VOLUME 4(1)Edited by
Zakaria Hossain
Jim Shiau

GEOMATE 2014 BRISBANE, AUSTRALIAGEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENTiPROCEEDINGS OF FOURTH INTERNATIONAL CONFERENCE – GEOMATE 2014
GEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENT BRISBANE,
AUSTRALIA 19-21 NOVEMBER, 2014

Geotechnique, Construction
Materials and Environment
Edited by

Zakaria Hossain
Graduate School of Bioresources
Mie University

Jim Shiau
School of Civil Engineering and Surveying
University of Southern Queensland

THE GEOMATE INTERNATIONAL SOCIETYii

Copyright @ 2014 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: geomate@gi-j.com
www.gi-j.com

ISBN Number: 978-4-9905958-3-8 C3051

iii

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

Table of Contents

PrefaceOrganization

xi
xii

ID Keynote Papers

1

1k

2k

ID

PRACTICAL APPLICATION OF PROBABILISTIC METHODS IN GEOTECHNICAL ENGINEERING
Stephen Buttling

2

PERSPECTIVES FROM ACCURATE MEASUREMENTS OF THE STANDARD PENETRATION TEST
Julian Seidel

10

Technical Papers

11

Geotechnique

12

4103

DESIGN AND DEVELOPMENT OF COMPOSITE FOUNDATION STRUCTURE FOR SOLAR SUPPORTSYSTEM
Hossain, M.Z., Ojiro C., Ozumi, S., Harada, H. and Okuyama, S.

13

4113

DETERMINATION OF THE APPROXIMATE DYNAMIC COEFFCIENT OF FRICTION ON UNDERGROUNDPIPES DUE TO VARIOUS BLAST SCENARIOS
Akinola Johnson Olarewaju

18

4125

VERIFICATION OF RANDOM FINITE ELEMENT ANALYSIS FOR EVALUATING BEHAVIOR OF A CEMENTTREATED SOIL COLUMN
Tsutomu Namikawa

24

4132

INFLUENCE OF LIME ON STRENGTH AND COMPRESSIBILITY BEHAVIOR OF MARINE CLAY
Nor Zurairahetty Mohd Yunus, Aminaton Marto, Faizal Pakir, Khairulanam Kasran and Mohd Akmal
Azri Jamal

30

4141

SEISMIC BEHAVIOR OF SHORT GROUPED-PILES IN LIQUEFIABLE SANDY SOILS
Chung-Jung Lee, Wen-Yi Hung, Chen-Hui Tsai, Yi-Chun Tu

36

4146

CHALLENGES IN ASSESSING THE INSTALLATION EFFECTS OF CONTROLLED MODULUS COLUMNS ON
BEHAVIOR OF SURROUNDING SOILS
Huu Hung Nguyen, Behzad Fatahi and Hadi Khabbaz

44

4147

EFFECT ON UNCONFINED COMPRESSIVE STRENGTH OF SAND TEST PIECES CEMENTED WITH
CALCIUM PHOSPHATE COMPOUND BY ADDITION OF SCALLOP SHELL POWDER
G. G. N. N. Amarakoon, Takefumi Koreeda, Satoru Kawasaki

50

4149

ENHANCING SLOPE STABILITY WITH VEGETATION
Nicholas Hytiris, Michael Fraser and Slobodan B. Mickovski

56

iv

4153

SMALL SCALE FIELD TESTS OF WATER INFILTRATION FOR COMPACTED SILTY LOESS SOIL
Aiassa Martínez Gonzalo, Arrúa Pedro and Eberhardt Marcelo

62

4154

METHOD FOR HAZARD ASSESSMENT OF SLOPE FAILURES BASED ON INFORMATION PROCESSINGTECHNIQUES
Shinichi Ito, Kazuhiro Oda, Keigo Koizumi, Kyohei Umemura, and Yohei Usuki

66

4158

HYDRAULIC CONDUCTIVITY IN LOESSIC STABILIZED SOIL
Alercia Biga Carolina, Arrúa Pedro, Eberhardt Marcelo, Aiassa Martinez Gonzalo

72

4159

MATHEMATICAL SIMULATION OF PILE INTEGRITY TEST (PIT)
Ramli Bin Nazir and Osman El Hussien

77

4161

DEVELOPING DESIGN TOOLS FOR SHEET PILE WALLS
Chane Brits and Jim Shiau

83

4165

SETTLEMENT BEHAVIOR OF DREDGED CLAY RECLAIMED LAND BY VACUUM CONSOLIDATIONMETHOD AND PROPOSAL OF ITS PREDICTION
Ikeda H., Kawano M., Kiyoyama T., Yamamoto S., Takase E., Katagiri M., Ohishi K. and Yoshifuku T.

89

4166

SLOPE STABILITY AND ROCKFALL HAZARD ANALYSIS IN AN OPEN PIT ZINC MINE
Maged Almandalawi, Greg You, Peter Dahlhaus, Kim Dowling and Mohannad Sabry

95

4171

A CONCEPTUAL MODEL OF ENVIRONMENTAL, GEOLOGICAL AND GEO-TECHNICAL RESPONSE OF
DREDGED SEDIMENT FILLS TO GEO-DISTURBANCES IN LOWLANDS
J. Rajaraman, K.Thiruvenkatasamy and S. Narasimha Rao

101

4174

3D NUMERICAL ANALYSIS OF A DEEP CIRCULAR EXCAVATION IN THE CITY OF RIO DE JANEIROJose Carlos Solis Tito, Celso Romanel

111

4178

STABILITY ANALYSIS OF THE SAIGON RIVERBANK SUBJECTED TO RIVER WATER LEVEL FLUCTUATION
A. Oya, H.H. Bui, N. Hiraoka, M. Fujimoto, R. Fukagawa

118

4190

EFFECT OF LIGHT HYDROCARBONS CONTAMINATION ON SHEAR STRENGTH OF FINE SAND
Rajab M. Abousnina, Jim Shiau, Allan Manalo, Weena Lokuge

124

4205

MONITORING THE STIFFNESS CHANGE IN CLAY WITH BENDER ELEMENT AND ELECTROMAGNETIC
METHODS
Chee-Ming Chan and Mohd Zarar Mohd Jenu

129

4208

NUMERICAL SIMULATION OF THE IMPULSE RESPONSE METHOD FOR RIGID PAVEMENTEVALUATION
Hudson Jackson and Kassim Tarhini

134

4213

NUMERICAL ANALYSIS ON THE EFFECT OF JET GROUT PILES ON AN EXCAVATION LOCATED IN AN
URBAN AREA
Akula Pavan, Thiruvengadam Tamilmani

140

4217

USING DRILL BIT REFUSAL AS AN INDICATOR OF STRENGTH AT THE CORING INTERFACE
B. Look, D. Lacey and D. J. Wiliams

145

4218

SPATIAL AND TEMPORAL VARIABILITY IN A RESIDUAL SOIL PROFILE
Daniel Mellish, David Lacey, Burt Look and Chaminda Gallage

151

4230

INTERACTION ANALYSIS FOR OIL STORAGE TANK ON MARINE CLAY
Pallavi Ravishankar B. and Neelima Satyam D.

157

v

4233

OPTIMIZATION OF TREATMENT AREA OF ENZYME MEDIATED CALCITE CEMENTATION: A NOVELSOIL IMPROVEMENT TECHNIQUE
Debendra Neupane, Hideaki Yasuhara and Naoki Kinoshita

162

4234

NUMERICAL ANALYSIS OF INFILTRATION INTO PERVIOUS CONCRETE-BASE SYSTEMS
Bertrand Teodosio, Jaehun Ahn and Hyun-Suk Shin

167

4236

PROPAGATION OF HARMONICAL VIBRATIONS IN PEAT
Darius Macijauskas and Stefan Van Baars

173

4237

SUBGRADE SUPPORT: A REVIEW OF SHORT-TERM AND LONG-TERM PERFORMANCEREQUIREMENTS
Andreas Nataatmadja

179

4240

EVALUATION OF RE-LIQUEFACTION BEHAVIOR OF SEGREGATED AND UNIFORM SPECIMENS INHOLLOW CYLINDRICAL TORSIONAL SHEAR TESTSUsama Juniansyah Fauzi and Junichi Koseki

185

4247

EFFECT OF FIBRE IN CONTROLLING DESICCATION CRACKS IN CLAY LINER SOILS
Dr. Sobha Cyrus and Veena. V.

191

4250

CYCLIC BEHAVIOR OF RECYCLED CONCRETE AGGREGATE IMPROVED WITH LIME AND GYPSUMADDITION
Wojciech Sas, Andrzej Głuchowski Alojzy Szymański

196

4252

USE OF WIRE EXTENSOMETERS FOR MONITORING PAVEMENT PERFORMANCE IN AREAS OF SLOPE
INSTABILITY
J. N. Kirjan, D. F. Marks and J.S. Shiau

202

4253

GENERATION AND DISSIPATION OF PORE WATER PRESSURE NEAR TO PILE AND FAR-FIELD IN
LIQUEFIABLE SOILS
Suresh R Dash, Subhamoy Bhattacharya, Atul Prabhakaran and C. Sreenivasulu

208

4262

A COMPARATIVE STUDY ON THE RESISTANCES OF BUCKET FOUNDATION IN SAND WITH DIFFERENTINSTALLATION METHODS
Ju-Hyung Lee, Jin-Ung Do and Sung-Ryul Kim

213

4280

OBSERVATION, MEASUREMENT AND ANALYSIS OF ORIENTED BOREHOLE CORE FOR LOCATING SLIPSURFACES IN FRACTURE ZONE LANDSLIDES IN SHIKOKU, JAPAN
Tsunataka Furuya and Jing-Cai Jiang

217

4295

EFFECT OF LAYER THICKNESS AND BLOCK RATIO ON ROCK SLOPES MOVEMENT STYLE
A. K. Alzo’ubi

225

4306

ESTIMATION OF THICKNESS OF LANDFILL BY GEOPHYSICAL EXPLORATION METHODS AT ILLEGALINDUSTRIAL WASTES DISPOSAL SITE
Minoru Yamanaka, Tomoaki Hachimura, Shuichi Hasegawa

232

4307

APPLICATIONS OF INNOVATIVE MATERIALS FOR PERFORMANCE IMPROVEMENT OF FLEXIBLEPAVEMENT OVER EXPANSIVE SUBGRADE
Ravin M. Tailor, Dr. Navin C. Shah

238

4308

A PHYSCIAL AND NUMERICAL INVESTIGATION INTO SINKHOLE FORMATION
Brian Lamb and Jim Shiau

244

4309

EFFECT OF TEMPERATURE AND LIQUID CHEMISTRY ON GEOTECHNICAL AND HYDRAULICPROPERTIES OF BENTONITE
H. M. A. Rashid, K. Kawamoto, T. Komatsu, T. Saito. and P. Moldrup

250

4310

CASE STUDY OF GEOGRID REINFORCED SEGMENTAL RETAINING STRUCTURE
Jia Xie, Barry Wai-Choo Kok, Jeroen Berends and Martin Silec

256

vi

4315

CONSOLIDATION PARAMETERS FROM ATTERBERG LIMITS – NEW CORRELATIONSC H Solanki

262

4329

RESEARCH OF PERIMETER REINFORCEMENT OF THE FOUNDATION SOIL BY CEMENT-SAND
MORTAR INJECTION
M.L. Nuzhdin, L.V. Nuzhdin

267

4335

GEOTECHNICAL CHARACTERISTICS OF SYNTHETIC MUNICIPAL SOLID WASTE FOR EFFECTIVELANDFILL DESIGN
Oluwapelumi O. Ojuri. and Peter K. Adegoke

273

4344

INNOVATIVE GROUNDWATER TABLE MONITORING USING TDR TECHNOLOGY
Vlastimil Chebeň, Marian Drusa and Michal Kuba

283

4363

DIFFERENTIAL CAPACITOR SENSOR OF WIRELESS SENSOR NETWORK FOR LANDSLIDE MONITORING
S. M. A. Motakabber, M. I. Ibrahimy, and M. Z. Hossain

289

4364

BRIDGE SCOUR MONITORING BY USING RFID SYSTEM
M. I. Ibrahimy, S. M. A. Motakabber and M. Z. Hossain

293

4368

MODELLING OF SHEAR STRENGTH PARAMATERS OF SATURATED CLAYEY SOILS
M. Inanc Onur, Burak Evirgen, Ahmet Tuncan and Mustafa Tuncan

296

4369

DETERMINATION OF THE FREEZING EFFECT ON UNCONFINED COMPRESSION STRENGTH ANDPERMEABILITY OF SATURATED GRANULAR SOILS
Burak Evirgen, M. Inanc Onur, Mustafa Tuncan and Ahmet Tuncan

300

4381

QUANTITATIVE ASSESSMENT OF HUMAN RISKS POSED BY MINE DEBRIS FLOW
Shuai Zhang, Limin Zhang

305

4386

A STUDY OF DYNAMIC SOIL STRUCTURE INTERACTION FOR PILED RAFT FOUNDATION WITH
VARIABLE SUB SOILS
Shukla S.J, Desai A.K. and Solanki C.H

310

Construction Materials

314

ID
4130

LIME LEACHABILITY STUDIES ON STABILIZED EXPANSIVE SEMI-ARID SOIL
Arif Ali Baig Moghal, Muawia A Dafalla , Tamer Y Elkady and Mosleh Ali Al-Shamrani

4137

BEHAVIOR OF AN EPDM GEOMEMBRANE 18 YEARS AFTER ITS INSTALLATION IN A WATERRESERVOIR
Manuel Blanco & Francisca Castillo, Nathalie Touze-Foltz, Bernat Amat, Escolástico Aguiar

320

4139

UNCERTAINTY OF BACK-CALCULATED VALUES IN PAVEMENT OVERLAY DESIGN WHEN USING THE
FWD DEVICE
Moshe Livneh

326

4145

4155

4157

UTILIZATION OF COCO COIR DUST AND PVC WASTE MATERIALS FOR WOOD-TILE QUALITYCOMPOSITE BOARD
Hermie M. del Pilar, Monesse Andrea Z. Antonio, Maricar A. Ilagan and Julius E. Seva
UNCONFINED COMPRESSION TESTING OF CEMENT-TREATED DEMOLITION MATERIALS IN BASE
AND SUB-BASE APPLICATIONS
Alireza Mohammadinia, Arul Arulrajah, Jay Sanjayan, Mahdi Miri Disfani, Myint Win Bo, Stephen
Darmawan
RECENT FOAMED BITUMINOUS STABILISATION WORKS IN QUEENSLAND
Lokanantham R. Logitharan, Kathirgamalingam Somasundaraswaran and Jothi M. Ramanujam

vii

315

334

340

346

4191

CHARACTERISTICS OF LIME STABILIZED EXPANSIVE SOIL FOR CONSTRUCTION OF FLEXIBLEPAVEMENTS
S. Patel, L.M. Reddy and J. T. Shahu

353

4239

UPTAKE OF ADVANCED AND SUSTAINABLE ENGINEERING MATERIALS IN CIVIL INFRASTRUCTURE
PROJECTSDavid S Thorpe

359

4243

A CASE STUDY – USE OF EXPANDED POLYSTYRENE BLOCKS IN LANDSLIDE REMEDIAL WORKS
M. Boyer, K.Chew and Dr B. Look

365

4313

CRACKING AND BOND SPLITTING BEHAVIORS OF CORRODED LONGITUDINAL BARS IN REINFORCED
CONCRETE BEAMS
Yasuji Shinohara and Aris Aryanto

270

4314

SURFACE HEAT REDUCTION OF ASPHALT CONCRETE BY TOP FILLING WITH RECYCLED AGGREGATESAND MINERAL MORTAR
Mohammad Raihanul Islam, Satoru Ishiguro, Masayoshi Yamanaka

376

4325

ASPHALT BINDER EXTRACTION FROM ASPHALT CONCRETE USING PULSED POWER TECHNOLOGY
Rétyce Ivan Hervé Dodji Togbé Amoussou, Youhei Takanabe, Nobuyasu Oyama,
Eva Arifi, Koichi Ishimatsu and Mitsuhiro Shigeishi

382

4345

ENGINEERING PROPERTIES OF CONCRETE INCORPORATING WASTE CARPET FIBERS
Hossein Mohammad Hosseini, A.S.M. Abdul Awal, M. Zakaria Hossain

388

4365

EFFECTS OF MOISTURE CONTENT ON RESILIENT PROPERTIES OF RECYCLED CONCRETE
AGGREGATES (RCAs)
Chaminda Gallage, Shiran Jayakody and Jothi Ramanujam

394

ID

Environment

400

4117

CONSERVATION AND EXPLOITATION OF BANG GRASS EFFECTIVE IN PHU MY VILLAGE, VIETNAM
Duong Minh Truyen, Le Hong Thia, Mashhor Mansor

401

4122

NUTRIENT TRANSFER AND TRANSFORMATION IN RIPARIAN GROUNDWATER WITH DIFFERENTLAND USE OF A LOWLAND WATERSHED, EASTERN CHINA
Xuyin Yuan, Lei Han, Huan Wang, Shouquan Wang, Hailong Chen

406

4129

HEAVY METAL DESORPTION STUDIES ON THE ARTIFICIALLY CONTAMINATED AL-QATIF SOIL
Arif Ali Baig Moghal, Mosleh Ali Al-Shamrani and Waleed M Zahid

411

4133

RECURRENCE INTERVALS OF METEOROLOGICAL DROUGHT EVENTS ACROSS EASTERN AUSTRALIA –IMPLICATIONS FOR DISTURBED LANDSCAPES
Devanmini Halwatura, Alex M. Lechner and Sven Arnold

416

4135

EUTROPHICATED SEDIMENT REMEDIATION USING SHELL FRAGMENT AS REGIONAL UNUSEDRESOURCES FOR NUTRIENTS ELUTION CONTROL
Kazuhito Murakami, Saki Agatsuma, Michio Gomyo and Akiko Inoue-Kohama

421

4142

THE VELOCITY REDUCTION EFFECT OF OBSTRUCTING STRUCTURES ON FLOOD WATER FLOWSDURING ROAD CROSSING
Abdul Naser Abdul Ghani, Ahmad Hilmy Abdul Hamid and Nursriafitah Kasnon

427

4168

ROLE OF A RETAINING WALL CONSTRUCTED OF NATURAL STONES IN PLANT BIODIVERSITY
Taizo Uchida, Masaaki Furuno, Takashi Minami, Sampei Yamashita, Tadashi Uchiyama, Teruo Arase
and Daisuke Hayasaka

432

4177

INFLUENCE OF EXOTIC PASTURE GRASSES AND FERTILIZATION ON THE VEGETATION RECOVERY OF
LANDSLIDE SLOPES FORMED BY TYPHOON 9512 IN MIKURA-JIMA ISLAND, JAPANTeruo Arase and Tetsuo Okano

438

viii

4188

FUNDAMENTAL PROPERTIES AND ANALYSIS OF WATER QUALITY IN A RESERVOIR AFFECTED BY
LITTLE WATER USE AND TEA PLANTATION
Masaaki Kondo and Takamitsu Kajisa

444

4200

SMALL WATER DISTRIBUTION SYSTEM DISINFECTION BY-PRODUCT CONTROL: WATER QUALITYMANAGEMENT USING STORAGE SYSTEMS
Sandhya Rao Poleneni and Enos C. Inniss

450

4216

PESTICIDE SUSTAINABLE MANAGEMENT PRACTICE (SMP) INCLUDING POROUS
BIOCHAR/GEOPOLYMER STRUCTURES FOR CONTAMINATED WATER REMEDIATION
Ian P Craig, Jochen Bundschuh and David Thorpe

455

4220

AN EVALUATION MODEL OF MEDICAL TRANSPORT WITH TSUNAMI EARLY WARNING SYSTEM
Norimitsu Koike, Susumu Kurahashi

458

4231

SEASONAL VARIATION OF THE ALIEN PLANTS INVASION INTO RIVER ECOSYSTEM
Michiko Masuda and Fumitake Nishimura

464

4241

LANDFILL WASTE WATER TREATMENT BY PULSED DISCHARGE IN WATER DROPLET SPRAY
Akio Takigawa, Keiichi Kato, Takashi Nakajima, Ryota Serizawa and Hiromu Tamba

472

4242

CHALLENGING FACTORS IN THE IMPLEMENTATION OF GREEN BUILDINGS IN MALAYSIA
Che Musa Che Omar, Hooman Abadi, Kamarusin Moh Noor

477

4245

GEOTEXTILE ENCASED COLUMNS (GEC): WHY, WHERE, WHEN, WHAT, HOW?
Dimiter Alexiew and Graham Thomson

484

4246

TSUNAMI-GENERATION WARNING SYSTEM USING THE EARTHQUAKE EARLY WARNING SYSTEM
Susumu Kurahashi and Norimitsu Koike

490

4255

ANALYSIS OF THE RISK OF CONFLICT AROUND THE TRANSBOUNDARY WATER RESOURCES OF THE
NORTHERN SAHARAN AQUIFER SYSTEM (NSAS)
Mohamed Redha Menani

494

4260

EFFECT OF THE “120-DAY WIND” ON AGRICULTURAL AND ENVIRONMENTAL CONDITIONS IN
HERAT, AFGHANISTAN
Homayoon Ganji Abdul Saboor Rahmany Takamitsu Kajisa Masaaki Kondo and Hajime Narioka

500

4263

USE OF GENETIC PROGRAMMING BASED SURROGATE MODELS TO SIMULATE GROUNDWATERFLOW AND BIOCHEMICAL TRANSPORT PROCESSES IN CONTAMINATED MINE SITES
Hamed Koohpayehzadeh Esfahani and Bithin Datta

504

4266

DECONTAMINATION OF RADIOACTIVE CESIUM FROM OCEAN SLUDGE BY MICRO-BUBBLE AND
MICROORGANISMS
Kyoichi Okamoto and Takeshi Toyama

510

4268

SOLID WASTE MANAGEMENT THROUGH ECOLOGICAL FOOT PRINT ANALYSIS – A CASE STUDY IN
KOCHI CITY, SOUTH INDIA
Subha Vishnudas, Athira Ravi

515

4274

GROUND CONDITIONS AND THE LAND OPERATIONAL PARAMETERS DETERMINED IN THE
PLANNING DECISIONS
Grzegorz Kmiecik, Marta Szejnfeld, Hanna Szymczak, Anna Szymczak-Graczyk

520

4320

EFFECT OF FLOCCULATION AIDS ON THE ELECTRIC FIELD ASSISTED DEWATERING OF SOLID LIQUIDSYSTEMS
Mohammed Saedi Jami, Masashi Iwata, Md. Monjurul Alam and Md Zahangir Alam

524

4323

IMPORTANCE OF CORYDALIDAE AS AN INDEX OF METAL CONTAMINATION OF RIVER
Akihiro Fujino and Hiroyuki Ii

528

4326

CHEMISTRY OF RIVER WATER, RIVER INSECT AND WATER PLANT IN THE KINOKAWA RIVER
CATCHMENT
Takuma Kubohara, Hiroyuki Ii

534

ix

4328

COMPARATIVE ANALYSIS OF EMBANKMENT METHODS UTILIZING EXPANDED POLY-STYROL AND
CONVENTIONAL METHOD IN MOUNTAIN ROAD IN JAPAN BY LIFE CYCLE ASSESSMENT
Hideyuki Ito, Koichi Yamanaka, Shoma Nehashi, Atsushi Fukuda and Kunio Minegishi

540

4330

CU, ZN AND AS CONTAMINATION OF SEAWEED BESIDE SHIZUKI AND KANAYAMA METAL MINES IN
JAPAN
Hiroyuki Ii

545

4340

WATER BALANCE ANALYSIS CONSIDERING RUNOFF OF UNGAUGED CATCHMENTS IN IWAKI RIVER
BASIN, NORTHERN JAPANSoichiro Kageyama, Shingo Tomiyama, Makoto Ikeda and Hiroyuki Ii

551

4347

REMOVAL OF CESIUM FROM SEA SLUDGE THROUGH DECOMPOSITION OF ORGANIC MATTER WITHAQUEOUS HYDROGEN PEROXIDEHirosuke Hirano, Takeshi Toyama, Nobuyuki Nishimiya and Kyoichi Okamoto

557

4383

THE EFFECT OF SUMATRA FAULT EARTHQUAKES ON WEST MALAYSIA
Noushin Naraghi Araghi, Mohd. Nawawi, Syed Mustafizur Rahman and Rosli Saad

561

4202

DEVELOPMENT OF SOIL FORMATION CORRESPONDING TO CYCLIC STRESS – DERIVED SHEARSTRAIN BASED ON STRATUM INDEX FACTOR
Abdull Halim Abdul

566

4324

UNEXPECTED HIGH CO2 CONCENTRATION IN CLASSROOMS OF WAKAYAMA UNIVERSITY
Masahiro Yamashita and Hiroyuki Ii

572

4337

ATTENUATION LANDFILL POTENTIAL EVALUATION FOR A MILLENIUM CITY, IN NIGERIA
Oluwapeluimi O. Ojuri

578

4338

SITE REMEDIATION IN NIGERIA: PROVEN AND INNOVATIVE TECHNOLOGIES (RECOVERY OF FREE
HYDROCARBON FROM SOIL/GROUNDWATER)
Oluwapelumi O. Ojuri, Samuel A. Ola, Olaolu G. Fadugba and Micheal A. Uduebor

585

4164

A CASE STUDY ON SLOPE REMEDIATION: A GREEN SOLUTION AND CONSTRUCTION REALITY
Elisabeth Simbolon and Bindumadhava Aery

591

4305

AMMONIA REMOVAL CHARACTERISTICS OF POROUS CONCRETE WITH ZEOLITE FOR ENHANCING
SELF-PURIFICATION ABILITY IN RIVER SYSTEM
Fumitake Nishimura, Toshio Yamada, Motohiro Tanaka, Hirofumi Kassai and Michiko Masuda

597

Authors index
Contents of GEOMATE 2011 – Volume 1(1) & 1(2)Contents of GEOMATE 2012 – Volume 2(1)Contents of GEOMATE 2013 – Volume 3(1)xFourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

PrefaceOn behalf of the GEOMATE 2014 Organizing Committee, we would like to welcome you in attending theInternational Conference on Geotechnique, Construction Materials and Environment held at the University ofSouthern Queensland, Australia in conjunction with GHD, Australia, GEOMATE International Society,Japanese Geotechnical Society, AOI-Engineering, Useful Plant Spread Society, HOJUN and Glorious
International.
On 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 wasdedicated to the tragic victims of the Tohoku-Kanto earthquake and tsunami disasters. The 2014 Geomate
conference 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

We have received very positive feedbacks; there have been paper submissions from 46 countries, including
Algeria, Argentina, Australia, Bangladesh, Belgium, Brazil, Cameroon, Canada, China, Colombia, Egypt,
Ethiopia, Germany, Ghana, India, Indonesia, Iran, Iraq, Israel, Japan, Libya, Luxembourg, Malaysia, Morocco,
New Zealand, Nigeria, Pakistan, Palestine, Phillipines, Poland, Russia, Saudi Arabia, Singapore, Slovakia,
South Korea, Sudan, Taiwan, Thailand, Tunisia, Turkey, UAE, UK, Ukraine, USA, Vietnam. The technicalpapers were selected from the vast number of contributions submitted after a review of the abstracts. The final
papers in the proceedings have been peer reviewed rigorously and revised as necessary by the authors. It relieson the solid cooperation of numerous people to organize a conference of this size. Hence, we appreciate
everyone who support as well as participate in the joint conferences.
Last but not least, we would like to express our gratitude to all the authors, session chairs, reviewers,
participants, institutions and companies for their contribution to GEOMATE 2014. We hope you enjoy theconference and find this experience inspiring and helpful in your professional field. We look forward to seeing
you at our upcoming conference next year.
Best regards,
Dr. Jim Shiau, Conference Chairman
Dr. Md. Zakaria Hossain, Conference General SecretaryxiFourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

Organization
Conference Chairmen:
Dr. Jim Shiau, Senior Lecturer, USQ, Australia (Chair)Dr. Stephen Buttling, S/Principals, GHD Geotech. (Co-Chair)Conference Honorary Chairman:
Dr. John Yeaman, Prof., Univ. of the S/Coast, Australia
Dr. Sohji Inoue, E/Prof., Mie University, Japan
Conference Organizing Committee:
Dr. Jim Shiau, Senior Lecturer Univ. of Southern Queensland, Australia
Dr. Stephen Buttling, Senior Principal GHD Geotechnics, Australia
Dr. Ivan Gratchev, Lecturer, Griffith University, Australia
Dr. Sohji Inoue, E/Prof. Mie University, Japan
Dr. Toshinori Sakai, Prof. Mie University, Japan
Dr. Zakaria Hossain, Prof. Mie University, Japan
National Advisory Committee:
Dr. David Thorpe, Senior Lecturer, USQ
Dr. Allan Manalo, Senior Lecturer, USQ
Dr. Soma Somasundaraswaran, Lecturer, USQ
Dr. Adrian McCallum, Lecturer, Uni. of Sunshine Coast, OLD, Australia
Dr. Mark Jaksa, Prof. University of Adelaide, Australia
Dr. Chaminda Gallage, Queensland Univ. of Tech. Australia
Dr. Iyad Alkroosh, Curtin University, Australia
Dr. Sammy Kwok, Geo. Eng. Cardno Bowler, Australia
Dr. Jun Sugawara, S/Eng. Golder Associates Pty Ltd, Australia
Dr. N. Sivakugan, A/Prof. James Cook Univ., Australia
Dr. Robert Lo, A/Prof. UNSW Canberra, Australia
Dr. Erwin Oh, Lecturer, Griffith University, Australia
International Advisory Committee:
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

xii

Dr. Shamsul Chowdhury, Prof. Roosevelt Univ., USA
Dr. Isabel Pinto, Prof. University of Coimbra, Portugal
Dr. Kingshuk Roy, Prof. Nihon Univ. Japan
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 University of Sci. & Tech.
Dr. Raja Rizwan Hussain, A/Prof. King Saud Univ. Saudi Arabia
Conference Secretariat:
Mr. Ryan Kemp, Mr. Mathew Sams, Secretary,
Faculty of Engineering and Surveying USQ Springfield Campus,
Education City, Sinnathamby Boulevard, QLD, 4300, Australia,
E-mail: Ryan.kemp@usq.edu.au, mathew.sams@usq.edu.au
Dr. Zakaria Hossain, General Secretary, Prof. MU, Japan
Division of Environmental Science and Technology
Graduate School of Bioresources
Mie University, 1577 Kurima Machiya-cho
Tsu-city, Mie 514-8507, Japan
E-mail: geomate@gi-j.com
Tel+Fax: +81-59-231-9578
Editorial Committee:
Dr. Jim Shiau
Dr. Hossain Md. Shahin
Executive Committee:
Dr. Jim Shiau
Dr. Stephen Buttling
Dr. Zakaria Hossain
Mr. Ryan Kemp
Mr. Mathew Sams

Note- A: Associate, E-Emeritus

xiiiGEOMATE-Brisbane, Nov.19-21, 2014

Keynote Papers

1Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

PRACTICAL APPLICATION OF PROBABILISTIC METHODS IN
GEOTECHNICAL ENGINEERING
Stephen Buttling, BSc(Eng), ACGI, PhD, CEng, FICE, FIEAust, CPEng
GHD Pty Ltd, Brisbane, Australia

ABSTRACT
Despite the fact that probabilistic methods in engineering have been around for about 50 years, and theirundoubted relevance to geotechnical engineering as a result of data uncertainty, they have not been widelyadopted in everyday geotechnical design practice. There have been many publications, both books and technicalpapers, by eminent academic authors, but the knowledge of statistics required to make good use of the methods
is held by few. In recent years, readily available commercial software has made it possible for probabilistic
analyses to be carried out extremely easily, perhaps too easily, as the basic statistical knowledge is still required.
Examples of misunderstandings of methods and misinterpretations of results will be shown, together withsuggested ways in which these can be overcome and more appropriate use of the very powerful methods made.
Keywords: Probabilistic analysis, slope stability, probability of failure, computer software

slope stability.
This is despite the fact that most of us
acknowledge that engineering in general, andgeotechnical engineering in particular, is concernedwith parameters which have a high level of
uncertainty. Ang & Tang [3] note that “the role ofprobability and statistics is quite pervasive inengineering.” This applies not only to soil properties,
but also to rainfall and hence run-off quantities,
wind forces on buildings, earthquake magnitudes,
traffic volumes, and many more examples. In someof these the role of statistics is acknowledged andincorporated, especially in the case of rainfall, but inothers we rely more on a factor of safety approach,believing that this will provide adequate protection,
without needing to know how much. It is worth
noting that the quotation from Ang & Tang [3] refers
to the role of statistics and not to the use.
The chart in Figure 1 was first published by
Christian et al [6], and has since been repeated bymany others, including Nadim et al [7] and Pollock
et al [8].

INTRODUCTION
Probabilistic methods have been around in civilengineering, and in geotechnical engineering, forquite some time, but yet they are not widely used
and accepted in practice. If we look carefully at thework which has been done, it tends to be centred inacademia, where the necessary understanding andknowledge can be expected to be available. On theother hand, the day to day practice may be left toengineers with a far lower level of skill, and this can,and indeed has, led to significant misunderstandings
and misinterpretations of results.
HISTORICAL PERSPECTIVE
Although they were specifically made withregard to the application of Bayesian Methods to
updated parameter values based on some priorknowledge plus some site specific testing, thecomments in Simpson & Driscoll [1] are believed tobe relevant and have a wider implication:
The necessary skills in statistics are held by“very few designers who have committed their timeto training and experience in geotechnicalengineering. Attempts by statisticians to tackle
geotechnical design have often ended in ridicule,and it is very difficult for one person to have asufficient grasp of both disciplines that he can
combine them sensibly.”
Nevertheless we have excellent text books, suchas two editions of Ang & Tang in 1975 [2] and2007 [3], Duncan & Wright [4], and Phoon [5]amongst others, but their influence does not seem tohave made its way into everyday engineering
practice, and in particular into the assessment of2

GEOMATE- Brisbane, Nov. 19-21, 2014use mean strength for design. If we consider that acharacteristic strength should be used, and that thecharacteristic strength may be defined as half astandard deviation below the mean, then this will
give a more conservative answer. For simplicity ofdemonstrating the concept it is assumed that the
distribution of factor of safety will be similar to the
distribution of strength, and therefore use of acharacteristic strength half a standard deviation
below the mean strength will be equivalent to a
Factor of Safety half a standard deviation below themean Factor of Safety, then we can find the
distribution of Factor of Safety which will give acharacteristic Factor of Safety of 1.5 or 1.2 as in
Figure 1. This is shown in Figure 2.
It is also noted that it has been recommended thatslope stability analyses should be carried out using
at least two computer programs, because of thecomplexities of the different algorithms within eachprogram. In geotechnical engineering consultancy
practice this is unlikely to occur as a result ofcommercial pressures both on time and licences.

Fig. 1 Effect of data uncertainty on probability of
failure for two mean Factors of Safety
It indicates the type of faith which practitioners
have in the traditional use of factors of safety,
derived from deterministic analyses, without
considering data uncertainty. Because statisticalanalyses are frequently associated with large
volumes of data, there is a very understandable
concept that they can only be used in geotechnicalengineering when we have large volumes of data,
and that is rare. However there is no doubt that weare dealing with data uncertainty, and statisticalmethods also have wide application when we havevery limited data. Duncan [9] has suggested the 6
sigma method amongst others, when there is little orno data, and this involves selecting the smallest
possible value and the largest possible value, andassuming that they are separated by six times thestandard deviation. Schneider [10] suggested
selecting the lowest (a), highest (c) and most likely(b) values, and then defining the mean as:𝝁𝝁 =𝒂𝒂+𝟒𝟒𝟒𝟒+𝒄𝒄

(1)

𝒄𝒄−𝒂𝒂

(2)

𝟔𝟔

BASIS OF METHODS

and the standard deviation as:

𝝈𝝈 =

𝟏𝟏𝟏𝟏

In general the probabilistic methods involve
determination of a distribution of values of aparameter, rather than a unique value as is used indeterministic analyses. Today we may also use
statistical methods to determine our unique value asa characteristic value, to represent the data set, or the
combination of a new data set with some previous
knowledge. It has been found by various authors, e.g.
Ang & Tang [3], and Bond & Harris [11], that soil
strength parameters, being “physical properties
based on a large number of individual, random
effects”, will often be normally distributed about themean value. However, great care is needed not to
overuse this familiar and convenient model. Since
the spread of the distribution needs to be defined aswell as the mean value, the standard deviation iscommonly used as a measure of spread. This is also
often expressed as the Coefficient of Variation, or
CoV, defined as:Using either of these methods to consider the likely
range of values of a parameter within a probabilistic
analysis will probably produce a more meaningful
output than picking a single value in a deterministic
analysis.
This is not to say, however, that probabilistic
analyses should replace deterministic analyses
entirely. There is clearly a need for both, but
probabilistic analyses are almost certainly not begiven appropriate weight at the present time becauseof misunderstandings over their applications andbenefits.

𝐶𝐶𝐶𝐶𝐶𝐶 = 𝜎𝜎�𝜇𝜇(3)where σ is the standard deviation and μ is the meanof the sample. Since it is known that 99.7% of allvalues in a normal distribution lie within the rangeof μ ± 3σ, it follows that if CoV > 33% then somevalues will be negative. Data published by Duncan[9], Nadim et al [7] and Bond & Harris [11] has
shown that CoV values for parameters such as
apparent cohesion, c’, undrained shear strength, su,
and coefficient of volume compressibility, mv, canrange up to 40, 50 or even 70%, this would produce
negative values if used with a normal distribution.
Since for these and most engineering properties

Fig. 2 Modified distribution with characteristic FoS= 1.5 and 1.2
In fact the curves in Figure 1 are considered to beslightly misleading, since it is considered that it is
not normal practice in geotechnical engineering to3

GEOMATE- Brisbane, Nov. 19-21, 2014

negative values are not permissible, the normal
distribution is unlikely to be appropriate if CoV >30%. This has also been discussed by Look [12].
On a project in Queensland, cement was being
mixed with a bi-product of the alumina industry,
known as red mud, in order to strengthen it to allow
an upstream raise of the tailings dam. Trials werecarried out, and in situ tests were used to measure
the undrained shear strength of the treated material.

The tests were carried out using a device called a
Wing Cone Penetrometer, developed in Sweden as avariation on a Cone Penetrometer Test to smoothover minor spatial variations in strength. The resultsof twelve profiles are shown in Figure 3, which
illustrates the scatter in the results. It is also apparent
that many strength values are over 300 kPa, withsome up to 700, while negative values are notpossible. As a result the data does not fit a normal
distribution.
Figure 4 shows the data for each profile plotted
as a cumulative distribution function, and it can beseen that some follow a smooth trend, while others
involve significant changes in gradient identify gaps
in the strength distribution.
What is remarkable is that, when all the data are
combined, making over 2,500 data points, thecumulative distribution function has a very close fit
with a log-normal distribution curve, as shown in
Figure 5.

Fig. 5 Cumulative distribution function for 12
profiles combined
This would suggest strongly that a log-normal
distribution is a good representation of the strengthof this modified material. In other recent examples, abeta distribution was found to give a good
representation of the probability distribution of someshear wave velocity results, seen in Figure 6, a lognormal distribution was found to work for some
Lugeon test results seen in Figure 7, and an inverse
Gaussian distribution gave the best fit for some
Point Load Index test results seen in Figure 8.

Fig. 3 Wing Cone Penetrometer profiles

Fig. 4 Cumulative Distribution Function plots for 12
profiles of WCP data

4

GEOMATE- Brisbane, Nov. 19-21, 2014

profile closely, while the combination of all the data
into one set produced the very close agreement withthe log-normal curve shown in Figure 5. Figure 9shows the log-normal probability distributionfunction for the data in Figure 5, as well as beta andgamma distributions which would be unlikely to be
distinguishable when applied to actual data sets inreal geotechnical engineering problems.

Fig. 6 A gamma distribution fitted through some Pwave velocity data

SPECIFIC METHODSUSE OF PROPRIETARY SOFTWARE
It is significant that, in the field of slope stability,
two of the programs believed to be most widely inindustry both offer probabilistic analysis as an
option. This has made it easy for geotechnicalengineers to carry out such analyses but,unfortunately, it has not ensured that they have thenecessary skills. This is one of the common featuresof modern proprietary software. Many years ago
such software was written and presented in complex
code or programming language, and only people
skilled in its use could understand and operate it.
Now everything is windows-based, and userfriendly, and it has become increasingly difficult toensure that software is only available to those withthe requisite skills to operate it. This is especiallytrue with the younger generation of computer literateengineers, who spurn hand calculations, and readily
assimilate such things as finite element modelingwithout needing a grounding in the theory ofstiffness matrices or constitutive modeling.
Returning to the subject of slope stability, it isvery easy to click on the buttons in a program such
as SLOPE/W to carry out a probabilistic analysis,
without understanding how the analysis is carriedout, or what the results mean. Examples have been
published in which the authors have carried out
probabilistic analyses, without understanding thatthey have not modeled spatial distribution ofstrength. By choosing a very simple geotechnicalmodel, in order not to have distractions from themain point they were trying to make, the Monte
Carlo method was only able to randomly selectstrength parameters, in this case c’ and φ’, and thenapply them to the whole slope since there was asingle soil layer. The resulting probability of failure,based on the proportion of critical failure surfaces
which returned a factor of safety of < 1, wastherefore the probability that the whole slope had
uniform properties which did not provide enoughresistance.
This helps to emphasise the difference between
probabilistic and deterministic analyses. In theformer, we choose suitably conservative strengthparameters and apply them to the whole slope. But
in the latter, in order for the probabilistic analysis
and the Monte Carlo simulation to have any

Fig. 7 A log-normal distribution fitted through some
Lugeon test data

Fig. 8 An inverse Gaussian distribution fitted
through some Point Load Index data

Fig. 9 Comparison of some skewed distributions
It is clearly essential to have a reasonableestimate of the probability distribution of therequired parameters, in order to be able to selectappropriate values to use in a probabilistic analysis.
Nevertheless it is noted that several have a similar
shape, such as the beta, gamma, and log-normal
distributions, and it is unlikely that a significantly
different outcome will result from their use. It is
worth noting that the individual real data profiles in
Figure 4 did not follow an idealized log-normal
5

GEOMATE- Brisbane, Nov. 19-21, 2014

meaning, there must be some realism to the random
sampling, and applying one set of strengthparameters uniformly to the whole layer is not it.
Within the context of a probabilistic slope stability
analysis, we need the random sampling to bemodeling the spatial variability of strength, so weneed there to be variations of strength within eachlayer.
In order to investigate this, the simple slopemodel shown in Figure 10 and analysed by Pollock
et al [8] has been re-examined. First their results
were regenerated, but it was found that the use of the
optimization feature of SLOPE/W combined with

The most striking thing about the results in Table
1 is the Probability of Failure at nearly 27%. Sinceno temporal variation has been allowed for in thisanalysis, it is only spatial variation that has been
considered. This means that the Monte Carlo
method, applied through 100,000 simulations, hasrandomly picked values for c’ and φ’, based on themean and standard deviation supplied as determined
Table 1
Probabilistic results from basic analysis
Mean F of S
Reliability Index
P (Failure) (%)
Standard Dev.
Min F of S
Max F of S
# of Trials

1.13090.707
26.9250.185
0.69976
1.5791
100000by Pollock et al [8], and then applied them to thewhole slope. While it is understood that this is a
special simple case chosen to illustrate a point withregard to the use of probabilistic analysis, it is also
important to realize that such a distribution ofstrength will never occur in practice, since therandom spatial distribution has not been modelled.
Again this is an extreme case which has made theinappropriateness of this model clear because it isapplied to the whole slope, but extreme care would
also be needed when applying such a model to a
multilayered slope, to ensure that the spatial
variation of strength has been appropriately
modelled.
The parameters which affect this are the autocorrelation distance, which relates to the distanceover which properties, such as strength, are found toremain constant such that they can be modelled by asingle strength selection in a Monte Carlo process.
Using the same parameter over the whole areamodelled is equivalent to using an auto-correlation
distance = ∞. El-Ramly et al [13] reported that, forthe lacustrine clays in the James Bay area ofQuebec, Canada, auto-correlation distances of about
30 m were found to be appropriate. This has also
been advised for quick clays in Norway. However,for older soils which may have been heavily overconsolidated and fissured, and for tropicallyweathered residual soils, very much shorter autocorrelation distances may be appropriate. Yu andMostyn [14] suggested auto-correlation distances of
1 to 2 m.
In order to investigate the effect of this on theslope in Figure 10, the geometry was modified tohave a mosaic of squares of soil of 2 m side, as
shown in Figure 12.
The soil model was cloned such that all squares
were notionally different soils, but with identicalproperties. This allowed the Monte Carlo simulation
to allocate different strengths randomly to each “soilsquare” which, it may be argued, is a reasonable

Fig. 10 Basic 15° slope analysed after Pollock et al[8]Fig. 11 Results of Morgenstern-Price analysis with
optimization
the Bishop Method of Slices gave distorted results,
even though they matched the output given in thepaper. Instead the Morgenstern-Price method wasselected, and this gave the results shown in Figure
11 and in Table 1.
A “standard” SLOPE/W analysis from Geostudio2007 was used, except that the optimization function
was turned on as it had been by Pollock et al [8].
The results were equivalent, except that they
appeared to have used the Bishop Method of Slices,which gives a higher Factor of Safety when usedwith the optimization function than either theMorgenstern-Price method with optimization of the
Bishop Method without.
6GEOMATE- Brisbane, Nov. 19-21, 2014

approximation to the random spatial distribution ofstrength in nature. The effect on the results was
dramatic.

Another problem in application which has
become evident relates to a misunderstanding ofannual probability of failure. It is now commonly
accepted that the term “risk”, when applied toFig. 14 Effect on probability of failure of number oftrials for model with 2 m soil squares

Fig. 12 Slope with mosaic of 2 m squares

landslides, is the product of likelihood andconsequence. This in itself can lead tocomplications, because the general population may
refer to risk in the context of probability, i.e. “therisk that something will happen”, or ofsusceptibility, i.e. “this is at a greater risk of slipping
than that”. However, accepting that in landslide risk
management, risk means the product of likelihoodand consequence, in practice it seems to be easier todetermine the consequences associated with alandslide of given dimensions, than it is to determine
the likelihood that it will happen. There are anumber of reasons for this, and obviously knowing
the cause of a landslide is very high on the list,
especially when we are referring to the cause of alandslide which has not yet happened. It is also
generally accepted that there is a link between
rainfall and landsliding, but details around the link
are sketchy. What is the period of extreme rainfall
which triggers landslides? Is it 10 minutes, an hour,
24 hours, 72 hours, or more? Is it different fordifferent types of landslides, such as natural slopes,
or fill slopes?
All of this makes the determination of an annual
probability of extremely difficult, but nonethelessnecessary if we are to establish likelihood in order toevaluate risk. It has already been noted that thereadily available commercial software for slope
stability will run a probabilistic analysis and produce
an average factor of safety and also a probability of
failure. What has happened is that users have notstopped to question what that probability of failure
actually means.
It is easy to see that there is a connection
between annual probability of failure, andprobability of failure during a design life, with thelatter probability increasing with increasing design
life. This leads to the equation:

The slip surface and the mean factor of safety
were basically unaffected after 100,000 trials as seenin Figure 13, but the probability of failure had
dropped by nearly three orders of magnitude, as
shown in Table 2.

Fig. 13 Output from probabilistic analysis withmosaic of 2 m soil squares
Table 2analysis

Probabilistic results from 2 m square
Mean F of S
Reliability Index
P (Failure) (%)
Standard Dev.
Min F of S
Max F of S
# of Trials

1.1294
3.423
0.031
0.038
0.97796
1.2813
100000The effect on the probability of failure of thenumber of Monte Carlo simulations was tested, andit was found that there was a small drop in theprobability as the number of trials was increased
from 10,000 to 200,000, as seen in Figure 14.
ANNUAL PROBABILITY OF FAILURE

𝑷𝑷𝑫𝑫𝑫𝑫 = 𝟏𝟏 − (𝟏𝟏 − 𝑷𝑷𝒂𝒂 )𝒚𝒚
7(4)GEOMATE- Brisbane, Nov. 19-21, 2014

available materials such as Excel from Microsoft.
Another example of this is the work of Cho [16].
In Example 1 in this study Cho [16] also looked
at a uniform homogeneous slope, with a mean
undrained shear strength = 23 kPa and a standard
deviation = 6.9 kPa. With his 5 m high slope at 1(V)to 2(H) and 5 m below the toe to the rigid boundary,
he found a deterministic factor of safety = 1.356. He
then argued that the selection of the critical surface
based on uniform parameters, followed by a Monte
Carlo simulation of spatial variability, is unreliable
since the spatial variability will inevitably affect the
selection of the critical surface. This wasdemonstrated by analysis using his Random Field
model, which is capable of modeling spatial
variability. The effect was to identify a number ofcritical slip circles with factors of safety ranging
between 0.834 and 0.983. However, an examinationof the contours of undrained shear strength used in
the different models suggests that an experienced
geotechnical engineer would not carry out adeterministic analysis with an undrained shear
strength of 23 kPa, because of the existence of large
zones of lower strength material in what would be
expected to be critical zones.

In which P DL is the probability of failure during thedesign life of y years, and P a is the annual
probability of failure. This is illustrated in Figure 15.

Fig. 15 Variation of probability of failure withdesign life.
In theory it would be possible, if the exact
probability of failure during a given design life were
known, to calculate the annual probability of failure.
In practice this is exceedingly unlikely to happen,
since circumstances dictate that it is more practicalto determine an annual probability of failure than it
is to determine a probability of failure during adesign life. Unfortunately, what has happened on atleast two occasions published recently, is thatanalysts have confused probability of failure, basedon spatial variability, with probability of failure
based on temporal variability, and have equated thespatial probability of failure with probability of
failure during a design life. They have then tried to
calculate an annual probability of failure byassuming a design life. This is clearly incorrect,
since it leads to the conclusion that annual
probability of failure decreases with increasing
design life.
What needs to be done is that a reasonablegeotechnical model is built, in accordance with theprevious section, which makes due allowance forspatial variability. Superimposed on this we can thenplace different groundwater levels, with appropriateannual return periods. It will then be straightforward
to determine a probability of failure which can be
combined with the temporal probability to produce
an overall annual probability of failure. These
probabilities for each groundwater level can then be
combined as in Table C6 in AGS [15].

Cho [16] also examined the influence of crosscorrelation between c’ and φ’ for a homogeneous
slope in his Example 2. He found the relationshipshown in Figure 16 between Coefficient of Variationand cross-correlation, using both a fixed criticalsurface and his Random Field method.

Fig. 16 Variation of Coefficient of Variation withcross-correlation coefficient after Cho [14]USE OF CUSTOM MADE SOFTWARE
An examination of the literature tends to suggestthat probabilistic analysis is still mainly carried out
by academics within universities or research
institutes, where the level of statistical understandingis suitably high, and time is available to write
dedicated software, even if it makes use of readily
8

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 17 Variation of Coefficient of Variation withcross-correlation coefficient using SLOPE/W[3] Ang AH-S & Tang WH, Probability Concepts
in Engineering – Emphasis on applications incivil & environmental engineering. 2nd Ed. New
York, Wiley 2007.
[4] Duncan JM & Wright SG, Soil strength andslope stability. New York, Wiley, 2005.
[5] Phoon KK, Reliability-based design in
geotechnical engineering – computations andapplications London, CRC, 2008.
[6] Christian JT, Ladd CC & Baecher GB,
Reliability and probability in stability analysis,
Journal of Geotechnical Engineering, ASCE,
120, 12, 2180-2207, 1994.
[7] Nadim F, Einstein H & Roberds W,
Probabilistic analysis for individual slopes in
s0il and rock, International Conference on
Landslide Risk Management, Vancouver, 63-98,
2005.
[8] Pollock D, Hurley G & Haberfield C, Linking
equilibrium analysis and landslide risk
assessment, Australian Geomechanics, 46, 2,
149-162, 2011.
[9] Bond A & Harris A, Decoding Eurocode 7,
London, Taylor & Francis, 2008.
[10] Duncan JM, Factors of safety and reliability ingeotechnicalengineering,
Journalof
GeotechnicalandGeoenvironmental
Engineering, ASCE, 126, 4 307-316, 2000,[11] Look B, Appropriate distribution functions forcharacteristic values (to be published) 2013.
[12] El-Ramly H, Morgenstern NR & Cruden DM,
Probabilistic slope stability analysis for practice,
Canadian Geotechnical Journal, 39, 665-683,
2002.
[13] Yu YF & Mostyn GR, Random field modelling
for the effect of cross-correlation, Proc. 13th
International Conference on Soil Mechanics andFoundation Engineering, New Delhi, 4, 13891392, 1993.
[14] AGS, Commentary on Practice Note Guidelines
for Landslide Risk Management 2007,
Australian Geomechanics, 42, 1, 115-158, 2007.
[15] Cho SE, Probabilistic assessment of slope
stability that considers the spatial variability ofsoil properties, Journal of Geotechnical andGeoenvironmental Engineering, ASCE, 136, 7,
975-984, 2010.
[16] Low BK, Practical probabilistic slope stability
analysis, Proc. 12th Panamerican Conference on
Soil Mechanics and Geotechnical Engineering,
MIT, Cambridge, Massachusetts, 2, 2777-2784,
2003.
[17] Wang Y, Cao Z and Au SK, Practical reliability
analysis of slope stability by advanced Monte
Carlo simulations in a spreadsheet, Canadian
Geotechnical Journal, 48, 162-172, 2011.

Attempts to reproduce this relationship in
SLOPE/W using the same slope and soil parameters,
and with a spatial correlation distance = 20 m, was
not successful as there was an unexplained peak inthe curve around a cross-correlation = 0, as seen in
Figure 17.
This helps to illustrate the dilemma faced bypracticing engineers. There is a lack of goodunderstanding of the statistical processes involved inthese analyses, and of the specialized jargon used bystatisticians which is indecipherable to most of us,
and there are now computer packages which appear
to make the processes simpler, but involve theextreme danger of being able to produce answers
without needing to understand the mathematicalprocesses. In design offices all over the world,
geotechnical engineers do not have the luxury oftime to write custom software, or even adapt
spreadsheets in ways which have been suggested bysome authors (El-Ramly et al [13]; Low BK et al[17]; Wang et al [18])
CONCLUSIONS
1
Probabilistic analyses are very powerful tools
in the correct hands, and have particularapplication in geotechnical engineering as aresult of data uncertainty.
2
The necessary statistical skills are held byvery few people, and geotechnical engineers
in general lack the necessary training instatistics.
3
Changes are needed in the education of
geotechnical engineers, to make them moreaware of engineering statistics, the tools
available, and how to make proper use ofthem.
4
Proprietary software now offers someprobabilistic analysis capability, but it is notwell documented and explained, leading toserious errors in analysis and reporting.
5
Although it has been recommended that slope
stability analysis is carried out using at least
two
computerprograms,
in actual
geotechnical engineering practice this isunlikely to occur due to commercialpressures.
REFERENCES[1] Simpson B & Driscoll R, “Eurocode 7 – acommentary”,
BRE Report BR 344,
BRE, London, 1998.
[2] Ang AH-S & Tang WH, Probability Concepts
in Engineering Planning and Design, Vol I,
Basic Principles. New York: Wiley, 1975.

9Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

PERSPECTIVES FROM ACCURATE MEASUREMENTS OF THE STANDARDPENETRATION TEST
Julian Seidel
Head, Specialist Foundation Engineering Consultancy, Australia
ABSTRACTThe SPT or Standard Penetration Test is a much maligned in-situ test method which despite its failings, continues
to be used extensively around the world, and is codified in standards such as ASTM-D 1586,BS 1377 and DIN 4094
to name a few. The test involves dropping a weight of 63.5kg from a height of 762mm onto a string of drill rods
which drive a standard sampler 450mm into the material at the base of a borehole. The SPT N value is the blow countfor the final 300mm of penetration, or equivalent. Despite the standardization of weight and drop height, there areconsiderable variations in the field implementation of the test which lead to variations in the SPT N. In addition, theway in which the blows are observed and recorded leads to inaccuracies. The authors have undertaken field studies
into improved monitoring of SPT tests, and these have highlighted the deficiencies in current SPT evaluation processes.
This paper will describe the field studies including the method of monitoring, provide results which highlightdeficiencies, and provide some recommendations for future research and practice.
Keywords: Standard Penetration Test, SPT, In-situ Testing, Monitoring, Measurement

10

GEOMATE, Brisbane, Nov.19-21, 2014

Technical Papers

11GEOMATE, Brisbane, Nov.19-21, 2014

Geotechnique

12Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

DESIGN AND DEVELOPMENT OF COMPOSITE FOUNDATIONSTRUCTURE FOR SOLAR SUPPORT SYSTEM
Hossain, M.Z.1, Ojiro C.2, Ozumi, S. 3, Harada, H. 2 and Okuyama, S. 3
１
Graduate School of Bioreseouces, Mie University, Japan2
Cosmowinds Company Ltd., Nagoya, Aichi, Japan3
Beppu Construction Company Ltd., Yokkaichi, Japan

ABSTRACT
Researches on solar plants are getting growing interest worldwide due to its renewable energy that combats
climate change and assures a sustainable energy source. These researches are divided into mainly 3 categories suchas 1) making current technology solar cells cheaper and/or more efficient to effectively compete with other energy
sources; 2) developing new technologies based on new solar cell architectural designs; and 3) developing newmaterials to serve as light absorbers and charge carriers. This paper presents the design and development of acomposite foundation structure for solar support system consisting of hollow circular steel pipe and thin cementsand mortar layer. Field experiments of composite piles including pullout, compression (axial) and lateral tests
were demonstrated and the results are summarized in this paper. Load-deflection relationships of pullout (uplift
tension) tests, axial compression (pushing into ground) for pile-bearing tests and lateral tests of two sites arereported and compared for two different soils. It is concluded that the pullout, compression and lateral loads
obtained from field tests are suitable to support solar panels against winds and weight of the solar systems.
Keywords: Solar plants, Composite foundation, Pullout, Bearing capacity, Load-deflection relationships

coefficients on hip roofs of low-rise buildings withthe variation of angle of solar panels were calculated
by researchers of the Japanese Architectural Society
and Aihara et al. [5,6]. In spite of the volume of
information available on the upper part of solar
system, very few researches are available on the solar
foundation installed in the ground. Solar foundationthat is directly related to the safety of the solar plants
against severe climate such as typhoon, cyclones andheavy rains as well as bearing capacity of thestructure; the cost-effective design of the solar
foundation is indispensable for economic
construction and long term performance of solar
plants.
The object of this paper is to highlight some ofthese challenges and provides an alternative
composite foundation for solar system that canfacilitate the ease of installation, strength
performance and minimize the construction cost.
Composite pile presented in this paper are made ofhollow steel pipe which supports the superstructureand sand-cement mortar between the pipe and the soil
which provides the enough bearing capacity. The
enhanced performance of composite pile comes fromits synergetic action of steel with mortar and mortar
with soil. Since, in composite pile, high tensile steel
pipe provides adequate tensile and pullout resistance
while the sand-cement mortar provides adequate
frictional resistances and improved cohesion owing to
its relatively greater surface area and roughness ascompared to conventional foundation. If properly

INTRODUCTION
Energy production from renewable sources has
become a crucial part for both industry andgovernments due to the growing demand forsustainable energy and climate change mitigation
policy. The demand of solar plants is especially highin Japan after the tragic Tohoku-Kanto earthquake
which occurred on Friday 11 March 2011, at 14:46
Japan Standard Time, in which the north east of Japanwas severely damaged along with the destruction of
Fukushima nuclear power plant. Literature review
showed that there are many researches on the growing
trend of creating renewable energy infrastructure,such as solar farms and wind turbines. To date, mostof the researches available in the technical literature
are on the technology of solar cells, architecturaldesign of frame structures against winds loads andmaterials development for battery and light absorbers
and charge carrier etc. Somekawa et al has conducteda research on the wind loads acting on thephotovoltaic panels arrayed near ground and provided
a design of frame structure against wind load [1].
There are some researches on the concrete
foundations of solar plants that were found in the
NEDO Organization, Japan [2]. These are mainly
made of concrete and steel bars as of reinforced
concrete foundation and cost-performance was nottaken into account. In addition with these, researcheson photovoltaic cells were performed by the JapaneseIndustrial Standards (JIS) [3,4]. Design wind pressure
13

GEOMATE- Brisbane, Nov. 19-21, 2014

designed, rough surface of mortar elements can grip
the soil particles, and the frictional resistance neededfor optimal design against pullout and compression
failure can be significantly improved. Unfortunately,
very little or no research attention has been given
towards investigating pullout and compression
response of composite foundation embedded in soil.
In view of this objective, the pullout, compression
and lateral response of composite pile embedded in
two types of soil is studied initially and then these are
optimized to obtain the necessary design strength.
The paper reports the load-displacement relationshipsof composite solar foundation and development of thetechnique as well as failure modes from the pullout,compression and lateral tests results.

Solar panel

200

125

Cement-mortar

150

105

GL

Steel
pipe

170
Fig.2 Outline of new solar foundation (cm)

SITE DESCRIPTION
The sites of the solar plants reported in this paper
are located in Kasigai city, Aichi prefecture and in
Matsuzaka city of Mie Prefecture, Japan (Fig.1). Bothof the locations have strong winds especially during
the typhoon. The types of soils are clayey and silty
soils. The ground stratigraphy and the details of thesoil properties can be found in elsewhere [8,9]. Boththe grounds are usually saturated because of frequentraining throughout the year.

Initial Check

Construction Check

Steps
Preparation
SurveyMarkings

Installation
Before boring

Boring machine

Pile length, Angle,
MortarCasing hole

Mortar quality

Pouring mortar
Test sample
Pile construction
Curing at leastdKasugaiCity

Compression test

Height and space Maintain

σ5=240N/mm2>Check

Height and space
Pullout test
Confirmation test

Completion

Att.）3% of all pile or atleast 3 piles must be tested※Confirm loadings of
all remaining

Fig.3 Work flow chart (Solid Line: Main Work,dotted Line: Specified Work, Construction Check:
Formation and Quality Management)

MatsuzakaCity
Fig.1 Sites of solar plants investigated in this research

Drilling and Construction Method

MATERIALS AND METHODS

The drilling was done using the rotary-percussion
drilling machine (Fig.4). The equipment was set at thedesignated location where the pile needed to beinstalled and then it was adjusted vertically (α＝90o).
Careful attention was taken against the angle ofdrilling, direction of equipment and inclination ofboring hole. Soil samples were collected from theboring hole and tested in the laboratory. Aftercompletion of drilling work, the mortar was pumpinto the drilled hole by using a pouring hose. The
mortar was poured into at the bottom of the drilledhole in such a way that the water inside the hole was
replaced by the sand-cement mortar. Finally, the steel
pipe was placed into the sand-cement mortar

The materials used are 76.3mm diameter steel
pipe of lengths 1.5m and 2.0m and the sand-cement
mortar mix with sand-cement ratio of 2.1 and watercement ratio of 2:1. Outline of new solar foundationis shown in Fig.2. The anchoring length of the left
pipe is 105cm and the right pipe is 125cm. In order toease of pouring of the cement-sand mortar under thepipe, additional burrow of 10cm was done below thepipe (Fig.2).
Work Procedure
The details of the work procedure are given thefollowing flow chart (Fig.3).
14

GEOMATE- Brisbane, Nov. 19-21, 2014

immediately upon pouring the mortar. All of theseworks were carried out according to the design andconstruction method of the Japanese GeotechnicalSociety (JGS).

Fig.6 Outline of lateral load tests

Fig.4 Rotary-percussion drilling machine used
Method of Testing

Pullout laod, kN

18

The axial compression, tensile and lateral load
tests were carried out in accordance with JGS 181131, 2002. A typical test setups for axial compression,
tensile and lateral tests are shown in Fig.5-6. For axial
compression, tension and lateral tests, pile head
movements were monitored by the Linear
Displacement Transducers (LDT). All LDT readings
were recorded automatically with the increment ofloads.
Chain
block

LVDT

14
10
6
2
3

4

5

6

7

Pile head displacement, mm
Fig.7 Pullout load-displacement relationships(Kasugai)
The maximum pullout load (17kN) was obtainedat displacement of nearly 6.2mm. The compression
load displacement curve can be characterized into
three parts; which is like a reverse s-shape indicating
a quick load increment at the initial stage and astraight line at mid-stage with a wider range ofdisplacement from 8.7 to 10.7mm resuming its higher
bearing capacity at the final stage. The maximum
compressive load is recorded as 35kN at displacementof 10.9mm (Fig.8).

Load cellCompression load, kN

Steel pipe

Fig.5 Outline of setup for axial compression andtensile load tests
RESULTS AND DISCUSSION

40
34
28
22
16
10
4
8

The load displacement curves of Kasugai solar
plants for pullout, compression and lateral loads are
given in Fig.7-9, respectively. It is observed that the
pullout load increases with the increase indisplacement with a flat curvilinear nature (Fig.7).

8.5

9

9.5

10 10.5 11

Pile head displacement, mm
Fig.8 Compression load-displacement relationships(Kasugai)15

GEOMATE- Brisbane, Nov. 19-21, 2014

The lateral load-displacement curve is seen as the
combination of two linear parts. The first linear partis narrow range up to a displacement of about 2.7 mm
at the initial stage while the second linear part is wider
up to a displacement of about 13mm that corresponds
to the failure of lateral load (8kN) (Fig.9).

Compression load, kN

25

Lateral load, kN

12
8

15
10

Pile1

5

Pile2

0
0

0.2

4

0.4

0.6

0.8

1

Pile head displacement, mm

Fig.11 Compression load-displacement relationships(Matsuzaka)

0
0

2

4

6

8

10

12

14

The lateral load-displacement curve of Matsuzaka
pile (Fig.12) can be characterized into three parts: thefirst linear part up to a displacement of 2mm,
followed by the second linear component with adisplacement ranging from 3mm to 14mm, and thethird linear component with a near-horizontal slope
up to a displacement of nearly 30mm. The maximum
lateral load for Matsuzaka soil was obtained as 14kN
at which the soil failure occurred along with lateral
bending failure of the pile (Fig.13).

Pile head displacement, mm

Fig.9 Lateral(Kasugai)load-displacement

relationships

The results of pullout, compression and lateralload tests of two piles of Matsuzaka area arepresented in Figs. 10-12. It can be seen from Fig.10
that the pullout load displacement curves for both thepiles at Matsuzaka site showed the similar trend as of
the Kasugai area pullout load-deflection curves. The
uplift load for both the piles increased in curvilinear
characteristics with a slight increase in thedisplacement.
The maximum uplift loads for
Matsuka are obtained as 15kN for both the piles.

Pullout load, kN

20Lateral load, kN

16
14
12
10
8
6
4
2
0

16
12
8
4
0
0

5

Pile1

10

15

20

25

30

35

Pile head displacement, mm

Pile2

Fig.12 Lateral(Matsuzaka)
0

0.2

0.4

0.6

0.8

load-displacement

relationships

1

Pile head displacement, mm

Fig.10 Pullout(Matsuzaka)load-displacement

relationships

It can be seen from Fig.11 that the compression
responses of both piles were non-linear. Both the piles
showed very small displacement (nearly 0.7mm) incompression. For this case, the displacements incompression and tension are smaller. However, thisbehavior was conspicuously absent for Kasugai soil
indicating the differences in load-deflection
relationships for two soils in different locations. The
maximum compression load for Matsuzaka area wasnoted as 20 for both the piles.

Fig.13 Bending failure of steel pipe after lateral test
16

GEOMATE- Brisbane, Nov. 19-21, 2014

CONCLUSION

photovoltaic panels arrayed near ground， The
22nd Wind Engineering Symposium, pp.157160, 2012．
[2] NEDO: New Energy and Industrial Technology
Development
Organization,
http://www.nedo.go.p/[3] JIS C8955: Japanese Industrial Standards,
Design guide on structures for photovoltaic array,
2004．
[4] JIS C8917: Japanese Industrial Standards,
Environmental and endurance test methods forcrystalline solar PV modules, 2005．
[5] AIJ2004: Architectural Institute of Japan,
Recommendations for Loads on Buildings, 2004．
[6] Aihara T., Asami Y., Nishimura H., Takamori
K., Asami R. and Somekawa D.: An area correct
factor for the wind pressure coefficient for
cladding of hip roof －The case of square plan
hip roof with roof pitch of 20 degrees－The 22nd
Wind Engineering Symposium, pp.339-344,
2008．
[7] Cosmo
WindsCompany
Limited,http://cosmowinds.jp/solar/studio/[8] Beppu Construction Company Limited,
http://www.o-beppu.co.jp/

Composite foundation structures of solar
support systems that have been designed andconstructed in this research study are some of theexamples in Japan. Results obtained havedemonstrated that both the utility and the economy
can be achieved using very simple techniques withlocally available materials. Results obtained showedthat the uplift pullout loads, compression loads andlateral loads of the piles are strong enough to support
the solar plants against strong winds loads of about
40m/s and have the bearing capacity enough to
support the weight of the solar plants. It is expectedthat the observations in this study will bring the newconcept in gaining wide acceptance of composite
foundation structures for the construction of strong,
durable and cost-effective solar plants.
ACKNOWLEDGEMENTS
The first author is grateful to Cosmo Winds
Company Limited, Japan and Beppu Construction
Company Limited, Japan for providing some of the
field tests data and information noted in this paper.
REFERENCES[1] Somekawa D., Koizumi T., Taniguchi T. andTaniike Y.: Wind loads acting on the17Fourth Internation al Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

DETERMINATION OF THE APPROXIMATE DYNAMIC
COEFFCIENT OF FRICTION ON UNDERGROUND PIPES DUE TO
VARIOUS BLAST SCENARIOS
Akinola Johnson OLAREWAJU
Civil Engineering Department, School of Engineering, Federal Polytechnic Ilaro, Ogun State, NIGERIAABSTRACTIn this study, different types of blast scenarios and blast loads for various explosives were consideredusing [11]. Consequently, ground movement parameters were estimated and blast load durations for studying
the dynamic effects of coefficient of friction on buried pipes due to blast loads were estimated. Simulated
models for ‘slip’ and ‘no-slip’ conditions were analyzed using explicit code in ABAQUS. Dimensional
analysis was used to process the results. It was observed that the ground shock parameters attenuate greatly inground media as the distance increases. In addition, duration of blast play a significant role in the behavior ofburied structures while the observed parameters reduced at coefficient of friction of around 0.8 compared tothe conventional coefficient of friction for static analysis. Parameters thus determined would help in the study
and designing of buried pipes to resist the effects of blast. Consequently, the environmental risk and hazards
caused by blasts would be greatly reduced.
Keywords: Blast, Underground, Coefficient of Friction, Simulation, Environment

1. INTRODUCTION

Analytically according to [6] and [10], axial
friction force is determined using this expression,

Buried structures and facilities such as
basements, foundations, mall facilities, storage
facilities, etc could be fully buried or partiallyburied and these can be any structures of diver’s
shapes. Considering the severity of destruction due
to blast; sufficient tremors could be created todamage substructures over a large area. At 138kpa
of blast wave, reinforced concrete structures willbe leveled resulting to loss of lives and property,
disruption in production, land degradation, air
pollution, etc. Blast occurs from terrorist’s attacks,
accidental explosion, wars, insurgent, nuclear
reactors, accidental explosions from military
formations, accumulation of explosive gases inpipes, etc. In view of these, there is need toestimate the blast load for the purpose of studying
the dynamic behavior of simulated buried
structures as well as the effects of coefficient offriction. The constituents of blast are basically the
explosive, ground media, structural components aswell as blast characteristics. In studying dynamic
soil-structure interaction through modeling,experimental results are required in other tosimulate the prevailing situations between all theconstituent materials [8].

F = µ (Wp 2γDH + Wp )(

1
)
12

(1)

where F = axial friction force (N/mm),=
coefficient of friction between pipe and soil. =density of backfill soil (kg/m3), D = outside
diameter of pipe (m), H = depth of soil cover to
top of pipe (m), Wp = weight of pipe and content(kg/m). The soil density and friction coefficient(under static loads) are obtained from soil tests.
In impact related problems such as blast, it
requires solution to equation of motion andanalytical method may not provide accurate
solutions to all the required variables. This is dueto the dynamic nature of the problem as well as theblast duration which is short (i. e. transient). The
non-linearity of the response of underground pipes
due to blast loads lies in the definition of material(in this study, the material is considered as linear,elastic, homogeneous and isotropic), contact
problem definition (boundary conditions), large
displacements and rotations due to large loads(non-linear geometry) and time increment toensure stability [2]. These responses could besuitably and easily studied by direct simulation, i.
e. modeling using a suitable finite element
numerical code, in this study, ABAQUS.
Considering the dynamic behavior of buried
structures, a lot of works have been done on
dynamic soil-structure interaction majorly forlinear, homogeneous, and semi-infinite half spaceeither linear or nonlinear using analytical or
numerical methods [5], [7]. In this paper, blast

2. BACKGROUND STUDY
The analysis of soil-pipe interaction throughmodeling using numerical tools involves
determination of variables such as pressure,displacement, strain stresses, etc around the pipe.

18

GEOMATE- Brisbane, Nov. 19-21, 2014

loads will be examined with a view to providing
design parameters for the design of buried
structures to resist the effects of blast loads inother to reduce environmental risk and hazards.
From experience, the most common ways bywhich blast scenarios are expected to occur are:surface blast above the ground surface; open
trench blast; underground blast below the groundsurface with the explosives completely buried in
the ground; and blast right inside the structures(whether the structure is buried in the ground orwithin the ground and the surface or on the groundsurface). These are presented in Fig. 1.

Fig. 2 Pressure-time curve
3. METHODOLOGY
In this study, in line with [11], blast load
parameters were determined. For verification of
blast load duration and dynamic effects ofcoefficient of friction on buried pipes, the soil of
100 m by 100 m by 100 m deep and pipes
materials of 1.0 m internal diameter, 20 mm and100 mm thick were modeled as elastic,
homogeneous and isotropic as shown in Figs. 3
and 4 using the two elastic constants as obtained
from different researchers and pipe manufacturers[1], [2], [3], [4]. Simulated models for ‘slip’ and‘no-slip’ conditions were analyzed using explicit
code in ABAQUS with ‘no-slip’ condition serving
as control. In the ‘no-slip’ condition, it was
assumed that perfect bond exist between the pipes
and the soil while for ‘slip’ condition, coefficientof friction were varied.
The governing dynamic equation of motion is
given as:Fig. 1 Blast scenarios common to undergroundpipes
According to [11], the violent release of energy
from a detonation converts the explosive material
into a very high pressure gas at very hightemperatures. It is followed by pressure front
associated with the high pressure gas which
propagates radially into the surrounding
atmosphere as a strong shock wave, driven andsupported by the hot gases. This pressure increaseor shock front travels radially from the source of
explosion with a reducing shock velocity which isalways in excess of the sonic velocity of themedium [8]. The shock front arrives at a given
location at time (ms). After the rise to the peakvalue of overpressure, the incident pressure decays
to the ambient value in time which is the positive
duration. The negative phase, shown in Fig, 2 witha duration which is usually longer than the positive
phase and characterized by a negative pressure(usually below ambient pressure) have maximum
values as well as reversal of the particle flow. The
incident pulse density associated with the blast
wave is the integrated area under the pressure-time
curve shown in Fig. 2.

[m] [Ü] + [c] [Ů] + [k] [U] = [P];Uo, and Ů (t = 0) = Ůo = vo

for U (t = 0) =(2)

where m, c, and k are element mass, damping andstiffness matrices, t is the time, U and P aredisplacement and load vectors and dots indicate
their time derivatives [5]. The explicit dynamics
analysis procedure in ABAQUS (finite element
based numerical code) was used to solve eq. 2 [3].
The boundary conditions shown in the model (Fig.
4) were defined with respect to global Cartesianaxes [2], [9].

19GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 5. In addition, the results of the peak side-on
overpressure for surface blast for explosives
ranging from 500kg TNT to 10000kg TNT are
presented in Fig. 6. Furthermore, displacement andpressure of pipes buried in loose sand for various
periods due to surface blast are presented in Fig. 7.
The results of various observed response/behavior
parameters at the crown, invert and spring-line ofburied pipes against varied coefficient of friction
are further processed using dimensional analysis
and the dimensionless responses at the crown,
invert and spring-line of buried pipes are presented
in Figs. 8 to 11.
It must be noted that P is the intensity ofsurface pressure, P (cr, inv and spr) are the crown,
invert and spring-line pressure respectively, H isthe cover depth while D is the diameter of pipe, x
is the displacement at the crown, invert and springline of pipes, P is the surface pressure intensity,
is the unit weight of soil and r is the radius of pipe.
These are shown in Figs. 8 to 11.

Fig. 3 Schematic diagram of underground pipe [8]Fig. 4 Finite element model showing discretization[8]
Dimensional analysis was used to analyze theresults of the dynamic effects of coefficient offriction on buried pipes due to blast loads [4]. All
the dimensions are power law monomials of the
form
a

b

[α] = K L M T

cFig. 5 Loading wave velocity due to underground
blast

(3)

where α is the dimension of a physical quantity
which would have a dimensionless quantity ([α] =1), K and (a, b, c) are constants. This property iscalled dimensional homogeneity which forms the
key to dimensional analysis [4].
4. RESULTS AND DISCUSION
In the case of underground blast, ground shock
parameters which are equally known as the soil
movement parameters translate into loading which
the soil delivers to the buried structures. These
parameters depend on both the seismic velocity
and peak particle velocity. For a totally or partiallyburied charge located at a distance from thestructure,groundmovement
parameters
determined for stand-off distances are shown in

Fig. 6 Peak side-on overpressure due to surface
blast

20

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 10 Dimensionless spring-line pressure against
coefficient of friction for underground blast

Fig. 7 Displacement in pipes buried in loose sandFig. 8 Dimensionless spring-line pressure against
coefficient of friction for surface blast

Fig. 11 Dimensionless spring-line pressure against
coefficient of friction for undetrground blast
From Figs. 5 and 6, it was observed that energy
attenuates greatly as the distances from the blast
increases. In the case of underground blast, energy
reduced to seismic velocity of the ground at lessthan 10m from the source of blast. Energy impulse
from underground blast decreases as it travels fortwo main reasons, firstly, due to three dimensional
dispersion of energy from blast, and secondly, due
to work done in plastically deforming the soil
matrix. Arrival time of blast wave depends oncompression seismic velocity of the ground media.
The arrival time is higher in saturated clay
compared to other ground media. For the behaviorof underground structures, especially pipes, arrival
time of blast wave is the determining factor
because it depends on the compression wave
seismic velocity of soil. For structures above theground surface, blast duration is the governing

Fig. 9 Dimensionless spring-line pressure against
coefficient of friction for surface blast21

GEOMATE- Brisbane, Nov. 19-21, 2014

increase of charge weight specified by [11], 1.220
could be used for both vertical and horizontal
displacement while 1.0936 could be used for bothvertical velocity and horizontal velocity and1.0595 could be used for both vertical andhorizontal acceleration [8], [11].
In the result of the effect of coefficient offriction on the response of underground pipes dueto blast loads as presented by [9], it was observedthat there is variation in the results due to various
parameters involved in the analysis. It became verymuch easier to interpret the results after evaluation
using dimensional analysis. From the results ofthis study shown in Figs 8 to 11, at low coefficientof friction, the value of the dimensionless observed
parameters is high in steel pipes due to ductility ofsteel pipes, while that of concrete pipes showed
little or no increase due to brittleness of concrete
pipes. Although the values of the dimensionlessobserved parameters for steel and concrete pipes
reduced at coefficient of friction of 0.8.
From the results of the dimensionless responses
of underground pipes shown in Figs. 8 to 11
obtained using dimensional analysis, it wasobserved that the observed parameters reduce at
coefficient of friction of 0.8 for both surface andunderground blasts. For all the ground media
studied for the various categories of blastsconsidered in the dynamic analysis [9], in thedesign of underground pipes to resist effects of
blast loads, coefficient of friction of average of 0.8
could be used. However, for practical applications
for design purposes to resist effects of static loads,
when test data are not available, the coefficient offriction of 0.3 (for Silt), 0.4 (for Sand) and 0.5 (forgravel) can be used. These coefficients of friction
are the lower bound values equivalent to thesliding friction and static coefficient of friction canbe as much as 70% higher than those stated above[6], [8], [9], [10].

factor. In line with [11], the blast wave parameters
for the direct induced ground shock are theoverriding factor for designing and studying the
behavior of underground structures. At shortduration which is common to blast, for low blastpressure due to surface blast, there is no behavior(i.e. response) of underground pipes even at small
depth of burial.
One of the major challenges in the predictionof blast loads and duration is the complexity anddifficulty in identifying the exact location, points
or heights where the explosion will take place forsurface blast. However, this problem is overcomeby the fact that for parameters and guidelines to besuggested, there must be behaviors of undergroundstructures (in this case pipes) due to blast loads.
Efforts is tailored towards arriving at specific blastloads parameters and duration that produce
behaviors or responses on underground pipes.
Even if these loads are increased, response will
also increase as well. In [11], the side-on
overpressure and peak reflected pressure in therange of 2500psi to 8000psi and 30000psi to
100000 psi respectively do not have duration
specified in the chart. For these pressures,
durations have to be specified. This is scaled
distance in the range of 0.1 to 0.45 and this does
not mean that there is no duration for such blastpressures at such scaled distances. However,judgment has to be applied, to adjudge duration tosuch events. For scaled distances of 0.45 to 1.3 and2.5 to 6, durations are almost the same irrespectiveof charge weight considered. It was observed from
Fig. 7 that at less than 5ms of surface blast load
duration, there is little or no behavior ofunderground pipes. This is noticeable in loose sandcompared to other ground media. But as theduration of blast load increases, behaviors also
increase. Since there must be behaviors inunderground structures in order to provide design
parameters and guidelines, duration of blast to be
used should not be less than 20ms. Conservatively,
to study the behaviors of underground structuresdue to blast, duration of 25ms is adequate forground media [8].
For the purpose of the estimation of blast loads
for various blast scenarios mentioned earlier on, inthe dynamic behavior study of undergroundstructures using finite element based numericalcodes, in order to convert blast parameters from
0% increase of charge weight to 10% increase of
charge weight, the following could be used as
multiplication factor: 1.108 could be used forvertical and horizontal displacement while 1.0472
could be used for both vertical velocity andhorizontal velocity. In addition, 1.02982 could be
used for both vertical and horizontal acceleration.
To convert the same blast parameters as abovefrom 0% increase of charge weight to 20%

4. CONCLUSION
This paper has highlighted the basic steps in
the estimation of loads arising from blast for the
purpose of simulating the dynamic effects ofcoefficient of friction on underground pipes. Blast
phenomenon and various blast scenarios applicableto underground structures were also examined andvarious durations for studying the behaviors ofunderground structures due to blast were equally
examined. Dynamic effects of coefficient offriction on buried pipes were studied andcoefficients of friction of friction were equallyvaried. Finite difference method in ABAQUS
numerical code [1] was used to solve the equationof motion throughout time and dimensional
analysis was used to evaluate the results.
Practicable coefficient of friction for practical

22

GEOMATE- Brisbane, Nov. 19-21, 2014

applications in the design of buried pipes was
suggested.

[6] Lester, H.G. Chapter 4: The Pipe/Soil
Structure – Actions and Interactions, 1-14,
http://plasticpipe.org/pdf/chapter4_pipe_soil_s
tructure, 05/10/2010, 2008.
[7] Olarewaju, AJ, Kameswara RNSV and
Mannan, MA, “Response of Underground
Pipes to Blast Loads”, Earthquake-Resistant
Structures - Design, Assessment andRehabilitation, Abbas Moustafa (Ed.), InTech
Publisher, Croatia, Europe, Feb., 2012, pp507- 524.
[8] Olarewaju, AJ, “A Study on the Response of
Underground Pipes Due to Blast Loads”, Ph.D
Thesis, SKTM, Universiti Malaysia Sabah,
Malaysia, 2013.
[9] Olarewaju, A.J. “Estimation of blast loads forstudying the dynamic effects of coefficient offriction on buried pipes by simulation”,
International
Journalof
GEOMATE,
Geotechnique, Construction Materials andEnvironment, Tsu city, Mie, Japan, ISSN
2186-2982 (P), 2186-2990 (O), Sept., (received
on Apr. 17, 2014), Vol. 7, No. 1 (SI No. 13), 2014,
pp 1017-1024..
[10] Peng L.C. “Soil-pipe interaction - Stressanalysis methods for underground pipelines”,
AAA Technology and Specialties Co., Inc.,
Houston, Pipeline Industry, May, 67-76, 1978.
[11] Unified Facilities Criteria, “Structures toResist the Effects of Accidental Explosions”,
UFC 3-340-02, USA, 2008.

5. ACKNOWLEDGEMENTS
It is a project funded by Ministry of Science
Technology and Innovation (MOSTI), Malaysia
under e-Science Grant no. 03-01-10-SF0042(Universiti Malaysia Sabah, Kota Kinabalu, Sabah,
Malaysia).
6. REFERENCES[1] ABAQUS Inc., “ABAQUS Analysis User’s
Manuals – Documentation, Version 6.7- and6.8-EF”,
Dassault
Systemes
Simulia,
Providence, USA, 2009.
[2] ABAQUS Inc.. Geotechnical Modeling andAnalysis with ABAQUS, Dassault Systemes
Simulia, Providence, Rhode Island, USA,2009.
[3] ABAQUS Inc.. ABAQUS/Explicit: Advanced
Topics, Dassault Systemes Simulia,
Providence, Rhode Island, USA, 2009.
[4] Barenblatt, G.I.. “Dimensional Analysis”,
Gordon and Breach Science Publishers, New
York, 1987
[5] Kameswara RNSV, “Vibration Analysis andFoundation”, 1st Ed., New Delhi, Wheeler
Publishing Co. Ltd., India, 1998.

23

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

VERIFICATION OF RANDOM FINITE ELEMENT ANALYSIS FOREVALUATING BEHAVIOR OF A CEMENT-TREATED SOIL COLUMN

Tsutomu Namikawa1
Civil Engineering Department, Shibaura Institute of Technology, Japan

1

ABSTRACTThis paper presents a verification of the random finite element analysis approach for evaluating thecompression behavior of a cement-treated soil column with spatial variability. In the verification, the unconfinedcompression tests of a full scale cement-treated soil column constructed by deep mixing method are simulatedusing the random finite element method. Samples of the full scale column are generated by means of Monte
Carlo simulation and the finite element analysis with an elasto-plastic model which is developed for describing
the mechanical behavior of the cement-treated soil is conducted for the generated samples. The statisticalparameters of the cement-treated soil strength in the numerical analysis are determined from the strength ofcored samples retrieved from the constructed columns. The numerical results indicate that the random finite
element method evaluates the overall strength of the full scale column reasonably.
Keywords: Cement-treated Soil, Spatial Variability, Finite Element Analysis, Monte Carlo Simulation

mainly discussed. The comparison of the numericaland experimental results indicates that the random
finite element method evaluates the overall strengthof the full scale column reasonably.

INTRODUCTION
It is well known that the strength of cementtreated soil ground by deep mixing is spatiallyvariable, even at a single column. Therefore, suchspatial variability has to be taken into account indesign procedures to obtain the benefit of ground
improvement. Finite element analysis combinedwith random field theory, called random finite
element analysis, could be a powerful analysis toolfor evaluating the behavior of the cement-treated soil
ground [1]. Before adopting the random finite
analysis in the design procedure, it is necessary toverify the random finite analysis for describing
properly the behavior of the cement-treated soil
ground with spatial variability.
This paper presents the verification of therandom finite element analysis approach forevaluating the compression behavior of a cementtreated soil column with spatial variability. Futaki etal. (1996) [2] conducted the unconfined compression
tests of full scale cement-treated soil columns
constructed by deep mixing method. This full scale
test is simulated using the random finite element
method. On the basis of the statistical parameters ofcored sample strength, full scale column samples are
generated by means of Monte Carlo simulation andthe finite element analysis with an elasto-plastic
model which is developed for describing themechanical behavior of the cement-treated soil isconducted for the generated samples. In this study,
overall strength Q u defined as the unconfinedcompressive strength of the full scale column is

FULL SCALE COLUMN TEST
Futaki et al. (1996) [2] conducted theunconfined compression tests of deep mixed
columns constructed at two sites. Group A testcolumns were constructed in cohesive groundhaving organic soil in the upper layer and Group B
test columns were constructed in sandy ground. Fourcolumns were tested in each group. The test columns
are 1 m in diameter and 2.2 m in height.
Cored sample strength
25 cored samples were retrieved from an upper
cutoff portion of each test column; 100 coredsamples were obtained for each group. The
statistical values of the unconfined compressive
strength q u of cored samples are shown in Table 1.
Using the sample mean m qu and standard deviations qu of q u in Table 1, the random field samples are
generated by mean of Monte Carlo simulation.
The probability distribution of q u is required togenerate the random field samples. Several studies
have been carried out to investigate the type of
probability distribution of q u [1], [3], [4]. Thesestudies indicate that the normal or lognormal
distribution provides a good fit for q u . In this study,
the Kolmogorov-Smirnov (K-S) test [5] was
24

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 1 Statistical parameters of cored sample
strengthA
B

Mean m qu
3.48 MPa
3.78 MPa

Experiment [2]θlnqu = 0.5 m
θlnqu = 0.7 m
θlnqu = 1.0 m

1.0Standard deviations qu1.46 MPa
1.20 MPa0.8ρ (d )

Group

strength in the Group B test column. The correlation

0.6
0.4
0.2

Table 2 K-S test results for cored sample strength

0.0

Group
A
B

Probability
distribution
NormalLognormal
NormalLognormal

D statistic

P-value

0

0.4

0.6

0.8

1

1.2

d (m)

0.088
0.067
0.117
0.077

0.42
0.76
0.13
0.60

(a) Group A
1.0
Experiment [2]0.8θlnqu = 0.1 m
θlnqu = 0.2 m

0.6

ρ (d )

conducted to evaluate the goodness of fit for normal
and lognormal distributions against the data for eachgroup. The results of the K-S test are summarized inTable 2. Low values of the D statistic indicate abetter fit of the data to the distribution than do highvalues. The K-S test result suggests that thelognormal distribution is better than the normal
distribution for the probability distribution of thedata. The P-value denotes the threshold value of thesignificant level in the sense that the null hypothesis
will be accepted for all values larger than the Pvalue. The K-S test result shows that the P-value aremuch larger than 0.1 in all the cases of the normal
and lognormal distributions, indicating that the null
hypothesis that both the distributions are suitable forthe probability distribution of q u can be accepted at
the 10% significant level. In this study, on the basisof the D statistic results, the lognormal distribution
is assumed for characterizing the probability
distribution of q u .
The spatial correlation should be considered todescribe the spatial variability appropriately. The
exponential-type autocorrelation function is assumed
for characterizing the spatial variability of q u . The
exponential-type autocorrelation function is defined
as

d 
ρ(d ) = exp − θlnqu 



0.2

0.4
0.2
0.0
-0.2
-0.4
0

0.2

0.4

0.6

0.8

1

1.2

d (m)

(b) Group B
Fig. 1

Correlation coefficient of q u

coefficient calculated from Eq.(1) is also plotted in
Figure 1. Here it is assumed that θ lnqu is not muchdifferent in magnitude from the autocorrelation
distance in the random field of q u [6]. The values ofθ lnqu could be estimated to range from 0.5 m to 1.0
m for the Group A test columns and range from 0.0
m to 0.2 m for the Group B test columns.
Unconfined compressive strength of a full scalecolumnFutaki et al. (1996) [2] obtained the overall
strength Q u of the full scale column from theunconfined compression tests. The obtained Q uvalues range from 1.3 MPa to 2.2 MPa in the GroupA test columns and from 2.5 MPa to 4.0 MPa in theGroup B test columns.

(1)

where ρ(d) = correlation coefficient; d = distance
between the two points; and θ lnqu = autocorrelation
distance in the random field of ln q u . Futaki et al.
(1996) [2] calculated the correlation coefficient of
the cored sample strength in each group. The
correlation coefficient of the cored sample strengthis shown in Figure 1. It can be seen that the strength
correlates clearly in the Group A test column.
Conversely, there is little spatial correlation of the

A DESCRIPTION OF
ELEMENT METHODRANDOM

FINITE

Finite element analysis combined with random
field theory, called random finite element analysis,
was conducted to simulate the full scale unconfinedcompression test described in the previous section.
In this analysis, Monte Carlo simulations were25

GEOMATE- Brisbane, Nov. 19-21, 2014

performed involving the generation of realizations of
the strength random field and the subsequence finite
element analysis simulating the unconfinedcompression test.

xz
Imposed displacement in
Z direction

Generation of random field
As mentioned in the previous section, thelognormal distribution and exponential-type
autocorrelation function defined in Eq.(1) are
assumed for characterizing the probability
distribution and spatial variability of q u . The random
field with the spatial correlation was generated bycovariance matrix decomposition [7]. Using the
Box-Muller method, the normal random numbers(white noise with the standard normal distribution)
were calculated from uniform random numbers
generated by the M-sequences method. Covariancematrix decomposition is a direct method of
producing a random field with prescribed covariancestructure. In this method, a random field vector X(r)with the mean value µ = 0 is derived as
X(r ) = L ⋅ u(r )Fixed in Z direction

Fig. 2The variable unconfined compressive strength
value of each element q ui is given by(2)(

qui = exp μlnqu + σ lnqu xi

where L is the lower triangular matrix of covariancematrix Σ, and u(r) is a white noise vector with astandard normal distribution. Σ consists of ρ(d)calculated from d by Eq. (1). L satisfies

LLT = ΣFEM meshσ lnqu =(3)) (i = 1,, N )e(4)  σ 2 
1qu  
2
ln 1 + 
,
μ
=
lnμ
−
σ
lnqu
qu
lnqu

 
2
  μ qu  where µ qu is the mean of the strength, σ qu is thestandard deviation of q u , x i is the standard normal
random variable and N e is the number of elements.
The value of x i generated by the method mentioned
in the previous section is assigned to each element in
the sample in the FE-analysis. The value of µ qu andσ qu are determined from the mean and standard
deviation of the cored sample strength as shown in
Table 1. Here q ui is classified into the discreteclasses whose interval is set to be 0.02µ qu .
Three different autocorrelation distances θ lnqu areconsidered in the simulation of each group. On thebasis of the correlation coefficient of the coredsample strength shown in Figure 1, the values ofθ lnqu were set to be 0.5 m, 0.7m and 1.0 m in thegroup A simulation, and 0.0 m, 0.1m, and 0.2 m in
the group B simulation. Typical samples of theGroup A columns are shown in Figure 3. The
samples consist of 1936 elements. Dark and lightregions depict “strong” and “weak” cement-treatedsoil, respectively. These spatial distributions of thestrength are derived from the same probability
distribution, that is to say, the lognormal distribution
with the same probability parameters. The differencein spatial distribution is brought about by thedifference of the autocorrelation distance θ lnqu .

L is obtained using Cholesky decomposition.
The random number with the lognormal
distribution was calculated from the normal random
numbers. 100 realizations of the Monte Carloprocess were performed for each case.
Finite element analysis condition
Three-dimensional finite element analyses were
performed using the finite element program
developed by Shiomi et al. (1993) [8]. The finite
element meshes for simulating the full scale column
tests are shown in Figure 2. The sample is modeled
as an isolated column of 1 m diameter and 2.2 m
height. The mesh consisting of eight-nodeisoparametric elements is used. The majority of theelements are cubic with a length of 100 mm. The
element length corresponds approximately to thestandard height of cored samples. Therefore thelocal average process [7] has not been carried out inthe analyses. The boundary condition for the sample
is shown in Figure 2. The boundary conditions at the
top and bottom surfaces are smooth. The loading
process consists of applying uniform verticaldisplacement at the upper surface of the sample.

26

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 3 Material parameters for FE-analysis

3µqu

0 (MPa)Elastic modulus E
Poisson’s ratio νFriction angle φ
Cohesion c

3000 MPa
0.167
30 degree
490 kPa

Stochastic
Deterministic
Deterministic
Stochastic

Tensile strength T f

380 kPa

Stochastic

Hardening parameter α

1.05

Deterministic

Hardening parameter e y

0.0002

Deterministic

Fracture energy G f

9.0 N/m

Stochastic

0.4

Deterministic

Softening parameter e r
Dilatancy coefficient D cθlnqu = 0.5 m

θlnqu = 0.7 m-0.4Deterministic

Localization size t s0

0.6 mmDeterministic

Characteristics length l c

100 mmDeterministicθlnqu = 1.0 m
NUMERICAL SIMULATIONS

Fig. 3 Typical samples for FEM analysis (Group A)

Using the random finite element method,
numerical analyses were carried out to simulate thebehavior of the Group A and B test columns. Five
realizations of the overall stress-strain relationshipobtained from the numerical analyses are shown in
Figure 4. In these stress-strain relationships, thestress is calculated from the total vertical load at the
top surface and the strain is calculated from thevertical displacement of the top surface. For theGroup A test with θ lnqu = 0.7 m, the stress-strain
relationships vary widely before the peak stress state.
Conversely, for the Group B test with θ lnqu = 0.1 m,
there are no significant differences between the
stress-strain relationships before the peak stress state.
This is so because as the autocorrelation distanceincreases, the difference between the stress-strain
relationships of the samples becomes large [1]. The
experimental results are plotted in Figure 4 forcomparison. The gradual stress increase during theinitial loading process is observed in theexperimental stress-strain relationships. This is
attributable to the bedding error occurring at the top
and bottom boundaries of the column. Consequently,
there are significant differences between the
numerical
andexperimental
stress-strain
relationships. It seems that such bedding error
occurs significantly in the Group B test results.
However, except the initial loading process, thecalculated stress-strain relationships reasonably
agree
with
the
experimental
stress-strain
relationships.
The computed overall strength Q u is summarized
in Figure 5. The variability of Q u increases as θ lnquincreased. For the samples in the absence of spatial
autocorrelation (θ lnqu = 0.0 m) for the Group B test,
it can be seen that the variability of Q u is quite low.
Conversely, the variability of Q u is high in thesimulation for the Group A test in which θ lnqu is

An elasto-plastic model developed for cementtreated soils [9] was used in these analyses. Thismodel can describe appropriately tensile and shear
strain-softening behaviors in the strain localization
zone after the peak stress state. In this model, thesmeared crack band concept [10] is used to avoid
mesh size dependency due to the strain localization.
Thus the FE-analysis with the elasto-plastic model
can simulate reasonably the post-peak behavior of
cement-treated soils under various boundary
conditions. The performance of the used model has
been verified by the simulations for several
laboratory tests of cement-treated soils [9], [11].
A list of elasto-plastic model parameters used in
the numerical modeling and their values are shownin Table 3. These parameters for q u = 1.7 MPa were
determined from the results of various laboratory
tests in which cement-treated sand specimens withthe unconfined compressive strength of 1.7 MPa
were used [9], [12]. As indicated in Table 1, theelastic modulus E, the cohesion c, the tensile
strength T f , and the fracture energy G f are regarded
as the stochastic parameters. With the constantfriction angle φ, the value of cohesion c isdetermined from the value of q ui . The values of E, T f
and G f are assumed to be proportional to the valueof q ui . Other parameters, Poisson’s ratio ν, thehardening parameters α and e y , the softening
parameter e r , the dilatancy coefficient D c , thelocalization size t s0 , and the characteristics length l c ,are assumed not to vary with q ui . The detailed
descriptions of the material parameters and thenumerical examples that can illustrate theapplicability of this model are available elsewhere[9], [11].

27GEOMATE- Brisbane, Nov. 19-21, 2014

relatively large.

6

A-1,A-2,A-3,A-4 : Experimental results [2]

3.0

FEM

5

A-1

4

Qu (MPa)

Axial stress (MPa)4.0

test columns.

A-2
A-3

2.0

A-4
1.0

Experiment [2]

mqu

3
2
1
0

0.0
0

0.2

0.4

0.6

0

0.8

0.5

1

θ lnqu (m)Axial strain (%)(a) Group A (θ lnqu = 0.7 m)
5.0(a) Group A

B-1,B-2,B-3,B-4 : Experimental results [2]5Experiment [2]

4.0

B-2

3.0

B-3
2.0

mqu

4

B-1

Qu (MPa)

Axial stress (MPa)

FEM

B-4

3
2
1

1.0

0

0.0
0.0

0.5

-0.2

1.0

0

0.2

θ lnqu (m)Axial strain (%)(b) Group B (θ lnqu = 0.1 m)(b) Group B

Fig. 4

Fig. 5

Typical Stress-strain relationships

The experimental results are plotted in Figure 5
for comparison. In the simulation for the Group A
test, most computed Q u values become larger thanthe experimental Q u values. The Group A testcolumns were constructed in cohesive ground withorganic soil. In such cohesive ground, it is difficult
to mix the ground thoroughly, with the result that theunmixed parts, that is, the defect parts, remain in
cement-treated soil columns. The lognormal
distribution used for the probability distribution ofq u cannot generate the low values of q u , implyingthat the samples in the simulation do not containdefect parts. The probability distribution which can
describe the defect parts in cement-treated groundshould be examined in future studies.
In the simulation for the Group B test, the meanof the computed Q u agrees reasonably with that of
the experimental Q u . However, the numerical result
cannot describe the large variability of Q u in theexperimental result. As mentioned before, thevariability of the computed Q u depends on θ lnqu . The
values of θ lnqu used in the numerical simulation were
determined from the correlation coefficient reported
by Futaki et al. (1996) [2] (Figure 1). The reported
correlation coefficient may not represent sufficiently
the spatial correlation of the strength in the Group B

Computed overall strength Q u

CONCLUSIONS
Finite element analysis combined with random
field theory, called random finite element analysis,
was conducted for simulating the unconfinedcompression behavior of a cement-treated soilcolumn. The objective of this study is to verify theapplicability of the random finite element analysis tothe evaluation of the overall strength of a cementtreated soil column. The comparison between theexperimental and numerical results indicates that the
random finite element analysis can describe theoverall strength of a cement-treated soil column
reasonably. However, there are some differences
between both the results. In order to improve thenumerical prediction, the probability distribution andthe statistical parameters used in the analysis should
be examined thoroughly in future studies.
ACKNOWLEDGEMENTS
The author is grateful to Takenaka Corporation
for their cooperation in the numerical analysis. The
author also acknowledges the support of the Japan
Society for the Promotion of Science (JSPS28

GEOMATE- Brisbane, Nov. 19-21, 2014

KAKENHI Grant No. 25420509).

[7] Griffiths DV and Fenton GA, “Probabilistic
methods in geotechnical engineering, Random
field generation and the local average
subdivision method”, Springer, Wien, New
York, 2007, pp. 201-223[8] Shiomi T, Shigeno Y and Zienkiewicz OC,“Numerical prediction for model No.1”,
Arulanandan & Scott (ed.) Verifications of
Numerical Procedures for the Analysis of Soil
Liquefaction Problems, Balkema, 1993, pp.
213-219.
[9] Namikawa T and Mihira S, “Elasto-plastic
model for cement-treated sand”, International
Journal for Numerical and Analytical Methods
in Geomechanics, 31(1), 2007, pp. 71-107.
[10] Pietruszczak ST and Mróz Z, “Finite element
analysis of deformation of strain-softening
materials”, International Journal for Numerical
Methods in Engineering. 17, 1981, pp. 327-334.
[11] Namikawa T and Koseki J, “Evaluation oftensile strength of cement-treated sand based on
several types of laboratory tests”, Soils andFoundations, 47(4), 2007, pp. 657-674.
[12] Namikawa T and Koseki J, “Experimental
determination of softening relations for cementtreated sand”, Soils and Foundations, 46(4),2006, pp. 491-504.

REFERENCES[1] Namikawa T and Koseki J, “Effects of spatial
correlation on the compression behavior of acement-treatedcolumn”,
Journalof
GeotechnicalandGeoenvironmental
Engineering ASCE, 139(8), 2013, pp. 13461359.
[2] Futaki M, Nakano K and Hagino Y, “Design
strength of soil-cement columns as foundation
ground for structures”, Proceedings of ISTOKYO’96
The
secondinternational
conference of ground improvement geosystems,
1996, pp. 481-484.
[3] Honjo Y, “A probabilistic approach to evaluate
shear strength of heterogeneous stabilized
ground by deep mixing method” Soils andFoundations, 22(1), 1982, pp. 23-38.
[4] Navin MP and Filz GM, “Statistical analysis ofstrength date from ground improved with DMM
columns”, Deep Mixing 05, 2005, pp. 145-154.
[5] Kanji GK, “100 Statistical Tests 3rd Edition”,
SAGE Publications, 2006, pp. 76-77.
[6] Griffiths DV and Fenton GA, “Bearing capacityof spatially random soil: the undrained clay
Prandtl problem revisited” Geotechnique, 51(4),2001, pp. 351-359.

29

FourthInternational Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

INFLUENCE OF LIME ON STRENGTH AND COMPRESSIBILITY
BEHAVIOR OF MARINE CLAY
*Nor Zurairahetty Mohd Yunus1, Aminaton Marto2, Faizal Pakir3, Khairulanam Kasran4 and Mohd Akmal Azri
Jamal4
1
Senior Lecturer, Department of Geotechnics & Transportation, Faculty of Civil Engneering, Universiti
Teknologi Malaysia, 86400, Skudai, Johor
2
Professor, Department of Geotechnics & Transportation, Faculty of Civil Engneering, Universiti Teknologi
Malaysia, 86400, Skudai, Johor
3
Post-graduate Student, Faculty of Civil Engneering, Universiti Teknologi Malaysia, 86400, Skudai, Johor
4
Bachelor Degree Student, Faculty of Civil Engneering, Universiti Teknologi Malaysia, 86400, Skudai, Johor
Coressponding author :nzurairahetty@utm.my

ABSTRACTThe presence of marine clay in Iskandar Malaysia Region, Nusajaya has caused expensive solutions in theconstruction of structures and roads. Alternatively, soil treatment is suggested to increase the strength of theunsuitable material to meet the constructions requirement for foundation and also to achieve the specifications
for development work. In this study, a series of laboratory test will be conducted to determine the potential oflime to stabilize marine clay to form the basis of a strong, reliable land for construction of roads and building.
Testing programme involves obtaining specimens of marine clays from various locations at Iskandar Malaysia
Region, followed by laboratory tests to determine the physical and engineering properties with and without theaddition of lime. The proportions of hydrated lime added are 3%, 6% and 9% to the untreated marine clay andtested at 7 and 28 days curing periods. Results show an increase in strength with increasing lime content. In
addition, strength also increases significantly as early as 7 curing days and continues for 28 curing days. In
agreement with the strength tests, compression characteristics improved with increasing lime content and as time
prolonged. Hence, lime is successful and considered effective to improve the strength and compressibility
behavior of Marine clay.
Keywords: Marine Clay; hydrated lime, Compressibility

improvement methods have been introduced andtested, both in research and in practice. However
their respective suitability are considered to be
project-specific; being dependent on the existingsoil’s characteristics, cost and the stabilizers’
potential impact or effectiveness for the proposed
application. Chemical stabilization is one of themethods recommended to improve the properties ofsoil and lime stabilization is proven effective in mostcases [6], [7], [8].
In order to develop a fundamental
understanding of the engineering behavior of
Malaysian marine clays, the influence of lime toimprove the strength and compressibility behavior of
Marine clay was investigated experimentally. Index
testing such as Atterberg limit, specific gravity andcompaction test were carried out initially on
untreated specimen to determine the suitability oflime for lime-clay reactions. Meanwhile, strengthand compressibility behavior were determined byunconfined compressive strength (UCS) test andoedometer test, respectively. In this study, theeffectiveness of lime to stabilize Marine clay was

INTRODUCTION
Marine clay is a type of clay found both in the
coastal and in several offshore areas spread overmany parts of the world. The properties of saturated
marine clay differ significantly from moist soil anddry soil. Marine clay is microcrystalline in natureand clay minerals like chlorite, kaolinite and illite
and non-clay minerals like quartz and feldspar arepresent in the soil. The soils have higher proportionof organic matters that acts as a cementing agent.
Marine clay soils in particular can present great
problems in pavement design due to uncertainty
associated with their performance [1], [2], [3], [4],[5]. They are often unstable beneath a pavement andthey are the most susceptible to problems due tochanges in moisture.
Nusajaya (about 4% of the area of Iskandar
Malaysia) is one of the main focuses of several
recent developments within the Iskandar region.
However, the weak behavior of clay deposit invarious site of development needs to be replaced or
be specifically improved. Various ground30

GEOMATE-Brisbane, Nov. 19-21, 2014

investigated on the basis of lime content and atdifferent curing periods.

mould. The inner surface of the brass mould waslayered with a thin, transparent sheet to minimize
friction. After that, the specimens were extruded
from the mould and wrapped with a cling film topreserve the water content and prevent from thecarbon dioxide (CO2) exposure. The weight of thespecimens was measured and cured in a controlledtemperature room at 20ºC and humidity greater than
90% for 7 and 28 days. Similarly, specimens ofoedometer test were prepared based on OMD and
MDD of untreated soil before being placed in thecylindrical metal ring with the dimensions of 75mm
diameter and 20mm height.

1.0 MATERIALS & SPECIMENPREPARATIONIn this research, Marine clay was the soil used
and it was obtained from Nusajaya, an area inGelang Patah, Johor. It was dredged from the seabedoffshore the southern coast of the Nusajaya where
there is an under-construction harbour project. The
soil was dumped on the other part of the area. It was
dark grey and highly disturbed by dredging. It wasthen collected in oil tanks and transported to thelaboratory. The properties of the collected Marine
clays in Nusajaya are shown in Figure 1. The
hydrated lime used was supplied by Limetreat (M)Sdn Bhd, a company from Pasir Gudang, Johor. It
was used as a chemical additive. The proportion oflime added to the soil was 3%, 6% and 9%. Table 1
summarizes the basic properties of Marine clay
obtained in Malaysia, Thailand and India, and thisdata was compared to the properties of marine clay
used in this study. Based on the comparison,
Nusajaya marine clay shares the same properties as
those from Kor Yo in Thailand, Eastern Cost ofIndia and Kuala Muda Kedah in Malaysia as shownin Table 1.
Table 1

Fig 1

Summary of properties of Marine clays

Marine clay in Nusajaya

The results of index testing carried out on
untreated Marine clay are summarized in Table 2. In
general, soil is considered as suitable to be stabilizedby lime because the plasticity index (PI) is morethan 10.

Location

Kor Yo,thailandEasterncoast of
India

Kuala
Muda,
Kedah

Nusajaya
Malaysia

Author

[3]

[4]

[5]

Mohd Yunus
et. al (2014)

Gs
MDD(kg/m3
)
OMC
(%)

2.69

2.62

2.6

2.62

1655

1430

1500

1600

Properties

Marine Clay

21

32

22

21

Liquid limit (%)
Plastic limit (%)

58
36

Plasticity index (%)

22

Specific gravity
OMC (%)

2.62
21

MDD (kg/m3)

1600

Table 2

Results obtained from the compaction tests
played an important role in the preparation of treatedspecimen. All the treated specimens were preparedreferring to the respective maximum dry densities(MDD) and optimum moisture contents (OMC) of
untreated soil. The required dry mass of soil samples
was calculated with the reference of the mouldvolume and the MDD. Predetermined quantities oflime were then measured based on the dry mass ofsoil sample and mixed until homogenous. The soil
specimen was then mixed with water content
corresponding to the OMC.
Mixing process was carried within a reasonable
time (approximately five minutes) to ensure thatlime was not exposed to the air for too long. The
specimens were mixed thoroughly and compacted inthree layers into the 38mm x 76mm cylindrical

Physical properties of Marine clay

3.0 TESTING PROGRAMME
Laboratory tests such as specific gravity
test, Atterberg limit test and standard proctor test
were carried out to determine physical properties ofmarine clay. The strength and compressibility of thelime stabilized soil was determined through UCS
and oedometer test at 7 and 28 days of curing.
Physical tests were carried out in the early stage as
an initial step to indicate the suitability of soil for31

GEOMATE-Brisbane, Nov. 19-21, 2014

between 7 days and 14 days are because of themodification process within mixes. This is becauseof frictional component of shear strength. For nearly
28 days, there is an increase in strength but at ahigher constant rate. This is due to the pozzolanic
reactions between lime and soil [12], [13], [14].

lime stabilization. In the second phase ofexperimental work, hydrated lime was added tostabilize the marine clay. This study was carried out
to investigate the effectiveness of lime to stabilize
clay with different amounts of lime contents. The
effectiveness of lime stabilization process wasinvestigated by monitoring the improvement ofstrength and compressibility behavior of lime-clay
reaction over time.

Table 3
Summary of UCS data at different
curing period

4.0 RESULTS AND DISCUSSION

UCS
(Kpa)

UCS
(kPa)

7 days28 days

Untreated

21

21

Marine clay + 3% of lime

138

144

Marine clay + 6% of lime

294

423

Marine clay + 9% of lime

379

517

Sample4.1 Shear Strength Behaviour

Axial Stress (kPa)

Unconfined compression test is carried out
to determine the maximum compressive strength ofmarine clay soil when lime is added. The summaryof the data from unconfined compressive test (UCT)
at different curing periods at different lime content isshown in the Table 2. The detailed calculation ofeach specimen is tabulated in Appendix. Table 3
shows the summary of the strength result obtained
from all of the samples of marine clay at different
curing period which is 7 days and 28 days. Fromtable 3, for untreated sample of marine clay thestrength of the sample remains the same for both
periods which are 21kPa. Besides that, strength at 7days increasing from 21kPa of untreated marine clay
to 138, 294, and 379 for lime treated marine clay 3%
6% and 9% respectively. In addition, it shows thatthe increase of strength gained from untreated to 3%of lime at 7 days is 85.5%. Increasing of strength
gained 3% to 6% of lime and 6% to 9% of lime are
53% and 22%. It shows that by increasing the lime,
the strength of marine clay is also increased.
Furthermore, by increasing the curing period, thestrength of marine clay is also reinforced [9], [10],[11]. This can be shown by comparing 9% of lime at
7 days and 9% of lime used at 28 days, the strengthis 379kPa and 517kPa. The difference is 138kPa
which is rather high.
The results of the unconfined compressive
strength is obtained and plotted at different curing
periods as shown in Figure 3, and Figure 4. Figure 3
shows the effect of lime content at 7 curing days,
while Figure 4 shows the effect of lime content at 28
curing days. The shear strength of each specimen isdetermined based on the peak strength of stressversus strain curve. Based on Figure 3 and 4, theresult for the untreated is the same and it remains
constant after achieving a peak strength which is
21kPa. In Figure 3, it can be seen that the strength
slightly increases at 7 days before decreases at 28
days of curing.
The sample also increased graduallyduring first 7 and 28 days of curing. After 7 days,
the increase became more rapid with sample treated
9% of lime showing the most increment. The small
increases of strength during early days of curing

3% of lime
treated6% of lime
treated9% of lime
treateduntreated

Strain (%)

Axial stress versus Strain at 7 days

Axial Stress (kPa)

Figure 33% of lime treated
6% of lime treated
9% of lime treateduntreated

Strain (%)

Figure 4

Axial stress versus Strain at 28 days

In general, the strength of marine clay with
9% lime at curing of 28 days is 517kPa which higher
than the strength of marine clay with 3% and 6%
lime. Comparing two result of 9% lime treatedmarine clay with different curing day, at 28 days thestrength of marine clay is higher than 7 days. So, it
is proven that curing process is a factor in
32

GEOMATE-Brisbane, Nov. 19-21, 2014

determining the strength of the treated marine clay.
The lowest strength is 138kPa when the sample isadded only 3% of lime and the curing period is 7
days. However, the strength of the soil slightly
increase at 144kPa when the curing period is longer
at 28 days and the concentration of lime is the sameat 3%. The strength gradually increases by adding
more concentration of lime which is 6%. It has been
proven that 3% increase in strength is lesssignificant, which shows that addition of 3% lime is
not really effective to stabilize marine clay.
However with further addition if 6% and 9% of lime
content, the strength gains more significantly. The
percentage of strength gained recorded for marine
clay treated of 6% and 9% of lime content between 7
to 28 days are 30% and 27%. Prior to analysis, thestrength of marine clay could be stabilized with highincreasing concentration of lime. Therefore, basedon the study, it is proven that the strength of limetreated marine clay will be reinforced if the curing
time is longer.

Table 4
Summary of oedometer tests on limetreated marine clay at 7 curing days.
Specimen
Diameter (mm)Height (mm)Initial void
ratio, eiCompression
index,Cc
Preconsolidatio
n pressure,Pc (kPa)

M0%
L
50.0
20.0
0.66

M3%
L
50.0
20.0
0.64

M6%
L
50.0
20.0
0.72

M9%
L
50.0
20.0
0.77

0.143

0.066

0.050

0.040

19.0

21.0

22.0

41.0

Table 5 summarises the initial properties oflime-treated marine clay after 28 curing days. In thisstudy, each specimen was prepared to an initialwater content equal to their respective compaction
test. Figure 7 shows the range of initial void ratio (ei)of lime-treated marine clay. The ei was calculated
prior to applying the necessary loads. The effect oflime content on compressibility behaviour of limetreated marine clay was further analysed at 28 days.
Table 5 summarises the initial properties of limetreated marine clay specimens at 28 curing days.
The compression index, cc for untreated marine is
0.143 and the value of compression is decrease to
0.028 for marine clay treated with 9% of lime.

4.2 COMPRESSIBILITY BEHAVIOUR
The odometer test was conducted on both
untreated marine and treated marine clay. The
untreated marine clay specimen was prepared andtested as a control specimen for comparison purpose
with the treated specimens. Meanwhile, each
duplicate sample was prepared for lime-treatedmarine clay at different curing period and lime
contents, respectively. The proportions of lime
added in this study were 3%, 6% and 9% and tested
at curing period of 7 and 28 days. In this experiment,
we use 12.5 kPa of sample as an initial load. The
vertical compression under each load is observed atsuitable intervals normally until up to 24 hours
period. The load increment ratio (LIR=2) applied
was 12.5kPa, 25.0kPa, 50.0kPa, 100kPa and lastly
200kPa while four decrement ratio were applied
during reloading stage which were 50kPa and12.5kPa. This section assesses the compressibility
behaviour of lime-treated marine clay at different
curing periods. The effect the lime-clay reactions isanalysed in terms of changes in void ratio (e),compression index (cc) and coefficient ofconsolidation (cv) which defines a soil’scompressibility.
Table 4 summarises the initial properties oflime-treated marine clay after 7 curing days. In thisstudy, each specimen was prepared to an initialwater content equal to their respective compaction
test OMC obtained from compaction test. Figure 6
illustrates the range of initial void ratio (ei) of thelime-treated marine clay. The ei was calculated prior
to applying the necessary loads. The compression
index, cc for untreated marine was 0.143, cc wasfound to decrease to 0.040 with addition of 9% of
lime.

Table 5
Summary of oedometer tests on limetreated marine clay at 28 curing days.
Specimen
Diameter (mm)Height (mm)Initial void
ratio, eiCompression
index,Cc
Preconsolidatio
n pressure,Pc (kPa)

M0%
L
50.0
20.0
0.64

M3%
L
50.0
20.0
0.59

M6%
L
50.0
20.0
0.62

M9%
L
50.0
20.0
0.73

0.143

0.047

0.040

0.028

19.0

34.0

37.0

50.0

From figure 5 we can see that about 7 days
curing period, the difference of void ratio of
untreated marine clay is 0.114 while for marine clay
treated with 3% of lime is about 0.03. For marine
clay treated with 9% of lime the difference of void
ratio is 0.022. It shows that the void ratio of limetreated marine clay decreases with increasing lime
content.

33

GEOMATE-Brisbane, Nov. 19-21, 2014

for 7 days curing period for untreated marine clay is
8.3 m2/years at 12.5 kPa than it increases to 8.61
m2/years at 25 kPa and for 200 kPa coefficient ofconsolidation is 13.31 m2/years. At 12.5kPa, marine
clay treated with 9% of lime the coefficient ofconsolidation is decrease to 5.6 m2/years compare to
untreated marine clay which is 8.3 m2/years.

Figure 5
Effect of lime on compression curves oftreated marine clay after 7 curing days
From figure 6 we can see that at 28 days
curing period, the difference of void ratio of
untreated marine clay is 0.114 while for marine clay
treated with 6 % of lime is about 0.036. For marine
clay treated with 9% of lime the difference of void
ratio is 0.014. It shows that the void ratio of limetreated marine clay decreases with increasing lime
content.

Figure 7
Effect of lime-treated marine clay on
coefficient of consolidation (cv) at 7 curing days.
From figure 8 we can see that, thecoefficient of consolidation (cv) for 28 days curing
period for untreated marine clay is 8.3 m2/years at
12.5 kPa than it increases to 8.61 m2/years at 25 kPa
and for 200 kPa coefficient of consolidation is 13.31
m2/years. At 12.5 kPa, marine clay treated with 9%of lime the coefficient of consolidation decreases to
5.5 m2/years, compared to untreated marine clay
which is 8.3 m2/years

Figure 6
Effect of lime on compression curves oftreated marine clay after 28 curing days
Figure 7 and figure 8 show the effect oflime-treated marine clay on coefficient ofconsolidation (cv) at 7 and 28 days respectively. The
rate of consolidation could be determined bymeasuring the coefficient of consolidation (cv)obtained for each specimen at corresponding appliedpressure. cv was evaluated based on the Taylor
method. Based on that figure, it can be seen cv
decrease with increasing lime content whichindicates that specimens experienced lesscompressible behaviour. Consequently, a decrease in
cv values were observed on lime-treated marine clay
with higher lime content[15], [16], [17]. From figure
8 we can see that, the coefficient of consolidation (cv)

Figure 8
Effect of lime-treated marine clay on
coefficient of consolidation (cv) at 28 curing days
5.0 CONCLUSIONSThe physical properties of untreated and treatedlime stabilized the marine clays were investigatedand discussed in this study. Plasticity chart the34

GEOMATE-Brisbane, Nov. 19-21, 2014

marine clay can be classified as MH which is highsilt. Since the value of Plastic Index (PI) is morethan 10, the marine clay is suitable to be stabilizedwith lime. From the Standard Proctor Compaction
Test, the maximum dry density (MDD) and
optimum moisture content (OMC) is1.55 Mg/m3 and21.20 % respectively while the specific gravity is
2.62. From the Unconfined Compression Test
(UCT) test, it was illustrated that the strength
development after 7 days is less significant. This isdue to the process of modification. However, thestrength treated soils increases rapidly at 28 days
curing period. This phenomenon could be related tothe process of stabilisation. Overall, this study
proves that when lime is added into soils, thereactions between lime and clay particles change theproperties of soils and these would increase thecompression strength and shear strength of soil,
which makes marine clay more stable. The
consolidation test concludes that the void ratio of thesample decreases as the percentage of lime content
increases from 3% to 9%. Then, the coefficient ofconsolidation (cv) of soil specimens with addition oflime decreases as the lime content increases
compared to the untreated marine clay where
specimen with 3% lime content increased about 18.4%
from untreated marine clay at 7 curing period.
Compression index (cc) value signifies thecompressibility of a soil, cc value decreases as lime
content increases.

[6]
[7]

[8]

[9]

[10]

[11]

[12]

6.0 REFERENCES
[1]

[2]

[3]

[4]

[5]

S. Horpibulsuk, N. Yangsukkaseam, A.
Chinkulkijniwat, and Y. J. Du,“Compressibility and permeability of
Bangkok clay compared with kaolinite andbentonite,” Appl. Clay Sci., vol. 52, no. 1–2,
pp. 150–159, Apr. 2011.
T. Petry and D. Little, “Review ofstabilization of clays and expansive soils inpavements and lightly loaded structureshistory, practice, and future,” J. Mater. Civ.
Eng., no. December, pp. 447–460, 2002.
T. Chalermyanont, S. Arrykul, and N.
Charoenthaisong, “Potential use of lateritic
and marine clay soils as landfill liners toretain heavy metals.,” Waste Manag., vol. 29,
no. 1, pp. 117–27, Jan. 2009.
S. Basack and R. Purkayastha, “Engineering
properties of marine clays from the eastern
coast of India,” J. Eng. …, vol. 1, no. 6, pp.
109–114, 2009.
Z. A. Rahman and W. Z. W. Yaacob,“Geotechnical Characterisation of Marine
Clay As Potential Liner Material,” Sains, vol.
42, no. 8, pp. 1081–1089, 2013.

[13]

[14]

[15]

[16]

[17]

35

N. L. Association, “Lime Treated Soils Save
Time & Money,” Tech. Dig., 2005.
Sakr MA and Shahin MA, “Utilization ofLime for Stabilizing Soft Clay Soil of HighOrganic Content.” Geotechnical andGeological Engineering, 2009, vol. 27, pp.
105-113.
Koslanant S, Onitsuka K and Negami T,“Influence of salt additive in lime
stabilization on organic clay.” GeotechnicalEngineering, 2006, vol. 39, pp. 95-101.
Consoli, N.C., da Silva Lopes, Jr. L. andHeineck, K.S. (2009). “Key parameters forthe strength control of lime stabilized soils.”
Journal of Materials in Civil Engineering
21(5): 210-216.
Consoli, N.C., da Silva Lopes, Jr.L., Prietto,
P.D.M., Festugato, L. and Cruz, R.C. (2011).
“Variables Controlling Stiffness andStrength of Lime Stabilized Soils.” Journalof Geotechnical and Geoenvironmental
Engineering 137(6): 628-632.
Davidson, L.K., Demeril, T. and Handy, R.L.
(1965). “Soil pulverization and lime
migration in soil lime stabilization.” HRB
Record 92, Highway Research Board,
National Research Council, Washington,
D.C., pp: 103-126.
Choquette, M., Andre Bérubé, M. and Locat,
J. (1987). “Mineralogical and microtexturalchanges associated with lime stabilization ofmarine clays from Eastern Canada.”
Applied Clay Science 2(3): 215-232.
Rajasekaran, G. and Rao, N. (1997). “Themicrostructure of lime-stabilized marine
clay.” Ocean Engineering 24(9): 867-875.
Mohd Yunus, N.Z., Wanatowski, D. andStace, L.R. (2012). “Effect of humic acidand chloride salts on the behaviour of limetreated organic clay.” PhD thesis, Universityof Nottingham, United Kingdom.
Burland JB, “On the compressibility andshear strength of natural clays.
“Geotechnique, 1990, vol. 40, no. 3, pp.
329-378.
Kassim KA and Huey CS, “Consolidation
characteristics of lime stabilised soil.”
Journal of Civil Engineering, 2000, vol. 12,
no. 1, pp. 31-42.
Tremblay H, Locat L, and Leroueil S,“Effect of organic matter on thecompressibility of a soil treated with cement.”
International symposium on coastal
geotechnical engineering in Practice, Sep
20-22, Yokohama, 2000, pp. 733-738.

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SEISMIC BEHAVIOR OF SHORT GROUPED-PILESIN LIQUEFIABLE SANDY SOILS
Chung-Jung Lee1, Wen-Yi Hung1, Chen-Hui Tsai1, Yi-Chun Tu1,
Chin-Chen Huang2,Yuan-Chieh Wu2, Meng-Hsiu Hsieh2
1
2

Department of Civil Engineering, National Central University, Taiwan.
Institute of Nuclear Engery Reserch, Atomic Energy Council, Taiwan.

ABSTRACTA series of centrifuge shaking table tests was conducted to simulate the seismic responses of grouped-piles thatwas embedded in liquefiable sandy soils and subjected to earthquake loading. The grouped-piles connected with apile cap were used to support 4 sets of model dry storage spent fuel casks. Different test conditions including theelevations of pile cap, and the grouped-piles embedded in the dry and saturated sand beds with the different levelsof groundwater table are reported. Using pre-shaking the profile of shear wave velocity in the tested sand bed andthe natural frequencies of both the sand bed and the grouped-piles were determined. The lower shear wave
velocities and the lower natural frequencies were measured for the saturated sand bed, but no obvious differencein the natural frequency of the grouped-piles system with the pile cap embedded in the sand deposit were observed.
The grouped-piles with the pile cap exposed to the ground surface and embedded in the saturated sand bed havethe lowest natural frequency. The magnitudes of bending moment along pile depths would increase with theincreases of base shaking. The lowest bending moment were measured for the grouped–piles with the pile cap
embedded in the dry sand bed while the largest bending moments were observed for the grouped–piles with thepile cap embedded in the saturated sand bed and the groundwater table at the surface.
Keywords: Seismic Response, Grouped-Piles, Liquefaction, Shaking Table Test, Centrifuge Modelingslab that is founded with a grouped-piles foundation.
The seismic responses of the grouped-piles system
located at the liquefiable sites are critically concerned.
In the study a series of model grouped-piles (2×2)
centrifuge shaking table tests at an acceleration of 80
g was conducted to simulate seismic responses of agrouped-piles embedded in liquefiable sandy soil
subjected to different magnitudes of earthquake
loading.

INTRODUCTION
Dramatic failure of structures founded on pilefoundations after a strong earthquake has led many
researchers to investigating the behavior of groupedpiles supported foundations in liquefiable deposits [1;2]. The liquefaction-induced pile foundation failures
not only occurred in sloped grounds (lateral
spreading) but were also observed in level grounds.
The failure of pile foundation, resulting from that thebending moments or shear forces that are experienced
by the piles exceed the bending or shear carrying
capacity of the pile section, were often accompanied
by settlements and tilting of superstructures. The
damages rendered the supported-structures becoming
useless or costing expensive to rehabilitate after big
earthquakes. Therefore soil-structure interaction
effects must be properly considered in the groupedpiles design especially embedded in the liquefiable
sandy soils. Currently, piles in liquefiable soils aredesigned as beams to resist bending failure fromlateral loads due to the inertia of the structure and/or
slope movement (lateral spreading)[3].
Dry cask storage is an alternative method of
temporary storing spent fuels that have already beencooled in a spent fuel pool. There are various designsof spent fuel dry storage cask system. With somedesigns, the casks are placed vertically on a concrete

GEOTECHNICAL CENTRIFUGE MODELING
AND TESTING SETUP AND PROCEDURES
Testing Equipment
The experimental work presented here wasundertaken in the Centrifuge at the National Central
University (NCU), Taiwan. The NCU Centrifuge has
a nominal radius of 3 m and is equipped with a 1-D
servo-hydraulically controlled shaker integrated intoa swing basket. The shaker has a maximum nominal
shaking force of 53.4 kN, a maximum tabledisplacement of ±6.4 mm, and is operated at an
centrifugal acceleration of up to 80 g. The nominal
operating frequency range was 0–250 Hz. A laminarcontainer with inside dimensions of 711 mm x 356
mm x 353 mm was constructed from 38 light-weight
aluminum alloy rings arranged in a stack. Each ring36

GEOMATE- Brisbane, Nov. 19-21, 2014

was 8.9 mm in height and was separated from theadjacent rings by roller bearings that were speciallydesigned to permit translation in the longitudinal
direction with minimal frictional resistance. The
laminar container was designed for dry or saturated
soil models and permits the development of stresses
and strains associated with 1-D wave propagation [4].
A flexible 0.3 mm thick latex membrane bag wasused to retain the soil and the pore fluid within thelaminar container.

Sand Bed preparation and Testing Layout
A fine quartz sand (No. 306) was used to prepare
the uniform dense sand deposit. The characteristics ofthe quartz sand are summarized in Table 1. The fourgrouped-piles were first screwed at the bottom oflaminar container and then the quartz sand was
pluviated with a regular path into the container froma hopper at a constant falling height and at a constantflow rate for preparing fairly uniform sand deposits
having relative density of about 85%. Finally thesaturation process was conducted for the saturated
sand bed. In the case of saturation an acrylic plate wasused to tightly cover the container for the saturation
process of sand bed. Air was then simultaneously andcontinuously vacuumed out from both the inside andthe outside of container. At the same time a deionized, de-air water-metulos solution having aviscosity of 80 times the viscosity of water was
carefully dripped into the container to saturate thesand bed until the fluid level rose to thepredetermined elevations. One day was required tosaturate a sand bed.

Design and Fabrication of Grouped-Piles Model
Figure 1 is a typical layout of spent fuel dry
storage system. The dry storage casks are placed on aconcrete slab founded with a row of grouped-piles
which are embedded in a medium dense to dense sanddeposit and penetrated into the bed rock. Eachconcrete pile having a diameter of 1.8 m and
EI=12772754 kN/m2 are used to support a dry storage
cask by means of the concrete slab. In the study 4 setsof spent fuel cask rest on a simplified 4 grouped-piles
model (2× 𝟐𝟐) is used in the centrifuge modeling.
The grouped-piles model (2× 𝟐𝟐) as shown in
Figure 2 was fabricated using 4 copper tubes with a
19 mm outer diameter and a 17 mm internal diameter.
The length of pile was 160 mm and the embedment
depth of the model pile in the sand bed was 125 mm
both in model scale. Strain gauges were attachedexternally at nine positions on the pile shaft surface
for two of four piles to measure the bending moment
distributions along both the front pile and the backpile (MA and MB). These two model piles are named
as the bending piles. The surface of model pile shaft
was then resin coated for waterproofing. The coatedmodel piles (22.5 mm in diameter) are designed toreplicate a circular pile with a diameter of 1.8 m andhaving an embedment depth of 10 m when it wastested at an acceleration of 80 g. The ratio of pilelength and diameter (L/D) is around 5.5. The model
pile exhibited flexural rigidity (EI) of 10350668 kNm2 in prototype scale. Here E and I are the Young’s
modulus and the inertia moment of the model
instrumented pile, respectively. In addition the strain
gauges are also attached on the pile shafts of the othertwo piles to measure the axial forces along the pile
depths. These two piles are named as the axial piles.
All the instrumented piles (two bending pile and two
axial piles) were calibrated for establishing therelationships between the output voltages andbending moments (or axial forces) prior to the model
tests. Therefore, the bending moment (or axial force)
profiles on the front and back piles can be measured
during the tests. The total weight of four model dry
storage casks and the pile cap as shown in Figure 2
are 24.2 N in model scale. The height of gravity centerof dry storage casks and the pile cap is scaled fromthe prototype.

Spent fuel dry
storage cask
crane
Crane track
Concrete slab
Concrete Pile
Diameter = 1.8 m
2
EI=12772754 kN/m

Medium dense
sand deposit
1.8 m

Bed rock

Fig. 1 Layout of spent fuel dry storage system.

4 Dry storage casks

Grouped-piles

Fig. 2 Four model spent fuel storage casks rested on
the concrete founded with grouped piles
Table 1 Characteristics of fine quartz sand.
Gs

37

D 50
(mm)

D 10
(mm)

1
ρ max
(g/cm3)1
ρ min(g/cm3)

GEOMATE- Brisbane, Nov. 19-21, 2014

Quartz
sand
1

2.65

0.193

0.147

1.66

1.44
LDT24 30mm
150mm

The maximum and minimum densities of the sand were
measured in the dry state, according to the method (JSF T
161-1990) specified by the Japanese GeotechnicalSociety.

