickness was selected to investigate the effect ofgeogrid position in the base course layer. Two moretests were performed; one with geogrid laid in thebottom-third of base course (a/h = 0.75) and the otherin the middle of base course (a/h = 0.5). The surface
and subgrade deformations were illustrated in Fig. 6
and Fig.7.

100

0

200

Pressure (kPa)
300
400

550

10
20
30
40

a/h = 1.0
a/h = 0.75
a/h = 0.5
a: geogrid position from surface
h: base course thickness

50
60
70

0

500

1000

1500

2000

2500

Load cycle

Fig.6

Surface deformation (geogrid position)

From Fig.6, it can be clearly seen that the surface
deformation was effectively reduced at all level ofloadings when a/h ratio became smaller. The
improvement due to the smaller a/h ratio was more
pronounced under high pressure levels (400 kPa and550 kPa). Interestingly, the subgrade deformations
were similar in these tests though there were obvious
differences between the respective surface
deformations. Thus, it was realized that the effect ofgeogrid position is insignificant on the subgrade
deformation behavior.
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Subgrade deformation (mm)GEOMATE - Mie, Japan, Nov. 21-24, 2017

Pressure (kPa)
200
300
400

100

0

surface deformations were attributed to the subgrade
deformations in both tests. On the other hand, thenon-stabilized sections: 20X (20 cm thick) and 30X(30 cm thick), and geogrid-stabilized sections:
20T1.0 (20 cm thick, a/h = 1.0) and 20T0.75 (20 cm
thick, a/h = 0.75) showed similar values of LBC under
low pressure levels (< = 200 kPa). Among these tests,
the slight reductions in LBC were noticed with basecourse thickness (20X to 30X) and geogrid position(20T1.0 to 20T0.5) under 300 kPa pressure, after
which the sudden failures were observed in 30X and
20T1.0. These failures were mainly contributed fromthe lateral flow of aggregate materials.

550

10
20
30
40

a/h = 1.0
a/h = 0.75
a/h = 0.5
a: geogrid position from surface
h: base course thickness

50
60
70

0

500

1000

1500

2000

2500

Load cycle

Fig.7

Subgrade deformation (geogrid position)

When geogrid was placed inside base-course layer
rather than above the subgrade layer, the geogrid
would have confined the aggregate materials on bothsides of the layer. As a result, the base course layer
became stiffer and the improved bearing resistancewould be achieved, sustaining until the end of 550
kPa loading stage, shown in Fig.6. In addition, thelateral flow potential of aggregate material was
effectively reduced with smaller a/h ratio due to
optimal confinement effect on both sides of geogrid.
Fig.8

Loss in Base Course Thickness

For the geogrid stabilized sections: 10T (10 cm
thick) and 20T0.5 (20 cm thick, a/h = 0.5), LBC
values were almost same under the pressures of 100
kPa, 200 kPa and 300 kPa. However, a larger value of
LBC was noticed in 20T0.5 than in 10T under 400 kPa
pressure. This could be explained from the subgrade
deformation behavior. The rate of subgrade
deformation in 10T test had been progressively
increased under 400 kPa pressure (10T in Fig.5).
Hence, the resulting surface deformation was mainly
contributed from this subgrade deformation. In
addition, the large deformation in subgrade would
promote to occur the tension membrane mechanism
in geogrid. This behavior is good in agreement withthe statement in which the tension membrane effect
was recognized when permanent deformation waslarger than 33% of the base thickness, reported by
Qian et al. [11].
On the other hand, the subgrade deformation of
20T0.5 (a/h = 0.5 in Fig.7) was considerably small,compared to that of 10T. Thus, the potential of loss inbase-course thickness of 20T0.5, due to lateral flow,
was successively increased under 400 kPa pressure.
This could result in a linearly increasing trend of
surface deformation under 400 kPa pressure, shownin Fig.6 (a/h = 0.5). A concave trend of this curve wasobserved under 550 kPa pressure. This means that therate of surface deformation became slower with load
cycles, unlike the linear trend under 400 kPa. This

In order to investigate the benefit of geogrid
stabilization, the loss in base-course thickness (LBC)
was calculated under each pressure level. This was
simply formulated considering the difference in therates of deformation between surface and subgrade,shown in Eq. (1).

LBC   d f  d sg 

Loss in base-course thickness(1)

Where,
d f : rate of surface deformation

d sg : rate of subgrade deformation
The variation in the loss of base-course thickness
is shown in Fig.8, in which the presented data weretaken after 500 cycles of loading. As seen in Fig.8,
the loss in base-course thickness was successfully
reduced at all pressure levels with the inclusion ofgeogrid. In all cases, the loss in base-course thickness
became more obvious with increasing pressure level.
Sun et al. also reported the similar behavior in theirstudy [12].
When LBC values were compared between nonstabilized (10X) and stabilized (10T) sections, thegeogrid-stabilized section reduced about 5 mm under
given pressure level, though it was known that the152GEOMATE - Mie, Japan, Nov. 21-24, 2017

slower rate might have been resulted from the certain
progressive rate of subgrade deformation (a/h = 0.5 inFig.7). Hence, tension membrane action would havebeen initiated in the geogrid together with thesubgrade deformation, resulting in the larger
confinement effect and in the lower rate of increase in
LBC values, as seen in Fig.8. From these test data, it
is generally realized that the loss or deterioration ofbase course is mainly related to the applied stresslevel, and this can be effectively reduced by changing
the geogrid position inside the base course layer.

A. Lacina and T. E. Smith, "Laboratory
Evaluationof
Geosynthetic-Reinforced
Pavement Sections," Transportation Research
Record, vol. 1439, no. 1439, pp. 25-31,
September 1994.
[2] R. P. Anderson, "Geogrid Separation," inProceedings of International Conference on
New Developments in Geoenvironmental andGeotechnical Engineering, Incheon, Republicof Korea, 2006.
[3] Stephen Archer, P.E., "Subgrade Improvement
for Paved and Unpaved Surfaces Using
Geogrids,"
CE
News
Professional
Development Hours, 2008.
[4] S. W. Perkins, "Mechanical Response ofgeosynthetic-reinforced flexible pavements,"
Geosynthetics International, vol. 6, no. 5, pp.
347-382, 1999.
[5] J.-P. Bardet, Experimental Soil Mechanics,
Upper Saddle River, New Jersey: Prentice-Hall
Inc., 1997.
[6] H. A. Alawaji, "Settlement and bearing
capacity of geogrid-reinforced sand overcollapsible
soil,"
Geotextiles
andGeomembranes, vol. 19, pp. 75-88, 2001.
[7] T. Yetimoglu, J. T. H. Wu and A. Saglamer,"Bearing Capacity of Rectangular Footings on
Geogrid-Reinforced Sand," Journal of
Geotechnical Engineering, ASCE, vol. 120, no.
12, pp. 2083-2099, December 1994.
[8] S. Miura and S. Toki, "A sample preparation
method and its effect on static and cyclic
deformation-strength properties of sand," Soils
and Foundations, vol. 22, no. 1, pp. 61-77,
March 1982.
[9] Y. P. Vaid and D. Negussey, "Technical Note:
Relative density of pluviated sand samples,"Soils and Foundations, vol. 24, no. 2, pp. 101105, 1984.
[10] T. N. Dave and S. M. Dasaka, "Assessment of
portable travelling pluviator to prepare
reconstituted sand specimens," Geomechanics
and Engineering, vol. 4, no. 2, pp. 79-90, 2012.
[11] Y. Qian, J. Han, S. K. Pokharel and R. L.
Parsons, "Performance of Triangular Aperture
Geogrid-Reinforced Base Courses Over Weak
Subgrade under Cyclic Loading," Journal of
Materials in Civil Engineering, vol. 25, no. 8,
pp. 1013-1021, August 2013.
[12] X. Sun, J. Han, J. Kwon, R. L. Parsons and M.
H. Wayne, "Radial stresses and resilient
deformations of geogrid-stablized unpaved
roads under cyclic plate loading tests,"
Geotextiles and Geomembranes, vol. 43, no. 5,
pp. 440-449, 10 2015.

CONCLUSIONSThe behavior of geogrid inclusion in the unboundgranular layer was studied through large scale model
tests. The uniform silica sands No.5 and No.1 wereused as model subgrade and base-course layers. The
cyclic loading with varying load magnitudes wasapplied through the circular rigid footing. From thisstudy, the followings were summarized as:(1) For the given type of granular material, theeffective improvement due to geogridstabilization was observed in thin base-course
section, if geogrid was placed at the boundary
between subgrade and base-course layer.
(2) The surface and subgrade deformations were
optimally reduced with the geogrid stabilization.
However, this reduction was insignificant with theincrease in base-course thickness.
(3) In thin base-course section, surface deformation
was mainly contributed from the subgrade
deformation, while lateral flow dominated in thicksection.
(4) Flow type deformation was obviously minimized
with the smaller reinforcement depth ratios. The
optimum depth was known when geogrid was laidat the middle of base course.
(5) The influence of reinforcement position was
negligible on the subgrade deformation behavior.
(6) Loss in base-course thickness (LBC) or basecourse deterioration is smaller in the thinner basecourse, while this is larger in thick section. This
LBC can be successfully minimized with thesmaller reinforcement depth ratios.
(7) In all tests, the increase in LBC was noticed withincreasing pressure levels.
ACKNOWLEDGEMENTS
This study was collaborated with NIPPOCORPORATION and MITSUI CHEMICALSINDUSTRIAL PRODUCTS LTD. Their supports arehighly appreciated.
REFERENCES[1] I. L. Al-Qadi, T. L. Brandon, R. J. Valentine, B.
153

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LONG-TIME STRENGTH PREDICTION METHOD OF CHEMICAL GROUTSPECIMEN WITH HEAT CURING
Shunsuke Takiura, Naoaki Suemasa and Kazuya Itoh 1, Takamitsu Sasaki 2 and Shunsuke Shimada 3
1
Urban and Civil Engineering, Tokyo City University, Tokyo, Japan
2
Research and Development, Kyokado Engineering Co., Ltd, Tokyo, Japan
3
President, Kyokado Co., Ltd, Tokyo, Japan
ABSTRACTIn Japan, where many large earthquakes have happened, there has been a growing demand for liquefaction
countermeasures. In this study, a chemical grouting method was focused on as a liquefaction countermeasuremethod because, it is excellent in performance compared to other methods. However, only ten several years havepassed since the grout having long term durability was developed and accordingly the proof experiments about its
durability have been carried out only during a period equivalent to it. In this study, the possibility to predict thechange of long-term strength was examined by a series of short-term laboratory test where heat curing wasprovided for in promoting time variation of the specimens in a thermostatic tank. Here, the acceleration mechanism
by heat curing was based on the chemical reaction rate theory of Arrhenius. As a result, it was confirmed that it
was possible to predict the future change of durability with the proposed method in which the Arrhenius plot was
adopted with unconfined compression test results from heat cure specimens.
Keywords: liquefaction, chemical grouting method, heat curing, Arrhenius plot, predicted values
resistance against earthquake vibration. Fig.1 showsa conceptual diagram of strength development
mechanism of a chemical improved body (Sasaki etal. 2011).

INTRODUCTION
Liquefaction is the most significant and urgent
concern in Japan and the countermeasures againstliquefaction especially for revetments have been
executed promptly since the 1995 Hyogoken-Nanbu
earthquake caused serious damage to coastal areas. A
chemical grouting method was selected as one ofthem. As a reason of the selection, there is lessvibration and noise than other methods during theconstruction. In addition, this method provides small
equipment for space saving, which can drill a hole not
only in a vertical but also in an oblique and a curved
line. Then, the Pacific coast of Tohoku Earthquake
occurred on March 11th 2011. The maximum
acceleration of 2933 gal was recorded in Kurihara
city in Miyagi prefecture. Liquefaction occurred inmany coastal regions from Tohoku to Kanto districts
and the total damage throughout Japan reached 42
square kilometers. The liquefaction countermeasuresusing a chemical grouting method were performed inseveral places along the Pacific coast in 2008 after the2007 Niigata Chuetsu-oki earthquake. It was revealed
through the damage survey of the 2011 Earthquakethat the chemical grouting method was quite effective
as a liquefaction countermeasure [1].

Fig. 1 Mechanism of improvement by active colloidal silica

The strength increase of an improved specimen
consists of three parts. In the first place, additional
confining pressure (P1) would be generated by thatgrout material adheres to sand particles and tends toreduce the volume when it is solidified. In the second,
confining pressure effect (P2) can be expected byrigidity of solidified grout material when it isdeformed by some kind of force. In the third, there isconfining pressure effect (P3) added by the cohesion
which the solidified grout material originally has.

The principle of the chemical grouting method isto prevent both contraction of sand skeletons and arise in excess pore water pressure caused by theseismicvibration by replacing pore water between
sand skeletons with a gelatinous silica compound. In
addition, the silica compound gives cohesion between
sand particles and accordingly increases shear

As mentioned above, although the permanent
grout material has been proved to be effective forliquefaction countermeasures, the long-term strengthof the improved soil has been unexplained. One
154

GEOMATE - Mie, Japan, Nov. 21-24, 2017

reason is that most of previous studies on chemical
grouting have focused on the development or the
choice of durable infusion materials [2]. The otherreason is that sufficient proof experiments for thematerials have not been carried out because it has
been only ten and several years since the permanent
grout material was developed. Under thesecircumstances, it is essential to establish a practical
way to estimate the strength change of the improved
soil with elapsed time.

Toyoura sand was used for this experiment. Table
1. and Fig. 2 show the Physical characteristics of
Toyoura sand.
The grout material used for the experiments was
active colloidal silica and silica sol whose
concentrations in weight were 29% and 6%,
respectively. The active silica colloid is one ofpermanent grouts used for a permanent work such asliquefaction countermeasures. It is based on the active
silica obtained by removing alkali from water glassby an ion exchange technique in order to exclude its
deterioration factor. While the silica sol is a grout
material for temporary constructions such as theground improvement for an excavation construction
where long term durability is not required. It is basedon the non-alkaline water glass solution obtained byneutralizing alkali of water glass with acid [4]. The
active colloidal silica has hardly changed in volume
for a long time. On the other hand, the silica sol has
remarkably changed in volume immediately after it
was solidified and therefore, the unconfinedcompression strength of the improved soil tended togradually decrease. It seemed to be because theconfining pressure and the cohesion of the gel
decreased or disappeared by the decrease in volume[5].

Therefore, the method in which the long-term
strength is able to be verified in a short-term test issuggested in this study. In the method, the improved
soil was provided with a special process to promotecuring. Additionally, an equation (1) was suggested,which can assume unconfined compression strength,qus, with internal friction angle, φs, increased byeffect of the dilatancy increase with gel in void [3].
∅

(1)

∅

In the study, a heat and cure process have been
applied to chemical improved specimens in atemperature and humidity testing chamber for 1000
days. Also, unconfined compression strength tests
were conducted using the specimens and the strengthchange was reported. In conclusion, the age of thematerials provided with standard cure was calculated
from the test results using the specimens provided
with promotion cure.

Two kinds of specimens; sand gel and plain gel,were prepared as follows. The specimen of sand gel
was induration sand infiltrated with chemical grout.
Toyoura sand was air-pluviated in a mold of 5cm ininside diameter so as to be a relative density of 60%.
The height of samples was set 10cm by putting aweight on the top of the samples and tapping sides ofthe molds with a wooden hammer. Then the chemical
grout deaerated in a vacuum pump was injected into
the specimens and removed from the molds after
solidification. Photo.1 describes the situation of
injecting the chemical grout solution.

EXPERIMENTAL PROCEDURE
Table 1.

Physical properties of Toyoura sandDensity test ofsoil particle(g/cm3 )Maximumvoid ratio
e max

Minimumvoid ratio
emin

2.634

0.986

0.621

Passage mass percentage %

100
80
60
40
20
0
0.001

0.01

0.1

Sieve (mm)1

10Photo.1

Infusion situation

Fig. 2 Grain size accumulation curve of Toyoura sand

The specimen of plain gel was an indurated gelformed chemical grout. For the plain gel, 200ml of155

GEOMATE - Mie, Japan, Nov. 21-24, 2017

chemical grout was poured into a glass container with
5cm in inside diameter and removed from thecontainer after solidification. A process of curing was
carried out under the conditions of three different
temperatures; 25, 45 and 50 in degrees Celsius. All of
the specimens wrapped in a wrap film were covered
with wet papers and put in an airtight container toprevent from being dried. As for normal curing, thespecimen was cured in the room where thetemperature was constantly controlled at 25 degrees
with an air conditioner. For heat curing, thespecimens in the containers were set in the constanttemperature tanks whose temperatures were
continuously adjusted at 45 and 55 degrees,

Unconfined compression strength (kN/m2 )

A

1000

600
400
200
0

Fig.3

Experiment case

Grouting
Activecolloidal silica

CuringTest piecetemperaturesand gelplain gelsand gel

Silica sol
plain gel

25℃
45℃
25℃
45℃
25℃
45℃
55℃
25℃
45℃
55℃

B

800

0

200

400

600
800
Time (day)

1000

1200

Unconfined compression strength of the active
colloidal silica sand gel

160

site

Unconfined compression strength (kN/m2 )Table 2.

1200

A
B
C
D
E
F
G
H
I
J

140

C

120

D

100
80
60
40
20
0

0

200

400

600

800

1000

120

Time (day)Fig.4

respectively. Experimental cases are shown in Table
2.
RESULTS AND DISCUSSION

Unconfined compression strength of the active
colloidal silica plain gel

Unconfined compression strength (kN/m2 )1200

Unconfined compression test result
Fig. 3 and Fig. 4 show the changes in unconfinedcompression strength of sand gel and plain gel
improved by active colloidal silica, respectively. In
both cases, the strengths of the specimens became
higher when provided with heating curing rather thanordinary temperature curing. From the result, it was
confirmed that heating curing was capable to promote
the chemical reaction of chemical grout.

E

1000

F
G

800
600
400
200
0
0

200

400

600

800

1000

Time (day)Fig.5

Fig. 5 shows the change in unconfinedcompression strength of sand gel specimens of silica
sol. The specimens provided with heating curing
showed lower strength than that with ordinary
temperature curing and all of them gradually
decreased in strength. Fig. 6 shows the change inunconfined compression strength of plain gel
specimens of silica sol. In the same way as the sandgel, the specimens provided with heating curing
showed lower strength than that with ordinary
temperature curing. The specimen with ordinary
temperature curing gradually increased in strength.
On the other hand, as for the specimens with heating
curing, the strength gradually decreased after having
increased at the initial stage. Therefore, it is assumed

Unconfined compression strength of silica sol sandgel

Unconfined compression strength (kN/m2)

160
I

120

J

100
80
60
40
20

Fig.6

156

H

140

0

0

100

200

300
400
Time (day)

500

600

700

Unconfined compression strength of silica sol plaingelGEOMATE - Mie, Japan, Nov. 21-24, 2017that the strength with ordinary temperature curing
would gradually decrease afterwards as well as theheated ones.

0

200

400

600

800

1000

1200

0.0
‐5.0

Volume change (%)

In the sand gel of active colloidal silica, the failuremode of the specimen differed between with andwithout the heating curing. The left of Photo.2 shows
the state of shear failure in the specimen observed inits early period. While the specimen provided with along-time heat curing had a tendency of tensile failure
as shown in the right of Photo.2. The tensile failure in
the lengthwise direction seems to be caused by thetensile strength generated when the specimen wascompressed in the vertical direction. It is said that thehigher the strength of specimen becomes, the more
frequently this phenomenon appears.

C

‐10.0

D

‐15.0
‐20.0
‐25.0
‐30.0
‐35.0
‐40.0

Fig.7

Time (day)Volume change in active colloidal silica plain gel
0

200

400

600

0.0

H

‐5.0

Volume change (%)

80

I

‐10.0

J

‐15.0
‐20.0
‐25.0
‐30.0
‐35.0
‐40.0

Fig.8

Photo.2

Time (day）Volume change in silica sol plain gel

It was also supposed by Kaga (1994 and 2000) that it
was possible to estimate a strength change with time
elapsed by changing curing temperature, assumingthat the hardening of infusion compaction sand was
influenced by a chemical reaction [7]. Kaga studied
the interrelation between a simpler chemical reaction
speed and a reaction rate to examine his assumption.
Equations for a chemical reaction speed base on
the Arrhenius theory are expressed by logarithm
indications as follows.

Failure mode of active colloidal silica sand gel

Volume change of plain gel

Fig. 7 and 8 show the changes over time in thevolume of plain gel of active colloidal silica and silica
sol, respectively. As for the active colloidal silica, therates of volume change were constantly near -2.5% in
all cases of ordinary temperature curing and heating
curing. While, as for the silica sol, the rate of volume
change in cases of heating curing grew larger thanthat in case of ordinary temperature curing. In
addition, when comparing between the specimens
with heating curing at different temperatures, the rateof volume change was larger at a higher temperature.
Since the silica sol tends to be changeable in volume,
it appeared that heating curing promoted the volume
change in silica sol more effectively than ordinary
temperature curing.

(2)

log
log
α

log
exp

(3)
(4)

Where A：density, A0：initial density, k：rate
constant, t ： time, C ： constant, E ： activationenergy, R ： universal gas constant, T,T1,T2 ：absolute temperature, α: acceleration factor.
Equation (2) shows the relationship between
reaction rate, ( A/A0, ) and time. The rate constant, kin the equation (2) is dependent on absolutetemperature as seen in the equation (3). Therefore,
when temperature at which the chemical reaction is
performed rises, the rate constant increases, and thenthe period required until the same degree of chemicalLong age strength estimation

Kaneko and Ozawa (1977) successfully estimatedthe deterioration time of insulating material under thecondition of standard temperature (by heating curing)using the technique based on the chemical reaction
speed theory of Arrhenius in their previous study [6].
157

GEOMATE - Mie, Japan, Nov. 21-24, 2017

stable change period, were separately plotted in orderto get more precise prediction. Fig.10 shows thestrength of sand gel of active colloidal silica which
was predicted using the acceleration factor obtained
from the Arrhenius plot of the same type in Fig.9.
The predicted strength change showed a similartendency to the measured strength changes frommaterials age 14 days to 1000 days. From the result,it was verified that the predicted values wereequivalent to the measured values. Additionally, thestrength change applied with standard curing for 3641
days was predicted using the strength change appliedwith heating curing for 1000-days.

reaction is achieved decreases. In general, thisreaction constant can be substituted with factors suchas a volume change, a weigth change, an area
increment and a strength rate which are directly
proportional to a chemical reaction speed [8]. Achange rate of specimen strength was adopted for a
substitution of k in this paper. Accordingly, strengthchange rates obtained from the experiment wereplotted in a vertical axis of a logarithm indication, andcuring temperatures were converted to absolutetemperatures and the reciprocals of the factored
absolute temperatures, 1000/T, were plotted in ahorizontal axis. Generally, this plot is called“Arrhenius plot”. The plot obtained from theexperiment results performed at more than two kindsof temperatures gives an acceleration factor shown in
the equation (4), which factor is multiplied by time in
the heat curing case to predict its future response. In
accordance with this theory, the strength change ofactive colloidal silica provided with standard curing
was calculated from the results of promotion curing.

The Arrhenius plot of the same type is shown in
Fig.11, which was calculated from the unconfinedcompression strength of plain gel of active colloidal
silica. Also, Fig. 12 shows the strength change ofplain gel of active colloidal silica, which waspredicted using the acceleration coefficient obtained
from Fig.11. In the same way as the sand gel, themeasured values and the predicted values of plain gel
showed similar tendencies in strength change.

Fig. 9 shows the Arrhenius plot of the same typecalculated from the results of this experiment. As
showed in Fig.3, the strength of active colloidal silica
changed conspicuously from material age of 1 day to
90 days and became relatively stable after 90 days.
These two periods, conspicuous change period and

The efficiency of promotion with heating curing
was confirmed in all cases through the experiments.
In addition, the predictive values of sand gel and plain
gel of active colloidal silica were calculated from the2

Active colloidal silica 1~90day

4.5
4Change rate of the strength(⊿kPa⊿t)

Change rate of the strength(⊿kPa⊿t)

5

Active colloidal silica 90~1000day

3.5
3
2.5
2
1.5
1
0.5
0

Fig.9

3.15

3.2

3.25

1000/T

3.3

3.35

1.2
1
0.8
0.6
0.4
0.2
3.15

3.2

3.25
1000/T

3.3

3.35

3.4

180

1000
800
600
400

Measured values
200

Fig.103.1

Fig.11 Arrhenius plot of active colloidal silica plain gel

Arrhenius plot of active colloidal silica sand gel

Unconfined compression strength(kN/m2)

Unconfined compression strength(kN/m2)

1.4

3.4

1200

0

Active colloidal silica 100~1000day

1.6

0
3.1

Active colloidal silica 1~100day

1.8

Predicted values

10

100

1000

10000

Predicted values

140
120
100
80
60
40
20
0

1

Measured values

160

1

10

100

day(day)Time(day)

1000

10000

Fig.12 Predictive strength of active colloidal silica plaingelPredictive strength of active colloidal silica sand
gel

158

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Chemically Stabilized Sand with Grouting.” Japan
Socuety of Civil Engineering Memoirs C (Ground
Zone Engineering), Vol69, No.2, pp162-173.
[3] Sasaki, T., Shimada, S., Oyama, T., Suemasa, N(2011). “Influence of Soil Characteristics On Gel
Time And Unconfined Compression Strength of
Ground Improved By Chemical Grouting
Method,” The Twenty-first International Offshore
and Polar Engineering Conference, 19-24 June,
Maui, Hawaii, USA[4] Geo-grouting development Organization
HP: http://www.jckk.jp/kokyu.php[5] Kaga, M., Mori, A (1994). “Basic Study on
Chemical Stability and Strength Durability of
Silicate Grout Sand,” Japan Socuety of Civil
Engineering Memoirs, No.496/V-24, pp31-40.
[6] Kaneko, T., Ozawa, T (1977). “The Handling of
the Chemical Kinetics of the Deterioration of theInsulating Material Which Increased Heating,Cooling Periodically,” The institute of ElectricalEngineers of Japan article magazine A, Vol97,
No.2, pp48-55.
[7] Kaga, M (2000). “ Physical and Chemical
Stability of Pure Silicate Grout and Prediction of
the Long-Term Strength of Grouted Sand,” Japan
Socuety of Civil Engineering Memoirs, No.652/Ⅲ-51, pp195-205.
[8] Hueno, T (1975). “Chemical Reaction Theory,”
Asakurashoten, pp24-30

results of heating curing. Judging from thesuperimposition of the linear approximate curves ofthe predicted and measured values, reliability ofpredicted values are high. Great potential can be
expected in the strength prediction method withheating curing using a constant temperaturehumidistat tank.
CONCLUSION

In the study, a heat and cure process has been
applied to a chemical grout in a temperature andhumidity testing chamber and attempted predictive
calculation in conformity with a chemical reaction
speed theory of Arrhenius. The values of predicted
strength change were similar to the measured values.
In conclusion, long-term prediction was enabled by ashort-term examination using a constant temperaturehumidistat tank.
REFERENCES[1] Sasaki, T., Oyama, T., Shimada, S., Suemasa,N(2011). “Influence of Soil Characteristics on Gel
Time and Unconfined Compression Strength of
Ground Improved by Chemical Grouting Method,”
The Twenty-first International Offshore and Polar
Engineering Conference, 19-24 June, Maui,
Hawaii, USA[2] Nakayama, T., Sawada, R., Hiraoka, Y., Akagi, H(2013). “Evaluation of Long Term Stability of159

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

FLY-ASH-BASED GEOPOLYMER AS STABILIZER FOR SILTY SANDEMBANKMENT MATERIALS
1,2

Jonathan R. Dungca1, Edward Ephrem T. Codilla II2
Civil Engineering Department, Gokongwei College of Engineering, De La Salle University, 2401 Taft Ave.,
Malate, Manila 1004, Philippines
ABSTRACTFly ash in the recent decades has become abundant resulting to improper waste disposal. However, it is also
known to be a precursor to the process of geopolymerization which is categorized under waste utilization.
Geopolymer has become known for being on par with cement and other chemical stabilizers in terms of strength.
It has been used in numerous studies focusing on concrete and on soil stabilization. This study proposes the use of
fly-ash-based geopolymer as a stabilizer for silty sand embankment material wherein the process of synthesizing
geopolymer is through the dry-mix method. The dry-mix method is another way of producing geopolymer,
requiring the aluminosilicate precursors and alkali activators to be in its dry state, and adding water to the dry-mix
would result to geopolymerization. The geopolymer was applied on Silty Sand to verify its reaction with the soil
and to obtain the effective mix that would enable the soil to be stabilized for embankment use. The effectivenessof this method in soil stabilization was tested through the following tests, the CBR Test (ASTM D1833) and the
UCS Test (ASTM D2166). Results have shown improvements of the geopolymer-stabilized soil in terms of the
CBR index and the UCS value. The effective geopolymer concentration was found to be at 30% geopolymer
concentration which produced the highest increase for the stabilized soil with a maximum CBR index of 34.32%
and a maximum UCS value of 1349.74 kPa.
Keywords: Fly Ash; Dry-mix Geopolymer; Embankment Materials; Soil Stabilization
problems and an increase in expenses for storage inavailable landfills [6], [7]. This eventually poses athreat to the environment if it is not properly managed[8]. Consequently, several studies [9], [10], [11], [12],[13], [14], [15], [16] have been conducted, which is
aimed towards recycling fly ash and utilizing it invarious applications.
An alternative to stabilizing soil is by introducing
geopolymer. Geopolymer is a product of the alkali
activation of aluminosilicate materials present inindustrial waste materials such as fly ash, red mud,and furnace slag [1]. The waste material used in the
study to synthesize geopolymer was fly ash.

INTRODUCTION
In geotechnical works, a site is surveyed whether
soil conditions meet the design criteria. However,most commonly, sites designated for earthworks do
not reach the minimum standards, such as those with
soft, highly compressible, or expansive soils lacking
the desired strength for loading during construction or
for their serviceability [1]. For this reason, such soils
are enhanced through soil stabilization, wherein themechanical properties of the soil are improved byapplying materials that have cementitious properties
or are considered to be binder materials [2]. The mostcommon soil stabilizers used nowadays are OPC(ordinary Portland cement) and lime. However, due
to the CO2 (Carbon Dioxide) emissions produced
during the manufacturing of aforementioned soil
stabilizers, which contribute to greenhouse gases,
other soil stabilizers are being sought out andrecommended. Studies and tests are being conductedin synthesizing alternative and eco-friendly soil
stabilizers from waste materials, which can allow
decrease in CO2 emissions and, simultaneously
decrease cost in earthwork construction [3], [4].
Fly ash is an industrial waste produced from the
combustion of coal into fuel for power generation [5].
Globally, fly ash produced by factories and thermal
power plants has been increasing for the past few
years. The mass production of fly ash causes disposal

MATERIALS AND METHODS
Soil
The soil used in the study was obtained from
Taguig City. It has a specific gravity of 2.50. The soil
passing the No. 40 sieve has a liquid limit (LL) of 26
and a plasticity index (PI) value of 4, which classifies
the soil to be slightly plastic as per ASTM D4318.
Referring to Fig. 1, the particle size analysis
performed on the soil indicates that the soil hasvarying grain sizes since it is composed of 18% gravel,
55% sand, and 13% silty fines. According to the
Unified Soil Classification System (USCS) and theAmerican Association of State Highway and160

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Transportation
Officials(AASHTO)
Soil
Classification System, the soil is classified as Silty
Sand (SM) with Gravel and as Silty Gravel and Sand
(A-2-4), respectively. The standard Proctor test wasalso performed on the soil to determine its maximum
dry unit weight ( 𝛾",$%& ) and optimum moisture
content (OMC), which were 17.61 kN/m3 and 15.15%,
respectively.
To determine the corresponding AASHTO ratingof the soil, the California bearing ratio (CBR) test was
performed. The soil, with a CBR index of 1.68%, wasrated as Poor for Subgrade use. The unconfinedcompression strength (UCS) test, however, could not
be performed as the soil could not form UCS samples;
these samples crumbled after being removed from the
UCS molds. The two strength tests, UCS and CBR,
were later on used as bases in verifying the soil
stabilization caused by the geopolymer in comparison
to the results of the unstabilized soil.

Fig. 1

Table 2 TCLP results of the fly ash
Heavy Metals

Permissible Limit

Fly AshCadmium
Chromium
Lead
Iron
Copper

1.000
5.000
5.000
0.300
1.000

Not Detected
Not Detected
Not Detected
0.06
0.02

Manganese

0.050

Not Detected

Zinc

5.000

0.008

Geopolymer Synthesis By Dry Mix Method
Soil stabilization should be practical when appliedin the field. For geopolymer, this is solved by using
the dry mix method. This method requires allmaterials to be in their dry state when initially mixed
together. Afterwards, water is added to this mixture
as the final step, which will result togeopolymerization.
The alkali activators used in the study were
Sodium Hydroxide (NaOH) pellets and Sodium
Silicate (NaSi2O3) pellets. In other studies [1], [17],[18], optimal range of values for activators to fly ash
ratio, NaSi2O3 to NaOH ratio, and NaOH
concentration were obtained; the values applied inthis study were 0.4, 14 M, and 2, respectively. Threegeopolymer concentrations were tested to stabilize
the soil. These were in the values of 10%, 20%, and
30% by percent weight of the sample batch.
Prior to preparing the specimens, the geopolymer
paste was produced. In the synthesis of thegeopolymer paste, the dry alkali activators and the fly
ash were initially mixed together using a mixer.
Afterwards, water was then added and mixed forapproximately 10 minutes. The total water required
was considered as the water required to reach the
NaOH concentration (14 M) and the OMC (15.15%)of the soil. The said procedure is shown in Fig. 2. Thisgeopolymer paste was then added to the soil toproduce that stabilized specimens.

The particle size distribution of the soil.

Fly AshThe fly ash used in geopolymer synthesis was
obtained from a coal-fired power plant in Mindanao.
The X-ray Fluorescence (XRF) test was performed on
the fly ash to determine its chemical compounds asshown in Table 1. As per ASTM C168, it is classified
as Class F. To test whether the fly ash is safe for use
in the environment with regards to leaching, theToxicity Characterization Leaching Procedure(TCLP) and Heavy Metal test was performed. Table
2 shows that the fly ash is a non-hazardous material
as its heavy metal content does not exceed thepermissible limits as per TCLP standards.
Table 1 XRF results of the fly ash
Chemical Compounds
Al2O3
SiO2
Fe2O3
SiO2 plus Al2O3 plus Fe2O3
SO3
CaO

Fly Ash (%)
26.50
36.50
16.20
79.30
8.20
10.70

Fig. 2 The dry mix method: (A) dry alkali
activators, (B) fly ash, (C) water, (C) geopolymer
paste.

161

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Soil Stabilization with
Characterization Tests

Geopoloymer

andsamples used in the FTIR tests were the fly ash, thesoil, the pure geopolymer, and the 30% geopolymer
concentration stabilized soil. The results were used
for comparison of the spectra of the samples to checkfor changes when geopolymer is applied to the soil.

UCS and CBR sample preparation and testing
Five samples were made for each geopolymer
concentration; a total of 15 samples per strength test
was synthesized. The UCS samples of the stabilized
soil were compacted into cylindrical PVC molds (40mm x 100 mm). Prior to testing, these were cured atroom temperature for 28 days. For the CBR samples
which were unsoaked, the stabilized soil wascompacted into the CBR molds at 5 layers with 56
blows per layer to obtain a 95% of the desired 𝛾",$%&
as per ASTM D1883. The CBR samples were cured
for 7 days prior to testing.

RESULTS AND DISCUSSION
Mechanical Properties of Geopolymer-Stabilized
Soil
In the UCS test, the soil being predominantly ofsand could not be tested solely due to sand being
cohesionless as shown in Fig. 3. When geopolymer
was applied starting at 10% geopolymer
concentration, UCS samples were able to be
produced; these samples started to have cohesive
characteristics. The geopolymer acts as a binder forthe sand particles and fills the gaps between theseparticles. Moreover, the geopolymer gel formation
creates a network that binds the soil particles and fly
ash particles together creating a stronger network ofparticles. Assessing the results in Table 3, the samples
with 10% geopolymer concentration had a UCS (qu)value of 78.29 kPa (Medium consistency), with 20%
it increased to 247.48 kPa (Very Stiff), and with 30%
it significantly increased to 1349.74 kPa (Hard).

Statistical analysis of mechanical properties ofgeopolymer stabilized soil
The statistical analysis of the data was performedin the Design Expert software v7.0. The partial sumof squares Type III analysis of variance (ANOVA)
was applied to test the presence of a main effectbetween the interactions of the model terms in amodel equation. The model order (linear, quadratic,or cubic) was selected based on the coefficient ofdetermination (R2) value; whichever model had thehighest R2 value indicated a great fit for the data
points. Each term of the model equation wasdetermined to be significant if its probability p (Prob> F) was less than 0.05. Moreover, the null hypothesis
is focused on the lack of fit, as it is assumed that there
is no lack of fit for the data points in a linear equation.
Small p values, those that are less than 0.05, indicatethat the null hypothesis is rejected and that a model ofhigher order is required. To verify the model
equations, equality graphs were made and thecorrelation value (r) between the predicted and actual
values was calculated.

Fig. 3

The UCS samples of the pure soil.

Table 3 UCS testing results of the stabilized soil
Geopolymer
Concentration
UnconfinedCompressive
Strength, qu (kPa)Morphological characteristics
The SEM (scanned electron microscopy) imaging
test was applied on the fly ash, the soil, and thesamples of the stabilized soil. These were used toverify the formation of geopolymer gels since the drymix method was used which could affect the rate ofgeopolymerization. Moreover, the stabilized soil with28 days of curing was used in the SEM imaging test
to better observe the formation of geopolymer gelswhen compared to the SEM images of the fly ash andthe soil. Portions of each sample, with a mass of 10 to
15 grams, were oven-dried before being tested.

Consistency

10%

20%

30%

78.29

247.481349.74

Medium

Very
Stiff

Hard

These qu values are comparable to a study using
the wet mix approach of synthesizing geopolymer
stabilizers. This study [18] used slag-based
geopolymer to stabilize clayey soil which resulted toa qu value of 1223 kPa at 25% geopolymer
concentration. Other studies [14], [15] which
stabilized expansive soil using fly ash resulted toincrease in qu value by 200 to 1400 kPa. In
comparison to a study which used cement
stabilization, qu values ranged from 500 kPa (5%cement) to 2150 kPa (20% cement) [19] for stabilized
dredged sediments composed of clay and silt.

Fourier Transform Infrared (FTIR) spectroscopy
The FTIR was performed to further prove thegeopolymerization in the dry-mix method. The
162

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Considering that these were stabilized with cement,
the fly-ash-based geopolymer can be considered tohave advantage over cost since fly ash is free as it isa waste material. At 30% geopolymer concentration,
similar UCS values were obtained. Moreover, it issaid that the hardness of geopolymer is twice as muchhigher than cement which indicates that geopolymer
is less deformable and has a higher brittle behavior[20]. This behavior was actually observed for thestabilized soil at 30% geopolymer concentration
wherein the cured UCS samples were physicallysimilar to concrete during its UCS testing as shown in
Fig. 4.

Fig. 4 The stabilized soil samples at
geopolymer concentration after UCS testing.

concentration ranging from 0% to 30%, wherein the
0% value is considered as the pure soil. The
independent variables are the strength properties
which are qu and CBR Index.
𝑞( = 3135.75𝐺 − 37564.80𝐺 5 + 140365𝐺 7(1)

𝐶𝐵𝑅 𝐼𝑛𝑑𝑒𝑥 = 2.77 + 25.64𝐺 + 257.66𝐺 5(2)

where qu is the UCS value (kPa), unsoaked CBR
Index (%), and G is the geopolymer concentration(%/100). The data points of both models for Eq. (1)and Eq. (2) have p (Prob > F) values of less than
0.0001 and indicate the rejection of the null
hypothesis. This means that the data points for boththe qu and CBR Index have a lack of fit in a linear
trend and require a higher order polynomial.
The R2 value of the model equations were 0.9856
for Eq. (1) and 0.9123 for Eq. (2). These denote a
good fit for the data points in terms of their respectivemodel equations. Referring to Fig. 5 and Fig. 6, theequality graphs of both equations are observed tohave high r values between the predicted values andthe actual values. This implies that the predicted andactual values have a very strong correlation which
verifies both model equations.

30%

Similarly, the CBR index of the soil improved as
it was stabilized with geopolymer. The CBR index of
the stabilized soil increased as the geopolymer
concentration increased as shown in Table 4. As
previously discussed, the geopolymer creates astronger soil structure since it acts as a binder between
the fly ash and the soil. At 10% and 20% geopolymer
concentration, the stabilized soil had CBR indices of
9.89% and 16.24%, respectively, which classifies it
as subbase material. At 30% geopolymer
concentration, the stabilized soil can be used as basematerial as its CBR index has reached 34.32%. With
this said, the highest increase in CBR index is 32.64%
when compared to the pure soil, which is 1.68%. Thisis slightly similar to a local study [11] and, studies in
Nigeria [12], Germany [13], Sudan [15], USA [16]which applied fly ash on several types of soil. Thesestudies had results wherein the CBR indices increasedby 30% to 55%. This suggests the possible use of thedry mix geopolymer for stabilizing soil based on the
improved CBR indices of the pure soil as the
improvements are similar to other studies.

Fig. 5The equality graph of the UCS values.

Fig. 6The equality graph of the CBR indices.

Table 4 CBR results of the stabilized soil
Geopolymer
CBR Index (%)
General Rating

10%
9.89
Fair

20%
16.24
Fair

Uses

SubbaseSubbase

30%
34.32
Good
Base,
SubbaseANOVA Analyses and Geopolymer Equations

SEM of Geopolymer-Stabilized Soil

The factor in the equations is the geopolymer

The SEM images in Fig. 7 show how the163

GEOMATE - Mie, Japan, Nov. 21-24, 2017

geopolymer gel formation spread throughout the
microstructure as the geopolymer concentration
increases. At 10% and 20% geopolymer
concentration, the fly ash and the soil particles arestill visible with the presence of geopolymer gels.
These geopolymer gels have bound the sphericalparticles of the fly ash together with the soil particles[21]. Notably, the 30% geopolymer gels barely show
any particles of both the fly ash and the soil particles.
The particles of the precursors have been completely
replaced by the geopolymer matrix caused by theincreased formation of geopolymer gels. The
microstructure shows a compact structure wherein theparticles are not separated; they are connected
together in the geopolymer matrix. Moreover, the
30% geopolymer concentration shows the crystallinelike structure [1], [22] which is commonly found ingeopolymer. These verify that geopolymerization
occurs in the dry mix method of synthesizing
geopolymer stabilizers.

feature, connecting and surrounding the fly ash
particles and soil particles. Moreover, the SEM
images of the pure soil and the stabilized soil shows
how the geopolymer changes the morphology of thepure soil into a denser soil structure. As for the FTIR
results, these have further confirmed thegeopolymerization taking place in the stabilized soil
which was evident in the change in peaks within the
spectra.

Fig. 8 The FTIR spectra of the fly ash, the puregeopolymer, the soil, and the stabilized soil.
The synthesized geopolymer in the study is
considered to be the most effective at theconcentration level of 30% since both mechanicalproperties, UCS and CBR Index, increase as thegeopolymer concentration is increased from 10% to30%. For the UCS results, the improvements are
considered to be significant. The application ofgeopolymer on the soil has allowed the stabilized soil
to be molded into UCS samples as the soil does nothave cohesive characteristics due to its sand content.
The qu values, from 10% to 30% geopolymer
concentration, increase significantly from 78.29 kPa
to 1349.74 kPa. As an embankment material, thegeopolymer has improved the performance of the soil
based on the CBR Index which has increased to avalue of 34.32%. The pure soil is rated as Poor for
Subgrade use, whereas the stabilized soil has
improved to Good for Base and Subbase use.
The geopolymer, based on these results, has thepossibility of being an alternative to conventional soil
stabilizers such as cement and lime. The main reason
for this is that the geopolymer in the study wassynthesized through a different approach rather thanthe method of using liquid activators, which allows
easier application in the field. Focusing on
geopolymerization, this further concludes thatgeopolymerization can still occur in the dry mix
method.

Fig. 7 The SEM images of SM at geopolymer
concentrations of 10% (left image), 20% (center),and 30% (right) at 2000x magnification.
FTIR of Geopolymer-Stabilized Soil
The FTIR spectra in Fig. 8 show how the spectraof untreated soil change when geopolymer is applied.
The stretched bands at wavenumbers from 800 to
1200 cm-1 are considered as the phase change of fly
ash when geopolymerization takes place. These peaksof the bands at that range (800-1200 cm-1) show a
behavior of shifting to the right or a shifting to lower
wavelengths from the untreated to treated soil caused
by geopolymerization [22]. Moreover, the bands ofthe untreated soil at 600 to 800 cm-1, as it is treatedwith geopolymer, shows the vibrations similar to thatof the pure geopolymer. This indicates the reaction ofbending and stretching of silicate frameworks [23].
CONCLUSION
The study is aimed towards testing an alternative
method of synthesizing a geopolymer soil stabilizer,
which can practically be applied in the field ofconstruction. The SEM images have qualitatively
verified that geopolymerization occurs in the dry mix
method. It has shown the formation of geopolymer
gels in the stabilized soil. These gels are characterized
by their crystalline-like structure and their binder-like

RECOMMENDATIONThe study has used a limited range of values forgeopolymer concentration due to the considerationthat higher concentration values are costlier due torequiring more alkali activators. However, since these164

GEOMATE - Mie, Japan, Nov. 21-24, 2017

are necessary in obtaining an optimal concentration
value, it is recommended for future studies to take
into consideration concentration values ranging from
40% to 90%. This will produce a geopolymer
concentration that can maximize soil stabilization.
The method of testing the CBR property of thestabilized soil was only through the unsoaked CBR.
The soaked CBR was not tested due to time
constraints. The soaked CBR is significant as it
simulates the strength of soil when saturated or during
events of flood. This is why it is recommended to test
the geopolymer stabilizer in terms of the soaked CBR.
The geotechnical properties of the stabilized soil
were not tested in the study. The geotechnicalproperties such as gradation and permeability are
considered to be significant properties. These may
change when soils are stabilized with geopolymer. As
such, it is recommended to test these properties tofurther discover the extent of the improvement ofgeopolymer soil stabilization.

[8]

Baykal, G., Edinçliler, A., & Saygılı, A. (2004).
Highway embankment construction using fly
ash in cold regions. Resources, Conservation
and Recycling,42(3), 209-222.
[9] Galupino, J. G., & Dungca, J. R. (2015).
Permeability characteristics of soil-fly ash
mix. ARPN Journal of Engineering andApplied Sciences,10(15).
[10] Dungca, J. R., & Galupino, J. G. (2016).
Modelling of permeability characteristics ofsoil-fly ash-bentonite cut-off wall using
response surface method. International Journalof Geomate.
[11] Dungca, J. R., & Jao, J. L. (2017). Strength andpermeability characteristics of road basematerials blended with fly ash and bottom
ash. International Journal of GEOMATE,
12(31).
[12] Okunade, E. A. (2010). Geotechnical properties
of some coal fly ash stabilized Southwestern
Nigeria lateritic soils. Modern Applied
Science, 4(12).
[13] Ismaiel, H. H. (2006). Treatment andimprovement of the geotechnical properties ofdifferent soft fine-grained soils using chemical
stabilization.
[14] Rajakumar, C., & Meenambal, T. (2015). Effectof coal ash in the stabilization of expansive soil
for the pavement. International Journal of
ChemTech Research, 8(1), 170-177.
[15] Zumrawi, M., & Hamza, O. (2014). Improving
the characteristics of expansive subgrade soils
using lime and fly ash. International Journal of
Science and Research.
[16] Edil, T. B., Acosta, H. A., & Benson, C. H.
(2006). Stabilizing Soft Fine-Grained Soils with
Fly Ash. Journal of Materials in Civil
Engineering, 18(2), 283-294.
[17] Ramezanianpour, A., & Alapour, F. (2013).
Compressive strength of fly ash geopolymer
paste designed by taguchi method. Third
International Conference On Sustainable
Construction Materials And Technologies.
[18] Legrans, R., & Kondo, F. (2015). Strength
improvement of dredged soil throughsolidification by eaf slag-based geopolymer.
Bull. Fac. Agr.,Sagauniv., 33-41.
[19] Yusuf, H., Palluh, M. S., Samang, L., &Tjaronge, M. W. (2012). Characteristicalanalysis of unconfined compressive strengthand CBR laboratory on dredging sedimentstabilized with Portland cement. International
Journal of Civil & Environmental Engineering,
12.
[20] Skvara, F., Kopecky, L., Nemecek, J., &Bittnar, Z. (2006). Microstructure ofgeopolymer materials based on fly ash.
Ceramics − Silikáty.
[21] Sukmak, P., Horpibulsuk, S., Shen, S.,

ACKNOWLEDGEMENTS
The authors would like to acknowledge the helpof DOST-ERDT for financially supporting this study
towards it completion. The help of Dr. MichaelAngelo Promentilla and Engr. Roy Alvin Malenab are
also greatly appreciated for their aid in the testing andanalysis of the SEM and FTIR tests.
REFERENCES
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Zhang, M., Guo, H., El-Korchi, T., Zhang, G.,& Tao, M. (2013). Experimental feasibility
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Makusa, G. (2012). Soil stabilization methods
and materials (In engineering practice). Lulea
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Thiha, S., & Phueakphum, D. (2015). Shear
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using Geopolymer. The 20th National
Convention On Civil Engineering, 8-10.
Dungca, J. R., & Dynchangco, L. T. (2016).
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blended with waste limestones. International
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permeability
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Ahmaruzzaman, M. (2010). A review on theutilization of fly ash. Progress in Energy andCombustion Science. Retrieved March 15,
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Chindaprasirt, P., & Suksiripattanapong, C.
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[22] Somna,
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166

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LONG-TERM STRENGTH OF BUBBLE-MIXED SOLIDIFIED SOIL
MADE FROM VOLCANIC ASH

1Atsuko Sato1 and Toshihiro Hayashi2
Civil Engineering Research Institute for Cold Region, Japan;2 Hokkaido Development Bureau, Japan

ABSTRACTThe Civil Engineering Research Institute for Cold Region has been developing a bubble-mixed solidified soilthat affords soil pressure reductions on civil engineering structures. This technique is one way to effectively use
soil generated at construction sites. The bubble-mixed solidified soil is created by mixing volcanic ash, water, airbubbles, and a soil stabilizer. The volcanic ash is from the suburbs of Sapporo, a city in central Hokkaido,
Northern Japan. The strength and density of a roughly 24-year-old specimen of bubble-mixed solidified soil
were measured, and the temporal changes in the strength of the specimen were investigated. Previous data on
this specimen was examined in comparison with the data from the current measurements. It was found that thematerial had the strength required for the structure. However, the strength of the material was found to increase
and peak in two years, after which the strength decreased and the material deteriorated.
Keywords: Long-term Strength, Bubble-mixed Solidified Soil, Volcanic Ash, Deterioration, Impact acceleration

it in any shape. The light weight of such soil cancontribute to load reductions on the ground. In
addition to the above advantages, the solidificationof this material progresses with time, and the earthpressure acting on civil engineering structures can be
reduced by using this material. Because of theseadvantages, bubble-mixed solidified soil is amaterial that can be used in various areas.

INTRODUCTION
The Civil Engineering Research Institute forCold Region (CERI) has been engaging in studies onbubble- mixed solidified soil [1]. In previous studies,
the long-term strength of this material has beenverified, and it has been reported that the material
has sufficient long-term durability for earth works[2]-[3]. CERI measured the strength and density of
approximately 24-year-old specimens of bubblemixed solidified soil, a type of lightweight soil. The
measurement results and previous data are reported
in this paper.

TESTING METHOD
Creation of Slurry
In the experiment of this study, bubble-mixed
solidified soil was created by using volcanic ash(Shikotsu pyroclastic fall deposit) from a site in thesuburbs of Sapporo, a surfactant foaming agent anda cement base solidification material. The basic
physical properties of the volcanic ash are shown in
Table 1, and the mix proportion of the bubble-mixed
solidified soil is shown in Table 2.

BUBBLE-MIXED SOLIDIFIED SOIL
Bubble-mixed solidified soil is a plasticizedmaterial made by mixing material soil, water, soil
stabilizer and bubbles as shown in Fig. 1. Various
soil materials, including poor quality soil generated
at construction sites, can be used as materials forbubble-mixed
solidified
soil.
Bubble-mixed
solidified soil is a plasticized material and does not
require compaction, which makes it possible to form
Water

Soil stabilizer

Creation of Specimens, and Test Method

BubbleTo measure the unconfined compressive strength,
in 1992 specimens were made by pouring slurry in
PVC pipe molds of 5 cm in diameter and 10 cm inheight, covering them with plastic wrap and curing
them at a constant temperature of 20℃ for 1, 7 and
28 days. Part of the above slurry was poured into an
experimental soil chamber of 4.5m in length, 4.23m
in width, and 2.25m in depth. At 28 days, thegenerated onsite solidified bubble-mixed solidified

Material soil
SlurryBubble-mixed solidified soil
Fig. 1 This is how to make the bubble-mixed
solidified soil
167

GEOMATE -Mie, Japan, Nov. 21-24, 2017

Table 1 This is an basic physical properties of soil
Sample nameTakinoSoil particle density ρs(g/cm3)
2.402
Natural water content wn (%)
33.7
17.5
≧ 2 mm (%)
Grain size
75 μm - 2 mm (%)
50.2
distribution
32.3≦ 75 μm (%)
Consistency limit
N.P.
Classification symbol of the groundSVmaterial

strength was measured. The other block had beenleft in the room for the roughly 24 years until
February 2016. The top surface and one of the sidesurfaces of a block were made flat. For these two
surfaces, the impact acceleration [4] was measured.
Soil hardness index was also measured on these two
surfaces by using a soil hardness tester [5]. An
unconfined compression test was done by using six
cylindrical specimens (5cm in diameter by 10cm inheight) that were cut out from the block used for theabove two measurements. The strength wasmeasured using three specimens cut out in theperpendicular direction and three specimens cut out
in the horizontal direction. The unconfinedcompressive strength was determined as an averagefor the values of three specimens for each direction.
The impact acceleration and Soil hardness index
were determined as an average of the values
measured at ten points on the two surfaces of theblock. The unconfined compressive test was alsodone on six specimens (three specimens for theperpendicular direction and three specimens for thehorizontal direction) after they had been submergedin water. The conditions for each test are shown in
Fig. 2.

Table 2 This is a mix proportion of the bubblemixed solidified soil
Volcanic ash (kg)752.06
Mixed
Water (kg)147.94amountBubble (l)395.853
per 1mSoil stabilizer (kg)100
Unconfinedcompressive
strength after 7-day curing
150
Target(kN/m2)value
Wet density (g/cm3)
1.00
Adjusted moisture content
60(%)
soil was dug out of the chamber and two blocks
were cut out and formed. They were 0.5m in length,0.5m in width and 0.25 in height. These two blocks
were left uncovered in a room with an averageannual temperature of about 20℃. This assumes thetemperature in the soil where bubble-mixed
solidified soil is to be constructed. In 1994, twoyears after the blocks were created, three cylindrical
specimens of 5cm in diameter and 10cm in height
were cut out in the perpendicular direction from oneof the blocks, and the unconfined compressive

TEST RESULTS
The Surface of The Bubble-mixed Solidified Soil
A 24-year-old block of bubble-mixed solidified soil
is shown in Photo 1. The edges of the block are stillintact and the surface has not changed from that at
the formation of the block. In the specimen that was
cut out from the block for the unconfinedcompression test, the voids clearly maintained their

Slurry5cm in diameter by
10cm in height

4.5m in length, 4.23m inwidth, and 2.25m in depth(Experimental soil chamber)

Curing them at a constanttemperature of 20℃

0.5m in width and 0.25 inheight (blocks)

1, 7 and 28
days curing

Room with an average annual
temperature of about 20℃

Unconfined compressivetest

2 years curing
5cm in diameter by 10cm inheight (cut out)
Unconfined compressive test

24 years curing
Impact acceleration and Soilhardness index
Horizontal and vertical direction
5cm in diameter by 10cm in height(cut out)
Unconfined compressive test
Perpendicularx, horizontal direction
Submergence non submergenceFig. 2 This is the conditions of each test
168

GEOMATE -Mie, Japan, Nov. 21-24, 2017

Water content (%)

60

Non submergence

50
40
30
20
10
0
1

Photo 1 This is a block and a specimen of 24-yearold bubble-mixed solidified soil

The temporal changes in the wet density of the
bubble-mixed solidified soil are shown in Fig. 3.
The wet density decreases with time. The wet
density of a 24-year-old specimen submerged inwater was equal to that of the specimen at its
formation 24 years earlier. It is considered that evenwhen the density of bubble-mixed solidified soil onsite increases from submergence, a structure nearthat bubble-mixed solidified soil is unaffected by thechanges in the density of the bubble-mixed solidified
soil.

Changes in Strength
The unconfined compressive strength of the
bubble-mixed solidified soil is shown in Fig. 5. The
unconfined compressive strength of the sample
increased for the 2 years since its creation. The
unconfined compression strength of the 24-year-old
sample was about the same as that of the 7-day-old
sample. The unconfined compression strength of thesample decreased with time after the initial 2 years.
Previous studies have reported that deterioration of
cement-treated soil starts at the surface [6] and thatthe strength of cement-treated coal ash decreases
when the coal ash is cured for a long time [7]. In thecase of this study, it was thought that the block of
bubble-mixed solidified soil had deteriorated fromweathering. It is thought that the strength of thecement-treated soil does not decrease as greatly onsite as measured in this study, because the cementtreated soil on site is covered with soil to a certain
extent. However, in designing cement-treated soil, it
is necessary to consider the long-term decrease instrength.
Next, the strength of the 24-year-old block in theperpendicular and horizont al direct ions wasdetermined,and the strength of an internal part of theblock was determined. The results are shown independing on direction were found. It is thought
Table 3. No notable differences in strength that thedirection of placement does not greatly affect theWet density （g/cm3）

1.2
Non submergence

1.0
0.9
0.8
0.7
0.6
10

100

1000

10000

water, the sample started to absorb water
immediately after being placed in the water and it
totally submerged in 10 minutes. The final moisture
content of the sample was roughly 60%, which is theadjusted moisture content. The specimen did notcollapse when submerged in water. The void ratio
remained almost unchanged for 24 years.

Changes in Density

1

100
1000
Elapsed time (day)Fig. 4 This is the days elapsed vs water content

shapes, and no deterioration was found by visualobservation.

1.1

10

10000

Elapsed time (day)Fig. 3 This is the days elapsed, and wet density
Changes in Moisture Content
The moisture content of the bubble-mixed
solidified soil is shown in Fig. 4. The moisture
content decreased with time, and became nearly zeroin 24 years. When the sample was placed in the169GEOMATE -Mie, Japan, Nov. 21-24, 2017

SUMMARY
Unconfined compressive
strength qu(kN/cm2)

2,500

The temporal changes in the properties of
bubble-mixed solidified soil were investigated inthis study. The investigation revealed the following.

2,000
1,500
1,000
500
Non submergence

0
1

10
100
1000
Elapsed time (day)10000

Fig. 5 This is the days elapsed vs unconfinedcompressive strength
Table 3 This is the direction vs strength
Items
Unconfinedcompressive strength
Impact acceleration
Soil hardness index

VerticalHorizontal

Perpendic
ular

258.4

224.1

-

48.6
27.5

47.5
29.4

25.0

Unconfind conpresive strengthqu(kN/m2)

strength of bubble-mixed solidified soil. Fig. 6
shows the relationship between the impact
acceleration and the unconfined compressive
strength of the bubble-mixed solidified soil atplacement in a laboratory soil chamber and therelationship between the impact acceleration and theunconfined compressive strength of the bubblemixed solidified soil at 24 years after placement.
The relationship between the impact accelerationand the unconfined compressive strength for the 24year-old sample is similar to that for the sample atplacement. It is possible to estimate the unconfinedcompressive strength from the impact accelerationeven after a long time.
About the bubble-mixed solidified soil madefrom fly ash, it is reported about elution to theenvironment [8]-[9]. However, since volcanic ash isa stable material, it is considered that hazardous
substances do not elute of bubble-mixed solidified
soil made from volcanic ash into the environment.
600
500
400
300
200
At launch
after 24 years old

100
0
0

25
50
75 100
Impact accerration I(G)125

Fig. 6 This is the Impact acceleration vs170
unconfined strength1) No marked changes were observed by visualinspectionof
24-year-old
bubble-mixed
solidified soil.
2) The water content, wet density and strength of
bubble-mixed solidified soil decreases with time.
Deterioration was observed in the bubble-mixed
solidified soil.
3) The strength of bubble-mixed solidified soil is notaffected by the direction of placement.
REFERENCES[1] Yasuaki Matsuda, Norihiro Mihara and Junichi
Nishikawa “An Experimental Study on Foam
Mixed Solidified Soil Using Volcanic Ash”,
Monthly Report of Civil Engineering ResearchInstitute of Hokkaido, No. 482, 1993.
[2] Yoichi Watabe, Hiroyuki Saegusa, Tomoyuki
Ueda, Takashi Tsuchida, Yoshio Mitarai andHiroshi Shinsha “Long-term Properties of Airfoam Treated Lightweight Soil Placed in
Coastal Areas,”, Proceedings C of JSCE, Vol.
63, No. 1, 2007, pp. 237-248.
[3] Kazuyori Fujioka, Nagao Kazuyuki, Kitamura
Yoshinori and Kato Yoshinori, ”Experiment on
the Long-term Durability of Bubble-mixed
Lightweight Soil”, 60th JSCE Annual Meeting,2005, pp. 725-726.
[4] The Japanese Geotechnical Society, “MethodsofSubsurface
Investigation,
andInterpretations”,2012, pp. 758-759.
[5] The Japanese Geotechnical Society, ”MethodsofSubsurface
Investigation,
andInterpretations”, PP. 758-759, 2012.
[6] Hirochika Hayashi, Satoshi Nishimoto, Kanta
Oishi and Masaaki Terashi, ”Long-term
Characteristics on Strength of Cement Treated
Soil (Part 1) ,Onsite survey of a soil-cement
column constructed by using the DJM method”,
Monthly Report of Civil Engineering ResearchInstitute of Hokkaido, No. 611, 2004, pp. 11-19.
[7] Atsuko Sato, Satoshi Nishimoto, Takahiro
Yamanashi, Teruyuki Suzuki and Shinichiro
Kawabata, “Long-term Properties of Solidified
Slurried Coal Ash Used for an Artificial Island
and Granulated Coal Ash Used forGEOMATE -Mie, Japan, Nov. 21-24, 2017

Embankments”, Proceedings of the JGS
Symposium on Environmental Geotechnics,
2013, pp. 109-112.
[8] Sivapullaiah PV and Arif Ali Baig Moghal,“Leachability of Trace Elements from Two
Stabilized Low Lime Indian Fly Ashes”,
Environmental Earth Sciences, Vol. 61, No. 8,
2010, pp.1735-1744.
[9] Arif Ali Baig Moghal and Sivapullaiah, “PV
Retention Characteristics of Cu2+, Pb2+ and
Zn2+ from Aqueous Solutions by Two Types of
Low Lime Fly Ashes”, Toxicological andEnvironmental Chemistry, Vol. 94, No. 10,
2012, pp. 1941-1953.

171

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEVELOPMENT OF CEMENT-BENTONITE MIXED SOILS BYMIXINGSODIUM CARBONATE
Ko Hashimoto1, Shuichi Kuwahara2, Yukio Uchida3, Tadaomi Eguchi4, Shinya Inazumi5
1Advanced Course of Architecture and Civil Engineering, Akashi College, National Institute ofTechnology, Japan, 2Marushin Co., Ltd., Japan, 3Japan Material Co., Ltd., Japan, 4Department of Civil
Engineering, Akashi College, National Institute of Technology, Japan, 5Department of Civil
Engineering, Shibaura Institute of Technology, Japan

Abstract
Cement milk is used as a grout to fill holes which are resulted from pile extraction. Although cement milk has anadvantage of being able to perform blending and placing according to circumstance of work on site, cement andwater cause segregation, so uniform filling is difficult over the entire length of holes. In addition, there is a
disadvantage that cement milk can’t perform a predetermined strength when diluted by groundwater erosion.
Sodium carbonate is a substance expected to suppress the segregation of cement milk and to speed up thedevelopment of strength. In this study, we conducted an indoor mixing test on fillers mixed with sodium carbonate
into cement milk which is a mixture consisting of water, cement and bentonite, and examined various
characteristics from the viewpoint of physical and chemical aspects. (1) By mixing sodium carbonate, bleeding of
cement milk is suppressed. This is considered to be due to increased swelling of bentonite by receiving sodiumions. (2) By mixing sodium carbonate, the strength development time of cement milk is advanced and the longterm strength also increases. This is considered that calcium carbonate is generated at the initial stage of reaction
from the reaction of bentonite and sodium carbonate.
Keywords: cement, bentonite, sodium carbonate, bleeding, early strength1.

Introduction

1.1.

BackgroundIn demolition work, it is necessary to remove existing
piles in the ground. If new land use is planned, existing
piles must be removed so as not to interfere with pilefoundation of newly built-structures. In addition,
existing piles remaining in the ground are industrial
waste, so troubles often occur in the land saletransaction. Therefore, removal of existing piles is
indispensable. In order to remove an existing piles, adrawing out method is generally adopted. In thedrawing out method, holes are formed in the ground,which adversely affect the ground environment. In thevicinity of the hole, it may cause problems such as
collapse of earth and sand, subduction of thesurrounding ground, weakening, so it is necessary tofill the filling and stabilize the ground quickly.
Depending on the construction site, the properties
required for the filling are different, but there is no
regulation on filling presently. From the above, there
is a demand for constructing a filler that can reliably
fill and secure stable strength.
1.2.

Purposeseparation when filling holes generated by pulling out
existing piles. We aim at sophistication of cement
bentonite typed cavity filling since it is possible toadjust blending filling at the construction site. By
mixing sodium carbonate (Na2CO3), it is expected thatthe strength development of the cement bentonite typecavity filling will be promoted and the bleeding will
be suppressed. We will examine the improvement andusefulness as cavity filling by conducting an indoor
blending test on cement bentonite and sodium
carbonate mixed cement bentonite. For examining theimprovement and usefulness, a comparative test is
conducted in view of strength characteristics, fluidity
and material separation.
1.3.

OutlineIn this research, we carried out uniaxial compression
test, penetration test, bleeding test and flow test on
cement bentonite and cement bentonite mixing sodium
carbonate, and examine usefulness of cement
bentonite typed filling by mixing sodium carbonate. In
addition, we consider the mechanism of thedevelopment of various properties exerted by mixing
sodium carbonate from the physical and chemical
point of view (Fig.1).

We will aim for the development of a filling thatexhibits uniform strength without causing material
172

GEOMATE - Mie, Japan, Nov. 21-24, 2017

2.

MethodResearch background

2.1.

Materials and Mixing Conditions
Purpose of research(1) Cement
The type of cement used in this study is ordinary
portland cement, and one is having a density of 3.16
g /cm3 and a specific surface of 3200cm2/g. Cement isa main component which exerts a curing function as a
cement bentonite typed cavity filling because it
reaction with hydration and develops initial and longterm strength by the formation of ettringite andcalcium silicate hydrate(C-S-H).

Indoor mixing test
Arrangement andconsideration of test results

Investigation of usefulness as
filling(2) Bentonite
The chemical components of the bentonite used on
our test are shown in Table 1. Bentonite has the effectof suppressing material separation of cement andwater by swelling property due to take water into theone1). Bentonite is a smectite clay mineral containing
montmorillonite as a main component and has alayered structure in which thin plate crystals arestacked. The crystal is negatively charged andelectrical equilibrium is maintained by adsorbing
cations between crystal layers. The interlayer cationsof montmorillonite are mainly composed of sodiumion (Na+), calcium ion (Ca2+), potassium ion (K+),
magnesium ion (Mg2+), and the properties of bentonite
vary depending on the type of the one. The type isdivided into two types, one is called Na type where alarge number of monovalent cations such as Na + andK+ are adsorbed, and the other is called Ca type wherea large number of divalent cations such as Ca2+ andMg2+ are adsorbed2). The bentonite used in thisexperiment is a Na type bentonite having many Na + ininterlayer cations.

Consideration aboutmechanism of upgrading

Fig.1

Table 1 Chemical components of bentonite
Chemical Components
SiO2
Al2O3
Fe2O3
MgO
CaO
Na2O
K2O
Ignition loss

Content (%)
67.1
16.8
3.7
3.3
2.7
2.2
1.3
2.9

Table 2 Chemical components of the admixture(3) Sodium carbonate
When we mix sodium carbonate as an admixture intoa cement bentonite typed cavity filling in thisexperiment, we use anhydrous salt obtained by heating
at a high temperature of 300°C. Table 2 shows thechemical components of the admixture, and it contains
Na2CO3 of 99.41%. Sodium carbonate is expected topromote the hydration reaction between cement andwater and exert the effect of early strength
development3).
(4) Mixing condition
Table 3 shows the mixing conditions of each material
used in the series of tests. The target strength is set to
0.5N/mm2 on the mixing condition. In the precast piledriving method prescribed in the "Public BuildingStandards Manual"4), since the pile circumferential
fixing liquid is set to 0.5N/mm2 at the compression
strength after 28 day material age and is considered tobe the same as the ground strength, the strength isgenerally adopted as a standard. In blend A and B,
cement bentonite and cement bentonite mixing sodium

Procedure of study

Chemical Components
Na2Co3NaCl
Fe2O3
Insoluble matter

Content (%)
99.41
0.35
0.003 or less0.001or lessIgnition loss

0.15

Table 3 Mixing conditions of each material
No.
A-1
A-2
B-1
B-2
C
D
E
F
G

B
(kg/m3)
50
50
50
50
50
50
50
50
50

C
(kg/m3)
240
240
300
300
180
200
220
250
260

S
(kg/m3)
0
20
0
20
20
20
20
20
20

W
(kg/m3)
905
897
886
878
916
910
903
894
891

W/C
(%)
377
374
295
293
509
455
410
358
343

carbonate whose weight ratios C/B=5, 6 of cement (C)and bentonite (B) were prepared, and we investigate
the properties of cement bentonite mixing sodium
carbonate perform. In blend C, D, E, F and G, only theamount of cement (C) is changed to prepare cement
173

GEOMATE - Mie, Japan, Nov. 21-24, 2017

bentonite mixing sodium carbonate and the correlation
between sodium carbonate and cement is examined. In
the mixing procedure, water (W) and bentonite (B)were added to a stirrer having a rotation speed of 1,500rpm/min and stirred for 3 minutes, then ordinary
portland cement (C) was added and stir for 3 minutes
and sodium carbonate was added and stir for 3 minutes(Fig.2).
2.2.

Strength Test

The strength development of cement bentonite
mixing sodium carbonate will be examined according
to the Japanese Industrial Standard (JIS A 1216)"uniaxial compression test". Each material is mixed
according to mixing conditions and it is poured into amold having a diameter of 50mm and a height of
100mm to prepare a sample. Curing is performed for7, 14, 28, 60, 90, 120 days in a thermostatic chamber
at 20°C, and a uniaxial compression test is performedat each curing day (Fig.3).
In order to investigate the change about the action of
cement bentonite due to mix sodium carbonate, we
conduct a simple penetration test on samples of A and
B. Penetration resistance values in immediately after
sample mixing and 30 minutes, 1, 2, 3, 4, 5, 6, 7, 8, 12,
24 hours are measured using a simple measuring
instrument (Fig.4).
2.3.

Fig.2 Mixing and stirring of materials

Bleeding Test

A test is carried out according to the JSCE Standards(JSCE-F522) "Bleeding Rate and Expansion Rate Test
Method of grouting Mortar of Prepacked concreat(Polyethylene Bag Method)" in order to evaluate
material separation of water and cement (Fig.5). The
Sample mixing each material put to a height of 200mm
in a polyethylene bag with a diameter of 50mm and theamount of bleeding water after 1, 3, 24 hours ismeasured, and the bleeding rate is obtained using thefollowing formula.

𝐁𝐫 = (

Fig.3 Uniaxial compression test𝑾𝒃
) × 𝟏𝟎𝟎𝑽

Br (%) is the bleeding rate, Wb (ml) is the amount of
bleeding water at each elapsed time, and V (ml) is thevolume of the whole sample.
2.4.

Fluidity Test

The fluidity of cement bentonite mixing sodium
carbonate is evaluated according to JSCE-F521"Fluidity Test Method of grouting Mortar of
Prepacked concreat (Method of P Funnel)". The
Sample mixing each material is filled in a P-funnel
tester having an outflow pipe inner diameter of 13mm,
an outflow pipe length of 38mm and a funnel portion
height of 192mm. The sample is allowed to flow by
releasing a finger from the flow pipe, and we measure

Fig.4 Simple penetration test
174

GEOMATE - Mie, Japan, Nov. 21-24, 2017

the time until the flow of sample is interrupted for the
first time with a stopwatch (Fig.6).

3.
3.1.

Consideration
Consideration on Strength Test

(1) Initial strength development
From the uniaxial compression test results in Fig.8(a), compare the initial strength of cement bentonite
and cement bentonite mixing sodium carbonate. A-1
has the 7th day strength of 0.09N/mm2, and A-2 has aseven-day strength of 0.30N/mm2, so A-2 is stronger
than A-1. Similarly in the comparison between B-1
and B-2, the 7th day strength of B-1 is 0.37N/mm2 andthe 7th day strength of B-2 is 0.59 N/mm2, so mixing
sodium carbonate makes cement bentonite stronger
than when it does not mix. Therefore, it can be said
that the initial strength of cement bentonite increases
by mixing sodium carbonate. In addition, since nosignificant difference is observed in the strength
development behavior up to the 28th day of age, it isthought that sodium carbonate influence the strength
development before the 7th day of age.
In Fig.7, the results of the penetration test showedthat the resistance values of cement bentonite of A-1
and B-1 rise about 8 hours after mixing and stirring ofeach material, but the values of cement bentonite
mixing sodium carbonate of A-2 and B-2 rise about 1
hour after mixing and stirring. Since the setting
initiation time of cement bentonite is accelerating, it
can be said that mixing sodium carbonate affects thesolidification performance at the one-day of age.
Exercising solidification performance in 1 hour after
filling prevents the invasion of groundwater in the
ground and helps developing stable strength cement
bentonite type cavity filling.
From the above, mixing sodium carbonate into
cement bentonite promotes the solidification
performance immediately after mixing and stirring ofeach material, and exerts a useful effect as a filling.

Fig.6 fluidity test
7

resistance value(kgf/cm2)(2) Long-term strength
From the uniaxial compression test results in Fig.8(a), compare the long-term strength of cement
bentonite and cement bentonite mixing sodium
carbonate. In comparing A-1 and A-2, B-1 and B-2,
the strength of mixing sodium carbonate is stronger
than not mixing at any age. However, as for thetendency of strength development, there is a tendency
that the strength increases up to about the 28th day of
age in any samples, and the strength hardly increase
after that. In addition, Fig.9 shows the values
normalized by the strength of 28th day of age(hereinafter referred to as compression strength ratio).
Comparison of each sample from Fig.9 (a) showed nosignificant difference in long-term strength
development behavior after 28th day of age, and theFig.5 Bleeding test

A-1

6

A-2

B-1

B-2

5
4
3

2
1
0
0

3

6

9

12

15

18

21

24

elapsed time (h)Fig.7 Result of penetration test

compressive strength ratio is around 1.0, except for
B-1. There is not effect on the long-term strength
development due to mix sodium carbonate, so thereason why the strength is larger on each age at the175

GEOMATE - Mie, Japan, Nov. 21-24, 2017

time mixing sodium carbonate is considered that theincrease of the initial strength affects the long-term
strength development.

1.40

unconfined cimpression
strength(N/mm2)

1.20(3) Increase mechanism of initial and long-term
strength
The amount of cement is changed in C, D, E, F, and
G of cement bentonite mixing sodium carbonate. From
Fig.8 (b), there is a trend that the smaller the watercement ratio is, the stronger the strength is at each age.
In addition, from Fig.9 (b), there is no clear differencein the tendency of strength development in any
samples except for C, and the compressive strength
ratio at 90th day of age is about 1.15. There is nodifference in behavior of initial and long-term strength
development of cement bentonite mixing sodium
carbonate by difference in cement amount, so it can besaid that sodium carbonate has no effect on cement.
Therefore, the initial strength increase of cement
bentonite by mixing sodium carbonate does notpromote the hydration reaction between cement andwater, and it is considered that forms a cured bodydifferent from cement hydrate.
Here, attention is paid to sodium carbonate andbentonite. Bentonite has different properties
depending on the type of interlayer cation ofmontmorillonite, but bentonite easily changes its
properties by ion exchange with other types of cations
since it has ion exchange properties. The interlayer
cation exchangeability increases in the following
order5).

B-1

B-2

0.60
0.40
0.20

0.00
20

40

60

80

100

120

140

material age (day）(a)

Comparison by mixing sodium carbonate

unconfined compression
strength(N/mm2)

0.60

C

D

E

F

G

0.50
0.40

0.30
0.20

0.10
0.00

0

20

40

60

80

100

material age (day)(b) Comparison by changing cement amountFig.8 Result of uniaxial compression test

compressibe strength ratio( σ/σ28)

1.400
1.200
1.000
0.800
0.600
0.400
0.200

A-1

A-2

B-1

B-2

0.000
0

20

40

60

80

100

120

140

material age (day)(a) Comparison by mixing sodium carbonate
compressive strength ratio(σ/σ28)1.400

Consideration on Breathing Test

Table 4 shows the results of the bleeding test. In
Cement bentonite of A-1 and B-1, the bleeding rateincrease with the passage of time, but in cement
bentonite mixing sodium carbonate of A-2 and B-2,
about 0.5% bleeding is only confirmed after 1 hour,
and there is no moisture on the surface of the specimen.
Similarly, in C, D, E, F, and G, it can be confirmed thatthe bleeding rate becomes 0% within 24 hours fromthe mixing of the materials. The decrease in the
bleeding rate of cement bentonite due to the mixing

A-2

0.80

0

𝑵+ < 𝑲+ < 𝑪𝒂𝟐+ < 𝑴𝒈𝟐+
When sodium carbonate (Na2CO3) dissolve in water,
it ionizes to sodium ion (2Na+) and carbonate ion(CO32-).Therefore, Ca2+ contained in the interlayer
cations in the bentonite and Na+ ionized from thesodium carbonate perform ion-exchange, and Ca2+ andCO32- are bonded to form calcium carbonate (CaCO3).
Calcium carbonate is a water-insoluble substance, andforms a cured body by binding molecules with eachother. The early strength development of cement
bentonite by mixing sodium carbonate and theincrease in long-term strength are attributed to theformation of a cured body of calcium carbonate
immediately after mixing of materials.
3.2.

A-1

1.00

1.200
1.000
0.800
0.600

0.400
0.200

C

D

E

F

G

0.000
0

20

40

60

80

100

material age (day)(b) Comparison by changing cement amountFig.9 Compressive strength ratio
sodium carbonate is attributed to the increase in theswellability of bentonite and the initial strength
development of cement bentonite. Bentonite exerts
swellability by interlayer cations of montmorillonite
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 4 Results of bleeding and fluidity test
No.

A-1
A-2
B-1
B-2
C
D
E
F
G

flowing
downtime (s)

1hour

7.7
7.6
7.8
7.6
7.7
7.7
7.7
7.7
7.7

3.6
0.5
4.0
0.4
0.9
0.7
0.5
0.5
0.5

bleeding rate (%)
3hour
24hour
9.3
0.0
9.5
0.0
0.8
0.5
0.0
0.0
0.0

9.5
0.0
9.8
0.0
0.0
0.0
0.0
0.0
0.0

adsorbing water molecules. As compared with Ca typebentonite, the Na type bentonite has a weak electricalattraction between the unit layers, and so it is likely toswell when adsorbing water molecules. As describedabove, sodium carbonate in water is ionized togenerate Na+, which is exchanged with Ca2+ contained
in interlayer cations in bentonite. It is considered thatthe swelling property of bentonite is improved,
because the interlayer cations become more inclusiveof Na+. In addition, a hardened body is formed quickly
since calcium carbonate is produced, and movement ofwater molecules in cement bentonite is inhibited.
There is also a decrease of the amount of water due tothe hydration reaction with cement. Therefore, it isconsidered that various phenomena such as increase ofswellability with bentonite due to mixing of sodium
carbonate, early strength development of cement
bentonite, and hydration reaction of cement and water
are involved, and the bleeding does not occur after
several hours from mixing.
3.3.

Consideration on Fluidity Test

Table 4 shows the results of the fluidity test. In eachsample, the flowing down time is about 7.7s, and nodecrease in fluidity of cement bentonite due to mixing
sodium carbonate is observed. As described above,since curing started in about one hour after mixing thematerials, the early strength development performancedoes not affect the fluidity at the time of filling.
Although there is a possibility that material separation
may occur due to flowing down, since bleeding hardly
occurs, it can be said that the samples are having
moderate fluidity. Therefore, it is able to say that thecement bentonite mixing sodium carbonate has
ensured workability as a cavity filling.

4.

Conclusions

In this study, the usefulness of the cement bentonite
typed cavity filling mixing sodium carbonate was
examined from the viewpoint of strengthcharacteristics, material separation and fluidity. The
obtained results are shown below.
(1) From the uniaxial compression test, mixing
sodium carbonate increases the initial and longterm strength of cement bentonite. The earlystrength development helps stabilizing the
ground as soon as possible.
(2) From the penetration test, by mixing sodium
carbonate, cement bentonite exerts curingperformance from about 1 hour after mixing
materials. The rapid gelation prevents invasion ofgroundwater into the filling in the ground, andthe filling can stably exhibit the predetermined
strength.
(3) From the bleeding test, bleeding of cement
bentonite is suppressed by mixing sodium
carbonate. When it fills into the hole made bypulling out piles in the ground, the materials is
kept homogeneous and the strength is not differ
depending on the depth direction.
(4) From the fluidity test, the fluidity of cement
bentonite is not lost by mixing sodium carbonate.
Workability is assured in filling holes in the
ground.
In the future, it is necessary to clarify the mechanismof various characteristics development by verifying
from a physicochemical point of view.

References[1] Kouken Horii, Masaaki Nishi, Tsutomu
Yamazaki, Junichi Sakamoto, Michimae Taizou,
Yasushi Utaka, “Development of cement
bentonite complex solidified bodies using
concrete recycled materials”, Summaries of the
Academic Lectures of the Japanese Association ofArchitectural Conferences, 2007.
[2] Yashima Takashi, “Estimation of smectite
exchangeable cations by powder X-ray regression
method”, JGCA Technical Forum 2011 lecturecollection, No. 40, 2011.
[3] Kiyoshi Kato, Naoki Kato, Toshio Yuzawa, Isao
Masukawa, “A Study on Rapid Evaluation ofLong-term Strength and Unit Cement Volume by
Ultimate Initial Strength of Rapid HardeningPromoted Concrete”, Report of ConcreteEngineering Annual Papers Report, pp. 343 - 346,
1990.
[4] Ministry of Land, Infrastructure and Transport,“Public
Building
Construction
Standard
Specification (Building Construction), Heisei
20th edition, Ministry of Land, Infrastructure andTransport, 2014.
[5] Masanobu Ogata, “Characteristics of bentonite
and its application”, Clay science vol. 46, No.2,
pp.131-138, 2007.

177

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEVELOPMENT OF REAL-TIME CHECKING SYSTEM FOR
GROUND IMPROVEMENT WORKS BY
HIGH PRESSURE INJECTION
Gicheol Lee1, Shinya Inazumi2, Hiroyuki Hashida3, Tadashi Chuman4, Keiji Okumura5 andKazuhiro Ishimaru6

National Institute of Technology, Akashi College, Japan, 2Shibaura Institute ofTechnology, Japan, 3Sumice Kenzai Co., Ltd., Japan, 4,5Estec Co., Ltd., Japan

1,6

ABSTRACTIn contrast to the mechanical stirring method in which the ground soil and the modifying material are mixed
and stirred by stirring blades and the improved body is formed in the ground, the high pressure injection stirring
method is a method in which the improved diameter is changed due to soil condition, etc. There is a possibility
that it can be changed with, and a method for easily confirming the shape, particularly the improved diameter, ishighly desired. In this research, we propose and propose a method that can make "visualization" of this improvement situation and confirm the improved diameter in real time. Confirmation was made by measuring water quality
in multiple items. From the results, it was confirmed that pH and the values of the other 5 items changed at thesame time. And the change was due to the arrival of the cement slurry. Therefore, it can be said that real-timemeasurement is possible by visualization of improved diameter by water quality measurement conducted this time.
Keywords: real-time checking system, pH, ground improvement, high pressure injection
rod is rotated and pulled up by several centimeters at
regular time intervals to form a columnar
improvement body. Although it is possible to makean improved body with a diameter of 2 to 5 m with asmall boring, it is very important to confirm that thediameter of the improved body is made according to
the plan as it depends on injection specifications andground strength.
As an earthquake countermeasure, in addition toreinforcement of the tide bank, reinforcement of thepile foundation can also be mentioned. However,
because the reinforcement of pile foundations is in
the ground and restrictions on sites and restrictions
on heads, reinforcement methods are currently
limited. One of the pile foundation reinforcement
work performed under such conditions is Confining
Pile Reinforcement Method. This method is aconstruction method that constructs a pilefoundation structure resistant to earthquakes byimproving the ground near the middle in the depth
direction of the pile using cementitious materials. An
improved body of the Confining Pile Reinforcement
Method is also produced by the high-pressure
injection agitation method, but there is a soundconfirmation method as a method for confirming thisform. The method is a method in which a guide pipe
is installed at a planned position to be the outer
peripheral portion of the improved body, amicrophone underwater is inserted into the guiding

INTRODUCTION
Currently as a measure against the Nankai
Trough Earthquake, strengthening breakwaters isurgent in Japan. The main way of present
reinforcement work is to strengthen the ground by
making columns with cement. It is an invisible partthat a soil-cement column is made, so it is importantto check if the soil-cement column is made asplanned. Particularly, in contrast to the mechanicalstirring method, the high pressure injection stirring
method has a possibility that the improved diametermay change depending on the soil conditions and thelike, therefore, a method of easily confirming thediameter is desired [1]. In this research, we propose
a method to confirm the improvement of thediameter in real time by "visualizing" this situation.
Experiments to confirm the state of improvement
construction were carried out at the site where
ground improvement is actually carried out. In thisresearch, we focused on improved bodies withdouble pipe type high pressure injection stirring
method. The high pressure injection stirring method
is a ground improvement method in which earth andcutting agent are mixed and stirred by cutting the
ground by spraying hardening material and air
horizontally from an injection nozzle attached to thetip of the injection rod [2]. Normally, the injection
178

GEOMATE - Mie, Japan, Nov. 21-24, 2017

tube, and the arrival of the solidified material isjudged by the observed sound [3].
However, in this study, we focused on
confirming the arrival of cement directly, so weselected water quality measurement. Measurement
was also conducted based on pH, which is strongly
related to cement even among water quality.

quality meter WQC-24 shown Fig. 1. This is an
instrument that can measure multiple items
simultaneously [4].
Fig. 2 and 3 show the boring datas of water
quality measurement points.

MATERIALS AND METHODS

We used these instruments for the measurement.

Materials(1) Sensor module WMS-24-1

Measurement tool

(2) Terminal WQC-24-1

Water quality measurements were conducted
twice on the site near a certain river in Osaka
Prefecture using the portable multi-item water(3) Computer(4) Vinyl chloride tubes
Methods

Fig. 1The design of the improved body has a length L= 8.4 m and a diameter φ 3500 mm. First, we placed
three vinyl chloride tubes of different lengths inadvance as shown in Fig. 4 at a point 1750 mm awayfrom the center of the improved body. In the vinyl
chloride pipe, 17 holes with a diameter of 10 mm
were installed between the length of 5 cm from thebottom, and the strainer portion was provided so thatthe cement slurry could enter. The measurement

Portable multi-item water quality meter
WQC-24depth(m)¹soil classification

depth(m)gravely sand¹²³

Fig. 2²

gravel³

gravel mixed cobblestone

⁴

⁴

⁵

⁵

⁶

soil classification

silt mixed clay

silt

⁶

⁷

⁷

⁸

⁸

silty sand

⁹

⁹

¹⁰

¹⁰

Boring data (the first point of measurement)

Fig. 3179

sandBoring data (the second point of measurement)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

items were pH, dissolved oxygen, electricalconductivity, turbidity, salinity, and watertemperature.
In the first measurement, measurements weremade by placing three water quality meters
throughout three vinyl chloride tubes. In the second
measurement, one water quality meter was moved toanother vinyl chloride pipe in accordance with thearrival of the injection, and measurement was carriedout while using it.
The installation depth of the water quality meterfor both the first and second times was set to threeplaces: GL - 9.0 m, GL - 6.0 m, and GL - 3.0 m. The
notation was 1CH, 2CH, 3CH in order from thedeepest point. The groundwater level exists in thevicinity of 3CH.

five items the pH rises due to cement influence,electric conductivity is difficult to convey electricity
by cement slurry mixing due to the properties of
cement. As the cement slurry arrives, the turbidity
rises rapidly, the temperature rises due to thehydration reaction between cement and water, andthe salinity is almost sea water, so if the cement
slurry mixes there, the proportion of salt decreases.
The results of the first water quality
measurement are shown in Fig. 5. At 1CH, no rise in
pH was detected after the cement reached themeasurement point. However, in 2CH and 3CH,
increase in pH could be confirmed immediately after
reaching the measurement point. 2 CH rose to about
11.3 to 13.4, and 3 CH rose to about 10.1 to 12.3.
The results of the second water quality
measurement are shown in Fig. 6-10. First, when thechange in pH is examined, the pH rises by about 3.0
immediately after the injection arrives in 1CH.
However, in 2CH and 3CH, only a small amount of
increase in pH immediately after injection was
confirmed. Examining the other items, the dissolved
oxygen decreased in 1CH, the electric conductivity
decreased, the turbidity increased to the upper limit,
the temperature increased and the salinity decreased.
In 2CH and 3CH, because the rise in pH was small,other values were small changes accordingly.

RESULTS AND DISCUSSION
Results
The first measurement was pH only, the second
measurement was six items of pH, dissolved oxygen,electrical conductivity, turbidity, temperature, andsalinity, and a graph was prepared based on the pH
measurement value. As expected results, it isdifficult to predict dissolved oxygen, but for other

Discussion
The reason why the pH of 1 CH did not change
during the first measurement (Fig. 5)
In 1 CH, no rise in pH was detected after reaching
the measurement location. The following can beconsidered as the cause.
14
12

pH

10
8
6

1CH

4

2CH

2

3CH

0

time(hour,minute,second)(OP: Osaka bay lowest sea level)

Fig. 4

Fig. 5

Arrangement of measuring instrument

180

The results of the first water quality
measurement (pH only)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

10
9
8
7
6
5
4
3
2
1
0

14

10

4
2
0

6
4
2
0

DO

time(hour,minute,second)

The results of the second water quality
measurement (pH and dissolved oxygen)

Fig. 8turbidity
pH

The results of the second water quality
measurement (pH and turbidity)

14

30

14

3

12

25

12

2.5

10

2

8

1.5

6

1

4

10

20

8

15

6

10

0.5

2

5

0

0

0

4

EC

time(hour,minute,second)Fig. 7time(hour,minute,second)pH

The results of the second water quality
measurement (pH and electrical conductivity)

Fig. 9salinity(%)(1) The solidified material injected at the time ofmaking an existing refinement nearby reached thevicinity of the vinyl chloride tube following theunderground water line and closed the tip of the pipe.
(2) The soil that remained in the ground when we
dug a hole to stand vinyl chloride tubes closed the tipof the pipe.
Reason why the pH of 3CH was high from the beginning (Fig. 5)
It is thought that the cause of the pH of 3CH being high from the beginning is the gravel layer andthe influence of the already improved ambient
groundwater.

181

2
0

temperature
pH

The results of the second water quality measurement (pH and temperature)
30

14

25

12
10

20

8

15

6

10

4

5

2

0

0

time(hour,minute,second)Fig. 10pH

temperature(℃)

3.5

pH

EC(S/m)Fig. 6time(hour,minute,second)

pH

pH

8

pH

pH

6

12

turbidity(mg/L)

DO(mg/L)

10
8

14

1000
900
800
700
600
500
400
300
200
100
0

12

salinitypH

The results of the second water quality
measurement (pH and salinity)

GEOMATE - Mie, Japan, Nov. 21-24, 2017rises at a slightly rising timing. Since it is difficult tothink that the value will drop to 0 as with 1 CH, dissolved oxygen isn't able to say useful only with thismeasurement result alone. On the other hand, electric conductivity and temperature can be confirmed
to change according to the properties of cement, so
it is considered to be useful as a confirmation item
for visualization of improved diameter. As turbidity
was also confirmed to increase due to arrival of cement slurry and earth and sand, turbidity is also considered to be useful as a confirmation item for visualization of improved diameter. Also, as in this case,when salinity is contained in groundwater, salinity is
considered to be a useful confirmation item for visualizing the improved diameter.

Summary of the first measurement result
No increase in pH could be confirmed with 1 CH.
However, in 2CH and 3CH, an increase in pH could
be confirmed. And in 2CH and 3CH, after vinyl
chloride tubes was pulled out and the tip part wasobserved, it was confirmed by eyes that cement
slurry adhered to vinyl chloride tube and high pressure jet reached. Also, although we checked the diameter by excavating the upper part of the improvement body, we could also confirm that even here it
was made almost as planned. From this, it can be said
that visualization of improved diameters by pH
measurement and real-time confirmation are possible because increase of pH due to arrival of cement
slurry can be confirmed in the first measurement.

Summary of the second measurement result
Cause of pH rise less than 1 CH at 2CH and 3CH in
the second measurement

Although only few results were obtained in thesecond measurement, useful data could also be reliably obtained. From the results of this research, it isconsidered that particularly useful items are pH,
electric conductivity and temperature. Because these
are indices directly related to cement. Other items
aren't able to say useful because there are not enoughsamples or the available conditions are limited.

As shown in the figure, the pH rose by about 3.0
immediately after reaching the cement slurry in 1
CH. However, in 2CH and 3CH which are not shownin the figure, only a small amount of pH increase ofabout 0.5 to 1.0 could be confirmed immediately after reaching the cement slurry. The reasons why theamount of increase in pH immediately after arrivalof cement slurry at 2 CH and 3 CH was small may
be as follows. Unlike 1 CH where the pH rose
sharply immediately after reaching the cement slurry,both 2 CH and 3 CH had already started to raise the
pH before cement slurry reached. As a result, the pH
increase in 2CH and 3CH became more gentle thanthe change in 1CH, so the change immediately after
arrival of the cement slurry became small. As a fundamental problem, it seems that the reason why thepH rise started before 2CH and 3CH before reaching
is because a trace amount of cement slurry began toenter the vinyl chloride tube before reaching the cement slurry. This tendency is considered to be particularly strong in 3CH because the increase in pH
was more gradual than 2CH. However, as mentioned
in the measurement method, since we used only one
water quality meter in the second measurement, it
was not clear when cement slurry started entering.
But This problem is thought to be avoidable by preparing the water quality meters for the number oftubes and always checking all the CHs at the sametime, as in the case of the first measurement, insteadof using one water quality meter at a time.

CONCLUSIONSIn this research, the relationship with the
improvement situation was verified by measuring
the water quality of six items of pH, dissolved
oxygen, turbidity, electric conductivity, temperatureand salinity by using the Portable multi - item water
quality meter. From the two measurement results, it
was confirmed that the timing at which pH and thevalues of the other 5 items changed, and that thechange was due to the arrival of the cement slurry.
Therefore, it can be said that real-time measurement
is possible by visualization of improved diameter bywater quality measurement conducted this time.
In this water quality measurement, visualization
and real-time measurement are possible, but there isa possibility of measurement failure such as clogging
of the detection tube in 1 CH of the firstmeasurement. Therefore, we need to pursue
measurement methods that can compensate for theabove weaknesses in the future.
In this research, we focused on preparing an
improved body by double pipe type high pressure
injection stirring method, but this is not the only way
to improve ground. Therefore, in the future, it isnecessary to pursue measurement method that can beused not only for the double pipe type high pressure
injection stirring method but also for confirming thesituation of various soil improvement. In addition to
being able to use it not only in various sites but also
it must be made cheaply and easily.

About items examined by the second measurement
Since the measurement results of 2CH and 3CH
showed almost no change as described above,
mainly the change of each item in 1CH will be considered here. Dissolved oxygen decreased significantly in 1 CH as shown in the Fig. 6. However, in 2
CH, the opposite result was obtained that the pH
182

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ACKNOWLEDGEMENT[3] Urano K, Tsukagoshi K, Sakuma K, et al.,“Outline and application example of CPR
method of pile foundation seismic
reinforcement method”, basic work Vol.44,
No. 5, May 2016, pp. 42-45.
[4] Rex Co., Ltd., “portable multi-item water
quality meter WQC-24”, http: //www.rexrental.jp/sui/wqc-24.html., Nov. 2016

In promoting this research, we received politeand enthusiastic guidance from many business people and teachers. I express my appreciation by writing it here.
REFERENCES[1] Light Industry Co., Ltd., “high-pressure
injection stirring method”,
http://www.raito.co.jp/project/doboku/jiban/ki
kai/index.html, Jan. 2017[2] Confining Pile Reinforcement Method Study
Group, “Confining Pile Reinforcement
Method”, http: //www.cpr-m.jp/gaiyou.html.,
Feb. 2017183

Seventh
International
Conference
on Geotechnique, Construction Materials and
GEOMATE- Mie,
Japan, Nov.
21-24, 2017
Environment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THREE-DIMENSIONAL NUMERICAL STUDY OF THE EFFECT OF
TUNNELING ON THE SETTLMENT OF PILE FOUNDATION
1, 2, 3

Mohammad Reza Atrchian1, MiladGhannadzadehKermani2, Ali Nisari Tabrizi3 and HamidTeennejad4
Civil Engineering, Islamic Azad University of Zanjan, Iran; 4Civil Engineering, Islamic Azad University ofCentral Tehran Branch, Iran

ABSTRACT
Problem statement: The issue of transport and mobility of citizens has always been in the town of principal
concern cities. However, capacity constraints, traffic urban planning and the use of the available space have pushed
below the surface cities. However, we can say use of underground transport, the perfect solution for solving traffic
problems and pollution in big cities. Ensure that the loss of the tunnel during and after implementation and lack ofsurface inappropriate deformation structures, including tunnels are the main objectives of the designers. Thus
mutual behavior, understanding and tunnels, soil and surface structures are important and should be examined.
With the aid of a numerical model, variations in the tunnel, and tunnel properties were
investigated.Approach/methodology: Numerical simulation method with software PLAXIS 3D. With the help of
a numerical model, various characteristics of the tunnel, soil and foundation were studied.
Results: The results show that the tunneling drill increases the subsidence and vertical displacements in the model
the points on the ground surface have the most displacement and subsidence. As the tunnel is pulled away fromthe pile, the tunnel effect on the seating and movement is reduced. As the tunnel radius increases, the amount of
displacement and settlement has increased.Conclusions: By reducing the gap between the tunnel and the pile groupthe settlement of the pile group increases. Also, the surface subsidence has been increased by increasing thediameter of the tunnel.
Keywords: Tunneling, Pile foundation, Land subsidence, Settlement buildings

INTRODUCTION
Due to urbanization and the need to develop
infrastructure and shortage of land for it, inevitably
underground space development is considered. An
excellent example of this development, urban
tunnels, underground car parks and tunnels in urban
subway train. On the other hand, many of thestructures built on the pile foundation and the tunnel
passage near such structures with the blink ofcomputing that such structures based on it were built,
would be affected the balance of the settlement [1].
Mohr-Coulomb investigated. Also, considering
the pros and cons of different methods and facilities,
numerical simulation finite element software
PLAXIS 3Dchosen for this study. With the help ofnumerical models feature different variations of thetunnel, the soil around the tunnel and the foundation,
were examined. The results show: that the tunnel
excavation increased land subsidence and verticaldisplacement. Points are at ground level have themost displacement and land subsidence. The
horizontal and vertical displacement of deep soil lessby taking away a tunnel of the pile group tunnel.
Effect on land subsidence and displacement is low.
By increasing radius of tunnel increased the amount184

of displacement and land subsidence [2]. However,in engineering analysis, problems often involve
interaction between the construction of tunnels andother structures. Such conditions include surface
structures (such as buildings), existing subsurface
structures (such as tunnels, urban pipes) or complex
underground structures such as tunnels andunderground stations are twins. Rock as a continuum
that by a limited number of discontinuities isinterrupted considered, while in theory the batch, therock mass as a combination of blocks, which
together were considered to be of since the area isbearish in this study for soil and environment isassumed to be continuous, so numerically using
finite element method (FEM) is. Plaxis 3D Tunnel
finite element software package is exclusively forthe analysis of deformation and stability ingeotechnical engineering projects have beendeveloped [3].

The identified parameters
Elastic-plastic Mohr-Coulomb model includes 5parameters E and C and Ǿ ʋ for elasticity and plasticity
soil and ɯ angle for expansion of the soil. The initial
estimate of the behavior of soil or rock does. It is theGEOMATE - Mie, Japan, Nov. 21-24, 2017

model used in the initial analysis issues. For each layerof soil is estimated constant average hardness. Becauseof the difficulty of constant, rapid calculations and basic
understanding of deformation can be achieved. In the 5parameters mentioned, the initial conditions of soil
(Table 1 and 2) had an important role in most of theissues deformation. The initial horizontal stress caused
the soil using the appropriate values of K0 [4].

The tunnel excavation is relatively loose soil, the soil
and fractured nature does not seem to be converging.
For numerical analysis in the study of threedimensional finite element modeling has been usedon the basis of finite element software PLAXIS 3D
tunnel works. In engineering analysis, problems
often involve interaction between the construction oftunnels and other structures. Such conditions include
surface structures (such as buildings), existing
subsurface structures (such as tunnels, urban pipes)
or complex underground structures such as tunnels
and underground stations are twins [1]. Numericalmodeling possible to reconcile the different
components provides an analysis of the issues
involved in the action. Different numerical methods
based on the theories of continuous anddiscontinuous are presented. In theory, continuumrock mass as a continuum that by a limited numberof discontinuities is interrupted considered, while intheory the batch, the rock mass as a combination ofblocks that together have been put in Taken Since thearea is bearish in this study for soil and environmentis assumed to be continuous, so the numericalmethod used a Plaxis 3D tunnel. Is (FEM) and finite
element method, finite element software package
exclusively for the analyses of deformation andstability in geotechnical engineering projects havebeen developed [6].

Table 1:Specifications of soilParameter

Name

Clay

DP.
Sand
17

Unit

15

DP.
Clay
16

Dry soil weight
Wet soil weight𝛾𝛾 𝑑𝑑𝑑𝑑𝑑𝑑

18

18.5

21

KN/M3

h. permeability

𝛾𝛾 𝑤𝑤𝑤𝑤𝑤𝑤
Kx

1.10-4

1.10-2

0.5

KN/M3

v. permeabilityKy

1.10-4

1.10-20.5

KN/M3

Young s modulus

Eref

1000

10000

120000

KN/M3

Increase E

Einr

650

-

-

KN/M3

Reference level

Yref

0

-

-

M

Poisson s ratio

𝜇𝜇

0.33

0.33

0.3

-

Cref

5.5

4

1.0

KN/M3

𝜑𝜑

24

25

33

0

0

0

3.0

0

Interface strength

Rinter

rigid

0.7

0.7

-

Interface perm

perm

neutralimpernimpern-Cohesion

KN/M3

Numerical Modeling
Friction angle
Dalliance angle𝜔𝜔

A pile of used computer modeling to evaluate theperformance of the group. The method is that first a
4×4 and pile with a diameter of 1 m, 8 m and 1 m
intervals modeled in sandy soil. In this study, allpiles on all models is constant and equal to thediameter of one meter is assumed loaded onto a pileon a load of 20 KN m wide and done. The time to
failure of soil mass gradually increases. This isachieved through the ultimate bearing capacity ofpile group. Then dig a tunnel with a diameter of 10
meters at a depth of 10 m above ground level change
and displacement following the settlement toexamine the group and pile. Of these parameters on
the results. The first group of piles in sandy soilmodeling with dimensions of 30×20×10 andhorizontal and vertical displacements at points A, B,
C and D obtained. Location points are: A: groundand left piles B:ground and the right pile group C: 2m below point A D: 2 m below point Baftermodeling results were presented as follows:

Also, lining profile is as follows:
Table 2:Specifications of lining
Parameter

Name

Value

Type of behavior

Elastic

Normal stiffness

Material
type
EA

1.4*107

KN/m3

Flexural rigidity

EL

1.43*105

KNm2/mEquivalent thickness

d

0.35

m

Unite

Weightw

8.4

KN/m/mPoissons ratio

v

0.15

-

As can be seen from the figure 1 and 2 are for areas
near the border cross points B and D thedisplacement of other points more. It can be seen thatat the start of the first swell slightly upward and thenstarts the settlement that this phenomenon is due tothe expansion in the sand. The charts can also beseen on the horizontal displacement of the points
where the Earth's surface and are near the head of the

The geometry of the tunnel
In this study, it is assumed that the tunnel
excavation using the TBM Oyster been done
immediately after casing drilling as lining installed.

185

GEOMATE - Mie, Japan, Nov. 21-24, 2017

pile the displacement of less than spots that are deepin the soil. This is due to the presence of head pile,which has prevented them from moving too much.

central portion of the compression curve will be
subsidence and settlement of curves on the sides,
horizontally placed under tension.

Fig 3: Land subsidence

Mohr Coulomb strength parameters in the model by
selecting any change in ductility by increasing thedepth of drilling, maximum sat down possible
reduction in the earth's sat down. While themaximum surface hardening soil, advanced modelwith the same selection parameters is possible. The
hardening soil model, the model elastoplastic model
is hyperbolic. This model can be used to simulate thebehavior of granular and cohesive soils used. In thefollowing tables parameters used in both models areprovided. Soil elements were prepared such that thelower model boundary condition is closed and there
is no displacement in horizontal and verticaldirection, but only in the horizontal direction
displacement is closed on the flanks. After forming
geometric modeling, finite element network iscreated that can be seen in 3 Figure Build a networkof 15 nodes triangular elements were used to model
the soil, Accordingly, the average size of each sideof the boundary conditions of the soil at least 4 times
the diameter of the tunnel and the model has been
replaced with proper border [7].

Fig1: Vertical displacement

Fig 2: Horizontal displacement

As can be seen from the figure [4] and [5]to point A
on the left is a pile group and nearby tunnels land
subsidence increased a lot. But elsewhere at a depthof 2 meters above ground level, with a slight increasein their land subsidence occurred.The charts can also
be seen on the horizontal displacement to point A on
the left is a pile group and tunnels near the land
subsidence has increased a lot. But elsewhere at a
depth of 2 meters above ground level, with a slightincrease in their land subsidence occurred. In thismodel after the analysis was conducted in thepresence of tunnel this time we have dug a tunnel
with a radius of 5 meters at a depth of 10 meters at a
distance of 11 meters from the ground and the pile.
Digging tunnels and walls of all sections of drillingwith lining was stabilizing. As can be seen from the

The effect of the tunnel excavation on settlement
In this part of the analysis model was used to diga tunnel with a radius of 5 meters at a depth of 10
meters at a distance of 9 meters of the pile. Digging
tunnels and walls of all sections of drilling withlining was stabilizing. By drilling underground Held
settlement curved surface and the central vertical
addition to the settlement, [Figure 3] but othersections vertical to horizontal displacement are.
When the different parts of the Earth's surface
horizontal displacement ratios to acquire land under
tension or horizontal compression occurs. The

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

above forms for Point A on the left is a pile group
and near the tunnels land subsidence is higher thanelsewhere. But elsewhere at a depth of 2 meters
above ground level, with a slight increase in theirland subsidence occurred.

REFERENCES:
1.

2.

3.

4.

Fig 4 :Vertical displacement

5.

6.

7.

Fig 5: Horizontal displacement
CONCLUSION:
After modeling and model analysis results were
presented as follows:
1.
2.
3.
4.
5.

Tunnel increases the vertical displacement sat
on the model.
Points where the Earth's surface is moving
further and have a land subsidence.
The horizontal and vertical displacement of
deep soil less.
The tunnel away from the land subsidence andthe displacement and pile tunnel effect is low.
By increasing the radius of the tunnel and land
subsidence increased the amount of
displacement.

187

Brinkgreve, R. B. J., &Broere, W. The
Influence of Tunnel Boring on Foundations
and Buildings in Urban Areas -A
Numerical Study. Geotechnics of Soft Soils
J. 2003. pp: 257-263
Ng, Cww., Lee, K.M., Tang, D.K. Threedimensional numerical investigations of
New Austrian tunneling method (NATM)
twintunnelinteraction.
Canadian
Geotechnical J. 41, 2004. pp:523-539.
Blackburn, J. Tanner, and Charles H.
Dowding. "Finite-element analysis of time
domain reflectometry cable-grout-soil
interaction." Geotechnical andgeoenvironmental engineering J. 130(3),2004. pp: 231-239.
Loganathan, N., and H. G. Poulos.
"Analytical prediction for tunnelinginduced ground movements in clays."
GeotechnicalandGeoenvironmental
Engineering J. 124(9), 1998.pp:846-856.
Attewell, P. B., and J. P. Woodman.
"Predicting the dynamics of groundsettlement and its derivitives caused bytunnelling in soil. Ground engineering J
15(8), 1982.
Cheng, C. Y., Dasari, G. R., Leung, C. F.,
Chow, Y. K., & Rosser, H. B. 3D
numerical study of tunnel-soil-pileinteraction. Tunnelling and UndergroundSpace Technology J.19(4), 2004. pp: 381382.
Xiang, Y., Zhiping J., Haijian H.
Assessment and control of metroconstruction induced settlement of a pilesupported urban overpass." Tunnelling andUnderground Space Technology J. 23(3),2008. pp: 300-307.

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

BEHAVIOR OF MODEL GROUP PILES SUBJECTED TO LATERALSOIL MOVEMENT IN SAND
*Saad Farhan Ibrahim1, Mohammed Khachi Hatem221Professor, Faculty of Engineering, Isra University,Amman,Jordan,drsaadfarhan@yahoo.com
Civil Engineering Department, Faculty of Engineering, Al.Mustansiriyah University, Baghdad, Iraq

ABSTRACTLaboratory model tests have been carried out to explore the behavior of piles subjected to lateral soil movementin sand. The results of a single pile test and ten tests on of group piles arranged in a row (perpendicular to thedirection of soil movement) are presented. Different parameters were utilized in these tests, (e.g., pile spacing,number of piles within a group and pile head condition). Group effect was calculated using group factor (Fm)which is defined in terms of the measured maximum bending moments of an individual with group and that of
the single pile. The results showed that the maximum bending moment of group piles decreases from the single
pile with decreasing pile spacing and the pile behaves essentially the same as a single pile when the pile spacing
is 7d or more. The maximum reduction of the maximum bending moments of about (17%) and (28%) ascompared with that for the standard single pile may be observed for a pile spacing of 3d for the free and capped
headed condition, respectively. The number of piles does not appear to have significant effect on the groupfactor Fm of piles, except for the free headed inner piles who's the group factors appear to decrease withincreasing the number of piles within a group.
Keywords: Piles, Sand, Lateral Soil Movement, Instrumentations, Bending Moment[8].

INTRODUCTION
Pile foundations are designed to give resistanceagainst active load (i.e., load from structure that is
directly transferred to the pile foundation by thecap). However, in many cases, pile foundations aredesigned to provide resistance against passive load,
which that is induced from the lateral soil
movements. Earthquakes, landslides and humanactivities, such as tunneling and deep excavation in
the vicinity of piles, might cause irreversible soil
movements [1]). These soil movements cangenerate lateral thrusts on the piles supporting both
onshore and offshore structures, in a variety ofcircumstances. In all these conditions, theexternally imposed soil movements will impart
extra forces, cause increase in bending moments
and lateral deflections in piles which may finallycause problems and even damage to the structure ofpiles [2] and [3].
In practice, piles are commonly used in groups.
When piles are closely spaced in a pile group, thepresence of loaded piles nearby affects the behaviorof each individual pile [4]. Many researchers [5];[6];[7] found that the piles within a group may
suffer some reduction in capacity compared withsingle isolated piles due to interaction effects. The
behavior of an individual pile within group isdifferent from that of single pile, and several factors
may be influenced on the behavior of group piles

In this study, a series of laboratory tests wereconducted on some pile groups subjected to lateralsoil movement for investigating the group effect on
the lateral response of an individual pile within agroup. Different parameters were utilized in thesetests, (e.g., pile spacing, number of piles within agroup and pile head condition). The piles arranged
in one row perpendicular to the direction of lateralsoil movement
SOIL PROPERTIES
Dry sand was used in this study and it wassieved on the sieve no. 10 (2 mm) to remove thecoarse particles. The specific gravity (Gs), themaximum and the minimum dry unit weights of thesoil are 2.65, 16.78 kN/m3 and 14.1 kN/m3
respectively. For 59% relative density, it was foundthat the angle of internal friction () is (35o). Fig. 1
shows the particles size distribution of this sand.
The coefficients of curvature (Cc) and uniformity(Cu) are 1.11 and 2.67 respectively. According to
the Unified Soil Classification System (USCS), thesand can be classified as poorly graded sand (SP).

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Percentage passing (%)

100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
0.001

with this near jack to measure the horizontal force
acting on the near upper part of the box. By turning
the near jack, the near upper moveable part of themodel steel box was forced to rotate around its
joints, and consequently causes the upper part of thesoil in the box to move. The moving soil thus issubjected to a triangular profile of horizontal
movement, with the maximum displacement at thesoil surface and zero displacement at the level ofjoints of the upper and lower parts. The base of thesecond horizontal mechanical jack (rear jack) was
welded perpendicular to the rear column of theframe to control on the movement of the rear upper
part of the box.

0.010

0.100 1.000 10.000
Particle size (mm)Fig. 1 : Particle size distribution of sand

The Details of Pile and Pile Cap
Hollow aluminum pipes of 30 mm outer
diameter, 1.4 mm wall thickness and 1000mm total
length with a bottom plug were utilized as a model
piles in this study. The flexural stiffness of eachmodel pile was calculated by conducting simply
supported beam test. By measuring the central
deflection under a known load at the center of thebeam (model pile), the flexural stiffness of the pile
was found (0.91 kN.mm2). The pile caps were
designed and fabricated from a solid aluminum
block of 60 mm thick. On one face of the pile cap,
there were predrilled holes of 30 mm deep, with adiameter to fit the piles. The diameter of each hole
was made 0.5 mm greater than the pile diameter toassist the piles to the pile cap connection. The caps
were not used just for connecting the pile heads
together during the test (capped headed case), butalso for helping the jacking system to drive the piles
into the sand bed.

TEST SET-UP
A special experimental apparatus was designed
and manufactured for the current study toinvestigate the effect of lateral soil movement on
pile foundation. It consists of five main parts, (i.e.,a steel box, a loading system, a sand raining system,an aluminum piles, and a measurements system).
Fig. 2 shows the overall arrangement of the testing
apparatus.
The Steel Box
The designed steel box made of thick steel plate
having a thickness of (6.5 mm) with internal
dimensions of (80cm×80cm) and (80cm) height
was used to apply triangular profile shape of lateralsoil movements. Across the width of the box, it was
divided into two parts, upper part and lower part.
The two parts were connected by two hinges at the
mid-height of the box. The upper portion is able torotate while the lower portion is fixed which makes
the soil in the box is divided into two layers(movable and stable). Four wheels were welded at
the bed of the box in order to allow the box to travelfrom underneath sand raining to under the pile
jacking system.

Instrumentations and Measurements
The data logger, strain gauges and load cell
utilized in this study to determine the strains along
the pile shaft and load required causing movementin the upper movable part of the model box. A
compact and handheld digital data logger (TC-32K)
was utilized to measure and store data from strain
gauge measurement for each pile test. TML strain
gauges type (FLA-5-23-3L) having a gauge
resistance of 120 ±0.3 Ohm was used to instrument
the model piles. The strain gauges were fixed along
the model piles using cyanoacrylate adhesive (typeCN). The strain gauges were then coated by 1 mm
epoxy resin in order to protect from damage during
the pile driving and testing under lateral soil
movement. Eight pairs of strain gauges wereattached along each instrumented pile to measure
the developed bending moment caused by lateralsoil movement. The number of instrumented piles
within the group depends on the number of piles
within the group. Due to the limited channels

Loading System
Three mechanical jacks with capacity of 3 tons
(for each one) were used to apply vertical andhorizontal loadings on the instrumented pile and thebox respectively. The vertical jack was used to drive
the pile into the model ground. A load cell with acapacity of 5 tons was connected with the verticaljack to measure the load required to install themodel pile into the sand. The base of the firsthorizontal (near) jack was welded perpendicular to
the near column of the frame in order to apply
horizontal force on the near upper part of the box.
A load cell with a capacity of 5 tons was connected
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

existing in the current data loggers (maximum ten
channels), several separated tests were conductedon pile groups to record the bending moments of therequired individual pile, and the number of theseseparated tests depends on the number of piles.

Mmaxi to the maximum bending moment of single
pile Mmaxs [9].
THE RESULTS
This section describes the results of free headed
single pile (standard) test and the tests of two, threeand four piles arranged in one row for free andcapped headed cases. The results of the effect of pile
spacing and number of piles on response of piles ina row are presented and discussed in the following
subsections.

The Sand Raining
A sand raining device fabricated from timber
pieces, having internal dimensions of 790 mm by
790 mm, and 150 mm in height was used to pour thesand in the box. The base of the sand raining
consists of two timber plates; the bottom is fixed
while the top is moveable. The thickness of thetimber plates was 18 mm and 6 mm for fixed andmoved respectively. The fixed plate was perforated
with 6 mm diameter holes on a 40 mm by 40 mm
grid pattern. The moveable plate can slide along theslots on one side of the sand raining. When the top
moveable plate is pulled out, the sand is discharged
from the sand raining in model box. The fallingheight of sand was selected as 400 mm, which gave
a relative density of sand about 59%, and a unit
weight of 15.6 kN/m3.

Single Pile (Standard)This test was performed on free headed single
pile of 30 mm in diameter; the box was filled withsand to the top. The pile length in the upper movablepart (Lm) was 400 mm, while that in the lower
stable part was 350 mm. The falling height of sandraining was (400mm) gave a relative density of
about 59%. Fig. 3 shows the response of pile interms of bending moment. It can be seen that the
profiles of the bending moment along the pile shaft
at different values of the lateral soil movements areanalogous to a parabolic shape. The measured
bending moment increases with increasing thelateral soil movement but the rate of the increase
reduces, especially when the soil surface movement
is greater than 60 mm.

Fig. 2 : Test set-up

Fig. 3 : Bending moment distributions from thestandard test

COMPRISON METHOD

Pile GroupTo explore the group effects on the lateral
response of piles, the pile group results werecompared with that of the single pile test and hencea suitable comparison method was needed to be
adopted. The group factor in term of bending
moment (Fm) represents the ratio of the maximum
bending moment of individual piles within a group

This test was performed on free headed single
pile of 30 mm in diameter; the box was filled withsand to the top.
5.2.1 Effect of pile spacing
For investigating the effect of pile spacing on
the lateral response of pile, many tests were carried
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

out on two piles arranged in a row for both free andcapped headed cases. Three different spacing (i.e.,
3d, 5d and 7d) were adopted in these tests. Due tosymmetrical arrangements of the piles in this typeof pile groups, the results of the two piles weresuggested to be basically identical and hence only
the re results of one pile were presented.
Fig. 4 presents the bending moment profiles forfree headed pile group for different pile spacing
together with that for the single pile test . It can beseen that the bending moment profiles are very
similar in shape for all cases; including the depth ofthe maximum bending moment, but different in themagnitudes of the bending moments. It can be also
seen that the variation of the calculated bending
moment with pile spacing is mainly within the
middle part of the pile length (which includes the
position of the maximum bending moment); whilethe variation is very small in the upper and lower
portions of pile. Also the maximum bending
moment decreases from the single pile test withdecreasing pile spacing. Since each pile in all cases
was subjected to the same magnitude movement,
this reduction in the bending moment may be due toa reduction of pile–soil contact pressure resulting
from pile-soil interaction. It can be observed from
Fig. 4 that a spacing of 7d seems to be large enoughto eliminate abolish the group effect. It can beindicated the pile behaves essentially the same as asingle pile when the pile spacing is 7d or more.

smaller. It can be noticed that, similarly to the freeheaded case, the maximum bending moment
decreases with decreasing pile spacing.

Fig. 5 : Bending moment distributions for capped
headed two piles
Fig.6 shows the plot of the group factor Fm
for both free and capped headed conditions anddifferent pile spacing. It can be seen that, (Fm)decreases with decreasing pile spacing for bothheaded cases and capped case, and it is smaller thanunity for all cases. The group factor was also seen
to be greater for the free headed case than that forthe capped case, which may be attributed to adeveloped negative bending moment and a larger
load sharing between the adjacent piles for the
capped condition. The maximum reduction of the
maximum bending moments of about (17%) andabout (28%) as compared with that for the standard
single pile may be observed for a pile spacing of 3dfor the free headed condition and capped condition,
respectively. It seems that the provision of a pile cap
for two piles in a row tends to results in a smaller
bending moments. Therefore, the provision of a pile
cap appears to be an advantage for piles in a row
utilized for resisting soils from moving laterally.

Group factor Fm

1.5
Fig. 4 : Bending moment distributions for freeheaded two piles

Free…
Capp…

1

0.5

The bending moment profiles for capped
headed two piles in a row for different pile spacing
together with that for the single pile test are shownin Fig. 5. Although the pile cap tends to develop anegative bending moment at the pile head level, thevalue of this negative bending moment was verysmall. Therefore, the bending moment profile for all
pile spacing was basically the same as that for thefree headed case, but its magnitude appears to be

0

3d

5d

7d

Pile spacing

Fig. 6 : The group factor against the pile spacing
for two piles
5.2.2 Effect of number of piles

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

the cap tends to develop a negative bending
moments at the pile head level piles, but it is value
is far less than the maximum positive bending
moment. The bending moment profiles for the innerpile and the outer pile for capped headed four piles
group (for 3d pile spacing) together with that of thestandard single pile test are presented in Fig. 8b.
Similar to the case of capped headed three piles
group, the cap tends to develop a negative bending
moments at the pile head level piles. The negative
bending moment appears to increase (but stay lessthan maximum positive bending moment) withincreasing the number of piles with the group, but
the maximum positive bending moment isapproximately constant.

To explore the effect of number of piles on thelateral response of piles in a row, four tests werecarried out on three piles and four piles groups forboth free head and caped cases with pile spacing 3d.
For both the three piles and four piles groups, theoutside piles were defined as an outer piles, while
the inside pile(s) were defined as inner pile(s).
Fig.7a presents the bending moment profiles forthe inner and outer piles for free headed three piles
group (for 3d pile spacing), together with that of thesingle pile test. It can be noticed that, the shape ofthe bending moment profiles is very similar for eachpile, but the maximum bending moment for theouter pile is larger than the maximum bending
moment for the inner pile. It can be also seen thatthe bending moments of the inner pile and the outerpile are smaller than the bending moment of thesingle pile. The similar trend is also observed forbending moment profiles for the four pile groups,
but the differences in the magnitudes of the bending
moments for the inner and outer piles appears to begreater than for the three piles group, as presented
in Fig.7b. Also, the bending moments of the innerpile and the outer pile are smaller than the bending
moment of the single pile.

0
S in g le p ile
In n e r p ile
O u te r p ile

100

Depth (mm)

200

300
400
500
600

0

S in g le p ile
In n e r p ile

100

700

O u t e r p ile

800
-1 0

200

0

10

20

30

40

50

60

70

80

90

100

Depth (mm)B e n d in g m o m e n t (k N .m m )300

0
S in g le p ile
In n e r p ile
O u te r p ile

400

100
500

200

Depth (mm)

600
700
800
0

10

20

30

40

50

60

70

80

90

100

B e n d in g m o m e n t ( k N .m m )

300
400
500

0

600
S in g le p ile
In n e r p ile
O u te r p ile

100

700

Depth (mm)

200

800
-2 0

300

-1 0

0

10

20

30

40

50

60

70

80

90

100

B e n d in g m o m e n t ( k N .m m )Fig. 8: Bending moment profiles for capped
headed three and four piles

400
500

The group factor Fm is plotted with the numberof piles to explore the influence of the number ofpiles on the lateral response and the resisting force
provided by piles. As shown in Fig. 9 the effect of
the number of piles within a group on the groupfactor Fm , for both the free headed and capped cases
is seen to be different for the inner pile and outerpile due to load sharing which develops between theadjacent piles. The number of piles does not appear
to have significant effect on the group factor Fm of
piles, except for the free headed inner piles (i.e., the

600
700
800
0

10

20

30

40

50

60

70

80

90

100

B e n d in g m o m e n t ( k N .m m )Fig. 7: Bending moment profiles for free headed
three and four piles
Fig. 8a presents the bending moment profiles
for the inner and outer piles for capped headed threepiles group (for 3d pile spacing) together with thatof the single pile test. Similar to the test of two piles,
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GEOMATE - Mie, Japan, Nov. 21-24, 2017group factors appear to decrease with increasing thenumber of piles within a group).

Group factor Fm

1
0.8

Inner free
Inner capped

REFERENCES[1] Qin HY. “Response of Pile Foundations due to
Lateral Force and Soil Movements”. Ph.D.
Thesis, Griffith University, 2010.
[2] Pan JL, Goh AT, Wong KS, Selby AR. “Three‐dimensional analysis of single pile response tolateral soil movements”. International Journal
for Numerical and Analytical Methods inGeomechanics. 2002 Jul 1;26(8):747-58.
[3] Al-Abboodi I, Toma-Sabbagh T, Al-Jazaairry
A. “Modelling the response of single passive
piles subjected to lateral soil movement using
PLAXIS”. International Journal of Engineering
Research & Technology. 2015 Mar
13;4(3):176-80.
[4] Poulos HG, Davis EH. “Pile foundation
analysis and design”. 1980.
[5] Broms BB. “Lateral resistance of piles incohesionless soils”. Journal of the Soil
Mechanics and Foundations Division. 1964
May;90(3):123-58.
[6] Randolph MF. “The response of flexible piles
to lateral loading”. Geotechnique. 1981
Jun;31(2):247-59.
[7] Chen LT, Poulos HG. “Piles subjected tolateral soil movements”. Journal of
GeotechnicalandGeoenvironmental
Engineering. 1997 Sep;123(9):802-11.
[8] Kong G, Zhou Y, Yang Q. “Group effect ofdragload in pile groups embedded inconsolidating soil under embankment load”.
KSCE Journal of Civil Engineering. 2016 Sep
1;20(6):2208-20.
[9] AlAbdullah S F,Taresh N S.“ Evaluation of
Soil Reinforcement with Geogrid in Subgrade
Layer using FE Techniques”. International
Journal of GEOMATE, 2017 June unpublishedyet.

Outer free
Outer capped

0.6
0.4
0.2
0

2 Piles

3 Piles

4 pilesFig. 9: The group factor against pile spacing forpiles in a row
CONCLUSIONS
Laboratory model tests have been conducted ongroup piles arranged in arrow in additional to single
pile subjected to lateral soil movement in sand toinvestigate the effects of the pile's spacing, numberof piles and piles headed condition on lateral
response of piles. The results of the tests indicatethat the maximum bending moment for both freeand capped headed cases decreases from the single
pile with decreasing pile spacing and the group piles
behaves essentially the same as a single pile when
the pile spacing is 7d or more. The maximum
reduction of the maximum bending moments ofabout (17%) and about (28%) as compared with thatfor the standard single pile may be observed for apile spacing of 3d for the free and capped headed
conditions, respectively. The maximum bending
moment for the outer pile was larger than the
maximum bending moment for the inner pile. For
four piles group, the differences in the magnitudesof the bending moments for the inner and outer piles
appears to be greater than those for the three piles
group. The number of piles does not appear to havesignificant effect on the group factor Fm of piles,
except for the free headed inner piles whose thegroup factors appear to decrease with increasing thenumber of piles within a group.

193

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

CHANGE OF DEBRIS FLOW CHARACTERISTICS DUE TO
DIFFERENCES IN PHYSICAL CONDITIONS OF LANDSLIDE DAM
1Naomasa Honda1
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
ABSTRACTA large-scale collapse can form a landslide dam, which can block a river and create ponds upstream. If alandslide dam outburst occurs, the resulting debris flow and flood can also cause serious problems downstream.
In this paper, based on a numerical analysis, we discuss changes in the debris flow characteristics caused by suchdifferences in a landslide dam’s physical conditions, as shape and material. We conducted numerical simulations
to specify the sediment runoff and the debris flow characteristics, including flow depth, flow velocity and flow
discharge along the river’s path. Judging from the analytical results, if landslide dams have an identical sedimentvolume, the debris flow scale is so large that the dam height will be high or the amount of the water overflow will
be large. To predict the scale of the debris flow with sufficient accuracy, we must carefully establish the physicalconditions that significantly influence sediment mobility.
Keywords: Landslide dam, Dam outburst, Debris flow, Landslide dam’s physical conditions, Numerical simulation
INTRODUCTION
A large-scale collapse due to earthquakes or
heavy rainfall can form landslide dams, which canblock rivers and create ponds upstream: for example,
the Imokawa River basin in the Mid Niigata
Prefecture Earthquake in 2004, the San-hazama Riverbasin in the Iwate-Miyagi Nairiku Earthquake in2008, and the Akadani River basin in the Kii
peninsula in the typhoon No.12 in 2011 [1] - [3].
If a landslide dam outburst occurs, the resulting
debris flow and flooding can cause serious problems
downstream. Therefore, many field surveys,
experimental studies, and numerical analyses onlandslide dams exist: formation, breakdowns, andsediment runoff processes [4] - [6].
Naturally, the debris flow’s scale and properties
due to landslide dam outburst vary by such conditions
as shape and material. But measuring thesecharacteristics at the actual sites is very difficult,because this spot is obviously dangerous during anatural disaster.
In this paper, based on numerical analysis, we
discuss the changes in the debris flow characteristics
caused by differences in a landslide dam’s physicalconditions, such as shape and material. We conductednumerical simulations to specify the sediment runoff
and such flow characteristics as flow depth, flow
velocity and flow discharge along virtual torrents.

formed a landslide dam. In Japan, earthquakes andheavy rainfalls are often geographically generated,
mountain slopes are topographically steep, and theearth’s layer is geologically weak. Japan suffers fromthe conditions under which landslide dams are easily
formed.
Landslide dam outbursts are caused by thefollowing reasons:(1) sliding failures due to infiltration from ponds(2) piping by subsurface backward erosion(3) overflow from ponds
Outbursts due to pond overflow cause the largescale debris flow and serious downstream damage,
because overflow occurs when the pond’s water levelis high. If a landslide dam is formed, draining must be
quickly installed and draining channel works must be
promptly constructed.
For debris flow hazard mitigation, warning andevacuation measures are as critical as structure
measures. The scale and characteristics of the debris
flow must be predicted and used to determine
warnings and evacuations.
Collapse
・・・・・・
Bed material
・・・・・・・・・・・ ・・・・Collapse
・・・
・・・・・
・・・

A
▽

RELATIONSHIP BETWEEN LANDSLIDEDAM OUTBURSTS AND DEBRIS FLOWOCCURRENCES

A

・
・
・・
・・
・・・
・・・・ ・・ ・・・・・ ・・・・・・・・・・・・・・
・
Landslide dam

Bed materialRiver bed

As shown in Fig. 1, when a huge collapse occurs
on a mountain slope and a large quantity of sedimentflows into a river, the river becomes dammed andA-A section・ ・ ・・・・ ・・・
・ ・・・

Fig. 1 Debris flow occurrence system
due to landslide dam outburst

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

  /   1 ctan  s 





/

1
1
c



METHOD AND PROCEDURE FOR STUDY
Governing Equations for Debris flowwhere θ e is the equilibrium river-bed slope
corresponding to the sediment concentration definedby Eq. (8). φ s is the internal friction angle of thesediment in this equation.
The following is the formula for τb , developed by
Egashira et al. [10]:The following are the mass conservation
equations for the flow mixture and for sedimentalone:
h 1 Bvh Et B xc*(1)

εch 1 εcBvh

E
t
B x

(2)

(8)

 e  tan 1  b  y fv 2

(9)

15

c
     1cgh cos  tan  s c* 

where t is the time, x is the coordinate axis along theflow, h is the flow depth, B is the flow width, v is theflow velocity, E is the erosion velocity (its negativevalue designates the deposition), c is the sedimentconcentration by volume, ε is the correction factor(see Egashira et al. [7], where εc = ct, ct is thesediment flux concentration), and c* is the sedimentconcentration of the river-bed layer.
The following is the momentum conservation
equation:
v
v
1 P vEτ v  g sinθ 

 b
t
x
ρmh x c*h ρmh(3)

 m     c  

(4)

f 

 kg


1  e 2 c 2 3  dh 

 

2

(11)

Virtual torrents
In actual torrents, the flow width and the riverbed
slope change irregularly, and the sediment that
becomes the constitution materials of the debris flow
are partly distributed on the riverbed. These
geographical conditions greatly influence thecalculation results of the debris flow characteristics.
Therefore, we set two virtual torrents to just focus on
the differences of the landslide dam’s physicalconditions (Fig. 2):
Case 1: θ=constant=10°，B =constant=30 m,
total river length, L=1,000 m (horizontal
distance=985 m, relative height=174 m),
no sediment that was entrained in the debris
flow exists on the riverbed.

(5)

(6)
300

where Zb is the river-bed elevation, and θ isexpressed by Eq. (6).
Even though E andτb play an important role in
the above governing equations, no general formulas
have been developed for them. We used the formulas
for E andτ b developed by Egashira [8], [9]. The
following is erosion velocity, E:E c* tan   e v

53

Relative height (m) Z b  x   sin 1  

25  1  c
k f
4 
c2 3

In Eq. (9), τy is the yield stress caused by theparticle-to-particle contacts defined by Eq. (10), andf is the friction factor defined by Eq. (11), where e isthe restitution coefficient, d is the reference grainsize, and kf and kg are the coefficients: kf =0.16, kg=0.0828.

The second term on the right-hand side in Eq. (3)is the pressure gradient and the third is the resistancedue to sediment erosion. g is the gravity acceleration,
θis the river-bed slope, P is the pressure, τb is theriver-bed shear stress, ρm is the mass density of theflow mixture defined by Eq. (4), σ is the massdensity of gravel, and ρ is the mass density of water.
The mass conservation equation of river-bed
sediment takes the following form:
Z b
E

t
c* cos(10) y 

Landslide dam
200

Case 2 (θ＝15°)

100

Case 1 (θ＝10°)
0
0

200

400

600

800

1000

Horizontal distance (m)(7)

Fig.2 Riverbed profile of virtual torrents
195

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Case 2: θ=constant=15°，B =constant=30 m,
total river length, L=1,000 m (horizontal
distance=966 m, relative height=259 m),
no sediment that was entrained in the debris
flow exists on the riverbed.

Water supply conditions
The overflow discharge from the pond, Qin , isassumed as follows:
・Qin = 10.0 m3/sec, 1.0 m3/sec, 0.5 m3/sec (variableconditions)

As shown in Fig. 2, a landslide dam is formed at
the upstream end of the virtual torrent. The landslide
dam outburst occurs due to pond overflow. The
sediment flows downstream and is transported asdebris flows.

Relationship between water density and fine sandconcentration in water
The fine sand concentration in water, cs , is closely
related to a rise in the water’s density (muddy water).
Because a rise in the water density increases
buoyancy, our analysis cannot ignore its influence[11]. Therefore, cs is assumed as follows:

Computational Conditions
Shape of landslide dam
In our numerical simulations, our imaged shapesof the landslide dams are shown in Fig. 3. In all cases,
the sediment volume that constitutes a dam isapproximately 40,000 m3.

・cs = 10 %, 20 %, 30 % (variable conditions)
According to Eq. (4), ρ is calculated follows:

Physical conditions of landslide dam material・ρ =1.17 g/cm3 (cs = 10 %), 1.34 g/cm3 (cs = 10 %),1.51 g/cm3 (cs = 30 %) (variable conditions)

The physical parameters of the landslide dam
material necessary for computation are specified asfollows:

Numerical analytical conditions
We used the finite difference method (leap-frog
scheme in Fig. 4). Time and distance are
discriminated as Δt=0.025 seconds and Δx=5.0 m,
respectively.

・σ=2.70 g/cm3=constant・ c* = 0.50=constant [5], [6]・ φs = 30°, 35°, 39°(variable conditions)・ d = 10 cm, 5 cm, 1 cm (variable conditions)

RESULTS AND DISCUSSIONS

LengthHeight

L1 (m)

L2 (m)

30
20
10

30
57
130

30
20
10

H

H (m)

Table 1 shows the numerical simulation results ofthe debris flow. Figure 5 shows the temporal changeof the debris flow characteristics under the conditionsin Table 1:

Landslide dam
Outburst, runoff

・river-bed slope: θ=15° (Case 2)・shape of landslide dam: H=30 m, φs =39°,d = 5 cm・water supply conditions: Qin = 10.0 m3/sec,
ρ =1.17 g/cm3 (cs = 10%)

x
L1
θ

L2

Fig. 3 Shape of landside dam

Progress of Landslide dam outburst due tooverflow water from a pond
As shown in Fig. 5(a), the landslide dam began tobe eroded by the overflow water soon after the watersupply. The eroded rose rapidly toward the upper
reaches of the dam.

t +1t
○ the unknown pointt -1● the known point

n -1

n

Change of debris flow characteristics
differences in landslide dam shape

n +1

by

According to Table 1, the debris flow scale is solarge that river-bed slope θ is so big and dam heightFig. 4 Schematic diagram of leap-frog scheme
196

GEOMATE - Mie, Japan, Nov. 21-24, 2017

H is so high or the same sediment volume.
Table 1 Results of numerical simulation of debris flow
River-bed slope
θ(°)
Case 1(θ=10°)
Case 2(θ=15°)

Other conditions

Conditions to change
φs (internal friction angle)d (reference grain size)
H (dam height)
φs hmax Vmax Qmax
Hdhmax Vmax Qmax
hmax Vmax Qmax(m)(m) (m/s) （m3/s）(m) (m/s) （m3/s） （cm） (m) (m/s) （m3/s）
(°)
30
3.7
5.0
250
1.0
3.0 3.7120
30
4.5 3.813020
2.5 3.3
77
35
4.7
4.1
155
5.0
4.5 3.81301010.0 5.0 3.4
135
－
－
－
39
4.5
3.8
130
1.0
5.3 4.5200
30
5.7 4.0
215
30
5.4
4.1
330
20
4.5 3.8
170
35
5.7
4.1
265
5.0
5.7 4.0215
10
0.2 1.2
6
10.0 6.0 3.8
225
39
5.7
4.0
215
H=30 m－
H=30 mφs=39°，d=5.0 cm
φs=39°
d=5.0 cm33
3
Qin=0.1 m /s，cs=10 ％Qin=0.1 m /s，cs=10 ％Qin=0.1 m /s，cs=10 ％Conditions to changeRiver-bed slope

Qin (water supply)
Qin

θ
(°)
Case 1(θ=10°)
Case 2(θ=15°)
Other conditions

cs (fine sand concentration)

hmax Vmax Qmax

cshmax Vmax Qmax
3
3(％) (m) (m/s) （m3/s）（m /s） (m) (m/s) （m /s）
0.1
4.5 3.8
130
10
4.5
3.8
130
1.0
5.0 4.1
190
20
5.7
4.9
236
10.0
7.3 5.1
500
30
5.9
5.8
360
0.1
5.7 4.0
215
10
5.7
4.0
215
1.0
6.5 4.4
280
20
6.7
5.1
390
10.0
9.3 5.6
625
30
6.0
6.0
457
H=30 mH=30m
φs=39°，d=5.0 cm
φs=39°，d=5.0 cm
3
cs=10 ％
Qin=0.1 m /s

x' =40m

t=0sec290

5.0

t=20sec

280

Flow depth h (m)Relative height (m)hmax: maximum
flow depth
Vmax: maximum
flow velocity
Qmax: maximum
flow discharge

6.0

300

t=40sec270
t=60sect=80sec260

t=100sec

250

x' =80m

4.0

x' =120m

3.0
x' =160m

2.0
x' =200m

1.0

x'x '： Distance from downstream of dam

240

0.0
0

0
20
40
60
80
Distance from the most upstream x (m)

120

240
360
Time t (second)

480

600

(a) Temporal change of flow depth(b) Landslide dam erosion due to overflow water

400

5.0
4.0

Flow discharge Q (m /sec)

x' =200mx' =160m

3

Flow velocity v (m/sec)

Legendx' =120m

3.0
2.0
x' =80m

1.0

x' =40mx' =40mx' =80m300

x' =120m
x' =160m

200

x' =200m

100

0

0.0
0

120

240
360
Time t (second)

480

0

600

120

240
360
Time t (second)

480

600

(c) Temporal change of flow discharge(d) Temporal change of flow velocity

Fig. 5 Example of temporal change of debris flow characteristics
197

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 2 Relationship between landslide dam’s physical conditions and debris flow characteristics
Physical conditions of landslide dam
Shape oflandslide dam

Water supply
condition

Physicalconditionsof dam materialRiver-bed slopeθ
Dam heightH
Overflow water
discharge Q in
Fine sandconcentration c s
Internal
friction angle φsReference
grain size dDebris flow scale
Debris flow scale is so large that θ is big.
In case of same sediment volume, debris flow scale
is so large that H is high.
Debris flow scale is so large that Q in is big.
v and Q are so large that c s is big.
v and Q are so large that φs is small.
h and Q are so large that d is big.

Figures 5(b), (c) and (d) show that the sedimentwater mixture has runoff toward the lower reaches
and accelerated.

・ Flow depth h・ Flow velocity v
・ Flow discharge Q
・ Flow depth h・ Flow velocity v
・ Flow discharge Q
・ Flow velocity v
・ Flow discharge Q
・ Flow velocity v
・ Flow discharge Q
・ Flow depth h・ Flow discharge Q

They collaborate to greatly increase Q.
CONCLUSIONS
Table 2 shows the above considerations:

Change of debris flow characteristics bydifferences in physical conditions of landslide dam
material

1) If landslide dams have identical sediment volume,the debris flow scale is so large that dam height H will
be high or the amount of overflow water Qin will belarge.

According to Table 1, flow velocity v is so large
and flow depth h is so small that internal friction angleof sediment φs and relative grain size d are small.
Therefore, the landslide dam embankment body is soloose that φs is small, and friction factor f, defined by
Eq. (11), is so small that d is small, raising the fluidityof the debris flow. However, notice that the influenceof φs on v is so small that θis big.
Flow discharge Q is so large that φs is small (v islarge and h is small), and since d is big (v is small andh is large) Q is large. Notice that flow width B isconstant (B=30 m) in this study, because Q is amultiplication of B and v and h. Therefore, theincrease and decrease of v directly influence theincrease and decrease of h.
When B is constant, the influence of the increasein h by the decrease in v has a bigger d than φs andinfluences the tendency to change Q. However, B andθ change irregularly in actual torrents and thesediment, which becomes the constitution materialsof the debris flow, is partially distributed on theriverbed. We must consider the influence of changesof φs and d on the debris flow characteristics.
Change of debris flow characteristics
differences in water supply conditions

Influence on
debris flow characteristics

2) Such physical conditions of landslide dams asinternal friction angle of sediment φs, relative grain
size d, fine sand concentration in water cs , andoverflow discharge Qin lightly influence the debris
flow scale. To predict the debris flow scale bynumerical analyses with sufficient accuracy, we must
carefully establish the physical conditions thatsignificantly influence sediment mobility based onfield survey results.
3) Recently, the temporal changes of landslide dam
shapes and upstream pond scales can be observed inreal time by satellite images. Therefore, it is criticalto get the aims of φs, d, and cs by numerical analysesof similar examples of landslide dam outbursts, while
comparing the local path of the debris flow a
calculation of the flow depth.
ACKNOWLEDGEMENTS
Part of the present study was supported by

Strategic Research Project from Tokyo University ofAgriculture.

by

REFERENCES

According to Table 1, h, v, and Q are so large that
overflow discharge Qin and the fine sandconcentration in water cs are also large. Qin especiallyaffects the change of h and cs affects the change of v.

[1] Kato Y., T. Miyano and T. Mizuyama, “Outburstof a small landslide dam on the Imokawa River(prompt report)”, Journal of the Japan Society of198

GEOMATE - Mie, Japan, Nov. 21-24, 2017

River, Miyazaki Prefecture, Japan, andsuggestions regarding evacuation procedures
when a landslide dam bursts”, Journal of theJapan Society of Erosion Control Engineering,Vol. 60(1), May 2007, pp.43-47 (in Japanese).
[7] Egashira, S., T. Itoh, K. Miyamato and N. Honda,“Importance of Correction Factor Associatedwith Sediment Concentration Profile in Debris
Flow Simulation”, The 2nd International
Symposium on Flood Defence 2002, Vol.2,
2002, pp.1658-1666.
[8] Egashira, S., “Mechanism of Sediment
Deposition from Debris Flow (Part 2)”, Journalof the Japan Society of Erosion Control
Engineering, Vol. 46(1), May 1993, pp. 45-49 (inJapanese).
[9] Egashira, S., “Prospects of debris flow studies
from constitutive relations to governing
equations”, Journal of Disaster Research, Vol.
6(3), June 2011, pp. 313-320.
[10] Egashira, S., K. Miyamoto and T. Itoh,“Constitutive equations of debris flow and theirapplicability”, Proc. of 1st Int. Conference on
Debris Flow Hazards Mitigation, American
Society of Civil Engineering, 1997, pp. 340-349.
[11] Egashira, S., N. Honda and K. Miyamoto,“Numerical simulation of debris flow at the
Gamaharazawa in the Hime River basin”,
Annuals of Hydraulic Engineers, Japan Societyof Civil Engineering, Vol.42, 1998, pp. 919924(in Japanese).

Erosion Control Engineering, Vol. 57(6), March
2005, pp.47-50 (in Japanese).
[2] Uchida T., A. Matsuoka, N. Matsumoto, J.
Matsuda, K. Akiyama, K. Tamura and K.
Ichinohe, “Overtopping erosion of landslide dam
at Numakura-urasawa, San-hazama river Miyagi
Prefecture, Japan”, Journal of the Japan Societyof Erosion Control Engineering, Vol. 62(3), Sept.
2009, pp.23-29 (in Japanese).
[3] Matsumura K., M. Fijita, T. Yamada, Y. Gonda,
S. Numata, D. Tsutsumi, K. Nakatani, F.
Imaizumi, T. Shimada, M. Kaibori, K. Suzuki, H.
tokunaga, Y. kashiwabara, E. Nagano, O.
Yokoyama, T. Suzuki, N. Takezawa, R. Oono, T.
Nagayama, T. Ikegima and S. Tsuchiya,“Sediment disasters due to typhoon No.12 at
2011, occurred in Kii peninsula”, Journal of theJapan Society of Erosion Control Engineering,Vol. 64(5), Jan. 2012, pp.43-53 (in Japanese).
[4] Oda A., T. Mizuyama and Y. Hasegawa,“Experimental study of process and outflow rate
when landslide dams outburst”, Journal of theJapan Society of Erosion Control Engineering,Vol. 59(1), May 2006, pp.29-34 (in Japanese).
[5] Oda A., T. Mizuyama and Y. Hasegawa, “Anexperimental on a landslide dam outburst”,
Journal of the Japan Society of Erosion Control
Engineering, Vol. 60(2), July 2007, pp.33-38 (inJapanese).
[6] Chiba M., T. Mori, T. Uchikawa, T. Mizuyama
and Y. Satofuka, “Bursting process of a landslidecaused by Typhoon 0514 (Nabi) in the Mimi

199

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EXPERIMENTAL STUDY ON SOIL BASED SEALING MATERIALFULFILLING DEFORMATION FOLLOWABILITY AND
UNDERWATER PLACEABILITY

1,3

Yusuke Tadano1, Seiichi Ishida2 and Masanori Shimomura3
Technology center, Taisei corporation, Japan; 3 Civil headquarter, Taisei corporation, Japan

ABSTRACTFor retaining walls composed of structural materials such as steel sheet piles that have been widely used inconstruction works, long term water cutoff performance is sometimes required; infilling work of an impervious
material is additionally necessary at joints/interfaces of these structural members. Though various engineering
materials for this purpose have already been developed and put into practice, attempts were made to develop a newmaterial that fill the gaps in the precast concrete (PC) wall piles. The authors focus on a soil based impervious
material with appropriate plasticity, generally used for filling larger spaces because of its low fluidity. Its fluidity
was improved to maintain sealing performance by optimizing the blending ratio of bentonite, sand, water anddispersing agents. As a result, the developed material has the hydraulic conductivity in the order of 10-10 m/s, lessconsolidation settlement, and capability of underwater placement. To confirm whether the material possessed
deformation followability, the authors conducted two types of permeability tests in which deformations caused byshearing and opening of joints/interfaces were taken into account. Underwater placement test with a small pumping
equipment was also carried out to demonstrate that the material has a high resistance against material segregation.
From these experiments, the mix proportion of the soil based sealing material was optimized and finally established
to offer the material fulfilling deformation followability and underwater placeability.
Keywords: Bentonite, Impervious material, Deformation followability, Shear deformation, Boundary separation
LegendWorkability
Good

Defomation followability

INTRODUCTION

High

Vertical sealing walls built to connect materials
such as steel sheet piles have been used as earth
retaining structures in which long term water cutoff
performance is required. Although these structuralmembers themselves are impermeable, it is difficult
to ensure water cutoff capability in theirjoints/interfaces. Impervious performance at thesegaps is a key of overall impervious performance ofthe earth retaining wall. Hence, a number ofimpervious materials for this purpose have been
already developed and put into practical use [1].
Impervious materials used for vertical sealing wallsof important structures that cannot tolerate leakage
also need to withstand accidental external forces due
to earthquakes and waves. Even when joints/
interfaces are deformed by the displacement of thewall member, the material is required to keep thesame sealing capability.
This paper deals with a new soil based sealingmaterial recently developed for PC wall piles,
demonstrating its applicability through various
element tests and underwater placing test by aconventional small grout pump.

Urethane
Swelling polymer

Asphalt

Swellable rubber

Bad

This study

Silicone resine

Soil-based

MortarLow(1)Several mmsize of a gap(2)About 100 mm (3)Handreds mm

Fig.1 Characteristic of impervious materials
Steel sheet pile10
400~600[mm]

Steel box pile[mm]500400~550

120

Fig.2

[mm]

180

PC wall pile [mm]500~900

Steel pile sheet pile

Types of structural members

impervious materials used for gaps between structuralmembers, in terms of the size to be sealed and thedeformation followability of the material. The size ofsealed parts depends on the types of members used
for the vertical sealing wall as schematically shownin Fig.2.
The following are the details of the application of

BACK GROUND STUDY
Figure 1 summarizes the characteristics of the200

GEOMATE - Mie, Japan, Nov. 21-24, 2017

by increasing the amount of unit water would be
effective. However, this leads to lowering its density,
resulting in poorer water cutoff performance,
dispersion resistance and larger consolidation
settlement.

impervious materials in terms of the gap size:(1) The gaps with several mm to several tens of mm
High water swelling polymers, water swellable
rubbers or silicone resins are generally used for thesmall gaps such as steel sheet pile joints.[1] Thesematerials expand several times in volume when theycome in contact with water to complete the gap filling.
Due to chemical effects, its deformation followability
is excellent. On the other hand, most of thesematerials are necessary to be pasted or adhered on the
joint surface beforehand. This is only acceptable
when the gap size is quite small because the material
may peel off during construction of the structuralmembers, and not acceptable in case joint surface islarge enough to be exposed to soil during installation
works.
(2) The gaps with about a hundred mm
Concrete mortar is generally used for filling the
gap of e.g., precast concrete (PC) pile members andsteel pipe sheet piles.[1] However, if the structuralmembers deform due to seismic effects after the
mortar solidifies, gaps against the members open, andcracks may occur in the mortar. As for the workability,
it has high fluidity at the time of mixing, and it can beapplied with conventional small pumps.
For steel sheet piles, asphalt may also be used.
However, viscosity of asphalt is temperaturedependent; its viscosity at normal temperature is verylarge. Therefore, filling into narrow spaces is difficult
without using special pumping facilities equippedwith a temperature control system.
(3) The gaps with several hundreds of mm
Soil based impervious plastic materials and amortar are generally used for relatively large gaps
such as those in H joints of steel box piles.[1] Soilbased impervious plastic materials have low fluidity,
and therefore large pumping facilities as for concrete
is necessary. After placing, it may get stiffer due toconsolidation, but deformation followability is stillhigh since it does not have a hydration.
Among these impervious materials, the authors
focused on the soil based plastic impervious material
following the strong points described above.

Materials used for development
In order to improve fluidity without increasing theunit water of the material, dispersing agents usuallyused for the stabilizing solution were implemented topore walls. To ensure the fluidity with which material
can be pumped through a small diameter tube and can
avoid segregation, the mixing proportion of bentonite,sand and water was optimized by assessing theblending ratio of the materials.
In the following study, two types of constituent
soils were used; a highly swellable powder sodium
bentonite and a silica sand. As for silica sand, No.5
(JIS G 5901) was used. The bentonite has many
applications for water sealing walls, while silica sandhas been used for improving fluidity to suppress
consolidation settlement due to its ball bearing effect.
As a dispersing agent for improving fluidity, a liquidpolyacrylate type was used.
Test procedure
Firstly, the fluidity was evaluated while adjusting
the composition of the constituent materials. Cylinder
flow test (JHS A 313), table flow test (JIS R 5201)
and P type funnel test (JSCE-F521-1999) were used
for the evaluation just the same way as for concrete
or mortar. In addition, falling head permeability tests(JIS A 1218) were conducted using some of the
mixtures to evaluate sealing performance. After
selecting two mixtures for the following studies,incremental loading consolidation tests (JIS A 1217)
were conducted to optimize a combination which canoffer good sealing performance. Furthermore, shear
deformation permeability test and interfacial
separation permeability test were conducted using the
optimized mixture to evaluate the deformation
followability. Finally, underwater placement test by asmall grout pump was conducted to confirm
pumpability and segregation resistance.

DEVELOPMENT OF A NEW IMPERVIOUS
MATERIAL

Target properties
Problems of existing soil based impervious
materials

Fluidity criteria of the mixture were set as follows:
Cylinder flow spread more than 160mm
Capability of natural falling down in P typefunnelThe criterion A) is a standard of fluidity used in
fluidized soil cement mixture. The criterion B) is anindex considering pipe blocking in pumping througha small tube. Both criteria were originally set for thepresent study.
A)
B)

Existing soil based impervious materials are
dredged soil mixed with bentonite, and added sand or
gravel to the mixture for controlling consolidationand improved fluidity [1]. These mixtures haverelatively low fluidity, necessitating to be pumped
only through a large diameter pipe using a highcapacity concrete pump. In order to apply them into
narrower spaces, modification of the mix proportion
201

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Results of trial mix tests
DisperEffective
Water
sing
Densityclay
contentNo.
agent
density
(kg)
(kg)
(kg)
(kg)
(kg)
(kg/m3)(kg/m3)
(%)
1
650
748
100
0
1498
0.15
76.7
2
650
748
100
6.5
1498
0.15
76.7
3
700
628
100
0.0
1428
0.14
96.2
4
700
628
100
3.3
1428
0.14
96.2
5
470(1%)
1134
150
3.3
1754
0.28
36.6
6
470(2%)
1134
150
3.3
1754
0.28
36.6
7
470(3%)
1134
150
3.3
1754
0.28
36.6
8
723
480
200
182
1390
0.25
133.1
Notes *1: Measured by table flow test, *2: ×(No flow down), − (Not implemented)
Numbers are given in the order of the experiment.
Fresh
water

Salt
water

Silicasand

Bentonite

Cylinder
flow
(mm)
115
230
147
311
104
170
183
184*1

P
funneltime*2
(sec)
×
71
×
33
×
200
×

segregation did not occur.
Finally, No.8 with the most bentonite content,
equivalent level of effective clay density to No.7 andthe less content of silica sand was prepared. This wasto assess the contributions of sand to low
consolidation settlement and of bentonite to low
hydraulic conductivity to be discussed below.

TRIAL MIX TEST AND BASIC PROPERTIESTESTSTrial mix tests
To obtain a combination of mixture satisfying theabove criteria, the blending ratios were adjusted on a
trial and error basis. The amount of the bentonite waspredetermined 100 to 200 kg/m3 based on the authors’previous experience.
Table 1 summarizes the mix proportions tested in
the present study. No.1 to No.4 were combination
with fresh water for mixing. By adding 0.25 to 0.5 %of the dispersing agent to the whole volume of the
mixture, the cylinder flow increased by 100 mm or
more, showing the dispersing agent is effective.
However, when fresh water is used, montmorillonite
took in water and swelled; accordingly, the amount ofunit water had to be kept large to maintain the target
fluidity.
Instead, salt water was used for mixing tosuppress the swelling of bentonite. The salt consistedof sodium chloride with a NaCl concentration of 95 %or more in weight. No.5 to No.7 were the
combinations using salt water with concentrations of
1 %, 2 %, 3 % in weight, respectively. In No. 5, thefluidity was low since small concentration of the
NaCl was less effective, while No.6 and No.7
satisfied the criteria of fluidity even though thedifference is only the NaCl concentration. On theother hand, a previous study pointed out thatbentonite flocculates when brought into contact withseawater, resulting in material segregation. However,bleeding ratio additionally confirmed were 0.0 % and
0.5 % for No.6 and No.7, respectively. Regarding thisresult, the author’s hypothesis is as follows: salt water
does not contain bivalent cations such as Mg2+ andCa2+ which have a high contribution to aggregation ofa sodium bentonite unlike seawater [2]; And theeffect of dispersion is more predominant than throughthe aggregation of NaCl. As a result, material

Falling head permeability tests
The sealing performance which satisfied thecriteria of fluidity was confirmed for the fourcombinations by falling head permeability tests.
Fresh water was used in ordinary permeability tests,
and we also used 3 % salt water, simulating theimpervious material used in under sea water
environment.
As summarized in Table 2, the combination
mixing with 2 % salt water (No.6) had a remarkably
low hydraulic conductivity for pure water flow ascompared with the combination mixing with fresh
water cases (No.2 and No.4). This is because theeffective clay density of the combination of mixing
with salt water is higher than that with fresh water.
When 3 % salt water was passed through the
combination No. 6, the hydraulic conductivity rose by
about 2 orders of magnitude as compared with purewater flow. It could still keep a hydraulic conductivity
on the order of 10-8 m/s. It was therefore confirmedthat No.6 gives sufficient sealing performance evenunder sea water environment.
Table 2 Results of falling head permeability test
No. Fresh water (m/s)
2
6.31×10-5
4
6.79×10-76
1.80×10-108
9.15×10-10*3: －(Not implemented)
202

3% salt water (m/s)*3－－
1.82×10-8
3.06×10-9

GEOMATE - Mie, Japan, Nov. 21-24, 2017

created between the member and the material.
In this study, the following two permeability tests
were conducted to reproduce the deformation modeshown in Fig. 4. In addition, aside from thepermeability tests, applicability of conventional small
pump and underwater placement was examined in alaboratory demonstration.

On the other hand, clay based No. 8 had highimpervious performance when either pure or salt
water was passed through.
Incremental loading compression test

Vertical displacement (mm)Incremental loading compression tests wereconducted on No.6 and No.8. The load wasincrementally increased to 30, 60, 120, 240 kN/m2,
and the end of consolidation was judged by √t method.
Figure 3 shows changes in vertical displacements
obtained from the mixtures. Both materials settled in
the initial stage (30 kN/m2) of loading, however in
No.8, mainly composed of clay, continued to settle
even after 48 hours, eventually converging at about
half the original height. On the other hand, in No.6,
mainly composed of sand, settled in about 1 hourfrom the time of loading, with little consolidation
thereafter. Compared to No.8, No.6 had a highblending ratio of sand, so that load might have been
supported by sand particles from the early stage.
Based on the above tests, No.6 was selected as amaterial that satisfies fluidity, sealing performanceand consolidation settlement amount.
0.01
0
-2
-4
-6
-8
-10
-12
-14

Fig. 3

Loading time (min.)1
100

Shear deformation permeability test
The following three tests have been formerly
developed for confirming followability under shear
deformation in impervious materials:(1) Sampling a specimen at an actual shear planefrom a box shear test, and conducting apermeability test [3].
(2) Conducting a permeability test using a specimen
artificially cutting a specimen [4].
(3) Conducting a permeability test under uniform
shear strain generated across the specimen set ina triaxial compression chamber [5].
Since the impervious material of this study does
not solidify due to lack of hydration, it is hard to
imagine that a clear shear plane occurs. For thisreason, the above (3) was adopted in which shear
strain was uniformly generated across the specimen.
Based on the results of the incremental loading
compression test, it was assumed that the impervious
material at a certain depth would deform according tooverburden pressure. The test specimen was therefore
prepared with a water content that corresponded to
the void ratio at 40 kN/m2. The specimen size was 25
mm in height and 50 mm in diameter, and the upperand lower ends were set on the pedestals wheresilicone grease, latex rubber and filter paper wereplaced in order to reduce end friction.
In the test procedure, firstly deaerated 3 % salt
water was thoroughly passed. Secondly it wasconsolidated at a back pressure of 100 kN/m2 and acell pressure of 140 kN/m2. Then the hydraulicconductivity before shearing was measured. Thirdly
the specimen was sheared under drainage condition at
a strain rate of 0.1 %/min to a predetermined shear
train level stepwisely. During shearing process, thecell pressure was gradually decreased so as not to

10000

No.6: 30 kN/m2
No.8: 30 kN/m2
No.6

No.8

Loading step 30→60→120→ 240 kN/m2

Results of consolidation tests

PERFORMANCE CONFIRMATION TESTSOutlineHydraulic conductivity,k (m/s)

Figure 4 schematically shows deformation modes
occurring in the soil based impervious material filledin the joint of the PC wall members. When there isdeviation between the members, the impervious
material undergoes shear deformation and cracks may
occur in the material. On the other hand, when there
PC wall member
Opening
Impervious
material

Deviation

in usual

Shear deformation Interfacial separation

Fig. 4 Deformation of impervious material filled
between PC wall members (Plan view, see Fig.2 foroverall figure of PC wall members)
is a separation between the members, an opening is

1E-08
No.6

1E-09
e = 0.615
e = 0.592 e = 0.577

e = 0.566

1E-10
-10

0

10
20
30
Shear strain, γ (%)

40

Fig. 5
Relationship between shear strain andhydraulic conductivity
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Filter papar

generate any volumetric strain and density change.
After shearing, the hydraulic conductivity wasmeasured after the burette water level became
constant. After that, the shear process andpermeability test were repeated until shear strain of
40 %.
Figure 5 shows the relationship between shear
strain and hydraulic conductivity. It was confirmedthat the hydraulic conductivity did not increase withincreasing shear strain. It became clear that evenwhen shear strain of as much as 40 % occurred, theimpervious material effectively followed the shear
deformation to maintain sealing performance.

Salt
Original mold

Mold coated with salt

Fig. 6 Mold using
permeability test
burette3% salt waterforinterfacial

overburdenpressure

separation

overflow

overflow

Interfacial separation permeability test

specimen

specimen 2cm

There have been no studies attempting to
reproduce the water permeability due to interfacial
separation in element tests. Therefore, the authors
developed the following new test method.
Figure 6 shows the mold used in the permeability
test designed to reproduce interfacial separation due
to opening between PC wall members by element
tests. Figure 7 shows a setup of interfacial separation
permeability test. The acrylic mold, having 100 mm
in diameter and 20 or 50 mm in height, was firstcoated with salt on the inner wall. Once this mold wasfilled with the impervious material and water flow
was started, the salt gradually dissolved and a space
would be created between the inner wall and theimpervious material. During the process of graduallyfilling this space by the impervious material, plastic
deformation was measured by a change in hydraulicconductivity. 3 % salt water was used for water flow.
For interfacial separation in practice, two modes
are possible: one side and two side separations. They
were demonstrated both modes by having the salt
coating on half the perimeter and the entire perimeterof the inner wall. The coating thickness was set tocorrespond to 5 % of the mold cross-sectional area inboth cases when coating with salt.
Figure 8 shows the change in hydraulicconductivity with increasing quantity of water flow.
The height of the mold was 20 mm. In case half theperimeter was coated with salt, the hydraulicconductivity was large immediately after the start ofwater flow. Then, the impervious material was
gradually filled into the space, resulting in thedecreased conductivity to about 1×10-7 m/s.
In case the entire perimeter of the inner wall wascoated with salt, the hydraulic conductivity gradually
decreased at the initial stage of water flow, followed
by slight increase after water flow exceeded 200 cm3.
Because of the test condition in which the heightof the specimen was small and the overburdenpressure was not applied, the lateral displacement due
to plasticity was negligible. Thus, it was thought
impossible to fill the space. It was consequently

10cm

5cm

10cm

valve

Inside the mold under flowing
impervious
materialvalve
acrylic mold

space

salt

1. Initial condition 2. Dissolving salt 3. Space createdHydraulic conductivity , k (m/s)

Fig. 7test

Set up of interfacial separation permeability
1E-04

No.6

1E-05

entire perimeter t=1.2mm
Height of the mold =5cm

1E-06
1E-07
No loading

1E-08
0

10kN/m2 20kN/m2

200
400
600
Total volume of water flow, W (cm3)

Hydraulic conductivity, k (m/s)

Fig. 8 Hydraulic conductivity
separation permeability test
1E-04

by

interfacial

half perimeter t=2.4mm
entire perimeter t=1.2mm

1E-05

Height of the mold =2cm
1E-06
1E-07
No.6
1E-08
0

100
400
200
300
Total volume of water flow, W (cm3)Fig. 9 Hydraulic conductivity by interfacial
separation permeability test under loading condition
decided to modify the setup by replacing the top coverby a loading device that could simulate theoverburden pressure. The maximum overburdenpressure corresponded to the self-weight of theimpervious material of about 1m high.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

As shown in Fig. 9, the hydraulic conductivity
decreased to the order of 10-7 m/s. It is confirmed thatthe impervious material can keep sealing
performance by plastic deformation induced by its
own weight.

reproduce the water permeability due to interfacial
separation in element tests available in the literature,
the authors had devised a new test method and applied
it to the developed impervious material. From theresults of the study, the following may besummarized:

Underwater placement test

(1) Sealing performance
Fresh water flow: the order of 10-10 m/s
Salt water flow: the order of 10-8 m/s(2) Consolidation
Amount of consolidation settlement was small
and it converged early because it containedplenty of sand.
(3) Sealing performance in shear deformation
Even at a high shear strain of 40 %, water barrier
was effective, and it effectively followed theshear deformation, and sealing performance wasmaintained.
(4) Sealing performance in openingWhentheoverburdenpressurethat
corresponded to its own weight was applied, theimpervious material deformed to the sides,
filling the spaces.
(5) Underwater placement
By appropriately setting the discharge flow rate,
it was possible to construct a uniform
impervious material vertically even underwater.

The authors conducted underwater placement test
by a small grout pump. A squeeze type pump MM
105 manufactured by ShinMaywa Industries, Ltd.
was used. The maximum discharge pressure is 2.5
N/mm2, and the discharge flow rate can be adjusted
in three stages of 40, 75, 100 cm3/min. Although thetube diameter of the grout pump is 50 mm in general,the diameter was reduced to 25 mm in the middle ofthe tube line, so that it could be placed in narrower
spaces between PC wall piles. Setting tube length as
10 m, the impervious material was pumped throughthe tube and was placed in an acrylic pipe having 100
mm in diameter and 1.5m in height, which had
initially been filled with fresh water. During theplacement, the discharging end of the tube was kept
in the material.
Before the actual placement, we made sure theimpervious material was discharged from the tube. In
pumping at 100 cm3/min which is the maximum
discharge rate of the pump, separation and clogging
was not observed.
Figure 10 is a photograph to show the state after
placing impervious material underwater. When the
discharge rate was set at 40 cm3/min, there was no
entrapment of water bubbles, nor segregation of thematerial. When the rate was increased to 75 cm3/min,the discharged material around the tube periphery was
disturbed because of too high a discharge rate. As aresult, the surrounding water was introduced in thematerial during placement, and water bubbles wereformed in the entire material placed underwater.

REFERENCES[1] Watabe Y, Yoshino H, Kakimoto R, Ukai A,
Oki T, Oka Y, Kita H, Nagao N, Mochizuki T,
Kinoshita M, “Applicability of impermeable
steel seawalls for confined waste disposal site incoastal areas”, Technical Note of the Port andAirport Research Institute, No.1142, 2006. (inJapanese)[2] Katsumi T, Ishimori H, Ogawa A, Yoshikawa K,
Hanamoto K, Fukagawa R, “Hydraulicconductivity of nonprehydrated geosynthetic
clay liners permeated with inorganic solutions
and waste leachates”, Soils and Foundations,Vol.47, No.1, 2007, pp.79-96.
[3] Kodaka T, Teramoto Y, Hirate T, Motoyama Y,“Performance evaluation of compacted
bentonite buffer material at shear failure”, J.
Geotechnical Journal, No.5, Vol.2, 2010,
pp.207-218. (in Japanese)[4] Takai A, Katsumi T, Inui T, Kamon M, Araki S,“Long-term durability of soil-bentonite cutoff
walls used for containment of groundcontamination”, Proc. of the 8AYGEC, 2016,
pp.263-268.
[5] Imamura S, Goto S, “Experimental study on
permeability characteristics of bentonite/sandmixtures”, Report of Taisei Technology Center,No.22, Extra number, 1989. pp.3-10. (inJapanese)

Water bubbles

40 cm3/min

75 cm3/min

Fig. 10 View of the impervious material after
underwater placement
CONCLUSIONSIn this study, the authors attempted to develop asoil based impervious material to be filled in asubmerged narrow space with a gap width of about
hundreds of millimeters. Through the laboratory
studies the blending ratio of bentonite, sand water andthe dispersing agent was optimized. Furthermore,since there were no studies that had attempted to205Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

SEISMIC RESPONSE ANALYSIS OF A REINFORCED EARTH WALL USING THE
REINFORCEMENTS INCORPORATING BOTH FRICTION RESISTANCE AND
BEARING RESISTANCE
1,3

Hirohisa Muto1, Takeshi Kodaka2 and Akihiko Naganuma3
Yahagi Construction Co. Ltd., Japan,2 Professor，Meijo University
ABSTRACTPast large earthquakes have demonstrated that the seismic performance of reinforced earth walls is
considerably high. Although 1g shaking table tests and centrifuge tests of reinforced earth walls have been
carried out to study the reinforcing mechanism, there are no sufficient filed measurements collected during
earthquake. We newly developed a reinforced earth wall using reinforcement members incorporating both
friction and bearing resistances. The dynamic behavior of the reinforced earth wall were studied from two
relatively large aftershocks of the 2011 off the Pacific Coast of Tohoku Earthquake occurred in the construction
area in 2012 and 2013. In this paper, acceleration response and axial forces of the reinforced earth wall are
discussed. Numerical simulations of the field measurements were also conducted using a dynamic finite element
analysis. The simulated axial forces match the field measurements well. The results also explain the effects ofreinforcements by friction and bearing plates accurately.
Keywords: Reinforced earth wall, Seismic behavior, Bearing resistance, Friction resistance2013. The reinforced earth wall and seismic
behavior were modelled using a finite element
analysis to study the interrelation between thereinforcement and ground. Then, we compared thefield measurements of acceleration and axial force
with the results of numerical simulations.

INTRODUCTION
In recent years, large earthquakes occurred
frequently in Japan. The Great East Japan
Earthquake of M9.0 occurred in 2011. A M9.0
magnitude, wide area and long shaking time werethe main characteristics of it. An earthquake
occurred in Kumamoto in 2016 exhibited more thanonce of maximum seismic intensity 6 in a shortperiod. Thus, the characteristics of earthquakes aredifferent. Therefore, it is important to evaluate theseismic performance of each structure. The Great
Hanshin-Awaji Earthquake occurred in 1995 became
a turning point for seismic designs in Japan. The
damages by earthquakes have largely been caused
due to collapse of the pier of reinforced concrete
structures and slope failures of embankments. There
were many cases of collapse of anti-earth pressure
structures like block stacking. However, reinforced
earth walls have been less damaged. Highearthquake performance of reinforced earth walls
has been proved in laboratory test such as 1-g
shaking table tests and centrifugal model tests [1].
Experiments [1] on gravity retaining wall andreinforced earth wall have revealed that deformationof reinforced earth walls is smaller. They have also
indicated that the deformation mechanism of thereinforced soil wall is related to the response
acceleration. Therefore, it is necessary to understandthe effect of reinforcement to evaluate the seismic
performance.
We developed a reinforced earth wall
incorporating bearing and friction resistances. Axial
force and response acceleration were measured
during aftershocks of the Great East Japan
Earthquake as the seismic observations in 2012 andTHE EXPERIMENTAL SET-UP
Front and cross-section views of reinforced earth
wall are shown in Fig. 1. The reinforced earth wallconsists of separate lower and upper parts. The
lower part of earth wall was constructed withimproved embankment materials by cement tosimulate the ground. In addition, the lower part was
reinforced by general and reaming type anchors. The
cross-section of the general anchors is maintained
throughout at 90mm. The diameter of the reaming
anchor is equal to that of the general anchor to apredetermined length and the tip end portion is large(see Fig. 2). The improved embankment material
was placed to the length of the general anchor. One
side of the reinforced earth wall was constructedwith a cantilever retaining wall. The other side andthe back side have natural gradients.
Lower Part of Reinforced Earth Wall
The reinforcement details of the lower part are
given in Table 1. The dimension of the facing panel
made of reinforced concrete is 1800mm in width,
1200mm in height and 150mm in thickness. Thesepanels are placed at the front of the reinforced earth
wall. A tibar (core material) of high rigidity is fixedo the center of the facing panel by a washer and nut.
The grout material is filled around the rod. Similar
206

GEOMATE - Mie, Japan, Nov. 21-24, 2017

A front view

Cross section view
（Lower part：Part of the reaming type anchor）
Ａ
14400

7200

12600

18000

6500

10000
300

Upper part of reinforced earth wall
（Red hatching）

Friction plate
Facing panel

1：
1.5

D19 L=4.5m □-400
D19 L=4.0m □-400

Reinforcement

D32 L=
4.5m
D32 L=
4.5m

Improvement area

8.0m
Length of improvement area

Upper part of reinforced earth wall Lb=19.8m
Lower part of reinforced earth wall Lc=21.6m

1800

D19 L=5.5m □-400

Bearing plate2@1200
=2400

0
1：3.

8000

D19 L=6.0m □-400

4@1200=4800

Lower part of reinforced earth wall
(blue hatching)

7500

1800

Improvement area

Cantilever retaining wall

Ａ

※Lower part of reinforced earth wall
The positions of blue circular are reaming type anchor
On the other hand,the general type anchor

Cross section
In the case of the general type anchor

8.0m
Length of improvement area

D32 L=
8.0m
D32 L=
8.0m

Fig. 1 Front and cross-section picture of reinforced earth wall
Facing panel
Drain valve

Facing panel

Back drainage layer
Fixing plate
The back filling material

Tiber

Grout injection guide90

reaming part

300

Friction plateCore material
Fixing washer

Bearing plate

Filling material（Grout）

Fig. 3 Upper part of reinforced earth wall
Table 2 Reinforcement specifications

Tapered washer
NutFig. 2 Lower part of reinforced earth wall
Table 1 Details of the reinforcements
Stage Height
2nd
1st

1.8m
0.6m

Tibar
Diameter Length
D32
4.5m
D32
4.5m

Generalpart

Reaming
part

φ90mm

φ300mmStage Height6
5
4
3

reinforcements are often used in soil nailing [2]. The
reinforcements are stabilized by friction resistance
between the fixing material and ground.
The reaming anchor provides both friction andbearing resistances. The reaming anchor has 90mm
diameter to 3.5m length and the remaining length of
1.0m is made with 300mm diameter as shown in Fig.
2. However, the general anchors were constructedwith 8m length since they provide only frictional
resistance. Generally, the soil nailing has a gradientof facing panel from 3/100 to 5/100. However, thewall gradient of this construction is vertical to alignthe wall gradient of the upper part.

6.6m
5.4m
4.2m
3.0m

Tibar
Diameter Length
D19
6.0m
D19
5.5m
D19
4.5m
D19
4.0m

Bearing platesize

400mm×400mm

reinforcement follows the embankment settlement,
and it is possible to reduce stress concentration on
the facing panel. The specifications of thereinforcement in the upper part are given in Table 2.
The dimension of the friction plate is 450mm wide,
600mm deep and 15mm thick. Also, ribs of 10mmhigh were placed on the upper surface of the friction
plate to increase pull-out resistance. The bearing andfriction plates are made of ultra-high strength fiber
reinforced concrete.
Embankment and Ground Conditions
An embankment in Tomita-cho, Kurokawa-gun,
Miyagi Prefecture was used in this study. The grain
size distribution of embankment material is shown in
Fig. 4. The material has 1.6kN/m2 of cohesion and35.3 degree of internal friction angle. Soilcompaction test gave 1.68g/cm3 of maximum dry
density and 18.4% of optimum water content.
Standard penetration tests, borehole lateral load
tests and in-situ density tests were performed.

Upper Part of Reinforced Earth Wall
The upper part of the reinforced earth wall is
illustrated in Fig. 3. A high rigidity rod (tibar) used as
the reinforcement incorporates friction resistance byfriction plate and bearing resistance by bearing plate.
The same facing panels used in the lower part areused here. The facing panel and reinforcement isconnected using a hinge. Therefore, the reinforcement
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

gauges were added since the behavior of axial force
at the front of the friction plate and back of thefacing panel are different.
Acceleration sensors were installed on thefoundation ground (Acc01), above (Acc02) andinside the reinforced earth wall (Acc03 - Acc05).
The Acc04 and Acc05 of sensors were attached to
the lid of a U-shaped groove and buried in soil.
Acc03 sensor was attached directly to the facing
panel. All sensors are water-proof and protectedwith a steel cover. Static measurement was taken at
1hr intervals. Dynamic measurement can be started
and stored automatically when an acceleration
sensor exceeds the set value by occurring earthquake.

Standard penetration test was carried out at 3m and
8m from the front side of the reinforced earth wall.
The results of standard penetration test are shown in
Fig. 5. SPT N-value in the upper part varies from 617, and increases with depth. SPT N-value in thelower part varies from 42-43 in the near borehole
while 12-24 in the far borehole from the facing panel.
The results indicate that the SPT N-value increases
near the facing panel due to soil improvement. The
borehole at 8m can be considered as the boundary
between the improved and unimproved grounds.
The positions of the borehole lateral load test
(LLT) are shown in Fig. 5. The borehole lateral load
test used the same boreholes constructed forstandard penetration test. The tests were conducted
at depths of 2.7 and 9.3m as shown in Fig. 5. The
test was conducted in compliance with JGS (JGS
1421-2003) standard. The tests produced thedeformation coefficient of 5.63MPa at LLT No.1,
2.42MPa at LLT No.2 and 4.74MPa at LLT No.3.
The N-values calculated using the deformation
coefficient are 8.7 for LLT No.1, 3.7 for LLT No.2
and 7.3 for LLT No.3. The calculated N-values
agree with the measured SPT N-values as shown in
Fig. 5.
In-situ density test was carried out in the upper
part of the reinforced earth wall. The measurement
position is about 1m from the facing panel,
underneath the friction plate and on the front side of
the bearing plate. The dry density, d varies from
1.52 to 1.77g/cm3. The degree of compaction, Dc(the ratio of the dry density, d and the maximum
dry density, dmax) varies from 90.3 to 105.3%. The
water content, w varies from 16.6 to 20.3%.

Pass mass percentage

(%)

100
80
60
40
20
0
0.001

0.01

0.1
1
Grain diameter (mm)

10

100

Fig. 4 Grain size distribution curve
3000

5000

4
2

2700

3
4 2
4

7
5 1
2 1
2 2
1.
1 1
3
7

LLT
No.3

0
1

9300

8

5
2 1
71
.
8
6 8

LLT
No.1

2
1

3
1
4
4

LLT
No.2

0
3

0
2

N-value

0
1

0

0
4

0
3

0
2

0
1

0

Axial forces and accelerations were measured in
the constructed reinforced earth wall. The
measurement positions are shown in Fig. 6. Bothstatic and dynamic measurements of axial force were
measured
duringandafterconstruction.
Deformation such as embankment settlement may
induce bending stress in tie bars. A strain gauge wasinstalled on the upper and lower surfaces of the tibar
to cancel such bending stress. However, if bearing
plate and facing panel is completely fixed, tension
induced by bending of tie bars is calculated as axial
force. As shown in Fig. 7, the strain gauges for static
axial force (TB3 - TB6, TC3 - TC6) was placed at thefront of the bearing plate (C3 - C6) and the front of
the friction plate (B3 - B6). The strain gauge forseismic axial force was set at the same positions and
500mm from the back of the facing panel (A3 - A6).
Friction resistance may mobilize between tibars andground during earthquakes [3]. Therefore, the strain

7.
33

Improvement Area

The Field Measurements

Fig. 5 Results of standard penetration test
Friction plate
Bearing plate

Acc02

Facing panel

A6

B6

A5

B5

Acc03

C6
C5
Acc05

A4
A3

B4
B3

C4

C3
Acc04

Acc01

【Explanatory note】
Acceleration

Strain gage（static，seismic）
Strain gage（seismic）

Fig. 6 Measurement positions
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

earth wall shown in Figs. 9(b) to 9(h) excluding 9(e)at H25. The numerical results indicate that 5-6Hz is
dominant at 5-6Hz at H24, 2-3 and 5-6 Hz and 78Hz are dominant at H24. It also suggests that 2-3Hz
and 4-5Hz are dominant at H25. Although there is aslight difference in the phase, they tend to agree well.

NUMERICAL SIMULATIONS
The analytical conditions are given in Table 3.
The foundation ground has a height of 5m and awidth of 80m. An elastic constitutive model was
assigned. The elastic coefficient was calculated
assuming a 300m/s of shear wave velocity. It was
assumed that the ground is strong and elastic
constitutive law was assigned since the lower part ofreinforced earth wall is constructed with improved
soil. The upper part of the reinforced earth wall was
assigned the Mohr-Coulomb law. All theconstructional members were considered as elastic
bodies. The boundary condition was set as thefoundation ground, the bottom of the ground is afree boundary and the side is a viscous boundary.
The earthquakes considered in this study occurredon 30 August 2012 (hereinafter H24) and 4 August
2013 (hereinafter H25). The earthquake waves wereapplied to the bottom of the foundation ground.
However, the measurement was taken above thefoundation ground (Acc01). Therefore, a pull-backcalculation was carried out using K-SHAKE todetermine the earthquake waves to induce on thebottom of the foundation ground. Acceleration ismeasured for 30 seconds or more, but 4s including
the maximum acceleration was used in the analysis,.
The earthquake waves from the fieldmeasurements and the pull-back calculation are
shown in Fig. 7. In Fig. 7, the acceleration direction
is negative on the embankment side and positive on
the facing panel side. The maximum accelerationfrom at Acc01 is 155cm/s2 from H24 and 95cm/s2
from H25. The amplitude of the earthquake waves
from the pull-back calculation is smaller. However,the phases are almost identical.

Static Measurement of Axial ForceThe static measurement of axial force is shownin Fig. 10. Axial force during the construction
increases with its progress. The axial force after
construction suggests a constant value. The axial
force is smaller on the front of the bearing plate (C3Table 3 Analytical conditions
Stage

3

4

5

6

N-value

15

12

8

6

196.2

169.1

129

106.5

Elastic
coefficientE

M N/m2

Cohesion

c

kN/m2

10

Internal frictio
angle

f

°

40

Dilatancy angle

y

°

10

Accerelation (cm/s2) Accerelation (cm/s2)

Rayleigh damping

0.02／0.02

／

150

(a) H24

75
0
-75

0

1

2

measured waves

-150
150

3

4
time (sec)calcuated waves(b) H25

75
0
-75

0

1

2

3

4
time (sec)-150

Acceleration (cm/s2)(a)H24、Acc01

150
0
-150

0

1

2

-300
300

3

0

0

1

2

-300
300

3

0
-150

0

1

2

3

Acceleration (cm/s2)

-300
300
150
0
-150
-300

209

0

1

2

3

1

2

-300
300

3

4
time (s)(f)H25、Acc03

150
1

2

3

4
time (s)-300300(g)H25、Acc04

150

0
4
0
-150
time (s)(d)H24、Acc05(e)H25、Acc01

150

0
4
0
-150
time (s)(c)H24、Acc04

150

300

0
4
0
-150
time (s)(b)H24、Acc03

150

-150

Acceleration (cm/s2) Acceleration (cm/s2)

The accelerations are shown in Fig. 8. The phaseand amplitude of the acceleration on the foundation
ground are consistent with each other. The
accelerations of the facing panel (Acc01) and theinside of the reinforced earth wall (Acc04, Acc05)
are almost identical in phase. However, thenumerical simulations gave a slightly higher
acceleration. Therefore, we can say that thereinforced earth wall can be modeled withacceptable accuracy.
The results of Fourier spectrum analysis of theacceleration are shown in Fig. 9. The frequencies on
the foundation ground shown in Figs. 9(a) and 9(e)are dominated by 5-6Hz and 7-8Hz at H24 and 23Hz at H25. The Fourier spectrum results agree wellwith the field measurements. Therefore, we canconfirm that earthquake wave from the pull-backcalculation is accurate. The field measurements ofthe facing panel and the inside of the reinforced

300

Acceleration (cm/s2)

Acceleration

Acceleration (cm/s2)

Acceleration (cm/s2) Acceleration (cm/s2)

Fig. 7 Field and calculated earthquake waves

1

2

-300
300

3

4
time (s)(h)H25、Acc05

150

0
4
0
-150
time (s)-3001measured2

3

4
time (s)calculated

GEOMATE - Mie, Japan, Nov. 21-24, 2017

100

0
100

5

Seismic Measurement of Axial Forcecalculated(e) H25,Acc01

0
100

0
100

10 H24,Acc03
15
20 0
(b)

5

10
15
20
(f) H25,Acc03
Frequency (Hz)5

10 H25,Acc04
15
20
(g)
Frequency (Hz)

5

10
15
20
(h) H25,Acc05
Frequency (Hz)

5

10
15
Frequency (Hz)Frequency (Hz)50

0

5

0
100

10H24,Acc04
15
20 0
(c)
Frequency (Hz)50

50
0

0

5

Frequency (Hz) 50

50
0

0
100

10 H24,Acc05
15
20 0
(d)

0

5

0

10
15
20 0
Frequency (Hz)The variation of axial force during anearthquake is shown in Fig. 11. Here, axial force
indicates that the change since the earthquake
occurred. Also, axial forces TBi~TCi (i=1~3) are thevalues measured by Bi~Ci (i=1~3). It can be seenthat the axial force is larger at sixth stage (TB6, TC6)
than third stage (TB3, TC3). It also indicates that theaxial force of friction plate is higher than the bearing
plate. This trend is similar to the static measurement
as well. The axial force on front of the bearing platesuggests a different tendency only at third stage TC3
that the phase was different and the value increased
monotonously. This may be attributed to thedifference in deformation since the improved soil isused in the lower part of the reinforced earth wall.
The results also suggest that the numericalsimulation gave slightly smaller axial forces,
although the phases are generally identical.

20

Fig. 9 Results of Fourier spectrum analysis(kN)

60
Constructionrdcompleted (a) 3 stage

Construction
thcompleted (b) 4 stage

40

axial force

40

TB3

20
0
60 6/840

060 6/81/18
8/30
Construction
thcompleted (c) 5 stage
TB5

20
TC5

6/8

1/18

Seismic Behavior of Each Resistance
The variation of each resistance with time isshown in Fig. 12. In Fig. 12, the change from
PB3~PB6 in bearing resistance is corresponding to
the change in axial force from TC3~TC6 at the front of
the bearing plate. The change from PF3~PF6 infriction resistance is corresponding to the change inthe difference in axial force between TC3~TC6 on thefront of bearing plate and TB3~TB6 on the front of

TB4

20

TC3

(kN)

(kN)
axial force
(kN)

0

50

0

was confirmed that friction and bearing plates
mobilized their resistance force from the start ofconstruction [4]. Here, the burden ratio of the total
resistance by the friction resistance after
construction has changed from 30 to 50%.

50

50

60

measured(a)H24、Acc01

100

axial force

spectrum (gal・s) spectrum (gal・s) spectrum (gal・s) spectrum (gal・s)

100

axial force

spectrum (gal・s) spectrum (gal・s) spectrum (gal・s) spectrum (gal・s)Fig. 8 Accelerations at the measurement points- C6) TC3~TC6 than the front of the friction plate (B3- B6) TB3~TB6. The difference in axial force between
the friction and bearing plates is the resistancemobilized by the friction plate. The axial force on
the bearing plate is the resistance mobilized by it. It

8/30

40

TC4

1/18

TB6

20
0

6/8

8/30

Construction
thcompleted (d) 6 stage

1/18

TC6

8/30

Fig. 10 Static measurement of axial force

Fig. 11 The seismic measurement of axial force
210

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 12 Results of seismic measurement of each resistancefriction plate. It can be seen that the change inresistance force.
bearing resistance from PB3~PB6 is larger at sixth
3. The results from the numerical model arestage than third stage. The change in friction
consistent with the field measurement of axial
resistance from PF3~PF6 is larger at third stage
force and acceleration. Thus, we can conclude thatthan sixth stage. The resistance by the friction plate
the reinforced earth wall can be simulated
is larger at third stage than sixth stage. Therefore, we
accurately.
can confirm that bearing and friction plates mobilise
4.
The numerical model could be validated. In future
their resistance even when an earthquake occurs. It
works, we will examine the stability and seismic
also indicates that the reinforcements at shallow
depth increases the resistance by friction plate, andbehavior of the reinforced earth wall by applying
the reinforcements at deep depth increases theother earthquake motions.
resistance by bearing plate.
The numerical simulations give slightly smaller
REFERENCES
axial forces than the field measurements, although
the phases are almost identical. Therefore, we can[1] Nakajima.S. ， Koseki.J. ， Watanabe.K. ， andconclude that it is possible to simulate the resistance
Tateyama.M.：Simplified procedure to evaluate
earthquake-induced residual displacement ofof bearing and friction plates by this analysis model
geosynthetic reinforced soil retaining walls,
quite accurately.
Soils and Foundations, Vol.50, No.5, pp.659677, 2010.
CONCLUSIONS[2] Fujiwara.Y. ： A study on the long-term
durability of reinforced cut slopes, Journal of
In this paper, the seismic measurements of axial
Japan Society of Civil Engineers, Ser. C
force of a reinforced earth wall and accelerations(Geosphere Engineering), Vol.71, No.3, pp.147from the 2012 and 2013 earthquake were discussed,
162, 2015 (in Japanese).
and compared them with analysis results. In addition,[3] Futaki.M., Misawa.K. and Tatsui.T. : Actual
the results from a numerical simulation of thesize vibration test on the Multi-anchoredretaining wall with large-scale shear box, Proc.
reinforced earth wall were compared with the fieldof 35th Japan National Conference on
measurements. The following conclusions were
Geotechnical Engineering, pp.2215-2216, 2000
drawn from the study.
(in Japanese).
1. The earthquake occurred on 30 August 2012 was[4] Muto.H., Kamiya.T., Naganuma.A, Kodaka.T.,
dominated by frequencies of 5~6Hz and 7~8Hz.
Cui,Y., Nakano.M. and Noda.T. : Construction
The earthquake occurred on 4 August 2013 was
experiment of reinforced soil wall using
dominated by frequency of 4~5Hz.
reinforcement member incorporating both
friction resistance and bearing resistance,
2. The results revealed that the resistance forces
Japanese Geotechnical Journal, pp.33-46, 2017
mobilised by bearing and friction plates during the(in Japanese).
earthquake
effectively
demonstrate
each
211

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EFFECT OF CEMENT TYPES ON STRENGTH DEVELOPMENT OFCEMENT-TREATED SOILS
Lanh Si Hoa,b, Kenichiro Nakaraia, Kenta Eguchia, Takashi Sasakic, Minoru Moriokaca

Hiroshima University, Department of Civil and Environmental Engineering, Graduate School of Engineering,
1-4-1, Kagamiyama, Higashi-Hiroshima, Hiroshima 739-527, Japanb

University of Transport Technology, Department of Geotechnical Engineering, Faculty of Civil Engineering,
54 Trieu Khuc, Thanh Xuan, Hanoi, Vietnamc

Denka Co., Ltd., Cement & Special Cement Additives Research Dept., Omi Plant, 2209 Oaza Omi, Itoigawa,Niigata 949-0393, Japan

ABSTRACTHigh early strength Portland cement (HPC) generates more hydrated cement products than ordinary Portland
cement (OPC) in early age. It suggests that we can utilize the pozzolanic reaction between clay particles andhydrated cement products by using HPC in order to achieve high compressive strength of cement-treated soils inearly age. Therefore, the objective of this study is to investigate strength development of cement-treated soils using
two types of cement (OPC) and HPC). Two soil specimen types (i.e. sand and sandloam mixtures) were cured
under sealed condition at 20C and 40C and then unconfined uniaxial compressive test and thermal analysis wereconducted. The results showed that the compressive strength of specimen using HPC under 20C was 50% and
24% higher than that of specimen using OPC for the sand and sandloam mixtures, respectively. However, theresults by thermal analysis did not provide clear evidence for explaining this unique behavior of HPC. In addition,
for the specimen using OPC, the compressive strength under 40C was 6% and 10% higher than that under 20C
for the sand and sandloam mixture, respectively; but, for the specimen using HPC, the compressive strength
under 40C was 15% and 48% lower than that under 20C for the sand and sandloam, respectively. The further
investigations on microstructure and mineralogy are needed to clarify the strength development mechanism of
cement-treated soils using several types of cement under various curing temperature.
Keywords: Cement Hydration, Pozzolanic Reaction, High Temperature Curing, Cement Types, Cement-Treated
Soils.

In the field of concrete engineering, the highstrength at early age was accelerated by hightemperature curing because cement hydration process
is promoted under that condition [79]. However, it
was stated that long-term strength of concretedecreases under high temperature curing because
main hydrated cement products formed have no time
to arrange suitably, and this caused a loss of strength,
this behavior had been called as the crossover effect[1013].
It is known that high early strength Portland
cement (HPC) has been applied to concrete andmortar for promoting cement hydration process, theheat generated from HPC at early age is larger thanthat from ordinary Portland cement (OPC) [14, 15].
As a result, the compressive strength at early age(until 7 days) of the specimens using HPC was 20%
higher than that of the specimens using OPC. It
suggests that HPC could be applied for cementtreated soils for producing high heat at early age that
may activate the pozzolanic reaction between
hydrated cement products and soil particles. Thus, we

INTRODUCTION
Cement-treated soils or cement-mixed soils havebeen applied popularly to soft soil improvement,
especially for deep mixing treatment. It is known thatthe compressive strength of cement-treated soils still
increases considerably for several years [1, 2]. The
short-term strength is produced by cement hydrationand long-term strength is mostly attributed topozzolanic reaction. The deep mixing method usuallyuses big size of soil-cement column. Previous study
on temperature history of field deep mixing column
revealed that temperature in the core of column
generated from cement hydration reachedapproximately 50C and maintained at thattemperature for several months [3]. It implies that thecore of soil-cement column was subjected to hightemperature. This high temperature may also promotehydration and pozzolanic reaction process. Previous
studies on cement-stabilized clay found that thestrengths in both short and long-term increase underhigh temperature curing [46].
212

GEOMATE - Mie, Japan, Nov. 21-24, 2017

can use HPC for cement-treated soils to promote
cement hydration and utilize pozzolanic reaction inorder to achieve high early strength development.
Therefore, the objective of this study is toinvestigate the strength development of cementtreated soils by using two types of cement (OPC and
HPC) cured under the sealed condition at different
temperatures (20C and 40C). The compressive
strength was measured by the unconfinedcompression test. Thermal analysis was applied to
examine the change in chemical reaction progress for
explaining strength development.

of the sandloam mixture, before mixing the soil withwater, the loam and Toyoura silica sand were mixed
together for 1 min by using the mixer. After mixing,
cylindrical specimens 50 mm in diameter and 100
mm in height were cast by compaction by using arammer with a weight of 1.5 kg based on JCAS L01:2006 standard. Each specimen had three layers;
the height of each layer was around 1/3rd the heightof the specimen. The rammer was dropped 12 times
from a height of 200 mm on each layer of eachspecimen.
Specimens were cured under the sealed condition.
The reproducibility of measurements after five timesof curing (1, 3, 7, 14, and 28 days) was tested
systematically on three similar specimens. For all
specimens obtained after casting into tin molds, thetop surfaces were immediately sealed with aluminum
tape and cured in a room at a constant temperature of
20°C and 40°C for the prescribed curing period. To
ensure the drying and carbonation did not occur, theweights of the specimens under the sealed condition
were measured and found to have constant values forthe entire curing period.

MATERIALS AND METHODS
Materials
Two types of soil were used in this study
including: Toyoura silica sand and Toyoura silica
sandloam mixtures. Toyoura silica sand was chosenbecause of its recognition as a natural standard sandfor experiments in Japan that has low pozzolanic
reactivity (166 mg of CaO consumed by 1 g of sanddetermined by the French standard for the modified
Chapelle test NF P18-513). Meanwhile, the Kantoloam produced in Kasama (Japan) is a kind of
volcanic cohesive clay that exhibits a high pozzolanic
reactivity (580 mg of CaO consumed by 1 g of loam
determined by the Chapelle test [16]). Ordinary
Portland cement (OPC) and high early strengthPortland cement from Denka (Japan) were used. The
specific densities of the Toyoura silica sand,
OPC/HPC, and loam are 2.65 ×103, 3.15/3.14 ×103
and 2.79 ×103 kg/m3, respectively. The designed
values of the specimens are listed in Table 1.
Table 1 Designed values of cement-treated soil
specimens.

Mixture

Sand
Sand–
loam

Sand

Loam

content

content(wt.%)(wt.%)

100
95

Cement/soil

Water/cement(wt.%)(wt.%)

0

8

100

5

8

100

Methods
The compressive strength of the specimens wasmeasured by the unconfined compression test [17]. At
each age of curing under tested condition, three
specimens were used for the compression test. The
tests were performed at a constant loading rate of 0.1
mm/min using a hydraulic universal system testingmachine from Shimadzu Corporation (Japan) withmaximum load capacity of 50 kN.
The amounts of chemically bound water andCa(OH)2 were measured by TG-DTA. The mass loss
due to chemical reactions was taken by the loss of thetemperature range (1051000C). The amounts of
Ca(OH)2 were determined from the values of massloss obtained from thermalgravimetry analysis curve(TGA) based on the initial and final temperatures (C)of the DTA peaks (between 400C and 460C).
RESULTS AND DISCUSSION
Compressive Strength

Specimen preparation

Fig. 1 shows the compressive strength of the sandmixture specimens using different cement types. In
the case of OPC specimens, the compressive strengthof the specimens cured under 20C and 40C
increased rapidly until 7 days, then it slightly
increased from 7 to 28 days. For that curing period,
the compressive strength of the specimens cured
under 40C was 6% higher than that of the specimens
cured under 20C. Thus, we can conclude that hightemperature curing could increase the compressive
strength of the sand mixture. This increase in strength
was caused by pozzolanic reaction between sandFirst, soil and water were mixed using amechanical mixer for 1 min to control the watercontent. Next, the mixtures were mixed again for 1
min by hand to remove the materials attached to thebowl and paddle of the mixer. Then, the mixtures
were mixed again for 1 min by using the mixer.
Subsequently, cement was added and mixed for 1 minusing the mixer. Finally, the materials were mixedagain for 1 min using the mixer after 1 min of mixing
by hand to achieve higher homogeneity. In the case213

GEOMATE - Mie, Japan, Nov. 21-24, 2017

compressive strength under 40C was not only 48%
lower than that under 20C but also significant lower
than those of the specimens using OPC. This may be
explained by the combined effect of high temperature
curing and rapid hydration process of HPC that could
promote crossover effect. At 28 days, thecompressive strength of the specimens using HPC
under 20C was 24% and 12% higher than that of thespecimen using OPC under 20C and 40C,
respectively, as observed in the sand mixture.
In both the sand and sand-loam mixtures, thecompressive strengths of the specimens using HPC at
28 days under 20C were 50% and 24% higher thanthose of the specimens using OPC, respectively. Thisis a unique behavior that was different from mortar
and concrete.

particles and hydrated cement products, which can fill
into porous structures of the sand mixture. This will
be explained in thermal analysis section.
With regard to the HPC’s specimens, thecompressive strengths increased quickly until 7 days
under both 20C and 40C, then they increasedslightly. At the age of 1 day the compressive strengthof the specimen cured under 40C was 48% higher
than that of the specimen cured under 20C. However,after 1 day, the tendency was different, at 28 days thestrength of the specimens cured under 40C was 15%
lower than that of the specimens cured under 20C,
this behaviour was similar to concrete, which wascalled as the crossover effect [1013]. Because thespecimens used HPC itself has quick hydration
process, and under high temperature curing thehydration process can be promoted more rapidly that
leads to crossover effect happened strongly.
It was interesting that the observed compressive
strength at 28 days of the specimen used HPC under
20°C was 50% and 42% higher than those of thespecimens used OPC under both 20C and 40C,
respectively. Particularly the compressive strength of
the specimen using HPC at 3 days under 20C was
14% higher than that of the specimens using OPC at
28 days. It suggests that using HPC could achieve
high strength at early age.

Fig. 2 Compressive strength of the sandloam
mixture specimens used different cement types andcured under different curing temperatures.
Thermal Analysis
The amounts of the chemically bound water andCa(OH)2 were measured to examine chemical
reaction progresses for explaining strength
development.
Fig. 3 shows the chemically bound water of thesand mixture. It was observed that the chemicallybound waters increased rapidly until 7 days, then they
were almost stable until 28 days. The chemicallybound water of the specimen using HPC and OPC
under 40C were 22% and 31% higher than those of
the specimen using OPC under 20C, respectively.
The higher chemically bound water are, the more
hydrated cement products generated. The higher
chemically bound water in the specimens using HPC
may explain for the difference between strength of thespecimens using HPC and OPC.

Fig. 1 Compressive strength of the sand mixture
specimens used different cement types andcured under different curing temperatures.
The compressive strength of the sandloam
mixture using OPC and HPC cured under 20C and40C is shown as in Fig. 2. Similar to the sand mixture,in term of OPC, the compressive strength increased
gradually until 28 days. At 28 days the compressive
strength of the specimens under 40C was 10% larger
than that of the specimens under 20C. It can be
explained that under high temperature curing, thecement hydration and pozzolanic reaction could bepromoted, leading the increase in compressive
strength.
For the case of HPC, the high temperature curing
had negative effect on strength development. The
214

GEOMATE - Mie, Japan, Nov. 21-24, 2017

water under 40C was 21% higher than that under
20C. This is caused by high curing temperature that
could promote cement hydration process. Similarly,
for the specimen using HPC, the amount of thechemically bound water under 40C was higher thanthat under 20C until 28 days. The amount of thechemically bound water in the specimen using HPC
was almost as same as that in the specimen using OPC
under 20C. The chemically bound water and amountof Ca(OH)2 could not explain for the higher strength
in the specimens using HPC under 20C.
Fig. 3 The chemically bound water in the sandmixtureFig. 4 presents the amount of Ca(OH)2 in the sandmixture. In the case of the specimen using OPC,
under 20C, the amount of Ca(OH)2 increased
gradually until 28 days. However, under 40C, theamount of Ca(OH)2 increased rapidly until 7 days due
to cement hydration caused by high temperature.
Then, the amount of Ca(OH)2 was almost constantfrom 7 to 28 days. At early age (until 14 days), theamount of Ca(OH)2 in the specimen under 40C was
6% higher than that in the specimen under 20C.
Nevertheless, at 28 days the amount of Ca(OH)2 inthe specimen under 40C was 4% lower than that in
the specimen under 20C. This is explained by
pozzolanic reaction between sand particles andhydrated cement products, which can explain for thecompressive strength at that age.
Regarding the specimens using HPC, the amountof Ca(OH)2 increased rapidly until 7 days under both
20C and 40C, then it increased slightly in thespecimen under 20C, but it was almost stable in thespecimen under 40C. It is clear that, at 28 days theamount of Ca(OH)2 in the specimens using HPC
under 20C was 14% greater than that in the specimen
using OPC. It implies that cement hydration processin HPC can be 14% larger than that in OPC until 28
days.

Fig. 5 The chemically bound water in the sandloam
mixture.
Fig. 6 shows the amount of Ca(OH)2 in the sandloam mixture. It can be seen that, in both thespecimens using HPC and OPC, the amounts of
Ca(OH)2 at 28 days under 40C were 34% and 13%
lower than those under 20C, respectively. It indicatesthat pozzolanic reaction was accelerated under hightemperature curing. This pozzolanic reaction could
explain for the 10% higher strength achieved under
40C in the specimen using OPC. However, for the
specimen using HPC, under 40C the pozzolanic
reaction could not produce an increase in compressive
strength because of negative effect of hightemperature curing that made strength under thistemperature was lower than that in other cases.

Fig. 6 The amount of Ca(OH)2 in the sandloam
mixture.

Fig. 4 The amount of Ca(OH)2 in the sand mixture.
The chemically bound water of the sandloam
mixture is shown in Fig. 5. For the specimen using
OPC, at 28 days the amount of chemically bound215

GEOMATE - Mie, Japan, Nov. 21-24, 2017

measurement results and curing temperature ofdeep mixing”, pp. 732733, (in Japanese)[4] Kitazume M, Nishimura S, “Influence ofspecimen preparation and curing conditions on
unconfined compression behaviour of cementtreated clay." Proc. of International Symposiumon Deep Mixing and Admixture Stabilization.
2009.
[5] Zhang RJ, Lu YT, Tan TS, Phoon KK, Santoso
AM, “Long-term effect of curing temperatureon the strength behavior of cement-stabilizedclay”, J. of Geotechnical and Geoenvironmental
Engineering, Vol. 140, 2014, pp.1-12[6] Wang D, Zentar R, Abriak NE, “ Tempeartureaccelerated strength development in stabilized
marine soils as road construction materials”, J.
Materials in Civil Engineering, Vol. 29, May
2017, pp. 04016281-13.
[7] Escalante-Garcia JI, Sharp JH, “Themicrostructure and mechanical properties of
blended cements hydrated at various
temperatures”, Cem Conc Res, Vol. 31, 2001,
pp.695–702.
[8] Brooks JJ, Kaisi AF, “Early strength
development of Portland and slag cement
concretes cured at elevated temperature”, ACI
Mater J, Vol. 87, 1990, pp. 503–7.
[9] Kim JK, Han SH, Park SK, “Effect oftemperature and aging on the mechanicalproperties of concrete, part I: experimental
results”, Cem Conc Res, Vol. 32, 2002,
pp.1087–94.
[10] Kim J, Moon Y, Eo S, “Compressive strength
development of concrete with different curing
time and temperature”, Cement and Concrete
Research, Vol. 28, 1998, pp. 1761-1773.
[11] Kim S, Han S, Song Y, “Effect of temperature
and aging on the mechanical properties ofconcrete Part I. Experimental results”, Cement
and concrete Research, Vol. 32, 2002, pp. 10871094.
[12] Ezziane K, Bougara A, Kadri A, Khelafi H,
Kadri E, “Compressive strength of mortar
containing natural pozzolan under various
curing temperature”, Cement and Concrete
Composites, Vol. 29, 2007, pp.587-593.
[13] Alexander KM, Taplin JH, “Concrete strength,
cement hydration and the maturity rule”, Vol. 13,
1962, pp. 277-284.
[14] JIS R5210: 2009 Japanese Industrial Standard
specifies Portland cement.
[15] Mallow, WA. "Low-cost, high early strength,acid-resistant pozzolanic cement." U.S. Patent
No. 5,352,288. 4 Oct. 1994.
[16] NF P18-513 August 2012, Addition forhydraulic concrete - Metakaolin -Specifications
and conformity criteria-Metakaolin, pozzolanic
addition for concrete.

CONCLUSIONSThis study shows the effects of cement types on
strength development of cement-treated soils using
two types of soil cured under the sealed condition at
20C and 40C. The following conclusions could bemade from the experimental results.
1. For the sand mixture, the compressive
strength of the specimens using HPC under
20C was 50% and 42% larger than that of
the specimens using OPC under 20C and40C, respectively. For the sandloam
mixture, the compressive strength of thespecimens using HPC under 20C was 24%
and 12% larger than that of the specimens
using OPC under 20C and 40C,
respectively. But, the results by thermal
analysis did not provide clear evidence for
explaining this unique behavior of HPC.
2. For the specimen using HPC, thecompressive strength under 40C was 15%
and 48% lower than that under 20C for thesand and sandloam, respectively. This may
be caused by the combined effects of hightemperature curing and rapid hydration
process of HPC, which could lead to thedecrease in compressive strength.
3. For the specimen using OPC, thecompressive strength under 40C was 6%
and 10% higher than those under 20C for
the sand and sandloam mixture,
respectively.
Because,underhightemperature curing, cement hydration andpozzolanic reaction could be accelerated.
The findings in this study suggest that we can use
HPC for cement-treated soils to achieve high earlystrength. The detail evidence is needed to investigate
using X-ray diffraction, mercury intrusion
porosimetry, and scan electronic microscopy tests to
explain the higher strength in HPC. In addition, hightemperature curing is recommended to apply for OPC
in order to achieve high strength at early age. This
study will be extended for long curing age (until 1year) and higher temperature as well as various soil
types.
REFERENCES[1] Kongsukprasert L, Tatsuoka F, Takahashi H,“Effects of curing period and stress conditions
on the strength and deformation characteristics
of cement-mixed soil”, Soils Foundations, Vol.
47, 2007, pp. 577–596.
[2] Seng S, Tanaka H, “Properties of cementtreated soils during initial curing stages”, Soils
Foundation, Vol. 51, 2011, pp. 775–784.
[3] Omura T, Murata M, Hirai M, “the influence ofstrength due to hydration heat on site216

GEOMATE - Mie, Japan, Nov. 21-24, 2017[17] JIS A 1216, Methods
compression test of soils.

forunconfined217Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ADDITIONAL BEARING CAPACITY OF PILESDUE TO TIME DELAY OF INJECTION* Abdul Hakam1, M Sofian Asmirza2 and Heka P Andriani1
1Enginering Fac., Andalas University, Indonesia; 2 Engineering Fac., North Sumatra University, Indonesia
ABSTRACTThe use of long piles to support construction loads has been recognized for thousands years. At the lastcentury it has been introduced the use of pressure for embedding pile foundations that is named injected piles.
In field implementations, if the design depth of the piles is long enough then additional piles are required tobe connected. It needs time delay to connect between the earlier embedded pile to the additional one. The
time delay can be also caused by other things such as equipment problems, unwilling bad weather etc. Basedon the experience of pile injection records, due to the time delay there is a temporary increase in pile bearing
capacity, so it takes more effort to continue pile penetrations until the specified length. In this study, theeffects of erection time delays on piles are investigated. This study is conducted using experimental injectedpile models at the laboratory. The initial depth of earlier piles prior to further injection is set the relatively
same, while the time delays are varied. The injection loads for penetration are recorded as well as the depthof penetration. The results of the experiments in terms of variation of time delays and additional penetrationloads show that there are 'jump loads' at the initial last depth due to time delay until a certain period. It can beconcluded that the time delay on the pile can increase the bearing capacity and must be limited to a certain
time in case of pile connection work on site.
Keywords: bearing capacity, injection pile, time delay, pile foundation
INTRODUCTION

Qu = qu Ap

Pile foundations have been used to transfer thebuilding load to the underlying soil layer since theearlier the first century [1]. Based on their loadtransfer mechanism, piles may be classified by
end-bearing and friction piles or combination one.
End-bearing piles develop most of their bearing
capacity mainly at the tip of the pile. Friction piles
transfer the load to the surrounding soil along thepile length by friction between the pile surface andthe soil. Piles also can be differed by the method of
construction that are driven piles (or displacement)
and bore piles (or replacement). The driven pile
may be placed into the ground by displaced
surrounding soil by hammer, injected, vibrated or
screwed. Bored piles are placed into the ground by
replacing soil in bore holes with pile materials. In
this paper the piles may classified as injected endbearing piles.
The pile tip resistance can be calculated basedon a traditional formula using the cohesion andinternal friction angle parameters of the soil. If thesoil at the end of the pile consist of sands only,
then the cohesion parameter can be avoided in thecalculation, so that the end bearing capacity
formula becomes:

(1)

with
qu = q' Nq + 1/2  B Nγ
Where: Qu = ultimate axial loadq' = effective overburden
B = pile tip diameter = unit volume of underneath soil
Nq and Nγ = bearing capacity factors
The effective overburden stress is thedifference between total overburden stress with thepore water pressure. Under static conditions, theeffective stress may be the result of reduction byhydrostatic pressure. The pore water pressure a
dynamic condition may exceed the hydrostaticpressure. The excess pore water pressure in
dynamic condition may generated during the pile
placement into the ground using dynamic way
such as jacking and driving. The effective
overburden then can be written as:
q' = qtot - u
Where qtot = total overburden stressu = excess pore water pressure
218

(2)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

recorded (Fig.2).

Besides static bearing capacity of pilefoundation, there are many problems must be
considered during the design. Some problems thatmight be taken into account in the used of piles arepotential consequences of liquefaction, differential
settlement, lateral loads and movement andpossibility on soil bearing capacity reduction [2].
Pile foundations may not only subjected to static
loads but also dynamic loads simultaneously. The
study on dynamic response of a single concrete
pile in soft clay subjected to static and dynamic
simultaneously has been presented [3]. The
connection between pile to the cap also may beinvestigated to understand its behavior respected tothe applied loads. The investigation of the moment
capacity and load-displacement relationship oflaterally loaded the pile to cap connection withdifferent connection details has been reported [4]On site pile work in order to achieve sufficientbearing capacity at the certain depth, often pileconnection work is needed. The pile to pileconnection thus become a special consideration inpractical works. The required pile to pileconnection in some cases are caused by the
manufacture limitations at the factory and/ortransportation problem of piles from the factory to
the site. Extremely long piles will be difficult to be
distributed from factory to the site. Very long piles
also create difficulties on their mobilization on site.
The pile connection process may need the time
and the driving process must be stopped
temporarily. The most popular pile connection inIndonesia is mainly done by welding to joint thepile ends. Each pile then has the end that made ofsteel which may function as a pad/base for prestressed wire of pile reinforcement. The steel pads
are then to connect the embedded and thesubsequent piles on the site.

Table 1 Properties of the soils
Mechanical Properties
Depth
Type
c

(m)
(Code)
(t/m2) (t/m3)
Sand
4.0-4.4
33.6
1.5
(S)
Silty
29
4.5
1.4
14.-14.5
sand(SM)
Gravelly
35.4
1.9
24-24.5
sand
(SG)
Nspt
0

20

40

60

80

0
5

Sand

depth (m)1015Silty Sand

20
Gravelly Sand25
30

Fig.1 Nspt values on the site

ON FIELD DATA

It can be seen that the first joining work at thedepth of 11m was finished within 16 minutes. The
increment of penetration load after 16 minutes
increased until 339t then came down to 226t for
the next record. It means for 16 minutes delay time,
the load of penetration increased until 113t. The
same thing happened after pile connection work at
the depth of 21m, the penetration load increase by
85t for 14 minutes delay.
There was also a unwilling case due to damage
penetration tools that cause penetration process
was stopped. The repair work by replacement ofbroken spare part took a few days. When thepenetration was continued, the loads have shown
the value that exceeded the maximum capacity ofthe pile injection tool. The depth of the pile at thatpoint has not reached the specified depth. In order

The soil sediment in the field consists of alayer of sand and silty sand until 20m of depth andgravelly sand for deeper. Groundwater in the field
is at depth 2m from the ground surface. This
indicates that the soil beneath the groundwatertable is under saturated condition. The mechanicalproperties of the soil layers are shown in Table 1.
Based on standard penetration test data on site
(Fig.1), the design depth of the 60cm of diameter
piles were about 26 to 30 m.
The spun-piles had been used to support the
Public Work Building in Padang. The piles camefrom the factory have the length of 10m and 12m.
Consequently they were needed pile connection
work to complete penetration every point on site.
During the penetration of piles on site, the applied
loads on every single pile was monitored and219

GEOMATE - Mie, Japan, Nov. 21-24, 2017

to continue penetration, the pile the was pulled
first, the it pushed again into the ground tocontinue penetrating to the specified depth. Thiscase indicates that the dissipated pore waterpressure within a few days may result in an
increase the effective stress in soil mass soconsequently increases the pile bearing capacity.
load (ton)
0

200

400

600

to injecting pile is considered equal to the tip
resistant of the pile only.
The test procedure of piles are started injecting
the pile into the soil to the depth of 25cm. During
the initial injection, the given loads for every unit
length are recorded. The next procedures are
purposed to record the additional load due to thetime interval between the first injection to the next
one. The results of the test procedure are shown in
Table 2 and plotted in Fig.4 as well.

05depth (m)10

16 mnt(113t)

15
20
14mnt
(85t)
25
30

max560t

Fig.2 Penetration load record on site
Fig.3 Dimension of the pile model
LABORATORY TESTSTable 2 Laboratory test results

In order to understand the increment of load
due to the excess pore water pressure during thepile penetration, a series of laboratory test is
conducted. This test is carried out using a small
scale pile model. A pile model has dimension oflength 30 cm and the cone tip with diameter of 1
cm (Fig. 3). The soil is made up of fine sands thatsieved pass trough sieve no 40. The soil is insaturated condition with dry unit volume of 1.53
t/m3 which produces relative density of about
30%. The strength parameter of the sand is
obtained from laboratory direct shear test, that giveinternal friction angle of  = 30 degree. With the
purpose to avoid result differences due to soil
differences, the tests were conducted using thesame soil for every desired time delay.
The pile model is pushed into the soil to havetip resistant. The sleeve of the pile model has
casing that keep staying still during the tests.
Consequently, the skin friction on the pile model
can be ignored in these tests. So, the applied loadDepth (cm)Time interval(mnt)

25.10 25.26 25.44 25.54 25.62
1

10

20

30

60

Increment (kg) 1.02

4.10

6.15

7.17

7.17

0
25

load (kg)01depth (cm)

10
20
30
60
(mnt)

26

Fig.4 Load increment .vs. time220

10

GEOMATE - Mie, Japan, Nov. 21-24, 2017

demonstrating the load increment on penetration
due to time delay. The results of the experimentswith of time delay variation show that theincrement loads will stop until a certain periods. In
practical work, the time delay on the pilepenetration must be limited to a certain time to
avoid difficulty for continuing pile penetration.

From the time-load graph it can be seen thatthe increment load increased with the time delay
and reached the maximum after reach time delay
about 30 minutes (Fig.5). This graph indicated thatthe excess pore pressure due to the pile injection
was fully dissipated after 30 minutes in this test. In
the field, if this delay time may be happened due tothe joining work of piles or other injection
disturbance. In the real work on site, the delay time
may cause the more efforts to continue penetrating
the pile are needed.

ACKNOWLEDGEMENTS
Thanks to our students that have given hands inlaboratory work to complete this study.
REFERENCES

increment (kg)8[1] Tomlinson, M. J. and Woodward J., Pile
design and construction practice, 5th ed. Fifth
Edition, Taylor & Francis, NY, 2008, ch. 1.
[2] Valley M, S.E., “Foundation Analysis andDesign”, FEMA P-751, NEHRP Recommended Provisions: Design Examples, 2009,ch. 5, pp. 48.
[3] Rathod D., Muthukkumaran K. and Sitharam,
T.G., “Dynamic Response Of Single Pile,
Located In Soft Clay Underlay By Sand”,
International Journal of GEOMATE, Oct.,
2016, Vol. 11, Issue 26, pp. 2563-2567[4] Kyle M. Rollins K.M. and Stenlund T.E.,“Laterally Loaded Pile Cap Connections”,
Report No. UT-10.16, Utah Department ofTransportation, August 2010

6
4
2
0
0

10

20
30
40
delay time (mnt)50

60

Fig.5 Delay time-load relationship
CONCLUSIONF Due to the time delay on pile injection on site,
the pile experienced a temporary increase in the
bearing capacity. The effects of time delay on pile
bearing capacity then can be understood by a seriesof laboratory experiments. The experimental work
using pile model on saturated sand has succeeded

221Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

INVESTIGATION ON THE EFFECTS OF PLANT VARIETY AND
SOIL SEDIMENT TO THE COASTAL ABRASION
IN WEST SUMATRA
Abdul Hakam1, * Bambang Istijono 1 and Taufika Ophiyandri1
1
Engineering Faculty, Andalas University, Indonesia.
ABSTRACT
Indonesia has many islands that are suffer from beach abrasion. This phenomenon has been often
happening and it categorized in one of the National Disasters. West Sumatra beaches with the total length ofabout 600 km stretch along the west side of Sumatra Island where directly opposite to the Indian Ocean. The
waves from the Indian Ocean in any circumstance may cause abrasion to damage houses and public facilities.
Factors that effect coastal abrasion include coastal geometry, wave parameters, soil sediment and beachplantations. An investigation on the plant species and soil sediment on the West Sumatra beach has been
done. The effects of the last tow factors on beach abrasion are then elaborated in this paper. It is found thatsome beach vegetations have shown remarkable role to reduce abrasion impact. Meanwhile the type of soil
sediments in which associated to physical properties showed also significant effect. From this study it was
found that vegetation roots will protect the beaches together with the soils. This investigation also concludes
that coastal endemic plants in the West Sumatra need to be explored as a mitigation action to reduce theabrasion impact.
Keywords: Abrasion, Marine Vegetation, Plantation Effect, Soil Effect, Disaster Mitigation
providing an engineering construction to reducethe incoming wave energy [5]. However, building
such wave protector to prevent abrasion could notrestore back the lost of sandy beaches. Further, ahard construction on the beach may also result
unpleasant scenery (Fig.2).
Abrasion becomes a research interest and isextensively studied related to the global warming
issue. It has been studied relationship between sea
levels and coastal damage from the 19th to the20th centuries [6]. It was strong correlation
between the global warming on the damage on
beaches. The damage to the beaches has been
doubled with the rate of actually sea level rise. It is
predicted the coastal abrasion problems that
already look severe in the 20th century will beworse in the next century.

INTRODUCTION
Indonesia is one of the largest countries withmany islands which has very long coastlines. The
Indonesian Geospatial Information Agency
reported that the total length of the Indonesiancoastline reaches about 100,000 kilometers [1].
There are many potential natural treasures andbeautiful sceneries along the coastline. Indonesianbeaches are often used as tourist destination for
local and international tourists. However recent
condition of the coastal areas of Indonesia areworrying due to the abrasion. It has been reported
that about 100 locations in 17 Provinces withcoastline length of approximately 400 km haveexperienced terrible coastal erosion [2]. The list of
coastal areas in Indonesia that are at high risk forabrasion disasters in 2013 including South Aceh,
Banda Aceh, Medan City, Surrounding Padang
City in Sumatra Island, North Jakarta, Rembang
Regency in Java Island, Bali Island, Sikka
Regency in East Nusa Tenggara and Selayar in
Sulawesi Island [3].
Beach abrasion that is essentially a coastal
dynamics influenced by seawater waves hascaused many disadvantages such as cutting theaccesses, destruction of houses and even the lossof such a beautiful sandy beach (Fig.1). For thatreasons the Indonesian government has included
abrasion into one of national disaster [4]. Abrasion
is part of the phenomenon of erosion andsedimentation cycles along the coastline. To deal
with abrasion, beaches can be protected by

Fig.1 Padang Beach in 1890 [7]222GEOMATE - Mie, Japan, Nov. 21-24, 2017

not natural and less beautiful. The more natural
way is by planting protective vegetations on thebeaches. A study to understand the way of thosevegetation roots in protecting beaches fromabrasion using numerical simulation has been
conducted. [11]. The simulations were successfully
demonstrated the mechanism of roots forprotecting the sandy beaches against seawatererosion (Fig.3).
Besides the numerical study, the field
investigation to observe the effect of vegetationand soil sediment to abrasion has also been done.
The field investigations were conducted along theWest Sumatra coastline. The investigation foundthat some kind of marine vegetations canwithstand against abrasion or seawater erosion.
The results of these investigations are further
described in this paper.

Fig.2 The missing sandy beach in Padang
It has been reported there are 14 beaches
classified in critical condition [8]. The 14 criticalbeaches are Air Bangis, Sasak; Pantai Tiku, Pasir
Baru, Pariaman, Ketaping, Pasir Jambak, Padang,
Bungus, Carocok Painan, Luhung, Surantih,
Kambang and Air Haji beaches. From 420 km of
the total length of West Sumatera coastline, 45%of them (approximately 180 km) have beendamaged by abrasion. With the many of needs onthe coastline, the actions are required forprotecting beaches from abrasion in West Sumatra.
Abrasion protection has been done by using
hard structures, but this way is not natural andresulting bad effect to the environment. A study on
the ecological impact to habitat loss due to thepresence of hard protective structures along thecoastline has been conducted [9]. It was found thesurprising drop off the number of seagulls andother seabirds on the protected beach. The study
suggested further studies on natural beachprotection that including the environmental
preservation. The artificial beachrock made ofsand solidification for coastal protection may be aprospects of environmental save solution [10].

WEST SUMATRA'S MARINE PLANTS
There are marine vegetations found from field
investigation along West Sumatra coastline that
empirically can protect beach from abrasion.
Mainly there are five kind of marine vegetations
exist in the West Sumatra Beaches, that are:a. Sea-pine,b. Coconut palm,c. Mangroves,d. Pinago, ande. Ketaping (Terminalia Cattapa).
The on site captures of those trees can be seen in
Fig.4 (a to e). The last two kind of tree seems to bein the same family but different species. However
we do not went deeper in to that kind of biologicalmatter.
The abrasion area will be terminated in thezone where there is a vegetation on it. In areas thatare not planted, seawater took sand away until
several meters into the mainland. Roots are a mostimportant part of vegetation that role the abrasion
protection. The marine vegetation roots can creep
up to 4 meters from the main wood. The maximum
distance of the root extension depends on the soil,
planting way and species. For the vegetation where
its soil sides have been removed by abrasion, it isfound that the roots go only up to about 2.5 meters.
This is caused the roots have lost the soil where
they need to grow for, are destroyed and taken by
the seawater. In order to play as an abrasion
protector, the roots and the soil has to take part insymbiotic mutualism.
There are two main types of roots according to

Fig.3 Simulation of sand-roots interaction
In order to protect beaches from abrasion it isnecessary to prevent the sea waves from taking thebeach sand particles away from their place. It canbe done by constructing wave energy breaker orcovering the ground such that the seawater cannot
transport the sands away. However, those ways are223

GEOMATE - Mie, Japan, Nov. 21-24, 2017

branching pattern as well known: taproot andfibrous root. The taproot is deep-rooted comparedto fibrous one. The marine vegetations that arehaving taproots are Sea-pine, Mangroves, Pinago
and Ketaping, meanwhile Coconut palms growwith the fibrous root. It is believed that the taproot
may anchor the tree better to the soil and can takewater from deeper part from ground surface.
However, the fibrous root is found to be denser
than the taproot system. This condition give an
advantage to the root system to keep thesurrounding soil from being taken by the seawater.
Then, a coconut tree is better in preventing
abrasion than a sea pine tree.

results that the Coconut palms with denser fibrousroot protecting beaches more than the Sea pines
with taproot (Fig.5). Even the field observation
also found the row of coconut palms are also foundsurvive better than the sea pine trees (Fig.6). This
result proves that taproot roots that capable forpenetrating deeper, are not necessarily better toprotect abrasion than fiber roots.

Fig.5 On site condition of Sea pine and Coconut

a. Sea pineb. Coconut palma. Coconut palm beachc. Mangrovesb. Sea pine beachd. Pinagoe. Ketaping

Fig.6 Beaches with marine vegetations

Fig.4 Marine vegetations in West Sumatra

For the same species, the density of vegetation
also determines its resistance to abrasion. The
vegetations that grow close each other will be
more resistant to abrasion than grow in distance.
The closer the spacing, the greater the ability toresist abrasion. Clearly that stand-alone tree will beeasily demolished by the seawater than they in agroup. The same thing happens for plants thatgrow out of line towards the sea, will easily be turn

Based on the study on the mechanism of roots
as abrasion protection [11], it is found that theroots give unification effect to the surrounding soil.
Further they hold each other and form a bigger
mass. The denser roots are the better role inunifying the soil to prevent abrasion. Thisphenomenon explains the field investigation
224

GEOMATE - Mie, Japan, Nov. 21-24, 2017

down by abrasion. Therefore, planting ofvegetations in the purpose of protection against
abrasion should be done in groups with a goodpattern (Fig.7).
The Field investigation also found that
reducing the number of plants in natural growing
mangroves will reduced on abrasion resistance(Fig.8). A group of mangroves that experienced a
reduction in the number, finally in a criticalcondition (Fig.9). Eventually that trees will begone from its original place. So, the density ofmarine vegetation is an important factor to protect
beaches from abrasion. The spacing which isshorter than maximum the root can go, will let theroots cross each other in the form of organic net.
This root net will keep the surrounding soil fromtransported by seawater. While single standing
plants with roots are not interconnected,
consequently easy to be overturned by seawater.

SOIL SEDIMENT OF BEACHES
In order to investigate the effect of soil
sediment for protecting the beach from abrasion,
the soil samples have been taken from the beaches
along West Sumatra coastline. The samples then
are tested in laboratory to elaborate their physicalproperties. Soil properties are very important
engineering as indicator of further engineering
behavior such as gradation, strength and stability.
Many references have described the testingprocedures and the meaning of the engineering
properties of soils [12].
The recent study has mentioned that sedimentswith predominantly non-cohesive materials may beeasily transported by seawater. The factor that cankeep the soils staying are gravity and internal
friction. The coarse grains with greater masses arealso more difficult to be mobilized than fine grains[13].
The sand samples taken and analyzed in thelaboratory came from 7 beaches in West Sumatra
as shown in map Fig.10. The names of eachlocation and the dominant species of vegetation are
as follows:
1. Teluk Batang, vegetation Coconut palm
2. Sago Painan, vegetation type: Sea pine
3. Guguk Kuranji Hilir, vegetation Sea pine
4. Tarusan, vegetation type: Sea pine
5. Surantih, vegetation type: Sea pine
6. Tanjung Mutiara, vegetation type: Sea pine
7. Bukit Buayo, vegetation type: Ketaping

Fig.7 Plants in group and stand alone

The sieve analysis results of the samples areshown in Fig.11. Furthermore, based on the sieve
analysis, the sand soils have a low coefficient of
uniformity (Table 1). This means that the soils arein uniform gradations. In general, the soil typefrom the beaches are sandy soil in medium until
loose density. In Tanjung Mutiara and Tarusan, thesediment is dominated by fine silty sand. Since
those sediments are predominantly non-cohesivematerials, then they may be easily transported byseawater. Since those sediments are predominantly
non-cohesive materials, then they may be easilytransported by seawater.
Based on the findings the sand beaches in West
Sumatra are composed of sediments that easily
eroded by seawater that is confirmed with the field
investigation. The sediments have the relatively
small the size of fine to medium sands that areeasily transported by seawater. In addition, theFig.8 Reduction of mangrove trees for houses

Fig.9 Reduction of mangrove resulting the dead225

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Physical properties of sand samples

gradations of the soils are uniform which indicatesless advantage in terms of stability. It has been
explained that the vegetations together with thesoil can protect the abrasion, therefore the existing
vegetation on the beach must be maintained for the
existence of the beaches in the future.

Parameter
Wet unit volume
Dry unit volume
Void ratio
Saturated water content
Sieve analysis
Mean size
Coef. Uniformity
Coef. Curvature

Location number
4
5
6
7
1
2
3

1.84 1.95 1.86 1.74 1.85 1.46 1.80

1.35 1.48 1.48 1.31 1.42 1.03 1.37e
0.93 0.87 0.61 0.76 0.76 0.76 0.76
w
32.58 31.24 28.14 36.80 32.68 46.77 32.30
Gravel 4.97 0.10 0.00 0.00 0.00 0.00 0.13
Sand 95.00 98.90 99.43 76.93 98.53 65.80 99.30
Clay 0.03 1.00 0.57 23.07 1.47 34.20 0.57
D50 0.7 0.49 0.35 0.21 0.42 0.18 0.31
Cu 4.29 2.89 2.80
2.94
2.11
1.07 0.92 0.77
Cc
0.92
0.71

SymbolCONCLUSIONS
Indonesian government decided that abrasion
has become one of national disasters that resulted
in disadvantage coastline changes. Based on thefield investigation that has been done there areseveral marine vegetations that can grow up in
decades. The field study also found that the marine
vegetations were effectively able to protect
beaches against abrasion. At least there are fivespecies of endemic marine vegetations found along
the West Sumatra coastline.
This study showed that the beach sediments inWest Sumatra are composed of fine to medium
sands that easily eroded by seawater. It has been
explained using finite element that the roots play arole to unify the soil mass that hold each other toprevent abrasion. Therefore, it is necessary toconserve the existing coastal vegetations as well as
planting new specific trees so they will protect thebeaches together with the soils. The absence ofvegetations on the beaches consequently will result
higher vulnerability to abrasion.

SAND
Fine sandCoarse to Medium

GRAVEL

Fig.10 Original sites of the soil samples

100
90
80
60
50
40

% P a ssin g

70

ACKNOWLEDGEMENTS

30

This research is funded by Andalas University
under Research Grant No 68/UN.16.17/ PP.HGB/LPPM/ 2017.

20
10
0
0.01

REFERENCES

0.10 Diameter (mm) 1.00
10.00
1.Tlk. Batang Palm
2.Sago Pine
3.Ggk Krj Hilir Pine
4.Tarusan Pine
5.Surantih Pine
6.Tjg Mutiara Pine
7.Bkt. Buayo Painan Ketaping[1] Badan Informasi Geospatial (BIG), 2013, in:
http://www.bakosurtanal.go.id/berita-surta/
show/pentingnya-informasi-geospasial-untukmenata-laut-indonesia, accessed on 30 April
2017[2] Diposaptono, S., Disaster Mitigation andClimate Change Adaptation (in Indonesia:
Mitigasi Bencana dan Adaptasi Perubahan
Iklim),, Ministry of Marine Affairs andFisheries, Jakarta 2011

Fig.11 Sieve analysis of sand samples

226

Unit
t/m3
t/m3
%
%
%
%
mm

GEOMATE - Mie, Japan, Nov. 21-24, 2017[9] Jenifer E. Dugan, David M. Hubbard, Ivan F.
Rodil, David L. Revell and Stephen Schroeter,“Ecological effects of coastal armoring on
sandy beaches”, Marine Ecology 29, Suppl. 1,
2008, pp. 160–170[10] Khan Md., N. H., Danjo T. and Kawasaki S.,“Artificial Beachrock Formation Through Sand
Solidification Towards The Inhibit of Coastal
Erosion in Bangladesh”. Int.
J.
ofGEOMATE, 9(2), Dec., 2015, pp.1528-1533[11] Hakam, A., Istijono B., Ophiyandri T.,
Darjanto H., Ma'ruf, M.F., “Vegetations as
Beach Protection: Simulations of Root
Protection Mechanism Against Abrasion”. 4th
ICEE, accepted, Padang August 2017[12] Holtz, R. and Kovacs, W., An Introduction to
Geotechnical Engineering, Prentice-Hall, Inc.,
1981[13] Feagin, R. A., Figlus, J., Zinnert, J. C., Sigren,J., Martínez, M. L., Silva, R., & Carter, G..
“Going with The Flow or Against The Grain?
The Promise of Vegetation for Protecting
Beaches, Dunes, and Barrier Islands from
Erosion”, Frontiers in Ecology and theEnvironment, 13(4), 2015, pp. 203-210[3] Hakam, A., Istijono, B., Ismail, FA., Zaidir,
Fauzan, Dalrino and Revalin, Report: Dealwith Coastal Abrasion in Indonesia (inIndonesia: Penanganan Abrasi Pantai diIndonesia), BNPB, Mataram, 2013[4] BNPB, Perka No. 07/2012, Indonesian
Disaster Management Data and Information
Manual (in Indonesia: Pedoman Pengelolaan
Data Dan Informasi Bencana Indonesia),
Jakarta,2012[5] Empung, Hiron N. and Chobir A.,”Oscillating Water Column (OWE) Building
Performance Analysis As Beach Abrasion
Reducing”, IIOABJ Vol. 7, Suppl. 1, 2016, pp.
515–520,[6] Zhang, K., Douglas, B.C. and Leatherman,
S.P., “Global Warming and Coastal Erosion”,
Climatic Change, 64: 41, May 2004,
doi:10.1023/B:CLIM.0000024690.32682.48[7] Ohgituto, Minangkabau Tempo Doeloe #1 Padang, http://ohgituto.blogspot.co.id, 27 Nov.
2012
[8] Balai Wilayah Sungai Sumatera (BWSS) V,
Project Report: Identification of Critical Coastin West Sumatera Province (in Indonesia:
Identifikasi Pantai Kritis di Propinsi Sumatera
Barat), Padang, 2009227

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PRELIMINARY STUDY OF LIFT-OFF TEST AND PERFORMANCEEVALUATION FOR ANCHORS ON FREEWAY SLOPES
1

Sao-Jeng Chao1, Chia-Yun Wei2 and Hong-Da Chou3
Professor, National Ilan University, Taiwan; 2Engineer, National Freeway Bureau, Taiwan; 3Master Student,
National Ilan University, Taiwan
ABSTRACTThe construction of the freeway system has nearly been completed in Taiwan currently, and many freeways
have entered the maintenance stage. Therefore, a series of slope service and maintenance mechanism areestablished for the National Freeway Bureau for the slope anchors. This paper describes the lift-off test briefly
and the performance evaluation of the test results. The purpose of the lift-off test is to obtain the residual tensile
load of the existing anchor. The test process is applying tension force in stages, when the pulling out load isgreater than the residual tensile load, the load-displacement curve would produce a significant turning point,
which is so called the lift-off value. According to the definition proposed by the National Freeway Bureau, theresults of anchor lift-off test can be divided into 5 groups, namely D (normal), C (acceptable), B (poor), A (verypoor), and X (damage). Through the results of anchor ratings, officers and engineers can be immediately
informed of the current conditions of the slope anchors. The results of the lift-off test shows that level D counted
for the overall 42.25%, level C counted for the overall 24.72%, level B counted for the overall 12.17%, level A
counted for the overall 11.04%, and level X counted for the overall 9.83% in this study. It is found that about
67% of the evaluation results of the lift-off tests are in the decent range, but some anchors need to be further
monitored to explore the loss of the pre-stress value as well as the reason. This paper provides clearly anddirectly understanding on the freeway slope anchor for their service performance.
Keywords: Anchor, Lift-off Test, Slope, Freeway
put forward. Planning, designing, constructing,operating and dismantling of engineering project areconsidered as a lifecycle. Most of the publicconstruction is currently entering an important stageof operational management and maintenance, andthe freeway system is not an exception. Therefore,
the establishment of freeway life cycle system, suchas recording slope anchor facilities, monitoring
systems, and slope inspection data, are implanted
under the concept of life cycle at the same time. The
anchor detection of the four major groups, including
anchor head appearance, anchor head assembly,
endoscopic, and lift-off tests, contain all anchor
detection data and performance results.
The results of the inspection data are defined tothe severity of the development of D level (normal),C level (acceptable), B level (poor), A level (verypoor) and X level (damaged). Comprehensive
assessment of the anchor appearance as well as theanchor performance provides recommendations
based on the follow-up review.
Because the mechanical behavior inside theanchor cannot be seen by the appearance of theinspection, lift-off test is the technique to obtain theresidual tensile load of the anchor. When the applied
pull-out load is greater than the anchor actuallyexisting load, anchor head with the bearing plate
provide obvious displacement to assess the residual

INTRODUCTION
The effect of frequent activities between theEurasian plate and the Philippine plate gives birth toa rich and unique terrain condition of Taiwan, which
is located in the southeast of Asia. In the distinctive
natural environment, there are 2,565 slopes along thefreeways, of which there are 1,638 embankment
slopes and 927 cutting slopes. In the case of cutting
slope construction, a large number of anchors areused to stabilize the slopes in Taiwan, so that the
freeway project can be completed smoothly and thesafeties of the car drivers are ensured. The
construction of the freeway has been nearlycompleted and many roads have reached themaintenance stage. In order to improve the quality oftransportation and guarantee the safety of driver, thefreeway bureau has established a series of slope
maintenance mechanisms. The government sets up
three district engineering office in the north, central
and south respectively with a total number of 13
branch stations to perform slope maintenancemanagement. At present, the total number offreeway anchors is 26,802 as shown in Figure 1.
With the help of regular slope inspection, groundanchor detection, and the implementation of themaintenance mechanism, the installation rate of theslope anchors is slowed down year by year.
In recent years, the concept of life cycle has been
228

GEOMATE - Mie, Japan, Nov. 21-24, 2017

tensile loading. The result of the lift-off test is themost direct representation of the current anchor at
this stage, but also the focus of attention from thepoint view of engineers. This paper describes the test
methods and processes of the anchor lift-off test, theclassification of the test results for description
purpose, the results of the test analysis withcomprehensive discussion, to optimize and improvethe management measures for achieving the freeway
slope sustainable management objective.

It is an important part for choosing the suitableanchor to carry out the lift-off test. In order toconfirm the average and randomness of the anchor
samples, it is recommended by the freeway bureau
to adopt the characteristics of the "uniform
distribution selection" of the anchor selection
principle. The main tools of the lift-off test include:
anchor head fixture, jack chair, hydraulic jack, loadcell, displacement gauge, etc. The lift-off test ofanchor is operated according to the process of stage
pull out.
Anchor detection frequency is performed forevery 4 to 5 years. The anchor detection content
includes: anchor head appearance, anchor headassembly, endoscopic, and lift-off test. However, theanchor free-end are filled with cement paste as thesecond grouting, this work makes it impossible toobserve the internal strand by the endoscope
anymore. Therefore, the results of the lift-off test aremuch more significant to show the status of theresidual load, and through the lift-off of the test
displacement-load curve to understand the situationof the anchor in the slope stratum with the serving
time.

14,000/通用格式
quantity of slopes

12,000/通用格式
quantity of ground anchor

quantity of slope

8,000

/通用格式
6,000

/通用格式
4,000
/通用格式

/通用格式

quantity of ground anchor

10,000
/通用格式

2,000

Neihu

Muzha

Zhongli

Guanxi Toucheng Miaoli

Dajia

NantouBaihe

Pingtung0

Fig.1 Total number of cutting slopes and anchors

Lift-off Test Principle

PRINCIPLE AND PROCESS OF ANCHOR
LIFT-OFF TEST

After the anchor was fixed, in general, somefactors will cause the strand and displacementchanges. The main reasons include: the sliding lossof the strand during the fixing, the friction loss of theprotection tube and the strand, strand relaxation,
stratum creep behavior, stratum compaction,
influence of proximity to engineering construction,
temperature change, various impact, as well aschanges in stress state of rock and soil.
There are many possible factors for the loss ofanchor force, it is not very easy to point out andexplain the exact reason. By employing the lift-off
test at the actual site, engineers can obtain thedisplacement-load curve to interpret the residualload data. The principle of the lift-off the test isbased on the existing load (Tr, or the residual load)of the anchor, and the anchor will have obvious
characteristics of displacement to evaluate theexisting load value of the anchor. An lift-off test of
displacement-load curve as an example can be seenin Figure 2 for anchor design load 45T and strand
length 25m (anchor fixed length 8m and free length
17m).
During the test process, the fixtures and clips isused to fix the anchor head first, and then thehydraulic jack is installed in the jack chair so thatthe tensile strand state is set (Figure 4). When thetension of the strand gradually leave out of the), the drawing thepressure plate (Figure 2,
displacement-load curve is plotting at the same time.
With the test moving on, we can find the anchor
appears "lift-off" phenomenon when the curve has aDuring the planning of the slope stability project,
the anchor has an initial design load (Tw). After 4 to
5 years of service period, the anchor is re-pulled tofind the residual load (Tr), and compared with thedesign load. In the progressing of lift-off test, whenanchor has "lift-off" phenomenon, the displacementload curve will present a more obvious turning
situation (Figure 2, point A), which provides thevalue of the anchor residual load. The results of thecurrent test and the results of the previous lift-off
tests can be compared to obtain the differences in theresidual load. The compared result and othermonitoring instruments can be used to assess theoverall safety of the slope.
/通用格式
/通用格式

B

/通用格式
/通用格式

A

/通用格式
load-displacement curve of lift-off test

Load （T）

/通用格式
/通用格式
/通用格式
/通用格式
/通用格式
/通用格式
/通用格式

O

/通用格式
/通用格式 /通用格式 /通用格式 /通用格式 /通用格式 /通用格式 /通用格式 /通用格式 /通用格式 /通用格式
Displacement （mm）

Fig.2 Load-displacement curve of lift-off test
229

GEOMATE - Mie, Japan, Nov. 21-24, 2017

significant turning point (Figure 2, A point). Lift-off
phenomenon of anchor means the strand load iscompletely provided by the hydraulic jack at thistime, there will be another oblique line (Figure 2,) after that. The safety and health of the anchor
can be evaluated comprehensively, according to thelift-off test results obtained from the displacementload curve.

Fixed End

Prestressing Strand

Bearing Plate

Anchor Head

P0
a. P=0, before lift-off

P

P0

P

P0

P

b. P0=P, lift-off

direction of the hydraulic jack to carry out the test in
the direction of the anchor head gradually applied to
the load. Therefore, the appearance of the anchor
head is not much change until P = P0 (Fig. 3-b andFigure 5). While the load of the hydraulic jack isequal to the original existing load of the anchor, theoriginal position of the anchor head happens to leave
the bearing plate by the process of full loading
conversion at this moment. This phenomenon is socalled the anchor head lift-off.
As a final point, after lift-off (turning point)
phenomenon (Figure 3-c), the force behavior of theinternal strand of the anchor is provided entirely by
the hydraulic jack. When the pull out load, thephenomenon has been lift-off, is less than the anchor
design load (Tw), the test load is stop at the 1.1 thedesign load (Tw) and then record the existing load
(Tr). Alternatively, when the pull out load is equal to
1.2 the design load (Tw) but the anchor is still not
lift-off, the test is stopped and the existing load (Tr)is recorded as the same.

c. P0<P, after lift-off

Fig.3 Loading conditions during anchor lift-off test

Fig.5 "Lift-off" of phenomenon for anchor head andbearing plate separation
Fig.4 Lift-off test

Experimental procedure
The implementation of the anchor lift-off test
attempts not to destroy the existing anchor as theprinciple. Carrying out the test is under theconsideration with the principle of selection to therequirements of the "Freeway Maintenance Manual".
It is depending on the slope of the anchor by thestatus of the anchor distribution, with therequirement that at least one per row of each stage
with no more than 15 ones per row; and at least 6
lift-off tests per anchored slope. In addition, theabnormal appearance of the anchor head (such as
corrosion, rust traces, efflorescence, or pre-castanchor beam and ground separation) is selected forthe priority detection object. Nevertheless, if theappearance can be judged as significant damage(such as the strand has been pulled) would not be
tested. The remaining anchors with normal

In the case where the strand are stressed (Fig. 3a), P0 is the original anchor for the existence of theload, which is the anchor of strand pull force so thedirection of the direction to the underground anchor
section. P is applied by the hydraulic jack to pull out
strand for the lift-off test, thus the force direction of
P is opposite. Prior to anchor lift-off test, the strand
only bears the original anchor load and theappearance of the anchor head is totally attached tothe bearing plate.
However, when the lift-off test was progressed(Fig. 3-b), the applied loads of the strand is from two
different directions. One, the original load of theoriginal anchor (P0), due to the initial pre-stressedloading, the steel strand locked to the bearing plate,resulting in the direction of the anchor force for theanchor phase direction. The other force (P) is in the230GEOMATE - Mie, Japan, Nov. 21-24, 2017

appearance are randomly sampling to understand thesituation of the existing anchor loadings.
In the course of the lift-off test, experimental
quality is no doubt the key issue for the residual loadof anchor. The test equipment consist of anchor head
fixture, clip, pull-out rod, hydraulic jack, load cell,and displacement gauge (Figure 4). Among them,
the latter three instruments for the lift-off test needlaboratory correction before entering the test site.
The procedure of lift-off test as follows:
1. Select the anchor to lift-off test according to
the provisions of the maintenance manual or
the contract.
2. Open the galvanized protective cover toremove corrosion and grease, and as
appropriate, to trim the excess strand.
3. To clamp and clip fixed anchor head, and fittedwith support rod and Jack chair.
4. Installation of test equipment, hydraulic jack,load cell and displacement gauge, etc. Pull out
strand and measure the initial anchor headdisplacement as a reference value.
5. According to pull out procedures to start thelift-off test and increase load with the sitting
time for recording test data.

minute. When reaching maximum test load (T), inprinciple, the test load is supposed to maintain 1 to
15 minutes, if necessary, depending on the status of
the situation to extend the sitting time, and record
the creep displacement as well.

The lift-off test is based on the above five steps.
During the test process, one needs to consider thedifferent in-situ problems as well as ground anchor
has been completed for some time, the function may
have some degree of loss, in order to avoid the test
load caused excessive anchor damage and to keep
construction safety concerns. Therefore, themaximum load is set to 1.25 times the design load(Tw) or the anchor head displacement of 20mm inorder to avoid excessive displacement.
If the test result shows that the residual load of
the anchor is smaller than the design load, i.e., when
the anchor head and the bearing plate has been
separated before Tw, it will be the case to insert
some different thickness of the steel sheets between
the anchor head and bearing plate to effectively
increase the anchor force to enhance the anchor
function. The test procedure will then be
decompressed in 5 steps to the residual load (Tr),and the final step is applied load again to the lockedload.
During the process of executing the anchor liftoff test, the load of the internal strand of the anchor
is very large and there is a risk of operation.
Therefore, it is necessary to pay attention to theprocedure of pull out load and the process of pull out
load sitting time. The maximum increasing tensile
force per minute of the test is not greater than 0.1
times the residual load prior to the test tension (T)exceeding the residual load (Tr). After the strand
tensile force exceeds the residual load (Tr), the idea
is taking to 5 steps to reach the maximum test strand,
and the maintenance time of each step is at least 1(▓ normal), C (▓ acceptable), B (▓ poor), A (▓ very

THE GRADING STANDARDS AND TESTRESULTS OF ANCHOR LIFT-OFF
Anchor inspection is an important part ofpreservation and maintenance and also responds theconcept of slope life cycle. Thus establishing a seriesof basic information about the anchor facilities
associated with the slope is essential. However,before the start of the in-situ test procedure, theslope location, geological condition, slope protection
structure and drainage facilities are needed to carryout for the investigation records. The main anchor
information, including design load, panel type,ground anchor length, strand, etc. That is to say, theslope conditions and the anchor initial design must
be thoroughly understood in the beginning.
The lift-off tests are carried out according to theprovisions of the maintenance selection principle by
the freeway bureau. The total number of anchors forthe lift-off test was 1,323 distributed in five levels, Dpoor), and X (▓ damage).
The residual load grading standards is illustrated
in Figure 6. If the residual load is between 0.8 ~ 1.2
design load (0.8 Tw <Tr <1.2 Tw), then rated as D(▓ normal). If the residual load is between 0.5 and
0.8, the design load (0.5 Tw <Tr <0.8 Tw) is rated as
C (▓ acceptable). If the residual load is between 0.2~ 0.5 design load (0.2 Tw <Tr <0.5 Tw), then rated
as B (▓ poor). If the residual load is greater than 1.2
design load or less than 0.2 design load (Tr> 1.2 Tw
or Tr <0.2 Tw), then rated as A (▓ very poor). If
during pull off process of the anchor test, the strand
is broken or damaged, then rated as X level (▓damage).

231

GEOMATE - Mie, Japan, Nov. 21-24, 2017

LIFT-OFF TESTA Very Poor.

D Normal.

.

C Acceptable.

.

B Poor.

.

A Very Poor

9.83%
11.04%

D (normal)

42.25%

12.17%C (acceptable)
B (poor)24.72%.

A (very poor)
X (damage)

X Damage
Fig.7 Pie chart for grading of anchor lift-off test

Fig.6 The lift-off test grading standards
The lift-off test results for anchor on the freeway
slope are comprehensively assessed in this study.
After a detailed statistical data analyzed, it can befound that a total of 1,323 anchors are ranked into 5

CONCLUSION

161 anchors rated as B (▓ poor), accounting as

The construction of the freeway has been almost
completed in Taiwan, and many roads have entered
the maintenance stage. At present, the number ofexisting anchors is 26,802 in total, while the numberof new anchors is slowing down year by year.
Recently, a total number of 1,323 anchors wereconducted the lift-off test. It is found that 559 anchor

12.17%; there are 146 anchors rated as A (▓ verypoor), accounting as 11.04%; finally, there are 130scores were rated D (▓ normal), accounting for42.25% of the total; 327 anchor scores were rated asanchors rated as X (▓ damage or function loss),accounting to the overall as 9.83%. The results canbe presented into the pie chart to show the
proportion of anchor detection project grading
situation.
The total number of anchors of the national
freeway is 26,802 in our database, while the total
number of anchors for lift-off test was 1,323. The
residual load in the 1,323 anchor data is divided by
the original anchor design load, and the percentageof residual load can be obtained and the percentageof residual load can be clearly seen at the present
stage as a pie chart (Figure 7). From the pie chart, it
can be learned that the residual load of the anchors isabout 67% maintained the values of 51~120% of theanchor design load. The residual load of the anchors
is about 12% fell to values of 21~50% of the design
load. The residual load of the anchor is about 11% of
the total number of anchors larger than the design
load of 120% or less than 20%. While about 10% of
the anchors are evaluated as damage. This finding
indicates that the current anchorage does notseriously affect the safety of the slope, but also
shows that the more attention must be paid fornational freeway anchored slopes.

grade C (▓ acceptable), accounting for the overall
24.72%. The percentage number of anchors in the Dlevel and C level (within the design loads of 51% to120%) is about 67% of the number of tested anchors.
This shows that the current anchor performance does
not seriously affect the safety of the slope but extra
attention is recommended.

levels. There are 559 anchors rated as D (▓ normal),accounting as 42.25%; there are 327 anchors rated as
C (▓ acceptable), accounting as 24.72%; there are

REFERENCES[1] National Freeway Technical Code, “Freeway
Maintenance Manual Chapter 5 Slope”, 2013,
National Freeway Bureau.
[2] Liu HS, Preliminary Performance Study ofFreeways Soil Anchor and Numerical
Simulation for the Pre-stress Attenuation, 2014,
Master Thesis, Department of Civil Engineering,
National Ilan University.
[3] Tang TH, Studies of Freeways Soil Anchor
Performance and Appropriate Numerical
Simulation Computer Programs, 2015, Master
Thesis, Department of Civil Engineering,
National Ilan University.
[4] Ye HS, Wei CY, Chao SJ, Wang P, and Tang
TH, “Performance Analysis and Application
Evaluation of Freeway Anchors”, 2016, The232

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Cross-strait Geotechnical Engineering /Geotechnical Technology Exchange Conference,
pp. 173-180.

233

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

INFLUENCE OF LIQUEFACTION ON SOIL-FOUNDATIONSTRUCTURE INTERACTION
Ryohta Takatoku1, Kentaro Uemura1, Barrios Gonzalo3, Naotaka Kikkawa2, Nobutaka Hiraoka2,
Kazuya Itoh1, Naoaki Suemasa1, Nawawi Chouw3, Thomas Larkin3 and Rolando Orense3
1
Urban and Civil Engineering, Tokyo City University, Tokyo, Japan
2
National Institute of Occupational Safety and Health, Japan
3
The University of Auckland, Auckland, New Zealand
ABSTRACT
Liquefaction occurred in filled grounds and embankments in the 2011 Tohoku-Pacific Ocean Earthquake and in
the 2016 Kumamoto earthquake. In New Zealand, medium and small type structures on spread foundations weredamaged by uneven settlement and lateral spreading induced by liquefaction in the 2010-2011 Canterbury
earthquake sequence. Many studies have been done in the past to elucidate such liquefaction phenomena. Amongthem, it is necessary to consider the interaction between structures and ground system for liquefaction damage insmall and medium type buildings. However, there are many unknown points in the dynamic interaction of theliquefiable ground and structures. In this study, geotechnical centrifuge shaking table tests were carried out toinvestigate the liquefaction behavior which changed depending on the weight of structures and the distance
between neighboring structures. For the cases examined in this study, adjacent structures tended to tilt with respect
to each other during liquefaction. In addition, it was confirmed that the inclination of the structures during shaking
was different from that after shaking as the distance between the structures changed.
Keywords: Liquefaction, geotechnical centrifuge shaking table test, soil foundation structure interaction, spreadfoundationnecessary to examine dynamic interaction between
structures and the liquefiable ground since there arestill many unexplained issues.
In this study, four cases of geotechnical centrifuge
shaking table tests were carried out. One was a freefield case and the second has two separated structureswith different weights set on top of the soil. The third
and the fourth cases involved two adjacent structureswith the same and different weights installed. Eachbehavior was investigated and the mechanism ofliquefaction-induced settlement was verified
throughout the tests.

INTRODUCTION
Japan is a nation of earthquakes where manyliquefaction-induced damages have occurred on
ground and structures every several years.
Devastating liquefaction occurred in filled grounds
and embankments in the 2011 Tohoku-Pacific Ocean
Earthquake. In recent years, wooden small houses
were damaged by soil liquefaction in the 2016
Kumamoto earthquake. In New Zealand, small andmedium size buildings on spread foundations weredamaged by uneven settlement and lateral spreading
induced by liquefaction in the 2010-2011 Canterbury
earthquake sequence. Methods to predict suchliquefaction damage include simplified methods,
such as the FL method shown in the Architectural
Basic Design Guidance [1]. However, the assessment
method makes judgment on the liquefaction potentialof the ground itself. According to the review of theliterature conducted on the topic regarding liquefiablesoil and structure interaction, liquefaction is lesslikely to occur in the ground directly under heavy
structures [2] and the behavior after liquefaction
differs depending on the distance between structures[3]. Several liquefaction countermeasure methods
have been actually suggested. For example, Shibata
et al. [4] carried out a large-scale shaking table test toverify the effectiveness of a countermeasure which
utilizes both the shear deformation suppression effectand the confining pressure increment effect. It is

GEOTECHNICALTESTSCENTRIFUGE

MODEL

Studying the phenomenon of soil liquefaction isdifficult due to the fact that earthquake occurs
relatively infrequently and this makes it more difficult
to predict the damage that may be caused by theliquefaction with high accuracy. As an alternative toactual earthquakes, dynamic centrifuge modelling
can be used to study the effects of shaking on soil and,in particular, the failure mechanism involving
liquefaction. In this study, a geotechnical centrifuge
facility was used to investigate the mechanism ofliquefiable soil and structures interactions. All the
tests were conducted on the JNIOSH Mark II
Centrifuge [5] owned by National Institute of234

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1. Scaling factor
Parameter

Model type

Proto type

LengthAcceleration
Times (dynamic)
Times (consolidation)

1/N
N
1/N
1/N2

1
1
1
1

Occupational Safety and Health, Japan (JNIOSH).
Unlike other centrifuges, its arms (forms) areasymmetric, which is one of its special features. One
side of the arm is provided with a bridge plate wherea swinging platform is fixed to its inner end plate withthe help of a pair of hydraulic suspension jacks when
the platform is lifted up (dynamic platform). In orderto balance this portion (weight of the end plate) of the
dynamic side arm while swinging, two counterweights are overhung on the two sides of opposite
arm which is used for non-shaking or static tests(static platform). A model ground was made on ascale of 1/50 and geotechnical centrifuge shaking
table tests were carried out under 50G. The results ofthe experiments were based on the scaling factor
shown in Table 1, which theoretically represents therelation between a prototype and a model [6].

Fig. 1 Outline figure of model ground
Table 3. Property of Toyoura sand
Property

Value

Particle density [g/cm3]

EXPERIMENTAL SETUP

Minimum density [g/cm ]1.343

Maximum density [g/cm3]

1.601

Maximum particle size [mm]0.425

D50 [mm]

0.106

In the experiments, liquefaction behavior was
examined under four conditions; the ground without
any structures (Case 1), two separated structures withdifferent weights (Case 2), two adjacent structureswith the same weight (Case 3) and two adjacentstructures with different weights (Case 4). Fig. 1
shows a layout of Case 2 where structures and sensors
were set in the model ground and Table 2 shows theexperiment conditions, including the distance
between structures and the values converted toprototype scale. A and B in the positional relationshipof the structures shown in Table 2 indicate thelocations of A and B shown in Fig.1. A laminar box
was used for the model container to reduce refraction
waves from side walls as a boundary condition and toreproduce the phenomenon of liquefaction in an
infinite ground. The soil used for the model ground
was air-dried Toyoura sand. The main properties ofthis sand are presented in Table 3.
Table 2. Experiment condition including distance between structures
Dr [%]
Bearing pressure
Sr
Model scale (kPa)[Prototype scale (kPa)]
Loose sand Dense sand
[%]
X
Y
case1
34.0
91.0
95.0
－
－
case2
40.0
73.0
93.0 1.40 [70.0] 2.30 [115]
case3
34.0
86.0
94.0 1.40 [70.0] 1.40 [70.0]
case4
34.0
86.0
97.0 1.40 [70.0] 2.30 [115]

235

2.638

3

Fig. 2 Input waveform
Positioning structure
A

B

Model type (cm)/ [ Proto type (m)]－－8.00 [4.00]
12.0 [6.00]
12.5 [6.25]
3.00 [1.50]
12.5 [6.25]
3.00 [1.50]

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 4. Number and location of sensors
Height from the ground surface
Layer
Model type Proto type
Loose layer
Dense layer

Accelerometer

Pore water pressure
sensorEarth pressure
sensor-2.00cm-1.00m3

3

2-7.00cm-3.50m3

3－-14.0cm-7.00m3

3－-19.5cm-9.75m－3－

Fig. 3 Time history of input acceleration D1 in case1 to case4
The sand was poured from a certain height forconsistent production of uniform deposit with anaverage dry unit weight of 14.04 kN/m3 and 15.47
kN/m3, and corresponding average relative densitiesof 70% and 40%. Initially, a bottom layer was spreadconsisting of gravel 30mm thick, then the second
layer was dense layer (DrD = 65% - 75%) 50mm thick,and the third layer was loose layer (DrL = 30% - 40%)
170mm thick. These layers correspond to prototype
layer thicknesses of 1.5m, 2.5m and 8.5m,
respectively. Sensors were installed directly under the
structures and at the center of the model ground. Nine
accelerometers, nine pore water pressure sensors andtwo earth pressure sensors in total were installed
within the loose layer and three pore water pressure
sensors were placed within the dense layer. The
setting number and the height from the surface to eachsensor are shown in Table 4. Here, the depths fromthe ground surface in prototype scale are: -1.0m, 3.5m, -7.0m, and -9.75m, respectively. In addition,
displacement sensors were installed in the upper partof the model ground to measure the settlement of thesurface ground by liquefaction. Five vertical linear

displacement transducers (LVDT’s) were set at bothedges of the footings and at the middle of the modelin Case 2 to Case 4. After setting the sensors, themodel ground was saturated by slow-fast penetration
with de-aerated silicone oil whose viscosity was 50
times that of water. After completing saturation, themodel container was set on the shaking table on thecentrifuge platform. All instrumentations were set
and centrifugal acceleration was applied up to 50G,
allowing self-weight consolidation of the soil.
Shaking table tests were carried out in which thedissipation of excessive pore water pressure wasconfirmed in a 50G centrifugal field before triggering
the input waves. The applied vibration of the shaking
table is a harmonic sine wave with 50 Hz frequency
in model scale. The maximum amplitudes in model
scale were 115m/s2 for D1, 175m/s2 for D2 and255m/s2 for D3, corresponding to 2.2m/s2, 3.2m/s2and 5.0m/s2, respectively, in prototype scale.
Hereafter, all the results of the centrifuge tests arepresented in terms of prototype scale.

236

GEOMATE - Mie, Japan, Nov. 21-24, 2017

EXPERIMENTALDISCUSSIONRESULTS

Then the amplitude largely decreased from the t=20
seconds in Case 1.
Fig. 4 shows the time histories of the excess porewater pressure when acceleration D1 was the input.
As for the cases where the structures were installed,when calculating the excess pore water pressure
ratios, the effective stresses were adjusted based on
the Boussinesq theory [7]. The excess pore waterpressure ratio in Case 1 quickly reached and thenslightly exceeded the value of 1.0 during strong
shaking. In addition, it is confirmed that theincrement of the excess pore water pressure ratio
became small at the time when the acceleration
decreased, as depicted in Fig. 3. When comparing thethree layers in detail: loose layers with Dr = 30% to
40% at GL-3.50 m, GL-7.00 m, and at dense layer
with Dr = 65% to 75% at GL-9.75 m, it appears thatthe excess pore water pressure ratios at GL-3.50 m inCase 2 to Case 4 in which the structures were installed
were much smaller than that in Case 1. At GL-7.00 m
and GL-9.75 m, on the other hand, those in Case 2 toCase 4 showed similar trends to that in Case 1. It is
likely that the confining pressure increment effect due
to the structure's weight have effect in counteracting
liquefaction occurrence. Moreover, as the depth
becomes deeper, the more the excess pore waterAND

Response of ground motion during liquefaction
Fig. 3 shows the time histories of input acceleration
D1 in Case 1 to Case 4 measured at G.L -1.00m, G.L.
-3.50m, and G.L. -7.00m, respectively. Althoughseveral acceleration sensors malfunctioned at someplaces, all the other sensors in the depth direction
worked normally in CH7, CH10 and CH13 located at
the left side of the laminar box, as described in Fig. 3.
It can be confirmed that while the input waves wereconstant, the accelerations decreased after t=20
seconds in almost all cases. It is assumed that theshear waves became difficult to be transmitted due tothe occurrence of liquefaction. The recorded
acceleration histories sometimes display a few
acceleration spikes around the onset of liquefaction.
Excess pore water pressure ratio

1.6

CH30 case1
CH30 case2
CH30 case3
CH30 case4

1.4
1.2
1

0.8
0.6
0.4
0.2
0

20

30

40

2

50

CH22 case1
CH22 case2
CH22 case3
CH22 case4

1.4
1.2
1

0.8

0.5
0

-0.5 02030

40CH18 case1
CH18 case2
CH18 case3
CH18 case4

1.4
1.2
1

0.8

Right structure case2

0-0.5 0
-1

0.2

1.5
30

40

50

Time(s)6

D1 Input30-3Structual tilt (deg)

-2
2

20

Time (s)

1

0.4

10

10

20

10

20

30

40

40

50

30

40

50

Time (s)10.5
0-0.5 0

10

20

-1
-2

50

Time(sec)

Fig. 4 Time histories of excess pore water pressure

30

Left structure case3
Right structure case3

Left structure case4

-1.5
0

50

0.5

-1.5

0.6

0

40

1.5

50

Structual tilt (deg)Excess pore water pressure ratio

10

Time(s)1.6

Acceleration(m/s2)

30

Left structure case2

-2
2

0.2

-6

20

-1

0.4

0

10

-1.5

0

＋

1

0.6

0

-

1.5

Time(s)

1.6

Excess pore water pressure ratio

10

Structual tilt (deg)0Time (s)Fig. 5 Time histories of structural tilt in case2 to case4237

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(1) Case 1, after shaking(2) Case 2, after shaking(3) Case 3, after shaking(4) Case4, after shaking

Fig. 6 Photographs of ground settlement and structure after experiment

case2

Measureme
nt problem

case1

x (m)

x (m)

case3

Measureme
nt problem

case4

x (m)

x (m)

Fig. 7 Tendency of settlement surface ground and structures
pressures tended to decrease. Especially those in Case
2 to Case 4 were the lowest at GL-3.5 m due to thestructures’ weight.

Structural tilt
Fig. 5 shows the time histories of structural tilt inCases 2 to 4 when acceleration D1 was the input. It isdefined that the tilt to the left is positive and tilt to the238

GEOMATE - Mie, Japan, Nov. 21-24, 2017

right is negative. In Case 4, measurement of the right
structure with heavier weight was not able to be
conducted because of defect of the displacement
sensor (CH41). In Case 2 where two structures were
set separately, it can be seen that the structures wererocked from t=16 to 35 seconds during shaking. Since
structural tilt was seen after shaking, it is consideredthat strength loss within the loose soil layer led topartial bearing capacity failure due to liquefaction
occurrence. On the other hand, in Case 3 where two
adjacent structures were installed, it can be seen thatthe structures tilted at the same time as shaking. Also,
for Case 4 where two structures with different
weights were set adjacent to each other, the structures
tilted during shaking in the same way as in Case 3.
From these results, it was found that the separated
structures tilt after shaking and adjacent structures tilt
during shaking regardless of the structures’ weight.

CONCLUSIONSA series of geotechnical centrifuge shaking table
tests was carried out to investigate the liquefaction
behavior which changes depending on the weight ofthe structure and the distance between neighboring
structures. The main observations which wereclarified by the centrifuge experiment are as follows:(1) The increment of confining pressure due to theweight of structures was effective in preventing
the occurrence of liquefaction.
(2) Adjacent structures tended to tilt with respect toeach other during liquefaction.
(3) It was confirmed that the inclination of thestructures during shaking was different from thatafter shaking as the distance between the
structures changed.
REFFERENCES

Settlements[1] Japan Institute of Construction and Technology:
Basic Structure Design Guidelines, pp. 163-169.
1995.
[2] Hayden, C. P., Zupan, J. D., Bray, J. D.,
Allmond, J. D., & Kutter, B. L.: Centrifuge testof adjacent mat-supported buildings affected byliquefaction, Journal of Geotechnical andGeoenvironmental Engineering, ASCE, 141(3),04014118, 2015.
[3] Yoshida N.: Mechanism of flow accompanying
liquefaction, Symposium on Fluidity andPermanent Deformation of Ground - Soil
Structure during Earthquake, pp. 53 – 70, 1998.
[4] Shibata K.: Development of liquefaction
countermeasures using direct loading on thefoundation, Taisei Construction Technology
Center Report No. 45, pp.1 – 6, 2012.
[5] Horii, N., Itoh, K., Toyowasa, Y., & Tamate S.:
Development of the NIIS Mark-II geotechnicalcentrifuge. In Proc. Int. Conf. on PhysicalModelling in Geotechnics, 141-146. 2006.
[6] Schofield, A. N., & Steedman, R. S.: State- ofthe-art report: Recent developments on dynamic
model testing in geotechnical engineering, Proc.
9th World Conference on Earthquake
Engineering, Vol. 8, pp. 813-824, 1988.
[7] Japanese Geotechnical Society: Introduction to
Geotechnical Equations, Introduction Series 9,
pp.167- 168, 2001.

Fig. 6 shows the photos of the amount of groundsettlement and subsidence of the structures in Case 1
to Case 4 after each shaking event was completed. It
is understood that the structures subsided in all cases,
i.e. from Case 2 to Case 4. Fig. 7 shows the settlement
trend of the ground surface and structures in Case 1
to Case 4. In Case 1 and Case 4, one of plots were
excluded because of malfunctioning of thedisplacement sensor (CH41). First, when looking at
the diagram for Case 1, the amount of verticaldisplacement on one side was large, which may be
due to the influence of the non-uniformity of themodel ground and the direction of excitation. In
addition, a difference was not observed in the amountof settlement despite the increase in input amplitude
D1, D2, and D3. It is likely that this was due to postliquefaction reconsolidation volumetric strains.
Comparing the settlement for D1 of Case 2 and Case4, the settlement of the adjacent structures in Case 4
was larger than that of the separated structures in Case
2. In Case 3 and Case 4, the weights of the structures
were different, however, there was no difference inthe settlement after D1 event. When D2 and D3 wasapplied thereafter, the proportion of verticaldisplacement was large in Case 4. Comparing case 1
and case 2, the amount of settlement of case 1 onwhich the structure is not placed was large. The
confining pressure increment effect due to structure's
weight have effect in counteracting liquefaction
occurrence, as shown in Figure 3 and 4. In otherwords, these results suggest that settlement reduces
for large values of bearing pressure.
From these observations, it was confirmed that the
inclination of the structures and the amount of verticaldisplacement of the ground changed after shaking asa result of changing the weights of the adjacentstructures.

239

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ULTIMATE BEARING CAPACITY OF CLAYEY FOOTING UNDERSQUEEZE BREAKDOWN USING RIGID-PLASTIC FINITE ELEMENTMETHOD
Kazuhiro KANEDA1, Masamichi AOKI2, Tomohiro TANIKAWA3 and Satoru OHTSUKA4
Takenaka corporation, Japan; 4 Department of Civil and Environmental Engineering, Nagaoka Universityof Technology, Japan

1,2,3

ABSTRACTThe relations of ultimate bearing capacity for foundations are specified in the guideline published by theArchitectural Institute of Japan for design of building foundations. The rigid-plastic finite element method
developed by Tamura and Ohtsuka has been employed to estimate the ultimate bearing capacity of footings. The
characteristic of this method is that, in contrast to deformation analysis, it applies limited soil constants; only thestrength parameters, such as cohesion and friction angle, are used since the method deals with the limit state
directly by disregarding the deformation of the building and ground. In this study, a series of rigid plastic finite
element analyses were performed to compare the ultimate bearing capacities of spread foundation for clayeysqueeze breakdown obtained by simulations and the formulae of the Architectural Institute of Japan. The change
in the failure mode of the ground was discussed considering the geometrical ratio between the width of thefooting and the surface layer. In addition, inclined load was considered for clayey squeeze breakdown. The
applicability of rigid plastic FEM to the assessment of ultimate bearing capacity of clayey squeeze breakdown
was demonstrated.
Keywords: Clayey squeeze breakdown, Ultimate bearing capacity, Rigid plastic FEM, Inclined load

as cohesion and friction angle, because it deals withthe limit state directly by disregarding thedeformation of the building and ground. Since
RPFEM uses the upper bound theorem of plastic
theory, it becomes slightly larger than the true value.

INTRODUCTION
The calculation of the ultimate bearing capacityof soil (Terzaghi et al., 1967) is important when
designing a building. The ultimate bearing capacity
formulae for building foundations are specified in
the guideline published by the Architectural Instituteof Japan (AIJ). These formulae were proposed basedon experiments and theoretical considerations
avoiding risk. However, the inclined bearing
capacity was not adequately investigated. In thisresearch, the bearing capacity of spread foundation
with a thin clay layer was analyzed using numericalsimulations. First, the clayey squeeze breakdown
was simulated (Kaneda et al., 2013), andsubsequently, the associated inclined bearing
capacity was discussed. The rigid-plastic finite
element method (FEM), developed by Tamura and
Ohtsuka (T. Tamura et al., 1984 and A. Asaoka and
S. Ohtsuka, 1986), was employed to estimate theultimate bearing capacity of footing. The Drucker–
Prager yield function was adopted as the soil
constitutive equation and the associate and nonassociate flow rules were introduced to establish theconfiguration relationship of the ultimate state.
Using this method, the structural safety assessment
or calculation of soil bearing capacity was evaluated.
The characteristic of this method is that, in contrast
with deformation analysis, it applies limited soil
constants; it only uses the strength parameters, such

SIMULATION OF CLAYEY SQUEEZE
BREAKDOWN WITHOUT INITIAL LOAD
What is clayey squeeze breakdown?
Consider a soft clay upper rigid foundation ofheight H, as shown in figure 1 (H. Yamaguchi,1990). When the foundation width B becomes larger
than the layer height H, the failure mode shifts fromthe general failure mode, specified by Terzaghi(Terzaghi et al., 1967), to that of the squeeze
breakdown, wherein the upper clay layer is pushed
out to both sides in plastic state. The bearing
capacity of squeeze breakdown can be expressed as
the following equation (Meyerhof et al., 1953).
c B(1)
q f  4.14cu  u2Hwhere qf, cu, B, and H are the ultimate bearing
capacity of squeeze breakdown (kN/m2), undrained
strength (kN/m2), foundation width (m), and clay
layer height (m), respectively.
When the relationship between B and H is(2)
B/ H  2
squeeze breakdown occurs.
240

GEOMATE - Mie, Japan, Nov. 21-24, 2017

In addition, with regard to the general failure mode,
AIJ proposed the following equation for ultimate
bearing capacity.
qu  i c  c u N c  i     1  B   N  iq   2  D f  N q (3)where qu is the ultimate bearing capacity (kN/m2),
Nc, Nγ, Nq are the coefficients of bearing capacity,
γ1 is the unit weight of soils (kN/m3), andγ2 is theunit weight of the penetration area (kN/m3). α,βare the shape coefficients, ηis the correction factor
for the foundation size, ix, iγ, iq are the correction
factors of inclined load, and Df is the penetration
length (m).
B

H

B

cu⊿x

y
σx

O

σx＋⊿σx
x

0

H

0 2cu

℄

H ＞B/ 2(b)(a)

Fig. 1

Outline of squeeze breakdown.

Analysis conditions
In this work, the formulation of the rigid-plastic
FEM was omitted; more information can be found in
the references (Tamura et.al.,1984, Asaoka andOtsuka, 1986). Figure 2 shows the numerical mesh,which is 150 m wide and 10 m high in the planecondition. The foundation widths were set as 10, 14,
16, 30, 40, and 50 m. Assuming a rigid foundation,
the strength of foundation was set as cu = 1000000
kN/m2. The soil layer was assumed to behomogeneous type c material. The inclined load
(horizontal load/vertical load (F/V)) was set as 0.1,
0.2, 0.3, 0.4, and 0.5.

clarify the mechanism of tearing; however, it isdifficult to evaluate the extension strength using the
Drucker–Prager yield function and would thus be
future work. In this simulation, it is necessary toconsider the extension strength. Without it, thesqueeze breakdown was simulated well using therigid-plastic FEM. Figure 5 shows the contours of
the shear strain at the point of failure. The general
failure mode occurred at the foundation width of 10m (B/H=1.0), the failure surface touched the bottom
for the foundation width of 16 m (B/H=1.6), thecross-shaped shear surface occurred at 30 m
foundation width (B/H=3.0). For the 40 mfoundation width (B/H=4.0), the cross-shaped shear
surface cannot be seen; squeeze breakdown occurredat both sides of the lower end of the foundation. The
calculation of the bearing capacity of squeeze
breakdown was performed by assuming that the clay
under the foundation was pushed to both sides due tothe application of the upper load. Somewhat
complicated destruction forms can be seen in figures5(e) and (f) that show the occurrence of the fan
shape failure mode and rigid passive mode at 45°.
Although the simulation could not correctly provide
the failure mode shown in figure 4, the other bearing
capacity values and failure modes obtained with thistheory were mostly correct.
Table 1 Comparison oftheoretical value
B/H

Bearingtheoretical
value

Bearing
numerical
analysis value

kN/m2

kN/m2

General failure
mode

-

51.40

Clayeysqueeze
breakdown

1.00
1.40
1.60
3.00
4.00
5.00
6.00

46.40
48.40
49.40
56.40
61.40
66.40
71.40

Analysis results

numerical

52.71
52.53
52.93
58.78
63.91
69.23
74.47

0.88
0.92
0.93
0.96
0.96
0.96
0.96

6

Nc

5
4
3
Analysis
Theory

1
0
0

2

4

6

8

B/H

Fig. 3

Relationship between Nc and B/H.

Foundation wide：10,14,16,30,40,50,60m
Clay layer （c materials）
150m

Analysis mesh.

5.27
5.25
5.29
5.88
6.39
6.92
7.45

7

2

2402
241

and

Numerical
analysis value / N c (Numerical
Theoretical analysis value)
value

8

Vertical bearing capacity
Table 1 shows the results of the simulation using
equation (1). Using equation (2), squeeze breakdown
was applied to the 14 m-wide foundation (B/H=1.4).
Figure 3 shows the relationship between Nc and B/H.
Nc is the value of the result divided by cu = 10
kN/m2. From the simulation results, it can beobserved that when the foundation width ratio (B/H)
is large, Nc is also large for the squeeze breakdown.
Figure 4 shows the pattern of the failure mode
according the foundation width ratio as per
Yamaguchi (Yamaguchi, 1982). The tearing failure
was accompanied by tensile cracks. It is important to

Fig. 2

result10m

GEOMATE - Mie, Japan, Nov. 21-24, 2017

0.10

5.9

6 5.14

0.00

Nc

4
4

(a) B =10.0m

Squeezing

0.10

Compression

2

Tearing
Punch
0
0.23
1

0.00

3.64

(b) B =14.0m

B/H

0.10
0.00

(c) B =16.0m
0.10

Tearing
FailurePunch
FailureFig. 4Compression
Failure0.00

Pattern of failure mode according to thefoundation width ratio.

(d) B =30.0m
0.10

0.10
0.00

0.00

(e) B =40.0m(a) B =10.0m

0.10

0.10
0.00

(f) B =50.0m

0.00

0.10

(b) B =14.0m
0.10

0.00

0.00

Fig. 7(c) B =16.0m(g) B =60.0m
Shear strain contour at F/V=0.1

0.10
0.10

0.00
0.00

(d) B =30.0m(a) B =10.0m

0.10

0.10

0.00
0.00

(e) B =40.0m(b) B =14.0m

0.10

0.10

0.00

0.00

(f) B =50.0m(c) B =16.0m

0.10

0.10

0.00

0.00

(g) B =60.0m
Contours of shear strain at the failure.

Fig. 5(d) B =30.0m
0.10

8
7
6

Nc

5

1

1.4

1.6

3

4

5

60

AIJ

0.00

(e) B =40.0m
0.10
0.00

4

(f) B =50.0m

3

0.10

2
0.00

1
0
0.0

0.1

0.2

0.3

0.4

0.5

and

B/H

Fig. 8

F/V

Fig. 6

Relationship(Analysis).

betweenNc

242(g) B =60.0m
Shear strain contour at F/V=0.3

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Inclined bearing capacity

0

0

0

Simulations were performed for both the verticaland horizontal load. Figure 6 shows the numericalresults of the relationship between Nc and F/V using
AIJ equations; the legend shows the B/H. In the caseof F/V=0, Nc increases as B/H increases. However,in the case of F/V=0.2, the value of each B/H are
almost the same. In the case of a larger F/V, a large
value of B/H corresponds to a small supporting force.
In the AIJ equation (3), the general failure mode wasadopted considering the inclined load as thefollowing; however, the inclined load of the squeeze
breakdown was not described.
2(4)
ic  1   / 90

0
0
0

0

0

Moment (in-phase)00

Load condition
0

0

0

0

Moment (anti-phase)

Figure 9 Initial load conditions for rigid-plastic FEM
Table 2 Analysis conditions

where θis the inclination angle (°).
For F/V˃0.2, the numerical results are nearly equal
to those obtained by equation (4). It is therefore
indicated that the general failure mode occurred
instead of squeeze breakdown. Figures 7 and 8
show the contours of shear strain at the failure point
for each foundation width. At large F/V, a large
value of B/H is not obtained at the squeeze
breakdown because the failure area becomes shallow.
However, when both B/H and F/V are large, thefailure slip is restricted to the bottom. Therefore, it
was considered that the opposite condition occurred,
which entails that the bearing capacity associatedwith a large B/H is smaller than that with small B/H.
In earthquake architectural design, the value of
F/V˃0.2. When detailed bearing capacity analysis is
not performed for the case of a large B/H, it isconsidered better to use the bearing capacity valueof the general failure mode obtained by equation (3)for safety.

Numerical results
Figure 10 shows the results of the simulation. As
with the inclination load consideration, the value of
Nc decreased as F/V increased. The values obtainedby numerical analysis were larger than those by AIJ.
Figure 11 shows the contours of the shear strain at
failure at B=10 m, Kh=0.2, H=1B and B=60 m,
Kh=0.2, H=0.15B. For the first condition, each Nc
was almost the same. Similar to the shear strain
distribution, there are differences in the occurrenceof shear faces on the left and right, but general
failure mode occurs. In contrast, for the second
condition, the value of anti-phase is larger than thatfor in phase. It is considered that the anti-phasemode is closer to the squeezing breakdown along
only the vertical direction. In fact, when assuming alarge earthquake, the assumed horizontal force andmoment do not change, and the margin of thevertical support force is important. Because thevalue obtained by the analysis is larger than thevalue of AIJ including the examination of theprevious inclined load, it can be said that the design
specification of the AIJ entails lesser risk.

SIMULATION OF CLAYEY SQUEEZE
BREAKDOWN WITH INITIAL LOAD
Analysis conditions
In order to consider the load during an earthquake,the initial vertical load V0, horizontal load H0, andmoment M0 were introduced as shown in figure 9.
Both in-phase and anti-phase moments against theearthquake direction were considered. The ultimate
vertical bearing capacity was calculated using rigidplastic FEM under the initial load conditions listed
in table 2. The unit weight of the building (3.3stories, 10 kN/m2 per floor) was assumed as γ=3
kN/m3. Three cases with different spread widths (10m, 30 m, 60 m) and two cases with different heights(1, 1.5 times high were considered. The horizontal
force and moment were assumed to be applied at the
midpoint of building height. The inclined load wasapplied to the foundation as the distribution load
divided into horizontal and vertical components.
“Kh” refers to the horizontal seismic intensity.

in-phase

6

anti-phase

AIJ

0.15

0.2

5

Nc

4
3
2
1

0
0

B=10 m, H=1B
243

0.05

0.1
F/V

GEOMATE - Mie, Japan, Nov. 21-24, 2017

in-phase

7

anti-phase

AIJ

in-phase

8

anti-phase

AIJ

0.15

0.2

7

6

6

5

5
Nc

Nc

4

3

4

3

2

2

1

1

0

0
0

0.05

0.1
F/V

0.15

0

0.2

in-phaseanti-phase

0.1
F/V

B=60 m, H=0.25B
Figure 10 Relationship between Nc and F/H for in
and anti-phase

B=30 m , H=0.3B
7

0.05

AIJ

0.30

6

0.00

5

In-phase
4

Nc

0.30
0.00

3

Anti-phase
B=10m, Kh=0.2, H=1B

2

0.065

1

0.00

0
0

0.05

0.1
F/V

0.15

In-phase

0.2

0.065

B=30 m, H=0.5B

0.00

Anti-phase
B=60, Kh=0.2, H=0.15B
Figure 11 Contours of shear strain at the failure
CONCLUSION
The vertical failure mode changes from thegeneral failure mode to squeezing breakdown withincreasing B/H. At B/H=3, the cross-shaped failuremode occurred at the ground under foundation.
Shearing blocks occurred at both ends of thefoundation. For B/H˃4, the cross-shaped failuremode cannot be seen and shear failure occurred fromboth sides of the foundation.
In the failure mode with inclined load, at small
F/V, the failure mode differed depending on the B/H.
For B/V˃0.2, the failure mode remained the same
regardless of B/H. From the results of numericalanalysis, it is considered that it is necessary toconsider the corrective inclined coefficient for thegeneral failure mode.
In the vertical failure mode with initial load,considering an earthquake, the Nc values were larger
than those obtained by the AIJ equation. This further

B=60 m, H=0.15B

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

implies that it is necessary to consider the corrective
inclined coefficient for the general failure mode.
REFERENCES[1] Terzaghi, K. and Peck, R.B.：Soil Mechanics
in Engineering Practice, John Wiley & Sons, pp.
472-569. 1996.
[2] Tamura, T., Kobayashi, S., and Sumi,
T.：”Limit analysis of soil structure by rigid
plastic finite element method”, Soils andFoundations, Vol.24, No.1, pp.34-42.1984.
[3] Asaoka, A. and Ohtsuka, S.：”The analysis of
failure of a normally consolidated clay
foundation under embankment loading”, Soils
and Foundations, Vol.26, No.2, pp.47-59. 1986.
[4] Yamaguchi, H. ： Theory and applications ofbearing capacity and deformation of shallow
foundation, Soil Japanese Society of Soil
Mechanics and Foundation Engineering，No.2,
pp.85-91, 1982. (In Japanese)[5] Architectural
InstituteofJapan,
AIJ(1988,20011), Recommendations for design ofbuilding foundation , pp.105-111, 2001. (InJapanese)[6] Kaneda, K., Tanikawa, T., Hamada, J., Ohtsuka,S., and Aoki, M. : “Analysis of ultimate bearing
capacity of footing of two layered clayey soil
system by rigid plastic finite element method”,
AIJ Journal of technology and design, Vol.19,
No.43, pp 881-885. (In Japanese)[7] Meyerhof, G.G. and Chaplin, T.K., : “Thecompression and bearing capacity of cohesive
layers”, British Journal of Applied Physics,
Vol.4, No.1. 1953.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

CORRELATION AMONG THE SOIL PARAMETERS OF THE
KARNAPHULI RIVER TUNNEL PROJECT
Khondoker Istiak Ahmad, Masnun Abrar, Hossain Md. Shahin, Sultan Al Shafian and Soumik Nafis Sadeek
Islamic University Technology, Bangladesh

ABSTRACTDefining correlation among the soil parameters and strength properties has become a popular research topic
among the soil mechanics researchers in recent years. As conducting laboratory test are quite tiresome and time
consuming, investigating correlation among the soil parameters using collected data will help to understand thecharacteristics of soil effortlessly. This research aims at stating a correlation analysis between the strengthparameters and index properties of the soils of Karnaphuli river tunnel project site . Around 120 borings were done
to determine both the index and strength properties of the soil in the laboratories. Along with the correlation,
multiple linear regression analysis was developed for the cohesion and liquid limit along with the collected
explanatory variables. This equation supports to adopt different characteristics of the soils of Karnaphuli River,and additionally a statistical significance of correlation among different soil parameters have also been unfolded.
Finally the equation is compared with some of commonly used classical soil mechanics equation to determine theacceptability of this correlation.
Keywords: Index Properties, Strength Parameters, Regression Analysis, Correlation.

INTRODUCTIONSTUDY AREA

Determining strength parameters and index
properties of a soil sample is a time consuming
process. By knowing the strength parameters (e.gshear strength) will help to determine soil
characteristics and to be useful for designing future
underground structures. Researchers have tried longfor stating correlation between strength parameters
and index properties of soil. Smith et al. [1]established a correlation among the index properties
and other parameters of soil in Israel. Correlation
analysis for rock and other marine soils have been
established many time by the researchers. But in thedeveloping countries like Bangladesh where soils arecharacterized as soft soil in a bulk, there are little
attempts have been made on correlation analysis. As
fas as Authors’ knowledge none of the studies haveconducted correlation analysis among different
parameters of soil in context of Bangladesh.

The soil samples studied for this project have beencollected from the Karnaphuli River tunnel Project
Site of Chittagong, the first ever underwater tunnel
project going to be constructed in Bangladesh. This
Multi-lane Road Tunnel project site is located at thesea entrance of River Karnaphuli of Chittagong
suburb, and its west coast starting point is connectedwith Coastal Road.

This study aims at establishing a correlation between
the strength parameters and other index properties ofthe soft soil of Karnaphuli River tunnel project.
Around one hundrerd and twenty (120) bore holesamples have been collected for testing anddetermining various strength and index properties ofthe soil. Considering depth and other geotechnicalproperties of soil, first a multivariate statisticalanalysis i.e. Multiple linear regression is establishedwhich comprises the statistical significant variables
and then a correlation analysis is established among
the soil parameters with proper statistical techniques.

Fig. 1 Location of the Karnaphuli River Tunnel
Project Site [2]Soil samples have been collected from various
parts of this project site. The depth of common
boreholes is 20 m under the tunnel design bottom
surface, while for controlling boreholes, they should
be 40 m under the design bottom surface or 5 m into
the complete bedrock at least. The number of246

GEOMATE - Mie, Japan, Nov. 21-24, 2017controlling boreholes account for 2/5 of the total
number of boreholes.[2]Table 1 represents the summary results of thestatistical model for two dependent variables (Liquid
limit and Cohesion). The model is developed in ‘R’ an open source statistical software.

METHODOLOGY
Multiple Linear Regression (MLR) has been used toestablish a multivariate equation with statisticalsignificant explanatory variables. MLR has been
preferred by many other researchers for establishingsuitable relationships among various parameters ofboth rocks and soils. [3]To measure goodness of fit of the model, squared R
is taken to show how close the data are to the fitted
regression line. Squared R assumes that every
predictor in the model explains the variation in the
response variable. It gives the percentage of
explained variation as if all predictors in the model
affect the response variable, whereas the adjusted Rsquared gives the percentage of variation explainedby only those independent variables or predictor thatin reality affect the response variables. To measure
the model overall significance F-statistics value
tested and evaluated. It can assess multiple
coefficients simultaneously.

Multiple Linear Regression
The most widely used regression model to analyze adependent variable on the basis of change in morethan one independent variables is the Multiple linear
regression (MLR) model which is given by

𝑦 = 𝑿𝜷 + ɛ(1)Correlationin Eq. (1) ,where, ‘y’ is the dependent or response
variable, ‘X’ is the vector of explanatory variables;′𝜷′ is a vector of parameters to be estimated and ′ɛ′ isan error term. In this research, an effort has been
made to create a relationship among different
geotechnical parameters with cohesion and liquid
limit. Around 15 variables are selected to formulate
this model. In statistics it is very common to conduct
hypothesis test to find the statistical significant
variables and put it into the model. For this reason, ttest was applied with 5% significance level whichmeans, if the p-value of any variable is less than 0.05,
than the null hypothesis will be rejected [4]Correlation describes the degree of relationshipbetween two variables. Product moment correlation
efficient (r) can be measured to identify thecorrelation among different important geotechnicalparameters. The equation is [4]:𝒓=𝑺𝒙𝒚√𝑺𝒙𝒙 𝑺𝒚𝒚(2)

where,
𝑺𝒙𝒚 = (∑ 𝒙𝒚) − 𝒏𝒙𝒂𝒗𝒈 𝒚𝒂𝒗𝒈

Table 1
Summary of the Multiple linear
regression (Only statistical significant variables areincluded)

𝑺𝒙𝒙 = (∑ 𝒙𝟐 ) − 𝒏𝒙𝟐𝒂𝒗𝒈
𝑺𝒚𝒚 = (∑ 𝒚𝟐 ) − 𝒏𝒚𝟐𝒂𝒗𝒈

Variables
StressVoid ratio*N
Dry density
Liquid limit
Total
Observation
R2
Adjusted R2
F-statistics

Liquid Limit
0.0091 (<0.001)
120.55 (<0.001)
102.16 (0.03)
102.16 (0.03)-

Cohesion
0.61 (<0.001)
97.37 (0.02)-16.19 (0.017)

75

75

66%
64%
33.33

65%
63%
41.54

It is also tested whether the correlation between two
variables are statistical significant or not. So, ahypothesis test is introduced with 5% significancelevel following two tailed test. Table 3.2 shows thecorrelation matrix among different independent
variables [5]Table 2 represents the correlation values of thesample data that has been used for establishing thecorrelation among the soil parameter*N = Natural mass density(All the parameters are of 95% of confidence interval,in bracket p-values are given)

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Table 2 Correlation matrix of independent variables
ϭ

W

N

e

LL

PL

ϭ

1

W
N
e
LL
PL
PI

-0.54*

1

0.62*-0.64*

1-0.61*

0.93*-0.86*

1

0.13

0.56*

-0.21

.5

1

0.14

0.54*

-0.20

0.49

0.99

1

0.11

0.57*

-0.21

0.50

0.99

0.98

From table 2, we can observe that the best positive
relationships exist between liquid limit – plastic limit,
liquid limit-plasticity index, plastic limit-plasticity
index and void ratio-water content for obvious
reasons as there are theoretical relationships among
these parameters. Marginal positive degree ofrelationship exists between natural mass densitystress, liquid limit-water content, plastic limit-watercontent, plastic limit-water content, void ratio withplastic limit and liquid limit. There are exists some
negative correlation among variables that means if
one parameter increases in a specific unit others will
decreases and vice-versa. There are some statisticalinsignificant variables i.e. they do belong to the null
hypothesis, cannot be rejected.

PI1(* represents statistical significant with 5% significancelevel)In the following Table 2, the abbreviations of the shortterms are :CONCLUSION

Ϭ = Stress
W= Water Content
N= Natural mass density
e= Void ratio
LL = Liquid limit
PL= Plastic limit
PI =Plasticity index

The relation that has been established among thesoil parameters is completely based on statistical
approach which will be very much helpful for
determining the proper characteristics of the soils of
Karnaphuli River Tunnel project in future.

REFERENCESRESULTS AND DISCUSSION[1] Smith, C.W., Hadas, A., Dan, J. andKoyumdjisky, H., 1985, “Shrinkage andAtterberg limits in relation to other properties ofprincipal soil types in Israel’’ ,Geoderma, 35:4765.
[2] China Communications Second Highway Survey,
Design and Research Institute Co. Ltd.,‘‘Detailed Investigation Report of Engineering
Geology-Multi lane Road Tunnel Under River
Karnaphuli Chittagong Bangladesh’’, Volume I
and II ,October 2016[3] Mishra, D.A., Basu, A., “Estimation of uniaxial
compressive strength of rock materials by index
tests using regression analysis and fuzzy
inference system”, Engineering Geology, Vol.
160, 2013, pp. 54-68[4] Montgomery, D.C., Peck, E.A., Vining, G.G.
(2012). Introduction to Linear Regression
Analysis (Fifth Edition), John Wiley and Sons
Ltd[5] Kottegoda, N.T., Rosso, R. (2008). Applied
Statistics for Civil and Environmental Engineers(Second Edition), Blackwell Publishing, John
Wiley and Sons Ltd

Using proper regression analysis, following two
equations has been derived.

Cohesion= -158.01 - 16.19(LL)+ 0.61(Ϭ)+ 97.37(N)(3)
LL= -296.82 + 0.0091(Ϭ) + 120.55 (e) + 38.33 (N) +102.16 (Dry density)(4)

In Eq 3 for one unit increase in LL, the cohesion will
decrease by 16.19 unit. For one unit increase of stress,
the cohesion will increase by 0.61 unit .For one unit
increase in natural mass density, cohesion will
increase by 97.37 unit.

In Eq 4, for one unit increase in stress liquid limit will
increase by 0.0091 unit. For one unit increase in void
ratio the liquid limit will increase by 120.55 unit. For
one unit increase in natural mass density, liquid limit
will increase by 38.33 unit. and lastly for one unit
increase in dry density, the liquid limit will increaseby 102.16 unit.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A STUDY ON COMPRESSION AND SOLIDIFICATIONCHARACTERISTICS OF VOLCANIC SAND
Katsuhiro Shibano1, Naoaki Suemasa1, Kazuya Itoh1, Tsuyoshi Tanaka1, Hiroto Akimoto1
Yoshitaka Yanagihara2, Yuan Zhang2, Kiyoshi Numakami2, Yasushi Furugaichi2
Katsuya Suzuki3, Shun Habara3
1
Urban and Civil Engineering, Tokyo City University, Tokyo, Japan
2
Tokyu Construction CO., LTD., Tokyo, Japan
3
Nitto Seimo CO., LTD., Hiroshima, Japan

ABSTRACTIn Japan called ‘Nation of volcanoes’, the majority of the land is mountain area and the volcanic activity is
still frequent. It is feared that huge amount of eruptive deposits such as volcanic ash could be generated andaccordingly serious damage could be caused especially when some of the active volcanos erupts. At present, oneof the eruptive deposits, Shirasu has been already variously used as concrete aggregate or road materials. In
order to utilize other volcanic sands, however, sufficient investigation has not yet been conducted about thecharacteristics of eruptive deposits including the base material and the influence of both formation process andsedimentary environment. In this research, an attempt is made to use effectively volcanic ash as a new
construction material. If volcanic ash can be compressed and formed in a block body, it can be used in various
ways instead of being disposed of as a waste. One-dimensional compression tests were carried out using several
kinds of volcanic ashes and the solidification states and the e-log p curves were investigated and compared. In
addition, the fragment states of particles of the samples were confirmed after compression to verify the
relationship between particle crushing and solidification.
Keywords: Frangible Sand, Volcanic Ash, One-Dimensional Compression, Solidification

INTRODUCTION
In 2003, Meteorological Agency of Japandefined 110 mountains in Japan as active volcanos
which have erupted within the past 10,000 years or
showed signs of unrest such as significant new gas
emissions. Volcanic ash which consists of fineparticles of pulverized volcanic rocks is created as
eruptive deposit when volcano erupts and hightemperature rocks slide on the hillside of volcano.
The appearance of volcanic ashes varies according
to ways of eruption or types of volcano, where thecolor ranges from bright gray to black and the size
ranges from almost the same as talc to a pebble. It isseen that thunder or lightning occurs because ofcollisions between floating small volcanic ash
during volcano eruption. Fine volcanic ash spreads
on the lee side with smoke and makes serious
damage in the around areas.

blocks and roadbed. Due to its advantages such as
durability, water retention and sound absorption, it isexpected to replace asphalt or has potential to be
used to reduce temperature rise of road surface [1].
It has been pointed out that sand particle crushingoccasionally causes the specific behaviors ofstructure on sand such as unexpected large
settlement of piles [2]. Such particle crush is
continual to occur in volcanic soils even in low
stress [3]. And also, it is revealed that interlocking
effect caused by the particle crushing may develop
cohesion of crushed sand although its effectdecreases as the applied stress increases [4].
Therefore, if the particle crushing occurs excessively,
it is thought that the interlocking effect may weaken.
It means that if volcanic ashes are utilized asengineering materials such as Shirasu, it is necessary
to grasp their compression and solidification
properties.

In general, volcanic ash is disposed as waste
because it has difficulty in reuse. At present, one of
the eruptive deposits, Shirasu has been alreadyvariously used as concrete aggregate or a roadmaterial. The major characteristics of Shirasu arelight but fragile in water. In addition, mixed withreinforcing materials to make up for its fragile
property, Shirasu has been used for lightweight hard

In this paper, in order to examine thecharacteristics of several kinds of volcanic ashes,
one-dimensional compression tests were carried out
to investigate the relationship between particle
crushing and solidification. The solidification stateof the particles and the extent of particle crushingwere evaluated from the result of one-dimensional
compression test.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table. 1. Sample Characteristics
Caracteristics
Sanple Name

Collection Place

Soil Particle Density(g/cm3)Cohesion(kPa)

Intenal Friction Angle(°）

Hard Kanuma

Tochigi

2.373

15.74524.313

Shirasu

Miyazaki

2.414

3.223

43.672

KanumaTochigi

2.601

19.78121.727

Fukushima Volcanic Soil

Fukushima

2.688

19.96536.859PumiceKagoshima

2.489

22.28933.465

Lapilli

Akita Lake Towada

2.764

19.69936.163

SAMPLE CHARACTERISTICS
The samples used in this study were as follows:
Hard Kanuma Soil, Shirasu, Kanuma Soil,
Fukushima Volcanic Soil, Pumice and Towada
Lapilli. All samples were dried sufficiently in adrying kiln until their moisture content became lessthan 1%. Density soil particle tests, box shear tests
and grain size analysis were carried out to measure
the characteristics of each sample.The characteristics
and the grain size distributions are shown in Table. 1
and Fig. 1, respectively. Shirasu and Pumice mainlycomposed of silicon dioxide include numerous
aluminum oxide and iron oxide as well. Photo. 1 and2 describe their state observed by an electron
microscope. It can be confirmed that both havevitreous and indeterminately squared shapes.

Fig. 1. Grain size distributions

ONE-DIMENSIONAL COMMPRESSION TEST
Compression molding was conducted using acompression tester until the pressure reached 10MPa
in a constant strain of 1%/min. Each sample was set
into a solidification test apparatus so that its heightbecame 5mm after compression. The e-log p curves
obtained from the tests were shown in Fig. 2.
Solidification by compaction molding of the sample
was confirmed in Hard Kanuma, Kanuma and
Pumice, although the other samples were fragile
enough to crumble with a few shocks. In this paper,
therefore, solidification was defined as a conditionof self-sustaining without collapsing even if it islifted up by a hand. As the characteristics of thesamples in which solidification was able to be
confirmed, the void ratio was large at its initial andgreatly decreased beyond its yield point, at whichstress the maximum curvature occurs in the e–logp
plot. Since it is reported that particle crushing begins
at its yield point when void ratio greatly decreases,
the appearance of this yield point seems to be related
to solidification of particle [5]. As for the samples in

Photo. 1. State observation by the electron
microscope: Shirasu

Photo. 2. State observation by the electron
microscope: Pumice250

GEOMATE - Mie, Japan, Nov. 21-24, 2017

which solidification could not be confirmed, theinitial void ratios were small and the yield points
were unclear.
However, since initial void ratios vary according
to the grain size distribution and the method ofpacking, it is difficult to use the initial void ratio as
an indicator for the degree of solidification.
Therefore, experiments were performed to grasp the
degree of solidification with the decrease in void
ratio from yield point. In the experiments, using thepumice in which solidification could be confirmed,
applied compression pressure was changed stepwise
from 1 to 15 kPa and the solidification state wasobserved in each step. The curves of e-log p aredescribed in Fig. 3. As seen in the cases of morethan 5 kPa of applied pressure in Fig. 3, the void
ratios greatly decrease beyond the yield point. On
the other hand, in the cases of 1 and 3 kPa ofpressure, the void ratios didn’t decrease too muchand the samples easily crumbled. From the above, itis thought that the solidification of sample is attainedby the compression with larger pressure than theyield stress.

Fig. 2. e-log p relationships for the sample used

Another series of the one-dimensional
compression tests was performed using compression
testing equipment which can provide a higher
compression pressure than the compression tester
used before. And as the solidification test apparatus
used was not able to endure such high pressure, acompression container was used as shown in Photo.
3. As this testing machine is not suitable for setting
constant-speed or detailed loading speeds, loading
speed for these tests was roughly set at around
10%/min of specimen height. The sample ofKanuma Soil was excluded in this high-pressure test
because of its large compressibility. The appliedcompression pressure was changed stepwise at 20,
4 0 , 6 0 , 80 and 1 00 MPa , and the state o fsolidification were confirmed at each pressure step.
As the result of compression tests, the solidification
was able to be observed in the specimens of Shirasu
at more than 40 MPa. As for Towada Lapilli,
although the solidification point was not able to be
confirmed since the compression pressures were notapplied in steps, solidification was able to be
confirmed in the sample compressed to 100 MPa.
The tendencies of decreasing void ratio were similar
for most of samples, which show the decrease in areverse S shape curve. It is thought that the particles
were crushed with increase in compression stressFig. 3. e-log p relationships for Pumicebeyond the yield stress and particles had beeninterlocked with each other according as the void
ratio decreased and solidified.
It focusses on the three inflection points in the elog p curve obtained by the one-dimensional
compression test. The pressure at which the void
ratio in the e-log p curve begins to decrease sharply
is named p1, the pressure at which the inclination
becomes the maximum is defined as p2, and thepressure at which the decrease in the void ratio
converges and the inclination does not change iscalled p3. For Shirasu, p1 and p2 are 1.5 MPa, 15MPa, respectively, and p3 cannot be determined yet,but assumed to be 100 MPa. For Pumice, p1, p2 andp3 are 0.2 MPa, 2 MPa and60 MPa, respectively.
From these results, it is considered that solidificationof sample was confirmed at a compression pressureof 60 MPa or more. It is thought that particle
crushing was accelerated by high pressure even in
the case of the sample in which particle crushing
was hard to occur and fine particles engaged eachother and caused solidification.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Photo. 3. Compression container

Fig. 4. Grain size accumulation curves of Shirasu

CRUSH EVALUATION FOR SAMPLE
In order to confirm the extent of compressed andcrushed particles by one-dimensional compression
tests, grain size analysis was conducted. The
appearance of crushed particles was observed with adigital microscope (VHX-6000). Particles crush
evaluation for the sample was carried out throughthese two results. The grain size accumulation
curves of Shirasu and Pumice which werecompressed stepwise describe in Fig. 4 and 5. The
grain size distributions of Shirasu and Pumice whichwere compressed stepwise describe in Fig. 6 and 7.
It is understood that the larger compression pressure
was added, the more Shirasu particles were crushed.
Especially, particles around 300μm were crushed
into particles of less than 30μm. Compression of 100
MPa produced less crushing than that of 80 MPa. It
was also found that by the increase in compression
pressure, pumice particles of around 100 μm werecrushed into 20 μm or less. Here, particle-crushingoccurred at 40 MPa the most, which is thought to be
due to dispersion of particles. For Towada Lapilli,
particles of 100 μm or more were crushed into
smaller particles. The conspicuous crush of theparticles was able to be confirmed in all samples andit was accordingly confirmed that high pressurecompression was effective for crushing.
In order to show the relationship between
particle crushing and solidification, crushing ofparticles has been numerically evaluated and various
indexes have been proposed according to changes ofparticle sizes before and after the crush [6]. Amongthese indexes proposed, it is said that the reduction
ratio of 15% diameter (D15 '/ D15) obtained fromgrain size accumulation curves is effective as anindicator of particle fragmentation [6]. In this paper,
therefore, the comparison of 15% diameter reduction
rate and the evaluation of particle crushing werec a rr ied o u t. T he r e l at io n s h i p b e t we e n t h ecompression pressure of each sample and theFig. 5. Grain size accumulation curves of PumiceFig. 6. Grain size distributions of Shirasu

252

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 7. Grain size distributions of Pumice
Photo. 4. Digital microscope

Fig. 8. Curves of diameter ratio to compression
pressure

Photo. 5. State after the compression: Shirasu

reduction rate D15 '/ D15 is shown in Fig. 8. Whenchecking at the compression pressures of the sample
in which the solidification was confirmed, D15 '/D15 was in values of 0.3 to 0.4. In addition, it wasable to be confirmed that the particle crushing was
carried out more conspicuously as the compression
pressure increased in all samples.
The digital microscope used to observe the crush
situation of particles is shown in Photo. 4. Shirasu
and Pumice were compared and the appearances of
Shirasu and Pumice after the compression are shownin Photo. 5 and 6, respectively. The particle crushing
was seen in Shirasu; however, solidification was
unperformed because the particles were too large to
be interlocked to each other. On the other hand,since the cross section of the particles have irregularshapes in Pumice, it is thought that the particles
interlocked each other to perform solidification.
Since Photo5 and Photo6 were used for confirming
the crush states of the samples, quantitativeevaluation can’t be conducted.

Photo. 6. State after the compression: Pumice
CONCLUSIONS
It was confirmed that particle crushing greatly
affected solidification of sand sample. Particle
crushing began at the yield point shown in the e-log
p curve of the sample that was able to be obtained by
one-dimensional compression tests and particle
253

GEOMATE - Mie, Japan, Nov. 21-24, 2017crushing was promoted as void ratios decreased. It isthought that particle crushing was accelerated byhigh pressure even in the case of the sample inwhich particle crushing was hard to occur and fineparticles interlocked each other and caused
solidification of sample.

REFERENCES[1] Ryoichi, W. Tomoko, M. Hiroki, I. Koreyoshi,
Y “Development and empirical study of highly
functional new soil materials with rainwater
infiltration and water retention using Silas”
Kyushu Engineering Management Association2010 Results Meeting[2] Yukio, N. Yoshinori, K. Masayuki, H. Takayuki,
H. Shuiti, M. “Particle fracturing characteristics
of sand during one-dimensional compression”
The 54th annual academic lecture meeting ofJapan Society of Civil Engineers[3] Yoshinori, K. Yukio, N. Masayuki, H. Hidekazu,
M. “Grains characteristics and one-dimensional
compression properties of crushable soils”
Journal of Japan Society of Civil Engineers vol.
2002 No. 701 P343-355[4] Keiji, K. Haruo, H. Shunji, U. “Bearing force
characteristics of crushable ground considering
the shape of soil particles” The 59th annual
academic lecture meeting of Japan Society of
Civil Engineers[5] Daisuke, K. Naotaka, K. Yukio, N. Masayuki, H.
Norimasa, Y. Hidekaza, M. “Influence ofsolidification structure and physical propertiesof particles on one-dimensional compression
characteristics of consolidated grain material”
The 38th Japan National Conference on
Geotechnical Engineering[6] Takeaki, F. “Index indicating the degree of theparticle crush” Soil mechanics and foundationengineering
29(12),
64-65,
1981-12-25

Grain size analysis showed that particle crushing
was accelerated with the increase in compression
pressure. Since the reduction rate of 15% diameter iseffective to be an index of particle crushing, particle
crushing is likely to be related to the factor that D15'/ D15 is a value of 0.3 to 0.4.
As observed with a digital microscope, thephenomenon that the crushed fine particles stuck
into large particles, and interlocked each othercontributed to solidification of sample. Easiness ofcrushing differs depending on the materials and it
can be said that it is easier to solidify as the material
is more prone to be crushed into the particles. It was
confirmed that the minerals are hard to crush and thematerial with high mineral content is hard to solidify.
ACKNOWLEDGEMENTS
This work was supported by the Space
Exploration Innovation Hub Center (TansaX), Japan
Aerospace Exploration Agency (JAXA) under the
Support Program for Starting Up Innovation Hub
promoted by the Japan Science and Technology
Agency (JST).

254

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

NUMERICAL ANALYSIS ON MECHANISM OF LIQUEFACTION NOTONLY IN MAIN EARTHQUAKE BUT ALSO IN AFTER SHOCK
1,4

Yukihiro Morikawa1, Hide Sakaguchi2, Akihiko Taira 3 and Ho Cho4
Department of Civil Engineering, Nagoya Institute of Technology, Japan; 2,3 Japan Agency for Marine-Earth
Science and Technology, Japan
ABSTRACTDuring the 2011 Great East Japan Earthquake, liquefaction occurred in reclaimed ground in wide area of east
Japan. In some areas, liquefaction happened in the aftershock was even more serious than that happened in themain shock. For this reason, the liquefaction that happened long time after the earthquake, caused not only by themain shock but also the multiple aftershocks within a short period of time, is intensively investigated in recent
years. In this paper, particular attention is paid to the characteristic features of the liquefaction and its consequentconsolidation-induced settlement. Based on the observed data, a series of dynamic-static analyses, considering not
only the earthquake loading but also static loading during the consolidation after the earthquake shocks, areconducted in a sequential way just the same as the scenario of the earthquake. The calculation is conducted with
3D soil-water coupling finite element-finite difference (FE-FD) analyses based on a rotating-hardening
elastoplastic constitutive model. From the analyses, it is recognized that small sequential earthquakes, whichcannot cause liquefaction of a ground in an independent earthquake vibration, cannot be neglected when the groundhas already experienced the liquefaction after a major shock. In addition, the aftershocks have great influence on
the long-term settlement of the soil layers with low permeability. It is confirmed that the numerical method usedin this study can describe the ground behavior correctly under repeated earthquake shocks.
Keywords: Repeated earthquake, Liquefaction, FEM, Settlement
Re-liquefaction happened in a first aftershock waseven more serious than that happened in the main
shock. This phenomenon indicates a very important
fact that the sand boiling was accelerated by theaftershocks and more severe liquefaction occurred
during the aftershocks at some sites.
In order to describe and predict correctly theground behavior in such kind of repeated earthquake
vibrations that may occur in future, it is necessary to
clarify the mechanism of this geotechnicalengineering problem. In this paper, a typical local siteof reclaimed ground in Chiba Prefecture Japan, isselected for the numerical analyses. Based on theobserved data, a series of repeated dynamic-static
analyses, considering not only the earthquake loading
but also the static loading during the consolidation
after each earthquake shock, are conducted in asequential way just the same as the scenario happenedin the Great East Japan Earthquake.

1. INTRODUCTIONOn March 11, 2011 14:46:18, a 2011 off the
Pacific coast of Tohoku Earthquake (The Great East
Japan Earthquake) happened with a magnitude of 9.0
in Richter, the greatest earthquake ever recorded inJapan history. Some typical characteristics of theGreat East Japan Earthquake can be given, e.g.,
duration time of the seismic motion was very long,multiple big aftershocks happened in a relative shortperiod of time and so on. According to an
investigations after the earthquake [1]-[2], thedamages due to tsunami and liquefaction were mostserious recorded in Japan. Especially multiple
aftershocks in a relative short period of time madedamages spread, many existing structures in a wide
area along coastal area suffered serious damages. The
increase of excess pore water pressure (EPWP) andthe development of anisotropy in the groundexperienced liquefaction due to the main shock may
cause instability of the ground and might cause reliquefaction in the consequential aftershocks even if
the aftershocks are not large. One of the interesting
phenomena is that liquefaction not only happened in
the main shock of earthquake vibrations, but also
happened in the first aftershock whose acceleration
was much less than that of main shock. However, it
was thought that such a low level of shock was notstrong enough to cause liquefaction.

2. CONSTITUTEIVE MODEL FOR SOILSAND FINITE ELEMENT METHOD
The numerical analyses and prediction are
conducted with 3D soil-water coupling finite
element-finite difference (FE-FD) analysis based on
the Cyclic Mobility model (CM model) proposed byZhang et al. [3]. CM model is a kind of rotating hardening elastoplastic model. It can properly
255

GEOMATE - Mie, Japan, Nov. 21-24, 2017

describe the nonlinear behavior of non-cohesive soils
under both dynamic and static loadings, especially thecyclic mobility of sand during liquefaction. With CMmodel and effective stress based FEM code, themechanical behavior of the ground, such as thechange of EPWP, the development of stress-induced
anisotropy and the post-liquefaction consolidation,
can be properly described not only in the liquefaction
stage during the earthquake but also in the postliquefaction consolidation stage in a unified way.
Numerical simulation is widely used the analysesof earthquake induced liquefaction. The object of thenumerical simulation or prediction conducted in thispaper is to reproduce or predict the overallmechanical behavior during and after the earthquakes,
including the liquefaction and consolidation in
repeated earthquake vibrations. The simulation was
conducted using a 2D/3D soil-water coupled finite
element method program named as DBLEAVES [4].
The applicability and the accuracy of the program
have been firmly verified by shaking table tests andother various liquefaction phenomena [5]-[9].
CM model is adopted to simulate thestatic/dynamic behavior of the non-cohesive soils in
the current study. CM model can consider the effectof the stress-induced anisotropy, the density and thestructure of soils in a unified way. It can properly
describe the mechanical behaviors of non-cohesive
soils subjected to monotonic/cyclic loading underdrained/undrained conditions. Based on the conceptsof subloading [10] and superloading [11], thesubloading, normal and superloading yield surfaces in
p-q (mean principal stress - deviatoric stress) plane
are adopted in the model to take into consideration theinfluence of density and the structure of soil, as
shown in Fig. 1.

stress-induced anisotropy. All parameters have clear
physical meanings and can be easily determined byundrained triaxial cyclic loading tests and drained
triaxial compression tests. A detailed description andapplicability of CM model can be found in thereference [3]-[9].
In the analysis with DBLEVES, the dynamic/static analyses are conducted using the same
program, the same parameters throughout the wholecalculating process. Newmark- method is used andthe integration time interval is 0.005 sec. Integration
time interval is decided from interval time ofobserved earthquake motion and previous studies.
Since it is expected that strong nonlinearity of the soil
would occur, Rayleigh type of initial-rigidityproportional attenuation is adopted and the damping
values of the soils, the structure and the piles are
assumed to be 2% and 10% for the first and second
modes respectively. Before dynamic analyses ofearthquake motions, a gravitational stress field
analysis is carried out to obtain the initial effective
stress of the ground.
3. NUMERICAL SIMULATION DURING AND
AFTER EARTHQUAKE
3.1 Earthquake waves
A typical two directions earthquake motion at
Simousa 2300m below the ground surface at Chiba
Prefecture was recorded and it is selected to be theinput earthquake motion in present analyses as shownin Figure 2. It is noted that the earthquake with a main
shock followed by two aftershocks shakes in E-W and
N-S directions at the same time. The main shock
lasted for 300 seconds with a maximum accelerationof 0.85 m/s2 and the first aftershock also lasted for
300 seconds with a maximum acceleration of 0.25
m/s2 while the second aftershock lasted for 135
seconds with a maximum acceleration of 0.04 m/s2.
The interval between the main shock and the firstaftershock was approximate 24 minutes and theinterval between the two aftershocks wasapproximate 6 minutes. It should be mentioned hereinthat such a long duration of motions has been
expected to be the major cause of the severeliquefaction and ground deformation.

Fig.1 Yield surfaces and its change with thedevelopment of anisotropy.
Besides, the elliptical yield surfaces may changewith the development of the stress-induced
anisotropy. These characteristics enable the model todescribe the cyclic mobility of non-cohesive soils.
Eight parameters are employed, among which fiveparameters are the same as those in the Cam-claymodel [12]. The others are parameter for controllingthe collapse rate of the structure, loosing rate of theoverconsolidation ratio and the developing rate of the

1.0

Acceleration, (m/s )

0.5

2

2

Acceleration, (m/s )

1.0

0.0
-0.5
-1.0

0

15

30

45

Elapsed time, t(min)(a) East-West

60

0.5
0.0
-0.5
-1.0

0

15

30

(b) North-SouthFig.2 Recorded seismic motions at Shimous
256

45

Elapsed time, t(min)60GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.3 Geological profile and FEM mesh.

(K-Net, http://www.k-net.bosai.go.jp)
3.2 Simulation for one column ground3.2.3 Material parameters
The material parameters used in calculation are
shown in Table 1, and Figure 4 shows the theoreticalestimation of the element behavior in undrained
cyclic loading test. Since no cyclic testing data ofsoils are available, some of these parameters were
determined with reference to the standard penetration
tests, and others were estimated with reference tothose of Toyoura sand. From the results, it is known
that the strain accumulates as the number of cyclicloading increases, and liquefaction accompanied bycyclic mobility may occur in the reclaimed layer andloose sand layer at the investigated site. However,liquefaction will not occur easily in the loose silt layer.

3.2.1 Simulation scenario
The following 3 cases are considered to evaluate
the influence of a main shock on its aftershocks andvisa verse:
Case 1: Calculation is conducted in the same way
just as the scenario happened in the Great East Japan
Earthquake: (1) main shock, (2) 1440 seconds
consolidation, (3) first aftershock, (4) 360 seconds
consolidation,(5)
secondaftershock,(6)
consolidation until the settlement of the groundceased completely (50 years).
Case 2: Calculation is conducted only considering
the main shock and consolidation after the main
shock for a comparison with Case 1: (1) main shock,(2) consolidation until the settlement of the groundceased completely.
Case 3: Calculation is conducted only considering
the aftershock-1 for a comparison with Case 1.

Table 1 Material parametersBAs1, 2 Ac1, 2
0.050 0.030 0.043
Compression index
0.0064 0.0060 0.0090
Swelling index
0.300 0.300 0.300
Passion’s ratioStress ratio at critical
3.650 3.650 3.000
state Rf
Void ratio e0 (p’=98kPa
0.870 0.870 0.920
on N.C.L)
Degradation parameter
2.200 2.200 0.100
of structure a
Evolution parameter of
1.500 1.500 0.100
anisotropy br
Degradation parameter
0.100 0.100 2.200of over-consolidation m
17.64 17.64 16.66
Unit weight  (kN/m3)
Permeability k (m/sec) 1.0E-4 1.0E-4 1.0E-9
0.800 0.800 0.600
Initial structure R*0
Initial degree of over4.000 2.500 1.500
consolidation 1/R0
0.000 0.000 0.000
Initial anisotropy 

3.2.2 Investigated site and analyses mesh for FEM
The investigated site was reclaimed by dredged
soils that consist predominantly of sand or silt fromthe seabed of Tokyo Bay. Figure 3 shows the result of
boring survey in the investigated site and thecorresponding FEM mesh used in the calculation. The
mesh is coincident with the boring data. It is one
column ground with a 1.0m x1.0m horizontal squarearea. Each mesh has depth of 1m. In the case of
dynamic analyses, an equal-displacement boundary,or called as periodic boundary, is applied to two sideboundaries in x and y direction respectively to deal
with the artificially introduced boundaries that do notexist in reality so that the incident waves are always
allowed to transmit freely from the artificial
boundaries introduced in FEM analysis in finite
domain. The bottom is assumed to be fixed inhorizontal and vertical directions. The drainedboundary (ground water level) is set at the groundsurface.

20
30
40
50

50

Deviatoric stress, q(kPa)40

Deviatoric stress, q(kPa)

N value
20
30

10

5
0
-5
-10

0

10

20

30

40

5
0
-5
-10
-0.20

50

Effective mean principal stressp'(kPa)Reclaimed soil (B)

-0.10

0.00

0.10

Axial strain, a

0.20(a) Reclaimed layer (B layer, GL-3.50m)

Sand (As1)10

10Clay (Ac1)
Sand (As2)Clay (Ac2)
Sand (Ds1)

Deviatoric stress, q(kPa)

Depth(m)1010Deviatoric stress, q(kPa)

0

0

10

5
0
-5
-10

0

10

20

30

40

50

Effective mean principal stressp'(kPa)

257

5
0
-5
-10
-0.20

-0.10

0.00

0.10

Axial strain, a

0.20

GEOMATE - Mie, Japan, Nov. 21-24, 2017of ground, the simulation was conducted. The Case 1
has a history of the aftershocks but Case 2 did nothave that. From the results, ground surface settlementof Case 1 with aftershocks than Case 2 without that.
It can be concluded that both the liquefaction and thesettlement are significantly affected by theaftershocks.

(b) Loose sand (As layer, GL-10.50m)
40

20
0
-20
-40

0

40

80

120

160

20
0
-20
-40
-0.02

200

Effective mean principal stressp'(kPa)

-0.01

0.00

0.01

Axial strain, a

1.0

0.02

Settlement, z(m)(c) Loose silt (Ac layer, GL-22.50m)

Fig.4 Effective stress paths and stress-strain relations.

0.5
0.0

-0.5
-1.0

2.0

B layer(GL-3.50m)
As1 layer(GL-10.50m)
Ac1 layer(GL-22.50m)

1.5
1.0
0.5
0.0

0

15

30

45

Elapsed time, t(minute)(a) Case 1

60

Excess Pore Water Pressure Ratio

Excess Pore Water Pressure Ratio

3.2.4 Results and discussions
Figure 5 shows analysis results of the excess porewater pressure ratio (EPWPR) in the Case 1 and 3.
Case 1 has a history of the main shock before theaftershock-1 while Case 3 did not have a history of
the main shock. Here, EPWPR is defined as the ratioof excess pore water pressure to the initial verticaleffective stress. Therefore, EPWPR equaling to 1means liquefaction.
From the result, in the Case 1, for the sand (As1)and the clay (Ac1), liquefaction did not occur in main
shock but excess pore water pressure (EPWP) kept
increasing after the aftershocks because of theconstant water supply from the lower layers. For thereclaimed layer (B), EPWPR increased up almost to
1 both in the main shock. And after the main shock,
EPWPR of the reclaimed layer (B) decreased to about
0.70, but liquefaction occurred again in theaftershock-1 even though the maximum accelerationof the aftershock-1 is less than 25 gal. On the other
hand, an increasing of EPWPR of Case 3 is muchsmaller than that of Case 1. Therefore, when a groundhas not recovered from damage by main shock, aliquefaction easily occur by small aftershock.
From the above results, it is known that theaccumulation of EPWP and development of stressinduced anisotropy induce ground liquefaction.
2.0

15

30

45

Elapsed time, t(minute)

0

5

10

15

Elapsed time, t(hour)

20

-1.0

0

20

40

60

Elapsed time, t(year)

80(b) 0 to 50 years

3.3 Simulation for three-dimensional ground3.3.1 Simulation scenario
In above simulation (Case 1) for one column
ground, the calculation is conducted in the same way
just as the scenario happened in the Great East Japan
Earthquake: (1) main shock, (2) 1440 seconds
consolidation, (3) first aftershock, (4) 360 seconds
consolidation,(5)
secondaftershock,(6)
consolidation until the settlement of the groundceased completely (50 years).
3.3.2 Investigated site and analyses mesh for FEM
Figure 7 shows the plan view of the soil
distribution based on the results of Swedish weightsounding test.by the inhabitants during six months
after the earthquake. Soil conditions in this area werealso investigated by in-situ boring combined with theStandard Penetration Test (SPT), prior to and after theearthquake. According to the results of SPT and theSwedish weight sounding test, the whole area can bedivided into three types of soil, that is, type A, type B
and type C. Based on the results shown in Figure 7,
the investigated site in the analysis can be divided into
four areas shown in Figure 8. The dimension of thecalculated area in FEM is 400m in length, 300m in
width and 50m in depth. As to boundaries between
different types of soil, transition zones were set to linkthe different types of soil as indicated in soil type AC,
type AB, type BC, type ABAC, type BCBA and type
CACB, as shown in Figure 8.

0.5

0

0.0

Fig.6 Ground surface settlements in Case 1 and Case
3.

1.0

0.0

Case 1(with 2 after shocks)
Case 2(without after shock)

0.5

-0.5

(a) 0 to 20 hours

B layer(GL-3.50m)
As1 layer(GL-10.50m)
Ac1 layer(GL-22.50m)

1.5

1.0

Case 1(with 2 after shocks)
Case 2(without after shock)Settlement, z(m)Deviatoric stress, q(kPa)

Deviatoric stress, q(kPa)4060(b) Case 3

Fig.5 Results of the excess pore water pressure ratio.
Figure 6 shows a comparison of ground surface
settlements after earthquake between the Case 1 and2. In order to investigate the influence of aftershocks
on the long-term settlement due to the consolidation
258

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 10 shows the finite element mesh. As forthe mesh size, the whole depth of calculation area is
50 m, the top 16 m is divided into 16 layers with eachlayer of 1m thickness and the below 34 m is divided
in to 17 layers with each layer of 2 m thickness. In theanalyses, the elements in each soil layer at the centerof type A, type B (the larger part) and type C area are
selected. In the case of dynamic analyses, an equal
displacement boundary condition is applied for twoside boundaries in x and y direction respectively todeal with the energy dissipation problem. The bottom
is assumed to be fixed in all directions. The drainedboundary (ground water level) is set at the groundlevel of -1 m.

Fig.7 Plan view of the soil distribution based on the
results of Swedish weight sounding test.

Fig.10 Finite element mesh3.3.3 Material parameters
The material parameters used in calculation are
shown in Table 2, and Figure 11 shows the theoreticalestimation of the element behavior in undrained
cyclic loading test. Even in this calculation, since nocyclic testing data of soils are available, some of theseparameters were determined with reference to theresults of SPT, and others were estimated withreference to Toyoura sand. From the analyses results,
it is known that the strain accumulates as the numberof cyclic loading increases, and liquefaction
accompanied by cyclic mobility may occur in thereclaimed layer, loose sand and very-loose sandexcept loose silt land the base silt.

Fig.8 Plan view of the calculated area in FEM
Figure 9 shows the geologic profiles of thecalculated area. All geologic profiles consist of loose
sand and loose silt above G.L. -15m. The loose sandlayer near the surface has a SPT N-value of 5~15 andit easily causing liquefaction.

Table 2 Material parameters
B
As1
As2
0.030 0.030 0.043

0.006 0.006 0.009

0.300 0.300 0.300
Rf
4.600 4.600 4.600
e00.720 0.720 0.880
a2.200 2.200 0.100br1.500 1.500 0.100m
0.100 0.100 0.100
 kN/m3) 17.60 18.00 17.00
k (m/sec) 1.0E-5 1.0E-5 1.0E-6
R* 0
0.800 0.800 0.600
1/R0
5.000 5.000 3.000
0.000 0.000 0.000
Fig.9 Geologic profiles of the calculated area.

259

Ac1
0.207
0.041
0.350
3.500
1.100
0.100
0.100
3.800
15.40
1.0E-7
0.600
2.500
0.000

Ac2
0.207
0.041
0.350
3.500
1.100
0.100
0.100
3.800
17.70
1.0E-7
0.600
2.500
0.000

GEOMATE - Mie, Japan, Nov. 21-24, 2017

0
-5
-10

0

10

20

30

40

0
-5
-10
-0.20

50

Effective mean principal stressp'(kPa)3.3.4 Results and discussions
Figure 12 shows the EPWPR with time indifferent soil layers at the center of type A, type B andtype C respectively. For the upper loose sand (As1) in
the area of type A, liquefaction did not occurred inmain shock, but that occurred in after shock. In thearea of type B, however, EPWPR in aftershock issmaller than that of main shock. For the very loose
sand (As2) in the areas of type A and B, EPWPR
raised up almost to 1 in the aftershocks although they
were much smaller than the main shock. In the areaof type C, however, liquefaction occurred seriously inboth the main shock and aftershocks. For the loose silt
(Ac1), it did not liquefy anyhow but EPWP kept
increasing after the aftershocks because of theconstant water supply from the lower layer of wholeground. For the lower loose sand (As3) in the area oftype B, liquefaction occurred in the main shock andalthough EPWP decreased somehow after the main
shock the ground liquefied again in the aftershocks.
In the areas of type A and C, however, EPWPR was
smaller than that of type B.

5

-0.10

0.00

0.10

Axial strain, a0.20(a) Filled soil in reclaimed layer (GL-1.50m)
Deviatoric stress, q(kPa)

Deviatoric stress, q(kPa)10(GL-3.50m, q/2p=0.100)

10
5
0
-5
-10

0

10

20

30

40

5
0
-5
-10
-0.20

50

Effective mean principal stressp'(kPa)(GL-3.50m, q/2p=0.100)

-0.10

0.00

0.10

Axial strain, a0.20(b) Loose sand (GL-3.50m)

10
0
-10
-20

0

10

20

30

40

50

Effective mean principal stressp'(kPa)(GL-8.50m, q/2p=0.100)

10

Excess Pore Water Pressure Ratio

Deviatoric stress, q(kPa)

Deviatoric stress, q(kPa)20(GL-8.50m, q/2p=0.100)

20

0
-10
-20
-0.20

-0.10

0.00

0.10

Axial strain, a0.20(c) Very loose sand (GL-8.50m)

10
0
-10
-20

0

20

40

60

80

10
0
-10
-20
-0.02

100

Effective mean principal stressp'(kPa)

-0.01

0.00

0.01

Axial strain, a

0.02(d) Loose silt (GL-12.50m)
Deviatoric stress, q(kPa)

Deviatoric stress, q(kPa)40(GL-32.00m, q/2p=0.100)

40
20
0
-20
-40

0

40

80

120

160

200

Effective mean principal stressp'(kPa)

1.00
0.75
0.50
0.25
0.00

0

15

30

45

Elapsed time, t(minute)

60

1.50

Type A(GL-7.50m)
Type B(GL-4.50m)
Type C(GL-6.50m)

1.25
1.00
0.75
0.50
0.25
0.00

0

15

30

45

Elapsed time, t(minute)

60

1.50

Type A(GL-12.50m)
Type B(GL-6.50m)
Type C(GL-10.50m)

1.25
1.00
0.75
0.50
0.25
0.00

0

15

30

45

Elapsed time, t(minute)

60

1.50

Type A(GL-15.50m)
Type B(GL-9.50m)
Type C(GL-13.50m)

1.25
1.00
0.75
0.50
0.25
0.00

0

15

30

45

Elapsed time, t(minute)60(c) Loose silt (Ac1) (d) Lower loose sand (As3)(GL-32.00m, q/2p=0.100)

Fig.12
area.

20
0

-0.01

0.00

0.01

Axial strain, a

Excess pore water pressure ratios in each

Figure 13 shows the distribution of EPWPR at
different depths. The left side of the figure is the
EPWPR immediately after the main shock and theright of the figure is the EPWPR immediately after
the aftershock-1. At the depth of 6m below the groundsurface, liquefaction area due to the main shock was
clearly smaller than that of the aftershock. In otherwords, liquefaction occurred in the aftershock was
more serious than that of the main shock in the areaof type A and type C. At the depth of 8m below theground, liquefaction only occurred in the area of type

-20
-40
-0.02

Type A(GL-4.50m)
Type B(GL-3.50m)

1.25(a) Upper loose sand (As1) (b) Very loose sand (As2)(GL-12.50m, q/2p=0.100)

Excess Pore Water Pressure Ratio

Deviatoric stress, q(kPa)

Deviatoric stress, q(kPa)20(GL-12.50m, q/2p=0.100)

20

1.50

Excess Pore Water Pressure Ratio

5(GL-1.50m, q/2p=0.100)

Excess Pore Water Pressure Ratio

Deviatoric stress, q(kPa)

Deviatoric stress, q(kPa)10(GL-1.50m, q/2p=0.100)

10

0.02

(e) Base silt (GL-32.00m)

Fig.11 Effective stress paths and stress-strain relations

260

GEOMATE - Mie, Japan, Nov. 21-24, 2017

A after the aftershock.
In general, the EPWPR in all areas and soil types
may increase again in aftershock.

3.3.5 X-ray CT image of geological features
Figure 16 shows the photograph and X-ray CT
images of core sections drilled immediately after theliquefaction at calculated area [13]. A very importantresult we have got in this research is that the liquefied
soil strata were perfectly identified with X-ray CT
images. The pink line next to the CT image indicatesthe liquefied soil layers that distributed at the depth of
6.2m to 8.6m, where the thin strata of reclaimed
ground that was observed clearly at the up strata from2.0m to 6.2 m, suddenly disappeared due to theliquefaction. This observed phenomenon was
remarkably similar to the calculated results showed in
Figures 13, 14. It is therefore reasonably to say thatthe analysis method based on CM model, used in thissturdy, can well describe the actual situation of theliquefaction in main shock, the re-liquefaction inaftershock, and the consolidation settlement ofground after multiple earthquakes.

(b) GL-6.00m(c) GL-8.00m
Fig.13 Distribution of EPWPR at different groundlevels (Left: main shock, Right: aftershock-1)
Figure 14 shows the calculated distribution of
settlement of ground surface. Six hours after theearthquake, an uneven deformation appeared in thearea of type C. In this area, maximum amount of
upheaval of the ground reach about 0.5m while theground in types A and B settled about 0.5m. This
uneven ground settlement was observed extensively
in the field survey. Photo 1 shows the unevensettlement in roadways near the observed site.
However, according to the analyses, the ground of allareas will turn out to be settled down 0.25m to 0.90m
in 50 years after the earthquake, as shown in Figure
14 (b).

Fig.14

2.0-3.0m

3.0-3.8m

3.8-4.8m

4.8-5.8m

5.8-6.8m

6.8-7.8m

7.8-9.0m

9.0-10.0m(a) 6hours(b) 50 years
Distribution of settlement of ground surface.

(a) Surface of sidewalk(b) Heaved sidewalk

Photo 1 Uneven settlement near the observed sites

Fig.16 Photograph and X-ray CT images of coresections drilled in calculated area after liquefaction.
261

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[7] F. Zhang, R. Oka, Y. Morikawa, Y. Mitsui, T.
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Test on Superstructure-foundation-Ground
System in Liquefiable Soil and Its Numerical
Verification, Geotechnical Engineering Journalof the SEAGS & AGSSEA, Vol. 45, No. 2, pp.
1-6, 2014.
[8] Y. Morikawa, Y. Tanaka, K. Maeda and H. Cho:
Countermeasure against liquefaction using
drainage diaphragm wall focused on the effect ofdissipation of water pressure, Journal of JSCE,
Ser. A2, Vol. 71, No. 2, pp. I_437-I_448, 2015.
[9] K. Hamayoon, Y. Morikawa, R. Oka, F. Zhang:
3D dynamic finite element analyses and 1 gshaking table tests on seismic performance ofexisting group-pile foundation in partially
improved grounds under dry condition, Soil
Dynamics and Earthquake Engineering, Vol. 90,
pp. 196-210, 2016.
[10] K. Hashiguchi and M. Ueno: Elastoplastic
constitutive laws of granular material,
Constitutive Equations of Soils, Pro. 9th Int.
Conf. Soil Mech. Found. Engrg., Spec. Ses. 9,
Murayama, S. and Schofield, A. N. (eds.), Tokyo,
JSSMFE: pp. 73-82, 1977.
[11] A. Asaoka, M. Nakano, T. Noda: Superloading
yield surface concept for the saturated structured
soils, Proc. of the Fourth European Conferenceon Numerical Methods in GeotechnicalEngineering-NUMGE98, pp. 232-242, 1998.
[12] Roscoe K. H., Schofield A. N. and Thurairajah
A.: Yielding of clays in states wetter than critical,
Geotechnique 13 (3), pp.211-240, 1963[13] A. Taira, K. Iijima, C, Igarashi, S. Sasaki, H.
Sakaguchi, A. Sakaguchi, E. Kikawa, T.
Kanamatsu, Y. Yamamoto, W. Azuma, T.
Tanaka, M. Nishimura, T. Suzuki, Y. Kido, N.
Watanabe, M. Okuno, T. Inoue, H. Mayuzumi, T.
Oda, T. Hamada, T. Muroyama, I. Takeo, J.
Takashina, H. Katsumata, N. Harada, F. Nishida,
H. Minamikawa and Y. Kanetaka: Identificationof a Soil Liquefied Layer due to the 2011 off the
Pacific Coast of Tohoku Earthquake Using X-ray
CT Scan Imaging: An Example from Core
Samples from Maihama 3-chome, Urayasu City,
The Journal of the Geological Society of Japan,
Vol. 118, No. 7, pp. 410-418, 2012.

4. CONCLUSION
In this study, 3D soil-water coupled finite
element-finite difference analyses based on CM
model were conducted to investigate the mechanismof liquefaction and consolidation settlement ofground in multiple earthquakes. The following
conclusions can be obtained:
1. According to the calculated results of theliquefaction and the settlement in simulation for one
column ground and three-dimensional ground,residual excess pore water pressure and stressinduced anisotropy have big influence on thesubsequent ground behavior.
2. When a ground receive the damage from main
shock and could not recovered promptly, excess porewater pressure in low permeability soil remains highand the stress-induced anisotropy develop to a verylarge level. As a result, liquefaction may be caused
again even by a small aftershock.
3. When an earthquake occurs at ground having
low permeability soil, excess pore water pressure may
cause not only immediate settlement but also longtern settlement due to consolidation. Furthermore, aground settlement is significantly affected by theaftershocks.
4. By the comparison between the calculated
results and the field observation, it is known that thecalculations are consistent well with the realliquefaction and settlement behavior. Therefore, it isconfirmed that the proposed numerical method is
possible to predict the ground behavior accurately as
such multiple earthquakes occur in future.
REFERENCES[1] M. Kazama: Overview of the damages of The
2011 Off the Pacific Coast of Tohoku
Earthquake and its geotechnical problems,
Japanese Geotechnical Journal, Vol. 7, No. 1, pp.
1-11, 2012.
[2] F. Oka, N. Yoshida, S. Kai, T. Tobita, Y. Higo,
N. Torii, S. Kagamihara, N. Nakanishi, S.
Kimoto, Y. Yamakawa, Y. Touse, R. Uzuoka
and T. Kyoya: Reconnaissance Report of
Geotechnical Damage due to the 2011 off the
Pacific coast of Tohoku Earthquake - Northern
Area of Miyagi Prefecture -, Japanese
Geotechnical Journal, Vol. 7, No. 1, pp. 37-55,
2012.
[3] F. Zhang, B. Ye, T. Noda, M. Nakano and K.
Nakai: Explanation of Cyclic Mobility of Soils:
Approach by Stress-Induced Anisotropy, Soils
and Foundations, Vol.47, No. 4, pp.635-648,
2007.
[4] Y. Bin: Experiment and Numerical Simulation of
Repeated Liquefaction -Consolidation of Sand,
Doctoral Dissertation, Gifu University, 2007.

262

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EVALUATION OF HEAVING RESISTANCE FOR DEEP SHAFT USINGNODULAR DIAPHRAGM WALL
1

Koji WATANABE1, Akira MITSUMORI2, Hidetoshi NISHIOKA3 and Masayuki KODA3
Technical Research Institute, Obayashi Corporation, Japan; 2 Design Department, Obayashi Corporation,
Japan; 3 Structures Technology Division, Railway Technical Research Institute, Japan
ABSTRACTIn recent years, an increasing number of plans in Japan have been proposed for large-scale railway structures
to be built deep underground. To construct a large-scale railway structure, it is necessary to construct verticalshafts that serve as the starting and ending point for the shield machine during the construction as well as the air
vents once it goes into operation. In such situations, it is expected that there will be an increase in the cases
where the vertical shafts will be built to reach deep underground. If typical diaphragm walls were used toconstruct these deep shafts, the embedment depth of the diaphragm walls would have to be made substantiallysignificant in order to control the heaving. Heaving as stated here is a phenomenon in which pressurized watercontained in the permeable layer below the impermeable layer close to the bottom of the excavated groundbreaks through the impermeable layer owing to the upward force of the water pressure during the excavation
process, which then causes the vertical shaft to lose its stability. Using nodular diaphragm walls that havenodular part on the diaphragm walls of the deep shaft could be relied upon for the purpose of supporting theembedment depth of the diaphragm walls. In this research, the influence the nodular part resistivity was
examined in resisting heaving when nodular diaphragm walls are used for the deep shaft. The experiments at
gravitational and centrifuge acceleration fields were conducted, and their effectiveness were confirmed.
Keywords: Deep Shaft, Heaving Resistance, Nodular Diaphragm Wall, Model Test
INTRODUCTION
In recent years, an increasing number of plans
have been proposed for large-scale railway
structures to be built deep underground. To construct
a large-scale railway structure, it is necessary toconstruct vertical shafts that serve as the starting andending point for the shield machine during theconstruction as well as the air vents once it goes into
operation. In such situations, it is expected that there
will be an increase in the cases where the verticalshafts will be built to reach deep underground. Whentypical diaphragm walls were used to construct thesedeep shafts, the embedment depth of the diaphragmwalls would have to be made substantiallysignificant in order to control the heaving. Heaving
as stated here is a phenomenon in which pressurizedwater contained in the permeable layer below theimpermeable layer close to the bottom of the
excavated ground breaks through the impermeable
layer owing to the upward force of the waterpressure (uplift force) during the excavation process,which then causes the vertical shaft to lose its
stability.
There are two methods to construct deep shafts:
the pneumatic caisson construction method and thediaphragm wall construction method. The pneumatic
caisson construction method has demonstrated toreach a maximum depth of approximately 40 to 50

Embedded section
Nodular partFig. 1 Schematic View of Nodular Diaphragm Wall
Diaphragm wall

②Shaft friction

Nodular diaphragm wall

②Shaft friction①Soil mass weight①Soil mass weight④Resistanceat nodular part
③Shear resistance
Uplift force③Shear resistance
Uplift force

Decrease ofembedded length

Impermeable
layer
Permeable
layer

Fig. 2 Effect of Nodular Diaphragm Wall
263

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(9)

(10)

m1), and as there is a need to highly pressurize the air
during construction, there are challenges in applying
this method to deep underground construction. On
the other hand, the diaphragm wall construction
method has shown it can reach a maximum depth ofapproximately 100 to 120 m 2), 3), but concerning
construction deep underground, as some havepointed out, there are chances of pouring
deficiencies of concrete due to, for example, thetremie pipes clogging2). Therefore, for this method,
it is necessary to make the embedment depth asshallow as possible. Using nodular diaphragm wallsthat have nodules on the diaphragm walls of the
deep shaft, as seen in Fig. 1, could be relied upon forthe purpose of supporting the embedment depth ofthe diaphragm walls (Fig. 2). The nodules of thenodular diaphragm walls are expressively able tobear the pressure and thus possess greater resistancethan normal diaphragm walls4). In the constructionof nodular diaphragm walls, a construction methodthat expands the mid-section of the diaphragm wallis used in order to create its nodular part. The abovementioned construction methodology was developedby the Obayashi Corporation and has already beenutilized in the field in a few construction projects
such as architecture field4), 5).
In this research, the influence the nodular part
resistivity was examined in resisting heaving whennodular diaphragm walls are used for the deep shaft.
The experiments at gravitational and centrifuge
acceleration fields were conducted, and theireffectiveness of heaving resistance were confirmed.
This paper reports the results of the modelexperiment subjected to gravitational and centrifuge
acceleration fields.

(11)

3.3

9.1
18.6

Fig. 4 Slime Cleaner for Nodular Part

z

z

LVDT

LVDT

30

600

(8)

400

(7)

30

97.2

Set of membrane(Bottom of model
ground)
200

(6)

600

(5)

400

(4)

200

(3)

6.2

(2)

18.6 18.6
30 30

(1)

Fig. 3 Construction procedure of cast-in-place concrete pile

Procedure of construction(1) Excavation of pile shaft(2) Excavation of under-reamed part(3) Measurement of pile shape(4) Excavation of nodular part(5) Measurement of pile shape(6) Slime treatment(7) Cleaning of nodular part(8) Slime treatment(9) Measurement of pile shape(10) Insertion of steel reinforcement cage(11) Concreting

143.4

t=3.3

143.4

t=3.3

150.0
150.0
Uplift force(Simulation of groundwater pressure)

NODULAR DIAPHRAGM WALL

Fig. 5 Shaft Model for Uplift Experiment at
Gravitational Acceleration Field

Figure 3 shows the construction process of thenodular diaphragm wall construction methodology.
First, use the diaphragm wall construction method to
excavate the trench, and then excavate the bottom of
the trench to enlarge. Next, use a specialized bucket
for the nodular section to excavate the nodular
section. After the excavation, the nodular part andthe pile tips are treated for slime and the slurry in thecavity is replaced with good fluids. For the slime
treatment of the knuckles, specialized slime cleaner
designed for the nodules is used as seen in Fig. 4.
After that, a steel reinforcement cage is inserted andset up inside the tremie pipe to pour concrete. The
shape of the nodular part is verified by the use of264GEOMATE - Mie, Japan, Nov. 21-24, 2017

ultrasound measuring equipment. For theconstruction experiment conducted here, the resultof the ultrasound was compared to the actual
measurements of the part that was dug up, and it wasverified that the nodular part were indeed in thespecified shape4).
UPLIFT
FORCE
EXPERIMENTGRAVITATIONAL FIELD

Table 1 Experiment Condition for Uplift
Experiment at Gravitational Acceleration Field
Undrained shea strength

Model shaft

2c (kN/m )Case 1Case 2
Case 3
Case 4
Case 5
Case 6

AT

105(Chemical grouting)
297(Cemented improvement)
512(Cemented improvement)

Overview of Uplift Force Experiment

20

Diaphragm wall
Nodular diaphragm wall
Diaphragm wall
Nodular diaphragm wall
Diaphragm wall
Nodular diaphragm wall

Case1 (Shaft)
Case2 (Nodular shaft)Uplift displacement (mm)The uplift force experiment at a gravitational
field was conducted to verify the heaving resistanceof the regular and nodular diaphragm walls. As seenin Fig. 5, two models- one shaped with no nodular
part (diaphragm wall model) and one shaped withnodular part (nodular diaphragm wall model)—wereused in this experiment. A 200 mm thickfoundational ground layer was created in a 600 mm
deep cylindrical model. Additionally, the insides ofthe models were coated with silica sand No. 7 (0. 3～0. 08 mm) to create roughness. The ground wascreated in the model had a solution injection layer
and modified concrete ground layer to set up theexperimental condition as stated in Table 1. It should
be noted that the undrained shear strength in the
Table 1 shows the actual strength during theexperiment. The chemical grouting soil layer (Cases
1 and 2) was created by mixing soluble glass typechemical grouting to the silica sand No. 7. The target
strength for the solution injection layer for theundrained shear strength was c=100kN/m2.
Additionally, the cemented improvement groundlayer (Cases 3 to 6) was created by mixing, silica
sand No. 7 and blast furnace slag cement type B.
The two target strengths for the undrained shear
strength were c=300 and 500kN/m2. The mix for thechemical grouting soil layer and the cemented
improvement ground layer were determined throughmixing experiments prior to this stage of theexperiment. Furthermore, prior to the uplift force
experiment, the same materials from the same batch
were used that were used to create the ground layerof the models to perform the unconfinedcompression test to verify they were reaching thespecified strength. For the uplift force experiment,
the heaving behavior by incrementally applying the
uplift force from the bottom of the improvement soil
layer was verified. This uplift force mimics the
upward water pressure from the pressurized water inthe permeable layer below the impermeable layer.
For this process, a membrane to simulate theimpermeable layer was installed when activating the
uplift force. By doing so, the destruction of theground layer through seepage as well as water fillingthe interface between the ground and the model wasprevented. Measurement items were the uplift
displacement on the surface of the ground and the

15

10

5

0

Maximumu uplift force

0

5

10
15
Uplift force (kN)2025(a) Case 1, Case 2（c=100kN/m2）
20
Case3 (Shaft)Uplift displacement (mm)Case4 (Nodular shaft)
15

10

5

Maximum uplift force
0

0

10

20

30

40

Uplift force (kN)(b) Case 3, Case 4（c=300kN/m2）
20
Case5 (Shaft)Uplift displacement (mm)Case6 (Nodular shaft)
15

10

5

Maximum uplift force
0

0

15

30

45

60

Uplift force (kN)(c) Case 5, Case 6（c=500kN/m2）
Fig. 6 Relationships between Uplift Displacement
and Uplift Force265

GEOMATE - Mie, Japan, Nov. 21-24, 2017

1.60

400

600

800
：LVDT

Undrained shear strength c (kN/m2)

260

260

150

260

150

260

150

260
50

Fig. 7 Relationships between Maximum Uplift
Force, Normalized Maximum Uplift Forceand Undrained Shear Strength

150：Earth pressure transducer

1900

150

uplift force. The uplift displacement is measured bychecking two-points in the radial direction (thecenter of the ground surface and 30mm from thewall) in order to see the distribution on the flat
surface.

800

200

600

0

：Pore water pressure transducer

1900

Elevation view

490

1.30

110

0

Case 4

Case 3490

1.36

Case 2110

10Case 1

490

1.42

110

20

490

1.48

110

30

Sand layer
Dr=80%

325

1.54

150

40

Plan view

325

Shaft
Nodular shaft
Normalized uplift force

Normalized uplift force Pn/Ps

Maximum Uplift force (kN)50

Fig. 8 Summary of Centrifuge Model Test
Table 2 Experiment Condition for Centrifuge
Model Tests

Results of Uplift Force Experiment
Figure 6 shows the relationship between uplift
displacement and uplift force obtained through thestudy of each case. In these cases, two measurement
points were used on the topside of the ground tomeasure uplift displacement, but the differences inthe displacement amount were not that different
from one another in each case; therefore, they wereorganized as the average displacement between two
points. According to Fig. 6, there is a tendency forthe uplift displacement to increase gradually as the
uplift force increases. Especially in the case of thediaphragm wall model (no nodular part) which are
represented with the red lines, it is seen that theelement of resistance against heaving is theperipheral friction between the surfaces where theground is up against the diaphragm wall model, it issaid that once the peripheral friction is triggered, theuplift displacement increases. On the other hand, if
the figure is looked upon at the blue line
representing the nodular diaphragm walls in each of
the figures, since the peripheral friction and nodular
resistance is activated, it can be said that it has an
improved performance in withstanding heaving.
When the uplift force is further increased, then amuch greater increase is seen in uplift displacement.
This seems to be because the resistivity (bearing
resistance) of the nodular diaphragm wall’s
resistance element against heaving is being
expressed in addition to the peripheral fiction. The
relationship among the maximum uplift force
obtained in each of the cases, the normalized
maximum uplift force, and the undrained shear
strength is plotted in Fig. 7. Here, the normalized

Model shaft
Case 1Case 2
Case 3
Case 4Disphragm wall
Nodular diaphragm wall
Diaphragm wall
Nodular diaphragm wall

Strength of model
2

ground c (kN/m )Friction at embedded
partWith friction

53

Without friction

maximum uplift force for each case is calculated by
dividing the diaphragm wall model’s maximum
uplift force, Ps, by the nodular diaphragm wallmodel’s maximum uplift force, Pn. It is seen from
Fig. 7 that the maximum uplift force increases as theundrained shear strength increases. This tendency isrepeated in the diaphragm wall model and the modelof the nodular diaphragm wall. From the normalized
maximum strength in the Fig. 7, it is seen that eachof the undrained shear strengths show a value ofapproximately 1.37 to 1.51. From this, it can be said
that when nodular diaphragm walls are used, owing
to the expression of the resistance of nodular part inaddition to the peripheral friction, the heaving
resistance becomes 30 to 50% greater.
CENTRIFUGE MODEL TEST
Summary of Centrifuge Model Test
A centrifuge model test was conducted to verify
the results of the nodular and the diaphragm wall’s
heaving resistance tested in the gravitational field.
Figure 8 covers the overview of the centrifuge
model test. The centrifuge model test was conductedby setting up four test pieces inside a large rigid
model container (Width 1900mm x Depth 800mm x
Height 800mm). The model ground was created by266

GEOMATE - Mie, Japan, Nov. 21-24, 2017using silica sand No. 7 (Gs=2.645) and using the airpluviation method to achieve a relative density of Dr= 82%, and then soaking the bottom side of the rigid
model box in water to saturate the sand. The
peripheral ground’s ground water level is the samelevel as the ground surface. The models used in thisexperiment are the same two shapes as listed in Fig.
5 (diaphragm wall model and the nodular diaphragmwall model), and in a 600mm deep cylindrical modela modified ground layer that is 110mm thick layer
was created. Additionally, for the cases where thefriction is recreated inside, the model was coatedusing silica sand No. 7 to create its roughness. The
cemented improvement ground placed inside themodel used a mixture of silica sand No. 7 and blast
furnace slag cement type B with the target ofachieving undrained shear strength of c=50kN/m2.
The ratio to create the mixture for the modified
ground was decided based on mixing experiments
conducted prior to this stage of the study. Before thecentrifuge model test was conducted, the samematerials from the same batch that were used tocreate the modified ground in order to conduct theuniaxial compression test to verify when it reached
the specified strength. The test was set up to firstreach the predetermined centrifugal acceleration(80G) to then simulate the gradual excavation to
verify the heaving behavior. To recreate the gradualexcavation, the salt water (specific gravity of 1.05)
was gradually drained that was covering thecemented improvement ground in the model. The
measurement item were the uplift displacement on
the surface of the cemented improvement ground,the decrease in the salt water’s water level over the
cemented improvement ground, and the waterpressure of the cemented improvement ground. The
experiment condition is shown in Table 2. The
ground strength stated in Table 2 is the actual
strength at the time of the test.

1.2

Case 1 (Diaphragm wall)
Case 2 (Nodular diaphragm wall)

Uplift displacement (m)

1.0
0.8
0.6
0.4
0.2
0.0

0

5

10

15

20

-0.2
Water level decrese in model shaft (m)(a) Case 1, Case 2（With friction）
3.5

Case 3 (Diaphragm wall)
Case 4 (Nodular diaphragm wall)

Uplift displacement (m)

3.0
2.5
2.0
1.5
1.0
0.5
0.0
-0.5

0

5

10

15

20

Water level decrease in model shaft (m)(a) Case 3, Case 4（Without friction）

Fig. 9 Relationships between Uplift Displacement
and Decrease of Water Surface in Shaft
nodular diaphragm wall, an increase in uplift
displacement is seen once the water level drops by
15 to 16m. From this phenomenon, it can be said
that in the diaphragm wall model, the resistive
element against the heaving behavior is only the
cemented improvement ground self-weight and the
peripheral friction between the cemented
improvement ground and the diaphragm wall model,
the uplift displacement occurred at a relatively lesssignificant drop in the water level compared to the
nodular diaphragm wall. On the other hand, when it
comes to the nodular diaphragm wall, it is said thatsince there was an additional element of resistanceagainst heaving in the form of nodular part, heaving
occurred only after the drop in the water level
became significant. For this examination, it was onlyused the inside of the model’s cemented
improvement ground and considered the existence or
the lack of friction in between the model’s boundary
surfaces as the parameter. It is said that the influenceof the boundary surface’s friction, or lack thereof,

Results of Centrifuge Model Test
Figure 9 shows the relationship between the
uplift displacement and the decrease in the waterlevel. The uplift displacement measured here is theamount of displacement that was measured at thecenter of the modified ground. Furthermore, both the
uplift displacement and the drop in the water levelare organized based on the real-life scale calculated
by multiplying with the magnification of thecentrifugal acceleration (80G). According to Fig. 9,
no significant differences are seen in the diaphragmwall or the nodular diaphragm wall in their uplift
displacement even when the water level starts todrop. However, there is a sudden increase in the
uplift displacement once the water level drops
between 10 and 13m. On the other hand, with the267

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Japan Society of Civil Engineers, Sep. 2010, pp.
507-508 (in Japanese).
[2] Kumagai K, Takahashi M and Abe Y “A Reportof Methods for the Structural Analysis of High
Depth Slurry Wall Supporting the Main Towerof a Suspension Bridge”, Journal of Japan
Society of Civil Engineers, No. 504, VI-25,
Dec. 1994, pp. 43-50 (in Japanese).
[3] Mizuno N, Nagashima M, Makino S and Okada
T “Prevention of Blocking of Tremie for Slurry
Wall Construction”, Concrete Research andTechnology, No. 1, Vol. 8, Jan. 1997, pp. 251265 (in Japanese).
[4] Watanabe K, Nishiyama T Sei H and Ishii Y“Static Axial Reciprocal Load Test of Cast-inplace Nodular Concrete Pile and Nodular
Diaphragm Wall”, Geotechnical Engineering
Journal of the SEAGS & AGSSEA, Vol. 42, No.
2, Sep. 2011, pp. 11-19.
[5] Watanabe K, Sudo T, et al. “Tensile Load Test
and Compressive Load Test of Nodular
Diaphragm Wall Supporting High-rise Tower”,
Proceedings of Annual Conference ofArchitecture Institute of Japan, Sep. 2009, pp.
545-554.

between the cemented improvement ground and themodel have on heaving resistance is small.
CONCLUSION
The modeled experiments to examine theheaving resistance of nodular diaphragm walls todetermine their suitability to be used as the deepshafts for railway structures were conducted. The
following findings are obtained from this study:1) Through the uplift force experiment at thegravitational field is confirmed that when the
nodular diaphragm walls are used for the verticalshafts, there would be an increase in the heaving
resistance due to the resistance of nodular part inaddition to the peripheral friction.
2) It is concluded that in the centrifuge model
test, which reproduces the full-scale stress and strain
fields, that the vertical shafts using the nodular
diaphragm walls had a greater heaving resistance.
REFERENCES[1] Uegaki Y, Sawatari T, Tajin M and Miyaji K“Measurement Result on the Largest Circular
Pneumatic Caisson Method in the World”,
Proceedings of 63th Annual Conference on

268Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

RESEARCH OF DAMAGED CONDITION BY THE 2016 KUMAMOTO
EARTHQUAKE AND GROUND INVESTIGATION ON STONE WALLSAND ERATH STRUCTURES IN KUMAMOTO CASTLE
Satoshi SUGIMOTO 1, Minoru YAMANAKA 2, Hideki MAEDA 3, Naozo FUKUDA 4, Yuuya KATSUDA 1
1
Faculty of Eng., Nagasaki University, Japan; 2 Faculty of Eng., Kagawa University, Japan
3
West Japan Engineering Consultants, Inc., Japan; 4 Fukken Co. Ltd., Japan

ABSTRACT
There are a lot of valuable historical structures with stone wall in Japan. Those structures are still active not
only as roads and waterways, but also are designated as cultural properties, and in some places, they also play animportant role as a tourism resource for the region. However, the current situation is that countermeasures against
disasters are delayed like the damage of Kumamoto Castle due to the 2016 Kumamoto Earthquake. In particular,
it is considered that it is important to elucidate the earthquake disaster mechanism by the interaction between the
ground and the stone wall.
In this research, the tendency of the damage of stone walls and earth structures will be clarified based on thesurvey team of the Geotechnical Engineering Society and the Kumamoto Castle Research Center, and it isdiscussed on the mechanism of collapse occurrence by estimating the geological structure under the several sites
in Kumamoto Castle by surface wave profiling method and so on.
Keywords: Kumamoto Castle, Earthquake disaster, stone wall, earth structure, investigation

hundreds especially. Therefore, the evaluation
method of stone wall and embankment stabilization isrequired from the view of geotechnical engineering
quickly. This paper reports the investigation of
structures’ damaged condition and ground survey
around damaged stone walls in Kumamoto Castle
after that earthquake with cooperation of Kumamoto
Castle Research Center and the survey mission ofJapan Geotechnical Society.

INTRODUCTION
A lot of historical and valuable stone structurescontinue using for hundreds of years in Japan. These
structures have valuable roles as regional tourism
resources with registration for cultural heritage andpractical usage. Almost structures degraded with age,
it is necessary to do maintenance and repair work.
However, it is difficult to do them because
mechanical evaluation method is never establishedfrom an engineering perspective, and information andreferences are not sufficient about these structures.
Some researchers investigated on the stone walls
and embankment in Kumamoto Castle and so on.
Kuwahara carried out to survey stone walls of
Kumamoto Castle about 30years ago [1]. Hecollected the data of surface shape on stone walls by
surveying tool. These data will be basic and importanton comparison of current cross-sectional shape.
Yamanaka et.al. carried out to survey embankment ofseveral traditional castles by microtremor in Japan[2][3]. They tried to clarify the distribution of
unstable area under the ground surface. It is expectedthat this method will be able to estimate the intricate
geological structure with broken stone, embankment
and original ground.
The 2016 Kumamoto earthquake gave hugedamage for several structures in Japan. Kumamoto
Castle was also damaged on architectural structures,stone wall, embankment and so on. The number ofdamaged stone walls and embankment is over

CHARACTERISTICSOF
KUMAMOTOCASTLE AND OVERVIEW OF GEOLOGIAL
STRUCTURE
Kumamoto Castle was constructed by Kiyomasa
KATO as a domain head in 1607. Fig.1 shows thelandscape around the castle before construction insecond hand of sixteenth century [4]. There is Mt.
Chausu-yama in center of this picture map, and thismountain was shaped a southern part of Uekitableland at an altitude about 50 meters. There is ascattering of erosional valleys surrounding here
shown in Fig. 2 because an ignimbrite layer exists
under the ground surface with humid climate [5].
Fig. 3 and 4 show the geological cross-section
based on the past boring survey in the Kumamoto
Castle [6]. There are only 12 boring data collections
around northern part of the castle tower surveyed in
1958 or 2015. Developed land material and volcanic
cohesive soil that N Value is around 10 constitute theground from the surface to 10meters depth. Volcanic
269

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 1 Picture map of landscape before constructing
Kumamoto Castle. [4]cohesive soil that N Value is under 20 and weathering
tuff breccia exist above 50meters depth. The andesite
bedrock that N values is over 50 was confirmed under
50meters depth. Fig.4 shows extreme changes ofgeological structures on the bedrock and the
pyroclastic flow layer with the large eruption at Mt.
Aso before ninety thousand years (hereinafter called“Aso4”) within just 50meters interval. Furthermore,
the reports of 2015 boring survey fingered theexistence of discontinuous surface under the castle
caused by Tatsuta-gawa geologic fault in northernpart of these area. It is estimated that resistance offoundation ground with stone wall and embankmentin the castle for huge earthquake because mainly
extending Aso4 has low N value under the castle’ssite.
GROUND DEFORMATIONMONITORING DATA

BASED

Fig. 2 Topographical structure around Kumamoto
Castle. [5]ON

Fig.5 shows the results of 2.5dimensional analysis
with Interferometric Synthetic Aperture Radar by
Geospatial Information Authority of Japan [7].
Kumamoto Castle is about 9km east of earthquake
center on main shock of the 2016 Kumamoto
Earthquake. It is estimated that the deformation ofground surface is 10cm subsidence and 30 to 40cm
movement to east direction. Fig.6 shows the groundsettlement in center of the Kumamoto city andKumamoto Castle calculated by altitude correction
software “PatchJGD” released from Geospatial
Information Authority of Japan. This calculation
results shows about 20cm settlement in this area.

Fig. 3 Distribution of N value under the site ofKumamoto Castle. [6]Kumamoto Earthquake. Authors especially focusedon the damage condition of stone wall andembankment in this report.
Fig. 7 shows the location of damaged stone wallaround the castle tower, and Photo 1 shows thedamage conditions. The JGS disaster investigatingteam confirmed the following damages in the whole
site of the castle; collapse and destabilization of stone

REPORT OF DISASTER INVESTIGATION ON
DAMAGED STRUCTURES
Site Investigation
Several stone walls, embankments andarchitectural structures were affected by the 2016
270

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 4 Geological structure under the tower of Kumamoto Castle. [6]Fig. 5 Ground surface deformation by the 2016 Kumamoto earthquake. [7]walls, slope failure and surface settlement ofembankment and crash of architectural structures.
Fig.8 shows the distribution of damaged stone
wall locations, collapse areas, maximum stone
movements and directions. It is not clarified thatdamage scale has causal relation between with height,
gradient, width and direction of each stone wall.
Fig. 9 shows the relationship between the
maximum stone movements and directions ofdamaged stone walls in the Honmaru area with thephotos by UAV and CAD’s plan views. There are a
lot of cases that data of stone wall movement in northsouth direction are more than the cases in east-west
direction. And it is confirmed that maximum
movement distance is also longer than in these cases.
It is estimated that ground vibrational characteristic
under this site has a huge effect because stone walls

Fig. 6 Ground settlement in center of Kumamoto
City and Kumamoto Castle.
271

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 8 Collapse area and Stone movements ofdamaged stone walls in the Honmaru area.

Fig. 7 Distribution of damaged stone wall andembankment.
almost construct equally in the direction of north,south, east and west.
Fig. 10 shows the relationship between the heightof stone wall and maximum movement distance. It is
confirmed that each parameter has almost linear
relation in whole tendency. These results indicate thatthe more ground investigation of this field will be
important on the foundation ground of stone wall andstrength of embankment for reconstruction in near
future.
Surface wave exploration
Surface wave exploration was carried out by using thehigh precision surface wave exploration equipment(McSEIS-SXW) in order to discuss on influence acompaction or depth of surface layer for the damageof stone walls. Vibration by hammering interval was
2m and geophone interval was 2m as receiving points.
In total 24 seismograph sensors were used. To makeFig. 9 Relationship between maximum distanceand direction.

Photo 1 Damaged stone wall and embankment in Kumamoto Castle272

GEOMATE - Mie, Japan, Nov. 21-24, 2017

good surface connection, the geophones were
properly installed in the ground.
Fig. 11 shows survey lines of Surface wave
exploration at Heizaemon-maru of Kumamoto Castle.
6 measuring lines are located in a reticular pattern.
Fig. 12 shows situation of surface wave prospection
at line 6 of Heizaemon-maru.
Fig. 13 shows the distribution of analyzing resultsof S-wave velocity at line 2 and 4. It is estimated that
Aso-4c layer with under Vs=240m/sec Vs and Aso4s layer with Vs=240–300m/sec locate withindeterminate undulation across a depth of about 8m.
Fig. 14 shows the distribution of N-value
calculated from Vs. N-value is calculated by thefollowing equation [8].

Fig. 10 Relationship between maximum stone
movement distance and height of stone wall.

N＝(Vs/97)0.314
(1)
here,
N: N-value by the standard cone penetration test
Vs: Surface wave velocity by surface wave
prospecting (m/sec）

amplification of vibration with earthquake forbuildings and structures.
CONCLUSION
The 2016 Kumamoto earthquake caused hugedamages for several structures in Kumamoto Castle.
These structures almost have high value as cultural
assets with past time of about 400years. Hundreds ofstone walls and embankments were also damaged orcollapsed with the massive earthquake.

Fig.11 Survey lines of Surface wave exploration at
Heizaemon-maru

Fig.12 Situation of Surface wave exploration atline 6

Depth (m)Depth (m)There is the loosen embankment layer that N-value
is about 2 above a depth of 2m. Aso-4c layer has Nvalue that is from 2 to 8 above a depth of 8m. And
Aso-4s extends with N-value from 10 to 25 under the
Aso-4c layer.
This result indicates that these soft ground gives

Distance (m)Distance (m)(a) Line-2(b) Line-4

Fig. 13 Distribution of surface wave velocity Vs
273

Depth (m)Depth (m)GEOMATE - Mie, Japan, Nov. 21-24, 2017

Distance (m)(b) Line-4

Distance (m)(a) Line-2
Fig. 14 Distribution of N-value
This investigation carried out with the limited
information of ground and geology under the
Kumamoto Castle because the boring survey has
minimally suppressed due to subsistent as a cultural
asset before the earthquake. Therefore, the collectionof past limited boring data, site investigation and themethod of estimation on geological structure and soil
characteristic were combined, and the following
results were clarified in this study.
1) There were more cases that stone walls
collapsed in north-south direction compared with thecases in east-west direction. This result indicates thatthe more ground investigation of this field will be
important on the foundation ground of stone wall andstrength of embankment for reconstruction in near
future.
2) It is clarified that the Kumamoto Castle wasconstructed on the Aso-4 centered volcanic soil layerswith low N-value. This result indicates that these soft
ground gives amplification of vibration withearthquake for buildings and structures.

Nippon Institute of Technology, 14-2, 1984,
pp.59-74 (in Japanese).
[2] Yamanaka M., Nishiwaki D., Koizumi K. andHasegawa S. “Detection of dynamic unstable
point of stone wall at Kochi Castle bymicrotremor”, Proceedings of 50th Annual
Conference of Japanese Geotechnical Society,2015, pp. 203–204 (in Japanese).
[3] Yamanaka M., Ishigaki H., Koizumi K.,
Hasegawa S. and Araki H. “Extracting method of
deformed part by microtremor on stone walls ofJapanese traditional castle”, International Journalof GEOMATE, 2017, Vol.13, Issue 35, pp.73- 79.
[4] Totsuka S., “The research of advancement
history on modern bridges in Kumamoto
prefecture”, Doctor thesis of Kumamoto
University, 1999, p. 90 (in Japanese).
[5] Geospatial Information Authority of Japan,“Active fault under urban area in Japan”,
http://www.gsi.go.jp/bousaichiri/active_fault.ht
ml，2016 (in Japanese).
[6] Kumamoto Castle Survey and Research Center,“The report of outsourcing geological survey forevaluation of seismic capacity on Uto tower inKumamoto Castle”, 2016 (in Japanese).
[7] Geospatial Information Authority of Japan,“ Information of the 2016 Kumamoto
Earthquake”, http://www.gsi.go.jp ，2016 (inJapanese).
[8] Imai, T. and Tonouchi, K. “Correlation of Nvalue with S-wave Velocity and Shear Modulus”,
Proceedings of the Second European Symposium
on Penetration Testing, 1982, pp.67-72.

ACKNOWLEDGEMENTS
The authors gratefully appreciate a lot support andunderstanding for this investigation from all officersof Kumamoto Castle Survey and Research Center
after shortly after the 2016 Kumamoto earthquake.
And our gratitude extends to all cooperators of thisinvestigation with several instruments andinformation.
REFERENCES[1] Kuwahara F., “The gradient of the stone walls in
Kumamoto Castle”, Report of researches /274

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ESTIMATION OF INITIAL GROUND CONDITIONS UNDER STUPAS
BASED ON ONE-DIMENSIONAL CONSOLIDATION THEORY
Yuko Ishida1, Ayaka Oya2, Chaweewan Denpaiboon3, Masamitsu Fujimoto4 and Ryoichi Fukagawa4
1
Research Organization of Science and Engineering, Ritsumeikan University, Japan;
2
Graduate School of Science and Engineering, Ritsumeikan University, Japan;
3
Faculty of Architecture and Planning, Thammasat University, Thailand;
4
Department of Science and Engineering, Ritsumeikan University, Japan
ABSTRACT
Many stupas located within the sacred historical site of Ayutthaya, Thailand are inclined. It is important tounderstand their ground conditions and causes of inclination in order to design appropriate conservation
countermeasures for these precious cultural assets. Soil investigations were conducted at four points around theinclined stupa of Wat Krasai, located outside the World Heritage Site ”Historic City of Ayutthaya” in 2013 and2016. Three key soil layers appear to be responsible for the inclination of this stupa: the second soft clay layer,
the third loose silty sand layer, and the fourth hard clay layer. The inclination of this stupa increased as the
thickness of the second soft clay layer. Thus, we assumed that the cause of stupa inclination and disproportionate
settlement of the stupa was only the second soft clay layer. The amount of settlement and the initial void ratio of
this second layer were estimated using the consolidation calculation formula based on Terzaghi's onedimensional consolidation theory. The results of this study indicate that the amount of settlement is not exactly
proportional to the thickness of the second soft clay layer, or that the void ratio is inhomogeneous in the layer.
Calculation is conducted in four directions, north, south, east and west, and the maximum settlement and theinitial void ratio of the second soft clay layer are estimated at approximately 6.9 m and between 1.46 and 2.48 at
the north side of the stupa, respectively.
Keywords: Consolidation, Differential settlement, Void ratio, Inclined cultural assets,
inclined at an angle.
In this study, we focus on the causes underlying
the inclination of stupas, which are in need ofconservation. Research was carried out on theleaning stupa of the Wat Krasai temple (indicative of
Sukhothai influence), located within the World
Heritage expansion planning area, with thepermission of the 3rd Regional Office of Fine Arts.

INTRODUCTION
The Phra Nakhon Si Ayutthaya Historical Park is
located 86 km north of Bangkok, and is surroundedby three rivers: the Chao Phraya, Pa Sak, andLopburi. This park is one of the most famous World
Heritage Sites in Thailand, attracting around one
million visitors every year. This important historiccity was registered as a UNESCO World Heritage
Site in 1991, and encompasses a total area of 289 ha.
The Kingdom of Ayutthaya included one of thelargest cities in Southeast Asia, and was animportant regional power for 417 years, between
1350 and 1767. During the 16th century, thiskingdom encompassed present-day Laos, Cambodia,
and Myanmar. Three palaces and more than 400
temples were built during this time. Many of thesestructures, however, were subsequently almost
completely destroyed by Burmese invaders. Manysurviving ruins have been painstakingly restored,
and two kinds of architecture are visible in
Ayutthaya. The first of these comprise cactus-shaped
obelisks called prangs that are indicative of Khmer(from the 9th to the 13th century) influence, while thesecond are more pointed stupas that exhibit
Sukhothai (from the 13th to the mid-15th century)
influence. Because stupas consist of weathered
bricks, some of them have collapsed, and many are

Ayutthaya
Bangkok

Google earth

The Ayutthaya
Historical Park
Wat Krasai

Google map

Fig. 1. Location of Ayutthaya and Wat Krasai
PRAVIOUS STUDIES AND OUR STUDYOBJECTIVE
Severalstudieshave
been
conducted
investigating the weathering conditions andrestoration of cultural assets made of brick,275

GEOMATE - Mie, Japan, Nov. 21-24, 2017

including the stupas in Thailand. For example,
Hatanaka et al. (2013) surveyed the weathered brickstupas at Wat Som and Wat Chaiwatthanaram within
the Ayutthaya Historical Area, and developed arestoration method that uses a surface toughening
agent [1]. Kuchitsu (1998) surveyed stones used tobuild historic monuments in Thailand, andconcluded that salt efflorescence and biodeterioration were the causes of brick deterioration[2].
Fujii et al. (2015) monitored the inclined stupa at
Wat Langkhakhao using photogrammetry, andconfirmed that there was no deformation over thecourse of approximately 2 years [3]. The National
Research Institute for Cultural Properties, Tokyo,
investigated the 2011 flood damage of culturalproperties in the Ayutthaya Historical Park, and theyreported that the 2011 flood did not impact the
inclination of these properties [4].
The famous Leaning Tower of Pisa is constructedon three formations. In the past, the cause of creep
had been widely attributed to the underlying softsensitive marine clay, which is normallyconsolidated. This marine clay is the second layer
extending from a depth of 10 m to about 40 m
underground. The precision level measurements,
which commenced in 1928, revealed the rotation of
the tower based on the fact that the center of thefoundation plinth had not been displaced verticallyrelative to the surrounding ground. The cause of thecontinual long-term rotation of the Tower lies in thefirst layer. In addition, the most likely cause of the
progressive seasonal rotation was a fluctuating
ground-water level due to heavy seasonal rainstorms[5]. These studies showed that the inclination of theTower had multiple causes.
Our project team comprises researchers fromThammasat and Ritsumeikan Universities. We
attempted to conduct two studies under thecircumstances we are in the lack of accurate
information on stupa construction, groundconditions, soil composition, and groundwater levels.
Chijiwa et al. (2015) analyzed two cases in
Ayutthaya using boring data of the other place in
Ayutthaya prefecture, the first of which anticipatedthe occurrence of two floods over the next 100 years,
while the second anticipated no flooding, andsubsequently compared the two results after 100
years. The result showed that the stupa are not likely
to sink rapidly by floods [6]. Ishida et al. (2016)
tried to reproduce the current inclined conditions
using a consolidation analysis, working with theassumption that the inclination was caused only due
to an imbalance in the stupa weight. The results
showed that the cause of inclination does not depend
only on the imbalance of stupa weight [7].
It is possible that the inclination of the stupa may
have multiple causes, as in the case of the Leaning
Tower of Pisa. However, in this study, we planned

to first attempt to reproduce the current inclination
using consolidation analysis from the time of
construction of the stupa, assuming that the uneventhickness of the soft clay layer is the cause forinclination. Because physical properties of the soil
are change before and after consolidation in general,
we have to estimate initial soil parameters. In thisstudy, the methodology of estimating the initial void
ratio, which is one of the parameters forconsolidation analysis, based on one dimensional
consolidation theory is described. The uneven layer
thickness and slope angle of the stupa was used in
the estimation.
OVERVIEW AND INCLINATION ANGLE OF
THE STUPA AT WAT KRASAIThe Wat Krasai site is a long rectangle in theeast-west direction. The temple was destroyed andonly the stupa remains. The direction of front of the
stupa is rotated approximately 8° from east to north.
The stupa consists of several parts, an eight-sided
pyramid and conical body with a multi-layered
structure. This entire structure is hollow, with anapproximate height of 27 m and an approximate
foundation diameter of 22 m. The stupa is bent, andthe inclination of the top and bottom were different,
and the base is tilted much more than the head.
Fig. 2 and Fig.3 show the stupa before and after
restoration. Before restoration work, the base part ofstupa was in a state filled under the ground. Thus, it
indicates that the stupa sank below the surrounding
ground. The foundation of stupa was excavated, andthe octagonal and bottom quadrangular bases wereadded using a lot of bricks for reinforcement.
Additionally, surrounding wall and base of temple
was reconstructed.

Stupa
Before repair（Google earth 2010.3.20 shooting）
Wall
Stupa

After repair（Google earth 2013.2.20 shooting）
Fig.2. Wat Krasai before and after restoration work
276

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Inclination toward to right is shown in plus andinclination toward to left is shown in minus. Data
show that the northern side of the Wat Krasai stupa
is the most sunken, followed by the eastern side.
SOIL INVESTIGATION
Standard Penetration Test at 4 points

Before restoration

The topography of the Bangkok plain reflects thefact that it was covered by a shallow marine sea
from 3000 to 1000 B.C. Soft clay was deposited in
the shallow waters near the shore, and which it isspreading to Ayutthaya [8]. In order to identify
ground composition, soil investigations were carriedout around the stupa at Wat Krasai. Standard
penetration tests (SPTs) at Bor-1 and Bor-2 (shownin Fig. 5) were conducted by the government ofThailand in March 2013, and we carried out
additional SPTs at two survey points within Bor-3
and Bor-4 in March 2016.

After restoration

Fig.3. Stupa before and after restoration work
The restoration work was carried out on the
missing part of the octagonal body, which was
below the bell shape in 2013. The entrance of the
stupa was closed using bricks, except for small
windows on the body in four directions. We
observed the internal structure of the small open
windows on four sides, and confirmed that the
inclination angle of the original bricks and the bricks
added during restoration has harmonic relation.
Therefore, the inclination of the bricks on thesurface of the body can be considered the same as
the inclination of the bricks before restoration. The
inclination angle of the stupa was obtained bymeasuring the inclination of the bricks at the yellow
and white lines (shown in Fig. 4), using a digitalclinometer. Table 1 shows inclination angle
measured at 3 points which are the left side, center,and right side in each face.

Stupa
Bor-2
Bor-3

Bor-4

Bor-1

Fig.5. Four points of soil investigation
Relationship between the key soil settlement layerand stupa inclination
We produced four cross-section drawings (Figs.
6–9) of northern side, southern side, eastern side andwestern side, using data from our soil investigations.
Layer thicknesses were prorated by distance fromboring points. These drawings illustrate the presenceof three key settlement layers. Of these, the second
and third layers are soft, while the fourth is hard.
This is illustrated in Fig. 6, where the second
layer, a very soft-to-medium stiff clay layer, is muchthicker on the northern side than the southern side,and the third layer, a loose-to-medium dense silty
sand layer, is also much thicker in the north. In
contrast, the fourth layer, a stiff-to-hard clay layer, ismuch thicker on southern side than the northern side,and it seems to support the stupa. Viewed fromwest-to-east, the top of stupa is inclined at 2.4°, andthe body is inclined approximately 2° to 11° towards
the north.
The other orientations are analyzed in the sameway, and plotted the difference of the soft layers

Fig.4. Inclination measuring station
Table 1. Inclination angle in each face
Direction
North face
NorthWest face
West face
SouthWest face
South face
SouthEast face
East face
NorthEast face

Inclination angle (degree)
Yellow line
White line
Left Center Right
Left Center Right
2
0
-3
2
0
-1
-7
-9
-9
-3
-7
-7
-3
-8
-11
-2
-9
-7
-9
-9
-9
-7
-7
-7
-4
-3
-4
0
0
0
-2
0
0
2
1
0
1
1
0
0
5
1
0
1
2
5
5
5

277

GEOMATE - Mie, Japan, Nov. 21-24, 2017

thicknesses at the both end sides of the stupa base
part as well as the degree of inclination (Fig.10).
Results showed that inclination of the stupa
correlates roughly with thickness of the soft layers.
ESTIMATION OF INITIAL VOID RATIO
We assumed that the cause of stupa inclination
due to disproportionate settlement of the stupa were
only the second soft clay layer.

2-11°

Fig.8. Cross-section drawing of southern side

Fig.6. Cross-section drawing of western side

Fig.9. Cross-section drawing of northern side

Fig.10. Correlation of layer thickness and inclination

Fig.7. Cross-section drawing of eastern side278

GEOMATE - Mie, Japan, Nov. 21-24, 2017

In addition, the amount of settlement due toconsolidation and the initial void ratio of the second
soft clay layer were calculated using the unevenlayer thickness, inclination angle of the stupa, andEq. (1) based on one dimensional consolidation
theory.
∆(m), S2 refers to the amount of settlement of thicklayer at the end of the stupa (m), H1 refers to theinitial thin layer thickness at the end of the stupa(m) , H2 refers to the initial thick layer thickness at
the end of the stupa (m) , h1 refers to the current thinlayer thickness at the end of the stupa (m) , h2 refers
to the current thick layer thickness at the end of the
stupa (m), and  is the inclination angle of the stupa.
S1, S2, and e0 were calculated using Eq. (2) and (3)in each directions, north, south, east, west faces.
These values are based on the conditions that theinitial void ratio of the soft clay layer at both sides ofthe stupa, differential of the current layer thickness
at both sides of the stupa, and settlement differences
at both sides of the stupa are the same in each case.

(1)

In this expression, S refers to the amount ofsettlement due to consolidation (m), H is the initial
thickness of the soft clay layer (m), e is current void
ratio (0.62 based on our soil tests), and e0 is theinitial void ratio.
We focused on the difference in layer thickness
and the amount of settlement at both ends of the
stupa. It was assumed that ground level was
horizontal when the stupa built. However, adifference in settlement had occurred over a long
period time, caused by the weight of the stupa. It is
assumed that the inclination of the stupa is equal tothe amount of differential settlement at both ends ofthe stupa as shown in Fig. 11. In this figure, B refers
to the width of octagonal base part, and  is theinclination angle of the each faces of the stupa. Thishypothesis follows Eq. (2), (3), (4), (5), (6), (7).

RESULTS AND DISCUSSION
The results of settlement amounts, S1 and S2, as
well as e0 based on maximum inclination angle ofeach faces are shown in Table 2. As the same way,
the inclination angle of 3 cases, average angle,
yellow line measurement average angle, white line
measurement average angle, were used for
calculation. Figure 12 shows settlement amounts in
4 orientations, North, West, South, and East. The
maximum settlement amount was estimated 6.90m
at western side.
We estimated the initial void ratios in eachorientations based on the maximum measurement
angle to be within the range of 1.46 to 2.48 as shownin Fig.13. The value of results are in the range ofgeneral soft clay.
This estimation method includes some problem,for example in the case of little amount of differenceof subsidence. We estimated the inclination angle bymeasuring on the body bricks. However, because
bricks are not perfect shape, the bricks which
consists the stupa wall have some minor deviations.
In addition, because the inclination is different
between top and bottom of the stupa, it is important
to decide where sites as the measurement location.



H1

h1

h2

H2



ΔS

S2

S1

Initial ground levelFig.11. Degree of inclination
,

(2)

,

(3)
(4)

∆ , ∆
∆

Table.2. Results of the consolidation settlement
calculation based on the maximum inclination angle

(5)

∙

(6)
∆

(7)

In this expression, S1 refers to the amount ofsettlement of the thin layer at the end of the stupa
279

North

West

South

East

h 1(m)

3.28

2.87

3.28

2.87

h 2(m)

4.90

6.00

4.90

6.00

θ (°)

3.0

11.0

4.0

5.0

B (m)

18.50

18.50

18.50

18.50

ΔS (m)

0.97

3.60

1.29

1.62

S 1(m)

1.96

3.30

2.62

1.48

S 2(m)

2.93

6.90

3.91

3.10

H 1(m)

5.24

6.17

5.90

4.35

H 2(m)

7.83

12.90

8.81

9.10

e

0.62

0.62

0.62

0.62

e0

1.59

2.48

1.91

1.46

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ACKNOWLEDGEMENTS
We thank the 3rd Regional Office of Fine Arts
and the Ayutthaya Historical Park for theircooperation and provision of information.
Additionally, we would like to thank Dr.
Damrongsak Rinchumphu of Thammasat University,
Assistant Professor Weerakaset Suanpaga, and Mr.
Chalermchai Trakulphudphong of Kasetsart
University for helping with the soil investigations.
REFERENCES[1] S. Hatanaka and T. Hasegawa,” Challenge forconservation technique of cultural assets - brickstructure-“ , Concrete Technology, Vol.51(1),2013, pp.132-136, (in Japanese).
[2] N. Kuchitsu,” Survey Report on the Stones andTheir Weathering at Historic Monuments in
Thailand”, Conservation Science, No.37, 1998,
pp.59-68, (in Japanese).
[3] Y. Fujii, K. Watanabe, U. Weesakul, N.
Poovarodom and B. Bhadrakom, “Measurementof leaning stupas and ground condition in
Ayutthaya, Thailand”, Proceedings of 50th
Japan National Conference on GeotechnicalEngineering, Hokkaido, Japan, 2015,(inJapanese).
[4] National Research Institute for Cultural
Properties, Tokyo, ”Report on the investigationsof the flood damage of cultural properties in the
Ayutthaya Historical Park”, 2012, pp.1-47.
[5] John B. Burland, Michele B. Jamiolkowski,
Carlo Viggiani, ”Leaning Tower of Pisa:
Behavior after Stabilization Operations”,
International Journal of Geoengineering Case
Histories, Vol.1, Issue 3, pp.156-169.
[6] S. Chijiwa, A. Oya, Y. Ishida, Y. Toyota, M.
Fujimoto and R. Fukagawa, ”The effect of floodon the differential settlement of the pagoda in
Ayutthaya”, Journal of Disaster Mitigation for
Historical Cities, Vol.9, 2015, pp.17-24, (inJapanese).
[7] Y. Ishida, S. Chijiwa, A. Oya, C. Denpaiboon,
D. Rinchumphu, Y. Toyota, H. Kanegae, M.
Fujimoto and R. Fukagawa (2016), ” STUDYON INCLINATION OF PRANG AT
AYUTTHAYA, THAILAND”, Proceedings of
the 6th Vietnam/Japan Joint Seminar on
Geohazards and Environmental Issues, 2016,
No.S2-5.
[8] Suksun Horpibulsuk, Satoru Shibuya, Kittitep
FuenKajorn, and Wanchai Katkan, “Assessmentof engineering properties of Bangkok clay”,
Canadian Geotechnical Journal, Vol.44, (2),2007, pp.173-187.

Fig.12. Amount of settlement in 4 orientations

North West South East

Fig.13. Initial void ratio (e0) in 4 orientations
CONCLUSION
The settlement due to consolidation under the
Wat Krasai stupa was analyzed in this study basedon a soil investigation. The result of the soil
investigation shows that it is possible that three key
layers are responsible for the inclination of thisstructure, a second soft clay layer, a third loose silty
sand layer, and a fourth hard clay layer.
We calculated both the amount of settlement andthe initial void ratio of the second soft clay layer.
Results indicate that maximum settlement wasapproximately 6.9 m at the northern end of the stupa,
while the initial void ratio falls between 1.46 and2.48. In the future, consolidation analysis of a model
including all soil layers will be required to determine
the additional settlement details, and to consider the
influence of the other layers.

280Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

AN EXACT FINITE ELEMENT MODEL FOR AXIAL LOADED PILEIN MULTILAYERED SOIL
Chinnapat Buachart1, Chayanon Hansapinyo1, Piti Pratomkhum1 and Worsak Kanok-Nukulchai2
1
Faculty of Engineering, Graduate School, Chiang Mai University, Thailand
2
Asian Institute of Technology, Thailand

ABSTRACTThe nodal exact displacement based finite element method for analyzing axially loaded pile embedded in multilayered of finite depth of elastic soil is presented. The investigation herein is conducted on the condition of shapefunction by which exact value may be reproduced at the nodal points regarding to a few number of elements. The
examined shape functions which satisfy the homogeneous governing equations in each layer of elastic soil are
introduced to obtain the so-called exact element stiffness matrix via total potential energy principle. The results
obtained from proposed finite element were compared with analytical solution from literature. Axial force anddisplacement solutions of pile in multi layered soil obtained from proposed finite element model show fairly good
agreement with analytical solutions and data from the available literatures.
Keywords: Axially loaded pile, Displacement method, Finite element, Multilayer soil

isotropic material, with elastic properties describedby soil shear modulus Gsi and Poisson’s ratio si. The
vertical depth from the ground surface to the bottomof any layer i is denoted by Hi. Hence, the thicknessof each layer Li is computed by Hi – Hi –1 with H0 = 0.
The pile is assumed to behave as an elastic column
with Young’s modulus Ep. The Poisson’s ratio of thepile material is neglected.

INTRODUCTION
In this study, the displacement of axially loaded
pile embedded in multi-layer soil is solved via
proposed finite element procedure. The nodal exact
shape function concept suggested in [1]–[4] are used
to construct the stiffness matrix and equivalent nodal
force incorporate with fixed-point iteration algorithm
to solve nonlinear algebraic equations. In each
iteration step, the coefficients of differential equation
describe pile settlement behavior were estimatedeasily via component of stiffness matrix and nodal
displacement obtained from previous iteration step.
Examples of elasto-static pile embedded in
multilayered soil subjected to quasi-static point loadon top soil level were analyzed [5]. The results fromproposed element are compared with analyticalsolution obtained from [6] to verify the accuracy of
proposed pile element.

Governing Differential Equations
Since the cylindrical pile settlement problem inFig. 1 is axisymmetric. Hence, we use the system ofcylindrical coordinates (r-z coordinate) to indicate
any position in pile and soil bodies. The origin of
cylindrical coordinate coincide with the center of pilecross section at the pile head level. The vertical(positive in downward direction) coordinate z-axis iscoincide with pile axis. The non-slip conditions
between pile surface and surrounding soil andbetween soil layers are assumed. The verticaldisplacement uz(r,z) at any point in the soil isrepresented as product of two functions in r and z
coordinates as follows:

MATHEMATICAL FORMULATION
Problem Definition
The analysis considers a single circular crosssection pile [5], with radius rp and total length Lp
embedded in a total of N horizontal soil layer (Fig. 1).
The pile is subjected to an axial force Qt at the pilehead which is flush with the ground surface. The pileitself crosses m layers (m < N). All soil layers are
assumed to extend to infinity in the radial direction,and the bottom layer (Nth layer) also extends toinfinity in downwards direction (half-space) as shownin Fig. 1. The soil medium in any layer (ith layer,
where i = 1,…,N) is assumed to be elastic anduz  r, z   w z    r (1)

where w(z) is the vertical displacement of pile at any
point along pile axis, and (r) is the soil displacement
decay function in the radial direction.
Then, the calculus of variations are used to obtain
the governing differential equation in pile andsurrounding soil by define the strains fromdisplacement functions in Eq. (1), and prescribe the281

GEOMATE - Mie, Japan, Nov. 21-24, 2017variation of total potential energy with respect to w
and  equal to zeros [6]. The governing differential
equation for the pile and soil below the pile tip is asfollow:

  Ei Ai  2ti 

d 2 wi ksi wi  0
z 2

is a zero order modified Bessel function of the second
kind:

(2)

where Ei = Ep and Ai = Ap when 1  i ≤ m (along pileaxis), and Ei = si + 2Gsi and Ai = rp2 when (m + 1)
 i < N (soil below the pile tip). The elastic constantsi + 2Gsi is a function of Poisson’s ratio si and shear
modulus Gsi of soil:si  2Gsi 

2Gsi 1  vsi (3)

1 2vsi 

Note that the coefficients ksi, and ti represent the shear
and compressive resistances of soil mass against pilesettlement. Both ksi, and ti are a function of decayfunction  and elastic properties of soil as follow:

Fig. 12

 d 
ksi  2 Gsi  r   dr
rp
 dr  
K0  r r r p ; rp  r   (r )  
K0   r (4)

ti   (si  2Gsi ) r 2dr

(5)

rp

2

(6)

where

r

n
 s
rp
ms

N

ms   Gsi 
i 1

N

Hi

Hi1

i 1

(8)

Hi

(11)

1
ti   rp2  si  2Gsi   2 1
2

(12)



2

 dwi dz
Hi1  dz 

ns   (si  2Gsi )

ksi   Gsi  r2 1  2   2 r 

where the coefficient  is the ratio between themodified Bessel function of the second kind of firstorder K1 and zero order K0, i.e.:(7)

wi 2dz(10)

Substituting decay function (r) into Eqs. (4) and (5),obtain the explicit formula for coefficients ksi and ti interms of modified Bessel function of second kind,zero and first orders [6]:The governing differential equation for the soil
surrounding the pile can be obtained by taking thevariation of total potential energy with respect to 
equals to zero:d 2 1 d   r 
    0

dr 2 r dr  rp Axially loaded pile and multi-layer soil [5](9)K1   r 
K0   r (13)

The general solution of Eq. (2) is given by:wi  z   Bi cosh i z   Ci sinh i z and the solution of Eq. (6) with boundary conditions
(r) = 0 at r extend to infinity, and (r) = 1 at r = rp

282

(14)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

where Bi and Ci are integration constant. The
characteristic parameter i of pile and soil interaction
is expressed as follow:

i 

ksi
 Ei Ai  2ti 

Note that the origin of vertical coordinate along thepile axis in potential function, Eq. (18), is now moved
to the top node of pile portion, instead of pile head on
ground level. The nodal displacement at top andbottom nodes are denoted by w1 and w2, respectively.
Suppose that the pile portion at ith layer is considered,
the pile length can be computed from different ofbottom depth between nearby soil layer, i.e. L = Hi –
Hi-1.

(15)

Note that the dimension of parameter i is inversionof length. An axial force Qi(z) at a depth z in the ith
layer is obtained defined as:

Qi  z     Ei Ai  2ti 

dwi
dz

(16)

or explicitly in the form:

Qi  z   ai  Bi sinh i z   Ci cosh i z  

L

(17)

where ai = i (EiAi + 2ti), the integration constants Bi
and Ci in Eqs. (14) and (17) can be determined
analytically from the procedure proposed in [5].
Finite Element Formulation
Consider one-dimensional element in Fig. 2,
which represents the portion of pile embedded in any
one layer of surrounding soil governed by Eq. (2).
Assuming that soil surrounding pile element is inelastic condition for whole length. Shear resistance ofsoil is represented by equivalent soil springcoefficient ksi. Pile element in Fig. 2 compose of two
nodes at top and bottom, numbering with node 1 and
2, respectively. The total potential energy of this soilpile element subjected to an equivalent nodal forces
P1 and P2 is defined as the sum of internal potential
energy (strain energy) and the external potential
energy due to external load as follow [4]:2L dw    Ei Ai  2ti     dz  ksi  w2 dz 
dz 
2
0
0


Fig. 2

Axially loaded pile element [4]Applying the appropriate Gauss-Green theorem to
Eq. (19) and setting δП = 0, gives the differential
equation for equilibrium similar to Eq. (2), and a setof natural boundary conditions as follows

P1    Ei Ai  2ti 

dw

P2   Ei Ai  2ti 

dw

(20)

dz z  0(21)

dz z  L

L

1

The natural boundary condition at first node, Eq. (20)
is similar to axial load expression in Eq. (16).

(18)

 Pw
 P2 w2
1 1

Interpolation function

where w(z) is the vertical pile displacement at depth z
where 0  z  L. The first variation of Eq. (18) leadsto:To construct the system of algebraic equations
with respect to nodal displacement, the trial solutionof w(z) in Fig. (2) is introduced in the form:w z   w1 N1  z   w2 N2  z L d w  dw dz
   Ei Ai  2ti    dz  dz 
0 
L

 ksi

The shape functions in Eq. (22) are taken fromhomogeneous solution of Eq. (2), i.e.

(19)  wwdz  P w  P  w
1

1

2

(22)

2

0

N1  z  283sinh i  L  z  sinh i(23)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

N2  z  sinh i z sinh iassembled to form global stiffness in Eq. (25).
At the bottom most layer (layer N), the thickness
is assumed to be infinity, and nodal displacement atbottom most point is prescribed to zero. Hence, theelement stiffness matrix in Eq. (28) has to be
redefined. Convergence of hyperbolic function whenL shows that the element stiffness matrix for
Nthlayer is similar with penalty spring coefficient [8]attached to Nth degree of freedom, wN, with thefollowing form:(24)

where the dimensionless parameter βi = iL.
In present work, the proposed finite element
procedure to solve Eq. (2) for a given load Qt (Fig. 1)
will be explained in next section. Then, the resultsfrom proposed nodal exact element will be comparedwith available analytical solution in [5, 6].
Fixed-Point IterationkNN  aN  N  EN AN  2tN 

According to Eqs. (8) and (9), the shape parameterof decay function, namely r in Eqs. (6) and (7)depends on pile settlement w(z). Hence, the finite
element discretization of Eq. (19) with trial
displacement function in Eq. (22) leads to the steadysteady-state set of non-linear algebraic equations asfollow:

K  w w  f

The convergence of hyperbolic function also showsthat the displacement in Nth layer can be interpolated
via the form below:w z   wN cosh N z   sinh N z  n 1w( n )  f

Calculation of Decay Parameter
The value of decay parameter r in any iteration
step of Eq. (26) can be evaluated from nodal
displacement solution w in each step. Substituting thedisplacement function, Eq. (22), into Eqs. (8) and (9)obtained:(26)

where K(n-1) = K(w(n-1)), n = 1,2,…, is stiffness matrix
evaluated from nodal solution w at previous iteration
step. An iteration is repeated until the value of rconverged. In this work, the convergence criteria are:

 r n    r n1  1052
2
2
Gsi  coth i  i csch i  wi  wi 1  i 1 2i  2w w csch  1   coth   (31)
i
i
i
i
i

1

G
 sN wN22 N
N 1

ms  

(27)

N 1

Note that the convergence criteria used in Eq. (27) issimilar with criteria used in [5, 6].

ns  

i Esi  icsch i  coth i  wi  wi 1  
2

2

2


2 2wi wi 1csch i 1  i coth i  E
+ N sN wN22i 1

Element Stiffness Matrix
Element stiffness matrix in Eqs. (25) and (26) canbe derived from first variation of strain energy termin Eq. (19) by substitute the trial solution w(z) andvariation δw(z) interpolated by the shape functions
proposed in Eqs. (22) and (23). Hence, the stiffness
matrix of layer i can be defined as: coth i cschi Ki  ai cschi coth i (30)

The interpolation of w in Eqs. (22) and (30) are thenused to compute axial force according to Eq. (16).
Note that coordinate z in Eqs. (22)–(30) is local
coordinate defined in ith-layer.

(25)

In which stiffness matrix K is a non-linear function of
nodal displacement w. The external nodal load f ispresented in term of specified vector. The nodal
solution w is obtained by solving an algebraic
equation via fixed point iteration technique [7]:

K

(29)


 (32)where E si  si  2Gsi , the values ms and ns are thenput into Eq. (7) to compute the parameter r.
NUMERICAL EXAMPLESIn this section, two numerical examples arepresented to illustrate the effectiveness of nodal exact
finite element proposed in previous section. Resultsfrom proposed element are verified using analyticalsolutions available in [5, 6].

(28)

where parameter ai was already defined in Eq. (17).
The element stiffness matrices in Eq. (28) are284

GEOMATE - Mie, Japan, Nov. 21-24, 2017

figures show that there is very good agreement
between proposed finite element and analyticalsolution in literature [5].

Pile with Ideal Rigid End Bearing
In this example, we study the behavior of pile inhomogeneous soil (one layer) subjected to pile headload as shown in Fig. 3. The ratio between pile elastic
modulus and soil shear modulus is set to be Ep/Gs =3000, and Poisson’s ratio vs = 0.4999. The pile tip isassumed to rest on a rigid layer and pile diameter B =2rp = 0.2 m. Note that this problem was alreadysolved in [6], and repeat hear to verify our proposed
finite element model.

Pile rest on rigid baseNormalized pile head stiffness, KN

0.08

0.075

Present study
Seo and Prezzi [5]
0.07

0.065

0.06
25

50

75

100

Normalized pile length, Lp/B

Fig. 4
Normalized pile head stiffness versus
normalized pile length of rigid-end pileFig. 3

Pile rest on rigid layer [6]Figure 4 shows relation between the normalized
pile head stiffness KN versus normalized pile length
Lp/B. The normalized pile head stiffness is defined as
KN = Qt/(w0EpB) where w0 = settlement at pile head.
The plot in Fig. 4 were obtained with the finite
element analysis proposed in this work and fromanalytical method in previous study [5]. The
normalized pile head stiffness in Fig. 4 decreases withincreasing of normalized pile length. The results offinite element analysis presented in this work is ingood agreement with previous study in [6].

Fig. 5

Soil Profile of Italy case [5]Table 1 Input properties for the analysis of micropile
tested in Italy (B = 0.2 m, Lp = 19 m, Ep = 27 GPa)

Micropile (Italy)
This example present the case of micro-pile, which
was installed in a complex soil profile [6]. The soil
profile and pile length are shown in Fig. 5. Pile
diameter and length are equal to 0.2 m and 19 m,
respectively. Modulus of elasticity of pile isapproximately 27 GPa. In all soil layers, the Poisson’s
ratio was assumed to be 0.3. The values of soil depth,
shear modulus, and Poisson’s ratio of Fig. 5 are listed
in Table 1. The numerical test was performed using
four proposed nodal exact elements with four active
degree of freedom. Figure 6 shows the calculated pilehead settlement versus input pile head load. Figure 7
shows measured and calculated load-transfer curves
for applied load equal to 50, 250, and 500 kN. These

Layer

Hi (m)Gsi (MPa)

νsi

1

12

19.2

0.3

2

19

45.0

0.3

3

21

45.0

0.3

4



53.1

0.3

CONCLUSION
The finite element model for pile embedded in
multilayered elastic soil subjected to axial load is285

GEOMATE - Mie, Japan, Nov. 21-24, 2017

proposed. The nonlinear algebraic equation has beensolved via fixed point iteration. Numerical examples
for static load pile embedded in multi layered elastic
soil were tested by proposed finite element comparewith available analytical solution from literature. Two
problems, composed of pile resting on rigid base, andinfinite bottom depth were solved to obtain pilesettlement and load transfer curves. Numerical test
indicates that the proposed finite element method arevery good agreement with available analyticalsolution proposed in literature.

ACKNOWLEDGEMENTS
The author acknowledge the financial support
received from Thailand Research Fund (NewResearcher Grant TRG5880066).
REFERENCES[1] Tong P, “Exact solutions of certain problems byfinite element method”, AIAA J., Vol. 7, 1969,
pp. 178-180.
[2] Kanok-Nukulchai W, Dayawansa PH, andKarasudhi P, “An exact finite element model fordeep beams”, Int. J. of Struc, Vol. 1, Jan. 1981,
pp. 1-7.
[3] Ma H, “Exact solutions of axial vibration
problems of elastic bars”, Int. J. Numer. Meth.

Load-settlement curve (Italy case)
3

Pile head settlement (mm)2.5

Present study
Seo and Prezzi [5]2Eng., Vol. 75, 2008, pp. 241-252.
[4] Buachart C, Hansapinyo C, and Sommanawat W,“An exact displacement based finite element
model for axially loaded pile”, Int. J. of
GEOMATE, Sept., Vol. 11(25), 2016, pp. 24742479.
[5] Seo, H and Prezzi, M, “Analytical solutions for a
vertically loaded pile in multilayered soil”,
Geomechanics and Geoengineering: An
International Journal, Vol. 2(1), 2007, pp. 51–60.
[6] Seo, H, Prezzi, M, and Salgado, R, “Settlement
analysis of axially loaded pile”, International
Conference on Case Histories in GeotechnicalEngineering, Vol. 27, 2008, pp. 1–8.
[7] Chapra SC, Applied Numerical Methods with
Matlab for Engineers and Scientists. McGrawHill, 2005.
[8] Zienkiewicz OC and Taylor RL, The Finite
Element Method. Vol. I. Oxford: ButterworthHeinemann, 2000.

1.5

1

0.5

0

0

100

200

300

400

500

Load (kN)

Fig. 6

Load-settlement curve at pile head (Italy
case)
Load transfer curve (Italy case)

600

Present (50 kN)
Present (250 kN)
Present (500 kN)
Seo and Prezzi (50 kN)
Seo and Prezzi (250 kN)
Seo and Prezzi (500 kN)

500

Load (kN)

400

300

200

100

0

0

5

10

15

20

Depth (m)Fig. 7
Load-transfer curve for pile head loadequal to 50, 250, and 500 kN (Italy case)286

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

STABILITY ANALYSIS FOR AN AIRPORT EMBANKMENT,EVALUATING SHORT AND LONG TERM TECHNIQUES
1

Ignacio Fructuoso Solís Quispe1, José Carlos Solís Tito2 and Mario Edisson Quilli Apaza3
Faculty of Civil Engineering, Universidad Nacional de San Antonio Abad del Cusco, Perú; 2,3 Universidad
Nacional de San Antonio Abad del Cusco, Perú
ABSTRACTThis article discusses the stability analysis corresponding to the construction project of a runway
embankment over soft clay, to reach the subgrade level, that conform the foundation of the runway No. 16/34,
for the project Aeropuerto International de Chincheros Cusco - Peru (AICC). The safety analysis consists inevaluating the strength reduction of the foundation, considering the effect of the consolidation, for the short term
and long-term construction techniques considering the soil improvement with preloading, vertical geodrains andstone columns techniques. The numerical analysis is developed with the Plaxis 2D v8.6 software, considering atypical section corresponding to a critical sector, located on the km 1+180 progressive of the landing strip.
According to the results of the definitive geotechnical study, the foundation soil, corresponding to the analysis
section, is a saturated soft clay, until a depth of 35 m; then to model its mechanical behavior was used the Soft
Soil Model; and for the embankment, that will be constructed of compacted soil obtained from the ground
cutting process, was considered the Mohr Coulomb model. The physical and mechanical parameters were
established based on the results of field and laboratory test, correlations and referential values established in thespecialized bibliography. From the comparative results based on the calculated safety factors, the stone columns
technique, presents a higher factor of safety compared to the preloading and vertical geodrains techniques; whileconsidering the short-term construction, the foundation soil fails due to loss of strength before reaching the total
embankment height.
Keywords: Stability of Embankment, Numerical Analysis, Stone Columns, Vertical Geodrains.
the central sector (S2) on which the embankment
will be constructed, is considered like a quaternary
deposit of lake origin compound for a sequence offine soils, shaped for silts and organic clays of
medium to high plasticity and typical inorganic soilsof elevated zones [5].

INTRODUCTION
The construction of the embankment for the
runway of the project Aeropuerto Internacional de
Chincheros Cusco - Perú (AICC) will allow to reachthe level of subgrade, which will form the ground offoundation for the subsequent construction of the
runway No. 16/34 (Fig. 1), whose heights vary from
7 m to 13 m according to the site topography [1].

Fig. 2

Fig. 1

Location of runway No. 16/34
Taxiways of the AICC project.

Longitudinal ground profile corresponding
to the runway shaft No. 16/34.

Posterior studies executed [1], concluded that thezone of the central sector of sedimentary origin iscomposed of fine soft soil permanently saturated dueto the accumulation of pluvial water, and mostly
correspond to gypsum in saturated state, which gives
a whitish color to the surface. According to the
USCS, soils are classified as CL, ML and MH.
In the definitive study [8] the longitudinal soil
profile of the runway No. 16/34 is presented (Fig. 3),
and indicates that the soft soils composed of clays
and silts, located between the progressive Km 1+100
to 1+860, with a power of 35m, have weakcompressive strengths lower than 0.25 kg/cm2.

andThe subsurface exploration (trial pits, borings,
drillings) and in-situ testing [5] allowed to identify
the type and the geological formation of the soils in
the zone, standing out its origin of lakebed (centralzone), being this zone an old lake that over time wasfilled with sediments.
In the longitudinal ground profile corresponding
to runway No. 16/34 (Fig. 2), are shown the cut
zones (S1, S3) and fill areas (S2, S4). The zone of287

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Most relevant field and laboratory tests
performed to characterize the soil for the
AICC.
Test

Fig. 3

Geotechnicalparameters
Ground Investigation
Trial pits
LL, IP, Gs
Compaction test
γnat
DPL
N10
SPT
NSPT
Drilling
sampling
Lefranc Test
kx
Piezometershp
Geophysical Investigation
Seismic Refraction
Vp
MASW Test
Vs
MAM TestVs
ERT Test
Ohm-meter
Laboratory Investigation
Sieve analysis
Cu, CcAtterberg limits
LL, IP
UnconfinedSu
compression test
Consolidationeo, Cc, Cr, Pc, Cv
Proctor Compaction
γdmax, CBR
Test and CBR Test
Triaxial UU
Su
Permeability (flexiblekywall permeameter)

Longitudinal soil profile of the runway No.
16/34.

In the present paper the stability analysis
corresponding to the construction of the runway
embankment No. 16/34 on soft clay is developed, ina representative critical section located at Km 1+180[7], onto the soft soil zone described in the definitive
study.
The stability analysis comprises the evaluation of
the embankment construction without ground
improvementcomparedwithimprovement
techniques such as preloading, vertical geodrains
and stone columns [2]. The analysis is developed
numerically using the finite element method, with
the Plaxis 8.6 software, considering a 2D analysis
with a plane strain model [6]. The numericalanalysis provides the results of settlements,
consolidation times, factor of safety (FS) expressedin graphs, corresponding to the process ofembankment construction, comparing indicatedtechniques.
METHODOLOGY
The geotechnical parameters of the materials
were established based on the results of the field andlaboratory tests, correlations and reference values
established in the specialized bibliography related tothe subject. The results of the site investigation
performed in the zone close to the critical section(Fig. 4) allowed to define the soft soil geotechnicalparameters to define the constitutive model for thenumerical analysis.

Fig. 4In the lakebed zones of the profile, theembankment will be formed by filling, with the
cutting materials of the elevated zones, as shown in
the longitudinal profile (Fig. 2), and mainly the soils
correspond to clays with presence of sand, evaluatedwith the Proctor Compaction and CBR test.
The stability and consolidation analysis for theconstruction of the embankment were executed with
the Plaxis 8.6 software. The method for the safetycalculation at each stage of the embankment
construction was the phi-c reduction, using the total
multiplier factor ΣMsf, which represents the factorof safety [6]. For stability analysis it was considered
as a minimum factor of safety FS = 1.3, whichallows to evaluate the maximum stable elevation ofembankment construction.
The consolidation analysis was developed toevaluate soil improvement techniques. For thisanalysis, the application of load was consideredthrough the option minimum excess pore pressure[6], with a value of 5 KN/m2, which is a criterion tofinish the analysis of consolidation, then thecalculation stops when the absolute maximum
excess pore pressure is less than the prescribed value
of |P-stop| [6].

MASW test and trial pits location plan, inthe central zone of the runway No. 16/34.

The definitive study of the project consisted ofthe execution of field and laboratory tests, as shownin Table 1.

288

GEOMATE - Mie, Japan, Nov. 21-24, 2017

For modeling the embankment construction, it
was considered the application of load by means of
the option staged construction [3], which allows
specifying a new state for each increase ofembankment elevation, to be reached at the end of
the calculation phase [6]. To each stage wasspecified a time interval of the calculation phase of 5days, considering the effect of the consolidation, foreach increase of load established by the embankment
elevation. The results corresponding to thesettlements were evaluated at a point located in thecentral zone of the base of the embankment, at the
ground surface.
The stability analysis of the embankment
construction comprises two periods; the firstconsisted in determining the maximum elevation ofembankment construction without considering
improvement techniques, evaluating the stability ofthe embankment by means of the establishedminimum factor of safety; for this period anembankment elevation of 4.5 m was reached. For thesecond period of the analysis the improvement
techniques of the soft soil were evaluated, applying
the improvement techniques elements to thegeometry established by the maximum embankment
elevation stable without improvement techniques(evaluated in the first period). For this latest
geometry, the period of consolidation for the clay
was considered, until a minimum excess porepressure of 5 KN/m2 was reached; and later theembankment elevation was gradually increased
every 1 m, controlling the minimum factor of safety,
until reaching the elevation established by the
project of 9.5m. The results corresponding to thesettlements and duration times for each construction
technique are compared, and allow establishing theadvantages of the improvement techniques.
For the geometric model of the embankment (Fig.
5) it was considered to analyze half of its geometry
for reasons of symmetry. A length of 60 m at thebase, a slope of 1:2 (V:H) and a height of 9.5 m
specified in the project were considered.

Fig. 5

Geometric model consideredanalysis of section Km 1+180.

forconsidering each row of stone columns as anequivalent longitudinal trenches with the same area[9], resulting for the numerical modeling, thediameter columns of 0.30 m and the separation
between axes of 2.70 m.
For vertical geodrains, a triangular distribution
with a separation of 1.5 m and an area of influenceof 2 m2 for each vertical geodrain were adopted. In
the consolidation analysis, drain elements were used,considering a null value of excess pore pressure at
all nodes (finite element mesh) along the lines
representing the drains in the model [6].
To model the behavior of the materials,
constitutive models available in the program Plaxis
8.6 were used. For the embankment, stone columns
and drainage layer the linear elastic perfectly plastic
Mohr-Coulomb model was used. For the soft clay,
the Soft Soil model was used, which provides
adequate results in situations of primaryconsolidation; these parameters are shown in Table 2
Table 2 Geotechnical Properties
Material

Clay

Model

Soft Soil

Embankment

Mohr
Coulomb
Behavior
Undrained Drained
General Parameters
15.7
19.5
γunsat kN/m3
γsat kN/m3
16.0
20.0
m/day 4.41×10-5 2.94x10-5
kx
m/day 2.94×10-5 2.94x10-5kyModel Parameters
E’
kN/m2
24769
ν'
0.3
c’
kN/m2
11.0
32.0
ϕ'
°
2.0
10.0
ψ
°
0.0
0.0
1.403
eo
0.207
Cc
Cs
0.026
Interface
1.0
1.0
RintertheStonecolumn,Drainage
layer
Mohr
Coulomb
Drained
19.0
20.0
10.02210.022
30000
0.3
1.0
42.0
0.0

1.0

DISCUSSION OF RESULTS
The embankment construction on the soft clay
was considered in stages, with increases of theembankment elevation in layers of 1 m, beginningwith a drainage layer of 0.5 m covered by ageotextile at the base of the embankment to allow abetter distribution of loads and drainage. Fig. 6
shows the finite element mesh corresponding to the

The stone columns technique has a distributionof square grid, with columns diameter of 1 m,
separated 3 m and an area of influence of 8 m2 percolumn. For its modeling was considered thetransformation of its geometry using an equivalent
geometry to perform the plane strain analysis [4],289

GEOMATE - Mie, Japan, Nov. 21-24, 2017

geometric model for the embankment construction
without any soil improvement techniqueFig. 9Fig. 6

Finite element mesh for analysis without
improvement technique.

Finite element mesh for analysis ofpreloading technique.

Figure 10 shows the result of safety analysis fordifferent embankment elevations and Fig. 11 shows
the diagram of settlement increase in function of theelevation of embankment construction and theperiod of time for each calculation phase, for theconstruction with preloading technique, reaching afactor of safety of 1.32 and a settlement of 87.5 cm,
in a period of time of 31.77 years, for an elevation of
5.5 m.

Figure 7 shows the result of safety analysis fordifferent embankment elevations and Fig. 8 shows
the diagram of settlement increase in function of theelevation of embankment construction and theperiod of time for each calculation phase, for theconstruction without improvement technique,reaching a factor of safety of 1.32 and a settlementof 11.1cm, in a period of time of 25 days, for anelevation of 4.5 m. This calculated elevation was thereference for the beginning of the consolidation
period for the posterior improvement techniques
analyzed.

Fig. 10 Factors of safety as a function of
construction elevations, for construction
with preloading technique.

Fig. 7

Factors of safety as a function of
construction elevations, for construction
without improvement techniques.

Fig. 11 Settlements vs. embankment elevation withthe time, for construction with preloading
technique.

Fig. 8In order to accelerate the consolidation andreduce the preloading time, the soil permeability isimproved by installing vertical geodrains. Fig. 12shows the finite element mesh for this analysis
considering the drain elements with geometric lines.

Settlements vs. embankment elevation withthe time, for construction without
improvement techniques.

Figure 9 shows the finite element meshconstructed for this analysis.
290

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 12 Finite element mesh for analysis of verticalgeodrains technique.

Fig. 15 Finite element mesh for analysis of stone
columns technique.

Figure 13 shows the results of the safety analysis
for different embankment elevations, and Fig. 14
shows the diagram of settlement increase in functionof the elevation of embankment construction and theperiod of time for each calculation phase, forconstruction with vertical geodrains technique,reaching a factor of safety of 1.34 and a settlementof 96.6 cm, in a period of time of 220 days, for anelevation of 5.5 m.

Figure 16 shows the results of the safety analysis
for different embankment elevations, and Fig. 17
shows the diagram of settlement increase in functionof the elevation of embankment construction and theperiod of time for each calculation phase, forconstruction with stone columns technique, reachinga factor of safety of 1.39 and a settlement of 47.1 cm,
in a period of time of 315 days, for the projected
elevation of 9.5 m.

Fig. 13 Factors of safety as a function of
construction elevations, for construction
with vertical geodrains technique.

Fig. 16 Factors of safety as a function of
construction elevations, for construction
with stone columns technique.

Fig. 14 Settlements vs. embankment elevation withthe time, for construction with geodrains
technique.

Fig. 17 Settlements vs. embankment elevation withthe time, for construction with stone
columns technique.

The technique of stone columns improves thesoil strength due the rigidization, decreasing thesettlement and improves the drainage. Fig. 15 shows
the finite element mesh for this analysis.

CONCLUSIONSThe construction in stages of the runway No.
16/34 embankment over soft clay, for the section
Km 1+180, was modeled with Plaxis 8.6 software,evaluating the stability, settlements and periods oftime for each stage; these results were evaluated tocompare the benefits of construction techniques
without improvement, preloading, vertical geodrains
291

GEOMATE - Mie, Japan, Nov. 21-24, 2017

and stone columns.
The analysis for the embankment construction
without improvement technique attained a maximum
stable elevation of 4.5 m, with a factor of safety of
1.32, in a period of time of 25 days, with 11.1 cm ofsettlement in the point of evaluation, located in thecentral zone of the base of the embankment. This
calculated elevation was the reference for the
beginning of the consolidation period for theposterior improvement techniques analyzed.
The construction of the runway embankmentconsidering the preloading technique attained amaximum stable elevation of 5.5 m, with a factor ofsafety of 1.32, in a period of time of 31.77 years,
with 87.5cm of settlement in the point of evaluation.
The necessary time required to dissipate the excess
pore pressure, makes the technique inadequate forthe construction.
The construction of the runway embankmentconsidering the vertical geodrains attained amaximum stable elevation of 5.5m, with a factor ofsafety of 1.34, in a period of time of 220 days, with
96.6cm of settlement in the point of evaluation. This
technique reduced the consolidation time making it
most effective than the preloading technique.
The construction of the runway embankmentconsidering the stone columns was the only
technique that attains the project elevation of 9.5m,
with a factor of safety of 1.39, in a period of time of
315 days, with 47.1 cm of settlement in the point ofevaluation.

with Preloading Embankment Techniques", 6thInternational Conference on Case Histories inGeotechnical Engineering, 2008[3] Bouassida M. and Klai M, "Challenges andImprovement Solutions for Tunis’ Soft Clay", J.
of GEOMATE, Vol. 3, No. 1, 2012, pp. 298307.
[4] Castro et al., "Modelización de columnas degrava", 10 Simposio Nacional de Ingeniería
Geotecnica, Vol. 2, 2016
[5] Consorcio Airways Novoa, “Estudio Técnico
Topografía y Geotecnia”, Estudios Definitivosde Ingeniería Aeropuerto Internacional Cusco,
1983.
[6] PLAXIS 2D Version 8, Reference Manual,
2007.
[7] Quilli A. M. E., "Comparación medianteanálisis numérico de métodos de tratamiento desuelo blando bajo un terraplén en Chinchero,
Cusco", Tesis de graduación, Facultad deArquitectura e Ingeniería Civil de la
Universidad Nacional de San Antonio Abad delCusco, 2016.
[8] Sotelo y Asociados, “Nuevo Aeropuerto
Internacional de Chinchero – Cusco. Informe deGeotecnia”, Nuevo Aeropuerto Internacional de
Chinchero – Cusco. Estudio definitivo deIngeniería - Estudios Generales. Informe deGeotecnia, 2014.
[9] Van Impe WF, De Beer E, “Improvement ofsettlement behaviour of soft layers by means ofstone columns”, 8th International Conference on
Soil Mechanics and Foundation Engineering,
Helsinki, 1983, pp. 309 – 312.

REFERENCES[1] Alg - Europraxis. “Anexo 3. Geotecnia y
Canteras”, Informe 9A-Estudio de Pre Inversión
a Nivel de Factibilidad, 2013.
[2] Bouassida M. and Hazzar L., "Comparison
between Stone Columns and Vertical Geodrains292

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DISPLACEMENT OF DIAPHRAGM WALL FOR VERY DEEPBASEMENT EXCAVATION IN SOFT BANGKOK CLAY
1

Dr. Wanchai Teparaksa1, Jirat Teparaksa2
Department of Civil Engineering, Faculty of Engineering, Chulalongkorn University, Thailand
2
Department of Civil Engineering, The University of Tokyo, Japan
ABSTRACTThe Rosewood Hotel Project consists of 6 basements by using the diaphragm wall as a soil protection system.
The elevations of Rosewood Hotel basements are -2.9, -6.5 -9.25, -11.95, -14.65 and -18.9m. depth from groundsurface. The final excavated depth of this project is -24.2m. from ground surface which is the area of lift pit.
Because the final depth of this project was very deep, the effect of water pressure was also considered. The
Finite Element Method (FEM) was carried out to predict the behavior and displacement of the diaphragm wall
which is used as a soil protection system. In addition, the Mohr-Coulomb soil modeling was used as the failure
criteria of FEM analysis. The measured lateral movement of the diaphragm wall by means of inclinometer at allstages of construction is compared with analytical results from FEM prediction. The predicted diaphragm wall
displacement by FEM agree well with field performance.
Keywords: diaphragm wall, basement construction, finite element method, wall displacement
INTRODUCTION
The Rosewood hotel consists of six basement
floor at -2.90 m,-6.50 m, -9.25 m, -11.95 m, -14.65
m, and -18.90 m. deep below ground surface whichis the lift pit of the project. The diaphragm wall isused as the temporary wall during excavation and isused as permanent wall at final stage. During
excavation, four temporary steel bracing layer wasused at elevation of -1.50 m, -7.45 m, -12.75 m. and-17.50 m. below ground surface. The diaphragmwall is 1.0 m. thick with tip penetrated in the very
stiff silty clay layer at -28.0 m. depth below groundsurface. The typical section of basement floor ispresented in Figure 1 while the detail of temporary
bracing system is presented in Figure 2.

Fig. 2 Detail of temporary bracing system Rosewood
Hotel.
The research work for study the behavior andperformance of diaphragm wall for basement
construction in Bangkok subsoil with various
conditions was presented by Teparaksa[1],[2],[3].
This paper presents the performance andFig. 1 Typical Section of basement Rosewood Hotel.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

behavior of the diaphragm wall. The lateraldisplacement of diaphragm wall is predicted by
FEM analysis by simulating the construction
sequence in the analysis. The lateral wall
displacement is monitored during excavation andcasting the basement floor. The FEM prediction iscompared and discussed with the field performance.

ANALYSIS BEHAVIOR OF DIAPHRAGM
WALL BY FINITE ELEMENT METHOD
Design Criteria of diaphragm wall
The behavior of diaphragm wall can be predictedby Numerical analysis by mean of Finite Element
Method (FEM). The result of FEM analysis ofdiaphragm wall behavior is presented in term ofbending moment and shear force induced in thediaphragm wall. The lateral displacement of
diaphragm wall is also presented. The soil modelingis one of the main parameter for FEM analysis. The
step of soil excavation, bracing installation, as wellas preloading in the strut system is simulated in the
FEM analysis. The casting of base slab, basement
floor and the step of removal of strut system are also
have to be designed and combined in the FEM
analysis of diaphragm wall. In this project, the
PLAXIS 2D [4] program is used as the FEM
program analysis to predict the diaphragm wall
behavior.
The Mohr-Coulomb soil modeling is used for
FEM analysis. The undrained Young’s modulus(Eu)of layer is correlated with undrained shear strength(Su). In the sand layer, the drained modulus (E’) is
correlated with the Standard penetration SPT NValue.
The correlation of Eu and Su as well as E’ andN-value can be conducted as follows.
 For soft to medium clay layer, Undrained
Young’s modulus(EU) = 500 – 700 Su (Undrained Shear
Strength) Stiff to very stiff silty clay layer
Eu = 1000 Su
 Sand layer
E’ = 2000(N) SPT-N-Value (kN/m2)
The above correlation between Eu-Su, and E’N(value) is based on the back analysis from various
basement excavation project by means of FEM
analysis compared with field measurement proposedby Teparaksa [5]

GEOLOGICAL CONDITIONS
Three bored holes of 70 m. depth is carried out toinvestigate the geological conditions of the project.
The soil conditions consists of soft to medium
Bangkok clay from ground surface to 14 m. depth.
The stiff silty to hard clay is encountered below soft
to medium clay up to -45 m. depth. The dense
second silty sand layer is found below 45 m. depth
below ground surface. At this project site, the firstlayer of silty sand is no found as the normal
Bangkok soil condition which is normally found at
about 27 – 30 m. depth. The soil condition as well as
soil engineering properties is presented in Figure 3.

Surcharge on the diaphragm wall
The ground surface surcharge behind thediaphragm wall during construction is assumed at 10
kN/m2. This ground surface is applied during
excavation, basement casting and completion of thebasement work.
Ground Water Table
The ground water in Bangkok subsoil condition
is in the draw down condition due to deep well
pumping. Recently, the deep well pumping is notallow, the recent ground water table is at -13 m.
below ground surface.

Fig. 3 Soil properties of Rosewood Hotel.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

RESULT OF FEM ANALYSIS

Figure 6 (a) presents the envelop of bending
moment diagram induced in the diaphragm wall withall excavation steps including soil excavation andbracing installation until casting the foundation. The
upward construction including casting base slab,
removing of bracing as well as basement casting is
also included in the envelope.
The dotted line outside of the bending momentenvelop is the bending moment resistance of thereinforcement. This dotted line of reinforcement iscalculated from reinforcement detail presented in
Figure 6(b)REINFORCEMENT DETAIL

2000

0

-5

-5
DB28 @ 0.167 m

DB28 @ 0.167 m

1500

1000

500

0

0

-500

-1000

BENDING MOMENT DIAGRAM(kN-m/m)
-1500

-2000

The FEM analysis was carried out base on MohrCoulomb soil failure criteria by simulating theconstruction sequence in the FEM analysis. Figure 4
presents the deformed mesh of FEM analysis at final
excavation depth -32.30 m. with 4 bracing layers.
Figure 5 presents the deformed mesh of FEM
analysis at stage of all 6 basement floor is casted.
The maximum lateral diaphragm wall deflection isfound at 43.34 mm. This maximum diaphragm wall
deflection is used as the Trigger Level formonitoring D-wall deflection as the safety control ofthe project.

-10
DB28 @ 0.167 m

-15

Depth

Depth

-10

-15

DB28 @ 0.167 m

-20

-25

Fig. 4 Deformed mesh from FEM analysis during
Final depth excavation.

-30

Step 1
Step 3
Step 5
Step 7
Step 9Moment Envelope EXC

-20

-25

Step 2
Step 4
Step 6
Step 8
Step 10
Moment Envelope Soil

-30

Fig. 6 (a,b) Envelop of Bending moment diagram
induced in the diaphragm wall.
TRIGGER LEVEL AND SAFETY CONTROLThe instrumentation for monitoring thediaphragm wall deflection is proposed as
inclinometer by installed inside the diaphragm wall
panel. The safety control and monitoring criteria is
proposed in terms of trigger level as presented inTable 1. The lateral diaphragm wall deflection ismonitored at all construction sequence as simulated
in the FEM analysis. The safety criteria is only one
method to control the behavior and performance ofdiaphragm wall during construction.
Fig. 5 Deformed mesh from FEM analysis during
construct B1 Floor at EL.-2.90 m.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Trigger level and safety control
Inclinometer
TriggerMovement
Safety Criteria
Level
(mm.)
Alarm
Inform designer to
Levelreview construction(70 % of
30.34
sequence
designvalue)
Alert Level
Inform all parties to(80 % ofreview construction
34.67
designsequencevalue)
ActionStop construction
Level
and revise the(90 % of
39.01
construction
designsequence.
value)
Maximum
43.34
FIELD MEASUREMENT OF D-WALL
DISPLACEMENT
Figure 7 presents the lateral diaphragm wall
displacement by mean of inclinometer reading. At
initial stage during first excavation and first strut
installation, the D-wall movement is in the mode of
cantilever. At other stage the movement of D-wall ischanged to be beam on supported shape. This isbecause the bracing strut is acted as the rigid supportof the diaphragm wall. The maximum wall
deflection is only 28.41 mm. at final depth
excavation. The maximum measured diaphragmwall deflection is less than the prediction of 42 mm.
This is because the basement construction period isvery fast and can be completed within 4 months.
Even the order of maximum measured wall
deflection is less than prediction, however, the shapeof wall deflection is similar. The FEM prediction ofdiaphragm wall agree well with field inclinometermeasurement.

Fig. 7 The lateral diaphragm wall displacement.
SAFTY AGAINST UPLIFTThe deepest basement of Rosewood hotel is at -24 m.
below ground surface. The uplift at the final depth
excavation is predicted by checking safety factor
against uplift. The safety factor against uplift can be
estimated as the ratio between weight of overburden
stress of soil from final depth to sand layer and upliftpressure as shown in Figure 8. The overburdenpressure is estimated at about 410 kN/m2 while
uplift pressure is at 320 kN/m2. The Safety factor
against uplift is 1.28.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

below ground surface. Four temporary steel bracingat -1.5 m, -7.45 m, -12.75 m and -17.5 m. is used for
excavation work with bottom up construction
technique. The behavior of diaphragm wall ispredicted by mean of FEM analysis. The MohrCoulomb soil modeling is used for FEM analysis
with simulating construction sequence in the FEM
analysis. The diaphragm wall displacement ispredicted. The measurement of D-wall displacement
by inclinometer agree well with FEM analysis.
REFERENCES[1] Teparaksa W, “Principal and application of
instrumentation for the first MRTA subway
project in Bangkok”, 5th International
Symposium on Field Measurement inGeomechanics, Singapore, 1999.
[2] Teparaksa W, “Deep Basement Construction of
Bank of Thailand Along Chao Phraya River
closed to Tewavej Palace and Bangkhunphrom
Palace”, Proc. of the 18th International
Conferenceson
Soil
Mechanics
andGeotechnical Engineering, Paris, 2013.
[3] Teparaksa W, P. Sontiprasart, N. Prachayaset
and S. Keawsawasvong. “Impact Assessmentsof the Deep Basement Construction in the MRT
Protection Zone”, The 28th KKHTCNN
Symposium. Civil Engineering, Bangkok,
Thailand, 2015.
[4] Brinkgreve, R.B.J., PLAXIS 2D Version 8
Manual, A.A. Balkema Publishers, 2002.
[5] Teparaksa W, “Displacement analysis ofdiaphragm wall for subway construction” The 7
th National convention in the Civil Engineering
Bangkok,2001

Fig. 8 Layer of soil for estimating uplift.
CONCLUSIONSThe Rosewood hotel consists of six basement
floors and constructed by means of diaphragm wall.
The maximum depth of excavation is at -24 m. depth
below ground surface. The diaphragm wall is 1.0 m.
thick with tip penetrated in very stiff clay at -28 m.

297

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE INFLUENCE OF SOLAR RADIATION ON PAVEMENTPERFORMANCE
1

John Yeaman1 and Adrian McCallum1
Faculty of Science, Health, Engineering and Education, University of the Sunshine Coast, Australia
ABSTRACT

For the past four years, the University of the Sunshine Coast (USC) has been monitoring the performance ofroad pavements through “in-situ” monitoring, in association with Sunshine Coast Council and Pavement
Management Services. During that time four sites have been built and monitored, wirelessly, minute by minute,24 hours per day. Each monitoring site is equipped with strain gauge sensors at critical positions within the
pavement, moisture gauges and thermocouples. The system is accompanied by a weather station that measures Air
Temperature, Wind Speed and Direction, Relative Humidity, Atmospheric Pressure, and Solar Radiation. We haveconfirmed that pavement stiffness is strongly influenced by pavement temperature, providing the moisture content
remains constant, and that for the most part, environmental conditions have a greater influence on pavement
behaviour than traffic. This paper examines the influence of solar radiation on pavement temperatures and thesubsequent influence on pavement behaviour over a twelve-month study period
Keywords: Solar radiation, Pavement performance
depth of 320 mm and in the subgrade at a depth of
420 mm in the following configuration:

INTRODUCTION
During December 2012, The University of theSunshine Coast (USC) in association with Sunshine
Coast Council (SCC) and Pavement Management
Services (PMS) installed an in-situ pavementmonitoring site on Sippy Downs Drive adjacent to the
University during upgrade of the pavement to dual
carriageway configuration. Results from this study
have been published by Fairweather (2014), Yeaman(2015) and Azawi (2015), with monitoring
continuing. Two other sites consisting of different
configurations continue to be monitored with respect
to Strain Energy Dissipation and Soil Suction.
As part of this overall research project, Yeaman(2017), at this subject site, postulated thatmaintenance of the pavement asset can be predictedfrom in situ strain outcomes as a function of bothtraffic and the environment but also that pavement
temperature has a strong influence on pavement
stiffness irrespective of the configuration.
The subject site is situated at Bellevista Boulevard,
Caloundra at Latitude S. 26° 47’ 41.28” andLongitude E. 153° 05’ 49.92” and consists of: Yellow Podzol subgrade with a stiffnessof 70 MPa 100 mm gravel subbase course with a
stiffness of 145 MPa
 270 mm cement treated base with a mean
stiffness modulus of 3500 MPa.
 50 mm Hot Mix Asphalt pavement
surface.
Sensors are fitted at the base of the stiff layer at aFig. 1

Pavement and sensor configuration –Bellevista site.

This section of Bellevista Boulevard, Caloundra
was constructed in September 2013 and has been
instrumented since that date.
Bellevista Boulevard is designed for a 20-year
lifespan with an initial high traffic growth of the first
five years of 8.3% and subsequent 15 years of 5%.
The design traffic is calculated as 5.21 million(5.21*106) Heavy Vehicle Axle Groups for the 20year design life.
This gives Critical Fatigue Strains of 428 µε for acemented layer of 3,500 MPa modulus and 1020 µε
critical compressive strain for subgrade deformation.
298

For relationships refer to reference 2 table 8.5.

Table 2 Example weather station data.
Wind_Speed_1min (m/s)

0.2
0.4
0.5
0.3
0.4
0.3
0.1
0.3

Wind_Dir_
1min (deg)

Rel_Humidity_1min (%RH)

Air_Pressure_1min (HPa)

306
166
218
195
114
100
216
147

88.9
88.8
89
88.9
88.9
88.9
88.9
88.9

1008.31008.31008.41008.41008.41008.31008.31008.3

SOLAR RADIATION
Solar Radiation is a unique commodity. Solarradiation comes directly to the earth’s surface only
inhibited by cloud, moisture and dust. It can bepredicted (within reasonable accuracy) for any pointon the earth’s surface for any hour of the day. We are
therefore able to use this parameter for evaluating theeffect of Solar Radiation on the performance of apavement.

Fig. 2a Configuration of Pavement Management
Site (G4SMART)

DISTRIBUTION OF SOLAR
THROUGHOUT THE YEAR

RADIATION

Clearly, the amount of solar radiation that impacts
on the road surface will vary throughout the year,
there being much less in mid-winter to mid-summer.
Figure 3 suggests the amount of solar radiation
accumulated during the hours of sunrise and sunset
for Latitude 26° south, Longitude 153° east. At thisLongitude, the sun is at its zenith at 12:03 pm daily.
The pattern for December 2015 and December
2016 are similar and that June (mid-winter)experiences much less radiation for each hour of theday, with the accumulated radiation being
approximately 10,000 watts per square metre when
the sun is at its zenith and 50,000 watts per square
metre at sunset. Clearly this must have a significant
effect on pavement temperature.

Fig. 2b Configuration of Pavement Management
Site (G4SMART)
Data in the format of Tables 1 and 2, following, ispassed from this site by telephone to a centralcomputer at 6:00 am daily.
Strain 1 is the strain measured at the underside of
the bound layer (HMA and cemented layer) and
Strain 2 is the top of the subgrade (subgrade layer).
The negative sign (-) in this instrumentation indicatesthat the strain is in tension.
Table 1 Example strain and temperature data.
See end of paper299

Fig. 3emitting heat. At 11:25 am equilibrium is attained andthe structural layer has the same temperature
throughout. Between 11:25 am and 11:30 pm thesurface temperature is in excess of the layer
temperature and the pavement is absorbing heat.
Equilibrium is attained at 11:29 pm. From 11:30 pm
to dawn (6:00 am) layer temperature is hotter than thesurface. Under these conditions where there is adifferential in temperature between the surface andthe layer then stresses are likely to be building in the
pavement.

Distribution of daily accumulated radiation.

THERMAL PROPERTIES OF A PAVEMENT
Figure 4 shows a typical strain and temperaturepattern during winter 2016 (23 June; cold & wet). At
6:00 am strain is in compression. At 08:23 something
happens that creates a major change in the pavement,
here Strain 1 changes to negative (i.e. tension),
simultaneously the layer temperature falls below
21 °C. Strain 1 continues to increase in tension until
around 5:00 pm (here the temperature is slightly
above 21°C). It then stays in compression until 6:00
am the next morning.

Fig. 6
Fig. 4

Diurnal Strain 1 vs time, 23 Jun 2016.

Diurnalpavement
September 2016.

temperatures,

8

SEASONAL VARIATIONS IN TEMPERATURE
PARAMETERS

Now consider the following day (24 June 2016).
Strain follows on from the same value as the previous
day, but with a sudden drop at 08:57 am (peak hour).
It then continues to a maximum tension value of 150µε at around 10:45 am when there is a sudden shift
upwards. Here temperature is just under 21°C. Once
layer temperature exceeds 21°C strain1 continues todecrease, until it enters a compression mode at about
6:00 pm where it remains until 6:00 am the next day.

Table 3 demonstrates the Maximum values
obtained for Air, Surface and Layer temperaturesduring the period December 2015 to December 2016.
Table 3 Seasonal variation maximum temperatures.
PeriodSUMMER
AUTUMNWINTERSPRING

Air
30.0
29.3
22.1
31.8

Surface
41.5
35.7
25.2
38.6

Layer
41.5
33.6
25.0
35.1

Table 4 demonstrates the Minimum values
obtained for Air, Surface and Layer temperaturesduring the period December 2015 to December 2016.
Table 4 Seasonal variation minimum temperatures.
Fig. 5PeriodSUMMER
AUTUMNWINTERSPRING

Diurnal Strain 1 vs time, 24 June 2016.

Clearly this change in behaviour is a function of
the pavement layer temperature.
DIURNALPATTERNTEMPERATURES

OF

PAVEMENT

Air
17.5
13.5
10.2
12.9

Surface
25.8
30.2
17.8
22.4

Layer
27.4
21.2
19.5
23.4

FIELD STUDIESRoad Surface temperatures are charted against
cumulative radiation during sunlight hours for every
day of the year example Figure 8c from which it canbe seen that there is a defined point of maximum roadsurface temperature; an example daily report is

Figure 3 shows air, surface and layer temperatures
for the Bellevista site on 8 September 2016. From thisit can be observed that between 6:00 am and 11:00 thetemperature at the underside of the bound layer
exceeds the surface temperature and the pavement is300

appended. At longitude 153°E the sun is at its zenith
at 12:03; this maximum occurs between 11:30 am and1:00 pm each day i.e. the sun’s zenith + 1 hour.
Oscillations in the solar energy chart are a function ofcloud cover.

Figure 8(c) Layer Temperature as a function of
accumulated radiation
Examination of these data indicates that twice a
day there is a point of equilibrium where thepavement is the same temperature at the surface andat the base of the bound layer. Between
approximately 11 am and 11 pm the surface
temperature is greater than the layer and between
approximately 11 pm and 11 am the underside of thebound layer is hotter than the surface
Clearly this is a function of the quantum of solar
energy radiating the pavement.
Compare thetemperature pattern for the shortest day of 2016 (June21st) and the longest day of 2016 (December 21st) at 3
pm (Table 5).

Fig. 7a Radiation parameters (shortest day).

Table 5 Temperature and Radiation measurements
for shortest and longest days.
Date

Changeintemperature
fromsunrise(°C)
Up to 3pm

Accum
ulatedRadiation(wattsper m2)20.5

2.0

93,68426.8

5.3

110,389

SurfaceTempe
rature (
°C)

Layer
Tempe
rature(°C)

Air
Temperature(°C)

At 3
pm

At 3
pm

At 3pm

23.6

21.7

37.4

32.8

Fig. 7b Temperature parameters (shortest day).

Shor
test
Day
Long
est
Day

Until 3pm

This is an important consideration when choosing
a design temperature for the design of asphalt
pavement thickness.

Fig. 8a Radiation parameters (longest day).

RELATIONSHIP BETWEEN SURFACETEMPERATURE & STRUCTURAL LAYERSTRAINIn figure 9 we see the distribution of strain as afunction of temperature over the full year where themoisture content is below 9%. Here structural layer
strain is only in tension at temperatures below 20°C
and then only above the critical limit of 248 με when
the temperature is below 18°C. The secondary effectof moisture above 9% is dealt with elsewhere(Yeaman [2]).

Fig. 8b Temperature parameters (longest day).

301

Fig. 9and microcontroller.
A code is uploaded to the microcontroller that
relates the angular degree of the servo motor to a
specific solar radiation; the code orders the servo
motor to move every five minutes. The code relies ondata obtained from the Pavement Monitoring System
on Sippy Downs Drive (near Sunshine Coast
University). Data from the hottest day on record in2015 was used (9 February). The microcontroller ran
throughout the day simulating the solar radiation.
A datalogger is used to record these temperatures
every minute from the thermocouples inserted into
the asphalt billet (at depths of 25 mm, 50 mm, 75 mm,
100 mm, 150 mm, 200 mm, 300 mm and 400 mm).
Figure 11 provides an example of the outcome
from the heat box comparing the solar radiation andthe actual and simulated radiation for the hottest dayof 2016 ( 9th February).

Distribution of Structural Layer Strain as afunction of Pavement Surface Temperature.

LABORATORY STUDIESLaboratory studies were conducted by Gray(2015), Westerway (2015) and Laws (2015) to better
understand the influence of solar radiation on asphalt
in a controlled environment (i.e. no wind, no cloudand no dust) .
An insulated box (Figure 10) was purpose built tohold a 200 mm square by 450 long billet of Hot Mix
Asphalt compacted in the University’s Shear box
compactor (IPC Global).

Fig. 11 Simulated Temperature: Solar Radiation forhottest day 2016 (Westaway et al 2017.
Figure 12 demonstrates the effect of thermalradiation on pavement temperatures from thesimulation method.

Fig. 12 Relationship between Accumulated Solar
Radiation
andPavement
SurfaceTemperature.
Here we see that there is:Fig. 10 Heat box and thermal lamp constructed toenable pavement insolation to be varied in acontrolled manner (Gray 2014).

The Heat Box is designed to simulate thermalradiation from the sun and to measure the temperaturechanges an asphalt pavement undergoes throughout
the day. The Heat Box uses a heat lamp, a servo motor302

A terminal condition at which thetemperature asymptotes to equilibrium andthis represents a pavement depth of around
300 mm (noting that this test was run for thehottest day),
Voids content has a significant influence onreceptor – an asphalt pavement. The Stirling Energy
principle has potential in this area.

the rate of conduction of heat through thepavement, andIn a road pavement, 100 mm thick, there is
the potential to store thermal energy as heat
energy (say 12 °C).

REFERENCES[1] Austroads 2007, “Guide to Pavement
Technology”, Part 4B Asphalt, Sydney[2] Yeaman 2017 “Managing Pavement Assets
through In-Situ Monitoring”, World Conference
on Pavement and Asset Management WCPAM
2017 Milan , Italy , June 12/16 2017[3] Yeaman 2017 “The Influence of Subgrade
Moisture Content on Pavement Performance”
under review[4] Gray C ,2014 Final Year Capstone thesis,
University of the Sunshine Coast[5] Westaway K ,2016 “Comparison of asphalt
material characteristics as a function of air void
content “Final Year Capstone thesis , Universityof the Sunshine Coast.
[6] Laws N 2016 , “A Profile of Brisbane City
Council Type 3 Asphalt Mix with Varying Air
Voids” Final Year Capstone Thesis , Universityof the Sunshine Coast.

CONCLUSION
Although this study is for a single site and one
type of pavement (thin Hot Mix Asphalt on acemented base) the results are sufficient to warrant
further investigation of this technology over a wider
range of conditions.
Solar Radiation has a critical influence on both thepavement surface and the structural layer of acemented base pavement. Further, a road pavement isa potential store for solar energy. Between midnight
and midday, the structural layer is hotter than the
pavement surface and the pavement is emitting heat,
To date the only values under which a criticallevel of fatigue is attained is when the structural layer
temperature is less than 20°C and at this time
(December 2016), the pavement is deemed to be
performing according to design criteria.
RECOMMENDATION
Further investigation should be undertaken toevaluate the potential energy source of a large solar
Timestamp
6:01
7:05
10:00
12:03
15:00
18:00
21:00
23:59

Strain1
75
568
5
-38
-19
66
105
115

Strain 2
137
133
114
110
133
145
124
130

Subgrade
Moisture
8.68
8.70
8.70
8.70
8.68
8.65
8.62
8.62

Air
Temperature
21.2
25.0
29.5
30.1
29.4
27.8
26.3
23.6

SurfaceTemperature
33.7
33.2
32.9
34.9
39.5
40.9
39.1
37.2

Layer
Temperature
35.0
34.7
33.8
34.1
35.7
37.5
37.8
37.2

Figure 1 Example results from Monitoring site (26 January 2017)303

Acc. Solar
Radiation
29
2912
23988
49760
84,689100,397
101,070
101,080Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE INFLUENCE OF SOLAR RADIATION AND SUBGRADE
MOISTURE CONTENT ON PAVEMENT PERFORMANCE
1

John Yeaman1 and Adrian McCallum1
Faculty of Science, Health, Engineering and Education, University of the Sunshine Coast, Australia
ABSTRACT

For the past four years the University of the Sunshine Coast (USC) has been monitoring the performance ofroad pavements through “in-situ” monitoring, in association with Sunshine Coast Council and Pavement
Management Services. During that time four sites have been built and monitored, wirelessly, minute by minute,24 hours per day. Each monitoring site is equipped with strain gauge sensors at critical positions within the
pavement, moisture gauges and thermocouples. The system is accompanied by a weather station that measures
Air Temperature, Wind Speed and Direction, Relative Humidity, Atmospheric Pressure, and Solar Radiation.
This paper examines the influence of solar radiation on pavement temperatures and the subsequent influence on
pavement behaviour over a twelve-month study period from December 2015 to December 2016. Additionally we
examine the influence of subgrade moisture content on pavement behaviour at the site, particularly during
cyclonic depression “Debbie” in March 2017. We confirm that pavement stiffness is strongly influenced bypavement temperature, providing the moisture content remains constant. Examination of the influence ofsubgrade moisture content on pavement behaviour shows that critical fatigue strain occurs when moisture
content lies above 8.5%. Moisture variation plays a measurable role in pavement strain, fatigue and design life
and wide variation in moisture content can occur over a short period. For the most part, environmental conditions
have a greater influence on pavement behaviour than traffic.
Keywords: Solar radiation, Subgrade, Moisture, Strain, Pavement performance
270 mm cement treated base with amean stiffness modulus of 3500 MPa.
 50 mm Hot Mix Asphalt pavement
surface.
Sensors are fitted at the base of the stiff layer at a
depth of 320 mm and in the subgrade at a depth of
420 mm in the following configuration:

INTRODUCTION
During December 2012 The University of theSunshine Coast (USC) in association with Sunshine
Coast Council (SCC) and Pavement Management
Services (PMS) installed an in-situ pavementmonitoring site on Sippy Downs Drive adjacent to
the University during upgrade of the pavement todual carriageway configuration. Results from thisstudy have been published by Fairweather (2014),
Yeaman (2015) and Azawi (2015), with monitoring
continuing. Two other sites consisting of different
configurations continue to be monitored with respect
to Strain Energy Dissipation and Soil Suction.
As part of this overall research project, Yeaman(2017), at this subject site, postulated thatmaintenance of the pavement asset can be predictedfrom in situ strain outcomes as a function of bothtraffic and the environment but also that pavement
temperature has a strong influence on pavement
stiffness irrespective of the configuration.
The subject site is situated at Bellevista
Boulevarde, Caloundra at Latitude S. 26° 47’ 41.28”
and Longitude E. 153° 05’ 49.92” and consists of: Yellow Podzol subgrade with a stiffnessof 70 MPa 100 mm gravel subbase course with a
stiffness of 145 MPa

Fig. 1304

Pavement and sensor configuration –Bellevista site.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

This section of Bellevista Boulevard, Caloundra
was constructed in September 2013 and has been
instrumented since that date.
Bellevista Boulevard is designed for a 20 year
lifespan with an initial high traffic growth of the first
five years of 8.3% and subsequent 15 years of 5%.
The design traffic is calculated as 5.21 million(5.21*106) Heavy Vehicle Axle Groups for the 20
year design life.
This gives Critical Fatigue Strains of 248 µε fora cemented layer of 3,500 MPa modulus and 1020
µε critical compressive strain for subgrade
deformation. For relationships refer to reference 2
table 8.5.

Strain 2 is the top of the subgrade (subgrade layer).
The negative sign (-) in this instrumentation
indicates that the strain is in tension.
Table 1 Example strain and temperature data.
Tim
e

1/1
1/2
016
6:0
1
1/1
1/2
016
6:0
2
1/1
1/2
016
6:0
3
1/1
1/2
016
6:0
4
1/1
1/2
016
6:0
5
1/1
1/2
016
6:0
6

Solar_Rad
Corrected(W/m2)
44.46

Wind
Dir
1min
(deg)

28.84

Roa
Surface
Temp(degC)
27.76

21.1

28.87

27.77

43.74

166

32.56
7

21.1

28.87

27.77

42.99

218

59.
50
0

32.56
8

21.2

28.87

27.78

41.92

195

‐
19.
09
4

54.
18
8

32.56
6

21.2

28.84

27.76

42.32

114

‐
24.
40
6

59.
50
0

32.56
6

21.2

28.86

27.76

44.04

100

Str
ain
#1
(ue
)
‐
26.
96
9

Str
ain
#2
(ue
)
56.
90
6

Soil‐
Moist
ure1
% (by
vol)
32.56
1

Air
Temp
1min
(degC
)
21.1

Surface Layer
Temp(degC)

‐
21.
68
8

64.
68
8

32.56
9

‐
16.
43
8

59.
50
0

‐
11.
21
9

306

Table 2 Example weather station data.
Fig. 2a Configuration of Pavement Management
Site (G4SMART)

Wind_Spe
ed_1min
(m/s)
0.2
0.4
0.5
0.3
0.4
0.3
0.1
0.3

Wind_Dir
_1min
(deg)
306
166
218
195
114
100
216
147

Rel_Humidi
ty_1min
(%RH)
88.9
88.8
89
88.9
88.9
88.9
88.9
88.9

Air_Pressu
re_1min(hPa)
1008.31008.31008.41008.41008.41008.31008.31008.3

SOLAR RADIATION
Solar Radiation is a unique commodity. Solarradiation comes directly to the earth’s surface only
inhibited by cloud, moisture and dust. It can bepredicted (within reasonable accuracy) for any pointon the earth’s surface for any hour of the day. We
are therefore able to use this parameter forevaluating the effect of Solar Radiation on theperformance of a pavement.

Fig. 2b Configuration of Pavement Management
Site (G4SMART)
Data in the format of Tables 1 and 2, following,is passed from this site by telephone to a centralcomputer at 6:00 am daily.
Strain 1 is the strain measured at the underside of
the bound layer (HMA and cemented layer) and305

GEOMATE - Mie, Japan, Nov. 21-24, 2017

DISTRIBUTION OF SOLAR
THROUGHOUT THE YEAR

Now consider the following day (24 June 2016).
Strain follows on from the same value as theprevious day, but with a sudden drop at 08:57 am(peak hour). It then continues to a maximum tension
value of 150 µε at around 10:45 am when there is asudden shift upwards. Here temperature is just under
21°C. Once layer temperature exceeds 21°C strain1
continues to decrease, until it enters a compression
mode at about 6:00 pm where it remains until 6:00
am the next day.

RADIATION

Clearly, the amount of solar radiation that
impacts on the road surface will vary throughout theyear, there being much less in mid-winter to midsummer. Figure 3 suggests the amount of solar
radiation accumulated during the hours of sunrise
and sunset for Latitude 26° south, Longitude 153°
east. At this Longitude the sun is at its zenith at
12:03 pm daily.
It can be seen that the pattern for December 2015
and December 2016 are similar and that June (midwinter) experiences much less radiation for eachhour of the day, with the accumulated radiation
being approximately 10,000 watts per square metre
when the sun is at its zenith and 50,000 watts per
square metre at sunset. Clearly this must have asignificant effect on pavement temperature.

Fig. 5

Diurnal Strain 1 vs time, 24 June 2016.

Clearly this change in behaviour is a function of
the pavement layer temperature.
DIURNALPATTERNTEMPERATURES

Fig. 3

PAVEMENT

Figure 6 shows air, surface and layer
temperatures for the Bellevista site on 8 September
2016. From this it can be observed that between 6:00
am and 11:00 the temperature at the underside of thebound layer exceeds the surface temperature and thepavement is emitting heat. At 11:25 am equilibrium
is attained and the structural layer has the same
temperature throughout. Between 11:25 am and11:30 pm the surface temperature is in excess of thelayer temperature and the pavement is absorbing
heat. Equilibrium is attained at 11:29 pm. From
11:30 pm to dawn (6:00 am) layer temperature ishotter than the surface. Under these conditions
where there is a differential in temperature between
the surface and the layer then stresses are likely to
be building in the pavement.

Distribution of daily accumulated radiation.

THERMAL PROPERTIES OF A PAVEMENT
Figure 4 shows a typical strain and temperaturepattern during winter 2016 (23 June; cold & wet). At
6:00 am strain is in compression. At 08:23
something happens that creates a major change inthe pavement, here Strain 1 changes to negative (i.e.
tension), simultaneously the layer temperature falls
below 21 °C. Strain 1 continues to increase intension until around 5:00 pm (here the temperatureis slightly above 21°C). It then stays in compression
until 6:00 am the next morning.

Fig. 6
Fig. 4

OF

Diurnal Strain 1 vs time, 23 Jun 2016.
306

Diurnalpavement
September 2016.

temperatures,

8

GEOMATE - Mie, Japan, Nov. 21-24, 2017

SEASONAL
VARIATIONSTEMPERATURE PARAMETERS

IN

Table 3 demonstrates the Maximum values
obtained for Air, Surface and Layer temperaturesduring the period December 2015 to December 2016.
Table 3 Seasonal variation maximum temperatures.
PeriodSUMMER
AUTUMNWINTERSPRING

Air
30.0
29.3
22.1
31.8

Surface
41.5
35.7
25.2
38.6

Layer
41.5
33.6
25.0
35.1

Fig. 8a Radiation parameters (longest day).

Table 4 demonstrates the Minimum values
obtained for Air, Surface and Layer temperaturesduring the period December 2015 to December 2016.
Table 4 Seasonal variation minimum temperatures.
PeriodSUMMER
AUTUMNWINTERSPRING

Air
17.5
13.5
10.2
12.9

Surface
25.8
30.2
17.8
22.4

Layer
27.4
21.2
19.5
23.4

Fig. 8b Temperature parameters (longest day).
Examination of these data indicates that twice a
day there is a point of equilibrium where thepavement is the same temperature at the surface andat the base of the bound layer. Between
approximately 11 am and 11 pm the surface
temperature is greater than the layer and between
approximately 11 pm and 11 am the underside of thebound layer is hotter than the surface
Clearly this is a function of the quantum of solar
energy radiating the pavement.
Compare thetemperature pattern for the shortest day of 2016
(June 21st) and the longest day of 2016 (December21st) at 3 pm (Table 5).

FIELD STUDIES
Comparison of road surface temperatures withcumulative radiation during sunlight hours showsthat there is a defined point of maximum roadsurface temperature; examples are shown (Figs 7a,7b, 8a and 8b). At longitude 153°E the sun is at its
zenith at 12:03; this maximum occurs between 11:30
am and 1:00 pm each day i.e. the sun’s zenith + 1
hour. Radiation oscillates due to cloud cover.

Table 5 Temperature and Radiation measurements
for shortest and longest days.
Date

Fig. 7a Radiation parameters (shortest day).
Shor
test
Day
Long
est
Day

Changeintemperature
fromsunrise(°C)
Up to 3pm

Accumulated
Radiation (watts
per m2)20.5

2.0

93,68426.8

5.3

110,389

SurfaceTemperature (°C)

Layer
Temper
ature
(°C)

Air
Temperature(°C)At 3 pm

At 3 pm

At 3pm

23.6

21.7

37.4

32.8

Until 3pm

This is an important consideration whenchoosing a design temperature for the design ofasphalt pavement thickness.

Fig. 7b Temperature parameters (shortest day).
307

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The Heat Box is designed to simulate thermalradiation from the sun and to measure thetemperature changes an asphalt pavement undergoes
throughout the day. The Heat Box uses a heat lamp,
a servo motor and microcontroller.
A code is uploaded to the microcontroller that
relates the angular degree of the servo motor to a
specific solar radiation; the code orders the servo
motor to move every five minutes. The code relies
on data obtained from the Pavement Monitoring
System on Sippy Downs Drive (near Sunshine Coast
University). Data from the hottest day on record in2015 was used (9 February). The microcontroller
ran throughout the day simulating the solar radiation.
A datalogger is used to record these temperatures
every minute from the thermocouples inserted into
the asphalt billet (at depths of 25 mm, 50 mm, 75
mm, 100 mm, 150 mm, 200 mm, 300 mm and 400
mm).
Figure 11 provides an example of the outcome
from the heat box comparing the solar radiation andthe actual and simulated radiation for the hottest dayof 2016 ( 9th February).

RELATIONSHIP BETWEEN SURFACETEMPERATURE & STRUCTURAL LAYERSTRAINIn figure 9 we see the distribution of strain as afunction of temperature over the full year where themoisture content is below 9%. Here structural layer
strain is only in tension at temperatures below 20°C
and then only above the critical limit of 248 με when
the temperature is below 18°C. The secondary effectof moisture above 9% is dealt with elsewhere(Yeaman [2]).

Fig. 9Distribution of Structural Layer Strain as afunction of Pavement Surface Temperature.

LABORATORY STUDIESLaboratory studies were conducted by Gray(2015), Westerway (2015) and Laws (2015) tobetter understand the influence of solar radiation on
asphalt in a controlled environment (i.e. no wind, nocloud and no dust) .
An insulated box (Figure 10) was purpose built
to hold a 200 mm square by 450 long billet of Hot
Mix Asphalt compacted in the University’s Shearbox compactor (IPC Global).

Fig. 11 Simulated Temperature: Solar Radiation forhottest day 2016 (Westerway et al 2017).
Figure 12 demonstrates the effect of thermalradiation on pavement temperatures from thesimulation method.

Fig. 12 Relationship between Accumulated Solar
Radiation
andPavement
SurfaceTemperature.
Here we see that there is:Fig. 10 Heat box and thermal lamp constructed toenable pavement insolation to be varied in acontrolled manner (Gray 2014).


308

A

terminal

condition

at

which

the

GEOMATE - Mie, Japan, Nov. 21-24, 2017

temperature asymptotes to equilibrium andthis represents a pavement depth of around
300 mm (noting that this test was run forthe hottest day),
Voids content has a significant influence on
the rate of conduction of heat through thepavement, andIn a road pavement, 100 mm thick, there is
the potential to store thermal energy as heat
energy (say 12 °C).

EFFECT OF MOISTURE ON PAVEMENTPERFORMANCE
The presence or ingress of moisture into apavement structure causes damage, or a loss in the
integrity of that pavement structure. The
development of damage is often progressive, andcan cause sudden failure of a pavement or slow
deterioration until the pavement is no longer safe touse. Due to the cumulative nature of moisturedamage, it is vital that moisture ingress isunderstood to ensure a pavement achieves its design
life.
Moisture within granular layers reduces thefriction between particles and thus the strength ofthe material by creating large pore pressures. The
dynamic loads imposed by moving vehicles makes
this even more complicated, as it creates a movingpressure wave with large hydrostatic forces.
Moisture conditions can vary from unsaturated to
fully
saturated.
Althoughpavements
aretheoretically compacted at the optimum moisture
content during construction, the degree of saturation
cannot be assumed.
Depending on the situation, the water content
may be considered in terms of volumetric watercontent (in soil science) or gravimetric water content(in geotechnical engineering). In this study, we will
examine only the effect of Gravimetric Moisture
content on the pavement behaviour.

Fig. 13 Soil moisture relationships (Austroads).
Kimmel[8]developed
soil
moisture
relationships for the subgrade at the Bellevista site,
as part of his final year undergraduate programme todesign and install the pavement monitoring
instrumentation at Bellevista Boulevard (Figure 2).
Over the past twelve months, the relationships
between Gravimetric Moisture Content and rainfall
have been established (Figures 14, 15, 16 & 17).

SOIL MOISTURE RELATIONSHIPS
Figure 13 (after Austroads) demonstrates thevarious relationships between soil, water andengineering properties. Of importance is the “zeroair voids line” or saturation line.

Fig. 14 Moisture density relation
subgrade (after Kimmel, 2014).

309

Bellevista

GEOMATE - Mie, Japan, Nov. 21-24, 2017

developed into a cyclonic depression with heavy
rainfalls and widespread flooding for the following
week.

Fig. 15 Distribution of moisture and rainfall,
Summer 2016.

Fig. 18 Rainfall and subgrade moisture - Cyclone
Debbie.

Fig. 16 Gravimetric moisture and rainfall, Autumn
2016.

Fig. 19 Bound layer strain and moisture – Cyclone
Debbie.

Fig. 20 Bound layer strain and moisture – Cyclone
Debbie.

Fig. 17 Gravimetric moisture and rainfall, Winter2016.

Bound Layer Strain passes from tension tocompression whenever subgrade moisture rises
above 8.5%. The subgrade strain passes from tension
to compression when the moisture content exceeds
8.5% i.e. the optimum of 8.3% (Kimmel [8]). This
indicates that moisture contents above optimum inthe subgrade will affect the performance of thispavement.

CRITICAL STRAINS AND MOISTURE
Let us consider the Strain conditions over a 7day period in March 2017 (Figures 18, 19 and 20).
In this case, the pavement was very dry on the 14th
March with the area being declared in drought. Rainbegan falling at 1:00pm on the 15th March and310

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Mo
istu
re
Co
nte
nt

DIFFERENCE IN MOISTURE CONTENT AS A
FUNCTION OF RAINFALL
The quantum and intensity of rainfall has anoteworthy influence on the Moisture Content (videFigures 4, 5, 6, 7). In some cases, it can take as longas 3 days for changes in rainfall to be reflected asmoisture content. Table 6 shows observed moisture
content changes at the Bellevista Site. It is apparent
that rainfalls of less than 5 mm have insignificant
effect on moisture content. Whereas rainfalls greaterthan 5 mm may have a significant impact for up to 3
days later.
Table 6 Differences
rainfall.
RainfallLess than 1
mm
1 to 5mm
5 to 15mm
More than
15mm

inmoisturecontent

7.81%

7.67%

8.91%

7.57%

In the month following the moisture reduces
rapidly and strains correspondingly increase intension (Figures 21 & 22).

with

Difference in Moisture Content
1 Day
2 days3 Days0.31 to-1.21 to-1.72 to
0.43
0.87
1.29
-0.24 to-0.34 to-0.45 to
0.43
0.55
0.57
-0.44 to-0. 34 to- 0.72 to
1.42
1.58
2.28
-0.44 to-0.55 to-0.5 to
1.42
2.45
2.40

Fig. 21 Influence of moisture content on subgradestrain (Strain 1).

DAILY CHANGESA preferred way to examine pavement
performance is to compare results obtained every
day at 10:00 am. A photograph is taken of thepavement and conditions at that time are recorded(Table 7). For the same conditions the latent strain(no traffic) remains relatively the same. As the
subgrade becomes wetter, bearing capacity is
reduced and the pavement becomes prone topermanent deformation.

Fig. 22 Influence of moisture content on subgradestrain (Strain 2).

Table 7 Moisture data during and after Cyclone
Debbie.
14 Mar2017

15 Mar2017

21 Mar2017

EFFECT ON STIFFNESSElastic Modulus with respect to pavements is notapplicable to permanent deformation, with the
Number of Cycles to Failure (Nf) being defined (inAustralia) [1, Table 8.5]; see Eq. (1).

21 April
2017

(1)

Str
ain
1
Str
ain
2

-92με

-93με

-1 μ

-188

-150με-142 με-17 με-155

Where με is the vertical compressive strain at the
top of the subgrade.
In the case of a cemented layer, Nf is derived
from the relationship for fatigue of cemented
materials (Austroads [1] ) as:

311

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 9 Derived layer stiffness for case study days.
Nf =

.

(2)

Date
Strain 1 @10:00 am(με)
LayerModulus(MPa)

Where:
Nf = Number of Cycles to failure
E = Modulus of cemented layer (MPa)με = compressive strain at the top of thesubgrade

14 Mar17

15 Mar17

21 Mar
17

21
April
2017

-93

-92

-61

-188

6237

6304

9508

3.085

Strain at the underside of the cemented layer isconstant for March 14 and 15, however, as the
moisture content increases on day 7 to 8.9 % (table7) it decreases by 30 με.
Strain at the top of the subgrade is not a functionof layer stiffness, hence the magnitude of this strain
indicates the potential to permanent deformation of
the subgrade. To date the values of Subgrade layer
strain are very much less than design (≈ 250 μεcompares with a design value of 1020 με ) and will
not be discussed further in his paper.

Using Boussinesq’s Generalised equation (Eq. 3)
relating depth of pavement to stress and strain we
find:




2

(1   ) o a 
1z  
zE
 1  2  1     

2
z
a
a

 1  z 

 


a
Where :

CONDITIONS FOR CRITICAL FATIGUESTRAIN z  Strain at depth z  Poisson's ratio - assume 0.45
a  Circular radius of the loaded area - assume 200 mm
 o  Stress on the surface

We now examine data from a 12 month period at
the Bellevista Site to examine conditions necessary
for critical fatigue strain.
Occasions when Fatigue Strain is criticalIn this case, the stress is derived from the traffic
spectrum (Table 8):

Fatigue Strain exceeded the design value of -248
µε on 19 Days between 31st May and 29th August
2016 (Table 10). These data indicate that the lower
the bound layer temperature and the lower the
moisture, the greater the tensile strain.

Table 8 Traffic distribution and associated tyrepressures.

9500
AADT
AssumedTyre
Pressure% Cars&Trailers
92.8
270
KPa

Class 3
Trucks*Class 4
Trucks

6.1

0.3

580
KPa

780
KPa

Classes
5-12
Trucks0.8

Table 10 Traffic distribution and associated tyrepressures.
PARAMETER
Structural Layer
Strain (µε) *Subgrade Strain(µε) *
Gravimetric
Moisture (%)
Modulus (MPa)
Air Temperature(°C)
SurfaceTemperature
(°C)
Layer
Temperature(°C)

780 KPa

This results in a calculated site stress of 420 KPa.
Therefore, the Dynamic Stiffness Modulus |E*| canbe calculated as ABS (580,000∕ (Strain 1)).
Using this relationship with the provision that the
average tyre pressure for this site is 420 KPa, thedepth of the bound layers are 320 mm (fig 1) and theLayer Modulus is 3,500 MPa (design value), we
derive the approximate layer stiffness for each of theconditions over the 1 month as follows:

312

MAXIMUM

MINIMUM

-253

-492

-146

-368

11.5

8.1

2560

1320

21.3

13.2

19.5

14.7

21.2

16.8

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Negative value indicates that parameter is in Fatigue
mode.

Here Bound layer strain is critical for moisture
contents above 8.5 % and Surface layer temperatures
above 27°C.

Relationship between Bound Layer Strain andMoisture Content
The relationships between Bound Layer Strain
and moisture content at various pavement
temperatures are now examined (Figures 23, 24, 25
and 26).

Fig. 26 Moisture content and STRAIN 1 @temperatures 33oC to 42oC.
Here Bound Layer Strain is critical for moisture
contents above 9% and surface layer temperatures
above 33°C.

Fig. 23 Moisture content and STRAIN 1 fortemperatures below 23oC.
Here strain is evenly distributed for all ranges ofmoisture with the only critical values (<-248 με)
occurring at moisture contents between 8.5 and 9%

From these relationships, we observe that criticalfatigue strain at this site occurs when moisture
content lies above 8.5%
CONCLUSION
Although this study is for a single site and one
type of pavement (thin Hot Mix Asphalt on acemented base) the results are sufficient to warrant
further investigation of this technology over a wider
range of conditions.
Solar Radiation has a critical influence on boththe pavement surface and the structural layer of acemented base pavement. Further, a road pavement
is a potential store for solar energy. Between
midnight and midday the structural layer is hotter
than the pavement surface and the pavement isemitting heat,
To date the only values under which a criticallevel of fatigue is attained is when the structurallayer temperature is less than 20°C and at this time
(December 2016), the pavement is deemed to be
performing according to design criteria.
At moisture contents above 8.5 % andtemperatures above 23°C, for this site, moisture has
an influence on fatigue damage of the cemented
layer. Therefore, in design calculations, we are notable to adopt one stiffness for the modulus of thestructural layer.

Fig. 24 Moisture content and STRAIN 1 @temperatures 23oC to 27oC.
Here Bound Layer Strain is critical for moisture
contents above 9.5% and temperatures above 23°C.

RECOMMENDATION

Fig. 25 Moisture content and STRAIN 1 @temperatures 27oC to 33oC.

Further investigation should be undertaken toevaluate the potential energy source of a large solar
313

GEOMATE - Mie, Japan, Nov. 21-24, 2017

receptor – an asphalt pavement. The Stirling Energy
principle has potential in this area.

content “Final Year Capstone thesis , Universityof the Sunshine Coast.
[6] Laws N, 2016 , “A Profile of Brisbane City
Council Type 3 Asphalt Mix with Varying Air
Voids” Final Year Capstone Thesis , Universityof the Sunshine Coast.
[7] Austroads (2008) “ Guide to Pavement
Technology” Part 2: Pavement
Structural
Design[8] Kimmel B (2014) “The Instrumentation of theentrance to Bella Vista Subdivision at
Caloundra” Capstone project thesis Universityof the Sunshine Coast[9] Fairweather, H., and J. Yeaman. A Study of theParameters Affecting the Performance of Roads
Under an Extreme Rainfall Event. International
Journal of GEOMATE, Vol. 7, No. 1, 2014, pp.
955-960.

REFERENCES[1] Austroads 2007, “Guide to Pavement
Technology”, Part 4B Asphalt, Sydney[2] Yeaman 2017 “ Managing Pavement Assets
through In-Situ Monitoring”, World Conference
on Pavement and Asset Management WCPAM
2017 Milan , Italy , June 12/16 2017[3] Yeaman 2017 “The Influence of Subgrade
Moisture Content on Pavement Performance”
under review[4] Gray C ,2014 Final Year Capstone thesis,
University of the Sunshine Coast[5] Westerway K, 2016 “Comparison of asphalt
material characteristics as a function of air void314

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE EFFECT OF LIVE TRAFFIC ON PAVEMENT PERFORMANCE

1

John Yeaman1 and Adrian McCallum1
Faculty of Science, Health, Engineering and Education, University of the Sunshine Coast, Australia
ABSTRACT

For the past four years, the University of the Sunshine Coast (USC) has been monitoring the performance ofroad pavements through “in-situ” monitoring, in association with Sunshine Coast Council and Pavement
Management Services. During that time four sites have been built and monitored, wirelessly, minute by minute24 hours per day. Each monitoring site is equipped with strain gauge sensors at critical positions within the
pavement, moisture gauges and thermocouples. The system is accompanied by a weather station that measures
Rainfall, Air Temperature, Wind Speed and Direction, Relative Humidity, Atmospheric Pressure, and Solar
Radiation.
Analysis of data accumulated over the past four years has been confirmed that pavement stiffness is strongly
influenced by pavement temperature, providing the moisture content remains constant, and that for the most part,
environmental conditions have a greater influence on pavement behaviour than traffic.
Examination of the of traffic and no traffic on the pavement and over a twelve-month study period reveals
that traffic load does not appear to severely jeopardise pavement life, at least early in the pavement life-cycle.
Pavement fatigue occurs due to a combination of numerous factors, one of which is traffic loading. However,in SE Queensland, traffic loading may play a less significant role than other environmental factors such aspavement temperature fluctuations and moisture ingress.
Keywords: Traffic, Moisture, Strain, Pavement performance
270 mm cement treated base with amean stiffness modulus of 3500 MPa.
 50 mm Hot Mix Asphalt pavement
surface.
Sensors are fitted at the base of the stiff layer at a
depth of 320 mm and in the subgrade at a depth of
420 mm in the following configuration:

INTRODUCTION
During December 2012, The University of theSunshine Coast (USC) in association with Sunshine
Coast Council (SCC) and Pavement Management
Services (PMS) installed an insitu pavementmonitoring site on Sippy Downs Drive adjacent to
the University during construction of the pavement
to dual carriageway configuration. Results from thisstudy have been published by Fairweather (2014),
Yeaman (2015) and Azawi (2015), with monitoring
continuing. Two other sites consisting of different
configurations continue to be monitored with respect
to Strain Energy Dissipation and Soil Suction.
As part of this overall research project, Yeaman(2017), at this subject site, postulated thatmaintenance of the pavement asset can be predictedfrom in situ strain outcomes as a function of bothtraffic and the environment .
The subject site is situated at Bellevista
Boulevarde, Caloundra at Latitude S. 26° 47’ 41.28”
and Longitude E. 153° 05’ 49.92” and consists of:

Yellow Podzol subgrade with a stiffnessof 70 MPa
100 mm gravel subbase course with a
stiffness of 145 MPa

Fig. 1315

Pavement and sensor configuration –Bellevista site.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

This section of Bellevista Boulevard, Caloundra
was constructed in September 2013 and has been
instrumented since that date.
Bellevista Boulevard is designed for a 20 year
lifespan with an initial high traffic growth of the first
five years of 8.3% and subsequent 15 years of 5%.
The design traffic is calculated as 5.21 million(5.21*106) Heavy Vehicle Axle Groups for the 20
year design life.
This gives Critical Fatigue Strains of 248 µε fora cemented layer of 3,500 MPa modulus and 1020
µε critical compressive strain for subgrade
deformation. For relationships refer to reference 2
table 8.5.

Strain 2 is the top of the subgrade (subgrade layer).
The negative sign (-) in this instrumentation
indicates that the strain is in tension.
Table 1 Example strain and temperature data.
Tim
e

1/1
1/2
016
6:0
1
1/1
1/2
016
6:0
2
1/1
1/2
016
6:0
3
1/1
1/2
016
6:0
4
1/1
1/2
016
6:0
5
1/1
1/2
016
6:0
6

Solar_Rad
Corrected(W/m2)
44.46

Wind
Dir
1min
(deg)

28.84

Roa
Surface
Temp(degC)
27.76

21.1

28.87

27.77

43.74

166

32.56
7

21.1

28.87

27.77

42.99

218

59.
50
0

32.56
8

21.2

28.87

27.78

41.92

195

‐
19.
09
4

54.
18
8

32.56
6

21.2

28.84

27.76

42.32

114

‐
24.
40
6

59.
50
0

32.56
6

21.2

28.86

27.76

44.04

100

Str
ain
#1
(ue
)
‐
26.
96
9

Str
ain
#2
(ue
)
56.
90
6

Soil‐
Moist
ure1
% (by
vol)
32.56
1

Air
Temp
1min
(degC
)
21.1

Surface Layer
Temp(degC)

‐
21.
68
8

64.
68
8

32.56
9

‐
16.
43
8

59.
50
0

‐
11.
21
9

306

Table 2 Example weather station data.
Fig. 2a Configuration of Pavement Management
Site (G4SMART)

Wind
Speed
1min (m/s)

Wind Dir
1min
(deg)

0.2
0.4
0.5
0.3
0.4
0.3
0.1
0.3

306
166
218
195
114
100
216
147

Rel.
Humidity
1min
(%RH)
88.9
88.8
89
88.9
88.9
88.9
88.9
88.9

Air
Pressure
1min (hPa)1008.31008.31008.41008.41008.41008.31008.31008.3

CLASSIFICATION OF VEHICLE TYPE USEDIN AUSTRALIAThe following vehicle classifications are adopted
for this study (Figure 3).

Fig. 2b Configuration of Pavement Management
Site (G4SMART)
Data in the format of Tables 1 and 2, following,is passed from this site by telephone to a centralcomputer at 6:00 am daily.
Strain 1 is the strain measured at the underside of
the bound layer (HMA and cemented layer) and316

GEOMATE - Mie, Japan, Nov. 21-24, 2017

PEAK HOUR AND QUEUING TRAFFIC
Table 4 shows hourly data for 2016. At this site
there are two peak periods: 7am to 10 am and 2 pm
to 5 pm. In the afternoon the environment isimportant as the pavement is hot, in this case a staticload may cause strains to go to a maximum, as
observed, during the calibration of the Sippy Downs
East site [3] where a standard axle parked on thesensors caused Strain 1 to go to 600με and remain
there until the load was removed after 3 minutes.
This can be compared with the 2012 traffic
survey from which we note the increase in Class 3
traffic due the development of the “Aura” city, a
new development designed to house a population of
300,000 residents [3].
Table 4 Comparison of hourly traffic numbers 2012
to 2016.

Fig. 3 Australian(Austroads [1]).

vehiclePeriod7 am to 10 am
2 pm to 5 pmclassifications

2012 survey
1165
1349

2016 survey
1523
1645

Figures 5 and 6 are typical of the situation as
traffic queues on the site.

ACTUAL TRAFFIC
Sunshine Coast Council conducts regular traffic
counts at the Bellevista site on behalf of the research
project. The following data were used in this study(Figures 4).

Fig. 4 Traffic count for the Bellevista site, 7th to
21st September 2017.

Fig. 5

Queuing traffic – morning peak.

Fig. 6

Queuing traffic – afternoon peak.

Table 3 lists vehicle class [1] and percentage traffic
for 2016.
Table 3 Vehicle class and percentage traffic.
Vehicle class
1
2
3
4
5
6
7

Traffic (%)
91.3
1.6
6.1
0.3
0.3
0.2
0.2
317

GEOMATE - Mie, Japan, Nov. 21-24, 2017

In the afternoon the pavement is at its mostvulnerable with respect to both fatigue cracking andpermanent deformation. In this case, the pavement isboth hot and wet and the static load may cause
strains to increase to a maximum, as observed during
the calibration of the Sippy Downs east site (ref 1)
where a standard axle parked on the sensors caused
the strain1 to go to 600 µε and remain there until
the load was removed after 3 minutes.
Observe here (Fig. 7) three different buses, four
minutes apart of which two are either standing stillor moving very slowly over the sensors with thestrains being in compression and the same order ofmagnitude.

in 1
Stra
in 2
Moi
stur
e
Lay
er
Te
mp
Sfc
Te
mp
Con
diti
on

288 µε184 µε192 µε

9.07 %

9.06 %

9.06 %

30.7 °C

30.4°C

30.3 °C

29.4°C

29.1°C

29.0

Warm & Dry

Warm & Dry

Warm & dry

Fig. 8 Comparison of critical strains for Class 3
vehicle (bus) same day, same time.
Compare this with the afternoon peak where thelast image has the critical fatigue strain in the fatigue
mode (Figure 9).
Tim
e
Stra
in 1
Stra
in 2
Moi
st.
Lay
er
Te
mp
Sfc
Te
mp
Con
diti
on

08:23 14
Nov 1631 µε

08:33 14
Nov 1611 µε

08:44 14
Nov 164 µε

288 µε184 µε192 µε

9.07 %

9.06 %

9.06 %

30.7 °C

30.4°C

30.3 °C

29.4°C
Warm & Dry

29.1°C
Warm & Dry

Time
Strai
n1
Strai
n2
Mois
t.
Laye
r
Tem
p
Sfc
Tem
p
Con
ditio
n

29.0
Warm & dry

Fig. 7 Comparison of critical strains for Class 3
vehicle (bus) same day, same time.
And at the same time, three days later (Figure 8).

14:57; 10
Nov 1630 µε

15:10; 10
Nov 1636µε

15:28 10
Nov 16-16 µε

234µε

243µε

185 µε

8.60%

8.60%

8.60%

33.0°C

33.1°C

33.3°C

36.8°C

37.0°C

37.2°C

Warm &Dry

Warm &Dry

Warm & dry

Fig. 9 Comparison of critical strains for Class 3
vehicle (bus) same day, same time.
‘ROGUES GALLERY’
Tim
e
Stra

08:23 14
Nov 1631 µε

08:33 14
Nov 1611 µε

One of the features of this in-situ monitoring iswhat we have termed the “Rogues Gallery”. In
essence a trigger is set in the data collection softwarethat takes a photograph of the site whenever a strain

08:44 14
Nov 164 µε
318

GEOMATE - Mie, Japan, Nov. 21-24, 2017

exceeds a predetermined value. In this case, wehave chosen initially a value of ± 180 με.

Fig. 12 Strain for Class 3 vehicles.

Fig. 10 A concrete pumper has exceeded the‘trigger’ strain value.
This method was used over the 12-month study
period to classify the strain exerted by various
vehicle classes with the following results (Figure 11,12, 13 & 14).

Fig. 13 Strains for Class 4 vehicles.

Fig. 11 Strain for Class 1 & 2 vehicles.

Fig. 14 Strains for vehicles Class 5 through 12.

319

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Of interest, here is the fact that the strains are
increasing from December 2015 to December 2016.
LATENT STRAIN
The ‘rogue’s gallery’ was observed on manyoccasions to produce multiple photographs without
the presence of traffic especially early in themorning.
These following figures (Figs 15 & 16)
demonstrate Strains without traffic for the full year.
Fig. 17 Resilient Modulus (Mallick and El-Korchi,
2015)
It is the accumulation of this plastic strain that
we see incorporated within the Latent Strain. When
this value reaches the ultimate critical strain, thepavement will have deemed to be failed.
CONCLUSIONAt this time, the Bellevista pavement isperforming within the design criteria. Traffic is not aserious issue with this pavement after almost one
quarter of the design life. Latent Strain is increasing
according to theory but is well below the criticalfatigue value for the bound layer of 428με and 1020
με for the subgrade layer. Although this study is of alimited nature it does serve to prove that in -situ
monitoring can be a useful tool to understand theimpact of traffic on a cemented pavement.

Fig. 15 Strain 1 for no traffic.

REFERENCES[1] Austroads (2008) “ Guide to Pavement
Technology” Part 2: Pavement
Structural
Design[2] Kimmel B (2014) “The Instrumentation of theentrance to Bella Vista Subdivision at
Caloundra” Capstone project thesis Universityof the Sunshine Coast[3] Fairweather, H., and J. Yeaman. A Study of theParameters Affecting the Performance of Roads
Under an Extreme Rainfall Event. International
Journal of GEOMATE, Vol. 7, No. 1, 2014, pp.
955-960.

Fig. 16 Strain 2 for no traffic.
The values for these strains have increased withtime without the influence of traffic .We have called
this “Latent Strain”. Environmental conditions are
increasingly observed to play a significant part inpavement fatigue (Yeaman and McCallum, 2017a;
Yeaman and McCallum, 2017b).
DIGRESSION – RESILIENT MODULUS
Recall the theory behind the measurement ofresilient modulus (Figure 17).

320

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LIQUEFACTION SIMULATION FOR THE OSAKA GULF COAST
USING THE LIQCA PROGRAM
1,2

Tetsuya Okano1, Keita Sugito2 and Ryoichi Fukagawa3
Graduate School of Science and Engineering, Ritsumeikan University, Japan;
3
Department of Civil Engineering, Ritsumeikan University, Japan

ABSTRACTA Nankai megathrust earthquake is expected to occur in the Kansai area within the next 30–40 years. According
to the worst-case estimations by The Headquarters for Earthquake Research Promotion [1], the earthquake willcause economic losses of approximately 220 trillion yen, and 134,000 buildings will be damaged by liquefaction.
To estimate future damage to the Osaka gulf coast, we conduct liquefaction simulations based on the LIQCA
program developed by the research group at Kyoto University. The liquefiable layers are composed of relatively
loose sand and the underground water level is high. The input earthquake motion is the L2 spectrum Ⅰ earthquakeresistant standard spectrum, according to the Design Standards for Railway Structures and Commentary [2]. We
consider not only the increase of excess pore water pressure, but also its dissipation. The calculated effective
stresses in the sand layers approached 0, after which the sand layers liquefied and unevenness occurred at the
ground surface. We evaluated the damage due to liquefaction by calculating vertical displacements and unevennessof the ground surface. Countermeasures are proposed for the shallow sand layers to reduce future liquefaction
damage.
Keywords: Liquefaction, Simulation, Nankai megathrust earthquake, Gulf coast, Unevenness
INTRODUCTION
Geo-Research Institute (LIQCARI), consisting ofresearchers from Kyoto and Gifu universities.

A Nankai megathrust earthquake is predicted for
the Kansai area within the next 30-40 years. The mostrecent Nankai megathrust earthquake occurred in1946 and the recurrence interval of this type ofearthquake is over 100 years, according to The
Headquarters for Earthquake Research Promotion [1].
If a Nankai megathrust earthquake were to occur, theeconomic losses would be approximately 220 trillion
yen, and 134,000 buildings would be damaged byliquefaction in the worst-case scenario [3], [4]. In
addition, a Tokai megathrust earthquake has notoccurred for 168 years, even though the recurrence
interval of a Tokai megathrust earthquake is also 100
years. It is expected that a Tokai megathrustearthquake would induce the occurrence of a Nankai
megathrust earthquake earlier than suggested by its
recurrence interval. A Nankai megathrust earthquake
would cause huge damage to the Kansai area. Within
this area, Osaka city has a significant effect on thenational economy and it contains many embankment
areas, which tend to liquefy more than other natural
ground types. In addition, the high ground waterlevels of Osaka city would enhance liquefaction.
Therefore, it is important to fully comprehend soilliquefaction characteristics. This paper presents anevaluation of ground liquefaction characteristics for
the Osaka Gulf coast. A liquefaction analysis is
implemented to assess the liquefaction characteristics.
For the scope of this study, the Computer Program for
Liquefaction Analysis (LIQCA) is used. This
software was developed by the LIQCA Liquefaction

SIMULATION CONDITIONSThe subject of analysis in this research is a site on
the Osaka Gulf coast. A cross sectional view of thestudy area is shown in Figure 1. The cross section
contains an embankment layer, which isapproximately 0.4 m to 0.5 m thick. The ground waterlevel is GL-2.3 m.
In this study, we consider the effect of a clay layer(Ac1) and a structure on the liquid sand layer. The
influence of the Ac1 layer between the sand layers Bs
and As1 is evaluated by considering the thickness of
the Ac1 layer. In addition, the influence of a structure
is evaluated by comparing the point that bears theload of the structure and the point that does not bear
any load. Point A is most affected by the load of thestructure and the clay layer Ac1 is thinnest at thispoint. Point B does not bear the load of the structure
and the clay layer Ac1 is thick here. Point C bears
some of the load of the structure and the clay layer
Ac1 is moderately thick at this point. By comparing
the results at these three points, we consider the effectof the clay layer between the liquefaction target layers
and the liquefaction damage due to the structure.

321

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The cross section in Figure 1 includes a structurein the form of a building, modeled as a point load in
the LIQCA program. It is hypothesized that this point
load will affect liquefaction damage. We evaluate theeffect of the load on liquefaction through the presence
and absence of the load.
Analysis parameters are based on the DesignStandards for Railway Structures and Commentary[2]. LIQCA specific parameters are based on theiroperating manual. Dynamic parameters are
determined using element simulation.
At first, all soil layers are classified as those that
determine the target of liquefaction (‘LiquefactionLayers’) and those that determine the non-target ofliquefaction (‘Non-Liquefaction-Layers’) based on[2]. Non-Liquefaction Layers are modeled using theRamberg-Osgood (R-O) model. Liquefaction-Layers
are modeled using the cyclic elasto-plasticity
constitutive model. The parameters of these models
are shown in Table 1 and Table 2, respectively.
The coefficients of permeability k of Bs, As1, As2,
and Tsg1 are determined based on a permeability test
conducted in the study area. The rest are determinedbased on the Creager method. The shear wave
velocity, Vs, is determined from the Design Standards
for Railway Structures and Commentary [2]. The Oc
layer is considered as an engineering base surface.
The unit weight γ in the Bs, As1, As2, and Tsg1 layers
is determined from a mean density soil test in the
study area; the rest are determined from the DesignStandards for Railway Structures and Commentary[2]. Other specific parameters and the dynamic
parameters are determined using the LIQCA programand element simulation.

Table 1 Material parameters of the R-O model
Tc1

Tsg2

Tc2

Oc

Un-sat.
1.8
1.4
×10-6
0.658
120
0.49

Ac1
Ac2
Ac3
Sat.
1.6
9.0
×10-10
1.038
120
0.496

Sat.
1.6
2.6
×10-7
0.724
200
0.494

Sat.
1.8
1.2
×10-5
0.777
260
0.488

Sat.
1.6
1.0
×10-7
1.098
208
0.492

Sat.
1.6
7.5
×10-9
1.799
208
0.492

0

33

198

0

149

149

Bs
ρ
k
e0
Vs
ν
c
(kPa)
φ
(deg)
a
b
α
r

30.9

0

0

34.0

0

0

6977
0.5
1.89
1.92

2241
0.5
-

4939
0.5
2.3
2.1

8530
0.5
2
3

4533
0.5
1.4
1.7

4165
0.5
1.5
1.6

Table 2 Material parameters of the cyclic elastoplastic constitutive model
ρ
k
e0
Vs
λ
κ
OCR*
G0/σ'm0
M*m
M*f
B*0
B*1
Cf
γP*
γE*r
D*0
n
Cd

Bs
Sat.

As1
Sat.

As2
Sat.

1.8
1.5E-6
0.658
140
0.002
0.025
1.3
935.5
0.909
1.012
3500
80
0
0.02
0.001
1
7
2000

1.8
1.5E-6
0.990
120
0.002
0.02
1.0
445.3
0.909
0.966
2500
50
0
0.002
0.3
1.5
2
2000

1.8
1.1E-6
0.673
170
0.1
0.02
1.0
646.1
0.909
0.958
5000
100
0
0.02
0.3
4
6
2000

Tsg1
Sat.
1.8
5.2E-6
0.505
240
0.001
0.001
1.6
1104
0.909
1.215
10000
200
0
0.005
0.001
4
8
2000

Fig. 1 Cross section of the study area showing the different soil layers.
322

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Input Seismic Vibration
SIMULATION RESULTS
The input seismic vibration is the H24 L2
earthquake-resistant standard spectrum, shown in
Figure 2. It is designed by the Design Standards forRailway Structures and Commentary [2].

Here, we consider the results in terms ofdisplacements and acceleration, the effective stress
reduction ratio, the angle of rotation, and therelationship between effective stress reduction andvolume strain, respectively.
Displacements and Acceleration
Figures 3, 4, and 5 show the time series of thehorizontal acceleration response, the horizontal
displacement response, and the vertical displacement
response, respectively. Table 3 shows the maximum
absolute values of displacement and acceleration on
the ground surface during shaking. Table 4 shows thedisplacements on the ground surface during thedissipation stage of excess pore water pressure.
Each horizontal acceleration of the output node isconverged. Once again, every output node is selectedfrom the ground surface on the longitudinal plane.
After all horizontal accelerations are converged, adissipation stage of excess pore water pressure
analysis is conducted. The time series of horizontal
acceleration show the same trend and the maximum
absolute value of horizontal acceleration isapproximately 2.0 m/s2 (Figure 3).
Each horizontal displacement of the output node
is converged, as with the horizontal accelerations.
The maximum absolute value of the horizontal
displacement of three output points is approximately
0.847 m. Although the time series of horizontal
displacement show the same trend, the final
displacements are different (Figure 4). The further tothe right the point is on the longitudinal plane, thelarger the horizontal displacement.
Again, each vertical displacement of the output
node is converged. The vertical sinking was largest at
point A, where the clay layer, Ac1, is thinnest (Figure5). Point B rose slightly due to lateral flow from thethinnest point of the clay layer.
Looking at the time series, when maximum
acceleration occurred and the excess pore waterpressure rose sharply, the ground surface vibrated
slightly. After that, with dissipation of the excess porewater pressure, points A and C experienced verticalsinking. In response to this, the ground surface atpoint B rose, but subsequently there was slightvertical settlement following dissipation of the excess
pore water pressure of the target layer under point B.
Regarding the effect of the structure, the groundsurface of point A and point C dropped significantly
under the load. Because of this reaction, the groundsurface at point B underwent significant flow. Since
the ground surface at point A received a larger load
than point C, point A dropped further.
After this, the excess pore water pressure

Fig. 2 Input seismic vibration.
Element Simulation
The specific parameters of Liquefaction-Layers
are determined by fitting the liquefaction strength
curves from the Design Standards for Railway
Structures and Commentary [2]. The specificparameters
of
Non-Liquefaction-Layers
aredetermined by fitting the dynamic deformation
characteristics from the Yasuda-Yamaguchi
equations [5].
The liquefaction resistance is regulated by the
number of cycles. The liquefaction layer is supported
in a simple shear test with a double amplitude of axial
strain (DA) of 7.5%, and the number of cycles
regulating the strength of the liquefaction is 20. The
cyclic shear stress ratios of Bs, As1, As2, and Tsg1
are 0.43, 0.35, 0.31, and 0.31, respectively.
Initial Conditions
We conduct an initial effective stress analysis,
where the mean effective stress with static
overburden pressure is analyzed for the case where
the coefficient of earth pressure, K0, is 0.5. All layers
are modeled using the Drucker-Prager type plasticity
models. Poisson’s ratios are determined as 0.33 for K0=0.5. The Young’s modulus, E, was determined byconsidering the influence of the effective overburdenpressure (Eq. 1), as follows:
𝐸𝐸 = 𝐸𝐸0 𝜎𝜎𝑚𝑚0 𝑛𝑛(1)

𝑬𝑬𝟎𝟎 : Constant of proportionality of Young's modulus(kN/m2)𝝈𝝈′𝒎𝒎𝒎𝒎 : Average effective stress in initial stress state(kN/m2)The side boundary condition is the verticalroller support and the bottom boundary conditionis fixed. After the effective stress analysis, alldisplacements and pore water pressures are set to 0.
323

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Horizontal acc. (m/s2)

dissipated to between 1×104 and 1×108 seconds andthe ground surface at all points experienced sinking.

effective stress reduction ratio of the Bs layer.
The excess pore water pressures of the sand, As1,
As2, and Tsg1 layers rose more than that of the Bs
layer. Because the Bs layer is closer to the groundwater level than other sand layers, the excess porewater pressure of the Bs layer dissipated more quickly
than that of the other layers.
Regarding the difference between the output
points, point B required more time for dissipation of
the excess pore water pressure than other points. We
consider that the thickness of the upper clay layer isrelated to the time required for dissipation of theexcess pore water pressure. A thicker clay layer
results in a longer dissipation time for the sand layer.
Because As1, As2, and Tsg1 layers are above the clay
layer, Ac1, their dissipation times are longer than thatof the Bs layer.

3.0
A
B
C

2.0
1.0
0.0
-1.0
-2.0
-3.0

0

150

100
Time (s)50200Fig. 3 Time series of the horizontal acceleration
response.
Horizontal dis. (m)

1
0.8
0.6
0.4
0.2
0
-0.2
-0.4

A
B
C
0

50

100
Time (s)

150

200

1.0

1-σ'm/σ'm0

Vertical dis. (m)Fig. 4 Time series of the horizontal displacement
response.
0.3
0.1

0.8

0.4
0.2
0.0
1E+0

0.0

A
C

0.6

1E+2

-0.1
A
B
C

-0.3
-0.4
1E+0

1E+4
step (s)

1E+6

1E+8

Fig. 6 The effective stress reduction ratio of the Bs
layer.
1E+2

1E+4
Time (s)

1E+6

1E+8
1.0
1-σ'm/σ'm0

Fig. 5 Time series of the vertical displacement
response.
Table 3 Maximum absolute value of displacements
and acceleration on the ground surface during shaking

A
B
C

0.6
0.4
0.2
0.0
1E+0

1E+2

Acceleration (m/s2)

Horizontal

VerticalHorizontal

A

0.847

-0.355

2.020

B

0.440

0.088

1.649

C

0.631

-0.163

2.079

Verticaldisplacement (m)displacement (m)

A

0.846

-0.355

B

0.437

0.042

C

0.626

-0.162

1E+6

1E+8

1.0

Table 4 Displacements on the ground surface during
the dissipation stage of excess pore water pressure
Horizontal

1E+4
step (s)Fig. 7 The effective stress reduction ratio of the As1
layer.

1-σ'm/σ'm0

Displacement (m)

0.8

0.8

A
B
C

0.6
0.4
0.2
0.0
1E+0

1E+2

1E+4
Time (s)

1E+6

1E+8

Fig. 8 The effective stress reduction ratio of the As2
layer.

Effective Stress Reduction Ratio
Figures 6, 7, 8, and 9 show the effective stress
reduction ratio of Bs, As1, As2, and Tsg1,
respectively. Table 5 shows the effective stress
reduction ratios during shaking. There is no Bs layer
at the B output point, so the table does not include the324

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Relationship between the Effective
Reduction Ratio and Volume Strain

1-σ'm/σ'm0

1.0
0.8

A
B
C

0.6
0.4

Regarding the excess pore water pressure, theeffective stress reduction ratio of the As2 and Tsg1
layers reached 1, indicating liquefaction. This resultshows that deeper layers can liquefy. However, theAs1 layer and the Bs layer were responsible forsignificant vertical sinking and horizontal
displacement. Figure 12, 13, 14 and 15 show the timeseries of volume strain of Bs, As1, As2 and Tsg1,
respectively. Figure 16 shows the relationshipbetween the effective stress reduction ratio andvolume strain. As a result, even though the sand layer
at a relatively large depth was liquefied, the amountof volume strain is considered small.
In the study area, the Bs and As1 layers, which are
the sand layers near the ground surface, are greatly
deformed. Therefore, it is necessary to propose
countermeasures.

0.2
0.0
1E+0

1E+2

1E+4
Time (s)

1E+6

1E+8

Fig. 9 The effective stress reduction ratio of the Tsg1
layer.
Table 5 Effective stress reduction ratios during
shaking
Bs

As1

As2

Tsg1

2.9%

61.3%

98.8%

98.8%

B

-

79.5%

96.1%

96.7%

C

21.1%

55.4%

99.0%

99.0%

A

Angle of Rotation

Volume strain

2.0E-2
1.5E-2AC

1.0E-2
5.0E-3
0.0
1E+0

1E+2

1E+4
Time (s)

1E+6

1E+8

Fig. 12 Time series of volume strain of the Bs layer.
Volume strain

2.0E-2
1.5E-2
1.0E-2A
B
C

5.0E-3
0.0
1E+0

1E+2

1E+4
Time (s)

1E+6

1E+8

Fig. 13 Time series of volume strain of the As1
layer.

180.0
179.7
179.4
Finish Acc.

179.1

2.0E-2

Converged

Volume strain

Angle of rotation (deg)Figures 10 and 11 show the angle of rotation at the
ground surface and the vertical displacement at the
ground surface, respectively.
The angle of rotation is an index indicating thedegree of unevenness. It is an angle represented by
the absolute value of a certain node and the angle
between two adjacent nodes. For example, it ishorizontal when it is 180° and vertical when it is 90°.
The angle of rotation decreased the most aroundthe point at which the load was applied. The groundtilted approximately 0.9° at the point that was most
severely affected. Ground unevenness when the
shaking ended and when the dissipation stage ofexcess pore water pressure converged showed thesame trend. Therefore, it is considered thatliquefaction and loss of strength would occur in a
relatively short time.

178.8
178.5
0

100

200

300

400

500

600

700

1.5E-2
1.0E-2A
B
C

5.0E-30.0
1E+0

Fig. 10 Angle of rotation at the ground surface.

1E+2

1E+4
Time (s)

1E+6

1E+8

Fig. 14 Time series of volume strain of the As2 layer

44.5

2.0E-2Finish Acc.
Convergedt0

44.0

Volume strain

Vertical displacement (m)Stress

43.5
43.0
42.5
42.0
0

100

200

300

400

500

600

1.5E-2
1.0E-2
5.0E-3
0.0
1E+0

700

A
B
C

1E+2

1E+4
Time (s)

1E+6

1E+8

Fig. 15 Time series of volume strain of the Tsg1
layer.

Fig. 11 Vertical displacement at the ground surface.

325

GEOMATE - Mie, Japan, Nov. 21-24, 2017

REFERENCES

1.0
Bs
As1
As2
Tsg1

Effective stress reduction ratio

0.8[1] The Headquarters For Earthquake Research
Promotion, “Past earthquake occurrence
situation”, Earthquakes occurring in the Nankai
Trough,http://www.jishin.go.jp/main/yosokuchizu/kaiko/k_nankai.htm (accessed 2017-06-05)[2] Railway Technical Research Institute, DesignStandards for Railway Structures andCommentary, 2012.
[3] Nihon Keizai Shimbun, Inc., “Estimated damage
amount of the Nankai Trough massive
earthquake”, Nankai Trough Earthquake,damage amount of up to 220 trillion yen Halvedbyreduction,
http://www.nikkei.com/article/DGXNASDG180
2L_Y3A310C1000000/ (accessed 2017-06-05)[4] Disaster Management, Cabinet office, “Aspect ofImmediate Disaster”, About the damage estimateof the Nankai Trough massive earthquake,
http://www.bousai.go.jp/jishin/nankai/taisaku_
wg/pdf/20130318_shiryo2_1.pdf,(accessed
2017-0605)[5] Yasuda S. and Yamaguchi I., “Dynamic soil
properties of undisturbed samples.”, Proceedingsof 20th Japan National Conference on
Geotechnical, 1985, pp539:542.

0.6

0.4

0.2

0.0
0.0

4.0E-38.0E-3

1.2E-2

1.6E-22.0E-2

Volume strain

Fig. 16 Relationship between volume strain and theeffective stress reduction ratio.
CONCLUSION
Liquefaction simulations using the LIQCA
program showed that the ground surface on the Osaka
gulf coast would sink by a maximum of 0.355 m andmove horizontally by a maximum of 0.847 m due toliquefaction. In addition, if there is a structure on the
ground surface, the sand would liquefy due to asudden loss of strength. Conversely, parts of theground surface would rise as a reaction to the sinking
elsewhere.
Shallow sand layers were displaced more thandeep sand layers by liquefaction. Regarding theeffective stress reduction ratio, the shallow sandlayers did not liquefy much, although they did
experience significant sinking. The shallow sandlayers moved horizontally because LiquefactionLayers lose strength due to liquefaction. Therefore,
the possibility of damage of liquefaction on the
ground at Osaka Gulf Coast is considered high.

326Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

NUMERICAL SIMULATION OF LIQUEFACTION AND RELATEDBEHAVIOR OF UNDERGROUND STRUCTURE ON OSAKA GULF
COAST
1, 2

Keita Sugito1, Tetsuya Okano2 and Ryoichi Fukagawa3
Graduate School of Science and Engineering, Ritsumeikan University, Japan; 3Department of Science andEngineering, Ritsumeikan University, Japan
ABSTRACTThe Kansai area has a high possibility of a huge plate-boundary-type earthquake within 30 years. If an
earthquake occurs, the Osaka Gulf coast will be struck by severe liquefaction disasters. Therefore, we tried toapply LIQCA, which is often used for liquefaction analysis, to a site on the Osaka Gulf coast. The input
earthquake motion is the seismic standard spectrum I, which is commonly used in Japan. The calculation time
continued until the excess pore water pressure dissipated. The site has an underground structure, so weinvestigated not only the liquefaction phenomenon of the ground itself but also the behavior of the undergroundstructure. The results of this analysis indicate that these soil layers of the target area become liquefied. After theexcess pore water pressure dissipates, the ground surface settles in the vertical direction and moves in thehorizontal direction. In addition, at the vicinity of the underground structure center, it rises in the verticaldirection and moves in the horizontal direction.
Keywords: Liquefaction, Numerical Simulation, Tunnel, Float up
INTRODUCTION
A Nankai trough earthquake, which is a plateboundary-type huge earthquake, has a highprobability of occurring within 30 years, and thewestern part of Japan will be severely damaged bythis earthquake. The Osaka Plain is no exception. In
particular, the Osaka Gulf coast is predicted to sufferfrom a severe liquefaction disaster [1]. Therefore,
we apply a liquefaction simulation to a typical siteon the Osaka Gulf coast. The simulation is based on
the LIQCA [2] program, which is widely used as aliquefaction simulation tool in Japan. The target
ground has a tunnel beneath the ground, so weinvestigated not only the liquefaction phenomenonof the ground itself but also the behavior of theunderground structure.
OUTLINE OF ANALYSIS
Ground to be analyzed

Other layers are composed of clayey soil and hard,
sandy soil. Thus, it is considered that liquefaction
barely occurs. Therefore, these layers are not judged
for liquefaction.
The groundwater level is set at GL-2.3 m. The
Oc layer is the base surface in this cross section. In
the B layer, the layer above the groundwater level isconsidered hard to liquefy, so the R-O model isapplied to this layer. The layer below thegroundwater level is modeled as a cyclic
elastoplastic constitutive model. Table 1 lists thematerial parameters used in the analysis. Theliquefaction layers and non-liquefaction layers are
fitted based on the respective standards. Theliquefaction layers have liquefaction strength curves
based on the Design Standards for Railway
Structures and Commentary [3]. The nonliquefaction layers are fitted as a Yasuda-Yamaguchi
model [4].

The analysis target is the ground of a plain on the
Osaka Gulf coast. Figure 1 shows the cross sectionof the ground that is the target of the analysis. The
cross section has a length of 100 m in the horizontal
direction and a depth of 40 m in the verticaldirection. The tunnel is located near the surface inthe center of the ground. The soil layers that may
liquefy are the As1 layer, As2 layer, and Tsg1 layer.

327

GEOMATE - Mie, Japan, Nov. 21-24, 2017

OP+4.000m

Belevation

groundwater

B

Ac1

level

Ac1

As1

As1

Ac2

Ac2

As2

As2

Tsg1

Tsg1
Tc1

Tc1
Tsg2

Tsg2

Tc2

Tc2

Oc(Ma12)Oc(Ma12)OsOshorizontal distanceFig. 1 Target ground of the analysis
Table 1 Material parameters used in analysis①
typeγ(kN/m3)ρ(g/cm3)
k
(m/s)
e0
Vs
(m/s)
λ
κ
OCR*
G0/σ'm0
M*m
M*f
B*0
B*1
Cf
γP*r
γE*r
D*0
n
Cd
ν
c (kPa)φ (deg)
a
b
α
r

Y

Bs

②
X

As1
X

③
Ac1,
Ac2
Y

④

⑤

⑥

⑦

⑧

⑨

As2
X

Tsg1
Y

Tc1
Y

Tsg2
Y

Tc2
Y

Oc
X

18.0

18.0

18.0

16.0

18.0

16.0

18.0

16.0

16.0

18.0

1.8
1.47
E-06
0.658

1.8
1.47
E-06
0.658

1.8
1.47
E-06
0.990

1.6
9.00
E-09
1.038

1.8
5.17
E-06
0.505

1.6
2.60
E-07
0.724

1.8
1.20
E-05
0.777

1.6
1.00
E-07
1.098

1.6
7.50
E-09
1.799

1.8
1.12
E-06
0.673

120

140

120

120

240

200

260

208

208

170

0.002
0.025
1.3
935.5
0.909
1.012
3500
80
0
0.02
0.001
1.0
7.0
2000

0.002
0.02
1.0
445.3
0.909
0.966
2500
50
0
0.002
0.3
1.5
2.0
2000

0.496
0
30.9
6977
0.5
1.89
1.92

0.496
33
0
2241
0.5
16.7
1.78

0.001
0.001
1.6
1104
0.909
1.215
10000
20
0
0.005
0.001
4.0
8.0
2000

328

0.494
198
0
4939
0.5
2.3
2.1

0.488
0
34
8530
0.5
2
3

0.492
149
0
4533
0.5
1.4
1.7

0.492
149
0
4165
0.5
1.5
1.6

0.1
0.02
1
646.1
0.909
0.958
5000
100
0
0.02
0.3
4
6
2000

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Notations:
X: cyclic elastoplastic constitutive model
Y: R-O modelγ = unit weight, ρ = density, k = coefficient of
permeability, e0 = initial void ratio, Vs = shear wave
velocity, λ = compression index, κ = expansion
index, Mf = stress ratio parameter corresponding to
failure angle, OCR* = factoid overconsolidation
ratio, G0/σ’m0 = non-dimensional initial shear
modulus, Mm = stress ratio parameter corresponding
to phase transformation angle, B*0, B*1, and Cf =plastic modulus parameters, γrP* = plastic strain, andγrE* = elastic strain, D*0, n = dilatancy coefficient, Cd= anisotropy elimination parameter, ν = Poisson’s
ratio, c = cohesion, φ= internal friction angle, and a,b, α, and r = R-O parameters

Boundary conditions
Soil skeleton
In the analysis model, the bottom of theboundary is an elastic base (viscous boundary). The
elastic base is placed as a dashpot on the bottom of
the model. The input earthquake motion is a 2E
wave. In LIQCA, only the horizontal lower
boundary can be set for the viscous boundary. Whena consolidation analysis is conducted, the dashpot is
automatically replaced with a rigid spring. The sideboundary is a method of connecting a wide freeground part, which is not easily influenced by the
FEM region, to the side surface when the soil layer
configuration of the side boundary is different.
TunnelThe boundary condition between the tunnel andadjacent ground is free from friction in the verticaldirection. The tunnel and its adjacent ground behave
similarly in the horizontal direction.

Tunnel model
Figure 2 shows model of the ground with thetunnel. The green lines indicate the tunnel. The
tunnel consists of an upper base plate and a lower
base plate, a sidewall, and a center pillar. The tunnel
is represented by beam elements. Table 2 lists thetunnel parameters used in the analysis. B is thehorizontal length of the element, and H is thevertical length of the element.

Input earthquake motion
The input earthquake motion is the seismic
standard spectrum I, which is commonly used inJapan. The waveform is shown in Fig. 3. The
increment of the calculation time is 0.005 s. The
Newmark method coefficients are β = 0.3025 and γ= 0.6. These values are common in LIQCA
simulations. The constant of the Rayleighattenuation α1 is equal to 0.001–0.003. The Rayleighattenuation α1 in the example of the LIQCA manual
is 0.0023. After seismic motion, consolidation
analysis is carried out until the vertical settlement
converges.
600

Fig. 2 Tunnel model

acc-y(cm/s2)

acc-y(cm/s2)

400
200
0
-200
-400

耐震標準スペクトルⅠ

-600
0

50

A max =524.10(gal)

100

150

time(s)Fig. 3 Waveform of seismic standard spectrum I
Table 2 Tunnel parametersbase plate(upper)base plate(lower)side wall
center pillar

Unit volume
weightγ(kN/m3)

Sectional Secondary
momentI(m4)Unit length
WeightG(kN/m)

B
(m)

H
(m)

Pitch
(m)

1

0.3

1

25

0.30

0.001125

7.5

1
1
2.3

0.4
0.4
0.4

1
1
4

25
25
25

0.40
0.40
0.23

0.002667
0.002667
0.001533

10
10
5.75

Sectional area
A(m2)

329

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Initial stress analysis

effective stress reduction ratio

1

The initial values of the soil skeleton
displacement and excess pore water pressure are all
0. The soil skeleton displacement and excess porewater pressure in LIQCA are the increments fromthe initial state, that is, the incremental values at thetime of the earthquake. What is necessary under the
initial conditions is to set the initial effective stressof the ground. Therefore, it is important to estimate
the initial stress state in the ground. The initial stressanalysis in this paper is a self-weight analysis. The
self-weight analysis calculates the initial stress byapplying self-weight to the model used for theliquefaction analysis in the zero-gravity state. It
considers the increase in ground rigidity andnonlinearity caused by adding weight to the model.

,

0.2
0

As1
10

103

10

103

10

103

105

107

time (s)105

107time (s)105

107time (s)109effective stress reduction ratio

0.8
0.6
0.4
0.2
0
-0.2
0.1

As2
109

effective stress reduction ratio

1
0.8
0.6
0.4
0.2
0

Tsg1

-0.2
0.1

109

Fig. 4 Effective stress reduction ratio of As1, As2,
and Tsg1 (25 m northward from tunnel center)
0.1
0vertical displacement (m)

1

0.4

1

The analysis results are shown below. After theearthquake motion, a consolidation analysis was
carried out until the convergence of the verticaldisplacement was confirmed. The effective stress
reduction ratio R is used as an index for determiningliquefaction. It is shown in the following equation:
R

0.6

-0.2
0.1

ANALYSIS RESULT

,

0.8

(1)

σ’m ： average effective stress corresponding tosome elapsed time (kN/m2)
σ’m0：average effective stress in the initial stressstate (kN/m2)

-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
0.1

10

103

time (s)

105

107

109

Fig. 5 Vertical displacement(25 m northward from tunnel center)

When this value reaches 1, it can be said thatliquefaction occurred in the ground. The nodes andelements that output the analysis results are thevicinity of the tunnel center and the stratum of thepoint 25 m northward from the tunnel center.

horizontal displacement (m)0.4

At the stratum of the point 25 m northward fromthe tunnel center

0.2
0
-0.2
-0.4
-0.6
-0.8
-1
0

40

80

time (s)120160Fig. 6 Horizontal displacement(25 m northward from tunnel center)

Figure 4 shows the effective stress reduction
ratio of As1, As2, and Tsg1. According to theseresults, it turns out that these soil layers becomeliquefied. The effective stress reduction ratio
decreases after 108 s (approximately 3 years). This
indicates that the excess pore water pressure that
occurs by liquefaction is dissipated, and theconsolidation settlement converged. Figures 5 and 6
show the vertical displacement and horizontal
displacement, respectively. After the excess porewater pressure dissipates, the ground surface settles
by 0.5 m in the vertical direction and moves 0.8 m in
the horizontal direction.

At the vicinity of the tunnel center
Figure 7 shows the effective stress reduction
ratio of As1, As2, and Tsg1. According to theseresults, it turns out that these soil layers becomeliquefied. Figures 8 and 9 show the verticaldisplacement
andhorizontal
displacement,
respectively. After the excess pore water pressure
dissipates, the tunnel rises by 0.9 m in the verticaldirection, and moves 0.8 m in the horizontal
direction.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 3

effective stress reduction ratio

1

Effective stress reduction ratio(just after excitation)

0.8
0.6

Effective stress reduction ratio (%)
As1
As2
Tsg1
99.9
99.9
99.9
99.9
99.9
99.9

0.4
0.2

A
B

0
-0.2
0.1

As1
103

10

time (s)

105

107

109

effective stress reduction ratio

1

Table 4 Effective stress reduction ratio(after excess pore water pressure dissipates)

0.8
0.6
0.4

A
−0.7330.898

0.2

horizontal displacement (m)Vertical displacement (m)

0

-0.2
0.1

As2
103

10

time (s)

105

107

109

effective stress reduction ratio

1

Displacement of the ground surface

0.8
0.6

Figure 10 shows the vertical displacement foreach time history. The data corresponds to the stateof the initial coordinate after excitation and after
consolidation of the ground surface coordinates. The
part from 45 to 55 m of the X coordinate is thetunnel position. When the state, after the excess porewater pressure dissipates, is examined, it can beseen that the tunnel rises by 0.9 m. Thisphenomenon is caused by the boundary condition
between the side surface of the tunnel and thesurrounding ground. The boundary was set under afree condition in the vertical direction, which has nofriction. Therefore, a settlement of 0.9 m is thought
to be the maximum floating amount.
In this analysis, we do not consider the changes
in the buoyancy of the surroundings owing to thefloating of the tunnel. In other words, the buoyancy
around the tunnel remains in its initial state. In
addition, this is considered to be a cause of the large
level of floating of the tunnel. The other surface part,
except for the tunnel position, settles atapproximately 0.5 m after the excess pore waterpressure dissipates.

0.4
0.2
0

Tsg1
-0.2
0.1

103

10

time (s)

105

107

109

Fig. 7 Effective stress reduction ratio of As1, As2,
and Tsg1 (tunnel center)vertical displacement (m)

1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
0.1

103

10

time (s)

105

107

109

Fig. 8 Vertical displacement (tunnel center)0.4
horizontal displacement (m)B−0.758−0.496

0.2
0
-0.2
-0.4
-0.6
-0.8

2
initial coordinate

-1

0

40

80 time (s)120after excitation

160

after consolidation

1.5

Fig. 9 Horizontal displacement (tunnel center)
Y (m)

1

0.5

Summary of some indices0

Table 3 lists the results of the effective stress
reduction ratio (just after excitation). Table 4 lists
the results of the effective stress reduction ratio(after excess pore water pressure dissipates). Point A
corresponds to the stratum, which is 25 m northwardfrom the tunnel center. Point B corresponds to thevicinity of the tunnel center.

-0.5
0

20

40

60

80

100

x (m)

Fig. 10 Vertical displacement for each time history
Deformation map of the groundFigure 11 shows the deformation of the groundaround the tunnel after the excess pore waterpressure dissipates. The floating of the tunnel may
331

GEOMATE - Mie, Japan, Nov. 21-24, 2017

depend on how the sediment cuts under the tunnel
tunnel becomes liquefied. The floating of the tunnel
is approximately 0.9 m. However, this value isperhaps the maximum floating amount, as
mentioned earlier. In fact, there is friction between
the tunnel and the surrounding ground, so it is highly
likely that the floating of the tunnel may have asmaller value than that of the analysis result.

when
the
As1
layer
aroundtheaddition, we did not consider the changes in thebuoyancy of the surrounding ground. We think that
it is necessary to make this phenomenon more
realistic. The buoyancy problem may be difficult.
Therefore, we will further investigate the boundary
condition between the sidewall of the tunnel and theadjacent ground. We will conduct more realistic
simulations.

CONCLUSIONREFERENCES

When an earthquake corresponding to seismic
standard spectrum I occurs at the target ground of
the Osaka Gulf coast, from the results of aliquefaction simulation based on LIQCA, it turns outthat the ground becomes liquefied and the tunnel at
the surface of the target ground floats up slightly. It
is necessary to investigate the floating amount more
precisely, hereafter, because the floating has aserious impact on the restoration process of thetarget area.
However, a settlement of 0.9 m is thought to be
the maximum value of the floating amount. Thisphenomenon is caused by the boundary condition
between the tunnel and the surrounding ground. In

Fig. 11[1] Matsuoka S, Wakamatsu K, and Hashimoto K,“Estimation method of liquefaction risk based
on topography: Ground classification 250 m
mesh map”, in Proc. of the Japan Earthquake
Engineering Association, 2011, pp. 35–36.
[2] LIQCA Liquefaction Geo-Research Institute:
LIQCA 2 D 15 · LIQCA 3 D 15 material, 2015.
[3] Railway Technical Research Institute, DesignStandards for Railway Structures andCommentary, 2012.
[4] Yasuda S, and Yamaguchi I, “Dynamic soil
properties of undisturbed samples”, of the 20th
GeotechnicalEngineering
ResearchPresentation, 1985, pp. 539–542.

Deformation around the tunnel

332

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ROBUST POSITIONING OF DRONES FOR LAND USE MONITORINGIN STRONG TERRAIN RELIEF USING VISION-BASED NAVIGATION

1

Oleg Kupervasser1,2, Vitalii Sarychev 2, Alexander Rubinstein2 and Roman Yavich 1
Department of Mathematics, Ariel University, Israel; 2 TRANSIST VIDEO LLC, Skolkovo, Russia
ABSTRACTFor land use monitoring, the main problems are robust positioning in urban canyons and strong terrain reliefs
with the use of GPS system only. Indeed, satellite signal reflection and shielding in urban canyons and strong
terrain relief results in problems with correct positioning. Using GNSS-RTK does not solve the problem
completely, because in some complex situations the whole satellites system works incorrectly. We transform theweakness (urban canyons and strong terrain relief) to an advantage. It is a vision-based navigation using a mapof the terrain relief.. We investigate and demonstrate the effectiveness of this technology in Chinese region
Xiaoshan.
Keywords: Vision-based navigation, Robust positioning, Land use monitoring, Urban canyons and strong
terrain relief, DTM
the past decades. Two common approaches for thenavigation problem are: the landmarks [11,12]. And
the ego-motion integration [13-17].
In [18], the drift is being corrected with the helpof a Digital Terrain Map (DTM). The DTM is adiscrete representation of the observed ground's
topography. It contains the altitude over the sea levelof the terrain for every geographical location. A
patch from the ground was reconstructed using`structure-from-motion' (SFM) algorithm and wasmatched to the DTM in order to derive the camera'spose. The algorithm presented in this work [4-9]does not require an intermediate explicit
reconstruction of the 3D world. By combining theDTM information directly with the images
information it is claimed that the algorithm is wellconditioned and generates accurate estimates forreasonable scenarios and error sources.
Comparison of the corrected position of theobject, measured from the data of Google Earth inChina, with the calculated position of the object
would estimate the real effectiveness of navigation
corrections. The correspondent investigation for thedescribed method was carried out during the flight in
Galilee in Israel [19]. The position error was about
25 meter and angle error was about 1.5 degree.
Based on the core theory [4-10], TRANSISTVIDEO LLC (Russian Skolkovo company under theleadership of Kupervasser) developed the computer
program “Vision-based navigation of UAV overrelief” [20]. This program was tested in Zhejiang
Province in east China near the capital Hangzhou
using Google Earth data. This work was funded byHangzhou AVISI Electronics Co. LTD. Currently
TRANSIST VIDEO LLC won the grant from thegoverning body of Hangzhou for creation of thereal-time version of the program. This program will

INTRODUCTION
Recently International Journal of Geomate has
published a very important paper about the
integration of Geography Information System (GIS)and Global Navigation Satellite System – Real Time
Kinematics (GNSS-RTK) for land use monitoring[1].
Indeed, the authors of [1] write: “limited open spacearea requires accurate monitoring to maintainchanges in land use that is not suitable with cityspatial planning. The difference between spatialplanning and existing land Use should be
minimized”. The main problems are robust
positioning in urban canyons and strong terrain
reliefs with the use of GPS system only. Indeed,satellite signal reflection and shielding in urban
canyons and strong terrain reliefs results in problems
with correct positioning. “In urban area study, signal
problems become obstacles for determining theposition and navigation due to some problems suchas shadowing and multipath effects” [1,2].
The paper suggests using GNSS-RTK (fullsystem which is a constellation of current satellites
such as GPS (Global Positioning System-USA),GLONASS (Russia), Galileo (Europe), BeiDou(China), and QZSS (Japan)) that can improve
positioning [1,3]. However, it does not solve theproblem completely, because in some complex
situations the whole satellites system works
incorrectly.
We need to transform the weakness (urban
canyons and strong terrain reliefs) to an advantage.
It is a vision-based navigation using a map of theterrain relief. This topic had been recently widely
developed by the authors [4-10].
Vision-basedalgorithms have been a major research issue during333

GEOMATE - Mie, Japan, Nov. 21-24, 2017

be developed in collaboration with Ariel University
in Israel.

 u ix  t k   yu i  t k 

METHODOLOGY     x  x i , y  y i  I x  x , y,t k  I t  x , y,t k    x , y WM  x i , yi  





x
x
,
y
y
I
x
,
y,t
I
x
,
y,t






i
i
y
k
t
k 
 
x
,
y
W





1

Finding of the corresponding characteristic
points on the first and second shots (optical-flow
field)(2)

We use affine or translation monitoring of thefirst shot points on the second shot using pyramid
realization (affine or translation) of Lucas andKanade tracker. [22].

Two methods are used to choose thecharacteristic points on the first shot:
1) the characteristic points on the first shot arechosen on the regular grid on the boundaries of the
shot. The grid is square of the size of N x N, where
N2 is the general number of the characteristic points.
2) the characteristic points on the first shot arechosen with the help of Shi Tomassi corner detector.
The Shi Tomassi corner detector [21] (Shi-Tomasi
or Kanade-Tomasi, 1993) works as follows: for the
given picture let us consider the window (usually thesize of the window is 5x5 pixel, but it can depend on
the size of the picture) in the centre (x0,y0).Let’s
determine M – autocorrelation matrix:

The Navigation Algorithm of DTM usage andoptical flow finding
The problem can be briefly described as follows:
At any given time instance t , a coordinate system
C (t ) is fixed to a camera in such a way that the Z-axis coincides with the optical-axis and the origin
coincides with the camera's projection center. At thattime instance t1 the camera is located at somegeographical location p1  p( t 1 ) and has a givenM x , y  0orientation R1  R ( t 1 ) with respect to a global0

I  x, y I  x, y Ix2  x, y  x x0, y  y0  I  x, y I  x, y x I2  x,y y  x, yWyyx

coordinate system W ( p(t ) is a 3D vector, R(t ) isan orthonormal rotation matrix). Consider now two
sequential time instances t1 and t2 : thetransformation from C ( t1 ) to C (t2 ) is given by(1)
where w(x,y) is a weight function (usually theGaussian function or a binary window is used)(Fig.1).

p12  p( t 1 , t 2 ) and theR12  R ( t 1 , t 2 ) . Let

the translation vector
rotation

matrixq 1i  q ( t 1 )Ci

andhomogeneousu i ( t 1 ), u i ( t 2 ) 

Fig 1.

A corner is characterized by large absolutevalues of the matrix eigenvalues M: M: λ1>>0 ,λ2>>0. Shi and Tomassi suggested the measure ofcorner: F(x,y)=min (λ1, λ2).The function finds theangles with large eigenvalues.
We use the same equation to analyze the Lucasand Kanade optical flow[22], this local method of
optical flow measurement widely used in thecomputer vision.
The optical-flow field is supplied: ui ( tk )
and ui (t2 )  

2

be

the

representations
2of. As standard, one can think ofthese vectors as the vectors from the optical-centerof the camera to the projection point on the image
plane. Using an initial-guess of the pose of thecamera at t1 , the line passing through p E ( t1 ) andWeight function(i=1...n, k=1,2). For the i 'th feature, ui (t1 )  

q 2 i C i q( t 2 )Ciq( t 1 ) can be intersected with the DTM. Any ray-tracing style algorithm can be used for this purpose.
The location of this intersection is denoted as

W

Q Ei

. The subscript letter “ E ” highlights the fact that
this ground-point is the estimated location for thefeature point, that in general will be different fromthe true ground-feature location2

represent its locations at the firstand second frame respectively:334

W

Q i (Fig. 2).

GEOMATE - Mie, Japan, Nov. 21-24, 2017

method after several iterations stopps to converge.
The applicability, accuracy and robustness of thealgorithm were verified though simulations and labexperiments.
THE
FLIGHTPROGRAMME

Denoted by N i the normal of the plane tangent toW

Q Ei , one can write:f i ( p1 , 1 , 1 ,  1 , p12 , 12 , 12 ,  12 )



=



 q 2 i q 2 i T  p12  R12  i Q Ei  p1
I  q Tq  p  R  Q  p = 0

2i
2i 
12
12
i 
Ei
1
(3)
where  i in the above expression represents:
i =

OF

THE

It was decided to carry out the flight testing of
the vision-based navigation programme on theterrain relief with the help of Google Earth video
data (based on the real data).
We chose the following conditions of the flight,
parameters of the trajectory, the video shooting andthe inertial navigation:
1) The trajectory parameters: The flight is over
Xiaoshan district between 30.0421571732 30.0545167923
degrees
latitudeand120.1245546341120.1479005814
degreeslongitude. The picture of the district of the flight andthe digital map of the flight district are presented on
Fig 3. The flight was at a speed of 50 m/sec during
19,6 sec in a straight line at an altitude of 1000 m
above mean sea level from the pint (30.05048444,
120.1321713) to the point (30.04588944,
120.1408507). This way is depicted by the red linefrom the point 1 to the point 50.

Fig. 2 Ground-feature location

the DTM at the point

TESTING

q1i N i T
N i T R1q1i(4)
This constraint involves the position, orientation andthe ego-motion defining the two frames of thecamera. For each of the n optical-flow vectors, thefunction f i : 12  3 is defined as the left-handside of the constraint described in (7). In the above
expression, R12 and R1 are functions of Euler

Fig. 3 The district of the flight and the digital map of
the flight district.

angles (12 , 12 , 12 ) and (1 , 1 , 1 ) respectively.
Additionally, the function F :  12   3n will be2) The parameters of the video shooting are as
follows:
The 50 images were shot with the 0,4 sec interval
between them. The field of view angle of the camera
along the short side of the shot are 38,68 degrees;along the long side of the shot - 59,97 degrees. The
pixel size of the picture is 4800х2923. The shots are
made with the help of the Google Earth. The longside of the shot is perpendicular to the direction of
the movement and the airframe, the short side isparallel to the movement, the aircraft flies to theupper side of the picture.
3) The parameters of the inertial navigation
system with a random noise are following: the noise
results in the average velocity change for the∆V=±20 m/sec during 1 sec along every axis andaverage Euler angle change for ∆φ= ±0.33 degrees
during 1 sec. Modeling of the inertial system outputs
was carried out with the help of the standard

defined as the concatenation of the f i functions:T.
F ( p1 , 1 , 1 , 1 , p12 , 12 ,12 , 12 ) =  f1 ,, f n 
According to these notations, the goal of thealgorithm is to find the twelve parameters thatminimizeM ( , D ) = F ( , D )2, where

represents the 12-vector of the parameters to be
estimated, and D is the concatenation of all thedata obtain from the optical-flow and the DTM. If
D were error-free, the true parameters would havebeen obtained. Since D contains some error
perturbation, the estimated parameters are drifted toerroneous values. An iterative scheme will be usedin order to solve this system. A robust algorithm
which uses Gauss-Newton iterations and Mestimator is described in [20].We begin to use
Levenberg-Marquardt method if Gauss-Newton
335

GEOMATE - Mie, Japan, Nov. 21-24, 2017

programmes of Matlab INS Toolbox, produced by
GPSoft [23].
For the vision-based navigation measuring theindex shots were chosen with time interval about 3.6
sec and an approximate distance from the previous
shot of the pair 175m. The characteristic points(about 300) were presented as a regular grid on theshot, the displacement of these points was measured
with the help of Lucas and Kanade method with theuse of the series of shots between the pair of theindex shots for the vision-based navigation (Fig. 4).
The arrows show the found displacement of thecharacteristic points between the pair of shots, used
for the vision-based navigation.

Fig. 6 The navigation errors. The red graphic isbased on the inertial navigation; the blue graphic isbased on the vision-based navigation with the use of
the inertial navigation, the blue graphic is based on
the vision-based navigation
The upper graphics – coordinates x,y,z. the lower
graphics – Euler angles, roll, pitch, yaw

Fig. 4 The pair of shots, used for the vision-basednavigation
GRAPHIC RESULTS OF THE VISION-BASEDNAVIGATION PROGRAMME TESTINGOn Fig. 5 we present three trajectories: the precise
trajectory; the trajectory based on the inertial
navigation; the trajectory based on the vision-basednavigation.

Fig. 7 The same graphic as on Fig 6, but in smaller
scale
CONCLUSION
We can make the following conclusions:1) The methods of vision-based navigation wereused for shots, obtained from an independent source– the programme Google Earth (they are obtained
from the flight testing). That means that these resultsof the vision-based navigation are valid because they
are obtained not on the basis of synthetical shots ofcomputer simulation but from an independent sourceon basis of flight testing.
2) The accuracy of the vision-based navigation
system corresponds to the expected for these
conditions:а) Maximum position error based on visionbased navigation is 20 mб) Maximum angle Euler error based on visionbased navigation is 0.83 degree.
3) Also the measurement without INS usage wascarried out:
For all the pairs of shots (used for vision-basednavigation) every other shot of the previous pair isthe first for the next pair except the first and the lastshot.

Fig. 5 Three flight trajectories: the precise trajectoryis presented in red, the trajectory based on theinertial navigation is presented in green; thetrajectory based on the vision-based navigation ispresented in blue
The navigation errors are drawn on Fig. 6,7.

336

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Between the two measurements with the help ofvision-based navigation method we consider thecamera movement as a straightforward one (without
rotation) at a speed found either from positions of
the cameras (with the help of the vision-basednavigation) for two pairs of shots or from the initialconditions. For this case we got the following
results:а) Maximum position error based on visionbased navigation is 30 m
б) Maximum Euler angle error based on visionbased navigation is 2.2 degrees
The results are worse than with the use of INS.

IEEE/ION Position, Location and Navigation
Symposium, P.1203-1212[6] Oleg Kupervasser, Vladimir Voronov , “Anavigation
filterforfusing
DTM/correspondence
updates”,
Proceedings of the IEEE International
Conference on Robotics and Biomimetics(ROBIO), 2011 , Page(s): 1591 - 1596
[7] R. Lerner, O. Kupervasser, .E. Rivlin,”Pose andMotion from Omnidirectional Optical Flow anda Digital Terrain Map”, In the Proceedings ofthe 2006 IEEE/RSJ International Conference onIntelligent Robots and Systems, P.2251-2256[8] Kupervasser O. Yu., Voronov V.V., “Correctionof Inertial Navigation System's Errors by the
Help of Vision-Based Navigator Based on
Digital Terrarium Map”, presented at XIX St.Petersburg international conference on the
integrated navigation systems (MKINS2012)[9] Kupervasser O. Yu., Rubinshtein A.A. “Thesystem of vision-based navigation for
unmanned aerial vehicles”, IV TRIZ
Conference, «TRIZ. Practice for applicaton of
methodical instruments», Moscow 19-20
October 2012

ACKNOWLEDGEMENTS
We would like to thank Alexander Domoshnitsky,
Ronen Lerner, Ehud Rivlin and Hector Rotstein forvery useful consultations.
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Samet, ``SoftPOSIT: Simultaneous pose andcorrespondence determination'', ECCV 2002,
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[13] D. Shin, S. G. Park, B. S. Song, E. S. Kim, O.
Kupervasser, D. Pivovartchuk, I. Gartseev, O.
Antipov, E. Kruchenkov, A. Milovanov, A.
Kochetov, I. Sazonov, I. Nogtev, S. W. Hyun,“Precision improvement of MEMS gyros forindoor mobile robots with horizontal motion
inspired by methods of TRIZ”, Proceedings of
9th IEEE International Conference on
Nano/Micro Engineered and Molecular Systems(IEEE-NEMS
2014)
April
13-16,
2014,Hawaii,USA, pp 102-107[14] J. L. Barron, R. Eagleson, ``Recursive
estimation of time-varying motion and structure337

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Parameters'', Pattern Recognition vol. 29, no. 5,
pp. 797--818, 1996[15] T.Y. Tian, C. Tomashi, D.J. Hegger,``Comparison of approaches to egomotion
computation'', Department of Psychology andComputer science, Stanford university, CA
94305, 1996[16] A.Chiuso, S.Soatto, ``MFm: 3-D Motion From
2-D Motion, Causally integrated over time'',Washington University Technical Report, 1999[17] M. Irani, B. Rousso, S. Peleg, ``Robust
Recovery of Ego-Motion'', Proc. Of CAIP 93,
pp. 371-378, 1993[18] D.G. Sim, R.H. Park, R.C. Kim, S.U. Lee, I.C.
Kim, ``Integrated position estimation using
aerial image sequences'', IEEE transactions on
pattern analysis and machine intelligence, vol.
24, no.1, 2002[19] R. Lerner, E. Rivlin, “Direct Method for VisionBased Navigation Using a Digital Terrain
Map”, IEEE transactions on pattern analysis
and machine intelligence, vol. 33, no. 2, 2011[20] Computer programs "Vision-navigation of UAV
over relief" Part 1, Part 2. The certificates on thestate registration of the computer programs №
2016613306, 2016613305. It is registered in theregister of the computer programs of Federal
service on intellectual property, patents andtrade marks, Russia, on March, 24, 2016(http://leah.haifa.ac.il/~skogan/Apache/mydata1/Oleg_home/2016613306.pdf).
[21] Shi-Tomasi Corner Detector:
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http://robots.stanford.edu/cs223b04/algo_affine_tracking.pdf[23] Matlab INS Toolbox, produced by GPSoft:
http://www.navtechgps.com/ins_toolbox_v3_0_
for_matlab/

338

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEGRADATION OF CEMENT TREATED SOIL DUE TO SULFATEATTACK
Cynthia Debby Heriyani, Sumiyati Gunawan, John Tri Hatmoko, and Luky Handoko
Faculty of Engineering, Universitas Atma Jaya Yogyakarta, Indonesia
ABSTRACT
Ground treatment method by utilizing binding agents has been becoming very popular. Some of the groundtreatment were applied at seabed under seawater level. The hardened soil mixture is subjected to sulfate attack
contained by sea water. This paper discusses about physical and mechanical degradation of cement treated clay
due to sulfate exposure. Grain size distribution, Atterberg limit and Penetration Test were conducted to cement
treated clay specimen by varying the initial clay water content, cement content prior to sulfate exposure. In thispaper, natrium sulfate (Na2SO4) was used as degrading agent to cement treated soil. Based on grain size
distribution, the size of particle especially in clay size range is increasing due to the addition of cement and curing
time. Furthermore, the plasticity index of cement treated clay decreases when the cement content increases.
However, the grain size and Atterberg limit of cement treated clay tends to turn back to original clay properties
after exposed with sulfate. The depth of degradation caused by sulfate exposure can be observed from Penetration
Test. It increases with the decrease of cement content after immersed to natrium sulfate. Those results indicate that
degradation occurs due to loss of binding ability of cement treated clay.
Keywords: Cement Treated Clay, Degradation, Natrium Sulfate, Penetration Test
focused on finding the influencing factors that canretard the reaction process [11, 12], such as organic
content, clay, and sulfate. However, not muchresearches discuss about the strength degradation of
cement treated clay under external corrosive
environment attack, such as seawater, sulfate and acid.
This paper discusses about the change of physical andstrength properties of cement treated clay undersulfate immersion. The physical properties include
Atterberg limit and grain size distribution. The
strength properties were observed by conducting
penetration test to investigate the depth ofdegradation occurred due to sulfate. Natrium sulfate
was selected to represent the corrosive environment.

INTRODUCTION
High water content soil has been utilized as
construction materials, recently. Dredged materials
from Port of New York and New Jersey was studied
to be used for geotechnical application [1]. In
Singapore, slurry pond has been used as part ofChangi East reclamation project [2]. Dredged soil
mixed with cement has been used as filling material
for airport construction in Japan [3]. High watercontent material is available numerously and mostly
produced from contaminated sediments at riverbed
and seabed [4] and port navigation channel dredging
works [1]. In Indonesia, huge volume of high watercontent volcanic mud existed in East part of Java
Island [5]. The volcanic mud has been produced since2006 and continue until now.
High water content soil is commonly known tohave poor characteristics and not suitable forconstruction materials. It has low strength, highcompressibility and low permeability. To be used forconstruction materials, improvement is required.
There are many studies to improve the poor
characteristic of high-water content soils. One of theavailable and famous method is chemical
stabilization by mixing high water content soil withbinding agent such as lime and cement [6-10]. Thismethod relies on chemical reaction process of
employed binding agent, water and soil. There are
two reaction that might occur: hydration reaction andpozzolanic reaction. The product of both reaction isstrong amorphous materials. Many researches have

LABORATORY TEST PROGRAM
Materials
This research utilizes a clayey silt soil as parent
material. The soil is derived from Vulcanic mud
eruption in Sidoarjo district, East of Java Province,
Indonesia. Physically, the soil contains high content
of water and 96.62% of the dry weight percentage isfine-grained soil (diameter less than 0.075 mm). The
liquid limit (wL) and plastic limit (wP) are 60% and34.08%, respectively. Ordinary Portland Cement wasused as chemical binder. The specific gravity (Gs) of
soil and cement are 2.785 and 3.00, respectively.
Natrium sulfate (Na2SO4) is used to represent thecorrosive environment which is expected to decrease
the strength of cement treated clay.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Load sensor
Penetration needle
SampleDisplacement
sensorCompression
test machine

Fig. 1 Scetch of penetration test apparatus

Fig. 3 Evolution of grain size distribution
Specimen Preparation and Penetration Test
Specimen were made by mixing soil, cement andwater. Before mixed, soil and cement were placed in
the 105C oven for 24 hours. A certain dry weight ofsoil, cement and water were mixed thoroughly using
automatic hand mixer for 10 minutes to insure thehomogeneity of the mixture. The mixture then placed
into a cylinder mold with diameter 6 cm and height
10 cm. The specimens were sealed to keep the water
inside the specimen by closing the top of the cylinderusing lid tightly. During the curing time, thespecimens were keep under constant temperature of30C. Samples were prepared with a certain watercontent (wc=100%,) and varied cement content

Fig. 2 Evolution of Atterberg limit due to addition of
cement340

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 4 Penetration test result of specimen without
immersed to Na2SO4 (cc=15% and wc=100%)

Fig. 5 Penetration test result of specimen without
immersed to Na2SO4 (cc=15% and wc=100%)(cc=10% - 30%). Fig. 1 shows the arrangement ofpenetration test equipment. This test uses apenetration needle which form a 60 conus at the end.
During the test, the needle will penetrate the specimen
and the tip resistance was measured for each depth.
The penetration rate of the needle is set to be 3
mm/minutes. To investigate the degradation occurred
due to corrosive environment, specimens were
submerged into Na2SO4 solution for 28 days. The
concentration of Na2SO4 solution used in thisresearch is 10 gr/L. For each specimen, 0.7 L Na2SO4
solution was prepared.

between soil and cement has particle size larger thanthe original soils. The different of particle size
between cement addition 1%, 2% and 3% is not too
significant. However, when it is compared with theoriginal soil, the different is significant. Whensubmerged into Na2SO4, the particle size isdecreasing at particle size between 0.005 mm – 0.02mm, while the other range does not change
significantly.
Penetration Test
Penetration test result shows the tip resistance at a
certain depth measured by load sensor attached at thepenetration needle. Figure 4 shows the result ofpenetration test of specimen without immersed in
Na2SO4. Based on the result, the tip resistance at nearsurface is very low due to the small contact of theneedle. The tip resistance gradually increase until acertain constant value which is referred to Rref. Figure
5 shows the result of penetration test of specimen
after immersed into Na2SO4 with the same watercontent and same cement content as the specimen at
Fig. 4. Comparing the result of specimen with andwithout immersed into Na2SO4, it is clearly observedthat the depth of the zone with low tip resistance isdeeper. This results shows that Na2SO4 decrease thestrength of the cement treated soil. Figure 6 shows thecomparison of penetration test for specimen with andwithout immersed into Na2SO4. The plot data wasfitted with the Eq. (1).

RESULTS AND DISCUSSIONS
Atterberg Limit
Change of physical characteristics of cement
treated clay due to additional cement and sulfate wasobserved by conducting Atterberg limit test and grain
size distribution test. The tests were conducted on
three different soil condition: 1) original soil, 2)
original soil added by cement and 3) 28-days age of
cement treated clay mixed with Na2SO4.
Figure 2 shows Atterberg limit test results. The
results show that Liquid limit is increasing along with
the increase of cement content, while the Plasticity
Index tends to decrease. When submerged to Na2SO4,
the Plasticity Index tends to increase.
Grain Size Distribution
Figure 3 shows the change of particle size
distribution due to cement addition with and without
Na2SO4. Based on the test results, the mixture

R  Rreff 

341

Rreff

1    d  

 

(1)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 6 Comparison of penetration test results for specimen with and without immersed into Na2SO4: a)cc=15%;b)cc=20% ; c)cc=25% and d)cc=30%
Where: R=tip resistance at certain depth,
Rreff=reference tip resistance where the contact area
ofpenetration needle has been fully work, d=depth ofpenetration and , , =fitting constant.
Based on the results shown in Fig. 6, it is clearlyobserved that the zone which has low tip resistance isgetting deeper when specimen is immersed into
Na2SO4. This results agree with obtained by otherresearchers [13, 14]. This zone is deeper as the
cement content decreases as shown in Fig. 7. Figure
8 shows the Rreff value for each specimen. The

results indicated that the tip resistance at undegradedzone for the specimen immersed with Na2SO4 ishigher than the one not immersed into Na2SO4. This
results indicate that while the cement treated soil
specimen losing the strength at the surface due to
Na2SO4, the strength of the lower layer keepincreasing due to continuous reaction of cement, soil
and water. The reaction occurred in this zone is more
likely to be the Pozzolanic reaction which take longer
time than Hydration reaction.
342

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 7 Penetration test result of specimen without
immersed to Na2SO4 (cc=15% and wc=100%)

Fig. 8 Penetration test result of specimen without
immersed to Na2SO4 (cc=15% and wc=100%)

CONCLUSION
This paper shows the comparison of physicalproperties and penetration test of cement treated soil
with and without immersed into natrium sulfate
solution. The natrium sulfate solution was selected torepresent the corrosive environment.
Based on the test result, the plasticity of cement
treated soil tends to decrease as the increase of cement
content. After submerged into natrium sulfate, theplasticity index tends to increase. The grain size of
cement treated soil is larger than original soils. Thereis no significant differences of grain size distribution
for addition cement from 1-3%. After submerged into
natrium sulfate solution, the percentage of particle
size between 0.005 mm – 0.02 mm become smaller.
The penetration test results clearly show thedegradation caused by natrium sulfate solution. As
the cement content increases, the degradation depthof cement treated soil due to natrium sulfate decreases

[3]

[4]

[5]

[6]

ACKNOWLEDGEMENTS
The authors acknowledge the help from college at
Soil Mechanics Laboratory of Universitas Atma Jaya
Yogyakarta for their support to this research. The
authors also express their gratitude for the financial
support from Civil Engineering Department of
Universitas Atma Jaya Yogyakarta.

[7]

[8]

REFERENCES[1] Bennert, T.A., et al., Use of Dredged Sedimentsfrom Newark Harbor for GeotechnicalApplications, in Geotechnics of High Water
Content Materials, T.B. Edil and P.J. Fox,
Editors. 2000, American Society for Testing andMaterials: West Conshohocken.
[2] Chu, J., M.W. Bo, and A. Arulrajah,
Reclamation of a slurry pond in Singapore.

[9]

343

Proceedings of the Institution of Civil Engineers- Geotechnical Engineering, 2009. 162(1): p.
13-20.
Kitazume, M. and T. Satoh, Development of apneumatic flow mixing method and its
application to Central Japan International
Airport construction. Proceedings of theInstitution of Civil Engineers - Ground
Improvement, 2003. 7(3): p. 139-148.
Kamon, M., T. Katsumi, and K. Watanabe,
Heavy-Metal Leaching from Cement Stabilized
Waste Sludge, in Geotechnics of High Water
Content Materials, T.B. Edil and P.J. Fox,
Editors. 2000, American Society for Testing andMaterials: West Conshohocken.
Handoko, L., N. Yasufuku, and A. Rifa'i,
Comparison of consolidation curves forremolded mud volcano of Sidoarjo, Indonesia.
Journal of Geotechnique, Construction
Materials and Environment, 2016. 10(22): p.
1978-1982.
Federico, A., C. Vitone, and A. Murianni, On
the mechanical behaviour of dredged submarine
clayey sediments stabilized with lime or cement.
Canadian Geotechnical Journal, 2015. 52(12): p.
2030-2040.
Antonio, F., et al., Plasticity of lime/cementstabilised
dredgedclayeysediments.
Environmental Geotechnics, 2016. 3(1): p. 1727.
Tsuchida, T. and Y.X. Tang, Estimation ofcompressive strength of cement-treated marine
clays with different initial water contents. Soils
and Foundations, 2015. 55(2): p. 359-374.
Watabe, Y., et al., Mechanical characteristics ofa cement treated dredged soil utilized for waste
reclamation
landfill,inInternational
Symposium Yokohama, T. Tsuchida, et al.,Editors. 2003, Taylor Francis: Yokohama. p.
739-744.

GEOMATE - Mie, Japan, Nov. 21-24, 2017[13] Hara, H., et al., Deterioration Progress of
Cement-Treated Ariake Clay under Seawater.
Journal of the Society of Materials Science,
2014. 63(1): p. 49-54.
[14] Yang, J., et al., Laboratory test on long-term
deterioration of cement soil in seawater
environment.
TransactionsofTianjin
University, 2016. 22(2): p. 132-138.

[10] Tang, Y.X., Y. Miyazaki, and T. Tsuchida,
Practices of reused dredgings by cement
treatment. Soils and Foundations, 2001. 41(5):p. 129-143.
[11] Sherwood, P.T., The Stabilization with Cementof Weathered and Sulphate-Bearing Clays.
Géotechnique, 1957. 7(4): p. 179-191.
[12] Sherwood, P.T., Effect of sulfates on cement andlime stabilized soils. Highway Research Board
Bulletin, 1962. 353: p. 98-107.

344

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

CHARACTERIZATION OF PHYSICAL, CHEMICAL, AND COMPACTION PROPERTIES FOR
BURIED MUNICIPAL SOLID WASTE AT THREE DUMPING SITES IN SRI LANKA

1

A.B.K.T. Piumali1, T. Saito1, N.H Priyankara2, A.M.N Alagiyawanna2, and K. Kawamoto1
Graduate School of Science and Engineering, Saitama University, Japan; 2Department of Civil andEnvironmental Engineering, Faculty of Engineering, University of Ruhuna, Sri Lanka
ABSTRACTOpen dumping of Municipal Solid Waste (MSW) is a common method for waste disposal in most of developing
countries. Due to rapid population growth and lack of lands, abandoned waste dumping sites are highly demanded
for the redevelopment and construction especially at big cities and their surrounding in developing countries. In
order to examine the stability analysis and the construction plan of abandoned waste dumping sites, more studies
for characterizing geo-mechanical properties of buried MSW are needed. In this study, a comprehensive laboratory
testing program including fundamental physical and chemical properties, and the standard proctor test were
performed on buried MSW collected from three waste dumping sites, representing three different climate zones in
Sri Lanka. The results indicated that Loss on Ignition (LOI) decreased with the dumped age of tested samples. For
all tested samples, measured specific gravities ranged between 2.3 to 2.6 and correlated inversely to LOI values.
Electrical conductivities decreased with the age of MSW and pH values ranged between 7 to 8. Based on the resultsfrom particle size distribution curves, Uniformity Coefficient decreased and Coefficient of Curvature increased
with the age of MSW and the fraction with less than 2mm increased with the age of MSW. Measured maximum
dry densities highly correlated to LOI values, suggesting that the LOI is a good indicator to evaluate the particle
density and compaction property for buried waste samples.
Keywords: Municipal Solid Waste, open dumping, laboratory testing, Geo-mechanical properties, Loss on Ignition(LOI)
encompass waste fill areas and build more frequently
in disposal areas and over wasteland. They sometimes
operate with a design life of several generations [5].
The post closure use of dump sites was not only
limited to the recreational uses, but also other hardend uses [6]. In Sri Lanka where available lands arevery much limited for development projects, theabandoned lands are leaned towards use forconstructions (i.e. Bloemandhal garbage mountain,
Colombo).
In order to take precautions for the safety ofstructures in designing foundations on such lands andto examine the stability of waste areas, the knowhow
of geotechnical properties of MSW is essential.
Though some studies have been done on thisemerging engineering aspect, more studies forcharacterizing geo-mechanical properties of buried
MSW are needed. One first feasible approach to thisstudy, is to characterize basic physical, chemical andcompaction properties to correlate with the geomechanical properties of MSW.
Unlike soil, investigation of geo physical,
chemical and mechanical properties of MSW is
intricate due to high variability of MSW in its
composition which is dependent on a variety offactors such as climate, disposal technology, and thedemography of the local community. It is therefore
essential that the design and stability evaluations oflandfills/dump sites in each region be performed

INTRODUCTION
Open dumping of Municipal Solid Waste (MSW)
is a common method for waste disposal in most ofdeveloping countries and many large dump sites arelocated in urban and suburban areas. Due to rapid
urbanization and increase in population, thegeneration of MSW is increasing. Available land in
urban and suburban areas are becoming scarcer withtime. Therefore, the local authorities are forced tostrain the existing open dumps to a level which thelandfills are reaching to critical heights, causing slope
failures or shear failures. Then the operation of dumpsite is happened to be stopped, it must essentiallymove to another location near urban or suburban area.
The landfills of Cincinnati, Ohio in USA [1], Payatas
in Philippines [2] are examples of catastrophic
failures of MSW dumps in the world. Sri Lanka iscorrespondingly facing this problem attributed to theimproper MSW management [3], most of collected
MSW is dumped at the disposal sites without any
engineering considerations such as ground settlement
and slope stability. The famous Meethotamullatragedy occurred on 14th April 2017 in Sri Lanka, is
one of the most appropriate examples, which tookapproximately 30 lives and a huge property damage[4]
Due to the limited available resources of lands incity areas, expanding communities now frequently
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

garbage by seven Local Authorities in Colombo Area.
The extent of the waste disposal site is 37 acres
marking it as the largest dump site in Sri Lanka. This
dump site is climatically located in Intermediate zone
and it represents the most urbanized locality in Sri
Lanka. It has been used as a dump site for more than
30 years. However, it is officially started operation
under Waste Management Authority, Sri Lanka in
1996 [9]. The dumpsite consisted of old and new
sections. The old section has buried waste more than
25 years old. The samples were collected at the oldest
location of the dump site and upon the excavation, up
to 8m depth, the buried waste of more than 20 years
old was found. Point sampling at each 1m intervalfrom 0-8m were done.

based on the local conditions [7]. However, effects ofclimate condition and waste age on geotechnicalproperties of MSW are not well understood [8].
Therefore, this study was formed with the objectiveof evaluating the climate and aging effect on the geotechnical properties of buried MSW by conducting acomprehensive laboratory testing program. It
includes fundamental physical and chemical
properties, and the standard proctor compaction test.
The tested buried MSW samples were collected fromthree waste dumping sites, representing threedifferent climate zones in Sri Lanka. Each dump site
has three different urbanization statuses. Climate
condition controls biological decomposition of buried
waste. Level of urbanization controls the fresh MSW
composition, and aging cause to change thecomposition of buried waste. Therefore, it is essential
to characterize new MSW and old MSW to identify
the aging effect on the geotechnical properties.
However, the benefits of such study are notexclusive to post closure land use and slope stability
issues on non-engineered landfills. Prominently they
could be utilized for designing, constructing andoperating engineered landfill facilities. Additionally,as MSW is a burden to a society, these findings could
be used to make recommendations to use MSW as ageo-material/fill material for roads or land
reclamations projects, etc. Therefore, this is asustainable engineering approach on utilizing MSW
as a geo-material and the knowledge made by thestudy would support for preventing slope failure
disasters.

ActiveDump A

ActiveDump B
Sampling Location, Fill
Age > 20 Years

Fig. 1METHODOLOGY
Site Selection and Sampling

50m

Site map of Karadiyana dump site
(Source:2017 Google Map on 16/5/17 andmodified)

Site and sampling information at Udapalatha
abandoned open dumping site in Central Province andHambanthota operating dumping sites in Southern
Province are shown in [8].

Table 1 summarizes the details of selected open
dump sites in Sri Lanka. Fig. 1 shows the satellite
map of Karadiyana dump site which is located in
Colombo district. The existing dumpsite is handling
Table 1 Information of sampling locations
Sampling
Site
Karadiyana
Udapalatha
Hambanthota

Local Authority
Western Province
Waste Management
Authority
Udapalatha
Pradeshiya Saba
Hambanthota
Municipal Council

Population[10]

Site Location

Annual Rainfall
and Temperature[11]

Daily Quantity
Receiving(T/D)

1,185,458

06°48'54.2"N
79°54'08.2"E>2000mm25-27.5 0C

632[9]

07°80'30.1" N
80°34'43.2" E
06010'36.0" N
81007'40.5" E>2500mm
17.5-25.0 0C<1250 mm25-32.5 0C

97,567
22,691346

1.78[12]9.9[12]

GEOMATE - Mie, Japan, Nov. 21-24, 2017

slowly with time unless they were subjected tomechanical crushing during dumpsite operation.
When the fill age is more than 20 years, in Karadiyana
dump site, the composition was basically identified as
a combination of a soil like material and other wastematerials as defined in [14]. The composition of otherwaste materials could only be distinguished and soil
like materials were hardly identifiable. The results ofcomposition analysis of Karadiyana dump site
showed that the contribution from the other wastematerials was increased as their fill age wasincreased.
The paste portion was rich with organic content
The LOI values which give the organic content is highin all three sites compared with those of intact soil
samples. The LOI values for wet zone andintermediate zone were higher than those for dry zone.
It was clearly identified that the Loss on Ignition was
decreasing with age in each site introducing the Losson Ignition as an indicator parameter of the age of
MSW. Due to particle crushing and packing, naturally
there should be higher specific gravity values for oldburied waste than that of new buried waste. As LOI
verifies the exact age of the waste sample, specificgravity showed a higher inverse correlation with Losson Ignition as shown in Fig. 2.

Testing Methods
The point samples and core samples taken from
boreholes were used to determine basic physicalproperties including moisture content, Atterberg
limits, specific gravity (Gs), and particle size
distribution. Importantly the basic chemical
properties including Loss on Ignition (LOI), pH andelectric conductivity (EC) were performed. Those
tests were carried out conforming to JapaneseIndustrial Standards (JIS) (JIS A 1202, JIS A 1203,
JIS A 1204, JIS A 1205) and Japanese GeotechnicalSociety (JGS) standards (JGS 0211-2009, JGS 02122009, JGS 0221-2009). The compositions for buried
MSW were characterized by the waste composition
analysis in which the waste components wereseparated visually based on the dry weight of eachgroup. Standard Proctor compaction test was carriedout according to (JIS A 1210). The material which has
the particle size distribution less than 9.5mm wasused in order to conform to the testing methods.
RESULTS AND DISCUSSION
Basic physical and chemical properties
Table 2 shows basic physical and chemical
properties of bored core samples taken from thedisposal sites of Udapalatha (wet zone), Hambanthota(dry zone) and point samples taken from the disposalsites of Karadiyana (intermediate zone). Field
moisture content values are highly scattereddepending on the daily weather conditions.
The results indicated that LOI decreased with thedumped age of tested samples and is becoming lesser
from wet zone, intermediate zone and dry zone
respectively at each new and old site. Inverse trend isshown for the change of Gs with age and the Gs
values for buried waste samples were ranged between
2.3 - 2.6, which were lower than that of soil samples.
The pH values for waste samples of old site in the wetzone were lower than other samples. The pH values
in dry zone is higher than that of intermediate zone.
Buried waste samples for all three sites werecharacterized as having higher EC value comparedwith soil. Especially, EC values are higher in wet
zone, intermediate zone and dry zone respectively

2.9

Specific Gravity (Gs)

2.8
2.7
2.6
2.5
2.4
2.3
2.2
2.1
2.0

MSW Composition
Many research studies have identified thecomposition of fresh MSW usually composed ofkitchen waste, garden waste, wood, paper andcardboard, plastics, textiles, ceramic, glass, rubber,rock, and soil [12], [13]. The composition analysis of
this study showed that after around 1 year fill age, all
the kitchen waste and around 80% of garden waste
portion is converted to residue by biodegradation.
Other materials could be inert and degrade very

0

20
40
Loss on Ignition (LOI) (%)

Karadiyana Old

Udapalatha New

Udapalatha Old

Hambanthota New

Hambanthota Old

Reddy et al. 2011

Fig. 2 Graph of Correlation of Specific Gravity with
Loss on Ignition.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 2 Basic Physical and Chemical Properties for Tested Samples
Location(Age)/
Depth(m)Description

Karadiyana (Old >20 Years)
0.00-2.00
2.00-4.00
Black, dumped waste
4.00-6.00
6.00-8.00

Field
Moisture
Content
wf %

wL
%

wP
%

45.5
59.0
47.8
65.9

68.2

6.7

pH

Ip

Specific
gravityGs<2.0 mmEC
mS/cm

Loss onIgnition
LOI %

54.3

13.9

2.26
2.26
2.35
2.66

7.1
7.3
7.3
7.5

1.46
1.63
1.41
1.55

19.5
18.7
13.6
11.2

-

-

-

2.28

7.5

1.43

14.3

35.8

-

-

-

2.23

7.1

1.98

16.7

27.2

-

-

-

2.40

7.3

1.18

12.1

14.8

-

-

-

2.60

7.7

0.57

5.5

57.1
78.7
13.6
10.1

17.8

-

-

2.32
2.06
2.57
2.82

6.0
6.1
6.7
6.9

0.84
1.15
0.71
0.20

22.4
14.2
9.4
2.7

29.9

25.7

-

-

2.49

7.4

0.64

10.0

11.8

40.5

-

-

2.68

7.3

0.69

4.4

7.0

64.4

25.0

39.4

2.55

8.0

0.29

3.6

19.1

29.5

-

-

2.63

7.9

0.37

10.1

7.3

30.6

15.5

15.1

2.64

7.6

0.46

2.9

4.4

66.5

24.8

41.7

2.54

7.3

0.33

3.9

Atterberg limits

Udapalatha (New <3 Years)
0.00-1.00
1.00-2.00
2.00-3.20
3.20-4.50

Black, dumped wastewith fine to medium
sandBlack, dumped wastewith organic clay, traceof coarse to fine sandBlack, dumped wastewith Coarse to finesandBlackish Brown, coarse
to medium sand withorganic clay anddumped waste

Udapalatha (Old 7-11 Years)
0.00-1.50
1.50-3.00
3.00-4.00
4.00-4.20

Black, dumped waste

Hambanthota (New <1 Year)0.00-1.00
1.00-2.00
2.00-3.00

Blackish dumped wastewith clay, trace of finesandBlackish dumped wastewith clay, trace of finesand
Reddish brown toyellowish brownlateratic clay, Trace offine sandHambanthota (Old7-8 Years)
0.00-1.00
1.00-1.50
1.50-2.50

Blackish dumped wastewith clay, trace of finesandBlackish dumped wastewith clay, trace of fine
sand

348

GEOMATE - Mie, Japan, Nov. 21-24, 2017

In wet and dry zones, the residue content below 4.75
mm were high for all waste samples, and that for the
new site in dry zone exceeding 60%. Based on the
results, it can be found that more variety of waste was
mixed in the wet zone samples. The results fromparticle size distribution curves demonstrates that theuniformity coefficient decreased and the coefficientof curvature increased with the age of MSW and thefraction with less than 2mm increased with the age of
MSW.

Particle Size Distribution
Fig.3 shows results of Particle Size Distribution(PSD) curves and Table 3 summarizes the derived
values of particle size distribution of buried waste
samples from the three dump sites. The coarser
fraction higher than 2.0 mm in waste samples wascomparatively higher than soil, though to a lesser
extent for waste sample from old site in Hambanthota
dump site. There was no significant difference in PSD
for waste samples except for that of waste sample
from old site in Hambanthota and Karadiyana.
Hambanthota old samples are mixed with sands
reasoning to end up with a finer curve than otherlocations. Though the sample collected from
Karadiyana dump site are more than 20 years old, theparticle size distribution is much coarser than othertwo sites. It is attributed to the urbanization level. As
Karadiyana dump site is located in highly urbanizedarea, the plastic, polythene usage is higher than othertwo sites. As those materials are non-degradable or
take more time to degrade or crushing, despite theage, it has higher coarser fraction. More than 60% of
residues of Karadiyana buried waste samples wereobserved as aggregated together making bigger unite
particles larger than 4.75 mm which are easily
crushable.

Compaction
Fig. 4 shows results of compaction tests. It can befound that maximum dry densities (ߩௗ௠௔௫ ) for dry
zone were about 1.5 times higher than those for wet
and intermediate zones. There is no any significant
difference between compaction curves for both new
and old waste samples from wet and intermediatezone. Fig. 5 illustrates the correlations between theߩௗ௠௔௫ values from standard proctor compaction tests
and LOI. The ߩௗ௠௔௫ values were well correlated with
LOI values. This implies that the LOI is a good
indicator to evaluate the particle density andcompaction property for buried waste samples.

80
Dry Density (g/cm3)

Percentage of Passing (%)

Udapalatha
New 0.5m
Udapalatha Old
0.5m
Hambanthota
New 1.0m
Hambanthota
Old 1mKaradiyana Old
8m

1.7

100

60
40
20
0
0.01

0.1
1
10
100
Particle Diameter (mm)Udapalatha New 0.5-2.5m
Udapalatha Old 0.5-2.5m
Hambanthota New 1.0m
Hambanthota Old 0.5-1.0m
Karadiyana Old 6-8m

1.5

1.3

1.1

0.9

0

20
40
Moisture Content (%)

60

Fig. 4 Compaction Curves.

Fig. 3 Graph of Particle Size Distribution.

Table 3 Properties of Particle Size Distribution for Buried Waste Sample
Sample Location
Karadiyana Old
Udapalatha New
Udapalatha Old
Hambanthota New
Hambanthota Old<0.075mm
Fraction %
0.4
2.3
2.3
0.4
0.6

<2mm
Fraction %
22.9
37.1
38.6
42.8
64.7
349

D50
mm
11.2
4.0
4.7
3.5
1.0

Uniformity
Coefficient
16.5
28.7
16.7
14.9
6.4

Coefficient ofCurvature
0.8
0.6
1.2
0.5
0.6

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Maximum Dry Density (ρdmax)(g/cm3)

1.8
1.7
1.6
1.5
1.4
1.3
1.2
1.1
1.0
0.9

5

15

25
LOI (%)
Udapalatha New 0.5 - 2.5 m
Udapalatha Old 0.5-2.5m
Hambanthota New 1mHambanthota Old 0.5-1.0m
Karadiyana Old 8m

landfill failure”, J. of Performance of constructed
Facilities, Vol. 19, No. 2, May. 2005, pp. 100107,[3] Sato N, Kawamoto K, Mangalika L, “Current
condition and issues of municipal solid waste
management in Sri Lanka”, in Proc. 7th AsianPacific Landfill Symposium (APLAS), 2012, pp
OMS 6-58-OMS 6-66.
[4] http://blogs.agu.org/landslideblog/2017/04/16/m
eethotamulla-1/ accessed on 26/05/2017[5] Landva AO, Clark JI, “Geotechnics of waste
fills”, Geotechnics of Waste Fills-Theory andPractice, 1990 pp.86–106, ASTM STP 1070,[6] Sharma HD, Krishna RR, “End Uses of Closed
Landfills”, Chapter 24, Geo-Environmental
Engineering, WILEY, 2004, pp. 898-912[7] Machado SL, Karimpour-Fard, M, ShariatmadariN, Carvalho MF, Nascimento JCF, “Evaluationof the geotechnical properties of MSW in two
Brazilian landfills.” J. of Waste Management30(12), 2010, pp. 2579–2591.
[8] Ohata H, Saito T, Tachibana S, Balasooriya
BLCB, Priyankara NH, Alagiyawanna AMN,
Kurukulasuriya LC, Kawamoto K “Geotechnical
Properties for Municipal Solid Waste at Open
Dumping Sites Located in Wet and Dry Zones,
Sri Lanka”, International Conference ofGeotechnical Engineering, 2015, pp 269-272[9] JAICA main report of the data collection surveyof solid waste management in Sri Lanka, 2016,
pp. 12-20[10] Census Department, Sri Lanka accessed on
3/05/2017http://www.statistics.gov.lk/PopHouS
at/CPH2011/index.php?fileName=ImpDates[11] Climate of Sri Lanka, Department ofMeteorology,
accessedon
02/05/2017
http://www.meteo.gov.lk/index.php?option=com_content&view=article&id=94&Itemid=310&
lang=en[12] Satreps project report of Waste Amount andComposition Surveys (WACS) implemented in
the Central and Southern Provinces of Sri Lanka.
2014, pp. 36-42, 74-79[13] Zekkos D, E Kavazanjian Jr, Bray JD, Matasovic,
N, Riemer F, “Physical characterization ofmunicipal solid waste for geotechnical purposes”
J.GeotechnicalandGeoenvironmental
Engineering, 2010, 136(9), pp. 1231-1241.
[14] Manassero, M., Van Impe, W. F., andBouazza, A.”Waste disposal and containment.”
In Proc. 2nd Int. Congress on Environmental
Geotechnics, Vol. 2, Balkema, Rotterdam, The
Netherlands, 1997, pp. 1425–1474.
[15] Reddy KR, Hettiarachchi, H, Gangathulasi, J,
Bogner, JE “Geotechnical properties ofmunicipal solid waste at different phases ofbiodegradation.” J. of Waste Management, Vol.
31, No. 11, (2011). pp. 2275-2286.

35

Fig. 5 Graph of correlation of maximum dry densitywith Loss on Ignition.
CONCLUSION
Using buried waste samples of three different ages
from wet, intermediate and dry zone in Sri Lanka,
basic physical and chemical properties, andcompaction properties were determined in thelaboratory. Results showed that buried waste samples
were characterized as having high EC and LOI values
and Gs values for waste samples in all zones were 2.32.6. The Gs values were highly correlated to LOI
values, implying the LOI as an indicator parameter tocharacterize the age and the particle densities of thewaste samples. Based on the results from PSD curves,
Uniformity Coefficient decreased and Coefficient ofCurvature increased with the age of MSW and thefraction with less than 2mm increased with the age of
MSW. The ࣋ࢊ࢓ࢇ࢞ values for dry zone became higher
than those for wet and intermediate zone, and it iswell correlated with LOI. With increasing in LOI, the࣋ࢊ࢓ࢇ࢞ values decreased, implying that compaction
properties for buried waste samples could be wellcharacterized by LOI of samples.
ACKNOWLEDGEMENTS
This study was supported by the SATREPS
Project of the Japan Science and Technology agency(JST) and Japanese International cooperation Agency(JICA).
REFERENCES[1] Stark TD, Eid HT, Evans WD, Sherry PE,“Municipal solid waste slope failure. II: stability
analyses”,
J.
of
GeotechnicalandGeoenvironmental Engineering, ASCE 126 (5),May. 2000, pp. 408–419.
[2] Merry SM, E Kavazanjian Jr, Fritz WU,“Reconnaissance of the July 10, 2000, Payatas
350

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

STRESS-STRAIN-DILATANCY RELATIONSHIPS OF NORMALLYCONSOLIDATED DHAKA CLAY
Muhammad Abdur Rahman1, Hossain Md Shahin2 and Teruo Nakai3
Lecturer, Department of Civil Engineering, MIST, Mirpur Cantonment, Mirpur, Dhaka-1216, Bangladesh.
2
Professor, Department of Civil Engineering, IUT, Board Bazar, Gazipur, Bangladesh.
3
Technical Adviser, Geo-Research Institute; Emeritus Professor at NIT, Nagoya, Japan; nakai.teruo@nitech.ac.jp
1

ABSTRACTIn this paper, stress-strain-dilatancy relationships of normally consolidated Dhaka clay is presented. Here twoconstitutive models of soils are used - one is Cam clay model (both original and modified) and subloading tij model.
To obtain the model parameters, drained triaxial tests of saturated cylindrical specimens under constant effective
confining pressure were conducted. The observed stress-strain relationship of the soil under consideration ispresented in the paper which confirms the normally consolidated soils. It is observed from the stress-dilatancy
relationship that, subloading tij model can well describe the stress-dilatancy behavior of normally consolidated
Dhaka clay. Therefore, subloading tij model can be used for the soil with better accuracy for the Dhaka clay.
Keywords: Stress-Dilatancy Relationship, Constitutive Modelling, Stress-Strain Relation, Drained Tri-axial Test.
Like most of the constitutive models for soils,
Cam clay model is formulated using the stressinvariants, e.g. mean stress p and deviatoric stress q
and the strain increment invariants, e.g. volumetricstrain increment dεv and deviatoric strain incrementdεd (Nakai et al., 2011).
Yield function of the model is defined by thefollowing equation:

INTRODUCTION
Usually, geotechnical engineering problems are
solved by considering soil as an elastic or rigid plastic
material where stress-dilatancy characteristics are nottaken into considerations. As in actual soil is anelastoplastic material most of the designs are either
over designed or under designed for not taking properconsiderations of constitutive model. There is thenecessity of a constitutive model which can simulate
the soil behavior accurately. On the contrary, most of
the constitutive models are not able to simulate total
behavior of the soil and does not fit with all the soils.
In this paper comparison between two simple
constitutive models in terms of stress-dilatancy
relationship is made to choose a better constitutive
model for Dhaka soils.
The first simple model which considered the soil
as an elastoplastic material is the Cam-clay model. In
the Cam-clay model (e.g., Schofield and Wroth,1968) positive dilatancy during strain hardening is nottaken into consideration along with some otherlimitations (Nakai et al., 2011). Subloading tij model(Nakai et al, 2011) can consider positive dilatancy
during strain hardening which has also been used inthis paper.

ln p + ζ(η) – ln p1 = ln

+ ζ(η) - ln

=0

(1)

Where, ζ(η) is an increasing function of η (η= q/p)
and satisfies the condition ζ(0) = 0, p0 is the value ofthe initial yield surface at p-axis, and p1 determines
the size of the current yield surface (the value of p at
η = 0).
The stress ratio function ζ(η) is expressed asfollows in Cam-clay model:
Original:
ζ(η) =(2)

Modified:(3)

ζ(η) =

Here, M is the stress ratio, η at critical state.
The plastic strain increment assuming associatedflow rule then can be expressed as follows (Nakai etal., 2011):

STRESS-DIALTANCY EQUATIONSIn this paper, comparison of stress-dilatancy
relation is made among the original Cam-clay model,
Modified Cam-clay model and subloading tij model.

.

Original Cam-Clay Model

351

(4)

GEOMATE - Mie, Japan, Nov. 21-24, 2017∗

Using Eq. (2), Eq. (3) and Eq. (4), the stressdilatancy relation can be derived as follows:
Original:(9)Here, Μ* expressed using XCS and YCS, which are thestress ratio X and Y at critical state (dεvp = 0).

(5)

Μ

∗

.

∗

Μ* = (XCS β + XCS β-1YCS)1/β(10)

Xcs and Ycs are expressed as follows (e.g., Nakai
and Mihara, 1984):
√

(11)
(12)

.

√

Where, Rcs is the critical stress ratio and expressed asfollows:

Fig. 1 Stress-dilatancy relation of original Cam
clay model.

RCS = (σ1/σ3)CS(comp).

Modified:

(13)

(6)

Fig. 3 Stress-dilatancy relation of subloading tij
model.
TRIAXIAL COMPRESSION TEST

Fig. 2 Stress-dilatancy relation of modified Camclay model.

To evaluate the stress-dilatancy relation, triaxial
consolidated drained compression test has been
conducted on two saturated specimens of Dhaka clay
under constant confining effective pressure of 199
kPa and 397 kPa.

Subloading tij model
In the subloading tij model (Nakai and Hinoko,
2004) yield function is given by,

Table 1 Test conditions.

The stress ratio function ζ(X) is then given by theequation below (Chowdhury and Nakai, 1998; Nakai
and Hinokio, 2004):

Effective
confiningpressure(σ3'), kPa(7)

B Value=0

Height(mm)+ ζ(X) - ln

Diameter
(mm)

= ln

Specimenln + ζ(X )– ln

(8)

A
B

38
38

76
76

0.97
0.98

199
397

ζ (X) =∗

Where β (≥1) is the parameter which controls theshape function. Finally, the stress dilatancy relation
can be expressed as,

RESULTS
Fig. 4 and Fig. 5 show the observed stress-strain,
volumetric strain – deviatoric strain relationships indifferent arrangements.
352

B
A
B
A

0

5

10

15

20

25

‐8

Deviatoric strain, εdVolumetric strain, εv

Fig. 4‐40

relationof

In Fig. 8 stress – dilatancy relation in subloading
tij model shows that for both the specimens the stress– dilatancy relation follow the identical pattern shownin Fig. 3.

3
2
B
A

1
0

5

10

15

0.7

B
20

0.6

A

25

0.5
0.4

Deviatoric Strain, εd

0.3
0.2

Fig. 5 Observed relation between volumetric strain
and deviatoric strain.

0.1

Figures 6 – 8 show the observed stress – dilatancy
relationship of Cam-clay model and subloading tij
model. In Fig. 6 it is observed that stress – dilatancy
relation of original Cam-clay model is linear. In Fig.
7 stress dilatancy relation of modified Cam-claymodel does not follow the unique pattern. In case of
the specimen A, the shape of the curve does notfollow the theoretical pattern as shown in Fig. 2.

‐1.5

1

A

0.8

0.2
0

0

0.5

Fig. 8 Observed Stress-dilatancy
subloading tij model.

relationof[1] Teruo Nakai, Constitutive Modeling of
Geomaterials, Principles and Applications, ISBN
13:978-0-203-86884-3, CRC Press.
[2] Schofield, A. N. and Wroth, C. P. (1968) Critical StateSoil Mechanics, McGrow- Hill,
London.
[3] Roscoe, K. H. & Burland, J. B. (1968) - Onthegeneralized stress- strain behavior of wet clay.
Heyman and F. A. Leckie (eds.), Engineering
Plasticity, Cambridge University Press, pp535609.
[4] Nakai, T., Shahin, H. M. Kikumoto, m.,
Kyokawa, H., Zhang, F. and Farias, M. M.
(2011): a simple and unified three-dimensional

0.4

‐0.5

0

REFERENCES

0.6

‐1

‐0.5
‐dεN*p/dεS*p

From the stress-dilatancy relationship presented
above it can be concluded that subloading tij model
fits better than the Cam clay model. Hence subloading
tij model can be used for the Dhaka clay.

η=q/p

1.2

‐1

CONCLUSIONS

1.4
B

‐1.5

‐2

‐dεvp/dεdp

Fig. 7 Observed Stress-dilatancy
Modified Cam-clay model.

Observed Stress-strain relation.

4

0

‐6

1.4
1.2
1
0.8
0.6
0.4
0.2
0

η=q/p

1.4
1.2
1
0.8
0.6
0.4
0.2
0

tS/tN

Stress ratio, η

GEOMATE - Mie, Japan, Nov. 21-24, 2017

0‐dεvp/dεdp
Fig. 6 Observed Stress-dilatancy relation of Camclay model

353

GEOMATE - Mie, Japan, Nov. 21-24, 2017

model to describe various characteristics of soils,
Soils and Foundation, 51(6), 1149-1168.
[5] Nakai, T. (2007): Modeling of soil behavior
based on tij concept, Proc. Of 13th AsianRegional Conf. on Soil Mech. And GeotechnicalEng.m Keynote Paper, 2, 69-89.

354

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

MECHANISTIC BEHAVIOR OF OPEN AND DENSE GRADEDUNBOUND GRANULAR MATERIALS UNDER TRAFFIC LOADS*Ali Alnedawi1, Kali Prasad Nepal1 and Riyadh Al-Ameri1
1

Science Engineering & Built Environment, Deakin University, Australia
ABSTRACTThe absence of natural unbound granular materials (UGMs) necessitates investigating alternatives such asprocessed crushed rock. Extensive use of crushed rock in pavement design requires proper modification ofcharacterization, design and construction practices. Many specifications and standards require adopting ofdense gradation of base materials. Although dense gradation has a high dry density, it also has low permeability
or voids. This low permeability results in a decrease in material strength when the pavement is exposed tomoisture. This research examines the effects of fines content on mechanistic behaviors of UGMs, particularly
resilient modulus (Mr) and permanent deformation (PD) using repeated load triaxial test (RLTT). Class 2(Victoria, Australia) crushed rock is used in two gradation, dense gradation and open gradation (without fillerpassing sieve 0.0075mm). Results from RLTT show that open graded Class 2 has an acceptable PD resistanceunder repeated loads for test’s Stages 1, 2 and 3 followed by a significant collapse at Stage 4 as per Australianpavement design guide. This investigation has found that open graded Class 2 has higher Mr than dense graded
Class 2. This paper suggests that open graded Class 2 could be used as a porous base material for roads with
low traffic volumes.
Keywords: Unbound granular material, Resilient modulus, Permanent deformation, Fines content, Repeatedload triaxial test.
1. INTRODUCTION
Unbound granular pavement materials (UGMs)
are used in many pavement structural systems asbase and subbase layers to support the surface layer
by distributing the traffic stresses to subgrade.
UGMs are mainly naturally occurring sourced
rocks, gravel or manufactured crushed rock [1].
The absence of natural aggregate necessitates
the need of such as processed crushed rock [2].
Crushed rock is the most widely used products inconstruction materials. It is produced by mining
suitable rock and processing it, then by breaking it
down to the proper size using crushers [3]. A proper
adjustment ofcharacterization, design andconstruction guides is needed after the extensive
usage of manufactured aggregates [4]. In addition,
producing fine particles from crushed rock is costly
and energy consuming. Some quarries are closed
because of the lack of fine particles, and row rocks
in these quarries are robust and difficult to process
into fines.
The UGMs are nonlinear and have a complex
behavior under repeated wheel loads (timedependent elastoplastic response) [5] [6]. Many
researches have been conducted to better
understand the behavior and the characteristics of
UGMs [7-12]. These materials reflect both
permanent strain (permanent deformation) andrecoverable strain (resilient deformation) as shown

Fig. 1 Plastic strain and resilient strain
in Fig. 1.
The deformation behavior of UGMs is essential
for performance and stability of the pavement
structure[11].
Permanent
andresilientdeformations usually are tested by using repeatedload triaxial test (RLTT), which is the best test thatsimulate the field traffic loads [13]. Both strains areused in flexible pavement structural design throughthe Mechanistic- Empirical (M-E) design methods.
For instance, Austroads pavement design method
and NCHRP design method [14].
Gradation of aggregates is one of the mainfeatures when studying the mechanical behavior of355

GEOMATE - Mie, Japan, Nov. 21-24, 2017

UGMs [15]. Specifications on gradation areintended to guarantee that the designer selects thesuperlative available combination of materials toachieve the desirable mechanical responses. Many
gradation specifications’ ambits assure to achievedense gradation to attain the maximum dry densityof the compacted materials such as specification of
VicRoads (Roads Corporation of Victoria).
Therefore, gradation specifications are so restricted
for this purpose. Pavement is susceptible tomoisture which comes from variety of sources suchas rainfall [16]. As mentioned latterly, dense gradedbase layer materials have high dry density thatcoincide with low permeability because of the low
voids ratio. If the pavement is exposed to moisture,then this low permeability allow water to gettrapped inside the base and subbase layers.
Eventually, pore pressure is induced yielding adecrease of material strength [17]. The purpose ofaggregate base material in low volume pavement isto protect the surface layer from the contaminationof subgrade’s fines and do not add much strength tothe pavement system [18]. Therefore, high quality
gradation with high resilient modulus (Mr) and highpermanent deformation (PD) resistance are notneeded all the time, low traffic volume pavement
can be designed with low mix quality.
Several factors affect the pavement strain
response of UGMs. These factors can be classified
broadly into two categories: stress and materials
related factors. Stress related factors include:
exerted repeated stresses by tire loads, load
duration, frequency of loading and load sequence.
Materials related factors include material density,
particles gradation, fines content, maximum grainsize, aggregate types, particle shapes and moisture
content [19].

pressure which leads to a decrease in the Mr. In
addition, open graded aggregates resist higher
stresses and strains compared to dense gradedaggregates. Type 5 aggregate base was tested by
Richardson and Lusher [22] in order to investigate
the effect of gradation on Mr. The purpose of the
proposed gradation is to help the manufacturer tolower the production cost of said aggregate. A
comparison has been made between the proposed
gradation (open gradation) and as-delivered
gradation. It was concluded that the open gradedgradation for the Type 5 aggregate base (withoutfines passing #200) is better than as-delivered one(dense, high fines content) because Mr is higher andthe degree of saturation is low.
Contrary to the previous findings, the variationof Mr is less significant depending on the material
gradation. However, the moduli were highest for the
open graded specifications than the dense gradedspecifications for lime stone aggregates [23].
Barksdale [24] observed the effect of fines
content in a crushed granite gneiss base after
100,000 load repetitions. Increasing the fines
percent from 3 to 11.25 caused 60 percent increasein rut index. Thus, when the fines percentage
increase, the plastic strain increase significantly.
Kamal, Dawson [25] conducted RLTT on UGMs at
a range of gradations and the results of the tests
revealed that the resistance to PD was high for wellgraded mix in comparison to the open graded one.
A recent study on the deformation behavior of
UGMs established by Rahman [11] has beensuggested to examine the influence of the grain size
distribution (gradation) and fines content on thepermanent deformation behavior of the UGMs.
It can be clearly seen from the previous works
that there is no agreement about the effect ofgradation and particularly the fines content on the
behavior of UGMs under repeated dynamic loads.
Therefore, this research focused on the fines content
effect on the deformation behavior of Class 2
crushed rock under repeated loading. Similarly to
Richardson and Lusher [22], open and dense gradedcrushed rock are investigated. In addition,
permanent deformation test is included anddifferent material is used (VicRoads’ Class 2). The
main objective of this research is to find the
response of UGMs without filler (particles passing
sieve 0.0075 mm) as an approach to design a porousbase layer. This research is part of an ongoing study
to investigate the response of UGMs with different
fines content.

1.1 Effect of Grading and Fines Content
The significance of identifying proper aggregate
gradation has been recognized for achieving
suitable performance in pavement design [15].
There are limited studies that investigated theeffect of gradation and fines content on the dynamic
properties of the UGMs. Hicks and Monismith [20]tested two types of materials, partially crushed
aggregate and crushed aggregate with different
relative densities and percentage of passing sieve
number 200 (filler) using RLTT. The effect ofgradation on Mr was not clear. However, when thefines content (in partially crushed aggregate)increases, Mr decreases. In the other hand, Mr
increases with the increase of fines content ofcrushed aggregates. Raad, Minassian [21] studied
the behavior of UGMs with different gradations
under saturated and undrained RLTT conditions. It
was recognized that the saturated dense gradedaggregates under dynamic loads induce excess pore

2. EXPERIMENTAL INVESTIGATION
2.1 Material
Crushed rock Class 2 is used as UGMs for thisresearch. Class 2 is recommended by VicRoads
356

GEOMATE - Mie, Japan, Nov. 21-24, 2017

specifications to be used as base material. Igneous(basalt) rock is the origin of crushed Class 2, which
was collected from Mountain View quarry locatedin Point Wilson, Victoria, Australia and delivered inplastic boxes. Fig. 2 shows Class 2 (as-delivered)particle size distribution. It can be clearly seen that
Class 2 is a dense graded material and fits inside the
VicRoads specification limitation envelope: upperand lower limits (UL, LL).

2.3 Testing Equipment
Repeated load triaxial test is conducted on thecylindrical crushed Class 2 specimens. The main

Fig. 4 New specimen confined by membrane
Fig. 2 Class 2 particle size distribution

parts of the system consist of load frame, actuatormotor, triaxial cell, digital control system,
pneumatic controller, external displacementtransducer and computer control. The actuator iselectro-mechanical with maximum dynamic axial
load capability of 5 kN, high precision position
feedback is provided capable of measuring the axial
displacement. The other transducer is used asadditional transducer to check the internal axial
displacement reading. The range of the LVDTs is ±11 mm. The system is capable of exerting up to 500
kPa of static confining pressure. Air and water areused as a confining medium. Triaxial cell pressure
is controlled via pneumatic controller which
controls air pressure. The digital control system iscapable of logging data from eight transducers.

2.2 Specimen Preparation
To prepare the open gradation, VicRoads’ Class
2 (as-delivered dense graded crushed rock) is
washed through sieve 0.0075 mm to purge out thefine particles. The specimens from these two
gradations are compacted into three split cylindricalmold with respect to optimum moisture content(OMC) and maximum dry density (MDD) of thetwo gradations as presented in Fig. 3.

2.4 Testing Sequences
Specimens are subjected to 4 stress stages. The
first preconditioning stage involves 50 cycles andeach permanent deformation stage involves 10,000
cycles. Repeated deviator stress, static confining
stress magnitudes and number of cycles arepresented in Table 1.

Fig. 3 Dry density-moisture content relationship

Table 1 Stress sequences
deformation test [26]Each specimen is compacted into 8 layers using
modified compactive effort with 25 blows per layer.
The final specimen size is 200 mm high and 100
mm diameter. Rubber membrane is encased thecylindrical specimen as shown in
Fig. 4. The preparation process is applied inaccordance with Austroads [26].

forpermanent

σ3 (kPa)σd (kPa)
CyclesStages
1
50
90
50
2
50
350
10000
3
50
450
10000
4
50
500
10000
Note: Preconditioning stage is added by author as
described in the European standard [27]357GEOMATE - Mie, Japan, Nov. 21-24, 2017

the specimen at this stage as shown in Fig. 7. Thisfinding confirm that pavement design proceduresshould not only be based on Mr values of pavement
materials, the PD needs to be examined likewise.

3. RESULT AND DISSCUSSION
In order to investigate the fines content effect on
the deformation behavior of the UGMs, zero fines
content gradation (no particles passing sieve 0.0075mm) is prepared by using the washing process
through sieve 0.075 mm to prepared the open
graded Class 2 crushed rock. Both dense and open
graded Class 2 were examined under RLTT toinvestigate the deformation behavior.
Fig. 5 compares the axial PD behavior for thetwo gradations of crushed rock materials, dense
graded Class 2 and open graded Class 2.

Fig. 6 Resilient deformation

Fig. 5 Permanent deformation
It can be seen that open graded Class 2 has high PD
resistance in the second stage (σd =350 kPa) and thethird Stage (σd =450 kPa) of the RLTT than dense
graded Class 2. This finding is contrary to Kamal,
Dawson [25]. Afterwards, when the test enteredStage 4 (after 20000 cycles, σd =500 kPa), PD
resistance starts to decrease showing steep upwards
trend while PD resistance of dense graded Class 2
decreases steadily. A possible explanation of thisbehavior could be that the open graded Class 2
could not withstand the high deviator stress at Stage4 (σd =450 kPa) because of the absence of fineparticles, which support the mix by transmitting theloads to other big particles. This preliminary finding
suggests that open graded Class 2 could be used asa porous base material but for low traffic volume.
Missing fine particles tends to high permeability
which minimizes the failure probability frommoisture. Even though further tests are required toconfirm this result with high degree of confidence.
Fig. 6 shows no significant variation in the RD
behavior for the two gradations.
Fig. 7 reveals that Mr values of open graded
Class 2 are greater than the Mr values of dense
graded Class 2, as concluded by Richardson andLusher [22]. Surprisingly, at Stage 4 of the RLTT
stress sequence (σd =450 kPa), Mr of open graded
Class 2 remain greater than Mr of dense graded
Class 2 despite the dramatic PD that happened inFig. 7 Resilient modulus
3. CONCLUSION
Results from RLTT show that open graded Class
2 has an acceptable PD resistance under repeatedloads for test’s Stages 1, 2 and 3 followed by asignificant collapse at Stage 4 as per Australianpavement design guide. Moreover, open graded
Class 2 has higher Mr than dense graded Class 2 forall stages. This paper suggests that open graded
Class 2 could be used as a porous base material forroad pavements with low traffic volumes.
Surprisingly, open graded Class 2 has high PD incoincidence with high Mr. Therefore, it isrecommended to examine both Mr and PD for an
accurate assessment.
4. ACKNOWLEDGEMENTS
Research material (crushed Class 2) was
donated by Mountain View Quarries in Point
Wilson, Victoria.

358

GEOMATE - Mie, Japan, Nov. 21-24, 2017

5. REFERENCES
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[2]
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Bowles, O., The stone industries. 1939:
McGraw-Hill Book Company.
Guimaraes, M., et al., Aggregate
production: fines generation during rockcrushing. International journal of mineralprocessing, 2007. 81(4): p. 237-247.
Chazallon, C., et al., Finite elements
modelling of the long-term behaviour of afull-scale flexible pavement with theshakedown theory. International journal
for numerical and analytical methods ingeomechanics, 2009. 33(1): p. 45.
Uzan,
J.,
GranularMaterial
Characterizationfor
Mechanistic
Pavement
Design.
JournalofTransportation Engineering, 1999. 125(2):p. 108-113.
Thompson, M. and K. Smith, Repeatedtriaxial characterization of granular bases.
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Research
Record,1990(1278).
Seyhan, U. and E. Tutumluer, Advanced
Characterization of Granular Materials for
Mechanistic Based Pavement Design, in
Pavement Subgrade, Unbound Materials,
and Nondestructive Testing. 2000,
American Society of Civil Engineers. p.
51-72.
Englund, J., Analyses of Resilient
Behavior of Unbound Materials for the
Purpose of Predicting Permanent
Deformation Behavior. 2011: Chalmers
University of Technology.
Cerni, G., et al., Resilient behaviour of
unbound granular materials throughrepeated load triaxial test: influence of theconditioning stress. Road Materials andPavement Design, 2015. 16(1): p. 70-88.
Rahman, M.S., Characterising theDeformation Behaviour of UnboundGranularMaterials
inPavement
Structures. 2015.
Azam, A.M., D.A. Cameron, and M.M.
Rahman, Permanent Strain of Unsaturated
Unbound Granular Materials from
Construction and Demolition Waste.
Journal of Materials in Civil Engineering,2015. 27(3).
Witczak, M. and J. Uzan, The Universal
Airport Design System, Report I of IV:
GranularMaterial
Characterization.
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Araya, A.A., Characterization of unboundgranular materials for pavements. 2011:
TU Delft, Delft University of Technology.
Xiao, Y., et al., Gradation effects
influencing mechanical properties ofaggregate base-granular subbase materials
in Minnesota. Transportation Research
Record: Journal of the Transportation
Research Board, 2012(2267): p. 14-26.
Zaika, Y. and L. Djakfar, GRADATIONBAND OF SOME TYPES MATERIALFOR RESERVOIR BASE OF POROUS
PAVEMENT. International Journal, 2016.
11(25): p. 2486-2492.
Rahman, M.S. and S. Erlingsson,
Influence of moisture on Resilient
Deformation behaviour of UnboundGranular Materials. Asphalt Pavements,
Vols 1 and 2, 2014: p. 571-580.
Muench, S.T., et al., Best practices forlong-lasting low-volume pavements.
Journal of Infrastructure Systems, 2007.
13(4): p. 311-320.
Lekarp, F., U. Isacsson, and A. Dawson,
State of the Art.II: Permanent Strain
Response of Unbound Aggregates. Journalof Transportation Engineering, 2000.
126(1): p. 76-83.
Hicks, R.G. and C.L. Monismith, Factors
influencing the resilient response of
granular materials. Highway researchrecord, 1971(345).
Raad, L., G.H. Minassian, and S. Gartin,
Characterization of saturated granularbases under repeated loads. 1992.
Richardson, D.N. and S.M. Lusher,
Resilient moduli of granular base materials
using a modified Type 5 gradation. 2009.
Heydinger, A., et al., Analysis of resilient
modulus of dense-and open-gradedaggregates. Transportation Research
Record: Journal of the Transportation
Research Board, 1996(1547): p. 1-6.
Barksdale, R.D. Laboratory evaluation ofrutting in base course materials. in
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Conference on the Structural Design ofAsphalt Pavements, Grosvenor House,
Park Lane, London, England, Sept. 11-15,
1972. 1972.
Kamal, M., et al., Field and Laboratory
Evaluation of the Mechanical Behavior of
UnboundGranularMaterials
inPavements. Transportation Research
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triaxial test for unbound mixtures. 2004:
Brussels.

permanent deformation and resilient
modulus characteristics of unboundgranularmaterials
underdrainedconditions, AG-PT/T053. 2007, Austroads
Publication
CEN, E.C.f.S., Unbound and hydraulicallybound mixtures - Part 7: Cyclic load360

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

STRUCTURAL NUMERICAL ANALYSIS ON AN OPEN-WING-TYPE
GROUND ANCHOR

1,2,3

Kota Kono1, Akihisa Nakahashi 2, Dong Daicho 3, Nobuo Fukushima 4 and Ryoichi Fukagawa 5
Graduate School of Science and Engineering, Ritsumeikan University, Japan; 4 Nakakura Inc., Japan; 5Ritsumeikan University, Japan

ABSTRACTThe anchor method involves connecting a structure or a slope with the anchorage zone by using the frictional
force between the grouting material and the surrounding ground to stabilize the structure or slope. However, overa long period of time said friction from traditional anchoring methods has been known to decrease, resulting indecreased anchor pullout resistance and ultimately, in anchor pull out. An open-wing type (OW) anchor method
developed by our research group is a new type of earth anchor method, in which we use open wings for pullout
resistance. Hence, this method can solve problems associated with existing methods. This study suggests an
optimum structure for the parts that open in the OW anchor using a numerical analysis, ANSYS (FEM). Threetypes of 3D analytical models – rotation axis type, bended steel sheet type, and impaction type – are used. The
analysis results show the optimum structure to be the impaction type structure, and simulations show that with abase metal yield strength safety factor of 1.5, an OW anchor could generate approximately 4250 N of extreme
pullout resistance.
Keywords: Landslide Prevention Work, Anchor Method, OW Anchor, Numerical Analysis, Ansys

anchor would be well suited to withstand significant
pullout resistance and enable practical anchoring.

INTRODUCTION
The anchor method employs means forconnecting a land retaining structure or a slope withthe anchorage zone by using the frictional force
between the anchor grouting material andsurrounding ground. Examples of the many types ofanchor methods include the ground anchor method,
earth anchor method, and ground reinforcing method.
These are applied at many construction sites formaintaining slope stability, preventing overturning ofretaining structures, in earth-retaining walls, etc.
The anchor’s pullout resistance relies on thefunctionality of the anchor’s main component,
grouting material, which is made of mortar. The
grouting material works as an adhesive connecting
and affixing the anchor via friction to its surrounding
ground in the anchorage zone. This friction has been
known to decrease over a long time period, ultimately
causing the anchor’s functionality to be lost as it ispulled out from its anchorage zone. The open-wing
type (OW) anchor method is a new type of earthanchor method [1]. In this method, we use open wings
for pullout resistance. Hence, this method can solve
the problems that are associated with the existing
methods.
This study presents an ANSYS (FEM) numericalanalysis to suggest an optimum structure for the
opening parts of an OW anchor. Then, using theresults of preceding studies, values of the cohesion
and, the internal friction angle. And this study
determines a range of root depths for which the OW

VERIFICATION
OF
THE
OPTIMUM
STRUCTURE BY NUMERICAL ANALYSIS
Method of Numerical Analysis
The pullout resistance of the OW anchor resultsfrom wings opened perpendicular to the direction ofpull and frictional force between the shaft andsurrounding ground. In analysis tool, pullout
resistance is expressed load to wings.
In this study, an analysis tool is used to model andcompare the pullout resistance of three anchor wing
configurations. When the wing or opening parts
stresses exceed a criterion, the corresponding load isdefined as the extreme pullout resistance for each of
the three configurations and the greatest value
determines the optimum OW anchor structure.
Points of Attention for Developing Analysis Model
Section size of analysis model
Ground anchors are used in the casing pipe of aborehole, which is placed underground. Hence, theOW anchor must fit into the borehole when theanchor wings are not open. For example, consider“shield casing 85” manufactured by TOHO
Underground Inc. as a reference [2]. Its outer
diameter is 85 mm and the inner diameter is 69 mm.
361

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Therefore, the outer size of the model must not be
more than 69 mm.

Table 1 Safety factor from pull out of ground anchor[3].

Cost of manufacturing
In the ground anchor method, many anchors ofordinary quality are used. Hence, a cheap material issuitable for fabricating an OW anchor. Therefore, itis preferable that the OW anchor structure is simple
and expensive materials are not used.

Type of anchor
Short span anchor (less than 2 years)
Long span
Normal timeanchor(more than
During an earthquake
2 years)

Criterion for Judgment of Practical Application ofModel
The pullout safety factor is widely used todetermine whether the anchor can be used practically.
Table 1 lists the pullout safety factors of different
ground anchors.
The OW anchor safety factor is related to wingbreakage during pullout, which is a primaryconsideration when considering the practicality of an
OW anchor for use. When planning for long time
usage of an OW using pullout safety factor, its safety
factor should be at least 2.5. But in this study, we use
breakage safety factor. Hence, we consider OW
anchors with a safety factor of 1.5.

Fig. 1 (a)Rotation axis type model.

Fig. 1 (b)Rotation axis type model.

Fig. 1 (c)Rotation axis type model.

3D Analytical Model
Three types of 3D analytical models are used inthis study. They are the rotation axis type, bended
steel sheet type, and impaction type models.
All 3D model have four wings and the angle
between shaft and open wing is 60°.
The rotation axis type model
Figure 1 shows the rotation axis type model. In
this model, wings are attached to shaft by rotation
axis (see Fig. 1 (b) and (c)). In this system, the wings
open as a result of rotation.
The bended steel sheet type model
Figure 2 shows the bended steel sheet type model.
In this model, wings are attached to shaft by steel
sheet. In this system, the wings open owing tobending of the steel sheet.
The impaction type model
Figure 3 shows the impaction type model. Thismodel has wings with a round base (see Fig. 3 (b))
and base part that contains a round hole (see Fig. 3(c)). This type is used to insert wings in a base partand the wings open as a result of the rotation ofwings.

362

Safetyfactor1.5
2.5
1.5–2.0

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Analysis Results
The rotation axis typeFigure 4 shows the relationship between the safety
factor and the extreme pullout resistance. The
optimum structure of the rotation axis type model cangenerate approximately 3350 N of extreme pullout
resistance when it is designed with a safety factor of
1.5. Figure 5 shows a colored distribution of safety
factor. Red shows the areas with the lowest safety
factor; hence, continuously increasing the load would
result in the red parts breaking first.
The bended steel sheet typeFig. 2

It can be concluded that the bended steel sheet
type model is not suitable for practical use, becausesome parts have safety factors less than 1 before thewings fully open. Figure 6 (a) and (b) show the
distribution of the safety factor. The factor is low
when the color is closer to red.

Bended steel sheet type model.

The impaction typeFigure 7 shows the relationship between the safety
factor and the extreme pullout resistance. The
optimum structure of the impaction type model cangenerate approximately 4250 N of extreme pullout
resistance when it is designed with a safety factor of
1.5. Figure 8 shows the distribution of the safety
factor. The safety factor is low when the color iscloser to red. When the load is increased, parts ofcircle in red break first, owing to the low safety factor.

Fig. 3 (a) Impaction type model.

3.5

Fig. 3 (b)safety factor

3

Impaction type model.

2.5

2

1.5

1
2000

3000

3350

pullout resistance (N)Fig. 4

Fig. 3 (c) Impaction type model.
363

Relationship between safety factor andextreme pullout resistance of the rotation
axis type.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 5Distribution of safety factor.

Fig. 8Distribution of safety factor.

STUDY ON MAXIMUM ROOT DEPTH OF
THE OPTIMUM STRUCTURE
Estimation of Maximum Root Depth when using
Optimum Structure

Fig. 6 (a)The optimum OW anchor structure was theimpaction type, owing to the greatest value of
extreme pullout resistance. To calculate themaximum root depth that can be withstood by said
pullout resistance, we use the results of precedingstudies, values of cohesion, and internal friction angle.
For estimation and comparison, a formula for thecomputation of pullout resistance exerted by a disk isused. Then, a series of experiments was conducted toinvestigate the relationship between the actual pullout
resistance exerted by an OW anchor and the actual
pullout resistance exerted by disk.

Distribution of safety factor.

Formula for Computation of Pullout Resistance
Exerted by Disk-shaped Earth Anchor

Fig. 6 (b)Katsumi and Nishihara (1978) suggested aformula for computing the extreme pullout resistanceexerted by a disk as a model of an earth anchor [4].
The formula is based on the formula for computationsuggested by Balla [5], Matsuo [6] - [8], Mors [9] andcan be expressed as Eq. (1),Distribution of safety factor.

3.5

safety factor

3

Q = G1 + Tv＋G2(1)

Where G1 is the weight of the soil mass, G2 is the selfweight of the anchor, and Tv is the summation of theperpendicular component of the shear resistance force
that is exerted on a slide plane and the perpendicularcomponent of the force that is perpendicularly exerted
on a slide plane.

2.5

2

1.5

Experimental Estimation of Pullout Resistance ofOW Anchor
1

2000

3000
pullout resistance (N)Fig. 74000 4250

We experimentally investigated the relationshipbetween the pullout resistance exerted by the OW
anchor and a disk. Figure 9 shows the experiment.
There are four experiment models. The first is the
open-wing ground anchor with four wings opened at

Relationship between safety factor andextreme pullout resistance of the impaction
type.
364

GEOMATE - Mie, Japan, Nov. 21-24, 2017

45°. The second is the same anchor with the wings
opened at 60°. The third is at 90°. The fourth is the
disk. The projected lengths of each wing on thehorizontal plane are all the same as the radius of the
disk. Figure 10 shows the pullout resistance exerted
by the OW anchor and the disk. Experimental results
show that an OW anchor with four wings opened at
60° exerts 58% of the pullout resistance exerted by
the disk.
Calculation of Root Depth
Figure 11 shows the flow chart of the method of
calculation of the root depth when using theimpaction type OW anchor. The results are shown in
Table 2. The root depth of the optimum structure
varies between 79 cm and 156 cm when the cohesion
value varies between 0–10 and the internal friction
angle varies between 15° and 45°.

Fig. 11 Method of calculation of root depth.

Fig. 9Image of the experiment.

Table 2 Root depth when using impaction type OW
anchor.

3000

c (kN/m2)
45°
60°
90°
disk

pullout resistance (N)

2500

0

2000

5

1500

1000

10

500

0
0

100

200

300

400

500

600

Displacement (mm)Fig. 10 Pullout resistance exerted by OW anchor
and disk.

365

φ(°)
15
30
45
15
30
45
15
30
45

D (cm)
156
102
83
146
99
81
138
95
79

GEOMATE - Mie, Japan, Nov. 21-24, 2017[9] Mors H., “Das Verhalten von MastgriindungenbeiZugbeansprunchung”, Die Bautechnik, Helf
10, pp.367-378,1959.

CONCLUSION
Summary
The optimum structure is the impaction typestructure, and it can generate approximately 4350 N
of extreme pullout resistance. The root depth of the
optimum structure varies between 79 cm and 156 cm
when the cohesion value varies between 0 kN/m2-10
kN/m2 and the internal friction angle varies between
15°-45°.
Future works
It is conceivable that for some use cases,
especially in applications with shallow root depths, an
OW anchor type, as described and proposed in thisstudy, could be used as a substitute for the existing
ground reinforcing type anchors. However, as the root
depths increase and approach 2 m, the OW anchor
type would not provide the holding abilities ofexisting ground reinforcing type anchors. For greaterroot depth applications, it would be essential to
improve the proposed OW anchor model or propose
a new model that would be capable of exerting more
extreme pullout resistance.
REFERENCES[1] Danjo T., Teramoto T., Miyajima Y.,
Fukushima N., Fujimoto M., Fukagawa R., “A
series of model experiments for developmentof Unfolding ground anchor”, Proceedings ofthe 7th Symposium on Sediment-Related
Disasters, 2014, Sept, pp. 241-246.
[2] TOHO underground Inc.
http://www.tohochikakoki.co.jp/cgibin/pdf2.cgi?p=casing.pdf, 2017/1/16.
[3] Japan Society of ground Engineers (2012),
architectonics, designed and basis on
construction of ground anchor, p.64．
[4] Katsumi T., Nishihara A., “Fundamental
studies on pullout resistance of earth anchors”,
J. Jpn. Soc. Civil Eng., No. 276, 1978, pp. 6576.
[5] Balla A., “The resistance to breaking out of
mushroom foundation for pylons”, Proc. 5th
ICSMFE, Vol. 1, pp. 569-576. 1961.
[6] Matuo M., “On the uplift resistance oftransmission tower footings”, J. Jpn. Soc. Civil
Eng., No. 105, 1964, pp. 9-18.
[7] Matsuo M., Shinjo T., “Study on the uplift
resistance of footings buried in cohesive soil”,
J. Jpn. Soc. Civil Eng., No. 137, 1967, pp. 112.
[8] Matsuo M., Tagawa S., “On an approximate
calculation method and a few specific problems
for the uplift resistance of footings”, J. Jpn.
Soc. Civil Eng., No. 149, 1968, pp. 27-35.
366

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

H/V SPECTRAL RATIO STUDY FOR ESTIMATION OF LOCAL SITE
EFFECTS IN VISHAKHAPATNAM CITY
*Swathi Priyadarsini Putti1, Dr.Neelima Satyam D.2
International Institute of Information technology-Hyderabad, India; 2 International Institute of Information
technology-Hyderabad, India

1

ABSTRACT
Dynamic soil properties have their own impact on ground motion intensity and hence regulate the damage.
Local site conditions control the frequency content of ground motions due to amplification or de-amplification.
Therefore in the present research an attempt has been made to estimate local site effects in Vishakhapatnam city.
The port city Vishakhapatnam comes under seismic zone II according to IS 1893:2002 and is one of those
rapidly growing cities of Andhra Pradesh, India. It lies in the midst of Bay of Bengal and Eastern Ghats,occupying an area of about 681.96 sq.km and is positioned at 17°41′18″N latitude and 83°13′07″E longitude. To
establish the predominant frequency and investigate the dynamic behavior of soils in the study area, micro
tremor testing was carried out in 75 locations of the city. Microtremor has been one among the contemporary
advances in geophysical testing techniques and is proved to be quite reliable from past studies. The results fromthe site study has shown presence of soils with frequency greater than 4Hz in most of the parts of the city andfew places has shown frequency of less than 1.9Hz where the predominant soils are clayey soils.
Keywords: Micro tremor, Vishakhapatnam, Local site effects, Spectral ratio(EGMB) Vishakhapatnam is bounded with Kailasa,
Narava and Yarada hill ranges on all the other threesides whereas the other side of the city is boundedwith Bay of Bengal. Figure-1 shows the politicalmap of the study area.
Major mineral deposits in the city comprises ofcharnockites, quartzites, pegmites and khondalites,
whereas predominant soil types in the area are redclay, gravel clay, sandy soil, clay, gravel loams.
Addressing the seismicity of the study area, the arealies in Stable central region of peninsular India.
Though major faults were not in the vicinity of
Vishakhapatnam city; abundant number oflineaments covers the area. About 85 seismic events(1828-2017) have been identified in about 300km
radius of the city with magnitude ranging from 2.0
to 5.5. Contrariwise, the regions which are deficit inpast seismic history are assumed to be prone toseismic risk due to excessive buildup of strainenergy. Therefore, the seismic hazard of the city is
proposed to be estimated in present research. The
quantification of seismic hazard can be done by theparameters such as frequency and amplitude.
Therefore it is proposed to carryout micro tremor
survey to estimate predominant frequency andamplitude.

INTRODUCTION
Dynamic soil properties play a prominent role in
the estimation of deformations and strains due tocyclic loading during an earthquake event. When thefrequency of the soil and the structure equals undercyclic loading, resonance occurs which leads tosevere damage. Therefore Frequency, time period,
amplitude are the influential parameters of a strong
ground motion. These parameters of strong groundmotion are highly variable depending on the local
site conditions. Hence estimation of local site effects
forms a reliable base for site characterization
studies. Though the study area Vishakhapatnam city
falls under Zone-II as per IS 1893:2002 with a zone
factor of 0.1, presence of operational port and rapid
development of infrastructure makes the cityprominent inspiring current research. The micro
tremor testing was therefore done to measure thefundamental frequency and amplitudes of the soils
all over the city. Site effects due to sand and clay
sediments are characteristic of the study area.
Higher frequency values (>4Hz.) are observed inmany parts of the city due to presence of rock andgravel and few places in eastern and western parts ofthe city has shown lower frequency values (<4Hz.)
indicating presence of silty sand and stiff clay
followed by marine clay with frequency values lessthan 1.9Hz in few places of the study area.

MICROTREMOR METHOD
Artificial ground vibrations with low amplitude
range are called as micro tremors. Microseisms canbe differentiated from micro tremors based on their
origin and frequency range. Micro tremors are theground vibrations with frequencies >1Hz because of
man-made activities such as movement of vehicles,

STUDY AREA
The study area Vishakhapatnam is a port city
located in southern part of India at
17°41′18″N latitude and 83°13′07″E longitude.
Characterized by Eastern Ghats Mobile Belt
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

impact loading etc. Heavy wind forces and otherFig.1 Political boundaries of the study area and marked test locations

Fig.2 Geological map of the study area (Modified from Subba Rao, 2008) [16]368GEOMATE - Mie, Japan, Nov. 21-24, 2017

October 6th city- Egypt (Mohamed et al., 2013).
Apart from these applications micro tremor has
been used to map collapsed columns in coal mines(Pei-Fen et al., 2009)[15] and for estimation ofseismic motion along expressways (Maruyama et al.,2000). Surve & Mohan, (2010)[18] conducted micro
tremor testing in Mumbai to demarcate thereclaimed area and actual basaltic islands from theresonant frequencies. Vulnerability index (Kg) frommicro tremor can be obtained by dividing the squareof amplitude with peak frequency. The index can beused to identify liquefiable sites. Supporting
evidence has been provided from case histories(Hardesty et al., 2010; Huang & Tseng, 2002; Saita,
Nakamura, & Sato, 2012)[16].
The steps involved in micro tremor survey aredata acquisition, data processing and analysis.
Important information regarding the site and sourceof noise can be observed from the type and form of
the H/V peaks. Clear peaks in the frequency plots
infer distinct impedance between upper soft layer
and the bedrock. Lower peaks at higher periods areusually imperative of hard rock. Clear peaks at
higher frequencies indicate that the sediment isindicative of weathered soil overlying rock. H/V
curves exhibit single peak when the sources are near
(4 to 50 times the layer thickness) and surficial. Twopeaks show up in case of distant source (more than
50 times the layer thickness) and located inside thesedimentary layer (Bonnefoy-Claudet,S. et al.,2006)[2]. Pappin et al., (2012)[14] from their studyin Hong Kong area inferred that the measured
frequency values match the calculated values when
the soil profile is considered up to a values where
SPT N>100. The limitation of using single station
micro tremor is that it is not reliable when the local
geology is complex and site effects are not due tosingle-impedance contrast (Chavez-Garcia et al.,2007)[7].

Oceanic activities causes vibrations withfrequencies <1Hz. which are termed as microseisms.
Microtremors
are pivotal in dynamic
characterization of soil.
The micro tremor peak which denotes thefrequency of first mode of vibration can be obtained
either from Raleigh wave ellipticity (Bonnefoy Claudet, Cornou, et. al., 2006)[3] or S-wave
resonance (Nakamura, 1989, 2000)[11] or Airyphase of love waves (Bonnefoy-Claudet et al.,2008)[2]. Rayleigh dominate the records in the caseof high impedance (I) contrast or frequency range(6-20Hz) and love waves when I< 3 or in the case of
low frequency (3.6-6Hz) (S.Bonnefoy-Claudet et al.,2008; Chavez-Garcia & Luzon, 2005)[2][6]. Basingeometry can have effects on resonance frequency
from HVSR technique (Gueguen et al., 2007)
particularly in narrow sediment basins.
Micro tremor method can be best described as ananalog of electrically passive magneto-telluric
exploration (Asten, 2004)[1]. Micro tremor methods
can be array based (ReMi) or single station. Array
based methods require more than one sensor and canbe used to correlate shear wave velocity using
Spatial Auto Correlation (SPAC) or Frequency
Wave number (FK) methods resulting in
identification of sediments thickness. Single station
method is much simple and can be used to estimate
dominant earth period, amplitude and vulnerabilityof an area.
Estimation of dynamic characteristics of soil
using micro tremor has been very habitual in the
1980s. But Standard spectral ratio method which
was used in earlier practices requires a reference sitevery near to the site of interest which is not viable inall geological and environmental conditions. The
horizontal to vertical spectral ratio (HVSR) method
has been introduced by Nakamura (1989)[12] gained
prominence in practice. H/V spectral ratio method
does not require any reference site for recordings.
Identification of a reference site at every survey
location will be a herculean task when the testing is
to be performed in densely populated cities. The
reliability of H/V method has been scrutinized bymany researchers by matching the results with theanalysis from strong motion records (Ch’avezGare’ia & Cuenca, 1996; Teves-Costa et a., 1996;
Bour et al., 1998; Jensen, 2000; Ch’avez- Garc’ia &Tejeda-J’acome,
2010;
Surve
&
Mohan,
2010)[4][5][18]. Since 1989, the method has been
applied to study dynamic properties and for micro
zonation of several cities Dinar-Turkey (Ansal,
2001); Southeastern Iran (Motamed et al., 2007);
lower Manhattan-New York (Stephenson et al.,2009); Marmara region- Western turkey (Hasancebi& Ulusay, 2006) ; Hong kong (Pappin et al.,2012)[13]; Izmir- Turkey (Eskisar et al., 2013);

FIELD TESTING AND DATA ACQUISITION
Though the present study area has experienced
no significant earthquakes in the past, from previous
earthquake case histories (1997 Jabalpur and 1993
Latur) no region of India is considered to be safe
against earthquakes. In case of a linear to low range
earthquakes, micro tremor along with non-invasive
active source technique best demonstrates theground response (Hardesty et al., 2010; Molnar etal., 2007). Hence this method can be applied tolocations such as Vishakhapatnam with nosignificant earthquake records.
Micro tremor survey has been conducted in 75
locations well distributed all over the city. Opengrounds away from structures, obstructions, windand underground structures were chosen to carry out
the test without any disturbances. During day lightthe ambient noise will be high that deviates theresults of frequency and amplitude. Hence
369

GEOMATE - Mie, Japan, Nov. 21-24, 2017with frequency value greater than 4Hz. has shown aclear distinctive peak indicating high impedancecontrast between the bed rock and the soil sediment
whereas plots for the locations with frequency rangeof 2.0-4.0Hz. has two peaks. This indicates that thesource of noise has been distant i.e, about 50 times
the layer thickness. It was observed that the areas
with gravely sand and soft disintegrated rock haveshown higher frequency values of greater than
4.0Hz. Whereas locations with soft clay deposits andmarine clay deposits near to the coast line has shown
lower frequency values of less than 2.0Hz.

recordings have been taken at early morning and lateevenings to assure reliability. The recorder records
microseisms instead of micro tremors if the ambient
noise is not avoided. The recording setup consists ofa tri axial velocity sensor (MS 2003+), recorder (MR2002-CE) and a field laptop. Figure-3 shows the
setup of the instrument at testing location MVP
colony.
The sensor is leveled and noise has beenrecorded for duration of 60 min with 1 sec pre-eventand post-event time. To record the latitude andlongitude of recording site global positioning system(GPS) has been used. Three-component recordingsfor H/V spectral ratio analysis were made at eachlocation stretching from Devada to Kapulauppada.
The frequency at maximum H/V ratio is indicativeof (among other parameters) presence of soft
sediment overlying stiffer materials.

Based on the frequency values and response
spectrum detailed characterization was carried out.
the proposed site classification based on H/V
spectral ratio analysis is shown in table-1
Table-1 site classes based on the results
S.No.
1.

Proposedclass
Type-1

Fundamental
frequency> 4.0Hz.

2.

Type-2

2.0-4.0Hz.

3.

Type-3< 2.0Hz.

From the results it was observed that most of thelocations where the predominant soils are gravelly
soil with pebbles, weathered rock and rock in few
places with a thin layer of soil cover has shownhigher frequency values as high as 10Hz resulting inlower amplification values. These locations with areclassified as Type-1. Few places in southern part ofthe city and western part of the city with mostly silty
sand and clayey sand has shown frequency values ofrange 2.0-4.0Hz and classified as Type-2. Other
locations in eastern part of the city and few locationsin the central part has shown frequency values <2.0Hz indicating presence of soft clay and marine
clay. These locations have shown higher amplitude
values indicating increased seismic risk in terms ofground motion amplification. Figure 4 shows typicalresponse spectrum for few locations of the study
area.
The amplitude values range from 1.11 to 2.46.
Amplitude values are dependent on the noiseproduced and its amplitude. During day time
amplitude may be recorded high and during nights it
might be low. High amplitude of vibration are
distinctive of south western locations (>2) andmoderate amplitude values (<1.5) has been recorded
all over the city. Iso-frequency maps have been
prepared from the frequency values of the study area
and can be used in further geotechnical engineering
practice.

Fig.3 Instrument set up at testing location(MVP Colony)
Summation of two horizontal components ineach sample was done to produce the Fourier
spectrum of horizontal ground motion for eachlocation. Fourier spectrum for the verticalcomponent was also calculated. The ratio ofhorizontal to vertical spectral amplitude wascalculated to produce H/V spectrum for eachlocation. For the clear identification of peak the
curves have been smoothened up to 10%. Eachspectrum was used to get the predominant frequencyof that location.
RESULTS AND CONCLUSIONS
From Micro tremor test results analysis using
Nakamura Horizontal to vertical spectral ratio
method, the peak frequency and amplitude has been
estimated at all the locations in the study area.
Figure5 shows the study area along with marked
testing locations. The frequency values are ranging
from 0.44-10.1Hz. The H/V plots of the locations370

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.4 Response spectra for test locations (a) Pendurthi, (b) Pedawaltair, (c) Dasapalla hills,(d) Chinnamushidiwada

Fig.5 Predominant frequency map of Vishakhapatnam city371

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 5 shows the frequency map along withsite characterization. Vulnerability index has been
calculated from the frequency and amplitude valuesof each location and hazard map was created using
the vulnerability index.

Microtremor Measurements for the estimationof seismic motion along expressways. In 6th
international conference of seismic zonation,Palm Springs,California,1361-1366[11] Nakamura,Y(1989).A method for dynamic
characteristics estimation of subsurface using
microtremor on the ground surface. Tokyo,
Railway Technical Research Institute/Tetsudo
Gijutsu Kenkyujo.
[12] Neelima Satyam, D. (2006). Seismic Microzonation of Delhi region. Doctoral Thesis,
Indian Institute of Technology Delhi. Delhi.
India.
[13] Neelima Satyam.D and Ikuo Towhata, Site
Specific Ground Response Analysis andLiquefaction Assessment of Vijayawada City
(India) Natural hazards March 2016, Volume
81, Issue 2, pp 705–724[14] Pappin,J, Jirouskova, N,So,M, Jiang,H,Yu,
Y.B&Ho, K.K.S(2012), Seismic Microzonation
Assessment in Hong-Kong. 15th worldconference
retrievedfrom
http://www.iitk.ac.in/nicee/wcee/article/WCEE2
012_1951.pdf[15] Pei-Fen, X., Chuan-Jin, L.Ying-Bing,Z., YinBing , Z., Zhao H,., & Yong –Jun. S (2009).
Mapping collapsed columns in coal mines
utilizing microtremor survey methods. Chinese
J. geophysics, 52 (7), 1923-1930.
[16] Saita, J., nakamura, Y., & Sato, T. (2012).
Liquefaction caused by the 2011. Off the pacific
Coast of Tohoku Earthquake and the result of
the prior microtremor measurement. In
conference on urban earthquake engineering.
Receivedfrom
http://www.sdr.co.jp/papers/15wcee_lique.pdf[17] Subba Rao,N.(2008). Iron content in groundwaters of Visakhapatnam environs, Andhra
Pradesh, India. Environmental monitoring andassessment, 136(1-3), 437-47.
[18] Surve, G., & Mohan, G. (2010). Site response
studies in Mumbai using (H/V) Nakamura
technique. Natural Hazards, 54(3), 783-795.