55mm

10mm

50mm(4.0m
)

10mm
55mm

10mm 10mm(0.8m)

50mm(4.0m)

Pile cap
A22
10mm(0.8m)

14mm

A12

14mm

40mm

Dry sand bed
Dr=85%

90mm(7.2m)

14mm

A8

A13

9
8
7
6
5

19mm
22.5mm

5
3

66mm
2

2

1

A16 1

30mm

A23

2mm

LDT24 30mm

55mm

10mm
55mm

10mm 10mm(0.8m)

A8

P1
4

A26

P15

40mm
50mm(4.0m)

Dr = 85%
Saturated sand
bed

P
6

50mm(4.0m)

Dr = 85%
Saturated sand bed

14mm

40mm
90mm(7.2m
)

14mm

A13

P18

40mm

130mm(10.4
m)

7mm
7mm
14mm

A23

P8

P1

A11

6
90mm(7.2m)

9
8
7
6
5
3

28mm

66mm

3
2

1

A16 1

Copper tube

A21

90mm(7.2m)

35mm

52.5mm

A16 1

P7

40mm

LVDT51

LVDT41

35mm

45mm

70mm

10mm
55mm

170mm
30mm
10mm
55mm
A24

55mm

Spent fuel 66.5mm 74mm
cask
Pile cap
3.5mm
2mm

A8

P6

P14

A6

10mm(0.8m)

A26

P15

90mm(7.2m)

A13

P18

7mm
7mm
7mm
14mm

9
8
7
6

14mm

4MA

4

3

3

14mm

5

19mm
22.5mmA11

90mm(7.2m)

A23

MB

2

2

1

A16 1

20mm

LVDT50256.5mm40mm
LVDT51

Coating

125mm

Copper tube

40mm

A21

P7

LVDT4190mm(7.2m)

30mm
2mm

P8

12.5mmP17

A1810mm(0.8m)

5

66mm

28mm

P16

9
8
7
6

70mm

35mm

45mm

511mm

(d) Gtest4
255.5mm
LDT24 30mm

10mm
55mm

150mm
LVDT45

30mm
170mm
10mm
55mm
A24

55mm
LDT26

Spent 66.5mm 74mm
fuel cask
35mm
A15
10mm

2mm

10mm(0.8m)

A8

P14

50mm(4.0m)

Dr = 85%
Saturated sand bed

P6A610mm(0.8m)

40mm
A26

P15

A13

P18

40mm
90mm(7.2m)

125mm(10m)

7mm
7mm
7mm
14mm

9
8
7
6

14mm

4MA

4

3

3

14mm

5

A11

A23

P8

19mm
22.5mm

3.5mm
A18

12.5mmP17

256.5mm40mm

5MB Coating

2

2

1

A16 1

LVDT50125mm

Copper tube
A21

40mm

P7

LVDT5190mm(7.2m)

70mm

35mm

45mm

20mm

10mm(0.8m)

30mm
2mm

Pile cap

9
8
7
6

66mm

28mm

P16

90mm(7.2m)

35mm

45mm

LVDT41
A25

200mm

511mm
Accelerometer

LVDT

PPT

LDT

(e) Gtest5
Fig. 3 Test setup and instrumentations: (a) Gtest1; (b)Gtest2; (c) Gtest3; (d) Gtest4; (e) Gtest5; the model
dimensions are in centimeter and prototype
dimensions (in parentheses) are in meters.
Table 2 Testing condition of grouped-piles

LVDT51Test
No.
Gtest1

LVDT4132.5mm LVDT50

P
7

125mm
40mm

LVDT51

LVDT4145mm

Gtest4

70mm

A25

200mm

1

A21

90mm(7.2m)

LVDT50

A25

30mm
2mm

2

200mm

Gtest3256.5mm40mm

MB Coating

42

Copper
tube

3

45mm

255.5mm

5

4 MA

2mm

40mm

125mm(10m)

45mm

12.5mm
A18 P1
E1510mm(0.8m)
7

98

19mm 76
22.5mm

P8

35mm

A15

A6
2mm
E13 7mm

66mm

2

125mm

A15

Spent 66.5mm 74mm
fuel cask
Pile
3.5mm
cap

10mm(0.8m)

MB Coating
4

30mm

40mm

A24
LDT26

3

32.5mm256.5mm40mm

5

511mm

10mm 10mm(0.8m)

Gtest2

35mm

A23

9
8

19mm 76
22.5mm

4 MA

LDT26

70mm

30mm
170mm
10mm
55mm

)

5

35mm

511mm

LVDT45P1
A11 28mm
690mm(7.2m

P18

9
8
7
6

255.5mm(a) Gtest1
150mm

A13

30mm
LDT24

A25

200mm

14mm

LVDT45Screw into the base
35mm

52.5mm90mm(7.2m)

2mm

14mm

40mm

130mm(10.4m
)

A6

150mm

32.5mm LVDT50

256.5mm 40mm
Pile after coating
φ = 19 mm (1.8
125mm
m)
A26
40mm
90mm(7.2m)
Copper tube

3P610mm(0.8m E13 7mm
7mm
)
7mm
14mm

(c) Gtest3

12.5mm10mm(0.8m)

Strain gauge

MB
4

P1
5

3.5mm
A18

9
8
7
6

MA
4

28mm

90mm(7.2m)

40mm
130mm(10.4m)

2mm
7mm
7mm
7mm

Spent
66.5mm 74mm
fuel cask
Pile
3.5mm
A15 cap
12.5mm
A18 P1
E15 10mm(0.8m
7
)

A25

Spent fuel dry
storage cask 66.5mm 74mm

A6

A11

40mm

P1
4

200mm

A24
LDT26

35mm

A24
LDT26

52.5mm

30mm
170mm
10mm
55mm

55mm

A1

A26

40mm

Dr = 85%
Saturatedsand bed

255.5mm
LDT24 30mm
LVDT4510mm(0.8m)

40mm

255.5mm

30mm
170mm
10mm
55mm

35mm

Five grouped-piles centrifuge model tests wereconducted. Figures 3(a), 3(b), 3(c), 3(d) and 3(e)show the soil profiles and the instrumentation layouts
used in the centrifuge modeling. Table 2 lists thetesting conditions. The total depth of the sand bed forboth the grouped-piles and the pile cap embedded in
the sand bed is 14.6 m and that for the pile cap
outcropping on the ground surface is 13.6 m both inprototypes. Two accelerometers were attached at twoelevations on the spent fuel cask to measure theseismic responses. Each sand bed was equipped with
3 rows of vertically spaced accelerometers (A#) torecord the propagation of shear waves from the baseto the ground surface, as shown in Figure 3. At theelevations near those of the accelerometers, eight
pore-water pressure transducers (P#) were installed
for the saturated sand beds. A linear variable
differential transformers (LVDTs) were installed on
the ground surface to measure the time histories of
surface settlement. The transducers were installed atsimilar locations in each test. Two laser displacementtransducers (LDTs) were used to measure thehorizontal displacements on the spent fuel casks.
Three LVDTs were attached on the side wall oflaminar container to measure the lateral wall
displacements. All measurement points were locatedaway from the boundaries of the laminar container tominimize boundary effects [4].
150mm

10mm
55mm

LVDT45511mm(b) Gtest2

Gtest538

Test conditions
Both the grouped-piles and the pile cap
embedded in the dry sand bed
Both the grouped-piles and the pile cap
embedded in the saturated sand bed having
groundwater table on the ground surface
Both the grouped-piles and the pile cap
embedded in the sand bed having the
groundwater table 4 m below the groundsurface
The grouped-piles embedded in the sand bed
having the groundwater table 4 m below theground surface but the pile cap outcroppingon the top of ground surface
The grouped-piles embedded in the sand bed
having the groundwater table on the groundsurface but the pile cap outcropping on the
top of ground surface

GEOMATE- Brisbane, Nov. 19-21, 2014

where ΔS and Δt are the distance between adjacentaccelerometers and the registered time difference
between the first peaks of the accelerometer pairs,
respectively. Figure 5 displays the typical test resultof shear wave velocity profile for Gtest1. Figure 6
displays the amplification factors of the acceleration
measured at various depths and at two different
elevations on the spent fuel cask as shown in Figure3(a). The peaks in the curves represent the nature
frequencies of the sand bed and the entire soil-pilecasks system. Table 4 lists the measured average
shear wave velocities and the measured nature
frequencies of sand deposit and grouped-piles
system. The dry sand bed has the highest nature
frequency (Gtest1), the saturated sand bed has thelowest nature frequency. There are two nature
frequencies measured from the grouped-piles, as
listed in Table 4 and shown in Figure 6(b). The firstone is the nature frequency of sand bed in which thegrouped-piles are embedded and the second one is thenature frequency of grouped-piles system. The
grouped-piles with pile cap embedded in the sanddeposit have the highest natural frequency (4.1 Hz for
Gtest1). By contrast the grouped-piles embedded in
the sand bed having the ground water table on the
ground surface and the pile cap outcropping on the
top of ground surface have the lowest nature
frequency (3.1 Hz for Gtest5).

Figure 4 shows a test package resting on the
NCU shaker is ready for testing. Comprehensive
instrumentation and detailed measurements at various
elevations and different positions are necessary to
determine the seismic responses of the grouped-piles
and the associated excess pore-water pressure
generation and dissipation in the sand deposits during
shaking. After completing the centrifuge flight safety
checks, the centrifuge was accelerated at anacceleration of 10 g per step until it reached 80 g. The
model was maintained at each g-level for 5 min. toensure that the sand bed reached full consolidation ateach overburden stress. Finally the model was
subjected to different base shaking events withvarious amplitudes of base acceleration at anacceleration of 80 g. The time histories ofacceleration, the pore-water pressure at various
elevations, the bending moments and the axial forceson the piles, and surface settlement were recorded
simultaneously. The measurements in the following
sections are presented in prototype units unlessspecifically noted otherwise.
Table 3 lists the typical shaking events for thefive tests (Gtest1 – Gtest5) in the study. The S1 event
is a pre-shaking technique for measuring the V s
profile of sand deposits and identifying the natural
frequencies of sand bed and soil structure system at
the acceleration of 80 g. The pre-shaking technique isa non-destructive test. It uses a shaker as a wave
generation source and a vertical array ofaccelerometers embedded in the sand bed and theaccelerometers attached to the pile head as receivers[5]. After the pre-shaking events each model was
subjected to multiple shaking events with amplitudes
of base acceleration from small to large.
TEST RESULTS AND INTERPRETATIONS
Fundamental Frequencies of Sand Deposit andGrouped -Piles
The pre-shaking method (S1 Event as listed inTable 3) was conducted to measure the profile ofshear wave velocity along the depths in terms of thevertical accelerometer array as shown in Figure 3.
The shaker fired one cycle of a low, controlled
amplitude sinusoidal wave (approximately 0.01 g in
amplitude and 1 Hz, 2 Hz, and 3 Hz in frequency, bothon the prototype scale) to provide a vibration source.
A higher sampling rate of 30 000 samples/s was used
to collect the acceleration time histories from theaccelerometers those which were embedded in thesand bed and were attached on the spent fuel cask.
Therefore the average shear wave velocity, V s , of thesand deposit between the accelerometer pairs could
be calculated using the following equation:
𝑽𝑽𝒔𝒔 = ∆𝑺𝑺/∆𝒕𝒕

Fig. 4 Test package resting on the NCU shaker
Table 3 Shaking events in the study
Test
events
S1-1HzS1-2HzS1-3Hz
S2
S3
S4
S5
S6

(1)

39

a max(base) /freq./No. of cycleg / Hz / cycles
0.0083g / 1Hz / 1
0.0091g / 2Hz / 1
0.0087g / 3Hz / 1
0.0118g / 1Hz / 15
0.0373g / 1Hz / 15
0.0858g / 1Hz / 15
0.1491g / 1Hz / 15
0.2112g / 1Hz / 15

Dr(%)

88.6
86.6
86.7
87.3
87.9
88.0

GEOMATE- Brisbane, Nov. 19-21, 2014

Shear wave velocity (m/sec)
0

0

50

100

150

200

250

Comparison of Time Histories of Acceleration andof Excess Pore Water Pressure at Different Depths
Figure 7(a), 7(b) and Figure 8(a), 8(b) show thetime histories of acceleration of Gtest1 (S5) and
Gtest5 (S5), those which were measured at thecorresponding depths in the sand bed and at the spent
fuel cask, respectively. The high frequency and highamplitude spikes in the histories of acceleration asshown in Figure 8(a) are observed. Figure 9 shows themeasured time histories of excess pore water ratio of
Gtest5 (S5) measured at different depths. Both theobserved results show the top 7 m depth of the sanddeposit becoming liquefying during big base shaking(the base acceleration ≅ 0.3 g).
After comparing the acceleration time histories
the soil responses of these two models are quite
different although nearly the same amplitude of input
base acceleration. A single parameter that includes
the effects of the amplitude and frequency content of
the acceleration time history is the root mean squareacceleration (RMS acceleration), defined as:

300

Gtest1 S1
2

Depth (m)

4

6

8

10

Amplification factor

Fig. 5 Measured shear wave velocity profile of sanddeposit for Gtest1
30
25

A11/A25
A12/A25
A13/A25
A23/A25

Gtest1 (S1)- 2 Hz

20
2.9 Hz

15
10
5
0
0

1

3

2

4

5

6

7

8

9

𝒂𝒂𝒓𝒓𝒓𝒓𝒓𝒓 = �

10Frequency (Hz)Amplification factor(a)A24/A25
A22/A25(A24-A22)/A25

Gtest1 (S1)- 2 Hz80
2.9 Hz60

4.1 Hz

40
20
0
0

1

2

3

4

5

6

7

8

9

10

Frequency (Hz)(b)
Fig. 6 Amplification factor vs. frequency for Gtest1:(a) measured at the sand bed; (b) measured atgrouped-piles system
Table 4 Average shear wave velocities and natural
frequencies of sand deposit and grouped-piles
system
Test
No.

Vs 1
(m/sec)fn 2(Hz)

1st f n 3
(Hz)

2nd f n 4(Hz)

Gtest1
Gtest2
Gtest3
Gtest4
Gtest5

225
170
170
170
160

2.9
2.4
2.9
2.4
2.1

2.9
2.4
2.9
2.4
2.1

4.1
4.1
3.97
3.6
3.1

(2)

where T d is the duration of the acceleration and dt isthe time interval of the acceleration time history. The
larger the RMS acceleration value the higher theenergy input to the sand deposit. An acceleration
amplification ratio is defined as the ratio of the RMS
acceleration value measured at different depths to thebase input RMS acceleration value.
Figure 10 presents the RMS acceleration
amplification ratios, those which were calculated
from the accelerometer array embedded in the sanddeposit and on the fuel spent cask; provide acomparison of amplification ratio profiles along thedepths and on the spent fuel cask for Gtest1 to Gtest5
those which were subjected to different levels of baseshaking. There was considerable amplifying effect on
the acceleration measured on the top soil following
shear waves propagating from the base to the surface
on Gtest1 - Gtest4, but no amplification of groundresponse on the top 7 m of the sand deposit (Gtest5)
were observed because occurrence of soil liquefying
blocked the shear waves upward propagating.
However the calculated amplification ratios on the
spent fuel cask of Gtest5 had the largest magnitude.
The spent fuel cask rested on the grouped-piles witha pile cap outcropping on the ground surface and thatwas embedded in the liquefied sand would experience
the highest acceleration. The pile cap outcropping on
the ground surface would greatly reduce the soil
confinement; as a result, the spent fuel cask
experienced the largest vibrations as shown in Figure10(e).

120
100

𝟏𝟏 𝑻𝑻𝒅𝒅∫ [𝒂𝒂(𝒕𝒕)]𝟐𝟐 𝒅𝒅𝒅𝒅
𝑻𝑻𝒅𝒅 𝟎𝟎

1

Measured average shear wave velocity of sanddeposit;2
Measured natural frequency of sand deposit;
3
Measured first natural frequency of grouped-piles
system;4
Measured 2nd natural frequency of grouped-pilesystem40

5

Acceleration (g)

0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

20

25

5

0.0
0

10

15

20

25
A13 (7.2 m)

20

30

40

50

60

70

80

90 100 110 120 130 140 150

1.0
P15 (4.0m)
0.5
0.0
0

5

10

15

20

25
A23 (10.4 m)

10

20

30

40

50

60

70

80

90 100 110 120 130 140 150

1.0

P18 (7.2m)

0.5
0.0
0

10

20

30

40

50

60

70

80

90 100 110 120 130 140 150

1.5

5

10

15

20

25
A25 (Base)P8 (10.4m)

1.0
0.5
0.0
0

10

20

30

40

50

60

70

80

90 100 110 120 130 140 150

Elapsed time (sec)

0

5

10

15

20

25

Fig. 9 Time histories of ratio of excess pore waterpressure for Gtest5 (S5)Elapsed time (sec)(a)

Amplification ratio

0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

0.0

Gtest1 (S5)

0.5

1.0

1.5

2.0

Amplification ratio

2.5

3.0

0.0

-10

A24 (Top)A22 (Bottom)
10

15

20

-5

2.0

2.5

0
Depth (m)

0

cap

5

S2
S3
S4
S5
S6

10

15

cap

5

10
S2
S4
S5
S6

15

1.0

Gtest5 (S6)20

A8 (0.8 m)

0.5

20

0.0

(a)

-0.5

0.4

(b)

Amplification ratio
0

5

10

15

20

3.0

-5

-1.0
25

0.0

30

0.5

1.0

1.5

2.0

Amplification ratio
2.5

3.0

0.5

0.2

Gtest3

0.0

1.0

1.5

2.0

2.5

3.0

-10

-10

A12(4.0 m)

0.0

Gtest4
-5

-5

-0.2
-0.4
5

10

15

20

25

0

30

Depth (m)0.4
A13(7.2 m)
0.2
0.0
-0.2

5

5

10

15

20

25

S2
S3
S4
S5
S6
S7

30

15

0.4
A23(10.4 m)
0.2
0.0

5

10

10

-0.4
0

cap

0

cap

Depth (m)0Acceleration (g)

1.5

25

(b)
Fig. 7 Time histories of acceleration for Gtest1: (a)measured at different depths in the sand deposit; (b)measured at two elevations on the spent fuel cask

Acceleration (g)1.0

Gtest2Depth (m)5

Elapsed time (sec)

S3
S4
S5
S6
S7

15

20

20

-0.2

(c)

-0.4
0

Acceleration (g)

0.5

-10

Gtest10

Acceleration (g)

10

1.5

0

Acceleration (g)Gtest5 (S5)

0.5

1.5

0

Acceleration (g)P17 (0.8m)
1.0

Excess pore waterpressure ratio, ru

Acceleration (g)Acceleration (g)

0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

15

1.5

A12 (4.0 m)

0
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

10

Excess pore waterpressure ratio, ru

0

2.0

A11 (0.8 m)

Excess pore waterpressure ratio, ru

0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

Gtest1 (S5)

Excess pore waterpressure ratio, ru

Acceleration (g)

0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3

Acceleration (g)GEOMATE- Brisbane, Nov. 19-21, 2014

5

10

15

20

25

30

(d)
Amplification ratio

0.4
A25 (Base)

0.0

0.2

0.5

1.0

1.5

2.0

2.5

3.0

-10

0.0

Gtest5

-0.2

-5

-0.4
0

5

10

15

20

25

30

Elapsed time (sec)0Depth (m)Acceleration (g)

(a)
0.4

Gtest5 (S6)

0.2

cap

5

10

0.0
A24 (Top)A15 (Bottom)

-0.2
-0.4

15
0

5

10

15

20

25

30

Elapsed time (sec)

S2
S3
S4
S5
S6
S7

20

(b)
Fig. 8 Time histories of acceleration for Gtest5: (a)measured at different depths in the sand deposit; (b)measured at two elevations on the spent fuel cask(e )Fig. 10 Profiles of RMS acceleration amplification
ratios along depths and on the spent fuel cask: (a)Gtest1; (b) Gtest2; (c) Gtest3; (d) Gtest4; (e) Gtest5

41

-5000-10000
5

10

15

20

25

10000

MA7 (2.56 m)

5000
0
-5000
-10000
10

15

20

2

5

10

15

20

25

10000

MA5 (4.24 m)

5000
0
-5000
-10000
0

5

10

15

20

25

10000

MA4 (5.36 m)

5000
0
-5000
-10000
5

10

15

20

MA3 (6.48 m)

0-5000-10000
0

5

10

15

20

MA2 (8.72 m)

5000
0
-5000
-10000
0

5

10

15

20

25

10000

MA1 (10.56 m)

5000
0
-5000
-10000
0

5

10

15

Elapsed time (sec)

20

25

25

20

25

30

MA5(4.24m)

malfunction
0

5

10

15

20

25

30

MA4(5.36m)

5

10

15

20

25

10

15

20

25

10

15

20

25

10

15
20
Elapsed time (sec)

25

8000
6000
4000
2000
0
-2000
-4000
-6000
-8000
8000
6000
4000
2000
0
-2000
-4000
-6000
-8000
8000
6000
4000
2000
0
-2000
-4000
-6000
-8000

15

20

25

30

5

10

15

20

25

30

malfunction
5

10

15

20

25

30

MB6(3.12m)

0

10

5

15

20

25

30

MB5(4.24m)

0

5

10

15

20

30

25

MB4(5.36m)

5

10

15

20

25

30

MB3(6.48m)

0

5

10

15

20

25

30

MB2(8.72m)

0

5

10

15

20

25

30

MB1(10.56m)

0

30

10

MB7(2.56m)

030

MA1(10.56m)

5

8000
6000
4000
2000
0
-2000
-4000
-6000
-8000

30

MA2(8.72m)

5

8000
6000
4000
2000
0
-2000
-4000
-6000
-8000

5

MB8(2.0m)

030

MA3(6.48m)

5

Bending moment (kN-m)

15

Bending moment (kN-m)

10

Bending moment (kN-m)

5

8000
6000
4000
2000
0
-2000
-4000
-6000
-8000

30

MA6(3.12m)

0Bending moment (kN-m)

25

Bending moment (kN-m)

20

Bending moment (kN-m)

15

0

0

30

malfunction
10

8000
6000
4000
2000
0
-2000
-4000
-6000
-8000

Bending moment (kN-m)

25

Bending moment (kN-m)

20

Bending moment (kN-m)

Bending moment (kN-m)
Bending moment (kN-m)
Bending moment (kN-m)
Bending moment (kN-m)
Bending moment (kN-m)
Bending moment (kN-m)
Bending moment (kN-m)

0

5

10

15

20

25

30

Elapsed time (sec)(b)

Gtest1

25000

Base input accleration
Acceleration at A24
20000

15000

10000

5000

0
0.0
5

10

15

20

0.1

0.2

0.4

0.5

0.6

Acceleration (g)MB6( 3.12 m)

5000

0.3

25

10000

(a)

0
-5000
-10000
5

10

15

20

25

30000

10000

MB5 (4.24 m)
5000
0
-5000
-10000
5

10

15

20

25

10000

MB4 (5.36 m)
5000
0
-5000
-10000
0

5

10

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MB3 (6.48 m)

5000
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5

-100000

Bending moment (kN-m)

0
10000

15

MB7 (2.56 m)

0
Bending moment (kN-m)

0-5000-10000

10

10000

0

Bending moment (kN-m)

MA6( 3.12 m)

5000

-5000
-10000

25

10000

25

MB8 (2.0 m)

5

8000
6000
4000
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30

30000

0

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25

MB9(1.4m)

Gtest5 (S5)Fig, 12 Time histories of bending moment along thedepths for Gtest5 (S5): (a) A pile; (b) B-pile

10000

0

Pile moment (kN/m )

5

20

8000
6000
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-4000
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(a)

-5000

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MA7(2.56m)

0-10000105

0

MB9 (1.4 m)

5

8000
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10

MA8(2.0m)

0

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5000

malfunction00Maximum bending moment at MA9 (kN-m)

25

MA8 (2.0 m)

8000
6000
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-4000
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-8000

MA9(1.4m)

Gtest5 (S5)

0

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Gtest1 (S5)

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Maximum bending moment at MA9 (kN-m)

20

Bending moment (kN-m)

Bending moment (kN-m)
Bending moment (kN-m)
Bending moment (kN-m)
Bending moment (kN-m)

15

0

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Bending moment (kN-m)

10

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Bending moment (kN-m)

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Bending moment (kN-m)

Bending moment (kN-m)-5000-10000

Bending moment (kN-m)

00

Bending moment (kN-m)

MA9 (1.4 m)

Gtest1 (S5)5000

Bending moment (kN-m)

10000

Bending moment (kN-m)

Bending moment (kN-m)

Figures 11(a) and (b) and Figures 12(a) and 12(b)show the time histories of bending moment measured
from the pile head to the pile tip for Gtest1 (S5) and
Gtest5 (S5), respectively. The grouped-piles and thepile cap both which were embedded in dry sanddeposit (Gtest1) experienced the less magnitude ofbending moments. Furthermore only top parts of piles(around 3.12 m in depth) experienced the bending
moments. By contrast the grouped-piles embedded in
the saturated sand bed and the pile cap outcropped to
the ground surface experienced the largest bending
moments. Nearly all the depths of pile shaft
experienced the larger bending moment (Gtest5)
compared to Figure 11. In addition the lower parts ofpile also experienced the bending moments thatdifferent from the measured results of Gtest1. These
resulted from the facts that the saturated sand becameliquefying in the top of sand deposit and greatly
losing the surrounding confinements to the piles if thecap of the grouped-piles exposed on the groundsurface. Figures 13(a) – 13(d) display the relations of
the measured maximum bending moment on the pileat MA9 (measured point is just below the pile cap)and the base acceleration or the acceleration
measured on spent fuel cask for Gtest1 – Gtest5. The
grouped-piles would experience the larger maximum
bending moments on the pile in the case of exposing
the pile cap on the ground surface than the case of thepile cap embedded in the sand deposit.

15000
10000
5000
0
-5000
-10000-15000

Bending moment (kN-m)

Time Histories of Bending Moment along Depths
on the Grouped-Piles

Bending moment (kN-m)

GEOMATE- Brisbane, Nov. 19-21, 2014

5

10

15

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MB2 (8.72 m)

5000
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MB1 (10.56 m)

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Gtest2

25000

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Base input accleration
Acceleration at A24
5000

0

0

0.0

-5000

0.1

0.2

0.3

-10000051015
Elapsed time (sec)20

Acceleration (g)

25

(a)
(b)
Fig. 11 Time histories of bending moment along thedepths for Gtest1 (S5): (a) A pile; (b) B pile.

(b)

42

0.4

0.5

0.6

GEOMATE- Brisbane, Nov. 19-21, 2014grouped-piles with a pile cap outcropping on the
ground surface and that was embedded in theliquefied sand would experience the highest
acceleration.
The pile cap outcropping on the ground surface
would greatly reduce the soil confinement; as a result,the spent fuel cask experienced the largest vibrations.
The magnitudes of bending moment along the pile
depths would increase with the increases of the baseshaking. The lowest bending moments were
measured for the grouped–piles with the pile cap
embedded in the dry sand bed while the largest
bending moments were evidenced for the grouped–piles with the pile cap embedded in the saturated sandbed and the groundwater table located at the surface.

Maximum bending moment at MA9 (kN-m)

30000

Gtest3

25000

20000

15000

10000
Base input accleration
Acceleration at A24
5000

0
0.0

0.1

0.2

0.3

0.4

0.5

0.6

Acceleration (g)(c)
Maximum bending moment at MA9 (kN-m)

30000

ACKNOWLEDGEMENTS
Gtest525000

The authors would like to express their gratitude
for the financial supports (NL1020467) from theInstitute of Nuclear Energy Research (INER), Atomic
Energy Council, Taiwan, ROC and the National
Science Council (NSC 100-2221-E-008-099-MY3),
Taiwan, ROC. Without their financial supports, thestudy would not become possible.

20000

15000

10000
Base input accleration
Acceleration at A24
5000

REFERENCES

0
0.0

0.1

0.2

0.3

0.4

0.5

0.6

Acceleration (g)[1] Tokimatsu, K., Oh-oka, H., Satake, K., Shamoto,Y., and Asaka, Y.“Effects of lateral groundmovements on failure patterns of piles in the
1995
Hyogoken-Nambu
earthquake,”
Geotechnical earthquake earthquake engineeringand soil dynamics III, Vol. 2, 1998, 1175-1186.
[2] Rollins, K.M., Gerber, T.M., Dusty, L.J., &Ashford, S.A. “Lateral resistance of a full-scale
pile group in liquefiable soils”, Journal of
Geotechnical and Geoenviromental Engineering,
ASCE, Vol.131, No.1, 2005, pp.404-414.
[3] Yao, S., Kobayashi, K., Yoshida, N., andMatsuo, H., “Interactive Behavior of Soil-PileSuperstructure System in Transient State to
Liquefaction by means of Large Shake Table
Tests,” Soil Dynamics and Earthquake
Engineering, 24,2004, pp.397-409.
[4] Lee CJ, Wei YC, and Kou YC. “Boundary
Effects of a Laminar Container in Centrifuge
Shaking Table Tests”, Soil Dynamics andEarthquake Engineering, Vol. 34, No.1, 2012,
pp. 37-51.
[5] Lee CJ, Hung WY, Tsai CH, Chen T, Tu YC, and
Huang
CH.
“Shear
Wave
Velocity
Measurements
andsoil-pile
SystemIdentifications in Dynamic centrifuge tests,”
Bulletin of Earthquake Engineering, Vol. 12,
No.2, 2014, pp.717-734.

(d)Fig. 13 Maximum bending moment measured at MA9
vs. base input acceleration and acceleration at spent
fuel cask (A24): (a) Gtest1; (b) Gtest2; (c) Gtest3; (d)Gtest5
CONCLUSION
A series of centrifuge shaking table tests was
conducted to simulate the seismic responses of shortgrouped-piles that was embedded in liquefiable sandy
soils and subjected to earthquake loading at anacceleration of 80 g. The grouped-piles connectedwith a pile cap were used to support 4 sets of model
dry storage spent fuel casks. Different test conditions
including the elevations of pile cap, and the grouped
piles embedded in the dry and saturated sand beds
with the different levels of groundwater table arereported in the study. Using pre-shaking techniquethe profile of shear wave velocity in the tested sandbed and the natural frequencies of both the sand bed
andthegrouped-piles
weredetermined
simultaneously. The lower shear wave velocities andthe lower natural frequencies were measured for thesaturated sand bed, but no obvious difference in thenatural frequency of the grouped-piles system withthe pile cap embedded in the sand deposit wereobserved. The grouped-piles with the pile cap thosewhich were exposed to the ground surface andembedded in the saturated sand bed have the lowest
natural frequency. The spent fuel cask rested on the43

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

CHALLENGES IN ASSESSING THE INSTALLATION EFFECTS OF
CONTROLLED MODULUS COLUMNS ON BEHAVIOR OF
SURROUNDING SOILS

1,2,3

Huu Hung Nguyen1, Behzad Fatahi2 and Hadi Khabbaz3
Centre for Built Infrastructure Research, University of Technology Sydney (UTS), NSW, Australia

ABSTRACT
Ground improvement technique using controlled modulus columns (CMC) has become increasingly popular
in recent years. A rotary displacement auger is screwed and pushed into the ground during installation, to createa vertical cylindrical cavity before concrete is injected to form a CMC. This process causes disturbance of thesurrounding soils and results in lateral displacement. In certain circumstances, such displacement may cause
damage to freshly grouted neighbouring columns or nearby structures.
This paper integrates the existing methods in assessing the lateral displacement of the surrounding soils due
to CMC installation. Analytical, numerical and physical modelling techniques are discussed. The study aims toprovide recommendations on novel techniques as well as important parameters for simulating CMC installation
process and assessing the effect of this process on nearby freshly grouted CMCs and bridge piles.
Keywords: Ground Improvement, Controlled Modulus Column, Horizontal Displacement, Cavity Expansion

Based on the size of auger and the methods ofpiling, CMC can be considered as "large
displacement piles", which may "cause adisplacement such that significant stresses are
induced in the surrounding soils, which may
increase the load capacity of the pile and cause
displacement of the surrounding soils" (AS21592009 – Piling – Design and Installation).

INTRODUCTION
The use of controlled modulus columns (CMC)
ground improvement technique has become amethod of choice for projects with tight construction
schedule or concerns related to contaminated ground.
The technique uses a rotary displacement auger witha diameter of up to 500mm to create a hole, followedby concrete injection through the hollow stem while
the auger is withdrawn (Fig. 1).

Fig. 2 CMC drill bit (courtesy of Menard-Bachy)
The displacement effects become more apparent
in a number of circumstances, e.g. design of closely
spaced columns in order to reduce differential
settlement at the surface of the embankment. As aresult, the installation-induced displacement at a newcolumn could cause damage to freshly grouted
surrounding columns. If installation is carried out
near a bridge abutment, the displacement may cause
lateral movement and impose additional load on thebridge piles. Such effects can be a major concern for

Fig. 1 CMC installation process by Menard [1]The drill bit comprises the lower partial flightauger segment, the middle auger segment weldedwith helically wound blades and the upper portion(Fig. 2). The soils carried upward away from the tipby the auger flights are pushed away laterally by theblades. Therefore, the technique has the features ofboth screwed and jacked-in piling methods.
44

GEOMATE- Brisbane, Nov. 19-21, 2014vibratory methods e.g. stone columns or driven piles.
In contrast to jacked-in and driven piles, action of
CMC auger rotation has large effects on the
resulting radial stress changes [7]. Pucker and Grabe[8] found that the higher ratio of the auger rotation
speed over the vertical penetration rate, the larger
lateral displacement occurs.
In addition, installation induced displacement isquite distinct at different portions of the CMC
column. Ground heave normally occurs near the
ground surface, to depths ranging fromapproximately 2.5m to 4.0m [9]-[10]. In the middle
region of the column, the installation results in aremarkable increase in soil density and stress level.
Near CMC column base, the stress increase isinsignificant [10]. In contrast, the base is the mostinfluenced portion for jacked and driven piles [10].

piling contractors and geotechnical engineers [2-4].
Plomteux et al. [2] reported a case study where the
CMC column spacing of 1m was designed near thebridge abutment piles, which posed a risk that lateraldisplacement caused by installation could damage
the surrounding freshly grouted columns. The
construction method was modified with CMCs
installed in two different interleave passes, each with
1.4m x 1.4m grids (Fig. 3).

Fig. 3 Modification of CMC installation layout [2]Installation-induced Changes in Soil State

Similar strategy was adopted as in [3], where
installation was commenced at the existingembankment and then working away from theexisting embankment and piles. Although reported
results from these modified installation patterns
were positive, there is no solid justification for those
selected patterns and how efficient they were incomparison to other possible installation patterns. To
date the magnitude of such installation induced
displacement remains unclear and, hence, requires
further investigation. It is important to emphasisethat properties of the CMC/soil interface play asignificant role in performance of infrastructure built
above the CMC improved ground [5, 6].
This paper highlights the challenges associatedwith the existing numerical, analytical and physicalmodelling methods in assessing the lateraldisplacement of the surrounding soils due to pile andcolumn installation, and possibility of applying thesemethods to CMC. Recommendations for the needed
improvement in predicting lateral displacement andsimulation of the CMC installation are provided.

Most current investigations were carried out forsand [7, 8]. During installation sand behaves underfully drained conditions since the excess porepressure dissipates quickly. As the auger reaches theelevation of a soil element located in the vicinity ofthe soil/column interface, the total and effective
stresses increases. However, as the auger passes thatsoil element, the soil within 1 diameter (1D) fromthe pile centre is loosened up [8] because of theslight change in cross section, from the displacement
body towards the drill rod. Outside this thin zone,
the soil densified significantly within a distance of
2D. Densified zone ranges from 6D for dense sandto 8D for loose sand. Long term effects in sand areconsidered as creep-induced ageing phenomenon[11], which has not been thoroughly investigated.
For saturated clayey soils, the behaviour during
installation is often assumed to be undrained due torapid auger penetration. The soils closer to thecolumn fail in shear due to large deformation causedby the installation. Excess pore pressure is generated,which will initially reduce the radial effective stress.
This failure zone is often referred as “plastic zone”,
extending to a radius R = r 0 [G/c u ]1/2, where r 0 is thepile radius, c u is the undrained shear strength and G
is the soil shear modulus [12]. Outside the plastic
zone is “elastic zone” where excess pore waterpressure is assumed zero. The clay behaviour also
relates to over-consolidation ratio. For normallyconsolidated clay, there is an increase in both total
stress and excess pore pressure Δu, but a decrease ineffective stress [13]. For over-consolidated clay the
total and effective stress increase everywhere but Δu,after increasing within a narrow zone near the pilewall, becomes negative in the next surrounding zone[13]. It should be noted that for a structured clayeysoil due to increase in the mean effective stress aswell as deviatoric stress, cementation degradation
may occur influencing the deformation of the ground

INSTALLATION EFFECTS
The first phase of installation process involves
formation of a cavity resulting from the auger
penetration together with simultaneous rotation in aclockwise direction. Soil cuttings at the auger tip are
carried upwards between auger flights, towards theauger segments with helically wounded blades,
where the soils undergo further destructuration andare displaced laterally. The surrounding soils
especially sands are brought into passive state ofstress during installation. Once desired depth isreached, concrete is injected through the hollow
stem with a moderate pressure, while the auger iswithdrawn.
The CMC installation is quasi-static, similar to
slowly-jacked piles, but as opposed to “dynamic”

45

GEOMATE- Brisbane, Nov. 19-21, 2014

immediately or long time after the installation [14].
Immediately after installation, the peak excess
pore pressure falls off rather quickly [12]. Excess
pore pressure decays during consolidation inducing
elastic visco plastic deformation together with soil
strength gain [15, 16]. At the end of consolidation,
radial effective stresses around the column is greaterthan the in-situ horizontal effective stresses in theundisturbed ground with decreasing magnitudes withincreasing distance from the pile centre within azone of 10 times the column radius [17].

under the expansion of the cylinder with a radius r 0 .
The predicted lateral displacement due to a closedended driven pile agreed quite well with thedeflection measured using inclinometers.
Similarly, Kelly et al. [20] predicted stone
column installation effects using estimation method
for pile driving via Eq. (2) with inclusion ofcoefficient β, which is used to match predicteddisplacement with measured value. A β value of 0.6
was found to fit well with the measurement although
β does not have any physical meaning, other thanthat the displacement caused by stone column
installation is less than that caused by driving a solid
pile with the same column diameter.

ASSESSMENT OF INSTALLATION EFFECTS
The behaviour of soils affected by installation
varies with time. For purposes of assessing
installation effects on the surrounding environments,
this paper focuses on short term effects. Since very
limited assessment of CMC installation effects isreported except in [17], assessment methods will be
discussed based on those used for different pilingand ground improvement techniques.

𝜌𝜌𝑟𝑟 = �𝑟𝑟 2 + 𝛽𝛽𝑟𝑟02 − 𝑟𝑟

where, ρ r is the displacement at a distance r fromthe centre of column and r 0 is the radius of thecolumn. β value should be calibrated for each depth,
which is a difficult task. Displacement can also be
estimated using Eq. (3) presented by Yu [18]:Analytical Methods𝜌𝜌𝑟𝑟 = 𝑠𝑠𝑢𝑢 /(2𝐺𝐺)(1 + ln(𝐺𝐺/𝑠𝑠𝑢𝑢 ))(𝑟𝑟0 /𝑟𝑟)2 𝑟𝑟

The advance of CMC auger to the groundcomprises soil loosening by auger flights, followed
by lateral compaction by the displacement body. If
the loosening stage is ignored, the process can beconsidered as cylindrical cavity expansion. Unlike
jacked and driven piles, CMC installation is not
simply a cavity expansion process, but rather
affected by the partial flight auger rotation, which
reduces significantly normal stress on the pile shaftthat would be estimated by cavity expansion theory[7]. The cylindrical cavity expansion is only
applicable for the middle section of CMC. Near thecolumn tip the installation resembles sphericalcavity expansion while near the surface theconfining stress is significantly lower and verticaldisplacement is normally dominant (i.e. heaving).
Furthermore, since the column is drilledincrementally, the cavity expansion theory cannot
simulate the installation process precisely. Despiteof these limitations, cavity expansion method can beused for preliminary assessment due to its simplicity
compared to more complicated methods.
Cavity expansion theory assumes radialdisplacement under plane strain conditions and novertical strain, which is well described in Yu [18].
Pestana et al. [19] suggested that pile installation canbe modeled as the undrained expansion of a cylinder
within an infinite, homogeneous soil medium, andsoil deformations can be estimated using Eq. (1).
𝜌𝜌𝑟𝑟 /𝑟𝑟0 = �1 + (𝑟𝑟/𝑟𝑟0 )2 − 𝑟𝑟/𝑟𝑟0

(2)

(3)

where s u is the undrained shear strength. Thisequation allows estimation of soil displacement at
various depths with G/s u obtained from field tests,
e.g. Seismic Dilatometer Marchetti Test (SDMT).
Numerical Methods
More accurate assessment can be carried out
using the finite element method (FEM) or the finite
difference method (FDM). Advantages andchallenges of various numerical techniques are
discussed in this review. Numerical simulation of
the penetration of a pile initially positioned above
the ground surface is one of the challenges due toheavily distorted mesh and complex soil/auger
contact. Instead, many studies omitted the physicalshape of the auger, and simulated cavity expansion
from a finite cavity with a prescribed horizontal
displacement e.g. [17, 21]. More sophisticatedanalyses involved simplifying auger as a coneshaped rigid body and often pre-installed into soils
before simulation started [9]. Although installationof CMC, jacked-in and driven piles all results in acavity to be filled with rigid piles or grout, the CMC
installation is strongly affected by the auger rotation.
Modelling auger effect is not possible in the 2D
axisymmetric model but within a 3D system [8].
Updated Lagrangian analysis(1)

Updated Lagrangian analysis such as “large
strain mode” in the commercial software FLAC and“Update Mesh” feature in PLAXIS allows grid-point
coordinates are updated at each step. This feature iswhere, a soil element at an initial radius r fromthe pile centre displaces towards a radius r + ρ r
46

GEOMATE- Brisbane, Nov. 19-21, 2014

Overall, although both ALE and CEL seem to be
the promising solutions to the very large strain
problems, CEL is more computationally friendly
since a fixed mesh means no mesh distortion andless solution convergence. These Abaqus/Explicit
analyses, however, seem to offer only single-phasepossibility with either fully drained or total stressundrained
condition
analyses
[23].
Also,
ABAQUS/Explicit currently only allows total stressor frictionless contact between bodies. The challenge
would be to create a user’s subroutine into Abaqus
to enable undrained effective stress analysis andfrictional contact.

useful in simulation of cavity expansion withprescribed displacement along the boundary [22].
However, when dealing with extreme large
deformation such as modelling the penetration ofpile into the ground, especially with the use of finer
meshes near the soil/pile contact, meshes are heavily
distorted. Zones in these models however, have
limiting distortions, which often cause “badgeometry” error message. For the program tocontinue to run, “Automatic Rezoning” feature(FLAC 2D 6.0 or later) may be used to map existing
stress onto a new generated, more regular mesh. So
far this automatic rezoning technique has a numberof limitations e.g. it does not allow use of interfaces
and axisymmetric model and does allow only one
soil model in the rezoned region. In addition, thetechniques require user intervention, which could bequite computationally expensive.

Effects of initial radius on predictions
There are two types of cavity expansion (1) froman existing cavity (2) from a cavity with an initial
zero radius. While pile installation resembles cavity
creation from an initial zero radius, numericalexpansion must necessarily be modelled from afinite radius rather than from zero radius to avoid
numerical difficulties (e.g. infinite circumferential
strain). For simulation of the installation of a drilleddisplacement pile as in [7], a “finite initial radius” a 0of 0.015m was specified compared to a final pile
radius r 0 of 0.165m. The authors argued that thisinitial radius was sufficiently small to obtain limiting
cavity pressure at the end of cavity expansion.
In fact, the restriction of numerical expansion
from a finite radius in place for a zero initial radiuswould cause no inconsistency in the final results[24]. Various initial sizes of the existing cavity has
been used but it is quite common to double the sizeof an existing cavity e.g. [10],[17]-[21]. Krasiński
[10] simulated screw displacement pile installation
using PLAXIS by modelling an initial cavity with aradius equal to half pile radius, and then doubled
that cavity to the full size of pile radius in an
axisymmetric model. While a smaller initial radius
results in better prediction [7], a larger amount ofexpansion ∆r = r - r 0 will be required, which may
eventually lead to heavily distorted mesh, especiallywith finer mesh. Again modelling for these cases is
an extreme deformation problem.

ALE and Eulerian-based analyses (CEL)
Pure Lagrangian technique describes the motionof the mesh with each node moving together withmaterials. In contrast, pure Eulerian analysis
describes the material deformation, relative to thespatially fixed mesh. The combined analyses forms
the Arbitrary Lagrangian – Eulerian (ALE) adaptive
meshing and Coupled Eulerian–Lagrangian (CEL)
analysis, both available in commercial FEM
software package ABAQUS.
ALE is available for both Abaqus/Standard and
Abaqus/Explicit. However, ALE in Abaqus/Explicit
is more robust and can handle a large variety ofproblems including severe distorted mesh, hence
will be discussed further. ALE mesh is allowed tomove independently of material deformation. In thefirst step the explicit Lagrangian analysis isperformed. The resulted distorted mesh will require
a new improved mesh. In the second step, theEulerian analysis is performed, where variables in
the previous analysis is transferred into the newmesh. ALE can deal with large deformation
problem; however, since elements and connectivity(i.e. topology) do not change, high quality mesh may
not be maintained during extreme deformation.
In contrast, CEL (only in Abaqus/Explicit) has
spatially fixed mesh. Eulerian and Lagrangianbodies within the same model can interact via acontact definition e.g. a Lagrangian auger travelling
into Eulerian yielding soil. Chosen portions of a
CEL model can be modelled as Eulerian or
Lagrangian. Since the Eulerian mesh is fixed in CEL,
soil displacement has to be calculated by integrating
node velocities of the Eulerian mesh recorded alonga predefined path over time [8]. The installation of ascrew displacement auger into dry sand wasnumerically simulated using CEL as in [8], however
the results were not adequately verified against fieldmeasurements.

Constitutive models and parameters
The choice of soil model is another challenge
since soils are subject to complex loadings during
installation. Selected models should capture highly
non-linear inelastic behavior, decay of excess porepressure, loading and unloading paths and densitychanges. Due to the complex shape of auger, cyclic
effects in soils may need to be considered [8]. Wellestablished models such as Mohr Coulomb (MC)and modified Cam Clay (MCC) are incorporated inmost of the commercial software packages. The MC
failure criteria if used should account for stress47

GEOMATE- Brisbane, Nov. 19-21, 2014

were carried out by Lehigh University [29],comprising installation of a 320mm-diameter CMC
with four surrounding CMCs acting as reaction piles,
instrumentation and one subsequent load test. The
instrumentation included four push-in pressure
sensors and four shape acceleration arrays (SAA) tocapture stress change and displacement in soft silty
soil throughout column installation and testing. At
the end of installation, an increase in horizontal
stress by 2kPa was recorded within 1D (i.e. one
diameter) distance from the CMC, by 8kPa within
2D distance, and then with decreasing trend withincreasing distance from the CMC. Some stressrelaxation by approximately 2 to 3kPa was recordedat the end of the installation. However, after
installation, the stress recorded around the central
CMC increased and was greater than stresses
recorded at the end of the installation. The recorded
soil displacement showed a clear decreasing trendwith increasing distance from the CMC. Althoughuseful, this project included only a limited numberof CMCs and tests for a particular soil type, without
theoretical or numerical prediction.

dependent stiffness. For MCC model, since the soil
surrounding the column is likely to be in criticalstate, this model can be quite representative. It canbe noted that above water table, soils may bepartially saturated and thus excess pore pressure
should be predicted considering coupled flowdeformation behaviour of unsaturated soils [25].
Compared to MC and MCC, hypoplasticity is arelatively new type of soil model and has been
increasingly utilized to solve large deformation
problems [8, 9]. Various hypoplasticity models exist,
noticeably by von Wolffersdorff [26] for sand andmodified version by Mašín [27] for clay. Von
Wolffersdorff [26] model for granular materials
incorporates the intergranular strain and dependencyof friction angle and stiffness on density changes
and compaction. The model requires 13 parameters
including critical state friction angle and void ratio.
Despite of advanced features, determination of alarge number of model parameters is a challenge.
Meanwhile, clay hypoplasticity model developedby Mašín [27] combines mathematical structure ofhypoplasticity models with basic principles of thecritical state soil mechanics. This model requires
five parameters, similar to those of MCC model;
however, it can provide a smooth transition between
overconsolidated and normally consolidated states.
Unlike MC, this hypoplasticity model correctlypredicts the state dependent soil stiffness.
Hypoplasticity models are not built-in in mostcommercial software packages, and implementationof these models is a difficult task.

CONCLUSION
Concerns over the extent of installation effects
on neighbouring structures should be addressed toassist the selection and evaluation of ground
improvement techniques. This paper describes anumber of challenges in assessment of CMC
installation effects on the surrounding ground andstructures. While the installation effects may be
preliminarily estimated using well establishedanalytical methods such as the cavity expansion
theory, numerical methods provide a morecomprehensive prediction tool, although there arestill great geotechnical challenges remaining.
Selection of a modelling technique and soil modelthat are able to account for very large displacement
are of paramount importance. Although simple
approaches may still have acceptable values inassessing the installation effects, the advanced
methods CEL and ALE are the most promising. The
other challenge is associated with the verification
methods including small and full scale model
testing. It is recommended that future CMC projects
allow more field measurements as a basis to improve
the assessment methods.

Physical Modelling
No laboratory experiment to assess CMC
installation has been reported in the literature.
Challenges during laboratory experiment would
include auger fabrication (Fig. 1), setting up driving
tools that can control torque and vertical crowd andcomplicated on-sample instrumentation. As analternative approach to on-sample instrumentation,transparent artificial soils contained in a chamberwith observable window allows the displacement
field to be captured by photographs and analysedusing “particle image velocimetry” technique. Suchstudies by Hird et al. [28] indicated that thedisplacement depends on rotation speed of the auger.
However, rigorous scaling is hard to be achieved totranslate the results into behaviour of a prototype
CMC and artificial soils like glass offers little
practical usefulness. Despite expected shortcomings,
small scale models provide roughly similar trends oflateral displacements in full scale field tests.
Field tests are not often readily available forverification of numerical analysis, e.g. Rivera et al.
[17] examined installation-induced stress around
CMC column but has not verified using field results.
In a separate case study, but rare, limited field tests

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[2] Plomteux, C., A. Porbaha, and C. Spaulding,"CMC Foundation System for Embankment
Support—A Case History", in GeoSupport,
2004.
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and pore water pressure under embankments",
Geomechanics and Geoengineering, 8(2), 2013,
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[17] Rivera, A.J., C.G. Olgun, T.L. Brandon, and F.
Masse, Numerical modeling of controlled
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[18] Yu, H.-S., Cavity expansion methods ingeomechanics. The Netherlands: Kluwer
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[19] Pestana, J., C. Hunt, and J. Bray, "SoilDeformation and Excess Pore Pressure Field
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[20] Kelly, R., T. Muttuvel, and K. Chan, Lateral
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Geo-Frontiers. 2011, ASCE. pp. 549-556.
[21] Castro, J. and M. Karstunen, "Numericalsimulations of stone column installation",
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[22] Ahmadi, M.M., P.M. Byrne, and R.G.
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[23] Elkadi, A.S.K., H. van Lottum, and H.J. Luger,
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[24] Carter, J.P., M.F. Randolph, and C.P. Wroth,"Stress and pore pressure changes in clay during
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[25] Ho, L., B. Fatahi, and H. Khabbaz, "Analyticalsolution for one‐dimensional consolidation of
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[26] von Wolffersdorff, P.A., "A hypoplastic
relation for granular materials with a predefined
limit state surface", Mechanics of Cohesivefrictional Materials, 1(3), 1996, pp. 251-271.
[27] Mašín, D., "A hypoplastic constitutive model
for clays", Int. J. for Numerical and Analytical
Methods in Geomechanics, 29(4), 2005, pp.
311-336.
[28] Hird, C., Q. Ni, and I. Guymer, "Physicalmodelling of deformations around piling augers
in clay", Geotechnique, 61(11), 2011, pp. 993999.
[29] Suleiman, M.T., et al., Instrumented Static load
test of CMC, Lehigh University, 2013.

[3] Hewitt, P., S.J. Summerell, and Y. Huang,"Bridge Approach Treatment Works On The
Coopernook To Herons Creek Section Of The
Pacific Highway Upgrade", in Sydney Chapter
Symposium 2009.
[4] Brown, D.A., "Practical considerations in theselection and use of continuous flight auger anddrilled displacement piles", ASCE-Geotechnical
Special Publication, (129), 2005, pp. 251-261.
[5] Hokmabadi, A.S., B. Fatahi, and B. Samali,"Seismic response of mid-rise buildings onshallow and end-bearing pile foundations in softsoil", Soils and Foundations, 54(3), 2014, pp.
345-363.
[6] Hokmabadi, A.S., B. Fatahi, and B. Samali,"Assessment of soil–pile–structure interaction
influencing seismic response of mid-risebuildings sitting on floating pile foundations",
Computers and Geotechnics, 55(0), 2014, pp.
172-186.
[7] Basu, P. and M. Prezzi, Design and applicationsof drilled displacement(screw) piles,
Publication FHWA/IN/JTRP-2009/28. Joint
Transportation Research Program, Indiana
Depart. of Transport'n & Purdue University,
West Lafayette, Indiana, 2009.
[8] Pucker, T. and J. Grabe, "Numerical simulationof the installation process of full displacement
piles", Computers and Geotechnics, 45, 2012,
pp. 93-106.
[9] Larisch, M.D., et al., "Simulation of auger
displacement pile installation", Int. J. of
Geotechnical Eng., 2013.
[10] Krasiński, A., "Numerical simulation of screw
displacement pile interaction with non-cohesivesoil", Archives of Civil & Mechanical Eng.,
14(1), 2014, pp. 122-133.
[11] Lim, J.K. and B. Lehane Characterisation of
the effects of time on the shaft friction of
displacement piles in sand. Géotechnique, 2014.
64, 476-485.
[12] Randolph, M.F. and C.P. Wroth, "An analyticalsolution for the consolidation around a driven
pile", Int. J. for Numerical and Analytical
Methods in Geomechanics, 3(3), 1979, pp. 217229.
[13] Ladanyi, B., "Expansion of a cavity in asaturated clay medium", J. of Terramechanics,
1(2), 1964, pp. 96.
[14] Nguyen, L.D., B. Fatahi, and H. Khabbaz, "Aconstitutive model for cemented clays capturing
cementation degradation", International Journalof Plasticity, 56(0), 2014, pp. 1-18.
[15] Le, T.M., B. Fatahi, and H. Khabbaz, "Viscous
behaviour of soft clay and inducing factors",
Geotechnical and Geological Engineering,30(5), 2012, pp. 1069-1083.
[16] Fatahi, B., T.M. Le, M.Q. Le, and H. Khabbaz,"Soil creep effects on ground lateral deformation
49

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECT ON UNCONFINED COMPRESSIVE STRENGTH OF SANDTEST PIECES CEMENTED WITH CALCIUM PHOSPHATECOMPOUND BY ADDITION OF SCALLOP SHELL POWDER
G. G. N. N. Amarakoon1, Takefumi Koreeda1, Satoru Kawasaki2
1

Graduate School of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-8628,
Japan
2
Faculty of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan

ABSTRACT
Chemical grout is composed of a calcium phosphate compound (CPC) which develops to form calcium
carbonate (CC) precipitation throughout the soil and leading to an increase in soil strength. In this paper, initiallythe condition for CPC precipitation by using different mixtures of calcium and phosphate stock solutions were
investigated and analyzed. For that, Toyoura sand test pieces were cemented by CPC solutions and cured up to 28
days and carried out unconfined compressive strength (UCS) test. Moreover, Toyoura sand test pieces were
cemented by CPCs with scallop shell (SS) powder and cured and these specimens also analyzed with UCS tests.
The UCS of the sand test pieces cemented by CPC with SS powder was larger than that of the test pieces with noadded powders. The UCS of Toyoura sand test piece cemented with the CPC-SS powder method increased to a
maximum of 156.9 kPa. Moreover, the best CPC-Chem mixture for cementation is CA: DPP with the concentrationof Ca/P ratio is 0.5. In addition pH concentration, scanning electron microscope (SEM), and density before andafter curing were observed. The results indicate that the density and the pH concentration of the sand test pieces
cemented by CPCs with SS powder were larger than that of the sand test pieces with no added powders. SEM
images of test pieces cemented with CA: DPP mixture by addition of SS powders not clearly identified a crystal
formation among particles of Toyoura sand.
Keywords: Calcium Carbonate; Calcium Phosphate Compound; Ground Improvement; Unconfined Compressive
Strength63.5 kPa [8]. Our aim is to achieve a UCS value of
100 kPa, which is needed to avoid groundliquefaction during earthquakes [11]. This implies
that the UCS of CPC-Chem is not sufficient for use
as a ground stabilizer, necessity of a preferable
mechanism for further increase in UCS.
An earlier research was said, the UCS of the test
pieces with TCP and CC additives exceeded thetargeted value of 100 kPa and increased to a
maximum of 261.4 kPa and 209.7 kPa respectively[12]. This observations indicates that the existence ofCC seed crystals can reinforce the strength of CPC
grouts. The main component of scallop shells is CC,
which are disposed of in large quantities as marine
industrial waste (410,000 tons/year in Japan) [13].
Scallop shells are non-toxic to handle andinexpensive to obtain. Hence, scallop shells can beused for CC which is a favorable material in thegeotechnical field from the view point of waste
utilization and costeffectiveness.
In the present study, our aim was to improvestrength by adding CPC with scallop shell powder.
This study aims to exceed a maximum UCS of 100
kPa after 28 days of curing, which is the strength
required to use the CPC and scallop shell powder
combination as a countermeasure against soil

INTRODUCTION
Cement grouting is used as a ground improvement
method for countermeasure against soil liquefaction
during an earthquake [1]. However, cement grouting
comprises several environmental problems such as
high CO2 emissions during cement production, highenergy cost for re-excavation and hard to recycling
the improved ground. Hence in present, grout
materials produce by microorganism have beendeveloped for ground permeability control andreinforcement [2]-[6]. Biogrouting is the process ofground improvement by biological action [7].
A novel ground stabilizer was developed toincrease the number of options available among
cementing mechanisms based on microorganisms[8],[9]. In addition, it is reported on a CPC chemical
grout (CPC-Chem) that utilizes self-setting CPC
mechanisms [10] and on a CPC biogrout (CPC-Bio)
whose solubility is dependent on its pH [10] (Fig. 1),
which can be increased by a microbial reaction.
CPC-Chem is easy to obtain, safe to handle, nontoxic, and recyclable, advantages that make it suitablefor geotechnical application [8]. The maximum
unconfined compressive strength (UCS) of sand test
pieces cemented with CPC-Chem was found to be50

GEOMATE- Brisbane, Nov. 19-21, 2014liquefaction during earthquake. UCS tests andscanning electron microscopy (SEM) observations
were conducted on sand test pieces as a function oftime. In addition, pH value and wet density were
measured. Based on the results, we discuss the effectof the amount of added powders, variation in wet
density (ρt), pH and crystal form on the UCS.
1

OCP β-TCPα-TCP
DCPD
0
-1

TTCP

DCPA

-2
-3
-4

HA

-5
-6

0

2

4

6
pH

8

10

12

Fig. 1 Solubility phase diagrams for the ternary
system, Ca(OH)2–H3PO4–H2O, at 25 °C,
showing the solubility isotherms of CaHPO4(DCPA), CaHPO4·2H2O (DCPD), Ca8H2(PO4)6·5H2O (OCP), α-Ca3(PO4)2 (α-TCP),
β-Ca3(PO4)2 (β-TCP), Ca4(PO4)2O (TTCP),
and Ca10(PO4)6·(OH)2, (HA). The figure isadapted from Tung [10].
METHODOLOGY
In this study, for the CPC-Chem, calcium acetate(CA) was used as a calcium solution anddiammonium phosphate (DAP) and dipottasium
phosphate (DPP) were used as phosphate solutions.
The concentration of CA was varied from 1.5 M to
0.5 M and the concentration of DAP and DPP wasconstant as 3.0 M for prepare the CPC-Chem solution
with two different Ca/P ratios (0.5 and 0.25). Then,
Toyoura sand test pieces were cemented with CPCChem only and cured up to 28 days and analyzed with
UCS tests. For this case, a standard sand test piece
was made from 320.09 g of Toyoura sand (meandiameter D50 = 170 µm, 15% diameter D15 = 150 µm)
and 73.3 mL of CPC-Chem according to the previous
report [8].
In addition, Toyoura sand test pieces were
cemented with CPC-Chem (CA: DPP = 0.6 M: 1.2 M)
by addition of scallop shell (SS) powder and cured up
to 56 days and these specimens also analyzed with
UCS tests. In this case, a standard sand test piece wasmade as same as previous case and it is called as`CPC-Cont` sample. The examined test pieces weremade with the combination ratios shown in Fig. 2. 1%(3.2 g) (Case SS-01), 5% (16.0 g) (Case SS-05), and
10% (32.0 g) (Case SS-10) of SS (mean diameter D50= 25.12 µm) were mixed with 72.21 mL, 67.84 mL,
and 62.38 mL of CPC-Chem respectively and added
to weight of a standard sand test piece of 320.09 g for
prepare CPC-SS samples.
It was uniformly mixed in a stainless-steel ball for
2 min and the mixture was divided into quarters, eachof which was placed into a plastic mold container (ϕ= 5 cm, h = 10 cm). The sand in the mold container
was tamped down 30 times by a hand rammer after
each of the four quarters was placed in the mold. The
molded test pieces were subsequently cured in an
airtight container at a high humidity for 28 days and
56 days at 20◦C.
The UCS of the test pieces removed from themold container after curing was measured at an axial
strain rate of 1%/min with the UCS apparatus T26631100 (Seikensha Co., Ltd., Japan). In all cases two
test pieces were tested. The pH of the test pieces wascalculated as an average of three measurements (top,bottom, and middle of each test pieces) using pH
Spear (Eutech Instruments Pte., Ltd., Singapore).
Segments of the UCS test pieces were observed by an
SEM. The segments were naturally dried at 20◦C fora few days and carbon-coated with a carbon coater.
SEM observations were carried out at an accelerating
voltage of 15 kV and at x 1000 magnification.
RESULTS AND DISCUSSIONUCS Test
In this study, Toyoura sand test pieces cemented
by four reaction mixture sets of CPC-Chem werechosen. The measured UCS in this study ranged from
26.1 to 143.6 kPa. The maximum value was measured
when the sand test pieces cemented with CA:
DPP=1.5M: 3.0M mixture and Ca/P ratio was 0.5(Fig. 3 (a)). The UCS is tended to increase with thecuring time for 28 days for sample prepared with CA:
DPP=1.5M: 3.0M mixture but the test piece at 14days of curing time shows that the UCS is tended todecrease. It is assumed that some error could occur
when preparing the sample. To clarify this result,further examination of the test pieces is needed in the
future. There is no significant variation of UCS in thetest pieces prepared with CA: DPP=0.75 M: 3.0 M
mixture. Also, the UCS value of the test pieces
cemented with CA: DPP=1.5M: 3.0M mixture (CA:DPP=0.5) is larger than the UCS value of the test
pieces with CA: DPP=0.75M: 3.0M mixture (CA:DPP=0.25).
According to Fig. 3(b), the value of UCS is tended
to constant for both CA: DAP=0.5 and CA:
DAP=0.25. Also, the UCS value of the test pieces
with CA: DAP=0.5 is larger than the UCS value ofthe test pieces with CA: DAP=0.25. Moreover, fromthe Figs. 3(a) and 3 (b), the UCS value of the test
pieces with CA: DPP=0.5 is larger than the UCS
value of the test pieces with CA: DAP=0.5.

51

GEOMATE- Brisbane, Nov. 19-21, 2014

Control
Case Name

CPC-Cont

Sand Weight (g)Sand320.09Weight of adding
powders (g)Without
powderVolume of CPCChem (mL)

73.30

CPC-SS Method
SS-01

SS-05

SS-10

Sand
320.09Sand
320.09Sand
320.09+++SS 3.2

SS
16.0

SS
32.0

72.21

67.84

62.38

Fig.2 Conceptual image of the contents.
Figs. 4(a) and 4(b) show the relationship between
UCS and Ca/P ratio for the sand test pieces cemented
with CPC-Chem only. The results are given
considering after 1 day and 28 days curing period. It
comprises that the UCS value (Ca/P=0.5) is larger
than the UCS value (Ca/P=0.25) for both testing casessuch as CA: DPP and CA: DAP. The UCS value islarger after 28 days curing time than 1 day curing
time. However, the rate of increase of UCS of sandtest pieces cemented with CA: DPP mixture is lager
in 28 days curing period than 1 day curing period(Fig. 4(a)).

In Fig. 4(b), when the test pieces cemented with CA:
DAP mixture, the UCS values are nearly same after 1days and 28 days curing period. Therefore, the rate ofincrease of UCS of sand test pieces cemented with
CA: DAP solution is lager in 1 day curing period than
28 day curing period. However, it is assumed as anerror and to get more precise result, further testing isrequired.
In addition, Toyoura sand test pieces cemented byfour reaction mixture sets were chosen (adding CA:
DPP = 0.6M: 1.2M mixture with no adding powders
(a)

(a)

CA:DPP=0.5
CA:DPP=0.25
0UCS(kPa)

(b)

20
40
Curing time(day)

200
160
120
80
40
0

CA:DAP=0.5
CA:DAP=0.25
0

CA:DAP = 0.5 & 0.25

200
160
120
80
40
0
0

20
40
Curing time(day)Fig. 3 (a) UCS of Toyoura sand test pieces cemented
by CA: DPP=0.5 and 0.25. (b) UCS of
Toyoura sand test pieces cemented by CA:
DAP=0.5 and 0.25.

CA:DPP = 0.5 & 0.25
CA:DPP=0.5
200
(1D)
160
CA:DPP=0.25
120
(1D)
80
CA:DPP=0.5
40
(28D)
0
CA:DPP=0.25
0 0.25 0.5 0.75 (28D)
Ca/P Ratio(b)

C A: D A P = 0 . 5 & 0 . 2 5
UCS(kPa)

UCS(kPa)

200
160
120
80
40
0

UCS(kPa)

CA:DPP = 0.5 & 0.25

0.25 0.5 0.75
Ca/P Ratio

CA:DAP=0.5(1D)
CA:DAP=0.25(1D)
CA:DAP=0.5(28D)
CA:DAP=0.25(28D)

Fig. 4 Relationship between UCS and Ca/P ratio of
Toyoura sand test pieces cemented by (a)CA: DPP=0.5 and 0.25. (b) CA: DAP=0.5
and 0.25.

52

GEOMATE- Brisbane, Nov. 19-21, 2014
crystal structure was observed in the sample preparedwith CA: DPP=0.5 mixture and other samples were
not clearly observed any crystal formation.
SEM images of test pieces subjected to CA: DPP
treatment with SS powders were not clearly identify
a crystal formation among particles of Toyoura sand(Fig. 9). The increase in UCS seemed to be becauseof the binding of the sand particles by the precipitated
CPC that enveloped the CC particles.
(a)UCS(kPa)

and adding SS powder with different percentages:
1%, 5% and 10%). The measured UCS in this study
ranged from 49.9 to 156.9 kPa.
The maximum value was measured when the sandtest pieces cemented with CA: DPP=1.2M: 0.6M
mixture by adding SS powder 10% (Fig. 5). The UCS
of sand test pieces cemented by CPC with SS powder
was larger than that of the test pieces with no added
powders when considering cured time until 28 days.
However, the UCS values of sand test pieces
cemented by CPC with SS-1% and SS-5% after 56
days curing period is less than that of the CPC-Cont
sample.
The test pieces with SS-10% show that the UCS
is tended to decrease at 14 days curing period, it isassumed that some error could occur when preparing
sample. To clarify this result, further examination of
the test pieces is needed in the future.

CA:DPP = 0.5 & 0.25

200
160
120
80
40
0

CA:DPP=0.5
CA:DPP=0.25
6.0

(b)

UCS(kPa)

Figs. 6(a) and 6(b) illustrate the effect of pH on
UCS for the test pieces cemented by CPC-Chem (CA:DPP and CA: DAP). The pH of the test pieces range
from acidic to weakly alkaline (6.4-7.5) for CA: DAP
and the pH range from weakly alkaline to strong
alkaline (7.0-8.7) for CA: DPP. Moreover the UCS istended to increase with the increase of pH for CA:
DPP (Fig 6 (a)) while the UCS was nearly constantwhen increase of pH for CA: DAP (Fig. 6(b)).

10.0

C A: D A P = 0 . 5 & 0 . 2 5

200
160
120
80
40
0

CA:DAP=0.5
CA:DAP=0.25
6.0

8.0
pH

10.0

Fig. 6 (a) Relationship between pH and UCS for CA:
DPP=0.5 and 0.25 (b) Relationship between
pH and UCS for CA: DAP=0.5 and 0.25.

CA : DPP = 0.6M : 1.2M
200
160
120
80
40
0

CA : DPP = 0.6M : 1.2M

0

20

40

UCS (kPa)

UCS(kPa)

8.0
pH

Effect of pH on UCS

60

Curing time(day)Fig. 5 Unconfined compressive strength (UCS) of
sand test pieces cemented by CPC with SS.
According to Fig. 7, the pH is tended to increase
with the time. Moreover, the pH value of CPC-SS
sample is larger than pH values of CPC-Cont sample.
When the concentration of SS powder is increased,
pH value is tended to increase. Although, when pH isincreased, UCS is tended to increase.
SEM Observation
Fig. 8 shows SEM images of sand test pieces
cemented with four reaction mixture set of CPCChem (CA: DPP=0.5 and 0.25 and CA: DAP=0.5 and0.25) and the curing time was 14 days. Wisker-like

53

200
160
120
80
40
0

CPC-Cont
SS-1%
SS-5%
SS-10%
6.0

8.0
pH

10.0

Fig. 7 Relationship between pH and UCS for CPCCont, and CPC-SS test pieces.
Effect of Wet Density on UCS
The estimated wet density of the test pieces isshown in Figs. 10 and 11. Wet density (before) was
calculated by measuring mold weight immediately
after being produced and wet density (after) is defined
as wet density immediately after cured. Fig. 10 shows
wet density of the test pieces cemented with CPC-GEOMATE- Brisbane, Nov. 19-21, 2014
Chem only. The results shows, UCS value isincreased with increase of density only in CA:
DPP=0.5. In addition, when curing time is increased
the UCS is tended to increase. In other cases, theUCS value neither increase nor decrease withincrease of wet density.
There is no significant difference between wet
density, before and after the test. That is because there
was no volume change such as expansion or
shrinkage after curing.
A1

A2

B1

B2

In the case of the test pieces treated by the CPCSS powder method, the wet density is larger than thetest pieces cemented with CPC-Chem only. (Fig. 11).
Also, it comprises that the UCS is tended to increase
with increase of density. In addition, when theincrease of SS and CC powders %, wet density is
increased.
Effect on Addition of SS Powder on the UCS
Figs. 3 and 5 show the UCS test results for Toyoura
sand test pieces cemented with CPC-Chem only and
CPC-SS powder respectively. It comprises that the
UCS of test pieces cemented with CPC-SS is larger
than that for CPC-Chem alone. Practically, the test
pieces to which the SS powder with 10% was added
show a UCS is larger than 100 kPa. This statement
recommends that through control of the CC content,
the CPC-SS and CPC-CC method would allow foradjustment of strength according to the required
strength properties of the ground while maintaining a
UCS of over 100 kPa. Considering results of UCS,
pH, wet density and SEM images in CPC-SS powder
method, the governing factors for increase thestrength of the sample are pH and wet density.

Fig.8 SEM images for test samples after 14 days
curing period (600 X). (A1) CA: DPP=0.25,(A2) CA: DPP=0.5, (B1) CA: DAP=0.25
and (B2) CA: DAP=0.5.

(a)UCS(kPa)

CA:DPP = 0.5 & 0.25

(a)
1 Day

14 Day(b)
1 Day

14 Day

200
160
120
80
40
0
1.90

1.95
2.00
Wet Density (g/cm3)
CA:DPP=0.5(Before)
CA:DPP=0.25(Before)
CA:DPP=0.5(After)
CA:DPP=0.25(After)(b)

UCS(kPa)

CA:DAP = 0.5 & 0.25

(c)
1 Day

14 DayFig.9 SEM images for test samples cemented with
CPC by adding SS powder after 1 day and
14 days curing period (1000 X). (a) SS-1%,(b) SS-5% and (c) SS-10%.

200
160
120
80
40
0
1.90
1.95
2.00
Wet Density (g/cm3)
CA:DAP=0.5(Before)
CA:DAP=0.25(Before)
CA:DAP=0.5(After)
CA:DAP=0.25(After)

Fig. 10 Relationship between wet density and UCS(a) CA: DPP=0.5 and 0.25 (b) CA: DAP=0.5
and 0.25.

54

GEOMATE- Brisbane, Nov. 19-21, 2014
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Society of Engineering Geology, Vol. 51, 2010,
pp. 10–18 (in Japanese with English abstract).
[7] Van Paassen LA, Harkes MP, Van Zwieten GA,
Van der Zon WH, Van der Star WRL and Van
Loosdrecht MCM, “Conference Proceedings”, in
Proc. 17th Int. Conf. on Soil Mechanics andGeotechnical Engineering, 2009, pp. 2328-2333.
[8] Kawasaki S. and Akiyama M., “Unique grout
material composed of calcium phosphate
compounds”, Int. Journal of GEOMATE, Vol. 4,
No.1, 2013, pp. 429-435.
[9] Akiyama M. and Kawasaki S, “Microbiallymediated sand solidification using calcium
phosphate compounds”, Journal of the Japan
Society of Engineering Geology, Vol. 137-138,
2012, pp. 29-39.
[10] Tung MS, “Calcium phosphates: structure,composition, solubility, and stability, in: A. Zahid(Ed.), Calcium phosphates in biological andindustrial systems”, Kluwer Academic Publishers,
Norwell, 1998, pp. 1-19.
[11] Yamazaki H, Maeda K, Takahashi K, Zen K and
Hayashi K, “Technical Note of Port and Harbour
Research Institute”, Vol. 905, 1998, pp. 1-29 (inJapanese).
[12] Kawasaki S. and Akiyama M, “Enhancement of
unconfined compressive strength of sand test
pieces cemented with calcium phosphate
compound by addition of various powders”,
Journal of Soils and Foundations, Vol. 53-(6),2013, pp. 966-976[13] “Recycling Technology Guidelines for Harborand Airport Construction and Maintenance”,
Edited in 2004, Ports and Harbours Bureau.
http://www.mlit.go.jp/kowan/recycle/.

CA : DPP = 0.6M : 1.2M

UCS(kPa)

200
160
120
80
40
0
1.90 1.95 2.00 2.05

CPC-Cont(before)
CPC-Cont(after)
SS-1%(before)
SS-1%(after)
SS-5%(before)
SS-5%(after)
SS-10%(before)
SS-10%(after)

Wet density (g/cm3)
Fig. 11 Wet density of Toyoura sand test pieces
cemented by CPC with SS.
CONCLUSION
In this study, initially the condition for CPC
precipitation using different mixtures of calcium andphosphate stock solutions was investigated andanalyzed. It concluded that the best CPC-Chem
mixture was CA: DPP with the concentration of Ca/P
ratio is 0.5.
Further, the study was expanded to CPC powder
method with using scallop shell powder. From thisstudy, it was concluded that CPC-SS powder method
had a significant potential for strength of the soil. The
UCS of a Toyoura sand test piece cemented with the
CPC-SS powder method increased to a maximum of
156.9 kPa. The aim of this study was to use CPCChem to achieve a maximum UCS of over 100 kPa,
which was the strength required to prevent groundliquefaction. Using the CPC-SS powder method, we
far exceeded this objective by achieving a UCS ofover 150 kPa.
Finally, considering above viewpoints, CPC-SS
powder method is more effective and reliable than
CPC-Chem method for achieve a maximum UCS ofover 100 kPa to prevent the ground liquefaction.
ACKNOWLEDGEMENT
The work has been partly supported by a Grantin-Aid for Scientific Research (No. 24300299) fromthe Japanese Ministry of Education, Sports, Scienceand Technology. This support is gratefully
acknowledged.
REFERENCES[1] Karol RH, “Chemical grouting and soil
stabilization”, 3rd ed., CRC Press, Boca Raton,
FL, 2003.
[2] Whiffin VS, Van Paassen LA and Harkes MP,“Geomicrobiology Journal”, Vol. 24, 2007, pp.
417-423.

55

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

ENHANCING SLOPE STABILITY WITH VEGETATION
Nicholas Hytiris1, Michael Fraser2 and Slobodan B. Mickovski1
Glasgow Caledonian University, Scotland, UK; 2 Mabey Hire Ltd, Scotland, UK

1

ABSTRACT
Landslides can have serious impact on natural and human environment and their prevention and mitigation isof global concern. The ability of a slope to resist a landslide depends on the materials and the properties of which
it is composed. This project focuses in the increased landslide resistance of a slope due to vegetation. The
properties of the soil-root composite were measured in laboratory and, from these results, calculation andgraphically based evaluation was used to determine their qualities for resisting landslide. The results show thatvegetation roots had a stabilizing effect on the slope, limited to the rooting depth. Knowing the rooting depth(generally between 0.5 and 1.5 m) and dependent on the species, a correlation between the ratio of root weight tosoil weight and the slope ability to resist landslide was implied from experimental results and a hypotheticaldesign chart and equation were derived.
Keywords: Geotechnical Engineering, Slope Stability, Root Weight Ratio, Root Reinforcement, EcologicalEngineering

Whitlow (2006) defines translational failure as„linear movement along a bedding plane or a soil
layer lying near to the (sloping) surface. Suchmovements are normally fairly shallow and parallelto the surface‟.
It is important to understand the ways in whichsoil and vegetation interact in order to be able toassess the safety of a slope to prevent humancasualties and economic losses.

INTRODUCTION
Slope stability is an important aspect of the built
and natural environment. Slope failures andlandslides can have a significant human andmonetary cost. Understanding and preventing thesefailures is an important facet of environmental civilengineering and the contribution of vegetation
towards increasing slope stability.
The use of vegetation to stabilise slopes is apractice which has been used throughout the world.
This form of slope stabilisation has been describedas „Ecological Engineering‟ and defined as „thedesign of sustainable ecosystems that integrate
human society with its natural environment for the
benefit of both‟ (Mitsch, 1998). It is seen as a „soft‟engineering approach when compared to traditional,„hard‟, methods of slope stabilisation, for example;
soil nails, anchors, meshes, retaining walls, slope
geometry modification etc. This, „soft‟, approach
offers many benefits such as increasing biodiversity,
self-sustainability, cost effectiveness and visual
aesthetics while being environmentally friendly(Mitsch, 1998).
. There are two types of slope, natural andartificial (Gray & Sotir, 1996).
Natural slopes are formed over time throughgeological and geomorphic processes, for example;
mountain forming, river activity, glacial and tidal
activity. These slopes are only stable if the soil ofwhich they are constructed has sufficient strength toresist the gravitational forces exerted on the potential
sliding mass.
Artificial slopes or earthworks are either cut into
the ground (soil or rock) or built up as in spoil
heaps, waste tips or embankments. Cut slopes andcuttings are made to provide access for infrastructuresuch as train tracks, roads, canals, etc .

VEGETATION BENEFITS FOR A SLOPE OVERVIEW
Freer (1990) comments that „…the mostimportant and general problem is a shallow seatedinstability of a slope‟. He goes on to say that this is
at a depth of around 0.5-2m below the groundsurface and that this is in fact the most widespread
form of slope failure particularly in cuttings andembankments.
It can also be seen that vegetation roots anchor
the vegetation and provide reinforcement of soil.
Factor of safety of unrooted and rooted soils
Danjon et al (2007) studied the effect on slope
stability of two White Oak (Quercus Alba) trees.
The findings of their research say that depending on
the potential slip surface, the factor of safety (FOS)
varied from 2.8-3.7 and 1.8-2.0 for unrooted soil.
When the mean value of the FOS increased
significantly for surface depths of 0.3m, however as
distance progresses to a depth of 1.2m these benefits
diminish.
According to Whitlow (2006), the factor ofsafety for a slope may be calculated using the„infinite slope model‟. This formula is shown below.

56

GEOMATE- Brisbane, Nov. 19-21, 2014()

finding the ratio of root area to soil area. In the caseof grass it was decided that this would be extremely
time consuming/ difficult to record accurate
measurements. Instead, the RWR (the weight of thevegetation mass within the sample against theweight of the sample as a whole) would be measured
in an effort to see if this is an adequate substitute for
RAR in the instance of grass.
The soil was determined by inspection to be„topsoil‟/ „organic‟ and by sieve test to be a „well
graded sandy soil‟. The moisture content was also
assessed. After each sample of rooted soil had beentested in the shear box, the superficial vegetation
was removed and it was washed in a 1.18mm sievefrom the sieve test rig. This particular sieve size wasselected in order to allow finer soil material to passthrough its apertures retaining any organic material.
The remaining vegetation was allowed to dry in thelaboratory. By comparing the weight of the driedroots against the original weight of the sample, theRWR was found and this could be compared against
the shear strength found for that sample.

Where: C‟- apparent cohesion of the soil
(kN/m2); Z – depth to shear plane (m); H – height ofground water level above shear plane (m); γ –density of soil (kg/m3); γw – density of water(kg/m3); β – slope angle (⁰); φ‟ – angle of friction (⁰)
Morgan and Rickson (1995) give a modificationof the formula from Whitlow for translational
failure on an infinite slope when including theeffects of vegetation, shown below.

The above formula incorporates four additionalvariables to the F.O.S formula for soil alone. These
are; C‟R – the enhanced shear strength due to roots(kN/m2), T- tensile root force acting at the base of
the shear plane (kN/m), W – surcharge of thevegetation (kN/m2) and D – wind loading parallel tothe slope (kN/m). By adding these factors into theformula a F.O.S for soil including roots can be found.
The authors comment that the most importantvariables in improving slope factor of safety are theenhanced shear strength and the tensile root force.

RESULTS AND ANALYSIS
Direct shear testing of the soil without vegetation
By plotting the results of the shear test, shear stressover normal stress, the apparent cohesion of the soil
was found to be, C‟ = 10kN/m2 and the peak angleof friction, φ‟ = 16⁰.

EXPERIMENTAL WORK
It was decided that the direct shear test would be themost appropriate testing equipment to evaluate an
improvement in resistance to translational failure
due to root (vegetation) presence.
The direct shear test, measures normal and shear
stresses directly on the failure plane. The shear box
has dimensions: 60x60x25mm The soil sample wascut/ extracted using a core cutter and placed inside
the box. Samples of grass were extracted from thein-situ site using a core cutter of dimensions
60x60x25mm, this was pressed into the box. Testing
was carried out according to BS 1377, 1990
In order to ascertain the cohesive strength (C‟) ofsoil alone and the pseudo-cohesion (C‟R) added byroots, incremental values of normal stress of 25.89,
39.51 and 53.14 kPa were applied to the samples. By
comparison of these normal stress values against thevalues of shear stress obtained from the tests, graphs
which showed the cohesive strength, C‟, and theangle of friction, φ, of the soil could be produced.
Shear tests for each value of normal stress werecarried out. The author was determined to evaluate
whether the mass of vegetation within a sample
would correlate to the increase in shear strength (ΔS)
observed (if any) within the same sample. This root
weight to soil ratio, „root weight ratio‟ (RWR), is notstrictly the same as the „root area ratio‟ (RAR), the
RAR is calculated by taking the diameter of all roots(generally larger roots, such as tree/ shrub roots) and

Slope Factor of Safety for unrooted soil
The factor of safety for the soil was calculated froma formula described in Whitlow (2006)
F.O.S =
Apparent cohesion, C‟ = 10kN/m2 – Experimental
result; Peak angle of friction, φ‟ =16⁰ - Experimental
result; Density of soil, γ= 10.6kN/m3 – Experimental
result; Depth to shear plane, z= 0.1 – 0.5m. This
range of depths was chosen as according to Wu et al(1979), „...maximum depth of roots of grass andforbs in temperate zones is usually no greater than
0.5‟. Therefore below this depth any slip plane will
be subject to the shear apparent cohesion and peakangle of friction of the soil alone; Density of water,γw = 9.81kN/m3; Height of water table, h = 0.5m –This was chosen as a worst case scenario to give thelowest factor of safety possible for completely
saturated conditions.
Angle of slope, β = 45⁰ - This was chosen as it is
the upper limit of slope angle for the equation.
Additionally, any slopes built of greater angles
would likely use other technologies, for example
geotextiles (Morgan et al, 1995).
F.O.S calculations are plotted below.
Direct shear testing57

GEOMATE- Brisbane, Nov. 19-21, 2014

values over depth from a graph of similar grasses(Baets et al, 2008).

Figure, shows the variation of the apparent cohesion,C‟ = 20kN/m2 and peak angle of friction, φ‟ = 21.8⁰.
So, the apparent cohesion due to roots, C‟R = C‟(roots and soil) – C‟(soil alone),C‟ = 20-10 = 10kN/m2.
In the case of vegetated soil, a modified versionof the “drained infinite slope model” formula wasused. This formula is from Morgan et al (1995) .
Experimental results: Apparent cohesion, C‟ =10kN/m2 ; Apparent cohesion due to roots, C‟R =10kN/m2;Density of soil, γ = 10.6kN/m3.
Depth to shear plane, z = 0.5m ; Density of water,γw = 9.81kN/m3; Depth of water table, hv = 0.5m.
Assumptions: Surcharge of vegetation, W = 0
kN/m2; Angle of slope, β = 45⁰ - Chosen to keep
consistency with calculation; Tensile root force, T =9.34x10-3kN ; Angle between roots and slip plane, θ= 45⁰; Wind loading force, D = 0k N/m.

Fig. 1 – Comparison of RAR with Depth
Root Weight Ratio (RWR)
After testing, the rooted soil samples were
washed clean of soil and the remaining roots dried
and weighed. The ratio of the weight of the dry roots
to the weight of the initial soil mass was calculated
this was compared with the shear strength found by
testing for each sample. The results of this test are
shown in figure 2.

Assumptions: The weight of the surface
vegetation and its subsequent normal force on thesoil are quantified as „W‟, the surcharge. This
surcharge is included in the calculation primarily
due to the plausibly high force exerted on soils bytrees, in this instance „W‟ has been assumed to be
zero as the surcharge exerted by grass is likely to bevery small and of little consequence.
The tensile root force for the grass used
experimentally was not tested. This testing would
require specialized equipment that was unavailable.
As a substitute for this, a value for tensile root force
from a similar grass was used. This value was takenfrom Hengchaonovich (2003) for a similar grass,„common centipede grass‟, as 5 kN/m.
The Wind loading force, „D‟, is chiefly
concerned with the effect of „wind throw‟. In thecase of grass, the surface area upon which wind canact is small in comparison to trees, additionallygrasses tend to be flexible and unlikely to transfer agreat deal of force to the roots.
Angle between roots and slip plane, θ, has beentaken to be equal to that of the slope angle, β, as it
was assumed that roots had grown in a gravitropic
manner.
Root area ratio (RAR) modification
Root area ratio is not uniform throughout its
depth. Instead there is a tendency for RAR todecrease non-linearly to zero between the surface
and its lowest depth. In order to account for thistransition between soil with additional root cohesion,
C‟R, and soil with soil cohesion alone, C‟, the C‟R
value has been factored down with depth according
to a chart of root area ratio. Based on Figure 1, an
average line was calculated and drawn in order tofind suitable reduction factors to take depth into
account. Figure 1 was created by averaging RAR

Fig. 2 RWR Results TableDISCUSSION
Soil properties
The in-situ soil was determined to have a densityof 1106.25kg/m3 and a moisture content of 33%.
The soil was classified as „well graded sandy soil‟ inaccordance with the British Classification System
for Engineering Purposes and visually identified as„topsoil‟ / „organics‟. All results and findings are
only valid for these soil parameters pending further
research.
Shear strength and angle of friction
It can be seen from the shear test results of both
unrooted and rooted soils that the individual samples
yielded varying results. This variation in results
could be attributed to the non-uniform nature ofdifferent samples in terms of soil composition and in
the case of rooted soils, root mass. When the resultsfor each value of normal stress were averaged they
produced values which gave linear lines withupward trends when graphed. This would be
expected from soil samples subjected to increasing
values of normal stress as increased loading would
create greater compaction of the sample and58

GEOMATE- Brisbane, Nov. 19-21, 2014

therefore greater friction between particles/ roots
and soil across the imposed shear plane.
The unrooted soil produced average values ofshear strength of 18.33, 24.72 and 27.59kN/m2 fornormal stresses of 25.89, 39.51 and 53.14kN/m2
respectively. The rooted soil produced shear strength
values of 30.09, 34.81 and 41.02kN/m2 for normal
stress values of 25.89, 39.51 and 53.14kN/m2
respectively. When graphed, this showed that theapparent cohesion, c‟, of unrooted soil was 10kN/m2
and of rooted soil, 20kN/m2, this apparent cohesion
occurs under a normal stress value of 0kN/m2 and isindicative of the strength of an unloaded soil. This
indicates that the apparent cohesion due to roots,
C‟R, for this particular grass is equal to 10kN/m2, atleast for the root mass found at 0.125mm below thesurface. From these results we see that the apparent
cohesion of the soil has doubled due to the presenceof roots.

should be applied to the slope would be that ofgravity and so the C‟ and C‟ + C‟R values of
unrooted and rooted soils are the most importantvalues in this graph.
In figure 4, a comparison of factors of safety has
been created for unrooted and rooted soil. We cansee that the F.O.S for both soils decreases with depth,
this would be expected as with additional depth, thehorizontal force of a soil mass due to increasing area
will increase, lowering its stability. We also see thatwith increasing depth the F.O.S of rooted soil
reduces until at 0.5m it reaches the same value asrooted soil. This would be expected as due to the
RAR modification applied to the rooted soil factorof safety formula, C‟R decreases from 0.84 to 0
between 0.1m and 0.5m depth. This shows that any
increased F.O.S due to roots can only exist whereroots are present in the soil and is dependent on theirdensity at that depth.
Since the soil type used in the experiment has
yielded apparent cohesion values C‟ and C‟R, of
10kN/m2 and 10kN/m2 respectively and given that
calculated factors of safety have been high, a graphhas been produced in which the apparent cohesion,C‟, of the soil has been reduced from 10 to 0 kN/m2
whilst keeping the apparent cohesion due to roots at
10kN/m2. An assumption has been made inmaintaining the C‟R value at 10kN/m2, this assumes
that the vegetation will grow in a similar manner andto a similar density with depth as that of the soil
used experimentally. The object of this comparison
is to find the properties of a soil that may be
improved to a useable standard by the vegetation
used in this experiment. The slope angle used in thiscomparison will be 45⁰ with a depth of 0.3m.

Fig. 3 - Comparison of Shear stress over normal
stress for unrooted and rooted soils.
Figure 3 demonstrates the comparison of rooted andunrooted soils, it can be seen that shear stress overnormal stress rises linearly with what would appear
to be a constant difference in shear stress of
10kN/m2. This can be attributed to the presence ofroots in the rooted soil samples.
Slope factor of safety

Fig. 5 Factor of Safety over Shear Stress for
Rooted and Rootless soil.
In Figure 5, a comparison of the factor of safety
for unrooted and rooted soil whilst lowering theapparent cohesion, C‟, of the soil and keeping theapparent cohesion due to roots, C‟R, constant ispresented. In this diagram we see that in order tokeep a factor of safety for slope stability above 1.5, avalue of apparent cohesion, C‟, of around 2.2kN/m2
is required for unrooted soil. The factor of safety at
this point for a soil rooted with the same vegetation

Fig. 4 Slope Factor of Safety over Depth forrooted and rootless soil.
Since a vegetated slope would require to beunobstructed on its surface so that sunlight may
reach the vegetation, the only normal stress which
59

GEOMATE- Brisbane, Nov. 19-21, 2014

used in the previous experiments was around 5.

cannot continue linearly as it would cross the RWRaxis at roughly 16-17(%). This would indicate thatwhen RWR is equal to 16-17%, shear stress is zero.
This cannot be true as the shear stress of the soil
alone is 18.33kN/m2 under a normal load of
26.89kN/m2.

Root weight ratio (RWR)
From laboratory experimentation, a positive
correlation between RWR and shear strength was
found and shown on figure 6. Sample 1 had a RWR
of 21.045% and a shear strength value of
30.83kN/m2, Sample 2 had a RWR of 20.593% anda Cu of 27.5kN/m2 and Sample 3 had a RWR of
21.176% and a Cu of 31.94kN/m2. Other samples
exhibited this relationship however due to the
problem of weight variance, the set of results fornormal testing of 25.89kN/m2 have been selected forfurther discussion as these results used samples withthe smallest weight variance. To investigate thisfurther, the relationship between RWR and Shear
Stress was plotted along with the average shear
stress of soil for the same normal stress, 18.33kN/m2.

Assumed polynomial curve
In figure 7 an assumed curve has been plottedbased on the assumptions. This curve increases
linearly before tending to a limit.
In an attempt to describe/ plot the hypotheticalcurve shown in figure 7, a polynomial equation wasused. This equation was of a degree of three as there
were four points and is shown below.
Solving for a, b, c and d respectively, an
equation to describe the curve was attempted to befound. Unfortunately due to the lack of data forsamples with RWR greater than 1 and less than
20.593% this produced an unsatisfactory curve withnegative values.
In order to produce a satisfactory curve, three
additional points were plotted on the hypotheticalcurve and these were used to create a formula which
accurately described the hypothetical curve. The
points were applied at RWR‟s of 5, 10, 15% andyielded approximate shear stress values of 19.5, 21
and 22.5kN/m2 respectively. Once applied to thegraph, a polynomial curve was drawn and an
equation describing the curve derived.

Fig. 6 – Shear Strength over RWR
Figure 7 shows the increase in shear stress from thefirst point, unrooted soil (e.g. 0% RWR) to the later
three rooted soil points. The black line indicates thetrend of the rooted soil points, this trend appears to
be linear and as no greater values of RWR were
found during the experiments, only assumptions canbe made. An assumption would be that the RWR(%) in a soil must tend to an upper limit. The
samples of rooted grass were from a mature lawn
which has had over ten years of growing time,perhaps for this grass type and possibly the soil
conditions present, values of RWR(%) will not
exceed approximately 23-25% as this may be a limit.
Since there appears to be a correlation between
RWR and shear stress, an assumption would be thatbetween values of RWR of 0 and 21.176% (thehighest value), shear strength must rise in apolynomial curve, the data points of which areplotted in figure 7.
The reasoning behind this assumption is basedon two main facts evidenced by the experimental
results:
A RWR of 0% must be equal to 18.33kN/m2 as thisis the shear stress of the soil itself under a normalload of 26.89kN/m2. The trend line in figure 7

Modified C’R +C’ over RWR graph.
Fig. 7 – Shear Strength over RWR
The derived equation:

When modified to replace the axis denotations wearrive at a hypothetical formula to obtain shear
strength from root weight ratio, shown below:“Total apparent cohesion (C‟R + C‟) over root60

GEOMATE- Brisbane, Nov. 19-21, 2014

weight ratio (RWR) equation.”
For values of C‟R+C‟ in kN/m2, RWR in percent(%) and where C‟ = 18.331 kN/m2

results strongly suggested a correlation between
RWR and C‟R.
Criticisms that could be made of the hypotheticalformula include the fact that only one soil type/grass type was tested, low amount of data used toplot graphs and the assumptions made. Further
research would be required to validate the results
found in this research.

CONCLUSIONS
The aim of this project was to investigate therelationship between vegetation and slope stability
in order to assess its benefits and to investigate
whether a relationship between RWR and shear
strength existed. The key findings of the project are
discussed in the following sections.
Laboratory experiments have confirmed thatvegetation roots increase the shear resistance, angleof friction and therefore the F.O.S of a soil however
this increase is not uniform with depth. For the soil
used in the experiments, vegetation was shown to
improve the F.O.S by 75% at a depth of 0.1m
however this diminished to 0% by 0.5m. It has been
seen that, depending on the species of vegetation,roots may not grow to a depth below the shear plane,
rendering them ineffective in slope stabilisation. Dueto this, shear plane depth and root growth depth
should be a major consideration when using
vegetation to stabilise a slope. The grass tested inthis project, could not be used to stabilise any slopes
with shear planes deeper than 0.4m but could
perhaps be useful if used in conjunction with othervegetation.
Work by Danjon (2007) discussed how areas of
reduced ΔS, increased shear strength due to roots,
could occur between trees stabilising a slope.
Perhaps the grass used in this dissertation or asimilar variety could be used to improve ΔS between
trees to stop localised failures. Research by Norris(2008) and Huat and Kazemian (2010) discussed
how artificially planting „live stakes‟ on a slope at
depths of up to two meters has been shown to be aneffective form of stabilisation. This method isparticularly attractive as it provides immediatestabilisation and can be planted at a depth of up to
2m which is greater than most vegetation roots can
grow. This method is also easier to understand andmodel when compared to a root mass as the „live
stakes‟ act in a similar manner to soil nails.

REFERENCES
Baets et al, 2008. Root tensile strength and root
distribution of typical Mediterranean plant species
and their contribution to soil shear strength. Plant
and Soil. 305(1-2)
Danjon, F.,2007. Using Three-dimensional Plant
Root Architecture in Models of Shallow-slope
Stability. Annals of Botany. 101 (8).
Denzin, N. and Lincoln, Y., 2005. The SAGE
handbook of qualitative research. 3rd ed. Sage
Publications.
Head, K.H., 2011, Manual of soil laboratory
testing, Volume 2, Permeability, shear strength ancompressibility tests. 3rd ed. John Wiley & Sons
Freer, R., 1990. Bio-engineering: the use ofvegetation in civil engineering. Construction and
Building Materials. 5(1)Huat, B.K., and Kazemian, S., 2010. Study of
Root Theories in Green Tropical Slope Stability.
The Electronic Journal of Geotechnical Engineering.
15.
Hytiris N., Kapellakis I.E., De la Roij R and
Tsagarakis K.P. “The Use of Olive Oil Residue in
Solidification Process”. Resources Conservation andRecycling Journal 2 January 2004, p 129-139.
Morgan, R. and Rickson, R., 1995. Slopestabilisation and erosion control. 1st ed. Taylor &Francis.
Mickovski, S. B., Stokes, A., van Beek, L. P. H.,
Ghestem, M. and Fourcaud, T. 2011. Simulation of
direct shear tests on rooted and non-rooted soil using
Finite Element analysis. Ecological Engineering, 37(10): 1523-1532.
Mickovski, S.B., Bransby, M.F., Bengough, A.G.,
Davies, M.C.R., Hallett, P.D. 2010. The resistanceof simple plant root systems to uplift loads.
Canadian Geotech. Journal 47(1), 78-95.
Mickovski S. B. and van Beek L. P. H. 2009.
Root morphology and effects on soil reinforcement
and slope stability of young vetiver (Vetiveria
zizanioides) plants grown in semi-arid climate. Plant
and Soil 324 (1-2 ): 43-56.
Whitlow R. “Basic Soil Mechanics fifth edition
Pearson education. (2006)
Wu, T. H., 2007. Root reinforcement: analyses
and experiments. Developments in Plant and Soil
Sciences. 103 (21-30).

Root weight ratio (RWR)
The RAR of roots in a soil mass was found to beof great importance as this diminished with depth
and correlated with C‟R. The RAR with depth varied
between vegetation species and this would have to
be considered in order to create an effective„Ecological Engineering‟ slope stability solution.
The difficulty of measuring RAR for grasses was
discussed as being difficult due to the small natureof grass root diameter (centipede grass roots
averaged 0.66mm in diameter). For this reason, it
was decided to see whether the RWR would be anadequate substitute.
When using samples of a similar weight, the61Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SMALL SCALE FIELD TESTS OF WATER INFILTRATION FORCOMPACTED SILTY LOESS SOIL
Aiassa Martínez Gonzalo1, Arrúa Pedro2 and Eberhardt Marcelo3
Facultad Regional Córdoba, Universidad Tecnológica Nacional, Argentina

1,2,3

ABSTRACT
Silty loess soils are widely spread on Córdoba city, Argentina. The ability to use this soil improved bycompaction on embankments it is of interest to different types of local constructions, with purpose of reducing
settlements and infiltration. This work research the water infiltration through compacted silty soils from Córdoba
by small scale field test. Four small test embankments were constructed on natural soil with different compaction
conditions using local silty soils. The site was characterized by typical geotechnical laboratory and field tests.
The infiltration tests were performed using double ring infiltrometers for a time period around of 2 months.
Results were used to field permeability estimated (k f ) and these were compared with laboratory results (k l ).
Conclusions regarding the behavior observed in the field are presented.
Keywords: Embankment Test, Double Ring Infiltrometers, Site Investigation, Córdoba Soil

INTRODUCTION

MATERIAL AND METHOD

Compacted soils are frequently used for different
engineering project. Soils excavated from nearest
works may be utilized for embankment construction.
This is an economic and sustainable alternative, butdata are needed to characterize the mechanical andhydraulic performance of the material. Lagoons andother waterworks, require barrier systems generally
include layers of compacted soil. In these cases it isof interest to determine the infiltration of water.
Permeability tests are generally performed on
samples in laboratory compaction molds, orundisturbed samples. However, these tests do nottake into account possible effects of scale which canbe noticed through large-scale laboratory [1] or fieldtest [2], [3], [4]. The study presented in [5] explores,by laboratory and field test, the possibility uses ofsilty soil as landfill liner material. A test pad wasconstructed in field using different soil compositionand different compaction effort. Sealed double ring
infiltrometers were employed to hydraulicconductivity determination. Differences between the
results of hydraulic conductivity obtained fromlaboratory and field were found. Laboratory values
were lower [5].
This work research the field water infiltration
through compacted silty soils from Córdoba [6], [7],[8]. Four small test embankments were constructedon natural soil with different compaction conditions
using local silty soils. The site was characterized bytypical geotechnical laboratory and field tests. The
infiltration tests were performed using double ring
infiltrometers. The results show the effect of scalecompared with previous laboratory data on thesesoils, and the effect on field compaction conditions.

Soil used in laboratory and field experiments wasa silty loess from Cordoba. The Table 1 reports
principal properties.
Table 1 Properties of liner soil
Properties
Unit
Value
Liquid limit%
26.7
Plasticity index%
4.3
Fines (<0.074mm)%
97
Fraction <0.002mm%
5Specific gravity
2.67
Class (ASTM D2487)
ML
Max dry unit weight
kN/m3
16.8
Optimal water content%
19
Note: max dry unit weight and optimal water content
are for Standard Proctor (ASTM D698).
For field infiltration test a small probe fills wasconstructed in the Universidad Tecnológica
Nacional campus located on City Southern Cordoba
City. The selected site was gated. The position ofeach cell was set and then excavations were
undertaken (Fig. 1). For the excavation, a dimension
plan of 1 m by 1 m was adopted and 0.55 m inthickness.
Soils excavations were scrapped because thesecontained many roots. Silty local materials wereused, in depths of 3-5 m, in order to avoid impurities(Table 1), and prepared carefully to remove clods
and mix well with added water. The construction of
the cells was performed under controlled compacted
soil layers. Each layer was compacted by dynamic
62

GEOMATE- Brisbane, Nov. 19-21, 2014

impacts. The compaction condition was controlled
by the number of blows applied. Control tests as
DCP (dynamic cone penetrometer) and in place unit
weight were performed (Fig. 2).

double ring infiltrometer. Inner ring of 30 cm
diameter and outer ring of 60 cm were used. The
water level was preserved approximately constantwith a height of 5 cm. During the test progress, awaterproof cover was installed on each cell toprevent from rain event (Fig. 4). Additionally, a
container for controlling evaporation occurred
during the test was used. This determination notintended to provide weather information, it wasmade only for the purpose of correcting the volume
of water infiltrated into the ring.
1

DCP INDEX (mm/blow)
10

100

0
CELL 1
CELL 220

Fig. 1

Depth (cm)

CELL 3

Construction stage.

CELL 440
60
80

INNER RING

OUTER RING
DA

DD

Fig. 3

DE

DE

DC

100

DA

DD

DC

DB

Infiltration tests were conducted at the site on thenatural soil without compacting, in order to assess
the influence of compaction. For this, the rings were
installed on a prepared surface where it wasremoved coverage of grass and roots.

DB

CELL 2

CELL 1GRASS

DCP TEST POINT

DA

DD

DC

DA

DD

DE

DCP test results.

DE

DB

CELL 3DC

DB

CELL 4SCALE: 1.0 m

Fig. 2

Location sketch of cell.

Results of in place unit weight test were 13.3
kN/m3 (Cell 1), 15.8 kN/m3 (Cell 2), 14.5 kN/m3(Cell 3), 15.2 kN/m3 (Cell 4). Relating to Standard
Proctor the relative compaction were 79% (Cell 1),
94% (Cell 2), 86% (Cell 3), 90% (Cell 4). These
values can be easily achieved in construction
practice. Figure 3 shows DCP test results. Generally,a first surface layer of 5 cm with relatively low
compaction is observed, then the embankment witha thickness of approximately 50 cm, followed by alayer of compacted natural soil to 65 or 70 cm deep.
Finally, natural soil not affected by compaction, witha DCP index of 30 mm/blow is detected.
The infiltration tests were performed using

Fig. 4

Test in progress.

RESULTS AND ANALYSIS
Measurements of water infiltration into thenatural silty soil are shown in Fig. 5. To analyze theresults the infiltration rate (I r ) is adopted. Eq. (1)presents the formulation for field infiltration rate
calculation.

63

GEOMATE- Brisbane, Nov. 19-21, 2014

ΔV ( t )Ir =Δt ⋅ A

Concerning results of laboratory tests on samples
compacted under similar conditions can be observedthat in field values are similar without a clear scaleeffect.

(1)

Where ∆V: volume infiltrate during time ∆t, A:
inner ring area.
For natural silty soil the Ir results 2×10-6 m/s.
This value characterizes the material located beneaththe cells with compacted soil.
In the case of the compacted soil a correction
was made for the infiltrate water, due the long test
duration, and consequently the evaporation effect.
Fig. 6 shows results of evaporation control test. In
simplified form, a constant correction factor of 5.2
mm/day was adopted.

η=

CELL 1
CELL 2
CELL 3
CELL 4

Infiltration (cm)

100
80
60
40
20

4
Infiltration (cm)

(2)

120

5

0

3

0

10

20

30
40
Time (day)

50

60

70

2

Fig. 7

Test 1
Test 2

1

Field infiltration test on compacted silty
soil.

CONCLUSION002

Fig. 5

4Time (hs)68

In this paper, an experimental study of field
infiltration tests on small silty soil compacted
embankments is presented. The embankments wereprepared under controlled compaction conditions.
Cells were protected from the rain and the effect ofwater evaporation was contemplated due to the longtest duration.
Compaction provides improved hydraulicperformance, considerably reducing the rate of
infiltration respect the natural soil. The condition ofcompaction affected the results. The greater relative
compaction (Cell 2) determined the lowest
cumulative infiltration, while the cell with lower
relative compaction (Cell 1) presented the highest
cumulative infiltration. Field results were similar toavailable laboratory compaction by similar
conditions.
Despite soil compaction, the infiltration rate may
be high for many project.
It could increase the relative compaction orincorporate some added material in order to attempt
to reduce the infiltration rate. However, this work is
one of the few local experiences with field
infiltration tests on compacted silty soil. So, moreembankments tests are needed in order to reachconclusions of general behavior.

Field infiltration test on natural silty soil.

600
500

Evaporation (mm)

I r1
Ir 2

400
300
200
100
0
0

Fig. 620

40
60Time (day)

80

100

Evaporation control test.

Fig. 7 shows corrected results of field infiltration
test from cells. For compacted silty soil the Ir results
2.0×10-7 m/s (Cell 1), 9.8×10-8 m/s (Cell 2), 2.4×10-7
m/s (Cell 3), 1.7×10-7 m/s (Cell 4).
The comparison of results is performed by afactor relating infiltration rate of two cases (Eq. 2).
Thus, η results 2.4 for cells 2 and 1. Comparing
natural silty soil relative to the improvement bycompaction, values for η between 8 to 20.

ACKNOWLEDGEMENTS
The authors thanks the support of Universidad

64

GEOMATE- Brisbane, Nov. 19-21, 2014

Tecnológica Nacional Facultad Regional Córdoba,
Ministerio de Ciencia y Tecnología, Gobierno de laProvincia de Córdoba (PID-GRF), and FONCyT
Agencia Nacional de Promoción Científica yTecnológica (PICT).

Engineering, Vol. 125, No. 5, May 1999, pp.
390–403.
[5] Bozbey I and Guler E, “Laboratory and fieldtesting for utilization of an excavated soil as
landfill liner material”, Waste Management,
Vol. 26, 2006, pp. 1277–1286.
[6] Arrúa P, Aiassa G., Eberhardt M and Alercia
Biga C, “Behavior of collapsible loessic soil
after interparticle cementation”, International J.
of GEOMATE, Vol. 1, November-December
2011, pp. 130–135.
[7] Aiassa G. and Arrúa P, “Desempeño de barreras
sanitarias
simplesdesueloloéssicocompactado”, Revista Tecnología y Ciencia,
Año 8, Noviembre 2009, pp. 26–40.
[8] Aiassa G, Zeballos M, Arrúa P and Terzariol R,“Infiltración en suelos limosos compactados”,
XIX Congreso Argentino de Mecánica deSuelos e Ingeniería Geotécnica, Octubre 2008,
La Plata, Argentina.

REFERENCES[1] Shackelford CD and Javed F, “Large-scalelaboratory permeability testing of a compacted
clay soil”, Geotehnical Testing J., Vol. 14, No.
2, June 1991, pp. 171–179.
[2] Stewart JP and Nolan TW, “Infiltration testingfor hydraulic conductivity of soil liners”,
Geotehnical Testing J., Vol. 10, No. 2, June
1987, pp. 41–50.
[3] Sai JO and Anderson DC, “Field hydraulicconductivity tests for compacted soil liners”,
Geotehnical Testing J., Vol. 13, No. 3,
September 1990, pp. 215–225.
[4] Benson CH, Daniel DE and Boutwell GP,“Field performance of compacted clay liners”, J.
of Geotechnical andGeoenvironmental

65Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

METHOD FOR HAZARD ASSESSMENT OF SLOPE FAILURES
BASED ON INFORMATION PROCESSING TECHNIQUES
Shinichi Ito1, Kazuhiro Oda2, Keigo Koizumi3, Kyohei Umemura4, and Yohei Usuki5
1,2,3,4,5
Osaka University, Japan

ABSTRACT
Recently, the sediment disasters, such as slope failures, debris flows, landslides and so forth, caused by typhoonor cloudburst have occurred somewhere in Japan. The progression of global warming will increase the scale oftyphoons and cloudbursts striking the Japanese Islands, so that it is a concern that the frequency of occurrence of
sediment disasters may increase. Thus, it is necessary to identify the slopes with higher hazard to sediment disasters
in order to establish disaster prevention planning. In this study, a method based on information processing
techniques is proposed. In the proposed method, self-organizing map (SOM), cluster analysis, and Hayashi’s
second method of quantification are combined. The proposed method and only Hayashi’s second method ofquantification are applied to the periodical inspection data. As a result, the availability of the proposed method is
confirmed by comparing the results of proposed method with only Hayashi’s second method of quantification.
Keywords: Sediment disasters, Self-organizing map (SOM), Hayashi’s second method of quantification, Cluster
analysisso that artificial neural networks, mathematicalstatistics and so forth should be applied as analyticalmethods.
In this paper, a method that can identify the slopes
with higher hazard to sediment disasters is proposed.
In the proposed method, self-organizing map (SOM)[3], which is one of the artificial neural network
techniques, and cluster analysis [4], which is one of
the mathematical statistics, and Hayashi’s second
method of quantification [5], which is a quality
determination method are combined.
In this study, the proposed method are applied tothe periodical inspection data of slopes in order to
identify the slopes with higher hazard to sedimentdisasters. Also, only Hayashi’s second method ofquantification is applied to the periodical inspection
data of slopes. The purpose of this study is to confirm
the availability of the proposed method by comparing
two results that are from the proposed method withfrom only Hayashi’s second method of quantification.

INTRODUCTION
In Japan, where mountainous districts occupy
70 % of land, the sediment disasters, such as slope
failures, debris flows, landslides and so forth, haveoccurred each year. Due to the progression of global
warming, the intensity of rainfalls brought by thetyphoons and cloudburst have become more severe,so the number of occurrences of the sedimentdisasters in Japan have also increased as shown in Fig.
1 [1]. Therefore, disaster prevention planning for the
sediment disasters should be established. However,there are innumerable slopes in Japan, and there arelimits to time and costs, so that it is difficult to
examine all the slopes. Thus, first of all, it isimportant to identify the slopes with higher hazard to
sediment disasters.
There are endogenous factors and exogenous
factors of the sediment disasters. The endogenous
factors mean the characteristics of the slopes, such as
topographical features, geological features and soforth. The exogenous factors mean the trigger of thesediment disasters, such as rainfall, earthquake and soforth. It is difficult to forecast when, where, and how
much rainfalls will be expected, so that it is useful toidentify the slopes with higher hazard to sedimentdisasters based on the endogenous factors. In Japan,
the detailed, periodical inspection [2] is performed inorder to prevent future disasters. Therefore, a method
for analyzing the characteristics of the slopes as easily
and effectively as possible from the periodical
inspection data in order to identify the slopes withhigher hazard to sediment disasters is necessary. The
method should be able to treat a large number of data,

Fig. 1 Number of occurrences ofsediment disasters in Japan66

GEOMATE- Brisbane, Nov. 19-21, 2014

fitted as shown in Fig. 4. However, if the right numberof clusters are applied to cluster analysis, theanalytical results of SOM and cluster analysis are
fitted as shown in Fig. 5.

ANALYTICAL METHOD
Self-organizing map (SOM)
SOM is one of the artificial neural network
techniques. The SOM is known to be an effective
technique for analyzing high-dimensional data. In
other words, high-dimensional vectors can be mapped
to two dimensional space for visual understanding.
The two-dimensional representation can then be used
to observe patterns and correlations present in highdimensional data. In addition, vectors with similar
characteristics are placed closer on the twodimensional map and dissimilar vectors are locatedfarther apart. Therefore, in the case where SOM isapplied to high-dimensional vectors, they can beclassified into several clusters automatically. Fig. 2
shows an example of an analytical result of SOM.
There are several parts with light gray color. Some
vectors gather at each light gray part. That is, a set ofsome vectors gathering at a light gray part is a cluster.
However, SOM has a disadvantage. It is difficult
to cluster high-dimensional vectors into several
groups objectively. For example, from the result of
Fig. 2, some users may cluster them into five groups
surrounded with white circles as shown in Fig. 3. On
the other hand, another users may cluster them into
different five groups surrounded with black circles.
The subjective judgment of the users controls theclustering based on visual mapping.

Fig. 2 An example of analytical result of SOM

Fig.3 Different clusters of SOM
by individual difference

Cluster analysis
A cluster analysis is one of the representativetechniques in the mathematical statistics. It can divide
objectively a set of high-dimensional vectors into
several clusters which is fixed previously according
to the similarity among the high-dimensional vectors.
However, the cluster analysis also has a disadvantage.
It is necessary to determine previously the number ofclusters before conducting the cluster analysis. The
number of clusters cannot be determined
automatically unlike SOM. It is difficult to determine
the number of clusters without preliminary analysis.

Fig.4 Analytical result of SOM and cluster analysis
in case of applying wrong number of clusters

Combination of self-organizing map and cluster
analysis
In this paper, both SOM and cluster analysis are
combined in order to overcome two disadvantage
which are objective clustering in SOM anddetermination of the number of clusters. The
analytical process is following. First of all, thenumber of clusters is visually determined by SOM.
Then the number of clusters is applied to cluster
analysis, and the objective clustering is performed.
The results of cluster analysis are plotted on the mapof SOM. If the number of clusters is wrong, theanalytical results of SOM and cluster analysis are not

Fig.5 Analytical result of SOM and cluster analysis
in case of applying right number of clusters
67

GEOMATE- Brisbane, Nov. 19-21, 2014

Hayashi’s second method of quantification

APPLICABLE DATA

Hayashi’s second method of quantification is amethod of mathematical statistics. It is known as arepresentative technique of the quality determination
method. This method treats categorical data andderives dependent variables from an explanatory
variable. In other words, Hayashi’s second method ofquantification can divide one group into two groups.
Therefore, if Hayashi’s second method ofquantification is applied to slopes, the slopes are
estimated to be failed or not failed.

Periodical inspection data
In this study, the periodical inspection data ofslopes are used. The periodical inspection data ofslopes are integrated into the database, so the data will
be stored and increased. Therefore, if the slopes withhigher hazard to slope failures can be identified byusing the data, it is useful for future disasterprevention planning.
The periodical inspection data that the slopes were
inspected in 1996 is used. The data contain 128 slopesof expressway and 89 slopes of national road. There
are 8 failed slopes of expressway and 29 failed slopesof national road in the periodical inspection data.
Table 1 shows the parameters which estimate thehazard of each slopes, and the categorical data
corresponding to each parameters.

Method for identifying slopes with higher hazard
The authors proposed the method for identifying
the slopes with higher hazard to deep-seatedcatastrophic landslides [6]. In this study, the proposed
method are applied to the periodical inspection dataof slopes in order to identify the slopes with higher
hazard to slope failures. Namely, the proposed
method are expected to identify the slopes with higher
hazard to various type of sediment disasters bychanging applicable data. Fig. 6 shows the flowchartof the proposed method. The proposed method has
three stages.
At first stage, only failed slopes are grouped into
several clusters through combination of a SOM and acluster analysis. There are all sorts of failed slopes.
All failed slopes do not necessarily have samecharacteristics. Therefore, the failed slopes aregrouped into several clusters in which the failed
slopes have almost similar characteristic in order toperform effectively following discriminant analysis.
At second stage, Hayashi’s second method ofquantification, one of the representative methods fordiscriminant analysis, can be applied to a set of slopes,
which includes the failed slopes in a cluster and all of
not failed slopes, in order to identify the slopes withhigher hazard to slope failures. The slopes with higher
hazard can be identified in this way.
At third stage, the slopes with higher hazard are
given priority according to the sample score of
Hayashi’s second method of quantification. The
sample score indicates the hazard of the slopes, suchthat the slopes with a higher sample score have ahigher hazard to slope failures. Additionally,
Hayashi’s second method of quantification also givethe score of the boundary between failed slopes andnot failed slopes. In this study, the priority of theslopes was determined by the difference between thesample score and the score of the boundary. In otherwords, the slopes having a higher difference between
the sample score and the score of the boundary are theslopes with the higher hazard.
In this way, the proposed method, which is basedon SOM, cluster analysis, and Hayashi’s second
method of quantification, can identify the slopes withhigher hazard and prioritize the slopes.

Verification method
In this study, the training data and the identity data
are used in order to confirm the availability of
proposed method. Firstly, the periodical inspection
data of slopes are divided into 7 to 3 ratio randomly.
The training data are 70 % of data, and the identify
data are 30 % of slopes. Secondly, the proposed
method and only Hayashi’s second method ofquantification are applied to the training data.
Herewith, the standards, such as the score ofboundary and the categorical scores, that eachparameters are quantified by Hayashi’s second
method of quantification, are established. Finally, theidentify data are applied to each standards, and thenumber of failed slopes in the identify data which are
estimated to failed is calculated. In the case where theproposed method has a high capture efficiency of thefailed slopes which are estimated to failed, theavailability of the proposed method is confirmed.
Failed slopes

First stage
Clustered by SOM and cluster analysis

Secondstage

Hayashi’s second
method of quantification

・・・・・・

Hayashi’s second
method of quantification

Failed slopes in a cluster

・・・・・・

Failed slopes in a cluster

All of NOT failed slopes

・・・・・・All of NOT failed slopes

Third stage

The slopes with higher risk

Fig.6 Method for identifying slopes
with higher hazard
68GEOMATE- Brisbane, Nov. 19-21, 2014

ANALYTICAL RESULTS

Proposed method

Only Hayashi’s second method of quantification

The proposed method were applied to the training
data. At first, only failed slopes were classified into
clusters by SOM and cluster analysis. Fig. 7 shows
the analytical result of combining SOM with cluster
analysis. The analytical result of SOM and cluster
analysis are fitted as shown in Fig.7, so the failed
slopes can be classified into four clusters. The
characteristics of several clusters were checked andthe distribution conditions of the failed slopes in eachclusters in regard to each parameters were shown in
Table 3.
There were 5 failed slopes in cluster 1. All of themwere the slopes of expressway, and almost all of themwere applicable to the parameters which had
relatively lower hazard to slope failures. However,the failed slopes in cluster 1 had high height of slopes.
There were 8 failed slopes in cluster 2. All of themwere applicable to fragile lithology. In addition, there
were more slopes that were applicable to the dip
slopes than cluster 1 and cluster3.
There were 8 failed slopes in cluster 3. All of themwere applicable to fragile soil, and almost all of themwere applicable to fragile lithology. In addition, they
had higher hazard about difference of permeability
and topsoil, loose part rock, boulder stone.
There were 5 failed slopes in cluster 4. All of themwere applicable to highest hazard categories about 4
parameters (talus cone, soil, lithology, formation).
Therefore, the failed slopes in cluster 4 had the higher
hazard to slope failures of the four clusters.
In this study, the characteristics of the failed
slopes could be classified into the four clusters. Thus,
the four clusters and not failed slopes made fourgroups. Namely, cluster 1 and not failed slopes
formed group A, cluster 2 and not failed slopes
formed group B, cluster 3 and not failed slopes
formed group C, cluster 4 and not failed slopes
formed group D. The each groups were then applied
to Hayashi’s second method of quantification, and theanalytical result shown in Table 4.

Only Hayashi’s second method of quantification
were applied to the training data (26 failed slopes and
126 not failed slopes), and the standards, such as thescore of boundary and the categorical score were
established. Table 2 shows the analytical result thatthe identify data (11 failed slopes and 54 not failed
slopes) are applied to the standards. From this result,
8 failed slopes in the identify data were estimated tofailed, but 3 failed slopes in the identify data were
estimated to not failed.

Table 1 Parameters and categorical data
parameters0
1
2 or morestablesoil
mediumfragilestablelithology
mediumfragileopposite slope
formation
dip slopesmall
difference of
mediumpermeability
large
topsoil,stableloose part rock,mediumboulder stone
unstablewithout spring
spring waterleakagespringconstructcovering condition
compoundvegetation, bare land
H＜15
15≦H＜30
height of slopes
30≦H＜5050≦Htalus cone

categorical
data
0
0.5
1
0
0.5
1
0
0.5
1
0
1
0
0.5
1
0
0.5
1
0
0.5
1
0
0.5
1
0
0.333
0.666
1

①
③

②

Table 2 Analytical result of identify data by using
only Hayashi’s second method of quantification

Estimate

FailedNot failed

③

④

Real
FailedNot failed
8
6
3
48

Fig.7 Analytical result of SOM and cluster analysis

69

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 5 shows the final result which is total of
Table 4. The result of Table 5 is difference from theresult which simply add the number of failed slopesin Table 4 because there are some failed slopes
estimated to failed in plural groups. Therefore, Table
5 is the final result which relieve the duplication of
the analytical results. From the result of Table 5, allof the failed slopes in the identify data are estimatedto failed.

Table 3 Distribution conditions of failed slopesin each clusters in regard to each parameters(a) Cluster ①
number of
number ofparametersslopesslopes03
topsoil,stable5talus coneloose part rock,1
2
medium0
boulder stone
2 or more
0unstable0
stable4
without spring1
soil
spring water
medium1
leakage4
fragile0spring0stable5
construct1
covering
lithology
medium0
compound4
condition
fragile0vegetation, bare0
opposite slope
5H＜150
formation
dip slope
015≦H＜300height of slopes
small
530≦H＜503difference of
medium050≦H2permeability
large
0
parameters

Table 4 Analytical results of each groups
by proposed method(a) Group A(b) Cluster ②

Estimate

number of
number ofparametersslopesslopes03
topsoil,stable5talus coneloose part rock,1
2
medium3
boulder stone
2 or more
3
unstable0
stable5
without spring3
soil
spring water
medium3
leakage3
fragile0spring2
stable0construct5
covering
lithology
medium0
compound3
condition
fragile8vegetation, bare0
opposite slope3
H＜15
1
formation
dip slope515≦H＜30
2height of slopessmall
330≦H＜503difference of
medium550≦H
2
permeability
large
0
parameters

FailedNot failed

Real
FailedNot failed
6
2
5
52

(b) Group B

Estimate

FailedNot failed

Real
FailedNot failed
2
8
9
46

(c) Group C(c) Cluster ③
number of
number ofparametersslopesslopes01
topsoil,stable0talus coneloose part rock,1
1
medium5
boulder stone
2 or more
6
unstable3
stable0
without spring3
soil
spring water
medium0
leakage3
fragile8spring2
stable0construct3
covering
lithology
medium1
compound2
condition
fragile7vegetation, bare3
opposite slope
8
H＜15
6
formation
dip slope
015≦H＜30
2height of slopes
small
130≦H＜500difference of
medium650≦H0permeabilitylarge
1parameters

Estimate

FailedNot failed

Failed3
8

Real
Not failed
1539(d) Group D

Estimate

FailedNot failed

Failed3
8

Real
Not failed
054(d) Cluster ④
number of
number ofparametersslopesslopes00
topsoil,stable1talus coneloose part rock,1
0
medium3
boulder stone
2 or more
5
unstable1stable0
without spring2
soil
spring water
medium0
leakage2
fragile5spring1
stable0construct3
covering
lithology
medium0
compound0
condition
fragile5vegetation, bare2
opposite slope0
H＜154
formation
dip slope515≦H＜30
1height of slopes
small
130≦H＜500difference of
medium4
50≦H0permeability
large
0
parameters

Table 5 Final result of proposed method

Estimate

70

FailedNot failed

Failed11
0

Real
Not failed
25
29

GEOMATE- Brisbane, Nov. 19-21, 2014

were applied to the periodical inspection data ofslopes, and only Hayashi’s second method ofquantification were also applied to the data. Then, theavailability of the proposed method was discussed.
The main summarized as follows.
1. SOM, cluster analysis, and Hayashi’s second
method of quantification can be applied to theperiodical inspection data.
2. The failed slopes can be classified into eachclusters objectively by combining SOM andcluster analysis.
3. The slopes can be estimated to failed ones or not
failed ones by using Hayashi’s second method ofquantification.
4. The proposed method can make the slopes into
order according to hazard of sediment disasters.
5. The availability of the proposed method can be
confirmed by comparing the results of proposed
method with only Hayashi’s second method ofquantification.

Discussion
From the results of Table 2 and Table 5, theprecision of the analytical results can be improved byusing the proposed method. In other words, there are
3 failed slopes in the identify data were estimated to
not failed in the case of using only Hayashi’s second
method of quantification, but all of the failed slopesin the identify data are estimated to failed in the caseof using the proposed method. Table 6 shows theresult of the priority of identify data according tohazard by proposed method. The slopes with greycolor shows the slopes which actually failed, and theslopes with white color shows the slopes which
actually not failed. From the result of Table 6, thefailed slopes with grey color have relatively higher
priority according to hazard. Therefore, the proposed
method can identify a lot of slopes with higher hazard
and can prioritize the slopes with actually higher
hazard. From the above results, the proposed method
is sufficiently available to the first step for the disasterprevention planning.

ACKNOWLEDGEMENTS
This study was funded by Grant-in-Aid for Scientific
Research (24510254), for which I wish to express
my gratitude here.

Table 6 Result of priority according to hazard
priority
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18

slope
number
U8
Bb
V7
W7
V6
T5
U4
V1
U2
W1
T6
T9
C9
Z4
U6
Ej
Z5
U5

difference

priority

2.686
2.229
1.945
1.917
1.789
1.710
1.597
1.584
1.564
1.385
1.355
1.331
1.312
1.278
1.121
0.797
0.700
0.477

19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36

slope
number
Bk
Ba
Bd
En
X8
Bg
Aw
De
Ed
Bo
Y0
W0
Am
Ar
Dj
Bw
Ch
Bf

difference

REFERENCES

0.420
0.393
0.368
0.347
0.344
0.230
0.192
0.192
0.151
0.128
0.128
0.055
0.028
0.024
0.024
0.024
0.024
0.016

[1] Ministry of Land, Infrastructure, Transport andTourism, “Instance of Sediment Disasters”,
http://www.mlit.go.jp/mizukokudo/sabo/jirei.ht
ml, (2014/07/11) (in Japanese)[2] Road Management Technology Center, “Manualof periodical inspection of road (heavy rain,
heavy snow)”, 2009, pp. 20-37. (in Japanese)[3] Okita M, Tokutaka H, Hujimura K, Gonda E,“Self-organizing Maps and Tools”, Springer
Japan, 2008, pp. 1-13. (in Japanese)[4] Murase Y, Takada H, Hirose T, “Multivariate
Analysis by SPSS”, Ohmusha, 2012, pp. 273-298.
(in Japanese)[5] Kan T, “Practice of multivariate analysis vol. 2”,
Company of Modern Mathematics, 2007, pp. 44116. (in Japanese)[6] Ito S, Oda K, Koizumi K, “Method for hazard
assessment
todeep-seatedcatastrophic
landslides due to heavy rain with both artificial
neural network and mathematical statistics”, The
14th International Conference of theInternational Association for Computer Methods
and Advances in Geomechanics, 2014.

CONCLUSION
In this study, a method based on information
processing techniques was proposed in order to
identify the slopes with higher hazard to slope failures.
In the proposed method, self-organizing map (SOM),
cluster analysis, and Hayashi’s second method ofquantification were combined. The proposed method

71

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

HYDRAULIC CONDUCTIVITY IN LOESSIC STABILIZED SOIL
Alercia Biga Carolina1, Arrúa Pedro2, Eberhardt Marcelo3, Aiassa Martinez Gonzalo4
Grupo de Investigación y transferencia en Geotecnia, Estructuras y Fundaciones (GIGEF),
Departamento de Ingeniería Civil, Facultad Regional Córdoba, Universidad Tecnológica Nacional,
Argentina
1,2,3,4

ABSTRACTThe loessic soils are the main geological storage available as a building material in Cordoba, Argentina.
Infiltration tests were done using remoulded samples and a flexible wall permeameter. Water content, dry unit
weight, and percentages of ionic stabilizer and bentonite have been studied. Experiment results were compared
between mixtures with different percentages of additives. The results show the reduction of hydraulic propertiesof local soils to improve geotechnical structures.
Keywords: Silty Clay, Infiltration Test, Flexible Wall Permeameter, Falling Head Methodions are Na+, Ca++, Mg++ and K+, with apredominance of sodium cations, hence its
classification [5]. It has high plasticity and highswelling capacity. Table 1 presents the principals
geotechnical properties of the soils used in this work.

INTRODUCTION
The loess soils have particles from 10 to 50
microns. In Argentina, covering a wide area and arenaturally macroporous [1]. The increment in watercontent cause a dissolution of soluble salts and thisreduce the shear strength [2]. In Córdoba city,usually geotechnical properties of loessic soils are
modified by compaction or with chemical stabilizers[3]. Addition of sodium bentonite in soil has shown
improvement of hydraulic properties [4]. During lastyear, artificial products have appeared in market, toreduce absorption capacity of loessic soils. In thispaper, analyzes and compares the improvement in
the hydraulic and mechanical properties of loess by
incorporation of bentonite and base polymericchemical stabilizer. Coefficient of permeability,
absorption capacity and stress strain curves are show
in this work.

Base Polymeric Ionic Stabilizer (BPIS)
BPIS is a viscous liquid, colorless, without odor,
miscible in water. It has a ph (13-14) and density is
1.05 gr/cm3. BPIS are composed of a biodegradable
polymer, mineral salts and cationic surfactant(potassium polyacrylate, potassium hydroxide andBelzanconio chloride). The ionic stabilizer is anargentinian additive provided by Polydem Argentina
SA, and it called Poly-Ses 028. The percentages ofchemical composition are reserved by industrial
protection. The chemical process of soil stabilization
is produced by neutralization of the electrochemical
activity of the clay particles (with negative electriccharge) thus avoiding the adsorption of positive
cations from water molecules, and so promote theattraction between particles ground, reducing theempty spaces and consequently increasing thedensity of the structure. The manufacturer ensuresthat the stabilizer BPIS modifies the surface tensionof water on granular bodies and increases the contact
angle of the water present in the interstices of thesoil.

MATERIALS
Loessic soil - Bentonite
The soil used was obtained from boreholes at 1m
depth, in Ciudad Universitaria, Córdoba. Sodium
bentonite was used, provided by Minarmco SA
deposits from Pellegrini Lake, Black River, locatedat north of Patagonia. Composed of 92% of
motmorillonita, and lower percentages of quartz,
gibbsite, feldspar, calcite and zeolites. It has a highsodium content product as a result of the presenceof soluble salts and cations retained in the thicknessof the diffuse double layer. The magnesium comesfrom octahedral positions of the clay structure, fromsoluble salts and exchangeable cations. Generally
show high proportions of iron between 4% and 6%.
It has a high cation exchange capacity, which varies
between 76 and 97 meq/100g. The exchangeable

METHODS
Soil/Bentonite and Soil/ BPIS mixtures
The materials were collected on trays at 20ºC
during 24hs. Soil passing sieve 100 was used. Soil72

GEOMATE- Brisbane, Nov. 19-21, 2014

adopted (Eq. (1)).

has been drying at 105 ºC during 24 hs. The loessic
soil comparison specimen was dry unit weight γ d(kN/m3) = 12.4, initial water content ωini (%) = 18.1.
Two groups of soil were selected, (a) loess andbentonite in dry weight in percentages SB1 = 3%,
SB2 = 6% and SB3 = 9%, the ωini (%) = 18.2, 18.2,
19.6, the γ d =12.8, 12.5, 12.7 respectively, and (b)loessic soil and BPIS with SE1 = 0.5 ‰, SE2 =1.0 ‰ and SE3 = 1.5 ‰ incorporated in water. Theω ini (%) in static compaction was 18.5 16.3 17.7, andγ d (kN/m3) 13.6, 13.7, 13.3 respectively. The
specimens were 0.07m in diameter and 0.14m in
high. Static compaction method was used to prepare
samples, in cylindrical molds. The specimen test was
built and compacted in three layers of equal
thickness. Extraction of samples was performed
using a hydraulic jack. In order to conserve watercontent, plastic bags were used.

Ir =

Loess

γ d (kN/m )γ (kN/m3)

12.2-14.5
14.9-16.8
20.8-32.2
0-8

3

LL (%)IP (%)(1)

Where ∆V: volume infiltrate during time ∆t, A:
cross section specimen area. Under saturated
condition the permeability parameter k is obtainedwith Eq. (2).

Vu (t ) − Vl (t1 ) 
PB1 + 1


aL
a
k=
Ln 

Vu (t2 ) − Vl (t2 ) 
A Δt 
PB
+
 2

a



(2)

Where a: area of burette, L: length of sample, A:
area of sample, ∆t: lapsed time, PBi: bias pressure,Vu(ti): volume reading of upper burette at time i,
Vl(ti): volume reading of lower burette at time i. The
saturation level was calculated as B = [(u 2 -u 1 )/(σ 2 σ 1 )]. Where u 2 - u 1 : increase in pore pressure, σ 2 σ 1 : increase in cell pressure. We consider that, B at
98% is saturation condition [7]. At the end ofexperiment, the water content was established ineach sample.

Table 1 Materials properties
Properties

ΔV (t )Δt A

Bentonite---301
231

Unconfined compression (UC)

Gs
2.68
2.71
Ps 200 (%)
96
100
Clay content<
0,002 mm (%)
4
85
SUCS
CL-ML
CH
Ss (m2 /g)
1731(*)
Ph>8
7-7.5
Sc (%)0.38< 0.1
Note: γ = natural unit weight, LL = Liquid limit, IP =Plasticity index, Gs = Specific gravity, Ps = passing
sieve, Ss = Specific surface, Sc = salt content. (*)[12]

For UC test a mechanical press was used
instrumented with a load cell with a capacity of
50kN and a digital comparator for recording
displacements with a precision of 0.001 mm, to a
constant deformation rate of 2.4 mm/min. UC tests
is used to evaluate the stress–strain characteristics
and the stiffness properties of the Soil-AdditiveMixture. Secant modulus at 1% of axial strain was
defined.
Capillary rise
To set the speed of capillary rise was used a
metal container with the addition of distilled water.
The specimens were placed on metal cylinders with
0.03 m height and slotted base. It was measured therise of moisture in function of time.

Infiltration test
A flexible wall permeameter was used toevaluate hydraulic properties of samples. Variablehead permeability test was conducted [6].
Loess-bentonite samples were infiltrated inunsaturated and saturated condition. At the ends ofeach sample, filter paper and porous stones wereused. Porous stones were saturated during 24 hours.
During infiltration tests, the gradient was 10 [6].
Pressures for the camera, upper and lower head weretaken as 117 kPa, 114 kPa and 100 kPa respectively.
Deaerated water was used as permeant fluid.
In unsatured condition, the infiltration rate (I r ) is

RESULTS DISCUSSION
Infiltration test
The results of infiltration tests were ω (3%)=
34.6 %, ω (6%)= 26.4 %, ω (9%)= 34.7 %, ω
( 0.5 ‰)= 29.2 %, ω ( 1 ‰)= 29.7 % , ω ( 1.5 ‰)=37.8 % and ω (soil)= 29.5%.
Incorporating clay to the silty soil produces adecrease in the infiltration and also on the73

GEOMATE- Brisbane, Nov. 19-21, 2014

once more and a half. The values obtained were Es
22
SE1 = 11.6 kN/m , Es SE2 = 16.6 kN/m , Es SE3 =2
2
16.8 kN/m and Es SOIL = 10.1kN/m .
Higher compression resistance is achieved insamples with bentonite than BPIS samples. The
value obtained was 36.95 kN/m2.

permeability coefficient [8]-[10]. No records ofpermeability tests results were found on remoulded
samples with densities near a value 13 kN/m2.
Figure 2 shows the response under infiltration
conditions for stage was done. In unsaturated
conditions, uncontrolled suction level, it has beenpretending to simulate field conditions. In
unsaturated conditions, non controlled suction level,
we have tried to simulate field conditions.
Under saturation condition decreasing permeability
coefficients with increasing percentage of bentonite
is observed. The minimum value of permeability
was obtained for samples with addition of 9% ofbentonite.
The permeability parameter magnitudes were,k SB1 = 1.36 x10 -6 m/s, k SB2 = 1.22 x10 -6 m/s , k-7
SB3 = 8.03 x10 m/s.
One possible explanation for this behavior is a highexchange capacity cation of sodium bentonite,provided by the presence of sodium ions Na+,
providing attraction in the water particles, increasing
the thickness of the diffuse double layer. Swelling of
the ions Na+ also occurs, develop their full potential
and affect the hydraulic conductivity. This behavior
is accentuated with increasing bentonite
In Figure 2, is shown the hydraulic behavior of thespecimens with the addition of stabilizer. It wasobserved a lower volume of fluid filtered withincreases the contained of stabilizer in the blends.
Values being lower permeability, so the lowest
permeability value is recorded for samples with
1.5 ‰ stabilizer. The value obtained was k = 3.98
x10 -6 m/s.

Capillary rise
Figure 4 shows the progress of hydration in thesoil-bentonite specimens for capillary rise testing.
The velocity of capillary rise increases with theamount of bentonite. Note that no significant
difference was observed in samples with 3% and 6%.

Axial stress (kN/m2)

60

20

0.0

0.5

1.0

1.5

2.0

2.5

2.0

2.5

Axial strain (%)(a)
60

Axial stress (kN/m2)

Infiltration (cm)

SB 2
SB 3
CL-ML

2.0

40

0

3.0
SB 1

SB 1
SB 2
SB 3
CL-ML

SE 1
SE 2
SE 3

40

SE 1
SE 2
SE 3
CL-ML

20

0
0.0

10

0.5

1.0
1.5
Axial strain (%)(b)
Fig. 3 Stress-strain curves unconfined compression
test. (a) Soil/Bentonite. (b) Soil/BPIS

0.0
0

50

100

150

200

Time (min)Fig. 2

Infiltration test on soil /bentonite and soil /BPIS samples

Unconfined compression (UC)The results of unconfined compression are
shown on Fig. 4. The graphic shows that stiffness
increase with bentonite content.
The increase of bentonite content causes anincrease of the stiffness four times. The values
obtained were Es SB1 = 19.7 kN/m2, Es SB2 = 25.6
kN/ m2, Es SB3 = 41.8 kN/ m2.
There is no significant change in stiffness
properties in soil-EIBP samples. The increment wasFig. 4 Capillary rise. Soil/Bentonite
Figure 5 presents the results of the mixtures withionic stabilizer. The results indicate that the speed of74

GEOMATE- Brisbane, Nov. 19-21, 2014

capillary rise decreases with increasing stabilizer
content.
An explanation of the phenomenon is the
reduction of the electrostatic potential of the soil
particles, precluding its adsorption capacity. Thus,
negative charges present in the soil are neutralized,
and prevent the absorption of positive charge present
in the water molecules, producing an attraction
between the solid particles, a rearrangement of the
granular bodies and reduction of voids.
Consequently, it produces a decrease of the film
layer present in the soil particles [11].

compression test shows no increase of resistancewith PBIS addition.
Capillary rise: (a) the capillary rise increase withthe content of bentonite. (b) The capillary risedecreases with increase of EIBP content.
ACKNOWLEDGEMENTS
The authors thanks the support of Universidad
Tecnológica Nacional Facultad Regional Córdoba,
Ministerio de Ciencia y Tecnología, Gobierno de laProvincia de Córdoba (PID-GRF), and FONCyT
Agencia Nacional de Promoción Científica yTecnológica (PICT).