REFERENCES[1] Asten, M. W. (2004). Passive seismic methods
using themicrotremor wave field forengineering and earthquake site zonation. SEG
74th Annual Meeting. Denver.
[2] Bonnefoy- Claudet, S.Kohler, a., cornou, C.,
Wathelet, M.,&Bard, P-Y.(2008). Effects ofLove waves on Microtremor H/V ratio. Bulletinof the seismological society of America, 98(1),288-300.
[3] BonnefoyClaudet,Sylvette,Cornou,C.,Bard, PY.,Cotton, F., Moczo, p.,kristek,j.,&Fah,
D.(2006). H/V ratio. A tool for site effects
evaluation. Results from 1-D noise simulations.
Geographical Journal international, 167(2), 827837.
[4] Bour, M,.Fouissac, d., Dominique,P.,& Martin,
C. (1998), On the use of microtremor recordings
in seismic microzonation ;J. Soil Dyn.Earthq.
Eng. 17,465-474[5] Chavez-garcia,F.J.,&Tejeda-J.(2010).Site
response in Tecoman, Colima, Mexico –II
Determination of subsoil structur andcomposition with observations; j,Soil,Dyn .
Earthq. Engg, 30 (8), 717-723.
[6] Chavez- Garcia F.G.&Luzon , F.(2005) On thecorrelation of seismic microtremors, Journal ofgeophysical research 110B11).
[7] Chavez-Garcea F.J Dominguez, T.Rodriguez,
M&Perez F (2007).Site effects in a volcanic
environment A comparison between HVSR andarray techniques at olima, Mexico. Bulletin oftheseismologicalsocietyoftheAmerica.97(2),591-604[8] Diagourtas,D, Tzanis,A and Makropolous,K(2002) .Comparative study of microtremor
analysis methods. Proc of Earthquake
micronizing, 2463-2479[9] GaoY
Jiang,Y
Li,B&Yamauchi,Y(2012).Studyonmicrotremor
spectrumproperties on tunnel lining. In 2012
International Conference on Renewable. Energy
Research and Applications (ICRERA), IEEE, 16[10] Maruyama,Y.Yamazaki,F&Hamada,T(2000).

372

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

STUDY OF GROUND PENETRATIN RADAR(GPR) EXPLORATIONFOR CAVITY UNDER THE GROUND USING FIELD TESTEXECUTION OF SEWER
Daeyoung Lee1, Dongmin Kim2
Korea Inst. of Civil Eng. & Building Tech., Goyang, Republic of Korea

1

Korea Inst. of Civil Eng. & Building Tech., Goyang, Republic of Korea

2

ABSTRACTThis study, as part of the way to prevent ground settlement by deteriorated sewer, was intended to identify thecause of cavity and soil relaxation and evaluate the cavity exploration technique using GPR (Ground Penetrating
Radar) exploration method. To simulate the cavity and ground relaxation caused by sewer leak, field test was
conducted. 450mm in diameter and 2,500mm long concrete pipe was used install the sewer for the test and toevaluate the exploration performance by depth, sewer was buried at 1.0m and 1.5m depth. After putting the ice
seized 1m×1.0m×0.3m on top and at the bottom of the sewer, hose was connected to promote the thawing. To
measure the cavity caused by ice thawing, GPR exploration was carried out in a day, 5 days and 15 days.
In the result of test, Cavity and ground relaxation caused by sewer leakage were simulated using GPR explorationand the cavity and ground relaxation by sewer leakage were monitored. According to GPR analysis, ice thawing
caused ground relaxation and the cavity. Given the reflective surface under the ground over time, cavity appeared
to have developed upward.
Keywords: Sewer, GPR exploration, Ground settlement, Field test
and cavity and loosened soil are mixed, it's difficult
to detect them. This study, as part of the way toprevent ground settlement by deteriorated sewer, isintended to identify the cause of cavity and soil
relaxation and evaluate the cavity exploration
technique using GPR exploration method. Cavity
simulation and GPR exploration were carried out
through field experiment and the possibility ofdetecting cavity and soil relaxation was reviewed.

INTRODUCTION
Ground settlement in downtown is attributable tovarious factors such as the impact by excavation, soft
ground settlement, deteriorated sewer and poor
compaction. According to Seoul city office, 2,714 of
3,205 or 84% of road sinking occurred since 2010
were attributable to deteriorated sewer and of
10,392km-long sewer, 73.3% was more than 20 years
old, indicating the need for urgent maintenance [1] .
According to National Land Technical Policy
Institute in Japan which investigated the causes ofroad sinking from 2006 to 2009, the cases caused by
the sewer totaled as many as 4,000 annually [2].
Road sinking resulting from deteriorated sewer ismostly by the soil penetrated into the damaged sewer.
Amid ever-increasing road sinking in urban area of
Korea, more concern on refurbishing deteriorated
sewer has been drawn and in a bid to prevent the
ground settlement in urban area, prediction andrecovery technology which will prevent the groundsettlement in advance becomes more than important[3].
Thus to prevent ground settlement in downtown,
it's necessary to develop the detection technique thatwill evaluate the mechanism and predict the groundsettlement by leaked sewer. GPR exploration is used
to detect the cavity under the ground but when thecavity is deep or boundary between cavity andloosened soil is unidentified or complicate utilities

SEWER TEST INSTALLATION AND GPR
EXPLORATIONGPR exploration is one of the geophysicalprospecting technologies for commercial use withhighest resolution which has been commonly used
domestically for investigating underground utilities,
cavity and anomaly zone For detecting the cavity
below heavy traffic road, vehicle-mounted device
runs at normal traffic speed which is the optimal
method when considering the site condition andsafety [4]. GPR exploration is to evaluate the internal
state in a way of analyzing the wave refracted,
reflected and distracted from other material or
structural layer by dielectric constant whileelectromagnetic wave from the transmitter to theground passes the pavement structure [5].
To simulate the cavity and ground relaxation
caused by sewer leak, field test was conducted.
373

GEOMATE - Mie, Japan, Nov. 21-24, 2017
Table 1. Specification of CCTV
Parts

Specification

Monitor19 in (48.26 cm)
Power, Lighting, Brightness,
Forward/ backward, Rotation camera,
Side-looking camera, Input power:
220V, 60Hz
Rotation endless, 1.3 million pixels,
Waterproof, Size: ø 110, L 250 mm,
Weight: 1 kg
Camera LED: 12 (1 W)
Halogen lamps: 2 (12 V, 35 W)
Pipe diameter: ø 300~1200 mm
Wheel: ø 80, ø 120, ø 50 mm
Output: 30 V, 60 W
6 wheel drive
Height adjustable (remote control)
Size: 621 × 530 × 55 mm
Weight: 20 kg
Size: ø 12.5 mm, L 150m
Weight : 15Kg

Main
devices
CameraLighting

Selfpropelled
car

Cable

450mm in diameter and 2,500mm long concrete
hume pipe was used in stall the sewer for the test andto evaluate the exploration performance by depth,
sewer was buried at 1.0m and 1.5m depth. Afterputting the ice seized 1m×1.0m×0.3m on top and at
the bottom of the sewer, hose was connected topromote the thawing. Sand and soil were used to burythe sewer and cavity and ground relaxation were
simulated by ice thawing. To measure the cavity
caused by ice thawing, GPR exploration was carriedout in a day, 5 days and 15 days. GPR equipments
used for the test is as Table 1. To evaluate theexploration performance depending on frequency,
frequency wad varied to 100MHz, 300MHz 500MHz
and 1,500MHz during exploration.

(b) Ice installation(c ) Sewer installation(d) ice installation(e) Compaction(f) GPRFig 2. Field test installation process
GPR EXPLORATIONUNDER THE GROUND

OF

THE

CAVITY

Ground cavity and relaxation mechanism
Fig 3 shows the result of GPR exploration analysis
over time. As a result of sewer cavity exploration withthe frequency 300MHz and top soil depth 1.5m, aparabolic reflective surface was distributed above thesewer after installation which was considered madeby the ice on top of the sewer. After a day, 5 days and
15 days, a parabolic reflective surface appeared at
upper level than immediately after installation, which
was attributable to cavity resulting from thawing ofice. According to GPR exploration, the surrounding
ground was loosened while the ice is thawing whichcaused to form the cavity. Reflective surface formed
under the ground in 5 days indicated that the cavity
was developed upward. Ground surface settlement
following the cavity was expected, but no groundsettlement occurred thanks to sufficient compaction.
And no reflective surface was monitored when the ice
was buried below the sewer, which was attributable
to the failure of penetration by radar wave into thebottom of the sewer.

Fig 1. Sewer installed

Table 2. GPR equipment

specification(a) Excavation

View

Zond 12e(RADAR Systems, Inc.)
Shield Antenna (300MHz, 500MHz)
Notebook P/CS/W (Prism2.5) for analysis

374

GEOMATE - Mie, Japan, Nov. 21-24, 2017

weak. Generally the higher the GPR frequency thehigher the exploration precision and at the depth 1.0m
～ 1.5m, 300MHz ～ 500MHz appeared to beappropriate.

(a) Immediately after installation(a) 100MHz(b) After a day(b) 300MHz(c) After 5 days(c) 500MHz(d) After 15 days
Fig 3. GPR analysis results
GPR exploration performance depending on
frequency
Fig 4 shows exploration result varied depending on
frequency. No response appeared at 100MHz but ahorizontal reflective surface with a little curve along
the top of the sewer was extended to sewer length
15.0m. A parabolic reflective surface was distributed
above the sewer where the ice was put on which was
attributable to the cavity formed when the ice above
the sewer was thawing. Reflective surface by cavity
was monitored at 500MHz which however
disappeared over time, indicating less reliability forroad sinking comparing to 300MHz. No reflective
surface by the sewer was monitored at 1,500MHz andthe signal considered the reflective surface by cavity
which was formed when the ice was thawing was very(d) 1,500MHz
Fig 4. Result of depending on GPR frequency
CONCLUSION
Field test installation and GPR exploration wereconducted in a bid to identify the cavity and groundrelaxation by sewer leakage and as a result, theconclusion was obtained as follows.
1) Cavity and ground relaxation caused by sewer
leakage were simulated through field experiment andthe cavity and ground relaxation by sewer leakage
375

GEOMATE - Mie, Japan, Nov. 21-24, 2017

were monitored.
2) According to GPR analysis, ice thawing caused
ground relaxation and the cavity. Given the reflective
surface under the ground over time, cavity appeared
to have developed upward. Though ground settlementby cavity was expected, no ground settlement
occurred which was attributable to bearing capacityof the well-compacted ground.
3) In case that the ice was buried below the sewer, noreflective surface was monitored which seemed to be
attributable to GPR radar wave that failed to penetrate
into the bottom of the sewer.
4) According to GPR exploration, reliability to roadsinking was higher than others at 300MHz and noreflective surface was monitored at 1,500MHz.

REFERENCES[1] Road Management Team of Seoul City, Seoul
City's Management of Road Sinking and Manual,Special Training Manual for Seoul City
Officials. 2015[2] Yokota, T, Fukatani, W and Miyamoto, T. The
Present Situation of the Road in Sinkholes
caused by Sewer System, National Institute forLand and Infrastructure Management, 2012
[3] Lee. DY, Choi, YW and Choi, H. “Cavity
Detection under Road Structure for Cause
Survey of Road Cave-in”, Proc. of 2015
Symposium by Korean Society of Civil
Engineers, 1, 2015, pp. 217-218.
[4] Park, JJ, Han, JG, Yoo, SK, Hong, KK (2015).
“GPR technology for cavity exploration”,
Journal of the Korean geosynthetics society, Vol
14, No 3, pp 12-17[5] Baek, JO and Choi, JS (2014). “Road exploration
technology using GPR”, Road Engineers, Vol
16, No 3, pp 11-16.

ACKNOWLEDGEMENTS
This research was supported by the Korea Agency for
Infrastructure Technology Advancement under the
Ministry of Land, Infrastructure and Transport of the
Korean government. (Project Number: 17SCIPB108153-03)
andEnvironment
Ministry's
Environment Policy Public Technology Development
Project (Project Number: 2014000700006)” .

376

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EFFECT OF CONFINING STRESS AND INCLINATION ANGLE ON
THE STRENGTH BEHAVIOUR OF SAND
1Navid Khayat 1
Department of Civil Engineering, Ahvaz branch,
Islamic Azad University, Ahvaz, Iran.
Khayat@iauahvaz.ac.ir
ABSTRACTThis study assessed the effects of anisotropy in sands with various confining stresses. The tests conducted inthis research include 20 hollow cylinder torsion shear tests conducted on Tehran sand with high angularity. The
confining stresses of the samples were 100, 200 and 400 kPa, and the effect of the inclination angle on the major
principal stress (alpha) was investigated. In each confine stress three inclination angle 15, 30 and 60 degree wereapplied. According to the results, an increase in the alpha will result in a more contractive behavior in the sands.
The effect of anisotropy also becomes more obvious, as the confining stresses increases; however it was foundthat the mechanical properties of sands changed markedly with confining stress.
Keywords: Sand; Strength; Anisotropy; Confining stress;
Park, et al. [17], were used to further explore the roleof induced anisotropy, principal stress rotation andintermediate principal stress.
The mechanical properties of sands change
notably with a variation of the confining stress.
Sugiura, et al. [18]were investigating confining
stress dependency of mechanical properties of sands.
From their test results, it was found that themechanical properties of sands changed very
markedly with confining stress, and the degree ofconfining stress dependency diverges with theprimary properties.
In this paper, the role of angularity differences inthree types of sand with the same initial confining
stress and same mineralogical properties was studied.
The tests was conducted on Tehran sand (TS), withhigh angular grains,. The effective confining stress
was performed in 100, 200 or 400 kPa. In addition,
the effects of the inclination angle of the major stresswere investigated.

INTRODUCTION
The stress-strain behavior of sands undermonotonic loading has been the subject of various
studies in the past [1-3]. Key parameters-such as
density, grain size distribution, particle shape andmineralogy, method of sample preparation, directionof loading, and anisotropy that affect the behaviourof a sand under monotonic loading have beenpresented widely [3-6].
In addition, Extensive studies have been focusedon the effects of inherent and induced anisotropy on
the behavior of clean sand [7-9].In somegeotechnical problems, such as the bearing capacityof shallow foundations on sand ground, theconfining stress dependency of sand mechanicalbehavior plays an important role as a stress level
effect.
In the geotechnical literature, a large number ofintensive experimental studies have been devoted toinduced anisotropy of granular material. First, theconventional triaxial apparatus was largely used by
Poorooshasb, et al. [10], Poorooshasb, et al. [11],Tatsuoka and Ishihara [12], Ishihara and Okada [13]and Vaid, et al. [14], among others, used toinvestigate the effects of stress-induced anisotropy
on the subsequent drained and undrained behaviourof dense sand. One of the objectives was torecognize the yield surface within the light of theelasto plasticity framework. Therefore, in thefollowing decades, with advances in measurements
and control techniques, complex machines such as
the true triaxial, by Arthur and Menzies [15]; hollow
cylinder torsional shear (HCTS) by Hight, et al.
[16]; Khayat, et al. [1]; and plane strain machines by

EXPERIMENTAL PROCEDURE
Material Properties
The materials employed in this study was TSwith angular grains,. The grain size distribution
curves for sand is given in Fig. (1), which indicatesthat influence of particle shape alone is isolated
without introducing a possible additional variable in
the form of grain size distribution.
Results of the XRD scans of sands indicate thatquartz as the main phase is the dominant mineral(>75%)among analyzed sands. The minor amountcontains Palygorskite and Kaolinite (<10%). The
377

GEOMATE-Mie, Japan, Nov. 21-24, 2017and on the direction of stress increment, and was
also found to decrease with increasing strains[20].
An effective factor in the general behaviour ofsaturated sands in monotonic loading is soil relativeminor phases Kaolinite (Table.1).
100Percent by weight finer (%)

80





a factor that indications the sample’s specifications
at the end of consolidation stage. The samples
prepared at low densities display contractive
behaviors in the drained tests; this behavior causes
excess pore water pressure in undrained tests, which
decreases the effective confined stress. The changeof stress-strain from the softening to hardening states
is related mostly to the relative density, which isobserved and reported by several researchers such as
Bishop [21], Castro [22], Castro, et al. [23]and Seedand Idriss [24].

70
60
50
40
30
20
10
0
0.01

0.1

1

10

Testing Apparatus And Method

Grain Size (mm)To investigation the inherent anisotropy, ahollow cylinder torsional shear (HCTS) device isused. For a better investigation of the post peak
response, the device can perform tests with bothstress and strain controls. A closed loop control isapplied to the machine to handle any type of desired
stress history including major principal stressrotation and intermediary stress ratio. Fourelectrical/pneumatic [E/P] transducers are used tocontrol the pressure for the inner and outer cellpressures in addition to the torsion and axial loadpneumatic actuators. The use of an alternative DC
motor for torsional strain control test enables thestudy of the post peak behavior. In the case of ourtests, the motor is utilized because strain control isessential to study the softening response. The motor
speed in all of the tests remains constant and equal
to one degree per min. Eleven transducers areadjusted to measure the different factors constantly:
three water pressure sensors, two for the inner andouter cell pressures and one for the pore pressure;
one vertical dislocation sensor to measure axial
strain and one rotation angel sensor to measuretorsional strain; two differential pressure sensors;
two axial and torsional stress sensors; and finally,
two limit switch sensors are set up. A computer
program is utilized to control all of the test
procedures by means of a PID control algorithm. A
data logging device is the last part of the control
system. The sample dimensions were 16 cm inheight, 5 cm in inner diameter and 8 cm in outer
diameter.
The maximum inclination of the principal stressFig.1 Grain size distribution curves of the Tehran
sand.
Table1 Results of semi-quantitative bulk XRD
analysis.
SampleNo
Tehran

density Dr  emax  e / emax  emin , which is

90

Main
Phase
quartz

Minor
phase
Kaolinite

Trace
Phase
-

In addition one of the important factors inexperiments on the sands under high pressure isparticle’s fracture. If the particles of the sands arebroken, under load, the grain size distribution of thesand is changed. Hence, to assessment of the particle
fracture, two direct shear tests with 64 kg load(equal 900 kPa) were performed for each type of thesands. The weight of the sands was passed throughthe sieve No.40 & 100 which measured before andafter the test. Results indicated that only one percentof the sand was fractured during the test, which canbe neglected. The physical characteristics of studied
sand were measured (Coefficient of curvature anduniformity respectively 1.22 and 1.69)
Maximum And Minimum Void Ratios Of Sand
Kandasami and Murthy [19] based on theirexperimental results, indicated that the inﬂuence ofsand mechanical response, is a function of thedeviatoric stress, relative density and confining
stress. Some researcher has extensively described on
the non-coaxial behaviour of sand under various
stress paths through a series of HCTS tests [1, 16,19]. The non-coaxial behaviour was found to dependon the type of sand, relative density of the sample(  ), initial confining stress and particle shape areconsidered the critical parameters in this research.
The intermediate stress parameter (b)is constant (=0.5), for avoid of more variable parameters in tests.
Figure (2) schematically displays details ofapparatus, the stresses and their directions in the378

GEOMATE-Mie, Japan, Nov. 21-24, 2017

studies in the past. Key parameters-such as density,
grain size distribution, particle shape and mineralogy,
method of sample preparation, direction of loading,and shearing mode which can affect the behaviour ofa sand under monotonic loading have been
investigated and reported widely [4, 26].
The main goal of this research is to study theeffect of grain shapes as well as the confining stressupon anisotropy features. The sand is tested using

hollow cylindrical torsional shear test. In Fig. (2),Ar
and A s are the cross sections area of the axial
rod and the sample, respectively.

different initial confining stresses and various  ,toavoid of another variable parameters effect on tests,
the intermediate stress parameter is constant ( b =0.5). In the laboratory, the protocol for reconstitutionof a sand sample generates an inherently anisotropic
fabric structure due to the orientation andmorphology of the particles [27]. As a result ofdifferent inherent anisotropy of investigated sands,
reaching the same void ratio in the similar
preparation method of samples is difficult. In equal
confining stress, we reach similar relative density insample sands. For this reason, ASTM 4253 and
ASTM 4254[28] (ASTM, 2006b)are used tomeasure the minimum void ratio (emin) (densest
state) and maximum void ratio (emax) (loosest state)
respectively.
Test results of stress-strain and effective stress
path curves are presented in Figs (3-5). According tothese curves, the samples behavior are similar to
those of dense sands based on the classification ofundrained sand behavior in most conducted tests,
which the results are in good agreement with
Yoshimine, et al. [8].The results also indicate that,

Fig. 2 Schematic details and view of stresses inhollow cylindrical torsional shear test.
a) Schematic details of HCTS apparatusb) Stress distribution
Experimental Program
For sample preparation, the proper amount ofsand are deposited into a split mold through a funnel
with a long tube after a molding vacuum of 5 kPa isapplied to the sample and the split mold is removed.
Then the cell parts are assembled. Carbon dioxide(CO2) and de-aired water are passed through thesample in their saturated states. The circulating time
for the CO2that is used in the tests conducted byZlatovic and Ishihara [25] were 30 min for clean
sand. This method is applied in the present study.
After circulation of the CO2, the de-aired water
enters from the bottom similar to the CO2, in the
opposite direction of gravity and seeps into all of thevoids in the sample. The saturation procedurecontinues as the confining stress increased, and thepore water pressure is measured in several steps. If
the B-value exceeded 0.95, then the sample issupposed to be wholly saturated. At this time, thesaturation stage is completed and the sample should
be consolidated. Since all of the tests conducted inthis research are of the Consolidated Undrained(CU) type, all drainage valves should be opened
during consolidation and connected to the system.
The amount of water discharged from the sample
during consolidation can be measured by reading theburette numbers at the beginning and end of thisstage. After consolidation, the shear stage starts with
one degrees per minute, which is the lowest speed
can be applied to the system. During the shearing
step the pore pressure is almost uniform.



the samples strength decrease with increasing  .

Fig. 3 (a) Stress path and (b) stress–strain curves inTehran sand subjected to an initial effective
stress of 100 kPa.

RESULTS
The stress-strain behaviour of sands undermonotonic loading has been the subject of various379

GEOMATE-Mie, Japan, Nov. 21-24, 2017

mapping of the network of contact vectors,
experiments of this study utilize the principal stressinclination (α) as an ensemble measure of fabric ofsands.
In summary, it is especially interesting to study
the effects of fabric on very angular particles, suchas the ones used in this testing program. Angularsands have a propensity for orienting themselves in aplane normal to the direction of deposition undergravity and exhibit signiﬁcant interlocking. The
inherent anisotropy is especially predominant invery angular sands[32]. Research hitherto reported
on various sands such as rounded sands (Ottawa
sand—by Dakoulas and Sun [33], sub rounded sands
like Nevada sand [30], angular sands by Kandasami
and Murthy [19], have signiﬁcantly enhanced ourunderstanding of sand behaviour. The samples witha different roundness ratio generate different fabricstructures.

Fig.4 (a) Stress path and (b) stress–strain curves inTehran sand subjected to an initial effective
stress of 200.

Effect Of Initial Effective Confining Stress On
The Behaviour Of Sand
As showed in Figs. (5-7), with increasing theconfining stress these phenomena is more obvious in
investigated sand. In other hand confining stress has
a significant effect on the strength behavior of
granular materials. Alim, et al. [34], also indicatedthat confining stress has a significant effect on thestrength behaviour of granular materials. Vaid andNegussey [35] showed that, at equal relative
densities, angular sand was more resistant toliquefaction at lower confining pressures however,less resistant at higher confining stress than roundedsands. Alim, et al. [34]was defined the average
number of contacts per particle, and called it, thecoordination number of the particle. The averagecoordination number of the assembly is defined as
the ratio of the total number of contact points within
the assembly volume to the total number of particles
in the assembly.

Fig.5 (a) Stress path and (b) stress–strain curves inTehran sand subjected to an initial effective
stress of 400 kPa.
The Effect Of Inclination Angle (  ) On The
Sand’s Behaviours
In Figs (8-10), the strength of samples in phasetransformation point is reduced as  increases in,which indicates that the soil becomes softer. Thisbehaviour has been confirmed and described by
Yoshimine and Ishihara [29] for Toyoura sand andby Khayat, et al. [1] for a Firoozkuh sand-silt
mixture.
The changes in the strength and deformation as aconsequence of principal stress inclination can beconstrued as a continuum level indicator of thefabric anisotropy in sands [20, 30]. During shearing,
sand particles continuously rearrange and adjust
themselves in an ensemble by sliding and rolling so
as to form an optimal and unique anisotropic fabricstructure [31] in relation to the loading conditions.
A slow monotonic shearing process is used inexperiments to reach the ﬁnal state, which also
shows coincident orientation of the stress and strain
increments. While this does not present a detailed


CONCLUSIONSIn this study, the following parameters were
controlled:
1) The grain-size distribution curves of theinvestigated sands were close to each other.
2) The sampling stages for studied sand weresimilar.
3) The comparison samples were consolidated
under similar confining stresses (100, 200
and 400 (kPa)).
4) With applying same initial confining stressthe relative density of studied will be close
to each other.
Among the parameters which have effect on sandbehaviors the grading curve, sampling stages,
relative density, tried to be identical, and results
380

GEOMATE-Mie, Japan, Nov. 21-24, 2017r[8] M. Yoshimine, K. Ishihara, and W. Vargas,"Flow deformation of sands subjected toprincipal stress rotation," Soils and Foundations,vol. 38, pp. 179-188, 1998.
[9] S. Sivathayalan and Y. Vaid, "Influence ofgeneralized initial state and principal stressrotation on the undrained response of sands,"
Canadian Geotechnical Journal, vol. 39, pp. 6376, 2002.
[10] H. Poorooshasb, I. Holubec, and A. Sherbourne,"Yielding and flow of sand in triaxial
compression: Part I," Canadian Geotechnical
Journal, vol. 3, pp. 179-190, 1966.
[11] H. Poorooshasb, I. Holubec, and A. Sherbourne,"Yielding and flow of sand in triaxial
compression: Parts II and III," Canadian
Geotechnical Journal, vol. 4, pp. 376-397, 1967.
[12] F. Tatsuoka and K. Ishihara, "Yielding of sandin triaxial compression," Soils and Foundations,vol. 14, pp. 63-76, 1974.
[13] K. Ishihara and S. Okada, "Effects of stresshistory on cyclic behavior of sand," Soils andFoundations, 1978.
[14] Y. Vaid, E. Chung, and R. Kuerbis,"Preshearing and undrained response of sand,"Soils and Foundations, vol. 29, pp. 49-61, 1989.
[15] J. Arthur and B. Menzies, "Inherent anisotropy
in a sand," Geotechnique, vol. 22, pp. 115-128,
1972.
[16] D. Hight, A. Gens, and M. Symes, "Thedevelopment of a new hollow cylinder
apparatus for investigating the effects ofprincipal stress rotation in soils," Geotechnique,vol. 33, pp. 355-383, 1983.
[17] C.-S. Park, F. Tatsuoka, J. N. Mukabi, T. Sato,
Y.-S. Kim, and Y. Kohata, "Measurements ofelastic properties of geomaterials in laboratorycompression tests," 1994.
[18] H. Sugiura, M. Ichinose, T. Oyake, Y. Mashito,
Y. Ohuchi, N. Endoh, et al., "Role ofperoxynitrite
inairwaymicrovascular
hyperpermeability during late allergic phase inguinea pigs," American journal of respiratory
and critical care medicine, vol. 160, pp. 663-671,
1999.
[19] R. K. Kandasami and T. G. Murthy,"Experimental studies on the influence ofintermediate principal stress and inclination on
the mechanical behaviour of angular sands,"
Granular Matter, vol. 17, pp. 217-230, 2015.
[20] Y. Cai, H.-S. Yu, D. Wanatowski, and X. Li,"Noncoaxial behavior of sand under various
stress paths," Journal of Geotechnical andGeoenvironmental Engineering, vol. 139, pp.
1381-1395, 2012.
[21] A. W. Bishop, "Shear strength parameters forundisturbed and remoulded soil specimens," inProceedings of the Roscoe Memorial

indicated variation of roundness ratio ( r ),  andconfining stress.
The results can be summarized as follow:
1) With increasing confining stress, anisotropy
behavior became remarkable, so the effect of shape
more pronounced.
2) For each sand at constant mean effective stress,
the decrease in the final state friction angle was a
direct consequence of the decrease in final stateshear strength under various inclination angles (  ).
Finally, these experimental results indicated thatsands with more angularity, not only cause
increasing the shear strength, but also cause
increasing the anisotropy. This behaviour has been
more pronounce with increasing confining stress.
The anisotropic behaviour of sand was a function of
the stress ratio, relative density, initial conﬁning
stress and particle shape ratios, which could effecton the behaviour of sand samples.
ACKNOWLEDGEMENTS
The author is grateful to the Islamic Azad
University Ahvaz branch for their support.
REFERENCES[1] N. Khayat, A. Ghalandarzadeh, and M. K. Jafari,"Grain shape effect on the anisotropic behaviourof silt–sand mixtures," Proceedings of theInstitution of Civil Engineers-GeotechnicalEngineering, vol. 167, pp. 281-296, 2014.
[2] V. Georgiannou, A. Tsomokos, and K. Stavrou,"Monotonic and cyclic behaviour of sand under
torsional loading," Geotechnique, vol. 58, pp.
113-124, 2008.
[3] P. Guo and X. Su, "Shear strength, interparticle
locking, and dilatancy of granular materials,"
Canadian Geotechnical Journal, vol. 44, pp.
579-591, 2007.
[4] V.
Georgiannou
andA.
Tsomokos,"Comparison of two fine sands under torsionalloading," Canadian Geotechnical Journal, vol.
45, pp. 1659-1672, 2008.
[5] V. Georgiannou, "The undrained response ofsands with additions of particles of various
shapes and sizes," Géotechnique, vol. 56, pp.
639-649, 2006.
[6] G.-C. Cho, J. Dodds, and J. C. Santamarina,"Particle shape effects on packing density,
stiffness, and strength: natural and crushed
sands,"
Journalofgeotechnicalandgeoenvironmental engineering, vol. 132, pp.
591-602, 2006.
[7] M. Symes, A. Gens, and D. Hight, "Undrained
anisotropy and principal stress rotation insaturated sand," Geotechnique, vol. 34, pp. 1127, 1984.
381

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Symposium, Cambridge University, Cambridge,
Mass, 1971, pp. 3-58.
[22] G. Castro, "Liquefaction of sands, Harvard Soil
Mechanics Series No. 81," Cambridge, MA:
Harvard University, 1969.
[23] G. Castro, J. Enos, J. W. France, and S. Poulos,"Liquefaction induced by cyclic loading,"
NASA STI/Recon Technical Report N, vol. 83,
1982.
[24] H. B. Seed and I. M. Idriss, "Simplified
procedure for evaluating soil liquefaction
potential," Journal of Soil Mechanics &Foundations Div, 1971.
[25] S. Zlatovic and K. Ishihara, "Normalized
behavior of very loose non-plastic soils: effectsof fabric," Soils and Foundations, vol. 37, pp.
47-56, 1997.
[26] A. Tsomokos and V. Georgiannou, "Effect ofgrain shape and angularity on the undrained
response of fine sands," Canadian Geotechnical
Journal, vol. 47, pp. 539-551, 2010.
[27] Z. Gao, J. Zhao, X. S. Li, and Y. F. Dafalias,"A critical state sand plasticity modelaccounting for fabric evolution," International
journal for numerical and analytical methods ingeomechanics, vol. 38, pp. 370-390, 2014.
[28] A. Standard, "D4254–91: Standard Test
Method for Minimum Index Density and Unit
Weight of Soils and Calculation of Relative
Density," Annual Book of ASTM Standards,
ASTM International, West Conshohocken, PA,
2006.
[29] M. Yoshimine and K. Ishihara, "Flow potentialof sand during liquefaction," Soils andFoundations, vol. 38, pp. 189-198, 1998.
[30] P. V. Lade, N. M. Rodriguez, and E. J. Van
Dyck, "Effects of principal stress directions on
3D failure conditions in cross-anisotropic sand,"
Journal of Geotechnical and Geoenvironmental
Engineering, vol. 140, p. 04013001, 2013.
[31] J. Zhao and N. Guo, "Unique critical statecharacteristics in granular media consideringfabric anisotropy," Géotechnique, vol. 63, pp.
695-704, 2013.
[32] K. Iwashita and M. Oda, Mechanics of granularmaterials: an introduction: CRC Press, 1999.
[33] P. Dakoulas and Y. Sun, "Fine Ottawa sand:experimental
behavior
andtheoreticalpredictions,"
Journalofgeotechnicalengineering, vol. 118, pp. 1906-1923, 1992.
[34] M. Alim, K. Suzuki, and K. Iwashita, "Effect ofconfining pressure on the strength behavior of
granular material simulated by the discreteelement method," in Proceedings of the 10th
IAEG International Congress, IAEG2006,
Nottingham, 2006.
[35] Y. P. Vaid and D. Negussey, "Relative densityof pluviated sand samples," Soils andFoundations, vol. 24, pp. 101-105, 1984.
382

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

INVESTIGATIONS OF INTERACTION OF JOINT PILES WITH
PROBLEMATICAL SOIL GROUND IN KAZAKHSTAN
Askar Zhussupbekov1, Abdulla Omarov1, Asemgul Moldazhanova1, Asel Tulebekova1, Karlygash
Borgekova1 and Gulshat Tleulenova1
1
Department of Civil Engineering, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan

ABSTRACTAt present time the large-scale constructions are built highly in Kazakhstan in particular a building with pilefoundations on problematic soils. In this paper are presented the results of pile field test in construction site in
Astana and Caspian Sea Port Prorva. In this construction sites were carried out the static load test with ASTM
and Kazakhstan standards (GOST) and dynamic load test with GOST. Also using the Pile Dynamic Analyzer
testing method need for quickly determination of bearing capacity for single joint piles. These investigations areimportant for understanding of interaction mechanism of joint piles with problematical soil ground of “Cargo
Transportation Route for Facilities of the north-eastern part of the Caspian Sea North Caspian Marine channel
with berthing facilities Cargo Offloading Facility” the “Prorva” oilfield, Atyrau region, Western Kazakhstan.
Results of static test of steel piles are shown in graphs.
Keywords: joint pile, GOST, bearing capacity, SCLT.

1.

Caspian Sea Port “Prorva”.
The project area is situated on the Northern
Caspian Shelf. At present the North Caspian Sea has
a limited water depth (maximum 5 to 8 m). The
water level in the Caspian Sea depends on a balance
between the inflow of river water and evaporation(see Figure 2).

INTRODUCTION

In Western Kazakhstan, a mega-project is“Cargo Transportation Route for Facilities of thenorth-eastern part of the Caspian Sea North Caspian
Marine channel with berthing facilities Cargo
Offloading Facility” (CaTRO, COF) the “Prorva”
oilfield, Atyrau region. Testing of soils by piles was
submitted data by engineers of the LLP “KGSAstana” during November 2016 to May of 2017.
This working plan (WP) has been developed for the
production of driving operations of precast concrete
piles consists of two segments, segment 1 andsegment 2 are interconnected that supply thesegment 1 length 16 m, segment 2 lengths 9.5 and11.5 m, the total lengths 25.5 and 27.5 m, thereinforcement diameter of 8 mm with a cross section
400x400 mm. The pile tested areas in construction
site were showed on Figure 1.

Fig. 2

Fig. 1

Geotechnical profile based on Lab Results.

This has resulted in large variations in sea levelin the past. This explains the sequence and soil
characteristics of the deposits. Table 1 showsengineering-geological structure of the construction
site. Eleven engineering-geological elements (units)
are identified based on the geological setting and theborehole logs.

The pile tested areas in construction site383

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Pile driving in EGE-10 material may be difficult.
However, this layer is only encountered in one
borehole (at the west side of the COF).
Table 1 Engineering-geological elements
(EGE)
Soil
type

Generalconsist
ency

С

φ,
deg

Su,
kPa

Eoe
d
;ref

29.4

γnat
ural
* ),
kN/
m3
19.4

(EGE1)FILL:
SAND,
clayey,calcareous(EGE2)
SILT,
slightlyorganic,
calcareous(EGE3)
SAND,
silty,
calcareous(EGE7)
CLAY,
silty,
calcareous(EGE8)
SAND,
silty,
calcareous(EGE9)
CLAY,
sandy,
calcareous(EGE10)CLAY,
silty,
calcareo
us

loose
to
mediu
m
dense

0.7

25

2,80
0

soft to
firm

0.7

29,4

19.3

15

2,75
0

mediu
m
dense
to
dense

2.7

31.5

19.0

-

30,0
00

stiff

20.
8

24.7

19.1

80

2,00
0

capital of Republic Kazakhstan. Construction site
located at South-East part of capital of Republic
Kazakhstan. Territory of Astana city arranged in
Kazakh shield so territory isn’t seismicity Loam,clay, eluvia formation presented by loam withinclusion of gruss and ballast stone, sandstone,siltstone. Geology-lithologic cut of construction site
shown in Figure 3 [1].

Fig. 3
Geology of construction site-Embassyof USA in Astana, Kazakhstan [1].
very
dense

2.4

31.8

20.0

-

40,0
00

very
stiff

22.
7

23.8

20.6

150

4,00
0

very
stiff

25

24.7

20.2

150

2,00
0

2. COMPRESSION STATIC LOAD TESTIN CONSTRUCTION SITE PRORVAThis test is used to measure the axial deflection of avertical deep foundation when loaded in static axial
compression. This vertical compression pile
maintained load test is usually carried out to ensure
the structural and geotechnical soundness of the pileand also to predict settlement of other piles. The
usual procedure is to increase the load in stages until
the proposed working load and a certain factor ofsafety is reached and then to unload and to leave theload off until the rise or rebound substantially ceases,
the test in standardized by ASTM D1143 [2].
Testing with a static load (compression) was
carried out in accordance with ASTM D 1143 [2].
Vertical static loading of piles using the SCLT
method is one of the most widely used field test
methods for soil used to analyze pile bearing
capacity [2].
Static compression load tests were performed on
precast concrete joint piles No. TP-02 and TP-03,

Second Project construction site-Embassy of USA in
Astana, Kazakhstan
Construction site located at South-East part of384

GEOMATE - Mie, Japan, Nov. 21-24, 2017

which are driving in COF Area with depth 25.50 and
27.50, from ground level Baltic datum -25,609 m
and pre-augering with auger dia. 330 m, depth 11.40
m before driving.
In SCLT testing, the test load on the pile is
specified for two cycles (1639 kN and 3274 kN,
respectively). Loading and unloading was carriedout in the following sequence: 0, 30, 60, 90, 125, 90,
60, 30, 0, 170, 210, 250, 210, 170, 125, 80, 40 and
0% of design. In the first cycle, the experimental pile
was loaded to 100% of the design value (1639 kN);
during the second cycle, to 200% (3274 kN). The
hold time while loading was 60 min; while
unloading −10 min. It took 360 min, respectively, toattain peak load [3-6].
Testing platform presented itself system fromsteel, which consists of metallic beam and 2
platforms located on equidistant distances from thecentre main beams (see Figure 4).

4
5
6
7
8
9

10
11
12
13

pile length, L
26,75 mYoung’s
B 40
Econ
45 000 000 kPa
Elastic
0.011 m= 11 mm
line=(P*L)/(A*E)
Davisson (ASTM)
0.78 cm= 7.8 mm
offset Δ=D/120+0.4
Pile Ultimate Capacity
2480(pile number TP-02)(see Figure 5)
Fu
Second pile (Pile number TP-03)
Pile length, L
23,00 mElastic
0.0096 m= 9.6
line=(P*L)/(A*E)
mm
Davisson (ASTM)
0.78 cm= 7.8 mm
offset: Δ=D/120+0.4
Pile Ultimate Capacity
2450 kN(pile number TP-03)(see Figure 6)
Fu

Figures 5 and 6 shows the results of SCLT testing.

Fig. 4

Testing platform for static compression
load test.

SLT is a highly accurate and robust system thatenables you to monitor static pile tests whilst also
ensuring the safety of site operatives.
Davisson’s Offset Limit Method (ultimate load)offers the benefit of allowing the engineer, when
proofing a pile for a certain allowable load, todetermine in advance the maximum allowable
movement for this load with consideration to thelength and size of the pile (See Table 1 and Figures
5 and 6) [7-11].
Table 1 Pile characteristics and formula’s Davisson

1
2
3

Pile number
Pile section area
Approximated pile
diameter
Load

Fig. 5Results of SCLT pile number TP-02.

Fig. 6

Results of SCLT pile number TP-03.

A primary advantage of this method is that theactual limit line can be drawn on the load movement
diagram already before starting the test. The offset
limit load criterion is primarily intended forinterpretation of quick testing methods, but it canalso be used when interpreting results from the slow
methods.
The Davisson Offset Limit is very sensitive toTP-02
A=0.16 m2
D=45.0 cm
P=3000 kN
385

GEOMATE - Mie, Japan, Nov. 21-24, 2017

errors in the measurements of load and movement
and requires well-maintained equipment andaccurate measurements. However, it is easy to apply
and has gained wide acceptance.
3.

Anchoring-stubborn stand consist with main andsubsidiary systems, four `anchor pile used for pile
test.
Research polygon equipped by driving of testing
and anchor piles, mounting of metalwork ofanchoring stand, welding of anchor band.
Equipment which used in static pile test as
follows:- hydraulic jack СМZh58А, carrying capacity 2000
kN;
- hand pumping station MNSR with manometer
MTP-160;- two deflectometer - 6 PАО.
Jack with under base hand strain to pile and by
up rag of it rod to basic hummer. Steel piles tested
for 600 kN bearing load to press load 1200 kN, for
400 kN bearing load to press load 800 kN.
Field static pile test taken as follows [12-15]:- “rest “ pile stand during 7-10 days instant endingof driving pile;- loading of pile made by load up to 1200 kN and
800 kN;- size of each step of load equal 50kN and 100 kN;- unloading of testing piles made step by step;- removal of samples from the deflectometer was
carried out in the following order: first reading right after the load application, and then sequentiallythrough the four samples every 15 minutes ofobservation, two samples with an interval of 30 min
and then every 60 minutes to conditional
stabilization of deformation, ie until the precipitation
rate of the pile at a given stage of loading will not
exceed 0,1 mm in the last 60 minutes;- removal of count elastic deformation made on eachstep on unloading over 15 min.

METHOD OF DYNAMIC LOAD TEST(PDA)

Pile Dynamic Tests were performed on precast
concrete joint piles No. G-26 and B-38. Piles were
tested with PDA (Pile Driving Analyzer – Model
PAX) using hammer JUNTTAN PM25LC with ahydraulic hammer HHK-9A of 9 tons of weight anda head-cap of 990 kg. On the tested pile a pair ofaccelerometers and at least a pair of straintransducers are attached at least two pile diameters
below pile head.
The Figure 7 presents CAPWAP analysis resultsthat include plots of measured pile head dataobtained under the hammer blows from the end ofdriving and associated simulated pile head and toe
static load-movement relationships.

Fig. 7

Results of SCLT and Dynamic load testwith PDA.

Difference between performed SCLT and PDA
test could be explained partly because time gap
between PDA and SCLT is 9 days and also becauseof driving nearby piles before SCLT test, what
produce additional pore pressure and less friction at
the time of SCLT. Since high bearing soil layers
have large permeability it could be assumed thatpore pressure effect and pile set-up are quicker.
We have to be aware that simulation of staticload test with CAPWAP (or DLT) does not include
any long term effects like creep or long term
settlements. This is why in almost all cases
CAPWAP load-set curve is little higher than load-set
curve from static load test, specially for higher loads
and toe bearing piles.

4.1 Execution of static test of steel piles before
heightening of pile length
Graphic of dependence of settlement pile fromload and variation of settlement on step of load
received in test results.
A static pile test of steel H-piles was carried out
after the "rest” of pile after driving. Results of static
test of steel piles before heightening of pile length
shown in Table 2 and Figure 8

4. STATIC PILE TEST IN CONSTRUCTION
SITE-EMBASSY OF USA IN ASTANAThe objective of static pile test is determinationof settlement and bearing capacity of pile.
386

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 2 - Results of static test of steel H - piles

Fig. 9Results of SLT pile numbers LT-3, 4.

Fig. 10 Graphics dependence of settlement S
from Load P for LT-5, 6 (by GOST 5686-94).
CONCLUSION
Testing pile LT-1, driving depth L=7,0 m;
Testing pile LT-4, driving depth L=9,25 m;
Testing pile LT-6, driving depth L=10,25 m;
Testing pile LT-7, driving depth L=8,0 m.
Fig. 8Since 1994 year Kazakhstan Standard has notchanged, ASTM standard was updated in 2007, andtherefore takes latest developments in technology
and technical terms and provides for the use of more
modern equipment.
The purpose of testing is determination of
bearing capacity and the penetration depth ofimmersion of composite piles in problematicalground soils of Atyrau region, Kazkhstan.
According to the results of DLT with PDA ofdriven piles (40×40 cm and lengths of 23 m and26.75 m) the bearing capacity of the piles amounted
to be 2143 kN. The bearing capacity of driven piles
according to the results of SCLT amounted to be
2067 kN and 2042 kN.
The disadvantage of the offset limit load lies inthe difficulty of determining the modulus ofelasticity E for concrete piles and concreted pipe
piles. Davisson's method needs the pile to be loaded
to failure to be applicable.
We have to be aware that simulation of staticload test with CAPWAP (or DLT) does not include
any long term effects like creep or long term
settlements. This is why in almost all cases
CAPWAP load-set curve is little higher than load-set
curve from static load test, specially for for higher
loads and toe bearing piles.

Graphics of dependence of settlement S
from load P regarding results of static pile
tests before heightening of pile length (byASTM D/D 1143M-07).

Results of static test of steel piles after heighteningof pile length shown in Table 3 and Figure 9-10.
Results of static pile test showed that after
heightening of pile length given best results.
Table 3 Results of static test of steel H - piles387

GEOMATE - Mie, Japan, Nov. 21-24, 2017

GeotechnicalConference.
Vilnius,LITHUANIA, 2016, pp. 201-205.
[9] Poulos, H. G., & Davis, E. H. (1980). Pile
foundation analysis and design // Series ingeotechnical engineering. – John Wiley & Sons,
p. 397.
[10] Zhussupbekov A.Zh., M.K. Syrlybaev, R.E.
Lukpanov, A.R. Omarov. “The applications ofdynamic and static piling tests of Astana”. 15th
Asian Regional Conference on Soil Mechanics
and Geotechnical Engineering, ARC 2015: New
Innovations and Sustainability, 2015, pp. 27262729.
[11] Abdelrahman G. E., Shaarawi E. M., andAbouzaid K. S. Interpretation of axial pile load
test results for continuous flight auger piles.
Proc. of the 9 Arab Structural Engineering
Conf., Abu Dhabi, UAE,. 2003.
[12] GOST 5686-1994. Soils. Field test methods bepiles. M.: Standards Publishing House.
[13] Zhussupbekov A.; Omarov A. “Modern
Advances in the Field Geotechnical Testing
Investigations of Pile Foundations”. Procedia
Engineering. Volume 165, 2016, pp. 88-95.
[14] MSP 5/01-101-2003-Design and installation ofpile foundation.
[15] Zhussupbekov, A., Omarov, A., Zhukenova, G.,
Tanyrbergenova, G. Pile Foundations of Mega
Projects: New Railway Station and LRT in
Problematical Soil Ground of Astana. Procedia
Engineering, Volume 189, 2017, pp.511-518.

REFERENCES[1] Assel S. Tulebekova. Control Equipment forPile TestAccording to American andKazakhstan Standards. Modern Applied
Science; Vol. 9, No. 6; 2015, pp. 192-198.
[2] Standard Test Methods for Deep Foundations
Under Static Axial Compressive Load
D1143/D1143M – 07´1. ASTM, 2007.
[3] SNiP RK 5.01-01-2002 “Soil basement andfoundations”.
[4] SNIP RK 5.01-03-2002-Pile Foundation, Astana,
KAZGOR, 2003.
[5] Zhussupbekov A.Zh., Lukpanov R.E., Omarov
A.R.. “Experience in Applying Pile Static
Testing Methods at the Expo 2017 ConstructionSite”. Journal of Soil Mechanics andFoundation Engineering. Volume 53, Issue 4,
2016, pp. 251-256.
[6] Zhussupbekov
A.Zh.,
OmarovA.R.
“Geotechnical and construction considerationsof pile foundations in problematical soils”.
Proceedings of the 8th Asian Young
Geotechnical Engineers Conference, 8th
AYGEC. Astana, Kazakhstan, 2016, pp. 27-32.
[7] Davisson, M. T., “High capacity piles".
Proceedings of Lecture Series on Innovations inFoundation Construction, American Society of
Civil Engineers, ASCE, Illinois Section,
Chicago, March 22, 1972, pp. 81-112.
[8] Zhussupbekov A.; Lukpanov R.; Omarov A..
“The Results of Dynamic (Pile Driving
Analysis) and Traditional Static Piling Tests in
Capital of Kazakhstan”. 13th Baltic Sea Region388

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE UTILIZATION OF WATER FOOTPRINT TO ENHANCE THE
WATER SAVING AWARENESS: CASE STUDY OF A CERAMICPRODUCT
Karin Kandananond
Faculty of Industrial Technology, Valaya Alongkorn Rajabhat University, Thailand
ABSTRACTOne of the methods to increase the water saving awareness is the water footprint which is based on thecalculation of water usage incurred during the whole life cycle of a product. The case study in this research is thewater footprint computation of a ceramic product, a mug. The life cycle of a mug is assessed from the first stage,resource extraction, followed by manufacturing, usage until the last stage, disposal. The calculation of water
footprint is based on the ISO 14046: 2014 guidelines. Another objective of this research is to verify that the water
footprint can be utilized effectively as a tool to enhance the awareness and the perception of the ceramic businessowners towards the water saving issue. According to the research results, the paired t-test statistics was utilized totest the difference of the awareness level before and after introducing the water footprint concept to the businessowners. The results indicate that the awareness is significantly built up after the application of water footprint
education. This will lead to the sustainable use of water in the ceramic business
Keywords: Awareness, Ceramic, Water footprint, Water saving
introduction of strategies leading to the reduced
consumption. Noga and Wolbring [2] conducted astudy on the perceptions of water ownership andwater management among one hundred and sixty fourindividuals. The questionnaires were used as a
research instrument and the questions regarding thewater footprint were included. The results reveal thatthe questionnaire respondents are concerned with thewater scarcity. Another finding is that education
regarding the water conservation and recycling areneeded and it is key leading to the raise of awareness.
Moreover, most respondents agree that the water
footprint might be a potential tool leading to alleviate
the awareness. A study by Attari [3] also points outthat the accuracy of water use perception (water
footprint) is more precise than other means ofperception measurement in the similar category, e.g.,
carbon footprint.
Hoekstra and Chapagain [4] signify that theamount of water consumed for the production ofservices and commodities is the clear definition ofwater footprint and this number directly reflects thewater use of the population in a nation. Their study isalso extended to the identification of four factors
affecting the amount of water footprint, namely,
volume of consumption, consumption pattern,climate (growth conditions) and agricultural practice.
Gerbens-Leenes and Hoekstra [5] identify that there
are two parts of water footprint, i.e., operational water
footprint and supply chain water footprint. Anotherway to categorize the water footprint is based on thetypes of freshwater sources, blue, green and graywater footprint. The blue water footprint is the

INTRODUCTION
The environment issues have come into theattention of people since the last decade and they areranged from global warming to water drought.
Although the society starts to be aware of theimportance of the environment, the pathway whichleads the conservation of environment in reality is
still unclear and not practical. As a result, initiatives,
such as carbon footprint, are introduced in order to be
used as a tool to assess the carbon emission due tohuman activities with the objective of having the
medium for carbon trade. Similarly, water footprint is
the concept introduced by A.Y. Hoekstra from
UNESCO-IHE in 2002 and it is the amount offreshwater used to make goods or provide services.
The water footprint of every product or service willreflect the tangible amount of used water which iseasy to understand for people who are related to any
part of the life cycle of product or service. The
objective of this research is to study the potential ofwater footprint as a tool to increase the level ofawareness among the people.
REVIEW
According to Badruzzaman, Oppenheimer, Hess,
Smith, Upson, Postle, and Jacangelo [1], the purposesof water footprint are differentiated into four
categories, the measurement of water consumption,
the identification of environmental influence in termof numerical results due to the consumption, the risk
assessment regarding the consumption, the389

GEOMATE - Mie, Japan, Nov. 21-24, 2017

amount of water retrieved from the surface andground water while the green water footprint is thewater evaporated from the rainwater in the soil. On
the other hand, the gray water footprint is the polluted
water due to the manufacturing activities. According
to Čuček, Klemeša and Kravanj [6], footprint is a
powerful indicator used to measure the level ofsustainability in term of environment, society andeconomy.

questionnaires. They will distributed before and after
the workshop regarding the water footprint was
carried on. The paired t-test was utilized to signify thedifferent level of awareness after the workshop.

METHODIn this study, there are two folds of processes used
to carry on the research, the total water footprint
calculation and the increasing level of awareness after
the workshop regarding water footprint was
introduced. The main concept of water footprint
calculation is based on the identification of theframework of life cycle analysis. In term offramework, there are five steps incorporating with theframework creation.
-identify the studied impact-identify the studied product-identify the functional unit of product-identify the period for data collection
The initialization of the framework is shown in thefollowing Fig. 1.

Fig. 1

Fig. 2

Material flow analysis.

RESEARCH PROCEDURES
Since the target group of this study is the ceramicbusiness owners and executives, the life cycle
analysis of the ceramic product is limited to only
cradle to gate which covers the impact from a partial
product life cycle, i.e., resource extraction andmanufacturing. A ceramic product which is used as
the case study is a ceramic yellow jug for serving
water. The weight of this jug is 500 gram and it isshown in Fig. 3. Therefore, the function unit ofproduct is a jug. To illustrate the life cycle analysis,
the manufacturing flow chart is depicted in Fig. 4 andit composes of six steps as follows: forming andfinishing, biscuit firing, glazing, glost firing,
polishing and packaging.

Research framework.

The life cycle analysis is depicted in Fig. 2 asmaterial flow analysis (MFA) which shows the scopeof product life assessment (in this case, cradle to gate).
For cradle to gate, the analysis focuses the life cycle
only from resource extraction (cradle) to factory gate.
However, if it is cradle to grave, the scenario will
cover the whole life cycle of product (resource
extraction, manufacturing, distribution, use anddispose). Moreover, another critical function of MFA
is to identify the flow of materials in the
manufacturing process of a certain product.
Elaborately, MFA breaks the whole process into subprocesses and each sub-process has inputs (resources),
waste (emission) and output [7]. Another important
method used to assess the potential of water footprint
as a tool to raise the level of awareness is theFig. 3 Ceramic jug.

390

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Input
Raw material
Item
Prepared ceramic bodyResources
Item
Electricity (Jolly machine)

UnitgQuantity
450

Unit
kWh

Quantity
0.004

Input
Resources
Item
LPG

Unit
kg

Quantity
0.3

Input
Raw material
Item
Glaze

Unit
g

Quantity
50

Input
Resources
Item
LPG

Unit
kg

Quantity
0.5

Input
Resources
Item
Electricity (Polishing machine)

Unit
kWh

Quantity
0.07

Input
Resource
Item
Corrugated paper

Unitg

Quantity
60

Fig. 4

Table 3 Water footprint of raw material extraction(corrugated paper)

Process
Forming + Finiishing

Resource

Weight(kg)

Corrugated
paper

0.06

Process
Biscuit Firing

Water
Footprint( l/kg)
38.9

Total
(l)
2.334

Process

The water footprint calculation shown in Table 4
and 5 obviously show that the generated electricity iscontributed to both blue and gray water footprint.
Since the blue water footprint equals 5.6 l/kWh while
the gray water footprint is 5.7 l/kWh, the generationof electricity causes more polluted water than theused water (the amount of gray one is higher than theblue one.). In conclusion, the electricity used to
manufacture a jug leads to the water footprint of
0.8362 liter. According to Table 6 and 7, the blue andgray water footprint are equal to 2.51 l/kg and this
implies that the extraction of LPG spends the sameamount of surface water as the water it polluted [9].
Totally, the water footprint of LPG for a jug is equal
to 4 liter. In conclusion, the total water footprint of
the resource extraction and fuel used is shown in
Table 8. Therefore, the water footprint of a ceramicjug (cradle to gate) is equal to 16.9202 liter.

Glazing

Process
Glost Firing

Process
Polishing

Process
Packaging

Manufacturing flow chart.

LIFE CYCLE ANALYSIS
According to the material flow diagram, there arethree raw materials required to manufacture a ceramicjug, prepared ceramic body, glaze and corrugatedpaper (for packaging). Due to Table 1 and 2, the water
footprint of prepared ceramic body (l/kg) is equal to14.4 while the one of glaze is 65 l/kg (the data wasforwarded from the suppliers who conducted the inhouse experiment to determine the water footprint
data). On the other hand, the water footprint ofcorrugated paper (l/kg) in Table 3 is equal to 38.9 [8].
Therefore, the total water footprint due to the resource
extraction equals 6.5+3.25+2.334 = 12.084 liter. The
forming, finishing and polishing tools are run byelectricity which is generated by natural gas.
However, the fuel of kiln is LPG (liquefied propanegas). The water footprint calculation for electricity
and LPG is shown in Table 4 and 5.

Table 4 Total amount of electricity used

Weight(kg)

Preparedceramic body

0.45

Water
Footprint( l/kg)14.4

Weight
(kg)

Glaze

0.05

Water
Footprint( l/kg)65

Electricity

Formingand Finishing
Polishing

Quantity
(kWh)
0.004
0.07

Table 5 Water footprint of electricity used
Process

FormingandFinishing
PolishingTotal(l)

Blue
Water
Footprint(5.6l/kWh)0.0224

Gray
Water
Footprint(5.7l/kWh)0.0228

Total(l)

0.392

0.399

0.791
0.83620.0452

Table 6 Total amount of LPG used

6.5

Resource
LPG
LPG

Table 2 Water footprint of raw material extraction(ceramic glaze)
Resource

Process

Electricity

Table 1 Water footprint of raw material extraction(prepared ceramic body)Resource

Resource

Total
(l)
3.25
391

Process
Biscuit Firing
Glost Firing

Quantity (kg)0.3
0.5

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 9 Questions and pre-training scores

Table 7 Water footprint of LPG used
Process
BiscuitFiringGlost
FiringBlue Water
Footprint(2.51l/kWh)0.75

Gray Water
Footprint(2.51l/kWh)0.75

Total(l)

1.25

1.25

2.5

Question
Q1: To what extent is yourgeneralattitudetowards
reducing your water footprint?
Q2: How aware are you of theenvironmental impact of water
usage?
Q3: What is your level ofawareness of water costs andwhere water is wasted?
Q4: How aware are you of theways in which you can savewater?
Q5: Other than reducing yourwater use, how aware are youof the other ways to reduce yourwater footprint at work?
Q6: How motivated are you to
reduce your water footprint?
Q7: The life cycle analysis forwater footprint is useful for
createenvironmental
awareness.

1.5

4

Table 8 Total water footprint of a ceramic jug
Stage

Material/fuelResource
extraction

Ceramic prepare body
Glaze
Material
Electricity
LPG
Total

Water
footprint
6.5
3.25
2.334
0.8362
4
16.9202

LEVEL OF AWARENESS
Two groups of samples are selected to be studied.
The first group is the business owners and top
executives (N=9) while the second group is the midlevel management (N=15). The last group is theoperators in the workshop (N=20). All of them isworking in the ceramic business. The level ofawareness is started from distributing questionnaires
by mails to all groups of respondents. Afterwards, allrespondents was invited to participate in a one-day
workshop. The content covers the life cycle analysis,
the water footprint calculation as well as the abovecase study. After the class, the same set ofquestionnaires is re-utilized to assess the awareness.
The questions are adapted from Carbon awarenessquestionnaires(availableon
https://www.dorsetforyou.gov.uk/media/191602/Car
bon-Awareness-Questionnaire/s) which are designed
to assess the following aspects: attitude,environmental impact, water cost and waste, watersaving, water usage reduction and motivation. The
paired t-test was conducted to assess the knowledge
and awareness of experimental group regarding thewater footprint by comparing the pre-workshop andpost-workshop means. The results signify that there
both means differ significantly (p<0.01). Therefore,
the conclusion is that the awareness of the topexecutive and workforces towards the environment
increases dramatically after water footprint has beenused a tool.

Pre-training
Mean
S.D.
1.21
0.98
1.58

1.04

1.96

1.21

1.41

1.44

1.77

1.13

1.28

1.22

1.15

0.98

Table 10 Questions and post-training scores
Question
Q1: To what extent is yourgeneralattitudetowards
reducing your water footprint?
Q2: How aware are you of theenvironmental impact of water
usage?
Q3: What is your level ofawareness of water costs andwhere water is wasted?
Q4: How aware are you of theways in which you can savewater?
Q5: Other than reducing yourwater use, how aware are youof the other ways to reduce yourwater footprint at work?
Q6: How motivated are you to
reduce your water footprint?
Q7: The life cycle analysis forwater footprint is useful for
createenvironmental
awareness.

Post-training
Mean
S.D.

3.95

0.81

3.51

0.78

4.05

0.89

4.29

0.82

3.69

0.96

4.41

0.85

4.69

0.91

CONCLUSIONS
Theoretically, environmental awareness is theissue that comes to the interest of many people.
Although a lot of information regarding theenvironment keeps flowing to the society throughdifferent mediums, a number of people still finds that392

GEOMATE - Mie, Japan, Nov. 21-24, 2017

the environmental issue is not tangible. As a result,
this study focuses on the utilization of the water
footprint concept an instructional media to raise theenvironmental awareness of a specific group ofpeople (who works in the ceramic industry). Based on
the life cycle analysis, the water footprint of a casestudy (a ceramic product) is calculated to show acertain amount of water contributed to manufacturinga ceramic jug. Afterwards, the lesson learned from thecomputation of water footprint was used to train thetarget group with the objective to raise theenvironmental awareness. The pre-test and post-test
were used to assess the awareness of thecorresponding group while the paired t-test showsthat the level of awareness before and after the test issignificantly different after the water footprint
training was introduced to the target group.
Therefore, the practical water footprint method isproved to be effective in alleviating the awareness ofpeople towards the environment.

REFERENCES[1] Badruzzaman M, Oppenheimer J, Hess T, Smith
H, Upson S, Postle M, Jacangelo GJ, “Water
Footprint: A New Concept for Sustainable Water
Utilities”, Denver: Water Research Foundation,
2014.
[2] Noga J, Wolbring J, “Perceptions of Water
Ownership, Water Management, and the
Responsibility of Providing Clean Water”,
Water, Vol. 5, 2013, pp. 1865-1889.
[3] Attari SZ, “Perceptions of Water Use”,
Proceedings of the National Academy of
Sciences, Vol. 111(14), 2014, pp. 5129-5134.
[4] Hoekstra AY, Chapagain AK, “Water Footprints
of Nations: Water Use by People as A Functionof Their Consumption Pattern”, Water Resource
Management, Vol. 21(1), 2007, pp. 35-48.
[5] Gerbens-Leenes PW, Hoekstra AY, “Business
Water Footprint Accounting”, Delft: UNESCOIHE Institute for Water Education, 2008.
[6] Čuček L, Klemeša JJ, Kravanja Z, “A Review ofFootprint Analysis Tools for Monitoring Impacts
on Sustainability”, J. of Cleaner Production, Vol.
34, 2012, pp. 9-20.
[7] Hoekstra AY, “The Water Footprint Assessment
Manual: Setting the Global Standard”, London:
Earthscan, 2011.
[8] Corrugated Packaging Alliance, “Corrugated
Packaging Life-cycle Assessment Summary
Report”, Grove Village, 2010[9] EPE Empresa de Pesq.uisa Energética, “National
Energy Balance 2011: Base year 2010”, Rio deJaneiro: Ministério de Minas E Energia, 2012.

DISCUSSIONS AND FURTHER STUDIESThe accuracy of water footprint calculation heavily
relies on the inventory data. However, the preparationof inventory data in Thailand is not standardized.
Therefore, most of the data is adopted from theforeign sources. This practice has the influence on the
final result of the calculation. Moreover, the water
footprint of the energy source might lead to thedifferent results if other energy sources, e.g., biogas
is used to fuel the kiln.
Since the target group of this study is the people
who works in the manufacturing, the life cycle
analysis only convers the manufacturing stage.
However, the research study might be interesting to alarge group of people if it is extended to the whole life
cycle of the product (including distribution, use anddispose).

393

Construction Materials

394Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

MECHANICAL PROPERTIES OF FLY ASH GEOPOLYMER MORTARCONTAINING RECYCLED GLASSNattapong Damrongwiriyanupap1, Yue Huang2, Sangsan Wongchairattana1, Sakonwan Hanjitsuwan3,
Tanakorn Phoo-ngernkham4 and Prinya Chindaprasirt5
1
Civil Engineering Program, School of Engineering, University of Phayao, Phayao, 56000, Thailand
2
Department of Civil Engineering, Faculty of Engineering and Technology,
Liverpool John Moores University, Liverpool, L3 3AF, United Kingdom
3Program of Civil Technology, Faculty of Industrial Technology,
Lampang Rajabhat University, Lampang, 52100, Thailand
4
Research Center for Advances in Civil Engineering and Construction Materials,
Department of Civil Engineering, Faculty of Engineering and Architecture,
Rajamangala University of Technology Isan, Nakhon Ratchasima, 30000, Thailand
5
Sustainable Infrastructure Research and Development Center, Department of Civil Engineering,
Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand
ABSTRACTThis study presents the development of green and sustainable mortars using novel geopolymer materials as the
new binder and recycled glass as part of the aggregates. Recycled glass was used to partially replace fine aggregate
at the amount of 0%, 25%, 50%, 75%, and 100% by weight. Sodium hydroxide (NaOH) and sodium silicate(Na2SiO3) solutions were used as liquid alkaline activation in all mixtures. The geopolymer samples were preparedwith different liquid to solid binder ratios at 0.5, 0.6, and 0.7, and the ratio of Na2SiO3 to NaOH were fixed at 2.0.
The compressive and flexural strength were determined at the age of 7, 28, 60, and 90 days. The results showedthat the compressive and flexural strength of specimens increase with age. The optimum percentage replacementof fine aggregates with recycled glass was observed at 25%. With the proportion higher than optimum level, thecompressive and flexural strength of geopolymer mortars were found to decrease with increasing amount of fineaggregate replacement.
Keywords: Geopolymer mortar, Recycled glass, Fine aggregate replacement, Compressive strength, Flexuralstrength
fibre-reinforced concrete. He reported that the
samples with recycled glass has 12% lower
compressive strength of the ones using silica sandwhen cured at room temperature and 4% lower when
cured at 90C. The average 28 day strength of thesamples cured at room temperature was found to be
110 MPa while that of samples cured at 90C was 150
MPa. Wille et al. [11] used very fine glass powder(median particle size of 1.7 micron) in the productionof UHPC with a food-type mixer. They reported thatglass powder can be used for cement replacement andthat the optimum amount of replacement is 25% of
cement by weight. Kou and Xing [12] used 45
microns recycled glass powder as a cement
replacement in UHPFRC. They reported that the
replacement of cement with glass powder helps
increasing the long-term strength of the concrete andthat 15% replacement performs better than 30%
replacement. Higher strengths are observed for the
specimens cured at 90C in comparison to those cured
at 20C. However, concrete production is highly
resource and energy intensive, with the industry

INTRODUCTION
Recycled glass is increasingly being used in civilengineering applications such as construction backfill
material, subbase and subgrade materials, pavement
aggregates, trench bedding material, and landfill
material. This clearly demonstrates the need for analternative method of glass recycling, one in whichlarge quantities of waste can be consumed. Thus, theconstruction industry presents an attractive way forthe use of waste glass. One of the principal
components of construction is concrete which is
widely used in many countries. Several studies havebeen conducted to utilize recycled glass as aggregatesin concrete [1]-[3] as well as using recycled glass
powder as partial replacement of cement in concrete[4]-[8]. Only a few have studied the use of recycled
glass as aggregate replacement and as cement partial
replacement in ultra-high performance concrete. Le[9] and Yang et al. [10] used recycled glass withparticle size of less than 600 microns as a replacementof 240 microns silica sand in ultra-high performance395

GEOMATE - Mie, Japan, Nov. 21-24, 2017mortar samples were then placed into 50x50x50 mm
cube and 75x75x300 mm prism molds forcompressive and flexural strength test, respectively.
The specimens were wrapped with vinyl sheet toprotect moisture loss and kept in the room
temperature. The compressive and flexural strengthof geopolymer mortars were measured at the age of 7
and 28 days. The results were the average value of
three samples.

responsible for approximately 5-8% of worldwide
greenhouse gas emissions [13]. As such,opportunities to reduce the environmental impacts ofthe concrete industry are required. Therefore, the useof new binding material i.e. geopolymer concrete is
one the ways to reduce CO2 emissions due to Portland
cement production. With natural aggregates within
the world being present in limited quantities anddecreasing every year, and producing crushed
aggregate for use in the construction industry is costly.
It can therefore be seen that incorporating recycled
glass as an aggregate in structural concrete has thepotential to not only produce environmental benefits
in the reduction of landfill and the consumption of
raw materials, but to also reduce costs for industry
costs. In addition, the outcome of this research could
help not only Thailand but also the world to divert
significant quantity of waste material, i.e. waste glassfrom landfills and considerably reduce environmental
damage caused by carbon emissions due to PC
production. Therefore, in this work, the study on theeffect of incorporation of recycled glass as fineaggregate replacement on mechanical properties ofgeopolymer mortar will be investigated.

RESULTS AND DISCUSSION
The 7-day and 28-day compressive strength ofgeopolymer mortars with L/B = 0.6 and 0.7 atdifferent amount of sand replacement with recycled
glass is summarized in Table 1. Figures 1 and 2
illustrated the compressive strength of geopolymer
mortars at 7 and 28 days, respectively. As seen in Figs
1 and 2, the compressive strength of mortar
specimens depended on L/B and percentage ofrecycled glass content in the mixtures. At 7 days, it isevident that compressive strength of specimens
decreased with increasing of amount of sandreplacement for both L/B = 0.6 and 0.7. And, thehighest compressive strength was obtained at thecontrol specimen, 0% replacement, that is 17.8 and13.2 MPa for L/B = 0.6 and 0.7, respectively.
Whereas, at 28 days, samples with 25% sandreplacement provided the highest strength that is 32.5
and 29.5 MPa for L/B = 0.6 and 0.7, respectively.
This is slightly higher than control specimens about
0.93% and 4.2% for L/B =0.6 and 0.7, respectively.
When the amount of sand replacement exceeded
25%, the compressive strength of geopolymer
mortars tentatively decreased. It is obviously noticed
that, at L/B = 0.6 and 0.7, the 28-day compressive
strength of specimens were higher than 7 days due tothe increase of degree of geopolymerization.
The flexural strength of geopolymer mortars
exhibited the similar trend to compressive strength
and was summarized in Table 2. The flexural strengthof mortars at different L/B cured for 7 and 28 days areillustrated as Figs. 3 and 4, respectively. The trend offlexural strength tended to decline with increasing ofsand replacement with recycled glass. At 28 days, theflexural strength of the mortar samples was higher
than 7 days curing due to the additional geopolymeric
reaction. At 7 days, the highest flexural strength of
specimens was obtained at 0% sand replacement thatwas 0.14 MPa for L/B = 0.6. Whereas, at L/B =0.7,
the highest flexural strength of mortars was observed
at 25% sand replacement i.e. 0.12 MPa. However, thiswas not much different obtained from 0%
replacement which was 0.11 MPa. Similar to the ageof 7 days, L/B of 0.6 yielded the highest 28-day
flexural strength of 0.29 MPa.

MATERIALS AND TESTING ANALYSIS
All geopolymer mortars were made of fly ash(FA) from Mae Moh lignite power plant in northern
Thailand. The chemical compositions of FA consistof SiO2 (25.6%), Al2O3 (9.1%), Fe2O3 (27.8%), CaO(25.0%), MgO (3.0%), K2O (3.0%), Na2O (0.2%),
SO3 (6.0%), and LOI (0.3%) indicating that FA
mainly consisted of SiO2 and Al2O3 and some
impurities. The sum of SiO2, Al2O3 and Fe2O3 was
62.5%, and the CaO content was high at 25.0%. This
FA was Class C fly ash as specified by ASTM C618
[14]. 10 molar sodium hydroxide (SH) and sodium
silicate (SS) with 13.89% Na2O, 32.15% SiO2, and46.04% H2O were used as alkali activators. The local
river sand with specific gravity of 2.62 and finenessmodulus of 1.41 was used as fine aggregate. Crushedrecycled glass used in this study has specific gravity
and fineness modulus of 25.1 and 1.67, respectively.
The abbreviations of FA-100S0G, FA-75S25G,
FA-50S50G, FA-25S75G, and FA-0S100G withcorresponding to fly ash geopolymer mortar with theamount of sand replacement with recycled glass at
0%, 25%, 50%, 75%, and 100% by weight,
respectively. The ratios of liquid to solid binder (L/B)
were varied at 0.6 and 0.7. While, the ratio of SS to
SH, and sand to binder was fixed at 2.0, and 1.0,
respectively.
In mixing process of geopolymer mortars, FA andsand/recycled glass were dry mixed until the mixture
was homogenous which took approximately 1 minute.
The alkali activator solutions were then added and themixing was done for another 3 minutes. After mixing,
396

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Compressive
mortars (MPa)

20
18
16
14
12
10
8
6
4
2
0

7 days
0.6
0.7
17.8
13.2
16.9
11.9
16.6
11.9
16.4
10.9
14.5
10.8

of

Table 2 Flexural strength of geopolymer mortars(MPa)geopolymer

Curing time
L/B
FA-100S0G
FA-75S25G
FA-50S50G
FA-25S75G
FA-0S100G

28 days
0.6
0.7
32.2
28.3
32.5
29.5
28.2
25.6
26.1
25.7
24.7
24.6

0.10
0.08
0.06
0.04
0.02
0.00

L/B = 0.6
L/B = 0.7

0.70

20
15
10
5

0.60
0.50
0.40
0.30
0.20
0.10
0.00

FA-100S0G FA-75S25G FA-50S50G FA-25S75G FA-0S100G

FA-100S0G FA-75S25G FA-50S50G FA-25S75G FA-0S100G

Geopolymer mortars

Geopolymer mortars

Fig. 2The 7-day flexural strength of geopolymer
mortars containing recycled glass.

0.80

L/B = 0.6
L/B = 0.7
Flexural strength (MPa)Compressive strength (MPa)Fig. 325

0FA-100S0G FA-75S25G FA-50S50G FA-25S75G FA-0S100G

Geopolymer mortars

The 7-day compressive strength ofgeopolymer mortars containing recycled
glass.

30

L/B = 0.6
L/B = 0.7

0.12

Geopolymer mortars

35

28 days
0.6
0.7
0.75
0.12
0.29
0.11
0.27
0.12
0.19
0.11
0.20
0.07

0.14

FA-100S0G FA-75S25G FA-50S50G FA-25S75G FA-0S100G

Fig. 17 days
0.6
0.7
0.14
0.11
0.10
0.12
0.10
0.11
0.10
0.11
0.09
0.07

0.16

L/B = 0.6
L/B = 0.7
Flexural strength (MPa)Compressive strength (MPa)Curing time
L/B
FA-100S0G
FA-75S25G
FA-50S50G
FA-25S75G
FA-0S100G

strength

The 28-day compressive strength ofgeopolymer mortars containing recycled
glass.

Fig. 4397

The 28-day flexural strength of geopolymer
mortars containing recycled glass.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

waste glass in concrete”, Cem. and Conc. Res.,
34(1), 2004, pp. 81-89.
[5] Shi C, Wu Y, Riefler C, Wang H, “Characteristics
and pozzolanic reactivity of glass powders”,
Cem. and Conc. Res., 35(5), 2005, pp. 987-993.
[6] Shayan A, Xu A, “Performance of glass powder
as a pozzolanic material in concrete: a field trial
on concrete slabs”, Cem. and Conc. Res., 36(3),2006, pp. 457-468.
[7] Schwarz N, Cam H, Neithalath N, “Influence ofa fine glass powder on the durability
characteristics of concrete and its comparison to
fly ash”, Cem. and Conc. Comp., 30(6), 2008, pp.
486-496.
[8] Soroushian P, “Towards board use of recycled
glass concrete on MSU campus”, Innovation in
Sustainability Seed Grant Report”, Michigan
State University, Dec. 2012.
[9] Le TT’ “Ultra high performance fibre reinforced
concrete paving flags”, Ph.D. Dissertation,
University of Liverpool, 2008.
[10] Yang SL, Millard SG, Soutsos MN, Barnett SJ,
Le TT, “Influence of aggregate and curing
regime on the mechanical properties of ultra-highperformance
fibre
reinforced
concrete(UHPFRC)”, Conc. and Build. Mat., 23, 2009,
pp. 2291-2298.
[11] Wille K, Naaman AE, Parra-Montesinos GJ,“Ultra-highperformance
concretewithcompressive strength exceeding 150 MPa (22ksi): A simpler way”, ACI Mat. J. 108(1), 2011,
pp. 46-54.
[12] Kou SC, Xing F, “The effect of recycled glass
powder and rejected fly ash on the mechanicalproperties
offibre-reinforced
ultrahighperformance concrete” Adv. in Mat. Sci. andEng., Volume 2012, Article ID 263243, 2012, 8
pages.
[13] Scrivener KL, Kirkpatrick RJ, “Innovation in use
and research on cementitious material”, Cem.
And Conc. Res., 38(2), 2008, pp.128-136.
[14] ASTM C618-15, “Standard specification for coal
fly ash and raw or calcined natural pozzolan foruse in concrete”, Annual Book of ASTM
Standard, vol.04.02, 2015.

CONCLUSION
This study investigated experimental study oncompressive and flexural strength of fly ash based
geopolymer mortar mixed with recycled glass.
Recycled glass was used to partially replace fineaggregate at the amount of 0%, 25%, 50%, 75%, and100% by weight. The results showed thatcompressive and flexural strength decreased withincreasing of the amount of recycled glass
replacement. At 25% replacement, it was found to be
an optimal amount of recycled glass to provide 28day compressive strength slightly higher than control
specimens, 0% replacement, which is about 0.93%
and 4.2% for L/B =0.6 and 0.7, respectively. Withhigher than 25% sand replacement, the 28-daycompressive strength tended to decline with theincrease of amount of recycled glass in the mixtures.
Both compressive and flexural strength at the age of
28 days were higher than 7-day curing due to theincrease of degree of polymerization.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the financial
support from European Commission Research
Executive Agency, via a research grant (H2020MSCA-RISE-2015-689857).
REFERENCES[1] Jin W, Meyer C, Baxter S, “Glascrete-Concretewith glass aggregate”, ACI Structural J., 90(2),2000, pp. 208-213.
[2] Meyer C, Egosi N, Andela C, “Concrete with
waste glass as aggregate”, in Proc. of the Int.
Symp. in Recycl. and Reuse of Glass Cullet,
Conc. Tech. unit of ASCE and Univ. of Dundee,
Mar. 2001.
[3] Park SB, Lee BC, Kim JH, “Studies onmechanical properties of concrete containing
waste glass aggregate”, Cem. and Conc. Res.
34(12), 2004, pp. 181-2189.
[4] Shayan A, Xu A, “Value-added utilisation of398

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEMONSTRATION OF LINER INTEGRITY MONITORING SYSTEM
IN A GYPSUM WASTE CONTAINMENT
1

H.B. Ng1 and Y.Y. Zheng2
GSE Lining Technology Co. Ltd, Bangkok, Thailand; 2 CGSE Environmental Lining Technology (Suzhou)
Co. Ltd, Shanghai Branch Company, Shanghai China
ABSTRACT

Polyethylene geomembranes have been widely used as primary barriers in environmental containments for
decades. A good Construction Quality Assurance (CQA) plays an important role in producing a quality
containment. Conventional geomembrane CQA program focuses only on quality of welded seams throughtraditional destructive and non-destructive seam tests. To ensure the sealing integrity of the installed
geomembranes and long-term performance of the liner system, leak integrity surveys and monitoring are
implemented so as to serve as validation at post-construction and even when the facilities are in operation. A newgeneration leak location liner system has been developed to facilitate a comprehensive liner leak testing and longterm liner integrity monitoring. This paper presents a demonstration project carried out at a gypsum waste landfill
facility in southwest China. Field investigations performed by third party surveyors have successfully andaccurately located the blind holes placed by the local authority and owner of the facility. Results from the fieldtests demonstrated that the improved leak location liner system associated with permanent liner integrity
monitoring technology can further reduce the risk of loss of containments, potentially enhances the environmental
and economy sustainability of geomembrane lined facilities.
Keywords: CQA, Electrical Liner Integrity Survey, Leak Location Liner, Spark Test, Permanent Monitoring.
system in the final design of the site expansion.
A demonstration project consisting of apreliminary test pad was built on an existing
phosphate gypsum stack at the facility in October
2015. The preliminary test pad was lined with highdensity polyethylene leak location liner (also known
as electrically conductive geomembrane) as theprimary barrier. After installation, an electricallyspark testing was performed on installed liners at site
to inspect for post-installation mechanical damage. A
permanent Liner Integrity Monitoring System(LIMS) was conducted after the lined test pad has
been covered with water, following with an Electrical
Liner Integrity Survey (ELIS) performed on the test
pad after covered with gypsum waste.

INTRODUCTION
Phosphate gypsum, a waste containing calcium
sulfate generated during the production ofphosphorus fertilizer, should be properly contained
due to environmental concerns. A large fertilizer(phosphate gypsum) processing operation located at
Guizhou province, Southwest China was selected inthis study. It has several large canyon gypsum stackdisposal sites with an average height of nearly 100
meters in the mountainous region. The waste disposalsites are lined with HDPE geomembranes and havebeen operating for almost 10 years.
Today, Guizhou is the only provinces in Mainland
China that requires a compulsory engineered
geomembrane lining system for general industrial
solid waste disposal facilities. This has been imposedby the provincial criteria (DB52/865-2013)
particularly due to the local karst geological features,
where seepage and ground water contamination inthis area could be much difficult to detect andremedy. The existing storage capacity that contains
gypsum stack is expected to reach its capacity andhence plans are underway to build vertical expansions
that combine two existing gypsum stacks, howeverleak prevention is a challenge to the design engineers
in this particular site condition. It was then decided toconstruct a test pad to demonstrate the current best
available technology and to acquire necessary
engineering parameters for inclusion of this liner

GEOMEMBRANE PERFORMANCE AND
ELECTRICAL LINER INTEGRITY SURVEYS
Polyethylene geomembranes have been widelyused as primary barriers in environmental
containments for many decades. Many reports
revealed that well-stabilized HDPE geomembranes
are able to perform satisfactorily for decades if they
are protected from mechanical aggressions. A proper
geomembrane
installation
andassociatedconstruction quality assurance (CQA) is crucial to thelong-term performance of lining system. Many casestudies demonstrated that a well-planned and wellexecuted CQA produces a high quality containment
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

system; on the contrary, geomembrane will lose partsor all of its functions due to poor CQA. The leakage
analysis shows that high quality liner installation
associated with a complete CQA program reduces
liquid losses by 92% at different hydraulic heads overthat of poor installation without an effective CQA
program. In addition, an important note regarding
geomembrane liners with “low quality” installations:data and in-house surveys suggest that over 30% ofsuch systems experience a failure that requires either
a substantial reconstruction or complete replacementof the system (Beck et al., 2009).
Traditional geomembrane CQA program focuses
only on weld quality through field destructive andnon-destructive tests. To ensure the sealing integrityof installed geomembranes, field monitoring and leakintegrity tests are required to serve as verification
during and after construction, and even when thefacilities are in operation. A case study of a landfill in
Victoria, Australia indicated that 57 holes and 350
dimples were found on the installed HDPE
geomembrane through electrical survey at postinstallation even though a strict construction quality
assurance program was executed (Bogoda et al. 2014).
Survey data on occurrence of liner defects reveals
that 24% of total amount comes from preliminary
construction phase (geomembrane deployment, seam
welding, etc.), 73% is related to final construction
phase (backfill on geomembrane), defects occurrenceat post-construction, early operational phase only
takes 2% (Nosko et al., 1996). Figures 1 and 2 areclassic examples of such defects. In addition,
traditional CQA program is only examining the liner
quality during preliminary construction phase. Thesestatistical data clearly indicates that in order to ensure
the liner integrity and long-term performance, it isessential to carry out electrical liner integrity survey(ELIS) on the entire installed geomembrane.
Electrically spark testing on exposed geomembrane(ASTM D7240) and dipole survey on covered
geomembrane (ASTM D7007) are proventechnologies for such surveys performed at the final
construction stage. Leak location liner featuring a
conductive backing is the geomembrane product thathas been tested and verified to be able to enhance theefficiency and accuracy of ELIS.

Fig. 1

Fig. 2

Liner damage caused by large aggregate.

Today, through combination of leak location linerand combi-modules, the system allows permanentleak monitoring of containments. The following
section of this paper illustrates in details theapplication of ELIS and LIMS technologies in field
and the results obtained from the demonstration.
DEMONSTRATION PROJECT
Test Pad Preparation
A test pad of 30m x 30m was constructed above
an existing gypsum stack. The test pad was preparedwith depth of about 30cm and side slope gradient of
4H: 1V. A 60cm deep trench was also constructed toanchor the geomembrane around the peripheral of test
pad. The subgrade was properly compacted andlevelling before receiving the geomembrane. Figure 3
shows the cross section of the test pad and Fig. 4 is an
overview of the prepared test pad.

A defect caused by welding process.
400

Fig. 3

Test pad cross section

Fig. 4

An overview of the compacted test pad.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

2.

Geomembrane Liner Installation
A 2.0mm thick white-surfaced leak location liner
was directly deployed on the well-prepared subgrade
foundation. Leak location liner has a thin integrated
conductive layer at the bottom surface that is installedfacing down. An ohmmeter can be used to check andensure the connectivity of the conductive layer at site.
The installation process of leak location liner is
identical with that of standard geomembrane
installation. Only few measures should be taken to
ensure the geomembrane have a well-connecting
electrically conductive bottom and a proper isolationof the dual track wedge welded conductive edges,
which are the key factors to the success of ELIS and
LIMS. These include:
1. Use ISOlation-Wedge (Iso-Wedge) for welding
the leak location liner. The Iso-Wedge is an
improved fusion wedge that breaks the
conductivity of the exposed flap from the rest of
the sheet at the welded seams to avoid false
positive signals when performing ELIS. The
installer just have to replace the standard wedge
with Iso-Wedge prior to seam welding andperform trial welding to verify that the IsoWedge functions as required (Figs. 5 to 7).

Fig. 5

Welded seam via conventional welder.

Fig. 6

Welded seam via Iso-wedge welder.

Place an extra piece of 1m x 1m leak location
liner at every 15 meters interval under thewelding seam with the conductive layer facing
up. This is to enhance the electrical connectivityof two adjacent panels (Figs. 8 and 9).

Fig. 8Extra piece insert and welding in progress.

Fig. 9Installed White Leak Location Liner.

Field Spark Testing
Leak location liner is an HDPE geomembrane thatincorporates an electrically conductive layer and canbe utilized for post-installation inspection, i.e., spark
testing per ASTM D7240. To perform spark testing,a high electrical voltage of negative polarity(neoprene pad) is applied to the membrane sheet to betested, and an electrode of positive polarity (testwand) is then passed over the geomembrane. Fig. 10shows the spark testing on installed geomembrane atsite. Spark testing on the entire geomembrane surface
was completed within few hours. Few damages
caused during installation were found and patched.

Fig. 7 Trial welding via Iso-wedge welder (left)
and check conductivity at weld flap (right).
Fig. 10 Field spark testing on installed liner.
401

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Permanent Liner Integrity Monitoring

In the early field test that was performed to
discover the synergies between the leak location linerand combi-module, it was found that when a hole wasdrilled on the liner, an electrical circuit between theenergy source and sensor was formed, and the combimodule closest to the hole received the mostsignificant levels of energy. It was concluded that the
conductive layer of leak location liner, independent
from the subgrade soil conductivity, provides“electrical super highway” to the generated current,
geomembrane welds does no effect on the survey data,
and data is complete reproducible (Weiss et al., 2014).
In this demonstration test pad, three combimodules were designed and integrated into theinstalled leak location liner. Leak as tiny as 1 mm2,that falls within the triangle area formed by the threecombi-modules can be pinpointed. After the
installation of leak location liner and combi-modules,
and the set -up, calibrations of the central computer
unit, a background state was established first. As
shown in Fig. 13, the site was then flooded with acidwater to a depth of 10-25 centimeters, and a local
EPA officer was invited to create a hole of about 1.5
centimeters in diameter through the liner with theabsence of all surveyors. The central computer unit
responds swiftly within less than 30 seconds after thehole is drilled, receiving data from the three combimodules to assist in locating the “blind” hole. Fromthe measured data and the subsequent data analysis,
the system detected the location of the blind hole withan estimated accuracy within a 1-meter diameter.
This calculated location was compared with the actual
measured location and was found varied by about 68
centimeters (See Fig. 14).

By integrating combi-modules into Leak Location
Liner as shown in Fig. 11, field tests havedemonstrated that this advanced technology iscapable of performing continuous monitoring andpermanent quality control of geomembrane liners
during the operation of the facility, which is thehighlight of this demonstration project.

Fig. 11 Combi-Module embedded in Leak location
liner.
Combi-module is an electronic device that acts
both as energy source and as sensor. It is a rare metal
plate and encapsulated into a HDPE casing, thus is
expected to last as long as the geomembrane. The
combi-module is embedded in the liner, for doing so,
a hole that is slightly smaller than the combi-module
is cut off in the membrane sheet and the sensor’s
flange is inserted and fixed by extrusion welding
along the edge. As shown in Fig. 12, an integrated
cable wire is assembled above the liner and connectedwith the central monitoring unit placed next to the testpad (normally indoor environment). The plugged-in
central computer unit is responsible for collecting andanalyzing data from the combi-modules located at
different positions, supplying power and activates
them.

Fig. 13 Lined test pad flooded with acid water.
The amount and layout of combi-modules
designed for leak monitoring depend on the site
geometry and the required detection accuracy. Whenusing leak location liner, the area monitored by one
combi-module is able to cover up to 3,000m2, which
will provide a substantial reduction in numbers ofcombi-modules used for the leak monitoring andhence allowing a more cost-effective solution.

Fig. 12 Installed combi-module with cable wire.
402

GEOMATE - Mie, Japan, Nov. 21-24, 2017

pond, a hole that is located at the peak of a wrinkle in
the liner is unlikely to be detected by ELIS on the
traditional liner because the electrical connection isbroken by the lack of intimate contact between thehole and the subgrade soil. In addition, in cases where
there is a dry subgrade or encapsulated geosynthetic
clay liner (GCL), the material beneath thenonconductive traditional liner may not be
sufficiently conductive to perform the leak survey(Peggs I., 2007). However, when using leak location
liner, the conductive layer in the geomembrane willserve as the conductive medium at the base ofgeomembrane and the aforementioned issues are nolonger the concerns (H.B. Ng et al., 2013)
At the demonstration test pad, a dipole test
(quadrupole) was conducted by a third party surveyor
after the local EPA personnel placed two “blind”
holes and test pad was filled up with 30cm thickgypsum. Figure 15 shows the leak survey was inprogress. The survey took almost 1.5 hours tocomplete and managed to identify leaks that wereintentionally placed. One of the holes, nearer to thecenter of the site than the other was very accurately
located to a distance of just a few centimeters. The
other leak was closer to the edge of the liner andbecause of some edge distortion effects the accuracy
was not quite as good, but still within a 20 to 30
centimeter radius. Figure 16 is the dipole test electric
potential diagram with two leaks being detected.

Fig. 14 Leak monitoring results.
Electrical Liner Integrity Survey (ELIS)
With the improvement of installation techniques,
today Leak Location Liner also enables ELIS to beeffectively performed over entire geomembrane andeven with shallow cover soils or water. ELIS asdetailed in ASTM D7007 are performed using theconcept that if there is a sufficiently conductive
medium both above (cover material) and below(subgrade soil or a conductive geomembrane layer)
an insulating barrier (geomembrane) and each ofthese conductive mediums are oppositely electricallycharged, electric current will flow towards andthrough any location where the integrity of theinsulating barrier has been compromised. This current
flow can then be detected using equipment thatmeasures voltage drop between two measuring points.
By taking these voltage drop measurements in apredetermined grid on the cover soil, holes can be
pinpointed by finding locations where the current
reverses direction (Ramsey B. et al., 2012).
To perform leak survey on a conventional nonconductive geomembrane, the conductive mediums
must be in intimate contact with the geomembrane sothat an electrical connection can be made through any
holes in the geomembrane. For single-lined systemusing nonconductive traditional liner, an electricalliner integrity survey can only be performed
successfully provided that the liner is in intimatecontact with the subgrade soil that maintains
sufficient natural moisture content. However, in mostof the applications, that is not always a guaranteed
condition to perform an electrical liner integrity
survey on traditional geomembrane liner. In addition,
covered ELIS cannot be performed easily on a double
lined pond where the primary geomembrane liner isseparated from the conductive subgrade by a geonet
and a secondary liner. Similarly, even in a single lined

Fig. 15 Dipole (quadrupole) test in progressFig. 16 Dipole test electric potential diagram.
403

GEOMATE - Mie, Japan, Nov. 21-24, 2017[2] ASTM D7240, “Standard Practice for Leak
Location using Geomembranes with an
Insulating Layer in Intimate Contact with a
Conductive Layer via Electrical CapacitanceTechnique (Conductive Geomembrane Spark
Test)”, American Society for Testing andMaterials, West Conshohocken, PA., USA.
[3] Beck A., Smith M. and Sample K., “Design
considerations for the use of the geomembranes
for phosphate tailing impoundments”, 3rdInternational Conference on the Valorization of
Phosphates and Phosphorus Compounds(COVAPHOS III), Marrakech, Morocco, 2009.
[4] Bogoda K. and Bouazza A., “Case study of ageomembrane liner damages in a new landfill
cell located in Melbourne, Australia”, 10th
International Conference on Geosynthetics,
Berlin, Germany, 2014.
[5] DB52/865-2013, “Standard for Pollution Control
on the Storage and Disposal Site for GeneralIndustrial Solid Wastes in Guizhou Province”,
Guizhou Environment Protection Agency &Quality and Technical Supervision Bureau of
Guizhou Province, Guizhou, China.
[6] H.B. Ng, D. Gallagher and A. Beck, “Electrically
Conductive Geomembrane Enhances Liner Leak
Detection Surveys at Post Installation”, Third
International Conference on Geotechnique,
Construction Materials and Environment(GEOMATE 2013), Nagoya, Japan, Nov. 13-15,
2013, ISBN: 978-4-9905958-2-1 C3051.
[7] Nosko V., Andrezal T., Gregor T. and Ganier P.,“SENSOR damage detection systems (DDS) –The unique geomembrane testing method,
Geosynthetics: Applications, Design andConstruction”, Proceedings of the First
European Geosynthetics Conference, EuroGeo1,
1996, pp. 743-748.
[8] Peggs I., “Liner integrity/leak-location survey:
The significance of boundary conditions”,
Geosynthetics, Feb-Mar 2007, pp. 34-38.
[9] Ramsey B.J., J., Youngblood J, Gallagher D. and
Peggs I., “New electrically conductive
geomembrane for post installation liner integrity
surveys”, Proc. Of the 5th European
Geosynthetics Conference, Valencia, Spain,
September 16-19, 2012, Volume 2, pp. 251-256.
[10] Weiss B., Geutebrück E., “Next Generation Leak
Location in HDPE Liners in Landfills and Other
Facilities of Environmental Risk”, 10th
International Conference on Geosynthetics,
Berlin, Germany, 2014.

SUMMARY AND CONCLUSION
A series of geomembrane leak tests has beensuccessfully demonstrated at a phosphate gypsum
stack in Southwest China. Leak testing was essential
at different construction stages, from the initial
deployment to the final construction and operation
phases. Completion of the field performance tests inthis demonstration project has demonstrated theability of electrically conductive geomembrane (Leak
Location Liner) to be used to facilitate an ELIS andpermanent LIMS. Few defects on the geomembrane
were located accurately, both intentionally placeddamage and other damages during construction.
Local EPA officers, project owner and design
engineers are satisfied with the outcome of the fielddemonstration, which provides them a complete
solution for the leak prevention at their future gypsum
stack projects located at the karst topography
landscape. Parameters and methodologies obtained
from the demonstration project will be served as areference for future design and construction ofenvironmental containments in the region.
New generation leak location liner system,
characterized by the modified welding andinstallation techniques, facilitates a comprehensive
liner integrity tests, inclusive of spark testing on
exposed Leak Location Liner, dipole test to be
performed after the geomembrane is covered withshallow soils or water, permanent liner integrity
monitoring at post-installation and even during theoperation of the facility. The new generation leaklocation liner system has been successfully tested andverified as a reliable and effective technology thatsignificantly enhances the quality of liner leak testing
and to ensure a safeguard engineering containment
system that potentially improves environmental andeconomy sustainability of geomembrane lined
facilities.
ACKNOWLEDGEMENTS
The authors wish to express their greatest
appreciation to Dr. Liu N. of Shanghai Jiaotong
University, China; Dr. Geutebrück E of Texplor
GmbH; Mr. Yuan Z. and Mr. Guo J. of Shenzhen
Shengyi Environmental Co., Ltd. for their support
and contribution in this paper.
REFERENCES[1] ASTM D7007, “Standard Practices for Electrical
Methods for Locating Leaks in Geomembranes
Covered with Water or Earth Materials”,
American Society for Testing and Materials,
West Conshohocken, PA., USA.

404

SeventhInternational Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE USE OF STEEL FIBER EXTRACTED FROM WASTE TYRE AS
REINFORCEMENT IN CONCRETE CONTAINING RICE HUSK ASH
1Fauzan1, Febrin Anas Ismail2, Rio Sandi 3 And Claudia Lovina A N4Engineering Faculty, University of Andalas, Padang City; 2West Sumatera, 3Indonesia
ABSTRACTThe generation and disposal of waste are inherent to life itself and have presented very serious problems to
the human community. Waste tyre is one of disposal problem, especially in Indonesia, more than 50 billion
waste tyre was generated per year. 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
rice husk ash (RHA) 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 of cylindrical specimen of steel fibers extracted from waste
tyre (SFEFWT) with addition of 0%, 0.25%, 0.5%, 0.75%, 1% and RHA with addition 15% by cement weigth
was used in concrete mix to fabricated and tested. The mechanical properties, compressive strength, flexuralstrength and tensile strength at 28th day age were studied for concrete prepared. The result show thatcompressive, flexural and tensile strength was positively affected by the additions of SFEFWT on concrete
containing RHA.
Keywords: Concrete; Steel Fiber; Waste Tyre; RHA; Compressive Strength; Flexural Strength; Tensile Strength.
inclusion of hooked steel fibers with cut length of 6
cm and aspect ratio of 80 and replacement of cementwith 0.5%, and 1% improved the mechanicalproperties of concrete [2]. The inclusion of steel
fibers in concrete considerably enhanced theengineering properties of mortar and concrete [3].
The addition of fibers to concrete considerably
improves its structural characteristics such as static
flexural strength, impact strength, tensile strength,
ductility and flexural toughness [4]. The results ofultrasonic pulse velocity revealed that the using of
small percentage of steel fiber in concrete improved
the quality of concrete [5]. Recent study shows thatthe utilization of by-products such as fly ash andother materials for example, sawdust and glass
powder is frequently used in recent research insteadof rice husk ash (RHA). It was found that RHA
which is high in silica content can become potential
cement replacement material Turgut and Murat
Algin [6]. RHA is a consequence of the cultivatedindustry which contains great amount of silicon
dioxide (SiO2). Ephraim et al [7] conclude that useof Rice husk ash in construction works will decrease
the environmental pollution, strengthen the concrete
quality and optimize the cost of concrete as well as
resolving the problem of agricultural waste
management. Khassaf et al [8] determine thatworkability of fresh concrete fall with the increaseof RHA content. Rice Husk Ash concrete gives adurable and good structural concrete for both shortterm and long term considerations [9]. In this study,
the effect of steel fiber extracted from waste tyre on
concrete containing rice husk ash was investigated.

I. INTRODUCTION
Concrete is the most frequently used construction
material in the world. However, it has low tensile
strength, low ductility, and low energy absorption.
An intrinsic cause of the deficient tensile behaviourof concrete is its low toughness and the presence ofmentioned defects. Therefore, improving concrete
toughness and reducing the size and amount ofdefects in concrete would lead to better concrete
performance. An effective way to improve thetoughness of concrete is the addiction of a relatively
small fraction (usually 0.5–2.0% by volume) ofshort fibres to the concrete during mixing. Recent
research is showing that adding to cement basedmaterials recycled steel fibres (RSF) from wasted
tires can decrease significantly the brittle behaviourof these materials, by improving its toughness andpost-cracking resistance. The fibers such as steel,glass, polymeric, natural and plastic fibers mixed
with concrete at particular cut length and specified
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. Using a little
percentage of steel fibers efficiently improve theload-carrying capability of slabs on ground andsignificantly improve the slab ductility [1]. With the405

GEOMATE-Mie, Japan, Nov. 21-24, 2017

II. Materials and Method
II.1 Materials Used
II.1.1 Cement
Ordinary Portland Cement (OPC) commonly
available in market was used.
II.1.2 Fine and Coarse Aggregate
Locally available aggregates were used; fineaggregate with size retained on 200 number sieveand passing from 4.75 mm. The specific gravity andfineness modulus of fine aggregate was 2.57
respectively. The coarse aggregate used was locallyavailable quarry having two different sizes; one
fraction is passing through 20 mm sieve and anotherfraction passing through 10 mm sieve. The specificgravity of 20 mm and 10 mm aggregates are 2.70
and 2.60 respectively.

Figure 2.

Cutting Process From Waste Tyre to
Obtained Steel Fiber Extracted

II.1.3 Water
Potablepreparation.

tape

water

was

used

in

mix

II.1.4 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(Figure 1 and Figure 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
in different proportions from (0-1%) with incrementof 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.

Figure 3. Steel Fiber Extracted From Waste Tyre

Figure 4. Steel Fiber in 1 Inch Cut Length

II.1.5 Rice Husk Ash
RHA is a consequence of the cultivatedindustry which contains great amount of silicon
dioxide (SiO2). RHA contains about 75 percent oforganic content and the remaining 25 percent ofhusk is transformed into ash during the burning
process, is identified as rice husk ash. RHA obtained
from rice sheller in Padang. The specific gravity of
RHA was 2.30. The chemical composition of RHA
was tested at Indarung II, Padang Cement Factory
Indonesia and the results is given in Table 1. Figure
4 shows the Rice Husk Ash material.

Figure 1. Waste Tyre

406

GEOMATE-Mie, Japan, Nov. 21-24, 2017

Cement was replaced with rice husk ash byweight. 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 1. Chemical Composition of Rice Husk Ash

ChemicalComposition

Formulae(%)
Content

SiO2

90.13

Al2O3

1.88

Fe2O3
CaO

0.89
0.23

MgO

0.87

K2O
LOI

2.55
2.65

Silicon Dioxide
Aluminium
Trioxide
Iron Oxide
Lime
Magnesium
Oxide
Potassium Oxide
Loss of Ignition

II.2.2 Casting of Specimens
Total 27 cylinders were casted, forcompressive, tensile and flexural strength test.
Cylindrical specimens of length 300 mm anddiameter 150 mm and beam specimens of length
500 mm, wide 100 mm, high 100 mm casted with
0%, 0.25%, 0.5%, 0.75% and 1% with used waste
tyre steel fibers extracted in Concrete containing ricehusk ash addition 15% by weight of cement.
II.2.3 Testing of Specimens
Compressive, splitting tensile and flexuralstrength tests were conducted on cylindrical
specimens and beam specimens using Universal
testing machine (UTM) and Flexural test in theconcrete laboratory of PT. Semen Padang as per SNI
1974:2011, ASTM C 496-86 and ASTM C 293-08.
Figures 6, 7 and 8 show the specimens undercompressive, splitting tensile and flexural testing in
the laboratory.

Figure 5. Rice Husk Ash

II.2 Experimental Program
II.2.1 Mix Proportions of Concrete
The concrete mix is designed as Indonesian
Nasional Standar (SNI) for the normal concrete.
M35 grade of concrete is used to examine themechanical properties of concrete with 0.52 water cement ratio. Five mixture proportions were made.
First was control mix (with RHA, without steel
fiber), and the other four mixes is steel fiber withpercentage of 0.25%, 0.5%, 0.75%, 1% contained
rice husk ash.
Table 2. Mix Proportions

332.
35

SF
0.5
0%
332
.35

SF
0.75
%
332.
35

332.
35

205

205

205

205

205

205

725.
6
108
8.4

725.
6
108
8.4

725.
6
108
8.4

725
.6
108
8.4

725.
6
108
8.4

725.
6
108
8.4

-

-

0.97
6

1.9
55

2.93
3

3.91
0

-

58.5
60

58.5
60

58.
560

58.5
60

58.5
60

C

Cement(kg/m3)Water(kg/m3)
F.A.
(kg/m3)C.A.
(kg/m3)
SFEFW
T(kg/m3)RHA(kg/m3)

391

SF
0%

Figure 6. Compressive Test on Cylindrical

SF
1%

SF
0.25
%
332.
35

SampelID

Figure 7. Splitting Tensile Test on Cylindrical407

GEOMATE-Mie, Japan, Nov. 21-24, 2017

III.2 Splitting Tensile Strength
The results of the tests for splitting tensile
strength performed on the samples are shown in
Table 4.
Table 4. 28 Days Splitting Tensile Strengthof Cylinder Specimen

Figure 8. Flexural Test on BeamIII. RESULT AND DISCUSSION
III.1 Compressive Strength
The results of the tests for compressive strength
performed on the samples are shown in Table 3.

No.

(SFEFWT)
Content
(%)

1
2
3
4
5

0
0.25
0.50
0.75
1.00

SplittingTensileStrength(N/mm2)
2.76
2.83
2.93
2.98
3.35

*SFEFWT : Steel Fiber Extracted From Waste Tyre

The Splitting tensile strength in concrete
containing rice husk ash mixes made with SFEFWT
was determined at 28 days. The results presented inTable 4, Figure 7 and Figure 10, that the splitting
tensile strength of concrete reinforced containing
rice husk ash with SFEFWT increases with theincrease of SFEFWT content. As can be seen from
Table 4, the maximum 21% increase i.e. 3.35
N/mm2 by addition of 1.0% SFEFWT on RHA
concrete.

Table 3. 28 Days Compressive Strength of
Cylinder Specimen
Rice Husk(SFEFWT)
Compressi
AshNo.
Content
ve Strength
Content(%)(N/mm2)
(%)
1
0
15
32.60
2
0.25
15
33.40
3
0.50
15
34.40
4
0.75
15
35.30
5
1.00
15
36.20

3.5
Splitting Tensile Strength(N/mm2)*SFEFWT : Steel Fiber Extracted From Waste Tyre

The results presented in Table 3, Figure 6 andFigure 9, that the compressive strength of concrete
reinforced containing rice husk ash with percentagesof SFEFWT slightly increases from 0% to 0.5%,
0.75% and 1% after 28 days. The maximum 11%
increase i.e. 36.20 N/mm2 as compared to without
SFEFWT concrete; at addition of 1.0% SFEFWT.
37
Compressive Strength(N/mm2)

Rice Husk
Ash
Content
(%)
15
15
15
15
15

3

2.5

2

36

0

0.25

0.5

0.75

1

35
SFEFWT (%)

34
33
32

Figure 10. Avarage Splitting Tensile Strength of
Ordinary And SFEFWT RHA Concrete

00.25 0.5 0.75
SFEFWT (%)

1
III.3 Flexural Strength
The results of the indirect flexural strength tests
performed on the samples are shown in Table 5.

Figure 9. Avarage Compressive Strength of
Ordinary and SFEFWT RHA Concrete408

GEOMATE-Mie, Japan, Nov. 21-24, 2017Table 5. 28 Days Indirect Flexural Strengthof Cylindrical Specimen
Rice Husk(SFEFWT)
Flexural
Ash
No.
Content
Strength
Content(%)(N/mm2)
(%)
1
0
15
5.30
2
0.25
15
5.66
3
0.50
15
5.78
4
0.75
15
5.89
5
1.00
15
6.00





*SFEFWT : Steel Fiber Extracted From Waste Tyre

The results of flexural strength of concrete
containing rice husk ash mixes made with SFEFWT
measured at 28 days are given in Table 5, Figure 8
and Figure 11. Test results indicate that the flexuralstrength increases as the percentage of the SFEFWT
from 0% to 0.5%, 0.75% and 1%. The maximum
flexural strength in concrete containing rice husk ashwith the addition of 1.0% of SFEFWT is 6.00
N/mm2, which is 13% increment as compared toconventional concrete.

At all the concrete investigated, themaximum of compressive strength 11%
increase i.e. 36.20 N/mm2 as comparedto without SFEFWT concrete; ataddition of 1.0% SFEFWT in Concrete
containing rice husk ash.
For splitting tensile strength, themaximum 21% increase i.e. 3.35
N/mm2 was observed at addition of
1.0% SFEFWT as compared to without
SFEFWT concrete.
The maximum flexural strength with theaddition of 1.0% of SFEFWT
containing rice husk ash is 6.00 N/mm2,
which is 13% increment as compared toconventional concrete.

ACKNOWLEDGEMENTS
The authors wish to acknowledge the staffs of
the Laboratory ofMaterial and Structure in
University of Andalas and the Laboratory ofConcrete in Padang Cement Factory for their support.
REFERENCES

Flexural Strength(N/mm2)

6[1] 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)[2] 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)[3] 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)[4] 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.
[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] P. Turgut, H. Murat Algin, Limestone Dust and

5.5

5

4.5

0

0.25

0.5

0.75

1

SFEFWT (%)

Figure 11. Avarage Flexural Strength of Ordinary
and SFEFWT RHA Concrete

IV. CONCLUSION
The following conclusions could be arrived atfrom the study: Compressive strength, Splitting tensile
strength and Flexural strength of steel
fiber extracted from waste tyre
(SFEFWT) in Concrete containing ricehusk ash concrete specimens werestronger than the plan concrete (controlmix) specimens at all the percentage.

Wood Sawdust as Brick Material, Building andEnvironment, 42, 3399-3403 (2007).

[7] Ephraim M, Akeke GA, Ukpata JO.
Compressive strength of concrete with RHA as
partial replacement of ordinary Portland
cement. Scholarly Journal of Engineering
Research. 2012; 1(2):32–6.

409

GEOMATE-Mie, Japan, Nov. 21-24, 2017[8] Khassaf SI, Jasim AT, Mahdi FK. Investigationon the properties of concrete containing ricehusk ash to reduction the seepage in canals.
International Journal of Scientific Technology
Research. 2014; 3:348–54.
[9] Akeke GA, Ephraim M, Akobo IZS, Ukpata JO.
Structural properties of rice husk ash concrete.
International Journal of Advances inEngineering
Sciences
andAppliedMathematics. 2013; 3(2):8269.

410

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

AN INVESTIGATION ON THE STRENGTH OF
AXIALLY LOADED COLD-FORMED STEEL Z-SECTIONS
1,2James Matthew L. De Jesus1 and Bernardo A. Lejano2
Gokongwei College of Engineering, De La Salle University, Philippines
ABSTRACT

Cold-formed steel (CFS) provides high strength-to-weight ratios that prove efficient in the construction ofsteel structures. CFS Z-section members exhibit buckling failures that may be difficult to predict due tocomplexity in geometry. There exists a gap in experimental and computational studies done in the Philippines
regarding the structural performance of locally-produced CFS members. The objective of this study is toinvestigate the load-carrying capacity of Z-section CFS members when subjected to axial compression using
experimental and computational methods. The study considers a total of 180 member samples with one section
shape, six different lengths and six different thicknesses. Experimentally, the CFS members were subjected tocompression loads using a standing steel frame with a hydraulic jack, a load cell and 4 displacement transducers
to record the parameters needed for the investigation. High-speed video recordings were used to verify thedifferent failure modes. These are then compared to computational results as per the National Structural Code of
the Philippines (NSCP). Furthermore, the study also provides a comparison of experimental and computational
results with Finite Element Method (FEM) using ANSYS. The main failure modes were torsional-flexural anddistortional buckling. Torsional-flexural buckling was observed in 74.01% of the samples. Although 72.88% of
the failure modes were predicted correctly, it was found that the provisions in the NSCP in predicting thestrength of the member were relatively high with respect to the experimental and FEM results. This means thatthe predicted strength was non-conservative. It was also found that a modification factor of 0.52 can be used toachieve similar results between the predicted and actual strength of the member.
Keywords: Cold-formed Steel, Compression Members, Buckling Failures, Z-section
Philippines [3]. The provisions in the Code areassumed to be correct and safe. Confidence in safety
is achieved when the provisions in the Code arereligiously followed. However, the design provisionsof Z-section CFS have not been fully verified in thefield. Experimental tests are needed to confirm theaccuracy of its design. In axial compression, Zsection CFS can be unstable in different failuremodes such as local, distortional and flexural or
torsional-flexural buckling [4].
For reference, the typical cross-section of a Cold
Form Steel Z-section is shown in Fig. 1.

INTRODUCTION
The gap of experimental studies done in thePhilippines for CFS may be overlooked by structuraldesigners. The National Structural Code of thePhilippines or NSCP (which will also be referred as
the Code) stipulates design procedures based on
foreign experiments and standards in the applicationof CFS members in the construction of various typesof structures. The use of thinner sections and higher
yield strengths can lead to structural design
problems [1], [2]. These are due to its complexitythat is not routinely encountered by most structural
engineers. To allow for safety, the structure must be
closely studied in accordance with the Code or othermethods such as performance-based analysis.
Currently, there are design provisions for CFS
members in the NSCP that can be used by structuraldesigners. It has the capability of computing thecompressive strength of Z-section CFS. However,these provisions in the Code were based on design
standards formulated in other countries. Although
the steel used may be the same, the process of local
manufacturing may have slight variation that might
affect its performance.
Over the years, the NSCP has been regarded as
the sole basis of design of structures all over the

Fig. 1

Cross-section of Z-section CFS

The main objective of this study is to investigate
the load carrying-capacity of Z-shaped Cold Formed
411

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Steel when subjected to axial compression. The
specific objectives are: (1) to investigate thedifferent buckling modes; (2) to evaluate the axial
strength based on the Code and experimental tests;(3) to analyze using Finite Element Method (FEM);
and (4) to compare the predictions (Code and FEM)
with the experimental results.

measurements of the dimensions of the samples
were taken prior to test of each sample. The
measurements were taken using a digital caliper
measuring two flanges, two lips, web, thickness andoverall height. Each element of the cross-section
together with the thickness and length were
measured three times at approximately threeequidistant sections (e.g. top, middle & bottom). The
web height is nominally 100 mm. The flange widthis nominally 50 mm. The lip height is nominally 20
mm.
Material properties that were considered to affectthe strength and failure modes of the member are theyield strength, fy, and modulus of elasticity, E.
These material properties were determined using
ASTM E8: Standard Test Methods for Tension
Testing of Metallic Materials where strips of metal
were cut and tested from the sample population of Zsection CFS. These material properties together withthe dimensions parameters were used in determining
the nominal strength and effective dimensions of theweb, flange and lip elements.

METHODOLOGYThis study focused on experimental andcomputational
methodsofresearch.
Theexperimental method of this study is to conduct
compressive tests on Z-section cold-formed steel toacquire its strength and mode of failure. The
computational aspect of the study is done by using
the formulas recommended by the Code in
determining the strength and mode of failure of eachmember. The critical loads obtained fromexperiment and calculations are compared to verify
the reliability of the Code provisions. Furthermore,these critical loads were then compared to the resultsof ANSYS Finite Element Method (FEM) analysis.

Experimental test set-up

CFS Z-section specimens

The experimental set-up is illustrated in Fig. 2.
The member sample was placed with its transverse
axis at a 45-degree angle with respect to the plane of
the steel frame. This is to allow space for theplacement of the displacement transducer and toensure that the displacements in the web and flange
are recorded.

The shape of the section is in the form of a Z andis skew symmetric. The section size conform to thelimits for unrestrained Z-sections with simple lip
stiffeners stipulated in section 553.4 of the NSCP.
The Z-section is with a web and two flanges withsimple lip stiffeners as shown in Fig. 1. It is also
considered as a point-symmetric section. Based on
the availability in the market and to conform to thelimits, a 2” x 4” (50mm x 100mm) Z-section CFS
member was used in the experiment. That is, 2
inches for the flanges and 4 inches for the web. The
code adopted for each member sample type istabulated in Table 1. There were six thicknesses andsix lengths considered in the study. Each type has
five test samples, for a total of 180 member samples
considered in this study.
Table 1 Code used for the test member sample type
Code
1
2
3
4
5
6

Length
(mm)
800
1100
1400
1700
1800
2000

Code
A
B
C
D
E
F

Thickness
(mm)
0.80
1.00
1.20
1.40
1.50
1.80

The lengths of the members were based on theexperiment done before for C-sections [5]. The
thickness of the steel was also dependent on theavailable thickness that are commercially available.
To ensure that calculations were accurate, actual

Fig. 2
412

Experimental set-up

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The member samples were loaded axially incompression by the use of a hydraulic jack. The
loading was gradual for all samples. Load cell wasplaced right below the hydraulic jack to monitor theload that was applied. To simplify the calculation of
the axial force, the end conditions were designed tobe pin-supported, that is, the supports are not
restrained from twisting and bending [5]. To
simulate the pin-ended condition of the member,steel end caps were placed in both ends of themember with a 20mm diameter bearing ball attached
to provide a ball and socket mechanism for the
sample to rotate freely about its ends. The ball was
positioned so that the line of action of the force willpass through the centroid of the cross-section of thesample so that the members can be said to beconcentrically-loaded.
Two displacement transducers were placed inboth flanges to record the distortion. Anothertransducer was also placed in the web to record
flexural and/or torsional movement. These threetransducers were placed approximately at mid span.
Another transducer was placed at the bottom cap tomeasure the vertical displacement. Data loggers,
load cells and transducers were used to measure theexperimental data for strength, displacement anddeformation to provide accurate results. High-speed
cameras were also used to observe the governing
failure mode, which is the first buckling failure that
occurred. The load, element movements andlongitudinal movement were recorded using a datalogger which was able to record all four
displacements and the load applied to the member.

Fig. 3

Section buckling modes of failure

RESULTS AND DISCUSSION
The calculation of strength depends heavily on
the values of the yield strength and modulus ofelasticity of Galvanized Iron sheets or G.I. sheetsfrom where the Z-section CFS were made from. Test
results indicate an average yield strength obtained
was 306.04 which is a typical strength forgalvanized iron sheets. Furthermore, the average
modulus of elasticity from the test was 23.99 GPa.
Evaluation of strength through experiment
The compressive strengths of the Z-section CFS
were evaluated from the 180 samples with varying
thickness and length. These strengths will be termed
as “experimental strengths”. The experimental
strength of each sample was taken as the maximum
load recorded. The experimental strength results are
summarized in matrix form in Table 2. The firstcolumn and first row represents the thicknesses andlengths, respectively. Referring from Table 1, codes
A to F represent the thickness, while Codes 1 to 6
represents the length, both in ascending values.

Failure modes

Table 2

Evaluation of the failure modes is as importantas determining the strength. The modes of failure aremainly of yielding, torsional or torsional-flexural or
distortional buckling. The standing steel frame wasused with data loggers to determine the movementsof the member as it is loaded in compression. Local
buckling was usually encountered first. Even if local
buckling transpired, it was further loaded to see thebuckling mode that the member will exhibit. The
different modes of failure are illustrated in Fig. 3.
However, the figures just demonstrate the general
movements of the elements for each mode. The
movement of the elements can either be inward or
outward which makes the failure modes more
complex. Consequently, a forward or backward
movement can also transpire. Furthermore, there
exists a local-global interaction in buckling failuremodes such that multiple modes can be exhibited bya member sample [6].

Code
A
B
C
D
E
F

Experimental strength results (kN)
1
1.64
2.41
3.21
4.96
5.08
8.16

2
1.37
2.06
2.92
4.33
4.13
6.93

3
0.93
1.94
2.73
4.17
4.80
5.84

4
1.19
1.87
2.51
3.31
4.06
5.18

5
1.20
1.39
2.45
2.84
3.36
4.65

6
0.79
1.46
2.13
2.77
3.09
3.73

As seen in Table 2, the experimental strengths
were affected by the thickness and the length. The
thicker the member the higher the load it can carry.
The longer the member, the lower is the strength.
The length and thickness also influence thebuckling mode of failure. Thickness governs the
local buckling susceptibility of the individual
elements. The length influences the global bucklingsusceptibility of the member. The values in Table 2
provide a more analytic measure on how much bothparameters affect the strength of the member.
The observation of the failure modes was doneby identifying the movement both locally andglobally. Local, torsional-flexural, and distortional
413

GEOMATE - Mie, Japan, Nov. 21-24, 2017

buckling conditions were the main failure modes tobe identified. These failure modes can be identified
when similar failures are observed as those shown in
Fig. 3. As example, Fig. 4 shows torsional-flexural(TF) and distortional buckling (DB). Yielding is notexpected to be observed since the GI sheets used in
the member are very thin.

Evaluation of strength through FEM“FEM strengths” is the term used for the strengthof the members that were obtained using the FEM
analysis. There were three general steps indetermining the strength of a member. These are
generation of the model and setting up of theboundary conditions, solving the model andgathering and analyzing the results [7]. Prior to
analysis, an input for the modulus of elasticity, theyield strength, and density of 8027.28 kg/m3 were
inputted in the engineering data. The FEM results
are summarized in Table 4.
Table 4 FEM strength results (kN)

Fig. 4

Code
A
B
C
D
E
F

Failure due to torsional-flexural bucking(right) and distortional buckling (left)

Evaluation of strength through computation

2
4.88
6.53
6.97
8.57
9.25
10.90

3
4.03
4.79
5.57
6.55
7.04
7.97

4
3.29
4.01
4.74
5.33
5.72
6.53

5
3.13
3.90
4.42
4.91
5.15
6.20

3
0.78
1.25
2.38
3.74
4.51
7.37

4
0.76
1.47
2.55
3.89
4.83
7.52

5
0.82
1.58
2.50
3.64
4.57
7.08

6
0.71
1.58
2.42
3.76
4.41
6.09

Fig. 5 Cross-section of sample A1 failure using FEM

Table 3 Computational strength results (kN)
1
4.73
7.42
8.67
11.73
12.50
14.71

2
0.78
1.58
2.34
4.03
4.93
8.30

The goal of using FEM is to verify further the
results of the computational and experimental
strength evaluations. The strength was analyzed
using the Eigenvalue buckling analysis of ANSYS.
A unit axial load was used as the initial load. A
sample result of FEM is illustrated in Fig 5. The load
multiplier is the strength of sample A1 in Newtons.

The computations of the strength of themembers, termed as “computational strength”, weredone using the formulas and provisions stipulated in
the NSCP for the design strength of Cold-Formed
Steel compression members. These provisions are
summarized in NSCP Sections 552 and 553. The
Code considers three main failure modes for CFS Zsection members. These are yielding, torsionalflexuralanddistortional
buckling.
The
computational strength considered based on theprovisions of the code was taken as the lowest load
amongst the three failure modes. Although theyielding strength is generally unattainable, it was
still computed for comparison with the bucklingstrength. The computational strength results are
summarized in Table 3.
The same influence of thickness and length isobserved in the computational strength, that is: thelonger the length, the lower the strength; and thethicker the member, the higher the strength. As seenin Table 3, the shortest length of 800 mm and a
thickest GI sheet of 1.8 mm resulted to the largest
computational strength.

Code
A
B
C
D
E
F

1
0.63
1.54
2.12
3.88
4.57
7.89

Analysis of Strength Evaluation Results
6
2.77
3.46
3.93
4.42
4.69
5.70

The strength results are compared to one another,as shown in Fig. 6. The diagonal line is the equalityline that represents the points at which thecomputational strength is equal to the experimental
strength. Majority of the data points fall below theequality line, indicating over-estimate of thecomputational strength. The FEM/experimental
strength was also plotted and showed good414

GEOMATE - Mie, Japan, Nov. 21-24, 2017agreement between FEM and experimental
strengths. A linear regression was done to showslope for the best-fit line. The FEM strengths show
better fit with the experimental results because theR2 value (0.8379) is higher than the R2 value(0.7107) of the computational strengths. Moreover,
the y-intercept for the computational/experimental
strength plot is approximately equal to zero. Thismeans that a relatively direct relationship can bemade between the computational and experimental
strength, such that the slope of 0.52 can be used as afactor to make computational strength smaller so as
to become almost equal to the actual strength.

analysis using ANOVA was conducted. The p-value
for the computational and experimental strength wascomputed at 4.20x10-7 while that of the FEM andexperimental was at 0.67. The results indicate that
the FEM and experimental strength had no
significant difference while the computational
strength had significant difference from both theexperimental and FEM strength.
Table 5 Compressive strength results.
Code
A1
B1
C1
D1
E1
F1
A2
B2
C2
D2
E2
F2
A3
B3
C3
D3
E3
F3
A4
B4
C4
D4
E4
F4
A5
B5
C5
D5
E5
F5
A6
B6
C6
D6
E6
F6

Fig. 6 Comparison of strength results
A comparison between the modes of failures issummarized in Table 5 to check for similarities
between the computation and the experimental
failure modes. It was calculated that 72.88% of the
population are similar. Furthermore, Only 25.99% of
the population exhibited distortional buckling failure.
Torsional-flexural buckling was the most observed
failure, at 74.01%, probably because the Z-section isan open section making it very flexible and weak inresisting to torsion.
The strength ratio is also shown in Table 5. Only
the ratio of the experimental strength against thecomputational strength is shown due to limited
space. The values indicated is less than one
indicating that the Code does not provide
conservative strength predictions. The other strength
ratios were also calculated. The experimental against
computational strength ratio yielded an average of
0.50 while FEM against computational strength ratio
resulted to 0.54. The experimental and FEM agreed
well with an average strength ratio of 1.10.
The FEM results were also compared with thecomputational and experimental results to verify
further the reliability of the results. Statistical

Expt.
Mode
Fail.

TF
DB
TF
TF
TF
TF
TF
TF
TF
TF
TF
DB
TF
TF
TF
TF
TF
DB
DB
TF
DB
TF
DB
TF
TF
TF
TF
DB
TF
TF
TF
TF
TF
TF
TF
TF

Comp
Mode
Fail

DB
DB
DB
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF
TF

Ave.
Expt.

Ave.
Comp

Same
?

1.64
2.41
3.21
4.96
5.08
8.16
1.37
2.06
2.92
4.33
4.13
6.93
0.93
1.94
2.73
4.17
4.80
5.84
1.19
1.87
2.51
3.31
4.06
5.18
1.20
1.39
2.45
2.84
3.36
4.65
0.79
1.46
2.13
2.77
3.09
3.73

4.73
7.42
8.63
11.69
12.49
14.71
4.87
6.53
6.97
8.57
9.25
10.90
4.03
4.79
5.57
6.55
7.04
7.97
3.29
4.01
4.74
5.33
5.72
6.53
3.13
3.90
4.42
4.91
5.15
6.20
2.77
3.46
3.93
4.42
4.69
5.70

No
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
No
Yes
No
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes

Expt/
Compt
Ratio

0.35
0.33
0.37
0.42
0.41
0.55
0.28
0.32
0.42
0.51
0.45
0.64
0.23
0.41
0.49
0.64
0.68
0.73
0.36
0.47
0.53
0.62
0.71
0.79
0.38
0.36
0.55
0.58
0.65
0.75
0.28
0.42
0.54
0.63
0.66
0.66

To be able to use the formulas stipulated in the
Code that would lead to a safe design, a factor=0.52
must be applied to the computational strength. When
this factor is applied, the computational strength
would result to a “factored strength” that agrees wellwith experimental strength as illustrated in Fig. 7.
The solid line is the regression line after applying
the factor to the original computational strength. On
the other hand, the dotted line is the originalcomputational strength.

415

GEOMATE - Mie, Japan, Nov. 21-24, 2017

thank. Acknowledgement is due to De La Salle
University – Manila, Civil Engineering Department
for the BSMS program. ERDT is also appreciatedfor providing the scholarship to one of the authors
and for providing a research grant. The authors also
acknowledge those who helped in the whole
research process, especially in doing theexperimental tests.

EXPERIMENTAL STRENGTH (KN)

STRENGTH RESULTS
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0

COMPUTEDFACTOREDy = 1.0001x - 0.0616
R² = 0.7107

REFERENCES[1] Dubina D, Ungureanu V & Landolfo R, Designof Cold-Formed Steel Structures 1st Edition.
Berlin: European Convention for Constructional
Steelwork, 2012, ch. 4.
[2] Hancock GJ, “Cold-formed steel structures”,
Journal of Constructional Steel Research, Vol.
59, April 2003, pp. 473-487.
[3] Association of Structural Engineers of thePhilippines, Inc. (ASEP), National Structural
Code of the Philippines Volume 1, 6th Edition,
4th Printing. Philippines: Association of
Structural Engineers of the Philippines, Inc.
(ASEP), 2010, ch. 5[4] Rondal J, “Cold formed steel members andstructures: General Report”, Journal ofConstructional Steel Research, Vol. 55, 2000,
pp. 155-158.
[5] Yu A and Lejano B, “Investigation on theStrength of Cold-Formed Steel C-Section inCompression” in International Conference on
Advances on Civil, Structural, Environmental
and Bio-Technology CSEB 2014, Kuala
Lumpur, Malaysia, 2014.
[6] Batista E, “Local–global buckling interaction
procedures for the design of cold-formed
columns: Effective width and direct method
integrated approach”, Thin-Walled Structures,Vol. 47, April 2009, pp. 1218-1231.
[7] MacDonald M & Kulatunga M. “Finite Element
Analysis of Cold–Formed Steel Structural
Members with Performations Subjected toCompression Loading”, Mechanics andMechanical Engineering, Vol. 17, May 2013 pp.
127–139.

y = 0.5233x - 0.0616
R² = 0.7107
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
COMPUTED STRENGTH (KN)

Fig. 7 Strength results with factor = 0.52
CONCLUSION
The local-global interaction of the buckling
failure modes was dependent on the thickness andlength of the member. The strength increases as the
thickness increases. Consequently, it was found thatthe longer length contributed to the occurrence of
global buckling failures. But, smaller lengths exhibit
higher strengths.
The comparison of failure modes shows that72.88% of the experimental results consistently
agree with the computational results. It is concluded
that the dominant failure mode was torsionalflexural buckling since 74.01% of the samples
experienced this failure.
A comparison between the three strength
evaluation methods (experimental, computational,
and FEM) is done on the averages of the samples’
strengths. The predictions made using the Codeformulas were too high such that the average ratio
between the experimental and computed strength
was only 0.50. Thus it may be concluded that the useof the Code formula for this case (in its presentform) may be non-conservative. On the other hand,the average ratio between the experimental and FEM
results was 1.10 indicating good agreement.
A modification factor of 0.52 may be used bymultiplying it to strength obtained based on theCode. This is to achieve a relatively similar result
between the predicted strength and actual strength ofthe member. This may be done to allow for the useof the provisions of the Code without changing the
stipulated equations.
ACKNOWLEDGEMENTS
Throughout the duration of this study, there are
numerous people that the authors would like to416

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

INVESTIGATION OF THE EFFECTS OF DIFFERENT NATURALFIBERS ON THE STRENGTH OF COMPRESSED STABILIZEDEARTH BLOCKS (CSEB)
1,2

Kyle Solomon D. Pineda1 and Bernardo A. Lejano2
Gokongwei College of Engineering, De La Salle University, Philippines
ABSTRACTThis study investigates the most effective combination of natural fibers (namely coconut coir, abaca, andmaguey) used as reinforcement for Compressed Stabilized Earth Blocks (CSEB). Portland cement and 0.25%
fibers by weight were used to stabilize and reinforce CSEB, respectively. The blocks were made primarily with
Manila soil and were formed using hand-pressed machine. CSEB without fibers were first tested with varying
cement contents of 6%, 8%, 10%, and 12% by weight. This was examined to determine the practical cement
content (PCC). Three strength tests namely dry compressive strength, wet compressive strength, and flexuralstrength were conducted on CSEB at PCC with different fiber combinations of coir, abaca, and maguey fibers todetermine the mix producing maximum strength. The highest dry compressive strength was obtained with 100%maguey fiber; the highest wet compressive strength was obtained with 100% abaca fiber; while the highest
flexural strength was obtained with 17% coir fiber, 17% abaca fiber, and 67% maguey fiber. Using the Response
Surface Methodology (RSM), the maximum strengths were predicted as follows: 100% maguey for dry
compressive strength, 100% abaca for wet compressive strength, and 38.4% abaca and 61.6% maguey for
flexural strength. However, the optimal mix of CSEB for three the strength tests consists of CSEB with 42.5%
abaca and 57.5% maguey. The fibers were found to improve the performance of the block such as the strengthand post-crack behavior. Furthermore, the performances of a wall made of fiber-reinforced and unreinforced
CSEB were investigated. The test results showed a 33.79% increase in load carrying capacity of the fiberreinforced wall compared to unreinforced wall.
Keywords: Earth Blocks, Natural Fibers, Abaca, Coir, Maguey, Response Surface Methodology
soils to achieve immediate higher strength while
lime stabilization is used for clayey soils. Soil as abuilding material has its own advantages such ascost efficiency, virtually soundproof, non-toxic,
environmental friendly, durable, abundant, andthermal properties.
Compaction of moist soil, containing 4-20%
optimum moisture content (OMC) and often
combined with 3-8% cement stabilization by weightof soil, based on economic standard, cansignificantly improve compressive strength, water
resistance,
durability,
dimensional
stability,
resistance, and tolerances, in comparison withtraditional adobe blocks [1]. To further improve its
mechanical properties and, at the same time, reduce
waste, researchers are reinforcing it with natural
fibers as they show a significant result in post-peakload deformation behavior. The use of fiber
reinforcement into CSEB production creates a
network of fibers that prevents cracking of the soil
resulting from shrinkage and improves tensile andshearing strengths [2], [3]. The inclusion of fibers
into CSEB results to resistance towards higher
stresses by absorbing high amounts of energy,
making them particularly important in earthquake
prone regions [4].
The purpose of this study is to evaluate binding

INTRODUCTION
Agricultural wastes are thrown away every day
and if not properly managed, these wastes can havean impact on the general condition of theenvironment by degrading water quality andcontributing to the amounts of pollution that isalready present. By utilizing certain wastes such as
coconut coir fiber, abaca fiber, and maguey fiber,
will not only help protect the environment, but will
also help provide alternative housing materials forconstruction. Given the abundance of these
agricultural wastes in the Philippines, this drasticallyhelps the environment through recycling wastematerials and utilizing them for different
applications such as in construction.
Housing problem exists in both rural and urban
areas today; wherein both government and nongovernment agencies have undertaken measures toprovide solutions for this problem, one of which isproviding informal settlers with low-cost houses.
A building material that is often underestimatedbut has immense beneficial effects to society is thecompressed stabilized earth block (CSEB). This is a
type of construction block primarily made up of
mechanically compressed soil stabilized by cement
or lime. Cement stabilization is preferable for sandy
417

GEOMATE - Mie, Japan, Nov. 21-24, 2017

effects of coir, abaca, and maguey fiber; such asincreasing strength and improving post-crack
behavior. It is hypothesized that using these fibers
increase the mechanical properties. The resulting
strengths were also expected to vary depending on
the fibers used and the characteristics of the chosensoil. Knowing these can increase the efficiency of
CSEB usage. However, the long-term behavior anddurability of the fibers are not included in this study.
.
METHODOLOGY

There are three categories to classify CSEB based on
its strength and usage according to [8]. The strengths
shown in Table 3 are dry compressive strength, wetcompressive strength, and flexural strength.
Table 2 Compressive strength per cement content
CementContent (%)
6
8
10
12

The soil used was obtained from a construction
site in Recto, Manila. The soil sample used consistsof 2.5% gravel, 69.7% sand, 27.8% fine. With thisparticle distribution, the soil used was classified assilty sand with shell fragments. The maximum dry
density of the soil was 1,530 kg/m3 while thespecific gravity was 2.67. Cement stabilization isrecommended for soil with a plasticity index of 15%
or less [5]. Since the soil was found to havenegligible plasticity, cement was used. The OMC ofthe soil was determined to be 15.19%. Soil at OMC
is the recommended condition to produce the blocks.
For high strength blocks, additional quantity ofwater is needed. Therefore, a moisture content of
16% was used in the CSEB mixture.
The length of the fibers considered was based on
the studies of [6], [7], where 50-mm fibers wereused in the production of their CSEBs. The coirfibers were processed using dry mill while abaca
fibers were extracted by hand. Consequently,
maguey fibers were retted in the ocean.
Shown in Table 1 are the properties of the fibers
used in this study. The coir fiber has the lowest
tensile strength, though it is above the averagetensile strength of 75.5 N/g.m. set by Philippine
Fiber Industry Development Authority (PhilFIDA).
Abaca and maguey fibers have almost the same
tensile strength, which is relatively high compared tothe coir. Although coir fiber has the lowest tensile
strength, it has the highest capacity to elongate
which is about twice of the standard of PhilFIDA of
10.62%. On the other hand, both abaca and maguey
fiber exhibit low elongation.

Table 3 Classification based on strength [8]CSEB
Category I
Category II
Category III

Grade
CH-3
S2
MR-1

Tensile Strength
112.6 N/g.m.
215.9 N/g.m.
232.3 N/g.m.

Dry≥ 2 MPa≥ 4 MPa≥ 6 MPa

Wet≥ 1 MPa≥ 2 MPa≥ 3 MPa

Flexure≥ 0.345
MPa

The average compressive strength for 6% and
8% cement content suggests that they are classified
as Category I. On the other hand, cement contents of
10% and 12% are classified as Category II. Data
produced by various researchers show strong, often
linear, correlation between compressive strength andcement content [1]. However, handling of blocks
with 6% cement content obtained cracks whentransferred. This entails that the handling of theblocks need to be considered in choosing thepractical cement content (PCC). Therefore, a cement
content of 8% was used in this study. This complies
with the suggested cement content of 3% to 8%
based from an economic stand point [5].
Block Production
The CSEBs were mixed at 16% moisture
content, 8% PCC (Category I CSEB), and 0.25%
fiber content as shown in the mixes in Table 4.
Table 4 Design mix of reinforced CSEB by weightMix Variations ofFibers(1) 100C(2) 100A(3) 100M(4) 50C-50A(5) 50A-50M(6) 50C-50M(7) 67C-17A-17M(8) 17C-67A-17M(9) 17C-17A-67M(10) 33C-33A-33M(11) Control Mix

Table 1 Physical properties of the fibers
Fiber
Coir
Abaca
MagueyAverage Compressive
Strength (MPa)
3.27
3.79
4.83
5.06

Elongation
20.43%
2.59%
2.59%

Blocks with varying cement contents of 6%, 8%,
10% and 12% were tested for compressive strength
to determine the practical cement content (PCC).
The results of the test are shown in Table 2. The
strengths obtained were compared to theclassification of CSEB that is presented in Table 3.
418

Coir,
C (g)
15
0
0
7.5
0
7.5
10
5
2.5
5
0

Abaca,
A (g)
0
15
0
7.5
7.5
0
2.5
10
2.5
5
0

Maguey,
M (g)
0
0
15
0
7.5
7.5
2.5
2.5
10
5
0

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The CSEB used in this study measures 295 mm x
140 mm x 100 mm. The blocks were formed using ahand-pressed machine. The soil weight per block
was 6kg, resulting to 15g of fiber that is to be mixed
per block. Fifteen block specimens were preparedand tested for each mix shown in Table 4. Five
specimens for each of the three strength tests.

Prior to the wall test, fiber-reinforced CSEBs andunreinforced CSEBs were tested again for their dry
compressive strength to be used in the computationof the expected maximum load that can be appliedon the wall.

Strength Test

The results of the tests of the blocks and the testof the walls will be presented in this section.

RESULTS AND DISCUSSIONSThe blocks were subjected to three strength tests,
namely dry compressive strength, wet compressive
strength, and flexural strength, after 28 days ofcuring, to evaluate the effects of natural fibers on
CSEBs. The blocks for dry and wet compressive
strength had the same production and testingprocess. The main difference was that the blocks for
wet compressive strength test underwent full
submersion in water bath for 24 hours before testing,while the blocks for dry compressive strength test
are directly tested after 28 days of curing. A uniform
loading rate of 0.0575 MPa/s must be applied for thethree strength tests [8].
Drop test was performed to qualitatively test theblock’s impact strength. The blocks were subjected
to fall freely at a height of 3.5 meters. This was done
to further highlight the effect of fiber reinforcement
and post-crack behavior difference between fiberreinforced and unreinforced CSEB.

Testing of Blocks
The results of testing of blocks are presented interms of how the fibers influenced the following:
strength test, failure mode, drop test, and optimalmix.
Influence of Fiber on Strength Tests
The summary of the strength tests are tabulated
in Table 5. The values are the average strength of thetest results of 5 CSEB specimens.
Table 5 Experimental strength test results
Mix
100C
100A
100M
50C-50A
50A-50M
50C-50M
67C-17A-17M
17C-67A-17M
17C-17A-67M
33C-33A-33M
Control Mix

Wall Test
A wall test was conducted on walls madeunreinforced CSEB and fiber-reinforced CSEB. It
has seven staggered rows with 3 blocks each. As
shown in Fig. 1, a proving ring was placed on top of
the wall to measure the load applied by the two
hydraulic jacks to the wall panel. The hydraulicjacks were situated below the constructed wall. The
two dial gauges were placed on opposite sides of thewall to measure the displacement.

Fig. 1

Dry
(MPa)
2.83
2.99
4.27
2.71
3.16
2.84
2.08
2.15
2.13
2.93
3.00

Wet
(MPa)
2.05
3.13
2.53
2.20
2.49
1.86
1.76
1.80
1.80
1.80
1.99

Flexure
(MPa)
0.377
0.297
0.407
0.459
0.466
0.351
0.409
0.449
0.495
0.380
0.424

The dry compressive strength test was performed
to determine the strength of the blocks that were
cured for 28 days. The compressive strength ismainly influenced by the type of soil, compacting
procedure, and binding materials used [9]. The
control (unreinforced) CSEBs have an average drycompressive strength of 3.00 MPa. This value
satisfied Category I CSEB, which has a minimum
dry compressive strength of 2 MPa. On the other
hand, the highest dry compressive strength for thefiber-reinforced CSEB was obtained from samples
with 100% maguey fiber (100M), which is 4.42 MPaor additional 42.33% strength compared to thecontrol.
The RSM was used to plot a 3D surface modelfor dry compressive strength and the result is shownin Fig. 2. This model was chosen to analyze the data

Wall test set-up
419

GEOMATE - Mie, Japan, Nov. 21-24, 2017

said block. On the other hand, the highest average
flexural strength of 0.495 MPa was obtained by
specimens with 17% coir, 17% abaca and 67%
maguey (17C-17A-67M) and this resulted to an
additional 16.89% strength compared to the control.
Similar to dry and wet compressive strength,
RSM was used to plot a 3D surface model for
flexural strength as shown in Fig. 4. Using thismodel, the highest value of flexural strength waspredicted to be 0.483 MPa and at 38.4% abaca and61.6% maguey (38.4A-61.6M).

because of its ability to show the relationshipbetween any fiber combination and its
corresponding dry compressive strength. Using thismodel, the highest value of dry compressive strength
was predicted to be 4.19 MPa at 100% maguey fiber(100M).

Fig. 2

Dry compressive strength model using
RSM

The wet compressive strength test was
performed to determine the strength of the blocks
that were cured for 28 days and then submerged inwater for 24hrs. Unreinforced CSEB has an average
wet compressive strength of 1.99 MPa, which satisfy
the requirement for Category I CSEB. On the other
hand, the highest average wet compressive strength
for reinforced CSEB, was found to be 3.13 MPa at
100% abaca fiber (100A). Thus, resulting to an
additional 57.59% in strength compared to thecontrol mix.
Similar to dry compressive strength, the RSM
was used to plot a 3D surface model for wet
compressive strength and is shown in Fig. 3. Using
this model, the highest value of wet compressive
strength was predicted to be 3.11 MPa and at 100%abaca fiber.

Fig. 3Fig. 4

Flexural strength model using RSM

Influence of Fiber on Failure Mode
The results obtained suggest that the higher thetensile strength of the fiber, the stronger the block is.
For dry and wet compressive strength test, it wasevident that the fibers provided sufficient resistancetowards breakage, holding the block more intact
compared to the unreinforced CSEB. This supports
the theory where reinforcing fibers in the soil
matrices prevent cracking through their adhesion or
bonding [6]. Meanwhile, unreinforced CSEB
presents noticeable breakage since there is no added
fibers that holds the block together. Said breakage
occurs roughly 15% of the block population.
For flexural strength, unreinforced CSEBs
underwent sudden failure resulting in a total
separation of the block in two halves during its 3point loading test. This sudden failure was present atroughly 1 second of the test, immediately ending theexperiment. Meanwhile, fiber-reinforced CSEBs
were tested until the fiber reinforcement can nolonger sufficiently hold the block for further testing.
The presence of the fibers prevented sudden failure
or total separation of the block and allowed
continuous testing. Upon the removal of thereinforced CSEB from the testing machine, it
became apparent that the blocks were split in two
but were still held together by the fibers. The
observed failure mode was consistent with thefindings reported by [1], [10].

Wet compressive strength model using
RSM

The flexural strength test was performed todetermine the 3-point bending strength and the postcrack behavior of the blocks that were cured for 28
days. It was obtained that unreinforced CSEB has anaverage flexural strength of 0.424 MPa, which
satisfies the strength for Category I CSEB. However,the block failed immediately after the peak strength,
breaking it in two and discontinues further testing on

Drop Test
A drop test is the simplest way to qualitatively
emphasize the advantage of reinforced CSEB420

GEOMATE - Mie, Japan, Nov. 21-24, 2017

against unreinforced CSEB in terms of the postcrack behavior. The drop test was performed byreleasing the block at a height of 3.5 meters above
ground. Dropped unreinforced CSEBs disintegrated
into many pieces upon impact, which shows a zeropossible recovery. On the contrary, dropped fiberreinforced CSEBs obtained damages but it did notdisintegrate fully. This clearly suggests that fiber
inclusion improves post-crack behavior.

width, height, and thickness of W= 900 mm, H=700mm, and T= 140 mm, respectively. The test wasdone by gradually applying compressive force on thewall. The failure load was measured and was also
predicted by calculating the maximum compressive
load (Pc), bucking load (Pe), and shear load (Pv).
The formulas used are as follows:
(1)
(2)
(3)

⁄
Optimal Mix
Using RSM, the optimal mix or most desirable
fiber combination based on the 3 strength tests was
obtained. The desirability of the fiber mixtures isshown in Fig. 5 using a contour model. The bestdesirability has a value of 1.0. Based on the figure, it
can be deduced that any mixture combining the threefibers results to low desirability. The optimal mix isthe combination of 42.5% abaca fiber and 57.5%
maguey fiber (42.5A-57.5M), with a desirability
value of 0.703. Using this model, the predicted drycompressive strength, wet compressive strength, andflexural strength for the abaca-maguey values were
found to be 4.42 MPa, 2.40 MPa, and 0.482 MPa,
respectively.

Where fdry = dry compressive strength of the block at
the day of wall testing, E = modulus of elasticity of
the wall, and Asheared = area sheared calculated bymultiplying the wall width by the product of theblock height x the number of rows sheared.
Unreinforced Wall Test
The peak strength was measured to be 142.61
kN. Shown in Fig. 6 is the observed failure patternof the wall. It can be noticed that the diagonal crack
indicates shear failure. The crack passed through 4.5
rows of blocks. The dry compressive strength ofthese unreinforced blocks is fdry=3.66 MPa.

`
Fig. 6 Complete failure of unreinforced wallFig. 5 Optimum mix based on desirability contour

Reinforced Wall Test

A verification test was performed for the optimalmix (42.5A-57.5M) to compare the resulting data
achieved through the RSM with the actual results.
The predicted value for the dry compressive strengthis 4.42 MPa and the actual value from testing is 4.19
MPa resulting to a 5.48% difference. The predictedvalue for the wet compressive strength is 2.40 MPa
and the actual value from testing is 2.46 MPa
resulting to 2.44% difference. Lastly, the predictedvalue for the flexural strength is 0.482 MPa and theactual value from testing is 0.525 MPa resulting to a
8.19% difference. Thus, the predictions made by
RSM are highly reliable.

The peak load was measured to be 190.79 kN,
Almost the same pattern of failure was observed,
indicating that the failure mode is also shear. The
crack passed through 5 rows of CSEB blocks. The
dry compressive strength of these fiber-reinforced
blocks is fdry=4.56 MPa.
Comparison of Wall Panels
It was clearly observed that the fiber-reinforced
CSEB wall was able to carry higher load than theunreinforced CSEB wall. This corroborate with thepreviously finding that fiber-reinforced CSEB isstronger than unreinforced CSEB. Shown in Fig. 7
are the plots of the load-displacement curves of thetwo walls. The wall test show that the fiberreinforced wall exhibit 33.79% increase in load

Wall Test
The blocks in the CSEB wall were arranged instaggered manner. The wall has a dimension of421

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Lastly, changes in the dimensions of blocks are also
recommended to further reduce the shear failure.

carrying capacity than the unreinforced wall. The
lower stiffness of the fiber-reinforced CSEB wall
may be attributed to the elongation of fibers causinglarger displacement but with an increase strength.

ACKNOWLEDGEMENTS
The authors wish to give thanks to Diosdado andSusan Pineda for their financial support of thisstudy. The authors would also like to express their
gratitude to the faculty and staff of the Civil
Engineering Department of DLSU for all their help.
Special appreciation is also due to the staff of the CE
Dept., IRTC, TUP for the testing of CSEB walls.

Load (kN)

200
150
100
50
0

Unreinforced Wall
0

10

20

30

REFERENCES[1] Morel J, Pkla A, & Walker P, “Compressive
strength testing of compressed earth blocks”,
Construction and Building Materials, Vol. 21,
2007, pp. 303-309.
[2] American Concrete Institute (ACI), “State-ofthe-art Report on Fiber Reinforced Concrete”,
ACI Committee, Detroit Michigan, USA, 1996.
[3] Elenga RG, Mabiala B, Ahouet L, GomaManiongui J, Dirras GF, “Characterization of
clayey soils from congo and physical propertiesof their compressed earth blocks reinforced with
post-consumer plastic wastes”, Geomaterials,
Vol. 1, 2011, pp. 88–94.
[4] United Nations Centre for Human Settlements(UN-Habitat), Earth construction technology,
Nairobi, 1992.
[5] Zami M, & Lee A, “Widespread adoption ofcontemporary earth construction in Africa toaddress urban housing crisis”, The Built &Human Environment Review, Vol. 4, 2011, pp.
85-96.
[6] Ghavami K, Filho R, & Barbosa N, “Behaviourof composite soil reinforced with natural
fibres”, Cement and Concrete Composites, Vol.
21, 1999, pp. 39-48.
[7] Danso H, Martinson D, Ali M, & Williams J,“Effect of fibre aspect ratio on mechanicalproperties of soil building blocks”, Construction
and Building Materials, Vol. 83, 2015, pp. 314319.
[8] New Mexico Adobe Code (NMAC), “Chapter 7
Building Codes General: Part 4 New Mexico
Earthen Building Materials Code”, Housing andConstruction, 2009.
[9] Riza FV, Rahman IA, & Zaidi AM,“Preliminary Study of Compressed Stabilized
Earth Brick (CSEB)”, Australian Journal of
Basic and Applied Sciences, Vol. 5, 2011, pp.612.
[10] Donkor P, & Obonyo E, “Earthen construction
materials: Assessing the feasibility of improving
strength and deformability of compressed earth
blocks using polypropylene fibers”, Materials &Design, Vol. 83, 2015, pp. 813-819.

Displacement (mm)Fig. 7 Load-displacement diagram of CSEB walls
Based from the calculation of strength at failure,both wall panels failed in shear as indicated in Table
6 since the calculated shear load is closest to theactual load. The calculations were done using Eq.(1)to Eq.(3).
Table 6 Calculated load compared to actual load
Wall type
U-CSEB
FR-CSEBPc (kN)
457.3
572.5

Pe(kN)
8120.44634.7

Pv(kN)
129.1
160.1

Note: U=unreinforced, FR=fiber reinforced

Actual142.6
190.8

CONCLUSION
The effects of adding coconut coir, abaca, andmaguey fibers in CSEB were investigated. The
results showed significant strength improvement of
CSEB at certain fiber combination may be obtained
for all strength tests conducted. RSM was used tomodel how the strength may be predicted for s given
fiber combination or vice-versa. Furthermore, using
RSM, a mix of 42.5% Abaca and 57.5% Maguey
was predicted and verified to be the optimum mix.
The increase in strength may be explained by thebonding effect of the fibers.
The wall test of reinforced CSEB walls shows a
33.79% increase in compressive strength compared
to unreinforced CSEB wall, where both walls failed
through shear. Due to the establishment of shear
failure as the governing mode of failure of the wall,
it is recommended that the blocks are best suited forpavements because of their high compressive
strength when used individually. It is also
recommended to have interlocking blocks for walls
instead of plain blocks to enable further
reinforcements such as steel, which minimizes shear
failure and enables it to be used as load bearing wall.

422

Seventh
International
Conference
on Geotechnique, Construction Materials and
GEOMATE- Mie,
Japan, Nov.
21-24, 2017

Environment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

USEFULNESS OF ARTIFICIAL BEACHROCK AND GEOTEXTILETUBE TECHNOLOGY
Md. Al Imran1, Kazunori Nakashima2, and Satoru Kawasaki3
1Graduate School of Engineering, Hokkaido University, Japan
2,3
Faculty of Engineering, Hokkaido University, Japan

ABSTRACT: In recent years, traditional forms of river and coastal structures have become very expensive
to build and maintain, because of the shortage of natural rock. As a consequence, the materials used inhydraulic and coastal structures are changing from traditional rubble and concrete systems to cheaper,
sustainable, and eco-friendly materials and systems such as artificial rock, gabion, slags, geosynthetics, andso on. Moreover, shorelines are being continually eroded by the wave action of the sea, and the river andcoastal structures are frequently damaged by both anthropogenic and natural causes such as over wash andstorm. How to deal with eroding coast problems is a main topic of this article. Recently, artificial beachrock
and geotextile tube technology has changed from being an alternative construction technique and, in fact, hasadvanced to become the prime solution of choice. Therefore, the objectives of the present study is to find out
the feasibility to protect coastal erosion in Asia along with using artificial beachrock and geotextile tube
technology in a cheaper, sustainable and eco-friendly way.
Keywords: Artificial beach rock, Geotextile tube technology, Coastal erosion, Sand cementation, Sustainable,
Eco-friendly
Therefore, increased interest in soft structures
for coastal protection and a combination of hardand soft structures like geotextile tube technology
is predominating and is consonant with advanced
knowledge on coastal processes and naturalprotective functions and researcher showed that,
artificial beachrocks (manufacture artificially inthe natural condition) have the potential to inhibit
coastal erosion [5]. Recently, geotextile tube
technology has changed from being an alternative
construction technique and, in fact, has advanced
to become the prime solution of choice. Geotextile
tubes, hydraulically or mechanically filled withdredged materials (woven, non-woven, andcomposite synthetic fabrics), have been variously
applied in hydraulic and coastal engineering fields.
The geotextile tube technology is mainly used forflood and water control, but they are also used toprevent beach erosion as well. In additionally,
considering the use of artificial rock in order topreserve such submerged-looking islands above
sea level, Danjo and Kawasaki [6], [8] conducted
several studies in Okinawa and Ishikawa, Japan.
They found sufficient information to build
artificial beachrock. Considering this importancesuch type of study is also essential in Asia, as andother vulnerable country to climate change, toinhibit the coastal erosion due to sea level riseusing artificial beachrock.
Therefore, the objectives of the present study is
to find out the feasible method to protect coastal
erosion in Asia along with using artificial
beachrock (Microbially Induced Carbonate

INTRODUCTION
The problem of coastal erosion is nothing new,
but in recent years, it seems to have increased in
speed especially in Asia. Because in Asia there area lot of islands, long coastal lines and population
density is much. So, initially we have focused on
Asia and later on we will work on other part of theworld regarding coastal erosion. Coastal erosion
has long been a significant problem globally,
typically due to anthropogenic changes along thecoastline, and it poses a hazard for people residingin these areas. Erosion of the sandy shore is often
used to refer to changes in the coastline due to thecollapse of the sediment balance. In order toprevent, or at least minimize damage from erosion,
a combination of various structures and processes
hasbeen
traditionallyused,
includingembankments, revetments, jetties, artificial reefs,
offshore breakwaters, and sand bypassing [5].
The costs of installing hard structures forcoastal protection are very high and development
within coastal areas has increased interest in
erosion problems; it has led to major efforts tomanage coastal erosion problems and to restore
coastal capacity to accommodate short-and longterm changes induced by human activities, extreme
events and sea level rise. The erosion problem
becomes worse whenever the countermeasures (i.e.
hard or soft structural options) applied areinappropriate, improperly designed, built, or
maintained and if the effects on adjacent shores are
not carefully evaluated.
423

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Precipitation-MICP method) and geotextile tube
technology in a cheaper, sustainable and ecofriendly way.

and diversion, that leads to less sediment supply tothe coast, and the clearing of mangrove forests,
which makes coastal areas more susceptible to thehazard.
According to Othman [22] nearly 30 percent of
the Malaysian coastline is undergoing erosion.
In Vietnam, most of the coastline in the souththat is located in a wide and flat alluvial fan andbordered by tidal rivers fringed by wide mangroveswamps, has been eroded continuously at a rate of
approximately 50 metres/year since the earlytwentieth century. Erosion still occurs in thecentral coastal zone of Viet Nam and preventive
measures such as sea dykes, revetments, and tree
plantations have been implemented to prevent
further erosion [3].
Sri Lanka’s experience with coastal erosion
dates back to 1920 and Approximately US$30
million has already been spent on breakwaters andother construction to combat coastal erosion on
southern and western coasts however, coastal
erosion still persists in some coastal areas [28].

METHODS
Data used in this study is obtained fromliterature survey of related works. Data wereorganized by geographical location of beachrocks
and coastal erosion in Asia. Quantitative scenario
of coastal erosion and protective measures in Asia
was shown in the obtained data.
For the prevention of coastal erosion
quantitative information for the prospects ofartificial beachrocks formation, their cement
components, geotextile tube technology, theirprospects, formation and composition etc. werecollected, compiled and compared. Since this was
the information that we deemed would be essential
for the manufacturing of artificial beach rock andat the same time possible protective ways for thecontrol of coastal erosion.
RESULTS AND DISCUSSION
Coastal Erosion in Asia
Coastal erosion has been studied in Viet Nam[3]; Bangladesh [17], [14], [4]; Malaysia [22];Indonesia [33]; Sri Lanka [25]; India [18], [12];China [2], Thailand [29] and Japan [6], [8], [16],[19] which is indicated in the Fig. 1 .
From the Fig. 1, it is seen that over 90 % ofbeachrocks are distributed between the proximityof 40´N and the Tropic of Capricorn. The
geographic distribution of beachrocks was notconcentrated near the equator. In particular, highconcentrations of beachrocks were found at
relatively high latitudes areas. This precludes thenotion that beachrocks are concentrated only inareas where the temperature of the air or sea ishigh [6]. Coastal erosion and accretion are naturalprocesses; however, they have become anomalous
and widespread in the coastal zone of Asia andother countries in the Indian ocean owing to
combinations of various natural forces, population
growth and unmanaged economic development
along the coast, within river catchments andoffshore. This type of erosion has been reported in
China, Malaysia, SriLanka, India, Japan, Indonesia,
Viet Nam, Thailand, and Bangladesh.
Bilan [2] reported that the erosion rate in thenorthern part of Jiangsu Province in China isserious and as high as 85 metres/year; inHangzhou Bay the rate is 40 metres/year, while in
Tianjin it is 16-56 metres/year. Erosion persists
even where preventive measures such as sea dykes
are constructed. Beach scour has been found along
coasts with sea-dyke protection. This erosion is
attributable to many factors such as river damming

Fig. 1 Location of beachrock deposition in some
Asian countries (google.map)
In India the rapid erosion of the coast of Sagar
Island in West Bengal, India, is caused by several
processes that act in concert; these are naturalprocesses that occur frequently (cyclones, waves
and tides that can reach six metres in height) andanthropogenic activities. The erosion rate from1996 to 1999 was calculated to be 5.47 square
kilometres/year [12]. The areas that are severely
affected by erosion are the north-eastern, southwestern and south-eastern faces of the island.
Malini and Rao [18] reported coastal erosion andhabitat loss along the Godavari Delta front owing
to the combination of the dam construction acrossthe Godavari and its tributaries that diminishes
sediment supply to the coast and continued coastal
land subsidence.
In Indonesia, coastal erosion started in thenorthern coast of Java Island in the 1970s whenmost of the mangrove forest had been converted toshrimp ponds and other aquaculture activities, and424

GEOMATE - Mie, Japan, Nov. 21-24, 2017

years [31] owing to interactions among sandsupply, cement precipitation from seawater andcoastal erosion by ocean waves [5]. Therefore, it
may be possible to slow down the erosion of coasts
by making man-made beachrock from coastal
sands. Because this artificial rock is made of local
materials, it has the potential to be a cheaper andeco-friendly product [5].

the area was also subjected to unmanaged coastal
development, diversion of upland freshwater andriver damming. Coastal erosion is prevalentthroughout many provinces [33] such as Lampung,Northeast Sumatra, Kalimantan, West Sumatra(Padang), Nusa Tenggara, Papua, South Sulawesi
and Bali.
In Thailand, intensification of coastal erosion
came to notice during the past decade overall, thenet erosion is approximately 1.3 to 1.7 metres/year
along the southern Thailand coastline. Total area
losses amount to 0.91 square kilometres/year for
the Gulf coast and 0.25 square kilometres/year for
the western coast [29].
Khan [17] and Islam [14] studied coastal
erosion and accretion activities in Bangladesh.
Heavy discharge currents through the GBM(Ganges-Brahmaputra-Meghna) river system,
wave action due to strong southwest monsoon
winds, high astronomical tides as well as sea level
rise (SLR), and storm surges in the Bay of Bengal
are the main causes of erosion in the coastal areaof Bangladesh [14]. Erosion due to SLR has been
discussed by Islam [14] at his study which wasdone under the U.S. Country Studies Program, andsome of the salient features of the study arepresented here.
The study was based on the erosion formula
given by Bruun [34].
x=ab/(e+d)

Characteristics of Beachrock
The majority of recent beachrock is formed onbeaches in the same regions that favour coral reef
formation. This is generally below 25° latitude
where there is a well-defined dry season and “thetemperature of ground water at a depth of about 76
cm in beaches remains above 21°C for at least 8months of the year” [24]. Several theories havebeen proposed to explain beachrock formation,
which can be divided into physico-chemically andbiologically induced precipitation of calcium
carbonate. Most of the theories have beenformulated to explain occurrences of beachrock.
Physico-chemical models explain marine
carbonate cement precipitation by the soaking ofbeaches during high tides and evaporation of sea
water during low tides [11], enhanced by (daytime)solar warming of the beach.
Biological processes may have an importantrole in beachrock formation. Biological activity
controls the partial pressure of CO2 by its
consumption, thus promoting the precipitation of
CaCO3 [13]. Ammonification of amino-acids,sulphate reduction and other bacterial processes
taking place during organic matter degradation
promote carbonate precipitation by raising the pH,
furthermore, organic matter may promote
carbonate precipitation [32].
So, there are a number of theories regarding theprocess of beach sand cementation. Different
mechanisms of cementation appear to be
responsible at different localities. The primarymechanisms proposed for the origin of beachrock
cements are as follows:
1) Physicochemical precipitation of high-Mg
calcite and aragonite from seawater as a result ofhigh temperatures, CaCO3 super saturation, and/or
evaporation [10],2) Physicochemical precipitation of low-Mg
calcite and aragonite by mixing of meteoric andfresh ground water with seawater [26],3) Physicochemical precipitation of high-Mg
calcite and aragonite by degassing of CO2 frombeach sediment pore water [30], and
4) Precipitation of micritic calcium carbonate as aby-product of microbiological activity [21].

(1)Where x is the shoreline recession due to SLR,
a is the rise in water level due to SLR, e is theelevation of the shore, and d is the depth of waterat a distance b from the coastline. Islam [14]applied the formula to the eastern region, where
the longest continuous sandy beach situated, ofBangladesh.
Coastal Protection
Natural beachrocks, which are formed naturally
on beaches, have attracted attention as a model for
artificial rocks. Danjo and Kawasaki [5] proposeda new method to protect coastlines from erosion,
the use of artificial rock that auto-repairs by meansof sunlight, seawater, and bacteria. Their model ofartificial rock is beachrock. Beachrock is a type of
sedimentary deposit that generally occurs on
tropical and subtropical beaches as a result ofintertidal lithification of loose beach sands andgravels by carbonate cementation.
Beach rock is generally limited to tropical andsubtropical climates, though not every tropicalbeach has beach rock Beach rock has also beenreported from temperate regions, but suchoccurrences are rare. Around the world beachrocks
have been reported to form over several thousand
425

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Properties of Beachrock and Beach Sand in
Asia

Artificial Beachrock Formation through Beachand Sand Solidification

From the Fig. 2 and Table 1, it is shown that,the main component for the formation ofbeachrock is CaO and SiO2. But other components
like Al2O3, TiO2, and FeO also play a vital role forthe beachrock formation.

Danjo and Kawasaki [5]-[7] conducted several
study in Okinawa and Ishikawa, Japan. They foundsufficient information to build manmade
beachrock. Danjo and Kawasaki [5] perform coralsand solidification test using ureolytic bacteria(Pararhodobacter sp.) and found this type ofbacteria has the ability to solidify coral sandprecipitating CaCO3. Considering this importancesuch type of study is also essential in Asia, andother most vulnerable country to climate change,
to inhibit the coastal erosion due to sea level rise.
Danjo and Kawasaki [5]-[7] found that,
Column specimens were cemented up to UCS of
10 MPa after 28 days under the conditions (curing
temperature; 30°C, injection interval; 1 day, Ca2+
concentrations in cementation solution; 0.3 M).
Based on formation methods observed by Danjoand Kawasaki [5]-[7] the sand cementation process
is very much suitable, eco-friendly, cheaper andsustainable for the areas in Asia where thetemperature, sand properties and other conditions
is almost same as Japan and the results of thisstudy will contribute to the application of a newtechnique for coastal sand improvement and biostimulation.

Table 1: The main component for the formation ofbeachrock in some Asian countries
Location
Bangladesh

India
Sri Lanka

Vietnam
Malaysia
Indonesia
China
Thailand
Japan

Rock
Formation
Type
Calcareous
coral sand,brokencoral orlimestone
Calcareous
coral sand,limestone

Component
Materials

References

Kaolinite[17]

Quartz,Feldspar,Kaolinte
Quartz,Calcite,Dolomite,
Aragonite
Data is not available
Calcareous,
Aragonite
Data is not available
Calcareous
sand, Lime
stone
Data is not available
Shell sand,Aragonite,
foraminifer, Mg calcite
sand, gravel

[23]
[15]

[1]

Protective Coastal Protection Learned fromBeachrock Formation: Through Geo-textile
Tube Technology[15]

The recent trend in the mitigation of coastal
erosion and costal protection has been shifted nowa-days towards soft novel cheaper, sustainable andeco-friendly methods. Pro-active methods andsolutions are being developed and employed,
which are not only eco-friendly, constructionfriendly and cheaper but also address the root
cause of the problem without much adverse
effects. Such kind of modern tool is geotextile
tube which is one of the geosynthetics structuresthat are increasingly used in coastal protection.
They are made from polypropylene (PP), polyester(PET), polyethylene (PE), polyamide (nylon),
olyvinylidene chloride (PVC), and fibreglass.
Sewing thread for geotextiles is made from Kevlar
or any of the above polymers [20]. Different fabriccomposition and construction are suitable fordifferent applications.

[5]Fig. 2 Beachrock compositions in some Asian
countries [17]426GEOMATE - Mie, Japan, Nov. 21-24, 2017activities. So, for the protection of coastal erosion
geotextile tube technology along with MICP
method can be applied which is very much ecofriendly, cheaper, and sustainable. Although, sandcementation and geotextile tube technology
procedure is poorly understood till now. However,actual field trials are always recommended prior to
final application.
REFERRENCES[1] Ali CA, and Mohamed KR, “Cementation in
Quaternary beach rock in the islands off theEast Coast, Peninsular Malaysia: petrographic
evidence”, Warta Geologi, Vol.23, No.2, 1997,
pp. 57-62[2] Bilan D, “The preliminary vulnerability
assessment of the Chinese coastal zone due tosea level rise”, Proceedings of the IPCC eastern
hemisphere workshop, 1993, Tsukuba, Japan,
pp. 3-6.
[3] Cat NN, Tien PH, Sam DD, and Bien NN,“Status of coastal erosion of Vietnam andproposed measures for protection”, FAO
forestry report, 2006, pp.10-21.
[4] Chowdhury SQ, Fazlul A T M, and Hasan KH,“Beachrock in St. Martin's Island, Bangladesh:
Implications of sea level changes on beachrock
cementation”, Marine Geodesy, 1997, Vol.20,
No.1, pp 89-104.
[5] Danjo T, and Kawasaki S, “A study of theformation mechanism of beachrock in
Okinawa, Japan: Toward Making Artificial
Rock”, Int. J. of GEOMATE, Vol.5, No.1,
2013, pp. 633-638.
[6] Danjo T, and Kawasaki S, “Characteristics ofbeachrock based on bibliographical research:toward the development of man-madebeachrock”, J. of Japanese Society ofEngineering Geology, Vol.53, No.3, 2012a, pp.
129-151.
[7] Danjo T, and Kawasaki S, “Microbially
Induced Sand Cementation Method Using
Pararhodobacter sp. Strain SO1, Inspired by
Beachrock Formation Mechanism”, Materials
Transactions ©2016 The Mining and Materials
Processing Institute of Japan, Vol. 57, No.3,
2016, pp. 428-437.
[8] Danjo T, and Kawasaki S, “Property evaluationof beachrock based on field investigation in
Okinawa Island, Japan”, Harmonising RockEngineering and the Environment Qian & Zhou(eds), Taylor and Francis Group, London,
2012b, pp. 949-952.
[9] Danjo T, Kawasaki S, Shimazaki S, andKoizuka K, “Coral sand solidification test
using ureolytic bacteria”, Geomechanics fromMicro to Macro-Soga et al. (Eds) © 2015

Fig. 3 Proposed Coastal Protection Method
Traditional Geotextile tubes widely used for
dewatering, flood control, and coastal protection.
Geotextiles are either woven or non-woven
permeable fabric or synthetic material which canbe used in combination with geotechnicalengineering material [27]. But our proposed
method is coastal protection along with MICP
method and these “Geotube” (Fig. 3). In case of
traditional methods, different rays from sun candamage the “Geotube” after a certain time and soil
protection may not be sustainable and the cost of
re-constructing “Geotube” is much. But, in our
proposed method, sand cementation using MICP
method can be applied over the “Geotube”. As aresult, the surface of the coast and “Geotube” will
be strengthened and will remain loner and soil will
be protected. In this method, cost is low
comparatively and local ureolytic bacteria is used,
so this is eco-friendly and sustainable. Thismethod can be applied in a broad range of civilengineering applications including construction,paving, drainage and other applications.
CONCLUSIONSIn conclusion, we can say that, the depositionof beach rock using MICP method is ofsignificance because of the timing of diagenesis
and the mode of cementation. Recently, geotextile
tube technology has changed from being analternative construction technique and, in fact, hasadvanced to become the prime solution of choice.
But the method is not sustainable and time
consuming and sometimes costly. However, thelower resistance of geotextile to damage needs tobe overcome to ensure the longer service period of
the geotextile tubes. Covering the tubes with
geotextile or rocks can protect the structures fromdirect contact with sharp objects or vandalism
427

GEOMATE - Mie, Japan, Nov. 21-24, 2017[23] Ravisankara
R,
Chandrasekaranb
A,
Kalaiarsia S, Eswaranc P, Rajashekhare C,
Vanasundaria K, and Alok A, “Mineral
analysis in beach rocks of Andaman Island:
India by spectroscopic techniques”, Archieveof Applied Science Research, Vol. 3, No.3,
2011, pp. 77-84.
[24] Russell RJ, “Water-table effects on seacoasts”,
Geology Society of America Bulletin, Vol.
82,1971, pp. 2343-2348.
[25] Sato Y, and Mimura N, “Environmental
problems and current management issues in the
coastal zones of south and southeast Asiandeveloping countries”, Journal of Global
Environmental Engineering, Vol.3, 1997, pp.
163-181.
[26] Schmalz RF, ‘Formation of beach rock at
Eniwetok Atoll”, In Bricker, O.P., (ed.),Carbonate Cements. Maryland: Johns Hopkins
University Press, 1971, pp. 17-24.
[27] Shina EC, Ohi YI, “Coastal erosion
prevention by geotextile tube technology”,
Geotextiles and Geomembranes, Vol.25, No.4,
2007, pp. 264-277.
[28] Swan SB, “The coastal geomorphology of Sri
Lanka: An introductory survey”, published byArmidale, NSW, Dept. of Geography,
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428

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

SHEAR BOND STRENGTH OF FA-PC GEOPOYLMERUNDER DIFFERENT SAND TO BINDER RATIO AND
SODIUM HYDROXIDE CONCENTRATION
Tanakorn Phoo-ngernkham 1*, Sakonwan Hanjitsuwan 2, Satakhun Detphan 3, Jaksada Thumrongvut 4,
Cherdsak Suksiripattanapong 5, Nattapong Damrongwiriyanupap 6,
Prinya Chindaprasirt 7 and Shigemitsu Hatanaka 8
1,3,4,5
Faculty of Engineering and Architecture, Rajamangala University of Technology Isan, Nakhon
Ratchasim, THAILAND; 2 Faculty of Industrial Technology, Lampang Rajabhat University, THAILAND;
6
School of Engineering, University of Phayao, THAILAND; 7 Faculty of Engineering, Khon Kaen
University, THAILAND; 8 Faculty of Engineering, Mie University, JAPANABSTRACTThis paper presents the effects of sand to binder (S/B) ratio and sodium hydroxide (NaOH) concentration on
setting time, compressive strength and shear bond strength of FA-PC geopolymer binder. Geopolymer binder
was manufactured from FA and PC at ratio of 90:10 by weight of binder. The liquid alkali solution used in thisstudy are sodium hydroxide (NaOH) and sodium silicate (Na2SiO3) solutions. The Na2SiO3/NaOH ratio of 2.0,
liquid alkali solution/binder ratio of 0.60, and curing at ambient temperature were fixed in all mixes.
The differences in NaOH concentrations of 5, 10 and 15M and S/B ratios of 1.00, 1.25 and 1.50 has been
investigated. Test results show that the differences of NaOH concentration and S/B ratio has an effect on setting
time, compressive strength and shear bond strength of FA-PC geopolymer mortar. The setting time of mortars
are obviously decreased with increasing of S/B ratio whereas the setting time of mortars are obviously increased
with increasing of NaOH concentration. The compressive and shear bond strengths of mortar increase asincreasing of both S/B ratio and NaOH concentration up to a threshold limit. The highest slant shear strength
between PCC substrate and FA-PC geopolymer mortar was found in the mortar with 1.25 of S/B ratio and 10M
NaOH concentration which gives 24.1 MPa.
Keywords: Geopolymer, Fly ash-Portland cement blends, Sand to binder ratio, NaOH concentration, Shearbond strength.
researchers [10, 11] reported that the temperature
curing at approximately 40-75 ºC could enhance thedegree of geopolymerization within the matrix andhence reasonable strength FA geopolymer gain. In
ideal of real construction, the use of temperature
curing is difficult for the construction practice.
Nowadays, the materials who consisted of calciumoxide could improve the strength development of FA
geopolymer. For example, Pangdaeng et al. [10]studied on the use of PC to replace FA for making
geopolymer binder cured at ambient temperature.
They reported that the generated heat from hydration
products could help the geopolymerization process.
Also, Temuujin et al. [12] reported that coexistenceof calcium silicate hydrate (C-S-H) and geopolymer
gel (N-A-S-H) provides higher compressive strengthof geopolymer binder than N-A-S-H gel.
One of the important factor on the strength
development of geopolymer binder is alkali solution.
Hanjitsuwan et al. [13] claimed that two types ofalkali solution viz., sodium hydroxide (NaOH) andsodium silicate (Na2SiO3) solutions were widelyused for making geopolymer binder. Also,
Hanjitsuwan et al. [13] explained that NaOH
solution was used for leaching out of Si4+ and Al3+

INTRODUCTION
The applications of Portland cement (PC) isessential to the rapid urbanization in many
developing countries. Advantages of PC are highmechanical performances and low cost; however,increasing of PC manufacture corresponds to energy
and environmental issues. An annual publication hasreported that approximately 1 ton of CO2 emissions
for each ton of the PC produced [1]. Recently,
geopolymer binder is one of the new binders thathave been developed by several researchers as analternative cementing agent to PC [2, 3]. This isbecause of geopolymer binder is having less CO2
footprint than PC as reported by McLellan et al. [4].
Geopolymer binder is made from aluminosilicate
source materials activated with high alkali solutions[5]. Many researchers [2, 3, 6] have already reported
that geopolymer binder could develop as cementing
agent because there are many advantages i.e., highstrength, excellent durability and high bonding.
In Thailand, fly ash (FA) from Mae Moh power
station is widely used for making geopolymer binder[7-9]; however, the production of FA geopolymer atambient temperature gives low strength [10]. Some429

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ions whereas Na2SiO3 solution was used forcondensation process to form aluminosilicate
material. In addition, ratio of sand to binder is one of
the important factor for considering as repair
materials which related to a homogeneous matrix ofgeopolymer binder as reported by Thakur and Ghosh[14].
In order to utilize geopolymer binder as analternative repair material, many researchers [2, 3,
15-19] have studied the setting time, strength
development and bonding strength for proving theirproperties compared with commercial repair
materials in the market. As mentioned, the 7-day
strengthrequirementof
rapid
hardeningcementitious materials was 28.0 MPa as per ASTM
C928-13 [20], and the initial setting time andminimum strength requirements for repair binder
were 30 minutes and 35.0 MPa, respectively as per
ASTM C881/C881M-14 [21]. Therefore, the aim of
this study is to investigate the effects of NaOH
concentration and S/B ratio on setting time,compressive strength and shear bond strength of FAPC blends geopolymer mortar. The obtained results
should be very beneficial to the understanding and to
the future applications of geopolymer binder as
fundamental of alternative repair materials.

mixes. Geopolymer binder was manufactured fromFA and PC at ratio of 90:10 by weight of binder. FA
was replaced by PC because it needs calcium oxidefor enhancing the strength development ofgeopolymer binder when cured at ambient
temperature as reported by Pangdaeng et al. [10].
The NaOH concentrations of 5, 10 and 15M, andsand to binder ratios (S/B) of 1.00, 1.25 and 1.50 has
been investigated.
For the mixing of mortars, NaOH and Na2SiO3
solutions were firstly mixed together before use as
liquid solution. The FA, PC, and sand were dry
mixed until the mixture was homogenous. Rightafter, the liquid solution was added and the mixingof mortars was done for 3 minutes.
Table 1 Chemical compositions of FA and PC
Chemical compositions
SiO2
Al2O3
Fe2O3
CaO
MgO
Na2O
K2O
SO3
LOI

EXPERIMENTAL DETAILS AND TESTINGANALYSIS
Materials
The precursors used in this study are fly ash (FA)from Mae Moh power plant in northern of Thailand,and ordinary Portland cement (PC). FA had specificgravity, median particle size and Blaine fineness of
2.65, 15.3 µm and 4300 cm2/g, respectively. While,
PC had specific gravity, median particle size andBlaine fineness of 3.15, 14.6 µm and 3600 cm2/g,
respectively. The liquid alkaline activators are
sodium hydroxide (NaOH) and sodium silicate(Na2SiO3) with 13.89% Na2O, 32.15% SiO2, and54.16% H2O by weight. Fine aggregate used in thisstudy is local river sand with specific gravity of
2.65, and fineness modulus of 2.00.
The chemical compositions of FA and PC are
illustrated in Table 1. FA consists of 31.32% SiO2,
13.96% Al2O3 and 15.64% Fe2O3, and the CaO
content is high at 25.79%, thus this FA is Class C as
per ASTM C618-15 [22]. In addition, physicalproperties of FA and PC are illustrated in Table 2.

FA
31.32
13.96
15.64
25.79
2.94
2.83
2.93
3.29
1.30

PC
20.80
4.70
3.40
65.30
1.50
0.40
0.10
2.70
0.92

Table 2 Physical properties of FA and PC
Materials
Specific gravity
Median particle size, d50 (µm)
Blaine fineness (cm2/g)

FA
2.61
15.3
4300

PC
3.15
14.6
3600

Table 3 Mix proportions of FA-PC geopolymer

Mix proportion of FA-PC geopolymer
The mix proportions of FA-PC geopolymer
under different NaOH concentration and S/B ratio
are shown in Table 3. Constant liquid alkali solution
to binder ratio of 0.60, Na2SiO3/NaOH ratio of 2.0,
and curing at ambient temperature were fixed in all
430

GEOMATE - Mie, Japan, Nov. 21-24, 2017

increasing of S/B ratio.
For effect of NaOH concentration, the leachingout of Si4+ and Al3+ ions is generally low at low
NaOH concentration whereas the leaching out of
Ca2+ is not interrupted; thus, the solution was filledwith calcium as reported by Rattanasak andChindaprasirt [25]. Also, Guo et al. [26] explainedthat calcium oxide could react with silica and/or
alumina from FA to form C-(A)-S-H gels withingeopolymer system. Hence, the setting time of FAPC geopolymer was thus short. At high NaOH
concentration, the leaching out of Si4+ and Al3+ ionsis much better than low NaOH concentration; incontrast, calcium oxide was hindered. Thus, thesetting time of FA-PC geopolymer with high NaOH
concentration is increased.

Experimental details and testing analysis
Setting time of FA-PC geopolymer
After mixing, the setting time of FA-PC
geopolymer was tested as per ASTM C191-13 [23].
Compressive strength of FA-PC geopolymer
Fresh FA-PC geopolymer mortar was cast in
a 50x50x50 mm3 cube molds for compressive
strength test as per ASTM C109 [24]. After that,sample has been wrapped with vinyl sheet to protect
moisture loss. The samples were cured for a day andthen demolded with immediately wrapped by vinyl
sheet and kept in ambient temperature until testingage. The compressive strength of samples has beentested at the age of 28 days. The reported results are
the average of five samples.
Shear bond strength between concrete substrate and
FA-PC geopolymer
Portland cement concrete (PCC) is a mixture of
500 kg/m3 Portland cement, 510 kg/m3 fineaggregate, 930 kg/m3 coarse aggregate and 238
kg/m3 water, respectively. The 28-day compressive
strength and Young's modulus of PCC were 35.0
MPa and 27.5 GPa, respectively, which based on
previous study [2, 3]. As mentioned, fresh PCC wascast in a 50x50x125 mm3 prism molds. After curing
time for 90 day, the PCC was cut in half at 45° line
to the vertical. For preparation of shear bondstrength between PCC and geopolymer mortar, fresh
FA-PC geopolymer was cast into a 50x50x125 mm3prism mold with the other half filled with PCC.
Then, samples were wrapped with vinyl sheet toprotect moisture loss and kept in ambient
temperature until testing age. The shear bondstrength was calculated as the ratio of maximum
load at failure and the bond area. The shear bondstrength was tested at the age of 28 days witha constant loading rate of 0.30 MPa/s. The reported
results were the average of five samples.

Fig. 1

Setting time of FA-PC geopolymer mortar
with various NaOH concentration and S/Bratio.

From this results, it can be concluded that thefast setting of FA-PC geopolymer is very attractive
for repair work which the fast setting is normallyrequired. As for ASTM C881/C881M-14 [21]required the initial setting time for repair binder at
30 min; therefore, all mixes meet the requirement of
ASTM standard.

RESULTS AND DISCUSSION

Compressive strength of FA-PC geopolymer

Setting time of FA-PC geopolymer

The results of 28-day compressive strength of
FA-PC geopolymer mortar with different NaOH
concentration and S/B ratio are shown in Figure 2.
The strength of FA-PC geopolymer mortar increase
with increasing of both S/B ratio and NaOH
concentration. For example, the 28 day-strength of
5M1.00SB, 5M1.25SB, 5M1.50SB, 10M1.00SB and
15M1.00SB mixes are 40.3, 50.4, 54.3, 46.8 and45.1 MPa, respectively.
As for effect of NaOH concentration, it has aneffect on the strength development of FA-PC
geopolymer mortar. At high NaOH concentration,
the leaching out of Si4+ and Al3+ ions from FA
particles increase which corresponds to increasing of
its strength. Hanjitsuwan et al. [13] claimed that theformation of N-A-S-H gel was improved at high

The results of setting time of FA-PC geopolymer
mortar with different NaOH concentration and S/Bratio are shown in Figure 1. The initial and final
setting time of FA-PC geopolymer tend to decrease
with increasing of both NaOH concentration and S/Bratio. With regard to effect of S/B ratio, theincreasing of S/B ratio has an effect on setting timeof FA-PC geopolymer mortar. For example, theinitial and final setting time of 10M-1.00SB, 10M1.25SB and 10M-1.50SB mortars are 19, 15, 15 min
and 30, 25, 23 min, respectively. This is because
increasing of fine aggregate in the geopolymer
system is related to decrease in the paste value;
therefore, the setting time of mortar is decreased as
431

GEOMATE - Mie, Japan, Nov. 21-24, 2017

increase with increasing NaOH concentration;
however, NaOH concentration at 15M seems to be aslight reduction. The CaO from PC could react with
SiO2 and/or Al2O3 from FA in the suitable NaOH
concentration; hence, additional formation of C-S-H
and/or C-A-S-H coexists with N-A-S-H gels [27,28]. Thus, an enhancement of bonding strength at
the interface transition zone between PCC substrateand FA-PC geopolymer mortar was obtained. In
contrast, the leaching out of CaO from FA and PC
was hindered at higher NaOH concentration [13].
Therefore, bonding at two surfaces slight decrease.
It can be concluded that a mixture of S/B ratio at
1.25 and NaOH concentration at 10M gives
the highest slant shear strength between PCC
substrate and FA-PC geopolymer mortar.

90

28-day shear bond strength (MPa)28-day compressive strength (MPa)NaOH concentration. Therefore, the coexistence of
N-A-S-H and C-S-H gels could enhance the strength
development of FA-PC geopolymer mortar [19].
However, at 15M NaOH gives lower strength of FAPC geopolymer mortar than that of 10M NaOH
concentration. This is because the leaching out of
CaO from FA and PC was hindered at high NaOH
concentration [13]; therefore, 10M NaOH
concentration is suitable alkali hydroxide for
producing FA-PC geopolymer. According to Figure
2, it can be concluded that the strength of FA-PC
geopolymer mortar increase as increasing of S/Bratio and NaOH concentration up to a threshold limitthat are 10M NaOH and 1.50 of S/B ratio.
The relatively highest strength was found in
the 10M1.50SB mix which gives 65.1 MPa of
28-day strength.
S/B=1.00
S/B=1.25
S/B=1.50

80
70
60
50
40
30
20

40

30
25
20
15
10
5
0

10
0

5

10

15

NaOH concentration (Molar)
510Fig. 3

15

NaOH concentration (Molar)

Fig. 2

S/B=1.00
S/B=1.25
S/B=1.50

35

Compressive strength of FA-PC
geopolymer mortar with various NaOH
concentration and S/B ratio.

Shear bond strength between PCC substrateand FA-PC geopolymer with various NaOH
concentration and S/B ratio.

CONCLUSION
This paper has provided an experimental study
on setting time, compressive strength and shear bondstrength of FA-PC geopolymer mortar with various
different NaOH concentration and S/B ratio. Basedon the obtained experimental results, the following
conclusions could be drawn:
1. The difference of NaOH concentration and
S/B ratio has an effect on setting time of FA-PC
geopolymer mortar. The setting time of mortars are
decreased as increasing of S/B ratio. While,increasing of NaOH concentration could delay thesetting time of FA-PC geopolymer mortar.
2. Compressive strength of FA-PC geopolymer
mortars are increased as increasing of both S/B ratio
and NaOH concentration up to a threshold limit. The
FA-PC geopolymer mortar manufactured from 10M
NaOH and S/B ratio of 1.50 gives the highest 28-day
strength of 65.1 MPa.
3. The FA-PC geopolymer mortar withthe optimum NaOH concentration and S/B ratio
could improve the shear bond strength between PCC
substrate and geopolymer mortar. The increase in
shear bond strength is due to an enhancement ofreaction products at two surfaces. A mixture of S/B

Shear bond strength between PCC substrate and
FA-PC geopolymer
Test results of shear bond strength between PCC
substrate and FA-PC geopolymer mortar under
different NaOH concentration and S/B ratio aresummarized in Figure. 3. The increase in both of
NaOH concentration and S/B ratio has an effect on
shear bond strength between two bonding surfaces.
The improvement of shear bond strength is directly
related to the behavior of their compressive strength.
For instance, the 28 day-shear bond strength of
5M1.00SB, 5M1.25SB, 5M1.50SB, 10M1.00SB and
15M1.00SB mixes are 18.2, 18.6, 15.9, 23.3 and24.2 MPa, respectively.
With regard to effect of S/B ratio, the slant shear
strength between PCC substrate and FA-PC
geopolymer mortar tends to increase with increase in
S/B ratio up to a threshold limit that is 1.25 of S/Bratio. As mentioned, the slant shear strength at 1.50
of S/B ratio obvious decrease when compared to1.25 of S/B ratio. As for effect of NaOH
concentration, the slant shear strength between PCC
substrate and FA-PC geopolymer mortar tends to432

GEOMATE - Mie, Japan, Nov. 21-24, 2017

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ratio at 1.25 and 10M NaOH gives the highest slant
shear strength which is 24.1 MPa.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the financial
supported from the Rajamangala University ofTechnology Isan, Thailand; and Khon Kaen
University and the Thailand Research Fund (TRF)
under the TRF Senior Research Scholar, Grant No.
RTA5780004.
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[22] ASTM C618-15, “Standard specification forcoal fly ash and raw or calcined natural
pozzolan for use in concrete”, Annual Book of
ASTM Standard, Vol.04.02, 2015.
[23] ASTM C191-13, “Standard test method for timeof setting of hydrualic cement by vicat needle”,
Annual Book of ASTM Standard, Vol.04.02,
2013.
[24] ASTM C109, “Standard test method ofcompressive strength of hydrualic cement
mortars (using 2-in. or [50 mm] cube
speciments)”, Annual Book of ASTM Standard,
Vol.04.01, 2002.
[25] Rattanasak U, Chindaprasirt P, “Influence of
NaOH solution on the synthesis of fly ash
geopolymer’, Miner. Eng., Vol. 22(12), 2009,
pp. 1073-1078.

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INFLUENCE OF SEAWATER ON THE STRENGTH OF RC BEAMSAND CORROSION BEHAVIOR OF STEEL
Bernardo A. Lejano1 and Cheryl Lyne C. Roxas2
1,2Faculty, De La Salle University, Philippines
ABSTRACTThe effects of seawater on the strength performance of reinforced concrete (RC) beams were investigated.
Four RC beams measuring 150 x 200 x 800 mm were constructed. Two beams were constructed with concrete
mixed with freshwater and the other two were constructed with seawater. Center point loading test was
conducted on the beams specimens. Load, deflection, and strain of each beam were monitored and recorded. It
was found that the difference between the strength test values obtained by using freshwater and seawater wereminimal. However, formation of rust in steel when seawater was used was very evident. Hence, the effects ofseawater on the corrosion behavior of steel were investigated. Mortar specimens with cold-joint were used as
medium to facilitate the investigation of corrosion. Ordinary Portland cement (OPC) Type 1 was used as binder
for the mortar and was partially replaced with fly ash at 30% and 50%. Rectangular prism specimens ofdimensions 40mm by 40mm by 160mm were cast for macrocell corrosion measurements and compressive
strength determination. From the test results, the following were observed: (a) Specimens with fly ash wereobserved to have lower corrosion rates compared with the ones without fly ash; (b) Specimens mixed withfreshwater resulted to the higher strength both at 7th-day age and 28th-day age; (c) Regardless of the type ofwater used in making the mortar, specimens cured in seawater achieved higher later strength values.
Keywords: Seawater, Corrosion, Reinforced Concrete, Mortar, Fly Ashwould affect the corrosion behavior of thereinforcing bars.
As a consequence, the effects of seawater on the
corrosion behavior of steel in mortar were
investigated. In addition, fly ash was also
investigated as a possible concrete ingredient thatcan possibly lower the corrosion rate of steel inconcrete. Fly ash is a pozzolan, hence it reacts withcalcium hydroxide that is produced during cement
hydration resulting to the conversion of larger pores
into finer pores [6]. This produces a more compact
concrete thereby blocking the flow of seawater orother chemical attacks. As a result, the corrosion riskof reinforced concrete structures in chloride richenvironments, such as seawater, can be lowered by
fly ash to a satisfactory level [7].
In this study, steel is assumed to undergo
macrocell corrosion. Corrosion happens whenchemical reaction, specifically oxidation, occurs insteel. The presence of this chemical reaction can bemonitored through the flow of electricity when steel
bars enclosed in concrete are arranged forming amacrocell circuit, that is, an anode and a cathode thatare separated from each other. Usually, the passive
film that is formed on the steel surface due to thealkalinity of concrete is broken down due to thepresence of chemicals or other environmental factors.
Mortar specimens were used in this research to
make it easier to measure to macrocell corrosion, as
the presence of coarse aggregate could complicate
the flow of electric current. Macrocell corrosion can

INTRODUCTION
Seawater is still currently not allowed to be usedin construction as stipulated in the National
Structural Code of the Philippines (NSCP) [1] andmost of the other codes all over the world. However,there are already studies [2] - [5] that indicate thepossibilities of using seawater as a substitute forpotable water in concrete; whether for mixing,
curing, or both. Results are varying and sometimes
contradicting. Studies of Otsuki et al. [2], indicate
the countermeasures that can be applied to eliminate
the disadvantages that seawater presents. Thesestudies indicate the possibility of using seawater inconcrete; but still more studies must be conducted tofurther validate the usage, especially in reinforced
concrete. Establishing criteria in using seawater inreinforced concrete members would benefit places
with abundant seawater resources, such as thePhilippines.
To investigate the effect of seawater when usedin making reinforced concrete (RC) beam, thestructural performance of two RC beams constructedwith seawater were compared to two control RC
beam specimens constructed with freshwater. Thisis done by testing the RC beams as simply supported
beams with center-point loading. The findings ofthis comparison are presented in this paper. It wasobserved that the major effect of seawater is incorroding the reinforcing bars. It is also believed that
exposing the RC beam to seawater environment
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

be further affected by chloride environment
especially when concrete surface has cracks [8].
Since macrocell corrosion may occur at any time toany reinforced concrete structure, it is important tohave good awareness of this corrosion process. As
seawater is known to increase the probability ofcorrosion of steel, it is important to determine underwhat conditions this will happen and what are thepossible remedies or solutions that may be applied.
To address the above mentioned problems, themain objective of this phase of study is to determine
the effects of seawater on the corrosion density andcorrosion rates and the possible countermeasuresthat fly ash can provide to the macrocell corrosion.
In addition, the effects of seawater and fly ash to thecompressive strength of mortar are also investigatedto provide more information.

Fig. 2Longitudinal details of the beam specimens

Testing for the flexural strength of the RC beam
was conducted at 56 days after casting. Center point
loading on a simply supported beam was adopted. A
hydraulic jack was used to apply the load andmonitored with a load cell. Clip gages anddisplacement transducers were used to monitor thestrains and deflection, respectively, at the midspanof the beam. Shown in Fig. 3 is the test setup. Afterthe beams were tested, the reinforcing bars wererecovered for evaluation of the effect of seawater.

METHODOLOGYThis research may be divided into two parts. The
first part is the testing of RC beams to evaluate theeffect of seawater on their structural performance.
The second is the macrocell corrosion test to study
the corrosion behavior of steel and find possible wayof counteracting it.
Test of RC beams
Four RC beams with dimensions of 150 x 200 x
800 mm with target concrete strength of f’c= 21MPa
were prepared. Two RC beams used freshwater as
mixing water while the other two RC beams usedseawater, which will be termed as “freshwater beam”
and “seawater beam”, respectively. The seawaterused was obtained near seashore at waist-deep withsalinity of 30.2 ppt. Other components such as sizeof aggregates, size of steel reinforcing bars, type of
cement, and water to cement ratio were held
constant to make the beams identical except for thewater used. The diameter of the longitudinal steel
reinforcement is 8mm and the stirrup is 6mm. The
cross-section detail of the beam is shown in Fig, 1
and the longitudinal dimensions and reinforcing
details of the beam is shown in Fig.2.

Fig. 1

Fig. 3

Experimental test setup of RC beam

Macrocell Corrosion Test
For the macrocell corrosion test, rectangularprism or block specimens measuring 40mm by
40mm by 160mm were used. The water cement ratio
used in making the specimens is 0.5 and the cementsand ratio is 1:2. Fly ash as partial substitute forcement at 30% and 50% by weight was implemented.
The seawater used had a salinity of 30.6 ppt. ASTM
Type 1 Portland cement was used in combination
with class F fly ash. Presented in Table 1 are thespecimen codes assigned for the different type of
specimens. The specimens were cured in either
freshwater or seawater, but the macrocell corrosion
test was done only for the specimens that were cured
in seawater. To provide more information about theeffect of seawater on mortar, compressive strength
tests were conducted at the 7th and 28th day age ofmortar.

Cross section of the RC beam specimens
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Table 1 Codes used for specimen
Specimen
Code
FA0FW-FW
FA30SW-FW
FA50SW-FW
FA0FW-SW
FA30SW-SW
FA50SW-SW

Fly ash(FA) %
0
30
50
0
30
50

Mixing
Water
FW
SW
SW
FW
SW
SW

Cold-joints are incorporated in the specimens toprovide a possible passage for the seawater used incuring. This will provide additional chloride ions toreach the steel aside from the ones that are alreadypresent in the mortar. The high alkalinity of themortar creates a thin layer of iron oxide thatprovides resistance to further oxidation by
preventing oxygen from reaching the steel [10].
However, the introduction of chloride ions, oxygen
and water into the mortar destroys this protectiveoxide layer.
As mentioned earlier, macrocell corrosion
monitoring was done only to steel in specimens
cured in seawater. A zero resistance ammeter (ZRA)
was used to measure weekly the macrocell current(refer to Fig. 4). Then the macrocell current densities
were calculated from the measured macrocell
currents. Macrocell corrosion current is defined as
the total electric current flowing through all
segmented steel bars in the mortar blocks taken as aunit. The macrocell current density formula is given
in Eq. 1 [11]:Curing
Water
FW
FW
FW
SW
SW
SW

Note: FW=Freshwater, SW=Seawater
For the macrocell corrosion test, reinforcing steel
bars, 12 mm in diameter, were arranged in mortar
block so that anode and cathode are spatiallyseparated resulting in a flow of electric current overthe spatial distance [9]. A 100 mm long deformed
bar was cut into three equal lengths and were placedin the mortar blocks as illustrated in Fig. 4. The bars
were cleaned by soaking them in 10% diammoniumhydrogen citrate to remove rust. Electrical wires
were soldered on both ends of the cut steel bars to beconnected to the ammeter that will measure theelectric current. The divided bars werelongitudinally joined together using epoxy. The
assembled steel bars were placed in the mortar block
maintaining a mortar cover of 10 mm from thesurface. Cold-joint was made in the mortar block toensure penetration of seawater. To do this, only halfof the mould was first filled with mortar. Then, themortar was allowed to set for a whole day before
filling the mould to its full capacity. Fig. 5 shows theresulting corrosion specimen with cold-joint. The
mortar blocks were then sealed with epoxy on all
sides except on the side nearest to the steel bar, theone with 10 mm mortar cover.

ai 

I i 1,i  I i ,i 1Si(1)where: ai = macrocell current density of steel
component i (A/cm2); Ii,j = macrocell corrosion
current from steel components i to j (A); and Si =surface area of steel i.
To evaluate the macrocell corrosion electricity, agraph is made by plotting the macrocell current
density against time. An example is shown in Fig. 6.
The macrocell current densities are plotted for aperiod of 8 weeks (56 days). The macrocell
corrosion electricity is obtained by integrating thearea under the curve in the graph shown in Fig. 6.

Fig. 4 Macrocell current density measurement [12]Fig. 6 Macrocell corrosion electricity [11]Fig. 5

According to Miyagawa et al. [12], the corrosion
rate may be evaluated as follows: If the maximum
corrosion electricity is below 20 Coulomb/cm2 in 56
days the corrosion rate is considered “low”, that is,
0.05 mm/year. If it exceeds 50 Coulomb/cm2 in 56

Corrosion specimen with cold-joint
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

days, the corrosion rate is considered “high”, that is,0.12 mm/year. He also predicted that for “low”
corrosion electricity in 30 years, the yield strength of
the reinforcing steel may decrease to about 70% of
the original strength, while for “high” corrosion
electricity, the yield strength may decrease to as low
as 35% of the original strength.

Table 2 Values from the test of RC beam specimens
At ultimate
condition(strain=0.003)
Ult. Load (kN)Deflection (mm)Mnexpt (kN-m)
Mncalc (kN-m)
Expt/Calc

TEST RESULTS AND FINDINGSAt the time of testing of the RC beam specimens,
the concrete strength was measured using concrete
cylinders. The average strength of concrete withfreshwater is 27.17 MPa and the strength withseawater is 23.94 MPa, indicating that that thecompressive strength of concrete with seawater is
11.88% lower than concrete with freshwater.
The yield strength (fy) of reinforcing bars
recovered from the tested RC beam specimens wasdetermined. Freshwater beams had an average
fy=499.5 MPa and seawater beams had fy=495.7
MPa. The difference is only 0.76% indicating thatthe strength of the steel reinforcing bars has not beensignificantly affected by the seawater. Hence, thedecrease in strength of the beam may be due only tothe slight decrease in concrete strength.
Fig. 7 shows the visual difference of the steel
reinforcement bars taken from the seawater beamspecimens and from the freshwater beam specimens.
Rust can be clearly observed on the steel
reinforcements from the seawater beam specimens
while no rust can be observed on the steel from the
freshwater beam specimens.

Fig. 7

Specimen TypeFreshwater
Seawater
beam
beam
42.11
39.54
0.986
1.113
6.84
6.42
6.72
6.45
1.018
0.995

50

Load (kN)

40
30

F0‐A

20

F0‐B
S0‐A

10
0

Fig. 8

S0‐B
0

0.001

0.002

Concrete compressive strain

0.003

Load-strain relationship of the RC beams

Comparing the nominal flexural strengths (Mn),the flexural strength of freshwater beams is higher
than compared to seawater beams as presented inTable 2. However, the difference between the twogroups is again very minimal. The percentage
difference is 6.14% only. The comparison between
experimental and theoretical nominal moments(Mnexpt, Mncalc) yielded very good agreement. The
theoretical values were calculated using the formulas
stipulated in the code (NSCP).
The test results from the loading test of RC beamspecimens indicate that there is very small differencein the structural performance between RC beamspecimens with freshwater and that with seawater.
The major effect is only in the corrosion of the steel
bars, which in the long run may contribute to thedeterioration of the structural integrity of the beams.
The macrocell corrosion rate evaluation of steel
in mortar provides an insight on the possible
corrosion of steel in beams with seawater andexposed to seawater environment. Fig. 9 shows themacrocell current density of the middle steel element
for each specimen type.
Although Fig. 9 does not consistently show
anodic or cathodic macrocell current densities, it is
only an indication that macrocell corrosion
measured is non-uniform. The anodic and cathodic
reactions may fluctuate throughout the investigation
period [8]. Based on corrosion rate calculation of
Miyazato [11] and Miyagawa et al. [12], themacrocell corrosion electricity may be calculated
from Fig. 9 and can be converted to macrocell

Steel bar from seawater beam (left), steel
bar from freshwater beam (right)

Tabulated in Table 2 are the important values
obtained from the test of beam, specifically at theultimate condition, that is, when the strain of
concrete reached 0.003. The average ultimate load
obtained from the freshwater beams is a little bit
higher than that of the seawater beams. The
difference is only 6.10%. The midspan deflection
was also almost the same for the two types of beams.
The difference is only 12.9%. The load-strain strain
curves of the tested beams are shown in Fig. 8.
Curves labeled starting in “F” are for freshwater
beams while those starting in “S” are for seawater
beams. It can be seen that the curves are almost
identical. Differences are very minimal.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

corrosion rate. It is evaluated for the period of 8
weeks (56 days), starting on the 98th-day up to 154thday of current measurement, when the current
measurements are significantly large.

Macrocell current density variations

Fig. 10 Macrocell corrosion rate of the specimens

Presented in Fig. 10 is the plot of the macrocell
corrosion rates of the mortar specimens for theinvestigation period of 8 weeks. The corrosion rateis calculated per period (per week) so that corrosion
development could be observed over theinvestigation period. The specimens without fly ash(FA0FW-SW) are observed to have the highest
corrosion rate. Moreover, the corrosion rate isconsistently increasing during the 8-week period andthe corrosion rate at the end of the 8-week period is
0.08mm/(8week) which may be projected to one
year as 0.51mm/year. For the specimen with 30% flyash (FA30SW-SW), the corrosion rate is lowest,
picking up only at the end of the 8-week period. The
corrosion rate at the end of the 8-week period is
0.01mm/(8week) or 0.09mm/year. The lower
corrosion rate of specimens mixed with fly ash canbe explained by the fine structure of fly ash
preventing the penetration of chlorides. However, inthe case of the specimen with more fly ash, that is, at
50% cement replacement (FA50SW-SW), thecorrosion rate turned out to be higher than thespecimens with smaller amount of fly ash. This
indicates that the amount of fly ash used as corrosion
countermeasure may have a limit and may be at
cement replacement lower than 50%. Furthermore, it
seems that using seawater as mixing water is a lesser
corrosion risk than exposing mortar to chloride-richenvironment. Moreover, the existence of cold-joints
may have also increased the corrosion activity as
surrounding seawater can easily penetrate the mortar.
Regarding the strength investigation of themortar specimens, the results of the compressive
strength test indicate the usual trend that thecompressive strength increases with time, as shownin Fig. 11. The strength increased from 7th-day to
28th-day. Furthermore, the compressive strength of
specimens mixed with freshwater exhibited higher
than those mixed with seawater. This is the sameobservation in the RC beam test. In general, theincrease in fly ash replacement percentage resulted
to the decrease in compressive strength of mortar,
which was similarly observed by Lim et al. [13].

Regardless of the mixing water, specimens cured inseawater resulted to higher 28th-day compressive
strength, except for the specimens with 50% fly ash
replacement. Results of this study corroborated thatmortars with fly ash immersed in seawater tend tohave higher compressive strength [14]. However, it
seems that the 30% fly ash replacement is the best
among the values considered because the increase instrength is higher when cured in seawater.

Fig. 9Fig. 11 Day 7 and day 28 compressive strengths
CONCLUSION
Rust was clearly observed on the steel
reinforcement recovered from the RC beamspecimens mixed with seawater. However, in termsof strength, the steel was not significantly affected.
Although there was a slight strength reduction in
concrete with seawater, in general, the seawater did
not have any significant effects on the flexuralstrength of the beam for the period covered in the
study. Since the strength performance of RC beams
with seawater was not significantly affected,
seawater may be used in short term general andminor construction purposes. However, the behavior
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GEOMATE - Mie, Japan, Nov. 21-24, 2017of reinforced concrete with seawater must still be
studied further on a long-term basis.
To provide insights on the effects of seawater on
the corrosion of steel reinforcement in concrete, theeffects of seawater and fly ash to the macrocell
corrosion behavior of reinforcement in mortar were
investigated. Rectangular prism mortar specimens
with segmented steel bars were used as specimens.
The macrocell corrosion currents were measured
every week for a period of 8 weeks in order tocompute for the corresponding macrocell corrosion
density and corrosion rates. From the results, thefollowing were concluded:
The specimens cured in seawater did not show
consistent anodic or cathodic current densities
throughout the exposure period, indicating nonuniform corrosion
Mortar specimens with fly ash were observed tohave very much lower corrosion rates comparedwith the ones without fly ash which can be explainedby the fine structure of fly ash that reduces theingress of aggressive elements. However, it wasobserved that less corrosion rate is obtained when
the cement replacement with fly ash is at 30% thanwhen the fly ash is at 50%.
Mortar specimens mixed with freshwater
resulted to higher strength both at 7th-day age and28th-day age. The compressive strength decreases as
the fly ash replacement percentage increases.
Regardless of the mixing water, mortar specimens
cured in seawater seemed to achieve higher 28th-day
compressive strength.

[4] Wegian FM, “Effect of seawater for mixing andcuring on structural concrete”, The IES Journal
Part A: Civil & Structural Engineering, Vol. 3,
No. 4, November 2010, pp.235–243.
[5] Olutoge FA and Amusan GM, “The effect ofsea water on compressive strength of concrete”,
International Journal of Engineering Science
Invention, Vol. 3, Issue 7, July 2014, pp. 23-31.
[6] Manmohan D and Mehta PK, “Influence of
pozzolanic slag and chemical admixtures onpore size distribution and permeability ofhardened cement paste”, Cement Concrete
Aggregates, Vol. 3, Issue 1, July 1981, pp. 63-7.
[7] Millard SG and Bungey JH, “In-situe
assessment of reinforcement corrosion in
concrete structures”, IABSE Report, 1989.
[8] Nanayakkara O and Kato Y, “Macro-cell
corrosion in reinforcement of concrete under
non-homogeneous
chloride
environment”,
Journal of Advanced Concrete Technology,
Vol. 7, No. 1, February 2009, pp. 31-40.
[9] Subramaniam K and Bi M, “Investigation ofsteel corrosion in cracked concrete: Evaluationof macrocell and microcell rates using Tafel
polarization response”, Corrosion Science,
Volume 52, Issue 8, August 2010, pp 27252735.
[10] Madlangbayan M, Otsuki N, Nishida T and
Baccay M, “Corrosion behavior of steel bar inchloride contaminated mortars with fly ash”,
Philippine Engineering Journal, Vol 26, No 2,
2005, pp. 13-24.
[11] Miyazato S, and Otsuki N, “Steel corrosion
induced by chloride or carbonation in mortar
with bending cracks or joint”, Journal ofAdvanced Concrete Technology, Vol. 8, No. 2,
June 2010, pp.135-144.
[12] Miyagawa T, Takewaka K, Demura K, Masuda
Y and Moriwake A, “Technical committee
report on the rehabilitation of concrete
structures” Proceedings of the Japan Concrete
Institute, Vol. 20, No. 1, 1998, pp. 39-48. (inJapanese)[13] Lim ED, Roxas CLC, Gallardo R and Otsuki N,“Strength and corrosion behavior of mortar
mixed and/or cured with seawater with various
fly ash replacement ratios”, Asian Journal of
Civil Engineering, (BHRC), Vol. 16, No. 6, Jan.
2015, pp 835-849.
[14] Donatello S, Palomo A and Fernández-Jiménez
A, “Durability of very high volume fly ash
cement pastes and mortars in aggressive
solutions”, Cement and Concrete Composites,
Vol.38, 2013, pp.12-20.

ACKNOWLEDGEMENTS
The authors would like to express their utmost
gratitude to the faculty members and staff of the
Civil Engineering Department of the De La Salle
University for their unwavering moral and technicalsupport. Appreciation is also due to students, friends,
families, relatives, and other DLSU personnel who
contributed in making the experimental tests
successful.
REFERENCES[1] NSCP 2010, “National Structural Code of thePhilippines 6th Ed.”, Chapter 4 – Structural
Concrete, Vol. 1, 2010, pp. 13-14, pp.
[2] Mohammed T, Hamada H, & Yamaji T,“Performance of seawater-mixed concrete in the
tidal environment”, Cement and Concrete
Research, Volume 34, Issue 4, April 2004, pp.
593–601.
[3] Otsuki N, Furuya D, Saito T, and Tadokoro Y,“Possibility of sea water as mixing water inconcrete”, 36th Conference on Our World inConcrete & Structures, Singapore, August 1416, 2011.
440

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A COMPARATIVE SETTLEMENT PREDICTION OF LIMESTONEBLENDED MATERIALS USING ASAOKA AND HYPERBOLIC
METHOD
Erica Elice Saloma Uy1 and Jonathan Rivera Dungca1
1
Civil Engineering, De La Salle University, Philippines
ABSTRACTThe construction industry in the Philippines is predicted to sustain its growth up to 2021 because of theinfrastructure plan of the government according to the Philippine Infrastructure Report. With this, the demand inconstruction materials would increase and as a result an increase in prices is expected. To address this problem,an alternative material must be explored. A promising material is limestone because it is abundant in thePhilippines. These materials can be used as a material for structural fill or embankment. In order to determine
the material’s possible use its capacity to withstand loads must be checked. In this study, its compressibility is
the main focus. Its consolidation parameters were first obtained by performing one dimensional consolidation
test. Limestone wastes were mixed with a conventional soil and it is proportioned at 0%, 20%, 40%, 60% and100%. After the consolidation parameters were determined, the data from the consolidation test were used to
predicting the settlement behavior of the material. The Asaoka method and hyperbolic method were used in theprediction and the results of both methods were compared. Based on the results, it was observed in the one
dimensional consolidation test, the limestone waste used had a minimal effect to the compressibility of theconventional material used. Lastly, the prediction from the hyperbolic method is larger for some mix proportions.
Keywords: Limestone waste, Asaoka Model, Hyperbolic Modelrate doubled since 2009 [5]. This trend could result
to an increase in the production of limestone wastematerial and this can also lead to a shortage instorage facility. Due to its abundance, possible usesof these materials are as a material for structural fillor embankment.
There were already several researches thatshowed the material’s potential as a construction
material. Limestone waste was used as an alternative
material for road based material and soil
stabilization. Based on their results, the use of
limestone waste improved the strength of the roadembankment and it was also found to be an
economical alternative construction material [6], [7].
Limestone wastes were usually mixed withconventional materials in order to determine themost suitable amount of limestone waste
substitution. It was found that a 50% blend oflimestone waste mixed with the conventional
material was able to produce the optimum strength[6]. Furthermore, limestone waste showed a very
high efficiency in improving weak soils and it canalso be used as a substitute for lime in soil
improvement for engineering construction [8].
However, there is a lack of knowledge on its
settlement characteristics. With this, it is theobjective of the study to evaluate the compressibilityof limestone waste. Limestone wastes were mixed
with conventional material and it is proportioned at
0% (L1), 20% (L2), 40% (L3), 60% (L4) and 100%
(L5). Its consolidation parameters such as coefficient

INTRODUCTION
In the recent Philippine Infrastructure Report of2017, strong growth in the construction andinfrastructure industry was predicted to occur in overthe next five years. The growth is due to thegovernment’s plans to improve transportation
infrastructure, residential buildings and social
infrastructure. Based on the report, the real growth
will reach 12.5% in-between 2017 and 2021 while
the average annual growth will reach 11.2% for theconstruction sector [1]. The Philippine Development
Plan was also launched in February of 2017. The
plan covers the year 2017 to 2022. The main goal of
the plan was to change the Philippine income trend
as an upper-middle-income country by 2022 [2].
With this shift, the compound annual growth rate
(CAGR) of the construction industry’s output value
is expected to rise by 9.79% [3]. The continuous
growth of the construction industry can result to anincrease in demand of construction materials.
According to the average construction cost forecastin the Philippines for 2016 to 2020, the average costof residential is expected to increase by 5.51% [4].
To address this problem, there is a need to explore
alternative materials. A promising material islimestone waste because it is abundant in thePhilippines. According to the 2013 Minerals
Yearbook, limestone quarry production in 2013reached at 73,359 thousand metric tons and it is thethird top quarried mineral commodity. Its production
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GEOMATE - Mie, Japan, Nov. 21-24, 2017of consolidation (Cv), compression index (Cc),
recompression index (Cr), coefficient of volume
compressibility (mv), overconsolidation ratio (OCR)
and preconsolidation stress (σ’c) were established by
performing one-dimensional consolidation test.
After the consolidation parameters were determined,
the data from the consolidation test were used in
predicting the settlement behavior of the material.
The Asaoka method and hyperbolic method wereused in the prediction and the results of bothmethods were compared.
INDEX PROPERTIESWASTES

OF

EXPERIMENTAL PROGRAM
Sample Preparation
The ash mixtures were prepared by moist
tamping. The target relative density is 90% to 95%.
In order to attain a fully saturated condition, thesamples were first soaked with distilled water for 16
hours. This was followed by adding distilled waterin the consolidation cell. It was made sure that thewater would reach the load cap to ensure a fully
saturated condition. The amount of distilled water
mixed with the sample is close to the value of the
optimum moisture content (OMC) as seen in Table 2.

LIMESTONE

Table 1. Index properties of limestone wastes

The limestone wastes used were from a quarryin Guimaras province in central Philippines. The
index properties of the five blends were tested
following American Society for Testing Materials
Standards (ASTM). Its index properties namely,
specific gravity (Gs), liquid limit (LL), plastic limit(PL), plasticity index (PI), maximum void ratio(emax), minimum void ratio (emin), maximum dry
density (ρdmax) and minimum dry density (ρdmin) aretabulated in Table 1. The index properties of L5
were compared with other existing studies. Only thissample was compared because the other samples
were blended with conventional material. The
conventional material mixed with limestone waste
was based on the requirements of the Department of
Public Works and Highways (DPWH) Blue Book.
The conventional material can be a common
material or rock. It must pass a sieve opening of 75
mm or 3 inches. The percentage passing must also
be less than 15 mass percent for the number 200
sieve or 0.075 mm opening. Lastly, the materialmust have a plasticity index less than 6 and a liquid
limit of less than 30 [9]. Based on the results ofexisting studies, the values of their specific gravity
for limestone wastes are 2.58, 2.65 and 2.59 [10], [7].
It can be seen that L5 has a value close to theirresults. For its plasticity, the limestone waste blends
tested are classified as samples with medium
plasticity [11]. On the other hand for other studies,
their limestone has very high plasticity having LL of
72%, PL of 53% and PI of 19%. The difference canbe due to the mineralogical composition, origin of
the material and its particle shape and size. The
effect of blending limestone waste with aconventional material can be seen in the results of
the index properties. When the amount of limestone
waste is greater the value of the specific gravity,
maximum dry density and minimum dry isdecreasing. For the result of liquid limit, plastic limit,
plasticity index, maximum void ratio and minimum
void ratio, it was observed that as the amount oflimestone is greater their values increased.

Index Property

L1

L2

L3

L4

L5

Gs

2.89

2.77

2.71

2.67

2.63

LL

13.73

14.2

15.82

17.29

19.7

PL

11.84

12.07

13.13

14.42

15.11
4.59

PI

1.89

2.13

2.69

2.87

emax

0.69

0.74

0.87

0.93

1.2

emin

0.32

0.37

0.43

0.48

0.76

ρdmax (g/m3)

2.18

2.03

1.89

1.81

1.49

ρdmin (g/m )

1.71

1.59

1.45

1.38

1.19

3

Table 2. Optimum moisture content (OMC) of
limestone wastes [6]
OMC (%)

L1

L2

L3

L4

L5

5.00

5.56

5.98

6.63

9.54

Consolidation Test
Consolidation test was performed in the study
under ASTM D 2435 Standard Test Method for
One-Dimensional Consolidation Properties of Soils.
The load increments implemented in the experimentwere 7, 12, 25, 50, 100, and 200 kPa. A seatingpressure of 7kPa was first applied before loading
was performed [12]. Reloading was also performedin the experiment and it was initiated at 200 kPa.
Reloading was performed until 7 kPa was reached.
The settlement was recorded every 0.1, 0.25, 0.5, 1,
2, 4, 8, 15, 30, 60, 120, 240, 480 and 1440 minutes.
The load was changed after 24 hours. For this study,
a total of 15 samples were tested. Each of thelimestone waste blends was tested three times.
OBSERVATIONAL METHODS
Observational methods or also known asgraphical method are techniques used to predict the
future settlement of a material. These methods use
field data or consolidation test data specifically theamount of settlement and time of settlement. Throughthese methods, uncertainties in soil variability,
magnitude and load distribution can be avoided [13].
Some of the widely adopted methods that produces
442

GEOMATE - Mie, Japan, Nov. 21-24, 2017

reasonable estimates are Asaoka method, hyperbolic
method and velocity method, just to name a few [14],[15]. For this study, Asaoka and hyperbolic method
were used due to its simplicity and accuracy.

Where
H = thickness of the stratum

Asaoka Method
The Asaoka Method is an observational methodthat utilizes the settlement data from the field or
either from a one-dimensional consolidation test to
predict the ultimate settlement (Sult) and thecoefficient of consolidation (cv) [15]. The onedimensional settlement (S) at a certain timeincrement (∆t) can be expressed as:
Sn  So   Sn 1

Fig 2 Settlement versus time under a constant timeinterval [18].

(1)Hyperbolic Method

Where:Sn = settlement at time t
Sn-1 = settlement at time tn-1
β = slope
So = intercept

The hyperbolic method is another observational
method that predicts the ultimate settlement of thesoil. It also uses the actual settlement data or onedimensional data in order to perform the prediction.
This method replaces the settlement curve with ahyperbolic curve [18]. The hyperbolic curve is atransformed plot of the settlement curve as seen in
Fig 3. The ordinate is the ratio of time to settlement
while the abscissa is time. When a fitted line is
introduced in the plot, the hyperbolic curve isdefined as [19]:The equation represents the linear trend line in an
Asaoka’s plot as shown in Fig 1. The figure is theplot of the settlements (Sn, Sn-1) having a constanttime increment (∆t). The plot is used to estimate theultimate settlement (Sult) by using the following
equation:

Sult So1 t   t
s

(2)

(4)

Where:
s = settlement at time t
t = time
β = slope
α = intercept
When time in Equation 4 becomes very large or it isapproaching infinity, the ultimate settlement (sult)can be predicted by [20]:Fig 1 Asaoka’s Plot [18].

lim s  limt Another method to estimate the ultimate settlement
is by drawing a 45 degree line on the Asaoka’s plot.
The intersection of both lines is the value of theultimate settlement [16]. Prior to creating the
Asaoka’s plot, the settlement must be obtained undera constant time increment (∆t) as seen in Fig 2. The
accuracy of estimation is dependent on the timeincrement employed [17]. The coefficient ofconsolidation (cv) can also be estimated by using thefollowing equation [18]:cv  

5 2 ln Ht12t  t1
 sult 

1



(5)

CONSOLIDATION PARAMETERS
The consolidation parameters for the limestone
wastes are discussed and presented in this section.
The Casagrande method was used to determine therecompression index (Cr), compression index (Cc),
preconsolidation stress (σ’c) and overconsolidation
ratio (OCR). The method uses the consolidation
curve in determining the consolidation parameters.
The typical result of the consolidation curve isshown in Fig 4. The recompression index is theslope of the recompression curve while the

(3)

443

GEOMATE - Mie, Japan, Nov. 21-24, 2017that contained 100% limestone waste. As seen in
Table 8, it has a higher σ’c which means it had
experienced a higher effective vertical overburden
stress in its loading history. Furthermore, Cc and
OCR is higher while Cv is smaller. In the study, theirlimestone wastes were classified as highly
compressible [7]. For this study, the limestone waste
tested was considered as very slightly compressible
based on values of the ratio of compression index
and the void ratio. More so, it is also considered tohave a very low compressibility based on the valueof its volume of compressibility. The difference inthe origin of the material can be the reason why the
results of both materials are different.

compression index is the slope of the normal
consolidation. The typical values for compression
index ranges from 0.1 to 0.8. While for therecompression index, it ranges from 0.015 to 0.35.
Both parameters can also be determined fromempirical formulas [22].The results are tabulated inTable 3. Based on the results, the indexes obtained
were smaller than the suggested values. This can be
due to the fact that the limestone wastes havemedium plasticity which means that it has a little
potential to compress. It was also observed that as
the percentage of limestone waste is increasing thecompression index is also increasing. Furthermore,these parameters are also used to classify the soil’scompressibility together with the initial void ratio as
seen in Table 4. Based on the values of the ratio ofcompression index and the void ratio, it implies thatthe limestone waste blends tested are very slightly
compressible. The range of values for thisclassification is 0 to 0.05.
The preconsolidation stress (σ’c) obtained fromthe consolidation curve has a value of 25 kPa for L1
and 50 kPa for L2 to L5. For the overconsolidation
ratio, larger values were observed for 7 and 12 kPa
On the other hand for 25 to 200 kPa, a decreasing
value was experienced. The samples for 7 to 12 kPa
except L1 at 25 kPa are overconsolidated while L1
at 25 kPa and L2 to L5 at 50 kPa are normallyconsolidated. The values of coefficient ofconsolidation (Cv) are tabulated in Table 6. The
parameter was obtained using the early stage log-t
method. From the results, no particular trend can beobserved. They are compared with the typical valuesof silts and clays. It was observed that 83.33% of thedata are within the range of the typical values. The
volume of compressibility is also obtained. Based on
the results tabulated in Table 7, the values are verysmall and when it was compared to the typicalvalues it was classified as a sample with very low
compressibility.

Table 3. Summary of results for Cc and Cr.
Compression Index (Cc)

Recompression Index (Cr)

L1

0.009

0.002

L2

0.015

0.004

L3

0.017

0.003

L4

0.024

0.003

L5

0.03

0.003

Table 4. Classification of soil compressibility.
Limestone Wasteeo

Cc

Cc/(1+eo)

L1

0.34

0.009

0.0067

L2

0.39

0.015

0.0108

L3

0.45

0.017

0.0117

L4

0.58

0.024

0.0152

L5

0.78

0.03

0.0169

Table 5. Summary of overconsolidation ratio (OCR)
Vertical Stress

250
200

OCR

σ'z (kPa)

L1

L2

L3

L4

L5

7

3.57

7.14

7.14

7.147

7.147

12

2.08

4.17

4.17

4.17

4.17

25

1

2

2

2

2

50

0.5

1

1

1

1

100

0.25

0.5

0.5

0.5

0.5

200

0.13

0.25

0.25

0.25

0.25

Table 6. Summary of coefficient of consolidation(Cv)

t-ti 150
s-si 100

Vertical Stress

β

50
0

Limestone Waste

α
0

1

2

3

4 5
t-ti

6

7

8

9

Fig 3 Hyperbolic Curve [21].
The limestone waste tested were compared toanother study were a road embankment wasconstructed over a limestone waste. Specifically,
only L5 was compared since it is the only sample444

Cv (cm2/sec x10-4)

σ'z (kPa)

L1

L2

L3

L4

L5

7

30.18

28.30

21.57

8.88

8.70

12

1.13

0.45

0.41

0.38

21.57

25

0.27

30.18

0.28

8.70

3.02

50

1.00

8.23

0.15

45.28

45.28

100

14.00

0.30

0.20

30.18

0.90

200

28.83

22.63

45.28

18.12

90.55

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Recompression Curve
Rebound Curve

Normal Consolidaiton Curve

void ratio, e

0.344

y = -0.0092x + 0.3545

0.342
y = -0.0016x + 0.3441

0.34
0.338
0.336

y = -0.0037x + 0.3424

0.334
0.332

0

0.5

1

1.5
logσ'z2

2.5

Fig 4 Typical result of the Consolidation Curve.
Table 7. Summary of volume of compressibility(mv)mv (mm2/kN)

Vertical Stressσ'z (kPa)

L1

L2

L3

7-12

2.0E-3

5.0E-412-25

4.0E-5

25-50

L4

L5

3.0E-32.0E-3

6.0E-4

3.0E-4

3.0E-48.0E-55.0E-4

1.0E-4

3.0E-4

5.0E-5

1.0E-42.0E-450-1007.0E-5

9.0E-5

3.0E-5

6.0E-52.0E-4100-200

1.0E-5

6.0E-55.0E-5

6.0E-5

1.0E-4decreased. This leads to the change in the value ofthe slope and the intercept as well. As seen in Table
10, a larger slope was observed for the 10 min. timeinterval and it continuously decreased when the timeinterval was increased. The coefficient ofconsolidation was also computed for each timeinterval and slope of each Asaoka’s plot. The
thickness used in the computation is the thickness ofthe sample which is 20 mm. The results aretabulated in Table 10 and it can be seen that for alltime increment, close values were computed from
L1 at 50 to 200 kPa and for L2 to L5 for all verticalpressures. For L1 at 12kPa for all time increment, alarger value was computed. The difference in results
can be attributed to the trend of deformation orsettlement the sample had experienced as it is being
compressed. Comparison was also made with Cv
from the early stage log-t method and the Asaoka’s
method. A large difference can be observed because
the early stage log-t method is a graphical methodthat uses the early stage of the consolidation curve
which can lead to a larger value of Cv.
Table 9. Ultimate settlement prediction using
Asaoka’s method at ∆t = 10 minutes.
Vertical Stressσ'z (kPa)

0%

20%

40%

60%

100%

7

0.06090.06090.06580.06710.0509120.19130.11930.29810.27080.209925

0.20250.18510.32300.29190.2050

Table 8. Consolidation parameters of otherlimestone waste [7].
Consolidation Parameter

Value

Cc

1.3

Cv

1.25E-04 to 2.33E-04 cm2/sec

σ’c

72 to 168 kPa

OCR

0.30 to 0.91

Sult (mm)500.20500.27950.36770.33040.3155100

0.26710.37270.40000.39380.4174200

0.32920.47200.48320.48940.6025

Table 10. Summary of coefficient of consolidation(Cv) using Asaoka’s method at various ∆t.

ULTIMATE SETTLEMENT PREDICTION
Two observational methods were used to predictthe ultimate settlement of the limestone wastes. For
the Asaoka’s method, the ultimate settlement waspredicted using 4 time interval and these are 10, 20,
30 and 40 minutes. This was done since the result ishighly dependent on the value of time incrementused. The Asaoka’s plot of various time increments
is shown in Fig. 5. It can be seen that the plots areoverlapping each other which means that theultimate settlement that will be predicted will havevalues that are in good agreement with each other.
The predicted ultimate settlement resulted to having
almost the same values for the time intervals 10, 20
and 30 minutes. A decrease by 0.01% to 0.39% was
observed for the 40 minutes time interval. The
summary of results for 10 minutes time interval istabulated at Table 9. The difference in results is
because as the time interval is being increased thenumber of data in the Asaoka’s plot is being∆t (min)Sampleσ'z (kPa)βCv (cm2/sec)

10

L1

50 to 200

0.8819

3.49

20

30

40

L2-L5

All

0.91952.33

L150 to 2000.7775

3.50

L2-L5

All

0.878

1.81

L1

12

0.803

2.03

L1

50 to 200

0.6888

3.45

L2-L5

All

0.8213

1.82

L150 to 200

0.6145

3.38

L2-L5

All

0.7703

1.81

For the Hyperbolic method, the hyperbolic
curve is shown in Fig.6. It can be seen that the ratioof time and settlement decreases as the pressure is
being increased. This was the behavior of the plot
for all the samples tested. The predicted ultimate
settlement for this method is tabulated at Table 11.
Comparing the results of the 2 observational
445

GEOMATE - Mie, Japan, Nov. 21-24, 2017

methods, it was observed that the predicted ultimate
settlement for the hyperbolic method is larger thanthe Asaoka’s method except for the ultimate
settlement for except for L1 at 100 kPa and L5 at 25kPa.

a mixture of limestone wastes and a conventionalsoil and they are proportioned at 0%, 20%, 40%,
60% and 100%. From the results of the onedimensional consolidation test, the blends are
considered to be very slightly compressible based on
the values of the ratio of compression index and thevoid ratio. More so, based on the values of thevolume of compressibility the blends are considered
to have a very low compressibility characteristic.
From these findings, it can be said that the limestone
waste used had a minimal effect to thecompressibility of the conventional material. With
this, the blends tested have the potential to be used
as a material for embankment. For the ultimate
settlement predicted using Asaoka’s method andhyperbolic method, these values can be used as areference for the performance of limestone waste
blends under a vertical stress of 7, 12, 25, 50,100
and 200 kPa.

0.25
0.2

Si (mm)0.15
45 degree line
10 min20 min30 min40 min

0.1
0.05
0

0

0.05

0.1
0.15
Si‐1 (mm)

0.2

0.25

REFERENCES

Fig 5. Asaoka’s plot of various time increments forL5 at 12 kPa.
18000

7kPa
12kPa
25kPa
50kPa
100kPa200kPa16000
time/settlement (min/mm)

[1]
[2]

14000
12000
10000

[3]

[4]

[5]

8000

[6]

6000
4000

[7]

2000

[8]

0

0

500

1000
Time (min)

1500

2000

[9]
[10]

Fig 6. Hyperbolic curve for L2.

[11]

Table 11. Ultimate settlement prediction using
Asaoka’s method at ∆t = 10 minutes.
Vertical Stress[12]

Sult (mm)σ'z (kPa)

0%

20%

7

0.06650.0844120.1969

25

40%

[13]

60%

100%

0.08120.08550.05370.12780.30130.27630.20050.20410.1866

0.32890.29240.208050

0.20610.28120.3727

0.33240.3886100

0.26380.38180.4074

0.39630.4270200

0.33090.4841

0.48650.49140.6106

[14]
[15]
[16]

[17]
[18]
[19]
[20]

CONCLUSIONS[21]

The limestone waste blends’ compressibility
characteristics were determined by performing onedimensional consolidation test. The blends tested are

[22]

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

HYPERBOLIC MODEL PARAMETERS OF PHILIPPINE COAL ASH
Erica Elice Saloma Uy1 and Jonathan Rivera Dungca1
1
Civil Engineering, De La Salle University, Philippines
ABSTRACTIn the 2016 Annual Energy Sector accomplishment report of the Philippine’s Department of Energy, power
generation in the Philippines relied on coal-fired power plant at 46%. An increase of 19.47% was observed from2003 to 2016. The increase in demand would result to an increase in production of waste material from thepower plant namely, coal ash. Furthermore, the disposal of these waste materials can be an issue because it cancause a shortage in storage facilities. To address this, there is a need to study on the possibility of reusing thesewaste materials. A probable use of the waste material is by using it as a construction material for roadembankments. In the Philippines some of these structures are constructed on areas exposed to seawater in orderto address traffic congestion. This study proposes to use coal ash as the material for road embankment. Triaxial
test under consolidated drained condition was performed considering the exposure to seawater. Three conditions
were implemented namely, no exposure, immediate exposure and prolonged exposure. Based on the results,
100% fly ash had the highest strength. Hyperbolic model was employed to simulate the material’s stress-strain
response. The hyperbolic model was chosen since it has the capability of predicting load-displacement behaviorof the waste material under monotonic loading. The Hyperbolic model prediction shows that the material canstill handle higher stresses. With this, the ash mixtures tested has a potential to be used as a construction material
for a road embankment.
Keywords: Coal Ash, Hyperbolic Model, Construction Material for Road Embankmentand structural fill [3], [4], [5], [7], [20], [21]. It wasproven that the partial replacement of fly ash to
cement can reduce the demand of water and it
improves the concrete’s workability. Furthermore,
due to its abundance it is an economical material
especially for road embankments and reclamation
projects [4], [5]. Bottom ash on the other hand wasfound to have similar performance when comparedwith typical highway materials. More so, it also
meets the conventional materials’ specifications andcan be used as subgrade and subbase [6]. To further
utilize these by-products or waste materials’
capability, mixture proportions were tested as apossible construction material for highway
embankments. A study investigated 3 mixture ratios
such as 50% fly ash and 50% bottom ash, 75% fly
ash and 25% bottom ash and 100% fly ash. Based on
their results, mixture ratio of 50% fly ash and 50%
bottom ash had the highest peak angle of internal
friction are suitable for highway embankments. In
addition, the results of the study were also in good
agreement with the strength and compressibility
specifications of a typical fill material [7]. Anotherstudy conducted a field performance investigation
on a 60% fly ash and 40% bottom ash mixture for aconstruction of an embankment. The construction
was monitored to determine the behavior andperformance of the material used. Results showedthat the ash mixture adopted is an acceptablematerial for embankment construction [3]. Although
there are several researches on the uses of coal ash,such as road embankment, there is still limited

INTRODUCTION
According to the Annual Energy Sector
accomplishment report of the Philippine’s
Department of Energy, power generation grossed at
42,700 Gigawatt hours (GWh) in the first semesterof 2016 [1]. Coal-fired power plant generated power
at 19,695 GWh. It was followed by renewableenergy, natural gas and oil-based power plant at
10,158 GWh, 10,141 GWh and 2, 705 GWh,
respectively. In the report, coal-fired power plantremains the major source of electricity at 46 %. In
the same year, coal production for the first threequarter reached 8.4 million metric tons (MMMT). In
the recent Summary of Installed Capacity,
Dependable Capacity, Power Generation andConsumption report of the Department of Energy
which was published in March 27, 2017, an increaseof 19.47% in contribution to the power generation
mix was observed from 2003 to 2016 [2]. The
increase in demand would result to an increase inproduction of waste material from the power plantnamely, coal ash. Furthermore, the disposal of thesewaste materials can be an issue because it can causea shortage in storage facilities such as ash pond.
Using coal ash as a construction material has been atrend in the construction industry due to its
abundance. The most frequently used coal
combustion by-products (CCB) or coal ash byproducts are fly ash and coal ash [3]. Fly ash has
been used as a material for cement, concrete andgrout production, road embankment, reclamation
447

GEOMATE - Mie, Japan, Nov. 21-24, 2017

knowledge on its performance when it is exposed tosea water. This scenario must be consideredespecially in the Philippines were roadembankments are now being constructed on bodies
of water, such as the sea, because of traffic
congestion. Some projects are the Manila-Cavite
Expressway (CAVITEX) and Cebu-Cordova Link
Expressway (CCLEX) [8], [9]. With this, there is aneed to study on the possibility of reusing thesewaste materials as a construction material for roadembankments exposed to seawater. It is theobjective of this study to determine the performanceof coal ash as a construction material consideringash mixtures such as 100% fly ash (S1), 100%bottom ash (S2) and 50% fly ash 50% bottom ash(S3). Consolidated drained triaxial test was
performed and the waste material will be exposed toseawater. The samples were exposed to seawater
under three conditions namely, no exposure (C1),
immediate exposure (C2) and prolonged exposure(C3). To simulate the material’s stress-strain
response hyperbolic model was employed. The
hyperbolic model was chosen since it has thecapability of predicting load-displacement behaviorof the waste material under monotonic loading.

EXPERIMENTAL PROGRAM
Sea water Preparation
The artificial sea water used in the experiment isprepared following ASTM D 1141 – 98 or “Standard
Practice for the Preparation of Substitute Ocean
Water”. The chemical compositions for the artificial
se water are tabulated in Table 2.
Table 2. Chemical composition of sea water
CompoundConcentration,g/L
NaCl
24.53
MgCl
5.2
NaSO
4.09
CaCl
1.16
KCl
0.695
NaHCO
0.201
KBr
0.101
HBO
0.027
SrCl
0.025
NaF
0.003
Ba(NO
9.94E-05
Mn(NO3.40E-05
Cu(NO3.08E-05
Zn(NO9.60E-06
Pb(NO6.60E-06
AgNO
4.90E-07

INDEX PROPERTIES OF COAL ASH
The coal ash used in the study is from a power
plant in central Philippines. The index properties of
S1, S2 and S3 are determined following theAmerican Society for Testing Materials and theresults are tabulated in Table 1. It can be seen thatall samples are non-plastic. The value of thespecific gravity of the ash mixtures are higher than
the recommended values ranging from 1.899 to
1.903 [10]. A possible explanation for the difference
is both materials came from a different coal-fired
power plant. For the results of S3, it is noticeable
that the values are in between S1 and S2.

2.08
-

2.25
-

2.11
-

1.75

0.94

1.14

The ash mixtures were prepared by moist
tamping. Instead of using relative density as thecontrolled variable for the initial target condition,
relative compaction was preferred to properly
simulate site conditions. A value of 95% relative
compaction was the target initial value in order tosatisfy the desired in situ condition [7], [11]. The
extent of sea water exposure for the experiment has
three conditions. The first condition (C1) has no sea
water exposure. Only distilled water was used andthe samples were soaked for 16 hours. The second
condition (C2) sample preparation is similar with C1.
Sea water exposure was performed duringconsolidation stage of the Consolidated Drained Test.
The third condition (C3) is when distilled water wascompletely replaced with artificial sea water both in
the sample preparation step and the consolidation
stage of the Consolidated Drained Test.

1.45

0.85

0.94

Consolidated Drained Test

9.9

13.94

11.7

36.6

15.85

27.1

ML

SM

Table 1. Index properties of ash mixtures
S1
S2
Index Property
Specific gravity(Gs)Liquid limit(LL)
Plastic limt (PL)Maximum void ratio(emax)
Minimum void ratio(emin)
Maximum dry unit
weight(γdmax) (kN/m3)
Optimum watercontent (ωopt) (%)
USCS

Sample Preparation

S3

Consolidated Drained Test or slow test was
performed in this study following British Standard(BS) 1377-8: 1990. Saturation, consolidation andshear are the stages in this test. For the saturation
stage, the sample must reach a fully saturated
condition before it is to be consolidated. To ensure afully saturated condition the B-value or the ratio of448

GEOMATE - Mie, Japan, Nov. 21-24, 2017

the change in pore water pressure and change in
confining pressure must reach a value greater than
0.95. For the consolidation stage, the confiningpressures (σ3) used are 50 kPa, 100 kPa, and 200 kPa.
For the shearing stage, a rate of loading of 0.05
mm/min was implemented. This was used for theproper dissipation of pore water pressure. Due to theslow rate, this stage normally performed for a
maximum of 7 hours and a minimum of 4 hours.
A total of 51samples were tested for this study as
shown in Table 3. It can be seen that sample S3 was
not tested for the C3 condition. During sample
preparation when the artificial sea water was mixed
with S1 some samples hardened into a rock-likestate. This made it difficult for S1 to be mixed with
S2.

deviator stress at failure. It can be used to define thefailure ratio together with the ultimate deviator
stress. The typical values for the failure ratio range
from 0.75 to 1.0 [16]. The failure ratio is defined as:
Rf 

Sea Water Exposure
C1

C2



C3

1   3

σ3 (kPa)
1

2

3

1

2

3

1

2

3

S1
S2

3
3

3
3

3
3

2
2

2
2

2
2

1
1

1
1

1
1

S3

3

3

3

2

2

2

-

-

-

Hyperbolic model or Duncan and Chang modelis an incremental stress-dependent model that isbased on the stress and strain’s hyperbolic
relationship (Stark). The soil model can simulate thenon-linear response of soil. It is also a variableparameter model and it is defined in terms of initialtangent modulus (Ei), actual deviator stress at failure(σ1- σ3)f and failure ratio (Rf) [12], [13]. The
parameters in this model can be determined by
performing a triaxial test [12], [13], [14]. From thevariables obtained in the model, prediction of loaddisplacement behavior of the soil can be performed.
The hyperbolic representation of the soil model has
the capability to yield acceptable results especiallyin cases under monotonic loading [14]. A typicalresult of this model is shown in Fig. 1. The
hyperbola in the figure can be mathematically
written as [12]:1Ei ( 1   3 )u

(2)



1


Ei (1   3 )u(3)Equation 3 presented is the modified format ofEquation 1. In Equation 3, initial tangent modulus is
the reciprocal of the y-intercept while ultimate
deviator stress is the reciprocal of the slope. In orderto perform the prediction of stress-strain behavior of
the soil, the primary loading modulus (K) andexponent number (n) must be also established. These
parameters are related to initial tangent modulus asseen in the following equation [12]:HYPERBOLIC MODEL1   3 ( 1   3 )u

The ultimate deviator stress, as seen in Fig. 1, is
asymptotic in nature. Its value when compared to thecompressive strength of the soil is always larger[14]. In order to establish the parameters needed in
the soil model, the stress-strain plot must betransformed in a linearized hyperbolic form. The
axial strain must be divided by the deviator stressand it is plotted against the axial stress. The
equation of the straight line in the transformed plotis [12]:

Table 3. Design of experiment

Ash Mixtures(1   3 ) f

Ei  KPa ( 3 Pa )n(4)

Where:
Pa = atmospheric pressure (Pa = 101.325 kPa)
Based on the study of Janbu, the increase inconfining pressure is proportional to the initialtangent modulus [14].

(1)Where:
ε = axial strain(σ1- σ3)u = ultimate deviator stressFig. 1 Hyperbolic model prediction typical result[12].
The parameters primary loading modulus andexponent number can be determined from a

The hyperbola produced by the model in Fig. 1 isacceptable only until point A. This point is the actual449

GEOMATE - Mie, Japan, Nov. 21-24, 2017

logarithmic plot of Ei /Pa against σ3/Pa. The plot islinearized in order to extract the mentioned
parameters. The equation of the straight line can be
written as follows [12]:weaker compared to S1. For S3, its values are in
between S1 and S2. For the results of C2, it can beseen that the values of the angle of internal friction
decreased for all ash mixtures but the values are still
within the typical values. The values for cohesion on
the other hand increased. This can be due to theeffect of sea water used in the consolidation stage.
For the results of C3, the angle of internal friction of
S2 is comparable to the results at C1. For cohesion,
it dramatically decreased and it is the smallest value
when compared to all the results.

E 
 
log10  i   log10  K   n log10  3 
 Pa 
 Pa 
(5)
The slope of Equation 5 is the exponent number
while the y-intercept is the primary loading modulus
when σ3/Pa is equal to 1.0. Once the hyperbolic
parameters are established prediction of the loaddisplacement behavior of the soil can be performedby using the following equation [12], [13]:1   3 

1
KPa ( 3 P a )n R f (1  sin  )2C cos   2 3 sin 

Table 4. Shear strength of ash mixtures.
Cohesion (kPa)
SeawaterAsh
Exposure
Mixture
C1
S1
38.53
8.65
S2
33.77
28.56
S3
38.94
8.13
C2
S1
31.95
33.32

(6)

Where:
C = cohesion
 = angle of internal friction

C3

The values of cohesion and angle of internal friction
can be determined by plotting the Mohr’s Circle.
The deviator stress from the stress-strain plot mustbe at the peak state. If peak state is not experienced,
the deviator stress at 15% of the axial strain can be
used.

S2
S3
S1
S2
S3

27.03
31.86
33.91
-

49.91
19.06
15.43
-

HYPERBOLIC MODEL PARAMETERS
The hyperbolic model parameters for ash
mixtures are tabulated in Table 5, 6, 7 and 8. In
order to determine these parameters, the stress-strain
plot was linearized as shown in Fig. 2. The plotshown is the typical result for the ash mixturestested. It was observed that as the confining pressure
increases the ratio between the axial strain anddeviator stress decreases. This can also lead to thedecrease in the value of the slope but the increase in
the value of the ultimate deviator stress. From thetabulated results, it showed that as the confiningpressure increases the ultimate deviator stress also
increases. Comparing the results of the three
conditions of sea water exposure, it was observedthat the exposure of sea water had an effect towards
the ultimate deviator stress of the ash mixtures.
Based on the results in Table 7, the values of C3-S2
at 50 kPa and 100 kPa are in between the results of
C1-S2 and C2-S2 under the same confiningpressure. For C3-S2 at 200 kPa the results are larger
than C2-S2 but smaller than C1-S2. At thisconfining pressure, the exposure to sea water
improved the strength of the ash mixture. When the
results of C1-S1 and C2-S1 were compared, it wasobserved that the values of ultimate deviator stressare larger for C2-S1 at 50 kPa and 200 kPa but asmaller value was observed for 100 kPa. For the
results of C1-S3 and C2-S3, it can be seen that theultimate deviator stress decreased due to sea water

SHEAR STRENGTH OF ASH MIXTURES
The shear strength of ash mixtures wasdetermined from the results of the Consolidated
Drained Test. The results are tabulated in Table 4.
The results were compared to the typical values ofprevious researches. The typical values for the angle
of internal friction and cohesion for silt is 30° to 35°
and 9 kPa, respectively. For silty sand, the typicalvalues for the angle of internal friction and cohesionis 26° to 35° and 50 kPa, respectively [17], [18],[19]. For S1 it was compared to the typical values ofsilts while for S2 it was compared with silty sand.
The results of S3 on the other hand were comparedto silty sand. For the results of the ash mixtures in
C1, it was observed that all the results are in good
agreement for cohesion. For its angle of internal
friction, the result of S1 is slightly higher than the
typical value by 10%. The increase was due to theamount of relative compaction which contributed tothe increase in strength of the ash mixture. It wasalso observed that S1 has a higher of value of angle
of internal friction compared to S2. This is because
the particle shape of the two was different. A flaky
particle shape was observed for S2 while a roundedshape was for S1. The particle shape for S2 is450

GEOMATE - Mie, Japan, Nov. 21-24, 2017

exposure. Comparing the results of the ash mixturesin each condition of sea water exposure, for C1 it
was observed that there is no particular trend when it
comes to the changes in the value of ultimate
deviator stress. On the other hand for C2, it wasobserved that S3 had the smallest values. Knowing
the values of ultimate deviator stress can serve as theupper limit or maximum strength of the ash
mixtures. There was no consistent trend observed in
the result of the ultimate deviator stress. This can be
due to the method of sample preparation since
preparing the exact replica of the relative
compaction is somewhat difficult. For the result of
initial tangent modulus, there is also no definite
trend. This parameter is highly dependent on the
behavior of the stress-strain results. When strain
hardening is more pronounced prior to failure thevalue of initial tangent modulus is smaller. Thisoccurred in C2-S2 at 50 kPa confining pressure. For
the failure ratio, it can be observed that almost all
the failure ratio is within its acceptable range which
except the result from C1-S2. Its value is 0.5335. It
was observed that for this ash mixture, the ultimate
deviator stress is high and its deviator stress at
failure is almost half of its value. This means that for
its transformed plot the slope is very steep. A steep
plot indicates that strain hardening was present in
the stress-strain diagram. Once the hyperbolic
parameters are established, prediction can now be
performed using Equation 6. The typical results areshown in Fig. 3 and 4. Three trends were observed
from the results. First, the prediction seemed lessaccurate as the confining pressure is increasing as
seen in Figure 3. This trend was observed for all
results in C1. Second, the prediction was in good
agreement with some parts of the stress-strain plot
such as the strain hardening portion and the behaviorof the plot until it reaches the ultimate shear strength
as seen in Figure 4. Third, the model cannot predictthe post peak strain behavior of the ash mixtures.
0.1

Deviator Stress, kPa

1200

ε/(σ1-σ3)

0.06

10
15
20
Axial Strain, mm/mm
Fig. 2 Typical results for linearized plot.

C1S2 predict 100kPa
C1S2 predict 200kPa

400
200
0

5

20

25

deviator stress, kPa

500
400
300
200

C2S2 actual 50kPa
C2S2 actual 100kPa
C2S2 actual 200kPa
C2S2 predict 50kPa
C2S2 predict 100kPa

100
0

0
5
10
15
Fig. 4 Hyperbolic prediction for C2-S2.
Table 5. Hyperbolic parameters for C1(σ1-σ3)ult

Ei

(kPa)

(kPa)

50

191.93

192.31(kPa)
217.390.9980100

398.15400.00625.000.9954200

619.39625.001000.00

0.991050

238.04238.10277.780.9998100274.24294.12181.820.9324200

666.871250.00

90.09

0.533550207.25208.33769.230.9948100

470.41476.19102.040.9877200

688.77909.09136.990.75765

σ3
(kPa)

S1

S2

S3

Rf

Table 6. Hyperbolic parameters for C2
Ash
Mixture

S2

25

S3

451

20

(σ1-σ3)fAsh
MixtureS1

5

C1S2 predict 50kPa

600

600

0.02
0

C1S2 actual 200kPa

10
15
Axial Strain, mm/mm
Fig. 3 Hyperbolic prediction for C1-S2.

0.04

0

C1S2 actual 100kPa

800

0

C2-S1
C2-S2
C2-S3

0.08

C1S2 actual 50kPa

1000(σ1-σ3)f(σ1-σ3)ult

Ei

(kPa)

(kPa)

50

239.77256.41(kPa)
416.670.9351100

305.66344.83126.580.8864

σ3
(kPa)

Rf

200

579.76666.67185.190.869650

244.62

270.2786.21

0.9051100

320.07344.83250

0.9282200

553.92666.67149.250.830950

181.76181.82370.370.9997100287.47333.33116.280.8624200

474.37476.19526.320.996225

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 7. Hyperbolic parameters for C3
Ash
Mixture
S2

σ3
(kPa)

(σ1-σ3)f(σ1-σ3)ult

Ei

(kPa)

(kPa)

0.9946can still handle higher stresses. The limitation of themodel is that it cannot predict the post peak strain
behavior.
Based on the results from theConsoldiated Drained test and Hyperbolic model,
they showed that the ash mixtures has a potential to
be used as a construction material for a roadembankment.
It is suggested that other percentage of ash
mixtures be tested in order to determine the mostsuitable ash mixture. It can be noted that the fly ash
specimen has a larger strength, increasing it might
improve the strength of the ash mixture.

Rf

50

187.66

188.68(kPa)
185.19100

248.44270.27129.870.9192200

586.24714.29153.850.8207

Table 8. Primary loading modulus and exponent
number for ash mixutures
Seawater
Exposure
C1

C2

C3

Ash
Mixture
S1
S2
S3
S1
S2
S3
S1
S2
S3

K

n

461.42
5.99
25.99
10.75
5.99
37.19
4.66
-

5.57
1.34
4.50
1.65
1.34
1.11
0.22
-

REFERENCES[1]

Department of Energy. (2016). 2016 major accomplishments. Retrieved
from
http://www.doe.gov.ph/sites/default/files/pdf/transparency/annual_report_
esar_2016.
[2]
Department of Energy. (2017). Summary of installed capacity, dependable
capacity, power generation and consumption report of the department ofenergy,Retrievedfromhttps://www.doe.gov.ph/sites/default/files/pdf/energy_statistics/summary_
2016_power_statistics_final_march_27_2017.pdf.
[3]
Yoon, S., Ph, D., Balunaini, U., Yildirim, I. Z., Prezzi, M., & Siddiki, N.
Z. (2009). Construction of an embankment with a fly and bottom ash
mixture : field Pperformance study, Journal of Materials in Civil
Engineering, 21, 271–278.
[4]
Yao, Z. T., Ji, X. S., Sarker, P. K., Tang, J. H., Ge, L. Q., Xia, M. S. & Xi,
Y. Q. (2015). A comprehensive review on the applications of coal fly ash.
Elsevier, Earth-Science Reviews, 141, 105-201.
[5]
Ahmaruzzaman, M. (2010). A review on the utilization of fly ash.
Progress in Energy and Combustion Science, 36(3), 327-363. Elsevier
Ltd. doi:10.1016/j.pecs.2009.11.003[6]Huang, W. H. (1990). The use of bottom ash in highway embankments,
subgrades
andsubbases.
Retrieved
fromdocs.lib.purdue.edu/cgi/viewcontent.cgi?article=1782&context=jtrp.
[7]Kim, B., Prezzi, M., & Salgado, R. (2005). Geotechnical Properties of Fly
and Bottom Ash Mixtures for Use in Highway Embankments, Journal of
Geotechnical and Geoenvironmental Engineering, 131(7), 914-924.
[8]
CAVITEX(2016).
Cavitexexpressway.
Retrievedfrom
http://cavitexpressway.com/[9]
Philippine News Agency (2017). Construction of CCLEX paves way for
morebridgeslinking
Visayasislands.
Retrievedfrom
http://news.mb.com.ph/2017/03/04/construction-of-cclex-paves-way-formore-bridges-linking-visayas-islands/[10] Antonio, O. V. M., & Zarco, M. A. H. (2007). Engineering properties of
Calaca Batangas bottom ash, 28(1), 37–56.
[11] Zabielska-Adamska, K. (2006). Shear strength parameters of compacted
fly ash–HDPE geomembrane interfaces. Geotextiles and Geomembranes,
24(2), 91–102. doi:10.1016/j.geotexmem.2005.11.006.
[12] Al-shayea, N., Abduljauwad, S., Bashir, R., Al-Ghamedy, H. & Asi, I.
(2001). Determination of parameters for a hyperbolic model of soils fromthe eastern province of Saudi Arabia. Proceedings of the Institution of
Civil Engineers. (4). 1-14.
[13] Stark, T. D., Ebeling, R. M. & Vettel, J. J. (1992). Hyperbolic stress-strain
parameters for silts. Journal of Geotechnical Engineering. 120(2). 420-441.
[14] Abdul-kareem, A. H. & Helal, A. (2007). Estimation of hyperbolic stressstrain parameters for gypseous soils. International Journal of Civil
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[15] Tatsuoka, F. & Shibuya, S. (1991). Modelling of non-linear stress-strain
relations of soils and rocks part 1, discussion of hyperbolic equation.
Seisan-Kenkyu. 43(9). 23-26.
[16] Chen, W. F. & Saleeb, A. F. (1994). Constitutive equations forengineering materials. Elsevier. 1. 517.
[17] Das, B. & Sobhan, K. (2014). Principles of Geotechnical Engineering
Sixth Edition, United States: Chris Carson.
[18] Geotechdata(2013).
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http://www.geotechdata.info/parameter/angle-of-friction.html.
[19] Geotechdata(2014).
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http://www.geotechdata.info/parameter/cohesion.html.
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International Journal of GEOMATE, 12(31), 9-15.

CONCLUSIONS
Ash mixtures were tested under Consolidated
Drained test. Three ash mixtures were considered
namely, 100% fly ash (S1), 100% bottom ash (S2)and 50% fly ash 50% bottom ash (S3). These ash
mixtures were exposed to sea water during thetriaxial test. This was done to determine the effect ofsea water towards the strength of ash mixtures.
Three exposures to sea water conditions were
simulated in the experiment namely, no exposure(C1), immediate exposure (C2) and prolonged
exposure (C3). Based on the results, the shear
strength of the ash mixtures are all within the typicalvalues and are considered to have sufficient strength.
For the exposure of sea water, it decreased thestrength but the values are still within the acceptable
limit. Among all the ash mixtures, S1 had thehighest strength. When 50% of S1 was mixed with
50% of S2 to form S3 it showed an improvement in
the strength of S3. Furthermore, it was observed thatthe exposure of sea water had an effect towards thevalues of the deviator stress at failure and ultimate
deviator stress of the ash mixtures. For the C2
condition, both values for S2 and S3 mixtures are
smaller compared to C1 and C3 condition. For thehyperbolic parameters, it can be seen that C1-S2 had
the highest ultimate deviator stress at 200kPa. The
value of the initial tangent modulus ranged from86.21 to 1000 kPa. The hyperbolic parameters wereused in predicting the stress-strain behavior of theash mixtures. The prediction shows that the material452

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EXPERIMENTAL STUDY ON MECHANICAL BEHAVIOUR
OF CONCRETE BEAMS WITH SHREDDED PLASTICS
Richard M. De Jesus1, Emmanuel Bastian Pelaez2, and Moises Carl Caneca3
1
Faculty of Civil Engineering in De La Salle University (Manila), Philippines
2–3
Undergraduate Student of Civil Engineering in De La Salle University (Manila), Philippines

ABSTRACTIn recent years, more attention is being paid to alternative disposal of wastes to lessen the harmful impact ofthese wastes to the environment. In the construction industry, alternative disposal of waste comes in the form ofutilization of waste as a substitute construction material. Plastic, typically in the form of plastic bags and bottles,
is one of the most abundant wastes in Manila, and, also among the most problematic when it comes to disposal
due to its non-biodegradable nature. Hence, more attention is given to alternative use of plastics as a substitutematerial in construction. In this study, experimental investigation was conducted to assess the performance ofconcrete beams with shredded plastics, sourced out locally, as one of its component as a partial replacement tofine aggregates. Strength properties of a concrete beam, in terms of compression, tension, and flexure, were done
for both plain concrete and concrete with shredded plastics. Results showed that concrete with shredded plastics
were significantly higher than that of plain concrete in terms of tension and compression strength. Flexural strengthof concrete with shredded plastic, though the difference were found to be statistically not significant, showedslightly higher strength than that of plain concrete. This study also showed the applicability of elastic flexural
theory to concrete beams with plastics as partial substitute to fine aggregates.
Keywords: flexural theory, beams with shredded plastic, alternative material, utilization of wastes

complicated, and would bring foul odor and eye sore.
Hence, most cities still preferred to have all wasted
hauled and disposed to a landfill located faraway.
The government needs help in combating waste
problem in the country. With regards to plastic in
particular, the construction industry has initiatedsome alternative means of disposing plastics byutilizing it as an alternative material in concrete
locally and globally. Several local studies had been
done to find an alternative use for plastics inconstruction [6] to [8].
Globally, studies about alternative use of plastics
had gained so much ground already. The studies of[9] and [10] have shown that plastics can be used inconcrete for gateway support, tunnel linings, light
precast elements, and road pavement applications.
Others have explored the possibility of using plastics
as partial substitute for sand in concrete for structural
applications in the hope that the application of thisventure can be extended to a wider range ofapplication. The study of [11] explored the influenceof using domestic plastic waste (polythene fibers) in
concrete using 0.5% plastic by weight of cement.
Results showed that an increase of only 3.84% wereobserved in compression of concrete cylinders while
split tensile strength gained only an increase of
1.63%. Based from [9], where they conducted a
critical review of recent studies regarding the use of
macro plastic fibers to reinforce concrete, they found
that: (1) macro plastic fibres decreases the

INTRODUCTION
There is a constant, now an increasing, demand
for alternative use of waste materials as its
management and disposal is worsening withincreasing population, continues development, andurban migration. Philippines has not been spared bythis and one of the top contributors to this problem inwaste disposal is plastics. According to [1], 16% ofwastes from Metro Manila are plastics. To makematters worse, Philippines is rated to be among theworst offender in terms of plastic waste disposal as it
was ranked 3rd among countries in Asia that disposes
plastic wastes into the ocean [2].
Apparently, there is an alarming call for a more
effective and environment-friendly disposal of plastic
wastes. Environmental Protection Agency (EPA)
estimated that 13% of total generated wastes is plastic[3]. Only 9% of the total generated plastic wastes(which are about 869,000 tons of plastic estimatedannually) are recycled based on [4].
The government, in order to address risingconcerns about plastic waste disposal andmanagement passed and implemented Republic Act
9003 or Ecological Solid Waste Management Act of2000. This law requires all barangay units to have its
own material recovery facility (MRF). However, theimplementation of such law had been difficult for
many local government units. As reported in [5],many cities find the construction of MRF to be costly,453

GEOMATE - Mie, Japan, Nov. 21-24, 2017that the composite section can be transformed into a
homogeneous one by transforming the shredded
plastics into a concrete equivalent. Aftertransformation, the elastic bending theory will beapplied to compute for flexural stresses or flexural
capacity. In this study, shredded plastics are
uniformly mixed in concrete during mixing, thus, it isassumed that plastics can be represented by a single
layer positioned along the centroidal axis. The
thickness of the plastic layer is measured, before
casting of concrete, by laying down all plastics
distributed uniformly in the mold which determines
the dimension of plastic in terms of height (orthickness). Modulus of rupture property, or the tensile
strength of concrete, is based from actual split tensile
test of concrete samples.
The area moment of inertia for the “transformed”
shredded plastics mixed into concrete is computed
based on the following equation:

workability of fresh concrete but limits plastic
shrinkage cracking; (2) it has no obvious effects oncompression and flexural strength; (3) and increases
ductility of concrete in post-crack region. Reference[12] investigated depolymerized PET plastics used as
an alternative binding material in concrete as a partial
substitute for Portland cement. Their study comparedengineering properties of concrete made up of several
variations of PET polymers. According to [13], it
investigated the performance of recycled PET fiber
reinforced concrete using 0.5%, 0.75%, and 1.0%
fiber volume fractions by testing its properties incompression, elastic modulus, and drying shrinkage
strain. They compared its performance to that ofpolypropylene (PP) fiber reinforced concrete. Theirstudy showed that compressive strength and elastic
modulus decreases with increasing volume of fiber.
However, use of fiber showed improve performanceagainst cracking due to drying shrinkage. Also,
structural performance, ultimate strength, and relative
ductility were shown to be better with PET fiber
reinforced RC beams compared to those without
reinforcements. Reference [9] showed that at 1.5%
volumetric weight percentage, using PET as fiber
reinforcement, resulted to a significant increase inflexural strength.
This study focused on investigating the effect inconcrete of partially replacing fine aggregates withcombined shredded local plastic bags (low density
polyethylene,
LDPE)
and
plastic
bottles(polyethylene terepththalate, PET), in terms of its
mechanical behavior, particularly its flexural
behavior to explore the suitability of its application tobeam members. It also investigated the applicabilityof classic elastic flexural theory to concrete withshredded plastics in conjunction with thetransformation procedure as suggested by [14].
Theoretical and experimental estimate of flexural
cracking capacity is also assessed.

‫ܫ‬௣௟௔௦௧௜௖ =௡ ௫ ௕௧ యଵଶ

(1)where Iplastic = area moment of inertia of a single layerof plastic transformed into concrete, n = modular
ratio, b = width of beam, and t = 10mm, the measured
equivalent thickness of plastics.
The inertia of the whole section, based on thetransformed section, is computed as the sum of the
moment of inertia of concrete and (transformed) thatof transformed plastic. Flexure formula is thenapplied to determine flexural stresses.
The following assumptions were further made forthis study; (1) the modulus of elasticity for concreteis 4700 √fc’; (fc’ is taken from actual compressiontest); (2) the modulus of elasticity for plastic, which
typically is within the range of 2.76 – 4.14 GPa, istaken as 3.45 GPa; and (3) the modulus of rupture istaken equal to tensile strength of concrete from split
tensile test.
Theoretical deflection calculations are based on
the deflection of a simple beam subjected toconcentrated loads applied at third points, and isgiven by the equation:

THEORETICAL BACKGROUND
The elastic flexure theory is proven to be
applicable for homogenous materials that behaveselastically. Hence, for flexural capacity, cracking
moment, and deflection of plain concrete beam, theelastic theory of flexure is adopted in this study.
Motivated by the transformation proceduresuggested by [14] where they transformed FRPreinforced concrete into a single concrete materialusing the classic transformation of non-homogeneous
elastic beam, this study will follow the same forconcrete beams with shredded plastics in calculating
for flexural stresses, cracking moment, and deflection.
For concrete with shredded plastics, it is assumed

ߜ=

௉௔
ଶସாூ

(3‫ܮ‬ଶ − 4ܽଶ )(2)where: δ = deflection at midspan, P = applied load at
third points on a beam, a = 1/3 of span length, L =span length, E = modulus of elasticity of concrete, andI = moment of inertia of concrete and transformed
plastic. All specimens were loaded up to failure.

454

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1. Summary of mechanical properties of plain concrete and concrete with 0.5% shredded plastics
Specimen

1
2
3
AverageCompressive strength (MPa)Tensile strength (MPa)

Flexural strength (MPa)

0% plastic

0.5% plastic

0% plastic

0.5% plastic

0% plastic

0.5% plastic

21.81
21.95
21.71
21.82

22.28
22.21
22.23
22.24

3.92
3.95
3.98
3.95

4.00
4.49
4.25
4.25

5.44
5.58
5.67
5.56

6.01
6.29
6.88
6.39

EXPERIMENTAL SETUP
Table 2. Cracking moment of beams
Measured cracking moment (kN-m)
Specimen
0%
%
0.5%
%
plastic
diff
plastic
diff
1
2.09
6.05
2.56
7.10
2
2.04
8.19
2.50
4.45
3
2.10
5.34
2.51
5.11
Theoretical
2.22
2.39

Properties needed for the application of elastic
flexural theory on beams, with and without shredded
plastics, requires the determination of mechanicalproperties of concrete. Hence, compression test, split
tensile test, and flexural test, were conducted on
concrete specimens.
To represent the typical concrete mix compositionof beams being used locally, a water-to-cement ratioof 0.4 was adopted in all concrete specimens, and ACI
mix design procedure were adopted to determine theproportions. For concrete with shredded plastics,
0.5% plastics by weight of total samples was used. All
specimens were cured for 28 days through immersion
in a water bath. Concrete cylinders of size 100mm x
200mm, were casted for both plain concrete andconcrete with shredded plastics for a total specimenof 3 per test per type. Tests were done after 28 daysof curing and in accordance with [15] ASTM C39(compression test) and [16] ASTM C496 (tension)
procedures.
For flexural properties, 3 rectangular specimensof size 100mm x 100mm x 530mm were prepared foreach type and tested after 28 days of curing. Testing
were done in accordance with [17] ASTM C78(Flexural strength of concrete using simple beam withthird-point loading). To measure deflection, a LVDT
(displacement transducer) was attached at midspan of
the specimen, and successive deflections wererecorded.

Comparison between cracking moment capacityof plain concrete and concrete beam with plastic
showed an increase in capacity for beams withplastics. Statistical test showed that this increase issignificant.
The gap between theoretical deflection andmeasured deflection was overwhelmingly large,
around 250%. As shown in Eq. (2), the theoreticaldeflection is calculated based on a transformed
section with modulus of elasticity (MOE) estimatedto be 4700√fc’. This MOE is a code prescribed
equation and fc’ is the compression strength from
actual tests. The rest of the parameters in Eq. (2) aredependent on the dimension of the section so the gap
points out to MOE as the cause of the discrepancy.
This, however, was no longer investigated by thisstudy.

deflection (mm)2.4DATA AND ANALYSIS
Mechanical properties, in terms of compression,
tension, and flexure, derived from experiments forboth plain concrete and concrete with shredded
plastics, are presented in Table 1. Statistical test for
all mechanical properties have shown that thedifference in values between plain concrete andconcrete with plastics were not significant. Hence,experimentally, addition of shredded plastics inconcrete up to 0.5% does not have a detrimental
impact to the mechanical properties of concrete.
Flexural behavior of beams made up of plain
concrete and concrete with plastics were investigatedfurther by determining the cracking moment (Table
2).

2.0
1.6
1.2

S1
S2
S3

0.8
0.4
0.0
0.0

5.0

10.0

15.0

20.0

25.0

load (kN)
Fig. 1 Load v. deflection for plain concrete beam
Plot of deflection of both beams with plain concreteand concrete with plastics exhibited a linear behavior
up to failure. Deflection capacity of beam with plastic
was higher (~1.9mm) compared to that of plain
concrete beam (~1.5mm).
455

GEOMATE - Mie, Japan, Nov. 21-24, 2017as exhibited by Fig. 1 and 2. For both beams, the one
with plain concrete and the one with concrete withplastics, deflection exhibited a linear behavior when
loaded up to failure. Measured deflections, for bothbeams, also showed comparable results withdeflection of beams with plastics achieving a slightly
higher value than that of plain concrete beam.

deflection (mm)

2.4

2.0
1.6
1.2
S1
S2
S3

0.8
0.4

REFERENCES[1] DENR (2015). Retrieved on October 19, 2015
from http://newsinfo.inquirer.net/42317/metromanila-produces-a-fourth-of-philippinegarbage.
[2] Jambreck, L. (2015). Worst Plastic offenders.
Retrieved from http://www.motherjones.com/
environment/ 2015/ 02/ocean-plastic-wastechina.
[3] Environmental Protection Agency (2010).
Municipal Solid Waste Generation, Recycling,
and Disposal in the United States: Facts andFigures for 2010. Retrieved September 29, 2015
from: http://www.epa.gov/epawaste/nonhaz/
municipal/pubs/msw_2010_rev_factsheet.pdf.
[4] National Environment Agency (2014). Waste
Statistics and Overall Recycling. Retrieved
September 29, 2015 from: http://www.nea.
gov.sg/ energy-waste/waste-management/wastestatistics-and-overall-recycling.
[5] Ranada, P. (2014, April 25). QC gov’t: Garbage
law too difficult to implement. Rappler.
Retrieved on June 5, 2017 from http://www.rappler.com/science-nature/environment/
56378-qc-garbage-management-difficult.
[6] Cuartero, M., Villanueva, P., & Oreta A. (2016).
Effects of Plastic Wastes as Partial Aggregate
Substitute to Concrete Hollow Blocks.
Conference Proceeding. Workshop on the
Utilization of Waste Materials, University of thePhilippines, Diliman, QC.
[7] Alcantara, J. Ayala, P., Santos, V. Yao, E. &Lejano, B. (2016). Effects of Fire on theCompressive Strength of Concrete Hollow
Blocks Mixed with Plastic Waste Aggregates,
Conference Proceeding. Workshop on the
Utilization of Waste Materials, University of thePhilippines, Diliman, QC.
[8] Benedicto, M., Eusebio, M., Granada, J., Tuazon,D., & De Jesus, R. (2016). Investigation ofStrength and Durability of Paving Blocks Madeof Non-Biodegradable Household Waste asPartial Substitute for Fine Aggregates.
Conference Proceeding. Workshop on the
Utilization of Waste Materials, University of thePhilippines, Diliman, QC.
[9] Yin, S., Tuladhar, R., Shi, F., Combe, M.,
Collister, T., & Sivakugan, N. (2015). Use of
macro plastic fibres in concrete: A review.
Construction & Building Materials, 93, 180-188.

0.0
0.0

5.0

10.0

15.0

20.0

25.0

load (kN)
Fig. 2 Load versus deflection for concrete beam withplastics
CONCLUSION
Waste disposal and management is spiraling outof control in response to country’s development. The
construction industry is in a perfect position to aid inthis problem by utilizing waste as alternative
construction material. As shown in this study, plastic
waste was incorporated as component of concrete. Its
mechanical properties were investigated.
It can be seen that all mechanical properties haveshown an increase for concrete with shredded plastics
compared to plain and summarized as follows:- compressive strength: 22.24 MPa v 21.82 MPa;
- tensile strength: 4.25 MPa v. 3.95 MPa;
- flexural strength: 6.39 MPa v. 5.56 MPa;
Though, statistical test showed that the increase was
not significant, this increase in mechanical strength isa testament that the use of shredded plastics, as apartial substitute, up to 0.5% by weight is not
detrimental to the strength properties of concrete.
Improvements were also observed in flexural
behavior of beams with shredded plastics, in terms ofcracking moment (2.52MPa v 2.07MPa) anddeflection. Statistical test showed that the increase inthese properties were significant compared to that ofplain concrete.
Another important finding from this study is thecomparison between the computed values of cracking
moment for concrete with shredded plastics using theclassical elastic flexural theory and transformation of
concrete with plastics following the procedure
adopted by [14]. The agreement between
experimental and numerical results have shown amaximum difference of only 8.2% for cracking
moment implying that the applicability of elastic
flexure theory, and that of transformation by [14] canbe extended to concrete with shredded plastics.
The deflection needs to be investigated further asdisparity between theoretical and measured values
was large. On the other hand, consistency wasobserved in terms of measured deflection for beams
456

GEOMATE - Mie, Japan, Nov. 21-24, 2017[10] Ochi, T., Okubo, S. & Fukui, K. (2007).
Development of recycled PET fiber and its
application as concrete-reinforcing fiber. Cement& Concrete Composites, 29(6), 448-455.
[11] Kandasamy, R., & Murugesan, R. (2011). Fibre
Reinforced Concrete using Domestic Waste
Plastics as Fibres. ARPN Journal of Engineeringand Applied Sciences, 6(3), 75-82.
[12] Mahdi, F., Abbas, H., & Khan, A. (2013).
Flexural, shear and bond strength of polymer
concrete utilizing recycled resin obtained frompost-consumer PET bottles. Construction and
Building Materials, 44, 798-811.
[13] Kim, S., Yi, N., Kim, H., Kim, J. & Song, Y.
(2010). Material and structural performance
evaluation of recycled PET fiber reinforced
concrete. Cement & Concrete Composites, 32(3),232-240.

[14] Mohamed, H., & Masmoudi, R. (2010). Flexuralstrength and behavior of steel and [14] FRPreinforced concrete-filled FRP tube beams.
Engineering Structures, 32, pp 3789-3800.
[15] American Society for Testing and Materials.
(n.d.). Standard Test Methods for Compressive
Strength of Cylindrical Concrete Specimens.
ASTM C39.
[16] American Society for Testing and Materials.
(n.d.). Standard Test Methods for Splitting
Tensile Strength for Cylindrical Concrete
Specimens. ASTM C496.
[17] American Society for Testing and Materials.
(n.d.). Standard Test Method for Flexural
Strength of Concrete (Using Simple Beam withThird-Point Loading). ASTM C78.

457

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PARAMETRIC STUDY OF RESPONSE OF BRICK MASONRY WALLTO OUT-OF-PLANE LOADING
Miroslav Mynarz1 and Lucie Mynarzova2
Faculty of Safety Engineering, VSB – Technical University of Ostrava, Czech Rep.; 2Faculty of Civil
Engineering, VSB – Technical University of Ostrava, Czech Rep.

1

ABSTRACT
Within the area of explosion prevention and protection, masonry buildings are taking into accountconsidering the danger of explosion of natural gas or other items. For favourable design or assessment ofmasonry wall exposed to the out-of-plane load, which involves also explosion, it is possible to calculate thestructure using some finite element model. Modelling and analysis of masonry seems to be complicated due totwo-component material with different properties and dimensions. Out-of-plane loading adds another issue to besolved. Therefore, it is necessary to perform a calibration to evaluate the dynamic properties of the structure. The
response of the finite element model is improved by predicting the parameter by performing a non-linear
structural analysis. The deformations obtained numerically were compared to that of experimental observations.
The experiments were carried out in one of the experimental galleries in the limestone pit. The study deals withthe response of the masonry separating walls at various thicknesses, mechanical properties or loading. This
contribution compares the effect of variability of particular parameters to the response of the walls.
Keywords: Brick Masonry, Separating Wall, Explosion, Dynamic Response, Nonlinear response
to be another suitable instrument for separating wall
design.

INTRODUCTION
Sorted by their purpose, underground premises
involve transportation structures, engineering
structures and others (water silo, silo gas, sewerage
plant, storage area etc.). Underground galleriesinterconnecting particular areas are designed withspecific aims mainly as transport and airing
connections. Purpose and lifetime of undergroundgalleries should be in balance with precautions givenon the basis of deep risk analysis. Leakage orformation of flammable gases in such areas certainly
represents high risk for interconnected undergroundlocations. Immediate presence of these gases could
cause the explosion when open flames or otherignition source are occur at the same time.
To prevent propagation and transfer of the
explosion, separating or dam walls are built in thegalleries. These structures separate two independent
areas with no need to pass through or they close
unused halls or premises. In the Czech Republic dam
or separating walls are usually built from masonry(Fig. 1) however other materials as plaster or fly ash
could be also used.
In the case of accidental event, e. g. explosion,these separating structures are subjected toconsiderable load therefore they should be designedwith sufficient resistance. For effective design andassessment of these walls, in-situ experiments
should be carried out to provide useful information
about the structures behaviour. Together with theexperiments, advanced numerical modelling seems

Fig. 1

View of the underground gallery.

EXPERIMENT VENUE
The experiments were carried out [1] in one of
the experimental galleries in the limestone pit inStramberk, Czech Rep. The galleries are used forresearch and tests in the field of explosion
prevention. There are three horizontal parts, two ofthem are parallel. Concerned gallery measures 300
m (Fig. 2) and its clear section is 10.2 m2 in testingpart.
Inside the gallery two separating walls were builtwith the distance of 5.7 m between them. Inside theconfined sector, steel frame was embedded inconcrete. Loaded structures are placed into thisframe with dimensions of 2200 x 2575 mm.
458

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 2

thicknesses are dealt with in this paper – 65 mm, 140
mm and 290 mm. This corresponds to thedimensions of used clay bricks (290 x 140 x 65 mm).
Their strength is denoted as P10 which corresponds
to the compressive strength of the unit 10 MPa;
density is considered as 1800 kg · m – 3 and flexuralstrength is 1.7 MPa. Compressive strength of used
cement-lime mortar is between 4 and 5 MPa after 28
days. Used strength characteristics of masonry
separating wall result from the standard Eurocode 6[3]. Other mechanical characteristics of theseparating walls are presented in other papers [1],[4]. The dimensions of the walls are approximately
2.2 m width and 2.5 m height, depending on usedmicromodel or macromodel and particular thicknessof the wall.
Each wall was modelled as restrained along all
four sides. The load on the structure was consideredboth as quasi-static action and as real time behaviour
measured in the gallery during explosion of
methane-air mixture [5]. Corresponding measured
load was used for the masonry structure. The
explosion pressure is acting like uniform continuous
load on the separating wall. For each separating wallof various thicknesses, different values of pressureload were considered according to conducted
experiments. Models of the masonry separating
walls were created in software ANSYS [6] as it isdescribed later in this paper.

View of the experimental gallery in
Stramberk.

There are two pipes with inner diameter of 800
mm at the edge of the barriers. The pipes provide
regulation of applied pressure by changing of their
free inner diameter. The confined sector and loaded
wall are shown in Fig. 3.

NUMERICAL MODELLING OF MASONRY
Fig. 3

Confined sector between barriers.

Numerical modelling of masonry brings several
issues to be solved. Masonry is a heterogeneous andanisotropic material composed of units (bricks,
stones) and mortar. These two components differ inmaterial characteristics, behaviour or dimensions.
Disposition of units in masonry in a regular pattern
or interface between brick and joint could be taken
into account as well. Common software usually offer
isotropic materials and necessity of simplified –homogeneous – model.
Masonry walls discussed in this paper weremodelled using two different approaches according
to [7], micromodelling and macromodelling.
Detailed micromodel (Fig. 4) consists of bricks andjoints. Dimensions and location of bricks correspondto real parameters of clay units. Layers of mortar(bed and head joints) are modelled between the
bricks. Two layers with different bonds are changed
regularly through the height of the modelled wall.
This micromodel could be useful for modelling ofdetails, for better understanding of local masonry
behaviour or for determination of homogenizedproperties of masonry. Density, Young´s modulus ofelasticity, Poisson´s ratio, eventually shear modulus
and others are defined for each material. Detailed
micromodel represents disposition of bricks in thebest way on the other hand it is also very

The gassed track is located opposite the loaded
wall and it is bounded by the dividing barriers anddiaphragm of PE sheeting. This sheeting is fixed byrubber hose to the gallery wall. Pressure tank withmethane stands out of the sector. Methane is dosing
into the confined sector in parallel with stirring themethane-air mixture. Two ways of stirring weresuggested: by ejector straight in the confined sector
or by ventilator outside the confined sector whichshould be connected by pipe with diameter of 150
mm. As ejector did not guarantee the homogeneityof the mixture, only ventilator is used for stirring.
During filling and stirring the mixture, methane
concentration is measured in different height levels
using single gas detectors. The way of ignition
affects the final explosion parameters. For theseexperiments, the electrical ignitor with the ignitionenergy of 80 J was chosen. The centre of theconfined sector, or alternatively the centre of backwall, was chosen as the ignition point. The explosion
pressure was recorded by two pressure transducers[2].
Experimental Parameters
The

separating

walls

of

three

different
459

GEOMATE - Mie, Japan, Nov. 21-24, 2017

computationally demanding. It is suitable mainly foracademic use or as the first-choice possibility for
subsequent calculations.

Fig. 4

Reinforcement could be also added. A non-linear
elasticity concrete model could be used for brittle
materials (concrete, ceramics), it is suitable mainly
for materials with high compressive load-carrying
capacity and low tensile strength.
In ANSYS “concrete model”, both crushing andcracking failure modes are included. The concretemodel assumes that behaviour is linear elastic until
the failure, than crushing or cracking could appear.
Three different colours (red, green, blue) are used
for the first, second or third cracks [11].
Tension cracks can occur in three different
planes of the element and they are illustrated by acircle outline in the plane of the crack, i. e.
perpendicular to the direction of the principal stressin one of the integration point of the element. In thecase that more than one integration point has
cracked, the circle lies in the average direction of all
cracked planes of the element. Cracking occurs
when the principal tensile stress in any direction lies
outside the concrete failure surface that is shown in
Fig. 6. Similarly, when all principal stresses arecompressive and lie outside the failure surface,crushing occurs.

Detailed micromodel.

In the case of macromodel, neither particularbricks nor mortar layers or their interface areconsidered. This model is created from one
composite (homogenized) material (Fig. 5) which
could be isotropic (simplified model) or orthotropic(different strength, stiffness, friction, displacement
along the cracks or other parameters could be
defined for direction parallel or perpendicular to the
bed joints) [8]. The masonry could be homogenizedon the basis of constitutive formulas (e. g.
modification of models for concrete) or using
homogenization techniques (including use of
empiric formulas or analysis of detailed macromodel
as in [9]). These models are not as precise as
macromodel (considering two different materials orunits disposition) but they are much lesscomputationally demanding, even for huge
structures, and they survey the stress distribution
through the whole structure or describe theinteraction between particular elements.

Fig. 5

Fig. 6

Homogenized macromodel.

Concrete failure surface [6].

Behaviour of the model is described, among
others, through uniaxial cracking stress, uniaxial orbiaxial crushing stress and shear transfer coefficients
which take into account sliding across the crack
face. Shear transfer coefficient for an open crack βvaries from 0 to 1. Zero value expresses smoothcracks with complete loss of shear transfer andnumber 1 represents rough cracks without loss ofshear transfer [12]. However, very low values (under0.1) do not need to lead to convergence. Sheartransfer coefficient for a closed crack β ranges from0 to 1 as well. Comparison of cracks inhomogenized macromodel is illustrated in Fig. 7.
For the illustrative example, both shear transfer
coefficients were chosen as 0.1 (left) or 0.9 (right).

The Concrete Model
For purpose of this paper, all mentioned walls
were modelled both as a micromodel and amacromodel. For non-linear solution, several
methods are possible. One of them considers the
Drucker-Prager plasticity model as it is mention for
example in [10]. In our case the “concrete model”
was studied. This approach of non-linear solution ofmasonry structures joins the finite element SOLID65
with the concrete material model available also in
ANSYS. The eight-node “reinforced-concrete”
element SOLID65 is used for three-dimensionalmodelling of solids. The concrete element SOLID65
is capable of treating the non-linear material
properties such as cracking in tension, crushing incompression, plastic deformations or creep features.
460

GEOMATE - Mie, Japan, Nov. 21-24, 2017

particular directions.

Fig. 7Illustrative examples of various shear
transfer factors.

Fig. 9RESULTS AND DISCUSSION

One of the advantage of the detailed micromodelwith separately created bricks and mortar is tomonitor only one material. Following detail (Fig. 10)shows cracks arrangement in mortar joints in the
middle of the wall.

Masonry wall under out-of-plane load(earthquake, wind, explosion) is subjected to flexure.
The cracks occur and develop depending on supportsof the wall. In our case, two-way spanning wall is
considered with all four sides restrained and it
undergoes biaxial bending. Therefore, resulting
crack pattern involves a combination of horizontal,
vertical and diagonal crack lines [13].
Display of the cracks when SOLID65 element isused could be highly advantageous. Partly, theoverview of general behaviour of the structure isgiven in relation to the presence of the cracks, andmoreover the load when the first indications ofcracks occur could be pointed out indeed.
Magnitude of pressure at the time of the first
cracks appearance is presented on the wall withthickness of 65 mm. The value of pressure load
perpendicular to the wall was 6.7 kPa. The first
cracks occurred in the middle of the wall at about 10% of the load (Fig. 8, left) which corresponds to thepressure of 0.7 kPa. After increase of applied load,cracks progressively spread to the corners of thewall. Later phase of cracks pattern at the pressure of
1.1 kPa is shown in Fig. 8, right. Together withcracks in the middle of the numerical model,
gradually developing cracks occur also along the
supports.

Fig. 8

Detail of crack pattern of homogenizedmacromodel.

Fig. 10 Detail of crack pattern in mortar joints in
micromodel.
Following
numerical
modelsillustrate
deformations of the wall of thickness of 140 mm.
Total value of displacement at micromodel (Fig. 11,left) was calculated as 24.8 mm. The other picture(Fig. 11, right) demonstrates deformations at
homogenized macromodel with result of c. 25 mm.
Both models are in close agreement with each otherand the results also correspond to the conducted
experiments.

Fig. 11 Total deformations, micromodel (left) andmacromodel (right).

The first cracks at 10 % (left) and 16 %(right) of applied pressure.

Detail of cracks in the middle of thehomogenized macromodel is presented in Fig. 9.
The first and the second cracks are outlined with461

GEOMATE - Mie, Japan, Nov. 21-24, 2017

value of dynamic response depends on tune of thestructure which is affected by its stiffness andweight. Fig. 14 presents the lowest natural vibration
modes of the separating wall. On the left side, the10th natural mode of homogenized macromodel of
the wall of thickness 140 mm is illustrated. 9thnatural mode of detailed micromodel of the wall of
290 mm is presented on the right side. Table 1
compares the natural frequencies of the walls createdas both micromodel and homogenized macromodel.

Dynamic LoadAt real dynamic load, besides dynamic part ofthe load self-weight is also applied to the masonry
separating wall. Such prestress prevents joints andbricks from formation and propagation of cracks.
Displacements along the cracks are also limited
regarding friction on cracks surface. Ultimate tensile
strength, crucial for masonry failure, is – at this typeof load – significantly lower compared tocompressive strength of masonry. Consequently, thecracks are formed even due to small tensile stresses[14]. The loaded wall is presented on the left sideand failure of tested wall is shown on the right sideof Fig. 12.

Fig. 14 Natural modes of vibration (left:
homogenized macromodel 140 mm, right:
micromodel 290 mm).
Tune of the structure is implied in character ofthe response. If time behaviour of positive phase of
the load is significantly longer than the lowest
natural vibration frequency, the structure response to
the explosion load corresponds to quasi-static
deformation of the structure.

Fig. 12 Masonry wall after explosion [2].
Fig. 13 shows time behaviour of deflection in the
middle of the tested partition wall in interaction withthe course of explosion load.

462

macromodel

micromodelAt dynamic action lateral to the centre-line of theplated structure of separating wall, this wall behaves
like a bending slab. Besides load characteristics,

micromodel

Modal Analysis

macromodelFig. 13 Measured time behaviour of explosion
pressure and deflection during experiment
investigation of the wall of thickness 65
mm [15].

for the wall of thickness
140 mm
290 mmmicromodel

1
2
3
4
5
6
7
8
9
10

Frequency
65 mm
macromodel

No. of eigenfrequency i

Table 1 Calculated natural vibration frequencies[Hz] of the separating walls

10.0
18.4
22.2
29.9
31.7
40.8
42.5
48.0
49.8
59.9

10.0
18.4
22.3
29.9
31.8
40.8
42.5
47.9
49.8
59.9

17.2
31.5
38.0
51.1
54.4
69.9
72.7
82.1
85.2
103.

21.2
38.6
45.9
61.2
65.6
82.3
85.9
95.9
100.3
118.5

48.1
85.2
97.5
127.6
138.5
151.6
159.6
164.3
174.1
188.9

47.4
85.4
96.6
127.3
138.7
151.3
157.7
162.0
174.3
187.4

GEOMATE - Mie, Japan, Nov. 21-24, 2017

reinforced and unreinforced masonry structures(in Czech). CEN 2005.
[4] Makovicka D, Explosion hazard to buildings
and design load parameters. In: Jones, N.,
Brebbia, C.A.: Structures Under Shock andImpact VI. WIT Press, Southampton 2000.
[5] Mynarzova L, Mynarz M, Study of the effectsof transient load on envelope structure Applied
Mechanics and Materials, 2014, Vol. 470, pp.
335-339.
[6] ANSYS® Academic Research, Release 12.1,
Help System, ANSYS, Inc.
[7] Lourenco PB, Computational strategies formasonry structures. Delft University Press,
1996.
[8] Brozovsky J, Jasek M, Mynarzova L,
Maluchova M, Numerical modelling of
historical masonry structures, Advanced
Materials Research, 2014, Vol. 1020, pp. 182187.
[9] Brozovsky J, Kalocova L, Materna A,
Constitutive modelling of structural masonry. In
Proceedings of VIII. Science conference,technical University of Kosice, 2007. pp. 21 –
25.
[10] Nguyen CT, Ha HB, Fukagawa R, Twodimensional numerical modelling of modularblock soil retaining walls collapse using
meshfree method, Int. J. of GEOMATE, 2013,
Vol. 5, No. 1 (Sl. No. 9), pp. 647-652.
[11] Brozovsky J, Konecny P, Mynarz M, Sucharda
O, Comparison of Alternatives for Remodellingof Laboratory Tests of Concrete, In Proceedingsof the Twelfth International Conference on Civil,
Structural and Environmental Engineering
Computing, 2009, paper 119.
[12] Kachlakev D, Miller T, Yim S, Chansawat K,
Finite Element Modeling of Reinforced
Concrete Structures Strengthened with FRP
Laminates,
Civil
and
Environmental
Engineering, Department California Polytechnic
State University, San Luis Obispo, 2001.
[13] Vaculik J, Unreinforced masonry walls
subjected to out-of-plane seismic actions,doctoral thesis, The University of Adelaide,
2012.
[14] Makovicka D, Kral J, Makovicka D, Jr.,
Selesovsky P, Brick Masonry Structure
Analysis to Gas Explosion on Partition Back
Side, Fire Prevention 2002, 1st Part, VSB-TU
Ostrava, pp. 221-230.
[15] Mynarz M, Zdebski J, Mynarzova L, Lepik P,
Response of masonry structure to the effects of
blast wave induced by deflagration process. In:
5.
Magdeburger
BrandundExplosionsschutztag. Magdeburg, 2017.

Relatively amplitude low frequency components ofmotion which corresponds to oscillation in natural
frequencies of the structure are superposed to its
response.
CONCLUSION
This contribution outlined possible numericalmethod for solution of masonry separating walls
used for partition of underground premises as the
explosion prevention. After description of theexperimental gallery and conducted experiment,
micromodel, macromodel and the concrete model
used in software ANSYS were presented and modal
analysis was performed. Nowadays non-linear
numerical calculations are often used for complex
engineering problems but it should be taken into
account that many input data are needed to be
discussed.
The lack of specific knowledge of the range ofvalues of shear transfer coefficients brings
requirements for more experiments as obtain data
could be used for further verification of numericalmodels. On the other hand, micromodels generated
from bricks and mortar joints are already in good
agreements with homogenized macromodel which
could reduce the time for creating the model andcomputations.
Separating walls as a way of explosion
prevention in underground areas could be designedwith the help of advanced numerical procedures on
condition that input data and used methods arechosen appropriately.
ACKNOWLEDGEMENTS
This paper was financially supported by the
project of grant ministry of interior the Czech
Republic under the Id. No. VI20152019047, entitled“Development of the rescue destructive bombs forthe disposal of statically damaged buildings".
REFERENCES[1] Makovicka D, Makovicka D, Jr., Dynamic
Response of Thin Masonry Wall Under
Explosion Effect. In: Jones, N., Brebbia, C.A.,
Rajedran, A.M.: Structures Under Shock andImpact VII. WIT Press, Southampton, 2002, pp.
47-56.
[2] Podstawka T, Janovsky B, Horkel J, Vejs L,
Pressure Fields Effects Modelling During
Explosions of Gases in Closed Buildings on
Engineering Structures, Fire Prevention 2001,
1st Part, VŠB-TU, Ostrava, CR, 2001, pp. 333340.
[3] CSN EN 1996-1-1: Eurocode 6: Design ofmasonry structures – Part 1-1: General rules for463

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

MACROCELL CORROSION ASSESSMENT OF STEEL IN
COLD-JOINTED CONCRETE MIXED AND CURED IN SEAWATER
1,2

Cheryl Lyne C. Roxas1 and Bernardo A. Lejano2
Faculty, De La Salle University – Manila, Philippines
ABSTRACTPrevious research works have been devoted to developing sustainable construction materials. This is due tothe potential risk of global warming resulting from the abuse and misuse of natural resources. Therefore, thisstudy aims to address this through the use of abundant and by-product resources in the production of concrete,
like seawater and fly ash. If these materials were proven comparable to conventional materials, then problems on
freshwater scarcity, fluctuating supply of cement and associated pollutants from its production can be addressed.
This research specifically concentrates on the effects of varying water to cement ratios and fly ash content on themacrocell corrosion behavior of steel in cold-jointed concrete. Ordinary Portland cement in concrete waspartially replaced with fly ash at 30% and 50%. Water to cement (w/c) ratios of 0.30, 0.35, 0.40, 0.45, 0.55 and0.60 were tested. Rectangular prism specimens were cast to monitor the macrocell corrosion activity of thereinforcements. Results have shown an increasing trend of corrosion rate with increasing w/c ratios regardless of
mixing water, with specimens mixed with seawater having higher values compared to freshwater. Generally, the0.30 w/c ratio resulted to the lowest corrosion susceptibility. In terms of fly ash content, it was found that
corrosion rate decreases with increasing fly ash percentage. Fly ash decreases the permeability of concrete, thus
making it less exposed to aggressive environments. Cold-joints showed evident corrosion effects as external
elements may penetrate through these planes of weakness in the concrete.
Keywords: macrocell corrosion, seawater, cold-joints, fly ash
areas, where obtaining freshwater might be difficult,
may benefit the most. However, the use of seawater,
particularly in the construction sector, is notpracticed because of its corrosion effects on
reinforced concrete structures.
Meanwhile, the Philippines primarily relies oncoal powerplants in generating electricity. With the
expected increase of 5.7% electricity consumption
on the average between 2015 and 2020, the country
is set to open 23 new coal-fired powerplants by 2020[3]. This increase in the demand for electricity
requires a corresponding increase in power
generation, thus, additional volume of fly ash is
produced. Disposal of this enormous amount of ash
becomes a problem to most companies in charge ofthe operations, coupled with the threat of leaching
heavy metals and other toxic chemicals. Therefore,
the use of fly ash as partial replacement to cement
can help address the management and disposal ofaccumulated fly ash. During the production of
cement, harmful gaseous substances are emitted into
the atmosphere, contributing to the global warming
effect. Hence, utilization of fly ash can also lessen
the amount of cement required in concrete, thereby
the reducing the demand for production andconsequently reducing pollutants.
The main objective of the study is to investigate
the effects of using seawater and fly ash in concrete
under the influence of cold-joints on a macrocell

INTRODUCTION
Concrete is one of the most widely-usedconstruction materials. The strength and durabilityof concrete are affected by the properties of its
constituents, mix proportions, mixing procedure,
curing method and exposure to environment. It is
primarily composed of cement, sand, gravel, waterand some chemical or natural admixtures. However,
due to the potential risk of global warming in theplanet resulting from the abuse and misuse of natural
resources, the availability of these components forthe next generation may be inadequate. Thus, anumber of research activities have been devoted todeveloping sustainable construction materials inorder to address this issue. This study focuses on theuse of abundant and by-product resources in the
production of concrete, specifically the use of
seawater and fly ash.
The United Nations Water reported that 1800
million people will be living in regions with absolute
water scarcity while two thirds of the world’s
population could be under water stress conditions by2025 [1]. Although the Philippines falls under the
little or no water scarcity category, it is close to thevulnerability state in terms of freshwater availability[2]. Thus, seawater which surrounds the Philippine
archipelago, may be used as an alternative tofreshwater. Moreover, people living near coastal
464

GEOMATE - Mie, Japan, Nov. 21-24, 2017

pores of the concrete as a result of hydroxide ions
(negatively changed) moving the cathode to anode,
and also ferrous ions (positively charged) movingfrom anode to cathode. The water in the concretepores consists of a dilute solution of alkali andcalcium hydroxide which serves as vehicle for ionicflow. The reaction of Fe2+ and OH- forms ferrous
hydroxide (FeOH)2 and with further combination
with oxygen results to an insoluble product called
rust. However, rust is only a byproduct of thecorrosion process while actual corrosion means
converting metal atoms to ferrous ions dissolved insurrounding aqueous solution.
The loss of metal during corrosion occurs at theanodic sites. The iron atoms are ionized to ferrous(Fe2+) which dissolves in the water solution
surrounding the steel. The electrons deposited on thesteel raise its electric potential and then flow to alower potential (cathodic site). At the cathodic site,
the electrons combine with dissolved oxygen andwater to form hydroxide (OH-) ions. The number ofelectrons accepted at the cathodic site must be equal
to the number of electrons given up at the anodic
site. Hence, two iron atoms must be ionized anddissolved at the anodic site for every dissolved
oxygen at the cathodic site. Therefore, for the
corrosion process to continue, oxygen and watermust be present at the cathodic site.
Depending on the different spatial location ofanode and cathode, corrosion of steel in concrete canoccur as either microcell or macrocell [6]. However,microcell corrosion of reinforcements must normallyco-exist with that of macrocell [9]-[10]. In microcell
corrosion, the anode and cathode are locatedadjacent to each other resulting to a uniform irondissolution over the whole surface [6]. This type ofcorrosion produces uniform removal of steel andcontains anodic and cathodic sites that are
microscopic in size [11]. It was found that microcell
corrosion is the major corrosion mechanism for steel
in concrete after 3 more than years of testing [12].
This type of corrosion is normally present inlaboratory tests on small samples of reinforced
concrete [9]. On the other hand, in macrocell
corrosion, there is a net distinction between the
corroding areas of the rebar and the passive surfaces[6]. Furthermore, macrocell corrosion further occurs
when the actively corroding bar is coupled toanother bar which is passive, which might be due toits different composition or because of different
environment [12]. Macrocells are probable on large
dimensions of real structures and often due to large
active reinforcement areas that are in contact with
passive areas [9].
Macrocell corrosion may be affected by the cover
depth and the properties or quality of concrete.
Increasing the cover depth resulted to lower the
corrosion rate in cracked concrete [13]. The cover
depth also increases the barrier to various aggressive

corrosion level. Cold-joints are planes of weakness
and discontinuity formed when there is a delay inplacement of two batches of concrete, i.e., theinitially placed and compacted concrete has started
to set before the next batch is delivered and placed.
Concrete may be difficult to cast monolithically at
one time. The delay may result from time gaps incasting or mixing; transportation of concrete fromready-mixed concrete plant to project site; extensionof the incomplete construction on next day andinadequate supply of concrete constituents [4].
These cold-joints may become the passageway for
aggressive elements that can corrode thereinforcements in concrete and may eventually leadto sudden failure of a structure.
The specific objectives of the study are:
∙ To determine the effect(s) of different water tocement ratios (w/c) on the macrocell corrosion
behavior of steel.
∙ To determine the effect(s) of different fly ash
replacement ratios on the macrocell corrosion
behavior of steel.
This paper is organized as follows: First, aliterature on corrosion behavior of steel in concrete
is presented in order to understand the process andsignificance of macrocell corrosion assessment. The
experimental set-up is discussed next, followed byresults and discussion. Finally, conclusions of theresearch are highlighted.
CORROSION BEHAVIOR OF STEEL IN
CONCRETE
The durability of concrete may be compromised
through alkali-aggregate reaction, sulfate attacks,
freeze-thaw cycles and corrosion, among others.
Corrosion of the reinforcing steel in concrete has
become a great concern as this may result to sudden
failure of structures. The high alkalinity of concrete(pH≈13) provides a thin oxide layer that protects therebar from chemical reactivity [5]. However, theprotective film around the reinforcing steel isdestroyed when sufficient chloride ions penetrate theconcrete and the pH of pore solution drops to low
values due to carbonation [6]. Chlorides may bepresent in the mixing water and aggregates of theconcrete at concentrations higher than 0.4-1.0% by
cement weight or may penetrate by through cracks
and construction joints. It was found that chloride
induced corrosion rate is higher than carbonation[7].
The corrosion of steel reinforcement in concrete
is an electrochemical process as described in [8].
During the corrosion process, two electrochemical
reactions occur simultaneously at two different sitesof the steel surface namely: the anodic and cathodic
reactions. For these reactions to proceed, electric
current must flow in the closed loop between the twosites. An external current also flows through the465

GEOMATE - Mie, Japan, Nov. 21-24, 2017

species and corrosion initiation time [14]. The waterto cement ratio significantly influence the macrocell
corrosion process [15]. A high water-cement ratio
leads to high permeability and a low concrete cover
reduces the time for corrosive substances to reachthe steel reinforcement [16]. This type of corrosion
can be further affected by a non-homogeneous
chloride environment and when cracks are inducedin the concrete surface [17]. Moreover, macrocell
pattern formation prevails and that corrosion rateincreases when w/c ratio is low and in the presenceof defects [7]. Macrocell corrosion investigation ofsteel in concrete under different w/c ratios and fly
ash content mixed with seawater was investigated inthis study. Furthermore, the influence of cold-joints
was also taken into account. These factors can createa non-homogeneous distribution of chloride ions that
may affect the anodic and cathodic transformation ofsteel through time. As fly ash complements thenegative effects of chlorides in the seawater by
converting larger pores to finer ones, the study
attempts to explain further their influence on amacrocell level.

exists between the elements except through the wires.
The cold-joint in the concrete was formed by casting
Section A first followed by Section B after 24 hours.
After demolding, each surface of the specimen will
be covered by epoxy except for the side with theconcrete cover of 10mm. This is to ensure thepenetration of outside elements through that surface
only. All specimens were then cured by total
immersion in freshwater and seawater. For purposesof comparison, control specimens with 0.50 w/c
ratio with and without cold-joint were also cast andcured in freshwater. Figure 1 shows the specimen
set-up.

EXPERIMENTAL SET-UP

Fig. 1

Material and Specimen Preparation

Measurement Methods and Computations

Ordinary Portland cement (OPC) Type 1 wasused as main binder. Cement was partially replaced
by weight with Class F fly ash at 30% and 50%.
OPC contained 20.70% silicon dioxide (SiO2),
5.00% aluminum trioxide (Al2O3), 3.36% ferricoxide (Fe2O3), 62.80% calcium oxide (CaO), 1.7
magnesium oxide (MgO), and 2.66% sulfur trioxide(SO3); while fly ash contained 53.30% SiO2, 29.10%,
Al2O3, 5.44% Fe2O3, 8.00% CaO, 3.70 MgO, and
0.80% SO3. W/C ratio was varied at 0.30, 0.35, 0.40,
0.45, 0.55 and 0.60. Freshwater/tapwater and natural
seawater were used as mixing water. The salinity ofseawater was measured to be 30.60 ppt.
Concrete mixing was done in accordance to
ASTM C192 (Standard Practice for Making andCuring Concrete Test Specimens in the Laboratory).
Rectangular prism concrete specimens of size
100mm height by 100mm width and 200mm length
were cast to investigate the macrocell corrosion
activity of the steel reinforcement. Three specimens
were cast for each type of specimen. Twelve
millimeter diameter deformed steel bars were used
as reinforcement. Segmented steel bars (around
60mm in length) were prepared to facilitate themeasurement of macrocell current flowing from oneelement to adjacent elements. Steel bars were
submerged in 10% diammonium hydrogen citrateprior to casting to ensure removal of surrounding
rust. Lead wires were soldered on both sides of eachsegment and then attached to one another by epoxy,making sure that no direct electrical connection

Macrocell currents passing through thesegmented steel bars were measured weekly using azero resistance ammeter. Macrocell corrosion
normally occurs in chloride-induced environment
and formed along crack and local patch repair areas[18]. Since seawater was used both for mixing andcuring concrete with cold-joints, more chloride ionsare present for macrocells to occur. Macrocells arecharacterized by pitting and consists of anodic areas
and large cathodic areas situated near or a few
distance away from anodes [18]. Formation ofmacrocells must be considered in designing
reinforced concrete structures in aggressive
environmental conditions.
The segmented steel bar facilitates themeasurement of the actual macrocell current passing
from a given element to the adjacent element [17].
Macrocell corrosion current is defined as the total
electric current flowing through all steel components
taken as a unit. This is given by Eq. (1) considering
Fig. 2 [7].

epoxy coating

100 mmcasting direction

segmented
steel

joint
A

B
200 mmElevation

100 mmCross-section

10 mmSpecimen set-up

I macro 

I i 1,i  I i ,i 1

(1)

Si

Where: Imacro = macrocell current density of steel
component I (A/cm2); Ii,j = macrocell corrosion
current from steel components i to j (A); andSi = surface area of steel i. For a corrosion density of466

GEOMATE - Mie, Japan, Nov. 21-24, 2017

100 µA/cm2, the corrosion rate of steel is equal to1.16 mm/year [7].

Fig. 2

Macrocell corrosion measurement
FW-freshwater; SW-seawater; NOCJ-no cold-joint;
WCJ-with cold-joint

RESULTS AND DISCUSSIONS

Fig. 3 Macrocell corrosion current density
variation of freshwater mixed specimens under
different w/c ratios

Effect of W/C Ratio
Three samples were cast to investigate themacrocell current variation in concrete specimens
under different w/c ratios. These currents were used
to compute for macrocell current densities of thesteel elements. Figures 3 and 4 show the macrocell
current density variation of freshwater specimens. A
uniform variation of macrocell corrosion throughout
the exposure period is not evident. The macrocell
current variation is acceptable if it behaves either
anodically or cathodically throughout the period
regardless of its magnitude [17].
Corrosion rates for freshwater and seawater
mixed concrete were calculated and presented inFig. 5 and Fig. 6, respectively. Generally, the values
increased with time. In addition, as the w/c ratio
increases, the corrosion rate also increases, except in
the case of 0.40 w/c ratio. This can be attributed tothe higher permeability associated with higher w/c
ratio. Higher w/c ratio leads to greater number andsize of pores which increased permeability. Increasein permeability means increase in the ingress ofexternal elements which then corrode the steel bar inconcrete. As expected, samples mixed with seawater
displayed higher corrosion rates. Figure 7 illustrates
the effect of cold-joints on corrosion. Samples withcold-joints mixed with seawater resulted to higher
corrosion rates. Clearly, the presence of cold-joints
resulted to an increase in corrosion activity sincesurrounding elements can easily penetrate thespecimen. At eight week, the 0.30 w/c ratio appeared
to be the least corrosive regardless of mixing water.

Fig. 4 Macrocell corrosion current density
variation of seawater mixed specimens under
different w/c ratios

Fig. 5 Corrosion rates of freshwater
specimens under different w/c ratios

467

mixed

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 6 Corrosion rates of seawater
specimens under different w/c ratios

Fig. 7 Effect of cold-joints on
specimens under different w/c ratios

Fig. 8

mixed

Effect of fly ash content on corrosion rate

CONCLUSION
This study highlights the utilization of fly ash
and seawater as components of concrete in order toaddress problems on coal ash by-product disposal
and global water scarcity. The effects of thesematerials, specifically on the macrocell corrosion
behavior of steel reinforcement in concrete withcold-joints were investigated.
Specifically, this study investigated the influenceof water to cement ratio and fly ash replacement
ratios to corrosion rate values. Segmented steel bars
facilitated the measurement of macrocell corrosion
current activities, with cold-joints acting as
corrosion catalysts. The following conclusions
summarize the results of this research:
1. Using seawater as mixing water showed anincrease in the corrosion rate of steel
reinforcement compared to specimens mixed
with freshwater. Curing specimens with seawater
greatly influenced the corrosion rate of thespecimens.
2. Specimens without cold-joints obtained lower
corrosion rates compared to those with coldjoints.
3. Corrosion rate increases with increasing w/c ratio.
A 0.30 water-cement ratio yielded the least
corrosion rate. It may be recommended in termsof the low susceptibility corrosion both for
freshwater and seawater mixed concrete.
4. Fly ash alters the normal characteristics ofconcrete when used as partial replacement tocement. It was found that the corrosion rate ofsteel decreases as fly ash content increases.
Specimens containing 30% and 50% fly ash inboth freshwater and seawater mixes gained anincrease in corrosion resistances. Fly ash
decreases the permeability of concrete thus
making it less exposed to aggressive
environments. Moreover, the fly ash content
caused lesser chloride intrusion to the specimens
during curing.

corrosion

Effect of Fly Ash Replacement Ratios
Figure 8 shows the corrosion rate with respect tovarying fly ash replacement ratios. Similar
increasing trends of corrosion values can beobserved in samples mixed with freshwater andseawater. Generally, those mixed with fly ash
exhibited lower corrosion rates. This can be
explained by the fine structure of fly ash that reduces
the ingress of elements, thereby improving thepermeability of concrete. This then delays theoccurrence of corrosion. However, 50% replacement
displayed higher value compared to 30%
replacement. It can also be seen that seawater adds
to the corrosiveness of the steel bar. Reinforcement
corrosion is initiated when chloride ions fromexternal environment penetrate the concrete andexceed the critical corrosion-inducing limit [19].
With the chloride content of seawater used for
mixing and curing, the electrochemical activity ofthe steel bars is further stimulated.

468

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Engineering Practice”, Great Britain: E & FN
Spon, 1997.
[9] Andrade C, Maribona I, Feliu S, Gonzales J, &Feliu Jr S, “The effect of macrocells between
active and passive areas of steel reinforcements”
Corrosion Science, 33(2), 1992, pp. 237-249.
[10] Ji Y, Zhao W, Zhou M, Mac H, & Zeng P,“Corrosion current distribution of macrocell andmicrocell of steel bar in concrete exposed tochloride environments”, Construction and
Building Materials, 47, 2013, pp. 104-110.
[11] Subramaniam KV & Bi M, “Investigation ofsteel corrosion in cracked concrete: Evaluationof macrocell and microcell rates using Tafel
polarization response” Corrosion Science, 52,
2010, pp. 2725-2735.
[12] Hansson C, Poursaee A & Laurent A,“Macrocell and microcell corrosion of steel inordinary Portland cement and high performance
concretes” Cement and Concrete Research, 36,
2006, pp. 2098-2102.
[13] Raupach M, “Corrosion of steel in the area ofcracks in concrete – laboratory tests andcalculations using transmission-line model”, In
C. Page, P. Bamforth, & J. Figg (Eds.),
Corrosion of Reinforcement in Concrete
Construction (pp. 13-23). Great Britain: Royal
Society of Chemistry, Information Services,
1996a.
[14] Shi X, Xie N, Fortune K, & Gong J, “Durabilityof steel reinforced concrete in chloride
environments: An overview”, Construction and
Building Materials, 30, 2012, pp. 125-138.
[15] Mohammed TU, Otsuki N, & Hamada H,“Corrosion of Steel Bars in Cracked Concrete
under Marine Environment”, Journal of
Materials in Civil Engineering, 15(5), October
2003.
[16] Millard S, & Bungey J, “In-situ assessment ofreinforcement corrosion in concrete structures”,
Zurich: IABSE Report, 1989.
[17] Nanayakkara O & Kato Y, “Macrocell
corrosion in reinforcement of concrete under
non-homogeneous
chloride
environment”
Journal of Advanced Concrete Technology, 7(1),February 2009, pp. 31-40.
[18] Raupach M, “Chloride-induced macrocell
corrosion of steel in concrete - theoreticalbackground and practical consequences”,
Construction and Building Materials, 10(5),1996b, pp. 329-338.
[19] Al-Attar TS & Abdul-Kareem MS, “Effect ofChloride Ions Source on Corrosion of
Reinforced Concrete”, Buletinul AGIR. 107112, 2011.