Capillary rise (m)

0.12
SE 1
SE 2
SE 3

REFERENCES

0.08[1] Aiassa G, Zeballos M, Arrúa P and Terzariol R,“Infiltración en suelos limosos compactados”,
XIX Congreso Argentino de Mecánica deSuelos e Ingeniería Geotécnica, Octubre 2008,
La Plata, Argentina[2] Arrúa P, Aiassa G., and Eberhardt M. “Behavior
of collapsible loessic soil after interparticle
cementation”, International J. of GEOMATE,
Vol. 1, November-December 2011, pp. 130–135[3] Arrúa, P.; Aiassa, G. and Eberhardt, M. Loesssoil stabilized with cement for civil engineering
applications. International Journal of Earth
Sciences and Engineering. ISSN: 0974-5904.
Vol. 5, No 1, 2012.pp.10-18[4] Aiassa G. and Arrúa P, “Desempeño de barreras
sanitarias
simplesdesueloloessicocompactado”, Revista Tecnología y Ciencia,
Año 8, Noviembre 2009, pp. 26–40.
[5] Hyang-Sig Ahn, Ho Young Jo, “Influence of
exchangeable cations on hydraulic conductivityof compacted bentonite.” Journal of Applied
Clay Science, Vol 44, 2009. pp.144-150.
[6] ASTM. D 5084. Standard Test Methods for
Measurement of Hydraulic Conductivity of
Satured porous Materials using a Flexible Wall
Permeameter.
[7] Fredlund, D,G; Rahardjo, H; Soils Mechanics
for unsatured soils. John wiley and Sons. 1993.
NY. USA.
[8] Cuisinier,O; Auriol, J.Cl;Le Borgne, T; Deneele,
D; “ Microestructure and hidraulic conductivityof a compacted lime-treated soil”, Journal ofEngineering Geology. Vol. 123, 2011 pp.187193.
[9] Qiong Wang ,Yu-Jun Cui, Anh Minh Tang,
Jean-Dominique Barnichon, Simona Saba, WeiMin Ye “Hydraulic conductivity andmicrostructurechangesofcompacted
bentonite/sand mixture during hydration”.
Journal of Engineering Geology. Vol 164, 2013
pp 67-76.

0.04

0
0

500

1000

1500

2000

Time (s)Fig. 5 Capillary rice. Soil/BPIS
An explanation of the phenomenon is the
reduction of the electrostatic potential of the soil
particles, precluding its adsorption capacity. Thus,
negative charges present in the soil are neutralized,
and prevent the absorption of positive charge present
in the water molecules, producing an attraction
between the solid particles, a rearrangement of the
granular bodies and reduction of voids.
Consequently, it produces a decrease of the film
layer present in the soil particles [11].
CONCLUSION
This paper has presented a study on mixtures ofloess soil, bentonite and materials and revised theimportance of interparticle interactions and theirinfluence on the mechanical and hydraulically
performance of the material. Water content, unit
weight, and percentage of stabilizer have beenstudied. For low unit weights (γ d = 13kN/m3) havebeen identified the main results as follows:
Hydraulic properties: (a) in unsaturated state, theinfiltration volume decreases with increasing content
of bentonite. (b) Soil / PBIS shows no reduction involume infiltration compared to loess soil in the
dosage used. In saturated condition, the behavior
tendencies are similar to unsaturated conditions.
Unconfined compression: (a) It has been
identified that the addition of bentonite increases thecompressive strength by 400%. (b) Unconfined75

GEOMATE- Brisbane, Nov. 19-21, 2014[10] India Sudhakar M. Rao, Ravi K., “Hydromechanical characterization of Barmer 1
bentonite from Rajasthan, India”. Journal of
Nuclear Engineering and Design. Vol 265. 2013.
pp 330-340.

[11] Mitchell K. James. Fundamentals of Soils
Behavior. Editorial John Wiley and Sons. Inc.
1993.
[12] Santamarina J., Klein K, Wang Y., and Prencke
E. Specific surface: determination and relevance.
2002 Published on the NRC Research Press
Web site at http://cgj.nrc.ca

76Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

MATHEMATICAL SIMULATION OF PILE INTEGRITY TEST (PIT)
Ramli Bin Nazir1 and Osman El Hussien2
Associate Professor, Faculty of Engineering, Universiti Teknologi Malaysia, 2PhD Student, Faculty ofEngineering, Universiti Teknologi Malaysia

1

ABSTRACT
Newly constructed piles are commonly tested using low strain integrity test in order to assess their integrity
as part of pile foundation quality control program. Mathematical model based on numerical solution of wave
equation, which incorporates soil effects, is formulated. This model accommodates soil resistance effects on the
stress wave that propagates in pile body as a result of hammer impact. The numerical analysis is carried out
using a computer program, which is developed based on the mathematical modeling of pile integrity test. The
simulation program output is compared with real pile integrity test results, and the generated velocity values arefound to have good similarity with in-situ test results. New procedure, which identifies pile integrity test
limitations based on the established model, is illustrated.
Keywords: Pile, Integrity, Numerical, Simulationbody [6]. An axisymmetric model using finite
element techniques was used the pile andsurrounding soil. A correction factor was suggested
in the study in order to improve the accuracy of themodel. The Parallel Seismic Test is considered to betime consuming test, while it requires drilling ofreceiver borehole adjacent to pile and fixing ofreceivers at different depths in the receiver borehole.
Furthermore, the model was found to be lessefficient in simulating real pile testing when the
stiffness of soil near pile increases.
The test is carried out by striking pile top withsmall hammer. Stress wave will be generated as aresult of the impact, which travels down pile body topile bottom where it reflects back. The reflectedwave generates measurable pile top displacement,
and the pile is considered to be free from major
damages when the stress wave is received at thecorrect time at pile top and no earlier reflections arereceived. A pile subjected to low strain integrity
testing is shown in Fig. 1.

INTRODUCTION
Nondestructive testing techniques are routinely
used in construction industry to evaluate material
properties, structure components and to assess
structure condition and performance without causing
damage to the tested element during testing.
Nondestructive testing methods are routinely used
for quality control and damage assessment for
hardened concrete. Static and dynamic load tests are
the nondestructive testing techniques, which arewidely used for pile foundations. Pile integrity tests
are commonly carried out to evaluate the quality ofrecently constructed piles. Low strain integrity test
(PIT) is the most common test used for evaluation ofpile integrity.
Pile integrity tests are commonly carried out
using acoustic testing techniques. Acoustic science
includes the study of energy generation,transmission and reception in matter in terms ofvibrational waves. Sonic sensation is the mostcommon acoustic technique that used for assessmentof materials. Low strain integrity test of piles
involves examining the response of the pile to light
impact that creates compressive wave within pilebody. The low strain pile integrity test procedurerequires measurement and analysis of force andvelocity records generated as a result of theexcitation at pile top caused by hand held hammer.
The PIT equipment should have signal amplification
capability to enhance analysis of signals that are
reduced by soil and pile material damping. However,it may be difficult in some cases to differentiate
between soil and pile responses [1].
A numerical simulation for dynamic testing ofpiles using Parallel Seismic Test was carried out toassess pile length as well as possible defects in pileFig. 1

77

Concrete pile subjected to low strain
integrity test [7].

GEOMATE- Brisbane, Nov. 19-21, 2014

Where (r 0 ) is pile radius, (G s ) is soil shear
modulus and (r m ) is the lateral distance from pile
center where soil vibration caused by the dynamic
force applied on the pile diminishes. Eq. (4) was
derived considering the concentric cylinders shownin Fig. 3 and the equilibrium of soil element.

MATHEMATICAL SIMULATION
Considering the pile shown in Fig. 2, which is
divided to (n) segments, the pile has constant crosssectional area (A) and made of elastic material
having a uniform density (ρ) and modulus ofelasticity (E). The pile is subjected to a dynamic
force (F), which caused a linear displacement (w) inthe (z) direction at time (t).

Fig. 3Fig. 2In this model (r m ) value is estimated using
ground vibration attenuation equation [2]:Schematic diagram of pile subjected to
dynamic force, and a selected pile segment.

A1 = A0 (r0 / r1 ) (γ ) eα ( r0 −r1 )The applied dynamic force will generate a stresswave, which propagates in pile body. The following
equation, which is known as the wave equation, is
considered as the basic equation in describing wave
motion in pile body.
∂2w

∂2w

∂t

∂ z2

= c2
2

(1)

Fi − f i Asi − C vi = ρ A ∆zEvi = .

(2)

ρThe generated wave is subjected to damping
effects produced from surrounding soil and pilematerial. Soil frictional forces are assumed to be
proportional to pile segment displacement, whilematerial damping force is proportional to pilesegment
velocity.
Hence,
wave
equationincorporating soil and material damping effects canbe written as follows [8]:
∂2w

=E A
2

∂2w
2

Gs
r
r0 . ln( m )r0wiwi (t + ∆t ) − wi (t )
∆t

(6)

(7)

wi +1 − wi(8)∆zWhere (fi ) is the skin friction generated at pilesegment, (v i ) is the pile segment velocity and (A si )is the surface area of that segment.
At pile toe, the force (Fr) caused by reflectedwave is correlated to the incident force (Fi) is: Z p − Zs  F
(9)Fr = 
 Z p + Zs  iWhere, (Zp) is pile impedance and (Zs) is soil
impedance.
Soil reaction (FR) at pile toe is calculated as per
Kagawa correlation [4]:−M w−CFR = E sb r0b δ 0b z + 2(1 + ν sb ) ρ sb G sb r02b δ 0b T3 v p

The (M) is the proportionality constant of thefollowing correlation [5]:fi =vi (t + ∆t ) − vi (t )∆tFi − f i Asi − C vi = E A

∂w
(3)
∂t
∂t
∂z
Where, (M) is the proportionality constant
between soil frictional force and pile segment
displacement, and (C) is pile material damping
coefficient.

ρA

(5)

Where, (A 0 ), (A 1 ) are vibration amplitudes at(r 0 ), (r 1 ) distances respectively, (γ) is a coefficientdepends on wave type and (α) is material damping
coefficient.
The numerical solutions of Eq. (3) are as
follows:

Where,c=

Concentric shearing cylinders model [5]Where:F R = Soil reaction at pile tip
E sb = Young’s modulus of soil
r 0b = Radius of pile tip
δ 0b = Soil reaction coefficient

(4)

78

(10)

GEOMATE- Brisbane, Nov. 19-21, 2014

z = Pile tip displacement
ν sb = Poisson’s ratio of soil at pile tip
ρ sb = Soil density at pile tip
G sb = Shear modulus of soil at pile tip
T 3 = Polynomial function coefficient
vp = Pile tip velocity
Force transmission and reflection at pile toe isillustrated in Fig. 4.

displacement and force values in time domain.
Sample of this graphical output is shown in Fig. 5.
Velocity Vs Time
0.2
0.18
0.16

Velocity (cm/sec)

0.14
0.12
0.1
0.08
0.06
0.04
0.02
0

Fig. 5
Fig. 4Force distribution at pile toe

Table 1 Program input parameters

1
2

Number of segments

3

Pile length4

Pile radius

5

Concrete density

6

Pile elastic modulus

7

Wave velocity in pile

8

Shear wave velocity in soil

9

Shear wave velocity in soil below pile tip

10

Soil density below pile tip

11

Poisson's ratio of soil below pile tip

12

Soil Reaction Coefficient

13

Polynomial function coefficient (T 3 )1415

Concrete Damping Ratio
Wave type coefficient

16

Soil damping coefficient

0.004

0.006

0.01
0.008
Time (sec)

0.012

0.014

0.016

Velocity at pile top in time domain
generated from the computer program

Raw and processed data was collected from aselected project. The project is located in Mesaieed
Industrial Area in State of Qatar. Low strain
integrity test results of 30 piles were used in thecomparison. Pile toes were socketed in Limestone
stratum, which is considered as high resistant layer.
There are complete sets of PIT and geotechnicaldata in this project. This includes borehole logs, piledrilling records, which include subsurface logging
during piles construction and bored piles details.
The concrete piles are made of concrete and havenominal diameters of 0.9m. Subsurface condition atpile location consists of soft to medium dense silty
sand overlies slightly to moderately weathered
limestone stratum. Piles were casted at same tip
elevation resulting in rock socket depths ranging
from 5.6m to 7.0m approximately. The PIT tester
used in the project is shown in Fig. 6.

The assembled pile integrity test model including
pile material and soil effects is programed using
MATLAB technical computing language. The input
data is as follows:

Input Parameter
Applied force amplitude

0.002

FIELD DATA COLLECTION

MODEL PROGRAMMING

No.

0Fig. 6

PIT tester and accessories

Piles tested using low strain integrity test, arecategorized as one of the following categories:
Category A: Clear indication of sound pile and pile
toe reflection.
1. Category (A1): Indication of sound pile aboverock socket.
2. Category B: Clear indication of serious defectin pile.

The computer program is designed to carry out
iterative calculations in order to analyze each pilesegment producing velocity, displacement and force
values for each segment. The program can generate
automatic graphical output showing velocity,79

GEOMATE- Brisbane, Nov. 19-21, 2014

11

3.

Category C: Indication of possible defective
pile.
4. Category D: Conclusion on pile integrity is notdefinite (Inconclusive).
The second category is associated with piles
socketed deeply in bedrock. This category includes
pile records do not show major impedance
reduction; hence, piles in this category are
considered having acceptable integrity with thelimitation that this conclusion is for the pile section
above rock socket. The fifth category is associatedwith pile test records that do not show toe reflection.
This can be attributed to high soil resistance thatdissipates the propagating wave energy [3]. The
second and fifth categories show indefinite
evaluation of pile integrity; hence, low strain
integrity test is considered as inapplicable in theconditions associated with these categories.

A
A(rr00)/A
A(rr)

.
0 .8

.
0 .4

.
0 .2

0
00

Fig. 7

22

4

6

4
6
,
R
Raadiaal dissttaannccee, rr

88

1100

PIT tester and accessories

Table 3 Velocity amplitudes at pile toe

COMPARISON WITH INSITU TESTSThe output generated from the new model wascompared with the collected field low strain integrity
tests. Test results of 30 piles are used in thecomparison. The following pile and soil data areused based on the actual pile details and subsurface
soil condition:
Table 2 Pile and soil input data
Item
Concrete Density, ρ c (t/m3)
Pile elastic modulus, E (kN/m2)
Pile Radius, r 0 (m)Soil Density, ρ s (t/m3)
Rock Density, ρ s (t/m3)
Rock Poisson's Ratio, ν r
Wave velocity in concrete, m/s
Shear wave velocity in soil, m/s
Shear wave velocity in rock, m/s
Soil Reaction Coefficient
Attenuation coefficient(γ) for soil
Attenuation coefficient(α) for soil
Attenuation coefficient(γ) for rock
Attenuation coefficient(α) for rock
Concrete damping coefficient

.
0 .6

Value
2.5
4x107
0.45
1.80
2.30
0.40
4000
275
2000
2.00
2.00
0.13
2.00
0.10
0.015

Pile influence radial distance (r m ) is calculatedusing Eq. (5) after substitution of theabovementioned pile-soil data. Wave amplitudeattenuation trend corresponding to the radial
distance is shown in Fig. 7. The velocity amplitudes
at pile toe produced from insitu pile integrity test
and the amplitudes predicted using the mathematicalmodel are shown in Table 3.
The negative signs indicate upward movement,
while the reflected wave, which is received at pile
top, causes upward movement of pile.

80

Pile No.

PIT-W
(m/s)

Model
(m/s)

P-1

-0.00134-0.00139P-2-0.00242-0.00192

P-3-0.00096-0.00483

P-4-0.00318-0.00183P-5-0.00089-0.00223P-6-0.00204-0.0014P-7-0.00089-0.00125P-8-0.00099-0.00155P-9-0.00062-0.00082

P-10-0.0008-0.00085

P-11-0.0006-0.00041

P-12-0.0016-0.00178P-13-0.0011-0.0011P-14-0.00217-0.00129P-15-0.00035-0.00136

P-16-0.00096-0.00163P-17-0.00169-0.00155P-18-0.00137-0.00143P-19-0.00361-0.00213

P-20-0.00028-0.00102P-21-0.00115-0.00061

P-22-0.00142-0.00131P-23-0.0003-0.00137P-24-0.00117-0.00119P-25-0.00087-0.00115

P-26-0.0008-0.00119P-27-0.00443-0.00435

P-28-0.00181-0.00105

P-29-0.00242-0.00307P-30-0.00133-0.00184

GEOMATE- Brisbane, Nov. 19-21, 2014

The velocity values in time domain for pile P-1
obtained from insitu testing and the mathematicalmodeling are shown in Fig. 8 and Fig. 9,
respectively.
6: # 19

0.00

Vel
F /Z
5

Fig. 81015- .
-00.0011.
R22 == 0.86R- .
-0.0022Toe

0-m- . Ve-lo. c ity (c. /s ec)- .
-00. 000022 -00.000044 -00.000066 -00.000088

00

MA: 10.00
MD : 4.80
LE: 23.98
W S: 4000
LO: 0.00
H I:
0.00
PV:
0
T1:
29

0.10

T1
-0.10

Velocity cm/sec

00

m//sseecc)
V
Veelloocciittyy (ccm

cm/s

0.20

The correlation between velocity amplitudes
received at pile top produced from field and model
results is shown in Fig. 11.

20 m

- .
-0.004- .
-00.000066

oou
uttlieerr ( P-3)

- .
-0.008Insitu velocity curve for pile P-1

- .
-0.01

.
0
0.3
3

.
0.2
2

Fig. 11 Correlation between insitu and model
velocity amplitudes

.
m//ss
2c
0.1
cm
0
16
62

Veelloocciittyy (ccmVm//sseecc)

.
0.1

To
T
oe
e
0
0

.
0.0025

.
0.005

.
0.01

.
0.0075EQUIVALENT IMPEDANCE CONCEPT

- .
cm s
.
.-0.00139 cm /s
0.015
0.0125

se
c)
Tiim
T
me
e (s
ec

A new envelope is introduced, which is the“Equivalent Impedance Envelope”. This envelope
can help in assessing the limitations of the PIT test
for a certain pile cast in a certain soil strata. This
envelope is based on expressing the losses in stresswave strength as change in impedance by calculating
the equivalent impedance that causes the sameamount of loss. The Equivalent Impedance Envelope
for the stress wave amplitudes is shown in Fig. 12.
This envelope is plotted for the points where
significant change in equivalent impedance
occurred, like change in soil layer or at pile toe.

. mngtth =
Pi le
= 23 .98m
en
e Le

- .
-0
0.2
2

- .
3
0.3
-0

Model velocity curve for pile P-1

The graphical comparison between the field
results and the mathematical model shown in Fig. 10
demonstrates that both sets of results are having
good similarity. Note that pile P-3 insitu result is
considered as up normal while this pile wassubjected to the highest impact force but resulted ina small velocity value received at pile top. Hence,model result for pile P-3 can be considered as morereasonable with respect to the amount of force
applied.

7755000000
70000
6655000000.
mpeedaannccee "Z"
m)
Z (kN
IIm
N.sseecc/m- .
-00.000022

m//sseecc)
Veelloocciittyy (ccmV

Waavvee aatt rroocck l aayyeerr ttoopp

6600000000

00- .
-00.000044

Waavvee aatt pilee ttoop

Fig. 95555000
5500000000
45000
440000Waavvee rreefleeccttss aatt ppilee ttooeeW3355000000

30000

nccee
Crritticcaal Im
mpeedaan

- .
-0
0.1
1

2255000000
2200000000
15000
1100000000

W aavvee aatt pilee ttoop

5000

- .
-00.000066

W
Waavvee rreeaacchheess ppiillee ttooee.
Z = 6361 726 kN.sec/m

Z0 = 6361.726 kN. sec /mWaavvee aatt rroocckk llaayyeerr ttoopp0
W

0

0
- .
-00.000088

00

1100

P
Pilee NNuum
mbeerrss

2200.
0 .0055.
0 .007755

T
Tiim
mee (sseecc)

.
0.011

.
0.0112255.
0.01155

Fig. 12 The Equivalent Impedance Envelope

mpplliittuudeess aatt P
IInnssiittuu V
Tooee
Viilloocciittyy A
Am
Piillee T
M
Tooee
Viilloocciittyy A
Am
Moodeell V
mpplliittuudeess aatt P
Piillee T

- .
-0.01

.
0. 002255

The “Critical Impedance” is the impedance whenreached, the PIT hardware and software will not beable to properly identify the toe reflection; hence,inconclusive result will be reported. This impedancevalue can be used to identify the PIT test limitations

300
3

Fig. 10 Velocity amplitudes produced from insitu
PIT and the mathematical model81

GEOMATE- Brisbane, Nov. 19-21, 2014

for certain pile and soil conditions.

REFERENCES[1] American Society of Testing and Materials(ASTM), 2013, Section 4, Vol. 04.09, ASTM
D5882, Standard “Test Method for Low Strain
Impact Integrity Testing of Deep Foundations”.
[2] Amick, H., and Gendreau, M., “Construction
Vibrations and Their Impact on VibrationSensitive Facilities”. 2000. Proc., ASCE
Construction Congress 6, Orlando Florida, pp.
1-10.
[3] GRL Shaft Integrity Report No. 095017, March
2009, Qafco-5 Project, Mesaied, Qatar.
[4] Kagawa T., “Dynamic Soil Reaction to Axially
Loaded Piles”, Journal of GeotechnicalEngineering, Vol. 177, No. 7, July 1991.
[5] Kraft, L. M., Ray, R. P., and Kagawa, T. (1981).
Theoretical t-z curves, Journal GeotechnicalEngineering Division, Proceedings Paper
16653, American Society of Civil Engineers,
Vol 107(GT11).
[6] Liao S., Tong J., Chen C., Wu T., “Numericalsimulation and experimental study of Parallel
Seismic test for piles”, International Journal of
Solids and Structures, 43, 2006.
[7] Pile Dynamic Incorporation (PDI), Cleveland,Ohio, USA.
[8] Rodriguez J. and Restrepo, V., September,2008. Analytic Solution for one-dimensional
propagation of waves and its adaptation to
Results Interpretation of Pile Integrity Test
(PIT). Proceedings of the Eighth International
Conference on the Application of Stress Wave
Theory to Piles 2008: Lisbon, Portugal.

MODEL APPLICATION
The proposed modelling procedure provides a
new methodology, which identifies the low strain
integrity test limitations through quantifying soil
resistance effects computed at pile circumference
and pile toe. Furthermore, PIT test applicability canbe identified through estimating the critical
impedance, which is the impedance value when
exceeded; the PIT test is no longer applicable. This
helps in assessing the test suitability prior carryingout the test, which provides efficient tool forengineers to decide about including the PIT test in
the quality control testing program based on site
subsurface condition.
CONCLUSIONS
The influences of soil friction at pile
circumference and soil resistance at pile tip
generated during testing of piles using low strain
integrity test method are evaluated mathematically.
The mathematical model is based on introducing
soil resistance at pile surface and pile toe in the basic
wave equation.
The skin friction is assumed to be mobilized
proportional to pile displacement, while soil
resistance at pile toe is assumed to be caused by thechange of impedance as well as the dynamic
reaction at pile tip.
The introduced method of analysis had showedcomparable results with insitu low strain integrity
test results.
A new method, which evaluates low strain
integrity test is introduced. This method can be used
to evaluate the test limitations based on pile andsubsurface soil conditions and the PIT tester
sensitivity.
It is required to identify the sensitivity of the PIT
equipment in order to assess whether model
calculated values at pile toe can be recognized by theequipment or no.
ACKNOWLEDGEMENTS
The authors would like to thank the Research
Management Centre of Universiti Teknologi
Malaysia (UTM) and Ministry of Education
Malaysia (MOE) for providing financial support
through research vote: R.J130000.7822.4L130 for
this research.
Appreciation is also extended to Pile Dynamic
Incorporation for providing the technical support
related to PIT-S software.

82

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

DEVELOPING DESIGN TOOLS FOR SHEET PILE WALLS
1Chane Brits1 and Jim Shiau1
Faculty of Engineering and Surveying, University of Southern Queensland, Australia
ABSTRACT

Nowadays, the engineering profession is discovering and using the computational powers of computer spread
sheets in practice. They are used in bid preparation, budget, control, engineering design computation, and manyother areas. However, the computational power of the computer-spread sheet is only the beginning of what canbe accomplished. Success of geotechnical works relies on important factors such as proper planning, analysis anddesign of sheet pile walls. This paper aids in understanding the conventional methods used in the design of sheet
pile walls better known as the limit equilibrium methods. It is aimed to develop an automated excel spread-sheet
to be used in the engineering and geotechnical industry suitable for any sheet pile wall design by means of using
the above mentioned methods.
Keywords: FLAC, Sheet pile wall, Design, Analyses, Stability

deformation, ground settlement and the location of
failure surfaces.

INTRODUCTION
Sheet piles are widely used as retaining structures,
especially in excavation support systems, slope
stabilization, floodwalls, and waterfront structures.
Sheet pile walls are known to be flexible structures,
thus when the sheet pile moves away and into the soil
respectively, active and passive pressure zones formon either side of the sheet pile wall. Thus when
designing sheet pile walls it is necessary to determine
the net pressure distribution exerted on the sheet pilefor stability purposes as well as determining thebending moment distribution along the sheet pile wall
for structural design purposes.
This can be
determined by means of analytical methods that havebeen around for many years [1] [2].

CANTILEVERED AND ANCHORED SHEETPILE WALLS
Sheet pile walls used to provide lateral earth
support could be classified as either cantilever oranchored depending on the wall height requirements.
Cantilever sheet pile walls are usually used with low
wall height between 3-5 m and sometimes less due tolimitations in availability of certain section modulus
and their costs [3].

The analytical methods normally consist of manyequations and may take a long time to solve by hand.
Computers on the other hand has evolved over the
past few decades and developing an automatic excel
spread sheet in excel for design purposes decreases
the time required to solve the equations as well as
decreasing the possibility of any human errors that
may occur. Although the analytical methods give agood indication of the soil-pile system, thehypotheses on which these methods are based uponare very conservative. Hence why developing
numerical models in commonly known industrial
available software programs such as Flac and Plaxis
may be undergone in the future. This enables further
information to be obtained, such as the wallFig. 1

Cantilever Sheet Pile (Hauraki Pilling LTD)

Cantilever sheet pile walls are suitable for places withtight space constraints due to the narrow base widthof the cantilever wall.

83

GEOMATE- Brisbane, Nov. 19-21, 2014

mass, containing the retaining wall system, rotatesalong a single failure surface. This type of failure isclassed as a soil failure only, independent of thestructural capacities of the wall and any anchorage
system. Another form of rotational failure occurs
when the retaining wall rotates due to the exerted soilpressures.

This type of sheet pile wall depends on the passive
resistance of the foundation material in front of thewall and the moment resisting capacity of the piles forstability. Therefore, it should not be used, where thefoundation material may be removed during wall
service life [4].
The anchored sheet pile walls are required when thewall height exceeds 5 m or when the lateral wall
deflection is limited for design consideration [5].
Anchoring the sheet pile wall requires lesspenetration depth and also less moment to the sheet
pile because it will drive additional support by thepassive pressure on the front of the wall and theanchor tie rod. Anchored sheet pile walls are
typically constructed in cut situations, and may be
used for fill situations with special design
consideration to protect the anchor from construction
damage that may be happened by fill placement andfill settlement [3].

Fig. 3

Failure modes for cantilevered sheet pilewalls [5]The prevention of this type of failure can occur due toadequate wall penetration into the soil or by
implementing an anchorage system.

Fig. 2

Macalloy Anchored Sheet Pile
(Iceland, 2002)

POSSIBLE FAILURE MECHANISMS
Several failure modes for a sheet pile system must
be considered in the design process. It is of upmost
importance in design not for the sheet pile wall
system to fail is it can lead to death and community
disruption. These failures are known to be, deepseated failure, rotational failure due to pilepenetration inadequacy, overstressing of the sheet
pile, and anchorage component failure.
An
investigation of load capacity of piles subjected to
combined loading was performed; due to the fact that
second-order bending effects reduce the lateral load
capacity of the wall when piles are exposed to
combined axial and lateral loads.

Fig. 4Deep-seated failure occurs when the complete soil

84

Failure modes for anchored sheet pile walls[4]GEOMATE- Brisbane, Nov. 19-21, 2014

force acting on the backfill slope is acting in a parallel
direction. Both active and passive pressure zones willdevelop on either side of the sheet pile wall as shownin the figure 5. When the sheet pile wall moves awayfrom the soil an active pressure zone is formed
however when the sheet pile wall pushes into the soil
it forms a passive pressure zone.

The other failures that may occur in retaining wall
systems are sheet pile overstressing, passive
anchorage failure, tie rod failure and wale system
failure. In the occurrence of pile overstressing due toboth lateral and axial loads, a plastic hinge leading to
failure will develop as a result. When the anchor
moves laterally within the soil due to the force exerted
on the anchor a passive anchorage failure will occur.
The tie rod may fail if the required tensile capacity is
not adequate, and the wale system may undergo abearing failure if the loads are not evenly distributed.

To develop the relationship for the proper depth ofembedment of sheet piles driven into a granular soil,
for a visual representation reference is made to figure
6.

THE ANALYTICAL DESIGN PROCEDURE
The following analytical design methods for
cantilever sheet pile walls have only briefly been
discussed due to the conference paper limitations.
There are several sheet pile walls design methods,
dating back from the first half of the 20th century;these original proposals have continuously and may
currently being reviewed. Analytical methods areused for establishing equilibrium of the horizontal
forces and moments developed along the wall, todefine the embedment depth below the dredge line for
either cantilever or anchored sheet pile walls bymeans of undergoing geotechnical design
calculations. This paper based the necessary design
calculation upon the earth pressures theories derived
by Rankine. The Rankine theory assumes that the
sheet pile wall has introduced no change in the shear
stress at the soil-structure interface.

Fig. 6

Cantilever sheet piling penetrating sandy
soils [2]Due to the development of active and passive
pressures on either side of the sheet pile wall, it isnecessary to determine both Rankine’s active andpassive pressure coefficients:
𝛟𝛟

(2-1)

𝛟𝛟

(2-2)

𝐊𝐊 𝐚𝐚 = 𝐭𝐭𝐭𝐭𝐭𝐭𝟐𝟐 �𝟒𝟒𝟒𝟒 − �𝟐𝟐

𝐊𝐊 𝐩𝐩 = 𝐭𝐭𝐭𝐭𝐭𝐭𝟐𝟐 �𝟒𝟒𝟒𝟒 + �
𝟐𝟐

It is important to note that after a geotechnical survey
had been done, the designer will know certain input
parameters. This is important information as it gives
knowledge about the type of soil, the friction angle ofthe soil, the length above the dredge line as well as
the soil cohesion.

Fig. 5 Active and Passive Pressure Distribution [2]It has been assumed that straight planes represent the
ground and failure surfaces and that the resultant
85

GEOMATE- Brisbane, Nov. 19-21, 2014

𝐩𝐩𝟒𝟒 = �𝛄𝛄𝐋𝐋𝟏𝟏 + 𝛄𝛄′ 𝐋𝐋𝟐𝟐 )𝑲𝑲𝒑𝒑 + 𝜸𝜸′ 𝑳𝑳𝟑𝟑 (𝐊𝐊 𝐩𝐩 − 𝑲𝑲𝒂𝒂 � +𝜸𝜸′ 𝑳𝑳𝟒𝟒 (𝑲𝑲𝒑𝒑 − 𝑲𝑲𝒂𝒂 )(2-9)

Knowing this input data the active pressure on theright side of the sheet pile wall can now be
determined:
𝐩𝐩𝟏𝟏 = 𝛄𝛄𝐋𝐋𝟏𝟏 𝐊𝐊 𝐚𝐚

𝐩𝐩𝟐𝟐 = (𝛄𝛄𝐋𝐋𝟏𝟏 + 𝛄𝛄′𝐋𝐋𝟏𝟏 ) 𝐊𝐊 𝐚𝐚

𝑳𝑳

𝒑𝒑𝟒𝟒 )( 𝟑𝟑𝟓𝟓)(2-4)(2-10)

Indicated on figure 6 it is clear that the net pressure
will be equal to zero at the point E, hence by using theratio given as 1 vertical to 𝛄𝛄′ (𝐊𝐊 𝐩𝐩 − 𝐊𝐊 𝐚𝐚 ) in thehorizontal the unknown length L 3 can be determined:
𝐩𝐩𝟐𝟐

𝐋𝐋𝟑𝟑 = 𝛄𝛄′(𝐊𝐊 − 𝐊𝐊 )𝐩𝐩

𝑳𝑳𝟓𝟓 =(2-12)

Where A 1, A 2 , A 3 and A 4 are given by [2]:𝒑𝒑

𝑨𝑨𝟏𝟏 = 𝜸𝜸′ (𝑲𝑲 𝟓𝟓−𝑲𝑲 )𝑨𝑨𝟐𝟐 =
𝑨𝑨𝟑𝟑 =(2-6)

𝑨𝑨𝟒𝟒 =

Summing the moments of all the pressure forces
exerted on the wall about point E and dividing by the
total pressure force P will provide the distance 𝒛𝒛� fromE to the force P.

𝒑𝒑

𝟖𝟖𝟖𝟖

𝒂𝒂

𝜸𝜸′ (𝑲𝑲𝒑𝒑 −𝑲𝑲𝒂𝒂 )𝟔𝟔𝟔𝟔[𝟐𝟐𝒛𝒛�𝜸𝜸′ �𝑲𝑲𝒑𝒑 −𝑲𝑲𝒂𝒂 �+𝒑𝒑𝟓𝟓 ]𝜸𝜸′ 𝟐𝟐 (𝑲𝑲𝒑𝒑−𝑲𝑲𝒂𝒂 )𝟐𝟐

𝑷𝑷[𝟔𝟔𝒛𝒛�𝒑𝒑𝟓𝟓 +𝟒𝟒𝟒𝟒]

𝜸𝜸′ 𝟐𝟐 (𝑲𝑲𝒑𝒑 −𝑲𝑲𝒂𝒂 )𝟐𝟐(2-13)(2-14)(2-15)(2-16)

Where 𝐩𝐩𝟓𝟓 is the passive pressure applied above point
E, thus the decline in active pressure right above point
E due to the large passive pressure being exerted on
the left side of the sheet pile wall:

𝑳𝑳𝟏𝟏⎡ 𝟎𝟎. 𝟓𝟓𝐩𝐩𝟏𝟏 𝐋𝐋𝟏𝟏 ∗ � 𝟑𝟑 + 𝑳𝑳𝟐𝟐 + 𝑳𝑳𝟑𝟑 � + ⎤⎢⎥𝑳𝑳
𝐩𝐩𝟏𝟏 𝐋𝐋𝟐𝟐 ∗ �𝑳𝑳𝟑𝟑 + 𝟐𝟐𝟐𝟐� +⎢⎥𝒛𝒛� = ⎢
⎥�𝑷𝑷
𝑳𝑳𝟐𝟐⎢𝟎𝟎. 𝟓𝟓(𝐩𝐩𝟐𝟐 − 𝐩𝐩𝟏𝟏 )𝐋𝐋𝟐𝟐 ∗ �𝑳𝑳𝟑𝟑 + 𝟑𝟑 � + ⎥⎢⎥𝑳𝑳
𝟎𝟎. 𝟓𝟓𝐩𝐩𝟐𝟐 𝐋𝐋𝟑𝟑 ∗ 𝟑𝟑𝟑𝟑⎢⎥

(2-11)

𝒑𝒑𝟑𝟑 + 𝒑𝒑𝟒𝟒

𝑳𝑳𝟒𝟒𝟒𝟒 + 𝑨𝑨𝟏𝟏 𝑳𝑳𝟑𝟑𝟒𝟒 − 𝑨𝑨𝟐𝟐 𝑳𝑳𝟐𝟐𝟒𝟒 − 𝑨𝑨𝟑𝟑 𝑳𝑳𝟏𝟏𝟒𝟒 − 𝑨𝑨𝟒𝟒 = 𝟎𝟎

The total pressure above the dredge line can now be
determined by applying the area of known pressure
exerting on the sheet pile wall and summing all theforces in the horizontal:
𝐏𝐏 = 𝟎𝟎. 𝟓𝟓𝐩𝐩𝟏𝟏 𝐋𝐋𝟏𝟏 + 𝐩𝐩𝟏𝟏 𝐋𝐋𝟐𝟐 + 𝟎𝟎. 𝟓𝟓(𝐩𝐩𝟐𝟐 − 𝐩𝐩𝟏𝟏 )𝐋𝐋𝟐𝟐 +𝟎𝟎. 𝟓𝟓𝐩𝐩𝟐𝟐 𝐋𝐋𝟑𝟑

𝒑𝒑𝟑𝟑 𝑳𝑳𝟒𝟒 −𝟐𝟐𝟐𝟐

The four equations above are then rearranged todetermine L 4 , solving an equation to the fourth
power:

(2-5)

𝐚𝐚

𝑳𝑳

𝑷𝑷(𝑳𝑳𝟒𝟒 + 𝒛𝒛�) − (𝟎𝟎. 𝟓𝟓𝑳𝑳𝟒𝟒 𝒑𝒑𝟑𝟑 ) � 𝟑𝟑𝟒𝟒� + 𝟎𝟎. 𝟓𝟓𝑳𝑳𝟓𝟓 (𝒑𝒑𝟑𝟑 +(2-3)

𝐩𝐩𝟓𝟓 = �𝛄𝛄𝐋𝐋𝟏𝟏 + 𝛄𝛄′ 𝐋𝐋𝟐𝟐 )𝑲𝑲𝒑𝒑 + 𝜸𝜸′ 𝑳𝑳𝟑𝟑 (𝐊𝐊 𝐩𝐩 − 𝑲𝑲𝒂𝒂 � (2-17)

Knowing the length L 4 , the sheet pile penetrating
depth is simply:(2-7)
𝑫𝑫𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕 = 𝑳𝑳𝟑𝟑 + 𝑳𝑳𝟒𝟒

Thus the only unknown is the length of L 4 , which isdetermined by deriving four equations containing the
unknown length L 4 by the formation of an equation
for 𝐩𝐩𝟑𝟑 by using the given ratio of 1 vertical to𝛄𝛄′ (𝐊𝐊 𝐩𝐩 − 𝐊𝐊 𝐚𝐚 ) in the horizontal (2-8), determining thenet pressure 𝐩𝐩𝟒𝟒 at the bottom of the sheet pile bysubtracting the total active pressure from the totalpassive pressure (2-9), summing the moments about
the point B at the bottom of the sheet pile (2-10) and
deriving an equation for the length L 5 , which forms
apart of the unknown length L 4 (2-11):
𝐩𝐩𝟑𝟑 = 𝐋𝐋𝟒𝟒 (𝐊𝐊 𝐩𝐩 − 𝐊𝐊 𝐚𝐚 )𝛄𝛄′
(2-8)(2-18)As a designer it is important to note that a certain
factor of safety (FOS) has to be satisfied to avoid any
possibility of the soil-system failure. This depends onthe designer whether to apply a FOS to the calculated
sheet pile penetrating depth, or to decrease the overestimated Rankine’s passive pressure coefficient.
As mentioned earlier it is important to determine themaximum bending moment distributed on the sheet
pile wall for design purposes. Thus we analyse thesheet pile as a normal beam to find the point of zero86

GEOMATE- Brisbane, Nov. 19-21, 2014

(2-20), the obtained solutions from this example aretabulated in table 1.

shear force, hence at this point the maximum bending
moment will occur:

𝐙𝐙 ′ = �𝟐𝟐𝟐𝟐(𝐊𝐊𝐩𝐩 −𝐊𝐊𝐚𝐚 )𝛄𝛄′𝑳𝑳𝟒𝟒
= 𝟔𝟔. 𝟎𝟎𝟎𝟎𝟎𝟎 𝒎𝒎
𝑫𝑫𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕 = 𝟔𝟔. 𝟔𝟔𝟔𝟔 𝒎𝒎
𝑭𝑭𝑭𝑭𝑭𝑭 = 𝟏𝟏. 𝟑𝟑
𝑫𝑫𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂 = 𝟖𝟖. 𝟔𝟔𝟔𝟔 𝒎𝒎
𝑳𝑳𝒕𝒕𝒕𝒕𝒕𝒕 = 𝟏𝟏𝟏𝟏. 𝟕𝟕𝟕𝟕 𝐦𝐦
𝑴𝑴𝒎𝒎𝒎𝒎𝒎𝒎 = 𝟕𝟕𝟕𝟕𝟕𝟕. 𝟏𝟏𝟏𝟏 𝐤𝐤𝐤𝐤. 𝐦𝐦(2-19)𝒁𝒁′

𝐌𝐌𝐌𝐌𝐌𝐌𝐌𝐌 = 𝐏𝐏(𝒛𝒛� + 𝒁𝒁′ ) − [𝟎𝟎. 𝟓𝟓𝜸𝜸′ 𝒁𝒁′ 𝟐𝟐 �𝐊𝐊 𝐩𝐩 − 𝐊𝐊 𝐚𝐚 �]( 𝟑𝟑 )(2-20)THE EXAMPLE

Tab. 1

The following example is solved analytically using
the analytical design approach discussed in theprevious section. The example will also be solved in
an excel spread sheet developed in the next section sothat the relevance of developing design tools for sheet
pile walls can be understood.

Output for specific problem

The stability of sheet pile walls depends on thepassive resisting capacity of the soil below the depthof excavation to prevent overturning. The depth of
the sheet pile walls below the dredge line isdetermined by the difference between passive andactive pressures acting on the wall. The theoreticaldepth (𝑫𝑫𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕 = 𝟔𝟔. 𝟔𝟔𝟔𝟔 𝒎𝒎) of penetration below thedredge line is obtained by equating horizontal forces
by taking the sum of moments about an assumed
bottom of piling. The designers would have to apply
a FOS, normally between 1.2 and 1.4, to provide
additional penetration depth such as 𝑫𝑫𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂𝒂 =𝟖𝟖. 𝟔𝟔𝟔𝟔 𝒎𝒎 in Table 1 to finalise their design.

The solutions obtained from the analytical methods
should then be validated, by comparing with thesolutions obtained from the excel spread sheet. This
will be discussed in the following section.
DEVELOPMENT OF EXCEL SPREAD SHEET

It was aimed at developing a spread sheet toautomatically solve the complex derived analyticalequations by means of only entering the known input
data by the user clearly indicated by the labelled cells
in Fig. 8.
Fig. 7

Cantilever Sheet Pile penetrating sand [2]After a geotechnical survey had been done, certain
input parameters will be known. These input
parameters give important information such as thelength L 1 and L 2 above the dredge line. For theexample in figure 7, the cohesion c 1 and c 2 of the soil
has zero cohesion and the sheet pile wall is only
penetrating sand. Also the friction angle 𝝓𝝓 and theunit weight 𝜸𝜸 and saturated unit weight 𝜸𝜸𝒔𝒔𝒔𝒔𝒔𝒔 of thesand are given in figure 7. Using equations (2-1) toFig. 887

Required Input Data

GEOMATE- Brisbane, Nov. 19-21, 2014

The analytical equations are identified in the excel
spread sheet under automatic analysis:

The development of this excel spread sheet is usefulin the design of sheet piles for undergoing parametricstudies to make relevant comparisons and being able
to get a result immediately with only changing the
input data.
CONCLUSION AND FUTURE WORK

Fig. 9Designing sheet pile walls using the analyticalmethods is a very tedious procedure and may take along time. In the Engineering Industry time is moneyand being able to develop this design tool that cansolve these equations automatically with the sameaccuracy, creating visual solutions and doing all of
this in a much faster time with only the necessity of
inputting known data, is a fantastic tool. The
solutions obtained using the excel spread sheet issimilar to the solutions derived from the analyticalmethods, thus the excel spread sheet has been provenboth accurate and successful. Such a design tool isdefinitely needed and can be most valuable in theengineering industry.

Automatic analysis solved in excel

The important output figures such as length L 4 ,theoretical depth D t , actual depth D a and maximum
bending moment M max are indicated in figure 10.

Fig. 10

However these analytical methods of design, has
found to be very conservative due to several
simplifications and assumptions made. Things likethe ground settlement and possible surface failures
are important information and cannot be obtained
from the analytical methods. For future work, it is
proposed to use numerical modeling such as FLAC
2D software to analyze soil-structure interaction andobtain critical information to provide higher accuracyof results.

Output data

Due to the fact that the analytical methods andcalculations does not provide the outputs graphically,a simple table has been developed to give graphicalvisual outputs for the deformation, shear force andbending moments distributed along the sheet pile wallin this development.

REFERENCES[1] J.E. Bowles, Foundation Analysis and Design,
5th ed. New York: McGraw-Hill, 1996.
[2] Braja M. Das, Principles of Foundation
Engineering, 3rd ed. Boston: PWS- KENT
Publishing Company, 1990.
[3] Geotechnical Engineering Bureau, Geotechnical
Design Procedure for flexible wall systems.:
New York State Department Of Transportation,
2007.
[4] California Depratment Of Transportation,
Retaining Walls Design.: Bridge Design
Specifications, 2004.
[5] Whitney Clark Huntington, Earth pressures andRetaining Walls.: Wiley, 1957.

Fig. 11

Visual Diagrammatic Output Figures

88Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SETTLEMENT BEHAVIOR OF DREDGED CLAY RECLAIMED LANDBY VACUUM CONSOLIDATION METHOD AND PROPOSAL OF ITSPREDICTION
Ikeda1 H., Kawano1 M., Kiyoyama1 T., Yamamoto2 S., Takase2 E., Katagiri3 M., Ohishi3 K. and Yoshifuku3 T.
1
Kyushu Regional Construction Bureau, MLIT; 2Coastal Development Institute of Technology;
3
Nikken Sekkei Civil Engineering, Japan
ABSTRACTOne of the methods for increasing the capacity of disposal pond for dredged marine clay is the reduction of
volume in already reclaimed dredged clay ground. In the vacuum consolidation method, the pore water in thereclaimed clay ground is squeezed by vacuum pumps, and ground surface settles. In this paper, the monitoring
results of reclaimed land with dredged clay by the vacuum consolidation method are introduced. In addition, theresults of reclamation analysis to obtain initial condition of reclaimed land before acting of vacuum pressure, theprediction and post analysis of ground behavior in the vacuum consolidation are described. The prediction
procedure of vacuum consolidation method is proposed, and its evaluation is reported.
Keywords: Dredged Clay, Vacuum Consolidation, Monitoring, Analysis

At a part of the S3-area in Shin-Moji Oki disposal
pond, a vacuum consolidation method was
performed. In this paper, a construction example ofthe vacuum consolidation method for the reclaimed
land with dredged clay is introduced. The results ofmonitoring and soil investigation after the vacuuming
are described. In addition, the pre-analysis and post
analysis for the vacuum consolidation method arereported. The key point of prediction of vacuum
consolidation method for reclaimed land withdredged clay is emphasized.

INTRODUCTION
The dredging of sea bottom sediment has been
continuously conducted along the Japanese coastal
area. One of the major purposes of dredging is thewidening and deepening of existing navigation
channels and anchorage areas to accommodate larger
ship traffics. Dredging process normally comprises
three phases that starts with the underwater
excavation, then transportation and ends withdisposal. The most common disposal method for
dredged clay is to discharge dredged clay into adisposal pond in the sea surrounded by containment
dikes.
As the construction of a disposal pond in the sea
requires huge cost in general, it is becoming difficult
to construct a new one. Therefore, the long use ofexisting disposal ponds has become important andurgent technical issue.
While the dredged clay is discharged into thepond, the clay layer increases its thickness andgradually approaches to the capacity of disposal
pond. In parallel to the above process, the dredged
clay layer is subjected to time-dependent self-weightconsolidation and reduces its volume. Therefore thewater content and consolidation characteristics ofdredged clay at the time of discharging are influential
factors for the life of disposal pond.
One of an extension of the life of disposal pond is
the reduction of volume in already reclaimed dredged
clay ground. The vacuum consolidation method withvertical drainage is one of ground improvement
methods for very soft ground. In this method, theatmospheric pressure as the loading pressure is used,
and the banking of fill materials is not necessary. The
maximum pressure, however, may be 70 to 80 kPa at
most due to the effectiveness of vacuuming pump.

OUTLINE OF SHIN MOJIOKI DISPOSAL POND
Figure 1 shows the Strait of Kanmon between the
Honshu and Kyushu Islands in Japan. Kanmon
waterway located in this Strait is one of the busiest
sea routes in Japan. To accommodate larger shiptraffics, the dredging in this waterway has been
conducted. For the protection of marine environment,

Disposal pond

Fig. 1 Site of Shin-Moji Oki disposal pond
89GEOMATE- Brisbane, Nov. 19-21, 2014

dredged materials, mostly clays have to be discharged
into the Kanda Oki and Shin-Moji Oki disposal ponds
shown in Fig.1.
Figure 2 shows the plan view of Kanda Oki and
Shin-Moji Oki disposal ponds. The Shin-Moji Oki
disposal pond is separated into three areas, S1-, S2and S3-areas. The S1- and S2-areas were reclaimed atearly stage, and are used as airfield. The S3-area isworking as disposal pond at present. The rest capacityof S3-area deceases gradually, and the mud surface
will arrive at the designed level in the next years.
In the S3-area, the additional embankment that
constructed with mechanical dewatered clay lumps ismounted near the revetment for an increase in thecapacity of disposal pond. The mechanical propertiesof dewatered clay lumps and its aggregates werereported by Moriki et al.1).

S2-area

Shin-Moji Oki
disposal pond
2425×900

with rubble mound and replaced sand. The original
elevation of sea bottom was DL-6.7 m, and the
alluvial clay having about 7 m of thickness overlaid
the diluvial layer. The elevation of revetment was
DL+8.0 m, and that of dredged clay layer was at
DL+6.2 m.
In the design of vacuum consolidation, the upperand lower sealing layers were determined as 1 m ofthickness according to the manual of vacuum
consolidation drain method2). The void water
squeezed from dredged clay layer by vacuuming was
gathered into horizontal tubes, and was flowed
through them up to the vacuum pump. For the controlof vacuum pressure, the origin, edge and tip pressures
shown in Fig. 4 were measured. The origin pressure
was the value of a vacuum pump. The edge and tip
pressures were measured at the end of horizontal tube
on the ground and at the tip of plastic board drain(PBD) as a vertical drain, respectively.
The pitches of vertical drains were set at 1.0 m and1.7 m in the S-type area and R-type area, respectively.
Here, the R-type area was designed as a buffer zoneof vertical settlements between S-type and nontreatment areas.
The settlement plates were set at the grid withintervals of about 10 m. After about 30 days from thestop of vacuuming, the post soil investigations at thecenter of the S-type area and near the boundary of the
R-type were performed at four lines and as shown in
Fig. 4.

Kanda Okidisposal pond
1700×900

Kanda
area

S3-areaS1-areaFig. 2 Plan view of disposal pond

482

Area for Vacuum
Consolidation(50×287m)

Shin-Moji Oki Disposal Pond (S3)

Figure 5 shows the settlement behavior of vacuum
consolidation area measured by the settlement plates.
The number of horizontal axis is the construction
points from the edge of west revetment, and S-1
through S-4 are the positions of settlement plate in Fig.
4. In the initial condition before the installing of
PBDs, the elevations were around 6.2 m. Figure 5 (a)is the state at the end of June before the vacuuming.
The maximum consolidation settlement is about 1.2
m due to the disappearance of excess pore waterpressure occurred after the installation of PBDs.
Figure 5 (b) shows the ground elevations on

1485

Fig. 3 Condition of S3-area
MONITORINGPLAN
CONSOLIDATIONFORVACUUM

Figure 4 shows the schematic cross section of
vacuum consolidation area near the North revetment.
The left hand side is the North revetment constructed

S-1 10.70 S-2

30.85
+8.0m
HWL+4.04m

VACUUMING AND MONITORING RESULTS

origin pressure
Settlement plate
Vucuum pump
Sealing layer
1.0

14.00

S-3 10.50 S-4

Position of post soil survey+6.2m
edge pressure

S-type (@1.0m)

1:2.0
Rubble mound levee windening-6.7m

tip pressure

R-type(@1.7m)Sealing layer
1.0

repalced sand-13.9mAlluvial clay
Diluvial
layer
50.00

Fig. 4 Design of ground improvement and monitoring plan in vacuum consolidation
90

GEOMATE- Brisbane, Nov. 19-21, 201412/02/2013 and that was one month later after
stopping the vacuuming. The total settlements after
the installation of PBDs were 1 to 3 m. The maximum
settlement of about 3 m generated around the crosspoint of No. 32 and S2 (No. 32-2).

SOIL INVESTIGATION AFTER VACUUMING

Elevation, m

DL-m

6.5
6.0
5.5
5.0
4.5
4.0
3.5
3.0

6-6.5
5.5-6
5-5.5
4.5-5
4-4.5
3.5-4
3-3.5

S4

15 14 32
13 12 28
11 10 249 8 207 6 16
5 4 123 2 8134

S1(a) before vacuuming

DL-m

6.5
6.0
5.5
5.0
4.5
4.0
3.5
3.0

Elevation, m

S4

1534
14 133212 112810 924 8 720 6 5164 3122 1 8

S1

6-6.5
5.5-6
5-5.5
4.5-5
4-4.5
3.5-4
3-3.5

0

S-type4
Elwvation DL+m

Elapsed Times from Installed PBDs, days

100

200

300

400

500

0
Measured Data at No.32-2
Post-Analysis (Ch≠Cv, Cc0.82, Cv120, -40kPa)
Pre-Analysis (Ch≠Cv, Cc0.95, Cv40, -60kPa)
At Design (Ch=Cv, eo=Const., Cc=1.04, Cv=40)

Total Settlement cm

50
100

350

150

No.16
No.24
No.28
No.32

0
-2
-4
Degree of Consolidtion：80％（60kPa）-6-8(a) S-type area

200

300

Vacuum pressure:60kPa

2

150

250

Consolidation yield stress kPa
50
100

6

(b) one month later from stop of vacuuming
Fig. 5 Settlement behavior in ground improvement0

The soil investigation was performed one month
later after the stop of vacuuming. The sites of soil
investigation were eight points set at the intersections
between S2 and S3, and No.16, 24, 28 and 32. Figures
7(a) and 7(b) show the distribution of consolidation
yield stress at the S2- and S3- lines, respectively. The
anticipated vertical effective stress distributions at 60
kPa of working vacuum pressure and 80 % ofworking pressure are also drawn. The consolidation
yield stresses of S2-line with the installing space of
1.0 m exceeded over 80 % of 60 kPa of vacuum
pressure. The S3-line located at the boundary
between S- and R-types did not reach 80 % ofeffective stress. The degree of consolidation wasrecognized to be dependent on the space of installed
PBDs.

0

Stop of Vacuuming

Consolidation yield stress kPa
50
100

150

6

Loading of
Vacuum4

leak of vacuum pressure

Vacuum pressure:60kPa2

Elevation DL+mFig. 6 Monitoring result and pre- and post- analysis

Figure 6 shows the time – settlement relation at
the cross point of No.32 and S2 (No.32-2). The originof horizontal axis is the installation of PBDs. In thisfigure, the prediction at design time are simulated.
The consolidation settlement at the point of
No.32-2 before the vacuuming generated about 1 m
after the installation of PBDs. The initial rate of
consolidation settlement was high, and thendecreased gradually. On the middle of this behavior
during the vacuuming, a decrease in the rate of
consolidation settlement occurred. This is the leak of
vacuum pressure. After the change of vacuum pumpafter 150 days from the start, the consolidation
settlement increased. After about 200 days from theinstallation of PBDs, the consolidation settlement
converged to form 300 cm of total settlement. Using
the approximation of hyperbolic curve, the time withconsolidation degree 90 % was equivalent to 230 days
from the install of PBDs.

0

R-type
No.16
No.24
No.28
No.32

-2
-4
-6
-8

Degree of Consolidation：80％（60kPa）

-10
-12

(b) R-type area
Fig. 7 Distribution of consolidation yield stress
Figure 8 shows the results of consolidation tests
on the samples acted the vacuum pressure. The
compression curves shown in Fig.8 (a) wererepresented from the over-consolidated to normal
consolidated conditions, and the consolidation yieldstresses were from 40 to 140 kPa mentioned earlier.
The compression indexes, Cc ranged from 0.53 to
0.95. The coefficients of consolidation in the normal91

GEOMATE- Brisbane, Nov. 19-21, 2014

consolidation condition were distributed from 40 to
400 cm2/day.
Cc= 0.82

Cc= 0.95

Void Ratio

2
1.5
1

All Data, No.16, 24, 28
No.32, S-type, DL 2.2m
No.32, S-type, DL-2.8m
No.32, S-type, DL-4.4m
No.32, S-type, DL-6.6m

0.5

Cc= 0.53

Determination of ground model at installation of
PBDs

0
1

10
100
1000
Consolidation Pressure kPa

10000

To predict the stress condition of reclaimed
ground, the reclamation analysis named ‘CONAN’
was used. The CONAN was developed based on a
generalized one-dimensional consolidation theory4).
The detailed procedure of this numerical method was
described by Katagiri et al.5).
The ground model including with consolidation
parameters should be determined by numericalsimulation of the reclamation stage. From the backanalysis of preceding reclamation with dredged clay,
the consolidation parameters are identified. Using
these parameters the soil profile of the reclaimed
ground at the installation of PBDs can be predicted by
the CONAN.
Figure 10 shows the measured elevation of thenorth area of disposal pond monitored from 2003 to
2011. The result of reclamation analysis with the bestfit combination of consolidation parameters
identified at the excavation area6) is simulated in thesame figure. In this area, the Alluvial Clay layer
presents within 5 m in thickness. The result of
reclamation analysis was recognized to reproduce themeasured data.
Figure 11 shows the distributions of void ratio andeffective stress of the reclaimed ground in north areaat the installation of PBDs obtained by thereclamation analysis. In Fig.11 (a), the measured data(a) compression curves

Coef. Of Consolidation cm2/day

10000

1000

Upper： round 400

Cｖ= 120100
All Data (No.16,24,28)
No.32, S-type, DL 2.2
No.32, S-type, DL-2.8
No.32, S-Type, DL-4.4
No.32, S-Type, DL-6.6

10

lower： round 40

1
1

10

100

1000

10000

Consolidation Pressure kPa(b) coefficient of consolidation
Fig. 8 Consolidation characteristics
BACK
ANALYSISFORCONSOLIDATION METHODVACUUM

Using the results of monitoring and soil
investigation, several post-analyses were performed.
The back analysis were used the Cc-method forconsolidation settlement and Barron’s Equation forprogress of consolidation. To express theconsolidation behavior of lower seal layer, thepractical method for partial vertical drains proposedby Hitachi et al. 3) was adapted.

Compression Index

Initail Void Ratio

2

Evaluation for prediction at design

2.5

3

3.5

0

0
1

Depth (m)At the design of vertical drains, the elevation ofreclaimed land was increasing as the dredged clays
were poured into the disposal pond. Then, the groundmodel as uniform condition shown in Fig.9 (a) was
assumed. The compression index was also set at 1.04
as shown in Fig.9 (b), and the coefficient ofconsolidation was 40 cm2/day as the lowest limit of
test results.
The prediction at the design was shown as “+” inFig. 6. To compare to measured data, the data wasplotted from 50 days from installing of PBDs. This
time was when the vacuuming started. The settlement
was measured from the installation of PBDs, and was

Designed Value；
2.95

1

2

2

3

3

4

4

5
6
7
8
9
10

0.5

1

1.5

5
6
7

H19-1-2
H19-1-3
H22-2T-1
H22-2T-2

Designed Value；1.04

H19-1-2

8

H19-1-3

9

H22-2T-1

10

H22-2T-2(a) void ratio(b) compression index
Fig. 9 Results of early soil investigations

92

2

0

Depth (m)2.5

approximately generated 100 cm just before thevacuuming and 200 cm during the vacuuming process.
The prediction of design was not represented for the
behavior after the installation of PBDs before
vacuuming, and was expressed the behavior only
after the vacuuming. The settlement after the
installation of PBDs was the disappearance of excess
pore water pressure accumulated during thereclamation of dredged clay. The model at the design
did not consider this excess pore water pressure, andcould not express the measured settlement.

GEOMATE- Brisbane, Nov. 19-21, 2014

Year

Elavation of ground （ＤＬ－ｍ）

15.0

180
1202009 2010 2011 2012 2013
01999 2000 2001 2002 2003602004 2005 2006 2007 2008

10.0
5.0
0.0
-5.0

-10.0

Reclamation Analysis (north area)

sea bottom

Max. height of ground in Plan
Ave. Elevation of reclaimed ground-15.0

Fig. 10 Measured data and reclamation analysis result in the north area
shown in Fig. 9 (a) were also plotted at elevation
converted with (DL+6.06 m) of ground surface. The
result of reclamation analysis presents the measured
data and to be believable as ground condition ofreclaimed land with dredged clay. Figure 11 (b)shows the distribution of effective stress in reclaimed
land. The pore water pressure is the difference
between total stress and effective stress.
The pre-analysis in Fig. 6 is the prediction of theground model obtained from Fig. 11. This analysis
used the horizontal coefficient of consolidation
depended on space of PBDs (Ch =(0.77*d – 0.24)*Cv,
d; space of PBD)6). The consolidation parameters
obtained from the soil investigation shown in Fig. 9(Cc=0.95, Cv=40 cm2/day) were used. The vacuum
pressure of 60 kPa was supplied. Whole settlement
behavior after installing of PBDs to stop vacuuming
was similar to measured data, but the magnitudes ofsettlement and consolidation rate were different.

These identified consolidation parameters wereplotted in Fig. 8. Both the compression index andcoefficient of consolidation were located in the
middle of scattering data. It was concluded that theidentified parameters were suitable for this groundcondition.
void ratio
2
40

Eff. Stress, σv (kN/m2)
0
50
100
150

6

15.0

Identified parameters of consolidation and theirevaluation

10.0: measured data
(H19-1, H22-2T)
GL; DL+6.06m

5.0
0.0
-5.0

15.0
Elevation of ground (DL-m)

Elevation of ground (DL-m)

◆

10.0
5.0
0.0
-5.0

-10.0

-10.0

-15.0

-15.0

(a) viod ratio(b) effective stressFig. 11 Results of reclamation analysis

In the post analysis, the parameters ofconsolidation and vacuum pressure were changed to
fit the measured data. As a result, the Cc was
identified as 0.82 and Cv was 120 cm2/day. To
identify the consolidation parameters, this fitting oftime-settlement behavior was not enough and moreevidence was needed. Figure 12 shows the analyzed
water content distributions of reclaimed layer at
U=90 %. In this figure, the initial condition before
installing of PBDs and the water contents obtained
from the soil investigation conducted after the stop of
vacuuming were also plotted. The analyzed results
except of the upper part, which is about 1 m as sealing
layer were piled on the surveyed results at No.32.
From these two evidences such as time-settlement
behavior and water content distribution, theconsolidation parameters used in the analysis could
be identified.

8.0

Analyzed result (U=90%)
Intial condition (model)
Survey results (all pionts)
Survey results (No.32)

6.0

Elevation (DL+m)

4.0
2.0
0.0
-2.0
-4.0
-6.0
-8.0

0

50

100

150

200

water content (%)

Fig. 12 Results of soil investigation and analysis

93

GEOMATE- Brisbane, Nov. 19-21, 2014

Prediction procedure of vacuum consolidation
method for a reclaiming land

CONCLUDING REMARKSIn this paper, the vacuum consolidation method
for the reclaimed ground with dredged clay is
introduced. The results of settlement behavior after
the installation of vertical drains and soil
investigation after the vacuuming are shown, and thepre- and back analysis are also described. From these
considerations, a prediction procedure of vacuum
consolidation method for reclaiming clay ground is
proposed. The followings are obtained from thispaper;
1) The ground model determined by limited
ground information at initial design could not
express the monitoring data. In particular, thesettlement behavior after the installation ofvertical drains was different.
2) The ground model determined from the resultof reclamation analysis could be represented
the results of monitoring and soil investigation.
3) From these considerations, a prediction
procedure of vacuum consolidation method
for reclaiming clay ground was proposed.

From above consideration and knowledge, aprediction procedure of vacuum consolidation
method for a reclaiming land is proposed.
A traditional procedure2) of prediction of vacuum
consolidation method for a soft clay ground is i)
determining the model ground using the results of soil
investigation and ii) predicting the time-settlement
behavior by Barron’s equation and Cc-method. In a
reclaiming clay ground, the elevation and groundcondition are changed with time. The elevation andground condition at the installation of vertical drains
are different from those at the soil investigation. It istherefore necessary to predict the elevation andground condition at the installation.
As mentioned earlier, the ground model can be
determined by numerical simulation during thereclamation process. So, the consolidation parameters
can be identified by back analysis, and the elevationand ground condition can be obtained by pre-analysis
using CONAN5) program.
A prediction procedure of vacuum consolidation
method for a reclaiming clay ground are proposed asfollows; i) identifying the consolidation parameters
by back analysis during reclamation process, ii)
predicting the elevation and ground condition ofreclaimed clay ground at the installation of verticaldrains, iii) determining a ground model from theresults of ii), and iv) predicting a settlement behaviorof ground installed vertical drains under vacuuming.
During the reclamation process, CONAN5) developed
from a generalized one-dimensional consolidation
theory4) can be used, Barron’s equation while Ccmethod may be used during the vacuum consolidation
process.
The prediction by the proposed method is shown
as a bold curve in Fig. 13. The gap between measured
data (marked as “△”) and prediction by the proposed
method at 250 days from the installation of drains was
30 cm, and 10 % of predicted settlement. It is
concluded that the proposed method is useful at thedesign of vertical drains for reclaiming lands.
0

50

100

Settlement (cm)0Erapsted Time (day)
150
200
250

300

ACKNOWLEDGEMENTS
The authors would like to thank the technicalcommittee (Chairperson: Prof. K. Zen of Kyushu
University) for their valuable advices.
REFERENCES[1] Moriki, A., Katagiri, M. and Terashi, M.;
Mechanical properties of dewatered dredged clay
lumps, Proc. of 14th Asian Region Conference ofGeo-mechanics and Foundation Engineering,Hong Kong, 2011, DVD-rom.
[2] Association for VCD-Koho; Manual of Vacuum
Consolidation Drain Method, 2010, pp.1-27. (inJapanese).
[3] Hitachi, S., Yamamoto, H., Ikeda, D., Oikawa,
K. and Nakanodo, H.; Consolidation of clay layer
underlying vertical drain improved ground, Proc.
of 29th JGS conference, 1994, pp.2107-2110. (inJapanese).
[4] Imai, G.; Analytical examinations of thefoundations
toformulateconsolidation
phenomena with inherent time-dependence, Proc.
of IS-Hiroshima ’95, Vol. 2, 1995, pp.891-935.
[5] Katagiri, M., Terashi, M. and Kaneko, A.; Backanalysis of reclamation by pump-dredged marine
clay – influence of ground water lowering –,Soils and Foundations, Vol. 41, No. 5, 2001,
pp.73-86.
[6] Ikeda, H., Kawano, M., Kiyoyama, T.,
Yamamoto, S., Takase, E., Katagiri, M., Ohishi,
K. and Yoshifuku, T.; Application of vacuum
consolidation method to sedimentation ofdredged clay, Proc. of 58th GeotechnicalSymposium, 2013, pp.85-92. (in Japanese)

350

50

proposed method (Ch≠Cv; Cc=0.95, Cv=80, -60kPa)
At design (Ch=Cv; eo=2.95, Cc=1.04, Cv=40)

100

Post Analysis (Ch≠Cv; Cc=0.82, Cv=120)
Measured Data at No.32-2

150
200
250

Loading of Vacuum

Stop of Vacuuming

300
350

leak of vacuum pressure

Proposed method

Fig. 13 Evaluation of proposed method

94

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SLOPE STABILITY AND ROCKFALL HAZARD ANALYSIS IN AN
OPEN PIT ZINC MINE
Maged Almandalawi1, Greg You1, Peter Dahlhaus1, Kim Dowling1 and Mohannad Sabry2
Faculty of Science, Federation University Australia; 2School of Engineering, University of Western Sydney,
Australia

1

ABSTRACTRockfalls are a major safety hazard in open cut mines, particularly in large-scale deep pits. The geotechnicaldesign relies on in-situ, site-specific, rock slope data to predict the trajectories and velocities of rockfalls that
present a residual hazard in the mines. This paper presents slope stability analyses using both static general limit
equilibrium methods and finite element stress analyses to estimate unstable areas and slope displacements in the
mid-west slope at Handlebar Hill Open Cut Zinc mine at Mt Isa, Queensland, Australia. A conventional program- RocFall - was used for the slope rockfall risk assessment. Results indicate the possible slope benches involvedin the initiation of rockfalls, and the maximum run-out distance, which could be defined as the pit's hazardous
zone. A rockfall restraining system to absorb the impact energy of boulders and prevent them further falling was
also modelled.
Keywords: Factor of Safety, continuum modeling, shear strength reduction, RocFall, rockfall hazard barrier

different triggering mechanisms and provide
simulations that may inform the design of optimalslope geometry and restraint mechanisms.

INTRODUCTION
Rockfalls are a major risk in open cut mining as
they often involve the unexpected detachment ofrocks from a slope and their rapid movement byrolling or bouncing deeper into the pit. The rockfragments could come to rest on the lower benches
or on the pit floor, generating high risk to workers,
mine assets and the mine environment. The impacts
depend on the size of the rockfalls, slope geometry,
momentum of the rocks, the presence of obstacles
and the site risk management.
Rockfall dynamics are largely a function of themechanical properties of the rock and rock mass,
location of detachment and downslope profile [1].
Falls have two successive mechanisms: the failure(i.e. rock detachment) and its propagation down theslope [2]. Once the potentially unstable areas havebeen identified, the potential run-out of the rockfalls
can be evaluated using propagation models.
This paper presents analyses aimed at better
understanding the rockfall hazard in the Handlebar
Hill Open Cut (HHOC) zinc mine, approximately
20km north of Mount Isa in northern Australia (Fig1). The study focuses on the slope stability of the
mid-west pit, which is characterised by four
geological domains with major discontinuities suchas faults and shear surfaces dipping 60o - 70o to thewest.
Standard models from the Rockscience suite ofprograms [3] were utilised to undertake the analyses.
The main objective of the analyses was to identify
the potential rockfall initiation areas and failure
mechanisms, predict the sensitivity of the slope to

Fig. 195

The HHOC mine pit location and view
looking south. This study focuses on thewestern wall, which is on the right handside of the image.

GEOMATE- Brisbane, Nov. 19-21, 2014

ROCK SLOPE STABILITY ANALYSES
Finite element analysis
Two software packages - Slide 6.0 and Phase2 were used to undertake a limit equilibrium analysis
and construct finite element stress models of the pit
slopes. The purpose of these analyses was to
identify the most likely areas where rockfalls would
be initiated. This information was then used as input
into the rockfall simulation models.

For many decades, limiting equilibrium has
dominated over any other method of analysis for
soil/rock slope stability practitioners. Uncertainty isa key factor in slope design as an increase of one
degree in excavated slope angle might make theslope unstable. Conventional slope practice is often
based on a FOS which can not explicitly address theuncertainty, which ultimately led to the developmentof probabilistic finite element slope stability analysis[6]. In addition, the advantage of finite element
methods for slope stability analysis over traditional
limit equilibrium methods is that no assumptions
needed to be made pre-analysis about the shape andlocation of the failure surface and geometry, such as
the failure slice side forces and directions.
To reduce the limitations of conventional
methods, the finite element shear strength reduction
method was used in which the explicit material
deformation and failure progression can be modelled.
The strength reduction factor of the mid-west slope
was modelled using the numerical method of thePhase2 software. The results are shown in Fig 3.

Limiting equilibrium analysis
Limit equilibrium analysis of the overall slope atthe HHOC pit was analysed using Slide 6.0.
Modern limit equilibrium software (such as Slide) ismaking it possible to handle ever-increasing
complexity in the analysis. It is now possible to deal
with complex stratigraphy, highly irregular porewater pressure conditions, various linear andnonlinear shear strength models, almost any kind ofslip surface shape, concentrated loads, and structural
reinforcement [4]. All methods used in limit
equilibrium analysis are based on a comparison offorces (moments or stresses) resisting instability ofthe mass with those that cause instability (disturbing
forces).
In slope stability analysis, the Factor of Safety(FOS) may be considered as the ratio of resisting
shear strength to the disturbing shear stresses atinitial failure [5], with a typical FOS for open pit
slope design ranging between 1.1 and 1.5. The
potential failure surface is assumed to be directed by
the linear Mohr-Coulomb relationship between rockshear strength and the normal stress applied on theslope failure surface.
The results of the general limit equilibrium
analysis for the HHOC pit slope is shown in Fig 2.
The critical surface specifies a minimum FOS of
1.21 for slope instability generated by the general
limit equilibrium analysis.

Fig. 3Modelled strength reduction factor for the
mid-west slope.

The resulting critical strength reduction factor(SRF) is 1.2 at maximum total displacement 0.026m.
Rockfall mechanisms
The movement of a numerical-continuum body isa continuous time sequence of displacements. The
rock material will occupy different configurations ofsize and shape at different times so that a particle
occupies a series of points in space which describe apath line.
The displacement vectors and contours
illustrated in Fig 4, shows that the most of rockdisplacements are close to the major discontinuities
at the upper part of the slope surface. The slope ismost likely influenced by the reduction in thestrength (mechanical) properties of the rock masses
in these zones.

Fig. 2 FOS using limiting equilibrium analysis.
(the critical surface shown has FOS = 1.21)

96

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 4Modelled displacement vectors of deformation showing the possible directions of block rotation andsliding modes.
For that reason, it is necessary to analyse thepotential for rockfalls in high rainfall events. In
addition investigating the causes of historical
rockfalls (and mine accidents) can help planning to
avoid future rockfalls.

Continuum modelling was used to determine thetotal displacements in the slopes and the locations ofyielded elements in the rock mass shows criticalstate conditions as illustrated in Fig 5.

ROCKFALL SIMULATIONS
An assessment of rockfalls was undertaken to
identify the potential fate of blocks that may
detached from unstable pit slope faces and therefore,
to improve the safety at the mine. The analysis wascompleted using RocFall, a program that simulates
the trajectories of rocks falling from the slope. The
trajectory is modelled as a two dimensional rockfall
simulation largely based on the slope geometry.
Using statistical analyses, the method calculates theprobable trajectories, energy, velocity and bounceheight envelopes for individual rock blocks. The
entire slope can be modelled by the program, so thatthe ultimate resting locations of rockfalls can be
determined, and the results are graphed withcomprehensive statistics automatically calculated [3].
Besides the slope geometry, the program requires
input data such as the slope roughness, restitutionsof normal and tangential rock energy, coefficient ofrolling friction and rock mechanical parameters.
To account for the uncertainty in the definition of
the input parameters, stochastic variability is used.
The determination of selected standard deviations
for input parameters of detached boulders is required.

Fig. 5 The total displacement in the slope. The mostcritical displacement for the slope surface
on which the proposed rocks could be
detached, is located in the bottom of theramp and nearby the upper benches aroundthe haulage road.
Generally, rockfalls could be initiated by specificclimatic conditions, which may create some changes
to the forces acting on the slope. This is especiallythe case in tropical zones (e.g. the HHOC mine
location), which experience a season of heavy rains.
Rainfall events may rapidly increase pore pressuresdue to infiltration through the rock mass. At suchtimes, the potential of rockfall initiation willprobably be higher than during drier seasons.

97

GEOMATE- Brisbane, Nov. 19-21, 2014

The potential rockfalls in the HHOC pit were
initially modelled using a starting point located at
the top slope vertex (0, 0), as shown in Fig 4. In thissimulation, the source of the rockfalls is theVolcanics formation rock mass and their fallingFig. 6

paths are illustrated in Fig 6. A number of 50
detached rocks was used, each of 300 Kg weight and28 Kn/m3 density. The simulation calculated that all
rockfalls would end on the haulage ramp.

Results of the simulation of a number of possible rockfalls from the top crest source area, using themodel inputs listed in Table 1.

Table 1 The input parameters of rock mass materials used in the above simulation
Rock mass material
Volcanics
Magazine Shale
Spears Siltstone
Urquhart ShaleRn(mean | std)
0.44 | 0.04
0.46 | 0.04
0.47 | 0.04
0.48 | 0.04

Rt
(mean | std)

Phi(mean | std)

Roughness(std)

Colour

0.87 | 0.04

150 | 00Black0.89 | 0.04

160 | 00Blue

0.91 | 0.04

360 | 00Green

0.93 | 0.04

350 | 00Red

A second sumulation was run using a starting
vertex in the Magazine Shale, which is from thelower bench following the the ramp on the slope
surface. This area is regarded as a probable source
for rock detatchments based on the results of themodelled displacement vectors (Fig 4).

The rockfalls source point and their paths areillustrated in Fig 7 (A). The same number of 50
detached rocks were used, 300 Kg weight and 26.5
Kn/m3 density for each falling block. The simulation
predicts that many rockfalls would end on the pit
floor and away from the toe of the slope.

98

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 7

The results of the RocFall simulations for the rockfalls sourced from the Magazine Shale on the top
bench face. (A) Red lines show rockfall trajectories and the horizontal distances of rock ends points. (B)The bar chart shows the distances and numbers of rockfalls from the source area. The majority of
rockfalls travelled horizontally to a stop point, indicating that a probable hazard exists and that the
installation of an effective protective system was required. (C) Shows the distributions of rockfall
bounce heights above the ground level. (D) Shows the total kinetic energy distributed on the slope andthe numbers of fallen rocks; the final impact energy on the ground is important for a safety design of the99

GEOMATE- Brisbane, Nov. 19-21, 2014

protective barrier fence or windrow.
vectors illustrated the potential areas for slope
instability and the potential areas of failures were
contoured.
Rockfalls simulations confirmed the potential for
individual rocks dislodged from the Volcanic rockformation at the slope crest to travel down slope andcome to rest on the haulage ramp. By contrast,
blocks falling from the top bench of the Magazine
Shale rock mass, can possibly travel beyond theslope toe and onto the pit floor, presenting a
hazardous zone. The models show that a barrier
located at the foot of the slope on the pit floor,
would be required to safely prevent the falling rocks
reaching the mining operation zone.
The installation of a protective structure may
partially control the rockfalls from the slope but thehazard cannot be fully eliminated.

Modeling a physical barrier for rockfalls
Assuming that rockfalls will be inevitable, thenrockfall restraint must be considered.
A number of protective measures have been
identified for the prevention of impacts on people
and assets from rockfalls in open pit mines [7].
These include flexible rockfall barriers, identifying
effective berm widths, bunds constructed on
production berms and using draped mesh.
Windrows and catch barriers could be positioned
to stop rockfalls from moving further down slope.
Barriers and collectors can be modelled in RocFall
as a line segment that can be positioned anywhere
along a slope so as to intercept the paths of the rocks
as they fall down the slope surface. The analysis
includes the kinetic energy of the falling rocks andtheir impact energy could determine the location andcapacity of the rockfall barrier. The proposed barrier
protection structure at the HHOC mine wasmodelled as perfectly inelastic; therefore rockfalls
that reach the barrier will finally stop. The rocks will
not bounce back and just will fall straight down-wallto the foot of the barrier. The horizontal locations for
maximum trajectories of falling blocks are shown in
Fig 8.

Fig. 8ACKNOWLEDGEMENTS
The authors sincerely extend their appreciation to
Glencore Zinc Asset Australia for their support ofthis research project, and in particular, Dr Ahmed
Soliman, Principal Geotechnical Advisor.
REFERENCES[1] Cheng YK, ‘Assessing Rockfall Hazards Usinga Three-Dimensional Numerical Model Basedon High Resolution DEM’, Proceedings of the
22nd International Offshore and Polar
Engineering Conference, June 17-22, 2012
Rhodes, Greece.
[2] Jaboyedoff M, Dudt JP & Labiouse V, 'An
attempt to refine rockfall hazard zoning basedon the kinetic energy, frequency andfragmentation degree', Nat. Hazards Earth Syst.
Sci., V: 5, 2005 pp: 621–632.
[3] Rocscience Inc, 2010, 'Slide, Phase 2 & RocFall
programs, Rocscience Inc. Toronto, Ontario,
Canada. www.rocscience.com[4] Krahn J., 2003, ‘The limits of limit equilibrium
analyses’, The 2001 R.M. Hardy Lecture, NRC,
Canada.
[5] Cheng YM & Lau CK, ‘Slope stability analysis
and stabilization: New methods and insight’,Routledge Press, USA. 2008.
[6] Kainthola A, Verma D, Thareja R & Singh TN,‘A Review on Numerical Slope Stability
Analysis’, Int Jour of Sci, Eng & Tech Res(IJSETR), Vol 2, No 6, June 2013[7] Meyers A, ‘Fundamental Techniques for
Reducing Risk Associated with Instabilities in
Mining Slopes’, Int Jour Min & Geo Eng, Vol.
45, No. 1, December 2011, pp. 43-55.

Simulated horizontal location of rockfall
end points utilizing a perfectly inelastic
barrier 25 metres from the slope toe.

CONCLUSION
Rockfalls are considered as a significant hazard
in open cut mines. Blocks falling from high up on aslope can easily travel into the pit floor may destroy
mining infrastructure and present a serious safety
hazard for mine personnel. At the mid-west slope ofthe HHOC mine, the results of a general limiting
equilibrium analysis indicate stable slopes with a
FOS = 1.21. This deterministic analysis was verified
through a finite element analysis using the shear
strength reduction method. Modelled displacement

100FourthInternational Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

A CONCEPTUAL MODEL OFENVIRONMENTAL, GEOLOGICALAND GEO-TECHNICAL RESPONSE OF DREDGED SEDIMENT FILLSTO GEO-DISTURBANCES IN LOWLANDS
J. Rajaraman1 K.Thiruvenkatasamy2 and S. Narasimha Rao3
1, Professor and Head,Department of Harbour and Ocean Engineering , AMET University, 135 East Coast road,
Kanathur - 603 112 , CHENNAI, INDIA . E-Mail rajaraman.usha44@gmail.com
2.Professor,Department of Harbour and Ocean Engineering, AMET University, 135 East Coast road, Kanathur
603 112 , CHENNAI, INDIA . E-Mail swamy2667@yahoo.co.in
3.Professor (Retd), IIT Madras, Director, Dredging Corporation of India (Govt.of India).E-Mailsnarasimharao@hotmail.com

ABSTRACTIn mineralogical evolution of clays, amongst the weathering phenomena, hydrolysis is very important. Clayminerals of 2/1 type, which first appear, are silica-rich with two tetrahedral silica sheets. The 1/1 clay minerals
that follow have but one tetrahedral sheet and the last, gibbsite, has none at all. It is important to consider
temperate and tropical environments. The kaolinite-gibbsite association is mostly characteristic of tropicalenvironments. When all the silicates disappear to the gain of gibbsite, it is called total hydrolysis. Kaolinite andgibbsite are stable products in tropical environment. In temperate environment, weathering is often halted at thestage of 2/1 minerals (for example montmorillonite). This weathering can continue with kaolinite. In both cases
it is partial hydrolysis only. This shows that the tropical environment is the only one to accumulate large
quantities of gibbsite. In temperate climate only small amount of gibbsite is produced. In this paper a conceptualmodel of three layer system consisting of kaolinite, illite and montmorillonite is considered with symbols K, I, M
respectively. The Geo- disturbance caused by dredging varies from pocket to pocket in the soil profile. The
permutations and combinations of placed dredged materials are considered with different combination of thethree clay types (KIM). All possible combinations will yield 24 different Geo-Technical sequences.
They are : KIM,MIK,IMK,KKK,III,MMM,KII,IKI,IIK,IKK,KIK,KKI,MII,IMI,IIM,KMM, MKM, MMK, KMI,
IMM, MIM, MMI, MKI, and IKM. The link equation between drainage conditions and hydrolysis is identified as𝝉𝝉 = 𝒄𝒄 + 𝝈𝝈 ′ 𝒕𝒕𝒕𝒕𝒕𝒕 𝝋𝝋. The cohesion c is controlled by hydrolysis (water) and 𝝋𝝋 is controlled by residual friction of
the mineral skeleton. 𝝈𝝈 ′ is effective normal stress. The above analysis is applied to important lowland Geotechnology problems in coastal areas such as sub-grade in pavement construction, land reclamation and fills tocontribute to marine multi-inter-disciplinary research.
Keywords: Hydrolysis Geo-disturbances Lowland-Geo-technology Residual friction Tropical,

Temperate environment

presents unique challenges to the geo-technicalengineer. In this paper the effect of heavy rainfall on
fills of dredged materials in coastal areas.

INTRODUCTION
Many Geo-Technical engineering projects are
not always under static loading alone, however,knowledge of dynamic properties and characteristics
of soil is also important and needed for analysis anddesign. Dynamic loading can be grouped according
to natural and anthropogenic origins: (a) natural
sources of dynamic loads including earthquake,tsunamis, volcanic explosion, wind, rainstorm,
waves, ice movement and current; and (b)anthropogenic sources of dynamic loads including
machine vibrations, bomb blast, construction andquarry blasting, construction operation, traffic, ship
impact and landing aircrafts. Each of these loadings

Dredging Operation
Once the soil is disturbed, the chaotic conditions
start. The only way to understand Geo-technicalbehavior / response of the dredged soil, is to extract
order out of chaos. In this paper an attempt is madeto take out order out of chaos. Dredged soil is
influenced by many environmental factors.
Dredging itself creates chaotic condition in all Geotechnical aspects of the soil. Dredging causes loss ofbonding stress, loss of fines with water .

101

GEOMATE-Brisbane, Nov. 19-21, 2014

Fig.1 Stability
Wheel and Axle.

Of

Clay

Minerals

[1].

Under

or degree of saturation in soil will decrease the shear
resistance as reflected by cohesion, c, or friction
angle, ϕ. This relationship is shown in terms ofcohesion by figures 2 and 3 .
Geo-Technical Behavior of Kaolinite, K, Illite, I,
Montmorillonite, M in the presence of very heavy
rainfall (moisture content very high %) of twenty
four different combinations of KIM forming threelayers of equal thickness.
Since moisture content is weight ratio Kaolinite is
assigned 150 %, Illite 50%, followed byMontmorillonite 300%. The distribution of moisture
content for saturated conditions for twenty fourcombinations of KIM will be :1. KIM 150+ 50 + 300 = 500
2. MIK 300 + 50 + 150 =500
3. IMK 50 + 300 + 150 = 500
4. KKK 150+ 150 + 150 =450 (intermediatemoisture)
5. III 50 + 50 + 50 = 150 (minimum
moisture)
6. MMM 300 + 300 + 300=900 (maximum
moisture)
Similarly calculating for KII,IKI,IIK, the %will be 250 each.
Similarly for others IKK,KIK,KKI, the %will be 350 each.
Then similarly MII,IMI,IIM will be 400.
KMM,MKM,MMK will be 750.
KMI, IMM, MIM will be 500,650 & 650
respectively.
And finally MMI,MKI,IKM will be 650,
500 & 500 respectively.
Considering all the combinations the % of moisture
content varies from 150 to 900. Considering eachcombination of the twenty four figures the soil will
be saturated if the % of rainfall over the dredged
materials (Fill) reaches 900%. The cohesion
becomes zero for the entire fill whatever may be the
combination.

STRENGTH OF SOIL INFLUENCED BYENVIRONMENT FACTORS
Clay Minerals and Stability
As the ability of soils to resist deformation depends
very largely on the internal friction, wet clay has theeffect of reducing or canceling out the frictional
resistance. It may also be pointed out that the socalled cohesive resistance is induced almost entirelyby the clay fractions, and therefore that clean sands
are noncohesive. Again we must note the importantpart played by water, as finely ground dry clay
particles exhibit no cohesive properties. If water isadded to a dry soil, the cohesive resistance will
normally increase with the addition of moisture andin most cases the frictional resistance will not begreatly impaired until a certain amount of moistureis added. Beyond this point, the friction willdiminish but the cohesive resistance may continue toincrease up to some point of higher moisture
content, after which both values will diminish as thesoil approaches a completely fluid state.
Metals are typical substances having little or nointernal friction; in them, resistance values arealmost entirely a result of the cohesive or tensile
strength. Fig.1 (a) shows wheel load and subgrade inroad construction in lowland coastal area. Fig.1 (b)is a chart showing characteristic curves illustrating
loss in stability or internal resistance of a crushed
sandy gravel due to the addition of increments of
1plastic clay.The combined figures 1(a) and 1(b)clearly
indicates the instability created by Montmorillonite( Bentonite), Illite (local clay), and Kaolinite in thepresence of water.Bentonite fails first followed byIllite. Kaolinite is more stable.
Moisture Content and Clay Minerals
Moisture content in the soil mass is a major factor
for controlling the state of stress of the soil. In
general, an increase in the moisture content

102

GEOMATE-Brisbane, Nov. 19-21, 2014

The important stages in the % of moisture content
starts from III 150% (minimum) KKK 450%
(intermediate) and MMM 900% (maximum %). The
following figure explains how increase in degree ofsaturation decreases cohesion for weathered
residual soil. The figure shows the effect of moisture
content on cohesion for four basic clay minerals.

others. These environmental factors can cause theloss of bonding stress between soil particles,
resulting in a gradual loss of shear resistance asshown in figure 4.

Fig.4. Gradual decrease of shear resistance of stiffclay with time.
[5].

Fig. 2. Increase in degree of saturation decreases
cohesion for weathered residual soils.
[2].

GEO-TECHNICAL RESPONSE OF DREDGED
MATERIALS
Lowlands Geo-technical problems are many. The
dredged materials represent Geo disturbed soils witherratic variation in Geo-technical properties. In arainy season in the beginning the rain firstcompensates soil moisture deficiency. Different
clays absorb different amount of water.Uptoshrinkage limit the stability is not affected by everincreasing amount of water. When there is very
heavy continuous rain the different clays reachliquid limit with time lag. One layer of pocket willreach liquid limit and other may not. But when there
is very heavy downpour (rain) all the layers reach
their liquid limit state simultaneously and due to thisshear failure occurs upto the depth influenced byshrinkage index. It is easier method to connect
stability of dredged soils and shrinkage index to
explain shear failure or liquefaction of the dredged
fills. Ultimately the understanding of the mineralogy
and consolidation properties of the dredged
materials will help to explain stability related
problems.
From Figure 1 a conceptual model of three layer
system consisting of Kaolinite, Illite andMontmorrillonite is considered with symbols K, I
and M respectively. The layers in order before
dredging has become chaotic after dredging. In orderto take order out of chaos, 24 different combinationsof K, I and M are considered.
Figures 1b.1 to 1b.24 represent the assumed
order out of chaos of clay minerals after dredging
operations

Fig. 3. Effect of moisture content on cohesion for
four basic clay minerals.
[3] [4].
The cohesion c becomes zero for Kaolinite atmoisture content 150%, for Illite 50% followed byMontmorillonite 300%.
Clay Minerals and Effect on Time
Shear strength of soils decreases with time, mainly
caused by local environmental changes such as
weathering, wet-dry cracking, creep and many103

GEOMATE-Brisbane, Nov. 19-21, 2014

Fig.1b.2

Fig.1b.2

Fig.1b.3

Fig.1b.4
104

GEOMATE-Brisbane, Nov. 19-21, 2014

Fig.1b.5

Fig.1b.6

Fig.1b.7

Fig.1b.8

Fig.1b.9105

GEOMATE-Brisbane, Nov. 19-21, 2014

Fig.1b.10

Fig.1b.11

Fig.1b.12

Fig.1b.13

Fig.1b.14

106

GEOMATE-Brisbane, Nov. 19-21, 2014

Fig.1b.15

Fig.1b.16

Fig.1b.17

Fig.1b.18

Fig.1b.19
107

GEOMATE-Brisbane, Nov. 19-21, 2014

Fig.1b.20

Fig.1b.21

Fig.1b.22

Fig.1b.23

Fig.1b.24
108

GEOMATE-Brisbane, Nov. 19-21, 2014

The Role of Co-efficient of Consolidation, c v , andShrinkage Index, I S , in Dredged Materials

CLAY MINERAL STRUCTURES
1.Kaolinite Group: Members of this group are
considered 1:1 minerals because there is 1
tetrahedral sheet for every octahedral sheet. Within
the octahedral layer there are generally aluminum
atoms , and within the tetrahedral layer the cations
are silicon.
2. Illite Group: Illite has a 2:1 structure and consistsof a gibbsite sheet between two silica tetrahedral
sheets, with the layers bounded together bypotassium cations in the inter layer region.The
octahedral cations are aluminum, magnesium oriron, and the tetrahedral cations can be aluminum orsilicon.
3. Montmorillonite Group: Montmorillonite is a 2:1
mineral and consists of two sheets of silica
tetrahedra on either side of a gibbsite sheet. Sodium(Na) Montmorillonite is a common form of the clay
within bentonite, and expansive clay often specified
in conjunction with drilling muds, borehole ceiling,
and waste containment.
Fig.4. Moisture up take by clay minerals. A. withIn Geo-technical Engineering it is always desirable
to relate c v to index properties of the sediments. Outof plasticity index and shrinkage index, indocumented research papers it is found that c v has abetter correlation with shrinkage limit and hence it isused in the discussion. The important equations are :Coefficient of consolidation cv (in m2/s) can be
expressed as:
𝑲𝑲
𝒄𝒄𝒗𝒗 = 𝒎𝒎
Eq. (1)𝜸𝜸𝒘𝒘𝒗𝒗

c v = 3/ 100 (I S )3.54
Eq.( 2)[7]
For which correlation co-efficient is r = 0.94 forequation 2
Where
k=hydraulic conductivity (m/s)
mv =coefficient of volume change (m2/kN)
γw =unit weight of pore fluid (kN/m3)
I S = Shrinkage index

It is well known that the coefficient of consolidation
is a parameter that indicates the rate of compressionof a saturated soil undergoing compression, which inturn directly depends on the hydraulic conductivityof the soil medium undergoing compression The
authors feel that for a soil that is more plastic as
indicated by higher plasticity index or shrinkage
index(Montmorillonite), hydraulic conductivity ofthe soil at any stress level will be less as compared
to a soil that is less plastic. The reason being that the
thickness of diffuse double layer (ddl) will be
relatively larger for a highly plastic soil as compared
to a less plastic soil. The thicker the ddl, the greater
the reduction in the effective pore size for flow, andhence, reduction in the hydraulic conductivity ofsoil.This is the reason for c v values being relatively
higher for less plastic soils than for more plastic
soils, though their liquid limit is nearly the same. As
the effective consolidation pressure for a normallyconsolidated soil increases, the soil particles become
more oriented and also come close to each other. Asaconsequence,for
moreplastic
soils(Montmorillonite), the diffuse double layer repulsive
forces mobilize, acting against the external loading,and hence, offer more resistance to compression(both rate and amount). This may be the reason forthe decreasing trend of c v versus σ' v for more plastic
soils. In the case of less plastic soils(Kaolinite, Illite)
whose compressibility behavior is governed mainly
by mechanical forces, as the consolidation pressure
increases, the gravitational forces increase and will
override the little repulsive pressure at the particle
level in retarding the compression of soil, and hence,
the increase in the rate of compression of the soil,i.e., an increase in c v with pressure. This explains
the varying trends of c v versus σ' v for soils withdifferent plasticity properties.

non-expanding Lattice. B. with expanding Lattice.
[6] .

Fig.5. Relationships of clay crystals to surface anddouble layer water.(After Lambe, 1958 b, p.17).
A. typical Montmorillonite particle 1000Å/10Å.
B. typical Kaolinite particle 10,000Å/1000Å. [6].

109GEOMATE-Brisbane, Nov. 19-21, 2014

stress which in turn modifies co-efficient ofconsolidation and permeability of the sediments.
9. When dredged materials are used as a fill incoastal areas invariably saline water is included as
pore water and hence the Geo-technical index
properties are modified along with shear strength.
10. However, when there is heavy downpour of rain,
all the above mentioned and discussed Geo-technicalparameters which resist the incoming water or flood
water fail in shear. No matter what the soil type isout of the 24 combinations which is only order outof chaos and not an exhaustive list of permutations
and combinations and probabilities.
11. The dredged sediments should be treated as
remolded samples.
12. The final conclusion is that water is more
powerful than solids of the soils and sun is more
powerful because it converts water into water vapor.

EXPLANATION FOR GEO-TECHNICALRESPONSE OF DREDGED SEDIMENTS IN
TERMS OF COAXIAL AND NON_COAXIALCOMPONENTS OF SHEAR STRENGTH
The basic equation for shear strength is𝝉𝝉 = 𝒄𝒄 + 𝝈𝝈 ′ 𝒕𝒕𝒕𝒕𝒕𝒕 𝝋𝝋. When moisture content isincreased (Figs.2 and 3) the cohesion for all the clay
minerals approximately reaches zero. The cohesion
represents the coaxial component of shear strengthor pure shear. Once the sediments lose their binding
effect what remains is the only the residual angle ofinternal friction (𝝋𝝋) or non-coaxial component ofshear strength or simple shear, which may not be
sufficient to resist ever increasing water in lowland
coastal areas. In this state shear failure or landslide
will be the only choice.
CONCLUSIONS
1. Dredging operations which is one of theanthropogenic activity, interferes and interrupts
Geological formations and their processes. It creates
imbalance to soils, flora and fauna, especially in thecases of 2/1 and 1/1 clay mineral types like
Montmorillonite, Kaolinite and Illite.
2. The Geo-technical behavior of dredged sediments
are drastically modified due to excessive rainfall.
3. The cohesion of the dredged sediments consistingof KIM ( Kaolinite, Illite and Montmorillonite)
decreases with increase in moisture content andhence decreases shear strength of the sediment fill.
4. The water absorbing and retaining capacity evenat higher moisture content percentage depends upon
the type of clay minerals.
5. Retaining shear strength at very high moisture

REFERENCES[1] Francis N Hveem, “Importance Of Clay In
Applied Soil Mechanics, Clays And Clay
Material”, 1952 Vol.1,No.1, pp.191-195.
[2] Lumb P, “The Properties Of Decomposed
Granite, Geo-Technique”, 1962,Vol.12, No. 3,
pp.226-243.
[3] Shibuya T, “Geological Study Of Landslide
Clay”, KICT Report No.10 Kajima Institute ofConstruction Technology, Tokyo, July,1973
pp.37[4] Fang HY, “Introduction To Environmental GeoTechnology”, CRC Press, Boca Raton, FL, 1997
pp.652.
[5] Skempton AW, “Long – Term Stability Of Clay
Slopes”, Geo-Technique Vol. 14 No.2 1964,
pp.77-102.
[6] Jacke Gillott, “Clay in Engineering Geology”
Division of building research, National
Research Council of Canada, Ottawa, Ont.,
Canada (Elsevier Publishing Company, 1968,
pp.109-111.
[7] Sridharan A, Nagaraj HB, “Coefficient ofConsolidation and its Correlation with Index
Properties of Remolded Soils” Geotechnical
Testing Journal, Vol. 27, No.5 Paper ID
GTJ10784

content depends upon the shrinkage index I s whereI s = ( W L - W SL ) Where W L is liquid limit of thesoil and W SL is the shrinkage limit of the soil
expressed in %.
6. When the shear strength approximately becomeszero the moisture content requirement for loss ofshear strength varies from pocket to pocket variation
in soil types. In other words the Montmorillonite
combination (MMM) can tolerate moisture content
upto 900% before failure in an ideal situation. And
this combination, MMM is one of the 24
possibilities as shown in figure 1b.1 to 1b.24.
7. In the random variation of dredged materials andtheir Geo-technical properties depend mainly upon
shrinkage index (which is different from shrinkage
limit).
8. When clay minerals take water from dry state toliquid limit state the clay minerals with ddl (diffuse
double layer) convert water into solid water which isincluded in ddl and offer resistance to effective
110Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

3D NUMERICAL ANALYSIS OF A DEEP CIRCULAREXCAVATION IN THE CITY OF RIO DE JANEIROJose Carlos Solis Tito1, Celso Romanel2
Departamento de Engenharia Civil, Pontifícia Universidade Católica do Rio de Janeiro, Brasil; 2 Pontifícia
Universidade Católica do Rio de Janeiro, Brasil

1

ABSTRACTAt present, due to the need for engineering works of large scale, we have the challenge of solving problems
related to deep excavations, where instability problems often occur. In this paper is presented the analysis andvalidation of the excavation of the service well PS – 39, of the executive project of collectors for treatment ofsanitary sewage, located in the city of Rio de Janeiro. This well was constructed using a contention system of awall of secant column, ring structure type of “shotcrete” covering the columns, and a slab of "jet grouting"anchored with passive tiebacks. The soil parameters of the different layers that compose the geotechnical profile,necessary for numerical modeling, were determined based on the geotechnical information available of the field
instrumentation, laboratory data and specific literature review, considering the Mohr-Coulomb constitutive
model. The results and interpretation, of the stresses and displacements during the excavation process, were
determined using the PLAXIS 3D (2012) program. These results were validated with the measurements
determined by instrumentation; then the numerical model will predict rationally the behavior of the set soilstructure during the excavation process. This allows to solve similar problems in advance, allowing proper
planning.
Keywords: Deep Circular Excavation, Validation of Analysis, Numerical Analysis of Excavation

N = 7469236000, E = 682000000, as shown in Fig.
1. The dimensions of the well are 16 m of deep and8.60 m of inside diameter.

INTRODUCTION
The different types of large-scale works that are
built today require deeper excavations. In this typeof excavation, failures often occur due to resistanceproblems or excessive deformations, presenting
stability problems at different stages of the
excavation, or in some cases, complete collapse.
This has generated a growing interest in theevaluation of design methods, construction andcontrol of excavations, and the different containment
structures. This interest is also set in the numericalanalysis of these problems, because from thesemodels can be obtained important conclusions thatwill contribute to a better design of the work
according to appropriate control systems.
The general objective of the research is tovalidate the 3D numerical analysis of the excavationof a circular well, based on the data from the field
instrumentation available, through the application of
the numerical method of finite elements using the
PLAXIS 2D and 3D program.
METHODOLOGY

Fig. 1The project of excavation of the service well PS39, of the executive project of collectors for sanitary
sewage treatment, is located in the Boas Vindas
Avenue, in the District of Caju, in the city of Rio deJaneiro. Its location corresponds to the coordinates

Plan of location of the well PS-39 of theexecutive project of collectors for treatmentof sanitary sewage.

The geotechnical information consisted of 5
perforations of recognition SPT, identified as SP-30,
SP-58, SP-59, SP-60A and SP-61, conforming the111

GEOMATE- Brisbane, Nov. 19-21, 2014

cross sections AA and BB, allowing to determine
two geotechnical profiles for modeling the terrain, as
shown in Fig. 2. From the SPT tests results, bydetermined correlations, were determined the index,
physical and mechanical properties of the soil.

Fig. 3Fig. 2

Geotechnical profile for the excavation of
the well PS -39.

The structure of primary containment consists ofthe secant columns, which have a diameter of 0.80 m,
and are superimposed 0.20 m, in alternate columns
were positioned 12 reinforcing bars (ø= 25 mm),these columns were performed with the technique of"wet-mixing" around the perimeter of the well to adepth of 19 m, which was modeled with a solid
element with linear elastic behavior The second
containment structure is formed by a ring of
shotcrete with 0.20 m of thickness, and built as the
excavation progressed; this structure was modeledby plate elements with elastic behavior. The third
structural element was a base plate with 3 m ofthickness, made with 67 columns of "jet-grouting"with nominal diameter of 1.20 m and 32 columns
with nominal diameter of 1.50 m, this plate wasanchored with 25 passive tiebacks in the foundation
ground. The jet-grouting plate was modeled with asolid element, and passives tie-backs with a
combination of embedded piles and spring
connections.
For analysis of the results is available theregisters of measurements for the last stage of
excavation, of the horizontal displacements
registered with the inclinometer I-01. Also isavailable the registers of piezometric heads,
determined during the period of excavation(consisting of 18 stages of excavation), registeredwith the piezometer P-03, at an average depth of
13.50 m, corresponding to the layer of silt.
The parameters used for modeling, according to
the model of Mohr Coulmb were determined basedon the results of field and laboratory test, data fromfield instrumentation, research results with similar

Geotechnical profiles from geotechnicalsections. The Section AA is formed by thesoundings SP -58, SP -59, SP -60A, SP -61,
and Section BB is formed by the soundings
SP -59 and SP -30.

According to the geotechnical profile of theground for the analysis of the excavation,
determined according to the perforation SP-59(presented in Fig. 3), the soil presents a layer ofembankment with an average thickness of 2.9 m,
followed by a layer of very soft clay, with anaverage thickness of 5.70 m. The next layer consistsof a sandy clay, with an average thickness of 3.20 m.
The last layer consists of a compact sandy silt
(residual soil), with an average thickness of 21 m.

112

GEOMATE- Brisbane, Nov. 19-21, 2014

soils in different areas of the city of Rio de Janeiro,
and specific literature review. These parameters
allow validating the model with measurements fromfield instrumentation. The values used in themodeling are presented in Table 1a e Table 1b.

Table 1b Parameters of the soil layers that form thegeotechnical profile.
Material
Model

Table 1a Parameters of the soil layers that form thegeotechnical profile.
Material

Embankment

Soft clay

Model

Mohr
Coulomb
Drained

Mohr
Coulomb
Undrained

Unit
kN/m3
kN/m3
m/s
m/s
m/s
-

19
20
0.5
10-5
10-5
10-5
1015
0.43
0.43

13.3
13.3
3.9
10-6
10-6
10-6
1015
0.59
0.59

kN/m2
kN/m2

6000
0.3
2

1800
0.3
3.3

°
°

35
0

24
0

-

1

1

Behavior
Parameter
γ unsat
γ sat
e0
kx
ky
kz
ck
K 0x
K 0y
Model
parameters
E’
ν'
c’
cu
ϕ'
ψ
Interface
R interModel
Behavior
Parameter
γ unsat
γ sat
e0
kx
ky
kz
ck
K 0x
K 0y
Model
parameters
E’
ν'
c’
cu
ϕ'
ψ
Interface

Unit
kN/m3
kN/m3
m/s
m/s
m/s
-

kN/m2
kN/m2

Embankment
Mohr
Coulomb
Mohr
Coulomb
DrainedSoft clay
Mohr
Coulomb
Mohr
Coulomb
Undrained

15
15
2.8
7×10-6
7×10-6
7×10-6
1015
0.58
0.58

17
17
0.9
10-5
10-5
10-5
1015
0.38
0.38

3000
0.25

5×104
0.3
10

25
°
°

0

38
0

DISCUSSION OF RESULTS
The finite element mesh of the three-dimensionalmodel is shown in the Fig. 4. For the boundary
conditions of this model, was adopted the standard
boundary conditions, which are completely fixed in
the base and only fixed perpendicular to the surface
in the lateral planes. Concerning to the initialconditions, the stresses were generated by the K 0
procedure, and the pore pressure calculation wasestablished by the phreatic level.

113

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 4

distribution in steady state, acting on both surfacesof the containment wall, determined for the four
representative stages of the analysis, these are for the
initial conditions (E0), the first stage of excavation(E1), the intermediate stage of excavation (E9) andlast stage of excavation (E18). The negative pressure
corresponds to exert on the surface at the active side,and the positive on the surface of passive pressures.
In the first stage of excavation (E1), the levels anddistribution of pore pressure are similar, because the
excavation did not reach the water table. In theintermediate stage of excavation (E9) the porepressure decreases to a height of 0.11 m, due to theabatement corresponding to this level of excavation.
In the last stage of excavation (E18) can observe theeffect of the stiffness of the structural element
formed by the plate of "jet grouting", in the elevationof -13.2 to -16.2 m.

Three-dimensional finite element model,
for the last stage of the excavation (E18).

In the Fig. 5 is shown the horizontal distribution
effective stress acting on both surfaces of thecontainment walls, for the four representative stagesof the analysis, which are the initial conditions (E0),the first stage of excavation (E1) with a depth of
0.90 m, the intermediate stage of excavation (E9)with a depth of 8.60 m and the last stage of
excavation (E18) with a depth of 16 m. In thisdiagram, the negative effective pressures correspondto those exerted on the inner surface (excavatedside) and the positive on the outer surface (supportedside). As the excavation proceeds, horizontal
effective stress on the passive side is increased to its
maximum value, acting directly on the plate of jet
grouting.

Fig. 5

Fig. 6

Evolution of the pore pressure on the activeside and the passive side.

In the Fig. 7a (1a), 5a (2a), 5a (3a), according to
the charge distribution of total pressure, can beobserved that the end of excavation, the drainage isestablished primarily through the layer of residual
soil.
The excess pore pressure generated during the
excavation process, considering established flow
conditions are shown in Fig. 7b (1b), 5b (2b), 5b(3b). The most significant changes on the active side
are due falling water level, corresponding to adecrease in pressure; and in the passive side are dueto the excavation process, concentrated in the
undrained layers. At the end, in the excavated side,
the effect of excess pore pressure is zero, because
the level of excavation reached the drained layer, but
this had effect in the previous stages of the
excavation.

Evolution of the horizontal effective stresson the active side and the passive side,
during the excavation process.

To model the effect of the water flow is
considered the flow at a steady state, because themechanical analysis was established as a resistanceanalyze, excluding the effect of consolidation due tothe short term of execution of the excavation, lastingalmost a month.
In the Fig. 6 is presented the pore pressure
114

GEOMATE- Brisbane, Nov. 19-21, 2014displacement had a value of 0.000953 m
corresponding to the elevation of 2.10 m, in thecontrol line.
On the surface, the soil displacement is lower,
accompanying the movement of the wall. The effectof flow in steady state has a minimum influence inthe displacements. The effect of modeling the waterflow in steady state in the 3D modeling, wasconcentrated in the layers of clay, producing aminimal influence in the displacements. It produced
a contribution to the maximum horizontal
displacement, of 0.00096 m.

Fig. 7a Distribution of total pressure loads, in thecondition of steady state flow, in stages
with excavation depth (1a) 0.90 m, (2a)8.60 m, (3a) 16.00 m.

Fig. 8Fig. 7b Excess pore pressure, in the condition ofsteady state flow in stages with excavation
depth (1b) 0.90 m, (2b) 8.60 m, (3b) 16.00
m.

Profile of horizontal displacements in theradial direction toward the center of the
excavation.

In Fig. 9 is presented the piezometer heads
registered during the 18 stages of the well
excavation. The piezometer level present a fall of
about 6 m, when the excavation reached the stratumof very soft clay (which is based on the elevation of-0.10 m). Also can be observed the validation of the2D and 3D models with the piezometer heads
recorded. The maximum difference between thedetermined head and the piezometric head waspresented at the excavation stage 12 (corresponding
to the date 14/10/1999). In the 2D model was 1.438
m and in the 3D model was 1.481 m, this depression
was due to the flow that occurred in the drainage
holes that were dropped off at the coating of
shotcrete. This shows that the overlapping secant
columns were not waterproof ring.

In the Fig. 8, the profile of horizontal
displacements of the control line (corresponding to
the location of the inclinometer I-01) is presented.
According to the diagram, the distribution ofhorizontal displacements with 3D modeling issimilar to axi-symmetric 2D model. The modeling
results show a pronounced curvature in the interface
between the layers of soft clay and sandy clay with aconvexity oriented toward the interior of the
excavation. The displacements registered with 2Dmodel show a marked discontinuity in the change oflayer. At the end of the excavation, the maximum
horizontal displacement in the control line waspresented at elevation -5.5 m, with a value of 0.0143
m, which corresponds to the position of the interface
soft clay and sandy clay. The minimum horizontal
115

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 9base of the secant column) is 64.296 kN/m2.
According to the 3D numerical analysis of the
excavation, considering steady state flow, the effectof excess pore pressures in the wall of secant
columns is greater in the soil content side, in the clay
layer. This is due to undrained behavior of thesesoils, discharge process and decrease the water table,
generating positive pore pressures (excess porepressure suction) on the boundary of the excavation,
increasing the effective stress. In the establishmentof the boundary conditions for the analysis, theinside of the well acts as a drainage system,
generating a progressive depression of the waterlevel, as the excavation progresses. Thereby
contributing to the horizontal movement, at the laststage of excavation, the interface of the layers of soft
clay and sandy silt, in an amount of 0.00096 m.
The finite element method has many advantages
due to its generality and ease of determination ofclusters of complex calculation in analysis of two
and three dimensions, constituting a tool to make a
lot of analysis, preventing the occurrence of failures.
This tool allows to determine an approximate
representation of reality by modeling, using
numerical analysis. Also allowing the drafting anddesigning of quality projects, obtaining results withadequate speed to the requirements and possiblyoffering better cost, therefore constitutes acompetitive tool.

Descent of the water level in the piezometer
P 03.

CONCLUSIONS
After collecting the index, physical andmechanical properties of the different soil types thatform the stratigraphic profile of the well PS -39,
according to the results of field and laboratory test,
field instrumentation data, results of research
conducted with similar soils in different areas of thecity of Rio de Janeiro and specific literature review,
the values used in the 3D numerical analysis wereobtained.
Once established the values of the soil parameter,of the four layers corresponding to the stratigraphic
profile of the well PS-39, required by the model
Mohr Coulomb and using the PLAXIS 3D program,the maximum displacements were determined in thecontrol line. In the last stage of excavation, themaximum horizontal displacement has a value of
0.0143 m at elevation -5.5 m, representing a ratio of
the horizontal displacement/wall height of 0.000918.
And according to the inclinometer readings, themaximum horizontal displacement at the elevationof -7.2 m, has a value of 0.0147 m. The difference
between the displacements determined with theprogram and field measurements is 0.000403 m,
representing a percentage of deviation of 2.74 %relating to the horizontal displacement registered in
the inclinometer.
Concerning to the earth pressures acting on thesecant columns, of the active horizontal pressure
side. For the elevation of - 13.2m (corresponding to
the bottom of the excavation) the horizontal
effective stress is 246.87 kN/m2, for the elevation of-16.2 m (corresponding to the base of the secant
column) the stress is 189.21 kN/m2. For the active
horizontal pressure side, the horizontal effective
stress for the elevation of 2.80 m (corresponding to
the top of the secant column) is 1.439 kN/m2, andfor the elevation of -16.2 m (corresponding to the

ACKNOWLEDGEMENTS
The authors wish to thanks to the Pontificia
Universidade Católica do Rio de Janeiro, for the
support granted, which allowed the completion ofthis work.
REFERENCES[1] Brinkgreve R. B. J., Engin E. and Swolfs W. M.,
PLAXIS 3D. Material Models Manual 2012.
Holanda: Plaxis bv, 2012.
[2] Massad, F., Escavações a céu aberto em solos
tropicais Região Centro-Sul do Brasil. São
Paulo: Oficina de textos, 2005.
[3] Potts, D. M., “Numerical analysis: a virtual
dream or practical reality?”, Géotechnique 53,
No. 6, 2003, pp. 535–573.
[4] Rodríguez, A. R. and Mejía, H. C.
Instrumentación de campo, Apuntes del libro:
La Ingeniería de Suelos en las Vías Terrestres
Carreteras, Ferrocarriles y Aeropistas Vol. 2.
México: División de Educación Continua,
Facultad de Ingeniería UNAM, 1984.
[5] Sandroni S. S., “Os casos de escavações naregião da cidade de Rio de Janeiro”, SEPE 4,
Vol. 2, 2000.

116

GEOMATE- Brisbane, Nov. 19-21, 2014[6] Schnaid, F. and Odebrecht E., Ensaios decampo, e aplicações à Engenharia de Fundações.
2a ed. São Paulo: Oficina de Textos, 2012.
[7] Whitlow, R., Fundamentos de Mecánica deSuelos.
México:Compañía
Editorial
Continental S.A. de C.V, 1994.
[8] Zdravkovic, L., Potts, D. M. and John ST H. D.,“Modeling of a 3D excavation in finite element

analysis”, Géotechnique, Vol. 55, Issue 7, 2005,
pp 497 –513.
[9] Puller, M., Deep Excavation: a Practical Manual,
2nd. Ed. London, England: Thomas Telford,
2003.

117

STABILITY ANALYSIS OF THE SAIGON RIVERBANKSUBJECTED TO RIVER WATER LEVEL FLUCTUATION
A. Oya1, H.H. Bui2, N. Hiraoka1, M. Fujimoto3, R. Fukagawa3
Graduate school of Science and Engineering, Ritsumeikan University, Japan,
2
Department of Civil Engineering, Monash University, Australia 3Department of Civil Engineering,
Ritsumeikan University, Japan
1

ABSTRACTThe Saigon River, which flows through the center of Ho Chi Minh City, is of critical importance for thedevelopment of the city as forms as the main water supply and drainage channel for the city. In recent years,
riverbank erosion and failures have become more frequent along the Saigon River, causing flooding and damage
to infrastructures near the river. A field investigation and numerical study has been undertaken by our researchgroup to identify factors affecting the riverbank failure. In this paper, field investigation results obtained frommultiple investigation points on the Saigon River are presented, followed by a comprehensive coupled finite
element analysis of riverbank stability when subjected to river water level fluctuations. The river water level
fluctuation has been identified as one of the main factors affecting the riverbank failure, i.e. removal of thebalancing hydraulic forces acting on the riverbank during water drawdown.
Keywords: Stability analysis, Water level fluctuation, Seepage, FEM

identified as one of the main factors affecting theriverbank failure. [2] However, the seepage behavior
due to water fluctuations and its effect on river bankstability have not been revealed. In this paper, field
investigation results obtained at multiple points on
the Saigon River are presented, followed by acomprehensive coupled finite element analysis ofriverbank stability when subjected to river water level
fluctuation.

INTRODUCTION
Many cities in south-east Asian countries havedeveloped in downstream areas of the regions greatrivers, and as a result they often suffer from flooding.
Ho Chi Minh City (HCMC), located in southern
Vietnam, is one of the leading economic andcommercial hubs in South-East Asia. The Saigon
River runs through the center of HCMC, provides its
main source of water, and contributes to its industrial
development. However, riverbank failure has recently
become a serious issue especially at the flood events,
with numerous reports of settlement and in somecases buildings collapsing. An example of ariverbank failure in the Thanh Da peninsula region(along the Saigon River) is shown in Figure 1.
Furthermore, the increasing frequency of riverbank
failures and subsequent flooding may hinder the
future economic development of HCMC [1].
Someexamplesofriverbankfailurecountermeasures currently in use along the Saigon
River are shown in Figure 2. These include: wooden
piles to structurally reinforce river banks, and soil
bags as temporary reinforcement measures. However,reinforcement of large sections of the river with piles
is likely to be prohibitively expensive, sandbags areat best of a practical short term solution; an effective
and economical countermeasure is required. However,in order to identify effective countermeasures it isnecessary to first develop an understanding of themechanisms leading to riverbank instability andfailure and their causes. Investigating riverbank
failure mechanisms has been a focus of our researchgroup. The river water level fluctuation has been

Figure 1 Riverbank failure along Saigon River

Figure 2 Countermeasure by wood piles
Thahn da peninsula
P7
P5
P6
P4
P1 P2

P3

Figure 3 Locations of the observation sites
118

P1

P2

P3

0.9 m

1.7 m

Fill soil

P4
0.9 m

1.7 m

Doppler Current Profiler (ADCP) at 3 locations(Figure 3). The results of ADCP testing are presented
in Figures 7 to 9. Also, groundwater level and riverwater level were measured at site P7 (Figure 3).

P5

1.7 m

Layer 1:Organic clay
14.3 m16.5 m19.0 m19.0 m17.5 mSub-surface conditions

Layer 2: Clay sand19.5 mThree cross-sectional profiles have been determinedat investigation site P1 to P5, P6 and P7, and crosssections are presented in Figures 4, 5 and 6
respectively.
Table 1 Soil parameters at P1-P5

25.0 m
26.0 mLayer 3: Roam

26.0 m28.0 mFigure 4 Soil layers at P1-P5

Layer1

Layer2

wL
wP
Ip
w

%

70

36

%

38

18

%

32

18

%

75

20

17

𝜌𝜌𝑡𝑡
𝜌𝜌𝑑𝑑

g/cm3

1.47

2.11

2.11

g/cm3

0.86

1.76

1.81

2.61

2.72

2.66

%

95.2

99.5

96.6

kN/m2

10.8

36.3

9.8

deg

4.38

15.7

28.1

m/sec

6.2×10-8

4.8×10-7

6.1×10-5

0-3

8-15

15-30

Item

Layer 1: Organic siltwith sandGs
Src
16.3 m

𝜙𝜙16.5 mk
N

Layer 2: Sandy clay

Figure 5 Soil layers at P6

Table 2 Soil parameters at P6
Layer1

Layer2

wL
wP
Ip
w

%

87.2

55.6

%

44.9

27.0

%

42.3

28.6

%

95.7

46.8

𝜌𝜌𝑡𝑡
𝜌𝜌𝑑𝑑

g/cm3

1.46

1.76

g/cm3

0.74

1.19

2.62

2.70

97.0

96.9

kN/m

11.8

16.6

deg

18.9

23.2

m/sec

4.02×10-10

1.62×10-10

0

3-7

Item
0.5 m

0.5 m

Fill soil

Layer 1: Organic clay

Layer 3a: Clayey sand14.3 m17.3 mGs
Src’

14.4 mLayer 2: Clay sandLayer317.0 m𝜙𝜙′Layer 3: Clayk
N

19.0 mFigure 6 Soil layers at P7%
2

Table 3 Soil parameters at P7
Item

GEOTECHNICAL INVESTIGATION
Site investigations have been conducted at sevenobservation points along the banks of the Saigon
River, most of which occur around the Thahn Da
peninsula in HCMC (Figure. 3). Standard Penetration
Tests (SPT) and comprehensive laboratory soil
testing (Moisture content, Wet density, Specificgravity, Atterberg limits, Triaxial test or Direct shear
strength test and consolidation test) based on ASTM
criteria were performed on soil samples recoveredfrom sites P1–P5 (blue dots), 2 points at site P6 (reddot), and site P7 (black dot). Bathymetry surveys of
the Saigon River were undertaken using an Acoustic

Layer2

Layer3Layer3a

wL
wP
Ip
w

%

73.4

39.2

51.1

%

46.8

20.3

30.2

%

26.6

18.9

20.9

%

86.7

26.6

44.0

27.0

𝜌𝜌𝑡𝑡
𝜌𝜌𝑑𝑑

g/cm3

1.45

1.95

1.71

1.88

g/cm3

0.77

1.52

1.19

1.48

2.60

2.72

2.72

2.67

95.0

92.0

93.0

89.0

2

kN/m

11.3

23.7

17.2

17.2

deg

12.3

23.4

7.55

m/sec

9.43
5.95
×10-6
1-2

-

-

-

12-13

7-11

8

Gs
Sr
c
𝜙𝜙

k

N
119

Layer1%

30 m

Soil parameters obtained from the soil testing arepresented Tables 1, 2 and 3. Symbols used for thetables indicate as follows; w L : Liquid limit, w p :Plastic limit, I p : plastic index, w: water content, ρ t :Wet density, ρ d : Dry density, Gs: Specific gravity ofsoil particle, Sr: Degree of saturation, c: cohesion, 𝜙𝜙:Friction angle, k: Hydraulic conductivity, N: SPT-Nvalue. At each of the investigation locations there
were typically 2 or 3 distinct soil units. At P7, 4 soil
layers were identified. At all locations, underlying thefill unit was a very soft organic clay/silt with athickness varying from about 14 m to 26 m. The
presence, and considerable thickness of this very soft
soil, is of particular importance for slope stability
assessment of the Saigon riverbank.

92 m

Figure 9 Cross-section at C-C’ (ADCP No.3)

Saigon River

Soil bag
5.0 m
4

2.5 m
3

2

1
Well

PuddleFigure 10 Set up condition of the wells

Water level (m)0.5Geometry of the bank
ADCP was used to investigate the threedimensional distribution of flow-velocities in the
Saigon River by obtaining three cross sections at
locations shown in Figure 3. ADCP measures theriver flow-velocities by transmitting ultrasonic waves
into the floodway, and the results of this investigation
are shown in Figures 7 to 9. Riverbank slopes of 30°
occur at both sites, and heavy and thin lines in theriver channels indicate the riverbed and the range ofmeasurement, respectively.

0
-0.5
-1

1
3
4
River water

-1.5
-2
-2.5
-3

15:00 19:00 23:00 3:00 7:00 11:00 15:00 19:00 23:00 3:00 7:00

9/23

9/24

9/25

Figure 11 Groundwater level / River water level
FLOW-STABILITY COUPLED ANALYSIS
Seepage flow-stability coupled analyses using
commercial FEM software PLAXIS was conducted
to examine how the water fluctuation and infiltration
characteristic of the bank affect stability of theriverbank.

River water levels and ground water levels
Measurement of the groundwater level was
carried out at three wells, numbered 1, 3, and 4; theseare presented in Figure 10. Similarly, the river waterlevel was measured using a water pressure gauge
placed directly on the river bed.
Figure 11 shows variations in the groundwaterlevel and river water level at observation site P7 overthe duration of the experiment. A zero-value for thelevel of both river water and groundwater was set as
equal to the ground level at 1. Groundwater level
fluctuations reach a maximum of approximately 0.5
m, despite the low permeability of the soil. Larger
fluctuations can be observed at observation points
closer to the river, and the groundwater level ishigher on at observation points furthest away. These
data show that the Saigon River water level fluctuates
by about 2 m in a single day, and the relationshipbetween river water levels and groundwater levels.

Analyses outlines

30 m

FEM analyses of the riverbank subjected to riverwater fluctuation were performed using PLAXIS [5].
Seepage flow-stability coupled analyses areundertaken. The analyses cover 3 points that site
investigations are done. Soil properties at P7, P1-5
and P6 are applied to ADCP profiles No.1, No.2, andNo.3 respectively. Soil properties at each site are
combined with cross section at nearest points of eachsite for soil properties. Young modulus E iscorrelated from N-value of the ground, Poisson’s
ratio ν is set at 0.33 which is typical value forgeomaterials, and. Dilatancy angle ψ is set at 0.[6]Other parameters are determined by the results oflaboratory soil tests mentioned above. Slope models
are based on ADCP survey, and we develop the slopemodels by reading directly the line in the pictures.
The slope model at No.1 is partly based on the fieldsurvey. Constitutive law is linear elastic perfectly
plastic model (Mohr-Coulomb model). Shear strength
reduction technique is applied to slope stability
analyses. Unsaturated infiltration characteristic is
determined by the Van-Genuchten model. Then, inorder to assess seepage behavior in the bank, riverwater fluctuation is given as a boundary condition on

185 m

20 m

Figure 7 Cross-section at A-A’ (ADCP No.1)

96 m

Figure 8 Cross-section at B-B’ (ADCP No.2)
120

river side of the bank. The observed water fluctuationof 2 m is assessed as part of this analysis.

Table 4 Analysis parameter for A-A’
Item

Analyses conditions

𝟐𝟐

𝜸𝜸𝒕𝒕

(𝐤𝐤𝐤𝐤⁄𝐦𝐦 )𝑬𝑬𝜸𝜸𝒔𝒔𝒔𝒔𝒔𝒔

Conditions for No.1: The geometry of the slope
stability model is presented in Figure.12, analysis
parameters are presented in Table 4. The model
consists of 3 layers based on the subsurface
conditions and soil parameters which were obtained
from the site investigation. Soil permeability tests
have not been conducted on Layer 2 and 3 materials
at this stage thus hydraulic conductivity is assumed
based on particle size distribution [7].
The initial water condition is based on an initialriver water level and phreatic level set at 19.5 m fromthe bottom of the slope, this was determined by site
survey. The water level is then linearly reduced to17.5 m over a period of 4 hours, kept at 17.5 m for anhour, and then increased to 19.5 m over a period of 4hours and kept at this level for an hour. Furthermore,
initial phreatic line in the ground is assumed to bestraight at 19.5m which is same as river water level.

𝝂𝝂

Layer1

Layer2

Layer3

13.2

19.1

16.8

(𝐤𝐤𝐤𝐤⁄𝐦𝐦𝟐𝟐 )

14.1

19.2

17.6

(MPa)

4.20

27.3

22.4

‐

0.33

0.33

0.33

𝒄𝒄

(𝐤𝐤𝐤𝐤⁄𝐦𝐦𝟐𝟐 )

11.3

23.7

17.2

9.43

12.28

23.38

𝝍𝝍

(deg)

0

m/s

5.95×10

𝝓𝝓

(deg)

k

0
-6

0
-8

-8

3.00×101.00×1015.5 mFigure 13 Slope model at B-B’
Table 5 Analysis parameter for B-B’

Conditions for No.2: The geometry of the slopemodel is shown in Figure.13, and analysis parameters
are shown in Table 5. The model consists of 3 layers
based on the subsurface condition and soil parameterswhich were obtained from the site investigation. The
initial river water level is set at 15.5m from thebottom of the slope, which is determined from theresult of ADCP measurement. The initial phreaticline in the ground is assumed to be a straight line andthe water level reduces 2 m over the period of 4 hours,
kept at 13.5 m for an hour, increase to 15.5 m overthe period of 4 hours and kept at this lever for an hour.

Item

Layer1

Layer2

Layer3𝟐𝟐(𝐤𝐤𝐤𝐤⁄𝐦𝐦 )

14.72

‐

‐

(𝐤𝐤𝐤𝐤⁄𝐦𝐦𝟐𝟐 )

15.2

20.7

21.1

(MPa)

5.60

33.6

64.4

‐

0.33

0.33

0.33

𝒄𝒄

(𝐤𝐤𝐤𝐤⁄𝐦𝐦𝟐𝟐 )

10.79

36.3

9.81

(deg)

4.38

15.7

28.1

𝝍𝝍

(deg)

0

𝜸𝜸𝒕𝒕

𝜸𝜸𝒔𝒔𝒔𝒔𝒔𝒔
𝑬𝑬
𝝂𝝂

𝝓𝝓
k

Conditions for No.3: Slope model is shown in
Figure.14, and the analysis parameter is shown in
Table 6. The slope model consists of 2 layers basedon the results of the site investigation as well as otherpoints. Initial river water level is set at 22.0 m, which
is determined by result of ADCP measurement. initial
phreatic line in the ground is assumed to be straight
as well The water level take a descend of 2 m
spending 4 hours as well as the point of profile A-A’.
Then, it is kept at 13.5 m for an hour, takes an ascentof 2 m spending 4 hours and kept for an hour.

0-8

6.2×10m/s

0-7

6.1×10-5

4.8×1022.0 mFigure 14 Slope model at C-C’
Table 6 Analysis parameter for C-C’
Item

Analyses results and discussion

Layer1

Layer2𝟐𝟐(𝐤𝐤𝐤𝐤⁄𝐦𝐦 )

14.72

‐

𝜸𝜸𝒔𝒔𝒔𝒔𝒔𝒔 (𝐤𝐤𝐤𝐤⁄𝐦𝐦𝟐𝟐 )

15.19

20.74

𝑬𝑬

(MPa)

5.60

33.60

𝝂𝝂

‐

0.33

0.33

𝒄𝒄

(𝐤𝐤𝐤𝐤⁄𝐦𝐦𝟐𝟐 )

10.79

36.30

(deg)

4.38

15.66

𝝍𝝍

(deg)

0

𝜸𝜸𝒕𝒕

For the analysis for No.1 (profile A-A’), results
are shown in Figure.15 as potential failure surface
obtained by stability analyses. The blue lines show

19.5 m𝝓𝝓kFigure 12 Slope model at A-A’
121

m/s

0

6.2×10-8

4.8×10-7

Elapsed time = 0 h

Elapsed time = 0 h

Elapsed time
=4h

Elapsed time = 4 hElapsed time
=5h

Elapsed time = 5 hElapsed time = 9 hElapsed time = 9 hElapsed time= 10 hElapsed time = 10 h

Figure 15 Potential failure surface on profile A-A’

18
17
15

Safety factor
0

2

4
6
Elapsed time (h)810Figure 17 Potential failure surface on profile B-B’
16

Figure 16 Safety factor on profile A-A’

14
13
12
11

the estimated the phreatic level in the ground. Safety
factors are plotted in Figure 16 with river water level.
When the water level goes down, the safety factor islower. The riverbank slope is stable because of
hydraulic pressure from the river when the waterlevel remains high; however, when the river waterlevel goes down, the hydraulic pressure dissipates
and the slope becomes unstable. When the phreaticlevel in the river water level goes down, the phreaticlevel in the ground remains at a high level because of
the ground’s low permeability, and the weight of thesoil remains high. It can be assumed that this leads tothe instability of the slope. Furthermore, potential
failure surface occurs in shallower point in lower
water level stage, which indicates more massive slope
failure can occur in this situation.
As for the analysis for No.2, results are shown in
Figure 17 as potential failure surface obtained bystability analyses. The blue lines show the estimatedthe phreatic level in the ground. Safety factors areplotted in Figure 18 with river water level. At 5h, thewater level ascent period, significant slip surface does
not appear. In other stage of analyses, failure surfaces
are observed on the boundary between layer 1 and 2.

Water level (m)15Safety factor
0

2

4
6
Elapsed time (h)

8

10

1.8
1.6
1.4
1.2
1
0.8
0.6

Safety factor

16

2.4
2.2
2
1.8
1.6
1.4
1.2

Water level (m)Water level (m)19Safety factor

Water level (m)20

Figure 18 Safety factor on profile B-B’
A safety factor value under 1.00, which indicates theslope is unstable, is estimated in the period of waterlevel descent. The maximum safety factor value ofthe slope at B-B’ is lower than any safety factors of
the slope at A-A’ and C-C’. From the aforementioned
factors, the slope is originally unstable, and gets moreunstable due to water level descent.
The results of the analysis for No.3 (profile C-C’)are shown in Figure 19 as potential failure surface
obtained by stability analyses. The safety factors of
the bank estimated stability analyses are s are plottedin Figure 20. The safety factor of the bank falls when
the water level decreases and remains low, as is thecase with profile A-A’. The phreatic level remains
higher than the river water level, which is assumed tobe the cause of the instability of the slope. The
difference in safety factors for water level decent, thelow water level period, water level ascent and thehigh water level period is smaller than that of otherpoints analyzed. This is because the height of theslope is bigger than other points. As for slip surfaces,

122

water level period, which is a typical phenomenon
that we can observe in the analyses of rapid
drawdown of reservoir level in the dam.[8] These
results suggest that river water fluctuation affects thestability of a riverbank, especially during water level
descent because he phreatic level in the river waterlevel goes down, the phreatic level in the groundremains at a high level because of the ground’s low
permeability, and the weight of the soil remains high,the slope is stable when water level is higher on theother hand. For future investigation, slope stability
and seepage behavior due to cyclic water level
fluctuations should be examined.

Elapsed time = 0 h

Elapsed time = 4 hElapsed time = 5 h

ACKNOWLEDGEMENTS
This research was financially supported by
Grants-in-Aid for scientific research (B) 23404012.
Also, authors would thank Dr. LUU Xuan Loc (Ho
Chi Minh City University of Technology) for his help
in carrying the site investigations.

Elapsed time = 9 h

REFERENCES
Elapsed time = 10 h

[1] National report on disaster reduction in Vietnam,
Socialist Republic of Vietnam, p.13, 2004.
[2] Oya et al., Kansai Geo-symposium 2013, JGS
Kansai Brunch, pp.11-16, 2013. (In Japanese)[3] Report On Geotechnical Investigation (2011),
Phan Tran Construction Foundation Geology
CO.LTD, 2011.
[4] Japan Road Association. 1987, Road
Earthworks Manual, Maruzen Co., Ltd, Tokyo.
(In Japanese)[5] Plaxis：Plaxis 2D Reference manual.
[6] Technical note PWRI No. 4163, Public works
research institute, Land slide research team, 2010.
(In Japanese)[7] JGS. 2010, Laboratory soil test, Maruzen Co.,
Ltd, Tokyo. (In Japanese)[8] Plaxis：Plaxis 2D Tutorial manual.

Figure 19 Potential failure surface on profile C-C’

Water level (m)

27
26
25
24
23

Safety factor
0

2

4
6
Elapsed time (h)

8

10

3
2.8
2.6
2.4
2.2
2
1.8

Safety factor

Water level (m)28Figure 20 Safety factor on profile C-C’significant ones do not appear when a water level isconstant such as elapsed time 0 h and 5 h. On theother hand, 2 failure surfaces on the boundary oflayer 1 and 2 and toe of the slope can be observed atelapsed time 4 h. There is a possibility that most
massive slope failure occurs in this period.
CONCLUSION
In this paper, geotechnical properties andhydraulic conditions along the Saigon River havebeen presented, and seepage flow-stability analysis
was conducted. Soft clay soil is deposited as thickhorizons, and the ground is mechanically weak at theall of points where we have carried out ourinvestigation. As results of our analysis, we canobserved that the safety factors of the slopes aredegraded during water level descent and the low
123Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECT OF LIGHT HYDROCARBONS CONTAMINATION ON
SHEAR STRENGTH OF FINE SAND
Rajab M. Abousnina, Jim Shiau, Allan Manalo, Weena Lokuge
Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba 4350, Australia
ABSTRACT
Shear strength is one of the most important soil properties in geotechnical engineering and design. This property
can be affected by several pollution sources such as crude oil. To investigate the effects of oil contamination,fine sand mixed with various amounts of light crude oil, ranging from 0 to 20% by mass were prepared. Direct
shear test was conducted to determine the friction angle and cohesion of oil contaminated sand. Results showedthat soil cohesion at its highest value of (10.7 kPa) at 1% oil contamination and decreases with as the oil
contamination increases. Meanwhile, a slight reduction in the friction angle is observed when oil is added into
the fine sand by as much as 20%. In general, the oil contamination is found to decrease the shear strength of finesand. The results of this study will benefit engineers and decision makers in recycling or re-using of oil
contaminated sand for building and construction.
Keywords: Shear strength, Hydrocarbons, Contaminated sand, Cohesion, Friction angle
pipelines, refiners, and major oil fields in Libya,
while Figure 1 (b) shows the contaminated sandaround the discharge disposal point of produced
water, and Figure 2 shows the oil spillage in one of
the Libyan oil fields.

INTRODUCTION
Oil leaks can happen accidentally or intentionallyduring the exploration, production and operation,and transportation of crude oil. Despite the fact thatmost spillages of crude oil happened accidentally,
there are some cases where crude oil was spilledintentionally, such as in the Gulf in 1991, where it
was reported that about 1.1 billion litres of crude oil
were purposely spilled into the Arabian Gulf, thePersian Gulf, and in the Kuwait [1, 2]. These areconsidered to be the largest oil spills in history. As aconsequence of this intentional leakage, 700 km ofcoastline were severely polluted between Kuwait
and Saudi Arabia, while approximately 49 square
kilometers of the Kuwait desert was affected by thisoil spillage. Furthermore, the explosions of the BP
deep water horizon drilling rig in the Gulf of Mexico
in 2010 caused a spill of around 91 million liters ofoil, and as consequence it has affected about 110 km
of Louisiana coastline. Whereas, 450,000 barrel ofcrude oil was intentionally discharged from oilstorage tank due to the human error cause tank fireat the Harouge Oil Operation petrochemical andrefining complex at the Ras Lanuf Terminal in Libya
in August 2008 [3, 4]. This intentionally spillage
was done to avoid an explosion of that tank due tothe fire caused by human errors during annual
maintenance [3].