ACKNOWLEDGEMENT
The authors would like to thank Christian Huy
Dalangin, Jayson Marco Gonzales, John Christopher
Ilagan, John Chritopher Yu, Joseph Caderao,
Raphael Fernandez, Zer Ivan Santos, Juan Philippe
Toreja and Kelly Temew for the experimentationand testing. Appreciation is also extended to
Pozzolanic Philippines for providing the fly ash and
De La Salle University faculty and staff; and for thelaboratory equipment and facilities.
REFERENCES[1] UN Water, Retrieved July 07, 2014, from
United Nations Water International Decade for
Action:
Water
for
Life
2005-2015:
2014.http://www.un.org/waterforlifedecade/scarcity.shtml[2] IWMI, Water for food Water for Life: A
Comprehensive
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M, & Pedeferri M, “Mixed-in Inhibitors forConcrete Structures” In M. Raupach, B. Elsener,
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469

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

INFLUENCE OF PRECURSORS AND ACTIVATOR ON STRENGTH
AND POROSITY OF ALKALI ACTIVATED BINDERS
Nurulhuda Nadziri1,3, Idawati Ismail1 and Sinin Hamdan2
Department of Civil Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, 94300 Kota
Samarahan, Sarawak, Malaysia
2
Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Malaysia
Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
3International College of Advanced Technology Sarawak, 93350 Kuching, Sarawak, Malaysia
1

ABSTRACT
Pore structure plays an important role in controlling durability and strength of binding materials. The objectivesof this study are to characterize porosity and mechanical strength of alkali activated binders and to acquire themajor factor that governs the relationship between both properties. Pastes of binder based on POFA and fly ash
activated with sodium hydroxide (NaOH) and combination of NaOH with sodium silicate (Na2SiO3) were preparedand cured at 80°C for a duration of 7, 28 and 90 days. Mechanical strength was obtained at the same curingcondition while porosity was measured via capillary sorptivity test. Coefficient of permeability in alkali activated
POFA exhibits the highest porosity while fly ash showed the lowest, in which both types of precursor showed
increment in porosity when silicate activator was used. Therefore, there is strong evidence that the choice of raw
materials and activator play a major role in controlling pore structures of these materials.
Keywords: Palm Oil Fuel Ash, Fly Ash, Alkali Activated Binders, Porosity, Strength
capillary tension and strong hydrogen bonds to thecalcium silicate hydrates (C-S-H) [8], a major binding
product in the hydration of ordinary Portland cement(OPC) . The C-S-H layers consist of physicallyadsorbed water molecules and interlayer water
between the sheet structure. The third type of water isthe chemically bound water, which is part of thechemical structure of the hydrated phases. IUPAC
also classifies pores according to micropores (<2 nm),mesopores (2–50 nm) and macropores (>50 nm)
pores. The latter is generally used for porous
materials and is used in the present research.
Limited work has been done on the relationshipbetween capillary porosity and strength in activatedmaterials using POFA and fly ash as the main
precursors. Alkali activated POFA was reported toform binder product of calcium-silicate-hydrate (C-SH) [9] while a fly ash based pastes consists of a
sodium-alumina-silicate-hydrate (N-A-S-H) gel[10],[11]. Due to their differences in chemistry andbinding products, pore structures in these materials
need to be characterized in order to use for durability
purposes. Therefore, this study investigates pore
structures and strength development of POFA withfly ash activated using sodium hydroxide (NaOH) andthe combination of NaOH and sodium silicate(Na2SiO3).

INTRODUCTION
Production of ordinary Portland cement (OPC) is
responsible for the release of anthropogenic carbon
dioxide gas and the trend is expected to increase[1],[2]. Alkali activated binders are amorphousmaterials that have a potential as the alternatives to
OPC as cementitious binders. Industrial by products
such as fly ash and agricultural waste such as palm oil
fuel ash (POFA), rice husk, coconut pitch andsawdust will be used effectively as binders [3],[4].
Pore structure is one of the most important
properties that controls durability and strength. Water
absorption of the alkali activated concretes is much
lower compare to the traditional OPC concretes,
depending on hydration products of these materials[5]. The use of supplementary materials such as fly
ash and slag which densify concretes can arrest thepenetration of “water” to enter inside the materials.
Water in alkali activated binders does not present in asimilar manner of that in a Portland cement binders[6]. Porosity of cementitious materials depends on
many factors, such as curing conditions, use of
supplementary materials and types of binding gel.
Pores in a cementitious matrix can be classified invarious ways. One possibility is the classification as
gel pores (<10 nm), capillary pores (10 nm–10 μm)
and voids (>10 μm) [7]. Three types of water are
related to these types of pores, the pore water, issituated in the capillary pores which mainly govern
durability of binders from surrounding environments.
The interlayer water held by the gel pores due to470

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 2 Mix proportions and the water to solid
precursor ratio of the alkali-activated POFA/fly ash
binder.

EXPERIMENTAL METHODOLOGY
Materials Preparation
To prepare the alkali activated pastes, Palm Oil
Fuel Ash (POFA) from palm oil mill in Lundu,
Sarawak and fly ash from Sejingkat Fired Coal Power
Plant in Kuching were used as raw materials. POFA
was pre-dried at 100°C for 24 hours and sieved in 45
micron sieve to remove large particles and to ensure
good pozzolanic reactivity. Access carbon on POFA
was removed by calcination at 500°C in a furnace forapproximately two hours. The removal of excesscarbon and other unburnt organic materials containedin POFA is important to avoid their adverse effect on
finished product. Particle size of the raw materials
was analyzed using CILAS laser particle size
analyzer where d50 obtained for POFA and fly ash are
at 16.7 μm and 9.67 μm respectively.
The chemical composition of POFA and fly ash
was shown in Table 1.

Binder ratio(wt.% POFA/wt.% fly ash)
100/0
0/100
50/50

The fresh pastes were manually mixed and poured
in 25 mm diameter x 50 mm height cylindrical molds.
The samples were sealed to prevent any moisture loss
and cured at 80°C until age of testing, i.e. 7, 28 and90 days. The influence of using higher temperature
may have some effect properties of the binder[6],[15]. For mechanical strength, the samples were
subjected to compression load at 1 mm/s rate until
failure. Capillary sorptivity was conducted as
described by Fagerlund [16] which measures water
uptake until samples become saturated. Fromsorptivity test, coefficient of permeability, k was
calculated using the initial gradient measured.
Sorptivity indicates pore structure and theirconnectivity or capillary network which is a major
factor influencing durability towards aggressive ionspenetration. A high coefficient of permeability
indicates a highly connected porous structure or low
tortuosity of the pore network in the binder.

Table 1 Chemical composition of raw materials by
XRF (%).
Precursors
SiO2
Al2O3
Fe2O3
CaO
MgO
SO3
Na2O
K2O
Others

POFA
44.10
1.20
2.10
10.30
9.13
5.80
0.55
12.40
14.95

Water/ solid
precursor Ratio
0.55
0.35
0.35

Fly Ash
55.90
21.80
6.62
4.91
2.00
0.32
0.32
2.20
5.94

RESULTS AND DISCUSSIONS
Compressive Strength
Figure 1 shows the compressive strength ofalkaline activated POFA/ fly ash pastes activated withdifferent alkali solution at 7 ,28 and 90 days of curingages. In sole alkaline activated POFA system (Fig.
1A), samples activated using sodium hydroxide(NaOH) and the combination of NaOH and sodium
silicate (Na2SiO3) shows continual compressive
strength up to 28 days, however decrease at 90 days
curing age. POFA activated using NaOH achieved
higher compressive strength at younger age (7 days)
compared to NaOH with silicate activator. Thisshows the alkalinity supplied by NaOH is sufficient
to promote dissolution of aluminosilicate species andpromote hardening [17] while silicate activator
suppressed the dissolution process. This iscontributed by the high ratio of silicate in theactivator. For alkaline activated sole fly ash systemwith sodium hydroxide as alkali activator (Fig. 1B),
the compressive strength at 7 days curing age isslightly higher than other precursor (sole POFA andthe combination of POFA and fly ash). This isbecause of higher content of alumina in the system.
In Fig. 1B, the substitution of Na2SiO3 as alkaline
activator is slowing down the condensation rate
between silica and alumina component and this may

POFA was rich in SiO2 and it has a very little
content of Al2O3 while fly ash was rich in SiO2 andAl2O3. The composition of fly ash is according to
ASTM C 618, “Standard Specification for Coal Fly
Ash and Raw or Calcined Natural Pozzolan for Use
in Concrete” [12], which is rich in silica and alumina.
Two types of alkali solution were used in this study;
sodium hydroxide (NaOH), and a combination of
NaOH and sodium silicate (Na2SiO3). Mix
proportions and the water to solid precursor ratio of
the alkali-activated POFA/fly ash binder are shown in
Table 2. Water to solid precursor ratio wasdetermined based on the workability of the mixes.
POFA pastes requires higher water/solid precursor
ratio due to its high absorbance properties [13] while
fly ash pastes utilizes less water/solid precursor ratio
due to its smaller particle size that improves
workability [14] which was also observed from
50wt.%POFA/50wt.%fly ash paste.

471

GEOMATE - Mie, Japan, Nov. 21-24, 2017

influence the compressive strength of the harden
paste. Silva et al. (2007) state that alumina component
tends to dissolve easily compare to silica component.
This influence the higher rate of condensation
between silica and alumina species compare to silica
species alone [18]. For sole POFA system with NaOH
and combination of NaOH and Na2SiO3 as alkaline
activator (Fig. 1A), shows the compressive strength
at 7 days curing were lowest than other blends. Thisis because of the lower content of alumina species.
Their compressive strength continuously increased at
28 days curing age as the geopolimerization
mechanism have been taken place. Substitution of fly
ash in alkaline activated POFA (Fig. 1C) leads to asmall increment in strength at early age as shown in
the 50/50 blends at 7 days of curing age and thecompressive strength continuously increase until 90
days curing age. The compressive strength is increase
because of the inclusion of fly ash which is rich inalumina. The compressive strength was decrease
when Na2SiO3 stand-in as the alkali activator which
slowing down the condensation rate between silica
and alumina component. This is because of the
reduction in the reaction mechanism as a result of
reduced alkalinity in the system as the raw materials
dissolves extensively during the early age [19],[20]which was also shown in sole alkali activated fly ash
system (Fig. 1B).
Overall, in sole alkaline activated POFA systemshowing lower strength compared to the combinationof POFA and fly ash geopolymer under this alkalinecondition. Calcium species supplied by POFA as
shown from XRF data (Table 1) also has significant
effect on strength contribution [11],[21], [22]. Ben
Haha. et al. (2011) proved that higher MgO content
of the POFA (shown in Table 1) influence thecompressive strength at 28 days curing age [23]. It issuspected that the co-existence of the calcium withthe aluminosilicate geopolymer gel favors thestrength development in sole POFA system but upon
inclusion of fly ash, aluminosilicate gel became more
dominant [24], hence reducing the strength for thisbinary blend. However, it shows almost the same
compressive strength of sole POFA. The higher
content of SO3 in POFA also influence the lower
compressive strength compare to fly ash which is also
influence the porosity of the geopolymer paste [25].
The silica content in alkaline activator solution also
influenced the compressive strength at higher laterage. This is because of the polymerized of the silica
into an array of small species [26] . Besides that, theformation of a more stable cross-linked
aluminosilicate geopolymer structure when theactivator used was NaOH and Na2SiO3.

Fig. 1 Compressive strength of alkali activated
POFA/fly ash pastes, as a function of the activator
type and the time of curing; (A) 100 wt.% POFA, (B)
100 wt.% fly ash and (C) 50wt.%POFA/50wt.% fly
ashCapillary Sorptivity
The rates of water permeability of alkali activatedpastes studied here are shown in Fig. 2 and Fig. 3 asa function of precursors and curing age. Sorptivity
measurement can be interpreted by the sharp linear
increase in water uptake that measures coefficient of
permeability, k. This initial water uptake controlled
by the larger pores while smaller pores control thecapillary suction at later times which can indicate
tortuosity or connectivity in a binder. Generally,
472

GEOMATE - Mie, Japan, Nov. 21-24, 2017

NaOH activated POFA shows the highest rate ofwater permeability by the amount of absorbed water
shown in Fig. 2A compared to sample with sole fly
ash in Fig. 2B and when both precursors were used asshown in Fig. 2C. This observation shows higher
capillary sorptivity in POFA binder as a result ofdifferent mechanism that may take place during
hardening process due to the chemical characteristicsof this material. The physical properties of POFA also
contribute to this increased rate of permeability inwhich POFA are also a high absorbent material [9].
In alkali activated fly ash pastes, lower sorptivity
slope and longer time was observed to reach fullsaturation in the samples indicates a lower porosityand higher tortuosity of this material compared to
POFA.
This phenomenon is expected due to thedifference in the chemistry of the gel developed inboth types of precursors. It has been observed thatalkali activated fly ash sample exhibit a sodium
alumina silicate hydrate (N-A-S-H) binding gel [11]compared to activated POFA whose gel is mainlycomposed of sodium rich silica gel with very low
calcium [9]. This investigation also allows direct
observation of the effect of gel type in porosity
measurement by this technique. For sample using
both POFA and fly ash (Fig. 2C), a slight differenceis shown in the water uptake and saturation time, butwith improved permeability compared to sole POFA
binder.
The measurement of coefficient of
permeability, k, is tabulated in Table 3.

Fig. 2 Capillary sorptivity of NaOH activated pastes
as a function of precursors proportions and curingage; (A): 100wt.% POFA, (B) 100wt.% fly ash and(C) 50wt.% POFA/50wt.%fly ash.
The measurement of capillary porosity is also
compared with pastes with silicate as activator,
shown in Fig. 3. Similar observation was seen where
activated POFA (Fig. 3A) exhibits the highest water
absorbed while fly ash (Fig. 3B) had the lowest. A
combination of both precursor (Fig. 3C) also reduced
permeability of alkali activated POFA.
The
observation from both sets of data implies that there
are no significant differences in porosity between
activators but strongly influenced by the type ofprecursor used.

473

GEOMATE - Mie, Japan, Nov. 21-24, 2017

between 19 MPa to 32 MPa collected at all curing
ages while large range in coefficient of permeability
values in these sets of samples (between 0.024 to0.220), nearly 10 fold. This shows strong influence of
raw precursor and the type of binding gel that wasformed during hardening process. Fly ash based
samples showed the highest mechanical strength withlowest coefficient of permeability compared to alkali
activated POFA. In alkali activated POFA paste, thereaction product is sodium silicate gel with a very low
calcium gel which has small contribution to strengthof the binder. This agrees to lower pozzolanic
reaction in POFA compared to fly ash [27]. In
addition, water could easily be removed during thedrying process prior to the sorptivity measurement
which created more pores [6], increasing coefficientof permeability. The hydration product of fly ash
alkali activated paste for both types of alkali activator
was N-A-S-H gel which has a different water
environment compared to calcium based binders. In a
N-A-S-H type gel, water is physically bonded inwhich would not cause significant change in pore
structure during drying [6] while water is chemicallybonded a calcium based gel binders. It is also
observed that NaOH contributes to increment instrength compared to silicate activator for all mixes
studied here. This shows the effect of activator inreaction mechanism of these binders. The results for
NaOH-activated pastes are in agreement withfindings from few researchers [28],[29]. It alsosuggests silicate activator decelerates reaction
mechanism in these pastes [30]. However, the impact
on capillary pores is minimal, first time observed inthis study.

Fig. 3 Capillary sorptivity of NaOH with silicate
activated pastes as a function of precursors
proportions and curing age; (A): 100wt.% POFA, (B)
100wt.% fly ash and (C) 50wt.% POFA/50wt.%flyash.
Table 3 summarizes the kinetics of capillary
sorption of water by the coefficient of permeability(k) calculated by the initial slope of the sorptivity
curves up to saturation limit as a function of precursor
proportions and curing age. The lowest k value isshown by fly ash paste in all curing ages, showing a
denser matrix in the gel with high tortuosity
compared to sole POFA paste which shows highest
coefficient of permeability, k value. This observationis true for both types of activator used in this study. It
also revealed that the use of silicate as activatorincreases porosity in these binders.
Table 3 Average capillary absorption coefficient as afunction of precursor ratios and curing age.
Precursor
propor
tion
(wt.%
POFA
/
wt.%fly ash)

Average Capillary absorption coefficient, k(kg/m2s1/2)
Activator: NaOH
Activator : Na2SiO3

7

28

90

7

28

90

100/0

0.050

0.079

0.045

0.082

0.121

0.159

0/100

0.024

0.028

0.026

0.183

0.229

0.145

50/50

0.065

0.072

0.065

0.060

0.088

0.068

Curing Age (Days)

Fig. 4 Correlation between coefficient of permeability
and strength as a function of raw materials andactivator

Coefficient of permeability, k vs mechanicalstrength

CONCLUSIONS

Figure 4 illustrates the coefficient of permeability,
k with mechanical strength of these binders. This plot
clearly shows the relationship between capillaryporosity and strength that is mainly governed by thetype of precursor used. There appear a small range ofstrength obtained between the mixes, which are

The choice of precursors and type of activator are
the main factors in controlling capillary porosity andmechanical strength of alkali activated POFA and fly
ash binders. Alkali activated fly ash binder has the474

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lowest coefficient of permeability with highest
mechanical strength compared to POFA binders.
When comparing the effect of activator used, NaOHactivated pastes measured lower rate of permeability
and improved strength compared to silicate activatedpaste, for both POFA and fly ash. This implies thatthese materials have potential applications forstrength performance, with differences in porosity
which may impact the choice of binder applicationand environmental exposures. Further works on
actual exposure in aggressive environments to test for
durability performance of these binders is
recommended.
ACKNOWLEDGEMENT
This work was supported by the Ministry ofHigher Education Malaysia under MyMaster,
MyBrain15 and Universiti Malaysia Sarawak under
grant number F02/SpSTG/1389/16/31.
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476

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

CURRENT SITUATION OF CONSTRUCTION AND DEMOLITIONWASTE IN VIETNAM: CHALLENGES AND OPPORTUNITIES
Nguyen Van Tuan1, Tong Ton Kien1, Dang Thi Thanh Huyen1, Tran Thi Viet Nga1, Nguyen Hoang Giang1,
and Ken Kawamoto2
1
National University of Civil Engineering, Hanoi, Vietnam
2
Graduate School of Science and Engineering, Saitama University, Japan

ABSTRACTWith the rapid urbanization and economic growth on all the fronts, lots of construction activities are conducted everywhere, especially in big cities in Vietnam (e.g., Hanoi, Haiphong, Ho Chi Minh). All activities such as
new construction, renovation, and demolition of buildings and structures generate huge amount of waste, called
the Construction and Demolition waste (CDW). According to the State of Environmental Report 2011 on Solid
Waste management issued by Ministry of Natural Resources and Environment (MONRE), the total municipal
solid waste generation was about 60 thousand tons/day averagely, in which the CDW waste accounts for 10%12% of total solid waste. In order to maximize the potential positive impacts but at the same time minimize thenegative effects of modernization and industrialization in the country, it is necessary to take immediate measures
to protect the environment. This paper presents the current situation of CDW in Vietnam and gives challenges
and opportunities in the legal and institutional framework for solid waste environmental management. The end
solution intended will be to propose suitable CDW management and recycling strategies to suit to these conditions with proven benefits to all stakeholders.
Keywords: Construction and Demolition waste (CDW), Solid waste management, Recycling, Reuse, Vietnam

on Solid Waste management (issued by Ministry of
Natural Resources and Environment - MONRE), thetotal municipal solid waste generation was about 60
thousand ton/day averagely, in which the CDW
waste accounts for 10%-12% of total solid waste.
Current generation of CDW in Vietnam can be seenin the Table 1 [1].

INTRODUCTION
Like many other developing countries, Vietnam
has been experiencing various kinds of environmental problems such as Municipal Solid Waste Management, in which Construction Demolition waste(CDW) management and recycled is one of the mostcritical engineering issues that need immediate intervention today.
Vietnam is the easternmost country on the Indochina Peninsula in Southeast Asia. It is bordered by
China to the north, Laos to the northwest, Cambodia
to the southwest, and the South China Sea to the east.
The area of Vietnam is approximately 330,000 km2
and it is ranked as the 65th largest nation in the world.
Currently the national economy heavily relies upon
the extraction and use of natural resources. As of
July 2016, the population was approximately 91.7
million, making Vietnam the 14th most densely inhabited country in the world and 8th in Asian region,
which imposes a constant and long lasting pressure
on the country’s natural resources.
With the rapid urbanization and economic
growth on all the fronts, lots of construction activities are conducted everywhere, especially in big cities in Vietnam (i.e., Hanoi, Hai Phong, Ho Chi
Minh). All such activities (new construction, renovation, and demolition of buildings and structures) are
generating huge amount of waste, called CDW. According to the State of Environmental Report 2011

Table 1 Current generation of Construction and
Demolition Waste (CDW) [1]
Amount ofPercent of
CDW generatCDW collecCities
ed (tons/day)tion (%)
Hanoi
1000 – 1500
70
Ho Chi Minh
2000 – 2500
75
Hai Phong400 – 450
40 - 45
Da Nang
500 - 600
60
Other cities
100 - 200
20 - 30
It is important to minimize CDW generation andmaximize reuse/recycling as the construction industry is consumer of tremendous amount of natural
resources and energy as well as emitter of GHGs.
Establishment of effective strategies and enactmentof laws and regulations is essential to achieve this.
In addition, provision for some incentives to users of
the recycled products seems to be necessary to promote the use. In most of developed countries, forexample, they actively introduce “Green Procurement” for newly-construction projects lead by gov477

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ernments, i.e., enhancing the use of recycled materials for constructing buildings and infrastructure. It isessential to assess the life-cycle as it provides quantitative tool to assess environmental impact of CDW
reuse/recycling [2]. In the move toward green or
sustainable environment, Vietnam has to benchmark
developed nations like Japan and Hong Kong inhandling construction waste issues.
This paper presents the current situation of CDW
in Vietnam and gives challenges and opportunities in
the legal and institutional framework for solid wasteenvironmental management. The end solution intended will be to propose suitable CDW management and recycling strategies to suit to these conditions with proven benefits to all stakeholders.

country become more sustainable in handling construction waste.
Table 2 Recycle of CDW in several countries

CURRENT SITUATION OF CDW IN VIETNAM- CHALLENGES AND OPPORTUNITIES OF RECYCLINGCountry
Region

Waste
Generation(million
tons /year)

RecycleRate (%)

Thailand

1.9

Almostno recycle

Vietnam

1.9

1-2

Malaysia

6.9

5

Korea

67

Concrete
36

Denmark

3

81

Netherlands

11

90

72.7

Concrete(~99),
Asphalt(~99),
Wood(~90)

Current situation of CDW generation in Vietnam
Japan

In fact, the CDW has great value for recycle. In Vietnam, the amount of solid waste has been being
generated more in urban areas. As reported by thenational environment agency on solid waste in 2011[1], the amount of municipal solid waste generated
about 12.802 million tons in 2008 and estimated to
be 22.352 million tons in 2015. In which, CDW isaround 10-15%, mainly arisen from works of construction and demolition. Approximately 2,200
apartments (about 6 million of m2) were built in the
70’s - 80’s, in which approximately 90% are degraded seriously. In 2007, the Vietnamese Government
issued Resolution 34/2007/NQ-CP [3] on a numberof solutions to the amelioration and reconstruction ofdamaged or degraded condominiums by 2015. So in
the coming years, a huge amount of CDW will bedischarged in the large cities or urban areas.
Furthermore, regardless of compositions of CDW, it
has been reported that the compositions of CDW areSoil, Sand, & Gravel (36%), Brick & Building block(31%), Concrete (23%), and others including metaland plastic (10%) [4]. Those major components ofconstruction generated soil, bricks, and concrete canbe recycled and reused efficiently and economicallyin construction and infrastructure systems, which
directly contribute to the reduction of CDW land
filling.
Because of great value, CDW has been valued
subjects for recycle in many countries (Table 2).
Especially, Japan has been one of leading countries
in promotion of CDW recycle products lines for
trade and implementation of related legal regulations
such as Construction Recycle Act and Standard for
Recycled Construction Waste. These legal approaches taken by Japanese government made theTreatment

Dumpedand landfill
Dumpedand landfill
Reuse andrecycle,landfill
Reuse andrecycleReuse andrecycleReuse andrecycleReuse andrecycleReference

[5]

[1]

[6]
[2]
[7]
[7]

[8]

It can be clearly seen that the huge amount of
CDW is actually the huge source of energy and saving we can obtain if we know how to take the opportunities. These sources of waste could be used as
new recycled materials for infrastructure construction:+ Production of recycled aggregates (RAs) from
CDW and application for Subgrade, base or
sub-base layer, laying course and road surface,or for replacement of natural aggregate in mortar and concrete production.
+ Fabrication of sustainable materials for theconstruction of traffic infrastructure: pervious
concrete containing RAs for paving flags; Roof
tile embankment, trench plate, blocking barrier; edge restraint; backfill and road embankment; Controlled Low Strength Materials(CLSM) Utilizing Recycled Aggregates, selfleveling CLSM for road base using a combination of all industrial / agricultural wastes (flyash, gypsum, blast furnace slag, rice husk ash);asphalt containing RAs; recycled aggregate
concrete pavement;+ Sustainable materials for building construction:brick, interlocking concrete block using RAs
and industrial/ agricultural wastes (towards
cement-less bricks); as raw material or additive
for cement production; manufacturing of reinforced concrete piles for reinforcing foundation works; ...
These sources of waste could be used for environmental pollution control:+ Wastewater treatment: Filter media, Biofilm
478

GEOMATE - Mie, Japan, Nov. 21-24, 2017attachment media (Carriers)+ Remediation of oil-polluted water and sea,
Remediation of coastal erosion(iv)

National Strategy on Environmental
Protection up to the year 2020 and Vision to2030 (2012).

In the 2009 National Strategy for solid waste
management, it is expected that by 2050, all kinds ofsolid waste will have been collected, reused, recycled and comprehensively treated by advanced, environmentally-friendly technologies, suitable to each
locality, thereby limiting the amount of solid wastethat needs to be land filled. Together with National
Strategies, there have been relevant laws and policy
documents such as decree, circular, joint circulationand standards that have been issued to support. Especially, the importance of research and development for the disposal and recycling of waste is emphasized in the newly revised “Law on Environment
Protection (2014)”: Article 6.6 encourages “Conduct
scientific researches, technology transfer and apply
the technology for the disposal and recycling ofwastes and environment-friendly technologies”.
The recycle of CDW has been emphasized oncein National strategy for management of solid waste
up to the year 2025 and Vision to 2050 (Table 3) inwhich up to 50% - 60% of collected CDW would
need to be recycled [5]. Nevertheless, the detailed
instructions such as Construction Recycle Act orRules for Recycling of CDW are not available. Furthermore, there are no standards and criteria for theuse of recycled materials from CDW such as subbase course materials, concrete aggregate, and construction generated soil in Vietnam. There are only
some Directives and Circulars promoting the application of recycled construction materials.

Current situation of CDW management in Vietnam
Disposal of such CDW in a sustainable manner
is a big challenge for the contractors and owners
while management of CDW at macro scale is a big
task for legal authority. The most common management of CDW at present in Vietnam is dumping indiscriminately and some of CDW are being disposedin landfills. The number of landfills is actually very
limited. For instance, there are currently 05 active
landfills in Hanoi (Van Noi, Nguyen Khe, Duong
Lieu, Van Con, Xuan Son leveling sites). The Van
Noi construction landfill in Dong Anh rural districtis the largest active one at present (Total 9.5 ha).
According to Master map for CDW and sludge management in Hanoi city towards 2030, vision to 2050,
there will be 24 CDW landfills and 03 landfills forsewer and fecal sludge treatment. In Haiphong, thereis the largest CDW landfill in Hai An district with29.6 ha including a leveling site for CDW. The management of CDW has been regulated in Master planon solid waste management in Haiphong city towards 2025 [9]. According to the master plan, Haiphong will have 7 domestic solid waste treatment
zones, 7 district treatment zones and 5 landfills for
CDW disposing as: Trang Cat (5 ha), Ben Gung (3ha), Dong Hoa (3 ha), Do Son (3 ha), Lai Cach (3ha).

Treatment methods of CDW in Vietnam
Dumped indiscriminately

Table 3: National strategy for management of solid
waste up to the year 2025 [10]Landfilling

Targets

In 2020 In 2025

Recycling (1-2%)

Ratio of cities that have solid waste
recycling system %% Reduction of plastic bags compare
to 2010

70

100

65

85

% Collection/%
Recycle90/85

100/90

80/50

90/60

50/30
90/75

100/50100/100

70/0

100/0

Fig. 1 Treatment of CDW in Vietnam
In the past two decades, Vietnam Government
has put in place a sound legal framework for environmental protection that addresses guidelines forthe management and disposal of all waste streams.
This framework is supported by several National
Strategies that apply to solid waste management:(i) Strategy for the Management of Solid Waste
in Vietnam Cities and Industrial Parks (1999).
(ii) National Strategy for Environmental Protection (2003).
(iii) National Strategy for Integrated Management of Solid Waste up to 2025 and vision
towards 2050 (2009).

479

Urban house Solid
Waste
Construction
andDemolition waste
Urban sludge
Non-hazardous Industrial SW
Hazardous Industrial
SW

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Protection up to the year 2020 and Vision to 2030
approved by Decision No.2149/QD-TTg in 2009. In
this legal document, one of the big tasks is to increase the reuse and recycling of solid waste by increasingly reuse solid waste; building and developing the waste market and economy; developing therecycling industry, promoting the purchase of recycled products, elaborating and applying incentive
policies for recycling activities and forming recycling funds.
Furthermore, there has been not much attention
from present public awareness and attitude towards
the waste generated from construction and demolition sites. This is required to be changed in first possibly the industrial practice. It is required to sensitize
not only the Engineers, but all stakeholders including regulatory authorities in construction industry.
This also requires full understand the reuse potential
of CDW and existing practices in implementationand enforcement for achieving the objectives of national strategy.
In Vietnam, the recycle of CDW has been at research scale only. JICA is one of leading donors insolid waste management (SWM) projects:+ 2006-2009: 3R initiative project in Hanoi city.
This project had been implemented for 3 years
from November 2006 to November 2009 aiming
at establishing a balanced and unique 3R systemcentered on the source separation and recyclingof biodegradable waste under the 3R Initiativein Hanoi City.
+ 2005-2013: Haiphong Environmental Improvement Project.
+ 2014-2018: Project for Capacity Development
on Integrated Management of Municipal Solid
Waste+ 2014- present: DAP Recycle of phosphogypsum
in Dinh Vu industrial zone- Haiphong.
Besides, some SWM and promotion of recycling
projects have been done under the support of Ministry of Environment in Japan.
+ 2009: Ichikawa Kankyo Engineering (IKE)
CDM Project on SW Composting+ 2014: Ichikawa Kankyo Engineering (IKE) Dwaste recycle project

Challenges and Opportunities of recycling CDW
in Vietnam
It is obvious that the concept of CDW management has been quite new in Vietnam and it is essentially required to spread the information in order togain the public and authority support. Vietnam Government indeed is facing a big challenge to deal withMSW (Municipal Solid Waste) management in general and CDW management in particular. The stage
wise problems could be identified in the following
manners.
Firstly, the construction technique remains outof-date, therefore, it generates huge amount of waste.
For instance, instead of underground digging withpipe ploughing technology for pipe installation, it iscommonly used the open ditch technique which generates CDW and expense for earth moving. The
buildings are constructed with concrete blocks instead of using bricks and mortars will save also lotsof money in cleaning the construction waste at sites.
The application of new advanced construction technologies would definitely help reduce the CDW atsource.
The illegal dumping of CDW, on the other hand,
can cause risks to human health and environment
including transportation obstacle (i.e., CDW on
roadsides and pavements) leading to accidents, impact of urban landscape, air pollution (due to dust),
degraded infrastructure (i.e., blocking the sewers),
waste of lands. It can be seen for the past ten years
Hanoi has been a giant construction site and the dust
from construction contributes significantly to air
pollution in Hanoi. The illegal dumping of CDW on
streets happens every day, which cause countless
accidents unfortunately. In addition, the improper
management of toxic materials including CDW suchas gypsum drywall (which can produce hydrogensulfide) and asbestos (which increase the risk of lungcancer) increases the potential risk to human health.
The issues of illegal dumping are mainly due to thecost and project location factors.
Right now, like other developing countries in
Asia, Vietnam is facing the shortage of legal andenforcement in CDW management as mentioned
above. The priority in current solid waste management is for organic waste management and hazardous waste management (health waste and hazardous
industrial waste). The CDW, which belongs to nonhazardous solid waste, is considered mostly at research scale and no big investment has been put inso far. At present, there are not any regulations (circulars, guidelines) on classification, collection,transfer and treatment of CDW. The priority policy
or investment policy for research, manufacture andbusiness investment in the recycle and managementof CDW has not been promulgated. The recycle policy has just mentioned in general solid waste management in National Strategy on Environmental

Similar projects have also conducted in related
Vietnamese Ministries:- "Investment of CDW recycle line to produce
construction materials project" by Ministry ofConstruction in 2010 - 2012. This project has
investigated properties of the recycled aggregates (RAs) from CDW from various CDW
sources collected from landfills in Hanoi, as
well as some properties of concrete, mortar andconcrete bricks and block using RAs. Besides,
the project also selected and appropriate technologies for recycling CDW to produce RAs forconcrete and mortars applied in Vietnam. How480

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ever the project was not entirely successful, RAs
is only applied to the base, sub-base layers of
rural roads, not for surface layer or highway applications.
- "Treatment and recycle of solid waste in construction of road infrastructure project by Ministry of Transportation in 2010 – 2014.
- “Investigation of management system of CDW in
urban areas” by Vietnam Urban Environment
and Industrial Zone Association in 2008 – 2010.
- “Research and piloting innovative construction
works in the islands” in 2015 – 2020.

CONCLUSIONTaking all facts presented into account, it is obvious that CDW management and recycled is one of
the most critical engineering issues that need immediate intervention in Vietnam today. Though there
have being some initiatives in the past to address thisissue, none has been successful mainly due to themultiplicity of the problem. Therefore a more holistic approach addressing all technical, social, institutional and economical issues is vital to achieve asustainable solution.

The biggest problem with current R&D public
investment projects is its limit in application. The
R&D manufacture line often stopped when the project finished since the input material and output were
not sustainable.
Recently, in 2017, one very important cooperation project between Vietnam and Japan institutional
links (Saitama University, Japan and National University of Civil Engineering, Vietnam) was applied
successfully, called “Establishment of Environmentally Sound Management of Construction and Demolition Waste and Its Wise Utilization for Environmental Pollution Control and for New Recycled
Construction Materials in Vietnam”. This project isfunded by SATREPS, a Japanese government program, that promotes international joint research targeting global issues. The program is collaboration
between two Japanese government agencies, i.e. theJapan Science and Technology Agency (JST) andthe Japan International Cooperation Agency (JICA).
The project proposes to promote the recycling of
CDW in Vietnam, which aims (1) to establish guidelines necessary for the environmentally sound CDW
management and quality standards for recycled materials produced from CDW; (2) to develop newtechnologies utilizing recycled materials produced
from CDW; and (3) to propose strategic businessmodels designed to promote the CDW recycling in
Vietnam and examine their effectiveness and feasibility through on-site pilot projects. The final goal ofthis project is to contribute to the achievement of a
CDW recycling rate of 60%, which meets the Vietnam national strategy for management of solid
waste up to the year of 2025, through the applicationof developed technologies and business models topractical recycling business.
This project is very crucial for Vietnam (1) totake advantage of sharing experience from Japaneseside in terms of recycle technology and policy implementation; (2) to strengthen the correlation of
stakeholders (research institutions, public authorityand private sectors) in implementing a cohesive national program to address waste management issues
in Vietnam and (3) to promote the waste recycle
business for better energy saving.

ACKNOWLEDGEMENTS
The authors would like to thank the SATREPS(Science and Technology Research Partnership for
Sustainable Development) project, a Japanese
goverment program for the research grant supported
by JST-JICA to promote the international joint
research targeting global environment issues.
REFERENCES[1] Ministry of Natural Resources and Environment(MONRE), 2011, State of Environmental Report 2011 on Solid Waste management (MONRE), Vietnam.
[2] Vietnamese government, 2007, Resolution No.
34/2007/NQ-CP A number of solutions to theamelioration and reconstruction of damaged ordegraded condominiums.
[3] Shishir Bansal, S K Singh. A Sustainable Approach towards the Construction and Demolition Waste. International Journal of Innovative
Research in Science, Engineering and Technology. Vol. 3, Issue 2, February 2014.
[4] Decision No. 609/QD-TTg approved by thePrime Minister of the Socialist Republic of Vietnam dated 24, April, 2014, Master plan onsolid waste disposal of Hanoi capital to 2030,
with a vision to 2050.
[5] T. Chinda, W. Engpanyalert, A. Tananoo, J.
Chaikong, and A. Methawachananont. The Development of the Construction and Demolition
Waste Dynamic Model . IACSIT International
Journal of Engineering and Technology, Vol. 5,
No. 5, October 2013.
[6] Papargyropoulou, E.; Preece, C.; Padfield, R.;
Abdullah, A.A. Sustainable construction waste
management in Malaysia: A contractor's perspective. Management and Innovation for a Sustainable Built Environment. 2011, Amsterdam,
The Netherlands.
[7] Anton Ming-Zhi, Gao. Construction & Demolition Waste Management: From Japan to HongKong. Griffin's View on International andComparative
Law.
Retrieved
from

481

GEOMATE - Mie, Japan, Nov. 21-24, 2017https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1131984 on 21 Jul 2008.
[8] Ministry of Land, Infrastructure, Transport andTourism, 2012 (in Japanese).
[9] Decision No. 1711/QD-UBND on October 11,
2012, Master plan on solid waste managementin Haiphong city towards 2025.

[10] Decision No. 2149/QD-TTg approved by thePrime Minister of the Socialist Republic of Vietnam, 2009, Approving the National Strategy
on Integrated Solid Waste Management up to2025 and Vision to 2050, Hanoi.

482

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

IRREPARABLE COMPRESSIVE CREEP DEFORMATION OF
CHLOROPRENE BEARING PAD
1Hidenori TANAKA1
National Institute of Technology, Gunma College, Japan
ABSTRACT

Rubber is indispensable to fill safety standards against earthquake and vibration. In Japan, this material isnormally used to support many concrete structures (bridges, buildings). But, the compressive irreparable creep
deformation as time goes by hasn’t been considered sufficiently. Generally speaking, rubber is non-compressive
and hyper-elastic. This creep would reduce the affect to absorb the horizontal deformation in earthquake. Basedon this, we have carried out simple compressive creep test by using cylindrical specimen made of chloroprenerubber as a bearing pad of bridge. At first, we pressed the specimen to equivalent forces which are equal to theself-weight of bridge girders. Secondly, we have kept them under compressive situation for three months. And
then, the pressure was released. The residual displacement was measured including unloading elasticity, delayedelasticity and irreparable creep. The irreparable creep was account for 17 % of the total displacement.
Furthermore, we simulated numerical analysis of the cylindrical specimen in 2 dimension based on finite
displacement theory. In this analysis, we adopt the hyper-elastic Ogden’s model in axisymmetric problem. The
result of analysis corresponded with the experimental result well.
Keywords: Bearing pad, Irreparable Creep, Finite displacement, Hyper-elastic, Chloroprene
INTRODUCTION
Seismic isolation rubber has been used for bearing
pad of bridges and buildings. The isolated effectwould be dependent on the horizontal deformationof rubber under earthquakes. There were many
experiments to evaluate the deformation without
axial force or axial mechanical properties, forexample (stress relaxation, creep, plasticity) .
It is very important to consider the affection to theisolated effect due to axial irreparable behavior.
Therefore, We have carried out simple compressive
creep test using chloroprene specimen [1].
Rubber is usually non-compressive and nonvolumetric material. In addition, the material will
have occurred large displacement even though theapplied loads are small. Due to these complicatedproperties, It has been more difficult to explainmathematical expression in mechanical behavior. In
this study, we showed the numerical analysis ofcompressive deformation by Ogden’s model that isthe basic theory to explain large displacement
behavior in 2 dimensional axisymmetric problem
comparing with the result of experiments [2].

Fig 1. Deformation of rubber (compressive test)
The relation between applied loads and longitudinal
displacements are shown in Fig.2. In this test, Theapplied loading speed was 10mm/minute.

COMPRESSIVE TESTThe load-displacement curve
We selected chloroprene rubber that has been used
as a bearing pad of bridge. The quasi-compressive
loads were applied on the cylindrical specimen (φ80mm, H=80mm) with upper and lower steel plates(refer Fig.1).

Fig.2 Loads-displacements curve
The curve is typical compressive behavior [3].

483GEOMATE - Mie, Japan, Nov. 21-24, 2017

Compressive creep test
The Compressive creep test was carried out asfollowing way. At first, we measured thedisplacements and applied loads until serviceability
state which is supporting the self-weight of bridge
girders. Secondly, the stress has been holding for 3
months to fix securely upper steel plate by 4 bolts
with nuts at the corner (refer to Fig.3).
Finally, we measured the displacements again after
releasing stresses unfastening the bolts and nuts
(refer to Fig.4). We could evaluate non-linear statethat including unloading elasticity, delayed elasticity
and irreparable creep to describe the deformation
curve after releasing stresses .
We determined serviceability state to consider
relationship between real chloroprene pad section
area and girders weight.
The serviceability state is shown in Fig.5. The redpoint in the figure is equivalent to the state.
This curve is approximately linear state comparing
with the curve in Fig.2

HoldingFig.5 Serviceability state
The curve after releasing stresses reveals creep
characteristics (refer to Fig.6). This curve is mainly
consist of three parts. The sharp descending line near
0 (hour) is unloading elasticity, by 200 (hours) it
showed delayed elasticity, and after 200 (hours) it
showed irreparable creep, respectively.
Even though the holding times are less than fourmonths, it was found that the irreparable creep
reached about 17 % of total displacement. In
addition, The creep would be occurred under thesmall load that is equal to serviceability state.
The plastic deformation could be visualized thespecimen after test (refer to Fig.7).

Irreparable creep

Fig.3 Holding stresses
Fig.6 Creep Characteristics

Fig.4 Releasing stresses
Fig.7 Plastic deformation of specimen484

GEOMATE - Mie, Japan, Nov. 21-24, 2017

functions for analysis. But, these models are
inadequate for nonlinearity in high strain region. So,
here, we adopted Ogden’s model to simulate highnonlinearity region in analysis[7].

NUMERICAL ANALYSIS
Base of finite displacement theory
Rubber has generally large deformation undercompressive loads. So, There are some limitations toapply the infinitesimal deformation theory.
The deformation gradient tensor has been used todescribe the mechanical properties of rubber. For
example, Cauchy stress , Green strain tensor[4].
In this paper, The deformation gradient tensor isdefined as follows[5].

n (1  2  3  3)n1  n
N

W 

n

(4)

n

W : strain energy function
 n , n : material constant1 , 2 , 3 : principal stretch ratio

ｘ
(1)
X
F : Deformation gradient tensor
ｘ : infinitesimal line element vector (after deformation)
X : infinitesimal line element vector (before deformation)F

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

Green-Lagrange strain tensor

Constant value

The strain should be described more than second
rank orders to apply this analysis. Green-Lagrange
strain tensor is reasonable for variational principle[6].

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

n

α

μ

First rank

α1=1.3μ1=1.491 (N/mm2)

Second rank

α2=5.0μ2=0.003 (N/mm2)

Third rank

α3=-2.0μ3=-0.0237(N/mm2)

Results of analysis
We carried out two dimensional axisymmetricanalysis considering the shape of specimen [2].
Fig.9 showed the deformation and the equivalentstress distribution at the quadrilateral point in Fig.8.

(2)

The Second Piola-Kirchhoff stress tensor
This stress tensor is the best expression
corresponding to the Green-Lagrange strain tensor.
And then, This form is useful formulation in analysis
because of the symmetric form[4].

S  JF 1 σ F T
S : second Piola  Kirchhoff stress(3)

Fig.8 Two example points for analysis

J : det( F)F 1 : Inverse tensor ofF

F : Transpose of F
σ : Cauchy stress tensor
T

Ogden’s model
Strain energy function has been used to analyze thelarge deformation of rubber under various loads.
Moony-Rivlin and Neo- Hooke models are popular

Fig.9 Deformation and equivalent stress No.1
485

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.10 showed the deformation and the equivalentstress distribution at the circular point in Fig.8.

Fig.12 Thermal distribution
In this analysis, We should check the viscoplasticity
under serviceability state. We have a plan to carryout the freezing and thawing test keeping thedeformation of rubber under serviceability state. So,
The compressive final deformation is the initial form
for unsteady thermal conduction analysis.
For example, Thermal distribution that thetemperature reached zero degree was shown in
Fig.12. The center line was heat insulation and theother surface of rubber were heat transfer borders.
The material properties are shown in Table 2.

Fig.10 Deformation and equivalent stress No.2
Equivalent stress is defined in equation (5).

 eq  3 J 2'(5)

 eq : Equivalent stress (N/mm 2 )J 2' : Second invariant of deviatric stress
We adopted the displacement control method.
The equivalent stress distribution is typical forcompression state. The highest stress is distributed at
the corner of specimen which is contacted with steel
plates (upper and lower). The maximum equivalentstress is approximately 0.6 (N/mm2).

Table 2 Heat properties
Specific heat

1.65 (J/g・K)

Specific gravity

1.39

Heat transfer

14 (W/m2℃)

coefficient

Unsteady thermal conduction analysis
The Thermal analysis was simulated under cyclic
temperature change which showed average value inNorth area in Japan. This is preliminary step tocheck the evolution of viscoplasticity of this padunder cyclic temperature[8]. The cyclic temperature
was shown in Fig.11. This temperature change wasdetermined due to the limit of application of freezing
and thawing test machine .

Thermal distribution was changed in about four
degrees from the surface to the center of rubber.
CONCLUSION
The knowledge found in this research are as below.
(1) The irreparable creep would be occurred under
the serviceability state even though the elapsed
time was only for three months.
(2) The value of irreparable creep was about 17 ％of total displacement.
(3) Second Piola-Kirchhoff stress and GreenLagrange strain tensor are suitable expression
for large displacement problem of rubber.
(4) The analysis has a good agreement with theresult of experiment.
(5) We have a plan to adopt F-bar method that isthe popular numerical way to describe elastoviscoplasticity of rubber .
(6) It was found that the maximum equivalent stressis distributed at the corner of specimen which iscontacted with steel plates.

Fig.11 Cyclic Temperature change486

GEOMATE - Mie, Japan, Nov. 21-24, 2017

rectangular shock absorbing device under an
extreme compression stress”, Journal of JACE,
No.661,Oct,2000,pp.71-83.
[4] Takashi Kyoya,”Continuum Mechanics ”,Japan
Association for Non-linear CAE,Dec,2008[5] Shigeru
Kuranishi,”Introduction
toMathematical
ModelsofMaterial
Characteristics”, Subcommittee of Structural
Mechanics Committee of Structural Engineering,
J.S.C.E.,Aug.,1989[6] B.R.Seth, “Generalized strain measure withapplications to physical problems”, IUTAM
Symposium on Second Order Effects in
Elasticity, Plasticity and Fluid Mechanics, 1962,
pp. 1-14.
[7] R.W.Ogden,D.G.Roxburgh, “A pseudo-elastic
model for the Mullins effect in filledrubber”,The royal society, 1999, pp. 2861-2877.
[8] Hidenori Tanaka, Fimiyasu Makinoshima,”The
adhesive characteristic of concrete block withfiber sheets under cyclic temperature”,
International Conference on the Regeneration
And Conservation of Concrete Structures
2015,I-17(7) We would like to research the thermal fatigue
behavior keeping serviceability state undercyclic temperature in next stage.
(8) There are only four degrees thermal distributionchanges from surface to center. The thermal
fatigue affection may be small.
ACKNOWLEDGEMENTS
The author appreciates Tokyo Fabric Co.,Ltd forproviding the chloroprene specimens. In addition,
Mr. Kanbe works for Sata Construction Co.,Ltd and
Mr. Kitazume works for Oriental Shiraishi Co.Ltd.
supported to gather data. And , Research Center ofComputational Mechanics, Inc. for supporting two
dimensional unsteady thermal conduction analysis.
REFERENCES[1] Yoichi Yuki, Hiroki Tamai et al, “Fundamental
experiment of shape and confining effect onrubber pieces’ cushioning characteristics”,
Journal of structural engineering, Vol.61A,
March,2015, pp. 313–321.
[2] EA de Souza Neto, D Peric, DRJ Owen,” Nonlinear finite element method”, June, 2012.
[3] Hisanari Uruta, Kazuhiko Kawashima etal ,“Evaluation of stress-strain relation for a rubber

487

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

FE ANALYSIS FOR LATERAL STRENGTH OF CONCRETE WALLSWITH AGGREGATESEDIMENTATION
1Mamoru Kawasaki1, Tetsuya Ohmura2 and Ryota ISHII 3
Graduate school, Tokyo City University, Japan; 2Architecture Department, Tokyo City University, Japan
3
The Zenitaka Corporation, Japan
ABSTRACT

Concrete walls are effective earthquake resisting elements for lateral force in concrete buildings. In addition,
stiffness and strength of walls are larger than one of columns and girders. As lateral force concentrate on walls,
lateral strength of a building would be influenced by that. Therefore a seismic evaluation for walls is significant.
However, concrete strength reduction (CSR) would be occurred for the vertical direction due to aggregate
sedimentation. Consequently, seismic performance of a whole building might be reduced by CSR. In this paper,
lateral strength of concrete walls with CSR was analyzed to get basic behavior by FE analysis. This paper reported
that forming compressive strut was influenced by CSR and lateral strength were decreased at concrete wall withthe shear span of less than 0.73. That wall was often seen in medium and low buildings, and seismic performanceof a building with fewer walls tends to depend on wall strength. Therefore, CSR should be taken into account at aseismic assessment in addition to a conventional concrete survey for an existing building.
Keywords: Concrete wall, Concrete strength reduction, Lateral strength, Shear span ratio, Compressive strut
at the top of the walls.
Concrete compressive strut is formed in diagonal
direction when the wall resist earthquake, and thelateral strength of the wall definitely depend on theconcrete compressive strut.
However, seismic performance of a building
might be reduced, because of concrete strength
reduction as shown in Fig.2. In this paper, concrete
walls with concrete strength reduction were modeled
and analyzed to have their lateral strength.

INTRODUCTION
Seismic evaluation is significantly important incountries where earthquake often occur like Japan. In
a concrete building, concrete walls are effective t oresist earthquake, and the seismic performance
depend on them. Most of the lateral force by
earthquake can be concentrated to the walls rather
than columns, because the stiffness of the wall ismuch larger. Therefor the stiffness and strength of thewalls must be properly evaluated.
On the other hand, concrete bleeding andaggregate sedimentation often cause concrete
strength reduction while concrete casting andconcrete curing, because concrete is compose ofwater, cement and aggregate.
Concrete strength distribution in columns an dwalls along their height is shown in Fig.11). Kasai, etal. concluded that concrete strength was reduced to 80
to 90% in walls and 60 to 90% in columns. Theirresult indicated that concrete strength can be reduced

Fig.1 Concrete strength reduction along height1)

ANALYSIS
Analyzed specimen for verification
We modeled and analyzed the wall specimen2) asshown in Fig. 3 and 4 at first to verify our model andanalysis. Figure 3 shows the geometric of the wall
specimen. The wall is 1/3 scale specimen and has fourstories, total height of 3,800mm (12.5 ft.), each heightof 1,000mm (3.3 ft.) and the span of 4,000mm (13 ft.).
The column section is 300mm (about 1 ft.) square andFig.2 Concrete strength reduction in a concrete wall488

GEOMATE - Mie, Japan, Nov. 21-24, 2017(b) Girder and wall(a) Column

Fig.4 Section of the column and girder (mm)Fig.3 Bar arrangement and the geometry (mm)the girder section are the wide of 160mm (6 in.) andthe depth of 200mm (8in.). Their rebar arrangement
are shown in Fig. 3 and 4. Table 1 and 2 show thematerial property. Table 3 shows Diameter and areaof rebar. Concrete strength is 26.6 to 29.4 N/mm2 (3.8
to 4.3 ksi.) and the yield strength of the rebar ismainly 323 to 385 N/mm2 (47 to 56 ksi.).

Table1 Concrete properties

2

2

2

(kN/mm ) (N/mm ) (N/mm )Model
Figure 5 shows meshed model. Four nodes andquadrate iso-parametric plan stress element is applied
for concrete and each elements are 100mm square.
Embedded element is applied for rebar. Bond slip isconsidered for longitudinal bar, and other bar isassumed to be perfectly bonded. The base stub isfixed, the gravity load and lateral displacement isforced at the top of the wall as shown Fig.5.

D4(SD295A)

Material property
The parabola model of Feenstra3) is applied for the
relationship between concrete stress and strain. 0.2%
strain of maximum compressive stress is assumed.
The fracture energy of 9.5N/mm for column andgirder, and 7.2N/mm for wall are considered based on
Nakamura, et al4). Hordijk5) model with 0.1N/mm6) of
fracture energy is applied for the relationship between
tensile stress and strain. The fracture criterion of
concrete under biaxial stress is based on Von Mises
yield criterion.
Rebar is modeled as bi-linear without strain
hardening. Bond slip model is based on Morita, Kaku,
and et al. as shown Fig.87).

Youg Concrete Tensile
modulus strength strength

Story
1, 2

21.5

29.4

2.59

3, 4

23.2

26.6

2.36

Table2 Rebar properties
Size (grade)

LocationYoug
modulus

Yield
strength

Tensilestrength22(N/mm )

(kN/mm ) (N/mm )

2

Wall

172

351

518

Stirrup

163

323

490

D6(SD295A)

Hoop

190

366

491

D10(SD345)

Girder

185

385

594

D22(SD345)

Column

185

563

738

D25(SD345)

Column

185

535

722

Table3 Diameter and area of rebar
Imperial Bar Soft MetricSize

Concrete strength vertical distribution
The concrete strength vertical distribution isassumed as shown Fig.9 based on Kasai, and et al.1).
Four zones are assumed along the height, and theconcrete strength is supposed to be reduced as theheight of the zone raise.
489

Size

JIS Size

Area
(mm2)

N/A

N/A

D4

14

N/A

N/A

D6

32

#3

#10

D10

71

#4

#13

D13

127

#5

#16

D16

199

#6

#19

D19

287

#7

#22

D22

387

#8

#25

D25

507

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Gravity load

Gravity load

εu

σ
εB/3

εB
Gc

σ
σt

ε
1/3σB

Displacement control

Gf
εcr

σB

(a) Compression

εu ε(b) Tension

Fig.6 Concrete model
σ2
σt

σB

σt

σ1

σB

Fig.7 Criterion

Fig.5 Meshed model

Fig.8 Bond slip

Column柱
Displacement (mm)Displacement (mm)i+1i＋1floor
階

0Reduction
ratio
強度比率

強度比率

400mm

i floor
i階

600mm
800mm

75%

80%

90%

90%

100%

100%

100%

110%

Wall

Girder
梁の強度：100%

梁
耐震壁

200mm

梁の強度：100%
Girder2,000

梁Lateral force (kN)

Reference
level
打込み面

壁

Lateral force (kN)

柱

5

10

15

1876kN

1822kN

20

25

Test

1,500

Analysis

1,000
500
0
0

Column
柱

0.1

0.2

0.3

0.4

0.5

0.6

Drift
Driftangle
angle (%)(%)

Fig.10 Lateral force versus drift angle
Fig.9 Assumed concrete strength reduction

Cracking
Figure 11 shows the cracking in the test2) andcrack strain vector in our analysis at 0.4% drift angle.
The failure mode was concrete compressive failure at
the bottom of the wall in both results. The diagonal
crack was observed overall the wall in the test. The
crack strain vector was shown overall the wall in our
analysis. Good agreement was shown in the test andour analysis results up to around 0.4% drift angle.

VERIFICATION
Test result2) and our analysis results are comparedto verify our model and analysis. In this verification,
the concrete reduction along the height is notconsidered, because the concrete of the specimen was
cast at high accuracy.
Lateral strength and drift angle

RESULTS

Figure 10 shows the lateral force versus drift angle.
The maximum lateral force are 1,822kN at 0.37%
drift angle in the test and 1,876kN at 0.36% in our
analysis. Our analysis result is suited to the test result
up to around the maximum lateral force, because thelateral strength in our analysis is 103% of one in the
test.

Our analysis was verified in the previous section,
because our analysis result was approximately suited
to the test results. In this section, the same and shortheight walls with the same section considered
concrete strength reduction along the height are
analyzed.

490

0.7

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure (b) shows the result of three stories (shear
span of 0.73) model. The maximum lateral force is2,253kN at 0.36% drift angle in the model without
concrete strength reduction, and 2,217kN at 0.36% in
the model with concrete strength reduction. The
effect of the concrete strength reduction was not seen
when the results of the models with / without theconcrete strength reduction are compared as well asfour stories (shear span of 0.97) model.
Figure (c) shows the result of two stories (shear
span of 0.50) model. The maximum lateral force is2,826kN at 0.38% drift angle in the model without
concrete strength reduction, and 2,592kN at 0.34% in
the model with concrete strength reduction. The
effect of the concrete strength reduction was seen
when the results of the models with / without theconcrete strength reduction are compared. The lateralstrength of model with concrete strength reduction
was decreased to 89.5% of one of model without
concrete strength reduction.
Figure (d) shows the result of one stories (shear
span of 0.27) model. The maximum lateral force is3,756kN at 0.44% drift angle in the model without
concrete strength reduction, and 3,215kN at 0.36% in
the model with concrete strength reduction. The
effect of the concrete strength reduction was seen
when the results of the models with / without theLateral force versus drift angle
The models with / without concrete strength
reduction are compared for .lateral force versus drift
angle.
Figure 12 shows lateral force versus drift angle.
Figure (a) shows the result of four stories (shear spanof 0.97) model. The maximum lateral force is1,876kN at 0.36% drift angle in the model without
concrete strength reduction, and 1,874kN at 0.36% in
the model with concrete strength reduction. The
effect of the concrete strength reduction was not seen
when the results of the models with / without theconcrete strength reduction are compared.

(b) Crack strain vector(a) CrackFig.11 Crack and Crack strain vector at the peak

Displacement (mm)Displacement
変位 (mm) (mm)10

水平力 (kN)

Lateral force (kN)

2,000

15
1876kN0

1,500

w/ CSR

w/o CSR

1,000

5

500

2217kN

2,000
1,500

w/ CSR

w/o CSR

1,000

0

0

0.1

0.2
0.3
相対変形角 (%)

0.4

0.5

0

0.1

0.2
0.3
相対変形角 (%)

Drift angle (%)

5

変位 (mm)102592kN0

水平力 (kN)

2,000

1,000

w/o CSR
0
0

0.1

0.2
0.3
相対変形角 (%)

0.4

5

変位 (mm)
10

15

4,000

2826kN

Lateral force (kN)w/ CSR

Displacement (mm)
15

3,000

0.5

(b) Three stories model

Displacement (mm)00.4Drift angle (%)(a) Four stories model

水平力 (kN)

152253kN

500

0Lateral force (kN)

変位 (mm)10

2,500

1874kN

水平力 (kN)

5

Lateral force (kN)

03756kNw/ CSR
3215kN

3,000

2,000

w/o CSR
1,000

0

0.5

0

0.1

Drift angle (%)

0.20.3
相対変形角 (%)

Drift angle (%)(d) One story model(c) Two stories modelFig.12 Lateral force versus drift angle
491

0.4

0.5

GEOMATE - Mie, Japan, Nov. 21-24, 2017concrete strength reduction are compared as well as
two stories (shear span of 0.50) model. The lateralstrength of model with concrete strength reduction
was decreased to 85.6% of one of model without
concrete strength reduction.

Principal strain (ε2)
Figure 14 shows principal strain (ε2) at the peak ofmodel with CSR. For all models, the angle ofcompressive strut was about 45 degree. For models
with CSR, compressive strut width of ε2 of 0.1% andgreater were more increased than models without
CSR. Shear span ratio was decreased to 0.97, 0.73,
0.50 and 0.27, those width were 2.0, 1.22, 1.64 and1.11 times of one without CSR.

Lateral strength reduction
Figure 13 shows shear span versus reduction ratio.
The reduction ratio for lateral strength at the shear
span of 0.73 and less was remarkably increased.

CONCLUSION

3,756kN0

w/o CSR
-0.1
-1.6

3,000

2,826kN

3,215kN-52,251kN

2,592kN

1,892kN

-8.3

2,000

2,217kNw/ CSR
1,000

-14.4

LSR

1 st

-10

1,870kN
-15

4 st.

3 st.

2 st.

0

Lateral strength reduction (%)

Lateral strength (kN)

4,000

Two dimensional non-linear FE analyses forconcrete walls with / without concrete strength
reduction were performed. This paper has reported
several conclusions as below.
1.
2.
3.

-20
0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Shear span

Fig.13 Shear span versus lateral strength reduction

Compressive strut width is 300mm.

Our analysis was verified to be compared
between the test and analysis results.
The reduction ratio for lateral strength at theshear span of 0.73 and less was remarkably
increased.
In models of two and one stories with concrete
strength reduction, concrete strength reduction
should be considered for the lateral strength
evaluation of a concrete wall.

600mm
900mm

(a-1)

w/o CSR(a-2) w/ CSR(a)(b-1) w/o CSR= 0.971,400mm(b)

1,100mm(b-2) w/ CSR= 0.732,300mm2,700mm(c-1) w/o CSR(c)(c-2) w/ CSR(d-1) w/o CSR= 0.50(d)
Fig.14 Principal strain ε2492

3,000mm(d-2) w/ CSR= 0.27

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ACKNOWLEDGMENTS
Ryota Ishii is thanked for working much valuable
analyses. The support of JIP Techonoscience in NTT
DATA group staff is deeply appreciated.
REFERENCES[1] Yoshio Kasai, Yuu Matsui. Studies on concrete
strength of structure in Japan, RILEM
symposium control of concrete structures, 1979,
Stockholm Sweden[2] Hiroki Tauchi, Masaomi Teshigawara, et al.
EFFECT OF INNER BEAMS OF MULTISTORY SHEAR WALL ON ITS SHEAR
STRENGTH, Journal of structural engineering(in Japanse) , Vol.56B, pp61-66, 2010
[3] Feenstra, P.H., ’Computational Aspects ofBiaxial stress in Plain and Reinforced Concrete’,
PhD Thesis, Delft University of Technology,
1993[4] H.Nakamura, T.Higai, ’Compressive Fracture
Energy and Fracture Zone Length of Concrete’,Seminar on Post-peak Behavior of RC
Structures subjected to Seismic Loads, JCIC51E, Vol.2, pp256-272, 1999
[5] Cornelissen, H.A.W., Hordijk, D.A., andReinhardt, H.W. ’Experimental Determinationof Crack Softening Characteristics of Normal
Weight and Light Weight Concrete’, Heron 31,
2, 1986[6] Ohoka Takunao, Yoshinori Hitsutaka, Ken
Watanabe. INFLUENCE OF SHORT CUTFIBER MIXING AND CURING TIME ON
THE FRACTURE PARAMETERS OF
CONCRETE, Journal of structural andconstruction engineering / Architectural
Institute of Japan, No.529, pp1-6, 2003
[7] Shiro Morita, Kaku Tetsuzo. BOND-SLIP
RELATIONSHIPUNDERREPEATEDLOADING, Journal of structural andconstruction engineering / Architectural
Institute of Japan, No.229, pp15-24, 1975493

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

FERROCEMENT - BRICK SANDWICH WALLAPPLIED TO NON-ENGINEERED HOUSES
Febrin A Ismail1, M Sofian Asmirza2, *Abdul Hakam1 and Fauzan1
2

1
Engineering Faculty, Andalas University, Indonesia;
Engineering Faculty, North Sumatra University, Indonesia

ABSTRACT
Indonesian houses are generally categorized as non-engineered buildings that are constructed without any
proper structural analyses. Bricks have long been used for hundreds years as main materials to make houses
for the reasons of simplicity and construction speed. Lesson learnt from the Padang earthquake in 2009concluded many casualties are resulted from the collapsed houses made of bricks. Ferrocement as aconstruction material that made of wire mesh and mortar plaster become alternative to be used for retrofitting
brick-houses. In this paper, structural analyses of a typical non-engineered house and a retrofitted housemade of ferrocement-brick sandwich material are described. The ferrocement-brick composite material hasrole as the main structure in the non-engineered house. The series of tests on that sandwich material has been
done prior to the analyses. The results of the tests are then used to determine the strength criteria of theanalyzed house. A structural analysis of the house is done by using the finite element computer program. As
a comparison, an analysis of an ordinary brick wall house is described. As previously thought, the house withwalls made of the ferrocement-brick sandwich material can withstand the given earthquake loads. It is
concluded that the ferrocement-brick sandwich material is very useful to build earthquake resistant houses inseismic prone areas such as the West Sumatra.
Keywords: ferrocement, masonry brick wall, composite, non-engineered house, earthquake engineering
the fall of the roof construction can hurt theoccupants of the house and even take a life. During
the very strong earthquake, seismic safe houseshould remain standing and may suffer from minor
damage on the construction materials such as wall
cracks on the wall. Each element of the earthquake
safe house must remain in original place and still
be in tied to each other during a very strong
earthquake.
The earthquake safe house as well as otherbuildings can be presented as a good team work ofhuman collaboration between owner, designer anda group of workers. An earthquake safe house ingeneral is ordinary house that may not analyzed
with the good science procedures that use ofengineered mechanics knowledge, but adopt the
principles of earthquake resistance. Dimensions
and cost of making a house depends on the desire
and ability of the house owner. The final quality ofphysical engineering work is determined by thebuilder of the house as a worker who create thehouse from its raw materials. The role of the housebuilder has enormous value in generating
earthquake safe house. By providing additional
knowledge and skills to the builders to create asafe house, earthquake risk reduction can berealized [1].

INTRODUCTION
The earthquake safe house can be defined as ahouse that provides security to its occupants in theevent of an earthquake whether a weak earthquake
or a very strong earthquake. The actual earthquake
does not directly cause the victim but the housethat collapsed when the earthquake that can cause
casualties. This house should be made in such a
way that it does not cause accidents or casualties tothe inhabitants in it and the people around it.
Psychologically secure homes also provide a senseof security to the inhabitants at all times. Small
cracks that occur due to small or moderate
earthquakes in a house will be very psychologicaldisturbing the people in the house. So the mainprinciple of earthquake safe house may be able toprovide security to the occupants at any time, both
psychologically and physically.
The earthquake safe house should not has any
damage even in case of a weak earthquake (Fig.1).
Minor damage is like the small cracks in the wallor loose roof arrangement must be avoided. Thisshould the main the criterion of earthquake safe
houses because since the minor damage may cause
bad feeling to residents of the house. The
earthquake safe house also must not suffer fromheavy damage such as the collapse of the wall or
the fall of roof construction due to the very strong
earthquake. Due to the collapse of the wall and / or494

GEOMATE - Mie, Japan, Nov. 21-24, 2017engineering, reinforcement in a house logicallyprovides additional resistance to earthquakes. So
the concept of applying additional reinforcement
can be justified and applicable to traditionalbuildings.
Although earthquake-safe houses have theprimary mission to avoid casualties from thecollapse buildings during the earthquake, people
still want a simple and inexpensive concept to be
adopted. There is some earthquake-safe housing
guidelines that nearly to eliminate the traditional
procedure of building a house that are common insociety. Some of these concepts have been used insome community in a few sample buildings [4].
Ferrocement as a construction material thatmade of wire mesh and mortar plaster become
alternative to be used for retrofitting brick-houses
to resist the seismic load. The concept offerrocement material has been applied to almost all
structural elements of a building such as floor, roof,
water thank including beams [5]. More advanceapplication of ferrocement composites also has
been studied by some researcher [6]. In this study
an application of ferrocement to ordinary brickwall is done to gain a seismic resistant of the house.
In this paper, the tests of brick walls including
ferrocement-brick sandwich wall and the structural
analyses of a typical non-engineered house aredescribed.

a. House before earthquake

b. Safe house after big earthquake

BRICK-FERROCEMENT WALL TESTSIn order to obtain the engineering strength
value of ordinary and ferrocement composite brickwalls, a series of laboratory tests had been
conducted. The specimens included in the tests
were:
1. Masonry brick wall
2. Brick wall with wire mesh (Brick wallcovered by wire mesh without mortar)
3. Mortared brick wall (Brick wall covered bymortar plaster)
4. Ferrocement brick wall (Brick wall withwire mesh covered by mortar plaster)
The tests were performed by applying single
axial force in two different directions, one wasparallel to the wall surface, and secondly
perpendicular to the wall plane surface (Fig.2).
The first one was purposed to obtain the shear
strength of the wall in the direction of the wallcross section, and the second direction was forresistant moment as well as shear strength in thewall surface direction.

c. Un-safe house collapse after earthquake
Fig.1 Earthquake safe house definition
The people still think that the earthquake safe
house is a concept of applying advanced
technology that is complicated. In addition,
earthquake safe house is also a masterpiece of theapplication of expensive engineering science. That
opinion is not entirely wrong, because of someearthquake safety guidelines circulating in thecommunity, tend to feature an addition to theordinary house so it looks more complex and
expensive [2] [3]. The transformation of a houseinto an earthquake safe house may need up to one
third of the overall cost of construction. The extra
cost depends on the concept of the earthquake safe
house to be adopted. In terms of mechanical495

GEOMATE - Mie, Japan, Nov. 21-24, 2017

400

Brick Wall
Brick+ wire mesh
Brick + mortar
Brick + ferrocement

Force (kg)

300

200

100

0

a. Force on the wall cross section

0

5

10

15
Disp. (mm)

20

25

30

Fig.4 Test results in wall cross section direction
4000

Brick Wall
Brick + wire mesh
Brick + mortar
Brick + ferrocement

Force (kg)

3000

2000

1000

0

b. Force on the wall surface0

Fig.2 Wall specimen test directions

5

10

15
20
Disp. (mm)2530

Fig.5 Test results in wall surface direction

During the tests, the damage to the specimens
in term of crack were monitored. There were twodifferent patterns observed on the tests depend on
the direction of applied forces as plotted in Fig.3.
The applied forces and displacement in thesame direction are recorded. The results in theterms of forces versus the displacements are shown
here (Fig.4 and 5).

Based on those test results, it can be taken thestrength values of the walls in terms of thetransversal and longitudinal shear forces as well as
bending moment resistances as written in Table 1.
The mortared brick wall seems almost has thesame strength compared to the ferrocement-brickwall, but it is very brittle. This condition is notgood for the buildings subject to earthquake load
which may experience suddenly collapse. Thissituation do not give chance for occupants toevacuate from the building.
It also can be seen that the ferrocement-brickwall has the strength about five times compared tothe ordinary masonry brick wall. The advantagesof the increase strength of ferrocement-brick wallcertainly can be used to retrofit brick wall houses
such that the earthquake safe houses can be gained.
In order to demonstrate the application offerrocement-brick wall to a non-engineered house,numerical simulations are performed in the next
section. Those values in Table 1 are then used todetermine the strength of the analyzed houses
subjected to an earthquake.

Fig.3 Crack during on tested specimens

496

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Wall strength
earthquake load

toperform

Longit.
shear
force
(kg)

Transv.
shear
force
(kg)

Bending
momentBrick Wall

42

800

240

Brick& Mesh

72

800

240

Brick& Mortar

300

2000

600

Brick& Ferroct.

220

2500

750

Wall types

are adopted from Indonesian Code for Padang Cityin transversal and longitudinal to the front side of
the house.

under(kg.m)NUMERICAL SIMULATION
Fig.7 Numerical model of analyzed house

In this section, structural analyses of a typicalnon-engineered house and a retrofitted house madeof ferrocement-brick sandwich material aredescribed. During Padang earthquake on 30
September 2009, many non-engineered houses in
the West Sumatra Province suffered from partially(Fig. 6) and totally collapse. This experience mustnot be happening in the future, thus the existing
ordinary brick houses in the West Sumatra need tobe retrofitted. The retrofitting model can be
performed by using wire mesh and mortar plasteron the houses to present ferrocement-bricksandwich material as the wall. This wall becomesthe main structure of the house to subject any
forces including seismic loads.

Force (kg):Fig.8 Numerical result for shear forces

Fig.6 Damaged house due to Padang earthquake
Numerical simulation is a tool can be used tocarried out the analysis of houses subjected to an
earthquake. Here, the numerical study of a typicalhouse that has experience the damage due toPadang 2009 earthquake are presented. The
simulations are carried out first for non-engineeredhouse and then for ferrocement-brick sandwichmaterial retrofitted house (Fig. 7). Seismic loads

Force (kg):Fig.9 Numerical result in longitudinal shear forces
The simulation results in terms shear forces
497

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Thanks to our students: Mangara, Rido andSiska who have generously involved in this study.

due to of transversal and longitudinal seismic loads
are shown in Fig.8 and Fig.9. In this paper only theinternal shear forces on the front side of house arepresented since they have the less strength basedon the laboratory tests.
The numerical results are then compared withthe results of laboratory testing which are used asstrength criteria analyses. The maximum forces
acting on the house exceed the strength forordinary brick wall and this indicates a housedamage in reality. The internal shear forces due toseismic loads are about 60 kg and 80 kg which are
more than 42 kg for the brick wall. Those internal
forces are still under the maximum ferrocementbrick wall strength that is 200 kg.
Thus, the ferrocement-brick sandwich material
is very useful to build the strength of the ordinary
house due to earthquake. The seismic resistant ofhouses may increase by applying mortar plaster tothe wall, but this way make the wall in brittle
condition which may collapse suddenly during theearthquake.

REFERENCES[1] Hakam A., Fauzan, Ismail F.A. and Istijono
B., “Capacity Building of Local Home Builders
on Application of Earthquake Safe House forDisaster Risk Reduction”, 4th Annual meetingof Indonesian Disaster Expert Association, will
be published in the Proceeding, May 2017,
Jakarta[2] Boen T., et al., “How to Fix Simple Buildings
Damaged by Earthquakes” (in Indonesia: Cara
Memperbaiki Bangunan Sederhana yang Rusak
Akibat Gempa Bumi), Jakarta: Boen Conslt.,
2010[3] DirJen Cipta Karya, Indonesian Code No:
111/Kpts/Ck/1993: “Guidelines for Building
Earthquake Resistant Construction” (inIndonesia: Pedoman Pembangunan Bangunan
Tahan Gempa), Jakarta 28 September 1993
[4] Imai H., Okubo N., Jamal A.U., Purwoko A.,
Zahrudin, Hamimie A., Setiyaningsih H.,
Satyarno I., Manual For Retrofitting Of Brick
Masonry Houses For Earthquake Safety: 1st
Edition, Jogja, Publisher: Kaliwangi Offset,
August 2009[5] Paramasivam P., “Ferrocement structural
applications, 26th Conference On Our WorldIn Concrete & Structures: 27 - 28 August 2001,
Singapore, pp. 99-107[6] Sakthivel P.B. and Jagannathan A., “Fibrous
Ferrocement Composite with PVC-coated
Weld Mesh and Bar-chip Polyolefin Fibers”,
Int. J. of GEOMATE, Dec., 2012, Vol. 3, No. 2(Sl. No. 6), pp. 381-388

CONCLUSION
Analyses of main structural component of nonengineered buildings have been studied in thispaper. The series of tests on that sandwich material
has been done. The tests showed that theferrocement-brick sandwich material increase thestrength up to three times compared to the brickwall. The results are used to determine the strength
criteria of the analyzed house. Based oncomparison study using numerical results andlaboratory tests, the ferrocement-brick sandwichmaterial is very useful to build earthquake strengthof ordinary brick houses in seismic prone areas
such as the West Sumatra.
ACKNOWLEDGEMENTS

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EXPERIMENTAL STUDY ON MASONRY BUILDINGSTRENGTHENED WITH FERROCEMENT LAYERS
1,2,3

Fauzan1, Febrin Anas Ismail2, Abdul Hakam3, Sindy Harvi Amalia4 and Siska Apriwelni5
Lecture in Engineering Faculty, Andalas University, Indonesia; 3,4Graduate students in Engineering
Faculty, Andalas University, Indonesia
ABSTRACTThis present study investigates the behavior of masonry building using ferrocement layers in a non-engineeredbuilding. Almost in all regions of Indonesia is an area of frequent earthquakes. In Indonesia, most of masonrybuilding are built with a limitation of finance, skills, building materials, and resulting in poor workmanship andpoor quality of construction. When an earthquake happens, the building had collapsed the walls of a sudden, thisis caused by the lack of stiffeners of the wall so that the wall is more fragile and vulnerable to tremors for thispurpose. Authors conducted a series of experimental study on masonry building strengthened with ferrocement
layers in non-engineered building. The specimens were tested above the shaking table (304 x 190) cm2 that has
simulated earthquake load with variation of ground motions. The specimens was built by masonry wall without
main structure elements (column, beam, and sloof). They consist of two models with respective size (90x90x110)
cm. The first model does not use ferrocement layers, while the second model given full of ferrocement layers.
Experimental results revealed that ferrocement layers can significantly improve masonry walls performance.
Keywords: Earthquake, Masonry, Strengthening, Ferrocement Layers
INTRODUCTION

Fig. 2
Fig. 1

The collapsed building of unreinforced
masonry building [2]Unreinforced masonry building

Non-structural components such as walls, roofs
and ceilings of a unreinforced masonry building are
not part of the main load that works on a structure, but
can be a major cause of losses due to the earthquakethat occurred.
Most damage buildings are spontaneously
constructed buildings (non-engineered building).
Where buildings are built on practical experiences
whose structural strengths are not calculated. The
building is usually built by the general public, in theform of residential houses, school buildings andtraditional home buildings. Cracks in brick wallconnections occurred during the earthquake in West
Sumatra due to the falling brick wall having no
stiffener [4].
The causes of this kind of unexpected structural
collapse can be explained from several aspects, theuncertainties inherent in the ground shaking [5],feature ground motions with larger damage potentials

Earthquakes that often occur in the area of West
Sumatra, many cause damage to buildings, especiallynon-engineering building, ranging from minor
damage to severe damage of unfit for habitation. In
general, non-engineering building are built withunreinforced masonry building as shown in figure 1
This Building is not in accordance with thestandards, because if it is built without reinforcement,
the wall of engineering building should be arranged
with composition of 1 brick. But in reality, there aremany people who rebuild the masonry building
constructed in ½ brick like figure 2, such buildings
are very vulnerable and not strong against earthquake
loads.

499

GEOMATE - Mie, Japan, Nov. 21-24, 2017[6-9], and deficiencies in our knowledge regarding
the collapse resistant design.
The choice for home improvement, certainly
influenced by the economic aspect. There are several
option to repair a damaged house, some are destroyed
and then rebuilt and some are repaired or given
strengthened, such as wire mesh.
In this study, authors are interested to perform
experimental by modelling a unreinforced masonrybuilding then strengthened with ferrocement layersthat are tested on shaking table. So it can be seen how
the behavior of unreinforced masonry building which
given variation of earthquake loads.

U Plate90

Brick Masonry(21 x 10 x 5 ) cm
Ferrocement
Layers

110

20

33

110

90

STRUCTURE MODEL

31

90

28

31

90

With ferrocement
layersWithout
ferrocement layers

M2

M1

53

110

There are two models structure that were built on
the shaking table in soil mechanical laboratory,
UNAND. Both models have a 1:4 scale of the actual.
This is due to the limitation of the table area. The firstmodel (M1) is the original of unreinforced masonrybuilding and plastered, the second (M2) is the same
masonry structure strengthened by providing fullusing ferrocement layers on both of the walls, acting
as sandwich structures. In the second model, allstrengthened parts are also plastered (figure 3).

(b)

110

(a)

50

28
90

(c)

12

90

(d)

Fig. 4 Schematic drawings of shaking table test formodel M2

Fig. 3 Two models for shaking table test : Model
M1 : unreinforced masonry structure; Model M2:
masonry structure strengthened by providing fullusing ferrocement layers on both sides of the walls,
act as sandwich structures.
Each model consisted of four walls with size 0.9m
x 1.1m. Figure 4 shows the schematic drawing ofmasonry walls for model M2. The masonry walls
were made brick (200x100x50)mm, bonded withmortar joints (1pc:4ps). The brick were imported
from Padang, Indonesia. Figure 5 showed theconstruction process for installing wire mesh andplastering. Figure 6 showed the detail of wallstrengthened with ferrocement layers.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

EXPERIMENTAL RESULTThe experimental results presented in this section
include the acceleration responses of the test
specimens and the observed cracks and failure
pattern. Testing has been done 3 times with different
model variations. Each test is given a weak
earthquake load and a medium earthquake, for thethird test, tested to a strong earthquake.
Acceleration Responses
Fig. 5 Construction process for installing wire
mesh and plastering

A g-trace device mounted beneath the shaking
table test that produces a graph showing the amountof vibration that occur in models. The test obtainedgraphs as in figure 10.
Figure 10 shows the acceleration time histories of
the 1st to 3rd test. It seemed that the maximum
acceleration responses of the 1st test were generally
greater than 2nd or 3rd test. This occurs because the 1st
test is not given additional load, so the load on thespecimen is lighter than the 2nd and 3rd tests. The
specimens on this 1st test received a larger earthquake
load, which resulted in the magnitude of theacceleration occurring.
In the 1st test as in figure 7, there is no collapse or
cracking of the specimen when subjected to a small
earthquake load or a medium earthquake load.

The specimens are made on the table in a 16˚
inclined position, this is in accordance with theearthquake loading rule of SNI 1729 - 2012 7.5.3
points, the loading applied separately in all two
orthogonal directions. The most critical load effectdue to the direction of application of earthquake
forces to the structure is considered to be satisfied if
its components and foundations are designed to carry
the following set load combinations: 100 percent
force for one direction plus 30 percent force for
perpendicular directions. Based on SNI 2012
earthquake, the slope of the prototype of 16˚ in the
direction of the positive x axis [1].
Source of electricalcurrent

Induction Motor

47

22

Shaking
Table

108

Anchor133

M1
U Plate304

Shaking
directionx
Fig. 7

y

22

39
64

190

Fig. 6151

126

Inverter
AC Drive
A1000

z

The specimens are tilted at 16˚

INPUT MOTIONS
Tests conducted by varying the frequency ofearthquake of small earthquake (SME), medium
earthquake (ME) and Strong Earthquake (SE) as
shown in table 1.
Table 1 Variation of the motions
Type of earthquake
SME (0.3g)
ME (0.6g)
SE (1g)

The specimens of the first test

Because of the limitations of the device capacity,
the acceleration of the earthquake load can not be
added until it reaches the collapse. Therefore, the 2nd
test is given an axial load on the specimen (as infigure 8) so that the earthquake load is greater than
the wall capacity and there maybe collapse in thespecimen. The load addition is calculated based on
the shear stress analysis obtained from SAP2000.
With a small earthquake acceleration and a
medium earthquake acceleration given in the second
test, the specimen (M1) only had a fine crack in theplaster but was not significant, whereas the M2
specimen did not experience any cracks. This showsthat plastering in each specimen contributes thestrength of the wall, so that the brick wall is not
destroyed.

47

108

133

M2

a (m/s2)
2.94
5.88
9.81
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 8G -trace
The specimens of the second test

Fig. 9Based on the data of the masonry building in thefield, the masonry building is also often made without
plastering or with plastering that mixture does notcomply with the applicable rules. The researcher thenattempts a 3rd test by peeling the plaster on thespecimen without ferrocement layers (M1), as shownin figure 9.

On a small earthquake acceleration, the specimen
did not collapse or cracked, then the acceleration of
the earthquake was upgraded to a medium earthquake
which resulted in fine cracks on the plaster but notsignificant. Then the earthquake acceleration isincreased until the earthquake load is strong. When astrong earthquake acceleration occurs, the wall of thespecimen (M1) is cracked.

1st Test of small earthquake load

1st Test of medium earthquake load

2

4

6

8 10 12
Time (s)14 16 18 20

0

2nd Test of small earthquake load

2

4

6

8
10
Time (s)12146Time (s)

2

8

4

10 12
Time (s)14 16 18 20

6Time (s)810

3rd Test of medium earthquake load

8

Max = 1.64g

Acceleration (g)Acceleration (g)46

Max = 1.28g

0

Max = 0.96g

2

4

Acceleration (g)16

3rd Test of small earthquake load02

2nd Test of medium earthquake load
Max = 1.24g

Acceleration (g)0Max = 2.38g

Acceleration (g)Max = 0.74g

Acceleration (g)0The specimen of the third tes

10

0

502

2

4

6

8 10 12 14 16
Time (s)18 20

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Acceleration (g)3rd Test of strong earthquake load
Max = 1.64g

0

2

4

Fig. 10 Acceleration time histories

Time (s)6810Observed Cracks and Failure Pattern
Collapse in the specimen occurs in the 3rd test witha strong earthquake load. Specimen collapsed isspecimen without ferrocement layers. When the test
is carried out, there is a lifting force on the side of thespecimen wall (M1) without opening until cracking
also occurs in each corner of the specimen as in figure
11, while on the wall having openings, there is also alarger crack may lead to collapse in the building as infigure 12. This means that the opening wall is more
vulnerable to collapse in the event of a large
earthquake, therefore the design of the house should
pay attention to the opening of a wall area and place
it not too close to the corners of the building andshould be given space from the corner of the building
to place the openings such as doors and windows.
While the specimen strengthened withferrocement layers (M2) did not experience a slightcrack during testing from the first test to the last test.

Fig. 20

The crack in the opening wall

CONCLUSION

Fig. 11

Based on data obtained from testing two Based ondata obtained from testing two models of masonrybuilding, M1 and M2 given cyclic load it can beconcluded that:
1. The specimens does not occur collapse,
because the load given does not exceed thecapacity of the specimen.
2. After providing an additional axial load. The
specimen (M1) had a fine crack in the plasterbut it is not significant. It can be concluded
that the plaster can reinforce the brick wall if
the plaster is made with a good mix andworkmanship in accordance with thestandards.
3. After providing an additional axial loadincrease and stripping of wall plastering.
There is a crack on the wall of the specimen(M1) with different rift patterns on each side

The crack of the wall without opening.
503

GEOMATE - Mie, Japan, Nov. 21-24, 2017

4.

collapse process of a three-story reinforced
concrete frame structure[4] Sihite, Ivan Darma. 2011. “Kawat anyam sebagai
perkuatan pada rumah sederhana tanpa beton
bertulang. Padang: Universitas Andalas.
[5] Takewaki I. “A comprehensive review of seismic
critical excitation methods for robust design”.
Adv Struct Eng 2005;8(4):349-62.
[6] Ni SH, Li S, Chang ZW, Xie LL. “An alternative
construction of normalized seismic design
spectra for near-fault regions”. Earthquake Eng
Eng Vib 2013;12(2):351-62[7] Wen WP, Zhai CH, Li S, Chang ZW, Xie LL.
“Constant damage inelastic displacement ratios
for the near-fault pulse-like ground motions”.
Eng Struct 2014;59:599–607.
[8] Raghunandan M, Liel AB. “Effect of groundmotion duration on earthquakeinduced structural
collapse”. Struct Saf 2013;41:119–33.
[9] Ruiz-García J, Marína MV, Terán-Gilmoreb A.
“Effect of seismic sequences in reinforced
concrete frame buildings located in soft-soilsites”. Soil Dynam Earthquake Eng 2014;63:56–
68

of the wall.
Throughout the condition, there is no crack at
the specimen with ferrocement layers (M2).
The shaking table tests demonstrated that thestrengthening using ferrocement layers is
effective in preventing collapse of masonrywalls when shakes by earthquake. This
strengthening method has such benefits as
more
simpleandunderstandable
workmanship by the local community, lowcost and time saving.

REFERENCES[1] Badan Standardisasi Nasional. 2012. “Tata Cara
Perencanaan ketahanan gempa untuk strukturbangunan gedung dan non gedung (SK SNI
1726-2012”. Jakarta.
[2] Boen, T. 2001. “Earthquake resistant design of
non-engineredbuildings
inIndonesia.
Kamakura.
[3] Li Shuang, Zuo Zhanxuan, Zhai Changhai, Xu
Shiyu, Xie Lili. 2016. “Shaking table test on the504Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

BIODEGRADEBLE POLY(L-LACTIC ACID) MICROCAPSULECONTAINING HEAT STORAGE MATERIAL: INFLUENCE
OF POLYMER MOLECULAR WEIGHT ON
ENCAPSULATION EFFICIENCY
Primprapa Sangjun1and Amorn Chaiyasat1,2*
1

2

Department of Chemistry, Faculty of Science and Technology, Rajamangala University of Technology
Thanyaburi, Pathumthani, Thailand 12110

Advanced Materials Design and Development (AMDD) Research Unit, Institute of Research and Development,
Rajamangala University of Technology Thanyaburi, Pathumthani, Thailand 12110

ABSTRACTMicrocapsule containing heat storage or phase change materials is useful in various applications. It provides
a larger heat transfer area and controls the volume change of phase change materials during phase transition.
Most polymer shells used in microcapsule are petrochemical-based polymers which is a growing concern about
their impact on the environment. Therefore, in this work, biodegradable polymer as a poly(l)-lactic acid (PLLA)
was implemented as the polymer shell to encapsulated octadecane (OD), a kind of phase change materials, by asimple emulsion evaporation method. Influence of PLLA molecular weight on the encapsulation efficiency andcolloidal stability of microcapsule was studied. The spherical microcapsules with a size range ca. 5-50 m wereobtained in all molecular weights of PLLA. However, at higher molecular weights (54,000, 77,000 and 145,000g/mol), some OD escaped from the droplets during solvent evaporation due to higher internal viscosity therein
where polymer chains hardly diffused to precipitate on the droplet interface. In contrast, using the lowest
molecular weight (24,000 g/mol), approximately 86 wt% microcapsule yields with about 100 %encapsulationand high colloidal stability were obtained which were much higher than those (44, 36 and 11% for 54,000,
77,000 and 146,000 g/mol, respectively) of higher molecular weights. In addition, latent heats of theencapsulated OD (200 J/g-OD) were closed to those (230 J/g-OD) of bulk OD. Based on high encapsulation
efficiency, this biodegradable microcapsule would enhance environmental sustainability for thermal energy
storage applications.
Keywords: Poly(l-lactic acid); Heat storage materials; Microcapsule; Simple emulsion evaporation method
petrochemical-based polymers which are a growing
concern about their impact on the environment [10,11]. Biodegradable polymer as PLLA is then thegood candidate to be used as the polymer shell ofparaffin microcapsules. Because of its non-toxicity
and environmental friendly, it is applied for avariousapplications
suchasbiomedical,
pharmaceutical, food packaging and agriculturalindustries [12, 13]. To the best of our knowledge,
there are a few researches using PLLA as phasechange materials microcapsule shell. From ourprevious work [14], we have successfully preparedmicrocapsule containing urea using PLLA as apolymer shell by a simple emulsion evaporation
method. Because urea can soluble in water, water1( containing urea) in oil ( containing polymer) inwater2 system was prepared in order to increase theencapsulation efficiency. In addition, PLLA wassuccessfully used to encapsulate more hydrophobic
material as vitamin E [15] using oil in water

INTRODUCTION
Phase change materials are used in manyindustrial applications such as solar heat storage, airconditioning of building and thermal adaptablefibers[1]. Paraffin wax is one of the most attractive
phase change materials. It melts and crystallizes
which can absorb and release energy, respectively, ata wide range of temperature. Because of theirmoderate thermal energy storage and low thermal
conductivity, paraffin is then encapsulated within thepolymer shell to increase surface area for providing
a larger heat transfer before the practical application.
Numerous polymer shells are used to fabricate
paraffin microcapsules such as polystyrene[2, 3],poly( styrene-co-methyl methacrylate)[4],
polydivinylbenzene[5, 6], poly(styrene-codivinylbenzene) [7], poly( methyl methacrylate) [8]and poly( methyl methacrylate-co-methyl acrylateco-methacrylic acid) [9]. However, most of them are505

GEOMATE - Mie, Japan, Nov. 21-24, 2017

emulsion system with a simple emulsion evaporation
method. Therefore, it would be possible to prepare
paraffin microcapsule using PLLA as a polymer
shell where paraffin and PLLA are dissolved in good
solvent as an oil phase before being dispersed in thecontinuous (water) phase having surfactant. Paraffin
microcapsule would be obtained based on an internal
phase separation mechanism. Because PLLA is morehydrophilic than that of paraffin, it should diffuse
from the polymer solution droplet to the droplet
interface during the solvent evaporation to form
polymer shell.
In this research, the preparation of paraffin
microcapsule with PLLA and octadecane (OD) as apolymer shell and phase change material core,respectively, by oil in water emulsion with a simple
emulsion evaporation method will be studied. In
addition, influences of PLLA molecular weight and
PLLA and OD ratio on the encapsulation efficiency
and colloidal stability of microcapsule will be
investigated.

system. Firstly, 2.50 g of PLLA was dissolved in 20
g of chloroform containing 2. 50 g of OD as an oilphase. It was added to 45 ml poly(vinyl alcohol)
aqueous solution (1% wt) and then homogenized at
5,000 rpm for 5 min to prepare polymer droplets in
oil in water emulsion as shown in Fig 1. Thereafter,
the obtained polymer droplets emulsion was stirred
overnight to evaporate chloroform resulting in theformation of polymer microcapsules.
Table 1 Reagent amounts for the preparation of
PLLA/OD microcapsules by a simple emulsion
evaporation method
Phase

Oil

Ingredients

AqueousMaterials

b

a

2.00

2.50

OD (g)

3.00

2.50

2.00

CHCI (g)

20.00

20.00

20.00

PVA solution(1 wt%) (g)

45.00

45.00

45.00

3

EXPERIMENTALa

PLLA (g)3.00

Molecular weight (g/mol): 24,000
Molecular weight (g/mol): 24,000 54,000 77,000
and 145,000a

PLLA molecular weights of 77,000 and 145,000g/mol were used as received from B. C. Polymers
Marketing Co., Ltd. OD (Sigma-aldrich, USA;
purity, 99%), poly(vinyl alcohol) (Aldrich,
Wisconsin, USA; degree of saponification, 87-90%)
and chloroform (RCI Labscan, Bangkok, Thailand;
purity, 99.8%) were used as received. Ethylene
glycol (Loba chemie, India; purity, 99.5%) was also
used as received.

bCharacterization of PLLA microcapsules
The microcapsules encapsulated OD wereobserved with an optical microscope ( SK100EB&SK-100ET, Seek, Seek Inter Co. Ltd. ,Thailand) and scanning electron microscope ( JSM6510, JEOL, JEOL Ltd. , Japan) to study themorphology of the particle surface and shape. For
scanning electron microscope observation, a few ofdried microcapsules were placed on a nickel
scanning electron microscope stub and dried before
Au-coated. Weight- and number-average molecularweights ( Mw and Mn, respectively) and Mw/ Mn of
PLLA were measured by gel permeation
chromatography ( Waters 2414, Waters, USA) withtwo poly(S/divinylbenzene) gel columns (Phenogel
5 x 103 and 5 x 105 Å (pores), 7.8 mm (i.d) x 30 cm(length), Phenomenex, USA) connected in series andusing tetrahydrofuran as eluent. The flow rate ofeluent was maintained at 1. 0 mL/ min with column
temperature of 40 °C and elution was monitoredwith refractive index detector (RI 2414/Waters). The
columns were calibrated with six standard PS
samples (2.5 x 103- 6.0 x 105, Mw/Mn = 1.05-1.15).
For the measurement of thermal properties, themicrocapsules were washed with 2-propanol before
dried in vacuum oven. The OD content in the dried
washed microcapsules was direction determined bythermogravimetric analyzer ( TGA, TGA 4000,

Preparation of low molecular weight PLLA
Glycolysis of commercial PLLA with molecularweight of 145,000 g/mol employing EG was carriedout to break PLLA chains[16]. PLLA and ethylene
glycol at 1:1 weight ratio were previously mixed anddissolved in chloroform (finally, 20 wt% of PLLA)
before transfer to a round bottom flask and sealedwith silicone rubber septum. The solution was
purged with five vacuum/ N2 cycles finally in a N2
atmosphere. The reaction was started at 175 C witha stirring rate of 200 rpm and kept at 30 and 60 min.
After the completion of reaction, PLLA short chainswere purified by precipitation in methanol before
dried overnight in a vacuum oven.
Microcapsule preparation
PLLA microcapsules encapsulated OD using
various molecular weight s ( 24,000, 54,000, 77,000
and 145,000 g/ mol) were prepared in oil in water
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Perkin-Elmer, USA) at a heating rate of 5 °C/ min.
The latent heats (∆Hm and ∆Hc) (J/g-capsule) and themelting (Tm) and crystallization (Tc) temperatures ofthe encapsulated OD were measured with adifferential scanning calorimeter ( DSC, DSC 4000,

Perkin-Elmer, USA) under a N2 flow in a scanningtemperature range of -20-40 °C and at aheating/ cooling rate of 5 °C/ min and shown as
average values of three measurements.

Fig. 1 Schematic diagram for the preparation of PLLA microcapsules containing OD prepared by a simple
emulsion evaporation method∆Hm* and ∆Hc* ( J/ g-OD) were, respectively,
obtained using the following equation ( 1) from the∆Hm and ∆Hc ( J/ g-capsule) and the OD content ineach washed microcapsule ( % loading) obtained
from the thermogravimetric analysis, which did notcontain unencapsulated OD.

preparation based on internal phase separation
mechanism is viscosity inside polymer solution
droplet. To the best of our knowledge, when thepolymer chains smoothly diffuse to the dropletwater interface, the microcapsule with highencapsulation would be obtained. The amount ofpolymer chain reached to the droplet-water interface
decrease with internal viscosity. In this work,
various molecular weights of PLLA were used toencapsulate OD in which using higher molecularweights was expected to obtain high capsule shellstrength. However, this parameter was optimized
based on both encapsulation efficiency and shellstrength. The low molecular weights PLLA wereobtained by glycolysis of high molecular weight
PLLA (145,000 g/mol) with various times at 30 and
60 min. It was found that the molecular weight of
PLLA significantly decreased to 54,000 and 24,000
g/ mol for the reaction times of 30 and 60 min,respectively, as shown in Fig. 1. It is due to thedepolymerization of PLLA by ethylene glycol toform shorter chain of hydroxyl ( OH) -terminated
PLLA where PLLA molecular weight decreased
with the reaction time [16, 17].

A = [B / C] x 100……( 1)WhereA = ∆Hm* and ∆Hc* of the encapsulated OD in
unit of joules per 1 g of encapsulated OD (J/g-OD)
B = ∆Hm and ∆Hc of the encapsulated OD in unitof joules per 1 g of microcapsule ( J/ g-capsule)measured with differential scanning calorimeter
C = % loading (experiment) of OD in the washedmicrocapsules measured with thermogravimetricanalysis
The theoretical % loading of OD in the washedmicrocapsules was calculated by equation (2)% Loading (theory)……(2)= [Wwax/(Wwax + WPLLA)] x 100
Where Wwax and WPLLA are weights of OD and
PLLA, respectively, in the preparation recipes
shown in Table 1.
Encapsulation efficiency ( % ) of OD was
calculated using the equation (3).
Encapsulation efficiency (%)= [%loading (experiment)/% loading (theory)] x 100……(3)
RESULTS AND DISCUSSION

(b)
(a)

One of the main driving forces for microcapsule507

GEOMATE - Mie, Japan, Nov. 21-24, 2017

in Fig. 4. For the three higher molecular weights( Fig. 4b-d) , three parts i.e. top, middle and bottom
layers of the suspensions were clearly observed
where small amounts of microcapsules floating on
the top layer were obtained. The PLLA dispersedand precipitated in the medium and the bottom
would be the broken particle and the PLLA particle
without OD, respectively. In contrast, most of
PLLA/OD microcapsules floated on the top layer forthe lowest molecular weight ( 24,000 g/ mol) of
PLLA ( Fig. 4a) . The amounts of PLLA/ OD
microcapsules at the top layer separating from eachsuspension were measured by gravimetry. It was
found that the amounts of PLLA/OD microcapsules
prepared by various PLLA molecular weights were11, 36, 44 and 86 wt% ( based on the original of
PLLA and OD) for 145,000, 77,000, 54,000 and
24,000 g/ mol, respectively. This indicates that theobtained microcapsules increased with the decreaseof PLLA molecular weight. From these results,
PLLA molecular weight of 24,000 g/ mol was
selected to be used as the polymer shell for further
study. The PLLA: OD ratio will be investigated inorder to obtain large amount of PLLA/ OD
microcapsules.

Fig. 2 Molecular weight distribution of PLLA (Mw
145,000) after glycolysis at various times (min): (a)30 and (b) 60
The PLLA/ OD solution droplets dispersed inpoly(vinyl alcohol) aqueous solution (1 wt% ) wereobtained with the homogenization. As seen in Fig. 3,
the PLLA chains with higher molecular weights
seemed incomplete miscible in CHCl3 containing
OD especially for 77,000 ( Fig. 3c) and 145,000g/mol ( Fig. 3d) where the PLLA/ OD solution
droplets contained dark domains. After CHCl3
removal, PLLA chains homogeneously distributed
throughout the microcapsule due to high internal
viscosity. This then resulted in low microcapsuleyield where numerous microparticle without OD
were obtained. In contrast, for lower molecularweights of PLLA, both PLLA/OD solution droplets,( Fig. 3a and b) and microcapsule ( Fig. 3a’ and b’)
were clearly transparent. Based on the theoretical
total density of microcapsule ( 1; densities of OD
and PLLA are 0.78 and 1.22 g/mol, respectively) at
the ratio of PLLA:OD of 1: 1, the microcapsuleshould be floated on the top layer of the suspension.
The suspension photos of PLLA/ OD microcapsuleswith various PLLA molecular weights were shown

Fig. 3 Optical micrographs of PLLA/OD droplets (a-d) and microcapsules (a’-d’) prepared by a simple emulsion
evaporation method using different PLLA molecular weights (g/mol): (a and a’) 24,000; (b and b’) 54,000); (cand c’) 77,000 and (d and d’) 145,000(a) 24,000; (b) 54,000); (c) 77,000 and (d) 145,000
PLLA:OD ratio was varied at 40:60, 50:50 and
60:40 wt% using PLLA molecular weight of 24,000
g/mol. The suspensions of three conditions wereshown in Fig. 5a-c. The densities of PLLA/OD
microcapsule increased with PLLA content inwhich most (82 % related to original of PLLA andOD) of PLLA/OD microcapsules precipitated onto
the bottom layer in the case of 60:40 wt%. However,this phenomenon was also observed for 40:60 wt%

Fig. 4 Suspension photos of PLLA/OD
microcapsules after centrifugation at 3,000 rpm
using different PLLA molecular weights (g/mol):508

GEOMATE - Mie, Japan, Nov. 21-24, 2017of PLLA:OD (30 % related to original of PLLA and
OD). The precipitated polymer is due to thepolymer part of the broken microcapsule in which
low content of PLLA was not enough to
encapsulate OD. The microcapsule size andmorphology of all PLLA:OD ratios were thenobserved by optical microscope as shown in Fig.
5a’-c’. It was found that uneven surface
microcapsules (Fig. 5a’) were observed with somebroken particles in the case of 40:60 wt% of
PLLA:OD according to the suspension photo. On
the other hands, the spherical microcapsules wereformed in the cases of 50:50 (Fig. 5b’) and 60:40
wt% (Fig. 5c’) without broken particle. This seems
that the PLLA shell can completely envelope the
OD core.

microcapsules using PLLA:OD ratio of 50:50 and
60:40 were observed by thermogravimetric analysis
and the thermograms are shown in Fig. 6. In thecase of dried PLLA/OD microcapsules (Fig. 6c andd), the decomposition temperatures of OD (130260°C) and PLLA (280-420C) were shown in two
respective steps. The degradation temperature ofbulk OD (Fig. 6a) of 140-300°C was closed to thatof the encapsulated OD. The thermogravimetricanalysis thermograms confirmed that OD existed in
the prepared microcapsules. In addition, in the caseof 50:50, the experimental percent loading was 50%
which was closed to the theoretical ones (50%)
giving 100% encapsulation where the experimental
percent loading was 27% giving only 65%
encapsulation in the case of 60:40 ratio. This
indicates that PLLA represented high efficiency toencapsulate OD.

Fig. 5 Suspension photos (a-c) and opticalphotographs (a’-c’) of PLLA/OD microcapsules
using PLLA molecular weight of 24,000 g/mol after
centrifugation at 3,000 rpm with different PLLA:
OD ratios (wt%): (a and a’) 40:60; (b and b’) 50:50
and (c and c’) 60:40

Fig.
7
Differential
scanning
calorimeter
thermograms of (a) bulk OD and (b) the
encapsulated OD in dried microcapsules at
PLLA:OD ratio of 50:50 %w/w
The latent heats (J/g-OD and J/g-sample forbulk and encapsulated OD, respectively) of bulk
OD (Fig. 7a) and the encapsulated OD (Fig. 7b)
were obtained from the heating/cooling peak areasof differential scanning calorimeter thermograms.
The latent heats (Hm* = 197 and Hc* = 196 J/gOD) of the encapsulated OD were quite closed tothose of bulk OD (Hm* = 233 and Hc* = 234 J/gOD). It may be due to the hydrophilicity of PLLA
increased the phase separation between polymer
shell and OD core where the encapsulated OD
behaved similar with bulk OD.

(d)Temperature

Fig. 6 Thermogravimetric analysis thermograms of(a) bulk OD, (b) PLLA and dried PLLA/OD
microcapsules at PLLA:OD ratio (wt%) of (c)50:50 and (d) 60:40

CONCLUSION
The spherical biodegradable poly(l)-lactic acidmicrocapsule containing octadecane with good
colloidal stability was successfully prepared by asimple solvent evaporation method. The molecularweight of poly(l)-lactic acid affected on theformation of the microcapsule shell. The lower

The degradation temperatures of bulk OD,
PLLA and OD encapsulated in the PLLA
509

GEOMATE - Mie, Japan, Nov. 21-24, 2017

molecular weight poly(l)-lactic acid formed thesmoother shell than the higher ones based on lower
internal viscosity. The latent heats of theencapsulated octadecane were closed to those ofbulk octadecane. Therefore, the prepared polylactic
acid/octadecane microcapsules were able to use inheat storage applications in place of petrochemicalbased microcapsule.

[8]

ACKNOWLEDGEMENTS[9]This work was supported by the project ofResearch and Researchers for Industries (RRI),
Thailand Research Fund (TRF) and STP Chem
Solutions Co., Ltd. (MSD60I0017)
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Eriksen M, Williamson N J, and Boldgiv
B, "High-levels of microplastic pollution
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GEOMATE- Mie, Japan,
Nov. 21-24,
Seventh International
Conference
on 2017
Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

COMPOSITE MATERIALS FOR CIVIL/STRUCTURALENGINEERINGK K Ganguly (Gangopadhyay)
Executive Director
Development consultants Private Limited, Kolkata, India
ABSTRACTThe use of composite materials for concrete is covered briefly starting from metallic reinforcement
along with stainless steel bars which have been used in concrete elements by the engineers successfully
primarily to improve the strength against tensile loads. The above combination has been further improved byusing different types of fibres covering natural, steel, glass, carbon etc. along with fibre reinforced polymers(FRP) in structures. Strengthening structural members for carrying additional loads to meet new requirements
have also been done with different wrapping FRP composite materials. Polymer composite materials are
manufactured by combining polymer resin with fillers and various types of reinforcing fibres. Concrete as amaterial is durable and energy efficient. Attempts are made for adopting eco-cement for carbon sequestrationand to use alternative material to Portland cement to make the applications more environment friendly.
Reference is given to the use of nano and geo-polymer concrete, polymer concrete, high strength and coloured
concrete etc. Concrete structures can be repaired and strengthened, if required, and concrete material can berecycled and used with other materials. Concrete material has been found to perform well in fire and against
blast. Routine monitoring for assessment of weaknesses, defects and delamination of FRP materials fromstructural elements and relevant studies are referred. A few applications are included. Further advancements
will be more suitable for the projects to come, in the future. This approach is expected to provide satisfactory
performance of the structures with added elegance, innovativeness and overall long-term economy at the end.
Keywords: Fibres, Polymer Composites, Different developments, Monitoring, Delamination
INTRODUCTIONFIBRE COMPOSITE MATERIALS

Composite materials for concrete had beenused by engineers for a long time [1], [2]. Use ofdifferent types of fibres along with reinforcement
had been tried successfully to overcome
weaknesses of concrete. Polymer composite are
multiphase materials produced by combining
polymer resin like polyester, vinyl ester, epoxy(thermoset) and polyethylene, polypropylene(thermo-plastic) with fillers and reinforcing fibres
to produce a material having much superiormechanical and chemical properties than theindividual base materials combined. The emphasis
was on high strength, low self weight anddurability.

Fibre composite materials have been usedfor various applications for a long time covering
concrete and steel structure. Common fibres may
be used.
Requirements of Fibres [5] - The desirable fibre
requirements are –• The variation of strength between individual
fibres should be less.
• The fibres should be stable and retain theirstrength during handling and fabrication.
• The diameter and surface of fibres should be
uniform.
Other Important Qualities [3], [5] – Matrix,
Interface and Geometrical information

TYPES OF COMMON FIBRES [3], [4]Numerous fibres have been tried. Some of thecommon types are as mentioned below:• Natural vegetable or mineral fibres (sisal, jute,bamboo & asbestos)• Alkali or non-alkali resistant glass fibres• Aramid fibres• Polypropylene fibres• Steel fibres• Carbon fibres• Other fibre types - Ceramic, Nylon, Polyester.

REINFORCING SYSTEM IN CONCRETE• Mild Steel Bars –••• ColdTwistedNormally not much
High
Strengthused
Bars
Galvanised Bars
• Stainless SteelFRP Bars - FRP is particularly beneficial in highly
corrosive environment & electromagnetic [6]applications.

Stainless steel may be used in areas directlyat the risk of chloride induced corrosion. The

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

stainless steel bars may be used as the first layer[7] of reinforcement for the structural members. In
marine environment where corrosion is moreaggressive, use of stainless steel bars may bejustified over carbon steel considering reduced
maintenance or extended service life of structures[8].

GLASS FIBRESGlass Reinforced Concrete (GRC) is acement based composite which has been applied
successfully in different areas of projects. The
resulting material will have high tensile, flexural,
impact and abrasion resisting properties [15].
Special e-GRC [16] will be suitable for economy
and to produce cleaner and brighter facades of thebuildings and will contribute towards reduction ofnoise and pollution in urban environment.

FRP Reinforcing Bars - Reinforcing bars are
made using mostly glass and carbon fibres [6] by“pultrasion” method with secondary process foradequate bond properties. Aramid fibres can also
be used.

Permanent Formwork with GRC - GRC panels
are of flat sheets or profiled sheets which have beenused as permanent formwork [17] for theconstruction of composite decks.

Basalt Reinforcement [9] - Basalt reinforcement
has been attempted in concrete beams to use as analternative to steel bars. Concrete beams withbasalt reinforcement have been tested against
flexural behaviour.

Arching Action in Concrete Slabs & FRP
Reinforcement - Concrete slabs were tested
utilising in plane Compressive Membrane Action(CMA) with Glass Fibre Reinforced Plastic(GFRP) bars [18]. The test results indicate higher
deflection for simply supported slab with GFRP as
compared to equivalent slab with steel
reinforcement. However, with lateral restraint the
mid span deflection was reduced significantly.

Special Application of Basalt Fibre Reinforced
Polymer Bars - Basalt fibre reinforced polymers(BFRP) have been used as rods [10] for theconnections of timber structures instead of steel
bars.
STEEL FIBRESCARBON FIBRES

The advantages of steel fibres, in concrete,
are for controlled crack width, redistribution ofstresses, enhanced load bearing a capacity, timesavings and added ductility [11]. When steel fibres
are added to concrete mix, the performance of thematerial particularly impact resistance andtoughness will be increased. For pile supported
floors this toughness will be very important in theload bearing and deformation behaviour [12]. A
combination of conventional reinforcement withsteel fibres may prove to be a proper solution
considering cost and performance. Steel fibre
reinforced concrete slabs have been tested
successfully. Reasonable agreement between
elastic theory and actual test results was observed[13].

Short pitch-based carbon fibres may be
used in concrete for increasing flexural strength,
toughness compressive strength etc..
High
modulus (HM20) carbon fibres may be used inconjunction with either a polymer or a cement
matrix [5].
ARAMID FIBRES
Aramid fibres are man made organic fibres
which have high degree of crystallinity. Higher
modulus fibres are used in polymer composites [5].
SYNTHETIC/NON-METALLIC FIBRES
The most relevant ones are polyolefins [5](Polypropylene and polyethylene), polyamide(nylon) and polyester. The polyolefins are used forthe production of cement/mortar composites. The
use of structural synthetic fibres will prevent
plastic shrinkage cracking in concrete floors slabs
and bridge decks and will demonstrate better
performance against impact resistance and tensile
strength in a more homogenous manner than steel[18]. Non-metallic reinforcement will increase
durability of concrete and such reinforcement do
not corrode [19].

Micro-silica & Steel Fibre Concrete [14] Micro silica with steel Fibres has been selected andused for industrial floors to provide high strength,
wear resistant durability and impact resistance.
Construction of Composite Floor Slabs using
Steel Fibre Reinforced Concrete - Steel fibre
reinforced Concrete is used for the construction offloor slabs in high-rise structures. Full scale tests[12] on suspended slabs have indicated specialist
steel fibres increased slab ductility and the yieldlines to develop.

MACRO SYNTHETIC FIBRES

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

It had been commented from research [20]that use of macro synthetic fibres, in concrete, wasefficient under seismic conditions due to tridimensional nature of the reinforcement.
Furthermore structural elements performed moreductile and the concrete with these synthetic fibres
would be able to absorb high levels of energy.
Fibres can be used in external concrete slabs andpre-cast elements [21].

conventional steel reinforcement using reinforcing
bars or fabric. Both macro synthetic and steel
fibres can perform the same function instead.
Micro synthetic fibres can be used to provide
control on shrinkage cracks mainly in groundbearing floor slabs, metal decking, sprayedconcrete.
POLYESTER FIBRES
Various applications have already been
done, in the past, using polyester fibres in cement
concrete.

MICRO POLY-PROPYLENE FIBRES
Primarily suitable to control drying
shrinkage and settlement cracking including
explosive spalling under fire [21]. The health andsafety benefits of using polypropylene fibre
reinforced concrete will cover construction,
maintenance and demolition [22]. It is commented[23] that monofilament polypropylene fibres will
provide great advantage in both design andperformance for external applications.

NATURAL FIBRES[27]Natural fibre reinforced concrete willconsist of small dia-meter discontinuous, discrete
natural fibres of different origin randomly mixed ina cementitious matrix.
FIBRE REINFORCED POLYMERS (FRP)
This is basically a combination of fibrous
reinforcement held in a polymer matrix to form
plates, tubes, rods and other structural profiles [28].
The fibres may be carbon, aramid or glass and theresins may be epoxy, polyester, vinylester or
phenolic. FRP materials exhibited good resistanceto fatigue and creep and are very durable. FRPs
have good fire resistance as they are poor heat
conductors and this is advantageous over metals.
When the composite and adhesive have beencorrectly specified, FRP materials will require
little or no maintenance during the service life.
FRP wrapping can increase the bending and shear
strength of an element by a factor around three [29].

INFLUENCEOF
GLASS,POLYPROPYLENE & STEEL FIBRESON
PHYSICALPROPERTIESOFCONCRETE
The following comments are from theinvestigation carried out [21]• Concrete workability was least affected by glass
fibres and most affected by polypropylene fibres.
• All fibres were efficient for compensating
shrinkage cracks.
• All fibres increased abrasion resistance ofconcrete.
• All fibres increased impact resistance of concrete
upto 10 kg./cum.
• Flexure strength increased with glass fibre
addition.
POLYPROPYLENECOMBINATION

&

STEEL

GLASS FIBRE REINFORCED POLYMER(GFRP)
Studies have been made to improve thebehaviour of the member by using glass fibre
reinforced polymer (GFRP), in concrete beams,
along with steel as reinforcement for studying theperformance at serviceability limit stage. TheGFRP reinforced beams had higher failure loads,
reinforcement strains, deflections and cracking
compared to similar beams with steel
reinforcement [30].

FIBRE

It has been commented that combination ofpolypropylene and steel fibres (i.e. hybrid system)
may be suitable for all types of concrete
applications but will be more beneficial for groundsupported slabs [25].

Large Diameter Columns Reinforced With
WRAPPED Glass Fibre Reinforced Plastic
Tubing Large diameter (greater than 300 mm) GFRP tubes
filled with concrete have been tested at
Southampton [31] University, U.K., for both
axially and eccentrically loaded columns. As
expected centrally loaded columns failed at higher
loads than corresponding eccentrically loaded

COMPARISONBETWEEN
MACROSYNTHETIC &STEEL FIBRE REINFORCED CONCRETE[26]
Comparison between two fibres have beenstudied specially in respect to limit crack widths inconcrete which is generally done by providing

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

columns. The failures were sudden and explosive
and at failure, located near the centre of columns
fibres tended to unwrap themselves from thespecimen.

SPECIALCOMMENTSON
FRP
STRENGTHENING
Confinement of FRP Jacketed Reinforced
Concrete Columns - Following the tests on FRP
jacketed reinforced concrete square/rectangular,
circular columns with 21 MPa Concrete and using
high tensile fibres of Carbon, glass and aramid,some comments are [36] –• FRP strengthening columns performed better,the failure can be sudden.
• Decreasing the corner sharpness increased both
ultimate strength and ultimate axial
deformation on square cross sections withcarbon fibre reinforced jackets.
• Circular columns experienced uniform
confined pressure with significant increase instrength with carbon fibre jacketing

CARBON REINFORCED POLYMER
Carbon fibres reinforced polymer (CFRP)
plates have been used for shear strengthening forbeams [32]. A large number of beams had beentested at Oxford Brookes University to study theperformance of carbon fibres reinforced polymer(CFRP) plates for increasing the shear resistance ofthe reinforced concrete beams. It was commented
that CFRP material was well suited forstrengthening, bonding to sofit was effective andbeam stiffness increased. Using two horizontal
CFRP strips over shear span and tension zone
seems to be an efficient method of shear
strengthening.

Inspection for FRP Strengthening - The
presence of moisture may be the main cause ofdeterioration of FRP strengthening system [37].
Techniques such as water jetting, grit blasting or
steam curing should not be used for cleaning. All
strengthened structures should be subjected toroutine visual inspections and regular, with moredetailed inspections from time to time. The
disadvantages of FRP strengthening are –[37]-[38]• The risk of soffit reinforcement hit by overweight vehicles.
Hence, some kind ofprotection has to be considered.

Evaluation of Carbon Reinforced Polymer
Plates for strengthening Reinforced Concrete
Members Experimental study of the strengthened reinforced
concrete beams by bonding composite plates has
been done [32]. Bonded plates increased ultimate
capacity of beams but reduced ductility.
Polymer (CFRP) Composite and Concrete Slab
- A concrete slab was designed with CFRP
corrugated sheet as permanent form work andtension reinforcement [33]. Following the test it
was commented that the slab was capable ofwithstanding large plastic deformation.
The
performance of the slab at serviceability limit state
was also satisfactory.

OTHER DEVELOPMENTS IN CONCRETE
TECHNOLOGY
The development of concrete took placesignificantly in the following areas Ferro-cement [39], [40] - Ferro-cement is
actually related to special reinforced concrete workwhen cement mortar and reinforcement in the formof layers of wire mesh and small diameter steel
bars are used to produce, stiff structural form.

HIGH PERFORMANCE POLYMER FIBRESHigh performance polymer (HPP) fibres
have been used for design and construction ofground supported slabs. They have high resistanceto acidic and alkaline environments [34]. HPP
fibres are used in pre-cast housing panels andindustrial floor slabs especially external slabs
where surface fibres do not corrode.

High Strength Concrete [1], [2] & [40] - The useof mineral aggregates such as in combination withsuper plasticisers such as polycarboxylic ethers(PCEs) are responsible for HSC and enhance
impermeability, durability and strength.

CREEP TESTS FOR FIBRE REINFORCED
CONCRETE

Nano & Special Concrete [41], [42] - The nanoconcrete is made with Portland cement withparticle size less than 500 nm. [42] as a cementing
agent. In recent years it has been observed that
concrete can be based on nano technology to
improve the properties of conventional concrete.
High performance binders reinforced with nano

The tests were done on plain and synthetic
fibre concrete beams for modulus of rupture,elastic deformation [35] and studied for a period of
12 months. The presence or otherwise of fibres did
not influence the flow component of creep. High
modulus macro synthetic fibres exhibited creep
similar to that of steel fibres [26].

514GEOMATE - Mie, Japan, Nov. 21-24, 2017

particles or nano tubes including nano cement may
be used [43].

The use of cellular high porous litght weightaggregate which is formed from volcanic ash
compressed under extreme pressure is made for the
preparation of HPLC concrete along with othermaterials as used for conventional concrete. It is
required for modern marine structures [50].

Geo-polymer Concrete [43], [44] - Geo-polymer
is an alternative cementitous binder that has been
attempted as a substitute for OPC which iscomprised of an alkali-activated fly ash. Geopolymers are in organic materials rich in silicon(Si) and aluminium (al) that will react with alkaline
activators to become cementitous.

FURTHER ADVANTAGESCONCRETE

OF

USING

Fire Engineering & Performance of Concrete
under Fire [51] - [53] - Concrete has performed
very well [2], [51] - [53] during fire over the years
and the same has been observed during tests
carried out. Performance based approach will
provide greater advantages [52]. It has beenreported that concrete strength higher than 55 MP[53] are more susceptible to spalling and may show
lower fire resistance. In order to reduce spalling,in high strength concrete under fire, fibres may be
used in the concrete mix or protecting the concretesurfaces at salient places with thermal barriers.

High Performance Concrete [1, 40] - Highperformance concrete will be high strength
concrete with low permeability. Higher doses ofsuper plasticisers may be required to provide
desired workability of the concrete mix.
Silica Fume for High Performance Concrete[45] - Silica fume is being used for the productionof high quality concrete for its high strength, highchemical and abrasion resistance and durability inmarine environment. For high performance silica
fume concrete is becoming popular for different
applications.

Design for Blasts - Concrete has performed wellagainst blast loads. Presence of continuous
reinforcement [54] with good detailing will
provide reserve capacity to develop alternate load
path and resistance mechanism under extreme
conditions. Steel fibre reinforced concrete (SFRC)
can make an important contribution to the integrity
and resistance to blast resistant structures [55].

Coloured Concrete [46] – [47] - The colour
system can offer excellent segment dispersion [46],
uniform colour, 28 standard [47], colours withcolour matching, UV-stable and fade resistantcolours in concrete.

UHPFRC Panel Testing for Explosion andImpact - Studies with the help of experimental
work were carried out with steel fibre
reinforcement to investigate the properties of ultrahigh performance fibre reinforced concrete(UHPFRC) under impact and explosive loading(100 kg TNT equivalent) and found to be suitable[53]. The material exhibited non-linear yielding.

Polymer Concrete [1], [40] - As compared tonormal concrete the strength and other propertiesof polymer concrete will be improved along withincreased chemical resistance and reduced
permeability.
Self Compacted Concrete [40] - Self Compacted
Concrete (SCC) will be compacting itself inpresence of reinforcement in the form work andsuitable for areas with limited access for placementof concrete and vibration. It is flowable, selflevelling, self-developing and cohesive and can behandled without segregation. Self compacting
concrete with premix GRC has been tried.
Rheology modifier may be required to control
segregation in the GRC mix. SCC can provide
improved durability and faster construction andinnovative design [48].

ECO CEMENT [56]The emphasis now is to find out thealternative materials to Portland cement and thefollowing may be considered in this connection ;• One alternative is to avoid the use of limestone altogether from manufacturer process.
It will be important to utilise magnesium incements to have carbon absorption
characteristics with greater impressive andtensile strength.
• Eco cements can be produced at low
temperature. This means manufacturers haveto use renewal sources of energy (i.e. solar
furnaces).
• Magnesium cements can have greater
compressive and tensile strength and can be

Sprayed Concrete [49] - Sprayed concrete has
been used for various application including new
construction strengthening and repair work, fire
protection to steel framed structures, tunnel linings
etc.
High Performance Light Weight Concrete High performance light weight concrete (HPLC) is
associated with high strength and long durability.

515

GEOMATE - Mie, Japan, Nov. 21-24, 2017used to build lighter structure with better
insulating properties.

The failure plane can be at the surface ofconcrete or at the level of steel reinforcement.
It is mentioned that the presence of concave
surface profile at the soffit of a beam will reducethe degree of flexural strengthening by externallybonded FRP composite.

RECYCLING CONCRETE MATERIALS [57]Concrete material after prolonged use whendemolished can be recycled for further re-use fordifferent construction activities.

Debonding Failures in CFRP – Strengthened[61] Steel Structures

Re-cycled aggregates - Upto 30% recycledconcrete aggregates (RCA) as replacement of
natural aggregates will have no adverse effect onengineering and durable properties of concrete [57].
RCA will be preferable consisting impact on –• Potentially reducing transport impacts

Studies including experimental work on theperformance of CFRP laminates/plates have been
made to assess the performance of the joint,
particularly the role of adhesive. De-bonding
failures between steel member and CFRP is critical
may take place in one of the following modes:• Within the adhesive (cohesion failure)•
Between the adhesive andadherends (adhesive failure)•
A combination of adhesion failure andcohesion failure

DE-BONDING OF FRP COMPOSITES
De-bond problems is a critical issue forproper assessment of performance related to FRP
composites in structural strengthening and repair
applications. Some comments are made on FRP tosteel and FRP to concrete based on experimental
and theoretical studies [58] as given below :DETECTING DELAMINATION IN FRPRETROFITTED CONCRETE STRUCTURES[62]

FRP Repair to Fatigue Damaged Steel
Members [59] - A few important comments fromtests on repair of fatigue damaged steel members
using FRP steel systems are • Notched steel specimens with FRP patches
have resulted in significant increases inremaining fatigue life of the specimen.
• Length of the patch (perpendicular to crackorientation) is found to be more effective thanits width (parallel to crack orientation)• Symmetric bonding of the patches isrecommended where possible
FRP Strengthening to RC Beams [59] - The
comments from studies and research work on
debonding failures in FRP strengthened RC
beams :• Assessment of proper de-bonding failures is an
essential part of RC beam strengthening using
FRP composites.
• Despite brittle nature of de-bonding failures, test
results indicated that initiation of FRP debonding took place at laminate ends and at crack
locations at early load levels.
• Cover of de-bonding takes place along with there-bar level differs significantly for FRP debonding mechanisms in its causes and behaviour.
Experimental studies have been carried out [60]to assess the effect of surface profile on the
flexural strength of RC sections with FRP. The
failure of concrete section strengthened byexternally bonded FRP can be due to• Failure where composite action is maintained• Failure where composite action is lost.

The concern exists for weakening of thebond due to environmental factors such as wet anddry cycles, thermal variation and freeze-thaw
cycles as applicable. The failure, if takes place,will be brittle type and will have catastrophic
consequences. Traditional ultrasonic methods(linear) have long been used for conditionassessment of the materials. In the study forassessment [63] non-linear elastic wave
spectroscopy (NEWS) has been used. In NEWSfrequency characteristics of the received signal are
analysed to understand the condition of thematerial. Following the laboratory experiments, it
is commented that NEWS can not be used as thebase line technique for condition assessment. Prior
measurements may be compared with newmeasurements for condition assessment of FRP.

516

GEOMATE - Mie, Japan, Nov. 21-24, 2017

APPLICATIONS - Composite materials have been used successfully, in various projects, in different
countries. Only a few are selected as given in the table with some brief details.
No.
01.

Item & Brief Details
Tunnel Lining [63]Use/Strengthening
Steel fibres

02.

Rock Support, Tunnel [64]03.

Suspended
floor
slab
supported on piles [65]Pile supported Car Park [66]External Cladding [67]Steel fibres, Sprayedconcrete
Steel fibres

04.
05.
06.
07.

08.
09.

The Atlantis Hotel, External
Cladding [68]Recladding WestChester
County Courthouse [69]Dome Structure, CatholicChurch [70]Black pool’s promenade [71]10.

Scrabster Harbour Sea Wall
[72]

11.

Underground
Car
Tunnel Lining [73]12.

Belfast International Airport,drainage channel [74]Tunnellining,ChannelTunnel Rail Link [75]

13.

Park,

14.

Tunnel linings [76]15.

Marine concrete [77]

16.
17.

Industrial floors [78]Hertfordshire Warehouse[79]18.

Biggest SF RC Flooring [80]19.

Fibres in floor screed [81]

20.
21.

Rigid pavement [82]Road Tunnel [83]22.

Pre-stressed concrete bridge
strengthening [84]Steel bridge strengthening
[85]

23.

Country
Netharlands,
Germany
U.K.

Remarks
SFRC exhibited reduced
crack development
50-100 aspect ratio was used

U.K.

Crack width may be criticalthan deflection
To withstand 100 KN/m2
Stone like finish was
required
Ribbedfaçadepanels,Lighter Units
External cladding

Steel fibres
GRC, Single skinpanels
GRC façade Units

Belfast, U.K.
Wharf
Galleria, U.K.
Dubai

GRC panels

N.Y.

GRC

UkraineMacro
Synthetic
fibresGround granulated
balst furnace slag
(ggbs)
Macro Synthetic
fibresU.K.

Macro Synthetic
fibresSteel &Polypropylene
fibresPolypropylene
Netherlands fibres
Monofilament
polypropylene fibres
Steel fibres (SFRC)
Steel fibres (50 mm
long 1mm diameter)
Steel fibres

ScotlandLargest marine engineering
application

Sweden,Norway &Japan
Belfast, UK

Sprayed Concrete

U.K.

Synthetic fibres replaced
welded reinforcement mesh
Precast Segments, use of
PPa

U.K.
U.K.
U.K.
U.K.

Polypropylene fibres
60 mm long and 60
micron in dia
Steel fibres
Steel/Macro
Synthetic fibres,
sprayed concrete
CFRP Plates

U.K.

Ultra high modulus(UHV) CFRP plates

UK

517

22 m dia dome, 26 m above
ground level
Strux 90/40 fibres used

Hind-Headtunnel, U.K.
Skipton, UK

Jointless, different projects
Large area of 60000 sqm
excellent flatness achieved
250,000 sqm. (approx..)area, Joint-less groundbearing slab
4 kg drop tests for screed
crushing resistance
As reinforcement
Executed quickly

Pre-stressed concrete beams
strengthenedJob
executed
without
interrupting rail traffic

GEOMATE - Mie, Japan, Nov. 21-24, 201724.

Concrete Bridges [86]

CFRP Plates, NSM
reinforcement.

25.

Strengthening of Concrete
bridges [87]26.

Concrete bridge
strengthening [88]Strengthening bridge
columns [89]Jack-arch beams
strengthening [90]Harbour City Car Park [91]

Carbonfibre
Composite Plates,
NSM reinf.
NSM tapes & FRP
Bars
Aramid FRP sheets

27.
28.
29.

30.
31.

32.
33.
34.
35.

36.

37.

Park House
Bridge(UK);
Tay
Road
Bridge (UK)Japan, USA,UK

CFRP
Compositematerials
Aramid fibre sheets

Car
park
Multi-storied,
Merseyside Police [92]Fertiliser prill tower [93]

NSM reinf.
CFRP Strips
CFRP-Plates

UK,
Liverpool
Qatar

Ribbedfloor
slabstrengthening [94]Composite
Metal
deck
applications [95]
Coastal Defence Project
Blackpool [96]Concrete Chimney strength
retrofitting [97]Carbonfibre
Laminates
Fibre reinforcement

UK

Glass fibre(GFRP)
reinforced polymer
CFRP Composites[97]
FRP Composites[98]
Geo-polymer
injection, Hoxton
Property
Ecl/Pie Island
Innovation
Strips, Sheet reinf.
(geotextile),
Composite
reinf.,
Anchors

UK

Soil stabilisation [99]Earth Reinforcement [100]Strengthening Soffit, Shear,
top deck

USA
Middlesborough, UK
London UG
Ltd. (LUL)
UK

bars

Used for different parts ofthe bridge

U.K.

24 No. tapered columns
strengthened on two bridges

164 No. Columns
strengthened, addition of
extra floors
Car park decks strengthened
against flexure
Specially
formulated
adhesive used
Carbon fibre laminates
bonded at the bottom
Time saving upto 20% may
be achieved

USA,
Switzerland,
Japan
USA, Europe
UK

Lower installation
maintenance cost

and

UK

Additional soil stabilisation

U.K.

Bridge Abantments, Vaults,
Land reclamation, Slopestability

To increase foundation load
bearing capacitywith corroded steel reinforcement. The durabilityof fibre reinforced concrete can be considered as
good.

DURABILITY OF FIBRE REINFORCED
CONCRETE [101]For durability, corrosion to steel fibres andperformance of polymeric fibres under alkaline
environment are the main concern. Polypropylene
fibre is the only polymeric fibre that has beentested for field applications for a long period. The
performance of polypropylene fibres underalkaline environment is found to be satisfactory
and unaffected by time and exposure in crack
width upto 5 mm, uncracked SRC specimens arelargely unaffected by corrosion [101].
Even
the fibres do corrode, small volume of each fibre
and the fibre being discontinuous will not create
problems of cracking like conventional concrete

STRUCTURAL PERFORMANCE
The performance of the composite
materials is expected to be better considering highspecific stiffness and strength. Low self weight ofthe material will provide other benefits such as
reduced structural dimensions and reduced cost fortransport and erection. It seems that performanceof FRP materials specially for strengthening work
is satisfactory and reliable when the same is
executed properly. However, regular checks and518

GEOMATE - Mie, Japan, Nov. 21-24, 2017

monitoring for condition assessment will be
required.

REPAIR WORKThe repair work to concrete structures isoften associated with the following types due tovarious reasons including environmental factors,
constructional deficiencies and poor quality of
improper rebar concrete cover. These are –FAILURE INVESTIGATIONS AND THE
FORENSIC PROCESS [102]Forensic engineering is associated with
detective skill as opposed to design skill which willbe the key requirement for the investigator.
Causation investigation will be the prime item forthe forensic approach. The forensic process starts
with an investigator collecting and collating
physical evidence connected with the failure in an
objective manner.

•
•
•
•

Non-destructive tests (NDT) are often done on
concrete structural elements for diagnosis and forproper assessment prior to repair work. Some
comments will be made on fire damaged structures
below :

CORROSION TO REINFORCEMENT
This is associated with the de-gradation of
the metal by an electro-chemical reaction with its
environment. The four essential items are anode,cathode, electrolyte and electrical connection. In
the absence of any one of the components, thecorrosion reaction will stop [103]. Both oxygen
and water must be present for corrosion to occur.
Corrosion to reinforcing bars, in concrete members,
is responsible for damage and associated repair
work.
INSPECTION&MONITORING
CONCRETE STRUCTURES

Cracking
Surface Repair
Strengthening/Retrofitting
Ground Stabilisation

Repairs to Fire Damaged Structures [106] The main purpose of repairing the structure will beto restore the structure to perform similar to thecondition it had before the fire, both in respect ofstrength and fire resistance in a future fire. The
properties of concrete will be altered at hightemperature and if the temperature reaches above
5000C and the outer layer of concrete will be muchaffected when the temperature reaches 9000C. The
concrete below the surface may not have sufferedmuch damage in many cases.

OF

The advantages of continuous structural
health monitoring are [104] –Early warning of problems, indication of structural
current life time, cheaper maintenance and lower
running cost, enhanced safety. The items forsurveying activities are visual inspection,
dimensional
measurements,
cover
depth
measurement, rebound hammer tests, carbonation
depth measurements and assessment of possible
onset of corrosion. The use of sensors is common.

Assessment for the effect of fire on structuralmembers [106] - Proper accounting for safety of
the affected structural members will be very
important. It may be necessary to remove someloads from structural members wherever possible
during repair work using proper propping. For
repairing materials Cementitous mortar andconcrete will be more suitable for fire damaged
concrete structures.
Load Tests - It may be necessary to carry out load
testing of some selected members of the affectedareas after completing the repair work for further
confidence and satisfaction.

PROTECTIVE COATINGS [105]Concrete surfaces, in a structure, can be treatedwith protective coatings for –• Prevention of direct deterioration due tochemical and physical effects.
• Prevention of indirect deteriorationinduced by reinforcement corrosion.
• Enhancement or maintenance ofappearance
The use of protective treatment on concrete
structures is quite common and has increased inrecent years.

COST [107]Fibre composite materials are expensive
initially as compared to conventional construction
materials. High cost is mainly due to the cost of
raw materials. The applications are attractive dueto their high strength-weight and stiffness toweight ratios, corrosion resistance, light weightand potentially high durability. With more use of
the composite materials the cost is likely to godown. However, maintenance cost including life
cycle cost will be much less as compared to519

GEOMATE - Mie, Japan, Nov. 21-24, 2017

conventional structural materials. Hence overall
economy is expected in the long run.

[09]

GOHNERT M, VAN GOOL R and
BENJAMIN M, Basalt reinforcement in
concrete beams in flexure, School of Civil
and Environmental Engineering, Universityof Witwatersrand, South Africa, StructuralEngineer, February 2014, PP. 38-43.
[10] YEBOAH D., TAYLOR S., mcpolin D &GILFILLAN R, Pullout behaviour of
axially loaded basalt fibre reinforced
polymer (BFRP) rods bonded parallel to thegrain of glulam elements, The StructuralEngineer, May 2012, PP. 42-57.
[11] GREENHALGH J, Ten years of steel fibre
concrete : a manufacturer’s view, Concrete,
September 2001, PP. 51-52.
[12] THOOFT H, Structural behaviour of steel
fibre reinforced pile supported concrete
floors, CONCRETE, September, 2000, PP.
50-54.
[13] WARD P, SFRC Suspended slabs inflexure, The Structural Engineer, January
2010, PP.16-19.
[14] MARTIN D, Micro-silica steel-fibre
reinforced concrete flooring, Concrete, April 2000,
PP. 14-16.
[15] MORRISON I, Specifying GRC, Concrete,
June 2010, PP. 14-15.
[16] BARTOS PJM, e-GRC – Improving theappearance of concrete buildings andquality of Urban Environment, Concrete,
April – 2009, PP. 25-27.
[17] mcclelland R, Permanent form work forcomposite bridge decks, Concrete, April
2007,
PP. 10-11.
[18] MULLIN B, Arching Action in Concrete
Slabs with novel reinforcement, The
Structural Engineer, January 2003, PP. 1517.
[19] JOWETT N, Fibre reinforcement the nonmetallic way, Concrete, May – 2004, PP.
43-44.
[20] RIDOUT A, Macro Synthetic fibres replacesteel fabric in chilean housing, Concrete,
September 2007, PP. 32-34.
[21] ATKINSON T, Fibres – the traditional
method of reinforcement, Concrete,
September 2010,
PP. 45-46.
[22] KITCHEN A, New regulations will load tohigh-fibre diet, Concrete, September 2006,
PP. 29-30.
[23] KITCHEN A, Micro Poly-propylene fibres
for external Concrete slabs and hard
standings, Concrete, September 2007, PP.
28-31.
[24] SADEGZADEH M, KETTLE R and
VASSOU V, The Influence of glass
polypropylene and steel fibres on physical

CONCLUSIONS
A review of composite concrete material
has been presented to some limited extent withdifferent reinforcement and fibres. Mostly, steel,polypropylene, carbon and glass fibres have been
considered and the behaviour of the same under
flexure, shear and other load conditions have beenreported. Steel and polypropylene fibres have beenused successfully in industrial concrete groundfloor slabs. It is commented that glass fibre
reinforced composite concrete may be suitable forcleaner and brighter facades of important buildings
and will contribute to the reduction of pollution in
urban environment. Different test results on theuse of composite materials are reported to bereasonable.
It may be concluded that proper use ofcomposite materials, the concrete structures will beable to perform satisfactorily upto the predicted life
span with minimum maintenance cost.
ACKNOWLEDGEMENT
The author would like to thank the
management of Development Consultants Private
Limited (DCPL) for their encouragement inpublishing the paper.
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[104] mccormick N, Structural health monitoringfor civil engineered structures, Concrete,
August 2009, PP. 40[105] HURLEY S, Coatings for Concrete,
Concrete July/August 2004, PP. 24-26.
[106] LONG W B, Repairs to fire damaged
structures, Concrete, May 1984, PP. 13-14.

[107] VAN L, EINDE D, ZHAO L and SEIBLE
F, Use of FRP Composites in Civil
Structural applications, Construction and
Building materials, Vol.-17, SeptemberOctober 2003, PP. 389-403.

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524

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ASSESSMENT OF ANTI-RUTTING ABILITIES OF WARM MIX
MODIFIED MIXTURES*Ivan Syed1, Md Amanul Hasan2 and Rafiqul A. Tarefder3
Graduate Research Assistant, University of New Mexico, United States; 2PhD Student, University of New
Mexico, United States; 3Professor, University of New Mexico, United States

1

ABSTRACTIn this study, asphalt binders’ rutting resistance were assessed using high temperature rheologicalproperties of warm mix-modified binders. For this evaluation process, frequency temperature sweep andmultiple stress-creep recovery tests were conducted on extracted binders at a fixed temperature of 50°C using
a dynamic shear rheometer. Two approaches were considered for determining rutting resistance: the Superpave
rutting specification parameter (G*/sinδ) and multiple stress-creep recovery. By using these specificapproaches, the rheological rut properties of modified asphalt binders were determined and then correlatedwith Hamburg Wheel Track Testing (HWTT) results performed at 50°C. A simple linear regression model wasdeveloped to study the relationship between rheological data and pavement rutting potential. It was observedthat non-recoverable compliance (Jnr) value obtained from the MSCR test demonstrated better correlation with
HWTT (R2 = 0.96) compared to Superpave rutting parameter (R2 = 0.91). In addition, the mixture incorporated
with both Cecabase® additive and polymer modification exhibited significant enhancement in rutting
resistance.
Keywords: Warm mix additives, Rutting resistance, MSCR, Frequency temperature sweep
uncertainty about how WMA may affect asphalt
mixtures’ short and long-term field performance.
Research has shown that as mixing temperature are
reduced for WMA, the mixes show increased
tendencies towards rutting and moisturesusceptibility [4], [5]. This was attributed todecreased aging of the binder, possible presence ofmoisture in the mixture incomplete drying of theaggregates due to lower temperatures.
A better understanding of the effects of warmmix additives on the performance of asphalt
concrete is a fundamental step towards the effective
application of WMA. As part of the structuraldesign processes to optimize field performance ofasphalt mixtures, simple performance tests such as
Hamburg Wheel Tracking Test (HWTT) has beendeveloped to determine rutting potential. However,the characteristics of the binder component are also
important, especially for cases involving binders
with modifying agents.
Despite the fact that asphalt bitumen make up 4
to 8 % of a pavement mix structure, it provides alevel of rigidity, structural bonding, resilience, andabsorbance which holds the total pavement mixture
together as a solid body [6]. However, with higher
traffic densities and effects of environmental
exposure, binder flows and dissipates energy withtime [7]. As a result, asphalt binder experience avariety of thermomechanical demands; where
pavement defects transpire such as rutting at hightemperatures due to thermal susceptibility ofasphalt [8].

INTRODUCTION
In perspective of global use, the associated costs
for the volume of raw materials used and energy
consumption required for asphalt production cost
could be astounding. The increasing costs of raw
materials and demand for environmentally suitablepaving materials in road construction havechallenged the asphalt industry to seek and develop
alternatives that aid in reduction of production andcompaction temperatures of asphalt mixtures
without compromising the required performance
behavior.
Warm mix asphalt (WMA), pioneered in Europe
in the late 1990’s [1], is the latest asphalt technologythat presents the capability of addressing thepractice of environmental sustainability andenhancement of mixture workability withoutcompromising performance. WMA additives can
reduce the viscosity of the binder, allowing
mixtures to be produced at a temperature grade of
38°C lower than traditional Hot mix asphalt (HMA)[2], [3], which lead to a number of environmental,
operational, and economical benefits.
The implementation of WMA has become morewidespread with an increasing number of paving
contractors
employingthesesustainable
technologies in construction in order to takeadvantage of reduced mixing and compaction
temperatures, lowered energy usage for production
and placement, and reduced emissions. However,
one of the challenges to implementation is the525

GEOMATE - Mie, Japan, Nov. 21-24, 2017

values of three replicates samples were determinedat 50°C, corresponding to the test temperature of the
HWTT test.

The asphalt contribution to permanent
deformation process has traditionally been handled
by observing the asphalt binder’s consistency basedon softening point and penetration tests [9] .
However, with priorities set for environmental
conservation and preservation, the integration ofpolymer modifiers, warm mix additives, andrecycling of reclaimed asphalt pavement (RAP)
materials into asphalt mixtures have gained
popularity [10], [11]. With this in mind, theempirical tests mentioned earlier are insufficient tocharacterize the rutting resistance behavior ofbinders. It would be helpful to examine the effectsof these modifying agents on the properties of plant
produced mixtures. In order to accomplish this task,
extraction and recovery of asphalt binder fromasphalt concrete were performed.
Thus, this research evaluates the rutting
resistance of binders modified with different warmmix additives.

Laboratory Evaluationof WMA mixes

II.
III.

Binder Evaluation

Rutting
Resistance

Extracted Binder
Properties

Hamburg Wheel
Tracking TestOBJECTIVES
I.

Performance Test

FrequencyTemperature Sweep

MSCR

G*/sin(δ)

Jnr , %R

Fig.1 Test methodology implemented in this study

Evaluate the effects of different warm mix
additives on the rheological and rutting
performance characteristics of asphalt
concrete.
Compare rutting resistance of the extracted
binders using two different rutting
parameters.
Assess the correlation between rheologicalproperties and permanent deformation
results obtained from HWTT.

Material Source and Classification
The pavement test sections selected for thisresearch are located in district four of central New
Mexico and were constructed in fall of 2014 along
the westbound lane of Interstate 40 near Santa Rosa,
New Mexico, where designs incorporate
approximately 20% RAP materials collected fromthe Interstate 40 and US 84 highway stockpile.
Material type of sand and gravel with gradation
classification of Superpave Mix type III withnominal maximum aggregate size (NMAS) of ¾
inches were utilized for design of these AC mixes.
In addition, 1% of versabind® were incorporated
into the mixes.
The production of asphalt concrete utilized in
the second test section were produced with Terex®
Foaming technology and WMA chemical additiveof Evotherm® was used in the construction of thethird test section. Cecabase® chemical additives wasconsidered for the two supplemental pavement test
sections in order to perform additional research on
the effects of other WMA production methods The
asphalt concrete mixing temperature considered fordesign of HMA and WMA were 322°F and 270°F,
respectively. The first four pavement sections were
manufactured using binder grade of PG 70-28.
However, the last section was prepared with thesame binder grade and enhancement of polymer
modifiers, thus resulting in the designation of PG
70-28+.
Based on the different additives used in thesetest sections, WMA technology is classified into
two different technologies namely: (i) water-basedand (ii) chemical additive technologies. In the

TEST METHODOLOGYThis section of the paper focuses on material
selection, experimental plan, and a brief descriptionof each test considered for the purpose of thisresearch. The test methodology is described in Fig.1,
where this test program is designed to evaluate therutting susceptibility of the selected pavements andto see if there are demonstrable differences in test
results between control HMA and WMA modified
test sections. This study was conducted in twophases: 1) rutting performance evaluation and 2)
assessment of extracted binder properties. The
rutting potential of WMA modified asphalt
mixtures, in comparison to HMA, were evaluatedthrough HWTT device. As samples were collectedfrom the LTPP pavement sections, binders on theseplant-produced asphalt mixtures experienced shortterm aging during their production stage [12]. The
process of laboratory short-term aging was annulled.
In order to measure the two rutting parameters,rheological tests were performed on the extracted
binders using a Dynamic Shear Rheometer (using a
25 mm diameter plate and 1 mm gap). The average526

GEOMATE - Mie, Japan, Nov. 21-24, 2017

foaming process, a certain amount of water is added
to the hot binder and then the water is turned into
steam, which results in a volume expansion ofbinder and consequently, a reduction of the binder’sviscosity [13]. This temporary reduction facilitatesaggregate coating and thereby improved
workability at reduced temperatures. The expanded
volume gradually deteriorates with time and theasphalt binder returns to its original characteristics[14]. This form of technology is currently more
popular and widely used compared to othertechnology categories.
Evotherm® and Cecabase®, for instance, areboth chemical additives. Cecabase® which do not
reduce the asphalt binder’s viscosity. They arepackaged by surfactant and adhesion agents, which
chemically enhance active adhesion and improve
the wetting of aggregates by binder without altering
considerably the rheological performance [5].
Evotherm® is an additive packaged in the form ofemulsion, which are introduced into the plant’sbinder line, allowing for the reduction of mixing
temperatures close to 38°C, translating to decreased
energy requirements for asphalt production [15].

20
18
16

StrippingSlope

Rut Depth (mm)

14
12
10

Post-Compaction
Consolidation

8
6

Creep Slope420

Stripping Inflection Point
0

2000

4000

6000

8000 10000 12000 14000 16000 18000 20000

Number of Wheel Passes

Fig.2 Schematic of HWTT results
3.3 Test Procedures for Binder Evaluation
In order to evaluate the effects of warm mix
additives and recycled materials, extraction andrecovery of asphalt binder from asphalt concrete
was the approach considered. Extraction was
performed following AASHTO D2172 andAASHTO D5404, respectively. The solvent used inthis process is trichloroethylene.
AASHTO T 315 was followed to perform
frequency-temperature sweep tests at 50°C in orderto determine the G*/sinδ values of the extracted
binders.
In addition, MSCR tests were conducted todetermine the percent recovery (% R) and nonrecoverable creep compliance (Jnr) values of thebinders, in accordance to AASHTO TP70.

Mix Performance Evaluation Tests
Mixture rutting performance was done using
HWTT following AASHTO T 324-14, a laboratory
test procedure which simulates repeated wheelloading on specimens in order to characterizerutting resistance potential and stripping
susceptibility. Linear variable displacementtransducers (LVDTs) located at the side of eachwheel are used to record the rut depth at 11 points
along the test samples with 0.01 mm precision.
Following the recommendation suggested by
Schram et al. [16], the average value of the rut
depths at 4th, 5th, 6th, 7th, and 8th points along thewheel path was considered as the HWTD test result
for this study.
Plot of rut depth vs. number of wheel passes areanalyzed to predict rutting and stripping
susceptibility. Fig.2 includes a post compaction
consolidation (PCS), a creep slope (CS), a stripping
slope (SS), and a stripping inflection point (SIP).
PCS occurs within 1,000 number of wheel passes
and simulates initial densification of pavement
mixtures when traffic movement is allowed on a
newly constructed pavement. CS relates the rutting
susceptibility through measurement of permanent
deformation which occurs due to plastic flow. SS
relates the stripping susceptibility of the mixtures.
A lower value of CS and SS indicates characteristics
of decreased rutting and stripping resistance oftested samples [17]. If the plot does not include a SS
or a SIP, the mixture has adequate moisture damage
resistance.

RESULTS AND ANALYSES
Hamburg Test Results
Fig.3 shows HWTT analysis of the SPS-10
pavement mixtures, where the average rut depth
values of four test replicates per mixture has beentaken as the symbolic rut depth value.
5

Control HMA
Foaming
Evotherm
Ceca
Ceca+

4.5

Rut Depth, mm

4
3.5
3
2.5
2
1.5
1
0.5
0

0

5000

10000

Wheel Passes

15000

20000

Fig.3 Hamburg test results for evaluated mixes
It is observed that all five mixtures has arepresentative PCS and CS. However, stripping
phase was not reached for any of the mixes,
indicating no incidence of damage due to the effects
527

GEOMATE - Mie, Japan, Nov. 21-24, 2017of moisture. Results display a significant reduction
in rutting susceptibility for Cecabase®+ (2.44 mm)
mixture in comparison to control HMA (4.72 mm).
However, between two Cecabase mixtures,
Cecabase® without polymers exhibited a slightly
higher rut depth (3.59 mm). On the contrary,
Cecabase®+ is polymerized, resulting in a hardermixture. This specific circumstance exhibits theeffect of linking warm mix additives with polymers.
6
4.72

Rut Depth, mm

5
4

3.41

10000 passes

3.07
2.58

3

3.99
3.48

that the incorporation of RAP to WMA has thepotential to improve the performance of these typeof mixtures at intermediate to high temperatures.
Superpave Rutting Parameter – G*/sinδ
The G*/sinδ values of the extracted binders was
explored. All forms of warm mix modification wasobserved to increase the superpave rutting
parameter (Fig.5a). For example, G*/sinδ value forbinders with Terex® foaming, Evotherm®,
Cecbase®, and Cecabase®+ was found to beapproximately 27.90, 20.47, 19.90,and 91.83 kPa,
respectively, compared to 11.70 kPa for control
HMA. Out of the four additives, results show thatthe addition of Cecabase® with polymerization
increased G*/sinδ substantially, indicating thehighest rutting resistance with this modification
arrangement. From these results, Cecabase®+ isrecognized to be the most effective additive in
improving rutting resistance followed by Terex®
foaming, Evotherm®, and Cecabase® unmodified.
Based on the simple regression analysis (Fig.5b), a
good correlation of R2 = 0.91 was observed between
the maximum rut depth and rheological parametervalues of these mixtures.

20000 passes
3.59
2.85

2.44
1.80

2
1
0

ControlFoaming Evotherm

Ceca

Ceca+

20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0

15997

15831
12720
10311

9144

100

Control Foaming Evotherm

Ceca

G*/sinδ (kPa)

Creep Slope (passes/mm)

(a)

Ceca+

(b)
1124

1200

80
60
40

1000
800
600

594

0

724

601

685

11.70

200

Control Foaming Evotherm

Ceca

Ceca+

(c)
Fig.4 Hamburg test results for evaluated mixes
In reference to Fig.4(a), a comparable trend wasobserved for permanent deformation measurements
at 10,000 number of wheel passes with slightly
lower values with respect to values from 20,000
wheel passes. Fig.4(c) indicates that as rut depth
increases, PCS decreases. CS of these mixtures also
illustrates this similar trend. Since, there is no
stripping slope, all mixtures have ample moisturedamage resistance. This may be attributed to theincorporation of 1% versabind® in these mixtures; awell-known anti-stripping agent. According toresearch conducted by Hill [18], it was observed

20.47

19.90

Evo

Ceca

Control Foaming

Ceca+

(a)

0.8

400

0

27.90

20

log(Rut Depth @200000
Passes), mm

Post-Compaction Slope(passes/mm)

1400

91.83

y = -0.3129x + 0.9846
R² = 0.9125

0.7
0.6
0.5
0.4
0.3
0.2
0.1
0

0.8

1

1.2

1.4

1.6

1.8

log(G*/sin(δ)), kPa

2

2.2

(b)

Fig.5 G*/sinδ parameter results
MSCR Rutting Parameters – Jnr, %R
As shown in Fig.6a, the Jnr value of control
HMA was found to be 0.59 kPa-1. The Jnr values ofthe extracted binders with Terex®, Evotherm®,
528

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Rut Depth @ 20000
passes, mm

Cecabase®, and Cecabase®+ was found to be 0.15,
0.46, 0.23, and 0.02, respectively. Lower Jnr values
were observed for all WMA modified mixtures incomparison to control HMA. This indicatesincreased rut resistance. As shown in Fig.6b, the %Recovery value of the control sample was found to
be 13.47. The % Recovery values of the extracted
binders with the presence of Terex®, Evotherm®,
Cecabase®, and Cecabase®+ was found to be 32.58,
18.14, 23.71, and 77.54, respectively. This also
indicates increased rutting resistance compared tothe control sample. Based on the lowered Jnr andheightened % Recovery values from theincorporation of Cecabase®+, the influence ofpolymerization is exhibited through the decreased
rutting potential.

Evo

Ceca

Jnr (1/kPa)

0.8

Rut Depth @20000
passes, mm

4.0
3.0
2.0
1.0
0

20

40

60

80

100

Fig.7 Simple linear regression analysis of MSCR
results with respect to HWTT

Ceca+

(a)

CONCLUSION
77.54

80

This study has evaluated the anti-rutting
abilities of warm mix additives in asphalt concrete
mixtures. The key findings drawn from thisresearch are discussed below:

70
60
50
32.58
13.47

0.6

(b)

Control Foaming

30

0.4

%Recovery

0.02

40

0.2

y = -0.0295x + 4.5402
R² = 0.7712

0.15

90

% Recovery

0.0

5.0

0.0

0.1

18.14

23.71



10
0

1.0

0.23

0.2

20

2.0

(a)

0.4

0.0

3.0

6.0

0.46

0.3

4.0

Jnr, 1/kPa

0.59

0.5

5.0

0.0

0.7
0.6

y = 3.7191x + 2.4817
R² = 0.9645

6.0

Control Foaming

Evo

Ceca

Ceca+

(b)
Fig.6 MSCR parameter resultsA simple linear regression analyses were
performed between the two parameter results
obtained from this test method in contrast to HWTT,As shown in Fig.7, a correlation value of R2 = 0.96
and R2 = 0.77 were found for Jnr and % Recovery,
respectively. Hence, indicating the non-recoverable
creep compliance parameter as a reliable measure
when it comes to evaluating rutting resistance, outof the MSCR parameters.
Based on the Jnr values, the order of rut
resistance for the extracted binders can be seen as(i) Cecabase®+, (ii) Terex® Foam, (iii) Cecabase®,(iv) Evotherm®, and (v) Control. This ranking ordershows that compared to the control HMA sample,
WMA modification improves the rutting potentialof the mixtures.

Based on the simple regression analysis results,
Jnr presents the best correlation (R2 = 0.96) withrutting results obtained from HWTT. With theabsence of MSCR test, the superpave rutting
parameter (G*/sinδ) may still be considered as
a viable option to evaluate rutting resistance.
Cecabase®+ exhibited significant rutting
resistance improvement among the fivepavement sections. In HWTT mixture testing,
stripping phase was not reached for all
mixtures, indicating ample damage resistanceagainst the effects of moisture.

It is recommended to conduct another study toevaluate the effects of higher percentages of RAP
content. In addition, if the opportunity presents
itself, the effects of these select additives on varying
binder performance grades and gradation will
provide good insight in evaluating the impact of
WMA technology.

529

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Prediction of Warm Mix Asphalt Containing
Reclaimed
Asphalt
Pavements”, Road
Materials and Pavement Design, Vol. 15, No.
1, 2014, pp.207-219.
[12] Irfan, M., Waraich, A.S., Ahmed, S. and Ali,
Y., “Characterization of Various PlantProduced Asphalt Concrete Mixtures Using
Dynamic Modulus Test”, Advances inMaterials Science and Engineering, 2016.
[13] Van de Ven, M.F.C., Jenkins, K.J., Voskuilen,
J.L.M. and Van Den Beemt, R., “Developmentof (Half-) Warm Foamed Bitumen Mixes: Stateof The Art”, International Journal of Pavement
Engineering, Vol. 8, No. 2, 2007, pp.163-175.
[14] Kristjánsdóttir, Ó., Muench, S., Michael, L.
and Burke, G., “Assessing Potential for WarmMix
Asphalt
Technology
Adoption”, Transportation Research Record: Journal of
the Transportation Research Board, (2040),
2007, pp.91-99.
[15] Rashwan, M.H., “Characterization of Warm
Mix Asphalt (WMA) Performance In Different
Asphalt Applications”, (Doctoral dissertation,
Iowa State University), 2012.
[16] Schram, S., Williams, R. and Buss, A.,“Reporting Results from the Hamburg Wheel
Tracking Device.” Transportation Research
Record: Journal of the Transportation
Research Board 2446, 2014, pp.89–98.
[17] Larrain, M.M.M. “Analytical Modeling of
Rutting Potential of Asphalt Mixes Using
Hamburg Wheel Tracking Device”, (Master’s
Thesis), 2016.
[18] Hill, B., “Performance Evaluation of Warm
Mix
Asphalt
Mixtures
Incorporating
Reclaimed Asphalt Pavement.” (Doctoral
dissertation, University of Illinois at UrbanaChampaign), 2011.

ACKNOWLEDGEMENT
This project is funded by New Mexico
Department of Transportation (NMDOT) andSouthern Plain Transportation Center (SPTC). The
authors would also like to express their gratitude to
the research bureau team of NMDOT.
REFERENCES[1] Jones, W., “Warm Mix Asphalt Pavements:
Technology of The Future?”, Asphalt, Vol. 19,
No. 3, 2014.
[2] Button, J.W., Estakhri, C. and Wimsatt, A., “A
Synthesis of Warm Mix Asphalt (No.
FHWA/TX-07/0-5597-1)”, College Station,
TX: Texas Transportation Institute, Texas A &M University System, 2007.
[3] Akisetty, C.K.K., “Evaluation of Warm
Asphalt Additives on Performance Properties
of CRM Binders and Mixtures”, (Doctoral
dissertation, Clemson University), 2008.
[4] Politano, L., “Warm Mix Asphalt-A Greener
Alternative to Hot Mix Asphalt”, 2012
Conference
andExhibitionoftheTransportation Association of CanadaTransportation: Innovations and Opportunities,
2012.
[5] Croteau, J.M. and Tessier, B., “Warm Mix
Asphalt Paving Technologies: A Road
Builder’s Perspective”, In Annual Conferenceof the Transportation Association of Canada,
Toronto, 2008.
[6] Bahia, H.U., Hanson, D.I., Zeng, M., Zhai, H.,
Khatri, M.A. and Anderson, R.M.,“Characterization of Modified Asphalt Binders
in Superpave Mix Design”, (No. Project 9-10
FY'96), 2001.
[7] Tabatabaee, H.A. and Bahia, H.U.,“Establishing Use of Asphalt Binder Cracking
Tests for Prevention of Pavement Cracking”,
Road
Materials
andPavement
Design, 15(sup1), 2014, pp.279-299.
[8] Pérez-Lepe, A., Martınez-Boza, F.J., Gallegos,C., González, O., Muñoz, M.E. andSantamarıa, A., “Influence of The Processing
Conditions on The Rheological Behaviour of
Polymer-Modified Bitumen”, Fuel, Vol. 82,
No. 11, 2003, pp.1339-1348.
[9] Morea, F., Agnusdei, J.O. and Zerbino, R.,“Comparison of Methods for Measuring Zero
Shear Viscosity in Asphalts”, Materials andstructures, Vol. 43, No. 4, 2010, pp.499-507.
[10] Yildirim, Y., “Polymer Modified Asphalt
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[11] Moghadas Nejad, F., Azarhoosh, A., Hamedi,
G.H. and Roshani, H., “Rutting Performance530Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LATERAL CYCLIC LOAD TEST AND SEISMIC DESIGN OF
PRECAST CONCRETE COLUMNS USING STEEL BOX CONNECTION
Nutchanon Siri, Chayanon Hansapinyo* and Chinnapat Buachart
Center of Excellence for Natural Disaster Management,
Department of Civil Engineering, Chiang Mai University, THAILAND*
Corresponding author
ABSTRACTDue mainly to lacking of skill labor, the precast construction has been widely adopted and increasingly
replace the conventional cast-in-place construction. This paper explains experimental investigations on precast
concrete columns using steel box connection at the column base under cyclic loading. The test results show
satisfactory seismic performance of the precast specimens both in seismic shear capacity, ductility and energy
dissipation compared with the identical cast-in-place specimen. The failure of the precast columns, with proper
details, was in flexural ductile mode. The shear capacity was respectively 1.16-1.24 times higher than the
averaged capacity of the cast-in-place column. The damping ratio was about 18-25 percent in the inelastic range,
after the drift ratio of 3.0%. Finally, seismic design of the precast concrete column using the steel box connection
is described based on the experimental results.

Keywords: Precast Concrete Column, Seismic Design, Column Steel Box Connection, Lateral Cyclic Loadpast lessons learnt from the failed buildings.
However, the design of precast concrete element has
not been clearly explained, as the existing buildings
are mostly reinforced concrete type. The adopted
innovative precast connection has then based on
experimental result of prototype element. This paper
presents lateral cyclic load test and seismic design ofprecast concrete columns using steel box connection.
The technique permits faster construction with useof this bolted connection type, as shown in Fig. 1.
Seismic design of reinforced concrete framebuildings is first described to overview demand
capacity for design of the precast concrete columns.
Then, precast concrete with the steel box connection,
as shown in Fig.1(b) and an identical cast-in-paceconcrete column tests under lateral cyclic load is
explained. From the test, seismic performance of the
precast columns is discussed compared with thecast-in-place one. Eventually, the design of the
precast columns and the steel box connection are
described based on the test results.

INTRODUCTION
The increasing rate of the construction industry
is related well with the economic growth of country
especially for developing countries. Nowadays, theproblems about labor shortage and labor cost havebecome more severe. These problems, as well as
high construction industry competition, have led tothe application of the precast construction. In
addition, the construction technique becomes more
popular due to the less time consumption.
In a seismic prone area, failure mechanism ofstructural elements in a building must be considered
to ensure ductile damage under a severe earthquake.
Columns and beam-column joint are maintained inelastic range. In other words, a good structure must
be able to control the location of damage or plastic
hinge under big earthquakes on beam elements forabsorbing and dissipating energy. This phenomenon
can be achieved by a systematic design for weak
beam-strong column. As the column elements arevery important, many past researches investigated
the shear capacity demand of reinforced concrete
columns and beam-column joints under the lateralloading [1-3]. For the precast column, Rejame et al[4] conducted an experimental investigation on
precast columns in socket foundations with internalsmooth interfaces.
Seismic design of ductile reinforced concrete
frames has been developed for a long period of time.
A successful design method has been based on the

SEISMICDESIGN
CONCRETE FRAMEOF

REINFORCED

An overview of seismic design of reinforced
concrete frame buildings is described below, asshown in Fig.2. Following the step, damage pattern
can be controlled in flexural mode at the beam ends
and the collapse of buildings under a strong
earthquake can be avoided.
531

GEOMATE - Mie, Japan, Nov. 21-24, 2017

including local seismic intensity, type of building,type of soil, building weight and dynamic properties.
The calculation starts from base shear force
estimation and then distributes the force to eachfloor of the building. Structural analysis is next
performed for element forces induced by all cases ofload combination.
Design for reinforced concrete beams
From the envelope flexural force, flexuralstrengths required for beams are obtained andrequired longitudinal reinforcement can be
determined accordingly. Considering under a strong
earthquake forming flexural hinge at the beam ends,
shear force ( Ve ) at the stage is estimated as shownin Eq.(1) and Fig.2. The beam shear strength
designed following this procedure ensures the
avoiding of shear failure in the beam element.

(a) Precast concrete column in a precast frameVe 

M pr1  M pr 2
ln

(1)



wu l n2

Where

M pr1 and M pr 2 are probable flexural strengthof the beam ends
wu is factored load per unit length of the beam(b) Steel box connection
Fig.1 Precast concrete column with steel box
connection

ln is clear length of the beam
Design of reinforced concrete column

Design for reinforced
concrete beams

To protect the columns against a strong
earthquake, design shear and flexural strengths ofthe columns must be higher than the flexuralstrength of the joining beams. According to ACI318[5], the flexural strengths of the columns shallsatisfy

Design ofreinforced concrete M  1. 2  M

Estimate seismic load
and building analysis

nc

nb

(2)

Where

Design of beamcolumn joint

Mnc

is sum of nominal flexural strengths ofcolumns framing into the joint
M nb is sum of nominal flexural strengths of

Fig.2 Seismic design of reinforced concrete frames

beams framing into the joint

Estimation of seismic load and building analysis

The required flexural capacity of the column

M nc is then used to determine the column

First, for a regular building, lateral seismic loadon building is estimated according to a local
standard. The load depends on seismic parameters

dimension and reinforcement. The required shear
capacity of the reinforced concrete column is also
determined. Consequently, the steel box connection
532

GEOMATE - Mie, Japan, Nov. 21-24, 2017is designed which will be explained next.

concrete columns with the steel box connection
satisfied seismic performances, compared with the

Design of beam-column joint
Damage of beam-column joint can lead to
reduction of redundancy of structure. Hence, elastic
performance of the region under an earthquake must
be confirmed. Based on the capacity of the designed
columns from the previous step, the required
strength of the beam-column joint can be determined.
TEST OF PRECAST CONCRETE COLUMNS
Specimens and Experimental Setup(a) Monolithic specimen M-100

To verify the applicability of the designed steel
box connection, tests of 5 precast columns werecarried out at the Structural Laboratory, Department
of Civil Engineering, Chiang Mai University [6].
The test results were compared with an identical
cast-in-place one. All the columns were 0.25 x 0.25
m2 section and 1.7 m in height from column base to
top. 4-DB16 were used as the longitudinal
reinforcement for all specimens. For the precast
specimens, the steel box connection was used for thebase connection. The difference between the precast
specimens is based on difference in construction
method, e.g. grouting, welding to nuts, welding of
the column reinforcement to the steel box. Fig.3
shows the specimen details. For the specimen
nomenclature, M and P stand the Cast-in-place
specimen and the Precast specimen, respectively.
Constant axial load of 0.1 f c Ag was applied to all(b) Precast specimens
Fig. 3 Test specimens

specimens. Lateral cyclic loading was applied to thetip of the specimen, as seen in Fig.4. While thecolumn bottom was arranged to be a fixed condition,
the application of the load induces a cyclic shear andmoment as if it is a half-story column in a rigid
frame. The deformation control at the loading point,
represented as story drift was adopted asrecommended in ACI T1.1-01 [7].
Lateral Load and Deformation RelationshipThe cast-in-place specimen failed in flexural
failure with yielding of the longitudinal
reinforcement at the column base. High ductility andenergy dissipation were observed. For all the precastcolumns, depending on different reinforcement
detailing, P-100-20 and P-50-20 specimens wereductile failure and P-100-20L, P-100-16 and P-15020L were brittle failure. The brittle failure wascaused by the improper welding details of thecolumn reinforcement on the steel box connection.
Under the lateral cyclic loading, the ductile precast

Fig. 4 Lateral cyclic load test
cast-in-place column. The ductile precast columns
were failed under flexural mode similar to that of thecast-in-place specimen but at section above the steel
box connection. Hence, the ultimate lateral load ofthe ductile precast is higher than the load of the castin-place column due to the shorter moment arm. Figs
5 and 6 respectively show the lateral loaddeformation relationship and damping of the ductile
precast columns (P-100-20 and P-50-20 specimens)533

GEOMATE - Mie, Japan, Nov. 21-24, 2017

place column. The equivalent damping ratios
determined from area under the load-deformation
curve [8] were between 18-25 percent after drift
ratio more than 3 percent.

and the cast-in-place concrete column. As seen in
Table 1, the ultimate lateral load capacities of theductile precast columns are about 1.16-1.24 times
higher than the averaged capacity of the cast-in-(a) M-100(b) P-100-20(c) P-50-20(d) P-100-16(e) P-100-20L(f) P-150-20L

Fig.5 Hysteresis relation of lateral load-deformation

534

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Lateral load capacity and damping ratio
Specimen

Pu_pushPu_pull

Pu_Theory (kN)3

Failure mode

Damping ratio (%)(Story drift >3%)

25.26
26.20
25.33
Flexural
22-25
Avg. (Pu_Ma1) 25.73
22P-100-20 30.46 (1.18) 30.53 (1.19)
39.33
Flexural
15-21
P-50-20 32.00 (1.24) 2 29.86 (1.16)2
39.33
Flexural
18-22
P-100-16 23.66 (0.92) 2 12.86 (0.50) 2
25.33
Slip of threaded dowel
3-4
P-100-20L 31.00 (1.20) 2 30.93 (1.20)2
39.33
Fracture of welding
7-15
P-150-20L 27.46 (1.07) 2 45.93 (1.79)2
39.33
Fracture of welding
5-61
Pu_Ma the average of push and pull ultimate capacity of specimen M-100
2
Numbers in parenthesis and ultimate capacity ratio compared with the Pu_Ma
3
Pu_Theory is calculated based on ultimate capacity of maximum shear and moment section (at column base). The
calculated strengths are controlled by flexure
M-100

must be higher than that of the column section above
the connection.
Number of dowel bar and threaded diameter
Under tension load on the column, longitudinal
reinforcement resists the entire load. Hence, at thesteel box connection, number and threaded diameterof the dowel bars are calculated based on
equilibrium, as shown in Eq.(3). It is noted that thebuildability also decides size and number of thedowel bars. For this test, as the reinforcement of thecolumn is 4-DB16, 4 dowel bars with the threaded
diameter of 20 mm. and same yield strength of thecolumn reinforcement were used. By using thisapproach, the design under tension becomes
conservative. In the real situation, columns will be
subjected to combined compressive load andbending. The entire column section will be curved
and the stress of the section is under distributed
compressive stress or compressive-tensile stress.

Fig.6 Equivalent damping ratio
DESIGNOF
PREACAST
CONCRETE
COLUMN USING STEEL BOX CONNECTION

Asc  f yc  Asj  f yj

(3)

where Asc , f yc and Asj , f yj are sectional areaand yield strength of the column reinforcement
adjacent to the steel box and dowel bars,
respectively.
Section of the steel box connection
This is the additional design procedure comparedwith the cast-in-place column. As seen in Fig.7, thetested precast concrete columns had the flexural
capacity of 38.6 kN-m. associated with the axial
load of 0.1 f c Ag . Based on AISC steel design [9],Fig. 7 Design of the steel box connection
After obtaining the designed column section, thesteel box connection dimension is determinedaccordingly. Similarly, to avoid weak points on theconnecting steel box, capacity of the connection

flexural yielding (My) and stiffness (EI) of the box
were 57.9 kN-m and 5.88 kN-m2 respectively,
providing 1.5 and 2.3 times relatively higher than535

GEOMATE - Mie, Japan, Nov. 21-24, 2017higher compared with the cast-in-place concrete
column, due to the relocation of the failure section.
Hence, based on the capacity design concept, theweak beam-strong column can be easily achieved.

the ultimate flexural capacity and non-cracked
flexural stiffness of the reinforced concrete column
section. With the capacity of the steel box
connection is higher than the column above,connection failure can be avoided.

ACKNOWLEDGEMENTS

Prevention of premature failure

The authors would like to express their sincere
appreciation to Chiang Mai University for financial
supports.

Premature failure introduces unexpected lower
capacity with brittle failure mode. For the design ofprecast concrete column with the steel box
connection, attention should be paid to providing
nuts with enough bond-slip capacity. For the column
reinforcement,
thelongitudinalcolumnreinforcements attached to the upper plate of theconnecting steel box can be done in either form of
welds, e.g. fillet weld with U shape or butt-weld.
However, the welding contents should be carefully
examined and the welding strength should beguaranteed for the designed purpose. Welding forthe built-up steel box is also carefully made.

REFERENCES[1] Lu, X., Urukap, T. H. Li, S. and Lin, F.,“Seismic behavior of interior RC beam-column
joints with additional bars under cyclicloading”, Earthquakes and Structures, Vol.3,
No.1, 2012, pp. 37-57.
[2] Bindhu, K.R., Jaya, K.P. and Manicka Selvam,
V.K., “Seismic resistance of exterior beamcolumn
jointswith
non-conventional
confinement reinforcement detailing”, Struct.
Eng. Mech., Vol.30, No.6, 2008, pp. 733-761.
[3] Han, S. W. and Jee, N. Y., “Seismic behaviorsof columns in ordinary and intermediate
moment resisting concrete frames”, Engineering
Structures, Vol.27, No.6, 2005, pp. 951-962.
[4] Rejame, M. F. C., Eimair, B. E. and Ana, L. H.,“Analysing the base of precast column in socket
foundation with smooth interfaces”, Materials
and Structures, Vol.42, No.6, 2009, pp. 725737.
[5] ACI318, Building Code Requirements for
Reinforced Concrete, American Concrete
Institute, Detroit, Michigan, 2005.
[6] Hansapinyo, C., Buachart, C. and Wongmetha,
P., “Cyclic Performance of precast concrete
columns using steel box connection”,
International Journal of Civil Engineering, Vol.
15, No. 4, 2017, pp. 663–676.
[7] ACI T1.1-01, Acceptance criteria for moment
frames based on structural testing, American
Concrete Institute, 2001.
[8] Chopra, A. K., “Theory and Applications to
Earthquake Engineering: Dynamic of structure(3rd Edition)”, Prentice Hall, Englewood Cliffs,
NJ, 1999.
[9] AISC, Steel Construction Manual, American
Institute of Steel Construction (4th Edition),
2011.

CONCLUSION
This paper presents the lateral cyclic load test
and seismic design of precast concrete column using
steel box connection based on capacity designconcept. First, seismic design of reinforced concrete
frames is reviewed based on capacity designconcept. Then, the guideline on how to obtain theseismic design force for the columns is made. The
design of precast concrete column with the steel box
connection is explained. To illustrate theapplicability of the designed steel box connection,
lateral cyclic load tests of precast concrete columns
was made and the results were compared with aresemble reinforced concrete column. The test
results show the good seismic performances of thedesigned steel box connection. The columns withconnection possessing the flexural strength andstiffness higher than the concrete column above theconnection performed the ductile behavior. The
flexural yielding strength and stiffness of the box
were 57.9 kN-m and 5.88 kN-m2 respectively,
providing 1.5 and 2.3 times relatively higher thanthe ultimate flexural capacity and non-cracked
flexural stiffness of the reinforced concrete column
section. It is noted that welding of the column
reinforcement to the steel box need to be carefully
made. The ultimate capacity of the precast column is536

Environment

537

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

GEOMATE - Mie, Japan, Nov. 21-24, 2017

UTILIZATION OF BUCKLEY-LEVERET THEORY IN BAZARKAMI OIL
FIELD IN NORTHERN OF AFGHANISTAN
Zabihullah Mahdi and Shigeo Honma
ABSTRACT
Hydrocarbon resources are important for the rehabilitation and sustainable progresses of Afghanistan’s infrastructure. The
purpose of this paper is to increase the oil production from petroleum reservoirs of Bazarkami oil field, applying BuckleyLeveret frontal displacement theory, in north part of Afghanistan. In this paper oil displacement is studied by injecting waterin to the petroleum reservoir which is known as waterflooding technique. The theory is investigated by laboratory experiment;
and graphical study is improved in a horizontal plane model which designed for study of fluid flow properties through porous
media. Furthermore, the result of laboratory experiment is compared with graphical calculation, then the theory is applied on
the planed oil field, which is now under process of a private petroleum company. The relative permeability of oil and waterthat obtained by laboratory experiment in reference to the literature by authors, is performed in this study. Based on this study,
a considerable amount of oil production obtained from Bazarkami oil field, by determining water-oil displacement
characteristic, residual oil saturation, Advance frontal saturation and FBL is determined.



Keywords—waterflooding, petroleum reservoir engineering, two-phase flow, immiscible displacement in porous media, relative permeability,
Buckley-Leveret.
INTRODUCTION
Fig. 1 illustrated a naturally general state of a petroleum
reservoir where gas is located at the top of the reservoir
under cap rock, oil is stored under the gas and there is waterin the bed of reservoir [5]-[8].
When water is injected into a petroleum reservoir, oil isdisplaced toward the production well in a situation of twophase flow. Buckley and Leverett, in 1942, have studied
the mechanism of immiscible displacement of two-phaseflow [6].

CO
W

Fig. 1 Typical petroleum reservoir

The Buckley-Leverett frontal displacement theory describes
a graphical method to calculate saturation profile based onrelative permeability; the effect of capillary pressure between
two fluids and the gravitational effects are assumed to beneglected. Based on this theory, the advance of a front
saturation by displacing fluid is affected by the oil and water
permeability and viscosity ratio between the two fluids [11].

In this pepper recovery of heavy oil by water based on the
Buckley-Leverett frontal displacement theory has been
evaluated. In this study first the oil displacement by waterobtained by laboratory experiment then the graphicalcalculation has been applied. Finally, the result of the laboratory
experiment and graphical calculation have been compared. In
this paper, the residual oil saturation, irreducible water
saturation, SBL, fBL and heavy oil recovery factor were
determined.
BUCKLEY-LEVERETT THEORY
Buckley-Leverett is a simple, widely used method ofinvestigating the advance of a fluid displacement front in an
immiscible displacement process [3],[8]. The theory is usedfractional flow and it is based on flow should be linear andhorizontal; water is injected into a petroleum reservoir; oil andwater are both incompressible; oil and water are immiscible andthe effect of gravity and capillary pressure are negligible [8].
Mostly in petroleum reservoir rocks there is a transition zone
between water and oil. Saturation of water is 100% in a true
water zone but in the oil zone, there is usually connate water,which counts as an immobile water. Oil and water will produce
together from a well if it is in the transition zone. The fractional
flow rate at each point will depend on to the water and oil
saturation in the reservoir. It is mentioned that BuckleyLeverett advance theory is an application of the law of the massconservation [8].
Fluid flow through a small volume section with length of ∆xand cross-sectional area of “A" may be expressed in terms of
w
total flow rate qt as in(1)-(3):o538qt  qo  qw
(1)

GEOMATE - Mie, Japan, Nov. 21-24, 2017q w  qt  f w

er

Produ

Wat

(2)

qo  qt  f o  qt  (1  f w )(3)
In Eq. 3 the q is volumetric flow rate in petroleum reservoir
situations, sub-script (o, w, and t) referred to the oil, water, andtotal rate, respectively and fw and fo are water and oil fractional
flow respectively.
The one-dimensional flow rate of oil and water byconsidering of oil displacement by water in a completely
saturated porous medium can be investigated by Darcy’s law asWO

k k A pqw   z rw  w
w  z(4)

Fig. 2 Displacement of oil by water in a natural petroleum
reservoir.

k k A pqo   z ro  oo  z(7) gives(5)
in equation 4 and 5,
kz is the intrinsic permeability of theporous medium, in equations 4 and 5, A the cross-sectional areaof the reservoir,
andare the dynamic viscosityof oil and water, kro and krw are the relative permeability of oil
and water, pw and po and pore pressure of water and oil
respectively.
As illustrated in Fig. 4 the relative permeability of oil andwater (kro and krw) are typically given as a function of water
saturation Sw and Sor and Swi are the residual oil saturation andirreducible water saturation in the petroleum reservoir. The
capillary pressure is denoted by po/w, and pw and it can write as
equation (6):(p  p )qw   kxkrwA  o o/w
w
x
subtracting Eq. (4) from Eq. (6), givesqT  qw (1 

(7)From the relation that explained in equation 1, 2 and 3 into Eq.

(8)

The fractional flow fw can give as

fw 

qw

qT

kx kro A  po / w
1 q 
T

o

x

(9)

kro  w
1k rw o

The capillary pressure (po/w) is essentially very small
compared with the oil/water pressure when oil displaced bywater in the petroleum reservoir. If the effect of capillarypressure neglected, for the horizontal flow, the fractional flow
equation is expressed simply as

fw 

(6)


p
1 q w( w
 qo o )   o / w
x
kx A
k rw
k ro

k ro  w k x k ro A  po / w)ok rw  ox1k 
1  ro w
krw o

(10)
The continuity equation may be presented to take theconservation of fluid mass [13], and this is expressed as



 qw
S
 A w
xt(11)
In equation (11), φ is the porosity of the reservoir rock. Using
the relations qw = fw qT and fw (Sw), Eq. (11) is rewritten as:
q T d f w S w
S w

t



(
)
A d S w  x

Because Sw (z, t), we can express saturation change as
539

(12)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

dSw

Sw

S
Sw
dx  w dt
x
t

1

(13)
In Eq. (13), if the fluid is at constant saturation during thedisplacement process, can rewrite it as

Sor

d

Sw

c

SBL

A=B

Water

S
Sw
dx  w dt
0
x
t
(14)
Then, it follows that

fw’

B

a

b

A

f

Oil
Swi

x

0

Sw
S dx
 w
x dt
t

Fig. 3 Tentative saturation profile

RELATIVE PERMEABILITY OF HEAVY OIL AND WATER

x qT dfw
 ( )t A dSw

(16)
Equation (16) indicates the Buckley-Leverett theory. Thisequation illustrates, the rate of the advance plane of fixed water
saturation Sw, which is directly proportion to the rate of changes
in the stream and is a composition with saturation. Because fw
is not an explicit function of t, so Eq. (16) can be integrated togive the position of a particular saturation value as a function oftime.

q t dfxSw  T ( w )  x0
A dSw

Relative permeability is an important parameter that controls
the immiscible displacement of two-phase fluids flow in porous
media. There are numerous factors that affect the relative
permeability such as fluid saturations, the effect of rock pore
structure, degree of initial saturation Swi, wettability, andtemperature. The relative permeability value is measured
through laboratory test by steady-state (SS) methods andunsteady-state (USS) methods [5]. The wetting fluid saturation
curves were usually water, Sw, extending from the irreducible
wetting-phase saturation to the residual oil saturation. As therelative permeability curve of water, krw, increases, the relative
permeability curve of oil, kro, gradually decrease withdesaturation of oil, and in contrast the relative permeability ofwater will gradually rises to its maximum value krws (end-pointwater permeability) at the time where kro is 0 because waterphase is mobile and at it has maximum saturation [12].

(17)In Eq. (17), z0 is the position of the water saturation at time t =0.
The saturation profile which explained by Eq. (17) is describedin Fig. 3 denoted by the curves “abcd”. The conservation of themass over the advance position was applied by Morel and
Seytoux [9]. Based on this application the hatched area which
denoted by A is equal to the hatched area described by B in Fig.
3. The saturation advanced immediately behind the front can becalculated by tangent point c on the fractional flow curve. The
tangent point c on the fractional flow curve is explained in Fig.
9. The sudden front in the saturation profile is given by line cf(Fig. 9) [10].

1.0
1.0

0.8

0.6

So

0.4

0.2

0

(b) Heavy oil
Sor = 0.27
Swr = 0.12
krws = 0.064

0.8krw , kro

(15)
Substituting Eq. (15) into Eq. (12), obtain

0.6

kro

0.4

Swr

Sor

0.2

krw
0

0

0.2

0.4

krws

Sw

0.6

0.8

1.0

Fig. 4 Relative permeability curves for heavy oil displacement bywater [12].

Fig. 4 illustrated the relative permeability curves of heavy oil
540

GEOMATE - Mie, Japan, Nov. 21-24, 2017
and water measured through laboratory experiment by steadystate method (SS). In Fig. 4 as relative permeability curves ofwater, krw, increases, the relative permeability curve of heavy
oil, kro, gradually decreases. At the left side of the Fig. 4 there
is irreducible water saturation (Swr = 0.12) and at the right sideof the graph, the residual oil saturation (Sor = 0.27) were
demonstrated. It is noticed that displacement of heavy oil bywater investigation by Buckley-Leverett frontal displacement
theory was calculated by using the relative permeability curvesof heavy oil and water illustrated in Fig. 4.

pours media. Water supply tank pushed oil and displaced itfrom the left side of plain to the right side, displaced fractional
fluids discharge were collected at the end of right side of themodel.
B.
Experimental investigation
Table 1 illustrated the properties of heavy oil, water, sand andexperimental model that have been used in the test. Horizontal
squire plain model that illustrated in Fig. 5 was packed sand,first saturated by heavy oil. Water pushed through saturated
sand plain to displaced heavy oil. Table 2 illustrated piezometerdata recorded during the test, from observation wells, itillustrated the hydraulic head verity with the time differences.
Fig. 6 illustrated fractional flow discharge of oil and water
through horizontal squire plain model. Fig. 6 illustrated heavy
oil displacement by water (qo = qT, qT is the total input rate). As
illustrated in Fig. 6 when soil pore in horizontal squire plain was
saturated by heavy oil, the fractional discharge at the outlet fod
is 1 until some pore volume, and later some amount of water
discharged. Therefore, there was only oil discharged at first 120
min during the operation. After 120 min the oil fractional
discharge decreased and water discharge was increased.
Finally, after 180 min fluid flow experiment, kerosene
discharge was too less, only water is discharged ( fwd = 1) andfluid flow became the steady state. There was still some amountof heavy oil remained in the plain that can refer to residual oil
saturation (Sor = 0.27).
In this experiment total amount of heavy oil displaced bywater until 120 min was 1073 cm3 (Qo = 0.39%) from total pore
Vv  V 2767
n  cm3). This experiment was done involume (180 min and total discharge of fluids were QT = 1610 cm3.

I.
EXPERIMENTAL INVESTIGATION OF WATERFLOODING
FOR HORIZONTAL DISPLACEMENT
A.
Experimental Model
Apparatus illustrated in Fig. 5 was used for horizontal oil
displacement by water. Toyoura sand (with the particle
diameter, D = 0.105-0.425mm) and the density of soil particle
ρs=2.65g/cm3, was packed in the horizontal square plane withthe constant density. It was saturated with heavy oil for the
purpose of oil displacement by water.
This apparatus was a regular plane and horizontal squaremodel of 60 cm length and 120 cm2 cross-sectional area. At theboth sides of the horizontal plane, there was volume area that
could keep piezometer pressure at a constant level. There waswater supply tank at the left side of the model. The model was
designed to study the fluid flow characteristic through porous
media. This model made from glass material and has 9observation wells, with the upstream and downstream level thathave been sat to evaluate the hydraulic head from fluid flowpressure. The purpose of this investigation was to evaluate
linear horizontal immiscible displacement of fluids flow in
4
Up Stream
W9

Piezometer
Pressure

3

Down Stream

W 1 W2 W 3 W 4 W 5 W6 W7 W8UpStream
60cm
W7

W4

W8

W5
1

W6

W2

Oil

W3

W

Fig. 5 Experimental apparatus

541

W9

Down

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table I Properties of heavy oil, water, and test material.
Soil nameToyoura sand (0.425～0.105mm)

Oil

Heavy Oil (20Ԩ）

Density of soil particle

2.65 (gr/cm3 )Density

0.837

Column length

60.0 (cm)

Viscosity

0.0107

Column diameter

3.0 (cm)

Volume of soil

0.001

Sectional area

120.0 (cm2)

Dry density

7200.00

Dry mass of soil

10000.0 (g)Porosity

1.389

Void ratio

0.908

Pore volume3436.42 (cm3)

Pumping rate of water- (cm3/s)

Pumping rate of oil

Table II Hydraulic head data recorded from the test.
Time : 15 min Time : 30 min Time : 45 min
WellnumberHydraulichead

Hydraulichead

Hydraulic
head

1

13 cm

17 cm

25 cm

2

12.2 cm

24 cm

25 cm

3

13 cm

25 cm

25 cm

4

7 cm

7 cm

14 cm

5

7 cm

7 cm

9 cm

6

6 cm

6.5 cm

9 cm

7

1 cm

1.2 cm

1.5 cm8

1 cm

1.2 cm

1.5 cm9

1 cm

1.2 cm

1.5 cmUpstream

25 cm

25 cm

25 cm

Downstream

0 cm

0 cm

0 cm

Time : 60 min Time : 85 min Time : 110 min
WellnumberHydraulichead

Hydraulichead

Hydraulic
head

1

26 cm

28 cm

28 cm

2

26 cm

28 cm

27 cm

3

26 cm

28 cm

27 cm

4

18 cm

21 cm

21 cm

5

10 cm

21 cm

21 cm

6

16.5 cm

21 cm

21 cm

7

2 cm

14 cm

14.5 cm

8

2 cm

15 cm

15 cm

9

2 cm

1.5 cm14 cm

Upstream

25 cm

25 cm

25 cm

Downstream

0 cm

0 cm

0 cm

542

-

(cm3/s)GEOMATE - Mie, Japan, Nov. 21-24, 2017
Fig. 7 illustrated the hydraulic head and experimental model
during a test at different times. By considering the hydraulichead and piezometer pressure and heavy oil displacement bywater in the horizontal square, the plane model is investigatedin Fig. 7. As illustrated in Fig. 7 every individual contour line
state equipotential line of pressure differences. In fact, thedrawing contour line is based on interpolation assumption andapproximation method using the observation data recorded
during the test.
Unstaedy statae(under displacment)

1

Start
i
t

of

During experiment

After 25 min duringexperiment

After 90 min duringexperiment

Steady state

Heavy oil
0.8

fwd

S w = 0.83
S or = 0.17

Displaced pore heavyoil (V).

0.6

Fig. 8 Experimental apparatus during operation.

water

fwd , fod0.4

qw= qT

0.2

fod

II.

EXPERIMENTAL MODEL

The data of table 1 were used for investigation of heavy oil
displacement by water through Buckley-Leverett frontal
1.0
displacement theory. Fig. 5 considered as an artificial
petroleum reservoir in this study. In this investigation relative
permeability of heavy oil and water that illustrated in Fig. 4
were used. The fractional flow of water and oil may be
calculated by equation 10 of section 2. It is known from theexperiment that discharge of fluids is 8.94 cm3 per min, so thewater saturation at the front and the average saturation behindthe front are found through the graphical method to be SBL =0.51 and Sw = 0.56. As illustrated in Fig. 9 the fraction flow ofwater is an S shape and by using intersection between thetangent line and fw = 1 can calculate the SBL and fBL.

Sor = 0.17
0

0.0

0.3

Vp

0.5

APPLICATION OF BUCKLEY-LEVERETT THEORY TO

0.8

Fig. 6 Experimental result of the fractional discharge of pore heavy
oil and water

1.0

1.0

0.8

So

0.6

k ro

k rw, k ro, fw

0.2

0.0

(b) Heavy oil
S or = 0.27
S wi = 0.12
krws = 0.064

C

fBL

0.8

0.4

0.6
0.4

fw
S wr

Sor

0.2
k rw
0.0

Fig. 7 Contour line for heavy oil displacement by water
based on piezometer pressure and it is cross- section.

0.0

0.2

S BL= 0.51

0.4

Sw

0.6

0.8

1.0

S w = 0.56

Fig. 9 Relative permeability for heavy oil displacement by waterand fractional flow curves.

Fig. 10 illustrated heavy oil displacement by water analyzed
based on Buckley-Leverett frontal displacement theory. It has
seen the saturation front progresses toward the outlet at aconstant speed, and breakthrough occurs at t = 147 min. As
543

GEOMATE - Mie, Japan, Nov. 21-24, 2017shown in Fig. 10 the water displaced heavy oil and reach to theend of a plane model at 147 min and breakthrough occurred, butthere is still some amount of heavy oil remained in the column
which may be discharged with water together as point out inexperiment investigation in section 4. The amount of oil
produced may be calculated for a reservoir of area A anddistance B by writing Eq. (16) as
d x / B  f w' qT dt / A B  f w' qT dt / V p  f w' d v p

displaced by water in units of pore volume [14]. The oilrecovery factor of this condition can be calculated by(18)

where Vp = AφB is the pore volume of the reservoir and dvp isthe pore volume of water injected. Because the saturation issteady, the equation can be integrated to obtain the front ofswept by water.
(19)
x  B f w' vp
where vp is the pore volume of water injected. When x reaches
B, the water saturation at the front is SBL, which makes it
possible to evaluate fw’ and calculate vp, the total amount of oil

RF S w  S or
1  Sor

(20)

RFD 


S w  S wi
1  S wi  S or

(21)

The heavy oil recovery factor is also calculated from Eq. (20)and found to be RF = 0.40, from which the amount of waterproduced up to the breakthrough is A φ B × RF = 1252 cm3 (QoV2746
n 3) for the=0.45%) from total pore volume (cmv V 
given experimental sand horizontal square plain model.

Fig. 10 Calculated results of saturation profile by Buckley –Leverett analysis for heavy oil. displacement by water.

544

GEOMATE - Mie, Japan, Nov. 21-24, 2017
RF Recovery factor.

III.

CONCLUSION

The conclusion for this study will be explained asfollows:
1 According to the Buckley-Leverett frontal
displacement theory which describes amethod of investigating saturation based on
the relative permeability and thegravitational effect and capillary pressure
effect between the two immiscible fluids
are neglected, had been evaluated. It has
been identified that fluid flow throughporous media should be linear andhorizontal. It is mentioned that thesaturation advance is largely affected by
the permeability of oil and water relativity
to collectors and to the viscosity ratio
between the two immiscible fluids.

ACKNOWLEDGMENT
The authors are great fully appreciate from Tokai
University to provide a comfortable environment for
doing the research. We would like to thank fromProf. HONMA who has supported us by his kindadvice and sharing his precious experience during
this investigation.
REFERENCES[1]“Enhanced Oil Recovery”, Don, W. Green, G. Paul
Willhite, 1998.
[2] M. Shepherd. Factors Influencing Recovery From Oil and
Gas Fields, In M. Shepherd, Oil Field Production Geology,
AAPG Memoir 91, p. 37-46.
[3] R.C. Craft and M. Hawkins, Revised by R.E. Terry,“Applied Petroleum Reservoir Engineering,” (PrenticeHall, 1991), pp.1-35.
[4] J X . Holdings: Construction of Petroleum Reservoir,
http://www.hd.jx-group.co.jp (accessed on 03/ 2014).
(Translated in English by authors.).
[5] (CRC Press, 2013), pp.45-83.
[6] J X . Holdings: Construction of Petroleum Reservoir,
http://www.hd.jx-group.co.jp (2014) data10. (Translated in
English by authors.), accessed on 02/ 2014.
[7] S.E. Buckley and M.C. Leverett, “Mechanism of Fluid
Displacement in Sands, Transactions AIME,” Vol.146,(1942), pp.107-116.
[8] “Principle of applied reservoir simulation”, John R. Fanchi.
[9] H.J. Morel-Seytoux, “Flow through Porous Media,” R.J.M.
de Wiest ed., (Academic Press, 1969), pp.456-516.
[10] A. Arabzai and S. Honma “Numerical Simulation of the
Buckley-Leverett Problem,” Proceedings of School ofEngineering of Tokai University, Vol.38 (2013), pp.9-14.
[11] Hagoort, J “Displacement Stability of Water Drives in
Water Wet Connate Water Bearing Reservoirs,” 1974. Soc.Pet. Eng. J., February: 63-74. Trans. AI ME.
[12] J. Nazari, F. Nasiry, N. Seddiqi and S. Honma “Influence ofRelative Permeability and Viscosity Ratio on Oil
Displacement by Water in Petroleum Reservoir,” Proc.
School of Eng. Tokai Univ., Vol.40 (2015), pp.15-20.
[13] Jacob Bear, “Dynamics of fluids in porous Media,” 1972, pp465-479.
[14] A.Y. Dandekar, “Petroleum Reservoir, Rock and Fluid
Properties,” (CRC Press, 2013), pp.2-10.

2

3

It is also investigated the rate at which an
injected water bank moves through a
porous medium. The graphical study isused by fractional flow theory and is basedsuch as flow should be linear andhorizontal, water is injected into a
petroleum reservoir, oil and water are bothincompressible, oil and water are
immiscible and the effect of gravity andcapillary pressure are negligible.
Recovery of heavy oil by water is studied
in the laboratory, experiments are done toevaluate the residual oil saturation andrecovery factor.
APPENDIXk
Intrinsic permeability
krw Relative permeability of water
kro Relative permeability of oil
krws Endpoint relative permeability
μw Viscosity of waterμo
Viscosity of oil
ρw Density of water
ρo Density of oil
pw
Water pressurepo
Oil pressure
Total pumping rate of oil and waterqT
qoAmount of oil
qw
Amount of water
So
Water saturation
Sw
Oil saturation
Sor Residual oil saturation
Swi Irreducible water saturation
fw
Fractional water flowφ
Porosity of the reservoir
Vp Pore volume
A
Cross-sectional area
B
Thickness of reservoir
545

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE BEHAVIOR OF WASTE PULLING BY PILE DRIVING
THROUGH THE BARRIER CLAY LAYER ON CONTROLLED
COASTAL LANDFILL SITE
Takayuki Hirao1, Yoshiaki Kikuchi2 Taichi Hyodo3 Masatsugu Kiko4 Kouta Katagishi5 Shohei Namiki5
Satoshi Matsumura6 and Makoto Takemoto1
1
Chuden Engineering Consultants Co., Ltd., Japan; 2,3,4,5 Tokyo University of Science, Japan; 6 Port andAirport Research Institute, Japan

ABSTRACTThe utilization of coastal waste landfill site remains at low level, up to now. In the consideration of advanced
use of these sites, it is necessary to drive some foundation piles through the barrier clay layer. However, there isa concern in the actual field that waste will be pulled into the clay layer by piling. Therefore, a series ofexperiments were conducted in this research, examining the effect of dragging prevention on pile tip, by model
pile penetration experiment and X-ray CT scanning. According to the experiments results, it was found that thepulled-in waste can be reduced by sharpening the tip of the pile. Additionally, with a pile that has an outer edge
on the tip, wastes can be easily pulled into between the clay layer and pile, but also found that the pulled-in
waste can be reduced by coating a swelling material on the pile surface. Therefore, it is assumed that bringwaste can be reduced with a pile that has reinforcement band.
Keywords: pile foundation, pulled-in waste, X-ray CT scanning, absorbent polymer

standard as waste landfill site after pile driving,
however the effect of pile driving through the barrier
clay layer on permeability performance has not beencleared in this stage. Also, there is a concern thatwaste will be pulled into clay layer or taken out ofsite in some case, while the pile is driving, becauseof the waste gets tangled and adhere to the pile,
However, the effect difference by each pile driving
method is also unknown. It is considered that suchfacts are the cause to not to make advanced use oflandfill site.
Against to this situation, Kikuchi and Hashizume[2] or Kamon et al. [3] are doing experimental
research about the effect to barrier performances. As
a result, it has shown that even if voids are formed
between clay layer and the pile surface, if clay layer
is normal consolidation state, the voids closed in
short time, and there is no influence to barrier ofclay layer. Also, about influence by earthquake,
Kikuchi et al. [4] have shown that barrier
performance is not lowered and pond water (internal
water) does not leak to outer site.
On the other side, about waste dragging in to theclay layer, there is an actual case [1] that piles were
driven through the barrier clay layer as bridgefoundation. In this pile driving method, the steel
casing is installed to the ground of landfill site. Thenremove the waste in the casing by hammer glove,and make the space that is not filled in waste, then,drive the pile into this space, at the last. With thispile driving method, waste can be completely
removed. However, the construction costs are very

INTRODUCTION
Like Tokyo bay or Osaka bay, the coastal waste
landfill has been executed mainly in the suburbs ofmetropolis in our country, Japan. These coastal
landfill sites have been constructed in offshore.
However, after the reclamation is completed, it will
become recognized as an important area, as theresult of surrounding port areas expansion. In thiscase, utility value of these landfill site will increase,which is expected to make effective use for as traffic
or industrial site. Nevertheless, currently the coastal
landfill site is used only horizontally, for such as
green space, park or golf course, but there are also
cases here and there that many sites are left unused.
As described below, the reasons are considered to belargely due to specific circumstance of the landfill
site.
When considering effective use for landfill site
as an industrial site, many foundation ground of
landfill site consist landfilled waste and clay layer as
barrier clay layer. Therefore, often the foundation
ground is too soft to support the constructions. Also,
clay layer is often normal consolidation states inthese case, that long term consolidation settlement
will become a problem for using the landfill sites.
Generally, a pile foundation type structure isconsider to be use in this case, and because of thepiles are required to install to a ground capable tosupport the structure, it is necessary to drive somefoundation piles through the barrier clay layer. The
barrier clay layer is necessary to satisfy structural
546

GEOMATE - Mie, Japan, Nov. 21-24, 2017

high, because it needs triple tubes. Therefore, theinferior of versatility to utilize as general structure
foundation is the current subject.
Against to this situation, Kikuchi [5] and Hirao
et al. [6] are doing experimental research, an effectfor waste type and pile tip shape about behavior ofwaste dragging by pile driving. And the result shownthat is inevitable dragging with close tip piles, and a
few dragging with shape tip piles, and it is effective
to digging in a pile or coating the swelling material
on pile surface in order to prevent the waste
dragging.
However, these experimental researches are
elemental experiments for finding the effect of pile
tip shape qualitatively, and it had carried out underconditions with using the closing tip piles and by
simulating the waste with sand. The foundation piles
that are mainly used in the actual field are open tip
piles made by concrete and steel. It is found thatwastes are not homogeneous granules, and have
many lumpy items and liner items such as wires
include.
From this background, in this research, consider
the behavior of waste dragging by installing open
ended piles and lumpy items, and investigate theeffect of the difference of the pile tip shape andswelling material applied to the pile surface.

it is impossible to reproduce these methods inexperiments. Therefore, assuming a driving pilemethod of directly driving into the ground which isconsidered to be the method pulled-in wastes themost, and then confirm the pulled-in conditions at
tip or surface of the piles by experiments.
MODEL PILE DRIVING TESTCREATE THE MODEL CLAY LAYER
In this experiment, commercial clay called “blueclay” as clay layer that simulates the barrier clay
layer was used. It was adjusted by sieving to 106μm,
considering the separate clay and sand as describedlater.
Properties of the clay are shown in Table 1. The
water content of the blue clay adjusted to slurrystates as water content ratio of 100%. It was put into
the test vessel shown at the left side on Fig.1. Afterone and a half day, consolidate with pressure
p=100kN/m2 (equivalent to stress states GL.-20m on
barrier clay layer). Then continue the consolidation
until time to 3Te, to create the model clay layer(thickness h=8cm).
LAYING SANDS AND GRAVELS
Silica sand No.5 and gravel No.7 were used asmaterials that simulate wastes. Silica sand No.5 issimulated as small particle size wastes, using theparticles (soil density ρs=2.65 g/cm3 ， average
particle size D50=0.589 mm) left in the sieve with
250 μm for separate from clay. Also, gravel No.7 issimulated as large particle size wastes, using theparticles (average particle size D50=3.304 mm)
remain in the sieve with 2 mm. Further, these silica
sands and gravels were laid on the clay layer byfalling underwater method. It carries out following
two type tests to compare the particle size. In case-1,
silica sand lay at thickness of 5 cm, this is simulated
as small particle size wastes. In other case-2, silica
sands and gravels mixed by weight ratio as 3:7. Thislay at thickness 1cm, and silica sand lay at thickness
4 cm. These are simulated as the condition withlarge particle size mixed.

METHODOLOGY OF EXPERIMENTIn the experiment for this research, to consider
the behavior that waste will be pulled into the clay
layer by piling, sands and gravels were laid on clay
layer, and drive the piles into this layer, thenmeasured the weight of the sands and gravels thatwere pulled into the clay layer. The following two
methods were used for a method of measuring thesands and gravels that was pulled-in.
The first method is to measure the weight ofsands and gravels that has been dragged directly bytaking clay layer out from the test vessel after piledriving (hereinafter referred to as “model piledriving test”). The second method is to observe
visually for pulled-in conditions of sands and gravels,and to count number of particles, by analysis using
the X-ray CT scanner of the test vessel (hereinafterreferred to as “X-ray CT scanning test”).
However, in the experiment in this research,barrier clay layer is modeled as clay layer, andwastes are modeled as sands and gravels, thenconfirmed the pulled-in conditions of sands andgravels by model pile driving to clay, sand andgravel layer. It is considered that the parameter todominate the pulled-in conditions are friction forces
between the piles and ground, or clearance aroundthe piles and particle size. In this experiment, it ismodeled by reproducing the stress state and theclearance and the particle size at the realization field.
Also, there are various methods for pile driving, andTable 1 Physical Property of BLUE CLAY
Soil Density
2.79 g/cm3
Liquid Limit
40.1 %
Plastic Limit
24.2 %
Plastic Index
15.9

Fig. 1
547

Experimental Method (outline draw)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

DRIVING MODEL PILES
Next, a model pile drives into the model clay
layer, using the 4 different type of pile tip shape asshown in Fig.3 for considering the influence of pile
tip shape. A model pile drives to the bottom of clay
layer statically at driving speed about 10 mm/min, atcenter of model ground, as shown left side in Fig.1.
Incidentally, model pile diameter is set to
φ19mm, to secure three times of the pile diameter
between pile and vessel inside wall, to not to beaffected by lateral conditions at test vessel (φ15cm) when pile driving.

visibility of sand particle, structural restrictions, andsecure experiment time in X-ray CT scanning tests.
For this reason, it is difficult to compare this Xray CT scanning tests and model pile driving tests indirectly. However, it can evaluate the mechanism ofpulled-in qualitatively by confirmation visually of
the pulled-in behavior of sands and gravels causedby pile driving.
First, to create the model ground, mix the clay
soil at initial water content of w=53 %. And thencreate by consolidation at pressure p=100 kPa toshorten the test time and ensure the thickness of test
piece using test vessel as shown in the left side of
Fig.4.
Next, lay the sands and gravels that is simulated
to waste layer on top of the model ground by methodof water falling. Sands that was used is YAMAICHI
silica sand No.3 (ρs=2.67 g/cm3, D50=1.276 mm),gravels is gravel No.7 as remaining at 4.75 mm sieve.
Same as LAYING SANDS AND GRAVELS,
conducted with two case, which is case-1 that laid
only silica sands at 5 cm thickness, and case-2 thatlaid mixed soils (weight ratio of gravels and silica
sands is 3:7) at 1cm thickness, and overlay silica
sands at 4 cm thickness. After that, drive the threedifferent model type of piles that have different
shapes on pile tip (Fig.5) in to the center of model
ground till the bottom at driving speed 2 mm/min
statically. At that time, stop driving the pile at eachcertain depth, to scan the test vessel. This is anaction to irradiates horizontally X-ray to test vessel,and visualize the absorption of X-ray that catch at
sensor through the test vessel. Conduct this action
certain times while the test vessel rotates 360
degrees, and reconstruction 3 dimension picturesfrom 2 dimension pictures obtained by analysis.
With this method, sands and gravels pulled-in
behavior by pile driving can be visually confirmed.
And count the number of sands and gravels on
pictures. Also, in this experiment, coating theswelling material on pile surface is conducted, assame as PILE DRIVING TESTS.

SWELLING MATERILALSIn all of the above experiment cases, experimentcase with coating the swelling material on the pilesurface, was also conducted. This material is highmolecular polymer in solid state in normal
conditions, however if it absorbs the water, it swells
then becomes to in gel state. It is expected so thatthe dragging wastes will be reduced by reducing
friction forces between the pile and wastes. Prior tothis experiment, coat swelling material 5 cm on thetip part of the piles, and let it dry enough. Further,
after driving a model pile to the bottom of sand layer(top of the clay layer), in order to absorb and swellenough, standing still for 2 hours, and then driven
into the bottom of model ground.
SAMPLING
After driving the pile, clay was sampled aroundthe pile in every 8mm thickness, as shown in thecenter of the Fig.1. Further, clay and sand wereseparated using 250 μm sieve as shown on the rightside of the Fig.1. And then measure the sands weightthat was pulled into model ground per depth.
X-RAY CT SCANNING TESTSThis experiment method is almost the same as
the method of model pile driving tests. It carries out
with some different conditions, in order to ensure theFig. 2Laying Method of Sands and Gravels (case-2)

Fig. 3

pile tip shape of model piles(Pile Driving tests)

Fig. 4

Test Vessel and Laying method (case-2)

Fig. 5 pile tip shape of model piles(X-ray CT Scanning tests)
548

GEOMATE - Mie, Japan, Nov. 21-24, 2017

However, after pile driving, it becomes to gel stateby swelling the water from the ground, and expands
suddenly. This expanded gel fills the gap between
piles surface and surrounding ground, and reduces
the friction forces between piles and ground.
Next, among the experiments(case-1) that carriedout on the ground made by only sands, by changed
the tip shape of the piles, the result that compareswith and without swelling materials are shown in
Fig.7. As the result, pulled-in behavior adjacent tothe surface of clay layer was confirmed at each piles,
same as Fig.6. Of these, it is difficult to confirm theeffect of reducing the dragging by swelling materials,
due to the low volume of dragging by (a) open tip
pile and (c) outer thin piles. Also, regarding the (b)close tip pile, it is pulled into the bottom of the clay
layer, because of the creation of active wedge on tipof the piles. However, there are no clearly
differences because of the existence of swellingmaterials or no, and the dragging reduction effect byreducing the friction forces around the pile surface,cannot be confirmed .
On the other hand, about (d) piles that has an

RESULT OF EXPERIMENTS
MODEL PILE DRIVING TESTSMIXURE OF SANDS AND GRAVELS
The result (case-2) that was conducted withsilica sand No.5 and gravel No.7. A distribution
chart of weight of sands and gravels that was pulled
into clay layer and its depth is shown in the Fig.6. It
shows the vertical axis is depth(cm) from top surface
of clay layer, and the horizontal axis is the average
weight of the sand contains in the sample collectedfrom thickness 8 mm of clay, and directly count the
number of gravels. Incidentally, the thick line on thechart shows average weight within measurement
range (8 mm), and the polygonal line is connecting
these values at average depth.
As the result, pulled-in sands and gravels
adjacent to surface of clay layer, was confirmed oneach piles. Also, about (a) open tip pile and (c) piles
that has an outer edge on the tip, pulled-in sands
and gravels was confirmed from slightly under theclay layer, . Particularly, it is remarkable in the casewith an outer edge on the tip. Of these, pulled-insands and gravels up to 3 cm depth was confirmedwith (a) open tip pile. Further, it becomes zero at
deeper, this fact shows that pulled-in sands andgravels are less.
As shown in the Fig.7(b), in case of close tip pile,
behavior that is different from a lot of pulled-insands at the tip of the piles was confirmed. In case of(c) piles that has an outer edge on the tip, verified
pulled-in sands at the bottom of clay layer.
Incidentally, in case of (b) with the piles that has
thin outside, it was confirmed that pulled-in sands
and gravels into the clay layer is almost none. It issuggested to sharpening the tip is effective to reducethe dragging.

(a)Open tip(b)close tip

DRAGGING
REDUCTION
EFFECT
BY
SWELLING MATERIALSFirst, the situations of coating and after swellingare shown in the Fig.8. After coating the swellingmaterials on piles and dried, it becomes to harden
state, and it will not peel off from the pile surface.
(c)outer thin(d)outer edge
Fig. 7 Dragging depth profiles (case1)(a)Open tip(b)outer thin(c)outer edge
Fig. 6 Dragging depth profiles (case2)

Fig. 8549

Effect of Swelling Material

GEOMATE - Mie, Japan, Nov. 21-24, 2017

outer edge, reduce of the dragging into the internal
clay layer is confirmed, cause of the swellingmaterial fills the gap between piles and ground thatwas created by an outer edge, which it is consideredthat the swelling materials are effected to reduce
dragging into gap.

were trucked that can be identified before and after
the pile driving. In Fig.11, horizontal axis shows
penetration amount of the piles, and vertical axis
shows the depth which sand particles are pulled-in.
No.1 particle in figure adhere to tip of the pile,and pulled into clay layer while pile driving. It
shows that particle leaves from the tip of the pile atthe time the pile was driven to 10 mm. Identically,
No.2 particle leave from tip of the pile after pulledin until 35 mm depth, and No.3 particles until 50
mm depth. All of the particles remain at the depth
where it left from the tip of the pile. It is unlikely forthe particles that was left from tip of the pile, will bepulled-in further more due to the friction force of
pile surface.
Further, the enlarged picture of the surroundingof gravels that was pulled-in to the outside of piles isshown in Fig.12. According to this figure, it isconfirmed that sand particles adhere to the surface ofgravels, which creates a concern of possibility thatdragging the large scale particles can promote thesmall scale particles dragging.

X-RAY CT SCANNING TESTS
A sample picture obtained by X-ray CT scanningtest is shown in Fig.9. Dragging behavior into theclay layer can be confirmed by this picture.
DRAGGING BEHAVIOR AT THE TIP OF THE
PILESWith all of the experimental conditions, sands orgravels adhere to the tip of the piles, and pulled-in
into clay layer. To find this behavior, count the
number of the sands and gravels at the tip of thepiles by horizontal scanning pictures, which isshown in Fig.10.
As the result, in the case of open end pile, it has
sands pulled in to the bottom of the clay layer. In thecase of the outer thin piles and outer edge piles,
pulled-in has remained at the 25 mm depth. Also inthe case of gravels, confirmed dragging into the 20mm depth on the open end piles, though it is up to
10 mm depth on the outer thin piles and outer edge
piles. It is considered that particles of sand andgravel are easy to leave (not dragging) from tip of
the piles by sharpen the tip of the piles.
Next, about the behavior of sand particles thatare adhered to the open tip piles, the three particles

void

DRAGGING REDUCTION EFFECT
BY
SWELLING MATERIALS
About the pile with an outer edge at the tip, that
had confirmed the effect of swelling materials, will
confirm the difference of pulled-in amount, between
with or without using the swelling materials. The
vertical sectional view after pile driving is shown in
Fig.13, and the number of sand particles that had
pulled into the gap between piles and surroundground at this time, is shown in Fig.14. On thevertical sectional view, it is confirmed that manysand particles fell in to the gap on an outer edge,
when the swelling materials was not used.
Though, this number was confirmed to be reduced

sand particles

gravels
sand particles

gravelsFig. 9Picture of X-ray CT Scanning tests

Fig. 11 Behavior of sand particles at pile tip

gravelsadheared sand particles
Fig. 10 Dragging in pile tip

Fig. 12 Draging in pile tip
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

various things, so experiments was not conducted
about string state wastes, like wires or bands,
because dragging mechanism is different fromparticle wastes. An experiment of such a case isnecessary.
REFERENCES[1] Katayama H, Tezuka H, Yamashita K, “Triple
Tubular Steel Pile in the Waste Disposal
Landfill - The Second Stage Construction ofTokyo Port Coastal Road -”, Bridge andFoundation Engineering, Vol. 42, No. 4, 2008,
pp. 43-46.
[2] Kikuchi Y, Hashizume H, “Laboratory test on
permeability of ground around a pile”, symposium on geotechnical and geo-environmental
engineering, vol. 6, 2005, pp. 217-224.
[3] Kamon M, Katsumi T, Inui T, Hamada S,“Experimental Study on the Interface
Transmissivity between Clay Layer and Steel
Pile Installed at Waste Disposal Site”, Reprinted
from Journal of the Society of Materials Science,
vol. 54, No.11, 2005, pp. 1100-1104.
[4] Kikuchi Y, Sugano T, “Construction Possibilityof Piles Penetrating Impervious Ground in
Offshore Waste Repository”, GeotechnicalEngineering Magazine, vol. 56, No. 8, 2008, pp.
28-29.
[5] Kikuchi Y, Moriwaki T, Katsumi T, Hirao T,
Tsutakawa T, Hattori A, Okamoto K, Yamada
K, Sasaki K, “Influence of pile installation on
the barrier performance of natural clay layer at
offshore waste landfill”, Technical Note of The
Port and Airport Research Institute, No. 1252,
2012.
[6] Hirao T, Tsutakawa T, Sanada K, Moriwaki T,
Hattori A, Okamoto K, “A study on theinfluence of the foundation pile driving to theclay liner in the controlled type seaside landfillsite”, The 44th Japan National Conference on
Geotechnical Engineering, 2009, pp. 1907-1908.
[7] Watabe Y, Mizutani T, Kaneko T, Masukado K,“Applicability of piled foundation at confineddisposal facilities in coastal area – in situ
demonstration for pile-driving and impermeable
performance at untreated wastes ground”,
Technical Note of the Port and Airport ResearchInstitute, No. 1321, 2016.
[8] Okamoto K, Umezaki T, Hattori A,“Development of Absorbent Polymer Materials
for Reducing Adhesion and Skin Friction ofUnderground Structures”, Journal of JSCE,
Division C : Geotechnics, vol. 67, No. 4, 2011,
pp. 407-421.

(a)no Swelling Material (b)Swelling Materials
Fig. 13 Dragging in pile tip

Fig. 14 Dragging number in pile tip
in the case of using swelling materials. This isconsidered because of the swelling materials fell the
gap that was created by an outer edge, which means
the piles that has an outer edge, can expect the
dragging prevention effect by using swellingmaterials.
CONCLUSION AND FUTURE ISSUE
In this research, wastes was simulated withsands and gravels, and the behavior of these sands
being dragging into the clay layer was investigatedexperimentally. As a result, in order to reduce thedragging particle wastes into the clay layer, it wassuggested, to sharpen the tip of the piles, and theeffectiveness of coating swelling materials on thesurface of outer edge piles. Also, it was confirmed ofthe possibility that the dragging large scale waste
promote dragging small scale wastes, and theparticles that adhere on the tip of the piles, will not
be dragging further more after it left from the tip of
the piles. In this research, for the convenience ofexperiment, clay layer was consolidated at pressure
100 kPa, and so, it was in over-consolidation statethat is difficult to recover from deformation.
However, actual barrier clay layer of landfill
sites is often in the normal-consolidation state,
therefore, it is necessary to conduct an experiment in
the same state. Additionally, wastes contains

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TOXICITY AND BIOEFFICACY OF WEED ESSENTIAL OILSAGAINST COWPEA BRUCHIDS AND THEIR EFFECT ON
MUNGBEAN SEEDS
1

Ruchuon Wanna1 and Perayos Khangkhun1
Faculty of Technology, Mahasarakham University, Thailand
ABSTRACT

These investigations aimed to determine toxicity and bioefficacy of weed essential oils Bitter bush
(Eupatorium odoratum L.), Finger grass (Limnophila aromatica (Lamk.) Merr.), and Vietnamese mint
(Polygonum odoratum) derived by hydrodistillation against cowpea weevil, Callosobruchus maculatus(Fabricius) on stored mungbean. Experiments was assessed under laboratory conditions (30±2C, 70-80%RH
and 16L:8D photoperiods). Results showed that weed essential oils from Bitter bush, Finger grass and Vietamesemint leaves have contact toxicity on cowpea weevil as shown by the impregnated filter paper test. LC50 values
were 137.15, 225.17 and 99.12 ppm at 48 h after exposure, respectively. Fumigant toxicity by the fumigation
method on cowpea weevil showed all weed essential oils had high efficiency against the cowpea bruchids C.
maculatus )100% of mortality). Repellency toxicity test showed that weed essential oils from Bitter bush, Finger
grass and Vietnamese mint leaves have repellent toxicity on cowpea weevil as LC50 values were 607.23, 141.93
and 109.81 ppm at 6 h after exposure, respectively. The potential of weed essential oils on reproduction of the
cowpea bruchids female adults had strong repellent activity for egg laid on mungbean seeds, were 100% at 48 h.
Three weed essential oils did not affect the seed germinating. These results suggested that essential oils fromthree weed plants could be used as potential control agents for cowpea bruchids, and the database can be used for
active ingredient studies to develop commercial products in the future.
Keywords: Lethal Concentration, Toxicity, Mungbean Insect Pests, Oviposition Behavior, Seeds Viability
loss of weight, nutritional value and viability ofstored grains [3].
Control of cowpea bruchids in the field and store
has to be considered in relation to the economic
importance of the crop, since it is obvious that theseweevils are capable of attacking cowpea both in thefield and in storage. In the latter, where feasible, theuse of synthetic insecticides is one of the methods
used to control cowpea bruchids [4]. Insecticides
may be applied as liquid or fumigant formulations.
However, continuous use of chemical insecticides
may lead to serious problems such as insecticide
resistance. Non-chemical methods of bruchid control
offer an attractive alternative because the neither
leave chemical residues in the commodity no could
their use give rise to resistance in the pest. Suchmethods include periodic exposure of the grains tothe sun, coating seeds with cooking oils, or mixing
them with ash or sand [5]. Some plant materials
have insecticidal properties that could help to control
the invading pests [6]. Alternative options forprotection cowpea bruchids are using of nature local
plant extracts. They can be found and annually
growth, such as using of essential oils extracted fromthe local weeds. Therefore, the most people see
weeds and no useful. The objective of this study wasto evaluate the lethal toxicity, fumigant toxicity,repellent toxicity and oviposition behavior of weed

INTRODUCTION
Mungbean, Vigna radiata L. Wilczek is one of
the most important legume crops in Thailand.
Mungbean grown as short rotation crops
interspersed with rice and vegetable crops. It
provides an inexpensive source of dietary protein to
the people and use as protein supplement for meatand fish in animal feed industries. It contains
digestible carbohydrate, dietary fiber, calories andlysine [1], [2]. Growing mungbean need to keep
seeds for used as seed and consumption. The
production of mungbean (V. radiate) was restrictedby biotic and abiotic factors both in the field and theseed in storage. Among the constraining biotic
factors are insect pest. While crops may be infested
in the field, infestations are often too low to detect at
harvest. Bruchids are most often not detected until
seed has been stored for over long periods (e.g. forlonger than three months), especially at small scale
farming levels. Bruchids are a major and growing
problem in stored mungbean in all regions. Bruchids
breed rapidly in storage and by the time they aredetected, the infested grain is usually unmarketable.
The bruchid responsible for most infestations inmungbean is the cowpea bruchids, Callosobruchus
maculatus (Fabricius). Larvae developing within thegrain do the largest damage. Their damage caused
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essential oils on cowpea bruchids, including theireffect on mungbean seed viability.

Randomized Design (CRD) with 5 replicates in 5
laboratory experiment.

MATERIALS AND METHODS

Contact toxicity bioassay of weed essential oils

Insect Stock Culture

Contact toxicity of three weed essential oils
against cowpea bruchids were evaluated byimpregnated filter paper test, a modified method
after Fournet et al. [8]. Bioassay was conducted at30±2C, 70-80%RH and 16L:8D photoperiod. The
serial solutions of weed essential oils were preparedby dissolving in acetone to achieve the desiredconcentrations: 5-6 concentrations. For each
preparation was dropped and flowed on a disk offilter paper ( 9 cm) placed in a Petri dish ( 9 cm
and height 1.5 cm) using micropipette. The treatedfilter paper was air dried and allowed to evaporate
the solvent completely before cover petri dish wasplaced on the petri dish. Ten female adults ofcowpea bruchids taken from insect stock culture
were released in a petri dish and five replicates wereset for each concentration. Acetone was used ascontrols. The dead cowpea bruchids, no response to
blunted needle poking, after 24, 48 and 72 h wererecorded. The data were analyzed for the Median
Lethal Concentration (LC50).

Cowpea bruchids, Callosobruchus maculatus
was collected from the previously infested
mungbean seeds in the grain storage of Departmentof Agriculture Technology, Faculty of Technology,
Mahasarakham University. Insect rearing was
carried out inside a glass bottles ( 15 cm andheight 30 cm) covered with mesh netting and kept
under laboratory conditions (30±2C, 70-80%RH
and 16L: 8D photoperiods). Fifty pairs of male andfemale of C. maculatus adults were isolated andreleased in a glass bottle having 500 g of mungbean
seeds, removed infested seeds and sterile by kept
under freezing for 2 weeks and left for 24 h underambient conditions [7], covered by mesh netting.
After 4 weeks, they were separated and used female
adults (3-5 days old) in the investigation. Toxicity
and bioefficacy bioassays were performed on theadults.
Stored Product

Fumigant toxicity bioassay of weed essential oils

Mungbean obtained from the local market
healthy and fresh seeds were used to avoid any prestorage infestation seeds or egg laying of cowpea
bruchids and stored followed Ojanwana and Umoru[7]. Mungbean was used in experiments as effect ofweed essential oils on the egg laying behavior andmungbean seed germination.

Fumigant toxicity of three weed essential oils
was tested against female adults of the cowpea
bruchids C. maculatus modified method of Keita etal. [9]. Ten female adults taken from the insect stock
culture were placed in a glass bottle ( 5 cm andheight 6 cm) and covered with mesh netting andrubber band. Using micropipette dropped weed
essential oil inside the center of filter paper ( 2 cm)
in another a glass bottle with various concentrations.
Bring a glass bottle contained cowpea bruchids tooverlap with a glass bottle dropped of weed essential
oil into it. Use clear tape wrapped around a joint ofboth glass bottles and carried out under laboratory
conditions (30±2C, 70-80%RH and 16L:8D
photoperiods). Cowpea bruchids C. maculatus
cannot be directly contact oil because it had a meshbarrier. Dead of adult cowpea bruchids C. maculatus
were counted after 12, 24 and 48 h.

Weed Essential Oils Preparation
Three weed essential oils extracted from Bitterbush (Eupatorium odoratum L.), Finger grass(Limnophila aromatica (Lamk.) Merr.) and
Vietnamese mint (Polygonum odoratum), werecollected around the Mahasarakham local in the
Northeast of Thailand. Bring fresh leave of eachweed was washed and air dried in the shade. Using a
Steam distillation, the extraction of the essential oils
was performed from 1,000 g of fresh weed leaves
and 1 liter of distilled water with a rotary evaporator,
at the Department of Agricultural Technology,
Faculty of Technology, Mahasarakham University.
The weed essential oils were desiccated withanhydrous sodium and kept into a vial with the lid
closed in the dark at 4C until use.

Repellent toxicity of weed essential oils
Repellency toxicity bioassay was modified
method [10] by weighing 10 g of sterile mungbean
placed in flask and treated with the solvents of three
weed essential oils. Let until mungbean seeds driedto evaporate. Pour the mungbean into plastic cup (5 cm and height 2 cm), had a hole in the bottom sothat insect can get through but mungbean cannot,
placed on the top a glass bottle ( 5 cm and height 6cm). Ten female adults of cowpea mungbean C.

Experimental Procedure
The experiment was conducted at laboratory
conditions (30±2C, 70-80%RH and 16L:8D
photoperiod). Experimental design was Completely

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maculatus (3-5 days old) were released the middle ofplastic cup within contain treated mungbean seeds. It
closed with mesh net (size 6  12 cm) to prevented
insect evasion. Each treatment was replicated fivetimes and the numbers of cowpea bruchids C.
maculatus settled on each glass bottle were counted
and recorded at hourly intervals for 1, 3, 6 and 12 h.
Treated mungbean with acetone was used as control.

RESULTSContact Toxicity Bioassay of Weed Essential Oils
Weed essential oil of Vietnamese mint (P.
odoratum) had the most contact toxicity to cowpea
bruchids within 48 h after treatment with the LC50 of
99.12 ppm compare with 137.15 ppm of Bitter bush(E. odoratum) and 225.17 ppm of Finger grass (L.
aromatic), respectively (Table 1). Mortality value
exposed with three weed essential oils to cowpea
bruchids after treatment at 48 h resulted in adultmortality values between 42-66% and it cause
highest significant different (P<0.01) (Table 2).

Impact of weed essential oils on the oviposition
behavior
Weighing 10 g of sterile mungbean placed inflask and treated with various the solvents of three
weed essential oils. Let until mungbean seeds driedto evaporate. One pair of adults cowpea bruchids
placed in a glass bottle within contain treatedmungbean seeds for 48 h. Adults were separated andcounted the number of eggs on surface of mungbean
in each treatment, compared the control withacetone.

Fumigant Toxicity of Weed Essential Oils
It is reported that all weed essential oils had
efficiency against the cowpea mungbean C.
maculatus, 100% of adult mortality whencomparison with distilled water and acetone
treatments and also was high significant different.

Effect of weed essential oils on the mungbean seedviability

Repellent Toxicity of Weed Essential Oils
Result showed that essential oil of Vietnamesemint (P. odoratum) has highest against the cowpea
bruchids C. maculatus. And then Finger grass (L.
aromatic) oil and Bitter bush (E. odoratum) oil had
against the cowpea bruchids C. maculatus. LC50 at 6h were 109.81, 141.93 and 607.23 ppm, respectively(Table 3). Repellent value exposed with three weed
essential oils to cowpea bruchids after treatment at 6h resulted in adult mortality values between 34-66%
and it cause highest significant different (P<0.01)(Table 4).

Weighing 10 g of sterile mungbean placed inflask and treated with various concentrations (LC20and LC40) of three weed essential oils. Let until
mungbean seeds dried to evaporate. Bring mungbean
seeds tested seed germination by each treatedmungbean seed was counted and divided into 5
replicates (50 seeds per replicate). Germination test
was conducted in a plastic box (size 22  33 cm andheight 7 cm) within contain 1,000 g of fine sand,was incubated at 150°C for 10 h and separated theother contamination with mesh net, and distilledwater 132 ml. Put 50 seeds in a plastic box by a row
of five rows along the length of the row of 10seeds
off the plastic covered and kept on the shelf underlaboratory conditions. When seed germination was
opened the plastic box and keep moisture, add water.
Until after 7 days of seed germination were counted
seedling in each treatment for checking percentage
of seed germination.

Effect of Weed Essential Oils on the Oviposition
Behavior
The effect of tested three weeds essential oils on
the reproduction of the cowpea bruchids C.
maculatus female adults were studied using nochoice test. All weed essential oils acted as
oviposition deterrent. Egg laid by female on treatedseeds with weed essential oils had strong repellent
activity (100%) at 48 h (data no representation).

Data Analysis
Toxicity bioassay, linear regression analysis was
performed from the data obtained to estimate adultmortality for each concentration of three weed
essential oils. The mortality was calculated using the
Abbott formula [11]. The resulting concentrationmortality data was subjected to probit analysis [12].
Data recorded for percentage of mortality in all
toxicity experiments and percentage of seed viabilityof different treatments were subjected to statisticalanalysis using CRD design by one-way analysis ofvariance (ANOVA). Means were compared by using
Duncan’s Multiple Range Test (DMRT).

Effect of Weed Essential Oils on the Mungbean
Seed Viability
The findings of the present study indicated thatmungbean seeds treated with all weed essential oils
did not lose their viability and also did not show
significant effect on the seed germination rate within
7 days (Table 5).

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Table 1 Contact toxicity of weed essential oils against the cowpea bruchids C. maculatus at 48 h.
Weed essential oils
LC50a (ppm)
Bitter bush (E. odoratum)
137.15 ± 87.63
Finger grass (L. aromatic)
225.17 ± 99.43
Vietnamese mint (P. odoratum)
99.12 ± 132.90
aLC50 represent the median concentration.
b
95%CL represent the lower and upper fiducially limits.

95%CLb (ppm)
42.15 – 446.26
97.24 – 521.38
11.40 – 861.24

20.00860.02450.0003P-value
0.92630.8756
0.9862

Table 2 Mortality of cowpea bruchids C. maculatus with contact toxicity treated weed essential oils at 24, 48
and 72 h.
Mean (±SE) mortality (%)
24 h
48 h
72 h
Distilled water
0.0 ± 0.00 g
0.0 ± 0.00 i
2.0 ± 0.45 g
Acetone2.0 ± 0.45 f
2.0 ± 0.40 h
12.0 ± 1.10 f
Bitter bush100
28.0 ± 0.84 c
50.0 ± 0.63 f
84.0 ± 0.55 e(E. odoratum)200
30.0 ± 1.22 b
50.0 ± 0.89 f
84.0 ± 1.14 e
300
34.0 ± 0.89 a
56.0 ± 1.02 c
86.0 ± 1.14 d
Finger grass
100
24.0 ± 0.55 e
42.0 ± 0.75 g
84.0 ± 1.14 e(L. aromatic)
20034.0 ± 1.34 a
54.0 ± 1.02 d
86.0 ± 0.55 d
300
34.0 ± 1.14 a
62.0 ± 2.04 b
90.0 ± 1.41 c
Vietnamese mint
100
26.0 ± 0.89 d
52.0 ± 0.40 e
90.0 ± 0.71 c(P. odoratum)200
28.0 ± 1.30 c
52.0 ± 0.98 e
98.0 ± 0.45 b
300
34.0 ± 1.14 a
66.0 ± 1.74 a
100.0 ± 0.00 a
Means within the same column followed by the same letter are not significantly different (DMRT: P>0.05).
Treatments

Conc.
(ppm)

Table 3 Repellent toxicity of three weed essential oils against cowpea bruchids C. maculatus at 6 h.
Weed essential oils
LC50a (ppm)
Bitter bush (E. odoratum)
607.23 ± 145.44
Finger grass (L. aromatic)
141.93 ± 42.85
Vietnamese mint (P. odoratum)
109.81 ± 51.64
aLC50 represent the median concentration.
b
95%CL represent the lower and upper fiducial limits.

95%CLb (ppm)
319.82 – 894.64
61.61 – 197.77
45.06 – 267.61

20.00050.1546
0.0525P-value
0.98150.69420.8189

Table 4 Repellent Percentage of cowpea bruchids C. maculatus with repellent toxicity treated weed essential
oils at 1, 3, 6 and 12 h.
Mean (±SE) Repellent Percentage (%)
Treatments
Conc.
(ppm)
1h
3h
6h
12 h
Distilled water
0.0 ± 0.00 g
0.0 ± 0.00 j
0.0 ± 0.00 i
0.0 ± 0.00 i
Acetone2.0 ± 0.45 f
4.0 ± 0.55 i
6.0 ± 0.55 h
6.0 ± 0.55 h
Bitter bush100
10.0 ± 0.71 e
14.0 ± 0.55 h
34.0 ± 0.55 g
68.0 ± 0.84 f(E. odoratum)200
18.0 ± 0.45 c
20.0 ± 0.00g
38.0 ± 0.84 f
74.0 ± 1.14 e
300
20.0 ± 0.71 b
30.0 ± 0.71 e
40.0 ± 1.00 e
94.0 ± 0.89 b
Finger grass
100
14.0 ± 0.55 d
22.0 ± 0.45 f
40.0 ± 1.22 e
64.0 ± 1.14 g(L. aromatic)
200
20.0 ± 0.71 b
40.0 ± 1.00 b
62.0 ± 1.30 b
86.0 ± 0.89 c
300
24.0 ± 0.89 a
48.0 ± 0.45 a
66.0 ± 1.14 a
94.0 ± 0.89 b
Vietnamese mint
100
18.0 ± 0.84 c
32.0 ± 1.10 d
46.0 ± 0.89 d
78.0 ± 0.84 d(P. odoratum)200
24.0 ± 1.14 a
38.8 ± 1.82 c
60.0 ± 2.00 c
94.0 ± 0.55 b
300
24.0 ± 1.14 a
40.0 ± 1.58 b
62.0 ± 0.84 b
98.0 ± 0.45 a
Means within the same column followed by the same letter are not significantly different (DMRT: P>0.05).

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Table 5 Effect of three weed essential oils in various concentrations on mungbean seeds viability.
Treatments

Mean (±SE) Germination Percentage (%)
5 days7 daysDistilled water
92.0 ± 1.00 d
92.0 ± 1.00 d
Acetone87.6 ± 3.56 k
87.6 ± 3.56 h
Bitter bush100
88.4 ± 0.84 i
89.2 ± 1.52 g(E. odoratum)200
89.2 ± 0.55 h
89.2 ± 0.55 g
300
91.2 ± 2.30 e
91.2 ± 2.30 e
Finger grass
100
90.4 ± 3.77 f
90.4 ± 3.77 f(L. aromatic)
200
95.2 ± 1.52 a
95.2 ± 1.52 a
300
94.2 ± 1.67 b
94.8 ± 1.67 b
Vietnamese mint
100
92.0 ± 1.58 c
93.2 ± 2.07 c(P. odoratum)200
88.0 ± 2.55 j
89.2 ± 2.70 g
300
89.6 ± 1.92 g
93.2 ± 1.14 c
Means within the same column followed by the same letter are not significantly different (DMRT: P>0.05).
Conc.
(ppm)

products volatilize quickly in the environment anddo not persist for longer duration unlike synthetic
pesticides, there could be a need for re-application to
obtain the desired results. The efficacy of plantbased pesticides could also be enhanced when
dissolved or mixed with a slow release fixative
material or carrier such as starch or liquid paraffin,
and incorporated as an integral part of integrated
pest management system especially at a small-scale
farmer level. The essential oil from these plants
could become a viable alternative to conventional
chemical control strategies. However, further studies
need to be conducted in order to evaluate the safetyof these oils before practical use in stored-productinsect control.

DISCUSSIONS
Different spice of plant products in the form
essential oils (EOs, powders, pellets, extracts or
distillates could be harnessed as potential toxicants,
deterrents, antifeedants, repellents and fumigants for
exclusion of stored-product pests from grain, andhave been used, but low toxicity has obtained muchattention for alternative control measures of storedproduct pest. Diverse essential oils (EOs) and otherplant products have been used. Three weed essential
oils investigated showed sufficient protection of
cowpea grains from damage by cowpea bruchids, C.
maculatus and these oils acted oviposition deterrent
by adult female. Also, we observed not to affect seedgermination which confirms non-adverse effect on
grain chemistry. This demonstrated the ability of theoils to act as suffocation materials with thepossibility of preventing respiration [13]. However,plant natural products that constitute effective safer
alternatives to synthetic insecticides without
producing adverse effects on the ecosystem havebeen tested in the management of stored-productpests [14]-[16]. In this study, we evaluated theinsecticidal and repellent properties of Bitter bush(E. odoratum L.), Finger grass (L. aromatica(Lamk.) Merr.), Vietnamese mint (P. odoratum) andEO against C. maculatus, under laboratory
conditions.

ACKNOWLEDGEMENTS
This research was supported by Research
Facilitation and Dissemination of Department ofMahasarakham University, Thailand, which isgreatly appreciated.
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CONCLUSIONS
Based on the results obtained in the current
study, it may be conclude that Bitter bush (E.
odoratum L.), Finger grass (L. aromatica (Lamk.)
Merr.), and Vietnamese mint (P. odoratum) weed
plant materials have a broad spectrum of activity
against cowpea bruchids C. maculatus, and theessential oils could have potential as bioinsecticides
in stored product protection. However, since plant556

GEOMATE - Mie, Japan, Nov. 21-24, 2017[4] Khalequzzaman
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[12] Finney DJ, Probit analysis. 3rd ed. Cambridge:
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[15] Ukeh DA, Birkett MA, Pickett JA, Bowman
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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

GEOPHYSICAL TOMOGRAPHY BASED ON SPARSE ESTIMATION
Takayuki Shuku1 and Hongyang Cheng2
Graduate School of Environmental and Life Science, Okayama University, Japan
2
Multi Scale Mechanics (MSM), ET, MESA+, University of Twente, The Netherlands.
1

ABSTRACTIn this paper, a new geophysical tomography method based on sparse modeling, where the least absoluteshrinkage and selection operator (LASSO) is used as an inverse analysis method, is proposed, and the proposed
method is applied to numerical examples of cross-hole seismic tomography designed to reconstruct an image ofthe ground between two boreholes. Compared with the conventional ridge regression-based method, theproposed method could reconstruct the image with higher accuracy, particularly when the observed data is not
sufficient. Therefore, this method is a promising methodology for reconstructing the layered structures ofgrounds and geotechnical structures in geotechnical practice.
Keywords: Sparse estimation, Geotomography, Inverse problems
Fig. 1 Cross-hole tomography.
Many methodologies such as smoothing filters
and regularization methods have been proposed for
managing ill-posed inverse problems. In particular,
sparse modeling has received much attention
recently in image and vision processing as well as inmachine learning (e.g., [4], [5]). According to thegeneral principle of sparsity, a phenomenon should
be represented with as few variables as possible.
Similarly, sparse modeling can be useful ingeotechnical engineering. This paper proposes asparse modeling-based geophysical tomographymethod and reports its effectiveness by applying it toa numerical example of cross-hole seismic
tomography: an image of the spatial distribution of
the geotechnical parameters of the ground isreconstructed using the proposed method, and theresults are compared with those of a current method.
The rest of this paper is structured as follows. In
Chapter 2, the theoretical basics of geophysicaltomography and inverse analysis are presented.
Chapter 3 outlines the least absolute shrinkage andselection operator (LASSO) and a sparse modelingreconstruction algorithm called the Alternating
Direction Methods of Multiplier (ADMM). The
numerical application of the proposed method andits results are reported in sections “Numerical
Experiments” and “Results.” The section“Conclusion” summarizes the method and key
findings of the study.

INTRODUCTION
Cross-borehole seismic tomography, also called
geophysical tomography, is a method of inferring
the properties of the ground between two parallel
boreholes (Fig. 1). In geotechnical practice, aproblem in geophysical tomography is that only alimited number of transmitters and receivers can beused because of the limitations in the construction
budget. In addition, the ray paths in geophysicaltomography are restricted, which is in contrast to Xray CT scanning wherein transmitters and receivers
can be placed arbitrarily around the targets. Theselimitations affect the quality of image reconstruction,
which in geophysical tomography tends to be an illposed problem from the perspective of inverse
analysis. Ill-posed problems in geophysicaltomography were particularly studied by Honjo andKashiwagi [1][2], who applied a smoothing filter forimage reconstruction and numerically simulated the
optimal design of the smoothing filters on the basisof the Akaike Information Criterion [3].
Borehole

Borehole

FORMULATION OF GEOTOMOGRAPHY

Transmitter

Reconstruction techniques can be classified into
two broad categories: transform methods and series
expansion methods. In the transform method, themotion of the target object is described as a

Reciever558

GEOMATE - Mie, Japan, Nov. 21-24, 2017

relationship between the dimension of theobservation vector m, rank of the observation matrixr, and dimension of the unknown parameter vector n.
When r = m = n, the problems are called evendetermined problems and can be easily solved.
However, most inverse problems in practice are not
even-determined.
When r = m > n, the problems are said to be
overdetermined. The entire vector x cannot
completely fit all the observation data; therefore, thesquared error ED is minimized as follows:

continuous function with a continuous set ofprojections, whereas in the series expansion methods,
the object of interest is comprised of elements, andseismic waves are propagated through the elements
to obtain a projection of the element values. The
reconstruction of images through the series
expansion methods can be theoretically discussed interms of linear algebra.
This paper focuses on the series expansion
methods as they are the most widely used in
geotechnicalapplications[1][2].
In
this
methodology, the reconstruction area is discretized
into cells (Fig. 2). The wave observations at thereceivers can be discretely approximated asy  Ax  ε ,minimize E D ( x)x

E D ( x) (1)

where y is an m-dimensional observation vector, x is
an n-dimensional parameter vector, A is an m-by-nobservation matrix, and  is an m-dimensional error(noise) vector. These are defined asy  { y1 , y2 ,  , ym }T(2)x  {x1 , x2 ,  , xn }T(3)

 a11 a12aa22
A   21 am1 am 2(4) a1n  a2 n    amn ε  {1 ,  2 ,  ,  m }T ,1 2 1
2
ε 2  y  Ax 2 .
22xˆ  ( A T A) 1 A T y .

~ED (x)  ED (x)  EW (x) ,T

Fig. 2ith

EW (x) 

1
1|| x ||22  x T x .
2
2

(10)

This quadratic regularizer is called ridge regression.
Substituting Eq. (10) into Eq. (9) yields thefollowing error function:

R

(11)

By minimizing Eq. (11) for x, the ridge estimator is
obtained as~x  ( A T A  I ) 1 A T y ,

ray

(12)

where I is the identity matrix.
Because the ray paths in geophysical tomographycell 1

Cross-hole tomography.

(9)

where  is the regularization coefficient that controls
the relative importance of the data-dependent error
ED(x) and the regularization term EW(x). One of thesimplest forms of the regularization term is the sumof-squares of the parameter vector x

1
1 2
~
2
E D ( x)  y  Ax 2   x 2 .
2
2

aij

(8)

Eq. (8) is called the least squares estimator and is
widely used for solving overdetermined problems.
When r = m < n, the vector x cannot be obtained
uniquely as it has many possible solutions. To solve
the problem, regularization terms are often added
into Eq. (7).

where the superscript "T" indicates the transpose of
the vectors and matrices. In this paper, the error i isassumed an independently and identically distributed
random variable that follows normal distribution
with mean 0 and standard deviation .
Determining the unknown parameter vector x,that is, reconstruction of the image of the groundbetween the two boreholes, can be classified into
one of three types of problems depending on thecell 2(7)

Eq. (7) can be analytically solved to obtain theestimated vector x̂ as(5)cell n(6)559

GEOMATE - Mie, Japan, Nov. 21-24, 2017

are restricted, as explained in the introduction, thereconstruction problems in geophysical tomography
tend to be underdetermined problems: the number ofobservations is much less than the number of
unknown parameters. Solving the underdetermined
problems is thus a central topic in geotechnicalpractice.

The LASSO problem is a convex minimization
problem, that is, a quadratic program with a convex
constraint. For simplicity, the following problem isused to explain the computational procedure for the
LASSO solution (e.g., [4]).

1minimize ( y  x) 2   x x
2SPARSE ESTIMATIONThe standard approach to this one-dimensional
minimization problem is to set the gradient withrespect to x to zero. However, one of the central
difficulties in solving Eq. (15) is the presence of anon-smooth L1 norm, |x|. In other words, theabsolute value function |x| does not have a derivative
at x = 0. Nevertheless, this problem can be solved byapplying to x a soft-thresholding operator (e.g., [7]),which is defined as

The regularization term EW(x) can have many
possible forms. Tibshirani [6] proposed the LASSO
for solving underdetermined problems, wherein if 
is sufficiently large, some parameters in x tend tozero, resulting in a sparse model in which thecorresponding basis functions play no role.
In the LASSO, the regularization term in Eq. (9)takes the following form:

EW (x)   x 1   x ,

(13)

 y

S ( y)   0 ywhere | . | indicates the absolute value. By
substituting Eq. (13) into Eq. (9), the objectivefunction of the LASSO is obtained as

1~
2
E D (x)  y  Ax 2   x 1 .
2

x̂

x2

x1

Fig. 3( y  )(   y   ) ,(16)( y   )where S is a soft-thresholding function (Fig. 4).
This operator translates x toward zero by a certain
amount and sets it to zero if |x| < . When  = 0, thesolution of Eq. (15) becomes the solution for theordinary least squares problem.
The general approach for solving the LASSO
problem can be summarized as follows:(14)

The LASSO yields sparse solutions, which
implies that many of the estimates are exactly zero
because of the geometry of its regularization term.
Fig. 3 illustrates the estimation picture for ridge
regression and LASSO. The residual sum of thesquares, which is obtained from the first term on theright side in Eq. (14), has elliptical contours centeredat the least-squares estimates. Both regressions findthe first point where the elliptical contours meet theregularization region. Unlike a circle, a diamond has
corners; if the solutions lie at the corners, then oneof the x parameters equals zero. In Fig. 3, x1
becomes zero because of the diamond-shaped
regularization term.

x2

(15)

Step 1: Minimize the first term in the objectivefunction
Step 2: Apply the soft-thresholding operator to x
Step 3: Repeat steps 1 and 2
OPTIMIZATION METHOD
Of the many reconstruction algorithms proposed
for solving convex problems, ADMM [8], which
blends the decomposability of the dual ascentmethod with the superior convergence properties ofx̂S ( y)x1Estimation picture for ridge (left) andLASSO (right) regression [5].

Fig. 4560

Soft-thresholding function.

yGEOMATE - Mie, Japan, Nov. 21-24, 2017

the method of multipliers, is used in this paper tosolve the LASSO problem. This algorithm solves
problems in the formz k 1  S1/  (x k 1  μ k )μminimize f (x)  g (z) subject to Ax  Bz  c ,(17)where f (x) and g(z) are assumed to be convex, A
and B are known matrices of constraints, and c is aconstraint vector. To solve this problem, a vector of the Lagrange multipliers associated with theconstraint is introduced to form the augmented
Lagrangian2
f (x)  g (z )  μ T ( Ax  Bz  c)  Ax  Bz  c 2
2

k 1

k 1

 arg min L (x , z, μ )(20)

μ k 1  μ k  ( Ax k 1  Bz k 1  c)

(21)

z

(25)

k

The accurate reconstruction of soil profiles using
existing geophysical tomography methods isdifficult. Consider the true distribution of thegeotechnical parameters depicted in Fig. 5. We
attempted to reconstruct this image using the
proposed method and ridge regression method,which is an existing geophysical tomographymethod, for comparison.
Each transmitter individually generates seismic
wave, and the receivers observe travel time of the
wave between two boreholes. Geophysicaltomography estimates elastic modulus of cells basedon the observed travel time. Therefore, in thisnumerical experiment, y and x in Eq. 1 mean thetravel time and elastic modulus respectively.
We considered two configurations of transmittersand receivers: Case 1 and Case 2 depicted in Fig. 6.
Case 1 has 21 receivers and transmitters each, whichyield 21 × 21 = 441 ray paths in total, and Case 2, (18)

(19)

k

(24)

 (x  z ) ,k

NUMERICAL EXPERIMENTS

where  > 0 is called the penalty parameter. The
ADMM is based on minimizing the augmented
Lagrangian (Eq. (18)) successively over x and z andthen applying a dual-variable update to . Thus, itconsists of iterations of an x-minimization step (Eq.
19), a z-minimization step (Eq. 20), and a dualvariable update (Eq. 21).

x k 1  arg min L (x, z k , μ k )

μ

k 1

where S is a soft-thresholding operator. A T A  I
is always invertible as  > 0. The algorithm involves
a ridge regression update for x, a soft-thresholding
step for z, and a simple linear update for .
Accordingly, the ADMM can be interpreted as amethod for solving the LASSO problem throughiterative ridge regression.

x,zL (x, z, μ ) k 1Similar to the method of multipliers, the dualvariable update uses a step size equal to theaugmented Lagrangian parameter .
The ADMM framework has several advantages.
First, convex problems with non-differentiable
constraints can be easily solved by the separation ofparameters x and z. Second, the ADMM can break
up a large problem into smaller problems. For
datasets with a large number of observations, thedata can be broken into blocks, and each block canbe optimized.
Next, the ADMM procedure is illustrated byapplying it to the LASSO.
The Lagrangian form of the LASSO can be
expressed in an equivalent form as

15

10

Y (m)

8
10

6
4

5

2
00

Fig. 5

2

4
6
X (m)

8

10

0

Schematic view of regularization.

 1
minimize y  Ax 2   z 1  such that x  z  0
x ,z
2
N



.

(22)

When applied to this problem, the ADMM updates
take the form

x

k 1



T

 A A  I

 A y  (z  μ ) 
1

T

k

k

Case 1
Fig. 6(23)
561

Configurations
receivers.

Case 2oftransmittersandGEOMATE - Mie, Japan, Nov. 21-24, 2017has 21 receivers and 11 transmitters, which yield 11
× 21 = 231 ray paths.
The synthetic observation vector y used forinverse analysis is generated as follows:

101) Assuming that all ray paths are straight,
compute the observation matrix A (Eq. (1)).

6

Y (m)

8

00





2

4
6
X (m)

8

10

(a) Ridge

10

0

15

8

Y (m)

(26)

10

6
4

where B represents the matrix for the spatial
derivative of parameters in cells called the total
variation [9].
The accuracy of the reconstructed image isevaluated in terms of the root mean square error(RMSE)RMSE 

5

2

The LASSO is effective when the vector x has
many zeroes, that is, when the solution is sparse.
The LASSO cannot function well in this numericalexample because most of the parameter vector x are
non-zero. Therefore, the L1 regularization term in
Eq. (14) is modified as follows:2
1 N estxi  xitrue ,N i 110

42) Compute Ax; the parameter vector x is given in
Fig. 5. We did not add observation noise to y forsimplicity.

1~
2
ED (x)  y  Ax 2   Bx 1 ,
2

15

5

2
00

2

4
6
X (m)

8

10

0

(b) Lasso
Fig. 7 Reconstructed images for Case 1.

(27)

10

15

8

Y (m)

where xitrue is the true value of the geotechnicalparameter for the ith cell shown in Fig. 5 and xiest is
the reconstructed (estimated) value for the ith cell as
obtained through geophysical tomography.
RESULTS

10

6
4

5

2

Fig. 7 presents the reconstructed image, that is,
the estimated parameter distribution, obtained
through ridge regression and LASSO for Case 1.
Both the methods can capture the layered structuresof the ground and an accurate image could bereconstructed. However, the LASSO almost
perfectly reconstructed the values of thegeotechnical parameters of the cells.
Fig. 8 depicts the image reconstructed using theridge and LASSO-based methods for Case 2. The
results prove that reconstruction using the LASSObased method is more accurate than that using ridge
regression, particularly at the left edge where theobserved data are not sufficient. he reconstructed
image almost completely coincides with the true
image shown in Fig. 5. Table 1 summarizes the
RMSE for each reconstructed image. The RMSE of
the LASSO-reconstructed images are considerably
lower than that of the ridge-reconstructed images.
Remarkably, the RMSE of the LASSO for Case 1 is

00

2

4
6
X (m)

8

10

0

(a) Ridge
10

15

Y (m)

8
10

6
4

5

2
00

2

4
6
X (m)

8

10

(b) LASSO
Fig. 8 Reconstructed images for Case 2562

0GEOMATE - Mie, Japan, Nov. 21-24, 2017

Numbers 15K18759.

Table 1 RMSE in ridge and lasso estimations

REFERENCES

RMSE
Case 1Case 2Ridge

0.04137

0.09600

Lasso

0.00258

0.02246[1] Honjo, Y. (1987): Geophysical tomography:
Estimation error and optimum choice of cellsize, In Proc. 5th Int. Conf. on the Applicationof Statistics and Probability in Soil and
Structural Engineering, Vancouver, 91-100.
[2] Honjo, Y. and Kashiwagi, N. (1991): On the
optimum design of a smoothing filter for
geophysical tomography, Soils Found., 31(1),131-144.
[3] Akaike, H. (1973): Information theory and an
extension of the maximum likelihood principle,
In Proc. 2nd Int. Symp. on Information Theory,
Petrov, B. N., and Caski, F. (eds.), Akadimiai
Kiado, Budapest: 267-281.
[4] Mairal, J., Bach, F. and Ponce, J. (2014): Sparsemodeling for image and vision processing,Found. Trends Comput. Graph. Vis., 8(2-3),
199.
[5] Hastie, T., Tibshirani, R. and Wainwright, M.
(2015): Statistical Learning with Sparsity, CRC
Press, p. 351.
[6] Tibshirani, R. (1996): Regression shrinkage andselection via the lasso, J. Royal. Statist. Soc. B.,
58(1), 267-288.
[7] Figueiredo, M.A.T. and Nowak, R.D. (2003):
An EM algorithm for wavelet-based image
restoration, IEEE Trans. Image Process., 12,
906-916.
[8] Boyd, S., Parikh, N., Chu, E., Peleato, B. andEckstein, J. (2011): Distributed optimizationand statistical learning via alternating direction
method of multipliers, Found. Trends Machine
Learning, 3(1), 122.
[9] Rudin, L. I., Osher, S., and Fatemi, E. (1992):
Nonlinear total variation based noise removal
algorithms, Physica D, 60, 259-268.

much less than that of the ridge regression method.
This implies that LASSO can reconstruct images
with high accuracy when the number of observed
data is not sufficient.
CONCLUSION
This study proposed a geophysical tomographymethod based on LASSO, which is a method forsparse modeling. The proposed method was applied
to the numerical examples of cross-hole seismic
tomography designed to estimate soil profiles. To
validate the effectiveness of the proposed method,
its results were compared with those of ridge
regression.
When the number of observed data is large
enough, both ridge regression and the proposed
LASSO-based method could accurately reconstruct
the image of the ground between the boreholes.
When the number of observed data is small, ridge
regression yields poorly reconstructed images. In
contrast, the proposed method yielded accurate
images regardless of the insufficient number ofobserved data. Thus, the proposed method is morerobust than ridge regression and is expected to be auseful tool in geotechnical practice.
ACKNOWLEDGEMENTS
This work was supported by JSPS KAKENHI
Grant-in-Aid for Young Scientists (B) Grant

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LESSONS AND ACHIEVEMENTS FROM THE MERSEY FOREST
BY NETWORKING PARTNERSHIP FOR TWENTY YEARS
1Tomoko Miyagawa1, Clare Olver2, Noriko Otsuka3, Takefumi Kurose4 and Hirokazu Abe5
Faculty of Systems Engineering, Wakayama University, Japan; 2 The Mersey Forest, the UK;
3,5
Cyber Media Centre, Osaka University, Japan;
4
Faculty of Human-Environment Studies, Kyushu University, Japan
ABSTRACTIn the UK, community forest projects have created an increase of new accessible open green spaces in postindustrial areas. However, there is a scarcity of sustainable funding for long-term management. Therefore,
partnership is recognised to be a key mechanism to maximise the benefits and to share the risks with a range oforganisation to maintain the quality of green spaces. This study is to clarify the achievements and the roles of theMersey Forest over the last twenty years in developing partnership approaches in the Northwest of England. The
study methods are based on literature reviews regarding on published literature on environmental regeneration andthe data provided from MF, and interviews with representatives of the Mersey Forest. The first 10 years from 1994
to 2004 focused on planting trees for creating new and extending woodland. After that opportunities for large
scale new planting decreased and there was a need for managing the newly created open green spaces. Therefore,
it has entered in the management phase and the role of the Mersey Forest is shifting to strengthen partnershipworking by providing advice to landowners. It also became clear that community forest approaches have beenachieved together with landowners and partners through partnership working led by the Mersey Forest for overtwenty years. Thus, the Mersey Forest has evolved from a governmental inspired organisation to a community
empowered organisation.
Keywords: Green Infrastructure; Environmental Regeneration; Community Forests; Post Industrial Landscapes
Community forest activities are to create andmanage new and existing open green spaces,
including derelict under-used and neglected land, in
England by forming a network of these spaces into apart of Green Infrastructure (GI), through working in
partnership with organisations [3]. In recent years,
institutional support for public participation is
becoming important in urban regeneration areas for
public benefits [4]. Regeneration of post-industrial
areas in the UK has been undertaken since 1980,
however, with not much provision for covering costs
for long-term management [1] which is necessary for
maintaining open green spaces.
In addition,
partnership approach is recognised to be a way
forward to balance risks and costs with partnerorganisations.
Environmental regeneration and post-industrial
landscapes with a focus on working in partnership canbe seen in the research for conserving and reusing
industrial heritage [3], activities of community forests
in England since 1994 [4], a way forward to form apartnership as a method of environmental
regeneration in a river basin environment [5], and theapproach used by environmental regeneration
organisations such as Groundwork in the UK an
intermediate sector organisation [6]. However, there
has been a change for community forests over time
particularly for financial support from the central

INTRODUCTION
A Creation of Post-industrial Landscapes
Through Environmental Regeneration in the UK
In recent years, newly created accessible green
spaces have increased by community forest activities
in post-industrial areas, particularly in the North ofEngland, and it is necessary to determine thecumulative effects of changes [1], [2]. Throughenvironmental regeneration, activities are becomingarea wide and networking surrounding areas to createa landscape with local characters [3]. Newly createdopen green spaces can be a platform for biodiversity
and culture which have possibilities to empower thecommunity in the local area for active participationand to create new socio-economy and culture, thus,
activities of environmental regeneration is reflecting
the community development [2]. Post-industrial
landscapes have blue (water) and green (open spaces)
systems. However, in some cases, it is difficult toaccess due to a lack of infrastructure for people to use
and not known by the local community. Therefore, it
may be important to manage these newly createdopen green spaces through a process of creating postindustrial landscapes with a long-term vision, as wellas to work in partnership with the community in thelocal area.
564

GEOMATE - Mie, Japan, Nov. 21-24, 2017

government in recent years, and there is a scarcity anda need for a further research on recent trends andpartnership working as a methodology.

land ownership, while promoting community forest
activities to create and manage open green spaces on
publicly and privately owned land by partnerorganisations, such as, local authorities, companies
and individuals. MF encourages people to become
more actively involved with their local trees andwoodlands through support to form ‘Friends’ groups,
assistance to obtain funding and by providing trees
for community planting [10].

Aims of the study and study methods
This study aims to clarify the achievements andthe role of the Mersey Forest (MF) by undertaking
environmental regeneration to create post-industrial
landscapes over the last twenty years. The Mersey
Forest Partnership was set up in 1991 withorganisations in Merseyside and North Cheshire in
the Northwest of England - an area containing muchbrownfield land. The study methods are based onliterature reviews regarding on published literature on
environmental regeneration and the data provided
from MF, and interviews with representatives of MF,
Clare Olver and Paul Nolan OBE.

Partnership Working with the Community
MF was established in 1991 as one of 12
community forests in England by the Countryside
Commission. However, in recent years, community
forest organisations have had to become morefinancially independent, therefore, activities are
becoming more focused on the local area [11]. Thus,
networking of a partnership and working with thecommunity in the local area is becoming increasingly
important.
Fig.2 illustrates a framework showing the levelsof community engagement in creating the MF. There
are seven stages from Stage 7: ‘Not informed but
using MF’, to Stage 1: ‘Community ownership’. This
allows a continuum of levels of participation,
therefore, ranges of people can participate and tosupport participation in various ways.

HISTORY AND ROLES OF MF
MF and Partner Organisations
MF covers 1370 square kilometers with 1.7
million inhabitants with a vision to create and manage
open green spaces in the long term for environmental
regeneration and community development in the
Northwest of England (Fig.1)[7]. Since 1991, MF has
been a leading partnership in Merseyside and North
Cheshire enabling community forest activities
focusing on urban, suburban and post-industrial areas
to provide open green spaces nearby the community[7].
Partner organisations include the local
authorities within the MF area, the governmentorganisations within the UK Government’s
Department for Environment, Food, and Rural
Affairs (DEFRA), such as Forestry Commission (FC),
Natural England (NE), and Environment Agency(EA), landowners, private companies, and thecommunity in the local area [8]. MF do not hold any

Fig.2 A creating process of MF with thecommunity [7]ACHIVEMENTS OF MF IN PARTNERSHIP
Newly Created Open Green Spaces by MF
Community forest activities led by the MF
partnership has created three times of the number of
newly planted trees since 1991 to reach 9 million trees
in Merseyside and North Cheshire in comparison to
the number of whole of England on average at thesame time [7]. According to an awareness survey on
environmental regeneration with local residents in2010 (1121 respondents, response rate 65%) said thatthe environment had improved by MF activities, andtwo thirds of people had visited newly created open
green spaces [7]. It also became clear that newly
created open green spaces have been recognised andFig.1 A map of MF[9] with some amendments
565

GEOMATE - Mie, Japan, Nov. 21-24, 2017

visited by local community. In terms of the
Woodland Access Standard, suggested by the
Woodland Trust (WT), a charity organisation forconserving woodland in the UK, in 2012 23 percentof the population in MF lived within ‘500m of anaccessible woodland of at least 2ha’, and 77 percentof the population lived ‘within 4km of one of at least
20ha’. This means that access to woodland is higher
in MF than in England as a whole [7]. Therefore, itis evident that community forest activities havepromoted to create and manage open green spaces
since 1990 particularly in the Northwest of England
where MF is located.

incomes by applying for external funding withpartners and by securing resources from the partners
to maximise benefits, and to impact on future policymaking [7].
ANALYSIS AND COMPARISON OF TWENTYYEARS OF ACTIVITIES BY MF
Area of New Woodland Planting
This section tries to examine the selected datafrom MF for the past twenty years of activities. Fig.
3 shows area of new woodland planting in MF area
since 1990/1991 to 2014/2015. It became clear thatfrom 1993/1994 to 2003/2004 was a time ofsignificant tree planting increasing new woodland
cover from 500ha to 2,500ha. New woodland
planting took place at most from 2000/2001 to
2002/2003. Since 2005, the increasing trend has
ended and became stable at around 3,000ha. This
trend has been seen right across England and thereasons for this are complex, including changes to
new woodland grant aid; EU Single Farm Payments
acting as a disincentive for woodland planting;increasing numbers of non-farmer landowners;changes to eligibility for new tree planting grants andan increase in commodity prices.

Plans for The Long term and The Short term
MF reviews The Mersey Forest Plan every ten
years based on the agreement between partnerorganisations, and minor amendments are updated on
the MF website [7]. In the plan-making stage, it iscompiled with partner organisations throughconsultation, therefore, it is a ‘locally developed plan’
which is approved by the local government [7].
The Mersey Forest Plan is a long term andstrategic guide to the work of The Mersey Forest teamand partners. This is accompanied by an annually
updated Delivery Plan which covers how the longterm vision of The Mersey Forest Plan will bedelivered and considers the resources available at thetime [7]. To achieve policies of The Mersey Forest
Plan can bring many benefits, and moreover, it is also
important to be in accordance with legal framework
and policy contexts [7]. For example, at the national
level, The Mersey Forest Plan is in accordance with
the Government’s Forestry and Woodlands Policy
Statement, 2013 and the National Planning Policy
Framework, 2012 [7]. In addition, policies of theMersey Forest Plan can be the ‘material consideration[12]’ on planning permission through planningsystem to support development control and local areaplanning [7].
Partnership of Local Authorities for MF

Fig.3 Areas of new woodland planting in MF(cumulative) [13]To undertake projects beyond local authority
boundaries, such as community forests activities,
cooperation of neighbouring local authorities is astatutory requirement stated by Localism Act, 2011[7]. Local authorities in MF area have a Partnership
Agreement among them to exchange knowledge andinformation, and to share opportunities for solutions[7]. Among local authorities, Cheshire West andChester Council (formerly Cheshire County Council)
is the lead authority providing employment, finance,
and treasury for the MF team [7]. In addition, local
authorities in the MF Partnership commit to investing
resources: ‘core funding’. MF is taking a role as aleader to work in partnership with variousorganisations, to invest in resources to generate

Fig.4 A number of consultations to MF(1989/1990-2014/2015) [14]566GEOMATE - Mie, Japan, Nov. 21-24, 2017

Tidy. It has become a benchmark national standard
for parks and green spaces.

Numbers of Consultation to MF
Fig. 4 shows numbers of requests for support bylandowners to the MF team between 1990/1991 and2014/2015. From 1989/1990 to 1999/2000 were in
average of 29 cases per year, while 2000/2001 to
2014/2015 rose three times to 108 requests in average
per year which may be a result of better monitoring
and recording.

Types of landowners
In the case of local authorities and others, where
landowners have many parcels of land and woodland,these have only been recorded once: ‘Unique
Landowners’. These landowners are frequently
supported with the management and evaluation ofprojects at many occasions by the MF team for many
separate parcels of land. There are also some sites
outside of MF geographical area but participating
towards the MF vision. This suggests an extending
and growing network of community forests activities
in the Northwest of England. Cooperation fromlandowners is necessary for MF covering a regional
area including privately owned land, to work in
partnership, and to create a network of GI of open
green spaces.

Landuses and Landowners Consulted MF
Types of land use
Fig.5 shows types of land use of landowners whorequested support by MF between 2001/2002 to
2014/2015. Agricultural land has the highest rate to
be a half of all land types during 2001/2002 to
2003/2004. At that time, funding for new planting by
WGS was available and many consultations had takenplace on transforming farmland to woodland. Since
2007/2008, requests for support to manage existingwoodland have increased to 28 percent on average.
Likewise requests from schools have also increased
since 2008/2009 to be at 28 percent on average.
Enquiries for support to improve and manage
public open green spaces remain at 5 percent on
average (Fig. 5) [14]. However, there are requests forsupport from many other types of open green spaces,such as, privately owned estate/church, golfcourse/sports field, and derelict land after reclamation
for greening, it comes up to 13 percent in total. 29
site owners consulted MF during 2001/2002 to
2014/2015 nearly 40 percent out of 71 sites within
local authorities in MF area have been selected by
Green Flag Award which recognises excellent
management and high quality green spaces [15]. The
Award is recognised by The UK Government’s
Department for Communities and Local Government,
and managed by environmental charity, Keep Britain

Unique landowners
Fig. 6 shows types of unique landowners from2001/2002 to 2014/2015 by land use types who
contacted MF. Of those 90 percent of the schools
were state schools (including nursery, primary school,
junior school and high schools), while the remaining
10 percent were privately owned. 70 percent of thewoodland owners who contacted MF were privatecompanies, including individual landowners, while
10 percent were owned by national and local
government.
The remaining woodland owners
included charitable organisations such as National
Trust and WT, and parish councils. From enquiries
around agricultural land, 90 percent were primarily
owned by private landowners. Of the 75 percent of
support requested for public open green spaces thesewere owned mainly by national and local
government; the remaining 25 percent owned bycharity organisations. From support requested forestate/church managed land, 50 percent of enquiriescame from church or parish councils, while 20
percent were from private companies andorganisations including individual landowners; theremainder from other land owners including national
and local government, and charity organisations.
Enquiries from managers of golf course/sports fields,
80 percent were private companies and organisations,
including individual landowners, the remainder fromnational and local government, and charity
organisations. 90 percent of support requested forderelict land came for land owned by privatecompanies and organisations including individual
landowners, with 10 percent from national and local
government.
In terms of land owners who contacted MF,
schools and public open green spaces are mainly
owned and managed by the public organisations,

80%
60%
40%

SchoolAgricultural land
Estate/Church
Derelict land

2014/20152013/20142012/20132011/20122010/20112009/20102008/20092007/2008

2006/2007

2005/2006

2004/2005

2003/2004

2002/2003

0%

2001/2002

20%
2000/2001

Percentage (%)

100%

Year

WoodlandPublic open green space
Golf course/Sports field
OthersFig.5 Land use for sites where support requested toMF (2001/2002-2014/2015) [14]567GEOMATE - Mie, Japan, Nov. 21-24, 2017

while other landuse types are mostly owned by theprivate landowners. This suggests that MF has
consulted ranges of partners to provide supports
requested.

funding is coming from FC with the largest share,
while 12 percent of funding is core funding from thelocal authority, and 11 percent of funding is coveredfrom the EU (Figs. 8 and 9). Funding from thenational government and government organisations
in total shares a half, while 40 percent of funding is
coming from DEFRA and affiliated organisations
including EA and NE. About the funding from FC in
2011/2012 and 2013/2014, EA and NE in 2012/2013
has a higher rate (Fig.9), and total funding to exceed
three hundred thousand pounds in 2012/2013 (Fig. 7).
This is due to special projects to increase funding,such as a river improvement project of EA and abrownfield regeneration project by FC.
Between 2008/2009 and 2011/2012 theNorthwest Development Agency (NWDA) funded
the creation of new community woodlands on derelict
land as part of its urban regeneration policy.
However, NWDA was abolished in 2012 and fundingfor urban regeneration has since decreased. Since
2012, through the Sustainable Transport Fund, theDepartment for Transport has provided funding for
improvements to promote cycling and walking which
has enabled the delivery of the MF street tree planting

80%
60%
40%
20%
0%

OthersTypes of landuses
Church/Parish council
Charity organisation
Private company/organisation
National/Local government

Fig.6 Types of unique landowners by landuse types(2001/2002-2014/2015) [14]Sources of funding for MF
Core funding from local authorities

EU, 11%

LandfillCommunities Fund,
6%

DEFRA, 6%

Other governmentorganisations, 7%

Fig.8 Funding sources (Unit: Percentage (%);
2008/2009-2014/2015)[16]OthersConsulting fee

60%

Landfill tax

40%

Other governmentorganisations
EA, NE

20%

Forestry Commission

0%
2014/20152013/20142012/2013

Funding from other organisations

2011/2012

DEFRA
2010/2011

Fig.7 Funding sources (2008/2009-2014/2015)[16]Lottery fund2008/2009

Other funding

Percentage (%)

2014/20152013/20142012/20132010/20112009/20102011/2012Year

Forestry
Commission,
28%

EA+NE, 6%

80%Core fundingCore funding, 12%

Heritage Lottery
Fund, 4%100%

2008/2009

Amount of income(a thousand pounds)

Core funding and additional funding secured
from other sources between 2008/2009 and2014/2015 is shown in Fig. 7. This shows 12 percent
is core funding (resources from the local authority
partners) while nearly 90 percent is funded by EU, thenational government, government, charitable andprivate organisations. By applying for externalfunding with partners the total budget increased to
exceed a hundred thousand pounds from 2011/2012
to 2014/2015.
3,500
3,000
2,500
2,000
1,500
1,000
500
0

Others, 19%

Consulting fees, 1%

2009/2010

Percentage (%)

100%

EU
Core funding

Year

Funding sources in percentage in total between
2008/2009 and 2014/2015 is shown in Fig. 8, andyearly based details is shown in Fig. 9. 28 percent of

Fig.9 Funding sources in percentage per year
(2008/2009-2014/2015)[16]568GEOMATE - Mie, Japan, Nov. 21-24, 2017

programme: Green Streets.
The prospects of EU funding are uncertain
owing to the Brexit procedure and the need to pay
attention to future trends. Other funding from nongovernmental organisations includes Landfill
Communities Fund [17] by Landfill Tax Regulations,1996 for community and environment, and Heritage
Lottery Fund through profits of the National Lottery
in the UK for conserving environment, ecosystem,and heritage to be around 10 percent in total.

REFERENCES[1] Davies C, “Old culture and damaged landscapes:
The new cultural landscapes of post-industrialsites in Britain”, in New cultural landscapes, Roeand Taylor, Ed., Abingdon: Routledge, 2014,
pp.41-58.
[2] Roe M, “Exploring future cultural landscapes, inNew cultural landscapes”, Roe and Taylor, Ed.,
Abingdon: Routledge, 2014, pp.241-269.
[3] Miyagawa T, Olver C, Otsuka N, Kurose T, and
Abe H, “The landuse changes and formation ofpartnerships through the environmental
regeneration in Cheshire, the UK”, J. of theJapanese Institute of Landscape Architecture,
Vol.79(5), 2016, pp.555-558 (in Japanese).
[4] Lawrence A, Anglezarke B, Frost B, Nolan P,
and Owen R, “What does community forestry
mean in a devolved Great Britain?”, International
Forestry Review, Vol. 11(2), 2009, pp.281-297.
[5] Mitsuhashi N, Tsutsui Y, and Kamata M, “On
implementation for regional environmental
regeneration through the partnership with public,
private and voluntary sector: A case study ofMersey Basin in the U.K.”, AIJ J. of technology
and design, No.20, 2004, pp.251-254 (inJapanese).
[6] Mitsuhashi N, and Koyama Y, “On the methodof community development with Groundwork in
the United Kingdom”, AIJ J. of technology anddesign, No.14, 2001, pp.259-264 (in Japanese).
[7] The Mersey Forest Office, “More from trees, The
Mersey Forest Plan”, 2014, Available at <http://
www.merseyforest.org.uk/about/plan/>, undated,[Accessed 2017.3.13.].
[8] The Mersey Forest, “Who creates the forest?”,<http://www.merseyforest.org.uk/about-themersey-forest/who-creates-the-forest/>, undated,[Accessed 2017.3.13.].
[9] The Mersey Forest, a provided material, undated.
[10] The Mersey Forest, “Funding and resources forcommunities”, <http://www.merseyForest.org.
uk/support-we-offer/funding-and-resources-forcommunities/>，undated, [Accessed 2017.3.13.].
[11] England’s Community Forest, “About England’s
Community Forests”, <http://www.community
forest.org.uk/aboutenglandsforests.htm>,
undated, [Accessed 2017.3.13.].
[12] Hart T, “The management of development”,
in Town and Country Planning in the UK
Fifteenth Edition, Cullingworth, Nadin, Hart,
Davoudi, Pendlebury, Vigar, Webb, andTownshend, Ed., Abingdon: Routledge, 2015,
pp.155 -160.
[13] The Mersey Forest, provided materials, undated,“Master Statistics”.

CONCLUSION
The data since 1991, when MF was established,
has clearly highlighted the role of the MF partnershipof leading a network of local governments,
government organisations, landowners, privatecompanies and the community in deliveringlandscape changes. It also became clear the progressof community forestry in the Northwest of the UK.
It can be divided into two phases: the creation
phase, from 1994 to 2004, when there was large scale
new woodland planting, and after that whenopportunities for new planting have decreased. There
then became a need to manage the newly created open
green spaces and woodlands delivering the MF vision‘to get more from trees’ [7]. Thus, it has entered in
the management phase and the role of MF has shiftedto strengthen partnership working to provide advice
and supports to landowners and partner organisations.
The above tendency is also evident from thefunding particularly since 2008/2009, nearly 90
percent is funded by the EU, the national government,
government and private organisations while 12
percent is funded from resources by the local
authority partners. Therefore, MF is applying for arange of external funding with partners and to secureresources from the partners for various activities toinvest in resources previously provided by thenational government partners.
It also became clear that community forest
approaches have been achieved together withlandowners and partners through partnership working
led by MF for over twenty years. Thus, MF has
evolved from a governmental inspired organisation to
a community empowered organisation.
Future challenges to work in partnership locallyfor the needs from the community, to continue thequality of management of open green spaces and toutilise its resources, and to create a further network ofthese open green spaces into the enhancement offorming GI in the area.
ACKNOWLEDGEMENTS
The authors would like to express our gratitude
for the financial support provided by the Japan
Society for the Promotion of Science (no. 16H04474).

569

GEOMATE - Mie, Japan, Nov. 21-24, 2017[14] The Mersey Forest, provided materials, undated,“Cumulative landowner support from 2001
onwards”.
[15] Keep Britain Tidy, <http://www.keepbritaintidy.
org/greenflagawards2015/2335>,
undated,[Accessed 2017.3.13].
[16] The Mersey Forest, provided materials, undated,“Finance totals”.
[17] ENTRUST, <http://www.entrust.org.uk/landfillcommunity-fund>, undated,[Accessed
2017.3.13] .

570

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

IMPACT OF INCREASE IN SIKA DEER (CERVUS NIPPON) ON
INFILTRATION RATE AND SOIL EROSION ON FORESTEDHILLSLOPE
Taijiro Fukuyama1, Shinya Hiramatsu1, Keisuke Kase1, Masato Kikuchi1, Shusaku Shiiba2, Hideto Ohmori2,
Masaaki Hanaoka3
1
Faculty of Agriculture, Shinshu University, Japan; 2 Tenryu River Upper Reaches River Office, Chubu
Regional Development Bureau, MLIT, Japan; 3Civil Engineering and Eco-Technology Consultants Co.,
Ltd., Japan
ABSTRACTTo assess the impact of increase in Sika deer (Cervus Nippon) on infiltration rate on forested hillslope, we
conducted a sprinkling experiment at Japanese Alps area, where is recognized as high density deer area. We
conducted sprinkling experiment totally 22 times at three experimental plots as follows: 1) plot with animal trail,2) without animal trail and 3) disturbed by treading. Based on the rainfall intensity and overland flow, infiltration
rate was obtained and compared among experimental plots. We compared the gradients of the linear regression
between rainfall intensity and the final infiltration rate for three plots. As a result, Final infiltration rates of 3)
disturbed plot and 1) plot with animal trail were respectively 6 % and 13 % less than that of 2) plot. Secondly, toassess the Sika deer impact on soil erosion, we monitored soil erosion from late autumn till early winter. We set
the 16 sediment collection troughs along the contour on October 10, 2016 and observed rainfall, air and surface
soil temperature, and counted the number of deer using sensor cameras. Soil loss increased with increasing thenumber of deer and with increasing freeze-thaw cycle. At the sprinkling experiment, the maximum value of soil
loss per unit width was 6.5 g/m. Soil erosion monitoring showed average soil loss per unit width as 665 g/m.
Therefore, soil erosion due to the freeze-thaw cycle and deer-disturbance seemed dominant than that induced byraindrop impact and/or overland flow.
Keywords: Sika deer (Cervus Nippon), animal trail, disturbed by treading, sprinkling experiment, soil erosion
increase in sedimentation rate in dams, or increase insuspended sediment concentration. Therefore, it isimportant to assess the impact of Sika increase on thesediment delivery at the hillslope scale and thewatershed scale.

INTRODUCTION
Recently, damage by wildlives to agriculture andforestry has been a serious problem especially inmountainous area in Japan. The total damaged area offorest became 90 km2 in 2013. In Nagano prefecture,
central Japan, damage to agricultural crops and forest,
reducing undergrowth in forests, mortality of the trees
due to rapid increase in Sika deer were reported. At
Mt. Senjougatake, located in the Akaishi Mountains,
structural changes in alpine plant communities causedby grazing has been reported [6].
The impact of increase in Sika deer is not limitedon the plants. Figure 1 shows that the direct andindirect impact of Sika deer increase on the forested
hillslope and the watershed. Decline of the understory
vegetation that covers the forest floor accelerate thesoil erosion due to the raindrop impact. Exposed soil
surface amplify the variation of the earth temperatureand increase the cycle of freezing and thawing, whichlead to aggregate destruction at the soil surface.
These mechanical destruction of aggregate can occur
due to the treading by animals. Therefore, recent Sika
increase may influence sediment production andtransport by fluvial processes. Increase in unstablesediment on the riverbed, off-site impact such as

Grazing

Treading

Decline of theunderstory
vegetation

disturbance of
surface soil
aggregates

Change in theraindrop impact

At hillslope scale
At the watershed scale

Change in the
frost heaving

Change in theinfiltration rate

Acceleration of
sediment production

Sediment transport tothe channel

Increase in sedimentation
rate in Dam

Increase in suspended
sediment

Fig.1 Scenario for the impact of Sika increase on the571

GEOMATE - Mie, Japan, Nov. 21-24, 2017sediment delivery at the hillslope scale and thewatershed scale.

and Japanese red pine (Pinus densiflora). In thiswatershed, Sika deer activity has been reported using
sensor cameras in 2015 by Tenryu River Upper
Reaches River Office.
The watershed is located in the east side ofMedian Tectonic Line (MTL). Along the MTL, thereis the Sambagawa metamorphic belt, which containcrystalline schist and serpentinite, and the Chichibu
belt, which is consisted with sedimentary rock of theaccretionary wedge in the Jurassic period.

To assess the impact of the Sika treading on
infiltration and soil erosion at forested hillslope, we
conducted a sprinkling experiment at Japanese Alpsarea, where is recognized as high density deer area.
Secondly, to assess the Sika deer impact on soil
erosion, we monitored soil erosion from late autumn
till early winter using 16 sediment collection troughs
along the contour.

SPRINKLING EXPERIMENTTo assess the impact of the Sika deer treading on
infiltration rate and surface soil erosion at forested
hillslope, we conducted a sprinkling experiment at
three experimental plots with different conditions asfollows: 1) plot with animal trail, 2) without animal
trail and 3) disturbed by treading, as shown in Fig. 3.
The plot with animal trail 1) shows poor understory
vegetation compared to the 2) plot without animal
trail. The disturbed plot 3) is the location with thepoor understory vegetation and with disturbed surface
soil because of frequent use by Sika deer.

Location of thestudy site〇: Location of sprinklingexperiment and soil
erosion monitoring

Fig.3 Sprinkling experiment at the plot 1) with animal
trail. a: Water tank with level gauge, b: Experimental
plot, c: Tipping-bucket raingauge, d: WindshieldFig.2 Location of the study site

We conducted sprinkling experiment totally 22
times: 6 cases of experiment in plot 1, 8 cases in plot
2 and 8 cases in plot 3. The intensity and duration ofsimulated rainfall were 20 to 110 mm h-1 and 180
minutes, respectively. The size of the experimental
plots is 0.5 m width and 0.5 m length. To supply water,water tank with level gauge was set upslope of the

SITE DESCRIPTION
The study site is located in the watershed of
Yamamuro river, which is the upper reach of Tenryu
river, at an elevation of about 1,270 m (Fig.2).
Dominant tree species are Larch (Larix kaempferi)572

GEOMATE - Mie, Japan, Nov. 21-24, 2017plots. In experiment, we measured the sprinklingintensity (water supply per unit time) and surface
runoff. Surface runoff was measured with automatedtipping-bucket raingauge. Then we calculated theinfiltration rate and compared among plots.

SOIL EROSION MEASUREMENT
To assess the Sika deer impact on soil erosion, wemonitored soil erosion from late autumn till early
winter. As shown in figure 5, we set the 16 sedimentcollection troughs along the contour considering the
spatial variability of soil properties on forested
hillslope on October 10, 2016. The sedimentcollection troughs No.1, 3, 6, 14 and 16 set bottom ofanimal trails. Rain gutter of 10 cm-width and 50cm
length was used as sediment collection troughs. We
collected sediment totally 22 times (2 to 10 days
interval). Collected sediment was oven dried at 80 °C
and weighed.
Nearby sediment collection troughs, we observed
rainfall (throughfall) using tipping bucket raingauge
and datalogger (HOBO Pendant, CO-UA-003-64,
Onset corp.) since September 28, 2016. Air andsurface soil temperature were observed using
thermometer (Thermorecorder, TR-71nw, T and D
corp.) and counted the number of deer using 4 motion
sensor cameras (Trophycam HD 119736C, Bushnell
Outdoor Products).

EFFECT OF SIKA DEER TREADING ON
SURFACE INFILTRATION RATE
We compared the gradients of the linear
regression between rainfall intensity of sprinklingexperiment and the final infiltration rate: infiltration
rate at the end of 30 minutes, for three plots. As aresult, gradients of the linear regression were 0.85 at2) plot without animal trail, 0.80 at 3) disturbed bytreading and 0.74 at 1) plot with animal trail,
respectively. Final infiltration rates of 3) disturbed
plot and 1) plot with animal trail were respectively
6 % and 13 % less than that of the 2) undisturbed plot
as shown in Figure 4.
1001) plot with animal trail

Final infiltration rate (mm h-1)902) without animal trail

803) disturbed by treading

70
60
50
40
30
20
10
0
0

20

40
60
80
Rainfall intensity (mm h-1)

100

120

Fig.4 Rainfall intensity of sprinkling experiment andthe final infiltration rate, measured at threeexperimental plots with different conditions oftreading

Fig.5 Static image of Sika deer using a motion sensor
camera on December 7, 2016.
White arrows in picture indicate sediment collection
troughs

There were no remarkable difference ininfiltration rate between 2) plot without animal trail
and 3) plot disturbed by treading. This result indicatesthat the change in infiltration rate, due to surface soil
disturbance by Sika deer, is not clear. In contrast,
infiltration rate observed in 1) plot with animal trail
was less than that of 2) plot without animal trail.
Therefore, repeated treading and formation of animal
trail may induce soil surface sealing and following
decrease in permeability.
Soil compaction, the process by which the soil
grains are rearranged to decrease void space, due totreading by grazing animals is one of the factors
responsible for the degradation of the physical qualityof soils, such as water infiltration [1]. In our study,
lower infiltration rate was observed on steep hillslope
in contrast with the relatively plain pastureland.

Total sediment yield of all 16 sediment collection
trough during monitoring period (October 10, 2016 toJanuary 13, 2017) was 4,787 grams. As shown in
Figure 6, soil erosion concentrated in the second halfof monitoring period. 88.2 % of total sediment yield
was observed during November 11 to the end of
period. Especially 56.5 % of total sediment yieldconcentrated in 10 days since December 8. Total soil
loss of each collection trough ranged from 73 to 704
grams. Although the greatest soil loss was observed
at No. 14, located at the end of animal trail, locationof greater soil loss was not necessarily corresponding
the location of animal trail.

573

GEOMATE - Mie, Japan, Nov. 21-24, 201715

Rainfall intensity (mm/h)

Soil loss (grams)

2,000
1,500

10

1,000

5

500
0
10/13

10/23

11/2

11/12

11/22

12/2

12/12

12/22

1/1

0

1/11

Daily rainfall (mm)Fig.6 Total soil loss of all 16 sediment collection
trough during monitoring period (December 10, 2016
to January 13, 2017)
Table 1 Presence of animal trail above the trough,number of deer and total soil loss during monitoring
period
1

2

3

4

5

6

7

8

Animal trail

A

N/A

A

N/A

N/A

A

N/A

N/A

Number of deer

42

137

466

38

46

499

276

95

Soil loss (g)

435

449

328

73

97

295

83

668

Trough No.

9

10

11

12

13

14

15

16

Animal trail

N/A

N/A

N/A

N/A

N/A

A

N/A

A

Number of deer

66

10

8

42

40

101

21

7

Soil loss (g)

228

292

88

257

358

704

247

184

10/27

11/16

12/6

12/26

1/15

10/7

10/27

11/16

12/6

12/26

1/15

50
40
30
20
10
0
20

Temperature (°C)

Trough No.

10/7
60

15

Air

10

Ground

5
0
-5
-10
10/7

10/27

11/16

12/6

12/26

1/15

Fig. 7 Daily rainfall, rainfall intensity and air/groundtemperature during monitoring period (December 10,
2016 to January 13, 2017)
Relationship between the maximum rainfall
intensity and the soil loss shows that the soil loss does
not always increase with the rainfall intensity (Fig.8).
Soil loss was observed even in case of no rainfall.
Similarly there was no clear correlation between total
rainfall and soil loss (Fig.9). These results infer thatrainfall-induced soil erosion is not dominant process.

Note: "Animal trail" indicates whether the collection
trough located at the end of animal trail. N/A in table
is an abbreviation for "not applicable". “Number ofdeer” indicates that the number of Sika deer thatpassed within 1 meter upslope the sediment collection
trough.

1800

RAINFALL AND TEMPERATURE

1500
Soil loss (g)Daily rainfall, rainfall intensity and air/groundtemperature during monitoring period were shown infigure 7. Total rainfall during monitoring period was
341 mm (December 10, 2016 to January 13, 2017).
Maximum daily rainfall occurred on November 27(52.5 mm). Maximum rainfall intensity occurred on
December 22 (13.5 mm/h). Snowfall started on
November 24, then accumulated after January 8, 2017.
Air temperature ranged from -10.2 °C to 15.7 °C. On
November 10, minimum air temperature fell below
freezing. During the non-snow-cover period after
latter half of November, frost heave on surface soil
was frequently observed. Although the groundtemperature essentially synchronized to the airtemperature, it showed smaller amplitude comparedto the air, especially during snow-cover period.

1200
900
600
300
0
0
5
10
15
Maximum rainfall intensity (mm/h)

Fig.8 Maximum rainfall intensity and the soil loss
Maximum rainfall intensity means the highest hourly
rainfall during each monitoring period of soil loss.

574

GEOMATE - Mie, Japan, Nov. 21-24, 20171800

EFFECT OF FREEZE AND THAWING ON
SOIL LOSS

Soil loss (g)

1500
1200

Air and ground temperature (Fig.7) and soil loss
(Fig.6) show that the increase in soil loss when thetemperature falls at the latter half period. Furthermore,at the timing of minimum temperature was below
freezing, remarkable increase in soil loss wasobserved. The frequency of freeze-thaw cycles (thenumber of times that the ground temperature go
below freezing then above freezing) showed positive
correlation to the soil loss of each monitoring period(Fig.11). This result infers that freeze and thawing
concern the movement of soil particles.

900
600
300
0
0

20
40
Total rainfall (mm)60

Fig.9 Total rainfall and the soil loss
ESTIMATE OF SIKA DEER IMPACT OF
TREADING

1800
1500
Soil loss (g)Appearance of Sika deer concentrate the latter
half of monitoring period as shown in figure 10.
Especially, 60.7 % of total was observed during 10days after December 8, 2016. The number of Sika
deer that passed within 1 meter upslope the 16
sediment collection troughs was 1,851 during
monitoring period (October 10, 2016 to January 13,2017). This is a cumulative number of individuals in
an image, not actual population of Sika deer. The
number of Sika deer ranged 7 to 499 among sedimenttrap. There were most Sika deer at the end of animal
trail (sediment collection trough No.6 and No.3).

900
600
300
0
0

5
10
Frequency of freeze-thaw cycles

Fig.11 The frequency of freeze-thaw cycles and soil
loss

800

Number of Sika deer

1200

600

Periglacial soil movements due to frost heaving
or freeze–thaw cycle has been measured [4, 5].
Moreover it has been reported that physicalweathering [7] or soil creep can occur due to thefreeze and thawing under sparse understory, even incase of mountainous hillslope below the forest limit.
Study of soil movement [8] on forested slopes with38 to 43 degrees, elevation of 1,350 meters in Akaishi
Mountains, central Japan, showed that the freezethawing in winter induces active soil movements as
the dray ravel and soil creep.
In the present study, soil loss observed at similar
condition to the previous study [7, 8]. We conducted
the monitoring at elevation of 1,270 meters, undercondition of sparse understory vegetation, at relative
steep hillslope ranges from 25 to 41 degrees. During
the non-snow-cover period, frost heave on surface
soil was frequently observed. Therefore, freezethawing and frost heave would partly contribute to the
disturbance and movement of surface soil.

400
200
0
10/13

10/23

11/2

11/12

11/22

12/2

12/12

12/22

1/1

1/11

Fig.10 The number of Sika deer that passed within 1
meter upslope the 16 sediment collection troughs
during monitoring period (October 10, 2016 toJanuary 13, 2017)
Previous studies on the effect of Sika deer on soil
erosion reported that strong negative correlation
expressed by an exponential function between the soil
loss per unit rainfall and the percentage of the forest
floor coverage [2], based on the 5-years monitoringof soil loss in Fagus trees with degraded understory
vegetation during warm period. At the same site, it isreported that the surface runoff and rainfall intensity
strongly affect the amount of soil loss [3].
Although during warm period (April to
November), under the condition of degradedunderstory vegetation due to grazing and treading,erosion process induced by the surface runoff andrainfall is dominant as previous studies shown, ourstudy conducted in cooling season showed different
trend.
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ACKNOWLEDGEMENTS

EFFECT OF TREADING OF DEER ON SOIL
LOSSThis work was funded by River Planning Division,
Water and Disaster Management Bureau, Ministry ofLand, Infrastructure, Transport and Tourism, Japan.

Number of deer and the soil loss shown in Figure
12 demonstrate that the soil loss increases withincreasing number of Sika deer. This result indicatesthat the increasing number of deer; more frequent
treading induce disturbance and movement of surface
soil. Judging from both relationship between thefrequency of freeze-thaw cycles and soil loss shownin figure 11, and relationship between number of deerand soil loss shown in figure 12, it was found that thedominant processes of soil loss are both disturbanceof surface soil induced by freeze-thawing andtreading by deer.

REFERENCES[1] Hamza MA, Anderson WK, Soil compaction in
cropping systems: A review of the nature, causes
and possible solutions. Soil & Tillage Research,
Vol. 82, 2005, pp. 121-145.
[2] Chu L, Ishikawa Y, Shiraki K, Wakahara T,
Uchiyama Y, Relationship between Forest Floor
Cover Percentage and Soil Erosion Rate on theForest Floor with an Impoverished Understory
Grazed by Deer (Cervus Nippon) at Doudaira,Tanzawa Mountains. Journal of the Japanese
Forest Society, Vol. 92, 2010, pp. 261-268.
[3] Biligetu, Ishikawa Y, Shiraki K, Wakahara T,
Hai Hu, Yoshimi Uchiyama Y. Relationshipbetween Rainfall Intensity, Rainfall Factor, andSurface Runoff and Soil Loss on the Forest Floor
with an Impoverished Understory Grazed byDeer in Doudaira, Tanzawa Mountains. Journalof the Japanese Forest Society Vol. 95, 2013 pp.
163-172.
[4] Matsuoka, N. Solifluction rates, processes andlandforms: a global review, Earth-Science
Reviews, Vol. 55, pp.107-134.
[5] Matsuoka N. Temporal and spatial variations inperiglacial soil movements on alpine crest slopes.
Earth Surface Processes and Landforms Vol.30,
2005, pp. 41–58.
[6] Tanaka T, Matsushima K, Tanaka R. Deer
Damage and Control in the Nanshin Regional
Forest Office. Water Science Vol. 58 No. 4, 2014,39-51.
[7] Tsutsumi D, Fujita M, Ito M, Teshima H, Sawada
T, Kosugi K, Mizuyama T. Fundamental study
on sediment yield due to freeze and thaw process,Field observation on bare slope in Tanakami
Mountains and its numerical simulation. Journalof the Japan Society of Erosion Control
Engineering Vol. 59, 2007, pp. 3-13.
[8] Imaizumi F, Ueji Y. Soil Movement in Artificial
Forests Located in Steep Mountain Area and its
Countermeasures Using Thinned Woods. Journalof the Japanese Forest Society Vol. 94, 2012, pp.
24-30.

1800

Soil loss (g)

1500
1200
900
600
300
0
0

200
400
Number of deer

600

Fig.12 The number of Sika deer and soil loss
CONCUSUSION
A sprinkling experiment at three experimental
plots as follows: 1) plot with animal trail, 2) without
animal trail and 3) disturbed by treading showed thatthe deer-disturbance and/or treading affect theoverland flow generation; final infiltration rate on
forested hillslope. Soil erosion observation andmonitoring of rainfall, air and surface soil
temperature and the number of deer, from late autumn
till early winter, demonstrated that combination of the
frost heaving and disturbance of surface soil by Sika
treading accelerates the soil erosion.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

TSUNAMI RISK MAPPING USING INTEGRATEDREMOTE SENSING AND GEOSPATIAL ANALYSIS
Abu Bakar Sambah12, Fusanori Miura3, Guntur1, Fuad1, and Defrian Marza Arisandi1
1
Faculty of Fisheries and Marine Science, Brawijaya University, Indonesia;
2
Marine Resources Exploration and Management Research Group, Brawijaya University, Indonesia;
3
Faculty of Engineering, Yamaguchi University, Japan

ABSTRACTTsunami risk is defined as a combination of the danger posted by tsunami hazard, the vulnerability of people
to an event (exposure), and the probability of destructive tsunami or likelihood of the tsunami occurring.
Tsunami risk is also defined as the mathematical calculation between tsunami vulnerability and tsunami hazard,
and it can be assessed using a spatial multi-criteria. The study applied the combination of element at risk toassess tsunami risk area along coastal area of East Java Indonesia off the Indian Ocean. Remote sensing
approach followed by geospatial analysis into tsunami risk assessment along with the existing perspective
evolving the role of Geographical Information System. The existing physical vulnerability parameter was
analyzed and evaluated. All parameters in both tsunami vulnerability and tsunami risk assessment were analyzed
through weighted overlay in geospatial analysis, in which the criteria’s weight was calculated through Analytical
Hierarchy Process. The results were provided as thematic maps of tsunami vulnerability and tsunami risk.
Tsunami risk map described five classes of risk from very low to very high based on the geospatial analysis. It
described that coastal area with low elevation identified as highly risk to tsunami. Coastal area with high densityof vegetation described a low level of tsunami risk. The existence of river and other water canal along coastal
area were also identified as important parameters in generating tsunami risk map. Risk map highlights the coastal
areas with a strong need for evacuation capacities, including evacuation route and evacuation building.
Keywords: Tsunami Risk, Remote Sensing, Geo-spatial Data

disaster mitigation is important. Tsunami risk
mapping is one of the approaches needed fortsunami disaster preparedness.
Tsunami risk mapping combines the results ofthe tsunami vulnerability and tsunami hazard(Fig. 1). Assessing tsunami vulnerability can provide
important information for tsunami disaster risk
management plans and mitigation. This also plays animportant role in preparing and mitigating for the
future events [5][6]. A risk to a tsunami disaster isdefined as the mathematical product between
tsunami vulnerability and tsunami hazard; it refers to
the expected loss from a given hazard to a given
element at risk [7]. A disaster is a function of therisk process. Risk results from the combination of
hazards, conditions of vulnerability and insufficient
capacity to reduce the potential negative
consequences of risk. Risk assessment combines theresults of the hazard and vulnerability assessments[8][9][10].
Moreover, disaster risk assessment is aqualitative or quantitative approach to determine thenature and extent of disaster risk by analyzing
potential hazards and evaluating existing conditionsof exposure and vulnerability that together could
harm people, property, services, livelihoods and theenvironment
on
which
they
depend.

INTRODUCTION
A tsunami is a series of waves generated in an
ocean by a disturbance such as an earthquake,landslide, volcanic eruption, or meteorite impact. An
earthquake can generate a tsunami in the overlying
water. It can be generated when the sea floor
abruptly deforms and vertically displaces theoverlying water. When tectonic earthquakes occur
beneath the sea, the water above the deformed area
is displaced from its equilibrium position. Waves areformed as the displaced water mass, which acts
under the influence of gravity, attempts to regain its
equilibrium. When large areas of the sea floor
elevate or subside, a tsunami can be created [1][2][3]South coast of Java Island as a part of Indian
Ocean is in the confluence of two major plates meeteach other, Eurasian and Indo-Australian, where themovement of tectonic plates will create anearthquake and generate tsunami. A potential
destructive tsunami in the period of 1991 to 2006,
recorded a tectonic earthquake in the Indian Ocean
and generated tsunami on the southern coast of East
Java, namely on June 3, 1994. A magnitude of 7.8
Mw hit southern coastal areas of East Java andcausing casualties of 215 people [4]. Due to thetsunami is a recurring event, create an appropriate
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

This is includes the identification of hazards, a
review of the technical characteristics of hazards(location, intensity, frequency and probability), theanalysis of exposure and vulnerability (the physical,
social, health, environmental and economic
dimensions), and the evaluation of the effectivenessof prevailing and alternative coping capacities withrespect to likely risk scenarios [8].
Traditionally risk assessment urges atdetermining the likelihood of specific losses anddamages, which includes population, economy,
supporting environment and institutional structures[5].
Satellite remote sensing approach combined withgeospatial analysis using Geographical Information
System (GIS) for disaster mitigation study provides
an important integrated contribution in conducting atsunami risk assessment. This study assesses tsunami
risk area through an integrated satellite remotesensing data and geospatial analysis in the south
coastal area of East Java. This is important fortsunami early warning and mitigation. General
concepts of the study as shown in Fig 1.

Ocean about 200 km south of Java. The earthquake,
which had a surface-wave magnitude of 7.2 and a
moment magnitude of 7.8 at 10.51°S and 112.87°E,
generated a devastating tsunami that took the livesof more than 200 East Java coastal residents; withmaximum runup value of 9.50 m was measured at
Rajekwesi area, east part of the study area [11][12].

Fig. 2

Study area.

DatasetSeismic data of the study area from 1992 to 2014
collected from The United States Geological Survey(USGS),
anddownloadedfrom
http://earthquake.usgs.gov/earthquakes/search/. wasused as a supporting parameter for tsunami
vulnerability in which further will generated seismic
map. In order to map the land cover of study area,
ALOS satellite imagery with the instrument of theAdvanced Visible and Near Infrared Radiometer
type 2 (AVNIR-2) with the spatial resolution of 10
m was analysed.
In addition to create tsunami vulnerability map,
Digital Elevation Model (DEM) from The ASTER
Global Digital Elevation Model (ASTER GDEM)
version 2 was applied to generate elevation andslope map. The Advanced Space-borne Thermal
Emission and Reflection Radiometer (ASTER)
GDEM is a joint product developed and madeavailable to the public by the Ministry of Economy,
Trade, and Industry (METI) of Japan and the UnitedStatesNational
Aeronautics
and
Space
Administration (NASA). Moreover, vector base mapof East Java Indonesia was applied to prepare vector
data of coastal morphology, coastal line, and river.

Fig. 1 General concepts of the study
METHODS
Study Area
The study was applied at the south coastal areaof East Java, focusing on the coastal area of Jember
District, Indonesia (Fig. 1). The coastal area ofJember district was known as one of importantmarine fisheries resources spot in East Java. This
area also affected by 1994 tsunami event along
coastal area of East Java. The tsunamigenic
earthquake occurred on June 3, 1994 in the Indian

GEOSPASIAL ANALYSIS FOR TSUNAMI
VULNERABILITY MAPPING
Vulnerability mapping has been generated using
the parameters elevation, slope, coastal proximity,
river proximity, coastal type, and land use. Together
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GEOMATE - Mie, Japan, Nov. 21-24, 2017with hazard or capacity, tsunami vulnerability is oneof the parameters in assessing tsunami risk. Cellbased analysis was applied in combining allparameters through GIS process. The classes ofcoastal proximity in meter (Fig. 3)was calculated
based on the measured run-up and water height inthe surveyed area during the last tsunami event incoastal area of East Java, June 3, 1994. It wascalculated using algorithm [13][14] :𝒀𝒍𝒐𝒈𝐗 𝒎𝒂𝒙 = 𝒍𝒐𝒈𝟏𝟒𝟎𝟎 + 𝟒⁄𝟑 𝒍𝒐𝒈 ( 𝟎⁄𝟏𝟎)

diverse and dissimilar inputs to create an integrated
analysis. Weighted overlay also one of the suitability
analysis based on spatial multi-criteria processing[13][17]. Vulnerability map was generating byapplying a weight value to each parameter in rasterdata
format.
The
calculation
applied[elevation*0.28]+[slope*0.19]+[coastal_proximity*0.18]+[river proximity*0.12]+[coastal
type*0.13]+[land use*0.09], as the result as shownin Fig. 4.

(1)

Xmax is the maximum reach of the tsunami over land,
and Y0 is the height of the tsunami at the coast.

Fig. 4

Fig. 3

Coastal proximity
vulnerability

map

for

The use of AHP analysis in generating weight ofparameters in which applied in weighted rasteroverlay describes five classes of vulnerability due totsunami in coastal area of study area (Fig. 4). It
describes that west part of study area, mostly in theclass of slightly high to high class of tsunami. This
area was identified as flat area with land use class ofurban area and agriculture. The associated dataset
required for the vulnerability assessment including
number of buildings, typologies of buildings,
number of floors, or age of building.
The coastal area exposed to tsunami inundation,
the buildings and infrastructure are not uniformly atrisk within the flood zone [18][19]. The probabilityof damage is related both to vulnerability and to thetsunami wave energy. Damage level to buildings
depends on building type and on inundation depth[20] or could be depend on the density of vegetation
around the coastal that assumed will reduce tsunami
impact. Assessing tsunami vulnerability in the urban
area has to considered that individual buildings willinteract differently with a tsunami depending on anumber of parameters [18][19]. Various parametersthat affect the resistance of the building interact togenerate a real class of building vulnerability[20][21].

tsunamiMoreover, land use map was generated fromsupervised classification process of ALOS/AVNIR2 image. Reflectance value of ALOS image appliedin maximum likelihood classification and generated
five classes of land use in the study area. Before
calculating parameters for tsunami vulnerability
mapping, each parameter should be re-classify basedon tsunami vulnerability classes, using criteria
described in Table 1.
Table 1

Tsunami vulnerability map

Parameter classification based on
vulnerability classes. [13][14][15][16]Raster overlay for tsunami vulnerability mapping
was done based on the weight of parameters.
Weights were calculated using Analytical Hierarchy
Process (AHP). Weighted overlay is a technique for
applying a common measurement scale of values to

SEISMIC AND RUN UP ANALYSIS
Seismic data are physical observations ormeasurements, seismic sources, seismic waves, andtheir propagating media. The purpose of processing
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

seismic data is to learn something about the Earth’s
interior. It needs to figure out some specific relations
between the intended targets and measurable
parameters in order understand certain aspects of the
Earth [22].
All initial tsunami warnings are based on rapid
detection and characterization of seismic activity.
Because of the fundamental differences in nature
between the solid earth in which an earthquake takes
place and the fluid ocean where tsunami gravity
waves propagate, the vast majority of earthquakes
occurring on a daily basis do not trigger appreciable
or even measurable tsunamis. It takes a large event(magnitude >7.0) to generate a damaging tsunami in
the near-field and a great earthquake (magnitude>8.0) to generate a tsunami in the far-field [23].
The study area was identified as a high numberof seismic point with the depth average of 1 to 5 km
and the range of magnitude 1 until >6. As the result,coastal area of East Java can be classified as a highvulnerable to tsunami. Based on historical data, it
was a magnitude of 7.8 Mw in the depth of 18 km
and latitude of -10.477º/longitude of 112.835º,
caused big tsunami and affected to the coastal areaof East Java, including in this study area (Fig. 5).

Fig. 5

epicenter and strong to violent shaking in epicenterarea.
The historical tsunami event of 1994 was used asa basic data for run up analysis. Maximum run up
was recorded at Tempurejo district (11.2 m), andminimum run up was 3.1 m in the area of Puger
district. Run up analysis described seven points ofrun up point along coastal area of Jember Regency.
Tsunami run up parameter is one of the importantparameters in determining tsunami risk due to thisparameter is the main parameter in hazard criteria.
Last survey reported by [11] described that in the
North West part of study area, Cape Pelindu, a small
fishermen village where a fishery created a sort ofbarrier to the sea water, separating houses from theopen sea. The fishery defense wall and three typicalstraw houses were destroyed. According to eyewitnesses, three big waves followed each other, thethird one being the biggest. The measured maximum
water height was 3.20 m and the maximum water
ingression was about 350 m. The next village was
Puger where no evidence of a tsunami could beobserved in the harbor. But, just a few kilometers
westward, in a place called Tambak Getem, thetsunami left visible marks on the beach: the keeperof a fishery reported that he weakly felt the shock
and about 15 minutes later three big waves flooded
the beach, the last penetrating about 300 m in land.
The measured maximum water height was 5.85 m[11].
Close to the area of Puger, it was a big river. In
general, rivers were identified in four different areas.
Rivers can play an important role in expanding theimpact of the damage during tsunami event. The
run-up of the tsunami reaches the hinterland not only
through the low elevation of the area, but also
through rivers. Rivers also act as flooding strips
transporting inundation [13][24].

Seismic data in Indian Ocean close tocoastal area of East Java from 1992 to 2004
from U.S. Geological Survey

TSUNAMI RISK MAPPING
Vulnerability refers to the potential for casualty,
destruction, damage, disruption or other form of loss
in a particular element. Risk combines this with theprobable level of loss to be expected from a
predictable magnitude of hazard (which can beconsidered as the manifestation of the agent that
produces the loss). Risk is thus the product of hazard
and vulnerability. It is an essentially hypotheticalquantity, in that it can only materialise in the form ofdisaster impacts [25][26].
Risk, vulnerability and hazard are the threefactors or elements which we are considering here inthis pseudo equation. Another definition of risk
given by Factor analysis of information risk which
may be related to disaster is 'the probable frequency
and probable magnitude of future losses. [27]The numeric value of risk can be calculated as
the product between vulnerability and hazard level.

Fig. 5 illustrated that based on the U.S.
Geological Survey data of seismic intensity aroundIndonesia, it was recorded that the range ofmagnitude was 1 to 6.3 Mw. It describes the typicaleffects of earthquakes of various magnitudes near
the epicenter. Intensity and thus ground effects
depend not only on the magnitude, but also on the
distance to the epicenter, the depth of theearthquake's focus beneath the epicenter, thelocation of the epicenter and geological conditions.
Magnitude of 1 – 6.3 was classified as micro tostrong effect or I until VII to X in Mercalli intensity.
It was categorized that the damage to a moderate
number of well-built structures in populated areas.
Earthquake-resistant structures survive with slight tomoderate damage. Poorly designed structures
receive moderate to severe damage. Felt in wider
areas; up to hundreds of miles/kilometers from the580

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Since vulnerability level ranges from 1 to 5 andhazard level ranges from 1 to 4, risk level of eachvulnerable element will be given by:
𝑹= 𝑽∙

𝑯
𝟒

High density of mangrove in coastal areas andreefs can be a barrier to reduce the effect of tsunami
wave, as well as the islands with steep-sided fringing
is only at moderate risk from tsunamis. Study about
predicting tsunami inundation area using coastal
vegetation density was carried out after the 2011
Japan tsunami and found that coastal vegetation also
important feature in reducing tsunami wave when hit
the coastal area [24]. The high density of mangrove
along coastal area has capacity to minimize thenegative impact of tsunami wave. Dense mangrove
forests growing along coastal areas can help reducethe devastating impact of tsunamis and coastal
storms by absorbing some of the waves' energy.
When the tsunami struck India's southern state ofTamil Nadu on 26 December, for example, coastal
areas in with dense mangroves (area of Pichavaramand Muthupet) suffered fewer human casualties andless damage to property compared to areas withoutmangroves [30].
Tsunamis waves may undergo extensive
refraction and create a process that may converges
their energy to particular areas on the coastal areasand increase the heights. High risk of tsunami isdepending on the water depth, the coastal
geomorphology, the direction of tsunami wave, andthe existence of rivers or other water canals. Fig. 8
described that the high class of tsunami risk was
identified in the area of Puger district. Total area oftsunami risk in the study area is described in Table 2
and Table 3.

(2)

R is risk, V is vulnerability, and H is hazard. R must
be an integer number ranging from 1 to 5, where 5
stands for the maximum risk level. Once risk levelhas been calculated it will be possible to plot it on arisk map by the process of GIS. Risk map also
generated using weighted cell-based overlay.
Weighted overlay analysis allows the user tocombine weight and rank several different types of
information and visualize it, so multiple factors canbe evaluated at once [10].
All parameters generated tsunami risk map weredisplayed in grid cells. Cells were then classified
based on its value to five classes of risk; represent
low, slightly low, medium, slightly high and highrisk. Grouping cells in this raster data followed zonal
function operation. Each cell is encoded based on
the criteria that make up a zone.
Tsunami riks map (Fig. 6) in the area of East
Java, as the result of this study, applied weighted
linear combination. This approach processed in araster GIS in which factors were combined byapplying a weight value to each followed by asummation of the results using equation of ∑ (𝑊𝑖 ∙𝑋𝑖 ), where Wi is the weight values of the parameteri, and Xi is the potential rating of the factor [28][29].

Table 2 Tsunami risk area
No.

Risk level

1
2
3
4
5

Slightly low
Low
ModerateHigh
Slightly high
Total

Cell
2,981
39,643
1,784
153
44561

Area
(m²)
298,100
3,964,300
178,400
15,3004456100

Area
(Ha)
29.81
396.4317.84
1.53
445,61

Table 3 Percentage of tsunami risk level in different
districtFig. 6

Tsunami risk map.

DISCUSSION
Tsunami risk map describes that risk level in the
study area divided into five classes. Moderate untilhigh class of tsunami risk were found in the western
part. This area mostly covered by flat elevation withrare density of coastal vegetation and high density ofurban area. In the previous tsunami event, run up of
4.85 – 5.85 m was recorded in this area.

Four district in study area was classified as highrisk of tsunami; Gumukmas (0.70 Ha), Puger (0.79
Ha), Wuluhan (0.001 Ha), and Tempurejo (0.001
Ha). Moreover, moderate tp low level was in the
district of Ambulu, Wuluhan dan Tempurejo. The
level of tsunami risk for each district was different
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

due to the topography or land cover of the area.
Puger was an area that most affected based ontsunami risk mapping. Land use in Puger was mostly
covered by urban area and the area with low
elevation, low density of vegetation, and close to big
river. This area is one of the important marine
fisheries activities in East Java province.
The use of pair-wise comparison matrix helps in
the analysis of multi criteria data where all of theparameters used in this study were calculated basedon its weight factor to create vulnerability and alsorisk map. The calculation of weight as a result ofpair-wise comparison matrix was created fromexpert judgment. Tsunami vulnerability research inAlexandria was applied all parameter in equal
weight due to the limitation of knowledge regarding
to the study area [31].
The high vulnerability areas were mostly foundin the coastal area with the sloping coast type.
Elevation and slope play an important role ingoverning the stability of a terrain. Tsunami
vulnerability research in Bali, Indonesia shows the
distribution of vulnerability is not uniform andphysically it is highly influenced by coastal
proximity, elevation, and slope [32][13]. Tsunami
risk map that described here based on the integrated
approach and to be provided to the people in the
study area in the near future due to less information
about tsunami risk in the study area.

ACKNOWLEDGEMENTS
Authors are thankful to Ministry of Research,
Technology and Higher Education Indonesia forfinancial support, METI and NASA for the Aster
GDEM version 2 products, Japan Aerospace
Exploration Agency (JAXA) for the ALOS images,
BIG Indonesia for providing the basic map of thestudy area, and U.S. Geological Survey for seismic
data. We also thank to Laboratory of Disaster
Prevention System, Yamaguchi University, Japanand Laboratory of Marine Resources Exploration,
Brawijaya University Indonesia.
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CONCLUSIONS
Tsunami risk can be assess using the application ofmulti criteria analysis followed by weighted cellbased processing in which DEM data was applied.
The result perform here can be used for theevacuation and reconstruction plan due to tsunami
disaster. Also this will be important basic
information in determining the evacuation route andevacuation building. Moreover, the final target oftsunami risk mapping is to reduce the effect oftsunami by generating a good mitigation plan.
The combination of raster weighted overlay inthe geo-spatial data analysis indicated thevulnerability and risk area due to tsunami anddescribed the possibility area that could be affectedby tsunami. The weight of each parameter was
calculated by pair-wise comparison matrix of expert
judgment, in which every parameter was weighted
not equally. By applying overlay process for tsunami
risk map and existing land use will describe whicharea need first to be evacuated when tsunami come.
The result of weighted overlay illustrated thathigh class of tsunami vulnerability and tsunami risk
mostly in the class of urban area, while forest area
was indicated in the low class. The more parametersthat are applied, the more detailed is the assessmentthat can be analysed and displayed.

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Training Course for Southern Africa, Creative
Commons Attribution-Share Alike 2.5 South
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Coastal Effects”, Natural Hazards, 1997, Vol.
15, pp.31–49.
[12] Storchak, D.A., D. Di Giacomo, I. Bondár, E.
R. Engdahl, J. Harris, W.H.K. Lee, A.
Villaseñor and P. Bormann, “Public Release of
the ISC-GEM Global Instrumental Earthquake
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[13] Guntur, Sambah AB, Miura F, Fuad, andArisandi,DM,“Assessing
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[14] Bretschneider, C.L. and Wybro, P.G, “Tsunami
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[15] Iida K., “Magnitude, energy and generation
mechanisms of tsunamis and a catalogue ofearthquakes associated with tsunamis”,
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[16] Van Zuidam RA, “Guide to Geomorphologic Aerial Photographic Interpretation and
Mapping”, International Institute for GeoInformation Science and Earth Observation,
Enschede, 1983, The Netherlands.
[17] ESRI, “Environmental Systems ResearchInstitute, Inc. Analyse Site Conditions Using
Weighted Overlay”, 2015, ESRI.
[18] Papathoma, M. And Dominey-Howes, D.,“Tsunami Vulnerability Assessment and Its
Implications for Coastal Hazard Analysis andDisaster Management Planning, Gulf ofCorinth, Greece”, Natural Hazards and Earth
System Sciences, 2003, Vol. 3 No. 6, pp733747.
[19] Papathoma, M., Dominey-Howes, D., Zong, Y.
andSmith,
D,“Assessing
TsunamiVulnerability, an Example from Herakleio,
Crete”, Nat. Hazards Earth Syst. Sci., 2003,
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[20] Tinti, S., Tonini, R., Bressan, L., Armigliato,
A., Gardi, A., and Guillande, G : Handbook on
Tsunami Hazard and Damage Scenarios,
Schema (Scenarios for Hazard-Induced
Emergen-Cies Management), Project No.
030963, Specific Targeted Research Project,Space Priority, Irc Scientific and Technical
RePort (www.schemaproject.org), 2010.

[21] Alberico I, V. Fiore D, Iavarone R, Petrosino
P, Piemontese, L, Tarallo D, Punzo Michele,
and Marsella E, “The Tsunami Vulnerability
Assessment of Urban Environments ThroughFreely Available Datasets: The Case Study Of
Napoli City (Southern Italy)”, J. MAR. SCI.
ENG. 2015, 3, pp 981-1005[22] Hua-Wei Zhou, “Introduction to seismic dataand processing”, Practical Seismic Data
Analysis, Cambridge University Press, 1991,
http://assets.cambridge.org/97805211/99100/e
xcerpt/9780521199100_excerpt.pdf[23] Committee on the Review of the Tsunami
Warning and Forecast System and Overview of
the Nation's Tsunami Preparedness; Ocean
Studies Board, “Tsunami Warning andPreparedness: an Assessment of the U.S.
TsunamiProgramandthe
Nation's
Preparedness Efforts”, Division on Earth andLife Studies; National Research Council, 2011,(https://www.nap.edu/read/12628/chapter/7#11
1)[24] Sambah AB and F. Miura, “Spatial Data
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Tsunami-Inundated
Areas”,
International
Journal of Remote Sensing, 2016, Vol.
37, Issue 9, pp. 2047-2065.
[25] AlexanderD,“NaturalHazards”,
GEOGRAPHY, 2000, Vol. I , p. 13.
[26] Wisner B, “Disaster Vulnerability: Scale,Power And Daily Life”, Geo. Jour., 1993,30(2), pp. 127-30[27] Smith, K, “Environmental Hazards- Assessing
Risk and Reducing Disaster”, Routledge, 1992,
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[28] ESRI, “Environmental Systems ResearchInstitute, Inc. Analyse Site Conditions Using
Weighted Overlay”, 2015, ESRI.
[29] Eastman JR, Jin W, Kyem PAK, Toledano J,“Raster procedures for multi-criteria/multiobjective
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[30] Upadhyay, VP, Rajiv Ranjan, JS Singh,“Human-Mangrove Conflicts: The Way Our”,
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[31] Eckert, S., Jelinek, R., Zeug, G. andKrausmann, E. (2012), “Remote sensing-based
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Alexandria, Egypt”, Applied Geography, Vol.
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[32] Eddy, “GIS in Disaster Management: a Case
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583

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

SAFETY AND EFFICIENCY FOR WEEDING WORK AND LEVEESLOPE’S FORM REQUIRED FOR MOWING MACHINES ON PADDY
FIELDS IN STEEP SLOPING AREAS IN JAPAN1

Yoshiyuki Uchikawa1, Masami Matsui2, Teruo Arase1, and Takahiro Tamura2
Academic Assembly Institute of Agriculture, Shinshu University, Japan; 2 Faculty of Agriculture,
Utsunomiya University, Japan
ABSTRACTIn Japan, land readjustment projects have standardized and expanded the design and size of rice paddy fields.
These projects have simultaneously promoted the conversion of levee slopes into stable inclines by expanding
the difference in levels between paddy fields, which has expanded levee slopes, i.e. the weeding area.
Continuous weeding work is required to prevent erosion and the collapse of steep levee slopes, and serious
accidents sometimes occur in the weeding work using brush cutters on such slopes. Brush cutters have been
popular for weeding work, but mowing machines are increasingly popular for reasons of safety and work
efficiency. However, the levee form was designed based on the assumption of using brush cutters, which
recommends small horizontal standing places both at the middle and the bottom of the slope. Therefore, it isnecessary to examine whether the form of the levee slope is suitable for mowing machines. We conducted
weeding work experiments in two types of levee slopes (with and without standing places) using two types of
weeding equipment (mowing machines and brush cutters), and the flora of the levee slopes and the working
stress on operators were investigated. Our conclusions are that (1) mowing machines are safer and more efficientthan brush cutters and (2) the conventional levee form with standing places will also be effective for mowing
machines.
Keywords: Steep Sloping Areas, Paddy Fields, Levee Slope Form, Weeding Work, Mowing Machines
mentioned “poor footing”, such as on steep slope
surfaces, as the cause of accidents. This problem has
been previously examined [1].
The cause of machine work accidents can be
categorized into three types: (1) “human factors”(e.g. erroneous operation, poor skills, and failure tocheck safety); (2) “mechanical factors” (e.g. defects
and damage to parts, and abnormal working); and(3) “environmental factors” (e.g. steep slopes anddefective safety facilities) [2]. These factors often
compound and lead to accidents. For “humanfactors”, every year the Japanese Government
carries out a campaign and training sessions forbrush cutters’ work security to prevent accidents. In
addressing “mechanical factors”, mowing machines
have recently become more popular for reasons ofsafetyandwork
efficiency.
Concerning“environmental factors”, the levee form has beenredesigned to have small horizontal standing places(small berms) both at the middle and the bottom of
the slope (Fig. 2) [3]. This design was developed
about 20 years ago and was based on the assumptionof using brush cutters.
Therefore, it is necessary to examine the form of
the levee slope that is suitable for mowing machines.
In this study, we conducted weeding work
experiments on two types of levee slopes (with andwithout small berms) using two types of weeding
equipment (mowing machines and brush cutters).
We investigated the flora of levee slopes and the

1．INTRODUCTION
Japan is mountainous and not blessed with
sufficient flat land – 47% of the country has slopesof 15° or more. Because of typhoons, paddy fields
are considered the best available form of cultivationand occupy 50% of cultivated land in Japan. All
paddy fields in steep sloping areas have levee slopes.
When these paddy fields were developed, they were
small-sized rice terraces. However, with recent rapid
development of mechanized farming technology,
land readjustment of the farmland was required.
Land readjustment projects not only standardized
and expanded plot design and size but also provided
stable inclines for levee slopes, which resulted in
expansion of the levee weeding area. Levee slopes
are occupied by various plants. Because growth ofplants in Japan is excellent due to the climate, if
weeding is not carried out in a timely manner, plant
succession will continue unchecked.
Many farmers use brush cutters to remove weedsfrom the slope of these levees (Fig. 1). Brush cutters
are useful for irregular slopes, but the incidence ofmachinery accidents is high. The injuries caused bybrush cutter accidents and are often serious and areof several types: those from contact with the edge
(e.g. cutting off a leg and cuts to a leg); those causedby breakage of the edge; injuries to eyes frombroken pieces of stone; and those occurring whileremoving entangled weeds. Many victims have584

GEOMATE - Mie, Japan, Nov. 21-24, 20171700 mm in total length, overall width 550 mm,
overall height 1100 mm (Fig. 5).

working stress on operators.

2.3 The Test Subject
The subject was a healthy man (178 cm tall, 78
kg in weight, and aged 41 years) who was an expert
with these kinds of machines.

Fig. 1

Fig. 2

Weeding work using a brush cutter

Fig. 3

Plot shape and methods of weeding work
used for the experimentFig. 4

A brush cutter

Levee slope surfaces with appropriate
weeding work areas

2．METHODS
In August 2014, we studied vegetation andconducted weeding work experiments at Obasute
District, Chikuma City, Nagano Prefecture, Japan[4]. The conditions and the methods follow.
2.1 Working Environment
The four experimental plots had levee slopes
with small berms both at the middle and the bottom(Fig. 3). The angle of inclination was 36.3°, theoverall slope was 4 m in width by 15 m in length,
and the small berms were 60 cm in width.
2.2 Working Machines
The brush cutter was a carried-type model
equipped with a steel rotary edge on the end of itsrod, with a chip saw attached (230 mm in diameter)(STIHL FS23P, engine output 0.75 kW, mass 3.9 kg,
and 1780mm in total length) (Fig. 4).
The mowing machine was a self-propelled-type(OREC SP850B, engine output 2.43 kW, mass 49 kg,
585

GEOMATE - Mie, Japan, Nov. 21-24, 2017congruent to the shape of the levee slope surface (theworking environment), work method, performanceof the machine, and the physical condition and skillof the worker. We measured a surface electrode on
both deltoid muscles of the shoulder, between thehand and the elbow on the back of the forearm, andthe muscle between the knee and the hip on the frontof the leg (femur). In addition, we measured the timerequired for work, and recorded the work using astationary video camera from two viewpoints.

Table 1 Plant species and coverage.
No.
small
berm
speciesmachineFestuca arundinacea
Trifolium repens
Equisetum arvense
Miscanthus sinensis
Erigeron annuus
Trifolium pratense
B: brush cutter

1

2

3

4

yes
B
1
1
1
3
1
1

yes
M
1
1
1
2
1
1

no
B
1
+
1
3
1
1

no
M
2
1
2
3
1
2

3．RESULTS
3.1 Vegetation Survey

M: mowing machine

Table 1 shows the representative common plant
species and coverage at the experimental plots.
We employed the following six classes of plant
coverage in each plot for the field survey, with theplant species covering: (+) < 1% of the plot area; (1)1–9%; (2) 10–24%; (3) 25–49%; (4) 50–74%; and(5) 75–100%.
3.2 Work Area and Weeding Time
Table 2 shows the results for the actual working
area and time. We calculated the work area per
working hour based on this result (Fig. 6). The
results clearly showed that the mowing machine had
more workload than a brush cutter.
Table 2 Area and work time for each plot

Fig. 5

Plot
no.

Small berm

1

Area [m2]Work time [s]

Yes

105.0

1194

2

Yes

112.5

999

3

No

79.5

794

4

No

82.5

757

A mowing machine

2.4 Methods of Weeding Work
Weeding work according to the methods isshown in Fig. 3. The direction of the arrow shows
the walking direction of the subject. The work
process is 1–6, proceeding from the levee crown, tothe upper slope and then to the lower part. Whenusing the brush cutter, the slope surface was entirely
cut by the downward weeding method; at the slopeend, the upward weeding method was used, so thatno grass fell to the plot below.
2.5 Methods of Measuring Physical Burden
The physical influence of weeding work appears

Fig. 6586

Mowing workload

GEOMATE - Mie, Japan, Nov. 21-24, 2017

than from the brush cutter, and the work efficiency
was superior. It is self-evident that the mowing
machine is safer than the brush cutter, because thecutting edges are not exposed.
Small berms of levee slopes have been provided
as a means to secure footing on the slope for safeand efficient weeding work and also as safety zones(stoppers) in the event of slips by brush cutters [1].
On the other hand, from this study, the stability offooting was not necessarily shown to be effective inthe work by the mowing machine either. From thewalking working conditions in the levee slope, it isexpected that the burden would be greater on thelower than the upper thigh. It was thought that the
judgment by such a measurement was necessary infuture. In addition, it was confirmed that the arm
length of the mowing machine suited the position of
the small berm according to the current design
standard.

3.3 Work Strain Imposed by Machines andSlopes
The work strain results are shown in Fig. 7.
During cutting, the work strain imposed by using themowing machine was 30, 56, and 50% less than thebrush cutter for the shoulders, forearms, and thighs,
respectively. Notably, the brushcutter imposed a large strain on the forearms
compared with other body parts.
The surface electrode on each muscle does notclearly show according to the availability of footing.

5． CONCLUSIONS

Fig. 7

The results led to the following conclusions: (1)mowing machines are safer and more effective thanbrush cutters, since the former had more workload,
and less physical burden than the latter; (2) the
conventional levee form with standing places did not
clearly proved to be effective for mowing machines
in the viewpoint of workload and physical stress.
However, the mowing machines were confirmed
applicable sufficiently to the conventional levee withstanding places in this study: the existence ofstanding places will enable the operators to movesafely, with low risk to slide down.

Work strain on three body parts from using
each machine during cutting

3.4 Density of Litter and Work Strain
Table 3 shows the density of cut material (litter)
about each plot and work strain on the shoulders andforearms. Regardless of the litter density, the work
strain imposed by the mowing machine was lessthan for the brush cutter.

6．REFERENCES[1] Kimura, K., Arita, H. and Uchikawa, Y. “Safety
and efficiency for weeding work and form oflevee slope on paddy field in a steep sloping
area - developing farm land consolidation
technique in regard to labor efficiency of levee
weeding (III)”, Trans JSIDRE, 170, 1994, pp.
11-18 (in Japanese with English abstract).
[2] Arita, H. and Kimura, K. Land Consolidation of
Paddy Field, Association of Agriculture &Forestry Statics, 2003, pp. 187-188.
[3] MAFF (Ministry of Agriculture, Forestry, andFisheries). Design Standard for Land
Improvement Project Plans: Planning and Field
Development (Paddy Field), 2000, pp. 309-314(in Japanese).
[4] Kimura, T., Matsui M., Honda, R., Uchikawa,Y., Tamura, T. and Aoyagi, Y. “Difference of
influence between Work strain of Mowing
Machines”, Journal of the Japanese Society ofAgricultural Machinery, 79(1), 2017, pp. 66-73(in Japanese with English abstract).

Table 3 Work area and weeding hours of each plot
plot no.
small bermmachinedensity oflitter[kg/m2]
work strain[mV･s/m2]

S
F

1
yes
B

2
yes
M

3
no
B

4
no
M

0.27
1.98
5.55

0.19
0.87
1.53

0.18
1.67
4.72

0.14
0.96
1.32

B: brush cutter

M: mowing machine

S: shoulders

F: forearms

4．DISCUSSION
The experimental results showed that thephysical burden from the mowing machine was less587

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-6-9 C3051

OPTIMAL RESTORATION STRATEGY OF A WATER PIPELINENETWORK IN SURIGAO CITY, PHILIPPINES
1

Agnes Garciano1, Lessandro Estelito Garciano2, Renan Ma. Tanhueco3 and Taze Jared Abubo4
Assistant Professor, Ateneo de Manila University, Philippines; 2,3Associate Professor, De la Salle
University, Philippines, 4undergraduate student, Ateneo de Manila University, Philippines
ABSTRACT

Quick recovery of water services immediately after an earthquake is critical. This is to minimize hazards toenvironmental sanitation and consequent health problems caused by the lack of potable water supply. It isnecessary therefore that water lifeline operators establish restoration strategies to deal with damage scenarios intheir respective concession areas specifically during extreme seismic events. The recent 6.7 magnitude
earthquake in Surigao City due to the movement of the Philippine Fault Zone: Surigao segment underscored thisneed. However due to the complexity of the network a systematic restoration sequence that minimizes
restoration time and maximizes delivery of water service should be employed. In this research, the authors
employed Horn’s algorithm to determine the optimal restoration strategy of a pipeline network in Surigao City,
Philippines. The repair sequence starts with the determination of a minimal spanning tree of the given pipeline
network. The water source is designated as the root of this tree while the nodes represent the water demand at
specific areas. The edges of the tree structure representing the pipelines connect the nodes. The assigned numericvalue or weight of an edge (link) denotes the time to repair that specific pipeline. This value is a function of thelength of the pipeline. The results show that an optimal job sequence may be carried out by considering maximal
ratios of expanding family trees within the network. A least penalty function is a consequence of the optimal
repair job sequence.
Keywords: water lifeline, seismic event, Horn’s Algorithm, minimal spanning tree, penalty function
2002), utility lifelines (Nojima 2012), redundancy
index of lifeline systems (Hoshiya and Yamamoto
2002). In 2004, Ueno et. al. developed fragility
curves of components of a gas system in Teheran
due to seismic loads. On damage estimation, Toprak
and Taksin (2007) estimated the buried pipeline
damage relationships using eight scenario
earthquakes. On the other hand, a stochastic
simulation model of damage and restoration of watersupply systems was presented and applied to Bay
Area water supply systems under hypotheticalearthquake scenarios (Porter 2016). Finally, Khin
Aye Mon et al. proposed a simplified seismic design
guidelines for buried pipelines for developing
countries. In this paper, the authors discuss analgorithm first proposed by Horn [10] and thenapply it to a water network system to determine an
optimal repair sequencing of the damaged pipeline
network.

INTRODUCTION
The Philippines is frequented by extreme windspeeds (typhoons), earthquakes, extreme floods andthunderstorms due to its geology and geographic
setting. Strong magnitude earthquakes which areconsidered as the most destructive is a constantthreat to the country’s built environment. The recent
earthquakes in the country, e.g, Bohol Earthquake
2013, Batangas Earthquake 2017 and the Surigao
Earthquake 2017, have shown that built structures
such as schools, hospitals, power supply system(Mallari and Cinco, 2017), historical structures(Luces,2013) and water lifeline systems (Crismundo,2017) can be damaged during strong ground motion
events. In this regard, quick recovery of vital lifeline
systems damaged by earthquakes is critical for postearthquake activities. However, it should beemphasized that pre-disaster programs should beestablished to assess the vulnerability of the systemand to manage the risk when a hazard strikes. The
recent earthquake in Surigao del Norte that pulledout some of the pipes from the support underscoredthe need to prepare contingency plans when groundstrains exceed the capacity of buried pipes.
There have been several studies to manage
lifelines under earthquake risk (Kameda 2000),
optimize restoration of electric power, i.e. (Chi et. al.

STUDY AREA
Surigao City is the capital city of Surigao delNorte located in the southeastern part of thePhilippines. The city proper is composed of threebarangays namely: Washington, Taft and San Juan
as shown in Figure 1. The city has a population of
about 140,540 with a land area of 245 km2.
588

GEOMATE-Mie, Japan, Nov. 21-23, 2017

The water system operator of Surigao City is the
Surigao Metropolitan Water District (SMWD). The
pipeline network of the study area is shown in
Figure 3.
Table 1. Link / Length of each pipe
Link
448
564
562
444

Fig.1 Study area
Data from the Philippine Institute ofVolcanology and Seismology (PHIVOLCS) showthat the main earthquake generator around Surigaodel Norte is the Philippine Fault Zone: Surigao
Segment (see Fig. 2).

Node i
352
354
348
348

Node j
354
355
347
349

Length (m)
1432
425
1531
581

Data of the network provided by SMWD showthat pipeline network consists of 416 nodes(junctions) and 415 links (pipes). Table 1 shows asample data links with connecting nodes i and j andtheir lengths. The weight of each edge is assumed tobe the length of the edge.
Minimum Weight Spanning Trees
Mathematically, a network consisting of nodes
and edges linking the nodes may be denoted by agraph. A graph is a pair G = (V, E) of non-empty
sets V and E where E consist of two element subsetsof V. The elements of V are the vertices or nodes of
G and those of E are the edges or links of G. A tree
is a connected graph with no closed paths called
cycles. A rooted tree is a tree with one vertex
designated as a root. A union of trees is called aforest.
A graph H = (V’, E’) is called a spanning
subgraph of G = (V, E) if V’ = V and E’ E. If eachedge e of a graph is assigned a real number w(e)called its weight, then G is called a weighted graph.
In the restoration work of a damaged network, abasic step is to find a minimum weight spanning treeof the network, that is, a tree which contains all thevertices of the network and whose edges have theleast total weight. Such minimum weight spanning
tree is obtained using Kruskal’s algorithm which
consists of intially arranging the edges in order ofincreasing weights. Edges that keep the graphconnected and total weight minimum are thenchosen. More information on Kruskal’s algorithm
may be found in [9].

Fig. 2 Active Faults / Trenches in the study area

Horn’s Algorithm
In applying Horn’s algorithm [8] to determine
the optimal repair sequence of a damaged network,
there are two assumptions: a rooted forest N is given
and the vertices follow a precedence relation P. We
say that x precedes y or xPy if there is a directed
path from x to y in N. To each vertex x in the rooted
forest, two nonnegative values V(x) and T(x) are
assigned corresponding to the value of therestoration job at vertex x and the time to complete

Fig. 3 SMWD pipe network system
589

GEOMATE-Mie, Japan, Nov. 21-23, 2017

the job at node x respectively. The best ratio at x,
denoted by r(x), is defined asV ( S )r ( x)  max: S  T [ x]
T (S )

total of 542 pipes as shown in Figure 3. Due to thehuge data, only a portion of the minimum weightspanning tree is shown in Figure 4 and Figure 5.

(1)

Table 2. Sample nodes with corresponding values ofV(x) and T(x)where T[x] denotes the set of all trees rooted in x and(2)
V ( S )   V (u )uSandT ( S )   T (u ) .
(3)
uS

Node
(x)
393
360
358
357
310
306

A maximal family tree of x, denoted by Fx is anelement of T[x] for which the best ratio is achieved.
In order to find an optimal repair sequence,
Horn defines a sequencing σ as a bijection
σ:V→{1,2,3, . . .,n} assigning to each vertex x V,
its position number σ(x) in the repair sequence. An
allowable sequencing is a sequencing σ with theproperty that if xPy, then σ(x)  σ(y). Finally a
linear delay penalty function is defined asV(x)(in lps)
0
0.89
0.081
0.89
0.79
0.214

T(x)
(proportional to length in m)
5691
313
95
234
55
10

f ( )   xX V ( x ) T ( y ) :  ( x )   ( y ) . (4)Fig.4 Minimal weight spanning tree

This function is a measure of the penalty caused bydelay in completion of the repair job at a node x.
Thus, the objective is to find an allowablesequencing σ which gives the least linear delay
penalty.

This spanning is rooted at node 376 because this is
the water supply source.
`

The methodology consists of three components:
1. Given a network, find a minimal weight spanningtree.
2. For each node x in the network, calculate the best
ratio r(x) and the maximal family tree Fx.
3. Generate the optimal repair sequence of the
network based on the best ratios obtained andcalculate the linear delay penalty function.
DATA AND RESULTS
In this study, data on the pipeline network of
Surigao City was used to construct a repair sequence
scenario in the event of massive earthquake where
all pipelines are assumed damaged. The network
consists of 416 nodes (junctions) and 542 links(pipes). The nodes represent the water demand in a
specific area and the links represent the supply
pipes. Each node x has a value V(x) corresponding
to the base demand in liters per second. Furthermore
we define T(x) to be the time (proportional to thelength of the pipe in meters) to supply water to node
x. A table of sample data is given in Table 2.
Using Kruskal’s algorithm, a minimal
spanning tree for the entire network is obtained withroot at junction 376. The spanning tree consists of
416 nodes and 415 links, removing 127 links from a

Figure 5. A portion of the minimum weightspanning tree (rooted at node 376)
Applying Horn’s algorithm to the rooted tree
obtained above yields an optimal repair sequence forin the network. The sequencing of repairs of thefirst 40 nodes of the network is shown in Table 3.
The table indicates that node 393 must be the first to
be repaired, followed by node 360, and so on. The
value of the least penalty function is f() =7773252.522.
590

GEOMATE-Mie, Japan, Nov. 21-23, 2017

Table 3. First 40 restoration jobs in an optimal
sequencing
order (x)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

node x
393
360
358
357
356
354
352
348
347
126
127
269
268
129
122
123
124
108
107
105

order (x)
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

node x
117
118
114
110
119
115
111
109
104
103
102
106
100
101
94
86
87
91
79
68

Fig.7: Sequence of restoring the network portion of
Barangay Canlanipa

Figure 6 below shows the portion of the water
pipeline network in the areas of Barangay Canlanipa
with node identification numbers. In Figure 7, thesame water pipeline network is shown but with thecorresponding values of (x) indicating the numberof node x in the cue of the repair work that must be
executed.

Fig. 8 Restoration Curve

Restoration curve

CONCLUSION

Figure 8 shows the restoration process of the water
pipeline of SMWD. This restoration curve is a nondecreasing function (Nojima and Kameda, 1992) andshows the repair on a node-to-node basis until theentire network is full operation.

A plan for restoring a pipeline network in a
post-earthquake scenario takes into account the best
ratio r(x) at each node x of the network. This value
is the maximum ratio of the demand of water supply
associated to the node over the time it takes to repair
the pipe leading to the node and is taken over all
family trees rooted in node x. In Surigao City, aminimum weight spanning tree is first obtained fromthe network to ensure that all nodes will be suppliedwith water using pipes with minimum total length.
At each node a best ratio is calculated measuring
how urgent the repair of the link to a node is over
the time to repair the link. Finally, the optimal
sequence of restoring the network is accomplishedby starting at the root node and choosing the nodewith largest best ratio at each step. For future work,
it is interesting to calibrate the restoration strategy
with actual damage during strong seismic events.
The methodology used study can also be replicatedto other tree-like systems, e.g. water, electric power,
in any area.

Fig.6 Minimal weight spanning tree of Barangay
Canlanipa

591

GEOMATE-Mie, Japan, Nov. 21-23, 2017

components for the gas distribution system inGreater Tehran, Iran. Proc. 13th WCEE,
Vancouver, B.C. Canada, Paper No. 193[9] Porter, K. (2016). Damage and Restoration of
Water Supply Systems in an Earthquake
Sequence. ESM 13-01, Structural Engineeringand Structural Mechanics Program, Department
of Civil Environmental and ArchitecturalEngineering, University of Colorado Boulder.
[10] Toprak, S and Taskin F. (2007). Estimation ofEarthquake Damage to Buried Pipelines Causedby Ground Shaking. Natural Hazards, Vol. 40,
Issue No. 1, pp. 1 – 24.
[11] Khin Aye Mon, Koike, T., Nishikawa, G.,
Garciano, L. E. and Kiyono, J., "A Simplified
Design Method of Water Lifeline in Developing
Countries" In. Proc. of the 7th China-Japan-US
Trilateral Symposium on Lifeline Earthquake
Engineering, Shanghai, China, June 1-4, 2016.
[12] Horn, W. A. (1972). “Single-machine job
sequencing with treelike precedence orderingand linear delay penalties," SIAM, Journal ofApplied Mathematics, 23(2), 189 - 202.
[13] Bondy, J.A and Murty, U.S.R. (2008). Graduate
Texts in Mathematics: Graph Theory. Springer.
[14] Nojima N. and Kameda H. (1992). Optimal
strategy by use of tree structure for postearthquake restoration of lifeline network system.
Proc. 10th World Conference on Earthquake
Engineering, Balkema, Rotterdam, pp. 5541 5546.
[15] Abubo, T. (2017): Job sequencing with tree-likeprecedence ordering and linear delay penalties.
Undergraduate thesis. Ateneo de Manila
University.

ACKNOWLEDGEMENTS
The authors would like to acknowledge theassistance of Engr. Ensomo of the Metro Surigao
Water District (MWSD).
REFERENCES[1] Luces, K. (2013). From treasure to rubble:
Heritage churches before and after the Bohol
quake. GMA News Online.
[2] Crismundo, M. (2017). Panic grips Surigao;
Strong aftershocks, water shortage keep quakeaffected residents on edge. Manila Bulletin[3] Mallari D. and Cinco, M. (2017). 5.6 Magnitude
quake causes power outages in Southern Luzon.
Phil. Daily Inquirer.
[4] Kameda, H. (2000). Engineering Management.
of Lifeline Systems under Earthquake Risk.
Proc. 12th World Conference on Earthquake
Engineering, pp. 2827 – 2843.
[5] Chi, J. M., Huang, R., and Yang, C. C. (2002).
“Practicalstrategies
forpost-earthquake
restoration of electric power systems," Proc. 10th
World Conference on Earthquake Engineering,pp. 159 – 164.
[6] Nojima N. (2012). Restoration Processes of
Utility Lifelines in the Great East Japan
Earthquake Disaster, 2011. Proc. 15th World
Conference on Earthquake Engineering, Lisbon,
Portugal.
[7] Hoshiya, M. and Yamamoto, K. (2002).
Redundancy Index of Lifeline Systems. Journalof Engineering Mechanics, Vol. 128, No. 9, Sept.
1.
[8] Ueno, J., Takada, S., Ogawa, Y., Matsumoto, M.,
Fujita, S., Hassani, N. and Ardakani F. S. (2004).
“Research and development on fragility of592

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

FOREST ROADS CAUSE EDGE EFFECTS ON PLANT SPECIESDIVERSITY IN ARTIFICIAL FORESTS
Hiroki Kohmori1, Tetsuoh Shirota1, Tetsuo Okano1 and Teruo Arase1
1

Faculty of Agriculture, Shinshu University, Japan
ABSTRACTTo evaluate the effects of narrow forest roads on plant species diversity in the forest understory, we analyzed
the relationship between distance from the forest road and vegetation structure in young and mature artificial
forests of Japanese cedar (Cryptomeria japonica). Although exotic species appeared along the side of the forest
road, their appearance frequencies and coverage were very small, suggesting that a decline in species diversity
due to exotic species did not occur. Although an obvious decrease in vegetation coverage and species number
with distance from the forest road was detected in the shrub layer of the young forest, a clear distancedependency was not observed in the mature forest. However, even though the effects on local species number (αdiversity) were unclear, replacement of species was detected with distance from the forest road (β diversity) inassociation with species’ shade tolerance. This replacement of species improved the overall diversity of forest (γdiversity). Thus, it was concluded that narrow forest roads can improve species diversity in artificial forests inassociation with a diversified environment and the replacement of plant species.
Keywords: Forest Road, Artificial Forest, β Diversity, Edge Effect, Forest Age
INTRODUCTION

MATERIALS AND METHODS

Installation of forest roads enables theintroduction of high-performance forestry machinery[1], which reduces costs and enhances forestry
productivity [2], [3]. Thus, a greater density of forest
roads is required in Japan [4]. The construction offorest roads also result in changes to the forest
environment, such as temperature, humidity andlight [5], [6]. Such environmental changes canimpact the species diversity of the forest [6], [7].
Several studies have shown that the existence offorest roads improves species diversity [8]–[10].
However, even if the construction of a forest roadinitially has positive effects, its impact on theneighboring forest can change over time [8]. On theother hand, the effects of forest road construction are
not always positive with respect to species diversity.
Road construction enables the invasion anddominance of exotic plant species, which reduce thediversity of native species [7]. Furthermore, theinfluence on diversity also depends on the roadwidth since the size of the canopy gap is related to
the width of the forest road. In the case of narrow
forest roads in Iran, the effects on forest species
diversity were not obvious [11].
It is generally assumed that Japanese forest
roads are narrow (4−6 m); therefore, their effects on
species diversity may be slight. In this study, wetested the effects of Japanese forest roads on exotic
plant invasion and plant species diversity in forestsof different ages.

Study Site
The survey was conducted in an artificial forestof Japanese cedar (Cryptomeria japonica) in Neba
Village, Nagano Prefecture in Central Japan. This
area is located 35°16′N, 137°35′E. From 2007 to
2016, the annual temperature was 9.6°C and theaverage annual precipitation was 2,697 mm at theclosest observation site (Namiai Observation Site,
Japan Meteorological Agency, 35°22′N, 137°42′E).
Two forest roads were surveyed in this study, theTakahashi-Gumino (TK) line, which passes througha young forest, and the Anada (AN) line, which
passes through a mature forest (Fig. 1, Table 1).

Fig. 1
593

Location of the study areas.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Outline of the surveyed forests.

Vegetation Structure
The vegetation survey represents a larger numberof plant species in the mature forest compared to theyoung forest. In the young forest of the TK line, 30
and 114 plant species were recorded in the shrub andherb layers, respectively. On the other hand, in themature forest of the AN line, 93 and 224 plant
species were recorded in the shrub and herb layers,respectively. Vegetation coverage, species richness,and species evenness were larger in the mature
forest than the young forest, with the exception of
species evenness in the shrub layer (Fig. 2).
Almost all of the plants present were native
species, except for the following three exotic species
found in the herb layer: Eragrostis curvula,
Indigofera bungeana, and Phytolacca americana.
Exotic species were found only in sub-plots facing
the forest road. However, only one individual ofeach of the three exotic species was detected and thecoverage of each was less than 1%.

Field Surveys and Data Collection
To evaluate the effect of forest roads on species
diversity in the understory, five and 18 belt plots
were established along the TK and AN lines,
respectively. The average road width was 4.8 m. For
vegetation investigation, belt plots of 10 m wide and20 m depth were set from the edge of the road to theinterior of the forest. Furthermore, each belt plot was
divided into four sub-plots, each 10 m wide and 5 m
deep, which were named Psub.1, Psub.2, Psub.3, andPsub.4 in order of distance from the forest road. All
sub-plots had three major layers including the
canopy layer, shrub layer, and herb layer, but lacked
a sub-canopy layer. The canopy layer consisted onlyof planted Cryptomeria japonica. The characteristicsof the survey area are summarized in Table 1.
We surveyed the vegetation structure of the
shrub and herb layers in each sub-plot. We recorded
the total vegetation coverage (%) and species
coverage (%) along with the names of all vascularplants detected. The scientific name refers tobotanical books [12]–[19].

Changes in Vegetation Coverage, Species
Number, and H’ with Distance from Forest Road
Changes in the species number, vegetation
coverage, and H’ with respect to distance from theforest road are shown in Fig. 2. In the young forestof the TK line, both species number and vegetation
coverage in the shrub layer were significantly larger
in sub-plots along the road side, whereas theseremained unchanged in the herb layer. On the other
hand, in the mature forest of the AN line, species
number and vegetation coverage in the shrub layer
did not show any obvious change along the belt
depth, whereas both were slightly larger in the herb
layer of sub-plots along the road side. In the herb
layer of both the TK and AN lines, vegetation
coverage and species number show a non-linear
pattern: they were larger in both edge and interior
sub-plots, but smaller in sub-plots positioned in the
middle. There was no significant difference in H’ in
any line or in any layer, but H’ in the shrub layer of
the TK line showed a tendency to increase toward
the road side.

Analysis Method
To characterize the change in vegetation
coverage and species diversity with respect todistance from the forest road, we calculated species
number and Shannon’s diversity index (H’) based on
the species coverage for each layer of each sub-plot.
We compared these characteristics among the subplots within each layer of each line using a repeatedmeasure analysis of variance and Holm’s multicomparison method.
To detect the plant species present with distancefrom the forest road in each layer of each line, we
conducted a screening test for all species using the
Jonckheere-Terpstra test in each sub-plot according
to the distance from road. Species coverage wasused for the screening test, and a coverage of 0.1%
was used when the coverage was less than 1%. We
referred to the species detected along the road side
and on the forest interior as “edge species” and“interior species”, respectively.

Species Appearance Pattern with Distance from
Forest RoadThe edge and interior species detected alongeach line are shown in Table 2. In the young
artificial forest of the TK line, 30 species weredetected in the shrub layer, four of which were edge
species; 114 species were detected in the herb layer,
two and four of which were edge and interior species,
respectively. In the mature artificial forest of the ANline, two of the 93 species detected in the shrub layer
were edge species; 224 species were detected in the

RESULTS
594

GEOMATE - Mie, Japan, Nov. 21-24, 2017herb layer, 11 of which were interior species.
Interior species were not detected in the shrub layerof either line. Along the AN Line, two edge species

Fig. 2(Rubus palmatus var. coptophyllus and Dioscorea
japonica) were commonly detected along the ANline, whereas any species were commonly detected

Vegetation coverage and species diversity with distance from forest road. Vegetation coverage (left),species richness (middle) and species evenness (right) of the shrub layer (upper) and herb layer (lower)of the TK and AN lines are shown. Bars represent standard error. Values with the same characteristics
were not significantly different within each line. Mean values of each belt are shown above the fourcolumns and were larger in the mature forest than the young forest with the exception of species
evenness in the shrub layer (U-test at 5% level).

Table 2 Edge and interior species detected in the shrub and herb layers of each line.

Species were detected using a screening test. Asterisks represent the level of statistical significance (*5% level,**1% level, ***0.1% level). NULL means that no species of that type were detected in the layer.

595

GEOMATE - Mie, Japan, Nov. 21-24, 2017

along the TK line. In both the TK and AN lines,
three species were commonly detected: one edge
species (Rubus palmatus var. coptophyllus) in the
herb layer, and two interior species (Lycopodium
serratum and Disporum smilacinum) in the herb
layer.

highest in the herb layer. In mature forests, because
the canopy gap along forest roads is reduced, theeffect of the gap tends to be small [27]. If canopy
closure is in progress, only light-sensitive species ofthe shrub layer at the forest edge decline, andvegetative recovery is underway in the herb layer.

DISCUSSION

Enrichment of Overall Diversity by Species
Replacement

Influence of Exotic Species on Species Diversity

In total, 20 edge species and 13 interior species
were detected by a species screen test. In general,
Rubus palmatus var. coptophyllus, Clethra
barbinervis, Boehmeria tricuspis var. unicuspis, andFallopia japonica, which prefer bright conditions,are detected as edge species. On the contrary,
Huperzia serrata, Disporum smilacinum, andChloranthus serratus, which prefer shaded
conditions, are detected as interior species. These
differences between edge and interior species
suggest that the replacement of plant species occurs
in association with their shade tolerances.
The existence of only edge species in the shrub
layer (Table 2) agrees with the decline of species
number with distance from the forest road (Fig. 2).
A lower species number in the shrub layer was clear
in the young forest of the TK line where more edge
species were detected (Table 2). On the other hand,the existence of both edge and interior species in the
herb layer (Table 2) suggests that edge species are
replaced by interior species with distance from theforest road. It is thought that this replacement createsa non-linear distribution pattern in species number inthe herb layer (Fig. 2). Edge and interior species
increase in number in the forest edge and forest
interior, respectively. However, both edge andinterior species decrease in number in theintermediate position, where the number of species
will be the lowest (Fig. 2).
Species replacement can also enhance overall
species diversity. Species diversity is classified into
α diversity, β diversity, and γ diversity according toa spatial scale [28]–[31]. α diversity is the diversityof one habitat, β diversity is the difference in species
composition between habitats, and γ diversity is thediversity of all habitats. The overall γ diversity is a
product of α and β diversities [30], [31]. Although
the effects of the forest road on the local diversity (αdiversity) were not always obvious in this study (Fig.
2), species replacement (β diversity, Table 2)enhanced the overall diversity (γ diversity). Thissuggests that forest roads have positive effects on γ
diversity even if the local species richness does notchange with distance from the forest road.

Three major exotic species were detected in thisstudy, as mentioned above. Eragrostis curvula andIndigofera bungeana, which appeared in the youngforest of the TK line, are generally used for artificial
greening [20], [21]. All exotic species appeared in
the sub-plots facing the forest road, suggesting thatthese exotic species are likely to invade areas along
forest roads. It has been pointed out that wide forest
roads are safe sites for exotic species and enhancetheir dominance, which can negatively impact native
species growth and reduce the species diversity of
the area [7]. However, the number of individuals andcoverage of the three exotic species was very small
in this study. Therefore, it is thought that species
diversity was not affected by exotic species along
the narrow forest roads in this study.
Vegetation Coverage and Species Diversity
Both vegetation coverage and species number
were larger in the mature forest of the AN line than
the young forest of the TK line (Fig. 2). It is
generally reported that thinning has positive effects
onunderstory
development
andspecies
diversification by improving the light environment[22]–[25]. Repeated thinning over time results inlow stand density and a small canopy coverage(Table 1), which enhances species diversification.
These findings contradict the results for secondary
forests of broadleaf species in France [10], but agreewith findings from artificial forests in Japan [26].
In the young forest of the TK line, vegetation
coverage and species richness of the shrub layer
obviously decreased from the forest edge to theinterior. This result is similar to that of other studies[8]–[10]. On the other hand, vegetation coverage,
species richness and evenness of the herb layer
showed no significant change from the forest edge tothe interior. In the young forest, the canopy gap on
the forest road was larger. However, the effect of thegap on the herb layer was relatively small due tolight interception by the developed shrub layer.
In the mature forest of the AN line, species
richness and evenness did not obviously change with
distance from the edge in either the shrub or herb
layer, as was the case with narrow forest roads inIran [11]. However, vegetation coverage at the edgeof the forest was lowest in the shrub layer and

CONCLUSION
In conclusion, narrow forest roads in artificial
forests have the following three characteristics.
596

GEOMATE - Mie, Japan, Nov. 21-24, 2017[8] Mullen K., Fahy O., Gormally M. (2003)
Ground flora and associated arthropod
communities of forest road edges inConnemara,
Ireland.
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andConservation, 12(1), 87-101.
[9] Pauchard A., Alaback B. P. (2006) Edge typedefines alien plant species invasions along
Pinus contorta burned, highway and clearcut
forest edges. Forest Ecology and Management,
223(1-3), 327-335.
[10] Avon C., Berges L., Dumas Y., Dupouey J.
(2010) Does the effect of forest roads extend a
few meters or more into the adjacent forest? A
study on understory plant diversity in managed
oak stands. Forest Ecology and Management,259(8), 1546-1555.
[11] Tehrani B. F., Majnounian B., Abdi E., Amiri
Z. G. (2015) Impact of Forest Road on Plant
Species Diversity in a Hyrcanian Forest, Iran.
Croatian Journal of Forest Engineering, 36(1),63-71.
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Tominari T. (1981) Wild Flowers of Japan
Herbaceous Plants Ⅲ. Heibonsha Ltd.
Publishers, Tokyo, 259pp. In Japanese.
[13] Satake Y., Ohwi J., Kitamura S., Watari S.,
Tominari T. (1982) Wild Flowers of Japan
Herbaceous Plants Ⅰ. Heibonsha Ltd. Publishers,
Tokyo, 305pp. In Japanese.
[14] Satake Y., Ohwi J., Kitamura S., Watari S.,
Tominari T. (1982) Wild Flowers of Japan
Herbaceous Plants Ⅱ. Heibonsha Ltd.
Publishers, Tokyo, 318pp. In Japanese.
[15] Satake Y., Hara H., Watari S., Tominari T.
(1989) Wild Flowers of Japan Woody Plants Ⅰ.
Heibonsha Ltd. Publishers, Tokyo, 321pp. In
Japanese.
[16] Satake Y., Hara H., Watari S., Tominari T.
(1989) Wild Flowers of Japan Woody Plants Ⅱ.
Heibonsha Ltd. Publishers, Tokyo, 305pp. In
Japanese.
[17] Iwaki K. (1992) Ferns and Fern Allies of Japan.
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[18] Shimizu T. (2003) Naturalized Plants of Japan.
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[19] Hayashi M. (2014) Leaves of Tree −Identify
1100 Kinds of Tree by Scaned Leaves−. Yamakei Publishers co., Ltd., Tokyo, p.184. In
Japanese.
[20] Yoshida H., Morimoto Y. (2005) A study on
the effects of mixed seeding of Chinese-grown
Indigofera spp. and evergreen broad-leaved
trees. Journal of the Japanese Society ofRevegetation Technology, 31(2), 269-277. In
Japanese.
[21] Muranaka T., Washitani I. (2006) A Report on
the Public Symposium at IMC9: Part 4: Status

Firstly, narrow forest roads can inhibit thedominance of exotic species and their negative
effects on species diversity. Secondly, the effects ofnarrow forest roads on local species diversity aresmall in mature forests. Lastly, narrow forest roads
can enhance the overall species diversity throughspecies replacement, even in mature forests.
Additionally, our study suggests that the effects ofnarrow forest roads will dynamically change overtime with the forest age. Therefore, a theoretical
approach to forest road management that enhances
species diversity can be established throughquantitative evaluation of age-responsiveness.
ACKNOWLEDGEMENTS
We thank the members of the Laboratory ofSilviculture, Faculty of Agriculture, Shinshu
University for their help with field surveys. We also
thank Dr. Jiro Kodani, the Ishikawa Forest
Experiment Station, for his valuable advices. This
study was based on a partnership agreement between
Shinshu University and Neba Village.
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Studies on the optimization of timber
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issue "forest roads network". Journal of theJapan Forest Engineering Society, 22(3), 119120. In Japanese.
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Applied Forest Science, 6, 83-86. In Japanese.
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(2014) Stand structure and plant species
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undergrowth within 5 years after thinning.
Bulletin of the Gifu Prefectural ResearchInstitute for Forests, (40), 1-13. In Japanese.
[26] Suzuki W., Suzaki T., Okumura T., Ikeda S.
(2005) Aging-induced Development Patterns ofChamaecyparis obtusa Plantations. Journal of
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Forest Ecology. Kyoritsu Shuppan Co., Ltd.,Tokyo, pp.122-135. In Japanese.
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598

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DRIFTWOOD ACCUMULATION AND FLOOD DAMAGE
AREA IN BLOCKED RIVER
Takaaki Okamoto1, Hiroshi Takebayashi2 Masato Takenaka 1 Yoshinobu Kashihara 1 and Keiichi Toda3
1
Department of Civil Engineering, Kyoto University, Japan; 2, Disaster Prevention Research Institute,
Kyoto University, Japan
ABSTRACTAt the time of heavy rains, a flank collapse occurs. A large driftwood flows into a river and blocks a river,which lead to increased water levels. In Uji city in August 2012, the detour flood-flow occurred around the bridge
and the left bank was eroded by high-speed flow. Consequently, the house along Shizugawa River was washedaway. However, there is almost no detailed information about the log jam formation and the flood damage by
detour flood-flow in a blocked river. In this study, three kinds of laboratory flume experiments (1. Driftwood
accumulation experiment, 2. Velocity measurement of Detour flow around a bridge by PIV(Particle Image
Velocimetory), 3. Bank erosion experiment) were performed in a 10m and 40cm wide glass-made flume. The
results revealed the blockage ratio of driftwood blocking and the flood damage area by detour flood-flow.
Keywords: Driftwood accumulation, blocked river, detour flood-flow, bank erosion
INTRODUCTION
At the time of heavy rains, a flank collapse
occurs. A large amount of driftwood flows into a riverand blocks a river, which lead to increased waterlevels (Fig.1). Detour flow around a bridge causes
floods and bank erosions. In Uji city in August 2012,
the detour flood-flow occurred around the bridge andthe house along Shizugawa River was washed away.
However, there is almost no detailed information
about the flood damage area by detour flood-flow ina blocked river. Some previous research conducted
the flume study and investigated a log jam formation.
Bocchiola et al. (2008) investigated jamming oflarge woody debris in experimental flumes. The
results revealed that the probability that large woody
debris is entrained in jams increases with its lengthand decreases with the approaching Froude number.
Schmocker & Hager (2011) conducted flume
experiments and evaluated the drift-blocking
probability at bridge decks depending on (1)driftwood dimensions (single logs and single root
stocks) and (2) bridge characteristics. Prister et al.
(2013) investigated the interaction between various
piano key geometries and woody debris sizes. They
found that the floating debris blocking probability ishighly influenced by trunk diameter and upstream
head. Recently, Rusyda et al. (2014) examined therelationship between a logjam and an obstruction in achannel, and proposed an empirical equation forpredicting the volume of a logjam at a bridge.
However, still more works are needed because
there is almost no detailed information about the log
jam formation around a bridge and flood damage by
a detour flood flow in a blocked river. So, in the

Figure 1 Log jam formation around the bridge (Sep.
2014, Fukuchiyama city)present study, three kinds of flume experiments (1.
Driftwood accumulation experiment, 2. Velocity
measurement of Detour flow around a bridge by PIV,
3. Bank erosion experiment) were performed. The
results of Experiment 1 revealed the accumulation
process and backwater rise (blockage ratio ofdriftwood blocking). After large amount of driftwoodmodels accumulated around the model bridge, thebackwater surface rose and the flood-flow occurred
around the bridge. The results of Experiment 2 and 3
revealed the flood damage area by detour flood-flow.
EXPERIMENTAL SETUP
Figure 2 shows the experimental set-up and thecoordinate system. The flume experiments wereconducted in a 10m long and 40cm wide glass-madeflume. The x-axis is in the streamwise direction, with
x=0 at the upstream edge of the model bridge. The yaxis is in the vertical direction, with y=0 at thefloodplain bed. The z-axis is in the spanwise direction,with z=0 at the channel wall. U, V and W are the time599

GEOMATE - Mie, Japan, Nov. 21-24, 2017

y

x

z

Flow

D1

YAG laser

Model bridgey, V

Porous board
z,W

Flow

Driftwood

LLS

x0

x,U

Slit

Model bridge

Trapped driftwood

L

Slope

Rightbank

Bm

Figure 2 Driftwood accumulation experiment(ExperimentD1 and D2)

Leftbank
塩ビ製
D

DR

Bf

Floodplain Main-channel Floodplain

High-speed
CCD camera

DL1

DL 2

Bf
Bm
Bf
Floodplain Main-channel Floodplain

ControlcomputerFigure 3 Velocity measurement of Detour flow around a
bridge by PIV
Rigid bed(a)averaged velocity components in the streamwise,
vertical and spanwise velocity components,
respectively; u, v and w are the corresponding
turbulent fluctuations.
Floodplain models (made of hard vinyl chloride)
were placed on both sides of the channel. The widthof both floodplains (Bf=10cm) is half the width ofMain-channel region (Bm=20cm). The bank height isconstant for both bank (D=10cm).
Figure 2 shows the driftwood accumulation
experiment set-up. The model bridge was mounted
4.0m from the upstream edge of the floodplain and9.0cm above the channel bottom. The model bridge
was composed of deck and two piers (9.0cm heightand 1.0cm width). The bridge roadway is 20cm long,
5.0cm wide and 1.0cm thickness. The model bridge
was fixed to the floodplains.
Cylinder wood pieces (d=6.0mm diameter and
l=6.0, 9.0, 12.0cm length) were used to model
driftwood. The wood density is 0.5g/cm3. The woodpieces were soaked in water for 1 hour prior to a test.
Driftwood models were supplied to the flow at 4.0m
upstream from the model bridge (x=-4.0m).
To evaluate the blocking probability at the bridge,
Experiment D1 was carried out by adding a single
driftwood model to the approach flow. If thedriftwood was trapped by the bridge, it was removed
before the next test.
To evaluate the effect of the driftwood
accumulation on the backwater rise, Experiment D2
was carried out by adding the group of the driftwoodmodels continuously to the approach flow over thetest duration. The number of wood pieces was 270
pieces/270s. Over the entire test duration, we
measured the temporal development flow depth H in
Main-channel at 10cm upstream of the bridge (x  0.1m) by using a manual point gauge to examine thebackwater rise due to driftwood accumulation at thebridge.
After large amount of driftwood models
accumulated around the model bridge, the backwater
surface rises and the flood water overflows thefloodplains. Then, we evaluated the blockage ratio

Rigid bed

Movable bed

x=0

800cm

(b)

z

y

Left bankx

Downstream of the bridge (x>0)
Laser
rangefinder

100cm
Detour flow

Porous board
Main-channel

z

Slope

Detour flow
Model bridge

D

Flow
Right bank

Detour flow

Movable bed

DL
Left bank

Movable bed

DR  DLDR  DLDR

Main-channel Right bank

(Left bank height is lower
than Right bank height)

Figure 4 Bank erosion experiment(porosity) of the driftwood accumulation. The woodpieces accumulated at the bridge were removed and aporous board (15cm height, 20cm width, 3.0mm
thickness and 3.0mm hole-diameter) was placed in
front of the woody model bridge in Main-channel tomimic a blocked river due to a woody debris jam at a
bridge. The blockage ratio of the porous board varied
between Ab/A=0.2 and 0.91. We measured the flow
depth in Main-channel H at 10cm upstream of thebridge by using a point gauge and compared themeasured data with that of the driftwood
accumulation test.
Flood-flow velocity around a bridge (x/Bm=0.01.0) was measure by PIV (see Okamoto & Nezu
(2013)). The blockage ratio of the porous board
Ab / A was also changed based on the Driftwood
accumulation test D2. In order to obtain two velocitycomponents, i.e., (u~, v~) on x-y vertical plane (20cm 20cm), a laser-light sheet (LLS) was projected into
the water column vertically from the water-surface, as
shown in Fig.3. The position of LLS on the right-bank
and the left-bank are z/Bm=0.2 and 1.8, respectively.
The 2.0mm thick LLS was generated by 3.0W YAG
laser using a cylindrical lens. The illuminated flow
pictures were taken by a high-speed CCD camera(1024  1024pixels) with 500Hz frame-rate and 60s
sampling time. The fluid tracers were Nylon-12
particles of 80 diameter and 1.02 specific density. The
instantaneous velocity components on x-y verticalplane (u~, v~) were calculated by the PIV algorithm.
To examine the effect of the detour flood-flow on
the flood damage, the bank erosion experiment was
conducted. Figure 4 shows the bank erosion
experiment set-up. Near the bridge (x=-0.2~1.0m)),
600GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Hydraulic condition (driftwood experiment)
CaseL6-1
CaseL6-2
CaseL6-3
CaseL6-4
CaseL9-1
CaseL9-2
CaseL9-3
CaseL9-4
CaseL12-1
CaseL12-2
CaseL12-3
CaseL12-4

Q (l/s)
3.0
5.0
7.0
9.0
3.0
5.0
7.0
9.0
3.0
5.0
7.0
9.0

U m (cm/s) H m (cm)
21.0
36.0
50.0
64.0
21.0
36.0
7.0
50.0
64.0
21.0
36.0
50.0
64.0

l (cm)B R (cm)

6.0

9.0

6.0

12.0

l/B R

D R (cm)

1.0

10.0

1.5

10.0

2.0

10.0

Fr
0.26
0.43
0.60
0.78
0.26
0.43
0.60
0.78
0.26
0.43
0.60
0.78

Pb

MethodS ingle driftwood blocking / Driftwood accumulation
S ingle driftwood blocking / Driftwood accumulation

Q (l/s)
7.0
7.0
7.0
7.0
7.0

U m (cm/s) H m (cm)
50.0
7.0
50.0
7.0
50.0
7.0
50.0
7.0
50.0
7.0

D R (cm)
10.0
10.0
10.0
10.0
10.0

D L1 (cm) D L2 (cm)
10.0
8.0
10.0
8.0
10.0
8.0
10.0
8.0
10.0
8.0

S ingle driftwood blocking / Driftwood accumulation

2

S ingle driftwood blocking / Driftwood accumulation
S ingle driftwood blocking / Driftwood accumulation

0.3

S ingle driftwood blocking / Driftwood accumulation

Fr  U m

1.5

S ingle driftwood blocking / Driftwood accumulation

1

S ingle driftwood blocking / Driftwood accumulation
S ingle driftwood blocking / Driftwood accumulation

0.2

S ingle driftwood blocking / Driftwood accumulation

A b /A
0.49
0.65
0.91
0.2-0.91
0.2-0.91

Fr
0.60
0.60
0.60
0.60
0.78

0.1
0

MethodBank e rosion
PIV / Bank erosion
Bank e rosion
Flow depth measurement
Flow depth measurement

the floodplain area is mobile. The floodplain models
were filled with sand (median size of 0.5mm) to adepth of 0.1m, as shown in Fig.4. In the remaining
part, the floodplain area is rigid. Experiment runs
were performed for 0.5h when a equilibrium state wasattained. The time variation of the bank height aroundthe bridge was measured by the Laser rangefinder(Bosch).
Table1 shows the hydraulic condition of thedriftwood accumulation experiment. The driftwoodmodel length l (l=6.0, 9.0 and 12.0cm) and the flow
discharge Q were changed. To evaluate the test
repeatability, ten times tests were conducted for eachcase. H m denotes the initial flow depth in Mainchannel.

l BR

0.4

S ingle driftwood blocking / Driftwood accumulation

Table 2 Hydraulic condition (Velocity measurement and thebank erosion experiments)
CaseR10L8-1
CaseR10L8-2
CaseR10L8-3
CaseR10L8-X1
CaseR10L8-X2

0.5

S ingle driftwood blocking / Driftwood accumulation

Fr  0.26

Fr  0.43

Fr  0.60

Fr  0.78

Figure 5 Blocking probability of the single driftwood
(a)
BR

PierB

(b)
R

BR

③ span two piers② get turned

BR

Pier

BR

BR

② span two piers①①

Driftwood Flow

Driftwood Flow

Figure 6 Trapping process of the single driftwood
Schmocker & Hager (2011). They revealed thatdriftwood transported by high-speed flow touches abridge but may be freed because of the stream power
and the vertical flow components.
To examine the effect of the driftwood
accumulation on the backwater rise, we conducted thedriftwood accumulation experiment D2. Figure 7
shows the photographic examples of the driftwood
accumulation for l/BR=1.5, Fr=0.6 and l/BR=2.0,
Fr=0.6. For l/BR=2.0 Fr=0.6, some wood pieces weretrapped and accumulated at the bridge. The otherpieces passed through the bridge. Once a single
driftwood model is trapped by the bridge, theblocking probability increases significantly. The
driftwood accumulation resulted in an increase inwater level upstream from the model bridge. Afterlarge amount of driftwood accumulated at the bridge,
the water overflowed the banks and the detour flow
occurs around the bridge.
Figure 8 shows the development of the flow depth
in Main-channel H at 10cm upstream of the bridge for
Test 1 and 2 (l/BR=2.0, Fr=0.6). The flow depth
values are normalized by the approach flow depth Hm.
nd is number of driftwood models supplied to water.
At the start of the driftwood accumulation, theflow depth increases rapidly with the number oftrapped driftwood models. After 70 wood pieces wereadded to the flow, the backwater rises slower. After
200 wood pieces, the flow depth reaches its final
value Hmax. For l /BR= 2.0, Fr=0.6, the flow depth is
1.75 times higher at test end.
Due to the random accumulation process, thedifference in the increase rate of the flow depth isobserved between Test 1 and 2. However, the resultsof Test 1 and 2 show the almost equal final values at

gH m denotes the approach

Froude number.
Table 2 shows the hydraulic condition of thevelocity measurement and the bank erosion
experiments. Experiments were conducted on thebasis of three flow scenarios, in which Ab / A waschanged based on the Driftwood accumulation test
( Ab / A =0.49, 0.65 and 0.91). Before a flood (without
the porous board), the water in Main-channel does not
overflow the banks. The bulk mean velocity is
Um=50.0 (cm/s) and the flow depth in Main-channel
is Hm=7.0cm.
RESULTS

Figure 5 shows the blocking probability of thesingle driftwood Pb. Pb increases with the relative
driftwood length l/BR. For l/BR=1.5 and Fr=0.6, somewood pieces touch a pier, get turned and span
between two piers, as shown in Figure 6. The
blocking probability of driftwood is Pb=0.075. For
l/BR=2.0 and Fr=0.6, Pb=0.225.
No blocking (Pb=0) was observed for l/BR=1.0.
Some driftwood models are temporally trapped but
driftwood models cannot span between two piers.
Consequently, the trapped driftwood models are
freed.
It is also observed that an increase of Fr results ina decrease of Pb. This result is good agreement with601

GEOMATE - Mie, Japan, Nov. 21-24, 2017(a)l/BR=1.5, Fr=0.6

50 wood pieces(a)

100 wood pieces

H / HmFr  0.602

1.8

Ab / A  0.65
1.6

Overflow

Ab / A  0.56
Ab / A  0.49

1.4
l BR
2

1.2
Flow

Flow

Trapped driftwood(b)l/BR=2.0, Fr=0.6

Trapped driftwood0

100 wood pieces

50 wood pieces
Detour flow

1.5

50

100

150

H / Hm

Detour flow

200

250

300

2

Ab / A  0.65
Ab / A  0.56

1.6

Overflow

Ab / A  0.49

1.4

l BR

2

1.2
Flow

Initial flow
depth 1

Trapped driftwood

Trapped driftwood

Figure 7 Photographic examples of the driftwood
accumulation at a bridge for l/BR=2.0, Fr=0.6 (a) andl/BR=1.5, Fr=0.6 (b)H / Hm

1.8
1.6

0

50

100

150

200

250

H f (cm)z Bm  1.55

Flow

Fr=0.60

Bridgey

1.2

6Left bank

Fr=0.78x

Initial flow 1
depth

Hf

4

0.8

nd

300

Figure 9 Development pf relative flow depth(a) Fr=0.6, (b) Fr=0.78

Flow

Test 2

1.4

Number of
supplieddriftwood

1.5

8

Test 1nd

Fr  0.78

(b)

1.8

Flow

Number of
supplieddriftwood

Initial flow
depth 1

H

0.6

x0

2

0.4
0.2
0
0

50

100

150

200

250

Number of supplied
driftwood
300 n dx / Bm  0.5

0
0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Slope edge
(Left bank)

1

Ab A

Figure 8 Development pf relative flow depth for Test 1
and 2 (l/BR=2.0, Fr=0.6)

Figure 10 Flood flow depth versus the blockage ratio ofan obstruction

test end. Therefore, the reproducibility is acceptable.
Figure 8 shows the relative flow depth in Mainchannel H/Hm at 10cm upstream of the bridge for
l/BR=1.5, 2.0, Fr=0.6 and l/BR=1.5, 2.0, Fr=0.78. The
values of the flow depth in ten times tests areaveraged for each case.
In Fig.9, the values of the flow depth H for
Ab/A=0.49, 0.56, 0.65 (blockage ratio of porous
board) are also indicated for comparison.
The values of Hmax for l/BR=2.0 are larger thanthose for l/BR=1.5. For l/BR=2.0, Fr=0.6, the value of
Hmax is in good agreement with the flow depth H for
Ab/A= 0.65. This indicates that the blockage ratio ofdriftwood accumulation for l/BR=2.0, Fr=0.6 is Ab/A=
0.65. The blockage ratio of driftwood accumulation
for l/BR=1.5, Fr=0.6 is Ab/A= 0.56. This implies thatthe increase of the driftwood projected area resulted
in the increase in the blockage ratio Ab/A of thedriftwood accumulation. It is also observed that theflow depth increases with the approach Froudenumber.
To investigate the occurrence condition of a detour
flood-flow around a bridge, we changed the blockage
ratio of an obstruction Ab / A for Fr=0.6 and 0.78.
Figure 10 shows the flood-flow depth Hf on the leftbank upstream of the bridge (x/Bm=-0.5). The floodflow depth Hf was measured by a point gauge.
For Fr=0.6, the flood-flow depth is Hf =0 when
Ab / A  0.49. This indicates that water in Mainchannel does not overflow the banks and the detour
flow does not occur when Ab / A  0.49. When
Ab / A  0.49, the water in Main-channel overflows
the banks ( H  D ) and the flood-flow depth
increases linearly.
The occurrence condition of a detour flood-flow
depends on the Froude number. For Fr=0.78, thedetour flood-flow occurs around the bridge when
Ab / A exceeds 0.3.
Figure 11 shows the contours of the flood-flow
depth Hf in x-z plain for CaseR10L8 (Fr=0.6 and
Ab/A= 0.65). Upstream of the bridge ( x / B m  0 ),the flood-flow depth Hf is almost constant in thestreamwise direction (Hf =3.0cm) and the difference
between the left bank and the right bank cannot be
observed.
Downstream of the bridge ( x / B m  0 ), thevalues of flood-flow depth Hf on both banks decreasein the streamwise direction. It is also observed that,602

GEOMATE - Mie, Japan, Nov. 21-24, 2017

z
0

x

0.5

-1

1

1.5

2

Flow

t=9s

z Bm

t=21s
Flow

Flow

-0.5
0

Model bridge
0.5

1

1.5

Main-channel

2Main-channel

Left bankMain-channel

2.5

t=35s

3

t=60s
Flow

Flow

3.5

Right bankx Bm

Left bank

Left bank

H fR , H fL (cm)Figure 11 Contour of flood-flow depth on both banks for
CaseR10L8 (Fr=0.6 and Ab/A= 0.65)
y Bm

z Bm  0 .2( Rightbank )

0.12

x Bm
-0.3

-0.15

0.09

Main-channel

0

Flow

0.15
0.3

0.06

x / Bm  0
0

0.3

y Bm

0.6

0.9

1.2

Right bank10

DL t  8

1.5

U U m.main

z Bm  1.8(Leftbank)

0.12

Ab / A  0.49

6

Flow
x Bm

0.09

Left bankFigure 13 Photographic examples of the bank erosion on
the left bank

0.03

0

Main-channel

Left bank

Ab / A  0 .65

4

-0.3

-0.15

Left bank

0
0.06

2

0.15

Ab / A  0.91

0.3

0

0.03

0

x / Bm  0 Slope edge

0
0

0.3

0.6

0.9

1.2

1.5

100

200

t s 

300

Figure 14 Time variation of the bank height DL(t)(Left bank)U U m.main

Figure 12 Vertical profiles of the streamwise velocity on
the left bank and right bank for CaseR10L8 (Fr=0.6 and
Ab/A= 0.65)
the values of the flood-flow depth Hf at z/Bm= 0.5, 1.5(floodplain edge) are smaller than those at z/Bm=
0.125, 1.875 (on the right bank and the left bank).
These results imply that the floodwater on both banks
flow into the Main-channel for x / B m  0 .
The effect of the floodplain shape on the floodprone area is clearly observed for x / B m  0 . The
values of the flood-flow depth Hf on the left bankdecrease in the streamwise direction and become
negligibly small for x/Bm=3.0. All of the floodwateron the left bank flows into the Main-channel forx/Bm>3.0. On the right bank, the flood-flow depth Hf
is negligibly small for x/Bm>1.5.
Figure 12 shows the vertical profiles of thestreamwise velocity on the left bank and right bank.
The velocity value increases in the streamwise
direction. This indicates that the detour flow occurs
around a bridge and the flood-flow runs into the both603

banks. The velocity difference between the left bankand the right bank is not significant upstream of thebridge. In contrast, downstream of the bridge( x / Bm  0 ), the detour flow is concentrated on theleft bank and the velocity value increases
significantly near the bed. The high-speed flow near
the bed may lead to the bank erosion.
Figure 13 shows the photographic examples of thebank erosion on the left bank for CaseR10L8. At t=0s,
the porous board was placed in front of the bridge. At
t=3.0s, the detour flood flow runs into the floodplain
and the bank erosion occurs around the bridge. The
bank erosion area becomes larger with time.
At t=60s, the detour flow eroded the left bank at
x / B m  1.0 ~ 0.0 (upstream of the bridge).
Downstream of the bridge, the bank erosion isobserved at x / B m  0.0 ~ 1.5 .
Figure 14 shows the time variation of the bank heightDL(t) around the bridge for Ab/A =0.49, 0.65, 0.91.
The bank height decreases rapidly at t=3.0-100.0s for
Ab/A =0.65. An increases of the blockage ratio Ab/A
results in an increase of the bank erosion rate.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

the right bank flows into the Main-channel forx / Bm  1.5.

CONCLUSION

In the present study, three kinds of flume
experiments (1. Driftwood accumulation experiment,
2. Velocity measurement of Detour flow around a
bridge by PIV (Particle Image Velocimetory), 3.
Bank erosion experiment) were performed toinvestigate the log jam formation around a bridge andflood damage by a detour flood flow in a blockedriver. Main findings are as follows:
1.

2.

3.

At the start of the Driftwood accumulation(Experiment D2), the flow depth increases
rapidly with the number of trapped driftwoodmodels. After 70 wood pieces were added to theflow, the backwater rises slower. After 200 woodpieces, the flow depth reaches its final value
Hmax. For l/BR=2.0, Fr=0.6, the value of Hmax isin good agreement with the flow depth H for
Ab/A= 0.65.

4.

The bank erosion experiment revealed that the
detour flow eroded the left bank at
x / B m  1.0 ~ 0.0 (upstream of the bridge).
Downstream of the bridge, the bank erosion isobserved at x / B m  0.0 ~ 1.5 .

5.

The bank height decreases rapidly at t=3.0100.0s for Ab/A =0.65. An increases of theblockage ratio Ab/A results in an increase of thebank erosion rate.

ACKNOWLEDGEMENTS

The present study was carried out under thefinancial support of the Research Project Grant-InAid for Scientific Research of Japanese Government(Kakenhi No.15K16311, Principle Investigator= T.
Okamoto). The authors greatfully acknowledge this
support.

We changed the blockage ratio Ab / A of an
obstruction (porous board) in Main-channel toexamine the occurrence condition of the detour
flow around the bridge. For Fr=0.6, when Ab / A 0.49, the water in Main-channel overflows thebanks ( H  D ) and the detour flow occurs. For
Fr=0.78, the detour flood-flow occurs around thebridge when Ab / A exceeds 0.3.

REFERENCES[1] Bocchila, D., Rulli, M.C. and Rosso, R.: A flume
experiment on the formation of wood jams inrivers, Water Resources Research, Vol.44, 2008,
W02408.
[2] Okamoto, T. and Nezu, I.: Spatial evolution ofcoherent motions in finite-length vegetation
patch flow, Environmental Fluid Mechanics,
13(5), 2013, 417-434.
[3] Pfister, M., Capobianco, D. and Tullis, B. andSchleiss, A.J.: Debris-blocking sensitivity of
piano-key weirs under reservoir-type approachflow, J. of Hydraul. Eng., 2013, pp.1134-1141[4] Rusyda, M.I., Hashimoto, H. and Ikematsu, S.:
Log jam formation by an obstruction in a river,
Proc. of Rievrflow2014, 2014, pp.717-724.
[5] Schmocker, L., and Hager, W.H: Probability ofdrift blockage at bridge decks, J. Hydraul. Eng.,
Vol.137, 2011, pp.470-479.

The velocity measurement results revealed thatthe flood velocity increases in the streamwise
direction downstream of the bridge. For
CaseR10L8, flood-flow is concentrated on theleft bank and the velocity values of the detour
flow on the left bank become larger than those on
the right bank. On the left bank, the detour flow
velocity the velocity value increases significantly
near the bed at x / Bm  0.15-0.3. All of thefloodwater on the left bank flows into the Mainchannel for x / Bm  3.0. All of the floodwater on604

SeventhInternational Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PERMEABILITY CHARACTERISTICS OF ROAD BASE MATERIALSBLENDED WITH FLY ASH AND BOTTOM ASH
Jonathan R. Dungca1 and Joenel G. Galupino1
Civil Engineering Department, De La Salle University, Manila, Philippines

1

ABSTRACT
Permeability, being the ability of water to flow through a soil, should be considered when designing roads.
Permeability should be employed when designing roads that will provide good drainage as well. Fly ash andbottom ash were utilized as partial substitutes to conventional road base materials in road base construction. The
study aimed to prove that employing fly ash and bottom ash would increase the permeability characteristics ofroad base while also decreasing the disposal costs of the said coal by-products. Series of experiments wereconducted to test the horizontal and vertical permeability of pure fly ash, pure bottom ash, pure conventionalroad base materials, and blends comprising of the said soil components. It was also established that horizontal
and vertical permeability had a significant difference wherein the flow of water at the horizontal-direction isgreater compared to the vertical-direction.
Keywords:Permeability, Fly Ash, Coal Ash, Waste Utilization

by-products of coal. Fly ash comprises 80% of thetotal coal by-products left at the boiler, while 20% is
composed of bottom ash in fuel gas [6].This study
aim to reduce disposal costs of fly ashes and bottom
ashes through utilizing these as road base materials.
Through this, they are thriving for a safe disposal ofthese coal by-products while also providing a new
input to how these can be properly and successfully
utilized. This will serve as a study on how to reduce
disposal of fly and bottom ashes while also puttingemphasis on effectively hampering harmful
emissions of solid particles and gases into theatmosphere and the improper disposal of hazardous
elements.
The study endeavored to present thepermeability characteristic of road base materials
blended with fly ash and bottom ash. Moreover, themain objective of this proposal is to evaluate thesuitability of conventional road subgrade, sub-base,and base materials blended with specific proportionand gradation of fly ash (as partial substitute forfines) and bottom ash (as partial substitute for fineaggregates) for highway embankments with respect
to the standard permeability characteristic of roadembankments.

INTRODUCTION
When designing structures, it is very importantfor engineers to understand the soil underneathbecause it will affect the way it is designed [1].
Roads, in general, play an important role in thedrainage capacity when there is an occurrence ofheavy downpour of water. Most of the time, anengineer place focus on the strength characteristicsof roads when in fact, permeability also plays animportant role in the drainage capacity of thesepathways. This study is concentrate on thepermeability characteristics of fly ash and bottom
ash as road base materials. Permeability is defined as
the ability of water to flow through the material. It isalso referred to as the “hydraulic conductivity” ofthe porous material [2].
Permeability can be a fundamental factor in
determining the strength and capacity of fly andbottom ashes as road base materials. Throughacquiring the size and shape of the ashes’ pores andtheir connectivity, the researchers will be able todetermine their permeability characteristics. With
these, they can establish whether fly and bottom
ashes will meet the standards of suitable
permeability as road base materials. Road base is a
blend of gravel and fine materials that will form a
hard surface with a high level of mechanical strength
when compacted [3]. Good drainage can increase as
well as maintain the strength of the subgrade. On theother hand bad drainage would have negative effects
in terms of the strength of the subgrade [4,5]. With
these, the researches would incorporate fly ash andbottom ashes to the road base materials to ensure theproper and efficient drainage.
Fly and bottom ashes are the two most common

METHODOLOGY
The fly ash and bottom ash which were collectedfrom a single and specific thermal power plant in thePhilippines. Shown on Table 1 is the soil mixturesthat were checked on the effect of specificproportions and gradations of fly ash (as partial
substitute for fines) and bottom ash (as partial
substitute for fine aggregates) for highway
embankments with respect to the standard
605

GEOMATE-Mie, Japan, Nov. 21-24, 2017

permeability characteristic of road embankments.
Table 1. Soil Mixtures used in the Study
BottomAsh
Other
Soil Mixtures
Content
Notations(B) %Blended Samples
B0 (Pure CRBM)
F0B0C100
0B20
F10B6.5C83.5
20
B40
F10B13C77
40
B60
F10B19.5C70.5
60
B80
F10B26C6480
B100
F10B32.5C57.5
100
Controlled
Samples
B50F0C0No Fly Ash
50
Pure Fly Ash
B0F100C00formulated by obtaining the area of the cylindricalvertical permeameter and then converting it into a
rectangular box. As for the length of the rectangularbox, it was obtained based on the diameter to heightratio of the vertical permeameter and the width tolength ratio of the horizontal apparatus.

Fig 2. Side View of Horizontal Permeameter
This method was accomplished by comparing thefalling-head permeability test results to that of thematerial requirements. If it passed the requirementsby actually exceeding the acceptable values of k,then the results for that certain material blend areconsidered. On the other hand, if resulting
coefficient of permeability values are lower than thebasis, the researchers responsible for testing thesamples repeated the tests to really verify thepermeability values. The permeability characteristicsof the blended materials were also related to theobtained index properties of coal ashes for it wasused to further analyze the results gathered.

A microscopic characterization test was done,
furthermore, the determination of the index
properties of fly ash, bottom ash, and conventional
materials through applicable laboratory tests such as
Specific Gravity of Soil Solids (ASTM D854) [7],Atterberg Limits (ASTM D4318 and ASTM D427)[8], Particle Size Analysis (ASTM D422) [9] andMaximum and Minimum Index Densities (ASTM
D4253 and D4254)[10,11] commenced [12].
Similar ideas of obtaining the horizontal
permeability of road base materials had beendeveloped by Roads Division Engineering incollaboration
Hydraulics
Research
Limited,Wallingford and they have also considereddesigning a horizontal permeameter, there are also
other designs of permeameters that may be used [13].
The dimensions used were 1.0m x 0.3m x 0.3m
respectively for the length, width and height of thebox apparatus while the standpipe was at a length of
0.29 m, shown on Figures 1 and 2. This study scaled
down on the dimensions of the apparatus because
using similar measures would not only be
impractical in terms of time and preparation, but also
because it is an in-situ test. As much as possible, thecomparison of the the horizontal permeability values
with that of the vertical, should be conducted in the
study.

RESULTS AND DISCUSSIONS
Index Properties
Microscopic Characterization
The particle shapes, surfaces, and textures wereanalyzed on a microscopic level in order to havemore appropriate observations and analysis of the
behavior of fly ash and bottom ash mainly during theexperimental process, Conventional Road Basematerials (CRBM) was also subjected to the testingfor source of comparison in later analysis. SEM tests
were used to analyze the morphology on all thesamples.
At first glance it can be observed that bottom ash
looks similarly like the sand that can be seen on thebeach which is small and angular particles withcoarse complexions, shown on Fig. 3. The core of abottom ash particle is angular in shape and issomehow porous making them easy to crush. Theseobservations were similar to the findings to somestudies [14] in where the researchers observed thatbottom ash particles exhibited angular and irregularshapes.

Fig. 1. Top View of Horizontal Permeameter
So as to properly compare the horizontal
permeability with that of the vertical permeability,
the researchers have thought of incorporating theconcept vertical permeameter’s design into thehorizontal. A design of the horizontal apparatus was
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GEOMATE-Mie, Japan, Nov. 21-24, 2017

Table 2. Specific Gravity of the Soil Blends
Soil Mixtures
Blended Samples
B0 (Pure CRBM)
B20
B40
B60
B80
B100
Controlled Samples
No Fly Ash B50F0C0
Pure Fly Ash B0F100C0

Fig 3. SEM of Bottom Ash, Fly Ash andConventional Road Base Materials (CRBM)
On the other hand, it was observed that the
microscopic characteristics of Fly Ash is quite
different that from Bottom Ash. By the naked eye,Fly Ash is brown in color and powder like in texture.
They have smaller particles compared to bottom ash.
The core of a fly ash particle is possess a more
spherical and round shape, shown on Fig. 3. They
also possess smoother texture and are more porous.
On a same microscopic scale it was observed that it
has more voids compared to bottom ash.
SEM was also used to observe CRBM to see its
difference from the two coal ashes. Under the naked
eye, CRBM are mostly angular and flat in shape. It
was observed that on a microscopic level,
agglomerate of CRBM are of rough texture moresimilar but not entirely the same to the Bottom Ashparticles. It also is composed entirely of indefinite
shapes which are very close to each other, shown on
Figure 3.

Gs

2.81
2.78
2.75
2.70
2.52
2.52
2.76
2.33

Atterberg Limits
Liquid limit of the CRBM of around 15.6 wasachieved and 13.65 for the plastic limit. Having
plasticity index of less than 3 of either the theoreticalformula or the polynomial equations, thus fines
content of CRBM is considered to be non-plastic.
Fly ashes are non-plastic that makes it very difficult
to perform the Atterberg test. From observation,
experiments and researches, fly ash and bottom ash
can be considered as non-plastic.
Compaction Behavior
Proctor test was used to determine the optimum
moisture content (OMC) and maximum dry unit
weight. These variables were acquired through using
the equation of the curve produced when the
different water contents and dry densities wereplotted. Differentiation of the equation for the curve
per blend was done and equated this to zero.
Conventional road base materials demonstrated
the highest maximum dry density. However, it alsopresented the least percentage of OMC. This
indicates that with little amount of water,conventional road base materials already reached
OMC promptly. This justifies that conventional roadbase materials reaches OMC even with little amountof water. Also it tends to display the highest
maximum dry density because of its relatively highspecific gravity that affects the total dry mass at
OMC. Pure fly ash and bottom ash exhibited diverse
results from each other. Pure bottom ash had low
percentage of OMC. Fly ash had a significantly
higher percentage of OMC. However, comparing
their maximum dry densities, fly ash had a lower
value than that of the bottom ash. These results showthat fly ash contained more mass of water in thevoids distributed among its total dry mass in contrast
to that of bottom ash. Since fly ash is considered to
exhibit particle size as that of fines, it ischaracterized to be absorbent of water gradually.
Before it can be considered saturated, more water is
employed for fly ash than bottom ash. It wasobserved that as the percentage of bottom ash wasincreased while the percentage of conventional road

Grain Size Distribution
In the Grain Size Distribution Curve of pure fly
ash, it can be seen that most of the particles are
ranging from 0.001 to 0.075 mm which passes the#200 sieve, as such it falls under the classification of
the size of silt; thus it can be considered as such. The
coefficient of uniformity as well as curvature of fly
ash samples were 1.43 and 1.157, respectively; assuch it falls under the classification of being poorly
graded. On the other hand a similar analysis wasmade for the pure bottom ash. As such it can be said
that Bottom Ash can be considered under theclassification that of sand. The coefficient ofUniformity was computed to be 4, while the
Coefficient of curvature was 1, therefore it can besaid that the bottom ash sample was poorly graded.
Specific Gravity
The specific gravities of the different blends
have followed an exponential form, which seems tohave been the best fit line that depended on specificbottom ash contents. As the percentage of bottom
ash increased in a blend, the specific gravity
decreased, shown on Table 2. The reason for thisbehavior is because of the fact that as the bottom ash
content increased, the amount of CRBM decreased.
The existence of these CRBM, namely the sand andgravel are denser than that of the bottom ash. The
specific gravities of the different blends also largely
depended on its morphology.

607

GEOMATE-Mie, Japan, Nov. 21-24, 2017base materials was decreased for a blend, OMC
increased also in value, shown on Figure 4. This
explains that more bottom ash content with lessconventional road base materials made the blend
require more water to reach OMC.

characteristic of CRBM particles, which are moreangular in shape compared to bottom ash.
Hydraulic Conductivity
Vertical Permeability
Among the controlled samples (CRBM,
pure bottom ash and pure fly ash), bottom ash has
the highest value of coefficient of permeability that
ranges from 1.00E-03 to 1.00E-02. The said values
are considered to be a very stable and good to be
used as road base material. Pure bottom ash hadeven surpassed the permeability characteristic of
CRBM.
Moreover, pure fly ash has a very poorcoefficient permeability that can be considered touse as an impervious layer for other embankment
applications but not as a road base material. By
looking at Blend F0-B42.5-C57.5, it can be said that
replacing bottom ash for the fines content of the soil
samples have an effect to the permeability.
By blending bottom ash and fly ash atconventional road base materials, the value of
permeability with respect to void ratio, relative
compaction and relative density varied at different
percentage of bottom ash content. A graphicalrepresentation of the coefficient of permeability ofbottom ash as a function of void ratio was
accomplished, shown on Figure 5. Different
proportions of bottom ash, namely 20%, 40%, 60%,
80%, and 100%, were tested using the Falling Head
Permeability Test. At these ratios, various
coefficients of permeability were attained. A graphshowing the relationship between coefficient of
permeability and void ratio was then arranged.

23
22.5
Dry Unit Weight (kN/m3)

22
21.5
21
20.5
20
19.5
19
18.5
18
0
F10-B26-C64
F10-B32.5-C57.5

5
10
15
Water Content (%)
F10-B13-C77
F0-B42.5-C57.5
F10-B19.5-C70.5
F10-B6.5-C83.5

20

Fig. 4 Dry Unit Weight and Water Content at
different blends
Maximum and Minimum Index Densities
The maximum and minimum index densities
and void ratio of the blended soil samples andcontrolled soil samples, which are the CRBM, purebottom ash, pure fly ash and CRBM blended onlywith bottom ash (F0-B42.5-C57.5) were determinedusing standard testing method of ASTM withdesignations D4253 [10] and D4254 [11]. Pure fly
ash has significantly larger values of void ratio
compared to bottom ash and CRBM. The results
were logical since fly ash is more porous compared
to bottom ash and to CRBM that is clearly shown to
the SEM photomicrographs. Thus, it tends toincrease the volume of voids over the volume of fly
ash. The same logic occurs when bottom ash iscompared to CRBM. As for the index densities, fly
ash obtained the lowest value compared to othercontrol samples. This simply justifies that fly ash
produces higher volume of voids over the mass of
the ashes. Looking at the controlled blend that has
no fly ash content, it produced a higher void ratio
and lower dry density when compared to 100% BAblend. This means that the fines content of bottom
ash produces more voids as compared to the fines
content of fly ash. This can be defended through theamount of fly ash being mixed to other blends isgreater in volume than of the bottom ash. The low
specific gravity of fly ash was able to let more fly
ash to fill the empty and small spaces of the blended
soil samples compared to the fines of bottom ashthat has higher specific gravity. For the blended
samples, the maximum and minimum void ratios
decreases as the bottom ash content increases.
Though the morphology of bottom ash particles are
more porous compared to CRBM particles, the grain
size of bottom ash gives better interlocking property
compared to CRBM. This is because of the physicalFig. 5. Coefficient of permeability of different
blends at varying void ratio
It can be observed that there was an increasing
trend based on the values of coefficient of
permeability and void ratio. This explains that as thevoid ratio, e, increased, the coefficient of
permeability, k, also increased. Thus, the soil
became more permeable when there was higher void
ratio. A specific function was employed inconveying the relationship between k and e. The
resulting coefficient of permeability, k is in cm/sec.
The relationship between e and permeability was
also influenced by the amount of bottom ash
incorporated in the blend. Furthermore, it produced
608

GEOMATE-Mie, Japan, Nov. 21-24, 2017higher void ratio and permeability when there weregreater amount of bottom ash in a blend. The bottom
ash content in a blend signified that as one decrease
the fraction of bottom ash, void ratio becomes
smaller and permeability of the soil also becomes
weaker.

Coefficient of Permeability,k (cm/sec)

ash content and void ratio.

Horizontal Permeability
The horizontal permeability was also consideredin this study as have been stated in the objectives.
An apparatus was devised in such a way that thehorizontal permeability of corresponding desired
relative compactions can be measured; involved
parameters such as the consequent particle sizes’
weights for desired relative compaction, void ratios,
hydraulic gradient, were also taken into
consideration in relation and similar to the vertical
set-up.
From the obtained data it was observed that thepermeability of all sample tests had a familiar trend
in where the permeability decreases as the relative
compaction increases. As explained earlier, thistrend can be attributed to the reason that due to theincreased compaction rate, the voids present in thesample would be lessened as the sample gets morecompacted.

0.00140.00120.001
0.00080.00060.00040.0002
0
0.00
0.20
0.40
Multiple regression
Void Ratio, eEmpirical Formula
Actual k

0.60

Fig 6. Validation of the Model
Statistical analysis was performed for specificgravity, maximum and minimum index density andvoid ratio, empirical formulas for verticalpermeability and multiple regression. From theanalysis, given a level of confidence of 95%, alltStat and P-value was satisfied. Given that there
were no value of t-Stat between 1.96 and -1.96 and a
P-value greater than 0.005. Thus, all correlation
done in the mentioned analyses are considered to be
acceptable. In addition, all the graphs for thecomparison of the actual and predicted permeability
produced a slope almost equal to one of an angle of
45 degrees. From here we could say that using thederived empirical formulas for the different blends
would generate consistent results to the actual
permeability.

Model
Many models may be considered in the study [15,16, 17, 18]. The experiments conducted for thedifferent blends had been reasonably included within
its limits which is 10-6< k <10-3 for sand and sandy
soils. Looking at the results, it can also be supposedthat the blend/s that qualify both Unified Soil
Classification System (USCS) recommendations andgood permeability are the ones that have around
40% to 60% bottom ash content for a desired
relative compaction, blends 3 and 4 for this study.
A multiple regression was also produced so as topredict the permeability at different percent bottom
ash content and void ratio. The equation is shown
below:

CONCLUSIONS AND RECOMMENDATIONSThis study aimed to present the permeability
characteristic of road base materials blended with fly
ash and bottom ash and to evaluate the suitability of
conventional road subgrade, sub-base, and basematerials blended with specific proportion andgradation of fly ash (as partial substitute for fines)
and bottom ash (as partial substitute for fineaggregates) for highway embankments with respect
to the standard permeability characteristic of roadembankments. With thorough researches, analysis
with the literatures related to this study and actuallaboratory experiments performed by the researchers,
the following conclusions are drawn:
1. From SEM tests, fly ash had the most visible
voids as compared to bottom ash and CRBM.
This had greatly affected the index properties ofthe soil samples as well as the permeability
characteristics of the blended soil samples.
2. Horizontal and vertical permeability of CRBM
and pure BA had a significant difference
wherein the flow of water at the horizontaldirection is greater compared to the verticaldirection which means that permeability largely
depends on the axis of flow and compaction.
3. Blending bottom ash and fly ash has great effect𝑘𝑘 = 𝑒𝑒𝑒𝑒𝑒𝑒 −14.2634+0.88735𝐵𝐵+13.361𝑒𝑒 Eq. 1

Where:

B = percent bottom ash content; (%)
e = desired void ratio; andk = predicted vertical permeability (cm/sec).
Equation 1 produced a coefficient of correlationof above 95% which indicates that it is highly
correlated, shown on Figure 6. Further statisticalanalysis was also done to verify the accuracy of thederived multiple regression equation. The results
showed that Equation 1 is acceptable in predicting
the vertical permeability given the percent bottom
609

GEOMATE-Mie, Japan, Nov. 21-24, 20174.

5.

to the permeability of soils. Among the designed
blends, the 40% to 60% substitute of bottom ash toconventional road base materials incurred the highest
vertical permeability at different relative compaction
but not for the higher relative compaction (RC =100%) where the amount of bottom ash did not havea significant effect to the permeability.
The permeability values obtained for all the blends at
the required compaction of 95% range from 1.00x1006 to 1.00x10-05, which is considered to be a fairly
stable material as a road embankment according to
USCS recommendation for road embankments.
Using the derived empirical model for permeability
produces good projection of the results, which canalso be proven acceptable through statistical analysis.

http://www.concretenetwork.com/concretesubgrades-subbases/what-is.html[6] Asilo, M., Pamintuan, C., & Roque, A. (2004).
Bottom Ash By-Product from Coal-Fired Power Plant
in Pangasinan Used as a Substitute for Fine
Aggregates in Concrete. (Undergraduate Thesis) De
La Salle University, Manila, Philippines.
[7] American Society for Testing and Materials.(n.d.).
Standard Test Methods for Specific Gravity of Soil
Solids by Water Pycnometer. ASTM D854. ASTM
D854.
[8] American Society for Testing and Materials.(n.d.).
Standard Test Methods for Liquid Limit, Plastic
Limit, and Plasticity Index ofSoils. ASTM D4318.
[9] American Society for Testing and Materials.(n.d.).
Standard Test Method for Particle-Size Analysis ofSoils. ASTM D422.
[10] American Society for Testing and Materials.(n.d.).
Standard Test Methods for Maximum Index Densityand Unit Weight of Soils Using a Vibratory Table.
ASTM D4253.
[11] American Society for Testing and Materials.(n.d.).
Standard Test Methods for Minimum Index Densityand Unit Weight of Soils and Calculation of Relative
Density. ASTM D4254[12] Liu, C., & Evett, J. B. (2000). Soil Properties: Testing,
Measurement and Evaluation. (E. Francis, Ed.)
Charlotte, North Carolina, USA: Prentice Hall.
[13] Smith, C. B. (2010). Horizontal Permeameter. Magna
Cum Laude Honors Research Project, University of
Florida, Department of Civil and Coastal Engineering,
Gainesville, Florida.
[14] Kim, B., Yoon, S. , Balunaini, Ll., Prezzi, M. &Salgado, R. (2006). Determination of Ash Mixture
Properties and Construction of Test Embankment Part A.
[15] Dungca, J., Galupino, J. (2016). Modelling ofPermeability Characteristics of Soil-Fly AshBentonite Cut-Off Wall using Response Surface
Methodology, International Journal of GEOMATE
10, 2018-2024.
[16] Dungca, J., Galupino, J. (2017). Artificial neuralnetwork permeability modeling, International Journalof GEOMATE 12, 77-82.
[17] Dungca, J.R., Jao, J.A.L. (2017). Strength andpermeability characteristics of road base materials
blended with fly ash and bottom ash, International
Journal of GEOMATE 12, 9-15.
[18] Uy, E.E.S., Dungca, J.R. (2017). Constitutive
modeling of coal ash using modified cam clay model,International Journal of GEOMATE 12, 88-94.

For future researches, further experiments on
different coal ashes of different origins or class may be
conducted where the resulting coefficients of permeability
may be compared with the outcomes in this thesis.
Conducting more researches would not only define thepermeability characteristics for the variety of coal ash byproducts even more, but also provide engineers withinformation when it comes to designing roadembankments.
It is also recommended for future studies that fly ash
content which is ten percent of all blend compositions may
be removed and replaced with bottom ash and/or
conventional road base material and distinguish if it will
have better permeability results than that of the ones
conducted in this study.
Moreover, it would be recommendable for future
researchers to study the horizontal permeability of theconventional road base materials blended with fly ash andbottom ash. It will be helpful to verify the ratio ofhorizontal over vertical permeability and confirm if it has
satisfactory rate of flow at the x-direction as a goodconsideration for road base materials.
REFERENCES[1] Galupino, J., Dungca, J. (2015). Permeability
characteristics of soil-fly ash mix. ARPN Journal ofEngineering and Applied Sciences, 15, 6440-6447.
[2] Mordecai & Morris. (1974). Permeability. Retrieved
June
22,
2011
from
http://outburst.uow.edu.au/html/permeability.html[3] Pacspi, (n. Understanding road base specifications.
Retrieved
August
10,
2011,
from
http://www.pacspi.com.aulroadbase.html[4] Summers. C.J. (2000) An idiot's guide to highway
maintenance. Retrieved August 2011, fromhttp://www.highwaysmaintenance.com/drainage.htm[5] American Concrete Institute. (2011). What is a
subgrade/subbase? Retrieved August 10, 2011, from610

Seventh International Conference on Geotechnique, Construction Materials and

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Environment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

REVIEWS ON THE APPLICABILITY OF CONSTRUCTION AND
DEMOLITION WASTE AND ITS RECYCLED MATERIALS AS LOWCOST ADSORBENTS TO REMOVE HEAVYMETALS IN WASTEWATER
G.M.P. Kumara, Takashi Saito, Shingo Asamoto, and Ken Kawamoto
Graduate School of Science and Engineering, Saitama University, Saitama, Japan
ABSTRACT
Heavy metal removal from wastewater is of special concern due to the uncontrollable persistency of heavy metals in the environment. The discharge of industries containing heavy metals adversely effects on soil and water
resources, aquatic organisms and ecosystem integrity. In addition, it reported high concentrations of heavy metals detected in solid waste landfill leachate in many developing countries due to non-segregated waste dumping.
At present, various kinds of adsorbents such as activated carbon, biomass resources, geo materials, and industrial
waste products have been used to treat heavy metal-contaminated water. However, the use of construction anddemolition waste (CDW) and its recycled materials to treat heavy metal-contaminated water has not been fully
examined. Because the generation of CDW is increasing due to the rapid urbanization and high demand of construction works, the wise-use of CDW and its recycled materials can be expected. This paper reviews publishedjournal articles from 2004 to 2016 which studying the applicability of low-cost CDW adsorbents to remove
heavy metals from wastewater. In especial, summarizing results from CDW and recycled materials such as cement, concrete, and brick, it compared to those from other various adsorbents such as bio sorbents, geo materials
and their industrial products. The potential effectiveness of the applicability of CDW and its recycled materials
as heavy metal-adsorbents have been examined based on the comparison table listing material properties, tested
conditions and measured adsorption properties.
Keywords: Construction and demolition waste, Recycled materials, Adsorbent, Heavy metalsof that 70% is waste concrete [7]. Then researchers
can predict densely populated India and China likecountries will produce huge amounts of CDW materials in the future by creating lots of environmental problems. Therefore, the efficient usage of thoseabundantly available resources for different activities investigation is timely. Therefore, objective of
this review is to investigate applicability of CDW
and recycle materials as an efficient adsorbent toremove heavy metals from wastewater with respect
to geo materials and bio sorbents.

INTRODUCTION
Conventional wastewater treatment methods
such as coagulation, flocculation, reverse osmosis,
membrane separation, ion-exchange are long conducted to provide a better water quality and to treat
it before being released into the water bodies [1].
However, those methods are expensive and higher
cost is needed during the operation [2]. Recently,
scientists have been studying on using low cost andabundant adsorbents to remove heavy metals in thewastewater. Natural and industrial geo materials
and bio sorbents are well known sorbents and researchers done many experiments to identify theadsorption capacity of those materials [3].
Rapid urbanization, industrialization and population
growth in developing and developed countries produce million tons of construction and demolition
wastes (CDW) per year. As an example, Malaysia,
Thailand and Vietnam produce 1.9, 1.9 and 6.9
million tons of CDW materials per year respectively and common treatment method is landfilling or
dumping [4];[5]. About 850 million tons of CDW isgenerated in the European Union (EU) per year,
representing 31% of the total waste generated in theEU [6]. However, the level of recycling and reuseof CDW varies greatly between less than 10% toover 90% across the EU [3]. In 2014 United State
produce 534 million tons of CDW materials and out

METHODOLOGY
A detailed literature search was carried out byinitially selecting several key words. Those used
include: heavy metal adsorption, natural and industrial geo materials, bio sorbents, and CDW materials. The search was limited to paper selection criteria given in Figure 1. All papers selected were published in Web of ScienceTM (Clarivate Analytics). A
total of 33 references were selected of which mostare journal papers from environmental engineeringand material science research areas. A careful review of those selected papers has been done bycomparing each category of adsorbents for experimental conditions, maximum adsorption capacity,
analysis methods, results and suggesting future
considerations.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 1: Procedure of journal paper selection for the review in this study
less consideration in each category, and common
solution were NaCl, NaNO3 or NaClO4 under theconcentration range of 0.001-0.1 N. It is clear that
CDW and recycle materials need higher equilibrium time than the other two categories of adsorbents.
Basically equilibrium time depend on the target
metals, adsorbent and its physical conditions andother operation parameters. Higher equilibriumtime is one of the main constrain for commercial
application of those adsorbents. Therefore, further
studies are needed to find out less equilibrium timeby changing other testing conditions.
According to Table 2, in all three categories ofmaterials showed lack of data regards to cation exchange capacity (CEC) and point of zero charge ofthe materials. But, these two parameters are essential to understand the potential of adsorption and to
explain adsorption behavior of metals. It revealed
that a wide range of initial concentration of metal
solutions was tested in the adoption studies. Solution pH is the one of critical parameter in adsorption experiments and especially if adsorbent

RESULTS AND DISCUSSION
Adsorption has been proved to be an excellent
way to treat wastewater, offering significant advantages like the low-cost, availability, profitability
and ease of operation. According to Fig. 1, scientist
and researchers gave highest priority for geomaterials and bio sorbents (>80%) for adsorption
heavy metals with compare to CDW and recycle
materials. Furthermore, adsorption study for concrete and cement materials are rare. Hence, investigation, comparison and identification of test conditions, adsorption capacity and analyzing methods ofvarious adsorption materials with respect to CDW
materials is beneficial for the next generations.
As shown in the Table 1, all three types of adsorbents, major target metals are Cu, Cd (39.9%),
Pb (33.3%), Zn (24%) while less consideration
gave for As (12.1%), Cr, Hg and Mn (6.1%) likemetals. Used particle size and adsorbent concentration is diverse for each category and for each metal
type in reviewed papers. Testing of backgroundelectrolytes effect on adsorption process also has

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1: Summary of followed methodology in each adsorption studies
Category ofadsorbent

Adsorbent

TargetmetalsParticlesize(μm)

Adsorbent
concentration (g/L)

BackgroundsolutionIonicstrength(mol/L)

Brick

As5+

≤ 300

10-40

DIW

(-)

Cu
Zn2+
Cu2+, Zn2+,
Pb2+

63-20045-4760
≤ 250

5
10
25

NaCl
DW
DW

0-0.34
(-)
(-)

Grout
Wood

Pb2+ ,Cd2+
Cr6+

A

≤ 80
1-100

20
1-5

NaCl
DW

Clay tile
Marble

Zn2+
Cd2+
Pb2+
As5+
Cd2+, Zn2+,
Cu2+ , Pb2+
As5+

45-4760
25 –63
25 –63
50
2000

10
2
1
10-40
40

14003000≤ 855

Ni2+ , Mn2+
Pb2+, Cu2+,
Zn2+ , Cd2+
Pb2+
Co2+

CementB

Bentonite
Kaolinite
ZeoliteSepiolite
Montmorillonite
Alluvial
soil
Bark
SawdustCoconutshell
Coir pith

C

Ref.

[8]
[9]
[10]
[11]

0.1
(-)

120
540-1200
7200 (Cu2+),>7200(Zn2+),
2880(Pb2+)
90
40

DW
DDW
DDW
DIW
NaNO3

(-)
(-)
(-)
(-)
0.01

1200
300
120
60
60

[10]
[14]
[15]
[8]
[16]

10-40

DIW

(-)

60

[8]

10

DIW

(-)

[17]

100-500
90-3002-10
5DDW
NaClO4(-)
0.01-0.05

150 (Cd2+),
250 (Pb2+)
180
<1440

20-53
≤ 200

2-20
0.2-1.4

DW
NaClO4(-)
0.001-0.1

360
120

[20]
[21]

Pb2+ , Cd2+

2000

100

MQW

(-)

[22]

Cd2+

≤ 500

4

Na2SO40-0.07

Pb2+ 360,
Cd2+ 60
25

Zn2+, Cu2+,
Cd2+, Fe2+,
Ni2+ , Mn2+
Pb2+ , Cd2+

400-1000

2-40

DW

(-)

30

[24]

≤ 75

100

MQW

(-)

[22]

Cd2+

≤ 96

0.25-3NaCl

0.001-0.1

Pb2+ 360,
Cd2+ 60180

2+Concrete

Equilibriumtime for
Isotherm(min)60

Cd2+ , Pb2+

[12]
[13]

[18]
[19]

[23]

[25]

Peanutshell
NeemleavesBambooHg2+ , Cd2+

100-200

8

DIW

(-)

120

[26]

Cr6+

850-1500

4-16

DW

(-)

4020

[27]

As3+, As5+

63-1250.01-0.15

DDW

(-)

[28]

Oat hulls

As5+

360-430

0.015

DIW

(-)

1800 forAs3+, 2130
for As5+
1440

[29]

Wheat
As3+, As5+
*
0.5-3
Fe3O4
0.5
720
[30]
straw
Note: DW-distilled water, DIW- deionized water, DDW- doubly distilled water, MQW- Milli-Q water, (-)- noionic strength, * No data available
materials are concrete or cement material, carefulobservation of working pH is essential for maxi-

mum adsorption of heavy metals [8]-[16]. Studies
regards to temperature effects on adsorption process

613

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 2: Summary of followed methodology in each adsorption studies
Category ofadsorbent

Adsorbent

TargetmetalsPoint ofzero
charge

Brick

As5+
Cu2+
Zn2+
Cu2+, Zn2+,
Pb2+

*
*

CEC of adsorbent(mmol/100
g)
*
*

*

*

Grout

Pb2+, Cd2+

*

453.2

Wood
Clay tile
Marble

Cr6+
Zn2+
Cd2+
Pb2+
As5+
Cd2+,Zn2+,
Cu2+, Pb2+
As5+
Cd2+, Pb2+

*

*

8.3
8.3

*
*

*

ConcreteA

CementInitialpH

Temperature (0C)

Ref.

2-9
1.5-6
2.5-4.5
5-7

25
25-45
25
20

[8]
[9]
[10]
[11]

5

25

[12]

52.2

0.1-1
200
40-90
873(Cu2+),837 (Zn2+),1041(Pb2+)
20 (Cd2+),
200 (Pb2+)
10-50
40-90
20-60
500-1500
0.1-150-1600

1-11
2.5-4.5
7
7
2-9
3-9

10-50
25
25
25
25
25

[13]
[10]
[14]
[15]
[8]
[16]

*
*

*
61.0

0.1-1
2-500

25
0-60

[8]
[17]

27-50
25

[18]
[19]

Kaolinite
ZeoliteNi2+, Mn2+
Pb2+, Cu2+,
Zn2+, Cd2+

5.5
*

11.3
*

100-500
5-20

2-9
5.2
(Pb2+),
8(Cd2+)
2-8
6

Sepiolites
Montmorillonite
Alluvial
soil
Bark
Sawdust

Pb2+

6.4

11.8

300

2-9

20-40

[20]

Co2+

*

86.1

9.8

3-12

30-70

[21]

Pb2+, Cd2+**

100-2000

2-8

25

[22]

Cd2+
Zn2+, Cu2+,
Cd2+, Fe2+,
Ni2+, Mn2+
Pb2+, Cd2+

5.32
*

*
*

25-300
5-200

2-5
5

20-50
25

[23]
[24]

*

*

100-2000

2-8

25

[22]

5.5
*

181
*

25-300
1-300

2-8
1-7

30
25

[25]
[26]

*

*

40-700

1-11

30

[27]

5
*
*

*
*
*

2-38
0.025-0.2
1-28

2-9
5-9
3-11

25
24
30

[28]
[29]
[30]

Bentonite

B

Coconutshell

Coir pith Cd2+
PeanutHg2+, Cd2+
shell
Neem
Cr6+
leavesBambooAs3+, As5+
Oat hulls As5+
Wheat
As3+, As5+
straw
Note: *No data available
C

Concentration range(mg/L)

for CDW and recycle materials is rare and researchers have potential for that. Reported maximum adsorption capacity (Qmax) illustrates in Figs.
2 and 3 for selected adsorbent and all adsorbent
show potential for adsorb heavy metals from waste

water. It is clear that less consideration for CDW
and recycle materials and limited for few heavy
metals such as Pb, Cd and Cu (see, Fig. 1). Furthermore, brick and marble materials show morethan 100 mg/g Qmax for Cu and Pb respectively

614

GEOMATE - Mie, Japan, Nov. 21-24, 2017[9],[15], implying that CDW and recycle materials
have a great potential for adsorb heavy metals as

geo and bio sorbents.

A

B

C

Figure 2: Reported adsorption capacities in selected adsorption studies

values of entropy (ΔS) suggest the probability of afavorable adsorption.
CONCLUSION

A

B

According to all parameters discussed in thispaper, it is clear CDW and recycle materials havesame potential as geo and bio sorbents for adsorb
heavy metals form wastewater which is marginalized material in current situation. Therefore researchers and scientist have to focus their attention
to improve and use this abundantly available material for wastewater treatment process in future.

C

Figure 3: Reported adsorption capacities in selected
adsorption studies

ACKNOWLEDGEMENTS

According to the data reported, Langmuir andFreundlich models for isotherm studies and pseudo
first order and pseudo second order models for kinetic studies are commonly used models and best fit
models during the data analyzing process in all
three categories. Furthermore, Langmuir model ismore than 90% act as a best fit model for CDW andrecycle materials by representing mono layer adsorption to adsorbent. There are different types ofadsorption mechanisms were reported and for CDW
and recycle materials such as ion exchange, chemisorption and film diffusion. Thermodynamic parameters are important to explain adsorption process when changing the temperature of the medium.
The Gibbs Free Energy (ΔG) is negative for CDW
and recycle materials by indicating the spontaneous
nature of the adsorption process and the negative

This study was supported by the SATREPS Projectof the Japan Science and Technology agency (JST)and Japanese International cooperation Agency(JICA).
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GEOMATE - Mie, Japan, Nov. 21-24, 2017[16] Yong et al., Heavy metal adsorption by a formulated zeolite-Portland cement mixture, Journal ofHazardous Materials, Vol. 147, 2007, pp. 91–96.
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[18] Dawodu et al., Simultaneous adsorption ofNi(II) and Mn(II) ions from aqueous solution unto a
Nigerian kaolinite Clay, journal of material researchtec. Vol. 3(2), 2014, pp. 129–141.
[19] Hutaf et al., Natural Jordanian zeolite: removalof heavy metal ions from water samples using column and batch methods, Environ Monit Assess,Vol. 157, 2009, pp. 319–330.
[20] Sharifipour et al., Kinetics and Thermodynamics of LeadAdsorption from Aqueous Solutions on
to Iranian Sepiolite and Zeolite, Int. J. Environ.
Res., Vol. 9(3), 2015, pp. 1001-1010.
[21] Guo et al., Enhanced sorption of radiocobalt
from water by Bi(III) modified montmorillonite: A
novel adsorbent, Journal of Hazardous Materials,
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[22] Paranavithana et al., Adsorption of Cd2+ andPb2+ onto coconut shell biochar and biochar-mixed
soil. Environ Earth Sci, Vol. 75, 2016, pp. 484.
[23] Ghodbane et al., Kinetic and equilibrium study
for the sorption of cadmium(II) ions from aqueous
phase by eucalyptus bark, Journal of Hazardous
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[24] Bozic et al., Adsorption of heavy metal ions bysawdust of deciduous trees, Journal of Hazardous
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[25]Anirudhan et al., Adsorption Characteristics of
Cadmium(II)ontoFunctionalizedPoly(hydroxyethylmethac
rylate)-Grafted Coconut Coir Pith, Bull Environ
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Polymers, Vol. 81, 2010, pp.335–339.
[27] Babu et al., Adsorption of Cr(VI) using activated neem leaves: kinetic studies, Adsorption,
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[28] Liu et al., Arsenic Removal from Water by
Iron-Modified Bamboo Charcoal, Water Air Soil
Pollut, 2012, Vol. 223, pp 1033–1044.
[29] Chuang et al., Adsorption of arsenic(V) by
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[30] Tian et al., Synthesis of magnetic wheat straw
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[3] Grace MA, Clifford E and Healy MG, The potential for the use of waste products from a variety
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AA, Sustainable construction waste management in
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MISBE 2011, Amsterdam, The Netherlands, June
20-23, 2011.
[5] Chinda T and Doan DT, Cost Factors of C&D
Waste Recycling Program Implementation, the 2nd
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[6] Fischer C, Werge M, EU as a Recycling Society: Present Recycling Levels of Municipal Waste
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[7] United State Environmental Protection Agency,
Construction and Demolition Debris Generation in
the United States, U.S Office of Resource Conservation and Recovery, 2016, pp 23.
[8] Sadia et al., Evaluation of industrial based adsorbents for simultaneous removal of arsenic andfluoride from drinking water, Journal of Cleaner
Production, Vol. 87, 2015, pp. 882-896.
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[10] Hoda et al., Characterization and Utilization of
Clay-Based Construction and Demolition Wastes as
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Solutions: an Equilibrium and Kinetic Study, Environmental Progress & Sustainable Energy, Vol.
33(3), 2014, pp. 777-789.
[11] Nichola et al., Interactions of aqueous Cu2+,
Zn2+ and Pb2+ ions with crushed concrete fines,
Journal of Hazardous Materials, B121, 2005, pp.
203–213.
[12] Chen et al., Removal of Pb2+ and Cd2+ by adsorption on clay-solidified grouting curtain for
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[13] Jyotikusum et al., Removal of chromium(VI)from wastewater by activated carbon developed
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[14] Shaban et al., Cadmium(II) sorption from water samples by powdered marble wastes, Chemical
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616

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

STUDY ON EXTRACTION AND ADSORPTION OF CESIUMFROM VERMICULITE MIXTURE SAND
Shota NISHIOKA 1, Keiichiro SHIBATA 2, Hidenori YOSHIDA 2
Naomichi MATSUMOTO 2 and Yoshihiro SUENAGA 2
1
Graduate School of Engineering, 2 Kagawa University, Japan

ABSTRACTA large amount of radioactive materials were diffused by the accident at Fukushima Daiichi nuclear power
station of Tokyo electric power company, and decontamination has been continued for about six years inFukushima. The contaminated soil that is stripped on the ground and is collected should be reduced in volume at
an intermediate storage facility. However, it takes a long time to operate the facility. The ministry of theenvironment shows the guidelines that it is possible to dispose the radioactive waste below 8000Bq/kg of radiationdose in an ordinary process. Therefore, it is more desirable that the radiation dose should be reduced below
800Bq/kg in flexible containers filled with contaminated soil than the reduction of radiation dose in theintermediate storage facility. Thus, in this study, the method in which only radioactive materials are collected fromthe contaminated soil in the flexible containers is proposed. The extraction of radioactive cesium from the soil isinvestigated so as to check the performance and availability of the proposed method. As a result, it is confirmedthat is possible to collect a certain amount of cesium from cohesive soil like vermiculite in which cesium is strongly
fixed.
Keywords: Cesium, Vermiculite, Ammonium acetate, Electrophoresis, Zeolite

INTRODUCTION

decontamination area of Fukushima are stripped. It iscurrently considered difficult to secure anintermediate storage facility in which these large
contaminated soils will be managed over a long
period of time. Therefore, the disaster waste safetyassessment study meeting organized by the Ministryof the Environment proposed that the polluted soil
whose radiation dose is less than 8000 Bq / kg can bereused as construction materials such as embankment[3]. This propose indicates that a certain amount of
cesium from the contaminated soil in the temporarystorage bag are removed without waiting for theconstruction of intermediate storage facilities.
As a technology for removing cesium, the method
in which the volume of contaminated soils can be
reduced by burning the burnable materials after
separating soil and organic matter mechanically andwith high precision is proposed. Other method inwhich contaminated soils are classified into fineparticles fixed with cesium and regenerated soil by
washing the soils is proposed [4]. However, in thesemethods, the contaminated soils are decontaminatedin large-scale facilities such as intermediate storage
facilities which is difficult to construct in the present
situation due to securing their construction sites.
Therefore, it is necessary to reduce the radiation doseof contaminated soil in temporary storage space.
In this study, the artificial soil mixed vermiculite
and Toyoura standard sand was prepared as the soil
to which cesium could be easily adhered, and astirring test was conducted using an ammonium

A serious nuclear accident at the Tokyo electric
power company’s Fukushima Daiichi nuclear power
station caused the spread of large amounts ofradioactive materials. Among released radioactive
substances, iodine 131, cesium 134, cesium 137 andstrontium 90 have serious influences on the humanbody and the environment in terms of release amountand half-life [1]. In particular, cesium 137 has a large
release amount of 1.5 × 1016 Bq and its half-life is aslong as about 30 years. Moreover the detection ofradiation still continues over a wide range ofFukushima.
Cesium fixed in clay minerals in soil is known tobe difficult to remove from the soil. The soil in
Fukushima prefecture is relatively abundant inviscous soils. In general, the viscous soils absorb thecesium well from the environmental point of view. In
addition, it has been confirmed that most ofradioactive cesium is fixed in mineral particles calledvermiculite (weathered biotite) which is unevenly
distributed in the soil of Fukushima [2], and it isnecessary to establish the efficient removal method of
cesium from vermiculite.
In Fukushima, the stripping on topsoil has been
carried out for the decontamination of cesium in soil.
The Ministry of the Environment estimates thatthe amount of generated contaminated soil is about 16
million m3 to 22 million m3 after the volume
reduction of the gathered one when all the soil in
617

GEOMATE - Mie, Japan, Nov. 21-24, 2017

acetate aqueous solution as an extraction solution.
Based on the results obtained in these cesium
extraction tests, electrophoresis tests were conducted
at different current values. In the test, it was aimed toinvestigate whether it is possible to transfer cesium
from vermiculite to the adsorbent and to investigate
whether it is possible to reduce the radiation dose ofcontaminated soil in the flexible container at thetemporary houseroom.

potassium ion. As a result, a portion where othercations can enter can be formed. This is called afrayed edge (Fig.4). The cesium ion fixed to thisfrayed edge becomes difficult to replace by othercations [6]. In this study, 0.7 mm, 1.0 mm, 2.0 mm ofgrain size of vermiculate was utilized.

MATERIALS AND METHODS
Materials
In this study, the soil mixed with Toyoura
standard sand (Fig.1) and vermiculite (Fig.2) wasused as an experimental soil to which cesium wasadded.
The Toyoura standard sand is composed with thesoil particle of the uniform grain size. Moreover, it isvery smooth, and the soil grains hardly stick eachother. Therefore, the difference between experimental
samples can be neglected under the same condition,and the reproducibility of experiments are secured.

Fig.1

Fig.2 Vermiculite (particle size 0.7mm, 1.0mm,
2.0mm from the left).

Fig.3

2: 1 type layered silicate schematic.

Fig.4

Schematic diagram of the frayed edge in 2:
1 type layered silicate.

Toyoura standard sand.

The vermiculite is the silicate mineral that mainly
consists of the oxidized silicon, magnesia andaluminum oxide. It is also called leech stone in Japan
since it expands at high temperature. The common
uses of vermiculite include soil improvement andlivestock food in agricultural and horticultural fields,
refractory materials and lightweight concrete inconstruction field, disposable hand warmer andfriction materials. It has been confirmed that thevermiculite is unevenly distributed in the soil of
Fukushima, which is a major obstacle to thedecontamination of radioactive cesium [5]. Cesium
present as a monovalent cation in soil adsorbs tonegatively charged soil particles in soil. It also has theproperty of selectively adsorbing to clay particles ofsmall particle size. Cesium is fixed to the soil by the
2: 1 type layered silicate (Fig.3) such as vermiculite
among the minerals constituting the clay mineral. The
weathering of the soil swells so that the terminal partof the layer of clay mineral gets frayed and releases

The cesium extraction test using decomposed
granite soil was conducted by Miyazaki (2016), but
the test result tended to vary on account of the size of
weathered granite soil. Therefore, in this study, theexperimental results with high reproducibility can be
secured by preparing the mixed soils mentioned
above, because only the Toyoura standard sand andthe vermiculite are employed as a soil sample. In theexperiment, it was decided to carry out a cesium
extraction test on the mixed soil with the Toyoura
standard sand and the vermiculite.
Powdered zeolite (Fig.3) was used as adsorbent
for cesium in the electrophoresis test. The skeleton
structure of zeolite is silicon and aluminum bonded
618

GEOMATE - Mie, Japan, Nov. 21-24, 2017

mL of the ammonium acetate aqueous solution whose
concentration is same as that used in the test wasadded to the soil after the test. Then, it is agitated for
10 minutes at 300 rpm of a rotation speed using astirrer. Moreover, it is sieved with a sieve of 38 μm,
Stirring is performed for 40 minutes in total byrepeating the solid-liquid separation step of filtering
to solution and soil four times. The amount of cesium
contained in the solution after the test and the soil isquantified for the solution separated by filtration witheach stirring using an atomic absorption spectrometer.

via oxygen. In the skeleton structure, the periphery ofsilicon is electrically neutral and the surroundings ofaluminum are negatively charged since aluminumand silicon share oxygen with each other. Therefore,
the cations are required in the framework tocompensate for the negative charge. Since the cation
is easily exchanged with other metal ions, the zeolite
is known to have ion exchange properties.

Electrophoresis test

Fig.5

As a test soil assuming contaminated soil,
vermicu-lite mixed sand with cesium is placed in atest container and a carbon rod (D 15 mm, L 40 mm)
to be an anode is installed on the bottom of container.
It is immersed in an aqueous solution of ammonium
acetate which is an electrolyte, and an adsorbent isplaced on an assumed contaminated soil. The
adsorbent was placed in the simple container which
consists of a filter paper and a bolding cloth for aneasy access after testing. Finally, an aluminum plate(W 30 mm, L 90 mm) is installed to serve as a cathodefrom the top of the adsorbent (Fig.4). Since cesium
exists as a cation in solution, it moves to thealuminum plate which is the cathode by energizationand is adsorbed by the adsorbent.

Powdered zeolite.

An aqueous ammonium acetate solution as an
extra-ction solution for extracting cesium in the soil
and as an electrolyte in the electrophoresis test wasused. It is known that the ammonium ion ofammonium acetate shows a high ion exchange
reaction with cesium ions fixed in the clay mineral.
Based on this fact, it is suitable for the extraction ofcesium in the mixed soil. From the study of Yoshida(2016), the higher the concentration of theammonium acetate aqueous solution used as theextraction solution and electrolyte, the higher the
extraction ratio of cesium [7]. Since, however, thecontaminated soil in which the radiation doze isdecreased below the reference value is reused, theammonium acetate aqueous solution in concentrated
form cannot be employed. Therefore, 5%concentration of ammonium acetate aqueous solution(concentration 3.0%) of a saturated aqueous
ammonium acetate solution (concentration 59.7%)
having a low concentration and an excellent extraction ratio.
Cesium extraction test method

Fig.6

Schematic drawing of electrophoresis test

In this study, the experimental sample should be
put into solution for the quantitative analysis for
cesium with atomic absorption spectrometry.
Therefore, it is necessary to separate the cesium in thesoil into the solution after the electrophoresis test. In
addition, it is difficult to separate only cesium fromthe adsorbent after the test into a solution. Thus, inorder to confirm the adsorption effect for cesium on
the adsorbent by electrophoresis, it is necessary toseparate cesium into solution and to compare thedifference of cesium between the tests with andwithout the adsorbent. As a separation method, 100

RESULTS AND DISCUSSION
Cesium adsorption of vermiculite
In order to confirm the adsorption performance ofvermiculite to cesium, the results of cesium extraction
test using aqueous ammonium acetate solution as an
extraction solution are shown. The purpose of theextraction test is to confirm whether cesium can be
efficiently extracted from vermiculite by using
aqueous ammonium acetate solution. In addition, the619

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 9 shows the result of washing out thecuring vermiculite with an ammonium acetate
aqueous solution. Comparing Fig. 8 with Fig. 9, it canbe seen that the extraction ratio of cesium is improved
by about 20% by washing with ammonium acetate.
Therefore, it was confirmed that the ammonium
acetate aqueous solution was effective and efficient
extraction of cesium for the curing contaminated soil.
In the cesium extraction test with 1.0 mm of thevermiculite particle size, the cesium extraction ratio
is slightly higher than that of 0.7 mm of thevermiculite particle size. The surface area per gram ofvermiculite is larger when the particle size is smaller.
The vermiculite having 0.7 mm of the particle size
contacts cesium more widely than the others, andtrend high performance of cesium adsorption.
For the vermiculite having 2.0 mm of the particle
size, the extraction ratio is higher than the other two.
As mentioned above, the extraction amount of cesium
depends on the surface area per gram of vermiculite.
However, it is found that the extraction rate by the
extraction with distilled water shows about 20% drop
due to curing in the case of 2.0 mm particle size.
From the results of these tests, it is confirmed that
it is difficult to extract cesium in the case of smaller
size
Extraction Ratio of Cs (%)

60
40

20

Fig. 8

80
60

40
20
0
1.0

80

0.7

100

0.7

100

0

Extraction Ratio of Cs (%)

Extraction Ratio of Cs (%)

tests are conducted under the conditions where
cesium is more easily to be fixed, such as the curing
tests in which the curing period of the assumed
contaminated soil is varied or the wet state is kept.
According to the test results, the compounding ratioof vermiculite and sand for the mixed sand isdetermined. As a result, 20 g of mass and 0.7, 1.0, and
2.0 mm of particle size of the vermiculite aredetermined.
In this test, cesium is extracted by washing withstirring. 1 mg of cesium is added to the vermiculite or
mixed sand in the test container. 0 hour and 168 hoursof curing period are set, 100 ml of ammonium acetate
aqueous solution as extraction solution is poured into
the assumed contaminated soil, and the washing out
by stirring is carried out. The concentration of theammonium acetate aqueous solution is set to 3.0%,
and the stirring is carried out for 10 minutes at 300
rpm of a rotation speed. Four sets of the stirring is
conducted, that is to say, 40 minutes stirring is totally
carried out. In some tests, the distilled water is added
into the assumed contaminated soil before theaddition of cesium into the soil so as to reproduce thereal condition in Fukushima. In this study, each test is
conducted three times under the same condition toensure a reproducibility.
In the cesium extraction test with 0.7 mm ofvermiculite particle size, Fig. 7 shows that about 20%of cesium can be extracted by washing out with
distilled water immediately after the addition ofcesium. However, compared with Fig. 8, the extraction ratio is reduced to 10% or less due to long curing
period. This is because the cesium is not completely
absorbed in the flied edge of vermiculite immediately
after the addition of cesium. However, the cesium issufficiently adsorbed in the flied edge of vermiculite
due to the long curing period. This face suggests thatthe washing out with the distilled water against thecuring contaminated soil is ineffective.

2.0

Extraction ratio of cesium by washing out
with distilled water (curing period 168 h).

80
60
40
20
0
0.7

Fig. 9Extraction ratio of cesium by washing out
with distilled water (curing period 0 h).

620

2.0

100

Particle Size（mm）

Fig. 71.0
Particle Size（mm）

1.0
Particle Size（mm）

2.0

Extraction ratio of cesium by washing out
with ammonium acetate aqueous solution(curing period 168 h).

GEOMATE - Mie, Japan, Nov. 21-24, 2017

cesium extraction ratio are obtained in both cases.
From the above test results, the addition of 5% ofvermiculite for 120 g of the mixed soil is determinedin the electrophoresis test.
Extraction Ratio of Cs (%)

is difficult to extract cesium in the case of smaller sizeof vermiculite particle and to extract cesium with
distilled water from cured contaminated soil. In thesetests, it is found that the vermiculite having 0.7 mm
of particle size adsorbs a lot of cesium. Thus, in thisstudy, the vermiculite having 0.7 mm of particle size
is mixed with the Toyoura standard sand and employ
an ammonium acetate aqueous solution as an
extraction solution.
Extraction of cesium from mixed sand

Extraction Ratio of Cs (%)

The vermiculite mixed sand is prepared based on
the results obtained from the tests in which the cesiumis extracted from only vermiculite. The vermiculitewith 0.7 mm particle size is employed in order toprepare the mixed soil. The total mass of the mixed
soil in the cesium extraction test and electrophoresis
test are set to 50 g and 120 g, respectively. The mixing
ratios of vermiculite to standard sand are three cases;
3, 5, 10%.
As can be seen from Fig. 10, the lower the cesium
extraction rate is, the higher the mixing ratio ofvermiculite to standard sand is. Unger the conditionof constant volume of standard sand, the more thecesium is adsorbed, the higher the mixed ratio ofvermiculite to standard sand is.
The extraction ratio of cesium in the case of only
the vermiculite and the mixed sand is considered.
Comparing Fig. 9 with Fig. 10, there is not muchdifference between only the vermiculite and themixed sand in terms of the extraction of cesium.
Figure 11 shows the result of cesium extraction ofassumed contaminated soil in the case of 120 g of themixed sand for electrophoresis test. Comparing Fig.
10 with Fig. 11, it can be seen that there is not muchdifference between 50 g case and 120 g case in termsof the extraction ratio of cesium. This is because thevolume ratio of vermiculite and standard sand hardly
changes between them even if their total amount of
mixed sand are different. Thus, more or less same

100
80
60
40
20
0

5

10

Mixing Ratio of Vermiculite (%)

Fig. 11 Extraction ratio of cesium in vermiculite
mixed sand 120 g (curing period 168 h).
Electrophoresis test
In the electrophoresis test, the vermiculite having
0.7 mm particle size, which adsorbs cesium most, isemployed based on the results of cesium adsorption aperformance test of vermiculite. In the assumed
contaminated soil used for the electrophoresis test, 1
mg of cesium is added after setting the moisture
content to 30% wet state, and the curing period is 168
hours.
In the electrophoresis test, the aqueous solution ofammonium acetate is employed as an electrolyte, andthe test is carried out under the conduction conditionsof 48 hours of the energization time, 25V or less ofvoltage, and 0.005, 0.010, 0.015, 0.025, 0.050 or
0.100 A of current. As a result, the most effective
condition in which the cesium moves from theassumed contaminated soil to the adsorbent isselected. The adsorption effect is evaluated throughthe comparison of the cesium extraction ratio in thecase of presence or absence of the adsorbent. In thisstage, the difference of the cesium extraction ratio
between two cases of gives us the adsorption
performance of absorbent for cesium.
As can be seen from Fig. 12, it is confirmed that acertain amount of cesium is adsorbed to the zeolite
which is employed as an absorbent in this study at
0.015 A or more of current. The cesium is considered
to be unmoving because 0.010 A or less of current is
not enough or the cesium to move. Compared Fig. 11
to Fig. 12, it is found that extraction ratio of cesium isdecreased by carrying on the electrophoresis test.
This is thought that the cesium which is not fixedmoves to the frayed edge of vermiculite by current
application.

100
80
60
40
20
0
3
5
10
Mixing Ratio of Vermiculite (%)

Fig. 10 Extraction ratio of cesium in vermiculite
mixed sand 50 g (curing period 168 h).
621

Extraction Ratio of Cs (%)

GEOMATE - Mie, Japan, Nov. 21-24, 201740
Use adsorbent

30

No adsorbent

20
10

0
0.005

0.010

0.015
0.025
Current Value (A)

0.050

0.100

Fig. 12 Cesium extraction ratio (adsorbent: zeolite) in vermiculite mixed sand for 48 hours electricity test.
CONCLUSIONS

extraction ratio of cesium decreases as the mixing
ratio of vermiculite is higher.
In the electrophoresis test, it is turned out that acertain amount of cesium is adsorbed to the zeolite
which is employed as an absorbent in this study at
0.015 A or more of current. In addition, it is also
confirmed that extraction ratio of cesium declines bycarrying out energization. However, there is no needto remove all the cesium from the contaminated soil,
so we need to consider how much cesium should be
adsorbed by an absorbent like zeolite. As for futuretasks, the containers assuming actual flexible
container bags will be prepared and theelectrophoresis test is conducted to investigate theamount of adsorption of cesium which is added into
the soil in the container.

The decomposed granite used in our previous
studies was heterogeneous in particle size, and there
was variability in the result of cesium extraction foreach test. The vermiculite which exists a lot inFukushima soil fixes cesium and causes the removalof cesium from the soil difficult. Therefore, in thisstudy, the vermiculite is employed as an assumed
contaminated soil. The aim of this study is to examine
the possibility of decontamination of contaminatedsoil in a flexible control bag through the extraction ofcesium test and electrophoresis test with thinking
much of reproducible conditions.
First, in order to investigate the cesium adsorption
ability of vermiculite used in this study as an assumed
contaminated soil, the extraction test in which somesize of vermiculite particle are used is conductedunder various conditions. The distilled water andammonium acetate aqueous solution are utilized as an
extraction solution to extract cesium from thevermiculite. As a result, it is found that the smaller theparticle size is, the more the cesium is absorbed in thevermiculite due to the lager surface area of theparticle. In the extraction of cesium test with using 0.7
mm of vermiculite particle size and the distilledwater, it is found that the extraction ratio is about 20%
without the curing period and about 10% under the
curing. Furthermore, it is clarified that extraction ofcesium with the distilled water is difficult. However,using an aqueous solution of ammonium acetate as an
extraction solution, the extraction ratio of cesium inthe case of 0.7 mm of the vermiculite particle size isabout 30% without respect to the curing period of anassumed contaminated soil after adding cesium into
it. Therefore, it is confirmed that more cesium can beextracted by using ammonium acetate aqueous
solution even if the curing period is provided.
Based on the above test results, the cesium
extraction test on mixed soil of vermiculite andToyoura standard sand is conducted. In this test, theextraction of cesium from the assumed contaminatedsoil with using 0.7 mm of vermiculite particle size is
examined. From the tests, it is found that the

REFERENCE[1] Ministry of the Environment, “Unified basic dataon health effects such as radiation”, 2014, pp. 32.
[2] Mukai H, Hatta T, Kitazawa H, et al, “Speciation of Radioactive Soil Particles in the Fukushima Contaminated Area by IP Autoradiography
and Microanalyses”, Environmental Science &Technology, Vol. 48, No. 22, 2014, pp.1305313059.
[3] Ministry of the Environment, “The basic conceptof the safe use of recycled materials of theremoved soil”, 2016, pp.1-8.
[4] Tokyo Sangyo Co., Ltd, “Decontamination andreduction system of radioactive substances”,
2014, pp.2-10.
[5] Ministry of the Environment, “About efforts oftechnology demonstration projects such as
decontamination and volume reduction”, 2016,
pp.1-7.
[6] Atsushi Nakao, Noriko Yamaguchi, “Movementof radioactive substance in soil”, Soil fertilizer
compilation, No.23, 2011, pp.85-93.
[7] Hidenori Yoshida, et al, “Fundamental study on
extraction of cesium from soil”, Environmental
Geotechnical Engineering Symposium paper,
Vol.11, 2015, pp.453-460.
622

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE ORIGIN OF GROUNDWATER IN THE KIONOKAWA RIVER
CATCHMENT
1,2

Hiroki Kitagawa1, Takuma Kubohara2 and Hiroyuki Ii3
Graduate school of Systems Engineering, Wakayama University, Japan
3
Faculty of Systems Engineering, Wakayama University, Japan
ABSTRACTThe origin for the shallow and deep groundwater in the Kinokawa River catchment was studied by measuring
the depth, water temperature, dissolved ions, and oxygen and hydrogen isotope ratios. δ18O and δD values ofshallow groundwater are on the meteoric line and thought to derive from precipitation.
The deep groundwater can be divided into two types, high δ18O groundwater and low δ18O groundwater. Na+
and Cl- for high δ18O groundwater is similar to modern seawater, however its δ18O is between metamorphic fluid
and precipitation. Therefore high δ18O groundwater is thought to be metamorphic water. Na+/Cl- for low δ18O
groundwater is between the Kinokawa River water and metamorphic water. Ca2+/Cl- and HCO3-/Cl- values forlow δ18O groundwater is also between the Kinokawa River water and metamorphic water. Therefore low δ18O
groundwater is mixture of precipitation and metamorphic water. High Ca2+ concentration deep groundwater is
mixture of precipitation and metamorphic water in calcium rich rocks.
Keywords: groundwater, dissolved ions, the stable oxygen and hydrogen isotope ratios, metamorphic water
INTRODUCTION
Groundwater is widely used for agriculture,industry or domestic water all over the world andthen its stable use is necessary to conserve source ofgroundwater and to determine origin of groundwater.
Precipitation is a main source for groundwater.
However seawater is also a main source ofgroundwater beside the sea. In recent years theorigin for saline hot spring water is studied and its
origin is thought not to be precipitation or modern
seawater but to be metamorphic dehydrated fluid [1],[2].
The stable oxygen and hydrogen isotope ratios
are useful tracers for clarifying the origin forgroundwater. Generally oxygen and hydrogenisotope ratios are expressed δ18O and δD. They arepresented as per mil (‰) of the standard average
seawater (SMOW: Standard Mean Ocean Water).
The formulas are shown in equation (1) and (2).
δ18O and δD of SMOW are denoted as (D/H)SMOW,(18O/16O)SMOW and δD and δ18O of the sample aredenotedas(D/H)Sample,(18O/16O)Sample.
Measurement error of δD is ±1.0‰ andmeasurement error of δ18O is ±0.1‰.
(1)

δD

δ18O
1]×1000:=

Fig.1 Location of study area.

Fig.2 Location map showing Shallow
groundwater in the Kinokawa River catchment.
In early period of those studies, one of theimportant characteristics of meteoric water was
found by Craig (1961). Generally δ18O and δDvalues in rain water are located in the vicinity of themeteoric line of equation (3) [3].

[(D/H)Sample/(D/H)SMOW-1]×1000:= [(18O/16O)Sample/(18O/16O)SMOW(2)δD = 8 δ18O+10:

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(3)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.3 Location map showing deep
groundwater in the Kinokawa River
catchment.
STUDY AREA
Fig.1 shows the study area. The Kinokawa River,approximately 136 km, flows from east to west in
the area. The river flow rate is estimated to be 37.4
m3/s on average [4]. The Median Tectonic Line
(MTL) is at the north end of Wakayama prefecture.
There are sedimentary rocks and Sambagawa
metamorphic rocks under the Kinokawa River
catchment. Sedimentary rocks are from 0 m to 600
m in depth, Sambagawa metamorphic rocks arelower than 600 m in the ground [5].

Fig.4 Relationship between δ18O and δD forshallow groundwater.

METHOD
Water samples were taken from the KinokawaRiver, shallow wells and deep wells (hot spring
wells). Sampling was performed from April 2012 toNovember 2016. The concentrations of Na+, Ca2+,
Mg2+, Cl-, NO3- and SO42- for the sampled water
were measured by ion exchange chromatography.
The concentration of HCO3- for the sampled water
was measured by TOC analyzer. Stable hydrogenand oxygen isotopic ratios were measured by mass
spectrometer (Sercon Geo Wet System) with dual
inlet and equilibrium with CO2 and H2 gas method.

Fig.5 Relationship between δ18O and δD
for deep groundwater.

Na⁺+Ca²⁺+Mg²⁺（mEq/L）

Deep groundwater

RESULT
All groundwater samples were taken from wellsin the Kinokawa River basin. The depth range ofwells is from 5 m to 1500 m, so groundwater can bedivided into two types, shallow groundwater from
5m to 100m in depth shown in Fig.2 and deep
groundwater from 100 m to 1500 m in depth shownin Fig.3.
Isotope

Shallow groundwater

1000
800
600
400
200
0

0

200

400

600

800

1000

Cl⁻+NO₃⁻+SO₄²⁻(mEq/L)

Isotope values of shallow groundwater andKinokawa River water are on the meteoric line in
Fig.4. Generally precipitation isotopic values are on
the meteoric line. Therefore shallow groundwater isthought to derive from precipitation.
As shown in Fig.5, there are two types of deep
groundwater, high δ18O (0 ~ 6 ‰) and low δ18O (-10Fig.6 Relationship between anion and cation
concentration.
~ -4 ‰). Groundwater with low δ18O is close to themeteoric line and groundwater with high δ18O is
between the meteoric line and the metamorphic fluid.
δ18O value for the metamorphic fluid is from 5 ‰ to25 ‰ [6].
624GEOMATE - Mie, Japan, Nov. 21-24, 2017

Generally δ18O values of rocks are higher thanthose of precipitation and seawater. If water reacts
with rocks for a long term under high temperature
condition, δ18O values of groundwater increase
because original silicate mineral contains highδ18O
values. On the other hand, groundwater with high δ
D values selectively reacts with rocks and clay
mineral is produced and thenδD values of residual
water decreases [6]. Metamorphic rocks are
distributed under the Kinokawa River basin. It isthought that seawater in marine sediments goes into
underground with sediments and water squeezed
from sea sediments is fossil seawater andfurthermore under both high temperature and highpressure condition it becomes metamorphic fluid.
Fig7 Relationship between Ca2+ concentration
and Na+ concentration for deep groundwater.

Chemical
Fig.6 shows anion concentration (Cl-, NO3-,
SO42-) and cation concentration (Na+, Ca2+ andMg2+) of shallow groundwater and deep
groundwater. Cation and anion values for deep
groundwater are high and its shallow groundwater
values are low.
If groundwater mixes with seawater or reacts
with rocks for a long term, dissolved substances ingroundwater increase. However all samples values
for shallow groundwater are low, moreover asshown in Fig.4 these isotope values are on themeteoric line, therefore these are thought to derivefrom precipitation.
Fig.7 shows relationship between Na+ and Ca2+.
Na+ concentration of high δ18O groundwater ishigher than 300 mEq. C1, C2, C3 are high Ca2+
concentration groundwater (Ca2+ concentration are
more than 100 mEq).
Low δ18O groundwater has two types, high Na+concentration groundwater and high Ca2+
concentration groundwater. The origin for high Na⁺
concentration groundwater is thought to be twothings, one is mixture of precipitation and modern
seawater or high δ18O groundwater, the other one isreaction with rocks.
Fig.8 shows relationship between Na+/Cl- ratio
and Cl- concentration. Na ⁺ /Cl ⁻ ratio of modern
seawater is 0.9 and that of the Kinokawa river wateris 3.2. Na+ / Cl- ratio of high δ18O groundwater issimilar to its modern seawater. However as shown in
Fig.5 high δ18O groundwater is different frommodern seawater. Low δ18O groundwater is between
the Kinokawa River water and modern seawater orhigh δ18O groundwater. Generally Cl- concentration
for groundwater doesn’t increase with depth unlessseawater is mixed or groundwater reacts with rocksalt. However there is no rock salt in Japan.
Therefore it is thought that low δ18O groundwater is
mixture of modern seawater or high δ18O
groundwater and precipitation. However as shown in

Fig.8 Relationship between Na+/Ca2+ and Clconcentration for deep groundwater.

Fig.9 Relationship HCO3-/Cl- and Ca2+/Cl- fordeep groundwater.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.10 Groundwater flow under
the Kinokawa River Catchment

Fig.5, δD values don’t change, so low δ18O
groundwater is not mixed with modern seawater.
Fig.9 shows relationship Ca2+/Cl- ratio andHCO3-/Cl- ratio. In the deep groundwater adecomposition of inorganic matter causes to increase
HCO3- concentrations and pH of the water is getting
low, therefore Na⁺or Ca²⁺ in rocks are dissolved
into groundwater.
Ca2+/Cl- values and HCO3-/Cl- values of high18
δ O groundwater are higher than those of modern
seawater, namely high δ18O groundwater is thought
to be in the deep ground. This result indicates thathigh δ18O groundwater is metamorphic water. And
low δ18O groundwater is between the KinokawaRiver water and high δ18O groundwater. Therefore
low δ18O groundwater is thought to be mixture of
precipitation and metamorphic water.
C1, C2 and C3 are high Ca2+ concentration
groundwater. As shown in Fig.5, C1 and C2 are on
the meteoric line. However they are on the right sidefor Kinokawa River water in Fig.5. Therefore they
are thought to be mixture of precipitation andmetamorphic water or modern seawater, and thenthey are influenced by calcium rich rocks.

Ca2+/Cl- and HCO3-/Cl- shows the difference ofbetween modern seawater and metamorphic water.
Beside sea there is high Ca2+ concentration deep
groundwater. They are the mixture of precipitationand modern seawater or metamorphic water. Also
they are influenced by calcium rich rocks.
REFERENCES[1] Ohsawa S, Amita K, Oue K, Sakai T and
Mishima, T, “Hypersaline hot-spring waterwith similar hydrochemical facies but different
isotopic characteristics from Arima-type
Thermal water-Yokawa hot spring, Hyogo
prefecture, Japan”, J. of Hot Spring Science,
2015, Vol. 64, pp. 369-379.
[2] Amita K, Ohsawa S, Nishimura K, Yamada,M, Mishima T, Kazahara K, Morikawa N and
Hirajima T, “Origin of saline waters
distributed along the Median Tectonic Line insouth-west
Japan:
Hydrogeochemical
investigation on possibility of derivation ofmetamorphic
dehydrated
fluid
from
subducting
oceanic
plate”,
Japanese
Association of Hydrological Sciences, 2014,
Vol. 44, pp17-38.
[3] Yamashita M and Ii H “Estimation of
evaporation rate of surface water usinghydrogen and oxygen isotopic ratios” Int. J. of
GEOMATE, Oct., 2016, Vol. 11, Issue 26, pp.
2659-2664.
[4] Ministry of Land, Infrastructure, Transport andTourism Kinki Regional Development Bureau
https://www.kkr.mlit.go.jp/river/kasen/kinoka
wa.html[5] Mizuno K, Tsukuda E, Takahashi, M,
Momohara T and Uchiyama T, “Subsurface

CONCLUSION
Fig.10 shows groundwater flow under the
Kinokawa River catchment. There are mainly two
types of origin for groundwater in the KinokawaRiver catchment. One is shallow groundwater
derived from precipitation because these isotope
values are on the meteoric line and total dissolved
substances are low. The other one is metamorphic
water because those isotope values are different
from seawater and between precipitation andmetamorphism. Moreover Relationship between
626

GEOMATE - Mie, Japan, Nov. 21-24, 2017geology of the Wakayama Plain, southwesternJapan based on the deep boring survey”, J. of
Geology Society of Japan, Vol. 105, March
1999, No.3, pp. 235-238.
[6] Auther Hugh Richard Rollinson, Using
Geochemical Date: Evaporation, Presentation,
Interpretation Longman Scientific & Technical.
Routledge, 1993.
[7] Cerling T.E, Pederson BL, Von Damm K.L,
“Sodium-calcium ion exchange in theweathering of shales. Implications for global
weathering budgets” Geology, Vol. 17, 1989,
pp. 522-554.

627

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

STUDY ON THE REMOVAL METHOD FOR CESIUM IN SOIL OF
SLOPE
Keiichiro Shibata1, Hidenori Yoshida2 and Naomichi Matsumoto3
Graduate school of engineering, Kagawa University, Japan, 2, 3Faculty of engineering, Kagawa University,
Japan

1

ABSTRACT
Various radioactive materials were spread by the accident at Fukushima Daiichi nuclear power station of Tokyo
electric power company. Though 6 years passed since the accident, the decontamination of difficult-to-return zone
is not in prospect. The reason why the decontamination has not carried on is the geographic factor around the zone.
In particular, there is a lot of forestry area around the zone, and radioactive cesium has been accumulated by arainfall and a wind all the time from forestry area since the accident. In this way, re-pollution is a serious concern
even if the level ground was decontaminated. It is necessary for decontamination of the slope that is the supply
source of radioactive cesium from the forestry area to a residential area or farmland. Thus, in this study, the simple
decontamination method using running water was proposed to solve the decontamination of forestry area. Thismethod has the characteristics that the vermiculite strongly fixes the radioactive cesium and the decontaminationsite is a slope. In particular, four different experiments; one utilizes only cesium, one does the standard sand, one
does the vermiculite and the other does their combination, were conducted. As a result, it is confirmed that it's
possible to reduce by 20% of the volume of contaminated soil because of removal of vermiculites. Since thevermiculite is lighter weight than the sand and water, it is easy to remove only vermiculite from the water. Removalof vermiculite using this method leads to volume reduction of the contaminated soil.
Keywords: radioactive cesium, contaminated soil, decontamination method, slope, vermiculite

the radioactivity because the half period of cesium137 is about 1hirty years. Therefore, it is considered
to be difficult to decrease the radiation dose. The
specific plans in the evacuation zone isn’t currently
devised regardless of decreasing of radiation dose
can’t expect. For example, the interim storage
facilities are built in the Okuma in order to store theflexible container bag in which the contaminated soil
is filled. The amount of contaminated soil estimatedto 16~20 million cubic meter, and the securement ofinterim storage facilities where the contaminated soil
is stored is difficult. Therefore, the volume reductionof the contaminated soil is urgent business.
Alternatively, the contaminated area is dominated by
the mountains and village forest. Even if theradioactive cesium of flatland is removed, the crayparticle including the radioactive cesium continues tobe carried from the village forest by wind or rain.
Thus the re-contamination is concerned by theradioactive cesium. In this way, the slope of themountainous area is a supply route of the radioactive
cesium from the forest area to residential areas andagricultural lands as in [2].
Therefore, it is necessary to remove theradioactive cesium in the soil on the slope and reducethe collected contaminated soil. Previous study isconducted by the faculty of engineering, Ibaraki
University in order to settle this problem, and it has
two feature as in [3].

INTRODUCTION
The Great East Japan Earthquake which is themost powerful earthquake on record occurred in
Sanriku offshore on March 11, 2011. The Fukushima
Daiichi nuclear energy plant of the Tokyo ElectricPower Company (1F) was hit by the great Tsunami
several times after an hour of the earthquake. The
power facilities were widely destroyed, and thebasement room and the shaft were inundated with the
Tsunami. Major quantity of radioactive materials
were discharged from the 1F for all of mentioned
backgrounds. The radioactive materials is spread toatmosphere, which is fallen down mountain, river andmarine by rain breeze. Especially, the radioactive
cesium is detected in Tokyo Bay far away. Also, theradioactive materials that have fallen into themountains are firmly bonded to the cray foods in thesoil. Especially, the cesium-137 is extensively
detected in Fukushima prefecture because thecesium-137 is vigorously discharged and long half
period. The influence is strongly shown around the 1F,
and the 12 of municipalities in Fukushima prefectureis designated the evacuation zone still (see Fig. 1). Fig.
1 is developed based on the data by the
Reconstruction Agency as in [1]. Okuma town where
the 1F is located is designated the difficult to returnzone of all municipalities. In Okuma town, the current
air dose is lower than the air dose at the time withdecreasing of cesium-134 (the half period is two
years). However, the cesium-137 continuously emit
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

1. The bentonite is spread onto the leaf mold in theforest so as to control the resorption of the radioactive
cesium to plants.
2. The moving of the bentonite including theradioactive cesium is controlled by polyion-complex(PIC) of excess positive charge and negative charge.
The radioactive cesium in the air and solution isadsorbed into the bentonite. The resorption to theplant is controlled by the adsorption performance ofthe bentonite. Alternatively, the forestry ecosystem is
not destroyed because the elements such as the flowof rainwater is used in this method. Furthermore, the
PIC is a harmless because the raw material of PIC is
mundanely used as the thickener of ice-cream as in[4]. The moving of cesium is controlled, but thecontaminated soil is not reduced in this method.
Besides, it takes time to complete the work due tousing the rainfall. Thus, in this study, the simple
decontamination method is proposed in order todecontaminate the contaminated soil on the slope byflowing water. The surface soil including a lot of
cesium [5] is collected in this method, and the method
is suitable for the feature of soil in the Fukushima.
The cesium is easy to be adsorbed into the vermiculite
which is eccentrically distributed in the soil of
Fukushima. The specific weight of vermiculite is verysmall, and the vermiculite floats on water.
Consequently, the vermiculite can be separated fromthe washed soil. Alternatively, both thedecontamination and volume reduction ofcontaminated soil are conducted because the cesium
which is not contained in the vermiculite can be
washed and collected. In this study, the reproducible
slope test in which the Toyoura standard sand andvermiculite are utilized is conducted to examine theusability of proposed method.

Fig. 1
Conceptual diagram in areas underevacuation orders as in [1]

CESIUM IN THE SOIL
The large amount of radioactive materials was
released by the accident in the 1F. Table 1 is the main
total amount of the discharged radioactive materials
in large quantities and its half-life. Table 1 isdeveloped based on the date by Ministry of
Echonomy as in [6]. Especially, the radioactive
cesium has harmful influences for a long-term
because its half-life is very long. The volume of
spreading of strontium-90 is comparatively small,though the half-life of strontium-90 is long. The
cesium exists as the monovalent cation in the soil, and
it is adsorbed into the soil particle having a negative
charge. Especially, the cesium is selectively adsorbed
into the small clay particle. The cesium is adhered tothe soil due to the 2:1 types of lamellar silicate. Whenthe part of silicon or aluminum substitute for anotherelement having a few positive charge in the silicontetrahedron sheet or aluminum octahedron sheet, thenegative charge is expressed with the shortage of
positive charge in the sheet. Moreover, the cation isadsorbed in order to neutralize the intercalation. The
charge in this intercalation shows a high selectivity
for the cesium ion. That is because the six-memberedring is nearly equal to the ion radius of the cesium ion
in the basal seat of the silicon tetrahedron sheet.
Alternatively, the bounding strength with the sixmembered ring becomes larger as the hydrationenergy is smaller, and the bounding strength ofcesium ion is the highest. Generally, the sixmembered ring is occupied by the potassium ion
because the abundance of potassium ion
predominantly is major in the soil (see Fig. 2). The
terminal of layer inthe cray mineral isswelled by thedisintegration, andthe potassium ion
isdischarged.
Thus, the empty
space that anothercation gains entry
is formed. This
space is called thefrayed edge (see Fig. 2 2:1 types of lamellar
Fig. 3), and the silicate
extraction ofcesiumion
fromthefrayed edge isvery difficult.
It is almost
impossible toextractthecesium in thefrayededge
onlyby
flowing water. Fig. 3 Frayed edge
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Thus, in this study, it is considered that thecontaminated surface soil can be collected with theflowing water by utilizing the strong fixation.

TEST AND ANALYSIS METHOD
In order to imitate the real behavior of cesium inthe soil of slope, the slope device is produced (see Fig.
5). The slope device is consisted with two equipment:
one is the slope section and another is the flowing
water section. A 3D printer is used to produce theslope section (20.0 cm x 20.0 cm x 6.5 cm). 8.0 mm
in diameter of drain is set at the bottom of slope
section in order to collect the water and soil whichcontains cesium. The flowing water section is madeby connecting the porous rubber hose to the water
pump with a tube.
The experiment and analysis methods are
explained below in detail. First, the cesium chloride
is added to the assumed soil, and the assumed soil is
set on the slope of the device. Secondly, the purewater is disembogued from the porous hose set on top
of slope until the assumed soil is completely done
away from the slope. Finally, both pure water and soil
are collected, and the cesium concentration isanalyzed by an AAS (Atomic Absorption
Spectrometer). The sample must be in a liquid state
when the sample is analyzed by the AAS. Therefore,
it is necessary to wash out the cesium in the soil after
the test. As the washing out method, 200.0 mL of purewater is soured for the collected soil, and the sample
is screwed with 300 rpm for the 10 minutes by thestirrer. After that, the solid-liquid separation isconducted four times with 38 μm of sieve size. The
extracted volume of cesium contained in both thesolution and the soil after the test is quantitated foreach filtrate by the AAS. Alternatively, in this study,
all of the tests are conducted three times under thesame conditions to ensure repeatability.

Table 1 Compendium of the discharged radioactive
materials
NuclideXe-133
Cs-134
Cs-137
Sr-90
Ba-140Te-132
I-131
Sb-127

Half-life (day)
5.2
766.5
10950.010621.5
12.7
3.3
8.0
3.9

Total discharge (Bq)
1.1×1019
1.8×1015
1.5×1016
1.4×1014
3.2×1015
8.8×1016
1.6×1017
6.4×1015

MOCK CONTAMINATED SOIL
In this study, the Toyoura standard sand,vermiculite or their mixed sand is used as the mockcontaminated soil that the cesium is added. The
Toyoura standard sand consists of uniform size of soil
grain (see Fig. 4). Moreover, it is very smooth, andthe soil grains hardly stick each other. Therefore, thedifference between experimental samples can beneglected under the same condition, and the
reproducibility of experiments are secured. The
vermiculite is the silicate mineral that mainly consistsof the oxidized silicon, magnesia and aluminum oxide.
The vermiculite expands with high-temperature
heating. The vermiculite has a high adsorption
performance for cesium, and the mechanism ofadsorption has been clarified as in [7]. The
vermiculite is widely distributed to Fukushima soil,
and the vermiculite constitutes barriers to thedecontamination of cesium from a soil. In this study,
the vermiculites of three grain size are used so as to
examine the influence of different size of the grain on
the adsorption of vermiculites. The actual soil
consists of not only vermiculite but also the various
minerals whose characterizations are different eachother. The actual soil environment is different fromthe artificial one when the mock contaminated soil
consists of only
the vermiculite.
Therefore, the
Toyourastandard sandandthevermiculate are
mixed as themockcontaminatedsoil and the Fig. 4 Toyoura standard sandmixed soil is (upper left), vermiculite ofused in the 0.7mm (upper right), 1.0mm
experiments.
(lower left), 2.0mm (lower right)

Fig. 5 Slope device
PRELIMINARY TESTThe three preliminary tests are conducted as theprevious step of slope test. One is the test in which
only cesium is flushed out, another is the test in which
only standard sand is flushed out, and the other is thetest in which only vermiculite is flushed out. As
630

GEOMATE - Mie, Japan, Nov. 21-24, 2017shown in Fig. 8. An average 25.8 μg of cesium is
detected from the solution after flushing. This result
is more or less same as that of the test using 5.0 g ofstandard sand. On the other hand, an average 46.9 μgof cesium is detected from the solution after stirringof the recovered sand and the extraction amount ishigher than that of the test using 5.0 g of standard sand.
It is confirmed that more than seventy percent of
cesium can be extracted from the recovered solution
and sand in the test using 15.0 g of standard sand, andthe extraction mount in the test using 15.0 g ofstandard sand is slightly larger than that in the test
using 5.0 g of standard sand. When an amount ofsample is too small, the sample may accumulate on
the bottom of the container and stirring may not be
performed well. Therefore, the wash away ofrecovered sand is not enough in the case of a small
amount of the sand. In the future, additional
provisions such as the increase of rotation speed ofstirring are required.

discussed later, the methods and results of each test
are explained in detail.
Cesium flush test
It is necessary to confirm whether added cesium
remains or not on the slope after flushing and all
cesium can be recovered or not in order to verify theaccurate extraction amount of cesium. To begin with,
0.1 mL of cesium chloride solution is added onto theslope and flushed out with pouring 100.0 mL of purewater over the slope. The amount of cesium in therecovered solution is analyzed by the AAS after thecesium is flushed out. The addition amount of cesiumis 100.0 μg (1 mg/mL). The extraction amount of
cesium in the test is shown in Fig. 6. From the figure,an average102.3 μg of cesium is detected. It can besaid that all cesium is flushed out from the addition
amount of cesium. Consequently, it is confirmed that
all cesium can be flushed out the slope in this method.
Standard sand flush test

Extraction amount of
cesium (μg)

100Extraction amount of
cesium（μg）

The assumed contaminated soil that mixes withthe standard sand and the vermiculite are employed in
the slope test discussed in the next section. In thissubsection, the flush tests for the standard sand andthe vermiculite are conducted in order to ascertain
their adsorption properties of cesium. As for the
standard sand, 5.0 g and 15.0 g of specimens areprepared. The pure water is poured over the slope
until the standard sand in which 0.1 mL of cesium
chloride solution is added is completely flushed out.
The extraction amount of cesium in the solution isanalyzed after collection and stirring by stirrer.
First, the extraction amount of cesium from 5.0 gof standard sand is shown in Fig. 7. The extraction
amount of cesium after flushing is an average 21.32
μg, and about twenty percent of cesium is extracted
against the addition amount. In addition, an average
35.6 μg of cesium is detected from the solution afterstirring, and more than fifty percent is extracted from
5.0 g of standard sand. Secondly, the extraction
amount of cesium from 15.0 g of standard sand is

Flowing

60
40

41.34
30.12

20
22.27
0
1

Extraction amount of
cesium (μg)

Stirring

80

Flowing

60
40
20

46.46

50.65

43.48

24.11

25.42

27.83

0
1

106.47103.9523.43

2
3
Specimen number

100

80
40

18.26

35.45

Fig. 7 Extraction amount of cesium in standard
sand flush test (5.00g)

100
60

Stirring

80

96.37

2
3
Specimen number

Fig. 8 Extraction amount of cesium in standard
sand flush test (15.00g)

20

Vermiculite flush test

0
1

2
3
Specimen number

1.0 g of the vermiculite whose particle size is 0.7
mm, 1.0 mm or 2.0 mm is set on the slope and 0.1 mLof cesium chloride solution is added into thevermiculite. Since it is conceivable that theFig. 6 Extraction amount of cesium in cesium flush
test
631

GEOMATE - Mie, Japan, Nov. 21-24, 2017

stirring the soil. The total extracted amount is 46.9 μg
on average, which is almost same as the extracted
amount of the test using 30.0 g of standard sand.
Finally, the extraction amount of cesium from theassumed soil using 10.0 g of standard sand is shownin Fig. 12. The extracted amount of cesium from thesolution after flushing and stirring is 55.0 μg on
average. In addition, it is confirmed that about fifty
percent of cesium is extracted from the assumed soil
against 1.0 g of additive cesium regardless of theamount of standard sand. The cesium is extracted
from the standard sand, but it is not extracted from thevermiculite. From these results, it is considered thatthe vermiculite including cesium can be recovered byflushing the contaminated soil out the slope withflowing water and the other cesium can be extracted

vermiculite may consist of various particle sizes in
the actual one, three particle size of the mixedvermiculite (hereinafter referred to as Mix) that threeparticle sizes of vermiculite is prepared. Besides themass of each vermiculite is set to be more or less samein the test.
The extraction amount of cesium from eachparticle size of vermiculite is shown in Fig. 9. The
extraction amount of cesium is an average 11.0 μg
from 0.7 mm of vermiculite, 13.2 μg from 1.0 mm,
14.8 μg from 2.0 mm and 13.2 μg from the Mix. The
extraction amount of cesium from the different
particle size of vermiculite is more or less same,
though it increases in proportion as the increase of theparticle size. In addition, it is reconfirmed to be
extremely difficult for the vermiculite to extract thecesium compared with the standard sand.

Extraction amount of
cesium (μg)

100Extraction amount of
cesium(μg)

100
80
60
40
20

10.95

13.15

14.77

13.19

Stirring
Flowing

80
60
40

35.07

34.3

16.05

15.66

20
0

1

0
0.70
1.00
2.00
Mix
Particle size of vermiculite

23.97
14.11

2
3
Specimen number

Fig. 10 Extraction amount of cesium from assumed
soil using 30.0 g of standard sandFig. 9 Extraction amount of cesium in vermiculite
flush test

Extraction amount of
cesium (μg)

100
Stirring

80

ASSUMED CONTAMINATED SOIL FLUSH
TEST

Flowing60

The test which an assumed contaminated soil isflushed out on the slope is conducted in order to makethe assumption that the contaminated soil including
the cesium on the slope is decontaminated. The
assumed contaminated soil is prepared by mixing thestandard sand with 1.0 g of the Mix. Besides, three
specimens of 10.0 g, 15.0 g and 30.0 g are prepared
regard to the standard sand, and each test result iscompared.
First, the extraction amount of cesium from theassumed soil using 30.0 g of standard sand is shownin Fig. 10. No more than an average 15.3 μg of cesiumis extracted by flushing the soil. By contrast, the total
extracted amount of cesium is 46.6 μg on average
which is added on the extracted amount from thesolution after stirring. There is a same tendency
between the test using the MIX and the test using only
standard sand.
Secondly, the extraction amount of cesium fromthe assumed soil using 15.0 g of standard sand isshown in Fig. 11. An average 14.8 μg of cesium is
detected from the solution after flushing, and an
average 32.1 μg is detected from the solution after

40
20
0

22.9

30.32

16.85

14.32

1

42.96
13.24

2
3
Specimen number

Fig. 11 Extraction amount of cesium from assumed
soil using 15.0 g of standard sand
Extraction amount of
cesium (μg)

100

Stirring
Flowing

80
60
40

35.32

20

35.09
39.28

18.76

25.95

1

2

0

10.53

Specimen number

3

Fig. 12 Extraction amount of cesium from assumed
soil using 10.0 g of standard sand632

GEOMATE - Mie, Japan, Nov. 21-24, 2017by just flowing the water into the contaminated soil.

vermiculite
because there are
only
twoconstituent
substances in theassumedcontaminated
soil.
In
near
future,itisnecessarytoverify whether thedecontamination
Fig. 13 Vermiculite floatingby the proposedon the water surface
methodispossible or not for the contaminated soil which
consists of various minerals such as the decomposed
granite soil.

CONCLUSIONSIn this study, the simple decontamination method
is proposed in order to decontaminate thecontaminated soil including cesium on the slope offorest or mountain area, and the flush test on the slope
is conducted to examine the performance andavailability of the proposed method by which thecesium is recovered from the slope. Specifically, thecesium is added into the assumed contaminated soilin which standard sand and vermiculite are mixed,
and the assumed contaminated soil is flushed out theslope by flowing water. Besides, the three preliminary
tests are conducted as the previous step of the flushingtest of the Mix on the slope. One is the test in which
only cesium is flushed out, another is the test in which
only standard sand is flushed out, and the other is thetest in which only vermiculite is flushed out. In thisstage, it is confirmed whether added cesium remains
or not on the slope after flushing and all cesium canbe recovered or not in order to verify the accurate
extraction amount of cesium. From the test results,
almost 100.0 % of added cesium is collected byflushing water. In addition, the flushing tests for the
standard sand and the vermiculite are conducted inorder to examine their adsorption property of cesium.
In consequence, approximately 70.0 % of the cesiumthat added into the standard sand is extracted byflowing water and stirring. Alternatively, threedifferent types of vermiculite which has 0.7 mm, 1.0
mm or 2.0 mm of particle size are used so as to
examine the influence of different particle size on theadsorption of cesium. As a result of the test, about
13.0 % of cesium against the added one into thevermiculite is extracted regardless of the particle sizeof vermiculite. It is confirmed that the extraction ofcesium from vermiculite is far hard than that fromstandard sand.
The flushing test using the assumed contaminatedsoil is conducted with consideration for the
preliminary tests. In the flushing test, the amounts ofstandard sand are changed and their results arecompared. As results, it is confirmed that about fifty
percent of cesium against 1.0 g of the additive cesiumis extracted from the assumed soil regardless of theamount of standard sand. The cesium can be extracted
from the standard sand, but it is not extracted from thevermiculite. From these results, it is considered thatthe vermiculite including cesium can be recovered byflushing the contaminated soil out the slope withflowing water and the other cesium can be extracted
by just flowing the water into the contaminated soil.
Furthermore, the vermiculite is easily separated andcollected after flushing because the density ofvermiculite is lighter than that of water and thevermiculite floats on the water (see Fig. 13). On theother hand, in this study, it is easy to separate the

REFERENCES[1] Reconstruction Agency, “Eliminating negative
reputation impact –reconstruction from nuclear
disaster & the history of safety and revitalizationof fukushima-“, Aug, 2016, pp. 5-9.
[2] Ouchi K, “Current measures and challenges on
the rehabilitation of radiation-laden farmlandandnaturaland manmade slopes”, Journal of theJapanese Society of Revegetation Technology
Vol. 38, 2012, No. 2, pp. 282-287[3] Ibaraki University, KUMAGAI GUMI CO.,LTD. and Japan Atomic energy Agency, “Newtechnology to control the removal of radioactive
cesium from forest to living area”, May, 2016, pp.
1-4.
[4] Naganawa H, Kumazawa N, Saitoh H et al.,“ Removal of Radioactive Cesium from Surface
Soils Solidified Using Polyion Complex Rapid
Communication for Decontamination Test at
Iitate-murain
Fukushima
Prefecture,”
Transactions of the Atomic Energy Society ofJapan, Vol. 10, 2011, No. 4, pp. 227-234.
[5] Seki K, “Remediation of Soil Contaminated with
Radionuclides Derived from the Fukushima
Nuclear Plant Accident”, Journal of businessadministration of Toyo University, vol. 78, Nov,
2011, pp. 13-26.
[6] Ministry of Echonomy, Trade and Industry,“Evaluation on conduction of reactor of Unit 1, 2
and 3 in The accident of Tokyo Electric Power
Company Holdings”, 2011, p. 13.
[7] Motokawa R, Endo H, Yokoyama S et al.,“Collective Structural Changes in Vermiculite
Clay Suspensions Induced by Cesium Ions”,
Scientific Reports (online), Vol. 4, Jun, 2014,
article number 6585.

633

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

NUMERICAL ASSESSMENT OF THE IMPACT OF STRONG WIND
ON THERMAL STRATIFICATION IN LAKE BIWA

Jinichi Koue1, Hikari Shimadera1, Tomohito Matsuo1, Akira Kondo1
1

Graduate School of Engineering, Osaka University, Japan
ABSTRACT

Water temperature near the surface of a lake increases with increasing air temperature, which results instratification. The strength of stratification substantially influences the transport of dissolved oxygen from thesurface to the bottom water of a lake. In recent years, the decrease in dissolved oxygen at the bottom of the northernpart of the Lake Biwa, the largest freshwater lake in Japan, has been observed. The main cause of this is considered
to be the change in stratification, which depends on weather and climate conditions. In the present study, numericalsimulations were carried out to investigate the effect of strong wind on the structure of stratification in Lake Biwa.
The baseline simulation was conducted using actual meteorological data, and experimental simulations wereconducted using meteorological data with modified wind speed and direction. The numerical experiments showedthat if the magnitude of the wind is strong enough, the stratification collapses and the wind can enhance the verticalmixing in the bottom layer even in summer season with strong thermal stratification. In a stratified season, when
the strong wind blows predominantly in one direction, the rate of the vertical mixing changes by the wind direction.
Moreover, as the duration of the strong wind extends, vertical mixing easily occurs.
Keywords: Strong Wind, Structure of Stratification, Vertical Mixing, Hydrodynamic Model, Lake Biwa
occurs by strong wind according to the observation.
When wind blows predominantly in one direction,wind driven currents develop in the surface layer andthe water in the lower layer proceeds to the opposite
direction. Upwelling or downwelling of the water
occurs depending on the wind direction toward thecoast. In a stratified season, the thermocline oscillates
by this movement. This generates internal waves in a
stratified lake. Wind driven currents and internal
waves were observed by measuring the vertical watertemperature and the velocity continuously with using
a thermistor chain and an acoustic current profiler [6],[7]. Wind forcing carries the major source of
momentum and energy and affects the generalcirculation in lakes at various scales. However, theprocesses and the effects of the strong wind on the
deep layer remains unclear. Therefore, it is importantto understand the effect of the strong wind on thebottom layer in the lake.
In the present study, we investigated the effect ofstrong wind on stratification in Lake Biwa by using athree dimensional hydrodynamic model. Numericalsimulations were carried out for a baseline case using
actual meteorological data and experimental cases
using meteorological data with modified wind speed
and direction.

INTRODUCTION
In warm season, water temperature near thesurface of a lake increases with increasing air
temperature, which results in lake stratification. The
thermocline disrupts the transport of substances suchas dissolved oxygen between the surface layer and thelayer under the thermocline.
In some lakes, a lack of oxygen occurred in the
deep layer during a stratified period because of thethermocline [1]. In recent years, the decrease indissolved oxygen at the bottom of the northern part ofLake Biwa, the largest freshwater lake in Japan, hasalso been observed. The strength of stratification
plays an important role in the varying amounts ofdissolved oxygen in the lake. The main cause of thechange in the stratification is weather and climate
conditions such as air temperature, wind strength, andthe precipitation.
Climate change leads to prolonged periods ofstratification in lakes [2]. In Lake Zurich, in
Switzerland, a continual long term increase in thermal
stability resulted in an increase of about 2-3 weeks inthe duration of the summer stratification from the
1960s to the 1990s [3]. This impact directly affected
the stratification characteristics and mixing processes.
On the other hand, strong typhoons will occur
more frequently due to climate change [4], [5]. Whenstrong wind blows, wind stress on the surface layer
provokes significant mixing, leading to theweakening of the stratification. Vertical mixing

634

GEOMATE - Mie, Japan, Nov. 21-24, 2017

v
v v
v
1p
 u  v  w  fu  
t
x y
z
0x

Hydrodynamic Model in Lake Biwa
Calculation domain
(a)

2v
2v
2v g 0 
 vh 2  vh 2  vz 2   dzxyz  z y

(b)

,

(2)

hydrostatic equation is given by0=－

1 ∂p ρ
－ g,
ρ0 ∂z ρ0(3)

continuity Equation is written by∂u ∂v ∂w
+ += 0,
∂x ∂y ∂z(4)

conservation equation for temperature is written by

(c)

∂T
∂T
∂T
∂2T
∂2T
∂2T
∂T
+ u + v +w
= κh 2 +κh 2 +κz 2 , (5)
∂x
∂y
∂z
∂x
∂y
∂z
∂t
where u , v , and w are the x , y , and z
components of current velocity (m s-1) , T is thewater temperature (K), p is the pressure (N m-2), is the density of water (kg m-3),  0 is the reference
density of water (= 103 kg m-3), g is the acceleration

Fig. 1 Calculation domain with topography of
Lake Biwa: (a) horizontal domain, (b) south-northand (c) west-east vertical cross sections throughImazu-oki.

due to gravity (= 9.8 m s-2), f is the Coriolis
parameter (= 8.34 × 10-5 s-1 corresponding to 35 ° N), h is the horizontal eddy viscosity for momentum

This study focused on Lake Biwa, which is thelargest freshwater lake in Japan. Fig. 1 shows thecalculation domain and water depth in thehydrodynamic model of Lake Biwa. The horizontal
domain is 36 km × 65.5 km with a horizontal
resolution of 500 m. The vertical domain consists of
86 layers from the lake surface to the depth of 107.5
m. The vertical grid size is 0.5 m from the surface tothe depth of 20 m and gradually increases up to 2.5 m.

equations (= 1.0 m2 s-1 [8]),  h is the horizontal eddy
diffusivity (= 1.0 m2 s-1 [8]),  z is the vertical eddy
viscosity (m2 s-1) for momentum equations,  z is thevertical eddy diffusivity (m2 s-1).
In summer, a thermocline is typically formed at
the depth from 10 m to 30 m. This thermocline
suppresses the vertical transport of momentum andheat. To take this effect into account, the parametervalues of vertical eddy viscosity and diffusivity are
estimated by using Richardson number. Richardson
number is a dimensionless number that expresses theratio of the buoyancy term to the flow gradient term
[9] and written by

Governing equations
The governing equations consist of the
momentum equation with Boussinesq approximation,
the hydrostatic equation, continuity equation and theconservation equation for temperature. The
governing equations are described in the Cartesian
coordinate system as follows. The origin of thecoordinate axes is in the southwestern edge of thedomain on the horizontal plane. The x and y axes are
set to west-east and south-north directions,
respectively, and the z axis directs upward.
Momentum equations (x, y direction) are written by
u
u u
u
1p
 u  v  w  fv  
t
x
y
z
0x
,
(1)
2
2
2
u
u
 u g 0 
 vh 2  vh 2  vz 2   dzxyz  z xgRi =  

0


z

 ,
U w 2z(6)where U w  u 2  v 2 is the horizontal current
velocity (m s-1). Vertical eddy viscosity anddiffusivity are respectively given by

z =
and

635

0.0001(1.0  5. 2 Ri) ,(7)

GEOMATE - Mie, Japan, Nov. 21-24, 2017z =Agency (GPV MSM). GPV MSM data have a spatial
resolution of 0.0625° (longitude) × 0.05° (latitude)(approximately 5 km) and a temporal resolution of anhour. The data were horizontally interpolated into
each surface mesh of the hydrodynamic model.
Solar radiation was derived from hourly
observation data at Hikone local meteorologicalobservatory (35°16’30” N., 136°14’36” E.). Solarradiation was assumed to be horizontally uniform
over the lake.
The boundary conditions for the water volume andtemperature associated with inflow from each riverand outflow from the lake were calculated by thehydrological model [10].

0.00013

10.
(1.0   Ri ) 2
3(8)

Initial conditions
As for the initial condition, the current velocity
was set to be 0 m s-1. The initial water temperature on
April 1st, 2006 was derived from linear interpolationof observed data on March 20th and April 10th, 2006.
The observations were conducted by the Lake Biwa
Environmental Research Institute twice a month at
the monitoring point Imazu-oki (35°23’41” N.,
136°07’57” E.), the depth of which was 0.5 m, 5 m,
10 m, 15 m, 20 m, 30 m, 40 m, 60 m, 80 m, and about
90 m.

Simulation cases
The baseline simulation was conducted using
actual meteorological data for a period from April 1st,
2006 to March 31st, 2008 including a spin-up period
from April 1st, 2006 to March 31st, 2007. In addition,
experimental simulations were conducted for thesame period using meteorological data with modified
wind speed and direction on and after July 15th, 2007
in order to investigate the effect of the strong wind on
the change of the stratification. The date was chosen
due to strongly developed stratification, and in
addition, strong wind associated with a typhoon asshown in Fig. 2. In the numerical experiments, thewind speed was fixed to 10 m s-1 or 20 m s-1. The winddirection was fixed to four different directions:
northward, southward, eastward and westward. The
duration of strong wind ranged from 1 day to 7 days.
Another simulation, in which the wind speed was
twice as strong as the baseline case and the winddirection was the same as the baseline case, wascarried out to analyze the more realistic situation. As
shown in Table1, each case was named for speed,
direction and duration of strong wind.

Boundary Conditions
The boundary conditions for the current velocity
at the surface of the lake are given by the following
formula, taking the wind stress into account.
u  xzz  0(9)
v  yzz  0where  x and  y are the surface wind frictional
stresses calculated by x  ρa C f U axU a, y  ρa C f U ayU a

C f  1.0  0.07 U a  10 3 ,

(10)
(11)

where  a is the density of air (kg m-3), C f is thewind frictional constant ， U ax and

Uay arerespectively the x and y components of wind

Table 1 Wind conditions in numerical experiments

velocity (m s-1), U a is the wind speed from a heightof 10 m above the surface (m s-1).
The heat flux through the water surface consistsof short-wave solar radiation ( S  ), latent heat flux
(Ql), sensible heat flux (Qs) and net long-wave
radiation (Lnet). The heat balance equation on thewater surface is given byTρC p  z= S  +Ql + Qs + Lnet
(12)zNo-slip condition is imposed at the bottom andthe side walls. The normal gradients of watertemperature are also zero so that there is thermal
insulation.
Air temperature, atmospheric pressure, winddirection and speed, and relative humidity over Lake
Biwa were derived from the Grid Point Value derived
from Meso-Scale Model of Japan Meteorological

636

Case
name

Wind
speed
(m s-1)Wind
directions10dS_day
s10dN_day
s10dW_day
s10dE_day
s20dS_day
s20dN_day
sX2dO_day

10
10
10
10
20
20
twice

Southerly
Northerly
Westerly
EasterlySoutherly
Northerly
Original

Strongwind
duration(day)
1,3,5,7
1,3,5,7
1,3,5,7
1,3,5,7
1
1
1,3,5,7

GEOMATE - Mie, Japan, Nov. 21-24, 2017

layer above the bottom one (Fig. 4d). Once thestratification collapsed, water temperature at thebottom rose and didn’t return to the original watertemperature. The destratification depends on thestrength of the wind.
The period of the strong wind influencing thewater in the bottom layer was investigated. As theperiod extended from 1 day to 7 days, the duration of
the change in water temperature was longer. Fig. 5
shows that the period of strong wind could affect the
movement of the water parcel in the bottom layer.
And, we could also find the difference in eachdirection. From Fig. 5b-d, the strong westerly wind
would affect the water temperature more than otherwind directions. It was because of the position of themonitoring point and the topography. The monitoring
point was located at the bottom of the eastern coast(Fig. 1c), thus the water proceeded down along thecoast and reached that point. In each direction, watertemperature of the bottom layer increased after thestrong wind blew. Even if after the overturning
occurred, the water temperatures were warmer thanthe original one, therefore, the bottom water wascompletely mixed with the water in the upper layer.

(a) Wind speed(b) Wind direction
Fig. 2 Hourly wind speed and direction used in thebaseline simulation at Hikone local meteorologicalobservatory from July 1st to July 31st, 2007.
RESULTS AND DISCUSSIONSAt first, simulated water temperatures werecompared with those of field observations at themonitoring point Imazu-oki as shown in Fig. 3.
Although the simulated water temperature of thesurface layer was a little lower than the observed one
in summer, the simulated water temperature from thesurface to the bottom layer agreed well with theobserved one. In addition, the stratification was also
reproduced well in the simulation.
Next, we examined the effect of the strong windon the bottom water in the lake. Fig. 4 shows timeseries of vertical water distribution in Baseline caseand some cases at the monitoring point, Imazu-okifrom 7th of July to 8th of August. Fig. 5 shows timeseries of water temperature at a depth of 87.5m ineach case.
In s10dS_1, s10dN_1, s10dW_1, and s10dE_1,
comparing the change of the vertical watertemperature, the wind could not influence the watertemperature of the bottom layer in each case rightafter the wind blew as shown in Fig. 4b and Fig. 5a.
Although the difference between Baseline case ands10dS_1 was small in August and September, it
suddenly got larger in October. After the overturningin the middle of winter, however, the watertemperature in all conditions became similar.
On the other hand, in s20dS_1, the stratification
collapsed right after the wind blew, and the verticalmixing occurred, as shown in Fig. 4c. In addition, in
sX2dO_1, the stratification also collapsed and thewater was mixed between the bottom layer and the(a) Observed water temperature(b) Simulated water temperature

Fig. 3 Time-vertical cross sections of watertemperature at Imazu-oki from April 1st, 2007 to
March 31st, 2008.

(a) Baseline case637

GEOMATE - Mie, Japan, Nov. 21-24, 2017(b) s10dS_1(b) s10dS,N,W,E_3(c) s20dS_1(c) s10dS,N,W,E_5(d) sX2dO_1(d) s10dS,N,W,E_7

Fig. 4 Time-vertical cross sections of watertemperature at Imazu-oki from July 9th to August 8th,
2007.

Fig. 5 Time series of water temperature at a depthof 87.5m from July 2007 to March 2008.
Fig. 6 shows the vertical distribution of simulated
water temperature and vertical flow speed when thestrong westerly winds blew from 15th to 17th of Julyfor 3 days. When strong westerly winds started toblow (eastward), the surface water was driven to thecoast. Then, the water in the lower layer moved
against the wind, and the thermocline tilted (Fig. 6a).
As shown in Fig. 6b, when the thermocline tilted
toward the coast, the water flew downward in the
coast. After winds ceased, the thermocline returned tothe original position and tilted toward the opposite
position on the 19th of July as shown in Fig. 6a. With
the amplitude of the internal wave being larger, theeffect of the wave reached the bottom, and thestratification collapsed. Finally, vertical mixing wasenhanced in the bottom layer on July 23th-25th. Thissimilar phenomenon was shown in the observation.
When severe winds associated with the passage ofthree typhoons blew in 1993, the depth of the(a) s10dS,N,W,E_1

638

GEOMATE - Mie, Japan, Nov. 21-24, 2017

thermocline rose deeply. After the wind ceased, it
declined suddenly. This movement generated waves
that affected the deep layer. The observation showedthat the passage of this wave (It is called internal
surge) lead to the vertical mixing [7]. The internal
wave whose amplitude was larger than usual
generated by strong wind became larger duringmoving, and as the gratitude of the wave suddenly
became steep and nonlinear, the amplitude of the
wave was such a large one. The internal waves brokeat the boundaries, and enhanced the turbulence in thebottom layer, which resulted in mixing events.

predominantly in one direction, the rate of the verticalmixing changes by the wind direction. The rate of thevertical mixing possibly depends on the topographyof the bottom of the lake. Once the stratification
collapses, the water temperature at the bottom layer
increases more than the original temperature evenafter the overturning. It implies that strong winds canchange the water environment surrounding thebottom next year.
In this way, strong winds such as typhoons areenergetic enough to tilt the thermocline from its
original position. After the wind ceases blowing, thethermocline oscillates at a certain period of time.
Internal waves redistribute this energy over different
time and length scales. Wind driven currents andwaves play an important role in the weakening ofstratification and vertical mixing in the lake. Thesephenomena can influence the transport of substancessuch as dissolved oxygen and the resuspension ofbottom sediments.
REFERENCES[1] Matzinger A et al., “Eutrophication of ancient
Lake Ohrid: global warming amplifies detrimental
effects of increased nutrient inputs.” , Limnology andOceanography, Vol. 52, 2007, pp.338-353[2] Coats R et al., “The warming of Lake Tahoe.”,
Climate Change, Vol.76, 2006, pp.121-148[3] Livingstone DM, “Impact of secular climatechange on the thermal structure of a large temperate
central European lake.”, Climate Change, Vol.57,
2003, pp.205-225[4] Kishtawal C et al., “Tropical cyclone intensification
trends during satellite er, Geophysical Research Letters,
Vol.39 (10), 2012, pp.810.a (1986-2010).”[5] Knutson T et al., “Tropical cyclones and climatechange.” Nature Geoscience, Vol.3, 2010, pp.157-163.
[6] Saggio A, Imberger J, ”Internal wave weather ina stratified lake.”, Limnology and Oceanography,
Vol.43, 1998, pp.1780-1795[7] Hayami Y, Fujiwara T, Kumagai M, ”Internal
Surge in Lake Biwa Induced by strong Winds ofthphoon.”, Jpn. J. Limnol., Vol.57, 4(2), 1996, pp.
425-444[8] Akitomo K, Kurogi M, Kumagai M, “Numerical
study of a thermally induced gyre system in Lake
Biwa”, Limnology, Vol.5, 2004, pp.103-114[9] Webb EK, “Profile relationships: the log-linear
range, and extension to strong stability.” Quarterly
Journal of the Royal Meteorological Society, Vol.96,
1970, pp.67-90[10] Shrestha KL, Kondo A, “Assessment of theWater Resource of the Yodo River Basin in Japan
Using a Distributed Hydrological Model Coupledwith WRF Model.” Environmental Management ofRiver Basin Ecosystems, Part of the series Springer
Earth System Sciences, 2015, pp.137-160(a) Water temperature(b) Vertical flow speed
Fig. 6 West-east vertical cross sections throughImazu-oki for (a) water temperature and (b) verticalflow speed from July 15th to 25th in 2007 in thes10dE_3 case.
CONCLUSION
In the present study, we examined the effect ofstrong wind on the bottom layer by using a three
dimensional hydrodynamics model in Lake Biwa.
If the magnitude of the wind is strong enough, thestratification collapses and the wind can enhance thevertical mixing in the bottom layer even in summer
season with strong thermal stratification. In a
stratified season, when the strong wind blows639

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

IMPROVED EFFICIENCY AND FEASIBILITY IN DEVELOPINGREGIONAL SCALE OPTIMAL MULTIPLE OBJECTIVE SALTWATERINTRUSION MANAGEMENT STRATEGIES IN COASTAL AQUIFERSUTILIZING NEW SURROGATE MODELS
1

Alvin Lal1 and Bithin Datta1
Discipline of Civil Engineering, College of Science & Engineering, James Cook University, Townsville, QLD
4811 Australia
ABSTRACT

Coastal aquifers are hydraulically connected to the sea and therefore susceptible to saltwater intrusion problems.
This study proposes the utilization of a new surrogate model within coupled simulation-optimization (S/O) modelfor the management of groundwater use strategies in coastal aquifers subjected to density dependent saltwater
intrusion processes. The simulation of the transient 3-dimensional density dependent flow and transport model isbased on the solution of an implemented numerical simulation model. The simulation model is coupled with multiobjective genetic algorithm (MOGA) based optimization technique with specified objective functions andconstraints. Direct coupling of the numerical simulation model with MOGA is computationally expensive. Hence,the solution of the numerical simulation model with random input variables are used for training and testing the
support vector machine regression (SVMR) surrogate models for approximately simulating the flow and transport
processes. The performances of the new surrogate models are evaluated using various performance evaluation
criteria’s. The resulting validated SVMR surrogate models are coupled to the MOGA and implemented for an
illustrative coastal aquifer with an aim to develop efficient coastal aquifer management strategies. Based on theobjective functions, execution of S/O model presented a set of optimal groundwater withdrawal rates from thesimulated aquifer. It also ensured salinity levels at the designated monitoring wells are constrained within specified
limits. The efficiency of the new SVMR surrogate models is also demonstrated. Evaluation results suggested thatthe projected S/O model is an effective way to develop feasible and reliable coastal aquifer management strategies.
It also enhances the possibility of solving more realistic large scale problems and developing regional-scale coastal
aquifer management methodologies.
Keywords: Coastal aquifers, Density dependent flow and transport model, Multi-objective, Surrogate models
reliability and accuracy of surrogate model
incorporated S/O models are always questionable.
INTRODUCTION
Saltwater intrusion (SWI) is imposing long-term
The present study focuses on developing andthreat to the beneficial use of life sustaining
implementing robust support vector machine
groundwater resources in coastal areas. Sustainable
regression (SVMR) surrogate model assisted S/Oplanning and management of coastal aquifers aremodel for optimal coastal aquifer management.
decisive to ensure future sustainability of these fragile
In numerous surrogate model performance
resources. Simulation-optimization (S-O) models arecomparison studies, SVMR has been ranked as an
one of the widely used methods for developing
accurate and most efficient predictive modeler [12management methodologies for coastal aquifers14]. Despite several successful applications andsubjected to SWI. The present study demonstrates annumerous benefits, SVMR surrogate model has neverintegration of a new yet efficient surrogate model into
been used for predicting SWI into aquifers. It is fora coupled S-O framework for developing improved,
the first time, SVMR surrogate models are trained forand efficient optimal strategies for groundwateremulating a numerical costal aquifer flow andutilization from coastal aquifers.
transport simulation model FEMWATER [15] used
for predicting impact of variable groundwater
The S-O approach has been used to develop different
pumping patterns. The surrogate model is thencoastal aquifer management models [1-6]. In many
integrated into a multi-objective genetic algorithm
cases, due to enormous computational requirements(MOGA) optimization algorithm within the R2016aand time constraints, numerical simulation models in
MATLAB environment, to develop a multi-objective
an S-O model are substituted by surrogate models.
coastal aquifer management strategy.
Some of the common surrogate models used indeveloping aquifer management strategies via a S/Omodel includes Radial Basis Function [7], Artificial
METHODS
Neural Network [8, 9], Modular Neural Network
Coastal Aquifer Management Model for Optimal
Groundwater Utilization[10], and Genetic Programming [5, 11]. However, the640GEOMATE - Mie, Japan, Nov. 21-24, 2017

The proposed coastal aquifer management model was
designed to sustainably pump groundwater frominstalled production wells (PWs) and barrier wells(BWs) in the simulated aquifer system. PWs were
installed for withdrawing fresh groundwater fordomestic utilization whereas BWs were installed near
the shoreline for controlling SWI into the aquifer.
Pumping from BWs induces a steeper hydraulicgradient towards the sea, averting encroachment ofseawater into the aquifer [6]. Thus, two conflicting
objectives i.e. maximizing total pumping from PWs
and minimizing total pumping from BWs wereconsidered. Monitoring wells (MWs) were also
installed for salinity level monitoring purposes.
Limiting salinity levels at respective MWs within
specified limits were incorporated as constraints in
the SVMR-MOGA optimization framework. The
mathematical expressions of the conflicting objectivefunctions, constraints and bounds [16] are given by;density dependent coupled groundwater flow andtransport processes in an aquifer system. An
illustrative study area containing of a portion of amulti-layered coastal aquifer was modelled using
FEMWATER. The length of the coastline (sea sideboundary) was 2.13 km and the other two boundaries
were of 2.04 km (Boundary A) and 2.79 km(Boundary B) respectively. The 2.53 km2 study area
incorporated 5 BWs, 8 PWs and 3 MWs. The study
area with specific well locations are presented in Fig.
1.
Boundary A
PW7
BW5

PW4
MW3

MW2
BW3

Maximize,

PW8

PW3

BW4

PW5

PW2

MW1

PW6

PW1

BW2

Minimize,

Constraints
Bounds

BW1

Figure 1: Illustrative study area with specific PW,
BW and MW locations after [16].

,∀,The sea side boundary was assumed to be a constanthead and constant concentration boundary having a
concentration of 35000 mg/L. The other twoboundaries of the study area were taken as no-flow
boundaries. The modelled aquifer was discretized
into triangular finite elements having an averageelement size of 150 m. The element size near thewells were set to 75 m. The total aquifer depth was 60
m, divided equally into 3 layers. A constant verticalgroundwater recharge of 0.00054 m/d was specified
over the entire study area. The screening interval of
all the wells were taken from the second and thirdlayers of the aquifer. The compressibility and velocity
of water was taken as 6.69796 X 10-20 md2/kg and131.328 kg.md respectively. Other key parameters
used for aquifer simulation are listed in Table 1.

denotes pumping from nth PW at tth time anddenotes pumping from the mth BW at tth time.
represents the saline concentration at the ithmonitoring well at the end of management time
period.
, symbolizes the surrogate model
replacing the numerical FEMWATER model andconstraint (3) denotes coupling of the surrogate model
within the S-O framework. M, N and T are the total
number of PW, BW and total number of time steps in
the management model. Inequality (4) represents theconstraints imposed to keep salinity concentrations
within specified limits at the respective MWs.
Inequality (5) and (6) represents the upper and lower
bounds of pumping from PWs and BWs respectively.
Pumping bounds for both the PW and BW was set
between 0 – 1300 m3/day. The constraints imposed aspermissible limits on concentrations (assumed to be aconservative pollutant) were
, of 425
mg/L at MW1,
of
510
mg/L
at
MW2 and
,
of
625
mg/L
at
MW3.
,

The 3D transient simulation was instigated from an
initially steady state condition of the aquifer,achieved via constant pumping of 300 m3/day from 3of the PWs for a period of 20 years only. The resulting
heads and salinity concentrations after 20 years wereused as initial conditions for the specified period of 4
years (4th time step) where pumping from all
production and barrier wells were instigated.

The Numerical Coastal Aquifer Simulation Model
The 3D numerical simulation FEMWATER model
was used for simulating pumping induced SI
processes into an illustrative costal aquifer system.
FEMWATER model (FM) allowed simulation of641

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1: Key
development

parameter

Properties

x direction
y direction
z direction

Hydraulic
Conductivity

Bulk density
Longitudinal dispersivity
Lateral dispersivity
Molecular dispersion coefficient
Density reference ratio
Soil porosity
Compressibility

valuesfor

model
where ɣ is the parameter of the kernel
andrepresenting
function withindependent variables. Key parameters that
control SVMR problems are the cost function , theradius of the insensitive tube ɛ and the kernelparameter. These parameters are dependent on eachother so altering the value of one parameter leads to achange in another parameter. For the present study,
Gaussian kernel was used, with ɛ, and ɣ having avalue of 0.60, 6.49 and 0.001 respectively. Evaluatingother values of these fundamental parameters werebeyond the scope of this study, although, otherparameter values may have provided more accurate
results.

Values
15 m/d
7.5 m/d
1.5 m/d1600 kg/m3
50 m/d25 m/d0.69 m2/d
7.14x10-70.46
8.5x10-15 md2/kg

Development of Support Vector Machine
Regression Surrogate Models
SVMR methodology is a statistical tool employed fornumeric data prediction utilizing support vector
machines (SVM). SVMs have been applied in various
engineering fields because of its attractive
featuresandencouraging
empirical
performance [17]. A comprehensive discussion
on SVM is presented in [18-20] and only a brief
theoretical background is given below. For a given
training dataset,
whereis the ith input
pattern and is the parallel target output and Є .
The aim of the SVMR is to find a function
thathas most ɛ deviation from the targets
for alltraining data, and also is at flat as possible [21]. A SVM
takes advantage of the kernel function to
map the input data onto a high-dimensionalfeature space. Later, linear regression is
performed in the high-dimensional feature
space. As a result, non-linear problems are
addressed in a linear space through nonlinear
featuremapping.
The
final
prediction function used by an SVM is:

500 data sets were generated out which 400 was used
for training and 100 were used for testing the trained
SVMR models. The training set was used to construct
the SVMR models while the testing set assessed theprediction capabilities of the trained model. 500
transient pumping (inputs) were obtained from
uniform sampling distribution using Latin Hypercube
Sampling (LHS) having an upper bound of 1300
m3/day and lower bound of 0 m3/day. The resulting
salt concentration at each monitoring well wereobtained from FEMWATER simulation after each setof pumping from all production and barrier wells are
fed to the model as inputs. Each FEMWATER
simulation took approximately about 4-5 minutes toconverge. 500 sets of pumping and resulting output
concertation were assembled by running thesimulation model 500 times. These input-output
patterns were used for surrogate model training andtesting purpose. The SVMR models were constructedto learn from the training data presented to them with
the intent of capturing the functional relation between
the pumping-concentration data sets. 3 SVMR
surrogate models namely M1, M2 and M3 wereconstructed for predicting salinity concentrations at
MW1, MW2 and MW3 respectively.

,

where
is Lagrange multiplier, and is afeature vector corresponding to a training
object. The components of vector
and theconstant b are optimized during training.
is penalty factor, which regulates the trade-off
between the flatness of and the extent up to which
deviations greater than ɛ can be accepted. The
kernel function is one of the most importantparts in the SVMR model. Commonly usedkernels are linear, Gaussian, polynomial
and sigmoid. The Gaussian function kernel
is the most commonly used kernel because ofits
effectiveness
and
speed
[17].
Mathematical expression of the Gaussianfunction is given by:
,

ɣ|

.

Performance Analysis of Surrogate Models
The prediction capabilities of the developed SVMR
surrogate models were measured using performance
evaluation indices (PEI’s). Mathematical expressionsof these error estimates are presented from Eq. (9) to
(12).

∑
∑

|

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∑

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 3 presents the simulated coastal aquifer utilizing
1 set of PW and BW pumping.

∑∑

Boundary A

where
and
are observed (from FM) andpredicted values of saltwater concentrations
andare observed and predicted
respectively,
saltwater concentration mean values respectively, andrepresents total data points.
Linked simulation-optimisation approach
The trained and tested SVMR models were used in
the S/O model as a set of binding constraints forsalinity concentration prediction purpose. Multiobjective Genetic algorithm (MOGA) was used as an
optimization tool. MOGA has been used efficiently
in solving multi-objective optimization problems [5,16]. When using MOGA optimization tool,
population size was set to 1500, with 5200
generations, crossover fraction of 0.8 and mutation
probability of 0.02. A flowchart for the linked
surrogate assisted S/O framework in given in Fig. 2.

Figure 3: Salinity concentration contours after aperiod of 4 years (1460 days) using a set of transient
pumping pattern.
The numerical coastal aquifer flow and transportmodel was executed 500 times with each run having
different transient pumping values. The obtained
pumping-concentration datasets were used to train
and test the SVMR surrogate models.

S/O Model

Start

SVMR Model Prediction Capabilities
The error estimates during the training and testing
phases are given in Table 2.

MOGA

Random population
generation

Table 2: Performance evaluation results
Phase

Tested SVMR
surrogatemodels used as
approximate
simulator

Fitnessfunction
evaluation

GA
Operators

Training

Testing

Pareto-optimal
Solution

FEMWATER
Simulation Model

PEI’s
MSE
RMSE
R2
NSE
MSE
RMSE
R2
NSE

M1
0.164
0.405
0.997
0.99
0.202
0.449
0.994
0.99

M2
0.057
0.238
0.997
0.99
0.105
0.323
0.993
1.00

M3
0.184
0.428
0.989
1.00
0.187
0.432
0.989
1.00

The performances of the SVMR models at thetraining and testing phases for M1, M2 and M3 interms of the 4 evaluation criteria showed similar
trends. RMSE, and MSE values for concentrations at
M1, M2 and M3 at both the stages were substantiallysmaller. During the training stage, SVMR model has
a smallest RMSE value of 0.238 accomplished for M2
and highest RMSE of 0.428 attained for M3.
Comparing RMSE values of SVMR models at thetesting stage, the lowest 0.323 is obtained for M2 andhighest value of 0.449 is achieved for M1.
Accordingly, MSE values of the SVMR models arecomparatively smaller. R2 and NES values do notsignificantly differ for the three models and havevalues close to 1. NSE value of 1 presents a perfectestimate with no errors [22]. A model can beconsidered accurate if the calculated NSE value isgreater than 0.8 [23]. The NSE values for M1, M2 andM3 were greater than 0.8 indicating that it can reliably
be used for SI prediction. A model’s good
performance in the testing phase is an indication of
its accuracy in prediction and hence its practical

Validation

Stop

Figure 2: Flowchart for the linked S/O model with
optimal solution validation stage.
RESULTS AND DISCUSSIONS
Coastal Aquifer Simulation Model

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

utility [24]. Hence, the observed good performance of
SVMR models at the testing stage establishes its
credibility, suggesting accurate results when used forprediction purposes.

Table 3: Optimal pumping solution validation results

Optimal Groundwater Pumping Solution Set
After evaluating the prediction performances, the M1,
M2 and M3 replaced the original FEMWATER modelin the S-O framework instituted for obtaining optimal
groundwater pumping rates from the PWs and BWs
installed in the simulated coastal aquifer. The
execution of the SVMR-MOGA coastal aquifer
management model presented a set of optimal
pumping solution. The resulting Pareto-front from theexecuted S-O model is given in Fig. 4.
Total BW Pumping (m3/day)

700
600
500
400

200
100
29500

30500

, at
MW2 ≤ 510
mg/L
SVMR
FM

, at
MW3 ≤ 625
mg/L
SVMR
FM

1

423.8

422.9

509.2

507.9

624.2

623.9

2

424.5

423.5

509.4

508.3

623.6

622.1

3
4

423.2
425.0

422.2
425.3

508.9
508.4

506.5
508.9

624.6
623.1

623.5
622.6

5

424.7

423.6

509.4

508.3

624.7

622.0

Conclusion
This paper presents an efficient and feasible SVMR
model assisted coupled S/O model for the optimal
sustainable management of coastal aquifers subjected
to SWI. The S/O model maximizes pumping from
PWs, and minimizes pumping from BWs while
maintaining salinity concentrations at respective
MWs within specified limits. Utilized SVMR
surrogate models have effectively approximateddensity-dependent SWI processes in the simulated
aquifer. Hence, SVMR models efficiently predictedsalinity concentrations at monitoring wells in
response to variable transient pumping patterns. The
execution of the developed management model
presented a set of optimal pumping patterns for boththe PWs and BWs. An optimal pumping solution set
can be chosen and implemented for the sustainableutilization of the modelled coastal aquifer. The
implementation of the developed management modelhas the potential to aid in developing regional-scale
coastal aquifer management strategies while ensuringcomputational efficiency, thus making it feasible toaddress much larger study areas. In future, it would
be beneficial to compare the prediction performancesof SVMR with other available surrogate modelling
methods and also apply the established management
model on a real case study area.

300

28500

, at
MW1 ≤ 425
mg/L
SVMR
FM

It was observed that the salinity concentration values
from both the modelling tools were very close to eachother. It was also observed that the optimal pumping
values satisfied the specified concentration
constraints at monitoring locations. Also, the optimal
solutions converged to the specified upper bound of
the concentrations constraint. The validation results
established that the SVMR surrogate models
predicted the salinity concentrations at MWs
accurately and can be utilized for developing coastal
aquifer management strategies.

800

0
27500

Sol.

31500

3

Total PW Pumping (m /day)Figure 4: Optimal Pareto-front from the executed
SVMR-MOGA model
Depending on the relative importance each of the two
objective functions in the management model, a set ofpumping solutions can be chosen and implemented
for optimal and sustainable utilization of groundwaterfrom the simulated aquifer. The selected optimal
pumping solutions from the Pareto-front will ensure
optimal pumping and maintaining salinity levels at
the MWs within specified limits which was the major
aim of the proposed management model. The Pareto
optimal solutions also show the conflicting nature of
the two objectives. For example, if the pumping for
beneficial use increases beyond 30500 m3/day, themarginal increase in barrier well pumping increases
exponentially.
Validation of Optimal Pumping Solutions
To establish the validity of the resulting optimal
solution, the salinity concentration obtained from the
SVMR surrogate models were compared with thesalinity concentration obtained from the original FM.
Five random solutions from the optimal Pareto-front
were chosen and the salinity comparison results arepresented in Table 3.

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pp. 182-190, 2014.
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646

Seventh International Conference on Geotechnique, Construction Materials and21-24, 2017, ISBN: 978-4-9905958-8-3 C3051
GEOMATE -Environment,
Mie, Japan, Mie,
Nov.Japan,
21-24,Nov.
2017

WATER POLLUTION OF KAMATANI-RIVER BASIN
IN YOKKAICHI
Sachie Takeuchi1. Masaaki Takahashi2, Yukimasa Takemoto2, Maki Oyagi2, Satoshi Chiba2, Yuzou
Morikawa2, Jia Zhou3, Kunihide Miyaoka3, Kaoru Ito4, Takanori Terazawa5
1

Faculty of Medicine, Mie University, Japan, 2Faculty of Information and Environmental Sciences, Yokkaichi
University, Japan, 3Faculty of Education, Mie University, Japan, 4Yokkaichi Kanngo Iryou University, Japan,
5
Mie Prefectural Environmental Conservation Agency, Japan
ABSTRACT
Kamatani-River is a small river which flows down from the Suzuka mountain chain to Ise Bay though thewestern part of Yokkaichi-Shi. In the catchment area of this river, tea plant fields spread widely, and some waste
disposal sites and a cow farm have been constructed. In order to find the influence of this land use on the riverwater, our investigation was carried out. Some polluted water from these disposal sources was found whichcontains high values of COD, phosphorus, D-Fe, D-Mn and nitrogen compounds. Especially significant nitrogen
pollution has been widely found. The main sources of the nitrogen compounds is considered to be related to thetea plant fields which are widely spread in this area.
Key word: Nutrients, Nitrogen compound, Land-Use, Kamatani-river
Suzuka-River), later, flows down to the Suzuka-River.
The catchment area of the Kamatani-River distributes
long and narrow from the source till the downstreamof the river, therefore, the influences of the waste
water from these disposal sites is consideredsignificant compared to other rivers. Therefore,
environmental counter measure are very importantmatter [1], and became an important concern in thecommunity of the drainage basin. In order to help
them, we investigated the water pollution in
Kamatani-River and around the catchment area [2].

INTRODUCTION
Yokkaichi-Shi is well know as one of theindustrial city, and also has very wide diluvial hill in
the west part, there are cultivated many tea plant
fields from the old times because of its warm climate,which is good for them. Recently, a waste disposalsite and stock farm were made in advantage of thegeometrical condition, and their influence on theenvironment around them is considered serious
matter.
Kamatani-River (extension: 20km) is one of thesmall branch rivers of Suzuka-River which flows
down to Ise-bay through this area. Kamatani-River
unites the Utsube-River (other branch rivers of the
The investigation was carried out at 14 sites
shown in Fig.1 from the year 2014 till 2016 (threetimes in year). The investigation sites from St11 toSt16 and St3, St8 are situated at the main stream of
the Kamatani-River (St11 is situated at the upperstream, and St16 is situated at the most down-streamof the river). St5 and St6 are leaching water from thetea plant fields. St2 is situated at the waste disposalsite (damping finished about 10 years ago), St4 issituated at the drainage of the cow farm. St7 and St9
are the leaching water near of the dumping site of theconstruction waste soil.

METHODS
Investigation Site and Date
Parameter and Analytical Method
Parameter and analytical method is listed below.
pH: glass electrode, EC: Platinum electrode, COD:
acidic manganese method, NO3-N: ultra purple lightabsorbance method, PO4-P: Molybdenum blue
method.
As a simple method, D-Fe, D-Mn, NH4-N,
NO2-N, Cl ion were tested using Simplified
chemical analysis product for water quality(Kyoritsu Chemical-Check Lab., Corp.).

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Suzuka-mountain

NagoyaYokkaichi
Suzuka-River

Kamatani-RverIse Bay

Utsube-River

Fig. 1

Investigation site (Using Yahoo Map)
tends slightly to be increased toward downstream (St
8 to St15, shown in Fig 2). The concentrations of the
NO3-N were low at upstream of the river, andincreased toward the down-stream till St8, later, theconcentrations tend to decrease toward St16. At St5
or St6, where water is flown out from the tea plant
fields, high concentrations of NO3-N were found, andat St2, St4, high concentrations of NO3-N were also
found. These values are higher than the main streamof the river (Fig 3). The concentrations of PO4-P werelow (under 0.1mg/L) at most of all monitoring
stations except for St4 (as mentioned before),
however, the concentrations were slightly increased
toward St 8 to St15 and St16 (Fig 4).

RESULT and DISCUSSION
Pollutants
High values of NH4-ion, Cl-ion and D-Fe were
found at St2, however, these pollutants were notdetected in the down-stream of the river, and theinfluence from the disposal site is considered to besmall. High concentration of PO4-P was found at St4,
and was considered to be come from cow farm. These
pollutants were not found at the downstream nearby,
therefore, this influence was considered to be small.
High values of COD were also found at St2, St4 andSt9, however, COD values of the main stream are low
compared by other rivers in Yokkaichi [3]. COD

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GEOMATE - Mie, Japan, Nov. 21-24, 201750
452014 Jun.

40

2014 Nov.

35

2015 Jun.

30

2015 Nov.

25

2016 Feb.

20

2016 Jun.

15

2016 Nov.

10
5
0

St11St12St13 St3 St8 St14St15St16(Upper)Fig.2

Main stream

St2 St4 St7 St9(Down)

St5 St6

Leaching-water

COD at the monitoring stations

30
25
20

2014 Jun.

2014 Nov.

2015 Jun.

2015 Nov.

2016 Feb.

2016 Jun.

2016 Nov.

15
10
5
0

St11 St12 St13 St3 St8 St14 St15 St16

(Upper)Fig 3

Main stream(Down)

NO3-N concentration at the monitoring stations

649

St2 St4 St9

St5 StLeaching-water

GEOMATE - Mie, Japan, Nov. 21-24, 2017

2.5
2014 Jun.

22014 Nov.
2015 Jun.

1.5

2015 Nov.
2016 Feb.

1

2016 Jun.
2016 Nov.

0.5
0St11 St12 St13 St3 St8 St14 St15 St16

(Upper)Main stream

St2 St4 St7 St9(Down)

St5 St6

Leaching-water

Fig.4 PO4-P concentration at the monitoring stations

considered to be related to the tea plant field. In orderto clarify the mechanism, further investigation about
the flow of nitrogen compounds is needed. It wasusual that the outstanding pollution of COD and
PO4-P was not found in main stream of the river.
Usually, pollution of nitrogen and phosphorus isrelated to each other, therefore, further investigationon the source of the nutrients will be needed.

Land UseIn this investigation, high concentrations of the
NO3-N were found, and in order to find a nitrogenflow, land use was investigated using aerial
photography [4]. The land use was analyzed in about
4 areas (Fig. 5) with 7 categories as a forest, tea
plantation, rice field, farm land, residential area, lakeand others (Fig.6).
Area 1: The upstream of St11, where most of the area
is covered by forest (Space: 1.45km2). Area 2: The
catchment area of St12 to St13, in where the area ismainly covered by tea plant fields and forest (Space:
2.43km2). Area 3: The catchment area from St13 toSt14, The half of the area is covered by tea plants andforest, and others are occupied by others (Space:
4.76km2). Area 4: The catchment area from St14 to
St16, where, the area is mainly covered by rice fields(Space: 2.35km2). From the result, concentrations of
the NO3-N increased in Area 2 and Area 3 where tea
fields spread widely, and NO3-N pollution is

CONCLUSION

In this investigation, high concentrations of
NO3-N were found in the Kamatani-River basin,suggesting the possibility of being a source of thenitrate pollution of the Suzuka-River [5-6]. The main
source of the NO3-N is reconsidered to be related tothe tea plant fields by the analysis of land use.
Contrarily, COD and PO4-P were only slightly foundin the main stream, and the mechanism of the nutrient
flow from these sources should be much moreinvestigated.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

St11

Catchment area

Area1
Area2

St13
Area3
St14

Area4

Fig. 5St16Situation of the investigated area

100%
Others80%

Lake and pond

60%

Residental land
Farm field40%

Rice field

20%
0%

Fig. 6

Tea plantation
Forest
Area1

Area2

Area3

Area4

Land use of the research area

Zhou, Kunihide Miyaoka, Kaoru Ito, Takanorii
Terazawa “Water pollution of the Kamatani
River in Yokkaichi” Yokkaichi University
Journal of Environmental and Information
Sciences Vol 20, No2, 2017, p31-p38.
[3] Yukimasa Takemoto, Peng Guo, Masaaki
Takahashi “Water Quality Analysis andEnvironmental Education (Ⅱ)” Yokkaichi
University Journal of Environmental andInformation Sciences Vol 16, No2, 2013,
p51-p72.

REFERENCE[1] Sachie Takeuchi, Yukimasa Takemoto, Masaaki
Takahashi, Maki Oyagi, Yuzou Morikawa, Jia
Zhou, Kunihide Miyaoka, Kaoru Ito, Takanorii
Terazawa “Water pollution of the Kamatani
River in Yokkaichi” The proceedings of the 42nd
annual conference of Japan Association ofEnvironmental Science, 2016, p124-p125.
[2] Yukimasa Takemoto, Masaaki Takahashi, Sachie
Takeuchi. Maki Oyagi, Yuzou Morikawa, Jia

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GEOMATE - Mie, Japan, Nov. 21-24, 2017[4][5]

Yahoo Map: https:// map. yahoo. co.jp.
Yokkaichi University “Information System on
the River using Internets GIS System” Thereport of Heisei 14 Nendo Cooperative Research
with
University
andMie
Prefectural
Government, 2003, p4-p8.
[6] Mie Prefecture “Anural Report on Environment in
Mie Prefecture” 2016.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

COMPARISON OF DIFFERENT VEGETATION INDICESFOR ASSESSING MANGROVE DENSITYUSING SENTINEL-2 IMAGERY
Firman Farid Muhsoni12*), A.B Sambah34, M. Mahmudi3), D.G.R Wiadnya3)
Marine Science Department, University of Trunojoyo Madura,
Jl.Telang, Bangkalan, Madura 69162, Indonesia
2
Post-Graduate Program, Faculty of Fisheries and Marine Science, University of Brawijaya
Jl. Veteran 65145 Malang, Indonesia
3
Faculty of Fisheries and Marine Science, University of Brawijaya
4Marine and Fisheries Resources Exploration & Management Research Group,
Brawijaya University, Jl. Veteran 65145 Malang, Indonesia
1

ABSTRACT
Vegetation mapping provides important information for understanding ecological condition throughcalculation of vegetation density. It based on vegetation indices developed through algorithms of mathematicalmodel within the visible and near-infrared reflectance bands. The indices is an estimate of either leaf density per
species, or vegetation types, respectively. This study aimed to evaluate those indices and find best algorithm
using Sentinel-2 satellite image. Twenty four algorithms of vegetation indices were analyzed for mangrove
density mapping, i.e., BR, GNDVI BR, GR, SAVI, MSAVI, NDRE, NDVI, NDVI2, NDWI, NNIP, PSRI, RR,
RVI, VIRE, SVI, VIRRE, MTV1, MTVI2, RDVI, VARI, VI green, MSR, and TVI. During pre-processing
stage, digital number of Sentinel-2 image was converted into radiance and reflectance value. The analysis
resulted in three algorithms that provide highest accuracy, i.e., MSR (Modified Simple Ratio), NDVI(Normalized Difference Vegetation Index) and RVI (Ratio Vegetation Index). All the three methods provided
comparable R2 (0.860, 0.859, and 0.850, respectively). Sentinel-2 satellite image may best using one of those
three algorithms, especially applied for mangrove vegetation.
Keywords: Vegetation Indices, Sentinel-2 Imagery, Mangrove Biomass
vegetation. The increase of carbon in the atmospherecaused by the damage or forest fire. More than 50%of the world's mangroves have been destroyed, in thepast two decades 35% of damage caused by coastal
cultivation and development [7]. Mangrove damage
has resulted in the contribution of carbon
sequestration in the atmosphere [8]. Mangrove area
is only 0.7% of the area of tropical forest, butmangrove destruction will supply 10% of CO2 fromthe mangrove deforestation [9].
Remote Sensing, flowed by the application of
GIS provide quantitative information to investigate
the spatial distribution of vegetation, including
mangrove forests in coastal area [10]. The
application of satellite image analysis has been
applied in various ways to illustrate mangrove
ecosystems. Some of the published study includes
mapping the distribution of mangrove in coastal
area, observing mangrove species by ground survey
combination, and estimates it structure such as leafarea, canopy height, and biomass [11].
Satellite imagery data is one of the basic
information that could describe the location of
deforested or degraded area, also healthy vegetation.
Satellite remote sensing approach, due to its

1. INTRODUCTION
Global warming becomes a global issue. It leads
to climate change, due to an increase in atmosphericgas or so-called greenhouse gases. Greenhouse gases
occur due to accumulation of carbon in atmosphere
accumulation due to burning of fossil fuels (theactivity of vehicle and industry) [1].
Mangrove has a function as a carbon sink,although the information and data are still relatively
minimal [2]. Mangroves are also called mangroves
for tree or shrub communities that grow on the
coastal area, or are applied to one type of vegetation
species [3]. Mangrove is an intertidal plant foundalong tropical and non-tropical coastlines [4]. This
plant is inundated by tides in the brackish area andhas physiological adaptations to salinity [5].
Mangrove ecosystem stored the highest carbon,
compared to tropical forests, subtropical forests andboreal forests. Much of the carbon stored in the richorganic underground [5],[6]. Mangroves store
carbon four to five times faster than tropical forests[5]. Climate change is closely related to theexistence of forest biomass. Biomass plays a role inthe carbon cycle. Forest carbon is stored in forest
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 2.

synoptic, multi-temporal, and multi-spectral ability
can effectively act as one of methods in providing
reliable information on mangrove extent and statusof its growth along the coastal areas. The reflectancepattern of the vegetation in red-visible & near infrared spectral region illustrated the density of allvegetation coverage in coastal area.
Moreover, earth observation satellite like Landsat
satellite was commonly apply to define the
distribution and density of the mangrove forest [12].
In addition to some satellite applied in vegetation
density mapping, Sentinel-2 satellite is a relatively
new satellite that is assumed can be use in mapping
the spatial distribution of vegetation. Sentinel-2 is a
European wide-swath, high-resolution, multispectral imaging mission. The full mission
specification of the twin satellites flying in the same
orbit but phased at 180°, is designed to give a highrevisit frequency of 5 days (temporal resolution) at
the Equator [13]. In this study, we analyze Sentinel2 satellite imagery to investigate and evaluate thedensity of mangrove forest by calculation of several
vegetation indexes.
Vegetation
mappingprovidesvaluable
information for understanding the natural and manmade environment. It is important to obtainvegetation cover in the framework of vegetation
protection and restoration programs [14]. Mangrove
ecosystems have tremendous relevance to theecological and economic conditions for conservation
and restoration measures. The latest information
concerning the extent and condition of mangrove
ecosystems is essential for management, policy
process and decision making. This can be solved
using remote sensing technology [15]. The
vegetation index approach in remote sensing iscommonly used for vegetation mapping [16]. The
vegetation index has calculated the vegetation
density of green leaf and specifically for vegetation
species. The purpose of this study was to evaluate
the different vegetation indexes that collected fromthe Sentinel-2 satellite image analysis.

Table 1. Sentinel-2 band spesification [4]
No

Band

1
2
3
4

Band 2 – Blue
Band 3 – GreenBand 4 – Red
Band 5 – Vegetation
Red Edge
Band 6 – Vegetation
Red Edge
Band 8 – NIR
Band 8a – Vegetation
Red Edge

5
6
7

Wave
length
(µm)
0.490
0.560
0.665
0.704

Spatialresolution
10m
10m
10m
20m

0.740

20m

0.835
0.865

10m
20m

Figure 1. Sentinel-2 10 m spatial resolution bands:
B2 (490 nm), B3 (560 nm), B4 (665 nm) and B8(842 nm) [4]2. MATERIALS AND METHODS

Figure 2. Sentinel-2 20 m spatial resolution bands:
B5 (705 nm), B6 (740 nm), B7 (783 nm), B8a (865nm), B11 (1610 nm) and B12 (2190 nm) [4]2.1. Satellite Remote Sensing Data

2.2. Rodiometry Corrections

Sentinel-2 satellite images (Copernicus
Sentinel data (2017)) were used in this study in thecalculation and mapping of mangrove distribution.
The Sentinel-2 satellite has 13 spectral bands fromnear-infrared to shortwave infrared. Spatial
resolution varies from 10m - 60m depending onspectral band [17]. Sentinel 2 image used in thisresearch was December 6, 2016. The bands used inthis study were band 2, 3, 4, 5, 6, 8, 8a, withspecifications as in Table 1. Moreover, theillustration of Sentinel- 2 spectral bands for 10m and20m spatial resolution as described on Figure 1 and

The radiometric correction uses the at-sensor
reflectance method by changing the pixel value tothe radiance-sensor. Then converted to at-sensor
reflectance, with the following formula [18]:
(1)
/

(2)

Where, Lᵪ is the radiance value; BV is
Brightness Value; And Offset, Gain from themathematical calculation of maximum-minimum
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

spectral radiance value in image metadata. The
radiance value is changed to the at-sensor
reflectance value based on the equation:
∗



∗



(3)

d = 1 – 0,01674 cos (0,9856(JD – 4))

(4)

∗

(13)

10

NNIP (Normalized Near Infrared) [19]
(14)

11

PSRI (Plant Senescence ReflectanceIndex)[29]12

RR (Red Ratio) [21]13

RVI (Ratio Vegetation index) [30](15)

Where: ρP = the value of at-sensor reflectance;Lᵪ = radiance value (Wm-2sr-1μm-1); Π =3,142857142857143; D = distance of earth-sun(astronomical unit); ESUNᵪ = spectral irradiance sunvalue (Wm-2μm-1); Ɵs = angle sun zenith (degree);
JD = Julian Day.

(16)

14

2.3. Transformation of Vegetation Index

15

The vegetation index method that used isstructure vegetation index. The vegetation index
method was also adapted to the images band spectralof Sentinel-2 images used in this study. The
vegetation index used in mapping of mangrove
distribution in this study is described in table 2.

16

17

Table 2. An appropriate vegetation index for
Sentinel image 2
18

No
1

Indeks Vegetasi
BR (Blue Ratio)[19]2

GNDVI (Green normalized difference
Vegetation index) [20]

, ∗

(5)

19

20

GR (Green Ratio) [21]SAVI (Soil-Adjusted Vegetation Index)[22], [23]
.

5

∗

21

(8)

.

22

∗

6

7

,

(23)

RDVI (renormalized difference vegetationindex) [23]/(24)

VARI (vegetation atmosphericallyresistant index)[33]
VI green [33]
(26)

(9)

23

NDRE (Normalized difference Red-Edgeindex) [25].
(10)
NDVI (normalized difference vegetationindex)[26],[27],[20]MSR (Modified Simple Ratio) [32]
.

24

(27)

TVI (triangular vegetation index) [30]
. ∗
∗
∗
(28)

NDVI2 (normalized difference vegetationindex) [26]Description: Blue (B), Green (G), Red (R), Nearinfrared 1 (NIR1), Near-infrared 2 (NIR2), Red
Edge 1 (RE1), Red Edge 2 (RE2).

(12)

9

∗√

∗

(11)

8

. ∗
∗

(25)

MSAVI(modiﬁed SAVI) [24]
∗

, ∗

, ∗

∗

(7)
4

, ∗

(22)
MTV 2 (Modified Triangular Vegetation
Index2)[32]
. ∗

(6)
3

(17)
SVI (Sentinel Improved Vegetation Index)
[19]
(18)
VIRE (Vegetation Index based on
RedEdge) [19].
(19)
VIRRE (Vegetation Index Ratio based on
RedEdge) [19](20)WVVI (WorldView Improved VegetativeIndex) [31](21)
MTV (Modified Triangular Vegetation
Index1) [32]

NDWI (Normalized Difference Water
Index) [28]655GEOMATE - Mie, Japan, Nov. 21-24, 2017

than differentiate the type of vegetation. The initialstages of the study began with radiometric correctionof sentinel-2 images. Radiometric correction was
done by converting radian value to at-sensor
reflectance. Corrected image then analyzed thevegetation index through the calculation of 24 typesof vegetation index (see Table 2). The result ofvegetation index analysis is presented in Table 3.

2.4 Estimation of Mangrove Biomass
Estimation of mangrove tree biomass in thisstudy was conducted using allometric equations.
Allometric equations for above ground biomass[34]; [35] are:
W=0.168**(DBH)2.471(29)

Table 3. Analysis Results 24 Types of Vegetation
Index.
No Index
Min
Max
Mean
Stdev
vegetasi
1
BR
-8.79
5.13
-4.56
1.10
2
GNDVI -0.09
0.52
0.35
0.07
3
GR
0.80
1.32
1.16
0.08
4
SAVI
-5943.
30299. -2.02
230.233100
5
MSAVI -0.23
0.66
0.49
0.08
6
NDRE
-13367. 10940. -4.40
201.74
00
00
7
NDVI
-0.07
0.59
0.41
0.09
8
NDVI2 -2442.
2449.
1.56
24.39
56
00
9
NDWI
-0.52
0.09
-0.35
0.07
10 NNIP
0.30
0.63
0.53
0.04
11 PSRI-107.94 10.88
0.05
0.91
12 RR
-1138.
144.26 -2.19
12.31
47
13 RVI
0.87
3.86
2.48
0.44
14 SVI-2442.
2449.
1.56
24.39
56
00
15 VIRE-15.230.0005 0.0017 0.14
16 VIRRE -829.
75.02
-0.82
9.25
78
17 WVVI-4546.
25214. 5.21
310.652000
18 MTV-6573-13520. 24856. 5439.4
4.08
64
80
0
19 MTV2
-4.59
-0.48
-1.22
0.41
20 RDVI-0.0000 0.0000 0.0000 0.0000
522
521 VARI
-0.19
0.33
0.17
0.08
22 VI
-0.11
0.14
0.07
0.03
green
23 MSR-0.001
0.02
0.01
0.003
24 TVI-1369
101924 572097 160378
40.00
0.00
.59
.89

Meanwhile, biomass measurements below groundlevel [5]; [35] are:
(30)

.

∗ .

∗

,

Description:
W = above ground level biomass, B = below groundbiomass (kg),  = Wood density (g / cm3), DNH =diameter at breast height (cm).
Finding the best vegetation index was done by
non-linear regression statistical analysis between
biomass and vegetation index values. The result of
non-linear regression analysis is the coefficient ofdetermination (R2) to determine the best vegetationindex in estimate of mangrove biomass. The best
regression equation is used to estimate mangrove
biomass.
2.5. Study Area
This research was conducted in Majungan
Village, Pademawu Sub-district, Pamekasan
Regency. This location is located at the Madura
Island which is part of East Java Province. The
boundary of the study area is the coordinates of113029’48”-113031’24” E, 7013’48”-7015’12” S.

Field measurements were carried out to obtainbiomass values of mangrove trees, i.e. above groundbiomass values and below ground biomass values.
Sampling point field measurement as on the map
Figure 4.
Based on the results of field measurements,
biomass mangrove for above ground biomass of 382
kg/100m2, below ground biomass was 352,7
kg/100m2 and total biomass was 735 kg/100m2. In

Figure 3. Map of Research Location
3. RESULTS AND DISCUSSION
In this study, the mangrove area was separated
by other land cover. The process of mangrove
masking was done due to the vegetation index wasapplied to detect canopy density variation, rather
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

this study for soil biomass is not taken into account.
Table 4 describes the minimum and maximum
values of mangrove biomass measured in the field.

much dispersion is explained by the prediction. The
value of zero means there is no correlation at all,while the value of 1 means the dispersion of theprediction equals the observation. A good R2 value
approaches 1.0 [36].
The Kolmogorov-Smirnov normality test was
performed before the independent variable used was
normally distributed against the dependent variable
or not. Normality test results will show normal
distributed data when the value of significance on
skewness ratio, and the kurtosis ratio is in the range 2 to 2. Based on statistical analysis of skewness ratio
and the kurtosis ratio value, 24 vegetation index isspanned between -2 to 2, only 3 Vegetation indexes
greater than 2, i.e. SAVI, NDVI2 and SVI.
Table 5. Regression results of 24 vegetation indexes
with R2 >0.8 value.

Figure 4. Map of the field measurement sample
points

Veget
ation
Index
NDVI

Table 4. Mangrove biomass from field data
calculation

Min
Max
Mean

Above
groundbiomass(kg/100m2)

Below
groundbiomass(kg/100m2)

Totalbiomass(kg/100m2)

86.9
817.3
382.0

84.2
754.4
352.7

171
1572
735

NNIP
RVI

Regression
Model

Regression
Equation

Eksponential
Polynomial

y = 0.0316e22.26x
y = 86773x2 62664x + 11397
y = 0.0000001e41.24x
y = 0.09e3.40x
y = 5534.6ln(x) 4538.8
y = 903.25x2 2542.1x + 1215.4
y=1,485,906.18e0.00x
y = 180217e5.32x
y = 1.7209e504.63x
y = 48,915,274.97x2- 812,817.55x +3,499.67
y = 0.362e0.000012x

Eksponential
Eksponential
Logarithmic
Polynomial

The mangrove species found in the sample
location plots are Rhizophora stylosa, Rhizophoramucronata, Rhizophora apiculata, Avicennia
marina, Aegiceras corniculatum, Sonneratia alba,
Ceriops decandra, Xylocarpus moluccensis.
Composition of dominant mangrove species in the
study area Aegiceras corniculatum (32%), Ceriops
decandra (21.2%), Rhizophora apiculata (18.9%),
Sonneratia alba (12.2%) and Rhizophora stylosa(10.7 %).
The next step is analyzed the relationshipbetween image vegetation index values that havebeen produced with field measurement data, using
logarithmic, quadratic, and exponential regression
Field measurement was the measurement ofmangrove biomass at the sampling point. The model
constructed for biomass estimation is based on
statistical analysis between vegetation index resultsof image transformation of Sentinel-2 with the resultof biomass calculation value in the field. The
regression analysis model used was non-linear
regression. Non-linear regression statistical analysis
was based on determination coefficient (R2). The
value of R2 shows the decreasing proportion ofvariation in the variation of free variables due to theutilization of the dependent variable information.
The range of R2 is between 0 and 1. It depicting how

MTV1

Eksponential

MTV2
MSR

Eksponential
Eksponential

TVI

Polynomial
Eksponential

R2
0.859
0.814
0.832
0.850
0.809
0.815
0.813
0.829
0.860
0.815
0.821

The best combination of vegetation index
results can be seen in Table 5. Consistently, the nonlinear regression approach through exponential
equation shows higher R2 value than logarithmic or
polynomial equation. The best result of 24
vegetation index is MSR (Modified Simple Ratio),with exponential approach value R2 = 0.860. Whilethe next appropriate vegetation index was NDVI
(normalized difference vegetation index) withexponential approach value R2 = 0.859, and thenvegetation index RVI (Ratio Vegetation index) withexponential approach value R2 = 0.850. RVI
vegetation index has good consistency withexponential, logarithmic or polynomial approachwith value R2> 0.8.
Spatial modeling of mangrove distribution
based on vegetation index was done using MSRvegetation index. Mapping of spatial distribution ofmangrove biomass in Pademawu Subdistrict of
Pamekasan Regency of East Java Province wasbased on exponential non-linear regression equation
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

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of MSR vegetation index. The results of thismapping as illustrated on the map Figure 3..

Figure 3. Spatial distribution of biomass inPademawu Sub-district of Pamekasan Regency of
East Java Province based on exponential non-linear
regression equation of MSR vegetation index.
The result of spatial modeling of mangrove
biomass shows that the average of mangrove
biomass at each pixel (10x10m) was 0,9 ton/100m2.
Total mangrove biomass for above ground andbelow ground vegetation in the research area was
24,879.6 tons
4. CONCLUSION
The best results of 24 vegetation indicesanalyzed by exponential regression were MSR(Modified Simple Ratio), NDVI (normalized
difference vegetation index) and RVI (Ratio
Vegetation index). Spatial modeling of mangrove
biomass with MSR approach shows an average ofeach pixel (10x10m) of 0,9 ton/100m2. Total
mangrove biomass for above ground and below
ground vegetation in the research area was 24,879.6
tons. This research shows that Sentinel-2 image isquite capable of being used in estimation ofmangrove distribution through vegetation index
calculation and can also be used in analyzing
mangrove biomass.
5. ACKNOWLEDGEMENTS
The author would like to thank the doctoral
program of Fishery and Marine Science Faculty ofBrawijaya University, Indonesia. The Sentinel-2
image used is a product of Copernicus Sentinel Data,
the European Space Agency (ESA).
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659

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ESTIMATING THE ENVIRONMENTAL EFFECTS OF THE
CAR SHIFTING BEHAVIOR ALONG EDSA

1Nicanor R. Roxas, Jr.1, Alexis M. Fillone2, and Krister Ian Daniel Roquel2
Manufacturing Engineering and Management Department, De La Salle University – Manila, Philippines;
2
Civil Engineering Department, De La Salle University – Manila, Philippines

ABSTRACTMetro Manila is the most populated region in the country and the largest contributor to the economy of thecountry at around 40%. Situated in this metropolis is the Epifanio Delos Santos Avenue (EDSA) whichcurrently serves approximately 330,000 vehicles daily, on the average. This number has greatly increased since
the early 2000’s. Because of EDSA’s significance, many transportation related studies have focused on it.
Among the largest studies is the Metro Manila Urban Transportation Integration Study (MMUTIS) which wascompleted in 1999 and has recently been updated through the MMUTIS Update and Capacity Enhancement
Project (MUCEP). There is also another ongoing project entitled Integrated and Optimal Scheduling of a Public
Transport System in Metro Manila (PUBFix) which is funded by the government (DOST-PCIEERD). The
project intends to improve the public transportation system in the metropolis, specifically the operations of thebuses along EDSA. In this research, the aim is to formulate SP logit choice models in order to predict the mode
choices of commuters along EDSA. Such results are important in order to determine the changes in travel
behavior of commuters when certain policies and measures are introduced. An EMME model is also prepared
for this study in order to quantify the differences between the baseline and hypothetical scenarios. Aside fromquantifying the difference of these scenarios in terms of environmental effects, other traffic parameters were also
calculated in order for transport policy makers to be guided in considering more appropriate measures.
Keywords: Logit Choice Models, Urban Public Transport, Stated Preference, Mode Choice

EDSA caters to both private and public
transportation for the region and links the North
Luzon Expressway at Balintawak in the north to theSouth Luzon Expressway at the Magallanes
Interchange in the south. EDSA serves an average
daily traffic of approximately 330,000 vehicles,
growing from an approximate number of 195,000 in2007 [1], [2]. Currently, over 3,700 public utility
bus units run along EDSA, while over 60,000
jeepneys and 3,184 AUVs are currently in operation
all over the metropolis [3]. Note that all publicvehicles are operated by private entities.
Most of the public transportation routes in Metro
Manila are concentrated along EDSA because muchof the areas of economic activities are adjacent to it.
Despite the number of buses and other travel
alternatives traversing EDSA, many commuters are
inclined to use their own private vehicles which add
more volume to the already congested roads of themetropolis brought about by various reasons.
Because of the importance of EDSA to thecommuters of Metro Manila and the complexity ofthe problems related to each of the transport
alternatives serving the corridor, the road demands
much more attention in order to improve its current
state. The unorganized public transport system inMetro Manila is one of the reasons that cause
commuters to be more inclined to use private modes

INTRODUCTION
The road network of Metro Manila is defined byten radial and six circumferential roads which links
the region, as seen in Fig.1. Among the region’s
major thoroughfares, Epifanio Delos Santos Avenue(EDSA), located at the heart of Metro Manila, is oneof the busiest roads in the Philippines. It is 24
kilometers long and passes through six of theseventeen cities comprising the metropolis.

Fig.1 Circumferential and Radials Roads in Metro
Manila.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

imperative that measures are devised in order toalleviate the worsening situation. Several strategies
may be implemented in order to achieve the desired
result and one of these measures may include
reducing the number of private cars from the roads.
When introducing strategies, the decision makers
should be guided accordingly as to which plan tooperationalize in order to save resources. This paper
focuses on estimating stated preference (SP) logit
choice models for private car users. Various choicesituations were presented to the private car users,
and they were made to choose between theircurrently used mode and shifting to a hypothetical
public transportation where improvements in thetransportation system are introduced. The various
significant factors affecting their choice were
determined using logit choice models. The models
enable transport planners to estimate the sensitivityof private mode users in shifting to public transportmodes. The estimated SP logit choice models willthen be used to assess the effects of the introductionof hypothetical transport modes in the urban
transportation network of Metro Manila. Resultsfrom such analyses may aid in devising plans on
how to induce the private car users to shift to the
public transport modes.
In this study, only the private vehicle users areincluded in the database which will be the basis forthe logit choice modeling. The origin-destination
matrix used for the transportation network is takenfrom the Metro Manila Urban Transportation
Integration
Study
UpdateandCapacity
Enhancement Project (MUCEP) which is funded byJICA.

of transportation. The inefficiencies caused by adisorderly system are enormous that costs theFilipino people and the economy a huge amount inmonetary terms annually. Added to this is the stressand anxiety it brings the commuters on a daily basis.
The Department of Transportation (DOTr) and theMetro Manila Development Authority (MMDA)
have tried improving the current situation throughvarious means.
However, the effects of themeasures employed to curb the problem of traffic
congestion remains to be felt.

Source: Facebook shared photo at North Ave.
StationFig. 5 Long queue in one of the MRT stations.
This research is part of the project entitled An
Integrated and Optimal Scheduling of Public
Transport Operations in Metro Manila (PUBFix)
funded by the Department of Science andTechnology, Philippine Council for Industry, Energy,
andEmerging
Technology
ResearchandDevelopment (DOST-PCIEERD).
PUBFix isundertaken in order to assess the actual and potential
demand of public transport service along EDSA. It
also aims to provide a more integrated transportation
plan by considering both the existing supply as wellas those being planned into the future. In lieu of this,logit choice models are developed in order to aid inplanning for the improvement of the transportation
network models. Through these logit choice models,the changes in travel behavior of commuters may be
estimated when changes in the transportation system
are introduced in the transportation network models.
Therefore, the effects of certain policies,
infrastructure improvements in the network, additionof new transport alternatives, may be estimated andquantified. One of the objectives of PUBFix is to
propose, test, evaluate, and recommend, using
scenario modeling, possible new high-capacity
public transport systems (i.e. LRT, MRT, BRT,
and/or city buses) in Metro Manila under 10-year
and 20-year planning horizons. Logit choice models,
indeed, are very useful in such procedures.
There is an increasing concern for the alarming
traffic condition in Metro Manila [4], [5]. It is

REVIEW OF RELATED LITERATURE
The transportation sector, specifically roadtransport, has consistently been cited as one of theleading causes of air pollution [6]–[10]. Reference[11] cited that mobility is correlated with income,
add to this the increasing population, resulting inhigher demand for passenger transport.
The
personal mobility offered by the private car makes it
more appealing than the other alternatives, thus, theincreasing auto use aggravates traffic congestion.
This causes the deterioration of air quality in urban
and suburban areas where congestion is severe [12]–[14]. There are several schemes that may beintroduced in order to reduce emissions. Drastic
behavioral and technological changes are needed inorder to attain targets. Among those suggested are
to encourage active transport, increase car
occupancy rates, reduce total urban car kilometers
traveled, improve vehicle efficiency, increase public
transport’s mode share of urban travel [7].
Reference [15] mentioned the implementation of a
BRT is considered by many developing countries
because of its lower investment cost and flexible
661

GEOMATE - Mie, Japan, Nov. 21-24, 2017and 27% were female. Lastly, the average size ofthe traveling group of the respondents is about 2
persons.

implementation than rail systems. Providing better
alternatives to cars make the transport system
sustainable [16]. Aside from pollution emissions,public transit also reduces traffic congestion,
accidents, parking congestion, excessive energy
consumption, road and parking infrastructure costs,
and many others [17]. From the experience ofBritish Government in providing a competitive
alternative to private cars, several conditions shouldbe implemented in order to increase modal shift to
public transportation such as effective marketing andstrict implementation of traffic laws. Reference [18]stated that public transit has significant benefits
especially when relieving congestion in urban areas,just like Metro Manila.

Table 1 Descriptive statistics of the sample
Usual departure time
Usual length of travel
Usual sum of costs
Average parking cost
Average age (all)MaleFemaleCivil Status
Gender

THEORETICAL BACKGROUND

Average number of people
in the group
Number of observations

The multinomial logit model is the simplest,
most practical, and most popular discrete choicemodel available [19]. It adheres to the utility
maximization theory [20]. Utilities can be divided
into two parts, the systematic or observable
component (V) and the disturbance or random
component [19], [21], [22]. In specifying thesystematic part, the linear combination of theestimated parameters and the attributes of thealternatives are taken. The error terms are assumed
to be independent and identically Gumbel
distributed where the choice probability is specifiedas  =

where,
Cn – choice set of respondent, n,
Vin – systematic component of utility of the chosenalternative, i, and
Vjn – systematic component of utility of the feasible
choices, j.
URBAN
TRANSPORTECONOMIC STATISTICS

AND

1.85
592

The majority of the respondents (61%) includedin the sample were college graduates. Next is thegroup of high school graduates with 27%.
Respondents with Master’s degrees comprise 11%of the dataset and the remaining 1% for vocational
training graduates. Almost half of the total trips aregoing to work. This is understandable because
commuters using EDSA are mostly going to theiroffices especially during the morning rush hours.
This is followed by the shop/personal/others trip
purpose (19%), and then school trips (18%), andfinally business trips (12%).
Majority of the individual incomes are less thanor equal to 100,000PHP/month (≈2060USD/month)with an average value of approximately
1100USD/month. This shows that majority of the
respondents belong to the high income groupaccording to the income categories of the National
Statistics Office.

(1)∑ ∈  

0800–0900
47.43min
84.02PHP
25.20PHP
35.01
35.19
34.55
Single: 68%
Married: 32%
Male: 72.97%
Female: 27.03%

LOGIT CHOICE MODELING RESULTS

SOCIO-

From the 592 observations, SP logit choicemodels were estimated.
The final model isformulated as seen in the following utility equations.
Respondents shifting to public transportation are
assigned to choice A, whereas choosing to remainusing one’s private vehicle is assigned to choice B.

Survey questionnaires were administered to
private car users traversing EDSA where a total of
592 observations were compiled and included foranalysis. Table 1 shows the descriptive statistics forthe data collected. The usual departure time of the
respondents was between 0800 and 0900 in themorning where the average length of travel isapproximately 48 minutes and costs 84PHP(≈1.75USD) on the average. The average parking
cost for the travelers was 25.20PHP (≈0.52USD).
The average age of the respondents was 35 years
old. As for the civil status, 32% were married,
separated, or widowed, while 68% were single.
Seventy three percent of the respondents were male =   +  ∗    + ! ∗" # $%& +  ' ∗(($$ & "$$ )% ' +  ∗* # ( # # %%$& & +** ∗  " &" +& +  ∗ &"  +"+
(2)

662

GEOMATE - Mie, Japan, Nov. 21-24, 2017

, =  ∗    (3)Shown in Table 2 is the final model estimatedthrough the use of NLOGIT software. It can be seenthat the model is significant with a corresponding
high Chi-squared value. The model performance is
acceptable with an R-sqrd value of 0.30651.
Looking at the final model, the various factors
significantly affecting the choices made by the
respondents are identified. It can be verified that
total travel time, age, access and egress type 3, levelof comfort of the new mode, and educational
attainment all affect choice. This is indicated by theindividual significance values in which all are lessthan the 0.05 level of significance.
Looking at the TOTTIME parameter which is
specified generic for both choices, it can be statedthat it negatively affects choice and serves as adisutility to the commuters. As for the age which is
specific to choice A, it can be said that older people
will be less likely to shift from their private vehicles
to a public transport. However, when one looks at
the educational attainment variable assigned to
choice A, the opposite is true. As the level of
educational attainment increases, the more they arelikely to shift to public transport modes. This could
probably be explained by the fact that when thequestionnaires were administered, the current traffic
situation is explained to everyone. Most likely,
those people with higher levels of educational
attainment understand how to contribute in solving
the problem of congestion. Access type 3 is adummy variable assigned to choice A. It takes avalue of 1 when the access and egress modes are
similar to high-occupancy on-call shared taxis. By
inspecting the parameter, it can be noted that when
the access and egress modes are upgraded, then the
respondents will tend to shift modes. Only this typeof improvement in the access and egress modes toand from EDSA was found to be significant among
the other three options. It just shows that private car
users, indeed, value the comfort and convenience ofdoor-to-door transport and avoid the inconvenienceof transfers. Lastly, the comfort and conveniencevariable has three levels and is orthogonally coded
which is assigned to choice A; high level of comfort
is designated a value of +1. For the purpose of thisstudy, comfort was represented by the load factor of
the mode. Inspection of the COMF coefficientshows that it is positive which only demonstrates
that improving the level of comfort of public
transportation along EDSA attracts private car users
to shift.
Note that when the SP part of the questionnaire
was designed, it was assumed that all the
improvements in the access, egress, and main modes
will not translate to any change in the costs alreadyincurred by the respondents. This is somewhat alimitation of this study. The total cost incurred is thesame for the current private mode of travel andshifting to public transportation combined with all
the improvements specified in the questionnaire.
Table 2 SP Logit Choice Model
No. of observations
R-sqrdChi-squared
Prob [chi squared > value]
Variable
Coefficient
ASCA-1.09028140
TOTTIME-0.02546769
AGE-0.03568077
ACCESS3
0.81024906
COMF
0.76930538
COLL
0.96494867
POST
1.09526421

592
0.30651105.30987
0.00000
P [|Z|>z]0.00070.00010.00030.00130.00000.00090.0189The model performance was also checked by
the accuracy to estimate the choices made by the
respondents. The following table is a crosstab
matrix which shows the distribution of the model
predictions. It can be verified that 406 or (59+347)
out of the 592 choice situations have been correctlypredicted by the model. This represents a 68.58%
accuracy which is acceptable.
Table 3 SP Logit Choice Model

A
B
Total

A
59
93
152

B
93
347
440

Total
152
440
592

A – shift
B – stay

EMME MODELING RESULTS
The EMME4 transportation planning software
was used in order to incorporate the SP model
results in measuring the economic andenvironmental effects of the mode shifting behaviorof travelers in Metro Manila. First, the baselinetransportation network of the whole Metro Manila ismodeled using the MUCEP data for peak hour
traffic. All the necessary data were encoded, themodel calibrated and important travel-related
statistics obtained. After this, a second scenario
was developed incorporating the SP logit choicemodel and the model was rerun. The differences intravel-related statistics between the results of the twomodels were then recorded. The following figure
shows the EMME baseline model for Metro Manila.

663

GEOMATE - Mie, Japan, Nov. 21-24, 2017transportation system along EDSA, as well as
lessening the harmful environmental effects oftraffic congestion. In order to achieve this, choicemodeling is necessary in order to estimate the effectsof certain policies on the choices made by thecommuters. For this study, SP logit choice models
were estimated in order to aid in the planning of thetransportation system in the metropolis.
Thebehavior of private car users were investigated andassessed when they were given several hypotheticalscenarios which involve several improvements in the
public transportation system traversing EDSA. Thiswas done in order to investigate the environmental
effects of mode shifting in the metropolis.
Based on the results of the SP logit choicemodel formulated, it was determined that travel
time, age, educational attainment, existence ofaccess type 3, and comfort and conveniencesignificantly affect the mode shifting behavior ofprivate car users in Metro Manila. Interesting tonote here is when one looks into the numericalcoefficients of travel time, access type 3, andcomfort and convenience.
The numericalcoefficients suggest that the provision of highoccupancy on-call shared taxis to private car users
has a similar effect of reducing the disutility oftravel time by approximately 32 minutes. Thissuggests that the convenience of a somewhat door todoor travel is particularly desired by the private car
users. Also, the provision of a high level of comfort
for the hypothetical BRT mode along EDSA isequivalent to a significant amount of reduction in
travel time, approximately 31 minutes. The highlevel of comfort is characterized by load factor lessthan 1.0, more organized stops, and roomier cabin
for passengers. Again, this reinforces the notion thatprivate car users are sensitive to the level of comfortof their mode of travel.
As seen from the EMME modeling results, theshifting of private car users to the hypothetical
public transport mode greatly affects thetransportation system of the metropolis.
The
number of vehicles on the road decreases while theaverage travel speed increases. This not onlytranslates to savings in value of travel time, vehicle
operating costs, but savings on environmental
pollution, as well. This analysis proves that when
the public transport modes are upgraded in terms of
their level of comfort, reliability, and speed, thenthere would be a significant amount of privatetransport users willing to shift to alternative public
transport modes. This is what the future of Metro
Manila should be. In order to have a sustainabletransportation system, various schemes should be
employed in order to attract private car users to shift
to the more efficient public transport modes. Strict
implementation of laws, major behavioral changes,
and technological improvements should be among
the government’s priorities to improve the current

Fig. 1 EMME Model.
Table 4 shows the values of the different
parameters measurable in the EMME model when
the baseline and with transfer scenarios were run.
An increase of 3kph in speed along EDSA, on the
average, has been registered. This outcome is a
result of the 12% private car users shifting to the
new hypothetical transport mode. Along with theincrease in average speed are the reductions in
vehicle operating costs and value of travel time
which are quite significant. Also, quite noticeable
are the reduction in environmental pollutants. The
differences in the CO2, NOx, and SPM values
translate to a total of 36% reduction inenvironmental cost when they are converted tomonetary units.
This suggests that when acompetitive public transport alternative such as a
BRT is introduced along EDSA, the current traffic
situation will be addressed. The effects are quite
significant and should be given ample considerationby the government.
Table 4 Differences between the baseline and withtransfer scenarios during the peak hour
BASELINE
Average speed(kph)
Vehicle operating
cost (PHP)
Value of time(PHP)
CO2 (g)NOx (g)
SPM (g)Environmental
Cost (PHP)

18.39

WITH
TRANSFER
21.32

386,382.7

329,641.2

28,151,511
2,765,655.92
599,308.71
47,666.68

15,846,214
1,885,906
518,045.6
27,579.6

198,483.07

126,430.72

CONCLUSION
The PUBFiX project is looking into the current
traffic condition in Metro Manila and is formulating
strategies in order to improve the public664

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Environmental Pollution, Issue 223, 2017, pp.
62-72.
[10] Chester M et al., “Infrastructure and automobile
shifts: positioning transit to reduce life-cycle
environmental impacts for urban sustainability
goals”, Environmental Research Letters, Issue
8, 2013, pp. 1-10.
[11] Dhar S and Shukla P, “Low carbon scenarios
for transport in India: Co-benefits analysis”,
Energy Policy, Issue 81, 2015, pp. 186-198.
[12] Pucher J, “The road to ruin? Impacts ofeconomic shock therapy on urban transport in
Poland” Transport Policy, 2(1), 1995, pp. 5-13.
[13] Kamba A N, Rahmat R A O and Ismail A,“Why do people use their cars: A case study in
Malaysia”, Journal of Social Sciences, Issue 3,
2007, pp. 117-122.
[14]U.S. Department of Transportation, “Federal
Transit Administration”, [Online] Available at:https://www.transit.dot.gov/regulations-andguidance/environmental-programs/transitenvironmental-sustainability/transit-role, 2016.
[15] Satiennam T, Jaensirisak S, Satiennam W and
Detdamrong S, “Potential for modal shift bypassenger car and motorcycle users towards Bus
Rapid Transit (BRT) in an Asian developingcity”, IATSS Research, Issue 39, 2016, pp. 121129.
[16] Davison L J and Knowles R D, “Bus Quality
partnerships,
modal
shift
and
traffic
decongestion”, Journal of Transport Geography,
Issue 14, 2006, pp. 177-194.
[17] Litman T, “Evaluating Public Transit Benefits
and Costs. Victoria: Victoria Transport Policy
Institute”, 2017.
[18] Harford J D, "Congestion, pollution, andbenefit-to-cost ratios of US public transit
systems”, Transportation Research Part D, Issue
11, 2006, pp. 45-58.
[19] Ortuzar J dD and Willumsen L G, Modelling
Transport. 4th ed. United Kingdom: John Wileyand Sons, Ltd, 2011.
[20] Hess S, “Advanced discrete choice models withapplications to transport demand (Thesis)”,London: Center for Transport Studies, Imperial
College, 2005.
[21] Ben-Akiva M and Lerman S R, Discrete Choice
Analysis: Theory and Application to Travel
Demand. Cambridge, Massachussetts: MIT
Press, 1985.
[22] Garrow L A, Discrete Choice Modelling and
Air Travel Demand. Vermont: Ashgate
Publishing Company, 2010.

transportation sector, with emphasis to curbing theworsening environmental pollution.
Enormous
investments on public transportation are imperativein order to achieve this vision. Current policies suchas modifying the number coding scheme are
momentary solutions to the serious transportation
problem of the metro. What this country needs arelong term solutions if the government is reallyserious. Transportation studies such as PUBFix
should not just be encouraged by the government.
Their results and recommendations should warrant
the consideration of the government, as well.
REFERENCES[1] Vallarta B, “With 31 malls near EDSA,
Christmas traffic crawls. GMA News”,
Retrievedfrom
http://www.gmanetwork.com/news/story/24164
6/news/nation/with-31-malls-near-edsachristmas-traffic-crawls, 2011.
[2] Kawabata Y and Sakairi Y, “Metro Manila
interchange
construction
project(IV)”,
Retrievedfrom:
http://www.jica.go.jp/english/our_work/evaluati
on/oda_loan/post/2008/pdf/e_project22_full.pdf, 2008.
[3] LandTransportation
Franchising
andRegulatory Board. http://www.ltfrb.gov.ph/.
[4] ALMEC Corporation, Pacific Consultants
International, Yachiyo Engineering Co., Ltd.,“MetroManilaUrban
Transportation
Integration Study, Metro Manila: Japan
International Cooperation Agency (JICA)”,
1999.
[5] JICA, “The Project for Capacity development
on Transportation Planning and Database
Management in the Republic of the Philippines.
MMUTIS Update and Enhancement Project(MUCEP)”,
Retrievedfrom:
http://open_jicareport.jica.go.jp/pdf/12247615.p
df, 2015.
[6] Hensher D A, “Climate change, enhanced
greenhouse gas emissions and passenger
transport - What can we do to make adifference?”, Transportation Research Part D,
Issue 13, 2008, pp. 95-111.
[7] Stanley J K, Hensher D A and Loader C, “Roadtransport and climate change: Stepping off thegreenhouse gas”, Transportation Research Part
A, Issue 45, 2011, pp. 1020-1030.
[8] Chapman L, “Transport and climate change: areview”, Journal of Transport Geography, Issue
15, 2007, pp. 354-369.
[9] Liu Y-H, Liao W-Y, Lin X-F., Li L., and Zeng
X-I, “Assessment of Co-benefits of vehicle
emission reduction measures for 2015-2020 in
the Pearl River Delta region, China”,

665

Seventh International Conference on Geotechnique, Construction Materials andInternational Journalof GEOMATE, Oct., 2017, Vol.13, Issue 38, pp.01-08

Environment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EFFECTIVENESS OF PERMEABLE REACTIVE BARRIER (PRB) ON
HEAVY METAL TRAP IN AQUIFER AT SOLID WASTE DUMPSITE: A
SIMULATION STUDY
Udayagee Kumarasinghe1, Y. Sakamoto2, T. Saito1, M. Nagamori3, C. S. Kalpage4. G.B. Herath4, M.I.M.
Mowjood5, and Ken Kawamoto1,6
1
Graduate School of Science and Engineering, Saitama University, Japan
2

National Institute of Advanced Industrial Science and Technology

3

Material Cycles and Waste Management Group, Centre for Environmental Science in Saitama, Japan
4
Faculty of Engineering, University of Peradeniya, Sri Lanka
5
Department of Agricultural Engineering, Faculty of Agriculture, University of Peradeniya, Sri Lanka
6International Institute for Resilient Society, Saitama University, Japan
ABSTRACTOpen dumping of solid waste causes serious environmental risk of groundwater contamination due to landfill
leachate rich in heavy metals. Identification of contaminant flow and implementation of remediation technologies
including permeable reactive barrier (PRB) are highly demanded. In this study, Geo Environmental Risk
Assessment System (GERAS) has been used to simulate two-dimensional heavy metal transport in an aquifer atsolid waste dumpsite and to estimate the effectiveness of virtual PRB on trap heavy metals. For simulation, Cd andPb were selected as target contaminant based on the results of water quality analyses at an abundant solid waste
dump site in Sri Lanka. First, two cases were examined: 1) An open dump of waste located above the aquifer and2) A buried dump waste inside the aquifer. Concentration changes of heavy metals inside the aquifer beneath thewaste unit, inside PRB, upstream and downstream points to PRB were examined by changing the hydraulicgradient in the aquifer and pollution load. Results showed the numerical simulations well captured the wash-out
process of heavy metals from the pollutant source. Time period required for full wash-out was highly dependent
on the range of hydraulic gradient and pollution load. Next, a virtual PRB was set in downstream of aquifer by
installing a section with a high heavy metal adsorption capacity (based on previous studies). Results showed thatthe virtual PRB well trapped the target metals and reduced the contamination level less than the effluent water
quality standards.
Key words: Solid waste dumpsite, Groundwater, Heavy metal, Permeable reactive barrier, Numerical simulation

simulations, the effectiveness of PRB on the heavy
metals (Cd and Pb) trap in an aquifer at solid waste
dumpsite has been examined.

INTRODUCTION
Open dumping is a common method used for the
final disposal of municipal solid waste in mostdeveloping countries [1]. Landfill leachate is rich intoxic hazardous heavy metals. The permeation ofleachate causes serious soil and groundwaterpollution in surroundings [2]. Thus, identificationand mitigation of groundwater contamination by
heavy metals at open solid waste dumpsites has
being highly demanded. Recently, Permeable
Reactive Barrier (PRB) system, which is one of insitu methods for treating contaminated groundwaterby immobilization of heavy metal in contaminatedgroundwater surrounding the open solid waste
dumpsites., become an option [3] PRB system does
not interrupt the groundwater flow in the treatment
process, thus highly suitable to use as in-situ
pollutant immobilization technique. In this study, anumerical simulation software, Geo Environmental
Risk Assessment System (GERAS) [4], has beenused to simulate a two-dimensional groundwaterflow coupled with heavy metal transport. In the

MATERIALS AND METHODS
Selection of Modeling Area
A conceptual contaminated site was classified
based on data collected from an open solid waste
dumpsite located in Central province of Sri Lanka.
The dumpsite has been used for 7 years of waste
dumping [2]. Fig. 1 illustrates the arrangement andsetting of the conceptual open solid waste dumpsite
model. The conceptual open solid waste dumpsite(waste unit) was fixed as 100m in length and 40m in
width and the area of aquifer was set to be 400m x
100m in x and y direction. The thicknesses of theaquifer and waste unit were set to be 2m. A 4m widthand 45m length virtual PRB was installed in thedownstream (20 m away from the end point of thedumped waste in x direction). In the simulations, twocases were studied: Case 1: An open dump of waste

666

International Journal of GEOMATE, Oct., 2017, Vol.13, Issue 38, pp.01-08

Fig. 1 Scale and initial boundaries of conceptual model for simulation: Case 1 [a] and Case 2 [b]
𝜕𝐶
𝜕
𝜕𝐶
𝜕
𝜕𝐶
𝜕𝐶
𝜕𝐶
=
[𝐷
]+
[𝐷
] − [𝑉𝑥− 𝑉𝑦 ]
𝜕𝑡 𝜕𝑥 𝑥 𝜕𝑥
𝜕𝑦 𝑦 𝜕𝑦𝜕𝑥𝜕𝑦1 − 𝑛𝑎
𝜕𝑆
−[
] 𝜌𝑠
(3)
𝑛𝑎
𝜕𝑡

(pollutant source) located above the aquifer anddirect permeation of rainwater into the aquifer
through waste layer (Fig. 1a). Case 2: A buried waste
dump inside the aquifer, no effect of rainfall,groundwater flow affects the washing out ofcontaminants (Fig. 1b). Spatial and temporalvariabilities of contaminants and the effectiveness of
the PRB were evaluated in both cases by analyzing
the changes in heavy metal concentrations at
upstream, downstream and inside the PRB.

where 𝐶 [ML-3] is the solute concentration, 𝑡 is thetime, 𝐷𝑥 and 𝐷𝑦 [L2T-1] is the diffusion coefficientin x and y directions, 𝑆 [MM-1] is the saturated
adsorption of contaminant into soil particles. The
𝐷𝑥 and 𝐷𝑦 are as follows:
𝐷𝑥 = 𝜀𝐷𝑀 + 𝜏𝐿 ⃓𝑉𝑥 ⃓𝐷𝑦 = 𝜀𝐷𝑀 + 𝜏 𝑇 ⃓𝑉𝑦 ⃓(4)

Governing Equations

where 𝐷𝑀 [L2T-1] is the molecular diffusion
coefficient of metal (Cd and Pb) in free water and 𝜀is the tortuosity (used Millington and Quirk model[7] in this study). The longitudinal and transverse
dispersivities, 𝜏𝐿 and 𝜏 𝑇 [L], were determined withrespect to the scale of aquifer in the simulation and𝜏 𝑇 was considered as 0.1 times of 𝜏𝐿 [8]. In theaquifer, linear adsorption model was used for theadsorption of heavy metals into solid phase:

GERAS simulation model is used to estimatecontaminant concentration (heavy metals) in the
groundwater as a function of time and space. The
model simulation is considered to be twodimensional in horizontal plane. The governing
equations has applied for three main zones of thecontaminated sites.
Zone 1: Aquifer

𝑆𝑠 = 𝑘𝑑−𝑤 𝐶𝑤

The model follows the flow equations as shownin Eqs. (1) and (2) assumingwater is an
incompressible fluid, fluid pressure created bygroundwater is low, and aquifer is homogeneous,and isotropic porous media [5].
2

𝑣𝑥 =

𝑛𝑎

.

𝜕∅
𝜕𝑥

where 𝑘𝑑−𝑤 [L3M-1] is the distribution coefficientof target heavy metal in the aquifer.
Zone 2: Waste unit2𝜕 ∅ 𝜕 ∅+
=0𝜕𝑥 2 𝜕𝑦 2−𝑘𝑥(5)

and 𝑣𝑦 =−𝑘𝑦𝑛𝑎

Few assumptions were made when applying
the governing equations to waste unit: 1) heavy
metal component in solid waste stocked within thewaste unit, 2) dissolution/ desorption of heavy
metal due to rainfall permeation and groundwaterflow in Case 1, and only by groundwater flow inCase 2. . Saturated adsorption of heavy metals into
waste particles: 𝑆𝑤𝑠 [MM-1] were determined

(1)
.

𝜕∅
𝜕𝑦

(2)

where ∅ [L] is the pressure head, 𝑣𝑥 and 𝑣𝑦 [LT-1]
are the groundwater velocities in x and y directions,𝑘𝑥 and 𝑘𝑦 [LT-1] are the hydraulic conductivities inx and y directions, 𝑛𝑎 [-] is the porosity of aquifer.
A solute transport equation used in thesimulations was as follows:

following linear adsorption model using the
distribution coefficient of target heavy metal in thewaste unit: 𝑘𝑑−𝑤𝑠 [L3M-1].

667

International Journal of GEOMATE, Oct., 2017, Vol.13, Issue 38, pp.01-08

𝑆𝑤𝑠 = 𝑘𝑑−𝑤𝑠 ∗ 𝐶𝑤𝑠

Aquifer(7)

The concentration of heavy metal component inporous media of waste (𝐶𝑤𝑠 ) [ML-3] is considered
to be equal to heavy metal concentration of adjacentsoil porous.

The hydraulic gradient was calculated based on
groundwater level measured at the studied dumpsite.
The model use the single value for the calculationand it is assumed that the hydraulic gradient isconstant throughout the simulation period. The
distribution coefficient of heavy metal in waterphase 𝑘𝑑−𝑤 was determined considering the soil
type of studied area. The soil type of the studied
dumpsite is Reddish brown latasolic and the
distribution coefficient calculated for the same soil
type was used [12].

Inflow flux of heavy metal in Case 1 follows
the Eq. (8).
𝑞ℎ𝑚 = 𝑅𝑞𝑟 𝐶𝑤(8)where 𝑞ℎ𝑚 [MT-1] is the inflow flux, 𝑅 is thepermeation ratio, 𝑞𝑟 [L3T-1] is the rainfall intensity,
and 𝐶𝑤 [ML-3]is the equilibrium concentration ofheavy metal in water phase. Inflow of heavy metal inCase 2 is controlled by Eq. (7).

Waste unit
Initial concentration of heavy metal was set byconsidering monitored metal concentrations atstudied dumpsite [2]. Referred values [13] were used
for the distribution coefficient of heavy metal in
waste. The weight of the dumped waste wasconsidered as 1.07E+07 kg, according to the in-situ
dry density of waste (= 0.6 kg/m3) and specificgravity (= 2.3) [2].

Zone 3: Permeable Reactive Barrier (PRB)
Langmuir adsorption model was applied tocharacterize the heavy metal adsorption at PRB in
the simulations:
𝐶𝑤𝑠
𝑆

=

1
𝑏𝑄𝑚

𝐶

+ 𝑤

𝑄𝑚

(9)

where 𝑆 is the adsorbent amount of heavy metal into
reactive material, 𝑏 [L3M-1] is the Langmuir constantand 𝑄𝑚 [MM-1] is the maximum adsorption capacity[9].

Permeable reactive barrier (PRB)
The PRB material was selected based on theprevious study [12]. In the simulations, the hydraulicconductivity of PRB is assumed to be equal to thehydraulic conductivity of aquifer.

Setting of Input Parameters
Table 1 summarizes parameters used in thesimulations.
Table 1 Input parameters used for model simulation
Zone
Aquifer

Waste unit

PRB

Description
Porosity
Hydraulic conductivity
Hydraulic gradient
Molecular diffusion
coefficient
Dispersivity

SymbolUnit𝑛𝑎𝑘𝑥 , 𝑘𝑦
𝑖

m/s
-

𝐷𝑀

m2/s

𝜏𝑥

m

Distribution coefficient

𝑘𝑑−𝑤

m3/kg

Initial concentration ofheavy metal component
Distribution coefficient𝑆𝑤𝑠

mmol/kg

𝑘𝑑−𝑤𝑠

m3/kg

𝑄𝑚

mmol/kg𝑏

m3/mmol

𝑞𝑟
𝑅

mm/yr

Maximum adsorption
capacity of heavy metal
Langmuir isotherm constantMeteorologicalRainfall intensity
parameters
Permeation ratio*Used for the sensitivity analysis

668

-

Value
0.4
1E-03
0.06 (0.006, 0.12)*
Cd: 6.0E-10
Pb: 7.9E-10
Cd: 10
Pb: 10Cd:1.3E-02
Pb:1.4E-01
Cd:3.24E-04
Pb:2.01E-02
Cd:1.3E-03
Pb:2.7E-03
Cd:2.7E+01
Pb:4.8 E+01
Cd:3.0E-02
Pb:9.4E-03
3.53 E+03
1

Reference

[10]
[10]
[11]
[10]
[12]
[12]
[2]
[13]
[12]
[12]
[2]
[14]

International Journal of GEOMATE, Oct., 2017, Vol.13, Issue 38, pp.01-08

controlled by the rainfall precipitation in Case 1.
These results suggest that rapid and higher pollution
migration easily occurs in the waste dump site witha buried waste. Furthermore, the heavy metals
trapped by the PRB in Case 2 were greater than thosein Case 1 due to the higher concentrations of heavy
metals in the inflow to PRB.

Rainfall data was collected from a rain-gauge
station near by studied dumpsite [2].
Sensitivity Analysis
Sensitivity analysis was conducted to analyze theeffect of various input parameters. The values
chosen were 1, 0.1, 2 times of the actual input
parameter for hydraulic gradient (0.06, 0.006, 0.12).
Similarly, the scale of the dumpsite (waste unit) waschanged into 40 m x 40 m in order to evaluate theeffect of pollutant loads. The time taken to peakheavy metal concentration in the monitoring points
were compared.

Evaluation of the Effectiveness of PRB
Figure 2 illustrates the temporal variation of theheavy metal concentration in different places of theaquifer. In most cases, the PRB trapped well heavy
metals in the aquifer and reduced the peakconcentration at the outflow from PRB. For both Cd
and Pb, the heavy metal concentrations observed at
the outflow from PRB were less than those of theeffluent water quality standards in Sri Lanka whichis 8.90E-04 and 4.83E-04 mmol/L respectively for
Cd and Pb [15].

RESULTS AND DISCUSSION
Model Outputs of Sensitivity Analysis
Table 2 exemplifies the model outputs ofsensitivity analysis. In both cases output values(peak time and concentration inside the PRB) werehighly sensitive to the hydraulic gradient for bothheavy metals. For example, the time for peakconcentration was mainly controlled by 𝑖: the peaktime for 𝑖 = 0.006 become 4-6 times higher than thatfor 𝑖 = 0.06 except for the Pb with low pollution load.
On the other hand, the effect of pollution load wassignificant only for the outputs from Case 2: the peakconcentration for the low pollution load became~20% of the peak concentration for the highpollution load.
As shown in Table 2, the washing out ofcontaminants (reduction in metal concentration) wasmuch faster in Case 2 than Case 1 for both Cd and
Pb. This attributes to the direct exposure of waste
unit into the groundwater flow in Case 2. On theother hand, the washing out of heavy metals is

Pollution Migration Process in the Aquifer
Figure 3 shows an example for pollutant
migration process in aquifer. The simulation was
carried out to observe the pollutant plume of Cd in
the aquifer, with respect to the Case 2. A rapid
washing out process was observed in the upstream to
the PRB and the pollutant plume reached to the PRB
within six months. Due to the adsorption at the PRB,a drastic reduction of Cd concentration was observedin the outflow from the PRB. However, even after 10
years, contaminants can be found in the aquifer
which is 300 m away from the buried waste unit.

Table 2 Model outputs of sensitivity analysis
CdHigh
pollutionload

Case 01

Case 02

Low
pollutionload

Case 01

Case 02𝒊

Time (Year)

0.060
0.120
0.006
0.060
0.120
0.006
0.060
0.120
0.006
0.060
0.120
0.006

5.50
3.70
24.0
0.90
0.50
5.30
7.50
4.60
41.9
2.80
1.70
17.7

Concentration(mmol/L)
2.05E-05
1.95E-05
2.10E-05
1.04E-04
1.09E-04
1.02E-04
1.29E-05
1.16E-05
1.43E-05
2.27E-05
2.80E-05
2.18E-05*N.B.: No breakthrough.

669

Time (Year)
41.7
25.3
148
6.70
4.20
39.7
78.2
45.8
N.B.*
30.1
17.8
N.B.*

Pb
Concentration(mmol/L)
1.18E-04
1.18E-04
1.05E-04
6.78E-04
8.93E-04
6.76E-04
8.06E-05
8.23E-05
N.B.*
1.26E-04
1.99E-04
N.B.*

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

Case 1: Low pollutant loadCase 2: High pollutant loadCase 2: Low pollutant load

Pb

Cd

Case 1: High pollutant load

Fig.2 Temporal variation of the heavy metal concentration at the different locations of the aquifer for Cd [(a), (b), (c), (d)] and for Pb [(e), (f), (g), (h)]670International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

Fig. 3 Pollution migration process in the aquifer[5] Bear J, (1972). Dynamics of fluids in porous
media. Elsevier, New York.
[6] Jury WA, Gardner WR, Gardner WH (1991).
Soil physics. 5thed. John Wiley & Sons, NewYork.
[7] Millington R J, and Quirk JP, (1961). Transportin porous media. P. 97-106.
[8] Neuman SP, (1990). Universal scaling of
hydraulic conductivities and dispersivities ingeologic media. Water Resour. Res. 26(8):1749-1758.
[9] Bulgariu D, Bulgariu L, 2012). Equilibrium andkinetics studies of heavy metal ions biosorption
on green algae waste biomass Bioresour.
Technol., 103(1), 489–493.
[10] USEPA: EPA Region III Risk Based
Concentration Table, EPA Region 3(1995).
[11] Nagamori M, Udayagee Kumarasinghe, Shakila
Hettiarachchi, Mowjood MIM, Herath, GBB,
Isobe
Y,
WatanabeY,
Kawamoto
K, (2015). Spatiotemporal variation of water
quality around and inside an open solid waste
dumpsite in Sri Lanka. International conference
on Advances in Civil and Environmental
Engineering
PracticesforSustainable
Development
FacultyofEngineering,
University of Ruhuna, Galle, Sri Lanka.
[12] Paranavithana GN, Kawamoto K, Inoue Y,
Saito T, Vithanage M, Kalpage C. S, and Herath
GBB, (2016). Adsorption of Cd2+ and Pb2+ onto
coconut shell biochar and biochar-mixed soil.
Environ. Earth Sci. 75:484.
[13] Allison JD, And Allison TL, (2005). Partition
coefficients for metals in surface water, soil, andwaste. U.S. Environmental Protection Agency,
Washington, DC.
[14] Richards LA, (1931). Capillary conduction ofliquids through porous mediums. Physics.1 (5):318.
[15] Central Environmental Authority, Sri Lanka.
(2005). Technical guidelines on solid waste
management in Sri Lanka.

CONCLUSIONSIn this study, numerical simulations were used tounderstand the washing-out process of heavy metals
from the pollutant source (waste unit) and to evaluate
the effectiveness of PRB. The time period needed forthe full washing-out was highly dependent on therange of hydraulic gradient and pollution load. The
PRB well trapped the targeted heavy metals andreduced the contamination level less than theeffluent water quality standard.
ACKNOWLEDGEMENT
This study was supported by the SATREPS
Project of the Japan Science and Technology agency(JST) and Japanese International cooperation
Agency (JICA).
REFERENCES[1] Christensen TH, Kjeldsen P, Bjerg PL, Jensen
DL, Christensen JB, Baun A, Albrechtsen HJ,
Heron G, (2001). Biogeochemistry of landfill
leachate plumes. App. Geochem., 16(7-8): 659718.
[2] Udayagee Kumarasinghe, Inoue Y, Saito T,
Nagamori M, Sakamoto Y, Mowjood MIM,
Kawamoto K, (2017). Temporal variations inperched water and groundwater qualities at anopen solid waste dumpsite in Sri Lanka .int. j.
geomate. 13:1-8.
[3] Park JB, Lee SH, Lee JW, Lee CY (2002) Lab
scale experiments for permeable reactive
barriers against contaminated groundwater withammonium andheavy metals
usingclinoptilolite (01-29B). J Hazard Mater 95:65–
79.
[4] National Institute of Advanced Industrial
ScienceandTechnology(AIST):
Http://www.aist.go.jp/aist_j/press_release/pr20
06/pr20060317/pr20060317.html.

671

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ARTIFICIAL PAPER FROM PUTTARAKSA (CANNA INDICA LINN.)
AND PLUBPLUENG (CRINUM ASIATICUM)
Kanokwan Rudisirisak, Nittaya Ngowattana
Department of Chemistry, Faculty of Science and Technology Rajamangala University of Technology,
Thunyaburi, Pathumthani, Thailand.
ABSTRACT
Puttaraksa (Canna indica Linn.) and Plubplueng (Crinum asiaticum) are utilized to decorate landscape.
Their branches and leaves are cut and abandoned for beauty and attraction. These parts of the plant are abolishedby using fire that cause the greenhouse effect. So this research focused to invent the artificial paper from leaf ofPuttaraksa and Plubplueng. We could produce pulp from these leaf by using three bases ; NaOH, KOH and ashes
solution in range of concentration 1-5 % (w/v); boiling pulp in range 5-25 minutes. The suitable conditions of
Puttaraksa artificial paper were 15 minute of boiling time and 4%(w/v) KOH. The chemical component of thispaper were 93.74 % holocellulose, 1.55% lignin and 3.66 % extractive. The physical properties of this paper
were 66.43 % brightness, 400 mN tearing resistance and 1.0 kg/cm2 burstjng strength. The suitable conditions of
Plubplueng artificial paper were 15 minute of boiling time and 4% (w/v) ash solution. The chemical componentof this paper were 93.25% holocellulose, 5.41% lignin and 4.24% extractive. The physical properties of thispaper were 68.08% brightness, 340 mN tearing resistance and 0.5 kg/cm2 burstjng strength. The chemical
properties of the artificial paper from Puttaraksa and Pubplueng were similar to paper from mulberry. The highholocellulose meaned the suitable forworking.
Keywords: Artificial paper, Puttaraksa, Plubplueng, Canna indica, Crinum lily, Holocellulose
INTRODUCTION
Puttaraksa(Thailand)

Fig.2 Plubplueng : Crinum asiaticum Linn
Plubplueng is the Thai name of crinum lily thathas the scientific name : Crinum asiaticum Linn. Its
common names is Seashore Lily, Poison Bulb,
Bakung, Crinum Lily, Asiatic Poison Lily, Spider
Lily, Seashore Crinum. Crinum lily is an herbaceousperennial plant that can grow in moist area (swamp,
marsh, lake and stream), develops from undergroundbulbs and reaches 90 to 120 cm at maturity.
Crinum leaves are typically long and strap-formed,
with light green to green colors. Crinum produces
white fragrance and large flowers.[3]Fig.1 Puttaraksa : Canna indica
Puttaraksa is the Thai name of indian shot thathas scientific name : Canna indica (Cannaceae).
Canna indica is a perennial rhizomatous herb thatgrows from a thick, branching, underground rhizome
and reaches to 1m. Its leaves are large and up to
50cm long and 25cm wide.[1],[2].

Puttaraksa and Plubplueng are utilizedtodecorate landscape. Their branches and leaves are

Plubplueng(Thailand)672

GEOMATE - Mie, Japan, Nov. 21-24, 2017

cut and abandoned for beauty and attraction. These
parts of the plant are abolished by using flaming thatcause the greenhouse effect. Someone try to explore
the process that can take the most useful from theirbranches and leaves and is the better than using
flaming. On the basis of cellulose from plant can use
to produce artificial paper, such as mulberry innerbark.[4] So, this research focused to invent theartificial paper from leaf of Puttaraksa andPlubplueng.

crucible no.3, washed with cold water and acetone
then dry up and calculate.
Lignin : TAPPIT 222 om-88.1988.[4], [5]In 50 mL beaker in ice bath ; 0.5 grams artificial
paper without extractives was added with 7.5 mL ofcold 72 %(v/v)H2SO4 and well stirred. Covered thebeaker with watch glass and placed in water bath
200C for 1.30 hrs. and stirred every 15 min. Poured
the solution in the 500 mL round bottom flask that
contained 200 mL distilled water and adjusted to287.5 mL. Reflux the solution for 2 hrs. then left
solution in 500 mL beaker for overnight. Filteredthrough sinter glass crucible no.3, washed with hotwater then dry up at 1050C 3 hrs, cool down andcalculate percentage of lignin.

EXPERIMENT
Plant Preparation For Artificial Paper
Small pieces of Puttaraksa leaf, 200 g, wasboiled for 10 minute in 1,000 mL of NaOH, KOH
and ash that varied in range 1, 2, 3, 4 and 5 %w/v.
The boiled pulp was adjusted to neutral pH bywashing in tap water. These pulp was blended todisperse for 15 minutes then soaked in 5% w/v
NaClO2 for 10 minutes. Artificial paper was
produced from dispersed pulp by using 10 cm x 10
cm wire screen frame, 3 hrs. incubated at 100 oC.
Artificial paper weight approxmately 1.00-1.30 g /sheet. The suitable basis condition was taken toexperiment for suitable boiling time ; 5, 10, 20 and
25 minute. Plubplueng leaf was experiment by using
the same procedure as Puttaraksa . The artificial
paper were photographed by stereomicroscope andanalyzed about the chemical component andphysical properties.
.
Microscopic images

Physical Properties Of Artificial Paper
Tearing resistance : Tear Tester[6]50x65 mm Artificial paper overlapped 4 sheets andtest with Tear Tester.
Bursting strength : Burst Strength[6]8x8 cm Artificial paper and test with Burst Strenght.
Brightness : Reflectivity of white light[6]Take white paper under artificial paper and test by
Brightness apparatus.
Table 2 Physical properties of artificial paper from
Puttaraksa boiled in various concentration of NaOH
for 10 minuteEnlarge 51.2X with ZEISS Stemi DV4.
Chemical Component Of Artificial Paper[NaOH]% w/v

Extractives : TAPPIT 204 om-88.1988.[4],[5]Extractives extraction in Soxhlet apparatus by thefollowing ; 3 grams of artificial paper were extracted
in Ethanol:Benzene(1:2) for 4-5 hrs. To evaporate
the solvent extraction , dry up and calculate thepercentage of extractives.

1
2
3
4
5

Holocellolose : Browing[4], [5]Brightness
(%)
60.09
61.11
63.54
65.31
65.93

Tearing
resistance
(mN)
300
360
380
400
400

Bursting
strength(kg/cm2)
0.5
0.5
1
1
1

Table 1 showed that the amount of NaOH
increased as the elimination of lignin andextractives were increased and holocellulose wasdecreased at 5% w/v NaOH. Table 2 showed that thephysical properties of artificial paper were increased
because of well-eliminated extractives and lignin.

In 250 mL round bottom flask; 2 grams artificial
paper without extractives, 89 mL distilled water,
0.25 mL acetic acid and 0.75 grams sodium chlorite;boiling at 70-80o C in water bath for 30 min in fume
hood and always shaking. Add 0.25 mL acetic acidand 0.75 grams sodium chlorite in hot solution at theend of the 1st , 2nd and 3rd hrs. and shaking flask.
Take the bottom on ice bath until temperature ofsolution is below 100C, filter through sinter glass
673

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 5 Chemical component of artificial paper
from Puttaraksa pulp boiled in various concentrationof ash for 10 minute[Ashes]
% w/v
1
2
3
4
5

Fig. 3 Puttaraksa artificial paper : 10 minutes boiled
in 4%w/v NaOH, 3 hrs. incubated at 1000C

Extractive
(%)
8.86
7.53
6.98
4.93
4.05

Holocellulose
(%)
85.02
87.70
88.38
90.32
87.43

Holocellulose
(%)
70.72
73.31
77.66
80.29
74.07

Lignin
(%)
17.03
15.88
13.54
9.63
8.51

Table 6 Physical properties artificial paper from
Puttaraksa pulp boiled in various concentration ofash for 10 minute

Table 3 Chemical component of artificial paper
from Puttaraksa pulp boiled in various concentrationof KOH for 10 minute
[KOH]
% w/v
1
2
3
4
5

Extractive
(%)
12.81
12.45
10.51
8.25
6.08

[Ash]
% w/v

Lignin
(%)
4.62
2.45
2.06
1.78
1.16

1
2
3
4
5

Brightness
(%)
53.24
54.28
55.26
58.92
58.94

Tearing
resistance
(mN)
Nd
Nd
Nd
Nd
Nd

Bursting
strength(kg/cm2)
Nd
Nd
Nd
Nd
Nd

Table 5,6 showed that the ability of ashes toeliminate extractives and lignin was worse than
NaOH and KOH. Tearing resistance and bursting
strength of artificial paper were not evaluate.

Table 4 Physical properties of artificial paper from
Puttaraksa pulp boiled in various concentration of
KOH for 10 minute
[KOH]
% w/v

Tearing
Bursting
Brightness
resistancestrength(%)(mN)(kg/cm2)
1
64.33
300
0.5
2
64.37
340
0.5
3
65.80
350
1
4
66.84
400
1
5
66.85
400
1
Table 3 showed that the amount of KOH
increased as the elimination of holocellulose wasincreased and holocellulose was highest at 4% w/v
KOH. Table 4 showed that the physical properties ofartificial paper were increased as the amount of
KOH was increased, too.

Fig.5 Puttaraksa artificial paper: 10 minutes boiled
in 4%w/v ash, 3 hrs. incubated at 1000C. This paper
must use more pulp than other paper(fig.3 and fig.4)% Holocellulose
100
90
80
70
60
50
40
30
20
10
0

Fig. 4 Puttaraksa artificial paper: 10 minutes boiled
in 4% w/v KOH, 3 hrs. incubated at 1000CNaOH 4 %KOH 4 %

Ashes 4 %Fig.6 Comparison of holocellulose of artificial paper
boiled in 4% NaOH, 4%KOH and 4%ash
674

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 6 showed that amount of holocellulose of
artificial paper boiled in 4%KOH was nearby
holocellulose of artificial paper boiled in 4%NaOH.
It meaned that the efficiency of KOH was similar to
NaOH and better than ashes. But KOH is safe forenvironment, so we selected KOH to experiment.

1
2
3
4
5

Extractive
(%)
6.36
4.93
3.66
2.84
2.39

Holocellulose
(%)
85.15
90.32
93.74
89.29
87.21

[NaOH]% w/v

Lignin
(%)
3.94
1.78
1.55
1.37
0.91

1
2
3
4
5

5
10
15
20
25

Brightness
(%)
65.43
66.24
66.43
66.62
66.69

Tearing
resistacce
(mN)
350
400
400
400
400

Bursting
strength(kg/cm2)
0.5
0.5
0.5
0.5
0.5

Table 11 Chemical component of Plubplueng pulp
boiled in KOH for 10 minute
Extractive
(%)
7.92
6.70
5.41
4.91
4.34

Holocellulose
(%)
93.37
94.15
94.85
91.26
90.92

Lignin
(%)
10.88
7.80
5.39
4.22
3.13

Table 12 Physical properties of Plubplueng pulp
boiled in KOH for 10 minuteFig. 7 Puttaraksa artificial paper : 15 minutes boiled
in 4%w/v KOH, 3 hrs. incubated at 100 oC.

[KOH]
% w/v

Plubplueng

1
2
3
4
5

Table 9 Chemical component of Plubplueng pulp
boiled in NaOH for 10 minute
Holocellulose(%)

Tearing
resistance
(mN)
300
300
320
320
320

Fig. 8 Lily artificial paper : 10 minutes boiled in
3%w/v NaOH, 3 hrs. incubated at 100oC

[KOH]
% w/v
1
2
3
4
5

Extractive(%)

Brightness
(%)
54.66
55.08
58.36
58.87
58.69

Bursting
strength(kg/cm2)
0.5
1
1
1
1

Table 7 and 8 showed that boiling time in 4%w/v
KOH was longer as extractives and lignin weredecreased. Holocellulose was the highest at 15
minute and was decreased. The physical properties
were nearby at any time, so the suitable boiling timewas 15 minute.

[NaOH] %
w/v

18.14
17.72
13.00
12.04
11.81

Table 9 and 10 showed that all concentration of
NaOH could extract holocellulose. Artificial paper
from Plubplueng pulp were the same properties.

Table 8 Physical properties of artificial paper from
Puttaraksa pulp boiled in 4%w/v KOH at any time
Time
(min)

87.33
86.89
89.39
88.76
88.49

Table 10 Physical properties of Plubplueng pulp
boiled in NaOH for 10 minute

Table 7 Chemical component of artificial paper
from Puttaraksa pulp boiled in 4%w/v KOH at any
time
Time
(min)
5
10
15
20
25

6.69
5.91
5.83
5.37
3.33

Lignin(%)
675

Brightness
(%)
55.71
55.43
57.36
57.78
57.61

Tearing
resistance
(mN)
300
300
320
320
320

Bursting
strength(kg/cm2)
0.5
0.5
0.5
0.5
0.5

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 11 and 12 showed that all concentration of
KOH could extract the nearby amount ofholocellulose . Artificial paper from Plubplueng
pulp were the same properties .

Fig. 10 Plubplueng pulp artificial paper :10 minutes
boiled in 4%w/v ashes, 3 hrs. incubated at 100 oC% Holocellulose
100
90
80
70
60
50
40
30
20
10
0

Fig. 9 Plubplueng pulp artificial paper : 10 minutes
boiled in 3%w/v KOH, 3 hrs. incubated at 100oC
Table 13 Chemical component of Plubplueng pulp
boiled in ash for 10 minute
[Ash]
% w/v
1
2
3
4
5

Extractive
(%)
6.56
5.01
4.61
3.91
3.86

Holocellulose
(%)
85.10
86.84
88.78
90.17
88.74

Lignin
(%)
7.07
6.42
6.22
5.96
5.48

1
2
3
4
5

Brightness
(%)
60.51
63.59
63.12
66.33
64.76

Tearing
resistance
(mN)
300
310
320
320
320

KOH 3 %

Ashes 4 %Fig.11 Holocellulose from Plubplueng pulp boiled
in 3 % w/v NaOH , 3% w/v KOH and 4% w/v ash
Figure 11 showed that result of holocellulose
extraction from lily using 4%w/v ash was similar toresult of 3%w/v NaOH and 3%w/v KOH and
Plubplueng pulp artificial paper were nearby
properties, too. We selected 4% w/v ashes toexperiment for boiling time of Plubplueng pulp.

Table 14 Physical properties of lily boiled in ash for
10 minute
[Ash]
% w/v

NaOH 3 %Table 15 Chemical component of Plubplueng pulp
boiled in 4%w/v ashes at any time.

Bursting
strength(kg/cm2)
0.5
0.5
0.5
0.5
0.5

Time
(min)
5
10
15
20
25

Extractive
(%)
6.16
4.55
4.24
3.91
3.69

Holocellulose
(%)
89.48
90.17
93.25
92.66
90.59

Lignin
(%)
8.58
5.96
5.41
5.04
4.41

Table 16 Physical properties of Plubplueng pulp
boiled in 4%w/v ash at any time

Table 13 and 14 showed that ash was welleliminate extractives and lignin. The amount ofholocellulose was high. Artificial paper from
Plubplueng pulp were the good physical properties.

Time
(min)
5
10
15
20
25
676

Brightness
(%)
61.08
66.33
68.08
63.76
63.45

Tearing
resistacce
(mN)
310
320
340
340
340

Bursting
strength(kg/cm2)
0.5
0.5
0.5
0.5
0.5

GEOMATE - Mie, Japan, Nov. 21-24, 201790.32% holocellulose, 1.78% lignin and 4.93%
extractive. The physical properties of this paper
were66.84% brightness, 400mN tearing resistanceand 1.0 kg/cm2 burstjng strength. The chemicalcomponent of the artificial paper from Puttaraksa andPubplueng were similar to paper from mulberry. The
high holocellulose meaned the suitable forworking.
As shown in table 17.This result showed that
Phutarucsa and Plubplueng were new material toproduced artificial paper.

Table 15 and 16 showed that 15 minute boilingtime with 4%w/v ash could produce the good pulp
and artificial paper and not longer time.

ACKNOWLEDGEMENTS
We appreciated to Faculty of Science andTechnology,Rajamangala University ofTechnologyThunyaburi.

Fig.12 Plubplueng artificial paper : 15 minutes
boiled in 4%w/v ashes, 3 hrs. incubated at 100 oC.

REFERENCES

CONCLUSION[1] https://pediaview.com/openpedia/Canna_indicaAuthor H, A Book. New York: Publisher, Yr, ch.
3.
[2] https://www.gardenseeker.com/bulbs/cannas/can
na-main-page.html[3] http://www.floridagardener.com/pom/crinum.htm[4] Vittaya Punsuvon. “ Chemical component
determination of non wood raw material for pulp
and paper industry.” Department of chemistry,
Kasetsart University,Thailand.Fianl report the
research project for higher utilization of forestry
and agricultural plant materials in Thailand(HUFA).
[5] Browing,B.L. .Interscience Publishers, New
York,London.Method in Wood Chemistry,1963,
pp.389-407[6] Dumrongsak Laoseangtham. “ Production of plupfrom Vertiver grass. Department of Sciencesurvice journal.vol 151.sep.1999.
1

Table 17 Comparison of chemical component
between leaf and artificial paper

Puttaraksa leaf
Puttaraksa paper at 15
minute boiling time with
4% KOH w/v
Plubplueng leaf
Plubplueng paper at 15
minute boiling time with
4% ash w/v
Mulberry paper [6]Chemical component
Holocellulose(%) Lignin (%)
79.62
23.44
93.74
1.55

73.75
93.25

18.35
5.41

77.55

7.64

The suitable conditions of Plubplueng artificial
paper were 15 minute of boiling time and 4% (w/v)
ash. The chemical component of this paper were
93.25% holocellulose, 5.41% lignin and 4.24%
extractive. The physical properties of this paper were
68.08% brightness, 340 mN tearing resistance and 0.5
kg/cm2 burstjng strength.
The suitable conditions of Puttaraksa artificial
paper were 10 minute of boiling time and 4% (w/v)
KOH. The chemical component of this paper were

1
111
1
1

677

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

CRUSTAL THICKNESS OF NORTH-WEST PENINSULAR MALAYSIAREGION INFERRED FROM RECEIVER FUNCTION ANALYSIS
1

Abdul Halim Abdul Latiff 1 and Amin Esmail Khalil 2
Department of Geosciences, Universiti Teknologi PETRONAS, Perak, Malaysia
2
School of Physics, Universiti Sains Malaysia, Penang, Malaysia
ABSTRACTThe receiver function analysis has been used in the past 20 years by seismologist in understanding and developing
crustal model beneath a 3-components broadband seismometer station. Waveform signal used in the analysis arerecorded from the 937 tele-seismic earthquakes occurred in between year 2005 to 2016, from a station located in
Kulim, Malaysia. The signal was analyzed by rotating, deconvolving before inverting the waveform based on the
IASP91 velocity model, to obtain the local velocity structure and crustal depth to Moho boundary. Unlike in theprevious and only crustal study in this region, the receiver function analysis conducted in this study involve morethan 800 waveforms, which then separated into different back-azimuth, with the addition to signal-to-noise
criterion applied to each individual signal. The waveforms were rotated to ZRT coordinate before the iterative
deconvolution was implemented to minimize the noise signal during the rotation. In addition, the H-k stacking
analysis were applied to each azimuth quadrants to obtain the estimated crustal thickness. From the results obtainedof each azimuth quadrant, the Moho boundary were found consistent at 28 to 32 km from the sea level, which
consistent with the result obtained in the previous receiver function study of the area.
Keywords: Receiver function, Crustal thickness, Peninsular Malaysia, Earthquake
be derived from Gondwana in the Devonian) which
separated from Indochina in the Permian by back-arc
spreading, and re-amalgamated with Indochina in the
Triassic. These two blocks were separated by a zone,
widely known as Bentong-Raub suture zone [3].

INTRODUCTION
In seismically active region, earthquake occurs
daily, with some of them are destructive anddangerous in nature. The sudden release of energy,
allow seismologist around the world to conductvarious studies related to earth system, its tectonic
settings and the impact of the earthquake towards
human being. The main study area in this paper inlocated at the north west of the Malay Peninsula,where generally known as a low seismicity region,
with relatively low number of earthquakes occurred
within the mini-continent while being surrounded by
active subduction zone that produce the devastating
earthquakes every yearly. Malay Peninsula is theelemental South-east Asian part of Eurasian plate,which commonly known as Sundaland [1].

The seismological station used in the receiver
function analysis, KUM station, is positioned on topof a granite rock, which is part of Bukit Mertajam
Kulim (BMK) granite, with STS-2 broadband
seismometer and Q330 digitizer is being used todetect the ground motion signal (Fig. 2). The Bukit
Mertajam Kulim granite is an isolated body located at
north-west Peninsular Malaysia. The granite, whichlies to the west of the Bintang batholith, is part of theWestern Belt granite of Peninsular Malaysia [4] (Fig.
1). To the west of this granite lies the Penang granite
which makes up the whole of Penang Island. The
study area which is located south of Kedah, thenorthern state in Peninsular Malaysia, mapped as the
Mahang Formation, with lower Silurian graptolites of
Llandovery and Upper Wenlock age have been
recovered [5]. Geological work also found Lower
Devoninan graptolites from the Mahang Formation,
belonging to the uniformsis, praehercynicus andpossibly hercynicus zones, occurring together withnumerous tentaculiditis.

Within the Peninsula, the general geologicalsetting was divided into three north-south regionalzones; eastern belt, central belt and western belt (Fig.
1). Each of the belt region has different tectonostratigraphic characteristic such as stratigraphies,
structural evolution, magmatism and volcanism [2].
The western belt, which contains a northwesterndomain, contains mostly lower paleozoic rocks, while
the central and eastern belts of the Malay Peninsula
are generally were found in upper Paleozoic age.
These findings indicate that both central and eastern
belt represent the fore-arc, arc and continental
basement of the Sukhothai Arc. The arc wasdeveloped on the margin of the Indochina Block (can678GEOMATE - Mie, Japan, Nov. 21-24, 2017

METHODOLOGY
Although the geological characterization of thesurface outcrop has been studied extensively, thedetail of the subsurface still relatively unknown. Thus,
through geophysical data acquisition such as seismic
refraction and reflection and potential methods, theearth properties and characteristic can be identified.
One of the most reliable method to determine thecrustal thickness and velocity properties is throughthe receiver function method. The general
methodology of receiver function is the analysis of Pwave and P-S converted wave signal recorded at thestation. The signal must come from an earthquake
ruptured at a distance larger than 30o and less than
100o, with a magnitude of 6.0 Mw and higher. Beside
the two primary signals, the multiple reverberations
such as PpPs and PpSs waveform is also desirable forthe higher details of the earth crust and upper mantle.
From the waveform recorded, the earthquake delay
time difference, i.e. time taken between P-wave and
P-S wave to reach the station, as well as amplitudes
of direct and multiple phases, will provide theinformation of crustal – mantle depth discontinuity
and the impedance contrast. Throughout the analysis,
only 1D structure travel time differences were taken
in to account which requires the dependency towards
different wave phase type and slowness only.
From the phase determination, the seismograms
are rotated to the ZRT-coordinate ray system
according to bac azimuth incident wave. This step isnecessary to isolate the converted S-phase from thedirect P-wave. Each seismogram is rotated from theoriginal Z, N-S and E-W components into the Z,
radial, R and tangential, T components respectively.
As a result, the Z-component points in the directionof the direct P-wave, with the R-component is
propagate perpendicular to the Z-component.
Meanwhile, the T component is perpendicular to both
Z and R components. The Z, R and T components
contain mainly P-energy, SV-energy and SH-energy,
respectively.

Fig 1. The geological map of Malay Peninsula
showing three distinctive North-South belts [2].
N

The next step is to remove the source and wave
propagation path effect from the recorded waveform
through the deconvolution procedure. The
deconvolution of the R component from the Z can be
conducted in time and frequency domain. By
deconvolving the vertical from the radial componentsof three-component recordings, a time-series that is
primarily a function of converted waves is produced.
The most common deconvolution method in receiverfunction studies is through the frequency domain
division with the addition of water level stabilization[6]. Nevertheless, due to the low signal to noise ratiosof the tele-seismic earthquake data obtained, thereceiver functions were computed using the timedomain iterative deconvolution technique [7] rather
than frequency domain deconvolution. In the iterative
deconvolution, the differences between the resultant

Fig 2. The earth surface map of Peninsular Malaysia
with the location of seismological station (red star).
Image from Google Earth.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

convolution of the observed vertical component witha spike function, and the recorded radial component
were computed and updated iteratively. This method
produces a comparably better noise suppression
deconvolution outcome compared to frequency
domain deconvolution even though the computation
process took slightly longer.

DATA AND PROCESSING
The study focused crustal and upper mantle
seismic structures of northern Malaysian Peninsula
where there is only a single station within the region.
Receiver functions were computed in between 2005
till 2016 which involve 889 earthquakes within theepicentral distances of 30o–100o from the station, andwith magnitudes, Mw larger than 6.0 were chosen.
The vast data availability has allowed a morecomprehensive subsurface velocity characterizationcompare to the previous work in the area which
involve only 83 earthquakes [9]. It can be seen fromthe earthquake tabulation, most of the event
distribution were recorded from north-east (backazimuth of 0o–90o) and south-east (90o–180o) earth
ruptures. Before the crustal thickness and velocity
inversion were carried out, a signal to noise ratio
criteria of each of the waveform were analyze
individually, with the ratio lower than 5 werediscarded from further work. This SNR criterion saw
50% of the data (448 of the erroneous and noisy
waveform) were eliminated, with remaining 441
earthquakes signal with good SNR were used in the
H-k and velocity inversion analysis.

While the deconvolution yields receiver function,
another algorithm approach is required to determine
the earth crustal thickness from the interpreted phases.
This was solved by implementing H-k stacking
technique, which a grid-search technique approach byincorporating multiple phases amplitude [8]. In the Hk search method, the delay times of P to S conversion
Ps and the later arriving multiples crustal
reverberations (multiples) such as PpPs and PpPs +PpSs are calculated for each pair of the pre-identified
H and k value with the input from mean P-wave
velocity above the discontinuity and the average
horizontal slowness value. Through the initial
experimentation, the suitable P-wave velocity andslowness estimation of the earth crustal thickness andits corresponding velocity ratio is 6.3 km/s and 0.06
s/degree, with the resultant outcome producing agood estimation indicator. However, if the earth
structure is complex, e.g. Tibetan Plateau, the H-kgrid approach producing ambiguous and lowconfidence result.

The resultant receiver functions at station KUM
show the good P wave arrival at zero time (Fig. 3a).
However, the P-s wave arrival as a result from Moho
conversion appears relatively weak, as the earthquake
originate from north-west and south-west cause thetwin peaks at 3 to 6 seconds. Meanwhile the receiver
functions with back azimuth 180o to 360o, a relatively
better P-s conversion can be found which indicate astronger reflection from the north-west and southwest direction. In addition, the PpPs multiple signal
is strong at 14 seconds with relatively weaker PpSs
multiple at 18 seconds. Beyond 20 seconds of the
waveform, several coherent multiple phases can beseen, particularly the 1st and 2nd quadrant earthquakes.
However, due to limited waveform available from 3rd
quadrant in addition to poor coda wave signal in 4th
quadrant, no phase interpretation possible for thisstation.

The Moho boundary thickness found in the H-kanalysis, then used as a guide in developing initial Pwave velocity model for the inversion procedure. The
inversion process, which involve the forward
modelling procedure, requires a synthetic receiver
function determination based on a given earth
structure model. The problem of this study however
is not to find the receiver function, but rather todetermine the earth structure that generate thereceiver function. Inversion of a waveform is a datafitting procedure that aims at obtaining estimates ofcrustal properties from the receiver function. Given
an initial model of the subsurface parameters, the data
are predicted by solving a wave-equation. The modelis then updated through forward modeling in order toreduce the misfit between the observed and predicted
data. This procedure is repeated in an iteratively until
the misfit between the model and receiver function
data is satisfactorily small [7]. To perform the
waveform inversion, an initial model needs to be
defined. Since the existing model does not provide agood detail of Peninsular Malaysia earth subsurface,
the IASP91 velocity was used as an initial model withsome modification according to the determined
thickness value from H-k method.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

(b)

(a)

(d)

(c)

Fig 3. (a) Receiver function analysis for KUM station as a result from tele-seismic earthquake. (b) The H-k analysis
from receiver function work indicate the crustal thickness and Vp/Vs ratio of the region. (c) First velocity inversion
outcome (in blue) after 100th iteration of initial velocity model (in red). (d) Second velocity inversion using thevelocity changes information in (c) with the outcome after 100th iteration (in red) based on the initial IASP91
velocity model (in blue).

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

layers, i.e. Conrad discontinuity at 28 km while Moho
discontinuity at 32 km.

CRUSTAL STRUCTURE ANALYSISThe H-k stacking analysis use the summation ofindividual receiver function computed. While thegrid-search method shows a few possibilities ofcrustal thickness and the corresponding Vp/Vs ratio,
only two possible thickness were considered, i.e. at
30 km and 35 km (Fig. 3b). Another high confidence
H-k result, at 19 km, is highly unlikely true, as the
Vp/Vs ratio is very high (Vp = 2.2 Vs), and far exceed
the global average at 1.78 [10]. Besides these threehigh confidence region contour, another two contours
can be seen which can be interpreted as coda wave
signal from the receiver functions. Since the 95%
confidence contour only appear at 35 km depth, thisis the highest likely the Moho depth beneath KUM
station, north-west Peninsular Malaysia. Anotherpotential interpretation from the grid search analysis
is the possibility of slanted crustal-mantle boundarywith the depth begin from 28 km on the western sideof Kulim and continue to the east with Moho depth at
35 km. This interpretation came from the differencesin receiver function signals of the waveform recorded
from 1st and 2nd quadrants of back azimuth (east of
Kulim), to the 3rd and 4th quadrant of back azimuth(west of Kulim).

We use this information in developing the 2nd andfinal inversion procedure, by modifying the IASP91
velocity model as the initial velocity model. The
IASP91 velocity model was chosen based on thefollowing reading; i) similar initial model used by
Malaysia Meteorological Department in theirprevious hypocenter relocation work, which was
found accurate [13], ii) the regular and consistentvelocity sampling interval compare to AK135F,
PREM and crust1.0 model. In the existing IASP91
model, velocity changes drastically at 20 km (toindicate the Conrad discontinuity) and 35 km (toindicate Moho discontinuity) within the crustal region.
Using the findings from the 1st inversion, the IASP91
model was modified to 28 km (first velocity change)and 32 km (second velocity change).
After 100th iteration in the 2nd inversion, withsimilar coefficients as in the 1st inversion procedure,
the final velocity model was found consistent withlarge velocity difference at 32 km, although thevelocity difference at 28 km is not suggesting aseparation between upper and lower crust layering,
due to lower velocity variation (Fig. 3d). Instead, agentle velocity gradient increase was identified
between 28 km to 32 km, which may indicate theslanted crustal-mantle boundary. These findings
consistent with the hypothesis proposed from thereceiver function observation, that the crustal
thickness and velocity structure in the north-west ofPeninsular Malaysia is changing from the west to theeast of the Kulim area. Another important observation
was found at 70 km depth, as both P and S-waves
velocity profile travel slightly slower, which signal
the asthenosphere zone of the Malay Peninsula. The
relatively high near-surface Vs value of 3.3–3.6 km/s
is an indication for plutonic rocks exposed in theregion.

The waveform inversion is well known as a nonlinear non-uniqueness process, where the resultant
velocity model depends on the several trade-in factors,
particularly the initial velocity model [10]. To solve
this problem, many studies considered the linearized
iterative inversion problem, which applies to bothsynthetic and observed data. There are otherapproaches, either through different optimization
solution such as genetic algorithm, neighborhood
algorithm and simulated annealing [11], or by the
integration of receiver function inversion with surface
wave dispersion procedure [12]. While each of thesolution proposed has their advantage, none of themcapable to fully solve the non-discriminative solution.
In this study, a two-steps inversion workflow wasused to lower the uncertainty from the inversion
outcome. The first inversion process used a single andfix velocity value at 8 km/s for P-wave and 4.5 km/s
for S-wave, to locate the ‘jump’ pattern in both P and
S-wave velocity function during the inversion process.
Since the velocity was fixed from surface level to 100
km depth, the resultant output velocity model was not
influenced by the sudden velocity increase in existing
velocity model. Throughout the 100 iterations processwith damping factor of 0.5 and smoothness value of0.4, the 1st inversion step allow a validation processof H-k stacking analysis, by locating the sudden
velocity increase in both P and S velocity components.
From the 1st inversion step, the sudden velocity
increase was found at 28 km and 32 km (Fig. 3c). Thisvelocity changes were interpreted as the crustal –upper mantle layer, due to the change in rock type.
Another possibility is this represent three distinctive

CONCLUSION
By incorporating receiver function modelling andinversion method, the crustal thickness and velocity
structure underneath the KUM seismic station locatedat the north-west Peninsular Malaysia were
determined. The finding was compared to previous
receiver function analysis for KUM station, andfound that our analysis shows a close similarity interm of crustal thickness, with 28-32 km in this study
compare to 30-34 km in previous published work. In
addition, the velocity composition beneath north-westpeninsular Malaysia might indicate a distinctive
crustal-mantle depth from the west to east side of
KUM station. However, a different crustal techniqueanalysis is required, such as surface wave dispersion
analysis and ambient noise tomography study, tovalidate the produced model. In addition, the analysis
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

for the seismic stations nearby KUM is also needed
to obtain a comprehensive 3D velocity tomography of
the Malay Peninsula.
REFERENCES
[1]

[2]
[3]
[4]

[5]

[6]

[7]

A. Yan Sze Wah, "Geological assessment ofearthquake sources hazard in Malaysia," inSeminar Teknikal Gempabumi, Malaysian
Meteorological Department, 2011.
I. Metcalfe, "Tectonic evolution of the
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Sciences, vol. 76, pp. 195-213, 2013.
I. Metcalfe, "The Bentong-Raub suturezone," Journal of Asian Earth Sciences, vol.
18, pp. 691-712, 2000.
A. A. Ghani, B. M. Doya, and G. H. Teh,"Age, petrochemistry and modelling of the
Bukit Mertajam-Kulim granite, northwest
Peninsular Malaysia," Bulletin GeologicalSociety of Malaysia, vol. 44, pp. 139-150,
2000.
C. K. Burton, "The Mahang Formation: A
mid-Palaeozoic euxinic facies from Malayawith notes on its conditions of depositionand palaeogeography," Geol. en Mijnb., vol.
46, 1967.
R. W. Clayton and R. A. Wiggins, "Source
shape estimation and deconvolution ofteleseismic
bodywaves,"
GeophysicalJournal International, vol. 47, pp. 151-177,
1976.
J. P. Ligorria and C. J. Ammon, "Iterative
deconvolution and receiver function
estimation," Bulletin of the Seismological

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Society of America, vol. 89, pp. 1395-1400,
1999.
L. Zhu and H. Kanamori, "Moho depth
variation in southern California fromteleseismic receiver functions," Journal ofGeophysical Research: Solid Earth, vol.
105, pp. 2969-2980, 2000.
K. Kieling, D. Roessler, and F. Krueger,"Receiver function study in northern
Sumatra and the Malaysian peninsula,"
Journal of Seismology, vol. 15, pp. 235-259,
2011.
C. J. Ammon, G. E. Randall, and G. Zandt,"On the nonuniqueness of receiver function
inversions," Journal of GeophysicalResearch: Solid Earth, vol. 95, pp. 1530315318, 1990.
B. H. Jacobsen and L. Svenningsen,"Enhanced Uniqueness and Linearity ofReceiver Function Inversion," Bulletin of the
Seismological Society of America, vol. 98,
pp. 1756-1767, 2008.
J. Julia, C. J. Ammon, R. B. Herrmann, andA. M. Correig, "Joint inversion of receiver
function and surface wave dispersion
observations,"
GeophysicalJournalInternational, vol. 143, pp. 99-112, 2000.
A. H. A. Latiff and A. E. Khalil, "Velocity
structure and earthquake relocations at
central Peninsular Malaysia region," inGEOMATE 2016, Bangkok, Thailand, 2016.

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ARSENIC CONCENTRATION AND STABLE ISOTOPIC RATIOS OFOXYGEN AND HYDROGEN FOR GROUNDWATER AND RIVER
WATER AROUND THE MIDORO AND SHINDENHIGASHISAMITUNNELS IN GOSE CITY, NARA, CENTRAL JAPAN
Hiroyuki Ii1, Hiroshi Kono2, Yuji Yamashita3, Jyunji Uno4, Hiroyuki Shimogaki5, Sota Ikeda6 and Toshiki
Nishimura6
1
Faculty of Systems Engineering, Wakayama University, Japan; 2Ministry of Land, Infrastructure, Transport
and Tourism, Japan; 3Takenaka Civil Engineering & Construction Co., Ltd., Japan; 4Tekken Corporation,
Japan; 5Maeda Corporation, Japan; 6 Undergraduate School, Faculty of Systems Engineering, Wakayama
University, Japan
ABSTRACTDuring the several tunnel constructions for the Keinawa high way road, arsenic contamination granitic rocks
were found at the north of Median Tectonic Line in the Kii Peninsula. Arsenopyrite (FeAsS) was certainly foundin granite and then main arsenic source is thought to be arsenopyrite. Arsenic concentrations of tunnel water
were found to be over 0.1mg/L, the Japanese Effluent Standard. River arsenic concentration was also found to be
widely over 0.01mg/L, the Japanese Environmental Water Quality Standards. Arsenic concentrations of river
bryophyte were widely high relative to the normal area. Copper minerals such as chalcopyrite (CuFeS2) andchalcocite (Cu2S) were found in both the tunnels. Copper concentration of river bryophyte was 10 to several
thousand mg per kg. Some places in the study area were copper contaminated. Molybdenum concentrations ofsome tunnel waters around molybdenite (MoS2) occurrence areas were over 0.07 mg/L, the JapaneseMonitoring-required Water Quality and then, main molybdenum source is thought to be molybdenite. Arsenic,
copper and molybdenum were contaminated in some places of the study area at the north of Median tectonic line
and this contaminated zone is thought to spread east and west parallel to Median Tectonic Line. The recharge
age of tunnel water is estimated to be less than 12.3 year. River and tunnel waters derive from precipitation
however oxygen and hydrogen stable isotope values were different. The isotope difference between river andtunnel waters is thought be caused by both evaporation and altitude effect of isotope. In forest under highhumidity condition isotope effect of evaporation is small.
Keywords: Arsenic contamination, Tunnel water, Metal mine, Oxygen stable isotope, Hydrogen stable isotope
INTRODUCTION
BeforetheMidoroTunneland
Shindenhigashisami Tunnel constructions in Gose
city for the Keinawa high way road connecting
Kyoto with Wakayama through Nara, arsenic
contamination rocks around the tunnels were foundfrom field and borehole researches. Figure 1 shows
the study area. The Midoro Tunnel at the north sideand Shindenhigashisami Tunnel at the south side are
5 to 10 km at theNorth of Median
Tectonic Line in theKii Peninsula and thetunnelarea
iscomposed of fresh
granite and sheared
granite. Black sheared
granite distributed in
the south of the area
contains often minutearsenic mineral,

Fig.1 The study area. ★River sampling point.
684

GEOMATE - Mie, Japan, Nov. 21-24, 2017arsenopyrite (FeAsS). At the north area of the study
area, closed copper and molybdenum mine and its
tailing were observed in the north area. The tailingcontains molybdenite (MoS2), chalcopyrite (CuFeS2),
chalcocite (Cu2S) and copper secondary mineralssuch as malachite Cu2(CO3)(OH)2 and chrysocolla(Cu, Al)2H2Si2O8(OH)4 ･ nH2O. From the valley
between two tunnels, tunnel digging started April in2015 and finished March in 2017. The maximum
distance from tunnel to surface is less than 100 m.
Then arsenic water contamination was studied using
river and tunnel waters during tunnel construction
and groundwater migration was traced by stable
oxygen and hydrogen isotope for analyzing
contaminated water migration. Tunnel water sample
is a good indicator for analyzing groundwater
migration and groundwater chemistry [1]. Metal
concentrations of river bryophyte and river insect arethought to be good indicators for metal
contamination [2], [3], [4]. The purpose of this study
is groundwater migration analysis using oxygen andhydrogen isotopes and metal concentrations.