(a)

(b)

Figure 1: Libyan major oil pipelines, refiners andmajor oil fields [6].

Figure 2: Oil spillage
Selecting remediation method for the existing
polluted sand requires knowledge of geotechnicalproperties and behavior of contaminated sand.
Therefore, this paper presents the results of alaboratory study on the effect of light hydrocarbons
on shear strength of fine sand. Light hydrocarbons
and fine sand has been selected to represent the
Libyan crude oil and sand in this study.

Most crude oil spills were caused unintentionally
due to ageing facilities, lack of maintenance, andhuman error by the oil companies. Libya is one of
the main countries exporting oil [5], and as such has
been affected by the same source of sandcontaminated with oil where large areas have been
contaminated. Figure 1 (a) shows the major oil

SHEAR STRENGTH OF SAND
The shear strength of sand is a one of the mostimportant parameters in the design of civil
124

GEOMATE- Brisbane, Nov. 19-21, 2014engineering structures. The safety of any
geotechnical engineering structure is based on theshear strength of the underlying sand [7]. Allconstructions, either in or on the land impose loads
on the sand which supports the foundations of thatparticular construction or building. The load
imposed on the sand may cause shear failure on theunderlying sand that occurs when the imposed shear
stress exceeds the maximum shear resistance (shear
strength) which the sand can offer [8]. Therefore,shear strength of the sand is considered to be an
important aspect in many foundations, such as thebearing capacity of shallow foundations and piles,
the lateral earth pressure on retaining walls, and thestability of slopes of dams [9]. In addition to thatshear strength of common engineering materials
from a continuum mechanics viewpoint, such as
steel, is governed by the molecular bonds whichhold the material. The higher the shear strength of amaterial is the stronger the molecular structure [9].
Due to the particulate nature of sand, unlike that of acontinuum, the shear strength depends on theinteraction of anti-particles rather than the internal
strength of the sand particles themselves [10]. Sand
derives its shear strength from two sources: cohesion
between particles and frictional resistance between
particles. Cohesion is the cementation between sandgrains or the electrostatic attraction between sandparticles [8]. Hence, an understanding of the shear
strength can play a great role in terms of the entity
classification of the sand [10], which can assist
engineers to derive the critical aspects of the overallsand mechanics in a specific environment. Hence,
the main reason for shear strength test on thecontaminated soil is to indicate whether the presenceof light hydrocarbons affects the shear strength byinvestigating the difference between the shear
strength of the sand without or with the presence oflight hydrocarbons contaminant. This investigationon contaminated sand will help the geotechnicalengineer to design the structure that will be built on
crude oil contaminated sand.

Particle size distribution

120
Passing (%)

100
80
60
40
20
0
0

0.5

1

1.5

2

2.5

Grain size (mm)Figure 3: Particle size distribution curve of the sandMineral Fork w2.5 motor cycle oil was used as
crude oil. This oil was selected because its densityand viscosity are very similar to light crude oil(Table 1).
Table 1: comparison between light crude oil and
Fork w2.5 Motorcycle oil
Specifications

Light
crude oil

Fork w2.5
Motorcycle oils

Density (Kg/L)
Viscosity (mm²/s)
Temperature (°C)

0.825
5.96
40

0.827
6.74
40

Ref.

[12, 13]

Direct Shear Test
A direct shear test was conducted using theShearTrac-II system called “Geocomp” as shown in
Figure 4 by applying shear to contaminated sandunder constant vertical loading and according to AS
1289.6.2.2—1998 [14]. The test specimen was 24mm thick and 63.5 mm in diameter, and it wasloaded into the shear box with the aligning pins andbottom porous stone in place. Figure 5 show theprocess of direct shear (shear schematic).

Experimental Approach
Materials
Figure 4: Direct shear (ShearTrac-II system
hardware and software)

Fine sand was chosen because it is similar to thesand in the Libyan Desert where the first author
originated. Figure 3 shows the particle size
distribution carve (PSD) of the fine sand based on
AS 1141.11.1-2009 [11]. Fine sand was air dried tomeet the condition of Libyan sand. Sieve analysis
was initially carried out to obtain the particle
grading curve of fine aggregate and it showed thatthe grain size of the sand particle is less than 2.36mm.

Figure 5: Shear Schematic125

GEOMATE- Brisbane, Nov. 19-21, 2014

Shear Strength Test Procedure180

In this test, a thin soil sample is placed in the shear
box consisting of two parallel blocks. The lower
block is fixed while the upper block is moved
parallel to the fixed one in the horizontal direction.
The soil fails by shearing along a plane assumed tobe horizontal. Ten samples were investigated withdifferent contaminated soil (0, 0.5, 1, 2, 4,6,8,10,15
and 20%). Thus, a total of 30 tests were conductedunder different normal stress (50, 100 and 200 kPa)
respectively.

160

Shear Stress (Kpa)

140
120
100
Oil content 0%
Oil content 0.5%
Oil content 1%
Oil content 2%
Oil content 4%
Oil content 6%
Oil content 8%
Oil content 10%
Oil content 15%
Oil content 20%

80
60
40
20

Sample Preparation

00

The methods used in preparing the samples followedin the Australian Standard (AS 1289: 2001).
Sample was filled up to the marked level then waited
to keep the consistence of all samples See Figure 6.

50

100

150

200

250

Normal Stress (Kpa)

Figure 7: Shear stress (KPa) as a function of normal
stress (KPa) with different crude oil content (%)
The results from the above charts are summarised in
the Table 2, to clarify how the oil affected thestrength parameters cohesion and friction angle. The
calculated results (cohesion and friction angle) are toclarify the effects of oil contamination on the shear
strength. These results are also presented graphicallyin Figures 8 and 9.

Figure 6: Sample preparation
Table 2: Cohesion and frictional angle result
Oil
Cohesion Friction
content % (kPa)
angle ø°Analysis
Effective stress and friction angle appear frequently
in commonly used equations. Shear strength isrelated to these parameters by another parameter
called cohesion, (c). The below equation relates
shear strength, effective stress, and cohesion. This iscalled Mohr-Coulomb failure criterion and isdefined as follows [9]:𝝉𝝉 = 𝒄𝒄 + 𝝈𝝈′ 𝒕𝒕𝒕𝒕𝒕𝒕∅(1)
where: 𝝉𝝉 = shear strengthc = cohesion
𝝈𝝈′ = normal pressureø = angle of internal friction

0
0.5
1
2
4
6
8
10
15
20

0.756
9.418
10.76
8.911
6.51
5.544
3.718
3.105
2.422
1.823

38
31
31
29
30
32
31
31
31
32

It can be seen from Figure 8 that a significant
increase in cohesion was observed from 0% to 1%(uncontaminated sample and 1% oil contaminatedsand). Interestingly, the cohesion decreases
dramatically after reaching 1% oil contamination.
The corresponding value of cohesion was observed
as 1.823 kPa with an oil content of 20%. Thisparticular trend may indicate the behavior of soil
suction.

Results and Discussions

Figure 7 shows the shear stress as a function of
normal stress with different oil content percentage
for a series of direct shear tests

126

GEOMATE- Brisbane, Nov. 19-21, 2014

Cohesion (c)Frictional angle

108

Frictional angle

Cohesion (kPa)

12

6
4
2
0
0

2

4

6

8

10 12 14 16 18 20

Hydrocarbons contamination (%)

40
35
30
25
20
15
10
5
0

Figure 8: Cohesion as a function of crude oil
contamination percentage (%)

0

2

4

6

8

10

12

14

16

18

20

Hydrocarbon contamination (%)

Figure 9: Frictional angle as a function of crude oil
contamination percentage (%)

The result of the shear strength test (Table 2 andFigure 8) illustrates a significant increase incohesion value between the control sample andcontaminated sand i.e. 0% to 1%. As can be seenfrom the figure, the cohesion is at its highest valueof 10.76 kPa for sand with 1% oil contamination.
This increase is reasonable because the moisture
content of the dry sand used in these experiments
was zero, so an addition of crude oil content has
increased the moisture content of the dry sand andhence, it is noted that the peak value of the cohesion
is obtained at 1% oil content. This observationagrees with a previous study [15], which concluded
that the cohesion component of shear strength attains
its peak value at around optimum moisture content
and then decreases. This outcome of the previous
study comparable with our observation since thecohesion value has decreased gradually withincreasing oil contaminated percentage from 1% to
20% which also agrees with some previous studies
that presented a similar trend on the shear strengthparameter of contaminated soils [16, 17]. The
reduction of the cohesion on the wet side is
attributed to the soil particle coated by crude oil
which leads to cohesion reduction between the soil
particles. This observation is in agreement with thefindings of Seed, et al. [18] they indicated that thecohesion reduction of the wet side is due to thethicker oil films around the soil particles and byincreasing the crude oil content, the chance of interparticle slippage will be higher as well which
resulting in a decrease in shear strength of the soil.

τ (kPa)Figure 9 shows the frictional angle as function of thepercentage of crude oil contamination. Based on the
figure the uncontaminated fine sand has thefrictional angle of 38º A significant reduction offrictional angle was observed between the control
sample (uncontaminated sand) and the contaminatedsamples (0.5%) where there was no significant
variation of the frictional angle of the contaminatedsand (0.5% to 20%). The frictional angle of oil
contaminated sand is between 29-32º The frictional
angle of the contaminated sand has been decreased
compared to the uncontaminated samples due to the
lubrication effect provided by the crude oil, and thisreduction of the internal friction is due to the intergrain lubrication of the soil particles by crude oil.
Thus, the characteristics of shear strength decline on
oil contaminated sand can be specified due tomechanical interaction caused by high pore fluid
viscosity.
Based on the analysis the shear strength values canbe mathematically illustrated using the MohrCoulomb equation since both cohesion and frictional
angle of oil contaminated sand were available.
160
140
120
100
80
60
40
20
0

Shear strength0

σ' 200 kPa
σ' 100 kPa
σ' 50 kPa

2 4 6 8 10 12 14 16 18 20
Hydrocarbon contamination (%)

Figure 10: Shear strength as a function of crude oilcontent (%)
Figure 10 shows the soil shear strength as functionof light crude oil content and it can be generally
deduced that light crude oil pollution affects theshear strength of fine sand. The shear strength of127

GEOMATE- Brisbane, Nov. 19-21, 2014

light crude oil contaminated sand was examined
under different normal stresses i.e 200, 100 and 50
kN/m2 respectively. Under shear stress of 200 kN/m2
the reduction of shear strength varied from 11 up to
22% compared to uncontaminated sample (oilcontaminated sand 0%), and under shear stress of
100 kN/m2 the shear strength decreased from 7 to 19% compared to uncontaminated sand, whereas when
the applied shear stress was 50 kN/m2, the reductionof shear strength varied from 1 to 23 %.

[4]

CONCLUSION[8]This paper investigated the effects of lighthydrocarbons contamination on the shear strength offine sand. Based on the results of the study thefollowing conclusions are drawn:• The cohesion increased significantly withoil contamination of up to 1% and thendecreased with increasing percentage ofcrude oil.
• A slight reduction in frictional angle wasobserved for fine sand contaminated with
crude oil.
• Up to 20% reduction in soil shear strength
was observed for oil contaminated sand.
These results provide a better understanding of theeffect of light hydrocarbons on fine sand for the
potential use of oil contaminated sand in building
and construction. They are useful benchmarks forfurther investigation on oil contaminated sand as analternative remediation method to reduce its adverse
impact in the environment.

[9]

[5]

[6]

[7]

[10]
[11]

[12]

[13]

[14]

ACKNOWLEDGEMENTS[15]
The first author would like to acknowledge thescholarship provided by the Libyan Government
during his PhD candidature.
[16]

REFERENCES
[1]

[2]

[3]

H. Al-Sanad, W. Eid, and N. Ismael,"Geotechnical
Properties
of
OilContaminated Kuwaiti Sand," Journal of
Geotechnical Engineering, vol. 121, pp.
407-412, 1995.
Mashalah Khamehchiyan, A. H. C. and,and M. Tajik, "The effects of crude oil
contamination on geotechnical properties ofBushehr coastal soils in Iran," IAEG, pp. 6,
2006.
T. F. S. B. Products, "Strorage Tank Fire
Protection-Leave Nothing to Chance,"
2008.

[17]

[18]

128

M. E. E. Survey, "Ras Lanuf Extinguished
After Seven Days," Middle east economic
survey, vol. 51, pp. 34, 2008.
G. Luciani, "The oil rent, the fiscal crisis of
the state and democratization," Democracy
without democrats, pp. 130-55, 1994.
U.S Energy Information Adminstration.
(2011, 10/10). Independent Statistics &Analysis Available: http://www.eia.doe.gov
M.
Budhu,
Soil
Mechanics
andFoundations: John Wiley & Sons, 2008.
I. Smith, Smith's elements of soil
mechanics: Wiley. com, 2013.
B. M. Das, Advanced soil mechanics:
Psychology Press, 2008.
D. P. Coduto, Foundation design: Prentice
Hall, 2001.
AS 1141.11.1, "Methods for sampling andtesting aggregates - Particle size
distribution - Sieving method," ed,2009/Amdt 1-2011.
C. Ltd. (2009 ). C. Putoline HPX Fork &Suspension
Oil
Available: http://www.championmotouk.com/product-info-t.php?Putoline-HPX-ForkSuspension-Oil-pid10650.html
SImetric. ( 2011). specific gravity ofliquids.
Available: http://www.simetric.co.uk/si_liq
uids.htm
A. 1289.6.2.2, "Methods of testing soils forengineering purposes - Soil strength andconsolidation tests - Determination of shear
strength of a soil - Direct shear test using a
shear box," ed, 1998.
E. Cokca, O. Erol, and F. Armangil,"Effects of compaction moisture content on
the shear strength of an unsaturated clay,"
Geotechnical & Geological Engineering,
vol. 22, pp. 285-297, 2004.
Z. Rahman, H. Umar, and N. Ahmad,"Geotechnical characteristics of oilcontaminated granitic and metasedimentarysoils," Asian J. Applied Sci, vol. 3, pp. 237249, 2010.
M. Khamehchiyan, A. Hossein Charkhabi,
and M. Tajik, "Effects of crude oil
contamination on geotechnical properties ofclayey and sandy soils," Engineering
Geology, vol. 89, pp. 220-229, 2007.
H. B. Seed, J. Mitchell, and C. Chan, "Thestrength of compacted cohesive soils, in
Shear strength of cohesive soils," 1961.

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

MONITORING THE STIFFNESS CHANGE IN CLAY WITH BENDER
ELEMENT AND ELECTROMAGNETIC METHODS
Chee-Ming Chan1 and Mohd Zarar Mohd Jenu2
Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, Malaysia; 2Research Centre forApplied Electromagnetic, Universiti Tun Hussein Onn Malaysia, Malaysia

1

ABSTRACT
Soil’s stiffness is usually measured in the laboratory in an indirect manner, such as by derivation from thegradient of a stress-strain plot. It requires numerous tests and may be compounded by error from the original
measurement itself. As such, the bender element test has been rather popular among researchers for determining
the small strain moduli of soils with minimal disturbance to the specimens. This paper examines the possibility ofrelating the bender element data with the dielectric constant obtained from the same soil specimen using anelectromagnetic test setup. As both tests are non-destructive, they can be easily repeated on the same specimen
over a period of time without the necessity of duplicate specimens. A clay sample was used in the present study,
with varying water content corresponding to different 1-dimensional compression stresses. It was generally foundthat the resulting stiffness change was detectable from both the shear wave velocity (v s) obtained from the benderelement tests, as well as the dielectric constant () of the electromagnetic measurements, with fairly goodcorrespondence between the two. These results shed light on the possibility of relating relevant geotechnicalparameters with both the measurements for establishing a unique set of signatures for stiffness monitoring anddetermination in soils.
Keywords: Stiffness, Bender element, Electromagnetic waves, Dielectric constantwater contents were used to establish the basic
correlation between water content of the soil and theelectromagnetic measurements. Oedometer test wasalso carried out with corresponding monitoring of thestiffness change with both the tests. As can beperceived, the soil’s water content is the parameterlinking measurements obtained from both the nondestructive tests, as elaborated in the ensuing sectionof the paper.
Bender elements are piezoelectric ceramic
devices wired in such manner as to transmit and/or
receive compression or shear waves. The direction of
motion of the bender element inserted to normally nomore than 5 mm of the ends of a soil specimen,
whether perpendicular or parallel with the orientationof the specimen, produces the respective waves. It has
become rather widely adopted in geotechnical testingin the past decade due to its simplicity, e.g. [1]-[4],though the definition of the wave arrival time remains
very much an area of subjectivity. Nonetheless aslong as caution is taken in conducting the test, andthat the same arrival time identification method isused throughout the exercise, the errors orinconsistencies are expected to be systematic, e.g.
reported by [5] & [6], and can be minimized withsome normalization manipulations, for instance. The
wave arrival time was determined by taking the time
lapse between trigger of the wave (time zero) and firstdetection by the receiver, as depicted as the initial
positive deflection in the received wave form

INTRODUCTION
Extensive field as well as laboratory tests andmeasurements are necessary to ascertain thesuitability of in situ soils for supporting a particular
structure, often incurring significant costs and time
consumption. This is especially so for the laboratory
tests, where undisturbed soil samples must be
retrieved, preserved and transported to the relevant
facilities for the various tests. As such, it is always
favourable to minimize test samples retrieval byimplementing non-destructive measurements withease of repetition and cross-check.
This paper attempts to describe one suchendeavour by using the bender element andelectromagnetic techniques to monitor stiffnesschange in clay soil. The soil sample was preparedfrom kaolin powder with the addition of various watercontents. A series of oedometer tests were also carriedout to simulate actual post-consolidation improved
stiffness of the soil in correspondence withmeasurements using the bender element andelectromagnetic methods. The data obtained werecross-correlated to determine the effectiveness ofmonitoring stiffness with both the methods.
MATERIALS AND METHODS
The soil sample was prepared by admixing kaolin
powder with water. These samples with different
129

GEOMATE- Brisbane, Nov. 19-21, 2014

Transmitted wave

Receiver

Received wave

Specimen
Transmitter

Fig.1
Bender element test setup.

11 cm

3 cm

2 cm

Fig.2

Electromagnetic test setup.
highfrequency
permittivity
valuesfromcharacteristic points of the waveforms [8]. The
present study adopted a setup developed in-house(Fig. 2), which comprised of a network analyzer(Rohde & Schwarz), a pair of coaxial cable and aparallel plate cell. The soil sample was placed in arectangular acrylic mould of 3 cm x 11 cm x 2 cm.
The system was conditioned to measure S-parameters
over the frequency range of 10 MHz to 14 GHz. The
measured S-parameters were saved in a Mathlab
programme for subsequent computations of therelative permittivity or dielectric constant.

captured on screen. The shear wave velocity (vs) was
then easily computed by dividing the tip-to-tip
distance of the bender elements on both ends of thespecimen with the arrival time determined. Note that
only shear waves were adopted in the present work to
avoid masking of the actual velocities by thecompression wave propagating through the porewater instead of the soil skeleton, i.e. giving P-wave
velocity of the water,  1480 m/s. The GDS BE
system was used in the present study (Fig. 1).. The
specimens were cylindrical, 38 mm in diameter and
76 mm in height subjected to the bender element test
(input frequency 650 Hz).
The electromagnetic method is a potential
alternative method to determine key soil properties
such as compressibility, strength and hydraulicconductivity. Referring to reports in [7], the highdielectric constant of water compared to soil solids
makes the dielectric constant of moist soil highly
dependent on the moisture content of soil, making it
a viable tool for estimating the amount of moisturepresent in a soil mass. The dielectric permittivity isfound to be the most suitable electromagnetic
parameter for soil testing, attributed to the highfrequency permittivity parameters of waveforms
produced by measurement systems with low
attenuation. The properties of the waveforms are used
to derive simple relations for estimation of low and

RESULTS AND DISCUSSIONS
Fig. 3 shows vs plotted against w, with a fairly goodcorrelations indicated in the correlation coefficient,i.e. R2 = 0.8808. With increased water content, thesoil’s structural skeleton essentially collapses into aliquefied mass. The solid particles are dispersed
within the large amount of pore water present,
resulting in excessive damping or impedance of theshear wave propagation. Note too that theperpendicularly traversing motion induced by theshear waves diminishes with reduced stiffness of themedium, such as a watery soil mass. As such, theshear waves take a longer time to travel between thetransmitting and receiving ends of the specimens,
130

GEOMATE- Brisbane, Nov. 19-21, 2014

resulting in declining vs.
On the other hand, the 1-dimensional compression
curve was derived from a standard oedometer test on
the soil specimen (Fig. 4), while Fig. 5 depicts thesame data in terms of water content change. As
consolidation causes gradual dissipation of excess
pore water with an applied load, the settlement
recorded (i.e. represented by the void ratio, e) is
directly proportionate to the water content of the soil
specimen at the end of a particular loading stage. The
w values shown in Fig. 5 were actual measurements
taken of samples from the post-consolidation
specimens. With expulsion of the excess pore waterand zeroing of the excess pore water pressure, theexerted load was progressively transferred to thesoil’s skeleton. This consequently enhanced the soil’s
stiffness as a whole, with greater load-bearing
capacity compared to its original form, i.e. stiffness
improvement.
It follows that with vs governed by w, and that w
is of direct relation to the void ratio changes uponloading of the soil specimen, vs can be correlated withe as shown in Fig. 6. With greater load applications in
the oedometer test, more significant pore water
dissipation took place, resulting in increased
settlement or void ratio reduction. The outcome of theprocess was the stiffening of the soil matrix, as
captured by the vs increment in Fig. 6. Of course, withan oedometer cell incorporated with bender elements,
actual real-time vs changes could be monitored as theconsolidation occurs, such as reported by [9]. The
current indirect correlation method notwithstanding,it was considered suffice for the end-of-primaryconsolidation vs values to be inferred from thecorresponding water content.
Fig. 8 summarizes the electromagnetic
measurement of dielectric constant (e) on the soil
specimen prepared at different water contents. The
specimens subjected to the electromagnetic test were
carefully prepared so as to have the same density andwater content as the oedometer counterparts. Clearlya linear regression line can be plotted through the data
points, indicating the rising trend of  with increased
w. It ought to be mentioned that the measurement
mechanism of the electromagnetic test setup is rather
sensitive, leading to the scatter of data obtained. The
scatter in Fig. 8 may be due to several factors,
including the inaccuracy of water addition in the soil,
the non-uniform distribution of water in the soil, thepossibly variable calibration conditions, themisalignment (albeit small) of the mould placed in
between the parallel plates, and possibly unevencontact surface of the soil with the top plate.
The electromagnetic field surrounding the soil
was apparently significantly influenced by the water
present in the soil specimen. The correlation in Fig. 8
enables estimation of the soil’s improved stiffness via
the water content, which is directly related to thecompressibility of a saturated specimen. For practicalvs = 275.3exp-0.06w(R2 = 0.8808)

Fig.3

vs – w.

Fig.4

e – v’.

w = 66.4exp-0.002v’(R2 = 0.9770)

Fig.5

w – v’.

purposes, one would only need to identify the  or vsvalue of a soil specimen to ascertain the stiffness,without having to subject the soil sample to the timeconsuming oedometer test.
It is intuitive to expect that the rise in stiffness ofa soil would be accompanied a proportional increasein strength as well. Fig. 9 relating the undrained shear
strength (cu) and e was derived from the Author’s pastwork with the same soil [10]. It is interesting to notethat the change in  in the lower strength range (<200kPa) is far less significant than in the higher strength
range. As problematic in situ clay soils are usually131

GEOMATE- Brisbane, Nov. 19-21, 2014Fig.6

 = 0.03w + 4.50
(R2 = 0.6564)

vs = 275.3exp-1.93w

vs – e.

Fig.8

vs = 10.55exp0.005v’(R2 = 0.9378)

Fig.7

– w.

cu = 8.55x104exp-1.31
(R2 = 0.9854)

vs – v’.

Fig.9
cu - .
progress to improve and refine the geocharacterisation techniques for application in a wider
range of soil type and conditions, e.g. mixed andcontaminated soils.

found in the low strength range, the electromagnetic
measurement technique appears to lack the sensitivity
necessary to detect the changes. Furthermore soils do
not normally have compressive strengths greater than
1 MPa (e.g. soft rocks), hence it is more relevant toexamine the cu- correlation within the common
lower strength range for foundation clay soils.
Nonetheless, it does show that the increment instrength corresponds with a reduction in watercontent, which in a clay soil indicates animprovement of the stiffness with expulsion of excess
pore water via consolidation. The much higher cu
within the low  range can be explained by the lower
water content of the soil with advanced consolidation,and hence greater stiffness.

ACKNOWLEDGEMENTS
Special thanks to W-K Loke who diligently
carried out the laboratory work described in the paper.
Funds were provided by the FRGS research grant,
Ministry of Education, Malaysia.
REFERENCES[1] Arroyo, M, Pineda, JA and Romero, E, “Shearwave measurements using bender elements inargillaceous rocks”, ASTM Geotechical Testing
Journal, Vol. 33, No. 6, 2012, pp. 1-11.
[2] Tanaka, H and Seng, S, “Properties of very soft
clays: A study of thixotropic hardening andbehavior under low consolidation presssure”,
Soils and Foundations, Vol. 52, No. 2, 2012, pp.
335-345.
[3] Chan, C-M, “Bender element test in soil
specimen: Identifying the shear wave arrival
time”, Electronic Journal of GeotechnicalEngineering, Vol. 15, pp. 1263-1276.

CONCLUSIONSThe shear wave velocity (vs) and dielectric constant() were both non-destructive techniques formonitoring stiffness change in clay soils. The present
work examined the measurements with an artificiallyprepared soil sample, i.e. kaolin at different watercontents. It was found that the soil with higher watercontent gives lower vs and higher , withcorresponding decrease in void ratio (e) and increasein stiffness respectively. Further work is currently in132

GEOMATE- Brisbane, Nov. 19-21, 2014[8] Savi, P and Maio, IA, “Soil permittivity
estimation from time domain reflectometry(TDR)
measurements:
properties
andguidelines”, in Proc. Int. Conf. on
Electromagnetics in Advanced Applications,
2007, pp. 288-291.
[9] Chan, C-M, “One-dimensional compressibilityof stabilised column systems with shear wave
velocity measurements”, Proc. 16th. South East
Asian Geotechnical Conference, 2007, pp. 247254.
[10] Chan, C-M, Wong, W-K and Mohd Jenu, MZ,(2013). “On the geo-electromagnetic propertiesof clay: elementary characterization”, in Proc. 1st
Int. Conf. on the Science and Engineering ofMaterials, 2013.

[4] Kawaguchi, T, Mitachi, T and Shibuya, S,“Evaluation of shear wave travel time inlaboratory bender element test”, in Proc. 15th. Int.
Conf. on Soil Mechanics and GeotechnicalEngineering, 2001, pp. 155-158.
[5] Chan, C-M, “Variation of shear wave arrival
time in unconfined soil specimens measured withbender elements”, J. of Geotechnical andGeological Engineering, Vol. 30, No. 2, .2012,
pp. 419-430.
[6] Yamashita, S, Fujiwara, T, Kawaguchi, T,
Mikami, T, Nakata, Y and Shibuya, S,“International parallel test on the measurement ofGmax using bender elements”, TC-29, ISSMGE,
2008.
[7] Siddiqui, SI, Drnevich, VP and Deschamps, RA,“Time domain reflectrometry development for
use in geotechnical engineering”, ASTM
Geotechical Testing Journal, Vol. 23, No. 1,
2000, pp. 9-20.

133

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

NUMERICAL SIMULATION OF THE IMPULSE RESPONSE METHODFOR RIGID PAVEMENT EVALUATION
Hudson Jackson1 and Kassim Tarhini1
1Faculty, United States Coast Guard Academy, United States of America.

ABSTRACT: The Impulse Response (IR) technique is a stress wave method that measures the structure’s responseto stress waves generated by an impact source. When applied to rigid pavements, the measured response contains
complex information on the dynamic pavement properties that is primarily used in detection of voids or loss of
support, and softening of the subgrade. The dynamic response of the pavement system is assumed to be similar tothat of a single degree of freedom (SDOF) system. This assumption is useful for practical purposes but introduces
inconsistencies and uncertainties in the data interpretation because it oversimplifies a complex dynamic problem.
Results of a Finite Element parametric study analysis conducted to identify key factors that influence rigid
pavement response during Impulse Response (IR) testing are presented. A dynamic modal analysis of a multilayer
rigid pavement, assuming viscoelastic and elastic linear material properties, indicates that the mobility spectrafrom IR testing is predominantly influenced by the properties of the surface layer and the subgrade. The presenceof voids beneath a rigid pavement results in increased mobility and less damped behavior of the pavement. The
validity of the SDOF assumption in void detection in the reduction of field IR data is also examined.
Keywords: Impulse response, Rigid pavement, Nondestructive testing, Voids, Flexibility spectrum, Finite element,
Mobility

method. The interaction of stress waves with internal
discontinuities critically depends upon therelationship between wavelength and the dimensions
and depth of the discontinuity [1].
The current IR data reduction procedure
represents the dynamic response of the pavement-soil
system as single degree of freedom (SDOF) system.
Curve fitting between the actual response and that ofa SDOF system is done to obtain the necessary modalparameters. The assumption of a SDOF response
oversimplifies the problem and, although useful forpractical purposes, introduces inconsistencies anduncertainties in the data interpretation [2]. The results
obtained from the SDOF simulation are not always
representative of the actual response of the pavementsoil system depending on the vibration mode,
properties of the supporting soil and characteristics(geometry, rigidity) of the pavement due to a complex
variation of stiffness and damping coefficient withfrequency.
In order to investigate the validity of theassumption of the SDOF response and to improvedata interpretation of the IR method used in the
Seismic Pavement Analyzer, a finite element based
parametric study of factors affecting the response of
rigid pavements with and without voids was
conducted. The first part of the paper discusses
fundamentals of the IR technique used in pavement
condition assessment. The second part deals with thefinite element simulation of the IR test and effects ofvarious parameters on the response and mobility
spectra.

INTRODUCTION
The Impulse Response (IR) method is a surface
reflection method that depends on the propagation ofstress wave through the pavement system. The
pavement is excited by an impact and the response
measured. There are generally three major types ofwaves in an elastic half-space that are of interest forpavement testing, namely; compression (P), shear (S)and Rayleigh (R) waves. The nature of an impact andthe medium of propagation determine which wave
dominates. In a layered half-space, with two or morelayers, the waves undergo reflections and refractions
at each interface. Changes in the wave velocity,
density or elastic modulus causes an impedancechange. The fraction of the incident wave that isreflected from an interface is dependent on the
impedances of both media.
Pavement systems can be considered as layeredelastic systems. Waves generated by an impact travel
through the structure producing disturbances within
the pavement. The disturbances are generally small
and in the elastic range; the effects can therefore beconsidered in terms of the propagation of elastic stresswaves within the pavement. The generated waves are
generally composed of widely distributed frequency
components. The nature of the stress waves generated
determines their ability to propagate through thevarious pavement materials and their ability to detect
defects in the pavement system. In general, defects on
the order of, or greater than, the wavelength of the
propagating wave can be fully detected by the IR
134

GEOMATE- Brisbane, Nov. 19-21, 2014

ratio of load to velocity, termed mobility, isdetermined. The mobility is integrated to obtain the
stiffness. The mobility of pavement slabs with good
support is fairly uniform up to a frequency of about
600 Hz, while a pavement with voids or loss of
support has multiple resonant peaks. The underlying
assumption of the IR method is that a rigid pavement
system can be approximated by a response of a SDOF
system, with the controlling stiffness being that of thesubgrade.
Both the load and time histories and corresponding
spectra are obtained from a load cell and a close lowfrequency geophone (G1) respectively. The dynamic
stiffness spectrum, representing the ratio of the two(load and displacement) spectra is matched by the
response spectrum of a single degree of freedom
system. The modal parameters of the SDOF system:
the natural frequency, static stiffness and damping
ratio are obtained to characterize the pavement. The
natural frequency and static stiffness are used toevaluate the shear modulus, and the mobility anddamping characteristics to detect voids or loss of
support.
Detection of loss of support due to presence of voids
underneath rigid pavements relies on a change in the
pavement mobility. Voids cause a significant portionof the wave energy to be reflected back to the surface,resulting in an increase in mobility and a less damped
response. Response of a slab with good support orsound contact can be described as a highly damped
response, because a large portion of the impact energy
can be radiated towards the interior of the medium.

OVERVIEW OF THE IMPULSE RESPONSE
METHODThe Impulse Response method also known as theTransient Dynamic method is a nondestructive testing
method that is used in quality control and conditionassessment of pavements and deep foundations. The
IR method has been successfully used to determine
the subgrade modulus and presence of voids or lossof support in rigid pavements [3, 4].
Field Testing
The pavement is first divided into square grids andtesting is done at the corner of each grid. The
pavement is excited and the response measured at a
nearby location. Spectra for both impact and response(particle velocity) are combined to obtain either themobility, flexibility or impedance function of thepavement. IR testing has been incorporated into a
device called the Seismic Pavement Analyzer (SPA).
The SPA, shown in Fig. 1, is a device fornondestructive testing (NDT) of pavements,
developed at the University of Texas at El Paso under
the Strategic Highway Research Program [2]. Five
different wave propagation techniques (spectral
analysis of surface waves, impact echo, ultrasonicbody waves, ultrasonic surface waves and impulse
response) are incorporated into this device. The IR
test done with the SPA uses the low frequency impact
source and a nearest geophone G1, 25 cm away (Fig.
1). The rigid pavement is impacted to couple stresswaves energy in the surface layer. A portion of theenergy is reflected at the slab-base interface and a
portion is transmitted to the subgrade. The load cellat the tip of the low frequency source records theimpact energy, while the response, in terms of theparticle velocity, is recorded by geophone G1.

FINITE ELEMENT PARAMETRIC STUDY
A finite element parametric study was conducted toinvestigate the influence of factors such as pavement
dimensions, Poisson’s ratio, elastic modulus andflexural rigidity of the slab; layer thicknesses, elastic
modulus of the base layer, the elastic modulus of thesubgrade, and depth to bedrock on the dynamic
response of a rigid pavement subjected to IR loading.
ABAQUS finite element software was used in thesimulation.
Rigid Pavement Model Geometry
The cross section and pavement layer properties
are shown in Fig. 2. The pavement is modeled as amultilayered viscoelastic system and is treated as aplane strain problem, symmetrical with respect to thepoint of load application. The finite element model isdiscretized using 8-node biquadratic plane strain
elements with a width of 10cm in the horizontal
direction. In the vicinity of the load, the mesh isrefined using smaller elements. Both the concrete slab
and base layers are discretized by 3 rows of elements
each.

Fig. 1 Schematic of the Seismic Pavement Analyzer.
2.2 Data Reduction and Interpretation
The recorded load and velocity histories are thentransformed to the frequency domain using a FastFourier Transform algorithm. At each frequency, the135GEOMATE- Brisbane, Nov. 19-21, 2014

and α = 10-3 s into Rayleigh damping equation yields
a damping ratio of 0 – 30 %. The damping ratio forthe models was assumed to be in this range.
Voids were simulated by defining them as cracks,
or by a removal of already generated elements. Whendescribed as cracks, voids were defined by two sets ofelements above and below the crack connected to two
sets of nodes of the same coordinates, but without adirect connection. The ranges of properties
investigated are shown in Fig. 3 and summarized asfollows:• Concrete slab thickness-15, 22.5, 30, 45 cm• Base layer thickness-0, 15, 22.5, 30, 40 cm• Young’s modulus of slab-22, 35, 50 GPa• Shear modulus of base layer-232, 300, 385 MPa• Shear modulus of subgrade-19, 76, 120 MPa• Depth to bedrock-2.5, 5, 10, 25 m

Fig. 2 Cross section and material properties of threelayer rigid pavement
Two finite element models, shown in Fig. 3, wereused. In both models, the same mesh discretizationand element type for the concrete slab and base layer
are used. Four-node plane strain infinite elements areused in the description of the subgrade in bothmodels. Using infinite elements eliminates the needto truncate the infinite domain and provide a meansof effectively modeling extensive subgrade soil layers[5]. Model 1 represents a pavement supported on a
uniform subgrade of finite thickness (stiff layer at a
depth of 4.95 m). Model 2 better represents a halfspace of infinite depth underneath a pavement.

RESULTS AND DISCUSSION
The absolute mobility and stiffness spectra 25 cm(similar to the location of geophone G1 in the SPA)
from the impact source are shown in Figs. 4 and 5.
The mobility for model 1 and model 2 with H/R=10,
increases with frequency and then decreases after
reaching a peak value. The absolute stiffness
generally increases with frequency. These trends are
identical to that observed from IR field results from
SPA testing. The mobility for both models are
uniform for high values of depth to bedrock/width(H/B) ratios—i.e. deeper depths to bedrock.

( )

nts
me
Ele

te
ini
Inf

Infinite Elements

nts
me
Ele

Horizontal restraint

Horizontal restraint

ite
Fin

5 (2.5) m

5 (2.5) m

5 (2.5) m

ite
Fin

nts
me
Ele

5 (2.5) m

te
ini
Inf

nts
me
Ele

Vertical Restraint(a)(b)
Fig. 3 Schematics of FE Model 1 (a) & Model 2 (b)Model 1Model 2 (H/R=2)
Model 2 (H/R=10)

Mobility [m/sN]

2.50E-07

Loading and Frequency Resolution
The loading was approximated by a Haversinefunction of 1.6 ms duration and maximum force of
5kN. This impact loading function was selected
because it closely describes a typical hammer impactof the Seismic Pavement Analyzer (SPA). Time
integration of 0.8 ms with 2048 increments was used,providing a maximum frequency of 625 Hz with a
0.61 Hz resolution.

2.00E-07
1.50E-07
1.00E-07
5.00E-08
0.00E+00
18

0

37

55

73

91

110 128 146 165 183

Frequency [Hz]Fig. 4 Typical mobility spectra for models 1 & 2
5.00E+09
Model 1Model 2 (H/R =2)
Model 2 (H/R=10)

4.50E+09
4.00E+09

Stiffness [N/m]Layer Properties
Since the strain level induced in the pavement
layers during IR testing is very low, materials of all
the layers are described as linearly elastic. Eachpavement layer is described by its shear modulus(shear wave velocity), mass density and Poisson’s
ratio. Damping is described as a Rayleigh type
damping, with Rayleigh constants β and α equal to 0
s-1 and 10-3 s, respectively. In this study, the maximum
frequency of interest was about 600 Hz and the lowest
frequency, 0 Hz. Substituting these values β = 0 s-1

3.50E+09
3.00E+09
2.50E+09
2.00E+09
1.50E+09
1.00E+09
5.00E+08
0.00E+00
0

12

24

37
49
61
Frequency [Hz]

73

85

98

110

Fig. 5 Typical variation of absolute stiffness withfrequency

136

GEOMATE- Brisbane, Nov. 19-21, 2014

The mobility and stiffness for model 1 and model 2(with H/B =10, implying extensive depth to bedrock)
being similar is an indication that infinite elements
suitable represent the subgrade as a half-space withno depth limitation. For model 2 with H/R = 2(implying shallow bedrock), multiple peaks areobserved in the absolute mobility and stiffness
spectra. Due to a slight rigid body motion caused by
the use of infinite elements, a small static component
is introduced resulting in a nonzero mobility at zerofrequency (Fig. 5). Two prominent peaks at 17 Hz and
44 Hz, corresponding to the natural frequency of thesubgrade to shear and compression waves,respectively, are evident in the mobility spectra ofmodel 2 with H/R = 2 (Fig. 4). It appears that the firstpeak (at 17 Hz) in the mobility spectrum is related, toa certain degree, to the amount of reflections within
the model.
For a harmonic excitation, an analogy can be drawn
between a SDOF oscillator and a massless 3D
foundation on an elastic half-space [6]. The dynamic
stiffness or impedance S(ω) (for a particularfrequency) is given by the following Eq. 1.

and is also typical for rectangular footings on ahomogeneous half-space [8].
Influence of Flexural Rigidity of Concrete Slab
Effects of slab thickness, d 1, and Young’s Elastic
Modulus, E sl, can be combined into a flexural rigidity(FR) of the slab given by Eq. 3.
FR = E sl d 1 3/12(1 - ν2)(3)

The range of slab thickness and Young’s modulus
investigated are shown in Table 1 as well as thecorresponding dimensionless stiffness ratios (SR),defined as:
SR = FR/G s R e 3(4)

Where, G s is the shear modulus of the subgrade and
R e is the equivalent radius of the concrete slab. SR
represents the relative flexural rigidity of the concreteslab to that of the soil subgrade.
Table 1 Range of flexural rigidity and stiffness ratio𝝎𝝎𝟐𝟐

𝑺𝑺(𝝎𝝎) = 𝑲𝑲𝒔𝒔 ��𝟏𝟏 − 𝝎𝝎𝟐𝟐 � + 𝒊𝒊𝒊𝒊𝜷𝜷𝒅𝒅
𝒏𝒏

𝝎𝝎

𝝎𝝎𝒏𝒏

�

(1)

Where, β d is the critical damping ratio, ωn the natural
frequency, and K s the static stiffness of the slab–soil
system.
The shear modulus of the subgrade can becalculated based on its relationship with static
stiffness (Eq. 2) developed for a rigid circular
foundation resting on a homogeneous half-space [7].
𝟒𝟒𝟒𝟒𝑹𝑹

𝑲𝑲𝒔𝒔 = 𝟏𝟏−𝝊𝝊𝒆𝒆

Slabthicknessd 1 [m]Elastic
Modulusof slab
E sl[GN/m2]

Flexuralrigidity
FR
[MNm]

0.150
0.150
0.150
0.225
0.300
0.450

22
34.5
49.7
22
22
22

6.3
9.9
14.3
21.4
50.6
170.9

Shear
ModulusofsubgradeGs[MN/m2]
76
76
76
76
76
76

Shear
Modulusof baseGb[MN/m2
]
232
232
232
232
232
232

Stiffness
Ratio
SR
x10-3

1.2
1.9
2.7
4.0
9.6
32.4

In general, mobility decreases with increasing
flexural rigidity or stiffness ratio. Mobility is moresensitive to changes in flexural rigidity due to changes
in slab thickness than to changes in Young’s modulus.
This is evident from Eq. 3; flexural rigidity varies
with thickness to the third power. There is a generalincrease in stiffness with flexural rigidity withchanges more pronounced at higher frequencies. The
static stiffness, K s was normalized to that of a“typical” rigid pavement. For the purpose of thisstudy, the typical or standard rigid pavement was
defined as one with a 450 mm slab, slab elastic
modulus of 22 GPa, shear modulus of base layer andsubgrade of 232 MPa and 76 MPa, respectively (i.e,flexural rigidity ≥ 170MNm, SR ≥ 0.032). There is
negligible change in static stiffness with increasing
stiffness ratio. There was only a 1% change in static
stiffness over the range of stiffness ratios investigatedfor model 1. The changes in static stiffness becomes
more significant with decreasing H/B ratio for model
2. The normalized static stiffness increases
logarithmically for model 1. Similar trends wereobserved for the individual variation of H/B ratios.

(2)

Where, G is the shear modulus of the subgrade, R e theequivalent radius, and υ Poisson’s ratio of the soil.
Since pavement slabs are not circular, K s must be
corrected by applying a shape correction factor toaccount for the effect of length to breadth ratio on
dynamic stiffness [7]. It can be seen from Eq. 1 thatthe dynamic stiffness of a SDOF system varies as asecond degree parabola with the first part
representing the spring function (real part ofspectrum) and the second, the damping function(imaginary part of spectrum). By measuring theimpedance, the parameters needed to characterize thesystem such as static stiffness, damping ratio andnatural frequency, the appropriate pavement
properties can be determined. In general spring
function for both models increases and then decreases
with increasing frequency. This trend is observed infield data of rigid pavements collected with the SPA

137

GEOMATE- Brisbane, Nov. 19-21, 2014

Peak(maximum)mobility
decreases
logarithmically with increasing slab flexural rigidity
and slab-subgrade stiffness ratio for both models.
However, model 2 is more sensitive to changes in the
flexural rigidity of the slab due to the effect of thedepth to bedrock on wave propagation within the
pavement layers.

observed for model 2. Both the static stiffness (SS)and peak mobility (PM) show a perfectly linear
relationship with TR. SS increases while PMdecreases linearly with TR. For the range of TR
investigated, a 5% increase in static stiffness wasobserved for model 1 and 9% increase in model 2.
These slight changes suggest that changes in baselayer thickness do not have a profound effect on thestatic stiffness of the pavement-soil system. Peakmobility on the other hand, is more sensitive tochanges in the thickness ratio. This implies that
contribution of the base layer can be significant insome cases related to mobility and should not always
be neglected in IR data reduction.

Influence of Shear Moduli of Base and Subgrade
The results are presented in terms of shear
modulus ratio GR, defined as the ratio of the shear
modulus of the pavement base layer to that of thesubgrade. Six different values of GR ranging from 2.0
to 12.0 were investigated. The shear modulus of thebase was held constant at 232 MN/m2, while that of
the subgrade was varied; this enabled the effects ofsubgrade shear modulus to be investigated. The shear
modulus of the base layer (GR = 3, 4, and 5) was also
varied while that of the subgrade was held constant at
76 MN/m2. The influence on the response due tochanges in the shear modulus of the base layer are
typically not significant. This is reflected in almost
identical results for shear ratios of 3, 4 and 5 when Gof the base was changed. Static stiffness decreases
with increasing shear modulus ratio. A high shear
modulus ratio implies a weaker subgrade compared tothe pavement base layer. One of the key assumptionsof the IR data reduction for rigid pavements is that the
subgrade, being the weakest layer, dominates the
response. The static stiffness is therefore expected todecrease with decrease in the shear modulus of thesubgrade.
For GR = 12, which can be considered as apavement with a weak subgrade support, more
pronounced peaks in mobility were observed. These
trends in mobility and stiffness are in agreement withthe assumption that response to low frequency
loading from IR testing is dominated by the quality ofthe subgrade support.

Influence of Depth to Bedrock
The results are expressed in terms of H/B ratio,
where H is the depth to bedrock and B is half thewidth of the pavement slab. Peak mobility increases
with decreasing depth to bedrock. As expected, thestatic stiffness decreases with increasing depth to
bedrock. For H/B = 10, the response approaches thatof a pavement resting on a homogenous half-space.
This is in agreement with work done by Gazetas,
which suggests that, the response of a rigid circular
disk on a stratum over a rigid base approaches that of
the corresponding half-space for H/B = 8 [8]. The
same trend is expected for rigid strip footings, but at
higher H/B ratios.
Influence of Voids
Three different void lengths, 60, 90 and 120 cm
were introduced at the slab-base layer interface. The
mobility of the pavement-soil system increases withincreasing void length, with a slight shift of the peak
to higher frequencies. As void size increases, thepeak becomes more pronounced over a narrower
frequency range. For model 2, as void length
increases, the second peak mobility becomessignificantly higher than the first. This is due to astronger reflection of stress wave from the voids
before reaching the horizontal boundary. Bothdamping and spring function decrease with increasing
void size. This is in agreement with findings ofNazarian et al as well as field data collected on rigid
pavements [3]. Changes are more pronounced for thedamping function. Most of the energy from theimpact is reflected back to the surface resulting in a
reduction of damping of the pavement system whenvoids are present. This reduced damping implies
higher displacements. If the loss of support isextensive, the slab tends to deform in a bending mode.
Depending on the location of the void, and themagnitude of the impact, the slab deforms similar toa simply or fixed supported beam with multiple
oscillations. In general, spring function decreases
with increasing void size. As void size decreases, theInfluence of Thickness of Base Layer
Effects of the thickness of the base layer were
investigated by varying it from 0 (slab on grade withno base layer) to 45 cm, while maintaining the slab
thickness at a minimum thickness of 15 cm. The shear
modulus of the base (G b ) and subgrade (G s ) were also
held constant at 232 MN/m2 and 76 MN/m2,
respectively (GR = 3.0). The results are expressed interms of a dimensionless thickness ratio, TR, definedas the ratio of thickness of the base layer (d 2 ) to thatof the concrete slab (d 1 ).
Mobility decreases with increase in thickness
ratio. As the thickness of the base layer increases, thestresses and strain induced in the subgrade reduces
because it acts as a stress cushion. This reduction inboth the strain and slab oscillation results in adecrease in overall mobility. Similar trends were138

GEOMATE- Brisbane, Nov. 19-21, 2014

for void lengths larger than double the thickness ofthe slab. As support conditions deteriorate, thefundamental response of the pavement is altered,resulting in the response being dominated by higher
modes of vibration. The effect of the thickness of thebase layer on pavement stiffness is less pronounced,
but in some cases may affect the overall pavement
mobility response significantly.

cross over frequency tends to increase, resulting in a
reduction in natural frequency. It is evident from theresults that the presence of voids or loss of support
results in very significant changes in the mobility
spectra.
VALIDATION OF THE SDOF ASSUMPTION
For a SDOF system, the displacement response
increases with frequency up to a resonance peak andthen decreases as frequency further increases. The
response spectrum has of a single peak. The trends
observed from the numerical simulation do notsupport a SDOF approximation in all cases, especiallyfor values of H/B < 10, and large void sizes relative
to the slab thickness. Multiple mobility peaks areevident for lower H/B ratios as well as for large voids.
These trends are also observed in IR field datacollected using the SPA. The mobility spectra fromtwo rigid pavement sections, with poor support andgood support, respectively are shown in Fig. 7.
Multiple peaks are evident in the pavement with poor
subgrade support. In general, mobility (velocity/load)
as well as the flexibility (displacement/load) of thepavement increases with voids, resulting in a slight
reduction of the fundamental frequency as the support
deteriorates. This indicates that above a given voidsize, the fundamental response of the system, invicinity of the void, is completely altered due to thechanges in support conditions. This phenomenon
cannot be fully captured by a SDOF model.
Hoffmann and Thompson also back-calculated rigid
pavement parameters by matching the measured andtheoretical SDOF frequency response and reported
error of up to 33% [9].
1.2E-05

REFERENCES[1] Sansalone, M.J. and Streett, W.B., “Impact Echo:
Nondestructive Evaluation of Concrete andMasonry.” Bullbrier Press, Jersey Shore, PA,
1997.
[2] Nazarian, S., Baker, M., & Crain, K.
“Development and Testing of a Seismic
Pavement
Analyzer.” Report SHRP-H-375,
Strategic Highway Research Program, National
Research Council, Washington, DC, 1993.
[3] Nazarian, S., Baker, M., & Reddy, S.
“Determination of Voids Under Rigid Pavements
Using
ImpulseResponse
Method.”Nondestructive Testing of Pavements and BackCalculation of Moduli: Second Volume, STP
1198, ASTM Publication, Philadelphia, PA, 473487, 1994.
[4] Gucunski, N., Vitillo, N. and A. Maher.
“Pavement Condition Monitoring by Seismic
Pavement Analyzer (SPA).” Structural Materials
Technology IV–An NDT Conference, Atlantic
City, New Jersey. 2000, pp337-342.
[5] Hjelmstad, K. D., Zuo, Q. and Kim, J. “Elastic
Pavement Analysis Using Infinite Elements.”
Transportation
Research
Record1568,
Washington, DC.
[6] Roesset, M., “Stiffness and Damping Coefficientsof Foundations.” Dynamic Response of Pile
Foundations: Analytical Aspects, ASCE, New
York, NY, 1980.
[7] Dobry, R., and Gazetas, G., “Dynamic Responseof Arbitrary Shaped Foundations,” ASCE
Journal of Geotechnical Engineering, Vol. 112,
No.2, New York, N.Y, 1986, pp109-135.
[8] Gazetas, G., “Analysis of Machine Foundation
Vibrations: State of the Art,” Soil Dynamics andEarthquake Engineering, Vol. 2, No. 1, 1983, pp
1-42.
[9] Hoffmann, M. S. and Thompson, M. R.,“Mechanistic Interpretation of Nondestructive
Pavement Testing Deflections” Transportation
Engineering Series No. 32, University of
Illinois, Urbana, 1981.

I-287: Poor Support
I-295: Good Support

1.0E-05

Mobility [m/sN]

8.0E-06
6.0E-06
4.0E-06
2.0E-06
0.0E+00
0

100

200

300

400

500

600

Frequency [Hz]Fig. 7 Mobility spectra from SPA field data
SUMMARY AND CONCLUSIONS
The results of a Finite Element parametric study
conducted on a three layer rigid pavement models
with unreinforced concrete slabs were presented. In
general, the stiffness of the pavement systemincreases with increasing flexural rigidity of theconcrete slab and thickness ratio, but decreases withincreasing shear modulus ratio. Void or loss of
support results in a significant increase in mobility
and a reduction in the overall stiffness. Furthermore,significant differences in the response were observed139

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

NUMERICAL ANALYSIS ON THE EFFECT OF JET GROUT PILESON AN EXCAVATION LOCATED IN AN URBAN AREA
Akula Pavan1, Thiruvengadam Tamilmani2
1
AECOM Singapore Pte. Ltd., Singapore
2
Bachy Soletanche, Singapore

ABSTRACTThe development of infrastructure in limited land space is a challenging scenario. Infrastructure in limited
land space regions (e.g. Singapore) does not provide freedom to develop at favourable locations instead forces
the engineer to design at the possible locations. Clay with high organic content, commonly referred as Peaty clay
is predominant in coastal areas. This clay being highly acidic (PH>7) and possessing very low shear strength is a
critical factor to the design of infrastructure in the vicinity. Ground improvement adopted weak strata will havevarying effect and may not be able to achieve the required strength. This paper discusses the effect of ground
improvement (Jet Grout Piles) on the sloped excavation predominantly in Peaty clay. A 15m deep excavation
which is 60 m wide is used for the Finite element modeling. Impact study on a tunnel located 40m from the
excavation is presented (The study is carried out for various achieved Jet grout piles strengths of 100, 200, 300,
400 and 500 kPa). The stability of the slopes for the various strengths is also discussed (GeoSlope was used as
the medium to perform the geotechnical analysis).
Keywords: Jet Grout Piles, Peaty clay, Sloped excavation, Impact study
hydrate when mixed with cement, thus it very
difficult to achieve the target undrained shear
strength.

INTRODUCTION
Sloped excavation in an urban area poses threatby means of slope failure which will in turn damage
nearby infrastructure. Hence, a conservative design
approach has to be adopted to prevent slop failure
during excavation. Slope failure is dependent on the
undrained shear strength of the soil and it isfavorable to execute excavation in sub soil
conditions which have high strengths. In cases when
the undrained shear strength is very low (1-2 kPa)ground improvement techniques has to be adopted.

Finite element modeling (PLAXIS) and limit
equilibrium model was used to study the viability ofthe excavation nearby critical structure (tunnel) andgreen field respectively. The constitutive soil models
are derived based on various conservative
assumptions and hence will prevent under design ofthe ground improvement technique adopted.
Modeling the ground improvement and predicting
the ground settlement are accomplished using finite
element modeling

Peaty clay also called as organic clay (due to thepresence of organic materials which starts underaerobic and anaerobic conditions through incomplete
decomposition of plant and animal matter) is highly
acidic in nature and also has very low undrained
shear strength. Unlike clays, in peaty deformation
does not take place by pore pressure dissipation
rather from a continuous rearrangement of soil
particles under constant vertical effective stress after
pore pressure dissipation Ground improvement
technique usually adopted for peaty clay is Jet
Grouted piles (JGP) or grouted stone column.
Grouted stone column may not be used in thepresence of critical structures nearby as it will cause
unnecessary disturbances during the process. Jet
grouted piles on the other hand do not cause these
disturbances and hence are adopted in most of thecases. Triple tube Jet grout system is adopted for thispaper. A challenging characteristic of peaty clay isthat it hinders the formation of calcium silicate

SUB SOIL CONDITIONS HEADINGS
Sub soil conditions are shown in Figure 1. It isevident that there is a predominant amount of peaty
clay. Consists of 10m thick peaty clay layer (acidic
in nature, PH>7) with a SPT value of 4-7. The
organic clay layer is bedded upon a thick layer ofpeaty sand.

Peaty Clay

11 m

12.3 mFig. 1 Sub soil conditions

140

GEOMATE- Brisbane, Nov. 19-21, 2014

necessary to maintain a factor of safety of greaterthan 2 (Global and local slope stability).

Peaty clay is a geological member of Kallang
formation. Kallang formation is a recent formationand has alluvial, marine clay, Estuarine and littoral
clays. The graph presented below shows variation of
Estuarine clay with depth [2]. This graph was plottedbased on the shear strength encountered in various
part of Singapore.

Berm 1 Berm 2 Berm 3

MRT Tunnel
JGP

JGP
JGP

Diaphragm
wallFig. 3 Geometry of the excavation

GROUND IMPROVEMENT SCHEME
The presence of weak sub soil strata (lowundrained shear strength) such as peaty clay andpeaty sand indicates the need for ground
improvement before the start of the excavation [6].
Jet grout piles 1m c/c spacing with varying depths oftreatment as shown in Figure 3. The varying depthof treatment was derived based on the minimum
depth of Improvement required to satisfy theallowable deflection criteria on the tunnel(Horizontal displacement of 25 mm)

Fig. 1 Undrained Cohesion of Estuarine Clays (Source:
LTA CDC, Singapore)

EXCAVATION GEOMETRY
The excavation geometry is shown in Figure 3.
The geometry of the excavation is adopted from thegeneral sloped excavation scheme is Singapore. The
excavation is 60 m wide and 30 m deep. Peaty clay
is encountered from 8 to 18 m overlaying 5m deep
5m peaty sand. Two 10 m wide promenades is to beprovided on either side of the excavation Slope of
1:1.5 is considered on either side. The slopes areinterrupted by two berms so as to increase thestability of the Slopes. Due to the sloped profile it is
not possible to provide Earth retaining stabilizing
scheme (struts and walers).
Side A: Near Critical Structure
A Tunnel 20m away is considered as shown in
Figure 3. The axis of the tunnel is 25m below
ground level Peaty clay. It will be influenced by the
excavation and hence advanced finite element
modeling techniques is considered to study the
impact of the excavation on the tunnel embedded inpeaty clay. In order to reduce the influence of the
excavation on the tunnel it is necessary to provide a
Diaphragm wall 1m thick.

Fig. 4 Jet Grout pile – Plan and Elevation view

Triple tube coring can be used to carry out the
ground improvement scheme as it reduces the timerequired and also attains a uniform mix of JGP. The
uniformity can be checked by taking core samples atthe overlap as shown in figure 4. The samples
should be tested for 7 day and 28 day strengths.

Side B: Near Green Field
Impact of the excavation to green field areas is
not a critical issue due to the absence ofinfrastructure and utilities in the vicinity. The
Diaphragm wall provided for Side A will cut of the
impact of excavation but due to the absence of Earth
Retaining Stabilizing Structure (ERSS) for side B
Slope stability is an important factor and it is141

GEOMATE- Brisbane, Nov. 19-21, 2014

Ground Improvement Methodology
Methodology for the design used is an
important factor in determining the efficiency of themodel. The flowchart presented in figure 5. The
governing criteria are the stability of slopes andimpact of excavation on critical structures.

Fig. 6 – FEM Model (PLAXIS)

Limit state Model

Fig. 7 Limit state model (GEOLSOPE)

Limit state model as shown in Figure 7 wasused for finding the global and local factor of safety
for the slopes near green field. Morgenstern andPrice (1965) [13] method is used to iterate the global
and local factor of safety. Morgenstern and Price[13] method is based on combined equations offorce and moment equilibrium equations. A
modified Newton-Raphson numerical technique wasused to solve for factor of safety satisfying force andmoment equilibrium equations.

Fig. 5 Design Flowchart

FINITE ELEMENT MODEL
The numerical tool used in this work is thecommercial PLAXIS finite element program.
PLAXIS 2D V12 is a 2 Dimensional Finite element
analysis. PLAXIS allows using two elements with 6
or 15 node triangles. All analysis in this paper use 15
node analysis unless otherwise stated. Mohr
Coulomb model (linear soil model) was adopted.

X / E = λf ( x )(1)

Where f(x) is a function that describes themanner in which X/E varies across the slope and λa constant representing a portion of the functionused when solving for factor of safety. Limitation ofthis method is that the direction of the resultant isarbitrary assumed.

Overview of Soil Model
Mohr Coulomb model (Method B - Stiffness
and strength are defined in terms of effective
property) was used for modeling the geologicalstrata. MC model as shown in Figure 6 behaveselastically before failure. The important parameters
used were E’, Cu or C’ for Undrained and Drainedcases respectively. Peaty clay was assumed to benormally consolidated (OCR=1). The drained
stiffness of JGP was based on E’=0.5Cu.
Moderatively, conservative parameters were takenfrom the LTA Civil design criteria thus preventing
under design of the excavation.

RESULTS AND CONCLUSIONSSlope Stability
Berm 1, Berm 2 and Berm 3 as indicated in
Figure 4 were analysed for slope stability. A factorof safety greater than 1.2 was set as minimum
criteria for the improvement strength to beconsidered. Figure 8 indicates the increase in global
Factor of Safety (FOS) is insignificant and increasein undrained shear strength of the JGP did not affect
the Global FOS. This is due to the formation of slip
circle beyond the treatment zone.
The inverse phenomenon is observed in thestability of Berms. Berm 1 and Berm 3 are
142

GEOMATE- Brisbane, Nov. 19-21, 2014

intercepted by untreated Fill and Peat hence theincrease in factor of safety is lower than berm 2
which is embedded in treated peaty clay. The trend
indicates that the liner relationship between the
undrained shear strength and the factor of safety issatisfied for the global and local slip surfaces andalso is in accordance with Morgenstern and Price(1965) limit equilibrium formula.
35

insufficient strength of JGP. Deflection can becontrolled by means of providing struts. The
deflection decreases as the strength of JGP increases
which substantiate the validity of this model.
It is nominal to achieve strength of 200-300 kPa
cause for strengths greater than 300 kPa the head of
the wall moves towards the soil side which in turnwill cause movement on the tunnel which isunfavourable.

Berm 130

Berm 2

It is evident from the figure 10 that the peakbending moment of 1100 kN/m is obtained at a
depth of 30m (Cu = 500 kPa). At a depth of 15m thesame strength of JGP causes the lowest bending
moment of 430 kNm. The trend signifies that greater
the Cu of the JGP greater the Bending moment at
30m and the inverse trend in observed at 15m.

Berm 325

Global

FOS

20
15
10

50

0

40
100

200

300
Cu- JGP (kPa)400

Depth (mRL)

5500

Fig. 8 – Slope stability (FOS) vs Cu – JGP

Finite Element model

00

Impact on Diaphragm Wall

500
1000
Bending Moment (kN.m/m)

1500

Fig. 10 Bending Moment vs. Reduced level

The toe stability of the diaphragm wall is thegoverning factor and hence sufficient toe
embedment to prevent rigid body movement is to be
designed [7]. Figure 9 plots the deflection Vs depth(mRL) for different strengths of JGP. From thegraph, we observe that the toe of Dwall has a lateraldisplacement of less than 10 mm and thus ensuring afactor of safety > 1 for toe stability.

Impact on Tunnel
Bending Moment of Tunnel

JGP strength(kPa)

600

50
40
Depth (mRL)

Cu=100kPa
Cu=200kPa
Cu=300kPa
Cu=400kPa
Cu=500kPa

20
10

Finite element modeling was carried out tostudy the excavation impact on the diaphragm walland tunnel located at 20m from the excavation.

500

0.5817400

0.5966

300

0.651

200

0.69281000.7224

0

30

0.5

0.55

0.6

0.65

0.7

0.75

Bending Moment(kN.m/m)

2010

Cu=100kPa
Cu=200kPa
Cu=300kPa
Cu=400kPa
Cu=500kPa

Fig 11. Bending moment vs Cu-JGP

A tunnel of 6.6m radius is introduced to see theeffect of JGP. The impact of the ground
improvement on the tunnel bending moment iscompared. Figure 11 shows the comparison ofbending moments for various strengths of JGP. The
JGP had helped in reducing the Bending moments ofthe tunnels. It can be observed the bending moments
are indirectly proportional to the JGP strength that is

0
-150

30

-100

-50
0
Deflection (mm)

50

100

Fig. 9 Depth (mRL) vs. Deflection (mm)Maximum deflection of 125 mm (towards the
excavation) is observed at a depth of 20m due to143GEOMATE- Brisbane, Nov. 19-21, 2014

higher the JGP strength lower is the bending
moment. There is a 25% decrease in bending
moment on an average between JGP strength of
100kPa & 500kPa.

[6] Sina, “A review of stablisation of soft soils by
injection of chemical grouting”, Australian
Journal of Basic and Applied Sciences, pp5862-5868[7] South Carolina department of transportation
geotechnical design manual (2010). pp 1-90
[8] Hossain MZ, “For a chapter in a book”, Soil
Mechanics, 4th ed. Vol. 2, Sakai, Ed.
Sankeisha: Publisher’s Name, Year, pp. 11–60.
[9] Author H, A Book. New York: Publisher, Yr,
ch. 3.
[10] Annnn B, “Unpublished work but accepted”,
accepted, Year.
[11] Loganathan.N,
Poulos.H.G,“Analytical
Prediction for Tunneling-induced Groundmovements in Clays”, J. of Geotechnical andGeoenvironmental Engineering, Vol. 124, Sep.
1998, pp. 846-856.
[12] Islam MR, “Conference proceedings”, in Proc.
2nd Int. Conf. on GEOMATE, 2011, pp. 8-13
[13] “Slopestability
modeling
with
SLOPE/W2007”, GEO-SLOPE International
Ltd, 2007, ch. 2.

Soil movement

0

Distance from the wall(m)
20
40

60

0
Displacement of Soil(mm)

10
20
30
40
50
60
70
80

100kPa200kPa300kPa
400kPa500kPa90Fig. 12 comparison of various displacement behind theDiaphragm wall

Figure 12 shows the soil displacement behind
the wall for a JGP strength of 500kPa. It is clearly
inferred that soil movement reduces as we go farther
from the diaphragm wall. There was an impact oftunnel on the displacement of soil but that was notvery high. Maximum displacement of about 40mm
was observed nearer to the wall. All themeasurements were taken along a line at 32mRL.
ACKNOWLEDGEMNET
We would like to thank AECOM Singapore Pte. Ltd.
and Bachy Soletanche, Singapore for theircontinuous support and encouragement.
REFERENCES[1] Biarez, J. and Hicher, P.Y. “Elementary
Mechanics of Soil Behaviour”, 1994.
[2] “Civil Design Criteria for Road and Rail Transit
Systems, Land Transport Authority:, 2010
Singapore.
[3] CP4: Code of Practice for Foundations (2003),
Spring Singapore, Singapore[4] Dames
andMoore(1983),
Detailed
geotechnical study – engineering report anddetailed interpretative report, Mass Rapid
Transit System, Singapore.
[5] Indraratna.B., Basack.S., Rujikiatkamjorn.C(2013), Numerical Solution of Stone Column–
Improved Soft Soil Considering Arching,
Clogging, and Smear Effects. Journal of
GeotechnicalandGeoenvironmental
engineering ASCE,Vol.139, No.3, pp.377-394

144

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

USING DRILL BIT REFUSAL AS AN INDICATOR OF STRENGTH
AT THE CORING INTERFACE
B. Look1, D. Lacey2,3 and D. J. Wiliams2
Foundation Specialists Group, Australia; 2Jacobs, Australia; 3The University of Queensland, Australia

1

ABSTRACTIn residual soil profiles, there is often a gradational transition from soil through to the weathered rock profile.
Across these indistinct interfaces, changes in drilling technique and testing also generally occur, with rock coring
preferred in comparison to advancing boreholes by augering. However significant core loss may occur within
low strength materials, and rock coring is more expensive than other investigative techniques. This quality speed - cost – benefit analysis of investigation is continually completed by the drillers in the field, however the
driller’s knowledge is often omitted from borehole logs in favor of numerical engineering or geological logging.
By capturing “operational” changes in site investigation procedures, an indication of the material profile canalso be made. Based on site investigations completed within South-East Queensland, drilling related data has
been used to show associated soil and rock properties. Relationships (or lack of) between various drill bits andSPT ‘N’ values, rock strength, rock quality designation, rock defects or parent rock types are presented.
Keywords: Residual Soils, Drilling, Coring Interface, Rock Strength, Standard Penetration Test, Drill Bits

the more expensive process of core drilling (i.e. low
likelihood of core loss). Such a result also indicatesthat the continuation of drilling with solid augers
would, in terms of penetration rate and wear and tearon drill bits, be less cost-effective for the driller andthat profit (for the driller) could be optimized by the
adoption of rock coring techniques. After thecommencement of rock coring, SPTs are also
generally not completed, additionally saving thedriller time (for test set-up) and equipment wear.
These commercial assessments, made onsite,
often determine the type and extent of insitu testing /samples that occur. However, the depth at which achange in drilling technique occurs is not necessarilya direct identifier for a significant change in
geological interpretation of, for example, theweathering grade or rock strength at the depth.
It was suggested by [1] that the depth at which
non-core and coring drilling techniques occurs
should not be automatically considered an interface
between extremely weathered (XW) to distinctly
weathered (DW) rock. Cored material should not be
considered to be a different weathering class to thenon-cored material that exists immediately above.
Specifically, as the soil to rock transition is a gradualchange in residual soils, any identified interface is asubjective assessment, and is different from a clear
interface which may be observed when alluvium
soils overly bedrock (refer Fig. 1).
This paper compares the “refusal” depths
identified using varying drilling techniques withother, quantifiable, rock properties such as rockdefect spacing, rock quality designation (RQD),
point load index strength indices (I s(50) ), and the

INTRODUCTION
Intact rock strength and rock structure (e.g.
defects, bedding, rock quality designation) areroutinely used in the assessment of foundation
bearing capacity. The state of rock weathering is
also commonly used to first classify the material andis also an indicator of the likely field strength.
Where deep (piled) foundations are required thepile capacity can be judged during construction,either by piling refusal or rate of pile penetration.
The type of drilling bit used, the rate of drill
penetration, and the type and size of drilling rig canalso be useful indicators of the strength of material.
However these have not traditionally been used as
there are so many variables (e.g. weight of rigs,
which may vary considerably).
Drilling refusal can be identified as being
dependent on both the intact strength and defectspacing in the rockmass, and thus should also beable to be used as a field assessment of rockmass
strength. Similarly, drill bit “refusal” level, based on
the driller’s assessment of when wear and tear on the
drill bits being used exceeds a productive rate ofborehole advancement, is valuable experience thatshould be quantified for engineering purposes.
The cost to advance a borehole using rock coringis, on a per metre basis, over 4 times the cost using
solid augers. This per metre rate excludes the costof testing and sampling; e.g. completion of Standard
Penetration Tests (SPTs) or obtaining an undisturbed
sample. Typically, when an SPT exhibits “refusal”(> 50 blows) this is interpreted as indicating thematerial is of sufficient strength to be recovered via
145

GEOMATE- Brisbane, Nov. 19-21, 2014

results of SPTs. This information was then used toestimate likely founding depths for pile foundations.

Fig. 1

based on the strength and types of soil or rock.
Once bit “refusal” occurs, rock coring will
generally be required. Some investigations use rockcoring as early as possible without taking the auger
to refusal. This has the advantage of recoveringcontinuous samples, but comes at a cost typically 4
to 5 times higher compared to non-core techniques.
There will also generally be significant core loss andlow RQDs associated with low strength rock.
The ‘V’ and TC bit would typically be expected
to display “refusal” within extremely weathered andmoderately weathered rocks with significant defects
respectively, depending on rock type and assuming
the employment of a heavy drilling rig. Table 1
compares the hardness of such drill bits with that ofvarious soil and rock materials.
As a driller aims to avoid wear and tear on
equipment, they select and change drilling bits basedon what they perceive as drilling resistance, which isinferred by the thrust of the equipment. During rockcoring, the selected core bit may vary between:

Simplified residual and transported soil
profiles (from [2])THE SOIL / ROCK INTERFACEThe question of the soil rock interface was raisedby [3], whilst [4] discussed the effect of material
type upon pile adhesion, and identified for a given
material strength, the average adhesion of a pile in a
mudstone, shale, sandstone or limestone rock was 4times greater than that in clay (Fig. 2). Thisdifference was attributed to smooth rock sockets
being produced in soil (clay) materials and impliedthat rock sockets have increased roughness. This soil
/ rock interface and roughness factor for pile shaft
resistance was explored further by [5], and [6]assessed weak rocks (UCS < 0.6 MPa) and equatedthem to soil with an upper bound soil strength (S u )of 300 kPa. Yet despite the significant effect thatthe difference between materials defined as either“soil” or “rock” has on the applied pile shaft
adhesion, this soil / rock interface continues to bepoorly defined on bore logs, especially within
residual soils.

ooo

Saw-tooth – soil or very soft rock
Carbide – soft to medium strength rock
Diamond – soft to extremely hard rockThus, although it would be expected there would
be a relationship between the depth of drill bit
refusal and rock strength, observation of drill bit
refusal would be not enough to provide a soundbasis for rock strength or weathering assessment
when used in isolation. However, when combinedwith other key rock indices, this data could provide
an improved basis for the assessment of subtle
strength change that may occur across the soil / rockinterface.
Table 1 Comparison of hardness of drill bits withmaterial types
Material‘V’ bit –SteelFig. 2 Adhesion factors for normalized shear
strength (from [4])Moh’s
Hardness
7

Comments‘TC’ Bit –Tungsten
Carbide9

Basalt6

with 50% Feldspar

Sandstone
Clays

5.5
7
2.5

with 50% Mafic
with 80% Quartz
Smectite, Kaolinite, Illite

Drilling techniques
Different drill bits are used during drilling toadvance the borehole. These may include auger
drilling with ‘V’ or Tungsten Carbide (TC) bits, orwash boring using a rotary blade, drag, rotary
tricone or rock roller bits. The selection of drill bit is146

GEOMATE- Brisbane, Nov. 19-21, 2014

typically used within Queensland, Australia – ‘V’,
‘TC’ and Rotary / Blade bits – this data was filteredby drill rig size and rock type. The discussion which
follows is for large drilling rigs (i.e. rig ≥ 10 tonnes).

CASE STUDY - TC BIT ‘REFUSAL’ VS ROCKCORING
This case study illustrates how the use of
information relating to TC drill bit refusal compared
to information gained from completion of rockcoring. It also illustrates the scope for incorrectclassification of materials, if the capabilities of eachof these drilling techniques are not understood by
the supervising engineer.
Initially, three boreholes were drilled at a site in
SE Queensland, in which NMLC rock coring wascommenced from within 2m of the surface. The
recovered rock core was logged and a suitablefoundation design completed based on thisinformation. Subsequently, additional probe holes(with no insitu testing) were carried out to assess
potential variability of the subsurface profile acrossthe site. Probe holes were extended to TC bit refusal,
which was subsequently identified to have occurred
within moderately weathered basalt.
Fig. 3 compares the “soil” samples obtained fromthe probe holes completed using the TC bit to rockcore obtained from the same depth at an
immediately adjacent borehole. The “soil” samples
obtained were comprised of low to medium strength
basalt rock fragments and, as the cored rockmass
exhibited a natural fracture spacing of approximately
100mm, the rock material was able to be penetrated
by the large (heavy) sized rig fitted with a TC bit.

‘V’ Bit Refusal
Fig. 4 compares the dataset (n = 57) of ‘V’ bitrefusal observed in all rock types compared to the
SPT ‘N’ value observed immediately adjacent torefusal. The log-logistic probability distributionfunction (PDF) was determined to best fit this datausing ‘goodness of fit’ tests; however the morefamiliar log-normal function was also determined toprovide a reasonable fit. Fig. 4 also indicates errorsthat may occur if the normal distribution is used todescribe this data (e.g. N = -62 at the 10% value).

Fig. 4

Fig. 3

SPT ‘N’ Value at depth of ‘V’ bit refusal,
overlain with fitted PDFs (n = 57)

The mean and median SPT ‘N’ value
corresponding to bit refusal of the ‘V’ bit dataset is
N = 127 and N = 80, respectively. Based on a
statistical analysis adopting a log-normal distributionfunction, and range of N = 24 to 274 is found tocover 80% of the dataset (i.e. 10% lowest and 10%
highest values omitted). This equates to a multiplierof approximately 11, however much of this range is
expected to be due to the extrapolation of the ‘N’value from a discontinued SPT – defined either as(a) >30 blows for <150mm penetration as per [7]; or(b) hammer bounce (in which a value of N = 500
being then assumed). The Australian definition of
SPT refusal (30 blows) has been discussed by [1],who demonstrated both the BS and ASTM standards
allow a larger value before test termination. It wasalso noted that the BS and ASTM standards refer tousing SPTs within rock materials, whilst theAustralian Standards refers to soil materials only.
A concentration of data between the 10th
percentile (N = 24) and the mean (N = 127) is also
shown in Fig 4. This was interpreted to suggest that‘V’ bit refusal can be expected to generally occur
within this isolated range of SPT ‘N’ values, which
would also limit the calculated multiplier to 6.

Moderately weathered basalt obtained via
TC Bit and NMLC core drilling techniques

DRILLING REFUSAL DATABASE
In order to compare material properties that canbe inferred from the level of drill bit “refusal,” data
mining of several hundred site investigation reports
has resulted in the construction of a database that
includes the rock type, insitu test results, drilling rig
type / size, and drill bit refusal within completed
boreholes. For the three (3) categories of drill bits

147

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 2 SPT N* statistics at ‘TC’ bit ‘refusal’ level– categorised by material

Tungsten Carbide (TC) Bit Refusal
The dataset (n = 112) of TC Bit refusal compared
to inferred SPT ‘N’ values is shown in Fig. 5, whilst
Table 2 presents a summary of the key statistics
relating to this dataset when the data is categorized
into various soil and rock materials. Table 2 suggests
a distinct difference in ‘N’ value statistics based onmaterial type, and suggests this data should not be
considered as a single dataset.
Specifically, it has been considered the low ‘N’values associated with the ‘residual soils’ category
may be due to premature exchange of the TC bit (i.e.
prior to bit refusal) with a rotary blade or drag bit(likely also associated with a possible change towash boring drilling techniques). Thus the ‘N’values correlated with TC bit ‘refusal’ is, in this case,thought to be associated with increasing drilling
penetration rates rather than true bit ‘refusal’ due toincreased strength of the material being penetrated.
Of the 74 data records for which the TC bit ‘refused’
within rock material (shown in Fig. 6), 72%
occurred within extremely weathered (XW) material,
14% within highly weathered (HW) material and 9%
within a moderately weathered (MW) rockmass. The
remaining 5% recorded refusal in slightly weathered(SW) to fresh (FR) rock.

Fig. 5

SPT ‘N’ Value at depth of TC bit refusal –All material types (n = 112)

Fig. 6

SPT ‘N’ Value at depth of TC bit refusal –rock materials only (n = 74)

Material
Residual
Sedimentary/
Metamorphic
Igneous
All Rock
All Materials

COV
(%)
80
103

SPT N* value (blows)
5% 10% 25% Mean
10
12
18
35
35
41
60
139

99
101
135

34
34
15

42
43
19

63
61
33

139
141
106

For the cases (n = 54) identified as indicating TC
bit ‘refusal’ within XW rock, the high RQDs
measured in rock core recovered immediately below
the level of bit ‘refusal’ also suggests that use of an
XW classification for the material was largely
incorrect. This effect has also been described by [1].
The results of ‘N’ values corresponding to ‘TC’
bit refusal are very similar for all rock origin
categories (igneous, metamorphic and sedimentary),as shown in Table 2. From this data it has beeninterpreted that the ‘TC’ bit can be typically
expected to ‘refuse’ (or provide less efficient
penetration) once rock materials exhibiting N ~ 100
are encountered (using a large drilling rig).
In limited cases (n = 15), a Point Load Index(PLI) test was completed immediately below thedepth of TC bit refusal. The distribution of PLI
results (i.e. I s(50) ) for this dataset is plotted in Fig. 7.
Using the best fit PDF (decaying exponentialfunction), the mean and median for the dataset wascalculated to be 1.5 MPa and 1.0 MPa, respectively.
For the data subset in which PLI testing wascompleted, the average N value at which ‘TC’ bitrefusal was observed was N ~ 100. Adopting UCS ~10 x I s(50) , then for this dataset UCS ~ 100 N. This issignificantly above the relationship reported by [8],whom suggested UCS ≥ 10 N. The conservatism inthis proposed relationship was highlighted by [1],who instead proposed UCS > 30 to 40 N (formedium to high strength rocks respectively) at thecoring interface. The limitations of the existing
Australian Standard relating to the completion of the
SPT to acquire the N values within this range ofrock strengths was also again highlighted.
The distribution of RQD values (%) for data inwhich RQD values were recorded immediately
below the depth of TC bit ‘refusal’ is presented inFig. 8 (n = 25). From both visual inspection and
PDF fitting, it was observed that the frequency ofdata is spread consistently across all RQD values,
and thus no obvious relationship was interpreted toexist between RQD and TC bit ‘refusal.’
Defect spacing of rock materials was similarly
examined (n = 21) at the depth of TC bit ‘refusal,’from which it was assessed the mean and median
defect spacing was 190mm and 100mm respectively.
148

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 3 Material properties at depth of drag (rotary)
bit refusal in rock (values rounded)
Drag Bit
Refusal
Level
25%
�)
Median (𝒙𝒙�)Mean (𝒙𝒙75%90%Fig. 7

Distribution of I s(50) values for tests
completed near ‘TC’ bit refusal (n = 15)

I s(50)
(MPa)

RQD
(%)

60
90
130
160
240

0.1
0.2
0.5
0.5
1.4

25
35
45
75
90

DefectSpacing
(mm)
50
100
200
370
520

Table 4 Distribution of refusal in rock at rock roller
bit refusal level (values rounded)
Rock Roller
Bit Refusal
Level
25%
�)
Median (𝒙𝒙�)Mean (𝒙𝒙75%90%Fig. 8

SPT
N*

SPT
N*

I s(50)
(MPa)

RQD
(%)

70
120
210
205
395

0.1
0.3
1.2
0.8
3.3

10
30
30
55
80

DefectSpacing
(mm)
50
100
200
210
475

value at which rock roller bit ‘refusal’ was observed
were 20% to 35% higher than those observed for any
other drill bits analyzed. The average rock strength
at bit refusal depth (I s(50) = 1.2MPa) corresponded tohigh strength rock, and was comparable to that
calculated for the TC bit (I s(50) = 1.5MPa).

RQD values near the TC bit refusal – allrock materials (n = 25)

Drag Bit (Rotary Blade) Refusal
The material properties present at the depth ofdrag bit refusal were assessed via a methodology
similar to that described for the TC bit. The resultsof basic statistics calculated for N* values(extrapolated N value), PLI values (I s(50) ), RQD andthe defect spacing are summarized in Table 3(calculated adopting a fitted log-normal PDF).
Most material properties (i.e. N* values, defectspacing and RQD) exhibited at the TC bit refusal
depth were reproduced almost identically within thedrag bit dataset. In regards to rock strength (I s(50) ),Table 3 indicates the strength at which bit refusal
occurred is distinctly lower when compared to theTC bit refusal value, by a factor to 3 to 5. This isinterpreted to suggest the TC bit would, with allother material properties being equal, penetrate
through stronger rock than the drag (rotary) drill bit.

Summary of material properties at bit refusal depth
Table 5 provides a comparative reference ofbasic statistical values of the N* and rock strength(I s(50) ) observed at the depth of bit refusal for thevarious drill bit types analyzed.
Note that as the ‘V’ bit was not associated withdrilling through rock materials, it only has SPT
values attributed. This refusal value is, for a residual
profile, interpreted to be generally associated withthe soil / XW rock interface.
Examining the median and mean values
presented in Table 5, key findings include:o SPT N* value – The rock roller refusal represents
a higher SPT value as compared to the refusal
levels of the other bits and can be expected topenetrate materials at least 1.5 times stronger
than the ‘V’ Bit.
o Rock Strength – The TC Bit and rock roller bits
appear to be able to penetrate rock materials up
to medium to high strength. The blade bit stops
in comparably weaker (low strength) rock.
o RQD – Limited relationship. Rock roller bit
penetration may be limited to materials withlower RQDs than the blade or TC bit.

Rock Roller Bit Refusal
Similar statistics were calculated for the dataset
relating to rock roller bit refusal, as presented inTable 4. These statistics show that RQD and defectspacing at the depth of bit ‘refusal’ is comparable tothat observed for the TC and rotary blade bit
databases. However, statistics relating to the SPT ‘N’149

GEOMATE- Brisbane, Nov. 19-21, 2014o Rock Defect Spacing – No difference between bit
types. All limited to an average spacing ofapproximately 200mm.

This paper has constructed a dataset of thedepth, material type and strength at which different
drilling bit types have ‘refused.’ Typical material
parameters corresponding to subsurface conditions
at drill bit ‘refusal’ level has been identified, andcorrelation between refusal and strength (N* andI s(50) ) or defect spacing have been presented. It wasalso observed that some (PSC) pile driving refusal
depths approximately correlate to TC bit refusal.
As the depth of drilling bit refusal provides
useful information for interpreting insitu material
properties and likely pile toe levels, it is thus
recommended that: (a) the drilling supervisor should
ensure different drill bits are used until bit ‘refusal’is observed; and (b) bore logs should include thisinformation, as well as details regarding the weightand size of drilling rig.

Table 5 Summary of material properties at drill bit
refusal depth

DefectSpace.
(mm)

RQD
(%)

I s(50)(MPa)

SPT N*Value

Bit Refusal
V
TC
Drag
RR
TC
Drag
RR
TC
Drag
RR
TC
Drag
RR

25%
40
60
70
70
0.4
0.1
0.1
25
25
10
45
50
50

Percentile
50%
Mean
80
125
100
140
100
125
120
210
1.0
1.5
0.2
0.6
0.3
1.2
50
50
35
45
30
30
100
230
100
200
100
200

75%
150
170
150
205
2.1
0.5
0.8
75
75
55
235
230
210

REFERENCES[1] Look, B. (2004), “Rock strength at the coring
interface”, Australian Geomechanics Journal,
Vol. 39, No. 2, pp 105 – 110.
[2] Wesley, L.D. (2010), Geotechnical engineeringin Residual Soils, John Wiley and Associates[3] Kulhawy, F H, Trautmann C H and O’Rourke T
D (1991), “The soil – rock boundary: What is it
and where is it?”, Detection of and construction
at the soil rock interface (GSP 28), Eds. W. F.
Kane and B. Amadei, ASCE, New York
[4] Kulhawy, F. H., and Phoon, K. (1993), “Drilledshaft side resistance in clay soil to rock”, Proc.
on Conf. on design and performance of deep
foundations piles and piers in soil and soft rock,
GSP No 38, ASCE, pp 172 – 183.
[5] Seidel, J. P. and Haberfield, C. M. (1995), “Theaxial capacity of pile sockets in rocks and hardsoils” Ground Engineering pp 33 – 38.
[6] Gannon, J.A., Masterton, G.G., Wallace, W.A.
& Wood, D.M. 1999. Piled Foundation in
Weak Rock (CIRIA Report No.181). UK, 80p[7] AS 1289 6.3.1 (1997), “Determination of thepenetration resistance of a soil – Standard
Penetration Test”, Australian Standards[8] Clayton, C. R. I. (1995), “The standard
penetration Test (SPT) methods and use”,
CIRIA Report 143.
[9] Adams, B., Look B. and Gallage, C. (2010),
Assessment of pile driving refusal using thestandard penetration test, Proc. of the 11th
International Association of Engineering
Geologists Congress, Auckland, New Zealand,
pp 2641 - 2648
[10] Lacey, D., Kemp, A., and Sundaram, M. (2012)“Use of drilling rig instrumentation to assess
subsurface profile and material characteristics
during piling operations,” Proc. of 11th ANZ
Conference on Geomechanics, Melbourne,
Victoria, Australia, pp. 1316 – 1321

PILE FOUNDING LEVELS
It has been shown by [9] that likely pile refusalof bridge PSC piles (450mm to 550mm diameter, fora set less than 5mm per blow) occurs at N* ~ 100
and 150 for sandstones and shales, respectively.
These N* values corresponds approximately to thetypical values of TC bit refusal observed within
sedimentary rocks (n = 51, 𝑥𝑥� = 96, 𝑥𝑥̅ = 139), andthus driven pile refusal can be inferred to typicallycorrespond to TC bit refusal. Typical rock properties
for TC bit refusal depth, and thus attributable todriven pile refusal level, were included in Table 5.
In relation to bored piles, [10] demonstrated how
the penetration rate for bored piles being constructedwithin a residual / XW rock profile, and drilling rig
properties (e.g. torque, pressure, RPM of auger)
could be used to determine site- and equipmentspecific correlations with rock strength and type.
The assessment completed in [10] was theconstruction phase equivalent of the material
parameter study detailed within this paper.
CONCLUSIONS
The interface between soil and weathered rockis not well defined, especially for residual soil
profiles. In residual soils there is often a recorded
disconnect in material properties across the soil-rockinterface, often resulting in an instantaneous jump instrength or weathering properties. As identified
herein, such jumps are likely attributable to drilling
technique rather than an insitu condition.
150

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SPATIAL AND TEMPORAL VARIABILITY IN A RESIDUAL SOIL
PROFILE
Daniel Mellish1, David Lacey2, 3, Burt Look4, and Chaminda Gallage1
Queensland University of Technology, Australia; 2Jacobs, Australia 3The University of Queensland,
Australia; 4Foundation Specialists Group1

ABSTRACT
It is well understood that there is variation inherent in all testing techniques, and that all soil and rockmaterials also contain some degree of natural variability. Less consideration is normally given to variation
associated with natural material heterogeneity within a site, or the relative condition of the material at the time oftesting. This paper assesses the impact of spatial and temporal variability upon repeated insitu testing of aresidual soil and rock profile present within a single residential site over a full calendar year, and thus range ofseasonal conditions. From this repeated testing, the magnitude of spatial and temporal variation due to seasonal
conditions has demonstrated that, depending on the selected location and moisture content of the subsurface atthe time of testing, up to a 35% variation within the test results can be expected. The results have also
demonstrated that the completed insitu test technique has a similarly large measurement and inherent variability
error and, for the investigated site, with up to a 60% variation in normalised results being observed. From theseresults, it is recommended that the frequency and timing of insitu tests should be considered when deriving
geotechnical design parameters from a limited data set.
Keywords: Inherent soil variability, measurement error, temporal variability, coefficient of variation, Dynamic
Cone Penetrometer, Moisture Content,

a single period of onsite work, and laboratory testing
conducted upon representative samples taken during
this limited duration of site visitation, all results areindicative of the material conditions at the single
time of material sampling. Accordingly, whenmaterial parameters are determined for LSD,
although spatial variability across the site andvariation in results due to errors within thecompleted tests can generally be accounted for bysuitable geological and analytical models
respectively, no allowance for any temporalvariability of results is routinely applied.
This paper summarises a field study completed toquantify the variation within the results of an insitu
testing program repeated upon a single site over a
period of 12 months, and the potential influence thatthe time of site testing may have on typical design
parameters. Both the temporal and spatial variabilityof a simple insitu penetration test has been
investigated by the repeated testing of a single siteover a full cycle of seasons (and thus soil moisture
content variation). This paper incorporates data
presented by [4] as well as additional data collected
to extend the duration of the study.

INTRODUCTION
Residual soil materials are known to beheterogeneous, and all insitu and laboratory tests are
accepted to contain some aspect of uncertainty(equipment error; operator, spatial or temporalvariation) associated with them [1]. In Limit State
Design (LSD) allowances are made for this inherent
variation and measurement error when determining
design parameters or characteristic values from adataset of soil test results (insitu and/or laboratory
test results), by the selection of a (generally)
conservative value for adoption in design. For
example, the recommendation of [2] is in theabsence of specific local test data, a characteristic
value determined by statistical methods should
produce a design parameter such that “a calculated
probability of a worse value governing theoccurrence of the limit state under consideration is
not greater than 5%”.
It is also accepted that the results of material
testing can be affected by moisture content [3].
Accordingly, the time of year that an insitu test iscompleted or a material sample obtained will
influence test results, as the moisture content of the
sub-surface varies based on recent climactic
conditions. This is especially true of the near-surfaceand “active zone,” the region defined as the depth towhich seasonal changes in moisture content occur.
As site investigations are often completed within

TEST EQUIPMENT
The insitu test repeatedly utilised for this study
was the Dynamic Cone Penetrometer (DCP), a
simple, portable and low cost tool commonly used as
151

GEOMATE- Brisbane, Nov. 19-21, 2014

an indicator of strength and variation of the groundprofile. An Australian Standard test method [5] wasadopted for all tests completed at the test site.
The results, denoted Penetration Resistance (PR),produced by repeated hammer blows (weight drops)
during the DCP test are reported as either: (a) the
number of blows required to produce a rod
penetration of a standard length; or (b) the length ofrod penetration produced per single hammer blow.
DCP test results are, via generic correlations, used
to infer relative density / consistency categories or toderive material parameters (e.g. shear strength,
California Bearing Ratio (CBR) or modulus values).
Differences exist between the Australian [5]standard test equipment and that specified by othercountries [6]. Specifically, the hammer weight, drop
height and the dimensions of penetration cone mayvary. However, as the energy imparted upon the rod
is approximately equal, correlations derived byresults of completed tests in any locality are often
adopted by others without modification. Existing
publications suggest that this assumption may [7], or
may not [8], be appropriate.

Fig. 1

Inferred weathered profile and expected“active” zone of site (after [9, 10])

Fig. 2

Observed (solid) and median (dotted)
monthly rainfall values and test intervals

SITE DETAILSThe site of the repeated testing was a residentialsite located in Chapel Hill, a suburb of Brisbane,
Australia. The subsurface was comprised of aresidual soil profile transitioning into weathered
phyllite rock by a depth of approximately 1.8m.
Particle Size Distribution (PSD) tests werecompleted upon the residual soil materials at depths
of 0.25m, 0.75m and 1.25m, and a USC
classification of Clayey Sand with Gravel wasderived based on the resultant grading curves andAtterberg Limits. The completed PSD tests also
indicated an 8 to 12% increase in gravel content
across the depth profile analysed (i.e. higher gravel
content with increased depth). This is typical of aresidual profile, as indicatively shown in Fig. 1.
Fines were evaluated to be of medium plasticity,and the site location inferred an “active” zone ofapproximately 1.5m was expected to exist, as
indicated by the applicable Australian Standard [9].

each investigation phase, as identified in Fig. 2,
multiple DCP tests were completed at each of thethree (3) spatially discrete locations. By theassessment of the difference between the multiple
DCPs completed at each sub-site and comparing theresultant averaged DCP profiles between each subsite, the inherent variability of the soil, measurement
error associated with the DCP test, and spatial
variability across the test site was assessed.
Similarly, by comparison of the DCP tests results
obtained for each sub-site at each phase ofinvestigation, and thus the change within thematerial state the period between tests, the temporalvariability of the material was assessed.
Insitu moisture contents were determined for the
initial 1.2 m profile within each sub-site, and thus
the change in moisture content could also becompared to the variation in produced DCP profiles.
This allowed the definition of the depth of the“active” zone within the site, and the variation of
DCP penetration rate with field moisture content.

STUDY METHODOLOGY
The completed study involved repeating astandard suite of insitu testing and sampling of thesite five (5) times over a full calendar year. The
selection of 12 months as the duration of the study
was to enable a test variation over a full seasonal
cycle to be observed.
Each period of testing involved the determinationof site conditions and spatial variation across the site
via repeated DCP testing. Three (3) locations (subsites A, B and C) within the Chapel Hill site were
defined, offset from each other by 12 to 15 m. At

RESULTSFor each period of testing, a typical DCP profile
was produced at each sub-site by averaging, bydepth, the PR values for all tests completed (n = 1 to152

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 1 Coefficient of Variation (COV) of DCP profiles within identified material units, top 1.5m of subsurface

ID

Test Date

1
2
3
4
5

14 Apr. 201303 Aug. 2013
21 Sept. 201327 Dec. 201308 Feb. 2014

Co-efficient of Variation (COV) of each material unit (%), top 1.5m material profile
Site A
Site B
Site C
Range
Average
Range
Average
Range
Average
17 – 43
32
0 – 4627
20 – 4724
17 – 4726
18 – 4933
30 – 7134
22 – 30
26
12 – 30
23
6 – 1712
23 – 3730
23 – 3929
12 – 3123
19 – 40
31
28 – 2929
24 – 37
32
profiles produced at each sub-site were compared byobserved PR value at regular (0.1m) depth
increments, and combined to construct a single DCP
profile representative of the full site for each date of
test, as shown in Fig. 4.
After controlling for the variation in results due totesting / inherent error, as described previously, thespatial variability of the site observed at each test
period was quantified by the calculation of residual
COV values. Spatial variability (i.e. COV values
above the variability associated with equipment andnatural heterogeneity error) was observed in 59% of
the results (44 of 75 records), with basic statistics ofthe quantified spatial variability for each test phasesummarised in Table 2.
Within the normalised spatial variation calculated,values of up to 70% were observed, with a medianand average of 4.5% and 9.5% respectively. Via
inspection of the data and from formal assessment
by linear regression no significant relationshipbetween the spatial variability magnitude and depth
was identified.
Accordingly, it is recommended that both inherent
� = 27.4%) and spatial variation ( 𝒙𝒙�=variability ( 𝒙𝒙9.5%) values should be assessed, and accounted for,equally across the full length of the DCP profile.
The static COV calculated by this study (~37%) issimilar to DCP repeatability reported by others [7].

4). As shown in Fig. 3, a PR versus depth profile
was produced, along with an estimate of thedeviation from these values. This variation is shownas the maximum and minimum value envelope
overlaid upon the averaged PR profile. Based on the
average PR value, the encountered subsurface
profile was also categorised into depth intervals ofsimilar consistency or relative density.
Inherent Variability and Measurement Error
An assessment of normalised variation displayed
within each sub-site’s typical DCP profile was
made, based on the calculation of a Coefficient of
Variation (COV) value both for each individually
identified material unit and averaged over all
identified material units present within each sub-site.
The COV values, as summarised in Table 1, isinterpreted to present a combination of both theinherent heterogeneity of the soil material being
tested and the measurement error associated with the
DCP test methodology. By inspection of Table 1, it
can be seen that the average COV encountered forcomparative profiles is 27.4% across the full study
length, and varies (with the exception of a single
value) between 23% and 34%.
Spatial Variation
Spatial variability was assessed based oncomparison of the results collected across the site ateach of the five (5) testing periods. Average DCP

Temporal Variation

Fig. 3Fig. 4

Simple comparison between the data available for

Typical DCP plot showing averaged profileand range of observed values versus depth.
153

Plot showing averaged DCP profiles (fortests completed in December 2013)

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 2 Summary of spatial variation observed
across site, by test period
Test
ID
1
2
3
4
5
ALL

(refer Fig. 1), the temporal variation observed would
also be expected to decrease with depth.
Total Observed Variation

Normalised Spatial Variation (%)
Range
Average
Median0.0 – 69.9
21.1
19.5
0.0 – 23.7
6.1
0.0
0.0 – 25.1
8.0
7.7
0.0 – 23.3
6.4
0.0
0.0 – 19.0
5.8
0.0
0.0 – 69.9
9.5
4.5

Combining the three (3) isolated sources ofvariation, an estimate of total variation profiled
against the initial 1.5m subsurface interval has been
produced (Fig. 6). This indicates the magnitude of
total variation varies from up to approximately 60%
� = 54%), before decaying towithin the top 0.50m (𝒙𝒙oscillate about a lower bound value below depths of� = 41%).
1.0m (𝒙𝒙These derived values also fall within the range ofvariation associated with another commonly
employed test, the Standard Penetration Test (SPT),
as detailed by [1]. This previous study found therange of total variation of SPT testing in sand
� = 54%).
materials was 19 to 62% (𝒙𝒙each sub-site produced a range and magnitude ofvariation observed across the full year of site testing,and produced a value of temporal variation for each
0.1m depth interval. The profile of temporalvariation produced for each sub-site are shown in
Fig. 5, and inspection of these profiles indicate thelargest temporal variation is associated at theexisting ground surface. The magnitude of temporalvariation decays from above 45% at the groundsurface to 0% at a depth of 1.0m. Below this depth
the temporal variation appears to stabilise about anaverage value, with sub-site ‘A’ indicating a higher
� = 26%)
temporal variation at depths below 1.0m (𝒙𝒙� = 3 to 11%).
than the other two (2) sub-sites (𝒙𝒙Linear regression analyses indicate the strongest
relationship, assessed by correlation co-efficient (R2)values, consistently exists when the data is isolated
from the ground surface to depths of 0.8m to 1.0m.
This suggests that data below such depths does not
display the same depth related relationship, andindicates the “active” zone of the investigated site islimited to a depth of approximately 1.0 m.
The observed general decrease in temporalvariation over a specific depth interval extending
from the ground surface is interpreted to be due tothe variation in the moisture content present within
this depth interval over the duration of the study. As
moisture content influences DCP results, and thelargest moisture content variation would be expected
to occur at the surface level and decrease with depth

Fig. 50-0.2

ept ( )

-0.4
-0.6

= Total Observed
Variation= Measurement Error /Inherent Variation

-0.8
-1
-1.2

= Spatial Variation-1.4= Temporal Variation
0

10

20

30

40

50

60

70

80

90

100

Total Observed Variation (%)

Fig. 6

Total observed variation with DCP results,
categorised by source of variation and error

CORRELATION WITH SOIL
CONTENT AND RAINFALL

MOISTURE

Disturbed samples were obtained and the inistu
moisture content determined (n = 49) for a depth
range of between 0.25m to 1.65m. The completed
testing allowed the construction of a soil moisture
content profile for each averaged DCP profile. The
average and range profiles produced for the
combined (full site) dataset is shown in Fig. 7, withthe results calculated for the individual sub-sites
summarised in Table 3.
Although the average field moisture content wasobserved to vary across the site, the largest range ofvariation over the 12 month study were consistently
identified to exist at the surface, and then decrease
with depth. It is also noted that within sub-site A, themoisture content increased with depth, which has
been interpreted to be due to a temporal groundwaterlevel located at 1.45m depth. However, at all subsites the minimum range in results was observed toexist at the 1.0m depth, again suggesting the “active”
zone is located above this level. On average, themagnitude of moisture content variation at 1.0m

Temporal variation within comparable DCP
profiles over study duration
154

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 3 Standardised range, average and COV of insitu moisture content, top 1.0m of subsurface
Depth
(m)
0.25
0.50
0.75
1.00

Fig. 7Range
8.7 – 23.3
11.3 – 19.4
11.3 – 19.9
17.3 – 23.4

Site A
Mean
14.7
14.5
15.4
20.1

COV
41
23
20
12

Moisture Content (%)
Site B
Range
Mean
COV
8.8 – 20.6
15.3
33
11.0 – 17.6
14.7
17
8.4 – 14.6
12.8
20
10.8 – 12.3
11.5
5

depth was 40% that observed at the sample taken
closest to the surface (0.25m).
Correlation between the soil moisture content
variation and the change in the PR results between
consecutive test periods was completed to in order todemonstrate the relationship between the two (2)measured parameters. A statistically significant (n =45, p < .001) linear relationship was determined forthe difference in all results, as detailed in Eq. 1.
(1)

Where, for the interval between repeated tests:
PRV = PR change (blows / 100mm penetration)
MCV = Moisture content change (%)
By isolation of the PR and moisture content
values observed at each 0.25m depth increment,variations of the PVR:MCV linear multiplier and theTable 4 Correlations between the observed moisture
content variation and PR variation recorded
during consecutive testing periods
Depth
(m)
0.25
0.50
0.75
1.00
ALL

Samplesize (n)
12
12
12
9
45

Relationship between
PR and MC variation
PRV = -0.30 MCV
PRV = -0.56 MCV
PRV = -0.31 MCV
PRV = -0.49 MCV
PRV = -0.39 MCV

Site C
Mean
18.1
12.6
9.6
8.8

COV
9
22
33
23

strength of the relationship (R2) were observed, assummarised in Table 4. The strongest relationshipbetween moisture content and PR values occurred
nearest to the surface (0.25m depth, R2 = 0.5) withthe calculated R2 generally decreasing with depth.
Combining Eq. 1 and the annual range ofmoisture content variation experienced over the2013 / 14 testing period (refer Fig. 7), the expected
influence that moisture content has upon the DCP
PR rate, and thus the variation of PR values based on
the time of testing, has been estimated. This analyses
indicated that the moisture content variation within
the subsurface materials would be expected to
produce an annual variation in DCP PR values of 4hammer blows at the ground surface, and 1 to 2
hammer blows at the base of the “active” zone.
Comparing the calculated annual variation in PR
values due to moisture content variation andcalculating this range as a percentage of the“average” DCP PR profile calculated for the site, theequivalent percentage variation in PR result was also
obtained. This indicated that the moisture content
variation would result in ±25% variation about themean PR value for depths of up to 0.5m, and ±10%variation in PR values over the remainder of the“active” zone. Such values approximately replicate
the temporal variation magnitudes (refer Fig. 5).
As shown in Fig. 8, the total rainfall in the 3month period preceding each suite of DCP testing[11] was compared to the proportion of averaged PR
that indicated “dense” or above (PR ≥ 5) materials.
A distinct increase in the proportion of thesubsurface that reported such values occurs as therainfall magnitude decreases and the subsurface isallowed to dry. Similarly, the profile showing thepercentage of the top 1.5m subsurface profile
interpreted to be “medium dense” or below (PR < 5)largely reflects the shape of the profile of the total
rainfall of the preceding three (3) months.

Moisture content and range of variation
observed over 12 month study duration

PRV (blows/100mm) = –0.39 x MCV (%)

Range
16.5 – 21.0
9.5 – 16.9
5.7 – 12.9
6.5 – 10.9

R2

IMPLICATIONS FOR DESIGN

0.50
0.24
0.11
0.43
0.25

CBR values are commonly derived from theresults of DCP testing, and CBR values are thencommonly incorporated into design as the basis forthe estimate of a deformation parameter. Thus, thevariation defined for the DCP PR values would also
influence any correlated CBR values.
155

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 8approximately the static variation value (36.9%) at
depths below of 1.0m.
Generic correlation between PR and insitu CBRvalues indicated the constant (36.9%) PR variation
would result in a range of ±26% about the CBR
calculated from the mean PR value. Incorporating
the maximum temporal variation (22%) would
increase the resultant CBR range to ±46%.
Accordingly, the results of DCP values should not
be relied on for high accuracy, and the results of a
DCP test should be viewed as representative of thesite under the conditions at the time of testing only.
Consideration for the season of testing and likely
moisture content of the “active” zone of soil within
annual variation should be considered when deriving
characteristic parameters for geotechnical design.

Proportions of subsurface classified tointervals of relative densities compared to 3
month preceding rainfall total

By adoption of a generic DCP to CBR value
correlation [12], the resultant range of CBR values
produced by the derived variation associated withaveraged PR values was calculated. The CBR range
calculated for such values are summarised in Table 4,
and indicate that for the one year that the site wasmonitored, insitu testing would have yielded
resultant CBR values that would have displayed avariation of between ±46% (at ground surface) and±28% (at 1.0m depth) about the average CBR value.

REFERENCES[1] Phoon, K.K. and Kulhawy, F.H. (1999).
“Characterisation of geotechnical uncertainty”,
Canadian Geotechnical Journal, Vol. 36 (4)[2] EN 1997-1: 2004. Eurocode 7: Geotechnicaldesign. Part 1: General rules. CEN.
[3] Das, B.M. (2011). Geotechnical Engineering
Handbook, J. Ross Publishing, Ft. Lauderdale[4] Mellish, D. (2013). Temporal and spatial
variation of moisture content and its effect on
the strength characteristics of soil, B. Eng.
Thesis, Queensland University of Technology[5] AS 1289 6.3.2 (1997). “Determination of thepenetration resistance of a soil – 9kg Cone
Penetrometer test”, Australian Standards[6] ASTM D6951 (2009). “Standard Test Method
for Use of the Dynamic Cone Penetrometer in
Shallow Pavement Applications”[7] Smith, R.B. and Pratt, D.N. (1983), “A fieldstudy of in-situ Californian Bearing Ratio
Dynamic Cone Penetrometer testing for roadsubgrade investigations”, Australian Road
Research, Vol. 13 (4)[8] Narendranathan,N.,
Archer,S.
andNarendaranathan, G. (2012). “Earthwork
practices in civil & mining industries andadvances in earthworks”, Int. Conf. on Ground
Improvement and Ground Control, Wollongong,
Australia, 30 Oct. – 2 Nov.
[9] AS 2870 (2000).
“Residential Slabs andFootings”, Australian Standards[10] Little,
A.L.
(1969).
The
engineeringclassification of residual soils, 7th Int. Conf. on
Soil Mechanics and Foundation Engineering(ISSMFE), Mexico, Vol. 1, pp 1 – 10
[11] Bureau of Meteorology (2014). Historical
Rainfall Observations, www.bom.gov.au/climate[12] Queensland Government (2010). Test Method
Q114B – Insitu California Bearing Ratio(Dynamic Cone Penetrometer), Materials
Testing Manual

Table 4 Insitu CBR variation based on depth fromsurface and total observed PR variation
Depth
(m)
0.00
0.25
0.50
0.75
1.00

PR Value(All sub-sites, all tests)
Mean Total Var. (%)
3.2
58
4.2
52
5.5
55
6.2
44
7.4
39

Insitu CBR
(%)
Min.
Max.
2.1
5.9
3.4
8.0
4.4
11.0
12.6
6.5
15.5
8.7

SUMMARY AND CONCLUSION
A residential site in suburban Brisbane wasmonitored by repeated DCP testing over a twelve
month period. The magnitude of various sources oftest error and result variation associated with the
DCP test has been derived from analysis of therecorded PR values (blows / 100mm rod penetration).
Inherent material variability and measurement
error was calculated to average 27.4% and sitespecific spatial variation was derived to average
9.5%. Thus, for any DCP completed at the site, aconstant average variation magnitude of 36.9% wasdemonstrated to exist for any individual PR value.
The “active” zone was found to be approximately
1.0m deep at the site. An average temporal variationof 22% was observed to occur between the groundsurface and a depth of 0.5m. Variation of PR values
totaled 58% at the surface before decreasing to156

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

INTERACTION ANALYSIS FOR OIL STORAGE TANK ON MARINE
CLAY
Pallavi Ravishankar B.1 and Neelima Satyam D.2
Research Scholar, Assistant Professor, Geotechnical Engineering Laboratory, Earthquake Engineering
Research Center, International Institute of Information Technology Hyderabad, INDIA

1

2

ABSTRACTThe engineering behavior of marine clay is very different than that of the moist and dry clay becauseof its structural and mineral composition [1]. Marine structure is subjected to the waves which create a cyclic
stresses inside the soil mass [2]. In this paper a cylindrical reinforced cement concrete tank with diameter 100m
and 40 m height founded on soft marine clay of undrained shear strength of 10 kPa is considered for the analysis.
The huge pile group is modeled by equivalent pier method and interaction factor method for the full and empty
loading conditions. Settlement including the soil pile interaction has been estimated for both the cases mentioned
above for different pile configuration including pile length, diameter and spacing of piles in a group. It has been
observed that the spacing of the piles plays a vital role in estimating the settlements and stresses. With thecomparison of the equivalent pier method (EPM) and interaction factor method (IFM) for settlement estimation,
IFM is found to be more suitable for interaction analysis to achieve the safety of the tank.
Keywords: Soil pile interaction, Oil storage tank, Settlement analysis, Pile foundation, Marine clay

There are a number of approaches commonly
adopted for the estimation of the settlement of pilegroups which employ the concept of interaction
factors and the principle of superposition [20]. Few
methods estimate the group settlement bymodifying the single pile load-settlement curve, totake account of group interaction effects.
Some of the methods are briefly explained in thissection.

INTRODUCTION
Due to an increase in the use of marine
recourses like petroleum products, biologicalproducts etc. a coastal activities are increased
tremendously. Due to this there is a huge necessity
to build marine structures like offshore platforms,
storage structures like fuel storage tanks, temporary
halt structures, etc. Such offshore structuresconsidered under heavy structures and give much
impact on the soft clay settlement which affects the
structural stability. Hence settlement analysis isneeded to be performed for such type of structures.
Originally very soft clay in sea bed or onshore clay
called as marine clay, has very poor shear strengthand shows shrinkage and swelling properties due toits structural arrangement and the minerals
compositions like montmorillonite, chlorite,kaolinite and illite and non-mineral traces likequartz and feldspar. Along with these minerals andnon-mineral compositions, marine clay consist oforganic matter (proportion is very high.
In the analysis, the settlement in the soil mass isestimated for the exact prediction of the responseof the structure along with the soil behavior. In
offshore structures the foundation is deeply
embedded to hard strata, thus pile experiences thefluid foundation interaction as well as soil
foundation interaction for the given loading
conditions throughout the life span of the structure.
It is now well recognized that the settlement of apile group can differ significantly from that of asingle pile at the same average load level.

1.

2.

3.

4.

157

The settlement ratio method: In this method
the settlement of a single pile at the averageload level is multiplied by a group settlement
ratio Rs, which reflects the effects of groupinteraction.
The equivalent raft method: In this method thepile group is represented by equivalent raftacting at some characteristic depth along thepiles.
The equivalent pier method: In this method thepile group is represented by a pier containing
the piles and the soil between them. The pier istreated as a single pile of equivalent stiffness inorder to compute the average settlement of thegroup.
The Interaction Factor Method: In this method
the settlement for one pile (reference pile) in
the group is estimated and considering theinteraction factor the settlement of the otherpiles in the group is calculated. The algebraic
sum of the settlement value of all piles gives
the settlement of the group.

GEOMATE- Brisbane, Nov. 19-21, 2014

5.

Numerical methods: Different numerical
techniques such as finite element method andthe finite difference method have been used tofind out the group settlement. While earlier
work employed two-dimensional analyses, it is
now less uncommon for full three-dimensional
analyses to be employed [7].

In this research paper the equivalent pier method
and the interaction factor method are used toperform a comparative analysis for estimating thesettlement of the pile group including soil pileinteraction.
Piles

Details of the storage tank considered for the
study

Fig. 2 Geometry of storage tank.

Large ground storage is considered to be located inwestern part of India. A settlement analysis
considering the soil pile interaction of marine
deposits under static loading is carried out
including the wind and gravity loading
combination for the full and empty oil in the tank.
The concrete oil storage tank of diameter 100m
and height including free board is 40 m is
supported by a initial set of pile foundation ofdiameter 0.4 m. Initially at a first iteration a pile isconsidered to be spaced on 3D to 6D and typicallength of the pile is 10 m. General layout of thepile is explained in the Figure 1.

The tank is constructed to store oil of specificgravity 7.6 kN/m3. Large ground storage is
supported by a local marine clay deposits. Table 1
explains the engineering properties local deposit.
Table 1 Soil properties considered for analysis [1]Parameter
Unit Wt.
Moisture Content
Shear Strength
Poisson’s Ratio

Unit
kN/m3
%
kPa

Value
16
38
10
0.35

The concrete grade is taken as M-30 for both tankand foundation system with the rebar
reinforcement of Fe-415 steel grade.

Piles

ANALYSIS
Equivalent pier method (EPM)
Paulos and Davis (1980) proposed an Equivalent
Pier method for heavy and large superstructures
where a large pile group needs to analyze. Few
researchers adopted a methodology of EPM to findout the settlement analysis for the huge pile group
[25].

Lp

Fig. 1 General layout of the initial arrangement of
the piles in a group.
Pile is provided with a uniformly thick pile cap of
thickness 0.5 m. Fig. 2 explains the basic model
geometry of the circular tank.

Eeq, Aeq

Fig. 3 Concept of equivalent pier method.
In this method the pile groups act as a whole pier tosimplify the procedure for estimating the settlementof pile groups which equals that of single pile bymeans of load-transfer functions. The diameter of158

GEOMATE- Brisbane, Nov. 19-21, 2014

series of nonlinear springs along pile shaft or pilebottom to resist the vertical load Pi at the pile top,
is taken out to be analyzed separately, as shown in
Fig. 4. The stiffness of spring at the pile bottom canbe conveniently expressed using the following
equation suggested [12].

the equivalent pier is given by the following
equation
𝐷𝐷𝐷𝐷𝐷𝐷 = 2�

𝐴𝐴𝐴𝐴
𝜋𝜋

(1)

Where, A g is the plan area of pile group.
The Interaction Factor Method

𝐤𝐤 = 𝟒𝟒 ∗For pile groups one of the common means ofanalyzing pile group behavior is via the interaction
factor method [20]. In this method, referring to Fig.
3, the settlement wi of a pile i within a group of npiles is given as follows:
𝑾𝑾𝑾𝑾 = ∑𝒏𝒏𝒋𝒋=𝟏𝟏 𝑷𝑷𝑷𝑷𝑷𝑷 ∗ 𝑺𝑺𝟏𝟏 ∗ 𝜶𝜶𝜶𝜶𝜶𝜶(4)Where, G is the shear modulus and µ is the
poison’s ratio of soil.
Pi(2)

where,
Pav = average load on a pile within the group;
S1= settlement of a single pile under unit load
(i.e., the pile flexibility);
αij = interaction factor for pile i due to any otherpile j within the group, corresponding to thespacing sij between piles i and j, can be written foreach pile in the group, thus giving a total of nequations, which together with the equilibrium
equation solved for the a rigid (non-rotating) pilecap, in which case all piles settle equally. In thiscase, there will be a uniform settlement but a nonuniform distribution of load in the piles. Generally
the interaction factors (αij) is computed fromboundary element analysis and plotted in graphicalform. In numerical analysis closed-form
expressions are used for the estimation ofinteraction factors which provided the ease inprediction of group settlement behavior using
numerical techniques [3]. The expression for theinteraction factor is given as follows.

α = A(s/d)^B

𝑮𝑮
𝝅𝝅𝝅𝝅(𝟏𝟏−µ𝟐𝟐 )kFig. 4 Equivalent/Single pile with soil represented
as a spring for soil pile interaction analysis [25].
Pile interaction
In this study the main focus in given on thevertically-loaded pile groups consisting of n
identical piles with the same length L, diameter d,pile space S, and elastic modulus E P embedded in
the homogenous soft soil. Generally, the resistanceof the surrounding soils at the pile/soil interface, i.e.
shaft frictional force named as τz, is mobilized oncethe displacement of the piles occurs. The
displacement of pile groups at a given depth isdifferent from that of single pile under the sameload due to the fact that the reinforcing effectcaused by the interaction between someneighboring piles confines the displacement of soils
along piles. Therefore, it is necessary to consider
the interaction between individual piles incalculating the settlement of pile groups. The soils
are assumed to be a series of nonlinear springs
attached along the pile shaft to simulate thebehaviors of soils subjected to shaft frictional force.
Obviously, the stiffness of springs, denoted as theratio of the shaft frictional force to the displacementof soils, is relative to the interaction between
individual piles in pile group.
According to the formulation [25] to estimate theshear- deformation mechanism of surrounding soils(3)

where, A = 0.57 to 0.98
B = –0.60 to –1.20.
Load Transfer function for individual pile in pile
group
The analysis method [13], proposed originally by
Coyle Reese and O’Neil [12], is an efficient method
to predict the load settlement relationship for single
piles subjected to vertical load for its simplicity andcapability of incorporating the nonlinear behaviorof soils. However, due to the emission of influenceof pile-to-pile interaction on the deformation of thesoil surrounding the pile, it is rather difficult to beextended to pile-group analysis. In this work, aload-transfer function is developed based on theanalysis of the aforementioned interaction between
individual piles in pile group. Pile i , supported by a
159

GEOMATE- Brisbane, Nov. 19-21, 2014

around piles subjected to the shaft frictional forceτiz, the displacement of a point of soils is expressed
as𝒅𝒅𝒅𝒅= 𝑷𝑷𝑷𝑷(𝒚𝒚)/(𝑬𝑬𝒑𝒑 𝐀𝐀𝒑𝒑 )𝒅𝒅𝒅𝒅

RESULTS AND DISCUSSIONSThe settlement analysis is carried out for the hugewater tank of diameter 100m and height 40m
founded on the marine clay of very less shear
strength using Equivalent Pier Method (EPM) andInteraction Factor Method (IFM) for different pileconfiguration of diameter, length and spacing
considering the soil pile interaction including thelinear spring with spring constant of equal to thesoil coefficient. Fig 6a and Fig 6b shows thegeneral settlement profile for the working loadcondition at the bottom node of the Equivalent pilefor full and empty conditions respectively.

(5)

Considering the interaction between soil and pileand pile to pile in the group the interaction factor is
proposed as

𝑰𝑰𝑰𝑰 =

𝑬𝑬𝒔𝒔

(6)

𝑬𝑬𝐩𝐩

Hence the Modulus of the equivalent pier ismodified as If *Eq considering the fact that the soil
has been entrapped between the piles in the group.
FINITE ELEMENT MODELLING
The tank is modeled using Finite element software
SAP 2000 using circular wall as a shell element andslab as a plate element and piles as a 1-D element
along with the soil modeled as a linear spring tocapture the realistic soil pile interaction scenario(Fig. 5).

Fig. 6a.Settlement for tank by EPM (full condition).

(a)

(b)

Fig. 5 Details of the finite element model for slab(a) and circular wall (b).
The analysis is carried out for considering single
pile which takes load considering the group actionand equivalent pier representing the pile group. The
loading considered in analysis for is done for both
empty and full condition of the tank.
In this method it is needed to consider a correction
factor for the equivalent pier as soil trapped
between the piles reduces the overall stiffness ofthe pile group. The correction in the equivalent
stiffness of the soil group is calculated. Theinteraction analysis is carried out for linear static
condition and the results are compared with theanalysis case which excludes the interaction for all
pile configuration. The parametric study is carriedout for the different pile to pile spacing, pile
diameters, pile length and the different D/L(diameter to side length ratio) ratio for the above
mentioned conditions of the tank.

Fig.6b. Settlement for tank by EPM (empty
condition).
The maximum settlement is calculated withinteraction method considering the interaction
between pile to pile using Eq. 2. The settlement foreach pile is calculated manually considering thecentral pile as a reference pile and the maximum
settlement for a pile group is estimated by
performing a numerical summation of all settlement
values obtained analytically. The settlement
obtained by EPM and IFM is compared and thedifference is shown in Fig. 7 for both empty andfull loading conditions. The comparison for the160GEOMATE- Brisbane, Nov. 19-21, 2014

analysis.
6. The % deviation in settlement with EPM andIFM method is found to be more in the fullload condition that the empty load conditionof the tank which proves that the interaction
between soil pile and pile to pile is more as
the loading on the structure increases from thegravity load condition.

maximum settlement has been carried out for both
empty and full loading conditions.

REFERENCES
[1]

[2]

Fig.7 Percentage deviation in maximum settlement
for critical load condition for EPM and IFM.
CONCLUSSIONSThe present study has drawn the following
conclusions.

[3]

1.

[4]

The Maximum settlement of the huge fueltank for empty and full both conditions arefound to be permissible range.
2. The settlement is found to be less for the pileconfiguration with D/L ratio 0.02 and forother ratios settlement is found to 20% more
for the empty loading conditions where as
D/L = 0.04 is proves to be an good choice as
it gives minimum settlement for the fullloading condition with EPM and IFM
methods. Thus the pile configuration diameter
0.4 m, total length 10 m and spacing 1.6 m isfound to be a good combination for the least
settlement criteria.
3. Equivalent pier method proves to be simple toget the settlement of the huge fuel tank but
interaction is need to explicitly provided withthe springs which is a the lengthy methodwith respect to the calculation.
4. Interaction factor method accounts forinteraction between soil and pile with springs
and the pile to pile interaction with theformulation of the interaction factors thus thismethod is found to be more precise as in pilegroup pile to pile interaction is one of theimportant criteria.
5. The settlement values was found to be moreby the interaction factor method (IFM) as
compared to the equivalent pile (EPM)
method which leads to fact that pile to pileinteraction also plays a vital role in settlement

[5]

[6]

[7]

[8]

[9]

161

Basackand
Purkayastha,“Engineering
properties of Marine Clays from the eastern
coast of India”, Journal of Engineering andTechnology Research,Vol.1(6), September
2009, pp.109-114.
S.S. Sharma and M. Fahey, “Cyclic
deformation characteristics of cemented
calcareous soil”, Deformation charecteristics
of Geomaterials, 2nd ed., 2004, NRC
Research Press, ISBN 905809604 1.
Mandolini, A. and Viggiani, C, “Settlementof piled foundations”, Géotechnique, Vol.47
1997, pp.791-816.
Reese, L.C. and O’Neill, M.W., (1988).
“Drilled shafts: construction procedures anddesign methods”, Publication No. FHWAH1-88-042.
Peaker, K.R.(1984). “Lakeview tower: a casehistory of foundation failure”, Proceeding inconference on Case histories in GeotechnicalEngineering, 1984 Missouri Rolla, pp.7-13.
Poulos, H.G., “Analysis of the settlement ofpile groups”, Geotechnique,Vol.18, 1968,
pp. 449-471.
Poulos, H.G. (1988). “Modified calculationof pile group settlement interaction
International Journal of GeotechnicalEngineering (ASCE), Vol. 114, 1988, pp.
697-706.
Poulos H.G., "Pile behavior ConsequenceesofGeolgical
andconstruction
imperfections”, International Journal of
GeotechnicalandGeoenvironmental
Engineering (ASCE), Vol. 131, 2005, pp.
538-563.
Randolph, M.F. and Wroth, “Analysis ofdeformation of vertically loaded piles”,
Journal of Geotechnical Engineering
Division (ASCE), Vol.104, 1978, pp. 14651488.

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

OPTIMIZATION OF TREATMENT AREA OF ENZYME MEDIATEDCALCITE CEMENTATION: A NOVEL SOIL IMPROVEMENTTECHNIQUE

1,2,3

Debendra Neupane1, Hideaki Yasuhara2 and Naoki Kinoshita3
Dept. of Civil and Environmental. Engineering, Ehime University, Japan

ABSTRACTThis paper evaluates a technique of enzyme mediated calcite cementation. In this technique, calcium ions andcarbonate ions are allowed to combine within the soil specimen in-situ to produce CaCO 3 . The precipitated
CaCO 3 solidifies and binds the soil particles resisting their movement, hence improving the mechanicalproperties of soil. The first part of this paper evaluates the improved mechanical properties of the sandspecimens treated in a mold with a diameter of 5 cm and a height of 10 cm. An attempt is made to obtain arelation between the amount of precipitated calcite and the achieved mechanical properties. An increase incompressive strength up to 1.6 MPa is obtained while the calcite content is up to 4%. The second part of thispaper evaluates the trend of distribution of the injected grout material in 1-m long vertical sand columns.
Uniform distribution of injected urea and CaCl 2 is achieved easily, but the solution volume is to be increased by
1.5 times to achieve the relatively uniform distribution of urease. Results show that the larger area treatment for
the real site application may be possible.
Keywords: CaCO 3 , Urease, Precipitation, UCS, Concentration

experiment. They achieved a uniaxial compressive
strength (UCS) of up to 12 MPa and an increase in
dry density of up to 37%. Nevertheless, the uniform
distribution of the improvement is yet to beachieved. The control and predictability of the insitu distribution of bacterial activity, reagents andthe resulting mechanical properties due toprecipitated calcite is yet not sufficient [5].
Homogenous distribution of bacteria andprecipitated calcite is a great challenge on bacterial
grouting because of higher flow velocity and poresizes smaller than the size of bacteria [4]. Clogging
may occur due to the bacterial absorbance in soil
grains and it may limit the treatment distance [5].
Utilizing the enzyme itself may be alternativeand more straightforward than using bacteria
because the cultivation and fixation of bacteria (i.e.,
biological treatment) do not need to be considered[6]. The Enzyme Mediated Calcite Precipitation,
EMCP, may be relatively simpler carbonate
precipitation technique, in comparison with thebacterial methods, in order to achieve uniform
calcite distribution.
In our current study, the EMCP technique thatshould improve the mechanical properties of soil has
been evaluated. In the first part of this study, the
EMCP technique is evaluated in small scale samples(i.e., with a diameter of 5 cm and a height of 10 cm).
Sand samples are treated with grout material and themechanical properties of improved specimens are
examined. In the second part, the feasibility of thisINTRODUCTION
Soil improvement is necessary in places where
the soil does not meet the engineering requirements.
Due to the scarcity of land in the cities and planes,
the relocation of the planned engineering structures
may not be possible, even the soil is weak. The
physical and mechanical properties of soil must be
modified in order to meet the engineering
requirements. The demand for new, sustainable
methods to improve soil continues to increase, withmore than 40,000 soil improvement projects being
performed per year at a total cost exceeding US$6
billion/year worldwide [1].
Recently, various soil improvement techniques
are in practice. One of the emerging soil
improvement techniques is the in-situ calcite
grouting technique. This technique employs the
enzyme of urease to dissociate urea into ammonium
and carbonate ions. Urease enzyme purified from thejack bean, or the bacterial cells (e.g., Sporosarcina
pasteurii) producing the urease enzyme, has beenused as a catalyst to dissociate the urea [3]. The
obtained carbonate ions precipitate in the presenceof calcium ions. The precipitated CaCO 3 , i.e., calcite,
forms bridges between the soil grains, binding themand restricting their movement. A lot of works havebeen carried out recently in the field of in-situ calcite
precipitation technique. But most of these works are
confined on small scale samples. However,reference [5] has conducted large scale biogrout
162

GEOMATE- Brisbane, Nov. 19-21, 2014

technique is evaluated in larger scale in a way toachieve a larger treatment area with uniform
distribution of the grout materials. In this part, thedistribution of the injected grout material is
examined throughout the sand packed inside a longtube with an internal diameter of 5 cm and a lengthof 98 cm.

Small Scale Tests to Evaluate the Mechanical
Properties
Small PVC cylinders with a diameter of 5 cm
and height of 10 cm are homogenously packed withkeisa #6 sand. A relative density of about 50% ismaintained throughout the specimen.
Enzyme solution and reagent solution are mixed
together. Concentrations of the reagent solution
range from 1.0-1.6 mol/L and the urease
concentration is fixed at 12 g/L. One pore volume ofthe solution, i.e., 85 mL, is poured into the sandsamples from the top at the rate of 10 mL/min. It isallowed to drain from a small pin hole at the bottomof PVC cylinder. The treated sand specimens arecarefully removed from the cylinder 24 hrs after thesolution injection, and are dried inside the oven at
100 °C for 24 hrs. The oven-dried specimens are
subjected to unconfined compression tests, toexamine the mechanical properties. After theunconfined compression test, the amount of CaCO 3
precipitated in the specimen is evaluated. Each ofthese experimental conditions is conducted twotimes to check the reproducibility.
Figure 1 shows the relation between CaCO 3
precipitated and the mechanical properties achievedin the treated sand specimens. As is apparent in the
figure, the noticeable improvement in strength canbe observed after the precipitated CaCO 3 approach avalue of 2.5%. An almost linear increment instrength can be observed afterwards.

EXPERIMENTS
Grout Materials
The grout used in this study is a combination ofreagents, i.e., urea and CaCl2 , and an enzyme calledurease. Urea and CaCl2 , having claimed purity
levels greater than 95%, are obtained from the Kanto
Chemicals Co. Inc., Tokyo, Japan. Urease, with theactivity of 2970 Units/g obtained from Kishida
Chemical Co. Ltd. Osaka Japan, has been used in the
bio-catalytic dissociation of urea (CO(NH 2 ) 2 ) (Eq.
1). The obtained carbonate ion precipitates in thepresence of the calcium ion (Ca 2+ ) supplied by the
CaCl 2 solution (Eq. 2).
2−(1)

CO 32- + Ca 2 + → CaCO 3(2)

Two different types of silica sands, keisa #6 andkeisa #8, are used in large scale experiments to
examine the flow and transport of the injected
solution in sands with different hydraulicconductivity. The hydraulic conductivity of keisa #8
is 22 times smaller than that of keisa #6. The
physical properties of these two types of sand areshown in Table 1.

Table 1. Physical property of sands
Properties
D 10 [mm]D 50 [mm]Sp. Gr.
e max
e min
k* [cm/s]

Evaluation Techniques
Different methods are followed to quantify theconcentration of the grout materials and the amountof precipitated calcite. The concentration of calcium
ion present in the solution is evaluated using ICPAES. To evaluate the concentration of urea, thesolution is mixed with the excess amount of urease.
Afterwards, the concentration of the released
ammonium ion is measured with the help of an ion
meter [2]. The amount of precipitated calcite present
in the treated sand is evaluated by acid leachingprocess. In this process, oven-dried treated sand ismixed with, Hydrochloric acid, HCl, until the gas
bubble formations stops. The acid treated sand isdried in oven and the weight loss before and afteracid leaching is calculated. The lost weight isassumed to be the weight of calcite.

Keisa #6
0.20
0.34
2.653
0.899
0.549
0.044

Keisa #8
0.04
0.10
2.650
1.333
0.703
0.002

*k is hydraulic conductivity
160

1600

UCS
E

UCS [kPa]

1200

120

50

800

80

400

40

E50 [MPa]+

CO(NH 2 )2 + 2H 2O → 2NH 4 + CO3

0

0
0

1

2

3

4

5

Amount of CaCO3 in sand [%]Fig.1 Relation between amount of calcite precipitated
and the mechanical properties

163

GEOMATE- Brisbane, Nov. 19-21, 2014

However, there are some exceptions. A maximum
strength of 1.5 MPa and stiffness of 129 MPa isachieved when the amount of precipitated CaCO 3 insand is about 4%.

Sand packing
Sand is packed in the pipe in 5 layers,maintaining a relative density of about 50% in eachlayer. For the case of medium sand, the relative
density of 50% is achieved easily with gentle
compaction. But the fine sand is tamped with thehelp of a wooden tamper to achieve a relative
density of 50%.

1-D Flow Experiment
The feasibility of the grouting technique depends
upon the volume of the treatment area that can betreated from one injection point. 1-D flow
experiment is carried out to examine whether thetreatment improved shape of about 2 m in diameteris possible or not. The acrylic pipe with an innerdiameter of 50 mm and a length of 100 cm is used
for the 1-D flow experiment.

Solution injection
The sand sample is saturated with water before
the solution injection. The tube connected to thebottom of acrylic pipe, i.e., injection tube, is filledwith the injecting solution. Afterwards, one porevolume of injecting solution is poured into the tankand valve A is opened to commence the solution
injection. The equal rate of injection, i.e., 60
mL/min, is maintained throughout the experiment.
For the case of keisa #6, a 60 cm head is prescribedto maintain an injection rate of about 60 mL/min asshown in Fig. 2(a). For the case of keisa #8, aperistaltic pump is employed to maintain the equal
rate of injection as shown in Fig. 2(b). Immediately
after finishing the solution injection, 5 mL of sample
solutions are pumped out of every hole with the helpof syringes fitted with needle. The pumped solutions

Experimental set up
The schematic diagram of the acrylic cylinder
test is shown in Fig. 2. The acrylic pipe contains
removable caps with a porous stone at its two ends.
The caps are connected with tubes with a diameterof 8 mm to inject and to drain out the grout material.
The acrylic pipe contains 11 holes with a diameter of
2 mm at equal intervals as shown in Fig. 2. Theseholes are kept covered with silicone seals during
sand packing and solution injection. The injection
tube contains a ball valve, i.e., valve A, near the inlet

9.8

98 cm

60 cm

Grout
material

Tubingpump

Fig.2 Experimental set up of 1-D flow testof the acrylic pipe which is used to regulate the flow.
164

Grout
material

GEOMATE- Brisbane, Nov. 19-21, 2014

are collected in PP tubes separately.

conditions similar to Ea1), the concentration of

Table 2. Experimental conditions of 1-D flow experiment
Test
Injecting
Injection
Head
Sand
name
solutionvolume (PV)
(cm)
type
Ca1
1 mol/L CaCl 2
1.0
60
Keisa #6

Dilution-

Reacting
solution-

Evaluation
methodICPAESCa2

1 mol/L CaCl 2

1.0-

Keisa #8--

ICPAESUa1

1 mol/L urea

1.0

60

Keisa #6

10 times

30 g/L urease

Ion meter

Ua2

1 mol/L urea

1.0

60

Keisa #8

10 times

30 g/L urease

Ion meter

En1

15 g/L urease

1.0

60

Keisa #6

10 times

1 mol/L urea

Ion meter

En2

15 g/L urease

1.0

80

Keisa #6

10 times

1 mol/L urea

Ion meter

En3

15 g/L urease

1.5

80

Keisa #6

10 times

1 mol/L urea

Ion meter

En4

15 g/L urease

1.5-

Keisa #8
10 times
1 mol/L urea
Ion meter
ammonium still decreases after 60 cm, however the

The properties of the injected solution andmixing solution for various cases are shown in Table
2. The sample solutions of case Ca1 and Ca2 aresubjected to ICP-AES to evaluate the amount of thecalcium ion present in the solution. The sample
solutions of the other cases are mixed separately
with an equal volume of mixing solutions as shownin Table 2. The mixed solution is allowed 24 hours
for the urea hydrolysis. After 24 hours, 1 mL of themixed solution is taken and is diluted 10 times by
mixing it with 9 mL of deionized water. The
ammonium concentration of the solution ismeasured and the result is analyzed.