1
South

North

0.8

As ppm

0.6
0.4
0.2
0
0

Fig. 2500 1000 1500 2000 2500 3000 3500
tunnel length m

Arsenic
waters.

concentration

(As)

of

tunnel0.2
ENSH RIVWNSH RIVSMI RIVNMI RIVARO RIV

0.15
As mg L-1

METHOD
River water was sampled around the tunnels andtunnel water was also sampled for water migration
analysis and then were filtered with 0.45 micrometer
filter. Metal concentration of sampled waters spicedwith concentrated nitric acid were analyzed by ICPAES (Inductively Coupled Plasma Atomic Emission
Spectroscopy, SPS1700HVR ; Seiko InstrumentsInc.). After sampled river insect and river bryophyte
were dried then dissolved with concentrated nitricacid solution, metal concentration of the solution
was also analyzed by ICP-AES.
3
H concentrations of tunnel and river waters
were measured by liquid scintillation counter for
estimating recharge age after electrolytic enrichment.
The stable hydrogen and oxygen isotopic ratio were
measured by mass spectrometer (Sercon Geo Wet
System) with dual inlet and equilibrium with CO2
and H2 gas method.

0.1

0.05

2/1/2017

11/1/2016

8/1/2016

5/1/2016

2/1/2016

11/1/2015

8/1/2015

5/1/2015

0

Fig.3 Arsenic concentration (As) of river waters

As mg kg-1 dry weight

50

RESULTS
Figure 2 shows arsenic concentration of tunnel
and river waters. South side from 0 to 1800 m shows
the Sindenhigashisami Tunnel. North side from 2000
to 3100m shows the Midoro tunnel. Tunnel lengthfrom 1800 to 2000 m is valley and open area.
Arsenic concentrations of tunnel water around thevalley between both the tunnels are over 0.1mg/L,
the Japanese Effluent Standard and reaches 0.9 mg/L.
In high arsenic area, arsenopyrite (FeAsS) is
certainly found from cracks of granite. In the southof the Shindenhigashisami Tunnel, sheared blackcolored granite with minute chlorite and small
amount of arsenopyrite was found.

40
30
20
10

MOSS MSH

MOSS EMI

MOSS NSH

MOSS SMI

MOSS MMIMOSS NMI

Gammarus0with time.
Fig.4 Arsenic concentration (As) of river gammarus
and bryophyte with sampled point.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 3 shows arsenic concentration of riverwaters with time. River sampling points, ENSH,
WNSH, SMI, NMI and ARO (MMI, EMI and MSH)
were shown as in Fig.1. Arsenic concentrations ofriver waters were widely over 0.01 mg/L, theJapanese Environmental Water Quality Standards
and decreased with wet season. The concentration isthought to depend on amount of precipitation. Figure
4 shows arsenic concentration of river bryophyte andriver gammarus. The concentrations of river
bryophyte were widely over 10 mg per kg. Arsenic
concentration of river gammarus is higher than thoseof river bryophyte and then gammarus has a higher
bioconcentration factor.
Figure 5 shows copper concentration of tunnel
waters. Copper concentrations of the tunnel waters
in the Shindenhigashisami Tunnel were over 0.02
mg/L and higher than those in the Midoro Tunnel. In
the both tunnels, many times copper minerals suchas chalcopyrite (CuFeS2) and chalcocite (Cu2S) were
found as vein and aggregate minerals in granite
however copper concentrations of the tunnel waters
were low.
Figure 6 shows copper concentration of riverwaters with time. Copper concentrations of someriver waters were higher than those in the tunnel
waters and reached 0.1 mg/L. Generally copper
concentrations decrease with pH values and tunnel
water is high pH values. Then, copper concentrationof tunnel is lower than those of river water.
Figure 7 shows copper concentration of river
bryophyte and gammarus. The copper concentrationof river bryophyte in the study area was 10 to lessthan 100 mg per kg and reached several thousand
mg per kg. Copper concentration of river gammarus
was higher than those of river bryophyte and thengammarus has higher bioconcentration factor.
Figure 8 shows molybdenum concentration oftunnel waters. Molybdenum concentrations of sometunnel waters in the Midoro Tunnel were over 0.07
mg/L, the Japanese Monitoring-required Water
Quality Parameters. Molybdenite (MoS2) was foundin crack of the sheared granite and molybdenum
concentration of tunnel water was high aroundmolybdenite occurrence areas. Then, main
molybdenum source is thought to be molybdenite.
Figure 9 shows δ D and δ18O values of tunnel
and river waters. Although those values werevariable, δ D and δ18O values of tunnel water werehigher than those of river water. Only tunnel values
can be found under both -55 ‰ for δ D and -8.4 ‰for δ18O values. Mainly river water values can beobserved over both -55 ‰ for δ D and -8.4 ‰ forδ18O values.
3
H concentrations of the tunnel and river waters
were 1.7 to 1.8 T.U. and 2.5 to 2.8 T.U. The
recharge age of tunnel water is estimated to be lessthan less than 12.3 year from the difference of both

0.1

South

North

Cu mg L-1

0.08
0.06
0.04
0.02
0
0

500 1000 1500 2000 2500 3000 3500
tunnel length m

H concentrations and then, tunnel water is young.

3

Fig. 5 Copper concentrations of tunnel waters with
distance.
0.2
ENSH RIVWNSH RIVSMI RIVNMI RIVARO RIV

Cu mg L-1

0.15

0.1

0.05

2/1/2017

11/1/2016

8/1/2016

5/1/2016

2/1/2016

11/1/2015

8/1/2015

5/1/2015

0

Fig.6 Copper concentration of river waters with time.

Cu mg kg-1 dry weight

104

1000

100

10

MOSS MSH

MOSS EMI

MOSS NSH

MOSS SMI

MOSS MMIMOSS NMI

Gammarus

1

Fig. 7 Copper concentration of river bryophyte andgammarus.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017Median Tectonic Line and the past copper mines in

DISCUSSION
Arsenic concentration of the JapaneseEnvironmental Water Quality Standards for riverand groundwater is 0.01 mg/L. Arsenic
concentrations of many tunnel and river waters areover the Japanese Environmental Water Quality
Standards. In particular, arsenic concentrations oftunnel water around the valley between both thetunnels are over 0.1mg/L, the Japanese Effluent
Standard and reaches 0.9 mg/L. In high arsenic area,arsenopyrite (FeAsS) is certainly found from cracks
of granite. In the south of the Shindenhigashisami
Tunnel, sheared black colored granite with minutechlorite and small amount of arsenopyrite was found.
Then main arsenic source is thought to bearsenopyrite. River arsenic concentration is found to
be widely over the Japanese Environmental Water
Quality Standards. Arsenic concentrations of river
bryophyte and river gammarus are also widely over
10 mg per kg. Generally, background arsenic
concentration of bryophyte is under 1.5 mg per kg[3], [5]. Then, widely arsenic contamination can befound by the concentration of river bryophyte.
Copper concentrations of some river waters werehigher than those in the tunnel waters and reached
0.1 mg/L. In both the tunnels, many times copper
minerals were found as vein and aggregate minerals
in granite however copper concentrations of thetunnel waters were low. Generally copper
concentration depends on pH values and tunnel
water is high pH values with concrete lining andconcrete spraying constructed by the NATM method.
Then, copper concentration of tunnel water evencontacted with copper minerals is thought to be low
because of high pH value of tunnel waters.
Generally, background copper concentration ofbryophyte is 1 to 50 mg per kg [3], [5] however
copper concentration of river bryophyte was 10 toless than 100 mg per kg and reached several
thousand mg per kg. Then, some places in the study
area were copper contaminated.
Molybdenum concentrations of some tunnel
waters in the Midoro Tunnel were over 0.07 mg/L,
the Japanese Monitoring-required Water Quality
Parameters. Molybdenite (MoS2) was found in crackof the sheared granite and molybdenum
concentration of tunnel water was high aroundmolybdenite occurrence areas. Then, main
molybdenum source is thought to be molybdenite.
Arsenic, copper and molybdenum were
contaminated in the study area at the north ofMedian tectonic line and this contaminated zone isthought to spread east and west parallel to Median
Tectonic Line because the valley between both thetunnels with high arsenic area spreads parallel to

0.15
South

North

Mo mg L-1

0.1

0.05

0
0

500 1000 1500 2000 2500 3000 3500
tunnel length m

Fig. 8 Molybdenum concentration of tunnel and-45
tunnel
River

δD ‰

-50

-55
水泥トンネル-60

Meteoric line
-65
-9 -8.8 -8.6 -8.4 -8.2 -8 -7.8 -7.6
δ18O ‰

river waters with distance.
Fig. 9 δD and δ18O values of tunnel and river waters.
the north of study area also were arranged parallel toMedian Tectonic Line.
Recharge age of the tunnel waters is estimated tobe less than 12.3 year. Therefore, long term contact
with metal contaminated rocks is thought to enablehigh arsenic concentration of tunnel water andactually arsenic concentrations of some tunnel water
were higher than those of river waters.
Figure.10 shows schematic diagram for waterpass from precipitation to river and tunnel. Tunnel
water is groundwater recharged from precipitationand surface run off on the hill. River water comesfrom precipitation, surface run off derived fromprecipitation on the hill and groundwater recharged
from precipitation on the hill. Therefore, river andtunnel waters derive from precipitation on the hill.
However, both their oxygen and hydrogen stable
isotope values were not same, the oxygen andhydrogen stable isotope differences between riverand tunnel waters were 0.5 ‰ and 4 ‰, respectively
687

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Similarly, oxygen and hydrogen stable isotope ofriver and spring waters at the Izumi Mountain 50 km
at the east of the study area were on the meteoricline [12] and the isotope difference between spring
and river waters can be estimated from altitudedifference between both recharge areas [12].
Therefore, evaporation and evapotranspiration occur
during migration from precipitation to river, spring
and tunnel water however isotope change caused byevaporation and evapotranspiration does not occur.
Generally, oxygen and hydrogen stable isotopechange for lake and pond waters during evaporation
process occurs [6], [13]. Typically oxygen andhydrogen stable isotope values increase with
evaporation rate under low humidity condition
however under high humidity condition, over 80 %oxygen and hydrogen stable isotope values do notincrease with evaporation rate and sometimes
decrease with evaporation rate. Under high humidity
condition, isotope values of liquid changes withisotope values of vapor and not always increase with
evaporation rate [9]. Therefore forest can keep highhumidity condition during and just after rain andthen oxygen and hydrogen stable isotope ofprecipitation water can keep uniform value during
evaporation by rainfall interception of trees.
Isotopic fractionation does not occur during
absorption water from soil at root and release waterfrom leaves because residual water stays at soil andtree for a long term. Transpiration from soil water toleaves caused by tree also is thought to keep uniform
oxygen and hydrogen stable isotope values.

although they were variable values. Therefore, riverand tunnel waters derive from precipitation however
the isotope values were different.
Tunnel water mainly derives from precipitationon the top of hill and river water comes fromprecipitation around the hill as shown in Fig.10.
Therefore, average altitudes of original precipitationof river and tunnel waters are different, average
altitude of original precipitation of tunnel water ishigher than that of river water. Generally, oxygenand hydrogen isotope values of precipitation
decrease with altitude, δ18O: -0.25 ‰ /100m [6], δD:-2.0 ‰/100 m [6]. In the Kii Peninsula, altitude
effect of δ18O is -0.15 to -0.4 (-0.23) ‰ /100 m [7]and in the Yakushima Island, the altitude effect ofδ18O is -0.09 to 0.11 ‰ /100 m [8].
In this area, although even altitude difference
between top of the hill and river level is less than
100m, the oxygen and hydrogen isotope differences
between river and tunnel water are 0.5 ‰ and 4 ‰,respectively and the difference is over twice ofaltitude effect.
Generally, isotope values of water on the surface
increase with evaporation [6]. [9]. Surface run off
water and soil water evaporate and transpire andthen isotope values increase. Then, the isotope
difference between river and tunnel waters isthought be caused by both evaporation and altitude
effect of isotope.
The evaporation rate can be estimated fromoxygen stable isotope change value during
evaporation [6], [9]. When half values of different
oxygen isotope value between tunnel and riverwaters is assumed to be caused by evaporation, thecalculated evaporation rate from oxygen isotope
values, 0.25 ‰ is 2.5 % using the relation forevaporation rate per oxygen isotope change during
evaporation process = 1 % per 0.1 ‰ under highhumidity condition, [9]. As annual precipitation of
Gojyo in 2015 and 2016 is 1450 mm per year [10],the amount of estimated evaporation from theisotope values is 36 mm per year.
Evapotranspiration for forest in Japan is about
600 to 900 mm per year [11]. Evaporation caused byrainfall interception of trees in Japan reaches 30 to
50 % of total evapotranspiration [11] and is
calculated to be 180 to 450 mm per year. Therefore,
the estimated evaporation from oxygen isotope
values is quite small. If evaporation is large, over
10 %, the isotope value separates from the meteoricline [6], [9]. However the observed isotope values ofriver and tunnel water are on the meteoric line.
Therefore oxygen and hydrogen isotope values are
not largely thought to be influenced byevapotranspiration and evaporation of river andgroundwater in forest.

evaporation

altitude effect of isotope
precipitation

evaporation

surface run off
groundwater

river
Tunnelmetal contaminatedriver

Fig. 10 Schematic diagram for water pass fromprecipitation to river and tunnel.
CONCLUSION
During the several tunnel constructions for the
Keinawa high way road, arsenic contamination rocks
composed of granite were found at the north ofMedian Tectonic Line in the Kii Peninsula. During
tunnel construction, arsenopyrite (FeAsS) was
certainly found from cracks of granite and in thesheared black colored granite and then main arsenic
source is thought to be arsenopyrite. Arsenic
688

GEOMATE - Mie, Japan, Nov. 21-24, 2017

observation at Matsumoto Tunnel, Matsumoto
city, Japan”, Int. J. of GEOMATE, Vol. 13, Oct.
2017, pp. 79-88.
[2] Kubohara T, and Ii H, “Cu, Co and Ni
contamination index for using river insects andriver plants”, Int. J. of GEOMATE, Vol. 11,
Oct. 2016, pp. 2651-2658.
[3] Kubohara T, and Ii H, “Evaluation of metal
contamination for river using bryophyte in the
Kinokawa River catchment”, Int. J. of
GEOMATE, Vol. 13, Sep. 2017, pp. 108-115.
[4] Ii H and Nishida A, “Effectiveness of using
river insect larvae as an index of Cu, Zn and As
contaminations in rivers, Japan”, Int. J. of
GEOMATE, Vol. 12, May. 2017, pp. 153-159.
[5] Fred M. Rhoades “A Review of Lichen andBryophyte Elemental Content Literature with
Reference to Pacific Northwest Species”, Forest
Service Pacific Northwest Region: UnitedStates Department of Agriculture, 1999.
[6] Sakai H and Matsuhisa Y, Stable Isotope
Geochemistry. Tokyo: University of Tokyo
Press, 1996, ch. 4.
[7] Ishizuka M, Sone Y, Ii H and Hirata T, “Effectof enriched early dropped rainwater on
mesoscale isotopic distribution in surface wateron the Kii Peninsula, Japan”, Water Resources
Research, Vol. 42, W12410.2006, pp.1-16.
[8] Yokota K, Ii H and Taniguchi M, “Effects ofaltitude and distance from coastline of oxygen
stable isotope for precipitation in theYakushima Island”, Environmental Engineering
Research, Vol. 47, 2010, pp. 667-677. inJapanese.
[9] Miyahara S and Ii H, “Proposal of simple
measurement method for evaporation rate byusing oxygen isotopic ratio”, Int. J. of
GEOMATE, Vol. 3, Sep.2012, pp. 318-324.
[10] Japan
Meteorological
Agency,http://www.jma.go.jp/jma/kishou/info/coment.ht
ml, 2017.
[11] Kondo J, Nakazono M, Watanabe T and
Kuwagata T, “Hydrological climate in Japan(3)-Evapotranspiration from forest-”, J.Japan
Soc. Hydrol. & Water Resour., Vol.5, No.4,
1992, pp8-18. in Japanese.
[12] Ishizuka M, Ii H, Tsutsumi H and Hirata T,“Characteristics of surface water chemistry inthe small forested basin in the Izumi mountains”,
Proceedings of hydraulic engineering, JSCE,
Vo.45, 2001, pp1015-1020. in Japanese.
[13] Allison G.B, Brown R.M and Fritz
P, ”Estimation of the isotopic composition oflake evaporate.”, Jour, of Hydrol., Vol.42, 1979,
pp.109-127.

concentrations of tunnel water were found to be over
0.1mg/L, the Japanese Effluent Standard. Riverarsenic concentration in the study area was also
found to be widely over 0.01 mg/L, the JapaneseEnvironmental Water Quality Standards. Arsenic
concentrations of river bryophyte and gammarus in
the study area were widely high relative to thenormal area and then widely arsenic contamination
was found.
Most copper concentrations of the tunnel waters
with copper minerals such as chalcopyrite (CuFeS2)
and chalcocite (Cu2S) were less than 0.02 mg/L
however copper concentrations of river waters in the
study area widely reached 0.1 mg/L. The copper
concentration of tunnel water is thought to be low
because of high pH control of concrete. Copper
concentration of river bryophyte in the study area
was 10 to less than 100 mg per kg and reachedseveral thousand mg per kg. Then, some places inthe study area were copper contaminated.
Molybdenum concentrations of some tunnel
waters around molybdenite (MoS2) occurrence areas
were over 0.07 mg/L, the Japanese Monitoringrequired Water Quality Parameters and then, main
molybdenum source is thought to be molybdenite.
Arsenic,
copperandmolybdenum
werecontaminated in some places of the study area at thenorth of Median tectonic line and this contaminatedzone is thought to spread east and west parallel toMedian Tectonic Line.
The recharge age of tunnel water is estimated tobe less than 12.3 year using 3H concentration. Riverand tunnel waters derive from precipitation howeveroxygen and hydrogen stable isotope values weredifferent. Although even altitude difference between
top of the hill and river level is less than 100m, theoxygen and hydrogen stable isotope differences
between river and tunnel water are 0.5 ‰ and 4 ‰,respectively and the difference is over twice ofaltitude effect. Then, the isotope difference between
river and tunnel waters is thought be caused by both
evaporation and altitude effect of isotope. Althoughevaporation and evapotranspiration rates were verylarge, the isotope difference between river andtunnel waters were too small. Oxygen and hydrogenstable isotope values are not thought to be largely
influenced by evapotranspiration and evaporation ofriver and groundwater in forest because under highhumidity condition isotope effect of evaporation issmall.
REFERENCES[1] Ii H, “Tunnel construction impact on
groundwater character over 25 years of689

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

GENETIC DIVERSITY OF PSEUDOLABRUS SIEBOLDI, USUAL FISH
SPECIES IN A WESTERN JAPAN COASTAL AREA
Michiko Masuda1, Wataru Kawase2 and Fumitake Nishimura3
1

Department of Civil Engineering, Nagoya Institute of Technology, Japan; 2 Shizuoka Prefectural Government,
Japan; 3 Department of Environment Engineering, Kyoto University, Japan
ABSTRACT

Pseudolabrus sieboldi is a very common labrid fish at Japan coastal region, so the species wasn't being watchedso much up to now. Therefore, the habitats of P. sieboldi have been developed easily. But it's pointed out thatgenetic isolation is easily occurred due to being polygynya in their mating system. In order to investigate thegenetic diversity of usual species, we sampled 6 populations of the species form western Japan coastal area, andstudied them for allelic variation at 24 enzyme loci. In comparison with other sea fishes, the total genetic diversity
is standard. Though sex ratio was inclined to females and inbreeding were easy to be performed, the gene diversity
was not decreasing. In fact, there were inbreeding mating within the population. Moreover, standard genetic
distance within populations along the Japan Sea is high and standard genetic distance within Pacific Ocean area islow. The fry of the species dispersed to the Pacific or Japan Sea. When they grew adults, they returned along rocky
shores for mating. The populations along Pacific Ocean did not return exactly at their birth area. On the other hand,the populations along the Japan sea returned more exactly at their birth area.
Keywords: Genetic Diversity, Genetic Distances, Coastal Conservation, Pseudolabrus sieboldi, Mating System
and genetic diversity of P. sieboldi to know thegenetic structure of usual species with 3 questions, 1)
Is there a relationship between the location andgenetic distance? 2) Is there a difference between
Pacific Ocean side and Japan Sea side? 3) Do theadults fishes return to the birth area? The attention
was paid at above-mentioned 3 points in our study.

INTRODUCTION
Recently it's thought that the conservation ofgenetic diversity is very important [1]-[3]. Many
researchers have pointed out the importance of thegenetic conservation. The maintenance of genetic
diversity is important for endangered species. Though
the same investigation was also necessary to usual
species for genetic diversity to be maintained, few
studies were done up to now.
Pseudolabrus sieboldi is very common labrid
fishes along rocky shores in the East Asian temperateregion. Recently Mabuchi and Nakano showed thespecies separated form P. eoethinus [4], differing incoloration and morphological characters. Mabuchi etal., also investigated the genetic diversity among 3
populations [5]. They collected 5 fishes each
population, total 15 fishes, and investigated. There
were some differences observed two labrid fishes.
But they couldn’t analyze the population structure
because of low numbers of species. Mabuchi et al.,also reported the mating system of the species, andthey are polygamous [6]. Polygamous species
restricts gene flow and caused population isolation.
Maruyama personal observation (2001) revealed
the larva of the species was observed at Pacific Ocean
and Japan sea, not at coastal area [7]. The
phenomenon suggested the adult fishes breed atcoastal area, the larva fishes go to Ocean and growing
fishes returned to coastal area. The phenomenon
suggests the gene flow easily occurred in Ocean.
In this study, we investigated the genetic structure

MATERIALS AND METHODS
Study Site
The samplings were carried out on 6 locations ofwest Japanese seashore (Fig. 1). Specimens (from 26
to 31 fishes) were collected from 6 localities widely
distant from each other: 30 samples Nobeoka Bay atMiyazaki Pref., 26 samples Senzaki Bay at
Yamaguchi Pref., 30 samples Miho Bay at Shimane
Pref., 31samples Seto Bay at Nagasaki Pref., 28
samples Tasoura Bay at Mie Pref. and 30 samples
Miyagawa Bay at Kanagawa Pref.

Fig. 1690

Map of sampling localities.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Miyazaki is Seto sea area, Yamaguchi, Shimane,and Nagasaki are Japan Sea area. Mie and Kanagawa
are Pacific Ocean area.

dehydrogenase (ADH), aldrase (ALD), menadione
reductase (MR), phosphoglucomutase (PGM) andglucose 6 phosphate dehydrogenase (G6PDH).
Muscle tissues were used to resolve the following 19
loci: tpi-1, tpi-2, mdh-1, mdh-2, mdh-3, mdh-4, acp1, acp-2, mpi-1, mpi-2, gpd, 6pg, pgi, me, adh, ald,
mr, pgm and g6pdh. Liver tissues werecorrespondingly used for 5 loci mdh, me-1, me-2,
pgm and adh. We followed previous works [6][8][9]about staining.

The Study Fish
Pseudolabrus sieboldi Mabuchi and Nakano avery common labrid fish at coastal region in Japan(Fig. 2). They have white spits on the dorsal part ofthe body from initial to terminal phase (IP and TP,
respectively). The species is known as the fish which
does a sex change, and all larval fish is being born asa female. Within a population the largest female
exchanges her sex to male. A matured male makes theterritory at sunken rocks and reproduces with a lot of
females.
Pair spawning occurred within TP male territories
during the daytime. P. sieboldi spawned above
smaller rocks with seaweed and seagrass, whereas P.
eoethinus.
(a) IP

The Statistical analysis
The number of alleles per locus (A), proportion ofpolymorphic loci (P), and gene diversity (h) were
calculated on each population. Additionally, total
gene diversity [10] was calculated for species level.
The population genetic structure was analyzed byinitially calculating Nei’s GST value [10]. Values forstandard genetic distance (D) was calculated for eachpairwise comparison of all populations. The neighborjoining method [11] based on D was used forconstructing a phenogram for P. sieboldi.

(b) TPRESULTS
24 loci were scored (19 for muscle and 5 for liver).
All loci have at least two alleles in at least one
population. Table 1 summarizes the resultant valuesof A, P and h for each population.

Fig. 2. Different phase of P. sieboldi, left side (a) is
IP (initial phase female) and right side (b) is TP(terminal phase male).

Table 1 Mean number of polymorphic loci (A),proportion of polymorphic loci (P), and genediversity within a population (h) at 24 loci for
examined populations of P. sieboldi

Electrophoresis

Population
Miyazaki
Yamaguchi
ShimaneNagasaki
Mie
Kanagawa

All fresh fishes were collected from 26-31
individuals per population in 2004 and 2005. Fishes
were kept on ice during transportation to thelaboratory. A part of liver tissues and muscle tissues
were cut and homogenized being added with anapproximately equal amount of 0.5M sucrose solution.
And homogenized tissues were centrifuged at
10,000rpm at 5 minutes. The supernatants were
subjected to horizontal starch gel electrophoresis. A
tris-citrate buffer system no.5 (Soltis et al. [6]) wasused. Starch gels were run for 2 hours at 80mA in arefrigerator at 4oC. After the run, the gel was sliced
horizontally. The following enzyme systems were
examined: triose-phosphate isomerase (TPI), malate
dehydrogenase (MDH), acid phosphate (ACP),
mannosephosphateisomerase(MPI),
Glycerophosphate dehydrogenase (GPD), 6phosphogluconate dehydrogenase (6PG), phosphoglucose isomerase (PGI), malic enzyme (ME), Alchol

A
2.208
1.583
1.542
1.792
1.542
1.792

P
0.917
0.500
0.542
0.625
0.500
0.750

h
0.206
0.217
0.092
0.091
0.028
0.019

And total gene diversity (HT) of the species was
0.278. The levels of genetic diversity in P. sieboldi
was high that of other fish species, for example,
Sonoran topminnow of 0.03 to 0.116 [12].
The mean level of isozyme variation within
populations and the total gene diversity of the species
are given in Table 2. The resultant hierarchicalanalysis of population genetic structure is GST. GST of
Pacific Ocean is 0.03, on the other hand, GST of Japan
Sea is 0.31. That of Japan Sea was higher than that ofPacific Ocean.
691

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 3 showed the phenogram using the NJ
methods based on Nei’s standard genetic distance[11].

fixation index at the Pacific Ocean side populations
was higher than those of others. The result showedthat inbreeding occurred within a population and theeffective population size is small at the Pacific Oceanside populations. The inbreeding was expected fromthe mating system of the labrid species. But there was
no inbreeding at other 4 populations.
Our data show another interesting fact. Standard
genetic distance within populations along the Japan
Sea is high (D=0.180). On the other hand, that within
the Pacific Ocean side is low (D=0.000). It showed
the gene flow easily occurred along the Pacific Oceanside, but hardly occurred along the Japan sea side.
And there was no relationship between real distanceand genetic distance. From the phenogram
populations of the Japan Sea side contains the Pacific
Ocean side populations.
The fry of the species disperses to the Pacific
Ocean or the Japan Sea. When the fry is grown up,
they return along rocky shores for reproduction. The
populations along the Japan Sea side return their birtharea exactly because of the genetic distances over0.01. But the populations along the Pacific Ocean side
did not return to birth area exactly due to the genetic
distance value within 0.01, so there were high geneflow among populations.

Table 2. Inbreeding coefficient within a population(FIS), Fixation index (FST) and inbreeding coefficientamong total populations(FIT).
Population
Miyazaki
Yamaguchi
ShimaneNagasaki
Mie
Kanagawa

FST-0.262
0.347
0.336
0.570
0.657
0.716

FIS
0.415
-0.196
0.504
0.236
0.703
0.754

FIT
0.262
0.220
0.670
0.672
0.898
0.930

Nagasaki
0.056
Mie
0.061
0.025

0.003
Kanagawa
0.016
Shimane0.041

Yamaguch

CONCLUSION

0.193

We get three main conclusions.
1) There is no relationship between the real distanceand genetic distance.
2) There is a difference between the Pacific Oceanside population and the Japan Sea side
population. The Pacific Ocean side populations
have low genetic diversity and easily occurredinbreeding. The Japan Sea side populations havehigh genetic diversity and isolated each
population.
3) The matured individuals returned exactly at theJapan Sea side population, on the other hand,
mixed return occurred at the Pacific Ocean side
populations.
Based on the conclusions, two proposals about theconservation activities are considered
1) There is a possibility of inbreeding in thepolygamous mating system species, so theinvestigation should be done at usual species,
because of low genetic diversity.
2) We should know the differences between theJapan Sea area and the Pacific Ocean area.

MiyazakiFig. 2
Phenogram using the neighbor joining
method based Nei’s (1987) standard genetic
distance. Under line locations are Pacific Oceanarea, □locations are Japan sea locations.
DISCUSSION
Mabuchi and Nakano investigated about thegenetic diversity of the species [5]. There were somegene diversity among populations. But the sampling
size was 5 each 3 populations. Then they cannot
analyze the genetic structure of the species. In thisstudy, we can collect over 25 individuals from 6
populations and analyze the genetic structure.
In comparison with other sea fishes, the total genediversity is standard [1][2]. But there are somedifferences about gene diversity among populations.
The gene diversity within a population (h) of Mie andKanagawa (Pacific Ocean side) was lower than thoseof other population. The value of h is from 1/4 to 1/6of the expected value. Moreover, the value of the

ACKNOWLEDGEMENTS
We wish to thank the fishermen advice to us forfishing. We also thank the members of our laboratory
for their assistance in the field works.

692

GEOMATE - Mie, Japan, Nov. 21-24, 2017

electrode buffesr and staining schedules”, Amer.
Fern J., Vol. 73, Jan. 1983, pp9-27.
[7] Maruyama T. “Morphology and distribution inlarva of labrid fishes”, graduate thesis of Ehime
University, Feb. 2002, in Japanese.
[8] Westerbergh A, Saura A. “The effect ofserpentine on the population structure of Silene
dioica (Caryophyllaceae)”, Evolution, Vol. 46,
Oct, 1992, pp. 1537-1548.
[9] Chepliak WM, Pitel JA, Techniques for starchgel electrophoresis of enzymes from forest tree
species., Information report PI-X-42., Petawawa
National Forestry Institute, Canadian Forestry
Service, 1984.
[10] Nei M. Molecular evolutionary genetics. New
York: Columbia University Press, 1987.
[11] Saitou N, Nei M, “The neighbor joining method:a new method for reconstructing phylogenetic
trees”, Molecular Biology and Evolution, Vol. 4,
1987, pp406-425.
[12] Vrijenhoek RC, Douglas ME, Meffe GK,“Conservation genetics of endangered fish
populations in Arizona”, Science, Vol. 229, July,
1985, pp. 400-402.

REFERENCES[1] Frankham R, Ballou JD, Briscoe DA.
Introduction
toConservation
Genetics.
Cambridge: Cambridge University Press, 2ndedition, 2010, ch. 3.
[2] Schonewald CM. Genetics and Conservation: areference manual for managing wild animal andplant populations. Washington, The BlackburnPress, 2004.
[3] Avise JC, Hamrick JL. Conservation Genetics:
Case Histories from Nature, Chapman & Hall,New York, 1996, ch. 5..
[4] Mabuchi K, Nakano T, “Revision of the genus
Pseudolabrus (Labridae) from the East Asianwaters”, Ichthyological Research, Vol. 44, May,
1997, pp. 321-334.
[5] Mabuchi K, Kobayashi T, Nakano T, “Genetic
Differences between two Pseudolabrus species(Osteichthyes: Labridae) from the southerncoasts of Japan”, Species Diversity, Vol. 5, May,
2000, pp. 163-172.
[6] Soltis DE, Haufler CH, Darrow DC, Gastony
GJ., “Starch gel electrophoresis of ferns: acompilation of grinding buffers, gel and693

SeventhInternational Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE INTEGRATION OF OUTDOOR HUMAN THERMAL COMFORTIN TROPICAL CLIMATE CAMPUS LANDSCAPE:CHULALONGKORN UNIVERSITY, BANGKOK, THAILAND
Ariya Aruninta1, Yoshihito Kurazumi2, Kenta Fukagawa3, and Jin Ishii4
Dept of Landscape Architecture, Faculty of Architecture, ChulalongkornUniversity, Thailand
2
Dept of Human Environment Design, Sugiyama Jogakuen University, Japan
3
Dept of Architecture, Kyushu Sangyo University, Japan
4
Dept of Architecture, Meijo University, Japan

1

ABSTRACTThe purpose of this research is to study and compare the outdoor spaces with different cooling effects
facilities in the tropical climate, city campus in the CBD of Bangkok, Thailand. The study aimed to find the most
comfortable outdoor space in a green campus referred to UI GreenMetric World University Ranking indicators,
the case study of Chulalongkorn University, tropical wet, in city center/high rise building. The ratio of area on
campus covered in planted vegetation (lawns, gardens) provided as percentage of total site area) will becompared, especially, the micro-climatic seems to be an important criteria of the physical design features of an
outdoor space: a) with cooling devices – shading, fountain, b) without cooling devices – pavement, open lawn.
The cooling effect of these devices which are evaluated by measurement result of thermal comfort responded bytropical environment of the campus. The study will also analyze the human physiological and psychologicalresponse in summer / less humidity (in March) and rainy / high humidity (in September) season. The study will
explain Micro/Macro-climatic effects from landscape features. The survey measured meteorological condition of
the outdoor spaces, skin temperature of the subjects by attaching sensor on skin surface, and then distributed
thermal sensation survey to collect psychological thermal comfort of the subjects. The study found out that the
shortwave solar-radiation, long-wave radiation from different materials should play an important role in a newparadigm in green design and planning.
Keywords: Thermal comfort, Micro climate, Outdoor environment, Climatic effect, Green campus
interact most efficiently and safely, especially in theindoor environment. But methods for making an
outdoor environment comfortable are very limited,while outdoor and indoor comfort zones may differ
from each other, so adaptation or acclimatization tothe outdoor environment should be studied [1]. This
paper aims to integrate human thermal sensation andpsychological responses as outdoor thermal
environment evaluation index in landscapearchitecture design and planning of an urban campus.
The factors influenced in outdoor environment
comfort are included this followings: the albedo,
sky temperature and surface temperature, humidity,
wind direction, air velocity, shortwave solarradiation and long-wave radiation heat quantity. In
addition, the measurement of sky and green upwardand downward ratios from an orthographic photo ofeach site will be considered in the study. A design ofan outdoor space, usually depends on functional andother aesthetic concepts. The authors who are fromdifferent research fields have intensively utilized theyear long surveys in different seasons for their own
aspects. This paper is intended to seek for a newparadigm in green design and planning to remediate
the urban heat island effect especially in campus

INTRODUCTIONUI GreenMetric has been launched in 2010 by
Universitas Indonesia, which the key objectives
initiated as the cooperative efforts among groups ofworld universities in order to take steps to manage
and improve their sustainability and help combat
global climate change. Chulalongkorn University
was ranked the world 15th of ‘City Center’ campus
setting category in 2016 and aims for the higher
ranking in the next following years. The green
campus planning involves the landscape design ofcampus outdoor environment and while there arestill the needs to decrease energy consumption
especially for indoor Heating, Ventilation, Air
Conditioning (HVAC) system. Thus, it leads to theresearch questions on campus outdoor thermal
comfort as followings: 1) how human sensation
responses to each outdoor space in summer andrainy seasons, 2) what cooling effects facilities in thetropical climate should be designed for outdoor
space for the best thermal comfort.
Many researches in ergonomics have focused on
the thermal comfort in designing and arranging
things people use so that the people and things694

GEOMATE-Mie, Japan, Nov. 21-24, 2017

survey due to the unavailability of the new
construction site, and north playfield was intended tocompare the difference between high and low SkyFactors, identified by the surrounding conditions(Table 1-2).

planning along to improve the thermal environment
from harsh to comfortable, in order to draw potential
activities to outdoor space and reduce energy
consumption in the buildings.
EXPERIMENTAL DESIGN

Table 1 Summary of summer season observation
pointsThis research surveys were designed to collectdata both from measurements of the meteorologicalcondition of the outdoor spaces in summer and rainyseason and the human physiological andpsychological response to those outdoor spaces. The
surveys were performed during two days in March(summer/dry season) and in September (rainy/wet
season) during the day time only from before noon
to the afternoon which is usually the peak hours of
outdoor space occupancy of the campus. The very
simple comparisons of the data aim to seek for themost comfortable condition of the outdoor spaces.

Site

Sky

Building
court

ConcreteEaves

1Open-air
café

Woodendeck

Awning /Trees

2

Pond side

Grass /
Pond

Trees

3

North
playfield

Trees

4

Engineering
bldg

Grass /
Bare
groundConcretepavement

5

Auditorium
plaza

Concretepavement0Sunshade/ TreesOpen

Surrounding
North

East

South

West

Building

Building

Building

Building

Building

Building

Open

Wall /
Tree

Open

Open

Trees

Trees

Open

Open

Trees

Open

Open

Building

Trees

Building

Building

Open

Open

Open

Table 2 Summary of rainy season observation points

Measurement Procedure

Site

The observation points and route patterns areshown in Fig. 1. For the comparisons, observation
points were selected with consideration of thecondition of the ground surface, such as paved
ground, green areas covered with plants, and water
surfaces, and with consideration for the condition of
the sky factor due to buildings and trees. Six
observation points were chosen in summer season
survey and five observation points were chosen in
Rainy season survey.

Fig. 1

Surface
GroundSurface
GroundSky

0

Building
court

Concrete

Eaves

1

Pond side

Grass /
Pond

Trees

2

North
playfield

Open*

3

Engineering
bldg

Grass /
Bare
groundConcretepavement

4

Auditorium
plaza

Concretepavement

Sunshade/ TreesOpen

Surrounding
North

East

South

West

Building

Building

Building

Building

Open

Open

Trees

Trees

Open

Open

Open*

Open

Open

Building

Trees

Building

Building

Open

Open

Open

Site Related Factors
When considering the thermal sense of humans,
it is necessary to include not only air temperature but
also the environmental elements of thermal radiation,
convection, humidity, and heat conduction. Briefly,
a strong solar radiation gives a hot feeling, a strong
wind gives a cool feeling, high humidity gives afeeling of an unpleasantly warm and humid (muggy
weather), and a heated ground surface that it cannot
be touched make us feel so hot. Kurazumi et al. [2][5] who revealed the relationship between thephysiological and psychological responses ofhumans and invented the enhanced conductioncorrected modified effective temperature (ETFe) as
the outdoor thermal environment evaluation index,
clarified in many of their research papers that thevariables that affect the thermal sensation are heat
conduction, humidity, and short wave solar radiation,
air velocity, heat conduction, and humidity.
Air temperature, humidity, wind direction, airvelocity, shortwave solar-radiation heat quantity,
long-wave radiation heat quantity, and groundsurface temperature were measured. The air

Sites location maps and patterns of survey
routes in summer and rainy season in thepeak hours (AM/PM).

Seasonal Related Factors
The observation points in summer season(March) and rainy season (September) were adjusted
accordingly with the experiments. Therefore, thepoint at open-air café was removed in rainy season
695

GEOMATE-Mie, Japan, Nov. 21-24, 2017

on the measurement day. The clothing quantity ofthe subjects was sought by the clo value by layering
the clothing reported by the subjects. As a
psychological condition for the human body, thepsychological response was measured after staying
at the observation point for 5min by means of rating
the whole-body thermal sensation (cold-hot) and thewhole body thermal comfort (comfortableuncomfortable) on a linear scale as Kurazumi et al2011.

temperature and humidity were measured at a heightof 90cm above the ground by means of an Assman
ventilated psychrometer. For the air velocity, theprevailing wind direction was measured for 5min ata height of 120cm above the ground by means of athree-dimensional
ultrasonicanemometer.
Concerning when the wind was very gentle, theaverage air velocity was measured for 5min at aheight of 120cm above the ground by a nondirectional anemometer and the three-dimensional
ultrasonic anemometer.
The short-wave thermal radiation heat quantity inthe regions from the visible to the near-and-midinfrared and the terrestrial thermal radiation in the
far infrared region, thermal radiation heat quantities
in downwards and upwards directions were
measured at a height of 90cm above the ground bylong and short-wave radiometer. The ground surface
temperature was measured by a radiation
thermometer.
The sky factor was measured by a photograph ofthe sky taken 120cm above the ground at theobservation point using a fisheye lens with an
orthographical projection format and a 35mmdigital
SLR camera. The albedo, sky temperature, andsurface temperature were calculated from eachdirectional component of the short-wave thermalradiation heat quantity and the long-wave thermalradiation heat quantity. The abbreviations and themeaning are as followings:
Ta is range of air temperature. Tf is range ofground surface temperature in the vicinity of thehuman body. RH is relative humidity. Va is air
velocity. RSdwn is downward short wave solar
radiation. RSup is upward short wave solar radiation.
RLdwn is downward long wave radiation. RLup is
upward long wave radiation.
The influence of short wave solar radiation in
outdoor environment appears to be strong in summer,
when the air temperature is higher than the skintemperature of the human body, evaporation is the
only means of dissipating heat [2].

The Cooling Effect Conditions and the Thermal
Environment Stimuli
Urbanization is a major cause of Urban Heat
Island (UHI) phenomenon, relates to a highpercentage of low-albedo and impermeable surface,a reduction of the cooling effect of shading, building
up areas and especially the urban canyon where heatis reradiated and reflected back to the surroundedenvironment [6].
Planners always include shade tree wherever
possible as a strategy to reduce heat islands andimprove outdoor environment in three ways ;through shading, through evapotranspiration, andthrough wind shielding [7],[8]. The studies in many
regions confirm that tree shade is an ecologicalsolution to reduce both mean radiant and surface
temperature, tree canopy can filter and absorb solar
radiation, whilst be most affects human’s thermal
comfort or physiologically equivalent temperature(PET) [7],[9].In macro scale, urban parks have been
demonstrated to have a significant cooling effectstrongest for land surface temperatures ofsurrounding urban areas as far as 860 m from thepark boundary[6].
While pavements with light-colored surfaces canoffset or reverse the heat island, which have highsolar reflectance and high thermal emittance canreduce the temperature of the surface, which reduce
urban temperature and improve urban air quality insummer season [6],[11],[12],[13].
Human Physiological and Psychological Responses
There was a study that acclimatization will nothave significant difference of psychological reaction
when the subject could not tolerate the environment
at the temperature is greater than 40˚C [4]. And Thai
people from a tropical region perceive an ETFe of
up to around 35˚C to be a moderate thermal
environment but cannot tolerate the temperaturearound more than 40˚C [5] or 3˚Cthan normal bodytemperature or normothermia = 36.8 ±0.7 °C.
Therefore, the effective outdoor environment
designers should be aware of the harsh environmentand consider avoid alternatives and factors that cancreate heat radiation especially in summer.

Human Related Factors
Subjects moved on foot to the observation points
without being planned to reduce mental fatigue atthe slow walking speed (around 0.7 m/sec), they
were exposed to the thermal environment in astanding posture. Skin temperatures were measured
as physiological conditions for the human body by athermistor thermometer. Skin temperature wasmeasured at the positions of the head, trunk, arm,
hand, thigh, lower leg and foot. The subjects freely
selected their clothing to be suitable to the weather
696

GEOMATE-Mie, Japan, Nov. 21-24, 2017

celestial sphere solid angle. According to Fig. 3 andFig. 4, the sites with the highest D-green factor are
pond site and north play field, where ground iscovered with grass, water, and bare ground. U-green
factor in each site shows tree canopy coverage ratio.
Therefore, at the north playfield site, when themeasurement point was moved from under the trees
to the field, sky factor is higher more significantly.
In addition, the auditorium site has higher sky factor
and less D-green factor, thus it tends to directly
expose to the radiation.

RESULTS OF EACH SITE’S THERMALENVIRONMENT
After data calibration, the results frommeasurements were compared in different methods
to illustrate the effects site conditions to humanthermal comfort. The results after comparing three
key issues; seasonal, site, and human related factors;
to find the high potential thermal comfort outdoor
environment in the urban campus.
GroundSummerRainy

Sky
Summer

Rainy

North
playfield

Pond side

Open-air café

Building court

Site[Summer season] Characteristics of thesites with different cooling conditions

Fig. 4[Rainy season] Characteristics of the sites
with different cooling conditions

Auditorium
plaza

Engineering
bldg side

Fig. 3Fig. 2Ground and sky photos of the sites withdifferent cooling conditions

Site Cooling Effects
The most significant factors to explain sitecooling effect are 1) Sky factor, 2) U-green factor,
and 3) D-green factor. From Fig. 2, ground and sky
orthographic photos of the sites show different
cooling conditions of space, especially ground coverand pavement materials from ground photos andbuilding canyon and tree canopy from sky photos.
Thereafter, sky factor and U-green / D-green
factor have been simulated. Sky factor is defined as
the ratio of configuration factor of sky to semicelestial sphere. U-green factor is defined as theratio of upward green, water surface and the likesolid angles to semi celestial sphere solid angle. Dgreen factor is defined as the ratio of downward
green, water surface and the like solid angles to semi

Together with the sky factors and green factors,
at each site, other factors relates to albedo effectwere measured, in order to explain the cooling effectof the sites (Table 3). These included the meanvalues of RSdwn (downward short wave solar
radiation), RSup (upward short wave solar
radiation), RLdwn (downward long wave radiation),
RLup (upward long wave radiation), Ta (air697

GEOMATE-Mie, Japan, Nov. 21-24, 2017

Rainy

SummerTable 3 Meteorological condition of the sites with different cooling conditions
Site[ND]
0-Building court
1-Open-air café
2-Pond side
3-North playfield
4-Engineering bldg side
5-Auditorium plaza
0-Building court
1-Pond side
2-North playfield
3-Engineering bldg side
4-Auditorium plaza

RSdwn[W/m2]
20.32
47.58
107.24136.2028.63
437.279.79
82.40
581.3618.42
371.61

RSup[W/m2]
4.67
3.36
26.05
35.64
3.60
116.06
0.42
17.94
96.92
-0.82
91.32

RLdwn
[W/m2]
484.41484.24478.67479.79482.99462.90482.76481.67451.17482.53467.72RLup[W/m2]
482.61488.76478.92489.40484.68530.50472.87479.84509.57479.57511.83

Mean Va

Mean RH

Mean Ta

0.58
0.69
0.95
1.52
0.79
1.61
0.80
0.68
1.63
0.83
1.22

61.51
60.87
61.09
63.05
62.48
61.02
59.36
61.44
58.47
62.13
59.46

30.10
30.00
30.20
30.20
30.20
30.90
30.8
30.8
31.5
30.5
31.4

DISCUSSION ON INTEGRATION OF HUMAN
THERMAL COMFORT AND SITE
CHARACTORISTICS

Table 5 [Rainy season] Mean temperature

We assumed that site characteristics of how theoutdoor spaces and their surroundings have been
designed are the key factors influence humanthermal comfort. Results from meteorologicalcondition of the sites show that both in summer andrainy seasons, the less cooling condition issignificantly presented at auditorium south side
plaza, where Tf-Ta is very high.

Time
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
1-Pond side
1-Pond side

Table 4 [Summer season] Mean temperature
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
0-Building court
1-Open-air café
1-Open-air café
1-Open-air café
1-Open-air café
2-Pond side
2-Pond side
2-Pond side
2-Pond side
3-North playfield
3-North playfield
3-North playfield
3-North playfield
4-Engineering bldg
4-Engineering bldg
4-Engineering bldg
4-Engineering bldg
5-Auditorium plaza
5-Auditorium plaza
5-Auditorium plaza
5-Auditorium plaza

10-1150
10-1330
10-1533
10-1716
11-1045
11-1226
11-1417
11-1604
10-1206
10-1552
11-1104
11-1438
10-1224
10-1659
11-1209
11-1456
10-1316
10-1610
11-1120
11-1549
10-1242
10-1642
11-1153
11-1515
10-1257
10-1628
11-1139
11-1530

Ta[℃ Tf[℃]
30.1 30.04
30.5 35.61
30.3 30.93
29.5 34.49
29.5 32.84
31.2 35.04
31.6 35.47
31.0 37.49
30.0 31.67
31.1 36.52
30.0 35.85
32.1 37.97
30.2 32.68
29.6 31.82
30.8 32.75
31.3 32.37
30.2 35.28
29.9 34.70
30.5 34.87
31.4 38.55
30.2 33.72
29.6 34.78
30.3 33.68
31.5 34.61
30.9 41.08
29.9 41.36
30.8 47.23
32.3 45.92

Tf-Ta
-0.06
1.67
2.48
5.08
3.52
10.18
-3.6
-0.9
5.9
-0.1
7.3

It is interesting that the sites, where surrounded withbuildings and pavement such as building court andEngineering building side, have quite high RLdwn
radiation. Whilst, the open field area with grass orbare ground such as north play field has very highRS both upward and downward, in addition to quite
high RLup but very low RLdwn.

temperature), Tf (ground surface temperature), RH(humidty), Va (air verocity), and Tf-Ta (cooling
effect temperature). The underlined numbers areamong those with cooling effect presented, and in
opposite, the bold numbers are those with harshthermal effect presented.

Time

Mean
Tf
30.04
31.67
32.68
35.28
33.72
41.08
27.2
29.9
37.4
30.4
38.7

1-Pond side
1-Pond side

difT Mean
-0.06
3.53
5.11
0.63
4.99
3.34
3.84
3.87
6.49
1.67
4.70
5.42
5.85
5.87
2.48
1.93
2.22
1.95
1.07
5.08
5.35
4.80
4.37
7.15
3.52
3.80
5.18
3.38
3.11
10.18 12.92
11.46
16.43
13.62

2-North playfield
2-North playfield
2-North playfield
2-North playfield
3-Engineering bldg
3-Engineering bldg
3-Engineering bldg
3-Engineering bldg
4-Auditorium plaza
4-Auditorium plaza
4-Auditorium plaza
4-Auditorium plaza

16-1033
16-1211
16-1336
16-1512
17-0943
17-110717-1254
17-1419
16-1054
16-1455
17-1050
17-1312
16-1114
16-1441
17-1034
17-1327
16-1133
16-141217-1017
17-1344
16-1149
16-1356
17-1001
17-1359

Ta[℃] Tf[℃]
31.1
28.7
31.6
20
32.2
29.5
30.8
28.5
29.4
26.2
30.2
27.2
30.5
29.2
30.5
28.3
31.4
30.8
31.2
30.6
30
29.1
30.6
29.2
32.5
38.7
31.2
34.7
30.4
35.3
32
40.8
31.4
30.4
30.7
31
29.8
29.3
30.2
30.9
32.5
37.1
31.8
41.3
30.4
36.2
30.8
40.2

difT
-2.4
-11.6
-2.7
-2.3
-3.2
-3.0
-1.3
-2.2
-0.6
-0.6
-0.9
-1.4
6.2
3.5
4.9
8.8
-1.0
0.3
-0.5
0.7
4.6
9.5
5.8
9.4

Mean
-3.6

-0.9

5.9

-0.1

7.3

CONCLUSION
Chulalongkorn University aims for the higher
ranking of UI GreenMetric in the next following
years. The landscape design of urban campus
outdoor environment still needs to decrease energy
consumption especially for indoor HVAC system.
Findings from the research, which integrated humansensation responses to each outdoor space insummer and rainy seasons and the meteorologicalcondition of the sites have shown a significant
finding that cooling effects facilities in the tropicalclimate can be designed for the best thermal
comfort, spaces between buildings in the very high698

GEOMATE-Mie, Japan, Nov. 21-24, 2017

Journal of Climate Change, Vol. 5,2016, pp. 5268.
[5] Kurazumi Y. et al., "The influence of tropicalurban climate upon the human body.", in Proc. :International Joint-Conference of SENVARiNTA-AVAN 2015, Johor.
[6] Al-Gretawee H, Rayburg S, Neave M, "Thecooling effect of a medium sized park on an
urban environment", International Journal of
GEOMATE, Oct., 2016, Vol. 11, Issue 26, pp.
2541-2546.
[7] Tukiran J MD, Ariffin J, Ghani A N A,
"Cooling effects of two types of tree canopy
shape in Penang, Malaysia", International
Journal of GEOMATE, Aug., 2016, Vol. 11,
Issue 24, pp. 2275-2283.
[8] Huang Y J, Akbari H, Taha H, "The windshielding and shading effects of trees on
residential heating and cooling requirements", inProc. :the ASHRAE Winter Conference, 1990.
pp. 1403–1411.
[9] Matzarakis A, Mayer H, Iziomon M G,
"Applications of a universal thermal index :physiological equivalent temperature", Int J
Biometeorol, V.43: 1999 pp.76–84.
[10] Tukiran J MD, Ariffin J, Ghani A N A, "A
study on the cooling effects of greening for
improving the outdoor thermal environment in
Penang, Malaysia", International Journal of
GEOMATE, June, 2017, Vol.12 Issue 34, pp.
62-70.
[11] Akbari H, Pomerantz M, Taha H, "Coolsurfaces and shade trees to reduce energy use
and improve air quality in urban areas", Sol.
Energy, vol. 70, no. 3, Jan. 2001, pp. 295–310.
[12] Taha H, Hammer H, Akbari H, "Meteorologicaland air quality impacts of increased urban
albedo and vegetative cover in the Greater
Toronto Area, Canada", Berkeley, Calif., 2002.
[13] Rosenfeld AH. et al., "Mitigation of urban heatislands: materials, utility programs", Energy and
Buildings, Vol. 22, 1995, pp. 255-265.

density area would be able to create a comfort zone
for outdoor activities. The most interesting finding
from this study is the paved outdoor space with lessshade can create very harsh thermal condition.
Therefore, although the built up area is the major
cause of UHI, but a court area between a group ofbuildings with tree canopies can offer a comfort
zone both in summer and rainy season. Open fieldarea is good as an infiltrated ground for Water
Sensitive Urban Design (WSUD) and keeps theaverage temperature cool only being covered withgrass. The heat from shortwave solar-radiation, andlong-wave radiation ; so called albedo effect andemissivity ; should play an important role in humanthermal comfort and landscape design of an outdoor
space.
ACKNOWLEDGEMENTS
The corresponding author would like to thanks
the Japanese authors who have travelled with all the
instruments to Thailand, a hot and humid country,
several times throughout the years in order to makethis research possible.
REFERENCES[1] Honjo T., "Thermal comfort in outdoor
environment", Global Environmental Research,
13/2009, pp. 43-47.
[2] Kurazumi Y. et al., "The influence of outdoor
thermal environment on young Japanese
females", Int J Biometeorol, Vol. 58, 2014, pp.
963–974.
[3] Kurazumi Y. et al., "Evaluation of enhanced
conduction-correctedmodifiedeffective
temperature ETFe as the outdoor thermal
environment evaluation index", Energy and
Buildings, Vol 43, 2011, pp. 2926–2938.
[4] Kurazumi Y. et al., "Ethnic differences inthermal responses between Thai and Japanese
females in tropical urban climate", American

699

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-23, 2017, ISBN: 978-4-9905958-6-9 C3051

ANALYSIS OF TSUNAMI IMPACT TO COASTAL VEGETATIONAND GEOLOGICAL LANDSCAPE AT KUALA TERENGGANU
1,2

Nurfarhana Aisya Anuar1 and Abdul Halim Abdul Latiff2
Faculty of Geosciences and Petroleum Engineering, Universiti Teknologi PETRONAS, Malaysia
ABSTRACTIn this study, the impact of potential tsunami occurrences on the Kuala Terengganu coastline, which originatedfrom the Manila Trench is analyzed. The tsunami effects were investigated with the aid of wave simulation models
while considering the coastal vegetation and geological factors of the study area. This study was initiated because
several seismologist and earth scientist discovered that there is a possibility of an earthquake with the magnitude
9.3 Mw will occur along the Manila Trench. Thus, to identify the potential tsunami impact on the East CoastPeninsular Malaysia area, data were gathered from field study and was used to generate a tsunami wave
propagation model and a run-up and inundation model. From the result, a tsunami will reach the coastline by 11
hours with a maximum wave height of 0.143m, a run-up height of 0.5m, and an inundation distance of 4m.
However, in consideration of external variables, a new model was constructed with a maximum wave height of
1.5m, a run-up height of 2m, and an inundation distance of 14m. The studied area, Batu Rakit beach coastline wasflooded and areas near the coastline have a high risk of getting impacted whereas areas with coastal vegetation
have a lower risk of impact.
Keywords: Tsunami; Geological Landscape; Coastal Vegetation
models. Whereas, the tsunami wave propagation
model will display the propagation of the tsunami
waves originating from the Manila Trench and thetime and magnitude of the tsunami impact on the
coast of Batu Rakit beach.

INTRODUCTION
Earthquakes and tsunami have caused countless
lives and assets losses throughout the history of
mankind. The greatest tsunami that has hit Malaysia
recently is the 2004 Andaman seaquake, which holds
a magnitude of 9.0. The Andaman Tsunami causes
more than 240,000 deaths throughout the Indian
Ocean coastline. Later, in 2011, a tsunami of a similar
magnitude took place off the Pacific coast of Tohoku,
Japan resulting in a death toll of 15,891 whereas
2,500 lives are still missing. Both major earthquakes
occur along a subduction zone. The next subduction
zone near Malaysia is the Manila Trench (Fig. 1).
Researchers are now predicting a potential
earthquake of a magnitude of 9.3 occurring from theManila Trench. Therefore, it is essential to identify
the impact of a tsunami originating from the Manila
Trench on the coast of Malaysia.
In this study, the potential tsunami impact on the
coastline of Batu Rakit beach, Kuala Terengganu will
be simulated. The geological landscape of the study
area such as the bathymetry, slope of the coastline aswell as the shape of the coastline will be identified
and used when generating the tsunami simulation.
The coastal vegetation of the study area will also be
considered. The objectives of this study is to study thegeological landscape of Batu Rakit beach coastline aswell as to construct a tsunami wave propagation
model. Information on the geological landscape of
Batu Rakit beach will be analyzed and taken into
consideration during the generation of the tsunami

Figure 1: Location of the Manila Trench from Kuala
Terengganu
EARTHQUAKES AND TSUNAMI
The Earth’s lithosphere is broken into pieces
called tectonic plates. These plates are constantly
moving due to the tectonic cycle which can be
simplified into four stages; formation of new
700

GEOMATE- Mie, Nov. 22-23, 2017

constant gradient with a gentle slope will form atsunami with lower speed compared to the seabedwith a sudden change in slope angle [5].

lithosphere from magma, seafloor spreading, plate
collision forming subduction zones and reabsorptionof the old plate into the mantle. These subduction
processes create tremendous stores of energy, which
are released periodically as earthquakes [1]. Tsunami
comes from the Japanese word “Tsu” and “Nami”
meaning harbour and waves respectively, thus isdefined as waves that increase in velocity and heightas the waves enter a harbour [1, 2]. As obtained fromthe Australian Government – Geoscience Australia
by Liew [2], 75% of the tsunami are caused byearthquakes, whereas the cause of 10% of the tsunami
are unknown followed by 8% due to landslides, 5%from volcanic eruptions and 2% from meteorologicalimpact. However, not all earthquakes can produce atsunami. Tsunami only develops when an earthquake
occurs in the ocean [3] with a vertical fault movement
and an earthquake of M7.5 [1]. These earthquakes canalso lead to underwater landslides and trigger tsunami.

Figure 2: Six segments of the Manila Trench,referred from [4]THE MANILA TRENCH
The Manila Trench is located on the west side of
the Philippines. The 1200 km-long subduction zone
is formed during the early Miocene and continue
active to the present day. Along the Manila Trench,
the South China Sea oceanic crust inclines eastward
below the Philippines, southern Taiwan and theoverriding ocean floor [4]. Several researchers haveassessed the tsunami hazard from Manila Trenchsource and concluded that the worst case scenario isan earthquake with a magnitude 8.2 as there havenever been recorded instrumentally an earthquake
exceeding 7.6 in the area. However, considering thelength of the Manila Trench, other researchers
proposed that a larger earthquake with a magnitude
up to 9.0 or 9.3 could occur [4]. Considering the fault
geometry of the Manila Trench, the Manila Trench is
divided into six segments (Fig. 2). Table 1 indicatesthe parameters of a source model for the Manila
Trench proposed by Nguyen et. al [4] sufficientenough to generate an earthquake of 9.3 Mw.

ROLE OF COASTAL VEGETATION IN
TSUNAMI EVENTSCoastal vegetation has been proven to ensure thestabilization of the beach and slope areas. Studies
have shown damages and impacts from tsunami
reduced due to the protection of the coastal vegetation.
However, some authors disagree, stating that no real
proof existed on the mitigation effects [6]. Despite
that, V. Selvum stated that the mangrove forests, a
type of coastal vegetation have protected the shore ofsouthern India against cyclones and other storms forthousands of years [7]. Similar in Malaysia, claims
have been made on how fishermen were saved during
thee tsunami of December 2004 due to the existenceof mangrove swamps along the Penang coastline. The
mangroveforests
minimize
erosionandsedimentation affects as well as dampening andabsorbing the wave energy. The mangrove forests
also contribute to the low settlement density in certain
areas thus reducing the risks to both human andproperty [7].

GEOLOGICAL FACTORS INFLUENCING
THE TSUNAMI IMPACTTSUNAMI SIMULATION MODELLING

The strength of a tsunami is measured by the wave
speed and run-up including how far inland thetsunami can travel. The factors that influence thestrength of the tsunami waves are the seaquake
magnitude, seaquake depth, shore distance with theepicentre and coastline morphology or bathymetriccharacteristic as well as the seabed gradient [5]. The
deeper the earthquake depth, the weaker the tsunami
generated. Whereas in term of the coastline
morphology, weak tsunami is generated if thegradient is greater nearing the shore. However, aTheIntergovernmental
Oceanography
Commission, the depth-averaged two-dimensional
shallow water equations (SWE) can be used tosimulate the tsunami propagation in deep ocean. The
conditions of the applicability of SWE is when the
wave heights are smaller than the depths of water andthe wavelengths. Comparing the 3D and 2D models,
2D models is adequate enough as the 3D models
require excessive memory and long computationaltime [8].
701GEOMATE- Mie, Nov. 22-23, 2017

Table 1: The hypothetical fault parameters of Manila Trench source [4]
Fault

Lon.

Lat.

1
2
3
4
5
6

120.5
119.8
119.3
119.2
119.6
120.5

20.2
18.7
17.0
15.1
13.7
12.9

Length
(km)
190
250
220
170
140
95

Width
(km)
120
160
160
90
110
80

Dislocation
(m)
25
40
40
28
12
5

The tsunami simulation used in the project is
TUNA software, which uses the shallow waterequations and under normal assumptions, theequations describing the conservation of mass andmomentum can be depth averaged and be written as
the following equations [8].

Depth
(km)
30
30
30
30
30
30

Strike
(⁰)
354
22
2
356
344
331

Dip
(⁰)
10
20
28
20
22
26

Rake
(⁰)
90
90
90
90
90
90

ANALYSIS OF COASTAL MAP
From the initial field study conducted, the coastal
map and seafloor cross-section of Batu Rakit
coastline was constructed and modelled (figure 3 andfigure 4). A total of 11 coordinates were taken along
the coastline of Batu Rakit beach with an interval of
100 m. The coastline of Batu Rakit beach is rather
straight, facing the South China Sea at a North-East
direction. The cross-section is perpendicular to thecoastline, with P6 as a starting point. The beach has awidth of 30 meters and the coastline elevation rise toalmost 6 m above the sea level. The difference
between high tide and low tide is around 1.5 metersvertically and 10 meters horizontally. The averageslope of the area is of 10⁰ thus is considered a gentle
slope. There is also a rather thick beach forest locatedat P1 and continues northwest of the area. Between
P3 and P4, more coastal vegetation is observed(figure 5). There are fisherman villages along thecoastline. At the end of the study area, starting from
P11, large granite boulders are observed. Theseboulders are used to prevent further coastal erosion to
the area. The coastal erosion defense continues up to
2 km eastward of the beach.

METHODOLOGYFirst, we conducted a few field studies in order tohave a deeper understanding of the geologicallandscape as well as the coastal vegetation available
at Batu Rakit coastline. During the fieldwork, thegradient of the beach will be measured to create thecross-section of the Batu Rakit coast and seafloor.
Traversing of the coastline is performed to obtain an
accurate image of the coastline. The work conductedsimilar to the procedure proposed in [9].
Then the tsunami wave propagation was modelled
by incorporating TUNA tsunami simulation software.
This software will be used to generate tsunami
simulation on the area of study. Certain criteria will
be taken into consideration during the generation of
the simulation such as geological landscape of thestudy area as well as the fault displacement, fault
location and focal depth of the tsunami origin. The
input parameters of the TUNA Software are divided
into five main controls; domain and output control,
source control, boundary control (other control),bathymetry control and time series. The domain andoutput control defines the computational power
required and the output by adjusting the number of
iterations, grid size, computational nodes and others[8]. Other controls section defines the boundary
conditions, whether the boundary is open or close. In
this section, the gravitational acceleration and theManning’s coefficient is also determined [8]. The
bathymetry and topography of the area is set in thebathymetry control section. The number and locationof observation points to record the wave simulation
height of the ocean is adjusted in the time series
control [8].

Figure 3: Coastal Map of Pantai Batu Rakit

702

GEOMATE- Mie, Nov. 22-23, 2017

Figure 4: Seafloor Cross-section of the Pantai Batu Rakit Coastline from A to B

Figure 5: Field Map of Batu Rakit beach.
TSUNAMI PROPAGATION MODEL
Seven tsunami wave models are generated using
the TUNA-M2 Software. The models are generated
according to the parameters in Table 2. The
parameters are obtained from Nguyen et. al [4] as thesource model incorporated all advantages of twomodels proposed by Wu and Huang (2009) andMegawati et al. (2009). However, the width of thefault zones is altered to 10km due to the difference inwidth definition used for the simulation. Six of themodels generated simulate the tsunami wave
propagation originating from different fault zones;
Fault 1 to Fault 6. Whereas one model is generated tosimulate the worst case scenario where the tsunami
wave propagation originates from all fault zones
simultaneously. All the models are run for 40001s ofsimulation. In all the models, by 11 hours, the tsunami
waves reach the coast of Kuala Terengganu but withdifferent wave heights. The maximum wave heights
for each tsunami model is recorded in Table 3.

Comparing each individual faults, the tsunami
waves originating from Fault 3 shows the highest
maximum wave height followed by the waves
originating from Fault 2, Fault 4, Fault 1, Fault 5 andFault 6. Fault 3 has the highest wave height due to its
high fault dislocation of 40m as well as the directionof the strike. However, the worst case scenario is
when the tsunami waves originates from all the fault
zones simultaneously with a maximum wave heightof 0.143m. The propagation of the tsunami wave
originating from all faults is shown in Fig. 7.
Table 3. Maximum wave height for each tsunami
models
Fault
Maximum Wave Height (m)Fault 1
0.028
Fault 2
0.059
Fault 3
0.082
Fault 4
0.042
Fault 5
0.018
Fault 6
0.006
All Faults
0.143
703

GEOMATE- Mie, Nov. 22-23, 2017

Figure 8: Tsunami Wave Run-up and Inundation
Model Originating from All Fault Zones

Figure 7: Tsunami wave simulation originating fromall fault zones simultaneously.
A tsunami wave run-up and inundation model isgenerated from the tsunami propagation model
originating from all faults simultaneously to illustrate
the maximum wave height as well as to identify the
run-up height and inundation distance of the tsunami
impact. With a maximum wave height of 0.143m, therun-up height of the tsunami impact is 0.5m and theinundation distance is 4m (Fig. 8). Regardless of the
9.3 magnitude earthquake in the Manila Trench, thetsunami has low impact on the coast of Batu Rakit
beach.

Figure 9. Tsunami Wave Run-up and Inundation
Model while Considering External Variables.
Thus, the inundation map of Batu Rakit beach(Fig. 10) indicates that the whole coastline, coloured
light blue, will be submerged by the tsunami. As thegeological landscape of the coastline is straight andfaces the open ocean, the energy of impact along thecoastline is constant. Areas in yellow colour have ahigh risk being effected by the tsunami, whereas areas
with coastal vegetation have a lower risk of impact by
the tsunami as the vegetation works as a barrier toprevent the tsunami from moving further inland.

However, in this study, the propagation model isgenerated with limited variables. In reality, many
more variables can influence the tsunami wave
heights. The earthquake in the Manila Trench may
reactivate other faults within the area as well as
triggering underwater landslides at nearby
continental slopes especially along the Palawan
Island where the continental slope is fairly steep thus
contributing to the impact of the tsunami. In a casewhere these events may occur, a higher maximum
wave height will hit the Batu Rakit coastline.
Considering the external variables, a higher
maximum wave height may be achieved. In a casewhere the maximum wave height is 1.5m, a run-up
height of 2m whereas the inundation distance of 14m
could occur (Fig. 9).

704

GEOMATE- Mie, Nov. 22-23, 2017

faults and underwater landslide occurring near the
Manila Trench are to be considered to identify theworst case scenario for precautionary measures.
ACKNOWLEDGMENT
We would like to Universiti Teknologi PETRONAS
for the resources and support in completing thisproject.
REFERENCES[1]

Figure 10: Inundation Map of Batu Rakit beach. Blue
region indicate the area will be flooded by sea water,while the yellow region is the high risk area.

[2]

CONCLUSION & RECOMMENDATIONIn this study, the study on the geologicallandscape of Pantai Batu Rakit Coastline was done.
Pantai Batu Rakit is a straight coastline facing theSouth China Sea in the northeast direction. The
coastal slope of the area is gentle with a gradient angleof 10o. Coastal vegetation are present along thecoastline, as well as fisherman villages and granite
boulders as coastal erosion defence. Several tsunami
wave propagation models were constructed. The
parameters used in this study generates an earthquakeof magnitude 9.3 in the Manila Trench. The models
indicate that the tsunami waves will reach thecoastline of Pantai Batu Rakit in 11 hours. The model
originating from all faults simultaneously shows thehighest maximum wave height. A tsunami run-up andinundation models is also generated thus concludingthat the tsunami waves with the following parameters
have low impact on the coast of Pantai Batu Rakit.

[3]

[4]

[5]

[6]

However, many more external variables may
contribute to the tsunami wave height. Considering
the worst case scenario involving these externalvariables, a new tsunami wave run-up and inundation
model is constructed. From this model, it is identified
that the coastline of Pantai Batu Rakit will be
submerged. Areas close to the coastline have high riskof tsunami impact except areas with coastal
vegetation which will have a lower risk. In conclusion,
all the objectives of this study is met. It is
recommended a further study of this project is to be
done. More possibilities such as the reactivation of

[7]

[8]
[9]

705

P. L. Abbott, Natural Disasters, 7th. ed.,New York: McGraw-Hill, 2009.
M. S. Liew. (2015, May). Impact of
Tsunami on Oil and Gas Facilities in the
Malaysian Waters from Manila Trench.
Presented
atUniversiti
Teknologi
PETRONAS Sharing Session.
Nola Taylor Redd. (April, 2015)
Earthquakes & Tsunamis: Causes &Information[Online].
Available:http://www.livescience.com/2148
6-earthquakes-causes.html
P. H. Nguyen, Q. C. Bui, P. H. Vu and T. T.
Pham, “Scenario-based Tsunami Hazard
Assessment for the Coast of Vietnam from
the Manila Trench Source,” Physics of the
Earth and Planetary Interiors, vol. 236, pp.
95-108, 2014.
B. Chatenoux and P. Peduzzi, “Impacts fromthe 2004 Indian Ocean Tsunami: AnalyzingthePotential
Protecting
RoleofEnvironmental Features,” Nat Hazards, vol.
40, pp. 289-304, 2007.
J. C. L. Bayas, “Modeling the Influence of
Coastal Vegetation on the 2004 Tsunami
Wave Impact”, doctoral dissertation, Facultyof Agricultural Sciences, University of
Hohenheim, Germany, 2012.
F. Colbourne, “Tsunami Impact on the West
Coast of Penang Island, Malaysia”, Research
Project Report, Emporia State University,
United States of America, 2005.
H. L. Koh & S. Y, Teh, “TUNA User
Manual”, Universiti Sains MARA, 2010.
S.S.S. Singh and A. H. Abdul Latiff,“Tsunami impact analysis to geologicallandscape in Perak coast, Malaysia”, in Proc.
6th Int. Conf. on GEOMATE, 2016, pp. 8-13.

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

FISH CATCH QUOTA ASSESSMENT FOR SUSTAINABLE MARINEFISHERIES RESOURCES IN EAST JAVA
AlfanJauhari1, *DefrianMarzaArisandi1, Abu Bakar Sambah1,2, WildanAlfarizi1
1

Faculty of Fisheries and Marine Science, Brawijaya University, Indonesia; 2Marine Resources Exploration andManagement Research Group, Brawijaya University, Indonesia
Veteran Street Malang east Java*)

Correspondence Author
ABSTRACTFish resources Information urgently needed by development planners in fisheries sectors, especially for fisheries
development. Quantitative information like the potential assessment number is determined by the presence orabsence of basic information such as the results of the surveying research vessel, and also from the informationthat is collected through a regular monitoring; particularly catch effort data, the fishing season, and the migrationof certain species in respective territorial waters. The fisheries resources utilization in East Java tends to be over
exploited. This caused uncertainty of fishing activities for the traditional fishermen in the East Java waters. Somestudies of population dynamics and fish stock assessment described fisheries resources exploitation in someareas of East Java was on fully exploited to over exploited condition. The aim og this research were; [1] to know
sustainable potential and total allowable catch of fisheries resources in the area of Pasuruan regency,
Probolinggo regency, and Banyuwangi regency; [2] tho know the utilization status of fisheries resources in thearea of Pasuruan regency, Probolinggo regency, and Banyuwangi regency; and [3] to determine theempowerment strategy for fishermen community in order to utilize fisheries resources in the area of Pasuruan
regency, Probolinggo regency, and Banyuwangi regency. The analyses were done through the calculation ofsustainability potential, and total alowable catch, and determine the controlling strategy of fisheries resources
utilization. The study described that the comparison analysis of fishing trip data, fish catch and total alowable
catch in the sustainable condition was in the over exploited condition. Moreover, based on the analysis offisheries resources utilization status in the research area, the controlling strategy was created based on therecommendation of all stakeholders. These strategy including the management of fishing area, management offishing time, and determine of an alternative activities in the scope of both fisheries and non-fisheries sectors.
These strategies can be used as a basic data in determining an empowerment strategy for fishermen in thefisheries resources utilization. These strategies including accompaniment approach and information services
through community and ecosystem based of fisheries resources management.
Keywords: fisheries resources, sustainability, total allowable catchpressure of exploitation of fishery resources in someareas such as East Java has experienced full
exploitation until more exploitation. This will affectthe work being built on the coastal area of East Java,or work as a fisherman. When the level of
exploitation of marine fisheries resources in themouth of East Java has experienced more capturethen the catching operation is not possible to be
repaired. This situation creates social and economic
problems for coastal communities. Arrangement of
capture quotas is one of the solutions to regulate
excessive exploitation pressure on marine fish stocks
in East Java.

INTRODUCTION
Information on fish resources is needed by
the special fisheries development planners for thedevelopment of capture fisheries. Quantitative
information such as potential numbers is largely
determined by the presence or absence of
information from survey results of research vessels
as well as from information collected through theperiodic weather system, in particular catch data,
fishing seasons, and distribution for certain speciesof fish in each region see (Purnomo, 2002).
The utilization of marine fisheries in East Java canbe said to have experienced excessive levels of
exploitation. This will impact the uncertainty offishing effort done by traditional fishermen in EastJava responsible area. Various studies of population
dynamics and indicator estimates indicate the

METHODSThis research is one of analyticaldescriptive research that is describing real condition
706

GEOMATE -Mie, Japan, Nov. 21-24, 2017that exists in field and doing situation analysis todata obtained. Descriptive method of analysis is amethod of gathering facts through appropriate
interpretation. This method of study is aimed atstudying the problems that arise in society in certain
situations, including community relations, activities,
attitudes, opinions, and ongoing processes and theireffects on certain phenomena in society. Thismethod is used to answer the research objectives,
namely;.................................................(1)Where :CpUE = Capture per unit of effort= Average portion of fishing gear 1 to total
fish production= Average catch of fish by fishing gear
= Mean Effort of the fishing gear
Considered standard (trip).
While the RFP is calculated using the equation:

1. To know the amount of sustainable potential and
JTB fish in the waters of the study area.
2. To know the status of the utilization of fisheryresources in the territorial waters of the study.
The steps taken to answer the first goal are:
1. Collection of captured data
The data collected is data collected from 10 years
since 2004-2013, the data is secondary data.
2. Treatment of data
The 10-year data is intended to obtain standard
data as input for analysis using Schafer, fox andWalterhilbern formulas. The treatment technique
is using the formula RFP (Relative Fishing
Power).
While the steps to answer the second
research objectives are:
1. Compare the sustainable potential value
calculated in the previous step to the actual
utilization rate in 2014.
2. Decision making to determine the status of
resource utilization expressed in the sustainableutilization rate..

...............................................(2)Dimana :RFPY/Y/= Index type conversion tool
Catch
= Catch per unit effort respectively
each fishing gear
= Catch per unit effort from tool
standard

Maximum Estimates Sustainable
The estimation of maximum sustainablebalanced tuna is done by using holistic approach or
surplus production method that is Schaefer model(1954) and Fox (1970) to determine which method is"best fit" which is able to represent actual
exploitation level of tuna. The maximum amount ofeffort sustained (fMSY), and maximum sustainable
yield (YMSY) can be calculated by the formula(1) According to Schaefer (1954)...............................................(3)dan........................(4)Where :
Y = Catch
F = Attempts to catch
A = Intercept of Schaefer model
B = Slope of Schaefer model
Ymsy = Maximum sustainable catch (potential
Sustainable catch)Fmsy = Sustainable fishing effort

Fig. 1 Study Area
[A] Pasuruan Regency;[B] Probolinggo Regency[C] Banyuwangi Regency(2) Menurut Fox (1970).........................................................(5)dan........................(6)Conversion of the Catching Efforts
The fisheries management model refers to theassumption that fishing gear must be transferred intoa standard unit. Thus it can be said that the fishinggear is made into one unit equivalent to the catchingequipment that is considered standard. The
conversion method used with the equation:

Where :
cd

= Intercept of Fox model= Slope model Fox

To calculate the utilization rate of a fishery resourceby the formula:
JTB = 80%Ymsy....................................................(7)707GEOMATE -Mie, Japan, Nov. 21-24, 2017

phenomenon or phenomenon of education. The
Likert scale is a psychometric scale commonly usedin questionnaires, and is the most widely used scale
in research surveys.
Based on the data obtained from respondents'
answers, then it is processed by multiplying eachpoint answer with the weight that has been
determined with the weighted table of values, using
the equation as follows:
Total Score = ( Answer x Weight strongly agree)+ ( Answer x Weight agreed) + ( Answer x
Neutral Weight) + ( Answer x Weight not agree)+ ( Answer Weight strongly disagree)
To get the result of interpretation, must first known
the highest score (X) and lowest number (Y) for
item of assessment with formula as follows:
Y = highest score likert x number of respondents(5th highest score) "Notice the Value Weight"
X = Likert's lowest score x number of respondents(Lowest number 1) "Notice the Value Weight"
So the assessment of respondents' interpretation of
the strategy of controlling the utilization of Marine
Fishery Resources in Pasuruan Regency is the resultof the resulting value using the formula Index% asfollows:
Formula index% = (Total score) / (Y × 100)

Estimation of the Potential of Sustainable
Reserves and Potential Backup
According to Walter and Hilborn (1976)
biomass from year t + 1, Bt + 1 can be expectedfrom Bt plus biomass growth for one year was
reduced by a certain amount of biomass during theyear reduced by the amount of biomass released by
exploitation of effort (f). The determination of stock
biomes follows the calculation by the equation:.....................................................(8)Where :
Bt = biomass stock at time t
Pdt = dB / dt = growth rate of biomass, intrinsic(Ton / yr)
K = maximum carrying capacity of natural waters
against biomass
R = intrinsic growth rate of population stock
T0 = time at Bt = ½ k
T = time, year, month and so on
The potential for sustainable reserves is obtained
from the equation Be = ½.k. While the potential offish stock in 2013 is obtained by the equation:
Bt+1 = Bt +Pdt – Yt.......Yt = ft x Bt x…..............(9)=Pdt = r x Bt - x Bt²........................................(10)DISCUSSION
Illustration of Concepts
The concept that try to be described ingeneral based on the existing condition is mainly
related to the utilization of marine fishery resources
obtained through several previous scientific studies
and inventory activities of potentials and issues at
the field level (location of the study).

Preparation of Control Strategies
Fish Resources
The compilation of alternative strategies
and the interest analysis of some of these structured
alternatives will be based on: Identification of potential carrying capacityof non-fishery fisheries in Pasuruan,
Probolinggo, and Banyuwangi.
 Identify issues of future utilization,
problems and prospects of fishery resources
in Pasuruan, Probolinggo and Banyuwangi
districts through observation and interview(questionnaire distribution).
 Focus Group Discussion (FGD) withstakeholders in the fishery and non-fisheryfields in Pasuruan, Probolinggo and
Banyuwangi districts to prepare whether or
not alternative strategies have beendeveloped.

Utilization of Fishery Resources by Fisherman of
East Java CONDITION STUDY• Open access• Analysis of• Common property

oceanographic factors• Overfishing-Under fishing• Catch Effort Survey• IUU Fishing• Mapping of potential• Natural phenomena

fishing areas• Indications of coastal
degradation

Sustainable
Management

Measurement of Interest Scale
One of the measurement of attitude scale in
the formulation of alternative interests of control
strategy of utilization of Marine Fishery Resources
in Pasuruan Regency, Probolinggo Regency and
Banyuwangi Regency is analysis in Likert Scale.
Likert scale according to Djaali (2008) is a scale thatcan be used to measure the attitude, opinion, andperception of a person or group of people about aFisheries
Resources
Management
Model Stock estimation
 Determination of
the number ofcatches allowed

Fig 2. Concept Research Framework

708

Strategy ofcontrolling theutilization offish resources

GEOMATE -Mie, Japan, Nov. 21-24, 2017

increase of 96,539 trips from 2008. Then it
decreased 112,822 trips in 2010 and then increased
in 2011 With 2013 as many as 128.51 trips. The
dominant fishing gear is payang, in this case theprediction of the result of the conversion of fishinggear and the amount of fish catch in Pasuruan waters
is needed because this is related to the estimation ofboth models. The results of the conversion of fishinggear to the standard of fishing gear and the numberof fish catch can be seen through Table 2.

Existing Fishery Potential as a Guideline for
Determining the Strategy of Fish Resources
Utilization Control.
A preliminary survey related to the
production of capture fisheries in the three study
areas is presented in Table 1.
Table 1. Production by fishery sub-sector per
District (in ton)Catch
Reegency
Amount For Prov.
East Java
Pasuruan
Probolinggo

Total

Sea

PublicWaters395.046,8

381.573,913.472,97.807,3

7.634,1173,29.755,7

9.665,290,549.663,1

49.532,0131,1Table 2. Data on the number of standard converted
tools
Catch fish in
Effort standart
Year
CpUE
Payang (trip)
water (ton)2004

561184,610403,40.018538(Source: East Java Fishery Statistics Data, 2016)

2005

550286,213139,30.023877

Based on Table 1, Banyuwangi Regency isthe area of study with the largest fishing productionin the sea when compared to Pasuruan andProbolinggo districts. Based on this data, theestimation of the utilization status of capture fisheryresources in the study area can be based on dominantcatch fish production, and into the catch groupwhich has important economic value..

2006

391226

9817,50.025094

2007

401990,19544

0.023742

2008

402027,5

9411,50.02341

2009

743624,3

9510,50.012789

2010

342852,1

7037,30.020526

2011

496436,4

7607,83

0.015325

2012

474066,3

7814,30.0164842013

694523,5

7634,10.010992

Banyuwangi

AnalysisofmarinePasuruan Regency

fisheries

resources

Based on the table of fishery production in
Pasuruan waters, in Figure 3 presents fluctuations in
the production of catches in Pasuruan.

The highest number of fishing gear was
743,624.3 trips in 2009 with catches of 9,510.5 tons.
The Schaefer and Fox models refer to the principleof the Surplus Production Model, the Schaefer andFox is also called the equilibrium state model.
Schaefer and Fox models can predict MSY
conditions from optimum production amount(Ymsy), optimum catcher (fmsy). Fishery status andexploitation rate can be analyzed throughcomparison of optimum production value withproduction value in the last year or it can also
through the number of fishing gear. Potential
Sustainable Reserve (Be) fisheries in waters can be
known through the Walter-Hilborn equation
approach. This method does not depend on theequilibrium conditions of a stock of fishery biomass
as in Schaefer's method (1954) and Fox (1970). In
addition, this method is able to estimate the valuesof population parameters (r = intrinsic biomass stock
growth rate (constant), k = maximum natural bearing
capacity, q = capture
capability (catchability
coefficient) in the model so as to make predictions
more dynamic and closer to reality In the field Thismodel is also known as the model of nonequilibrium state model.Based on the results of theanalysis on this model obtained the following
results:

Fig 3. Graph of fish production in Pasuruanwaters(Source: East Java Fishery Statistics Data, 2016)

Fig 4. Proportion of trips of four types of fishinggear inWaters of Pasuruan.
The development of the standard payang
fishing equipment shows that gear equipment inPasuruan waters has the highest increase of 235,438
trips from the previous year from 2004 to 2008 there
was a decrease of 66,509 trips. In 2009, there was an
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GEOMATE -Mie, Japan, Nov. 21-24, 2017

Table 3. The value of the non-equilibrium state
model
Variable

Walter-Hilborn

Intercept

B0 = r

X variable 1

B12951,977462

X variable 2

B2 = q2,02622k7,0359Be

3,5179Analysis of Marine
Probolinggo District

Information :R = Intrinsic population growth rate
K = The maximum carrying capacity of the water(carring capacity)
Q = capability of catch (catchability coeficien)
Be = Potential reserve of sustainable fish
The utilization rate (TP) of fish obtained fromthe calculation of the average value of effort over thelast five years divided by fMSY. The result of thecalculation is multiplied by 100 resulting in autilization rate of 86%. From the calculation of theutilization rate can be said that the status of fisheryutilization in the waters of Pasuruan is fully
exploited the stock of resources already exploited
close to MSY value and the increase in the numberof fishing effort is not recommended.

Fig 5. Map of distribution of fishing area
Based on fishing gear in Kab / Kota
Probolinggo

Table 4. Potential sustainable yield data
MSY
JTB

Fox

Walter-hilbern

9.830,97.864,7

9,419
7,535

31154,84663
4,34404E-10

Productionofcatchesincreasedsignificantly from 2004 to 2006 by 56.9%.
Production of this catch in 2006 is the largest fish
production that is as much as 65,854.50 tons. While
the production of the lowest fish is 21,361,7 tons in2012. In 2008 the production of catch is relatively
fixed until 2010, and began to decline until 2013.
Fish production in 2006 to the year of 2007
decreased production by 32%, and continues todecline Until 2013. If compared with the highest
production (in 2006) then the decline until the year
2013 amounted to 34, 4%

Utilization of Fish Resources in Pasuruan
The catch (tons )Number of fishing trips
7942,9460868

Table 5. Potential sustainable yield data
585.231,9

Year
2014
460868124.363,9

Utilization
rate
Over

9.830,97942,91888

Over

7.864,76354.31510.4Over

Model Schaefer

Quantity

Fe (number oftrips of catchingequipment insustainablecondition) unit
Ye (number ofcatches ofsustainablecondition) tons /
year
JTB

ResultResources

Participatory mapping is done by involving
local fishermen in Probolinggo Regency to create amap of potential marine fisheries in Probolinggo
District / City waters. Validation of this map is done
through active participation in several trips fishing
operations at sea. This active participation also
records the main fishing grounds of all fishermen
who conducted fishing operations and had a fishingbase in Probolinggo District / Town, including
mapping the fishing grounds of Probolinggo District/ local fishermen as well as local naming tablatureand geographical position of fishing areas ofProbolinggo

102,5054386

Schaefer

Fisheries

At the level of pengoprasian fishing gear
has exceeded the capacity causing the occurrence ofover-fishing or over fishing. Therefore, efforts
should be made to formulate strategies forcontrolling the utilization of fish resources inPasuruan waters with technical fishing should notexceed MSY and for precautionary action by
catching does not exceed JTB.

Fig 6. Graph production yield in probolinggo
Potential Sustainable Reserve (Be) fisheries
in waters can be known through the Walter-Hilborn
equation approach. This method does not depend on
the equilibrium conditions of a stock of fisherybiomass as in Schaefer's method (1954) and Fox(1970). In addition, this method is able to estimate
the values of population parameters (r = intrinsic
biomass stock growth rate (constant), k = maximum
natural bearing capacity, q = capture capability
710

GEOMATE -Mie, Japan, Nov. 21-24, 2017

local naming tablature and geographical position of
Banyuwangi fishermen fishing area.

(catchability coefficient) in the model so as to makepredictions more dynamic and closer to reality In thefield This model is also known as the model of nonequilibrium state model.
Table 6. The value of the non-equilibrium statemodel
b1 = rb2
b3 = qk =b1/(b2*b3)

1,014468592
0,17940405
3,50335E-05
161407,0965

Be = k/2
Pd = (r*k)/4

80703,54824
1,57129E-06

Y_MSY = (b1*k)/440935,60749

f_MSY = r/(2*q)
U_MSY = C/E
JTB = 80%*Y_MSY
TP (rata2 E /Y_MSY)*100

14478,5434
2,827329128
32748,48599
79%

Fig 7. Map of distribution of fishing areas and fish
catching line in the Regency of Banyuwangi
Calculation of the result of the conversionof fishing gear and the number of fish catches in
Banyuwangi waters is needed because this is related
to the estimation of both models. The results of theconversion of fishing gear to the standard of fishinggear and the number of fish catch can be seen
through Table 8. While Table 9 illustrates thecalculation of the Potential Lestari And Total
Alowable Catch / Number of Fishes Captured (JTB).

Information :R = Intrinsic population growth rate
K = The maximum carrying capacity of the water(carring capacity)
Q = capability of catch (catchability coeficien)
Be = Potential reserve of sustainable fish
The utilization rate (TP) of fish obtained
from the calculation of the average value of effort
over the last five years divided by fMSY. The resultof the calculation is multiplied by 100 to yield theutilization rate of 79%. From the calculation of theutilization rate can be said that the status of fisheryutilization in Probolinggo waters is fully exploited ie
the stock of resources already exploited close to
MSY value and the increasing number of fishingeffort is not recommended.

Table 8. Data on the number of standard converted
tools
Year

Table 7. Potential sustainable yield data
MSY
JTB

Schaefer
65.511,55
52.409,24

Fox
59.817,56
46.053,11

Walter-hilbern
40.935,61
32.748,49

Utilization of Fish Resources
The results of thecatch(ton)22.686

Number of fishing trips

fY(Trip)

(Ton)

CpUE

2004

20.443,68

2.406,50

0,1177142005

101.189,86

13.876,80

0,1371362006

2.277,46

62.223,50

27,321482007

174.374,14

61.801,00

0,3544162008

7.104,27

51.371,00

7,231004

2009

69.562,34

51.371,00

0,7384892010

17.163,03

29.264,00

1,705062011

226.194,26

31.018,46

0,1371322012

65.406,91

38.879,95

0,5944322013

126.123,81

46.366,10

0,367624

2014

4608687942,90,017235

Table 9. Result of sustainable potential calculation
and Total Allowable Catch / number of fish that canbe caught (JTB)

159.054

3.5 Analysis of marine fisheries resources inRegency of Banyuwangi
Mapping of capture areas is done throughparticipatory mapping. This participative mapping isdone by involving local fishermen of Banyuwangi
Regency in making map of potential of marine
fishery in Banyuwangi Regency waters. Validationof this map is done through active participation inseveral trips fishing operations at sea. This active
participation also records the main fishing groundsof all fishermen who have been engaged in fishing
operations and have a fishing base in Banyuwangi
Regency, including mapping the fishing areas oflocal fishermen in Banyuwangi Regency as well as

b1 = r

1,778348467

Y_MSY = (b1*k)/41187559,319

b2

0,080916473

f_MSY = r/(2*q)

108070,0588

b3 = qk=b1/(b2*b3)

8,22776E-06

U_MSY = C/E

2.671.150,99

Be = k/2

1.335.575,50

JTB = 80%*Y_MSY
TP (Cthntrakhir/Y_MSY)*10
0

Pd = (r*k)/4

1.187.559,32

950047,4553
32%

Analysis of FGD Results on Formulation
Strategy
Based on the results of FGD analysis it canbe explained that the three alternatives of thecompiled strategy are alternative strategies that are711

GEOMATE -Mie, Japan, Nov. 21-24, 2017agreed by all FGD groups. This is evidenced by the
choice of all groups against the four strategies thathave been compiled. Based on the score of interest,
then strategy number 2 or is the preferred strategy
that ranks first the FGD results. The last strategy isthe alternative of other substitution fishery activities
in the hope that the stock of marine resources in thewaters of the research area is given time to recovernaturally. This indicates that it takes a certain periodof time for fishermen to be able to try alternative
fisheries and other non-fishery activities in responseto the catch status of more fish resources in the
research area.

can be done one of them based on the study ofpotential lestasi and fishery resource utilization
status first. [2] Comparison of data analysis on thenumber of fishing trips in sustainable condition, thenumber of fish catches in sustainable condition andthe number of catches allowed in the research area
indicates the utilization level of marine fisheryresources experiencing more catching condition. [3]Based on the analysis of the utilization status ofmarine fishery resources in the research area, thestrategy of controlling the utilization of fisheryresources is prepared based on the recommendationof all relevant stakeholders. These strategies include
setting up fishing grounds, setting up fishingseasons, and setting alternative fisheries / nonfisheries alternatives. This strategy forms the basis
for determining the setting of catch quotas forsustainable management of marine fisheries
resources in the research area. This strategy includes
advisory approach and information services throughcommunity-based fishery resource management
programs and ecosystems provided to fishermen.

Measurement of Interest Scale
Likert scale is done to measure approval anddisapproval of respondent to all alternative ofstrategy which is arranged, with level consist of: [1]strongly disagree; [2] disagree; [3] neutral between
agree and not; [4] agree; [5] strongly agree. Likertscale analysis in this research is based on strategy
which have been arranged in FGD and also analysis
of Likert scale result using weighted value table.

ACKNOWLEDGEMENTS

Table 10. Percentage of values of all alternative
strategies
strategy
1. The strategy for controlling theutilization of fish resources
includes:1. Capture time settings
2. Arrangement of catch areas
3. Alternative fishing andother non-fishery activities

The researchers would like to thank theEast Java Provincial Government, the Faculty ofFisheries and Marine Sciences of Brawijaya
University, the Stakeholders, and the Laboratory ofMarineResources
Exploration,
Brawijaya
University Indonesia.

Response Answer[1] [2] [3] [4] [5]0
0 5 11 7

REFERENCES[1].Djaali, 2008. Skalalikert. Jakarta: PustakaUtama.

Information :[1] strongly disagree; [2] disagree; [3] neutral; [4]agree;[5] strongly agree
Total Score[2].Data Statistik Perikanan. 2014. Potensi
Perikanan Kabupaten Pasuruan. Dinas Perikanan
dan Kelautan Provinsi Jawa Timur.

= (7 x 5) + (11 x 4) + (5 x 3) + (0 x 2) + (0 x 1)
= 94[3].Fox, W.W. Jr., 1970. An Exponential SurplusYield Model for Optimizing Exploited FishPopulation. Trans.Am.Fish.Doc., 99:80-88.

Based on the total score above, then theinterpretation result is calculated as follows :Y = 5 x 23 = 115
X = 1 x 23 = 23
Respondent's interpretation of the strategy ofcontrolling the utilization of Marine FisheryResources are:[4].Purnomo, H. 2002. Analisis Potensi dan
Permasalahan Sumberdaya Ikan Pelagis Kecil Di
Perairan Utara Jawa Tengah. Universitas
Diponogoro. Semarang.
[5].Schaefer, M., 1954. Some Aspects of the
Dynamics of Pupolations Important to theManagement of the Commercial Marine
Fisheries. Bull.I-ATTC/Bol.CIAT, 1(2):27-56(category highly agree)
CONCLUSIONS[6].Walters, C. J., and R. Hilborn. 1976. Adaptive
control of fishing systems. Journal of theFisheries Research Board of Canada 33:145159.

Based on the results of the study that has
been done can be concluded :[1] Research on the regulation of capture quota forsustainable management of marine fishery resources712

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

USE OF INSECTICIDE-TREATED NETS AMONG PIG OWNERS
LIVING IN JAPANESE ENCEPHALITIS ENDEMIC AREAS OFNORTHERN MYANMAR
Aung Kyaw Soe, Cheerawit Rattanapan, Somsak Wongsawass, Orapin Laosee*
ASEAN Institute for Health Development, Mahidol University, Nakorn Pathom 73170, Thailand
ABSTRACTJapanese encephalitis (JE) virus is the leading cause of vaccine-preventable encephalitis in Asia and theWestern Pacific region. This study was carried out to explore the use of insecticide-treated nets (ITNs) to prevent
JE among pig owners in the high endemic area of Kachin State, Myanmar. A total of 420 pig owners wereinterviewed by trained research assistants between March and May 2016. The majority of the respondents werefarmers with low family income, living in poor housing conditions. Pig-raising by respondents was mainly
categorized as closed-type (75%), however those pigs were kept in sties close to the house at night. Analysis
indicated that less than a quarter (21%) of family members slept under insecticide-treated nets at night.
Households with five or less members, owning more than two ITNs were more likely to use them at night (AOR:
3.71; 95% CI: 2.07-6.62) (AOR: 5.47; 95% CI: 3.20-9.33). This study highlighted the adequacy of providing
ITNs for all family members as a critical issue to prevent JE virus. Initiation of strategies to expand
interdisciplinary collaborations and communication in all aspects of health care for humans, animals and theenvironment could take place. Availability of vaccines must be reconsidered as they are important in prevention
and control of JE.
Keywords: insecticide treated nets, Japanese Encephalitis, Pig owner, Myanmar*Correspondence to: Orapin Laosee, ASEAN Institute for Health Development, Mahidol University, 999 Salaya,Phutthamonthon, Nakorn Pathom 73170, Thailand
Phone: (662) 441 9040-3 ext.43 Fax: (662) 441 9044 Email address: orapin.lao@mahidol.edu
indicated that the number of reported cases
fluctuated [7].

INTRODUCTION
Japanese Encephalitis (JE) is the most importantcause of viral encephalitis in Asia and Western
Pacific [1], [2]. JE virus is transmitted to humans
through the bite of an infected mosquito, primarily
Culex species. Humans are incidental or dead-end
hosts, because they usually do not develop a level orduration of viremia sufficient to infect mosquitoes.
Culex tritaeniorhynchus, the major mosquito vector,
breeds by lying eggs in rice fields, and the pig is
considered the most common amplifying host of JE
virus[3]. An estimated 67,900 JE cases typicallyoccur annually, of which only 10% are reported to
the World Health Organization [4]. Transmission
mainly occurs in rural agricultural areas, often
associated with rice cultivation and flood irrigation[2], [3], [5].

There is no specific treatment for JE, therefore,
prevention and control are critically important [1],[6]. The World Health Organization recommends
having strong JE prevention and control activities
which include ITNs, personal protective equipment,
and integrated vector management. Although JE
vaccines are available and cost-effective to preventthe disease [8], Myanmar has limited resources andcannot make JE vaccination available through the
public sector [9]. There is also no establishedsurveillance system in place[8]. Therefore,
Insecticide Treated Bed-nets (ITNs) is one of themost effective methods to prevent mosquito-borne
zoonotic disease including JE [10]-[13] in thiscountry. Previous research studies identified several
factors related to use of ITNs, these includes sociodemographic factors, availability of bed nets,
knowledge, and attitudes towards mosquito-borne
diseases [14]-[17]. Lack of information on use andinfluencing factor on utilizing ITNs to prevent JE in
Myanmar. This study aims to examine the use of
ITNs and to identify factors associated using ITNs
among pig owners the endemic area of Myanmar.

Myanmar has had one of the highest increases in
irrigated rice areas over the past 15 years [1]. Dataon JE incidence in Myanmar is limited, and it can beassumed that few cases are reported. According toavailable data, between 2007 to 2012 there were 74
JE cases in Myanmar, with the highest mortality andmorbidity reported in 2012 [6]. There were 113
reported cases in 2015. A report on vaccine
preventable disease surveillance from 2006-2011713

GEOMATE - Mie, Japan, Nov. 21-24, 2017

METHODOLOGY

Ethical considerations

Study design and subjects

The study was reviewed and approved by thecommittee for research ethics of the university(COA No.2016/123.2903). The research study wascollaborated with the Ministry of Health, Myanmar
and Department of Health. Personal data of
respondents was coded and kept as confidential
information.

This cross-sectional descriptive study was
conducted in Moemauk Township, Kachin State,
Myanmar, which borders the People’s Republic ofChina. In 2015, the total population was 62,914
within 1,068.95 square meters. It has low land areasin the west and south with a warm-temperate
climate. The majority of residents are poor who use
agriculture as their main source of family income.
There were Japanese Encephalitis outbreaks in thisarea in 2013, 2015 and 2016. A sample of 420
households (required for 5% precision) around 54%
of community residents reported sleeping under an
ITN the previous night, with 95% confidence limits
and assuming 95% response rate. Simple random
sampling was employed to identify pig owners inselected villages of three JE endemic areas. Pig
owners responsible for feeding pigs in samplingareas were interviewed from March to May 2016.
Interviewers introduced the topic, objectives, andtype of questions. Oral informed consent was
obtainedprior
tointerview.
Householdenvironmental observation was also conductedduring each interview.

RESULTS
Four hundred and twenty pig owners participatedin this study. Over three quarters of respondents(76.9%) were female. The median age was 38 years(QD 11). Most participants are Shan, Buddhist. Over
half completed primary school and lower, and earn a
low level of income. Most respondents (73.3%)
were raising pigs for sale, and over half owned atleast five pigs. Closed type (74.8 %) was the mostcommon type of pig farming, while half of the pig
farms (51.2 %) were located only 6 meters from pig
owner’s house. For the closed type, pigs were kept
in a sty close to the house at night (picture 1). About
one-quarter of respondents also owned cows or
buffalos. According to environmental observations,rice fields and wild birds were commonly found in
the study area (Table 1).

Research instrument
Table 1 Distribution of respondents by demographic
characteristics, and environmental factors (n=420)
Respondents’ characteristics andn (%)
environmental factors
Sex; Female
328 (78.1)
Age in year Median 40, QD.11, Min. 18, Max. 74
Ethnicity; Shan
315 (75.0)
Religion; Buddhism
304 (95.0)
Education; Primary school and below
214 (50.9)
Occupation; Farmer
318 (75.7)
Family income (Kyats per month)*
Median 100,000, QD. 45,000, Min 50,000, Max 500,000
Purpose of pig raisingSell
308 (73.3)
Consumption
98 (23.3)
Debt
14 (3.3)
Number of pig: Median 4, QD. 2.5, Min. 1, Max. 60
Type of pig farm
Closed type
314 (74.8)
Free range
106 (25.2)
Other animal raise
Own and feed duck; Yes
11 (2.6)
Own and feed cow; Yes
114 (27.1)
Own and feed buffalo; Yes
101 (24.0)
Keep large animals under the house; Yes
6 (1.4)
Environment surrounding household (within 5 km.)
Rice field; Yes
256 (61.0)
Wild birds; Yes
144 (43.3)
Vegetable field; Yes
80 (19.0)*1 USD = 1,200 Kyats (As of 18 July 2016)

A questionnaire was developed based on theliterature and local context. It was first drafted in
English, then translated into the local language,
reviewed by a panel of experts and pre-tested in avillage with comparable proximity and demographic
distribution to the target sample. Observation wasused to assess environmental factors related to JE
outbreak during data collection time. The
questionnaire consisted of four topics; 1)
respondents’ characteristics, 2) knowledge regarding
signs and symptoms of JE and attitude toward theuse of ITNs, 3) animals raised and environment
surrounding house, 4) use of ITNs by family
members-whether they slept under a net the previous
night. Approximately 20 to 30 minutes was needed
to survey each respondent.
Data analysis
Descriptive statistics were employed todetermine central distribution and frequency of thestudy variables. Bivariate and multivariate logistic
regression were conducted to identify thesignificance of use of ITNs. Use of ITNs refers towhether all family members slept under an ITN on
the night prior to being surveyed. A P value <0.05
was considered statistically significant.

714

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Picture 1: Closed type of
pig farming

Picture 2: Free range

The majority (88%) of the respondents owned
ITNs and approximately one-fifth reported sleeping
under the ITNs on the night prior to being surveyed.
Nearly one-third (30.5%) had a poor level ofknowledge regarding signs & symptoms of JE(Table 2).
Table 2 Use of ITNs, level of knowledge andattitude of respondents
Use of ITNs, knowledge, andn (%)
attitudeOwn ITNs
370 (88.1)
Use ITNs prior nightYes
88 (21.0)No
332 (79.0)
Knowledge related to JE signs and symptoms
Poor
128 (30.5)
Good
292 (69.5)
Attitude toward use of ITNs
Negative
122 (29.0)
Fair
130 (31.0)
Positive
168 (40.0)
Bivariate analysis indicated that level of family
income, family size, number of ITNs owned andpresence of rice fields near the house wereassociated with the use of ITNs (Table 3).
Table 3 Association between independent variables
and use of ITNs
Independent
variables

Sex
Male
FemaleAge in years
Less than 31
31-45
More than 45
Ethnicity
Shan
Kachin and others
Religion
Buddhism
Christianity
Education level

Use of ITNs
No
(%)

23.9
20.1

76.1
79.9

1.25(0.72-2.16)
1

15.7
23.9
22.3

84.3
76.1
77.7

1
1.69(0.90-3.15)
1.54(0.83-2.85)

20.0
23.8

80.0
76.2

1
1.25(0.74-2.12)

20.1
23.5

79.9
76.5

1
1.22(0.72-2.08)

24.3

75.7

1.50(0.94-2.44)

17.5

82.5

1

20.3
23.7

79.7
76.3

1
1.21(0.67-2.19)

14.5

85.5

1

24.1

75.9

1.87(1.08-3.24)

12.6
27.3

87.4
72.7

1
2.59(1.54-4.38)

16.4
22.9

83.6
77.1

1
1.51(0.88-2.60)

20.3
21.5

79.7
78.5

1
1.07(0.67-1.72)

12.7
36.8

87.3
63.2

1
4.01(2.45-6.54)

20.6
21.9

79.4
78.1

1
1.08(0.64-1.82)

21.3
19.8

78.7
80.2

1
0.91(0.52-1.59)

15.2
24.6

84.8
75.4

1
1.81(1.08-3.02)

No
Yes
Vegetable field near
house
No
Yes

21.7
19.4

78.3
80.6

1
0.86(0.52-1.43)

20.3
23.8

79.7
76.3

1
1.22(0.68-2.18)

Multiple logistic regression revealed that pig
owners with low family income are two times more
likely to use ITNs compared to those in highincome(adjusted odds ratio 2.04, 95%CI: 1.13-3.70).
Pig owners with less than five members in theirfamily are nearly 4 times more likely to use ITNs
(AOR 3.71, 95%CI: 2.07-6.62). In addition,
respondents who own more than two nets are 5
times more likely to use ITNs compared torespondents who own only two nets or less(AOR
5.47, 95%CI: 3.20-9.33) (Table 4).

OR(95%CI)

Yes(%)

Primary schooland below
High school andhigher
Occupation
FarmerOthersFamily income
High (>100,000
Kyats)
Low (≤100,000
Kyats)
Number of family
memberMore than five
Five or less
Knowledge level
Poor (< median)
Good (≥ median)Attitude
Negative
Positive
Number of ITNs
own
Two or lessMore than two
Own and feed cow
NoYes
Own and feedbuffalosNo
Yes
Rice field near house
No
Yes
Wild bird near house715

GEOMATE - Mie, Japan, Nov. 21-24, 2017

However, the use of ITNs is related to many factors.
A study of the use and maintenance of bed nets andrelated influence factors in Kachin Special Region in2015 revealed that residents consist of poor families,
living under thatched roofing, with limited
knowledge of how to prevent disease transmission[14]. The Ministry of Health, Myanmar began
distributing ITNs to prevent vector-borne diseasesuch as Malaria, Dengue, Hemorrhagic Fever, JE,
etc. to families in rural endemic areas [14]. Free
distribution of ITNs resulted in a higher rate ofownership among the poor. As found in this study,
though a high number own ITNs, only 21% usethem regularly. The low use of ITNs might be due tothe issue of inadequacy. Our study found thatfamilies consisting of less than five members are
more likely to use ITNs (AOR 3.71, 95%CI 2.076.62). However, we found that low income families
are more likely to use ITNs compared to highincome families, similar to a previous study ineastern Myanmar [17]. This could be explained by
the fact that poorer residents were more aware of
their risk of being infected by JE due to their work.
Most farmers in this area had to sleep in their farmduring the harvesting period. They recognized thatthey could be infected by JE at any time due to theunsafe environment.

Table 4 Multiple logistic regression analysis forpredictive factors of use of ITNs among pig owners
p-value
Independent Variables
Adjusted OR
95% CI
Family Income
High
1
Low
2.04
1.13-3.70
0.018
Number of family member
More than five
1
Five or less
3.71
2.07-6.62<0.001
Knowledge level
Poor
1
Good
1.75
0.97-3.17
0.062
Number of ITNs owned
Two or less1
More than two
5.47
3.20-9.33<0.001
Hosmer and Lameshow Test=8.527, p-value=0.384.

DISCUSSION
In rural areas of Myanmar, the majority ofresidents work in agriculture as their main source ofincome. Approximately over half of the households
in Moemauk township, Kachin state own at least one
pig, while the median ownership is four pigs. This
study identified the majority of subjects as farmers,
with nearly three-quarters (74%) raising pigs asproperty which they could sell if financiallyconstrained. In addition, pork is considered anessential luxury food for social and culturalactivities such as wedding ceremonies, religious andharvest festivals. The literature indicated that pigs
play a central role in the transmission of both
Japanese Encephalitis virus and cysticercosis [18].
Expansion of the JE virus-endemic area depends on
irrigated rice farming and pig rearing[3]. A higher
proportion of rice-planting could therefore predicthigher risk of JE [19].

Study limitations include the disparity indemographics. More females (78.1%) wereinterviewed than males, due to the fact that maleheads are working in the farm, while females had therole of caring for children, feeding animals anddoing household work. Another limitation is that
residents in this area consist of different ethnic
groups, thus the language barrier could introduce
information bias.

This study found that the majority of pigs
(74.8%) are reared in open or unroofed pigpens,close to human dwellings, which hence govern the
spread of JE virus. Lindahl, J. (2012) indicated thatclosed pigpens were associated with the number ofvectors to the human dwelling [20]. Furthermore,
one-quarter of pigs were raised as free range, andallowed to freely scavenge food from garbage
dumps, markets, rice fields, and paddy fields, which
could lead to a higher likelihood of diseasetransmission. Most JE cases were found in rural
areas, especially in rice-planting and pig-rearing
areas. In Kachin state, a less-developed area of
Myanmar, a greater proportion of therural
population was often short of funds for JE
prevention and control, a finding similar to a study
in China [21].

CONCLUSION
In the union of Myanmar, especially in high JE
endemic areas, an effective surveillance systemshould be established, along with adequate provisionof ITNs for all family members. Introduction of
immunization coverage for the prevention andcontrol of JE should be set as high priority agenda,
beginning in rural setting. Moreover, mosquitocontrol efforts emphasizing improved knowledge
related to prevention and control should continue,
especially before the onset of the rainy season.
Community awareness of these issues should beraised by effective use of available resources which
all community members can access, in different
local languages. In addition, management ofhousehold environments could be further targeted toreduce the breeding sites of vectors close tohouseholds.

Systematic review and meta-analysis identified
clear evidence that ITNs have the potential to reduce
pathogen transmission and morbidity from vector
borne disease where vectors enter a house [12].

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716

GEOMATE - Mie, Japan, Nov. 21-24, 2017

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[6] World Health Organization. (2014).
Japanese encephalitis Fact sheet No 386
March
2014.
Available:
http://www.who.int/mediacentre/factshee
ts/fs386/en/[7] World Health Organization, "Expanded
program on Immunization Multi Year
Plan 2012-2016," Central Expanded
Program on Immunization, Department
of Health, Ministry of Health 2012,
Available:
http://www.searo.who.int/myanmar/docu
ments/EPImultiyearplan2012_16.pdf?ua=
1.
[8] World Health Organization, "Prevention
and Control of Japanese encephalitis(JE), report of the bi-regional meeting,
Bangkok, Thailand," 2015, Available:
www.searo.who.int.
[9] Armed Force Research Institute ofMedical Sciences, "Japanese encephalitis
morbidity, mortality and disability.
Reduction and control by 2015," in"PATH, Seattle, WA," Bill & Melinda
Gates
Foundation2009,
Available:
http://www.path.org/vaccineresources/fil
es/JE_Reduction_and_Control_by_2015.
pdf.
[10] Hiscox A., et al., "Risk factors formosquito house entry in the Lao PDR,"
PloS one, vol. 8, no. 5, p. e62769, 2013.
[11] Alpern JD., Dunlop SJ., Dolan BJ.,
Stauffer WM., and Boulware DR.,
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Medicine and Hygiene, vol. 87, no.
6, pp. 1076-1082, 2012.
[21] Cao M., Feng Z., Zhang J., Ma J.,
and Li X., "Contextual risk factors
for regional distribution of Japanese
encephalitis
inthe
People’sRepublic of China," Tropical
Medicine & International Health,vol. 15, no. 8, pp. 918-923, 2010.

Travel Medicine, Review vol. 14,
no. 4, pp. 259-268, 2007.
[20] Lindahl J., Chirico J., Boqvist S.,
Thu HTV., and Magnusson U.,"OccurrenceofJapanese
encephalitis virus mosquito vectors
in relation to urban pig holdings,"
American Journal of Tropical718

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EFFECT OF ORGANIC BIOPOLYMER ON THE MICROBIALLY
INDUCED CARBONATE PRECIPITATION AND ITS MORPHOLOGY
Thiloththama Hiranya Kumari Nawarathna1, Kazunori Nakashima2, Satoru Kawasaki2
1
Graduate School of Engineering, Hokkaido University, Japan
2
Faculty of Engineering, Hokkaido University, Japan
ABSTRACTMicrobially induced carbonate precipitation (MICP) by using ureolytic bacteria is a novel and environmentallyfriendly way to treat the un-cemented sand. It was implemented successfully in number of geotechnicalapplications. Use of organic additives to improve the MICP process is a novel and interesting approach. In thisresearch, effect of the cationic biopolymer poly-l-lysine on the MICP process was investigated by using ureolytic
bacteria Pararhodobacter sp. Urea hydrolysis by the bacteria in the presence of CaCl2 was conducted with theaddition of the polymer under different conditions. Morphology of the precipitate of CaCO3 after oven dried wasanalyzed by using the scanning electron microscope. Bell-shaped curve was obtained for the variation between
the amount of the precipitate with the increase of the amount of the poly-l-lysine. Poly-L-lysine gives higher
amount of precipitate than conventional MICP process and morphology of the crystals changed drastically fromwell-developed rhombohedral crystals to ellipsoidal shaped aggregates.
Keywords: Bio-polymer, Calcite, Morphology, Ureolytic bacteria
and non- petroleum based product. They consist ofmonomeric units bonded covalently to form large
molecules. Number of researches had been done
previously to investigate the applicability of
biopolymers to improve the weak soil and they
concluded that bio polymer have a better ability to
improve the weak soils.
Combination of the above two biologicalprocesses such as use of biopolymer to the MICP
process seems to be novel and innovative idea toimprove the efficiency of the MICP process. In thisresearch, effect of the cationic biopolymer on the
MICP process was investigated by using ureolytic
bacteria Pararhodobacter sp.
Poly-L-lysine was used as the cationicbiopolymer and it is a kind of basic polypeptide. In
neutral pH, its amino group side chains are
positively charged [6]. Generally, silica particles
have negative charge due to the presence of thesilanol group. If we use poly-L-lysine for the MICP
process, negatively charged bacteria cell and silica
particles could be bound with each other due topositively charged property of the poly-L-lysine. So
it can be help to increase the efficiency of the MICP
process [7]. Chemical structure of the poly-L-lysine
is shown in Fig.1. In this research work, we
examined the effect of poly-L-lysine on the MICP
process.

INTRODUCTION
Today in the world, due to urbanization andrapid growth of population, lands available for the
infrastructures and other developments have been
decreasing. So people are moving to use loose
problematic soils to construct earth structures byusing proper ground improvement techniques.
Chemical grouting is a most common and effective
way to treat weak soils. Cement is the main material
use for the chemical grouting, but cement production
is more energy consuming and environmental
unfriendly method. CO2 emission from the cement
production is 7% from the global CO2 emissions [1].
So today world is seeking for an environmentallyfriendly biological approach to treat the loose soils.
Microbially Induced Carbonate Precipitation(MICP) is a one of such kind of novel andenvironmental friendly ground improvement
method. In MICP process, CaCO3 is precipitated byhydrolysis of the Urea by using ureolytic bacteria
and it includes biochemical reactions governed byurease enzyme produced by these ureolytic bacteria
as given in the Eqs.(1-3) [2][3][4][5].

→

O
H
N

→

CH C
CH2

Use of organic additives such as biopolymers
and protein to improve the weak soil is an alternative
biological approach to the MICP process.
Biopolymers are organic polymers synthesized byplant or microorganism and it is a natural, non-toxic

n

CH2
CH2
CH2
NH3+

719

Fig. 1 Structure of the poly-L-lysine.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

were analyzed using Scanning Electron Microscope(SEM).

METHOD
Preparation of Microbial Cell Culture

Table 1 Experimental condition for system with andwithout poly-L-lysine

Ureolytic bacteria Pararhodobacter sp. wasisolated from the beach sand in Sumuide, Nago,
Okinawa, Japan [8] and cultivated using
Zobell2216E medium ( Polypeptone 5.0 g/L, Yeast
extract 1.0 g/L and FePO4 0.1 g/L, prepared by using
artificial sea water, pH 7.6-7.8). Bacteria cells wereprecultured using 5ml of Zobell2216E medium andkept in the shaking incubator at 30οC and speed of
160 rpm for 24 hours. One ml of the pre-culture was
inoculated into 100ml of fresh Zobell2216E medium
and kept in the shaking incubator under the same
condition as pre-culture for 48 hours. Finally,
bacterial culture was centrifuged to collect the cellpellets, which were dispersed again using distilledwater to make bacterial suspension. Cell
concentration of the bacterial suspension wasmeasured by UV–vis spectrophotometer and then
OD600 value was adjusted to one.

Sample
No

CaCl2
(M)

Urea
(M)

Bacteria
OD600

A

0.01

B

0.1

C

0.2

D

0.3

E

Poly-LLysine(mg/L)

0

0.3

0.3

0.01

F

0.1

G

0.2

H

0.3

10

Table 2 Experimental conditions to evaluate theeffect of poly-L-lysine concentration

Precipitation Test
SampleNo

Effect of the poly-l-lysine on the MICP process
Same concentration (3 mol/l) of CaCl2 and urea
solutions and the stock solution of the poly -L-lysine(0.1g/L) were used for the precipitation test. Twosets of samples were prepared without adding
biopolymer and with biopolymer by varying theconcentration of bacteria (OD600) as shown in Table
1. Total volume of the samples were adjusted to
10ml by using distilled water and after preparation,
samples were kept in the shaking incubator under
30οC and 160 rpm speed for 24 hours. Then thereaction mixture was centrifuged to collect the
precipitate, and supernatant of tubes were removed
separately by using filter paper (11μm).
Both of the filter papers and the tubes with theprecipitate were oven dried at 100οC 24 hours anddry weights were measured. Weight of the
precipitate was calculated by subtracting the empty
weight of the tube and the empty weight of the filter
paper from the dry weight of the tube and the dryweight of the filter paper. FTIR analysis was
conducted for the sample with and without poly-llysine and finally samples were analyzed by using
Scanning Electron Microscope (SEM) to identify themorphology of the precipitated calcium carbonate
crystals.

CaCl2
(M)

Urea
(M)

Bacteria
OD600

Poly-LLysine (mg/L)

1

0

2

1

3

0.3

0.3

0.1

10

4

30

5

50

RESULTS AND DISCUSSION
Effect of the Poly-L-Lysine on the MICP Process

Precipitate (g)Variation of the amount of precipitated CaCO3
with and without adding poly-L-lysine under
different bacteria concentrations is given in theFig.2.
0.3

Effect of the poly-L-lysine concentration
Samples were prepared by varying theconcentration of poly-L-lysine as shown in the Table
2. Sample preparation is same as earlier and samples

without
poly‐L‐lysinewith
poly‐L‐lysine

0.2
0.1
0

0

0.2
0.4
Bacteria concentration (OD600)

Fig. 2
Variation of the amount of carbonate
precipitates with the bacteria concentration (OD600)

720

GEOMATE - Mie, Japan, Nov. 21-24, 2017

According to the Fig. 2, it can be seen that in both ofthe cases, amount of the precipitated CaCO3 increase
with the bacteria concentration. However,considerable amount of increment can be seen only
up to the OD600=0.2 after that, rate of the
precipitation of CaCO3 was getting decrease and it isalmost become constant for further increase of theconcentration of bacteria. So, higher concentrationof bacteria inhibits the formation of calcium
carbonate. It may be due to the lack of bacteria
growth due to higher concentration of the bacteria.
System with the poly-L-lysine gave higher
amount of precipitate compared with that without
biopolymer. However, for higher bacteria
concentration, amount of precipitated CaCO3 withand without biopolymer were approximately similar.
At higher bacteria concentration significant
influence from the biopolymer couldn’t beidentified. However, it can be seen that poly-Llysine has positive effect on the MICP process.
Figure 3 shows the Scanning Electron
Microscopy (SEM) images for the various bacteria
concentrations.

According to the SEM images, lower
concentration of bacteria gave well-developedrhombohedral calcite crystals. At higher bacteria
concentration, agglomeration of rhombohedral
crystals can be seen and size of the crystals reducedwith the increase of the bacteria concentration.
Higher concentration of bacteria inhibits the growthof CaCO3 crystals. In the presence of the poly-Llysine, morphology of the crystals change toellipsoidal shape as shown in Fig. 4. At higher
bacteria concentration both of the rhombohedral andellipsoidal crystals can be seen. This morphology
changes may be due to the adsorption of the poly-Llysine on the crystal surface and formation of new
crystal faces.
Effect of the Amount of Poly-L-Lysine
Variation of the amount of the CaCO3 precipitate
with the increase of the amount of the poly-L- lysine
is given in the Fig. 5.

(a)

(b)

(c)

(d)

Fig. 3 SEM images of the CaCO3 precipitate for different bacteria concentration without poly-L-lysine(a) OD600 = 0.01 (b) OD600 = 0.1(c) OD600 = 0.2 (d) OD600 = 0.3

721

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(a)

(b)

(c)

(d)

Fig. 4 SEM images of the CaCO3 precipitate for different bacteria concentration in the presence ofpoly-L-lysine (a) OD600 = 0.01 (b) OD600 = 0.1(c) OD600 = 0.2 (d) OD600 = 0.3

The amount of precipitate increase with the polyl-lysine concentration and further increase of thepoly-l-lysine concentration leads to reduce theamount of precipitate. This may be due to theexcessive amount of poly-L-lysine would reduce theactivity of the bacteria. Highest amount ofprecipitate was obtained at the poly-L-lysine
concentration of 10 mg/L. According to the SEM
images given in Fig. 6, crystal size was larger
compared with the other concentrations when theconcentration of the poly-L-lysine was 10mg/L. At
lower concentration of poly-L-lysine, combinationsof polyhedral crystals were predominant. With theincrease of the concentration, morphology of thecrystals changed to ellipsoidal shape aggregates. At
higher concentration of poly-L-lysine agglomerationof ellipsoidal shaped crystals were obtained.

0.26

precipitate (g)

0.25
0.24
0.23
0.22
0.21
0.2
0.19
0.18

0

1mg/l 10mg/l 30mg/l 50mg/l

Poly‐L‐Lysine concentration

Fig. 5 Variation of the amount of carbonate
precipitate with the poly-L-lysine concentration

722

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(a)

(b)

(c)

(d)

Fig. 6 SEM images of the CaCO3 precipitate for different poly-L-lysine concentration (a) 1 mg/L (b)10 mg/L (c) 30 mg/L (d) 50 mg/L

Similar relationship between the amount ofprecipitate and the poly-L-lysine concentration was
found from the previous researches, which reported
the precipitation of calcium carbonate usingchemical reaction of CaCl2 and Na2CO3 solutions in
the presence of calcite seed and poly-L-lysine. They
have explained that the increase of the calcite
growth at low concentration of poly-L-lysine andgrowth reduction at higher concentration of poly-Llysine is a typical behavior of the additives that wereweakly, non- selectively, bonded to the surface. This
explanation is identical to our research work.
Furthermore, they have concluded that theinteraction between the poly-L-lysine and the calcite
is pure electrostatic and it is between the positively
charged polypeptide and the negatively charged
calcite surface [6] [9].

FTIR Analysis
Results of the FTIR analysis with and without
poly-L-lysine are shown in Fig 7. Both graphs look
like similar. However, small peak can be seen at
1200 cm-1 in the graph with poly-L-lysine. This peak
represents the C-N bond and we can conclude thatsome amount of poly-L-lysine present in the CaCO3
precipitate.
CONCLUSION
Effect of the cationic organic biopolymers on the
MICP process was investigated by using poly-llysine. The results shows that, Poly-L-lysine has a positive effect on the
MICP process. However with the presenceof higher concentration of bacteria
significant influence from the poly-L-lysine
on the MICP process couldn’t be seen.
723

GEOMATE - Mie, Japan, Nov. 21-24, 2017

With the increase of the bacteria
concentration, the rate of the formation of
calcium carbonate decrease. So, higher
bacteria concentration will reduce thecrystal growth.
0
5000
4000
-0.2

Transmission

(a)

3000

2000

1000

[2]

0

[3]

-0.4
-0.6
-0.8
-1
-1.2

Wave number (cm-1)

0
5000
4000
‐0.2

Transmission

(b)

[4]

3000

2000

1000

0

[5]

‐0.4
‐0.6
‐0.8

[6]

‐1
‐1.2

Wave number (cm-1)
Fig. 7 FTIR spectra for samples (a) with poly-L-lysine(b) without poly-L-lysine







Relationship between the amount ofprecipitate
andthepoly-L-lysine
concentration is bell shaped and higher andlower concentrations of the poly-L-lysine
concentration inhibit the calcium carbonate
precipitation but intermediate concentration
give higher amount of precipitate.
With the increase of the bacteria
concentration morphology of the crystalschange from well-developed rhombohedral
crystals to agglomeration of therhombohedral crystals and size of thecrystals reduces.
Presence of the poly-L-lysine produces
ellipsoidal shape crystals. Morphology of
the crystals changes from the polyhedral
crystals to agglomeration of ellipsoidal
crystals with the increase of the poly-Llysine concentration.

[7]

[8]

[9]

REFERENCES[1] Chang I, Im J, Cho G C, “Introduction of
microbial biopolymers in soil treatment for
724

future environmentally-friendly and sustainablegeotechnicalengineering”,
Journalofsustainability, Vol. 8, Mar.2016, pp.1-23.
Akiyama M, Kawasaki S, “Novel grout
material comprised of calcium phosphate
compounds: In vitro evaluation of crystal
precipitation and strength reinforcement” ,Journal of engineering geology, Vol. 125,
Jan.2012, pp. 119-128.
Khan N H, Amarakoon G G N N, Shimazaki S& Kawasaki S, “Coral sand solidification test
based on microbially induced carbonate
precipitation using ureolytic bacteria”, Journalof materials transactions, Vol. 56, Aug. 2015,
pp. 1725-1732.
Pacheco T F, Labrincha J A, Diamanti M V,
Yu C P & Lee H K, “ Production of bacteria
for structural concrete”, Biotechnology and bio
mimetic for civil engineers, springer,2015,
pp.309-323.
Fujita M, Nakashima K, Achal V, Kawasaki S,“Whole-cell evaluation of urease activity ofPararhodobacter sp. isolated from peripheral
beachrock” Biochemical engineering journal,
Vol. 124, April. 2017, pp. 1-5.
Dzakula B N, Falini G, Brecevic L, Skoko Z &Kralj D, “Effects of initial supersaturation on
spontaneous precipitation of calcium carbonate
in the presence of charged poly-L-amino acids”,
Journal of colloidal and interface science, Vol.
343, Dec. 2009, pp.553-563.
Colville K, Tompkins N, Rutenberg A D,
Jericho M H, “Effects of poly(l-lysine)
substrates on attached escherichia coli
bacteria”, Langmuir, Vol.26,sep.2009,pp.
2639–2644.
Mitsuyama S, Nakashima K, Kawasaki S,“Evaluation of porosity in biogrouted sandusing microfocus x-ray ct”, International
journal of GEOMATE, Vol. 12, Mar. 2017, pp.
71-76.
Dzakula B N, Brecevic L, Falini G & Kralj D,“Calcite crystal growth kinetics in the presenceof charged synthetic polypeptide”, Journal of
crystal growth and design, Vol.9, Feb.2009,
pp.2425-2434.

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PREDICTION OF SALTWATER INTRUSION PROCESSES USING AWAVELET-FCM-ANFIS HYBRID MODEL
1, 2

Dilip Kumar Roy1, and Bithin Datta2
Discipline of Civil Engineering, College of Science and engineering, James cook University, QLD 4811,
Australia
ABSTRACT

Sufficiently accurate and reliable prediction of saltwater intrusion processes can help ensure sustainablegroundwater abstraction from coastal aquifers. In this study, a surrogate model based on combination of multisignal discrete wavelet transforms (MDWT) and adaptive neuro-fuzzy inference system (ANFIS) is proposed toapproximate and predict density dependent coupled flow and salt transport processes in a multi-layered coastal
aquifer system. MDWT is used as a pre-processing step to improve the ability of the ANFIS model by capturing
relevant important information at different resolution levels. The variables used to train and validate the proposed
prediction model are the transient groundwater extractions as inputs, and the resulting saltwater concentrations at
the end of the simulation period as outputs. To reduce dimensionality of the input space, an additional step of datacompression is utilized to prepare data required for ANFIS training. Therefore, input space is divided into a numberof clusters by using fuzzy c-mean (FCM) clustering algorithm. The performance of the proposed surrogate model
is evaluated for an illustrative study area. It is demonstrated that MDWT in conjunction with FCM can improveaccuracy of ANFIS based surrogate model for saltwater intrusion processes prediction. The results of the present
study indicates the potential applicability of the proposed MDWT-FCM-ANFIS based surrogate model inapproximating and predicting coupled flow and salt transport processes in an illustrative multi-layered coastal
aquifer system.
Keywords: Saltwater Intrusion, Multi-signal Discrete Wavelet Transforms, Adaptive Neuro-fuzzy Inference System,
Fuzzy C-mean Clusteringand fuzzy c-mean (FCM) clustering algorithm areused as preprocessing steps for training of the
proposed adaptive neuro-fuzzy inference system(ANFIS) based saltwater intrusion prediction model.

INTRODUCTION
Unplanned groundwater extraction is considered
as one of the major drivers of saltwater intrusion
processes in coastal aquifers [1, 2]. Accurate andreliable prediction of saltwater intrusion processes
can be adopted to develop long-term planning andmanagement policy for coastal groundwater
resources. Saltwater intrusion phenomena can bepredicted by simulating density dependent and nonlinear coupled flow and salt transport processes.
Saltwater intrusion management models aredeveloped by using repetitive simulation of thesecomplex processes within an iterative simulationoptimization (S/O) approach. Use of the original
simulation model is computationally prohibitive(because of multiple calls of the simulation model by
the optimization algorithm) in such a linked S/Omethodology. Sufficiently accurate approximationsof saltwater intrusion processes can be used fordeveloping a regional scale management model tocontrol saltwater intrusion [3]. Present study proposesa fuzzy logic based prediction model to approximate
density dependent coupled flow and solute transport
processes in a multi-layered coastal aquifer system.
Multi-signal discrete wavelet transforms (MDWT)

Generalization capability of a trained model toproduce similar results from a new pattern of unseen
test dataset is an important evaluation criterion. Basedon this criterion, quite a few prediction models havebeen used successfully to predict saltwater intrusion
processes in coastal aquifers. Artificial Neural
Network (ANN) [4-7], Genetic Programming (GP)[6-8], Evolutionary Polynomial Regression (EPS)[9], Fuzzy Inference System (FIS) [10], Multivariate
Adaptive Regression Spline (MARS) [11] and cubic
Radial Basis Function (RBF) [12] are the commonlyused approximation models for saltwater intrusion
prediction. Despite simplicity and reasonableprediction accuracy, most of the surrogate models
proposed recently have certain limitations. Therefore,
there is still a substantial scope of developing a
reliable prediction model with better prediction
accuracy. Recently, ANFIS based prediction models
have achieved considerable attention as an effective
tool to model non-linear systems by capturing nonlinear relationships between predictors and response
variables [13, 14]. ANFIS combines the concepts of725

GEOMATE - Mie, Japan, Nov. 21-24, 2017

approximate saltwater intrusion processes in a multilayered coastal aquifer system. Transient input-output
patterns generated by using a numerical simulation
model are used to train the proposed ANFIS model.
MSWT and FCM are used as preprocessing steps of
ANFIS model formulation. The performance of the
proposed MSWT-FCM-ANFIS based approach isevaluated for an illustrative multi-layered coastal
aquifer system. The stratified aquifer system consistsof four distinct layers of aquifer materials withdifferent hydraulic conductivity values. Aquifer
materials within each layer are consideredhomogeneous.

both neural networks and fuzzy set theory [15].
Present study seeks to propose a MWDT transformed
and FCM based ANFIS model as a computationallyefficient substitute of complex numerical simulation
model to overcome some of the limitations of thecommonly used prediction models.
Wavelet transforms (WT) have become a popular
preprocessing step for time series analysis in various
application domains of water resource engineeringand hydrology [16-19]. Wavelet transformed dataenhances the prediction capability of a model by
extracting important features on various resolution
scales of the original data [17]. Discrete wavelet
transformation provides approximation (lowfrequency) and detail (high-frequency) components
after decomposition of the original data to a desired
level. Different wavelet components characterize
distinct properties of the original data. For instance,high-frequency components capture discontinuities,
ruptures, and singularities of the original data. On theother hand, low-frequency components characterize
the overall gross structure of the data that helps
identify long-term trends. Several previous studies
demonstrated the potential benefits of discrete
wavelet transforms in improving the capability ofprediction models for time series prediction in thedomain of river flow forecasting [17], streamflow
prediction [19], and lake water level prediction [18].
Wavelet transformed ANFIS has also been usedpreviously in the time series analysis of lake waterlevel prediction [18], precipitation prediction [20],groundwaterlevel
prediction
[21],
and
evapotranspiration estimation [22], etc. However,wavelet transformation has not been utilized
previously as a preprocessing step to train ANFIS
based surrogate models for predicting saltwater
intrusion processes resulting from spatial andtemporal pumping stresses applied to a multi-layered
coastal aquifer system.

METHODOLOGY
The proposed methodology consists of utilizing a
numerical simulation model for simulating aquifer
processes; and using an ANFIS based prediction
model trained and validated using MSWT
transformed and FCM clustered modified inputs oftransient groundwater extraction values. The
following paragraphs provide a brief description of
the methodologies.
Numerical Simulation Model
A finite element based numerical simulation model,
FEMWATER [23] was used to simulate three
dimensional coupled flow and salt transport processes
for generating input-output datasets. Governing flow
and transport equations are expressed as [23]


 ρ
ρ
ρ h
   K   h  z    q
F
ρ0
ρ0 t


 ρ

(1)

where ρ represents water density at chemical
concentration C, ρo is referenced water density at zero
chemical concentration, F indicates storage
coefficient,  stands for del operator, K symbolizes
hydraulic conductivity tensor, h is pressure head, z
indicates potential head, ρ* represents density of
injection fluid or that of the withdrawn water, and q
indicates either a source or a sink.

However, a major challenge in the application of
ANFIS based prediction models to approximate
saltwater intrusion processes is to handle highdimensionality of data associated with spatial andtemporal groundwater extraction values as input
variables. FCM provides a solution to this issue by
dividing the high dimensional input space into
identical clusters that makes ANFIS generation
feasible by limiting the number of rules in the initial
FIS for ANFIS generation. This study utilizes FCM
clustering approach to generate initial FIS structure
for building the final ANFIS model.

CS V  C    D  C 
 b
t
t
 h

      C  b S   K wC  b K s S 
 t




m

(2)

 h o   C CqC   F V    

t



 o  t 
in which θ represents moisture content, C
indicates chemical concentration,  b is the bulk
density of the medium, V represents discharge, D
indicates Dispersion coefficient tensor, α′ and β′ arerespectively the modified compressibility of the water

Therefore, the contribution of the present study is
to develop a reliable and accurate prediction model to726

GEOMATE - Mie, Japan, Nov. 21-24, 2017

and the medium, S stands for saturation, Kw is the firstorder biodegradation rate constant through dissolved
phase, Ks is the first order biodegradation rate throughadsorbed phase, Kd is the distribution coefficient, andt represented time.

realization of the validation sample to checkvalidation performance with new unseen data. For
consistency, this validation part was done for all thedeveloped models using the original input values.

Dataset Preparation
Input-output datasets were obtained from thesolution results of the numerical simulation modelthrough repeated simulation of the aquifer processes
using a set of transient groundwater extraction values.
The input transient groundwater extraction values
were generated from a uniform distribution within therange between 0 and 1300 m3/day through Latin
Hypercube Sampling (LHS) [24], and is presented in
Fig.1. Saltwater concentration values at specified
monitoring locations (ML) at the end of thesimulation period obtained as solution from thesimulation model constitute the output part of the
input-output pattern. The study area selected for thisresearch is similar to the one developed in Roy andDatta [10] as shown in Fig.2. The aquifer system has
an aerial extent of 4.35 km2. The depth of aquifer is
80 m divided into four distinct layers of materials
having different hydraulic conductivity values.
Materials within each layer were consideredhomogeneous. Combined operation of a set of
production and barrier wells was consideredsymbolized by PWs and BWs, respectively in Fig. 2.
Water was extracted from the 2nd and 3rd layers of theaquifer using the wells, which were assigned apractical extraction limit of 0–1300 m3/day. Saltwater
concentrations due to the transient pumping stressapplied to the aquifer at the end of the simulation
period of five years were monitored at five MLs.

Fig. 2 Three dimensional view of the study area (after
Roy and Datta [10])Multi-signal(MDWT)

Discrete

WaveletTransforms

WT is an effective tool in the field of analyzing
non-stationary time series data. WT allows
decomposition of the original data series into several
components with different resolution levels. Eachcomponent of the wavelet transformed data has
certain characteristics. Present study utilizes Discrete
WT (DWT), which is suitable for analyzing signals
by decomposing them into progressively finer octave
bands. This multi-resolution signal processing
enables to recognize unseen patterns of the raw data.
Multiple one dimensional signals of input transient
pumping variables of same length are stored in amatrix before being decomposed using a one
dimensional MDWT. In DWT, the original data series(S) is decomposed into low frequency approximation
coefficients (A) and high-frequency detailcoefficients (D) after passing through a low-pass anda high-pass filter, respectively. The low-pass filteredsignal of any decomposition level acts as input to thenext step of decomposition, and the iteration processcontinues until the specified decomposition level isreached. The A components contain the general trendof the original data series whereas the D components
characterize the original signals’ local variations.
MDWT was performed using Wavelet toolbox of
MATLAB [25].

Fig. 1 Three dimensional view of the transientgroundwater extraction values

Adaptive Neuro-fuzzy Inference System (ANFIS)

Transient groundwater extraction values and theresulting saltwater concentration at the end of the
management period constitute one set of input-output
pattern. A set of such patterns was used to train andvalidate the proposed prediction models. Properly
trained models were then presented with a new

Despite having simple architecture, Sugeno type
ANFIS structures have good learning capabilities[26] suitable for non-linear mapping of input-output
patterns of non-linear systems [13, 14]. Therefore, aSugeno type ANFIS has been adopted in the present
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

study to approximate density dependent coupled flow
and salt transport processes in a multi-layered coastal
aquifer system. Final ANFIS structure was achievedby tuning the parameters of an initial FIS structureusing hybrid algorithm. For a first order Sugeno FIS,
the generic form of the fuzzy if-then rule set for two
inputs, one output, and two rules can be expressed as

optimum number of clusters was chosen for which the
RMSE value was minimum, and the difference in
RMSE between the training and test dataset was
minimum as well. Based on this criterion, twoclusters were found optimal for generating the initial
FIS for final ANFIS development. Therefore, thisstudy considered 160 Gaussian input membershipfunctions (80 input variables × 2 clusters) and 2 (1output variable × 2 clusters) linear output
membership functions for all developed ANFIS
models at each ML.

Rule 1: If  is P1 and  is Q1 thenf1  p1  q1   r1 ,(3)

Rule 2: If  is P2 and  is Q2 , thenf 2  p2  q2   r2

Conjunction Model (MDWT-FCM-ANFIS)(4)

The hybrid model (MDWT-FCM-ANFIS)
developed in the present study utilizes wavelet
transformed and FCM clustered input variables. Input
variables are the spatial and temporal groundwater
pumping values obtained from a uniform distribution
using LHS.

in which P1 and P2 represents membershipfunction values for input variable  whereas valuesof membership functions for input variable  aredenoted by Q1 and Q2 . Parameters of the output

Selection of appropriate WT involves adjustmentof the three basic parameters, such as selection of amother wavelet family, an order within that family,
and the number of levels of decomposition.
Daubechies (db4), Haar (haar), and Symlet (sym4)
mother wavelets were used and compared in thepresent study. Number of decomposition levels was
decided based on the number of sample index of the
input data. Generally, DWT requires that thedecomposition at level k of the input dataset should
be an integer value such that 2k divides evenly into thelength of the dataset. As the number of input-output
patterns is 1500 in the present study, the number ofdecomposition levels was restricted to ten [210 =1024; 211 = 2048]. In the case of 10 levels of
decomposition, the original data signal wastransformed into an approximation component (A)and 10 detail components (D1, D2,…, D10).

functions f1 and f 2 are symbolized by p1 , q1 , r1
and p 2 , q 2 , r2 , respectively. Gaussian and linear typemembership functions are used as the input andoutput membership functions, respectively for the
initial FIS structure.
The proposed ANFIS consists of five layers,
namely, an input fuzzy layer, a product layer, anormalized layer, a defuzzification layer, and an
output layer. Detailed description of each of theselayers are described in Jang, Sun and Mizutani [26],and is not repeated here.
Fuzzy C-mean (FCM) Clustering
Fuzzy C-mean (FCM) [27] clustering technique wasused to reduce dimensionality of the input dataset for
generating initial FIS structure. FCM is an important
tool for compressing the dataset into a group ofidentical clusters within the input space. FCM
clustering helps reduce number of fuzzy if-then rules
as well as limits the number of linear and nonlinear
modifiable parameters of a FIS. Desired number ofclusters is achieved by minimizing fuzzy overlap
between clusters using Eq. 5
KNO m     ijm  i  c j

2

Thirty five different conjunction models based on
ANFIS, FCM, and MDWT have been developed byusing the specified mother wavelet families (db4,haar, and sym4). In first step, all the decomposedcomponents from these mother wavelets wereseparately correlated with the output variables at fiveMLs. Decomposed details components with lowest
correlation coefficients were removed while theremaining details components and the respective
approximation components were summed to obtain
the input variables for the proposed models. In thesecond step, all the approximations and details
components were summed for obtaining the input
datasets. This step is executed because allcomponents of the decomposed signals have certain
characteristics of the original data. Therefore,
removing any one of them from the input dataset(5)

i 1 j 1

where, Om = function to be minimized, m = fuzzy
partition matrix exponent, K = sample index, N =number of clusters, αi = ith data point, cj = center ofthe jth cluster, µij = membership degree of αi in the jthcluster.
Optimum number of clusters was selected byobserving the Root Mean Square Error (RMSE) (Eq.
6) between the actual and predicted data. The
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

based on the linear correlation may deteriorate themodel performance. The correlation coefficientmeasure only provides an indication of linear
relationship between input and output variables,
which is not the case in the present study. In addition,
two variables that have a small or no linear correlation
might have a strong nonlinear relationship. Present
study deals with a highly non-linear relationshipbetween the groundwater pumping input variables
and the corresponding saltwater concentration values.
Therefore, combining all decomposed components toobtain input variables for the ANFIS models is logicalin the context of the present study. Finally, models
developed with wavelet transformed input datasets
were compared with those obtained by using theoriginal groundwater extraction values.

coefficient A and details coefficients D1–D10 atdecomposition level 10. Each component of thedecomposed dataset carries different characteristicsof the original dataset. While some researchers usedthose decomposed components of the original datasetthat have highest correlations with the original output
variable [19, 20], others argued that all of thedecomposed components should be summed toprepare the final inputs for the prediction models [18,28]. The approximate coefficient A captures only the
major trends whereas the detail components D1–D10
carry abrupt changes, outliers, and shortdiscontinuities in transient groundwater extraction
values. Present study chose input data for the ANFIS
models by looking at the correlation coefficients
between each input subsets and the original saltwater
concentration values at specified MLs. However, thecorrelation coefficients only determine linear
correlations, and the datasets are obtained from ahighly non-linear system in which non-linear relation
exists between the input pumping variables and theoutput concentration values. For this reason,
summing all components of the decomposed datasets
were also considered so that non-linearity of thedatasets is included in the final inputs. Allcomponents (A and D1–D10) were summed byreconstructing the decomposed subsets. The
reconstruction error was computed, which was
negligible in this present study for all considered
wavelet families. Summed components all together
constitutes a dataset very similar to the original data
sets except that the features of the wavelet
decomposed datasets are different, which may help
improve training of the prediction model compared towhen using the original data series. For eachmonitoring location, seven ANFIS based prediction
models (One model developed using the original data,
three models are developed using summing all
decomposed wavelet components each for threedifferent wavelet families, three models aredeveloped for three mother wavelets based oncorrelation between the decomposed series and theoriginal output variable) were developed. Therefore,a total of 35 ANFIS based prediction models weredeveloped and compared. At this stage of the model
development, all developed models were checked fortheir prediction error and model overfitting by
dividing the dataset into a training (80%) and a test
(20%) set. Once the models were developed, they
were presented with a new realization of the original
test dataset for validation of the prediction results.

Performance Indicators
The performance of the proposed prediction models
was evaluated using RMSE, Correlation Coefficient(R), and Mean Absolute Percentage Relative Error(MAPRE) criteria.
Root mean square error (RMSE) is given by

1 n
 (Ci,o  Ci, p )2
n i1

RMSE 

(6)

Correlation coefficient (R) is calculated asnR (C  C )(C  C )
o

i ,o

i 1

n

p

i ,o

(7)

n

 (C  C )  (C  C )
i 1

i ,o

o

2

i 1

i, p

p

2

Mean absolute percentage relative error (MAPRE) isexpressed as

MAPRE 1 n Ci,o  Ci, p C 100n i 1i ,o(8)where, Ci ,o and Ci , p are the observed and predictedsaltwater concentrations; C o and Cp denotes themean of the observed and predicted saltwater
concentrations; and n represents the number of data
points.
RESULTS AND DISCUSSIONANFIS Models

Wavelet Decomposition of the Original Data

ANFIS models were developed for each ML using
the original input-output patterns obtained fromsimulation of the aquifer processes as a result of
spatial and temporal pumping stress applied to theaquifer. Table 1 shows the performance measures ofTransient groundwater extraction datasets werebroken down into several sub-sets with different
resolution levels by using MDWT. The original
dataset S was decomposed into an approximation
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

the five ANFIS models developed for predicting
saltwater concentrations at MLs ML1–ML5. In
general, all models produced R values very close toone. This is attributed to very high degree ofcorrelation between the actual and predicted saltwater
concentration values. The developed models also had
smaller values of RMSE and MAPRE. This indicatesthe potential ability of the models to capture the trendof the data quite precisely. The MAPRE criterion wasused to measure the distribution of errors. The results
obtained from these models at five MLs were used as
benchmark for comparison with the wavelet-ANFIS
models presented in the following sub-section.
Table 1 Performance measures of ANFIS models
trained on original data and validated with new test
dataset
MPs
MP1
MP2
MP3
MP4
MP5

Performance Indices
RMSE

MAPRE, %

R

0.242
5.185
3.787
6.541
3.416

0.458
0.281
0.274
0.073
0.043

0.99860.99940.99960.99980.9999Wavelet-ANFIS Models
Statistical performance measures of the wavelet
transformed ANFIS models developed at five MLs
were calculated. Totally, 30 different ANFIS
structures were developed based on the use of threedifferent mother wavelet families and on the selectionof decomposed components. It was observed that R
values were very close to 1 for all developed models.
Therefore, an R criterion did not provide a goodmeasure of comparison among models in this case.
RMSE and MAPRE criteria were used for comparing
ANFIS models developed using original data (Table
1) and those using wavelet transformed componentsof the original datasets. As the input-output patterns
come from a highly non-linear system, wavelet
decomposed components selected based on linear
correlation between decomposed components and theoriginal output may not be the logical way of
selecting input variables for the ANFIS models.
Moreover, each decomposed components carries
distinct and essential characteristics of the original
datasets. In this viewpoint, present study used bothtypes of datasets as inputs to the ANFIS models. To
make a valid comparison and to reproduce theprediction of the models, random number generatorof MATLAB was set to its default value (Mersenne
Twister with seed 0). Also, for consistency, alldeveloped models were presented with a totallyunseen set of original test data. Results suggested thatmodels developed with different datasets based on
730

three different mother wavelets produced higher
values of R and lower values of RMSE and MAPRE.
This implied a good generalization capability of thedeveloped models on unseen datasets. A more precise
investigation on RMSE and MAPRE values indicatedthat for monitoring location ML1, ANFIS model
developed using all decomposed components of sym4
decomposed datasets produced the lowest value of
RMSE (0.230 mg/l). This result was also better thanthe RMSE values for ANFIS model developed when
original dataset was used for training. Possible
explanation for this trend is that WT improves thequality of data at different regions of the input spacethat helps better training of the ANFIS model. At thismonitoring location, db4 decomposed datasets
selected using linear correlation produced the worst
result (highest RMSE value of 0.560 mg/l). At ML2,
haar decomposed datasets produced the lowest
RMSE compared to the original datasets. At ML3 andML5, sym4 decomposed and original datasets
produced the similar results. At ML4, all thecomponents decomposed using db4 provided thelowest RMSE (5.898 mg/l) compared to the original
datasets (RMSE = 6.5405 mg/l).
CONCLUSIONANFIS models were developed for approximating
and predicting density dependent coupled flow andsalt transport processes in a multi-layered coastal
aquifer system. Solution results of a numericalsimulation model were used for training andvalidation of all developed ANFIS models. Original
datasets as well as the wavelet transformed datasets
using db4, haar, and sym4 mother wavelets were used
to develop a total of 35 ANFIS models at five MLs.
Validation of all the models was carried out by using
a new unseen original test data. The results revealed
that wavelet transformed datasets helped improve thetraining of proposed ANFIS based prediction models.
Moreover, FCM made it possible to use highdimensional dataset (80 input variables) for
developing ANFIS based prediction models. The
results also showed that types of mother wavelet
selection depended on the actual original non-linear
relationship between the transient groundwater
extraction values and the resulting saltwater
concentration values at different MLs. Wavelet
transformed data provided better learning capabilitiesof the ANFIS based prediction models by capturing
important features of the data on different resolution
levels. Future research may be directed towards theinvestigation of possible improvement in the Pareto
optimal solution of a saltwater intrusion management
model using these wavelet transformed trained
ANFIS models.

GEOMATE - Mie, Japan, Nov. 21-24, 2017

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

LINKED SIMULATION-OPTIMIZATION MODEL FOR OPTIMUM
HYDRAULIC DESIGN OF WATER RETAINING STRUCTURESCONSTRUCTED ON PERMEABLE SOILS
1

Muqdad Al-Juboori1 and Bithin Datta1
Discipline of Civil Engineering, College of Science and Engineering, James Cook Univ., Townsville, QLD
4811, Australia
ABSTRACT

Hydraulic Water Retaining Structures (HWRS), such as dams, weirs and regulators are important projects and necessary
for water management. Seepage analysis under HWRS substantially influences the design of HWRS. One of the biggest
challenges in design of HWRS is to determine the accurate seepage characteristics with complex flow conditions, andsimultaneously to find the optimum design considering safety and cost. Therefore, this study concentrates on developing alinked simulation-optimization (S-O) model for non-homogenous anisotropic soil properties. This is achieved via linking
the numerical seepage simulation (Geo-Studio/SEEPW) with the Genetic Algorithm (GA) evolutionary optimization solver.
Since, a direct linking of numerical model with optimization model is computationally expensive and time consuming,
accurate surrogate models are integrated instead of a numerical simulation model within the S-O model. A Support vector
machine (SVM) based surrogate model is linked with the optimization model to achieve the optimum hydraulic design of
HWRS. The seepage characteristics of optimum design obtained by S-O are evaluated by comparing these with thenumerical seepage modeling (SEEPW) solutions. The comparison, in general, shows good agreements. Accordingly, the SO methodology is potentially applicable for providing safe, efficient and economical design of HWRS constructed on acomplex seepage flow domain.
Keywords: Support vector machine, Genetic algorithm, Seepage modeling, Hydraulic structures design
achieved. This methodology involves developing a
constrained optimization model based on Genetic Algorithm(GA) to integrate all design safety factors regarding the wide
range of applied forces, i. e. , hydrostatic pressure, upliftpressure, exit gradient, and considering, the minimum cost
as the objective function.
The developed optimization model must be linked with
the numerical seepage analysis model to concurrently
evaluate the candidate designs (solutions) of the HWRS.
However, the direct linking of optimization model with thenumerical seepage model is a computationally demanding
and time consuming task. This is because, the GA calls thesimulation model numerous times to evaluate the objectivefunction and the constraints in order to achieve an optimal
solution. Alternatively, machine learning technique is used
to build a well-trained model (surrogate model), which could
be efficiently used instead of the numerical model. A welltrained surrogate model can expeditiously and accurately
predict the responses of the numerical model for complex
problems within the linked S-O model.
Many machine learning techniques could be used inbuilding the surrogate models, such as artificial neuralnetwork (ANN), fuzzy logic, multivariate adaptive
regression splines (MARS), genetic programming (GP) andsupport vector machine SVM. In this study, SVM is selected,
because SVM is considered a powerful deep-learning tool.
SVM is utilized in the classification, function approximationand prediction by which a nonlinear and complex civilengineering problems can be efficiently modeled. Moreover,in addition to the efficiency and predictive accuracy, SVM
has a generalization ability to accurately predict data beyond

INTRODUCTION
Construction of Hydraulic Water Retaining Structures(HWRS) is the strategic aim for the most communities
around the world to build a strong water management system.
Seepage analysis related to HWRS is a critical step of
HWRS design [1]. In addition to the direct impacts ofhydrostatic water pressures on the structural system of the
HWRS, the seepage design parameters such as upliftpressures and exit gradient are the other fundamental factors
needed to be incorporated in HWRS design.
The earliest theories and methods, such as Bligh’s creep
theory, Lane’s weighted creep theory, Flow-net method,fragment method and Khosla’s theory [1] used to analyse
seepage related to HWRS involve many simplifications andare based on many empirical assumptions. These methods
are applicable only for simple, symmetrical cases and quite
general soil conditions (homogeneous and isotropic), which
are rarely found in field soils[2]. Moreover, the solutions oftheses method are approximation solutions, and thesegenerally display noticeable error compared withexperimental observations and the numerical solutions [3].
In contrast, the numerical seepage analysis methods suchas the finite element method (FEM) provides accurate
solutions for a wide range of the seepage problems
encountered in the real field [4, 5]. However, these solutions
might not be useful, as the resulting designs may not satisfy
the safety requirements and also not optimize theconstruction costs. Therefore, employing the optimization
technique could provide a reliable and optimum solution,
especially when accurate numerical seepage simulation
responses are integrated in the optimization model.
Accordingly, based on linked simulation-optimization S-O
methodology [6-8], an ideal HWRS design could be732

GEOMATE - Mie, Japan, Nov. 21-24, 2017

hydraulic conductivities are (kx1, kx2, kx2) with theanisotropy ratio (Ky/Kx)1, (Ky/Kx)2, (Ky/Kx)3 respectively.
The total upstream water head (H) is also considered avariable.

the training range. Additionally, SVM can overcome thenoisy data in the training phase by integrating the most
governing support vectors. Hence, SVM has the ability toovercome the over-training phenomena [9] .
Recently, SVM has been utilized to model complex civilengineering problems to provide an extensive understandingof the variables involved in the model [9-16].In the majorityof the conducted researches, SVM is utilized to predict
specific responses depending on the input variables or tosimulate performance of a particular engineering system withspecial conditions. For example, in hydraulic structure
design, SVM has been used to predict the forecasting of thetangential shift of a concrete dam[14], and to predict future
dam responses with environmental variables [17].
Nonetheless, SVM has been rarely utilized as a surrogate
model within the optimization model in the hydraulicstructure design problems. Application of other machinelearning techniques for solving optimization problems
related to hydraulic structures design incorporating complex
soil properties has been very limited as well.
This paper concentrates on developing a linked S-O model
based on two different models. The first model is theconstraint optimization model based on GA as the
optimization solver. The objective function is the minimum
construction cost of HWRS and the constraints reflect the
HWRS design requirements. The second model is thesurrogate model which is based on the SVM. The surrogate
model is extensively trained using numerically simulated
data generated by a numerical seepage modeling software(Geo_Studio2012/ SEEPW) [18]. The seepage design
parameters obtained as the solution of the optimal design by
the S-O model are evaluated using SEEPW to investigate theprediction accuracy of the SVM within an S-O model.

Fig. 1 Conceptual numerical modelAll the input sets (1700 sets) are randomly generated using
Latin hypercube sampling method (LHS) within specified
ranges. LHS provides a uniform periodic random data bywhich robust training could be achieved in the machinelearning process[19]. Each set of input data represents one
scenario of the HWRS design. The SEEPW software isutilized to find the resulting seepage characteristics for eachscenario. The seepage characteristics include the upliftpressure in front (θEi) and behind (θCi) each single sheet pilein addition to the exit grained at the end of the floor ofhydraulic structure (toe). The seepage characteristics
resulting from the numerical seepage modeling represent theoutput data used for training the SVM models.
SUPPORT VECTOR MACHINENUMERICAL MODEL SOLUTION AND TRAININGDATA GENERATION

Support vector machine is a deep learning technique used
for classification and regression problems. Recently, SVM
has been implemented in wide academic applications andengineering problems because the SVM has a good
generalization ability, and is less impacted by overfitting
phenomena. Generally, the SVM algorithm selects from thetraining data the best hyperplane (vector) which provides anefficient classification. The SVM algorithm maximizes the
distance between the center of the hyperplane and its
boundary (margin) to attain the best SVM model. therefore,
the ideal SVM must have wider margins, then the SVM
model could provide accurate prediction and highgeneralization ability [20, 21].
The SVM technique is applied to build the models that
could accurately predict the numerical responses. Matlab
programing language is utilized to develop the SVM models,
because Matlab is a versatile tool and provides many options
that can be modified to build perfect SVM models. 1700 setsof the simulated data obtained by solving SEEPW numericalcode are used to train and build the SVM models. Twenty one
models are built to determine the uplift pressure in front, andbehind each sheet pile, and the exit gradient near the end of
the structure. The SVM is trained on the simulated data where
90% of the data are utilized for training and 10% are used fortesting. The coefficient of determination (RSQ) and meansquare error (MSE) for the training and testing phases are

In contrast to an experimental study, the numerical model
could provide accurate and quick solutions even for complex
problems, especially by using high speed processors. The
optimization model incorporates the numerical responses,
either obtained directly using the numerical model code orapproximately by the surrogate models. As it is difficult andcomputationally very costly to directly link the optimization
model with the numerical model, a surrogate model needs
to be developed.
To train the surrogate model, Input–output data sets mustbe generated and solved by the numerical model. Also, aconceptual comprehensive numerical HWRS model shownin Fig.1 is assumed with different variables. These variables
represent the decision variable in the optimization model tofind the best variables values and best combinations of thesevariables, which provide the optimum solution.
The conceptual model comprises different sets of deign
variables randomly varied within assumed ranges. In thisstudy, the proposed design variables are the dimensions andinclination of ten sheet piles (S1-S10) (cut-off) and the spacing
between them. The symbols for the sheet pile depths are(d1, d2 … d10), for the angles are (β1, β 2,… β 10) and for thewidth between the sheet piles (b1, b2,…. b10). The subsoil
foundation consists of three layers (DL1, DL2, DL3) and their733

GEOMATE - Mie, Japan, Nov. 21-24, 2017

listed in the Table A2. The parameter for each SVM model
are carefully selected after several iterations of trial anderrors until best RSQ and smaller MSE are achieved. It could
be concluded that the most influencing parameter on SVM
performance is the kernel function type, and the constraintbox. The kernel function used in this study is the polynomial
kernel with varied order, which provide precise prediction
compared to the other kernels.

Minimize:(1)
Where: Ti represent the average thickness of the floor
between two sheet piles,
The cost of constructing theThebody of the HWRS per cubic meter ($500/m3),
construction cost of the sheet pile per cubic meter($1000/m3),
the thickness of the sheet pile, which isconstant = 0.5m .
The decision vector is subjected to the following
constraints:
Flotation constrain: The uplift pressure on the foundationof the HWRS along all width of HWR must be safe [24, 25].
Therefore, the value ØC and ØE near each sheet pile must be
sufficiently counterbalanced by the floor thickness at thesepoints. The safety factor assumed is 1.3 as shown in Eq. (2).

OPTIMIZATION MODEL
The optimization model integrated in the S-O model isformulated to find the best design of HWRS at a minimum
cost. Because of the complexity of the optimization task, theGA is used in this study. GA evaluates the fitness value andthe constraints based on the surrogate models responses.
Additionally, GA is likely to provide a global optimum
solution and has the ability to deal with a complex problem
as it does not rely on differentiating the performanceequations to find the optimum solution. Instead GA is basedon a natural selection principle[22, 23]. The GA is efficientin finding the global solution in such a problem, where theperformance function is based on the surrogate model
responses. In the S-O model, GA calls the surrogate models(SVM) huge number of times to evaluate the fitness value
and the constraints for each individual until the optimum
design is achieved. Matlab programing language is used to
implement the optimization model. The GA parametersspecified in this study are: Population Size 2000, Elite Count
10, Crossover Fraction 0.8, Function Tolerance 1e-6,
Constraint Tolerance1e-3, and the rest of GA options are left
to default Matlab options.
The decision vector (X) involved in the optimization model
represents the most important design variable of the HWRS
model (conceptual numerical model). The X is modified
many times by GA to find the minimum construction cost of
the design, and simultaneously to provide safe design thatsatisfies all design requirements (constraints).
The decision vector is listed as shown below, where thedesign variables from x1 to x11 represent the width between
sheet piles (b1, b2…b11), variables form x12 to x22 represent
the depth of the sheet piles (d1, d1,…d10) the variables fromx23 to x32 represent the inclination angle for the cutoffs ( β1,β2,… β 10) . The optimization problem is formulated as shown
below:

Find

.
.
.
.
.
.

1.3

Ø

Ø

, i = 1,2,3...20(2)

Where Gc is the specific gravity of the concrete.
Exit gradient constrain: If the exit gradient is equal ormore than the critical gradient, piping failure is likely.
Therefore, it is recommended that the exit gradient value
must be at least 3 to 5 times less than critical gradient [26, 27]
Usually, the shortest stream line or the closest point to
HWRS toe is the most critical point at which the largest valueof exit gradient could be seen. The safety factor of exit
gradient is determined by Eq. (3)
i
F. S
(3)
i
Where ic is critical exit gradient and given by Eq.(4)γ(4)γ
Where γ is the submerged soil density, γ is the weight
density of water. The soil properties are considered mixed
grained sand, which has γsat =21.2 kN/m3 and that results in
icr=1.15 [28].
Other constraints: Many other constraints are also
considered in the optimization model, such as sliding
constraint and overturning constraint. The preventing
eccentric loading state constraints is incorporated also toensure uniform distribution of the loads on the soil surface.
It is interesting to note that the value ØC and ØE for each
sheet pile, and ie values involved in the S-O model are
determined based on the surrogate models responses. The
surrogates models within the optimization model are also
represents the binding constraints where the decision vector
must satisfy the simulation constraints in addition to thedesign constraints.
i

b1
b2
.
.
.
b11
d1
d2
.
.
.
d10
β1
β2
.
.
.
β10

RESULTS AND DISCUSSION
The developed methodology was applied to optimize theconceptual model based on the surrogate models responses.
Ten different cases having different H values starting from
10 m to 100 m were solved by S-O model as shown the table
A1. The other parameters value are left constant, such as

Which minimizes the objective function shown in Eq. (1)734GEOMATE - Mie, Japan, Nov. 21-24, 2017

evaluation results showed that maximum percentage of error
between the S-O model and SEEPW solutions is around 10%.
This figure demonstrates that the SVM generalization ability
with unseen and extreme data is good. On the other hand, theprediction of SVM for exit gradient is less accurate, which
could be attributed to the large number of input variable forexit gradient surrogate model. However, the most of the exit
gradient safety factor for the optimum solution is still within
the standard and safe limit, and not less than 3.

hydraulic conductivity for each layer is 5 m/day, theanisotropy ratio is 1 and the depth of each subsoil layer is 50
m for all cases. For all implemented cases the solution
obtained by S-O model satisfy the design requirement and thesafety factors.
Generally, the contribution of the variables b1to b8 and d1
to d8 on the safety of the HWRS is neglected, where theoptimum values for these variables is almost zero.
Consequently, as the length of d1 to d8 reach their minimum
value, their inclination angle become meaningless.
Nonetheless, the inclination angle has a noticeable effect on
reduction of uplift pressure, especially when β value is lessthan 90 degrees. In contrast, when β value is more than 90
degree it has a significant effect in reduction of the exit
gradient value.
However, the optimum solutions obtained for each case arebased more on increasing the width of HWRS to reduce theuplift pressure on the body of HWRS, and less based on the
sheet piles lengths to decrease the PWP. This could be
attributed to two reasons. First, the uplift pressure value must
be counterbalanced by the weight of the construction materialof HWRS. Accordingly, even if it is costly solution, it isnecessary to provide safe thickness against the upliftpressure. Secondly, some design requirements significantly
influenced the design features. For example, to ensure thestability of HWRS against overturning condition, the GA
increases the total width of HWRS to provide more stability
against the overturning forces and the huge amount of theactive moments. Besides, preventing eccentric load state in
the foundation of HWRS is another critical design
requirement, therefore GA restricts the loads resultant to belocated within the second third of the total width. Hence, GA
increases the total width to ensure uniform distribution ofstress on the soil foundation. Additionally, the construction
cost of the sheet piles is more expensive than the construction
cost of the HWRS floor.
On the other hand, because of the crucial impact of the exit
gradient on the design of HWRS, the d10 length has asignificant control in reduction of the exit gradient value. As
a result, for all optimum solutions the d10 values have aconsiderable length, as shown in Table A3. Additionally,
the optimum sheet pile inclination angle of β10 is 150 degree
toward downstream. The increase of β10 value effectively
decreases the exit gradient value, as the streamline length ofseeping water significantly increases and in turn the exit
gradient value decreases. Moreover, another factor whichmight affect the exit gradient is the length of b10, because
increasing the b10 reduces the uplift pressure andconsequently decreases the exit gradient value.
Mainly, the exit gradient value for all cases reach the
maximum allowable value to satisfy a minimum safety factorof five with respect to the critical gradient. Accordingly, theexit gradient parameter plays a critical role in the selection of
optimal decision variable values in the optimization process.
Additionally, an extensive evaluation was conducted forvalidating the S-O optimum solutions. The seepage design
variables (θE, θC, exit gradient) were evaluated by solving
the optimum solutions using SEEPW, then compared theseepage characteristic obtained by SEEPW with the samevalues obtained from the S-O model. In general, the

CONCLUSION
The optimization based searching process is an expensive
and computationally demanding task, especially when the
optimization model linked to a numerical simulation toevaluate the fitness value and the constraints. Therefore, thelinked S-O model based on SVM surrogate models was
implemented to find the optimum design of HWR. Many
SVM surrogate models were precisely built to predict the
seepage analysis results. Based on the accurate responses ofthe surrogate models, GA evaluate the fitness value and theconstraints. Therefore, a reliable and optimum design of
HWRS could be achieved.
The seepage design variable values (θE, θC, exit gradient)obtained as optimum solutions were validated using
numerical solutions. The validation process showed that thesurrogate models predictions were accurate, even in thesolution range beyond the training data range.
In general, the optimum and safe hydraulic design of
HWRS must include sufficient floor width (more than H
value) and one of the end sheet piles with the optimum length( not less than 0.5H), with inclination angle attaining up to
150 degrees. Finally the methodology is potentiallyapplicable for funding find the optimum design of HWRS at
minimum cost for different scenarios, within the specified
training data range. Future studies may include expanded
training ranges, and use of different machine learningtechniques and optimization solvers to achieve moreaccuracy.
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APPENDIX
Table A1 optimum solution and the objective function value for different value of H
H (m)

100

90

80

70

60

50

40

30

20

10

43850223763560

3326936223686515788831098975

631827497585130951

53324

b1
b2
b3
b4
b5
b6
b7
b8
b9
b10
b11
d1
d2
d3
d4
d5
d6
d7
d8
d9
d10
dd
β1
β2
β3
β4
β5
β6
β7
β8
β9
β10

0.0
15.1
0.5
0.1
0.7
0.7
3.9
0.1
31.2
113.2
10.3
7.4
0.1
0.0
0.0
0.0
0.2
0.0
0.0
0.4
56.2
0.0
65.3
85.9
91.9
70.7
44.1
67.6
73.1
32.5
44.6
150.0

3.1
3.7
2.6
2.5
2.2
2.9
3.5
1.9
21.2
113.1
11.1
1.7
0.2
1.0
0.1
0.0
0.2
0.3
0.4
0.0
56.5
0.0
67.4
85.6
89.3
70.7
46.9
76.2
61.3
100.4
30.0
150.0

0.0
0.6
1.5
1.6
0.6
1.2
4.3
1.1
36.0
111.9
11.3
0.2
0.1
0.4
0.2
0.0
0.3
0.0
0.5
0.5
55.4
0.1
64.4
83.8
90.0
71.6
46.1
78.1
77.0
45.0
30.0
128.5

0.7
0.3
0.7
0.9
2.3
1.6
2.3
2.7
33.4
72.6
6.3
0.0
0.0
0.2
0.3
0.7
0.0
0.9
0.4
1.7
34.4
0.0
63.1
77.9
87.5
81.4
57.2
85.3
76.3
43.7
30.0
150.0

0.6
1.5
0.6
0.5
0.8
1.5
2.9
2.5
22.5
62.7
6.1
0.4
0.3
0.0
0.2
0.0
0.3
1.1
0.0
0.4
31.0
0.0
66.9
84.9
88.3
79.8
61.5
89.5
83.6
93.8
30.0
149.7

0.0
1.4
0.5
0.5
0.1
0.6
0.7
2.3
15.1
59.6
5.8
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
29.8
0.0
66.2
69.0
82.1
73.3
88.4
91.8
76.0
30.0
30.0
135.3

0.0
2.6
7.1
5.8
0.0
0.1
0.3
0.7
0.9
37.2
5.0
0.8
0.5
2.7
0.0
0.0
0.0
0.1
0.0
0.0
17.5
0.0
70.0
83.7
91.8
78.7
77.7
98.8
95.7
103.0
30.0
150.0

0.3
0.0
0.0
0.0
0.0
0.0
0.4
1.0
9.2
54.6
8.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
27.0
0.0
70.6
84.3
89.4
79.8
30.0
117.4
30.0
30.0
30.0
110.9

0.1
1.3
1.4
1.3
0.6
1.0
0.1
3.2
2.0
14.7
1.0
0.0
0.1
0.0
0.2
0.0
0.0
0.0
0.0
0.0
7.3
0.0
77.9
81.6
85.9
142.9
60.0
136.0
78.8
149.5
30.0
121.6

0.7
1.2
1.1
0.2
0.5
0.5
0.5
6.0
2.8
7.7
2.4
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.0
0.0
2.5
0.0
46.3
31.3
30.0
30.0
30.0
30.0
30.4
104.8
30.0
101.9

Objective
Functionvalue ($)

736

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table A2 Properties of the developed SVM models
model

Exit
gradient
θC10
θE10
θC9
θE9
θC8
θE8
θC7
θE7
θC6
θE6
θC5
θE5
θC4
θE4
θC3
θE3
θC2
θE2
θC1
θE1

RSQ
TRAIN
0.95

MSE
TRAIN
0.1

RSQ
TEST
0.91

MSE
TEST
0.17

function

ORDER

polynomial

4box
constraint
1

0.97
0.96
0.95
0.99
0.98
0.99
0.99
0.98
0.99
0.99
0.99
0.99
0.99
0.99
0.999
0.999
0.99
0.99
0.99
0.99

1.22
4.57
7.66
1.32
3.74
0.82
2.12
5.25
1.74
1.08
0.99
0.63
1.21
0.77
0.95
0.94
1.92
1.11
2.75
3.2

0.97
0.97
0.95
0.99
0.98
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99

1.08
3.64
6.35
0.96
2.93
0.97
1.59
0.77
1.46
0.65
1.13
0.54
1.2
0.74
0.94
0.93
1.94
1.13
3.2
2.8

polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial
polynomial

4
3
3
3
4
3
3
2
4
3
3
2
3
2
3
3
4
3
3
2

10
10
20
15
1
3
1.5
10
5
17
4
4
2.1
1.6
4
2.8
2.7
1.5
8
20

training input variables
x8 x9 x10 x11 x19 x20x21 x22 x30 x31 x32 AB *x11 x21 x32 AB
x10 ABx20 x31 AB
x9 AB
x19 x30 AB
x8 AB
x18 x29 AB
x7 AB
x17 x28 ABx6 x22 ABx16 x27 AB
x5 AB
x15 x26 AB
x4 AB
x14 x25 AB
x3 AB
x13 x24 AB
x2 AB
x12 x23 AB
x1 AB

Note: AB equal to [DL1 DL2 DL3 kx1 ( ky/kx)1 kx2 ( ky/kx)2 kx3 ( ky/kx)3 H ]Seepagedesignvariable
H=100
H=90
H=80
H=70
H=60
H=50
H=40
H=30
H=20
H=10

Table A3 Evaluation results of the S-O model for different value of H

S-O
SEEPW
% Error
S-O
SEEPW% Error
S-O
SEEPW% Error
S-O
SEEPW% Error
S-O
SEEPW% Error
S-O
SEEPW% Error
S-O
SEEPW% Error
S-O
SEEPW% Error
S-O
SEEPW% Error
S-O
SEEPW% Error

ΘE1

ΘC1

ΘE2

ΘC2

ΘE3

ΘC3

ΘE4

ΘC4

ΘE5

ΘC5

ΘE6

ΘC6

ΘE7

ΘC7

ΘE8

ΘC8

ΘE9

ΘC9

ΘE10

ie

98.7
100.0
-1.3
88.3
85.5
3.3
79.0
80.0
-1.3
69.0
67.7
-1.3
59.2
59.0
-1.3
49.4
50.0
-1.3
39.5
40.0
-1.3
29.6
29.4
0.7
19.8
19.8
-0.2
9.9
9.2
-1.3

93.6
86.4
8.3
85.3
83.0
2.8
76.3
78.1
-2.3
66.6
67.0
8.3
56.8
56.5
8.3
47.3
48.7
-3.0
37.6
36.3
-3.0
28.0
28.8
-2.8
18.5
18.8
-1.9
9.0
8.8
-3.0

91.0
81.4
11.8
83.2
81.1
2.5
74.3
77.2
-3.8
64.6
66.6
11.8
55.0
55.4
11.8
45.7
46.6
-2.0
36.2
34.8
-2.0
26.9
28.8
-6.4
17.7
17.5
1.1
8.5
8.2
-2.0

89.4
81.2
10.0
81.4
80.7
0.9
72.5
76.5
-5.3
63.0
66.0
10.0
53.5
54.6
10.0
44.3
46.2
-4.0
35.0
34.1
-4.0
26.0
28.4
-8.3
17.0
17.1
-0.4
8.4
8.1
-4.0

88.9
81.1
9.6
80.8
79.7
1.4
72.0
75.4
-4.6
62.6
65.3
9.6
53.1
54.3
9.6
44.0
45.8
-3.9
34.6
31.4
-3.9
25.7
28.3
-9.1
16.7
16.2
3.1
8.1
7.7
-3.9

88.3
80.9
9.1
80.0
78.6
1.8
71.2
74.5
-4.3
61.9
64.6
9.1
52.5
54.0
9.1
43.3
45.4
-4.6
33.8
29.2
-4.6
25.0
28.0
-10.5
16.0
16.0
0.1
7.7
7.6
-4.6

87.3
80.9
7.9
78.9
77.7
1.5
70.3
73.7
-4.5
61.1
64.1
7.9
51.8
53.8
7.9
42.8
45.1
-5.2
33.2
27.7
-5.2
24.5
28.0
-12.2
15.5
15.4
0.8
7.2
7.5
-5.2

87.0
80.7
7.8
78.6
77.5
1.4
69.9
73.1
-4.4
60.6
63.3
7.8
51.3
53.1
7.8
42.2
44.8
-5.9
32.6
27.6
-5.9
23.8
27.7
-14.0
15.0
15.1
-0.6
6.6
7.4
-5.9

86.7
80.5
7.7
78.1
76.5
2.1
69.4
72.9
-4.8
60.0
62.2
7.7
50.7
52.7
7.7
41.7
44.8
-6.9
32.1
27.6
-6.9
23.4
27.7
-15.4
14.7
14.9
-1.7
6.3
7.2
-6.9

83.2
80.4
3.5
74.9
76.3
-1.9
66.5
72.6
-8.4
57.5
61.2
3.5
48.6
52.4
3.5
40.0
44.5
-10.0
30.8
27.5
-10.0
22.8
27.4
-16.8
14.2
14.7
-3.7
6.5
7.1
-10.0

83.0
80.2
3.5
74.5
75.2
-0.8
66.3
72.1
-8.1
57.1
60.5
3.5
48.3
51.7
3.5
39.7
44.2
-10.3
30.5
27.5
-10.3
22.4
27.4
-18.3
13.7
14.3
-4.1
6.0
7.0
-10.3

81.4
80.0
1.8
73.2
74.9
-2.3
65.1
71.7
-9.2
56.2
60.2
1.8
47.5
51.2
1.8
39.0
43.8
-10.8
30.0
27.3
-10.8
22.0
27.2
-19.1
13.4
14.2
-5.4
6.2
6.8
-10.8

80.9
78.6
2.9
72.6
73.6
-1.4
64.5
69.7
-7.6
55.6
59.4
2.9
46.9
50.2
2.9
38.5
43.4
-11.4
29.5
27.2
-11.4
21.6
26.9
-19.8
13.1
14.1
-7.0
6.2
6.7
-11.4

80.3
78.5
2.3
71.9
73.4
-2.0
63.7
69.6
-8.4
54.7
58.4
2.3
46.0
49.1
2.3
37.8
43.2
-12.6
28.8
27.0
-12.6
21.4
26.7
-19.9
12.7
14.0
-9.0
6.0
6.6
-12.6

77.1
78.4
-1.8
69.1
72.8
-5.0
61.4
69.3
-11.4
52.9
57.6
-1.8
44.5
48.3
-1.8
36.7
42.0
-12.7
28.1
26.9
-12.7
20.8
26.3
-20.9
12.3
12.8
-3.8
5.7
5.2
-12.7

77.2
78.3
-1.4
68.3
72.5
-5.8
61.1
68.8
-11.3
52.6
57.2
-1.4
44.0
48.1
-1.4
36.7
41.8
-12.3
27.7
26.7
-12.3
20.8
26.1
-20.5
12.2
12.7
-3.8
5.6
5.1
-12.3

66.1
68.5
-3.5
60.8
65.5
-7.2
53.4
57.9
-7.8
46.7
46.1
-3.5
40.0
40.2
-3.5
33.7
36.2
-6.9
25.8
26.4
-6.9
19.0
23.3
-18.5
11.0
12.0
-8.5
4.8
4.5
-6.9

65.6
68.3
-4.1
60.9
65.4
-6.9
53.5
57.7
-7.4
46.3
45.4
-4.1
39.8
40.1
-4.1
33.3
36.0
-7.6
25.1
26.3
-7.6
18.1
23.2
-21.7
10.3
11.9
-13.4
4.4
4.4
-7.6

38.7
39.7
-2.6
35.7
37.7
-5.2
32.4
36.1
-10.3
30.2
26.8
-2.6
27.7
23.9
-2.6
24.3
22.4
8.7
19.8
15.6
8.7
14.1
15.1
-6.7
8.1
8.1
0.0
3.2
2.9
8.7

0.23
0.28
-17.940.21
0.25-16.32
0.21
0.19
9.89
0.23
0.30
-17.940.23
0.30-17.940.23
0.26-11.470.23
0.30-11.470.16
0.22-27.570.23
0.36-36.170.23
0.32-11.47737

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

JOINT BENMARKING AND ECO-EFFCIENCY FOR
THE SUSTAINABLE PERFORMANCE OF SWINE PRODUCTION
IN THAILAND
Weerawat Ounsaneha1 Punthila Janthaphat2 Thunwadee Tachapattaworakul Suksaroj3,
Cheerawit Rattanapan3*
Faculty of Science and Technology, Valaya Alongkorn Rajabhat University under the Royal Patronage,
Klong Nuang, Klong Luang, Pathumthani, 13180, Thailand,2
Faculty of Environmental Management, Prince of Songkla University, Hat Yai, Songkhla, 90112, Thailand
3
ASEAN Institute for Health Development, Mahidol University, Salaya, Phutthamonthon, Nakhonpathom,73710, Thailand
1

ABSTRACTThis research aimed to develop the sustainable performance of swine production through joint
benchmarking and eco-efficiency. The economic and environmental performance of fifteen swine farms in
Thailand between 2011 – 2013 were evaluated by Gate to Gate sector boundary. The results showed the highest
and lowest values of eco-efficiency in the swine farming sector were feed and water consumption respectively.
Benchmarking of eco-efficiencies in all indicators demonstrate that best practice for swine farms was obtainedwith average feed consumption of 1 kg/head-day, average water consumption of 1.17 L/head-day, use ofrenewable energy from bio-gas of 0.014 kWh/head-day, use of swine fever vaccination and anthelmintics,
greenhouse gas emissions of 0.00875 tonCO2eq/head-day and total amount of waste produced was 6.25 kg/headday. Lastly, the sustainable development master plan for swine production in Thailand, which includes breeding
selection, husbandry management, farm management and attendance, and the environmental management offarms was developed using material flow analysis concepts, in-depth interview and brainstorming with bestpractice swine farmers.
Keywords: Benchmarking; Eco-Efficiency; Sustainable Performance; Swine Production; Thailand.
benchmarking and eco-efficiency to improve
agriculturaloperations.
This
study
uses
INTRODUCTION
benchmarking and the concept of eco-efficiency
The concept of environmental sustainability
with the objective of performing an eco-efficiency
applies to operations management within food andassessment of swine farms in Thailand. In addition,
agricultural systems [1].In Southeast Asia, Thailand
a joint study was conducted to identify the bestis the largest producer of swine with13.07 million
performing farms for use in public policy to improveheads in 2013 [2]. Nuengjamnong and Rachdawong
the eco-efficiency of swine farm production.
[3] investigated environmental impact issues within
the industry, noting that the size of swine farms has
shifted from small to large scale operations.
Additionally, consumers in developed countries
METHODS
demand safe food of high quality produced with
The swine farm production process
According to the previous study [3], verified in aminimal adverse environmental impact [4-7].
swine farm in the southern part of Thailand, the firstA feasible approach to measure sustainability at
step of swine farm production is swine breeding.
an individual level, increasingly adopted, isPregnant swine are given water and feed for four
represented by eco-efficiency, which appeared in themonths. Then, vaccines, energy, water, and feed are
1990s as a practical tool to measure sustainability.
needed to care for piglet for one month, or till they
The World Business Council for Sustainable
have reached 16 kilograms in body weight. Piglets
Development [8] introduced the term “ecoare separated into two groups, those directly sold,efficiency”, identifying a management philosophy
and swine grown for a further forty days. In
aimed at encouraging businesses to search for
addition, this step in swine production produces
environmental improvements that yield parallelsignificant wastes from swine feces and wastewater
economic benefits. Eco-efficiency studies were usedfrom floor and corral cleansing, which can beto assess performance and identify opportunities for
directed to a biogas system or preliminary treatment
improvement [9]. This concept, together with
before environmental discharge (Figure 1).
integrative design, offers an opportunity to
substantially improve eco-efficiency. Various
reports [10-11] studied effective methods of linking
738

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The eco-efficiency calculation is shown in equation
(1).
=

/Σ

(1)

Where: E is Eco-efficiency value; EV is the
economic value of swine production; Σis thetotal environmental impact from the material andresource use of swine production.
The master approach of swine production towardsustainable development by joint benchmarking
and eco-efficiency concept
The eco-efficiency values of swine farm
production were used to identify best practice bybenchmarking the value of each indicator. Firstly,
indicator
units
were
normalized
beforebenchmarking, then, the eco-efficiency value of eachindicator was benchmarked to identify best practiceperformance. The concept of material flow analysis[13] was used to confirm the process of best practicefarm in each indicator. Finally, in-depth
interviewing and brainstorming with farm owners
were included for approach verification by and thenthe master plan of swine production towardsustainable development in Thailand was developed.

Figure 1. The swine farm production process
Eco-efficiency indicator and data collection
procedure
The eco-efficiency assessment of swine farm
production required the conclusion of the literature
review and farm survey including inputs, outputs
and by-products. Eco-efficiency indicators consistedof economic and environmental indicators (Table1).
A questionnaire was developed to collect data on theselected indicators, based on a questionnairedeveloped by the National Round Table on theEnvironment and the Economy [12]. This
questionnaire was approved by the Social EthicalCommittee of Mahidol University.
The environmental and economic performance offifteen swine farms in the southern and central partsof Thailand between 2011 - 2013 were collectedbased on farm size recommendations of the
Pollution Control Department, Thailand, including
small (50-500 pigs), medium (500-5,000 pigs), andlarge (more than 5,000 pigs) farms.

RESULTS AND DISSCUSSION
Eco-efficiency value of swine farm production
The resulting eco-efficiency values of swine farm
production are shown in Table 2. The eco-efficiency
values of small size farms are highest and lowest forelectricity consumption and greenhouse gas
emissions respectively. Additionally, the trend for
eco-efficiency values increased annually for small
farms. However, the net sale of swine productionslightly increased due to the increased cost of feed.
The main advantage of small size farms was
identified as labor cost savings because they arefamily-run.
The highest and lowest eco-efficiency values for
medium size farms were electricity and water
consumption respectively (Table 2). These findings
show that the swine production process, including
heating, ventilation and water pumping in mediumsized farms, requires significant electricity supply.
Additionally, the water consumption trend increased
annually due to the processes of swine drinking andtwice daily corral cleaning.
The highest and lowest eco-efficiency values forlarge-size farms were water and electricity
consumption respectively (Table 2). This finding is
consistent with the medium-size farms in the issueof water consumption. Vu et al [14] found that thevolume of water consumption was 40 liters/swine
for corral and floor cleaning, which was similarity
with the result of this study. However, the watersupply system and the reuse of treated wastewater
were applied in this farm size for reducing water

Table 1 Eco-efficiency indicator of swine productionin Thailand
Indicators
Economic indicator
Net sale
Environmental indicator
Feed consumption
Drug and vaccine
consumption
Electricity
consumption
Water consumption
Waste production
Greenhouse gas
emission

Unit
Baht/year
Ton/yearML/yearKwh./year
m3/yeaYon/year
Ton CO2-eq/year

Eco-efficiency Assessment
The eco-efficiency assessment of swine farm
production was modified from key concepts of the
World
Business
Councilfor
Sustainable
Development [8] and previous studies [13], with theratio between swine production value and total
environmental impact from the production process.
739

GEOMATE - Mie, Japan, Nov. 21-24, 2017

animal health management, swine farmers should
provide drug and vaccine doses based on
government regulations. Additionally, pathogen
contamination prevention techniques should be
implemented as standard. Feed and water
consumption management should provide for thedemands of swine based on the growing stage.
Swine feed can be prepared by farmers, reducing
cost. Moreover, feed storage buildings should be
separate, protecting from human, insect andpathogen contamination. To provide clean water for
drinking, water storage tanks and pipes with nozzles
are recommended to reduce water consumption.
Thirdly, farm management and attendance including
corrals, staff, and document management areproposed as part of the master approach to swine
production. The master approach to corralmanagement should be to provide clean, dry, orderly
housing, and should be cleaned and sterilize done to
two times daily. Regarding staff management, a
suitable ratio between personnel/swine is 1 person
per 200 swine, together with 1 veterinary specialist.
The documentation management of farms, including
administration, productivity management, andproduct and by-product volumes should be
developed for data backup and use. Lastly, soundenvironmental management of farms should be
included in the master plan of swine management.
All wastewater and feces produced should becollected and treated before environmental
discharge. Biogas production systems arerecommended as part of the waste management ofswine farms, as they produce environmentallyfriendly energy from waste by-products. The reuseof solid waste in swine farm should be implemented.

consumption. Additionally, biogas production
systems can be used to reduce electricity
consumption in large-size farms with the lowest ecoefficiency value in this study.
Benchmarking value of eco-efficiency for swine
production
The results of the eco-efficiency assessment offifteen swine farms were used to identify bestpractice performance by benchmarking. This data isshown in Table 4. Regarding feed consumption, thebest practice swine production with eco-efficiency
values of 58,159.70 baht/ton was farm K, as thetablet type of feed and feed limitation and control at
0.12 ton/head-year with twice daily feeding wasused. Regarding water consumption, farm C had thebest practice with eco-efficiency values of 14,679.94
baht/m3 and 1.17L/head-day water consumption, as
well water was pumped to a large storage tank forsupplying swine drinking water needs and oncedaily cleaning. Farm O had the best practice
regarding electricity consumption, with ecoefficiency values of 5,642.25 baht/kWh and1.72kWh/head-year. A biogas system using farm
wastewater provided all energy needed at a cost of
394 Baht/month. In the case of drug and vaccine
consumption, farm A had the best practice with ecoefficiency values of 2,208.77baht/ml and 8.38
ml/head-year. Concerning waste production, an
average eco-efficiency of 12,998.90 baht/ton and6.25 ton/head-year were found in Farm O, as biogas
production supported by the government was used totreat both wastewater and solid waste to cover theenergy consumption costs of this farm. Finally,
farm O also presented the best practice ingreenhouse gas emissions, with eco-efficiency
values of 9,260.22 baht/ton CO2-eq and 0.00875 ton
CO2-eq/head-year.
Master approach of swine production towardsustainable development
Using the results of swine production ecoefficiency benchmarking to identify best practices,
the master approach of swine production towardsustainable development was developed usingmaterial flow analysis, in-depth interviews andbrainstorming with the best practice farms withineach indicator. The master approach consisted of
two paradigms including a technique approach withprocess improvement and a management approachwith farm improvement. The details of the masterapproach of swine production toward sustainable
development are shown in Figure 3 and consist offour components. Firstly, breeding selection should
be based on rapid growing, disease-resistanceanimals. Secondly, the master approach of
husbandry management consists of animal health,and feed and water consumption management. For
740

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 2. Eco-efficiency value of swine production
Indicators
Feed consumption
Drug and vaccine
consumption
Electricity consumption
Water consumption
Waste production
Greenhouse gas emission

Unit
Ton/yearML/yearKwh./year
m3/yearYon/year
Ton CO-2eq/year

Large Farm
2011
2012
2013
26,148.99 22,270.51 23564.67

Eco-efficiency value
Middle farm
2011
2012
2013
12,868.14 14,060.16 16,802.43

2011
7,269.69

Small farm
2012
2013
8,716.32 11,759.55

992.493,243.52
327.12
11,390.58
5,323.36

999.33333.81
1,046.05
5,522.60
547.85

1,322.49
441.91
1,379.83
7,224.13
725.27460.15
196.542,468.17
2,559.34
322.57558.26238.962,985.72
3,105.30
329.19

J

K

L

M

N

O

Table 3. Benchmarking of eco-efficiency for swine production
Indicators
A
B
C
D
E
Feed
31147.90
2529.94
17973.95 2630.20 12011.69
consumption(Baht/ton)
Drugand vaccine
2208.77
233.671095.81
182,83332,71
consumption(Baht/ml)
Electricity
1208.7884.11
487.3087.77
337.48
consumption(Baht/kwh)
Water5594.65
729.1014679.94
605.947649.04
consumption(Baht/m3)
Waste production
11326.88
1090.28
6136.69
907.342300.12(Baht/ton)
Greenhouse gas
emission
1983.88138.05799.77144.04553.89Baht/tonCO2-eq)

824.062,724.78
272.649,559.36
4,471.99

1008.67
3,289.61
332.15
11,594.21
5,399.00

FG

3320.594038.113415.8111262.90

19595.18

58159.70

12254.52

22495.51

38930.39

9846.50713.06700.29888.171396.84727.58

1960.98

1071.90368.441499.962208.7729.24

147.72135.75582.84242.39526.53388.131781.87

1285.115642.255419.89

1511.32

1004.24

3513.56

5160.113851.03791.617495.14164.18232.052255.68

3783.69

1172.60

5433.886359.177429.586964.708340.947342.6512998.90

3675.28

2680.97220.80956.57397.82864.15637.002888.38

2109.169260.22741

1,098.99
367.551,150.09
6,045.79
603.23Swine farms
HI

773.48333.704,103.77
4,242.03
547.61GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 2. Master approach of swine production toward sustainable development742

GEOMATE - Mie, Japan, Nov. 21-24, 2017[4] Falguera, V, Aliguer N, Falguera M, “Anintegrated approach to current trends infood consumption: moving toward functionaland organic products?”, Food Control,
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CONCLUSION
The research objective was to examine thesustainable performance of swine farm productionin Thailand using joint eco-efficiency andbenchmarking technique. A suitable measure of
eco-efficiency values of swine production wasdeveloped and used to generate a questionnaire forcollecting data on the economic and environmental
performance of fifteen swine farms in Thailand.
Consequently,
eco-efficiency
valuesandbenchmarking were combined to identify bestpractices for a proposed master approach ofsustainable swine production. The results showed
an evident difference, as small and medium-size
farms were concerned with water consumption, andlarge farms were most concerned with heating andcleaning issues. Then, joint benchmarking and ecoefficiency values were used to ascertain the bestpractices in swine production. These results
identified that best practice attained 1.17 L/headday water consumption, 0.014kWh/head-day
electricity consumption,0.00875 ton CO2-eq/headyear greenhouse gas emission, and 6.25 ton/headyear waste production. Finally, best practice in
breeding selection, husbandry management, farmmanagement and attendance and the environmental
management of farms were identified by material
flow
analysis,in-depth
interviews
andbrainstorming, then included as part of the masterapproach to sustainable swine farm production.
ACKNOWLEDGEMENTS
This research was supported by The Thailand
Research Fund (contract reference number
RDG55520075).
REFERNCE[1] Rebolledo-Leiva R, Angulo-Meza L, Iriarte A,
Marcela C. “González-Araya MC, Joint
carbon footprint assessment and dataenvelopment analysis for the reduction ofgreenhouse gas emissions in agriculture
production” Sci Total Environ, Vol 593-594,
2017, pp. 36-46[2] The Office of Agricultural Economics,“Agricultural product data (Swine). [Online]”,Available:
http://www.oae.go.th/download/prcai/livestock/swine.pdf. Accessed April 17,2015 (in Thai), 2013.
[3] Nuengjamnong C, Rachdawong P.
“Performance analysis of the combined plugflow anaerobic digester (PFAD) and upflow
anaerobic sludge blanket (UASB) for treating
swine wastewater in Thailand”, Thai J Vet Med,
46(3), 2016, pp. 435-442.

743

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EVALUATION OF ATTENUATION OF ULTRASONIC DURING
PROPAGATION THE AIR TO MEASURE CONCRETE SURFACEROUGHNESS BY THE AERIAL ULTRASONIC SENSORNAGAOKA Seiya1, ISLAM Mohammad Raihanul2, OKAJIMA Kenji1, ISHIGURO Satoru1, ITO Ryoei1,
WATANABE Ken3 and ITO Tetsu421Graduate school of Bioresources, Mie University, JAPANDepartment of Farm Structure and Environmental Engineering, Bangladesh Agricultural
University, Bangladesh
3
Maruei concrete industry Co., Ltd., JAPAN4
X-ability Co., Ltd., JAPANABSTRACTJapan has possessed main concrete agriculture irrigation canals that are total length of about 50,000km. These
canals are becoming deterioration over time. Therefore concrete surface of canals have been becoming rough. One
method of the roughness measurement is using the aerial ultrasonic sensor. However previous research have been
not study about attenuation of ultrasonic during propagation the air using the 42 kHz sensor. The purpose of thisstudy were to evaluate attenuated value of the ultrasonic wave and to correct attenuated value of the ultrasonicwave. Reflected wave of the aerial ultrasonic was measured under the different condition of temperature, humidity
and atmospheric pressure with smooth board and roughness board. These were compared measurement value andcorrection value by ISO9613-1 equation. The relative error of correction value was smaller than measurement
value. The result of this study reveal that correction using ISO9613-1 equation for attenuation of ultrasonic wave
42 kHz is effective method.
Keywords: attenuation of aerial ultrasonic, ISO9613-1, concrete surface roughness, aerial ultrasonic sensor
following methods to measure the arithmetical meanroughness.
Sand patch test: This method is one of the mostcommonly methods used for examination ofmacrotexture depth of concrete surfaces. This direct
volumetric method consists in careful application ofa given volume of granular materials (a glass spheresor sand) of given granulometry onto surface andsubsequent measurement of the total area covered.
The sand patch test is exposed to a greater probabilityof human error; it is a test that cannot be performed
quickly without comprising accuracy [1], [2].
Concrete Surface Profiles: This method is basedon the visual inspection of the prepared surface, being
this compared with nine standard Concrete Surface
Profiles (CSP) of increasing roughness [3].
Outflow Meter: This is a volumetric method used
to assess the surface roughness of asphalt andconcrete road pavements. The method gives anaverage value for the surface roughness but no otheradditional information [1], [4].
Moulage gauge Method: This method is possible
to measure the arithmetical mean roughness. This is
the simple measurement method, since managers’
only pushes the moulage gauge to the concretesurface. However, managers need complication
analysis that read displacement from one by one themoulage gauge [5], [6].

INTRODUCTION
Japan has possessed many concrete irrigation
canals mainly used for agriculture that have a total
length of 49,239 km. Including lateral canals areabout 400,000 km. These canals were constructedsince the high economy era of 1954 - 1973 andbecame too old for work. Reconstruction of canals
costs too huge. The government are necessary to be
repaired old canals, on other word, they were
promoting policy “stock management” in japan.
Stock management mean to improve the life of the
facility by appropriate inspection.
The concrete surface of canal is worn out by flowwater and flow-sand, and become rough. The
roughness of concrete surface causes decline of thewater flow function. If canals become decline of thewater flow function, causes decreasing the flow
velocity and raising the water level. As a result,irrigation water will not reach the end of some lateralcanals. However, method of measurement roughness
concrete surface of irrigation canals has not been
established yet. Roughness of concrete surface isgenerally by arithmetical mean roughness (ISO25178).
Over the years, considerable attention has been
paid to the study of measurement of the arithmeticalmean roughness. Scientists are proposed the744

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Laser Displacement Sensor Method: This method
is possible to measure the arithmetical meanroughness. Measurement range of this method is line
information of the concrete surface. This method ishigh precision, but high price to measure irrigation
canal [7], [8].
Aerial ultrasonic sensor: This method is possible
to measure the arithmetical mean roughness. This wasdeveloped by the authors. The frequency was used 42
kHz. Measurement range from 1000 mm can measure
diameter 600 mm and from 550 mm can measure
diameter 300 mm. This sensor uses to be bought
about 25 $, therefor this is economical to measure
canals [10].
Method of the aerial ultrasonic sensor is
economical, wide range and simple. However, theamount of the aerial ultrasonic wave during
propagation an air is declined by wind velocity over
6 m/s. In the similar, the authors considered that theaerial ultrasonic wave during propagation an air iscaused attenuation under different atmospherecondition. The theory of this phenomenon is definedby ISO9613-1 [11]. However, the applicable range ofthe frequency is defined 50 Hz to 10 kHz. Therefore,
the authors have been used sensor 42 kHz is overrange in ISO9613-1. Further there is no study focus
on reflected wave. The attenuation of the aerial
ultrasonic is problem to measure roughness ofconcrete surface. It is reason that the measurement
value change under different condition. The purposeof this study were to evaluate attenuated value of theultrasonic wave and to correct attenuated value of theultrasonic wave.

Table 1 Specification of the aerial ultrasonic sensor

MATERIALS AND METHOD

Thermometer and Hygrometer

Aerial Ultrasonic Sensor

The TR-73U and TR-72wf-H (T&D Corporation,Inc) was used as the thermometer and hygrometer.
Measuring range of the thermometer is -30 to 80°C,
and the hygrometer is 0 to 99 humid. These sensors
can record internally and send it to PC with USB
connection.

Frequency
dimension

42
16.4
15.5
19.9
22.1
4.3

A
B
C
D

weight

D

B
A

kHz
mm
mm
mm
mm
grams

C

Fig. 1 The aerial ultrasonic sensor

Fig. 2 The horn attached and this size

The LZ-Maxsonar-EZ1 (MaxBotic, Inc) was usedas the aerial ultrasonic sensor. The sensor is designed
the ultrasonic range finder. Frequency was selected
42 kHz. Sensitivity of the open type (the sensitivity:min. -80.5dB) and the waterproof type (thesensitivity: min. -58.2dB) were compared. The open
type has 13 times higher sensitivity than thewaterproof type at each output voltage. So, the open
type was selected. But measurement of the aerial
ultrasonic wave must limit not to get wet. Other
specification shows Table 1. The aerial ultrasonicsensor was attached the horn. The horn was attached
due to increase the sound of the aerial ultrasonic. It
was made of resin and was made by 3D printer. The
Fig.2 shows an example with the horn attached sensor.
Measurement value was acquired by the digital
oscilloscope TBS1152 (Tektronix, Inc).

Fig. 3 TR-72wf-H
745

GEOMATE - Mie, Japan, Nov. 21-24, 2017or heat dissipation, and molecular relaxation due tooxygen, nitrogen, and water vapor vibrational,
rotational, and translational energy. The attenuationof sound varies significantly with temperature, water
vapor content and frequency. The range of thestandard specifies is as follows.
－Frequency from 50 Hz to 10 kHz－Temperature from -20°C to +50°C－Relative humidity from 10% to 100%－pressure of 101,325 kPa (one atmosphere)
Equation are provided for wider ranges suitablefor particular, however frequency 42 kHz of using theaerial ultrasonic is over range.

Concrete Board
The concrete board was made for this experimentby the cooperation of the Maruei concrete industry
Co., Ltd. The size of this board is length 700 mm,
width 700 mm, height 50 mm. The weight of thisboard is 45 kg. We prepared two types of roughness.
First type of arithmetical mean roughness was 0.04
mm. The condition of concrete surface is smooth. In
this study, first type was called smooth board. Second
type of arithmetical mean roughness was 1.04 mm.
The condition of concrete surface is roughness. In thisstudy, second type was called roughness board.
Experiment Method

Symbols

Measuring materials was set as Fig.4. The aerial
ultrasonic sensor was set 1000 mm height fromconcrete board. The hygrothermograph was set 0 mm
and 500 mm height from concrete board. The
ultrasonic data was acquired under different conditionof temperature and humidity. We got measurement
value of reflected wave, temperature, humidity andair pressure. The measurement value was voltage
mV of peak to peak of reflected wave. The
roughness of concrete was estimated by themeasurement value of reflected wave. Preceding
study (2016) showed between the measurement value
and roughness of concrete [10].

: Frequency of the sound, in hertz: Molar concentration of water vapour, as apercent: Reference ambient atmospheric pressure, inkilopascals: Initial sound pressure amplitude, in pascals: Sound pressure amplitude, in pascals: Ambient atmospheric pressure, in kilopascals: Distance, in metres, through which the soundpropagation: Ambient atmospheric temperature, in kelvins: Reference air temperature, in kelvins: Pure tone sound attenuation coefficient, in
decibels per metre, for atmospheric absorption
Calculation
The equation (1) is basic equation of attenuation.
is exponentially attenuated
The sound pressure
from the sound pressure by absorption in the air.
.

(1)

The attenuation of pressure levelis describedusing coefficient and distance of propagation in the
air.
(2)

Fig.4 Experiment system
THE ATTENUATION OF ULTRASONICDURING PROPAGATION THE AIR

.

.

/

The Attenuation of sound during propagation the
air has been to be standardized by ISO 9613-1 at 1993.
This standard aims noise problems about urban
environmental noise and airplane noise. This standard
specifies an analytical method of calculating theattenuation of sound as a result of atmosphericabsorption for a variety of meteorological conditions
when the sound from any source propagates throughthe atmosphere the air. Absorption of sound throughthe air is due to shear viscosity, thermal conductivity

.

.
.

.

(3)
/

746

)

/

(4)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

temperature of atmosphere was under 20°C,
attenuation tended to be small. When temperature of
atmosphere was over 20°C, attenuation tended to belarge. The Fig.6 and Fig.7 shows that when thetemperature was over 20°C, the humidity was under
60%. The Fig.5 shows that when the humidity is low,
the attenuation coefficient tend to increase as thetemperature increase. There is no research thatthe phenomenon changes with boundary of 20°C.
It is considered to be the relationship between
humidity, atmospheric pressure and features of sensor.
The slope of approximation with smooth board islarger than roughness board. It was because themeasurement value of smooth board was large thanthe measurement value of roughness board.
The attenuation rate of change was investigated todue to difference in roughness of concrete. The
reference temperature was set to 20° C, and the rateof change was calculated by equation (9). The Fig.10
shows the rate of change was similar between smoothboard and roughness board. So the degree of theroughness is not related to the amount of theattenuation of the aerial ultrasonic.

(5)

.

.

(6)

The is molar concentration of water vapor inpercent. The
is calculated from the relative
humidity as follows.
%

(7)
.

.

.

(8)

Humidity 0%

1.8

30%
60%

1.6

90%

1.4

30

Temperature °C

1
0.8
0.6
0.4

20
Temperature°C

Fig.5 Relation between

30

40

0

20

70
60

15

50
40

10

0

90
80

Humidity

30
20

5

0.2
10

Tempreture

25

1.2

0

100

10
0

10

20

30

40

50

60

70

0

Data No.

and temperature

Fig. 6 Atmosphere condition with smooth board

RESULTS AND DISCUSSION

30

Measurement Result of Attenuated Ultrasonic
Wave

100
Tempreture25
Temperature °C

The Fig.6 and Fig.7 shows 71 data under different
atmosphere condition. Since the aerial ultrasonicsensor can’t measure with rainy weather, the data
were acquired mainly with fine weather.
The measurement value was acquired using theaerial ultrasonic with smooth board and roughness
board. The measurement value was the peak to peakof reflected wave and was calculated 15 times
average. Since the measurement value depended on
the temperature, the temperature was taken on thehorizontal axis.
The Fig.8 and Fig.9 show that the measurement
value was fluctuated by attenuation. When

80
Humidity

20

70
60

15

50
40

10

30
20

5
0

90

Humidity %.

.

Humidity %The attenuation is the function of the relaxation
frequency of molecular oxygen
and therelaxation frequency of molecular nitrogen
.

10
0

10

20

30

40

50

60

70

0

Data No.

Fig. 7 Atmosphere condition with roughness board
747

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Measurement voltage mV

3500
3100

become approach initial voltage. Fig.11 and Fig.12
shows that the slope of approximation with thecorrection value become small. This phenomenon
was also similar with the roughness board. The
relative error was calculated. The theoretical value
was taken as the average of all. Table 2 shows that therelative error of the correction value was less than halfof the measurement value. This result shows that
correction data did not depend on atmospherecondition. However, when it was temperature over
25°C, the correction value tended to become small.

y = -21.871x + 2657.1
R² = 0.6703

2700
2300
1900
1500

Smooth
0

5

10

15

20

25

30

(10)

Temperature °C: Masurement value mV,

Fig. 8 Measurement data using the aerial ultrasonicwith smooth board

3500

y = -12.395x + 1210.8
R² = 0.654

correction voltage mV

Measurement voltage mV

2000
1600
1200

800
Roghness

400
0

0

5

10

15

20

25

2700
2300

2000

: Average voltage mV at

1600
correction voltage mV(9)r: Rate of change

1.1
1
0.9
0.8

0.5

0

5

Roghness

10
15
20
Temperature °C

10

15

20

25

30

y = -4.6177x + 1380.6
R² = 0.1545

1200
800
Roghness

4000Smooth5

Fig. 11 Correction data by equation ISO9613-1 withsmooth board

1.2

0.6

0

Temperature °C

Fig. 9 Measurement data using the aerial ultrasonicwith roughness board

0.7

Smooth

1900
1500

30

y = -4.6057x + 3041.1
R² = 0.0857

3100

Temperature °C: Rate of change,
temperature 20±0.5°C: Correction value mV

0

5

10

15

20

25

30

Temperature °C
25

Fig. 12 Correction data by equation ISO9613-1 withroughness board

30

Fig. 10 Relation between rate of change andtemperature with smooth board and roughness board

Table 2 Compere correction value and measurement
value with relative error

Correction Result of Attenuated Ultrasonic Wave
The Attenuated ultrasonic wave was corrected by
ISO9613-1 equation (10). The correction voltage
748

Correction value

Measurement value

Average of all mV

2970

2319

Relative error %

2.7

6.4

GEOMATE - Mie, Japan, Nov. 21-24, 2017[4] Mokarem D, Use of the digital surface
roughness meter in Virginia, Research Report
VTRC 07-R4, Virginia Transportation ResearchCouncil, 2006.
[5] Kitamura K, Honma S and Kato T, Quantitative
Evaluation for Forecast of Irrigation Canal
Abrasion, J of Water, Land and Environmental
Engineering , Vol 76, No. 9, 2008, pp. 823-828.
[6] Kawakami A, Asano I, Mori M, Kawabe S andTokashiki M, Abrasion measurement method
Using a Profile Gauge, journal of irrigation,
drainage and rural engineering, No.1, Vol.85,
2017, pp. 77-84.
[7] Nakaya T, Tokashiki M, Mori M and Mori T,
Estimation of the Coefficient of Roughness
from Surface Characteristics of Abraded
Concrete Channel, journal of irrigation,
drainage and rural engineering, No. 258, 2008,
pp. 501-506.
[8] Uchida K, Ishida M and Ogawa S, Estimation of
the Coefficient of Roughness for Irrigation
Canals by Transcription Method for Concrete
Surface, presented at JSIDRE, 2008, pp. 432433.
[9] Tokashiki M, Studies on Erosion Mechanism
and Accelerated Erosion Test of Concrete
Irrigation Canal, Bull. Natl. Inst. Rural Eng.
Japan, Vol. 52, 2013, pp. 1-57.
[10] Okajima K, Nagaoka S, Ishiguro S, Ito Ryoei,
Watanabe K and Ito Tetsu, Measurement of theRoghness of the Concrete Surface by the Peak
to Peak Value of the Aerial Ultrasonic Wave, Jof Water, Land and Environmental Engineering,Vol. 84, No. 3, 2016, pp. 233-240.
[11] ISO9613-1, Acoustics of sound during
propagation outdoors-Part 1 : Calculation of theabsorption of sound by the atmosphere, 1993.
[12] Yhoshihisa K, Calculation of the Absorption ofSound by the Atomosphere (ISO9613-1), The
Institute of Noise Control Engineering of Japan,
Vol. 21, No. 3, 1997, pp. 130-135.

CONCLUSION
The measurement value was measured using theaerial ultrasonic sensor with 71 data under different
atmosphere condition. The measurement value wasfluctuated by attenuation. The measurement value
depended on the temperature. The attenuation
increased at boundary of 20°C. The degree of theroughness is not related to the amount of theattenuation of the aerial ultrasonic.
The measurement value was corrected using
ISO9613-1 equation. The slope of approximation
with the correction value was smaller than themeasurement value. The relative error of thecorrection value was less than half of themeasurement value.
The result of this study reveal that correction using
ISO9613-1 equation for attenuation of ultrasonicwave 42 kHz is effective method.
ACKNOWLEDGEMENTS
This study is funded by the Ministry of Agriculture,
Forestry and Fisheries, japan.
REFERENCES[1] ASTM E 2380, Standard test method formeasuring pavement texture drainage using an
outflow meter, West Conshohocken (PA)ASTM International, 2005.
[2] Courard L, Garbacz A, Bissonnette B,
Topography evaluation methods for concrete
substrates: parametric study, International
Congress on Concrete Repair, Rehabilitation
and Retrofitting, 2012.
[3] Pedro M.D. Santos a, Eduardo N.B.S. Júlio, “A
state-of-the-art
reviewonroughnessquantification methods for concrete surfaces”,
Construction and Building Materials, 2013, 38 ,pp. 912–923.

749

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A STUDY OF PUBLIC OPINION ON GREEN SPACES USING DATAFROM FREE-TEXT DESCRIPTIVE RESPONSES- A CASE STUDY OF REGIONAL CITY IN JAPAN 1

Shinya Tsukada1 and Tetsuo Morita2
Maebashi City Office, Japan, 2Maebashi Institute of Technology, Japan;
ABSTRACTThe present study analyzed public opinion data from free-text descriptive responses obtained by administering
a questionnaire on green spaces to local residents. Maebashi City, the capital city of Gunma Prefecture, wasselected as the subject for the study. Maebashi is a standard-sized city in Japan, thus the opinions of its residents
can be analyzed and compared to other standard-sized cities. The present study adopted a text mining method foranalysis. Text mining can discover the characteristics of words and examine the relationships between words in alarge amount of text data objectively and quickly. By exploring the residents’ thoughts on green spaces using thedata from their free-text descriptive responses, the present study extracted problems with existing green spaces
from the viewpoint of the public.
Keywords: Text data, Text mining, Tract, Imageand the private sector, including a wide range ofentities such as local councils to support flexible
urban park management.

INTRODUCTION
BackgroundAt present, depopulation, low birthrates, aging
citizens, and decreased financial resources are serious
social problems in Japan, and the appropriate
development, maintenance, and management ofurban facilities are urgently required. To deal withthese social problems and related requirements, newpolicies on green and open spaces contain strategies
to enhance the stock effects of nature spaces, toaccelerate the cooperation between the government
and private sectors, and to make further use of urban
parks.

SUTUDY AREA AND STUDY METHODS
Position of this study
Maebashi City, which is a study area, is shown in
Fig. 1. Maebashi City is the prefectural capital of
Gunma Prefecture, with a population of 340,000
people and a local city located about 100 km from
Tokyo. In Maebashi City, motorization is progressing
even among local cities, and Maebashi City is
studying toward realization of compact city.
Maebashi is a standard-sized city in Japan, thus
the opinions of its residents can be analyzed andcompared to other standard-sized cities.

Social situation
To this end, the Ministry of Land, Infrastructure,
Transport and Tourism published an interim
summary of the “Review Meeting for the Nature of
Urban Parks Corresponding to Urban Management ofa New Era.” This summary contains three main points.
First, in this new era, green and open spaces that
help support cities, including urban parks and private
gathering places, must be strategically secured andused.
Second, the multifunctional properties of urban
parks must be advertised and exhibited using
cooperation between the government and private
sectors in order to draw on the power of individual
towns and citizens.
Finally, a new framework must be constructed inwhich the quality of urban parks can be improved
through this collaboration between the government

Gunma Prefecture

Maebashi City

Fig. 1750

Location of Maebashi CityGEOMATE - Mie, Japan, Nov. 21-24, 2017

Kobayashi, Terada and Sato [4] analyze residence
selection behavior based on resident preference ofresidential attribute in for Saiki City, Ooita Prefecture.
Kobayashi applied the text mining method to free-text
descriptive responses obtained via a questionnaire to
analyze the problems peculiar to a local community.

Table 1 Details regarding the questionnaire survey

Date of survey- Distribution:
October 14-16,2015- Collection:
October 31,2015

Data collection

Maebashi city area
Gunma Prefecture

Data collection
method- Distribution:
putting mail box- Collection:
Mailing

Question

Please enter your thoughts
about the green spaces
surrounding you, and youropinions and desires regarding
Maebashi City’s future
policies on green spaces,parks, and street trees.
in Maebashi-area(free answer)

Distribution
and collection- Number of questionnaire
cards distributed: 1,500- Number of questionnaire
cards collected: 402- Recovery: 26.8%

Purpose and method of this study
The present study analyzed public opinion datafrom free-text descriptive responses obtained byadministering a questionnaire on green spaces to local
residents, and evaluate the quality of life.
The present study adopted a text mining method
for analysis. Text mining can discover thecharacteristics of words and examine therelationships between words in a large amount of text
data objectively and quickly.
By exploring the residents’ thoughts on green
spaces using the data from their free-text descriptive
responses, the present study extracted problems withexisting green spaces from the viewpoint of the public.
Comparing the problems identified by the study withthose recognized by an administrative organization
allowed the present study to better examine future
policies regarding green spaces.
KH Coder software
The present study used KH Coder software, thetechnical information of which has been publishedand which has been used for several existing papers.
A morphological analysis function has been
incorporated into this software.
Morphological analysis is an operation to divide astatement or a sentence into minimal units that have asyntactic function, and to discriminate each part ofspeech. This is used instead of artificial dataprocessing to analyze data objectively.
In the present study, we conducted a questionnaire
survey on the Table 1. The present study analyzed
free-text descriptive answers to the question, “Please
enter your thoughts about the green spaces
surrounding you, and your opinions and desires
regarding Maebashi City’s future policies on green
spaces, parks, and street trees”.
The responses were encoded as text data and thenanalyzed in order to understand the image that theresidents have of green spaces, and evaluate thequality of life.
The initial questionnaire on green spaces wasadministered by the Maebashi Institute ofTechnology on October 16, 2015, in which 1,500
questionnaires were randomly distributed tohouseholds in Maebashi City. 402 completed surveys
were collected by mail. The present study analyzed
181 samples, in which the free-text descriptive
responses were examined as text data.

Overview of the study
We will review the existing studies related to thisstudy. There are many studies on the quality of life
given by green. Morita, Kogure, Sugita, Baba,
Tsukada and Miyazato [1] focus on the environmentof the water and green for Maebashi City, andevaluate the quality of life. In addition, Tsukada,Morita and Yuzawa [2] analyzed the Relationshipbetween consciousness and environment including
water and green of the Tenguiwa-Irrigation in
Maebashi City.
There are also many that analyzed free text data
as a similar study. Text data must be processed using
a particular method so that the data can be analyzed
objectively and quantitatively. The field of natural
language processing has developed specific software
for text mining. As the text mining method canobjectively extract important trends in words fromstatements and free-text descriptive responses, thismethod has been used in previous studies.
Sasaki, Maruishi [3] studied about Traffic Policy
towards the introduction for Fuji-yoshida City,
Yamanashi Prefecture. Sasaki attempted to visually
analyze public opinions using statements made inworkshops transformed into text data.
751

GEOMATE - Mie, Japan, Nov. 21-24, 2017

RESULTS AND DISCUSSION

Table 2 Result of extracted words

Result of extracted words

No
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50

The present study examined free-text descriptive
responses regarding green spaces, obtained fromresidents via questionnaire and analyzed as text data.
The researcher performed morphological analysis
on the data and created a list of top 50 words withhigher frequencies of appearance (Table 2).
Of the nouns and adjectives extracted from these
responses, “park” (first place, Fig.2), “suppose”(second place), “greenery” (third place), “roadsidetree” (fourth place, Fig.3), “ management” (fifth
place), “environment” (sixth place), “Maebashi”(seventh place), “ many” (eighth place), “ tree”(ninth place) and “construction” (tenth place), allsymbols of greenery in cities, were the most common.

Fig. 2

Small scale-park, Maebashi-city

Fig. 3

Roadside-tree, Maebashi-city

752

Extracted Ward

Frequency

Park
SupposeGreenery
Roadside tree
Management
Environment
Maebashi
Many
Tree
Construction
Road
Maintenance
Good
Near
Place
Necessary
Rose
Child
PeoplePlant
Cleaning
Resident
NatureTree and shrubs
Can
Urban
Feel
Cut
Think
Few
Increase
District
Flower
Do
Go
Walk
City
CitizenLive
Very
AbsentGreening
Beautiful
Advanced age
Surroundings
Housing
Grass
Money
Refuse
Bad

102
80
68
43
35
30
28
26
26
24
24
21
21
19
19
18
17
17
17
16
15
15
14
14
14
13
13
13
12
12
12
12
11
11
10
10
10
9
9
9
9
9
8
8
8
8
8
7
7
7

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 4Co-occurrence network

created.
First, the group “concerning the use of green
spaces” was strongly connected with the words“walk,” “near,” “child,” and “play,” centering on“park.” The trends of these words revealed that thesituation of using a park, such as “I can walk in a
nearby park,” and the desire for a park, such as “there
is no place for my child to play in a nearby park,”
were related.
Next, the group “concerning the maintenance andmanagement of green spaces” was strongly connectedwith the words “management,” “maintenance,”“cleaning,” “resident,” and “cost,” centering on“greenery.” By studying the tendencies of theseconnections, the desire for maintenance andmanagement of greenery was extracted as, “resident
participation and costs are required to maintain andmanage abundant greenery in Maebashi City.”

Result of Co-occurrence network
It was revealed that the residents were moreinterested in having parks and street trees installed
and managed by the public sector rather than ingreenery kept on private land. Since “environment,”“Maebashi,” and “many” were extracted in sixth,
seventh, and eighth place, respectively, the residents
were revealed to feel that the environment ofMaebashi City is rich in greenery.
To understand the residents’ opinions on green
spaces in detail, a co-occurrence network diagram
was created using KH Coder, which visually
expressed the correlations between words thatappeared in the responses.
From this diagram, the rough groups “concerning
the use of green spaces” and “concerning themaintenance and management of green spaces” were753

GEOMATE - Mie, Japan, Nov. 21-24, 2017

quality of life and renovation of parks for the citizen.
As mentioned above, the present study will be able toreflect public opinions on the development of parks.
By exploring the residents’ thoughts on green
spaces using the data from their free-text descriptive
responses, the present study extracted problems withexisting green spaces from the viewpoint of the
public.

CONCLUSION
The results obtained in the present study can besummarized as follows:(1) The present study administered a questionnaire on
greenery in Maebashi City, used free-text
descriptive responses obtained in the survey astext data, applied the text mining method to thetext data, and perform morphological analysis of
the residents’ opinions on green spaces expressedby word choices in the responses.
(2) When the residents’ opinions on green werevisually analyzed using a co-occurrence network
diagram, the groups “concerning the use of green
spaces” and “concerning the maintenance andmanagement of green spaces” were extracted.
Subsequently, opinions such as “there is no place
for my child to play in a nearby park” and“resident participation and costs are required tomaintain and manage abundant greenery in
Maebashi City” were extracted.
(3) These opinions of the residents were related topolitical
issues,whichadministrative
organizations have attempted to address
themselves. Words related to the development of
dog runs and the management of greenery bycommunity residents appeared in the minority of
responses.
The whole parks in Maebashi City is obsolete andneeds renovation. Meanwhile, due to the population
decrease and aging, the financial situation of
Maebashi City will be severe.
Thus, I think that highly efficient collection isnecessary. I think that it will be a new tool to support

REFERENCES[1] Tetsuo Morita, Yoshihito Kogure, Hiroshi Sugita,
Tsuyoshi Baba, Shinya Tsukada and Naoki
Miyazato, “A Study on Evaluation of Quality ofLife in Consideration of Water/Green
Environment”,
International
Journalof
GEOMATE, Vol. 2, No. 2, 2012, pp. 241-246.
[2] Shinya Tsukada, Tetsuo Morita and Akira
YUZAWA, “STUDY ON ASSESSING THE
VALUE OF THE TENGUIWA IRRIGATIONCANAL, International Journal of GEOMATE,
Vol. 10, Issue 22, 2016, pp. 2007-2010.
[3] Kuniaki
Sasaki,
KouichiMaruishi“Summarization
andVisualization
characteristics of a Workshop Discussion using
Text Mining Method”, Journal of Japan City
Planning Review, 43(6), 20011, pp. 1039-1044.
[4] Yuji Kobayashi, Akinobu Terada and Seiji Sato,“ANALYSIS OF FREE ANSWER INQUESTIONNAIRESURVEYANDEVALUATION OF LIVING ENVIRONMENTBY TEXT MINING”, Architectural Institute ofJapan, Vol, 77(671), pp.85-93, 2012.

754

Seventh International
Conference
on Geotechnique,
Construction Materials and
GEOMATE- Mie, Japan,
Nov. 21-24,
2017
Environment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

IMPACT OF AGRICULTURAL WATER ALLOCATIONON THE ECOSYSTEMS IN THE INNER NIGER RIVER DELTA*Barry Kassambara1, Homayoon Ganji1 and Takamitsu Kajisa1
1

Graduate school of Bioresources, Mie University, Japan

ABSTRACTThe Sahel, a transition zone between the humid tropics and the great desert of northern Africa, faces
major challenges regarding the survival of its human population and the preservation of its ecosystems. The
Niger River, whose source is in Guinea and which crosses much of the Sahel, is a lifeline for humans andbiodiversity. Over the past three decades because of climate change and population increase, the inhabitantsof the Sahel are witnessing a significant reduction in resources, particularly in the Inner Niger Delta. The
main water intake from this river in Mali is the Markala dam, which is located upstream of the Inner Niger
Delta. This dam irrigates 118,000 ha of paddy fields and 16,276 ha of sugar cane fields. During the dry
season (December - May) some of the paddy fields are used for double cropping (paddy, vegetable etc.). In
the recent years, because of the government’s policy of developing irrigated agriculture particularly on theland of Office du Niger, a sustained rate of expansion has been seen with an average of 5,000 ha of new land
irrigated for agriculture each year. This expansion of agriculture, poor management of water resources, andreduction of the river’s hydrologic regime downstream are limiting factors in achieving food self-sufficiency
and conservation of the wetland ecosystem in the Inner Niger Delta. The delta covers an area of 41,800 km²
with a total catchment area of 130,000 km². In 1987, this Delta was selected as a Ramsar Site because of its
wealth of waterfowl.
Key words: Office du Niger, Niger River, Inner Delta, Water Allocation, Irrigation, Ecosystems

INTRODUCTION
The republic of Mali is a landlocked country in West
Africa. It is the eighth-largest country in Africa, withan area of 1,241,190 km² and a population of
approximately 16.8 million (2013). According to the
UNDP 1 report (2015) 50.6% of the population lives
below the income poverty line ($1.25/day) and 10.8%
are near multidimensional poverty [1]. With 80% of
its population engaged in agricultural activities, this
sector is the cornerstone of Mali’s economy andshows great potential to drive economic growth. Over
31% of the population is exposed to food insecurity[2] and only 7% of 43.7 million hectares arable land iscurrently cultivated. Potential irrigable lands that are
currently developed correspond to 2.2 million hectares
or 14% of the total [3].
The landlocked territory of Mali is very close to the
Tropic of Cancer and as result, it has a tropical climate.
Mali has distinct periods of summer and winter withthree main seasons. Average temperatures range
between 24 and 32°C. During the last 50 years, theaverage temperatures have increased significantly.
The annual rainfall is approximately 1400 mm in thesouth, 1120 mm at Bamako, and 127 mm in thenorthern part of the country. Central Mali (where
1 United Nations Development Program

Office du Niger and Inner Delta are located) receives
most of its rainfall between June and August.
Around half of Africa’s total wetland area comprises
floodplains. These include famous large-scale
examples that cover several thousand square
kilometers such as the Inner Niger Delta in Mali, theOkavango Delta in Botswana, the Sudd of the Upper
Nile in Sudan and the Kafue Flats in Zambia [4].
Beyond the town of Ségou, the Niger River forms avast inland delta (41,800 km²). It joins with its main
tributary the Bani at Mopti then forms several lakes.
The watershed area of this Inner Delta covers 130,000
km².
The vast majority of the Inner Niger Delta
ecosystems are in a state of continuous degradation
due to climate change and anthropogenic activities.
The rapid expansion of irrigation upstream in the areaof Office du Niger (mainly due to paddy and sugar
cane production) has had a significant impact on theavailability of water resources in the Niger River andassociated delta.
To address this problem, this investigation analyzes
the historical variation of the Niger River hydrology
and the evolution of irrigation areas and crop patternsin Office du Niger. As a result of this analysis, it ishoped that a solution to save water resources and to755

GEOMATE - Mie, Japan, Nov. 21-24, 2017

overcome the reduction in the floodplain of Inner
Niger Delta can be proposed.

ANALYSIS
Climate conditions
The 1960s coincided with a period of increased
rainfall. However, during 1970s and 1980s a large
rainfall deficit was recorded and this corresponded toa great drought in the Sahel countries. Sahel rainfall
has been linked to Atlantic as well as Mediterranean
SSTs via evaporation rate and supply of moisture(Giannini et al., 2003; Rowell, 2003). Recently, thevariability of rainfall in the Inner Niger Delta has
improved, although the level remains below theaverage of 646 mm/year with a minimum of 390 mm
recorded in 1980 and a maximum of 957 mm recorded
in 1999 (Figure 1).

40%

Rainfall anomaly (%)

20%

Fig.2 : Reference Evapotranspiration at Mopti
Station (Inner Niger River Delta) during 2015 (Source
FAO CLIMWAT).
The Niger River and its hydrological potential in
Mali
The Niger is the main river in western Africa. It
extends approximately 4,185 km (2,600 mi) with1,700 km (1,060 mi) in Mali (Figure 3). The source islocated in the southeastern part of the Guinea
Republic and the total catchment area of the Niger
River is 2,117,700 km² (817,600 mi²).
In the 1960s, the independent countries of the Niger
River Basin decided to coordinate their efforts to
exploit natural resources with a priority on water. The
Commission of the Niger River was renamed the
Niger Basin Authority (NBA) on 21 November 1980.
The member countries are: Benin, Burkina Faso,
Cameroon, Côte d’Ivoire, Republic of Guinea, Mali,
Niger, Nigeria and Chad.

0%
-20%
-40%
-60%
-80%

Fig.1 Rainfall and rainfall anomaly shown in relation
to average rainfall from 1961 to 2014 (data from
Mopti Meteo Station).
The daily ET0 (Reference Evapotranspiration) in the
Inner Delta is very high particularly during the dry
season (March to May). The annual ETP ranges from4.72 mm/day in August to 8.63 mm/day in April(Figure 2).

Fig.3 Niger River in Mali
Dams, reservoirs and other water users
The Upper Niger has four dams (Sélingué, Sotuba
weir, Markala and Talo) and four dams that are underconstruction or in the project (Fomi in Republic of
Guinée, Kandadji in Republic of Niger, Taoussa andDjenné in Mali).

The Sélingué dam on the Sankarani River has beenused for hydropower since 1982. It has a total volumeof 2.17 km3, an effective volume of 1.9287 km3 and a
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

design flood discharge of 3600 m3/s. The Sotuba weir,
which has been in operation since 1929, is anothervery small hydropower plant located directly
downstream from Bamako. Because of the limited
storage volume of the Sotuba weir, this reservoir does
not have a significant hydrological impact on the
Niger River flow. The Markala dam which opened in1947 is a diversion dam just downstream of Ségou
with a storage volume of 0.17 km3. This dam is used
to irrigate the surrounding area of the Office du Niger.
There are two diversion dams on the Bani (tributary of
the Niger River), namely Talo which was constructed
in 2007 with a storage volume of 0.18 km3 and Djenné,
which is under construction.
Data is available for five gauging stations fromupstream to downstream of the Inner Delta (Koulikoro,
Ke-Macina, Mopti, Akka and Diré) for the period
1960 to 2015. Variation in water flow allows anevaluation of water used and lost between different
points (as shown in Figure 4).

Fig.4 Water flow rate from Koulikoro to the Inner
Niger Delta.
From 1960 to 1982 the data recorded by the stations
represents the natural flow of the Niger River before
the construction and operation of the Sélingué dam in1982 (Figure 5). This dam is located approximately
200 km upstream of Koulikoro on the Sankarani River,a tributary of the Niger River. It has a catchment areaof 33,460 km2. The Sankarani River contributes
significantly to water supplies during dry periods. Thisis accomplished through the Sélingué, which regulates
the flow of the Niger River provides water to the
Office du Niger and other irrigated schemes
downstream.

(Q: flow)

Fig.5 Hydraulicity of the Niger River before and after
construction of the Sélingué dam
Agricultural land of Office du Niger
The Government of Mali has adopted several
irrigation policies and strategies, in which thedevelopment of the Office du Niger land is a priority[5]. At the Second Ordinary Assembly of the African
Union (AU) in July 2003 in Maputo, African Heads ofState and Government endorsed the “Maputo
Declaration on Agriculture and Food Security in
Africa” (Assembly/AU/Decl. 7(II)). The Declaration
contained several important decisions regarding
agriculture, but the most important among these was
the “commitment to the allocation of at least 10% ofnational budgetary resources to agriculture and ruraldevelopment policy implementation within five years[6]. Moreover, the ministers’ council of 3thAugust
2015 of the Malian government decided to allocate
15% of the budget to the rural sector [7].
The irrigation area of Office du Niger is located at
the death Delta “delta mort” an ancient branch of the
Niger River in the westerly region of the Inner Niger
Delta “delta vif”. This irrigation zone covers a grossarea of 2,458,506 ha with an irrigable area of
1,947,406 ha. Of this total, 1,445,000 ha is fed bygravity from the Markala dam, and by 2015 only
138,000 ha was developed.
Historically, the regime of paddy field constructionin Office du Niger has changed significantly as
dictated by the political situation (that is, a change
from colonial rule to the present government) (Figure6). In 1979, because of a high degree of degradation of
paddy fields, the Malian government and its technicaland financial partners decided to focus efforts on oldland improvement. From 1979 till the present, 48,600
ha of paddy fields have been improved. This land
improvement has allowed a reduction in water757

GEOMATE - Mie, Japan, Nov. 21-24, 2017consumption from 35,000 m3/ha to 15,000 m3/ha with
the implementation of new water control equipment,
land leveling, land consolidation and water turnbetween farmers.
In 1965, sugarcane was introduced in Office duNiger with an initial 5,800 ha under cultivation by thiscrop. This total has increased to 16,276 ha by 2015
with a total of 20,000 ha planned by 2018. Cotton,
which was previously the main crop during colonial
rule, was banned in 1970.

made between principle crops in term of waterproductivity and profit-water ratio during the dry
period (March to May).
WP = CP/ WR (1)PWR= WP * CP (2)WR= (ETC+Per - R)*10*Eff (3)WP: Water Productivity [kg/m3], CP: Crop
Production [kg/ha], WR: Water Requirement [m3/ha],
PWR: PWR: Profit-Water Ratio [$/m3], CP: Crop
Price [$/kg], ETC: Crop Evapotranspiration [mm],Per: percolation & seepage [mm], R: Effective
Rainfall [mm] and Eff: Efficiency
Ecosystems of the Inner Niger Delta

Fig.6 Evolution of irrigated land construction in
Office du Niger (Data source: Office du Niger).
Between Koulikoro and Ke-Macina stations there
are two main irrigation areas: Office Riz Ségou (ORS)
which is comprise of 44,718 ha land irrigated byflooding during the rainy season and Office du Niger(ON) which has 138,000 ha under gravity irrigation(100% of the land is in use during rainy season and 10
to 25% is in use during cool and dry seasons). From1995 to 2015, which represents the second average
hydraulicity period, 17% of the Niger River annual
average volume (36 km3) is used mainly byagriculture. The annual flow can be classified asfollows: High flow period from June to February andlow flow period from March to May.
Crop water production is only governed bytranspiration. As it is difficult to separate the effect oftranspiration from that of evaporation from the soil
surface, defining crop water productivity using
evapotranspiration rather than transpiration makes
practical sense at field and system level (FAO, 2003).
In the Office du Niger area which is characterized bylarge earthen canals and significant drainage, theamount of water lost is important and the global
efficiency is 60% (Adama et al. 2011). This efficiency
is used to define the water productivity for different
crops. Using, crop evapotranspiration, irrigation
efficiency, crop yield and crop price, a comparison isSome plant species have become very rare such as
Acacia albida, Adansonia digitata, Boscia senegalensis,
Balanites aegyptiaca and Echinochloa stagnina locallyknown as bourgou (Figure 7). Bourgou is distributed
in areas persistent flooding with water level 2-5 m indepth. According to Jerome Mari, the bourgou
superficies represent 10% (1,613 km²) of the plantmaterial in the floodplain of the delta. Since the great
drought of the 1970s and 1980s to the present, 85% of
the coverage due to bourgou has disappeared.
Bourgou fulfills multiple roles in terms of human andanimal populations of the Delta. The seeds of thisplant act as a food source for humans while the stems
have medicinal applications. Its grass production of 15
to 30 tons/ha, feeds almost 2 million cattle and 3
million small ruminants for 5 to 7 months a year. The
vast pastures of bourgou are also favorable zones forthe reproduction and growth of the numerous speciesof fish of the Delta. Furthermore, the large number ofHerons species are present owe their survival to theplentiful supply of juvenile fish.
Cattle in the borgou fieldA fisher boat near bourgou field

Waterfowls in bourgou field

Fig.7 “A vital resource”: Echinochloa stagnina(bourgou) in Inner Niger Delta (credit photo OPIDIN)

This wildlife capital was previously the home ofwide variety of fauna and flora which included: large
herbivores such as gazelle, Hippopotamus amphibious,
manatee (Trichechus senegalensis), large reptiles suchas the Nil Crocodile (Crocodylus niloticus), Python(Python sebae) and Nile Varan (Varanus niloticus) [8].
At present, these floodplains are now poor in animaland plant species as a result of strong human pressureand environmental degradation. Evidence of this is the758

GEOMATE - Mie, Japan, Nov. 21-24, 2017

fact that large herbivores and large reptiles havealmost disappeared.
The number of fishermen in the Inner Niger Delta isestimated at 65,000. This corresponds to an
approximate population of 240,000 including children,
women and elders depend on fishing as an importantpart of their livelihood. A large fraction of thesefishermen move from their villages to the lakes
between December and March and this coincides withthe time that the shoals of fish migrate. Due to lack ofdata it has not been possible to estimate the evolution
over a long period. However, according to the Malian
National Statistics Institute report on fishery andaquaculture 2010-2015 [9], the quantity of fish caught
in the Inner Delta has decreased significantly during
this period (Figure 8).

between 1982 and 2014, the highest flow rate recorded
was in September 2001 with a corresponding value of
5,500m³/s. According to the historical variation of thehydraulicity of the Niger River from 1960 to 2015
may be classified as follows (Figure 9):• A period of high hydraulicity for 1960 to 1969
with an annual average flow rate 1,654 m3/s.
• Two periods of average hydraulicity (1970 to1981 and 1995 to the present) with an annual
average flow rate between 1,226 and 1 301 m3/s;• A period of low hydraulicity from 1982 to 1994
with an annual average flow rate 776 m3/s.

Fig.9 : Hydraulicity of the Niger River before andafter construction of the Sélingué dam in Koulikoro

The Analysis of remote sensing data
Remote sensing data (Landsat images, 2014) andaerial photographs from 1970 (provided by the Malian
government hydraulic Service) were analyzed by
ArcGIS. As result we found 16,041 km² of maximum
flooded area between the period 1970 and 2014 of the
Inner Niger Delta with 20,851 km² of flood area, thelost represent 23% during the last four decades (mapin Annex). During the same period the irrigated areaof Office du Niger increased by 67% (from 58,287 ha
to 138,418 ha).

Figure 10 (b) clearly shows the increase in water
intake and water lost between Koulikoro and KeMacina during the period of low flow despite theimprovement in Niger river hydraulicity incomparison with the situation in the 1970’s and1980’s. The water loss gap between water inflow andoutflow in this section of the river changes from lessthan 20% in 1960’s to 70% today.
HIGH FLOW PERIOD (FROM JUNE TO FEBRUARY)

3 000
2 500
Flow (m3/s)

Fig.8 : quantity of fish caught in the Inner Delta(adapted from Ministry of fisheries report 2010-2015)

This difference reprensete water use, lostand reserve amont Makala dam

2 000high inflow(Koulikoro)

1 500
1 000

High
outflow(kemacina)

5000

LOW FLOW PERIOD (FROM MARCH TO MAY)
250
200
Flow (m3/s)

RESULTSTo characterize the hydrological regime of the Niger
River, the Koulikoro station was selected for statisticalanalysis. It is located approximately 200 km upstream
from the Markala dam. Koulikoro station has been
operational since 1907 and as a continuous data set
since its inception. This station therefore allows
characterization of the hydrology of the Niger River
with an acceptable level of precision.

150

(b)
This difference reprensete water use, lostand reserve amont Makala dam
low
Inflow(Koulikoro)

100
50
0

In the period 1907-1982 before construction of
Sélingué dam, the highest flow rate recorded was
7,586m³/s in 1928. After the dam construction
759

(a)

Low outflow(
Kemacina)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.10 Inflow and outflow of the Markala Dam (forthe period 1960 to 2015)
A minimum flow rate of 40 m³/s was established
downstream of the Markala Dam through anagreement between the Governments of Niger Basin
Authority countries. Despite this agreement, recent
hydrometric surveys at the Markala-downstream
station show that at the present the minimum flow
conditions are not maintained continuously. For thelast five years (2011 to 2015), the flows recorded atdownstream of the Markala dam is less than 40m³/s
for average of 73 days per year (source Office duNiger).
The percentage of water Levy by Office du Niger
River ranges from 3% in September to 69% in May.
This illustrates the pressure on Niger River water
resources during dry periods when the upstream flowrate is below 200m3/s (Figure10b). Despite thissituation the cultivation of paddy rice and sugarcane(both high water consumption crops) increases during
this period instead of diversification crops (DC)(onion, garlic, tomatoes, corn, potatoes etc.) as shownin the Figure 11. In 2000 the total cultivated area
during the dry period increased from 17,102 ha (34%DC, 32% of rice and 34% Sugarcane) to 43 703 ha(24% DC, 39% rice and 37% Sugarcane).

Fig.11 : Evolution of diversification crops, sugarcane
and rice cultivation field surface during dry period
from 2000 to 2014 (data source, Office du Niger
annual activities reports from 2001 to 2014)
From the evapotranspiration, efficiency of irrigation
system, crop yield, and crop price data for the dry
season 2014, a comparison was made between someprinciple crops through water productivity and profitwater ratio (Figure 12).

Fig.12 : Profit-water ratio and water productivity forpaddy, sugarcane and vegetables (onion, tomato,
sweet potato during dry period 2014.
From the Figure 12 it can be clearly seen that paddy
and sugarcane are less profitable in terms of waterproductivity (WP) and profit-water ratio (PWR) thandiversification crops. The Paddy rice has the lowest
benefit (WP=0.24 kg/m3 and PWR=0.09$/m3) while
onion and potato have the highest water productivity(WP=3.86 and 3.51 kg/m3) and garlic the highest
profit-water ratio (PWR=3.13 $/m3).
DISCUSSION
The rapid development of the large-scale schemesin the area of Office du Niger which is irrigatedupstream may have a significant impact on the Niger
River’s hydrology as well as the floodplain and theecosystem of the Inner Niger Delta. In this study,changes in the Inner Niger Delta are evaluated as aresult of the expansion of the irrigated area andcropping pattern of Office du Niger.
During the high flow season from June to February,almost all the crop is paddy rice in Office du Niger(118 418 ha in 2014) and other irrigated areas
upstream of the Inner Niger Delta. Despite the highdemand of water for paddy rice and sugarcane, theimpact on the Niger River flow remains very low andcan reach more than 5 500 m3/s (Figure 10a).
The impact of irrigation is very significant during
the low flow season from March to May. This
corresponds to a period with flow rate below 250m3/s;(Figure 10b). In the past, the paddy rice cropping was
avoided during this season. However, from the year
2000 the Malian government decided to introduce
paddy rice double cropping per year. The sugarcane

760

GEOMATE - Mie, Japan, Nov. 21-24, 2017

cultivation area also increased from 5 800 ha to 16
276 ha in 2014.

constructed dams of Talo and Djenné on the Bani
(tributary river)(Figures 5&10).

The cultivated area of diversification crops(vegetables and others) which is the alternative to
paddy during the dry season has the highest profit
economically and in terms of water saving does notfollow the trend, as more farmers prefer paddy. There
are four main reasons for this: The farmers use
calabash and other container (manual labor) for
irrigation and it is very difficult to irrigate a large farm,
the access to market is very difficult, the harvest
occurs at the same time and prices are very low, there
is a lack of refrigerated storage and there is noprocessing and packaging industry.

• During the last three decades, the floodplain of the
Inner Niger Delta has been reduced by 23% and
the irrigated area increased by 51%. In the
Government program for the development of
100,000 ha of irrigated land between 2014 and2018, 67,850 ha will be realized upstream of the
Inner Delta (see sections 2.3 & 2.5).

How to reverse the trend:
To minimize the impact of Office du Niger
particularly and other small-scale irrigated areas
located upstream of the Inner Niger Delta, thefollowing actions are required:• Limitation of rice cultivation during the dry
period (March to May )• Limitation of the extent of sugarcane fields• Changing of crop pattern during the dry period
and opting for diversification crops (vegetable& others)• Reducing the length of rice growth stage
through the use of new varieties.
SUMMARY
At present, It is clear that water has become aconstraining factor in the development of irrigatedagriculture in Mali and the preservation of the Inner
Niger Delta ecosystem.
• After the major drought in 1970’s and 1980’s,
rainfall in the Inner Delta region has improved
over the last decade. This condition remains fragile
as it is impacted by climate change (Figure 1).
• Despite the recent improvements in upstream
hydraulicity of the Niger River, less and less waterreaches the Inner Delta. This occurs mainly during
the dry season (March to May) and is largely due
to water withdrawals for irrigated as a result of
paddy cultivation located between Koulikoro andMarkala as well as between the recently• To formulate a balance between Inner Niger Delta
floodplain and the development of irrigatedagriculture, some action needs to be taken.
Suggestions include: limiting of rice cultivation
especially during the dry period, limiting of area
available for sugarcane, changing or reducing rice
to vegetable crops during the dry period and the
reduction of rice growth stage through theintroduction of new varieties (Figures 11 & 12).
ACKNOWLEDGMENT
Our warm thanks to Office du Niger, Mali’s
National Direction of Hydraulic for their supporting interms of providing some data. Thanks to the
Laboratory of Forest Resources of Mie University for
their help in term of remote sensing data analyzing.
REFERENCES[1] UNDP, ‘Human Development Report 2015 Work
for
Human
Development’
http://hdr.undp.org/sites/default/files/2015_human_development_report.pdf , 2015, pp 228[2] Instat-Mali,’’Enquete Modulaire Et Permanente
Aupres Des Menages (EMOP), Rapport d’analysepremierpassage’’,
http://www.instatmali.org/contenu/eq/rana16pas1_eq.
pdf , Août 2016, pp 27[3] Cessouma Adama, ‘’ l’agriculture irriguee et lesperspectives d’economie d’eau au mali’’, revue HTE
n°141, http://www.anafide.org/doc/HTE%20141/1412.pdf, Décembre 2008, pp 04[4] “ conservation: Conflict on a global scale’’,Environ. Manage., 25(5), 2000 , pp 485[5] Leo Swart& al, “The Niger, a lifeline” wetland
International, A&W, 2005, pp 39-77[6] INSTAT-MALI, Recueil des données du systèmed’informations sur la pêche et aquaculture 2010-2015(SIPA), October 2016, pp 5

761

GEOMATE - Mie, Japan, Nov. 21-24, 2017[7] Strategic axes of the agricultural policy of theGovernmentofMali
http://ma.gouv.ml/index.php/strategies/vision[8] Conference of ministers of agriculture of theAfrican union Maputo, Mozambique “Report of theministers of agriculture” , 1-2 july 2003, pp 2
[9] Presidency of Mali “ Communiqué du conseil
des ministres du 03 Août 2015 ’’, 2015,
http://www.koulouba.ml/officialstatements/communique-du-conseil-ministres-dulundi-03-aout-2015
ANNEX

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A STUDY ON SELECTION FACTORS OF RESIDENCE FOCUSING ONPERSONAL ATTRIBUTES AND DISTRICT CHARACTERISTICS- A CASE STUDY OF REGIONAL CITY IN JAPAN 1

Tetsuo Morita1and Shinya Tsukada2
Graduate School of Engineering, Maebashi Institute of Technology, Japan; 2Maebashi City Office, Japan,
ABSTRACTIn Maebashi City, Gunma Prefecture, Japan like other regional cities, motorization is progressing year by year.
Dependence on automobiles has become a major cause of urban sprawl. In Maebashi City, the DID (Densely
Inhabited District) is expanding year by year, but the population density is decreasing. In this study, in solving
these various problems of local cities, we will consider "Compact City" as one future image of local cities andconsider the consolidation of cities. The purpose of this study is three as shown below. The first aim is to analyze
the factors of resident consciousness to live in Maebashi City. The second aim is to analyze the reasons forsettlement by resident, and to clarify the settlement factors. The third aim is to analyze the factors that define theawareness of residence selection by migrant-oriented persons.
Keywords: Personal Attribute, District Characteristic, Selection Factor of Residence, Maebashi City
addition, Morita et al. [5] focused on the environmentof the water and green for Maebashi City, andevaluate the quality of life.
As mentioned above, this study is on the line ofresearch on residence selection in local cities. The
characteristic of this study is to divide it into people
who intend to settle down and those who intend toemigrate, and analyze the factor of choosing a placeof residence.

INTRODUCTION
Background and purpose of this study
In Maebashi City, Gunma Prefecture, Japan likeother regional cities, motorization is progressing year
by year. In 2015, 78% of transportation in the central
metropolitan area of Gunma prefecture is occupied byautomobiles [1]. Dependence on automobiles has
become a major cause of urban sprawl. In Maebashi
City, the DID (Densely Inhabited District) is
expanding year by year, but the population density isdecreasing. In this study, in solving these various
problems of local cities, we will consider "Compact
City" as one future image of local cities and consider
the consolidation of cities.
The purpose of this study is three as shown below.
The first aim is to analyze the factors of resident
consciousness to live in Maebashi City. The second
aim is to analyze the reasons for settlement by
resident, and to clarify the settlement factors. The
third aim is to analyze the factors that define theawareness of residence selection by migrant-oriented
persons.

Study Area
The study area, Maebashi City, is shown in Fig. 1.
Maebashi City is the prefectural capital of Gunma
Prefecture with a population of 340,000 people, and alocal city located about 100 km from Tokyo. In
Maebashi City, motorization is progressing evenamong local cities, and Maebashi City is studying
toward realization of compact city.

Gunma Prefecture

Maebashi City

Review of literature

100km

Fujii [2] studied about Traffic Policy towards theintroduction of Compact City for Takasaki City,
Gunma Prefecture. Nishiyama et al. [3] analyze
residence selection behavior based on resident
preference of residential attribute in Utsunomiya
metropolitan area. Morita et al. [4] analyzed the living
consciousness in the mountainous area of Gunma
prefecture and proposed compact area creation. In

Tokyo

Fig. 1
764

Location of Maebashi CityGEOMATE - Mie, Japan, Nov. 21-24, 2017

RESIDENT CONSCIOUSNESS IN MAEBASHI
CITY
The Gunma Person Trip Survey was carried out
in 2015, and this data is used in this study. Fig. 2
shows resident consciousness. The percentage of
those who want to continue living in the current placeis 86.0%, and the proportion of people planning tomove to other places or to move is 14.0%. Looking at
the proportion of residence by type of age group,
those who want to continue living are over 60% intheir 10’s and 20’s. As the age group goes up, thecomposition ratio of those who want to continue
living in the current place tends to be higher.
The reason for continuing living (excluding
unknown) is shown in Fig. 3. From this figure, it isfound that 19.0% is "easy to go to commercial
facility", 16.8% is "easy to go to medical and welfare
facility", and 3.3% is "easy to go to child care support
facility". The reason for accessibility to daily-related
facility accounts for 39.1%. Also, "rich in green andnature" is 12.5%. 7.5% "easy to use railroad and bus",
12.3% "easy to move on foot and by bicycle", 18.9%"easy to move by car".
Figure 4 shows the items that people who want tomove and people planning to move from the current
location emphasize when choosing a place ofresidence. Importance degree 1 means "absolutely notimportant", importance degree 2 means "not very
important", importance degree 3 means "neither",importance degree 4 "slightly important" andimportance degree 5 means "very important".
When looking at the composition ratio ofimportance degree 4 (slightly important) and
importance degree 5 (very important), the highest is
90.8% in the "district with less risk of natural
disasters and fires", 84.0% is district easy to go to
medical and welfare facility ". Regarding
accessibility to facilities, 73.2% are "easy to go tocentral shopping area" and 64.6% are "easy to go to
shopping center in suburb". Regarding mobility,
74.3% are "district easy to move by car", 73.0% are"district easy to move on foot and by bicycle ", 67.4%
for "district easy to use railway and bus". From theabove, it is assumed that there are people who
emphasize mobility by car and accessibility tosuburban shopping centers, and people who emphasis
mobility on foot and by bicycle and accessibility tocentral shopping areas.
Next, we will grasp the relationship between the
district characteristics of the residential area and theresident consciousness. Fig. 5 shows the resident
consciousness by distance range to station, and Fig. 6
shows the resident consciousness by distance range tobus stop. As a result, there is no difference in the
consciousness by any district characteristics. There isan influence of individual attributes such as age group

0%

age

20%

40%

60%

80%

100%

10's(N=587)

63.2

36.8

20's(N=1426)

62.3

37.7

30's(N=2301)

73.8

26.2

40's(N=3073)

83.4

16.6

50's(N=2901)

87.5

12.5

60's(N=4200)

92.4

7.6

70's(N=3296)

95.2

4.8

80's(N=1660)

96.3

3.7

over90(N=326)

97.9

total(N=19770)

2.1

86.0

14.0

people who want to continue living
people who want to move, people planning to move

Fig. 20%

Resident consciousness by age group in
Maebashi City (excluding unknown)
20%

19.0

40%
16.8

60%

3.3 12.5

7.5

80%

12.3

100%

18.9

9.8

easy to go to commercial facility
easy to go to medical and welfare facility
easy to go to child care support facility
rich in green and natureeasy to use railroad and bus
easy to move on foot and by bicycle
easy to move by car
otherFig. 3

Reason for continuing living (multiple
answers)
20%

40%

district easy to go to central
3.16.3 17.3
shopping area

0%

60%

32.7

district easy to go to shopping
3.48.0 24.0
center in suburb
district easy to go to medical and 2.3
1.512.2
welfare facility
district easy to go to child care
support facility

26.9

37.7
53.2

20.1

24.5

33.2

district rich in green and nature 2.7
4.6 24.7

40.0

28.0

district easy to use railroad and bus 4.17.0 21.6

33.1

34.3

district easy to move on foot and by
5.0 18.9
3.0
bicycle

31.4

41.6

district easy to move by car 2.7
3.6 19.4

35.1

39.2

district with less risk of natural
1.17.2 18.8
disasters and fires

importance degree 1

importance degree 2

importance degree 4

importance degree 5

Fig. 4

765

40.5

30.8

13.2 8.9

80% 100%

72.0

importance degree 3

Items to be emphasized in selecting
residence (people who want to move, people
planning to move)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

0%

20%

40%

60%

80%

100%

less than 1km to station(N=6384)

87.1

12.9

1km or more to station(N=13386)

85.4

14.6

total(N=19770)

86.0

14.0

Table 1 Discriminant
analysisonresident
consciousness (Variable quantification II
analysis)peaple who want to continue living

10's
20's
30's
40's
50's
60's
70's
over 80
primary industry
secondaryindustry
tertiary industry

273
741
1191
1597
1453
2104
1576
1035
371

-1.970-2.221-1.215-0.320
0.195
0.602
0.880
1.163
0.187

1231

0.066

3985

0.021

other occupation
student
housewife/husbandunemployed
always necessary
necessarynecessity ofaccording toattendance
circumstances
unnecessary
myself only
car ownership family shared
none
distance range less than 1km
to station
1km or moredistance range less than 300m
to bus stop 300m or more
urbanization
promotion area
urbanization
control area

54375

-0.166-0.0711365-0.0342589
470-0.060-0.072539-0.126

8961
7041
1022
1907
2656
7314
7814
2156

0.011
0.044
-0.064-0.1290.158-0.0570.023-0.0846474-0.062

2080

0.076

1006

0.282

outside city
planning area

410

-0.101

peaple who wantto contine living

8585

0.120

peaple who want tocontine living,planning to move1385

-0.746

Resident consciousness by distance range tostation
0%

20%

40%

60%

80%

100%

less than 300m to bus stop(N=6384)

85.6

14.4

300m or more to bus stop(N=13386)

87.2

12.8

total(N=19770)

86.0

14.0

individual
attribute

peaple who want to continue living
peaple who want to move, peaple whi planning to move

Fig. 6categoryscore

age group

peaple who want to move,peaple whi planning to move

Fig. 5

number ofsamples

explanatory variable

Resident consciousness by distance range tobus stop

districtcharacteristic

in resident consciousness, and multivariate analysis
considering individual attributes and district
characteristics is considered necessary.
DISCRIMINANT ANALYSIS ON RESIDENTCONSCIOUSNESS

occupation

area wherecity planning urbanizationarea
promotion area
and urbanization
control area are
not distinguished[objective variable]
resident consciousness

The analysis results are shown in Table 1(variable quantification II analysis).
The explanatory variable which most affects
resident consciousness is age group, and both thecategory range and the partial correlation coefficientare higher than other explanatory variables. The
explanatory variable that most affects the resident
consciousness is age group. The category range andpartial correlation coefficient are both higher thanother explanatory variables.
Looking at the category score, the higher the agegroup, the higher the intention of "wanting tocontinue living" (hereinafter referred to as settlement
intention) tends to be higher. Looking at otherpersonal attributes, the variable with the greatest
influence after age group is occupation. The
settlement intention for people in the primary industry
is high, and the intention to "want to move"(hereinafter referred to as migration intention) of
students and unemployed people is high. The next
most influential variable is car ownership, and there
is a certain relationship between car ownership andresident consciousness.

category

range(rank)

partialcorrelation
coefficient(rank)

3.384
(1)

0.294
(1)

0.353
(3)

0.018
(5)

0.137
(6)

0.010
(6)

0.173
(5)

0.020
(4)

0.215
(4)
0.107
(7)

0.030
(2)
0.009
(7)

0.384
(2)

0.021
(3)

correlation ratio
0.300

Regarding district characteristics, the explanatory
variable with a great influence is city planning area.
People living in urbanization control area and area
where urbanization promotion area and urbanization
control area are not distinguished are highly likely tosettle down. Residents urbanization area and area
outside urban planning areas are highly motivated tomigrate. It is assumed that residents of urbanization
control area, area where urbanization promotion area
and urbanization control area are not distinguishedhave a long residence age and are highly attached tothe district. Also, since outside urban planning area isthe mountainous area of Mt. Akagi, it seems that there
is an intention to migrate to the area with highlifestyle convenience.
Regarding the distance to station, less than 1km
tends to settle down, less than 1km tends to be more
likely to emigrate. The distance to bus stop is lessinfluential compared to all the other variables, butwhen it is close to the bus stop, the intention to settle
is seen.
766

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ANALYSIS OF THE INTENTION OF
RESIDENTS OF SETTLERS (SETTLEMENTINTENTION)

their 60’s want to have rich green and nature, people
over the age of 70 want to go to medical and welfare
facilities and to live on foot or bicycle.

As a result of discriminant analysis of the resident
consciousness, it became clear that the variables that
greatly influence the residence intention are the agegroup. For that reason, we analyze the relationship ofsettlement reasons by age group. For the analysis, we
use samples of people who have settlement intention.
Correspondence analysis was performed to visualize
analysis data.
In conducting correspondence analysis, acomposition frequency table of the settlement reasonsof people who intend to settle down by age group(respondents who want to continue living) was
prepared. The analysis results are shown in Fig. 7.
With respect to the horizontal axis, since it isarranged in the positive direction that "easy to moveon foot and by bicycle" and "easy to go to medical
and welfare facility" are arranged, " living area isnarrow ". The negative direction, "easy to move bycar" is arranged, so "living area is wide" named. The
vertical axis is named "natural" because "rich in green
and nature" is a large positive value. We named thenegative direction "urban".
Looking at each age group, the area of living
becomes narrower as the age group goes up, withrespect to the horizontal axis. Looking at each age
group individually, the 30’s cited it as reason for“easy to move by car". The 40’s and 50’s cited thereason for "easy to go to commercial facility". The
60’s cited the reason for “rich in green and nature".
The 70’s cited the reasons for "easy to go to medical
and welfare facility " and " easy to move on foot andby bicycle”. From the above, it became clear that thereasons for settlement differ according to age group.
Young people want the convenience of life, people in

ANALYSIS OF THE INTENTION OF
RESIDENTS OF MIGRATION (MIGRATIONINTENTION)
In this study, we analyze the intention of persons
who intends to migrate ((people who want to move,people planning to move). In the survey, people who
intend to emigrate are questioned about the degree ofimportance of choosing a place of residence(hereinafter referred to as residential preference).
Table 2 shows the results of applying principal
component analysis to these data.
There were two principal components whose
eigenvalues exceed 1. The accumulation contribution
ratio of the two main components is 52.3%.
Looking at the principal component loading
amount of principal component 1, since all variables
are positive values, it is regarded as a comprehensive
evaluation for selecting residences, and the name ofprincipal component 1 was taken as "living
environment". The principal component 2 is positive
value for "district easy to move by car" and "easy to
go to shopping center in suburb". Also, negativevalues are "district easy to move on foot and by
bicycle" and "district easy to use railroad and buse".
Therefore, the name of principal component 2 was"suburb". The negative direction is "city".
By using the principal component scores obtainedby principal component analysis, residential
preference maps for each attribute were created (Fig.
8). In the residential preference map, the horizontal
axis is defined as the principal component 1 "living
environment", and the vertical axis as the main
component 2 "suburban - urban". By calculating the
average value of the principal component scores byattribute and plotting the values on the coordinates,
we can visually ascertain the difference of theTable 2 Principal component analysis on residential
preference
variable
district easy to go to central shopping area

Fig. 7

Analysis of the intention of residents ofsettlers (Correspondence analysis)
767

principal
principal
component 1 component 2
livingsuburbanenvironment(- urban)
0.672-0.233

district easy to go to shopping center in suburb
district easy to go to medical and welfare facility

0.611
0.744

0.251
-0.022

district easy to go to child care support facility
district rich in green and nature
district easy to use railroad and bus

0.474
0.595
0.630

0.414
0.234
-0.520

district easy to move on foot and by bicycle
district easy to move by car
district with less risk of natural disasters and fires

0.662
0.533
0.682

-0.5240.510
0.128

eigenvalue

3.542

1.167

contribution ratio

39.4%

13.0%

accumulation contribution ratio

39.4%

52.3%

1
area where urbanization
promotion area and0.8
urbanization control area
are not distinguished30'surbanization control area
tertiary industry

suburban→

GEOMATE - Mie, Japan, Nov. 21-24, 20170.6

primary
industrycar: miself only
0.4
attendance: unnecessary

20's
secondary industry
outside city planning area

←weak: living environment
‐1

‐0.8

‐0.6

0.2

attendance:
always necessary
peaple who want to contine
living, planning to move
distance: less than 1km

peaple who want to contine
living40's
maledistance:1km or more
0
‐0.4
‐0.2
0

living environment: storong →50's 0.2

0.4

0.6
60's

0.8

1

housewife/husband‐0.2

car: family sharedover 70

student
10's‐0.4
unemployed

‐0.8

‐1

attendance:
necessary according to circumstances←urbancar: none

urbanization promotion areaother occupation‐0.6

Fig. 8femailResidential preference maps for each attribute s (Principal component analysis)

residential preference by the attribute.
Car ownership has great influence on "suburban urban". People who do not own cars are strongly
urban oriented, and those with their own car tend tobe suburban oriented. In terms of gender, female tend
to have strong feelings for living environment.
Looking at by age group, young people are more
suburban-oriented, weak in their living environment,
the elderly are more urban oriented, and their habitatis strong. However, the tendency of the 10’s is urban
oriented, and there are trends of students who do notpossess cars or students who go to school outside theprefecture. By occupation, people in the primaryindustry and secondary industry are oriented towards
the suburbs, students and unemployed people areurban oriented. People who need attendance
depending on circumstances when going out are
urban oriented, and those who always needattendance tend to have weak consciousness to living
environment.
By the above principal component analysis, wewere able to grasp the tendency of intention to
migrate by individual attribute.

who want to continue living in the current place giveaccessibility to facilities and mobility by means oftransportation as a reason for settlement. Some people
who intend to emigrate are emphasizing mobility by
car and accessibility to suburban facilities. On theother hand, there are people who place emphasis on
mobility of walking and bicycle and accessibility to
the city center.
Maebashi citizens, as a whole, are aiming forautomobile use. On the other hand, there is a tendency
that people who intend to settle live in the vicinity ofstation, and the elderly desire "easy to go to medical
and welfare facility" and "easy to move on foot andby bicycle". From this, it is thought that there are acertain number of people who are oriented towards
public transportation. Among those who intend toemigrate, there are those who do not possess cars,
those who need attendance when going out, and urban
oriented students. It will be necessary to support the
lives of such citizens from the transportation side andto form compact cities that are easy to use for public
transportation.
ACKNOWLEDGEMENTS

CONCLUSION

The data of the Gunma Person Trip Survey used inthis research was lent from Gunma prefectural
government. We express our appreciation here.

Maebashi citizen's intention to settle is higher,
and the tendency is higher for elderly people. People
768

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Preference”, Journal of Japan Society of Civil
Engineers, Ser. G, Vol. 67, No. 6, 2011, pp. 1-10,
2011.
[4] Morita T, Tsukada S, Sano K, “Analysis on
Population Trend and Residential Attitude in
Depopulated and Aged Area toward the Compact
Area: Case Study of Kuni Village in Gunma
Prefecture”, Papers on city planning, No.45-3,
2010, pp. 511-516.
[5] Morita T, Kogure Y, Sugita H, Baba T, Tsukada
S and Miyazato N, “A Study on Evaluation of
Quality of Life in Consideration of Water/Green
Environment”,
International
Journalof
GEOMATE, Vol. 2, No. 2, 2012, pp. 241-246.

REFERENCES[1] Comprehensive City Transportation PlanningCouncil of Gunma Prefecture, Results of Gunma
Person Trip Survey in 2015-2016, 2017,
http://www.kendoseibi.pref.gunma.jp/section/to
shikeikaku/gunma-pt/result.html.
[2] Fujii S, “An Empirical Test of Hypothesis on
Influence of Travel Behavior on Residential
Choice Behavior: A Fundamental Study on
Transportation Measures for Promoting
Compact Cities”, Traffic Engineering of Japan,
Vol. 43, No. 6, 2008, pp. 53-62.
[3] Nishiyama Y, Nakatani J, Kurisu K, Aramaki T
and Hanaki K, “Analysis of residential Choice
Behavior Based on Classification of Residential769

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

REMOVAL OF RADIOACTIVE CESIUM FROM OCEAN SULUDGE
BY THE BACTERIUM USING PURIFICATION SYSTEM OF
CIRCULATION TYPE
Tomoe KOMORIYA1, Kyoichi OKAMOTO2 and Takashi TOYAMA2
1
CIT, Nihon University, JAPAN; 2CST, Nihon University, JAPANABSTRACTThe Fukushima nuclear accident of March 11, 2011 resulted in soil and water contamination by radioactive
cesium. Radioactive cesium transported by rivers was also found in the ocean sludge of Tokyo Bay. Cesium
adsorbed on the sludge is not easily removed. One of the authors has developed an ocean sludge decomposition
system that employs micro-bubble circulation. The circulation of micro-bubbles creates an aerobic state that
activates aerobic bacteria, facilitating decomposition and purification of the sludge. The objective of this study
was to investigate the effect of the addition of bacteria to the micro-bubble circulation system on the efficient
removal of radioactive cesium from ocean sludge. We tested the water purification effect of the system byadding bacteria directly. Results confirmed that the decomposition of the deposited sludge using our systemfacilitates the elution of the radioactive cesium. Any cesium eluted in the water can be remedied using existing
technology such as zeolites. Purification efficiency seems to be greatest when additional bacteria are added
directly to the process. With time, bacterial concentration doubles, and 76% of cesium in the liquid phase (driedsludge) and 51% of cesium in solid phase (water) is removed.

Keywords: Decontamination, Radioactive Cesium, Ocean Sludge, Micro-bubble, Bacteria

remedied using existing technology such as zeolites[5]; resulting in the complete decontamination of
sediment.
In this study, to effectively remove radioactive
cesium, we added bacteria to break down sludge inthe micro-bubble circulation system, andinvestigated the effect of the addition of
microorganisms.

INTRODUCTION
The 2011 accident at the Fukushima Daiichi
nuclear power station led to radioactive cesium
contamination of soil and water. Rivers flowing into
the Tokyo Bay have transported radioactive cesium
into the ocean sediments of the bay [1].
Cesium is reportedly easily adsorbed onto themicroscopic particles that constitute soil [1-2]. Most
cesium adsorbed by sediments is difficult to removeby external factors, and persists over long timescales.
Moreover, closed water environments such as riverand bay systems make accumulated organic sludge
difficult to decompose. Therefore, radioactive
cesium is predicted to be deposited in the sedimentof the seabed over time, extending radioactive
contamination into the ocean. It is important todecontaminate the sediment.
Okamoto, one of the authors, developed adecomposition system for ocean sludge that employs
the circulation of micro-bubbles to promote aerobic
conditions that activate aerobic bacteria, facilitating
decomposition and purification of the sludge [3].
Moreover, sea-sludge particles were observed todecrease in size through the course of the treatment
with our micro-bubbles system and bacteria addition[4].
Radioactive cesium can thus be eluted after thedeposited sludge is decomposed by our system. If
the cesium is eluted into water, it can then be

MATERIALS AND METHODS
Decomposition System of the Micro-Bubble
Circulation TypeThe micro-bubble circulation system comprises
two parts, as shown in Fig. 1. The water circulates
through two tanks. In one tank (length 40 × width 28
× height 28 cm), highly soluble, micro-bubbles are
generated. Consequently, water rich in dissolved
oxygen (DO) circulates through these tanks. The
experimental tank is 60 × 29 × 35 cm. We used 30 Lof seawater and 1 kg of sludge. The micro-bubble
generator was based on [6] and the flow rate was
900 L/h. The flow rate of the water pumps
connected to each tank was 300 L/h. A cooler for thetank that generates the micro-bubbles was set to
30
°C.

770

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 2

Zeolites 4A set in experiment tank

Table 1 Experimental conditions
Fig. 1

Circulation purification system
Case 1Case 2

Experiments on Decomposition of Deposited
Sludge for Cesium Removal
Fig. 1 illustrates the system used toexperimentally remove cesium from ocean sludge.
The ocean sludge samples and seawater wereobtained from Funabashi Port in Chiba Prefecture,
Japan. The first 10 cm of sludge from the seabed
was discarded before the samples were taken.
Model sludge was prepared using one kg ofocean-sludge, 30 L of seawater, cesium chloride was
mixed. The cesium chloride was included to become
100 mg/L. The model sludge was poured into thesystem and stirred for 24 h.
Zeolites 4A were placed in the second tank (Fig.
2), and micro-bubbles were generated by a microbubble generator using a flow rate of 900 L/h. The
flow rate of the water pumps connected to each tankwas 2400 L/h. The cooler was set to 30 °C.
After 24 h, bacterial species “Alcaligenes fecalis”(15 × 108 cells) [5,7,8] and Glutamic acid (100 ppm)
as an activator [9] were added. The activator wasadded to the experimental tank after 24 and 60 h
periods. At 0, 12, 24, 48, 60, 72, 96, and 120 h, DO,
water temperature, and pH were measured by amulti-parameter water quality meter. A digital packtest (Kyoritsu Chemical-Check Lab. Corp., Japan)
was used to measure ammonium ion (as ammonium
nitrogen, NH4-N), nitrite ion (as nitrite nitrogen,
NO2-N), nitrate ion (as nitrate nitrogen, NO3-N),
total nitrogen (T-N), and hydrogen sulfide (H2S)
concentrations. The seawater was then filtered.
Seawater and sludge samples at 0, 12, 24, 48, 72,
96, and 120 h were collected for DNA concentrationand cesium concentration measurements. DNA wasextracted from sludge and measured byspectrophotometry. Cesium was measured withenergy dispersive X-ray analysis (EDX) in driedsludge and atomic absorption spectrometry inseawater.
Experimental conditions are given in Table 1.

Microbubble◯—

Additive amountof bacteria
1.5 × 108 cell−

Activator
100 ppm−

RESULTS AND DISCUSSION
Decomposition of Deposited Sludge for Cesium
RemovalResults of water temperature, pH, DO and H2Sunder varying environmental conditions
Figures 3 and 4 show the pH and DO
respectively, resulting from the environmental
conditions prevalent in cases 1 and 2 (Table 1).
After 24 hrs, the pH of case 1 and 2 was constant at
about 8.0. The initial concentrations of DO are 4.9
mg/L and 3.7 mg/L in cases 1 and 2 respectively.
The DO of case 1 is saturated at about 7.3 to 7.8
mg/L after 24 h, because the concentration ofoxygen saturation is 8.1 mg/L-pure water. The DOof case 2 is saturated at about 3.5 to 4.2 mg/L after
24 h.

Fig. 3771

Change in water pH over time in case 1 (●)
and case 2 (∆).

GEOMATE - Mie, Japan, Nov. 21-24, 2017

nitrogen) concentration in the experimental tankover time. In case 1, initial concentrations of NO2-N
are approximately 0.28 mg/L. Subsequently NO2-N
constant at 0.01 mg/L up to 48 h, after which it isdecreases and remained at 0.02 mg/L at 120 h. Incase 2, initial concentrations of NO2-N are
approximately 0.28 mg/L. NO2-N decreases to 0.13
mg/L at 48 h, then increases to 0.24 mg/L at 120 h.
Fig. 4

Change in DO concentration over time incase 1 (●) and case 2 (∆).

H2S concentration is shown in Fig. 5. In case 1,
H2S decreases up to 24 h; after which it is no longer
detected, before the addition of A. fecalis to theexperimental tank. A. fecalis is not inhibited by H2S.
In case 2, H2S decreased slightly and remained at
0.16 mg/L at 120 h.
Fig. 7

Fig. 5

Change in NO2-N concentration over timein case 1 (●) and case 2 (∆).

Figure 8 shows the change in NO3-N (nitrate
nitrogen) concentration in the experimental tankover time. In case 1, initial concentrations of NO3-N
are approximately 3.7 mg/L. Following this, NO3-N
increases to 4.6 mg/L at 6 h, then decreases to 0.60
mg/L at 120 h.
In case 2, initial concentrations are approximately
4.14 mg/L. Following this, NO3-N increases to 4.7
mg/L at 24 h, then decreases to 2.2 mg/L at 96 h
before continuing to gradually increase to 3.3 mg/L
at 120 h.

Change in H2S concentration over time incase 1 (●) and case 2 (∆).

Results of NH4-N, NO2-N, NO3-N and T-N
Figure 6 shows the change in NH4-N(ammonium nitrogen) concentration in theexperimental tank over time. In both cases (Table 1),
initial concentrations of NH4-N are approximately
1.5 mg/L. In case 1, NH4-N decreases and is nolonger detected at 72 h. The effect of A. fecalis on
NH4-N concentration could not be ascertained
because A. fecalis was added at 24 h. In case 2, NH4N increases to 1.8 mg/L at 120 h.

Fig. 6

Fig. 8Change in NO3-N concentration over timein case 1 (●) and case 2 (∆).

In case 1, concentrations of NH4-N and NO2-N andNO3-N decreased. Conversely, concentrations of
NH4-N and NO2-N and NO3-N increased orremained constant in case 2. It is assumed that the
metabolism of the bacteria switched fromdenitrification to nitrification because the conditionof the experimental tank water changed to saturated
dissolved oxygen concentration (Fig. 4). Therefore,
we assume that the nitrogen source shifts to NH4+ →NO2− → NO3− and that this trend of NO3-N
concentration is similar to NO2-N.
In case 1, dissolved inorganic nitrogen (DIN;
NH4-N + NO2-N + NO3-N) shows a 90 % decrease

Change in NH4-N concentration over timein case 1 (●) and case 2 (∆).

Figure 7 shows the change in NO2-N (nitrite
772

GEOMATE - Mie, Japan, Nov. 21-24, 2017

(Fig. 9). While T-N (total nitrogen, and inorganicand organic nitrogen) decreased and was eventually
no longer detected (Fig. 10).

Fig. 9Results of cesium concentration
Cesium and silica in the sludge were measured
with energy dispersive X-ray analysis (EDX). The
weight ratios of cesium to silica (Cs/Si) in driedsludge are shown in Fig. 12. The cesium
decontamination ratio was calculated from the ratiosof cesium content at 0, 6, 24, 48, 72, and 120 h as
measured by EDX, using standard values for silica
after measuring the weight of the dried sludge. The
decontamination ratio obtained in case 1 was about
51 %.
Cesium concentrations in the water are shown in
Fig. 13. In case 1, initial concentrations of Cesium
are approximately 40 mg/L. Subsequently Cesium
decreases to 8.3 mg/L at 120 h indicating that 71 %of cesium was removed
In case 2, cesium concentrations in the driedsludge and the water did not decrease. Therefore,
eluted cesium from the sludge was adsorbed onto thezeolites after the sludge was decomposed by microbubbles and A. fecalis.

Change in DIN concentration over time incase 1 (●) and case 2 (∆).

Fig. 10 Change in T-N concentration over time incase 1 (●) and case 2 (∆).
Results of Bacterium concentration
Fig. 12 Change in Cs/Si over time in case 1 (●) andcase 2 (∆) in dried sludge.

DNA concentration in sludge was measured asbacterial concentration. Fig. 11 shows the change in
DNA concentration. In both cases, initialconcentrations of DNA are approximately 2 ug/gsludge. In case 1, DNA doubled, while in case 2,
DNA increased to 2.6 ug/g-sludge at 24 h, thendecreased to 1.2 ug/g-sludge at 120 h.
The effect of the addition of A. fecalis to acirculation purification system on T-N concentration
was investigated.

Fig. 13 Change in Cs concentration over time incase 1 (●) and case 2 (∆) in liquid phase.

The Model sludge was prepared 100 mg/L
Cesium chloride in tank and mixed for 24 h. So, at
the time of experiment start, Cesium concentrationof water was 39.6 mg/L, cesium adsorbed onto
sediments was 60 mg/L. After 120 hrs, 31 mg/L

Fig. 11 Change in DNA concentration over time incase 1 (●) and case 2 (∆).

773

GEOMATE - Mie, Japan, Nov. 21-24, 2017

unsupported 210Pb by mineral soils andsediments”, J. Environ. Radioactivity, Vol. 30(2),1996, pp. 117–137.
[3] Okamoto K, Hotta K, Toyama T, Kohno H,“Purification system of ocean sludge byactivating microorganisms”, Int. J. of
GEOMATE, Vol. 6(1), 2014, pp. 791–795.
[4] Komoriya T, Okamoto K, Toyama T, “Effect ofadding of bacteria on the removal of radioactive
cesium from ocean sludge in a circulation typepurification system”, Int. J. of GEOMATE, Vol.
12, 2017, pp. 121–126.
[5] Okamoto K, Toyama T, “Decontamination ofradioactive cesium from ocean sludge by microbubble and microorganisms”, Int. J. of
GEOMATE, Vol. 9(1), 2015, pp. 1390–1394.

(51%) of cesium onto sediments, and 8.3 mg/L ofcesium in water had been remaining. Accordingly,
using micro-bubble circulation system with bacteria
and zeolite, 61 mg/L of cesium was removed and its
removal ratio was 61%.
In case 2, using zeolite only, 42.8 mg/L ofcesium in water was removed, while, cesium on
sediments was remain unaltered. Therefore, total
cesium removal ratio was 42.8%.
Moreover, Okamoto et.al (2015) was reported
that cesium concentration of water and sediments
was remain unaltered using micro-bubble circulation
system with bacteria [4]These results suggest that after the deposited
sludge is decomposed by our micro-bubble
circulation system with bacteria and zeolite, thecesium is eluted into water, it can then be remove
using zeolites.

[6]Matsuo K, Maeda K, Ohnari H, Tsunami Y,
Ohnari H, “Water purification of a dam lakeusing micro bubble technology”, Progress inMultiphase Flow Research, Vol. 1, 2006, pp.
279–286.
[7]Inamori
Y,
Wu
X-L,
KimochiY,“Characteristics of N2O production by
Alcaligenes faecalis under aerobic conditions”,
Journal of Japan Society on Water Environment,
Vol. 22, 1999, pp. 904–909.
[8] Okamoto
K,ToyamaT,“Oceandecontamination: Removal
efficiency ofradioactive cesium from ocean sludge by using
micro bubbles and activating microorganisms”,
Int. J. of GEOMATE, Vol. 10(21), 2016, pp.
1924–1928[9] Okamoto K, Hotta K, “Purification experimentson sedimentary sludge by microorganism
activator”, In Proc. of Pacific Congress on
Marine Science and Technology (PACON), 2008.

CONCLUSION
We carried out elution and fixing of cesium inocean sludge using a micro-bubble and bacterial
circulation decomposition system. From water
quality measurements, it can be concluded that after
adding A. fecalis, T-N decreases and is then nolonger detected. A. fecalis has a remarkable ability totreat samples through denitrification.
The cesium concentrations in sludge and water
decreased through treatment with micro-bubbles andbacteria for 120 h. 76% of cesium in dried sludge
and 51% of cesium in water were removed. From
the results obtained, we can affirm that the system
proposed would greatly facilitate cesium removalfrom ocean sludge.

ACKNOWLEDGEMENTS
The authors would like to express sincere thanks
to OSHTA Rintarou students of Nihon University, inJapan, for executing the experiments.
This work was supported by KAKENHI C17K06969 (Grant-in-Aid for Scientific Research).

REFERENCES[1] Soemori A, Shozugawa K, Nogawa N, Higaki S,
Matsuo M, “A change in the concentrations ofradioactive cesium in Tokyo-bay’s sediments
released by the Fukushima Dai-ichi Nuclear
Power Station accident”, Bunseki Kagaku, Vol.
62(12), 2013, pp. 1079–1086.
[2] He Q, Walling D E, “Interpreting particle size
effects in the adsorption of 137Cs and774

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

GEOCHEMICAL REACTIVE MODELING OF FLOW AND
TRANSPORT PROCESS AT A MINE SITE IN NORTHERNTERRITORY, AUSTRALIA
1

Michael S. Hayford1, Bithin Datta1, 2College of Science and Engineering, James Cook University, Australia; 2CRC-CARE, University of New
Castle, Australia
ABSTRACT

Subsurface contamination of metals and radionuclides are common problems in abandoned mine sites. Metals
and radionuclides are likely to occur in the mobile phase or may bind to soil particles and geologic framework.
The transport process for reactive contaminants also include chemical reactions in groundwater aquifers which arecomplex physical and biogeochemical processes. Accurate tools to reliably predict the movement and changes inconcentration of metals and their daughter products (radionuclides) formations in the subsurface environment isimportant for decision makers to analyze impact, and to evaluate the effectiveness of remediation strategies. An
advanced numerical model can provide such useful direction of predictions. A 3-D contaminant transport model
for fluid flow, hydrogeologic transport, and biogeochemical kinetic and equilibrium reactions in saturated andunsaturated media was calibrated, validated and implemented to model the hydrogeochemical processes that occur
in the subsurface at such a complex contaminated site, consisting of waste rock dumps and flooded mine pits inof this an abandoned uranium mine site. The developed flow and transport simulation model for no longer in use
mine site in Northern Territory of Australia is discussed.
Keywords: Reactive Transport, flow and transport modelling, groundwater contamination, Mine sitethe majority of AMD is anthropogenic and originatesfrom reactive sulphide minerals stored in waste rockdumps (WRDs), mine pits, and tailings.
Notwithstanding the fact that extensive rehabilitation
studies at the mine site exist, a well-defined reactive
transport model, with a comprehensive suite ofreaction types and reaction rates incorporated into amodel aimed at the remediation and rehabilitation of
the site, has not been implemented yet. These reaction
types includes but not limited to aqueous
complexation, adsorption-desorption, ion-exchange,oxidation-reduction, precipitation-dissolution, acidbase reactions, and microbial mediated reactions.
The main sources of pollutants to the environment
are the open pit, the waste rock damps and the tailings
dam. The waste rock damps and tailing dams mostoften consist of several minerals and geologicalmatrix which are exposed to weathering conditions.
Pyrite oxidation is the principle reaction in theleaching of metal and radionuclides into environment.
Accurate prediction of the release rate of metal andradionuclides from these sources and their transport
into the subsurface environment is a critical factor to
the assessment of environmental impacts and to thedevelopment of effective remediation strategies. To
produce a realistic representation of the system understudy with the existing real complex problems,
sophisticated models are required. Reactive transport
codes are powerful tools in the evaluation of coupledhydrological chemical processes and in the predictionof the long-term performance of remediation

INTRODUCTION
Groundwater plays an important role in humanhistory and groundwater contamination has attracted
intensive investigations in the past 30 years.
Contaminants in the aqueous environment undergochanges in concentration resulting from physical,
chemical, biological processes, and a capability tounderstand and model these processes is at the core ofassessing the efficacy of environmental remediation
strategies. The modeling and prediction of thecomplex multiple species reactive transport process
in mine sites is particularly challenging. The
development of an accurate model capable ofpredicting the transport scenario is very challenging,but a necessity for designing future remediation
strategies. Therefore, a robust numerical multiple
species reactive transport simulation model
HYDROGEOCHEM 5.0 [1] has been calibrated andvalidated for a study area comprising of an underlying
aquifer in a no longer operational mine site in the
Northern Territory of Australia. Acid rock drainage(ARD) and heavy metal mobilization at the former
mine site have led to significant environment impacts
on local groundwater and in the East Branch of theFinniss River [2].
Acid and metalliferous drainage (AMD) also
referred to as acid mine drainage or acid rockdrainage occurs when sulphidic minerals, such asarsenopyrite, chalcopyrite and pyrite, are exposed tooxygen and water. Although AMD occurs naturally,
775

GEOMATE - Mie, Japan, Nov. 21-24, 2017changes over the course of a year [5]. The mine area
mineral field contains polymetallic ore deposits, suchas the Ranger and Woodcutters ore deposits. The
mine site includes the Giant’s reef fault. The main
lithological units are the Rum Jungle Complex andmeta-sedimentary and subordinate meta-volcanic
rocks of the Mount Partridge Group. The Rum Jungle
Complex consists mainly of granites and the Mount
Partridge Group consists of sedimentary units:
Geolsec formation, the Whites formation, the
Coomalie Dolostone, and the Crater formation [6].

strategies.
A presentation of the application of a reactivetransport model to simulate the transport of reactive
multi-species contaminants in heterogeneous,anisotropic, saturated-unsaturated waste rocks damp
and mine open pits of the first uranium mine site inAustralia is illustrated in this paper. The computer
program used to describe the complexhydrogeochemical processes that control thegeneration of acid drainage and the distribution ofsolutes between groundwater and waste rock damp isthehydrogeochemicaltransport
model,HYDROGEOCHEM 5.0. This numerical code has
been earlier used for modeling a mine site in
Queensland Australia [3]. The computer program is a
3-D numerical model of fluid flow, thermal,hydrologic transport, and biogeochemical kinetic andequilibrium reactions in saturated and unsaturated
media.
The purpose of this paper is to focus on thesolution results of reactive transport geochemical
modeling to predict the important complex processes
that control the movement and distribution ofcontaminants in ground water. It is also likely that thiscalibrated and validated transport model will beutilized for a contamination source characterization
study for this contaminated aquifer site. Information
gained from these investigations should also provide
insight into processes that occur at other sites
similarly contaminated.

Fig. 1 Satellite view of the study site
Numerical Simulation
Flow Model
The general equations for flow through saturated–unsaturated media are obtained based on following
fluid continuity, solid continuity, fluid movement(Darcy’s law), stabilization of media, and watercompressibility [1]METHODOLOGY
Study Area Description
The former mine site is located approximately
105km by road south of Darwin in the headwaters of
the East Branch of the Finniss River, near Batchelor
in the Northern Territory, Australia. This former mine
was one of Australia’s first major uranium mines andproduced approximately 3,500 tonnes of uranium and20,000 tonnes of copper concentrate between 1954
and 1971 [4]. Uranium was mined from White's andDyson's open pits from 1954 to 1971, while copper
was extracted from the Intermediate pit in 1964. The
site underwent rehabilitation from 1983 to 1986 at a
total cost of $18.6 million. Several rehabilitation
works have taken place since 1986 and rehabilitationis still on going. [4]    h    K . h 
z  Fq
o t
o  o 
 

(1)

  O o g  o  K k
gK=
KsKr = o  so r O  O
(3)

Where F = generalized storage coefficient (1/L)
defined asdSF=  
(2)    ne
ne
dh
K=

and V = Darcy’s velocity (L/T), described as:
V= - K   o h  z 
(4)
 

Where: : effective moisture content (L3/ L3); h:pressure head (L); z is the potential head (L), t: time(T); q: source or sink of fluid [(L3/ L3)/T]; : fluid
density without biochemical concentration (M/ L3);
: fluid density with dissolved biochemical
concentration (M/ L3); ρ*: fluid density of either
injection (= ρ*) or withdraw (= ρ) (M/ L3); o: fluid

Geological and hydrogeological characterization
The mine areas consist of east branch of theFinniss River about 8.5 km upstream of its confluencewith the West Branch of the Finniss River. Surface
water enters the mine site from the east via the upper
East Branch of the Finniss River and from thesoutheast via Fitch Creek. River flows vary in
response to intra annual variability in rainfall and776

GEOMATE - Mie, Japan, Nov. 21-24, 2017

dynamic viscosity at zero biogeochemical
concentration [(M/L)/T]; μ: the fluid dynamic
viscosity
withdissolved
biogeochemical
concentrations[(M/L)/T];
α’:
modified
compressibility of the soil matrix (1/L); ß: modifiedcompressibility of the liquid (1/L); ne: effective
porosity (L3/L3); S: degree of effective saturation ofwater; G: is the gravity (L/T2); k: permeability tensor(L2); ks: saturated permeability tensor (L2); Kso:
referenced saturated hydraulic conductivity tensor(L/T); kr: relative permeability or relative hydraulicconductivity (dimensionless).The finite element
method was used to solve Eq. (1), (2), (3) and (4), andthe constitutive relationships among the pressure
head, degree of saturation, and hydraulic conductivity
tensor, together with the appropriate initial conditions
and boundary conditions. The temporal-spatial
distributions of the hydrological variables, includingpressure head, total head, effective moisture content,
and Darcy’s velocity were simulated.

November 2014. This numerical flow model is amathematical representation of a conceptual modelthat enables a quantitative representation of real fieldfeatures. The numerical representation is based on thefollowing assumptions: The aquifer system at theformer mine site can be subdivided intohydrostratigraphic units that represent either waste
rock damps or the naturally occurring bedrock aquifer,
each hydrostratigraphic unit is represented as a single
model layer with representative hydraulic properties
and recharge is estimated as a proportion of incident
rainfall, mine waste is represented by a single model
layer of variable thickness of the waste rock damps
and Dyson’s (backfilled) open Pit, whereas thegeological aquifer units is represented by model
layers with constant thicknesses across the model
domain, water movement in the hydrostratigraphic
units follows Darcy’s law, the flooded open pits isrepresented by specified head boundary condition
that is equivalent to observed water levels in the pits
during the simulation period.

Reactive transport Model
Numerical method

Governing equations for the reactive transport of
the reactive biogeochemical system is discussed
below. The equations for transport were derived
based on the continuity of mass and Fick’s flux
laws. The main transport and fate processes areadvection, dispersion/diffusion and biogeochemical
reactions (including radioactive decay). The
general transport equation governing the temporalspatial distribution of any biogeochemical species
in a reactive system is described below [1]:Cih   Ci  LCi   ri  M i , i  M tt

The finite element method is used for temporaland spatial discretization of the governing partial
differential equations in the flow module. The
Galerkin finite element method was used for spatial
discretization of the modified Richards equation thatgoverns the distribution of pressure fields. For thismodel, the critical assumption of this approach is thatevery element within a particular section of a layer isassigned a set of hydraulic properties to account forheterogeneity. The layers are discretized horizontally
into triangular wedge elements but each layer of afinite element mesh is one element thick. The flow of
the groundwater is simulated for the observation
period 2010 and 2014. Two case scenarios of both
steady state and transient flow is simulated for the
flow.

(5)

Where L is the transport operator denoting(6)LCi     VCi     D  Ci where Ci is the concentration of the i-th species inunits of chemical mass per water volume [M/L3]; ri is
the production rate of the i-th species because ofbiogeochemical reactions in chemical mass per water
volume per unit time [M/L3/T]; {M} = {1,2,…,M} inwhich M is the number of biogeochemical species; D
is the dispersion coefficient tensor [L2/T]; and Mi is
the source/sink of the i-th species in chemical mass
per unit volume of media [M/L3/T].

Spatial Discretization
The numerical model domain was spatiallydiscretised into a 3-dimensional mesh with atriangular wedge mesh. In planar view, each element
is a triangular wedge, whereas the thickness of theelements depends on the number of layers used tovertically discretize the model domain. The thicknessof the elements varies depending on lithology. The
model is made up of 6 layers and covers a maximum
elevation of about 110 m. Surface topography from a
recent terrain elevation data was used to define the topof layer 1, including the WRDs and Dyson

Conceptualization and Model discretization

A numerical groundwater flow model isconstructed to simulate variations in the groundwaterflow system at the mine site from December 2010 to777

GEOMATE - Mie, Japan, Nov. 21-24, 2017(backfilled) pit. Figure 2 shows a plan view of finite
element model domain. Layer thicknesses areallocated in this order. Layer 1 which consist mainlyof waste rock damps is assigned variable thickness,layer 2 thickness is from 0 to 7.5 m, layer 3m is 7.5m
to 15 m, layer 4 is 15m to 45 m, layer 5 is 45m to 105
m, and layer 6 is 105m to 150 m. The tops andbottoms of layers 3 to 6 are set to thicknesses values
listed above which is fixed throughout the model.

copper. Table 2 shows some chemical reactions
incorporated in the model.
Table 1 Aquifer hydrogeologic properties
Aquifer parameter
Number of nodes
Number of elements
Horizontal hydraulicconductivity, Kx Ky
Layer 1
Layer 2
Layer 3Layer 4Layer 5Layer 6
Vertical hydraulic conductivity, Kz
Layer 1
Layer 2
Layer 3Layer 4Layer 5Layer 6
Effective porosity, θLongitudinal dispersivity, αLTransverse dispersivity, αT
Vertical dispersivity (αV):
Average rainfall

Boundary conditions

Specified heads boundary conditions is assigned
to elements from layers 1, 2, 3, and 4 that intersects
the perimeters of the flooded pits which includes
main, intermediate and brown oxide pits. Theseelements represent the bedrock aquifer that is incontact with standing water within the pits and wereassigned a head that is equal to the measured waterlevel in the pits. Flows within the flooded open pits
themselves are not simulated by the model soelements within the head boundary are set to beinactive. Pit water levels and groundwater levels atmonitoring locations close are used to represent the
open pit as a head boundary. The browns oxide open
pit is not completely flooded so heads were only
specified for elements in layers 3 and 4. Time varied
constant head nodes are set that simulate water levelchanges in the main, intermediate and brown’s pits
and the river. The aquifer parameters imputed tomodel area is shown in Table 1

Value
6587
10704
m/d
0.01728 - 5.0112
0.00864 - 0.7776
0.00864 - 0.84672
0.00864 -0.84672
0.00864 - 0.02592
0.0001728 - 0.0648
m/d
0.00864 - 0.24192
0.00432 - 2.4192
0.00864 - 0.864
0.00864 - 1.296
0.00864 - 0.20736
0.00864 - 0.0648
0.28
10 m/d
0.1 m/d
0.01
2372 mm/year

Table 2 Chemical reactions involved in transport
Chemical reactions
H2O(aq)  H+ + OHH+ + SO4  HSO4Cu 2+ + H2O  Cu(OH)+ + H+
Cu2+ + SO4 2-  CuSO4
Cu2+ + 2H2O  Cu(OH)2 + 2H+
Cu2+ + 3H2O Cu(OH)3- + 3H+
Fe2+ + H2O  H+ + FeOH+
Fe2+ + SO42-  FeSO4
Fe2+ + 2H2O  2H+ + Fe(OH)2 (aq)Fe2+ + 3H2O  3H+ + Fe(OH)3Fe2+ + 4H2O  4H+ + Fe(OH)42Mn2+ + SO4 -  MnSO4
Mn2+ + H2O MnOH+ + H
Mn2+ + 3H2O Mn(OH)3- + 3H
UO22+ + SO4 2-  UO2SO4
UO22+ + SO4 2-  UO2(SO4)2 2UO2 +2 +2H2O↔ UO2(OH)2 aq + 2H+

Fig. 2 Three dimension finite element representationof the study site
To model and simulate the reactive transport
processes, equations of either the conventional finite
element methods or the hybrid Lagrangian–Eulerianfinite element methods were used for spatial
discretization. The chemical equilibrium equations
were solved by the Newton–Raphson method or
Picard method. This study considers the possiblehydrogeochemical transport of 6 components,
including OH-, Cu2+, Fe2+, Fe3+,Mn2+, UO2 2+ and 20
species are considered in this study. These selected
sets of components are based on the fact that the
primary mining commodities were uranium andConstant
rate(log K)-13.99
1.99
-9.19
2.36
-16.19
-26.9
-9.50
2.20
-20.57-31.00-46.002.26-10.59-34.08
3.15
4.14
12.15

Conceptual Modelling

The transport model for the mine site was built upon
the flow model by including the necessary transportconditions which includes the transport boundary
conditions, the total number of components and thespecies to be simulated. The assumption is that thetransport of the contaminants is based solely on theflow fields simulated whereby there is a possible rockinteraction or mineral interactions with the aquifer
rock bed and formation of daughter products or
778

GEOMATE - Mie, Japan, Nov. 21-24, 2017as well. The model’s boundary conditions areadjusted manually to achieve the calibration targets.
The measured and simulated heads were compared atselected points.
The developed model was calibrated for flow using
observed head data obtained at monitoring points. In
the calibration process, estimates of the values ofrecharge for each recharge zone and therepresentative hydraulic conductivity of each layer
were calibrated. Results of simulated heads
calibration are shown in Table 3.

additional species.
It is assumed that the oxidative dissolution of pyrite
is the driving force in the discharge rate of metal andradionuclides from waste rock damps. The reactive
system is completely defined by geochemical
reactions through a network of reactions specifying
chemical reactions and the total number of chemical
species involved in the reaction. The standard
equilibrium expression with a suitable equilibrium
constant is used to represent all the fast reactions,such as the aqueous complexation reaction andprecipitation of secondary phases. The slow reactions
were represented by the kinetic expression andassociated rate constants to address the dissolution
reactions of key minerals present in the waste rockdamps and pits. The reaction network that describes
the evolution of the geochemical system is shown in
the Table 2.

Table 3 Comparison of observed and simulated heads

RESULTS AND DISCUSSION
The flow model calibration is carried out by runningthe forward simulation repeatedly, and manually
adjusting the input parameters selected forcalibration, including those used to define initial andboundary conditions, at each time, until a satisfactory
match between model results and field data isachieved. The trial and error procedure is used in thisstudy. This is adopted because it is conceptuallystraight forward and requires nothing morecomputationally than making multiple forward
simulation runs. This procedure is flexible allowing
any adjustment in parameter values and parameter
structures, including changes in mesh designs and therepresentation of the geologic frame work
The main aim of calibration was to obtain theestimation of hydraulic conductivity and groundwaterlevels for the aquifer based on limited fieldmeasurement data. Hydraulic head measurement datafrom 20 monitoring locations distributed across themining area were used for the simulation model
calibration. The hydraulic head data used for model
calibration and validation were recorded in 2010 and2014. A portion of the average rainfall intensity per
year was specified as recharge for calibration of thesimulation model also using measured head data frommonitoring locations. Calibration targets for thedeveloped model were set to be within 2m intervalsof the observed hydraulic head value in monitoring
locations with a confidence level of 90%. Exact
boundary conditions are difficult to determine withvery limited observed measurement data. Hence,
realistic boundary conditions need to be specified thatmatches the site conditions. In the calibration process,one of the most difficult issues is to assign
appropriately the correct boundary conditions.
Therefore, the boundary conditions need to be
determined based on preliminarily calibration results

Location
ID
P1a
P1b
P2
P3

observed
head(m)
61.44
62.65
63.27
60.29

P4
P5
P6
P7
P8D

60.41
57
58.33
56.39
53.96

P9D
P10
P11
P12
P13

56.57
57.63
57.16
56.44
56.89

P14
P16
P17
P18
P19

57.06
56.27
56.45
57.28
57.35

P20

51.01

computedhead(m)Residual
(m)

62.48
63.65

-1.04
-1

63.12
64.9
60.86
57.14
59.09

0.15
-0.11
-0.45
-0.14
-0.76

59.05
54.68
56.69
58.03

-2.66
-0.72
-0.12
-0.4

57.87
56.91
56.9
57.55
57.16

-0.71
-0.47
-0.01
-0.49
-0.89

57.29
58.27
58.23
51.69

-0.84
-0.99
-0.88
-0.68

The flow model is calibrated first to adjust the model
input parameters that control the flow process, suchas hydraulic conductivity and recharge, sink/sources
stress. When the flow model is calibrated to a certain
degree, calibration of the transport model isinitialized to adjust those parameters specific to thetransport model, such as porosity, dispersivity andsource concentration. Recalibration of the flow model
is done to further adjust the initially calibrated flow
parameters. After readjustment of the flow
parameters, a new velocity distribution is calculated
and used in the transport model where further
adjustments in the transport parameters are made.
This iterative procedure is repeated until both flow
and transport related field data are matched by thesimulation results. The results of the calibrated heads
779

GEOMATE - Mie, Japan, Nov. 21-24, 2017

against the observed heads is shown in Table 3. These
results show fairly good history matching of thehydraulic heads. The reactive transport model
simulation time is 2 years from 2012 to 2014 as of theavailability of data. The precipitation/dissolution on
the changes of porosity, hydraulic conductivity, andhydrodynamic dispersion of aquifer media may be a
key hydrogeochemical mechanism in the transport
process. Thus, the effect of precipitation/dissolution
reactions on both flow and reactive transport arealso considered in the simulations. Moreover, toevaluate the effect of redox processes influencing on
the formations of degradation materials, pyrite
oxidation, sulfate reduction reactions are also
incorporated in the simulation scenarios.
Copper (Cu2+), sulphate (SO42-), Manganese (Mn2+),
Uranium (UO22+) and Iron (Fe2+) are introduced as
initial contaminants in the waste damp rocks and theopen pits, which is assume to be involved in chemical
reactions listed in Table 2. The assumed initialconditions for contaminant concentration are
specified in the simulation model based on theavailable data and extrapolation within the area. The
sources considered for this study are dysons waste
rock damp, dyson open pit, main waste rock damp,
intermediate waste rock damp, main pit andintermediate pit. The objective was to demonstrate
the flexibility of the model to adapt a known reaction
network to an abandon mine site setting and todemonstrate the capability of the code to simulate
large complex problems. The results of the simulated
concentrations are shown in the Figure 4, Figure 5
and Figure 6.

Fig. 7 Comparison of observed and simulated
uranium concentrations mg/ l at monitoring points
CONCLUSION
The calibrated flow model, and the developed
transport simulation model are capable of simulating
the complex flow and multiple species reactive
transport processes in the geologically complex
multiple layer, heterogeneous aquifer comprising of ano longer in use uranium mine site in NT, Australia.
The aquifer processes are considered as 3dimentional, geologically layered and heterogeneous,with transient flow and transport. It was possible tocalibrate the flow model by using sparse spatialtemporal hydraulic head measurements. The
contamination simulation scenario resembled thefield conditions to a certain extent. The
concentrations predicted for the chosen species matchwith the concentration measurement values available.
Therefore, the simulation model, based on
HYDRGEOCHEM once calibrated for site
conditions, is potentially a good candidate to model
the complex flow and transport processes in ageochemically and geologically complex mine site
aquifer.
ACKNOWLEDGEMENTS
The authors acknowledge the financial support forthis work provided by CRC-CARE, University of
New Castle, Callaghan NSW 2308, Australia andJames Cook University, Australia.
REFERENCES

Fig. 4 Comparison of observed and simulated copper
concentrations mg/ l at monitoring points[1] Yeh GT, Sun J, Jardine PM., Burgos WD, Fang
Y, Li M., Seigel M.D, ( “HYDROGEOCHEM
5.0:AThree-Dimensional Model of Coupled
Fluid
Flow,
ThermalTransport,
andHydrogeochemical Transport through Variably
Saturated Conditions - Version 5.0”, 2004
[2] Kraatz M, “Rum Jungle Rehabilitation Site
Scoping Study, Environmental Issues andConsiderations for Future Management”,
Report to the Department of Industry,
Tourism and Resources, M4K Environmental
Consulting, February 2004.

Fig. 5 Comparison of observed and simulated ironconcentrations mg/ l at monitoring points
780

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Jungle Mine Site, northern Australia”.
Proceedings of 9th International Conference on
Acid Rock Drainage ICARD), May 20-26, 2012,
Ottawa, Canada.
[6] Robertson GeoConsultants Inc., Phase 3 (Stage 2
Report) “Groundwater Flow Model for the Rum
Jungle Mine”, RGC Report submitted to NT DoR,May 2012.

[3] Esfahani HK, Datta B, “Linked Optimal Reactive
Contaminant Source Characterization in
Contaminated Mine Sites: Case Study”, Journalof Water Resources Planning and Management,
Vol 142, Dec. 2016[4] Norther Territory Government. “Rum Jungle
Conceptual Rehabilitation Plan”, May 2013
[5] Ferguson PR, Wels C, Fawcett M, “Current
water quality conditions at the historic Rum

781

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

IMPACT OF LAND LEVELING ON THE WATER BALANCE FORAGRICULTURE IN EASTERN AFGHANISTAN*Shakerullah Hashimi1, Pervaiz Ahmad Naseri 2, Najumuddin Anjum3 and Takamitsu Kajisa4,
Master candidate, Graduate School of Bioresources, Mie University, 514-8507 Kurimamachiya-cho 1577,
Tsu, Japan. 2Project Manager of On-Farm Water Management Project, Ministry of Agriculture Irrigationand Livestock (OFWMP/MAIL) Kabul, Afghanistan. 3 Water Management Specialist (OFWMP/MAIL)
Kabul, Afghanistan. 4Professor of Bioresources, Mie University, 514-8507 Kurimamchiya-cho 1577, Tus,
Japan.

1

ABSTRACTThe aim of this study was to investigate the effect of laser land leveling (LL-leveling) on the vertical movementof water through soil (seepage rate). Although we could have discussed the use of LL-leveling for crop yield andwater efficiency in eastern Afghanistan the difference in seepage was not clear. Therefore, herein, both the waterbalance at the land surface and the impact of LL-leveling on infiltration rates were investigated. The field
experiments were comprised of two parts: Farm-A underwent LL-leveling; and Farm-B was used as the control
farm with all other practices maintained the same. The results from Farm-A illustrate that, from a water balance
perspective, water seepage was reduced due to smaller water inflow, larger farm size or regular farm shape. By
comparing the two farms, we could confirm the linearity of water input to water seepage based on measurements
in both areas. Seepage was reduced with increasing field size. In our data, the water input decreased following LLleveling. This may be strongly related to the water saving mechanisms employed in Farm-A. Further, the areal
size of the farm increased following LL-leveling and potentially also contributed to the observed increase in watersavings. Simultaneously, we could affirm that the seepage is affected by land cultivation practices and the selectionof crop types. Overall, in Farm-A the seepage rates were reduced with LL-leveling by 18%, 77%, and 25% in plots
cultivated for wheat, corn, and eggplant, respectively. Thus, it has become clear that LL-leveling will increasewater savings.
Keywords: Infiltration, Crop Type, Cultivation Age, Irrigation Interval
regional standards. About 20% of both the traditionaland modern irrigation systems require an upgrade of
the on-farm water management in order to improve
the low crop yield or to address water logging andsalinization. In fact, the land production potential
under low and variable rainfall can be improved bypromoting technology transfer [8]-[9]. In traditional
as well as modern irrigation schemes, the dominant
irrigation method is basin/border irrigation for cereals
and furrow irrigation for vegetables and grapes.
Farmers are usually not aware about crop waterrequirements, and over-irrigation is a common
practice.
The overall efficiency is only about 25%–30% forboth modern and traditional irrigation schemes,
resulting in significant water losses and low
productivity [4]. The cropping intensity (it is the ratioof net area sown to the total cropped area) varies
widely between irrigation systems depending onwater availability. It reaches 200% in the upper partof the irrigated area, whereas, in the lower parts, up
to-thirds of the crop area remains fallow each year on
a rotational basis. In the large schemes supplied byrivers, floods often damage irrigated land as a resultof the frequent change in river course due to the highsediment loads and unfavorable geomorphological

INTRODUCTION
The main challenges faced by the Afghan
agricultural sector are the shortage of water and thehigh demand for irrigation water [2]. The country is
not self-sufficient in its water requirements nor is it
relieved from the impacts of its neighbors’. Whileundeniably land-locked, the country has five river
basins of which four major rivers flow intoneighboring countries. However, only a small
proportion (around one third) of the water thatoriginates here is utilized within the country. The
economy of Afghanistan relies mostly on agriculture,
particularly on irrigated agriculture.
Nonetheless, farmers still use traditional farming
techniques wherein oxen provide the draught power.
The farmers’ knowledge of new irrigation
technologies and cultural practices is insufficient.
Consequently, the efficiency of the irrigation system
is quite low (25%–30%) mainly due to highconveyance losses in the traditional watercourses
with earth canals, high operational losses in modern
schemes with lined conveyance canals, and high onfarm distribution losses (e.g., over-irrigation, poorly
leveled land) in both traditional and modern irrigation
schemes. The productivity levels are low even by782

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Afghanistan in 2016 on crop yields and water
efficiencies in LL-leveled areas did not confirm adifference in the vertical movement of water throughsoil (seepage rate). Thus, herein, the water balance atthe land surface and the effects of LL-leveling on
seepage rates have been investigated. The current
research was undertaken at the irrigation
demonstration site of the on-farm water management
project in the Barabad village, (Bihsud district,Nangarhar Province; Fig. 1). The objective of thisstudy is to investigate the vertical movement of water
into soil in relation to cultivation age, the durations of
the irrigation interval, water inputs, and crop type.

conditions[8]-[9].
Traditional
management
approaches to irrigation supply and conveyance often
contribute to high-water losses.
Moreover, low irrigation efficiency is further
accentuated by traditional irrigation methods andpractices used by farmers, as well as inadequate landleveling [12]. Water scarcity can be overcome by
improving water use efficiency at the field level [11].
With traditional applications of water to the fields,
crop yields decrease by 75%–85% on average, a
percentage that varies widely among farms.
Furthermore, poor farm designs and uneven fields
are responsible for 30% of the water losses [6]. About
18 million acre-feet of water are lost while irrigating
uneven fields in Pakistan [3]. Due to the low water
use efficiency and lack of inputs (chemical fertilizer,
improved seed and so on), crop yields are very low.
At present, drought has caused a further reduction incrop yields, e.g., the average yield of wheat is 0.8
tons/ha today as opposed to about 1.1 tons/ha in 1978.
The total area (irrigated and rainfed) cultivated for
cereal crops is about 3.39 million ha. The total cereal
production is 4.15 million tons, 2.65 million tons ofwhich are from wheat [8]-[9].
Irrigated agriculture is the mainstay of foodsecurity and income for most of the rural populationin Afghanistan. It accounts for more than half of thecountry’s GDP and 70% of the total crop production;
moreover, it provides a reliable and sustainableproduction base for several rural communities. The
total cultivable area of Afghanistan is about 8 million
hectares, which is 12% of the total area of the country.
Nearly 3.9 million ha of cultivated land exists in
Afghanistan, of which 1.3 million ha is rainfed and2.6 million ha are irrigated. This irrigated area
produces almost 85% of the total agricultural
production [10]. LL-leveling and agricultural
technology transfer programs were implemented
from 2008 to 2011 for wheat crops in the Kama
district (Nangarhar and Balkh provinces,Afghanistan). During this period, the maximum
reported wheat yield was 6.18 tons/ha and theminimum was 4.01 tons/ha [7].
LL-leveling and layout improvements wereconducted in the Bihsud district (Nangarhar province,
Afghanistan). Yields of 41, 5.25, and 4.4 tons/ha werenoted for eggplant, corn, and wheat respectively. The
water savings found in these fields were 17%, 27%,
and 21% for eggplants, corn, and wheat, respectively[13]. Seepage is the lateral movement of subsurface
water in soil, whereas, percolation is the verticalmovement of water beyond the root zone to the watertable, and the two are often inseparable [17].
Percolation losses have been reported to vary from
0.1 to several hundred mm/day [16]. These rates canbe decreased by increasing the resistance to water
movement in the soil and by reducing the hydrostaticpressure of the ponded water [1].
However, studies conducted in eastern

MATERIALS AND METHODS
The field experiments were conducted in theeastern region of Afghanistan from November 2013
to September 2014, shortly after LL-leveling. The
experimental farms are located in the Barabad village
under the agriculture command area of the Barabad
irrigation canal near Jalalabad city, Nangarhar
province, Afghanistan (34.27° N, 070.24° E,
elevation = 572 m). The region is classified as a semiarid, Mediterranean-type climate with an annual
maximum air temperature of 42°C, an annual
minimum air temperature of −2°C, and an annual
precipitation varying from 178 mm to 324 mm. The
monsoon begins in January and lasts until May, withlittle rain during the summer season. The wind speed
is roughly 30 km/h, and the maximum wind pressure
occurs between July and November [5].
Prior to the final selection of the experimental
farms, a total of 29 fields, 14 water channels, 39 water
inlets, about 116 boundaries and approximately 752
m2 of fields were mapped (Fig. 1). Following layout
improvements and LL-leveling, a total of 12 fields, 2
water channels, 12 water inlets, and approximately
1925 m2 of fields were mapped (Fig. 2). The research
was conducted on two separate agricultural farms thatwere both located along a main irrigation canal. The
field experiments included two parts. The first part
involved the Farm-A layout improvement, and thesecond part involved LL-leveling.
LL-leveling is also called laser-guided landleveling or precision-custom farming laser landleveling, and it is a process applied for smoothing aland surface up to ±2 cm from its average elevation
with the help of a laser-guided drag bucket.
The entire Farm-A was investigated before
commencing the actual experiment. Permanent
benchmarks were installed and a detailed topographic
map was created using a total station theodolite (TST).
Next, the features of Farm-A were designated on themap, and detailed information specified about theslope, the elevations of the low and high spots of the
fields, the number and sizes of the fields, the numberof water inlets, and the available water channels.
The main and secondary water channels were783

GEOMATE - Mie, Japan, Nov. 21-24, 2017

surveyed using the same approach, and their profiles
were developed. The water channels were designed
for earthen lining, and each field in Farm-A wascarefully analyzed to improve the farm’s layout. With
the new layout, the size of each field was expanded,
and regular straight boundaries were created acrossall the fields. Moreover, the water inlets and control
structures were considered as suitable points for the
installation of the farm’s irrigation system. They wereselected based on the irrigation demand.
The cut-and-fill soil ratio of the low and highpoints was calculated for each field and displayed in
the site plan to facilitate field leveling for themachinery operators. Both the irrigation channels andthe water inlets were adjusted based on the quantityof water required for the fields. In addition, the water
channels were earthen improved, and brick water
inlets and a control structure were proposed.
Following layout improvements, water channels(contour, unwanted bunds, and water inlets) were
removed. In the next stage, rough leveling and LLleveling were applied. To implement LL-leveling, themaximum elevation difference between the different
land points should not be above 12–15 cm. In thisstudy, however, most of the selected fields indicatedgreater differences in elevation.
In order to solve this problem, another tractor was
hired to plow and make the soil soft for leveling. All
the fields were laser-leveled, and their sizes increased
to at least 0.19 ha. Hence, 12 fields were establishedinstead of 29 (Figs. 2 and 3). All unnecessary water
channels, undesired field boundaries, water inlets,and ditches were removed, and new straight fieldboundaries were created. The laser-leveled fields inFarm-A were chosen to observe the impact of LLleveling, and the un-leveled fields in Farm-B wereselected as the controls (Fig. 1).
The soil texture of the experimental farms are
predominantly sandy loam soil. Crop fields arearranged in a rectangular shape and are about 2054,
2052, 1924 m2 in LL-leveled Farm-A and nearly 1875,
2000, 1680 m2 in un-leveled Farm-B. The conditionof the crops was kept equal across both farms.
A cutthroat flume was used to determine the water
depth (WD) applied to the irrigation. The flume wasinstalled in a uniform, straight, and vegetation-freechannel. The flume sides were entirely stoppered withdirt to prevent water leakage from the sides andbeneath the flume. The flume was installed at
appropriate points to maintain free-flow conditions
and to facilitate flow calculations. Whenever, thewater flow became stable, constant readings wererecorded; five to six readings were taken during
irrigation periods. The duration of irrigation wasrecorded, and the area of the fields was measured by
TST. Then, the depth of the applied water was
calculated for each irrigation line using thehydrologic formula given in Eq.1.
While the number of irrigation bouts wererecorded 4, 5, and 8 in the both areas, the WD was not
equivalent. Farm-A received 283, 334, 570 mm of
WD while Farm-B received 319, 394, and 650 mm of
WD in wheat, corn, and eggplant fields, respectively.
In the next step, the climate parameters needed for the
calculation of the water seepage rate were
downloaded from the meteorological station of the
National Climatic Data Centre (NCDC) [14]. Missing
parameters were calculated with the help of the daily
Penman-Monteithevapotranspiration
equation(FAO-56 method) [15]. The seepage rate for both
farms was simulated with the help of the unsaturated
water balance Eq. 2.
(1)
Where is the discharge (m3/s), is the irrigation
duration is seconds, is the field area (m2), andis the applied WD (mm).
1000

∆
∆

(2)

Where P is precipitation over the time interval ∆(mm),
is evaporation from the land surface(mm/d),is lateral inflow of surface water into theis lateralwater balance area ( ) (m3/day),outflow of surface water from the water balance area( ) (m3/d), is the water balance area (m2), and ∆is the change in surface water storage (mm).

Fig. 1 Layout of Farm-A before LL-leveling [13].

Fig. 2 Layout of Farm-A after LL-levelling [13].

784GEOMATE - Mie, Japan, Nov. 21-24, 2017

B

A

Fig. 3 The location of Farm-A and Farm-B, in Nangarhar, Afghanistan (latitude 34. 27° N and longitude 070.24°
E; elevation = 572 m; Source: Google maps, 2016 [13].
Table 1 WD and mean seepage from Farm-A and Farm-B
Crop

Wheat
Corn
Eggplant

Farm-A (Leveled)
Plot
area
size
(m2)
2054
2052
1924

Irrigation
MethodIrrigation
numberbasin
basin
furrow4
5
8

Used
irrigation
depth
(mm)
283
334
570

Farm-B (Un-leveled)Mean
seepagerate(mm/day)
1.6
0.3
3.0

Plot
area
size
(m2)
1875
2000
1680

Irrigation
Number4
5
8

Used
irrigation
depth
(mm)
319
394
650

Mean water
seepage (mm/day)
2.0
1.2
4.0

seepage rate recorded was around 3 mm/day, and thelowest was nearly 1.5 mm/day and occurred in
November and December, respectively.
In addition, the seepage rates calculated forJanuary and February were 1.6 and 1.9 mm/day,
respectively. Hence, in Farm-A, the seepage rate was
reduced by 17.5% compared to Farm-B.
Next, the eggplant seepage rate was computedfrom May to late July for both farms. The highest
seepage rate was more than 4 mm/day in May.
However, during the next irrigation bout in early June,
the seepage rate declined considerably to 1 mm/day
and then gradually increased to approximately to 4
mm/day by mid-June. After mid-June, the seepage
rate steadily declined again and reached about 1
mm/day in late July. Whereas, in Farm-B, the highest
seepage rate of 6 mm/day was observed in May andthe lowest rate of 2.5 mm/day was observed in June.
The last crop that was planted was corn. The
highest seepage rate observed in the corn field was
1.5 mm/day in July and the lowest was −0.6 mm/day
in late June. Over the next months, the seepage rate
fluctuated throughout the complete season of crops.

RESULTS
Temporal changes in infiltration rates
Figure 4 represents the vertical movement ofwater through soil (seepage rate) in relation to various
times of the year in both the leveled (Farm-A) and in
the un-leveled (Farm-B) fields. The seepage rate ofused-irrigations was observed shortly after thecompletion of LL-leveling in the wheat, eggplant, andcorn fields.
The first seepage rate in Farm-A was observed in
the wheat field. The seepage rate for the very firstirrigation, which was applied in November, peaked atabout 2.7 mm/day. However, during the next
irrigation bout in the following month, the seepage
rate declined to around 1.4 mm/day. While during thethird irrigation bout the seepage rate stayed constant,the seepage rate dropped substantially to 1 mm/day
during the last irrigation bout. Whereas, in Farm-B,
the seepage rate was consistently higher across allcrop types than that in Farm-A. In Farm-B, the largest
785

GEOMATE - Mie, Japan, Nov. 21-24, 2017

In contrast, the corn crop displayed the lowest
seepage rates throughout the complete season
compared to the other two crops in both farms. In
Farm-A, the seepage rate for the WD of 80 mm wascalculated as 2 mm/day, and for the lowest WD of
about 60 mm the seepage rate was calculated as −0.6mm/day. Whereas in Farm-B, the equivalent lowest
and highest WDs were 65 and 98 mm, respectively.
The concurrent highest and lowest seepage rates were
2 mm/day and −0.60 mm/day, respectively. The
overall WD and seepage rates of the remaining
irrigation bouts were considerably lower in Farm-A
than in Farm-B.
As a result, in Farm-A, the seepage rate was
reduced by an average of 24%, 17.5%, and 40% in thewheat, eggplant, and corn fields, respectively. The
seepage rate was, however, found to be directly linear
to water intake.

In Farm-B, the highest seepage rate calculated was
2.6 mm/day in mid-June and the lowest seepage ratewas −0.7 mm/day in late June. In the other months,
the seepage rate fluctuated. As a result, the seepage
rates in Farm-A were 22% lower than in Farm-B.
Across crop types, the seepage rate was highest in
the initial month and then fluctuated throughout theremainder of the growing season in both farms.
Further, the average seepage rate of any crop in FarmA was consistently lower than that of Farm-B. In thedays following wheat harvesting and prior to theplanting of the eggplant and corn, an increase in
seepage rates was observed.
8.0

4.0

8.0

2.0
0.0
Aug-13-2.0

Nov-13Mar-14Years
Wheat (A)
Eggplant (A)Corn (A)Jun-14seepage rate mm/day

seepage rate mm/day

6.0

Sep-14

Wheat (B)
Eggplant (B)Corn (B)

6.0
4.0
2.0
0.0
-2.0

Fig. 4 Cultivation age vs seepage rate (mm/day).
Used-WD

0.0

50.0

100.0

150.0

Applied WD (mm)Wheat (A)
Wheat (B)
Eggplant (A)Eggplant (B)Corn (A)Corn (B)Fig. 5 Relationship between seepage rate (mm/day)and applied WD (mm).

Figure 5 illustrates the relationship between
seepage rate and WD in both farms. The colored anduncolored solid shapes of the diamond, square, andtriangle markers, represent the seepage rate relative towater intake over the whole growing season for wheat,corn, and eggplant in Farm-A and Farm-B,
respectively.
Across all crop types, with an increase in water
intake, the seepage rate increased. For instance, thehighest observed seepage rate of the eggplant inFarm-B was 6 mm/day concurrent with a peak WD atnearly 90 mm. Likewise, in Farm-A, a similar relation
was observed, however, the measured water intake
and seepage rate were 15 mm and 2 mm/day lower
than in Farm-B, respectively.
In Farm-A, the highest seepage rate for wheat wasdetermined to be 2.4 mm/day concurrent with a WD
of 90 mm. While, in Farm-B, the highest seepage rate
was around 3 mm/day with the WD being almost 100
mm. During the next irrigations, the applied WDs in
Farm-A were computed as about 64, 77, and 55 mm
with concurrent seepage rates of 1.5, 1.4 and 1
mm/day, respectively. Whereas in Farm-B, thecalculated seepage rates were around 2, 1.7, and 1.5mm/day concurrent with WDs of 75, 80, and 70 mm,
respectively.

Irrigation Interval
Figure 6 indicates water seepage rates relative tothe duration (in days) of the irrigation interval overthe period of growing season of wheat, eggplant, andcorn in both farms. The duration intervals between
irrigations were maintained equivalent across all
crops.
In general, the most and the least number of days
between irrigations among crops were noted for thewheat and eggplant crops as 33 days and 9 days,
respectively. Conversely, the lowest seepage ratemeasured was less than 1 mm/day for an 11-day
interval and the highest was about 6 mm/day for a 10day interval in corn and eggplant fields in Farm-A andFarm-B, respectively. Overall, the highest seepage
rates per number of interval days were always
observed in Farm-B.
In the wheat field in Farm-A, the lowest irrigationinterval was 24 days and the highest 33 days.
However, the lowest seepage rate of 1 mm/day wasobserved in the 26-day irrigation interval. On theother hand, the highest rate of 2.7 mm/day was786

GEOMATE - Mie, Japan, Nov. 21-24, 2017

observed in the 24-day irrigation interval. Whereas,in Farm-B, the lowest seepage rate of 3 mm/day, wasobserved in the 33-day irrigation interval.
During other irrigation bouts, the interval
between irrigations and the seepage rate either
remained equal or fluctuated slightly In Farm-A, theseepage rate decreased by an average of 23%.
Similarly, in the corn fields of both farms, thenumber of irrigations were five and the highest andlowest irrigation intervals were 20 days and 11 days,
respectively. Remarkably, the seepage rates did not
remain equal. In Farm-A, the highest seepage rate
was 1.27 mm/day and occurred in the 12-day
irrigation interval, and the lowest rate of −1.22mm/day was observed in the 20-day irrigationinterval. Nonetheless, for the 11-day irrigationinterval, the seepage rate was 1.25 mm/day. Whereas,in Farm-B, the highest seepage rate discovered was
2.6 mm/day and occurred in the 11-day irrigationinterval and the lowest as −0.6 mm/day and occurredin the 18-day irrigation interval. In both farms, for the
next irrigation bouts, the irrigation intervals, and theseepage rates did not remain stable. In Farm-A, theseepage rate was considerably lower than in Farm-B.
The number of irrigations counted in the eggplant
field was eight. The highest irrigation interval
recorded was 12 days and the lowest recorded was 9days in both farms. In Farm-A, the lowest seepage
rate of 0.8 mm/day occurred in the highest irrigationinterval, and the highest seepage rate of 4.7 mm/day
occurred in the lowest irrigation interval. Whereas, in
Farm-B, the highest seepage rate of 5.8 mm/day
occurred in the 9-day interval and the lowest rate of
2.1 mm/day occurred in the 12-day irrigation interval.
During the remaining irrigations, the interval days
were all similar, while the water seepage rate differed.
In Farm-A, the seepage rate decreased by an averageof 26% during each irrigation.

Land area size
Figure 7 depicts the effect of different land areal
size on seepage rates in fields for three different crops,
namely wheat, corn, and eggplant across both farms.
The field size is shown in m2 and the water seepage
rate in mm/day.
The lowest seepage rate (1 mm/day) was observedin the larger sized field (2000 m2) and the highest
seepage rate (6 mm/day) was observed in the smallest
sized field (1680 m2).
In Farm-A the highest seepage rate (2.7 mm/day)
was observed in the smallest sized field (1900 m2) ofthe eggplant crop. In addition, the lowest seepage rate
(1.31 mm/day) was found in the biggest sized field(2054 m2).
Similarly, in Farm-B, the highest seepage rate (3.7mm/day) was recorded in the smallest sized field(1680 m2) and the lowest seepage rate (0.9 mm/day)
was observed in the largest sized field (2000 m2).
Hence, the areal land size has a relation to theseepage rate, with increasing field size corresponding
to lower seepage rates.
7.0
seepage rate mm/day

6.0

seepage rate mm/day

5.0

2.0
1.0
0.0

-1.0 0

500

1000

1500

2000

2500

Area m2
Wheat (A)
Wheat (B)
Eggplant (A)Eggplant (B)Corn (A)Corn (B)DISCUSSION

4.0

The simulation results of this study provide
information regarding the losses of water throughseepage from irrigated wheat, corn, and eggplant
fields of both farms. These results highlight important
aspects of seepage rates relative to temporal changes,
seasonal fluctuations of WD, different field sizes, andthe variation in the duration interval between
irrigation bouts. The findings of this research indicatethat seepage rates could differ with WD in the fields
affected by seasonal fluctuations in the field watercontent.
Consequently, the same field may lose different
volumes of water at different times of the year; strong,
dry soil conditions could rapidly increase water
seepage losses in the field, and conversely, strong,

3.0
2.0
1.0

-2.0

3.0

Fig. 7 Relation between land area (m2) and seepage
rates (mm/day).

6.0

0.0

4.0

-2.0

7.0

-1.0 0

5.0

10

20

N (day)Wheat (A)
Eggplant (A)Corn (A)30

40

Wheat (B)
Eggplant (B)Corn (B)Fig. 6 Duration of irrigation interval (days) vsseepage rate (mm/day).

787

GEOMATE - Mie, Japan, Nov. 21-24, 2017

choice of crop types. For example, the water seepage
rates for wheat, corn, and eggplant were, on average,
1.6, 0.3, and 3 mm/day in Farm-A, respectively.
Whereas, in Farm-B, the rates were 2, 1.2, and 4
mm/day, respectively (Table 1).
Therefore, it has become clear that the LLleveling contributes to increased water savings andcan decrease seepage rates through the soil by
maintaining slow seepage rates, small water inputs,
and longer soil moisture conditions.

wet soil conditions can cause very low, even negative,
seepage losses. In our data, across all crop types, theseepage rate was higher just after LL-leveling andthen quickly decreased during the following
irrigations. We think that this fast reduction inseepage rate may be due to high antecedent watercontent in the soil from the previous irrigation. Before
LL-leveling, the fields were not irrigated for morethan three months nor was there any rainfall, hence,the soil was very dry.
In addition, the seepage rates in Farm-A wereconsistently lower than those in Farm-B, across allcrop types. It could be suggested that this may haveresulted from a positive effect of LL-leveling because
in the laser-leveled field, moisture was more uniform
and lasted for a longer time than in Farm-B. Moreover,it may also be a result of the development of a
hardpan layer under the plow layer in the laserleveled fields.
Further, as the LL-leveling increased the size ofeach field in Farm-A the water intake and the seepage
rates decreased. The seepage rate dropped withincreasing field size in both farms. In our results, theintake of water declined and the irrigation duration
became shorter because of LL-leveling. There were
understandable variations between the two operations
at the time of irrigation and after irrigation. Thesechanges, even though small, may be an indication of
the advantages brought by LL-leveling. We could
purpose that with an increase in field size, water
intake and water seepage rates may become lower.
Furthermore, seasonal WD, that was measured
separately, resulted in a difference in the amount ofirrigation water applied in both farms. Farm-A
received 283, 334, and 570 mm WD, while, the FarmB received 319, 394, and 650 mm WD in wheat, corn,and eggplant fields, respectively. We believe thatthese reductions in water intake could be a result of
the leveled land surface in Farm-A, which provided amore appropriate environment for water to flow
across the surface and to reach all corners of a field
equally. The total number of irrigation bouts used forthe crops were considered the same (4, 5 and 8) inboth farms because the farmer did not separate out theirrigations. By comparing this variation, we could
verify both the smaller WD in Farm-A and thelinearity of WD to the seepage rate that was measured
in both farms (Table 1).
Toward the end of the experiment, reports fromthe farm’s irrigator indicated that the water was
becoming difficult to manage in Farm-B, despite thesmall visual changes in, for instance, plant growth,plant height, canopy cover, tillers, and grain sizes.
This may also be attributed to LL-leveling. Since thesame varieties were sown in both places, differencesin yield are most likely due to the optimal crop soil
moisture in laser-leveled fields. At the same time, it
could be suggested that the order of the seepage rateis affected by both land cultivation practices and the

CONCLUSION
LL-leveling plays a substantial role in decreasing
the loss of water in soil due to seepage, by
manipulating the high-water input. In addition, LLleveling can precisely level land and allow for theestablishment of larger fields than usual in those areas.
The larger field size can help reduce irrigation
duration and the amount of water required, by
slowing the seepage rate in the soil. Additionally, LLleveling can distribute water more uniformly in soil,
which can support moisture in the soil for longer
periods of time.
Moreover, in the laser-leveled field a crop can
resist a longer period without water than in an unleveled field. This implies that the duration of theirrigation interval in days between irrigations can belonger, which can assist farming communities,
especially where water intensive practices last forextended periods of time. Furthermore, in a laserleveled field, the seepage rate can decrease with anincrease in crop cultivation age, which is not clear for
an un-leveled field. However, the application of
traditional land practices can adversely affect water
inputs, irrigation duration, cultivation age, andseepage rates.
The results of the present study indicate that, froma water balance perspective, seepage rates werelowered across crop types in the leveled fields. Such
practices can, further result in increased water savings,
the tackling of water shortage problems, the delivery
and access to adequate and reliable water, andincreased crop production per unit water and per unit
area. More importantly, it could provide an
opportunity to downstream farmers to have access toirrigation water, thus, minimizing water conflicts andexpanding cultivable area.
In summary, LL-leveling is a proper practice thatcan save water by reducing seepage losses,
minimizing irrigation duration, decreasing water
inputs, maintaining uniform soil water distribution,
preserving soil moisture for longer periods of time,and by creating a hardpan layer that is more resistantto water movement in the soil. This is a promising
approach to using available water more efficiently
and effectively in areas where water scarcity is aserious problem for agricultural production. These
practices should be the best options to produce more
788

GEOMATE - Mie, Japan, Nov. 21-24, 2017with less water.
Working paper 49, Pakistan country series No.
14, IWMI, 2002.
[10] Rout, B. Water management, livestock, and theopium economy. How the water flow: A
typology of irrigation systems in Afghanistan
Research and Evaluation Unite (AREU).
Synthesis paper series. Kabul, Afghanistan,
2008.
[11] Rana, M., Arshad, M., & Mausd. Effect of basin,
furrow and rain gun sprinkler irrigation systemon irrigation efficiencies, nitrate-nitrogenleaching and yield of sunflower. Pakistan
Journal of water resources. Vol. 10, No.2, 2006,
pp. 1.
[12] Wolf, P., & Stein, T. Improving on farm water
management. A never-ending challenge. Journalof Agriculture and Rural Development in thetropic sand and sub tropic. Vol. 104, No. 1, 2003,
pp. 34.
[13] Shakerullah Hashimi, Homayoon Ganji, Kondo,
Ryoei Ito and Takamitus kajisa, Laser landlevelling for crop yield and water efficiency ineastern Afghanistan. International Journal of
GEOMATE, Tsu, Mie, Japan. Vol. 13, Issue. 36.
2017, pp 116-121.
[14] National Climate Data Centre (NCDC), country
Afghanistan, Jalalabad station No. 691166.
[15] FAO Irrigation and Drainage Paper No. 56,
Chapter 2, Equation 6, pp 24.
(https://www.ncdc.noaa.gov/CDO/cdosubqueryrouter.cmd).
[16] Sharma, P.K., De Datta, S.K. Effects of puddlingon soil physical properties and processes. Soilphysics and Rice. IRRI, Los Banos, Philippines,
1985, pp 217-234.
[17] Wickham, T.H., Singh, V.P. Water movement
through wet soils. Soils and rice. IRRI, Los
Banos, Philippines, 1978, pp 337-357.

ACKNOWLDGEMENT
The authors appreciate the tireless support fromthe technical team of On-Farm Water
Management Project and the Ministry ofAgriculture Irrigation and livestock of
Afghanistan for giving chance for conducting thisstudy.
REFERNCES[1] Anbumozhi, V., E., Tabuchi, T. Rice crop andyield as influenced by changes in ponding water
water depth, water regime and fertigation level.
Water manages. 1998.37, pp 241-253[2] Azimi, A. & McCauley, D. Afghanistan natural
Resources comprehensive need assessment final
Report. Published by Asian Development Bank.
No.010103. Afghan Digital Libraries, 2002, pp
9.
[3] Gill, M. water for life. Proceeding of seminar on
world food day. Directorate of Agriculture
Information. Dept. Agric. Govt. Panjab, India.
[4] National Development Strategy Article No. 114,
Afghan water law, 2005.
[5] Khaurin, E. Trees and Bushes of Afghanistan.
Forest National Coordination Office, FAO,
Kabul, 2003, pp 9-13.
[6] Asif, M., Ahmad, M., Gafoor, A. & Aslam, Z.
Wheat productivity, land and water use
efficiency by traditional and LL-levelling
techniques. Online Journal of Biological
Sciences (Pakistan), Vol. 3, No. 2, 2003, pp 141164.
[7] Prepared by New Mexico State University final
report of Afghanistan water, agriculture, andtechnology transfer, 2011, pp 13.
[8] Qureshi, A.S. Water resources management in
Afghanistan. The issues and options.
International water resource institute. Working
paper 49, Pakistan country series No. 14, IWMI,
2002.
[9] Qureshi, A.S. Water resources management in
Afghanistan. The issues and options.
International water resource institute.

Copyright © Int. J. of GEOMATE. All rights
reserved, including the making of copies
unless permission is obtained from the
copyright proprietors.

789

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PREDICTORS OF BEHAVIOR INTENTION TO
DEVELOP GREEN UNIVERSITY:
A CASE OF UNDERGRADUATE UNIVERSITY IN THAILAND
Weerawat Ounsaneha1, Nahathai Chotklang1, Orapin Laosee2, Cheerawit Rattanapan2
Faculty of Science and Technology, Valaya Alongkorn Rajabhat University under the Royal Patronage,
Klong Nuang, Klong Luang, Pathumthani, 13180, Thailand,
2
ASEAN Institute for Health Development, Mahidol University, Salaya, Phutthamonthon, Nakhonpathom,73710, Thailand
1

ABSTRACTThe aim of this study is to identify the level and predictor of behavior intention to develop green university ina case of undergraduate university in Thailand. The university students and staffs in Valaya Alongkorn Rajabhat
University under the Royal Patronage, Thailand were included as the participants in this study by structure
questionnaire with the six major criteria of the UI GreenMetric World University Ranking. The best predictor
factors of dependent variable was performed and find out by multiple logistic regression. The results showed thatthat positive attitude towards transportation and education were found to be the significant predictors of intention
to develop green university behavior. This finding implied that the preparation stage with identification of
behavior intention to develop green university of UI GreenMetric World University Ranking should be promoted
and provided the opportunity for succession of green university.
Keywords: Behavior Intention to develop Green University, Undergraduate University, Valaya Alongkorn
Rajabhat University under the Royal Patronage, Thailand, UI GreenMetirc World University Ranking.
METHODSINTRODUCTION
For almost three decades, the sustainability
society concept was recognized and highlighted forthe significant role of higher education organizationand then represented the opportunity for generating
the behavior change based on the daily life attitude
toward sustainable development [1,2,3]. Besides, theenhancing concern on many environmental problems
should be generated knowledge and integratesustainability performance in educational andresearch programs, as well as promoting
environmental view to the society [4]. Hordijk [5]identified that the knowledge of the university
community was the key role of sustainable campus
with ecological and social challenges in the future.
Currently, the concept of green university have been
initiated in the worldwide. Universitas Indonesia(UI) developed the UI Green Metric World
University Ranking for universities to share
information about their sustainability practices withthe basis of Sustainability for Higher Education [6].
However, a green university initiative may be thebest tool for everyone when universities are wellprepared for it. Hence, only 15 universities inThailand involved in this ranking on the process in2014 [7]. Lack of researches was found on the
preparation stage of green university development inThailand. Therefore, this study was to identify thelevel and best predictor of behavior intention todevelop Green University in a case of undergraduate
university in Thailand.

A Case Study Setting
Valaya Alongkorn Rajabhat University (VRU)
under the Royal Patronage, Thailand was included
as a case study of this research. This university
located at Pathum Thani province and northernborder of Bangkok. The main type of VRU students
is the undergraduate degree. VRU had not yet
entered and will strongly purpose to participate in
the ranking system of UI green in 2018. Hence, thebehavior intention to develop green university
assessment was the preparation stage of UI green
participation for this university.
Sample size calculation and procedure
Taro Yamane’s equation [8] was used to
calculate the sample size of VRU participants andpresented in (1)n = N / 1+ N (e)2(1)
n = 14,000/1+14,000(0.05)2= 700 people
Where n is the sample size; N is population size,and e is level of precision; 95 % confidence levelwith a precision rate of ±5 % and 0.5 of degree ofmaximum variability.
Therefore, the sample
participation in this study was 700 people including
280 staffs and 420 students by the proportion to size.
For sample size procedure, VRU staffs or students
790

GEOMATE - Mie, Japan, Nov. 21-24, 2017education were nearly two time more likely tosupport green university (Adj. OR 1.55; 95%CI:
1.09-2.18, 1.86; 95%CI: 1.33-2.59) (Table 2)
because the public transport promotion in theuniversity should be the potential of UI green
implementation [6].
It can be concluded that the identification of
behavior intention to develop green university of UIGreenMetric World University Ranking should bepromoted for the preparation stage. More positive
attitude and behavior would be the increase thepotential of green university implementation. The
initiative would be planed the successful strategy
and encouraged the world sustainability.

who had been worked or studied in this university
for at six months were invited to fill thequestionnaire with no incentive. The simple random
sampling was used to include the participant in thisresearch in the main cafeteria of VRU during 1
weeks.
Data collection tool and analysis
The data collection questionnaire of this study
consisted of three sections. The general informationof participant including eight question was collectedin the first section of questionnaire. The second andthird sections were the forty-three questions ofattitude and fourth questions of behavior intention todevelop green university, respectively based on the
UI green categories including (1) Setting andinfrastructure; (2) Energy and climate change; (3)Waste management; (4) Water management; (5)Transportation; and (6) Education. Reliability tests
of attitude and behavior parts were 0.7 ofConbrach’s Coefficient-Alpha formula.
Statistical analysis of this study was performed
by SPSS software. The descriptive statistics wasused to assess the level of knowledge and behavior
intention to develop green university. Associationand strength of the relationship between factors wasdetermined by Chi-square and logistic regression.
Finally, the best predictor factors of dependent
variable was performed and find out by multiple
logistic regression.

Table 1 Demographic information of the participant
Information
Number
Percent
Sex
Male
228
32.6
Female472
67.4
Age (Year)
18-20
351
50.1
21-30
218
31.1
31-40
102
14.6
41-50
29
4.1
Education
Bachelor
481
68.7
Master
199
28.4
Ph.D
20
2.9
StatusStudent
420
60.0
Staff
280
40.0
House type
Home
271
38.7
Condominium
102
14.6
University
47
6.7
dormitory
Rent home57
8.1
Private dormitory
223
31.9
Transportation
touniversity
Car
63
9.0
Motorcycle
187
26.7
Bicycle49
7.0
Public transport
319
45.6
Other
82
11.7
Transportation
inuniversity
Car
37
5.3
Motorcycle
155
22.1
Bicycle67
9.6
Public transport
41
5.9
Other
400
57.1

RESULTS AND DISSCUSSION
Based on the data of questionnaires (Table 1),more than 67 % of participants were female. Most ofthem (50.10 %) were in the age group of 18 – 20years old. Concerning the participants’ background,most of them (68.7 %) were educated in undergirded
level. Almost of participants (31.9 %) lived at homeand more than 45.6 % used the public transportation.
Besides, the results presented that the knowledge
levels in the six categories of UI green university
were moderate. Most of the participants (52 %) had
good behavior intention to develop green university.
Participants who were female, having positive
attitude toward setting and infrastructure, energy andclimate change, waste management, transportationand education intended to support green university.
This finding was according to the results of Mamat
et al. [9]. This study mentioned that green officepractices have the highest in the categories of solid
waste management, water resources management
and education and awareness. By multiple logistic
regression analysis revealed that female were 1.4
times more likely to support green university (Adj.
OR 1.21; 95%CI: 1.00-2.01) because males wereconsidered as primary destroyers of the environment,
while females were deemed as secondary users of
the environment [10]. In addition, those who had
positive attitude towards transportation and791

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 2. Association and predictor with behavior intention to develop green university
FactorSex
Male
FemaleAge (Year)
18-30
30-50
Education
Bachelor
More than bachelor
StatusStudent
Staff
House type
Home/Condominium
Dormitory/rent house
Transportation to university
PublicOwnerTransportation in university
PublicOwner
Attitude to Green University
Setting and infrastructure
Low
High
Energy and climate change
LowHigh
Waste management
Low
High
Water management
Low
High
Transportation
Low
High
Education.
Low
High

NumberBehavior
Good (%)

Bad (%)

OR

95% CI

Adjusted OR

95% CI

228
472

58.8%
50.2%

41.2%
49.8%

1.00
1.41

1.02-1.94

1.00
1.42

1.00-2.02

569
131

53.4%
51.1%

46.6%
48.9%

1.00
1.09

0.74-1.60

1.00
1.17

0.72-1.91

481
219

52.6%
53.9%

47.4%
46.1%

1.00
0.95

0.68-1.30

1.00
1.11

0.61-2.01

420
280

52.6%
53.6%

47.4%
46.4%

1.00
0.96

0.71-1.30

1.00
0.77

0.42-1.42

373
327

55.8%
49.8%

373
327

1.00
1.26

0.94-1.70

1.00
1.22

0.88-1.68

319
381

54.9%
51.4%

319
381

1.00
1.14

0.85-1.54

1.00
1.20

0.82-1.73

192
508

53.1%
53.0%

46.9%
47.0%

1.00
1.00

0.72-1.40

1.00
0.93

0.61-1.41

551
149

55.5%
43.6%

44.5%
56.4%

1.00
1.61

1.12-2.32

1.00
1.27

0.86-1.88

597
103

54.8%
42.7%

45.2%
57.3%

1.00
1.62

1.06-2.47

1.00
1.13

0.71-1.80

526
174

56.1%
53.0%

43.9%
47.0%

1.00
1.54

1.16-2.32

1.00
1.22

0.82-1.82

274
426

55.5%
51.4%

44.5%
48.6%

1.00
1.17

0.86-1.59

1.00
0.85

0.60-1.19

415
285

59.3%
43.9%

40.7%
56.1%

1.00
1.86

1.37-2.52

1.00
1.55

1.09-2.18

420
280

60.2%
42.1%

39.8%
57.9%

1.00
2.08

1.53-2.82

1.00
1.86

1.33-2.59792

GEOMATE - Mie, Japan, Nov. 21-24, 2017

CONCLUSION
This was study was to identify the level andpredictor of behavior intention to develop green
university: A Case of Undergraduate University in
Thailand. The students and staffs at Valaya
Alongkorn Rajabhat University under the Royal
Patronage, Thailand was included as the sample
size of this study. A questionnaire for collecting
data was developed by the six major criteria of the
UI GreenMetric World University Ranking.
Association and strength of the relationshipbetween factors was determined by Chi-square andlogistic regression and the best predictor factors
was performed by multiple logistic regression. The
results showed that that positive attitude towards
transportation and education were found to be thesignificant predictors of intention to develop green[3] Tukker A, Emmert S, Charter M, Vezzoli C, Sto
E, Andersen MM, Geerken T, Tischner, U,
Lahlou S, “Fostering change to sustainableconsumption and production: An evidence
based view”, J. Clean. Prod., Vol 16, 2008, pp.
1218–1225.
[4] Geng Y, Liu K, Xue B, Fujita T, “Creating a“green university” in China: a case of Shenyang
University”, J. Clean. Prod., Vol 61, 2013, pp.
13-19.
[5] Hordijk I, “Position paper on sustainable
universities”, J. Clean. Prod., Vol
14, 2014, pp.810–819.
[6] Tiyarattanachai R, Hollmann NM., “Green
campus initiative and its impacts on quality oflife of stakeholders in Green and Non‑Green
Campus universities” SpringerPlus, Vol 5,
2016, pp. 84.
[7] Universitas Indonesia, “UI GreenMetric World
University Ranking”,
http://greenmetric.ui.ac.id/. Accessed 17 April
2015.
[8] Yamane T, “An introductory analysis”, Harperand Row, New York, 1967.
[9] Mamat L, Basri NEA, Zain SM, Rahmah E.,“Determining the level of environmental
sustainability practices at campus dormitories
using green indicators”, Asian Social Science,
Vol 11(12), 2015, pp. 25-31.
[10] Omoogun AC, Odok AO, “Influence of genderand environmental awareness on attitude ofpeople towards forest conservation in Ekuri
communities in Akamkpa local governmentarea of cross river state”, J Public Admin Gov,
Vol 3(2), 2013, pp.219–225.

ACKNOWLEDGEMENTS
This research was supported by Valaya Alongkorn
Rajabhat University under the Royal Patronage.
REFERNCE[1] Wright T, “University presidents’conceptualizations of sustainability inhigher education", Int. J. Sustain. High. Educ,
Vol 11, 2010, pp. 61–73.
[2] Seitzinger SP, Svedin U, Crumley, CL, Steffen
W, Abdullah SA, Alfsen C, Broadgate WJ,
Biermann F, Bondre NR, Dearing JA,“Planetary stewardship in an urbanizing world:
Beyond city limits”, Ambio, Vol 41, 2012, pp.
787 –794.

793

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

GIS BASED IDENTIFICATION OF WATER BORNE DISEASES*Hania Arif 1, Shahid Iqbal2
Research Scholar, University of the Punjab, Pakistan; 1, 2
ABSTRACT: In Pakistan, water contamination is one of the most threaten health hazard. There is no check andbalance for its management and monitoring. In our country, Surface and Ground water both are contaminated with
toxic metal, pesticides and artificial organic materials. World Health Organization (WHO) set the standards fordrinking water but unfortunately no one follow them. Main causes of water contamination are industrial wastes,
higher concentration of pesticides and other human induced activities mainly due to inappropriate sites for
dumping/land fill. Toxic elements are the main factors to pollute the ground water which have direct impacts on
the human health. In this present research quality of drinking water and their borne diseases are discussed. If theconcentration of these toxic elements increase above their threshold limit then they became a cause of sewer
diseases like skin cancer, lung cancer, affects the teeth and bones directly. GIS is a powerful technique for
geographical representation and spatial analysis of groundwater. Spatial distributions of ground water quality in
the Gujranwala District of Punjab Province is monitored. The data for ground water quality of the study area isprepared using spatial interpolation technique against each parameters. Measured values of the each parameters
are classified as per WHO standards for developing countries. The final result conclude that, groundwater of thestudy area need proper treatment for its usage as drinking water.
Keywords: Health Hazard, WHO, Toxic Elements, GIS
million children in developing countries for annum.
In terms of financial cost, the UN estimates that $7.3
billion may be saved in healthcare costs by improving
water quality and sanitation conditions [2]. Rapid
increase in population, especially in urban areas, has
led to poor water quality management, which isfurther aggravating the problem [3]. The recently
approved National Drinking Water Policy also
recognizes the need to ''provide access to safe andsustainable drinking water supply to the entire
population of Pakistan by 2025'' and the safe waterrefers to the water complying with National Standards
for Drinking Water Quality[4].

INTRODUCTION
Water borne diseases are among one of the major
public health problems in developing countries like
Pakistan. They are the leading causes of morbidity
and mortality in all age groups particularly in children
under 5 years of age. According to the World HealthOrganization (WHO) 3 million deaths occur every
year from diarrheal diseases worldwide. The problemof water borne diseases is especially prevalent wheregeneral hygiene and environmental sanitation arepoor and where there is a shortage of protected watersupply (1, 5). It is believed that 80% of all diseases in
the world are caused by inadequate sanitation,
polluted water or unavailability of water (WHOMonica II). Poverty, illiteracy, overcrowding and low
health services are contributing factors that directly or
indirectly affect the prevalence of water borne
diseases. Therefore an integrated prevention andcurative approach with community participation isrequired in order to tackle this prevalent public healthproblem.
Water borne diseases are viral, bacterial and parasitic
diseases which use water as a common means oftransmission. In this module we will discuss thosewater borne diseases in which the mode of entry of
their etiologic agents into a susceptible host is oral.
The connection between human health and water
quality has been well recognized. Use ofcontaminated water has its health and financial cost.
In terms of health cost, it is reported that 80% of all
diseases, in developing countries, may be attributed
to the use of contaminated water [1]. Poor water
quality is responsible for the death of an estimated 5

LITERATURE REVIEW
Water naturally contains largely suspended anddissolved substances both inorganic and organic innature. Surface water (Rivers, springs, streams,
Lakes, etc.) carries suspended particles of sand, silt
and clay and microorganisms both nontoxic anddisease causing especially bacteria, protists, algae,
protozoa and parasites etc. Ground water includes
dissolved substances like dissolved minerals e.g.,
Calcium, Magnesium, Sodium, Potassium, anddissolved salts of these minerals like sulphates,
chlorides, carbonates, bicarbonates, and dissolved
metals. Nutrients like phosphorous -and nitrogen etc.
are also present in water. There are a variety of traceelements like heavy metals e.g. Arsenic, Chromium,etc. which are also there in ground water.
Composition of water is determined by natural
influences in addition to human actions. Under
natural influence, water undergoes diverse physical,
794

GEOMATE - Mie, Japan, Nov. 21-24, 2017

biological and chemical processes. For example,
surface water composition is a function of natural
weathering of rocks, presence of plant roots andleaves, rock minerals and deposition of soil and salts
by wind. As water moves on such surfaces, materials
like particles of sand, clay and silt, which makes
water turbid or mucky, organic materials andminerals are added up in the water. This determines
the physical and chemical composition of surface
waters. In addition the biological composition ofthese waters is determined by presence of
microorganisms like algae, bacteria, etc. These arenaturally in attendance in environment like soil, air,attached to plant leaves and roots. The ground watercomposition is a function of nutrients andmicroorganisms present in the plants, leaching of
natural organic substances, and the soil naturally.
Moreover surface run-off in case of rain storms(ground water recharge) passes through different land
surfaces, carrying plant nutrients and minerals,different types of soil particles, eventually seeps
through soil. Suspended impurities of percolatingwater find naturally filtered when the water seeps
through diverse soil strata. Nevertheless, dissolved
impurities get mixed by means of ground water.
The natural influences are both spatially andtemporally altered. Surface water quality depends on
kind of rocks and soil on which it moves. Groundwater quality is a function of composition of form of
bed rock, recharge water, minerals and undergroundstrata present underneath. By and large, normal water
quality varies from place to place, depends on climatechange and seasonal variation.
Human activities, conversely, affect watersignificantly and in diverse ways. Included in this are
agricultural or farming practices, disposal of urban
and industrial waste water in the natural water bodies.
Like use of pesticides, fertilizers and insecticides
which can mix by storm or rain water and get mixed
with ground water during seepage. Mining operations
can too contaminate water bodies. Water quality ismeasured in relation to its anticipated utilization.
There are different uses of water i.e. irrigation andagriculture,
recreationaluse,
industrial,constructional domestic use, etc. standards or
permissible / acceptable limits and Guidelines dependon the anticipated use of water. For example, potablewater or water used for drinking will have dissimilar
standards as compared to water which is used inindustries and agriculture. The subsequent segment isfocused on water quality relating to human health.

south is the provincial capital, Lahore. Sialkot andGujrat lie to its north. Gujrat connects Gujranwalawith Bhimber, Mirpure Azad Jammun and Kashmir,and Silakot connects it with Jammun. About 160
kilometers (99 mi) southwest is Faisalabad. To its
west are Hafizabad and Pindi Bhattian, which connect
Gujranwala to Jhang, Chiniot and Sargodha.
HEALTH FACILITIESHealth Medical facilities are on average available inthe city. The main government hospital established in
the city is THH (Tehsil Headquarters Hospital). There
are several other private hospitals, Health centre andClinics at different locations within the city.
WATER SOURCE
Good quality water source is the main component forthe development of water supply system in the cityand selection of water source depends upon thequality and availability of adequate water to meet the
future requirements. Water source i.e. surface waterin the form of canal or ground water can be selected
keeping in view the adequate availability of water thathas to be required for the town and must meet the
future requirement.
WATER RELATED DISEASESThe water related diseases can be classified into 4categories.
i.
Water-borne diseasesii.
Water-washed diseases
iii.
Water-based Diseases
iv.
Water-related Diseases
Water-borne disease is a disease which is acommunicable one caused by drinking
contaminated water or eating food cooked withsuch water contaminated with human or animal
excreta (faces or urine). So both water and foodcan be the source or way of transfer of waterborne diseases.
ii. Water-washed disease is the one that is causedby skin or eye contact with contaminated water.
Including in this are Trachoma, Scabies andflea, Lice and tick borne diseases include
diarrheal diseases, typhoid, paratyphoid,cholera, Dysentery (both amoebic andbacillary), infectious hepatitis etc.
iii. Water-based disease is the one caused by theParasites found in organisms living in water.
Diseases like Schistosomiasis, Dracunculiasis,
Helminthes etc., fall in this type.
Schistosomiasis is caused by a small worm, aparasite recognized as Fluke which enters
human body by drinking contaminated water.
Or it may also enter through skin if one swims
or baths in contaminated water. It is one of themost widespread parasitic diseases.

i.

DISTRICT OVERVIEWi.

BOUNDARY

Gujranwala is 226 meters (744 ft) above sea level,
sharing borders with Ghakhar Mandi and several
towns and villages. About 80 kilometers (50 mi)
795

GEOMATE - Mie, Japan, Nov. 21-24, 2017

iv. Water-related diseases are caused by breedingof insect vectors like mosquitoes in the water.
Common water associated diseases are Dengue,
Malaria,
Trypanosomiasis,
Filariasis,
Onchocerciasis, Yellow fever etc.
WATER BORNE DISEASE OF DIFFERENTPARAMETERSi.
pH:
High pH (more than 11) values cause skin disorders,eye irritation and mucous membranes. pH from 10 to
12.5 cause hair fiber swell. Receptive individuals may
undergo gastrointestinal problems due to elevatedpH.pH of potable water is 7. Low pH has also healthimpacts. pH below 2.5 may cause irreversible damage
to epithelium. Below 4 pH redness and eye irritation
may happen which can become cruel with extra
lowering of pH. NSDWQ permissible limits for pH
ranges from 6.5 to 8. NSDWQ has no health based
guidelines for pH.
ii.
Total Dissolved Solids (TDS):
It is a chemical property of water. Water having
elevated TDS levels may become unpleasant to theconsumers. Lofty TDS can cause taste trouble. The
palatability of water as per recommended by tasters
ranges from Excellent ( TDS less than 300 mg/L) to
Good (between 300 to 500 mg/L) and Unacceptable
if TDS measures more than 1500 mg/L.WDS may beaffected by corrosion if sulphates, chlorides,
carbonates are present in water. TDS in excess of 500
mg/L can cause scaling of boilers, pipe lines andhome appliances like kettles, heaters and steam irons
etc. (WHO, 1996).
iii.
Arsenic (As):
Arsenic is a metal-like substance found in small
amounts in nature. Arsenic is widely distributed
throughout the Earth’s crust, most often as arsenic
sulfide or as metal arsenates and arsenides. (IPCS,
World Health Organization, 2001). Drinking watercontaining elevated levels of arsenic may cause grave
health problems mostly skin problem.
iv.
Fluoride
Fluoride is found in all natural waters at someconcentration. Seawater typically contains about 1
mg l–1 while rivers and lakes generally exhibit
concentrations of less than 0.5 mg l–1. In
groundwater, however, low or high concentrations offluoride can occur, it’s directly effect on bone.
v.
Nitrate & Nitrite
Nitrate (NO3) is found naturally in the environment
and is an important plant nutrient. It is present atvarying concentrations in all plants and is a part of thenitrogen cycle. For drinking water 1mg/L is limit for
nitrite. Nitrate can reach both surface water andgroundwater as a consequence of agricultural activity(including excess application of inorganic
nitrogenous fertilizers and manures), fromwastewater disposal and from oxidation of
nitrogenous waste products in human and animal
excreta, including septic tanks. Surface water nitrateconcentrations can change rapidly owing to surface
runoff of fertilizer, uptake by phytoplankton anddenitrification by bacteria, but groundwater
concentrations generally show relatively slow
changes.

Sr #Parametrs

1

pH
Total Dissolved Solids
(TDS)

2
3
4
5
6

Arsenic (As)
Fluoride
NitrateWHO
Standards
6.5‐8.5
1000
mg/L
0.05 ppm
1.5 mg/L
50 mg/L
0.3 mg/L

NitriteTable 1: WHO Standard
METHODOLOGY
In case of present study we digitize the main features(Road Network, Settlements, and Irrigation Network)of district Gujranwala. The data from hospitals/clinics
were also collected to investigate the water borne
diseases related to drinking water available in the
study area. This study has conducted to investigate
such pollutants of drinking water which damaging
human health. We conduct the GPS survey to collectthe water sample and hospital data. Collect the Water
samples of different sources and depths.

Figure 1: Water Sampling
Hospital data collected for getting the all information
regarding toxic elements diseases, major diseases,
etc. we just do the GPS survey for knowing thelocation of water sources and hospitals. After
collecting and preparing the data water sample data,
generate the surface with the help of GIS
interpolation method. In this method, we used thespecial Kriging technique to generate the surface
which have some own parameter to define its
correlation between values. When we get the final
surface of water samples parameter then we correlate
this with hospital data and location. In the results we
see how contaminated water effect on people health796

GEOMATE - Mie, Japan, Nov. 21-24, 2017

badly.

Figure 2: Hospital Data Collected by GPS
And these water sources generate the water borne
disease due to the toxicification. In addition toharming animals water pollution can also affectplants, trees, the soil and other natural materials andresources of the earth.

Figure 4 TDS Concentration in Water

Satellite Imagery and
DEM

Demarcation of land
Features

Drainage Pattern
Spatial Data SamplingThrough GPS
Hospital Data

Water Sources

Water Borne Diseases
Data (Non Spatial Data)

Interpolation

Validation

Figure 3: Flow ChartANALYSIS
We perform krining analysis using interpolation
technique. With the help of GIS, we identify thecontaminated area of polluted water and that flows
from different sources which are causes of waterpollution. Against each parameter interpolation is
being done upon which we are able to highlights thoseareas having higher concentration of toxic materials.
Below Maps shows the vulnerability of drinking
water which is contaminated by toxified elements.

Figure 5: Arsenic Concentration in Water
797

GEOMATE - Mie, Japan, Nov. 21-24, 2017

also effect by this pollution badly. And people used
this water for drinking, farming etc. For the validationof this data, we collect the hospital data, we performthe overlay analysis. We have seen the relationship of
cantainemeted water with hospital data. And its
shows the 80% people are affected by toxic water
directly.
CONCLUSION
The results indicated that the concentrations of allparameters were higher in groundwater samples of
Gujranwala District. They were found toxic elements
in water samples which is collected by survey, among
different parameters studied in water samples, TDS,
As, F, NO3, NO2 was found within the permissible
limits for drinking. The results of the water samples
indicated that most of the area is effected by theseelements and its effect on ground water and thesurface water. It’s just not polluted the water it’s also
effect the people health badly. These elements havelong term effect on people health and its damages thebones, skin and other features of human body.
RECOMMENDATION
We identify source of pollution and control is onserious note. Finding a way to develop cheap
filtration systems and better waste disposal
management systems is going to be a vital step
towards improving the health of our drinking waterand the bodies of water that surround us. To makeawareness among People about drinking water
standard and water borne diseases. All water sources
supervised on regular basses.

Figure 6: Flouride Concentration in Water

REFERENCES[1] Leeuwen F. X. R. Van. 2000. Safe drinking
water: the toxicologist's approach. Food andChemical Toxicology, 38: 51-58.
[2] NDRC. 2014. Safe water: Keystone ofenvironment, health, economy and security.
Retrieved October 30, fromhttp://www.nrdc.org/international/safewater.asp[3] Huang, G. H. and Xia, J. 2001. Barriers tosustainable water-quality management. Journalof Environmental Management, 61: 1-23Kimura
S, “Journal paper title”, J. of Computer Science,Vol. 1, Aug. 1987, pp. 23-49.
[4] Govt. of Pakistan, SRO-1062(I)-2010. National
Standards for Drinking Water Quality.
[5] CENSUS ORGANIZATION, District Census
Report Rawalpindi 1998, Buru of Statistics,
Gujranwala.
[6] “Planning and Development in a Hill Side City,
A Case Study of Murree”, Pakistan Journal of
Geography, Vol. 2- No. 1&2. 1992. Pp. 145-161.
[7] World Health Organisation 1996, Guidelines fordrinking water quality, 2nd Ed, Vol. 2 Health

Figure 7: Nitrate Concentration in Water
It indicates the impact in near area that how
containment area effect water pollution directly
which not only affect the surface water but also
disturb the ground water because these toxic elements
penetrate by soil, and other ways. And drinking water
798

GEOMATE - Mie, Japan, Nov. 21-24, 2017

US inactivated delta-aminolevulinic aciddehydratase of whole blood and the blood leadlevel. Biochemical medicine, 1973, 8:149-159.
[11] Risebro, H.L.; Breton, L.; Aird, H.; Hooper, A.;
Hunter, P.R. Contaminated small drinking watersupplies and risk of infectious intestinal disease:
A prospective cohort study. PLoS One 2012, 7,
doi: 10. 1371/journal.

criteria and other supporting information,
Geneva, World Health Organization[8] Krajnc EI et al. (1987) Integrated criteria
document. Cadmium — Effects. Appendix.
Bilthoven,National Institute of Public Health andEnvironmental
Protection(ReportNo.
758476004)[9] WHO 1972-73 Technical Reports Series No.
505, 532. World Health Organization, Geneva.
[10] Harlan WR et al. (1973) Blood lead and bloodpressure. Relationship in the adolescent and adult799

SeventhInternational Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ANALYSIS OF RAINFALL IN THE EASTERN THAILAND
1

Wonlee Nounmusig1
Faculty of International Maritime Studies, Kasetsart University, Thailand
ABSTRACT

Understanding of rainfall pattern in eastern Thailand is required to support the planning of water
management. In this study, the patterns of rainfall in eastern Thailand are analyzed by using statistical analysis.
The data used from rain gauge stations in 15 stations (period in 1969-2008). The results show that the yearly
rainfall has been a tendency to decrease. The significant correlation between monthly rainfall and ENSO indices
has the largest number in the transitional period (April, May and October).
Keywords: Rainfall, Eastern Thailand, Correlation, ENSOINTRODUCTION
Eastern Thailand is a region of Thailand lying
between the Sankamphaeng Range to the north andthe Gulf of Thailand to the south. The border of theregion is Cambodia on the east and central Thailand
on the west. Eastern Thailand consists of 7 provinces(Chachoengsao, Chanthaburi, Chonburi, Prachinburi,
Rayong, Sa Kaeo and Trat) covering an area of
34,381km2 and account for 6.7% of country. In 2010,
approximately 62.49% is an agricultural land
proposes, 22.92% for forest land, 6.84% for urban
and built-up land, 2.46% for water body and 5.29%
for miscellaneous land as shown in Fig. 1[1]. In
addition, a major industrial zone (the Eastern
Seaboard) which plays a key role in Thailand's
economy is also located in the region. Thus, the need
for water in the region increases daily due topopulation growth, economic developments andurbanization.
The main source of water in the region is mainly
from rain. Too much or too little rain can havedisastrous effects on the agricultural, industrial, andothers consumption sectors. For example, severe
drought of the region in 2005 led to a conflict inwater resource allocation caused a fall in crop
production and the industrial sector shipping waterby truck from nearby regions [2].
In general, the climate in Thailand is dominatedby northeast monsoon and southwest monsoon [3].
The monsoons are controlled by the Inter Tropical
Convergence Zone (ITCZ). Anomalies in the ITCZ
and monsoon rainfall are typically in phase with theanomalies in central and eastern Pacific Ocean. The
variations in the position and intensity of the ITCZ
are associated with climate phenomena known as the
El Nino – Southern Oscillation (ENSO) [4-5].
Therefore, the study and understanding ofrelationships between rainfall and ENSO in eastern
Thailand is required to support the planning of water
management.

Land use type
Urban and built-up land
Urban and built-up land

Area
km2
2,353.02
2,353.02

Agricultural land
Paddy field
Field crop
Perennial
Orchard
Horticulture
Pasture and farm house
Aquatic plant
Aquaculture land
Integrated farm/Diversified farm

21,485.01
4,876.80
5,560.24
6,385.67
3,197.02
41.27
154.281.08
1,268.47
0.17

62.49
14.18
16.17
18.57
9.30
0.12
0.45
0.003
3.69
0.0005

Forest land
Dense forest
Disturbed forest

7,879.94
433.927,446.02

22.92
1.26
21.66

844.49844.492.46
2.46

1,818.04
1,604.50
213.54
34,380.50

5.29
4.67
0.62
100.00

Water body
Water body
Miscellaneous land
Other miscellaneous land
Marsh and swamp
Total

Fig. 1
800

Land use map in eastern Thailand [1].

%
6.84
6.84

GEOMATE-Mie, Japan, Nov. 21-24, 2017

DATA AND METHODS
Climate in Thailand
Climate in Thailand is divided into three seasons
as follows: 1) southwest monsoon season (mid-May
to mid-October). The southwest monsoon prevails
and brings warm and wet air from the Indian Ocean
to Thailand. Eastern Thailand has also abundant rain
occurs in this period. The wettest month in theregion is in July to August. 2) Winter or northeast
monsoon season (mid-October to mid-February).
The northeast monsoon brings cold and dry air from
China to upper Thailand. 3) Summer or premonsoon season, mid-February to mid-May. This is
the transitional period from the northeast to
southwest monsoons. The weather becomes warmer,
especially in upper Thailand. April is the hottest
month for all regions of Thailand.

Data used
Rainfall data
15 rain gauge stations during 1969 to 2008 fromthe Thai Meteorological Department (TMD) wereused to analyze rainfall distribution pattern. Table 1
shows the description of the 15 rain gauge stations
used in this study. The mean annual rainfall and rain
day in eastern Thailand was shown in Table 2. The
maximum of rainfall and rain day found at Khlong
Yai (Station ID. 501201) with 4713701mm. and
19219day, respectively.
Table 1 Description of the 15 rain gauge stations
StationID.

StationName
440201 Aranyaprathet
423301 Chacherngsao*
480201 Chanthaburi
459201 Chon BuriLong. (E) Elv.
(m)
134200 1023500 47.0
133357 1012730 69.4
123700 1020648 2.9
132200 1005900 0.9

478301 HuaiPong*
430401 Kabin Buri

124400 1010800 43.3
135900 1014226 10.2
114600 1025300 2.0

501201 Khlong Yai
459202 Ko Sichang

459205 Lam Chabang
459203 Phatthaya
480301 Phriu*
430201 Prachin Buri
478201 Rayong
459204 Sattahip

440401 Sa Kaew

Lat. (N)

ENSO indices
Sea surface temperature anomaly (SSTA) data
for equatorial regions of the Pacific Ocean whichcalculated from the HadISST1 [6] were used for thisstudy. The regions included here were Nino3 (thearea averaged SST from 90°W–150°W and 5°S–
5°N), Nino4 (the area averaged SST from 160°E–
150°W and 5°S–5°N), and composite region Nino34( the area averaged SST from 120°W–170°W and
5°S–5°N).
The Indian Ocean Dipole (IOD) intensity isrepresented the gradient in the difference between
sea surface temperatures of the western equatorial
Indian Ocean (50°E-70°E and 10°S-10°N) and thesouth eastern equatorial Indian Ocean (90°E-110°E
and 10°S-0°N). This gradient is named as Dipole
Mode Index (DMI). When the DMI is positive then,the phenomenon is refereed as the positive IOD andwhen it is negative, it is refereed as negative IOD [6].
The Southern Oscillation Index (SOI) is definedas the normalized pressure difference between Tahiti
and Darwin. There are several slight variations in the
SOI values calculated at various centre. The SOI
data used here were calculated using the method
given by Ropelewski and Jones [6-7].

130942 1004807 24.9
130437 1005233 80.7
125512 1005210 58.9
123100 1021000 22.3
140300 1012200 4.1
123805 1012045

2.6

124100 1005900 16.0
134720 1020205 40.9

Table 2 Mean annual rainfall and rain days withstandard deviation
Station Recording
ID.
Period440201423301480201459201478301430401501201459202459205459203480301430201478201

1969-2008
1989-2008
1969-2008
1969-2008
1969-2008
1970-2008
1969-2008
1969-2008
1993-2008
1981-2008
1969-2008
1969-2008
1981-2008

Mean annual
Rainfall Std. Rain days Std.
(mm)
(Day)
1372
175
130
13
1323
200
120
14
2917
484
167
14
1276
216
118
13
1392
277
119
16
1653
238
132
11
4713
701
192
19
1222
320
102
13
1160
200
103
12
1119
234
106
11
3166
636
171
23
1862
286
134
13
1362
288
114
15

Data Analysis
The Pearson correlation coefficients (r) wereused for investigation significant relationships
between rainfall data and ENSO indices (SSTAs,
SOI, IOD) as shown in Eq. (1).
n  x  x  y  y 

r

i

i 1

n

i

n

x  x   y  y 
i 1

801

2

i

i 1

i

(1)
2

GEOMATE-Mie, Japan, Nov. 21-24, 2017

Table 3 and 4 summarize the significant
correlations between ENSO indices and averageannual rainfall and rain day, respectively at 15
stations. The correlation between average yearly
rainfall and all of ENSO indices is mostly weak (r<=-0.51). The rainfall has only the significant
correlation with Nino and SOI Correlation in station
ID 440201 and 459202. When consider thecorrelation between the ENSO indices and rain day,rain day in most of the station has the significant
correlation with ENSO indices.

where n is the number of data, xi and yi are thedata set at time i , and x is defined as in Eq. (2),x

1 n
 xi (2).
n i 1The significance test of correlation can becalculated with a t statistic using the Eq. (3).

t

r n2
1 r2

(3)

Table 3 Correlation between the ENSO indices andAverage Yearly rainfall at 15 stations

The null hypothesis was rejected at a significant
level of  when t is more than or equal to t
2

,n 2

.

RESULTS AND DISCUSSION
RainfallAnnual rainfall and rain day
Fig. 2 shows an average annual rainfall in easternregion of Thailand. The 40-year average of rainfall
is 1921mm. The annual rainfall has been a tendency
to decrease. When El Niño (La Niña) phenomenon is
identified, the SSTAs in the Niño34 region is above
the threshold of +0.5°C (-0.5°C). The correlation
between average yearly rainfall and Nino34 is weak(r=-0.28). During El Nino year, most of the yearly
rainfall is below normal especially in 1992 and 1997
(1577 and 1613mm, respectively). During La Nina
year, the yearly rainfall is mostly above the averageas in 1974, 1975, 1988, 1999 and 2000 with eachyear exceeding 2000mm. When Consider only in the
ENSO year, it is found that the yearly rainfall has
the significant correlation with Nino34 (r=-0.46).

Fig. 2

Station ID NINO3 NINO34 NINO4440201
-0.33
-0.45
-0.49
423301
-0.16
-0.25
-0.26

SOI

DMI

0.52

0.10

0.36

0.21

480201

-0.03

-0.08

-0.01

0.03

0.05

459201

-0.29

-0.33

-0.31

0.32

-0.08

478301

-0.13

-0.20

-0.20

0.24

-0.20

430401

-0.08

-0.18

-0.23

0.21

0.00

501201

-0.02

-0.09

-0.11

0.02

0.24

459202

-0.33

-0.39

-0.37

0.37

-0.26

459205

-0.44

-0.42

-0.30

0.44

-0.51

459203

-0.16

-0.20

-0.14

0.23

-0.26

480301

0.15

0.05

0.05

-0.08

0.22

430201

-0.29

-0.31

-0.31

0.31

-0.06

478201

-0.20

-0.25

-0.21

0.25

-0.23

459204

-0.12

-0.18

-0.24

0.25

0.02

440401

-0.07

-0.29

-0.38

0.48

0.56

Note: Correlations in bold are significant at the p=0.05 level

Table 4 Correlation between the ENSO indices andaverage annual rain day at 15 stations

Average yearly rainfall in eastern Thailand(– represent 40-year average of rainfall, …
represent linear trend, bar represent amountof rainfall, and --■--represent the sea
surface temperature anomaly region
Nino34)

Station ID NINO3 NINO34 NINO4

SOI

DMI

440201

-0.26

-0.28

-0.33

0.27

-0.06
0.10

423301

-0.55

-0.61

-0.54

0.64

480201

-0.44

-0.45

-0.39

0.42

0.10

459201

-0.56

-0.60

-0.55

0.61

-0.21

478301

-0.31

-0.33

-0.25

0.36

-0.17

430401

-0.39

-0.46

-0.49

0.49

0.00

501201

-0.36

-0.39

-0.38

0.35

0.25

459202

-0.33

-0.34

-0.32

0.30

-0.09

459205

-0.58

-0.70

-0.68

0.71

-0.50

459203

-0.18

-0.20

-0.17

0.22

-0.15

480301

-0.15

-0.23

-0.22

0.19

-0.07

430201

-0.45

-0.54

-0.60

0.50

-0.13

478201

-0.38

-0.40

-0.32

0.41

-0.27

459204

-0.29

-0.38

-0.41

0.40

0.03

440401

-0.42

-0.65

-0.77

0.82

0.62

Note: Correlations in bold are significant at the p =0.05 level

802

GEOMATE-Mie, Japan, Nov. 21-24, 2017

Seasonal Variation in Rainfall
Fig. 2 and Fig. 3 show mean monthly rainfall andrain day, respectively at 15 stations in East Thailand.
During May to September has abundant of rainfall.
The maximum of rainfall and rain day found in
August at Khlong Yai (Station ID. 501201) withexceed 1000mm and exceed 25day, respectively. Allof stations have a number of rain days exceed 10day
during May to October.
When consider the correlation between the
ENSO indices and average monthly rainfall, therainfall has the largest number of significant
correlation with ENSO indices in the transitional
period (April, May and October) as shown in Fig. 4.
The highest number of significant correlations isfound at station ID 440401 in April and May with
r=-0.71 and r=-0.52, respectively. For the rain days,
it is also found that the largest number of correlation
with ENSO indices is in the transitional period(April, May and October). But, the rain days along
the near shore station have no significant correlation
with Nino34.

(a)

(b)

Fig. 2

Mean monthly rainfall in eastern Thailand(c)Fig. 4 Correlation map between the Nino34 andaverage monthly rainfall of 15 stations in (a) April,(b) May and (c) October.
CONCLUSION

Fig. 3

The 15 rain gauge stations data during 1969 to2008 from the Thai Meteorological Department(TMD) were used to analyze rainfall distribution
pattern. The main source of rainfall in the region
comes from southwest monsoon which brings
abundant rain during May to October with a numberof rain days exceed 10day. The 40-year average ofMean monthly rainy day in eastern part ofThailand803

GEOMATE-Mie, Japan, Nov. 21-24, 2017

rainfall is 1921mm. Since 1969, the annual rainfall
has been a tendency to decrease.
The correlation between yearly rainfall andNino34 is weak (r=-0.28). When consider thecorrelation between the ENSO indices and monthly
rainfall, it is found that the rainfall has the largest
number of significant correlation with ENSO indicesin the transitional period (April, May and October).
For the rain days, it is also found that the largest
number of correlation with ENSO indices is in thetransitional period (April, May and October). But,
the rain days along the near shore station have nosignificant correlation with Nino34.
In future work, the atmospheric model will beapplied to study the rainfall pattern in Eastern
Thailand and mechanism of atmosphere during thetransitional period.

[2] Chitradon R, Boonya-aroonnet S andThanapakpawin P, “Risk Management of Water
Resources in Thailand in the Face of Climate
Change”, Sasin Journal of Management, 2009,
pp. 64-67.
[3] Zhang Y, Li T, Wang B and Wu G, “Onset of
the Summer Monsoon over the Indochina
Peninsula: Climatology and Interannual
Variations”, J. Climate, Vol.15, Nov. 2002, pp.
3206–3221.
[4] Lau KM and Yang S, “Climatology andinterannual variability of the southeast asiansummer monsoon”, Adv. Atmos. Sci., Vol. 14,
Jun. 1997, pp. 141-162.
[5] Waliser DE and Jiang X, “TropicalMeteorology: Intertropical Convergence Zones(ITCZ)”, Encyclopedia of Atmospheric
Sciences, 2th ed., Academic Press.
[6] Smith C, “Climate Time series”, NOAA ESRL
PhysicalSciences
Division,
http://www.esrl.noaa.gov/psd/gcos_wgsp/Times
eries/index.html, 2017.
[7] Ropelewski CF, and Jones PD, “An extensionof the Tahiti-Darwin Southern Oscillation
Index”, Monthly Weather Review, Vol. 115,
1987, pp. 2161-2165.

ACKNOWLEDGEMENTS
The rainfall data used in this study wereobtained from the Thai Meteorological Department(TMD), Ministry of Digital Economy and Society
Thailand.
REFERENCES[1] Land Development Department (LDD),
http://www.ldd.go.th/ldd_en/en-US/map/mapdetails/land-use-in-eastern-region/6/, 2014.

804

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

CHANGES IN THE ZOOPLANKTON COMMUNITY BEFORE AND
AFTER NUTRIENT DIVERSION AND REVETMENT CONSTRUCTION
IN LAKE FUKAMI-IKE, JAPAN
Hiromi Suda1, Masaaki Tanaka2, Maki Oyagi2 and Akihiko Yagi3
Faculty of Science and Technology, Meijo University, Japan
Faculty of Environmental and Information Sciences, Yokkaichi University, Japan
3
Faculty of Civil Engineering Department of Urban Environment, Aichi Institute of Technology, Japan1

2

ABSTRACT
Lake Fukami-ike is a small eutrophic lake, to improve the water quality of the lake, a lake management project
was carried out in 1992. This project involved nutrient diversion and revetment construction along the lake shore.
A biotope was built near the lake in 2000. As a result, although the inorganic nitrogen in the lake decreased
considerably, chlorophyll-a (phytoplankton) increased slightly.
The zooplankton community in the lake before the project in 1978-1979 predominantly comprised large-sized
species (about 1.8 mm), however, small-sized species (about 0.1-0.2 mm) were dominant after in 2013-2015. The
reason for the decrease of the large-sized zooplankton was thought to be the possibility of losing habitat spacebecause aquatic macrophytes of the littoral zone were filled up when revetment construction built in 1992. We
compared the body length and composition of zooplankton community between the lake (nearly emergent plantson the lake shore) and the biotope (emergent and floating-leaved plant cover). Large-sized zooplankton (about 0.91.2 mm) were dominant in the biotope, and size distribution did not differ in 1978-1979. The presence of developed
aquatic macrophytes was suggested to promote the survival of large zooplankton.
Keywords: Zooplankton community, aquatic macrophytes, body length
measured, but its species composition as
phytoplankton has not been clarified continuously.
Reference [2] shows the difference in species
composition between zooplankton and phytoplankton
before and after the project, which also reports thatchl-a increase slightly despite the nutrient diversion
and large-sized species (body length about 1.8 mm,e.g., Cyclops vicinus) dominated the lake in 19781979 (before the project), whereas small-seized
species (body length about 0.1 mm e.g., Keratellacochlearis) dominated the lake in 2013-2014 (after
the project).
In addition to the results of reference [2], resultsfrom 2014 to 2015 are also included, and the bodylengths of zooplankton before and after the project
have been extensively compared in this paper.
Furthermore, in order to clarify the influence ofaquatic macrophytes of the lake shore which was usedfor zooplankton as a habitat space and an evacuate
space from fish, which is considered as one of thefactors in the reducing of large-sized zooplankton, we
decided to compare the appearance situation of
biotope (Adjacent to the west side of the lake) to lakes
with different vegetation and lake.

INTRODUCTION
Lake Fukami-ike is a small monomictic andeutrophic lake, located in southern Nagano Prefecture
in central Japan. In 1992, a lake management project
was carried out to improve the water quality of thelake; this project involved a reduction in external
nutrient loadings from surrounding paddy fields into
the lake (nutrient diversion), revetment construction
along the lake shore (Except for some, the aquaticplants disappeared) [1]. This project was expected to
improve the water quality of the lake, but only
inorganic nitrogen, and not inorganic phosphorus,
was found to be decreased significantly. Moreover,chlorophyll-a (chl-a) increased slightly after the
project [2]. In June 2000 and July 2016, blue-green
algae (Cyanophyceae, Microcystis aeruginosa,
Anabaena affinis, respectively) blooms occurred,
which was not observed before the project. Althoughmore than 20 years have passed since the project, it isdifficult to say whether it effectively improved thewater quality by nutrient diversion.
Studies on Lake Fukami-ike began from 1978
onwards, and investigations are still being conducted
mainly on water quality roughly once a month.
However, zooplankton and phytoplankton have notbeen investigated in detail. Chl-a have been805

GEOMATE - Mie, Japan, Nov. 21-24, 2017

METHODS
Study Site
Lake Fukami-ike
The lake is located at a north latitude of
35°32′55″77 and east longitude of 137°81′93″56. Its
short diameter is 150 m, diameter is 300 m, area isabout 2.2 ha, and volume is 1.0×105 m3 (Fig.1). The
lake has six inflows and an outflow [2, 3]. In 2016,
the maximum depth of the water was observed to be
7.6 m.
The dominant macrophytes communities on thelake shore have been established as follows: Zizania
latifolia and Phragmites australis, (both species
belong to Poaceae). Among them, Z. latifolia wereplanted after the project [1].
The fish community is dominated by Lepomis
macrochirus (Centrarchidae) and Micropterus
salmoides (Centrarchidae), which are piscivorous fish
[4].

Fig. 2The biotope on July 6, 2013.

Sampling and Analysis
Field observations in the lake were conductedfrom March 2013 to February 2015, including theobservations in the biotope from May 2013 to June
2014, roughly once a month.
Lake plankton samples were collected at the
deepest point with a Van Dorn water sampler (10L,
Rigo Co., Ltd., Tokyo, Japan) from every 0.5m.
Biotope plankton samples were collected with
polyethylene bottle by scooping water directly.
All the samples were preserved in 1% formalin in
the field immediately. Zooplankton were identified
using an optical microscope (BX51, Olympus OpticalCo., Ltd., Tokyo, Japan) in the laboratory.
RESULTS AND DISCUSSION
Comparing body length of zooplankton before andafter project

Fig. 1

Reference [5] shows that the zooplankton werecollected using plankton-net (mesh size 0.1 mm, Rigo
Co., Ltd., Tokyo Japan) from 1978 to 1979. Therefore,
we compared the length of zooplankton before andafter project, excluding the size smaller than 0.1 mm.
The species with high frequency before and after
the project is shown in Table 1.
Before the project, the frequencies of large-sized
zooplankton are as follows: Cyclops vicinus (36.2%),
Bosmina longirostris (20.6%), and Cyclops sp.
(11.8%), respectively. On the other hand, the smallsized zooplankton that appeared after the project are
as follows: Keratella cochlearis var. tecta, Keratellacochlearis var. micracantha and Nauplius of
Cyclopoida (15.6% in total), Brachionus angularisand Polyarthra dolicoptera (13.4%), Filinia longiseta(11.2%).
While there were many large species in thespecies with high occurrence frequency before theproject, there were many small species after the
project.

Location of the Lake Fukami-ike.

Biotope
The biotope is on the west side of the lake andbuilt by local residents in 2000. The biotope isconnected to the lake by a hose filled in the ground.
The range of water depth is about 0.1-0.3 m, water inthe biotope will dry out in the midsummer andfreezing in the midwinter temporarily.
In summer, the biotope was found to be covered
with Nelumbo nucifera (Nelumbonaceae), Z. latifolia,
and P. australis (http://fukami-ike.jp/page012.html).
Pelophylax nigromaculatus (Ranidae) was also foundin the biotope.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Comparison of high frequency species and body length before and after the project.
Project
Before(1978-1979)
[5]
After
(2013-2015)

Species
Cyclops vicinus
Bosmina longirostris
Cyclops sp.
Keratella cochlearis var. tecta
Keratella cochlearis var. micracantha
Nauplius of Cyclopoida
Brachionus angularis
Polyarthra dolicoptera
Filinia longiseta

frequency(%)

40
30
20
10
0
0.5

1.0

1.5

2.0

1.5

2.0

body length (mm)frequency(%)

40
30
20
10
0
0.0

0.5

1.0

body length (mm)Frequency (%)
36.2
20.6
11.8

0.10

15.6

0.125

13.4

0.25

11.2

type. They are distributed in gently sloping places,
generally called “lake-shelves”, in strips at different
water depths, and established aquatic macrophytes
community.
Aquatic plants play an important role in theecosystem of the lake. They provide habitats forliving things, absorb nitrogen and phosphorus so as tomaintain water quality, and so on [12]. The developed
aquatic macrophytes in the lake shore provides
habitats for zooplankton and other organisms because
there are three-dimensional structures. The developed
aquatic macrophytes in the lake shore also helps thezooplankton to escape from predators such as fish.
Emergent plants are shallowly submerged in water
while the floating-leaved plants have only the leaves
floating on the surface; both these categories of plants
are less likely to form complex structures. However,the submerged plants have their whole bodysubmerged in the water, so they have a high hiding
effect from fish [10,12]. For this reason, the existenceof a submerged plant community is considered
important in places where large sized zooplankton
exists so as to help hide them from their predators.
In the Lake Fukami-ike, some of the aquatic
macrophytes communities in the littoral zone on the
shore were left behind before the revetment
construction in 1992. But later, many of thesemacrophytes communities disappeared during theconstruction process.
To see the influence of macrophytes community,
species composition of zooplankton from biotope(emergent and floating-leaved plant cover) was
compared with the lake (nearly emergent plants on
the lake shore) after the project.

Figure 2 shows the comparison of the body lengthof zooplankton collected before and after the project.
This finding indicates that many large species
inhabited the lake before the project, while the small
species mainly inhabited the lake after the project.

0.0

Body length (mm)
1.8
0.5
1.5

Fig.2 Comparison of the body length and frequencyof the zooplankton in Lake Fukami-ike before(upper figure) and after (lower figure) the
project.
Factors responsible for reducing the large species
in the lake
In general, an increase in grazing pressure ofplanktivorous fish led to the loss of large-sized
zooplanktons [6, 7].
Zooplankton behavior that escapes from predationfrom fish is well known, it is necessary to movevertically to the layer where light does not reacheasily visible during the day [8, 9]. In addition, it is
known that zooplankton moves horizontally toaquatic macrophytes community on the lake shore inorder to conceal it from fish [10, 11].
The aquatic macrophytes communities areclassified in emergent plant, floating-leaved plant,
and submerged plants mainly by their form and life-

Relationship between macrophytes communityand species composition of zooplankton1
Macrophytes community of the lake and biotope
Table 2 shows the macrophytes community of thelake and biotope. Before the project in the lake, themacrophytes community included emergent plants,
floating-leaved plants, and submerged plants.
807

GEOMATE - Mie, Japan, Nov. 21-24, 2017

After

Reference [10] shows the difference between theliving types of aquatic plants and the abundance ofDaphnia. The abundance of Daphnia in thesubmerged plants community shows that the
population density has increased significantly
compared with the floating-leaved plant group, theemergent plant group, and the control group (withoutwater plants).
These results suggested that the presence ofdeveloped aquatic macrophytes suggested thepromotion of the survival of large-sized zooplankton.

〇〇

CONCLUSION

Although there is no data on the area to prove that thecommunity disappeared by revetment construction,
the macrophytes community of the lake became
simpler with emergent plants on the lake shore.
Table 2 Main macrophytes community of the lakeand biotope.

Species

LivingForms*

Zizania latifolia
Phragmites australis
P. japonica
Typha latifolia
Nelumbo nucifera
Potamogeton cristatus

E
E
E
E
F
S

Area
Lake
Before
After
[13]
〇
〇
〇
〇
〇
〇

BiotopeWith the lake management project in 1992, theamount of nitrogen in the lake was decreased
significantly; however, the amount of chl-a did notdecrease but increased slightly. Although thisphenomenon was one of the question, this may be dueto the low prey pressure for chl-a (phytoplankton)with remarkably small number of large-sized
zooplankton. Moreover, the decrease in large-sized
zooplankton was believed to be due to the lack ofdeveloped macrophytes for cover from predators as aresult of the large landfilling of the lake shore by therevetment construction.
In order to reduce the amount of chl-a in the lake,
it is important to increase the predation pressure
against them. Developing aquatic macrophytes
community on the lake shore is thought to promote
the population of large-sized zooplankton, and it also
has the effect of stable absorption of nitrogen andphosphorus in the lake.
Although it is still an issue to examine theinfluence of predatory pressure of fish against
zooplankton, restoring the developed community
seems to have the potential to improve the ecosystemof the Lake Fukami-ike.

〇〇*E: emergent plants, F: floating-leaved plants, S: submerged plants*Before: before the project, After: after the project

Comparing body length of zooplankton in the lakeand biotope after the project
To see the difference in zooplankton composition
and macrophytes, the body size of the zooplankton
collected from the biotope and the lake werecompared (Fig. 3). The size of the circle indicates thatthe number of zooplankton corresponded to that
position.
From the biotope, most cases were dominated bylarge zooplankton (Cladocera, Scapholeberis kingi)
with a body length of about 0.9 to 1.2 mm during thestudy period. The distribution of the body size wasdifferent from the sample collected from the lake after
the project. The size distribution of zooplankton
collected from the biotope was similar to that of thelake before the project, and large-sized zooplankton
were mainly obtained.
frequency(%)

40

ACKNOWLEDGMENTS

30

We are grateful to the Anan-cho authorities in
Shimoina-gun, Nagano Prefecture, who generously
provided research facilities. We also thank Megumi
Nobori, Sohey Hane, Seiya Kato, Ryosuke Nakagami,
Goto Hironori, Takuya Yokoyama in Yagi laboratory
for their help in the field.

20
10
0
0.0

0.5

1.0

body length (mm)

1.5

2.0

CC
C

REFERENCES＋
R[1] Limnology of committee of Shimoina kyoikukai, “Shimoina-shi”, Shimoina Editorial
Committee of Shimoina-shi edited, (in Japanese),[Translated from Japanese], 2009, 353pp.
[2] Suda H, Tanaka M, Oyagi M, Nobori M, andYagi A, “Water quality and compositions of thephytoplankton and zooplankton before and after
building a bulkhead maintenance construction in

RR
0.0

0.5

1.0

1.5

2.0

body length (mm)Fig.3

Comparison of body length and frequency ofthe zooplankton in Lake Fukami-ike after the
project (upper figure, refer to Fig.2) andbiotope (lower figure).
808

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Lake Fukami-ike, Japan”, International Journalof GEOMATE, Vol. 10, Jun. 2016, Issue 22, pp.
1983-1988.
[3] Yagi A, “Biological manganese cycle in the oxic
and anoxic layers of Lake Fukami-ike” (inJapanese), Limnology in Tokai Region of Japan,
Vol. 43, 2010, pp.51-60.
[4] Kawanobe M, Hosoe A. “Extermination of thealien fishes in the Fukami Pond”. Annual Reportof Nagano prefectural fisheries experimental
station, (in Japanese) [Translated from Japanese]
2008, p.15.
[5] Tanaka M, “11-18. Lake Fukami-ike”, The lakes
in Japan (in Japanese), 1th ed. Nagoya, The
University of Nagoya Press., 1992, pp.417-421.
[6] Brooks, J. L., and S. I. Dodson, “Predation, bodysize, and composition of plankton.” Science,
1965, 150, 3962, pp.28-35.
[7] Dahl-Hansen, G. A. P., “Long term changes incrustacean zooplankton – the effect of mass
removal of arctic charr, Salvelinus alpinus (L),from an oligotrophic lake.”, Plankton Research,
1995, 17, pp.1819-1833.
[8] Kikuchi, K., “Diurnal migration of plankton
crustaceae.”, The Quarterly Review of Biology，
1930, 5, pp.189-206.

809[9] Sekino, T., and N. Yoshioka, “The relationshipbetween nutritional condition and diel verticalmigration of Daphnia galeata.” Japanese Journalof Limnology, 1995, 56, pp.145-150.
[10] Hayashi N, Nakano Y, Ozaki Y and Inamori Y.,“Influence of Aquatic Plant Communities for
Planktonic Biomass.”, Japanese journal of water
treatment biology. 2007, 43, pp.113-119.
[11] Burks, R. L., D. M. Lodge, E. Jeppesen, and T.
L. Lauridsen, “Diel horizontal migration of
Zooplankton: costs and benefits of inhabiting thelittoral.”, Freshwater Biology, 2002, 47, pp.343365.
[12] Sakurai Y. and Ministry of Land, Infrastructure
and Transport Kasumigaura River Office(editing), “Aquatic organisms of Lake
Kasumigaura: records of changes from 1972 to1993”, (in Japanese) [Translated from Japanese],
Shinzansya Publisher Co., Ltd., 2007, 307pp.
[13] Environmental Science Society (Ueda), “Lake
Fukami-ike”, Inland water of Shinshu, (inJapanese) [Translated from Japanese], 1974,
pp.117-128.

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

SPATIAL ASSESSMENT ON THE IMPACT OF FLOOD TO MELAKA’SECONOMY
Rosilawati Zainol1, Hanan Elsawahli2 and Wan Suzita Wan Ibrahim3
Centre for Sustainable Urban Planning and Real Estate, Faculty of Built Environment, University of
Malaya, Malaysia; 2The National Ribat University Sudan; 3Universiti Kebangsaan Malaysia, Malaysia
1

ABSTRACT
Melaka was a significant trading state in the 16th century. It had attracted traders from various continents tobe its trading partners. Many of these traders had left their footprint enormously. Over the years, these tangible
and intangible historical assets have been an attraction to tourism sector which contributes significantly to
Malaysian GDP. However, due to the impact of climate change and rapid urban development in Melaka, theflood has posed a risk to Melaka’s economy especially in the tourism sector. To protect its interest, Melaka hastaken proactive measures in mitigating flood incidences. Thus, this study intends to examine the impact of theflood on Melaka’s economy from 2012 to 2016 using spatial assessments. This study employs a quantitative
approach by using secondary data obtained from the Department of Statistics Malaysia and the Department of
Irrigation and Drainage. Moran’s I, Local Indicator and Spatial Association and Bivariate Moran’s I were used toanalyse the data spatially. Findings show the mitigation measures taken have relieved the risk posed by floods
towards economic activities in Melaka as a whole.
Keywords: Moran’s I, Bivariate Moran’s I, Local Indication Spatial Association, Flood Modification
INTRODUCTION
Flood has become a global concern, as flood
risks caused extensive damage and threatened thelives of many people around the globe. Climatechange is causing increased flood damages [1],making flood risks no more associated with
underdeveloped countries. Hurricane Katerina hit
the Gulf Coast in the USA and caused serious
damages to people and property [2]. In 2012 the cityof New York was also hit by a hurricane. In Austria,
Germany and Hungry excessive heavy rains caused
serious damages and losses in billions of Euros. In
2007, England suffered a major flood which caused
the destruction of property and loss of lives [3].
Malaysia, being a tropical country suffers flood
risks. Flooding is one of the major hazards facing byseveral cities in Malaysia. However, debates aroundpossibilities of flood occurrence, do not take placeagainst the background of climate change only, butalso against the background of rapid urbanisation,
resulting in 4.8 million people living in flood-prone
areas [4, 5]. The Malaysian government has initiatedseveral programs at both local and national levels toimprove flood risk management. However, theeffectiveness of these measures has yet to bemeasured using various assessment tools. Thus, thisstudy intends to examine the impact of mitigation
measures taken on economic activities using spatial
analysis. The area for this study is Melaka.

BACKGROUND
Flood is the most devastating natural disaster
experienced in Malaysia. It has a terrible impact
socially and economically and its likelihood to occur
in the future is high. There are about 189 river basinsin Malaysia, and 85 of them are prone to flood.
Flood disaster in Malaysia affects an area ofapproximately 28,800 km2 and almost 4.82 million
people are affected by this disaster (DID, 2009).
There are two categories of flood that affect
Malaysia. First is a flash flood and the other ismonsoon flood. The difference between these two is
the time taken to recede. Flash flood will only takehours to return normal level, and monsoon flood canlast a month.
Mitigation Measures
There are various approaches used by various
countries to mitigate flood impact. Among others
include flood modification, property modification
and response modification.
Flood modification is a traditional method of
mitigation that deals with the use of structural
measures to keep water away from development. It
requires the government to allocate some funding
which involves modifying the flow of flood water.
Examples of measures are levees, dams, diversions
810

GEOMATE - Mie, Japan, Nov. 21-24, 2017and channel improvements, flood gates anddetention basins.
Property modification measure, a non-structural
measure, refers to the placement of development bykeeping away from flood prone area using land use
planning or building design. Examples of thismeasure are zoning and land use planning, voluntary
purchase or acquisition, building regulations andhouse raising.
Response modification places more emphasis on
risk management as it seeks to modify humanbehaviour through activities such as planning,warning system, education and awareness campaign.
Examples of this measure are state and national
emergency services response, forecasts and warning
systems, preparedness (planning for emergency) andinformation and education programs.
Nevertheless, each approach has its strengths andweaknesses. Flood modification requires a heftyamount of funding to be implemented. Usually, theresponsibility of this approach lies on thegovernment to prepare for a big budget to tackle
areas that are currently located in flood prone areas.
Property modification will only be effective in a new
development area. However, most of the floodincidences occurred in an area in which thedevelopment had been completed. Sometimes it may
affect areas which had never experienced flood
before. Response modification will be a reactive
measure in life-saving. Nevertheless, all theseapproaches should be implemented in countries thatare facing flood risks.

MelakaIn this study, Melaka was selected as its study area.
This is because Melaka has a lot of tourism areas
and flood posts high impact on its wellbeing,
economically and socially. The worst flood that everoccurred in this state was in December 2006. Areas
that were affected are Sungai Melaka river basin,
Sungai Duyung and Sungai Kesang. Almost 70.4
hectares of its area was flooded with a height of 1.5
meters. Almost 19000 families were evacuated. Lossof properties and public facilities reached almost
RM54.139 million. [6].
Melaka is one of the states in Malaysia thatexperiences flood annually. It has three main
districts namely Alor Gajah, Melaka Tengah andJasin. Most of the tourists’ attractions are located in
Melaka Tengah District. Figure 1 shows the locationof the districts in Melaka.

Fig. 1 Districts in Melaka.

Impact of Flood on Economy

Melaka experiences flood annually. According toMelaka State Structure Plan Report (2011) thesefloods occurred to heavy rains, overflow river
stream and high tide. Table 1 shows the number ofareas that were affected by flood annually according
to districts [6] from 2011 until 2015.

Floods have coast a lot of damages
socioeconomically [12]. It is most pronounced inurban areas which have high densities of people,
assets, economic activities and vulnerable
infrastructures. Malaysia experienced massive flood
damages in floods that occurred in 2011 and 2015.
However, according to [13] the estimated cost ofdamages in the 2014 flood in Malaysia is the worst
which is within RM 1 billion.

Table 1 Number of Areas Affected by Flood in
Melaka by Districts from 2011 to 2015 [6]Districts
Alor Gajah
Jasin
Melaka Tengah

METHODOLOGYThis study employs a quantitative approach. It uses
secondary data which are basic data retrieved fromMelaka State Government official website, flood andmitigation measures from the Department of
Irrigation and Drainage (DID) Melaka Tengah,
mitigation measures from Melaka State Structure
Plan and also demographic data from the
Department of Statistics Malaysia.

‘11
5
2
2

‘12
7
5
15

‘13
2
2
1

‘14
15
21
40

‘15
14
18
36

Figure 2 shows the flood area in Melaka. Most
the affected areas are located in Melaka Tengah andJasin districts.

811

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Warning systems are also placed at strategicareas along the rivers that often overflow. Oncewater level reaches a danger zone, the warning
system will signal a siren to the water station.
Melaka has five flood warnings systems which areplaced in Lubok China, Kg Gadek, Pekan Jasin,
Parit Sidang Seman (Sg Rambai) and Taman Malim
Jaya.
Mitigation measure: Melaka State Town andCountry Planning Department and Local Authority
Fig. 2 Rivers and flood affected area (DID Melaka
Tengah, 2016)

Flood areas are considered as sensitive areas fordevelopment by the State Town and Country
Planning Department [7, 8]. Most of these flood
affected areas are located in the buildup areas,
especially in Melaka Tengah. The only mitigation
measures that are documented in the structure andlocal plan include increasing drainage capacity tohandle the flood, to control flood affected areas
effectively [8] and to provide a complete irrigation
system to overcome flood issues [7].

FINDINGSThis study employs a quantitative approach. Bothdata and information on flood and mitigation
measures obtained from the Department of Irrigation
and Drainage, Melaka Tengah were analysed.
Similarly, data and information on economic
indicators from Melaka State Government official
website were also analysed.

Population Distribution in Melaka
Melaka has a population of 790,136 people
distributed in its three districts; Alor Gajah with
173,712; Jasin with 131,539; and Melaka Tengah
with 484,885 [9]. Melaka Tengah has the highest
number of the household of 119,120. Alor Gajahranked second with 40,385 and finally Jasin with
31,888. According to Moran’s I analysis, thedistribution of households is slightly significant witha p-value < 0.05 (0.03), z = 2.14. Local Indicator
Spatial Association (LISA) analysis shows that its
working population is concentrated in Melaka
Tengah. Figure 4 shows the output of this analysis.

Mitigation Measures in Melaka
Melaka has taken a drastic measure to address flood
issues in its state. Two main approaches are being
used which are flood modification and response
modification.
Flood modification: Water Reservoir, Detention
Ponds and Warning System
Melaka through the Department of Irrigation andDrainage builds a water reservoir and detention
ponds to alleviate the flood water from overflowing
into the city and build up areas. These reservoirs anddetention ponds are controlled by water gates.
Figure 3 shows the water reservoirs and water gatesin Melaka.

Fig. 4 LISA Analysis on working population
Fig. 3 Water reservoirs in Melaka (DID Melaka
Tengah, 2016)
812

GEOMATE - Mie, Japan, Nov. 21-24, 2017used have been effective in reducing the cost ofdamages among the household.

Economic Indicator in Melaka from 2011 to 2015
Melaka relies heavily on three main economic
sectors namely services, manufacturing, andagriculture. However, services and manufacturingcontributed more than 75% in its gross domestic
product (GDP) annually for the past six years [10].
The outcome reflects the importance of tourism
relatedproducts
suchasattractions,accommodations and eateries. Table 2 shows thegross domestic product for Melaka from 2011 to2015.

DISCUSSION AND CONCLUSION
Do the mitigation measures heavily taken by the
Department of Irrigation and Drainage, Departmentof Town and Country Planning and the local
authority make any difference to Melaka’s GDP?
The results of Bivariate’s Moran’s I show a negative
correlation between 2012, 2014 and 2015 flood
affected areas. This is also reflected in GDP.
Mitigations measures taken by the authorities havehelped minimise the negative impact of flood
although the numbers of affected areas are morefrom the previous years.
However, development in any areas should be
carried out sustainably. The United Nations has
proposed the Sustainable Development Goals todemand all the countries in the world to becommitted to handling climate change issues andflood is one of them [11]. Although some of the
mitigations measures seem to be effective,
developments should be controlled sustainably. The
mitigations employed today might not be able tohandle future disasters if preventive measures
regarding sustainable developments are not handledproperly.

Table 2 Gross Domestic Product (%) by Sector,
Melaka from 2011 to 2015
SectorServices
Manufacturing
Agriculture

‘11
46.2
41.6
9.3

‘12
52.5
23.2
9.8

'13
53.2
22.9
9.5

‘14
53.4
23.0
9.2

‘15
53.5
23.0
8.9

Floods that occurred in 2011 and 2015 werequite bad. These two floods hit many states in
Malaysia including Melaka. Costs in damages inthese floods were not revealed to the public andunknown to researchers. The only analysis that canbe done is by using the percentage of gross domestic
product (GDP) disclosed yearly. Since the available
data is only until 2015, it is quite difficult to observe
the impact of the flood in 2015. As shown in Table 2,
a flood that occurred in 2011 does not give any
negative impact to Melaka’s GDP. Similarly tofloods that occurred in 2014. GDP for both services
and manufacturing sectors are on the increasing side.
However, agriculture sector experienced a declining
percentage in 2015.
Due to limited data availability, a Bivariate
Moran’s I analysis was carried out to only examine
the correlation between flood affected areas from2011 to 2015 and the total household. Melaka washit badly in flood Table 3 shows the Moran’s I scoreaccordingly.

ACKNOWLEDGEMENTS
Authors wish to thank the University of Malaya for
grant no. BKP011/13 and Department of Irrigation
and Drainage Malaysia Melaka for their strong
supports.
REFERENCES[1] Millard-Ball, A, “The limits to planning: causal
impacts of city climate action plans”, J. of
Planning Education and Research, 2012. Vol.
33(1), 2012, pp. 5-19.
[2] Burby, RJ, “Hurricane Katrina and theparadoxes of government disaster policy:
bringing about wise governmental decisions forhazardous areas”, The ANNALS of theAmerican Academy of Political and Social
Science, 2006, Vol. 604(1), pp. 171-191.
[3] Eliasa Z, Hamin Z, and Othman, MB,“Sustainable management of flood risks in
Malaysia: some lessons from the legislation in
England and Wales”, Procedia - Social and
Behavioral Sciences, 2013, Vol. 105(2013), pp.
491-497.
[4] Diya, SG, et al., “Floods in Malaysia: historicalreviews, causes, effects and mitigations
approach”, Int. J. of Interdisciplinary Researchand Innovations, 2014, Vol. 2(4), pp. 59-65.

Table 3 Results of Bivariate Moran’s I Analysis
Flood
2011
2012
2013
2014
2015

Morans’I Score
0.191-0.4990.496-0.467-0.477

The negative correlations can be observed inflood affected areas in 2012, 2014 and 2015. The
result shows the higher number of affected areas islocated in areas with a low number of households.
Thus, these results show the mitigation measures813

GEOMATE - Mie, Japan, Nov. 21-24, 2017[10] Melaka State Government. Basic Data. 2017[cited 2017 20 April]. Available from:https://www.melaka.gov.my/en/media/publicati
ons/basic-data?set_language=en.
[11] United Nations. Sustainable Development Goals.
Sustainable Development Knowledge Platform
2015 [cited 2017 27 February]; Available from:https://sustainabledevelopment.un.org/sdgs.
[12] Svetlana, D., D. Radovan, and D. Ján, The
Economic Impact of Floods and their
Importance in Different Regions of the World
with Emphasis on Europe. Procedia Economics
and Finance, 2015. 34: p. 649-655.
[13] Akasah, Zainal Abidin, & Doraisamy, Sunitha
V. (2015). 2014 Malaysia flood: impacts &factors contributing towards the restoration ofdamages. Journal of Scientific Research andDevelopment 2(14), 53-59.

[5] Chan, NW, Impacts of disasters and disasters
risk management in Malaysia: the case of floods,
in Economic and Welfare Impacts of Disasters
in East Asia and Policy Responses, in Sawada,
Y and Oum, S, Editor. 2012, Jakarta: ERIA, pp.
503-551.
[6] DID, Urban storm water management manualfor Malaysia, 2000a Kuala Lumpur: Departmentof Irrigation and Drainage Malaysia.
[7] Jabatan Perancangan Bandar Dan Desa Negeri
Melaka, Rancangan Struktur Negeri Melaka.
2005, Jabatan Perancangan Bandar dan Desa
Semenanjung Malaysia: Melaka. p. 1 - 298.
[8] Majlis Bandaraya Melaka Bersejarah,
Rancangan Tempatan Daerah Melaka Tengah
2005 - 2015, M.B.M. Bersejarah, 2005, Majlis
Bandaraya Melaka Bersejarah: Melaka[9] Department of Statistics, Population distribution
by local authority areas and mukims. 2010,
Putrajaya: Malaysian Department of Statistics.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PROPOSAL OF A FLOATING-TYPE ENVIRONMENTAL
PURIFICATION FACILITY INCORPORATING THE FUNCTION OF
TIDELAND1

Sato Shinji1, Yuji Yamakage2
Department of Oceanic Architecture and Engineering ,College of Science and Technology,
Nihon University,Japan
2
Daiwa House Industry Co., Ltd., Japan
ABSTRACT

Landfill in Tokyo Bay has a direct effect on the disappearance of tideland and shallow waters. Former
tideland is a habitat for benthic creatures with the function of decomposing organic substances flowing out fromthe land area, which were eaten by small fish and served as a feeding point for migratory birds feedingthem.Also, in recent years, aquatic plants such as combs forming seaweed beds are being reviewed as being
superior to onshore plants in function to absorb CO2 and produce oxygen. In addition, since seaweed is also
expected as a fuel for biomass power generation in recent years, this economic value is great.
In other words, regenerating tidal flats and seaweed beds in Tokyo Bay will contribute not only toenvironmental improvement of the sea area, but also to CO2 reduction as well as alternative energy source,which will greatly contribute to our lives.
In this study, we propose a floating type purification facility incorporating the functions of tideland andshallow waters in the northwestern coast of Tokyo Bay and proposing artificial tideland and seaweed bed
regeneration.
Keywords: Tideland,Seaweed, bed, Environmental improvement, Alternative energy source, Floating typepurification facility
In response to these circumstances, the Tokyo
Metropolitan Government has been implementing
policies for water quality purification through the
expansion of sewage treatment plants in the landarea to improve the quality of water in Tokyo Bay.
However, such measures to improve water quality
only in the land area are currently not a direct
countermeasure for the entire sea area.
Also, in recent years, aquatic plants such as alga
forming seaweed beds are being reviewed as being
superior to onshore plants in the function to absorb
CO2 and produce oxygen. In addition, seaweed isalso expected as a fuel for biomass power generationin recent years, so this economic value is great.
In other words, regenerating tidal flats andseaweed beds in Tokyo Bay will contribute not only
to environmental improvement of the sea area, butalso to CO2 reduction as an alternative energy
source, which will greatly contribute to our lives.
In this research, we propose a floating typepurification facility incorporating the functions oftideland and shallow waters in the north west ofTokyo Bay. This aims to improve the environment
including the ecology of Tokyo Bay. In addition, thetideland and seaweed bed of this floating structure
are planned to be an offshore resort of Tokyo Bay.
There, it becomes a new type of accommodation
type resort facility that can experience and learn theenvironment through various researches and power

1.INTRODUCTION
Japan has become a blessed country by the higheconomic growth of the 1960s. As a result, various
forms of land use such as logistics, transportation,commerce, residential, heavy industry and park wereextensively conducted. On the other hand, it faced
many environmental problems such as air pollution,
global warming, marine pollution, illegal dumpingof waste, exhaustion of resources, etc.
In Tokyo Bay, reclamation in the coastal area
was activated for land use from the 1960s, and 15%of the surface area was landfilled [1]. On the land
landfilled, environmental problems such as red tideand blue tide caused by domestic wastewater andindustrial wastewater have become frequent in thewaters while logistics and industries are developing.
Landfill in Tokyo Bay has a direct effect on thedisappearance of tideland and shallow waters [2].
Former tideland is a habitat for benthic creatureswith the function of decomposing organic
substances flowing out from the land area, whichwere eaten by small fish and served as a feeding site
for migratory birds feeding them. In these waters,
fish and shellfish played an important role as aspawning place for laying eggs. Furthermore,decomposition of phosphorus and nitrogen was
carried out in algae formed by seaweed spreading inshallow waters.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

generation using seaweed. These proposals areinvestigations considering feasibility study.
2. Background of the plan

Fig.1

Landfill distribution in Tokyo Bay[3]2.2.1 Importance of tideland
Wetlands such as tidal flats have become
effective on 1975 (December 21), with the Ramsar
Convention, meaning that it is very important as awaterfowl habitat, nurturing diverse organisms.
Concluding countries have registered 2208 wetlands
in 168 countries. In Japan, 50 places are registered,and only Yatsu tidal flat is registered in Tokyo bay.

2.1.1 Transition of Tokyo Bay by Reclamation
The area of the bay in Tokyo Bay is 138,000 ha,
but due to various developments about 26,000 ha has
been landfilled so far. It is said that it decreased by
20% from the former area[1]..
Table 1 Landfill area by Tokyo Bay birthday

2.2.2 Reduction of migratory birds
Sea birds with wetlands as a place to relax havebeen confirmed to decrease by 40 to 50% due tolandfill. Moreover, the data of only Yatsu tidal flatsaccording to the data of "Tokyo Bay Sigi, Tidri allover the same survey" shows a clear declining
tendency in which 108 birds were confirmed in 2012,14 birds in 2016.

2.1.2 Reduction of tideland / shallow area bylandfill
In the Meiji era (1868 - 1912's), tidal flats spread
continuously from the bay to the mouth of the mouth.
However, to date, 26,000 ha, which is 20% of thearea of the bay (138,000 ha), is landfilled, the tidal
area has been lost to 8,000 ha (6% of the bay area)
since the 1950s, .
Tidal flats have inhabited a wide variety ofbenthic organisms and have been responsible for the
spawning and growing areas of living creatures inthe sea, the role of migratory birds' important feeds
and the function to purify sewage in rivers. The
functions of this tidal flats are now reviewed, andthe movement of tideland function conservation isincreasing among citizens to conserve the rich
ecosystem.
In addition, it has been found that there is a big
difference between simply purifying water quality
and the environment where living things are easy tolive. Furthermore, recent studies have revealed thatcreatures do not increase in Tokyo Bay as long as itincreases not only tidal flats but also algae fields andshallows of seaweed.

2.2.3 Changes in Catches
In Tokyo Bay, various fisheries such as shellfish
fishing, fishery and algae fishery are still being
conducted. However, it is far less than the catch as
in the past, making it difficult to continue fishing. In
recent reports by the Tokyo Bay Study Group, theyield has been decreasing for many fish species,
suggesting the possibility that the lumps of water
caused by poor oxygen have an adverse effect on thegrowth environment of the fish species ing. In
addition to the lump of poor oxygen, "Reduction /disappearance of habitats such as shallow and tidal
flats" is considered to be one of the causes of theslump of biological resources.

Fig.2 Changes in catches and landfill area[4]2.3.1 Forest of the sea
In recent years, the phenomenon "sea breeze"
which seaweed in the sea has disappeared and thesurface of the rock of the sea bed is covered with816

GEOMATE - Mie, Japan, Nov. 21-24, 2017

white or pinkish lime algae has become remarkable.
This may be caused by artificial effects such as
rising seawater temperature and water pollution,
supply shortage of iron required for algae growthand damage of algae useful due to sea urchins andfish.
Because seaweed beds are also the habitat forfish spawning and frying, it is easy to imagine that it
will have a major impact on the underwater
ecosystem. This directly leads to a reduction incatches. The "sea forest" in Tokyo Bay, which has
been rich, is said to be "desertification of the sea" inrecent years. This is because natural purification
action of seawater is not properly performed, whichindicates that artificial environmental conservation
measures are indispensable.

total of five scenarios were set and examined.
As a result, the CO2 fixed amount is the highest
at about 17,500 t-CO2 per year when only green
algae (Minami aonori) are produced, and it is thesmallest at approximately 8,300 t-CO 2 per year
when only brown algae (seaweed) are produced I
found out.
Table 2 Annual carbon dioxide fixed amount by
seaweed culture [6]2.3.2 Regeneration of "Sea Forest" by humanintervention
In recent years, seaweed beds are not sufficientfor natural purification action, and artificial
measures for environmental conservation are
required. Therefore, since 2010 Kobe Steel Group,
which is a steel company, has begun to develop
marine area utilization of artificial reefs bysteelmaking slag in Okinawa Prefecture and Kobe
City. As a result of this marine area development by
this artificial reef, the effect as a population reef isdemonstrated, such as the glimpse of use as a habitat
for frying fish one month later.

2.4.2 New biomass energy
Regarding the use of renewable energy andrenewable energy, development of more effective
production technology is definitely required. In
recent years, bioethanol made from seaweed has
been recognized as renewable energy, and attracts
attention as it contributes to maintenance of the
global environment and reduction of GHG(greenhouse gas).
2.4.3 Biofuel production
Biofuel production from soybean is 1,900 L per
hectare per year and palm oil 5,950 L per year. On
the other hand, biofuel production from seaweed isremarkably high at 98,500 L, and it is known that it
has the ability to absorb ten times more CO 2 thantrees.

2.4 About how to use environmental load
2.4.1 About fixed amount of CO2 by algae culture
deviceIn the "CO2 marine immobilization / effective
utilization technology survey project[6]" participatedby Takenaka Corporation and the authors, theMinistry of Economy, Trade and Industry's
subsidiary research research project, CO2 fixation
using seaweed culturing equipment ,investigated.
The results are shown in the table.
In estimating the amount of CO2 fixationaccompanying the cultivation of algae, the casewhere only green algae (Minamionaori) was
produced (44.3 t-dry / day), the case where only red
algae (onia manori) was produced (23.0 t-dry / day) ,When green algae, red algae and brown algae were
produced at a ratio of 2: 1: 1 (32.1 t-dry / day) when
only brown algae (seaweeds) were produced (16.8 tdry / day), green algae In the case of producing
brown algae at a ratio of 1: 1 (30.6 t-dry / day), a

2.4.4 Green tideIn recent years, environmental problems called"green tide" have occurred in various coastal areas.
This is a phenomenon in which the seaweed Aosha
grows abnormally and accumulates on the coastline,
and various adverse effects such as the deteriorationof the landscape of the coastal area, the bad smell
accompanying the decomposition of the seaweed,
the death of shellfish such as clams are occurring.
As shown in 2.4.1, it is thought that it is useful forthe global environment in a dual sense thatenergizing environmental problems can reduce
expenses for removal and further produce profits
through production.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

facilities such as aquarium and hotel as assumed use.

2.4.5 Thalassotherapy
By introducing a facility incorporating natural
remedies such as seaside bathing seawater, blood
circulation promotion massage using seaweed andesthetics using sea mud, the effect of deepening
interest in the ocean by guests is there.

4. Basic plan
4.1 Calculation of the size of artificial tidal flats
In this project, we plan a floating body of 300 m
× 300 m, assuming that the area of the tidal flat is 9
ha. By doing so, we plan to recover 0.005% of thearea of tidal flats lost in Tokyo Bay so far. As statedabove, by installing floating bodies having various

3. Planning policy
3.1.1 Floating Flats- Floating function ① Artificial tidal land: Improve the migrationof migratory birds and the work of natural
purification② Seaweed bed: Water purification andrecovery of DO value Creation of ecologicalenvironment③ securing solar radiation: securing solar
radiation to the sea area by subdividing thefloating body
- Supposed introduction function ④ Resort hotel: induce publicity of Tokyo Bay
problem and measures⑤ Company: Make maritime countermeasuresby entering business in similar fields⑥ Research: artificial tidal flats, biomass,
plankton, seaweed⑦ Biomass: regenerate seaweed as a useful
resourcefunctions at ten locations, it is assumed that 0.75%
of the area of the tidal flat is recovered.

Fig.4 Increase due to tidal flats size in Tokyo Bay,Calculation of Recovery Rate
4.2 Site selection criteria① Area where river exists and inland watercrosses sea water② waters where characteristic landscapes exist③ Area where the DO value is low, poor
oxygen water mass is generated④ Sea area with floating structure possible
depth of water⑤ waters where concern about environmental
impacts such as sewage treatment plants areconcerned
Based on the above conditions and theconsideration of the marine environment based onthe "Tokyo Bay Water Quality Survey Report", wewill select the sea area off the Tokyo Disneyland at
the B type T22 point described in the report as thesite of this project.

Fig.3 Conceptual diagram of green floating
3.1.2 Introduction function
By using the floating function in 3.1.1 as thecentral function of this plan, the functions to be
introduced in other places can have diversity.
We plan to introduce facilities to produce
bioethanol from seaweed using biomass power
generation as well as commercial and tourist

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

assumed to be 128 rooms, and a thalassotherapyfunction incorporating marine resources is
introduced.
Table 3 Introduction function and scale

5.2 Securing an area to deliver light to the ocean
floor
By planning a large floating body of 300 m ×
300 m, a wide area shadow appears in the waters
under the floating body. For this reason, the floating
body is subdivided into 25 squares, and each isshifted at regular intervals, thereby securing an areafor delivering light to the seabed. In this project,when the floating body of 60 × 60 m is moved 3 m
at a time, the area where light is delivered is
calculated, and when it is shifted by 12 m, thestrength of the floating structure and the area wherelight is delivered to the seabed are optimal I foundout something. Other seaweed beds are supposed toilluminate the ocean floor by providing LED light as
an alternative function of sunlight.

Fig.5 Plan map in Tokyo Bay[5]4.3 Overall plan
The whole floating body is zoned into L letters,
and it is classified into three types of migratory birds,
tideland, and architecture. By doing so, we plan toplace restrictions on the rate at which humanintervention is intervened. As a result, shellfish suchas clams in areas for migratory birds will beprotected from the collection of human beings. In
the tideland, it is planned that tourists can observe
the ecological system of valuable Tokyo Bay
closely.The second level headings should be in 10pt,
bold, justified, and First Characters of Each Word
are in Capital font. Leave one blank line both before
and after the heading, respectively.

Fig.7 Percentage of appearance of light-transmitting
layer when 25 masses are separated by 5%
Fig.6 Conceptual diagram of floating body plan
5. Building plan
5.1 Introduction function and scale calculation
In this project, we plan to classify it into 3
buildings, hotel building, research building, power
generation building. We calculated the scale byreferring to the area ratio of various categories ofexisting resort hotels and other departments
responsible for functions such as drinking, banquet,
kitchen and management. The number of rooms is

5.3 Incorporate artificial tidal of tideland
By adopting the water depth adjustment function
by ballast water for the floating type structure, we
made it possible to artificially create tidal difference
which is characteristic of tideland. This will be a819

GEOMATE - Mie, Japan, Nov. 21-24, 2017

directing to the guests to see the tide difference as alandscape while staying in the center of Tokyo Bay.
5.3 Arrangement plan for seaweed bed
Place a 25 m wide seaweed bed on the outer sideof the 16 squares located on the outer periphery of
the floating structure. Also, in the 9 squares arrangedin the center, seaweed beds are spirally arranged oneach of the four sides. These seaweed beds aresupposed to adhere to the larvae flowing from thesurrounding seas and have a floating structure with
continuity with the tidal flats.

void to incorporate solar radiation into the seaweed
bed. Also, as the difference in level between
construction and water level changes due to thechange in water level due to tides, we planned theentire building as a high floor type like a pier.
Considering the influence of the sea breeze on
the accommodation building, we adopted a designthat blows the wind upward by raising the buildingof other functions.

5.4 Flow line planning
The flow line of general customers and the flowline of loading goods are done from the same
docking station, but we plan to separate them into a
hotel flow line and a carry-in flow line extending instraight line. In the interior of the building, wearranged plans that divide the categories and otherfunctions such as drinks, banquets, kitchens,
management, etc., into plans that emphasize theprivacy of the resort hotel.

1. Coastal areas are already under development bylandfilling of tidal flats and shallow fields, and there
is little room for regenerating these.
2. In the central part of Tokyo Bay there is plentyof room to build tidal flats and shallow spaces if you
remove the shipping routes for ship navigation.
3. When building floating tidal flats in the central
part of Tokyo Bay, it is necessary not to disturb the
ship's sailing and consider consideration to theseabed part so that there is no influence on thenatural environment and fishery.
4. In order to transmit light to the bottom of thesea while sufficiently satisfying the function oftideland and shallow, it is necessary to devise
arrangement and design of facilities.
5. It is quite promising in Japan to use seaweed
to fix carbon dioxide. Because Japan's land area isabout 380,000 square kilometers, which is 60th in
the world, it has eleven territorial waters and EEZ.

6. CONCLUSIONS

5.5 Planning of planning and arrangement ofwatersheds
We designed a plan for connecting floating
bodies subdivided into 25 squares based on theoverall plan of 4.3 and introduced the necessaryfunctions for construction purpose to it.
We arranged rooms to provide both the urban
dynamic landscape of Tokyo spreading to the northside and the natural landscape of the sea spreading to
the south. The accommodation building, the power
generation building, and the research building to be
introduced in this program are connected by acorridor integrating solar power generation units.
Moreover, by making production and researchfacilities publicly available, it becomes a facility thatwill be utilized not only as a resort but also as aplace for learning. In addition, the tidal flat on thefront of the hotel is open to guests all the time, andin addition to enjoying maritime recreation in places
facing the sea area, it also functions as a place toconduct educational experiences through lectures by
researchers.
Fig.8 Left：Floating bodies to Connecting circuit
Right：Placement plan

REFERENCES[1] Ports and Harbours Bureau MLIT/MOE ：Towards the reclamation of tideland network[2] Fisheries Agency ： Conservation of algae,
tideland and coral reefs[3] NILIM ： Outline of Tokyo Bay and its
watershed and issue on water environment[4] Fisheries and the environment in Tokyo Bay：
Current situation of the water environment inTokyo Bay[5] Tokyo Bay Environment Information Center：
The environment surrounding Tokyo Bay[6] Takenaka Corporation、 Heisei 24th Survey
businessofcarbondioxideocean
immobilization/
effective
utilization
technology、Department of Japanese METI、2013.Feb.28、.pp.552-563
http://www.meti.go.jp/meti_lib/report/2014fy/E
003661.pdf

5.6 Section planning
In the center of the guest room etc, plan a large

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

WALL OPENINGS AND ITS ABILITY TO MINIMIZE FLOOD
INDUCED FORCES ON RESIDENTIAL BUILDINGSNur Aqilah Ahmad Faisal1, Abdul Naser Abdul Ghani2 and Nuzaihan Aras Agus Salim3
Postgraduate; 2,3 School of Housing Building and Planning, Universiti Sains Malaysia, Malaysia

1

ABSTRACT
Flood induced forces could threaten the stability of residential building during flooding event. The building
will have to face the hydrodynamic pressures and sometime impact load from the debris carrying floods. A study
on the behavior of flood water movement through external wall were carried out to identify the various wall
opening dimensions and its capability to minimize the flood water forces on buildings. Two types of experiments
were carried out. First, a water flow table was used to visualize the water pattern diffusion. Next, flood tunnel
was used to measure the water velocity reduction response of the various walls. The wall opening configurations
were based on the common types of wall opening found in Malaysia. Generally, the results show that walls withbigger openings could withstand the water forces better. This is indicated by the smaller velocity reduction anddiffusion when the flowing water passes through the wall. However, the level of opening from the ground couldchange the overall performance of the various opening sizes as shown by some of the models. Therefore, further
studies should be carried out to determine suitable dimensional characteristics and level of the wall openings
from the ground. This could produce an optimum impact reduction wall design for residential building in floodprone area.
Keywords: Flood, Residential Building, Wall Opening, Water Velocity
INTRODUCTION
It can be seen that most Malaysians are lessconcerned regarding environmental issues especiallynatural disasters because they assume the issue is atrivial issue which ought to be resolved by theauthorities and government[3] and have made little
effort to face possible property damage in case offlooding. Flood induced forces could threaten thestability of residential building during flooding event.
The building will have to face the hydrodynamic
pressures and sometime impact load from the debris
carrying floods. Flood impact proofing or reduction
can be achieved by making adjustments to building
design and building components that could
withstand flood forces.

Floods are considered as the worst calamity
experienced in Malaysia [1]. As the most frequent
natural disaster in Malaysia it affected many areasand cause annual catastrophe and damages toinfrastructure, property, crops and other intangible
loss. There are no official categories of floods in
Malaysia but is often broadly categorized as
monsoonal, flash and tidal floods.
A study conducted by Kong et al.[2], on urban
flooding found that, 28% of respondents concurredthat flood is due to improper drainage system, 20%
cause is pollution, 18% the management ofurbanization and 16% cause is environment factor
and 11% weather while 7% because of dam break[2]. Figure 1 below shows the results of theirresearch.

Building Response and Flood Damage
A research by Vinet [4] concluded that theeffects of flooding caused damage to home, shops
and industries. Sani et al.[5] research concluded that,
there are at least 4 effects of flooding which
comprise water damage to houses, disruption oftransportation, reduction of income and damage offurniture and other appliances. However, majority ofthe population strongly believes that, water damage
to houses is the main effects of flooding. Hence, it isrecommended that buildings should be properly built
to avoid building on the floodplain and on the floodprone zones [5]. The main idea in the traditional
approach for estimation of direct flood damage

Fig. 1: Public perception of causes of flooding[2]821GEOMATE - Mie, Japan, Nov. 21-24, 2017

model a new tsunami resistant structure. This
research concludes a need to study on how building
configuration could be used to better withstand wave
loading.
A study on the effect of flood water diffuser onflow pattern using flow water table by Ghani andKasnon [20] have concluded that the longer thewave diffusion or the higher the wave amplitude, themore velocity can be reduced. Most closely related
to this study is the recent work of Ghani et al. [21]which utilized a hydraulic flume tank with sensors
placed before and after the diffusing objects to study
the velocity reduction effect in a 3-dimensional
hydraulic environment. The research conducted
identified suitable shape and dimension of objects
and its capability to reduce flow velocity across theroad. In order for a building to survive loading
forces from moving floodwater exerts on wall haveto be reduced. This comprises the external andinternal wall of a building. Debris resulted from highimpacted external wall may produce a greater load
compared to original moving water velocity. Thus,
laboratory experiments will be conducted to study
the effect of wall opening configuration towards its
velocity reduction through walls.

monetary terms is the concept of loss functions or
depth-damage functions [6]. In actual event, flood
damage is influenced by other factors such as flow
velocity, debris concentration, flood duration, leadtime and information content of flood warning, andthe quality of external response in a flood situation[7] [8] [9].
Distributed resistance parameters are needed for
local prediction of velocity [10] [11] which might berequired for damage assessment or predictions of
sediment erosion and deposition [12]. Based on
Becker et al. [13] findings, he concluded thatstructural failure comprises a large portion of the
response space for higher depth and velocity
combination under flood response scenarios. Thus,
by developing a greater understanding of building
response to high-velocity floodwaters through thistype of behavior modeling, actions could be
investigated that may improve resistance ofbuildings in flood-prone areas. A study by Grundy etal. [14] determine that a large proportion of deaths
could be linked to structural failure of buildings
since this prevented vertical evacuation from thefloodwaters, and damaged buildings createddangerous debris impacts. However, in addition todepth, water velocity has been shown to be a crucial
parameter with the potential to cause significant
damage [15]. The relationship between the (d x v)
factor and flood damage of buildings is the mostwidely acknowledged predictor of the effect of watervelocity. Yet, no further applied theoretical analysis
of how swiftly moving floodwaters affect buildings,
in terms of structural damage or in terms of theirability to provide for human safety [16].
This study is set out to identify the various wall
opening configurations and its capability tominimize the flood water forces on buildings.

Laboratory Experiment
In this laboratory experiment, the equipment
must be set up and functions properly include thewater visualization table, flood tunnel and camera to
take video of the test. The various wall configuration
models have been prepared for the experiment
purpose. The experiment will be conducted using
every type of typical configuration of wall openingof houses in Malaysia and the result gained byobservation of the experiment. The wall panel will
be varying in configuration of its door(s) andwindow(s), including their size(s). The size of themodel will use scale of 1:50 of the living size. The
experiment will only focuses on qualitative
observations regarding the flood water breaking,response, or diffuse through wall opening. This
research will run two types of experimental test
which are (1) flow water table to observe water
response pattern through wall opening configuration,and (2) flood tank to measure the velocity responseby wall opening configuration. The flow water table
experiment will only use the horizontal section of
the wall, whilst the flood tunnel experiment will
utilized a full height model. Observation method
will be used for data collections, which when theexecution of laboratory test is running, data will berecorded from the start until the end of the test. The
outcome of the water response and diffusion will be
witnessed and recorded as collecting data.

METHODOLOGYThis study utilizes laboratory scale experiments
to generate data for the parametric analysis. The
experiments and setups are based on several
previous related works in the study of flooding.
Ramsden [17] directly measured the lateral forces ona vertical wall due to long waves, bores, and dry-bed
surges instead of calculating the force from pressure
measurements. A study focuses on qualitative
observations regarding the structures response towave loading was conducted by Arnason [18] in asmall hydraulic wave flume with long aspect ratio(the controlled environment), theoretical predictionsof wave height and force aligned well with theory.
Thusyanthan and Madabhushi [19] have run a
research utilizes a small 4.5 m long tsunami wave
tank with waves generated by dropping a 100-kg
block in the water. One model of coastal structure
was designed similar to a common Sri Lankan houseand another one structure designed attempted to

Development of the Wall Model

822

GEOMATE - Mie, Japan, Nov. 21-24, 2017

A series of typical elevation of houses in
Malaysia especially in flood prone and affectedareas was selected and illustrated in accordance tolaboratory suitability. Flood affected area selected
for this case study is in Perak Tengah region whichmerely inundated by flood in December 2014.
Following are the typical elevations in Table 1.

7

8

9

Table 1: Wall Elevation Model
Model
1

Plan

Elevation

Flood Diffusion Pattern Experiment
The equipment used in this experiment werewater flow table, adjustable stand, water color,camera and double cello tape to represent the sectionof the walls. See Fig. 2 for the flow patternlaboratory testing instrumentation details.
As the configuration and size of opening areexpected to influence the breaking of the flood water,
9 models of different configurations were
established for experimenting the performance andreduce the impact towards opposite walls. The
experiment were carried out using the 9 patterns ofmodels’ sections as shown in Table 1 and the result
were acquired by observing the processes. The result
outcome will be recorded by video to observe it
more clearly without repeating the experiment.

2

3

4

5

‐

6

Fig.2: Flow pattern testing
flume as configure and time is taken at the external
and internal side of the wall to study the behavior offlow occurred when the flood water broke and hit
another wall. Velocities (V) of two points wererecorded and all the data obtained were comparedfor every model. This research make use of a small
flood tank measuring 1.15m long, 0.3m deep, and
0.25m wide (Fig. 4). Water was allowed to passthrough the models whilst data was being collected.

Flood Tunnel Model Experiment
Creating a flood event under laboratory
conditions requires a hydraulic flume andcontinuously flowing water. The flood tunnel was
set up as in Fig. 3 and Fig. 4 in which all the 9 3dimensional wall models were used to study thevelocity behavior effect in 3-dimensional hydrauliccondition. Water were circulated into hydraulic823

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 3: Plan of flood tunnel modelFig. 4: Flood tunnel model instrumentation
diffusion category.
DATA COLLECTION AND ANALYSIS
Table 2: Score and diffusion category

Based on the two approaches, data wereobserved and recorded for the 18 different models;nine numbers of 2-dimensional models for diffusion
pattern, and another nine 3-dimensional models forvelocity testing.
Flood Diffusion Pattern
By using the flow visualization table, theexperiments were conducted on 9 models ofdifferent wall configurations. The pattern ofdiffused flow were then divided into 5 point. Eachpoint of diffusion will be measured, and given ascore of 0 until 3 (0-3) which indicates; 0- Not
Affected (0.00cm), 1- Poor (0.10-0.60cm), 2Intermediate (0.70-1.30cm), 3- Good (1.402.00cm). The cumulative value of all five points
then resulted to diffusion pattern category of eachmodel. The diffusion pattern can be categorized
into three categories; (1) low, (2) moderate, and (3)high. The first category which is low diffusioncategory which obtained less than 7 total value offlow categories score. The second category ismoderate diffusion that obtained total value of 8 to
12 score on cumulative flow categories. High
category of diffusion described the most diffused
flow pattern which cumulated more than 13 scoreof flow categories. Thus, the experiments
observation were been interpreted based on

Model

Score

Diffusion
Category

1
2
3
4
5
6
7
8
9

6
10
13
10
8
11
12
12
9

Low
Moderate
High
Moderate
Moderate
Moderate
High
High
Moderate

Based on the 9 models experimented, one
produced low diffusion, five models categorized asmoderate diffuser, and three of them indicated highdiffusion pattern. Out of the nine wall
configurations, 3 configurations can be consideredas the most capable in defusing water flow. Model3, 7, and 8 are the configuration models that
produced the most diffusion. This is because these
configurations produced high deflection on mostpoints and have high number of wave amplitude.
As a general indicator, the higher the wave
amplitude, the more the velocity reduces. However,in this experiment, the magnitude of velocity
reduction cannot be verified numerically.
824

GEOMATE - Mie, Japan, Nov. 21-24, 2017

which is 75.3%. From these results it also can beseen that the reduction can be categorized in few
groups. 2 of them which are model 3 and 9
produced a very low reduction, model 1 and 2
produced a reduction in range of 28-30%
considered as low reduction, model 4, 6, and 7 witha reduction range of 47-50% which are quite high,and the remaining 2 models, 5 and 8 produced avery high velocity reduction.

Flood Velocity Reduction
This experiment focused on the flood watervelocity behavior before and after passing throughall the nine models. Table 3 shows the before andafter velocity.
It can be seen that all nine models produced
velocity reduction. The result showed based on
those models, the least reduction produced is 2.3%
by model 9, and the most reduction by model 8

Table 3: Velocity reductions
Model
1
2
3
4
5
6
7
8
9

Velocity Before(cms-1)
18.0
18.0
18.0
18.0
18.0
18.0
18.0
18.0
18.0

Velocity After (cms1
)
12.61
12.97
17.07
9.13
5.69
9.49
9.55
4.44
12.94

Velocity Reduction (%)

Reduction Category

29.7
Low
27.9
Low
5.12
Very Low
49.3
High
68.3
Very High
47.3
High
46.9
High
75.3
Very High
2.3
Very Low
suitable impact may exert on walls to produced
suitable diffusion and reduce optimum velocity
should be done.
.
CONCLUSIONDISCUSSION
Based on all the data that have been obtained
from flow diffusion experiment, we can conclude
that the wall configurations that give the mostdiffusion are model 3, 7, and 8. However, forvelocity reduction of those models are not in thesame category. Model 3 produced very low
reduction, model 7 produced high reduction whilstmodel 8 very high. It can be seen too that model 5
resulted a very high velocity reduction while it is
only categorized as moderate diffuser. We canconclude that the diffusion performance is not tallywith the velocity reduction. This may cause byother factors or parameters itself such as area andwidth of opening, that will affect the amount ofwater passed through in a time, or gap between
opening such as wall between windows or doorsthat will act as barrier that diffuse the flow andvelocity, etc. Becker et. al [16] suggested thatapplication of uncertainty investigation is favoredto gain further perception into how significant
building and flood parameters influence response.
Nevertheless, many uncertainties in the analysis
remain. Building response parameters have beensignificantly generalized for this research. Moredetail and reliable damage estimates could beobtained by acquiring more accurate estimations ofbuilding strength and response properties [13].
Further study on diffusion versus velocity should be
conducted. High reduction of velocity may result
from high amount of impact act on walls. Study on

Generally, the results show that walls withbigger openings could withstand the water forces
better. This is indicated by the smaller velocity
reduction and diffusion when the flowing water
passes through the wall. However, the level of
opening from the ground could change the overall
performance of the various opening sizes as shownby some of the models. Therefore, further studies
should be carried out to determine suitabledimensional characteristics and level of the wall
openings from the ground. This could produce an
optimum impact reduction wall design forresidential building in flood prone area.
ACKNOWLEDGEMENT
This work is supported by Universiti Sains
Malaysia RUI Grant No. 1001/PPBGN/814283.
REFERENCES[1] Chan, N. W. (2012), ‘Impacts of Disasters andDisasters Risk Management in Malaysia: The
Case of Floods’, in Sawada, Y. and S. Oum(eds.), Economic and Welfare Impacts ofDisasters in East Asia and Policy Responses.
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

study of Baldwin Hills, California. Advances
in Water Resources 32 (2009) 1323-1335.
[13] Becker, A. B., Johnstone, W. M. and Lence, B.
J. (2011). Wood Frame Building Response to
Rapid-Onset Flooding. Natural Hazards
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1527-6988/2011/2-85–95.
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[14] Grundy, P., Thurairaja, A., and Walker, G.
(2005). Some reflections on the structural
engineering aspects of tsunami damage. Proc.
Earthquake Engineering in Australia Conf.
2005, Albury, New South Wales, Australia.
[15] Kelmen,
I.
(2002).
Physicalfloodvulnerabilities of residential properties incoastal, eastern England. Ph.D thesis,
University of Cambridge, United Kingdom.
[16] Becker, A. (2008). Wood Frame Building
Response to Rapid Onset Flooding. A Thesis
Submitted in Partial Fulfillment of The
Requirements for The Degree of Master ofApplied Science in The Faculty of Graduate
Studies (Civil Engineering). Master of Applied
Science. The University of British Columbia(Vancouver) September 2008.
[17] Ramsden, J. D. (1993). “Tsunamis: Forces on a
vertical wall caused by long waves, bores, andsurges on a dry bed.” Rep. No. KH-R-54, W.
M. Keck Laboratory, California Institute ofTechnology, Pasadena, Calif.
[18] Arnason, H. (2005). “Interactions between an
incident bore and a freestanding coastal
structure.” Ph.D. thesis, Univ. of Washington,
Seattle.
[19] Thusyanthan, I. and Madabhushi, G. (2008).
Tsunami wave loading on coastal houses:amodel approach. Proceedings of ICE Civil
Engineering 161 May 2008 Pages 77–86 Paper
07-00037. doi: 10.1680/cien.2008.161.2.77[20] A.N. Abdul Ghani and N. Kasnon (2014).
Effect of Flood Water Diffuser on Flow Patternof Water during Road Crossing. MATEC Web
of Conferences 10 06006 (2014). DOI:
10.1051/matecconf/20141006006[21] Abdul Naser Abdul Ghani, Ahmad Hilmy
Abdul Hamid and Nursriafitah Kasnon. (2015).
Study on The Use of Obstructing Objects to
Diffuse Flood Water Velocity During Road
Crossing. Int. J. of GEOMATE, March, 2015,
Vol. 8, No. 2 (Sl. No. 16), pp. 1245-1249.

ERIA Research Project Report 2011-8, Jakarta:
ERIA. pp.503-551.
[2] Kong Yoke Yoon, Noor Azima Binti Bahrun,
and Yew Kun. (2010). A study on the urban
flooding. October 2010.
[3] Mohamad Sukeri Khalid and Shazwani Shafiai.
(2015). Flood Disaster Management in
Malaysia: An Evaluation of the Effectiveness
Flood Delivery System. International Journalof Social Science and Humanity, Vol. 5, No. 4,
April 2015. School of Law, Government andInternational
Studies,
Universiti
Utara
Malaysia,
Malaysia.
DOI:
10.7763/IJSSH.2015.V5.488.
[4] Vinet, F. (2008). Geographical analysis ofdamage due to flash floods in southern France:
The case study of 12-13 November 1999 and
8-9 September 2002. Journal of hydrology,361(1-2), 199-213.
[5] Sani G. Diya, Muhd Barzani Gasim, Mohd
Ekhwan Toriman and Musa G. Abdullahi.
(2014). FLOODS IN MALAYSIA Historical
Reviews, Causes, Effects and Mitigations
Approach.
International
JournalofInterdisciplinary Research and Innovations Vol.
2, Issue 4, pp: (59-65), Month: October December 2014.
[6] Pistrika, A. (2010). “Flood Damage Estimation
based on Flood Simulation Scenarios and a
GIS Platform”. National Technical Universityof Athens. European Water 30: pp. 3-11.
[7] Smith, D. I. (1996). “Flood damage estimation– A review of urban stage-damage curves andloss funtions. Water SA, 20(3), pp. 231-238.
[8] USACE. (1996). Engineering and Design. Risk
– based Analysis for Flood Damage Reduction
Studies. Manual No. 1110-2-1619.
[9] Kelmen, I. and Spence, R. (2004). An
overview of flood actions on buildings.
Engineering Geology 73 (3-4), pp. 297-309.
[10] Bates, P. D., Horritt, M. S., Smith, C. N., et. al.
(1997).
Integrating
remotesensing
observations of flood hyrology and hydraulicmodeling. Hydrol Process 1997;11 (14):177795.
[11] Horritt, M. J. and Bates, P. D. (2002).
Evaluation of 1D and 2D numerical models forpredicting river flood inundation. J Hydrol
2002;268:87-99[12] Humberto, A. G., Jochen E. S. and Brett, F. S.
(2009). Two-dimensional, high-resolution
modeling of urban dam-break flooding: A case826Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

APPLICATION OF A HYDROLOGICAL LAND SURFACE MODEL TO
WATER RESOURCES ASSESSMENT IN PENINSULAR MALAYSIA
Chee-Loong Wong1,2 , Zulkifli Yusop1,3 , Tarmizi Ismail1,3 and Raymond Venneker4
Faculty of 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
4
UNESCO-IHE Institute for Water Education, PO Box 3015, 2601 DA Delft, The Netherlands
1

ABSTRACTThis paper presents a land surface model application to water resources assessment in Peninsular Malaysia.
The approach enables to capture the spatial and seasonal temporal variability of the terrain characteristics, andcan be applied for time scales of one year or longer. The spatial resolution used here is 0.05 degrees(approximately 5.5 km). The results are presented in terms of mean annual evaporation and runoff for the period
1999-2004. The model performance in simulating mean annual runoff for this period is evaluated using observed
discharge data from 31 hydrological stations across Peninsular Malaysia, with drainage areas between 450 and
25,600 km2. A mean absolute error of 10% in the simulated mean annual runoff was found, after excluding threestations that are known to have significant upstream offtakes. A simple and mostly illustrative regional analysis
is carried out to assess the spatial and inter-annual variability of the available water resources and the relation
with population distribution. While a major part of the population is living in urban centres along the coast,
water resources must be drawn from a limited number of relatively small inland basins. The results are discussed
and compared with those of previous studies carried out for Peninsular Malaysia, where available. It is shownthat for annual time scales, the model configuration is able to assess the amount and spatial variation of natural
water resources, and has potential for application within a complex arrangement of multiple river basins or, if
required, arbitrarily-defined adminstrative regions.
Keywords: Water resources assessment, Land surface models, Water balance, Regionalization, Peninsular
Malaysia
hydrogeological and physiographic data, followedby regionalization to assess the spatial distribution
and temporal variation [1]. For Peninsular Malaysia,
the above-mentioned studies by Scalf [3] and Teh etal.[4] produced interpolated maps of potential
evaporation and runoff, respectively, using Penman
and Hargreaves evaporation methods and a simple
Thorntwaite-Mather water balance model withobservation data for 1960-1970. Althoughcomprehensive, the procedure was time-consuming
and involved. The results are still being used inmany current applications. A reassessment has notbeen carried out since.
Continuous monitoring and assessment of water
resources are important in relation to environmental
changes that occur at local, regional and global
scales due to economic development and population
growth. A review of the hydrological impacts fromchanges in land cover for Southeast Asia has beenpresented by [15]. In-depth analysis of flow records
in relation to the Malaysia water resources masterplan for 2000-2050 could not result in conclusions
on possible impacts of climate change and\slash or
short-term land-use changes on the water resources

INTRODUCTION
Water resources assessments are essential to thesustainable development and management of water
resources. Information about the extent andvariability of water resources is required to evaluate
the potential for utilization and control. A
combination of factors related to development,
human activity, population growth, and changes inland use and climate result in changing hydrologicalpatterns and trends that need to be monitored andassessed for future planning and development [1].
An early investigation in the water balance ofPeninsular Malaysia was carried out by [2].
Comprehensive studies by the Department of
Irrigation and Drainage (DID) provided further
insight in the regional water resources [3,4]. Other
studies have focused on understanding the small
scale hydrological processes related to land use andagricultural practice [5-9], the hydrologicalbehaviour at river basin scales [10-13], and water
use aspects [14].
A basic water resources assessment programme
involves collection and processing of hydrological,
827

GEOMATE - Mie, Japan, Nov. 21-24, 2017[16]. Xu and Singh [17] present a review ofrepresentative model approaches for assessment ofregional water resources under stationary andchanging conditions. An essential issue is the role ofthe land surface in partitioning the precipitation
between evaporation, rapid runoff and recharge togroundwater.
The objective of this study is to explore the useof a hydrological land surface model (LSM-A) toassess regional mean annual water resources overrelatively short time periods for humid tropicalconditions in Peninsular Malaysia. It also provides asimple, illustrative, assessment to obtain insight inthe variability of the water resources and available
water for the peninsula. The study is carried out forthe period 1999-2004.
Section 2 describes the general methodologicalapproach,
introduces
the
LSM-A
model
computations relevant to this study and presents an
overview of the data. Overall results and validationof the model performance against discharge
observation records are presented in Section 3. Abaseline analysis of the water resources availability
and variability are presented in Section 4. In Section
5, a discussion of the approach and conclusions are
given.

(1)Q PE
which is taken to represent an estimate of the mean
available water resources [17]. The procedure can beapplied to river basins delineated by the upslope
drainage area at any point in the model grid, or toarbitrary regions such as a State.
The model performance is evaluated using
observation records from discharge stations acrossthe peninsula. Subsequently, the model results areused to assess the regional mean annual water
resources availability and inter-annual variation for
the individual States, and for several of the majorriver basins in Peninsular Malaysia. We reportcomputed mean values as complete figures with anuncertainty at the 95% confidence interval, obtainedby applying a scale of ±1.96 to the standard errors
about the sample mean, assuming a Gaussian
distribution.
Model Description
The LSM-A land surface model is composed ofgrid-distributed land cover and soil components.
Land cover is classifified according to theInternational Geosphere-Biosphere Programme(IGBP) legend [20]. The leaf area index varies withspace and time according to an annual cycle of mean
monthly values. Soils vary spatially according to the
USDA soil texture classification [21]. The soil
profile is subdivided into five layers of downward
increasing thickness up to 2 m depth. The
atmospheric forcing consists of downward
shortwave and longwave radiation, precipitation,
windspeed, and air temperature, pressure andhumidity. The computed fluxes include the upward
radiation, the latent, sensible and ground heat fluxes,
the potential and actual evaporation, the surface
runoff production from infiltration or saturation
excess, and the soil percolation flux at the bottom of
the soil profile. In addition, the model also computes
the soil water content and soil temperature for thesoil layers.
A general characteristic of land surface models isthat model parameter values are prescribed
depending on land cover or soil types, and can beobtained from the literature. As such, calibration is
not commonly carried out. This may be considered auseful feature but on the other hand it is noted thatvalidation of land surface model output is notstraightforward since measurements of model
variables at grid scales are mostly unavailable. For
grid boxes with a vegetative cover, the effective
areal vegetation cover fraction cv (m2 m−2) isobtained from the Bouguer-Lambert-Beer relation
cv  1  exp  K 0 LAI(2)METHOD AND DATA
Methodology
The administrative system in Malaysia isarranged as a federation of states, see Fig. 1, which
has implications for conducting water-related
assessments. The land mass of Peninsular Malaysia,
also referred to as West Malaysia, comprises 11
States and two Federal Territories with a total areaof 135,000 km2, and a total population of 17,726,283
in 2000 [18]. For simplicity, this study includes theFederal Territories Kuala Lumpur and Putrajayawith Selangor State. Located between latitudes 1oN
and 7oN, a humid tropical climate characterized by
two monsoon periods prevails. Mean annual rainfall
is in the order of 2350 mm [19].
The LSM-A model computations provide dailyenergy and water balance output on a 0.05 degree(approximately 5.5 km) spatial grid, taking accountof spatial variability in land cover and soils. The
atmospheric input data are obtained from the gridded
daily hydrometeorological data set described byWong et al. [19]. The daily sum of the surface
runoff production and the soil water percolation are
subsequently accumulated and spatially averaged toobtain mean annual runoff for the period 1999-2004.
For time scales of several years or longer, short-termand seasonal variations in surface and subsurface
water storage are assumed to cancel out and thecomputed runoff production Q should represent thedifference between rainfall P and evaporation E, i.e.

where K0 is an optical attenuation coefficient,ranging 0.4−0.6 [22], and LAI is the leaf area index(m2 m−2).
828

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig 1 Major administrative division of Malaysiaq   q  Tsk  is the saturated specific humidity

The surface energy balance is written

Cv

dTsk
 Rn  H  LE  G
dt(kg kg−1) of the evaporating surface and qa is the
specific humidity of the air (kg kg−1). Furthermore, adimensionless surface resistance factor  is appliedin Eq. (7) to partition the latent heat flux between
evaporation from the wet canopy and bare soil, andtranspiration from the soil-vegetation root complex
using a resistance scheme as described by Essery et
al. [23].

(3)

where Cv is the surface heat capacity (J m−2 K−1), Tsk
is the skin temperature (K), t is the time (s), Rn is the
net radiation flux (W m−2), H is the sensible heat
flux (W m−2), L is the latent heat of vaporization (Jkg−1), E is the evaporation flux kgm−2s−1 and G is theground heat flux (W m−2). The surface heat capacity
for the vegetated part of a grid box is parameterizedfrom the water in the biomass and the waterintercepted by the canopy, i.e.

Cv 

Cw

w

wl LAI W v 

The soil heat transport is described by
T G
(8)
CT

z
t
where CT is the volumetric heat capacity of the soil
(J m−3 K−1), T is the soil temperature (K) and z is thedepth below surface. Parameterization of CT is
carried out following [24]. The soil heat flux isdecribed by Fourier's law, i.e.

(4)where Cw is the volumetric heat capacity of liquidwater (J m−3 K−1),  w is the density of water (kgm−3), wl is the mass of water per unit leaf area (set

T
(9)
z
where k is the thermal conductivity of the soil,
which depends on soil water content  (m3 m−3) andis parameterized following [25]. A zero heat flux atthe bottom of the soil profile is assumed.

to 0.5 kg m−2 and Wv is the intercepted water (kgm−2). The heat capacity for the unvegetated part ofof a grid box is assumed zero. The net radiation is
described by
4
R n  1   R S  R L   TradG  k  

(5)where  is the surface albedo,  is the surface
shortwave and longwave radiation fluxes (W m−2),
 is the Stefan-Boltzmann constant and Trad4 is the

The energy balance is solved numerically by
linearizing the surface fluxes to obtain an extended
Penman-Monteith formulation for the evaporation
potential. The actual evapotranspiration issubsequently derived by limiting the evaporation
flux to the available water in the soil and vegetation
storages [cf. 23].

LE  LC U q  q 

The vegetation water balance is described by Rutter
et al.[26]RL  are the downward

emissivity, RS  andradiative temperature (K). The sensible and latent
heat fluxes are obtained fromH  c p C H U Tsk  Ta


H

a

(6)
(7)

respectively, where cp is the specific heat capacity ofdry air (J kg−1 K−1),  is the density of the moist air(kg m−3), CH is the dimensionless heat transfer
coefficient, U the magnitude of the horizontal windspeed (m s−1), Ta is the temperature of the air (K),dWv
 c v P  Qv  E w
dt

(10)

where P is the above-canopy precipitation rate (kgm−2 s−1), Qv is the canopy interception drip rate (kg829

GEOMATE - Mie, Japan, Nov. 21-24, 2017

m−2 s−1) and Ew is the wet canopy evaporation rate
(kg m−2 s−1). The interception storage is capped by alimiting storage, which is proportional to the leaf
area index. The soil profile water balance per unit
surface area is described by the Richards equation

Q  w  wS
w
t
z

soil profile towards groundwater is parameterized as
gravity flow from the lowest soil layer, reduced by
the fractional soil water content above field capacity
reference conditions  N Q s   w K  N  sat  sat   ref (11)

where  N is the soil water content of the bottom soil

where  w is the density of water (kg m ),  is thelayer and  ref is the soil water content at field−1

volumetric soil water content (m3 m−3), Qw is the soil
water flux (kg m−2 s−1) and S is the plant root
extraction flux (m3 m−3 s−1). The soil water flux is
described by Darcy's law for unsaturated conditions,i.e.

capacity (m3 m−3). Soil water percolation is assumed
to stop for conditions below field capacity.
Percolation also ceases for very wet soil bottom
conditions that are taken to indicate highgroundwater levels. In effect, the groundwater
behaviour is unknown.

 

(12)
Qw    w  D
 K

z


where D is the hydraulic diffusivity (m−2 s−1) and K
is the hydraulic conductivity (m s−1). The
dependencies of both diffusivity and conductivity on
soil water content are parameterized using empirical
relations [27]. Subgrid infiltration and surface runoff
production are modelled using the method of
Schaake et al [28], which is based on a stochastic
distribution of time step accumulated fluxes. The
spatially averaged mean infiltration flux (kg m−2 s−1)
is given by

I sf 

1 Pn I ct Pn  I c

In the present application, the runoff for a
specified area Eq. (1) is computed as the timeintegrated spatial average sum of the surface runoff
production Eq. (15) and groundwater percolation Eq.
(16) over the target area.
Data
The land cover type distribution is derived from
MODIS 1km MOD12Q1 V004 products, based on
majority of occurrence in the period 2001-2004.
Table 1 shows the areal proportion of the covertypes after aggregation into the 0.05 degree modelgrid. The IGBP legend class for agricultural lands is
restricted to crops less than 2 m height. Malaysia has
extensive oil palm and rubber plantation stands,
which are classified together with natural tropicalforest as broadleaf evergreen forest. The mean
monthly leaf area index is derived from MODIS 8day 1km MOD15A2 V005 products for the period
2003-2007. The 8-day data were averaged into mean
monthly fields at 0.05 degree spatial resolution.
Table 1 shows the model grid average and range
distribution of leaf area index. Grid box-scaleeffective values are evidently smaller than thosetypically observed inside a forest stand or crop field.

(13)

where Pn  Qv t is the time step accumulated
input of water to the ground surface (kg m−2), i.e. thesum of the canopy drip and free throughfall fromprecipitation, and Ic is the cumulative infiltration
capacity (kg m−2). The latter is obtained here fromthe advancement of the wetting front and the nonsaturated fraction of the pore space, viz.

Ic  w

K sat

 sat

   t
sat

1

(14)

The USDA soil texture type distribution is
obtained from global 5 arcmin resolution maps ofsand, silt and clay separates that have been extracted
from the ISRIC-WISE global soil properties database linked to the FAO-UNESCO Digital Soil Mapof the World [29]. The data have been resampled
into grid resolution based on majority grid box area
fraction. Table 2 shows the areal distribution in themodel grid, with most of the area covered by loamy
types of soil. The areal distribution of separate
fractions and the resulting texture type classification
should be considered best-estimates on the basis of
the availability of soil profiles in the data base [29].

where Ksat is the saturated conductivity (m s−1),  sat
is the saturated soil water content (m3 m−3), and 1
is the soil water content of the top layer (m3 m−3).
The soil hydraulic properties are obtained from [27].
The surface runoff production is obtained fromQsf  Qv  I sf  Rsf

(16)

(15)

where Rsf is the saturation excess flux (kg m s−1),−2obtained from accumulating any oversaturated soil
water through the layers at the end of each time step.
The soil water percolation flux at the bottom of the830

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 1 Distribution of IGBP land cover type characteristics obtained from MODIS MOD12Q1 andMOD15A2 products aggregated on a 0.05 degree spatial grid. Coverage is tabulated as areal percentage forPeninsular Malaysia. Leaf area index is tabulated as the mean and uncertainty at the 95% interval, and theminimum and maximum of the mean monthly values, as applicable for the cover types.
Mean monthly leaf area index
Area
Land cover type
(%)
Mean
Min
Max

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

Evergreen Needleleaf Forest
Evergreen Broadleaf Forest
Deciduous Needleleaf Forest
Deciduous Broadleaf Forest
Mixed Forest
Closed Shrublands
Open Shrublands
Woody Savannas
Savannas
Grasslands
Permanent Wetlands
Croplands
Urban and Built-Up
Cropland/Natural Vegetation Mosaic
Snow and Ice
Barren or Sparsely Vegetated
Water Bodies

0.3

1.83 ± 0.12

1.45

2.26

86

3.60 ± 0.31

2.48

4.44

2.82 ± 0.25

1.46

2.80

1.39 ± 0.18

0.96

1.90

1.37 ± 0.10

1.18

1.79

2.11 ± 0.14

1.65

2.59

—
—
0.4
—
—
—
0.1
—
0.1
5.8
1.0
6.6
—
—
0.2

surface meteorological parameter values incombination with satellite observation-derived
radiation and cloud properties obtained from theNASA/GEWEX Surface Radiation Budget (SRB)
Release-3.0 data archive. Fig. 2 shows the locationof rainfall observing stations and the interpolated
mean annual rainfall field for the six years of thisstudy. An average number of 159 daily rainfall
observations from 175 rainfall observing stations
were available. The largest mean annual rainfall
amounts of more than 3400 mm occur along thenortheastern coast, mostly during the northeast
monsoon period from October to March. The
smallest mean annual rainfalls of 1800 – 2000 mm
are present in the southern inland and southwestern
coastal areas, and in the nortnern parts of thecountry. Refer to Wong et al. [19] for further
analysis of the atmospheric input data set.

Table 2 Distribution of USDA soil texture types
aggregated on a 0.05 degree spatial grid as areal
percentage for Peninsular Malaysia, as derived fromthe ISRIC-WISE [29] data.
Soil
Soil
Area
Area
texturetexture
(%)
(%)
type
type
Sandy
1 Sand—7
56
clay loam
Loamy
Clay
2
—
8
14
sand
loam
Silty clay
Sandy
0.3
9
—
3
loam
loam
Sandy
4 Loam
6,2
10
19
clay
5 Silt loam—
11 Silty clay—
6 Silt—12 Clay
4.5
The hydrometeorological input data used in thisstudy are provided by the gridded data set describedin Wong et al. [19], in which daily data fields ofpressure, temperature, humidity, wind speed andprecipitation were obtained from interpolating
station data, taking account of elevation and land
cover characteristics as appropriate. Elevation data
are derived from SRTM 30 version 2 data [30].
Daily input fields for downward shortwave andlongwave radiation are estimated from the gridded

SIMULATION RESULTS
Spatial Evaporation and Runoff
Fig. 3 shows the spatial distribution of thecomputed mean annual potential and actual
evaporation for Peninsular Malaysia over the sixyear study period. The potential evaporation shows asimilar pattern to the interpolated maps for forestand grass cover presented in the earlier study by831

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig 2 Location of rainfall observing stations (left panel) and the distribution of mean annual rainfall(mm) for 1999-2004 (right panel).

Fig3 Estimated mean annual evaporation (mm) in Peninsular Malaysia for 1999-2004. The left panel
displays the potential evaporation, the right panel displays the actual evaporation.
Scarf [3]. The highest potential evaporation valuesof 1500 – 1700 mm are computed for the coastalzone areas, where relatively high wind speeds occur
over low cropland vegetation.
The presence of tall forest in the inland areas
reduces the interpolated windspeed [19], resulting in
reduced mean evaporation potential. The potential
evaporation of 1100 – 1150 mm in the most central
mountainous inland areas computed here aresomewhat larger than those of 1000 – 1100 mm
estimated by Scarf [3], which may be due to a lessaccurate representation of the orography on the 5.5
km model grid. The maps in Fig. 3 also show thatthe mean annual actual evaporation estimate
compares close to that of the potential evaporation,
as can be expected for humid tropical conditions.
Given the relatively small spatial variation inmean annual evaporation, the spatial distribution of832

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig 4 Left panel: estimated mean annual runoff (mm) in Peninsular Malaysia for 1999-2004. Rightpanel: location of 31 discharge stations that were used for validation of the model simulation results.
mean annual runoff, i.e. the time-integrated sum of
the surface runoff production and groundwaterpercolation, shown in the left panel of Fig. 4
resembles that of the rainfall (Fig. 2). The rightpanel of Fig. 4 shows the location of discharge
stations that were selected for validation of thecomputed runoff, which is further detailed in thenext section.

based on the catchment area as resolved by themodel grid using a steepest descent delineation
method [31].
Sg. Johor and Sg. Muar are known to beextensively used for water supply purposes [16],which results in an overestimation of model runoff.
For the latter station, the discrepancy between
observed and simulated runoff is justified by the thematch for Sg. Segamat, a tributary downstream ofthe offtake. The Sg. Muda basin in Kedah State (seeFig. 1) is a complicated area as it supplies part of its
water for the Muda Irrigation Project along the west
coast [10,16]. Water is diverted from the most upperareas of the basin, which explains the overestimation
at Jeniang and to a smaller extent at Jam. Syed Omar.
However, at the most downstream station Ldg.
Victoria, the simulations match the observations,suggesting potential inconsistency in observation
records. Minor abstractions for water supply and/ or
irrigation water are known to affect Sg. Selangor, Sg.
Bernam and Sg. Lipis, Sg. Perak and Sg.~Besut[4,16]. Two relatively large reservoirs regulating Sg.
Perak and Sg. Terengganu are mostly used forhydropower generation and to some extent for flood
control. It is therefore assumed that besides possible
increase of open water evaporation the operations do
not significantly affect water quantities at annual
time scales.
The 18% underestimate at Sg. Triang is likely
explained by lack of rainfall data. The records for
two years from nearby rainfall stations did not passquality control as described in Wong et al. [32]. The
underestimate at Sg. Tembeling (18%) may possibly

Model Validation
Table 3 summarizes the runoff validation resultsby comparison with 31 hydrometric stations that
could be included in this study. Criteria for station
selection were: a minimum record of five years with
85% of available daily discharge data in the period
1999-2004; a catchment area larger than 450 km2 tocomprise a minimum of 14-15 grid boxes; and thatthe catchment area resolved by the model gridmatches within 20%. Two stations with known
rating curve problems during the simulation period
were also excluded. Nine stations lack one year ofdata, indicated by ‘(5)’ after the station location in
Table 3. For all station observation records, anaverage proportion of 8% of daily data are missing.
Only two stations (Sg. Pahang at Lubok Paku and Sg.
Muda at Jam. Syed Omar) have a complete record
without missing data. The mean absolute error in
gridded catchment area for all stations is 6%. The
observed annual runoff for the stations wascomputed from daily discharge values as archived in
the DID database and the catchment area as listed in
the station registry. The simulated annual runoff is833

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 3 Simulation validation results for 31 stations with minimum five years of sufficient data
during 1999-2004. The Data column gives the amount of daily observations and Δ denotes thedifference between simulations and observations.
Station location
Area
Data
Mean annual runoff (mm)
2
(km )
(%)
Observed
SimulatedΔ (%)
Sg. Johor di Rantau Panjang (5)1130
94740 ± 200983 ± 184
+33*
Sg. Sayong di Jam. Johor Tenggara
624
86
898 ± 211
1001 ± 154 +11
Sg. Kahang di Bt. 26 Jln. Kluang
587
901253 ± 214
1262 ± 97+1
Sg. Muar di Buloh Kasap
3130
92
410 ± 97554 ± 100
+35*
Sg. Segamat di Segamat
658
96
792 ± 135746 ± 225
−5
Sg. Selangor di Rantau Panjang
1450
951028 ± 134
1223 ± 116 +19
Sg. Bernam di Jam. SKC
1090
981360 ± 127
1413 ± 112 +4
Sg. Slim di Slim River Town (5)455911660 ± 440
1428 ± 104 −14
Sg. Pahang di Lubok Paku
25600
100
850 ± 181894 ± 114
+5
Sg. Pahang di Temerloh
19000
96
943 ± 123967 ± 135
+3
Sg. Triang di Jam. Keretapi (5)2000
87864 ± 185
709 ± 121
−18
Sg. Lipis di Benta
1670
96919 ± 241980 ± 174
+7
Sg. Jelai di Jeram Bungor (5)732085997 ± 203
1019 ± 227 +2
Sg. Jelai di Kuala Medang
2630
881294 ± 119
1190 ± 251 −8
Sg. Tembeling di Kg. Merting
5050
881094 ± 112
1060 ± 238 −3
Sg. Tembeling di Kuala Tahan (5)2700
941439 ± 124
1187 ± 315 −18
Sg. Kecau di Kg. Dusun (5)497
941025 ± 184
867 ± 201
−15
Sg. Perak di Jam. Iskandar
7770
94979 ± 160
1018 ± 193 +4
Sg. Kinta di Weir G di Tg. Tualang (5)1700
871394 ± 181
1284 ± 259 −8
Sg. Plus di Kg. Lintang
1090
92996 ± 251
949 ± 171
−5
Sg. Terengganu di Kg.Tanggol
3340
962608 ± 307
2144 ± 364 −18
Sg. Muda di Ldg. Victoria
4010
99
982 ± 279996 ± 228
+1
Sg. Muda di Jam. Syed Omar
3330
100
782 ± 236
946 ± 223
+21
Sg. Muda di Jeniang
1710
88
583 ± 185
850 ± 228
+46*
Sg. Ketil di Kuala Pegang (5)70488786 ± 271
853 ± 262
+9
Sg. Kelantan di Jam. Guillemard
11900
971188 ± 252
1291 ± 168 +9
Sg. Nenggiri di Jam. Bertam
4130
931134 ± 135
1122 ± 178 −1
Sg. Lebir di Kg. Tualang
2430
851581 ± 300
1413 ± 255 −11
Sg. Pergau di Batu Lembu
1290
91
2040 ± 278
1761 ± 293 −14
Sg. Besut di Jam. Jerteh (5)787951945 ± 523
1713 ± 332 −12
Sg. Golok di Rantau Panjang
1075
921502 ± 263
1555 ± 261 +4
periods of five to six years is equal to or better than
±10%. This figure compares favourably to the ±15%error that was determined for the procedure used by
Teh et al.[4]. The mean absolute error in annual
runoff for any year for the 28 stations during thesimulation period is 199 mm, which amounts to 16%of the mean observed annual runoff value. It should
be noted, however, that the rainfall stations are not
evenly distributed over the peninsula (Fig. 2) andthat the number of reporting rainfall stations also
varies from one day to another Wong et al.[32],which may have an influence on the results for someparts of the model grid.

arise from lack of orographic rainfall representationin the input data set. For Sg. Terengganu, possible
overestimation of evapotranspiration by the model in
the northeastern part of the peninsula (see Fig. 3)
may be the cause of the 18% deficit in simulated
runoff.
Stations with extensive abstractions as decribedabove are marked by an asterisk in the last columnof Table 3 and have been discarded from overall
error analysis. For the remaining 28 stations, themean absolute error between observation andsimulation of mean annual runoff during 1999-2004
is 8.8%. From this result, it is infered that the model
error in simulating natural mean annual runoff for834

GEOMATE - Mie, Japan, Nov. 21-24, 2017

APPLICATION TO REGIONAL WATERRESOURCESThe water laws in Malaysia stipulate a sharedFederal and State governance of water resources
with a large responsibility at State level. Details of
the legislative and institutional framework for water
resources management are described in Tan andMokhtar [33]. As a consequence, studies carried out
toinformwater
resources
management,
development and planning in Malaysia generally
need to summarize findings per State, as applicable.
The State boundaries do only partly coincide withbasin boundaries, whereas in some cases the rivers
are the boundaries.
The left graph in Fig. 5 presents the mean annual
runoff aggregated over the area of each State. Thereis a significant difference in available annual water
resources ranging from around 500 mm for Melaka
in the southwest to more than 2000 mm for
Terengganu on the northeastern coast. States with
substantial coastal area exposure, i.e. Kedah, Pulau
Penang, Perak, Selangor, Johor, Pahang, Terengganu
and Kelantan, have abundant runoff. The States of
Negeri Sembilan and Melaka, although locatedalong the coast, are part of the dryer zone extending
inland into the centre of the peninsula, which is
caused by rainfall shading from the mountain ranges
in Sumatra [32]. Inter-annual variability ranges±10% to ±28%, with the largest variations occuringin Pulau Penang and Melaka that are confined in
narrow zones on the west coast. Comparison withthe results in Teh et al.[4] suggests a reduction inmean annual runoff with respect to the period 19601970. It is impossible at this stage to judge if this isrelated to short-term climate variation, long-termclimate change, and/or human interference in theenvironment. However, in thirty years the
population must have significant grown. The rightgraph in Fig. 5 shows the water availability perperson, based on population statistics for the year
2000 [18]. The smallest mean annual water
availability per capita for Pulau Penang, Selangor
and Melaka is less than 1700 m3, which is generally
taken indicative for water stress conditions. These
States contain some 40% of the population on only
8% of the total area for Peninsular Malaysia. Manyof the major urban centres are located in the coastal
zones that need to fulfill their water demand fromupstream sources. Groundwater is hardly being
utilized in Peninsular Malaysia [16]. In reality,
States such as Pulau Penang and Melaka draw theirwater from outside their boundaries, either naturally
from a transboundary river basin or through watersupply. The shortage in Selangor is currently being
addressed by the development of the PahangSelangor Interstate Raw Water Transfer system,
involving a 45 km tunnel through the central
mountain range [16,33]. Water transfers are also
foreseen for the southern part of the Peninsula [16].
Characteristic for Peninsular Malaysia is thepresence of many smaller river basins along thecoast, which are less favourable for large-scale water
resources development due to either lack of
capacity, vulnerability, or marine influence. It is
more efficient to satisfy demand from the larger
inland basins. To assess this, five inland river basins
have been selected, using the hydrometric stations asbasin outlet for the sake of simplicity (Table 3).

Fig 5 Computed mean annual runoff (mm, left panel) and the available water resources (m3/capita, rightpanel) for the States of Peninsular Malaysia during 1999-2004. The error bars indicate the 95%
confidence level inter-annual variability. The estimated mean annual runoff (mm) as assessed by Teh etal.(1976) for 1960-1970 are indicated by black dots. PL: Perlis, KD: Kedah, PP: Pulau Penang, PR:
Perak, SG: Selangor, NS: Negeri Sembilan, MK: Melaka, JH: Johor, PH: Pahang, TR: Terengganu, KT:
Kelantan.
835

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig 6 Estimated mean annual water availability per person for selected basins in Peninsular Malaysia
during 1999-2004. The left panel considers only the population upstream of the hydrometric station.
The right panel considers the population in the entire basin up to the coast. The bar width is scaled bypopulation proportion.
Peninsular Malaysia during the period 1999-2004.
The simulations were carried out at daily time steps
using input from a previously developed griddedhydrometeorological data set [19]. The simulation
results were integrated to annual time scales andaveraged over area as required.
The model is based on commonly usedparameterizations found in land surface schemes ofatmospheric models, with minor adaptation towardshydrological application at smaller grid scales ofapproximately 5.5 km. One advantage of land
surface schemes is that model parameters can beregionalized by simply applying land cover and soil
type-prescribed parameter values reported in theliterature. As a consequence, the requirement forcalibration is absent, which is a major point ofpractical interest in application over large areas. The
land cover, seasonal variation in biomass and soil
description for the model are derived from global
data sets that are becoming more widely available.
On the other hand, the global character of such data
sets distinguishes a rather limited selection ofgeneric soil and land cover types, which may beinsufficient for some applications, such as thoserelated to agriculture. The grid-based structure, in
combination with regionalized parameters, provides
a direct means for water balance simulations in
ungauged (parts of) river basins, which is essential
in water resources assessment [1]. Moreover, in thepresent annual application, the results can be
aggregated over arbitrarily defined units, which isuseful within a water resources management
framework such as implemented in Malaysia.
For the purpose of validation, the model
simulation results were qualitatively compared withfindings in the literature and quantitatively evaluatedagainst observation records from 31 hydrometricstations across the peninsula. A mean absolute error

These are the Muda basin at Ldg. Victoria, theKelantan basin at Jam. Guillemard, the Perak basin
at Jam. Iskandar, the Pahang basin at Lubok Paku,
and the Muar basin at Buloh Kasap, and are themajor inland basins in the peninsula. The population
within the basin upstream of the stations and for thewhole basin were estimated using district population
statistics for 2000 [18]. The left graph in Fig. 6
shows the mean annual available water per person
considering only the population upstream of thegauging station. The right graph shows the meanannual available water taking account of the entire
population living in the basin up to the coast. The
simulated mean inter-annual variability for thebasins is ±17%. Comparing the height of the bars forthe same basin in the two graphs, it is clear that theratio of whole-basin population to upstream
population varies considerably among the basins,
ranging from 1.25 for the Pahang basin to more than
7 for the Perak basin. This is again related to thelocation of the major urban centres along the coast.
It should be noted, however, that there may exist
additional demand from coastal cities outside thestrict basin boundaries. Fig. 6 also indicates that the
per capita available water varies considerably perbasin. Provisionally, it would appear that the
Kelantan and Pahang basins have the largest
potential for development of their water resources.
However, it needs to be stressed that the simulations
provide natural runoff. Currently implemented
operations for irrigation, water supply and other uses,
are not reflected in the results shown here.
CONCLUSION
This study presented the implementation andapplication of the LSM-A hydrological land surface
model to assessment of annual water resources in836

GEOMATE - Mie, Japan, Nov. 21-24, 2017

malaysia; Water Resources Publication No.6;
Department of Irrigation and Drainage: Kuala
Lumpur, Malaysia, 1976.
[5] Abdul Rahim, N.; Harding, D. Effects of
selective logging methods on water yield andstreamflow parameters in peninsular malaysia.
Journal of Tropical Forest Sciences 1992, 5,
130-154.
[6] Noguchi, S.; Abdul Rahim, N.; Baharuddin, K.;
Tani, M.; Sammori, T.; Morisada, K. Soilphysical properties and preferential flow
pathways in tropical rain forest, bukit tarek,
peninsular malaysia. Journal of Forest
Research 1994, 2, 115-120.
[7] Ziegler, A.D.; Negishi, J.N.; R.C., S.; Abdul
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hillslope saturated hydraulic conductivity in a
tropical forest in peninsular malaysia. CATENA
2006, 67, 89-104.
[8] Henson, I.E.; Yahya, Z.; Noor, M.R.; Harun,
M.H.; Mohammed, A.T. Predicting soil water
status, evapotranspiration, growth and yield of
yound oil palm in a seasonally dry region inmalaysia. Journal of Oil Palm Research 2007,
19, 398-415.
[9] Chow, M.F.; Yusop, Z.; Shirazi, S.M. Storm
runoff quality and pollutant loading fromcommercial,residential, andindustrial
catchments in the tropic. Environmental
Monitoring and Assessment 2013, 185, 83218331.
[10] Ali,
M.H.;
Lee,
T.S.
Potential
evapotranspiration model for muda irrigation
project,
malaysia.
Water
Resources
Management 2009, 23, 57-69.
[11] Ab Ghani, A.; Ali, R.; Zakaria, N.A.; Hasan,
Z.A.; Chang, C.K.; Ahamad, M.S.S. A
temporal change study of the muda river
system over 22 years. International Journal ofRiver Basin Management 2010, 8, 25-37.
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[13] Tan, M.L.; Ibrahim, A.L.; Yusop, Z.; Duan, Z.;
Ling, L. Impacts of land-use and climate
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in spatial runoff prediction of 10% was found. An
example application to water resources assessment
illustrated the variability of water resources, as wellas the complex relation between the water resources
and the uneven population distribution for
Peninsular Malaysia. It is also shown that thisparticular type of models can be used with relative
ease within a rather complex basin arrangement.
The utility of models in water resources
assessment and management programmes isgenerally acknowledged [17]. The model describedhere can be applied to analyze the natural runoff,
which in turn can be used with stream flow
observations to monitor the effects of water
operations, such as for example water supply andirrigation offtakes, and diversions. Regularapplication in continuing assessment programmes
provides a means to follow the effects and variations
in hydrological regime due to short and long-termclimatic change and structural change in theenvironment.
A major limitation is that the present
configuration does not permit to assess seasonal andmonthly water cycle dynamics, which could be
useful for certain water resources management
applications. To this end, an extension of LSM-Awith a grid box-based runoff storage and routing
scheme has been investigated for three large basins
in Peninsular Malaysia (submitted for publication).
Further studies are being carried out to assess
whether the water resources in Peninsular Malaysia
have been impacted by climatic or physicalenvironmental changes during the last decades.
ACKNOWLEDGEMENTS
The authors thank the Department of Irrigation
andDrainage
Malaysia(DID),
Malaysia
Meteorological
Department(MMD),andNOAA/NCDC for providing the data.
REFERENCES[1] WMO. Guide to hydrological practices,volume ii management of water resources andapplication of hydrological practices. sixth
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World
MeteorologicalOrganization, Geneva: 2009; Vol. WMO-No.
168.
[2] Nieuwolt, S. Evaporation and water balances inmalaya. Journal of Tropical Geography 1965,
20.
[3] Scarf, T. Evaporation in peninsular malaysia;
Water
Resources
Publications
No.5;
Department of Irrigation and Drainage: Kuala
Lumpur, Malaysia, 1976.
[4] Teh, S.K.; Still, D.C.; Scarf, T. Average annual
surface water resources of peninsular
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resources in peninsular malaysia 2000-2050;
Economic Planning Unit, Prime Minister’s
Department: Kuala Lumpur, 1999.
[17] Xu, C.-Y.; Singh, V.P. Review on regional
water resources assessment models under
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838

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

BIFUNCTIONAL MICROCAPSULE FOR HEAT STORAGE AND
AITIBACTERIAL PROPERTIES PREPARED BY MICROSUSPENSIONIODENE TRANSFER POLYMERIZATION
Amorn Chaiyasat1,2, Siriluk Namwong1, Boontida Uapipatanakul1, Warayuth Sajomsang3, Preeyaporn
Chaiyasat1,2 *1Department of Chemistry, Faculty of Science and Technology, Rajamangala University of Technology
Thanyaburi, Pathumthani 12110

2

Advanced Materials Design and Development (AMDD) Research Unit, Institute of Research and Development,
Rajamangala University of Technology Thanyaburi, Pathumthani 12110
3

National Nanotechnology, 111 Innovation Cluster 2 (INC2 Building), Thailand Science Park,
Paholyothin Road., Khlong Nueng, Khlong Luang, Pathumthani 12120, Thailand

ABSTRACT
It is well known that the microcapsules encapsulating heat storage or phase change materials are coated onto
the fabrics for thermoregulating property. To increase their function on textile application, in this work,
bifunctional microcapsules having both thermal energy storage and antibacterial properties were fabricated.
Chitosan was used as surfactant of poly(methyl methacrylate-divinyl benzene) microcapsule encapsulated
octadecane (OD) prepared by microsuspension iodine transfer polymerization. The nonspherical with dent
microcapsules were prepared in acidic condition without any free polymethyl methacrylate particles nucleated byemulsion polymerization. Due to amino groups in chitosan chains were protonated in which presented positive
charge,the microcapsules stabilized with such molecules were then obtained without any coalescence. In
addition, percent yield of microcapsules decreased with chitosan concentration in aqueous medium. It may be
due to high viscosity of the aqueous medium where the monomer droplets are unable to maintain the shape inearly stage of the polymerization. For thermal properties, the latent heats of the encapsulated octadecane (234 J/
g-OD) were closed to those (233 J/g-OD) of bulk octadecane. For antibacterial property, 2 millimetres overcontrol sample of the resulting inhibition zones of both S. aureus and E. coli were observed. Based onbifunctional feature derived from both microcapsule core and shell for thermal energy storage and antibacterial
properties, respectively, the developed microcapsules would express a great potential for textile application.
Keywords: Heat storage materials; Antibacterial property; Microcapsule; Microsuspension iodine transfer
polymerization
phase change occurs [3]. One of the most famous
techniques for phase change material microcapsulepreparation is microsuspension conventional radical
polymerization due to high encapsulation efficiencyof phase change material [4, 5]. Various kinds ofpolymer shell are used for the encapsulation basedonmicrosuspension
conventional
radicalpolymerizationsuchaspolystyrene[6],poly(styrene-co-methyl
methacrylate)[7],
polydivinylbenzene[8,9],poly(styrene-codivinylbenzene) [10], poly(methyl methacrylate)[11] and poly(methyl methacrylate-co-methyl
acrylate-co-methacrylic acid) [12]. To the best of
our knowledge, among these polymer shells,
polymethyl methacrylate is the best one to provide
high latent heats of phase change material due tocompletion of phase separation between polymethyl

INTRODUCTION
Because all seasons of Southeast Asia are hot
and humid, thermoregulating fabrics or thermal
adaptable cloths and antibacterial fabrics are theninterested in the commercial production. For theformer case, microcapsules containing phasechange materials are often coated onto thefabrics[1, 2]. Because Paraffin waxes can melt andcrystallize at a wide range of temperature to absorb
and release energy, respectively, they then are
preferably used as phase change material andencapsulated in the microcapsules. Encapsulation ofparaffin waxes not only increases surface area forproviding a larger heat transfer but also prevents
phase change material reactivity to the outsideenvironment and controls the volume change as
839

GEOMATE - Mie, Japan, Nov. 21-24, 2017

methacrylate shell and wax core [13]. However,using microsuspension conventional radical
polymerization, approximately 35% of freepolymethyl methacrylate particles respects to total
monomer used were formed competition withmicrocapsules. In previous work, such phenomenon
can be overcome with microsuspension iodinetransfer polymerization which reduced radical exitfrom the monomer droplets to an aqueous medium[11, 14]. Chitosan is one of the most famous
biopolymer because its beneficial properties include
antifungal
andantibacterial
[15,
16],
neuroprotective [17], anti-inflammatory [18] and soon. Since chitosan contains amino group in its chain
which was protonated to give positive charges inacidic condition, it may able to be used as thesurfactant of microsuspension polymerization inplace of the conventional one as polyvinyl alcohol.
To the best of our knowledge, there is a lack of
research for phase change material microcapsulepreparation using chitosan as a surfactant inmicrosuspension iodine transfer polymerization.
Therefore, in this research, the preparation ofbifunctional microcapsule for both heat storage andantibacterial properties by microsuspension iodinetransferpolymerizationusing
octadecane,
polymethyl methacrylate and chitosan for phasechange material core, polymer shell and surfactant,respectively, was studied in the first time. The
influence of chitosan concentration on theencapsulation efficiency was investigated.

homogeneously dissolved in 2.50 g of octadecane,
0.02 g of CHI3 and 0.20 g of benzoyl peroxide as
oil phase. It was then added to 45 g aqueous
solution containing either 1%wt of poly(vinyl
alcohol) or chitosan before homogenized at 5,000rpm for 5 minutes to prepare monomer droplets in
oil in water emulsion. Thereafter, the obtained
polymer suspension was subsequently transferred toa round bottom flask, sealed with a silicone rubber
septum and purged with a vacuum/N2 cycle for fivetimes (finally in N2). It was finally polymerized at
80 °C for 3 hours and following at 90C for 5 hours
at a stirring rate of 500 rpm. The concentration of
chitosan was varied as shown in Table 1.
Table 1 Recipes for the preparation of polymethyl
methacrylate/octadecane(50:50wt%)
microcapsules prepared by microsuspension iodinetransfer polymerization
Phase
Ingredients
MMA (g)2.50
2.25
DVB (g)
0.00
0.25
OD (g)
2.50
2.50
Oil
BPO (g)0.20
0.20
CHI3 (g)0.02
0.02
Surfactant
45.00a45.00b
Aqueoussolutiona (g)Abbreviations: MMA, methyl methacrylate; OD,
octadecane; BPO, benzoyl peroxide; CHI3,
iodoform; CS, chitosan; PVA, polyvinyl alcohola
PVA solution 1 wt% or CS solution at 0.25, 0.50
and 1.00 wt%b
1 wt% of CS

2. EXPERIMENTAL
2.1 Materials
Methyl methacrylate (Aldrich, Wisconsin, USA;
purity, 99%) was purified by passing through thecolumn packed with basic aluminum oxide toremove the polymerization inhibitors before use.
Octadecane (Merck, Munich, Germany; 99.5%)
was used as received. Reagent-grade benzoyl
peroxide (Merck, Munich, Germany) was purified
by recrystallization. Iodoform (CHI3; Aldrich,
Wisconsin, USA; purify, 99%), poly(vinyl alcohol)(Aldrich, Wisconsin, USA; degree of saponification
87-90%, molecular weight 3-7x104 g/mol) andChitosan were used as received.

2.3 Characterization of microcapsules
The microcapsules encapsulated octadecane
were observed with an optical microscope (SK100EB&SK-100ET, Seek, Seek Inter Co. Ltd.,
Thailand) and scanning electron microscope (JSM6510, JEOL, JEOL Ltd., Japan) to study themorphology of the particle surface and shape,
respectively. For scanning electron microscopeobservation, a few of dried microcapsules wereplaced on a nickel stub and dried before Au-coated.
For the measurement of thermal properties, themicrocapsules were washed with 2-propanol before
dried in vacuum oven. The octadecane content in
the dried washed microcapsules was determined bythermogravimetric analyzer (TGA 4000, PerkinElmer, USA) at a heating rate of 5 °C/min. The
latent heats (∆Hm and ∆Hc) (J/g-capsule) and themelting (Tm) and crystallization (Tc) temperatures ofthe encapsulated octadecane were measured with adifferential scanning calorimeter (DSC 4000,
Perkin-Elmer, USA) under a N2 flow in a scanning

2.2 Microcapsule preparationThe
preparationofpolymethyl
methacrylate/octadecane
microcapsulesbymicrosuspension iodine transfer polymerization
using chitosan as the stabilizer was carried out asfollows. Firstly, 2.50 g of methyl methacrylate (ormethylmethacrylate/divinyl
benzene)was840

GEOMATE - Mie, Japan, Nov. 21-24, 2017

thermogravimetric analyzer
The theoretical % loading of OD in the washedmicrocapsules was calculated by equation (2)% Loading (theory) = [Wwax/(Wwax + WP)] x 100…(2)
Where Wwax and WP are weights of octadecane
and polymethyl methacrylate, respectively, in thepolymerization recipes shown in Table 1.

temperature range of -20-40 °C and at aheating/cooling rate of 5 °C/min and shown as
average values of three measurements. The ∆Hm*and ∆Hc* (J/g-OD) were, respectively, obtainedusing the following equation (1) from the ∆Hm and∆Hc and the octadecane content in each washedmicrocapsule (% loading) obtained from thethermogravimetric analyzer, which did not contain
unencapsulated octadecane.
A = [B / C] x 100

Encapsulation efficiency (%) of octadecane wascalculated using the equation (3).
Encapsulation efficiency (%)= [%loading (experiment)/%loading (theory)] x100…(3)
2.4 Antibacterial property
The antibacterial property of the preparedmicrocapsules was tested for Staphylococcus
aureus (S. aureus) and Escherichia coli (E.coli)
using disk-diffusion method at 35C for 24 h.

………………(1)Where
A = ∆Hm* and ∆Hc* of the encapsulated
octadecane in unit of joules per 1 g of encapsulated
octadecane (J/g-OD)
B = ∆Hm and ∆Hc of the encapsulated
octadecane in unit of joules per 1 g of microcapsule(J/g-capsule) measured with differential scanningcalorimeter
C = % loading (experiment) of octadecane in
the washed microcapsules measured with

Fig. 1 Optical micrographs before (a-d) and after (a’-d’) polymerization of polymethyl methacrylate/octadecane(50:50 w/w%) microcapsules prepared by microsuspension iodine transfer polymerization with 1 wt% ofpoly(vinyl alcohol) aqueous solution (a, a’) and various concentrations of chitosan in aqueous solution (wt%):
0.25 (b, b’); 0.50 (c, c’) and 1.0 (d, d’)polymethyl methacrylate/octadecane microcapsules
were unstable and broken in both cases of 0.25
3. RESULTS AND DISCUSSION(Fig. 1b') and 0.50 (c') wt% of chitosan. In addition,
In general, poly(vinyl alcohol) is used as amost of the obtained microcapsules (75% based on
surfactant in microsuspension polymerization. The
monomer/octadecane in the recipe) were coagulated
obtained microparticle/capsules represented highas shown in Fig. 2a and b. After left overnight, a lot
colloidal stability without coalescence. In this work,of unencapsulated octadecane dispersed in the
chitosan was used in place of poly(vinyl alcohol) toaqueous medium (Fig. 2c) whereas octadecane wasincrease antibacterial property where the various
not detected by thermogravimetric analyzer (Fig.
concentrations of chitosan were studied compared2d) in the remained polymer particle precipitated inwith poly(vinyl alcohol) as shown in Fig. 1. It was
the bottom. It may be due to insufficient chitosan
found that at all chitosan concentrations (Fig. 1 bamount to maintain the microcapsule stability.
c), monomer droplets were spherical with
However, such phenomenon was improved by the
micrometer-sized. After polymerization, the841

GEOMATE - Mie, Japan, Nov. 21-24, 2017

increase of chitosan to 1 wt% (Fig. 1d') in which
the obtained polymethyl methacrylate/octadecane
microcapsules shape was similar to those of using
poly(vinyl alcohol) 1 wt% (Fig. 1a'). In addition,
microsuspension iodine transfer polymerization
represented high performance to reduce freepolymethyl methacrylate particles nucleated inaqueous medium. The aqueous medium of theobtainedpolymethyl
methacrylate/octadecane
microcapsule using 1 wt% of chitosan was changed
from milky (Fig. 3a) to transparent (Fig. 3b) after
centrifugation at about 3,000 rpm. It accorded withthe previous articles [11, 14] where most of theobtainedpolymethyl
methacrylate/octadecane
microcapsule having total density lower than that of
the water floated on the top of the suspension.

However, after washing polymethyl methacrylate/
octadecane microcapsules with 2-propanol (Fig.
3c), some microcapsules were broken and having ahole on their surface in which reduced theencapsulation efficiency (80%) of octadecane.
This finding may due to some of chitosan having
high molecular weight absorbed on somemicrocapsule surfaces as chitosan-riched surface
obstructed the polymethyl methacrylate chains toadsorb at the interface. The shell strength thendecreased giving a hole after washing. Therefore, toimprove the polymer shell strength, polymethyl
methacrylate was then copolymerized with 10 wt%
related to monomer of crosslinking monomer as
divinyl benzene.

Fig. 2 Suspension photos (a and b), optical micrograph (c) andthermogravimetric thermogram (d) of polymethyl methacrylate/octadecane
microcapsules prepared by microsuspension iodine transfer polymerization using various concentrations ofchitosan in aqueous medium (wt%): 0.25 (a) and 0.50 (b)from 90 C (polymerization temperature) to room
temperature. The polymer shell with complete
enveloping octadecane core would not withstand theexternal pressure leading to the formation of dent
on their surfaces. In contrast, polymethyl
methacrylate/octadecane microcapsules can reduce
the external pressure via a hole where they canmaintain their shapes without any dents. Therefore,
the encapsulation efficiency (100%) was improvedby copolymer shell where the exited octadecane
floated on the top of the suspension after
polymerization was not observed.

Fig. 3 Suspension photos before (a) and after (b)centrifugation at 3,000 rpm for 15 minutes ofpolymethyl methacrylate/octadecane microcapsulesand scanning electron micrograph (c) polymethyl
methacrylate/octadecane microcapsules washedwith 2-propanolThemonomer
dropletsofmethylmethacrylate/divinyl benzene/octadecane were
spherical (Fig. 4a) similar with methacrylate/
octadecanemonomer
droplets.
Afterpolymerization,
theobtainedpoly(methyl
methacrylate-divinyl
benzene)/octadecane
microcapsules represented nonspherical shape witha big dent (Fig. 4b and c). The dent formation isdue to the encapsulated octadecane volume
shrinkage based on the decreasing of temperature

Fig. 4 Optical micrographs of (a) monomer dropletsand(b)poly(methyl
methacrylate-divinyl
benzene)/octadecane microcapsules and scanningelectron micrograph of poly(methyl methacrylatedivinyl benzene)/octadecane after washing with 2propanol842

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The degradation temperatures of bulk
octadecane,poly(methyl
methacrylate-divinyl
benzene) and the encapsulated octadecane in thepoly(methyl
methacrylate-divinyl
benzene)microcapsules were observed by thermogravimetricanalyzer as shown in Fig. 5. The decomposition
temperatures of poly(methyl methacrylate-divinyl
benzene)/octadecane microcapsule (Fig. 5b) wereshown in two respective steps which were
octadecane core (130-260°C) and poly(methyl
methacrylate-divinyl benzene) shell (220-430C),
respectively. The degradation of bulk octadecane(Fig. 5a) at 140-250°C was closed to that of theencapsulated octadecane. The thermogravimetric
thermograms confirmed that octadecane existed in
the prepared microcapsules in which about 50%
loading of octadecane in poly(methyl methacrylatedivinyl benzene)/octadecane was obtained. In
addition, it was close to the theoretical value (50%for 50:50 of monomer:octadecane ratio). This
indicates that high encapsulation efficiency (ca.
100%) was obtained.

benzene)/octadecane microcapsules using methyl
methacrylate:divinyl benzene ratio of 90:10(w/w%) prepared by microsuspension iodinetransfer polymerization (b)The latent heats of bulk octadecane (J/g) (Fig.
6a) and the encapsulated octadecane (J/g-sample)(Fig. 6b) were obtained from the heating/coolingpeak areas of differential scanning calorimeter
thermograms at Tm and Tc, respectively. The latentheats (Hm* = 234 J/g-OD and Hc* = 236 J/g-OD)
of the encapsulated octadecane calculated fromequation 1 were quite closed to those of bulk
octadecane (Hm* = 233 J/g-OD and Hc* = 234
J/g-OD). Because main polymer shell is ahydrophilic polymer as polymethyl methacrylatecontaining only 10 wt% of hydrophobic polymer as
divinyl benzene, it would increase the phaseseparation between polymer shell and octadecanecore where the encapsulated octadecane behaved
similar to bulk octadecane.
Antibacterial property of the obtainedpoly(methyl
methacrylate-divinyl
benzene)/octadecane microcapsules using chitosan as thestabilizer was performed on a bacterial culture of S.
aureus and E. coli by measuring the size of theinhibition zones. It was found that a few
antimicrobial activity of poly(methyl methacrylatedivinyl benzene)/octadecane microcapsule wasobserved based on the small size (2 millimeters) of
the resulting inhibition zones of both bacteria. This
indicates that amino groups in chitosan chainsrepresented low performance of antibacterial
property. Therefore, in the future work, aminogroups in chitosan chains will be functionalized tobe ammonium salt having high performance
antibacterial activity and used as the surfactant inmicrosuspension iodine transfer polymerization.

Fig. 5 Thermogravimetric thermograms of bulk
octadecane (a), poly(methyl methacrylate-divinyl
benzene)/octadecane microcapsules using methyl
methacrylate:divinyl benzene ratio of 90:10(w/w%) (b) and poly(methyl methacrylate-divinyl
benzene) particles (c) prepared by microsuspension
iodine transfer polymerization

Fig.
6
Differential
thermograms of bulkpoly(methyl

4. CONCLUSION
The nonspherical shape with a dentpoly(methyl
methacrylate-divinyl
benzene)microcapsules containing octadecane was preparedby microsuspension iodine transfer polymerization
using chitosan as a stabilizer without any
coagulation. Using polymethyl methacrylate as apolymer shell, microcapsules with a hole wereobtained resulting in about 80% encapsulation
efficiency. The encapsulation efficiency (100%)
was improved by poly(methyl methacrylate-divinyl
benzene) copolymer shell. The latent heats of theencapsulated OD were close to those of bulk
octadecane. The antibacterial activity of chitosan
absorbed on the microcapsule surface was still low(2 millimeters inhibition zone) which needed to be
improved in the future work.

scanning
calorimeteroctadecane (a) andmethacrylate-divinyl

ACKNOWLEDGEMENTS
This study was supported by the RMUTT843

GEOMATE - Mie, Japan, Nov. 21-24, 2017

annual government statement of expenditure in2016 (NRMS No. 2560A16502037 given to P.C.,
A.C. and W.S.)[9]

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

KONDO THEORY FOR SPHERICAL SHELL TECTONICS
Kazuhei Kikuchi1, 2* and Hiroyuki Nagahama2
Research Center for Earthquake Prediction, Disaster Prevention Research Institute, Kyoto University, Japan;
2
Department of Earth Science, Graduate School of Science, Tohoku University, Japan;*K. Kikuchi’s present affiliation is Kyoto University.

1

ABSTRACTThe buckling phenomenon of a flat or spherical shell lithosphere (tectonic plate) has been investigated inprevious research. However, previous research cannot give us a curvature effect in the buckling phenomenon.
Kondo applied Riemannian geometry to the yielding or buckling of curved materials. When the Riemannian
manifold ( dimensional manifold) with a nonzero Euler-Schouten curvature tensor is manifested in theenveloping manifold (Euclid space:dimensional manifold), the included Riemannian manifold (dimension) protrudes into the enveloping manifold (dimension ). The curvature effect for the buckling phenomenon ofmaterials can be formulated by a force-balance equation from mechanics and the Euler-Schouten curvaturetensor from differential geometry. In this paper, using the Euler-Schouten curvature tensor from differential
geometry, the authors derive a formulation for the buckling phenomenon with the curvature effect for a sphericalshell lithosphere as a buckling equation with high-order strain for lithosphere deformation.
Keywords: Buckling phenomenon; Spherical shell lithosphere; Riemannian geometry; Euler-Schouten curvaturetensorINTRODUCTION

the enveloping manifold (Euclid space) of, the included Riemannian manifold ofdimension
protrudes into the enveloping manifold ofdimension. From the Euler-Schouten curvaturetensor and the force-balance equation, materialscience is exhibited by the use of the curvature effectfor the buckling phenomenon in differential
geometry. In this paper, the authors derive thebuckling phenomenon with the curvature effect for aspherical shell lithosphere. The authors can apply
the Euler-Schouten tensor to the buckling equation
with high-order strain for lithosphere deformation.
Using deformation theory based on Riemannian
space for the buckling system of the flat plate andspherical shell, the equation for the lithosphere
deformation and buckling can be derived from theEuler-Schouten curvature tensor. Therefore, thiscurvature tensor is an important tensor for
lithosphere deformation.

The mechanism of flat or spherical shelllithosphere deformation is presented by using
buckling theory [e.g., 1–4]. Yamaoka et al. [5]pointed out the buckling phenomena of the
subducting lithosphere due to the sphericity of theearth. Moreover, Fukao et al. [6] and Yamaoka [7]denoted the similarity of lithosphere buckling withcylindrical buckling of spherical shells throughexperiments and numerical simulations based on the
nonlinear finite element method. Kikuchi andNagahama [8] found a new linear relationshipbetween the Batdorf parameter and normalizedhydrostaticpressurealong
thebottomcircumferential edge of a hemisphere in sphericalshell tectonics. The Batdorf parameter for a
subducting lithosphere is equivalent to the length of
the slab and is also related to the wavelength (lengthof the island arc) of buckling. However, previous
research has not revealed the buckling equation withhigh-order strain for the curvature of the lithosphere.
The buckling equation with the high-orderstrain effect has been addressed in the field ofengineering science [9], in which Riemannian
geometry has been applied to the yielding andbuckling of curved material. Kondo used the conceptof dimension protrusion, in which buckling in thetwo dimensions of a flat plate can occur in threedimensional space (Fig. 1). In general, when the
Riemannian manifold of dimension
with anonzero Euler-Schouten curvature tensor exists in

Fig. 1 Two-dimensional pre- and post-buckling of
the flat plate. (a) Pre-buckling of material is in
two dimensions. (b) Post-buckling of material isin three dimensions.
845

GEOMATE -Mie, Japan, Nov. 21-24, 2017PREVIOUS BUCKLING THEORY,

The authors briefly introduce the previous
buckling theory used in earth science. The
mechanism of geological folding (flat crust
buckling) was described by use of buckling theory[1]. First, the authors introduce the balance equationof the flat crust as follows (Fig 2):,

10where is the shear modulus,
is crust density,
is mantle density, is gravity, and is height(Fig. 3). However, previous studies have notdemonstrated a high-order curvature effect in thebuckling phenomenon.

1

,

2

where is the shearing force, is the coordinate of
the system,
is the load, and is the moment.
Moreover, the authors can derive a relationshipbetween the load and moment using Eq.(1) andEq.(2),.

Fig. 2 Buckling of flat crust deformation, where isthe coordinate of the system,
is the load,
is deflection,is moment,
is axial
compressive force, and is shearing force.

3

Then, the authors can use the proportion of curvature
to describe the flexure moment and curvatureequations,,4,Fig. 3 Buckling of lithosphere deformation, whereis the crust density,
is mantle density, isdeflection, andis the applied load
[modified from 4].

5

where
is Young's modulus,
is the second
moment, is curvature, and is deflection. Next,
from Eqs. (1)–(5),,KONDO THEOREM
In a previous paper [9], Kondo provided some
important information regarding materials science.
By using differential geometry in the study of thebuckling of plate and shell, Kondo [9] proceeded asfollows: The object was placed in Cartesian
coordinates and -dimensional Riemannian space; , are frames of reference in(envelope space
Fig. 4).

6

,

7
.

8

Eq. (8) is the crust buckling equation. If the crustundergoes axial compressive force, the authors canwrite the equation as follows:,

9

where is the axial compressive force.
The mechanism of spherical shell lithosphere
deformation is presented, assuming buckling theory[e.g., 2–4]. Turcotte and Schubert [4] showed thatlithosphere deformation is given by:

Fig. 4 Riemannian manifold of dimension with anonzero Euler-Schouten curvature tensor in theenveloping manifold (Euclid space) of , with
, ,⋯,coordinates, and frames of reference, . is the normal vector of .
846

GEOMATE -Mie, Japan, Nov. 21-24, 2017

Moreover, the deformation of the normal directionof the object can be expressed using strain andChristoffel symbols

⋅
⋅

,

;;

⋅⋅

⋅

⋅

⋅⋅

⋅

,

,

⋅

.

;

.

Then, the subspace of the enveloping protrusion (space protrusion) is defined by the Eulerto
Schouten curvature tensor . [10]:≡,where is the contravariant tensor in -space andand are indices. From Eq. (15), the balance
equations (Eqs. 17–18) and the coordinatetransformation (Eqs. 19–21), the authors can write:

space, andiswhere is the deflection inorder of the Landau symbol. In this case, theobject deformation is expressed by normal direction
( ):

.

,

;;

Moreover, when the material is isotropic, thetensor can be expressed with the constant ,.

;.
DISCUSSION

The second term of the components of the curvatureorder. Hence, the authors omitted thetensor issecond term in the small deformation theory:

The authors consider the relationship between
previous research and Kondo theory. DiDonna [11]presented the buckling equation for an elastic sheet,.

.

The approximate expression is compared toexpression (11). It is configured by omitting a verysmall amount. Metrics are defined by the following:where h is thickness, is Poisson’s ratio,is theis an external pressure field. The
stress, andcurvature tensor can be written as the derivative of acontinuous curvature potential [11]

,
where
and
are matrix elements. The authors
use the equation of equilibrium of forces andequations of equilibrium with a small strain,,

25

is the curvature tensor. Here the potential
where
is not identical to the local function used above,
but is approximately equal tofor nearly flat
surfaces [11]. The parameteris the EulerSchouten curvature tensor. Hence, this buckling
equation for an elastic sheet is a low-order strain
equation. Furthermore, the authors writein termsof the stress potential

,

.

, 24

12 1

,

where is the tangential force per unit volume,is the difference in the tangential frictions at theis the stress
upper and lower boundaries,
components in the shell space, is the normal force
per unit
volume,is the difference in thetangential frictions at the upper and lower
boundaries, andis the Euler-Schouten curvature
contravariant tensor.
The coordinate transformation law is expressed
by:

,

26

where
and
are antisymmetric tensors. In termsof the potentials and , the von Karman equations[12] can be expressed by
,
847

,

27

GEOMATE -Mie, Japan, Nov. 21-24, 20171
2

for the shell, the authors derived a unified theory forbuckling of flat plates or spherical shells in Eq. (23).
,

.

28

ACKNOWLEDGEMENTS

This von Karman equation is a generalized
buckling equation (23) for low-order strains.
Moreover, the buckling can be described by asimplification of Eq. (9). It is apparent that Eq. (23)is the extended two-dimensional version equation of
Eq. (9) with constant vertical forces (i.e., = const.)
and without body forces. It is also apparent that a
two-dimensional version equation (e.g. [4]) is
included in the kind of equations reduced from Eq.
(23). Thus, various kinds of geological deformations
can be described by the simplification of thegeneralized buckling equation. For example, themechanism of geological folding occurs by platemotion. In this case, three-dimensional flat plate
buckling (geological folding) can be described by
Eq. (23), the buckling equation of the flat plate.
The buckling phenomena of the subducting
lithosphere due to the sphericity of the earth havebeen studied in the context of spherical shell
tectonics [5–7]. The slab length is approximately
proportional to the arc length, and the lithosphere
thickness is related to the lithosphere age. Moreover,the length of the deformable portion of the shellcorresponds to the length of the subducting slab. The
lithospheres defined by the length of the WadatiBenioff zone and the thickness of the shell whichcorresponds to the effective elastic thickness of thelithosphere. From the dataset of geometricalparameters for subducting lithosphere, Kikuchi andNagahama [8] presented a new linear relationshipbetween the normalized hydrostatic pressure and the
Batdorf parameter as the dimension of the shell (i.e.,
the flatness). Therefore, in this case, Eq. (23)becomes the buckling equation of the spherical shelllithosphere as a three-dimensional Riemannian
manifold ( ).

One of the authors (K.K.) is supported by theInstitute for International Advanced Research and
Education, Tohoku University and the Disaster
Prevention Research Institute, Kyoto University.
This work was supported by JSPS KAKENHI(15J00934). The authors would like to thank Editagefor English language editing.
REFERENCES[1] Biot MA, Ode H, and Roever W, “Theory offolding of stratified viscoelastic media and its
implications in tectonics and orogenesis”, Bull.
Geol. Soc. Am, Vol. 72, November 1961, pp.
1595–1620.
[2] Tanimoto T, “Bending of spherical lithosphereaxisymmetric case”, Geophys. J. Int., Vol. 129,
May 1997, pp. 305–310.
[3] Tanimoto T, “State of stress within a bending
spherical shell and its implications for
subducting lithosphere”, Geophys. J. Int., Vol.
134, July 1998, pp.199–206.
[4] Turcotte DL, and Schubert G, “Geodynamics
3rd ed.”, Cambridge: Cambridge University
Press, 2014.
[5] Yamaoka K, Fukao Y, and Kumazawa M,“Spherical shell tectonics: Effects of sphericity
and inextensibility on the geometry of thedescending lithosphere”, Rev. Geophys.,Vol. 24,
February 1986, pp. 27–53.
[6] Fukao Y, Yamaoka K, and Sakurai T,“Spherical shell tectonics: buckling of
subducting lithosphere”, Phys. Earth Planet.
Inter., Vol. 45, January 1987, pp. 59–67.
[7] Yamaoka K, “Spherical shell tectonics: On thebuckling of the lithosphere at subduction zones”,
Tectonophysics, Vol. 147, April 1988. pp. 179–
191.
[8] Kikuchi K, and Nagahama H, “Spherical shell
tectonics: Batdorf parameter of subducting
lithosphere”, Asia Oceania Geosciences Society
2016 Abstract, AOGS 13th Annual meeting,
SE18-D4-PM2-P-022.
[9] Kondo K, “Theory of metaphorical plates andshells”, RAAG memoirs Vol. I, Kondo Ed.
Gakujutsu Bunken Fukyu-kai, 1955, pp. 47–60.
[10] Schouten JA, Ricci-calculus. Berlin: SpringerVerlag, 1954.
[11] DiDonna BA, “Scaling of the bucklingtransition of ridges in thin sheets”, Phys. Rev. E,
Vol. 66, July 2002, 016601.
[12] von Karman T, “Collected Works of Theodore
von Karman”, London: Butterworths Scientific
Publications, 1956.

CONCLUSIONS
Buckling of the plate and shell in the field ofmaterials science is considered, using differential
geometry [9]. From the Euler-Schouten curvaturetensor of the shell as a Riemannian manifold and theforce-balance equation for the shell, the authors
derived a unified theory for buckling of sphericalshells. When the Riemannian manifold ofdimension
with a nonzero Euler-Schouten
curvature tensor exists in an enveloping manifold(Euclid space) of dimension, the including
protrudes into the
Riemannian manifold ofenveloping manifold of dimension. From theEuler-Schouten curvature tensor on the shell as a
Riemannian manifold and the force-balance equation

848

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PHOTOELECTROCATALYTIC CONVERSION OF CO2 INTO
VALUE-ADDED ORGANIC COMPOUNDSUSING Cu2O PHOTOCATHODE
Pattranit Thongthep1, Chatchai Ponchio1,2*
1Department of Chemistry, Faculty of Science and Technology, Rajamangala University of Technology
Thanyaburi, Pathumtani 12110, Thailand
2
Advance Materials Design and Development (AMDD) Research Unit, Institute of Research andDevelopment, Rajamangala University of Technology Thanyaburi, Pathumtani 12110, Thailand*Corresponding Author; E-mail address: chatchai@rmutt.ac.th
ABSTRACTThe global warming from CO2 emission effect and finding renewable energy are two major issues in today’senvironmental and energy problems. The conversion of CO2 into value-added chemicals to achieve an energysaving and low-carbon economy is needed to be developed. Photoelectrocatalytic technology is one of the mostalternative ways to reduce CO2 under the advantage of high efficiency and inexpensive resembles of the artificial
photosynthesis process. This research focuses on photoeletrocatalytic reducing CO2 solution into organic
compounds at a Cu2O photocathode. The Cu2O electrode fabrication was developed by electrochemical deposition
method to enhance the reduction catalytic activity under visible light irradiation. The effects of light intensity,
applies potential, pH and catalytic mechanism parameters were studied in order to enhance the CO2 conversion toorganic compounds efficiency. Carbonyl and methanol compounds were produced at the applied potential of
0.2 V and -0.4 V (vs. Ag/AgCl), respectively with the suitable pH in a solution of carbonate under visible lightirradiation. This results illustrate that an applying potential and pH adjustment are the key factors of organic
compounds production. This developed photoelectrocatalytic cell shows that the interesting method for reducing
CO2 from air pollutant and also producing value-added chemicals for alternative energy supplying.
Keywords: Photoelectrocatalytic cell, CO2 reduction, Organic compounds, Cu2O, Electrodeposition
photoelectrocatalytic CO2 reduction with good
properties for hydrocarbon formation [4]. The
photocatalytic activity of Cu2O photoelectrode is also
related to the efficiency of semiconductor depositionon the substrate. The electrodeposition is one of themost attractive methods to deposit Cu2O on thesubstrate which the advantage of simple, rapid
methods, and suitable to scaling up for the large scale
applications. This research is developed theelectrodeposition method of the Cu2O semiconductor
on fluorine-doped tin oxide (FTO) conductive glass
by using cyclic voltammetry deposition method(CVD). The developed FTO/Cu2O photoelectrodewas used to reduce CO2 solution into organiccarbonyl and methanol compounds.

1. INTRODUCTION
The global warming is main problems of theworld by the effect of CO2 emission to an
environment from the combustion of industrial plants
or fossil fuel [1]. The methods to convert CO2 intovalue added production has attractive been developed
to solve the air pollutant and value creation of waste.
There are many methods to convert a CO2 compound
into a fuel or a valuable chemical especiallyphotocatalytic,
electrocatalyticandphotoelectrocatalytic methods[2-4]. The
photoelectrocatalytic method has been attracted withmany advantages of reducing the recombination
effect of the photocatalyst and using low bias
potential than the electrocatalytic method [5]. The
performance of the photoelectrocatalytic method isdepended on the semiconductor selection and theefficiency of semiconductor deposition on thesubstrate. Cu2O has been selected to develop forseveral reduction reaction applications with thenarrow band gap energy and high negative potentialof conduction band [6]. Recently Cu2O
photocathodes
were
also
appliedin

2. EXPERIMENTAL
2.1 Preparation of FTO/Cu2O electrode
FTO/Cu2O electrode fabrication was developedby cyclic voltammetry deposition method(FTO/Cu2O (CVD)) which is a new method for Cu2O
deposited on FTO substrate. The electrochemical cell849

GEOMATE - Mie, Japan, Nov. 21-24, 2017containing three electrodes system consist of FTO
substrate as a working electrode, Ag/AgCl as areference electrode and Pt as a counter electrode thatimmersed in the electrolyte solution of 0.01 M
Cu(NO3)2 and 0.1 M KNO3. The potential range incyclic voltammetry mode at -0.5 V to 0.5 V for 20
cycles, scanning rate 50 mV/s and keep thetemperature of an electrolyte at 55 oC were performed
with the optimum condition for FTO/Cu2O
preparation. The FTO/Cu2O (CVD) was comparedwith the previous research of fix potential deposition
method (FTO/Cu2O (FPD)) by considering thephotoelectrocatalytic reduction properties [6].

which used to study the CO2 conversion to methanolcompound. The cyclic voltammetry technique wasused to determine the methanol production at thepotential range of -0.5 V to 0.5 V (vs Ag/AgCl) using
Pt wires as working and counter electrode [8].
3. RESULTS AND DISCUSSION
3.1 Characterization and photoelectrocatalytic
properties of the fabricated FTO/Cu2O electrodes
3.1.1 Absorption properties

2.2 Characterization and photoelectrocatalytic
properties of FTO/Cu2O electrodes study
An optical absorption of the FTO/Cu2O electrodes
were studied by UV-Vis spectrophotometer(Shimadzu, UV-1601) in the wavelength range of 200– 1,000 nm. The photoelectrocatalytic performance of
FTO/Cu2O photocathodes were performed bymeasure the photocurrent response from water
reduction at the applied potential of -0.2 V (vs.
Ag/AgCl) in 0.1 M Na2SO4 solution under visible
light irradiation. Electrochemical impedance
spectroscopy (EIS) with VersaSTAT3 (Princeton
Applied Research, Inc.) was introduced to study the
charge transfer resistant of electrode surface which
carried out under the frequency range from 100 kHz
to 0.1 Hz with -0.2 V.

Fig. 1. UV-Vis spectra of (a) FTO and the
FTO/Cu2O films prepared by different method of(b) FPD (c) CVD.
Fig. 1 shows that the UV-Vis spectra comparisonof FTO/Cu2O prepared by CVD and FPD method.
The absorption edge of FTO/Cu2O (FPD) electrodewas set at 650 nm corresponding to the band gap of
2.2 eV. While the absorption of FTO/Cu2O (CVD)electrode was red shifted to 700 nm indicates that thenarrower band gap corresponding to the higher visible
light absorption properties.

2.3 Photoelectrocatalytic conversion of CO2 tocarbonyl compound study
The photoelectrocatalytic cell for CO2 compoundconversion to carbonyl compound study was
performed by using the FTO/Cu2O electrode asworking electrode, Ag/AgCl as a reference electrodeand Pt wire as a counter by using an amperometrymode with VersaSTAT3 (Princeton Applied
Research, Inc.). The effect of bias potential, pH ofelectrolyte and the intensity of light were studied withthe optimum condition for highest photoreduction
current of the fabricated FTO/Cu2O electrode. The
three electrodes were immersed in the
Na2CO3/NaHCO3 buffer solution which used as theCO2 saturated solution to study the CO2 conversion tocarbonyl compounds. UV-Vis spectrophotometer
was used to confirm carbonyl compound production
at the wavelength (λ) of 280 nm [4, 7].

3.1.2 Photoelectrocatalytic activity

Fig. 2. Photocurrent responses of FTO/Cu2O
electrodes under the chopped visible lightillumination.

2.4 Photoelectrocatalytic conversion of CO2 tomethanol (MeOH) compound study
The experimental was set up similar to thecarbonyl compound production process except for thebias potential and electrolyte solution. 0.1 M Na2CO3
solution was performed as the saturated CO2 solution

The photocurrent response of FTO/Cu2O
electrodes from water reduction at the applied
potential of -0.2V vs Ag/AgCl and under the chopped
850

GEOMATE - Mie, Japan, Nov. 21-24, 2017visible light illumination were operated to study thephotoelectrocatalytic activity of photoelectrode. Fig.
2 shows that the photocurrent of the FTO/Cu2O
electrode prepared by CVD method higher than that
the FPD method about 2 times. The enhancing
photocatalytic activity of FTO/Cu2O (CVD) is related
to a narrower band gap energy properties caused tothe increasing of the photoelectron generated
efficiently to enhance water reduction efficiency.

conversion to carbonyl compound by using
photoelectrocatalytic
process.
The
photoelectrocatalytic cell was contained with
FTO/Cu2O as a working electrode, Ag/AgCl as areference electrode and Pt wire as a counter electrodein the Na2CO3/NaHCO3 buffer solution. The effectsof bias potential, pH of electrolyte, the power of lightintensity were studied for the optimum condition ofcarbonyl compound production. The absorbance bandat 280 nm which related with the formation ofcarbonyl compounds [4] was monitored forconsidering the optimum condition (Fig.4).

3.1.3 Charge transfer resistant properties
The electrochemical impedance spectroscopy(EIS) was carried to verify the FTO/Cu2O electrodes
performance of interfacial charge transfer properties
at the bias potential of -0.2 V vs Ag/AgCl undervisible light illumination. Fig. 3 shows the Nyquist
plots of FTO/Cu2O (CVD) electrode has a smaller
semicircle than that of FTO/Cu2O (FPD) electroderelated with charge transfer resistant (Rct) values of
FTO/Cu2O electrodes prepared by CVD and FPD
methods were 364.8 and 1,754 ohm, respectively. It
could indicate that the FTO/Cu2O electrode preparedby CVD method obtained the high efficiency forcharge separation at the interfacial electrodeelectrolyte
causedtoimprovethephotoelectrocatalytic activities for water reduction.

Fig. 4. UV spectra of carbonyl compound
functional with the time of photoelectrocatlytic CO2
reduction process.
The effect of applied potential is studied at -0.1,
0.0, 0.1, 0.2 and 0.3 V vs Ag/AgCl and observed theabsorbance value at the λ of 280 nm. Fig. 5 shows thatthe applied potential significantly affects with theCO2 conversion to a carbonyl compound. The
specific bias potential of 0.2 V presented the highest
performance for carbonyl compound production andwas selected for next study.

Fig. 3. Nyquist plots of FTO/Cu2O electrodes
prepared by different methods of CVD and FPD in
0.1 M Na2SO4 under bias potential of -0.2 V vs
Ag/AgCl and visible light illumination condition.
The results show that the FTO/Cu2O electrodefabricated by CVD method have many goodcharacteristics and photoelectrocataytic activities forwater reduction suitable to further apply to the CO2
reduction to carbonyl and methanol compounds.

Fig. 5. Absorbance value of carbonyl compound
production (λ=280nm) with the different bias
potential in range of -0.1 to 0.3 V vs Ag/AgCl.

3.2 The CO2 conversion to carbonyl compound
performance using the developed FTO/Cu2O
photocathodeThe pH of the electrolyte was varied from 9 to 11
at an applied potential of +0.2 V under visible lightirradiation. Fig. 6 shows the proper pH value of 9 forCO2 compound conversion to the carbonylcompound. The power of light intensity was directly

Based on the comparison of the electrodes
properties, FTO/Cu2O (CVD) electrode was selected
to study the optimum condition for CO2 compound
851

GEOMATE - Mie, Japan, Nov. 21-24, 2017

related to the carbonyl compound production due tothe high power of light intensity irradiate at thephotosemiconductor cause high efficient to generate
photoelectron for reducing CO2 to carbonylcompound as well.

using photoelectrocatalytic process with the working
electrode of FTO/Cu2O. The effects of applied
potential, the power of light intensity and catalytic
mechanism were studied with the optimum condition
for MeOH production. A cyclic voltammetry method
was introduced to analyze the methanol concentrationfrom the process using Pt wire as working and counterelectrode and Ag/AgCl as a reference electrode. The
correlation of methanol oxidation current at 0 V asa function of methanol concentrations range of
0 (blank) - 5,000 ppm (MeOH) were performed to use
as the standard calibration curve (Fig. 8).

Fig. 6. Absorbance value of carbonyl compound
production (λ=280nm) with the different pH value of9, 10 and 11.
Moreover, the catalytic mechanisms to induce
FTO/Cu2O photoelectrode for carbon dioxide
conversion to carbonyl compounds were studied
under photoelectrocatalysis (PEC), photocatalysis(PC) and electrocatalysis (EC) process. The resultshows that the photoelectrocatalytic process (PEC)
presented the highest efficiency for the CO2compound conversion to carbonyl compound (Fig. 7).
This result confirms that the highest efficiency of
PEC process due to the catalytic action applied
potential and light irradiation at photoelectrode cause
decreased the recombination effect of the electronhole pair at the Cu2O semiconductor efficiently
induce photoelectron to reduce CO2 to carbonyl as
well.

Fig. 8. Cyclic voltammograms of methanoloxidation reaction at Pt wire electrode in 0.1 M
Na2CO3 and the inset shows the standard calibration
curve as a relation of oxidation current versus
methanol concentrations.
The effects of applied potential at -0.3, -0.4 and-0.5 V vs Ag/AgCl in 0.1 M Na2CO3 (CO2 saturated)
under PEC process with 20 W tungsten lamp for 60
minutes were studied. Fig.9 shows that the applied
potential of -0.4 V presented the highest methanol
generation to 575 ppm for 1h.

Fig. 7. Absorbance value of carbonyl compound
production (λ=280nm) with the different catalytic
mechanismofphotoelectrocatalysis(PEC),
photocatalysis (PC) and electrocatalysis (EC)process.

Fig. 9. Methanol production by PEC process withthe different of applied potentials for 1 h.

3.3 The CO2 conversion to MeOH compound
performance using the developed FTO/Cu2O
photocathodeThe result indicates that the applied potential isspecific to the kind of product from CO2 reduction
process. The power of light intensity is one of theparameters affected by the CO2 conversion to MeOH.

The CO2 conversion to MeOH was performed by852

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The light intensity is direct related to the MeOH
production efficiency. Therefore, the position andpower of light source to irradiate at thephotoelectrode have to consider the optimum
condition. Furthermore, the catalytic mechanisms of
FTO/Cu2O photoelectrode for CO2 compound
reduced to methanol were studied with the process of
PEC, EC, and PC. The result shows that the PEC
process has the highest efficiency for the reduced CO2
compound to methanol production of 726 ppm for1 h.

developed FTO/Cu2O photoelectrode was performedhigh efficiency to reduce CO2 solution into organiccarbonyl and methanol compounds as well. Thisdeveloped photoelectrocatalytic cell indicates that thepowerful method for reducing CO2 from air pollutant
and also producing value-added chemicals foralternative energy supplies.
5. ACKNOWLEDGEMENTS
This work was supported by the RMUTT annual
government statement of expenditure in 2017 (NRMS
2560A16502099 ; given to C.P)

3.4 Comparison of FTO/Cu2O prepared by CVD
and FPD methods for CO2 compound conversion
to carbonyl and methanol compounds

6. REFERENCES[1] Kiewchaum A, Thepanondh S, Sirithian D,
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The carbonyl and MeOH compound production
efficiency were compared to confirm the CO2
reduction performance of FTO/Cu2O(CVD) andFTO/Cu2O(FPD) photoelectrodes. The results showthat FTO/Cu2O electrode prepared by CVD method
presented the higher performance for converting CO2
compound to both carbonyl (Fig.10a) and methanol(Fig.10b) compounds than that the FPD method.
(a)

(b)

Fig. 10. Comparison the performance of FTO/Cu2O
electrodes prepared by CVD and FPD for CO2
compound conversion to (a) carbonyl and(b) methanol compounds.
4. CONCLUSIONS
The developed cyclic voltammetry deposition
method(CVD)electrodeposition
methodsuccessfully for the Cu2O semiconductor fabricatedon fluorine-doped tin oxide (FTO) and presented thegood characteristic and more photoelectrocatalytic
activities than that the previous research. The

853

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEVELOPMENT AND DESIGN OF PHOTOELECTROCATALYTIC
REACTOR FOR DYE REMOVAL FROM INDUSTRIAL SYSTEMS
Watcharapong Nareejun1, Chatchai Ponchio1,2*
1Department of Chemistry, Faculty of Science and Technology, Rajamangala University of Technology
Thanyaburi, Pathumtani 12110, Thailand
2
Advance Materials Design and Development (AMDD) Research Unit, Institute of Research andDevelopment, Rajamangala University of Technology Thanyaburi, Pathumtani 12110, Thailand*Corresponding Author; E-mail address: chatchai@rmutt.ac.th
ABSTRACT

Organic dye is a toxic and carcinogenic substance, it is extensively used as the colorant in industries.
There is a need to develop the efficient technique to eliminate the dye wastewater and control this environmental
problem. The study is developed and designed the photoelectrocatalytic (PEC) reactor with the high efficiency,
rapidity and simple method to remove dye from the industrial systems. The WO3/BiVO4 electrode was applied as
the photoanode under visible light irradiation. The effects of batch and flow system, electrodes size, electrodeposition, light intensity, applied potential, pH of the solution and mechanism were studied for development anddesign reactor with the highest dye degradation efficiency. The optimum condition could be degraded methyl red
dyes up to 85% for 3 hours. Significantly, this condition also applied to degrade dye wastewater from the industrial
factory up to 93% for 3 hours. It could be reduced the chemical oxygen demand (COD) over 50% confirms highefficiency of PEC reactor with simple and short duration of the operation for dye degradation system. It isappropriate to scale up and apply for remove dye from industrial system.
Keywords: Photoelectrocatalytic reactor, Dye degradation, Visible light irradiation, WO3/BiVO4
1.

2. EXPERIMENTALINTRODUCTION

The textile industry has been released thewastewater containing a variety of organic content,
toxic and carcinogenic compounds to theenvironment. The high-efficiency method to remove
this dye wastewater has been expected consideringwith a simple and low-cost process [1].
Photoelectrocatalytic (PEC) method is one of themost interesting choices to overcome this advantage
requirement. The key factors to improve theefficiency of PEC method are electrode development
and PEC reactor designation. The previous work, a
WO3/BiVO4 electrode was developed to enhance thephotoelectrocatalytic activities of water oxidation [2]and dye degradation [3] under visible lightirradiation. However, the previous work just studied
only laboratory level. The development of the
prototype of PEC reactor was expected to study forthe scaling up with industrial application. Therefore,
the PEC reactor designing is required to improve theefficiency of the PEC cell [4, 5]. This research
focuses on the development of visible light PEC
reactor for dye degradation with the high efficiency,
simple and short time operation method.

2.1 WO3/BiVO4 electrode preparation
The WO3/BiVO4 electrode fabrication was
described in our previous work [2]. A precursor of 0.1
M BiVO4 solution was prepared by the mixing
solution of 0.2 M Vanadium (IV) oxide
acetylacetonate in acetyl acetone solution and 0.2 M
bismuth (III) nitrate penta hydrate in acetic acidsolution. A 0.1 M WO3 solution was prepared by themixing solution of 0.1 M tungstic acid in 30%
NH4OH solution and then refluxing at 60°C for 1
hour. The WO3/BiVO4 thin films were deposited on
fluorine doped tin oxide (FTO) substrate by spin
coating technique. The WO3 solution was deposited
at first layer by spin coating method and covered with
5 layers of BiVO4. Each layer deposition was dried at
150°C for 5 minutes. The FTO/WO3/BiVO4 film
electrode was calcinated at 550°C for 1 hour.
2.2 PEC reactor set up for dye degradation study
Figure 1 shows that the PEC reactor set up for dye
degradation. The PEC reactor consisted of a beaker
250 mL using the FTO/WO3/BiVO4 (35x40 mm) as
an anode and Cu sheet ( 40 x 40 mm) as a cathode854

GEOMATE - Mie, Japan, Nov. 21-24, 2017

and the electrodes were connected to a DC power
supply. An 11W tungsten lamp was placed parallel to
the FTO/WO3/BiVO4 anode. The synthetic methyl
red dyes in 0.05 M NaCl and real dye without
adjusting condition from paint industry wereintroduced to study the efficiency of dye waste water
degradation. The wastewater in a container wascirculated by a pump to study the effect of flow andbatch system. The electrodes size, the angle ofelectrode position, light intensity, applying potential,
pH of the solution and catalytic mechanism process
were studied. The dye degradation efficiency wasmonitored by sampling the treated solution from PEC
reactor every 10 minutes and measured an absorbanceby UV-Vis spectrophotometer (UV-1601, Shimadzu
Co., Ltd, Japan) at 420 nm for methyl red and 660 nm
for real dye samples. The percentage of dye
degradation was calculated by using:

improves the high oxidizing frequency of organic dyeat the electrode surface. The larger electrode size of
35×40 mm shows significant higher%
degradation for 9 times than the smaller electrode sizeof 2×2 cm which demonstrated that the active surface
area is the key factor to enhance the dye oxidation
efficiency proposes considering for further scalingup.

%

Fig. 2. Comparison % dye degradation between Batch
and Flow system. Using FTO/WO3/BiVO4photoanode electrode at 1.0V under 25W tungsten
lamp in solution of 5 mg/L Methyl Red and 0.05M
NaCl

where, A0= absorbance at t = 0 min, At = absorbanceat t minutes after the treatment process [3]. In
addition, chemical oxygen demand (COD) was
determined to confirm the mineralization of dye
degradation efficiency using standard dichromate
method.

Based on the effect of the electrode position for dye
removal, the degree of electrode placement 30, 45,
and 90 degrees were studied. The experiments showthat the electrode angle of 45 degrees has the highest
removal potential due to at 45 degrees the dyesolution flows through contact with thesemiconductor surface better than 30 degrees and 90
degrees. The effect of light intensity was studied at
5W, 11W, 20W and 28W that classified by the powerof tungsten lamp. The intensity of light is direct
depended with the dye removal efficiency due to thefact that high light intensity stimulates semiconductor
electrodes induces high hole (h+) generated at valenceband, resulting in increasing the efficiency of dye
oxidation process. However, at high light intensity
irradiation may effect with electrode lifetime.
Therefore, the suitable condition for highphotocatalytic activity, long electrode lifetime andlow energy consumption are considered. The lightintensity of 11 W was selected with the optimum
condition for next step. The effect of applied potential
was studied in range of 0.5 to 2.0 V. The % dye
degradation on PEC oxidation was significantly
enhanced with more positive bias potential. This canbe explained by increasing the positive bias potential
induce to enhance the electron flow rate from theanode electrode to the cathode electrode, caused theh+ increasing at the surface of the anode electrode andresulting in the oxidation reaction. However,increasing the voltage too much affects the lifetime ofthe electrode. Therefore, the optimum voltage
condition was selected of 1.5 V. The initial solution
pH is a key factor influencing the dye degradation

Fig. 1. Schematic diagram of PEC reactor for study
dye degradation 1: WO3/BiVO4 anode 2: Cu sheet
cathode 3: Tungsten lamp 4: DC power supply 5:
stirrer 6: flow pump
3. RESULTS AND DISCUSSION
3.1 Evaluation of the optimum condition on dye
degradation
The effects of batch and flow system,
electrodes size, electrode position, light intensity,
applied potential, pH of the solution and mechanism
were studied with the highest dye degradation
efficiency. Figure 2 shows that the flow systempresents higher dye removal than that the batch
system due to the effect of surface refreshing855

GEOMATE - Mie, Japan, Nov. 21-24, 2017

process. Figure 3 shows that the dye removal
significantly increasing in the acidic condition. The
result is related to the researched by Galenda et al.
which pH 3 and 4 obtained highest methyl red
degradation efficiency due to high adsorption abilityof dye at semiconductor surface under lightirradiation [6].

3.3 The performance of PEC reactor for real dye
wastewater treatment

Fig. 5. Decolorization of dye and COD degradationof real dye wastewater effluent treated by
WO3/BiVO4 thin-film PEC reactor as a function of
degradation time (applied potential of 1.5 V, pH = 4
and 11 W of tungsten lamp)

Fig. 3. Effect of pH value in the solution of 5 mg/L
of Methyl red and 0.05 M NaCl for dye degradationby using FTO/WO3/BiVO4 as photoanode, applied
potential of 1.5 V.

Figure 5 shows the color removal and
COD reduction at 180 min intervals during the entire
experiment. The optimum condition of PEC reactor
was applied for removal the real dye waste water fromindustry. The developed PEC reactor presents dye
removal up to 93% for 180 minutes can be achieved
the efficiency for dye decolonization from dark blue
until it becomes a clear solution. Especially, the resultshows that the COD reduction up to 50% able confirm
the mineralization efficiency of this technique. The
results demonstrate that the PEC reactor can degrade
practical dye wastewater efficiently.

The efficiency of synthetic methyl red dye
removal was optimized at pH 4 with 11W and 1.5V.
This optimum condition could be degraded methyl
red dyes up to 85% for 3 hours.
3.2 Catalytic mechanism of FTO/WO3/BiVO4photoelectrode for dye degradation
The dye removed under various catalytic
mechanism at FTO/WO3/BiVO4 photoelectrode were
presented in figure 4 with phtoelectrocatalytic (PEC),
photocatalytic (PC) and electrocatalytic (EC). It can
be clearly observed that the PEC is the most powerfulprocess to degrade the methyl red in aqueous solution.
The highest dye removal (75%) is detected after 60
min in PEC method, while only 49% and 40% of thedye degradation at the same degradation time arefound in the PC and EC process, respectively.

4. CONCLUSIONSThe
developed
PEC
reactorusing
FTO/WO3/BiVO4 photo anode presents highefficiency for 85% synthetic methyl red and 93% realdye degradation under visible light irradiation. This
work demonstrated a high efficiency of PEC reactor
with a simple and rapid method for dye degradation
system suitable to scaling up and apply for dye
removal from the industrial system.
5. ACKNOWLEDGEMENTS
This work was supported by the project ofResearch and Researchers for Industries (RRI),
Thailand Research Fund (TRF) and STP Chem
Solutions Co., Ltd. (MSD59I0017)
6. REFERENCES[1] Akio T, Keiichi K, Takashi N, Ryota S and
Hiromu T. “ Landfill waste water treatment by
application of pulsed high voltage” Int. J. of
GEOMATE, Vol. 9 No. 1 (Sl. No. 17), 2015,
pp. 1375-1379

Fig. 4. Methyl red degradation using difference
process of FTO/WO3/BiVO4 stimulation mechanism(potential 1.5 V, 11 W tungsten lamp, pH 4)856

GEOMATE - Mie, Japan, Nov. 21-24, 2017[2] Ponchio C, Yoshinori M, Shin-ya K, Atsuko Y N,
Yoshio N, “ Efficient photocatalytic activity ofwater oxidation over WO3/BiVO4 composite
under visible light irradiation” , Electrochim.
Acta, Vol. 54, 2009, pp. 1147-1152.
[3]

placed TiO/2Ti anode ”Chem. Eng. J. Vol.150,
2009, pp.302 –307.
[5] Mengb X, Zhanga Z, and Li X, “Synergetic
photoelectrocatalytic reactors for environmental
remediation: A review ”J. Photoch. Photobio. A :Photoch. Reviews, Vol. 24, 2015, pp. 83–101.

Ponchio C, Atsuko Y N, Yoshio N,“
Photoelectrocatalytic
performanceof
WO3/BiVO4 toward the dye degradation” ,Electrochim. Acta, Vol. 94, 2013, pp. 314– 319.

[6] Galenda A, Crociani L, El Habra, Favaro M,
Natile M M, Rossetto G, “Effect of reaction
conditions on methyl red degradation mediatedbyboron and nitrogen doped TiO2” Appl. Surf.
Sci, Vol. 314, 2014, pp. 919–930.

[4] Xua Y, Jia J, Zhongb D, and Y Wanga,“Degradation of dye wastewater in a thin-film
photoelectrocatalytic (PEC) reactor with slant-857

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

IMPROVEMENT THE BIVO4 PHOTOANODE FABRICATED FOR
WATER OXIDATION BY ELECTRODEPOSITION TECHNIQUE
Nuanlaor Kiama1, Chatchai Ponchio1,2*
1Department of Chemistry, Faculty of Science and Technology, Rajamangala University of Technology
Thanyaburi, Pathumtani 12110, Thailand
2
Advance Materials Design and Development (AMDD) Research Unit, Institute of Research andDevelopment, Rajamangala University of Technology Thanyaburi, Pathumtani 12110, Thailand

ABSTRACT
Photoelectrocatalytic (PEC) technique for water oxidation technologies could become important components
in the renewable energy sector. BiVO4 has been receiving attention for applications in PEC cell for O2 evolution
with high photoelectrocatalytic activity and the advantage of visible radiation absorption. The simple and highefficiency BiVO4 thin film fabrication for large scale is very important for scaling up to the industrial
application. This research describes the BiVO4 thin films fabrication on fluorine doped tin oxide (FTO) byelectrodeposition technique as simple, fast and suitable for scaling up of electrode preparation. Cyclic
voltammetry deposition was developed by studied the effect of potential range, scan rate, number of scan,temperature and pH of solution to enhance the photoelectrocatalytic activity of water oxidation under visible
light irradiation. The fabricated FTO/BiVO4 thin films were characterized by scanning electron microscope(SEM), X-ray diffractometer (XRD) and UV-Vis spectrophotometer. The developed FTO/BiVO4 present thephotocatalytic activities for water oxidation improvement more than 10 times when comparing with theprevious spin coating techniques. Therefore, this developing technique show that the high efficiency, fast,
simple and suitable in scaling up able to approach for water oxidation in the industrial application.
Keywords: Photoelectrocatalytic properties, Water oxidation, BiVO4, Electrodeposition
In this work, the FTO/BiVO4 fabricated thinfilms using cyclic voltammetry electrodeposition
method (CVD) was developed by the study of theeffects of apply potential range, scan rate, numberof cycle scan, temperature, and pH of the solution.
The developed BiVO4 prepared by CVD method wascompared with the other electrodeposition techniqueand classical spin coating method.

INTRODUCTION
Photoelectrochemical (PEC) water splitting is
an alternative way to produce hydrogen and oxygen
supporting the hydrogen fuel cell which animportant choice in the renewable energy and green
technology sector [1, 2]. The development ofphotoelectrocatalytic
activity
basedonsemiconductor materials with appropriate narrow
band-gap energy is the key factor to energy
conversion efficiency driven by sunlight. Recently,
many metal oxide semiconductor materials such as
Co3O4, Fe2O3, WO3, and BiVO4 have been
employed as photocatalysts for visible light driven
water splitting [3-6]. Among them, BiVO4 hasrecently been extensively investigated as aphotoanode for the generation of oxygen from water
due to its favorable optical band gap (~2.4 eV), nontoxicity, and stability [7-9]. Especially in the last
few years, the PEC performance of BiVO4photoanode has been significantly improved via thebuilding of nanostructures [10, 11]. One of the mostselected BiVO4 thin film fabrication iselectrodeposition method due to the advantages ofhigh efficient, simple, rapid method and practicableto scaling up.

EXPERIMENTAL
Materials
Fluorine doped tin oxide (FTO, ~7 Ω/sq, SigmaAldrich) was used as a bare electrode substrate. The
chemicals used in this study was Bi(NO3)3·5H2O( 98.0%, Sigma-Aldrich), VOSO4·xH2O (97%,
Sigma-Aldrich), HNO3 (70.0%, Sigma-Aldrich)
CH3COONa ( 99.0%, Sigma-Aldrich), and Na2SO4(Univar)..
Preparation of BiVO4 thin films
The BiVO4 thin films were fabricated on FTO
substratebyelectrodeposition
technique.
A precursor solution was prepared by mixing
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

solution of 10 mM Bi(NO3)3 and 35 mM VOSO4
and adjusted pH < 0.5 with HNO3[7]. Then 2 M of
sodium acetate was added for adjusting pH of thesolution to study the effect of pH at four pH valuesof 3.0, 4.0, 4.5, and 5.0. Cyclic voltammetry was
introduced for BiVO4 thin film fabrication by using
potentiostat (Metrohm 663VA Stand). A typicalthree-electrode system was comprised of the FTO
as working electrode, the Ag/AgCl (3 M KCl) as areference electrode and a platinum wire as a counterelectrode. The amorphous Bi-V-O film deposition
was studied with the effect of several parameters;
the apply potentials of +1.5 to +2.5 V, the precursor
solution temperatures of RT (25°C), 40°C, 50°C,
60°C, and 70 °C, the scan rate of 25, 50, 100, and
250 mV/s and the number of cycle scan of 1, 3, 5,
and 7 cycles. The crystalline BiVO4 thin film wascarried out by annealing the amorphous Bi-V-O at
the temperatures of 500°C. The optimum condition
was considered with the highest photocurrent fromthe photoelectrocatalytic water oxidation depending
with the FTO/BiVO4 photoanode from eachcondition. The photocurrent was measured at a
fixed potential of 1.0 V vs. Ag/AgCl in 0.5 M
Na2SO4 aqueous solution under chopped visible
light illumination.

Evaluation of the optimum condition for BiVO4
thin films fabricated by CVD method
3.1.1 Effect of pH
Afterdissolving
Bi(NO3)36H2O
withconcentrated HNO3, VOSO4 was added in thechemical bath solution and adjusted pH again bysodium acetate to study the effect of pH value of
3.0, 4.0, 4.5 and 5.0. At pH 3.0 the precursor
solution was turbid and presented reddish brown
peeling out occurring of BiVO4 film from FTO
substrate because Bi(III) is soluble at a very low pH
value, there is no film formation on the substrate.
When pH of the electrolyte solution increases to the
middle acidity rank, the BiVO4 film could becompletely deposited on the FTO substrate which
improved the photoelectrocatalytic activity at pH
4.5. At the pH 5.0, the BiVO4 was also deposited on
the FTO substrate but the photoelectrocatalytic
activity was decreased due to the V(IV) precipitatesfrom the solution at the pH above 5 [7]. This result
indicates that the specific pH value of a precursor
solution is very important to control the quality of
BiVO4 thin film fabrication at FTO substrate.
3.1.2 Effect of precursor solution temperature
400
Photocurrent (µA)

Characteristic
andphotoelectrocatalytic
properties of BiVO4 thin films
The morphologies of the BiVO4 thin films on
FTO were investigated by using scanning electron
microscopy (SEM, JEOL, JSM -5410LV). X-ray
diffraction (XRD, JEOL, JDX-3530) analysis was
carried out (Cu Kα radiation) to confirm thecrystallinity of the prepared BiVO4 electrodes. The
optical absorption spectra of the electrodes were
measured by using a UV/vis spectrophotometer(Shimadzu, UV-1601). The photoelectrocatalytic
activity and the electrochemical impedance
spectroscopy (EIS) were performed with a
VersaSTAT3 (Princeton Applied Research, Inc.) at
the potential of 1.0 V vs. Ag/AgCl under visible
light illuminated and frequencies ranging from 100
kHz to 0.1 Hz. The characteristic andphotoelctrocatalytic activities of BiVO4 thin films
electrode prepared by CVD method were comparedwith the other BiVO4 thin films fabrication by theamperometry (keep the potential of 1.9 V) [7] andspin coating methods (5 layers of BiVO4) [12].

light on

300

b

200

c
d
e
a

100
0

0

20

40

60 80
Time (s)100 120
light off

Fig. 1. Amperograms of FTO/BiVO4 prepared with thedifferent precursor solution temperatures of (a) Room
Temperature (b) 40 °C (c) 50 °C (d) 60 °C and (e)70 °C
The photoelectrocatalytic water oxidation of the
BiVO4 photo anode obtained at the different precursor
solution temperatures during cyclic voltammetryelectrodeposition process are shown in Fig. 1. It was
found that at room temperature BiVO4 film could not
be deposited on FTO substrate and did not present thephotoelectrocatalytic activity. When the temperature
was increased to 40°C a BiVO4 film was completely
immobilized onto the substrate cause to theincreasing photo current from the water oxidation.

RESULTS AND DISCUSSION
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

However, the BiVO4 was agglomerated on thesubstrate surface and decreased photo current when
the temperature is higher than 40oC. This effect due
to the increasing temperature would create manyions on the surface that may resulted in the
agglomerated and peeled BiVO4 [13]. Therefore, thetemperature of a precursor solution for BiVO4electrodeposition was selected at 40oC.
3.1.3 Effect of scan rate
Figure 2 shows that the effect of scanning
rate on CVD technique for BiVO4 thin film
fabrication related with the photocurrent from wateroxidation. As a result, the low scan rate values of 25
and 50 mV/s presented high photoelectrocatalytic
water oxidation of FTO/BiVO4 electrode. The
increasing scan rate to 100 and 250 mV/s were
performed the decreasing of photoelectrocatalytic
activity. It indicates that faster scan rate affects the
speed of a precursor deposition to incompletely
grow the BiVO4 on FTO while slower scan rate withmore diffusion time of a BiVO4 precursor to deposit
completely on the substrate. Based on thisexperiment, the scanning rate of 50 mV/s was
selected with the highest photocurrent from wateroxidation.

The
characteristic
properties
andphotoelectrocatalytic water oxidation of different
BiVO4 electrode fabrication methods were studied.
The BiVO4 electrode prepared by CVD ( applied
potential of 1.5-2.5 V) method was compared withthe previous research of the amperometry method( keep the potential of 1. 9 V) [ 7] and spin coating
method (5 layers of BiVO4) [12]light on300

3.2.1 Absorption properties
4

b
a

200

c
d

100
0

Comparison BiVO4 electrode with different
deposition method

Absorbance

Photocurrent (µA)

400

Fig. 3. Amperograms of FTO/ BiVO4 electrodeprepared by CVD method with the study of scanning
cycle number (a) 1 (b) 3 (c) 5 and (d) 7 cycles

0

20

40

60 80 100 120
light off
Time (s)Fig. 2. Amperograms of FTO/BiVO4 prepared by thedifferent scan rates of (a) 25 (b) 50 (c) 100 and (d) 250
mV/s

tocurrent (µA)

200
d

300

d b
400
500
600
Wavelength (nm)a

700

The absorption edge of electrodes were used to
calculate a band gap energy with equation 1.
(1)
Where, Eg is band gap energy and λ is absorption
edge (nm)The band gap energy of BiVO4 from CVD, spin
coating, and amperometric method were calculated

light oncbc1Fig. 4. The UV-visible spectra of (a) FTO andFTO/BiVO4 electrodes prepared by different methodof (b) Cyclic voltammetry (c) Amperometry and (d)spin coating

The experiment shows that the photocurrent
enhance with the increasing number of scans from 1-5
cycles and decrease when the cycle is more than 5cycles ( Fig. 3) . Moreover, the photocurrent was
related with the EIS results which the charge transfer
resistance decreased at the cycle scan 1 to 5 andincreased at 7 cycles. This result indicates that thephotocurrent of BiVO4 depended on the film thickness
that related with the number of the scan. However,high film thickness may affect with the charge transfer
rate resistance at the electrode surface.

300

2

0

3.1.4 Effect of scanning cycle number

400

3

860

GEOMATE - Mie, Japan, Nov. 21-24, 2017of 2.21, 2.38 and 2.29 eV, respectively (Fig.4). The
results show that BiVO4 prepared by CVD have anarrower band gab energy than that other technique
indicates that higher visible light absorption
property.

8000

Zim (ohms)

3.2.2 Photoelectrocatalytic properties
The photoelectrocatalytic properties werestudied by measure the photocurrent from wateroxidation reaction at the FTO/ BiVO4 electrodesurface. The photocurrent from FTO/ BiVO4
prepared by CVD technique shows the significantly
higher photocurrent than that the amperometry andspin coating technique about 2 and 15 times,
respectively (Fig. 5). The result can use to confirm
the photoelectrocatalytic improvement of theintroduced CVD method for BiVO4 film fabrication.
There are related with high absorption property of theelectrode could be produce high photo hole( h+ ) at
valent band efficient to oxidize water to oxygen
cause present high photocurrent from this reaction.

Photocurrent (µA)

400

a

6000
4000
2000
0

b
c
0

10000
20000
Zre (ohms)

30000

Fig. 6 Nyquist plot of BiVO4 electrode prepared bydifferent methods of (a) spin coating (b) amperometry(c) Cyclic voltammetry
3.2.4 Morphology and crystalline structure

light on

300

c

200
b

100
0

a
0

50
Time (s)100Fig. 7. SEM images of (a) bare FTO substrate and
FTO/BiVO4 electrode prepared by the different methods of(b) Amperometry (c) Cyclic voltammetry and (d) Spincoating

light off

Fig. 5. Photocurrent of BiVO4 electrode prepared bydifferent methods (a) spin coating (b) amperometry (c)cyclic voltammetry

Figure 7 shows the morphology of bare FTO waschanged by the covered BiVO4 and different
characteristic depended on the deposition method.
The morphologies of BiVO4 electrodes prepared by
CVD method presented the small particle size andwell distribution. The particles are clustered
together and the size is different when BiVO4 was
prepared by the amperometry method. While thespin coating method shows flat surface by the fused
together of BiVO4. As a result, it can support thatthe uniform morphology given a good
photoelectrocatalytic properties. Figure 8 shows the
XRD patterns of BiVO4 film fabricated with applied
potentials after annealing at 500 °C for 1 h. The
XRD peaks observed at 2θ = 18.8°, 28.9° and 30.6°
were indicated to the diffractions monoclinic
BiVO4 plane of (011), (121) and (040), respectively.
As the results show that the monoclinic BiVO4
crystalline structure can be performed by all
methods preparation after annealed at 500oC.

3.2.3 Charge transfer resistant properties
An EIS measurement was applied tocharacterize electrochemical interfacial reaction of
FTO/ BiVO4 electrode for water oxidation undervisible light irradiation that shows in Fig. 6. The
narrowest semi-circle of the Nyquist plot of BiVO4electrode prepared by CVD method represents thelowest charge transfer resistant or highest electrontransfer rate at the electrode surface. The result canbe support the highest photocurrent of the electrodedue to the reason of high photo e-- h+ generation andlow e- - h+ recombination effective with the highest
photoelectrocatalytic activity of the developed BiVO4electrode.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

[4]




Intensity (au)

4000
3500
3000
2500
2000
1500
1000
500
0



 * * 
 

*

10

* FTO
 BiVO
4

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modification of porous BiVO4 photoelectrodes forwater oxidation”, J.Phys. Chem. C., Vol. 120,
2016, pp. 23449–23457.
[11] He H.C, Berglund S.P, Rettie A.J.E, Chemelewski
W.D, Xiao P, Zhang Y.H, Mullins C.B, “Synthesis
of BiVO4 nano flake array films forphotoelectrochemical water oxidation”, J. Mater.
Chem. A, Vol. 2, 2014, pp. 9371–9379.
[12] Ponchio C, Yoshinori M, Shin-ya K, Atsuko Y
N, Yoshio N, “Efficient photocatalytic activityof water oxidation over WO3/BiVO4 composite
under visible light irradiation” , Electrochim.
Acta, Vol. 54, 2009, pp. 1147-1152.
[13] Kim H.R., Kim G., In S, and Park Y.,“Optimization of porous BiVO4 photoanode fromelectrodeposited Bi electrode: Structural factors
affecting photoelectrochemical performance”,
Electrochim. Acta., Vol. 189, 2016, pp. 252–258.

d
c
b
a

30

50
2 theta (degree)70

Fig. 8. X-Ray diffraction patterns of (a) FTO andthe FTO/BiVO4 prepared by the different methodsof (b) Cyclic voltammetry, (c) Amperometry(d) Spin coating
CONCLUSIONSThe BiVO4 thin film deposited on FTO using
cyclic voltammetry method were successful
optimized and presented the photoelectrocatalytic
for water oxidation improvement under the goodcharacteristic of films properties. This developed
CVD method for FTO/BiVO4 fabrication shows thehigh efficiency, fast, simple method and suitable inscaling up able to approach for water oxidation in
the industrial application.
ACKNOWLEDGEMENTS
This work was supported by the project ofResearch and Researchers for Industries ( RRI) ,Thailand Research Fund ( TRF) and Allianceenvironmental conservation Co., Ltd. (MSD60I0025)
REFERENCES[1] Von D, Krol R, Grätzel M, “Photoelectrochemical
Hydrogen Production” Electron. Mater. Sci.
Technol. Vol. 102, 2012, pp.13–21.
[2] Klabsong M, Kungskulniti N, Puemchalad C,
Charoenca N, and Punsuvon V, “Feasibility
study of biodiesel production from residual oilof palm oil mill effluent” Int. J. of GEOMATE,
Vol. 12, 2017, pp. 60-64.
[3] Zhao J, Zou Y, Zou X, Bai T, Liu Y, Gao R, Wang
D, Li G.D, “Self-template construction of hollow
Co3O4 microspheres from porous ultrathin
nanosheets and efficient noble-metal-free wateroxidation catalysts” Nanoscale, Vol.6 , 2014, pp.
7255–7262.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PHOTOELECTROCATALYTIC DETERMINATION OF CHEMICALOXYGEN DEMAND USING WO3/BIVO4 PHOTOELECTRODE
Niphawarn Kangkun1, Chatchai Ponchio1,2*
1Department of Chemistry, Faculty of Science and Technology, Rajamangala University of Technology
Thanyaburi, Pathumtani 12110, Thailand
2
Advance Materials Design and Development (AMDD) Research Unit, Institute of Research andDevelopment, Rajamangala University of Technology Thanyaburi, Pathumtani 12110, Thailand
ABSTRACT

Chemical Oxygen Demand (COD) is one of the most extensively used parameter for water quality
monitoring with the present of organic level as it can be used to predict a wastewater treatment. The COD
determination method is based on as simple, rapid and non-toxicity method has been attracted. The
photoelectrocatalytic (PEC) technique could covered the previous mentioned advantage and be an efficient methodfor determination of COD. A visible light responsive WO3/BiVO4 photoelectrode as COD sensor was proposed.
A COD detection limit (a signal-to noise ratio of 3) of 1.66 mg L−1 COD with a linearity range of 10 –200 mg L−1
COD were achieved at the optimum condition of applied potential of 1.0 V (vs. Ag/AgCl) and 100 W visible lightillumination. This method exhibit high precision and accuracy with the percentage of the relative standard
deviation and recovery of 3.17 and 100.87, respectively. The proposed PEC technique for COD sensor represents
the simple, rapid and environmental friendly method for the COD monitoring in the wastewater system.
Keywords: Chemical oxygen demand, photoelectrocatalytic cell, phtotoanode, Visible light responsive
INTRODUCTION

Preparation of WO3/BiVO4 photoelectrode
The FTO/WO3/BiVO4 film photoanode electrodewas prepared by using precursor solutions of 0.05 M
BiVO4 and 0.10 M WO3 as described in the previous
research [6]. Fluorine-doped tin oxide (FTO) wasused as the substrate for deposited WO3 at 1st layerand 5 layers of BiVO4 at outer side by using spin
coating method at the condition of 1000 rpm for 60 s.
Each layer deposition was dried at 150 ◦C for 5 min
and calcined at 550 oC for 1 h with the last layer.

Chemical oxygen demand (COD) is
widely used for water monitoring as it can be used torepresent the organic pollution level in wastewater[1]. The traditional dichromate method for COD
determination is obtaining many drawbacks of a longtime-consuming process, highly corrosive and toxic
reagents in used [2, 3]. The COD determination
method is based on as simple, rapid and non-toxicity
methodhas
beenattracted[4].
The
photoelectrocatalytic process (PEC) is one of thecandidate methods with the several advantages ofhigh oxidation ability, non-toxicity, and low cost [5].
TiO2 usually used in PEC with high photocatalytic
activity and stable but it only responding with UVlight cause low activity in the solar light application.
The narrow band gap energy semiconductors havebeen investigated for the photooxidation under visible
light region [6, 7]. In this work, a visible light
responsive WO3/BiVO4 photoelectrode was
performedfor
COD
determinationusing
photoelectrocatalytic process.

Thephotoelectrocatalytic
activity
photoelectrode
FTO/WO3/BiVO4
characterization studyofand

The fabricated FTO/WO3/BiVO4 electrode wasstudied the absorption properties by UV/Vis
spectrophotometer (Shimadzu, UV-1601) in the
wavelength of 300-800 nm. The photoelectrocatalytic
activity for water oxidation was performed by a
VersaSTAT3 (Princeton Applied Research, Inc.) withamperometry at the potential of 1.0 V vs. Ag/AgClunder visible irradiation.
The photoelectrocatalytic performance of
FTO/WO3/BiVO4 photoelectrode for COD
determination study
The
fabricated
FTO/WO3/BiVO4
was

EXPERIMENTAL
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

introduced to the photoelectrocatalytic cell asworking electrode combining with Ag/AgCl as areference electrode and Pt wire as a counter electrode.
The three electrode system was immersed in theelectrolyte solution of 0.1 M Na2SO4 using cyclic
voltammetry deposition technique (CVD) for
determining the photocurrent from the organic
glucose oxidation at the electrode surface. The COD
value was calculated by the mole ratio of organic
glucose and O2 by the equation of 1.1.
C6H12O6(aq) + 6O2(g)fabricated electrode. Figure 2 shows that thephotocurrent under the light on significantly higher
than light off condition corresponding with highphotoelectrocatalytic water oxidation activity of the
FTO / WO3 / BiVO4 photoelectrode .

6CO2(g) + 6H2O(l) (1.1)

The standard calibration curve was operated bymeasure the photocurrent depending on the COD
value in the range of 10 – 200 mgO2/L. The effect of
supporting electrolyte, pH and electrode size werestudied for the optimum condition. The characteristicof the standard calibration curve for COD
determination was performed by using glucose as theorganic sample and considered with the optimum ofsensitivity by slope, interference by y-interception
value and linear regression (r) parameters. The figureof merit consist of linearity range, limit of detection(LOD), precision (% Relative standard deviation; %RSD) and accuracy (% Recovery) were performed toconfirm the efficiency of PEC method for COD
determination.

Fig. 2. The photocurrent of FTO/WO3/BiVO4electrode in 0.1 M Na2SO4 at an applied potential of
1.0 V vs Ag/AgCl and under the chopper of visible
light irradiation.
Evaluation
thephotoectrocatalytic
COD
determination using FTO/WO3/BiVO4 electrode

RESULTS AND DISSCUSSION

Characterization
andphotoelectrocatalytic
activities of FTO/WO3/BiVO4 photoelectrodeFig. 3. Standard calibration curve of COD
determination by PEC method with the different
FTO/WO3/BiVO4 electrode size of 0.5x0.5, 1x1 and2x2 cmFigure 3 shows that the standard
calibration information for COD determination ,which considered with the higher slope, low yintercept value and r closest to 1.00 (Figure 3). The
effect of pH value of the solution is a very importantparameter in the phtotelectrocatalytic COD
determination process. The result shows that the pH
value of 4 is the specific condition for high sensitivity
and good correlation photocurrent and COD value.
Therefore, the pH should be kept constant by the
buffer solution with the further work. The supporting
electrolyte is crucial to the charge transfer process
between anode and cathode electrode. In order toselect a suitable electrolyte and concentration of
sodium salts were tested in the photoelectrocatalytic

Fig. 1. the absorption spectra of FTO andFTO/WO3/BiVO4 electrodeFig. 1 shows the optical property of the fabricated
FTO / WO3/ BiVO4 electrode over FTO substrate. It
was found that the absorption edge was at 540 nm
corresponding to the band gap energy (Eg) value of
2.30 eV, which agree to the Eg value of the BiVO4.
The result can use to confirm the BiVO4 existent on
the FTO surface and facility to absorb visible light.
The oxidation efficiency of FTO / WO3 / BiVO4 wasstudied to confirm the photoelectrocatalytic of the864

GEOMATE - Mie, Japan, Nov. 21-24, 2017

process. However, this experimental the electrolyte
solution of NaCl and Na2SO4 have no different result.
The electrode size is one of the important parameter
effects with the performance of COD determination.
At the larger surface area shows higher sensitivity but
more interference. The suitable surface size of 1x1 cm
was selected with the optimum of sensitivity,interference and good correlation of photocurrent and
COD concentration.
At the optimum condition with applied
potential of 1.0 V (vs. Ag/AgCl) and 100W visible
light illumination could also be applied for COD
determination using potassium hydrogen phthalate(KHP) as another organic sample. Fig. 4 shows that
this condition can be used for COD determination
with several organic samples. However, thesensitivity is depended with the kind of organic
sample. The COD detection limit (a signal-to-noise
ratio of 3) and linearity ranges were 1.66 mgO2.L−1
and 10 –200 mgO2.L−1, respectively. Moreover, the %RSD and % recovery were achieved of 3.17 and100.87, respective. The result indicates that thedeveloped PEC method using FTO/WO3/BiVO4photoanode exhibited high performance for COD
determination with high precision, accuracy, and low
detection limit.

and environment-friendly technologies for the COD
monitoring in the wastewater system.
ACKNOWLEDGEMENTS
This work was supported by the project of Researchand Researchers for Industries (RRI), Thailand Research
Fund (TRF) and Alliance environmental conservation
Co., Ltd. (MSD59I0016)
REFERENCES[1] Jin B.H, He Y, Shen J.C, Zhuang Z.X, Wang X.R,
Lee F.S.C, “ Measurement of chemical oxygen
demand (COD) in natural water samples by flow
injection ozonation chemiluminescence (FI-CL)
technique” J. Environ. Monit., Vol. 6, 2004, pp.
673-678.
[2] Dan D.Z, Dou F.L, Xiu D.J, Qin Y.Q, “Chemical
oxygen demand determination in environmental
watersby mixed-acid digestion and single sweep
polarography” Anal. Chim. Acta, Vol. 420, 2000,
pp. 39-44.
[3] Dharmadhikari D.M, Vanerkar A.P, Barhate N.M,
“ Chemical oxygen demand using closed
microwave digestion system” Environ. Sci.
Technol., Vol. 39, 2005, pp. 6198-6201.
[4] Akio T, Keiichi K, Takashi N, Ryota S, andHiromu T, “ Landfill waste water treatment by
application of pulsed high voltage” Int. J. of
GEOMATE, Vol. 9, No. 1, 2015, pp. 1375-1379.
[5] Chao W, Jiancheng W, Peifang W, Yanhui A, Jun
H, and Jin Q, “Photoelectrocatalytic determinationof chemical oxygen demand under visible light
nanotube arrays
using Cu2O-loaded TiO2electrode” Sensors and Actuators B, Vol. 1 8 1 ,2013, pp. 1– 8.
[6] Ponchio C, Yoshinori M, Shin-ya K, Atsuko Y N,
Yoshio N, “ Efficient photocatalytic activity ofwater oxidation over WO3/BiVO4 composite
under visible light irradiation” , Electrochim.
Acta, Vol. 54, 2009, pp. 1147-1152.
[7 ] Ponchio C, Atsuko Y N, Yoshio N,“
Photoelectrocatalytic
performanceof
WO3/BiVO4 toward the dye degradation” ,Electrochim. Acta, Vol. 94, 2013, pp. 314– 319.

Fig. 4. Standard calibration curve of COD
determination by PEC method with the different
organic samples of glucose and KHP.
CONCLUSIONSThe proposed PEC method using
FTO/WO3/BiVO4 electrode represents a good
performance for COD determination under visible
light irradiation. This method shows a simple, rapid

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THE PERFORMANCE RAINFALL DURING RAINY SEASONAL OVER
THAILAND BY USING PRELIMINARY REGIONAL COUPLEDATMOSPHERIC AND OCEANIC (WRF-ROMS) MODEL
Pramet Kaewmesri1, Usa Humphries1,*, Boonlert Archevarapuprok2 and Sirapong Sooktawee3
Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi(KMUTT), 126 Pracha-Uthit Road, Bang mod, Thung khru, Bangkok 10140, Thailand;2
Thai Meteorology Department, Bangkok, Thailand;
3
Environmental Research and Training Center, Department of Environmental Quality Promotion, Ministry of
Natural Resources and Environment, Thailand
1

ABSTRACT
A coupled regional climate between atmosphere-ocean coupled model systems is developed using the regionalmodel Weather Research and Forecasting (WRF) and Regional Ocean Modeling System (ROMS) to simulate
performance rainfall during the rainy season over Thailand. The processes of the atmospheric model is provided
to the ocean model. The wind (Uwind, Vwind), the atmospheric pressure (Patm), the relative humidity (RH), theatmosphere surface temperature (Tair), the cloud fraction (Cloud), precipitation (Rain), the short wave (SW), thelong wave (LW). The processes of the oceanic model provides sea surface temperature (SST) to atmosphere model.
The simulation period is during June-July-August (JJA) in 2014, and the results are compared with rainfall gauge
station from Thai Metrology Department (TMD). The results show a good trend performance rainfall and cancapture large amount rainfall in June, July and JJA 2014. The average rainfall and Mean Absolute Error (MAE)
were show good value in June, July and JJA 2014, especially in June was shown good value average (236.25 mm)
and MAE (4.389) than other months.
Keywords: Coupled Model, Rainy Season, Regional Ocean Modeling System (ROMS), Thailand, Weather
Research and Forecasting (WRF)
Thailand. However a good simulation andforecasting rainfall are main factor for improving
water management. Because a good water
management can prevent and decrease the damage
from the natural disasters.
A majority of the Atmospheric General
Circulation Model (AGCMS) has difficulty insimulating the mean well as the intra-seasonalvariability of monsoon rainfall mainly due to the lackof air-sea interactions [3]. On the other hand,coupled models are powerful tools for enhancing theskill of seasonal simulation and forecasting. It’s
providing realistic simulation and forecasting overtropical phenomenon [4].
However, the researches in Thailand are based on
rainfall event. They were used AGCM andstandalone regional model to simulation rainfall
events that were neglected of air-sea interactions. In
this study, to use a regional couple modeling systemby the Coupled Ocean Atmosphere Wave SedimentTransport (COAWST) to simulate rainfall in rainyseason of Thailand. The simulation period was
during June, July and August (JJA) in 2014. The
results was basic compared with rainfall gauge
station from Thai Metrology Department (TMD)
data.

INTRODUCTION
Seasonal prediction of the Asian Monsoon
System (ASM) rainfall in advance with high spatial
resolution is a major challenge due to influence ofmultiple factors, including the topography of thesubcontinent and the impact of the surrounding
oceans [1]. The ASM is regarded to be separate into
two subsystems the Indian Ocean monsoon systemand the East Asian Monsoon System (EAMS) [2].
The two main points of AMS has impact overThailand, that regimes are the northeast monsoon(winter season) during November to March and thesouthwest monsoon (summer season) during midMay to mid-October. The one important feature ofclimate in Thailand is rainfall. It is the main sourceof fresh water on the earth and is a major componentof the hydrologic cycle on the earth’s surface. Hence,in every annual year, the southwest monsoon(summer season) is blow wet air form the Indian
Ocean to over country. So it make the rainfall overThailand in this period. Sometime the rainfall eventsoccurred in Thailand producing breaking flash floodand enormous amount of property damage.
Therefore we can say, the rainfall is the main factor
for agriculture, industrial, irrigation and etc. in866GEOMATE - Mie, Japan, Nov. 21-24, 2017

Toolkit (MCT) that allow the transmission andtransformation of various distributed data between
component models using parallel coupled approach.
MCT is a program written in Fortran90 and works
with the MPI communication protocol. In this study
used the COAWST coupled model to simulate
WRF-ROMS over the rainy season in 2014 year. In
the processes of the atmospheric model is provided
to the ocean model. The wind (Uwind, Vwind), theatmospheric pressure (Patm), the relative humidity(RH), the atmosphere surface temperature (Tair), thecloud fraction (Cloud), precipitation (Rain), the shortwave (SW), the long wave (LW). In the processes ofthe oceanic model provides sea surface temperature(SST) to atmosphere model [6]. The Fig.2 isrepresent a transfer parameter between atmospheremodel and ocean model.

METHODOLOGY
The atmospheric model part
The atmosphere part of the coupled model is theWeather Research and Forecasting model (WRF).
This model was developed by the National Center
for Atmosphere Research (NCAR). The model iscontained with a terrain following sigma coordinate
in the vertical coordinate, Arakawa C-gridstaggering for horizontal grid, initial conditions,boundary condition, multiple-nested domain and fullset of physical parameterisation options. The moredetailed description of WRF in [5]. The physics
parameterizations used in this study that is: WSM3class scheme for microphysics scheme, the BettsMiller-Janjic (BMJ) for cumulus scheme, the Rapid
Radiative Transfer Model (RRTM) for long wave
radiation scheme, the Duhia for short wave radiation
scheme, the Noah Land-Surface Model for surface
and the Yon-Sei University (YSU) Planetary
Boundary Layer (PBL) scheme PBL scheme. The
model domain is covers over Thailand and neighborwith horizontal grid spacing of 30 km, 28 layers invertical levels and the model top of 50 hPa.
The oceanic model partThe oceanic part of the coupled model is theRegional Ocean Modeling System (ROMS). Thismodel is a general class free-surface, terrainfollowing numerical model that solve the three
dimensional Reynolds-averaged Navier-Stokes
equations using the hydrostatic and Boussinesq
approximations. This model is based on primitive
equation ocean model and uses finite-difference
approximations on the Arakawa-C staggering in thehorizontal with on a vertical stretched terrainfollowing coordinate. The basic ideal case study thevalues of thetas, thetab and Tcline in this study are
3.0, 0.4, and 50.0 respectively. The initial values ofu wind (wind direction from east to west), v wind
(wind direction from south to north), temperature,and salinity before transfer in coupled model are 0,0, 35, and 18 respectively. The oceanic model
domain is the same as the regional atmosphericmodel. The horizontal grid spacing is 30 km. But thevertical level of oceanic model is 21 levels. The
model domain is shown in Fig.1.

Fig. 1 The domain was used in this study. Thisdomain has 179×179 grids spacing covering atlatitude -10.86 degree north to 45.89 degree northand longitude 68.65 degree east to 131.35 degree
east

The coupled and experiment configuration
In this study was used the Coupled Ocean
Atmosphere Wave Sediment Transport (COAWST)
model system. The COAWST model system is an
agglomeration of open source modeling componentsthat has been tailored to investigate coastal processesof the atmosphere, ocean, waves and coastal
environment [6]. The coupler is the Model Coupling

Fig. 2 The application was showed configurationsof data exchanged WRF and ROMS model

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The model runs were initialized at 0000 UTC 1
May 2014 and ended at 0000 UTC 31 August 2014
for a three month simulation. The first month
simulation (May 2014) was regarded as model spinup and excluded from comparison with observation,
as show in Fig. 3.

118 Gauge Station Data (TMD)

Fig. 4 The station locations used for model
evaluations.
RESULT AND DISCUSSION
Fig 5 shows the month accumulate rainfall from
TMD station data and month accumulate rainfall
simulation from WRF-ROMS coupled model in June
2014.
The TMD station data show the rainfall
distribution (in the rage of 0 mm to 400 mm) almost
over the country. But the rainfall distribution withlarge amounts rainfall is (more than 500 mm) overUbon Ratchathani and Nakhon Phanom province inthe northeastern Thailand, Trat province in the coasteastern Thailand and Ranong province in thesouthern Thailand, as shown in Fig 5(a).
The WRF-ROMS coupled model shows therainfall distribution (in the range of 0 mm to 400mm) almost over the country. But the rainfall
distribution with large amount rainfall is (more than
500 mm) over Ubon Ratchathani and Nakhon
Phanom province in the northeastern Thailand, as
shown in Fig 5(b).
Fig 6 shows the month accumulate rainfall from
TMD station data and month accumulate rainfall
simulation from WRF-ROMS coupled model in July2014.
The TMD station data show the rainfall
distribution (in the rage of 0 mm to 400 mm) almost
over the country. But the rainfall distribution withlarge amounts rainfall is (more than 500 mm) overUbon Ratchathani, Bung Kan and Nakhon Phanom
province in the northeastern Thailand, Trat province
in the coast eastern Thailand and Ranong province inthe southern Thailand, as shown in Fig 6(a). The

Fig. 3 The period month spin-up and month
simulation in this study.
In this study was used the National Centers forEnvironmental Prediction (NCEP) Final Operational
Global Analysis (FNL) data for initial data. The
NCEP-FNL product is from the Global Data
Assimilation System (GDAS). The grid spacing data
are in 1-degree by 1-degree and 6-hourly intervals.
The period of data during 1800 UTC 30 July 1999 to
the present and the surface area covered longitude
180 degree east to 180 degree west and latitude 90
degree south to 90 degree north. Table 1 wasconcluded the physics parameterization schemes andscenario configuration.
The observation data used to verify the resultsfrom the model. In this study are measurements
made at 118 gauge stations from the Thai
Meteorological Department (TMD). The location of
118 gauge stations are covered Thailand, as shownin Fig 4.
Table 1 The physics parameterization schemes andscenario configuration.
Physics
Details
Cumulus scheme
BMJ
Microphysics scheme
WSM3
Short wave radiation scheme
RRTMLong wave radiation scheme
Duhia
Planetary boundary Layer scheme YSULand surface
Noah
Run period
3 Mon (JJA)

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WRF-ROMS coupled model shows the rainfall
distribution (in the range of 0 mm to 400 mm) overcenter, lower northeastern and lower southern
Thailand.

But the rainfall distribution with large amountrainfall is (more than 500 mm) over northern, upper
northeastern, western, Rayong and Trat province overcoast eastern Thailand, as shown in Fig 6(b).

TMD

WRF-ROMS(a)(b)
Fig. 5 Spatial rainfall pattern of month accumulate rainfall (mm) in June 2014: a) TMD and b) WRF-ROMS.
TMD

WRF-ROMS(a)(b)
Fig. 6 Spatial rainfall pattern of month accumulate rainfall (mm) in July 2014: a) TMD and b) WRF-ROMS.
(more than 500 mm) over northern, Bung Kan, Sakon
Nakhon, Nong Khai and Udon Thani province innortheastern, Sa Kaeo province in coast eastern andKanchanaburi province in western Thailand, shownin Fig 7(b).
Fig 8 shows the month accumulate rainfall from
TMD station data and month accumulate rainfall
simulation from WRF-ROMS coupled model in JuneJuly-August (JJA) 2014.
The TMD station data show the rainfall
distribution (in the rage of 0 mm to 400 mm) almost
over the country. But the rainfall distribution withlarge amounts rainfall is (more than 500 mm) overUbon Ratchathani and Nakhon Phanom province in

Fig 7 shows the month accumulate rainfall from
TMD station data and month accumulate rainfall
simulation from WRF-ROMS coupled model inAugust 2014.
The TMD station data show the rainfall
distribution (in the rage of 0 mm to 400 mm) almost
over the country. But the rainfall distribution withlarge amounts rainfall is (more than 500 mm) overMae Hong son in northern and Trat province in the
coast eastern Thailand and Ranong province in thesouthern Thailand, as shown in Fig 7(a).
The WRF-ROMS coupled model shows therainfall distribution (in the range of 0 mm to 400 mm)
almost southern and center of Thailand. But therainfall distribution with large amount rainfall is869

GEOMATE - Mie, Japan, Nov. 21-24, 2017

rainfall distribution with large amount rainfall is(more than 500 mm) over almost northern, Loei,
Nong Bua Lamphu, Amnat Charoen, Yasothon,
Nakhon Phanom and Udon Thani province innortheastern Thailand, as shown in Fig 8(b).

the northeastern, Trat province in the coast eastern
Thailand and Ranong province in the southern
Thailand, as shown in Fig 8(a).
The WRF-ROMS coupled model shows therainfall distribution (in the range of 0 mm to 400 mm)
almost southern and center of Thailand. But the
TMD

WRF-ROMS(a)(b)
Fig. 7 Spatial rainfall pattern of month accumulate rainfall (mm) in August 2014: a) TMD and b) WRF-ROMS.
TMD

WRF-ROMS(a)(b)
Fig. 8 Spatial rainfall pattern of month accumulate rainfall (mm) in JJA 2014: a) TMD and b) WRF-ROMS.
Table 2 was shown the average rainfall. It was
shown overestimate average rainfall than the TMD
data in all cases. The Mean Absolute Error (MAE)
was shown good performance in June (4.389). Butshow a more MAE value in July (12.126). In
summary, the results was overestimated in average
rainfall and the MAE results shown good
performance with TMD data.
Fig. 10 shows the temporal MAE over Thailand.
It’s shown less significant (more than 12) over
Chiangmai, Lamphun, Lampang, Phetchabun and
Chiangrai in northern, Loei in northeastern, Trat ineastern, Ranong and Phang Nga in southern Thailand.
However, the overall of temporal MAE was shown
good performance (less than 12) in many part ofThailand. For example over central, western, lower
southern and northeastern Thailand.
CONCLUSION
In this research used a preliminary coupledmodel between atmospheric model WRF and
Oceanic model (Regional Ocean Modeling System(ROMS)) to simulation performance rainfall during
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distribution, compared with the TMD. However, theresults show in a good trend performance rainfall andcan capture large amount rainfall in June, July and
JJA 2014. When comparison rainfall gauge stations
by using MAE method over Thailand. The MAE
shown the relation between TMD and the coupledmodel similar average rainfall value. The temporal
MAE was shown good performance over Thailand.
Future work, we will improve the result from thecoupled model (WRF-ROMS). We will update theinitial boundary condition from ideal case to realcase in Oceanic model (ROMS).

the rainy season over Thailand.
Table 2 Comparison TMD and WRF-ROMS
Average (mm)MAE
TMD
WRF-ROMS
Jun
186.45236.254.389
Jul214.77540.04 12.126
Aug
237.98416.327.150
JJA
213.07397.54
7.201

ACKNOWLEDGEMENTS
The authors are also grateful NCEP for the FNL
data sets, TMD for the station data sets, NCAR for
the WRF model and the Department of Mathematics,
Faculty of Science, King Mongkut’s University ofTechnology Thonburi (KMUTT). This research was
fully supported by the International Research Network (IRN) (IRN5701PDW0002).
REFERENCES[1] Salama BK, Nagaraju C, Banerjee S, Kaginalkar
A and Dalvi M, “Study of the Indian summer
monsoon using WRF-ROMS regional coupledmodel simulation”, Atmospheric science letters,Vol. 14, Aug. 2012, pp. 20-27.
[2] Pokhrel S, Chaudhari HS, Subodh KS, Dhakate
A, Yadav RK, Salunke K, Mahapatra S,
Suryachandra AR, “ENSO,IOD and Indian
Summer Monsoon in MCEP climate forecast
system”, Clim Dyn, Vol. 39, Mar 2012, pp.
2143-2165[3] Rajendran K, Kitoh A and Arakawa O,“Monsoon low-frequency oscillation and oceanatmosphere coupling over the Indian Ocean”,
Geophysical Research Letters, Vol. 31,
L002210, DOI:10.1029/2003GL019031[4] Kristma KK, Hoerling M, Rajagopalan B,“Advancing dynamical prediction of Indian
monsoon rainfall”, Geophysical Research
Letters,
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32,
L0874,
DOI:10.1029/2004GL021979.
[5] Skamarock WC, Klemp JB, Dudhia J, Gill DO,
Barker DM, Duda MG, Huang XY, Wang W,
and Powers JG, A description of the AdvanceResearch WRF Version 3. National Center for
Atmospheric Research, Boulder, Colorado,
2008.
[6] Warner JC, Armstrong B, He R, and Zambon, JB,“Development of a Coupled Ocean-AtmosphereWave-SedimenTransport (COAWST) modelingsystem”, Ocean Modeling, Vol. 35, July 2010,
pp. 230-244.

Fig. 10 The temporal MAE in JJA 2014 overThailand.
The simulation period is during June-JulyAugust (JJA) in 2014. The results from coupledmodels were shown overestimate accumulate
rainfall in June, July, and August 2014. Table 2, theaverage rainfall were confirmed the coupled model
overestimating in all cases.
However, it can capture the large amount rainfall
similarly TMD data. In June 2014, the coupledmodel can capture large amount rainfall similar
TMD over Ubun Ratchathani and Nakron Phanom
province in northeastern. In July 2014, the coupledmodel can capture large amount rainfall similarly
TMD over Ubun Ratchathani and Nakron Phanom
province in northeastern and Trat province in eastern.
In June-July-August (JJA) 2014, the coupled model
can capture large amount rainfall similar TMD over
Ubun Ratchathani and Nakron Phanom province innortheastern.
Therefore, the WRF-ROMS coupled model
performed overestimate in simulating spatial
871

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

THE LONG TERM CHANGE OF FORM OF NITROGEN IN YAMATO
RIVER BASIN
1

Masanobu Taniguchi1 and Hiryuki Ii1
Facultyof System Engineering, Wakayama University, Japan
ABSTRACTThe long term of the amount of pollutant load was estimated by relation between water level and water quality.
The long term data is not enough to the calculation of the amount of pollutant load. The pollutant load in floods is
not cleared, so the pollutant load in flood condition is important for the annual pollutant load. The water quality isimproved, and the water quality target is being achieved in the Yamato River. To improve the water quality, thesewage systems had been constructing from 1970’s in Yamato River Basin. The amount of annual nitrogen loadin 2011 was estimated in 2016 by Taniguchi et al. However the long term change of amount of annual load is
unclear. It is estimated that the form of nitrogen load was changed. This research is consider the influence forwater quality of the construction of sewage system, improvement of riverbed and the River purification facility. It
is estimate that the treatment systems had change the environment of the oxygen in the river bed.
Keywords: Annual load, Water quality, Nitrogen, River flow rate, Sewage system
the sewage system was 7.4% in 1975, 33% in 1990,
58.7% in 2000 and 85.3% in 2013[3]. The analysis ofnitrogen load was performed using data for the water
information system of Ministry of Land,
Infrastructure, Transport and Tourism, Japanese
Government. However there was not enough data tocalculate the amount of nitrogen load in YamatoRiver Basin, so some estimation methods wereapplied for making this calculation[4].

INTRODUCTION
The Yamato River had problems of waste waterfrom sewage. The river water was polluted in 1970’s,
as the city developed rapidly. The sewage system in
the Yamato River Basin had established while eachyear. The condition of the water quality in the YamatoRiver was improved from 1970 to 2017. It isestimated that the nitrogen form in the river water waschanged by the oxygen condition. The water quality
and water flow of the database system was publishedby Japanese governments. Resultingly, there was notenough data to calculate the amount of nitrogen loadin Yamato River Basin[1] It is necessary that clear the
relation between everyday data of water quality
example EC and nitrogen concentrations. The
research purpose is clear the relation between theeveryday data and the monthly data. Moreover
estimate the nitrogen load form change from 1970 to2016.
RESEARCH AREA AND METHOD
Fig.1 shows the map of the Yamato River Basin.
Fig.2 shows the population of the Yamato River
Basin. River basin is 1070km2. Green, yellow, pale
blue and purple colors show forests, orchards, rice
fields and housing sites. The population of the basin
is about 2 million people in 2015. The basin has big
cities in its upper stream, and the population of the
Nara basin is 1 million people. Population increased
significantly in high-growth period. The sewage
system has been in use since 1970s. The cover area ofFig. 1 Map of the Yamato River Basin

872

GEOMATE - Mie, Japan, Nov. 21-24, 201750

Taishi Bridge
Asaka
Fujii

40

BOD (mg/L)

30
20

2012

2014

2016

2012

2014

2016

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

1970

0

1972

10

Fig. 3 Time series of BOD concentration
20

Nitrogen (mg/L)

NO 3- -N
NO2--N
NH 4+ -N
T-N

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1972

1970

0

1974

10

Fig. 4 Time series of nitrogen concentration at Fujii
2.5

90

Nara
Osaka
Sewage System

2.0

80
70

1.5

60
50

1.0

40

Rate(%)

Population(million people)

1974 to 1988. And the BOD concentration in 2012
decreased about the one-fourth of 1970’s. The
Taishi Bridge is located at lower stream of the out
flow point of Sewage System in Nara. And Fujii islocated in lowest point of the Nara Basin, The waterin the Nara Basin is collected at the point. Asaka islowest point of the Yamato River Basin. The BOD
concentration is not measured in all years. So it isdifficult to know the annual BOD load, and estimate
the influence of decompose the Organic compoundby the data only. However the BOD change tends
several year is similar, the BOD concentration range
is same in 3 points. Therefore it is estimated that the
BOD concentration is not almost change at the 3
point in the River. The trends of the BOD
concentration is analyzed at the follow in detail.
Fig. 4 shows the time series of nitrogenconcentration at Fujii. The Total-Nitrogen is highfrom 1982 to 1988, same as BOD concentration
tends. The T-N concentration is not measured before
1981. The ammonia nitrate concentration is high from1970 to 1988. The ammonia nitrogen concentration
decrease from 1989 to 2012. The nitrate nitrogen

100

30
0.5

20
10

2013

2008

2003

1998

1990

1985

1980

1975

1970

1965

1960

1955

1950

1945

1940

1935

1930

1925

0
1920

0.0

Fig. 2 Population of the Yamato River Basin
TIME SRIES OF WATER QUARLTY AND
FLOW RATE
Fig. 3 shows a time series of BOD concentration
at Fujii, Asaka and Taishi Bridge. The graph useddata of Ministry of Land, Infrastructure andTransport. The BOD concentration was high from873

GEOMATE - Mie, Japan, Nov. 21-24, 2017

concentration tends to increase year by year
from1976 to 1999, and not change after 2000. Nitrite
nitrogen concentration is always low.
Generally, organic compounds in an anaerobic
condition were decomposed to ammonia by bacteria.
The reaction formula is given by the following
equation (1).

T-N (mg/l)

20(CH2 O)106 (NH3 )16 H3PO4  53CH4  53CO2  16NH3  H3PO4 (1)T-N (mg/l) = 1.01 NH4+-N (mg/l) + 3.74
Year
1970～1975
1975～1980
1980～1985
1985～1990
1990～1995
1995～2000
2000～2005
2005～20102010～2015
2015～2020

10

The Nitrification in an aerobic condition is shownby the following equation (2).

0

(2)

-



NH4  1.86O2  1.98 HCO3 

0

10
NH4+-N (mg/l)-(0.0181 0.0024)C5H7 NO2  1.04H2O  0.98NO3  1.88H2CO3

Fig. 5 Relation between T-N and ammonia nitrateconcentration at Fujii

Generally Ammonia changes into nitrate in
aerobic conditions and then finally organic
compounds change into nitrate. These reactions
depend on activity of living organisms. Temperature
is important for the activity of the organisms.
However nitrate nitrogen concentration did notchange with temperature. Nitrate acid was consumedby photosynthesis or denitrification and the biologicalactivities of photosynthesis or denitrification werealso dependent on temperature.
Denitrification reaction is shown by the following
equation (3).


(CH 2O)106 (NH3 )16 H 3PO 4  84.8NO3  84.8H  
106CO 2  42.4N 2  16NH 3  H 3PO 4  148.4H 2O

20

Fig. 5 shows the relation between T-N andammonia nitrate concentration at Fujii. T-N
concentration was increased with ammonia nitrateconcentration, and T-N concentration was decreased
in recent years. The ammonia nitrogen concentration
is different by period. The cause is the sewage
system is constructed constantly in the period, and it
is estimated that the sewage water had become
gradually not directly inflow the river. As theammonia is created by organic compound
decompound, the cause of ammonia rich is thatorganic compound become ammonia in the river, or
not inflow ammonia directly. It was estimate thatthe ammonia nitrate concentration has been tend toinclude by constant ratio against T-N. In recent years,
as the ammonia nitrogen concentration is low, it wasestimate that organic compound did not flow intoriver, or ammonia was change to nitrate. The
ammonia nitrogen concentration before 2000 isincreased with T-N concentration. The T-Nconcentration 1970s was estimated from ammonia
nitrogen concentration.
20(3)

Photosynthesis reaction is shown by the following
equation (4).
-106 CO 2  16NO 3  16H   H 3 PO 4  122H 2 O  (4)(CH 2 O)106 (NH 3 )16 H 3 PO 4  138O 2

As the form of nitrogen is change by the reactions,the nitrogen concentration is

T-N (mg/l) = 1.43 NO3 - -N (mg/l) + 0.06
Year

1970～1975
1975～1980
1980～1985
1985～1990
1990～1995
1995～2000
2000～2005
2005～20102010～2015
2015～2020

OF

T-N (mg/l)

INFLUENCVE OF DECOMPOSITOIN
ORGANIC COMPONENT

10

0
0

1

2
3
4
NO3 -N (mg/l)

56Fig. 6 Relation between nitrogen nitrate concentration
874

GEOMATE - Mie, Japan, Nov. 21-24, 2017

and T-N at Fujii
Fig. 6 shows the relation between T-N andnitrogen nitrate concentration at the Fujii. The
nitrate nitrogen concentration is clarity increased
with T-N concentration after 2000. However thenitrate nitrogen concentration is not related to T-Nconcentration before 2000. Moreover T-N
concentration is high in low nitrate nitrogenconcentration. It is estimated that the nitrate nitrogenchange became clarity by construction of the sewage
system. Recent years, the 80% of amount of riverwater in the Yamato River Basin is treatment waterof sewage system. It is estimated that the water
quality of the river water is almost due to the sewage
system condition. However before 2000, thehousing water of sewage is inflow directly into theriver, in the river, the organic compound of nitrogenis change to ammonia, finally change nitrate. The
chemical change of nitrogen is due to the fungus, thereaction is different by water temperature, therefore
it is estimated that nitrogen concentrations is notstable.

T-N

20

WATER LEVEL CHANGE AND NITORGEN
CONCENTRATION CHANGE

2000 Flow rate = 7.00(Water level)^ 2.60

Flow rate

Year

1000

0

0

1

2

3 4 5 6
Water level

78Fig. 8 Relation between Water level and flow rate at
Fujii
Fig. 8 shows the relation between water leveland flow rate at Fujii. The water level is measured
every day, however flow rate is not measured every
day, and moreover flow rate in flood time cannot
measured direct. Therefore the flow rate is
calculated using next formula by the water level.

(T-N) = -0.17 (Water temperature) + 8.19
Year
1970～1975
1975～1980
1980～1985
1985～1990
1990～1995
1995～2000
2000～2005
2005～20102010～2015
2015～202010

1970～1975
1975～1980
1980～1985
1985～1990
1990～1995
1995～2000
2000～2005
2005～20102010～2015
2015～2020

(5)

.

7.00

F:Flow rate (m3/sec) W:Water level(m)

20
0

0

10
20
30
Water temperature

Year

40

T-N

Fig. 7 Relation between water temperature and T-N
at Fujii
Fig. 7 shows the relation between watertemperature and T-N at Fujii. The T-N concentration
is decreased with Water temperature. The T-Nconcentration before 2000 is tend to higher than its
after 2000. It is estimated that the cause of high T-Nconcentration is due to high ammonia nitrogenconcentration. So, if ammonia concentration exist, it
is considered that more actually nitrogen load can becalculated. Moreover it was estimated that thenitrogen concentration can be calculated using bytemperature before and after 2000.

1970～1975
1975～1980
1980～1985
1985～1990
1990～1995
1995～2000
2000～2005
2005～20102010～2015
2015～2020

10

0

0

1

2

3 4 5 6
Water level

78Fig. 9 Relation between water level and T-Nconcentration at Fujii
and875

Fig. 9 shows the relation between water level
T-N concentration at Fujii. The T-N

GEOMATE - Mie, Japan, Nov. 21-24, 20176000
T-N(g/sec)

T-N(g/sec)

5000
4000
3000
2000

0

1970/1/1
1971/1/1
1972/1/1
1973/1/1
1974/1/1
1975/1/1
1976/1/1
1977/1/1
1978/1/1
1979/1/1
1980/1/1
1981/1/1
1982/1/1
1983/1/1
1984/1/1
1985/1/1
1986/1/1
1987/1/1
1988/1/1
1989/1/1
1990/1/1
1991/1/1
1992/1/1
1993/1/1
1994/1/1
1995/1/1
1996/1/1
1997/1/1
1998/1/1
1999/1/1
2000/1/1
2001/1/1
2002/1/1
2003/1/1
2004/1/1
2005/1/1
2006/1/1
2007/1/1
2008/1/1
2009/1/1
2010/1/1
2011/1/1
2012/1/1
2013/1/1
2014/1/1
2015/1/1
2016/1/1

1000

Fig. 11 Time series of T-N load (g/sec)8000
T-N(t/year)

T-N(t/year)

7000
6000
5000
4000
3000

1000

1970/1/1
1971/1/1
1972/1/1
1973/1/1
1974/1/1
1975/1/1
1976/1/1
1977/1/1
1978/1/1
1979/1/1
1980/1/1
1981/1/1
1982/1/1
1983/1/1
1984/1/1
1985/1/1
1986/1/1
1987/1/1
1988/1/1
1989/1/1
1990/1/1
1991/1/1
1992/1/1
1993/1/1
1994/1/1
1995/1/1
1996/1/1
1997/1/1
1998/1/1
1999/1/1
2000/1/1
2001/1/1
2002/1/1
2003/1/1
2004/1/1
2005/1/1
2006/1/1
2007/1/1
2008/1/1
2009/1/1
2010/1/1
2011/1/1
2012/1/1
2013/1/1
2014/1/1
2015/1/1
2016/1/1

2000

Fig. 12 Time series of T-N load (t/year)
concentration is not change by the water level. The
range of water level is narrow, and the range ofseasonal change of T-N concentration is tend tolarge compared with range of water level. It wasestimated that the T-N concentration is not
influenced by the increased the flow rate byprecipitation et.al. Generally it is considered that the
T-N concentration is decreased with cause ofdilutionofprecipitation.
However
T-N
concentration is not decreased by dilution, moreover
it is estimated the nitrogen is supply from othersource example farmland or rice field. Therefore it
was considered that the T-N concentration is small
influenced by dilution.

8

Water level (m) = 1.10 ouji(m) + 0.55
Water level (m)Water level (m)

7
6
5
4
3
2
1
0
-2 -1

0

1 2 3
ouji(m)4

5

6

Fig. 10 Relation between the water level at the Ouji
and the water level at the Fujii
Fig. 10 shows the relation between the waterlevel at Ouji and the water level at Fujii. Ouji islocated upper about 2.7km distance from Fujii. The
section from Ouji to Fujii has only little stream, theflow rate of the little stream is not influence. The
water level at Fujii was no data in several year, so thewater level at Fujii was interpolated by the water level
876

GEOMATE - Mie, Japan, Nov. 21-24, 2017

3500t/year after 1994. It is estimated that the causeof T-N load of decrease is influence of constructionof the sewage system and the river purification
facility. The main nitrogen form before 2000 wasammonia, the main after 2000 was change to nitrate.
As against the ratio of T-N is cleared, it wasestimated that the nitrate nitrogen load was about
70% of T-N after 2000, and the ammonia nitrogenload was more than 50% of T-N before 2000 when
there are many.

data at Ouji. The water level at Fujii was calculated
by next formula.
CALCULATION OF ANNUAL LOAD
Fig. 11 and 12 show the time series of T-N load.
The T-N concentration was related to watertemperature. The T-N load could be calculatedroughly. The flow rate was calculated from the waterlevel. The T-N load was multiplied flow rate and TN concentration. Generally, in the case of
calculation of the load amount, the influence of theflow rate is larger than the concentration. Annual
total nitrogen load at Fujii station was calculated tobe maximum 7208t/year in 1976, minimum 1334t/year in 2010. The T-N load was decreased less than
3500t/year after 1994. It is estimated that the causeof T-N load of decrease is influence of constructionof the sewage system and the river purification
facility.

REFERENCES[1] Masanobu Taniguchi, Hiroyuki Ii, Tatemasa
Hirata, Analysis of organic nitrogen compoundin domestic sewage in Yamato River using asocial experimental test, 2010, vol. 30, Part 10, p.
1587–1590, Stuttgart, April 2010[2] Ministry of Land, Infrastructure and Transport,
Japan,
Water
information
system,http://www1.river.go.jp/[3] YamatoRiver
construction
office,http://www.yamato.kkr.mlit.go.jp/YKNET/inde
x.html[4] Masanobu Taniguchi, Hiroyuki Ii, Tatemasa
Hirata, The development of water resource system– The Water balance of Yamato River Baisin,
Environmental Engineering Research Papers Vol.
48,2011.
[5] Isamu
Munemiya,
HiroshiTsuno:
Environmental
Water
Quality
Studies,
KoronaSya, in Japanese, p48, 2001.
[6] Mikio Hino: Clear hydraulics, p138-152, inJapanese, 1983

CONCLUSION
The amount of nitrogen load was estimated andthe distribution of nitrogen load was analyzed in
Yamato River Basin from 1970 to 2016. Although
there was not enough data to calculate nitrogen loadin the basin, some estimation methods were applied
for calculation. At Fujii station, flow rate is
calculated by water level. Total nitrogen load isestimated using water temperature. Annual total
nitrogen load at Fujii station was calculated to be
maximum 7208t/year in 1976, minimum 1334t /year
in 2010. The T-N load was decreased less than877

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

HEAVY METAL CONCENTRATION OF SEAWEED BY INFLUENCE
ON COPPER MINE AT SADAMISAKI PENINSULA
Erika Ueno1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan;
2
Faculty of Systems Engineering, Wakayama University, Japan

1

ABSTRACT
There were about 66 copper active mines in the Sadamisaki Peninsula from middle Meiji to Taisho era
although all mines closed. It is important to evaluate influence of waste water and tailings from mines
accompanied with past copper mine activity on environment for surrounding area. Sea water heavy metal
concentration is low and changeable however heavy metal concentration of seaweed is generally high because of
bio-concentration and depends on long term surrounding condition. Therefore, it is easy to measure heavy metal
concentration and to evaluate long term environment. Then, seaweeds were sampled at both the Sadamisaki
Peninsula and the surrounding non copper mine areas, the Yashiro Island in Yamaguchi prefecture and Kada in
Wakayama prefecture and copper, iron, manganese, lead, zinc and arsenic concentrations of seaweeds were
measured. As a result, copper and iron concentrations of green seaweed at sampled at the Takaura Bay in the eastof the Sadamisaki Peninsula were 100 to 350 ppm and 100 to 1000 ppm respectively and ten times higher thanthose of the other samples. Manganese, lead, zinc and arsenic concentrations for seaweed sampled at the
Sadamisaki Peninsula were almost the same as those sampled at the other areas. As ore minerals of the copper
mines were mainly pyrite FeS2 and chalcopyrite CuFeS2, the waste water and tailing contained iron and copper.
The biggest mine, the Takaura mine in the Sadamisaki area faced the Takaura Bay. High copper and ironconcentrations of seaweed sampled at the Takaura Bay were thought to indicate contamination caused by activityof copper mine.
Keywords: Heavy metal, Mine, Seaweed, Contamination
INTRODUCTION
Seaweed contains 15 kinds of trace elements
besides various kinds of minerals taken from sea
water. The elements are in indispensable for humanbeings and humans and marine creatures [1].
Seaweed gets nutrition and heavy metal by taken inseawater. Then, seaweed reserves the heavy metals
such as arsenic in the body for long term. This
characteristic is bioconcentration. It is clear thatheavy metal concentration in seaweed is higher thanthat in seawater by bioconcentration. In previous
studies,characteristics
oftrace
element
concentration in each region were studied [2]-[6].
The one of the study area is the Sadamisaki
Peninsula located in the western part of Ehime
prefecture and the area is famous for many closed
copper mines operated in Taisho to beginning ofShowa era [7]. And development of mines was
actively carried out in Taisho era.
Figure.1 shows points of mining trace in the
Sadamisaki Peninsula. There were 66 mine traces
operated during the heyday. Although at present allmines closed, waste water from some closed mines
and from tailings of mines still flows into sea. As themost area of the Sadamisaki Peninsula ismountainous and its coast is steep slope and cliff,
waste water directly flows into sea.
Therefore, seaweed sampled around theFig.1. Points of mining trace
Sadamisaki Peninsula can be assumed as seaweed inmetal contamination sea. Then, seaweed in the
Sadamisaki Peninsula and the other areas are
sampled and their metal contaminations aremeasured for evaluating metal contamination in sea.

878

GEOMATE - Mie, Japan, Nov. 21-24, 2017

In the previous study, heavy metal concentrationin seaweed at the Kii Peninsula was measured andheavy metal concentration pattern for each seaweed
species was also clarified. It’s known that Cu, Fe
and Mn concentrations in green seaweed werehigher than those in brown and red seaweed and that
there was no clear difference of Pb and Znconcentrations among green, brown and red
seaweeds and that As concentration in brownseaweed was higher than those in green and red
seaweed. In this research, to clarify the tendency
around the Sadamisaki Peninsula based on theprevious study.

METHOD AND STUDY AREA

Fig.2. Sampling area

Cu concentrations in seaweed

Fig.2 shows sampling area, the Sadamisaki
Peninsula, Yashiro Island in Yamaguchi prefecture
and Kada in Wakayama Prefecture.

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue・ izumi
Mue
Izumi
0.1

1

10

100

1000

Cu(p pm)

Fig.4.1 Cu concentration in seaweed at the
Sadamisaki PeninsulaFig.3. Sampling points at the Sadamisaki Peninsula
Lighthouse
Uchinoura
TakauraFig.3 shows 14 sampling points around the
Sadamisaki Peninsula, 8 points along the Seto Inland
Sea and 6 points along the Uwakai Sea.
8 sampling points along the Seto Inland Sea are
Lighthouse, Yobokori, Myoujin, Kojima, Ooe,
Ikatagoshi, Mue and Izumi, 6 points along the
Uwakai Sea are Uchinoura, Takaura, Inoura, Natori,
Futami and Mekkomisaki.
The seaweed are collected at the time of the ebb
tide.
The collected seaweeds are dried and thendissolved with concentrated nitric acid. Heavy metal
concentration of solution is measured by ICP-AES.
Heavy metal concentration in seaweed was
calculated according to equation (1)KojimaOoe
Mekkomisaki
Ikatagoshi
Mue
Izumi
1

10

100

1000

Cu(p pm)

Fig.4.2 Cu concentration in Ulvales at the
Sadamisaki PeninsulaFig.4.1 shows Cu concentration of seaweed.
Green seaweed, brown seaweed, and red seaweed
are shown as circle, triangle and square. The Seto
Inland Sea and the Uwakai Sea are shown as solidand open symbol. Cu concentrations in seaweed
along the Seto Island Sea were 0.19 to 6.57 ppm, Cu
concentrations in seaweed along the Uwakai were0.26 to 337 ppm.
Fig.4.2 shows Cu concentrations in Ulvales. Cu
concentrations in most green seaweed were 1 to 10
ppm. Especially, Cu concentration in green seaweed
at Takaura was 121 to 334 ppm.

(1)
RESULTS
The heavy metal concentrations in seaweed at
the Sadamisaki Peninsula879

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.6 shows Mn concentrations in green
seaweed along most points were several to several
10 ppm. Especially Mn concentrations in Ulvales at
Takaura were 136 to 206 ppm.

Fe Concentration in Seaweed
Fig.5.1 shows Fe concentrations in seaweed at
the Sadamisaki Peninsula. Fe concentrations inseaweed along the Seto Inland Sea were 30 to 1676
ppm, and along the Uwakai were 30 to 8196 ppm.

Pb Concentration in Seaweed

Lighthouse
Uhinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
・
Mue
Izumi
Izumi

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue・ izumi
Mue
Izumi
10

100

1000

0.01

10000

0.1

1000

10000

Fe (ppm)

Zn Concentration in seaweed

Fig.5.2 Fe concentrations in Ulvales at the
Sadamisaki Peninsula

Fig.8 shows Circles show green seaweed,
triangles show brown seaweed, and squares show
red seaweed. Zn concentrations in green, brown andred seaweed at all 15 points were 10 to 100 ppm.
Therefore there was no clear difference in 15 points.

Fig.5.2 shows Fe concentration in Ulvales. Fe
concentrations at Kojima and Ikatagoshi were 3109
ppm and 1313 ppm, Fe concentrations at Takaura
and Mekkomisaki were 1619 to 8195 ppm and 3082
to 4102 ppm.

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
・Mue
Mue
Izumi
Izumi

Mn Concentration in Seaweed.
Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue・ izumi
Mue
Izumi
1

100

Fig.7 shows Circles show green seaweed,
triangles show brown seaweed, and squares show
red seaweed. Pb concentrations in green, brown andred seaweed at 8 points along the Seto Inland Sea
were 0.1 to 10 ppm. On the other hand Pb
concentrations in green, brown and red seaweed at 7
points along the Uwakai Sea were 0.1 to several 10
ppm. Therefore Pb concentrations at the Sadamisaki
Peninsula were no clear difference between green,brown and red seaweed.

Lighthouse
Uchinoura
TakauraKojimaOoe
Mekkomisaki
Ikatagoshi
Mue
Izumi
100

10

Fig.7 Pb concentrations in seaweed at the
Sadamisaki Peninsula

Fig.5.1 Fe concentrations in seaweed at the
Sadamisaki Peninsula

10

1
P b(ppm)F e (ppm)

1

10

100

1000

Zn(ppm)Fig.8 Zn concentrations in seaweed at the
Sadamisaki Peninsula
10100

As Concentration in Seaweed

1000

Mn(p pm)

Fig.9 shows As concentrations in brown seaweed
at all fifteen points were several to 100 ppm.
Therefore there was no clear difference in 15 points.

Fig.6 Mn concentrations in seaweed at the
Sadamisaki Peninsula
880

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.11 shows Fe concentrations in seaweed at thethree sampling area. Fe concentrations in seaweed at
Takaura were higher than those of the other area.

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue・ izumi
Mue
Izumi
0.1

Mn concentrations in seaweed

1

10

100

Fig.12 shows Mn concentrations in seaweed at
the three sampling area. Mn concentrations inseaweed at the Yashiro Island were higher thanthose of the Sadamisaki Peninsula.

1000

As(p pm)

Fig.9. As concentrations in seaweed at the
Sadamisaki Peninsula

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
・
izumi
Mue
Izumi
YashiroKada

The heavy metal concentrations in seaweed at thethree sampling areas
The heavy metal concentrations in seaweed at the
Sadamisaki Peninsula were compared with the
Yashiro Island and Kada. The Yashiro Island isalong the Seto Island Sea, Kada is along the Osaka
bay.

1

1000

10000

Pb concentrations in seaweed

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
・
Mue
izumi
Izumi
YashiroKada

Fig.13 shows Pb concentrations in seaweed at
the three sampling area. Pb concentrations inseaweed at Takaura and Mekkomisaki were higher
than those of the other area.

1

10
Cu(p pm)

100Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
・
izumi
Mue
Izumi
YashiroKada

1000

Fig.10 Cu concentrations in seaweedat the three sampling area
Fig.10 shows Cu concentrations in seaweed at thethree sampling area. Cu concentrations in seaweed at
Takaura were higher than those of the other area.

0.01

Fe concentrations in seaweed

0.1

P b(ppm)

1

10

100

Fig.13 Pb concentrations in seaweedat the three sampling area

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
・
Mue
izumi
Izumi
YashiroKada
1100
Mn(p pm)

Fig.12 Mn concentrations in seaweedat the three sampking area

Cu concentrations in seaweed

0.1

10

Zn and As concentrations in seaweed
Fig.14 and 15 show Zn and As concentrations inseaweed at the three sampling area. Zn and As
concentrations in seaweed at the Sadamisaki
Peninsula were not higher than those of the other
area.
10

100
Fe (ppm)

1000

10000

Fig.11 Fe concentrations in seaweedat the three sampling area
881

GEOMATE - Mie, Japan, Nov. 21-24, 2017

and Mn concentrations in Hijiki at Takaura werelower than those at some areas. Cu, Fe, Mn, Pb, Zn,
and As concentrations in Ishige were about the sameas those at the other areas.
So, Cu, Fe and Mn concentrations in Ulvales
were considered to be a sensor for finding
contaminated area.

Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
・
Mue
izumi
Izumi
YashiroKada

CONCLUSION

1

10

Zn(ppm)100

1000

There were about 66 closed copper mines in the
Sadamisaki Peninsula from middle Meiji to Taishoera. The Takaura Mine was the biggest copper minein the Sadamisaki area operated from middle Meiji
to Taisho era. As ore minerals of the copper mines
were mainly pyrite FeS2 and chalcopyrite CuFeS2[8], the waste water and tailing contained iron andcopper. The Takaura mine faced the Takaura Bay.
At Takaura, Cu, Fe and Mn concentrations in green
seaweed were very high. High copper and ironconcentrations of seaweed sampled at the Takaura
Bay were thought to indicate metal contamination
caused by activity of now closed copper mine. Also
Fe concentrations in green seaweed at Kojima werehigher than those sampled at the other areas. It is
faced inside the bay, so sampling point is not
influenced by ocean current.
The heavy metal concentrations in seaweed at the
Sadamisaki Peninsula were compared with the
Yashiro Island and Kada.
Cu and Fe concentrations in green seaweed at
Takaura were 100 to 350 ppm and 100 to 1000 ppm
respectively and about 10 to 20 times higher thanthose sampled at the Yashiro Island and Kada. The
other metal concentrations in seaweed at the
Sadamisaki Peninsula were not higher than those of
the Kada and Yashiro Island. Takaura area isconcluded to be Cu and Fe contaminated area using
seaweed heavy metal concentrations comparing
normal area such as the Kada and Yashiro areas.

Fig.14 Zn concentrations in seaweedat the three sampling area
Lighthouse
Uchinoura
Yobokori
InouraTakauraMyoujinNatori
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
・
izumi
Mue
Izumi
Yashiro
Kada
0.1

1

10
As(p pm)

100

1000

Fig.15 As concentrations in seaweedat the three sampling area
DISCUSSION
Cu and Fe concentrations in Ulvales at Takaura
were higher than those of the other areas.
The heavy metal concentrations were studied
about seaweed species at Takaura. Cu, Fe and Mnconcentrations in Ulvales at Takaura were about 10
to 20 times higher than those of the other kinds ofseaweed at Takaura although Pb, Zn and As
concentrations in Ulvales at Takaura were not higher
than those of the other kinds of seaweed at Takaura.
The heavy metal concentrations in Ulvales at
Takaura were compared with the other areas.
Cu concentrations in Ulvales at Takaura wereabout 100 times higher than those of the other areasat the Sadamisaki Peninsula, Fe concentrations inUlvales at Takaura were about 10 times higher thanthose of the other areas at the Sadamisaki Peninsula.
Also Cu concentrations in Ulvales at Takaura
were about 10 times higher than those at the Yashiro
Island. And Fe concentrations in Ulvales at Takaura
were 100 times higher than those at the Yashiro
Island.
The other hand, the heavy metal concentrationsin Hijiki and Ishige at Takaura were not higher thanthose in Ulvales at Takaura. The heavy metal
concentrations in Hijiki and Ishige at Takaura werecompared with those in Hijiki and Ishige at the otherareas. Cu, Pb, Zn and As concentrations in Hijiki
were about the same as those at the other areas. Fe

REFERENCES[1] Oishi K, Science of seaweed: Asakura
Bookstore, 1933.
[2] Abe N, Sudo S, Sera K, Saitou Y, Yoshida N
and Kudo T, “PIXE analysis of trace heavy
metal elements concentrated in seaweed”
Report on NMCC Collaborative Research
Results 11, 2003, pp.70-77.
[3] Ii H, “AS, SR, ZN, FE, MN, PB AND CU
CONCENTRATIONS OF SEAWEED AT THE
KII PENINSULA, JAPAN” International
Journal of GEOMATE, June, 2016, Vol. 10,
Issue 22, pp. 2036-2042.
882

GEOMATE - Mie, Japan, Nov. 21-24, 2017[4] Ii H, “CU, ZN AND AS CONTAMINATION
OF SEAWEED BESIDE SHIZUKI AND
KANAYAMA METAL MINES IN JAPAN”
Int. J. of GEOMATE, Sept., 2015, Vol. 9, No. 1(Sl. No. 17), pp. 1411-1417.
[5] Yamamoto T, and Ishibasi M, “The Content ofTrace Elements in Seaweeds”, in Proc. 7th Int.
Seaweed Symposium, 1971, pp. 511-514.
[6] Yamamoto T, “Chemical Studies on the
Seaweeds (27) The relations between
Concentration Factor in Seaweeds andResidence Time of Some Elements in Sea
Water”, Records of Oceanographic Works inJapan., Vol. 11, No.2, March. 1972, pp. 65-72.
[7] Fujioka K, Human geography of the Cape
Peninsula - Ehime Prefecture Sadamisaki
Peninsula Scientific Research Report -:Taimeido, 1966.
[8] Kimura T and Kobayashi K, “Report on copper
sulfide iron ore floor survey in the western partof Ehime prefecture” Geological Surveyor
Monthly Report, 1954, 5(10) pp.505-528.

883

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

EVALUATION OF IMBIBITION PROCESS IN POROUS MEDIABY INVADED PERCOLATION PROBABILITY
1

Junichiro Takeuchi1 and Masayuki Fujihara1
Graduate School of Agriculture, Kyoto University, Japan
ABSTRACT

Water retention property of soil is determined by soil texture, soil structure, and physical properties of grainsurface. Specifically, it is influenced by various factors such as pore size, pore shape, connectivity to neighbor
pores, and contact angle of grains in a bottom-up manner. The water retention curve, which is a relation between
retained water in soil and matric potential, can exhibit different shape depending on such factors. However, fromour previous numerical experiments with a pore-network model, it was suggested that the various water retention
curves can be integrated into an almost identical curve irrelevantly to different pore-size distributions whenvariously saturated porous media is evaluated by an evaluation index derived from the percolation theory. The
evaluation method is called invaded percolation probability here, and it is extended from the percolation
probability, which is the one that evaluates a degree of connectability of a network. In this study, more detailed
numerical experiments for imbibition process are conducted and the applicability of the invaded percolation
probability is investigated. It is found from the obtained results that a common curve of the invaded percolation
probability is obtained if pores in the pore-network do not have any correlation with their neighbor pores. In a casewhere the pore-network has some spatial structure, it was found that a different curve of the invaded percolation
probability is obtained, and that this evaluation method is applicable unless the structure is disturbed.
Keywords: Water Retention Property, Pore-network, Percolation Theory, Invasion Percolation
While physical indices are used in both axes in thewater retention curve, proportions of invadable andinvaded pores to total pores are used in the invaded
percolation probability. The matric potential in thewater retention property corresponds to the
proportion of invadable pores in the invaded
percolation probability, and saturation to the
proportion of invaded pores. By introducing thisevaluation method, there is a possibility various water
retention curves obtained from different soil type istreated in a unified way, and this deepens
understanding of invasion processes as a basic
principle. In this study, applicability of the evaluation
method and factors that determine the shape of theinvaded percolation probability are investigatedthrough numerical experiments.

INTRODUCTION
Soil is essential for not only agriculture but also
all terrestrial flora and fauna including humankind.
Among various soil properties such as physical,
dynamic, and chemical ones, hydraulic properties arequite important for crop production since water
retention characteristics and permeability have a large
influence on crop growth. So far, many models suchas van Genuchten-Mualem model [1], [2], which isone of representative functional ones based on thebundle of capillary tubes model, have been utilized.
In addition, to reproduce the hydraulic properties ofsoil in a bottom-up manner, an approach with a
network of pores has been conducted focusing on theimportance of connectivity of pores [3] after Fatt et al.
proposed a pore-network model [4], and thisapproach was employed to analysis pore structure [5],[6]. Recently, detail shape of pores and frequency ofpore size is being directly grasped due to thedevelopment of observation apparatus such as a highresolution X-ray CT (computed tomography) scan [7].
On the other hand, it was reported that invasion
phenomena such as imbibition and drainage
processes can be put together into a single curve
based on the percolation probability from the analysis
with the percolation theory [8]. The curve, which isreferred to the invaded percolation probability in thisstudy, shows a relationship between invadable andinvaded pores, and resembles the water retention
curve, which shows a relationship between matricpotential and saturation or water content in soil.

MODEL
Pore-network Model
To conduct numerical experiments in thefollowing section, a pore-network model is utilized,
and it is extracted from a virtual porous medium
which is made by the discrete element method. A
virtual porous medium is composed of equal-size
spherical grains packed randomly in a cubic container.
From the porous media, a pore-network is extractedwith the modified Delaunay tessellation method [9].
In Fig. 1, a virtual porous medium, which is formedby about 5800 spherical grains of 0.2 mm in a
3mm×3mm×3mm container, and a pore-network
extracted from the porous medium are shown.
884

Network1
Network2
Network3

0.4

0.2

0.2
0.0

2 4 6

8 10 12 14 16 18 20(a) Coordinate number (-)

0.0
0.0

0.2

0.4

0.6

0.8

(b) Pore body radius (0.1 mm)

1.0

Frequency (-)

0.6
0.2

0.4

0.1

0.2

0.0
0.0

1.0

2.0

3.0

4.0

0.0
5.0
0.0

(c) Pore throat length (0.1 mm)

0.2

0.4

0.6

0.8

1.0

(d) Pore throat radius (0.1 mm)

Fig. 2 Histograms of coordinate number and pore sizes

A pore-network consists of pore bodies (PBs) andpore throats (PTs). Pore bodies are relatively large
pores and are represented by circles in Fig. 1. Porethroats are relatively small pores that connect two
PBs, and are represented by tubes here. The extracted
pore-network, which is referred to Network1 here, inFig. 1 (b) has about 14,000 PBs and 35,500 PTs, andfrequency distributions of pore sizes and coordinate
number, which is the number of PTs that a single PB
connects, are shown in Fig. 2. Figure 3 shows thecorrelations between coordinate numbers andbetween pore body radii of PBs and other PBs
surrounding them. Except for the vicinity of the rightends of both graphs, where values disperse since thenumber of samples in each dot is small, the shape ofthe graphs is generally flat, which shows that neither
coordinate number nor PB size have strong spatial
correlation with their neighbors. But the level of low
radii is a little lower compared with others, whichmeans that small PBs tend to connect small PBs.

Neighbor mean
coordinate number (-)

0.4

0.6

Neighbor mean
PB roudius (0.1mm)

Frequency (-)

GEOMATE - Mie, Japan, Nov. 21-24, 201720

average
one sigma

Network1
Network2
Network3

10

30

10

0

0

20

40

(a) Coordinate number (-)
1.0
0.8
0.6
0.4
0.2
0.0
0.0 0.2 0.4 0.6 0.8 1.0(b) PB radius (0.1 mm)

Fig. 3 Correlation ofneighbor PBs

using networks, two processes are considered on a
network: One is a site process, in which sites play amain role, and the other is a bond process, in whichbonds play a main role. In a case of a site process,each site takes one state from two states: ‘open’ or‘close’. When a site is open, the open site can convey
something, which depends on an objective system
and information, electricity, and infectious disease
are given as an instance [10]. In this study, open sites
represent invadable pores that are small enough, andclose sites represent non-invadable pores that arelarge in a case of imbibition process. Then, conveyed
matter is water. In a case of drainage process, open
(invadable) pores are the ones that are large enough,and conveyed matter is air. Basically, the imbibition
process into normal (hydrophilic) soil can be treatedas a site process, because PBs regulate water invasion.
This means that if water can invade into a certain PB,
water can inevitably invade into the PTs connecting
to the PB since the connecting PTs are smaller than
the PB. And the drainage is treated as the bondprocess for the same reason.
The percolation probability is an index ofconnectability inside a network, and is represented bya relation between the proportion of all open elements(sites or bonds) in a network and that of the largest

Percolation Probability
In the percolation theory, a network is represented
by sites and bonds, which correspond to PBs and PTs,
respectively, in a pore-network model. In an analysis
885normal PB-size
based

0.8

-60

Matric potential (cmH 2O)

Percolation probability (-)

1.0

Network1
Network2
Network3

0.6
0.4
0.2
0.0
0.0

0.2

0.4

0.6

0.8

Proportion of ‘open’ sites (-)

Fig. 4 Percolation probability

1.0

original shuffled
Network1-50

Network2
Network3

-40
-30
-20
-10
0

0.0

0.2

0.4

0.6

0.8

Saturation (cm 3 /cm3 )Fig. 5 Water retention curves

1.0

Invaded percolation probability (-)

GEOMATE - Mie, Japan, Nov. 21-24, 2017

1.0
original shuffled
Network1

0.8

Network2
Network3

0.6
0.4
0.2
0.0
0.0

0.2

0.4

0.6

0.8

Proportion of invadable PBs (-)

1.0

Fig. 6 Invaded percolation
probability

fluid invades uniformly forming an invading front,
and the amount of remains that are not invaded issmall. When the number is small enough, fluid
invades in a fingering manner, and the amount ofremain is large even if all pores are invadable.
After the invasion process is finished, the invaded
percolation probability, which is a relation between
the proportion of invadable pores and that of invaded
pores, is calculated from the obtained final state of the
network in the same way with the percolation
probability [8]. The invaded percolation probability
never exceed the percolation probability from its
definition.

open cluster, which is the maximum subnetwork
formed by open elements, among all open clusters in
the network. Normally, as the proportion of open
elements increases, the number of open clusters
decreases, and one large subnetwork is formed
eventually by connecting each other.
In Fig. 4, two types of percolation probability ofthe site process are shown: one is a normal
percolation probability as a network, in which thepercolation probability is computed based on random
numbers given to sites. The other is a percolation
probability that is computed based on the PB size.
These show a typical shape of the percolation
probability. As the proportion of open sites increases,
the percolation probability rises suddenly at a point,
and approaches a diagonal line asymptotically. The
point of sudden rise is referred to the percolationthreshold, and it shows phase transition since thesystem changes from non-conveyable to conveyableat this point. In soil physics, the transition point has
an important meaning. In a case of imbibition process,it corresponds to the point where water begins toinvade into soil at the water-entry pressure of the soil.
It can be interpreted in the following way. When thepressure passes across the water-entry pressure, theproportion of invadable pores becomes large enoughso as to form a large subnetwork that spreads fromone side to the opposite side. In a case of drainage
process, it corresponds to air-entry pressure.