Maximum value

Ca2+ [mol/L]

1.5

1.0

0.5
Ca1
Ca2
0.0
0

20

40

60

80

100

Distancefrom ion
inletconcentration[cm]
Fig.3 Distributionof calciumof CaCl2 injection

Results

1.5

Maximum value

NH4+ [mol/L]

The vertical distributions of the individual grout
materials are plotted. Vertical distribution of thecalcium ion as evaluated by ICP-AES is shown in
Fig. 3. As is apparent in the figure, distribution of
the precipitated calcite is almost uniform throughout
the height of the sample. It shows that theconcentration of the CaCl2 solution can distribute
uniformly throughout a distance of about 1 m fromthe injection. Vertical distribution of the ammonium
ion for case Ua1 and Ua2 is as shown in Fig. 5. As isapparent in the figure, the concentration of theammonium ion does not decrease remarkably in bothof the sands, keisa #6 and keisa #8. Hence, theconcentration of the urea solution injected into thesand distributes almost uniformly throughout adistance of about 1 m from the injection. However,the variation of distribution of urea seems tooscillate more than the variation of distribution of
calcium ion. The variation of ammonium ion isrelatively higher in keisa #8 sand. The vertical
distribution of the ammonium ion for the case En1En4 is shown in Fig. 6. As is apparent in the figure,the distribution of the ammonium ion for case Ea1 isuniform until a height of 60 cm from the inlet.
Afterwards the concentration decreases. For Ea2(i.e., head is increased to 80 cm keeping other

1.0

0.5
Ua1
Ua2
0.0
0

20

40

60

80

100

Distance from inlet [cm]Fig.4 Distribution of ammonium ion concentrationof urea injection
1.5
En1
En2

NH4+ [mol/L]

Maximum value

En3
En4

1.0

0.5

0.0
0

20

40

60

80

100

Distance from inlet [cm]Fig.5 Distribution of ammonium ion concentrationof urease injection
165

GEOMATE- Brisbane, Nov. 19-21, 2014

decrease is relatively gradual. In the next attempt toachieve the uniform distribution of the urease,
volume of solution is increased. The distribution ofammonium ion is found relatively uniform in caseEa3, where the injection volume is increased to 1.5
pore volumes. With an increase in the volume of
injection, the problem of non-uniform distribution of
the urease content may be solved in keisa #6. To
examine the distribution of urease in keisa #8, 1.5
pore volumes of solution is injected using aperistaltic pump. As is apparent in the figure, theurease content is observed only up to a few
centimeters from the inlet. It may be due to the small
pore size of keisa #8 sand. The relatively smaller
pores may have resisted the flow of the colloidal
particles of urease. These results conclude that theflow of urea and CaCl 2 is relatively uniform over a
vertical distance of almost 1m for both finer andcoarser sand evaluated in this work. The uniform
distribution of urease can be easily achieved incoarser sand by increasing the injection volume.
Hence, the treatment distance of approximately 2 m
may be feasible in EMCP technique.

sand. In the near future the mixed grout material isinjected and the distribution of calcite throughout thesand column is evaluated. Afterwards, the similar
test is replicated in 3- dimensional samples.
ACKNOWLEDGEMENTS
This work has been partly supported by research
grants from the Maeda Engineering Foundation,
Tokyo, Japan and the Shikoku Create Association,
Kagawa, Japan. Their support is gratefully
acknowledged.
REFERENCES[1] DeJong JT, Mortensen BM, Martinez BC,
Nelson DC, “Bio-mediated soil improvement”,
Ecol. Eng., Vol. 36, 2010, pp. 197-2010.
[2] “Handy ion meter TiN-9001 instruction
manual”, Toko Chemical Laboratories Co., Ltd.
[3] Harkes MP, Van Paassena LA, Booster JL,
Whiffin VS, and van Loosdrechta MCM,
“Fixation and distribution of bacterial activity insand to induce carbonate precipitation forground reinforcement”, Ecol. Eng., Volume36(2), 2010, pp. 112–117.
[4] Keykha HA, Huat BBK, and Asadi A, “Electrobiogrouting stabilization of soft soil”,
Environmental Geotechnics, 2013, pp. 1-9.
[5] van Paassen LA, Ghose R, van der Linden TJM,
van der Star, WRL, and van Loosdrecht M CM,“Quantifying biomediated ground improvement
by ureolysis: Large-scale biogrout experiment”,
J. Geotech. Geoenviron. Eng., Volume 136 (12),2010, pp 1721–1728.
[6] Yasuhara H, Neupane D, Hayashi K, andOkamura M, “Experiments and predictions ofphysical properties of sand cemented byenzymetically-induced carbonate precipitation”,
Soils Found., Volume 52(3), 2012, pp. 539–549.

CONCLUSION

The efficacy of EMCP technique is evaluatedin small scale laboratory samples. The results
show an appreciable increment in mechanicalproperties. For the utilization of EMCP as analternative soil improvement technique inengineering applications, the treatment area should
be increased. The distribution of individual grout
materials is evaluated in 1 m sand columns. The
distribution of reagents is found to be uniform inboth coarser and finer soil. In order to achieve theuniform distribution of urease in coarser soil,
injection of higher volume of the solution isrequired. However, the injection techniqueemployed in this work is found not appropriate toachieve a uniform distribution of urease in finer

166

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

NUMERICAL ANALYSIS OF INFILTRATION INTO PERVIOUS
CONCRETE-BASE SYSTEMS
Bertrand Teodosio1, *Jaehun Ahn2 and Hyun-Suk Shin3
1
Graduate Student, Pusan National University, Korea
2
Assistant Professor, Pusan National University, Korea
3
Professor, Pusan National University, Korea

ABSTRACT
Decrease in pervious area due to urbanization, and rapid change in climate prompted to reconsider ourphilosophy in stormwater management. One of innovative approaches for stormwater management is a concept
called Low Impact Development (LID). Among other techniques of LID, construction of pervious pavement canutilize vast paved surfaces, traditionally impervious, allowing stormwater to infiltrate through its surface. In thisstudy, the hydrologic performance of a particular pervious concrete system section was investigated using Finite
Element Method (FEM) modelling. The influence of initial saturation and rainfall intensity to produce run-off
were examined to imply possible design considerations. Further, rainfall data recorded from July 15, 2012 in Busan,
South Korea was employed to probe the effect of evaporation and pipe installation in the hydrologic capacity andbehavior of the pervious concrete system. The results and implications to hydrological design are discussed herein.
Keywords: Low Impact Development, Pervious concrete, Finite Element Method, Infiltration, Run-off

INTRODUCTION

INFILTRATION CAPACITY CALIBRATION

Flooding is recurring in most urban areas which
affects economic growth. According to Crichton[2],total gross domestic product (GDP) losses due tostormwater run-off accumulation are approximately
14% and 2% for poorer and richer countries,
respectively.
Inundation does not only lead to economic
damage, it also causes bereavement in different
affected regions. Conferring to the United Nations[5],above 90% of recorded death from natural disasters
are related to water from the year 1975 to 2001 in
Asia.
Possible methodologies to prevent severe
flooding that could cause financial damage and life
loss is through stormwater management. One ofinnovative approaches for stormwater management is
a concept called Low Impact Development (LID).
LID is an emerging practice to lessen inundation andhazards due to lack of pervious surfaces in an urban
region. Among other techniques of LID, constructionof pervious pavement can allow stormwater toinfiltrate through its surface preventing or attenuating
run-off occurrence.
To quantify the feasibility of a pervious pavement,
the hydrologic performance should be investigated byobtaining the infiltration capacity and run-off
threshold of a system. Generally, infiltration capacity
can be obtained using calculation methods such as
Darcy’s Law, Horton’s Equation, Curve Numbers,
and Green-Ampt Model.

Infiltration is governed by the pull of gravity andcapillary action. The soil characteristics including
hydraulic conductivity, porosity, and ease of entry
also affects the infiltration process.
In this study, Green-Ampt Model was comparedto FEM model to verify the applicability of the used
FEM software, SVOffice’s SVFlux[6].
Green-Ampt Model
The Green-Ampt Model[4][7] is a method toestimate infiltration which considers wetting front
suction head (ψ), volumetric water content (θ),
saturated hydraulic conductivity (k s ), and cumulative
volume infiltrated (F). Eq. (1) shows the formula to
be used for rainfall intensity (I) less than or equal to
the saturated hydraulic conductivity to obtain theinfiltration, f, at a specific time, t.
f=I(I ≤ 𝑘𝑘𝑠𝑠 )(1)

For rainfall intensity greater than the saturated
hydraulic conductivity refer to Eq. (2).
f = k 𝑠𝑠 �1 +∆𝜃𝜃∙𝜓𝜓
𝐹𝐹�(I > 𝑘𝑘𝑠𝑠 )(2)

Where Δθ is the initial moisture deficit (θ s -θ i ) and ψ
is the average suction at wetting front.
To obtain the cumulative volume of water
infiltrated, F, Eq. (3) should be used.

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GEOMATE- Brisbane, Nov. 19-21, 2014

k 𝑠𝑠 (𝑡𝑡 − 𝑡𝑡𝑠𝑠 ) = 𝐹𝐹 − ∆𝜃𝜃 ∙ 𝜓𝜓 ∙ ln(𝐹𝐹 + ∆𝜃𝜃 ∙ 𝜓𝜓)−𝐹𝐹𝑠𝑠 + ∆𝜃𝜃 ∙ 𝜓𝜓 ∙ ln(𝐹𝐹𝑠𝑠 + ∆𝜃𝜃 ∙ 𝜓𝜓)(3)

To calculate for the cumulative infiltration, F s , refer
to Eq. (4).
∆𝜃𝜃∙ 𝜓𝜓

F𝑠𝑠 = 𝐼𝐼

𝑘𝑘𝑠𝑠

−1

(4)

Where t s is the time to achieve surface saturation
calculated by getting the ratio of the cumulative
volume of infiltration at moment of surface saturation,
F s , and rainfall intensity, I.

Fig. 2

FEM and GA models, I=100 mm/hr.

FEM INVESTIGATIONS

Finite Element Method (FEM)

Initial Condition

The infiltration of a single layer crushed limestone
was modelled in SVFlux to compare with the GreenAmpt infiltration model. The material properties of
the crushed limestone is presented in Table 1 andTable 2 for Soil Water Characteristic Curve (SWCC)
and unsaturated permeability property, respectively.

For the following investigations, a pervious
pavement system was modelled with two different
layers. The top layer is a pervious concrete (PC) withproperties listed in Table 3 and Table 4 based on
experimental tests conducted. The height of the PC
layer is 0.15 m.

Table 1 Crushed limestone SWCC [1]Table 3 Pervious concrete SWCC

Layer
θs
a
n
m
h
CrushedLimestone 0.34
0.71 1.74 0.47 100
Note: a, n, m, h are constants from Fredlund-Xing Fit.
Table 2 Crushed limestone unsaturated k properties

Layer
θs
a
n
m
h
Pervious
Concrete
0.32
2.23 1.63 8.60 0.21
Note: a, n, m, h are constants from Fredlund-Xing Fit.
Table 4 Pervious concrete unsaturated k propertiesLayer
k s (cm/s)
k min (cm/s)p
CrushedLimestone
1.1x10-4[3]1x10-85
Note: k min = minimum permeability;
p=estimation constant for Modified Campbell

Layerk s (cm/s)
k min (cm/s)p
Pervious
Concrete
0.1291x10-85
Note: k min = minimum permeability;
p=estimation constant for Modified Campbell

The comparison of infiltration models is shown in
Fig. 1 and Fig. 2. The Green-Ampt model and FEM
model for the infiltration of the single layer crushedlimestone are almost coinciding with each other. The
curves completely converges at around 35 minutes for
all the applied infiltration intensities.

The bottom layer is made-up of crushed limestone
with properties listed in Table 1 and Table 2. The
height of the bottom layer is 0.45 m. The width of thetypical pervious pavement system is assigned to be 3m.
The boundary conditions of the system was
assigned to be zero flux at both sides and at bottom
indicating that there might be a liner or ageomembrane installed to have no exfiltration. For
the interface of PC and crushed limestone (CL), a noboundary condition was designated to allow flow. For
the upper side of the PC layer, a direct rainfall wasapplied, hence, climate boundary condition was
assigned. Refer to Fig. 3 for the boundary conditions
designated to the pervious pavement system.

Fig. 1

FEM and GA models, I=25 mm/hr.
Fig. 3
168

Boundary conditions for PC and CL layers.

GEOMATE- Brisbane, Nov. 19-21, 2014

To investigate the effect of initial condition of thepervious system, the degree of saturation was
assigned to be 0%, 25%, 50%, 75%, and 100%. The
equivalent initial matric suction is listed in Table 5 for
PC and limestone.

Concentrating in the water storage capacity, thetotal V v of the system is 0.1994 m3/m2. Applying theconstant rainfall intensity 25 mm/hr (4.17x10-4
m/min), the time to fill the whole system is around
480 minutes for a dry initial condition. Due to thedisparity of hydraulic conductivity of the twomaterials, run-off might occur after filling the PC
layer. The total V v for the said layer is 0.0483 m3/m2.
It will take about 120 minutes for the PC layer to be
filled. Conferring to Fig. 5, the 0 % initial saturation
system experienced a run-off at 217 minutes. The
FEM value is between the computed time using V v
which has a range equivalent to 120 to 480 minutes.
Same steps for calculating the range were made forthe remaining system with increased initial saturation
condition. The ranges are tabulated in Table 6.

Table 5 Initial condition of the pavement system
Degree ofSaturation
0%
25%
50%
75%
100%

ψ i (kPa)
PC
-1.4
-90
-0.7
-0.28
-0.08

ψ i (kPa)
Limestone-250-1x106
-3.7
-0.66
-0.05

Table 6 Range of possible run-off threshold

The increment assigned for the iteration is 1
minute. For the initial condition saturation
investigation, the end time is 900 minutes since thistime is sufficient for the system to achieve fullsaturation. Fig. 4 presents the mesh for PC andlimestone layers.

Fig. 4 FEM meshes for PC and limestone layers.
For the results of the five runs with constantpervious pavement section and material properties
but different initial condition, refer to Fig. 5.
According to the graphs presented, the initialsaturation affects the run-off threshold due to thedifferences in water storage availability. The curves
is logical since the process of infiltration continues if
there is a water storage available to fill additional
water in the system. However, this graphs gives
quantification to the time required to experiencestormwater run-off for the specific section with
SWCC and unsaturated hydraulic conductivity
properties.
The run-off threshold for the pervious pavement
system is 217, 183, 94, 10, and 3 minutes for initialcondition equivalent to 0%, 25%, 50%, 75%, and 100%
saturation, respectively.

Min.
Max.
FEM
InitialSaturation
(min)
(min)
(min)
0%
116
479
217
25%
87
359
183
50%
58
239
94
75%
29
120
10
100%
0
0
3
In system with higher initial saturation conditionof 75% and 100%, it is reflected that the FEM run-off
threshold was not in the range calculated. This effectis possibly due to the SWCC and unsaturated
hydraulic conductivity of the materials.
The graphs for the cumulative run-off aredisplayed by Fig. 6. The cumulative run-off after 600
minutes for 0%, 25%, 50%, and 100% are 0.33 m3,
0.36 m3, 0.50m3, 0.70 m3, and 0.75 m3, accordingly.

Fig. 6

Infiltration of pervious system having
different rainfall intensities applied.

Rainfall Intensity

Fig. 5To expand the range of analysis, rainfall intensity
was assigned to be a variable with all the remaining
parameters left constant. The constant initialcondition chosen was 25% saturation since theoptimum gravimetric moisture content can beobtained with this value according to experimental

Infiltration of pervious system having
different initial saturations.

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GEOMATE- Brisbane, Nov. 19-21, 2014

that has the ability to drain substantial water flow was
drawn at the midpoint of the width on the bottom
surface of the basalt layer. The boundary condition
for the pipe was an excess pore pressure constantequal to zero (u=0). The pipe is 100 mm in diameter.
Fig. 9 illustrates the section with drain installed.

tests. The rainfall intensities applied were 25, 50, 75,
and 100 mm/hr and run-offs are experienced at timeequal to 183, 62, 27, and 23 minutes, respectively.
The infiltration curves are shown in Fig. 7.

Fig. 9Fig. 7

Pervious pavement system section with pipe
installed.

Table 8 FEM cases for run-off analysis concerning
pipe and evaporation

Infiltration of pervious system having
different rainfall intensities applied.

Case
1
2
3
4

The cumulative run-off are 2.62 m3, 1.89 m3, 1.11
3m , and 0.36 m3 for 100 mm/hr, 75 mm/hr, 50 mm/hr,
and 25 mm/hr, respectively, for the rainfall intensity
test simulation within 600 minutes. Refer to Fig. 8 forthe cumulative run-off graphs of pervious pavement
system with different rainfall intensities applied.

Pipe
None
None
Implemented
Implemented

Evaporation
None
Implemented
None
Implemented

There are four cases for the application of thecollected rainfall data. At the preceding page, Table 8
presents the cases for examining the effect of pipe andevaporation in the hydrologic performance of thepervious concrete and limestone.
The rainfall data applied to the cases in Table 8
are plotted in Fig. 10.

Fig. 8

Infiltration of pervious system having
different rainfall intensities applied.

Rainfall Data Application
A rainfall data was collected from July 15, 2012
in Busan, South Korea. The historical weather for thesaid day is listed in Table 7 which was used for the
implementation of evaporation effect in the SVFlux
software. The potential evaporation method used wasconstant while the actual evaporation method used
was Wilson Limiting Equation.

Fig. 10 Rainfall data (July 15, 2012) collected andapplied in the FEM cases
Case 1 shows run-off without pipe installed andwithout evaporation implemented. It is evident fromthe graph that for a no exfiltration pervious pavement
system and no evaporation implemented, notable
volume of run-off should be experienced. Conferring
to curve of Case 2, there is a small amount of
reduction in the run-off due to the evaporation
implementation which serves as an outlet at the top
surface of the system. When pipe was installed, therun-off plummeted which is evident in both Case 3
and Case 4. The run-off graphs are shown in Fig. 11.

Table 7 Historical weather in Busan, South Korea
07-15-12 T(°C) H(%) W(mph)
Max
29.4
94
21
Min
22.8
68
17
Ave
26.1
81
19
Note: T = air temperature; H = humidity; W = windspeed; C = potential evaporation constant.
To investigate the effect of the pipe, an opening
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GEOMATE- Brisbane, Nov. 19-21, 2014

CONCLUSIONSIn this study, three sets of experimental runs wereconducted. The first set was conducted to investigate
the influence of initial saturation condition (0%, 25%,
50%, 75% and 100%) of the pervious pavement
system to the run-off buildup. A constant rainfall
intensity of 25 mm/hr was applied. According to thedata collected curves plotted, initial saturation,
SWCC and unsaturated hydraulic permeability
affects the behavior of water protrusion through thesystem. For a dry system until around 50% saturation,
the run-off threshold time is in between the time tofill the PC layer (Minimum) and the time to fill thewhole system (Maximum).
On the other hand, for initial saturation more than
50%, the run-off threshold time from the runs were
not in between the computed range. For the 75%
initial saturation, the run-off happened earlier. In thecase of 100% initial saturation, the run-off happened
late. The cause could be the initial matric suction
assigned in the initial condition input based on the
SWCC. The proximity of values of both PC andlimestone for 75% initial saturation seems to have aneffect to the analysis which resulted to earlier
occurrence of run-off. While in the 100% initialsaturation, the initial matric suction of PC has ahigher value in comparison with the crushedlimestone layer that could possibly ensued latter runoff occurrence. The pore pressure buildup might havean effect to the infiltration of water. Further
examination should be conducted regarding thisoccurrences.
In relation with the cumulative run-off of theinitial saturation investigation, there are noobservable pattern that can be deduced from thecurves plotted. However, 0% and 25% has almost
similar run-off volume within 600 minutes. Similarcase with the 75% and 100% initial saturation, thecumulative run-off volume’s value are near.
The second set, focused on the effect of rainfall
intensity applied to the system. The curves observed
were reasonable. There is an inverse proportionality
between the rainfall intensity applied and run-off
threshold. As the rainfall intensity applied wereincreased, the time for run-off to occur decreased.
Rainfall intensities of 75 mm/hr and 100 mm/hr haveclose run-off threshold time. A pattern can beobserved in the cumulative run-off curves. Assumingthat the baseline rainfall intensity is 25 mm/hr,
increasing the rainfall intensity to 50 mm/hr (twice
the baseline value) will increase the accumulated runoff volume by 208%. Similarly, applying rainfall
intensity with a value thrice the baseline rainfall
intensity would increase the cumulative run-off
volume to 425%. Also, multiplying the baseline
rainfall intensity (25 mm/hr) by four will increase thecumulative run-off volume by 628%. Hence, eachtime you increase the rainfall intensity by a factor, theFig. 11 Run-off graphs for rainfall data applied topervious pavement system.
To quantify the run-off volume accrued, thecumulative run-off volume for each cases are plottedin Fig. 12. The maximum run-off volume collected
for Case 1 is 0.36 m3. By implementing evaporationin Case 2, the cumulative run-off volume decreased
to 0.28 m3. Case 3 and Case 4 collected 0.13 m3.

Fig. 12 Cumulative run-off graphs for rainfall dataapplied to pervious pavement system.

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GEOMATE- Brisbane, Nov. 19-21, 2014

cumulative rainfall intensity will increase
approximately 200% multiplied by the factor where
25 mm/hr rainfall intensity was assumed to be thereference.
The third set of simulation incudes the applicationof the rainfall data collected from July 15, 2012. The
rainfall data was used to investigate the run-off
reduction by implementing pipe and evaporation.
From the graphs obtained, the evaporation may havelittle significance when pipe was implemented to thesystem.
There is a 20% reduction in the cumulative runoff volume when evaporation is implemented. For apartial exfiltration system, 64% can be reduced in the
cumulative run-off volume by installing a 100-mm
pie at the center over the bottom surface of thelimestone layer.

REFERENCES[1] Ba M, Nokkaew K, Fall M and Tinjum J, “Effectof matric suction on resilient modulus ofcompacted aggregate base courses”, J. of
Geotechnical and Geological Engineering, Vol
31, Issue 5, Oct. 2013, pp 1497-1510.
[2] Crichton D, International historical , political,
economic, social, and engineering responses toflood risk. Florida: CRC Press, 2011.
[3] Cote J and Konrad JM, “Assesment of hydrauliccharacteristics of unsaturated base-course
materials: a practical method for pavement
engineers”, Canadian Geotechnical Journal, Vol
40, 2003, pp 121-136.
[4] Mein RG and Larson CL, “Modeling infiltration
during a steady rain”, J. of Water Resources
Research, Vol 9, No. 2, Apr. 1973, pp 384-395.
[5] United Nations, Guidelines for reducing flood
losses. Geneva: United Nations International
Strategy for Disaster Reduction (UNISDR),
2004.
[6] Thode R and Fredlund M, SVFlux Tutorial
Manual. Saskatchewan, Canada: SoilVision
Systems Ltd., 2013, ch. 2.
[7] Zhang J, A laboratory scale study of infiltrationfrom pervious pavements. Australia: RMIT
University, 2006, ch. 4.

ACKNOWLEDGEMENTS
This research was supported by a grant from
Advanced Water Research Program funded by
Ministry of Land, Infrastructure and Transport of
Korea government, and the Mid-Career Researcher
Program (No. 2012-047702) funded by National
Research Foundation of Korea government.

172

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

PROPAGATION OF HARMONICAL VIBRATIONS IN PEAT
Darius Macijauskas1 and Stefan Van Baars2,
Faculty of Science, Technology and Communication, University of Luxembourg, Luxembourg

1,2

ABSTRACT
In order to check the reliability of man-made vibration prediction methods, vibration tests were performed on
one of polders in the North-West of the Netherlands. The polder was chosen because it has a rather homogenous,
thick and soft peat top layer. Here sufficient harmonical vibrations could be generated by a rather small shaker.
The shaker was designed and manufactured in order to produce harmonical vibrations at the soil surface. It
consists of two counter rotating electric vibrators (with rotating eccentric masses) in order to produce a verticallyoscillating force. For the recordings of the vibrations, six 2D or 3D geophones were placed on the soil surface
and one 2D geophone was placed on top of the shaker.
The measured vibration amplitudes of the vertically oscillating shaker were compared with 1. Two different
analytical methods used for the design of vibrating machine foundations, 2. The Confined Elasticity approachand 3. The Finite Element Method, for which Plaxis 2D software was used. Also the measured vibration
amplitudes at the soil surface were compared with Barkan-Bornitz’s solution and Finite Element Modeling.
Keywords: Soil Vibrations, Man-made Vibrations, Vibration Propagation, Soil Waves

used for the peat strength research is marked byletter “B” in Fig 1. In there, geologicalinvestigations have been carried out in May 2012.
Three boreholes were drilled and they are marked by“c1”, “c2” and “c3” in Fig. 1 and Fig. 2.

INTRODUCTION
For most developing countries the urban
environment is getting larger and denser. Therefore
civil engineers have to pay more attention to theeffect of man-made vibrations. According toresearch by Hölscher and Waarts [2] the reliabilityof prediction methods for man-made vibrations is
unfortunately disappointingly low. In order to checkthis conclusion, a field test was performed tomeasure the vibration propagation with anexperiment on site.
In order to produce harmonic vibrations at thesoil surface, a shaker was designed andmanufactured. For the recordings of the vibrations,six 2D or 3D geophones were placed on the soil
surface and one 2D geophone was placed on top of
the shaker.
The measured vibrations of the shaker and thesoil surface will be compared with analytical andnumerical (FEM) solutions.

N

c1

c2

c3

B
A

Fig. 1

Location of the test site (Google, Map data)

The top layer is a thin clayey layer with athickness varying between 0.2 m and 0.5 m. Below
this layer there is a peat layer of 4.5 m thick. It wasreported that the bulk density of the peat layer
ρ = 0.98 ± 0.08 t/m3 [3].

SITE LOCATION AND STRATIGRAPHY
In order to produce sufficient harmonic
vibrations on the soil surface with a rather small
shaker, the potential site for the field test should
fulfil two major conditions: it should be rather
homogeneous and rather soft. Therefore a peaty site
in the Netherlands was chosen. The test site is
located about 10 km North-East from Amsterdam in
the village of Uitdam. The test area is marked byletter “A” in Fig. 1.
Near the test area, other research has been madebefore, related to the strength of peat [3]. The area

EQUIPMENT AND SETUP
Shaker Design
In order to make the shaker transportable, twosmall counter rotating electric vibrators (withrotating eccentric masses) have been used to produce
173

GEOMATE- Brisbane, Nov. 19-21, 2014a vertically oscillating force. This type of vibrator isfrequently used in geotechnics (for example sheet
pile driving or soil densification).
west

c1

c2

c3

but of the biggest vertical vibration peaks.

4

6

east

5

Profile location in the site

c1

c2

c3
2

3

1

B
Fig. 3A

The measured P-wave and S-wave velocities onsite are respectively v p = 66.9 m/s and v s = 17.4 m/s.
From the velocities of the body waves and the bulk
density of the peat ρ ≈ 1 t/m3, according to Eq. 1,
Eq. 2 and Eq. 3 the shear modulus G = 303 kN/m2,
the Poisson’s ratio ν = 0.464 and the Elastic modulus
E = 886 kN/m2 can be determined. The R-wave
velocity can be calculated from the Poison’s ratio
and S-wave velocity: v r = 16.5 m/s.

Clay
Peat
Sandy clay
Sand

Fig. 2Vibration test setup: 1) Shaker; 2)
Frequency inverter; 3) Power generator; 4)Geophones; 5) Data acquisition box; 6)
Laptop

Data from geological investigations [3]G = ρv s2

The vibrators are connected to a plate of 40 cm
in diameter and 2 cm in thickness. Additional squareplates can be added on site to vary the total mass ofthe system. The whole is tightened together withbolts. This makes a total weight of the shaker
variable up to a maximum of 300 kg (which makes
the vertical gravity force 2.94 kN) and the verticaloscillating force (due to the rotating eccentricmasses) can vary up to 2.06 kN.

(1)

1 (v p / v s ) − 2ν=
2 (v p / v s )2 − 1(2)

E = 2G (1 + ν )(3)

2

In order to compare the analytical solutions of
the shaker vibration amplitude with the vibration
amplitudes of the soil surface, the site will bemodelled as an elastic isotropic homogenous
half-space with the previously defined elastic
properties.

Vibration Tests Setup
The equipment used for the vibration tests,
consists of a: 1) Shaker; 2) Frequency inverter; 3)Power generator; 4) Geophones; 5) Data acquisition
box; 6) Laptop. All these components with theircorresponding numbers are shown in Fig. 3.

SHAKER VIBRATION AMPLITUDES
ELASTIC PROPERTIES OF THE SITE
In 1904 Lamb [4] solved the problem of the
wave propagation in three dimensions (also known
as the dynamic Boussinesq problem). Based on
Lamb’s work, Reissner in 1936 [5] first developed
the vertical response of a uniformly loaded flexible
circular area resting on an elastic half-space. The
vertical displacement amplitude at the center of theflexible loaded area is, according to Reissner,
defined by:

In order to evaluate small strain stiffness
parameters of the peat, pressure (P) and shear (S)wave velocity measurements were carried out. Thiswas done by hitting the shaker with a hammer andmeasuring the arrival times at the geophones. The
geophone on top of the shaker records the input
wave.
The P-wave velocity was measured from thearrival time differences between of the first radialvibration peaks and the S-wave velocity similarly
174

GEOMATE- Brisbane, Nov. 19-21, 2014

Using this, the vibration amplitude can be written

f12 + f 22

F
AR = 0Grpl(1 − ba f ) + (ba f )
2
2
0 1

2
2
0 1

,

as:

(4)

AL =

in which: F 0 – amplitude of the vertically exciting
force; r pl – radius of the loaded circular area; f 1 , f 2 –displacement (compliance) functions;a0 –dimensionless frequency; b – dimensionless mass
ratio. The dimensionless frequency and mass ratio
are calculated as follows:a0 = ωrpl
b=

ρ
,
G

mvib
,
ρrpl3

ωn =
(5)

(7)

 1 − ν  mvib  1 − ν B=
b .
 2 =
 4  ρrpl  4 

D=

1 −ν

(12)

K
.
mvib

(13)

(14)

,

Gρ .

ωc =

4G
,
ρrpl2

(15)

mc =

2(1 −ν ),1 − 2ν

(16)

The static displacement is defined as follows:
(9)

As =

And suggested an analogous spring stiffness K
and damping ratio D.

3.4rpl2,2nin which: ω c – characteristic frequency; m c –material constant, A s – static displacement.

Hsieh [8] modified in 1962 Reissner’s solution
and proved, that it is possible to have a mechanicalanalogue in a form of single-degree of freedom
system. Later Lysmer and Richart [9] proposed afrequency independent mechanic analogue.
Lysmer modified the mass ratio:

1 −ν

2

−1

1.93
.
a03

4Grpl

2

 ω exp(iω / ωc ) − ωc sin(ω / ωc ) AC = ReAs ,2 
 16 B  ω  
 πm (1 −ν )  ω   c 
 c

(8)

K=

2
n

Another analytical solution was suggested by
Verruijt [10]. He suggests to neglect here thehorizontal displacements (while they are very small
compared to the vertical ones), which is called theconfined elasticity approach. This approach was first
proposed by Westergraad [11] and generalised forelastodynamics by Barends [12]. In this way thevibration amplitude of a rigid circular plate on aconfined elastic half space becomes:

where: ω – angular frequency; m vib – total vibrating
mass.
Bycroft [6] provided a solution for forced
vibrations of a rigid circular plate attached to thesurface of an elastic half-space for large values ofthe frequency (a 0 > 1.5, which is also the case in thisarticle). Using Eq. (4), according to Kruijtzer [7] thecompliance functions can be simplified to:f2 ≈[1 − (ω / ω )] + 4D(ω / ω )2

in which: ω n – natural angular frequency of themechanical analogue system:(6)3
f1 ≈ 2 ,4a 0

F0 / KF0 mc,
πrpl λ + 2G

(17)

in which λ – is the Lame constant:Eν.
(1 + ν )(1 − 2ν )

(10)

λ=

(11)

These three methods described above will becompared to the measured vibration amplitude of the
shaker on site.
175

(18)

GEOMATE- Brisbane, Nov. 19-21, 2014

VIBRATION AMPLITUDES OF THE SOIL
SURFACEthe material absorption
determined by:

In this article only the vertical vibration
amplitudes at the surface will be investigated.
Barkan [1] suggested to distinguish between thenear-field and the far-field.
For the near-field, vertical vibration amplitudes
on the surface may be determined by:.

,coefficient

can

be

(23)

The field test was performed with frequency
f = 24 Hz, therefore, the absorption coefficient hereis α = 0.09 m-1.
The Barkan-Bornitz equation will be used to
predict the vibration amplitudes on the soil surface
in the vicinity of the shaker.

(19)

NUMERICAL SIMULATION
where f 1,s and f 2,s – displacement (compliance)
functions for the surface. Barkan [1] advised to use
displacement functions solved by Shekhter [13].
For the far-field, an assumption was made thatvibrations are caused only by R-waves, giving thefollowing vertical vibration amplitudes:,

The field test was modeled with the Finite
Elements Method (FEM). Plaxis 2D software wasused. A 2-dimensional, axial symmetric model wasbuilt. The used geometry and mesh of the model canbe seen in Fig. 4. The modelled area is 30 m in both
length and depth. Measurement points fordisplacement recording were placed from radiusr = 1.2 m to r = 6.2 m (reflecting positions of thegeophones on the site). The soil is modelled with 15node triangle elements.

(20)

in which k p , k s and k r are P-, S- and R-wave
numbers; g k – function of wave numbers:.

(21)

The distance, where A nf,s = A ff,s is the end of thenear-field and beginning of the far field.
Another method to predict vibration amplitudes
on the soil surface was suggested by Bornitz [14]:

,

where

(22)

is the amplitude of vibration at distance r 0

from the source,is the amplitude of vibration at
distance r 1 from the source, n is the geometrical
damping factor, α is the material absorption
coefficient. The benefit of the Bornitz’s equation islimited, because the vibration amplitude
at theFig. 4

FEM model: geometry and mesh

Elasticity properties defined from the P- and Swave velocity measurements were used for the
calculations. The shaker was defined as a plateelement with axial stiffness EA = 21 GN/m, bending
stiffness EI = 17.5 MN/m and weigth w = 21.94
kN/m/m. The selected weight corresponds to thetotal vibrating mass m tot .
The general force-displacement matrix in Plaxis
2D is based on the following equation:

distance r 0 should be known a priori. However, thesecond part (i.e. exponential part) of the equation
represents the material damping law which will be
used together with Eq. 19 and Eq. 20. In this way thematerial damping will be considered. Based on
Coelho [15] a material damping will be used for peatof D = 1 %.
Furthermore by assuming that, 1) most of thevibrations on the soil surface are caused by R-waves[16], [17], and 2) damping is frequency independent,

,

176

(24)

GEOMATE- Brisbane, Nov. 19-21, 2014

where [M], [C] and [K] are mass, damping andstiffness matrices respectively, {u} is thedisplacement vector (with the first and second
derivatives) and {F} is the force vector.
In Plaxis 2D, the Rayleigh damping is used,
where [C] is a function of the mass and stiffness,
defined by:[C ] = α R [ M ] + β R [ K ] ,the analytical
calculations.

Method(25)

Measured
Reissner
LysmerConfined Elasticity
FEM

Displacement amplitude [μm]

(27)

(28)

Nevertheless, in this simulation there is only
one frequency ω = ω 1 = ω 2 and one damping ratio
D = D 1 = D 2 , therefore Eq. 27 and Eq. 28 can be
simplified and the coefficients can be defined by:

α R = Dω ,βR = D / ω .

also

the

FEM

Amplitude
[μm]
292
293
309
316
302

P/M ratio
[-]
1
1.00
1.06
1.08
1.04

The measured and the predicted vibration
amplitudes can be found in Fig. 5.

(26)

Solving Eq. 26 for two target frequencies andtwo target damping ratios yields:

ω D − ω 2 D1,
α R = 2ω1ω 2 1 22
ω1 − ω 22
ω D −ω D
β R = 2 1 12 22 2 .
ω1 − ω 2

andTable 1 Comparison between the predicted and themeasured shaker vibration amplitudes

in which α R and β R determines the influence of massand stiffness respectively.
The relationship between the Rayleighdamping coefficients and the damping ratio is:

α R + β Rω 2 = 2ωD .

approach

500
450
400
350
300
250
200
150
100
50
0

Measured
Barkan_NF D = 1%
Barkan_FF D = 1%
FEM D = 1%

~0.73 m Near-Field
Far-Field

0Fig. 5
shaker

(29)
(30)

2
4
6
8
Distance from the shaker center axis [m]Vibration amplitudes in the vicinity of the

The P/M ratios between the predicted and themeasured surface vibration amplitudes for the farfield can be seen in Table 2.

In this case, for the vibration frequency
f = 24 Hz, α R = 1.508 and β R = 6.63 ∙ 10-5.

Table 2 Comparison between the predicted and themeasured surface vibration amplitudes

PREDICTIONS AND MEASUREMENTSFirst of all the measured amplitude of the shaker
vibration is compared to the predicted by the
analytical methods. Predicted and Measured
amplitude ratios (P/M) are calculated in order toevaluate how good the predictions are.
Table 1 shows that independently from themethod used for a prediction, the amplitude of the
shaker vibration has been predicted with at least
92 % accuracy. The highest P/M ratio is for theConfined Elasticity approach, which can be
explained by the fact that horizontal deformations of
the soil were neglected. It is also worth to mention
that all methods over-predicted the vibration
amplitude.
Not only the measured amplitudes of the shaker,
but also of the soil surface in the vicinity of the
shaker, have been compared with the predictions ofDistance
[m]
1.2
2.2
3.2
4.2
5.2
6.2

P/M ratio
Barkan-Bornitz
Far-Field
4.2
6.6
8.7
31.4
36.5
48.9

FEM
0.6
0.9
1.0
4.5
5.5
7.2

The near-field of Barkan-Bornitz’s method ends
before the first measurement point (Fig. 5), therefore
only P/M values for the far-field are calculated. The
analytical approach strongly over-predicts thevertical vibrations, this can be due to the fact that the177GEOMATE- Brisbane, Nov. 19-21, 2014[3] Zwanenburg C, “De bepaling van sterkteeigenschappen van veen”, Geotechniek, Vol.
Juli, 2013, pp. 26-32.
[4] Lamb H, “On the propagation of tremors overthe surface of an elastic solid, Phil. Trans. RoyalSoc.”, series A., Vol. 203, 1904, pp. 1-42.
[5] Reissner E, “Staionare axilasymmetriche durcheine schuterende Masse erregte Schwingungeneines homohenen elastischen Halbraumes”,
Ingenieur Archiv, Vol 22, Dec. 1936, pp. 381396.
[6] Bycroft GN, “Soil-Structure Interaction at HighFrequency Factors”, Int. J. of Earthquake
Engineering and Structural Dynamics, Vol. 5,
1977 pp. 235-248.
[7] Kruijtzer G, The vertical motion of foundations
and pontoons, Delft: VSSD, Reprinted 2006,
Appendix 1.1.
[8] Hsieh TK, “Foundation Vibrations”, in Proc. Of
inst. Of Civil Engineers, Vol. 22, 1962, pp. 211226.
[9] Lysmer J and Richard FE, “Dynamic responseof footings to vertical loading”, J. of Soil
Mechanics and Foundations Division, ASCE,
Vol. 92 No. SM1, January 1966, pp. 65-91.
[10] Verruijt A, Soil Dynamics. Delft, 2006.
[11] Westergraad HM, “A problem of elasticity
suggested by a problem in soil mechanics: soft
material reinforced by numerous strong
horizontal sheets”, Contributions to the
Mechanics of Solids, Stephen Timoshenko 60th
Anniversary Volume. New York: Macmillan,
1938.
[12] Barends FBJ, “Dynamics of elastic plates on a
flexible subsoil”, LGM-Mededelingen, Vol 21,
1980, pp. 127-134.
[13] Shekhter OY, “Consideration of Intertial
Properties of Soil in the Computations ofVertical Forced Vibrations of Massive
Foundations” NII, Symposium 12, Vibratsii
Osnovaniy y Fundamentov, Moscow, 1948.
[14] Bornitz G, Über die Ausbreitung der vonGroßkolbenmaschinen
erzeugten
Bodenschwingungen in die Tiefe. Berlin:
Springer, 1931.
[15] Coelho BEZ, Dynamics of railway transition
zones in soft soils, PhD Thesis, TU Delft, 2010.
[16] Miller GF and Pursey H, “On the Partition ofEnergy between Elastic Waves in a SemiInfinite Solid”, Proc. Of the Royal Society of
London, Series A, Mathematical and PhysicalSciences, Vol 233, No. 1192, 1955, pp. 55-69.
[17] Macijauskas D and Van Baars S,“Decomposition of measured ground vibrations
into basic soil waves”, in Proc. of the 3rd Int.
Symposium on Computational Geomechanics(ComGeo III), Krakow, Poland, 21-23 August,2013.

method assumes only R-waves in the far-field,
which could have led to misjudge of the destructive
interference caused by body waves.
The FEM results are much better, but still underpredict the vibration amplitudes for the first 3
meters, and over-predicts further away. The weakerdamping just next to the shaker and higher damping
than expected further away from the shaker may be
explained by the fact, that there is less vibration
caused by the Rayleigh waves closer to the shaker
and more vibrations caused by the Rayleigh waves
further away from the shaker. This implies a
different damping per different waves.
CONCLUSIONSThe shaker vibration amplitudes can bepredicted by three analytical approaches: Reissner,
Lysmer and the Confined Elasticity approach and bynumerical (FEM) calculations. The accuracy
depends on the method used for the prediction, andranges from 92% to 100%. This shows that theamplitude of the shaker can be predicted accurately
enough for geotechnical purposes.
The soil surface vibration amplitudes can bepredicted by Barkan-Bornitz’s analytical approachand by numerical (FEM) calculations. The BarkanBornitz’s approach over-predicted the amplitudes
between 4.2 and 48.9 times. The FEM underpredicted the amplitudes for the first three meters
and over-predicted up to 7.2 times for the last threemeters. This shows that the amplitudes of the surface
cannot be predicted accurately.
This confirms the conclusion made by Hölscher
and Waarts [2], that the reliability of man-madevibration prediction methods is disappointingly low.
This shows a demand of more research in the manmade vibration field.
ACKNOWLEDGEMENTS
The authors express their acknowledgments to
Mr. KJ Tromp from the village of Uitdam, whoallowed using his land to perform the vibration
experiments. Also to dr. C Zwanenburg forproviding the geological investigations data of thesite nearby.
REFERENCES[1] Barkan DD, Dynamics of bases andfoundations. New York: McGraw-Hill Book
Company Inc., 1962, Chapter VIII.
[2] Hölscher P and Waarts PH, “Reliability ofvibration prediction and reducing measures”,
Final Report. Delft Cluster, Delft, 2003.

178

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SUBGRADE SUPPORT: A REVIEW OF SHORT-TERM AND LONGTERM PERFORMANCE REQUIREMENTS
Andreas Nataatmadja
Faculty of Health, Engineering and Sciences, University of Southern Queensland, Australia

ABSTRACT
Subgrade performance is a function of a soil's strength and its behaviour under traffic loading. The subgrade
should be stable to prevent excessive rutting and shoving during construction, provide good support forplacement and compaction of pavement layers, keep pavement rebound deflections to acceptable limits, restrict
the development of excessive rutting during the service life of the pavement and minimise effect of changes inmoisture level.
In the case of weak subgrades, a capping layer of some thickness may be placed on top of the subgrade tofacilitate field construction. This paper demonstrates that a semi-infinite effective subgrade stiffness can in fact
be calculated for a combination of a capping layer and a semi-infinite subgrade. Furthermore, this paper
discusses the importance of thickness and quality of capping layer, for both short- and long-term loading
conditions. The recommended capping thicknesses have been benchmarked against the UK and US requirements.
Keywords: Pavement, Subgrade, Capping Layer, Modulus, Elastic Analysis

1,000 passes of a standard axle (single axle load of
80 kN). Note that this requirement is different fromthat of the Illinois Department of Transportation(IDOT) Subgrade Stability Manual [4], which
specifies, through an analytical study, that thefinished subgrade must have a minimum ascompacted CBR of 6% if untreated, or 10% if
treated, and a maximum rut depth of 13.0 mm underconstruction traffic.

INTRODUCTION
During construction, traffic is relatively low andis not as channelised as normal service life traffic.
Nevertheless, because the traffic-generated subgrade
stresses are relatively high during construction, asuitable capping material of an appropriate thickness
may be placed on top of the natural subgrade toprovide a stable foundation upon which pavement
layers can be compacted. The capping layer (orworking platform) itself may consist of several
materials/layers. In this case, the effective (i.e.
combined) strength of the subgrade and its capping
layer can be used for the design of flexible
pavements.
In the United Kingdom, for many years
pavement foundations had been designed andconstructed using established empirical relationships
and a recipe specification [1]. The capping
thicknesses vary from 0 mm to 600 mm (Fig. 1).
However, irrespective of the thickness, theprocedure assumes that all foundations achieve asimilar minimum level of performance, and hence,
are treated equally. A draft interim replacement
specification offering 4 foundation types [2] iscurrently available but will not be discussed in thispaper due to some technical differences [3].
Figure 1 was based on the assumption that acapping layer with as-compacted CBR value greaterthan 15 would provide an adequate platform forconstruction of the subbase when compacted to theappropriate thickness.
The capping thickness from Figure 1 was used in
the UK to limit the permanent deformation causedby construction traffic to a maximum of 40 mm for

Fig. 1

Example of capping thickness requirementin the UK [1].

Figure 2 shows the IDOT’s minimum capping
thicknesses on top of subgrades of varying CBR
179

GEOMATE- Brisbane, Nov. 19-21, 2014

values. It is seen that despite the differences in theirperformance criteria, both the UK and IDOT
methods yield similar thickness requirements. In thefollowing sections, the choice of CBR and thickness
for the design of a capping layer and the associatedconstruction issues will be reviewed and discussed.

•

Fig. 2

Fig. 3•IDOT’s capping thickness requirements [5].

STRUCTURAL
CAPPING LAYERCONTRIBUTION

whereApplication of subgrade equivalency basedon the Japan Equation [6].

OF
Figure 4 shows the required capping thickness
according to the Japan Equation to achieve aneffective CBR of 6% for original subgrade CBRvalues of 1% to 6%. The capping materials shown inthis figure have CBR between 8% and 15%. It isseen that for an original subgrade CBR of 2%, 750
mm thick capping layer of CBR 8% would beneeded to produce an effective semi-infinite CBR of
6%. It will be shown later in this paper that such athickness is insufficient if material anisotropy is
considered.

Clearly, given an appropriate thickness, theexistence of a capping layer with a stiffness higher
than that of the in situ subgrade would increase theeffective stiffness of the subgrade. However, thiseffective stiffness cannot be assumed to be equal to
the stiffness of the capping layer unless the capping
layer is of a significant thickness.
A recent study [6] demonstrated that when two
or more elastic layers are placed one on top of
another, such as a capping layer on top of a subgrade,the layers will work together in such a way that they
can be represented by an equivalent layer with aneffective or combined modulus (E e ) based on thework of Odemark [7]: ∑n h E 1/3 i i 
Ee= f × 1 n ∑h 
 1 i 

Both the original structure and the transformed
structure have the same stress & strain
distribution (f = 1); andThe existence of a semi-infinite subgrade
thickness is ignored, i.e. only 1 metre total
depth is considered (Fig. 3). In other words,
the effect of applied stress is assumed to be
negligible below this depth. This is an
assumption that may be acceptable fordesigning concrete pavements but is erroneousin the case of flexible pavements.

3(1)

E i = modulus of layer i (MPa)h i = thickness of layer i (m)f = correction factor

Fig. 4This equation is known as the Japan Equation in
the Austroads Guide Part 2 [8], where CBR i replaces
E i , with f =1 and Σ h i = 1 metre. The Japan Equation[9] implicitly assumes the following condition:•
All layers are isotropic and have the same
Poisson’s ratio;

Thickness of capping layer from the Japan
Equation to obtain an effective semi-infinite
CBR of 6% [6].

ODEMARK’S METHOD WITH CORRECTION
FACTOR
It has been shown above and also in [6] that theJapan equation (Eq. 1 above with f = 1 or Eq. 25 of180

GEOMATE- Brisbane, Nov. 19-21, 20141[8]) has a number of limitations. Therefore, theequation should not be used in the design of flexible
pavements.
Attempts have been made to find a correction
factor for the Odemark equation based on themethod of equivalent surface deflection [6], [10].
The method of equivalent surface deflection isbased on the premise that if a correct thickness of a
capping layer of a certain CBR value is used over a
subgrade with a certain CBR value, the two layer
system can represent a semi-infinite subgrade with asingle design (effective) CBR [10].
In accordance with the current Austroads
mechanistic pavement design procedure, theprevious study [6] assumed both capping layer andsubgrade soil were cross-anisotropic with E V /E H = 2.
The Poisson’s ratio was assumed 0.45 for both thecapping and subgrade layers. Sublayering of the
capping was also done according to [8].
As reported earlier [6], the load chosen for the
analytical work was a half-axle configuration with
550 kPa tyre pressure rather than 750 kPa since it isconsidered that the lower pressure would be more
appropriate to represent the stress regime at the
subgrade level. CIRCLY analyses were carried out
to find the thickness of capping layer that canconvert a subgrade with lower CBR values to an
equivalent half-space CBR of various values for thesame magnitude of surface deflection (i.e. method ofequivalent deflection) under the centre of a dual
wheel assembly.
The authors of [6] observed that the f values in
Eq. (1) are variable, which support the results of [11].
When the ratios between effective CBR overoriginal subgrade CBR are plotted against the fvalues, it becomes clear that f varies with the ratio
between effective CBR to the original, semi-infinite,
subgrade CBR. The following equation was
suggested for finding the correction factor f for a
capping thickness of up to 1.0 m (i.e. practical limit)
and capping CBR values of up to15%: CBRe 
f = 1.5251−0.5251×  CBRs  CBRe  3 −CBR 1 3

s
f 
h =
c

(3)

1

1
CBRc 3 − CBRs 3

Using Eqs. (2) & (3), Figs. 5 and 6 were plottedto show the variation of capping thickness with theoriginal subgrade CBR to achieve an effective CBRof 3% and 5%, respectively, for a maximum capping
layer thickness of 1 m [6].
From Figs. 5 & 6 it can be seen that, theoretically,
the effective (combined) CBR of the capping andsubgrade materials will never be equal to the CBR of
the capping layer unless a capping layer of infinite
thickness is used.

(2)

Fig. 5

Capping thicknesses to obtain an effective
CBR of 3% [6].

Fig. 6

Capping thicknesses to obtain an effective
CBR of 5% [6].

SHORT-TERM PERFORMANCE CRITERIA
where CBR e is the effective CBR and CBR s is theoriginal subgrade CBR.
Equation 1 can be rearranged to produce anequation that can be used to obtain the thickness (h c )and CBR value (CBR c ) of a capping layer (h c < 1.0m and CBR c ≤ 15%) for a nominated CBR e value ofthe capping layer and subgrade (CBR e < CBR c ):During compaction, a maximum Benkelman
beam deflection of 1.2 mm to 1.3 mm is oftenprescribed at the top of the subgrade layer to enableproper placement of the overlying layers. It can beshown analytically that this criterion correspondswith a minimum in situ CBR of 6% (see also Fig. 7).

181

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 7

original subgrade, there is a possibility that the
capping layer itself may not be strong enough towithstand construction traffic if the as-compacted
CBR is less than 15%. Often it has to be either
partially or fully replaced with a more suitablematerial or chemically modified during theconstruction.
Previous investigators [4] suggested that during
compaction of a subgrade layer, the maximum
deviator stress should be less than 75% of thesubgrade’s unconfined compressive strength. Highsubgrade deviator stresses (σ DEV ) and Subgrade
Stress Ratios (SSR = σ DEV /Q u where Q u is theunconfined compressive strength) indicate high“subgrade rutting potentials” under the wheel load of
construction vehicles or construction equipment (thesame principle applies to the compaction of a
capping layer if it the as-compacted CBR is less than
15%).
Construction vehicles typically have tyrepressure of about 500 kPa but compaction
equipment may apply a much higher pressure in theorder of 1,000 kPa [14]. To protect the subgradefrom failure due to these applied tyre pressure, asufficiently thick capping layer (as-compacted CBR≥ 15%) may be initially placed so that under the fullloading of construction vehicles and construction
equipment the subgrade is not overstressed.
This particular criterion, although most criticalduring compaction, is rarely considered by pavement
designers as it is often assumed to be a part of theearthwork construction and layout. However, if thisrequirement is not satisfied, subgrade failure may
occur during construction such that it would be
difficult, if not impossible, to construct the next
pavement layer.
As suggested by [15], it was assumed that the
subgrade CBR = 0.09 s u (kPa), where s u =undrained shear strength of the subgrade.
Calculations were then performed with a tyrepressure of 750 kPa to find the minimum thicknessof capping layer in order to protect the subgradefrom failure using a multilayer isotropic elastic
computer program CHEVRON (assuming capping
layer CBR of 15%).
Figure 9 shows the calculated capping
thicknesses compared with the UK requirement [1].
For subgrade CBR < 6%, the calculated capping
thicknesses are lower than those of the UK
requirement [1] since anisotropy was not considered.
Overall, this figure suggests that a capping layer
should always be placed on top a subgrade with anin situ CBR < 15%, and that a minimum capping
thickness of 200 mm may be used on top of a

CBR prediction based on Benkelman beam
results [12].

To improve a subgrade in situ CBR say, from 4%
to 6%, a capping layer may be used. If this capping
material is compacted at the correct moisture content,
an as-compacted capping CBR ≥ 15% would
normally be achievable. With this in mind, a 500
mm of this material may be adequate to produce aneffective CBR of 6% according to Eq. (3). However,if the capping material is compacted wet of optimum
or subjected to an adverse moisture regime, the ascompacted CBR could drop to a lower value (Fig. 8)
such that a thicker capping layer would be required.
For example, if the as-compacted capping CBRdrops to 10% due to unintentional wetting, a 750
mm capping layer would be required to improve theoriginal subgrade.

Fig. 8

Example of CBR variation due to moisturevariation [13].

It should be noted that while the use of a capping
thickness of suitable thickness will strengthen the182GEOMATE- Brisbane, Nov. 19-21, 2014

subgrade with an in situ CBR > 8%.

Fig. 9With regards to the possibility of mixing
between a subgrade material and its overlying
aggregate layer, Ref. [17] divides subgrade materials
into four categories based on their CBR values(Table 1). Based on this, it appears that capping
materials should have a minimum soaked CBR of
7%.

Comparison of capping thicknesses.

Figure 9 also shows that there is a significant
difference between the minimum capping thickness
for subgrade protection (initial compaction criterion,
failure stress criterion) and that for satisfying thedeflection test (final compaction criterion, deflection
criterion). The recommended capping thickness tosatisfy both criteria is therefore shown. Considering
the required thickness, in practice it may be difficult
to satisfy the deflection criterion if the in situ
subgrade CBR is less than 3%, unless a much stiffer
capping layer or subgrade stabilisation is used (forwhich additional multilayer elastic analyses will be
required).

Fig. 10 Undesirable interaction between capping
land subbase layers.

LONG-TERM PERFORMANCE CRITERIA
Fig. 11 Loss of aggregate vs. subgrade CBR [16].
The choice of capping material is not only
dictated by pavement construction and pavement
design requirements. During construction, the ascompacted CBR is important; however, forpavement design a soaked CBR is often used. In thelatter, if a capping material with a soaked CBR of
5% is chosen, there may be a risk that the long-term
performance of the pavement could be compromised
due to the possibility that the subbase layer may be
weakened through undesirable interactions (Case 1,
2 and 3) between the two layers (Fig. 10). Note that
Case 3 is not desirable but may have been accounted
for if the subbase is assumed to be soaked during
design.
Reference [16] presented Fig. 11, which shows
the assumed aggregate thickness loss as a functionof subgrade strength. From this figure, it may appear
that the subbase layer is less likely to experienceaggregate loss as long as the capping material has aminimum soaked CBR of 3%. However, it ispossible that the capping material should have aminimum soaked CBR higher than 3% to completely
eliminate the possibility of aggregate loss.

Table 1 Subgrade quality in relation topossibility of interlayer mixing [17].
Subgrade
CBR (%)<3

3-7

7 - 15> 15

theQuality
This material is extremely poor
quality. Substantial mixing will takeplace between the subgrade and thefill material.
Subgrade is generally acceptable foruse in paved roads, but is of poor
enough quality to allow mixing
between the layers.
Subgrade consists of fairly goodquality material which is unlikely to
mix with the overlying material.
Fines may however be carried withany excess pore water into the layer
above thereby reducing the quality of
the upper layer.
Subgrade is of good quality material.

It is interesting to note that Ref. [18] suggested
183

GEOMATE- Brisbane, Nov. 19-21, 2014

that geotextile separator be used for subgrade with
CBR < 3 and for subgrade CBR between 3% and6.5%, the use of a geotextile separator isrecommended. Therefore, without using a separator
the soaked CBR of a capping layer should be ≥ 7%.

Transportation, Department of Civil andEnvironmental Engineering, University of
Illinois at Urbana-Champaign, Urbana, IL
61801, USA, 2009.
[6] Nataatmadja, A, Tao, SY and Chim, K,“Design subgrade CBR for flexible pavements:
Comparisonofpredictive
methods”,
Proceeding 25th ARRB Conference, Perth,
WA, Australia, 2002.
[7] Ullidtz, P, “Pavement analysis, development incivilengineering”,
Vol.19,Elsevier,
Amsterdam, The Netherlands, 1987.
[8] Austroads “Guide to pavement technology part
2: Pavement structural design”, Sydney, NSW,
Australia, 2012.
[9] Japan Road Association, “Manual for asphalt
pavement”, Japan Road Association, Tokyo,
Japan, 1989.
[10] Reddy, MA, Reddy, KS and Pandey, BB,“Design CBR of subgrade for flexible
pavements”, IRC Highway Research Bulletin,
India, 2001, p. 64.
[11] El-Badawy, M and Kamel, MA, “Assessmentof improvement of the accuracy of theOdemark transformation method”, Int. Journalof Advanced Engineering Sciences andTechnologies, 5 (2), 2011.
[12] Lay, MG, “Handbook of road technology”, Vol.
1, Gordon and Breach Science Publishers, New
York, USA, 1990.
[13] Road Research Laboratory, “Soil mechanics
for road engineers”, Department of Scientificand Industrial Research, Road ResearchLaboratory, HMSO, London, UK, 1952.
[14] Garcia, G and Thompson, MR, “Working
platform
requirementsforpavement
construction”, A White Paper Prepared for theTechnical Review Panel, Project IHR-R30,
Upgrade subgrade stability manual, Illinois
Cooperative Highway and Transportation
Research Program, USA, 2003.
[15] Black, WPM, “The calculation of laboratory
and in-situ values of California bearing
capacity data”, Geotech., 11, 1961, pp. 14- 21.

CONCLUSION
This paper has reviewed and discussed the issueof calculating effective semi-infinite subgrade
modulus for the combination of a capping layer anda semi-infinite subgrade. Some empirical methods
for finding the effective semi-infinite subgrade CBR
are presented and their validity examined.
It has been shown that the required thickness of
capping layer is a function of its CBR and thesubgrade in situ CBR. Recommendations havetherefore been presented as to the choice ofminimum capping layer stiffness and thickness,based on a minimum as-compacted CBR value of
15% at the time of compaction, in order to minimise
the subgrade stress and deformation underconstruction traffic. The need to satisfy the
Benkelman beam test criterion has also beenoutlined together with some related construction
issues.
In addition, the need to keep soaked CBR value≥ 7% for the capping layer has been discussed, toavoid the intrusion of the subbase material into thecapping layer or the pumping of capping material
into the subbase layer.
REFERENCES[1] Highways Agency, “Design manual for roads
and bridges”, Pavement Design and
Maintenance, Foundations, DMRB 7.2.2,
HD25/94, HMSO, London, UK, 1994.
[2] Highways Agency, “Design guidance for roadpavement foundations (Draft HD25)”, Interim
Advice Note 73/06 (W) Revision 1, UK, 2009.
[3] Brown, SF and Thom, NH, “Recent
developments in pavement foundation design”,
Proceedings of the 18th International
Conferenceon
Soil
Mechanics
andGeotechnical Engineering, Paris, 2013.
[4] IDOT, “Subgrade stability manual”, Illinois
Department of Transportation, Bureau of
Bridges and Structures, Illinois, USA, 2005.
[5] Tutumluer, E, Debakanta M and Abbas AB,“Characterization of Illinois aggregates for
subgrade replacement and subbase”, Report
FHWA-ICT-09-060, Illinois Center for[16] FHWA, “Task force 25 report”, Department ofTransportation,FederalHighway
Administration, USA, 1990.
[17] TRH, “Structural design of interurban and ruralroad pavements”, Pretoria, South Africa, 1995.
[18] California DOT, “Subgrade enhancement
geosynthetic design and construction guide”,
California Dept. of Transport, USA, 2013.
184

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EVALUATION OF RE-LIQUEFACTION BEHAVIOR OF
SEGREGATED AND UNIFORM SPECIMENS IN HOLLOWCYLINDRICAL TORSIONAL SHEAR TESTSUsama Juniansyah Fauzi1 and Junichi Koseki2
Graduate Student, School of Engineering, The University of Tokyo, Japan
2
Professor, Institute of Industrial Science, The University of Tokyo, Japan

1

ABSTRACTDuring the March 2011 Great East Japan Earthquake Disaster, there were a lot of evidences that sanddeposits can liquefy repeatedly (or “re-liquefaction”) at the same sites after initial liquefaction during previous
earthquake shaking. Unlike most prior studies, uniform and segregated specimens were used in this study.
Uniform specimens were reconstituted by moist tamping and segregated specimens were reconstituted bydepositing sand particles in three layers through water sedimentation. The latter specimen preparation was used
to model a deposit of reclaimed land constructed by dredging and pumping method. In order to study reliquefaction resistance and to examine the effect of segregated layer, undrained cyclic loadings were conducted
on uniform specimens and segregated specimens of the same materials using hollow cylindrical torsional shear
apparatus with the cyclic shear stress ratio, CSR, of 0.10, 0.12, 0.15, and 0.20 while maintaining the specimen
height constant. In addition, the local deformations of specimens were observed by using a special image
analysis technique.
Keywords: Re-liquefaction, Segregation, Water Sedimentation, Katori sand, and Hollow Cylindrical Torsional
Shear

the March 2011 Great East Japan Earthquake
Disaster (M w 9.0), re-liquefaction was observed at a
total of 62 sites in the Kanto region (35 sites arereclaimed land), where past liquefaction occurred
during the 1987 Chibaken Toho-oki Earthquake (M w
6.7). Re-liquefaction was also reported during
September 2010 (M w 7.1), February 2011 (M w 6.2)
and June 2011 (M w 6.2) Canterbury Earthquakes [8].
It was found that sand deposits which had beenliquefied, might be re-liquefied by a futureearthquake even though with smaller amplitude thanthe previous one. In other words, the liquefaction
resistance can decrease after first liquefaction.
Reference [9] is the first researcher who
observed the re-liquefaction phenomenon inlaboratory tests. It was found that liquefaction
resistance decreases if it has been sheared beyond athreshold value. However, a different result was
found using a large shaking table. Liquefaction
resistance increased after first liquefaction eventhough no significant change in the relative density[10]. Later, it was found that mechanical behavior ofsand relies sensitively on pre-strain or stress history.
Reference [11] indicated that the residual strain is amain factor to control the liquefaction resistance in a
subsequent re-liquefaction test. The small preshearing will result in hardening effect by whichliquefaction resistance increase while large preshearing will cause opposite result. Further
investigation revealed that re-liquefaction behaviors

INTRODUCTION
Liquefaction has been studied extensively since
its first comprehensive observation of damage due toliquefaction during 1964 Niigata and 1964 Alaska
Earthquakes, and fundamental advances have been
made in understanding this phenomenon. The seriesof laboratory tests, model tests, field observation,and numerical modeling have led to a series ofpractical procedures for evaluating liquefaction
resistance and estimating its effects [1]. During anearthquake shaking, excess pore water pressure isdeveloped in saturated sandy soil leading to loss ofstrength and stiffness. The excess pore waterpressure then starts to dissipate, generally throughground surface. The densification or reconsolidationaccompanied by volume change occurred which ismanifested by ground settlement [2-3].
Many studies have concluded that liquefaction
resistance may increase with the increase of relative
density such as reported in triaxial apparatus [4] andground improvement projects [5]. However, there
are a lot of evidences that liquefaction can take place
repeatedly in natural deposits and reclaimed land. In
1983, Akita prefecture suffered serious damaged byoverall liquefaction of alluvial sand due to 1983
Nihonkai-Chubu Earthquake (M w 7.7). One month
later, an aftershock with lower magnitude (M w 7.1)
hit the area and caused similar damage byliquefaction [6]. Reference [7] reported that during
185

GEOMATE- Brisbane, Nov. 19-21, 2014

are influenced by the effects of uniformity of void
distribution, inherent anisotropy, induced anisotropy,
and loading direction [12].
One limitation of previous re-liquefaction studies
is the number of liquefaction stages. The number of
re-liquefaction stages that can be performed wasusually limited to two stages. In 2010, Reference[13] conducted liquefaction tests up to five stages
using triaxial apparatus. It was found that therelationship of anisotropy induced in postliquefaction and effects of different loading
directions are not simple enough to be simulated bytriaxial apparatus. One year later, liquefaction tests
up to five stages were conducted by shaking table
tests [14]. The results found that re-liquefaction
resistance is not correlated with relative density orvoid ratio but the coefficient of consolidation, c v , orproxy values such as D 10 2Dr2.8 or D 10 /C U .
Recently, the University of Tokyo has develop a
new laboratory apparatus to study re-liquefaction
behavior called multi stacked-ring shear apparatus.
The results show the pre-shearing history of soil is amajor parameter that influences the re-liquefaction
resistance [15]. However, this apparatus has alimitation. Its rigid metal rings boundary mobilizes
friction in both vertical and circumferential
directions which can affect the behavior during reliquefaction tests. In this paper, undrained cyclic
tests using hollow cylindrical torsional shear
apparatus are conducted. Unlike the tests conductedin multi stacked-ring shear apparatus, the hollow
cylindrical torsional shear apparatus uses latex
membrane.
Furthermore, urban development has speared
into unsuitable ground condition which, for instance,
has loose sandy soil with high ground water table;
hence liquefaction potential is high as well. Since
reclamation became popular, areas of reclaimed land
are prone to liquefaction. Most prior liquefaction
studies have focused their efforts to establish astandard method of specimen preparation by which
homogenous specimens can be formed in order toobtain reliable and repeatable results. However,reclaimed lands constructed by dredging andpumping method are not uniform due to different
sedimentation velocities of soil particles in water. In
this paper, segregated specimen and uniform
specimen were used. Segregated specimen was used
as a model of reclaimed land.
HOLLOWCYLINDRICALSHEAR APPARATUS

pressure was measured by a high-capacity
differential pressure transducer (HCDPT) with acapacity of over 600 kPa. A LVDT (linear variabledisplacement transducer) was equipped to measurevertical displacement. Two potentiometers having
diameter of 3.5 cm (main) and 5.0 cm, respectively
were attached to the loading shaft and the top cap
perimeter to measure the large shear strain. The
measured vertical and shear stress were corrected forthe effects of the membrane force [16].
Vertical Control
SystemPneumatic
Actuator

Servo motor

Pneumatic
Actuator

Servo motor

Rotational
Control System

Potentiometer

LVDT
Cell Pressure

Load
Cell
Potentiometer

Specimen
Do = 20 cm
Di = 12 cm
H = 30 cm

PorousStone

Back Pressure
DPT

Electronic
BalanceFig. 1

Torsional shear test apparatus on hollow
cylindrical specimen scheme.

MATERIAL, SPECIMENAND TEST PROCEDURE

PREPARATION,

Test Material
Katori sand passing through 4.75 mm sieve wasused as test material. Its particles properties havemean grain size (D 50 ) = 0.16 mm, coefficient of
uniformity (Cu) = 1.81, coefficient of gradation (Cc)
= 0.97, G s = 2.65, maximum void ratio = 1.35,
minimum void ratio = 0.92, and fines content of
about 5% [17].
Specimen Preparation

TORSIONAL

Details of this specimen preparation can befound in [17], but a brief description is made here.
An acrylic pipe with length of 100 cm was used toelongate the height of mold for specimen preparation
with water sedimentation (WS). A mixture of soil
and water at a mass ratio of 1:2 was poured into theacrylic pipe using a funnel. The specimen consists ofthree sand layers and two silt layers. In addition, theA hollow cylindrical torsional shear apparatus asshown schematically in Fig. 1 was employed to
conduct undrained cyclic loading. A two-component
load cell having capacities of 15 kN and 0.3 kN.m
respectively, was used to measure both the verticalload and the torque components. The confining
186

GEOMATE- Brisbane, Nov. 19-21, 2014

tests with CSR = 0.2 are shown in Fig. 4 and Fig. 5.
For the image analysis, dots with spacing of 5mm x 5 mm grid were pasted on the outermembrane. A digital camera is employed to observe
the dots movement. Details of this image analysis
technique can be found in [17].

moist tamping (MT) method was used to reconstituteuniform specimen with fines content, fc, about 5%(Fig. 2)

Layer 3

1st Virgin consolidationand liquefaction

300 mm

1.2

Void ratio

Layer 2300 mm1.3

Layer 1(a) Segregated (WS)

2nd Re-consolidation
and re-liquefaction

3rd Re-consolidation
and re-liquefaction

1.1

4th Re-consolidation
and re-liquefaction
5th Re-consolidation
and re-liquefaction

1.0(b) Uniform (MT)

6th Re-consolidation

Fig. 2Illustration of segregated and uniform sandspecimens.

0.9

0

20

40

60

80

100

Effective mean principal stress, p' (kPa)

Test Procedure

Fig. 3Re-liquefaction tests were conducted on hollow
cylindrical specimens having initial height of 30 cm,
inner and outer diameters of 12 cm and 20 cm,
respectively. Prior to application of cyclic load,
specimens were prepared at D r = 18-22%. Double
vacuum method [18] was used during the saturation
process due to large specimen size. Skempton’s Bvalues could be achieved to be greater than 0.96 in
all the specimens. After completion of saturation, thespecimens were consolidated isotropically toeffective stress, σ c ’ = 100 kPa (Dr c = 26.7-27.9%).
The first stage of liquefaction test was conducted
after applying a drained creep loading for 15 min oreven longer. The undrained cyclic loadings wereapplied with constant shear strain rate of 1%/minwith single amplitude shear stress of 10 kPa, 12 kPa,
15 kPa, and 20 kPa (i.e., the cyclic shear stress ratio,
CSR, of 0.10, 0.12, 0.15, and 0.20) while
maintaining the specimen height constant. The firstloading direction was on clockwise direction which
will be hereafter defined to be positive. The
specimens were considered to have been liquefied
when the double amplitude of shear strain, γ DA ,reached 15%. At the end of liquefaction test, theglobal shear strain (γ G ) was resumed to be zero
while maintaining the undrained condition. The
next stages of liquefaction were started by opening
the drainage valve and re-consolidating the liquefied
specimen into the same initial effective stress, σ c ’ =100 kPa. An example of re-consolidation behaviorof segregated specimen is shown in Fig. 3.
The next stages of liquefaction tests wereconducted by following the same procedures as theone described in the first liquefaction test. The
effective stress path and stress-strain behavior ofsegregated specimen during 1st and 2nd liquefaction

Effective mean principal stress-void ratio
relationship during re-liquefaction test ofsegregated specimen with CSR = 0.20.
30

1st Liquefaction
2nd Liquefaction

Shear stress, τ (kPa)

20
10
0
-10
-20
-30

0

20

40

60

80

100

Effective mean principal stress, p' (kPa)

Fig. 4

Effective stress path for
specimen with CSR = 0.20.

segregated30
20

Shear stress, τ (kPa)

1st Liquefaction
2nd Liquefaction

γDA = 15%

10
0
-10

γDA = 15%-20
-30
-12 -10 -8

-6

-4

-2

0

2

4

6

8

10 12

Shear strain, γG (%)

Fig. 5187

Shear
stress-strain
relationshipsegregated specimen with CSR = 0.20.

forGEOMATE- Brisbane, Nov. 19-21, 2014

does not always increase with the increase of
relative density. This observation is consistent withthe results from many previous studies that theincrease of relative density is not the main factor of
re-liquefaction behavior. These figures also show theincrease in relative density of the specimen during
re-consolidation follows a quadratic trend. Suchtrend is different from the observation made in [15]that the increase in relative density follows a linear
trend.

TEST RESULTS AND DISCUSSIONSIn this section, the re-liquefaction behaviors ofKatori sand are explained by experimental andimage analysis results.
Experimental Results
Figure 6 and Fig. 7 show the relationshipbetween the stage of liquefaction and number ofcycles to liquefy and relative density. Figure 8
shows the relationship between relative density andnumber of cycles to liquefy. Figure 9 shows anexample of excess pore pressure generation at eachstage of liquefaction. These figures indicate that theliquefaction resistance can decrease, keep constant,and/or increase in the second stage of liquefaction.
Then, in the third and further stages of liquefaction,liquefaction resistance will increase. Theliquefaction resistance of the segregated specimen
increased gradually but that of the uniform specimen
by moist tamping increased more significantly.

350
Katori, CSR =0.10 WS
Katori, CSR =0.12 WS
Katori, CSR =0.15 WS
Katori, CSR =0.20 WS
Katori, CSR =0.10 MT
Katori, CSR =0.15 MT

Number of cycles to liquefy

300
250
200
150
100
50
0
0

20

40

60

80

100

Relative density, Dr (%)
Katori, CSR =0.10 WS
Katori, CSR =0.12 WS
Katori, CSR =0.15 WS
Katori, CSR =0.20 WS
Katori, CSR =0.10 MT
Katori, CSR =0.15 MT

350

Fig. 8Relative density and liquefaction resistance
relationships.

250
200
100

150

Excess pore pressure (kPa)

Number of cycles to liquefy

300

100
50
0
0

1

2

3

4

5

6

Stage of liquefaction

Fig. 6

Variation of liquefaction resistance witheach stage of liquefaction.

80
60

1st Liquefaction
2nd Liquefaction
3rd Liquefaction
4th Liquefaction
5th Liquefaction

40
20
0
0

40

80

120

160

Number of cycles
120

Fig. 9Relative density, Dr (%)

100
80
60

Image analysis results

40

Katori, CSR =0.10 WS
Katori, CSR =0.12 WS
Katori, CSR =0.15 WS
Katori, CSR =0.20 WS
Katori, CSR =0.10 MT
Katori, CSR =0.15 MT

20
0

0

1

2

3

4

5

6

Figure 10 and Fig. 11 show the distributions oflocal horizontal strain after consolidation (i.e.,
before each stage of liquefaction) for segregated anduniform specimens, respectively. These figures showthat specimens undergo horizontal compression in
the upper layer and expansion in the lower layer
after each stage of liquefaction, suggesting that thediameter of specimen decreases at the top part andincreases at the bottom part. It can be seen from theimage analysis results that, after first stage ofliquefaction, the specimen shapes are not uniform

7Stage of liquefaction

Fig. 7

Pore pressure generation during reliquefaction tests. (Case: segregatedspecimen with CSR = 0.20)

Stage of liquefaction and relative density
relationships.

All the specimens show densification during reconsolidation. However, the liquefaction resistance188

GEOMATE- Brisbane, Nov. 19-21, 2014

anymore. This condition would affect the stress
distribution during the next stage of liquefaction.
εx,L(%)

εx,L(%)

εx,L(%)

γL (%)

γL (%)

γL (%)
30

S-1
S-2
S-3

25

εx,L(%)y (cm)

20

15

10

5

S-1
γG=2.9%

1st

2nd

3rd

S-2
γG=-8.3%

S-3
γG=8.8%

0 10 20 30
Local Shear strain, |γL| (%)

Fig. 12 Local shear strain of segregated specimen
during first liquefaction (Case: CSR = 0.15)

4th

Fig. 10 Local horizontal strain of segregatedspecimen after consolidation (Case: CSR =0.15)

γL (%)

γL (%)

γL (%)
30

S-1
S-2
S-3

25

εx,L(%)

εx,L(%)

εx,L(%)

εx,L(%)y (cm)

20

15

10

5

S-1
γG=1.4%

1st

2nd

3rd

S-2
γG=-7.3%

S-3
γG=7.6%

0 10 20 30
Local Shear strain, |γL| (%)

Fig. 13 Local shear strain of uniform specimen
during first liquefaction (Case: CSR = 0.15)

4th

Fig. 11 Local horizontal strain of uniform specimen
after consolidation (Case: CSR = 0.15)

CONCLUSION

The distributions of local shear strain during thefirst stage of liquefaction for segregated and uniform
specimen (CSR = 0.15), respectively, are shown in
Fig. 12 and Fig. 13. In addition, distribution of thelocal shear strains that are averaged at respective
elevation is also plotted in these figures. In case ofsegregated specimens, at the interface between layer
1 and layer 2 (as defined in Fig. 2), and layer 2 andlayer 3, higher concentration of local shear strain isobserved. Such concentration appeared when theeffective stress reduced close to zero. This behavior
may be caused by a formation of water film whenliquefaction happens. In case of uniform specimens,such concentration of local shear strain is notobserved. However, the deformation of specimens
are not completely uniform.

The re-liquefaction resistance of segregated anduniform specimens of Katori sand were investigatedby undrained cyclic loading tests in hollow
cylindrical torsional apparatus. From the test results,
it was found that liquefaction resistance will notalways increase with the increase of relative density
after re-consolidation. The behavior of reliquefaction of segregated Katori sand at second
stage can be decrease, increase or constant. Afterthat the resistance against liquefaction will increase.
However, the behavior of uniform specimens show
higher resistance after each stage of liquefaction.
The specimen shapes in hollow cylinder apparatus
are not uniform after the first liquefaction. Thiscondition will affect the stress distribution in thespecimen. There are still many behaviors that remain
unclear, such as pre-shearing history, loading
189

GEOMATE- Brisbane, Nov. 19-21, 2014

Observed during the 2010 and 2011 Canterbury
Earthquakes”, Seismological Research Letters,Vol. 82, No. 6, Dec. 2011, pp. 905-918.
[9] Finn WDL, PL Bransby, and DJ Pickering,“Effects of strain history on liquefaction ofsand”, Journal of Soil Mechanic andFoundation, Vol. 96, No. 6, Nov/Dec. 1970, pp.
1917-1934.
[10] Seed HB, K Mori, and CK Chan, “Influence ofseismic history on liquefaction sands”, Journalof Geotechnical Engineering Divisions, Vol.
103, No. 4, Apr. 1977, pp. 257-270.
[11] Ishihara K and S Okada, “Effects of large preshearing on cyclic behavior of sand”, Soils andFoundations, Vol. 22, No. 3, Sep. 1982, pp.
109-125.
[12] Oda M, K Kawamoto, K Suzuki, H Fujimori,and J Sato, “Microstructural interpretation on
reliquefaction of saturated granular soils undercyclic loding”, Journal of Geotechnical andGeo-environmental Engineering, Vol. 127, No.
5, May 2001, pp. 416-423.
[13] Yamada S, T Takamori, and K Sato, “Effects on
reliquefaction resistance produced by changes
in anisotropy during liquefaction”, Soils andFoundations, Vol. 50, No. 1, Feb. 2010, pp. 925.
[14] Ha IS, SM Olson, MW Seo, MM Kim,
“Evaluation of reliquefaction resistance using
shaking table tests”, Soil Dynamics andEarthquake Engineering, Vol. 31, No. 4, Apr.
2011, pp. 682–691.
[15] Wahyudi S, J Koseki, and T Sato,“Characteristics of Re-Liquefied Behavior of
Sand by Means of Image Analysis in StackedRings Shear Apparatus”, Bulletin of Earthquake
Resistant Structure, Vol. 47, Mar 2014, pp. 1526.
[16] Tatsuoka F, S Sonoda, K Hara, S Fukushima,
TBS Pradhan, “Failure and Deformation of
Sand in Torsional Shear”, Soils and Foundation,
Vol. 26, No. 4, Dec. 1986, pp. 79-97.
[17] Fauzi UJ and J Koseki, “Local Deformation
Properties of Segregated Sand Specimen in
Hollow Cylindrical Torsional Shear Tests”,
Bulletin of Earthquake Resistant Structure, Vol.
47, Mar. 2014, pp. 27-36.
[18] Ampadu, SK and F Tatsuoka, “Effects of setting
method on the behavior of clays in triaxial
compression from saturation to undrained
shear”, Soils and Foundations, Vol. 33, No.2,
Jun.1993, pp. 14–34.

direction, and specimen preparation. However, thisstudy has started the study of re-liquefaction
behavior using hollow cylinder torsional apparatus.
ACKNOWLEDGEMENTS
The authors wish to express their sincerest
gratitude to Mrs. Yukika Miyahita, Mr. Seto
Wahyudi, and Mr. Takeshi Sato for their highly
cooperative supports made during the developmentof image analysis technique and during theassembling works of both the mechanical andelectronic components of the testing apparatus.
REFERENCES[1] Seed RB, KO Cetin, RES Moss, AM
Kammerer, J Wu, JM Pestana, MF Riemer, RB
Sancio, JD Bray, RE Kayen, and A Faris,“Recent Advances in Soil Liquefaction
Engineering: A Unified And Consistent
Framework”, Keynote Speaker in Proc. 26th
Annual ASCE Los Angeles GeotechnicalSpring Seminar, pp. 1-71.
[2] Ishihara K, “Evaluation of Settlements in Sand
Deposits Following Liquefaction during
Earthquakes”, Soils and Foundations, Vol. 32,
No.1, Mar. 1992, pp. 173-188.
[3] Tokimatsu K, HB Seed, “Evaluation of
Settlements in Sands due to Earthquake
Shaking”, Journal of Geotechnical Engineering,Vol. 113, No. 8, Aug. 1987, pp. 861-878.
[4] Toki S, F Tatsuoka, S Miura; Y Yoshimi, S
Yasuda; Y Makihara, “Cyclic undrained triaxial
strength of sand by a cooperative test program”,
Soils and Foundations, Vol. 26, No. 3, Sept
1986, pp.117-128.
[5] Mesri G, TW Feng, JM Benak,” Post
densification penetration resistance of clean
sands”, Journal of Geotechnical Engineering
Vol. 116, Issue 7, Jul. 1990, pp. 1095–1115.
[6] Yasuda S and I Tohno, ‘‘Sites of reliquefaction
caused by the 1983 Nihonkai-Chubu
earthquake.’’ Soils and Foundation, Vol. 28,
No. 2, Jun. 1988, pp. 61–72.
[7] Wakamatsu K, “Recurrent Liquefaction Inducedby the 2011 Great East Japan Earthquake
Compared with the 1987 Earthquake”,
Proceedings of the International Symposium on
Engineering Lessons Learned from the 2011
Great East Japan Earthquake, Mar. 2012, pp.
675-676.
[8] Orense RP, T Kiyota, S Yamada, M
Cubrinovski, Y Hosono, M. Okamura, and S
Yasuda, “Comparison of Liquefaction Features

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Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECT OF FIBRE IN CONTROLLING DESICCATION CRACKS IN
CLAY LINER SOILS
Dr. Sobha Cyrus 1and Veena.V2
Professor,Cochin University of Science & Technology, India; 2Research Scholar, CUSAT, India

1

ABSTRACTThe most general method adopted now a days for the disposal of Municipal Solid Waste (MSW) is by land
filling. The desiccation of liner materials is a major factor affecting the performance of compacted clay liner
landfills. This leads to the formation of cracks which provides pathways for moisture migration, increasing thegeneration of waste leachate and ultimately increases the potential for soil and ground water contamination. The
problem of desiccation cracking is encountered when the clay liners are subjected to alternate wetting anddrying, which are due to seasonal variations. The long term effect of these cracks is to reduce the sealing effectof the cover system significantly. Liner materials commonly used include bentonite enhanced sand mixture(BES) and locally available materials, which satisfy the norms as laid down in EPA. In the present study
conducted on samples of BES subjected to alternate wetting and drying, the desiccation cracks has been
quantified using crack intensity factor (CIF).Tests were also conducted on these soil samples amended withdifferent percentages of polypropylene fiber.. For different fiber inclusions,( 0.2%, 0.4 %, 0.6% and 0.8%), 3
cycles of alternate wetting and drying were performed. The behavior of BES for different percentage ofpolypropylene fiber was analysed .The study concluded that the problem of desiccation cracks in liner soils caneffectively be addressed by fiber inclusion.

Keywords: Desiccation, Amendment, Wetting and drying, Crack intensity factor, Digital image processing

without fibers [5]. A model which describes theincrease in tensile strength in terms of fiber
properties, soil properties, and fiber/soil interface
parameters has been developed [4]. Further, it wasobserved that there was definite improvement in theproperties of the liner materials when it was
reinforced with discrete random fibres. As such thedesiccation cracks could be controlled with the helpof fibre reinforcement [3]. Here an attempt is madeto study the formation of desiccation cracks in
Bentonite enhanced sand mixture soils when used asa liner material and containment of cracks with fibre
amendments to BES soils.

INTRODUCTION
The major problem of the day is the solid waste
disposal. Landfills are one of the solutions for thisproblem. The main component of an engineered
landfill is a liner system at the base and sides, aleachate collection facility and a final coversystem.The primary purpose of the liner system is toisolate the landfill contents from the environment
and to protect the soil and ground water from
pollution, originating in the landfill.
Desiccation of compacted clay liners is a major
factor affecting the performance of landfills. Duringcertain stages in the life of landfill, it could be
subjected to seasonal changes, resulting insignificant variation in water content leading to thedesiccation of clay liner material. The developmentof tensile stresses facilitates the initiation of tensile
cracks [2]. Cracks provide pathways for moisturemigration into the landfill which increases thegeneration of waste leachate and ultimately
increases the potential for soil and ground watercontamination [1]. Use of fibres to reduce thedesiccation cracking in liner soils has caught theattention of geotechnical engineers. The fibers
increase the tensile strength of the clay and provide a
ductile behavior that was not present in the samples

MATERIALS
Soils
Bentonite
Commercially available bentonite was used toprepare the BES mixture. The properties ofbentonite used are given in Table 1
Fine sand
The commercially procured sand was dried andthe portion passing through 425μ sieve and retained191

GEOMATE-Brisbane, Nov. 19-21, 2014

in 75μ sieve was used for the study. Earlier
investigators have added sand in different
proportions to bentonite to reduce the volume
change, and have suggested that a combination of
80% sand to 20% bentonite satisfies the liner
requirements. The properties of sand used are given
in Table 2.

Bentonite enhanced Sand (BES)
The application of bentonite is currently the mostaccepted practice for lining purpose. In the study
bentonite sand combination is taken as 20%
bentonite and 80% sand. The properties of BES aregiven in Table 4
Table 4 Properties of BES

Table 1 Properties of Bentonite
Particulars
Specific Gravity
Liquid limit(%)
Plastic limit(%)
Plasticity Index(%)
Shrinkage limit (%)
Grain Size Distribution
Sand (4.75-0.075mm) (%)
Silt size (0.002-0.075mm)(%)

Particulars
Specific Gravity
Liquid limit(%)
Plastic limit(%)
Plasticity Index(%)
Shrinkage limit (%)
Grain Size Distribution
Sand (4.75-0.75mm) (%)
Clay size (<0.002mm) (%)

Bentonite
2.8
293
52
241
9
0

29.4
70.3

Clay size (<0.002mm) (%)

80
20This has been adopted and this liner soil is termed as
bentonite enhanced sand mixture (BES) in this study

Table 2 Properties of fine sandParticulars
Specific Gravity
Effective size D 10 (mm)D 30 (mm)D 60 (mm)Uniformity Co-efficient

BES
2.67
50
25
25
25

Preparation of samples

Sand

In this study, the test specimens were compactedin Standard Proctor mould at their respective dry
density, and 2% above optimum moisture content. In
the preparation of the entire specimen, the air driedsoil was mixed with an amount of water dependingon the optimum moisture content of the soil. All
mixing was done manually and proper care wastaken to prepare homogenous mixture, at each stageof mixing.

2.64
0.15
0.18
0.25
1.67

Polypropylene fibre
Polypropylene is the most common synthetic
material used to reinforce soil. It easily mixes withsoil and has a relatively high melting point whichmakes it possible to place the specimens of the
fibrous soil in the oven and conduct the tests formoisture content. The amendment polypropylene
fibre mesh was supplied by Taian Modern Plastic
Co. Ltd, China. The properties of the fibre as givenby the manufacture, is given in Table 3.

When fibre was used as an amendment, theprescribed content of fibres was first mixed into the
air dried soil in small increments by hand, making
sure all fibres were mixed thoroughly to achieve a
fairly uniform mixture and then the required amountof water was added. Afterwards the soil was sealedin plastic bags and allowed to hydrate for 24 hrs
prior to compaction. The fibre content selected
ranged over 0.2% to 0.8% depending upon the easein mixing and the ‘balling effect’ experienced whenhigher fibre contents were tried.

Table 3 Properties of Polypropylene Fibre Mesh
Particulars
Average Diameter (mm)Acid ResistanceAlkali ResistanceTensile strength (MPa)Melting Point (0C)
Water Absorption (%)

Polypropylene
fibre mesh
0.1
StrongStrong>450
160-170
Nil

METHODS
Drying Procedure
The prepared specimen was then placed in
specially designed drier, Fig 1, which simulate theslow rate of drying that occur in the field, while
maintaining reasonable test time cycle. The test
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GEOMATE-Brisbane, Nov. 19-21, 2014

specimen were insulated on the sides using a thermal
insulating material, so that only the top surface was
exposed to heat and hence drying occurred from top.
Thus the lab drying conditions simulated the field
conditions precisely.

first drying period was kept as 6 days for BES
sample.
In order to determine the duration of wetting
period, dried samples were saturated by ponding
with water. Every two days, soil specimens weretaken from different samples for determination ofwater content from top, middle and base of sample.
The experiments were conducted for 3 wet and dry
cycles. The duration of wetting and drying cycles are
as tabulated in Table 5
Measurement of Cracks
Digital Image Acquisition
The image acquisition was done using a digital
camera HP Photo smart R507/R607 with HP instantshare, 4.23 Mega Pixel. The colour image of thedesiccated sample was taken. Digital image
acquisition is the process by which a continuous
visual scene is converted into a digital image filethat can be saved, interpreted and redisplayed bycomputers.

Fig 1 Photograph of Specially Designed Drier
Drying test was conducted till no significant
decrease in weight of the specimen occurred.
Considering the local climatic condition, a drying
temperature of 400C was selected.

Table 5 Duration of wet/dry cycles
Soil

Saturation Procedure

Bentonite
Enhanced
Sand (BES)

In order to saturate the sample specimen, aspecial arrangement was made. Rubber membrane of
10cm diameter was used. The dried sample alongwith the membrane was wrapped with a thick double
layered plastic sheet of height slightly more than thatof the sample. The top portion of the membrane wasfolded down over the edge of the outer cover. The
bottom end of the sample was sealed to prevent
entry of water from below. The so prepared sample
was ponded with water by keeping them in a tub fullof potable water.

Cycle
No.
I
II
III

No. of days
Drying
Wetting
6
5
5
4
5
4

Development of Computer Algorithm
To obtain numerical information about the cracks
in image, computer image processing algorithms
were developed using MATLAB R2010a.
The RGB images taken by the digital camera are
stored in the computer under the TIFF file format.
The first stage in processing an image is to convert itto a gray scale image. The grayscale image provides
a single value between 0 (black) and 255 (white) for
each pixel in the image.

This arrangement allowed water to enter into thespecimen from top only which simulated the actual
field condition. The membrane helped in preventing
the lateral expansion of soil, allowing expansion
only in the vertical direction

In second stage in crack determination, thegrayscale image is binarized using a direct thresholdmethod. The binarization is performed by setting aparticular grayscale value as a threshold so that all
the pixels that have grayscale values greater than orequal to the threshold value turn to white, while all
the pixels that have grayscale values less than thethreshold turn to black.

Determination of duration and number of Wet/Dry Cycle.
Tests were conducted in BES samples todetermine the duration of drying and wetting
periods. The compacted soil specimens were kept indrier until the weight of the specimen became stable.
The weight of the sample was taken at every 24hrs
interval. It was found that no significant change inweight occurred after 6 days of drying. Hence the

For the crack determined image the total cracked
area can be determined by counting the number ofblack pixels in the image. The total number of black
pixels then is converted into area units using a
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GEOMATE-Brisbane, Nov. 19-21, 2014

defined scale. Counting the number of black pixels
is easily done, either using one of the Matlab matrix
commands or by writing a simple algorithm thatscans through the image row by row and counts thenumber of the encountered black pixels.
The surfacial cracked area was used for thedetermination of Crack intensity factor (CIF) .Crack
intensity factor is defined as the ratio of the cracked
area to the total surface area of the sample.
RESULTS AND DISCUSSIONS(a) Cycle1(b) Cycle 2(c) Cycle 3
Fig.2 Desiccated samples of unamended BES

Compaction characteristics of fibre amended
BES soils
Standard Proctor tests were conducted on
Bentonite enhanced sand mixture (BES) using
various percentage (0.2%,0.4%,0.6% and 0.8%) offibre inclusion The compaction characteristics of thesoils are as given in Table 6. Since there was no
significant change in the values of optimum
moisture content and maximum dry density, theresults without fibre inclusion were used for the
study of desiccation cracks.
Table 6 Compaction characteristics BES with
polypropylene fibre mesh(a)Cycle1(b) Cycle 2(c) Cycle 3
Fig.3 Desiccated samples of BES fibre amended
soils with 0.2% fibre content

BES
Fibre content
(%)
0
0.2
0.4
0.6
0.8

Max dry
density(kN /m3)
17.8
18.0
17.6
18.1
18.4

OMC
(%)
17
17.3
16.8
17.4
17.5

Effect of fibre content on BES(a) Cycle1(b) Cycle 2(c) Cycle 3
Fig.4 Desiccated samples of BES fibre amended
soils with 0.8% fibre content

The investigation of wet –dry cycle was done in
the following sequence: drying of compacted soil,
then wetting to saturation, followed by drying and soon. This sequence can be expected to simulate better
field conditions.

A visual interpretation of the figure shows that at
the end of cycle 2, the surficial cracks haveincreased and the amount of surficial cracks has
decreased in cycle 3.

The desiccation test for alternate wetting anddrying cycles were conducted on unamended BES
and BES with 0.2, 0.4, 0.6 and 0.8 percentage offibre inclusion. The photographs taken at the end ofeach wet/dry cycle for unamended BES, BES with
0.2% and 0.8% fibre inclusion are presented in
Fig.2, Fig. 3 and Fig.4 respectively.

The effect of fibre amendment on BES isrepresented in the form of bar chart for readyreference, Fig.5. It is seen that the CIF increases up
to second cycle and then it falls. The same
phenomena were observed with increase inpercentage of fibre inclusion. This shows that the
maximum shrinkage takes place in the second cycle.

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GEOMATE-Brisbane, Nov. 19-21, 2014

Table 8 Maximum crack depth details of Fibre
amended BES soil for various cycles

Cycle
1
2
3

0.0
0.4
2.4
2.2

Maximum depth of crack (cm)Fibre content (%)
0.2
0.4
0.6
0.8
1.9
2.0
1.4
1.3
2.2
2.1
1.6
1.5
1.2
1.8
1.2
0.8

CONCLUSION
The effects of fibre amendments in containing
desiccation cracks in BES soils were studied. An
attempt was also made to obtain the optimum valueof fibre inclusion. The crack intensity factor and thedepth of cracks were the parameters used for the
study. The study reveals that the value of CIF
decreases from 5.38% without fibre to 1.1% at 0.8%
fibre inclusion in Cycle 3. The depth of crack wasanother parameter considered. It was observed thatthe maximum depth of crack steadily decreases withincrease in percentage of fibre.

Fig.5 CIF with different % of fibre inclusion in BES
for alternate wetting and drying cycles
The data obtained from the analysis ofphotographs of all cycles of desiccated samples offibre amended BES is represented in Table 7.The
observed value shows that, with increase in thepercentage fibre inclusion, the percentage of CIF
decreases. The very same pattern is noticed in all the
3 wet/dry cycles. The CIF decreases from 5.38% to1.1% at 0.8% fibre inclusion in Cycle-3.The
optimum value of CIF, 1.1% is when the percentage
of fibre is 0.8%.

In short, the problem of desiccation cracks in
BES soils can effectively be addressed by fibre
inclusion.
REFERENCES

Table 7 Desiccation crack details of Fibre amended
BES soil for various cycles

Cycle
1
2
3

0.0
5.3
7.55
5.38

[1] Carol J Miller, Hong Mi, and Nazli
Yesiller,“Experimental Analysis of Desiccation
Crack Propagation in Clay Liners ”, Journal of
the American Water Resources Association,34(3), 1998, pp.677-686.
[2] Costa S, Kodikara J, and Thusyanthan N I,
“Modelling of Desiccation Crack Developmentin Clay Soils”, in 12th International Conferenceof International Association for Computer
Methods and Advances in Geomechanics(IACMAG),2008, pp 1099-1107.
[3] Cyrus S and Babu T Jose , “Studies on theDevelopment and Control of Desiccation cracks
in compacted clay liner soils”,.Dyuthi digital
repository, Copyright © 2007-2011 Cochin
University of Science and Technology.
[4] Sami M Rifai, “ Impact of polypropylene fibers
on desiccation cracking and hydraulicconductivity of compacted clay soils”, Ph.D.
Dissertation, Graduate School of Wayne State
University, Detroit, Michigan,2000[5] Shulley, Stacy, Leshchinsky, Dovand Ling, Hoe
I(Corporate Author : Delaware Univ Newark)(1997), “Effects of Short Polymeric Fibers on
Crack Development in Clays’’, DTIC online
information for the defense community

Crack Intensity Factor (CIF)
Fibre content (%)
0.2
0.4
0.6
0.8
5.48
4.33
2.08
1.72
6.54
4.6
3.98
3.59
3.13
1.56
1.15
1.1

The depth of the crack was measured using thinwire gauges. The maximum depth of crack in
centimeter with different % of fibre inclusion in
BES for alternate wetting and drying cycle is given
in Table 8. The maximum depth of crack steadilydecreases with increase in percentage of fibre. Fromthe point of view of depth of crack, the optimum
value of fibre inclusion 0.8.
The study indicates that the CIF and the depth ofcrack decrease with the increase of fibre inclusion.It
is further observed that the maximum value of CIF
and depth of crack occurs during the second cycleand decreases during the third cycle. This may be
due to the self-healing property of the soil.

195

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

CYCLIC BEHAVIOR OF RECYCLED CONCRETE AGGREGATE
IMPROVED WITH LIME AND GYPSUM ADDITION
Wojciech Sas1, Andrzej Głuchowski1 Alojzy Szymański1
Facultyof Civil and Environmental Engineering, Warsaw University of Life Sciences, Poland

1

ABSTRACTIn this paper, study on the use of reclaimed waste in Recycled Concrete Aggregate (RCA) was
conducted. Reclaimed concrete problem has increased over the past decade, due to the replacement old concreteparts, such as rail substructures or pavement curb. The main idea of this article was the introduction of recycledmaterials to pavement engineering, which in Poland were usually deposited on waste landfills. Geotechnicalstudy was undertaken to obtain physical and mechanical properties of RCA
For better understanding of its exceptional behavior under repeated loading, cyclic triaxial test was
conducted in various stages of loading. For the purpose of bearing capacity analysis, uniaxial tests were made.
Moreover, RCA improvement of mechanical properties was proposed. Chemical stabilization with lime andgypsum was undertaken in order to ameliorate mechanical characteristics. While the mechanical stabilization isa cause of aggregates crushing, created fine fraction could be a stabilizing medium. Determination of resilient
modulus M r from repeated loading test for non-stabilized and stabilized material was also presented. The paper
also includes an investigation of possible application of stabilized RCA as subbase in pavement construction.
Keywords: Recycled Concrete Aggregate, cyclic CBR, Stabilization, Lime

These problems eliminate the possibility ofusing RCA as building material in the nearest future.
Many tests conducted nowadays - for example direct
shear test, triaxial tests and uniaxial compression
tests - have shown that RCA is reliable and that thismaterial shown good performance [3].
In case of pavement design it is important toobtain data about material cyclic loading. Among
traditional cyclic triaxial tests, dynamic hollow
cylinder tests are used for this purpose.
Nevertheless, those methods are highly sophisticatedand cannot be applied for such material like RCA.
Applying this apparatus in pavement laboratories is
expensive and simply too complicated.
In order to simplify the tests and shorten theirtime, another manner was proposed. Replacing
empirical methods, such as the CBR test, is thegreatest advantage in utilizing this procedure [4].
Repeated loading CBR or cyclic CBR (cCBR)
methods use common CBR apparatus and similar
procedures to obtain resilient modulus M r ,characteristic for cyclic phenomena.
Resilient modulus is calculated as follows:
𝚫𝚫𝝈𝝈𝑴𝑴𝒓𝒓 = 𝚫𝚫𝜺𝜺𝒅𝒅(1)

INTRODUCTION
Recycled Concrete Aggregate (RCA) is a
product of crushing process of concrete waste leftfrom demolished constructions. Due to developmentof civil engineering and limited place forconstruction sites, old buildings are replaced by new
structures. Such events are the cause of increasingof concrete debris on waste landfill.
In order to stop this unpleasant situation, manystudies on possibility of recycling crushed concrete
were made. In transportation geotechnics, forexample, an application of RCA as subbase andimproved subgrade was proposed. Interesting
possibility of use RCA as noise barrier embankmentis promising [1].
For RCA to be applied in pavement design asparts of road structures, its mechanical properties
need to be described well. Many studies carried out
over past decades, point out with a doubt that as
artificial aggregate, RCA needs special tests in orderfor to obtain accurate strength properties.
Most obvious property which lights out
problem of RCA is the greater angularity withcomparing to natural aggregate. Moreover, surfaceof RCA is much rougher and aggregates display an
unusual build. Voids in RCA are divided into twoparts: accessible for water on surface, termed“surface pores”, and those that are isolated, namely“internal pores” [2]. This occurrence of the voids
results in higher degree of water absorption. This
fact makes existing standards inaccurate for RCA
testing.

𝒓𝒓

where, 𝚫𝚫𝝈𝝈𝒅𝒅 is deviator stress pulse ∆𝝈𝝈𝒅𝒅 = ∆𝝈𝝈𝟏𝟏 −∆𝝈𝝈𝟑𝟑, 𝝈𝝈𝟏𝟏 is major principal stress, 𝝈𝝈𝟑𝟑 = 𝝈𝝈𝟐𝟐 is minor
principal stress, and 𝚫𝚫𝜺𝜺𝒓𝒓 is recoverable or resilient
strain over deviator pulse 𝚫𝚫𝝈𝝈𝒅𝒅 [5].
Pozzolanic compounds which cause the grainscombine with cement cannot be entirely exploitedand part of them can be activated after crushing.
Because of that, efforts to stabilize RCA, by adding
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GEOMATE- Brisbane, Nov. 19-21, 2014

gravel was w opt = 8.67% and maximum dry densityof optimum moisture content was 1.97g/cm3.

lime have been made. Calcium hydroxide induces
reaction with pozzolanic compounds, as well as withsiliceous or aluminous material.
The biggest advantage of using the repeatedloading test is the possibility of gaining data relating
to the permanent strain. This information can beused in the design of to pavement and shallow
foundations [6]. Information about stress levels andperformance of material during cyclic phenomena
can also be obtained.
This knowledge can be better utilized simply
because of ready to use results.
MATERIAL AND METHODS
Material
Tests were conducted on material obtained
from demolished concrete from building demolitionsite. Concrete aggregates were an element of
concrete walls and floor, whose strength classestimated from C16/20 to C30/35. Aggregates werein 100% composed from broken cement concrete.
Grain gradation curve was adopted according toPolish technical standard [7] and placed between
upper and lower grain gradation limits.
For estimation of physical properties, aseries of tests was conducted. The sieve analysis led
to classifying this material as sandy gravel (saGr), in
reference to [7, 8]. Test results are shown in Figure
1. This distribution of particles from 31.5mm to0mm is typical for soils used for subbase andsupport structures.

Fig. 1.

Fig. 2The Proctor test results for sandy gravel.

Methods
After the optimum moisture content has
been estimated, the calculation of peak dry density
ρ ds for tested samples relative density was
performed.
Observations during the Proctor tests showhigh water absorption of the material. Soil wascompacted in three repetitions and registered data
have been different each time. After 24 hours, tests
were repeated on grains conditioned in constantmoisture. After three repetitions, the recurrent
results were obtained.
When marking of material physicalproperties and preparation of the samples weredone, cCBR tests were performed. cCBR method
was based on common CBR test. Main idea behindusing this equipment came from its popularity. On
the other hand, cyclic load triaxial apparatus istreated as an advanced machinery. Long existence of
CBR method and its usefulness in pavement design,
resulted in its worldwide spread. Although formechanistic-empirical design CBR test becomes too
empirical.
By using CBR mould and repeated loading
apparatus, cCBR test method was established. The
main principle of this test approach is to use
standard CBR test procedure as a reference in orderto study the later cyclic loading stage.
As was mentioned above, the first step isstandard CBR test loading to 2.54mm. Afterreaching desired displacement with the use ofplunger, unloading procedure was attempted, withthe use of up to 10% of force obtained at 2.54mm.
Loading and unloading is treated as the first cycle ofcCBR test. Next cycles are determined by maximaland minimal force from the first loading. Test wasParticle size distribution of tested soil.

Results of the Proctor test are presented in
Figure 2. The test was conducted by compaction in
the Proctor mold, whose volume equaled 2.2dm3, byusing standard energy of compaction, equal to
0.59J/cm3. Optimum moisture content for sandy
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GEOMATE- Brisbane, Nov. 19-21, 2014

Figures 3, 4 and 5 present exemplary cCBR test
result. In this case, the tested material is RCA with
6% moisture content, compacted with normal
Proctor energy. Figure 3 presents the relation of plot
axial stress [kPa] to displacement [mm]. Figures 4
and 5 present plot of axial stress and displacement
against time. Cyclic wave propagated in one axis
stress state results in displacement, which is divided
into two components: elastic - recoverable andplastic - irrecoverable displacement. These
constitute the basis of numerous cyclic loading
analyses. Figure 4 presents this phenomenon. At theend of every cycle, difference of displacement
between analyzed test and cyclic test constitute theplastic displacement. Recovered displacements are
represented by a difference between peak maximal
strain and peak minimal strain in one cycle. In otherwords, the total plastic displacement increment is thevalue of minimal strain in each cycle.

carried out with standard 1.27mm/min. velocity.
Number of cycles is determined by the percentage ofplastic strain in one cycle. cCBR method assumes
that the test can be stopped, when 1% or less ofplastic displacement in one cycle will occur.
Amount of the cycles to obtain this condition usuallyoscillates around 50 [9, 10].

Stabilization
Stabilization of non-cohesive soils - especiallycoarse grained soils, with greater content than 50
percent by weight of 75μm grains diameter - isbeneficial, if chemical stabilization could occur.
Improvement can be much higher up to ten times
when compared to untreated material [11].
RCA containing cement could still possess someunreacted pozzolanic compounds. Crushing process
uncovers active pozzolanic compounds and leading
to a reaction. In order to improve this reaction, limeand gypsum addition was undertaken. Lime as a
hydraulic bounder immobilized by pozzolan andproduced calcium silicate hydrate. Moreover,addition of gypsum triggered the increase in
hydration rate due to presence of RCA lime andgypsum, Ca and Al ions, in the mixture [12, 13].
In this study, RCA was stabilized with additionof lime and gypsum in amount of 5% and 0,5%
respectively.
Material was stabilized in optimal moisture
content, which was 8.7% for non-stabilized
aggregate. This capacity was raised up to 10.7% due
to water loses, caused by hydration.
After 50 cycles, the material reached resilient
response to applied load and test was completed.

Fig. 3. Stress – displacement curve from cCBR test.

Fig. 4.Displacement – time curve from cCBR test.

RESULTS

Fig. 5.

Tests conducted on non-stabilized RCA haveshown good performance of this material. During
standard CBR test the CBR value reached from 36%
for material compacted in 4% moisture content
conditions, to 44% for RCA in optimal moisture
content, although important feature of RCA
performance under cyclic loading is characterized bydisplacement. It is easy to notice that the same
penetration of plunger during the first load c is the

Plot of cyclic wave from cCBR test.
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GEOMATE- Brisbane, Nov. 19-21, 2014

same as a tested value of overload to desired rut inpavement engineering in next cycles, but results indifferent plastic displacements. Lower moisture of
RCA causes 3.5mm displacement with optimal
moisture content conditions resulting in 3.0mm
displacement. This phenomenon is clearly caused bydegree of compaction of this material. Figure 2
presents Proctor’s test results and differences of dry
unit weight between 4.5% and 8.7% moisture
content seem to be rather low, but due to theirirregular shape, the grains could reduce righty of
RCA surface and create better conditions to assume
better position of grains in skeleton.
The problem of the RCA righty was observed inprevious studies conducted in this research program.
For example, direct shear tests friction angle resultsfor 4% of moisture content and in optimal moisture
content reached 44º, but in case of 4% moisture
content, apparent cohesion was observed in quantityof 10kPa.
Stabilization process in details is presented infigures 6, 7 and 8. Plots present results of cCBR test
in function of axial stress and displacement on fig. 6.
Figures 7 and 8 present the changing in time ofdisplacement and axial stress respectively.
After 24 hours from stabilization process, cCBR
test conducted on this material presents
improvement in CBR bearing capacity. CBR value
has reached 72% and is 28% higher than results in
optimal moisture content for non-stabilized sample.
During cCBR test, displacement reached during
the 50th cycle equaled 2.47mm during the unloading
phase, which is 0.53mm less than in case of nonstabilized sample. Detailed view is presented on
figure 9.
RCA and especially stabilized RCA exhibit very
resilient response to cyclic loading and thisphenomenon can be observed in first cycles. Figure
10 presents results of cCBR test for stabilized RCA
and an example of the second cycle of cCBR test forsandy clay. This plot picture presents RCA as theelastic displacement to cyclic load. In comparison to
sandy clay tested by cCBR method, unloading pathcame back almost to beginning of load phase insingle cycle. Sandy clay exhibits less resilient
respond. Hysteresis loop did not close after the 50th
cycle, which caused
plastic displacement toincrement.
In case of parallel stabilized and non-stabilized
RCA, samples are more likely to exhibit resilient
response as stabilized RCA, but this phenomenon
occurs in a slighter manner.
These properties result in fast customization ofthis material to new load conditions. Material
recovers its elastic properties in first few cycles, andrut depth in case of pavement engineering will notproceed or growth will be small. Plot of thisphenomenon is presented in figure 10.
The analyzis of plastic displacement for RCA ispresented in figure 11. Average functions of plastic
displacement growth show that for stabilized RCA,
acceleration of plunger penetration will be smaller
than for the non-stabilized RCA.

Fig. 6.

Plot axial stress-displacement from cCBR
test, for stabilized RCA.

Fig. 7.
Plot of cyclic wave from cCBR test forstabilized RCA.

Fig. 8.
Plot of cyclic wave from cCBR test forstabilized RCA.
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GEOMATE- Brisbane, Nov. 19-21, 2014

Stabilization process therefore became reason of
stiffness increase in this material. This statement
came from not only total displacement observation,
but moreover from slope of the hysteresis loop, best
seen in figure 9.
Resilient modulus which cannot be calculated
directly from stress-displacement plot and ispresented on equation (1), needs to be recalculated.
In literature, such recalculation was presented infugure [14]. Equivalent modulus from repeatedloading CBR, which in this case is named resilient
modulus M r , can be obtain as follows:
1.513�1−𝜈𝜈1.104 �Δ𝜎𝜎 ∙𝑟𝑟

𝑝𝑝
𝑀𝑀𝑟𝑟 =(2)∆𝑢𝑢 1.012
where: ν –Poisson’s ratio [-] (in this study 0.35 for
granular materials), Δσ p – change between
maximum and minimum axial stress in one cycle[MPa], r – radius of plunger [mm], Δu – recoverable
displacement in one cycle.
Resilient stimulus for non-stabilized RCA
calculated in this manner is equale M r = 543.2MPa
which is reasonable result [15], and M r = 816.5MPafor stabilized RCA.

Fig. 9.
Plot of last cycles from cCBR test forstabilized and non-stabilized RCA.

CONCLUSION
Results of cCBR test on stabilized and nonstabilized RCA presented in this paper are as
follows:
1. RCA as artificial aggregate behavesdifferent than natural aggregates. Thisphenomenon came from its irregularity andrough surface.
2. Value of M r for non-stabilized samples in
optimal moisture content was 44% and 72%
for stabilized specimen. In case of resilient
modulus, values were as follow: 543.2MPaand 816.5MPa respectively.
3. Displacements due to cyclic loading were
the smallest in stabilized specimens. Nonstabilized samples exhibit higher total
displacement and its value rose with thedecrease of moisture content.
4. Resilient modulus describes resilient
response tested material in one cycle.
Therefore no data about total displacement
is available.
5. Material such as RCA generates resilient
response much faster than, for example,
cohesive soils such as sandy clay.
Mobilization of elastic properties washighest in case of stabilized RCA.
6. Stabilization process demonstrates existenceof free pozzolanic compound in crushedconcrete. Addition of lime and gypsum asstabilization media could trigger hydration
reaction.
7. Future studies should concern estimation ofFig. 10.
Plot of results from cCBR test forstabilized RCA and sandy clay.

Fig. 11.
Averagefunctionsofdisplacement growth from cCBR test.

plastic

200

GEOMATE- Brisbane, Nov. 19-21, 2014

optimal lime, water and gypsum content,evolution of displacements in more than 50
cycles and in other frequencies.

[12] Degirmenci N., Okucu A., Turabi A.,„Application of phosphogypsum in soil
stabilization.”, Building and Environment, Vol.
42 (9), 2007, pp. 3393-3398.
[13] Poon C.S., Qiao X.C., Chan D., “The cause andinfluence of self-cementing properties of finerecycled concrete aggregates on the propertiesof unbound sub-base.”, Waste Management,
Vol. 26(10), 2006, pp. 1166-1172.
[14] Araya A.A., “Characterization of UnboundGranular Materials for Pavements” PhD Delft,
2011.
[15] Arm M., “Self-cementing properties of crusheddemolished concrete in unbound layers: resultsfrom triaxial tests and field tests.”, Waste
Management Vol. 21(3), 2001, pp. 235-239.

REFERENCES[1] Krezel Z.A., McManus K., “Recycled aggregate
concrete sound barriers for urban freeways.”
Waste Management Series Vol. 31, 2000,
pp. 884 - 892.
[2] Yogini S. Deshpande J. Hiller E., „Pore
characterization of manufactured aggregates:
recycled concrete aggregates and lightweightaggregates” Materials and Structures DOI
10.1617/s11527-011-9749-2A[3] Aurstad J., Berntsen G., Petkovic G.
“Evaluation of unbound crushed concrete asroad building material – Mechanical properties
vs field performance.” in Proc. 26th International
Baltic Road Conference, Kuressaare, 2006.
[4] Nazarian S., Pezo R., Picornell M., “Testing
Methodology for Resilient Modulus od BaseMaterials”. Research rep. 1336-1, Center for
geotechnical and Highway Materials Research,
1996 ch. 2.
[5] Taha T. R., Abbiss C.P., Rosyidi S.A.P. Chik
Z., Ismail A. Nayan K. A.M. “Briefing: Studyof the relationship between stiffness parameters
for base materials.” Proceedings of the ICE –Transport. Vol. 165(3), 2011, pp. 159-165.
[6] Frost M.W., Edwards J.P., Fleming P.R.,
Arnold S.J. “Simplified laboratory assessmentof subgrade performance parameters formechanistic design of pavement foundations”
Transportation Research Board, vol. 1913,
2005, pp.77-85.
[7] PN – EN ISO 14688: 2a: Projektowanie
geotechniczne – Część 1: Rozpoznawanie I
badanie podłoża gruntowego.
[8] WT – 4: Mieszanki niezwiązane do dróg
krajowych. GDDKiA.
[9] Sas W. Głuchowski A, Szymański A.,“Determination of the resilient modulus M R for
lime stabilized Clay obtained from repeatedloading CBR tests.” Annals of Warsaw
University of Life Sciences-Land Reclamation,
vol. 44, 2012, pp. 143-153.
[10] SasW.,
Głuchowski
A.,„Metodyka
wyznaczania modułów sprężystości (E i Mr) na
podstawie badania CBR pod obciążeniem
cyklicznym.” Scientific Review – Engineeringand Environmental Sciences, vol. 57, 2012,
pp. 171- 181.
[11] Little D.N., Nair S., “Recommendation Practicefor Stabilization of Subgrade Soils and BaseMaterials.” NCHRP Document no. 144 webonly, 2009.

201

GEOMATE- Brisbane, Nov. 19-21, 2014

USE OF WIRE EXTENSOMETERS FOR MONITORING PAVEMENTPERFORMANCE IN AREAS OF SLOPE INSTABILITY
J. N. Kirjan1,2, D. F. Marks2 and J.S. Shiau1
Faculty of Health, Engineering & Sciences, University of Southern Queensland, Australia; 2Department ofTransport and Main Roads (TMR), Queensland, Australia.

1

ABSTRACT
Geotechnical instrumentation has been widely used as the basis of early-warning monitoring systems that
detect the impending failure of slopes, embankments dams and road pavements. In conjunction with remotewireless data acquisition systems, geotechnical instrumentation provides an invaluable risk management tool andenhances safety for road users. This paper outlines the investigation, design and installation of an instrumentation
system for undertaking near real-time monitoring of a road pavement adjacent to an unstable slope located inCentral Queensland, Australia. The arrangement of the monitoring schedule and alert protocols for the system arealso discussed. The monitoring system provides data that is used to analyse ground movements and provides analarm system to notify personnel of any road surface deformations that may impose a risk to road users. A systemof 3 wire extensometers and a weather station, connected to satellite telemetry was installed on the remote site.
The wire extensometer system provides a unique solution to the requirement for a reliable early-warning systemon remote sites. The proven success and reliability of the system has provided a cost effective alternative to
traditional instrumentation systems for monitoring pavements in the vicinity of unstable slopes.
Keywords: Instrumentation, Early-warning system, Slope instability, Pavements.

as remotely monitored networks of vibrating wire
piezometers.
Over the years, the advancement intelecommunications systems, particularly the mobile
network has paved the way for new and innovative
remote monitoring systems. It is now possible for thecollection of near real-time data anywhere on theplanet. This advancement means that instrumentation
has become a feasible risk management strategy inmanaging road pavement safety and performance inareas of slope instability.
This paper describes the implementation of a nearreal-time early warning system consisting of a
network of wire extensometers coupled with asatellite telemetry system

INTRODUCTION
Slope instability can be one of the major causes ofpremature road pavement failure. These instabilities
have the potential to cause costly damage topavements and property as well as injury or loss oflife. Much research has been undertaken into suitablesystems and methodologies for mitigating the risks
associated with unstable slopes and road pavements.
One such methodology is the installation of
instrumentation in the vicinity of the slope or the
pavement itself. These systems can provide an early
warning to any imminent failures, so remedial action
can be taken.
Reference [1] states that slope stability
monitoring involves selecting certain parameters andobserving how they change with time. The two mostimportant parameters are groundwater levels anddisplacements. Displacements may be characterised
by depth of failure plane, direction magnitude andrate.
There are various types of instrumentation
systems available for measuring the above
parameters. These range from devices that measuresurface movements such as simple survey
monuments, to complex networks of strain gauges
imbedded in the road pavement itself. Devices thatmeasure groundwater levels also range from the very
simple, such as observation bores, to complex, such

SITE HISTORY
During open cut mining operations on the westernwall of the mine, small to large slips have occurred.
The largest being in September 2000, and another in
December 1999. Reference [2] states that the
September 2000 failure appears to have occurred byslipping down a low strength faulted area in thewestern wall of the mine, with sub-horizontal
shearing through approximately 40 m thickness ofrock at the toe of the excavation. Reference [2] also
states that the major factors in the development of therock slide were considered to be the presence and low
strength of material contained in the zone of the202

GEOMATE- Brisbane, Nov. 19-21, 2014

western wall faulted zone, and the elevatedgroundwater pressures in this zone. Additionalpressure relief drain holes were drilled in the lower
west wall as a consequence of the September 2000
failure, and the mine was forced to cut back
operations in this area [2]. It is also a point of interest
that the September 2000 failure was preceded bycracking in the mine haul road.
According to Reference [2], on the evening of 18
July 2005, mine staff reported cracking in the roadpavement, adjacent to the south-west wall. The total
length of this cracking now extends over 100 m of the
roadway, and at the closest point, the crack is only 50
m from the crest of the mine open cut pit (see Fig. 1& Fig. 2). Geotechnical specialists were engaged, andrecommendations were made to immediately seal thecracking and install survey monitoring prisms in thisarea in order to monitor possible ground movements.

themselves, which could possibly compromise theintegrity of the data.
Reference [3] also highlight the shortfalls of theprism survey, and states that to date they havedisplayed a number of deficiencies, including
occasional anomalous readings, significant gaps
between readings (when instruments require repair)and finally, the display of erratic variations (+/- 5 to
10 mm).
In summary, the survey prisms had shown someinsight into the possible mechanism and magnitude ofsurface movements due to the unstable mine slope,and this was enough to warrant further and ongoinginvestigation as there is a significant risk to road users.
However, the prism survey is a somewhat unreliable
method of monitoring in its current condition, so thiswas a major motivation for TMR to investigate morereliable and accurate methods of monitoring the site.
MONITORING SYSTEM DESIGN &INSTALLATION
Several types of instrumentation were consideredas the basis of an early-warning monitoring system.
These included FBG strain sensors, soil strainmeters
and inclinometers. The type of instrument and theinstallation arrangement with respect to dataacquisition and ongoing monitoring were criticalfactors in the selection of an appropriate system.
After careful consideration, wire extensometers
were selected as the basis of the monitoring system as
they had a number of advantages over the instruments
mentioned above, most importantly they could beinstalled without any disturbance to the pavement
surface.

Fig. 1 Location of cracking on the roadway inrelation to the mine.

Wire Extensometers: Operating Principle
The wire extensometer, also known as a linear
displacement transducer, is an instrument whichenables the monitoring of a change in distance
between two points. Typical applications of the wire
extensometer include measurements of large
displacements associated with landslides, monitoringrock-masses and surveying earth faults [3].
The device consists of an enclosure, in which adisplacement transducer is housed. A long cable orwire is attached to the transducer at one end, and isplaced under tension spanning the desired area. The
end of the cable is attached to an anchor. Any
movement between the anchor and the transducer unit
will alter the output signal from the transducer, fromwhich the displacement can be determined.
Reference [3] also state that their device has asensitivity of 0.03 mm, an accuracy of +/- 1 mm anda measurement repeatability of +/- 0.03 mm.

Fig. 2 Cracks on the roadway sealed with bitumen.
Although the survey data gathered from theprisms has provided some evidence that significant
horizontal ground movement may be occurring, a site
visit by TMR personnel highlighted some serious
deficiencies in the installation of the prisms
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GEOMATE- Brisbane, Nov. 19-21, 2014

water ingress inside the pits. A cross-section of the
instrumentation arrangement is shown in Figure 3(below).
It was decided that temperature sensors would
also be installed in the wire extensometer pits in orderto monitor possible effects of thermally induced
strains on the extensometer wires.
In addition, a weather station would also be
included in the installation so accurate rainfall
measurements could be undertaken. This could be
easily connected to the chosen data acquisition
system, therefore it would provide an important partof the early-warning monitoring system. The weather
station selected was the Vaisala WXT520 weather
station.
The telemetry and data acquisition systemselected was a Campbell Scientific CR1000 datalogger coupled with a Hughes BGAN 9502 satellite
modem.
Finally, in order to provide a safe location for thetelemetry and data acquisition system, a custom 8mtall mid hinged pole was designed and fabricated.

System Design
It was proposed that the instrumentation would beinstalled in three locations, two locations spanning
the road pavement, and one location spanning the
projected failure zone extended from the western wallof the mine. Each instrument would span around 35
metres, so this would easily enable the full width ofthe pavement to be monitored.
The instruments spanning the road pavement
would be installed by means of horizontal boring
under the road pavement, terminating at pits at either
end for the anchor and wire extensometer transducer.
The instrument spanning the cracking in the minearea could be installed by excavating a trenchterminating at pits at either end.
Within the pits, concrete filled steel bollards
would be installed extending below the base of thepits in order to provide a solid datum for the sensor
and anchor ends of the installations. Adjustablebrackets were designed and fabricated to allow thetransducer to be mounted as high as possible within
the pits. This is to help protect the devices from any

Fig. 3 Cross-section of instrumentation arrangement.
Installation

Stage 1The various components of the system were
installed in two stages. The first stage involved theground works, including excavation and directional
boring, as well as the installation of bollards, brackets
and communications pits. The final part of this stage
was the installation of the footing cage for the hinged
pole foundation.
The second stage of the installation involved theinstallation of the wire extensometers, weather station
and associated hardware and wiring. The hinged pole
was also installed along with the associated logging
and data transmission hardware.

Before the directional boring could commence,
the locations were marked out carefully. Once the pits
had been marked out, the pits were excavated and thedrilling was undertaken, and the pits, bollards andbrackets were then installed. Each pit was finishedwith concrete edging and lockable steel lids were also
installed on the live end pits.
Stage 2The wire extensometers were then installed alongwith the communications pole and telemetry and data

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GEOMATE- Brisbane, Nov. 19-21, 2014

logging system. During this stage, temperature
sensors were also installed in the pits.
The wire extensometer and temperature sensor
cables were then connected to the data logger. The
devices were then calibrated and a function test wasundertaken. Figures 4, 5 & 6 show selected completed
components of the system.

Fig. 6 Telemetry system showing data logger,
modem, power management and batteries.

DATA ACQUISITION AND PRESENTATION
Fig. 4 Live end completed installation.

Data Acquisition
The following section explains the 5 step
processes involved in transferring the data from the
instrument to the end user.
1.

Data logging

The Campbell Scientific CR1000 logger is
programmed to collect data from the wire
extensometers, weather station and temperature
sensors every hour. The data is stored in the logger’s
memory until an upload is triggered.
2.

Data transmission

Every 3 hours, a relay is triggered to power the
Hughes 9502 satellite modem. The satellite modem isconnected to the CR1000 by a Campbell Scientific
NL120 mounted on the CR1000 peripheral port. The
satellite modem then makes a connection to the server
and transfers data to the server through a File Transfer
Protocol (FTP).
3.

Web server

In the web server, the software utility ‘Cron’ isrunning every minute to check for files that have been
sent to the server. Cron is a software utility used toschedule activities at certain times. If a file is found,
the Cron utility will execute a PHP script on theserver. The PHP script will extract the file andcompare the raw data values with the pre-defined
trigger levels.

Fig. 5 Completed installation showing logger box(bottom), satellite antenna (mid), weather station andsolar panel (top).

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4.

Triggers and alerts

settlement of the pits and conduits after a period ofheavy rainfall. The large data spikes are due tofunction tests undertaken on the devices duringscheduled maintenance.
This plot also displays the trigger level thresholds
for movement recorded by the extensometers, and is
depicted by the red and amber lines on the plot. The
trigger level threshold for the amber alert has been set
at 25mm and the red alert threshold at 100mm. In
addition to movement trigger levels, trigger levels for
rainfall have also been defined. The amber alert
rainfall trigger is set at >50mm and 125mm of rainfall
in any 24 hour period will trigger a red alert.
As explained previously in the data acquisition
process, when either trigger level is reached, SMS
and email alerts will be sent by the system to key
personnel. The actions to be undertaken upon receipt
of alerts are detailed in the Site Emergency
Management Plan. Receipt of an amber alert willprompt an immediate site inspection, and the receipt
of a red alert will initiate an emergency site inspection
a possible road closure.

If any trigger values are found, an email will besent via the SMS Gateway. The SMS Gateway willthen convert the email to a SMS message. Finally, alldata will then be saved to the server where it can beaccessed remotely by registered users.
Data Presentation and Alarm Triggers
Upon successful log-in to the web server, the user
is presented with a page which displays the mostrecent data from the wire extensometers, temperature
sensors and weather station. This page is shown in
Fig. 7.
Data plots for all devices can be accessed by
selecting the appropriate date range through thedevice summary page. As an example, a plot for
device WE2 is shown in Fig. 8 for the specified date
range shown in the top left hand corner. Note that thisplot displays a slight increase in displacement fromlate January 2013. This movement was attributed toFig. 7 Web server summary page showing most recent data for all devices.

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GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 8 Plot of data output from WE2.

CONCLUSIONREFERENCES
The
wire
extensometer
early-warning
instrumentation system has provided a uniquesolution to the risk management of the site. It should
be considered as a viable alternative overconventional types of instrumentation forundertaking monitoring of road pavements or otherstructures which are prone to cracking and failure due
to slope instability.
The fact that the system can be installed without
any disruption to traffic should be considered as a key
advantage of wire extensometers, as well as the easeof setup, access for maintenance and relatively low
cost in comparison to the identified alternatives. The
use of a mid-hinged pole as the base for the systemcommunications is ideal for use in remote locations,
as it provides protection from bushfire and vandalism
while still allowing hassle-free access to the hardware
for maintenance purposes.

[1] Kane, WF & Beck, TJ 2000, Instrumentation
Practice for Slope Monitoring, Engineering
geology practice in Northern California.
association of engineering geologists
Sacramento and San Francisco sections, viewed
31 May 2013,<http://www.iti.northwestern.edu/tdr/publicatio
ns/ipfsm.pdf>.
[2] Coffey Geotechnics 2011a, Report
GEOTGARB00881AA-AG to Department ofTransport and Main Roads, QLD, Coffey
Geotechnics.
[3] SISGEO 2011, Wire Crackmeter Datasheet,viewed 17 September 2013,<http://www.sisgeo.com/wpcontent/uploads/201
1/03/D241_EN_01Wire_Crackmeter.pdf>.
[4] Bassett, R 2012, A Guide to Field
Instrumentation in Geotechnics: Principles,
Installation and Reading, Spon Press, NewYork.
[5] Dunnicliff, J 1988, Geotechnical
Instrumentation for Monitoring Field
Performance, Wiley Interscience, Canada.

ACKNOWLEDGEMENTS
The authors would like to thank TMR Northern
Region, in particular Cheryl Ridd, for theopportunity to undertake this project, also the staff
from Geotesta for their ongoing assistance andtechnical support.

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Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

GENERATION AND DISSIPATION OF PORE WATER PRESSURE
NEAR TO PILE AND FAR-FIELD IN LIQUEFIABLE SOILS
Suresh R Dash1, Subhamoy Bhattacharya2, Atul Prabhakaran3 and C. Sreenivasulu4
1
Assistant Professor, IIT Bhubaneswar, India
2
Professor in Geomechanics, University of Surrey, UK
3,4
UG Student, IIT Bhubaneswar, India

ABSTRACTThe degree of liquefaction as characterised by the excess pore water pressure plays an important role in defining
soil strength and stiffness. The pile-soil interaction, if modelled using BNWF model, the strength and stiffness ofthe soil spring can suitably be reduced by using a reduction factor. This reduction mainly depends on the soil type,its SPT/CPT value and the degree of liquefaction. Ideally this reduction should be based on the excess pore waterpressure near the pile. However, it is difficult to estimate the degree of liquefaction near the pile. Hence, the lateralresistance of liqueﬁed soil at soil-pile interface is normally characterized by the degree of liquefaction expected in
the soil at the site without considering the influence of pile.
Though, excess pore pressure near to the pile could be the governing parameter of soil resistance, it is hard tocharacterize the expected value of it in a field condition, as it depends on many parameters including soil type,shear loading, pile dimension, gap formation near to pile that facilitates easy dissipation of EPWP, soil
densification during pile driving, etc. Hence, to understand the difference between the far-field and near-pile
response of liquefied soil, one high quality centrifuge test results are studied in this paper. The pattern of excess
pore water pressure generation and development has been compared for both near-pile and far-field. The results
are critically reviewed and discussed in this paper.
Keywords: Pile foundation, Liquefaction, Pore water pressure, Earthquake

model tests. Several centrifuge tests have also been
carried out by [4] and [5] to study the effect ofstructure on liquefaction potential of the underlying
soil, which showed that the pore water pressure builtup was quicker at free field than below the structure.
Few field cases has also been reported by [6] and [7],which suggest apparent increase in liquefaction
resistance due to the presence of structure. In contrast
to the above observation, Liu and Quio [8] havesuggested that the conditions for liquefaction areworse near to a structure than free field, based on a
back-calculated damage investigation following
Tangshan, China earthquake of 1976.
Although, it is expected that the liquefaction
behavior of soil at far field (i.e., free field behaviour)and near field (close to structure behavior), the exact
difference and their influence is very uncertain anddepends on many site conditions. For pile foundation
design, some researchers suggests to consider zerostrength and stiffness of the liquefied soil [9],whereas, many other researchers [10], [11], believes
that the liquefied soil bears certain strength andstiffness which shall be considered in pile foundation.
The codes of practice of various countries does not
say anything in this regard.
Sticking to any one of the two conditions as listed
above, the design in some cases may become un-

INTRODUCTION
Pile foundations are long slender structuralelements mostly used for foundations in weak soils,
including seismically liquefiable areas. It is routinely
used to support foundations bridges and high risebuildings where the loads are very high and the top
soil is weak.
To define strength and stiffness of liquefied soil,
the degree of liquefaction as characterised by theexcess pore water pressure plays an important role.
The pile-soil interaction, if modelled using BNWF
model, the strength and stiffness of the soil spring cansuitably be reduced by using a reduction factor. This
reduction mainly depends on the soil type, its
SPT/CPT value and the degree of liquefaction.
Ideally this reduction should be based on the excess
pore water pressure near the pile. However, as it isdifficult to estimate the degree of liquefaction near
the pile, the strength and stiffness of the liqueﬁed soil
at soil-pile interface is normally characterized by the
degree of liquefaction expected in the soil at the site
without considering the influence of pile [1].
It is often observed that the excess pore waterpressure close to pile stays lesser that that occurs at
free field for similar shear loading ([2], [3]) in 1g
208GEOMATE- Brisbane, Nov. 19-21, 2014

The scaling parameters related to the centrifuge tests
at centrifugal acceleration of n-g are presented inTable-1.

conservative. For example, while calculating thebuckling strength of pile in liquefiable soil,
considering the strength of liquefied soil as 30% thatof overburden (as per JRA 2000 [12], which specified
the bending calculation due to lateral spreading ofliquefied soil, see Fig. 1) may grossly overestimate
the buckling load, making the design unconservative.
Similarly, when modelling the lateral spreading ofliquefied soil, considering zero strength of liquefied
soil may underestimate the bending moment in pile,as the liquefied soil subjected to very large strain
offers resistance due to particle interlocking.
Hence, it would be prudent to consider thestrength and stiffness of the liquefied soil suitably tomake the design conservative.

Table-1: Scalling laws for centrifuge modelling at
n-g.
Parameters
Unit
Model /
PrototypeStress
ML-1T-2
1
Strain-1
LengthL
1/nTime (Dynamic)T
1/n
Acceleration
LT-2
N
Seepage velocity
LT-1
N
Pile bending stiffness ML-3T-2(1/n)4-1
Natural frequency
T
1/n
A laminar box was used in the test, which had 14
rectangular frames made up of square steel tubes. The
frames were connected by thin linear bearings of
2mm thickness placed in between them. The inside of
the container was lined with a 1mm thick rubber
membrane for waterproofing of the box and to protect
the bearings from soil. The inside dimensions of thebox were 807mm long, 475mm wide and 324mm
high.
Test Layout

Fig. 1

Strength of liquefied soil as suggested by
JRA (2000).

The model scale test setup used here is shown in
Fig 2. For this centrifuge test, two pile groups weremodelled on each side (side A and Side B) of thecentral partition wall. This kind of setup was
beneficial in modelling both pile groups with therequired soil/ structural parameter variation while
keeping all other model parameters exactly same.
In this test setup, the free end quay wall wasmodelled near to one end of the container to simulate
the soil flow condition (i.e. lateral spreading). In eachof the tests, both the pile groups (A and B) were
subjected to nearly identical conditions with respect
to input motions and soil liquefaction.
Steel pipe of outer diameter 10mm and wall
thickness of 0.2mm is used as pile in the test. Fourlayers of soil was placed in the test box, where top
soil (soil-1) was unsaturated and all other three soils
are saturated. The second layer of soil (soil-2) was
prepared as medium loose saturated sand, whichliquefied during the test. The pile was initially fixed
to the bottom of the box. Four layers of soil were thenfilled in the box with required relative densities. The
geotechnical properties of the sand layers areprovided in Table-2.
The model was subjected to a varying magnitude
base acceleration of a 60 Hz sine wave (2 Hz at
prototype scale). The magnitude of base acceleration
was gradually increased to make the liquefaction
process more realistic, which went up to ~8g in 0.25s.
This allowed the soil to liquefy in 5-6 cycles of

Therefore, to understand the difference between
the far-field and near-pile pore water pressure
behavior for pile-soil interaction in liquefiable soils
and its implication in lateral strength of liquefied soil,
a high quality centrifuge test results are studied in thispaper. The pattern of excess pore water pressure
generation and development has been compared forboth near-pile and far-field. The pore water pressure
measured very close to pile is termed as near-pilemeasurement, and the measurements those are done
more than D distance from pile is termed as far-fieldmeasurement, where D is the diameter of the pile. The
results are critically reviewed and discussed in thispaper.
EXPERIMENTAL SETUP OF PILE IN
LIQUEFIABLE SOILS
A high quality centrifuge test data is used in thispaper to study the near and far field pore waterpressure response during seismic vibration.
The centrifuge test was carried out in thecentrifuge facility Shimizu Corporation, Japan. The
tests was carried out at centrifugal acceleration of
30-g. The stress and strain parameters were modelled
by a factor of unity and the linear dimensions by thescale factor of 1: n (model: prototype), where n = 30.
209

GEOMATE- Brisbane, Nov. 19-21, 2014

Acceleration (g)loading in the model. The base acceleration input inprototype scale is shown in Fig 3.
Table 2 Geotechnical properties of the sand used in
the test
Item Soil-1
Soil-2
Soil-3
Soil-4
Soil
SilicaSilicaToyouraSilicaType Sand-8 Sand-8 Sand
Sand-3
e max
1.385
1.385
0.951
0.974
e min
0.797
0.797
0.593
0.654
Dr
50
50
90
90
12.85
7.652
9.908
9.496
γ′
(γ t )
Sr
10
100
100
100
Note: e max and e min = Maximum and minimum
void ratio, D r = Relative Density (%),
γ′ = Effective unit weight (kN/m3), γ t = Dry unit
weight (kN/m3), S r = Saturation Ratio.

0.4

0.4

0.2

0.2

0

0

-0.2

-0.2

-0.4

0

Fig.3

500

1500

1000
Time (s)

-0.4

5

0

10
Time (s)20

15Base acceleration input in the centrifuge test

OBSERVATION OF LIQUEFACTION FARFIELD AND NEAR THE PILE
The near pile pore pressure observation was madebehind the pile during the test. The value of EPWP,
being a stress parameter, remains same for bothprototype and model scale measurement in thecentrifuge test. But, the time axis changes with a scaleof 1 : n (model : prototype). The results here arepresented in prototype scale.
Fig.4 shows the excess pore water pressurerecorded near to the pile and far field for vertical piles(Side-A). It has been observed that the pore waterpressure generation is slower near the pile foundationas compared to far field. The pore water pressure ratio
for these two cases are also plotted in Fig.5. The soil
near to pile took long time (10s) to reach fullliquefaction, whereas the soil at same depth in freefield fully liquefied at in (5s). This could be due to theavailability of dissipation path at the pile-soil
interface, which prevents the built up of pore waterpressure. Hence it takes more time for the soil to fullyliquefy near the pile in comparison with far field.
40

40

Excess pore pres (kPa)Far field (A-PPT1)
Near the pile (A-PPT3)

30

30

20

20

10

10

0

0

-10

-10

Far field (A-PPT1)
Near the pile (A-PPT3)500

0Fig. 4

1000
Time (s)1500

Pore Water Pressure Ratio

Centrifuge test layout for pile foundation inliquefiable soils.