NUMERICAL EXPERIMENTS
Based on the extracted pore-networks, various
pore-networks with different frequency distributionof pore sizes are generated, and two numericalexperiments of the imbibition process are conductedin this study. In an imbibition process, pores thatsatisfy the following inequality are classified as
invadable.
pwe  pc(1)
with
pc  pair  pwater , pwe  P cos  adv / A(2)

where p we is the water-entry pressure of an objective
pore, and pc is the capillary pressure, pair and pwater
are the air and water pressures at the vicinity of the
air-water interface, P and A are the wetted
perimeter and the cross-sectional area of the pore, is the interfacial tension, and  adv is the advance
contact angle of the grain surface. The air pressure isassumed to be constant, and the water pressure is tobe hydrostatic from the pressure at the pore-network
bottom, to which desired pressure is imposed. The top
and bottom are open to air and water, respectively,
and the four side faces are enclosed by walls. Then,
air and water cannot go in and out through side faces.
Water is supplied from the bottom, and air isdischarged from the top freely in an imbibition
process. The maximum number of pores invaded in
one time step is set as 10,000, which gives no limit
substantially.

Invasion Percolation and Invaded Percolation
Probability
The dynamic process of water- or air-invasion ismodeled by the invasion percolation [11]. The
invasion percolation is a temporally and spatiallydiscretized model, and invading fluid proceeds into
invadable pores step by step satisfying the continuity
rule. Hence, each pore takes one state from threestates in addition to open (invadable) and close (noninvadable). The third state is ‘invaded’, which means
an invadable pore invaded by invading fluid literally.
As reported by Takeuchi et al. [8], the number ofpores invaded in one time step has an effect on theinvading mode. When the number is large enough,886

GEOMATE - Mie, Japan, Nov. 21-24, 2017from the three pore-networks, respectively. The
generated pore-networks are referred to ‘shuffled’,and the original ones are to ‘original’ here. The
computed water retention curves and invaded
percolation probability are shown in Figs. 5 and 6.
These figures show that the difference between eachtype of pore-network is small enough, and that thewater entry pressure of the original pore-networks islarger than that of the shuffled pore-networks
reflecting the large percolation threshold of theoriginal pore-networks.
In Fig. 7, the correlation of neighbor PBs of the
shuffled pore-networks is shown. Unlike that of theoriginal pore-networks in Fig. 3 (b), totally flat graphs
except for the right end are obtained, which showseach size of PBs connect to all size of PBs evenly. In
Fig. 8, spatial distributions of invadable and invaded
PBs in the original and shuffled pore-networks of
Network1 are shown when the percentage of
invadable PBs is 34.9%. At this time, the waterpressure applied to the bottom of the pore-network is-26 cmH2O, and only little water invades from thebottom face in the original pore-network while water
spreads in the shuffled pore-network as shown in Figs.
5 and 8. Table 1 shows that invadable PBs forms
separate small clusters in the original pore-network,and that a big cluster is formed in the shuffled porenetwork.

Different Packings of Grains
Three pore-networks extracted from different
porous media, which are made from randomlyperturbed initial position of grains, are used toinvestigate the individual difference of the porenetwork. As shown in Figs. 2 through 4, thefrequency distributions of the coordinate number andpore sizes, the correlation with neighbor PBs, and thepercolation probability are almost identical, althoughthese three pore-networks have different topology.
Besides, the computed results of the water retention
property and the invaded percolation probability
shown in Figs. 5 and 6, respectively, are also almost
identical. These results assure that the volume ofporous media employed in this study is sufficient, andthat this volume exceeds the representative
elementary volume (REV).
In addition to the verification of porous media
volume, another experiment is conducted toinvestigate the effect of the arrangement of PBs. In
the normal percolation probability, each site is treatedequally. Hence, whether a site is open or close isgiven stochastically. On the other hand, the size ofeach PB is used as a value in the PB-size-based
percolation probability. That is, 0.3 in the horizontal
axis in Fig. 4 means that 30% of sites (pores) from thesmaller ones are open. Figure 4 shows that thearrangement of PBs makes discrepancy between
normal and PB-size-based percolation probability.
The percolation threshold of the normal percolation
probability is about 0.35, and that of the PB-sizebased one is about 0.55. From this result, it is foundthat the networks as a pure network have potential toform an open subnetwork which expands sufficiently
if about 35% of sites are open, and however the
network as a pore-network need about 55% of open
sites (invadable PBs). This implies that small PBs do
not exist uniformly in the pore-network. This
inference is supported by the fact that the small PBs
whose radius is about 0.03 mm or less tend to connect
to small PBs from Fig. 3.
Another three virtual pore-networks in which PB
size is randomly shuffled in each network are madeTable 1

Properties of invadable clusters
original

the number of pores
the number of invadable pores
the number of clusters
the minimum of NIP†
maximum of NIP
mean of NIP
standard deviation of NIP

shuffled

14060
4907
1860
1045
1
1
54
2364
2.7
4.8
4.1
73.6

NIP is the number of pores in an invadable cluster.

†

Various Distributions of Pores
In this subsection, three different types of pore887

GEOMATE - Mie, Japan, Nov. 21-24, 2017

structure of small pores, which form many clusters ofseveral pores in the pore-network, was destroyed bymixing different size of pores. But even in a case of
the shuffled pore-network, the obtained invaded
percolation probability of the bimodal distributions isalmost identical to those of other distributions since
shuffled one does not have such structure.
Further, it is also found that the water-entry
pressure of a pore-network can be estimated from thepercolation probability of the site process (Fig. 4) andthe cumulative distribution of invadable pores (Fig.
10). As an example, a case of A1 is explained here. It
is found from Fig. 4 that the percolation thresholds ofthe original and shuffled pore-networks are about
0.55 and 0.35, respectively, and it is found from Fig.
10 (a) that the values of the matric potential of both isabout -39 cmH2O and -48 cmH2O when the
cumulative probability of those are 0.55 and 0.35.
This value is identical to the water-entry pressure of
A1, which is about -38 cmH2O and -48 cmH2O from
Fig. 12 (a).

size distribution, such as average-shift type, variancechange type, and bimodal type, are given to PBs andPTs of Nerwork1 (Fig. 9) to investigate the effect ofpore size distributions on water retention property andinvaded percolation probability. In the average-shifttype, the distributions are shifted upward or
downward without changing its shape from theoriginal distribution (A3), and in the variance-change
type, the variance of distributions are changed larger
or smaller from the original distribution (V3). A3 andV3 are equal to Network1. In the bimodal type,bimodal distributions are generated by mixing two
different distributions of B1 (=A1) and B5 (=A5) atvarious rates. The cumulative distributions ofinvadable pores to the matric potential of each
distributions type are shown in Fig. 10. In the same
way with the previous subsection, pore-size-shuffledversions of each pore-network are also generated.
The computed water retention properties and theinvaded percolation probabilities are shown in Figs.
11 and 12. It is found from these figures that although
the shape of water retention curves changes variously
depending on the pore-size distributions, all theobtained invaded percolation probability are almost
identical except for the bimodal distribution in theoriginal pore-network, and that the shapes of theinvaded percolation probability is the same with thosein Fig. 6 and derives from the percolation probabilityof the site process shown in Fig. 4.
In the original pore-network with the bimodal
distribution, the invaded percolation probability of B2,
B3 and B4 deviate from others. This is because the

CONCLUTIONSIn this study, two types of numerical experimentwere conducted using extracted pore-networks fromvirtual porous media to investigate the applicabilityof the evaluation method termed invaded percolation
probability. From the first numerical experiment, it
was shown that porous media randomly packed withequal-size spherical grains have a spatial structurethat small pores form separate clusters compared with888

GEOMATE - Mie, Japan, Nov. 21-24, 2017

area as revealed by a pore-scale network model”,
Water Resour. Res., Vol. 32, 1996, pp. 2345–2358.
[4] Fatt I, “The network model of porous media”, Trans.
AIME, Vol. 207, 1956, pp. 144–181.
[5] Takeuchi J, Sumii W, and Fujihara M, “Modeling of
fluid intrusion into porous media with mixed
wettabilities using pore-network”, Int. J. GEOMATE,
Vol. 10, 2016, pp. 1971–1977.
[6] Takeuchi J, Tsuji H, and Fujihara M, “Modeling of
permeability of porous media with mixed wettabilities
based on noncircular capillaries”, Int. J. GEOMATE,
Vol. 12, 2017, pp. 1–7.
[7] Mukunoki T, Miyata Y, Mikami K, and Shiota E, “Xray CT analysis of pore structure in sand”, Solid Earth,Vol. 7, 2016, pp. 929–942.
[8] Takeuchi J, Tsuji H, and Fujihara M, “The effect of
capillary radius distribution on the hydraulicproperties of porous media”, Precision Farming andResource Management, Excel India Publishers, New
Delhi, 2016, pp. 292–304.
[9] Al-Raoush R, Thompson K, and Willson CS,“Comparison of network generation technique forunconsolidated porous media”, Soil Sci. Soc. Am. J.,
Vol. 67, 2003, pp. 1687–1700.
[10] Hunt A and Ewing R, “Percolation theory for flow inporous media”, Springer, Heidelberg, 2009, p. 319.
[11] Wilkinson D and Willemsen JF, “Invasion
percolation: a new form of percolation”, J. Phys. A:
Math. Gen., Vol. 16, 1983, pp. 3365–3376

the uniformly distributed pore-network, and that the shapeof the percolation probability and the invaded percolation
probability depend on the structure. In addition, it was also
found that the structure obstructs water invasion and makes
the water-entry pressure higher as a result. From the second
experiment with various pore size distributions, it was
shown that almost identical invaded percolation probability
in each type of pore-network are obtained unless the pore
structure is destroyed, while various water retention curves
are obtained depending on the different pore size
distributions. This shows the feature of the evaluation
method that the same type of network has the same shapeof invaded percolation probability. Hence, it is concluded
that this evaluation method based on the percolation theory
is applicable, but the shape of the percolation probability isvalid only in the same type of soil.
REFERENCES[1] van Genuchten MT, “A closed form equation forpredicting the hydraulic conductivity of unsaturated
soils”, Soil Sci. Soc. Am. J., Vol. 44, 1980, pp. 892–
898.
[2] Mualem Y, “A new model for predicting thehydraulic conductivity of unsaturated porous media”,
Water Resour. Res., Vol. 12, 1976, pp. 513–522.
[3] Reeves PC and Celia MA, “A functional relationshipbetween capillary pressure, saturation and interfacial889

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

MEASUREMENT METHOD OF HEAVY METAL CONCENTRATION
IN SOIL OF OSAKA PREFECTURE USING CICADA SHELL
1

Satoru Ueda1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan
2
Faculty of Systems Engineering, Wakayama University, Japan
ABSTRACT

Shell of cicada is useful for evaluating heavy metal contamination because heavy metal concentration of
cicada is high and has long term information. Soil heavy metal concentration is variable and each soil mineral isquite different chemical composition and its concentration is not always bioavailable concentration. Adult cicada
flies after emergence and then it is difficult to determine original metal source. Then, cicada shell is easy todetermine original metal source area. In order to investigate effectiveness of using shell of cicadas for evaluating
the heavy metal concentration of the soil, heavy metal concentration of shell of popular cicada, Cryptotympana
facialis in metropolitan parks and factory site was studied. It is thought that heavy metal concentration is high infactory site, and urban park is not so. Cicada larvae absorb nutrients from trees. Cherry is very popular at bothparks and factory sites and many shells of cicada were sampled surface of cherry tree. Heavy metal
concentrations of leafs and flower of cherry were concluded to be also high and heavy metal of shell of cicada
was thought to derive from soil through trees.
Keywords: Heavy metal, Cicada, Cherry, Contamination, Park
INTRODUCTIONMETHOD AND STUDY AREA

Chemical substances such as metals will affectecosystems and the environment when excess
amount of metal is released into environment. As
heavy metals in the soil increase, it also affects
ecosystems, groundwater and plants. Therefore, it isnecessary to grasp the heavy metal concentration of
the soil [1].
However, it is not a good idea to directly measure
metal concentration of soil because all amount ofheavy metal in soil is not soluble and organisms
cannot use all amount of heavy metal in soil. Then,bioavailable heavy metal concentration is importantfor health of organization. Then, heavy metal
concentration of organization is thought to dependon bioavailable heavy metal concentration. Cicada
larva live for long term underground and get nutrientfrom tree root [2]. Adult cicada flies and then it isdifficult to determine its original ground where its
cicada lives. Cicada shell is useful for measuring thesoil heavy metal concentration. Cicada shell is foundon the tree around the ground. Tree gets nutrient andmetal from soil. Therefore, metal concentrations oftree leaves, tree flowers and cicada larva are used forevaluation of metal contamination. The habitat of
cicada larvae depends on trees [3]. Cicada shell wasseen most often on the surface of cherry tree andthen cherry flower and leaves were also analyzed.
Cicada shells were sampled at metropolitan parks
and cherry trees are also found in the parks. Cu, Zn,
Fe, Pb and Mn were studied for evaluation of heavy
metals.

Fig.1 shows 12 sampling points in Osaka, Japan.
Osaka
is
an
urban
area.

Fig.1 sampling points in Osaka, Japan.
No.1 sampling point is site after chemical factory.
Many factories are lined up around the No.1
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

sampling pint. There is a possibility that the waste
discharged at the factory is absorbed by the soil.
No.2 to No.12 sampling point is metropolitan parks.
There are no factories in the surrounding area, and it
is a place where artificial environmental burden isdifficult to apply. Therefore, soil contamination isconsidered to be small. The heavy metal
concentrations of soil are expected to differ between
No. 1 and No. 2 to No. 12. By comparing
concentrations of cicada shell sampled at No. 1 andNo. 2 to No. 12, heavy metal contamination andeffectiveness of using cicada shell were evaluated.
Cicada shell, cherry flowers and cherry leaves
are collected. The shell of the cicada collected is a
black cicada (Cryptotympana facialis). The cicadasthat inhabit the most in Osaka are black cicadas[4].
Therefore, black cicada was selected. The shell of
the black cicada was attached to the cherry tree themost. The cherry tree chose a Cerasus ×yedoensis
which is the tree with the most number of shells of
black cicadas. At least 20 cicada shells were
sampled in each place. A cherry flower was taken 1
g in each place. A cherry leaves was taken 3 leaves
in each place. Cicada shells were collected in July of
2016, cherry flower and cherry leaves were collectedin May of 2017.
The concentration of heavy metals for each pieceof cicada shell was measured. At least 10 pieces (13pieces in No.1 sampling points) in one place were
measured. Cherry flowers and leafs measured theheavy metal concentration per 0.02 g. Cherry
flowers were measured in 0.2 × 4 pieces (0.2 × 5
pieces in No. 1 sampling point, 0.2 × 3 pieces in No.
6 sampling point). Cherry leaves were measured 0.2
× 5 pieces per place. As a pretreatment, the cicada
shell was washed with an ultrasonic washer and thendried. Cherry flowers and leaves only dried. Then,they were dissolved in concentrated nitric acid,filtered, and ICP plasma emission spectrometer wasused to measure the concentration of heavy metal innitric acid. The concentration of heavy metals in
nitric acid was converted into heavy metal
concentrations of cicada shell, cherry flowers andcherry leaves using the formula shown below.
B ppm ∗

1.

Cu Concentration in cicada shell, cherry
flowers and cherry leaves

Fig.1 shows Cu concentration in cicada shell.
The maximum value is 32 ppm. The minimum value
is 5 ppm. The average value is 11 ppm. Cu
concentrations in No. 1, No. 2, No. 5 and No. 11
sampling points are high. Cu concentrations in No. 6
and No. 9 sampling points are low. Cu concentrationin No. 1 sampling point is 6 to 32 ppm. Cu
concentration in No. 2 sampling point is 10 to 14
ppm. Cu concentration in No. 5 sampling point is 9
to 26 ppm. Cu concentration in No. 11 sampling
Concentration of Cu(ppm)

35
30
25
20
cicada15
10
5
0

0 1 2 3 4 5 6 7 8 9 10 11 12 13

point is 7 to 26 ppm. Cu concentration in No. 6
sampling point is 5 to 7 ppm. Cu concentration in
No. 9 sampling point is 6 to 8 ppm.
Fig.1 Cu concentration in cicada shellFig.2 shows Cu concentration in cherry flower.
The maximum value is 26 ppm. The minimum valueis 4 ppm. The average value is 12 ppm. Cu
concentrations in No. 2, No. 5 and No. 9 sampling
points are high. Cu concentrations in No. 11 and No.
12 sampling points are low. Cu concentration in No.
2 sampling point is 19 to 26 ppm. Cu concentrationin No. 5 sampling point is 13 to 18 ppm. Cu
concentration in No. 9 sampling point is 12 to 15
ppm. Cu concentration in No. 11 sampling point is 4
to 8 ppm. Cu concentration in No. 12 sampling pointis 6 to 8 ppm.

(1)

30

Concentration of Cu(ppm)

A ppm

RESULTS

A= Concentration in dry sample
B= Concentration in nitric acid
C= Weight of nitric acid
D= Weight of dry sample
The dry sample is a cicada shell, a cherry flowers
and a cherry leaf. Measurement items are Cu, Fe,
Mn, Zn, Pb.

25
20
15

Flower10
50

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Fig.2 Cu concentration in cherry flower
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.3 shows Cu concentration in cherry leaf. The
maximum value is 23 ppm. The minimum value is 4
ppm. The average value is 10 ppm. Cu
concentrations in No. 5 and No. 6 sampling points
are high. Cu concentrations in No. 3, No. 4, No. 11
and No. 12 sampling points are low. Cu
concentration in No. 5
Fig.3 Cu concentration in cherry leaf

Fig.5 shows Fe concentration in cherry flower.
The maximum value is 305 ppm. The minimum
value is 72 ppm. The average value is 128 ppm. Fe
concentrations in No. 3 and No. 5 sampling points
are high. Fe concentrations in No. 10 and No. 12
sampling points are low. Fe concentration in No. 3
sampling point is 125 to 305 ppm. Fe concentrationin No. 5 sampling point is 138 to 244 ppm. Fe
concentration in No. 10 sampling point is 72 to 162
ppm. Fe concentration in No. 12 sampling point isConcentration of Cu(ppm)

25
20

1000

Concentration of Fe(ppm)

15
Reef

10
5
0

0 1 2 3 4 5 6 7 8 9 10 11 12 13

sampling point is 18 to 23 ppm. Cu concentrationin No. 6 sampling point is 10 to 17 ppm. Cu
concentration in No. 3 sampling point is 4 to 6 ppm.
Cu concentration in No. 4 sampling point is 5 to 7
ppm. Cu concentration in No. 11 sampling point is 6
to 8 ppm. Cu concentration in No. 12 sampling pointis 7 to 9 ppm.
Cu concentration in cicada shell, cherry flower
and cherry leaf is high in No. 5 sampling point. Cu
concentrations in shell of cicadas were 5 to 32 ppm.
Cu concentration in cherry flower were 4 to 26 ppm.
Cu concentrations in cherry leaf were 4 to 23 ppm.
Cu concentration in cicada shell, cherry flower andcherry leaf is similar.

10

Fig.6 shows Fe concentration in cherry leaf. The
maximum value is 185 ppm. The minimum value is
67 ppm. The average value is 115 ppm. Fe
concentrations in No. 2, No. 5 and No. 8 sampling
points are high. Fe concentrations in No. 1, No. 7
1000

Fig.4 shows Fe concentration in cicada shell. The
maximum value is 3300 ppm. The minimum value is638 ppm. The average value is 1632 ppm. Fe
concentrations in No. 10 sampling points are high.
Fe concentrations in No. 2 sampling points are low.
Fe concentration in No. 10 sampling point is 1440 to3300 ppm. Fe concentration in No. 2 sampling pointis 770 to 2012 ppm.
Concentration of Fe(ppm)

100

10

Reef

0 1 2 3 4 5 6 7 8 9 10 11 12 13

and No. 9 sampling points are low.
Fig.6 Fe concentration in cherry leaf

10000

100

0 1 2 3 4 5 6 7 8 9 10111213

Fig.5 Fe concentration in cherry flower

Fe Concentration in cicada shell, cherry
flowers and cherry leaves

1000

Flower90 to 100 ppm.

Concentration of Fe(ppm)

2.

100

Fe concentration in No. 2 sampling point is 130
to 182 ppm. Fe concentration in No. 5 sampling
point is 142 to 175 ppm. Fe concentration in No. 8
sampling point is 100 to 185 ppm. Fe concentrationin No. 1 sampling point is 70 to 111 ppm. Fe
concentration in No. 7 sampling point is 70 to 86
ppm. Fe concentration in No. 9 sampling point is 67
to 97 ppm.
Fe concentration in cicada shell is 10 to 25 times
higher than Fe concentration in cherry flower andcherry leaf.

cicada0 1 2 3 4 5 6 7 8 9 10111213

Fig.4 Fe concentration in cicada shell892

GEOMATE - Mie, Japan, Nov. 21-24, 20173.

concentrations in No. 2, No. 3, No. 6, No. 9 and No.
12 sampling points are high. Mn concentrations in
No. 8 and No. 11 sampling points are low.

Mn Concentration in cicada shell, cherry
flowers and cherry leaves

Concentration of Mn(ppm)

Fig.7 shows Mn concentration in cicada shell.
The maximum value is 1655 ppm. The minimum
value is 159 ppm. The average value is 533 ppm.
Mn concentrations in No. 5, No. 8 and No. 9
sampling points are high. Mn concentrations in No.
11 and No. 12 sampling points are low. Mn
concentration in No. 5 sampling point is 387 to 917
ppm. Mn concentration in No. 8 sampling point is
336 to 1655 ppm. Mn concentration in No. 9
sampling point is 230 to 964 ppm. Mn concentrationin No. 11 sampling point is 184 to 821 ppm. Mn
concentration in No. 12 sampling point is 159 to 713
ppm.

Concentration of Mn(ppm)1000

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Fig.7 Mn concentration in cicada shell
Fig.8 shows Mn concentration in cherry flower.
The maximum value is 120 ppm. The minimum
value is 10 ppm. The average value is 38 ppm. Mn
concentrations in No. 6 and No. 9 sampling points
are high. Mn concentrations in No. 7 and No. 11
sampling points are low. Mn concentration in No. 6
sampling point is 100 to 120 ppm. Mn concentrationin No. 9 sampling point is 78 to 104 ppm. Mn
concentration in No. 7 sampling point is 11 to 18
ppm. Mn concentration in No. 11 sampling point is
10 to 15 ppm.

4.

Concentration of Zn(ppm)Concentration of Mn(ppm)Zn Concentration in cicada shell, cherry
flowers and cherry leaves

Fig.10 shows Zn concentration in cicada shell.
The maximum value is 1377 ppm. The minimum
value is 11 ppm. The average value is 146 ppm.

1000

Flower

1000

100

10
10

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Mn concentration in No. 2 sampling point is 144
to 200 ppm. Mn concentration in No. 3 sampling
point is 125 to 252 ppm. Mn concentration in No. 6
sampling point is 183 to 300 ppm. Mn concentrationin No. 9 sampling point is 121 to 236 ppm. Mn
concentration in No. 12 sampling point is 119 to 188
ppm. Mn concentrations in No. 8 sampling point is
15 to 17 ppm. Mn concentration in No. 11 sampling
point is 19 to 32 ppm.
Mn concentration in cherry flower and cherryleaf has variation. However, Mn concentration in
cicada shell has no variation. Mn concentration in
cicada shell is more than 10 times higher than Mnconcentration in cherry flower. Mn concentration in
cicada shell is more than 5 times higher than Mnconcentration in cherry leaf.

cicada

100

10

Reef

Fig.9 Mn concentration in cherry leaf

1000

100

100

cicada0 1 2 3 4 5 6 7 8 9 10 11 12 13

Fig.10 Zn concentration in cicada shell
0 1 2 3 4 5 6 7 8 9 10 11 12 13

Zn concentrations in No. 1, No. 5 and No. 11
sampling points are high. Zn concentrations in No. 4
and No. 6 sampling points are low. Zn concentrationin No. 1 sampling point is 138 to 1377 ppm. Zn
concentration in No. 5 sampling point is 77 to 272
ppm. Zn concentration in No. 11 sampling point is
25 to 1276 ppm. Zn concentration in No. 4 samplingFig.8 Mn concentration in cherry flower
Fig.9 shows Mn concentration in cherry leaf. The
maximum value is 300 ppm. The minimum value is
15 ppm. The average value is 119 ppm. Mn
893

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.13 shows Pb concentration in cicada shell.
The maximum value is 339 ppm. The minimum
value is 1 ppm. The average value is 31 ppm. Pb
concentrations in No. 1 sampling points are high. Pb
concentrations in No. 3, No. 6 and No. 7 sampling
points are low. Pb concentration in No. 1 sampling
point is 12 to 339 ppm. Pb concentration in No. 3
sampling point is 1 to 3 ppm. Zn concentration in No.
6 sampling point is 1 to 2 ppm. Zn concentration in
No. 7 sampling point is 1 to 3 ppm. Pb concentrationin cherry flower and cherry leaf could not be
detected.

point is 11 to 203 ppm. Zn concentration in No. 6
sampling point is 15 to 68 ppm.
Fig.11 shows Zn concentration in cherry flower.
The maximum value is 211 ppm. The minimum
value is 28 ppm. The average value is 75 ppm.

100

10

FlowerConcentration of Pb(ppm)Concentration of Zn(ppm)1000

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Fig.11 Zn concentration in cherry flower
Zn concentrations in No. 1, No. 2 and No. 3
sampling points are high. Zn concentrations in No.
10 and No. 12 sampling points are low. Zn
concentration in No. 1 sampling point is 85 to 211
ppm. Zn concentration in No. 2 sampling point is 53
to 147 ppm. Zn concentration in No. 3 sampling
point is 75 to 152 ppm. Zn concentration in No. 10
sampling point is 28 to 93 ppm. Zn concentration in
No. 12 sampling point is 40 to 60 ppm.
Fig.12 shows Zn concentration in cherry leaf.
The maximum value is 71 ppm. The minimum value
is 20 ppm. The average value is 41 ppm. Zn
concentrations in No. 4, No. 5 and No. 9 sampling
points are high. Zn concentrations in No. 3 and No.
11 sampling points are low. Zn concentration in No.
4 sampling point is 38 to 63 ppm. Zn concentrationin No. 5 sampling point is 59 to 71 ppm. Zn
concentration in No. 9 sampling point is 34 to 66
ppm. Zn concentration in No. 3 sampling point is 20
to 47 ppm. Zn concentration in No. 11 sampling
point is 24 to 37 ppm.
Concentration of Zn(ppm)cicada10

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Fig.13 Pb concentration in cicada shell
Pb concentration in cicada shell of No. 1
sampling point is high.
Consideration
Cu concentration in the cicada shell, cherry
flowers and cherry leaves was high at No. 5
sampling point. No. 5 sampling point is the Osaka
Castle Park. In 1945, there was an air raid at the
Osaka Castle Park. At that time, bombs and bullets
were dropped. Dropped bullets accumulated in thesoil, and the concentration of Cu was thought to behigh[5].
The concentration of Fe contained in the cicada
shell is very high. Therefore, it is thought that larvaof cicada absorb a large amount of Fe.
Mn concentration in the cicada shell is very high.
Therefore, it is thought that larva of cicada absorb alarge amount of Mn. In addition, Mn concentrationin the cherry flowers and cherry leaves has a large
difference between the maximum value and theminimum value. However, the Mn concentration in
the shell of the cicadas has a small difference
between the maximum value and the minimum value.
Therefore, there is no correlation between Mn
concentrations of cicadas and cherry trees.
Zn and Pb concentrations in cicada shell, cherry
flowers and cherry leaves at sampled No.1 werehigher than those at sampled other areas. Then, Zn
and Pb concentrations in soil at No.1 were thought
to be higher than those at the other areas.

Reef

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Fig.12 Zn concentration in cherry leaf
5.

100

1

100

10

1000

Pb Concentration in cicada shell, cherry
flowers and cherry leaves

Conclusion
894

GEOMATE - Mie, Japan, Nov. 21-24, 2017[2] K Hirose, Y Ito, “On an ecological note ofcicada”, Proceedings of the Kanto-Tosan Plant
Protection Society, Vol. 1961 (1961) No. 8 pp.
59[3] Yosihiro Tokue, Fumiko Imamura, Satoshi
Osawa,“Factors
Influencing
CicadaDistribution in Urban Forests”, Journal of The
Japanese Institute of Landscape Architecture,
Vol. 76 (2013) No. 5 pp. 465-46[4] Toshiyuki Minami, “On Global Warming andPredicting
OccurrenceofHeatstroke”,
JAPANESEJOURNAL
OF
BIOMETEOROLOGY, Vol. 41 (2004) No. 1
pp.41-44[5] Sinya Inano, Hideo Yamazaki, Shusaku
Yoshikawa, “The History of Heavy Metal
Pollution during the Last 100 Years, Recorded
in Sediment Cores from Osaka Castle Moat,
Southwestern Japan”, The Quaternary Research(Daiyonki-Kenkyu), Vol. 43 (2004) No. 4 pp.
275-286

In this study, the heavy metal concentration of
the soil from cicada shell, cherry flowers and cherry
leaves were estimated.
As a result, it was found that some heavy metal
concentrations in the cicada shells were higher
values than heavy metal concentrations contained incherry flowers and cherry leaves.
In addition, heavy metal concentrations in the
cicada shell, cherry flowers and cherry leaves werevariable with places. Heavy metal concentrations inplant are thought to depend on those in soil as
generally plant absorbs heavy metal from soil.
As well as heavy metal concentrations in plant,
heavy metal concentrations in cicada are thought tobe influenced by soil heavy metal concentration andthen cicada shell is also depend on soil heavy metal
concentration.
Therefore, shell of cicada is effective for
estimating heavy metal concentration from soil.
REFERENCE[1] Kenichi Ito, “Soil, Clay and Minerals on Metals
Contaminated Groundwater and Soil”, Journal of
the Clay Science Society of Japan (in Japanese),
Vol. 50 (2011) No. 3 pp. 144-153

895

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PRECIPITATION AMOUNT ON TOPOGRAPHY AT BETWEEN THE
OSAKA PLAIN AND THE SOUTH IKOMA MOUNTAINS, OSAKA
PREFECTURE, JAPAN1

Hiroki Nishiwaki1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan
2
Faculty of Systems Engineering, Wakayama University, Japan
ABSTRACT

Rain cloud direction is important for high precipitation around the mountains. The cloud direction is todetermine how many times cloud meets mountains. When cloud or wet air from sea crosses mountain in land,
updraft brings out at the mountain and new cloud occurs. As a result, at the mountain, amount of precipitation ishigher than that around the area. However, when cloud or wet air passes through other mountain before it comesto the mountain, it rains heavily at the first mountain and then it rains little at the second mountain. Wet air or
cloud from the Osaka Bay can go to the Ikoma Mountains directly from west to northwest direction and in thiscase, at the Ikoma Mountains, we have a lot of rain relative to Osaka Plain. However, wet air or cloud fromsouthwest to south firstly meets the other mountain and we have small rain at the Ikoma Mountains because wet
air or cloud precipitates before they arrive at the Ikoma Mountains.
Keywords: Amount of Precipitation, Topography, Cloud Direction, Osaka Plain, Ikoma Mountains
INTRODUCTION

change.

About 60 present area of the Japan’s land is themountain. Since heavy rain leads to landslides [1], itis necessary for safety to estimate amount ofprecipitation in mountain. It has been recognizedthat amount of precipitation increased with altitude
in mountain [2]. In other hand, it has been reported
that amount of precipitation didn’t increase inmountain. For example, Yamada et al (1995) [3] hasbeen reported that relational expression between
altitude and amount of precipitation estimate fromprecipitation sample in the Yubari Mountain,
Hokkaido, and the Gozaishyo Mountain, Mie
prefectural, Japan. However, sample gathered in the
Owase, Mie prefectural didn’t increase with altitude.
Yamada (1984) [4] has reported from samples
gathered by 28 typhoons in the upper stream of Tone
River that amount of precipitation increased withaltitude when wind was blocked by mountain. Whenwind crosses mountains in land, updraft brings out at
the mountain and new cloud occurs. New cloud canmake new precipitations. Wakimizu et al (1991) [5]has reported that topography on windward side of
the mountain can change distribution of precipitation.
A number of studies reported relationship between
topography and wind is the important factor for
amount of precipitation. Relationship topography
and precipitation has not been clarified because
topography of mountain is complicated. Therefore,
in this study, the purpose is to clarify the relation
between precipitation amount and topography andthen rain sample was sampled from the Osaka Plainto the Ikoma Mountains covering big topography

METHOD
Sampling and Analysis
Fig. 1 shows location of sampling points. Fig.2
shows location of sampling point and cross-section
from the Osaka Plain to the Ikoma Mountains. The
Ikoma Mountains is located in the north-south
direction on the border of Osaka and Nara in Japan.
There were 7 rain gauges points at the east of Osaka,
Plain, East Plain, Foot, Hillside Top, East Top andEast Hillside in east side of the Ikoma Mountains.

Fig.1 Location of sampling points
896

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.2 Location of sampling point and crosssection view. Circles are sampling points
and names are Plain, East Plain, Foot,
Hillside, Top, East Top and East Hillsidefrom west point. Diamond is themeteorological observation stations at
Yao.

W⁄ρ ⁄ C⁄2

3.0
2.5
2.0
1.5
1.0

East
Hillside

East TopTop

Hillside

Foot

0.0

EastPlain

0.5

Fig.3 Precipitation ratio in each sampling point.
Circle is the value in each event. Triangle
is the average ratio of each event.
East Plain, and Foot are 0, 0, 10 m and theirsampling points were called flat area. Precipitation
ratios for three sampling points, Plain, East Plainand Foot varied 0.5 to 1.5 and their average ratios
were 1.0. Amount of precipitation in the flat area
was constant. Altitude of four sampling points,
Hillside, Top, East Top, and East Hillside are 120,
430, 440, 280 m and their sampling points werecalled mountain area. Average of precipitation ratios
for thee sampling points, Hillside, Top and East
Hillside were 1.3 however average of precipitation
ratios for East Top was 1.0. It was thought thatamount of precipitation on mountain area was higher
than those of flat area excluding East Top. Each
precipitation ratio for Hillside, Top and East Hillsidewere not always over 1.0. Therefore, it was foundthat precipitation on the mountain was not always
high. In particular for East Top, amount ofprecipitation is less than those of another mountainarea. For mountain area, high precipitation
phenomenon was not simple and very complicated.

Rain sampling was performed 43 times by every
precipitation from May in 2014 to December in2015. 500ml bottle made of polyethylene with wide
mouth, 43.6 mm in diameter was used for sampling.
It was put on the ground at each sampling points.
Precipitation amount was measured by the following
equation.
P

Each event

3.5

Plain

Rate of precipitationeach sampling point(mm) / East plain(mm)Average
4.0

π

P: Precipitation amount (mm), W : Weight (g),
ρ : Density of water (10⁻³ g/mm³), C : Caliber ofSampler (43.6 mm)
Data of wind direction and wind speed wereobtained from Japan Meteorological Agency (JMA)at Yao point. Yao point is the closest observation
station from sampling area. Wind direction of each
event was selected the most numerous direction andwas shown by 8 directions. Cloud direction was
estimate by weather chart. Cloud direction shows
direction where rain cloud coming from and wasshown by 8 directions. Weather chart wasannounced by Japan Weather Association.

Characteristic of high precipitation in mountain
area
From Fig.3, precipitation ratios in each sampling
points were variable and complicated. The sampling
point Top is the mountain peak and then each event
was grouped into two types based on precipitation
ratio of sampling point Top. Precipitation ratio for
Top of over 1.5 was defined as A group events.
Precipitation ratio for Top of less than 1.1 wasdefined as B group events. A group events have 12
events. B group events have 9 events.
Fig.4 shows precipitation ratio of A group events
classified based on Top precipitation ratio. Average
precipitation ratio of A group events in Hillside, Top
and East Hillside was about 1.6. Precipitation ratio
for East Top varied from 0.4 to 2.4 and the average

RESULTS AND DISCUSSION
Precipitation ratio in each event
Fig.3 shows precipitation ratio in each sampling
points. Precipitation ratio is the value obtained by
dividing amount of precipitation on each sampling
point by amount of precipitation on East Plain forcomparing amounts of precipitation between Plain to
East Top. Altitude of three sampling points, Plain,
897

0.0

East
Hillside

0.5

East
Top

East
Hillside

East
Top

Top

Hillside

Foot

0.0

East
Plain

0.5

1.0

Top

1.0

1.5

Hillside

1.5

2.0

Foot

2.0

2.5

East
Plain

2.5

3.0

Plain

Precipitation ratio
Each sampling point (mm) /East Plain (mm)

3.0

Plain

Precipitation r
Each sampling point (mm) /East Plain (mm)GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig.5 Precipitation ratio of B group events
Circle is the value in each event. Triangle
is the average ratio of each event.

Fig.4 Precipitation ratio of A group events.
Circle is the value in each event. Triangle
is the average ratio of each event.

Wind and cloudrise along the slopeand make cloudWind and cloudmove aroundmountain

Multiple peak mountain

One peak mountainFig.6 Air motion types based on peak shape, one peak or multiple peaks.
mountain, one peak or multiple peaks. When shapeof mountain is multiple, air moves around mountain.
When air meets slope, air rises along slope. Air
temperature decreases with elevation by adiabatic
expansion and then saturated vapor pressure
decreases. When air vapor pressure is over thesaturated vapor pressure, raindrops occur and makerain cloud. When shape of mountain is cone, airmoves around mountain. Cloud is moved by air.
Thus, small precipitation ratio for East Top wasthought to be caused by cone shape of mountainpeak, because rain clouds move to around mountainand updraft does not occur.

was 1.3. For A group events, precipitation ratio
increased with altitude from foot via Hillside to Top
along the mountain slope. However for the east sideof Top, precipitation ratios for East Top were clearly
low and precipitation ratios for East Hillside also
were lower than those for Top.
Fig.5 shows precipitation ratio of B group events
classified based on Top precipitation ratio.
Precipitation ratios for four sampling points, Hillside,
Top and East Hillside varied 0.5 to 1.0. Precipitation
ratios for Top were almost same as those for Hillsideand East Hillside and higher than those for East Top.
Average precipitation ratio of B group events for
Hillside, Top and East Hillside was about 0.9.
Average precipitation ratio for East Top was about
0.5. In mountain area from Hillside to East Hillside,
precipitation ratio of A group events was higher thanthose of B group events. Precipitation ratio of both
A and B group events in East Top were lower thanthose around anther mountain sampling points.
Fig.6 shows air motion types based on shape ofRelationships between wind direction and highprecipitation of mountain area
Table.1 shows weather conditions of A groupevents. Table.2 shows weather conditions of B groupevents. Amount of precipitation in table.1 and 2 arevalue for the sampling point Plain. Precipitation
898

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table.1 Weather conditions of A group eventsA
group
events13-Jul-14
6-Aug-14
11-Dec-14
15-Jan-15
22-Jan-15
1-Mar-15
1-Apr-15
3-Apr-15
19-Apr-15
16-Sep-15
1-Oct-15

Amount of Precipitation
Precipitation
Ratio
(mm)
Sampling for Sampling for
Plain
Top
18.2
1.6
196.9
1.6
10.0
2.1
34.4
1.5
23.3
1.6
29.2
1.5
8.7
1.9
21.6
1.7
25.8
1.5
8.9
1.7
47.2
2.6

Wind
Direction

Wind
Speed
(m/s)
obtained by JMA
at Yao point
SW
2.6
NE
4.6
W
2.4
N
3.5
W
2.7
NW
3.2
N
3.2
N
3.2
SW
3.2
N
3.2
W
3.2

Table.2 Weather conditions of B group events
B
group
events30-Mar-14
29-Apr-14
15-Aug-14
28-Dec-14
29-Mar-15
8-Jun-15
26-Jun-15
16-Jul-15
27-Oct-15

Amount of Precipitation
Precipitation
Ratio
(mm)
Sampling for Sampling for
Plain
Top
35.8
0.9
18.3
0.6
5.6
0.6
12.0
0.8
7.5
1.1
29.8
0.9
22.8
0.9
143.2
0.8
6.7
0.7

Wind
Direction

Wind
Speed
(m/s)
obtained by JMA
at Yao point
E
3.4
E
3.1
E
1.6
W
1.2
N
2.2
E
2.6
E
2.8
NE
1.9
SE
2.0

Fig.7

Schema diagram of cloud direction. a), b),c) and d) indicate that rain clouds comefrom the northwest, west, southwest andsouth respectively.

A groupCloud
B group
Cloud
Table.3
Directionof the rain clouds
for each event.
eventsDirection
eventsDirection
Left side:
A group events,
Right side:B
26-May-14
W
30-Mar-14SW
13-Jul-14group events
W
29-Apr-14
SW
6-Aug-14
11-Dec-14
15-Jan-15
22-Jan-15
1-Mar-15
1-Apr-15
3-Apr-15
19-Apr-15
16-Sep-15
1-Oct-15

ratio in table.1 and 2 are value for the sampling point
Top. Both A and B group events had all season.
Seasons of A and B group events were variable.
Amount of precipitation of A group events forthe sampling point Plain were from 4.6 to 124.8 mm.
Amount of precipitation in B group events for the
sampling point Plain were from 6.8 to 178.1 mm.
August 6, 2014 of A group events and July 16, 2015
in B group events were both Typhoon rain. A and B
group events were variable types of rain. Thus, thedifference between A and B group events do notdepend on rain scale and then increase of
precipitation with altitude is not thought to becaused by scale effect.
Most of wind directions in A group events were
north to west. Most of wind directions in B groupevents were east. Some wind directions of A groupevents were east and north east. Similarly one winddirection of B group events was west. Then, winddirection is not absolute parameter to determine
whether A or B group events. However, western andnorthern wind can easily come up the Ikoma
Mountains slope because the mountain direction issouth to north and most of events was thought todepend on wind direction.

NW
NW
W
NW
W
NW
NW
W
W
W

15-Aug-14
28-Dec-14
29-Mar-15
8-Jun-15
26-Jun-15
16-Jul-15
27-Oct-15

SW
SW
SW
S
W
S
NW

Relationships between raincloud direction andhigh precipitation
Wind direction can cover the phenomenon ofmost precipitation. Then, cloud direction during raintime was studied.
Fig.7 shows schema diagram of cloud direction.
a), b), c) and d) indicate that rain clouds come fromthe northwest, west, southwest and south
respectively.Table.3 shows direction of rain clouds
for each event. A group events had only northwest
and west. B group events were Southwest, south,
west and northwest directions and many events of B
group were southwest directions. If rain clouds comefrom northwest or west, rain clouds move from the
Osaka Bay to the Ikoma Mountains across the Osaka
Plain.
Rain clouds go up along the slope of the Ikoma
899

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Make cloud andAmount of precipitation
Increase
Dry air can’t make cloud

Cloud or Wet air rise

Mountain

Mountain

Place

Flat

Firstly
Mountain

Secondly
MountainAmount ofprecipitation

Constant

Increase

Constant

Fig.8

Relation between Amount of precipitation and topography
was grouped into two types based on precipitation
ratio of sampling point Top. Precipitation ratio ofover 1.5 for Top was defined as A group events.
Precipitation ratio of less than 1.1 for Top was
defined as B group events.
Most of wind directions in A group events were
north to west. Most of wind directions in B groupevents were east. Some wind directions of A groupevents were east and north east. Similarly one winddirection of B group events was west. Then, winddirection is not absolute parameter to determine
whether A or B group events. However, western andnorthern wind can easily come up the Ikoma
Mountains slope because the mountain direction issouth to north and most of events was thought todepend on wind direction.
Wind direction can cover the phenomenon ofmost precipitation. Then, cloud direction during rain
was studied. Cloud directions in A group eventswere northwest or west. The other hand, cloud
directions in B group events were southwest or south.
If rain clouds come from southwest or south, rain
clouds cross the Izumi Mountains before the Osaka
Plain. When rain clouds cross the Izumi Mountains,
new rain clouds occur around the Izumi Mountains
and amount of precipitation increases around theIzumi Mountains. After passing through the Izumi
Mountains, some clouds disappear and wet air isdried at the Ikoma Mountains because of rain aroundthe Izumi Mountains.
Therefore rain cloud direction is important forhigh precipitation around the mountains. The cloud
direction is to determine how many times cloudmeets mountains. When cloud meets firstly the

Mountains and new rain clouds occur around themountains and amount of precipitation increases
around the mountain area. If rain clouds come fromsouthwest or south, rain clouds cross the Izumi
Mountains before the Osaka Plain. When rain clouds
cross the Izumi Mountains, new rain clouds occur
around the Izumi Mountains and amount ofprecipitation increase around the Izumi Mountains.
After passing through the Izumi Mountains, someclouds disappear and wet air is dried because of rainaround the Izumi Mountains. Then, rain cloud
direction is important for high precipitation aroundthe mountains.
The cloud direction is to determine how manytimes cloud meets mountains. For the sampling siteat the Ikoma Mountains cloud from northwest to
west meets firstly the Ikoma Mountains andprecipitation around the sampling area is high.
However cloud from southwest to south meets firstly
the Izumi Mountains and secondly meets the Ikoma
Mountains and then, precipitation around the Ikoma
Mountains is not high as shown in Fig. 8.
CONCLUSION
The purpose of study is to clarify the relation
between precipitation amount and topography. Thenrain sample was sampled from the Osaka Plain to the
Ikoma Mountains covering big topography change.
As a result, amount of precipitation in the flat area
was constant. Amount of precipitation on mountainarea was higher than those of flat area however it
was not always higher than flat area. The sampling
point Top is the mountain peak and then each event
900

GEOMATE - Mie, Japan, Nov. 21-24, 2017

mountain, amount of precipitation is high around themountain. However when cloud meets secondly themountain, amount of precipitation is not high aroundthe mountain.
REFERENCES[1] I. M. Patuti, Ahmad R, K. B. Suryolelono,“Mechanism and Characteristics of The
Landslides in Bone Bolango Regency,
Gorontalo Province, Indonesia”, International
Journal of GEOMATE, Vol. 12, Issue 29, pp. 18, Jan., 2017.
[2] Yabusaki S, Kono T, “Characteristics of stable
isotopes in precipitation at Kyoto basin”,
Bulletin of geo-environmental science, Vol. 14,
2010, pp23-30.
[3] Yamada T, Hibino T, Araki T, “Statistical
Characteristics of Rainfall in Mountainous
Basins” Journal of Japan Society of Civil
Engineers, No. 527, 1995, pp1-13.
[4] Yamada K, “Special Distribution of Heavy
Rainfall in Mountainous area”, Proceedings of
The Japanese Conference on Hydraulics,
Vol.28, 1984, pp.509-513.
[5] Wakimizu K, Kobayashi T, Hyashi S, “OnCharacteristics of the Rainfall Distribution on
the Isolated Conical Mountain”, Sciencebulletin of the Faculty of Agriculture, Kyushu
University, Vol. 46, Feb. 1992, pp. 237-242.

901

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

INFLUENCE OF WASTE LOADING RATE ON BIOGAS
GENERATION FROM MUNICIPAL SOLID WASTE
1Sartaj M.1, Kennedy K.1 and, Nair A.1
Civil Eng. Dept., University of Ottawa, Canada K1N6N5

ABSTRACT
Higher growth rate for acidogens compared to methanogens in Anaerobic Digestion (AD) process could result in
Volatile Fatty Acids (VFAs) accumulation, pH drop, and process instability. The organic waste loading rate and its
distribution could alleviate this problem. The objective of this study was to evaluate the effect of organic wasteloading rate and load distribution on biogas generation from organic fraction of municipal solid waste (OFMSW).
Biomethane potential (BMP) tests were carried out in 2 phases. In phase 1, the effect of 3 different organic wasteloading rates was investigated by adding 3, 6, or 9 g of OFMSW to each BMP bottle. In phase 2, the objective wasto analyze the effect of distributed loading of OFMSW. The results from phase 1 showed that the lower the organicload, the higher was the methane generation. The specific biogas generation for all three loading rates was 297 mL/g
for 3 g organic load, 155 mL/g for 6 g organic load, and 142 mL/g for 9 g organic load, respectively. The resultsfrom phase 2 showed that that there was a distinct advantage in a staged fed (distributed organic waste loading)
BMP assay with faster biodegradation and a higher yield with increasing intervals of loading. It was observed thatthe reactors with three loads of 1 g (3 X 1 g) spread over the duration of the test produced higher total biogas at afaster rate compared to the 1 X 3 g and 2 X 1.5 g OFMSW loading.
Keywords: Anaerobic Digestion, Biogas, Municipal Solid Waste, Organic Loading Rate, Leachate.

dilutes the total VFAs and moderates the pH whichmakes the substrate and conditions in the landfill more
conducive for the methanogens [4].
Since the concentration of VFAs is a function of therate of hydrolysis of carbohydrates and lipids, it was
decided to evaluate the effect of organic waste loading
rate and load distribution on biogas generation from
OFMSW. It was hypothesized that the organic loading
rate would have an effect on the performance of AD
process. Also, it was hypothesized that by distributing
the organic waste load over time would result in a morestable AD process and an increase in methane yield.

INTRODUCTIONOFMSW is mainly the waste contained in kitchen
waste and yard waste which contain organic content
from which gas and energy can be tapped and utilized.
The methane generated from the OFMSW is ofsignificance, since this is utilized to generate energy.
Methane constitutes to anywhere from 40%-60% oflandfill gas generated [1]. By better understanding oflandfill decomposition processes, a shift in thephilosophy of landfill design from the storage concept
towards a process-based (or bioreactor) approach wasinevitable in the recent decades.
An anaerobic Bioreactor LandFill (BLF) has ashorter stabilization time compared to conventional
engineered landfills and is more of a treatment systemthan a typical landfill. In BLF technology, the entire
landfill works as an anaerobic digester and accelerates
the waste decomposition by maintaining a healthyanaerobic bacterial consortium. During the acidformation phase of AD of OFMSW, the hydrocarbons
that were broken down by hydrolysis are converted
into VFAs, mainly acetic acid, butyric acid and alsohydrogen gas with a drop in pH. This along with highconcentrations of ammonia inhibits methanogenic
bacteria and restricts the potential biogas and methane
production [2]-[3]. Since the specific growth rate foracidogens are significantly higher than methanogens,
VFA accumulation causes the pH to drop which proves
detrimental to the methanogens. Leachate recirculation
with supplemental water addition employed in BLFs

MATERIALS AND METHODS
To achieve the objectives, a series of BMP assay
experiments under a controlled environment was
conducted as explained below. Two hundred and fifty
mL Kimax® glass bottles capped with butyl rubber
stoppers were used to perform mesophilic BMP assays.
BMP tests were carried out in 2 phases. In phase 1, theobjective was to determine the effect of 3 different
organic waste loading rates by adding 3, 6, or 9 g ofprepared OFMSW waste to each bottle, each
duplicated. In phase 2, the objective was to analyze theeffect of distributed loading of OFMSW with the best
loading obtained from batch phase 1, which was 3 g. A
total organic load of 3 g of prepared OFMSW was
added to reactors in different time intervals. In the firstcase, the entire 3 g of organic load was applied right at
the start of the batch test, in the second case; the initial902

load of 1.5 g was supplemented by a second load of 1.5
g at the end of day 16. And finally in the third set ofreactors, the initial load of 1 g was supplemented by
two loads of 1 g each at the end of day 16 and day 29.
All BMP tests were duplicated. Total working volume
for all BMP tests was 200 mL consisting of OFMSW(as discussed above), 30 mL of leachate, 70 mL ofmesophilic anaerobic inoculums, and 100mL of

distilled water added for dilution. The leachate blend(30 mL) used was a mix of young leachate and oldleachate. Anaerobic sludge collected from a local
wastewater treatment plant was used as inoculum. The
characteristic properties of the anaerobic inoculums
obtained from R.O. Pickard Environmental Center,
Ottawa, are also given in Table 1.

Table 1. Properties of prepared OFMSW and Inoculums

OFMSW
Inoculums

Alkalinity
mg/L
1,600
4,250

COD
mg/L
536,317
26,500

Ammonia as
N mg/L779
990

A mixture simulating the OFMSW was prepared in
the lab to be used in the experiments as a model waste
to minimize compositional variation seen in a real
OFMSW. The model waste composition was intended
to simulate kitchen waste and industrial foodprocessing waste and had a similar composition as the
Canada Food Guide, thus was representative of
Canadian kitchen waste [1]. To reduce the particle size,
the model waste was placed in a food processor for 30
s at high speed and stored at 4°C until being used.
Equal portions of NaHCO3 and KHCO3 were added toeach bottle to achieve an alkalinity concentration of
between 4,000 and 6,000 mg/L (as CaCO3). Thisbuffered the pH in the bottles between 7.8 and 8.1. The
bottles were subsequently sparged with nitrogen gas fortwo minutes to produce anaerobic conditions and thensealed. The measurement of the gas produced by thebatch BMP bottles were monitored on a daily basis
using a tube in tube manometer. Bottles were incubatedat 35 ± 1°C in a New Brunswick Scientific Controlled
Environment Incubator Shaker at 80 rpm, to keep
bacteria and substrate in suspension. The measurementof the gas produced by the batch BMP bottles weremonitored on a daily basis using a tube manometer.
Gas samples were analyzed for gas composition withthermal conductivity gas chromatograph (series 400,
Gow-Mac Instrument Co., USA). VFAs were measured
using the gas chromatographic method (5560-D,
APHA,
2005)
with
an
Agilent-6890
gas
chromatograph.
RESULTS AND DISCUSSIONS
The results from the BMP tests, phase 1, are shown
is Fig. 1, which shows the total biogas generated(average of the two duplicates) for 3 different organic
waste loading. The total biogas yields were used tocompare the performances of the reactors with thethree different organic loads of 3 g, 6 g and 9 g. The
biogas produced from the reactors with 9 g of preparedfood waste had an initial surge in gas production whichsaturated after day 21 producing nearly 1200 mL ofbiogas in total. The reactors with 6 g of OFMSW waste
on the other hand produced nearly 900 mL of gas.

903

Moisture
Content %65.4
na

TS mg/L

VS mg/LpH

305,100
20,900268,200
11,800

4.9
7.3

Based on the data for 6 g and 9 g and after deducting
the biogas contribution from the leachate andinoculum, the average gas production under these
conditions per gram of OFMSW waste was anywhere
between 142 mL and 154 mL. Based on this, thereactor with 3 g should technically have produced only
450 mL of gas. On the contrary, the reactor with 3 g ofwaste actually produced 890 mL of gas. This indicatesthat the biodegradable portion in the reactors with 6 g
and 9 g of waste was not completely utilized. The
specific biogas generation for all three loading rates
was as follows:
Batch bottle with 3 g organic load: 297 mL/g
Batch bottle with 6 g organic load: 155 mL/g
Batch bottle with 9 g organic load: 142 mL/g
This meant that in terms of performance, the lower
the organic load, the higher was the performance interms of methane generation. One possible reason forthis is that as the amount of food waste increases, themethanogenic bacteria experience a lower pH becauseof the increased acidogenesis in case of higher organic
loading and as a result do not perform to the fullpotential. Methanogenic bacteria have a lower specificgrowth rate compared to acidogenic bacteria and due tothis, the acid formation happens quicker which in turndrops the pH. This also makes available an excess
substrate for methanogenic bacteria in cases of higherorganic loads and this shock loading cannot be wellreceived by the methanogenic bacteria. This explains
why the initial rate of gas production was higher for thehigher organic loads of 9 g and 6 g bottles while the 3 greactors had a more consistent production curve. The
results observed in this study indicated that the reactors
having an organic loading rate of 3 g had the highest
efficiency in terms of biodegradation. This however, is
not to be mistaken as a standard value of organic
loading or optimal loading for all bioreactor landfills.
From this set of batch tests, it can be observed there isa limit on the amount of loading which can beeffectively utilized by the methanogenic bacteria
within the bioreactor landfill. This is more or less athreshold beyond which there is an inhibitory effectcaused by the either the additional organic load which
increases the VFA content and drops the pH orpossibly even the increase in ammonia to inhibitorylevels. The concentration of acetic acids at the
beginning, 3 weeks after the start, and at the end of test
was 280, 1160, and 140 mg/L, respectively, showing
the increase in VFA content discussed above.
COD concentrations of these bottles at the start,
after week 3 and at the end of day 60 of the BMP
bottles is presented in Fig.2. During the start-up of thereactors, the average initial COD concentration in thebottles was found to be 3,690 mg/L. After 3 weeks ofbiodegradation, the COD concentration had dropped
down to 2,770 mg/L of COD. Though the decrease is
not very high till the end of the third week, the biogas
generation curve gives an explanation as to why thedecrease is not that high. The biogas generation rate till
the end of the third week is comparatively lower (452mL of biogas for 3 g loading) which explains why
there is not much of decrease in the COD
concentration.
Ammonia concentrations of these bottles at thestart, after week 3 and at the end of day 60 of the BMP
bottles are presented in Fig.2. During the start-up of thereactors, the average initial ammonia concentration in
the bottles was found to be 405 mg/L. The averageammonia concentration in these batch bottles wasnoted to be 479 mg/L at the end of 3 weeks ofoperation. There is a significant amount of hydrolysis
of proteins taking place as a result of which theammonia concentration is comparatively higher at this.
The results from the BMP tests, phase 2, are shown
is Fig. 3, which shows the total biogas generated(average of the two duplicates) for 3 different
distribution of organic waste loading investigated inthis study. The same total organic load of 3 g ofprepared OFMSW waste was added to all reactors in
different time intervals as explained above. The test
results shown in Fig. 3 indicate that there is a distinct
advantage in a staged fed (distributed organic wasteloading) batch BMP assay with faster biodegradation
and a higher yield with increasing intervals of loading.
It was observed that the reactors with three loads of 1 g(3 X 1 g) spread over the duration of the test started
producing biogas at a rate corresponding to the total
biodegradable portion of the food waste. Immediately
after a loading, the biogas generation curve for 3 X 1 g
showed much steeper curves and by day 30 the reactor
had produced the same biogas yield (618 mL) as thereactors loaded once with 3 g (1 X 3 g) of food waste.
In calculating the biogas production for each case thebiogas contribution from the leachate and inoculum isdeducted. With every subsequent loading, the rate ofgas production had increased and by day 45, the reactor
with 3 X 1 g loading rate had yielded the same amountof gas (1400 mL) produced by the reactor with 2 X 1.5
g loading rate. In addition to producing biogas faster,
the reactor with 3 X 1 g loading also produced a higher
total biogas generation of 1530mL compared to the 1 X
3 g and 2 X 1.5 g loading which produced a total of
896 mL and 1367 mL, respectively. The reactors withthe 2 X 1.5 g loading showed similar characteristics tothe 3 X 1 g loading reactors with the exception that thebiogas production rate was very high after the second
loading. These reactors equaled the biogas yield (560mL) from the 1 X 3 g reactors on day 24; soon after thesecond loading was applied. The reactors with the 1 X
3 g single loading reactors showed a very smooth andconsistent curve with the least yield and the slowest
rate compared to the other reactors. The cumulative
biogas generation curve resembles a standard batch
BMP assay curve.
A possible explanation for this increased
performance with smaller loads spread out over time isthat the bacteria responsible for biodegradation havealready acclimatized to the food waste. In addition tothis, the acidogenic and methanogenic bacterial
consortia are at a better balance which results in more
conducive pH stability and a good VFA balance. The
methanogens would have been able to utilize thesubstrate since the methanogenic bacterial population
would be well acclimatized which is the rate limiting
step for organic biodegradation. No VFA measurement
was available for this set of test due to a malfunction of
the equipment.
CONCLUSIONSThe test results indicated that a lower the organic
loading rate of 3 g had the highest efficiency in termsof biodegradation compared to the higher organic loads
of 9 g and 6 g of OFMSW. The results observed in thisstudy also indicated that that there was a distinct
advantage in a staged fed batch BMP assay with fasterbiodegradation and a higher yield with increasing
intervals of loading.
REFERENCES[1]

Nair A, Sartaj M., Kennedy K., Coelho NMG. (2014)
Enhancing biogas production from anaerobic
biodegradation of the organic fraction of municipal
solid waste through leachate blending and recirculation.
Waste Management & Research, 2014, Vol. 32(10)939–946.

[2]

Dong S., Sartaj M. (2016). Statistical analysis andoptimization of ammonia removalfrom landfill
leachate by sequential microwave/aeration processusing factorial design and response surface
methodology, J. of Environmental Chemical
Engineering, 4, no. 1, 100-108.

[3]

Berge N.D., Reinhart, D.R., Dietz, J., Townsend, T.
(2006) In situ ammonia removal in bioreactor landfill
leachate. Waste Management, 26, 334–343.

[4]

Sanphoti N., Towprayoon S., Chaiprasert P.,
Nopharatana, A. (2006). The effects of leachate
recirculation with supplemental water addition on
methane production and waste decomposition in asimulated tropical landfill. Journal of Environmental
Management, 81(1), 27-35.

904

Average Cumulative Gas Production- Different Organic Loads

Average Cumulative Gas Production (mL)

1400
1200
1000
800
3 gm OFMSW loading600

6 gm OFMSW loading
9 gm OFMSW loading

400
200
0
0

Fig. 1

10

20

30
Days

40

50

60

Average cumulative gas production for different organic loading- BMP tests- Phase 1

Fig. 2COD (left) and Ammonia (right) at the start, after 3 weeks and completion

1800.01600.0

Cumulative gas (mL)

1400.0Organic

1200.01000.0
800.0
1g

600.0

1g Duplicate
1.5g

400.0

1.5g Duplicate
3g

200.0

3g Duplicate

0.0
0

10

20

30

40

50

DAYS

Fig. 3Cumulative gas production for distributed organic waste loading - Phase 2

905

60

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ASSESSING URBAN WATER SUPPLY SYSTEM IN NORTHEASTERNIN THAILAND: WATER QUALITY AND AUTHORITY
ORGANIZATION
Oranee Roongrueang1, Pensupa Wirikitkhul2, Jareeya Yimrattanabavorn3 and Sudjit Karuchit 4
Master student, 3,4Assistant Professor, School of Environmental Engineering, Institute of Engineering,
Suranaree Univ. of Technology, 111 University Ave., Muang District, Nakhon Ratchasima, Thailand 30000.
1,2

ABSTRACT
Providing safe water supply is one of important public health priorities. The water quality of water supply isclosely associated with human health. The aim of this study was to assess the quality of water in the urban watersupply systems and their authority organization to assess the existing performance of water supply system andtheir organization. The sampling locations were covered of 4 cities namely, Nakhon Ratchasima (Korat),
Chaiyaphum, Buriram and Surin provinces. The total of 13 samples site locations of urban water supply system
which owned by provincial and municipal waterworks authority. Water samples of each sampling site locations
were collected from water resource, storage tank and household taps water and analyzed for various parameters.
The results showed he water quality of urban water supply system had met water quality standards in parameterturbidity, TSS, TDS, Nitrate and total coliform except colour, iron due to the retention time of sedimentation
process is not the proper. And there were problem with residual chlorine at storage tank and household tap water
which were lower than standard limit and might affect with population health. There were no difference between
the performance of provincial and municipal waterworks authority. The outcome of this study can support
improvement of urban water supply system and their authority organization.
Keywords: Urban water supply system, Water quality, Authority organization, Thailand
Systems in North-Eastern Region in Thailand”. The
main goal was thoroughly evaluating the existing
urban water supply system in northeastern region ofThailand in term of the water resources, water
quality, associated health risk and engineering
aspect. The aim of this study was to assess thequality of water in the urban water supply systems
and their authority organization to assess the existing
performance of water supply system and theirorganization. The outcome of this study can support
improvement of urban water supply system and theirauthority organization.

INTRODUCTION
Access to safe water supply is a basic concern
for human health and health protection. According
to the World Health Organization (WHO), a
concentration of microorganisms, parasites orsubstances posing a possible risk to human healthhas to be prevented [1]. The water quality of watersupply is closely associated with human health. If
the water supply was contaminated by pollutants andmicroorganisms, it would affect with water qualities
and affect the health of the population. Thus, watersupply system and authority organization are obliged
to monitor water quality for human consumption.
The water qualities need to meet standard, which is
why quality of water resource and tap water of watersupply system should be assess to state their aspectof problems. Water supply in urban area ischallenged by increasing population. In this study,
the sampling locations were covered of 4 cities
namely, Nakhon Ratchasima (Korat), Chaiyaphum,
Buriram and Surin provinces. This region is covers
more than one-third of the country which is called“Khorat plateau”. The water supply consumption inthis area has been seriously concerned because of
the low level of rainfall intensity and long dry period
in this area. This study is one of four sub-projects inresearch project “Study of Management Efficiencyof Water Resources and Urban Water Supply

METHODS
Study Sites and SamplingThis study was carried out to collect water fromurban water supply system in the lower northeasternof Thailand. The area covers of 4 provinces namely
Nakorn Ratchasima (N), Chaiyaphum (C), Buriram(B) and Surin (S) provinces as shown in Fig 1. The
urban water supply system was typically consistedof the coagulation-flocculation, sedimentation,
filtration and disinfection systems. The water sourceof water treatment system was commonly takenfrom surface water. The water supply systems innortheastern Thailand are organized by twoorganizations: the provincial waterworks authority
906

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Fig. 1 Map of the study area and the sampling locations.
and the local authority. Thus, this study was focusedon urban water supply system owned by provincial
and municipal waterworks authority. The total of 13
samples site locations of urban water supply systemwere collected during dry period (January-April,2016) and rainy period (July-October, 2016). The
distribution of 13 sampling site locations was shownin Table 1.

Data Analysis
Water quality assessment
The results of water quality were checked withthe guideline of World Health Organization (WHO)for water resources quality and standard of
metropolitan waterworks authority for storage tankwater quality and household tap water quality as
shown in Table 3. The percentages of not exceed
standard water sample were calculated by using theEq. (1)

Table 1 Sampling site locations of urban watersupply system.
Authority organization

Study area

Provincial
2

Municipal
4

Total
6

Chaiyaphum (C)Buriram (B)

2
1

1
1

3
2

Surin (S)

1

1

2

Total

6

7

13

Nakorn Ratchasima (N)Number of samples thatwere not e xceed s tandard%Not exce ed stand ard  100
Total samp leStatically analysis
The results of water quality of provincial andmunicipal waterworks authorities were analyzed,
mean and standard deviation (SD) and analyzed
variance with Independent Sample Test (2-tailed).
SPSS Statistics Version 22.0

Analytical Methods
Water samples of each sampling site locations
were collected from water resource, storage tank andhousehold taps water. Water samples were analyzed
for various parameters and analytical methods asshown in Table 2.

Table 3 Water quality standard.
Parameters

Table 2 Parameters and analytical methods.
Parameters

Analytical methods [2]Parameters

Physical and Chemical quality

Turbidity

2130 B. Nephelometric Method

Nitrite, Nitrate

4500-NO2-, NO3- B. Spectrophotometric

Colour2120 D. Spectrophotometric Method

Fluoride4500-F- D. SPADNS Method

BOD

5210 B. 5-day BOD Test Method

Ammonia-N

4500-NH3 C. Titrimetric Method

Iron

3500-Fe B. Phenanthroline Method

TKN

4500-Norg Kjeldahl Method

Manganese

3500-Mn B. Persulfate Method

TDS, TSS

2540 C., D. Gravimetric Method

Hardness

2340 C. EDTA Titrimetric Method

Residual chlorine

4500-Cl B. Iodometric Method

Sulfate4500-SO42- E. Turbidimetric Method

Biological quality

Chloride4500-Cl- B. Argentometric Method

Total Coliform

Units

Water quality standards
Surface water *Tap water **Physical and Chemical quality
Turbidity
NTU
Colour
Pt-Co
≤ 300
DO
mg/L
≥4
BOD
mg/L
≤ 2
Nitrate
mg/L
≤ 5
Iron
mg/L
≤ 50
Manganese
mg/L≤ 5
Hardness
mg/L≤ 500
Chloride
mg/L
Ammonia nitrogen
mg/L
≤ 0.5
TDS
mg/L
≤ 1500Residual chlorine
mg/L
Biological quality
MPN/100 mL
Total Coliform≤ 20000* : The guideline of World Health Organization (WHO).
** : Standard of metropolitan waterworks authority.

Analytical methods [2]Physical and Chemical quality(1)9222 B. Membrane Filter Method

907

≤4
≤ 15
≤ 50
≤ 0.3
≤ 0.3
≤ 250
≤ 1500≥2
Not foundGEOMATE - Mie, Japan, Nov. 21-24, 2017

standard of metropolitan waterworks authority in
100 % of samples. However they found more than
50% of water samples that had residual chlorine lessthan standard limit and had lower concentrations
than at storage tank. These results indicated that the
distribution system might have problems aboutleakage of piping. It was supported by conclusion of
the sub-research project that found the amount ofwater loss from distribution system of water supply
system were in range of 31-47% of water production[3]. These might affect with population health.

RESULTS AND DISCUSSION
Water Quality Assessment
Surface water resource quality
The results of surface water resource qualities
were presented in Table 4. The results showed theparameters; turbidity, Iron, hardness, sulfate,chloride, TKN and ammonia-N met the guideline of
WHO and not exceed standard value in 100% of
samples. However, the parameters; colour, DO,manganese, nitrate, total coliform and BOD had
number of samples that were limit exceed standard
in range of 8-50% of samples. And all sampling site
locations had surface water resource quality thatwere limit exceed standard of BOD about 50% of
samples. These indicated that water resources ofurban water supply were polluted due to wastewater,urban area and dense population. And Nakhon
Ratchasima is the second largest cities in Thailand
and had the poorest water resources among the othersampling cities.

Table 5 The percentage of water samples that were
not exceed standard for storage tank.

ChemicalPhysicalColour

Turbidity

Iron

Manganese

TSS

TDS

NitrateResidual chlorine

Total Coliform

Study area
N
C
B
S

Table 4 The percentage of water samples that were
not exceed standard for water source.

Biological

Water quality of storage tank

50.0
100.0
100.0
25.0

91.7
100.0
100.0
100.0

41.7
100.0
75.0
100.0

66.7
88.3
100.0
75.0

100.0
100.0
100.0
100.0

100.0
100.0
100.0
100.0

100.0
100.0
100.0
100.0

58.3
50.0
50.0
50.0

100.0
100.0
100.0
100.0

Biological

Table 6 The percentage of water samples that were
not exceed standard for household tap
water.

Total Coliform

Biological
Residual chlorine

Total Coliform

N
C
B
S

NitrateAs shown in Table 5, the water quality at storagetank had values of parameters TSS, TDS, nitrate andtotal coliform that met the standard of metropolitan
waterworks authority in 100% of water samples.
And the water quality of storage tank in NakhonRatchasima also had limit exceed in parameters
colour, turbidity, iron, manganese and residual
chlorine. These results indicated that they might
have the problem with the process of water
treatment. These findings were supported byconclusion of the sub-research project that theretention time of sedimentation process is not theproper range [3].

TDS

Water quality of storage tank

TSS

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 50.0 100.0 100.0 100.0 100.0

Manganese

100.0 100.0 75.0 100.0 100.0 100.0 100.0 100.0 50.0 100.0 100.0 100.0 100.0

S

Iron

B

Chemical

91.7 100.0 100.0 83.3

Turbidity

75.0 100.0 50.0 100.0 100.0 100.0 100.0 100.0 50.0 100.0 100.0 100.0 100.0

Colour

91.7 100.0 83.3 100.0 91.7 100.0 100.0 100.0 58.3

C

Study area

N

Water quality of household tap waterPhysical

TKN

Ammonia-N

Nitrate

BOD5

Chemical
ChlorideSulfateHardness

Manganese

DO

Iron

PhysicalTurbidity

ColourStudy area

Water quality of water source

50.0
100.0
100.0
50.0

100.0
100.0
100.0
100.0

50.0
100.0
75.0
100.0

80.0
100.0
100.0
75.0

100.0
100.0
100.0
100.0

100.0
100.0
100.0
100.0

100.0
100.0
100.0
100.0

50.0
25.0
50.0
0.0

100.0
100.0
100.0
100.0

Efficiency of Water Supply System Plants
The efficiencies of water supply system were
calculated by the reduction concentration of water
qualities from water resource to storage tank. In Fig.
2, 3 and 4 shown the efficiency of urban watersupply system in range of 76.6-95.8% for colour,
47.1-82.9% for iron and 0-68.5% for manganese.
These results indicated that only Chaiyaphum urban
water supply system had manganese removal
efficiency higher than 50%, the others were lower
than 25%. To assess the distribution system bycomparison water qualities between storage tank andhousehold tap water. In Fig. 5 shown increasing of

Water quality of household taps water
As shown in Table 6, the water quality ofhousehold tab water had value of parameter turbidity,
TSS, TDS, nitrate and total coliform that met the908

GEOMATE - Mie, Japan, Nov. 21-24, 2017iron concentration from storage tank to household
tap water. These result indicated that the distribution
system of water supply system had problem. It was
supported by conclusion of the sub-research projectthat they had a potential problems of leakage inwater supply system and the maintenance ofequipment [3]. The distribution system in many
cities in Thailand are decade old. And numerous
water contaminants has been reported in many cities
in Pakistan, which could be the results of decade oldcast iron pipes and mixing of sewerage water withportable water in poorly
managed the water
distribution system [4,5].

Fig. 5The comparison of iron concentration
between storage tank and household tap
water.

The Authority Organization Comparison
To assess performance of the authority
organization by comparison the water qualities ofprovincial and municipal waterworks authority bycompared percentages of water samples that were
not exceed standard level as show in Table 7 forwater source, Table 8 for storage tank and Table 9for household tap water. The data of water resource
qualities were analyzed with Independent Sample
Test (2-tailed) and presented the p-value, mean and
SD of water qualities in Table 10. The results of pvalues shown they had no significant in allparameters between the water resource qualities ofprovincial and municipal waterworks authority
except sulfate parameter. However, they shown thatmany parameters had high SD values; these
indicated that the data were fluctuating. And when
considered of mean values, they shown thatmunicipal authority waterworks had better water
qualities than of provincial authority waterworks.

Fig. 2 Remove efficiency of urban water supply
system for colour.

Table 7 The percentage of water samples that were
not exceed standard for water sourcecompared between Province and Municipal
waterworks authority.

Fig. 3 Remove efficiency of urban water supply
system for iron.

Fig. 4 Remove efficiency of urban water supply
system for manganese.
909

Total Coliform Biological

TKN

Ammonia-N

BOD5

NitrateChemicalSulfateChloride

Hardness

Iron

ManganeseDO

PhysicalTurbidity

ColourAuthority organization

Water source

P rovincial

90.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 50.0 100.0 100.0 100.0 90.0

Municipal

92.9 100.0 64.3 100.0 92.9 100.0 100.0 100.0 57.1

92.9 100.0 100.0 92.9

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 8 The percentage of water samples that were
not exceed standard for storage tankcompared between Province and Municipal
waterworks authority.

Table 11 The conclusion of data analysis with
Independent Sample Test (2-tailed) ofstorage tank.
Parameter

Units

Colour

Turbidity

Iron

Manganese

P rovincial

66.7

100.0

75.0

75.0

100.0 100.0 100.0

50.0

100.0

Municipal

57.1

92.9

71.4

78.6

100.0 100.0 100.0

50.0

100.0

Residual chlorine

NitrateTDS

TSS

PhysicalChemicalAuthority organization

Total Coliform Biological

Storage tank
ColourPt-Co
Turbidity
NTU
pH
DO
mg/L
Iron
mg/L
Manganese
mg/L
Chloride
mg/L
TSS
mg/L
TDS
mg/L
Nitratemg/L
Residual chlorine mg/L

Parameter

Turbidity

Iron

Manganese

Total Coliform Biological

Colour70.0

90.0

100.0 100.0 100.0

40.0

100.0

Municipal

58.3

100.0

75.0

83.3

100.0 100.0 100.0

25.0

100.0

Residual chlorine

NitrateTDS

TSS

PhysicalChemicalAuthority organization

100.0

Colour
Turbidity
pH
DO
Iron
Manganese
Hardness
SulfateChloride
TSS
TDS
BOD
Nitrate
TKN

Units
Pt-Co
NTU
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L

Water source
Provincial
Municipal
Mean
136.9
12.2
6.9
4.9
1.1
0.7
40.0
0.01
50.1
29.6
288.3
3.1
0.6
0.3

SD
103.1
14.0
0.6
1.3
1.4
0.7
35.7
0.01
78.0
24.3
352.1
1.6
0.5
0.3

Mean
112.2
9.8
7.1
4.3
0.8
1.0
55.8
0.02
44.5
31.2
262.2
2.5
0.9
0.2

SD
84.1
10.5
0.3
1.7
0.5
2.4
35.9
0.02
60.0
26.6
229.5
1.2
1.6
0.3

p-value

Result

0.524
0.629
0.225
0.347
0.371
0.681
0.300
0.019
0.843
0.886
0.827
0.292
0.623
0.801

Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.

Result

0.383
0.483
0.140
0.737
0.732
0.405
0.241
0.656
0.218
0.402
0.582

Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.

Household tap water
Provincial
Municipal
Mean
12.4
0.9
7.2
5.5
0.4
0.1
29.1
17.6
152.9
0.4
0.2

SD
9.8
0.4
0.5
0.9
0.5
0.2
25.5
17.6
94.7
0.4
0.3

Mean
13.3
1.2
7.2
5.4
0.4
0.9
56.7
20.1
245.6
1.3
0.4

SD
9.2
0.7
0.4
0.9
0.6
2.6
67.5
20.4
287.4
2.1
1.0

p-value

Result

0.825
0.208
0.933
0.798
0.963
0.378
0.236
0.770
0.342
0.155
0.590

Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.
Non-sig.

The p-value, mean and SD of water qualities ofstorage tank and household tap water were analyzed
by Independent Sample Test (2-tailed) andconcluded in Table 11 and 12 respectively. The
results of p-values shown they were no difference inall parameters of the water qualities at storage tankand household tap water between provincial andmunicipal waterworks authority. However, they had
high SD values similar with water resources
qualities and indicated that the data were fluctuating.
On the other hand, when considered of mean values,
they shown that provincial authority waterworks had
better values than of municipal authority
waterworks. These results indicated that the urban
water supply system which authorized by municipal
authority waterworks produced water qualities better
than urban water supply system of provincial
authority waterworks. However, the conclusion of
the sub-research project was survey people
satisfaction by using questionnaires; it was foundthat 83.43% of people were satisfied with the qualityof water and the service of water supply authority
organization [6].

Table 10 The conclusion of data analysis with
Independent Sample Test (2-tailed) ofwater source.
Parameter

Units

ColourPt-Co
Turbidity
NTU
pH
DO
mg/L
Iron
mg/L
Manganese
mg/L
Chloride
mg/L
TSS
mg/L
TDS
mg/L
Nitratemg/L
Residual chlorine mg/L

Household tap water

80.0

p-value

Table 12 The conclusion of data analysis with
Independent Sample Test (2-tailed) ofhousehold tap water.

Table 9 The percentage of water samples that were
not exceed standard for household tap watercompared between Province and Municipal
waterworks authority.

P rovincial

Storage tank
Provincial
Municipal
Mean
SD
Mean
SD
18.8
16.8
13.8
11.5
1.6
0.7
1.4
1.0
6.8
1.1
7.3
0.6
5.8
1.1
5.6
1.5
0.4
0.4
0.4
0.6
0.3
0.4
0.9
2.4
28.2
24.3
50.9
61.2
27.6
34.0
22.4
25.5
125.2
65.8
217.3
244.0
0.7
0.6
1.1
1.8
0.5
0.6
0.7
1.2

910

GEOMATE - Mie, Japan, Nov. 21-24, 2017[2] APHA, AWWA, and WEF, Standard Methods
for the Examination of Water and Wastewater,
22nd ed. American Public Health Association,
2012.
[3] Racho P, Namgool S and Namseethan K,“Evaluation of the design and operation forwater supply system in the Northeast”, in Proc.
16th Conf. on National Environmental
Engineering Conference, 2017.
[4] Baig SA, Xu X, and Khan R, “Microbial water
quality risks to public health: potable water
assessment for a flood-affected town in northern
Pakistan”, J. of Rural and Remote Health, Vol.
12(3), Sep. 2012.
[5] Khan K, Lu Y, Khan H, Zakir S, Ihsanullah,
Khan S, Khan AA, Wei L, and Wang T, “Healthrisks associated with heavy metals in thedrinking water of Swat, northern Pakistan”, J. ofEnvironmental Sciences, Vol. 25(10), Oct.
2013, pp. 2003-2013.
[6] Racho P, Namseethan K and Namgool S,“Serviving-Oriented Evaluate of Urban Water
Supply System in North-Eastern Region”, in
Proc. 16th Conf. on National Environmental
Engineering Conference, 2017.

CONCLUSION
In conclusion, the water quality of urban watersupply system had met water quality standards inparameter turbidity, TSS, TDS, Nitrate and total
coliform except colour, iron due to the retention timeof sedimentation process is not the proper. And there
were problem with residual chlorine at storage tankand household tap water which were lower thanstandard limit and might affect with population
health. There were no difference between theperformance of provincial and municipal
waterworks authority. The outcome of this study can
support improvement of urban water supply systemand their authority organization.
ACKNOWLEDGEMENTS
This research was supported by Suranaree
University of Technology.
REFERENCES[1] WHO, Guidelines for Drinking Water Quality,
4th ed. 2011.

911

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

COMBINATION COAGULATION AND ADSORPTION PROCESSESFOR TREATING TEXTILE WASTEWATER IN HOUSEHOLDINDUSTRY
Tharika Kaenjun1, Watcharapol Wonglertarak2, Boonchai Wichitsathein3 and Jareeya Yimrattanabavorn4
Master student, 2Doctoral student, 3,4Assistant Professor, School of Environmental Engineering, Institute ofEngineering, Suranaree Univ. of Technology, 111 University Ave., Muang District, Nakhon Ratchasima,
Thailand 30000.

1

ABSTRACT
Textile wastewater is a considerable source of environmental contamination due to its strong color, high pH
and chemical oxygen demand (COD), and low biodegradability. The discharge of textile wastewater not only has
diverse aesthetic effects, but such discharge can be carcinogenic, mutagenic and generally detrimental to ourenvironment. Thus, textile wastewater should be removed completely before they are discharged into received
water. Many methods have been reported for treating textile wastewater, among which coagulation andadsorption are widely used processes due to their relatively simple operation and low cost and suitable forhousehold industry. The aim of this study was using the combination coagulation and adsorption processes totreat textile wastewater in household-scale industry. Coagulation performance and removal efficiencies in COD
and color from four varies sources of textile wastewaters were investigated. The effluent from coagulation was
treated with adsorption. The adsorption isotherm and removal efficiencies were investigated. The results showed
the combination processes had the overall COD were in range of 72.9-93.8% and color removal efficiencies
were in range of 70.6-98.5%. The results of coagulation study were found that in some cases of wastewater wereeffective in color removal but failed in COD removal, in another cases, had fail in color but were effective in
COD removal efficiencies. The results showed varies of pH had much affected on color removal efficiencies
more than COD removal efficiencies. The further experiments should be carried out to improve the combination
removal efficiencies for application as suitable for textile household industry.

Keywords: Coagulation, Adsorption, Textile wastewater, household industry
to solve this problem and usually two or threemethods have to be combination in order to achieveadequate level of color and COD removal [1]. Many
methods have been reported for treating textile
wastewater, among which coagulation andadsorption are widely used processes due to theirrelatively simple operation and low cost [3, 4] thus
they are suitable for household industry. In thisstudy the coagulation and adsorption processes wereselected as combination to treat textile wastewater
because of they were the most effective techniques
for treatment textile wastewater and its simple
design and low cost. The dyes of textile householdindustry can be classified as natural and synthetic
which are complex organic molecules having groups
such as azo, carbonyl, methane, nitro, quinoid, etc.
[5]. The aim of this study was using the combinationof coagulation and adsorption processes to treat
textile wastewater in household industry. The
performance of coagulation and adsorption
processes were investigated in term of COD andcolor removal efficiencies. The outcome of thisstudy could be applied to be used as the wastewater
treatment process for textile household industry.

INTRODUCTION
Textile wastewater is a considerable source ofenvironmental contamination due to its strong color,high pH and chemical oxygen demand (COD), andlow biodegradability. Due to toxic and carcinogenic
effects of textile wastewater on living creatures andnegative effects to photosynthetic activities ofaquatic plants, removal of coloring agent, andchemical complex compounds in wastewater appears
to be very important for human health andenvironment [1, 2]. Thus, textile wastewater should
be removed completely before they are discharged
into received water. Elimination of both dyes and
COD in the textile wastewater by conventional
wastewater treatment methods is very difficult.
Conventional treatment methods such as biological,
anaerobic microbial degradation, coagulation,
adsorption and chemical oxidation, membrane
separation process, electro-chemical are generally
unsuccessful for the removal of wastewatercontaining dyes [2]. However, all of the methods
suffered from one or another limitation. There is no
single economically and technically viable method912

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The characteristics of wastewater and analyticalmethods

MATERIALS AND METHODS
The scope of this study was carried out toinvestigate wastewater treatment of textile
household industry on the sub-district namely Pak
Thong Chai, Pak Thong Chai district, this district isin the southern part of Nakhon Ratchasima Province,
northeastern Thailand as shown in Fig.1. And it is afamous place to produce textile products especially
Thai silk. There are many groups of householdindustry. Thus, in this study divided the group of
textile household industries in two groups accordingwith dye type. The dyes can be classified as naturaland synthetic dye. The four sampling sites of textile
household industries were selected; two samplingsites have used synthetic dyes in their process
namely, Mudchada and Kayabatic. Another two
sampling sites have used natural dyes in theirprocess namely, Bandu-Yellow and Bandu-Red.
The procedure of study is presented in Fig.2.

The study was carried out to collect raw
wastewater from four sampling sites of textile
household industries were Mudchada, Kayabatic,
Bandu-Yellow and Bandu-Red. Wastewater samples
were analyzed for various parameters and analyticalmethods as shown in Table 1.
Table 1 Parameter and analytical methods for
wastewater.
Analytical methods [6]Parameters Unit
Physical and Chemical quality
pH
pH Meter
Pt-Co
Color
2120 C. Spectrophotometric Method
mg/L
COD
5220 C. Closed Reflux ,Titrimetric Method
TS

mg/L

2540 B. Total Solid Dried at 103-105๐ C

TDS

mg/L

2540 C. Total Dissolved Solid Dried at 180๐ C

TSS

mg/L

2540 D. Total Suspended Solid Dried at 180๐ C

TVS

mg/L

2540 E. Fixed and Volatile Solid Dried at 550๐ C

VSS

mg/L

2540 E. Fixed and Volatile Solid Dried at 550๐ C

VDS

mg/L

2540 E. Fixed and Volatile Solid Dried at 550๐ C

The coagulation process
The chemicals of coagulation
The coagulation-flocculation studies were carriedout using the jar test method to determine theoptimum pH range, suitable volume ofpolyaluminium chloride (Al2(OH)3Cl3 or PAC andpolymer for each sampling wastewater.
The performance of coagulation process

Fig. 1

The coagulation studies were carried out by use
the optimum pH range, volume of PAC and polymer
from chemical of coagulation study. Calculated
COD and color removal efficiencies by using Eq. (1).

The scope of this study namely Pak Thong
Chai in the southern part of Nakhon
Ratchasima Province.

%Removal Efficiency 

C0  Ce   100
C0(1)

The adsorption process
Adsorption isotherm

Fig. 2

Adsorption isotherm studies were carried out at
six different activated carbon (AC) mass (1, 2, 3, 4,
5 and 6 g.) which had Iodine was 1,015.30 mg/g. A
series of 250 mL Erlenmeyer flask containing 200
mL of treated textile wastewater with coagulation
process and required amount of AC mass weremixed using the shaker at constant agitation speed of
150 rpm. The sorbent was then separated byfiltration. The filtration treated textile wastewater
was measured color.

The procedure of study.
913

GEOMATE - Mie, Japan, Nov. 21-24, 2017

The performance of adsorption process

Table 3 The characteristic of raw textile wastewaterfrom household industry.

Batch adsorption experiments were performed asa function of varies pH (2, 4, 6, 8, 10, and 12). The
conditions of batch experiment are shown in Table 2.
A series of 250 mL Erlenmeyer flask containing 100
mL of treated textile wastewater with coagulation
process, 2 g of AC mass and required varies of pH
were mixed using the shaker at constant agitation
speed of 150 rpm. The sorbent was then separated
by filtration. The filtration treated textile wastewater
was measured color. Influent and effluent ofadsorption process were analyzed COD and color.
Calculated COD and color removal efficiencies byusing Eq. (1).
Table 2 The conditions
experiments.

of

Batch

COD(mg/L)
pH

Synthetic Dye
Mudchada Kayabatic
2,872
2,733
6.1
9.7

Natural Dye
BanDu -Yellow BanDu -Red
84,614
10,7088.9
4.1

Color (Pt-Co)
TS(mg/L)
TSS(mg/L)
TDS(mg/L)
TVS(mg/L)
VSS(mg/L)
VDS(mg/L)
VS/TS
TDS/TS
VDS/TS543
11,827
187
11,640
2,301
117
2,184
0.1946
0.98420.184751,86772,043
10,58061,46347,257
9,737
37,5200.65590.85310.5208Parameter

9,671
2,928
97
2,831
1,257
143
1,113
0.42920.96700.3803

5,650
6,733
351
6,382
6,671
776
5,896
0.99080.94790.8756

adsorption

2

3

2.5

3

Temperature (oC)

25

25

25

25

Bandu-Red

Bandu-Yellow

Mass (g)FactorMudchada

Kayabatic

pH

Volume of MB solution (mL)

100

100

100

100

Contact time (hour)

4,24

4,24

4,24

4,24

Agitation speed (rpm)

150

150

150

150

pH

Fig. 3

2,4,6,8,10,12

The solid fraction of raw textile wastewater.

The coagulation process

RESULTS AND DISCUSSION

The chemicals of coagulation

Characteristics of Textile wastewater

The results of coagulation studies were carriedout to determine the chemicals and optimum pH for
coagulation process. They were found the optimum
pH were in range of 9 and 6 for synthetic dye groupand for natural dye group respectively as shown in
Fig 4 and the volume of PAC and polymer were 5mL (Dosages PAC is 50,000 mg/L) and 0.4 mL(Dosages Polymer is 1,000 mg/L) for synthetic dyegroup and were 9 mL and 0.4 mL for natural dyegroup respectively as shown in Fig.5 and 6.

As shown in Table 3, The results of raw
wastewater characteristics were in wide range of
COD from 2,872-84,624 mg/L, pH from 4.1-9.7 andcolor from 543-19,000 Pt-Co. The ratio of TDS/TSof all wastewater samples were in range of 0.85310.9842. These results indicated that raw wastewatercontained dissolved solid more than 80%. And in
Fig.3 showed the raw wastewater of synthetic dyegroup, Mudchada and Kayabatic had the ratio
FDS/TS higher than the natural dye group of BanduYellow and Bandu-Red. On the other hand, thenatural dye group had the VDS/TS volatile dissolved
solid higher than synthetic dye group. These
indicated that raw wastewater of natural dye
contains mainly organic substances which were inform of dissolved solids. The natural dye extracted
from many kind of plants which are organic matter.
Whereas the synthetic dye group contained mainlycomplex organic molecules having group such asazo, carbonyl, methane, nitro, quinoid, etc. [5].
These results similar with many researches [7] thatreported wastewater from textile industries contains
low biodegradability and had different types of dyes,
which because of high molecular weight andcomplex structures.

Fig. 4914

The Results of coagulation studies todetermine the optimum pH

GEOMATE - Mie, Japan, Nov. 21-24, 2017of Bandu-Red. The mechanism of coagulation
applied to decolorize wastewater is still not clear,color removal by coagulation is found in some cases
very effective, in another cases however, has fail at
all [8].
The efficiency of the coagulationflocculation method depends on the raw wastewater
characteristics, pH and temperature of the solution,
the type and dosage of coagulants, and the intensityand duration of mixing [9].
Fig. 5

Table 5 The results of COD and color removal
efficiencies of coagulation process

The Results of coagulation studies todetermine the optimum PAC.

Before CoagulationFlocculation

SampleFig. 6After CoagulationFlocculation% Removal

pH

Color
(Pt-Co)COD(mg/L)pH

Color(Pt-Co)COD(mg/L)Color

COD

Mudchada
Kayabatic
Bandu-Yellow
Bandu-Red

9.0
9.0
6.0
6.1

473
9,778
19,000
4,507

7,067
7,533
34,667
1,200

6.9
5.1
6.9
4.2

333
3,847
11,222
5,248

3,755
7,076
31,333
667

29.58
60.66
40.94
0.00

46.86
6.06
9.62
44.44

Fig. 7

The results of COD and color removal
efficiency of coagulation process

The Results of coagulation studies todetermine the optimum polymer.

Table 4 The conclusion of optimum conditions forcoagulation process.
SampleOptimum Condition
PAC (mL)a Polymer (mL)b

Mudchada
5
Kayabatic
5
Bandu-Yellow
9
Natural Dye
Bandu-Red9aDosages PAC is 50,000 mg/Lb
Dosages Polymer is 1,000 mg/L
Synthetic Dye

0.4
0.4
0.4
0.4

pH
9
9
6
6

The adsorption process
Adsorption isotherm
Langmuir and Freundlich isotherms are widely
recognized and have been successfully applied todefining many adsorption equilibriums and evaluateadsorption equilibrium of dyes from effluent of
coagulation. Therefore, dye adsorption data wereanalyzed by Langmuir and Freundlich Eq. (2) and(3), respectively;

3.2.2 The performance of coagulation process
The results of optimum conditions forcoagulation process as summarized in Table 4 werecarried out to treated raw wastewater from four
sampling sites for measuring the performance of
coagulation process. The wastewater samples before
and after treated by coagulation process wereanalyzed COD and color and calculated the removal
efficiencies. The results of COD and color removal
efficiencies of coagulation process were presented inTable 5 and Fig.7. They showed Mudchada andBandu-Red had a same range of COD removal
efficiencies were 44.44 and 46.86% respectively inthe other hand, Kayabatic and Bandu-Yellow had
similar range of COD removal efficiencies only 6.06
and 9.62 %. Whereas, the color removal efficiencies
Kayabatic and Bandu-Yellow higher than Mudchadaand Bandu-Red. And coagulation process showednone of color removal efficiencies from wastewater

Ce
X



Ce
Xm



1
KX m

(2)

1
log Ce(3)nWhere K and Xm are Langmuir constants (L mg-1)
and maximum monolayer adsorption capacity (mgg-1), respectively and Freundlich coefficients n and
Kf are related to adsorption intensity and adsorption
capacity, respectively. Isotherm coefficients of bothmodels are given in Table 6. They were shown
Freundlich isotherm are much closer to experimentallog X  log K f 

915

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Table 7 The selected performance of COD andcolor removal efficiencies of adsorption
process

points than Langmuir isotherm. The coefficients ofdetermination, R2 of Freundlich isotherm were in
range of 0.8583-0.9973 and R2 of Langmuir
isotherms were in range of 0.6791-0.9940.
Madchada had the highest adsorption capacity 1.39
Pt-Co/g.

Before Adsorption
SampleTable 6 The constants of Langmuir and Freundlich
isotherms for adsorption process.

After Adsorption

Color(Pt-Co)COD(mg/L)pH

Color(Pt-Co)COD(mg/L)Color

COD

Mudchada

8.0

67

4,337

8.4

10

333

85.00

92.32

Kayabatic

8.0

2,730

9,131

8.9

1,529

280

44.00

96.93

Bandu-Yellow

2.1

3,218

24,5333.2

803

22,933

75.04

6.52

Bandu-Red

2.0

2,621

933

4.1

1,663

667

36.54

28.57

Before Adsorption

SampleMudchada
Kayabatic
Bandu-Yellow
Bandu-Red

Langmuir constantR2
qmax (Pt-Co/g) KL (L/g)
6.57 x 10-3 0.9994
78.125-31.95-212.77294.11-3.77 x 10

-40.9980-8.10 x 10-5 0.6791
6.78 x 10-4 0.9356

2.92 x 10

0.21
3.39 x 10-22 0.16
0.038
0.47

After Adsorption% Removal

TheSample
performance of combination coagulation and
Color
COD
Color
COD
pH processes
pH
Color
COD
adsorption(Pt-Co)(mg/l)(Pt-Co)(mg/l)

Freundlich constantR2
Kf (Pt-Co/g) n
1.39
1.49 0.9973-14% Removal

pH

Mudchada

8.010

66.67

4,337.07

8.45

10.00

333.30

85.00

92.32

Kayabatic

2,730.00 9,130.67
8.88
1,528.80 280.00
96.93
The 8.013
conclusionsof CODand color 44.00
removalBandu-Yellow 2.080 3,217.78 24,533.33 3.24
803.3022,933.33 75.04
6.52
efficiencies
forcombination
coagulation
andBandu-Red
2.002 2,621.11 933.33
4.13
1,663.33 666.67
36.54
28.57
adsorption processes are presented in Table 8. The
overall removal efficiencies were calculated by
selection optimum condition for coagulation andadsorption process under the characteristics ofeffluent and standard for textile effluent. The results
showed the combination processes had the overall
COD were in range of 72.9-93.8% and color
removal efficiencies were in range of 70.6-98.5%.
Although the performance of the combination
processes obtained high removal efficiencies but the
COD concentrations did not meet the standard forindustry effluent. Our studies are going on to
improve the removal efficiencies of this combination
system such as using the other type of coagulants
and optimum conditions for adsorption process.

0.93540.85830.87703.3.2 The performance of adsorption process
Batch adsorption experiments were performed
as a function of varies pH (2, 4, 6, 8, 10, and 12) in
effluents after coagulation processes. Influent andeffluent of adsorption process were analyzed COD
and color. The Calculations of COD and color
removal efficiencies were summarized in Fig.8 and
9 respectively. The results showed varies of pH had
much affected on color removal efficiencies morethan COD removal efficiencies. In table 7, theoptimum condition and removal efficiencies foradsorption processes were selected and concluded
the performance of adsorption processes byconsideration of effluent characteristics and standard.

Table 8 The conclusion of overall COD and color
removal efficiencies for combination
coagulation and adsorption processes
Influent
SamplepH
Mudchada
Kayabatic
Bandu-Yellow
Bandu-Red

6.1
9.7
8.9
4.1

COD
(mg/L)
2,872
2,733
84,614
10,708Effluent

Color(Pt-Co)

pH

543
9,671
51,867
5,650

8.4
8.9
3.2
4.1

COD
(mg/L)
333280
22,933667%Over allremoval efficiency

Color(Pt-Co)

COD Color

10
1,529
803
1,663

88.4
89.8
72.9
93.8

98.2
84.2
98.5
70.6

CONCLUSION

Fig.8

The performance of adsorption process in
COD removal.

Fig. 9The performance of adsorption process incolor removal.

In conclusion, the results showed the
combination processes had the overall COD were in
range of 72.9-93.8% and color removal efficiencies
were in range of 70.6-98.5%. The results ofcoagulation study were found that in some cases ofwastewater from Mudchada and Bandu-Yellow wereeffective in color removal but failed in COD
removal, in another cases, wastewater from
Kayabatic and Bandu-Red, had fail in color but wereeffective in COD removal efficiencies. The results
showed varies of pH had much affected on color
removal efficiencies more than COD removal
efficiencies. The further experiments should be
carried out to improve the combination removal
efficiencies for application as suitable for textile
household industry.
916

SampleMudchada
Kayabatic
Bandu-Yellow
Bandu-Red

GEOMATE - Mie, Japan, Nov. 21-24, 2017

ACKNOWLEDGEMENTS
This research was supported by Suranaree
University of Technology.
REFERENCES[1] C. Deepa, “A review of the textile industries
wastewater treatment methodologies”, J. of
Scientific & Engineering Research, Vol. 7, Jan.
2016, pp. 392-403.
[2] S.C.R. Santos, V.J.P. Vilar, R.A.R. Boaventura,“Waste metal hydroxide sludge as adsorbent fora reactive dye.”, J. of Hazard. Master, Vol. 153,
2008, pp. 999-1008.
[3] O. Gercel. A. Ozcan. A.S. Ozan, H.F. Gercel,“Preparation of activated carbon from arenewable bio-plant of Euphorbia rigida by
H2SO4 activation and its adsorption behavior inaqueous solutions.”, J. of Applied Surface
Science, Vol. 253, Mar. 2007, pp. 4843-4852.
[4] T. Chen, B.Y. Gao, Q.Y. Yue, “Effect of dosing
method and pH on color removal performanceand floc aggregation of polyferric chloridepolyamine dual coagulation in synthetic dyeing
wastewater treatment”, J. of Colloids andSurfaces A: Physicochemical and Engineering
Aspects, Vol. 355, Feb. 2010, pp. 121-129.
[5] F. Aci, M. Nebioglu, M. Arslan, M. Imamoglu,
M. Zengin, M. Kucukislamoglu, “Preparation ofactivated carbon from sugar beet molasses andadsorption of methylene blue”, J. of Fresenius
Environmental Bulletin, Vol. 17, 2008, pp. 9971001.
[6] APHA, AWWA, and WEF, Standard Methods
for the Examination of Water and Wastewater,
22st ed. American Public Health Association,
2012.
[7] A.K. Verma, R.R. Dash, P. Bhunia, “A review
onchemicalcoagulation/flocculation
technologies for removal of colour from textile
wastewaters”, J. of Environmental Management, Vol. 93, Jan. 2012, pp. 154-168.
[8] M. Janeczko, S. Gaydarazhiev, “Removal ofdyes from textile effluents by chemical
coagulation”, in Proc 23rd Int. Conf. on
International
MineralProcessing
Congress,2006, pp. 2163-2167.
[9] P.W. Wong, T.T. Teng, N.A.R. Nik Norulaini,“Efficiency of the Coagulation-Flocculation
Method for the Treatment of Dye Mixtures
Containing Disperse and Reactive Dye”, J. of
Water Quality Research Journal of Canada, Vol.
42, 2007, pp. 54-62.

917

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A COMPREHENSIVE METHOD OF EROISON RESISTANCE AND
GROWTH PROMOTION FOR PISHA SANDSTONE
Zhishui Liang1,2, Zhiren Wu3, Caiqian Yang1, Mohammad Noori1, Xiangyang Wu3, Hanbin Ge2, Wenyi
Yao4 and Peiqing Xiao4
1
School of Civil Engineering, Southeast University, Nanjing 210096, China, 2 Department of Civil
Engineering, Meijo University, Nagoya, 468-8502, Japan, 3 School of the Environment and Safety
Engineering, Jiangsu University, Zhenjiang 212013 China, 4 Key Laboratory of Soil and Water Loess
Process and Control on Loess Plateau of MWR, Yellow River Institute of Hydraulic Research, 45 ShunheRoad, Zhengzhou 450003, China
ABSTRACT
Pisha sandstone is a special kind of soft rock that is severely eroded by wind, rainfall and gravity force, andthe surface land is degraded resulted from the excessive human activities, and the vegetation coverage rate in thisarea is extremely low. In order to control it and develop new methods, the material components, nutrient content
and the shear strength was studied and the field experiment used the new comprehensive method based on a kindof hydrophilic polyurethane (W-OH) was carried out. The results shows that in Pisha sandstone, the main minerals
are quartz, feldspar, plagioclase, montmorillonite, illite, kaolinite, montmorillonite is the main cementitious
material but is easy to expand when meets water. The nutrient content is low, organic matter, total nitrogen, total
phosphorus, total potassium and available phosphorus belong to the six-level, available nitrogen is five-level andavailable potassium is four-level. In the field experiment, vegetation coverage rate of the control model was morethan 95% after 4 months, and there was almost no shallow trench. The amount of sediment erosion was reducedby more than 90%, indicating that the effect of erosion prevention and promoting vegetation growth is significant.
A demonstration project of 0.2 km2 had been carried out in Odors in 2015 in this control model and a good result
has been received, and the method has been widely accepted by local people and soil conservation bureau.
Keywords: Field experiment; Growth promotion; Mineral component; Sediment yield; Shear strength; Water andsoil conservation[13]. About half of the coarse sediment is deposited
so that the lower reaches of the Yellow River has
gained the reputation as the “Hanging River” [14].
Consequently, the Pisha sandstone area is called themost severe soil erosion region in both Loess Plateau
and in the world [4], [5], [15].
From 1950s, the control measures for water andsoil conservation in Pisha sandstone areas are mainly
biological and engineering measures [16]. Amongthem, the biological measures are mostly applied,such as forest shelter belt, windbreak and sandfixation forest, slope protection plants, seabuckthorn
flexible dam and so on [12], [15]. Engineering
measures mainly include slope engineering, such as
Terrance, level trench, scale-hole, intercepting ditch,protection engineering of gully head and channel
engineering [7]. Nevertheless, there are some
limitations for these measures and they cannot
achieve the comprehensive goals of soil solidification,
erosion resistance, vegetation growth promotion, andsteep slope governance [14].
Recently, Pisha sandstone solidification andimprovement combined with vegetation growth
becomes a trend to protect and utilize this resource aswell as controlling its adverse effects on the

INTRODUCTION
Pisha sandstone is formed in Jurassic, Triassic andCretaceous period [1]. It is widely distributed in an
adjacent region close to Shanxi, Shaanxi and Inner
Mongolia autonomous region in the Yellow Riverbasin and Ordos Plateau (Fig. 1) [2], [3]. It is
composed of a thick layer sandstone, arenaceous
shale, and mudstone [4], [5]. The total area that Pisha
sandstone underlies is approximately 16,700 km2 [6],[7]. The Pisha sandstone has a low degree of
diagenesis, poor bonded mechanism, and low
compressive strength. As a result, it is extremely hardwhen it is dry but rapidly disintegrates when facedwith water [7]-[9]. Due to the special properties of
Pisha sandstone, in the condition of rainfalls, erosion
occurs frequently in gullies and the erosion rate isconsiderably large [10]. The soil erosion modulus canreach about 3,000 ~ 4,000 t/ (a·km2) on average
according to the available statistical data. Coarse
sediment (particle size＞0.05 mm) [11] derived fromthe Pisha sandstone area is the primary sediment [12]source of coarse sediment into the reaches of the
Yellow River and accounts for 71.1% of the totalcoarse sediment yield (0.301 billion tons per year)918

GEOMATE - Mie, Japan, Nov. 21-24, 2017environment [17]. Wu, et al. [18] studied a kind ofhydrophilic polyurethane as a sand fixation agent. Su[19] analyzed the influence of EN-1 on engineering
mechanical characteristics and simulated slope
resistance to scour of Pisha sandstone weathered soil.
Han et al., [20] proposed to compound soil with Pisha
sandstone and aeolian sandy soil to improve the water
retention characteristics Li et al., [21] used Pisha
sandstone via alkali activation process to produce a
new raw structural material.
In order to develop a new efficient method toprotect Pisha sandstone erosion, a novel hydrophilic
polyurethane composite material (W-OH) was
introduced [22] and based on it a new dual stereo
configuration control model combined vegetation
measures was proposed in the first time to protect
Pisha sandstone. Actually, W-OH has been used onsand fixation to control desertification and to achieve
ecological restoration [23]. In this paper thecharacteristics of Pisha sandstone and the reason for
erosion were studied, and then the field experimentbased on the comprehensive method was also carriedout and the effect was evaluated in the following fourmonths.

Fig. 1 Distribution of Pisha sandstone,
experimental plot.

heavy metal ion and has no harmful effect onvegetation and animals [23].
Methods
The mineral components were analyzed by X-ray
method based on "transfer target polycrystalline Xray diffraction method General" (JY / T 009-1996) by
X-ray diffractometer (XRD-7000S, produced in
Shimadzu Corporation).
Field experiment
In order to study the effect of the novel material
and technology, the field experiment was conducted.
The experimental field plot was selected in the middleof Erlaohu Gou in Inner Mongolia Ordos(110°36′2.74″ E and 39°47′38.79″ N, Fig. 1) and wasconstructed and monitored from May to October 2014.
The topography in this area belongs to the transitionalzone of Loess plateau and the Ordos plateau andtypical bare Pisha sandstone area. The climate is arid
and semi-arid temperate continental monsoon climate
with cold winter, hot summer and there is more windand sand in winter and spring. According to themeteorological data of Jungar Banner, the averageannual rainfall is 400 mm, but the inter-annual change
is large and the distribution is extremely uneven in
one year (The total rainfall reached 250.2 mm in2014). The largest months of rainfall are often
concentrated from July to September, accounting for
70~80% of one year. Moreover, short-term heavy
rainfall often occurs and the highest intensity rainfall
can reach 80 mm per mouth. However, because of theharsh climate and sterile soil, the overall vegetation
coverage rate is less than 30%.
Experimental design: The experimental slope in
Erlaohu Gou with the height of approximately 43.5 m,
vertical height of 29.9 m, and average gradient of
44.5° was chosen. According to the changes of slopes,
the slope area was divided into three regions:consolidation & waterproof area, consolidation &growth promotion area and consolidation & green
area. Moreover, a meteorological station, a water &sediment monitoring stations and a rainfall station
were built to observed rainfall intensity, temperature,humidity, wind, sediments and other parameters.
In the top of slope, stereo configuration with trees,
bushes, grass was established, and Chinese pine wereplanted, water drainage ditches were dug, and acellar/tank was built to collect rainfall to make fulluse of. For the consolidation & waterproof area, theslope exceeded 60° and 8~10% W-OH solution was
sprayed on the surface. However, in consolidation &growth promotion area, the slope was about 30~60°,
the spayed concentration of W-OH was about 4~5%,
bushes and grass were planted and the micro
irrigation systems were constructed to provide water
for the vegetation. In respect to consolidation green

is

MATERIALS AND METHODS
Materials
Pisha sandstone was taken from the Erlaohu Gou
in Ordos, Inner Mongolia Autonomous Region,
China and it belongs to bare Pisha sandstone area.
Horizontal stratified sampling method combining
artificial and mechanical excavation [24] was used to
get the samples with a bulk density ranging from 1.36
~ 1.58 g/cm3, and a water content from 7.9 ~ 21.1%.
The liquid limit (WL) is 32.2%, plasticity (IP) is 10.6,
specific gravity (Gs) is 2.65, and the optimum watercontent (Wop) is 17%.
W-OH: a kind of hydrophilic polyurethanecomposite (produced by Toho Chemical Industry Co.
Ltd,). This plyometric material doesn’t contain any
919

GEOMATE - Mie, Japan, Nov. 21-24, 2017with feldspar and a bit amount of calcium carbonate.
Montmorillonite (accounting for more than 15% for
red Pisha sandstone, and approximately 10% forwhite one) is one kind of the common clay minerals
and is the most important cementitious material in thematrix of Pisha sandstone. However, when it absorbs
water, the volume will expanse drastically, and the
maximum volume expansion rate can be achieved
approximately 400%, this is the main source of
expansion in Pisha sandstone. Montmorillonite will
gradually soften with producing enormous pressure
and lose the bonding capacity after it absorbs water,
resulting in destroy of the structure. Moreover, thecrystal of montmorillonite is small and scaly, and it ishydrophilic, therefore, it is easy to be entrained bywater, which is an important reason for the erosion of
Pisha sandstone. Kaolinite, the product of feldspar
and other silicate minerals, is an aqueous aluminosilicate. The properties of kaolinite are high water
absorbability and strong plasticity, while once
exposed to water, it will soften, inflate and lose thebonding capacity rapidly. Moreover, montmorillonite
and kaolinite and other expansion of clay minerals
will be easy to be weathered under certain conditions
and decomposed in to silica and alumina in a longterm in hot and humid conditions.

area with less than 30°slope, trees, bushes, and grasswere planted. Last, at the bottom of the gully, two
shunt barrels and collecting barrels were installed tocollect rainfall erosion sediment and runoff. The
barrels’ height and diameter was 1 m, respectively.
Between the shunt barrels and collecting barrels, nine
tap holes with the same size were set up and the one
in the middle was jointed with the collecting barrels
through honeycomb dust.
RESULTS AND DISCUSSION
Mineral components in Pisha sandstone
From Table 1 it can be seen that the main minerals
in Pisha sandstone includes quartz, feldspar,
plagioclase, montmorillonite, illite, kaolinite, calcite,
dolomite and hematite. In which, quartz, feldspar,
plagioclase and hematite are primary minerals,
accounting for about 70% ~80%, whilemontmorillonite, kaolinite, calcite and dolomite aresecondary minerals from weathered primaryminerals, therefore, Pisha sandstone is a kind ofsandstone that has a low degree of rock diagenesis.
The characteristic of quartz is high strength,
hardness and good performance for water resistance.
It forms a strong skeleton of Pisha sandstone together
Table 1
No.

Mineral components in Pisha sandstone
Quartz
38-43
28
23-28
25-30
35-40

1-1
1-2
1-3
1-4
1-5

Plagioclase
25
30-35
20-25
10
25

Feldspar
20
15
20-25
10-15
15

Mineral contents /%Montmorillonite
Illite
5-10
1
15-20
1
10-15
2
20-25
3
10-15
1

Kaolinite
2
2
3
4
2

Dolomite
11
1
1
1

Calcite
2
1
10
15-20
5

Hematite
1
1-

Available
phosphorus(mg/kg)
0.31
0.10
0.20
＜3.0
Six-level
0.91
0.69
0.77
＜3.0
Six-level

Available
potassium(mg/kg)
78.5
55.2
62.8
40-85
Four-level
52.6
27.3
44.8
40-85
Four-level

Nutrient content
Table 2

Surface nutrient content of Pisha sandstone

Color

pH

Maximum
Minimum
Average
Range
Grade
MaximumRed
Minimum
Average
Range
Grade

10.04
8.91
9.51
＞8.5
Six-level
9.15
9.00
9.08
＞8.5
Six-level

White

Organic
matter
(%)
0.78
0.17
0.44
＜0.60
Six-level
0.20
0.15
0.17
＜0.60
Six-level

Total
nitrogen
(%)
0.054
0.017
0.026
＜0.05
Six-level
0.036
0.020
0.030
＜0.05
Six-level

Total
phosphorus(%)
9.5×10-6
3.5×10-6
6.6×10-6＜0.040Six-level
1.9×10-5
5.9×10-6
1.2×10-5＜0.040Six-level

It can be seen from Table 2 that both the red andwhite Pisha sandstone, the pH ranges from 8.91
to10.04 and thus it is alkaline. The content of organic
matter is approximately 0.15%-0.78%. The contents
of total nitrogen, total phosphorus, total potassium,
available nitrogen, available phosphorus andavailable potassium are in the range of 0.017%0.054%,
3.5×10-6%-1.9×10-5%,
9.07×10-5%2.75×10-4%, 0.10-0.91 mg/kg, 39.6-53.8 mg/kg andTotal
potassium(%)
2.75×10-4
9.07×10-5
2.04×10-4＜0.60
Six-level
2.42×10-4
9.22×10-5
1.67×10-5＜0.60
Six-level

Available
nitrogen(mg/kg)
53.8
42.4
47.9
30-60
Five-level
50.9
48.1
49.5
30-60
Five-level27.3-80.8 mg/kg. According to the six-levelclassification of soil nutrient content grading table inour nation, pH, organic matter, total nitrogen, total
phosphorus, total potassium and available
phosphorus belong to the six-level, available nitrogenis five-level and available potassium is four-level,
indicating that the overall nutrient content in Pisha
sandstone is extremely low, resulting in difficult
growth of vegetation.
920

GEOMATE - Mie, Japan, Nov. 21-24, 2017change (Fig. 3a). The surface in consolidation green
area had no obvious gully, and there was no Pisha
sandstone particles in different barrels. However, inthe control area, some shallow ridges appeared,
indicating that the consolidation layer had a certain
effect of anti-erosion.
Twenty days later, the surface in consolidation &Fig. 2 The SEM images of red Pisha sandstone (a)waterproof area did not change and the consolidation
Original Pisha sandstone particles; (b) Solidification
layer remained completely, however, in thelayer on Pisha sandstone by spraying W-OH solution
consolidation & vegetation promotion area a few
As can be observed from Fig. 2, the original
small cracks appeared in some unsmooth places. As
sandstone particles are discrete in SEM and thefor the consolidation green area, the seeds began toadhesion between particles is poor, so it is not stablesprout, seabuckthorn and Boston ivy began to growand easy to become collapsible when meets water or
new leaves, and green could be seen in some parts.
wind. However, when W-OH solution was sprayed on
Sediments of Pisha sandstone particles were found in
the surface, a consolidation layer is formed and thedifference barrels and it demonstrated that with theparticles are bonded together tightly. Thereby, theincrease of rainfall and rainfall intensity, the sedimentintegrity is improved and the porosity is decreased
yield showed a trend of increase in both experimental
significantly. Thereby, the Pisha sandstone particles
and control areas (Table 3). When the rainfall reachedcannot be easily destroyed in the condition of water,
41.2 mm/h, the sediment yield of control area reachedwind erosion or sunshine conditions.
1895.7 kg and the average unit loss was 11.8 kg/m2.
The results of field experiment
However, in the experimental area, the sediment yield
was just 11.9 kg and the unit loss was 0.074 kg/m2,
The results and effects had been observed andthe decreased rate was more than 99%. The results
studied in the following four months.
indicated that the consolidation layer had a significant
Sediment yield: after finishing constructing theeffect on improving the performance of water,
experimental and control areas, on the second day it
gravity, and wind erosion resistance of Pisharained and lasted for 15 hours. The field observation
sandstone slopes. In addition, the sediment yield also
showed that the consolidation & waterproof area andhad a direct relationship with the rainfall erosion
the consolidation & growth promotion area did notforce and the proportion of vegetation coverage.
Table 3 Results in experimental and control area during 7~8 month.
Date
7.1
7.22
7.28
8.2
8.12
8.22
16.4
8.6
23.2
35.6
20.6
34.4
Rainfall （mm）
Rainfall intensity I30(mm/h)
26
4.4
15.6
41.2
26.8
20
Rainfall erosion force (MJ·mm/(ha·h))
94.8
9.43
77.2
373.3
131
133.3
Sediment yield in experimental area (kg)
8.6
0
1.8
11.9
0..4
1.6
Sediment yield in control area (kg)
216.1
42
27.3
1895.752.1
18.7
Reduced rate of sediment yield (%)
96.0
100
93.4
99.4
99.2
91.4
On the other hand, the consolidation layer in the
consolidation & waterproof area stayed intact with acertain thickness, but in some places, a few cracks
began to appear with the time going on (Fig. 3a). This
indicated that under the effect of water and gravity
erosion force, some changes on Pisha sandstone
surface have taken place, leading to a minor damage
in some places where the material was not sprayeduniformly. As time went by, the quantity of thegrooves increased gradually, the width and depth also
increased. By the end of August, there were 10
grooves in control area, 6 cm in width and 10~15 cm
in depth on average. Some of them appeared acrossthe entire growth promotion area. The monitoring
results showed that the grooves appeared from theedge of the control area, of which depth increased
with the rainfall intensity, and moved towards to the
middle gradually, resulting in destruction or collapseof the entire slope. These were also one of the major
forms of water erosion for slope.

Fig. 3 Comparison of experimental and control area.
(a) a few cracks in consolidation and water proof area,(b) comparison with two plots in September, 2014
In the experimental area, where the amount ofsprayed solution was small, the vegetation coverage
was large even though the rainfall was heavy, but theslope surface showed a small erosion at the first time.
However, as the vegetation coverage rate increased,
921

GEOMATE - Mie, Japan, Nov. 21-24, 2017

the gullies disappeared and vegetation played an
important role on preventing weathered Pisha
sandstone from further erosion.
Vegetation coverage rate: From Fig. 4 it could beseen that vegetation in growth promotion and green
area grew fast and the vegetation coverage rate
gradually increased. Three months later the rate
reached 95%, and the height run up to 50~60 cm (Fig.
4b). However, the rate of the vegetation coverage wasvery slowly in the control area. It only occupied 8%with a height of 10 cm in average. Therefore, it was
obvious that with the increase of the vegetation
coverage rate, the surface roughness and permeabilityof Pisha sandstone could be enhanced to protect Pisha
sandstone from water and wind erosion. This also
indicated that material measure by W-OH combinedwith vegetation could have a significant effect on
preventing Pisha sandstone from water, wind, andgravity erosion.
Height in EA
Height in CA

Height (cm)50
40

nitrogen, total phosphorus, total potassium andavailable phosphorus belong to the six-level,available nitrogen is five-level and available
potassium is four-level, indicating that the overall
nutrient content in Pisha sandstone is extremely low,
resulting in difficult growth of vegetation. The
experimental area was divided into three sections
according to the slope gradients and vegetation
coverage, consolidation & waterproof area,
consolidation & growth promotion area andconsolidation & green area. The new control method
combining W-OH with vegetation was adopted. Fourmonths later, the vegetation coverage rate reachedmore than 95%, and almost no shallow grooves wereformed in the experimental area, but several deep
grooves appeared and vegetation coverage was stillless than 30% in the control area. The sediment yieldin experimental area had been reduced by more than
95% compared with that in the control area. This newcontrol method could reach the comprehensive
efficiency of Pisha sandstone conservation both inwater erosion resistance and ecological restoration.
These results also indicated that combining materials
with vegetation measures could be used as anefficient comprehensive method to protect water andsoil from loss and erosion in the Pisha sandstone area.

(a)

30
20
10
0

Vegetation coverage (%)

0

ACKNOWLEDGEMENTS

20 40 60 80 100 120
Day (d)This work is funded by the State Key Research
Development Program of China (Grant No.
2017YFC0504505).

Vegatation coverage in EA (b)Vegatation coverage in CA

120
100
80
60
40
20
0

REFERENCES

0[1] Zhen, Q, Zheng, J, He, H, Han, F, & Zhang, X.
Effects of pisha sandstone content on solutetransport in a sandy soil. Chemosphere, Vol. 144,
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[2] Ma, W & Zhang X. Effect of Pisha sandstone onwater infiltration of different soils on the Chinese
Loess Plateau. Journal of Arid Land, Vol. 8, No.
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[3] Ni, H, Zhang, L, Zhang, D, & Wu, X. Weatheringof pisha-sandstones in the wind-water erosion
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[4] Chen, W. The Pisha sandstone in Yellow Riverbasin- non farming land and watch as picture
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20 40 60 80 100 120
Day (d)Fig. 4 Vegetation coverage and height inexperimental and control area from May to
September 2014
CONCLUSION
In order to develop the new comprehensive method
to control Pisha sandstone erosion, the material
components, nutrient content and the shear strength
was studied and the field experiment based on a kindof hydrophilic polyurethane (W-OH) together withvegetation measure was carried out. The resultsshows that in Pisha sandstone, the main minerals are
Quartz, feldspar, plagioclase, montmorillonite, illite,
and kaolinite. Quartz, feldspar, plagioclase andhematite are primary minerals, and montmorillonite
is the main cementitious material but it is easy to
expand when meets water, leading the structuraldestroy of Pisha sandstone. organic matter, total
922

GEOMATE - Mie, Japan, Nov. 21-24, 2017[17] Liang Z, Wu Z, Yang C, Yao, W & Leng, Y.
Mechanism of erosion resistance and vegetation
promotion by W-OH in Pisha sandstone. Journalof hydraulic engineering, Vol. 47, No. 9, 2016,
pp.1160-1166. (in Chinese).
[18] Wu, Z, Gao, W, Wu, Z, Iwashita, K & Yang, C.
Synthesis and characterization of a novel
chemical sand-fixing material of hydrophilic
polyurethane. Journal of the Society of Material
Science Japan, Vol. 60, No. 7, 2011, pp.674-679.
[19] Su T. Mechanism on scour resistance stability of
EN-1 solidified slope in Pisha sandstone region.
Doctoraldissertation,
Northwest
A&F
University, Beijing, China, 2011. (in Chinese).
[20] Han J, Liu Y & Luo L. Research on the coretechnology of remixing soil by soft rock and sandin the Maowusu sand land region. China Land
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[21] Li C, Zhang T & Wang L. Mechanical properties
and microstructure of alkali activated Pisha
sandstone geopolymer composites. Construction
and Building Materials, Vol. 68, No. 15, 2014,
pp.233-239.
[22] Liang Z, Wu Z, Yang C, Yao W & Deng, L.
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durability of Pisha sandstone solidified body.
Yellow River, Vol. 36, No. 8, 2016, pp.46-48. (inChinese).
[23] Wu, Z, Gao, W, Wu, Z, Iwashita, K & Li, R. New
technology of desertification control andecological restoration based on W-OH organic
composite curing material. National seminar onwater and soil conservation, Desertification
control and ecological res-toration, 2009,
pp.244-252. (in Chinese)[24] Yao W, Wu Z, Liu H, Xiao, P & Yang, C.
Experimental research on the anti-Erosion andvegetation promotion for sandstone region in the
Yellow River basin. Yellow River, Vol. 37, No.
1, 2015, pp. 6-10. (in Chinese).
[25] Zeng Y, Qin F & Yue Y. Analysis on plantcomposition and diversity of hippophae forest insandstone areas of Jungar Banner. Northern
Horticulture, Vol. 37, No. 22, 2013, pp.98-101.
(in Chinese)[26] Miao L, Zhong X & Yin Z. The relationshipbetween strength and water content of expansive
water content of expansive soil. Rock and soil
mechanics, Vol. 20, No. 2, 1999, pp.71-75. (inChinese)[6] Wang, Y, Wu, Y, Kou, Q, Min, D, Chang, Y &Zhang, R. Definition of arsenic rock zone
borderline and its classification. Science of Soil
& Water Conservation, Vol. 5, No. 1, 2007,
pp.14-18. (in Chinese).
[7] Wang, Y, Wu, Y, Kou, Q & Li, M. Study onwater and soil loss and control methods in Pisha
sandstone.
The
Yellow
River
Water
Conservancy Press, Zhengzhou, China, 2007. (inChinese)[8] Li, C. Mineral composition and anti-erodibilityof pisha sandstone. Science of soil and water
conservation, Vol. 12, No. 2, 2015, pp.11-15. (inChinese)[9] Guo, J, Shi Y & Wu L. Gravity erosion andlithology in Pisha sandstone in southern Inner
Mongolia. Journal of Groundwater Science andEngineering, Vol. 3, No. 1, 2015, pp. 45-58.
[10] Ziadat F M & Taimeh A Y. Effect of rainfall
intensity, slope, land use and antecedent soil
moisture on soil erosion in an arid environment.
Land Degradation & Development, Vol. 24, No.
6, 2013, pp.582–590.
[11] Xu, J, Wu, C, Lin, Y, Gao, Y, Zuo, Z & Yu, Q.
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sediment in middle Yellow River.., Vol. 20, No.
1, 2006, pp.6-14. (in Chinese).
[12] Zhang K, Xu M &Wang Z. Study onreforestation with seabuckthorn in the Pisha
Sandstone area. Journal of Hydro-environment
Research, Vol. 3, No. 2, 2009, pp. 77-84.
[13] Yang, F, Cao, M, Li, H, Wang, & Bi, C.
Ecological restoration and soil improvement
performance of the seabuckthorn flexible dam in
the pisha sandstone area of northwestern china.
Solid Earth Discussions, Vol. 6, No. 2, 2014,
pp.2803-2842.
[14] Xiao P, Yao W & Liu H. Research Progress andharnessing method of Soil and Water Loss in
Pisha Sandstone Region. Yellow River. Vol. 36,
No. 10, 2014, pp.92-94. (in Chinese).
[15] Yang, F, Cao, M, Li, H, Wang, X. H & Bi, C.
Simulation of sediment retention effects of thesingle seabuckthorn flexible dam in the pisha
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No. 3, 2013, pp.228-237.
[16] Li X, Yue G, S & Yu, Y. Research on Pishasandstone’s anti-erodibility based on grey multilevel comprehensive evaluation method. Journalof Groundwater Science and Engineering, Vol. 4,
No. 2, 2016, pp.103-109.

923

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PREARATION AND EVALUTION BY ARTIFICIAL AGING TEST OF
SIO2 / FLURINATED POLY-STYRENE-ACRYLATE COMPOSITE
MATERIAL
Xiaoying Zhang1, Dongya Yang, Wenya Wen2, Hanqiang Yu2, Xiangyang Wu1*, Jicheng Xu2,3 , Qian Chen2
1
School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China
2
School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China
3
School of Chemical and Materials Engineering, Zhenjiang College, Zhenjiang 212003, China Road,
Zhengzhou 450003, China
ABSTRACT
Recently, some heritages are suffering from varying degrees of physical, chemical and biological weatheringdamage. The aim of the project is the development of high hydrophobic and durability to provide protective
coatings for stone. A series of SiO2-fluorinated poly-styrene-acrylate (SiO2/FPSA) composite emulsion was
prepared with different content of 2,2,2-trifluoroethyl methacrylate content. The composite materials prepared bya semi-continuous emulsion polymerization process were characterized by various methods. The results exhibitedthat the SiO2/FPSA emulsion (S-5 emulsion) had satisfactory stability and low viscosity and surface tension, andSiO2/FPSA film (F-S-5 film) had excellent water resistance and acid/alkali resistance. Therefore, S-5 emulsion
was chosen as the protect coating, and the effect of protect coating was evaluated by the artificial aging test. The
artificial aging experiments such as freeze-thaw, acid aging and soluble salts tests of the SiO2/FPSA composite
coating were investigated. The results indicated that SiO2/FPSA composite could be applied to the protective
coatings for stone surface relics.
Keywords: Stone conservation; cultural heritage; composite; protective polymers
At the same time, the increase in size of the particles
could enhance mechanical properties of the films.
Nano-SiO2 possesses high hardness, and reasonable
price among other nanoparticles.
The aim of this work is to prepare the core-shell
SiO2-fluorinated poly-styrene-acrylate (SiO2/FPSA)
composite emulsion. The composite materials
preparedby asemi-continuous
emulsionpolymerization process were characterized by various
methods. Performances of the satisfactory
SiO2/FPSA were tested on calcites taken from
Jiaoshan Steles Grove (China). The protective
performances had been evaluated by the artificial
aging tests, including freeze-thaw aging test, acidaging test and soluble salts aging test. The analysis
revealed that the protective effects were satisfying.

INTRODUCTION
The cultural heritage was created in a uniqueenvironment, promoting the development of modern
civilization [1]. Recently, some heritages are
suffering from varying degrees of physical, chemicaland biological weathering damage [2]. Thus, theessential properties required to as protective agent
could be summarized as follows: hydrophobic,
permeability to water vapor, transparency,
reversibility or possibility to re-treat the surface,
durability [3-4]. The only way to preserve, as early as
possible, is to investigate the new material or novel
methodologies to resist these physical chemical andbiological attacks. In summary, the protection ofstone relics must be seriously.
Using of chemical materials to safeguard stone
relics is a common method to avoid further
weathering in outdoor conditions. Currently, most oforganic materials have been attempted in theconservation of stones, such as acrylate, epoxies,
silicones, fluorinated polymers, etc [5]. Recently
years, acrylate and silicones or their mixtures havebeen widely used in the protection of stone relics.
Fluorinated styrene-acrylate (or acrylate) copolymer
has attracted a great deal of attention. Not only it isrelatively low cost and environmental friendly, butalso it contains the excellent properties of both
fluorine and styrene-acrylate (or acrylate) copolymer.

EXPERIMENT
Materials
Styrene (St), ethyl acrylate (EA), methyl
methacrylate (MMA), butyl methacrylate (BMA),
acrylic acid (AA, 99.5%), 2,2,2-trifluoroethyl
methacrylate (TFEMA), tetraethyl orthosilicate(TEOS), γ-methacryloxypropyl trimethoxysilane(KH-570), polyethylene p-octyl glycol phenylether(OP-10) and ethanol (C2H5OH) and sodium sulfate(Na2SO4) were all purchased from Sinopharm924

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Chemical Reagent Co., China. Sodium dodecyl
sulfate (SDS) was obtained from Shanghai reagent
factory, China. Potassium persulfate (KPS) was
purchased from Tianjin Chemical Reagent Factory,
China. Sodium hydrogen carbonate (NaHCO3) was
obtained from Shanghai Su Yi Chemical Reagent Co.,
China. Ammonia (NH3·H2O) was provided by
Shanghai Pilot Chemical Co., China. All reagentswere used without any further purification.

emulsion was neutralized with NH3.H2O to pH = 7-8.
Varying the contents of TFEMA (0, 2%, 4%, 6%,8%, and 10%, based on total monomers), and the
addition of nano-SiO2 was 3%, a series of SiO2fluorinatedpoly-styrene-acrylate(SiO2/FPSA)
composite emulsion were prepared and named as S-2,
S-3, S-4, S-5, S-6 and S-7, respectively, while purestyrene-acrylate emulsion was named as S-1 (PSA).
The synthetic route of SiO2-fluorinated poly-styreneacrylate (SiO2/FPSA) is shown in Fig. 2.

Preparation of modified the nano-SiO2
Nano-SiO2 particles were prepared by the wellknown sol-gel process. Firstly, absolute ethanol,
deionized water were introduced in a 250mL, threeneck, round-bottom flask heated to 30 oC understirring. HCl was added into the reaction system andkept pH= 3; and TEOS was added into the solution
and stirred at 30 oC for 3 h. Then it started withstirring a mixture of silica sol and KH-570 at 60 oC
for 6 h under constant stirring. Finally, the KH-570modified nano-SiO2 was obtained. The syntheticroute of nano-SiO2 was shown in Fig. 1.

Fig. 2 The synthetic route of SiO2-fluorinated polystyrene-acrylate
All SiO2/FPSA emulsions (S-1, S-2, S-3, S-4, S-5,
S-6 and S-7) were poured into the poly(tetrafluoroethylene), and the SiO2/FPSA films wereobtained by drying for 6 days at room temperatureand labeled as F-S-1, F-S-2, F-S-3, F-S-4, F-S-5, FS-6 and F-S-7, respectively.
Characterization

Fig. 1 The synthetic route of nano-SiO2

The procedures for the measurements of the films
were briefly described as follows：The dried films
prepared (20×20 mm2) were soaked in deionizedwater or 5% NaOH or 5% H2SO4 solution at room
temperature after being weighted (Original weightrecorded as m1). After 24 h, the liquid remaining on
the films surface was then wiped with filter paper andweighed again (the weight was denoted as m2). The
water absorption (or swelling degree), ω, wascalculated by as follows (1):Preparation of SiO2-fluorinated poly-styreneacrylate (SiO2/FPSA) composite emulsion
SiO2/FPSA composite emulsions were preparedby a semi-continuous emulsion polymerization
process. A certain amount of water, 30 g of themonomer mixture and emulsifier (50 wt%, relative tothe whole emulsifier level), polyethylene p-octyl
glycol phenylether (OP-10) and sodium dodecyl
sulfate (SDS) (at weight ratio of OP-10/SDS = 2:1)
were pre-emulsified.
Seed emulsion polymerization was carried out ina 250 mL four-necked glass reactor. The initial charge
in the reactor was water, the rest of the emulsifier,
NaHCO3 as buffer, the monomer pre-emulsified
mixture (9 g) and varying contents of TFEMA. Whenthe flask was heated to the reaction temperature, thesecond charge, part of the initiator solution was added.
The reaction was held at 75 oC for 30 min, after which
the rest of the pre-emulsified mixture was added into
the reactor drop wise for about 2–3 h. The rest of
initiator solution was then added to the system. Then,the mixture was kept at 90 oC for two more hours tocompletely polymerize all the monomers; and thencooled down to room temperature. Finally, the%(1)

The contact angles of water on SiO2/FPSA
composite films were measured with a commercial
CAM200 optical system (KSV Instruments, Finland)by the sessile drop method with a micro-syringe at 25o
C. More than 3 contact angles were averaged to geta reliable value for each sample.
To investigate the morphology of the film andstone, scanning electron microscopy (SEM)
micrographs were taken with a field emission
scanning electron microscope (S-4800, Hitachi Corp.,
Tokyo, Japan) at a voltage of 15.0 kV. The samples
were diluted with deionized water, dropped onto
silicon wafer and dried at room temperature.
Artificial ageing test

925

GEOMATE - Mie, Japan, Nov. 21-24, 2017

To evaluate the performance of the protective
material, artificial aging experiments were
performed. Samples “A”, “C” and “E” were treatedby the prepared emulsions; and samples “B”, “D” and“F” were blank samples. All stone samples wereobtained from the hillside near the Moya stone
inscriptions for consistency and smoothed withabrasive paper.

RESULTS AND DISCUSSION
Some properties of SiO2/FPSA Films
Water absorption or swelling degree data are also
listed in Table 1. Water absorption or swelling degree
is another important indicator of stone protective
material. A good protective material must haveexcellent hydrophobicity and good acid or alkali
resistance. Compared with F-S-1 film (PSA film), theF-S-2, F-S-3, F-S-4, F-S-5, F-S-6, and F-S-7 films(SiO2/FPSA films) present the satisfactory result inwater absorption. The introduction of the fluorinatedmonomer improved the hydrophobic properties of thecopolymer. The water contact angles are also shownin Fig. 3, reflecting an increase of hydrophobic with
the increasing of the TFEMA content. The watercontact angle for F-S-1 film is 52.71o. However, thewater contact angle becomes 75.70o for F-S-6 film.
The surface of SiO2/FPSA film includes a large oflow surface energy fluorinated groups. The
fluorinated groups are an important factor to lead to agood performance in water resistance. Additionally,
the existence of hydrophobic Si-O-Si also leads tofilms with lower water absorption. Meanwhile, thesimilar change can be found in swelling degrees(5.0% H2SO4 solution) or swelling degrees (5.0%
NaOH solution). Therefore, SiO2/FPSA films haveexcellent water resistance and acid / alkali resistance.

Freeze - thaw aging test
First, the stone samples “A” and “B” were soaked
in distilled water for 8 hours. Then, the stone samples“A” and “B” were moved to the freezing chamber,and freezing period lasts for 16 hours at -10 °C.
Finally, samples “A” and “B” were removed from thefreezing chamber, and transferred to an oven about 80°C. The multiple cycles were performed.
Acid aging test
The stone samples “C” and “D” were immersed in
H2SO4 solution (pH=1) in 72 h, observing the changes
in the stone samples.
Soluble salts aging test

The stone samples “E” and “F” were immersed in
0.5 mol/L Na2SO4 solution about 8 h. Then both
samples were natural weathering at room temperature
for the salt crystallization. The multiple cycles werecarried out.
Table 1 The properties of SiO2/FPSA films
Sample
F-S-1
F-S-2
F-S-3
F-S-4

F-S-5

F-S-6

F-S-7

Water absorption (%)

33.30

23.06

17.71

15.65

9.43

10.05

11.76

Swelling degree(5.0% H2SO4solution)

17.63

9.45

8.74

8.23

7.24

7.28

7.21

Swelling degree(5.0% NaOH solution)

10.15

11.16

11.23

9.71

9.51

9.65

9.47

Water contact angle (o)

52.71

65.46

69.22

69.83

72.63

75.70

75.43

SEM analysis
SEM images of the fracture surface of F-S-1 (a),F-S-2 (b) and F-S-5 (c) films are shown in Fig. 4. The
surface of the PSA (F-S-1) film is relatively flat andsmooth. However, there are small waves on thesurface of SiO2/PSA film with adding 3 wt% SiO2 (FS-5 (b) film), indicating that the introduction of SiO2
particles made the surface become rough.
Furthermore, when simultaneously introducing SiO2
and TFEMA (F-S-5 (c) films), there were manyripples on the surface, indicating between inorganicand organic phases formed interwoven network
structure. The stone sample is observed by SEM
analysis to investigate the morphology of stone andFig. 3 The water absorption and water contact angleof the SiO2/FPSA films
926

GEOMATE - Mie, Japan, Nov. 21-24, 2017

SEM images are shown in Fig. 5. As can be seen from
Fig. 5, the structure of stone sample is relatively loose
and there are some pits and cracks on the surface.
These results indicate that stone samples have been
severely damaged.

Fig. 4 SEM images of F-S-1 (a), F-S-2 (b) and F-S-5(c)Fig. 7. The weight loss of stone sample in acid aging
test
Soluble salts aging test
Soluble salts are considered to be the key
deteriorating element of stone relics. The images ofsoluble salts aging test are shown in Fig. 8. As can beseen from Fig. 8, the untreated stone surface has takenplace significant changes. However, there is noremarkable change on the treated stone surface.
Compared to the treated stone sample “E”, theuntreated stone sample “F” has cracks and pits after
15 cycles. That is to say, SiO2/FPSA composite
materials succeeded to reduce salt accumulation
phenomena. This can be attributed to SiO2/FPSA
composite materials developed a network structure in
the stone voids, effectively preventing the formationof crack, further weathering.

Fig. 5 SEM image of the stone sample
Freeze - thaw aging test
The images of freeze-thaw aging test after different
cycles are illustrated in Fig. 6. It can be seen from Fig.
4, after 10 cycles, the letter “B” has blurred on thesample “B”; and after 15 cycles, the sample “B”
begins to appear little cracks. After 20 cycles, there
are obvious cracks on the surface of the sample “B”;
however, the sample “A” has almost no change.

Fig. 6 The images of freeze-thaw aging test after
different cycles
Acid aging test

Fig. 8 The images of soluble salts aging test

As shown in Fig. 7, after acid aging test, both stone
samples mass is reduced in varying degrees. This canbe attributed to the reaction of sulfuric acid andcalcium carbonate. There are still fluctuations in thesample “C” mass, but the rate has been significantly
reduced, indicating markedly improved acidresistance.

The uniform core–shell SiO2/FPSA composite
materials were successfully prepared. The resulting
SiO2/FPSA composite emulsions exhibited higherhydrophobic property. Thus, SiO2/FPSA composite
materials can be used for the conservation of the stone
relics.
.

CONCLUSION

927

GEOMATE - Mie, Japan, Nov. 21-24, 2017

coating materials in conservation of stone relics.
Prog Org Coat, Vol. 76, 2013, pp. 1127-1134.
[3] Varas MJ, de Buergo MA, Fort R. The influenceof past protective treatments on the deteriorationof historic stone facades - A case study, Studies
Conserv, Vol. 52, 2007, pp. 110-124.
[4] Pecchioni E, Gomez Ubierna M, Cagnini A,
Galeotti M, Fratini F, Porcinai S. Ancient andnew repair mortars for conservation: Application
to the case of san leonardo pulpit (Florence, Italy).
Int J Archit Herit, Vol. 8, 2014, pp. 556-580.
[5] Tsakalof A, Manoudis P, Karapanagiotis I,
Chryssoulakis I, Panayiotou C. Assessment ofsynthetic polymeric coatings for the protection
and preservation of stone monuments. J Cult
Herit, Vol. 8, 2007, pp. 69-72.

ACKNOWLEDGEMENTS
This project was supported by the Innovation
Program for Graduate Education of Jiangsu Province(SJLX_0477), Society Development Fund of
Zhenjiang (SH2014074 and SH2013020), Zhenjiang
College Scientific Research Team (ZJCKYTD07)
and Sponsored by Qing Lan Project (2012-2015).
REFERENCES[1] Abbott A. Rescuers of Europe's cultural heritage
struggle for funding. Nature, Vol. 414, 2001, pp.
572-572.
[2] Zhang H, Liu Q, Liu T, Zhang BJ. The
preservation damage of hydrophobic polymer

928

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

STUDY ON OUTDOOR THERMAL ENVIRONMENT OF CAMPUS
BASED ON GIS
1Minxue Zheng1, Shanwei Li1 and Hongxiao Liu1
School of Environment and Safety Engineering, Jiangsu University, China
ABSTRACTIn recent years, the campus population and the buildings of Jiangsu University have increased and the patternof the micro-city has preliminarily formed. The data of outdoor thermal environment of campus based on
Geographic Information System (GIS) has found that the average temperature difference of outdoor temperaturein space distribution in Jiangsu University is about 1℃. Five different underlying surfaces have a great influenceon the outdoor thermal environment of campus, and the daily variation of temperature showed an inverted "V"single peak curve. The daily variation of temperature on the concrete road (direct sunlight) is approximately 4℃
above that of the grassland at the time of 14:00. The temperature of the concrete road (direct sunlight) is higher
than that of the concrete road (shadows), and the temperature difference between them is about 1℃. At the sametime, five suggestions have been proposed for the improvement of outdoor thermal environment in Jiangsu
University according to the results.
Keywords: Heat Island Effect, Outdoor Thermal Environment, Spatial Change, Underlying Surface, GIS
carbon dioxide measuring instrument (model C2DW02TR) was adopted to measure the outdoor
temperature and relative humidity of the campus of
Jiangsu University. GIS was used to analyze andstudy the distribution characteristics of outdoor
thermal environment in campus.
The research object is the whole area of campus
in Jiangsu University, which is in east longitude
119°30′～119°31′30″E, and north latitude 32°11′40″～32°12′50″N. The campus area was divided into 30
measuring area with each 300m*300m as a measuringunit. A position with marked facility of eachmeasuring unit was chosen as a measuring point formeasuring the latitude and longitude to ensure thateach measurement was performed at the same
location (Fig. 1 and Fig. 2). All the measuring points
were measured in three time periods at 7:00-8:00 in
the morning, 10:00-11:00 at noon and 17:00-18:00 at
evening for three times a week. The underlying
surfaces of the measuring points were divided into 4categories, such as grassland, lake, concrete andmarble road to discuss the temperature and relative
humidity changes of different underlying surfaces.

INTRODUCTION
Urban heat island effect, whose temperature ishigher than that of outer suburbs, reduces the
comfortability of the manufacture and life of people,
that endangers the health and even life of human [1,2].With the warming of global, the influences ofurban heat island effect on lives of people havebecome increasingly apparent. The rapid
development of urban has accelerated the aggravationof urban heat island [3]. In recent years, theenrollment of Jiangsu University continues to expand,
and the campus construction develops rapidly. The
campus covers an area of 1,880,000 m2. Among them,
all types of building area hold more than 1,280,000
m2, and nearly 50 thousand students are in school.
With the increases of the campus population andbuildings, the pattern of micro-city has preliminarily
formed. Surface temperature change of different
underlying surfaces is an important factor to improveurban heat island effect [4]. Accompanied by theincreasingly obvious urbanization and hugedevelopment of the university campus, reducing theheat island effect has become an important topic toimprove the learning and living environment ofstudents, and create a comfortable outdoor
environment [5, 6].

DATA
MONITORINGRESEARCH METHODS

Data Analysis Method
In this work, Microsoft Excel 2013 software wasused to database establishment, data collection andanalysis. GRASS and GMT software were used tovisualize the temperature spatial distribution data,
which directly and quantitatively reflected thetemporal and spatial distribution characteristics oftemperature in the campus.

AND

Data Monitoring Methods
In this study, the Japanese advanced portable
929

GEOMATE - Mie, Japan, Nov. 21-24, 2017a small quantity of population such as Thorpe plum.
The temperature in the morning has bigger variation
than that at noon and in the evening, which might berelated to the sunshine, the wind speed, theunderlying surface and the surrounding environment.

A

Figure 1 Area division of campus outdoor
temperature measurement.

B

Figure 2 Point distribution of campus outdoor
temperature measurement.

TEMPORALANDSPATIAL
DISTRIBUTION CHARACTERISTICSOF TEMPERATURECAs shown in Figure 3, the temperature differenceof the average temperatures among morning, noonand evening is about 1℃. The lowest temperatures ofmorning, noon and evening was concentrated near theround covers in front of the auditorium (D3). Thismeasuring point is at the crossroads with good
ventilation, where a lawn is in the front and issheltered by tall trees. The trees can block
shortwave radiation of the sun and absorb
long-wave radiation of the ground. The highest
temperature in the morning appeared in sixth canteen
corner of Jiangsu University (A6) and the main
entrance in front of the Mechanical College (C2). The
highest temperature at noon was under a ladder ofSanjiang Floor Front Gate (E2). The highest
temperature in the evening was at the entrance to theauditorium (D2). Except for the factors of theconcrete surface, tall buildings and poor ventilation inthese places, the influences of the traffic andpopulation also contributed to the high temperature.
So the temperature is higher in the areas with lots of
population and traffic, such as canteen andaccommodation areas. The temperature was low in
the areas with plentiful vegetation cover andFig. 3 Temperature distribution in time interval (A:morning; B: noon; C: evening).

930

GEOMATE - Mie, Japan, Nov. 21-24, 2017

studying the changes of the temperature and relative
humidity around their surrounding environments.

As shown in Figure 4, the low temperature
region was centered near the round covers in front of
the auditorium (D3), near the lawn opposite the
Valentine Valley (E3) and the yellow road in front ofexpert floor (E4). At these places, trees not only can
reduce the outdoor wind speed, making the heataccumulation phenomenon appeared, but also canremove a large amount of short-wave radiation by
reﬂection and transmission through their leaves todecrease the surrounding ambient air temperature.
The high temperature region was distributed in the
middle of the round altar opposite the Three Hillbuilding (D1), at the entrance to the lecture hall (D2),in the roadside of Jiangsu University (E1), and under
the stairs at the main entrance of Sanjiang building(E2). The minimum temperature was 22.5℃ and the
maximum temperature was 23.5℃. The averagetemperature difference was about 1℃. In this study,
300m*300m is a measurement unit, and the lowest
and the highest temperature regions were only 1 to 2
measurement unit intervals. That is to say, in therange of 300m to 600m, the temperature has alreadychanged 1℃. It shows that there was a more obvious
heat island effect on the campus of Jiangsu University.

CHARACTERISTICSOFTEMPERATURE AND RELATIVEHUMIDITYAT
DIFFERENTUNDERLYING SURFACES
Daily Variation Of Temperature At
Different Underlying Surfaces
As shown in Figure 5, temperatures of fivedifferent underlying surfaces in one day presented
inverted "V" single peak curves. The temperatures
were low in the morning and evening, which was highin the afternoon at about 16:00. The main reason isthat the study area is located in the south, and thesunshine period is longer in spring. So that theendothermic and exothermic reached the balance at
16:00, when the temperature was the highest. It also
found that the temperature of grassland is the lowest,
while the temperature of the concrete road (direct
sunlight) is the highest. The temperature of theconcrete road under the shadow is lower than that of
the concrete road with direct sunlight. The
temperature difference between them is about 1℃.
Because tree canopy tends to reduce surface
temperature in the shade and thus reduces storage andconvection of heat. Shading by trees can remove alarge amount of incoming short wave radiation by
reﬂection and transmission through their leaves.
Therefore, the surface and air temperature can belower in the shade of trees than in surrounding
unshaded areas. So one way to mitigate urban heatisland thereby reduce human heat stress is to increase
vegetation cover in urban areas as vegetation can
provide evatranspiration cooling and shading beneﬁts
as well as other ecosystem services.

34

T (℃)

32
30
28

Fig. 4 Spatial distribution of the mean temperature.

26

In order to further investigate the effect of heatisland effect, we select five measurement points tostudy the influences of different underlying surfaces
according to the results of figure 4. Grassland (E3),riverside (F2), marble road (E2), concrete road with
(C5) and without (C4) shadow were chosen for

GrasslandRiverside
Marble road
Concrete road (Shadows)
Concrete road

8:00 10:00 12:00 14:00 16:00 18:00

Time
Fig. 5 Daily variation of temperature at different
underlying surfaces.

Daily Variation Of Relative Humidity At
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

The temperatures and relative humidity ofdifferent underlying surfaces were numerical
averaged. As shown in Figure 7, the peak temperature
was at 16:00, when the relative humidity was at thelowest level. It is because that in the morning, thetemperature and the relative humidity of the air risewith the increase of the solar radiation. After that, thetemperature of the air continues to rise due topersistent solar radiation, while the relative humidityof the air decreases gradually and reaches a criticalpoint at 16:00. Then, the radiation of sun weakened
and the temperature began to decrease, while therelative humidity of the air gradually rose. According
to the results, the temperature is negatively related to
the relative humidity. Transpiration can mediate
latent heat loss during the conversion of liquidwater to vapour, thereby resulting in the coolingof the leaf and the surrounding environment.

Relative humidity (%)

Different Underlying Surfaces

56
52
48
44
40
36

GrasslandRiverside
Marble Road
Concrete road (Shadows)
Concrete road

8:00 10:00 12:00 14:00 16:00 18:00

Time
Fig. 6 Daily variation of relative humidity at different
underlying surfaces.

CONCLUSIONAs shown in Figure 6, the highest values of air
relative humidity for five different underlying
surfaces all appeared at 10:00, while the lowest values
appeared at 16:00. Trees release water vapour to the
air from leaf stomata during photosynthesis, which is
known as transpiration. Leaf transpiration and soil
water evaporation are all contributed to the air
humidity. The relative humidity of the air changed at
the beginning of 8:00 in the morning. It risen first,
then dropped, and finally continued to rise following
the sine curve. Although the trend of the curvechanges in the same trend, there are obvious
differences in the influence of the different
underlying surfaces on relative humidity. For
example, the relative humidity of hardened roads
were lower than those at the riverside and thegrassland.

34

55

32

50

30

45

28
26

Temperature
Relative humidity

8:00 10:00 12:00 14:00 16:00 18:00

40

Relative humidity (%)

T (℃)

The Relationship Between Temperature
and Relative Humidity

35

In this work, the outdoor temperature, relative
humidity and other environmental parameters of
Jiangsu University campus were tested. GIS
technology was used to study the distribution
characteristics of campus thermal environment andthe influences of different underlying surfaces on
campus thermal environment.
According to the temperature spatial distribution
map of Jiangsu University, the distance between the
low and the high temperature region were about 300m
~ 600m and the temperature difference was 1℃. So
that the heat island effect is more obvious.
The daily variation of the temperature of fivedifferent underlying surfaces showed inverted "V"single peak curves. The temperature was low in themorning and evening and high in the afternoon. At
14:00, the temperature difference between thegrassland and the concrete road (direct sunlight) was
about 4℃.
The temperature and the relative humidity
showed a trend that the temperature was rising while
the relative humidity was decreasing obviously. The
temperature was negatively correlated with therelative humidity.
The temperature of concrete road with direct
sunlight was obviously higher than that of concreteroad with shadow, and the temperature difference
between them was about 1℃. It means that trees play
an important role in regulating the temperature.
The temperature is higher with abundant of
population and traffic, such as canteens, playgrounds
and bathrooms.
OUTLOOK

Time
Fig. 7 Daily variation of mean temperature and mean
relative humidity.

According to the conclusions, we forward fivespecific suggestions for improving the outdoor
thermal environment in Jiangsu University:
932

GEOMATE - Mie, Japan, Nov. 21-24, 2017

Environ, 577 (2017) 349-359.
[6] D.C. Zhou, L.X. Zhang, L. Hao, G. Sun, Y.Q. Liu,
C. Zhu, Spatiotemporal trends of urban heatisland effect along the urban development
intensity gradient in China, Sci Total Environ,
544 (2016) 617-626.

The protection of the existing grassland is aneffective way to mitigate the heat island effect.
Therefore, the management system of campus
vegetation should be perfected as soon as possible.
Recently, our school is on the remediation of the
Yudai River Basin. Widening the river channel andincreasing the drainage area could effectively reduce
the outdoor temperature of the campus.
In summer, the temperature in the places witha small number of vegetation coverage and lots ofpeople, such as the library is high. Sprinkling water
could be used to increase the humidity of the air anddecrease the temperature, which can provide a
comfortable learning environment for students.
Tall shrubs should be planted in the areas withdirect sunlight, which can increase the shadow area,
and thus effectively decrease the temperature.
Students should be encouraged to instill the ideaof environmental protection into all aspects of daily
life. This is a long-term and meaningful work, which
can directly reduce the anthropogenic heat emission
and weaken the campus heat island effect.
ACKNOWLEDGEMENTS
The
atmosphericparameter
measuring
instrument used in this project is provided by Nagoya
Industry University of Japan.
REFERENCES[1] S. Zhong, Y. Qian, C. Zhao, R. Leung, H.L.
Wang, B. Yang, J.W. Fan, H.P. Yan, X.Q. Yang,
D.Q. Liu, Urbanization-induced urban heat island
and aerosol effects on climate extremes in the
Yangtze River Delta region of China, Atmos
Chem Phys, 17 (2017) 5439-5457.
[2] M. Palme, L. Inostroza, G. Villacreses, A. LobatoCordero, C. Carrasco, From urban climate toenergy consumption. Enhancing building
performance simulation by including the urban
heat island effect, Energ Buildings, 145 (2017)107-120.
[3] W.F. Li, Q.W. Cao, K. Lang, J.S. Wu, Linking
potential heat source and sink to urban heatisland: Heterogeneous effects of landscapepattern on land surface temperature, Sci Total
Environ, 586 (2017) 457-465.
[4] J.Q. Chen, H. Wang, H.Z. Zhu, Analytical
approach for evaluating temperature field of
thermal modified asphalt pavement and urban
heat island effect, Appl Therm Eng, 113 (2017)739-748.
[5] R.C. Estoque, Y. Murayama, S.W. Myint, Effectsof landscape composition and pattern on land
surface temperature: An urban heat island study
in the megacities of Southeast Asia, Sci Total

933

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEGRADATION OF FAMOTIDINE IN WATER WITH Ag-ZnO UNDERUV LIGHT IRRADIATION
Md. Ashraful Islam Molla1,*, Ikki Tateishi1, Mai Furukawa1, Hideyuki Katsumata1, Tohru Suzuki2, Satoshi
Kaneco1,2
1Department of Chemistry for Materials, Graduate School of Engineering, Mie University, Japan2
Mie Global Environment Center for Education & Research, Mie University, Japan
ABSTRACT
Ag–doped ZnO photocatalysts were successfully synthesized at different Ag contents (0–15 wt%) throughsimple, effective, high yield and low cost mechanochemical combustion technique. The addition of silver acetate
to zinc acetate and oxalic acid mixture was performed for mechanochemical technique. The photocatalytic
performance of different prepared photocatalysts was evaluated by the degradation of Famotidine (FMT) under
UV irradiation. The photodegradation rate increased with increasing the Ag contents from 0 to 10%, and it was
2.1 times better than undoped ZnO on 90 min. The photocatalytic degradation of FMT with Ag–doped ZnO wasaffected by degradation parameters such as calcination temperature, calcination time and doping concentrations.
The Ag–doped ZnO demonstrated higher activity due to small particles size, large surface area, and reduction ofelectron−hole recombination. The trapping test with different scavengers proved it that the oxidation of FMT
occurred with the reactive species of •O2−, •OH and h+. In these species, •O2− radical was the main reactive
species in the photodegradation process.
Keywords: Famotidine, Photocatalytic Degradation, Ag/ZnO, UV Light Irradiationtransfer [7]–[12]. One of these methods is to dopetransition metal into ZnO photocatalysts. Doping oftransition metals into the ZnO lattice can lead tochanges in the electrical, optical, and magnetic
properties of ZnO. Besides, it reduces band gap
energy of ZnO, improves charge separation between
electron and hole by forming electron traps and,enhances photocatalytic activity of ZnO [13].
Different transition or noble metals such as Mn, Fe,
Ni, Cu and Ag have been widely used for doping of
ZnO. Among them, Ag is the cheapest noble metaland has potentials in industrial productions [14]–[16]. The wide band gap ZnO semiconductor shows
only photo-absorption under UV irradiation whereas
silver metal acts as electron sink, which effectively
trapped photo-excited electrons from ZnO surface
and preventing the recombination of electron-hole[17]. Also the silver metal nanoparticles wereeffectively trapped the photo-excited electrons fromthe ZnO surface and enhanced the hole generation[18],[19]. The photo-generated holes and metal
trapped electrons have effectively produced thehydroxyl radicals and super oxide radicals. The
generated hydroxyl and superoxide radicals arestrong oxidant species which can degrade the FMT
molecule.
In this study, the various proportions of Ag/ZnO
nanocomposites were prepared by hydrothermal
method. Furthermore, the photocatalytic activities ofpure ZnO and Ag/ZnO nanophotocatalysts were
investigated by degrading Famotidine in aqueous

INTRODUCTION
Famotidine (FMT) is a histamine H2–receptor
antagonist
used
to
treat
pepticulcers,gastroesophageal reflux, and conditions, where thestomach produces an excess of acid [1],[2]. It has
been documented that 65~70% of the parent
compound is found unchanged in the urine, when
patients used the FMT [3]. It creates stablecomplexes with palladium, copper, cobalt and nickel.
Previous research reports have proved the stabilityof FMT in the environment and water bodies [4].
Taking the above–mentioned issues into account,
one can argue that FMT should be considered aspersistent contaminants in an aqueous environment.
Zinc oxide (ZnO) is a wide band-gap (3.2 eV)semiconductor with large exciton binding energy of
60 meV at room temperature [5]. It is known as oneof the important active photocatalysts due to its
advantages, including the large initial rates ofactivity, many active sites with high surface
reactivity, low price and environment safety [6].
However, ZnO have several disadvantages such as a
rapid recombination of photoexcited electron andhole pairs which inhibits its photocatalytic efficiency.
To improve the photocatalytic activity of ZnO,
surface charge transfer processes should beenhanced and the recombination rate of electron andhole should be decreased. Several methods havebeen
improved
toreduceelectron–holerecombination and increased the surface charge934

GEOMATE - Mie, Japan, Nov. 21-24, 2017

measured using a high-performance liquid
chromatograph (HPLC, GL–7400), equipped with a
HITACHI L–3000 optical detector and an Inertsil
ODS–3 column (GL Science, Japan). The elution
was monitored at 276 nm. The mobile phase was a
mixture of acetonitrile and water (1/1, v/v) and was
pumped at a flow rate of 1.0 mL/min.

medium under UV-light. It is found that the
10%Ag/ZnO photocatalyst exhibits excellent
photocatalytic activity.
EXPERIMENTAL
Chemicals and Materials

Detection of reactive oxygen species

Zinc acetate dehydrate (99.9%), oxalic aciddehydrate (98%), silver acetate (99%) andFamotidine (99%) were obtained from Wako Pure
Chemical Industries, Ltd. and were used as received
without further purification. Laboratory pure water
was obtained from an ultrapure water system(Advantec MFS Inc., Tokyo, Japan) resulting in a
resistivity >18 MΩ cm.

The scavenging experiments of reactive oxygen
species were similar to the photodegradation
experiments. Three scavengers were selected,
namely, tert-butyl alcohol (•OH radical scavenger),di-ammonium oxalate monohydrate (hole scavenger)
and ascorbic acid (•O2− radical scavenger). Different
quantity of tert-butyl alcohol, di-ammonium oxalatemonohydrate [20] and ascorbic acid [21] were added
into the FMT solution prior to addition of catalysts.

Preparation of Photocatalyst

RESULTS AND DISCUSSION

In a typical synthesis, 2.195 g of zinc acetate
dihydrate and 2.521 g of oxalic acid dihydrate weretaken in agate mortar and the mixture was groundfor 10 min in order to obtain a paste of zinc oxalate
dihydrate and acetic acid. The existence of acetic
acid was confirmed by its typical smell. The loss ofacetic acid byproduct in the form of fumes became adriving force for the reaction. Silver acetate wasadded to the above paste as a source of silver, andthe grinding process was continued for the next 10
min to obtain zinc oxalate−silver oxalate.
The Ag–doped zinc oxide crystallites wereobtained by calcination of precursor powders at thetemperature of 300−700 °C under an air atmosphere.
The undoped ZnO was also synthesized bycalcination of a paste of zinc oxalate and acetic acidfor the comparison.

Effect of Ag-doping Amount
Photocatalytic Degradation of FMT

on

the

The influence of silver doping amounts on thephotocatalytic FMT degradation was studied in the
aqueous solution under UV light irradiation. The
results are depicted in Fig. 1. The degradation rateincreased with an increase in silver percentage up to
10 wt% in the composite, and exceeding this silver
percentage photocatalytic activity decreased
ZnO
1%Ag/ZnO
3%Ag/ZnO
5%Ag/ZnO
7%Ag/ZnO
10%Ag/ZnO
15%Ag/ZnO

1.0

C/C0

0.8

Photocatalytic Activity

0.6
0.4

The photocatalytic activities of Ag/ZnO were
evaluated by the degradation of Famotidine under
UV irradiation at ambient temperature. Typically, 30
mL of Famotidine solution, 10 mg of photocatalyst
were added to a 35–mL Pyrex glass cell. The initialconcentration of Famotidine in all experiments was
10 mg/L and the Famotidine solution containing theappropriate quantity of the photocatalyst powder
was magnetically stirred before and during
irradiation. Before irradiation, the photocatalyst
suspension containing Famotidine was allowed toequilibrate for 30 min in the dark. The sample
solution was irradiated with a Black lamp (365 nm)
which was positioned on the side of the reaction cell.
After the desired irradiation time, the photocatalyst
was separated by the centrifugation. The amount of
the remnant Famotidine in the aqueous solution was

0.2
0.0

Dark

‐15
‐30

0

15

30

45

60

75

90

Time (min)Fig. 1 Effect of Ag–doping amount on thephotocatalytic degradation of Famotidine with
Ag/ZnO under UV light irradiation. Calcination
temperature 500 °C; calcination time 3 h.
The possible reason may be attributable to thetradeoff between the decrease in particle size and thedeterioration in crystallinity for ZnO [22]. An
optimal amount (10%) of silver doping into ZnO is
935

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

desirable for higher photocatalytic activity, whichleads better charge separation at ZnO surface andefficient electron transfer to Ag metal. On the other
hand, the higher percentage of silver shows higher
negative charge on the silver surface, which
effectively attracted positively charged holes fromZnO surface resulting in increased recombination
rate [23]. Also, the higher percentage of silver
masked the ZnO surface and affected the absorbanceof UV light [24].

Effect of Calcination Time on the Photocatalytic
Degradation of FMT
The effect of calcination time on thephotocatalytic FMT degradation using Ag–doped
ZnO was investigated under UV light irradiation for
1 h. The results are illustrated in Fig. 3. As thecalcination time increased up to 3 h, thephotocatalytic FMT degradation with Ag/ZnO
increased gradually. After the calcination time of 3h, the photocatalytic FMT degradation turned fromincrease to decrease.

Effect of Calcination Temperature on the
Photocatalytic Degradation of FMT

1.0

The photocatalytic FMT degradation with theAg–doped ZnO was evaluated in the aqueous
solution under UV light irradiation for 1 h. Figure 2
shows the effect of calcination temperature on thephotocatalytic FMT degradation with undoped anddoped ZnO materials. The oxides were sintered at
different temperatures such as 300, 400, 500, 600
and 700 °C and were tested for their photocatalytic
degradation of FMT. The optimum calcination
temperatures for Ag–doped ZnO were 500 °C.

0.8

C/C0

0.6

0.4

0.2

0.0

1.0

1

2

3

4

Calcination time (h)0.8Fig. 3 Effect of calcination time on thephotocatalytic degradation of Famotidine with
Ag/ZnO under UV light irradiation. Ag doping 10wt%; calcination temperature 500 °C.

C/C0

0.6
0.4

Role of the reactive species in the photocatalytic
process

0.2
0.0

0

300

400

500

600

The role of the reactive species in thephotocatalytic process was studied by using different
quenchers. The quenchers used to scavenge therelevant reactive species were: tert–butyl alcohol(•OH radical scavenger), di-ammonium oxalatemonohydrate (h+ scavenger) and ascorbic acid (•O2−
radical scavenger). The effect of different
scavengers on the FMT degradation over Ag/ZnO
heterojunction is presented in Fig. 4. It was observedthat by using AO, TBA and AA as scavenger, thephotocatalytic activity significantly reduced from88% (no scavenger) to 18% (due to •O2−), 33% (dueto •OH) and 46% (due to h+), respectively. Hence, it
was concluded that all the reactive species (•O2−,•OH and h+) contributed to the photodegradation
process. In these species, •O2− was the main reactive
species in the photodegradation process since worst
photocatalytic activity was found by using AA as
scavenger.

700

Calcination temperature (°C)

Fig. 2 Effect of calcination temperature on thephotocatalytic degradation of Famotidine with
Ag/ZnO under UV light irradiation. Calcination time
3 h; Ag doping 10wt %.
Above 500 °C, the photocatalytic FMT
degradation decreased with the calcination
temperatures. It was reported previously that the
crystallite size of the oxides increased withincreasing the calcination temperatures [25]-[28].
Therefore, the reason for the decrease in thephotocatalytic FMT degradation may be due to thelarger particle size of ZnO. The best material for thephotocatalytic FMT degradation was the 10%Ag–
doped ZnO, which was sintered at 500 °C.

936

GEOMATE - Mie, Japan, Nov. 21-24, 2017

CONCLUSION
1.0

In summary, the Ag–doped ZnO was applied
into the photocatalytic degradation of FMT inaqueous medium under UV light irradiation. The
optimum calcination temperature and time were 500°C and 3 h, respectively. The best Ag–doping
amount was 10 wt%. The maximum photocatalytic
activity for FMT degradation on Ag/ZnO was morethan two times better compared with undoped ZnO.
According to the investigation of the photocatalytic
mechanism, the Ag/ZnO degradation of Famotidine
under UV light irradiation could be attributed to theoxidization by •O2−, •OH and h+ radicals. Moreover,the •O2− radical was the main reactive species in thephotodegradation process.

0.8

Dark

C/C0

0.6
0.4

AA

0.2
0.0

TBA

‐15
‐30

0

15

30

45

Time (min)

60

75

90

Fig. 4 Effects of different radical scavengers on thephotocatalytic degradation of Famotidine with
Ag/ZnO under UV light irradiation.

ACKNOWLEDGEMENTS
The present research was partly supported by
Grant-in-Aid for Scientific Research (C) 15K00602
from the Ministry of Education, Culture, Sports,
Science, and Technology of Japan. All experiments
were conducted at Mie University.

Mechanism
A plausible photocatalytic mechanism for the
degradation of FMT in the presence of Ag/ZnO
photocatalyst under UV light is illustrated in Fig. 5.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ACCELERATING METHANE PRODUCT IN REACTION OF
METHANOGENS ARCHAEA WITH COAL IN MUARA ENIM
FORMATION
Ildo Muhary Putra, Muhammad Ihsan , T.J.L Tobing, Dio Rizqi Irawan, D.A.A. Putri
Geological Engineering, Sriwijaya University, Indonesia
ABSTRACT
Coal bed methane (CBM ) is one of prospectus of renewable energy in the future , due to the many countries hadcoal deposit in the world. Indonesia has many potential deposit of coal and one of them is situated in South
Sumatra with 183 tcf total potential. In 2025 Indonesia focuses to increase the invention and applicator of new
and renewable energies until 17 % from total energy consumption. Therefore, exploration research were neededin order to enhance information related. Low volatile bituminous coal were selected due to its ability sa sourcerock for CBM. In this experiments, coal were mixed with methanogens from rumen liquid to initiate its reaction
on methane gas production. Coal sample were collected from Muare enim Formation, South Sumatera Basin,Indonesia. The coal, cattle rumen fluid and various water condition (fresh, brackish, and saline) were mixed into
in vitro bottle culture by 1:4:5 proportions and incubated in 340C for 30 days. Gas production and CH4
concentration were collected every 5 days using gas gas springe and analyzed its composition by gas
chromatography (GC) technique. The data tabulated and processed in descriptive statistics . The result showedthat CBM generated from anaerobically fermentation were optimally obtained from brackish water.
Keywords: Coal Bed Methane (CBM), Bituminous Coal, Methanogens Archaea, Gas Chromatography (GC)southwest with distance between Palembang is 149
km. Sample location in pit of economical mining
This research focus into a coal sample in prospectseam which collected and analyses and react
biologically to increasing the quantity of methane.

INTRODUCTION
The Exploitation of CBM was occured in several
country and successes to exploitation like USA,
Canada, China, and other. This is causing theintensive research in related aspect with thisresources , In Indonesia there are many basin that
contain potential Methane gas as CBM , but stillneed the further related research. Coal Seam Gas(CSG) or Coal Bed Methane (CBM) has several
dangerous in working coal mines and causing thegreenhouse gas. Nevertheless it is source of energy
in the place contains coal as the source rock andreservoir. One of it , using biological processing
with methanogens bacteria. This processing wasdemonstrated in the early 1980s and now thisresearch moving toward and apply in every coalfrom basin in Indonesia. The research has to do inenhancement coal bad methane in biological
technique at Indonesia such as the coal sample from
East Kalimantan by [1] that showed in the result is
fit temperature for make sure the biological enhancecoal bed methane optimally. So with [2] explanation
the mechanism in forming of CBM for involving
methanogens bacteria in laboratory experiment. The
detail of coal analysis from coal rank, geochemical,
and geology. In Indonesia showing the highpotential to produce CBM.
Research location that contain sample of coal inSouth Sumatra Basin, Muara enim Formation, In
administration the site in Lahat regency toward to

Fig.1 (a) Research area in South Sumatera basin and(b) Using seam B for research object
The aim of this research :a. To prove the activity of methanogens archaea inorder to produce coal bed methane withlaboratory experiment.
b. To obtain the best water salinity condition to get
the optimum production of CBM with several
process of methanogen by using cow rumen.

939

GEOMATE - Mie, Japan, Nov. 21-24, 2017

AN OVERVIEW OF COAL GEOLOGYCBM Controls
Muara Enim Formation

The level or rank of coal from thermal maturity
describe as the moisture of coal , vitrinite reflectanceand another measuring. Entity from gas can be saveinto coal as fit as the coal rank. The porosity of coalseam characteristic by two things. There are welldefined and almost uniformly distributed network ofnatural fracture (cleats) and a coal matrix containinga highly heterogeneous porous structure between thecleats (coal bed reservoirs and their Co2
sequestration).
Coal bed methane forming in several process incoalification there are changing vegetation inchemical until become coal
involvingtransformation biology complex and molecule
structure in cell into chemical fragment. The productin this production sorption into high pressure coal.
In geometry CBM came from geology andbiology processes during million of years or geology
time scale. This process change the vegetation into
several rank of coal with characteristic each other(Fig.4) such as lignite sub bituminous-bituminousantracite-graphite.

According to [3] the South Sumatera basin is the
big basin with Central Sumatra basin and identify byeach sediment rock and separate by Tigapuluh
mountain. The focus of research is toward Muara
enim formation from late Miocene until Pliocene(10.2-1.65 Million years ago). From the calculationby [4] there are gas potential amount of 183 tcf inthis formation. Muara enim formation have 18 coalseams but not all of it so important and named. A
few of this coal bed are thin and not widely
continuous with low rate economical to be mine.
The significant layer gives an important status,
Keladi layer as base of Muara enim formation.
Shallower layer is niNu with top border in Muara
enim formation. Middle layer from base of Muara
enim formation there are Petai, Suban, Mangus,
Burung, Benuang, Kebon, Babat/Benakat and Enim.
In this area the Niru and Lematang layer is notdeveloped. Mangus ,Suban, and Petai are splitted in
two, which named upper (A1) and lower (A2) of
Mangus seam , Upper (B1) and lower (A2) Suban
seams and upper (C1) and lower (C2) Petai seams(Fig.3). The common nomenclature using A1, A2,
B1, B2, C1, C2. The thickness of this formation is450-750 meters [5]. In general the depositional
environment are from tropical delta

Fig. 3 Stratigraphy Muara enim formation as coal bearing formation [6]940GEOMATE - Mie, Japan, Nov. 21-24, 2017

fungi, methanogenic , archaea, and bacteriofag tohelp variation function in microbial ecosystem [7].
There are three main substrate to produce
methanogens ; CO2, the materials compound that
produce metyl group or acetate [8]. Archae canadapt in many anaerobic environment, it can befound in the rumen gastrointertinal tract ofruminants.
Using Indicator Total Dissolve Solid (TDS) that
contain of water with classification in many salinity,
Fresh (0-1.000 ppm), brackish (1,000-10.000 ppm),
saline (10.000-100.000) and brine (more than
100.000 ppm) [9]. In this research is using fresh,
brackish and saline condition water salinity.

Fig.4 Coal rank [5]Tabel 1. Proximate and Maceral Analysis

MATERIALS & METHOD
Component

Value

RemarkTotal Moisture
Inherent
Moisture

16.12

Proximate

8.14

Analysis

Ash Content
Volatile Matter
Fixed Carbon
Total Sulfur
Calory Value
Ar
Adb
Daf

From many seams in Muara enim formation, we arechoosing Suban seam which knowing as B seam.
The Information from primary by collected in fieldsite and laboratory analysis, and secondary datafrom literature in any reference. To understanding
the characteristic of coal is needed to determine bygeochemistry test by proximate and maceral test.
Coal collect by channel sampling where to do it
must in fresh layer and get in three point, top bottom
and middle, then mix equally. The coal getting crush
into powder using hammer, then getting heat in theoven with temperature 1500C for 10 Minutes todecrease the moisture of coal/ The rumen liquid getfrom cattle from animal husbandry and filtering it
using gauze to hold the another macro substrate,
adding water conditions (fresh, brackish and salty)
with proportions 1:4:5. Incubated with incubatorwith temperature 340C because the optimum
temperature for in vitro reaction in batch culture
according [1] pretend in 30 days and take the gas
contain every 5 days using venoject capsule before
laboratory analysis with chromatography gas.
In this occupation gas chromatography candetermine the volume of quantity gas , so can readthe CH4 content.
Processes to forming Coal bed methane frommassive coal related with fermentation. Occur inthree degradation steps :1. Hydrolisis process
p process from long chain compound into shortchain compound with ingredient mass. This biomass
such as cellulose, hemiselulose and other extractive
product like protein, carbohydrate and lipid. This
process involving the extracellular enzyme activity,
there are Celolitic, amylase protease and lipase. Thisis occur while polisacaride became monosacaride
and protein become peptide and amino acid [2]2. Acidic Process
Present of bacteria producing acid which changing

5.61
43.6
42.65
0.23
5976.24

RD
ID

6556.47519.26
1.31
1.27

HGI

58.5

Vitrinite
Liptinite
Inertinite

90.40%
4.21%
3.28%

Other Minerals

2.04%

MaceralAnalysisUsing low volatile bituminous coal, there are fit
capacity to save the CBM as adsorbent function
Methanogens Archaea
Methanogens is a different group in organism
which can be found in anaerobic environment, forexample in mud accumulation, plant trees, rumen
and black mud sediment. Methane is metabolism
organic product which using carbon dioxide andhydrogen. In methanogenesys process with using
Co2 and H2 for digest the organic material andconvert into methane gas in anaerobic condition
under the land. With the infiltration by protozoa,
941

GEOMATE - Mie, Japan, Nov. 21-24, 2017

the organic molecule complex like protein becameamino acids, carbohydrate became simple compound
like sugar, fat became length chain of acid and thendivided into volatile fatty acid (VFA) as shown in(Fig.5). The fermentation of carbon dioxide
producing VFA as main product for energy
resources. So the use of Carbon for growth andretain the life living of organism community [2]3. Methanogenesis process
With the aim to produce methane using acidic ion
process which using Co2 and H2 to produce
methane gas. Decomposition of Acid organic
substance by methanogenic bacteria to produce Ch2
into two ways. First, with fermentation acetate acidbecame methane and Co2 as shown in (Fig.6).
Second, with reduction of Co2 became methane
using hydrogen gas of acid that producing fromanother bacteria [2].

medium production in fresh water and minimum
product CBM by saline water. The ability of thisbacteria to adapt in fit salinity water condition andthen expand to produce with his function as
producer methane with some reaction in matrix ofcoal and not fit with brine water to adapt andproducing methane gas.
From plotting at laboratory analysis graph ,showing the plots of fluctuated or CBM producing
top production is in the 20 days and then decreasingin time but it still producing some CH4 , we can see
in Fig. (7). According research before in [2] using 34
0C temperature degree which the best condition
which able for ruminal bacteria to live, growth andproduce in Microcosm jar and to resist the
enzymatic structure from bacteria.

Fig. 7 The Quantity of methane according gas
chromatography
The phases that happened in graphic:

Fig. 5 Protein degradation in rumen

1.

Lag phaseWith observation in under batch condition
growing is zero. Log phase defined as transmission
to exponential phase whereas first population had
double itself [10]. There are adaptation phase fromcell in culture condition. The length of this phase isdepends on several factor because it control by
medium type, and initial inoculums size.
2.

Exponential phase
Observe in batch system in exponential phase.
Characterize by the raised growth, because thedevelopment is too fast which makes it able to
growth in batch culture. During this phase,accelerating of total amount of cells is increasing
according the time . This conditions can be explain
by progression geometric theory 20.21,22,23,……2n.

Fig. 6 Cellulose fermentation until producing
VFA and CH4
To get the methane gas as product in anaerobic
reaction is needed the activity any renic creature like
protozoa, fungi, methanogenic, bacteriofag together
for chemical reaction and biological process in batch
culture.

3.

Dead phase
Characterized by losing the cell that culturingcondition, although the dead of many cell in
condition, some bacteria still doing metabolism andgrowing to produce the methane product.

RESULT & DISCUSSION
ResultIt’s clearly that the path of graph show the top
production in water salinity condition of brackish,942

GEOMATE - Mie, Japan, Nov. 21-24, 2017of theIndonesia Petroleum Association, Fourth
Annual Convention[4] Balkin HE, et al. “Geochemistry and Petrology
of Selected coal Samples from Sumatera ,Kalimantan, Sulawesi , and Papua, Indonesia”.
International Journal of Coal Geology 77( 2009 ) 260-268.
[5] Stevens SH & Sani K, “Coalbed methane
potential of Indonesia: preliminary evaluation ofa new natural gas source”, Proceedings ofIndonesian Petroleum Association, IPA01-G063, 2001, pp. 727-738.
[6] Endar BB, Nurhandoko, et al,”Rock Physics
Study of Coal Bed Methane Reservoir Rock:Case Study of Muara enim Coal, Proceedings ofIndonesian Petroleum Association , IPA12-G157,2012.
[7] Morgavi DP, et al.”Microbial Ecosystem andMethanogenesis in Ruminants”. Animal (2010 )
4:7, pp1024-1036 The Animal Consortium 2010
doi:10.1017/S1751731110000546.
[8] Liu Y & Whitman WB, Methabolic,phylogenetic, and ecological diversity of themethanogenic archea. Annals of the New York
Academic of Science 1125,171-189.
[9] Gorrel HA 1958. Classification of Formation
Waters Based on Sodium Chloride Content,
Bull. American Association of Petroleum
Geologists, vol 42., p. 2513
[10] Yates G T , and Smotzer T ( 2007 ) On the lagphase and initial decline of microbial growth
curves . J. Theoret. Biol. 244 , 511 – 517 .
[11] Strapoc D, et al, “Methanogenic Microbial
Degradation of Organic Matter in Indiana Coal
Beds. AAPG Annaul Convention, San Antonio,
Texas, April 20-23 , 2008.
[12] Bahrani A, et al, ”Coalbed methane reservoirs
and their Co2 sequesteration potential”,
International of Oil, Gas, Petrochemical andPower Plant.
[13] Candra A”Potential Evaluation of Coal Bed
Methana Based on the Grade and Quantity of
The Coal In the Mangus Seam, Muara enim
Formation, Nibung Region, South Sumatera
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[14] Doefert BN, et al.”Methanolobus zinderi sp.
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Discussion
There are many prospect seams in Muara enim
formation that can be analysis and syntheses withmicrobial process to accelerating methane product incoal. Concern with several aspect such as thickness,quantity, outcrop condition and other. Hope the next
research get more valuable data with the diversity
seams an can be show for consideration.
Conclusion
This research using the laboratory analysis inanaerobic reaction the coal, rumen liquid and adding
diversity of water formations (fresh, brackish andsaline) and to make the result equally in chart to findthe maximum condition in producing coal bed
methane (CBM) in microcosm environment can be
the initiator before application in large scale system[11]. In this capacity to producing its gas withseveral mechanism with biological enhance coal bed
methane is able for accelerate quantity of methanegas and other gas product with change the substrate
in anaerobic condition. Naturally the forming of coalhappened in wet environment and calm watercondition. Nevertheless there are some factor the
influence the conversion microbial bacterial intomethane gas, there are salinity, PH, nutrition, trace
metal and coal surface area/bioavailability. Thismethod can be pioneer in develop the new andrenewable resources as mix energy that happened in
microbiology process.
ACKNOWLEDGEMENTS
Thanks for participation pertner from association of
Geological Engineering. This research opportunityfrom facilitation gives to us by Arfan abrar PHD inanimal feed and nutrition laboratory,
AnimalScience, Sriwijaya
University with assistantlaboratory. For the moral value, supporting, andcorrection by Steve nalendra and proof reading by
Ardiansyah.
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[22] Pratiwi R, et al,”Structural Geology And
Tectonism Influence in Predicting Coalbed
Methane Potential of Seam Pangandang-A, In‘DIPA’
Field,South
Sumatera
Basin”.Proceedings of Indonesian Petroleum
Association, IPA14-G-247.
[20] Pujibroto A,”Organic Petrology andGeochemistry of Bukit Asam Coal, South
Sumatera, Indonesia”. Research Online
University of Wollongong thesis Collections.
[21] Rifai, 2010.”Efect of Sellolitic Bacteria Isolate
from Buffalo’s rumen in Diverent woof”.
Minithesis, Husbandary Faculty, Bogor
agriculture Institute (in Bahasa Indonesia).
[22] Schlumberger,2009 Oilfiled Review
Summer:21 , no.2.
[23] Wattimury PS, Amijaya, H, Hafsari, SW, ”A
Modelling of Co2 Injection Based on Sensitivity
Study To Improve The Coal Bed Methane(CBM) Production Profile In ‘RAY’ Field ,South Sumatera Basin Indonesia. IPA
ProceedingsofIndonesianPetroleum
Association , IPA13-E-006.
[24] Zieminski K, & Frac M,”Methane Fermentation
Processes as Anaerobic Digestion of Biomass:
Transformations, Stages and Microorganisms.
African Journal of Biotechnology Vol.11(18),pp.4127-4139,
1
March
2012.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

A POST-LIQUEFACTION STUDY
AFTER THE 2014 CHIANG RAI EARTHQUAKEAT TUNG-FAH-PAH VILLEGE IN CHIANG RAI, THAILAND

Sethapong Sethabouppha1, Suriyah Tongmunee2, Chollachai Kamtawai3and Jittanan Kawilanan4
1,2Faculty Members; 3,4Graduate Students, Department of Civil Engineering,
Chiang Mai University, Thailand
ABSTRACT
A post-liquefaction study at a remote village was conducted after the 6.3 ML 2014 Chiang Rai Earthquake.
Site surveying, aerial map study, standard penetration test were conducted and found that the subsoil at this site
was easily liquefied because the village was lying within abandon river channel with very loose sand layer fromthe depth of approximately 1.5 to 6 meters underneath the cohesive soil at the surface. Four liquefaction potential
assessment methods commonly used in the United States and in Japan were examined. The calculation revealed
that all four method yield slightly different factor of safety against liquefaction but can still be considered
reliable. The calculation also showed that this site can still be re-liquefied if a strong earthquake strikes again.
Keywords: Earthquake, Soil Liquefaction, Post-Liquefaction Evaluation, Liquefaction Potential, Liquefaction
Susceptibility
occurred frequently. Within the area of Chiang Rai
Province, there are four groups of active faults
almost all over the area. Mae Chan - Chiang Saen
Fault is the one that most people are concerned
about because there was a tale that very strong
earthquakes occurred at night causing an ancient cityof Yonok to become submerged underground(possibly by liquefaction phenomena). There is anevidence of a large lake in Chiang Saen District
supporting that this tale was possibly true.

INTRODUCTION
The 6.3 ML earthquake [1] which struck Chiang
Rai Province (the northern-most province ofThailand - Figure 1) in the evening of May 5, 2014
was the first one that caused soil liquefaction in the
recent history of earthquakes in Thailand. Soil
Liquefaction has never been a significant issue in the
country’s earthquake concern since mostearthquakes in this country were relatively small.
Since that day, it is believed that stronger
earthquakes are possible in the future. Learning
about soil liquefaction starting with its affecting
factors and potential assessment are important. It is
the first step toward preventing liquefaction
damages.
Learning from a case history is one of the mosteffective ways. Thus, a study was conducted in orderto achieve two main objectives:
1) Understanding the conditions of factors
affecting soil liquefaction at a selected sitewhich liquefaction occurred during the
Chiang Rai Earthquake in 2014.
2) Finding the most appropriate method toassess liquefaction potential in Thailand forthe future.

Kingdom ofThailandTHE 2014 CHIANG RAI EARTHQUAKEAs previously described in the introduction,
Chiang Rai is a province located at the most
northern point of Thailand. To the north are
Myanmar and Laos where strong earthquakes

Figure 1 the location of Chiang Rai Province.
(https://th.wikipedia.org)
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GEOMATE-Mie, Japan, Nov. 21-24, 2017

epicenter.
Mae Chan – Chiang Saen Faults

Upper Payao Faults

Chiang Rai City

Epicenter
Mae Ing Faults

Epicenter of the 2017 Earthquake

Tung-Fah-Pah Village

Lower Payao Faults
Lower Payao Faults

Figure 3 Location of Tung-Fah-Pah Village and theepicenter of the 2014 Chiang Rai Earthquake.
(modified from www.google.com)

Mae Tha Faults

Figure 2 Chiang Rai Province and active faults.
(modified from www.dmr.go.th)

Evidences of Soil Liquefaction
There were plenty of evidences indicating thatliquefaction occurred here in the village as shown in
the following figures.

As seen in the figure, there are four active faults
lying all over the area. Therefore, preparing forearthquake in the future is necessary. Preparation
activities should include liquefaction study.
THE STUDY PROGRAM
The study of earthquake-induced liquefaction has
just been around 50-60 years. However, it is widely
known that there are three major factors affecting
the phenomenon: soil type of sand, saturation of thesand layer, and strong vibration. It was interesting to
see the combination of these three factors atliquefaction sites.
To obtain the answer and conclusion for theobjectives indicated above, a program of study was
designed that a study should be conducted at aliquefaction site. The study should include threemain activities.
1) Site visit for investigating evidences ofliquefaction and the environment suitable forliquefaction to occur,2) Subsoil investigation by standard penetration
test (SPT) to obtained the soil type and density; and3) verifying liquefaction potential assessment
methods.

(a)(b)

Figure 4 (a) Ground cracking occurred all over thevillage (this picture was taken at the primary schoolof the village,) (b) Pure sand appeared at the bottomof the cracks.

SELECTED SITE: TUNG-FAH-PAH VILLAGE
Tung-Fah-Pah Village is located approximately
25 km southwest of the epicenter of the 2014 Chiang
Rai Earthquake as shown in Figure 3. Mostliquefaction sites caused by this earthquake were
within 15 km around the epicenter.
The reason for selecting this village as the casestudy site was that this is the farthest site ofliquefaction caused by this earthquake. Mostliquefaction sites were within 15 km from the

Figure 5 Fine sand ejected through ground cracks.
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GEOMATE-Mie, Japan, Nov. 21-24, 2017

located within 3 meters from the wells filled with theinjected sand. Borehole BH-4 was at the primaryschool front yard (see Figure 12 for their locations).
Figure 9 demonstrates SPT N-values, and Figure 10
shows the grain size distributions of the soil sample
taken from the boreholes.
All 4 SPT boreholes yield very identical soil
layers. The top layer was cohesive soil from theground surface down to the depth of approximately
1.2 m, the gravel layer was from approximately 6-7
m downward, between top cohesive soil layer andthe gravel layer was a layer of loose to medium sandwhich was expected to undergo liquefaction. (Theliquefaction analysis will be shown later.)
(a)

(b)

Figure 6 (a) Sand ejected through the joints ofconcrete pavement, (b) Separation of a wall madefrom interlocking bricks due to ground settlement.

Cohesive Soil Layer

Layer of Loose Sand

Layer of Gravels

Figure 9 SPT N-values from all 4 boreholes.
An interesting finding obtained from the SPT
investigation was the sand taken from the liquefied
layer has “gap-graded” distribution as shown in
Figure 10. However, when look at Figure 11 whichshows the grain size distribution of the fine sandfound on the ground (Figure 4) and in those wells(Figure 8) it shows that these injected sand particles
may be those missing from the curves shown in
Figure 10. This means sand particles of a certain size
were ejected from the liquefied loose sand layer.

Figure 7 Liquefies sand was ejected from the bed ofthis pond like a fountain of about 3-meter high (frominterviewing an eye-witness.)

Liquefiable
Soil Samples

Figure 8 Sand injected into wells of several houses
replacing the groundwater.

Potentially Liquefiable

STANDARD PENETRATION TEST
After the first site visit, standard penetration
test (SPT) was conducted at four locations in thevillage. Boreholes marked as BH-2, BH-3, and BH-5

Figure 10 Grain size distribution of the sand samples
taken from boreholes by SPT sampler.
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GEOMATE-Mie, Japan, Nov. 21-24, 2017

significant sign of liquefaction. This issue can beeasily explained by 1) an aerial photo of the village’s
landscape as shown in Figure 12. The village wassituated in the area with traces of abandoned rivers
which can be liquefied easily [2], especially a groupof houses was in the area of a so called “the island”
which indicates that it was surrounded by water, 2)
the sand layer should be saturated when earthquake
struck because the groundwater at the time of theearthquake was at only 1.0-1.2 m below the groundsurface and the area around the village wall filledwith water as the farmer grew their off-season rice
farm, 3) the distance of approximately 25 km fromthe epicenter was not surprise because this conforms
to Figure 13 showing the earthquake of 6.3 Richter’smagnitude can cause liquefaction at sites farther than
25 km, and 4) at this distance the peak groundacceleration was still high enough assuming thisearthquake conformed to the relationship shown in
Figure 14.

Sand sample from the ground
Sand sample from the wellFigure 11 Grain size distribution of the sand foundon the ground in Figure 4 and found in the well in
Figure 8.
SITE ANALYSIS
There is another issue that should be addressedin this study. It was very interesting to find out why
this site liquefied easily while other villages nearby
and within closer distances did not have any

BH-2

Existing River

Abandon River
BH-5

The “Island”
BH-3
BH-4
The Primary
SchoolFigure 12 Aerial view of Tung-Fah-Pah Village. (modified from www.google.com)

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GEOMATE-Mie, Japan, Nov. 21-24, 2017

Figure 13 Maximum distance from epicenters toliquefaction sites. [3]Figure 14 Relationship between peak groundacceleration versus distance from earthquake
epicenter. [7]

LIQUEFACTION POTENTIAL EVALUATION
Due to the availability of SPT test the following
methods of liquefaction potential evaluation werestudied.
1. Method proposed by NCEER 1996 [4]. Thismethod was modified from the original Seedand Idriss’ method first proposed in 1971.
2. Method proposed by Boulanger and Idriss in2014 [5]. This method has been modified
from the prior with some correcting factors.
3. Method proposed by Iwasaki in 1990 [6].
This one was the most commonly used inJapan as it appears in the Japanese Highway
Bridge Code. The method relies heavily on
D50 of the subsoil particles which can beobtained from grain size distribution curves.
4. Method proposed by Iwasaki in 1996 which
has been revised from the 1990 version byadding the effect of SPT N-value [6].

ResultFigure 15, 16, 17 and 18 show values of thefactor of safety against liquefaction of soil layers at
BH-2, BH-3, BH-4 and BH-5, respectively.
Following are the analysis of the results.
1) Those four methods are reasonably reliable
since all of them indicated liquefaction had
occurred. In these figures, some factor ofsafety numbers shown here are slightly morethan 1.0 because they were calculated byusing post-liquefaction SPT surveying.
2) Those three methods other than Iwasaki
version 1990 yielded very close factor ofsafety values except when the SPT N-values
reached 20 (see Figure 16 and 17 at theelevation below -3.5 m along with SPT Nvalues in Figure 9).

Those four methods are similar in the stressbased approach but the major differences between
them are criteria, equations, correcting factors andsome input data. Details of those four methods canbe found in the indicated references.
Another important factor was the groundacceleration at the site. For this study, there was no
ground acceleration record available. Therefore, therelationship between peak acceleration versus
epicenter distance as shown in Figure 14 should be
helpful. From the distance of about 25 km, groundacceleration of 0.15g, 0.20g, and 0.25g were used in
the calculation.
Figure 15 Factor of safety against liquefaction, BH-2
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GEOMATE-Mie, Japan, Nov. 21-24, 2017

situated on the area of abandoned rivers
with loose sand layer at a shallow depth of
1.2 m. The soil was saturated because therice field was filled with water and it
rained a lot before the earthquake.
2) Among those four, Iwasaki’s method
version 1990 was the most conservative
while the 2014 Boulanger and Idriss’
method may be more reasonable.
ACKNOWLEDGEMENTS
The authors would like to express theappreciation to Chiang Mai University and theGovernment Office at Chiang Rai for the researchfunding.

Figure 16 Factor of safety against liquefaction, BH-3

REFERENCES[1] Thai Meteorological Department, “Report on
the 2014 Chiang Rai Earthquake” (in Thai),available at http://www.earthquake.tmd.go.th.
[2] Wakamatsu, K., “Evaluation of Liquefaction
Susceptibility Based on Detailed
Geomorphological Classification”. Proc.,
Technical Papers of Annual Meeting,Architectural Institute of Japan, B, 1992,
pp.1443-1444.
[3] Towhata,
I.,
Geotechnical
Earthquake
Engineering, Verlag Berlin Heidenburg:
Springer, 2008.
[4] Youd, T. L., & Idriss, I. M., “ Liquefaction
Resistance of Soils: summary report from the1996 NCEER and 1998 NCEER/NSF
Workshops on Evaluation of Liquefaction
Resistance of soils. Geotechnical andGeoenvironmental Engineering, 2001, 127(4),297-313.
[5] Boulanger, R. W., and Idriss, I. M., CPT AND
SPT Based Liquefaction Triggering Procedure,
Davis: University of California, 2014.
[6] TechnicalCommittee
forEarthquake
Geotechnical Engineering, T., ISSMGE.
“Manual for Zonation on Seismic GeotechnicalHazards” (Revised Version): The Japanese
Geotechnical Society, 1999.
[7] Joyner, W.B., and Boore, D.M., Recent“Developments in Strong-motion Attenuation
Relationships”, UJNR 28th Joint Meeting of
United States-Japan Panel on Wind and Seismic
Effects, NIST SP904, Gaithersburg, 1996,
pp.101-115.

Figure 17 Factor of safety against liquefaction, BH-4

Figure 18 Factor of safety against liquefaction, BH-5
CONCLUSION
Two main conclusions can be made from thisstudy.
1) The site of Tung-Fah-Pah Village was
perfect for liquefaction. The village was950

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan,Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PRESENCE STATE OF TRACE ELEMENTS IN THE OHTAKIGAWA
RIVER WATERSHED FROM THE FOOT OF Mt. ONTAKE*Akiko Usami1, Megumi Nobori2, Akihiko Yagi1, Eiji Iwatsuki1
1

Faculty of Engineering Aichi Institute of Technology (AIT), JAPAN,
2
Mie Prefectural Center of Constructional Technology, JAPANABSTRACTThis paper is aimed at understanding the influence of Mt. Ontake volcanic activity on the water quality of the
Ohtakigawa River watershed. For this purpose, various properties of trace elements are investigated. The
Ohtakigawa, which flows along the southern foot of Mt. Ontake, has several tributaries such as Nigorigawa
River, Shirakawa River, Shimokurosawa River, and Uguigawa River. Seven sampling stations were selectedin the four tributaries (four points) and the Ohtakigawa (three points). Filtration of samples was carried out
with teflon filter paper (PTFE, 0.5μm, φ 47mm), and the samples were separated into dissolved and suspended
matters. Trace elements contained in them were analyzed by using the ICPE. The concentrations of the traceelements were high in the following order: the Nigorigawa (6.16mg L-1), the Ohtakigawa after the confluenceof the Nigorigawa (1.92mg L-1 and 0.88mg L-1), and the others (0.06-0.70mg L-1). This result indicates thatamong the four tributaries, the Nigorigawa plays a predominant role for the change in the water quality of the
Ohtakigawa.
Keywords: trace elements, Mt. Ontake, volcanic activity, Ontake Landslide, Ohtakigawa River watershed
and change their water quality and biota. The
Ohtakigawa River flows on the southern side of Mt.
Ontake and is strongly influenced by volcanic
eruptions. The river has many tributaries (Fig. 1).
The Nigorigawa River, which is one of thetributaries of the Ohtakigawa, remarkably differs in
pH, electric conductivity, and biota from othertributaries [1], [2]. The water quality of the
Ohtakigawa changes at the junction with the
Nigorigawa [3], [4].

INTRODUCTION
Mt. Ontake (altitude 3,076m) is located acrossNagano Prefecture and Gifu Prefecture. Mt. Ontake
often has shown large volcanic activities since theprehistoric age. Recently the Western Nagano
Prefecture earthquake (M6.8) occurred on
September 14, 1984, and the volcano erupted on
September 27, 2014.
Volcanic activities affect surrounding rivers

N

Mt. Ontake

Miure dam

Ohtakigawa 2
Ohtakigawa 1
Ohtakigawa 35km

Fig. 1 Map of the locations of sampling stations in the Ohtakigawa watershed.

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International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

example, the concentration of Al is 0.70mg L-1 at
the Ohtakigawa 1 station, 1.92mg L-1 at the
Ohtakigawa 2 station, 0.88mg L-1 at the Ohtakigawa
3 station. In the tributaries, it is 6.16mg L-1 at the
Nigorigawa station and 0.06-0.10mg L-1 at thestations of the other tributaries.
In addition, the concentration of S, which has
the influence on the change in pH, is observed. The
S concentration is 4µg L-1 at the Ohtakigawa 1station, 30µg L-1 at the Ohtakigawa 2 station, 20µg
L-1 at the Ohtakigawa 3 station, 83µg L-1 at the
Nigorigawa station, and 0-1µg L-1 at the otherstations, and it is observed that pH is low (5.4-6.0)
at the Nigorigawa, the Ohtakigawa 2, and the
Ohtakigawa 3 stations and is high (6.4-6.8) at theother stations. Therefore, it is confirmed that
sulfuric acid causes the lowering in pH in the
Nigorigawa and in the Ohtakigawa after the
confluence of the Nigorigawa.
Next, the component compositions at the sevenstations are investigated. Figure 3 shows the rates of
the trace elements at the sampling stations. At the
Ohtakigawa 1, the Shirakawa, the Shimokurosawa,and the Uguigawa stations, Si (37-47%), Ca (1826%), and Na (11-23%) are the main components.
As minor components, Al, Fe, and Mn account for
1-5%, 5-15%, and 0-1%, respectively. At the
Nigorigawa, the Ohtakigawa 2, and the Ohtakigawa
3 stations, the rate of Si (16-25%) decreases
compared with that at the above four stations.
However the rates of Ca (17-22%) and Na (17-18%)
show hardly change. By contrast, the rates of Al, Fe,
and Mn increase to 3-5%, 22-31%, and 6-7%,
respectively.
It is on the confluence point with Nigorigawa
that the rates of Al, Fe, and Mn drastically increase.
Therefore, it has been clarified that the water quality
in the Ohtakigawa is affected dominantly by the
Nigorigawa newly from analyzing the component
compositions.
Finally, the maintenance process of dissolved
matters is explained. In many circumstances, Al, Fe,
and Mn exist as suspended matters, since they havea low redox potential. In this investigation, however,at the three stations which show high concentrationsin Fig. 2, namely, at the Nigorigawa, theOhtakigawa 2, and the Ohtakigawa 3 stations, Al,
Fe, and Mn are detected mainly as dissolved matters.
The dissolved oxygen level is 90-92%, quite high,thus clearly the water of the three stations is notunder the reduction state. In contrast, pH indicates
low values (5.4-6.0) at the three stations. Thereby itis found that the dissolved matters are maintainedby the acidic environment.

It is one of the most important topics to provide
useful information to recover the river environment
damaged owing to the influence of the volcanic
eruption. In this paper, we investigate traceelements in water of the Ohtakigawa and tributariesof the Ohtakigawa to clarify the formation processof water quality of the Ohtakigawa.
METHODS
Study site
Figure 1 shows a map of sampling stations. We
select seven stations as the sampling stations. They
consists of four stations for the tributaries of the
Ohtakigawa (the Shirakawa, Shimokurosawa,
Nigorigawa, and Uguigawa) and three stations for
the Ohtakigawa. We call the three stations in the
Ohtakigawa as the Ohtakigawa 1, Ohtakigawa 2,
and Ohtakigawa 3 stations, respectively. The
Ohtakigawa 1 station is located before the joiningof the Sirakawa, the Ohtakigawa 2 station is locatedafter the junction with the Nigorigawa, and the
Ohtakigawa 3 station is located after the confluenceof the Uguigawa.
Observations were conducted three times on
October 10 in 2015, September 17, and October 29
in 2016.
Sampling and analysis
Dissolved oxygen (DO)DO was measured by a DO meter (input
electrode type, fluorescence method, HACL Inc.,
turned electrode type).
Trace elements
Samples were filtered. Filtration was carried out
with teflon filter paper (PTFE, 0.5μm, φ 47mm),
and the samples were separated into dissolved andsuspended matters.
The filtrate samples were added to aqua regia(HNO3:HCl=1:3), and the suspended particle matteron the teflon filter was decomposed in aqua regia.
Trace elements contained in them are analyzed andnine element species: Na, Mg, Al, Si, S, K, Ca, Mn,
and Fe are measured by using the ICPE.
RESULTS
Figure 2 shows the concentrations of the nineelement species. They have the similar tendency
that the concentrations are high in the following
order: at the Nigorigawa, at the Ohtakigawa 2, at the
Ohtakigawa 3, and at the other stations. For
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International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

Fig. 2 Concentrations of suspended and dissolved trace elements at the sampling stations.

Fe are contained in the erupted materials [6]. Asami
et al. reported that owing to the erupted materials
injected into the river, pH was decreased to 2.5 [4].
This implies that the anomalous water quality in the
Nigorigawa has been formed by the erupted
materials.
Until now, only the dissolved matters of traceelements have been focused on. However,investigation on the precipitation of the traceelements is also an important issue, if the influenceof the erupted materials on biota is discussed in the
future. Trace elements are precipitated as pH
recovers to the neutral state. Now it is predicted thatthe precipitation of the trace elements already has
been accumulated in the Nigorigawa and

CONCLUSIONS AND DISCUSSION
In this work, it has been found that the
Nigorigawa and the Ohtakigawa after the junctionof the Nigorigawa have the anomalous water qualitythat the water is acidified, and the concentrations of
Al, Fe, and Mn as dissolved matters are high.
Consequently, it has been confirmed that the water
quality in the Ohtakigawa is significantly affectedby the Nigorigawa.
Now it is discussed that how the anomalous
water quality is formed in the Nigorigawa. Thereare enormous sediment of erupted materials in the
Nigorigawa basin [5], and large amounts of Al and953

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

Fig. 3 Rates of trace elements at the sampling stations.

Ohtakigawa. This prediction is based on thefollowing two facts. The one is that pH in the
Nigorigawa varies seasonally, as reported by Asami

et al. [4], and the other is that the acid water in the
Nigorigawa is clearly diluted by joining to the
Ohtakigawa. It would be one of the most important954

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

research topics to investigate in what way theprecipitation of the trace elements affects attachedorganism and organism feeding on it.

[2] Onoda Y. and Kayaba Y. “Comparison of fish
fauna in a river that received pyroclastic flowfrom the volcanic eruption of Mt. Ontake in2014 with that in neighboring rivers”,
Rikunomizu (Limnology in Tokai Region ofJapan), Vol.74, 2016, pp. 23-28.
[3] Taniguchi T. “Special feature: Effects of the2014 Mount Ontake eruption on inland waters”,
Rikunomizu (Limnology in Tokai Region ofJapan), Vol.74, 2016, pp. 1-3 (in Japanses).
[4] Asami K. et al. “A study on the water
environment of around Mt. Ontake after
eruption (140927) (5)”, Book of abstracts in
The Study Meeting of the Association ofJapanese Geographers Spring 2017, pp.
100107 (in Japanese).
[5] Kusano S. et al. “H26 Ontakesan hunka ni
tomonau nigorigawa ni okeru dosha idou jittai”,
JSECE (Japan Society of Erosion Control
Engineering) Publication No. 81, 2017, pp. B412-B-413.
[6] Yamada N. and Kobayashi T. “Geology of the
Ontakesan district. With Geological Sheet Map
at 1: 50,000”, Geological Survet of Japan,
136p., 1988, pp. 122-127 (in Japanese).

ACKNOWLEDGEMENTS
The authors thank Takashi TASHIRO of
Nagoya University, Tomomasa TANIGUTHI of
Mie University, Kentaro NOZAKI of Sugiyama
Jogakuen Univercity, Yoshitaka MATHUMOTO
of National Institute of Technology, Toyota College,
and Yukio ONODA of the Aqua Restoration
Research Center for cooperation in the field survey
and valuable suggestions. They thank students of
Aichi Institute of Technology for their helping inthis work. The analysis in this work is performed on“ICPE-9000” (SIMADZU) which supported by2012 Ministry of Education Private University
Research Facilities Maintenance costs subsidies.
REFERENCES[1] Nozaki K. “Autumn and winter periphyton
biomass in the Ohtakigawa River watershed 1
year after the 2014 eruption of Mount Ontake,central Japan”, Rikunomizu (Limnology inTokai Region of Japan), Vol.74, 2016, pp. 1321.

955

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

ASSESSMENT ON THE AEROSOLS VARIATION DURING THE
INTENSE HAZE EVENT OF JUNE 2013 OVER MALAYSIA BYUTILIZING THE SATELLITE REMOTE SENSING AND GROUNDBASED MEASUREMENT.
1,2

Nur Atiqah Aainaa Abd Latiff1, and Takashi Machimura2
Division of Sustainable Energy and Environmental Engineering,
Graduate school of Engineering, Osaka University

ABSTRACTThe rapidly occurrence of forest fires in Southeast Asia and associated biomass burning, has contributed
obviously to the problem of trans-boundary haze and the dispersion of pollutants in the region. Atmosphericpollutants, such as particulate matter in the atmosphere, have received extensive attention, mainly because of theiradverse effect on people’s health. In 2013, Malaysia experienced an intense haze episodes with high concentrationof aerosols were recorded and degrading the local air quality and reduce the visibility. This paper aim is to analyze
the spatio-temporal variation of aerosols concentration during intense haze event in 2013 over Malaysia by using
remote sensing data and ground-based measurement. The air quality data across Malaysia was assessed based on
PM10 concentration which provided by Malaysia Department of Environment (MDOE) and the spatial view ofaerosols optical depth (AOD) data from satellites (Terra Moderate-resolution Imaging Spectroradiometer(MODIS). The environmental parameters including temperature, rainfall, and wind speed were obtained fromNOAA’s National Climatic Data Center (NCDC) while an additional information about the occurrence of active
fires in surrounding region were retrieved from MODIS Active Fire Data was retrieved from NASA/LANCE –FIRMS. In June 2013, the PM10 value were recorded high in few stations over the Peninsular Malaysia with thehighest PM10 was recorded in the Bukit Rambai Station from 21st until 23rd of June with more than 400 µg/mᶟ.
Low wind speed and low mixing depth, together with the absence of rainfall persisted during this hazy condition.
The PM10 were began cleared with the increase of wind speed starting 26th of June with the rainfall also contributed
to disperse the haze from the atmosphere. The sources and destination of aerosols are identified via the HYSPLT
trajectory model, revealing that aerosols during June 2013 are mainly originated from the west and southwest area
(Sumatera, Indonesia).
Keywords: Haze, Air quality, Remote sensing, Aerosols, Malaysia
based measurement. Particularly emphasize on PM10
as the aerosols and pollutant indicator. Other
metrological parameters such as, surface wind speed
and direction, rainfall amount, hotspot, temperatureand visibility were also analyzed. Meanwhile,
HYSPLIT backward trajectories were assessed totack the pollutant transport during haze episode in
2013.

INTRODUCTION
Haze situation is generally defined as theexistence of fine particles with 0.1–1.0 l m indiameter range dispersed in highly concentrated
portion at the atmosphere which reducing thehorizontal visibility, giving the atmosphere acharacteristic opalescent appearance [1][2]. Thisparticles which are of respirable sizes, are of concern
because of their negative effect on health, as well as
their other environmental impacts [3][4][5][6].
In Malaysia, haze phenomenon have been
plaguing almost every year since 1980’s. The recent
haze event was in 2013 which severely weakened
regional horizontal visibility as thick smoke
blanketed Peninsular Malaysia and Singapore.
Extensive biomass burning from the land and forest
clearing process in some places in neighboring
country had resulting in trans-boundary haze which
degrading the air quality in Peninsular Malaysia[3][7][8][9][10]. Therefore, this study aimed toprovide a spatio-temporal assessment on aerosols
concentration during intense haze event in 2013 over
Malaysia by using remote sensing data and ground-

DATA AND METERIALSAir Quality and Metrological Data
Daily PM10 concentration for 2013 were acquired
from Malaysian Department of Environment(MDOE). Meanwhile, the metrological parameterssuch as rainfall amount, temperature, wind speed, andvisibility were gathered from NOAA’s National
Climatic Data Center (NCDC). Thirteen monitoring
stations were considered in this analysis of the aerosol
properties located all over Peninsular Malaysia andEast Malaysia (Fig. 1). The station locations represent
highly urbanised or industrialised areas (Kuching and
Sultan Abdul Aziz International Airport (SAAIA)),956

GEOMATE - Mie, Japan, Nov. 21-24, 2017

moderately urbanised/industrialised areas (Kota
Kinabalu, Setiawan, Bukit Rambai), high traffic areas(Johor Bahru), coastal areas (Sultan Ismail Petra
Airport (SIP), Kuantan, Tawau, Sandakan, Labuan)
and a rural/unurbanised site (Sibu, Limbang). Daily
mean composites of wind vector were computed over
the Southeast Asia region. In this region, it
strategically depicts the tropospheric flow patterns
where; it covers Malaysia and other neighboring
countries. The maps were constructed from
NCEP/NCAR Reanalysis Product developed by
NOAA-ESRL9

the level 2 data and it represent the first level of
MODIS aerosol retrieval. These data had beenrevised frequently and widely being used to retrieve
AOD with high accuracy of 0.05±0.2 [14][15].
RESULTS AND DISCUSSION
PM10 Variation in Malaysia during the 2013
Intense Haze
Daily PM10 concentration at 13 selected air quality
monitoring stations and the daily average of windspeed are presented in Fig. 2, from which can be seenthat the PM10 peak occurred in June 2013, whichstarted on 20th of June and keep increased until 25thof June 2013. The highest PM10 was recorded in the
Bukit Rambai Station from 21st until 23rd of June
(PM10 concentration more than 400 µg/mᶟ). PM10
concentration were also recorded high in few otherstations mainly over Peninsular Malaysia which are;
Bukit Rambai, Singapore, SAAIA and Setiawan. In
addition, high concentration of PM10 during thisperiod indicating high level of haze and air pollution
over Malaysia during the dry season in 2013. As beenshown in Fig.2, the haze episode were started fromthe southern region and move to the north ofPeninsular Malaysia. Besides that, the daily averagewind speed were recorded low and initially shown alow mixing depth in the atmosphere during the hazyperiod in June 2013.

.
Fig. 1 Map of the 13 monitoring stations over
Malaysia which the air quality and metreological data
were obtained.
Active Fire and Hotspot Data
In order to do the analysis on the occurrence ofactive fires in Sumatra, the active fire and hotspot
data were used and obtained from the Moderate
Resolution Imaging Spectroradiometer (MODIS)
from the Terra and Aqua satellite. MODIS Active
Fire Data acquired from the NASA/LANCE – FIRMS
website to monitor the distribution of hotspots within
the Sumatera area. A polygon area was outlined
which includes Riau (0° 32’ N, 101° 27’ E) and Jambi(1° 35’ S, 103° 36’ E) province in Sumatra. Only
hotspot counts with confidence level higher than 30%
were included in this study.
Aerosol Optical depth (AOD)
Aerosol Optical Depth (AOD) from Terra satellite
on Moderate-resolution Imaging Spectroradiometer(MODIS AOD) was used in this study to analyse thespatial distribution of aerosols during the haze
episode in 2013 over Malaysia. In general, the
MODIS aerosol data are retrieved twice daily; in themorning from MODIS on Terra platform and in theafternoon (on Aqua platform) at 10 x 10 km spatial
resolution [13]. Seven channels between 0.47 and2.13 µm (calibrated and geolocated reflectance level1B data) are used to retrieve aerosol properties[13][14]. AOD data that were used in this study wasFig. 2 Variation of PM10 concentration at 13
monitoring stations over Malaysia and the daily
average wind speed within three consecutive month(May until July) in 2013.
In the Fig. 3a) and 3b) illustrates the variation ofdaily surface wind speed and rainfall amount together
with the PM10 concentration for the period of May
until July 2013. The wind speed were relatively low
for each four stations within 20th of June until 25thof June 2013, while the daily temperature were957

GEOMATE - Mie, Japan, Nov. 21-24, 2017

increased up to 36.11oC with the absences of rainfall.
Hence, low wind speed with lack of rainfall which
introduced to low mixing depth that worsened thecondition during these intense haze episodes. The
persistent supply of haze particles from it sources
coupled with the surface inversion associated with thedry situation, light surface winds, and the nature of
the topography resulted in the haze particles being
trapped in Peninsular Malaysia.

lower surface pressure than southern hemisphere. The
pressure gradient is a consequence of the temperature
contrast between the northern and southernhemisphere due to seasonal variations. Moreover,during the haze period (June 2013) equatorial tradewinds above the western Pacific weakened to a lesser
extent. Since the effects of northeasterly trade winds
were offset by the stronger southwesterly monsoonal
flow, the northeasterly flow was essentiallysuppressed. The resulting southwesterly flow brought
relatively less rainfall from the Straits of Melaka to
the west coast of Peninsular Malaysia. Less rainfall in
the west coast and southern part of Malaysia resulted
in surging PM10 concentrations at this area.

a)

20 June 2013b)
21 June 201322 June 2013

Fig. 3 The daily variations at four selected stations
for a) PM10 concentration and surface wind speed,
and b) temperature and rainfall amount within May
until July
23 June 2013

The mixing depths and the wind speeds are
relatively low, which also indicate to inefficientventilation in the atmosphere. Thus, this condition
was intensified with high temperature and less rainfallthat may related with the southwest monsoon season.
As shown in the Fig. 4, the wind direction maps show
a weakening of the regional wind over Southeast Asia
mainly at Malaysia and Indonesia area from 20th until
24th of June 2013. Generally, the southwest monsoon
season flow was strengthened by a south to northpressure gradient, with northern hemisphere having a

24 June 2013

958

GEOMATE - Mie, Japan, Nov. 21-24, 2017

on 19th of June 2013, the meteorological effects were
not immediately shown on Peninsular Malaysia.
Long-range trans-boundary haze across the Straits ofMelaka was further delayed by lower southwesterly
wind speeds during the monsoon season. The
HYSPLIT backward trajectories in Fig. 6, shown thatthe polluted substance were brought up to Peninsular
Malaysia from 21st until 24th June 2013 were mainly
from Sumatera within 24 hours.

Fig. 4 Daily wind direction map at 10m overSoutheast Asia region for the period of 20th until 24thof June 2013.

a)
a)

b)

Fig. 5 The four day time average map of Terra
Modis AOD during the intense haze a) 18th – 21st June2013 and b) 22nd – 25th June 2013.
b)

Spatial distribution of AOD during the intense
haze in 2013 over Southeast Asia region weredisplayed in the Fig.5. The AOD distribution map
were plotted based on high PM10 concentration day
as shown in Fig. 2. Based on Fig. 5(a), the AOD
reaches maximum value particularly along theSumatera Island. According to previous study,
southwest monsoon will inducing wind circulationthat blow the wind from south to north which may
related to trans-boundary pollution happen during thisperiod [2][3]. As shown in Fig. 5(b) the AOD
distribution were moved towards Peninsular
Malaysia and South China Sea region. This finding isjustified by the result of that been presented in Fig.
6(b) the HYSPLIT trajectory model that ran during
the hazy period in June 2013.
According to MODIS satellite observation the
hotspot counts in Fig. 6 show a prominent peak on 19
June 2013 with more than 3000 hotspot were foundover Sumatera, Indonesia on that particular date. Thissituation can be attributed to the existence of biomassburning activity that occurred in the Riau Province
which had been reported by [1]. Therefore, biomassburning in surrounding area had indicate on theincreasing of PM10 concentration in Peninsular
Malaysia during June 2013 [9][10][11]. As thebiomass burning activities in Sumatra were detected

Fig. 6 a) The hotspot counts in Sumatera and PM10
concentration from May until July 2013 and b) 5 days
backward trajectories ending on 23rd of June 2013
which ends at the Bukit Rambai station. .
Impact of June 2013 Haze Episode on Malaysia
Visibility deprivation is a proxy measurement ofpolluted atmosphere. Poor visibility may cause by
scattering and absorption of solar radiation ofparticles and gaseous pollutants [4][5][6]. The
visibility in Malaysia were recorded poor during the20th until 25th of June 2013 as it dropped until less959

GEOMATE - Mie, Japan, Nov. 21-24, 2017

than 2 km compared to during non-polluted day withvisibility more 10km. Thus, these hazy condition has
given a huge impact toward the economy and healthcrisis to the surrounding community not only in
Malaysia but also in Singapore and Indonesia.

ACKNOWLEDGEMENTS
We would like to thank the Malaysian Department ofEnvironment for providing us a complete air quality
data for our further study on Malaysian environment.
We also gratefully acknowledge Moderate-resolution
Imaging Spectroradiometer (MODIS) Terra AOD
products data, NOAA’s National Climatic Data
Center (NCDC), MODIS Active Fire Data from
NASA/LANCE – FIRMS and the HYSPLT trajectorymodel that we used in this study.
REFERENCES[1] Malaysian Meteorological Service, “Report on
air quality in Malaysia as monitored by the
Malaysian Meteorological Service 1994”, MMS
Technical Note, No. 55, 1995.
[2] Cheang B K, Leong C P, Ooi S H, and Tusin A
M, “Haze episode October 1991”, Malaysian
Meteorological Service Information Paper no. 2,
1991.
[3] Anwar A, Juneng L, Othman M R and Latif M T,
“Correlation between hotspots and air quality in
Pekanbaru, Riau,[4] Indonesia in 2006–2007”, Sains Malaysiana
2010, Vol. 39, pp. 169–74.
[5] Heil A and Goldammer J G, “Smoke-hazepollution: a review of the 1997 episode inSoutheast Asia”, J. of Regional Environment
Change, Vol. 2, 2001, pp. 24-37.
[6] Latha K M and Badarinath K V S, “Black carbon
aerosols over tropical urban environmental casestudy” J. of Atmospheric Research, Vol. 69,
2003, pp. 125–33.
[7] Han S, Bian H, Zhang Y, Wu J, Wang Y, Tie X,
Li Y, Li X and Yao Q, “Effect of aerosols on
visibility and radiation in spring 2009 in Tianjin”,
J. of China Aerosol and Air Quality Research,
2012, Vol. 12, pp. 211–217.
[8] Jones D S, “ASEAN and transboundary inSoutheast Asia”, Asia Europe J. 2006, Vol. 4, pp.
431–446.
[9] Andreae M O, Jones C D and Cox P M, “Strong
present-day aerosol cooling implies a hot future”,
Nature, 2005, pp. 435 1187–1190.
[10] Anderson I P and Bowen M R, “Fire zones andthe threat to the wetlands of Sumatra, Indonesia
forest fire prevention and control project”, 2000.
[11] Lestari R K, Watanabe M, Imada Y, Shiogama H,
Field R D, Takemura T and Kimoto M,“Increasing potential of biomass burning over
Sumatra, Indonesia induced by anthropogenic
tropical warming”, Environment Research Letter,
2014, Vol. 9, pp. 104010.

Fig. 7 Relationship of PM10 concentration andvisibility over four stations in Peninsular Malaysia
CONCLUSION
This study had analyzed the spatio-temporalvariation on PM10 concentration during intense haze
condition in 2013 by utilizing all source of data
including remote sensing data and ground-based data.
In this study comprised with numerous parameterssuch as hotspot, rainfall amount, temperature,visibility, HYSPLIT trajectories, surface wind speed
and direction via PM10 as the aerosols indicator. This
assessment found that, during 2013 the highest peakof PM10 concentration started on 20th until 24th ofJune 2013 and were detected high at four stations overPeninsular Malaysia; Bukit Rambai, Singapore,
SAAIA and Setiawan station. This condition coupledwith low wind speed and less rainfall amount which
relatively causing to low mixing depth and inefficientventilation to the atmosphere. Haze episode in 2013
also occurs during the southwest monsoon season
where; the wind flow southwesterlies and thepollutant substance were transported from Sumatera,
Indonesia to Peninsular Malaysia. Thus, these transboundary haze were proved by the hotspot count in
Sumatera, which were recorded high on 19th of June2013 (more than 3000 counts). Trajectory modelingwith HYSPLIT showed that smoke fire moves from
Sumatera area towards the Peninsular Malaysia. A
decline in air quality also affecting towards thedecreasing in visibility. Hence, these situation may
slow down the economy and disturb community
health in the surrounding area.

960

GEOMATE - Mie, Japan, Nov. 21-24, 2017

spectroradiometer”, J. of GeophysicalResearch, 1997, Vol. 102, pp. 17,051-17,067[12] Vadrevu K P, Lasko K, Giglio L and Justice C,“Analysis of Southeast Asian pollution episodeduring June 2013 using satellite remote sensing
datasets”, J. of Environmental Pollution, 2014,
Vol. 195, pp. 245–56.
[13] Kunii O, Kanagawa S, Yajima I, Hisamatsu Y,
Yamamura S, Amagai T and Ismail I T “The1997 haze disaster in Indonesia: its air quality
and health effects”, Archives of Environmental
Health 2002, Vol. 57, pp. 16–22.

[15] Li X, Zhao X, Kahn R, Mishchenko M, Remer L,

Lee K H, Wang M, Laszlo I, Nakajima T, Maring
H, “Uncertainties in satellite remote sensing ofaerosols and impact on monitoring its long term
trend: a review and perspective”, J. of Ann.
Geophys., 2009, Vol. 27, pp. 2755-2770.
[16] Levy R C, Remer L A, Dubovik O, “Second
generation algorithm for retrieving aerosol
properties over land from MODIS spectralreflectance”, Journal of Geophysical Research,
2007, Vol. 112[14] Kaufman Y J, Tanre D, Remer L A, Vermote

E F, Chu A, Holben B N, “Operational remotesensing of tropospheric aerosol over land from
EOS
moderate
resolution
imaging961

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

MAT FOUNDATION DESIGN REFERENCE FOR METRO MANILA,
PHILIPPINES

Jonathan R. Dungca1, Raynold Y. Pua2, Raynold, Nelson Que3,
Anne Kristine M. Sangalang4, Ayran Nicole Tan5
12345
Civil Engineering Department, De La Salle University – Manila, 2401 Taft Avenue, Manila, Philippines

ABSTRACTTo design mat foundations, there are certain values which are required for calculations and analyses, one of which would
be the vertical modulus of subgrade reaction. It can be obtained through various deterministic tests such as the Plate Load Test.
On the other hand, the study calculated this factor through the use of Standard Penetration Test (SPT) results by using four
different methods. Comparative study and validation were also performed to confirm the most recommendable method to be
used to compute for the soil spring constant, given the limitations of the SPT results, by correlation of this parameter to the
California Bearing Ratio (CBR) test results. Through this, the study considered and used the equation formulated by Bowles
to calculate for the vertical modulus of subgrade reaction. Then, a Geographic Information Systems (GIS) software was utilized
to generate maps of these values by the method of ordinary kriging. These maps presented the locations with the predominantly
high and low values of the soil spring constant. They were also used to create a digitized reference of the values of the verticalmodulus of subgrade reaction for the design of mat foundations for preliminary design through the use of Visual Basic
Applications 2010

Keywords: mat foundation, modulus of subgrade reaction, standard penetration test foundation design reference

spring constant is used as a quantity that simplifies andgeneralizes its behavior. Imaginary springs are
positioned continuously beneath the structure and aconstant value, k, is generated [1]. The dilemma now isthat the soil spring constant is not unique for specifictypes of soils [1] and is affected by various factors suchas the depth of the foundation and dimensions of the matfoundation being considered such as its base width
which will be considered as a variable in this paper.
Therefore, the soil spring constant for a given type ofsoil cannot be generalized with a specific range unlike
other parameters such as density, porosity, and the like.
A soil test, specifically the Plate Load Test, can be used
to determine such a geotechnical parameter; however,with the limited budget most constructions face,engineers are forced to theoretically propose or estimate
conservative values for these to pursue their design.

INTRODUCTION
With the on-going modernization of the society,more technologically and competitively complex
structures are being developed and constructed
throughout the Metropolis. Civil engineers are facedwith the constant dilemma of ensuring the safety andstructural stability of any structure being designed,
whether simple or complex. Before all the other safety
and stability considerations, the design of foundations isthe basic concern when designing any structure.
Foundations are best known to be among the primaryelements in any structure that provide structural stability.
However, the design of any foundation would require
the attainment of geotechnical parameters thatnecessitate extensive analysis and exploration of the soil
where the structure would be built.
With a land area of approximately 619.5 square
kilometers, Metro Manila covers a large portion of
Luzon. Greater coverage means greater variation in thetypes of soils that are considered in the design of various
structures. Along with the change of the soil types comesthe adjustment in the foundation requirements, where
despite the possibility of constructing exactly the samebuildings in two different locations, the surrounding
conditions will dictate what type of foundation design
would be required.

Mat foundation is a specific type of shallow
foundation that is commonly used when the loading on
the ground is aimed to be spread throughout an area inconsideration. Mat foundations are very useful because
it controls differential settlement which causes
additional moments in structures thus affecting its
stability. Because mat foundations are designed to covera large area with a slab, it helps in creating uniform
settlement along the entire mat. To be able to design amat foundation fit for a particular soil, there are specificsoil parameters that should be obtained through the helpof soil reports.

Among those parameters greatly affected bychanging soil conditions is the modulus of subgrade
reaction, k, also known as the soil spring constant.

There have been some similar studies related to thisresearch [2]-[8], however, there is not one dedicated tothe estimation of subgrade reaction to be used for the

In the different models used to analyze soil, the soil

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

design of mat foundations for Metro Manila.

Portions of Taguig and Pasig on the east.

This study aims to generate a design reference format foundations through the computation of the soil
spring constants of the various locations in Metro
Manila through Standard Penetration Test (SPT)
borehole logs.

The Guadalupe tuff formation (GF) is a series of soil
classifications that is comprised of rock or tuffaceous
materials distributed along Quezon City, Makati,
Mandaluyong, parts of Pasig, and Rizal. It is divided into
two members namely the Alat Conglomerate and theDiliman Tuff due to their differences in composition andstructure. The Alat Conglomerate, the lower member ofthe formation, is generally composed of conglomerates,
mudstones and sandstones. This member is locatedalong the lowland hills of eastern Bulacan and southern
Nueva Ecija. A predominant rock type in the GF
member is conglomerate which is massive and poorly
sorted with well- rounded pebbles. Cemented by coarse
grained, calcareous, sandy matrix are small boulders ofunderlying rocks. It also contains mudstone which is
medium to thin bedded with some varied characteristics
of softness, stickiness, siltiness and tuffaceousness.

METRO MANILAThe National Capital Region, also referred to as
Metropolitan Manila, is the country’s leading urban
region and is considered as the centre for the Philippines’
economy, politics and culture. The region is highly
urbanized, providing jobs for a huge percentage of thecountry’s population. Metro Manila is heart of thecountry’s
finance,commerceandindustrial
development. Within its borders lie the largest economic
hub of the country, which is Makati. Other leadingbusiness districts which strive to be among the country’s
best districts are also within NCR, these are Eastwood in
Quezon City, Bonifacio Global City in Taguig and
Manila Reclamation Area in Manila. Because of this, ahuge amount of structures are built to fit the economy
and the lifestyle of Metro Manila. Design data concluded
from soil conditions are required for majority, if not all,of the structures that are built in the region.

The Diliman tuff (the upper member) is made up of
tuffs, pyroclastic breccias and tuffaceous sandstones.
This member of the Guadalupe Formation consists of
vitric tuffs and welded pyroclastic breccias . It also
contains minor fine to medium grained tuffaceous
sandstone. Some dark mafic minerals and pumicematerials are spread out in the tuff matrix. The Diliman
tuff stretches from Quezon city to the southern parts ofMetro Manila, namely Pasig, Makati and Rizal province.
[9].

Metropolitan Manila is bordered by different
provinces and water systems which help the region
become prosperous. The provinces of Bulacan and Rizal
are situated on the north and east of the region
respectively. On the south-west lies the province ofCavite while on the south is Laguna. Water systems also
envelop the region, these are Manila Bay on the west andLaguna de bay on the south-east.

METHODOLOGYIn designing foundations, geotechnical parameters
can be acquired by various soil exploration methods. In
the case of mat foundations, the geotechnical parametersthat need to be considered are the modulus of subgrade
reactions and the bearing capacity of the soil varying ina certain depth. In attaining these variables, plate load
test should be performed, but due to availability and cost,
the researchers utilized the Standard Penetration Test
(SPT) values to derive the modulus of subgrade
reactions. This value is significant because aside fromthat it is the basis of good foundation design,conservative assumptions of one of the factors forfoundation design can also be avoided.

Out of all the regions in the Philippines it is the only
one that is subdivided into 17 government units, with noprovinces where in 16 are cities and one is a municipality.
The 16 cities include: Caloocan, Las Pinas, Malabon,
Manila, Marikina, Makati, Mandaluyong, Muntinlupa,
Navotas, Paranaque, Pasig, Pasay, Quezon, San Juan,
Taguig and Valenzuela. Pateros is the only municipality
in the region. The city sums up to a total of 63.6 square
kilometres of land area with Quezon City as the largest
and Navotas City as the smallest.
According to the data and maps provided by the
Bureau of Mines and Geosciences, the entire region isdivided into two major stratifications. These are
Quaternary Alluvium and the Guadalupe formation.

Borehole logs and other soil data from all the 16
cities and 1 municipality of Metro Manila were obtained.
Soil data from some cities and municipalities
surrounding Metro Manila including Rizal, Cavite,
Laguna and Bulacan were also obtained for the properinterpolation of data. Data from soil tests such as the
SPT and Borehole tests from government agencies,
structural firms, and geotechnical firms were gatheredby the researchers. A total of 809 borehole data werecollected for the study, 776 of which are found within
the Metropolitan and 33 are located on areas orprovinces bordering around NCR. Factors such as thetype of soil tested, undrained shear strength, and the Nvalues were extracted from these data. Further

The quaternary alluvium soils are consisted ofdeposited sediments from nearby water systems such as
the Manila bay and Laguna de bay. These include
detrital deposits composed of mostly silt, sand andgravel. The locations in the Metropolitan that are foundon the coasts or along water systems are those that areconsisted mainly of Quaternary Alluvium. These include
Pasay City, Manila City, Paranaque and parts of Las
Pinas on the west while there are Muntinlupa, Marikina,

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

computations were performed to estimate other soil
parameters such as bearing capacity, settlement, andModulus of Elasticity.

As for the validation of the result, there can bedifferent deterministic tests that could compute for thevalue of the Modulus of Subgrade Reaction. Plate Load
Test is widely used to acquire actual values of the soil
spring constant [14]. In this test, a load is applied to theplate in increments depending on the design load.
Loading continuously applied until the change insettlement is significantly reduced to a specified amount.
However, many researches also claim the inaccuracy ofthis test because of the size of the samples and theequipment being used. Other than this, there are issues
regarding the availability of the equipment. According
to the research of Thornton [15], another method that canbe used to estimate the value of the soil spring constantis through the CBR test [16].

The obtained N-Values were corrected using Eq. 1,
standardizing it into the N60 value.
N60 = (5/3) (CNCECBCRCS)(1)

where:
N 60 = Corrected SPT blow counts;
C E = Energy Effect depending on hammer type;C B = Correction factor for borehole diameter;
C R = Correction factor for rod length;
C S = Correction factor for type of samplers;
C N = Effective overburden pressure coefficient.

The CBR results used in this study were obtained
from geotechnical companies that performed the actual
CBR testing in various locations in Metro Manila. The
collection of CBR data was geared towards therepresentation of different cities around the National
Capital Region, wherein CBR data were collected foreach city in Metro Manila. Out of the original 16 data
points, only 13 data points were used in the study. Thiswas due to the fact that the other CBR data werecollected at shallow depths that are less than one (1)meter from the natural ground surface. This is not within
the range of depths that are used in the study.
Furthermore, there are many external factors that may
affect the soil conditions at such a shallow depth and thismay not provide accurate results for the modulus ofsubgrade reaction.

Certain parameters that are required for thedetermination of the Modulus of Subgrade Reaction are
the base (width) of the lot area being considered and theflexural rigidity of the materials that will be used for thefoundation. Since the base width is a value that isconstantly changing and is dependent on the area to beconstructed as well as the design of the structural
engineer, the authors have deemed it to be a variable
along with the values of the flexural rigidity. With thevalues of N 60 , modulus of elasticity (Es), Poisson’s ratio(ν), and base as a variable, the study calculated themodulus of subgrade reactions through four methods.
The first method is by using the definition of the soil
spring constant which is a ratio between the appliedpressure and the settlement (Se) created by such apressure. In this study, the soil spring constant wascomputed through dividing the ultimate bearing capacity(Qu) by the settlement of the corresponding soil; boththe bearing capacity and settlement were computed
using values that were obtained from the SPT andborehole data. The second method was through astandard equation proposed by Vesic[10] which isusually used in the industry to estimate the value of thesoil spring constant. This equation incorporates Nvalues to estimate elastic constants such as the Modulus
of Elasticity of the soil and Poisson’s ratio which arerequired by the said standardized equation.

Using the equation formulated by Thornton [15]through the correlation of the CBR test results to the soil
spring constants, values of the vertical modulus ofsubgrade reaction were computed. The results wereconcluded based on the nearness of the values (from thefour methods) to the value obtained using the CBR test.
This was done through the help of the statistical methodof t-test analysis. A graph was also generated to present
the differences of the values visually.
Since the aim of this paper is to provide a designreference for mat foundations, the values of spring
constants calculated was plotted out onto the map ofMetro Manila. To provide values for places where there
are not enough available data, the Kriging method for
optimal interpolation was performed so that a map of thevalues will be generated [17]. This is the reason why
soils in places outside Metro Manila were analyzed aswell, to provide reliable interpolation of the values. The
said contour maps were generated for every 1m layerinterval and were done with the help of a Geographic
Information System software.

The third method is the use of Empirical Equations
provided by other researches performed by Moayed andNaeini [11] for gravely soils incorporating N60-values
and Ou [12] for sandy and clayey soils incorporating
N60-values and undrained shear strength (Su),respectively. The fourth, and last method, is theestimation by Bowles [13] that modifies the definition
by limiting the settlements at certain values, particularly
25 mm.
From these four methods, a comparative study was
conducted by comparing the outcomes of modulus ofsubgrade reactions from the different methods toconclude which of these is the most appropriate result.
The value chosen from the different methods was
mapped for the various cities and locations in Metro
Manila.

MAT FOUNDATION REFERENCE
With the aim of this study to generate a map bychoosing the most recommendable method of obtaining
the values of the modulus of subgrade reaction. To do so,964

GEOMATE - Mie, Japan, Nov. 21-24, 2017a simple comparison of the values obtained for all four
methods of computations of the modulus of subgrade
reaction was performed.

that the author chose to limit the settlement to certain
structurally acceptable values such as 25 mm, 20 mm,
12 mm and the like. The value of the modulus ofsubgrade reaction can be obtained through the equation
shown below:

The first method is by definition. The soil spring
constant (k) is defined as the ratio between the soilpressure(q) applied on the soil and the settlement (δ)
produced by such an applied soil pressure,mathematically represented as:
k=q/δ

k = 40(SF)(q u )where:
SF = factor of safety;
q u = ultimate bearing capacity.

(2).
A screening of individual values per layer was done
to compare the results obtained for all four methods ofcalculation for the soil spring constant. This is to provide
a better understanding on how the values turned out asthey have and what factors may have played roles forsuch an outcome to occur.

The second method is estimation of k throughstandard equations. Different standard equations arereadily available for the computation of the Modulus of
Subgrade reaction. The same comparisons were
performed by the Sadrekarimi & Akbarzad [18]. They
compared the resulting values with each other and haveconcluded that the equation provided by Vesic [10]provided the most accurate variable. The value of thesoil spring constant in this method can be computed by:𝒌𝒌 =𝟎𝟎.𝟔𝟔𝟔𝟔𝑬𝑬𝒔𝒔 𝟏𝟏𝟏𝟏 𝑩𝑩𝟒𝟒 𝑬𝑬𝒔𝒔

(𝟏𝟏−𝒗𝒗𝟐𝟐
𝒔𝒔 )

(7);

�

𝑬𝑬𝑬𝑬

With the individual analyses of the methods for thecomputation of the Modulus of Subgrade reaction, themethod by Bowles and by definition provided the mostrecommendable values. Contrary to what the authors
expected, the most conservative estimation of themodulus provided the value closest to the actual k values
as shown in the validation through CBR testing. Thismay be because of the fact that both the Bowles andcomputation by definition are limited to existing soil
specific data and required minimal assumptions. One of
the methods used in this study, the computation bystandard equation, required too many parameters
majority of which are basic design data that are usuallyassumed. An example of this would be the Poisson’s
ratio. Perhaps this method can be best used if only atheoretical analysis of the modulus would be done. As
for the empirical methods, these calculations resulted tovery low values and has a high per cent difference fromthe site-specific k values obtained from the validation.
This may be because these are obtained fromcorrelations with the Plate load test, which as claimed byvarious literature is unreliable for obtaining the modulus
of subgrade reaction. Because of all these reasons, theauthors have mapped only the values obtained throughthe Method of Bowles.

(3);

where:
E s = Modulus of Elasticity of the soil (kPa);
EI = Flexural Rigidity of Mat (kN-m2);
B = Slab width (m);v s = Poisson’s Ratio.
The third method Estimation of k through empiricalequations. The research by Moayed & Naeini [19] uses
the N-values obtained from the Standard Penetration test
and correlated it with the plate load test to be able toderive an equation that represents the relationshipbetween the standard N 1,60 value (blow counts corrected
to 60% hammer energy and overburden pressure) and k.
Once the value of the N 1,60 was obtained, it was
statistically correlated to the results of the plate load teston the same soil sample and a relationship wasdetermined by Eq. (4):For Gravelly Soil:
k= 3.143 (N1) 60 0.489(4).

Despite the lack of uniqueness among the values ofthe modulus of subgrade reaction, there are some generaltrends in the values that can be observed for each levelof soil stratum. One trend is that the values of themodulus of subgrade reaction increases as the depth
increases. This is due to the fact that as the depth of theanalysis increases, it approaches the rock formation
further. As the rock formation is reached, the soil
becomes more compact and dense that it would havegreater resistance to forces acted upon the soil ascompared to the previous layers. This greater resistanceis manifested by the increase in the values of theModulus of subgrade reaction.

The derivation of Eq. (4) only focuses on gravely
soils and the other soil types were delimited in the study
performed by Moayed & Naeini [19]. Because of this,the empirical formula provided by Ou [20] would be
helpful in the estimation of the values of the Modulus of
Subgrade Reaction for clayey and sandy soils. Theseequations are as follows:
For Clayey Soil: k = 40 – 50 s u
For Sandy Soil: k = 70 – 100 N
where:
k in (t/m3);s u = undrained shear strength (t/m2) and;N = SPT N-values.

(5);
(6);

Shown in Figure 1 is the map generated by the study
from the collected data for depths 1 meter from theground surface to 4 meters. It can be seen from Figure 1
and Figure 2 that the values of the modulus of subgrade

The fourth method is k through estimation of Bowles[13]. It is a variation of the estimation of the modulus ofsubgrade reaction by definition. The only difference is965

GEOMATE - Mie, Japan, Nov. 21-24, 2017

reaction are high where the depth of the rock formationis shallow.

Fig. 1

Areas where the values of the modulus are highest
would be for the cities of Mandaluyong, Makati,
Paranaque and Quezon City or all those cities that areaway from the large basins or bodies of water and areunderlain by the Guadalupe tuff formation. This isbecause through time, continuous deposition of soils on
locations near the bodies of water have compacted thesoil strata of those places found at the middle of theregion. As expected also, the values of the subgrade
reaction decrease as data points approach the large
bodies of water particularly the Manila bay and theLaguna de bay. These cities that are nearest the bodies
of water stated previously, are Manila, Pasay, Navotas
and Muntinlupa. The decrease in the values of themodulus may explained by the soils found in theselocations which are locations are mainly made up of silt
and clay materials, or generally alluvial deposits.
Furthermore, the values of the modulus of subgrade
reaction increases again once the data points are moving
away from large bodies of water and into mountainous
areas and even the central part of the region. These
trends can be seen in Figure 1 which is a sample map of
the values of the modulus of subgrade reaction using themethod suggested by Bowles.

Map of Metro Manila with values of modulus
of subgrade reaction (all values are in kN/m3)
using Bowles [13]CONCLUSION

Fig. 2The design of mat foundations considers theresistance of the soils to any force applied onto it. The
study has limited the study depths from 2 to 6 meters
because any deeper than this would not berecommendable for the construction of mat foundations.
To assess such a resistance from the soil, the final outputof the study has been to compute for the values of themodulus of subgrade reaction which are determinedthrough borehole logs collected all over the region.
These borehole logs were collected from different
private testing companies, city government offices andnational government offices in Metro Manila. However,certain places in Metro Manila are not yet as fully
represented in this study. The cities of Caloocan,
Valenzuela, Muntinlupa, and the Municipality ofPateros are among those that have data points that
represent only around 60% of the total area. The
calculation of the Modulus of subgrade reaction were
performed through an excel program wherein soil
properties, SPT N-values, and RQD were used to obtain
information that would lead to the estimation of the kvalues.

Geologic Map of Metro Manila [21]Another trend is that it is evident that the results arehighly affected by the soil compositions of a particularregion. Some areas, particularly where the upper layersof soil are composed of tuffaceous material, haveobservably higher values for the modulus of subgrade
reaction compared to other areas where the rock layers
are at a greater depth. The high values of the modulus ofsubgrade reaction are underlain by the Guadalupe Tuffand the low values are underlain by alluvial, delta
deposits. It can also be observed in the comparison of
the two maps (Figure 1 and Figure 2) that there is asudden change in the values of the modulus of subgrade
reaction (from dark red suddenly changed to blue) inareas that are divided by or are passed by the West
Valley fault systems.

The locations in Metro Manila that provided the low
values of the Modulus of subgrade reaction are Manila,
Pasay, Navotas, and Muntinlupa, which could be
attributed to the type of soil layers underlain in thesecities which is mainly composed of loose silty sand andclay materials. It could be because of the large bodies ofwater that are bordering these locations such as Manila
Bay and Laguna de Bay which can be considered as agood source of sand, silt, and clay deposits in the area. It
could be safe to claim that the modulus of subgrade
reaction has significantly low values if the areas are966

GEOMATE - Mie, Japan, Nov. 21-24, 2017

located in these cities and may not be recommendable
for the use of mat foundations.
On the other hand, cities such as Mandaluyong,
Paranaque, Makati, and Quezon provided significantly
high values of the modulus of subgrade reaction. Thismay be attributed to the tuffaceous material from the
Guadalupe tuff formation that is underlying these cities.
Soils within the Guadalupe tuff formation are highly
dense compared to other soils within Metro Manila andthe rock formation is at very shallow depths. Because of
these, computed settlements were small and theallowable bearing capacity is of a remarkable value
making the modulus of subgrade reaction significantly
high. It is for these locations where the use of mat
foundations is recommendable.

[9] Hosono, T., Siringan, F., Yamanaka, T., Umezawa,Y., Onodera, S., Nakano, T., & Taniguchi, M.
(2010). Application of multi-isotope ratios to study
the source and quality of urban groundwater inMetro Manila, Philippines. Applied Geochemistry,25(6), 900–909.
[10] Vesic, A.B. [1961]. “Beams on elastic subgrade andWinkler’s hypothesis”, Proc. 5 th. Int. Conf. on Soil
Mech. Found. Engrg., Paris, p.p. 845-50.
[11] Moayed, R. & Janbaz, M. (2008). Foundation Size
Effect on Modulus of Subgrade Reaction in Clayey
Soil. Electric Journal of Geotechnical Engineering,
13[12] Ou, C.Y. & Lai, C.H. (1994). Finite-element
analysis of deep excavation in layered sandy andclayey soil deposits. Canadian Geotechnical
Journal, 31(2), pp. 204- 214[13] Bowles, J. E. (1987), Elastic foundation settlements
on sand deposits, Journal of GeotechnicalEngineering, ASCE, 113, No. 8, pp. 846–860.
[14] ASTM 1994. Test method for bearing capacity ofsoil for static load on spread footings, D 1194-94,
Annual Book of ASTM Standards, 4.08. American
Society for Testing and Materials, WestConshocken, PA.
[15] Thornton, Sam I. Correlation of Subgrade Reaction
with CBR, Hveem Stabilometer, or Resilient
Modulus. Arkansas State Highway andTransportation Department. Little Rock, Arkansas.
(1983).
[16] ASTM D1883-16, Standard Test Method for
California Bearing Ratio (CBR) of LaboratoryCompacted Soils, ASTM International, WestConshohocken, PA, 2016, www.astm.org.
[17] E.H. Isaaks, R.M. Srivastava. An Introduction to
Applied Geostatistics, Oxford University Press,
New York (1989)[18] Sadrekarimi, J. & Akbarzad, M. (2009).
Comparative Study of Methods of Determinationof Coefficient of Subgrade Reaction. Electronic
Journal of Geotechnical Engineering, 14, pp. 1-14.
[19] Moayed, R. & Janbaz, M. (2008). Foundation Size
Effect on Modulus of Subgrade Reaction in
Clayey Soil. Electric Journal of GeotechnicalEngineering, 13.
[20] Ou,C.Y. & Lai, C.H. (1994). Finite-element
analysis of deep excavation in layered sandy andclayey soil deposits. Canadian Geotechnical
Journal, 31(2), pp. 204- 214.
[21] Bureau of Mines and Geosciences, 1981. Geology
and Mineral Resources of the Philippines, 1(Geology). Ministry of Natural Resources, Manila.

REFERENCES[1] Daloglu, A & Vallabhan, G. (2000). Values of k for
Slab on Winkler Foundation. Journal of
Geotechnical and Geoenvironmental Engineering,126(), pp. 462 – 471.
[2] Dungca J. R. (1997). Liquefaction Potential Map
of Manila (Masteral Thesis, De La Salle University,
Philippines.
[3] Dungca J. R. and Chua R. A. D., “Development of
a Probabilistic Liquefaction Potential Map for
Metro Manila”, International Journal of
GEOMATE, Vol. 11, Issue 25, Sep. 2016, pp.
2461-2467.
[4] Dungca J. R., Concepcion I., Limyuen M.C.M, See
T. O. and Vicencio M. R., “Soil Bearing Capacity
Reference for Metro Manila”, International Journalof GEOMATE, Vol. 12, Issue 32, Apr 2016, pp. 511.
[5] Dungca J. R. and Macaraeg C. J., “Development ofa Reference for Seismic Amplification: The Case ofMetro Manila”, 19th Congress of International
Association for Bridge and Structural Engineering,
Stockholm, Sweden Sep. 2016.
[6] Saldivar – Sali, A. (1992). An Earthquake Risk
Analysis of Metro Manila from a Foundation
Engineering Perspective. Journal of the GeologicalSociety of the Philippines, 50, 287 – 289.
[7] Guevarra E., Santos, J., Sy, Hazel (1999). Data Aidfor the Design of Foundation in Las Pinas City.
Manila- De La Salle University Press. Codilla, M.,
de Castro, A., Palanca, R. (2007). Basic
Geotechnical Characterization of Malabon andNavotas Subsoil. Manila: DLSU Press.
[8] Mustafa, K. (1995). Evaluation of Soil Bearing
Capacities in San Mateo, Rizal.

967

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

PERFORMANCE OF ANN MODEL IN PREDICTING THE BEARING
CAPACITY OF SHALLOW FOUNDATIONS
Mozaher Ul Kabir1, Syed Shadman Sakib2, Istiakur Rahman3, Md. Sirajul Arefin4, Hossain Md. Shahin5
Student, Islamic University of Technology, Bangladesh; 3Lecturer, Islamic University of Technology,
Bangladesh; 5Professor,Islamic University of Technology, Bangladesh

1,2,4

ABSTRACTThis study deals with the performance of the Artificial Neural Networks (ANNs) for predicting the ultimate
bearing capacity of shallow foundations on cohesion less soil. Footing geometry and other soil parameters fromcone penetration tests (CPT) were the input variables considered to have the most significant impact on bearing
capacity predictions. The application of Artificial Neural Network was carried out through the following steps
considering total 100 sets of data .Firstly for training, 89 sets of data were used to determine a relation between
input variables and the bearing capacity of the soil. For testing and validation, the other 11 data sets were used.
The performance of the model was evaluated by comparing the results with conventional bearing capacity
equations. High coefficients of correlation, low root mean squared errors (RMSE) and low mean absolute errors(MAE) were the indications to confirm that the ANN based model predicts with much perfection.
Keywords: ANNs, Bearing Capacity, RMSE, MAE.

In the most recent two decades a few analysts havecreated successful demonstrating instruments. Oneof them is Artificial Neural Networks (ANNs)
methodology. In the current past, ANNs have beenconnected to numerous geotechnical designingissues, including the expectation of the bearing
capacity of footings, settlement forecasts,liquefaction and stability of slopes [7]. The realpreferred standpoint of ANNs is that they can beused effectively as and when new information end
up noticeably accessible that wipes out therequirement for a researcher to reanalyze the old and
new information, use the old outline helps orconditions and additionally propose new conditions[8]. This paper shows the relevance of ANNs
method in building up a compelling nonlinear model
for anticipating a definitive bearing capacity ofshallow foundations on cohesion less soils. The
database, which comprises of load test aftereffects ofextensive scale footings and smaller estimateddemonstrate footings, is utilized to create and check
the ANN model. This paper additionally goes for abroad assessment of the ANN model with
Regression based models for ultimate bearing
capacity using in total 100 sets of field data andevaluates their benefits and restrictions. The
execution of these models is then contrasted and themost regularly utilized bearing capacity speculations.

INTRODUCTION
Every foundation setup requires satisfying two
imperative criteria: ultimate bearing capacity ofconfinement and limiting settlement of foundations.
Of these two criteria, a complete bearing capacity ofconfinement is managed by shearing nature of thesoil and is evaluated by the theories of Terzaghi [1],Meyerhof [2], Vesic [3] and others. The explanation
behind an extensive part of as far as possible
theories is the most remote point adjust procedure.
As far as possible in this manner got are affirmed
through lab considers by different researchers. In
any case, the trial looks at are generally done ontinier measured models, which are significantly cut
back models stood out from real field footings. In
this way, various authorities (e.g., [4, 5]) haveprompted that one should be amazingly vigilant
while extrapolating disclosures of examinations
driven on little footings that have a width of several
inches, to the broad evaluated footings. The
clarification behind this is credited to the extension
in shearing strain along the slip line with thedevelopment in width of the foundation and theextent of mean grain size of the soil and the adjust
width [6]. For extensive scale establishments on
dense sand, shearing strains demonstrate significant
variety along the slip line and the normal assembled
point of shearing resistance along the slip line islittler than the greatest estimation of the angle ofshearing resistance (φmax) gotten via plane strain
shear tests. Henceforth, an option technique isrequired that gives better gauges of bearing capacity.
968

GEOMATE - Mie, Japan, Nov. 21-24, 2017

DEVELOPMENT OF ULTIMATE BEARING
CAPACITY MODEL

angle of shearing resistance (φ). Extreme bearing
capacity (qu) is the single yield variable.

The data used for testing and validation of the
ANN model were gathered from literatures, which
incorporate load test data on real sized foundations
and in addition the associated data regarding thefooting and soil.From the 100 field data collections,
47 are from load tests on large scale footings and 50
are from small shallow footings. Of the 47 large
scale footing data, 24 were reported by Muhs andWeiß [12], 11 by Weiß [13], 5 by Muhs et al. [14], 2
by Muhs and Weiß [15], 5 by Briaud and Gibbens[16].
One of the more vital initiative in the model
improvement for the estimation of bearing capacityof shallow foundation is distinguishing proof ofparameters that influence the bearing capacity, forwhich a portion of the conventional bearing limit
techniques [1-3] are analyzed. In spite of the waythat the bearing limit esteems gotten through thesetechniques vary impressively, the fundamental typeof condition is the same for every one of thestrategies, which is as per the following forestablishments in cohesionless soil:

ANN model Development:
In this study feed-forward multilayer perceptron(MLP) is utilized; the portrayal of which can befound in numerous publications [9, 10]. The dataset
was arbitrarily separated into three subsets: training
and testing. 70% (or 63 cases) of the information
was set for training the model,15% (or 13 cases) was
utilized for training ,while the staying 15% (or 13
cases) was utilized for testing the execution of the
proposed ANN based model. Using an trial-anderror strategy, the optimum number of hidden layers
in the model was resolved which concluded by using
ten hidden layer. Because of five input and one
output variable; five node were used in the input
layer and one in the output layer. A typical way todeal with problem of over fitting is early stopping.
This
approachincludesmonitoringthegeneralization error and stopping training when theminimum validation error is observed. Be that as it
may, some care is required when to stop, since thequ = γDNqSqdq + 0.5γBNɣSɣdɣ
where B – width of footings, D – profundity offootings, c – unit weight of sand (underneath ormore the establishment level), Nq, Nɣ – bearing
capacity factors, Sq , Sɣ – shape factors and dq, dɣ –depth factorsAmong the parameters identified withthe footings, the principle factors influencing thebearing capacity are its width (minimum horizontal
measurement, B), length of footing (L), shape(square, rectangular and round) and depth of thefoundation (D). The depth of the foundation has thebest impact on the bearing capacity among all thephysical properties of the foundation [5]. The
fundamental parameters with respect to the soil
(sand) are its angle of shearing resistance and theunit weights from above and beneath the water table,
if introduce. There are some different factors, forexample, compressibility and thickness of the soil
layer underneath the establishment that add to alesser degree. Of the considerable number ofproperties of a soil, the edge of shearing resistancehas most noteworthy impact on the bearing capacity,which increments with the relative thickness of thesoil. The bearing capacity is straightforwardly
corresponding to the unit weight of the soil and isaffected by the area of water table.
In light of above discussion, the five input
parameters used for the model advancement are
width of footing (B), depth of footing (D), ratio oflength and width (L/B), unit weight of sand (ɣ) and

Fig. 1. Architecture of ANN model.
approval mistake surface may have local minima or
long flat regions preceding a steep drop-off. To
minimize these constraints Mackay [11] proposed
the use of Bayesian back propagation neuralnetworks which minimizes a combination of squared
errors and weights and after that decides the correct
combination, in order to create a network whichsums up well. This procedure is called Bayesian
regularization. In the Bayesian structure, the weights
and the biases of the network are assumed to berandom variables with indicated appropriation of
distribution. The regularization parameters are
identified with the unknown variances related withthe distribution. These parameters are then evaluatedusing statistical techniques. In the present
investigation, the Levenberg– Marquardt algorithm
is utilized under the Bayesian network.

969

GEOMATE - Mie, Japan, Nov. 21-24, 2017

evaluates the performance of the model in predicting
the ultimate bearing capacity values away from themean is found to be more than 98% for calibrationand validation data for the ANNs model was close towhere it was first referenced.

Multiple-regression analysis
To develop a relationship between the single
dependent variable, qu and one or more independent
variables ci, hi and B, multiple-regression is used,
the prediction of qu is accomplished by the following
equation:
qu = w1c1 + w2c2 + w3c3 + w4c4 + w5h1 + w6h2 +w7h3 + w8B + b
where wi are the regression weights and areprocessed in a way that limits the aggregate of thesquared deviations. Here b is the y axis intercept.
Multiple-regression is associated with multiple
correlation coefficient, which is the variance of thedependent variable explained collectively by all of
the independent variables.A multiple-regression
model was obtained using StataSE 12

Fig. 2. Distribution of prediction error acrossdifferent error thresholds.
Fig. 2. Output result from StataSE 12 for MLR
model.
The following formulas, using the MLR technique,were found to offer the best fitting:qu = 1976.073D + 86.464h -2833.27
where qu(kPa) is the bearing capacity, s (m),h(deg) is the angle of friction.
Performance Evaluations & Results
Here the performance is being evaluated byassessing the degree to which model the simulations
match the actual output. The assessment was
performed in the current study with various
goodness-of-fit or correlation statistics. The valuesof performance indices or measures for the threemodels are summarized in Table 2. The correlation
statistic (R), which evaluates the linear correlation
between the actual and predicted ultimate bearing
capacity, is good for all the models, for calibration
as well as validation data. The model efficiency that970

GEOMATE - Mie, Japan, Nov. 21-24, 2017

REFERENCES[1] Terzaghi K. Theoretical soil mechanics. New
York: John Wiley & Sons; 1943.
[2] Meyerhof GG. Some recent research on the
bearing capacity of foundations. Can Geotech J
1963;1(1):16–26.
[3] Vesic AS. Analysis of ultimate loads of shallow
foundations. JSMFD, ASCE 1973;99(1):45–73.
[4] De Beer EE. The scale effect on the phenomenonof progressive rupture in cohesionless soil. Proc. of
the 6th int. con. on soil mech. and found. engg. vol.
2. 1965. p. 13–7.
[5] Meyerhof GG. The bearing capacity of sand.
PhD thesis, University of London; 1950.
[6] Steenfelt JS, Scale eﬀect on bearing capacity
factor Nc. Proc. of the 9th international conferenceon soil mechanism and foundation engineering. vol.
1. 1977. p. 749–52.
[8] Shahin MA, Maier HR, Jaksa MB. Artificial
neural network applications in Geotechnical Eng.
Austr Geomech 2001;36(1):49–62.
[8] Pande GN, Shin H-S. Artificial intelligence v.
equations. Proc ICE Civil Eng 2004;157(1):43–6.
[9] Zurada JM. Introduction to artificial neuralsystems. Jaico Publishing House; 2003.
[10] Fausett LV. Fundamentals of neural networks:
architectures,algo-rithms
andapplications.
Englewood cliﬀs (NJ): Prentice-Hall; 1994.
[11] Mackay DJC. Bayesian methods for adaptivemodels. PhD thesis, California Institute ofTechnology; 1991.
[12] Muhs H, Weiß K. Untersuchung vonGrenztragfa¨higkeit
undSetzungsverhalten
flachgegru¨ndeter
Einzelfundamente
imungleichfo¨rmigennichtbindigen Boden. Deutsche
Forschungsgesellschaft fu¨ r Bodenmechanik(DEGEBO), Berlin. HEFT 69, 1971.
[13] Weiß K. Der Einfluß der Fundamentform auf
dieGrenztragfa¨higkeit
flachgegru¨ndeter
Fundamente. Deutsche Forschungsgesellschaft fu¨ rBodenmechanik (DEGEBO), Berlin. HEFT 65, 1970.
[14] Muhs H, Elmiger R, Weiß K. Sohlreibung undGrenztragfa¨higkeit unter lotrecht und schra¨gbelasteten
Einzelfundamenten.
DeutscheForschungsgesellschaft
fu¨rBodenmechanik(DEGEBO), Berlin.HEFT 62, 1969.
[15] Muhs H, Weiß K. Inclined load tests on shallow
strip footings. Proceedings of the 8th international
conference on soil mechanismand foundation engineering. vol. II. 1973. p. 173–9.
[16] Briaud JL, Gibbens R. Behavior of five large
spread footings in sand. ASCE J Geotech
Geoenviron Eng 1999;125(9):787–96.

Fig. 3. Measured vs. predicted ultimate bearing
capacity values.
Table 2
Performance evaluation & comparison

Performance index
R2

ANN
0.98019MLR
0.7138Meyerhof
0.648

CONCLUSION
Artificial neural networks (ANNs) and themulti-linear regression model (MLR) were used to
predict the bearing capacity of circular shallow
footings on cohesion less soil. The artificial neuralnetwork model serves as a simple and reliable tool
for the bearing capacity of shallow foundations inclay soil. The results produced high coefficients ofcorrelation for the training and testing data of
0.99308 and 0.98019 respectively which has much
more higher perfection then MLR model.
Nevertheless this study deals that having someknown parameters we can easily be able to have idea
about the ultimate bearing capacity through the
ANN model.

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Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

DEVELOPMENT OF THE TRADITIONAL LOCAL WISDOM INNOVATIONUSING COCONUT SHELL FOR STRESS RELAXING MASSAGE

Peerada Damapong1, Pongmada Damapong1, Wichai Eungpinichpong2, and Thanarat Sripongngam3
1College of Allied Health Science Suan Sunandha Rajabhat University, Bangkok 10300, Thailand
2Research Center in Back, Neck, and Other Joint Pain, and Human Performance, Faculty of Associated Medical

Sciences, KhonKaenuniversity, KhonKaen 40002, Thailand
3
Department of Health and Sport Science, Faculty of Education, Mahasarakham University, Thailand
ABSTRACTThis study was the research and development for developing innovation of coconut shell and studying
the effectiveness of wisdom of the local doctor on using coconut shell for stress-relieving massage. The researchand development was divided into 3 phases; Phase 1 – Developing innovation, Phase 2 – Testing innovation inpatients with stress and cervicogenic headache, and 60 volunteers were selected by using Self-Stress Assessment(SSA) which they were treated by getting 10-minute of coconut shell massage for 5 days, then they wereassessed before and after the treatment and Phase 3 – Concluding the effectiveness of innovation. The
measurement instruments were Self-Stress Assessment (SSA), Visual Analog Scale (VAS), Cervical Range of
Motion (CROM), Tissue Hardness Meter and Algometer, and Heart Rate Variability (HRV).
The findings revealed that; Phase 1 – the innovation of coconut shell for stress-relieving massage
had occurred, Phase 2 - tested the innovation of coconut shell for stress-relieving massage in 60 volunteers andPhase 3 – effectiveness of the innovation, after they were treated by getting coconut shell massage, the level ofcervicogenic headache was decreased with 0.95 level of significance (P<0.05), the cervical range of motion wasincreased with 0.95 level of significance (P<0.05), the tissue hardness meter and algometer compared before andafter of the treatment were increased with 0.95 level of significance (P<0.05), and SDNN (Standard Deviation ofNormal to Normal) and HRV value from the heart rate variability after the treatment was increased with 0.95
level of significance (P<0.05). In consequence, coconut shell for stress-relieving massage could relieve the stressand cervicogenic headache, and affected to the better change of relative variables in patients with stress as theappropriate and effective innovation for self-stress relief
Keywords: Local wisdom, Traditional innovation, Effectiveness, Stress relaxing massage
suicide [2].

INTRODUCTION
Stress is the most common mental
health issue in all ages, it is the physical, mental andbehavioral reactions of people to the internal andexternal stimulators which might be a person,
emotion, circumstance or environment. If a person is
not adaptable when faces up the pressure, the stresswould occur and affects to unbalance the living.
Nowadays, the society has changed rapidly ineconomy, society and culture, and people have to
face up many issues from the economic competition
that affects to their physical and mental health. Fromthe study of World Health Organization (WHO)which it has studied the circumstance or painfulness
affecting to the stress and mental health in 21
countries around the world revealed that witnessing
violence 2 1 .8 %, experiencing interpersonal violence
18.8%, accidents 17.7%, exposure to war 1 6 . 2 %,The wisdom of local people or local
medicine, the passing on knowledge and experienceof living, health treatment and disease treatment
which a massage is one of the local wisdom for
health treatment. Thai massage is not only for
disease treatment but also for health treatment. A
health massage is treated for freshness, stress relief
and beautiful body [3]. From the past, the local
people or local doctor has applied the existingmaterials in their house for self-massage, disease
treatment and health treatment such as using coconut
shell for foot massage in patients with the foot pain,
analgesia in foot, inflammation of heel and forstress-relieving massage.
Samut Songkhram, Thailand is a province
with a large number of coconut which the coconut
shell is normally found in all houses and isdeveloped as the innovation for stress-relieving

trauma to a loved one 12.5% [1]. It should be careful
for the treatment in patients with stress, especiallythe monitoring system to protect a self-injury and972

GEOMATE - Mie, Japan, Nov. 21-24, 2017

massage and disease treatment. In consequence, theresearcher has studied the developing innovation andstudying the effectiveness of wisdom of the local
doctor on using coconut shell for stress-relieving
massage in Samut Songkhram province.

designing and developing innovation revealed that a
prototype of the innovation of coconut shell had
occurred, tested and developed the innovation for 2
times. (Figures 1and 2)
The findings of Phase 2 and Phase 3
revealed that most of 60 volunteers were female(71.70%), most of the age was 59 – 61 years(40.00%), most of the marital status was married(75.00%), most of the occupation was agriculturist(53.40%) and most of them were not have the

OBJECTIVE

1. To develop the innovation fromcoconut shell for health treatment.
2. To study the effectiveness of wisdomof the local doctor on using coconut shell for stressrelieving massage
MATERIALS AND METHODS
DesignThis study was the research anddevelopment.
The study was approved by the Ethics
Review Committee for Research Involving Human
Subjects, Mahasarakham University (number
273/2557).

congenital disease (73.30%).
Figure 1: A prototype of the innovation of coconut

Subjects
The sample groups were 60 patients at theage of 18 years old and above who were selected byusing the Self-Stress Assessment (SSA) of
Department of Mental Health (DMH) and weretreated by getting coconut shell massage.
shell.
Figure 2: The massage points of coconut shell forstress relaxing massage.

Measurement Instruments
The measurement instruments were SelfStress Assessment (SSA), Visual Analog Scale(VAS), Cervical Range of Motion (CROM), Tissue
Hardness Meter and Algometer, and Heart Rate
Variability (HRV).

Assessing the level of cervicogenic
headache by using Visual Analog Scale (VAS)
before and after treating by coconut shell massage inthe 5th day revealed that the level of cervicogenic
headache was decreased with 0.95 level ofsignificance (P<0.05).

Intervention
The volunteers who were selected would
get 10-minute of coconut shell massage for 5 days
and they were assessed before and after thetreatment.

Assessing the cervical range of motion;
cervical flexion, cervical extension, cervical leftlateral flexion and cervical right lateral flexion
compared before and after of the treatment bycoconut shell massage in the 5th day revealed that
all the cervical range of motions were increased with
0.95 level of significance (P<0.05).

Statistical Analysis
In this research, the descriptive statistic wasused to describe the characteristic of volunteers;mean and standard deviation. Additionally, thepaired t-test was used to analyze the variables
compared before and after of the treatment with 0.95
level of significance (P<0.05).

Assessing the pressure pain threshold(kg/cm2) compared before and after of the treatment
by coconut shell massage in the 5th day revealed
that the pressure pain threshold was increased with
0.95 level of significance (P<0.05).

RESULTSThe findings of Phase 1 – Developing
innovation of coconut shell for stress-relieving
massage; from the study of coconut shell, principles
of medical physics, anatomy and physiology for

Assessing the tissue hardness before andafter treating by coconut shell massage in the 5th973GEOMATE - Mie, Japan, Nov. 21-24, 2017

day revealed that the tissue hardness was increased
with 0.95 level of significance (P<0.05).

Patients with Cervical Spondylosis: Comparison of
Therapeutic Effects of Non-Steroidal AntiInflammatory Drug and Traditional Thai Massage
which the findings of 8 weeks study revealed thatcervical flexion, cervical extension, cervical leftlateral flexion and cervical right lateral flexion after
treating by Thai massage were increased and could
be described that Thai massage would stretch themuscle, decrease the muscle fascia and increase themuscle flexibility.

The findings of heart rate variability
from the study of Time Domain Analysis; SDNN,
RMS-SD and the study of Frequency Domain
Analysis; LF, HF, LF/HF compared before and afterof the treatment by coconut shell massage in the 5th
day revealed that SDNN, RMS-SD and LF, HF,
LF/HF value were increased with 0.95 level ofsignificance (P<0.05).( Figure 3)

Effects of the increase of the pressure pain
threshold, it was consistent with the study of Peerada
Damapong et al.[7], Short-Term Effects of CourtType Traditional Thai Massage on Pressure Pain
Threshold and Pain Intensity in Patients with
Chronic Tension-Type Headache which revealed
that after the volunteers were treated by Court-Type
Traditional Thai Massage for assessing the pressure
pain threshold, it was increased with 0.95 level ofsignificance (P<0.05).
Effects of the decrease of the tissue
hardness, it was consistent with the study of Zheng
et al.[8], Therapeutic Evaluation of Lumbar Tender
Point Deep Massage for Chronic Non-Specific Low
Back Pain which revealed that the pressure pain
threshold and tissue hardness were increased with
0.95 level of significance (P<0.05).

Figure 3: Heart rate variability by SDNNDISCUSSION

Effects of the increase of the heart ratevariability compared before and after of thetreatment by coconut shell massage revealed that
SDNN, RMS-SD and LF of CTTM value wereincreased with the level of significance whichindicated that after treating by Royal Thai Massage,
the stress of patients was decreased (more relief);
SDNN value was increased, the variance of
myocardial function to the parasympathetic nervous
system was increased, then the stress was decreased.
It was consistent with the study of Toro-Velasco etal. [65], Immediate Effects of Head and Neck
Massage on Changing of Heart Rate Variability(HRV), Mood States, and Pressure Pain Thresholds(PPTs) in Patients with Chronic Tension-Type
Headache which revealed that HRV time interaction
had changed with the level of significance.
Additionally, it was consistent with the study ofPeerada Damapong et al. [9], A Randomized
Controlled Trial on the Effectiveness of Court-Type
Traditional Thai Massage versus Amitriptyline inPatients with Chronic Tension-Type Headache
which had assessed the Heart Rate Variability(HRV) before and after the treatment in patientswith tension-type headache revealed that after
treating by Thai massage, the heart rate variability
hadchangedwhich
indicatedthattheparasympathetic nervous system was increased(P<0.05). In consequence, the innovation of coconut

The findings of the level of pain revealed
that VAS value was decreased with the level ofsignificance, it was consistent with the study ofPeerada Damapong et al.[4], Effectiveness of CourtType Traditional Thai Massage in Patients with
Chronic Tension-Type Headache: A Pilot Study
which revealed that the level of headache wasdecreased with 0.95 level of significance (P<0.05).
Effects of a decrease of the level of pain bycoconut shell massage could be described as thephysiological effect that massage was the pressure
through skin and muscle which affected to increase
the circulation of blood and lymph. Additionally, theincreased blood circulation might be an effect ofstimulating the sympathetic nervous system; when
the circulation of blood and lymph were increased,
the vascular and excretory system were also
increased that affected to decrease the inflammation,
edema and pain [5].
The findings of assessing the cervical rangeof motion revealed it was decreased with 0.95 levelof significance which the volunteers were treated bycoconut shell massage and affected to a relief of thecervical muscle, an increase of blood circulation andcervical range of motion, it was consistent with thestudy of Eungpinichpong et al.[6] in 2 0 0 0 ,Therapeutic Effects of Traditional Thai Massage on974

GEOMATE - Mie, Japan, Nov. 21-24, 2017

shell for stress-relieving massage could increase theparasympathetic nervous system and affected torelieve the stress.

Matschinger, H., Mneimneh, Z., Nakamura, Y.,
Ormel, J., Posada-Villa, J., Sagar, R., Scott, K.M.,
Tomov, T., Viana, M.C., Williams, D.R., Nock,
M.K. Cross-national analysis of the associations
between traumatic events and suicidal behavior:findings from the WHO World Mental Health
Surveys. PLoS One. 2010 May 13;5(5):e10574.
[2]. Damapong, P. and Damapong, P. (2016).
Model Development for Outbreak of Dengue Fever
Surveillance System in District Level. International
Journal of GEOMATE. 11(27): 2777-2781.
[3].The Foundation for the Promotion of Thai
Traditional Medicine Ayurved School, Traditional
massage (Court-type Thai traditional massage).
2005, Bangkok: Pickanesprinting[4].Damapong, P. Kanchanakhan, N.
Eungpinichpong, W, and Damapong, P (2015).
Effectiveness of court-type traditional thai massage
in patients with chronic tension-type headache: apilot study. J Health Res. 29(5): 351-356.
[5]. Eungpinichpong, W., Therapeutic Thai Massage.
2008, Bangkok: Chonromdek publishing house.
[6]. Eungpinichpong, W., et al., Therapeutic effectsof traditional Thai massage on patients with cervicalspondylosis: comparison of therapeutic effects of
non-steroidal anti-inflammatory drug andtraditional Thai massage. KKU Research Journal
2000. 2: p. 5-7.
[7]. Damapong, P. Kanchanakhan, N.
Eungpinichpong, W., Putthapitak, P,
and Damapong, P., Short-Term Effects of CourtType Traditional Thai Massage on Pressure Pain
Threshold and Pain Intensity in Patients with
Chronic Tension-Type Headach. International
Journal of GEOMATE.vol. 11, no. Dec., 2016..
[8]. Zheng, Z., et al., Therapeutic evaluation oflumbar tender point deep massage for chronic nonspecific lowback pain. JTCM, 2012. 32(4): p. 534537.
[9]. Damapong, P. Kanchanakhan, N.
Eungpinichpong, W., Putthapitak, P,
and Damapong, P., (2015). A Randomized
Controlled Trial on the Effectiveness of Court-Type
Traditional Thai Massage versus Amitriptyline inPatients with Chronic Tension-Type Headache. Evid
Based Complement Alternat Med.2015(2015): 12
pages.

CONCLUSION
The findings of developing innovation andstudying the effectiveness of wisdom of the local
doctor on using coconut shell for stress-relieving
massage revealed that; The decrease of Current
visual analog scale (CVAS) with the level ofsignificance, nevertheless, the other variables wereconsistently such as the increase of cervical range of
motion after treating by coconut shell massage
which affected to a relief of the cervical muscle andan increase of blood circulation. The increase ofpressure pain threshold with the level of significanceafter treating by coconut shell massage. The
decrease of tissue hardness with the level ofsignificance indicated that coconut shell massage
could decrease the muscle tone. The decrease ofheart rate variability compared before and after of
the treatment revealed that SDNN, RMS-SD, LF and
LF/HF were increased with the level of significancewhich indicated that after treating by coconut shellmassage, the stress of volunteers was decreased(more relief). In consequence, coconut shell massage
could relieve the stress and cervicogenic headache,and increase the parasympathetic nervous system
which affected to relieve the stress in patients, anddecrease the variables which related to thecervicogenic headache and stress for the betterchange.
ACKNOWLEDGEMENTS
This study was supported by the Office of theHigher Education Commission : OHEC. Thispublication has been supported by Suan Sunandha
Rajabhat University, Bangkok, Thailand.
REFERENCES[1]. Stein, D.J., Chiu, W.T., Hwang, I., Kessler, R.C.,
Sampson, N., Alonso, J., Borges, G., Bromet, E.,
Bruffaerts, R., de Girolamo, G., Florescu, S., Gureje,O., He, Y., Kovess-Masfety, V., Levinson, D.,975

Seventh International Conference on Geotechnique, Construction Materials andEnvironment, Mie, Japan, Nov. 21-24, 2017, ISBN: 978-4-9905958-8-3 C3051

SHORT-TERM EFFECTS OF THE AROMATHERAPY TO REDUCESTRESS IN THE ELDERLY
Pongmada Damapong1, Peerada Damapong1 and Kanyamanee Koomhangsung1
1 College of Allied Health Science, Suan Sunandha Rajabhat University, Bangkok 10300, Thailand
ABSTRACTThis research was aimed to study the effects of stress treatment by inhaling the aromatherapy oflavender essential oil. It was a quasi-experimental research; the populations of this research were the elderly
people in Wat Khok Ket Health Promoting Hospital, Plai Phong Phang Sub-district, Amphawa District, SamutSongkhram Province. The data was compiled using the questionnaire for the level of stress assessment to select40 participants; 20 for the experimental group and 20 for the control group, by using random samples method.
The experimental group was treated by inhaling the aromatherapy of lavender essential oil; the volunteers would
lie down and inhale the essential oil from the kiln in 10 minutes for 3 days and the control group would receive acommon suggestion. Both of 2 groups were assessed by using the HRV (Heart Rate Variability) before and after
the experiment for comparing their results. The statistics for data analysis were percentage, mean and standard
deviation, paired t-test and t-test.
As to the research result, the SDNN (Standard Deviation of Normal to Normal) and HRV score of
the experimental group before and after the experiment had a differentiation with 0.95 level of significance(P<0.05). Additionally, the SDNN and HRV score of the experimental group after the experiment were morethan the control group with 0.95 level of significance (P<0.05).
The findings revealed that using the aromatherapy could treat the stress; in consequence, inhaling thearomatherapy of lavender essential oil is a choice for the stress treatment.
Keywords: Short-term effects, Aromatherapy, Stress, Elderly

INTRODUCTION

better physical, mental and health balance.

Nowadays, stress becomes a significant
issue of mental health in all ages which affects to thebody systems; the nervous and brain system,
endocrine system and immune system. The person
who has a high stress would affect to the gastricdisease, hypertension, coronary disease, insomnia
and tension-type headache [ 1]. From the study of atrend of Thai population revealed that the elderly
people tended to increase rapidly which they had theregressive changes, some of them were forced andaffected to their physical and mental health, and thestress had occurred. From the report of Thai
people’s mental health of Department of Mental
Health and National Statistical Office of Thailand
2008 – 2010 revealed that the elderly people had thelowest score of mental health compared with theother ages [ 2] and the health care of the elderly
people should have a monitoring system for thehealth administration to monitor the unexpected
symptoms [3]. In consequence, having a good healthshould have the stress management or stresstreatment which the aromatherapy is a choice for the
stress treatment by using the natural aroma or
essential oil as it affected to the nervous system,
relieve the stress and anxiety, relieve or stimulate theFrom the information of this issue, theresearch had studied the stress and effects ofreducing stress by inhaling the aromatherapy oflavender essential oil from the kiln in the elderly
people, and brought the research result for defining a
guideline of reducing stress of the elderly people.
OBJECTIVE
General Objective
To study the effects of aromatherapy on
reducing stress of the elderly people.
Specific Objective
1 . To study the heart rate variation of theelderly people who was treated by inhaling thearomatherapy of lavender essential oil.
2 . To compare the effects of aromatherapy
on reducing stress of the elderly people in theexperimental group and the control group.

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GEOMATE - Mie, Japan, Nov. 21-24, 2017

Figure 2: Aromatherapy of lavender

MATERIALS AND METHODS
DesignThis research was the quasi-experimental
research which conducted in Wat Khok Ket Health
Promoting Hospital, Plai Phong Phang Sub-district,
Amphawa District, Samut Songkhram Province.
Subjects
The sample groups were 40 elderly people
at the age of 60 years old and above who wereselected with the moderate level by the questionnaire
for the level of stress assessment; 20 for theexperimental group and 20 for the control group.
Assessment
Both of 2 groups were assessed by using the HRV
before and after the experiment for comparing theirresults. (Figures 1)
Measurement Instruments
The data was compiled using the Suanprung
Stress Test-20 (SPST-20) of Department of Mental
Health and the HRV.

essential oil.
Statistical Analysis
The researcher had conducted theexperiment by announcing for the elderly people asvolunteer, selecting 40 volunteers by thequestionnaire for the level of stress assessment; 20
for the experimental group and 20 for the control
group, using random samples method by drawing
and signing an agreement of the 3 days experimentparticipation, assessing before the experiment by the
HRV after assessing before the experiment of theexperimental group who was treated by thearomatherapy for 10 minutes, and the control groupwould receive a common treatment and assessed by
the HRV after the experiment immediately. The
research was conducted for 3 days and assessed
before and after the experiment immediately in eachprocess.
RESULTSThe findings revealed that; in theexperimental group: most of them were female 75%
and male 25% and in the control group: most ofthem were female 90% and male 10%, most of theage was 60 – 65 years old: 35% in the experimentalgroup and 40% in the control group. The findings ofusing the aromatherapy in relieve the stress by the
HRV revealed that SDNN, LF (Low Frequency) andHF (High Frequency) scores from before and after
the experiment immediately had increased with 0.95
level of significance (P<0.05). (Figures 3)

Figure 1: Assessed by using the HRV
before and after the experiment.
Intervention
The experimental group was treated byinhaling the aromatherapy of lavender essential oil;the volunteers would lie down and inhale theessential oil from the kiln in 10 minutes for 3 days
and the control group would receive a common
suggestion. (Figures 2)

Figure 3: Heart rate variability by SDNN within
experimental group.
Additionally, the comparison between theexperimental group and the control group revealed
that SDNN of HRV score after the experiment had
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GEOMATE - Mie, Japan, Nov. 21-24, 2017

increased with 0.95 level of significance (P<0.05).
(Figures 4)

As to the findings and the research which
they were consistent with the study of essential oil in
reducing stress of the elderly people, the assessmentof the HRV revealed that SDNN, LF and HF scoresfrom before and after the experiment immediately ofthe experimental group and the comparison between
the experimental group and the control group had
increased with 0.95 level of significance (P<0.05), it
showed that after the volunteers were treated by the
essential oil, they had less stress (more relief).
Nevertheless, inhaling the essential oil could reduce
the stress and increase the parasympathetic nerve
which affected to reduce the stress of the volunteers
and the better changes of variables that related to thestress of the elderly people.

Figure 4: Heart rate variability by SDNN
between groups
ACKNOWLEDGEMENTSDISCUSSION

This study was supported by the Suan Sunandha
Rajabhat University, Bangkok, Thailand.

The findings revealed that after theexperiment, the experimental group who was treatedby the aromatherapy had SDNN of HRV scoreincreasingly which affected to the parasympathetic
nerve and stress reduction. It was consistent with thestudy of Waraporn Yammeesri [ 4], the study ofeffects of aromatherapy in relieving stress of patientsin the Intensive Care Unit (ICU), Chiang Rai
Prachanukroh Hospital revealed that the patient who
was treated by the aromatherapy had the physicalchanges of relief; reducing in heart rate, breathing
rate and mean coronary pressure. Buckle, [ 5] which
had studied the patient after operating without the
respirator but remaining in the ICU compared with
applying 2 types of the aromatherapy for thephysical changes; Lavender A ( Lavendula
Angustifolia) and Lavender B (Lavendula Burnatii),
it was revealed that 2 types of lavender had affectedto the physical changes; reduce the breathing rate,
relieve the stress. Additionally, it was consistent
with the study of Peerada Damapong and team, thestudy of short-term effects of court-type traditional
Thai massage on pressure pain threshold and pain
intensity in patients with chronic tension-type
headache [ 6] which the findings revealed that thearomatherapy could reduce the stress of the elderly
people.

REFERENCES[1]. Ward TN, Levin M, Philips JM. Evaluation andmanagement of headache in the emergency
department. Med Clin North Am 2001; 85: 971–84.
[2]. National Statistical Office of Thailand. Statistic
Data. (2012). Executive Summary: The Report ofThai People’s Mental Health 2010. Searched on 2
October 2016. Searched fromhttp://service.nso.go.th/nso/nsopublish/themes/theme_2-4-10.html[3]. Damapong, P. and Damapong, P. (2016).
Model Development for Outbreak of Dengue
Fever Surveillance System in District Level.
International Journal of GEOMATE. 11(27):2777-2781.
[ 4].Waraporn Yammeesri. ( 2004) . Effects ofAromatherapy in Relieving Stress of Patients in the
Intensive Care Unit (ICU). Master of Nursing in
Adult Nursing, Graduate School, Chiang Mai
University.
[5]. Buckle, J. (1993).Aromatherapy.Nursing
Times,89(20),32-35[6]. Damapong, P. Kanchanakhan, N.
Eungpinichpong, W.,and Damapong, P., ShortTerm Effects of Court-Type Traditional Thai
Massage on Pressure Pain Threshold and Pain
Intensity in Patients with Chronic Tension-Type
Headach. International Journal of GEOMATE.vol.
11, no. Dec., 2016..

CONCLUSION

978

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IMMEDIATE EFFECTIVENESS OF TRADITIONAL THAI MASSAGE
ON CERVICAL RANG OF MOTION WITH CHRONIC TENSION-TYPE
HEADACHE
Chamiporn Kongmong1 and Peerada Damapong1
1College of Allied Health Science, Suan Sunandha Rajabhat University, Bangkok 10300, Thailand
Abstract
This research was aimed to assess the immediate effectiveness of Thai traditional massage on
cervical range of motion in patients with tension-type headache. The data was compiled using the quasiexperimental research design; the populations of this research were 30 patients with tension-type headache, theassessment was before and after receiving the 45-minute of Thai traditional massage. The results were assessed
immediately after the intervention which consisted of the increased cervical range of motion after receiving theThai traditional massage while a significant difference was occurring (P < 0.05). In conclusion, Thai traditional
massage would relieve the muscle tension by reducing its pain and increase the cervical range of motion.
Keywords: Immediate effectiveness, Traditional Thai Massage, Cervical Rang of Motion, Chronic Tension-type
headachemore chronic tension-type headache. Therefore, theaim of treatment of the chronic tension-type
headache is to emphasize on decreasing a volume ofusing the medicine or change to the nonpharmacologic treatment are the safe methods for
reducing a risk state from the pharmacological effector painkiller addiction [ 3] which there are various
methods. Nevertheless, the treatment by Thai
traditional massage becomes a key role [4] to protect
the tension-type headache systematically formonitoring the unexpected tension-type headache orillness [5].
The Thai traditional massage is one of thetreatments for the muscular pain [6]. The massage isdivided into 2 types; the royal massage and generalmassage, which are different technics [7 ]. The aims
of massage are for; the better blood circulation,
relieve the muscle tension, increase the cervicalrange of motion, extend the capillary, increase theelimination from cell to the vein system and thebetter urine which would reduce the pain from thearrearage of the chemical substance from cellfunction and affected to decrease the hypertension.
In consequence, this research was aimed to
study the immediate effects of Thai traditional
massage on cervical range of motion in patients withtension-type headache as the guideline for thetreatment choice and affirm its treatment result to be
more accepted.

INTRODUCTION
The tension-type headache is the mostcommon type of headache, it could continue for few
days, a week or a month which is disturbing, causes
the uncomforting and it could be stable. However, it
is not harmful but it comes and it goes. It probably
occurs in patients with Episodic Tension-Type
Headache (ETTH) or Echronic Tension-Type
Headache (CTTH). Otherwise, it is an effect fromcontinue using the painkiller for a long time, so theaim of treatment is to use less medicine or change tothe non-pharmacologic treatment especially thetreatment by Thai traditional massage as it is fromthe various methods.
The tension-type headache is the pain
above the eyes, ears and around the head or might beon the upper back [ 1]. Nowadays, most of thetension-type headache is the Tension-Type
Headache (TTH) which consists of; pressure pain
threshold on the temple or forehead occurring on 2
sides of the head and might be on the occiput or
cervical area, and the intenseness is in the low tomoderate level that patients can spend the day
normally [ 2]. The factors of this Tension-Type
Headache (TTH) consist of; stress, anxiety, sadness,
insanitary motion and hardworking of the cervicalmuscle which affect to the contracture of cervicaland scalp muscle [2]. The treatment is divided into 2
types; 1) Pharmacologic treatment and 2) Nonpharmacologic treatment due to continue using the
medicine for a long time w hich could cause it to be
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objected by conducting the result analysis
immediately in the first day of the assessment.

MATERIALS AND METHODS
DesignThis research was the quasi-experimental
research design which the cervical range of motion
assessment was conducted in the Department of
Traditional Thai Medicine, Bamnet Narong
Hospital, Bamnet Narong District, Chaiyaphum
Province, Thailand

RESULTSThe findings of the general informationof 30 volunteers revealed that; most of them werefemale (86.70%), most of the age was 37 – 50 years
old (43.30%), most of the marital status was married(86.70%) and most of them have no chronic disease(83.30%), most of the tension-type headache was 15
times per month or more (1 0 0 %), most of thetension duration was 30 minutes - 1 hour (60.00%)
and the level of tension-type headache in 24 hours
last week was 6.26±1.17.
The assessment of the level of tensiontype headache by the Visual Analog Scale (VAS)
before and after the treatment immediately revealed
that the VAS score was decreased with 0.95 level ofsignificance (P < 0.05).
The assessment of the cervical range of
motion; cervical flexion, cervical extension, cervicalleft lateral flexion, cervical right lateral flexion
before and after the treatment immediately revealed
that the immediate cervical range of motion wasincreased with 0.95 level of significance ( P < 0.05)(Table 1).

Subjects
The sample groups were 30 patients at theage of 18-65 years old with chronic tension-type
headache, at the level 4 of VAS score by the criteriaof chronic tension-type headache of International
Headache Society: IHS[2]Assessment
This research was the cervical range of
motion assessment.
Measurement Instruments
In this research, the Visual Analog Scale(VAS) was used to assess the level of the tensiontype headache which was a straight line with 10
centimeters long. The volunteers would mark thelevels of the tension on the straight line; the left
hand side was no tension (VAS = 0) and the righthand side was the highest tension (VAS = 10) which
represented to the level of the tension-type headache
before and after the treatment immediately, and theresults were recorded as centimeter. Additionally,
the Cervical Range Of Motion (CROM) was used toassess the cervical range of motion; cervical flexion,
cervical extension, cervical left lateral flexion,
cervical right lateral flexion, in a week before thetreatment, before and after the treatment
immediately, and the results were recorded as
degree.

Table 1 Comparison of the outcome measures
between baseline (pre-test) and post-test
assessments in Cervical range of motion(degree) (paired t-tests).
Baselin Immediate
OutcomeP-valuee(Mean ± SD)
Cervical
52.94± 58.16± 10.55 <0.05
flexion
9.27
Cervicalextension(%); mean ±SD
Cervicalleft lateral
flexion
Cervicalright lateral
flexionmean± SD

Intervention
The volunteers were treated by getting 45minute of Thai traditional massage which was thepressure threshold; shoulder muscle, cervicalmuscle, front head and back head.

60.22±
7.37

64.38± 8.15

<0.05

37.49±
6.0

43.94± 6.98.

<0.05

36.22±
6.49

41.27± 7.83

<0.05

Note: CTTM is court-type traditional Thai massage.
NA is not available. 𝑃𝑃< 0.05 is statisticallysignificant differences from baseline.

Statistical Analysis
In this research, the descriptive statistic wasused to describe the characteristic of volunteers;mean and standard deviation. Additionally, thepaired t-test was used to analyze the variables as
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DISCUSSIONCONCLUSION

The findings of the immediate cervicalrange of motion assessment were different in eachmotion with 0.95 level of significance ( P < 0.05)
which was increased more than 5 degrees. In
consequence, it was different in the clinicalsignificance that the volunteers were treated the Thai
traditional massage would have a relief of muscle,
shoulder muscle, cervical muscle, better blood
circulation and affected to the better cervical rangeof motion.
The findings were consistent with the studyof Kruapanich et al.[8], the study of Thai traditional
massage (TTM) group compared with a nappingwith the episodic tension-type headache after thetreatment for volunteers of the TTM group, thecervical range of motion was increased with 0.95
level of significance ( P < 0.05) ; cervical flexion,
cervical extension, cervical left lateral flexion,
cervical right lateral flexion. Additionally, thecomparison of each TTM group revealed that it had
more cervical range of motion than who had a relief
with 0.95 level of significance ( P < 0.05) of all
cervical range of motion at after 3-week, 6-weekfollow-up after the final treatment in TTM group.
Besides, it was consistent with the study of Sooktho
et al.[9], the study of effectiveness of Thai
traditional massage in patients with chronic tensiontype and migraine headache compared with thegroup immediately at after 3-week, 6-week followup after the final treatment, the group who weretreated by g e t t in g Thai traditional massage had abetter cervical range of motion than the shamultrasound group. Moreover, it was consistent withthe study of Puusjarvi et al. [10], the finding
revealed that cervical range of motion was increasedin the 3 and 6 phase. Lastly, it was consistent withthe study of Eungpinichpong et al.[11] in 2 0 0 0 , thestudy of therapeutic effects of Thai traditional
massage on patients with cervical spondylosis:
comparison of therapeutic effects of non-steroidal
anti-inflammatory drug and Thai traditional massage
for 8 weeks, it revealed that after the treatment by
Thai traditional massage; cervical flexion, cervicalextension, cervical left lateral flexion, cervical rightlateral flexion were increased as traditional Thai
massage by stretching the muscle would decrease its
tension and increase the cervical range of motion.

As the findings and the research whichwere consistent with the study of the cervical rangeof motion was increased after its studies, revealed
that Thai traditional massage would increase thecervical range of motion due to Thai traditional
massage had decreased its tension and increased thecervical range of motion [63] which affected toincrease the cervical range of motion in all direction.
In addition, there was a difference between before
and after the treatment by Thai traditional massage
which the pressure threshold on muscle and in-depth
had affected to stimulate the peripheral receptor toreact directly on those areas to be treated [64] thatwould decrease its tension and increase the cervicalrange of motion.
ACKNOWLEDGEMENTS
This study was supported by the National
Research Council of Thailand. This publication has
been supported by Suan Sunandha Rajabhat
University, Bangkok, Thailand.
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982

Authors Index

A

Ali Nisari Tabrizi

184

A.B Sambah

653

Alsidqi Hasan

72

A.B.K.T. Piumali

345

Alvin Lal

640

A.M.N Alagiyawanna

345

Amin Esmail Khalil

678

AUNG AUNG SOE

148

Amorn Chaiyasat

505

Abdul Hakam

222

Amorn Chaiyasat

839

Abdul Hakam

218

Andy Fourie

72

Abdul Hakam

499

Anoop Aujayeb

108

Abdul Hakam

494

Anthony Shun Fung Chiu

114

Abdul Halim Abdul Latiff

700

Ariya Aruninta

694

Abdul Halim Abdul Latiff

678

Arul Arulrajah

2

Abdul Naser Abdul Ghani

821

Arul Arulrajah

96

Abdulla Omarov

383

Asel Tulebekova

383

Abu Bakar Sambah

577

Asemgul Moldazhanova

383

Abu Bakar Sambah

706

Askar Zhussupbekov

383

Adrian McCallum

298

Atchariya Saengthongthip

90

Adrian McCallum

304

Atsuko Sato

167

Adrian McCallum

315

Atsushi Yashima

78

Afshin Asadi

28

Aung Kyaw Soe

713

Agnes Garciano

588

Avirut Chinkulkijniwat

108

Ahmad Amirul Faez

66

Ayaka Oya

275

Akihiko Naganuma

206

Akihiko Taira

255

B

Akihiko Yagi

805

Badhrulhisham Abdul Aziz

72

Akihisa Nakahashi

361

Bambang Istijono

222

Akira Kondo

634

Barrios Gonzalo

234

Akira MITSUMORI

269

Barry KASSAMBARA

755

Alexander Rubinstein

333

Bernardo A. Lejano

411

Alexis M. Fillone

660

Bernardo A. Lejano

417

AlfanJauhari

706

Bernardo A. Lejano

464

Ali Alnedawi

355

Bernardo A. Lejano

435

Ali Murtaza Rasool

60

Bithin Datta

640

Authors Index

Cynthia Debby Heriyani

339

Bithin Datta

725

Bithin Datta

732

Bithin Datta

775

D

Boonchai Wichitsathein

912

D.A.A. Putri

939

Boonlert Archevarapuprok

866

D.G.R Wiadnya

653

Boontida Uapipatanakul

839

DR. K K GANGULY

511

Bujang B.K.Huat

28

Daeyoung Lee

373

Daisuke Komori

84

Dang Thi Thanh Huyen

127

C
C. S. Kalpage.

666

Dang Thi Thanh Huyen

477

Caiqian Yang

918

Defrian Marza Arisandi

577

Charlle Sy

114

DefrianMarzaArisandi

706

Chatchai Ponchio

849

Dilip Kumar Roy

725

Chatchai Ponchio

854

Dong Daicho

361

Chatchai Ponchio

858

Dong Hyun Kim

133

Chatchai Ponchio

863

Dongmin Kim

373

Chaweewan Denpaiboon

275

Dongya Yang

924

Chayanon Hansapinyo

281

Dr. Wanchai Teparaksa

293

Chayanon Hansapinyo

531

Dr.Neelima Satyam D

367

Chee-Loong Wong

827

Cheerawit Rattanapan

790

E

Cheerawit Rattanapan

713

Edward Ephrem T. Codilla II

160

Cheerawit Rattanapan3

738

Emmanuel Bastian Pelaez

453

Cherdsak Suksiripattanapong

429

Erica Elice Saloma Uy

447

Cheryl Lyne C. Roxas

435

Erica Elice Saloma Uy

441

Cheryl Lyne C. Roxas

464

Erika Ueno and Hiroyuki Ii

878

Chia-Yun Wei

228

Chinnapat Buachart

531

F

Chinnapat Buachart

281

Fauzan494

Chollachai Kamtawai

945

Fauzan405

Clare Olver

564

Fauzan499

Claudia Lovina A N

405

Fauzan Sahdi

72

Authors Index

Febrin A Ismail

494

Hirohisa Muto

206

Febrin Anas Ismail

405

Hirokazu Abe

564

Febrin Anas Ismail

499

Hiroki Kitagawa

623

Firman Farid Muhsoni

653

Hiroki Kohmori

593

Fuad

577

Hiroki Nishiwaki

896

Fumitake Nishimura

690

Hiromi Suda

805

Fusanori Miura

577

Hiroshi Kono

684

Hiroshi Takebayashi

599

Hiroto Akimoto

249

G
G.B. Herath

666

Hiroyuki Hashida

178

G.M.P. Kumara

611

Hiroyuki Ii

623

Gicheol Lee

178

Hiroyuki Ii

890

Gulshat Tleulenova

383

Hiroyuki Ii

896

Guntur577

Hiroyuki Ii

684

Hiroyuki Nagahama

845

Hiroyuki Shimogaki

684

H
H.B. Ng

399

Hiryuki Ii

872

HamidTeennejad184

Ho Cho255

Hanan Elsawahli

810

Homayoon GANJI

755

Hanbin Ge

918

Hong-Da Chou

228

Hania Arif

794

Hongxiao Liu

929

Hanqiang Yu

924

Hongyang Cheng

558

Heka P Andriani

218

Hossain Md Shahin

351

Hide Sakaguchi

255

Hossain Md. Shahin

246

Hideki MAEDA

269

Hidenori TANAKA

483

I

Hidenori YOSHIDA

617

ISHIGURO Satoru

744

Hidenori Yoshida

628

ISLAM Mohammad Raihanul

744

Hideto Ohmori571

ITO Ryoei

744

Hidetoshi NISHIOKA

269

ITO Tetsu

744

Hideyuki Katsumata

934

Idawati Ismail

470

Hikari Shimadera

634

Ignacio Fructuoso Solís Quispe287

Authors Index

Ikki Tateishi

934

Jonathan Rivera Dungca

447

Ildo Muhary Putra

939

José Carlos Solís Tito

287

Ilyas AKRAM

148

Junichiro Takeuchi

884

Ivan Gratchev

133

Jutaporn Tanok

90

Ivan Syed

525

Jyunji Uno

684

K

J
Jaksada Thumrongvut

429

K. Kawamoto

345

James Matthew L. De Jesus

411

Kakuta Fujiwara

78

Jareeya Yimrattanabavorn

912

Kali Prasad Nepal

355

Jareeya Yimrattanabavorn

906

Kanokwan Rudisirisak

672

Jeremy Stephens

133

Karin Kandananond

389

Jicheng Xu

924

Karlygash Borgekova

383

Jim Shiau

36

Katsuhiro Shibano

249

Jin Ishii

694

Katsuya Suzuki

249

Jinichi Koue

634

Kazuhei Kikuchi

845

Jirat Teparaksa

293

Kazuhiro Ishimaru

178

Jiro KUWANO

148

Kazuhiro KANEDA

240

Jiro Kuwano

60

Kazunori Nakashima

423

Jittanan Kawilanan

945

Kazunori Nakashima

719

Joenel G. Galupino

605

Kazuya Itoh234

Joenel Galupino

114

Kazuya Itoh249

John Tri Hatmoko

339

Kazuya Itoh154

John Yeaman

315

Keiichi Toda

599

John Yeaman

298

Keiichiro SHIBATA

617

John Yeaman

304

Keiichiro Shibata

628

Jon Arnel S. Telan

102

Keiji Okumura

178

Jonathan Dungca

114

Keisuke Kase

571

Jonathan R. Dungca

605

Keita Sugito

321

Jonathan R. Dungca

102

Keita Sugito

327

Jonathan R. Dungca

160

Ken Kawamoto

127

Jonathan Rivera Dungca

441

Ken Kawamoto

477

Authors Index

Ken Kawamoto

611

M.I.M. Mowjood

666

Ken Kawamoto

666

Mahdi Miri Disfani

96

Kenichiro Nakarai

212

Mai Furukawa

934

Kennedy K.

902

Maki Oyagi

805

Kenta Eguchi

212

Maki Oyagi

647

Kenta Fukagawa

694

Makoto Takemoto

546

Kentaro Uemura

142

Mamoru Kawasaki

488

Kentaro Uemura

234

Mario Edisson Quilli Apaza

287

Khondoker Istiak Ahmad

246

Mary Ann Q. Adajar

43

Kiyoshi Numakami

249

Mary Ann Q. Adajar

49

Ko Hashimoto

172

Masaaki Hanaoka

571

Koichi Nagao

142

Masaaki Takahashi

647

Koji WATANABE

269

Masaaki Tanaka

805

Kota Kono

361

Masami Matsui

584

Kousuke Takahama

78

Masamichi AOKI240

Kouta Katagishi

546

Masamitsu Fujimoto275

Krister Ian Daniel Roquel

660

Masanobu Taniguchi

872

Kritika Trakoolngam

137

Masanori Shimomura

200

Kyle Solomon D. Pineda

417

Masato Kikuchi

571

Kyoichi OKAMOTO

770

Masato Takenaka

599

Masatsugu Kiko

546

Masayuki Fujihara

884

L
Lanh Si Ho

212

Masayuki KODA

263

Lessandro Estelito Garciano

588

Masnun Abrar

246

Lucie Mynarzova

458

Md Amanul Hasan

525

Luky Handoko

339

Md. Al Imran423

Md. Aminul Islam

36

Md. Ashraful Islam Molla

934

M
M Sofian Asmirza

494

Melvyn Leong96

M Sofian Asmirza

218

Menglim Hoy

2

M. Azizul Moqsud

66

Michael S. Hayford

775

M. Mahmudi

653

Michiko Masuda

690

Authors Index

MiladGhannadzadehKermani

184

Nattapong Damrongwiriyanupap

429

Miller DL. Cutora

43

Navid Khayat

377

Minoru Morioka

212

Nawawi Chouw

234

Minoru YAMANAKA

269

Nguyen Hoang Giang

127

Minxue Zheng

929

Nguyen Hoang Giang

477

Miroslav Mynarz

458

Nguyen Van Tuan

127

Mohammad Noori918

Nguyen Van Tuan

477

Mohammad Reza Atrchian

184

Nicanor R. Roxas Jr

660

Mohammadjavad Yaghoubi

96

Niphawarn Kangkun

863

Mohammed Khachi Hatem

188

Nittaya Ngowattana

672

Moises Carl Caneca

453

Nobuo Fukushima

361

Muhammad Abdur Rahman

351

Nobutaka Hiraoka

234

Muhammad Ihsan

939

Noel Lester C. Gozum

102

Muqdad Al-Juboori

732

Noriko Otsuka

564

Muzamir Hasan

66

Noriyuki Okano

55

Myint Win Bo

96

Norsuzailina Mohamed Sutan

72

Nuanlaor Kiama

858

Nur Aqilah Ahmad Faisal

821

N
N.H Priyankara

345

Nurfarhana Aisya Anuar

700

NAGAOKA Seiya

744

Nurulhuda Nadziri

470

Nahathai Chotklang

790

Nutchanon Siri

531

Nair A

902

Nuzaihan Aras Agus Salim

821

Najumuddin Anjum

782

Naoaki Suemasa

142

O

Naoaki Suemasa

154

OKAJIMA Kenji

744

Naoaki Suemasa

234

Oleg Kupervasser

333

Naoaki Suemasa

249

Oranee Roongrueang

906

Naomasa Honda

194

Orapin Laosee

713

Naomichi Matsumoto

628

Orapin Laosee

790

Naotaka Kikkawa

234

Naozo FUKUDA

269

P

Nattapong Damrongwiriyanupap

395

Pattranit Thongthep849

Authors Index

Peiqing Xiao

918

Ryohta Takatoku

234

Pensupa Wirikitkhul

906

Ryoichi Fukagawa

275

Perayos Khangkhun

552

Ryoichi Fukagawa

321

Pervaiz Ahmad Naseri

782

Ryoichi Fukagawa

327

Phang Biao Yu

66

Ryoichi Fukagawa

361

Piti Pratomkhum

281

Ryota ISHII

488

Pramet Kaewmesri

866

Preeyaporn Chaiyasat

839

S

Premkamol Thuennadee

137

Saad Farhan Ibrahim

188

Primprapa Sangjun

505

Sachie Takeuchi.

647

Prinya Chindaprasirt

395

Sakonwan Hanjitsuwan

395

Prinya Chindaprasirt

429

Sakonwan Hanjitsuwan

429

Punthila Janthaphat

738

Sangsan Wongchairattana

395

Sao-Jeng Chao228

Sartaj M.

902

Satakhun Detphan

429

Sato Shinji

815

Satoru Kawasaki

423

Q
Qian Chen

924

R
Rafiqul A. Tarefder

525

Satoru Kawasaki

719

Rajeshwar Goodary

108

Satoru OHTSUKA

240

Ratamanee Nuntasarn

90

Satoru Ueda

890

Raymond Venneker

827

Satoshi Chiba

647

Renan Ma. Tanhueco

588

Satoshi Kaneco

934

Richard M. De Jesus

453

Satoshi Matsumura

546

Rio Sandi

405

Satoshi SUGIMOTO

269

Riyadh Al-Ameri

355

Seiichi Ishida

200

Rolando Orense

234

Sethapong Sethabouppha

945

Roman Yavich

333

Shahid Iqbal

794

Roodheer Beeharry

108

Shakerullah Hashimi

782

Rosilawati Zainol

810

Shanwei Li

929

Ruchuon Wanna

552

Shigemitsu Hatanaka

429

Runglawan Rachan

2

Shigeo Honma

538

Authors Index

Shingo Asamoto

611

T

Shinya Hiramatsu

571

T. Saito

345

Shinya Inazumi

172

T. Saito M. Nagamori

666

Shinya Inazumi

178

T.J.L Tobing Dio Rizqi Irawan

939

Shinya Tsukada

764

Tadaomi Eguchi

172

Shinya Tsukada

750

Tadashi Chuman

178

Shohei Namiki

546

Taichi Hyodo

546

Shota NISHIOKA

617

Taijiro Fukuyama

571

Shuichi Kuwahara

172

Takaaki Okamoto

599

Shun Habara

249

Takahiro Tamura

584

Shunsuke Shimada

142

Takamitsu KAJISA

755

Shunsuke Shimada

154

Takamitsu Kajisa

782

Shunsuke Takiura

154

Takamitsu Sasaki

154

Shusaku Shiiba

571

Takamitsu Sasaki

142

Sindy Harvi Amalia

499

Takashi Nakayama

55

Sinin Hamdan

470

Takashi Saito

611

Sirapong Sooktawee

866

Takashi Sasaki

212

Siriluk Namwong

839

Takashi TOYAMA

770

Siska Apriwelni

499

Takatoshi Hondo

55

Siti Hanggita Rachmawati

36

Takaya KOGURE

148

Siti Noor Linda Taib

72

Takayuki Hirao

546

Sohei Itaya

55

Takayuki Shuku

558

Somsak Wongsawass

713

Takefumi Kurose

564

Sota Ikeda

684

Takeshi Kodaka

206

Soumik Nafis Sadeek

246

Takuma Kubohara

623

Sudjit Karuchit

906

Tam Weng Long

66

Suksun Horpibulsuk

96

Tanakorn Phoo-ngernkham

395

Suksun Horpibulsuk

2

Tanakorn Phoo-ngernkham429

Sultan Al Shafian

246

Tarmizi Ismail

827

Sumiyati Gunawan

339

Taufika Ophiyandri

222

Suriyah Tongmunee

945

Taze Jared Abubo

588

Swathi Priyadarsini Putti

367

Terry Lucke

19

Authors Index

Teruo Arase

593

U

Teruo Arase584

Udayagee Kumarasinghe

666

Teruo Nakai

351

Usa Humphries

866

Tetsuo Morita

750

Tetsuo Morita

764

V

Tetsuo Okano

593

Vatanavongs Ratanavaraha

108

Tetsuoh Shirota

593

Victor Carlo F. Torres

102

Tetsuya Ohmura

488

Vitalii Sarychev

333

Tetsuya Okano

321

Tetsuya Okano

327

W

Thapthai Chaithong

84

WATANABE Ken

744

Tharika Kaenjun

912

Wan Suzita Wan Ibrahim

810

Kumari Nawarathna T.H.

719

Warayuth Sajomsang

839

Thomas Larkin

234

Wataru Kawase

690

Tachapattaworakul Suksaroj T.

738

Watcharapol Wonglertarak

912

Timothy Scott Y. Uytengsu

102

Watcharapong Nareejun

854

Ting Wee Kiet

72

Weerawat Ounsaneha

790

Tohru Suzuki

934

Weerawat Ounsaneha

738

Tomoe KOMORIYA

770

Wenya Wen

924

Tomohiro TANIKAWA

240

Wenyi Yao

918

Tomohito Matsuo

634

WildanAlfarizi

706

Tomoko Miyagawa

564

Wincent Nicole K. Pabilona

49

Tomonori Ishigaki

127

Wonlee Nounmusig

800

Tong Ton Kien

127

Worsak Kanok-Nukulchai

281

Tong Ton Kien

477

Toshihiro Hayashi

167

X

Toshiki Nishimura

684

Xiangyang Wu

918

Toshinori Sakai

10

Xiangyang Wu

924

Tran Thi Viet Nga

127

Xiaoying Zhang

924

Tran Thi Viet Nga

477

Tsuyoshi Tanaka

142

Y

Tsuyoshi Tanaka

249

Y. Sakamoto

666

Authors Index

Y.Y. Zheng

399

Zulkifli Yusop

827

Yasushi Furugaichi

249

and Satoshi Anzai

84

Yoshiaki Kikuchi

546

Yoshifumi Taguchi

121

Yoshihito Kurazumi

694

Yoshinobu Kashihara

599

Yoshitaka Yanagihara

249

Yoshiya Touge

84

Yoshiyuki Uchikawa

584

Yota Togashi

55

Yu Fujiwara

10

Yuan Zhang

249

Yue Huang

395

Yugo Isobe

127

Yuji Yamakage

815

Yuji Yamashita

684

Yukihiro Morikawa

255

Yukimasa Takemoto

647

Yukio Uchida

172

Yuko Ishida275

Yukoh Hasunuma

142

Yusuke Tadano

200

Yuta Mitobe

84

Yuta Yamanaka

78

Yuto Sukegawa

84

Yuuya KATSUDA

269

Z
Zabihullah Mahdi

538

Zakaria Hossain

36

Zhiren Wu

918

Zhishui Liang

918

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