1.2
Far field (A-PPT1)
Near the pile (A-PPT3)

1
0.8

0.5

0.6
0.4
0

0.2
0

-0.5

0

Fig. 5

210

20

15

Comparison of excess pore water pressurenear to the pile and at the far ﬁeld in Side-A
model (Vertical pile group).

1

Fig. 2

10Time (s)

5

0

500

1000
Time (s)

1500

-0.2

0

5

10
Time (s)15Comparison of pore water pressure ratio
near to the pile and at the far ﬁeld in Side-A
model (Vertical pile group).

20

GEOMATE- Brisbane, Nov. 19-21, 2014

40

40
Near the pile (A-PPT3)

50

Excess pore pres (kPa)

Similar behavior has also been observed forinclined pile group (Side-B) as can be seen in Fig. 6.
50

Excess pore pres (kPa)Far field (B-PPT1)

40Near the pile (B-PPT3)40Near the pile (B-PPT3)

30

30

20

20

10

10

0

0

-10

-10

Near the pile (A-PPT3)
Near the pile (B-PPT3)

30

30

20

20

10

10

0

0

-10

0

Fig. 6500

1000
Time (s)

1500

-10

0

Fig-8
Far field (B-PPT1)
Near the pile (B-PPT3)

0

5

10
Time (s)

15

500

1000
Time (s)

1500

0

5

10
Time (s)1520Comparison of excess pore water pressurenear the pile for vertical (Side-A) andinclined (Side-B) pile group.

20

Fig. 9 shows the lateral soil resistance displacement behavior (p-y curves) at different times
during the test. Viewing Fig. 9 in conjunction with
Fig. 4 and 5 shows that the resistance of liqueﬁed soil
subjected to shear was partly attributed from thedecrease in EPWP. This behaviour is similar to thatobserved in the laboratory element tests during
monotonic shearing of liqueﬁed soil, for example:
Yasuda et al., 1999, 1998; Sitharam et al., 2009. In
the initial phase of loading, free field pore waterpressure reached a maximum value (that corresponds
to effective stress = 0) in 3 to 4 cycles. But near to thepile, development of pore water pressure wasdependent on pile vibration, and in each cycle thepore water pressure dissipation was also happening
due to the availability dissipation path at soil-pileinterface.

Comparison of excess pore water pressurenear to the pile and at the far ﬁeld in Side-B
model (Inclined pile group).

The pore water pressure ratio for inclined pilegroup is plotted in Fig. 7 for both near to pile and far
field. It is clearly evident that even at the same depth,
the soil close to the pile could not fully liquefy, but atfree field full liquefaction has been observed. Thereis a slight overshooting of the pore water pressure
ratio above 1. The maximum value of pore waterpressure ratio should be 1, as this corresponds to fullyliquefaction.
Howeverthe observanceofovershooting of this value can be attributed to (1) the
actual effective stress at the measuring location might
be more than the calculated value due todensification, and/or (2) settlement/dislocation ofpore water pressure sensor during the test.

Pore Water Pressure Ratio

1.5
1

Far field (B-PPT1)
Near the pile (B-PPT3)

1

0.8
0.6

0.5

0.4
0.2

0

0
-0.5

0

Fig. 7500

1000Time (s)

1500

-0.2

0

5

10
Time (s)1520Comparison of pore water pressure ratio
near to the pile and at the far ﬁeld in Side-B
model (Inclined pile group).

Fig. 8 compares the excess pore water pressurenear the pile for straight (Side-A) and inclined (SideB) pile group. This figure shows that for inclined pilegroup the pore water pressure generation is slower
than that of vertical pile group. This is because, thepresence of pore pressure dissipation path is smaller
in vertical pile group as compared to longer inclined
path in inclined pile group.
The lateral resistance of soil at pile-soil interface
has been estimated from the strain gauge reading atdifferent depths of the pile. This lateral soil resistancewith respect to soil-pile relative deformation is
generally known as p-y curves. The detailed
procedure of estimating p-y curves for this test can bereferred in Dash (2010).

Fig. 9p-y curves at different time range during test

Though, excess pore pressure near to the pile
could be the governing parameter of soil resistance, it
is hard to characterize the expected value of it in afield condition, as it depends on many parameters
including the soil type, shear loading, pile dimension,
gap formation near to pile that facilitates easy
dissipation of EPWP, densification of the soil close to
pile during pile driving, etc. Hence, the lateralresistance of liqueﬁed soil at soil-pile interface isnormally characterized by the degree of liquefaction
expected in the soil at the site without considering the211

GEOMATE- Brisbane, Nov. 19-21, 2014

influence of pile.
Hence, the lateral strength of liquefied soil (i.e.,
its p-y behavior) has to be suitably chosen to make thedesign safe and conservative.

[3] Yoshimi YK and Tokimatsu K, “TwoDimensional Pore Pressure Changes in Sand
Deposits during Earthquakes”, Proc. 2nd Int.
Conf. on Micro-zonation, National Science
Foundation,” Vol. 2, 1978, pp. 853-863.
[4] Whitman RV and Lambe PC, “Liquefaction:
Consequences for a Structure”, Soil Dynamics
andEarthquake
Engineering
Conf.,Southampton University, Vol.2, 1982, pp- 941949.
[5] Takemura J, Imamura S and Takashi Y,“Stability of Oil Tank Supported by Piled-Raft
Foundation on Liqefiable Sand”, Proc. of Sixth
International Conference on Urban Earthquake
Engineering, March 3-4, 2009, Tokyo, Japan[6] Watanabe T, “Damage to Oil Refinery Plants anda Building on Compacted Ground by the Niigata
Earthquake and their Restoration”, Soils andFoundatio, Vol.15 No.3, 1966, pp. 27-40.
[7] Ishihara K, Kawase Y, Nakajima M,“Liquefaction Characteristics of Sand Deposits
at an Oil Tank Site during 1978 Miyangiken-Oki
Earthquake”, Soils and Foundation, Vol.20,
No. 2, 1980, pp. 97-111.
[8] Liu H and Quio T, “Liquefaction Potential of
Saturated Sand Deposits Underlying Foundationof Structure”, 8th World Conf. on Earthquake
Engineering, Vol. 3, 1984, 199-206.
[9] Bhattacharya S, “Pile instability during
earthquake liquefaction”, PhD thesis, Universityof Cambridge, UK, 2003.
[10] Goh S, O’Rourke TD, “Limit state model for
soil–pile interaction during lateral spread”, Proc.
of seventh US–Japan Workshop on Earthquake
Resistant Design of Lifeline Facilities andCountermeasures against Soil Liquefaction,
Seattle, 1999. p. 237–260.
[11] Abdoun T and Dobry R, “Evaluation of Pile
Foundation Response to Lateral Spreading”, Soil
Dynamics and Earthquake Engineering, Vol.22,
No. 9-12, 2002, pp. 1051–1058.
[12] JRA. Specifications for highway bridges, part V.
Seismic design, 1996.
[13] Dash SR, “Lateral Pile Soil Interaction in
Liquefiable Soils”, PhD Thesis, 2010, Universityof Oxford.
[14] Yasuda S, Terauchi T, Morimoto M, Erken A
and Yoshida N, “Post liquefaction behavior ofseveral sands”, Proc. of 11th European
conference on Earthquake Engineering,
Balkema, Rotterdam, 1998.
[15] Yasuda S, Yoshida N, Kiku H, Adachi K and
Gose S, “A simplified method to evaluate
liquefaction-induced deformation”, Proc. ofEarthquake Geotechnical Engineering, Balkema,
Rotterdam, 1999, pp. 555—566.

CONCLUSION
The response of soil for possible near field and far
field liquefaction of soils is different with variation inboth depth and the spread. Design codes proveineffective in analyzing possible modes of failure
while over estimating other modes. The following
recommendations may be followed for a conservative
design of pile foundations in liquefiable soils.
While estimating the natural time period of thestructure, the pile should be considered an integral
part of the structure with the soil considered as zerostrength at full liquefaction to full non-liquefied
strength at no liquefaction to check the possible
variation of the fundamental time period of thestructure during an earthquake.
Where there is a possibility of the structure’s
natural time period transiting and falling within the
predominant time period of the earthquake, possible
effect of resonance shall be considered in the design.
The liquefied strength shall be considered in such a
way that the worst effect of resonance is observed.
For lateral spreading, loads on the pilefoundations is larger. Thus a representative fractionof the non-liquefied strength can be considered, e.g.,
JRA 2002 code assumes 30% of overburden as thelateral pressure on pile for liquefiable soil flow.
While designing for possible buckling, lateralconfinement is an important parameter and it may beconservatively assumed that liquefied soils offer nolateral resistance.
ACKNOWLEDGEMENTS
The centrifuge data provide by Late Prof. Takashi
Tazoh (Japan) of Shimizu Corporation is greatly
acknowledged.
REFERENCES[1] Rollins KM and Seed B, “Influence of Buildingon Potential Liquefaction Damage”, J. of
Geotechnical Engineering, Vol. 116, No. 2, Feb
1990, pp. 165-185.
[2] Ishihara K and Matsumoto, “Bearing Capacity of
Saturated Sand Deposits during Vibration”, Proc.
4th Japan Earthquake Engineering Symposium,
Tokyo, Japan, 1976, pp-431-438.

212

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

A COMPARATIVE STUDY ON THE RESISTANCES OF BUCKETFOUNDATION IN SAND WITH DIFFERENT INSTALLATIONMETHODS
Ju-Hyung Lee1, Jin-Ung Do2 and Sung-Ryul Kim3
Senior Researcher, Geotechnical Engineering Research Div., Korea Institute of Construction Technology,
Republic of Korea; 2Research Specialist, Geotechnical Engineering Research Div., Korea Institute ofConstruction Technology, Republic of Korea; 3Associate professor, Dept. of Civil Engineering, Dong-A
Univ., Republic of Korea

1

ABSTRACT
Model tests have been performed to investigate the vertical, horizontal and cone tip resistances of bucket
foundations embedded in sand with different installation methods; suction force by pump and jacking force byactuator. Micro-cone penetrometer was used to evaluate the variation of the effective stress inside pile aftermodel pile installation. As a result, in vertical pull-out test, the pile installed jacking force method shows 3 times
larger resistance than installed suction force method. In horizontal pull-out test, the ultimate horizontal capacity
and the slope of load-displacement curve for the model pile installed by suction force were decreased by 22%
and 40% respectively compared to the pile installed by jacking force. In cone penetration test, inside cone tip
resistance of the pile installed by suction force shows about 40% smaller than that installed by jacking force. It isbecause the effective stress was reduced due to upward seepage of inner pile in sand by suction force. Therefore,
we can see that the effect of installation method on bucket foundation has to be considered to investigate thebehavior of it experimentally.
Keywords: Bucket Foundation, Model Test, Vertical Resistance, Horizontal Resistance, CPT

stress [1] (Fig. 1).
The seepage effect helps bucket pile installation
by reducing the penetration resistance during the
installation, on the other hand, reduces the horizontal
and vertical capacity of bucket foundation from thesignificant disturbance at the tip of the bucket
foundation. Due to the complexity and difficulty inquantification of the suction installation effects(including seepage effect), many previous
researchers generally neglect the effect of suction
installation in their experiments. Therefore, in thisstudy, the effects of suction installation on theresistance of bucket pile have been examined.

INTRODUCTION
The suction installation of bucket foundation into
sandy soils induces seepage flow from outside to
inside of bucket foundation; therefore, thedownward seepage near the outside of bucket pie
increases the effective stress while the upward
seepage inside the bucket pile decreases the effective
Total water pumped out of
the bucket

Suctionpressure
Inner wall andat the tip :decreased

Sand

TEST METHOD

Outer wall:
increased

To examine the effect of suction installation on
the vertical and horizontal behavior of a bucket pile,
the model pile was installed both by suction force
and jacking force, respectively. When installed byjacking force, model pile had been penetrated into
the model ground by actuator. When installed bysuction force, model pile had been penetrated by
imposing suction force using venturi pump. In thisregard, the size of model pile, the penetrating depth,
and velocity were controlled equally. The model pile
were made of aluminum pipe with 1.2 mm thickness,
60.0 mm diameter and 180.0 mm length. The size ofused soil chamber is 100 mm width, 100 mm length

Seepage flow

Fig. 1 Effect of seepage gradient on soil effective
stress [1]213GEOMATE- Brisbane, Nov. 19-21, 2014

and 200 mm height. After the model pile installed,
the pull-out test had been performed by using
hydraulic cylinder. A displacement had been
controlled as 100 mm/min [2], [3]. The vertical pullout tests were performed after installation in 0 hour,
2 hours, 20 hours to check the set-up effect. The
loading location of model piles are 67% of L (L =180 mm) from the pile top for the horizontal pull-out
tests.
Joomoonjin sand from the East Sea in Korea
were used in this study (Table 1). For vertical pullout tests, the model ground was formed as 30% of
relative density (D r ) to estimate the resistance inloose state. The model ground of D r 70% was used
for horizontal pull-out tests.
More details of the test program are summarizedin Table 2.

resistances, the initial uplift capacity shows that thepiles installed by jacking force (about 30N) haveabout 3 times larger resistances than those installedby suction force (about 10N).
Also, the pile installed by suction force after
installation in 20 hours indicates about 20% larger
resistance than 0 hour. In general pattern, however,it can be concluded that the set-up effect seems
insignificant in comparison with installation
methods.

Uplift Capacity (N)30

Table 1 Engineering properties of Joomoonjin sand
𝑮𝑮𝒔𝒔

2.62

𝑪𝑪𝒖𝒖

1.43

𝑪𝑪𝒄𝒄

0.9

𝒆𝒆𝒎𝒎𝒎𝒎𝒎𝒎

0.929

𝒆𝒆𝒎𝒎𝒎𝒎𝒎𝒎

0.620

USCS

Verticalpull-out
test
Horizontal
pull-out
test

15
10
5

0

SP
Fig. 3

Dr

Loading
point

Installation
method30%

Pile top

Suction /Jacking

70%

67% ofpile
lengthSuction /Jacking

50

100

150

200

250

300

Displacement (mm)Test results of vertical pull-out resistanceson suction and jacked pile

Horizontal Pull-out Test
Figure 4 shows the experimental results of thehorizontally-loaded suction model piles installed bysuction force and jacking force. The horizontal
loading was placed at 67% from the piles' top
without any loading inclination. In the Figure, theultimate horizontal capacity and gradient (orstiffness) of "horizontal resistance-displacement
curve" of pile installed by suction force wereapproximately 10% and 30% lower than those of
pile installed by jacking force.
S-0.67L by suction force

Horizontal resistance (N)For each test, a miniature cone penetration test
was performed to examine the soil states of insideand outside the bucket pile. The cone penetrometerused in this study consists of 5 mm diameter oflower part and 12 mm diameter of upper part having
micro strain gauge (Fig. 2).

Fig. 220

0

Table 2 Test programs for pull-out tests
Types

S-0hr
S-2hr
S-20hr
J-0hr
J-2hr

25

Micro cone (left) and input / output device(right)S-0.67L by jacking force

L

L

Displacement ( /D)

Fig. 4TEST RESULTS

Horizontal resistance-displacement curvesof bucket piles installed by suction force
and jacking force

Vertical Pull-out Test

Cone Penetration Test

The results have been shown in Fig. 3. When
comparing the maximum vertical pull-out

Like the above result, in cone penetration test
(CPT), the cone tip resistance of the pile installed by214

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 7 represents the additional CPT results of
inside and outside on bucket piles for themeasurement of effective stress difference resulting
from suction force. The solid and dashed lines in the
figure are the CPT test results of the bucket piles
installed by suction force and jacking force,
respectively. The significant difference in CPT
results of the inside and outside of the bucket pile
results from the higher cone resistance due to thehigher confinement inside of the pile wall.

jacking force shows about 50% larger than thoseinstalled by suction force (Fig. 5).

(a)0Cone tip resistance (MPa)
2
4
6
8

0

Inside-Suction pressure
Inside-Jacking force
Outside-Suction pressure
Outside-Jacking force

(b)
(c)

50

(d)

Inside pile

Depth(mm)100

Fig. 5

Cone tip resistances on inside suction andjacked pile300

CPT result

The suction installation effect on the cone
resistances inside of the bucket pile is much greaterthan those outside of the pile. The CPT test results ofoutside on the bucket pile indicated that the cone
resistances at depths of 100 mm and 200 mm of thejacked pile were 2% ~ 15% higher than those of thesuction-installed pile. As also mentioned by [1], thedownward seepage of outside on the bucket pile
within dense sand (relative density approximately
equal to 70%) may not increase the effective stresssignificantly. Contrarily, the cone resistance ofinside on the suction-installed pile was 35% lower
than that inside on the jacked pile. The much lower
cone resistance inside of the suction-installed pile
may be caused from the decreased effective stressinduced by the upward seepage, as also insisted by[1]. The cone resistance at the suction-installed pile
tip was about 33% less than that at the jacked piletip.
It can be inferred that the lower cone resistances
for suction-installed pile compared to those forjacked pile at any depth contribute to the lower
horizontal capacity (about 10% difference as shownin Fig. 4) of the bucket pile. However, more precise

Sand

Fig. 633%

Fig. 7 CPT results of inside and outside on bucket
pile by different installations

Model
pile

(c)

Pile wall
embedment level

Outside pile

250

CPT

(b)

35%

150

200

In case of the pile installed by jacking force,
before the micro cone escapes from the tip of thepile, the cone tip resistance just increased (Fig. 6a).
But in close to the tip of the pile, the cone tip
resistance suffered extremely high confiningpressure by the pile wall (Fig. 6b). Sequentially,
after escaping from the pile tip, the cone tip
resistance rapidly decreased due to relaxation fromhigh confining pressure (Fig. 6c). Lastly, after
penetrating further, the cone tip resistance increased
again due to original model ground (Fig. 6d).
In case of the pile installed by suction force, thepattern of the cone tip resistance were also almost
same as Fig. 6a ~ Fig. 6c. In phase of Fig. 6d,
however, the increase of resistance was not clear.
The reason can be inferred due to the effect ofsuction installation.

(a)

10

(d)

Sequence of micro cone penetration

215

GEOMATE- Brisbane, Nov. 19-21, 2014

and extensive future research is required to identify
the lower horizontal capacity for suction-installed
pile.

Finally, estimating changed friction angle of themodel ground is the goal of this study.
ACKNOWLEDGEMENTS

CONCLUSION
The research presented in this paper was
conducted with funding from the project entitled"Development of Novel Technologies for Low-Costand High Efficiency Bucket piles" at Korea Instituteof Civil Engineering and Building Technology. The
authors acknowledge the financial support from theinstitution.

In this study, the effect of installation methods
on bucket pile has been studied. As a result, theresistances of the pile installed by suction force andjacking force shown obviously different on verticaland horizontal pull-out resistances. This can beinferred because of decrease of effective stresscaused by seepage flow from outside to inside of thepile. Thus, in the test on bucket pile, it can beconcluded that the installation method affect on thebucket pile un-negligibly.
In summary, to examine the actual horizontal
behavior of a bucket pile in sands, suction effect on
the vertical and horizontal behavior of bucket pile
plays an important role. Therefore, bucket piles were
designed to be installed by suction force.

REFERENCES[1] Manh NT (2005), “Installation of Suction
Caisson in Dense Sand and the Influence of Silt
and Cemented Layers”, Ph.D. Thesis, The
University of Sydney.
[2] Bang S, Jones KD, Kim KO (2011), “Inclined
loading capacity of bucket piles in sand”, Ocean
Engineering, 38, pp.915-924.
[3] Coffman RA, Fugro-McClelland Marine
Geosciences, Inc.; El-Sherbiny RM, Rauch AF,
Olson, RE (2004), “Measured Horizontal
Capacity of Suction Caissons”, Offshore
Technology Conference, Houston, Texas
U.S.A., OTC 16161.

FUTHER STUDY
To verify more effect on the installation
methods, it seems necessary more to do test in termsof more detailed relative density, and not only insideresistances, but also outside resistances of the pile.

216

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

OBSERVATION, MEASUREMENT AND ANALYSIS
OF ORIENTED BOREHOLE CORE FOR LOCATING SLIP SURFACESIN FRACTURE ZONE LANDSLIDES IN SHIKOKU, JAPAN
Tsunataka Furuya1 and Jing-Cai Jiang2
1

Graduate School of Advanced Technology and Science, The University of Tokushima, Japan2
Department of Civil and Environmental Engineering, The University of Tokushima, Japan

ABSTRACTThis study employed oriented borehole cores for site characterization of two large fracture zone landslides in
Shikoku, Japan. In situ and laboratory observations, geophysical measurement and digital imaging analysis oforiented borehole cores were performed to determine slip surfaces in the landslides that are in slow movement.
The data obtained from each oriented borehole are (1) a depth distribution of rock quality designation, magnetic
susceptibilities, the Equotip hardness values and wet unit weight of core samples, (2) geometric orientation ofgeologic discontinuities (cracks, joints, etc.), and (3) a depth distribution of numerical color values from digital
imaging of borehole core. It is shown that a clearer change in rock quality designation, the Equotip hardness
value and unit weight, and the orientation of cracks and joints was observed respectively near the slip surfaces,
but the color values clearly varied only in one of the landslides and no change of magnetic susceptibility of coresamples was found at both sites. The results demonstrate that it is capable of locating the slip surface in a
fracture zone landslide by using the above-mentioned methods in combination.
Keywords: Oriented core sample, Slip surface, Digital imaging, Equotip, Magnetic susceptibility, CIELAB model

inference from the contrast in properties between
materials above and below a slip surface and subsurface geophysical techniques [6]-[8]. However,using such methods to find slip surfaces usuallyrequires careful logging of borehole data and certain
experiences and skills [7]-[9].
Most of fracture zone landslides in Shikoku are
distributed in the two geological strips sandwiched
between the three tectonic lines (Fig. 1) [10]-[11].
The fractured state of bedrocks particularly near thetectonic faults and hytrothermal alteration of rockminerals into weaker clay minerals produced highly
favorable conditions for landslides in the region.
Such geological structures together with weatheringof the bedrock minerals result in formation of multilayers of clayey soil in different depth [10]-[11], andthis causes the difficulties in locating slip surfaces
for stationary and slow-moving landslides. Usually,
it is required to use a number of different techniquesin combination for site characterization of landslides
in fractured geologic zones [8]-[9], [12].
This paper employed oriented borehole cores fordetermining slip surfaces in two large fracture zone
landslides in Shikoku, Japan (i.e. the Azue landslide
and the Kashio landslide). In situ and laboratory
observations, geophysical measurement and digital
imaging of oriented borehole core were performed.
It was shown that the slip surfaces in fracture zone
landslides could be located from the data obtainedusing the above techniques in combination.

INTRODUCTION
As a mountainous country, Japan has recognizeda large number of active and potential landslide sites.
These landslides can be divided into three categories,
namely Tertiary type of landslides, facture zone typeand hot spring type [1]-[2]. Shikoku Island in thesoutheast part of Japan has been designated as ahighly landslide-prone region with a large number offacture zone landslides induced primarily due totectonic activities. Many of these landslides are in
relatively slow movement, some of which wererestarted to move rather slowly due to heavy rainfall
after a long term stop [3]-[4]. There also are naturalslopes in Shikoku region that shows clearly landslide
topography but so far there have been no movements
to be observed or/and recorded [4]-[5].
An essential part of the investigation of a landslide is the determination of the depth and geometryof the slip surfaces that characterize it. For moving
landslides the slip surfaces are easily inferred fromdata which can be obtained using surface movement
observations, direct measurements of sub-surface
displacements and geo-acoustic sensing. However, it
is difficult to locate the slip surfaces in stationary
and/or very slow-moving landslides, to which theabove mentioned methods are usually not applicable.
The available techniques for slow-moving landslides
include direct observation of slip surfaces in exploratory and other excavations and in large diameter
boreholes, observations on recovered samples,217

GE
EOMATE- Brrisbane, Nov. 19-21, 2014

igations of thee unstable
Surface and borrehole investig
blo
ock suggest th
hat sliding surrface reaches depths of
up to 50m [14]-[16]. Stabilizazation works carriedcoutrthe moovement of thee landslide maass are theto reduce
con
nstruction of several waterr collection wells in thelanndslide mass for deep draainage. Fig.3 illustrates
thee slip surfacess observed froom the water collection
weells. The slip surface has ddeveloped at oro close tothee interface beetween the str
trong weatherring green
rocck and the unnderlying beddrock. It is sm
mooth andalsso exhibits sttriations or sccratches in thet downslo
ope direction. A thin layer of the slip-su
urface clay
waas formed alon
ng the failure plane where small sizerou
und gravel cou
uld be occasioonally found.
The Kashio landslide is loocated in the south sideof the Sanbagaw
wa geological belt (Fig. 1). This hugede occurred inn fractured roccks consistingg of pelitic
slid(m
muddy) schist and basic schhist. Due to large scale
tecctonic activity, the rocks aro
round the land
dslide area
aree highly fractu
ured and weatthered. Fig. 4 illustrates
plaan view and cross section oof the Kashio landslide.
Th
he average inclination of tthe slope surface is 24
deggrees. The head of the landdslide is locatted at 950
m above sea levvel, and the ttoe is locatedd at 650 m
neaar the Kashio river bed. Thhe slide is diviided into amaain block and two small bllocks in the loower part.
Th
he main block
k slide is strucucturally contrrolled, andocccurred within the weatheredd pellitic (mudddy) schist.
Th
he slide planess are located aat depths of 10
1 to 30 m
deeep for the maiin block.

GEOLOGICAL CHA
ARACTERIS
STICS
Shikooku Island iss divided intoo four stripss ofgeologicaal formations by the threee major faultss ineast-westt direction, namelynthe MedianM
Tectoonic
Line (alsso known ass Chuokozoseen which is thelongest ttectonic fault system in Jaapan and passses
cross Shikoku Island), the Mikabu Tectonic
TLine andL(Fig. 1) [13]. Most off thethe Butsuuzo Tectonic Line
fractured zone landsliddes in Shikok
ku region are ddist Chichibu bbelt
tributed iin the Sanbagaawa belt and the
between the three teectonic lines [10]-[11]. T
The
wa belt is a depositdof meetamorphic roocks
Sanbagaw
consistingg mainly of greengand blacck schist, and the
Chichibuu belt consistinng of the threee sub-belts forrms
a narrow
w strip of thhe Mikabu grreen stone aas ametamorpphic deposit along the tecctonic line itsself.
The rockk type in the Chichibu beltt is sedimen-ttarycomposedd mostly of green schistt, mudstone andconglomeerate [10]-[11]].
The A
Azue landslidde is located in the Chichhibu
geologicaal belt (Fig. 1). This slidee took place jjust
after sloppe failure andd debris flow in the Azue aarea
triggered by the heavy rainfall of typ
phoon Namthheun
in 2004. Fig. 2 showss the slope faailure and debbrisa[14], plann view and crrossflow site in the Azue area
section of the Azue lanndslide. This huge slide bllock
Azue
was fundd just above the main scaarp of the A
debris floow site. Numeerous cracks were
w observedd on
the slopee above the mainmscarp just after the evvent.

Fig. 1 Map
M of Shikok
ku showing m
major tectonic lines,lgeologiccal belts and llocationsof tw
wo landslide siites in fracturee zones (after [13])218

GE
EOMATE- Brrisbane, Nov. 19-21, 2014(a) Plan view of the site of slope faailure and debrris
4]
flow in Azue area [14(a)) Photograph of the wall off an excavated hole forwaater collectionn; (b) Slip surrface with strriations indow
wnslope direcction; and (c) Slip-surface clay
c alongthee failure plane
Fig. 3 Slip surfacessobserrved from the watercollecttion wells in A
Azue landslidee((b) Plan view of the landslid
de blockElevation（ｍ）

850

Se
ection800

BV
V-1 Borehole-1

750

Dep
pth 柱 Soil or状 Rock
(
(m)
図
24
4.00
28
8.10 Soil

700

36
6.00

ce
rfa
su
il p ble
S
ta
rv
ate
W

Green
schistBV-1(a) Plann view of the landslide areaa

650

105
50

Borehole-3
Depth 柱
状
(m) 図
35.00

100
00

600

Soil or
Rock
R

Soil

95
50

100

150

200

3
300

350

40
00(m)

Elevation（ｍ）

50(c)) Cross section of the landsslide block
Fig. 2 AzueA
landslid
de

41.70
Green
schist

45.00

90
00

BV-3

ble
rvta
ate
W

85
50
R

R

p
Sli

e
fac
sur

80
00

75
50

R

R

ODS
METHO

70
00
50

100

150

200

300

350

400

450

500

550

600

650

700

750(m)(b) Cross section of thee landslide bloockFig. 4 Kashio llandslide

ng Oriented CoreC
Obtainin
Oriennted boreholee core providees data wherreby
the geom
metric orientatiion of geologic discontinuiities(joints, faaults, beddings etc.) may bee determined. We
employedd an oriented drilling technnique and douuble
tube sam
mpling systeem [17]-[18]] for obtainningoriented core. As shoown in Fig. 5,
5 the systemm isdrods, ddualcomposedd of three partts: dual tube drillingtube sammpler and a directiondfix rod. Dual tuube

sam
mpling uses two sets of probe rods tot collectconntinuous soil rock cores. O
One set of rodss is driven
into the ground as an outer caasing (tube). TheseT
rods
recceive the driving force fromm the drillingg machine.
Th
he other set of rods are placeed inside the outer
o
tube.
Ou
uter tube rotates and allowss for the remo
oval of thecutttings while inner tube iss fixed with thet inside219

GE
EOMATE- Brrisbane, Nov. 19-21, 2014

qof thee core [17]-[118] and aenssured high quality
carrful measurem
ment of core pieces more than 5cm
lon
ng was carriedd out along thhe base line markedmonthee core, as show
wn in Fig. 6.
WeatheringWgra
ade and discoontinuity descrription
The weatherring/fracture ggrade is a measuremofhow
w the core properties
p(i.ee. strength, mineralogy,metcc.) have been changed froom their origiinal form.
Table 1 shows suggestedsweaathering/fractu
ure gradesandd their associaated descriptioon.
ples
Geeophysical Measurement oof Core Samp
MagneticMsusceeptibility
Magnetic su
usceptibility mmeasures the ‘magnetisabbility’ of a material.
m
In thhe natural env
vironmentaroound a landslide, the magneetisability tells us about
thee minerals that are found inn rocks, particcularly Febeaaring mineralss. It is used too classify diffeerent typesof materials andd to find the suubsurface of a landslide
9]-[20]. In this study, maggnetic suscep
ptibility of[19thee core was coontinuously mmeasured along
g the baseline using a KT--10 magnetic susceptibility
y meter by
Terraplus [21]. Its
I sensitivity is 110-6 SI units witha measurementm
999.910-3
range of 0.000110-3 to 19
SI units and an operatingofreququency of 10 kHz.
k

Fig. 5 D
Drilling/sampling systems fo
or oriented coore
rod and does not rotaate as it is supportedsby thebearings inside of the joint. The dirrection fix rodd isfixed on outer fixing arms and deffines directionn ofwing
the fixed rod together with the inneer tube, allow
us to obtaain oriented coore samples.
Orientedd Core Treatm
ment and Log
gging

Equotip
Evalues for rock harddness assessm
ment
The Equotip
p is an electtronic hardneess testing
dev
vice. It was orriginally desiggned for testinng metals,
butt it has now been used exteensively for teesting rockharrdness [22]-[224]. For the mmeasurement of hardnessof the core, wee used an E
Equotip hardn
ness tester
prooduced by Prroceq with a maximum haardness of940
0 HV and an accuracyaof +44L (+ 0.5%).

The ffollowing stepps are carried out for oriennted
core sampples in laborattory:
1) Conffirm and re-mmark the base line on the ccore
samples sshowing a knoown direction..
2) Cleann the core of drillingd
fluidss or mud in orrder
to obtain clear photo im
mage of the coore outside.
3) Perfoorm observatiion and sketching of the ccore
through thhe full length for visual desscription logs..
4) Deterrmine a new defined param
meter called rrock
quality deesignation, which will be describeddin nnext
section laater.
5) Meassure physical//geophysical properties
pof thecore alonng the base linne, including wet unit weigght,
magnetic susceptibilityy and Equotip values.
6) Photoograph the corre by rotatingg the core sampples
to obtainn oriented, 3600 photo imaage of the ouutersurface of the core. Thhe digital imag
ges such obtaiinedoof ddisare analyyzed later to calculate the orientation
continuitiies and to obtaain color values of the core .

Base line
alongg thecore center

Fig. 6 Base line marked oon the borehole core
Table 1 Weatherring grades annd descriptions
GrradeW1
W

Rock Quuality and Fraacture/Weathhering Gradee

W2
W

Rock Quuality Designaation (RQD)
This pparameter is defineddby summming the lenngth(betweenn natural jointss) of all core piecespmore tthan
5cm longg as a percentaage of the total core length.
Length ( m) of core piecces  5 cm
 1000%RQD (%%) 
Total llength ( m) coree run

W3
W

W4
W

Double tube samplling system useduin this stu
tudy
220

Field iden
entification
Descrip(Rocks)(D
Discontinuities)) tion
Original rock fabric is
Struuctural discontiialmost desttroyed.
nuiities are perceiiRock fabricc is partialn
vedd only between
ly destroyeed and rockinteerface of W1 &Fractureis friable or changed
W22.
structurealmost to a soil.
The originaal fabric of Disscontinuities aree
the rock is visible.
opeen and gravel iss
No clay soil is obser- disp
sposed in crackss
ved in rockks.
aloong joints etc.
Rock may beb slightly Disscontinuities aree
discoloured
d adjacent sligghtly open alonng Crack
to discontin
nuities that beddding joints, etcc. structure
partially exxist in rock.

GE
EOMATE- Brrisbane, Nov. 19-21, 2014

Digital Im
maging Analyysis
uitiesGeometrric orientationn of discontinu
The ooriented, 360 photographs of the outsidee ofthe core are first treaated and dispplayed as a 22-D
uter surface. T
The
image shhowing the coore’s entire ou
images can then be ussed to locate and measure thedip and oorientation off structural features (fractuures,
boundariees between different rock tyypes) in the coore,as shownn in Fig. 7. Thhis operation was
w carried ouut inthis studyy by using the WELL CAD software [25]].
(a) Oriented 360 core andd rotated core image

Color vaalues based onn CIELAB mo
odel
CIELA
AB is an oppponent color system basedd on
the system
m of Richard Hunter calledd L, a, b[26]. T
Thiscolor systtem indicates distinctions betweenblight anddark, redd and green, anda blue and yellow by ussing
numericaal values with three axes: L*, a*, and b*. T
The
L* axis reepresents lighttness whose valuesv
run fromm0(black) too 100 (white). As a color can't
cbe both red
and greenn, or both bluue and yellow
w (because thhese
colors opppose each other), the valuesv
run frrom
positive tto negative onn the a* or b* axis. On thee a*axis, positive values indicate
iamou
unts of red whhile
negative values indicatte amounts off green. On thee b*axis, yelllow is positivve and blue is negative. For
both axess, zero is neuttral gray. Therrefore, values are
only needded for two coolor axes and for the lightnness
or graysccale axis (L*). CIELAB color systemm isdevice inndependent andatherefore become a vvery
popular ccolor model inn practice. We
W used a SPA
AD503 devicce for color measurementmtoo obtain of valluesof L*, a*, and b* of the borehole coree.

b) Calculationn of strike andd dip of planarr fracture(b
Figg. 7 Concept of calculatingg orientation ofo fracture
Results of observationoannd measuremeent of thecorre samples off the Kashio llandslide are illustrated
in Figs. 9 and 10(b). The rocck type is poliitic schist.
Weeathering gradde of the rockss at depth of 3545m
3
isfroom W1 to W44, gradually deecreased, whiile there ishigghly(W1) weaathered muddyy schist abovee the shearban
nd (slip surfacces) around a 441-42m depthh.
The unit weiight is increassed with decreease in theweeathering gradde, ranging frrom 1.62.5 kg/m3 forthee W1-W3 gradde rocks to 2.662.7 kg/m3 forf the W4
graade rocks. Thee decrease in the unit weig
ght may be
cauused by increease of void rratio and water content
duee to grain refining of fractuured rocks. Th
he Equotip
harrness index anda the RQD
D values meaasured arealmmost consisten
nt with the disstribution of unit
u weight,
as shown in Fig. 10(b). A chaange of the coolor values
d a positive peeak value of L* are alsoof a* and b* andund near the shearsband (sslip surfaces). Note thatfousucch a peak of thet color valuues of L* alsoo appeared
at other depths. Rocks abovve and below the shearban
nd can be cateegorized to frracture/crack structures,
resspectively. Disscontinuities aare oriented in a wideran
nge in rocks ofo above and bbelow the slip
p surfaces
butt in a very narrow range inn the vicinity of the slip
surrfaces. No meaningfulmchhange in the magnetic
sussceptibility waas found in thee Kashio land
dslide.

TS AND DISCCUSSIONRESULT
Resullts of observaation and meaasurement of thecores of tthe Azue landdslide are show
wn in Figs. 8 and
10(a). Thhere are highlyy and slightly weathered grreen
rocks aboove and below
w the slip surrface at depthh of
28.2m (Fig. 8), respecttively.
b
24-288m/
Averaage unit weighht measured between
28-36m w
was 2.36 kg/m
m3 and 2.76 kg
g/m3, respectivvely.
The RQD
D defined for thist study incrreased from 442%
above thee slip surface to 92% below
w the slip surfa
face.
A clear cchange in thee Equotip value is also fouund
near the slip surface. Fracture and crack structuuresnd below the slip
are obserrved in the roocks above an
surface, rrespectively. DiscontinuitieD
es are orientedd ina very naarrow range inn the vicinity ofo the slip surfface
but in a w
wide range in other depths. Their inclinattion
is less thaan 50 above the slip surfacce and more tthan
50 for mmost discontinnuities below the slip surfa
face.
Such a cchange in the structural fraactures mightt be
producedd by large shear deformatio
ons along the slip
surface aand weatherinng. From Fig.10 (a) it is sseenthat the mmagnetic suscceptibility andd the color vallues
do not inndicate a meaaningful channge near the slip
surface inn the Azue lanndslide.
221

GE
EOMATE- Brrisbane, Nov. 19-21, 2014

Fig. 8 ObservationO
oof core samplees from Azue landslidelFig. 9 ObservationO
off core sampless from Kashio landslide222

GE
EOMATE- Brrisbane, Nov. 19-21, 2014

Fiig. 10 Resultss of measurem
ment and imagge analysis of the cores fromm Azue and K
Kashio landslid
desetcc.) involved inn the core sam
mples, and (33) a depth
disstribution of numericalncollor values fro
om digital
imaging of boreehole core. It has been indiicated thata clearercchang
ge in rock ququality design
nation, theEqquotip hardness value andd unit weightt, and theoriientation and inclination of discontinu
uities wasobserved respectively near thhe slip surfacees for bothcvalues cclearly varied only nearsitees, while the color
thee slip surface in the Kashioo landslide. In
n addition,
no change of maagnetic suscepptibility of corre samples
nstrate thatwaas found at both sites. The rresults demon
thee data gained from observaation, geophyssical measurrement and digitald
imaginng analysis of oriented
corre samples caan be successffully used to determineslip
p surfaces in fracturefzone llandslides.

Fracctured bed roccks near the teectonic faults andhydrotherrmal alteratioon of rock mineralsm
are themain reassons of fractuure zone landslides in Shikooku,
Japan. S
Such geologiccal condition
ns together w
withweatherinng might resuult in different distributionss ofgeologic discontinuities, rock quaality designatiion,
Equotip hardness, and numerical color valuess inTherocks/soills above andd below a sllip surface. T
informatiion gained froom observatio
on, measurem
mentand digiital imaging analysis off oriented ccore
samples, such as thosee shown in Fig
gs. 8-10, allow
wed
the succeessful determinnation of slip surface depthhs in
fracture zzone landslidees.
USION
CONCLU
Thiss study preseented examples of laborattory
observations, geophyssical measurem
ment and diggitalole core from ttwo
imaging aanalysis of oriented boreho
study sitees in Shikokuu, Japan wherre many fractturezone landdslides are distributed.
dTh
he data obtaiinedfrom eachh site include (1) a depth distribution of rrock
quality ddesignation deefined in this study, magnnetic
susceptibbilities, the Eqquotip hardnesss values and wet
unit weigght of core samples; (2) Orientation andinclinatioon of geologic discontinuitiees (cracks, joiints,

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Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECT OF LAYER THICKNESS AND BLOCK RATIO ON ROCKSLOPES MOVEMENT STYLE
A. K. Alzo’ubi1
College of Engineering, Abu Dhabi University, UAE

1

ABSTRACTIn rock slopes, toppling movements are very common. In such slopes, the layers thicknesses and block ratio
relative to slopes height might determine the type of slope movements and what will be the style of toppling. In
this paper a numerical parametric study has been conducted to evaluate the effect of block ratio and block
thickness, in both crystalline and sedimentary rock, on the style of rock slopes movement in slopes that are prone
to toppling. The mechanical defects or joints of rocks can be either random or well defined sets depends on therock mass origin, metamorphic, igneous, or sedimentary. Different styles of movements were observed
numerically in this study ranging from block toppling to rock falls. The styles of movement were also comparedto the ones observed in the field.

Keywords: Slopes, Sedimentary, Toppling, Bed-Height ratio
observation: block flexural toppling, which ischaracterized by gradual changes in the bedding
orientation within the rock mass; multiple block
toppling, which is characterized by more than one
distinct zone of abrupt change; and block toppling,which is characterized by abrupt changes in theorientation between blocks between the topplingrock mass (the Chevron topple, [3]).

INTRODUCTION
Rock slopes can be divided into two maincategories: structurally controlled slopes, such as theplaner and wedge failures, and the non-structurally
controlled slopes in which rupture surface penetrate
the intact rock to form circular or spiral failuresurface. The structurally controlled slopes normally
fail by shear, sliding along one or more continuous
discontinuities, whereas, in the non-structurally
controlled slopes, failure is a complicated process
and involves failure in both the discontinuity and theintact material [1]. The assumption that single
discontinuity controls the slope failure is a
simplified approach for analyzing rock slopes and isapplicable only for small scale slopes, while forlarge slopes, the continuity has limited validity
unless a fault or any continuous large rock structure
existed prior to failure.
Different modes of toppling movements havebeen observed in the field on both anaclinal andcataclinal slopes. De Freitas and Watters [4]introduced the term “toppling” to describe themovements of rock slopes in rotation with steeply
dipping beds. Goodman and Bray [7] extended thediscussion of toppling mechanisms and showed that
toppling in anaclinal slopes is possible. Goodman
and Bray [7] identified three modes of toppling:
flexural toppling, block-flexural toppling, and block
toppling. Later, [6] explored toppling in cataclinal
slopes and extended Goodman and Bray criteria for
toppling to accommodate the underdip toppling.
Figure 1 shows an example of a toppling movement.
Cruden and Hu [2] described 16 topples in the
Highwood Pass in Alberta. These researchers
identified three modes of toppling based on the field

Fig.1 Rock falls/toppling in Hafeet Mountain, UAE.
Cruden and Hu [2] concluded that the different
styles of toppling were associated with the joint
spacing, bed thickness and slope angle, and used theblock ratio to distinguish between different styles of
toppling. Later, [5] further the investigation of theeffect of the block ratio and concluded that using theblock ratio to identify the toppling style is not thebest way due to the overlap between the different
modes of toppling. The following parametric study
will investigate the effect of the joint spacing, thebed thicknesses, the slope angle, and jointdistribution on the style of toppling rock slopes byusing the geological model proposed by [1].

225GEOMATE- Brisbane, Nov. 19-21, 2014

the slope face angle variation between 45°-60°. The
bedding was kept at a constant dip of 80°, while the
bed’s thicknesses were varied from 1.5 m to 3 m to 6
m for each slope.

GEOLOGICAL MODEL
Terzaghi [1] proposed a geological model forrock slopes in hard-unweathered rock masses. The
mechanical defects of rocks can be either random orwell-defined sets. He described the mechanicalmodel of stratified sedimentary rocks:“Stratified sedimentary rocks consist of layerswith a thickness averaging between a few inches andmany feet. These are commonly separated from eachother by thin films of material with a compositiondifferent from that of the rest of the rock. The
bedding planes are almost invariably surfaces ofminimum shearing resistance. They are likely to becontinuous over large areas. The cross-joints,
generally nearly perpendicular to the bedding joints,
are commonly staggered at these joints. The
cohesive bond along the walls of the cross-joints isequal to zero.
The intersections between the cross-joints andthe bedding planes may be more or less parallel toone of two or more directions, or less parallel to one
of two or more directions, or less commonly, theintersection may have a nearly random orientation.
Because of the almost universal presence of bedding
or cross-joints, stratified sedimentary rock with noeffective cohesion (Ci=0.0) has the mechanicalproperties of a body of dry masonry composed oflayers of more or less prismatic blocks which fit
each other. The boundaries between the individual
layers of blocks constituting the masonry correspondto the bedding planes of the rock. The cohesion
across the joints between all the blocks of each layer
is zero, and most of the joints between the blocks of
two adjacent layers are staggered at the boundaries
between layers. The stability of a slope on a rockwith the mechanical properties of such a body ofmasonry depends primarily on the orientation of thebedding planes with reference to the slope”. Cruden[8] also observed the same geological model.
Terzaghi [1] also described a geological model forthe crystalline rocks such as marble or granite as
irregular-shaped crystalline particles, which fit eachother like blocks between joints in a rock with arandom joint pattern. The above-mentioned
geological models are adapted in the present study.

Fig. 2Illustration of the numerical model
geometry and joints details inside the beds

The effect of the bed’s thickness and the slope
face angle were tested by using two patterns of joints
distributions. The first joint pattern was uniformly
distributed and perpendicular to the bedding tosimulate stratified sedimentary rock. The second
pattern was irregular joint pattern intersecting thebeds at different angles wad used to simulate
crystalline rocks. The insert in Figure 2 shows thejoints patterns used in the numerical model. For the
45° models, the cross-joints were also changed from
8 m to 4 m to 2 m, to investigate the cross-joints
spacing effect on the slope deformation style,producing block ratios between 5 and 0.1. A total of
30 models with different geometries were modeled
and monitored to determine the toppling modes andbehavior with numerical time. Table (1) shows thegeometrical setup of the slopes used in thisparametric study.
Table 1 Geometries of the toppling slopes used inthis study
Slope
Face
Bed
Cross-joints
Angle (ͦ) thickness (m)spacing (m)A
45
6, 3, 1.5
8, 4, 2B
50
6, 3, 1.5
8C
55
6, 3, 1.5
8D
60
6, 3, 1.5
8

THE NUMERICAL MODEL
Terzaghi [1] and Cruden [8] described
conceptual geological formations for rock masses inboth sedimentary and crystalline rocks. Fournumerical models, A, B, C, and D, were built basedon the description of the geological model of rockmasses, proposed by [1] and [8], to examine theeffect of the block geometry and the slope face angle
on the movement modes of rock slopes. The basic
Numerical model used in this analysis is presented
in Figure 2. It shows the details of the jointing and

STRENGTH PROPERTIES
According to [1] and [8], the cross-joints and thebeds have no cohesion, and the friction angle of therock mass is the only strength parameter involved instability analysis of the slopes. In this analysis, thecohesion and the tensile strength were assumed to beequal to zero, and a friction angle of 30° was used
for both the cross-joints and the steeply dipping
226

GEOMATE- Brisbane, Nov. 19-21, 2014

joints. The cohesion along the beds can be easily
destroyed and becomes equal to zero [1].
Although Patton [9] showed that the friction
angle of rocks was composed of two components,
the basic friction angle and the asperities, Cruden[10] showed that the friction angle in the CanadianRockies could be reasonably estimated as the basic
friction angle and zero angles of the asperities.
Based on an experimental study using a tilt table, Hu
and Cruden [11] concluded that the friction angle
could have a range from 21.5° to 41.4°. Cruden [8]used a friction angle of 30° to build a process
diagram to describe the type of slope movement
based on the slope face and the beds’ orientation.
Table 2 shows the properties used in this parametricstudy for both the beds and the cross-joints.

surface, Figure 3 shows the model at 120000 cycles.
As the model allowed deforming with cycling, thetoppling continued around the lower pivot rupture
surface and the blocks above the upper rupture
surface continued to topple. Eventually, the slope
moved gradually from the multiple block-toppling toblock-toppling mode which was described by [3] asChevron, Figure 3 shows the model at 320000 cycles.

Table 2 Elastic blocks and joints properties
Property
E (MPa)Poison’s ratioϕ (ͦ)
C (MPa)σ t (MPa)
Kn (GPa)
Ks (GPa)

Elastic blocks
20000
0.25

Joints

30
0
0
20
5

a)

Block-flexural toppling, 40,000 cycles

MODES OF TOPPLING
Three modes of toppling were observed
numerically: block-flexural toppling, multiple blocktoppling, and block toppling (Chevron). Table 1
shows the different slopes’ configurations used inthis paper. All of these slopes are prone to topplingaccording to the Goodman and Bray’s criteria. The
effect of the block geometries and the slope faceangle on development of the toppling modeinvestigated. The slopes were monitored withcycling to observe the mode of toppling formed. As
topples deformed with cycling the style of topplingchanged from flexural toppling to multiple toppling
and eventually block toppling, the toppling style
kept changing as cycling continued.
Figure 3(a) shows slope A (45°) with 3 m bed
thickness and 8m cross-joints. This slope shows agradual rotation of the rock columns with no rupture
surface formation and experienced block flexural
toppling mode. Cruden and Hu [2] and McAffee and
Cruden [5] found block flexural toppling with norupture surface formation in Highwood Pass topples.
The model in the figure is shown at 40,000
cycles. By allowing the model to cycle, two or morerupture surfaces were formed inside the slope: apivot lower rupture surface and upper rupture
surfaces, which formed a multiple block topplingthat is characterized by more than one ruptureb) Multiple block toppling, 120,000 cyclesc)Fig. 3227

Block toppling, 320,000 cycles

Development of toppling style with time,(a) block-flexural toppling, (b) multiple
block toppling, and (c) block toppling.

GEOMATE- Brisbane, Nov. 19-21, 2014

This deformation process and moving from stage
to stage was observed in all the toppling models
used in this study, for both regular and irregularcross-joints patterns, i.e. time is important factor in
determining the toppling styles observed in the
numerical simulation, the style is controlled by thetime allowed for the slope to deform and move fromstage to stage. McAffee and Cruden [5] concluded
that weathering, which is time dependent process,caused the toppling to occur at the Highwood Pass.
The next section will discuss the effect of the bed
thickness normalized to the slope height as opposedto the block ratio on the toppling style.
BED THICKNESS VERSUS BLOCK RATIOEFFECTa)

To normalize the bed thickness, the bed-heightratio is defined as the bed thickness to total slope
height. Cruden and Hu [2] studied the effect of theblock ratio on the toppling mode and suggested thatthe block ratio can determine the style of toppling.
Two models with the same block ratio but different
bed-height ratios were set up and tested numericallyto determine if the toppling mode controlled by theblock ratio or the bed-height ratio (1.5 block ratio
and bed-height ratios of 0.017 and 0.0085
corresponds to 6 m and 3 m bed thicknesses,
respectively). The two models had a 45° slope face.
The slopes were monitored with time and comparedat the same number of cycles (120000) and at thesame numerical time (25 seconds).
Figure 4 shows the two models at 25 seconds.
The slopes experienced two different modes of
toppling despite that the same block ratio was used.
The 0.017 bed-height ratio slope shows a blockflexural toppling while the 0.0085 bed-height slope
shows a multiple block toppling at the same numberof cycles. These results suggest that bed-height ratio,
rather than the block ratios, plays an important rolein determining the toppling style.
Martin and Kaiser [12] discussed the effect of theinternal shears on rock slopes and showed theimportance of these internal shears to accommodate
failure along the basal shear plane. As mentioned
earlier, the bed-height ratios were varied from0.0043 to 0.017 to investigate their effect on the
toppling mode as opposed to the effect of the block
ratio in order to explain the mode of toppling. The
smaller bed-height ratios introduced more shear
planes in the rock mass than the high bed-heightratio, along which more sliding and shearing
occurred at the instance at which the rock slope
started moving. As the bed-height ratio became
smaller the numerical simulations showed smootherrotational movements for the thin beds than for the
thick beds. The comparisons between the different
models were always made at the same number ofcycles or the same numerical time.

Block-flexural toppling, 0.017 bed height(25 seconds)b) Multiple block toppling, 0.0085 bed-height(25 seconds)
Fig. 4Comparison of toppling style for two slopes
at the same block ratio and different bedheight ratios, a) 0.017 bed-height ratio, b)
0.0085 bed-height ratio.

According to this numerical model parametricstudy, the rupture surface or pivot line also affectedby the bed-height ratio, the thinner the beds, thesteeper the rupture surface for the same slope faceangle. Figure 5 shows the 55°slopes at three bedheight ratios, 0.017, 0.0085 and 0.00425, as shownin Figure 5, the rupture surface or the pivot line isshallower for the small bed-height ratio than thelarge bed-height ratio. In all the models, an uphillback scarp formed (see Figure 5), notice depth of theuphill back scarp in the models, it increased as the
bed-height ratio increased.
This behavior occurred because the thin beds
will introduce more shear planes, which allow moresliding and shearing between the rock columns than
the thick beds (6 m) allowed. These shear planes
between the beds accommodated more internal
shearing and displacement and resulted in asmoother toppling movement than the toppling of
the thick beds and shallower pivot or rupture surface.

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GEOMATE- Brisbane, Nov. 19-21, 2014

allowed more gradual rotation and smoothercurvature through the rock columns than the thickbeds. Slopes with a 45° and 55° slope face angle
tended to develop slopes susceptible to slide.

Due to the increased amount of shear planes in the
low bed-height ratio’s slopes, the deformation due tothe toppling movement was accommodated byshorter columns, and the pivot line or the rupture
surface was formed closer to the surface and was
steeper for the low bed-height ratio’s slope than thehigh bed-height ratio’s slopes, the rupture surface
angle from the horizontal was measured and foundto be as following: 28° for the 0.017 bed-height ratio,
31° for the 0.0085 bed-height ratio and 33° for the
0.0043 bed-height ratio.
EFFECT OF THE SLOPE FACE ANGLE
At this parametric study, four slope face angles
were modeled 45°, 50°, 55° and 60°. The results
show that the mode or style of toppling was notaffected by the slope face angle. By comparing theslopes at different face angles and the same bed
thickness, the slopes were found to behave in thesame pattern with the three modes of toppling:
block-flexural, multiple blocks toppling and block
toppling.
The low bed-height ratio slopes required moretime to pass through this process of toppling, and insome cases it might need fracturing or removal of
the failed material at the toe of the slope. The
monitoring of the models showed that, the uphill
scarp depth increased as the slope face increased, theuphill scarp for the 60° slope (0.017 bed-heightratio) was 123 m while the uphill scarp depth for the
45° was 83.4 m. This result was due to that, at
steeper slopes the stresses was greater which
resulted in higher stress-induced deformation. The
highstress-induced
deformations
were
accommodated by shearing along longer and deeper
portions of the columns along the interface between
the beds, and this resulted in deeper uphill scarp.

a)

Block toppling, uphill scarp depth = 106.3
m, rupture surface at 28°b) Multiple block toppling, uphill scarp depth= 83.8 m, rupture surface at 31°

ROCK SLIDES AND ROCK FALLS
Toppling movement is characterized by shearing
along the beds and rotation around the pivot line.
This rotational movement may result in theformation of a rupture surface if enough rotational
movement allowed.
This rupture surface evolves from the toe of theslopes, and propagates up the slope. Depending on
the amount of rotation of the rock columns, therupture surface may form partially or completely
through the rock mass, i.e. through progressive
development. Cruden and Hu [2] found topples that
had been displaced by sliding along the rupture
surface. The simulation revealed that the rupture
surface was always initiated at the foot of the slope
and propagated as the columns rotated and extended
into the slope. In all models, the higher bed-heightratio slopes developed a rupture surface faster thanthe low bed-height ratio because the thin bedsc)Fig. 5

Bed-height ratio = 0.00425

55° slopes with three bed-height ratios andsame number of cycles 320,000.

If further fracturing occurred and/or the cross-joints
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GEOMATE- Brisbane, Nov. 19-21, 2014

toppling due to the presence of the steeply dipping
joints. As the cross-joints intersected the beds in
different angles, the cross-joints were required torotate and move more than the sedimentary rocks
perpendicular cross-joints to form rupture surface.
UDEC-DM [14] was used to create an irregular
joints pattern at a random orientation inside the rockmass that contained steeply dipping joints (see theinsert in Figure 2).

were more closely spaced, the rock will slide and thedebris will move down the slope. A slope with a 45°
slope, 0.0085 bed-height ratio, and 2 m cross-joints
were used to examine if sliding will occur at closer
spaced cross-joints than 8 m.
Figure 6 shows the slope at failure and thesliding mass down the toe of the slope. In naturalslopes, if natural damping did not stop the sliding
mass, the material may travel away from the slope,as these failures may fail catastrophically at a highspeed. McAffee and Cruden [5] noticed that five of
the slopes at the Highway Pass developed a sliding
mass away from the slope area. Note that rock falls
were developed in the slopes with 55° and 60°
degrees slope face angles especially at the 0.017
bed-height ratio. As the columns bent, the rock up
the slope moved from flexural toppling, to multiple
blocks toppling, to block toppling. At the stage ofblock toppling, the rocks at the top of the slope
tended to detach from slope and fell catastrophicallyat very high speed, Figure 7 shows rock falls.
This behavior was observed more in the highbed-height ratio than the 0.085 and 0.0425 ratios
because the slopes with high bed-height ratio moved
easier and faster to block toppling stage, and left theupper part of the slope unsupported. The 0.0085 and0.00425 bed-height ratio slopes tended to develop
rock falls at the toe of the slopes. If erosion or any
natural process removed the displaced material fromthe toe of the slope, or if the natural damping did notstop the rock falls at the toe the slope, the slopes
would continue to move toward the block topplingstage and develop rock falls.

Fig. 6

Fig. 7

Rock falls at 60° slope face angle and 0.017
bed-height ratio

The toppling mode, displacement, and formationof rupture surface were monitored and showed asimilarity with the behavior of the sedimentaryrocks. By comparing the two joints’ patterns, theregular and irregular one, the later pattern was foundto provides more planes that could accommodate
sliding and shearing in the direction of the steeply
dipping joints than the first pattern as the irregular
joints’ pattern contained joints in variable directions
and some cross-joints might also have had the sameorientation as that of the main joint set, which
resulted in a steeper rupture or rotation surface thanthat of the sedimentary rocks. The three stages of
toppling; flexural-block toppling, multiple blocks
toppling, and block toppling occurred in theseslopes, however, this behavior was more obvious in
the sedimentary rocks.
Figure 8 shows the 60° foliated crystalline slopewith a 0.017 bed-height ratio and irregular joints’
pattern. By comparing Figure 8 and Figure 7, thetwo slopes at the same number of cycles, twodifferent modes of toppling can be identified as thedifferent joints orientations allowed shearing to beaccommodated near the surface and delayed thetransition from multiple block to block toppling.
Further cycling permitted more deformation, which
resulted in block toppling, Figure 9 shows the modelat 720,000 cycles, this stage can be characterized as
block toppling, notice the block falls, due to highslope face angle. Figure 10 shows an example ofrock falls of steep slope. The slope shown in Figure
is an example of a slope prone to topple; the rockSliding proceeded by toppling

TOPPLING IN CRYSTALLINE ROCKS
Unlike the sedimentary rock slopes discussed
above, the foliated crystalline rocks may containcross-joints with an irregular joints pattern. These
joints can form at any angle with the steeply dipping
joints. Nichol et al. [13] reported toppling inmetamorphic and igneous rocks in natural rockslopes. This geological model is susceptible to230

GEOMATE- Brisbane, Nov. 19-21, 2014

rupture surface was initiated at the foot of the slope,as the columns down the slope were susceptible tomore rotation than the columns up the slope.

falls are shown at the heel of the slope.

REFERENCES

Fig. 8[1] Terzaghi, K. Stability of steep slopes on hard
unweathered rock. Geotechnique, Vol. 12, 1962,
pp. 251–270.
[2] Cruden, D. and Hu, X.-Q. Topples on underdip
slopes in the Highwood Pass, Alberta, Canada.
Quarterly Journal of Engineering Geology, Vol.
27: 1994, pp. 57–68.
[3] Cruden, D. and Varnes, D. Landslide types andprocesses. In Landslides: Investigation and
Mitigation, Transportation Research Board.
Special Report, Serial, edited by S. R. Turner,
A.K., no. 247, 1996, pp.36–75. Washington D.C.
[4] De Freitas, M. and Watters, R. Some field
examples of toppling failure. Geotechnique, Vol.
23, 1973, pp. 485–514.
[5] McAffee, R. and Cruden, D. Landslides at rockglacier site, Highwood Pass, Alberta. Canadian
Geotechnical Journal, Vol. 33, 1996, 685–695.
[6] Cruden, D. M. Limits to common toppling.
Canadian Geotechnical Journal, Vol. 26, 1989,
737–742.
[7] Goodman, R. and Bray, J. Toppling of rockslopes. In Specialty Conference on RockEngineering for Foundations and Slopes, Vol. 2,
1976, pp. 739–760. ASCE, Boulder, CO.
[8] Cruden, D. The shapes of cold, high mountains
in sedimentary rocks. Geomorphology, Vol. 55,
2003, pp. 249–261.
[9] Patton, F. D. Multiple modes of shear failure inrock. In 1st International congress, International
Society for Rock Mechanics, Lisbon, Portugal.
Vol. 1, 1996, pp. 509–513.
[10] Cruden, D. M. Rock slope movement in the
Canadian cordillaera. Canadian Geotechnical
Journal, Vol. 22, 1985, pp. 528–540.
[11] Hu, X.-Q. and Cruden, D. A portable tilting
table for onsite tests of the friction angles of
discontinuities in rock masses. BulletinInternational Association of Eng. Geology, Vol.
46, 1992, pp. 59–62.
[12] Martin, C. D. and Kaiser, P. K. Analysis of rockslopes with internal dilation. Canadian
Geotechnical Journal, Vol.21(4), 1984, 605–624.
[13] Nichol, S., Hunger, O., and Evans, S. Largescale brittle and ductile toppling of rock slopes.
Canadian Geotechnical Journal, Vol. 39, 2002,
pp. 773–788.
[14] Alzo’ubi, A., Martin, C., and Cruden, D. A
discrete element damage model for rock slopes.
In Rock Mechanics, Meeting Society’s
Challenges and demands, Vol. 1, 2007, pp. 503–
510. Vancouver, B.C.

Toppling at 60° slope face, and irregular
joints pattern at 320,000 cycles

Fig. 9: Block toppling and rock falls, 60°slope, and
0.017 bed-height ratio at 720,000 cycles
CONCLUSION
According to the numerical results presented inthis study, the toppling style is more likely to becontrolled by the time allowed for the slope todeform and move from stage to stage, the slope
prone to topple moves with time from block-flexural
toppling stage to block-toppling stage. The
numerical modeling results suggest that bed-heightratio, rather than the block ratios, plays an importantrole in determining the toppling movement style.
The smaller bed-height ratios introduced more shear
planes in the rock mass than the high bed-heightratio, along which more sliding and shearing
occurred at the instance of rock slope movement.
According to this parametric study, the rupture
surface or pivot line also affected by the bed-heightratio, the thinner the beds, the steeper the rupture
surface for the same slope face angle. In the field
weathering with time, since the onset of toppling,might play an important role in controlling the
movement style or stage. The steeper the slope thehigher possibility of developing rock falls. The
231

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

ESTIMATION OF THICKNESS OF LANDFILL BY GEOPHYSICALEXPLORATION METHODS AT ILLEGAL INDUSTRIAL WASTESDISPOSAL SITE
Minoru Yamanaka1, Tomoaki Hachimura2, Shuichi Hasegawa1
1
Facultyof Engineering, Kagawa University
2
Graduate School of Engineering, Kagawa University

ABSTRACT
Serious environmental pollution has caused by illegal disposal of industrial wastes in Kagawa Teshima Island,
Kagawa Prefecture, Japan. For restitution of Teshima, a distribution of the industrial waste by the drilling survey
by past administration’s research became clear roughly. But since the wastes was buried partially such as a pot
into the sandy soil layer under the waste layer, it is necessary to investigate in detail the thickness of the wastes
as removal of the waste layer progressed.
In this paper, the surface wave prospecting, the microtremor, the Electromagnetic method (EM) sounding andthe Continuous wave radar sounding, which is new geophysical exploration methods, were carried out at theillegal industrial wastes disposal site for the purpose of estimating the thickness of the waste layer with sufficientaccuracy.
Keywords: Landfill, Investigation, Geophysical Exploration, Surface Wave Prospecting

the wastes are distributed from the lower part. The
granite rock has many cracks, and the surface ofgranite has been weathered strongly [3].

INTRODUCTION
In order to estimate a volume of industrial wastes
disposed illegally, it is necessary to measure aground surface and to investigate a depth of thewastes by boring survey in general. The usual boring
survey which uses water at the time of drilling has apossibility of making a contaminant expanding froma waste layer with concern of soil pollution. Because
metal and rubber pieces may mix so much in wastes
containing shredder dust (SD), it is very difficult tocheck the depth of wastes such a cone penetration
test [1]. And more, the waste may be partially buried
deeply such as pot at an illegal disposal [2]. Therefore
application of geophysical exploration method
which can detect continuous layer thickness
distribution is desired strongly.
In this study, some geophysical exploration
methods such as the surface wave prospecting andradar exploration were carried out at the illegal
industrial waste disposal site, and the detection
capability of continuous distribution of the waste
layer was discussed.

Amount of Treatment of Wastes
The industrial waste which reaches to about
675,000 tons will carry out from Teshima by March,
2016, and the carry out waste will be processed withincineration and melting style in the disposing
facility in Naoshima island next to Teshima by the
mediation provision of the pollution mediation with
Kagawa Prefecture and Teshima residents [4] [5].
Table 1 shows the amount of treatment of wastes
and a polluted soil under wastes by estimating in asof March, 2011. The weight of wastes is increasingfrom 675 000 at the beginning to 938 000 tons
because of an increasing of the waste density and a
detection newly of wastes in banking layer soil
under wastes layer. The polluted soil under thewastes layer will utilize as a cement material.
Table 1 Amount of treatment

TESHIMA ILLIGAL DISPOSAL SITE

VolumeWeight(Thousands m3)(Thousands tons)

Wastes458.20499.44

Polluted soil

70.20

122.85

Cover soil

19.40

33.92

Total

547.80656.21

Kind

Topography and Geology
Figure 1 shows the plane of Teshima illegal
disposal site. The site is at the seashore part of thenorthwest of Teshima Island, Kagawa Prefecture. As
for the geology of the site, a granite rock, an
alluvium soil, a reclamation soil, a banking soil and232

GEOMATE- Brisbane, Nov. 19-21, 2014

GEOPHYSICAL EXPLORATION METHODS
Survey Line of Investigation
Figure 1 shows the plane with survey lines ofthree types of geophysical explorations at the site.
The A-A' line was set on the sandy layer after thewaste layer was removed, and the surface wave
prospecting was carried out only at A-A' line. The
B-B' line was set on shredder dust (SD) waste layer,and surface wave prospecting and microtremor werecarried out at B-B' line. In addition, there is about 5
m difference in the ground level of A-A' line and BB' line (see in Photo 1 (a),(b),(c)).
C-C' line and D-D' line of the direction from east
to west the surface wave prospecting, theelectromagnetic method (EM) sounding, andcontinuous wave radar sounding were carried out
after excavating SD wastes accumulated on thesouth at B-B' line (see in Photo 2 (a),(b),(c))

B’

C’
D’

Photo. 3 Close view of SD wastes
Photo. 3 shows the close view of the SD wastes. It
can see that a large piece of rubber or metal iscontained in much quantity.
Investigation methods
Surface wave prospecting
The Surface wave prospection was carried out by
using the high precision surface wave explorationequipment (McSEIS-SXW), and the land streamer
type which draws on the surface of the waste layer
was used because of roughness of the waste layer.
The interval was 0.5 m for vibration points byhummer, and was 1.0 m for receiving points by 24
seismograph sensors. In order to make aseismograph catch certainly vibration transmitted in
SD wastes deposited very loosely, it took care sothat the base plate of the seismograph sensor might
stick to waste.

A’

CA
B
D

100m

A-A’ 測線

Fig.1 Plane with survey lines of three types ofgeophysical explorations(a) A-A’ line and B-B’ line(b) Surface wave prospecting on A-A’ line(c) Surface wave prospecting on B-B’ line

Photo. 1 State of exploration on A-A’ line and B-B’ line(a) C-C’ line and D-D’ line(b) EM sounding on C-C’ line(c) Continuous wave radar sounding on B-B’ line

Photo. 2 State of exploration on C-C’ line and D-D’ line
233

GEOMATE- Brisbane, Nov. 19-21, 2014

image (time section image) under the line is
obtained by putting receiving records ofmeasurement points in order.

Microtremor
Measurement of microtremor was used the servo
type
accelerometer(McSEIS-MT
NEO).
Microtremor was measured every 10 m at a total of
15 places from the starting point of the B-B' line
which carried out surface wave investigation.
Because the surface level of the waste layer from 20
m to 70m at the B-B' line was downed by about 1 mfrom the level at the time of the surface wave
investigation by progress of construction, the 1 m
was considered when it analyze microtremor date.

INVESTIGATION RESULTS
Estimation of waste layer by surface wave
prospecting and microtremor results
Figure 2 shows the analysis result of S-wave
velocity V s obtained by surface wave prospecting on
the A-A’ line on the sandy layer after the waste layer
was removed. Since the V s indicates 300 m/s overfrom 0 to 10 m in distance, it seems that the baserock (granite) layer is distributed near this. And it
can be said that the high density sandy soil showing
about 100 to 300 m/s of V s is distributed from near
10 m of distance. In addition, at near 90 m of
distance, because of influence of the noise byvibration of the exhaust hose crossing at this point
was not able to be removed enough, it wasconsidered as the white zone in this figure.
Figure 3 shows the relation between N s byconverting from V s and N d by converting from thepenetration resistance value by the simple dynamic
penetration test at 30 m in Fig. 5(a) and 80m in Fig.
5(b) on A-A’ line. N s is becoming large gradually tothe depth estimated to be sandy soil which shows N s=30 over at 30 m and at 80 m in both figures. And
since N d shows the properties of the sandy soil
which is a matrix on the whole although N d changes
largely because a rod hits stones, it can berecognized that N d is smaller a little than N s . Herealthough the simple dynamic penetration test was
carried out a total of 17 on A-A' line, it was almost
the case that the test was not fully able to carry out
because the rod hit frequency a gravel or a cobble
stone in the surface layer.
Figure 4 shows the S-wave velocity V s and thepoint of microtremor on B-B’ line which is on thewaste. V s indicates about 300 m/s because of thebase rock (granite) at near the starting point. And it
can be clear that the waste layer that is V s < 100 m/s
distributed from 15 m to the end of distance. The
thickness of the waste layer can be estimated to bearound 5 m judging from the value of V s . Since thedifference of the surface level between B-B' line

Electromagnetic method (EM) sounding
EM sounding is the method of analyzing the
conductivity of the ground by observing the artificial
induction electromagnetic field which occurs by thecurrent sent through the coil or the loop. EM
sounding was used together both measurements oftype of EM31 and EM34. It becomes possible toobtain the image sectional view showing a ground
conductivity structure by this combined use.
EM31 is a rigid boom type which fixed thetransmitting coil and the receiver coil at a certain
interval. EM31 is designed to measure by one person
only, and is possible to investigate up to 6 m undersurface at several hundred points per one day.
EM34 is the measuring device which separates thetransmitting coil and the receiver coil. EM34 can beinvestigated up to about maximum 30m below bychanging the distance of the coil separation.
Continuous wave radar sounding
As for method of continuous wave radar sounding,it irradiates electromagnetic waves to ground surface,
analyzes the reflected wave from some layers having
different electric physical properties (conductivityetc.), and obtains the visible continued image. In
order to obtain the analyzed reflective section image(time section image) under the line, the profile
method was used in this study. In measurement by
the profile method, using a transmitting antenna anda receiving antenna as a pair, it measured by keeping
an antenna interval at 3 m and moving a transceiverantenna every 0.5 m. The analyzed reflective section

Depth (m)VsDistance (m)Fig.2 Analysis result of S-wave velocity Vs obtained by surface wave prospecting on the A-A’ line
234

GEOMATE- Brisbane, Nov. 19-21, 2014

Nd

Nd

Ns

Depth (m)Depth (m)NsDistance (m)Distance (m)(a) Point at 30 m on A-A’ line(b) Point at 80 m on A-A’ line
Fig.3 Relation between Ns from Vs and Nd from the penetration resistance value
B

B’

Vs

Depth (m)microtremor

Distance (m)Fig.4 S-wave velocity Vs and the point of microtremor on B-B’ line

Vs (m/s)Vs (m/s)Vs (m/s)

SD waste

Sandy soil

Depth (m)Depth (m)Depth (m)SD waste

Sandy soil

Sandy soil

10.0

10.0

10.0

H/V

H/V

(b) Point at 30 m(c) Point at 80 m
Fig.5 Change of Vs toward depth at each point on B-B’ line

H/V(a) Point at 10 m

1.0

1.0

NS direction
EW direction

NS direction
EW direction
0.1

0.1
0.1

1.0

10.0

frequancy (Hz)(a) Point at 10 m

1.0

NS direction
EW direction
0.1

0.1

1.0

10.0

frequancy (Hz)(b) Point at 30 m
Fig. 6 H/V spectral ratio on B-B’ line
235

0.1

1.0

10.0

frequancy (Hz)(c) Point at 80 m

GEOMATE- Brisbane, Nov. 19-21, 2014

Now, the thickness of the waste layer can becalculated by the 1/4-wave rule shown in equation(1) using the frequency f corresponding to Vs of thewaste layer and waste layer of an every place point.

which is on the waste and A-A’ line which is on the
sandy soil is about 5 m from the point of directsurvey, it can be confirmed that the thickness of thewaste layer is about 5 m on B-B’ line. Moreover,although the contour line of S-wave velocity showsa shape as a concave at 40 m, 80 m and near 105 m
in distance, it suggests that a existence of
undiscovered wastes into the sandy soil under thewaste.
Figure 5 (a), (b) and (c) show the in-depth profile
of V s at 10m, 30 m and 80 m in distance individually.
The waste does not accumulate at the point of 10 m
in distance, and the V s of sandy soil indicates morethan about 120 m/s in Fig. 5(a). On the other hand,
the waste accumulated at 30 m in Fig. 5(b) and at 80
m in Fig.5(c), it estimated that the value of S-wave
velocity of the waste layer is V s < 110 m/s.
Figure 6 (a), (b) and (c) show the H/V spectral
ratio obtained by analyzing a ground micro vibrationby the microtremor at the same point as above Fig. 5.
Frequency of 10 Hz or more was judged to be thefrequency corresponding to the base rock. And since
the site was near the seashore, the frequency of 1.0
Hz or less was judged to be the value having an
influence of sea wave. Therefore the frequency
which shows the value of a high H/V spectrum inthe range with a frequency of 1.0 to 10 Hz was
judged to be the frequency corresponding to thewaste layer.

H= V s / 4f

eq.(1)

Layer thickness by surface

表面波探査による廃棄物層厚（m）
wave prospecting (m)Here, H : estimated thickness of waste layer (m).
f : frequency corresponding to waste layer
obtained by the microtremor (Hz).
V s : S-wave velocity obtained by Surface
wave prospecting (m/s).
8
6
4

R² = 0.7344

2
0

0

2

4

6

1/4波長則で算出した層厚（m）(m)
Layer thickness
by 1/4-wave ruleFig.7 Correlation of layer thickness by surface wave
prospecting and one by 1/4-wave rule
～ Lower line of waste

深 度

Depth (m)8VsSurface after excavation
0
1
2

(m) 3

4
5
0

5

10

15

20

25

30

40

35

45

50

55

60

65

70

距離程 (m)(m)Distance(a) S-wave velocity Vs obtained by surface wave prospecting

Depth (m)Depth (m)Distance (m)(b) Dielectric constant obtained by EM sounding

Depth (m)Depth (m)Distance (m)(c) Reflected wave obtained by continuous wave radar sounding
Fig.8 Results of geophysical exploration methods on C-C’ line
236

GEOMATE- Brisbane, Nov. 19-21, 2014

Figure 7 shows the correlation of layer thickness
by surface wave prospecting and one by 1/4-wave
rule. It became clear that both layer thicknesses had
positive correlation, and it can be said that the
thickness of the waste layer by two geophysicalinvestigation methods has enough accuracy.

CONCLUSIONSAs a result of this study, important conclusions
are summarized as follows.
1) The S-wave velocity of the SD waste of Teshima
Industrial illegal disposal site is very low, it
estimates about Vs= 100 m/s.
2) With the combination of the surface wave
prospecting and the microtremor, it can estimate
useful accuracy the thickness of the waste layer.
3) The surface wave prospecting is most suitable for
estimation of the thickness of the SD waste layer
among three kinds of geophysical exploration
methods by this study.

Estimation of layer thickness by EM sounding
and continuous wave radar sounding
Figure 8 (a), (b), (c) show the decipherment result
by three kinds of geophysical exploration carried out
on the SD waste on C-C' line individually.
From Fig. 8 (a) which is result of the surface wave
prospecting, the layer of the value of V s =80~120 m/s
distributes in the surface on C-C' line, therefore thislayer is estimated to be the SD waste layer. The redline in the figure means the boundary between the
SD waste layer and the sandy soil layer. Since thered line falls largely at 8~25 m and 35~60 m indistance, it is considered that the waste is buriedsuch as a pot. After the removal work of the SD
waste was carried out after of proceeding the surface
wave prospecting on C-C' line. The dashed blackline shows the surface of sandy soil after theremoval work. Although the lower boundary of theestimated waste layer correspond mostly to thesurface of sandy soil at 10~20 m in distance, thesurface of sandy soil seems to be deeper about 1~2
m in depth at other area. As this reason, it
considered that the sandy soil mixed wastes a little
under the SD waste and a discolored sandy soil
which anxious about contamination was removed
together. And more, although the value of V s of theestimated SD waste on C-C' line is bigger a little
than the one of the SD waste on A-A' line, it can besaid that it is influence of increase of density of the
SD waste in order to mix much sandy soils into theSD waste on C-C' line.
From Fig. 8(b) which is result of the EM sounding,the contrast of comparatively clear conductivity isdetectable. The dielectric constant of the waste layer
is 50 or more mS/m, and one of the base rock
(granite) set as 20 or 30 mS/m each. Although there
is a zone where a dielectric constant shows 150
mS/m or more at 45 ~ 70 m in distance, it can guessthat the waste of different density is buried in thiszone. And from Fig.8(c) which is result of thecontinuous wave radar sounding, the reflected waveof two lines was detected comparatively clearly. The
above line was estimated as the reflected wave ofundersurface boundary of the waste, and the low line
was estimated as the reflected wave of upper surface
boundary of the granite. On the other hands, as forthe thickness of sandy soil layer, it can be read as 3
~ 4 m by the surface wave prospecting, as 1 ~ 3 mby the EM sounding, and as 1 ~ 2 m by thecontinuous wave radar sounding.

ACKNOWLEDGEMENTS
The authors would like to appreciate Mr. Masaya
Komino of the waste management division, Kagawa
prefectural office for his support in carrying out thisstudy, Miss. Takako Takahashi of OYO Corporation
for her technical advice for the surface wave
prospecting, and Mr. Kiyoshi Yoshida of Kawasaki
Geotechnical Engineering Co.,Ltd. for his technicaladvice for the EM sounding and the continuous
wave radar sounding.
REFERENCES[1] Hachimura T., Yamanaka M., Ohno H. andHasegawa S. “New Investigation Methods toEstimate Waste Properties of Existent Landfills”,
Proc. of the 20th Int. Offshore and Polar Eng.
Conf., ISOPE, Beijing, China, pp.739-742, 2010.
[2] Yamanaka M., Ishida S., Hasegawa S. and Ikeda
A., “Estimation of Layer Thickness of Landfill
Waste
byGeophysicalInvestigation
Techniques”, Proc. of Annual Conference of
Shikoku branch of Japanese GeotechnicalSociety, pp.9-10, 2012. (in Japanese)[3] Hanashima M., Takatsuki H. and Nakasugi O.,“A Case Study of Environmental Contamination
Caused by Illegal Dumping op Hazardous
Wastes”, Waste Management Research, Vol.7,
No.3, pp.208-219, 1996. (in Japanese withEnglish abstract)[4] Kagawa Prefectural Management Committee for
Disposal of Waste in Teshima, “Report on the
Current Situation of Waste Disposal in Teshima”,
Waste Management Research, Vol.18, No.5,
pp.304-314, 2007. (in Japanese with English
abstract)[5] Kagawa Prefecture’s Technological Examination
Committee for treatment of Teshima’ Industrial
Wastes, “A Technological Examination for
Treatment of Teshima’s Industrial Wastes,
Waste Management Research, Vol.12, No.2,
pp.117-124, 2001. (in Japanese with English
abstract)
237

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

APPLICATIONS OF INNOVATIVE MATERIALS FORPERFORMANCE IMPROVEMENT OF FLEXIBLE PAVEMENT OVER
EXPANSIVE SUBGRADE
Ravin M. Tailor1, Dr. Navin C. Shah2
Assistant Professor, S. V. National Institute of Technology, Surat, Gujarat, India;
2
Director, Chhotubhai Gopalbhai Patel Institute of Technology, Bardoli, Gujarat, India
1

ABSTRACT
Expansive soils are one of the most problematic materials that are widely encountered in significant land
areas in several parts of the world; like Africa, Australia, India, United States and Canada. The South Gujarat
region in India have majority of top soil as black cotton soil. The black cotton soil has characteristics ofshrinking on drying and heaving on wetting. This soil being expansive creates several types of damages topavement structures, and in some cases the pavement may even become unserviceable. The normal climate
condition of study area shows short wet and long dry period which aggravate the problem of swelling andshrinkage. The IRC: 37 – 2001, Annexure – 4 suggest 0.6 to 1.0 m thick non-cohesive soil cushion on the
expansive soil for road construction which led to higher cost for road construction. Also for new urban areas it isdifficult to raise the embankment or to excavate the subgrade upto such a depth due to existing structures andunder laying service lines. To provide economical solution along with feasible application two innovative
materials were used namely, CONSOLID and Geotextile for flexible pavement. The CONSOLID applicationshows the great improvement of CBR values helping the overall stability of the pavement. The Geotextile
provided below the pavement components to act against the heaving of the swelling soil at the same time it helps
as drainage layer also. Field study is undertaken to observe the effect of Geotextile in flexible pavement
performance and 2 specific boundary conditions are created for observations. The Observations shows about
50 % reduction in shrinkage effect for paved road reinforced with Geotextile subjected to drying and wetting
cycles. Both the materials are having its unique advantage in the performance improvement of flexible pavement
over expansive subgrade.
Keywords: Expansive Soil, CONSOLID, Geotextile, Pavement Performance

majority of South Gujarat area having black cottons
soil as top layer.

INTRODUCTION
Roads are vital to link our communities andsustain the economy and quality of life in society.
Roads constructed over the expansive soil observedwith high maintenance expenditure inspite of highcapital cost. These are because many roads in thisregion are failing prematurely due to the expansionof reactive soils underneath the roadway, causing
safety issues and increases road maintenance costs.
Frost, Fleming and Rogers (2004) [1] outline theprimary roles that a subgrade or pavementfoundation must play in pavement design. The
volume change at subgrade creates variety of failurein flexible pavement like cracking, rutting, potholes
etc. Expansive soils are one of the most problematic
materials that are widely encountered in significant
Land areas in several parts of the world e.g. parts ofAfrica, Australia, India, United States and Canada.
In these countries expansive soil is having great
impact on the construction and maintenance costs ofhighways. The South West region of India iscovered by top soil as black cotton soil. Fig. 1, mapof soil deposits in Gujarat State shows that theFig. 1

Map of Soil Deposits in Gujarat StateTo understand the phenomenon of expansion ofswelling soil and to provide economical solution
along with feasible application utilising various
238

GEOMATE- Brisbane, Nov. 19-21, 2014pole of dipolar water molecules and cations(Snethen, 1980) [4]. In addition, expansive soils
have high degree of shrink-swell reversibility withchange in moisture content. Petry and Little (2002)[5] discuss the history of clays and their engineeringsignificance, dating back to papers written in theearly 1930’s.
The effects on buildings constructed on reactive
soils with inadequate footings can be dramatic(Smith R, 2004) [6]. Road subgrades can be viewed
as the footings/ foundations for road pavements, andif these footings are not adequate, structural damage
can occur.

strength of Geotextiles study started at the SVNIT
campus, South Gujarat region of India. Geotextile isprovided below the pavement components to act
against the heaving of the swelling soil at the sametime it helps as drainage layer also. Field study isundertaken to observe the effect of geotextile inflexible pavement performance and 2 specificboundary conditions are created for observations.
Observations summarized shows about 50 %reductions in shrinkage effect for paved roadreinforced with geotextile compared to road without
geotextile.
Also the advanced material called CONSOLID
system with two different types of soil were
examined for better performance of south Gujarat
soil. The samples are collected from SVNIT Campus
in South Gujarat region and experimental work
carried out for evaluation of CONSOLID system.
Two samples are collected and named as, 1) SVNIT
Road Side Shoulder Soil, and 2) SVNIT Campus
Soil. The soil samples are found of MH and CH typeof soil. The Soak CBR for MH type of soil fornatural condition is 2.4% which improves about
45% With CONSOLID Treatment. Similarly, theSoak CBR for CH type of soil natural condition is
2% which improves about 27% with CONSOLID
Treatment.

STUDY AREA OBSERVATIONS
The research started based on the theme toprovide effective solution against the moisturevariation and differential swelling / shrinking of
expansive soil in the area. There was planning ofroad construction at SVNIT campus near theobserved site. The flexible road was proposedconnecting transportation lab to workshop buildingon the back side of Civil Engineering Department.
This site was selected for the further research work.
Fig. 2 shows the aerial view of the site as observedin Google web page.

EXPANSIVE SOIL
Expansive soils are clayey soils, mudstones or
shales that are characterized by their potential forvolume change on drying and/or wetting. Usually
the clay content is relatively high and the clay
mineral montmorillonite dominates. They arecharacterized by their high strength when dry; very
low strength when wet; wide and deep shrinkage
cracks in the dry season; high plasticity and very
poor trafficability when welled. Wheneverinsufficient attention is given to the deleterious
properties of expansive soils, the results will bepremature pavement failure evidenced byundulations, cracks, potholes and heave. Methods
were developed for the identification andclassification of expansive soils both locally andworldwide. In India IS: 1498-1970 [2] describe themethods to identify the expansive soil.
There are three basic particle size components ofnaturally occurring soil: sand, silt and clay. Plastic
clays termed as expansive soils or active soils
exhibit volume change when subjected to moisturevariations (He-Ping Yang et al, 2007) [3]. Swellingor expansive clay soils are those that containswelling clay minerals (such as montmorillonite andsmectite) and can often be scientifically referred toas Vertosols. Vertosols are soils that contain clay
minerals which, because of their natural
physiochemical properties, posses a net negativeelectrical charge imbalance that attracts the positive

Study Area Road

Fig. 2

Location of Road Joining Transportation
Engineering Lab to Workshop, at SVNIT
Campus, South Gujarat, India

The study by Jigisha (2008) [7] shows theaverage soaked CBR for typical South Gujarat
undisturbed or compacted soil as 2.0 %.
Also study carried out by Yogendra (2008) [8]shows the similar type of observation for the South
Gujarat region soil. Table 1 shows the Geotechnical
Properties of Black cotton soil as observed by
Yogendra (2008) [8].
Table 1 Geotechnical properties of black cotton
239

GEOMATE- Brisbane, Nov. 19-21, 2014

soil.
Property
Grain Size
Gravel (%)
Sand (%)
Silt + Clay (%)
Atterberg’s
Liquid Limit (%)
Limit
Plasticity Index (%)
Compaction
MDD (kN/cu.m)
Test
OMC (%)
Swelling
Free Swell
Test
Index (%)
CBR (%)UCS (kN/sq.m)
Permeability (m/s)

Values
1
12
87
55
27
15.50
21.75
70
a) Geotextile above Murrum,
1.77
59
8.75 x 10-9

Also the samples are collected from the SVNIT
campus to access the suitability with CONSOLID
system. Various laboratory tests were carried out forthe samples collected and mainly the CBR values
are reported for the same. Table-2 shows the results
for the same.
Table 2 CBR values of study area soils
Sample I.D.

Unsoak CBR %Soak CBR %1 - S.V.N.I.T.
Road
Side Shoulder
Soil
5.7
2.4

b) GSB spreading on Geotextile

2S.V.N.I.T.
Campus
Soil
4.7
2.0

Fig. 3

Road construction work in progress at site.

Pavement Observations & Analysis
The following observations were started after
finishing of the pavement construction upto grouting
layer.
1) Visual observation for cracks and other changes
2) Ground profile reading to get amount of change insoil thickness with change in moisture content (i.e.
change in season).
The visual observation shows that in some of the
portion the Top Surface was deteriorated because of
non-availability of appropriate Bituminous Layer. In
general the area with Geotextile shows lessundulation.

GEOTEXTILE FOR FOUNDING FLEXIBLEPAVEMENT ON SWELLING SUBGRADE
The proposed road is studied for its design andplanning was done for the observation of the
expansive subgrade behaviour. After taking
necessary approval from authority it was decided toprovide the Geotextile GARWARE made GWF-52240 PP Grey Multi 240 Twill 5 M, just below thesubbase layer for further observation.
The geotextile was laid in such a manner that 2
boundary conditions can be created for the site.
1) Road with both side covered ground (length
between Transportation Engineering Lab and Water
Resources Engineering Lab)
2) Road with one side covered and one side open
ground (length along WRE lab & after WRE lab).

Ground profile survey
The leveling exercise carried out after pavement
construction in Month of December 2010 to get theinitial Ground Level RL. After one year during
December 2011 further the ground level are
surveyed and another ground level survey was
carried out in June 2012.
The detailed observation are summarized andpublished by Tailor R.M. et. al. in year 2012 [9] and2014 [10]. The summertime graphs shown in Fig. 4,
5 and 6 represents ground profile for various
observations at Right, Centre and Left side.

Figure 3 shows various stages of the road
construction at site.

240

GEOMATE- Brisbane, Nov. 19-21, 2014

Ground Observation for Right side of Pavement
97.100Dec-1097.050Dec-11
Jun-1297.000RL ( m )96.95096.90096.85096.80096.75096.700
0

10

20

30

40

50

60

70

80

90

100

Chainage (m )Fig. 4Ground observation for Right side of Pavement.
Ground Observation for Centre of Pavement

97.1
Dec-1097.05

Dec-11
Jun-12

97

RL (m)

96.95
96.9
96.85
96.8
96.75
96.7
0

10

20

30

40

50

60

70

80

90

100

Chainage (m)Fig. 5Ground observation for Centre of Pavement.
Ground Observation for Left side of Pavement

97.1
Dec-1097.05

Dec-11
Jun-12

97

RL (m)

96.95
96.9
96.85
96.8
96.75
96.7
0

10

20

30

40

50

60

70

80

90

100

Chainage (m)Fig. 6Ground observation for Left side of Pavement

Observations for WBM unasphalted pavement at
Transportation Engineering Laboratory

crust was also pervious to some extent. The textile
was laid on subgrade in December 2010.
The December 2011 & June 2012 observationsof elevation on road with nominal traffic shows:1) The introduction of geotextile fabric in sector ofwalls on both sides shows 40% reduction inshrinkage of fill & subgrade.

The subgrade was saturated clay. The typicalroad construction with structures on both sides andstructure on one side were under observation. The
other side is water logged and absence of topping241

GEOMATE- Brisbane, Nov. 19-21, 2014

behaviour in saturated condition and hence is very
critical for the regions with heavy rainfall andretentive soil types. The soak CBR test is carried out
after the submergence of sample in water for 4 daysin accordance to IS: 2720 (Part 16) [11]. The test
results are presented in Table 3 & 4 below for both
samples.

2) Wall on right & free surface on left, Chainage 54– 90 m. The performance in December 2011 shows
43 mm average reduction of settlement of surface infabric reinforced zone. (Reduction of about 60 %with reference to no reinforcement zone)3) In middle sector with wall on right & free water
access to left typical ingress of water can be seen to
centre of road by December 2011. The left end
shows ultimate heave where as right end shows
settlement with little movement at centre in zone. In
reinforced sector of this road overall performanceshows settlement of 37 to 19 mm.
4) In general, trend shows shrinkage effect leading
to settlement indicates drastic reduction of 50 % or
more.

Table 3 CBR values of SVNIT Road Side Shoulder
soil with CONSOLID System.

CONSOLIDATE SYSTEM TO IMPROVE CBR

Soil Condition

Natural Soil

Unsoak CBR %Soak CBR %

5.7
2.4

Soil with
CONSOLID
System54
45

Table 4 CBR values of SVNIT Campus soil with
CONSOLID System.

Sustainable production and consumption, leading
to increased resource efficiency, is now high on thepolitical agenda. Various alternatives are developed
in form of advanced materials and waste utilization
for resource intensive activities such as theconstruction of infrastructure including highways.
The range of materials incorporated includes
recycled asphalt, recycled concrete, ashes, slags,
foundry sand, glass, plastic, rubber and otherchemicals. Feasibility studies concerning thepotential for the use of these materials are plentiful
and some studies exist which have considered theengineering as well as environmental credentials ofsuch practices. This particular study summarizes
work conducted to date and investigates theengineering as well performance of CONSOLID
system, which is combination of Consolidate444 &Solidry powder to replace conventional materials in
non-bituminous layers of flexible pavement. Alsosame can be used to improve the soil CBR.
To study behavior of CONSOLID system withtwo different types of soil; samples are collectedfrom Surat city and surrounding area in South
Gujarat region and experimental works carried out
for evaluation of CONSOLID system. The study forsoil characteristics, Free Swell Index, Standard
Proctor Test, Specific Gravity, CBR and UCS are
conducted for natural and treated soil samples. Two
samples are collected from the SVNIT campus andnamed as, 1) SVNIT Road Side Shoulder Soil, and
2) SVNIT Campus Soil.
The California Bearing Ratio test is penetration
test meant for the evaluation of subgrade strength ofroads and pavements. The results obtained by thesetests are used with the empirical curves to determine
the thickness of pavement and its component layers.
This is the most widely used method for the designof flexible pavement. The CBR value of thespecimen reflects on the strength of the specimen insoaked or un-soaked condition as tested in thelaboratory. The soaked CBR values reflect the soil

Soil Condition

Natural Soil

Unsoak CBR %Soak CBR %

4.7
2.0

Soil with
CONSOLID
System
32
27

The 1) SVNIT Road Side Shoulder soil sample
found of MH type of soil while the 2) SVNIT
Campus soil observed as CH type of soil. The Soak
CBR for MH type of soil for natural condition is
2.4% which improves about 45% With CONSOLID
Treatment. Similarly, the Soak CBR for CH type ofsoil in natural condition is 2% which improves about
27% with CONSOLID Treatment.
CONCLUSION
The textile was laid on subgrade in December
2010. The December 2011 and June 2012
observations of elevation on road with nominal
traffic shows:1) The area without geotextile bothside buildingshows uneven change in ground profile while thearea with Geotextile bothside building shows about
50 % reduction with uniform change in groundprofile.
2) The area without Geotextile Rightside buildingshows the considerable change of ground in groundprofile on lefthand side because of direct entry ofrainwater on that side. The area with Geotextile
Rightside building shows slight changes in leftside
region.
3) Overall the observations show the positive impactof Geotextile laying in flexible pavement overswelling subgrade.
The overall visual observations also indicate
considerable reduction in ground profile change for242

GEOMATE- Brisbane, Nov. 19-21, 2014[4] Snethen D R, “Expansive Soils in Highway
Subgrades”, U. S. Department of transportation,
United States of America, 1980.
[5] Petry T M, & Little D N, “Review of
Stabilisation of Clays and Expansive Soils in
Pavements and Lightly Loaded Structures History, Practice, and Future”, Journal of
Materials in Civil Engineering, Nov/Dec 2002,
pp. 447-460.
[6] Smith R L, “Achieving the Goal ofManagement of Reactive Clays”, AustralianInstitute of Building Surveyors Conference,
Australia, (2004).
[7] Vashi J, “Review of Geotechnical Parameter:
CBR and Modulus of Subgrade Reaction (k) for
Rigid Pavements”, M. Tech (SMFE)
dissertation, Applied Mechanics Dept., SVNIT,
Surat, India, 2008.
[8] Tandel Y, “Utilization of Copper Slag to
Improve Geotechnical Properties of Soil”,
M.Tech(SMFE)
dissertation,
AppliedMechanics Dept., SVNIT, Surat, India, 2008.
[9] Tailor R M, Desai M D and Shah N C,
“Performance Observations for Geotextile
Reinforced Flexible Pavement on Swelling
Subgrade: A Case of Surat, India”, International
Journal of Civil Engineering and Technology,
Volume 3, Issue 2, July- December 2012, pp.
347-352[10] Tailor R M and Shah N C, “Performance
Improvement of Flexible Pavement on Swelling
Subgrade Using Geotextile”, Journal of Trafficand Logistics Engineering, Vol. 2, No. 2, June
2014, pp. 80-85[11] Methods of Test for soil - Part-16: Laboratory
Determination of CBR, IS: 2720 (Part 16),
1987, Reaffirmed 2002, Bureau of IndianStandards, New Delhi, India.

flexible pavement embedded with Geotextile overswelling subgrade.
The CONSOLID system results shows great
improvement in soaked CBR values from 2.4% to
45% for MH soil and 2% to 27% for CH soil, which
encourage its utilization to improve subgradecondition.
ACKNOWLEDGEMENTS
The authors are thankful to M/s Garce and Sachi
Enterprise, Ahmedabad for funding the CONSOLID
system project. Also thank to Dr. C.H. Solanki,
Professor, Applied Mechanics Department, SVNIT,
Surat for his continues support during the researchwork. Thanks are due to late Dr. M. D. Desai, Shri
Jignesh Patel, Dr. Jigisha Vashi, Dr. Yogendra
Tandel and Shri C. R. Patel for their unconditional
support throughout the research work.
REFERENCES[1] Frost W M, Fleming P R, and Rogers C D F,
“Assessment of a Performance Specification
ApproachtoPavement
Foundations”,
Transportation Research Record 1757, Soils
Geology and Foundations, Transportation
Research Board, Washington D.C, 2001,
pp.100-108.
[2] Classification and Identification of Soils for
General Engineering Purposes, Indian Standard,
IS: 1498-1970, Reaffirmed 2002, Bureau ofIndian Standards, New Delhi, India.
[3] Yang H P, Zheng J and Zhang R, “Addressing
Expansive Soils”, Institute of Special Soils,
2007, pp 64-69.

243

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

A PHYSCIAL AND NUMERICAL INVESTIGATION INTO SINKHOLEFORMATION
1

Brian Lamb1 and Jim Shiau1
Faculty of Engineering and Surveying, University of Southern Queensland, Australia
ABSTRACT

Sinkholes are a global phenomenon which can result in a major impact to a community. This paper aids inunderstanding the phenomena of sinkholes better through physical and numerical simulations. The research is
conducted by closely examining a physical model to simulate the formation and collapse of a sinkhole and thenby analysing sinkhole structures through utilizing finite difference software FLAC. The completion of 2D
numerical models allows for numerous sinkhole simulations, with varying material properties and different
overburden depth to cavity width ratios. The sinkholes are analysed through a strength reduction method, which
can produce the factor of safety of the formation. By completing many simulations with different overburden depth
to cavity roof width ratios the sinkhole phenomenon mechanics is explained. Future work is to conduct 3D
simulation models for the investigation of sinkhole formation shape.
Keywords: FLAC, FOS, Formation, Sinkhole, Stability

Sinkhole collapse in most circumstances is an
instantaneous event, producing extreme difficultywith in situ measurement during collapse failure [2].
This vastly increases the difficulty for investigating
the formation, triggering mechanism and influential
factors of specific ground failures and sinkhole
events.
The relationship between the material propertiesof the overburden and overburden depth plays animportant role in not only the mechanics of the
failure, but also the cause. In limestone areas, a
gradual solution of underground rock in groundwater
passageways leads to subsidence instability ofoverburden and possible later collapse. Sinkholes ofgreater concern are those which are formed by asudden collapse of an underground rock cavity. Theseoccur often as initially small cavities, mainly on a soil
and rock interface (Fig. 1) [1], [4]. Eventually, thecavity becomes large enough that the overburden can
no longer support itself and collapses. Other causes
include reduction in groundwater levels [5] fromincreased urbanisations’ use of bore water. Mining
also causes sinkholes due to the mined void causing
instability in the overlaying material or overburden.

INTRODUCTION
Sinkholes are a global phenomenon which canhave devastating consequences. There are manydifferent causes, but all are based on the overburden’ssoil pressures. The pressures increase to a breaking
point where then the overburden material, thematerial above an underground cavity, falls into thecavity, leaving in many cases a conical shape andcircular ground opening.
This paper is focused on investigating sinkholes
by generating idealised physical and 2D models,describing the sinkhole phenomena so it can befurther explained. Fast Lagrangian Analysis ofContinua (FLAC) software produced by the Itasca
Consulting Group, Inc. is used for the 2D analysis.
SINKHOLE DEFINITION AND CAUSES
Sinkholes are soil surface depressions caused bychanges to soil and rock beneath the ground. Thesechanges of the underground structure are caused by
the production of a cavity and then the collapse of theoverburden or overlaying material into the cavity [1].
This collapse creates a funnel-shaped depression witha hole at the center, this being a sinkhole.
Overburden is the overlaying material of a cavity.
The Overburden’s material properties and depth has
a great effect on the dependence of a collapse.
Subsidence can occur gradually over time as aprogressive event, known as dynamic subsidence.
Subsidence can also occur very rapidly, for instancewhen a tunnel or pipeline collapses. Dynamic
subsidence is the depressions formed on theoverlaying overburden material before sinkhole
formation [3].

Fig. 1

244

An idealised model of a formed void.

GEOMATE- Brisbane, Nov. 19-21, 2014

how the overburden soil material falls into the cavity
below. It also shows the cavity opening chute in therock.

In natural occurring sinkholes, the sinkhole size isa function of several variables such as the soil
strength, position of water table, weathering of soil,
cohesiveness of soil, depth of cavity and compositionof the limestone rock [6]. Tunneling and pipelines canalso create sinkholes or subsidence if they collapse,
since they create underground voids [3], [4].
Earthquakes can directly trigger a sinkhole formation
by disturbing the settled overburden to collapse.

PHYSICAL MODEL
To physically model a sinkhole, first a test box was
produced and then based on the initial design acomplete acrylic box was created. The boxes are open
at the top for access and have weep holes on the basefor drainage. The cavity is built using sugar and thendissolved via an in situ water tube, to simulate
limestone dissolution.
An initial design was made. Dimensions for the
initial test, using a constructed wooden box withacrylic front, were 300 mm (length) by 200 mm(width) by 200 mm (depth). Figure 2 shows steps inthe production of the model up to it being ready fortesting. Picture 1 (Fig. 2) shows the acrylic viewing
window. Picture 2 (Fig. 2) shows the drilled weep
holes for drainage. Picture 3 (Fig. 2) shows a stone
pebble base for added drainage. Picture 4 (Fig. 2)
shows the first layer of sand and sugar, the material
used to simulate a material subjective to dissolution,such as limestone. Picture 5 (Fig. 2) shows thehalfway step of sand and sugar layering and the water
pipe being laid into the model. Picture 6 (Fig. 2)
shows the model about to be tested, and the use of thepipe to keep the sugar centrally placed at the face of
the acrylic window.

COLLAPSE MECHANICS
Reference [3] explains that subsidence groundmovements have horizontal and vertical components.
Vertical movement is at its largest in the central
location of the subsidence, and gradually becomesless until the boundary of the subsidence is reached.
The boundary is where there is no longer any groundsurface deformation. Horizontal movement occurs in
subsidence troughs as the surface tends to movetowards the center of subsidence. This horizontal
movement of adjacent points around the subsidence
center moving closer to one another createscompressive strains of the surface. The compressive
strains are at their maximum in the center of thedepression and is reduced as it moves away from thecenter and adjacent points move further apart.
Eventually, a point of zero compressive strain isapproached, the inflection point where no horizontal
displacement will occur. Beyond the inflection point
the ground’s neighboring points are moving further
apart. This results in tensile strains on the ground’s
surface. The inflection point also, for the reason of
being the location where tensile and compression are
zero, is where the shape of the surface of subsidencechanges between convex and concave [3].
The compressive and tensile strains as discussed
above, either side on the infliction point, comprise thecompression and tensile zones on subsidence. The
forces can be represented as strains, because strain
involves the dimensional change compared to theoriginal position before being subject to tension orcompression. Tensile strain pulls apart andcompressive strain pushes inwards. The compressivezone makes up the central section of subsidence,
above the center of failure above the cavity collapse.
The tensile zone represents the remainder and often
extends beyond the cavity failure. Soil has no or little
tension, therefore this paper will focus on the failureof the overburden due to the compressive nature of
the soil properties, as well as friction angle.
Once the overburden soil has reached a point where
the strain is too great for stability, where the soilpressures distribution no longer keeps the overburden
from collapsing, the overburden will fall into thecavity below, typically leaving a conical shape. In
many cases the initial cavity produced is in rock, forexample limestone which can become dissolved [5].
Figure 1, an idealised model of a formed void, shows

1

2

3

4

5

6

Fig. 2245

Preliminary design setup.

GEOMATE- Brisbane, Nov. 19-21, 2014

Figure 3 shows the cavity created and the circularshaped opening of the sinkhole. A conical shape isalso evident as predicted and the circular extent of the
opening onto the surface is highlighted in red. This
preliminary investigation is encouraging and will be
repeated with a new acrylic box to capture all earth
movements, using slightly larger dimension to ensure
the complete extend of the sinkhole formation is
captured.

Fig. 3

were the same for each material for comparative
analysis.
Table 1 Material Properties
Undrained Clay
Material Property
Mass-Density (kg/m3)
Elastic Modulus (kPa)
Poisson's Ratio
Cohesion (kPa)Tension (kPa)
Friction Angle
Dilation Angle
Drained Sand
Material Property
Mass-Density (kg/m3)
Elastic Modulus (kPa)
Poisson's Ratio
Cohesion (kPa)Tension (kPa)
Friction Angle
Dilation Angle
c-ϕ Soil
Material Property
Mass-Density (kg/m3)
Elastic Modulus (kPa)
Poisson's Ratio
Cohesion (kPa)Tension (kPa)
Friction Angle
Dilation Angle

Preliminary results of model tests.

Value
1900
1000
0.25
30
1.00E+7
0
0
Value
1900
1000
0.25
0
1.00E+7
35
0
Value
1900
1000
0.25
30
1.00E+735
0Numerical results are investigated through theplots of plasticity state indicators, y displacement
contours, elemental principal stresses and shear strain
rate. Each material has six different cases, ranging
from shallow to deep, each case had certain height towidth ratio. The height (h) representing the height ofthe overburden material above the cavity and width(w) representing the length or diameter of the cavity
roof, as shown in Figure 4.

The final full acrylic box design inside dimensions
are 400 mm (length) by 250 mm (width) by 300 mm(depth).
2D FLAC MODEL
While
physicalsoil
conditions
andoverburden/cavity interactions have high complexity,
the model uses simplification and assumptions to aid
predict theoretical soil responses within cavity
opening and overburden soil relationships. The
sinkhole model assumes the use of Mohr-Coulomb
failure criteria, with set soil characteristics of massdensity, elastic modulus, Poisson’s ratio, cohesion
and friction angle.
Table 1 shows the respective material properties
in the analysis. The major characteristic of theundrained clay was the relatively high cohesion andzero friction angle. The drained sand was given zerocohesion and a non-zero friction angle. The c-ϕ soil
was given the same cohesion and friction angle as theclay and the sand. The remaining material properties

Fig. 4

Idealised sinkhole in 2D space.

In FLAC each case was constructed and thematerial properties set. The initial equilibrium wassolved for and then a section width was released fromthe x and y fixed boundary condition, as shown in246

GEOMATE- Brisbane, Nov. 19-21, 2014

Figure 5 a typical FLAC mesh. Then the model was
solved through Factor of Safety (FOS) which is ameasure of the shear strain rate and sinkhole failure.
If the FOS is below one, then the properties of the soil
are insufficient and the height by width (h/w) ratio is
too small to prevent collapse.

Fig. 5Drained Sand
Table 3 Drained Sand Results

RESULTS AND DESCUSION
Undrained Clay
Table 2 Undrained Clay Results
h/w

FOS

1
2
3
4
5
6

1.667
2
2.5
3.33
5
10

0.51
0.592
0.682
0.795
0.947
1.189

estressMin. Value-3.23E+05-2.82E+05-2.45E+05-2.23E+05-2.18E+05-2.13E+05

FOS

1
2
3
4
5
6

1.667
2
2.5
3.33
5
10

<0.03
<0.03
<0.03
<0.03
<0.03
<0.03

estressMax.
Value
8.81E+13
1.96E+07
2.96E+05
9.82E+05
3.29E+05-1.87E+03

estress Min.
Value
-2.84E+13-5.18E+06-2.50E+05-4.25E+05-2.56E+05-2.57E+05

c-ϕ Soil
Table 4 c-ϕ Results

Undrained clay

1.5

FOS

estressMax.
Value
1.16E+05
9.99E+04
8.61E+04
7.30E+04
6.00E+04
4.18E+04

h/w

Drained sand had an immediate failure in eachcase, due to the zero cohesion material property. The
sand immediately fails under self-weight as thepossibility of stability can only come from its nonzero (35ᵒ) friction angle. Factor of safety calculationsin FLAC are not stable for immediate failure, due toits strength reduction process requiring a transition ofstrength until the limiting parameter is found to
produce failure and the sand fails immediately, notallowing for this transition. Force relaxation methods
through FLAC are evidently more relevant for weaksoils [4]. Although factor of safety calculations havea more practical analysis by giving the stability of a
scenario in the form of a single number.

A typical FLAC mesh (h/w=1.667).

case

case

1

case

h/w

FOS

1
2
3
4
5
6

1.667
2
2.5
3.33
5
10

0.518
0.604
0.748
1.006
1.494
2.595

estressMax.
Value-1.96E-03-2.43E-02-3.30E-03-6.74E-03-2.17E-03-1.53E+00

estressMin. Value-5.65E+05-5.09E+05-4.21E+05-3.46E+05-2.53E+05-2.16E+05

0.5
0c-ϕ soil30

5 (h/w) ratio 10

15

2.5

FOS

2

Fig. 6

FOS vs h/w ratio plot (undrained clay).

1.5
1

The clay results showed an increasing factor ofsafety with depth, or with increase of the h/w ratio(Fig. 6). This is as expected. Clay’s cohesion has theability to the support its self-weight above a cavity
opening. The deepest case, or narrowest opening
width had a factor of safety larger than 1, indicating asafe case with substantial self-support of its selfweight over the cavity opening

0.5
0

0

Fig. 7247

24 (h/w)6 ratio 8

FOS vs h/w ratio plot (c-ϕ soil).

1012GEOMATE- Brisbane, Nov. 19-21, 2014

Plasticity and Shear Strain Ratec-ϕ soil had the most stable cases due to theinclusion of both the friction angle and cohesion. The
trend increase from shallow to deep case, or widecavity to narrow cavity with increasing h/w ratio wasnear linear (Fig. 7). Friction angle adds to the abilityof a soil to withstand it’s self-weight over a cavity
along with its cohesion.
Effective Principle Elemental Stresses

Fig. 11
Plasticity & max. shear strain rate vectors(undrained clay; h/w = 5)

Fig. 8 Principle stress vectors (undrained clay;
h/w = 5)

Fig. 9h/w = 5)

Fig. 12
Plasticity & max. shear strain rate
vectors (drained sand; h/w = 5)

Principle stress vectors (drained sand;Fig. 13 Plasticity & max. shear strain rate vectors(c-ϕ; h/w = 5)

Fig. 10

From the plasticity plots no indicator represents
elastic, a green cross represents yield in the past anda red cross represents present yielding. The present
yielding is an indication of the collapse failure plane,
as with the shear strain rate and y-displacement
contour plots. Shear strain rate being the rate ofchange of shear strain. Shear strain is a measure of
deformation, the change in location of a particle fromits original location perpendicular to a plane of theoriginal location. Shear strain rate being an indicationof the rate of deformation and thus is also a
representation of the slip failure plane of thesinkholes. The shear strain rate for Drained Sand incases 1 to 5 exhibited chimney failure.

Principle stress vectors (c-ϕ; h/w = 5)

The effective elemental principle stresses wereplotted for each case. For the plots it is evident that anarching effect occurs in all cases, apart from cases 1
to 5 for sand, where the immediate collapse produceda chimney type failure. The arching process is amechanism of stress relocation of the opening of acavity to attempt to support the soils own self-weight
before collapsing into the cavity. Increase the cavity
width, or shallowness, stretches the arching effect,
reducing the factor of safety and opportunity forstability.

248

GEOMATE- Brisbane, Nov. 19-21, 2014

factor of safety method of calculating the stability ofsinkholes has been proven to be successful. The factorof safety calculation represents a practical method todetermining the stability and safety of overburden
above a cavity opening.
c-ϕ soil was more stable when compared toundrained clay and drained sand. Zero cohesion soils
appear to fail immediately once the cavity is open. A
non-zero friction angle though does aid in increasing
safety and stability of overburden. An arching effectof soil stresses appears to play a key role in thestability of the overburden.
Future work is to attempt to model in three
dimensions, for a more realistic sinkhole simulation.
Also to conduct another, final physical model test
based on the initial design.

Y-Displacement Contours

Fig. 14 Y-displacement contours (undrained clay;
h/w = 5)ACKNOWLEDGEMENTS
Appreciation is due to Mr. David Lamb for aiding
with the construction of the initial physical model
design.
Fig. 15h/w = 5)

Y-displacement contours (drained sand;

REFERENCES[1] Augarde, C Andrei, L Sloan, S 2003, Predictionof Undrained Sinkhole Collapse, Journal of
Geotechnical and Geoenvironmental
Engineering, March 2003 p.197-205.
[2] Lei, M Gao, Y Jiang X, Hu, Y 2005,
Experimental Study of Physical Models for
Sinkhole Collapses in Wuhan, China, Sinkhole
and the Engineering and Environmental Impactsof Karst.
[3] Potential Impacts from Underground Mining
2006, Bureau of Mining, Pennsylvania
Department of Environmental Protection.
[4] Shiau, J, Kemp, R 2013, 'Developing a
Numerical Model for the Stability Design ofTunnel Heading', Third International Conference
on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan.
[5] Tharp, T 2003, Cover-Collapse Sinkhole
Formation and Soil Plasticity, Sinkholes and theEngineering and Environmental Impacts of Karst,
American Society of Civil Engineers.
[6] Zisman, E.D 2003, Sinkhole Size, BTL
Engineering Services, North Occident Street,Tampa, Florida.

Fig. 16 Y-displacement contours (c-ϕ; h/w = 5)
The y-displacement contour plots represent the
behaviour of the vertical movement or slump of thesoil after the cavity is open. The more shallow thecase, or wider the cavity, more of an extent thecontours will cover. Undrained clay has narrower
contours when compared to c-ϕ soil and drained sand.
Drained sand for cases 1 through 5 exhibited chimney
type failure again.
CONCLUSION
This paper has successfully demonstrated thecollapse mechanism of a sinkhole via physicalmodeling. Through 2D analysis software FLAC,

249

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECT OF TEMPERATURE AND LIQUID CHEMISTRY ON
GEOTECHNICAL AND HYDRAULIC PROPERTIES OF BENTONITE
H. M. A. Rashid1, K. Kawamoto1,2 , T. Komatsu1, T. Saito1. and P. Moldrup3
1
Graduate School of Science and Engineering, Saitama University, Japan.
2
Institute for Environmental Science and Technology, Saitama University, Japan3
Department of Civil Engineering, Aalborg University, Denmark

ABSTRACTThis study investigated the effect of single-species salt solutions on geotechnical properties (swell index andliquid limit) and hydraulic conductivity of bentonite applying different cations, concentrations, and temperatures.
Results showed that both the swell index and the liquid limit decreased with increase in salt concentration
irrespective of the type of cation. Monovalent cations showed higher values of the swell index and the liquid
limit compared to divalent cations. In general, the swell index of bentonite increased whereas the liquid limit
decreased with increasing temperature for all cation types and concentrations. Significant and high correlations
were found between swell index and liquid limit of bentonite at all three temperatures. Hydraulic conductivity ofbentonite was found to increase with increasing temperature. No significant change in hydraulic conductivity
with time was observed for all concentrations and cation types, and, overall, concentration and valance of cations
had little effect on the hydraulic conductivity of bentonite.
Keywords: Bentonite, Hydraulic conductivity, Liquid limit, Swell index, Temperature effects

geotechnical properties and hydraulic performanceof bentonite. For example, Ishimori and Katsumi [1]has investigated the effects of temperatures (20 oC
and 60 oC) on the swelling capacity and barrier
performance of bentonite using deionized water (DIwater) and three different concentrations (0.1 – 0.4
M) of NaCl solutions and found that swell andintrinsic permeability increase with increase intemperature. Other studies were focused on
hydraulic conductivity [16] - [17] and hydromechanical behavior [18] using only water for
specific applications in high level nuclear waste
repertories. Therefore, the combined effect oftemperature and liquid chemistry is still to beinvestigated to fully understand the behavior of GCL
liners in long term performance of landfills.
This study investigated the effects of singlespecies salt solutions on geotechnical properties(swell index and liquid limit) and hydraulicconductivity of bentonite applying different cations,concentrations, and temperature. Thirteen solutions,(DI water and twelve salt solutions of four major
exchangeable cations (Na+, K+, Ca2+, Mg2+), each atthree different concentrations (0.01M, 0.1 M, 1M))
were used as hydrating liquids. The swell index andliquid limit tests were carried out using all thethirteen solutions at three different temperatures(20 oC, 40 oC and 60 oC). The hydraulic conductivity
was evaluated using DI water, NaCl 0.01M andintermediate concentrations (0.1M) of all the four
cation solutions at 20 oC and 40 oC. The hydraulicconductivity tests were followed by the pore size
distribution analysis to understand the solute

INTRODUCTION
Geosynthetic clay liners (GCLs) are widely used
as an essential component of bottom liner system oflandfills for solid waste disposal. GCLs offer a final
defense against the migration of landfill leachate
into the underlying environment [1]. The main
component of GCL responsible for its barrier
performance is sodium bentonite, which is primarily
composed of clay mineral sodium montmorillonite
while the minor constituents include quartz,
feldspars, carbonates and micas [2]. Sodium
montmorillonite is characterized by its large specificarea, high cation exchange capacity and highswelling potential which are responsible for thedesirable physical and chemical properties ofbentonite [3].
The biodegradation of organic waste inside
landfill produces a chemical substance, leachate,
which, when it comes in contact with the bentonite
component of GCL, can alter its geotechnical andhydraulic properties as barrier material. In addition
to the generation of leachate, the biodegradation oforganic substances also generates heat, which can
result in an increase of temperature inside thelandfill up to 60 oC [4] - [7]. Chemicals in landfill
leachate, coupled with a rise in temperature, canaffect the geotechnical and hydraulic performance ofbentonite. A number of researchers haveinvestigated the effects of chemicals on theproperties of bentonite [2], [8] - [15]. However, avery few researches have reported the combined
effect of temperature and liquid chemistry on
250

GEOMATE- Brisbane, Nov. 19-21, 2014transport phenomenon through the bentonite.

in triplicates and averages were used for subsequent
analysis.

MATERIAL AND METHODS
Liquid Limit Tests
The bentonite used in this study was sodium
bentonite extracted in powdered form fromcommercially available GCL (Bentofix®, NAUE
GmbH & Co. KG, Germany). The bentonite passed
through US sieve no. 200 (75 µm) was oven dried at
105 oC for subsequent testing. The particle densityof bentonite for this typical GCL was 2.61
g/cm3 [19]. The natural water content, liquid limit,
plastic limit and swell index were measured using
ASTM Standards. The results are given in Table 1.

The liquid limit tests were carried out using themultipoint test method in accordance with ASTM
4318-10. The bentonite samples were prepared bythoroughly mixing the oven dried bentonite witheach hydrating liquid at different moisture contents.
The samples were then allowed to hydrate for atleast 24 hours in double wrapped sealed plastic bags
at specified temperatures (20 oC, 40 oC and 60 oC).
To avoid evaporation during the hydration process,wet tissue papers were kept between the bothwrappings. The samples were remixed before
starting the experiment. A minimum of five trials
were performed for each test and the liquid limit wasdetermined using equation of the flow curve.

Table 1 Physical Properties of Bentonite
Property
Natural water content
Liquid Limit
Plastic Limit
Plasticity Index
Swell Index
Particle density

Unit
%
%
%
%
mL/2g
g/cm3

Value
11.78
559
51
508
30
2.61

Hydraulic Conductivity Tests
Constant head hydraulic conductivity tests wereconducted using a rigid wall permeameter as shownin Fig. 1. The apparatus consisted of a lower ring, a
middle ring and an upper ring placed between an
upper and lower cap all made of acrylic. First, thebentonite samples were prepared with thepermeating solution with a moisture content equal toits liquid limit for that particular solution, andallowed to hydrate for at least 24 h in sealed plasticbags. After 24 h, the prehydrated bentonite samples
were placed in the circular middle ring with a porous
filter at the bottom placed on the top of lower ring.
Typically the inner diameter of the middle ring was
6 cm with a height of 1 cm, which represents the

The permeant solutions used in swell index andliquid limit tests were DI water and the salt solutionsof NaCl, KCl, CaCl2 and MgCl 2 . Concentrations ofsolutions were varied from 0.01 M to 1 and the tests
were carried out at three different temperatures(20 0C, 40 0C and 60 0C ). Hydraulic conductivity
tests were carried out using DI water, NaCl 0.01M
and intermediate concentrations (0.1M) of all thefour cation solutions at two different temperatures(20 0C and 40 0C). The cations were selected
because they are major exchangeable cations inbentonite Na+, K+, Ca2+ and Mg 2+ [20]. Chemicals
used for making solutions were purchased in
powdered form and their formula weights weremixed with DI water to prepare the desired chemicalsolution.

Mariotte Tank

Threaded Rod∆h=30 cm

Top Plate

Swell Index Tests

Upper Ring

The swell index tests were carried out inaccordance with ASTM D5890. Initially, 2 g of ovendried bentonite was dusted into a 100 mL graduatedcylinder filled with 90 mL of hydrating solution.
Then, after the dusting of bentonite was completed,the cylinder was filled upto the 100 mL mark withthe same solution washing the particles adhering to
the walls of the cylinder. The cylinder was thencovered with plastic wrap to prevent evaporation andcarefully placed in a climate control room with atemperature maintained at 20 oC or placed in anoven for elevated temperatures (40 oC or 60 oC).
The cylinders were kept undisturbed for 24 h prior totake the readings. The measurements were repeatedMiddle Ring
Bentonite
SampleLower Ring
Bottom Plate

dimensions of the sample.
Fig. 1 Schematic of hydraulic conductivity test
apparatus
The lower ring was first filled with permeating
solution, then sample was placed in the middle ring251

GEOMATE- Brisbane, Nov. 19-21, 2014

by slight tamping, making due care to prevent
entrapment of air bubbles inside the sample. A
porous filter was then placed on top of the sample insuch a way that the sample was sandwiched between
the lower and upper porous filters to avoid washing
off of the soil particles during the tests. After placing
the sample and porous filters, the upper ring wasplaced on top of the middle ring and the cell was
clamped after placing the top cap. To avoid leakage
of water at the contact points, silicon grease wasused.
The permeant solution was then supplied from a
Mariotte tank to the sample through an inlet valve ofthe lower cell allowing the escape of air bubbles.
Once the permeating solution started coming out of
the sample ensuring that all air bubbles have escaped,
the upper ring was then filled with the permeating
solution up to a height equal to that of the lower ring
and whole cell was made airtight. After that, thewhole setup was placed in the climate controlled
room with temperature maintained at 20 oC or in an
incubator with a pre-set temperature of
40 oC. Permeant solution was then supplied to thesample from the Mariotte tank through an inlet valveof the lower ring while maintaining a constant headof 30 cm across the sample which correspond thehydraulic gradient. The effluent was collected froman outlet valve of the upper ring in a collecting jar at
specified intervals of time. To measure theevaporation, a reference jar with an opening equal tothe colleting jar was placed near the apparatus in thesame environment and the evaporated volume wasadded to the measured volume to minimize theeffect of evaporation during the test. The tests were
continued for several days and hydraulicconductivity was calculated using Darcy’s law [21].
The tests were conducted up to 100 days andelectric conductivity (EC) and pH of the effluent
was measured during the test period in addition to
the hydraulic conductivity. After terminating thetests, weight of the each sample was measure andone part of it was taken to measure the moisture
content (w), porosity (ɸ), and void ratio (e) while therest was freeze-dried to measure the pore size
distribution using Mercury Intrusion Porisometery(MIP).

molecule enters the interlayer. The later phase canoccur only when the exchange sites are occupied bymonovalent cations [22] - [23] having Δradius(hydrated radius - ionic radius) to valance ratio ofgreater than 300 and more than three hydration
shells (limited to Na+ and Li+) [3].
The swell index seems to be highly controlled
by concentration of the solution in bulk pore water
as shown in Fig. 2. It was observed that the swell
index decreased with increase in concentration
irrespective of the type of cation. This finding is
consistent with the studies conducted by Jo et al.
[10] who explained the phenomenon as a result of
the moving out of the interlayer water due togradient in free energy caused by the elevatedconcentrations in bulk pore water.

Swell Index (mL/2g)

40.0
30.0

NaCl
KCl
CaCl2
MgCl2

DI Water

20.0
10.0
0.0
0.001

0.01

0.1

1

Concentration (M)Fig. 2 Effect of liquid chemistry on swell index of
bentonite
The highest value of the swell index was
observed for the bentonite samples hydrated with
NaCl solution at low concentration (0.01M)
followed by the samples hydrated with DI water. As
the bentonite is hydrated with NaCl solution, allexchange site are occupied by Na+ cation which takepart in osmotic swelling phase resulting an increasein swell volume. All other cations were found to
give similar values of swell index at allconcentrations with the lowest value of the swellvolume obtained for the bentonite samples hydrated
with high concentration (1M) of KCl solution.
Temperature of the hydrating liquid was found tohave significant effect at lower concentrations ofmonovalent cations as shown in Fig. 3 (a) and Fig 3(b). At intermediate and high concentrations,however, the effect was insignificant. It wasobserved that for bentonite samples hydrated with
DI water and low concentrations of monovalentcations, swell index increased with increase intemperature. Contrary to this, there exist a tendency
of decrease in swell index with an increase intemperature at all concentrations for divalent cations
as shown in Fig. 3 (c) and Fig. 3 (d).

RESULTS
Swell Index Tests
The swelling of bentonite can be explained as atwo phase process [3]. First phase known as“crystalline swelling” occurs at small scale and amaximum of three to four layers of water molecules
can be adsorbed in the interlayer around theinterlayer cations which corresponds to less than
25% by mass. This phase is then followed by“osmotic swelling” where numerous layers of water
252

10.0

40.0

0.01
0.1
Concentration (M)

(c)

30.0
20.0
10.0
0.0
0.001

0.01
0.1
Concentration (M)

1

30.0

limit was found to decrease slightly with increase intemperature. DI water showed the highest value ofliquid limit (559%) when hydrated at 20 oC. The
liquid limit was lowest at 60 oC (524%). A similar
trend of decrease in liquid limit with increase intemperature was found with bentonite hydrated with
NaCl solution at low concentrations. However, athigh concentrations the effect of temperature was
not significant. Temperature was found to haveinsignificant effect on the liquid limit of bentonite
hydrated with KCl and divalent cation solutions(CaCl2 and MgCl2 ).

KCl 20 oC
KCl 40 oC
KCl 60 oC
DI Water 20 oC
DI Water 40 oC
DI Water 60 oC

20.0
10.0
0.0
0.001

1

CaCl2 20 oC
CaCl2 40 oC
CaCl2 60 oC
DI Water 20 oC
DI Water 40 oC
DI Water 60 oC

(b)

40.0

0.01
0.1
Concentration (M)

(d)

30.0

1

MgCl2 20 oC
MgCl2 40 oC
MgCl2 60 oC
DI Water 20 oC
DI Water 40 oC
DI Water 60 oC

20.0
10.0
0.0
0.001

0.01
0.1
Concentration (M)1

Fig.3 Effect of temperature on swell index of
bentonite

600

NaCl 20 oC
NaCl 40 oC
NaCl 60 oC
DI water 20 oC
DI Water 40 oC
DI Water 60 oC

(a)

500
400
300
200

Liquid Limit (%)

20.0

40.0

Liquid Limit (%)

30.0

0.0
0.001

Swell Index (mL/2g)

NaCl 20 oC
NaCl 40 oC
NaCl 60 oC
DI Water 20 oC
DI Water 40 oC
DI Water 60 oC(a)Swell Index (mL/2g)

40.0

Swell Index (mL/2g)

Swell Index (mL/2g)

GEOMATE- Brisbane, Nov. 19-21, 2014100

Liquid Limit (%)

Effect of liquid chemistry
Figure 4 is showing the effect of liquid chemistryon the liquid limit of bentonite.

600

0.01
0.1
Concentration (M)

(c)

400
300
200

400

0.01
0.1
Concentration (M)(d)

1

MgCl2 20 oC
MgCl2 40 oC
MgCl2 60 oC
DI Water 20 oC
DI Water 40 oC
DI Water 60 oC

500
400
300
200
100

0.01
0.1
Concentration (M)

0
0.001

1

0.01
0.1
Concentration (M)1Fig. 5 Effect of temperature on liquid limit ofbentonite

300

Correlation between Swell Index and Liquid
Limit

200
100
0.01
0.1
Concentration (M)A comparison between the swell index and theliquid limit of bentonite is shown in Fig. 6. It was
found that significant and high correlations exist
between the both geotechnical properties at all
temperature (Fig. 6 (a) – Fig. 6 (c)).

1Liquid Limit (%)

Fig. 4 Effect of liquid chemistry on liquid limit ofbentonite
It was observed that liquid limit decreased withincrease in salt concentration irrespectively of thetype of cation. The liquid limit was highest (559 %)with DI water. The liquid limit was found to be
similar at very low (0.01M) and very high (1M)
concentrations irrespective of the hydrating liquid.
However, at intermediate concentration (0.1M), bothmonovalent cations show higher values of the liquid
limit than divalent cations, with highest value of theliquid limit obtained for bentonite hydrated with
NaCl solution. Both divalent cations showed similarvalues of the liquid limit at all concentrations.

600
500
400
300
200
100
0
0

Liquid Limit (%)(a)

y = 18.816x + 13.335
R² = 0.9421

700
600
500
400
300
200
100
0

Liquid Limit (%)

0
0.001

600

10
20
30
Swell Index (mL/2g)

0.01 M
0.1 M
1M
DI Water(b)y = 15.353x + 66.512
R² = 0.9327

0.01 M
0.1 M
1M
DI Water0(c)y = 13.959x + 49.562
R² = 0.9068

600
500
400
300
200
100
0

40

10
20
30
Swell Index (mL/2g)

40

(d)

20

Slope (tan ϴ)

Liquid Limit (%)

500

300
200
0
0.001

CaCl2 20 oC
CaCl2 40 oC
CaCl2 60 oC
DI Water 20 oC
DI Water 40 oC
DI Water 60 oC

500

0
0.001

NaCl
KCl
CaCl2
MgCl2

DI WaterKCl 20 oC
KCl 40 oC
KCl 60 oC
DI Water 20 oC
DI Water 40 oC
DI Water 60 oC

400

1

100

600

(b)

500

100

0
0.001

Liquid Limit (%)

Liquid Limit Tests

600

15
y = -0.1215x + 20.904
R² = 0.9429

10
5
0

0

10
20
30
Swell Index (mL/2g)

40

0

20
40
Temperature (oC)60

Fig. 6 Correlation between swell index and liquid
limit

Effect of temperature

Figure 6 (d) is showing the relationship between
slopes of the regression lines with temperature. It
can be seen that the slope decreases with increase in

The effect of temperature on the liquid limit ofbentonite is shown in Fig. 5. In general, the liquid
253

GEOMATE- Brisbane, Nov. 19-21, 2014

temperature which shows the temperaturedependence of both the geotechnical properties.

reased and total porosity (Φ) decreased with theincreasing salt concentration. This suggests that thewater bound in the interlayer pores actually do nottake part in the hydraulic conductivity of bentonite.
Supporting this, the available pore space for the flow(the effective porosity of bentonite) did not change
significantly with change in salt concentrations, seein Fig 8.

Hydraulic Conductivity
Hydraulic conductivity of bentonite wasmeasured using all the thirteen permeant liquids. It
was observed that for all cation types andconcentrations, hydraulic conductivity do not change
significantly with time. The duration of permeation(t), total pore volumes of flow (PVF), total porosity(ɸ) and void ratio (e) of each permeated sample isshown in table 2.

0.008

Incremental pore Volume (mL/g)

NaCl 0.01M

Table 2 Summary of hydraulic conductivity tests

DI water

e

0.01
0.1
1
0.01
0.1
1
0.01
0.1
1
0.01
0.1
1
-

20
109
35
123
78
76
95
111
106
79
89
97
108

2.4
8.9
5
11
41
189
112
71.8
84.8
124
29
51
4.8

0.94
0.91
0.69
0.91
0.90
0.69
0.92
0.81
0.73
0.91
0.82
0.71
0.94

17.4
10.17
2.27
10.43
9.93
2.32
12.01
4.42
2.73
10.51
4.79
2.45
15.44

MgCl2 0.1M
0.004

DI Water

0.003
0.002
0.001
0
0.001

0.01

0.1

1
10
Mean Dia (µm)

100

1000

10000

Fig. 8 Pore size distribution of bentonite samples
permeated with DI water and salt solutions
Hydraulic conductivity test conducted at 20 oC
and 40 oC showed that hydraulic conductivity as
expected increases slightly with temperature; see
Fig. 9.
(DI Water)

1.0E-04
1.0E-05

20 0C
40 0C

1.0E-06
1.0E-07(NaCl 0.01M)

1.0E-04
1.0E-05

20 0C

1.0E-06

40 0C

1.0E-07

1.0E-08

1.0E-08

1.0E-09

1.0E-09

1.0E-101.0E-101.0E-11

1.0E-110

Figure 7 is showing the effect of concentration
on average hydraulic conductivity of bentonite.
Hydraulic conductivity was found to increase withincrease in concentration for the samples hydrated
with KCl solutions. For other cations, however,concentration was found to have little effect onbentonite samples even though the void ratio (e) inc-20

1.0E-0440
60
80
100 120
Time (days)(NaCl 0.1M)

0

20
40
60
Time (days)(KCl 0.1 M)

1.0E-04
1.0E-05

1.0E-05

20 0C

1.0E-06
1.0E-07

20 0C
40 0C

1.0E-06

40 0C

1.0E-07
1.0E-08

1.0E-08

1.0E-09

1.0E-09
1.0E-101.0E-101.0E-11

1.0E-11

0

20

40

60

80

100

120

0

20

Time (days)

Hydraulic Conductivity, k (cm/s)

Avg. hydraulic conductivity, k (cm/s)

CaCl2 0.1M

Hydraulic Conductivity, k (cm/s)

MgCl2

ɸ

NaCl 1M

0.005

Hydraulic Conductivity, k (cm/s)

CaCl2

PVF

NaCl 0.1 M

0.006

1.0E-04(MgCl2 0.1 M)

1.0E-04
1.0E-05
1.0E-06
1.0E-07
1.0E-08
1.0E-09
1.0E-101.0E-11

20 0C
40 0C

0

20

40

60

80

100

Hydraulic Conductivity ,k (cm/s)

KClt(days)

Hydraulic Conductivity, k (cm/s)

NaCl

Conc.
(M)

Hydraulic Conductivity, k (cm/s)

Permeant
Liquid

0.007

40
60
Time (days)

80

100

(CaCl2 0.1 M)

1.0E-04
1.0E-05

20 0C
40 0C

1.0E-06
1.0E-07
1.0E-08
1.0E-09
1.0E-101.0E-110Time (days)

20

40
60
80
Time (days)

100

120

1.0E-05

Fig. 9 Effect of temperature
conductivity of bentonite.

1.0E-06
1.0E-07
1.0E-08

DI water

1.0E-101.0E-11
0.001

0.01

0.1

hydraulic

CONCLUSIONS

NaCl
KCl
CaCl2
MgCl2

1.0E-09on

The study investigated the effect of temperatureand liquid chemistry on swell index, liquid limit andhydraulic conductivity of bentonite. Concentrationand type of cation were found to have significant
effect on swell index and liquid limit of bentonite.
However, the effect was small for hydraulicconductivity. It was found that the hydraulic1

Concentration (M)Fig. 7 Effect of cation concentration on hydraulicconductivity of bentonite.
254

GEOMATE- Brisbane, Nov. 19-21, 2014[11] Jo HY, Katsumi T, Benson CH, and Edil TB,“Hydraulic conductivity and swelling of nonprehydrated GCLs permeated with single
species salt solutions”, J. of Geotech. andGeoenv. Engg., Vol. 127 (7), July 2001, pp.
557–567.
[12] Shan HY, and Lai YJ, “Effect of hydrating
liquid on the hydraulic properties ofgeosynthetic clay liners”, Geotextiles andGeomemberanes.,Vol. 20, Feb. 2002, pp. 19-38[13] Kolstad DC, Benson CH, and Edil TB,“Hydraulic conductivity and swell of
nonprehydrated geosynthetic clay liners
permeatedwithmultispecies
inorganic
solutions”, J. of Geotech. and Geoenv. Engg.,
Vol. 130 (12) Dec. 2004, pp. 1236–1249.
[14] Katsumi H, Ishimori A, Ogawa K, Yoshikawa
K, Hanamoto R, and Fukagawa, “Hydraulicconductivity of nonprehydrated geosynthetic
clay liners permeated with inorganic solutions
and waste leachates” Soils and Foundations,Vol. 47 (1), 2007, pp. 79–96[15] Kaufhold, S, and Dohrmann, R, “Stabiltiy ofbentonite in salt solutions | sodium chloride”
Applied Caly Science, Vol. 45, May 2009, pp.
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[17] Cho WJ, Lee JO, and Chun KS, “Thetemperature effects of hydraulic conductivity ofcompacted bentonite”, Applied Clay Science,Vol. 14, Aug. 1999, pp. 47 – 58.
[18] Villar, MV, and Lloret, A, “Influence oftemperature on the hydromechanical behavior
of compacted bentonite”, Applied Clay Science,Vol. 26, Aug. 2003, pp. 337 – 350.
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and Lake CB, “Diffusion of
Sodium and Chloride through Geosynthetic
Clay Liners”, Geotextiles and Geomembranes,
Vol. 18, April 2000, pp. 103-131[20] Komine, H, and Ogata, N, “Predicting Swelling
Characteristics of Bentonite”, J. of Geotech. andGeoenv. Engg., Vol. 130 (8), Aug. 2004, pp.
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[21] Darcy H, “Les fontaines publiquis de la ville deDijon”, 1856, Dalmont, Paris.
[22] Norrish K, and Quirk J, “Crystalline swelling ofmontmorrilonite, use of electrolysis to controlswelling”, Nature,Vol.173,Feb. 1954, 255 – 257.
[23] Jellandar R, and Mareelja S, “Attractive doublelayer interaction between calcium clay
particles”, J. of Colloid and Interface Science,Vol. 126 (1), Nov. 1988, pp. 194 – 211.

conductivity is mainly controlled by the effective
porosity rather than the total porosity. Liquid limit
was found to decrease whereas swell index andhydraulic conductivity were found to increase withincreasing temperature.
ACKNOWLEDGEMENTS
This work is partially supported by JST-JICA
SATREPS project.
REFERENCES[1] Ishimori H, and Katsumi T, “Temperatureeffects on the swelling capacity and barrier
performance of geosynthetic clay liners
permeated with sodium chloride solutions”,
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[3] Likos WJ, Bowders JJ, and Gates WP,“Minerology and engineering properties ofbentonite”, Geosynthetic Clay Liners for Waste
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[4] Yoshida H,
Hozumi H, and Tanaka N,“Theoretical study on temperature distribution
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255

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

CASE STUDY OF GEOGRID REINFORCED SEGMENTALRETAINING STRUCTURE
Jia Xie1, Barry Wai-Choo Kok2, Jeroen Berends3 and Martin Silec4
Geotechnical Engineer, 2.3Principal Geotechnical Engineer, Geoinventions Consulting Services,
Australia. 4Managing Director, Concrib Pty Ltd, Australia.

1

ABSTRACT
A geogrid reinforced Keystone® segmental retaining wall structure was designed for a large industrial projectin Redbank, southeast Queensland, Australia. The 230m long segmental retaining structure with a maximum heightof 7.2m has recently been completed. Insufficient ground bearing capacity was identified due to the presence ofsoft to firm clay and ground improvement was required to address this issue. The worst ground condition appeared
to be underneath the highest section of the structure, as it is located within the vicinity of the creek crossing.
Considering the size of the Keystone® blocks, the significant height of the structure and the unsatisfactory groundcondition, excessive wall deflection and differential settlement were the key issues for the design. In addition to
the conventional stress-based limit equilibrium design approach, the strain-based approach was adopted to addressthese design challenges. This paper describes the design and analysis methodology adopted to mitigate the longterm performance risk. The results of the finite element and limit equilibrium assessments will be presented anddiscussed.
Keywords: Geogrid reinforced segmental wall, Ground improvement, Stress-based approach, Strain-based
approach, Long term serviceability

stress-strain behaviour of the structure and provides
more comprehensive solutions for structures sensitive
to deflection or settlement.
This paper presents the design approach andanalytical results of the most critical section of ageogrid reinforced segmental retaining wall. The
design considers the stability and long term
performance of the structure. Stability assessment
was conducted by using limit equilibrium commercial
software Slope/W. Displacement of the structure
were simulated by finite element commercial
software Phase2. The outcomes concluded from thiscase study could provide a helpful reference fordesign and analysis of geogrid reinforced Keystone®
segmental retaining structure in south-east
Queensland.

INTRODUCTION
A new industrial development at Monash Road,
Redbank, Queensland required an in total 230m long
geosynthetics reinforced segmental retaining
structure. The facing comprised the Keystone®
modular masonry concrete units with the nominal unit
dimensions of 203mm (H) x 457mm (W) x 315mm(D). The structure was reinforced by high-tenacity
woven polyester geogrids at 600mm vertical spacing.
The most critical section of the structure is in excess
of 7.2m high and founded on soft to firm clay layer.
Geosynthetic reinforced soil structures wereintroduced in the 1970’s. The use of dry-stacked
columns of interlocking modular concrete units as thefacing for geosynthetic reinforced retaining wall
structures were first appeared in the mid-1980’s, andhas since increased rapidly [1], [2], [3]. McGown [4]pointed out that the geosynthetic reinforced soil
structures were adopted in practice successfully firstand researched and standardised later. Therefore,technically efficient and reliable design and analysis
approaches have been of great concern formaintaining the confidence of the industry
practitioners.
Stress-based limit equilibrium approach has been
employed dominantly to date. The limitation of thisapproach is that it deals with all loads as pseudo-static
loads and does not take the strains into account. To
address this shortcoming, strain-based finite element
design approach has been adopted lately. It studies the

DESIGN METHODOLOGY
Current Design Practices Review
The most common design and analysis
methodologies of segmental retaining walls can befound in guidelines published by Federal Highway
Administration (FHWA) [5]; the National Concrete
Masonry Association (NCMA) [6]; and the American
Association of State Highway and Transportation
Officials (AASHTO) [7], [8]. All of these guidelines
are based on stress-based limit equilibrium approach[9]. This approach generally treats all types of loads
as pseudo-static loads and with no regard to the stress256

GEOMATE- Brisbane, Nov. 19-21, 2014

soil parameters are listed in Table 1.

strain behavior of various structures under different
loading combinations. This can lead to insufficientdesign considerations on the long term performanceof the structure induced by displacement.
Apart from the conventional limit equilibrium
approach, FHWA guideline [5] also suggests thatboth total and differential settlements should beconsidered, however, there is no standard method toevaluate the overall displacement of reinforced soil
wall.
Berg et al. [10] and Greenway et al. [11] carriedout systematic studies of the design methods andassessment techniques adopted in North America for
Geosynthetic Reinforced Soil Structures since the1970’s. They revealed that slight modification has
been made on design codes and guidelines to date.
The design of the reinforced segmental retaining wall
requires analytical models and performance data
unique to this system [9]. More specific andcomprehensive design approach should be adopted.

Table 1 Properties of the structure materials
Material
Properties

Reinforced FillControlled Fill
Crushed RockSoft to Firm
Clay
Firm to Stiff
Clay
Stiff to Very
Stiff Clay

Frictionangle,
φ’ d
(Deg)
36
28
45
26

Unit
weight,γ(kN/m3)
20
18
20
16

Cohesion,

28

18

3

30

19

5

c’
(kPa)
0
5
0
2

Minimum embedment depth was computed as
total wall height/20 in accordance with Roads andMaritime Services (RMS) Specification R57. To
prevent potential bearing failure due to the excessive
vertical stress and insufficient bearing capacity of thesoft clay layer, a 750mm thick layer of crushed rockfill was adopted as the ground improvement option to
replace the existing soft clay layer. In addition, a
300mm concrete footing was casted beneath the
Keystone® blocks as raft foundation.
Uniaxial polyester geogrids Miragrid® 8XT wereadopted as reinforcement in the design. The long term
design strength of the reinforcement was determinedby applying partial factors for durability, installation
damage and creep for a 120 year design life. The longterm design strength was adopted as 49.7kN/m.
A 20kPa uniformly distributed load was adopted
to simulate the traffic loading on top of the structure.
Groundwater was defined in accordance with the
Q100 flood level recorded. The overview of thecompleted wall is shown in Fig. 1.

Regional and Local Geology
The structure is located within close proximity to
the Brisbane River, in the suburb of Redbank midway
between Brisbane and Ipswich. The regional geologyof the Ipswich Basin comprises sedimentary andigneous rocks of the Bundamba Group and Ipswich
Coal Measures. According to previous geotechnicalinvestigation of the area, the site was believed to beunderlain by alluvial soils which in turn overlies
sedimentary rocks of Ipswich Basin [12].
Additional site inspections were carried out prior
to this project and Dynamic Cone Penetrometer(DCP) tests were conducted to verify the local
geotechnical condition. The results indicated that thesubsurface soils consist of soft to stiff alluvial clay up
to 3.0m overlying stiffer alluvial soils. The worst
ground condition appears underneath the highest
section of the structure which is within the vicinity ofa creek crossing.
Design Requirements and Material Properties
The design life of the Keystone® segmental
retaining structure is 120 years in accordance with
Australian Standard (AS) 4678-2002 [13],categorized as major development zone by local
council. The structure was designed to support themain access road into the industrial park with highvehicle volume. The critical section for design is
7.2m high and founded on the soft to firm clay layer
up to 1.0m depth overlying 3.0m depth of firm to stiffclay.
The soil properties adopted in the retaining
structure were determined based on the site
investigation results and authors’ previous projectexperiences in southeast Queensland, Australia. For
limit equilibrium stability assessment, the adopted

Fig. 1 Overview of the completed wall.

257

GEOMATE- Brisbane, Nov. 19-21, 2014

height of structure. Strain-based design approach was
adopted to justify the design for long term
performance. The commercial finite element software
Phase2 was employed to assess the total, horizontal
and vertical displacements.
The initial finite element analysis focused on theregulated maximum allowable settlement and wall
face deflection of 50mm in accordance with AS46782002. However, this regulated allowance applies toall structures and does not consider the magnitude ofstructure height. This could lead to potential longterm serviceability issue for structures withsignificant height. In this design, the potential
cracking on the wall face induced by excessive tensile
strain was a significant long term performanceindicator. Bathurst and Simac [9] reported thatmodular concrete blocks have been observed to crack
in reinforced segmental retaining wall structures. The
appearance of cracking is not desirable from either
aesthetic or structural point of view, especially forhigh structures consist of smaller concrete blocks.
The differential settlement was summarized byAnderson [15] as one of the major sources causing
cracking. In this design, the critical section of thestructure was initially located on top of a 3.0m (W) x
1.5m (H) dimension concrete culvert which foundedon soft clay area as shown in Fig. 3. This layer wasthen replaced by a layer of crushed rock fill as ground
improvement option. The potential differential
settlement between the combination of wall andculvert section versus the full height wall section wasof primary concern.

Modelling and Analysis
The analysis conducted includes stress-based
limit equilibrium modelling to assess the global
stability of the structure, and strain-based finite
element modelling to assess the displacement of thestructure.
Stress-based approach – limit equilibrium analysis
Commercial software Slope/W 2012 was
employed to assess the global slope stability of thecritical cross sections of the structure to achieve aminimum factor of safety (FOS) ≥ 1.50. In this study,
the proposed geometries with and without ground
improvement layer were analyzed using theMorgenstern-Price method. The grid and radius
method was adopted to define circular trail failuresurfaces between specified coordinate limits and thecritical failure surface with the minimum FOS was
obtained [14].
Soil properties adopted in the stability
assessments are listed in Table 1. Instead of adopting
the conventional monolithic model for the
Keystone® wall, a new constitutive model wasdeveloped based on the large scale direct pull-out test
results
undertaken
byBathurst,
Clarabut
Geotechnical Testing, Inc. in Canada. The normal
stress versus shear stress relationship was modelled tosimulate the shear capacity and the operational
behavior of reinforcement at different wall heights. In
this design, pore-water pressure was defined by
piezometric line function in Slope/W based on thelocal Q100 flood level provided. It indicated a watertable of approximately 3.0m above the ground surface
at the critical wall section as shown in Fig. 2.

Fig. 3 Overview of concrete culvert section.
Due to the lack of standard method to evaluate theserviceability problem caused by displacement, amethodology introduced by Mair et al. [16] forclassifying the damage of masonry structures withprediction of ground movement and calculation ofstrains induced within the structure was adopted forthis study. It established an important link between
the estimated tensile strain and the potential damage
category, which thus provided a principle forverifying the segmental block wall design from theserviceability assessment perspective.
Six categories of damage was defined by Burland
et al. [17], numbered 0 to 5 in increasing severity.

Fig. 2 Slope/W model of geometry with ground
improvement.
Strain-based approach – finite element analysis
Part of the design risks of this project were thepotential wall deflection and excessive settlement due
to the soft clay foundation layer and the significant
258

GEOMATE- Brisbane, Nov. 19-21, 2014

would be required. However, the ground condition
underneath the highest section of the structure waslater found to be on a soft clay layer within a creek
vicinity and ground improvement option was required.
A 750mm thick layer of crushed rock fill was adopted
to replace the soft clay layer. The crushed rock fill
was designed to distribute the vertical stressuniformly into stiffer soil strata below and to prevent
excessive wall displacement.
The Slope/W result shown in Fig. 5 shows that the
FOS of structure founded on soft ground without
treatment is 1.36 thus does not meet the minimum
long term requirement of FOS 1.50 by local authority[19]. The Slope/W result illustrated in Fig. 6 indicatesthat the crushed rock fill effectively improved theground condition and the FOS increased to 1.51
which satisfied the long term stability FOS
requirement.

Extensive case histories were analyzed by Boscardin
and Cording [18], and the damage categories related
to the magnitude of the tensile strain induced in the
structure were summarized in Table 2. Based on thisrelationship, structures with induced tensile strain
greater than 0.3% which classified category 4 to 5
represent severe to very severe degree of damage andrequire extensive or major repair. Therefore, thesuggestion of 0.3% limiting tensile strain was adopted
to compare with the computed differential strain fromthe finite element analysis to justify the serviceabilityof the structure.
Table 2 Relationship between category of damage
and limiting tensile strain [18]Category ofdamage012
3
4 to 5

Normal degreeof severity
Negligible
Very slight
SlightModerate
Severe to very
severeLimiting tensile
strain (%)
0-0.050.05-0.075
0.075-0.15
0.15-0.3>0.3

The finite element geometry was modelled withand without crushed rock fill ground improvement.
The mesh was defined as a uniform pattern ofapproximately 1500 triangular elements with 6 nodes
as shown in Fig. 4. The analysis will compute thevariation of stress and strain throughout the mesh.
The computed displacement outcomes were used toverify the long term serviceability of the structure.

Fig.

5

FOS of geometry
improvement.

without

groundFig. 4 Phase2 model with ground improvement.
RESULTS AND DISCUSSIONS
Fig. 6 FOS of geometry with ground improvement.

Effects of Soft Ground Improvement on the
Slope Stability

In order to further justify the effectiveness of theground improvement method, the slope stability
analysis of improved ground scenario were
undertaken with different friction angle of the crushedrock ranging from 30 degree to 60 degree. The
sensitivity check results illustrated in Fig. 7 presents
the trend of the FOS increasing linearly with the

To assess the stability of the structure in terms of
FOS, the analysis introduced in previous chapter was
conducted for different ground conditions. Prior todesign, it was reported that the in-situ ground bearing
capacity was sufficient and no ground treatment
259

GEOMATE- Brisbane, Nov. 19-21, 2014

friction angle of the crushed rock fill. It was noted thatin order to satisfy a FOS of 1.50, the crushed rockmaterial must achieve a minimum friction angle of 45
degree. In this project, the crushed rock material wastested and verified in the laboratory before
construction commenced.

Height of Wall (m)

8

1.8

FOS

1.7
1.6

6
4
2
0
30.0

36.0 42.0 48.0 54.0
Toal Displacement (mm)with crushed rock fill

1.5

without crushed rock fill

1.4

Fig. 9 Computed total displacement along wall facewith & without crushed rock fill.

1.3
30
35
40
45
50
55
60
Friction angle of crushed rock (deg)The strains percentage of wall displacement wasthen computed from the Phase2 results and checked
for the serviceability requirement. The strains alongwall face were calculated and the maximum value
was adopted to compare with the 0.3% of limiting
tensile strain described in previous chapter. The
estimated maximum strain on the wall face wascalculated as 0.26% based on total displacement
outcome shown in Fig. 8.
The result indicates that the potential strains
induced cracking on the face of the critical wall
section could be classified as category 3. It
corresponds to a moderate level of severity damage
according to Table 2. Implication of typical damageand ease of repair and maintenance were suggested by
Burland et al. [17]. This classification of damage
could be conservative and the original paper
suggested that there was no evidence of severe
damage resulted from the tensile strains up to 0.3%
by then. However, it provides a practicalmethodology for prediction of serviceability issue.
Thus enables the design to be evaluated from theserviceability perspective which is unable to beaddressed by stress-based analysis approach.

Fig. 7 FOS sensitivity check with different friction
angle of crushed rock.
Design Verification Using Strain-based Approach
As the long term excessive wall deflection anddifferential settlement were the key issues of thisdesign, it was justified by using the strain-based
approach described in previous chapter.
The finite element analytical results computed
using Phase2 were adopted to justify the requirements
stated in AS4678-2002 [20] which allows a maximum
50mm displacement. The comparison of thecomputed
maximumhorizontal and total
displacement on the wall face of geometries with andwithout crushed rock fill are demonstrated in Fig. 8
and Fig. 9. The maximum horizontal displacement
decreased from 52mm to 37mm, while the maximum
total displacement decreased from 56mm to 38mm.
Both results indicate that the crushed rock fill layer
was effective on reducing the wall face displacements.
8
Height of Wall (m)

60.0

6

CONCLUSION

4

The paper has focused on the design and analysisof the critical section of a geogrid reinforced
segmental retaining wall that employs the Keystone®
modular concrete units as the wall facing system. The
stability of the structure was investigated by theconventional stress-based limit equilibrium approach.
The long term performance of the wall face subject todisplacements were analysed by strain-based finite
element approach coupled with a serviceability
evaluation methodology for masonry structures. The
following conclusions were drawn from this casestudy:• The long term performance of the wall underdisplacement is one of the key issues for the

20

30.0 35.0 40.0 45.0 50.0
Horizontal Displacement (mm)with crushed rock fill

55.0

without crushed rock fill
Fig. 8 Computed horizontal displacement along wall
face with & without crushed rock fill.
260

GEOMATE- Brisbane, Nov. 19-21, 2014[8] AASHTO/AGC/ARTBA, “Design guidelines foruse of extensible reinforcements (geosynthetic)
for mechanically stabilized earth walls inpermanent applications”, In Situ Soil
Improvement Techniques, 1st ed. AASHTO,
1990, pp. 28-38.
[9] Bathurst RJ and Simac MR, “Geosynthetic
reinforced segmental retaining wall structures inNorth America”, in Proc. 5th Int. Conf. on
GEOTEXTILES, GEOMEMBRANES AND
RELATED PRODUCTS, 1994.
[10] Berg RR, Allen TM and Bell JR, “Design
procedures for reinforced soil walls-a historicalperspective, in Proc. 6th Int. Conf. on
GEOSYNTHETIC, 1998, pp.491-496.
[11] Greenway D, Bell R and Vandre B, “Snailback
wall – first fabric wall revisited at 25-year
milestone”, in Proc. Conf. on
GEOSYNTHETICS ’99, 1999, pp.905-919.
[12] Burkitt G, Redbank River Park Earthworks,
Bulking Densities & Erosion Potential
Assessment. Brisbane: Soil Surveys
Engineering Pty Ltd, 2011, pp. 3-5.
[13] Committee CE-032, “Design life”, AustralianStandard (AS) 4678-2002 Earth-retaining
Structures, 1st ed. Standards Australia
International Ltd., 2001, pp. 29.
[14] GEO-SLOPE International Ltd., Stability
Modelling with SLOPE/W 2012 Version: An
Engineering Methodology. Alberta: GEOSLOPE International Ltd., 2014.
[15] Anderson RB, “Construction consideration for
geogrid-segmental block mechanicallystabilized earth retaining walls”, J. of
Transportation Research Record, Vol. 1414,
Dec. 1992, pp. 12-15.
[16] Mair RJ, Taylor RN and Burland BJ, “Perditionof ground movements and assessment of risk ofbuilding damage due to bored tunneling”, in
Proc. Conf. on GEOTECHNICAL ASPECTS
OF UNDERGROUND CONSTRUCTION IN
SOFT GROUND, 1996, pp. 713-718.
[17] Burland JB, Broms B and De Mello VFB,
“Behaviour of foundations and structures –SOA report, in Proc. 9th Int. Conf. on SMFE,
1977, pp. 495-546.
[18] Boscardin MD and Cording EG, “Building
Response to Excavation-Induced Settlement”, J.
of Geotechnical Engineering (ASCE), Vol. 115(1), Jan. 1989, pp. 1-21.
[19] Queensland Department of Transport and Main
Roads Geotechnical Section, Geotechnical
Design Standard-Minimum Requirements.
Brisbane: Department of Transport and Main
Roads, 2014.
[20] Committee CE-032, “Construction tolerances”,
Australian Standard (AS) 4678-2002 Earthretaining Structures, 1st ed. Standards Australia
International Ltd, 2001, pp. 40.

design of Keystone® segmental wall withsignificant height. In order to fully address thedesign risks, the strain-based finite element
approach for displacement analysis should be
adopted in addition to the traditional stress-based
limit equilibrium approach for stability
assessment.
• The wall face cracking is a major performanceindicator of reinforced masonry segmental
retaining structure. The strain-based finite
element approach could be extended by adopting
a classification of damage methodology to
examine the potential damage category based on
the estimated tensile strains. Thus the long term
serviceability could be evaluated in a more
specific and comprehensive way with predictionof potential cracking damage in addition to thegeneral displacement outcomes.
ACKNOWLEDGEMENTS
The authors of this paper would like toacknowledge and thank Shadforths Civil Contractors,
Keystone® Systems and Concrib Pty Ltd for theirassistance and kind permission to publish this paper.
REFERENCES[1] Anderson RB, Boyd FN and Shao L, “Modular
block faced polymer geogrid reinforced soil
walls U.S. postal service combined carrier
facility”, in Proc. On GEOSYNTHETICS’91,
1991, pp. 889-902.
[2] Hill JJ and Berg RR, “Use of segmental wall
system by Minnesota department oftransportation”, J. of Transportation Research
Record, Vol. 1414, Dec. 1992, pp. 1-5.
[3] Simac MR, Bathurst RJ and Goodrun RA,“Design and analysis of three reinforced soil
retaining walls”, in Proc. Conf. on
GEOSYNTHETICS’91, 1991, pp. 781-789.
[4] Mcgown, A, “The behaviour of geosynthetic
reinforced soil systems in various geotechnicalapplications”, in Proc. 2nd EU. Conf. on
GEOSYNTHETICS, 2000, pp. 3-23.
[5] Christopher BR, Gill SA, Giroud JP, Juran I,
Mitchell JK, Schlossser F and Dunnicliff J,
Reinforced Soil Structure Volume I. Design andConstruction Guidelines. Washington, D.C.:
FHWA, 1990, ch. 3.
[6] Simac MR, Bathurst RJ, Berg RR and
Lothspeich SE, Design Manual for Segmental
Retaining Walls, 3rd ed. Herndon: NCMA, 2010,
pp. 250.
[7] AASHTO/AGC/ARTBA, “Guidelines for thedesign of mechanically stabilized earth walls”, In
Situ Soil Improvement Techniques, 1st ed.
AASHTO, 1990, pp. 4-18.

261

GEOMATE- Brisbane, Nov. 19-21, 2014

CONSOLIDATION PARAMETERS FROM ATTERBERG LIMITS –NEW CORRELATIONSC H Solanki
Applied Mechanics Department, S V National Institute of Technology, Surat – 395 007 Gujarat, India,

ABSTRACT
Various methods and empirical correlations are available to predict consolidation parameters. Use of empiricalcorrelations for consolidation parameters cannot be generalized for all places and all soils. Empirical correlations
should be used only after verifying its feasibility for particular region and type of soils. Consolidation test is
expensive. Reliability is poor due to sampling disturbances. Time to investigate add more time to finalize the soil
report. Normally soil report excludes the consolidation tests. In such cases empirical correlations are very usefulto estimate consolidation settlement of shallow foundations. The test results and datasets containing index andconsolidation parameters are used to conduct a statistical study to determine suitable correlations for estimating
consolidation response of alluvial soil. This statistical analysis is carried out in order to obtain the most suitableand practically applicable relationships. New correlations are proposed for prediction of compression index andcompression ratio using liquid limit, plasticity index, water content, voids ratio and porosity (n o ) for alluvial
deposits of Surat city & surroundings situated in the Gujarat state of India. Correlations obtained using atterberg
limits having higher value of correlation coefficient. These correlations are use for prediction of compressibility
parameters for all zones of Surat city and SUDA (Surat Urban Development Authority) region of South Gujarat
in India.
Key Words: Alluvial Deposits, Atterberg limits, Empirical correlations, Soil Consolidation, Soil Properties.
INTRODUCTION[文書
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目ポイント を強調したりしましょう。このテキストボックスは、ドラッグしてページ上の好きな場所に配置できます。
]
In the selection and design of foundation system, it isimportant to determine the types and properties of thesoil. In a detailed investigation, the conventional
approach is to perform subsurface investigation being
to obtain for a sufficient number of soil samples which
are then tested in the laboratory to obtain thenecessary soil properties including consolidation
parameters. The basic index properties are watercontent, dry density, void ratio, consistency limits.
Consolidation tests are expensive and time
consuming. In order to obtain realistic values, special
sampling and testing techniques and testing systems
are required. It is required to conduct these tests withthe utmost accuracy and to adopt realistic and suitableprocedures to evaluate and interpret the results
obtained. However, the group of tests performed toobtain index properties of soil is relatively
inexpensive and simple. They do not require muchtime or any sophisticated testing system. Hence, it isvery useful to develop empirical correlations for262

estimating the consolidation properties with soil index
properties. The industrial growth and real estate
activity in decade has been very fast. There are veryfew qualified equipped agencies to serve the sectors
demand for soil investigations in time and ataffordable price. The test for normal range of stresstakes a more time. This constrain and normal practiceto test typical one or two samples for a soil strata ofapproximately 3000 m3 of the soil per unit could bestatically unacceptable and occasionally misleading
particularly for alluvial stratified layered deposits.
Thus the expected accuracy of results and predictedfinal settlement or its time rate is highly variable. The
aim of study is to establish fairly reliable forecast of
consolidation parameters and finally total settlement at
a specified time by passing statistically not acceptable
tests with reference to time and cost both. New
approach is evolved for quick analysis and to assess
sensitivity of structure at a site for settlement. The
derived parameters and approach can be new, quick
and economical.
Subsoil Characteristics
The study area is divided in to 10 zones of Surat Cityand SUDA (Surat urban development authority)
situated in Gujarat state of India. Six zones are ofSurat Municipal Corporation and 4 zones of SUDA.
The subsoil characteristics of each zone are studied indetail from large number of datasets. A datasets
containing index and consolidation parameters are

GEOMATE- Brisbane, Nov. 19-21, 2014

used to conduct a statistical study to determine
suitable correlations for estimating consolidation
response. This statistical analysis is carried out inorder to obtain the most suitable and practicallyapplicable relationships. This database can provide
information regarding trends, relationships andstatistical properties, a mechanism whereby test
results can be checked and provides geotechnicalinformation for preliminary design purposes. The soil
characteristics of each zone are studied up to a depthof 8 m. This depth is stress zones for shallow
foundations. Generally for multistoried buildings
foundations are located at 3 to 4 m depth in the study
region. The average soil properties up to depth of 8 m
are shown in Table 1.
Table 1 Average range of Subsoil characteristics forstudy area
Soil Properties

Most Range

Liquid Limit (w L )Plastic Limit (w p )Plasticity Index (I p )Void Ratio (e 0 )Dry unit weight kN/m3 (γ d )Water Content (w)Porosity (n 0 ) %% Fines
Clay %
Silt %
Compression Index (C c )Compression Ratio(C c’ )=Cc/1+e 0
Soil Classification

30 – 60
20 – 30
15 – 30
0.6 – 0.9
14 – 16
15 – 30
40 – 46
60 – 90
20 – 30
40 – 60
0.24 - 0.37
0.14 – 0.18

Differential Free swell
Mineralogy

that mean value range of liquid limit 38.5 – 51 %,plastic limit 20 – 25 %, plasticity index 20 – 27 %,void ratio 0.7 - 0.77 %, dry unit weight 15.2 - 16.0
gm/cc, water content 19 - 23 and % finer 55 - 84.
Coefficient of variance for most soil properties in allzones found below 30% except very few cases. The
lower values of skewness and kurtosis in all zones
indicate symmetry of data. Various methods andempirical correlations are available to predict
consolidation parameters are used for study area for
determination of compressibility parameters. It isfound that use of empirical correlations forconsolidation parameters can not be generalized for allplaces and all soils. Empirical correlations should be
used only after verifying its feasibility for particularregion and type of soils. Consolidation test is
expensive, and its reliability is also poor due tosampling disturbances. Time to investigate adds moretime to finalize soil report. Normally soil report
excludes the consolidation tests in the study area. In
such cases empirical correlations are very useful toestimate consolidation settlement of shallow
foundations. Laboratory test results of the study areaused for deriving new correlations. New correlations
are proposed for prediction of compression index andcompression ratio using liquid limit, plasticity index,
water content, void ratio and porosity for alluvial
deposits of study area as shown in Table 2.
Correlations are obtained using soil plasticity
characteristics having higher value of correlation
coefficient.
Table 2 New Correlations

Low to HighCompressible Fine
Grained Soil
10 – 80Montmorillonite &Kaolinite

The consolidation characteristics such as compression
index and compression ratio of west zone Surat arefound less compared to other zones. The coarsegrained soil is predominant in west zone Surat. The
properties covered in the table are liquid limit , plastic
limit , plasticity index , void ratio, dry unit weight ,water content , % finer , compression index andcompression ratio.
Statistical Summary of Subsoil characteristics andEmpirical Correlations
Statistical summary of parameters such as mean,
median, and standard deviation, coefficient ofvariance, skew ness, kurtosis and range are studied ofall zones. This statistical analysis is done with thesoftware statistixl. Statistical summary of subsoil
characteristics of all zone of Surat and SUDA shows
263

Correlation
C c = 0.0061 w L – 0.0024
C c = 0.4066 e 0 – 0.0415
C c = 0.0082 Ip+ 0.0915
C c = 0.0107 n 0 – 0.1818
C c = 0.0091 w + 0.0522
C c ’ = 0.0022 w L + 0.0478
C c ’ = 0.0029 Ip + 0.0833
C c ’ = 0.0035 w + 0.0631

Correlation
Coefficient (R2)
0.84350.72230.78620.71150.77
0.90630.85790.6735

Correlations
obtainedusing
soil
plasticity
characteristics having higher value of correlation
coefficient in compare to other soil properties. These
correlations are use for prediction of compression
index and compression ratio for different zones ofSurat and SUDA region. Statistical summary of
predicted values of compression index andcompression ratio for Surat and SUDA are shown intable 4. New correlations derived for compressibility
parameters of soil using index and plasticity properties
are used for all zones of Surat and SUDA region.
Experimental results are studied for soil index andconsolidation properties. Available test datasets ofSurat and SUDA gave reasonably good correlation

GEOMATE- Brisbane, Nov. 19-21, 2014

coefficient between soil plasticity and compression
characteristics. Initially liquid limit and plasticity
index are used separately for determining compression
characteristics of alluvial soil. The average values ofcompressibility parameters are computed from values
obtained using liquid limit and plasticity index
correlations. From detail study of results, it is foundthat both parameters of soil may improve thecorrelation coefficient. The further study is carried out
for determining consolidation parameters of soil using
single or both parameters of soil. Large numbers ofdatasets of study area are used from S V National
Institute of Technology and different agencies forderiving correlations of consolidation parameters.
Empirical correlations are proposed for overconsolidation ratio, coefficient of consolidation withsoil plasticity characteristics. Correlations are also
proposed for compression index and compression ratiousing single or both parameters. Validations of new
correlations are done with existing consolidation test
datasets of other region. The proposed correlations
derived by author for compressibility parameters of
alluvial soil of above mention properties withcorrelation coefficient 0.75 and more are as follows
for shallow foundations.
The ratio of pre-consolidation pressure andpresent overburden pressure is known as overconsolidation ratio (OCR). Based on OCR soils areclassified as normally consolidated, over consolidated
or under consolidated. Selection of consolidation
parameters such as compression index (C C ),Recompression index (C r ) or coefficient of volume
change (m v ) is on the basis of OCR for computing
consolidation settlement. The correlations are alsosuggested by researchers to obtain Pre-consolidationpressure and Nagaraj and Murthy (1994), Chetia andBora (1998) etc.
Based on the test data of study area following relation
is derived for over consolidation ratio

finite percentage of consolidation to occur. The
coefficient of consolidation Cv generally decreases as
the liquid limit of soil increases. The range ofvariation of C V for given liquid limit is very high. C V
varies with both level of stress and degree ofconsolidation.
For
practical site
settlement
calculations, measure C V relative to loading range
applicable to site, and then assume this value to beconstant. In the present study coefficient ofconsolidation is correlated with liquid limit andplasticity index of soil. It is observed that Cv for
alluvial soil is giving higher value of correlation
coefficient with plasticity index than to liquid limit.
The correlation of Cv with liquid limit is also quitesatisfactory.
Based on the test data of study area following
correlations are derived for coefficient ofconsolidation
Coefficient of consolidation using liquid limit(C v ) = 108 w L -6.7591
cm2/sec
R2=0.7867…….(2)
Coefficient of consolidation using plasticity index(C v ) = 7.7525 Ip-3.1025 cm2/sec R2=0.9156……..
(3)
Compression ratio using liquid limit(Cc′) =0.0032 w L +0.0004
R2=0.7806(4)……

Compression ratio using liquid limit and plasticity
index(Cc′) = 0.002 w L + 0.001 Ip + 0.037 R2=0.8674 …
(5)
Fig 1(a) shows comparison of measured and predicted
compression ratio from liquid limit and plasticity
index.

Over consolidation ratio
0.25(OCR) = 1.85 − 0.007 p o − 0.225 (e/e L ) R =0.793........(1)The rate of settlement of the soil layer takes place isessential from design consideration. This can be
determined using coefficient of consolidation Cv. To
obtain Cv it is essential to conduct a routine onedimensional consolidation test. The various time
fitting curves are available to evaluate Cv. This is time
consuming process. Curve fitting procedures available
in the literature are not completely satisfactory inevaluating Cv and hence large variation is obtained in
the evaluated values by different procedures.
Generally square root time fitting or Log time fitting
curves are use for evaluation of Cv. The rate ofsettlement is directly related to the rate of excess porepressure dissipation. Coefficient of consolidation C V
is useful in the determination of the time required for aCompression ratio from test
results

2

R2 = 0.8674

0.20
0.15
0.10
0.05
0.00
0

0.05

0.1

0.15

0.2

Predicted com pression ratio

Fig 1 (a) Comparison of measured and predicted
Compression ratio

264

0.25

GEOMATE- Brisbane, Nov. 19-21, 2014

Comparison of measured and predicted compression
index using ANN (Artificial Neural Network) is
shown in fig 1 (b).

Count
Skewness
Kurtosis135.000
0.678-0.151135.000
0.823-0.151

Empirical Model for Computation of Settlement of
Shallow Foundations

0.25

Output

0.2

0.15

0.1

0.05

0
1

8

15

22

29

36

43

50

57

64

71

ExemplarFig 1 (b) Comparison of measured and predicted
compression index Using ANN
MSE
MAE
Min Abs Error
Max Abs Errorr0.000141866
0.009728118
2.11004E-05
0.030127471
0.931366511

The software neurosolution5 was utilized for training,
testing and cross validation. Various architectures of
ANN along with numerous training algorithms weretried till satisfactory results were obtained.
The comparison of compression ratio frommeasured 135 numbers test data from literature andusing above empirical correlation liquid limit andplasticity index both are determine. It is found that thevalues obtained using empirical correlations are close
to consolidation test data. Compression ratio of soil isgiving higher value of correlation coefficient withliquid limit and plasticity index both. Table 3 shows
statistical comparison of compression ratio using test
datasets of other region from literature and empiricalcorrelation using liquid limit and plasticity index.
Table 3 Statistical summary of compression ratio
from test data and correlation
ParameterCc’ from test
data

Mean
MedianStd Error
Std Dev.
COV.
Sum
Minimum
Maximum
Range

0.175
0.167
0.004
0.043
24.39123.609
0.103
0.296
0.193

Cc’ fromcorrelation
W L & Ip
0.178
0.172
0.003
0.039
21.31224.582
0.126
0.280
0.154
265

Empirical model is proposed using Visual Basic
Program to predict the settlement of shallow
foundations incorporating soil index and plasticity
characteristics.
The model incorporates thecomputation of over consolidation ratio, time rate
settlement, magnitude of settlement and differential
settlement of foundations. The model will be usefulfor foundation design incorporating the differential
settlement of foundations. This model is proposed toobtain settlement of shallow foundation for finegrained alluvial deposits of same subsoil range. In
this model input parameters are soil index &plasticity characteristics for obtaining settlement offoundations. The soil index and plasticity
characteristics
inadditiontogeometricalfoundation parameters and load on the foundation
are required to obtain settlement using thisempirical model. The program is also prepared forpredicting contact pressure between soil and footing(Safe or Allowable bearing Pressure) from input of
required parameters. For Prediction of total anddifferential settlement soil
properties
andgeometrical parameters used as input parameters
are % finer, bulk unit weight of soil (γ) watercontent (w) , liquid limit (w L ), plasticity index (Ip),
specific gravity of soil grains (G) , standard
penetration resistance (N) , width of footing (B),length of the footing (L), depth of the footing (D) ,degree of consolidation (U). Model computes areaof footing, safe load on the footing with dry unit
weight of soil (γ d ), void ratio (e) , thickness of thecompressible layer (H), void ratio at liquid limit(e L ) ,existing over burden pressure (p o ), overconsolidation ratio (OCR). Magnitude of settlement isdetermined using compression ratio of soil. The soil
for which plasticity index is not known Cc′ isdetermined using liquid limit. When liquid limit(w L ) and plasticity index (Ip) both are known
compression ratio is
determine using bothparameters. Recompression index is taken as 10% ofcompression ratio.
For determining magnitude of settlementof normally consolidated soil geometrical factor istaken as 0.7 and for over consolidated soil taken as
0.5. Depth factor (D f ) and Rigidity factor (R f ) aretaken as 0.8 in computation of magnitude ofsettlement.
Modulus of elasticity is assumed orcomputes using standard penetration resistance (N) in
this model. The total settlement of the foundation istaken as sum of corrected immediate settlement andcorrected consolidation settlement. The model also
incorporates differential settlement between two

GEOMATE- Brisbane, Nov. 19-21, 2014

footings or two edges. Angular distortion is computedby giving center to center distance between two
footings. If computed settlement is exceed thepermissible settlement it highlights the values. These
computations are used to check differential settlement
for structural member of frame. The empirical model
also includes computation of time rate settlement.
Coefficient of consolidation is to be determined using
liquid limit, if plasticity index is not known. Whenplasticity index of soil is known coefficient ofconsolidation (Cν) is computed on using plasticity
index. The model incorporates single drainage or
double drainage. The output of time rate settlement isobtained in days.
CONCLUSION
Empirical model is prepared to obtainsettlement of shallow foundation for preliminary
design. In this model input parameters are soil index
and plasticity characteristics with some basic soil
properties and geometrical dimensions. Modelcomputes parameters such as over consolidation ratio.
Coefficient of consolidation, compression ratio,
immediate settlement, consolidation settlement anddifferential settlement. This model is enable thedesigner to decide safe bearing capacity or permissible
bearing capacity which ever governs the design,
Critical differential settlement zones in a structure to
proportion foundations or stiffen structure and indicate
critical sample site to minimize errors in transfer or
remolding of samples collected by driller.
REFERENCES[1] Celik, S. and Tan, O. (2005) Determinationof Pre-consolidation pressure with Artificial
neural network , Civil Engineering andEnvironmental system .22 (4) pp 217-230[2] Cherubini C & Giasi C I (2000), “Correlation
equations for normal consolidated clays”.
Coastal geotechnical engineering in practice,
Nakase & Tsuchida balkema Rotterdam pp
15 - 20.
[3] Crumley, A. R. (2003) “Compressibility
Relationships for soils in Puerto Rico” 12th
Pan-American conference on soil Mechanics
andGeotechnicalEngineering
Massachusetts Institute of Technology,
Boston. pp. 1-5.
[4] Koumoto, T. and Park, J. (2004), “Newcompression index equation”. Journal of
Geotechnical&Geoenvironmental
Engineering ASCE 130 (2) pp 223 -226.
[5] Lav, M. A. and Ansal, M. A. (2001)“Regression
Analysisof
Soil
Compressibility”
Turk
JournalEnvironmental Science. Vol.25 pp 101-109
266[6] Nagaraj, T. S., Shrinivasa murthy B. R., andVatsala, A. (1991), “Prediction of soil
behaviors –part ii- saturated uncementedsoil”. Canadian Geotechnical Journal . Vol.
21 (1) pp 137 - 163.
[7] Nath, A. and DeDalal S S (2004), “The Roleof Plasticity index in predicting compression
behavior of Clays” Electronic Journal of
Geotechnical Engineering. pp 1-7[8] Robinson, R. G. and Allam, M. M. (2003) “Compression index of clays and silts”
Journal of testing and evaluation ASTM 31(1) pp 1-6[9] Senol A , Seglamer A (2000) “Determination of Pre-consolidation pressure
with a new strain energy –log stress method“ Electronic Journal of GeotechnicalEngineering pp 1-11
[10] Shahin, M. A. Maier, H. R. and Jaska, M.
B. (2000) “Predicting settlement of shallow
foundations using neural networks” Journalof Geotechnical and Geoenvironmental
Engineering pp 785-793[11] Sridharan, A. and Nagaraj H.B. (2000),“Compressibility behavior of remolded finegrained soils and correlation with index
properties”. Canadian Geotechnical Journal
37 pp 712-722[12] Sridharan, A. and Nagaraj, H. B. (2004) “
Coefficient of consolidation and its
correlation with index properties of remolded
soil “ Geotechnical testing Journal ASTM
27 (5) pp 1-6[13] Yoon, G. L. Kim, B. T. and Jeon, S. S.
(2004),“Empiricalcorrelationsofcompression index for marine clay from
regression analysis”. Canadian Geotechnical
Journal. .41 pp 1213 – 1221.

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

RESEARCH OF PERIMETER REINFORCEMENT OF THE
FOUNDATION SOIL BY CEMENT-SAND MORTAR INJECTION
M.L. Nuzhdin1, L.V. Nuzhdin2
SPEC Company “O&F”, Russia; Novosibirsk State University of Architecture and Civil Engineering(Sibstrin), Russia

1

2

ABSTRACTThe article analyzes the results of a series of laboratory experiments studying consolidation of foundations byperimeter reinforcement of the soil by rigid incompressible irregularly shaped inclusions. The experiments
modelled consolidation of a shallow soil foundation base by directed high-pressure injection of mobile cement
and sand mixtures. The essence of the method of high-pressure injection is pumping of a cement-sand mixture in
the foundation under a pressure exceeding structural strength of the soil, as a result of which the massif
continuity is broken and a cavity filled with cast-in-place concrete is formed in the soil. Laboratory tests in soil
trays and a number of full-scale experiments on a test field were made in order to define rational design
parameters of such consolidation. Several series of experiments were conducted: with different distance between
inclusions in plan, with different depth of inclusions and etc.
Keywords: Mortar injection, perimeter reinforcement

significant benefits. These are: the possibility toperform work in confined space (for example, fromthe basements of existing buildings); the absence ofdynamic effect on the surrounding constructions;lack of coupling with the reinforced foundation (nointerference with its condition); no need for special
expensive equipment and materials; as well as thehigh efficiency of carried out reinforcing works with
their low cost and quite a high speed of execution. In
this case the reinforcement of the ground base andfoundations can be done for existing buildings andfacilities during their reconstruction and repair, as
well as during the engineering preparation for new
construction.
In Novosibirsk and other Russian cities the topic
of reinforcing the ground base and foundations ofhistorical buildings during their reconstruction, as
well as reinforcing of existing buildings in order toavoid a negative impact on them during constructionof new closely located buildings and structures ishighly relevant.
With the variety of possible schemes for thereinforcement of the ground base and subsurface
foundations, one of the most effective ones is outline
reinforcement - insertion of a range of verticalelements (that consist of solid bodies) in the groundbase along the edges of foundations. From apractical point of view, the reinforcing members thatare made along the outline with a certain step
function as a "compression wall" along thelongitudinal edges of subsurface foundations, theyalso create some prestress of the ground base that islimited by the "compression veils" and the base of
the foundation. These two factors can significantly

INTRODUCTION
The technology of reinforcement of foundationsoil that is about using the targeted high-pressure
injecting method is quite widespread in the city of
Novosibirsk and in the West Siberian region of
Russia. Technical essence of the method consists infeeding the workable cement-sand mortar in the
ground base under pressure that is slightly higher
than the structural strength of the ground. In thiscase the continuity of the ground mass is violated,
and the formed cavities are filled with injectablemortar, after hardening of which in the foundationsoil the incompressible inclusions are created.
The targeted high-pressure injecting technology
consists in placing the injectors in certain
geometrical order and simultaneous feeding ofmortar through all the injectors. This allows creatingin the ground the injection bodies of “given” forms.
Thus, with the placement of the three injectors at thecorners of the conditional equilateral triangle andwith the usage of injectors with only one opening (atthe lower end of the pipe) the flat disk-shaped body
is formed. When positioning the injectors along a
straight line and using injectors with slotted
openings in their lower part in the base the verticalbody oriented along a straight line is created. In bothcases, the distance between the injectors, injection
pressure, the consistency of the mortar and otherparameters are assigned according to thecalculations depending on the physical andmechanical properties of the ground.
Application of the targeted high-pressure
injecting technology is quite productive and has
267

GEOMATE- Brisbane, Nov. 19-21, 2014

each layer gravel chippings were introduced into itwith small effort, creating certain compaction,
relatively shaping the compaction of the surrounding
ground while injecting the cement-sand mortar.

reduce the deformation of foundation soil.
For the effective commissioning of "compression
walls" it is necessary to provide minimal vertical andhorizontal displacements of reinforcing members,
and to prevent horizontal ground heave from underthe base of the foundation between the reinforcing
members.

Fig. 1

Gravel chippings of different size, shaping
solidincompressible
inclusions
inexperiments on outline reinforcing in asmall ground tray.

Fig. 2

Vertical stability of the reinforcing members isachieved by immersing them to a certain depth. The
upper part of the reinforcing member, due tofrictional forces between the ground and its sidesurface, reduces stress in the ground, and the lower
part of the reinforcing member due to friction
transmits the load to the ground base. Clamping of
the ground in the form of the created "arch roofs"
during the loading prevents the ground punching.
The experiment of reinforcing inclusions
formation while reinforcement of the groundfoundation and the existing buildings foundation
with the help of high-pressure injecting technology
has proved to be efficient. Here (as with any otherinjecting) arises the question of allocation ofeffective inclusions geometrical parameters, such as
the number and spacing between inclusions in“columns”, inclusions diameter and the distance
between them, etc.

Gravel chippings arrangement while
experimenting with effective parameters of
perimeter plate outline reinforcement.

Vertical action, applied to the plate, was createdwith screw jack through spring dynamometer. Plateload was transferred as a point force through thesupport construction of the tray. High rigidity ofmetallic plates ensured even distribution of pressure
on the ground over their bottom.

Fig. 3

Experimental set up in small and large groundtrays

Gravel chippings arrangement while
experimenting with effective parameters ofsquare plate outline reinforcement.

Measurementof plates
vertical strain(settlement) was carried out through Maximov’s
deflectometer with division value 0.01 mm.
Laboratory research program consisted of 12series (6 series for rectangular and 6 for squareplate) 3-4 experiments in each, all experiments wererepeated at least 3 times.
The following parameters varied while
experimenting:Dimensions of rigid inclusions: 0.02…0.04 mm(0,2b…0,4b);
Outline reinforcement spacing: 1d, 2d and 3d (d– nominal inclusion diameter), approximately
0.2b…1.2b;
Number of reinforcement layers: 3-10;

To define rational parameters of outline
reinforcing of shallow foundation, created throughpumping of cement-sand mixtures, a complex oflaboratory research has been carried out on different
scale models of foundations and reinforcing
members. The experiments were carried out in a
0.9×0.38×0.5 m ground tray, filled with dry medium
sand. As a model of foundation perimeter, a hard
metallic rectangular 0.37×0.11 m plate was used;
and as a pier foundation – metallic square plate
0.10×0.10 m.
Inclusions were shaped by gravel chippings with
0.02…0.04 m diameter. The sand was poured into
the tray layer by layer without compaction, after
268

GEOMATE- Brisbane, Nov. 19-21, 2014

In order to confirm qualitative dependence ofexperimental data, obtained in small ground tray,
and quantitative evaluations of outline reinforcing
influence on shallow foundations subsidence underload, a number of experiments in large ground tray
and half-sized models was carried out.

Gaps in depth between inclusions: 1d (tightlaying), 2d and 3d;In-plane distance from reinforcing members to
the plate edges.

Fig. 4

Fig. 6

Experimental studies perimeter reinforcedbase of the square plate 5,000 cm2 in area inthe big soil tray on small packed sand (theloading device includes directional vibrator
and allows transfer of vertical or horizontal
dynamic loads to the plate in addition tostatic loads – this article does not examine
the dynamic tests results).

Fig. 7

Diagrams of perimeter plate subsidence on
unreinforced base and on the base,reinforced with inclusions 0.2b withspacing 3d in plane and gaps 3d in depth.

Schemes of some experiments on studying
the influence of geometrical parameters on
the efficiency of outline perimeter plate
reinforcement.

After each experiment, the sand and inclusions
were taken out of the tray, the sand was sifted
through, and a new experiment was being prepared.

Fig. 5Experiments in the big soil tray 300×300 cm and200 cm deep were carried out on small packed airdry sand with internal friction angle φ = 37°, pseudocohesion c = 5 kPa and deformation module E = 27
MPa (see fig. 6). The tray had no rigid bottom below
and under the sand there was slightly wet stiff silty
clay with layer thickness more than 9 m. The load on
the soil base was transferred by means of a hydraulicjack 1,000 kN set on a standard rigid plate 5,000 cm2
in area. The plate settlements were registered by four

Schemes of some experiments on studying
the influence of geometrical parameters on
the efficiency of outline perimeter squareplate reinforcement.

Dependence diagrams «plate bottom pressure –plate subsidence» were constructed based on theobtained results.
269

GEOMATE- Brisbane, Nov. 19-21, 2014

deflectometers with scale interval 0.1 mm.
Measurements were made with time delays after
deformations stabilization.

foundations we also used the results obtained inplate tests on several construction sites ofNovosibirsk during reinforcement of sand, silty
clays and lean clays.
Laboratory research results
Efficiency of outline reinforcement with various
parameters may be evaluated by comparing thediagrams of dependence of plate subsidence fromthe load (Fig. 7…Fig. 14). The diagrams areconstructed on the basis of the experiments carriedout on the small ground tray.
Analysed the results of the experiments we may
come up with some general conclusions.

Fig. 8, 9 Diagrams of subsidence of perimeter andsquare plates on a base with contiguous
outline reinforcement. The base isreinforced by the inclusions with a 3dlateral step and 3d gaps in depth with size
0.2b (Fig. 8) and 0.4b (Fig. 9).
Results obtained in laboratory conditions wereexperimentally checked during tests of a large-scalefoundation model on a test field in natural soil
conditions represented by slightly wet stiff silty clay
with layers of lean clays and sand, having thefollowing characteristics: internal friction angle φ =27°, pseudo cohesion с = 21 kPa, deformation
module Ε = 14 MPa. As the foundation model weused a standard metal plate 5,000 cm2 in area andstock reinforced concrete foundations withdimensions in plane 100×100 cm and 60×240 cm.
Foundation models and plates were loaded by meansof a system of beams, ballast weight (or anchoring
system) and a hydraulic jack. Settlements anddeformations of the surrounding soil surface wereregistered by a special reference measurement
system, including deflectometers, watch-likeindicators and reference points for geodetic.
Experiments were made using a stress relaxation
method, also called a method of controlled
displacement (MCD). In our analysis of theefficiency of various ways of perimeter
reinforcement of foundation soil of heavy-loaded

Fig. 10, 11
Diagrams of subsidence of aperimeter plate on a ground base reinforced
with inclusions of different size (0.2b and0.4b). Contiguous outline reinforcement(Fig. 10), distribution of reinforcing
members with the step in plane of 0.3d and3d gaps in depth (Fig. 11).
All the parameters of the reinforced groundfoundation varied in experiments influence the end
result – value of plate subsidence under load – insome degree. Even minimal reinforcement used inexperiments (inclusions size 0.2b, step 3d on theplan, gaps of 3d depth) reduces subsidence forapprox. 25% (Fig. 7) in comparison with an
unreinforced base.
The most influence on the results for both
perimeter and square plates is made by the270

GEOMATE- Brisbane, Nov. 19-21, 2014

abundance of reinforcing members. Reinforcing
members inserted tightly both in plane and in depth
provide maximal compression effect and thus
subsidence is minimal. In this case subsidence may
be 100% (for perimeter plate) and 400% (for squareplate) less than if the reinforcing members have gaps
between each other. At the same time a significant
increase of ultimate load on the base is observed.

inclusions with a size of 0.4b are used in contiguous
outline reinforcement the subsidence at all stages ofload is 2-3 times lower than in the same scheme ofreinforcement with 0.2b inclusions. Significant
increase of ultimate load on the base is observed by
the reinforcement with larger inclusions.
If reinforcement was made with inclusion of thesame size the plate subsidence directly depends onthe distance between the reinforcing members. If thestep between the members is increased laterally andheight along, the subsidence increases as well. If thestep between the members is increased in plane up to
3d (in contiguous vertical reinforcement) the
subsidence increases for 75-100% in comparison
with contiguous outline reinforcement. Results
analysis revealed a curious fact that the similar
vertical increase of gaps (in contiguous lateral stepof the members) results in the equal increase of
subsidence.
In both cases closer position of both laterally
situated reinforcing members and inclusions in depth
results in significant increase of ultimate load on aplate.

Fig. 12 Diagrams of subsidence of perimeter plate
on a base with contiguous outline
reinforcement with 0.2b inclusions and on abase with various distances: step and gaps
in depth of 3d.

CONCLUSION
Outline reinforcement around the subsurface
foundations (plates) with high-pressure injections
allows to reduce the subsidence of a ground basesignificantly in comparison with unreinforced base.
Supporting of the existing foundations with such
reinforcement results in the increase of base loadbearing capacity and makes extra loads possible.
REFERENCES[1] Nuzhdin LV, “Account of interaction between afoundation frame and soil in pile foundation
oscillations”, in Theses of the Report at Nation.
Scien.-Techn. Conf. “Soil mechanics andfoundation engineering”, SPb: SPbGASU, 1995,
pp. 505-510.
[2] Nuzhdin ML, “Prevention of non-uniform
settlements of foundation plate by means ofhigh-pressure injection” in Mat. of Int. Sсient.Techn. Conf. “Experience of construction andreconstruction of buildings and structures on
weak soils”, Arkhangelsk: Arkhangelsk State
University, 2003, pp. 119-122.
[3] Nuzhdin ML, “Use of cement-sand grouts toconsolidate of soil foundations by means of
directed high-pressure injection”, in Int.
Collection of Scien.-Techn. works, Issue 59,
Kiev, 2003, pp. 430-433.
[4] Nuzhdin ML, “Application of injection
conductors to prevent occurrence of foundation
plate tilts above the permitted standard bymeans of high-pressure injection” in Works ofInt. Geotech. Conf. devoted to the RussianFig. 13, 14
Diagrams of subsidence of
perimeter and square plates on a base with
contiguous outline reinforcement withelements of equal volume, inserted withdifferent step and in depth gaps.
With the similar reinforcement scheme used, thesize of inclusions is of large significance: if
271

GEOMATE- Brisbane, Nov. 19-21, 2014

Federation Year in Kazakhstan “Geotechnicalproblems of large-scale and unique objects
construction”, Almaty, 2004, pp. 351-354.
[5] Nuzhdin ML, Nuzhdin LV, “Experience ofhigh-pressure injection method application for
erection buildings on plate foundation” in Proc.
of XIVth Danube-European Conf. on Geotech.
Eng. Key lectures, main lectures and abstractsof papers “From Research to Design in
European Practice”, Bratislava, Slovak Univ. of
Tech., 2010, p. 310.
[6] Nuzhdin ML, Nuzhdin LV, “Erection manystorey buildings one plate foundation withapplication high-pressure injection method” inProc. The 14th Asian Reg. Conf. on Soil Mech.
and Geotech. Eng. (Hong Kong, China, 23-27
May 2011) “Soil Mechanics and GeotechnicalEngineering: Challenges and Solutions”, Hong
Kong, The Hong Kong Polytech. Univ., 2011, p.
219.
[7] .Nuzhdin ML, Nuzhdin LV, “Application highpressure directional injection method forstrengthen soil base” in Proc. of the IVthCentral Asian Geotech. Symp. “GeoEngineering for Construction and Conservationof Cultural Heritage and Historical Sites –Challenges and Solutions”, Samarkand, 2012,
pp. 201-205.
[8] Patent for invention No. 2352723 of the RussianFed. «Method of adjustment of the vertical
position of buildings and structures on platefoundations» by Nuzhdin LV, Nuzhdin ML,
bulletin 11, 2009.

272

FourthInternational Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

GEOTECHNICAL CHARACTERISTICS OF SYNTHETIC MUNICIPALSOLID WASTE FOR EFFECTIVE LANDFILL DESIGN
Oluwapelumi O. Ojuri1. and Peter K. Adegoke1
1

Department of Civil and Environmental Engineering, Federal University of Technology, Akure, Nigeria

ABSTRACT
Geotechnical characteristics of Solid Waste are crucial for effective landfill design and operation, including
stability issues and integrity of lining components and sub-grade. This paper presents the results of laboratory
investigation performed to determine the geotechnical characteristics of Synthetic Municipal Solid Waste(SMSW); simulating typical composition of municipal solid waste (MSW) generated in Akure metropolis,
South-western Nigeria. Geotechnical tests performed include; basic index property tests, strength/compressibility
test and the hydraulic conductivity test.
The two compactive efforts used are the modified AASHTO [American Association of State Highway andtransportation Officials] and four times (4X) modified AASHTO to simulate higher compactive effort needed forfield compaction of MSW. It was generally observed that the unit weight, specific gravity and shear strength of
the SMSW increased with increase in compactive effort. Direct shear tests gave cohesion value of 7.6kN/m3 forboth modified AASHTO and 4X modified AASHTO compaction methods, while angle of shearing resistance formodified AASHTO compaction method was 42.40, and 48.50 for 4X modified AASHTO compaction. In designof landfills the least shear strength failure envelope should be used for effective design. The hydraulicconductivity for both compactive efforts were within the same order of magnitude indicating that the modified
AASHTO compaction was a good approximation of field compaction for the municipal solid wastes.
Compressibility test on SMSW gave compression ratio of 0.20 with total compression of 33.0% under maximum
load of 224kN/m2. This complies with the results reported in literature. Compression index (cc) was 0.4, initial
compression ratio (r0) was 0.19, primary compression ratio (rp) was 0.71 and secondary compression ratio (rs)
was 0.10. These provide the necessary information needed for the computation of expected settlement in thelandfill.
Keywords: Synthetic municipal solid waste, Geotechnical characteristics, Shear strength, Hydraulicconductivity, Compactive effort.
INTRODUCTION
The methods of waste disposal have continued
to change with development and advancement ofindustrialized nations. In recent time wastes are notsimply dumped into an open pit, due to healthhazard posed by them and adverse environmental
impact; hence, modern methods of disposing MSW
were generally adopted. Sanitary landfill is themost common method of MSW disposal andprobably accounts for 54% of United States MSW
disposal, though it has been proven to be
responsible for contamination of portable water incertain areas [3]. It is the most cost effective
method of waste disposal adopted by most nationsof the world compared to other waste management
techniques, such as incineration and composting.
Although, waste management authorities advocate
recycling and reuse of waste material, many
countries worldwide prefer land filling of MSW as
an economic option [1]. However, in Nigeria theMunicipal solid wastes (MSW) as wastematerials typically consist of food wastes, garden
wastes, paper products, plastic, textiles, woods,
metal, construction demolition wastes and soil,
However, the composition of MSW varies fromregion to region and it depends upon lifestyle,demographic features and legislation [1].The
disposal of municipal solid waste (MSW) in theworld is a problem that continues to grow with thegrowth of population and the development of
nations. Since the beginning of the time people
have needed to find a way of disposing their refuse,
as far back as 18th century in England and France,
Carters were paid by individuals to carry refuse anddiscard it in the outskirts of cities. Disposal ofwaste in open pit became a routine and BenjaminFranklin initiated the first municipal cleaning
program in Philadelphia in 1757 [2].

273

GEOMATE-Brisbane, Nov. 19-21, 2014

most populous black nation in the world, sanitary
landfill design and construction is not yet embraced
as expected. This modern form of waste
management technique should be considered inview of the deleterious environmental effects ofopen waste dumping on the geo-environment
especially the surface water and underground water
resources. It must be stressed that open dumping is
still prevalent in most parts of Nigeria with theconcomitant health consequences of this poor
environmental management technique.

Integrity, sustainability and potential for future
land reclamation of closed landfills depend upon
the geotechnical characteristics of MSW stemmingfrom the engineering properties of its
constituents/elements. Though the failure ofsanitary landfill may not be rampant, it does occur
in different parts of the world. Modes of failure
associated with; landfill sub-grade, waste and lining
system was reported by [4]. Table I shows theengineering properties of MSW required for
effective design of sanitary landfill.

Table I Engineering properties of MSW required for design [4]Designcase
Sub-grade stability
Sub-grade integrity
Waste slope stability
Shallow slope linear stability
Shallow slope linear integrity
Steep slope linear stability
Steep slope linear integrity
Cover system integrity
Drainage system integrity
Leachate/gas well integrity

Unitweight
X
X
X
X
X
X
X
X
X
X

VerticalShearcompressibility strength
X
X
X
X
X
X
X
X
X
X
X
X
X

Horizontal
in-situ stress
X
X

X

X
X

X
X
X

X

by weight: 10% paper and cardboard, 54.0% foodand other putrescible materials, 12.5% plastic,nylon and rubber, 4.3% metal and aluminium, 2.0%
glass, 6.0% wood, 5.2% textiles and leather and
6.0% of soil like waste. Some previous studies haveused synthetic municipal solid wastes (SMSW) toinvestigate the engineering properties of MSW [1],[5], [6] and [7]. Various components were further
grouped into biodegradable and non biodegradable
components according to [8]. These components
were used for preparation of SMSW used in thisstudy. The maximum aggregate size of thecomponents was limited to 15mm to facilitate theuse of conventional geotechnical testing
equipments. Table II shows the SMSW
composition used for this study.

MATERIALS AND METHODS
Study area
MSW generated within Akure was selected forthis study. Akure is a growing urban area within
latitudes 7◦ 10ꞌN and 7◦ 20ꞌN and between
longitudes 5o 07ꞌE and 5o 17ꞌE in Ondo State,
Nigeria. The mean annual temperature ranges
between 24oC -27oC, while the annual rainfall,varies between 1500mm and 3500mm.
Municipal Solid Wastes Composition
MSW sampled from various parts of Akure
contain approximately the following components
Table II SMSW composition of Akure metropolis
Compositions
Non biodegradable
Biodegradable
Garden waste
Vegetable waste
Cellulose non paper
Paper waste
Meat

X
X
X
X

Hydraulicconductivity%
30

Material used
Gravelly lateritic soil

20
15
14
16
5

Grass clippingGreen leaves
White bread
Shredded paper
Ground pork meat274

FourthInternational Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

and moisture content of 50.3% in accordance withPart 5:3 of [9]. The oedometer used in this study
was floating ring type with a circular brass ring of
60mm diameter and 20mm thickness, the specimen
was compacted into the brass ring with porous
stone at the top and bottom of the sample;
compaction was done to get the initial bulk unit
weight of the sample and the specimen was
subjected to vertical load ranging from 0.01kN0.64kN. Loading was done at 24 hours interval.

Methodology
Various tests carried out on SMSW samples are;moisture content, specific gravity, particle size
distribution, compaction, compressibility and shear
strength.
Moisture content
The moisture content of SMSW was determinedaccording to Part 2:3 of [9]. The SMSW was ovendried with the oven temperature being maintained
at 600 c to avoid combustion of volatile material.

Direct shear test
The shear strength parameter of prepared SMSW
was determined by conducting direct shear tests on
specimens from each SMSW unit weight variation.
The test was conducted in accordance with Part 7:5
of [9]. Shear box used in this research was squaretype. SMSW was compacted into shear box having
60mm lengths and 20mm height. SMSW specimens
were tested under different normal stressconditions. Initial wet unit weights are 8.2kN/m3
and 11.1kN/m3; with moisture contents of 50.3%
and 35% respectively from compaction result.
Porous stones were place on the top and bottom of
the sample content; vertical stress was applied tothe sample and then sheared at a constant strain rateof 0.5mm/min.

Specific gravity
The specific gravity of prepared SMSW wasdetermined according to Part 2:8 of [9]. The
specific gravity test was carried out on both freshand dis-aggregated compacted SMSW toinvestigate their variation as reported by [10].
Particle size distribution
The grain size distribution of SMSW wasdetermined using BS standard, according to Part
2:9 of [9]. The test was carried out on wet basis.
The materials was washed using sieve no 200(0.075mm), oven dried and sieved using BS set ofsieves. After vigorous shaking for 10 minutes thematerial was allowed to settle down for 2 minutes
and the weight of material retained on each sieve
was recorded against it, and the percentage finer
was determined. The sieve size was plotted against
the percentage passing, on semi logarithm scale.

Hydraulic conductivity
Hydraulic conductivity test was conducted on two
sets of prepared SMSW samples with three samples
from each set, based on the two unit weightvariation from compaction tests. The test was
conducted in accordance with BS 1377 Part 5:5 of[9]. The initial bulk/wet unit weights of the samples
were arrived at by compaction of the SMSW
samples in permeameter cell with tamping rod.

Compaction test
Compaction tests were conducted on prepared
SMSW samples. The tests were conductedaccording to Part 4:3 of [9]. The two compactive
efforts used are the modified AASHTO and fourtimes (4X) modified AASHTO to simulate higher
compactive effort needed for field compaction of
MSW while still maintaining the framework of astandard test method as reported by [10]. Factors
affecting compaction were investigated during thetests. The method used in addition of water is non
pre-wetted method (NPW), where only the firstwater added to the loose sample of SMSW wasallowed to hydrate it for 18 hours. Subsequentwater added, for higher target moisture content wascompacted immediately, without further hydration
time.

RESULTS AND DISCUSSIONSMSW Moisture Content
The average value of moisture content taken fromSMSW was found to be 31.5%, this fall within therange (25%-70%) reported in literature [1], [3], and[11]. However, the oven temperature wasmaintained at 600c during oven drying to avoid
combustion of volatile materials. Moisture content
of waste depends on waste composition, climaticcondition of the area, amount of organic content
present in the waste and rate of decomposition.
Therefore, higher moisture content is expected fromolder waste than for fresh waste; especially duringdecomposition process.

Compressibility Test
Compressibility test was conducted on prepared
SMSW samples with bulk unit weight of 8.2kN/m3
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GEOMATE-Brisbane, Nov. 19-21, 2014

SMSW Specific Gravity

SMSW Particle Size Distribution

The specific gravity of SMSW determined ranged
between 1.39 and 1.53. These comply with therange of values reported in published paper for
fresh waste [10]. However It is noteworthy to know
that, the value of specific gravity is a function ofcompactive effort, the percentage of soil likematerial present in MSW and degree ofdecomposition of the waste; hence the higher
boundary of the range would be expected for waste
subjected to higher compactive effort, with higher
percentage of soil like material or waste which
decomposition process have commenced.

The result of particles size distribution of SMSW
shows that, approximately 30% of the sample wasretained on 10mm sieve and remaining constituentsare of sizes less than 10mm diameter. In addition tothat, some of the materials used in generating
synthetic waste are two dimensional; their sizes will
not adversely affect the test results due to theirrelatively small thickness. Hence, SMSW used inthis research would not over influence the results
obtained using conventional equipment from soil
mechanics laboratory. Figure 1 shows the graph of
SMSW particles size distribution.

100
90
80

Percentage Finer (%)

70
60
50
40
30
20
10
0
0.001

0.01

0.1

1

10

100

Fine MediumCoarse Fine Medium Coarse Fine MediumCoarse Cobble Boulder
CLAY

SILT

0.002

SAND
0.06
Particle

GRAVEL
2
size

in

mm

STONE
60

600

Fig. 1 SMSW particle size distribution curve

SMSW Compaction
AASHTO was 10.9kN/m3; optimum moisture
content for modified AASHTO and 4X modified

The maximum dry unit weight for modified
AASHTO was 8.1kN/m3, while that of 4X modified
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GEOMATE-Brisbane, Nov. 19-21, 2014

AASHTO were 50.3% and 35% respectively. These
values fall within the range of values reported inliterature [10]. The curves for both methods arepresented in Fig. 2.

12

Dry unit weight (kN/m3)

10
4X Modified AASHTO
Modified AASHTO

8

y1
y2

6

4

0

10

20

30

40

50

60

70

80

90

Moisture content (%)
Fig. 2 SMSW compaction curve
is not as prominent as that of soils because, therelative difference between unit weight of waterand unit weight of solids is lower for wastes thanfor soils.

The general shape of the compaction curves
obtained for SMSW in the laboratory wasconsistent with the shape of compaction curves
commonly obtained for soils. Dry unit weights
increased with moisture content to a maximum
value and then decreased with further increases inmoisture content. Similar to soils, the additional
solids content per unit volume was attributed to the
lubrication of the particles from water addition,
resulting in a denser packing arrangement. The
water addition also produced a softening of thesolid materials in wastes, increasing compressibility
and decreasing rebound (significant for wastes) in
response to compaction forces. The effectiveness ofthe moisture addition diminished at wet of optimum
conditions as indicated by the decreasing dry unit
weight (γd) due to the replacement of solids withwater. In general, the relative locations of thecompaction curves for low and high effort weresimilar to those for soils. However, the decrease in
dry unit weight at high moisture content for wastes

SMSW Compressibility
Compressibility test on SMSW resulted incompression ratio of 0.20 with total compression of
33.0% under maximum load of 224kN/m2. This
complies with the result reported in literature forfresh SMSW [1], [3], [5], and [7]. Compression
index (Cc) was 0.4, initial compression ratio (r0)
was 0.19, primary compression ratio (rp) was 0.71
and secondary compression ratio (rs) was 0.10.
These provide the necessary information needed forthe computation of expected settlement in thelandfill. However the effect of degradation due todecomposition of waste should be properly
investigated as it may influence the amount ofultimate settlement.

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FourthInternational Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

50

0.1

1

Time in minutes in Log scale
10
100

1000

10000

a0

Dial ggauge reading in mm-2

as

y
100
a100
af

150
Fig. 3 SMSW Compression curve using Cassagrande’s method
Also, 𝒓𝒓𝒑𝒑 is the primary compression ratio;
𝒂𝒂𝒐𝒐 , 𝒂𝒂𝒔𝒔 and 𝒂𝒂𝒇𝒇 are as defined in Eq. (1) while
𝒂𝒂𝟏𝟏𝟏𝟏𝟏𝟏 is the limit of primary consolidation process.
Equation (3) represents the expression forsecondary compression (𝒓𝒓𝒔𝒔 ), while 𝒓𝒓𝒐𝒐 and 𝒓𝒓𝒑𝒑 are asin Eq. (1) and Eq. (2).

The initial compression ratio was calculated
according to the following equations by [12].
𝒓𝒓𝒐𝒐 =

𝒂𝒂𝒐𝒐 −𝒂𝒂𝒔𝒔𝒂𝒂𝒐𝒐 −𝒂𝒂𝒇𝒇(1)

Where 𝒓𝒓𝒐𝒐 is the initial compression ratio; 𝒂𝒂𝒐𝒐 is thestart of compression process; 𝒂𝒂𝒔𝒔 is the start ofconsolidation process and 𝒂𝒂𝒇𝒇 is the limit ofsecondary consolidation process. The primary
compression ratio can be expressed according to
Eq. (2) shows below.
𝒓𝒓𝒑𝒑 =(2)

𝒓𝒓𝒔𝒔 = 𝟏𝟏 − �𝒓𝒓𝒐𝒐 + 𝒓𝒓𝒑𝒑 �(3)
Shear Strength

𝒂𝒂𝒔𝒔 −𝒂𝒂𝟏𝟏𝟏𝟏𝟏𝟏

Direct shear tests resulted in cohesion of 7.6kN/m3
for both modified AASHTO and 4X modified
AASHTO compaction methods, while frictional
angle for modified AASHTO compaction method

𝒂𝒂𝒐𝒐 −𝒂𝒂𝒇𝒇278GEOMATE-Brisbane, Nov. 19-21, 2014

was 42.40, and frictional angle for 4X modified
AASHTO compaction method was 48.5o as
indicated in Figure 4. The shear strength failureenvelope for the two compaction variation is shownin Figure 4. Cohesion is within the range of results
reported in literature for fresh wastes, however theangle of internal friction for sample compactedusing 4X modified AASHTO (i.e. with
11.1kN/m3wet unit weight) was found to be slightly
above the range reported in literature [13], [14], and[15]. This may be as a result of higher proportion ofreinforcing component. Thus, in design of landfill
the least shear strength failure envelope should beconsidered for effective design. The shear stressversus shear displacement plots for the two variantsof compactive efforts hence degree of densification(indicated by bulk unit weight [γb] ) for threenormal stresses 13.9kN/m2, 27.8kN/m2 and41.7kN/m2 used for the direct shear test arepresented in Figure 5. Shear stress versus horizontal
displacement graph indicates a general bilinear plot
for all normal stress values within the elastic zone.
Plastic softening occurs close to the critical shear
value, and the slope of shear stress versus
horizontal displacement tends to flatten in theplasticzone.

60ɣb = 11.1 kN/m3

ɣb = 8.2 kN /m3

50

Shear stress τ in kN/m2

40

30

20

10

0

0

10

20

30
Normal stress σ in kN/m2

Fig. 4 SMSW shear strength failure envelope

279

40

50

60

GEOMATE-Brisbane, Nov. 19-21, 2014

60.0

Shear stress (τ) kN/m²

50.0

ɣb = 11.2kN/m² (σ=13.9kN/m²)

40.0

ɣb = 11.2kN/m² (σ=27.8kN/m²)
30.0

ɣb = 11.2kN/m²( σ=41.7kN/m²)
ɣb = 8.2kN/m² (σ=13.9kN/m²)

20.0
ɣb = 8.2kN/m²( σ=27.8kN/m²)
ɣb = 8.2kN/m² (σ=41.7kN/m²)

10.0

0.0

0.00

1.00

2.00

3.00

4.00

5.00

6.00

Shear displacement (mm)Fig. 5 SMSW shear stress curves
Hydraulic Conductivity
CONCLUSION
Municipal Solid Waste hydraulic conductivity isimportant to landfill designers because of theinfluence it has on Leachate pressure distributionsin the waste body and hence on the magnitude anddistribution of effective stresses and, therefore, on
shear strength [16]. Since shear strength isinversely proportional tocompressibility/compression, the combined effectof hydraulic conductivity and compression issimulated by the SMSW.
Average hydraulic conductivity value in thisresearch was 2.16x10-6m/s for samples with wet
unit weight of 11.1kN/m3 and, 2.04x10-6m/s forsamples with wet unit weight of 8.2kN/m3. Thisshows that hydraulic conductivity values are
relatively high, also only minimal variation in
hydraulic conductivity was observed due to densitychange of the samples. Hydraulic conductivity ofgravelly lateritic soil used to represent nonbiodegradable component of SMSW may be thereason for this behaviour. However, the results
were within the range of hydraulic conductivity
values as reported by [3], [17], [18] and [19]. A
comprehensive report on waste hydraulicconductivity was given by [20].

This article presents the geotechnical characteristics
of SMSW of Akure metropolis South-western
Nigeria. The wide spread of indiscriminate
dumping of MSW all over Akure metropolis haslead to environmental degradation and poses a great
threat to public health. In finding a permanent
solution to this menace, proper waste management
technique is needed, hence the need forconstruction of a sanitary landfill. In constructionof a stable sanitary landfill three most importantfactors are considered, the stability of the lining
system, the stability of sub-grade and the stabilityof the waste materials itself. The strengthcharacteristics of SMSW simulating typicalcomposition of MSW generated in Akure
metropolis was determined in this work.
Knowledge of unit weight of MSW is required for
all aspects of landfill design as reported in theliterature. Initially the unit weight of waste isdependent on waste composition, the daily coverand the degree of compaction during placement.
Mechanisms resulting in settlement of waste
include physical compression and creep, raveling,
and decomposition due to biodegradation of280

GEOMATE-Brisbane, Nov. 19-21, 2014

organic components. For simplicity, the total
settlement of a landfill can be taken as the
combination of initial, primary and secondary
compression. Initial compression includes reduction
in voids due to removal of air. Primary compression
includes the physical compression of components
and consolidation. Secondary compression includes
all creep effects and those relating to degradation.
Knowledge of shear strength is required in order toassess the waste slope stability. Laboratory methods
have been used widely but results from such studies
should be interpreted carefully due to theirassociation with disturbed samples. Out of themethods available, the direct shear box used in thiswork has been adjudged to produce the mostreliable information. From the results of various
test carried out on the SMSW the following
conclusions could be drawn.
1) The unit weight of SMSW increased by
35% with 300% increase in compactive
effort and specific gravity increased with
14%.
2) Shear strength of SMSW increases withincreased unit weight (as a result ofcompaction), due to densification of thesolids and increase in cohesion of wastes
materials.
3) Compressibility of SMSW material is high;hence the expected settlement would be
high.
4) Only minimal variation in hydraulicconductivity was observed due to densitychange of the samples.

Hill Landfill”, Waste Management Journal, In
Print, 2008.
[4] Dixon N, Ng’ambi S, and Jones DRV,
“Structural performance of a steep slope landfill
lining system”, Proceedings of the Institution of
Civil Engineers Geotechnical Engineering Vol.
157, 2004, pp. 115–125.
[5] Dixon N, Langer U, and Gotteland P,“Classification
andmechanicalbehaviour
relationships for municipal solid waste; study usingsynthetic waste”, Journal Geotechnical Geo
environmental Engineering; ASCE, Vol. 134, 2008,
pp. 79-90.
[6] Hettiarachchi CH, “Mechanics of biocell
landfill settlement”, Dissertation, Doctor ofPhilosophy,
Department
of
Civil
and
Environmental Engineering, New Jersey Institute ofTechnology, USA.
[7] Langer U, “Shear and compression behaviour of
undegraded municipal solid waste”, Dissertation,
Doctor of Philosophy, Loughbrough University,
2005.
[8] US.EPA, “Municipal solid waste generation,
recycling, and disposal in the United States: Facts
andfiguresfor2006”,
http://
www.epa.gov/osw/nonhaz/municipal/pubs/msw06.
pdf, April 20, 2008.
[9] BS (British Standard), “British Standard
Institution, Methods of Test for Soils for Civil
Engineering Purposes, Second Edition”, Chiswick
High Road, London W4 4AL, 1990.
[10] James LH, Nazli Y, Shawna AVS, and Wilson
WW, "Compaction characteristics of municipal
solid waste", Journal of Geotechnical andGeoenvironmental Engineering; ASCE, Vol.136,
2010, pp. 1095-1102.
[11] Landva A, Clark JI, “Geotechnics of waste
fills: geotechnics of waste fills theory and practice”,
ASTM STP Vol. 1070, 1990, pp. 86–106.
[12] Garg SK., “Soil Mechanics and Foundation
Engineering”, Khanna Publishers, 4575/15, Onkar
House, Opp. Happy School Daryaganj, New Delhi,
2009, pp. 224-263.
[13] Jones DRV, Taylor DP, Dixon N, “Shearstrength of waste and its use in landfill stability
analysis”,
Proceedings
Geoenvironmental
Engineering Conference. Thomas Telford, 1997,
pp. 343–350.
[14] Kavazanjian E, 2001, “Mechanical propertiesof municipal solid waste”, Proceedings Sardinia,
Eighth International Waste Management andLandfill Symposium, Cagliari, Italy, Vol. 3,
pp.415–424 .
[15] Manassero M, Van Impe WF, Bouazza
A,“Waste disposal and containment”, Proceedings
Second International Congress on Environmental
Geotechnics”, Osaka, Vol. 3, 1996, pp.193–242.
[16] Jones DRV, Dixon N, “Landfill lining stability
and integrity: the role of waste settlement”,

ACKNOWLEDGEMENT
The authors would like to acknowledge thecontribution of Azeez, Gafar Adetunji in datacollection for this work.The equipment used for thisresearch was made available by the Department ofCivil and Environmental Engineering, Federal
University of Technology, Akure, Ondo State,
Nigeria.
REFERENCES[1] Reddy KR, Gangathulasi J, Parakalla NS,
Hettiarachchi H, Bogner JE, and Lagier T,“Compressibility and shear strength of municipal
solid waste under short-term leachate recirculation
operations”, Waste Manage. Res. Vol. 27, 2009, pp.
578–587.
[2] Adebayo FA, “Basic elements of water supply
and waste management”, Supreme Printing Press,
2005, pp. 109-111.
[3] Reddy KR, Hettiarachchi H, Parakalla NS,
Gangathulasi J, and Bogner JE, “Geotechnicalproperties of fresh municipal solid waste at Orchard
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GEOMATE-Brisbane, Nov. 19-21, 2014

Geotextiles & Geomembranes Vol. 23, 2005, pp.
27–53.
[17] Landva AO, Pelkey SG, and Valsangkar AJ,“Coefficient of permeability of municipal refuse”,
Proc. of The Third International Congress on
Environmental Geotechnics, Lisboa, Portugal, Vol.
1, 1998, pp. 63-67.
[18] Chen T, and Chynoweth DP, “Hydraulicconductivity of compacted municipal solid waste”,
Bioresour. Technol. Vol. 51, 1995, pp. 205-212.

[19] Jain P, Powell J, Townsend TG, and Reinhart
DR, “Estimating the hydraulic conductivity oflandfilled municipal solid waste using boreholepermeameter test”, Journal of environmental
engineering, ASCE, Vol.132, 2006, pp. 645- 653.
[20] Powrie W, Beaven RP, “Hydraulic propertiesof household waste and implications for landfills”,
Institution of Civil Engineers GeotechnicalEngineering Journal, Vol. 137, 1999, 235–247.

.

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INNOVATIVE GROUNDWATER TABLE MONITORING USING TDRTECHNOLOGY
Vlastimil Chebeň1, Marian Drusa2 and Michal Kuba3
Faculty of Civil Engineering, University of Žilina, Slovakia; 3Faculty of Electrical Engineering,
University of Žilina, Slovakia

1,2

ABSTRACTThis paper introduces an innovative and economically convenient measurement system that is based on a novelty
method of installation, operation and remote control technology for ground watertable measurement. The
technology is based on TDR (Time Domain Reflectometry) that employ a unique hollow coaxial cable.
Installation is performed by CPT/DP penetration testing equipment, that in its nature, is relatively light, versatile,
operative, and is not demanding of manpower or machinery. This method brings benefit to currently unreachablesites ex. steep slopes, places with little or no road access, option for setting up additional probes on existing
structures etc., as the method doesn´t require conventionally truck-mounted drilling rigs. Electronic origin of
measurement offer the possibility of probe networking, remote sensing, automatic data acquisition andevaluation through developed software. Proposed measurement system has been laboratory tested, calibrated andinstalled on various sites over past 6 years in Slovak republic.
Keywords: TDR, Groundwater Level Measurement, Coaxial Cable, Penetration Testing
properties occurs, e.g. a damaged cable, change indielectric constant of environment and is sent back.
Signal travel time, hence time domain, and known
propagation velocity determine localization of signal
reflection. The development of a new type of TDR
probe for measuring groundwater level was started
in order to meet requirements for reliable, low cost,
remote sensing capable and possibility of installationin vehicle inaccessible areas. Proposed groundwaterlevel sensing is based on air-filled coaxial cable
resembled to an open pipe piezometer.
Measurements of water level are determined bytravel time analysis of the reflected signal from airwater interface, hence TDR piezometer. Laboratory
testing and calibration as well as field installation
experiments and actual field data are presented .

INTRODUCTION
Slope instability has been an issue worthy ofconcern in applied soil mechanics engineering for
decades. It causes serious losses to both private andpublic sectors all over the globe and has beenstudied throughout history by many researchers,
scholars, academics, and practitioners from different
perspectives. Unfortunately, landslides with severe
consequences regularly occur in potentially unstableareas, which are not covered by a soil monitoring
system due to lack of funding or priority. There areseveral factors which initiate soil movement, but the
principal trigger mechanism is the presence of water,
generally formed in ground water level - phreatic orpressure
combinedwithgeological,
geomorphological and climate conditions in certain
time and locality. Over past 10 years, demand forautomatic and remote sensing monitoring systems
for collecting required geotechnical data, mostly soil
deformation and water level, initiated competition
between electric based techniques. TDR technology(Time Domain Reflectometry) is a technology thathas been employed for a variety of uses in electricalengineering. Since the 1930’s, TDR has been used
for examining electrical properties of cables andtransmission lines, and measuring electricalproperties of organic liquids. Universality andfurther enhancement of the technology during the1990 is led to monitoring of landslide slope
movements, soil electrical conductivity or watercontent measurement in soil [3]. TDR uses principleof radar, where an electric voltage pulse is reflectedfrom point where inconsistency of electrical

LANDSLIDES IN SLOVAKIA
The role of monitoring of negative factors ofslope deformation is a highly demanded in Slovakia.
Altogether, more than 5.25 % coverage of land isendangered by slope deformations, furthermore
about 98 km of motorways and 67 km of railway
lines pass through landslides. The most known
landslides occurred in Handlova in 1953, Riecnica in1961 and in Velka Causa, Kapusany, Nizna Mysla in2010. The most often trigger factor of slope
deformations in Slovakia is effect of undergroundwater combined with geological, geomorphologicaland climate conditions. According to statistics ofnational geological institute of Dionyz Stur,
localization of slope deformation is mostly in zones

283

GEOMATE- Brisbane, Nov. 19-21, 2014of Carpathian flysch belt, then Neovolcanic, West
Carpathians and Central Carpathian Paleogene zone.
The reason to implement TDR technology for
deformation and groundwater monitoring in
Slovakia was to find an attractive alternative to otherwater level measurement systems that would benefit
in rapid and relatively easy installation, cost
efficiency and suitability for remote sensing.
Research and design of piezometer for phreaticwater table based on TDR started in 2008 and later
installed on three localities in Northern Slovakia –Dolna Tizina, Povazska Bystrica, and BrusnoChrenovec. First two of them are presented in thearticle.

Acquired data were sorted, compared and analyzed.
As in radar, TDR utilizes the roundtrip travel time in
the air section to determine the water level, proper
data reduction method of travel time determinationand calibration of pulse propagation velocity wasneeded. The precise time of reflection that
corresponded the position of the interface-required
calibration, due to different velocity of propagationin lead and sensing cable. Waveguide with 5/8´´diameter was feasible due to larger inner space
where water can freely pass through.
FIELD INSTALLATION AND TESTING
In 2010 and 2011 TDR piezometer probes were
installed on three test sites in northern and western
Slovakia, situated on slopes that are inaccessible totrucks. These sites were selected intentionally toconfirm feasibility of installation using penetration
test equipment.

TDR LABORATORY TESTING
In the period of 2008-2010 laboratory testing of new
type piezometer for phreatic water tablemeasurement based on TDR principle was carriedout. Sensing probe was formed by a waveguide –hollow coaxial cable where dielectric is an air. This
construction format allow water freely penetrate thecable according to principle of communicating
vessels where water balances out to the same level
as it settles. Determination of water level isprincipally trivial while air is replaced by water thathas different dielectric constant Eq. (1) which resultsin signal reflection at exact point.

εw = Kw ⋅ε0

Installation method
Installation of TDR piezometers were to small
diameter holes of ø 35 - 40 mm carried out by static
CPT or dynamic penetration equipment. Detail of
special adaptor needed for installation to certain
depth is shown on Fig. 2.

(1)

Testing scheme plotted on Figure 1 consisted of a
tube representing a borehole, measuring waveguide hollow coaxial cable and TDR unit. Two types ofsensing waveguides with 50 Ω impedance were
tested Heliflex HCA 58-50 with 5/8´´ and HCA 1250 with 1/2´´ diameter. Water level was increased
and decreased in many cycles while taking
measurement by TDR and controlled and comparedwith measuring tape.

Fig. 2

Detail of installation using penetrationequipment

Principally, determination of TDR ground waterlevel is similar to standpipe piezometer which isbased upon equilibration of standpipe water pressure
with that at the measurement point and pore pressure
is calculated in Eq.(2):Fig. 1∆u = ∆h ⋅ γ w

Laboratory testing scheme

284

(2)

GEOMATE- Brisbane, Nov. 19-21, 2014

Test site Povazska Bystrica

were two or more significant water level horizons. In
badly accessible places (I8, I8-P) TDR inclinometer
and TDR piezometer were installed.
TDR piezometer I8-P was installed in the bore
made by DP equipment. Sensing waveguide had
length 7.9 m capturing the first water level horizon.
Before embedding the waveguide, calibration
measurement had to be performed with no water.
Figure 3 shows two measurements of ground waterlevel, the first one as of April 2010 and the mostrecent from June 2014. It is obvious that sensing
waveguide is still in good condition and doesn´tsuffer any damage or deterioration of key
parameters. As seen on the figure, apparent
waveguide length is 8.6 m and has to be adjusted bysignal velocity propagation v p =0.92. This is due todifferent propagation velocity in lead coaxial cableand sensing waveguide. Therefore, while taking
measurements, the parameter v p is set to 1.0. Last
taken data say that groundwater was in 3.68 m
depth. It must be noted that 0.6 m section of
waveguide sticking out above the ground levelshould be subtracted.

Test site is located near town Povazska Bystrica
in Northern Slovakia, where new bypass road was
built in cut off of the hill in difficult geologicalconditions that was affected by landslides. Area
belongs to the territory of hill called St. Helena,
which ranks to orographic northwestern nesses ofStrazovske Mountains. The relief in the studied area
reflected the obvious connection between theresistance of rocks against weathering processes andmorphology of the terrain. Orlovske layers make the
top of the area of interest and are represented
predominantly by sandstone containing thin marls ormarlits inserts. Soft shape of lower part of the area ismade up with spherosiderit layers with low
resistance against weathering processes resulting in
eluvial-deluvial deposits of clayey sediments that aresusceptible to sliding.
Geotechnical monitoring of slope deformations
was performed on the site mainly by inclinometers,and 3D inclinometers. Water pressure in layers
important for stability calculations was measured byopen pipe piezometers in certain depth level. There

Sensing waveguide L = 7.9 m

Hw = - 7.75 m

Hw = - 3.68 m

01.04.2010

03.06.2014

Fig. 3

Measurement of GW level in piezometer I8-P at Povazska Bystrica

285

GEOMATE- Brisbane, Nov. 19-21, 2014

Sensing waveguide, L= 6.5 m
Hw = - 4.18 m
Hw = - 3.58 m

20/05/2014

Fig. 4

11/04/2014

Measurement of GW level at locality Dolna Tizina
fencing were damaged. In 2001, the landslide was
re-activated when creeping slide mass ataccumulation zone endangered adjacent properties.
In 2003, re-initiated movements were threat again.
Later in 2006, slope failures extended to sides withdecrease of terrain in the active zone from 2 to 2.5
m. Soil movement caused structural damages ofhouse no. 358 that remained uninhabitable.
Owing the soil instability, a TDR piezometer was
installed in 2010 employing dynamic penetration
technique to create a bore. Waveguide calibration
preceded its soil embedment. The same process withmeasured data described in previous section
concerning calibration should apply. Figure 4 plots
data of ground water level in last 1.5-month span.
Relatively rainy end of April 2014 and beginning ofMay 2014 resulted in rise of groundwater level of
0.55 m.

Test site Dolna Tizina
Locality of Dolna Tizina is situaed in Central
Carpathianpaleogene.
Accordingtothegeomorphological division of the territory of the
Slovak Republic, considered territory belongs to
Fatra-Tatra region of Zilina basin subunit Varinske
Podolie. Based on the documented visible externalsigns, whole area of slope deformation is a part ofmorphologically significant landslide activity, which
has length of about 250 m and width of 130 meters.
Within this relatively extensive active area two
smaller partial landslides were identified intransportation and accumulation part. The primarycause in the development of landslide activity was
erosion of local stream in the bottom part of area ofinterest.
Buoyancy effects of water and the presence ofdisturbed shear zones were the main trigger factorsof the slope deformation. Ground water level at thetime before remediation works reached theaccumulation zone level 2 m below the groundsurface, while two distinct horizons of GW level
were found. Effectiveness of drainage wells, inparticular, showed a significant decrease of
buoyancy effects in the transportation andaccumulation zone of the landslide.
The activity of slope failure started in 1997 due
to excessive torrential rainfall when local road and

AUTOMATIC DATA EVALUATION USINGMEDIAN FILTERIn the next section, principles of automaticground water level determination are proposed.
Since the measurement system consists of cables
that are not perfectly homogenous, noise can havenotable influence on its performance. While TDR
signature is a non-linear signal, the powerful method286

GEOMATE- Brisbane, Nov. 19-21, 2014

has to be employed for waveform examination withrespect to recognition of lead cable that can beseveral hundred meters long and sensing cable,
which length is particularly up to 30 m. For
automatic data evaluation, perhaps, the mostfundamental form of signal manipulation is that offiltering, which describes a rule or procedure forprocessing a signal with the goal of separating or
attenuating a desired component of an observed
signal from either noise, interference, or simply fromother components of the same signal. It is obvious
from the TDR signal, that water level is in the point
where sharp transition represented by waveform
drop occurs. Localization of this point by numericalmethods is a way to automatic water level detection.
Therefore, use of running median filter - a nonlinear
signal processing method in this application aiming
at exploiting the system’s nonlinearities or thestatistical characteristics of the underlying signals.
The running median was first suggested as anonlinear smoother for time-series data [1].
Regarding definition of the running medianfilter, a discrete time sequence x(n) of N samples intime instants n = 0, 1 2, … N must be defined. The
running median passes a sliding window of length M
samples over the time sequence x(n) that selects,
at each instant n, an odd number of M consecutive
samples to comprise the observation vector x(n)as Eq.(3):x ( n )=

i 1, 2, ..., M x ( n − M + i )  , =positive
integerthatsatisfies
conditiony(m) > threshold or y(m) < threshold, meaning theformer no water presence in cable, the latter water
presence in cable.

a)b)Fig. 5Adjusted index m value corresponds to signal
travel time from transmitter to water level and back.
Since propagation velocity is known, distance fromreference point to water level can be obtained from
Eq.6:

Lm
=

(3)

The median smoother operating on the input
sequence x(n) produces the output sequence y(n),defined at time instant n as Eq.(4):y (n) = Median {x ( n )}Median {x=( n )}x ( ( M + 1) / 2 )1( t2 − t1) vL
2(6)where L m is the length of sensing waveguide, t 1 isreflected signal travel time in lead cable, t 2 isreflected signal travel time in measuring waveguide.
Hence, value of L m is measured water level. Issue ofsystem calibration is not discussed while quality andmanufacturing precision of sensing waveguideguaranties its material characteristics.

(4)

Setting the symmetric observation window,
operator Median{.} is then defined as follows
Eq.(5):=y ( n)

TDR waveform a) as measured b) after
median filtering

CONCLUSION
Despite the fact that air-dielectric TDR
piezometer was first proposed by [3] in 1990´s, its
wide spread hadn´t been yet very successful. A new
type of TDR probe for groundwater level
determination proposed in the paper, comprising of
waveguide Heliflex HCA58-50 and Campbell
Scientific hardware. We developed software fortaking measurements and data processing. First field
application was set 4 years back in 2010, when TDR
piezometers were installed into a small diameterbore of 30-40 mm, created with equipment for
dynamic or static penetration. This technique wasproved feasible and viable on condition that skilled
and experienced manpower. Recent data from two
probes are presented showing that sensing
waveguide as a key element, is in good condition(5)

where x ( ( M + 1) / 2 ) is the ( ( M + 1) / 2 ) − thelement of the vector x ( n ) . Vector x ( n ) contains
the same elements as the vector x(n) but theelements in vector x ( n ) are in ascend order of theirvalues.
The reason of applying a running median filter
consists in smoothing neighboring extreme values ofthe signal with no effect on subsequent evaluation.
After the waveform is smoothen using medianfilter as shown on Fig. 5, signal is processed indecision block and threshold procedure is performed
finding discrete time index m, where signal exceeds
pre-set level. It means, that index m is smallest
287

GEOMATE- Brisbane, Nov. 19-21, 2014

SGEM 2012 Vol. II. ISSN 1314-2704 p.143150, DOI: 10.5593/sgem2012[7] Drusa M., Chebeň V., Prohovníková P., 2013.
Functionality of TDR Piezometers andInclinometers for Monitoring of Slope
Deformations In: Sgem 2013: 13th international
multidisciplinary scientific geoconference:
conference proceedings. Vol. II. - Sofia:
STEF92 Technology, 2013. - ISBN 978-95491818-8-3. pp. 157-164.
[8] Drusa, M., Chebeň, V., Stolárik, L.,
Prohovníková, P.: Laboratory calibration of
TDR measurements of underground slope
deformations. In: Theoretical foundation of civilengineering: XXII Slovak - Polish - Russian
Seminar: Žilina, Slovak Republic, 09.09.2013 13.09.2013. Moskva : Izdateľstvo ASV, 2013.
ISBN 978-5-93093-986-6. - S. 437-442.
[9] Drusa, M., Chebeň, V. Bulko, R. 2014. New
Technologies Implemented In Geotechnical
Monitoring on Transport Constructions, In
SGEM 2014 Proceedings, Book 1 Vol.2 pp.
651-656, ISBN 978-619-7105-08-7, DOI:
10.5593/sgem2014B12[10] Marschalko, M., Yilmaz, I., Křístková, V.,
Fuka, M., Kubečka, K., Bouchal, T.: An
indicative method for determination of the mosthazardous changes in slopes of the subsidencebasins in underground coal mining area in
Ostrava (Czech Republic). Environmental
Monitoring
andAssessment
02/2012;
DOI:10.1007/s10661-012-2571-7[11] Mužík, J.: Analysis of Geotechnical Structures
Using Meshless Local Petrov-Galerkin Radial
Point Interpolation Method, In SGEM 2014
Proceedings, Book 1 Vol.2 pp. 651-656, pp. 4148,
ISBN
978-619-7105-08-7,
DOI:
10.5593/sgem2014B12[12] Segalini, A, Carini, C.: Underground Landslide
Displacement Monitoring: A New MMES
Based Device, Landslide Science and Practice,vol. 2, 2013, Early Warning, Instrumentationand Monitoring - Margottini, Canuti & Sassa
Eds. - Springer London pp. 87-93 - doi:
10.1007/978-3-642-31445-2[13] Yilmaz, I., Marschalko, M., Yildirim, M.,
Dereli, E, Bednarik, M., (2012) Preparation of
the GIS based kinematic slope instability andslope mass rating (SMR) maps: an application
to a railway route in Sivas (Turkey). Bulletin ofEngineering Geology and the Environment.
DOI: 10.1007/s10064-011-0384-5

and still work. Assumption of clogging the innerspace by fine particles of clay surrounding soil was
not confirmed due to special sand filter at the bottom.
Even if the clogging was the case, a probe
replacement could be possible both physically andeconomically. The large pulse reflection at the airwater interface allows measurement at considerable
distances, therefore when multiplexed one TDR
point can cover area of hundreds meters benefittingin hardware cost reduction. New areas can bemonitored with no or reduced access roads that
suffer from potential of geohazard risk, e.g. steep
slopes, dense forests, active landslides.
Electric nature of the technology is perfect not
only for remote sensing but for automatic dataprocessing and evaluation. Running median filter isused for smoothen TDR signature reducing noise,interference or reflection in the cable and forrevealing water level at exact point where thresholdvalue is exceeded.
Couplings and connectors are probably the weaklink in the chain as they are exposed to humid andcorrosive environment when installed unprotected.
Next research will head to building remotesensing measuring system with automaticgroundwater level detection and improving
reliability of the technology.
ACKNOWLEDGEMENTS
The research is supported by European regional
development fund and Slovak state budget by the
project “Research centre of University of Zilina”,
ITMS 26220220183.
REFERENCES[1] Arce R.A., Nonlinear Signal Processing.
Hoboken, New Jersey: John Wiley & Sons,
2005[2] Chung C. et al., New TDR waveguides and data
reduction method for monitoring of stream anddrainage stage, Journal of Hydrology, Vol.505,
2013, pp. 346-351[3] Connor
K.M.,
Dowding
C.H.,
Geomeasurements by Pulsing TDR Cables andProbes, Boca Raton: CRC Press, 1999
[4] Decký M., Drusa M., Pepucha Ľ., Zgútová K.
Earth structures of transport constructions,
Harlow, Essex: Pearson, 2013. - 180 s., ISBN
978-1-78399-925-5[5] Dowding, C. H., O'Connor, K. M.,
Geomeasurements by Pulsing TDR Cables andProbes, Boca Raton: CRC Press, 1999. ISBN
08-493-0586-1[6] Drusa M., Chebeň V. 2012. Implementation of
TDR Technology for Monitoring of Negative
Factors of Slope Deformations, Proceedings of288

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

DIFFERENTIAL CAPACITOR SENSOR OF WIRELESS SENSOR
NETWORK FOR LANDSLIDE MONITORING
S. M. A. Motakabber1, M. I. Ibrahimy1, and M. Z. Hossain2
Faculty of Engineering, International Islamic University Malaysia, 53100 KL, Malaysia
2
Graduate School of Bioresources, Mie University, Mie 514-8507, Japan

1

ABSTRACT
Every year all over the world, many lives and properties are lost due to many geological catastrophes like,landslide or land-slip. Manual and electronic monitoring systems are used to predict the landslide happening
period. The manual monitoring system is laborious and not practicable, then again, most of the electronicsystems are complex and expensive. To monitor the natural disasters, a detecting system faces a lot of harderconditions. Natural tragedy occurs unexpectedly and damages the instrument system as well. The sensor systemshould be planned as a spread network with a simple positional identification device such as RFID. In addition,
the network should have self-recovery, self-directed operation and actual data transmission facility in urgent
situations. A distributed node network needs lot of sensors with complex structure and it is expensive too. This
paper describes a simple and low cost system which comprises an underground pretension cable with a capacitor
gage sensor attached at one end. A wireless sensor network has been proposed for a simple landslide monitoring
system using RFID. The sensing node network can be operated by initializing mode, measuring mode and urgent
mode depending on the situation. A switching mechanism is used to switch automatically to any one of these
operating modes which makes a robust and dynamic control of data transmission system. A mathematical model
has been developed for the system and verified by simulation. The result shows that an early prediction of thelandslide is possible by using the proposed system.
Keywords: Wireless Sensor Network, Landslide, Capacitor Sensor, RFID, Geological Catastrophe
movement, velocity and acceleration of the landslideof the target area. Practically a large number ofnodes are used for landslide monitoring system. For
simplicity of the structure, each node addressed by

INTRODUCTION
It is very hard to forecast an exact time, date andplace of incidence of many natural disasters like alandslide. Worldwide, landslides cause about 1,000
deaths per year and property damage ofapproximately US$ 4 billion [1]. Therefore, regularinspection and a record maintaining around thehazardous area is essential. If somehow we can catch
some symptoms before the worst incidence, theinformation can help us to report to the residents andit can be useful to predict to operate the monitoring
system efficiently. Existing manual solutions are
insufficient and sometimes costly to landslide
monitoring and prediction. Installing a single sensor
for monitoring a wide hilly target area is not
sufficient, since most of the cases the property on
the hill is changed in about every 10-15 meters
distance. Wiring with multiple sensors to a central
data logger is also not practicable due to reliability
and it requires frequent maintenance. Therefore,
wireless sensor networks are used for real-timelandslide monitoring system. A basic topology of awireless sensor network is shown in Fig. 1. In thisarrangement all nodes addressed by RFID tag arewirelessly connected to each other and finally these
are linked with the local base station (LBS1). Eachnode has at least one sensor to measure theparameter of the land, such as temperature, land

Fig. 1 Basic wireless sensor network forlandslide monitoring
RFID tag, has a short distance communication
facility (about 100m). It is sufficient to make a
network for a large area. However, it is not enoughto communicate with a secure distance during
disaster time. Different algorithm and wirelessprotocol can be used among the nodes and LBS1 forcommunicating to each other. The LBS1 has a long
distance communication facility with the remotecontrol station, which is connected with server.

289

GEOMATE- Brisbane, Nov. 19-21, 2014

land user for protecting the people’s lives andproperties.

Therefore, the server can always receive real-timedata of the sensor through LBS1.
A capacitor type sensor can be used formonitoring the land movement. A thin film strain
gage pressure sensor with high accuracy pressure
measurement is claimed [2]. A simple pretension
underground cable attached with a strain gage at one
end can be used to measure the pressure of the soil
for the landslide monitoring system [3]. But it
introduces noises and needs a complex thermal
adjustment. A differential capacitor sensor of
wireless sensor network for landslide monitoring has
been proposed as shown in Fig. 2 which introduce
less noise and low thermal adjustment. The
differential capacitor sensor is simple, robust,

SENSOR MODELING
A simplified force diagram of the proposedlandslide sensor that is, pretension cable withdifferential capacitor cell is shown in Fig. 3.
Assume that a pretension steel cable of length L is
attached with two end supports under the ground. If
the cable linear expansion coefficient is α L and thesurrounding temperature of the cable is changed ∆T
degree Kelvin then the change of cable length ∆LT
can be calculated as follows.

Fig. 3 Simplified force diagram of the proposedlandslide pressure sensor

Fig. 2 Basic arrangement of a single sensor node forthe proposed landslide monitoring systemαL =reliable and chipper compares to other types of
sensors. A slide movement of the soil is produced aforce on force plate as well as the pretension wire. A
variable differential capacitor is connected with one
end of this wire. Therefore, due to the movement of
the land there is a change of the capacitance in the
differential capacitor cell. This capacitance change
can be used to calculate the landslide prediction anddetection. An electronic circuit (used to measure thecapacitance change) and a small distance (about
100m) wireless communication system are used tomake a sensor node. A number of the same kind of
sensors setup or node can be used for monitoring awide land area. Thus it is important to define eachnode carefully by a unique number by RFID tag
within a wireless network to identify the exact
location of the incidence. This ID number can beeasily used to locate the landslip zone. A majority of
the Wireless Sensor Network (WSN) arrangements
are mainly data collection networks [4],[5]. The
wireless sensor network will recurrently collect therespective data and collaboratively process
measurements from the field under study before
forwarding them to the central monitoring station.
The central monitoring station will execute morecomputationally-intensive algorithms such as finite
element modeling and parameter identification [6],[7] and will act as the expert interface to the system.
A mobile communication system can be used totransmit the sensors sampled data and relevant
information to a distant central database server
computer for analysis purpose. The instantconveying of information will allow us to implement
instant disaster rescue measures and to notify the

1 ∆LT
L ∆T

(1)

Or, ∆LT = αL L∆T

(2)

E=

F/A
∆L/L

(3)

∆L =

F(L + ∆LT )EA(4)When the land is slightly moved to a distance S
from its initial position then it will create a force F
on force plate as well as on the cable. If the Yang’s
modulus of the cable is E then at force equilibrium
condition be represented by Eq. (3).

Where, A is the cross sectional area of the cableand ∆L is the change in length of the cable due toforce.
Considering the temperature effect,

The work U E done by the movement of the soil
can be calculated by Eq. (5).
UE = FS(5)

The potential energy U W stored in the cable canbe calculated as follows.
∆L

UW = � F d∆L
0(6)

From Eq. (4) and Eq. (6), it can be written as

290

GEOMATE- Brisbane, Nov. 19-21, 2014

follows.
UW = �

∆L

0

EA∆L
d∆L
(L + ∆LT )

EA∆L2
∆LF
UW =
=
2(L + ∆LT )2

Or,

capacitance ∆C of the differential capacitor cell withrespect to the total capacitance C can be calculated
by Eq. (12).
(7)

Or,

(8)

ES AS ∆LS
LS

(9)

Where, A S and L S are the cross section area andlength of the supporting spring respectively, F S is
the force on the substrate and ∆L S is the change inlength of the substrate due to force. So the potential
energy U S storage in the spring can be calculated asfollows.
US = �∆LS

0ES AS ∆L2S
2LS

US =

F �S −ES AS ∆L2S
∆L
�=
2
2LS

∆LS
2F
∆L
=�
�S − �LS
LGS EGS AGS
22FS∆C = C �k�+ αT�LS E S A S(14)RESULT AND DISCUSSIONA PSPICE simulation has been studied for the
proposed landslide sensor for monitoring system.
The result is shown in Fig. 5. In this simulation it isconsidered that the Yang’s modulus E of the cable isinfinity and the temperature coefficient of thecapacitor cell is very low. From Fig. 5 it is foundthat from the beginning there is a very slow
landslide effect and about four months later theeffect is more visible. The sensor ID number 001(RFID tag number) shows that its capacitance ischanging exponentially; it means a massive
landslide will be happened within short time in theregion under the sensor ID 001. The others sensor
nodes also experienced some land slide effect.

(10)

Combining Eq. (8) and Eq. (10), it can be written as
follows.

Or,

(13)

Eq. (14) indicates that the change of capacitanceof the differential capacitor cell is directly
proportional to the squire root of the force anddisplacement of the land.

FS d∆LS

Or,

2F∆L∆C = C �k��S − � + αT�
LS E S A S
2From Eq. (4), if the Yang’s modulus E of thecable is very large then ∆T ≈ 0 and Eq. (13) can be
rewritten as Eq. (14).

Again, if the Yang’s modulus of the spring of thedifferential capacitor cell is E S then at force
equilibrium condition can be calculated by Eq. (9).
FS =

(12)

Combining Eq. (11) and Eq. (12), the change ofdifferential capacitance can be calculated by Eq.
(13).

From Eq. (5) and (7), the potential energy U C
stored in the differential capacitor cell (supporting
spring of the capacitor) can be calculated as follows.
∆LF
UC = UE − UW = FS −2
∆L
UC = F �S − �
2

k∆LS
∆C
=�
+ αT�
C
LS

(11)

A basic construction of a differential capacitor
cell is shown in Fig. 4. If the cell factor and thetemperature coefficient of the differential capacitor

Fig. 4 Construction of a differential capacitor
sensor cellFig. 5 Change of capacitance of the capacitor cellwith time due to land movement

are k and α respectively, then the change of291

GEOMATE- Brisbane, Nov. 19-21, 2014pressure transducers”, Sensors and Actuators A:
Physical, Vol. 35, Issue 3, 1993, pp. 265-268.
[3] Motakabber SMA, Ibrahimy MI and Anwar F,“Wireless Sensor Network for Landslide
Monitoring”, in proceedings of the 3rdInternational Conference on Geotechnique,
Construction Materials and Environment,
Nagoya, Japan, Nov. 13-15, 2013.
[4] Szewczyk R, Polastre J, Mainwaring A andCuller D, “Lessons from a sensor network
expedition”, in proceedings of the 1st European
Workshop on Sensor Networks, Jan. 2004.
[5] Xu N,
Rangwala S,
Chintalapudi KK,
Ganesan D, Broad A, Govindan R, and Estrin
D, “A wireless sensor network for structuralmonitoring”, in proceedings of the 2nd
International Conference on Embedded
Networked Sensor Systems, New York, USA,2004, pp. 13-24.
[6] Kuppusamy T, Sheng J, Parker JC and Lenhard
RJ, “Finite-element analysis of multiphase
immiscible flow through soils”, Water
Resources Research, Vol. 23, Issue 4, 1987, pp.
625-631.
[7] Hoshiya M and Sutoh A, ”Kalman Filter-Finite
Element Method in Identification”, J. Eng.
Mech., Vol. 119, Issue 2, 1993, pp. 197-210.

CONCLUSION
A pretension cable and a differential capacitor
sensor with RFID tagged ID can be used forlandslide prediction and detection purpose. Thechange of cell capacitance is a direct indication of
the landslide effect. This principle can help todevelop a simple and low cost real time landslide orlandslip monitoring system. According to themathematical model Eq. (13) for an efficient system,
the Yang’s modulus of the cable must be very large.
The steel and carbon fiber cable have a very large
Yang’s modulus and can be used in thisdevelopment.
ACKNOWLEDGEMENT
This research has been supported by the Ministry ofHigher Education of Malaysia through theFundamental Research Grant Scheme FRGS13-0270268.
REFERENCES[1] Lee S and Pradhan B, “Landslide hazard
mapping at Selangor, Malaysia using frequency
ratio and logistic regression models”,
Landslides, Vol. 4, No. 1, 2007, pp. 33-41.
[2] Hongye W, Kun L, Zhichou A, Xu W and Xun
H, “Ion-beam sputtered thin-film strain-gage292

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

BRIDGE SCOUR MONITORING BY USING RFID SYSTEM
M. I. Ibrahimy1, S. M. A. Motakabber1 and M. Z. Hossain2
Faculty of Engineering, International Islamic University Malaysia, 53100 KL, Malaysia
2
Graduate School of Bioresources, Mie University, Mie 514-8507, Japan

1

ABSTRACT
Bridge scour is an erosion which removes stream bed or bank material from bridge foundation due to flowingof water. Too much bridge scour is risky for the bridge foundation and causes sudden bridge to collapse without
any warning. It implements significant impacts on the traveling public safety as well as the economy of thecountry. A number of parameters are associated with scour, thus different types of sensors are required tomeasure the individual affecting factor. A complex and expensive data logging from sensor and electronic
communication systems are used to monitor the bridge scour in real-time to ensure the integrity of bridge
structure. A high frequency band (13.56MHz) radio frequency identification (RFID) system has been proposed
and that has been validated by simulation using PSpice software for direct scour monitoring scheme, which issimple and low-cost. A number of passive RFID tags have been piled surrounding the bridge foundation which
are continually detected by the FRID reader. The erosion of the river bed carries out the RFID tag from nearby
the bridge structure. As a result, the RFID reader can directly detect the absence of the tags as well as the amountof the scouring. Since, the design structure of the RFID system is simple, it is highly robust and easy to
implement. The system can easily be implemented with an existing bridge structure and a wireless telemetry canbe used to send the real-time data from the proposed system to a desktop computer in the monitoring lab.
Keywords: Scour, Bridge Monitoring, Riverbed Erosion, RFID, Passive Tag

Once the scour takes place, the tags are washed out
and thus they are not detected. Therefore, the result
indicates that bridge scours have been occurred at
the known depth, where the tags are initially buried.
That will reduce the huge cost of physicalmonitoring for bridge maintenance. Mobile
communication can be used to transmit relevant
information to bridge maintenance and management
units and road users when a bridge would be
potentially damaged by manmade or natural
disasters. The instant conveying of information willallow the bridge management units to implement

INTRODUCTION
An RFID system is simple in its structure which
consists of two main components only: the reader
and the tag (transponder) with their antennas asshown in Fig. 1. A passive RFID system, the tag
does not contain an onboard power supply andharvests the energy from the reader transmitted RF
wave for its operation. Since the passive tag has nobattery, it is simple, low cost, long life and easy tomaintain. The RFID technology permits thewirelessly two-way transfer of information from areader to a tag via RF waves transmitted throughantennas. Two major advantages of the highfrequency band RFID system (13.56 MHz) to makeit suitable for monitoring the bridge scouring. First,
it does not need line of sight between the reader andthe tag for communication. Second one, it can easily
communicate through the metal, water, soil etc.
Therefore, the tag can be detected even when it isburied in the bed substrate of the bridge. The highfrequency band RFID system (13.56 MHz) can
easily communicate up to 100m distances. Generally,
the tags are buried at predetermined locations(depths) side by side with known lengths. The tags
are subsequently driven into the bed substrate at thelocation where bridge scour holes are expected
within the detection range of the reader antenna,
which are installed directly above the tags. The tags
are kept perpendicular to the RFID reader antenna
plane, so that they can be continuously detected.

instant disaster rescue measures and to notify road
users to avoid dangerous road sections, thus thepeople’s lives and properties will be protected.
Bridge scour is the meaning of removal of soil,
sand and rocks from around a bridge supports orpiers as shown in Fig. 2. Rapidly moving water can
293

GEOMATE- Brisbane, Nov. 19-21, 2014

both devices called the inventory round. An RFID
reader can identify an object, location, orientation
etc. through the RFID tag. Fig. 3 shows an RFID
reader antenna coil and tag arrangement surroundingof a bridge pied. Each RFID tag has a unique

wash out the river bed materials and make scour
holes, which can be threatening of the existence of abridge structure [1]. Scour happens under the waterand hard to see by naked eye. As a result, every year
a number of bridges are collapsing all over the world
and it damages lot of money and lives. The threemain causes of bridge failure are collision,
overloading and scour. It has been estimated that
60% of all bridge failure results occurred fromscouring and other hydraulic-related causes [2].

(a)

(b)

Fig. 3 (a) Cross sectional top view of the bridge
pier and RFID tag arrangement (b) Cross sectional
side view of the bridge pier and RFID tag
arrangement
number or code and the reader can sequentiallyinterrogate one by one of the tags with their code
numbers. The tags are buried vertically in the river
bed under the reader antenna coil as shown in Fig.
3(b) for the best performance. The scour will carryout the tag(s) from the vicinity of the reader antennacoil. As a result, no response will be found from thetag during the routine checkup of the reader byinterrogation one by one of the tag with theircorresponding code numbers. If a tag is not
answered during the query of the RFID reader, thetag identification number gives a direct indication of
the score position and its depth. For an improved
service, the RFID reader can be interfaced with awireless network communication system tocommunicate with the central control system, so thatmany bridge scour can be monitored simultaneously
from a single place or a monitoring room.
The coupling factor between the RFID reader
antenna and the tag antenna depends on geometricalparameters, distance and orientation of the antennas.
In this case, the inductance values, number of turnsof the coil of the tag are not involved. A simplified
representation of the coupling factor k between areader antenna coil and a tag antenna coil isrepresented by Eq. (1).

Fig.2 Bridge scour [1]Scour is a complex natural occurrence and a numberof parameters are associated with it. Hence, topredict the bridge failures and real time scour
monitoring, different types of sensors are required tomeasure the individual affecting factor [3, 4].
Among them sonar altimeter can be used to measure
the distance between sensor and river bottom [5]. Achange in distance-to-bottom is an indication ofscour. Non-contact radar water level sensor can beused to measure the water level across a wide
temperature range and varying water surface
conditions [1]. Ultrasonic water velocity sensor andside-looking acoustic Doppler current meter can beused to measure bi-directional velocity of the water.
The sensors read all the parameters including
scouring, water levels and velocity of water flow.
These sensor readings are transferred to a computer
through wire or wireless communication systems.
The reading is programmed to give an early warning
to the computer. These sensors are generally
selected and arranged based on local weather
conditions, climate change effect, natural hazards
and environmental conditions. Most of these typesensors are complex and very expensive.

k=

DEVELOPMENT OF RFID SYSTEM FORSCOUR MONITORING

R2r × R2t × cos(θ)
3�R r × R t × �R2r + d2

(1)

Here, R r and R t are the radius of the reader andtag antenna coil respectively, d is the distance
between the coils and 𝜃𝜃 is the tilt along the axis of
the coils.

Design and development of a low cost RFID
system which is related to the bridge scouring, is an
exciting matter. An RFID system consists of a tag
reader (also called the interrogator) and a passive
tag. All communication between the tag and reader
ensures completely through a wireless link which issometimes called an air interface. Through asequence of commands sent and received between

RESULT AND CONCLUSION
The PSpice simulation result of the coupling
factor is shown in Fig. 4(a). There are two bumps,
instead of having a good single peak in the294

GEOMATE- Brisbane, Nov. 19-21, 2014

frequency response. These bumps, one for the tag
antenna and the other for the reader antenna circuits
respectively. It seems as two different resonant
frequencies and which are well detached. Thisannoying effect is indeed what makes possible thedesign of an RF filter, made with cavities or helicalresonators, slightly mistuned and carefully coupled
to one another until the desired frequency response
is obtained.

there is only 3 RFID tags are left surrounding of it.
Similarly, scouring starts at pier 2 from the month ofAugust to November and lastly, there is 6 RFID tags
are left surrounding of it. Pire 4 also starts small
scouring from the month of September. It is foundthat the bridge is in threatening condition of its
existence due to huge scour with pier 1. Similarly,
pier 2 also indicates moderate threatening to thebridge. However, the others have not significant
indications to the bridge. It can be concluded thatduring the monsoon season the probability of bridge
scouring is high.
ACKNOWLEDGEMENTS
This research has been supported by the Ministryof Higher Education of Malaysia Government
through the Fundamental Research Grant Scheme
FRGS13-027-0268 entitled of the project “Analysis
and Characterization of Chipless RFID Tag forInvestigating the Scope of Uses in Malaysia”.

REFERENCES[1] Anderson NL, Ismael AM and Thitimakorn T,“Ground penetrating radar: a tool for monitoringbridge scour”, Environmental & Engineering
Geosciences, Vol. 13, No. 1, 2007, pp. 1-10.
[2] Ballio F and Radice A, “A non-touch sensor for
local scour”, Journal of Hydraulic Research,
Vol. 41, No. 1, 2003, pp. 105-108.
[3] Glaser SD, Li H, Wang ML, Ou J and Lynch T,“Sensor technology innovation for theadvancement of structural health monitoring: astrategic program of US-China research for the
next decade”, Smart Structure and System, Vol.
3, No.2, 2007, pp. 221-244.
[4] Lin YB, Lai JS, Chang KC, Chang WY, Lee FZ
and Ten YC, “Using MEMS sensors in thebridge monitoring system”, Journal of theChinese Institute of Engineering, Vol. 33, No.1,
2010, pp. 25-35.
[5] Lin YB, Chang KC, Chen CC, Wong SC, Lee
LS, Wang YK and Gu MH, “Integrating realtime bridge scouring monitoring system withmobile location-based services”, International
Journal of Automation and Smart Technology,
Vol. 1, No. 2, 2011, pp. 51-62.

(a)

(b)
Fig. 4 (a) Coupling factor between RFID reader andtag antenna coils (b) Relation between scour andnumber of RFID tags
Fig. 4(b) shows the relation between bridge scour
and an RFID tags. In this simulation 4 bridge pierswith 10 RFID tags for each pier has been considered.
From April to October is considered as the monsoon
season, the result shows that a scouring starts at pier1 from the month of April to November and finally295

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

MODELLING OF SHEAR STRENGTH PARAMATERS OF
SATURATED CLAYEY SOILS

1,2,3,4

M. Inanc Onur1, Burak Evirgen2, Ahmet Tuncan3 and Mustafa Tuncan4
Department of Civil Engineering, Faculty of Engineering, Anadolu University, Turkey

ABSTRACT
Shear strength of a soil can be defined as the maximum shear stress that can resist by the internal forces of the soil.
Shear strength must be determined to solve the soil stability problems. The shear strength parameters of the soil
are cohesion and internal friction angle. These parameters can be determined in the laboratory by the direct shear
test, triaxial test and unconfined compression test. However, laboratory tests take time and engineers want to define
these parameters easily by using software. The development of the computer technology presents abilities to model
the soil behavior in civil engineering applications. In this study, triaxial compression tests are performed onsaturated clayey soils under different confining pressures. Unconsolidated-Undrained test is chosen to identify
short term behavior. After the experimental procedure, the test is modeled by using the Plaxis program and theresults are compared. Relationship between the results are presented.
Keywords: Shear strength, Clayey soil, Triaxial compression test, Plaxis

INTRODUCTION
Defining the soil parameters is the first step of the
all designs in geotechnical engineering. Especially,shear strength must be determined for soil stability
problems. Shear strength of a soil is the maximum
resisting capacity under shear stress. Soils are gain
this capacity from the internal forces. Shear strength
is related to internal friction for coarse grained soils
and cohesion for fine grained soils, respectively. The
other factors affecting the clay soil strength can besuch as effective stress, plasticity, cementation,
moisture content, anisotropy and loading rate.
The soil strength parameters can be found byusing triaxial shear tests (consolidated-drained CD,
consolidated-undrained CU, and unconsolidatedundrained UU), direct shear test, vane shear test,
unconfined compression test in the laboratory andstandard penetration test, cone penetration test,
pressuremeter test in the site. All of these test require
maximum care and time because experimental errors
can affect the results significantly. After determining
the parameters, soil strength is calculated by using
Coulomb theory, derived in 1776 [1]. Equation (1) isgiven below and shear strength (τ) is accepted justabout shear stress on the failure plane [1].

τ f = c + σ ′ (tan φ )ShearStress

ϕ
A

2θ

c
σ3
Fig. 1O

σ1NormalStress

Mohr’s circle and failure envelope.

If the failure plane makes an angle θ with the
major principal plane, the normal stress and the shear
stress on the plane are given in Eq. (2) and (3).

σ1+σ 3 σ1−σ 3+
cos 2θ
22
σ1−σ 3τf =sin 2θ
2

=
σ

(2)
(3)

Many researchers studied shear strength of thesoils in the literature. Some of them determined theparameters by using some laboratory tests and fieldtests or developed new test methods [2], [3], [4], [5].
Some researchers used numerical and statisticalmethods for modelling the soil strength [6], [7], [8],[9].
Nowadays, shear strength problems are solved byusing software to save time. The soil behavior can bemodeled by softwares using finite element or finite(1)

where; c is cohesion ϕ is angle of internal friction andσ' is effective stress.
Mohr-Coulomb failure criteria is used to definesoil stress concept. Stress conditions at failure in asoil mass is given in Fig. 1.

296

GEOMATE- Brisbane, Nov. 19-21, 2014

differences methods. Thus, soil stability problems
such as bearing capacity, slope failure etc. can beeasily solved. In this study, triaxial compression tests
are performed on saturated clayey soils under
different confining pressures. UnconsolidatedUndrained (UU) test is chosen to identify short term
behavior of clayey soil. After the experimental
procedure, the test is modeled by using the Plaxis
program and the results are compared. Relationshipbetween the results are presented.

The reconstituted samples have 70 mm indiameter and 140 mm in length. In this study samples
were prepared by compacting with optimum moisture
content. Unconsolidated-Undrained triaxial test is
performed on the compacted samples. The test
procedures were designed according to the ASTM
D2850. A test sample is given in Fig. 3.

MODELLING AND METHODSIn this study; Plaxis 2D performed to determine
soil behavior. Plaxis is a commercially available
program which is using finite element method andcommonly used in civil engineering applications [10].
Example screen of the Plaxis menu is given in Fig. 2.

Fig. 3A test sample.

The confining pressures are chosen 10, 20 and 30
psi and the deviator stress are applied to the failure.
Shear stress parameters are found by drawing the
Mohr’s circles. Detailed information is given in Table
2. Mohr’s circles are also given in Fig. 4.
Table 2 Test Details

Fig. 2

SampleConfining
StressDeviatorStressPrincipal
StressMax.
StrainCohesion
Friction
angle

Example screen of the Plaxis menu.

Experimental Procedure
Test soil is taken from a construction site in thecity of Eskisehir, Turkey. After boring, soil index
properties determined such as moisture content,
atterberg limits, specific gravity, sieve analysis, andhydrometer. Standard proctor tests are also performedon the samples. Basic characteristics of the soil are
given in Table 1.
Table 1 Basic characteristics of test soilUSCS
ω n (%)
ω L (%)
ω P (%)
ω opt (%)
Gs
Gravel (%)
Sand (%)
Silt (%)
Clay (%)

MH-OH
30,20
85,00
20,00
49,00
2,52
0,32
12,50
64,18
23,00

Fig. 4
297

A

B

C

10,0 psi

20,0 psi

30,0 psi

20,4 psi

28,7 psi

35,7 psi

30,4 psi

48,7 psi

65,7 psi

6,0 %
4,99 psi

8,0 %
4,99 psi

9,0 %
4,99 psi

160

160

160

Mohr’s circles of the test samples.

GEOMATE- Brisbane, Nov. 19-21, 2014

Modelling Procedure

RESULTS

Plaxis is using different soil models to define soil
behavior such as Mohr-Coulomb Model, Hardening
Soil Model, Soft Soil Model, Soft Soil Creep Model,
Jointed Rock Model and Modified Cam-Clay Model.
Mohr-Coulomb Model is chosen for this study.
Because it is commonly used and not required extra
soil parameters. The behavior is linearly elastic andperfectly plastic in this model that needs Young’s
Modulus, Poissons Ratio, and cohesion, internal
friction angle and angle of dilatancy [10].

Plaxis models are performed and strains arecalculated. Maximum strains are compared with thetriaxial test results. The comparisons of the maximum
strains are given in Table 4.
Table 4 Strain Values
SampleMax. Strain(Triaxial
Test)
Max. Strain(PlaxisModel)

A

B

C

6,0 %

8,0 %

9,0 %

5,9 %

8,1 %

9,1 %

The results shows approximately similar values
despite the lack of three dimensional analyses. MohrCoulomb model is known as conservative model andgives safe results. In this study Mohr-Coulomb model
simulate the results safely. Strain value in the Plaxis
is a bit less in the first model but it is negligible.
CONCLUSION

Fig. 5In this paper, the comparison between thelaboratory tests and computer modelling arepresented. Unconsolidated-Undrained triaxial test is
performed in the experimental analyses and Plaxis 2D
is performed to simulate these test results. The strain
results under the loading and modelling are presented.
Based on the results, the following conclusions can be
drawn:−The study shows similar results as theliterature.
−
Mohr-Coulomb model shows approximately
similar values as laboratory tests, and gives
safe results.
−
If more sensitive results are desired 3D
analysis should be done with considering thethird dimensional confining effect.
−
Presented values can be used in geotechnicalapplications.

Model screen.

Plaxis modelling is prepared with consideringboundary conditions, loading and soil properties.
Modulus of elasticity is calculated from the initialpart of stress-strain graphs of the samples. Confiningpressures are applied as the triaxial test at top and twosides. Three dimensional effect is ignored because of
the 2D analysis. Deviator stress are applied at the top
and the deformations are determined. Model details
are given in Table 3.
Table 3 Model Details
SampleSoil
Model
Cohesion
Friction
angle
Young
Modulus
Dilatancy
angle
Poissons
Ratio

A
MohrCoulomb
4,99 psi

B
MohrCoulomb
4,99 psiC
MohrCoulomb
4,99 psi

160

160

160

2875
kN/m2

2875
kN/m2

2875
kN/m2

0
0,3

0
0,3

0
0,3

REFERENCES[1] Das BM., Principles of GeotechnicalEngineering, Pws-Kent Publishing Co., 1990, ch
8.
[2] Alikonis A., Amšiejus J., Stragys V.,“Improvement of shear box apparatus andmethodology of test”, in Proc. Soil Mechanics
and Geotechnical Engineering, The 12th
European Conference, 1999, pp. 1053–1057.
[3] Guo P., “Modified Direct Shear Test for
Anisotropic Strength of Sand”, Journal of298

GEOMATE- Brisbane, Nov. 19-21, 2014

Geotechnical & Geoenvironmental Engineering,
vol. 134(9), 2008, pp. 1311–1318.
[4] Matsuoka H., Liu SH., Sun DA., “A new in-situ
direct shear testing method for rockfill materials
sands and clays”, in Proc. Proc of the 15th
International Conference on Soil Mechanics andGeotechnical Engineering, 2001, pp. 455–458.
[5] Vervečkaitė N., Amšiejus J., Stragys V., “Stress–
strain analysis in the soil sample duringlaboratory testing”, Journal of Civil Engineeringand Management, vol. 13(1), 2007, pp. 63–70.
[6] Amšiejus J., Dirgėlienė N., “Probabilistic
assessment of soil shear strength parameters
using triaxial test results”, The Baltic Journal ofRoad and Bridge Engineering, vol. 2(3), 2007,
pp. 125–131.Author H, A Book. New York:
Publisher, Yr, ch. 3.

[7] Dounias GT., Potts DM., “Numerical analysis ofdrained direct and simple shear tests”, Journal of
Geotechnical Engineering, vol. 119(12), 1993,
pp. 1870–1891.
[8] Jacobson DE., Valdes JR., Evans TM., “Anumerical view into direct shear specimen size
effects”, Geotechnical Testing Journal, vol.
30(6), 2007, pp. 512–516.
[9] Zhang L., Thornton C., “A numericalexamination of the direct shear test”,
Geotechnique, vol. 57(4), 2007, pp. 343–354.
[10] Brinkgreve, R.B, Vermeer, P.A. Plaxis Ver. 7.2
Manual Finite Element Code for Soil And RockAnalyses, Balkema, 1998.
[11] ASTM D2850 Standard Test Method for
Unconsolidated-Undrained
Triaxial
Compression Test on Cohesive Soils

299

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

DETERMINATION OF THE FREEZING EFFECT ON UNCONFINEDCOMPRESSION STRENGTH AND PERMEABILITY OF SATURATEDGRANULAR SOILS
Burak Evirgen1, M. Inanc Onur1, Mustafa Tuncan1 and Ahmet Tuncan1
Department of Civil Engineering, Faculty of Engineering, Anadolu University, Turkey

1

ABSTRACTArtificial ground freezing usage gradually rises in civil engineering applications as a soil supporting system.
However, many unknown fundamental parameters have been still waiting discovery, especially for granular soil.
Granular soil can not carry its own weight during unconfined conditions. If water turns to ice that locates in thesoil pores, it proceeds as a cementitious material. First step of design phenomena is to identify the material
properties in geotechnical engineering. Within this scope, unconfined compression tests (UCC) and permeability
tests are performed on frozen granular soils subjected to 1, 3 and 7 day-freezing periods to observe time effect.
Experimental procedure are applied totally on 12 sand and gravel type of specimens with saturated cases after
freezing application in the CDF/CIF freezing thawing machine. Stress - strain behaviors, ultimate load capacities
and permeability of specimens are determined. This method will be used while taking undisturbed granular soil
samples from the construction site.
Keywords: Artificial Ground Freezing, Granular Soils, Unconfined Compression Test, Permeability

useful undisturbed sampling method without any
modified cooling cell is purposed within this study.
Reference [1] presents that mechanical propertiesof frozen soil depends directly on water content. On
the other hand, it is inversely proportional with theincrease of consolidation pressure and sand content
according to experimental results. Reconstituted soil
samples that consist of silty - clay (inorganic clay of
medium plastic) and sand (grain size ranged between
0.42 and 0.074 mm) mixtures were used during thesetests. Sand content changes between 0, 10, 20, 30 and
50% of the total weight of solid material. Cylindrical
specimens have 3.5 cm in diameter and 7 cm in height
were used after subjected to 25, 50, 200 and 400 kPa
consolidation pressures. Specimens were placed in
the freezing chamber having a -14 ºC temperature for24 hours freezing period. Reference [2] gives that the
specimens were prepared at higher dry density having
more uniaxial compression strength than lower onesat the same strain rate and temperature for saturated
frozen soils as a result of cohesion according to resultof given equation in the paper. Remolded silty
samples are used. Maximum (1.111) and minimum(0.503) void ratios were kept at constant temperaturein freezing cabinet. They preferred the Eq. (1) as afunction of strain - temperature according toinvestigations on the saturated frozen silty soil withdifferent parameter ranges between -2 to -15 ºC and1.10-6 to 7.10-4 s-1, temperature and strain values,
respectively.

INTRODUCTION
Soil supporting system is an essential component
for geotechnical engineering in many soil projects.
Undergoing applications are such as laterally loaded
piles, retaining walls and sheet piles, braced cuts fordeep excavations and NATM or classic tunnel boring
methods for tunnel constructions. All of them require
dewatering if ground water table creates a risk in thesite. Artificial ground freezing (AGF) presents easy,
safety, eco-friendly and economical (without initialcost of machines) solution and dewatering as well.
Many researchers have studied artificial groundfreezing and its effects on the soil properties.
However, limited study have been found in theliterature about fundamental mechanical properties
such as unconfined compression strength andpermeability of saturated frozen granular soils undernormal conditions. Unconfined compression test
application on the unfrozen granular samples are
impossible having to avoid the dispersion of solid
particles along the lateral direction according towithout confining pressure around the soil media.
However, triaxial test can be applied to the granularsamples after difficult sample preparation with using
vacuum and gradually pressure increment as a cellpressure. Another methods of UCC tests and triaxial
tests have been performed inside the modified coldstate cells that regulates the environmental
temperature at constant value according toundergoing studies. But, proposed approach involves
the basic UCC test while room temperature effects tofrozen specimens. Evaluation the results of easy andσ f = σ o' (θ θ 0 ) i (ε ε0 ) m
300

(1)

GEOMATE- Brisbane, Nov. 19-21, 2014

Where; θ 0 is reference temperature, θ is negative
temperature, σ f is axial compression strength, έ isstrain rate, έ 0 is reference strain rate and m is theparameter changes due to dry density and temperatureof samples. Reference [3] shows that ductile
deformation type occurred at low water content inpartially frozen soils. On the other hand, brittle typeof failure was seen on frozen soils that have highwater content. Residual compressive strength offrozen soils are independent of their dry unit weightat a particular temperature. However, it increases withdecreasing temperature according to peak.
Compressive strength observation was studied onsaturated fine grained frozen samples with respect tothe water content, dry unit weight and temperatureparameters. Reference [4] indicates that some of thefollowing practical advantages and disadvantages
within the compressive strength observation underthe effect of strain rate for both confined (-6 ºC to -10ºC) and unconfined cases (-2 ºC to -15 ºC) ofartificially frozen sand samples. Perfectly end platen
preparation are not necessary for frozen soils. Softplaten material can eliminate the minor irregularities
after freezing. Relatively short frozen cylindricalshaped samples can be used during strength
determination after core drilling from construction
site. Compatible platen usage reduces the stiffness ofthe test system and makes difficult to control test
parameters.
In the AGF phenomena, free water that moves inthe soil voids turns to ice as a cementitious material.
So, concrete like material is obtained easily. But,
many factors affect the artificial ground freezing
applications in the site. For example, freezing
duration, amount of given energy, used machine
capacity, location of construction site as a function of
weather temperature, construction period, coolingliquid and sizes of circulation pipes. In this study,
effect of soil type and freezing duration on theuniaxial bearing capacity and permeability ofsaturated frozen granular soils were studied.

Fig. 1

Grain size distribution curve for samples

Table 1 Soil properties
Soil
Specific Gravity
Gravel (%)
Sand (%)
Silt & Clay (%)
D 10
D 30
D 60
Cu
Cc
Void ratio (e)Type of Soil

I
2.54
94.60
5.20
0.80
9.10
11.00
15.00
1.65
0.89
0.94
GP

II
2.58
1.30
98.30
0.40
0.30
0.62
1.60
5.33
0.80
0.54
SP

Permeability is used to understand the water flow
in soil media. This physical property affects thebearing capacity, settlement, shear strength andliquefaction potential of construction area. Proper
dewatering process requires if ground water flow
exists. Capacity of discharge increments also makes
the removing of water difficult. In this case, AGF
presents the useful dewatering technique eveneliminating the seepage. Table 2 gives the common
coefficient of permeability values [5].
Table 2 Coefficient of permeability values [5]MATERIAL PROPERTIES

Soil Type
Clean Gravel
Coarse Sand
Fine Sand
Silty
Clay

Gravel and sand type of soil materials were usedduring experiments. First of all, fundamental
geotechnical tests were performed. Figure 1 shows
the grain size distribution curve as a result of sieve
analysis. Physical properties of soil samples represent
the common values of poorly graded granularmaterials as shown in Table 1.

k (cm/sec)
1.0 - 100.0
1.0 - 0.01
0.01 - 0.001
0.001 - 0.00001
Less than 0.000001

EXPERIMENTAL PROCEDURE
Cylindrical specimens, 70 mm in diameter and
130 mm in height, were used. Six specimens wereselected for unconfined compression tests and theothers were used for permeability tests as shown in
Fig. 2. Solid particles were placed without any
compaction energy by using gravitational energy.

301

GEOMATE- Brisbane, Nov. 19-21, 2014

Then, freezing process was applied after saturation.
First, unfrozen specimens were kept at -10 ºC during
1 day before the tests as pre-freezing period. Then,
specimens were removed from molds with hydraulicmachine.

Fig. 4

Fig. 2

CDF/CIF freezing thawing machine

Six samples were subjected to axial compression
force with 1.0 mm/min loading rate to perform theunconfined compression test. Load rate was selected
higher than normal value within the scope of
eliminating the quick thawing process. Plexiglas wereused at the top and at the bottom caps at -15 ºC. Stressand strain values were collected with using Utest dataacquisition system as shown in Fig. 5. Other six
samples were used to perform permeability tests.
Constant head permeability tests were performed at
300 mm constant head. Amount of water wascollected simultaneously during 30 minutes for eachspecimen as shown in Fig. 6. Coefficient of
permeability values are calculated according to thesevalues.

Unfrozen gravel and sand specimens

Freezing of soil particles with lateraldisplacement under anisotropic and known principle
stress is expected situation during both natural andartificial freezing process. However, freezing
experiments are generally realized with eliminating
displacement by using molds in the laboratory [6].
Accordingly, frozen specimens show volumetric
expansion along the longitudinal direction from the
top surface. Surface was levelled with spiral grinding
machine as shown in Fig. 3.

Fig. 5 Unconfined compression test device withdata acquisition system

Fig. 3

Surface levelling of expanded part

The prepared specimens were kept at constanttemperature as -15 ºC in a CDF / CIF freezing
thawing machine during 1, 3 and 7 days as shown in
Fig. 4. In spite of the apparent abundance of publishedexperimental data on frozen soil behavior, somequestions has not been answered, yet [6]. Some ofthem are such as unconfined compression strengthand permeability change according to under thawing
effect at room temperature after short term freezing
periods.

Fig. 6302

Permeability test device

GEOMATE- Brisbane, Nov. 19-21, 2014

RESULTS
Soil is known as heterogeneous material thatconsists of solid particles, air and water. So,
unexpected stress and deformation behavior canoccur inside the soil phases. Arrangement of particles
is less important for frozen soil according tocementitious ice formations. Fine grained soil has
more stress and strain capacity than coarse grained
soil according to the results of unconfinedcompression tests as shown in Fig. 7. Unconfinedcompression strength values of poorly graded gravel
specimens are determined as 1.64, 2.92 and 3.49 MPa
for 1 day, 3 days and 7 days freezing periods,
respectively. On the other hand, strength values are
obtained as 2.94, 3.04 and 5.13 MPa during same
periods for poorly graded sand specimens.
Compressive strength of frozen samples increases
with increasing time up to 7 days. Strain rates areapproximately similar for sandy specimens. However,
it is inversely proportional with increment of freezing
period for gravel type of soils. Curves of both 3 days
specimens and 1 day specimen of sandy soil aresimilar. Lower strength and higher strain values of 1
day gravel sample rises from partially freezing ofsolid particles and ice lenses.
All of the frozen specimens are started to thaw
around 5 minutes as a result of constant head
permeability tests on the frozen samples. If thefreezing time increases, permeability of frozen sandy
specimen decreases. However, coefficient of
permeability value is inversely proportional withfreezing time, unexpectedly. Coefficient of
permeability of granular sample is about 5 times
greater than the other one. Permeability test results ofthe samples are shown in Fig. 8.

Fig. 8 Change in coefficient of permeability forfrozen granular specimens, a. Poorly graded gravel, b.
Poorly graded sandObserved failure modes at the end of thecompression tests are completely different for graveland sand type of samples. Vertical cracks are
occurred on the frozen gravel surfaces as shown in
Fig. 9a. On the other hand, horizontal cracks areformed on the sand type of specimens as shown in Fig.
9b. All of the failure models are similar to concrete
type of brittle material rather than soil like material.
However, finer graded frozen soil material has moreductility than the coarser one.

Fig. 7 Stress - strain behavior of frozen granularspecimens, a. Poorly graded gravel, b. Poorly gradedsandFig. 9 Failure mode and observed cracks on thesamples a. gravel sample, b. sandy sample
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GEOMATE- Brisbane, Nov. 19-21, 2014

Bursting behavior can occur on the frozen
samples under very fast or slow loading rate [5]. If
loading rate is too slow, ice turns to water - ice
mixtures. If loading rate is too fast, frozen soil sample
easily disperse due to the lack of cohesion or any finermaterial. Bursting phenomena was observed on thetrial specimen under fast loading rate with using
concrete compressive test machine as shown in Fig.
10.

REFERENCES[1] Anagnostopoulos CA, Grammatikopoulos I,“The Effect of Freezing on the Strength of SiltyClay-Sand Mixtures”, Electronic Journal of
Geotechnical Engineering, Vol. 10, 2005, bundle
G.
[2] Li HP, Zhu YL, Pan WD, “Uniaxial Compressive
Strength of Saturated Frozen Silt”, 8thInternational Conference on Permafrost, 2003,
pp. 679-684.
[3] Joshi RC, Wijeweera H, “Post Peak Axial
Compressive Strength and Deformation
Behavior of Fine-Grained Frozen Soils”, in Proc.
Proceedings of the Fifth Canadian Permafrost
Conference, 1990, pp. 317-325.
[4] Baker THW, Jones SJ, Parameswaran VR,“Confined and Unconfined Compression Tests
on Frozen Sands”, Proceedings Fourth Canadian
Permafrost Conference, 1981, pp. 387-393.
[5] Das BM, Principles of Geotechnical Engineering,
Boston: Pws-Kent, 1990, ch. 4.
[6] Ono T, “Lateral Deformation of Freezing Clay
Under Triaxial Stress Condition Using LaserMeasuring Device”, Cold Regions Science andTechnology, Vol. 35, 2002, pp. 45-54.
[7] Ladanyi B, “An Engineering Theory of Creep ofFrozen Soils”, Canadian Geotechnical Journal,
Vol. 9, February 1972, pp. 63-80.

CONCLUSION
In this study, experimental analyses of twelve
saturated frozen granular samples are examined with
1 day, 3 days and 7 days freezing time effect. Thechange in unconfined compression strength andcoefficient of permeability values are presented.
Based on the results, the following conclusions may
be drawn:
Both brittle and ductile deformations and different
strain values can be observed under same loading
conditions according to the degree of water freezingin the pores or amount of fine material. Strength anddeformation varies by the using area of the artificial
ground freezing in the geotechnical projects.
Compressive strength of frozen samples increases
with increasing time up to 7 days. Strain rates areapproximately similar for sandy specimens. However,
it is inversely proportional with increasing freezingtime for gravel type of soils.

Fig. 10 Bursting formation under fast loading rate
All of the frozen specimens are started thawing
around 5 minutes. If the freezing time increases,
permeability of frozen sandy specimens decreases.
However, coefficient of permeability value isinversely proportional with freezing time,
unexpectedly. Coefficient of permeability for
granular sample is about 5 times greater than the otherone.
Presented values can be used for modelling of
geotechnical projects both using finite element
software and theoretical calculations as well.
304

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

QUANTITATIVE ASSESSMENT OF HUMAN RISKS POSED BY MINEDEBRIS FLOW

1

Shuai Zhang1, Limin Zhang2
Department of Civil and Environmental Engineering, The Hong Kong University of Science andTechnology, Clear Water Bay, Hong Kong

2

Department of Civil and Environmental Engineering, The Hong Kong University of Science andTechnology, Clear Water Bay, Hong Kong
ABSTRACT

Prolonged rainstorms had triggered several large-scale debris flows along Provincial Road 303 near the
epicenter of the 2008 Wenchuan earthquake. A lot of concrete-aggregate plants distributed along this road wereburied by the runout debris, leading to a large number of fatalities. A Quantitative Risk Assessment (QRA)
methodology is being developed for debris flows induced by various rainfall scenarios. QRA for these debris flow
hazards is of significance to determine the probability distribution, consequence and human risk profile arisingfrom these disasters. With the aid of Geographic Information System (GIS) platform, a potential channelized debris
flow catchment in the study area is identified based on remote sensing images and field study. Rainfall intensityduration thresholds for the local channelized debris flows are used to determine the occurrence probability under
six rainfall scenarios for the purpose of hazard analysis. Subsequently, human losses of debris flow are assessedby considering the variations of rainfall events, and the final human risks can be obtained using a general risk
model. Finally, the societal human risks are obtained, which provide a benchmark for studying the long-term
human risks of these potential debris flows and engineering decision in the perspective of mining manufacture.
Keywords: Debris Flow, Quantitative Assessment, Human Risk

INTRODUCTIONSTUDY AREA

Debris flows are among the most frequent mass
movement processes in mountainous areas (Kang etal. 2004; Jakob and Hungr 2005), and are attributed
to an adequate supply of loose materials, surface
runoff, and steep drainage channels (Takahashi 1981).
The 12 May 2008 Wenchuan earthquake in China
triggered about 197,481 landslides (Xu et al. 2013).
Numerous loose landslide deposits were retained on
steep hill-slopes or in channels. Such deposits are ina quasi-stable state in the dry season but can provide
source materials for debris flows in the wet season(Tang et al. 2011; Zhang et al. 2012; Zhang et al.
2013; Zhang et al. 2014). In the past four years, threelarge-scale debris flows occurred in the Pubugou
Ravine near the epicentre of the Wenchuan
earthquake on 24 June 2008, 14 August 2010 and 4
July 2011. Approximately 1.76 million m3 of
sediment was deposited during these three events. It
is expected that debris flows will continue to occur inthe coming years. Therefore, it is important toevaluate the risks of debris flows so that the potential
loss of lives can be reduced in the future.
This research aims to develop a method to obtain
the risk profile of mine debris flows along PR303 inYingxiu area, and to conduct a case study on Pubugou
debris flow to illustrate the methodology.

The Pubugou Ravine is approximately 3.5 km
from the epicentre of the Wenchuan earthquake,
Yingxiu, in Sichuan Province, China (Fig. 1). The
ravine is characterized by rugged mountains anddeeply incised valleys. It has an area of 3.06 km2 andelevations ranging between 1,100 m and 3,200 m. As
shown in Fig. 1, the ravine consists of two sub-basins,
namely the Xiezi Gully and the Wuming Gully. The
Xiezi Gully extends 2288 m from the gully mouth tothe topmost of the stream, having a local relief of1580 m and a mean channel gradient of 28°. The
Wuming Gully ranges from 1100 m to 1920 m, witha channel length of 977 m and a mean channel
gradient of 27°.
The exposed lithology within the study area ismainly composed of four kinds of Proterozoic
magmatic rocks; namely, diorite, biotitic granite,
granodiorite and hornblende diorite. The maximum
and mean annual precipitations within the study area
are 1225 mm and 828 mm, respectively.
Approximately 68% of the total precipitation falls
between June and September. Zhang et al. (2012) and
Chen et al. (2012) reported field investigations andnumerical analysis of the landslide and debris-flowhazards in the study area.

305

GEOMATE- Brisbane, Nov. 19-21, 2014

R = p f × E ×V

(1)

where p f = occurrence probability of debris flow; E =element at risk; V = vulnerability related to the runout distance of the debris.

Xiezi Gully

Wuming
Gully

Fig. 1 Location of the study area

HAZARDS IDENTIFICATION

Concrete aggregate plantFig. 2 - Distribution of the source materials within
Pubugou Ravine

During the Wenchuan earthquake, large-scalerock avalanches and landslides took place. A large
amount of colluvium was retained on the hill slopes
or deposited in the channels (Table 1 and Fig. 2). The
landslide scars and the deposition zones together
cover more than 50% of the terrain (Fig. 2). The
volume of the deposited materials in the Pubugou
Ravine was approximately 5.6 million m3 (Table 2).
After the Wenchuan earthquake, the hill-slope
deposits are at a quasi-stable state under normal
weather conditions. Upon a storm event during therainy season, some of these deposits reactivate, slide
down the slope and evolve into channel deposits.
Some of the hill-slope materials may also evolve intohill-slope debris flows due to either post-sliding soil
movements or bed erosion. The materials in thechannels, no matter how far away from the highway,
may gradually move to the gully mouth along thechannel, which eventually run out as a channelized
debris flow under rainstorm conditions. Several
concrete-aggregate plants distributed near the gully
mouth were buried by the runout debris, leading to alarge number of fatalities (Fig. 3).

Determination of occurrence probability
Rainfall is an essential predictor for the debris
flow. It is well known that the correlation between therainfall and the debris flow is the most widely usedmethod to predict the occurrence of debris flow.
Some precious rainfall-induced debris flow data had
been collected, a statistical model (rainfall intensity –duration threshold model) is adopted to calculate theoccurrence probability.
Logistic regression method is a useful tool for
analyzing binary systems. The basic idea to predictthe debris flow occurrence probability with logistic
regression is to link the observed rainfall intensity andduration, i.e., the debris flow will either occurred or
not occurred. The logistic regression model for debris
flow prediction can be written based on Eq. (2) as
follows
1Pf =1 + exp{− (b0 + b1 ln I + b2 ln D)}(2)

ASSESSMENT OF HUMAN RISK POSED BY
MINE DEBRIS FLOW IN PUBUGOU RAVINE

where b0, b1, and b2 are unknown coefficientsthat can be calibrated using the maximum likelihood
method. Based on the post-earthquake data including
27 occurred and 36 non-occurred debris flow cases,
values for b 0 , b 1 , b 2 are -7.776, 1.651, and 2.143,
respectively.
According to the rainfall threshold model, thedebris flow occurrence probability under the six
rainfall conditions is obtained (Table 2). The
empirical relations are statistically valid and provide
threshold rainfalls for issuing warning signals.

Assessment model
In this section, the risk of debris flow in the
Pubugou valley is assessed in terms of the potential
loss of lives. The element at risk is taken as thepassengers traveling on the road who may be buriedby the runout debris should a debris flow event occur.
The risk, R, is quantified by306

GEOMATE- Brisbane, Nov. 19-21, 2014

Landslide runout distance

Element at risk during normal operation of theroad

The runout distance of a debris flow is the basis
for estimating the element at risk and vulnerability of
the landslide (as shown in Fig. 4). When a detailed
study is not expected, the runout distance can be
estimated using empirical relations. Here the relation
proposed by Zhang et al. (2013) is adopted:

The number of people, E, that can be buried
depend on the traffic flow and the length of the roads
that is buried by debris flows. Assuming a constanttraffic flow over the road segment concerned, E may
be expressed

L f = 2.04V 0.18 H 0.1e aE=(3)where Lf is the predicted runout distance (m); V
is the volume of debris flow (m3); H is the elevationdifference of the mass movement (m); ea is a discretevariable, which is expressed using a virtual discretevariable that represents either presence or absence ofan attribute; e the natural logarithm base; a is 2.90
(Zhang et al. 2013).

WTn
v

(4)
where T = vehicles passing through the road per
second; W = the length of road that is buried by thecollapse of one or several deposits; v = averagevehicle speed; n = average number of passengers in
one vehicle.
According to the Grade-2 highways design
requirements specified for PR303, The value of T is
1/6 vehicles per second and the design vehicle speed
is 40 km/h at difficult parts of the road. The numberof persons in a vehicle is 2.35, which is obtained
during filed statistic analysis.
0.20

Potential loss of life

Tourist houses
0.15

0.10

0.05

0.00
0

Fig. 3 Runout debris destroyed the concrete
aggregate plant near the gully mouth of Pubugou
Ravine, and buried the roadath

Ru
Travel distance, L

250

In the study area, the width of the road is 8 m. As
shown in Figs. 3 and 4, all the runout material that
may run over the road, the calculated runout distanceis 104 m. That means that all the debris will bury theroad completely. Therefore, it is reasonable to assume
that the vulnerability factor, V, is 1.0; i.e., thepassengers will be buried once a landslide runs overthe passengers (Finlay et al. 1999).

rea

wp

200

Vulnerability

urc

Flo

150

Fig. 5 Relationship between 12 hour rainfall andpotential loss of life caused by channelized debris
flows in Pubugou RavineeaElevationdifference,
H

100

Rainfall intensity (mm/12 h)Once the runout distance of debris flow isdetermined, the probability of runout debris reaching
the element at risks (P Lf ) can be quantified byapplying Monte Carlo simulation, considering theuncertainties of the volume of debris flow (Table 2).
So

50

D
zo epos
ne iti
on
no
ut
dis
L tan
f
ce
,

Risk to human lives
Given the probability of occurrence, element at
risk and vulnerability of debris flow, the human risk
can be calculated using Eq. (1). The risk is measured

Fig. 4 Parameters related to runout distance ofchannelized debris flow
307

GEOMATE- Brisbane, Nov. 19-21, 2014in terms of the potential casualty that could be causedby the debris flow.

The impact of the debris flow on the traffic andconcrete aggregate plant is significant, potentiallyinvolving over 10 casualties in a single slide event.
To mitigate the risk, a warning system should beestablished to reduce the elements at risk when astorm occurs.

Table 1 Volumes of loose materials deposited inchannels and hill-slopes

0.64
3.63
0.03
0.60
36

0.23
1.31
0.003
0.06
13

1.00E+00
240mm/12h

70mm/12h

The debris flow occurs within a short period sothat all veicles within the landslide area may beburied. In reality, once a debris flow occurred and theroad is blocked by the first occurrence of landslide,the rest vehicles may attempt to escape from further
landslides.
Table 2 Human risk of debris flow under different
rainfall scenarios
Rainfall(mm/12 h)
Pf
P Lf
E
V
R

240

140

70

30

0.99
0.96
11.75
1
0.145

0.77
0.74
9.47
1
0.192

0.12
0.23
7.18
1
0.053

0.00150.00065.12
10140mm/12h

1.00E-01

30mm/12h

1.00E-02

1.00E-03

Unacceptable

1.00E-04

1.00E-05
ALARP
1.00E-06

1.00E-07

IntenseScrutiny
RegionChanneldeposits

Number of loose
deposits
Total area (km2)
Volume (106 m3)
Total area (km2)
Volume (106 m3)
Mean width (m)WumingGully
12Frequency of N of more fatalities per year

Hillslope
deposits

Xiezi
Gully
22

Broadly
Acceptable

1.00E-08
1

10

100

1000

10000

Number of fatalities, N

Fig. 6 F-N curves for debris flow in Pubugou
Ravine after the Wenchuan earthquake in six rainfall
scenarios

The risks at different rainfall scenarios are
summarized in Table 2. The most serious human risk
posed by the debris flow is 0.19 under the 140 mm/12
h rainfall condition followed by 0.15 under the 240
mm/12 h rainfall condition. The societal risk can also
be graphically presented in the form of potential lossof life (PLL) (Fig. 5). The increment of risk is not
significant when the rainfall intensity increases from
5 mm/12 h to 30 mm/12 h rain. However, the riskincreases substantially when subject to a rain severer
than 70 mm/12 h.
The societal risks of the debris flow under the six
rainfall conditions can also be presented in an F-N
curve in Fig. 6. One of the advantages of an F-N curveis that it provides additional information on the fullrange of credible fatal scenarios and thecorresponding likelihood of occurrence (Wong et al.
1997). The societal risk acceptance criteria proposed
by GEO (1998) are adopted in this paper as abenchmark, which is suitable for a study area with areference toe length of 500 m or smaller. As shown in
Fig. 6, the societal risks of the different rainfall
scenarios are mainly located in the unacceptableregion.

CONCLUSIONSThe loose deposits formed during the 2008 Wenchuan
earthquake on the steep terrains in the Pubugou valley
near the epicenter are identified in a GIS platform.
These deposits have very high probabilities of failure
when subject to a storm and involve into a deadly
debris flow. The risks to passengers on the road arealso evaluated. Upon failure, the runout debris ofdebris flow in Pubugou Ravine could run out andbeyond the road. Such debris flow could cause over
10 casualties in a single event under normal traffic
flow conditions. The human risk under the conditionsof 140 mm/12 h is higher than those under the otherrain scenarios. Under the extreme rainfall conditionof 240 mm/12 h, the failure probability is high and theconsequence is very serious. However, the annual
frequency is small; hence the final risk reflected in the
F-N curve is not the worst. Such risk level is nottolerable; hence risk mitigation measures must be
taken and an effective warning system established toreduce the risk level.
308

GEOMATE- Brisbane, Nov. 19-21, 2014[12] Zhang, S., Zhang, L.M., and Thomas, G. 2014.
Characteristics of Earthquake- and Rain-induced
Landslides near the Epicenter of Wenchuan
Earthquake. Engineering Geology, accepted.

ACKNOWLEDGMENTS
The work in this paper was supported by Sichuan
Provincial Department of Transportation andCommunications and the Research Grants Council ofthe Hong Kong SAR (Project No. 622210).
REFERENCES[1] Chen, H.X., Zhang, L.M., Chang, D.S., andZhang, S., 2012. Mechanisms and runout
characteristics of the rainfall-triggered debris
flow in Xiaojiagou in Sichuan Province, China.
Natural Hazards, 62, 1037–1057.
[2] Finaly, P. J., Mostyn, G. R., and Fell, R. 1999.
Landslide risk assessment: prediction of travel
distance, Can. Geotech. J., 36, 556–562.
[3] Geotechnical Engineering Office (GEO), 1998.
Landslides and boulder falls from natural
terrain: interim risk guidelines. GEO Report No.
75, Geotechnical Engineering Office, Hong
Kong, 183 pp.
[4] Jakob, M., and Hungr, O. 2005. Introduction ofdebris flow. In Debris-flow Hazards and Related
Phenomena. Edited by M. Jakob and O. Hungr.
Springer, Berlin, pp. 1-7.
[5] Kang, Z.C., Lee, C.F., Ma, A.N, and Law, K.T.
2004. China Debris Flow Studies. Science Press,
Beijing.
[6] Takahashi, T. 1981. Estimation of potential
debris flows and their hazardous zones. Journalof Natural Disaster Science, 3: 57-89.
[7] Tang, C., Zhu, J., and Qi, X. 2011. Landslide
hazard assessment of the 2008 Wenchuan
earthquake: a case study in Beichuan area.
Canadian Geotechnical Journal, 48: 128-145.
[8] Wong, H. N., Ho, K. K. S, and Chan, Y. C. 1997.
Assessment of consequence of landslides, in:Landslide risk assessment-Proceedings of theWorkshop on Landslide Risk Assessment,
Honolulu, Hawaii, USA, 19-21 February 1997,
edited by: Cruden, D.M., and Fell, R., Balkema,
Rotterdam, 111-149.
[9] Xu, C., Xu, X.W., Yao, X., and Dai, F.C. 2013.
Three (nearly) complete inventories oflandslides triggered by the May 12, 2008
Wenchuan Mw 7.9 earthquake of China andtheir spatial distribution statistical analysis.
Landslides, doi: 10.1007/s10346-013-0404-6.
[10] Zhang, S., Zhang, L.M., Peng, M., Zhang, L.L.,
Zhao, H.F., and Chen, H.X. 2012. Assessment ofrisks of loose landslide deposits formed by the2008 Wenchuan earthquake. Natural Hazards
and Earth System Sciences, 12: 1381-1392.
[11] Zhang, S., Zhang, L.M., Chen, H.X., Yuan, Q.,
and Pan, H. 2013. Changes in runout distancesof debris flows over time in the Wenchuan
earthquake zone. Journal of Mountain Science10, 281–292.

309

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

A STUDY OF DYNAMIC SOIL STRUCTURE INTERACTION FOR
PILED RAFT FOUNDATION WITH VARIABLE SUB SOILS
Shukla S.J1, Desai A.K.2 and Solanki C.H.3
1

Assistant Professor, Applied Mechanics Department, Sardar Vallabh Bhai National Institute of Technology, Surat, Gujarat,
India E-mail: sdv@amd.svnit.ac.in

2

Professor, Applied Mechanics Department, Sardar Vallabh Bhai National Institute of Technology, Surat, Gujarat, India,
E-mail: akd@amd.svnit.ac.in

3 Professor, Applied Mechanics Department, Sardar Vallabh Bhai National Institute of Technology, Surat, Gujarat, India,

E-mail: akd@amd.svnit.ac.in

ABSTRACTThe piled raft foundation system has recently been widely used for many structures, especially high risebuildings. In this foundation, the piles play an important role in settlement and differential settlement reduction,and thus can lead to economical design without compromising the safety of the structure. Foundation rafts areanalyzed as a plate on elastic foundation with the representation of the foundation media using the Winkler
idealisation. The elastic constant of the Winkler springs is derived using the sub-grade modulus. The post
earthquake study of the structures reveals that the interaction of soil and foundation is playing a major role in thedamage/response of structure. Perusal of literature reveals that very few investigations were done on the effect ofvariable sub soil on the behavior of structures supported on pile raft foundations. So in this research, an iterative
dynamic analysis was performed using SAP2000 program to carry out three dimensional time history analysis of
non-linear soil-foundation-building models under a great earthquake ground motions. The interaction between
the soil and structure is represented by Winkler spring model. The obtained results confirmed that the dynamic
characteristics of soil structure system should be recommended for conservative nonlinear seismic response of
the high building since it mitigates of earthquake hazards.
Keywords: Sub-grade modulus, Soil-Structure Interaction, Seismic Response, Time history analysis

soil and structural parts of foundations inherently
accounts for the interaction of the soil and structure.
There will also be energy losses due to internal
friction of the soil. Because of these effects, theresponse of a structure on a soft foundation to a give
earthquake excitation will, in general, be different
from that of the same structure supported on adifferent sub soil. It is the influence of a soil
structure interaction on the response of structures toearthquake motion that is the general subject of thispaper.

INTRODUCTION
Piled raft foundations provide an economicalfoundation option for circumstances where theperformance of the raft alone does not satisfy thedesign requirements. Under these situations, theaddition of a limited number of piles may improvethe ultimate load capacity, the settlement anddifferential settlement performance, and the required
thickness of the raft Buildings are susceptible to soil
structure interaction effects due to the inducedchanges in the dynamic characteristics of soil during
seismic excitation; particularly several buildings
have been constructed on soft soil. Because of thisdetrimental effect, this paper aims at clarifying thesoil structure interaction effect on the seismic
response of buildings under strong ground motions
to provide damage control and enhance the safetylevel of such buildings
The load and deformation characteristics of thestructural and geotechnical (soil) components of thefoundations of structures can affect, and in somecases dominate, seismic response and performance.
Recognizing this important fact, many structural
engineers have included representations offoundation strength and stiffness in their seismic
analysis models for many years. The modeling of theBASIC CONCEPTS OF MODULAS OF
SUBGRADE REACTION
The concept of spring constant was first introducedby Winkler in 1867. He modelled flexible
foundation, such as raft, to stand on an independent
discreet spring elements or supports. In 1955, Karl
Terzaghi, in his paper ‘Evaluation of coefficients ofsubgrade reaction’ proposed a method to estimate
the magnitude of the spring constants. His approach,also known as subgrade reaction model, was thenbecome popular and commonly used in the design ofraft foundation.
In 1955, Karl Terzaghi (Liao, 1995) published aclassic paper titled ‘Evaluation of coefficients of310

GEOMATE- Brisbane, Nov. 19-21, 2014

5- Empirical and theoretical relations that areproposed by researchers (Bowles 1998;
Elachachi et al. 2004).

subgrade reaction’, in which he presented
recommendations for estimating the spring constants
which have come to be commonly used to model thefoundation sub grade in the analysis of mat
foundations and other similar problems Because of
the complexity of soil behaviour, sub grade in soilfoundation interaction problems is replaced by amuch simpler system called sub grade model. One of
the most common and simple models in this context
is Winkler hypothesis. Winkler idealization
represents the soil medium as a system of identicalbut mutually independent, closely spaced, discreteand linearly elastic springs and ratio between contactpressure, P, at any given point and settlement, y,produced by it at that point, is given by thecoefficient of sub grade reaction, ks (Dutta and Roy2002).
Starting with the pioneering work of McClelland andFocht (1958), beam-on nonlinear Winkler
foundation (BNWF) models have been used formany years for analyzing the response offoundations, most notably piles, for static loads(Matlock, 1970; Cox et al., 1974) and dynamic loads(Penzien, 1970; Nogami et al., 1992; Boulanger etal., 1999). Key advantages of these models overcontinuum formulations lies in their ability todescribe soil-structure interaction phenomena by
one-dimensional nonlinear springs distributed along
the soil-foundation interface. It is well-known thatthe modulus of the springs (also known as modulus
of sub-grade reaction) is not uniquely a soil
property, but also depends on foundation stiffness,geometry, frequency, response mode, and level ofstrain. A limitation of the approach relates to its onedimensional nature. A spring responds only to loads
acting parallel to its axis, so loads acting in aperpendicular direction have no effect on the
response of the spring.
In this model the sub grade soil assumes to behave
like infinite number of nonlinear elastic springs thatthe stiffness of the spring is named as the modulus
of sub grade reaction .Nonlinear springs for shallow
foundations have been used in conjunction withgapping and damper elements by Allotey andNaggar (2003 and 2007) as well as Raychowdhury
and Hutchinson (2009).
The direct method to estimate the modulus of sub
grade reaction is plate load test that it is done with
30-100 cm diameter circular plate or equivalent
rectangular plate (Reza & Janbaz, 2008). In general,the methods of determination of ks can be classified
as: [3]1- Plate load test (Dutta and Roy 2002;
Bowles 1998),
2- Consolidation test (Dutta and Roy 2002;
Bowles 1998),
3- Triaxial test (Dutta and Roy 2002),
4- CBR test (Nascimento and Simoes 1957)
and

Because of the limitation of available data andthe uncertainty of soil condition, it was also roposed
to use the empirical equations.

The Vesic’s equation clearly shows that the modulus
of sub grade reaction depends not only on the widthof the foundation, B, but also on the elastic
parameters of soils, Es and μs, and on the shapefactor of the foundation, Ip.
Table:- 1Range of modulus of subgrade reaction
Use values as guide and for comparison when using
approximate equations[1]Soil
Loose sandMedium dense sand
Dense sand
Clayey medium dense
sand
Silty medium dense sand, kN/m3
48000 – 16000
9600 – 80000
64000 – 128000
32000 – 80000
24000 – 48000

Clayey soil
200<

12000 – 24000
24000 – 48000> 48000

After broader idea of sub soil type’s discussion,
three major group of soil are selected for subsoil forthe actual work problem. They are classified as
under
The sub soils selected are c-soils- ϕ soils and ϕ soils.
As c – soils the clayey soils with sub grade modulus
30000 kN/m3, as c- ϕ 48000 kN/m3 and as ϕ – soils
medium dense sand with 70000 kN/m3 modulus of
sub grade reaction were selected and the further
analysis was carried out and various outputs arecompared for different sub soils as mentioned inabove discussions.

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GEOMATE- Brisbane, Nov. 19-21, 2014

Table :-2Values or value ranges for Poisson’s
ratioType of soil
Clay, saturated
0.4 - 0.5
Clay, unsaturated
0.1 - 0.3
Sandy clay
0.2 - 0.3
Silt
0.3 - 0.35
Sand. gravelly
0.1 - 1.00
sandcommonly used
0.3 - 0.4Rock
0.1 - 0.4 (depends somewhat
on type of rock)Loess
0.1-0.3
Ice
0.36
Concrete
0.15
Steel
0.33

Fig:- 1 25 storey building supported on piled raftfoundation

PROBLEM STATEMENT
Foundation along with surrounding soil is considered
for analysis. For analysis the building along withfoundation was modelled as frame and shell element
consisting of 9049 and 3305 elements. The
Discretization of shell element was done at the rate of
1.2m x 1.2m with 0.3m of sub mesh

Fig:-2 A time history analysis was carried out using
El Centro earthquake

Material properties:Grade of concrete :- M35
Poisson’s ratio(µ) :- as per the soil
Type of pile :- friction pile
Section of pile :- circular section
Details of The Problem
Height - 90m
Building Plane - 43.2 x 20.7m
Column Dimension – 600mm x 600mm
Beam Dimension – 250mm x 600mm
Shear Wall Thickness – 300mm
Foundation Data
Piled raft foundation
Analyse Type – Flexible approach (Winkler’s
model)
Thickness of raft –1 m ,Area of raft – 1050.45 m2
Pile Diameter, 1000 mm.
Pile length (l )– 15m, 30m
Spacing between piles :- 4.3 m atcentre,8.6 at edge
Total no of piles:- 36 nos

Fig: - 3 Settlement of raft in z direction for El Centro
earth quake (l = 15 m)

A time history analysis was carried out using El
Centro earthquake time history as shown in fig. 2
Fig: -4 For El Centro earthquake settlement in z
direction l = 30 m

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GEOMATE- Brisbane, Nov. 19-21, 2014

gave 1 mm to 2 mm which shows reduction of 99%
structure remain steady in all sub soil conditions
because settlement within permissible limits (65 to
100 mm for raft IS; 1904-1966) and for l = 30 m ,c-ϕ shows reduction of 65 to 70 % and ϕ soil shows
reduction of 99% structure remain steady in all sub
soil conditions because settlement within
permissible limits (65 to 100 mm for raft IS;19041966
Displacement of raft for l = 15 m
c soil gives settlement in the range of 4 to 5 mm
where as c-ϕ soil gives it in the range of 4 mm whichshows reduction of 10 % and ϕ soil gave 1 mm to 2
mm which shows reduction of 99% structure remain
steady and for l = 30 m c soil gives settlement in
the range of 3 to 4 mm where as c-ϕ soil gives it in
the range of 3 to 4 mm which shows reduction of 0
% and ϕ soil gave .00 mm which shows reduction of
100% and structure remain steady.

Fig: - 5 Displacement of raft in x direction for El
Centro earth quake (l = 15 m)

Conclusions
For medium duration earthquake the ϕ soil behavesin desired manner. The settlement and displacementof raft gets reduced in considerable extent of and forshort duration earthquake these results are evenmore effective considering all the three specified sub
soil types. This exhibits excellent behaviour of
medium dense sand (ϕ) soil as subsoil.
The frequency of occurrence of longer duration
earthquake with high PGA is relatively very less but
for medium to low duration earthquake it is veryfrequent. In that way performance of dense sand or
medium dense sand as a sub soil results in reduced
settlement and displacement to a considerable
extent as compared to c and c-ϕ soil.

Fig: - 6 Displacement of raft in x direction for El
Centro earth quake (l = 30 m)

References
1) Bowels J.E “Foundation Analysis and Design”4thedition McGraw hill international edition.

Fig:- 8 Maximum acceleration along the depth ofpile for El Centro earthquake. l = 15 m

2) Hamdy h. A, ahmedabd el “contribution of soilstructure interaction to Seismic response ofbuildings” journal of engineering sciences, assiut
university, vol. 39, no. 4, pp. 715-750, july 2011
3) Indo-Norwegian Training Prgramme on Seismic
Design of Multi-storey Buildings: IS 1893 vs. Eurocode 8 May 26-28, 2014 at New Delhi
4) sadrekarimi J. Akbarzad M. “Comparative Studyof Methods of Determination of Coefficient of
Subgrade Reaction”ejge vol 14 bundle E,2008

Fig: - 9 Maximum acceleration along the depth ofpile for El Centro earthquake. l = 15 m

5) Kame .C.S., Sawant V.A. “A Parametric Study
On Raft Foundation”
The 12th International
Conference of International Association For
Computer Methods And Advances In Geomechanics(IACMAG) 1-6 October, 2008 Goa, India

ANALYSIS AND RESULTS
1) settlement in raft for l= 15 m
c soil gives settlement in the range of 22 to 32 mm
where as c-ϕ soil gives it in the range of 12 to 17
mm which shows reduction of 45 to 55 % and ϕ soil
313

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Construction Materials

314Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

LIME LEACHABILITY STUDIES ON STABILIZED EXPANSIVE
SEMI-ARID SOIL
Arif Ali Baig Moghal1, Muawia A Dafalla 2, Tamer Y Elkady3 and Mosleh Ali Al-Shamrani4
Assistant Professor; 4 Professor; Department of Civil Engineering, College of Engineering,
King Saud University, Riyadh

1, 2, 3

ABSTRACTThe present study is aimed at examining the role of lime and the nature of leaching solution on the lime leaching
characteristics of an expansive soil originating from the Kingdom of Saudi Arabia. Lime leachability studies werecarried out in specially fabricated molds subjected to continuous leaching conditions. The specimens werecompacted directly into specially fabricated perspex molds and cured for 7, 14 and 28 days under constant humidity
conditions. In order to study the rate at which the calcium ions leach out from the lime treated clay matrix, water(leaching solution) was allowed to flow through the compacted specimen continuously for seven days and theresultant calcium concentration in the leachate was determined. The effects of various parameters like lime content,
curing period and the pH of leaching solution on the lime leachability values has been studied. It is observed that,at a given lime content, the calcium concentration in the leachate reduces with curing period. Relatively higher
amounts of lime leached under acidic conditions and the flow period does not affect the lime leaching patterns.
Keywords: Expansive soil, Cementitious Compounds, Landfill, Lime, Lime leachability, Mineralogy.

INTRODUCTION

MATERIALS

The expansive soils with their innate potential in
exhibiting detrimental volume changes at different
moisture conditions have been a cause of concern
globally [1-2]. Major corrective measures tocircumvent the problems posed by these soils include
preloading [3], chemical treatment [4] and the use ofcohesive non-swelling soil (CNS) cushion [5]. Limeis by far the most widely used chemical additive forthe treatment of expansive soils. It has been provensuitable for clays or silty clays. In most of theapplications such as structural fills, liners and landfill
covers, road bases, and embankments etc., lime
treated soils are often prone to the leaching of lime,
which will reduce the lime content from the stabilized
clay matrix affecting their performance [6]. Further,
the lime leaching from the clay matrix severely
hampers the rate at which pozzolanic reactions
proceed, resulting in the increased material porosity
as well as hydraulic conductivity and reduced
mechanical properties. Hence, the durability of lime
treated soils depends on the leachability of lime fromthe matrix. In this article, lime leachability studies on
Al-Ghat soil, stabilized with lime have been
conducted. The effects of various parameters likelime content, curing period and the pH of leachingsolution on the lime leachability values have beenstudied. The mechanism with which the lime
retention is achieved has also been brought out.

Soil
The tests were conducted on cohesive soil collectedfrom Al-Ghat town, located 270 km to the Northwestof Riyadh (26° 32' 42'' N, 43° 45' 42'' E). Sampling
was carried out at a depth of 3 m. The physicalproperties and chemical composition are reported inTables 1 and 2 respectively. It has been classified asa high plasticity clay, as per unified soil classification
system. The degree of expansivity was establishedbased on measured modified free swell index (MFSI)
values measured by means of sediment volume incarbon tetra chloride. For Al-Ghat the MFSI value
was less than 1.5 cm3/g.
Table 1 Physical properties of the soil
Physical Property
Liquid Limit (%)
Plastic Limit (%)
Shrinkage Limit (%)
Plasticity Index (%)
Linear Shrinkage (%)% Finer than 200 μm
USCS Classification

Al - Ghat
62
30
17
32
31
87.3
CH

*‘USCS’ refers to unified soil classification system;‘CH’ refers to clay with high plasticity.

315

GEOMATE- Brisbane, Nov. 19-21, 2014

content for Al-Ghat. Remoulded samples withdifferent lime dosages were tested for lime
leachability in specially fabricated Perspex moulds,
the details of which are shown in Fig. 3. The inside of
the perspex mould was coated with a thin layer ofsilicon grease ensuring a good contact between thecompacted material and the inner surface of themould. All the tested samples were compacted to theirmaximum dry density and corresponding optimum
moisture content values as per ASTM D5856-07 [8].
The top and bottom of the perspex mould were
provided with perforated PTFE (Poly Tetra-Fluoro
Ethylene) screens.

Table 2 Chemical composition of the soil
Chemical Composition (%)
K+
K2 O
Al
Al 2 O 3
Si
SiO 2
Ca+2
CaO

Al - Ghat
1.1
1.3
7
13.3
9.8
21
1.4
2

The predominant minerals present in the soil were
determined by carrying out XRD using Bruker D8Advance system. Sample was scanned from 2° to 60°(2θ) using 2.2kw cu anode long fine focus ceramic xray tube at a scanning rate of 1 degree per minute. Fig.
1 depicts comprehensive X-Ray Diffraction analysis.
Apart from quartz, the predominant minerals include
Kaolinite, Endelite, Dickite, Calcium sulfate hydrate
and Calcium aluminium silicate.

Fig. 2. Effect of lime content on the density
characteristics of Al-Ghat soil
Chemically inert glass beads of 0.5 cm diameter were
sandwiched between the two PTFE screens at boththe ends enusring uniform flow of water. The perspex
mould with the compacted specimen was kept in a
desiccator maintained at a relative humidity greaterthan 95%, and cured for 7, 14 and 28 days. After
curing the specimen, the perspex mould was fitted
into the position and connected to ultra-chemical
resistant tubing (Tygon). Millipore grade water (forneutral water conditions) and acidified water (using
0.1N HNO 3 for pH 4 condition) was allowed to flow
through the specimen and the entrapped air if any wasremoved using the air vent provided at the top of theperspex mould and leachate was collected in thegraduated cylindrical jars. The concentration of thecalcium in the leachate was determined immediately
by PinAAcle 900T Atomic Absorption Spectrometer.

Fig.1. X Ray Diffraction analysis of Al-Ghat Soil
Lime
Analytical grade Calcium Hydroxide, supplied byWinlab Chemicals, UK has been used in the present
study.
METHODOLOGY
Lime leachability test procedure
The target lime content percentages of 2 and 4 weremixed to Al-Ghat soil on dry weight basis. The
maximum proctor density values corresponding toeach percentage of lime addition shown in Fig. 2 were
determined by employing mini compaction test
procedure developed by Sridharan and Sivapullaiah[7]. From Fig. 2, as the lime content increases the
maximum dry density values were found to reducewith corresponding increase in optimum moisture

RESULTS AND DISCUSSIONSThe leaching of calcium ions from pore solution
forces the dissolution of calcium hydroxide which
severely hampers the rate at which pozzolanic
reactions proceed [2]. Hence in order to study the rate
at which the calcium ions leach out from the lime
treated clay matrix, water was allowed to flow
316

GEOMATE- Brisbane, Nov. 19-21, 2014

Outlet
Inlet
Perspex column of 15 cm lengthand 2.5 cm diameter

Glass beads of .5 cm
diameter

Stainless steel screen

PTFE distributory plate

Fig. 3. Schematics of lime leachability test Apparatus
5. But with increase in curing periods, the solubilityof silica from the clay is enhanced as the excess lime
breaks the Si-O bonds in the silica rich phases of clay
particles (Particularly Quartz as seen from Fig. 1).
This dissolution of silica is better at 4% lime content
compared to 2%, as it is nearer to the optimum lime
content [9]. Apart from silica, alumina is also released
from the mineral phase. This triggers a significant
reduction in the lime leachability values at 4%
compared to that at 2% lime addition at any given
curing period.

through the compacted specimen continuously forseven days.
The effects of various parameters like lime,
curing period and the pH of leaching solution on thelime leachability behavior have been studied in detail.
Fig. 4 shows effect of flow and curing periods on thelime leachability behavior of Al-Ghat soil under
neutral conditions at 2% lime content. Prima facie, itappears that the flow duration does not affect the lime
leachability and these values remain consistently
same from the third day onwards. With increase incuring period, the leachability values are drasticallyreduced as lime is converted from more soluble form
to less soluble form of calcium silicate hydrates. The
cementation products formed at higher curing periods
harden the clay matrix thereby reducing the lime
leachability
valuesconsiderably.
Similarobservations were noticed by Moghal andSivapullaiah [6], and Moghal and Elkady [2] underidentical conditions for different tested soils.

Fig. 5. Effect of flow period and curing period on thelime leachability behavior of Al-Ghat soil under
neutral conditions at 4% lime content
Effect of Nature of Leaching Solution on the Lime
Leachability Behavior
The surface of clay particles is rich with oxides of
SiO 2 , Fe 2 O 3 and Al2 O 3 as seen from Fig.1. When the
pH of the leaching solution is reduced it severely
hampers the dissolution of lime from clay matrix
from these oxide surfaces. From Fig. 6, at 2% lime
content, when the pH of the leaching solution was
reduced to 4, lime leachability values increased to
61% compared to neutral solution at a given curing
period. However with increase in curing period, there

Fig. 4. Effect of flow period and curing period on thelime leachability behavior of Al-Ghat soil under
neutral conditions at 2% lime content
With increase in lime content to 4%, theconcentration of lime in the leaching fluid increases,
particularly at lower curing periods as seen from Fig.
317

GEOMATE- Brisbane, Nov. 19-21, 2014is a significant reduction in the leaching of calcium
ions from the stabilized matrix (Fig. 6).

duration of flow period does not affect the lime
leachability values (Fig. 6).
With increase in lime content to 4%, even atlower curing periods, apart from cation exchange
reactions,flocculation
reactionsbecomepredominant, which in turn hold the calcium ionsintact, thereby reducing the lime leachability values
at any given curing period (Fig. 7). Further at this lime
content (4%) in addition to primary soil-lime
reactions, secondary reactions (cementation andcarbonation) are pronounced as well, where in the
dissolved calcium ions react with silicate tetrahedral
and aluminate octahedral sheets from the clay mineral
lattices at their edges forming calcium silicate hydrate(CSH) and calcium aluminate hydrate (CAH) gels
[10-12]. These cementitious gels are relatively inamorphous form at lower curing periods resulting at
higher lime leachability values as seen from Fig. 7.
With increase in lime content from 2 to 4%, at agiven curing period of 7 days, there is a 27% increasein lime leachability values, which is attributed toreadily soluble gelatinous materials under aggressive
environments (leaching solution pH 4). However withincrease in curing period to 28 days, this difference inlime leachability values (at 2 and 4% respectively)
reduces to 16.7%, as relatively more curing time isallowed which leads in the formation of cementitious
compounds which are relatively crystalline in nature
and are resistant to the acidity (pH 4) of leachingsolution. Further, even at 4% lime content, theduration of flow period does not seem to affect thelime leachability values as seen from Fig. 7.

Fig. 6. Effect of flow period and curing period on thelime leachability behavior of Al-Ghat soil underacidic conditions (pH 4) at 2% lime content

Practical Importance of the Study
Chemically modified clays have great potential in theconstruction of base liners for waste containment
facilities. One of the most overriding requirements for
efﬁcient functioning of a landﬁll liner material is topossess lower hydraulic conductivity values as it
controls the migration of leachate and its toxic
constituents into underlying aquifers or nearby rivers.
In most of the cases, the pH of the leachate varies
drastically in the acidic range which dictates theprevailing hydraulic conductivity and issues related
to durability. The current study tries to simulate theacidic conditions a landfill liner might experience
when it is constructed with chemically modified (limetreated) clay.
The amount of lime retained invariably reflects
the long term performance and consequently
addresses the issues related to the durability of theselected clay as a material for liner in the constructionof a landfill. In this study, the ability of Al-Ghat soil
to retain the stabilizer (lime) under aggressive
leaching conditions is investigated and it is observedthat even at pH 4, at varying lime contents, theamount of calcium leaching from the clay matrix is
reduced, particularly when the samples cured (asFig. 7. Effect of flow period and curing period on thelime leachability behavior of Al-Ghat soil underacidic conditions (pH 4) at 4% lime content
Since soil lime reactions are time dependent, at lower
curing periods, the cation exchange reactions (taking
place between the ions such as sodium or potassium
associated with the surfaces of the clay particles andcalcium cations of the added lime) are predominant.
This results in the modification of density of charged
particles around diffused double layer. As a result
when the pH of the leaching solution is reduced(around 4 in this case) the rate at which these cationexchange reactions occur are hampered, which resultin increased release of calcium ions from the claylime matrix. This is particularly true at lower curing
periods around 14 days as seen from Fig. 6. The
318

GEOMATE- Brisbane, Nov. 19-21, 2014

stabilization methods to treat low volume roadsubgrades in Texas”, Transportation Research
Record. 1819, Transportation Research Board,
Washington, D.C., May. 2003, pp.63–71.
[5] Sivapullaiah
PV, Subba
Rao
KS, and Gurumurthy JV, “Stabilisation of ricehusk ash for use as cushion below foundations on
expansive soils”, Ground Improvement, Vol. 8,
No. 4, Jan. 2004, pp. 137-149.
[6] Baig MAA, and Sivapullaiah PV, “Role of Lime
Leachability on the Geotechnical Behaviour of
Fly
Ashes”,
International
Journalof
Geotechnical Engineering, Vol. 6, No. 1, Jan.
2012, pp. 43-51.
[7] Sridharan A, and Sivapullaiah PV, “MiniCompaction Test Apparatus for Fine grained
Soils”, Geotechnical Testing Journal, Vol. 28,
No. 3, May 2005, pp. 240-246.
[8] ASTM D5856 – 07, Standard Test Method for
Measurement of Hydraulic Conductivity ofPorous Material Using a Rigid-Wall,
Compaction-Mold Permeameter, 2007, WestConshohocken, Philadelphia.
[9] Sivapullaiah PV, Sridharan A, and Bhaskar Raju
KV, “Role of amount and type of clay in the lime
stabilization of soils”, Ground Improvement,
Vol. 4, No. 1, Jan. 2000, pp. 37-45.
[10] Eades JL, and Grim RE, “Reaction of Hydrated
Lime with Pure Clay Minerals in Soil
Stabilization,” Highway Research Board,
Washington, D.C. Bulletin No. 262, 1960, pp.
51-63.
[11] Bell FG, “Lime Stabilization of Clay Minerals
and Soils,” Engineering Geology, Vol. 42, No. 4,
July. 1996, pp. 223-237.
[12] Moghal AAB, Al-Obaid AK, and Refeai TO,“Effect of Accelerated Loading on theCompressibility Characteristics of Lime-TreatedSemiarid Soils”, Journal of Materials in Civil
Engineering, Vol. 26, No. 5, May 2014, pp.
1009-1016.

noticed from the curing period adopted in the study).
Further, this study emphasizes and addresses theissues related to the use of locally available materials
as a suitable choice for the construction of base liners
for a landfills (both domestic and industrial).
CONCLUSIONS
The durability of lime stabilized clays depends on theamount of lime retained in the clay matrix particularly
when they are prone to leaching. The calcium
leaching from the lime stabilized clay matrix severely
affects the performance of the material and in mostcases, the selected material may not meet the desired
requirements. In this study, lime leachability studies
on Al-Ghat soil, stabilized with lime were conducted.
The effects of various parameters like lime content,
curing period and the pH of leaching solution on thelime leachability values were studied. It was observedthat lime leachability values increased with increasein lime content at any curing period. At a given lime
content, the lime leachability values reduced with theincrease in curing period as relatively more time isallowed for the formation of cementitious
compounds.
When the pH of the leaching solution was
reduced (pH 4), relatively higher lime leachability
values were obtained. With increase in curing period,
these gelatinous amorphous cementitious compoundtransform to crystalline form which resist the leachingof calcium due to their poor solubility. It was obviousthat the flow duration does not affect the lime
leachability pattern.
ACKNOWLEDGEMENTS
This paper is a part of a research project that was
supported by NSTIP strategic technologies programs,
11BUI1489-02 in the Kingdom of Saudi Arabia. The
authors would like to thank the Eng. Abdulla Bugshan
Research Chair for Expansive Soils for providing thenecessary facilities to carry out the experimental
work.
REFERENCES[1] Lu N, and Likos W, “Unsaturated Soil
Mechanics”, 2004, Wiley, New York.
[2] Moghal AAB, and Elkady TY, “Durability
Studies on Expansive Soils Treated with Lime,”
In the proc. of the International Conf. on Ground
Improvement and Ground Control, 30th October
to 2nd November 2012, held at Wollongong,
Australia, 2012, pp.1187-1192.
[3] Chen FH, “Foundations on expansive soils”,
1988, 2nd Ed., Elsevier Scientiﬁc, Amsterdam,
The Netherlands.
[4] Puppala AJ, Wattanasanticharoen E, and Hoyos
LR, “Ranking of four chemical and mechanical319

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

BEHAVIOR OF AN EPDM GEOMEMBRANE 18 YEARS AFTER ITSINSTALLATION IN A WATER RESERVOIR
1Manuel Blanco & Francisca Castillo1, Nathalie Touze-Foltz2, Bernat Amat3, Escolástico Aguiar4
CEDEX (Laboratorio Central de Estructuras y Materiales [Central Laboratory of Structures and Materials]),
Ministries of Infrastructure and Agriculture and Food and Environment, Spain;
2
IRSTEA, France; 3Firestone Building Products, Belgium; 4BALTEN, Spain

ABSTRACTThe purpose of this study is to evaluate the durability of an EPDM geomembrane installed 18 years ago in
the water reservoir of El Boquerón (Canary Islands, Spain). To do so, samples were regularly taken fromdifferent places of the water reservoir. Samples were laboratory tested as follows: foldability at low temperature,static and dynamic puncture resistance, Shore-A hardness, tensile strength and elongation at break, seam strengthand microscopic techniques. The obtained results confirm the EPDM geomembrane is still in good condition.
Keywords: Geomembrane, Waterproofing, EPDM, Durability, Water Reservoir.

geographical area where the maximum Global SolarUV Index in clear weather (Bournay E., 2007) is
considered as high (index between 6.5 and 8.5). The
technical characteristics of the reservoir arepresented in Table 1.

INTRODUCTION
In its report published in Paris in 1991, theInternational Commission of Large Dams indicatedthat the first geomembrane used in a hydraulicproject was made from butyl synthetic rubber [1]. It
was used in 1959 to waterproof the Kualapuu
reservoir in Holokai (Hawaii).
In Spain, it was also this type of synthetic rubber
which was originally used to waterproof water
reservoirs. The use of this product began in the Ibi
region, on the Mediterranean coast and extended
across the entire country up to the Portuguese border,
where Azud (small scale dam) in Matavacas(Huelva) was waterproofed in 1974 [2], [3].
Butyl rubber is a macromolecule which presents
in its structure a large number of double bonds, ofwhich the "TT" (trans-trans) chains are likely to be
attacked by electrophilic reagents such as ozone and,
consequently butyl geomembrane may experiencesignificant degradation. The researchers looked for asynthetic rubber which was not susceptible to thisphenomenon and they found this in the EPDM
terpolymer. This macromolecule is comprised ofthree monomers: ethylene, propylene and diene, thelatter being present in maximum concentrations of
5%. The first diene used was 1,3-butadiene which
was then replaced by other types such as
cyclopentadiene, considerably improving the initial
performances [4].

Fig. 1

Geographical location of the reservoir.

Fig. 2

El Boquerón reservoir.

THE RESERVOIRThe El Boquerón reservoir is located in the areaof Valle de Guerra, in the municipality of La Lagunain the north of the island of Tenerife (Figure 1 andFigure 2). The Canary Islands are located in a320

GEOMATE- Brisbane, Nov. 19-21, 2014

laboratory. Unless otherwise indicated, the values
presented refer to samples taken from the northbanks of the reservoir (bank most exposed to
sunlight, and consequently most exposed to high UVand temperatures).
As far as the foldability test at low temperature isconcerned (-55ºC), no cracks or fissures wereobserved in the flexing area on the samples analyzed
after 18 years of exposure. Similarly, during the
dynamic puncture test, no fissures or any other typeof degradation was noted in the impact area when theplunger was dropped from a height of 350 mm.

Table 1 Technical characteristics of the reservoir
Location
Capacity
HeightAltitude
Perimeter
Thickness of EPDM geomembrane
Area of the geomembrane laidYear of installation

La Laguna51.747 m³
11.0 m376.7 m
340.7 m1.50 mm8,991 m²
1992

Tensile Characteristics
FEEDBACK
Figure 3 shows the evolution in tensile strength atbreak, stress at 300% elongation and elongation atbreak over the 18 years since installation of the
EPDM geomembrane. It can be seen that the tensile
strength has not changed significantly, whileelongation at break decreases noticeably. It can also
be seen that the force necessary to obtain the same
300% elongation increases over time.
We note that after 18 years of exposure, theelastic elongation of the EPDM geomembrane islarger than 190% (remains elastic to breaking point),
which is very high in comparison with the majorityof thermoplastic geomembranes. This data issignificant as the permissible elongation determines
the ability of the geomembrane to adapt todifferential settlements and irregularities in the soil
and therefore defines its puncture resistance in realconditions.
The decrease in elongation at break and increasein stress at 300% elongation in the period is
explained by the fact that, in the case of EPDM,
during the oxidation phenomenon (induced by thetemperature and UV exposure), the combination
reactions of the carbon chains (cross-linking) has aprevails upon the cleavage reaction of the principal
carbon chain [5]. Consequently, a decrease inmolecular mobility and an increase in molecularmass can be seen [5]. These reactions are similar tothe process of curing used during EPDM
geomembrane production.

Initial Characteristics
Table 2 presents the initial characteristics of the
EPDM geomembrane installed in the El Boquerón
reservoir. The initial physical properties arecompliant with the values declared on the
manufacturer's technical data sheet. This data isconsequently used as reference values for assessing
the evolution over time of EPDM geomembranes.
Table 2 Initial Characteristics of the EPDM
geomembrane
Characteristics (Standards)
Average thickness(EN 1849-2)
Shore A hardness (ISO 7619)
Foldability at -55 °C(EN 495-5)
Resistance to dynamic puncture*(EN 12691)
Tensile Strength at break(ISO 527)
Stress at 300% elongation(ISO 527)
Elongation at break(ISO 527)
Static puncture
Resistance to puncture(EN ISO 12236)
External surface
Internal surface
Depth of the plunger before
perforation (UNE 104 317)
External surface
Internal surface
Seam resistance by tensile-shear(EN 12316-2)

Values1.51 mm68
Without
fissures> 350 mm
12.6 MPa
9.1 MPa527%

266 N/mm
266 N/mm

40 mm
40 mm
68 N/50 mm

Evolution Over Time
Fig. 3 Evolution over time in tensile strength andelongation at break, stress at 300% elongation.

After the EPDM geomembrane was installed,
samples were taken regularly and tested in a321

Distance made by the plunger, mm

GEOMATE- Brisbane, Nov. 19-21, 2014

Shore A Hardness
The Shore-A hardness value has increased overtime as shown in Figure 4. The increase in the ShoreA hardness can be explained by the decrease inmolecular mobility as explained in the Section of theInitial Characteristics.

Shore A hardness

Shore A hardness

External face
Internal face

Time, years
Fig. 6 Evolution of the depth of the plunger before
perforation over time.
Seam Resistance
After 18 years of exposure, the value for shear
resistance of seams is 645 N/50 mm. Figure 7
illustrates that, during the first 8 years, themeasurements for peel resistance of seams wererelatively variable. The measurements taken in thefollowing 10 years are more consistent and show thatpeel resistance is fairly constant.
The variability of peel measurements is explainedin part by the seaming method used at the time thatconsisted of applying a butyl based glue for which
uniform application was not guaranteed. This is oneof the reasons why, for a number of years already,butyl glue has been replaced by other systems suchas self-adhesive tape which ensures better quality
consistency.

Time, years
Change in the Shore A hardness over time.

Resistance to Puncture

Puncture resistance, N/mm

Figures 5 and 6 respectively present the staticpuncture resistance and the distance travelled by theplunger before perforation. The distance travelled by
the plunger before perforation is a measurement
which allows for the evaluation of the resistance topuncture in actual conditions as it gives an idea of
the adaptability of the geomembrane to the soil
conditions. The resistance to puncture stays fairly
constant in time (this is confirmed by samples taken
after 21 years of exposition in this same water
reservoir). On the other hand, the distance travelledby the plunger before perforation decreases
accordingly given the decrease in molecular mobility(the same phenomenon that explains the decrease inelongation at break). It should be noted that this lastvalue (27 mm after 18 years) remains very high andwell above the measurements usually recorded on
the vast majority of thermoplastic geomembranes [6].

Strength

Strength, N/50
mm

Strength Variation

Variation,%

Fig. 4External face
Internal faceFig. 7 Evolution of peel resistance of seams
over time.
Microscopic Analyses
Observations under reflection optical microscopy(magnified 40 times) and by scanning electron
microscopy (magnified 90 times) have beenTime, years
Fig. 5 Evolution in the resistance to static puncture
over time.
322

GEOMATE- Brisbane, Nov. 19-21, 2014

conducted according to the conditions documents inthe literature [7] for the purpose of evaluating thecondition of the geomembrane surface 18 years after
installation (figure 8).
If we take into account the condition of thesurface of an EPDM geomembrane that has not been
exposed [8], we can see under reflection optical
microscopy that after 18 years, the internal andexternal surfaces of the geomembrane seem to be ina good condition, with the internal surface presenting
the best state of condition.
The scanning electron microscopy shows thateighteen years after installation of the geomembrane,
the presence of a microporous structure can bedetected confirming a slight degradation of theinternal surface of the geomembrane. The externalsurface also presents some microcracks.
These microcracks seem relatively superficial
and do not affect the mechanical resistance of thegeomembrane, as proven in the evolution of theresistance at break and puncture examined above.
This is explained by the highly cross-linked networkof the EPDM geomembrane which distributes loads
evenly across all carbon chains and limits the
diffusion of potentially degrading elements [9].
These observations are to be compared with theresults of the study on the surface condition
conducted by Soriano et al. (2012) looking atdifferent types of geomembranes. This study
concluded that the impact of UV exposure is visibleon these organic materials and that it is moresignificant on thermoplastic geomembranes thanthermostable geomembranes such as synthetic
rubbers [7].

a)c)north bank, samples were also taken from the bottom(less exposed, due to protection from water) and thebank on the south side of the reservoir. Results
obtained are presented in Table 3.
Regardless of their orientation and their degree of
exposure, all samples analyzed after 18 years show asimilar evolution in their mechanical properties. It issystematically observed that tensile strength is moreor less constant, that elongation at break and the
distance travelled by the plunger before perforation
decreases significantly and that Shore-A hardness
and resistance to static puncture increases over time.
The results also show that the more apparent signs ofageing are observed on the samples taken from thenorth bank; the area that receives the most significant
amount of solar radiation.
Table 3 Characteristics of the geomembrane
according to exposure 18 years after installation

b)

12.6

Bank
N
11.6

BottomS
12.9 10.0

527

193

271

255

266

351

367

371

40

27

30

34

69
68

79
58

78
60

80
45

Characteristics

Ref.

Tensile Strength,(MPa)Elongation at break(%)
Resistance topuncture (N/mm)
Depth of theplunger before
perforation (mm)Shore A hardness
Seam resistance bytensile-shear(N/50 mm)
CONCLUSION

The results obtained during the periodic
inspection of the EPDM geomembrane installed in
the El Boquerón reservoir allows us to draw thefollowing conclusions: Both foldability at low temperature (-55ºC) andresistance to dynamic puncture showed no cracks,
breaks or any other indication of degradation
after conducting the tests, proving the good stateof conservation of the EPDM geomembrane 18
years since its installation; The tensile resistance that does not change
significantly over the years; whereas elongation
at break reduces significantly, a characteristic
behavior of thermostable materials, as a result of
the increase in the number of links between
carbon chains (cross-linking); elastic elongationis larger than 190% after 18 years of exposure,which is very high for a geomembrane; this lastproperty provides important information on theability of the geomembrane to adapt todifferential settling and irregularities in the soil;d)Fig. 8 18 years of exposition – microphotographs:- x40 of the (a) external surface and (b) internalsurface taken using reflection optical microscopy.
- x90 of the (c) external surface and (d) internalsurface, taken using scanning electron microscopy.
Influence of the Sampling Area on Samples
For the purpose of knowing the condition of the
EPDM geomembrane in other areas apart from the323

GEOMATE- Brisbane, Nov. 19-21, 2014

 The Shore A hardness measurements increaseover time; this is a consequence of the increase in
the level of cross-linking in the geomembrane
which reduces molecular mobility; the resistanceto puncture is fairly constant and the distancetravelled by the plunger before perforation, ameasurement that allows us to evaluate theresistance to puncture in actual conditions,decreases over time; however, the value obtained
after 18 years' exposure (27 mm) is greater thanthe measurement for the majority ofthermoplastic
geomembranes
usedinwaterproofing; The shear resistance of the seams, testament to
the quality of the seams, indicates that the seams
between the panels are correct; the values for peel
resistance of seams are relatively low andvariable, given the use of an old seaming method
which consisted of applying a butyl based glue tothe seam area;
 The microphotographs taken by optical andscanning microscopy show a material in a goodstate of conservation; only micropores and somemicrocracks were detected but we note thecomplete absence of craters, fissures and microcracks; No significant differences in condition wereobserved between the samples taken from thebottom (covered by water) and the samples takenfrom the top of the banks (exposed to weather);
the area most affected by ageing was the zone
located on the north bank; given that the reservoir
is located in the northern hemisphere, the northbank is the one facing the equator andconsequently receives the largest amount of solar
radiation (UV and temperature) which is
responsible for the degradation of organic
material.
After 18 years of exposure to demanding weather
conditions (high temperature and UV rays), theEPDM geomembrane used in the El Boquerón water
reservoir has retained the mechanical properties
which are still well suited to this[4] Davis J. A., Hoff J. L., Kalwara J. J., Kane E. G.
“A review of EPDM Systems Development
Proc”. Copenhague, X International Congress:
International Waterproofing Association, 1998,
pp. 263-274.
[5] Kumar A., Commereuc S.,Verney V. “Ageing ofelastomers: a molecular approach based onrheologicalcharacterization”;
Polymer
Degradation and Stability 2004; 2004, 751-757[6] Blanco M., Aguiar E., Castillo F., Soriano J.,
Noval A.M., Touze-Foltz N., Pargada L., Rico
G., Aguiar E. “Comparative study of threedifferent kinds of géomembranes (PVC-P,
HDPE, EPDM)”. BESANCON, 5th European
Geosynthetics Congress, 2012, Volume 2. 25
030.
[7] Soriano J., Blanco M., García M. A., Aguiar E.,
Leiro A., Rubín de Célix M., Mateo, B., Burgos
J. Optical and scanning electron microscopy as
advanced analysis methods to dertermine thecondition of geosynthetic geomembranes.
Valencia, Proc. Eurogeo5, 2012.
[8] Blanco M., Aguiar E., García F., Vara T.,
Soriano J., Castillo F. “État de la géomembrane
en EPDM de la retenue d’ “El Golfo” dans l’îled’El Hierro (Îles Canaries)”. Tours, Proc. 8eme
Rencontres Géosynthétiques, 2011, 283-293.
[9] Scott G. “Degradable polymers, Principles andapplications, 2nd edition”; Kluwer Academic
Publishers; 2002, pp.18-19.
[10] EN 1849-2. Feuilles souples d'étanchéité Détermination de l'épaisseur et de la masse
surfacique - Partie 2 : feuilles d'étanchéité detoiture plastiques et élastomères. Bruxelles,
Comité européen de normalisation.
[11] EN 495-5. Feuilles souples d'étanchéité
Détermination de la pliabilité à basse
temperature. Bruxelles, Comité européen denormalisation.
[12] EN 12691. Feuilles souples d'étanchéité Feuilles d'étanchéité de toitures bitumineuses,
plastiques et élastomères - Détermination de larésistance au choc. Bruxelles, Comité européen
de normalisation.
[13] EN ISO 527. Plastiques Détermination despropriétés en traction. Bruxelles, Comité
européen de normalisation.
[14] EN ISO 7619. Caoutchouc vulcanisé ou
thermoplastique - Détermination de la dureté par
pénétration - Partie 1 : méthode au duromètre(dureté Shore). Bruxelles, Comité européen denormalisation.
[15] EN ISO 12236. Essai de poinçonnement statique(essai CBR). Bruxelles, Comité européen denormalisation.
[16] EN 12316-2. Feuilles souples d'étanchéité Détermination de la résistance au pelage desjoints - Partie 2 : feuilles d'étanchéité de toiture

REFERENCES[1] International Commission on Large Dams.
“Watertigth Geomembranes for Dams”. Paris:
State of the Art Bulletin ICOLD Nº 78, 1991.
[2] Cea J.C. de, Asanza E., Blanco M. “Face
Protection: Geomembranes Lining vs. Paint
Coating”. Montreal, Proc. 21 International
Congress on Large Dams,2003.
[3] Blanco M., Castillo F., García F., Soriano J.
“Las
geomembranassintéticas
enlarehabilitación y mantenimiento de paramentos
de presas. II”. In Romeo et al. (eds.). London,
Dam Maintenance and Rehabilitation Taylor &Francis Group, 2010, pp. 335-341.
324

GEOMATE- Brisbane, Nov. 19-21, 2014

la perforación en geomembranas sintéticas
impermeabilizantes instaladas en balsas.

plastiques et élastomères. Bruxelles, Comité
européen de normalisation.
[17] UNE
104
317.
Matériales
sintéticos.
Determinación del recorrido del punzón antes de325

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

UNCERTAINTY OF BACK-CALCULATED VALUES IN PAVEMENTOVERLAY DESIGN WHEN USING THE FWD DEVICE
1

Moshe Livneh 1
Civil and Environmental Engineering Faculty, Technion-Israel Institute of Technology, Haifa, Israel

ABSTRACT
Several pavement-design methods, among them the Israeli Flex-Design method for interurban roads and the
new American FAARFIELD method for runways and taxiways, still rely on the subgrade CBR value together
with its equivalent resilient modulus. The latter is determined from the CBR value by a predefined correlativeequation. The use of these two methods for overlay or reconstruction design involves a determination of theexisting subgrade CBR value by various in-situ testing methods, including the Falling Weight Deflectometer(FWD). For that test, the subgrade CBR value is calculated from the FWD back-calculated subgrade resilient
value. Using just one of the predefined equations, however, makes the required design very uncertain. This
uncertainty is demonstrated in the paper by two runways, one constructed with a conventional flexible pavement
and the second with an all-asphaltic pavement. Both structures were designed for the same clayey subgrade witha design CBR value of 5%. Immediately after construction, both structures were tested by the FWD apparatus.
For both structures, the 15-percentile MODULUS back-calculated subgrade resilient modulus yielded a highvalue for the case of an infinite depth to bedrock and a low value (about one half to one third of the infinite depthcase) for the case of a back-calculated depth to bedrock. The consequences of these and additional outputs givenby the old AASHTO and EVALIV forward-calculation procedures are discussed in light of the uncertainty they
introduce into pavement overlay design.
Keywords: Back-calculation, CBR, Forward-calculation, FWD, Overlay-design, Resilient-modulus

projects moduli may vary for each program. It istherefore necessary to use engineering judgment toensure the calculated moduli are reasonable."
In contrast to those two quotations, the following
quotation from [3] states: “The FWD is capable ofproviding accurate information on the stiffness ofexisting pavements using the EFROMD and
ELMOD programs. The FWD test procedure is fast
and accurate, and the stiffness values produced areconsidered to be more acute than field CBR test
methods.” Since its publication, many othertechnical papers have contradicted this quotation;see, for example, the findings of [4].
The present paper concentrates only on theconsequences of obtaining subgrade moduli fromdeflection-basin back-calculation or forwardcalculation analyses. (Note: pavement granular-layer
moduli are discussed in an earlier paper; see [5]).
The updated MODULUS 6.0 program [6] served the
back-calculation analysis, as it is the leading
program in Israeli practice. In addition, both the
EVALIV [7] and the old AASHTO [8] programs
served the forward-calculation analysis. The
introduction of these two forward-calculation
programs in this present paper stemmed from theattempt to follow the content of the following
quotation: “Because of the unavoidable uncertainties
involved in the fundamental assumptions of thetheories and in the numerical values of the soil
constants, simplicity is of much greater importance

INTRODUCTION
Pavement-layer and subgrade moduli may beobtained from deflection-basin back-calculation
analyses through any of a variety of calculation
programs. These differing programs, however, render
non-uniform solutions and, in certain cases, may evenlead to erroneous conclusions. Moreover, for any
given program, the initial input assumptions influence
the moduli outputs, a situation that obviously puts into
doubt every proposed program code. It also raises
once more the following question: Which calculation
program is the most applicable?
Even when a seemingly applicable calculation
program is utilized, uncertainties associated with its
outputs still exist. These uncertainties are wellformalized in [1]: “It is, however, stressed thatspecial care must be taken when trying to interpretdeflection data to determine in situ pavement-layer
properties. It is well known that real highway
materials are neither truly linearly elastic nor are thein situ material properties and geometry uniform.
Owing to generally poor problem conditioning,small anomalies between actual and assumed
responses can lead to considerable differences
between the predicted and actual moduli. These
differences can be best minimized by incorporating
judgment into a back-calculation algorithm.” A
similar quotation is given in [2]: “Experience obtained
from the backcalculated programs shows that the326

GEOMATE- Brisbane, Nov. 19-21, 2014

than accuracy. If a theory is simple, one can readily
judge the practical consequences of various
conceivable deviations from the assumptions andcan act accordingly.” [9]Another issue dealt with in the present paper is adetermination of the subgrade CBR value from theabove back-calculated or forward-calculated subgrade
resilient modulus. This calculation is necessary, as
the Israeli Flex-Design method [10] for the flexible
pavement design of inter-urban roads and the new
American FAARFIELD method [11] for the flexible
pavement design of runways and taxiways still use
the subgrade CBR value as a major input in both new
pavement and overlay/reconstruction calculations.
This required CBR value is calculated from the backcalculated or forward-calculated subgrade resilient
modulus by using a pre-defined transformation
equation specific for each method.
Unfortunately, the above-mentioned procedureof obtaining the CBR value also leads to uncertain
results as fully discussed in [12]. Thus, issues
connected to both a correct determination of the subbase resilient modulus and a correct transformationof the latter into the CBR value will be discussed indetail in the sections to follow.

BACK AND FORWARD CALCULATIONSAs previously mentioned, the MODULUS 6.0
program [6] served to back-calculate resilient
moduli of the subgrade and pavement layers for thetwo given structures. These back-calculations
assumed that the depth to bedrock was (a) infinite and(b) equal to a back-calculated value.
Figure 1 shows the inequality of the subgrade
resilient moduli outputs for the two given structures,the higher values being associated with theassumption of an infinite subgrade depth to bedrock.
In addition, Fig. 2 shows the influence of the backcalculated depth to bedrock on the ratio of the backcalculated subgrade resilient moduli. This ratio isdefined as the modulus obtained for the infinitedepth case divided by the same modulus obtained
for the back-calculated depth. This figure clearly
demonstrates the reduction of the ratio of the backcalculated subgrade resilient moduli with the increaseof the back-calculated depth. Obviously, for a backcalculated depth approaching infinity, these two typesof back-calculations should yield the same results.
700

Subgade Resilient Modulus: Infinite Depth [MPa]

MODULUS 6.0

OBJECTIVES
The aforementioned issue of uncertainty will bedemonstrated here by two runways, one constructedwith a conventional flexible pavement having a total
thickness of 1,560 mm, and the second with an allasphaltic pavement having a total thickness of 900
mm. Both structures were designed for (a) a subgrade
CBR value of 5% and (b) the same aircraft loading.
Immediately after construction, both structures were
tested by the FWD apparatus. Thus, in light of theforegoing background and the two recent FWD
measurements, the objectives of this paper are as
follows:• Presentation of MODULUS back-calculated
subgrade resilient modulus results, together
with their consequences, from the two FWD
measurements when the depth to bedrock is
assumed to be (a) infinite and (b) equal to a
back-calculated value.
• Comparison of the MODULUS back-calculated
results with both the old AASHTO and the
EVALIV forward-calculated subgrade resilient
modulus results, including their consequences,from the above two FWD measurements.
• Elaboration of the uncertainty associated with adetermination of the design subgrade modulus
and the design subgrade CBR from the FWD
measurements for the pavement-overlay design.
Finally, the paper offers a tentative procedure fordetermining the required stiffness and strengthparameters for an existing subgrade, based on FWD
pavement-surface deflection measurements.

y=1.7542x
R²=-0.26

600

Line of Equality500
y=1.3471xR²=-5.025

400

300

200

100
Conventional Pavement
All-Asphaltc Pavement
0
0

100

200

300

400

500

600

700

Subgade Resilient Modulus: Back-Calculated Depth [MPa]Fig. 1 Subgrade modulus for the case of infinite
depth to bedrock versus subgrade modulus forthe case of back-calculated depth to bedrock:
MODULUS 6.0 outputs for the two given
structures
5

Ratio of MODULUS Subgrade Moduli

The ratio is between the moduli of the infinite depth to
bedrock and those of the back-calculated ones.
4

y=-0.935ln(x)+9.667
R²=0.850

3

2

1

Ratio of 1:1
y =-0.308ln(x)+3.934
R²=0.578

Conventional Pavement
All-Asphaltic Pavement

0
0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Back-calculated Subgrade Depth to Bedrock [mm]Fig. 2 Ratio of MODULUS back-calculated subgrade
moduli with an infinite depth to bedrock tothose with back-calculated depth versus thelatter depth for the two structures
327

GEOMATE- Brisbane, Nov. 19-21, 2014

In addition, it can be stated that (a) the low valuesof the back-calculated subgrade depth to bedrock of
Fig. 2 are very unrealistic; and that (b) the
characteristics of the results associated with theconventional pavement are entirely different fromthose associated with the all-asphaltic pavement
although the characteristics of the subgrade of both
pavements are the same. All these facts point to thehigh rate of uncertainty of the moduli outputs
involved in these back-calculation procedures.
Figure 3 depicts a comparison of the MODULUS
back-calculated subgrade resilient moduli with the
EVALIV forward-calculated moduli for the two given
structures. The figure indicates that the EVALIV
results are well correlated with the MODULUS
results of the subgrade infinite depth to bedrock; i.e.,
R2=0.597 for the conventional pavement and
R2=0.995 for the all-asphaltic pavement. Thesefindings are expected, as EVALIV also assumes aninfinite depth to bedrock.

to the all-asphaltic structures, and the second values
to the conventional structure.
Figure 4 depicts a comparison of the MODULUS
back-calculated subgrade resilient moduli with the old
AASHTO forward-calculated moduli when, in Eq.
(1), Ca equals 0.33.
700

MODULUS Subgade Resilient Modulus [MPa]Conventional Pavement600
y=2.6956xR²=0.3320

500

400

y = 1.8171x
R² = 0.1268

300

Equality Line

200

[a]

100

Back-calculated depth to bedrock
Infinite depth to bedrock
0
0

150

200

250

300

700
All-Asphaltic Pavement

MODULUS Subgade Resilient Modulus [MPa]Conventional Pavement

MODULUS Subgade Resilient Modulus [MPa]100

AASHTO Subgade Resilient Modulus [MPa]

700

600
Equality Line
500

400

y = 1.2608x
R² = 0.5970

300
y = 0.8338x
R² = -0.1465

200

100

600
y=3.3027x
R²=0.8752

500

400

300

y=1.7568xR²=0.3516

Back-calculated depth to bedrock
Infinite depth to bedrock
0

100

200

300

400

500

600

[b]

100

Back-calculated depth to bedrock
Infinite depth to bedrock
00

EVALIV Subgade Resilient Modulus [MPa]

100

150

y=1.0667xR²=0.9954

500

400

200

Es=Min{Ca×0.24×P/(δ r ×r)}
Equality Line

[b]

0

100

200

300

400

500

300

600

(1)

where Es denotes the subgrade resilient moduli, in
MPa; P denotes the FWD dynamic load, in N; rdenotes the radial distance from the plate center,
where the deflection measurement is recorded, inmm; δ r denotes the recorded deflection at a radial
distance of r, in mm; and Ca denotes the correction
factor, equal to 0.33. Note: Eq. (1) is derived from(a) Boussinesq stress-distribution theory for ahomogenous medium with a Poisson ratio of 0.5 andan applied concentrated load, and from (b) the
AASHTO correction factor of 0.33 in order toaccommodate the relationship between thelaboratory test results and the back-calculated results
according to the original Boussinesq equation.
Figure 4 shows that only the old AASHTO results
for the all-asphaltic pavement are well correlated with

Back-calculated depth to bedrock
Infinite depth to bedrock0250

To recall, the old AASHTO equation for
calculating the subgrade resilient modulus isessentially Eq. (1).

y=0.5678xR²=0.4155

100

200

Fig. 4 MODULUS subgrade modulus for both casesof infinite and back-calculated depth to
bedrock versus the old AASHTO subgrade
modulus for (a) the conventional pavementand (b) the all-asphaltic pavement

All-Asphaltic Pavement

300

50

AASHTO Subgade Resilient Modulus [MPa]

700

700

600

Equality Line

200

[a]

0

MODULUS Subgade Resilient Modulus [MPa]

50

700

EVALIV Subgade Resilient Modulus [MPa]Fig. 3 MODULUS subgrade modulus for both casesof infinite and back-calculated depth to
bedrock versus the old EVALIV subgrade
modulus for (a) the conventional pavementand (b) the all-asphaltic pavement
Figure 3 also indicates that the ratio of thesubgrade resilient modulus, obtained by dividing
MODULUS by EVALIV, varies between 1.07 and1.26 (i.e., around the expected value of 1.0) for thecase of infinite subgrade depth to bedrock, and from0.57 to 0.83 for the case of subgrade back-calculated
depth to bedrock. The first value in each case relates
328

GEOMATE- Brisbane, Nov. 19-21, 2014

the MODULUS results of the subgrade infinite depth
to bedrock; i.e., R2=0.875. As for the conventional
pavement, these results, in contrast to the EVALIV
case, are badly correlated; i.e., R2=0.332.
Figure 4 also shows that the ratio of the subgrade
resilient modulus, that obtained by MODULUS
divided by that obtained by the old AASHTO, varies
between 2.70 and 3.30 (i.e., around the expectedvalue of 1/Ca=1/0.33=3.0) for the case of infinite
subgrade depth to bedrock, and between only 1.82
and 1.76 for the case of subgrade back-calculated
depth to bedrock. Again, the first value in each pairrelates to the conventional structure, and the second
to the all-asphaltic structure.
Finally, Fig. 5 describes the relationship between
the EVALIV and the old AASHTO outputs, both forthe subgrade resilient modulus. This figure points tothe fact that the EVALIV results are well correlatedwith the old AASHTO results; i.e., R2=0.716 for theconventional pavement and R2=0.862 for the allasphaltic pavement. In addition, Fig. 5 indicates thatthe ratio of the subgrade resilient modulus, thatobtained by EVALIV divided by that obtained by theold AASHTO, varies between 2.13 for theconventional pavement and 3.09 for the all-asphaltic
pavement.

Table 1 and Fig. 6 show that MODULUS/b (asdefined in the notes to Table 1) and the old AASHTO
subgrade modulus outputs for the two given structures
are in essence the same. This finding was expected, as
it follows the fact that the compacted and natural
subgrade is actually the same, for these two given
structures, each possessing a design CBR of 5.0%. In
addition, the 15th percentile MODULUS backcalculated subgrade resilient modulus for theconventional structure yielded the value of (a) 193
MPa for the case of infinite depth to bedrock and (b)86 MPa for the case of back-calculated depth to
bedrock. For the all-asphaltic structure, these resilientmodulus values yielded values of 246 and 80 MPa,
respectively. Considering these back-calculated
results, it should be emphasized that many
investigators agree with the following: "The successwith which a calculated deflection basin is 'matched'with a measured basin is not a good indicator of theaccuracy of the back-calculated moduli. It is
possible to obtain small error terms with inaccurate
moduli values" [13].
100Conventional Pavement
90
85 Percentile

Cumulative Percentage [%]

80

700

EVALIV Subgade Resilient Modulus [MPa]Linear Regression600
y=3.0944xR²=0.8617

500

y=2.1344xR²=0.7163

400

70
60
50
40
30

[a]

20

MODULUS:
Back-calculateddepth
15-‫חוזון ה‬‫א‬
MODULUS: Infinite depth
AASHTOEVALIV

15 Percentile
10

300

0
0

200

50

100

150

200

250

300

350

400

450

500

Subgrade Resilient Modulus [MPa]Equality Line

100

100
Conventional Pavement
All-Asphaltic Pavement090
85 Percentile

0
0

50

100

150

200

250

80

300

Cumulative Percentage [%]AASHTO Subgade Resilient Modulus [MPa]Fig. 5 EVALIV subgrade modulus versus old
AASHTO subgrade modulus for the two given
structures
UNCERTAINTY OF CALCULATED MODULIAll-Asphaltic Pavement

70
60
50
40
30

[b]

20

MODULUS: Back-calculated depth
MODULUS: Infinite depth
AASHTOEVALIV

15 Percentile

The preceding section clearly demonstrates theinequalities that exist among the subgrade resilient
modulus outputs obtained according to all four
calculative procedures. In order to sum up theseinequalities, Fig. 6 depicts the cumulative percentageof these subgrade resilient modulus outputs obtained
for the two given structures. Figures 6a and 6b bothdemonstrate the remarkable dispersion that exists in
the MODULUS subgrade back-calculated outputs forthe case of back-calculated subgrade depth to
bedrock. This finding is not surprising, as Fig. 2 hasalready shown that a large proportion of the backcalculated subgrade depth to bedrock yields small,and even very small, unrealistic values.

10
0
0

50

100

150

200

250

300

350

400

450

500

Subgrade Resilient Modulus [MPa]Fig. 6 Cumulative percentage of subgrade resilientmodulus outputs obtained according to all four
calculative procedures for (a) conventional
pavement and (b) all-asphaltic pavement
Table 2 contains the calculated values of the 15thand 85th percentiles of the calculated subgrade
modulus: respectively, EVALIV outputs divided by
MODULUS/b outputs and EVALIV outputs divided
by old AASHTO outputs. These values werecompared with the 1/slope values given by the329

GEOMATE- Brisbane, Nov. 19-21, 2014

constrained regression (linear regression through theorigin) of Fig. 3 and with the slope values given by
the constrained regression of Fig. 5. The comparable
values as taken from these two figures with those of
Table 2 are as follows: 1/0.8338=1.1993 for the fourth
row of the table, 1/0.5678=2.134 for the third row,
2.344 for the second row, and 3.0944 for the first row.
(Note: All rows are measured from the bottom of
Table 2.) These values and those of Table 2 indicatethat for the case of EVALIV divided by
MODULUS/b, the two sets of values differ
significantly, whereas for the case of EVALIV
divided by old AASHTO, the two sets of values
almost coincide.

developed in these two references. This finding adds
additional weight to the uncertainty issue.
UNCERTAINTY IN CBR DERIVATION
To sum up the previous findings, there is aserious lack of consistency in the interpretations
made by various back- and forward-calculation
programs for the same field data. This finding
complies, as mentioned earlier, with that reported in[2] and, in addition, that in [16]. Furthermore, thelimitations of back-calculation and forwardcalculation of stiffness parameters in the field whenutilizing non-destructive test methods include poor
agreement between interpreted moduli and thecorresponding laboratory-measured or in-situ
directly measured moduli.
As mentioned previously, it is recommended in
old AASHTO [8] that back-calculated Es values
according to Eq. (1) be multiplied by a correction
factor of Ca=0.33 in the determination of SN for
design purposes. The analyses described in [8]pertain to the fine-grained AASHTO Road Test siteplus fine-grained soil from seven other projects. No
attempt was made in the old AASHTO study toinvestigate the relationship between back-calculated
and laboratory Es values for granular subgrades. It
may be that back-calculated Es values for granularsubgrades would not require a correction factor aslarge as that required for a cohesive subgrade.
In this context, it should be added that a later
research publication recommended a series ofcorrection factors as a supplement to the old
AASHTO design guide. Some of these correction
factors are given in Table 3 [17]. In addition, othersources, as summarized in [12], indicate that thiscorrection factor ranges from 0.2 up to 1.2.

Table 1: 15th and 85th percentiles of the back or
forward calculated subgrade modulus astaken from Fig. 6
Calculated Subgrade
Back or
Modulus [MPa]ForwardPavement
Calculative
15th
85th
Procedure
Percentile Percentile
MODULUS/b
86
197
193
240
Conven- MODULUS/itionalAASHTO
69
89
EVALIV
145
194
MODULUS/b
80
196
MODULUS/i
246
343
AllAsphaltic
AASHTO
79
100
EVALIV
229
320
Notes: MODULUS/b denotes MODULUS 6.0 for
the case of back-calculated subgrade depth to
bedrock; MODULUS/i denotes MODULUS 6.0 for
the case of infinite subgrade depth to bedrock.
Table 2: Ratio values of 15th and 85th percentiles of
the calculated subgrade modulus: EVALIV
divided by MODULUS/b and EVALIV
divided by old AASHTO

Table 3: Some old AASHTO modulus correction
factors for Eq. (1) obtained from the LTPP
study [17]Ratio of Subgrade
ModulusEVALIV
Pavement
Values of Values ofdivided by:
15th
85th
Percentile Percentile
Conven- MODULUS/b
1.69
0.98
tionalold AASHTO
2.18
2.10
AllMODULUS/b
2.86
1.63
Asphaltic old AASHTO
3.20
2.90

Type of Structure above
Subgrade
Stabilized Subgrade
Full-Depth AC/PCC
Granular Base/Subbase

Correction
Factor
Ca
1.32
0.52
0.35

Coefficient of
Variation
[%]
80
37
49

Other ratios have been documented in thetechnical literature, and a partial summary of them isgiven in [15]. All these values indicate again that evenwhen the back- or forward-calculated subgrade resilient-modulus values are the "true" ones, theirderived CBR values are uncertain, especially in lightof the coefficient of variation values given in Table 3.
Equation (1), with Ca=0.33 (the old AASHTO
method), postulates that the relationship between Es
and its corresponding CBR value is as defined by

Note: MODULUS/b denotes, as in Table 1,
MODULUS 6.0 for the case of back-calculated
subgrade depth to bedrock.
At this juncture, it is important to note that theratio values of Table 2 differ substantially (i.e., they
are much higher) from those calculated according to
the correction equations given in [14] and [15]. Hereit is worthwhile noting that the EVALIV forwardcalculations of AASHTO pavement parameters were330

GEOMATE- Brisbane, Nov. 19-21, 2014

Eq. (2) for which k=10.3 and m=1.00.
Es=k×CBR(1/m)

almost the same as that defined by k=15.0 and
m=1.41. On the other hand, the FAA’s default
expression for the FAARFIELD software does not
utilize the above modified expression, but the oldone, defined by k=10.3 and m=1.00.

(2)where k and m are empirical parameters varying
from source to source; Es is the direct-cyclic triaxial
test modulus or the corresponding FWD backcalculated modulus.
Equation (2) is displayed graphically in Fig. 7
for other frequently used values of k and m thanthose of the old AASHTO method. The m=1.00 and
14.0 values were taken from [18]. The m=1.41 and
k=15.0 or 20.0 values were taken from [19]. The
TRL or the new AASHTO Mechanistic-EmpiricalPavement Design Guide (MEPDG) expression was
taken from [20], for which k=17.6 and m=1.56.
Further, the U.S. Army Corps of Engineers
expression was taken from [21], for which k=37.3
and m=1.41; and that of the Georgia Department ofTransportation for medium clay sand was taken from[22], for which k=21.5 and m=2.09. Finally, theexpression of the FAA’s NAPTF for low to highstrength clays was taken from [23], for which
k=23.2 and m=1.46.

TENTATIVE RECOMMENDED PROCEDURE
For a tentatively recommended procedure, it may
be postulated that the EVALV procedure yields
more reliable results, as it is based on all sevendeflection measurements at a given location, andincludes the important input of the total pavement
thickness. In contrast, the old AASHTO procedure isbased on only one deflection measurement at a
specified lateral distance and excludes the thickness
input. The questions now are the following: (a) Whatvalue is to be assigned to the correction factor for
the EVALIV Es output? (b) What values should be
assigned to the k and m factors to calculate CBRfrom the corrected EVALIV Es values?
It seems that the correction factor for the
EVALIV Es outputs (Ce) is a function of the total
thickness of the pavement. The data given in thepresent paper, together with that given elsewhere(see Fig. 8), indicate that the following tentative
relationship may exist (see Fig. 9):

Back-Calculated Reslient Modulus [MPa]300k=37.3m=1.41250

k=14.0m=1.00k=10.3m=1.00200

k=20.0m=1.41k=20.7m=1.56k=15.0k=17.6 m=1.41
m= 1.56

150

100

50

0
4

8

12

16

20

(3a)

Ce=1/b(3b)where b denotes the slope of the restrained linear
regression (regression through the origin) of
EVALIV Es versus the old AASHTO Es; Hpdenotes the total pavement thickness, in mm; Cedenotes the correction factor (multiplier factor) for
the EVALIV Es outputs.

k=21.5m=2.090b=4.3054-0.0017×Hp

24

Measured CBR Value [%]Fig. 7 Back-calculated subgrade resilient modulus
versus CBR values according to various
sources300

EVALIV Subgade Resilient Modulus [MPa]Additional flexible pavements in Ben-Gurion airport

Figure 7 indicates that the range of subgrade
modulus estimations for a given CBR value issignificant. For any given case, the lack ofknowledge of its “true” expression may lead toconsiderable error, as much as 300% and more, inthe modulus estimation for high CBR values. Part ofthe discrepancy in this CBR estimation comes fromthe range of Es values that can be obtained fromapplying various back-calculation-program codes tothe same deflection- bowl measurements.
In Israel, the default expression for the Es-CBR
relationship is defined by k=20.0 and m=1.41 or,alternatively, for the Flex-Design software, by
k=14.0 and m=1.00. For low CBR values, thedifference in the subgrade modulus between these
two expressions is insignificant.
In addition, it should be mentioned that the TRLor the new AASHTO Mechanistic-EmpiricalPavement Design Guide (MEPDG) expression is250

y=2.8694xR²=0.1046

200

150
y=1.5332xR²=0.8689

Equality Line100

50
H=1,560 mm
H=730 mm
0
0

20

40

60

80

100

120

140

160

AASHTO Subgade Resilient Modulus [MPa]Fig. 8 EVALIV subgrade modulus versus old
AASHTO subgrade modulus for additional
flexible pavements at Ben-Gurion Airport
Thus, for a total pavement thickness of 900 mm,
the correction factor (Ce) is equal to 0.36; and for a
total thickness of 1,560 mm, the correction factor(Ce) is equal to 0.60. For the example of Table 1, in
which the design value of EVALIV Es is 229 MPafor the 900 mm pavement and 145 for the 1,560 mm
331

GEOMATE- Brisbane, Nov. 19-21, 2014

pavement, the corrected EVALIV Es values are
229×0.36=82.5 MPa and 145×0.60=87.7 MPa,
respectively. These latter two values are almost
identical, as they should be, since they refer to thesame natural and compacted subgrade possessing, as
mention earlier, a design CBR value of 5%. Here it
is important to note that the Eq. (3a) expression
should be verified by the directly measured andforward-calculated data of additional pavements.
As for the CBR derivation, it is tentatively
suggested that Eq. (2) may be utilized for the casewhere k=15 and m=1.41 or for the case wherek=17.5 and m=1.56. This suggestion follows the
new AASHTO Mechanistic-Empirical Pavement
Design Guide (MEPDG) expression, which seems to
be a modification of the old AASHTO expression.
Note should be taken that the two expressions yield
almost the same results for low CBR values asmeasured by the old AASHTO Road Test. Thus, the
new expression modifies the old one in the region of
medium to high CBR values.

uncertainty is involved: this one in the calculation of
the CBR value from these subgrade resilient
modulus outputs. Various calculative expressions
exist in the technical literature; however, thedifferences in their output may be very significant.
In spite of the above limitations, the paper
concludes with a tentative suggestion of how to
calculate (a) the proper subgrade resilient modulus
from the FWD deflection measurements and (b) the
CBR value from the above calculated subgrade
resilient modulus.
RECOMMENDATIONS
Together with the calculative procedure, it isvery much recommended [see also 24] that the EsCBR relationship in any rehabilitation design beassessed by conducting both FWD and in-situ CBR(DCP) tests on the existing pavements underconsideration. It should be noted that thisrecommendation is similar to the following, given in[25]: "As a part of this process, some procedures
include the testing of materials in the laboratory todefine their stiffness (modulus) characteristics, inparticular, undisturbed subgrade specimens. Cores
from the asphalt concrete and other treated layers
may also be obtained. These results are important toinsure that the moduli determined by backcalculation are reasonable. Relative to the core data,
it must be recognized that the back-analysis provide
values for the bulk material while the cores provide
spot values for the intact material."
Finally, it is worthwhile emphasizing thefollowing statement, made in the old AASHTO
guide [8]: "Users are cautioned that the resilient
modulus value selected has a very significant effecton the resulting structural number determined.
Therefore, users should be very cautious about using
high resilient modulus values, or their overlay
thickness values will be very thin."

5.0

Slope of EVALIV Es to AASHTO Es

Data taken from Fig. 5, Fig. 8 and an additional recent measurement

4.0

3.0

y = -0.0017x + 4.3054
R² = 0.7584

2.0

1.0

Data taken from Fig. 5 and Fig. 6
Data taken from an additional recent measurement
0.0

500

700

900

1,100

1,300

1,500

1,700

Pavement total thickness [mm]Fig. 9 Slope of EVALIV subgrade modulus versus
old AASHTO subgrade modulus (the bparameter of Eq. [3]) in relation to total
pavement thickness
To conclude, for the two corrected EVALIV Es
values given above (i.e., 82.5 and 87.7 MPa), thecorresponding CBR values are 11% and 12%,
respectively. These values are higher than the design
value (5%), as they refer to a dry-moisture state; i.e.,
to a state before possible wetting.

REFERENCES[1] Stolle, D. and Hein, D., “Parameter Estimate ofPavement Structure Layers and Uniqueness of
the Solution,” Nondestructive Testing ofPavements and Back-calculation of Moduli,
ASTM, STP 1026, American Society for Testing
Materials, 1989, pp. 313-340.
[2] Zhou, H., Hicks, K.G., and Huddleston, I.J.,“Evaluation of the 1986 AASHTO Overlay
Design Method,” Transportation Research
Record No. 1215, Transportation Research Board,
1989, pp. 299-316.
[3] Goode, J.I. and Mills, K.G., “Development of theFalling Weight Deflectometer for Economical
Pavement Overly Design,” in Proc. 16th Conf.,
Part 2, Australian Research Board, 1992, pp. 1935.

CONCLUDING REMARKSThis paper presented back- and forwardcalculations of FWD deflection bowls measured
recently at Israel’s Ben-Gurion International Airport.
The calculations clearly demonstrate the inequalities
that exist among the subgrade resilient-modulus
outputs obtained according to four different
calculative procedures. The consequence of this
output is the introduction of uncertainty into thepavement overlay design.
In addition to the uncertainty involved in thesubgrade resilient-modulus outputs, another332

GEOMATE- Brisbane, Nov. 19-21, 2014

[4] Livneh, M., "The Influence of Some Initial
Assumptions on Back-Calculated Moduli," Road
and Transport Research, Journal of the AustralianRoad Research Board, Vol. 8, No. 2, 1999, pp.
12-26.
[5] Livneh, M., "Some Findings Concerning theDetermination of Granular-Base Moduli for
Flexible-Pavement Thickness Design," in Proc.
of the 1st Inter. Conf. on Road and RailInfrastructure, Opatija, Croatia, 2010, pp. 273282..
[6] Liu, W. and Scullion, T., "MODULUS 6.0 for
WINDOWS: User’s Manual," Report No.
FHWA/TX-05/0-1869-2, Texas Transportation
Institute, Texas A&M University System,
College Station, Texas, 2001.
[7] Livneh, M., "Combining FHWA and EVALIV
Spreadsheets for Forward-calculating Subgradeand Pavement-Layers Moduli," in Proc. of theInternational
ConferenceonTransport
Infrastructures (ICTI 2010), São Paulo, Brazil,
2010.
[8] American Association of State Highway andTransportation Officials (AASHTO), “AASHTO
Guide for Design of Pavement Structures 1993,”
Washington, DC, 1993.
[9] Terzaghi, K. and Peck, R.B., Soil Mechanics inEngineering Practice, John Wiley & Sons, Inc.,New York, 1948.
[10] Uzan, J., "A Pavement Design and Rehabilitation
System," Transportation Research Record, No.
1539, Transportation Research Board, 1996, pp.
110-115.
[11] Federal Aviation Administration (FAA), "Airport
Pavement Design and Evaluation", Advisory
Circular, AC 150/5320-6E, September 2009.
[12] Livneh, M., "Uncertainty Associated with PreDefined Correlative Expressions of Various InSitu Tests Outputs," in Proc. of the 2007 Federal
Aviation Administration (FAA) Technology
Transfer Conf., Atlantic City, NJ, 2007.
[13] Briggs, C.R., Scullion, T., and. Mazer. K.R.,“Asphalt Thickness Variation on Texas Strategic
Highway Research Program Sections and Effecton Backcalculated Moduli,” Transportation
Research Record No. 1377, Transportation
Research Board, 1992, pp. 115-127.
[14] Livneh, M., "On Forward-Calculations of
AASHTO Pavement Parameters from FWD
Surface-Deflection Basins," in Proc. of the 2010
ATAP Symposium, South Korea, 2010, pp. 195210.
[15] Livneh, M., "An Alternative Forward-calculation
Technique as a Screening Procedure for Review
and Evaluation of Backcalculated Moduli," TheInternational Journal of Road and Airports(IJRA), Vol. 1, No. 2, 2011, pp. 85-117.
[16] Puppala, A.J., "Estimating Stiffness of Subgradeand Unbound Materials for Pavement Design,"

NCHRP Synthesis 382, Transportation Research
Board, 2008.
[17] Von Quintus, H.L. and Killingsworth, B.H.,"Design Pamphlet for the Back-calculation for
Pavement Layer Moduli in Support of the 1993
AASHTO Guide for the Design of Pavement
Structures," Report No. FHWA-RD-97-077,
FHWA, USDOT, Washington, DC, 1997.
[18] Uzan, J., “A Pavement Design and Rehabilitation
System,” Transportation Research Record No.
1539,
Transportation
Research
Board,
Washington, DC, 1996, pp. 110-15.
[19] Livneh, M., “Verification of CBR and Elastic
Modulus Values Derived from Local DCP
Tests,” in Proc. of the 9th Asian Regional
Conference on Soil Mechanics and Foundation
Engineering, Bangkok, Vol. 1, 1991, pp. 45-50.
[20] Powell, W.D., Potter J.F., Mayhew, H.C., andNunn, M.M., “The Structural Design ofBituminous Roads,” TRRL Laboratory Report
1132, Transportation and Road ResearchLaboratory, Wokingham, Berkshire, UK, 1984.
[21] Green, J.L. and Hall, J.W., Jr., “Nondestructive
Vibratory Testing of Airport Pavements:
Experimental Tests Results and Development of
Evaluation Methodology and Procedure,” Report
No. FAA-RD-73-205, Vol. I, Federal Aviation
Administration, Washington, DC, 1975.
[22] Webb, W.M. and Campbell, B.E., “Preliminary
Investigation into Resilient Modulus Testing for
the New AASHTO Pavement Design Guide,”
Office of Materials and Research, Georgia Department of Transportation, Atlanta, GA, 1986.
[23] McQueen, R.D., Marsey, W., and Arze, J.M.,“Analysis of Nondestructive Test Data on
Flexible Pavements Acquired at the National
Airport Pavement Test Facility,” FAA, William J.
Hughes Center, Airport Technology Researchand Development Branch, AAR-410, Atlantic
City International Airport, NJ, 2001.
[24] Livneh, M., "Small-Scale Dynamic Devices for
Subgrade and Granular Layers Characterization," in Proc. of the 3rd Trans-portation
Engineering Specialty Conference, CanadianSociety for Civil Engineering (CSCE), London,
Ontario, 2000.
[25] Monismith, C.L. and Brown, S.F., "Developments in the Structural Design andRehabilitation of Asphalt Pavements over Three
Quarters of a Century," Journal of the
Association of Asphalt Paving Technologists,Vol. 68A, 1999, pp. 128-251.

333

GEOMATE- Brisbane, Nov. 19-21, 2014

UTILIZATION OF COCO COIR DUST AND PVC WASTE MATERIALSFOR WOOD-TILE QUALITY COMPOSITE BOARD
Hermie M. del Pilar1, Monesse Andrea Z. Antonio2, Maricar A. Ilagan3 and Julius E. Seva4
1
Faculty, Malayan Colleges Laguna, Philippines;
2,3,4
Malayan Colleges Laguna, Philippines

ABSTRACT
Gearing on sustainable technology, two waste materials, coco coir dust and PVC were utilized to
produce a wood-tile quality, high density composite board material. Adopting the technology in producing
fiberboards, the use of PVC as binder to combine with dried coir dust (5% moisture content) was investigated.
Three mix ratios of PVC:Coir Dust were used: 80:20, 70:30 and 60:40. The produced board from eachcombination was then subjected to mechanical and physical property tests. Their properties were compared using
the analysis of variance. The mixing process involves the use of two-roll mill machine operating at 204OC while
the pressing involves the heat press machine at 108OC and pressure of 450 psi for 3minutes. The finishedproducts highlight a glossy brown surface comparable to a wood tile, and can be readily manufactured without
the additional veneer coating. Physical properties of the 3 ratios were tested against ordinary board. All 3 ratios
exhibit 0% Water Absorption (WA) and Thickness Swelling (TS) while ordinary board showed 28.5% WA and
16.5% TS. Mechanical tests for the 80:20 ratio yielded a highest mean value of 55KPa·m on Impact Strength(IS) and 68.85MPa on Modulus of Rupture (MOR) while ordinary boards yielded 50KPa·m on IS and 7.51MPa
on MOR. The least mean on different properties of the bio-composite material were compared with the means ofcommercial board product. This study found that the PVC-Coir Dust combination exhibited highly satisfactory
performance based on the physical and mechanical properties as compared to the ordinary board
Keywords: High density board, Coco peat, PVC pellet, Modulus of Rupture, Impact Strength
the leader Polyethylene in the plastic industry. It is
one of the most commonly used thermoplastic
materials in worldwide polymer consumption(Sadat-Shojah M., 2011).
The Crown Asia Compounders Corporation(CACC) is one of the manufacturing companies in
the Philippines. It manufactures plastic compounds
and other plastic products for direct and indirect use
in the construction and telecommunicationsindustries. The company is currently located in
Guiguinto Bulacan with an operating cost of 1,800
metric tons per year (Crown Pipes, 2011). Being a
producer of PVC plastic pipes, the company yields
residual PVC waste materials particularly on its
plastic injector and converted into PVC pellets.
In this study, the base material for the biocomposite High Density Board product is the cococoir dust, also known as coco peat. A large amountof coir dust is produced in the process of extracting
coco fiber. Coir dust is described as a brown spongylight weight particle which falls out when the fiber isshredded from the husk. It is estimated that the coir
dust composed about 70% of the weight of thecoconut husk (Tejano, 1985). The company Soriano
Multi-Purpose Fibre Corporation (SMPFC) is one of
the companies that produce coconut products in thePhilippines. Being a subsidiary of the famous
Foundation for a Sustainable Society, Inc. (FSSI),
the company also operates in fibre-making

INTRODUCTION
Today’s industry demands various sources of
construction materials. Since the increasing problem
in the supply of materials goes with the increasingproblem in solid waste management, the use oftechnology in producing composite board materials
out of plastic wastes like PVC and agricultural
wastes like coco peat can be a practical alternative.
Recycled materials converted to good use andreducing the energy required to make them arecalled “green building materials” (Kubba, 2010).
The intent to create green building materials
from wastes and the opportunity to utilize theavailable technology, like technology in making
Medium Density Fibreboard (MDF) and HighDensity Fibreboard (HDF), led to creating acomposite board material using coco peat and PVC
wastes.
The PVC waste was chosen as binder inmaking a composite High Density Board sinceamong various waste materials, plastic wastes andmunicipal solid wastes are of great concern.
Municipal solid wastes containing PVC when burnt
gives rise to toxic gases like dioxins. In fact,disposal of plastics in an eco-friendly way is one of
the thrusts of today’s research (Vasudevan, 2012).
Polyvinyl Chloride (PVC) at global level exceeds ademand of 35 million tons per year, second only to334

GEOMATE- Brisbane, Nov. 19-21, 2014

particularly in Laguna, Quezon and Albay (School,2011). The coco peat waste products derived fromthe production of coconut products of a factory at
San Mateo, San Pablo, Laguna were utilized in thisstudy.

Machines for the composite board production
The machines used in the production of HDB
are the two roll mill and the heat press. The two rollmill is equipped with rolls made of corrosion
resistant steel and its surface is hardened andpolished. The two rolls run at fixed speed at a fixed
temperature. The temperature of the two roll mill
was set at 204-210OC a bit higher to the melting
point of the PVC. The mixing process for the cocopeat and PVC was done as these components were
continuously fed to the roll mill.
The heat press machine compress the HDB
composition using two parallel plates. The heat pressmachine was set at 180OC and pressure of 3.11MPa
sufficient to form the desired HDB.
The machines used, are found in the Industrial
Technology Development Institute (ITDI) DOST
Compound, Gen. Santos Ave., Bicutan, Taguig
City, Philippines.

METHODOLOGY
Materials and equipment
The materials in producing the high quality HDB
were sourced from the Soriano Multi-Purpose Fibre
Corporation (SMPFC) in San Pablo, Laguna for thecoco peat base material and Crown Asia
Compounders Corporation (CACC) in San MiguelBulacan for the binder PVC waste material. Figures
1a and 1b shows the appearance of the coco peat and
PVC pellet upon purchase from SMPFC and CACC.

Fig. 1a: Coco Peat

Fig 1b: PVC pellets
Fig. 2: The 2-Roll Mill Machine

The moisture content of the coco peat wasdetermined using the oven-dry method. Oven-dry
method is the most commonly used method indetermining moisture content of a sample. The
moisture content of the coco peat was determined bysubtracting the weight of the coco peat before
placing in to the oven to the weight of the coco peat
after oven drying, this process will continue until thedifference approximately reach zero. The equation
below determines the percent of moisture content(MC), where it depends on the original weight (W o )and the final weight (W f ) after oven drying.
𝑴𝑴𝑴𝑴 =

𝑾𝑾𝒐𝒐 − 𝑾𝑾𝒇𝒇𝑾𝑾𝒐𝒐

𝒙𝒙 𝟏𝟏𝟏𝟏𝟏𝟏%

Figures 2a shows the 2 roll mill machine used inthis study.
Manner of Mixing and Percent Adhesion
The 2-roll mill machine was used in mixing the
PVC and coco peat. It rotates with temperature set at
204oC – 210oC, same as the melting point of PVC.
The ratios of the PVC binder to the coco peat usedwere 60:40, 70:30, and 80:20. The PVC pellets werepoured between the two roll mill to melt and thecoco peat mixed as repeatedly kneaded by therotating roll mill. After mixing, the mixture wasplaced in a 200 x 200 x 9.5 mm molder.

(1)

A moisture content of 5% or less qualifies for the
HDB production. The use of sieves was employed tonote the particle size of the coco peat, and thesieving procedure followed the AASHTO T 27,
Sieve Analysis of Fine and Coarse Aggregate.

Heat Press on Mixtures
The molder containing mixture was then placed
between two parallel plates of the heat pressmachine with the temperature that was set atapproximately 180oC and subject to a pressure ofaround 3.11MPa applied for 3 minutes. Trial mass
mixtures were tested for hot compress to identify
which density will provide a high quality board
material which was judged according to appearance
and texture.

The commercial board, plywood, with similar
thickness was used to compare with the mechanicaland physical properties of the HDB composite
boards. This plywood is commercially available athardware stores in the Philippines.

335

GEOMATE- Brisbane, Nov. 19-21, 2014

immersing in water respectively (Hlaing and Kyi,
2011).
Thickness Swelling (TS) Test (ASTM D1037-99,
100-107)
The Thickness swelling test was conducted rightafter the water absorption test. After immersing thesample boards in water for 24 hours, the thickness ofeach board were measured using a Vernier Caliper.
The measured thickness was compared to thethickness of the sample before immersion in water(Hlaing and Kyi, 2011). The test for TS and WA
were based on the ASTM standard method D103799 (American Society for Testing and Materials,
200).

Fig. 3: The finished HDB product with wood tile
quality.
Figure 3 shows the physical appearance of the
HDB composite product derived from the mixed
coco peat and PVC binder.
HDB Specimen HandlingAfter heat press, the molder was removed fromtwo parallel plates of heat press machine; the HDB
was extracted from the molder with the use of handprotection to avoid breakage or damage to the HDB,
and to avoid burn due to early contact between
newly pressed HDB and the handler. The boards
were cooled at room temperature and carefully
sealed in plastic bag container upon cooling, before
testing. The boards were then conditioned for 3
weeks in a room with temperature of 25OC andrelative humidity of 65, before subjecting to physicaland mechanical testing.

Mechanical Property test

Physical Property test

The modulus of rupture was determined using
the three point bend test. The flexural test measures
the force required to bend the HDB and thecommercial board under three point loading
conditions. Portions of the 200 x200mm boards were
cut into 50mm x 200mm to serve as specimen for
testing in each mix ratio.
The MOR is used as an indicator of the sample
boards’ stiffness when flexed. Each sample board
was subjected to a concentrated or breaking load at
the centre of the sample board using the universal
testing machine (UTM) with the bend fixture. Afterobtaining the value of the breaking load in eachsample board, the MOR of each sample board wasdetermined using the formula:

The mechanical property tests for HDB andcommercial board consists of tests for modulus ofruptures(MOR) and impact strength (IS). The tests
for strength were based on the ASTM code D1037.
The results of these tests were compared todetermine the significance of differences between
HDBs and the least performing HDB with that of the
CB performance.
Modulus of Rupture (MOR)

The physical property tests employed for HDB
and commercially available boards were water
absorption and thickness swelling. The results ofthese tests were compared to determine if they are
significantly different.
Water Absorption (WA) Test (ASTM D1037-99,
100-107)
The water absorption test measures the moisture
content of HDB and the commercially available
board (plywood). Portions of sample boards derived
from the 200 x 200 mm boards were cut into 50 mm
x 50 mm for each mix ratio. The specimens were
weighed and placed in a container and immersed inwater for 24 hours. When retrieved, the water at thesurface of the sample boards were wiped out using
filter paper or tissue and then weighed. The moisture
content of each sample boards were computed using
equation 2:
𝑴𝑴𝑴𝑴 =𝑾𝑾𝑾𝑾
𝑾𝑾𝑾𝑾

x 100% =𝑾𝑾𝑨𝑨 − 𝑾𝑾𝑺𝑺
𝑾𝑾𝒔𝒔

𝒙𝒙 𝟏𝟏𝟏𝟏𝟏𝟏%

𝑴𝑴 =𝟑𝟑𝟑𝟑𝟑𝟑𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐(3)

where M is the modulus of rupture, P is thebreaking load, L is the span between the two
supports, b and d are the width and the depth of theboard samples respectively (Based on ASTM CodeD1037).

(2)

Impact Strength (IS) Test (ASTM D256)

where MC is the moisture content, Ww is theweight of the water being absorbed equivalent to thedifference of W A and W S, the weight of the board
before immersing in water and the weight after

The impact strength (IS) test measured theamount of energy or load required to break the board
specimens. The method of un-notched impact
336

GEOMATE- Brisbane, Nov. 19-21, 2014

strength was used for the IS test where the sample
board was held horizontally supported at its ends
with dimension 50mm x 10mm area and hit at its
center by a pendulum. The IS was measured by theamount of energy per unit thickness of the specimen.
The Humburg Pendulum Impact Tester was used inthis study and the procedure was based on ASTM
D256 standard.
50

50

50

50

For
WA &

For
WA &

Statistical tool
The Analysis of Variance was utilized todetermine if there is a significant difference on themeans of the HDBs produced using the 60:40, 70:30
and 80:20 ratio for the physical tests (WA and TS)
and the Mechanical Tests (MOR and IS). The t-test
was used to determine whether there is a significant
difference on the means of HDB having the lowest
value among the three mix ratios and thecommercial board for each test.

50

RESULTS AND DISCUSSION
For
MO
R
Test

For
WA &

For
WA &

50

Physical Property Test
Water Absorption and Thickness Swelling Test

For
WA &

For
WA &

For ISFor ISFor ISFor ISFor ISFor IS

The 12 specimens - 50mm x 50mm for each 3 mix
ratios of HDB and the commercial board (plywood)yields the mean Water Absorption shown in Table 2.

50

10
10
10

Table 2 Data on the Mean Water Absorption andThickness Swelling (24 hours after immersion onwater for all board’ mix ratios).

20

DISCARD

Board Type
Fig. 4: Cutting pattern of test specimens for physicaland mechanical testing (dimensions in mm.)
HDB (60:40 ratio)
HDB (70:30 ratio)
HDB (80:20 ratio)
Plywood

Figure 4 shows how the test specimens were cut
in each mix ratio from board materials.
Table 1. Number of board materials, number of
specimens, sizes for the physical and mechanicaltestingType ofNo.
No. ofBoard
Type of Testof
Board
Speci RequiredmenPhysical WA
12
2X3
Test
(mix
TS
12
ratios)=6
HDB
Mechan MOR
4boardsical Test IS
12
Plywood

200

For
MO
R
Test

Physical
Test
Mechanical Test

WA
TS
MOR
IS

12
12
4
12

Ave.
Density(g/cm3)
1.3
1.2
1.3
0.6

Mean
WA
(%)
0
0
0
28.5

Mean
TS
(%)
0
0
0
16.5

Based on results, the HDBs regardless of the mix
ratio, exhibit the ability to prevent water absorption
and thickness swelling, both registering zero
percent! The commercial board records 28.5% and16.5% on WA and TS, respectively. This is apromising quality of a developed product out ofthese materials.
Mechanical Property Tests
Modulus of Rupture
The 4 pcs – 200mm x 50mm specimens cut ineach mix ratio and commercial board yield thefollowing means as shown in Table 3.

6 boards

Results showed that the HDB, which yielded thehighest and lowest MOR were the 80:20 and 70:30,
respectively. The commercial board records a low
7.51MPa, which indicates that the composite HDB
has a flexure quality far exceeding that of thecommercial board.

The distribution of specimens produced for various
tests of physical and mechanical properties of HDBs
is shown in Table 1.

337

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 3 Means of the Modulus of Rupture Test forthe different board specimens (HDB and Plywood)
Type
of
Board
Mix ratio MOR Mean (MPa)
High
60:40
53.91
density
70:30
51.71
Board
80:20
68.85
Plywood
Not
Applicable

Impact Strength (IS)The 12 pcs – 50 mm x 10 mm test specimens foreach type of board (60:40, 70:30, 80:20 mix ratios
and plywood) were tested using the Humburg
Pendulum Impact Strength Test. The results of the ISmeans are shown in Table 6.
Table 6 Mean of the Impact Strength Test for thedifferent board specimens of HDB and CB
Type ofMix Ratio
No. ofISST
BoardSpecim
(KPa­
D
ens
m)
DE
V

Using one way Analysis of Variance with 5%
significance level for the 3 mix ratios of HDB, it
shows that there was no significant difference
between the means of the MOR derived from the 3point bend (flexure test). Table 4 shows the ANOVA
results of calculation.

High
Density
Board

Table 4 One Way ANOVA for the 3 composite
boardsSOURCESS
df
MS
Fp
BetweenGroupsWithin
Group
Total

695.
77
55.6
9
751.
46

2
9

347.8
9
6.19

56.2
2

Plywood> 0.05(Accept Ho)
Null
Hypothesis)

60:40

12

39.38

2.65

70:30

12

51.88

3.54

80:20

12

55.00

2.30

Not
Applicable

12

50.00

1.28

Table 6 shows that 70:30 yields the highest meanon IS, while 60:40 yields the lowest. Plywood has an
IS mean comparable to the IS of any HDB mix ratio.
This result suggests that plywood exhibit goodquality in terms of impact resistance which iscomparable to the IS of the HDBs.

1
1

Table 5 showed that the 70:30 mix ratio yielded
the lowest MOR (51.71MPa). This value wascompared to the MOR performance of thecommercially available plywood, which yielded
7.51MPa. Using the one-tailed test and 5% level ofsignificance, the result shows that the lowest
performing HDB has an MOR significantly, whichis greater than that of the plywood. Table 5 shows
the values in computing the test of significance.

Table 7 shows the values for the test ofsignificance among the 3 mix ratios of the HDB.
Table 7
One Way ANOVA test for the 3 mix
ratios of HDB
SOURCE

Table 5 One-tailed t-test with 5% level ofsignificance between 70:30 HDB and CB
BOARD
TYPE
70:30
HDB

No. ofSpecimen
4

MEAN
(MPa)
51.71

p value
STD
DEV
1.91 p comp = 1.02
x10-5

Plywood

4

7.51

0.06

SS

df

MS

F

p

Between 1639.875
819.938
Groups2
99.0108.281> 0.05 ,Within 273.285
therefore
Groups33
reject Ho
Total 1913.160 35
A significant difference on the means of the
HDBs produced were found among the 3 mix ratios,
where the 60:40 ratio emerged as the highest,
followed by the 80:20 ratio and least performing is
the 70:30 ratio as shown in Table 7

The MOR of HDB 70:30 ratio is significantly
greater than that of the plywood. Since p comp <0.05,
which means that the flexural stress of the HDB far
exceeds that of the plywood material.

The variation in values of the mechanicalproperties of the boards is summarized and shown in
Figure 5, where the HDBs are noted to excel in the
MOR performance while the plywood excel in the
IS performance. HDBs with 80:20 mix ratio
demonstrate highest performance in MOR while the

The values in Table 5 show that the MOR of HDB
70:30 ratio significantly exceeds that of theplywood, therefore the HDB exhibits good quality interms of flexure or bending stress resistance.

338

GEOMATE- Brisbane, Nov. 19-21, 2014

70:30 ratio is the least. The 60:40 ratio demonstrate
the highest performance in IS while the 70: 30 is theleast.
80

4.

68.85

60 53.91 51.71

The authors would like to acknowledge thesupport of Malayan Colleges Laguna in availingreference materials as well as the use of laboratory
equipment in preparing and testing the composite
board materials. Also, the Industrial Development
Technology Institute (ITDI) of the Department of
Science and Technology for allowing the authors use
the 2 roll mill machine and hydraulic heat press forthe production of the composite boards

IS (KPa-m)

200

ACKNOWLEDGMENT

MOR (MPa)

40

The physical appearance of the HDB biocomposite product shows a quality comparable
to a fine wood-tile. The surface exhibits a
glossy surface which enhances the aesthetic
feature of the composite material.

7.51
60 - 40 70 - 30 80 - 20 CB

Fig. 5: Combined graph of the MOR and IS Means
CONCLUSIONREFERENCES

Based on the results on Physical andMechanical Properties of the bio-composite HDB
made of PVC waste and Coco Peat waste, thefollowing conclusions were drawn:[1]Kubba, S. (2010). Chapter 6 - Green Materials
and products. LEED Practices,
Certification and Accreditation Handbook,
pp.151 - 209.

1.

2.

3.

The WA and TS of the composite HDB had
shown excellent quality regardless of the mix
ratio used. All specimens demonstrated 0% on
both WA and IS tests. These results can be
attributed to the plastic property of the binder
PVC which comprises the greater percentage ofthe HDB component.

[2] Vasudevan, R. S. (2012). Construction and
Building Materials. onstruction and
Building Materials, pp.311 - 320.

[3] Sadat-Shojah M., B. G. (2011). Recycling of
PVC wastes. Polymer Degredation andStability, Vol. 96, pp.404 - 415.

The mechanical test of the HDBs in resistingflexure or bending exhibit good performancecompared to plywood. Among the mix ratios
60:40, 70:30 and 80:20, the best mixture was
80:20 recording an MOR of 68.85 MPa, while
the 70:30 was the least performing with an
MOR value of 51.71 MPa. Though statistics
show that the MOR values of the 3 mix ratios
do not differ significantly, the plywood had
shown weak resistance in bending as reflectedby its low MOR value of 7.51 MPa.

[4] Crown Pipes. (2011). Crown Pipes. Retrieved
January 28, 2014, from Crown pvc.com.ph:
http://www.crownpvc.com.ph/crownpipes/about/[5]Tejano, A. (1985). State of the art of coconut coir
dust and husk utilization: general overviewPaper presented during the National
Workshop on waste utilization, coconut
husk. Philippine Journal of Coconut
Studies, Vol. 2, pp.4-11.

The plywood demonstrated impact resistancecomparable to the HDBs. The 60:40 ratio
exhibits best IS while the ratio 70:30 exhibitedthe least. The plywood has an IS mean of 50.00
KPa-m, which is quite high as compared to the39.38 KPa-m value of the 60:40 HDB. The
resistance of plywood against impact can be
attributed to its physical structure since theboard was produced through adhesion of woodply, whereas the HDBs are of homogenous
mixture bonded though heat and pressure.

[6] School, M. H. (2011). Coconut Magic, Local
specialties. Retrieved January 30, 2014,
from msc.edu.ph:
http://www.msc.edu.ph/cyberfair_2008/loc
al_specialties/smpfc.html

339

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

UNCONFINED COMPRESSION TESTING OF CEMENT-TREATEDDEMOLITION MATERIALS IN BASE AND SUB-BASE
APPLICATIONS
Alireza Mohammadinia1, Arul Arulrajah2, Jay Sanjayan3, Mahdi Miri Disfani4, Myint Win Bo5, Stephen
Darmawan6
1,2,3,4
Swinburne University of Technology, Melbourne, Australia; 5DST Consulting Engineers Inc., Ontario,
Canada; 6Geotesta Pty Ltd, Melbourne, Australia

ABSTRACTOne of the major challenges of current world and Australia is sustainable waste management. A major
proportion of waste materials present in landfills are Construction and Demolition materials (C&D) which can bea suitable replacement for high quality quarry material. Conventionally, quarry materials were used as pavementfoundations base and sub-base. With the increasing need of high quality quarry material in various industries andlimitation of resources in many parts of Australia, replacement of traditional road building materials withalternative materials is a major concern from both environmental and economic perspectives.
The geotechnical properties of various cement-treated recycled demolition materials were assessed by
Unconfined Compressive strength (UCS), results of which will be presented in this paper. The experimental
program undertaken also included particle size distribution, modified Proctor compaction. The geotechnicalproperties obtained were compared with existing local road authority specifications for pavement base and subbase applications. The method of sample preparation to achieve repeatability of the results has been discussed.
The effect of curing duration on strength of the specimen has been analyzed. C&D materials were obtained fromrecycling facilities at Melbourne, Australia for the experimental program.
Unconfined compressive tests indicated that cement treated recycled material can be considered confidently
as a pavement base or sub-base material in the field. The laboratory testing results indicate that temperature andhumidity curing plays an important role in the strength development in cement-treated materials.

Keywords: Cement Treatment; Pavement Base; Demolition Materials; Crushed Brick; Secant Modulus

applications have been investigated and engineering
properties of CB blends with other C&D materials
were compared with typical state road authority
specifications in Australia [6]. Stabilization of RAP
materials with cement was attempted in various
research projects to evaluate the effectiveness of
cement treatments in enhancing the strengthparameters and resilient characteristics of RAP
aggregates [7, 8]. Recycled glass was proved to be
applicable for light duty foot-path base application[9-11].
The objective of this research study is to evaluate
the performance of cement-treated C&D materials inpavement base/subbase applications, particularly asa majority of metropolitan road pavements are
traditionally constructed with cement-treated quarry
aggregates. The assessment of the performance of
cement-treated C&D materials, will lead to higher
uptake of this alternative material and enable thediversion of significant quantities of C&D materials
from landfills. The assessment of the performance of
cement-treated C&D materials will also result inincreased confidence in the usage of these

INTRODUCTION
Construction and Demolition materials (C&D)
account for a major proportion of the wastematerials present in landfills in Australia.
Developing a reliable technique for the evaluation ofthese reclaimed products as a base/sub-base material
will increase level of confidence within industry
regarding in-service performance of the recycledmaterial and will result in a higher uptake ofrecycled materials in urban areas where cement
treated sub-base pavements are commonly used.
Reusing recycled materials will lead to lower carbon
footprint from construction process, as using C&D
materials have significant carbon savings compared
to extracting virgin quarried materials [1, 2]. A
considerable portion of waste materials presented inlandfills worldwide contains C&D materials.
Granular stabilization of unbound C&D materials
such as RCA without any cementitious binder has
been investigated in recent years in pavement andfootpath applications [3-5]. The potential use of
crushed brick blends in pavement sub-base systems
340

GEOMATE- Brisbane, Nov. 19-21, 2014

found to be non-plastic. Since RAP has less than 5%fines fraction, hydrometer test was not conducted on
this material. The gradation of RCA and CB moved
to the left which shows the breakage in aggregates
due to compaction effort. However, RCA gradation
after compaction was not significantly alteredcompared to CB which shows RCA aggregates arestronger in nature than CB aggregates. On the other
hand, gradation of RAP aggregates after compaction
moved to right which is due to bitumen content of
the RAP material causing the small aggregates toattach to each other during the compaction. Sieve
analysis tests were conducted on materials obtained
from three separate stockpiles of each C&D material
obtained from the recycling site for consistency
purposes. The minimum amount of 3 kilograms was
sieved and the particle size distributions were plottedfor each of the tested C&D materials [13]. A
hydrometer was used to determine the particle size
distribution for particles finer than the 75µm sieve[14].
Australian Department for Transport, Energy andInfrastructure suggested static compaction ofmaterial for preparing samples which is anappropriate technique to prevent the horizontal
cracks along the layer interfaces for aggregates andincrease possibility of repeatability of UCS samples[15]. MDD obtained from the modified compaction
method was used to calculate the required mass tofill the known volume of mould in order to optimise
the advantages of static compaction. Split
compaction mould of 100 mm diameter and 202 mm
length with a collar was used to facilitate the sample
extrusion. Samples were compacted under constantpressure of 12.5 MPa in eight layers (with the
thickness of 25 mm) with the OMC obtained frommodified compaction curve to achieve the target
density.

alternative low carbon materials by end-users,
contractors and design consultants alike.
MATERIALS AND METHODS
C&D materials comprising were collected fromtwo different recycling facilities in Melbourne,
Australia. The C&D materials which wasinvestigated in this research are crushed brick (CB),recycled concrete aggregate (RCA) and Recycledasphalt pavement (RAP), with a maximum particle
size of 20 mm. The laboratory program to determine
the engineering properties of CB, RCA and RAP
comprised particle-size distribution, hydrometer,
Atterberg limits, water absorption, particle density,
flakiness index, foreign materials content, organic
content, Los Angles abrasion, pH value, modified
compaction, Unconfined Compressive Strength(UCS) tests. The characterization tests were initiallyperformed to determine the properties of untreated
C&D materials and also when treated with General
Portland (GP) cement. The Strength and stiffness
development of the materials due to cementtreatment was studied later by undertaking UCS.
Fig 1 shows the particle size distribution of C&D
materials considered in this study before and after
compaction. The particle size distribution curves of
the untreated C&D materials were determined fromsieve analysis and hydrometer tests. The particle size
distribution plots were compared with upper andlower bound limits specified by the local state roadauthority [12].
The particle size distribution curves of theuntreated C&D materials were determined fromsieve analysis and hydrometer tests. CB has thefinest gradation between the three tested C&D
materials followed by RCA and RAP. The fines
content of the materials are low and the fines were

Fig. 1

Particle size distribution plots for C&D materials.
341

GEOMATE- Brisbane, Nov. 19-21, 2014

material to evaluate the rate of increase in strength.

Typically, achieved densities of compacted
materials were more than 95% of MDD. The surfaceof each layer was scarified before adding thematerials for next layer to provide interlocking
between the layers and to minimize the possibility ofhorizontal cracks in the specimen. The advantage ofusing the split mould, rather than open ended
compaction mould was that the sample could be
extracted from the mould intact with no scratches on
the sides, leaving a smooth area to install local onspecimen measurement devices [3].
UCS tests were conducted on samples compactedwith the aforementioned split mould under static
loads to ensure the specimens were homogenously
compacted and were not damaged during removal
and parallel end faces were maintained [16-18].
UCS test were performed on untreated C&D
materials and materials treated by 2% and 4% of GP
cement. The cement dosage in this study was limited
to maximum of 4% by weight due to economic
considerations of road construction.
In order to ensure that aggregates are fully
soaked, materials are mixed with water and cured for
12 to 24 hours (based on material type) in room
temperature before compaction. The cement ismixed with the respective C&D material prior tocompaction. This will ensure that there is enoughfree water for hydration process and there would not
be any loss of moisture due to water absorption. The
moisture content of the material was determined
immediately after compaction from the remaining
mix and also after performing UCS tests. The
cement-treated samples were cured in a fog chamber
which maintained the humidity approximately 97%
to 99% and at a chamber temperature of between
19°C to 22°C. Curing durations of 1 day, 7 days and
28 days were selected to evaluate the effect of curing
on strength development.

Table 1 Basic geotechnical properties of untreated
C&D materials
Geotechnical Properties

CB

RCA

RAP

MDD* (Mg/m3)
OMC† (Mg/m3)
G s (Mg/m3)
USCS‡
pH
Organic content (%)

1.99
11.38

1.96
12.49

2.06
6.59

2.65

2.67

2.61

GW
10.92
1.72

GW
11.85
3.07

GW
9.79
5.15

Foreign material content (%)

1.8

2.9

0.5

Flakiness index
L.A. abrasion loss

25.90

16.44

10.63

35.47

30.80

20.81

*Max dry density†Optimum moisture content‡Unified Soil Classification System

RESULTS AND DISCUSSION
Geotechnical properties of the untreated C&D
materials are presented in Table 1. The pH values
indicate that the C&D materials are alkaline bynature. The foreign material content of the C&D
materials were visually assessed. RCA comprised of
1.2% CB material and 1.4% RAP material by weight
and a very small fraction of other foreign material
such as glass, wood and gypsum. CB contained up to
70% brick component, with the balance proportions
comprising predominantly of RCA and less than 2%of other foreign materials. RAP contained less than
1% of foreign material.
UCS results for C&D material are presented in
Fig 2, Fig 3 and Fig 4. Although only the 7 day
curing period of UCS value is specified by the local
road authority specification [19], the 28 day curing
period tests were undertaken as an extra measure to
determine the strength of the cement-stabilized C&D

Fig. 2 a) Development of strength in CB withcuring time and cement dosage, b) 28 days Stressstrain curves of CB stabilized with 2% and 4%
cement.
Fig 2a shows the increase in strength propertiesof CB with curing time for 2% and 4% cement.
Substantial increases in UCS values are evident
between the cement-treated C&D materials
342

GEOMATE- Brisbane, Nov. 19-21, 2014

compared to the Control materials. It can beobserved that the dominant increase is happening
during the first 7 days and the strength development
moderates significantly after the first 7 days ofcuring. Fig 2b shows the stress strain curve of 28days treated CB with 25 and 4% of cement. The
same strength development chart for RCA an RAP ispresented in Fig 3 and Fig 4 respectively.
The hydration process was found to progresswith time, creating a stronger bond between theaggregates, which leads to improvement inunconfined strength. Also it should be noted thathigher cement content will increase the strength ofbond between materials and will lead to higher UCS
value. It is evident from the results that the hydration
process slows down with time. In other words, theUCS starts to increase at a rapid rate at the
beginning of the curing period and then starts tolevel off after 28 days. RAP was found to performbetter than RCA and CB in all cases with the same
cement content and under the same curing duration
while RCA showed higher strength values comparedto CB.

The high strength results for RAP indicates that
RAP used in this study was stronger and more
durable than the RAP materials previously reported.
This suggests that results of strength tests are reliant
on the source of RAP.
Loading stiffness of material can be calculated
from UCS test. E 50 is the secant modulus at 50% of
final strength and can be used for numericalanalyzes. It can be observed from Fig 2b, Fig 3b andFig 4b that there is an initial phase of stress strain
curve that shows a moderate gradient due to sittingpressures. This is due to swelling of sample incuring period. In this delay phase, a considerable
amount of strain will yield a very small increase inaxial stress. The sharp increase in axial stress will
start afterwards which is an indication of young
modulus. The corrections for the initial lag phasehave been done on the stress-strain graphs forcalculation of secant modulus (E 50 ). The procedureof this correction is as stated in CBR test [20]. It is
worth mentioning that the samples failed at a
maximum of 1.6% strain and show a rather rigid
behavior with cement treatment.

Fig. 3 a) Development of strength in RCA
with curing time and cement dosage, b) 28 days
Stress-strain curves of RCA stabilized with 2% and
4% cement.

Fig. 4 a) Development of strength in RAP withcuring time and cement dosage, b) 28 days Stressstrain curves of RAP stabilized with 2% and 4%
cement.
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GEOMATE- Brisbane, Nov. 19-21, 2014

Fig 5 shows the increase in E 50 due to curing
period for 2% cement treated C&D material. It canbe observed that secant modulus increases
significantly during the first 7days. The 28 days
stiffness of CB and RCA are very close to 7 days
stiffness which implies that the these material reachto a significant amount of final stiffness after 7 daysof curing. RAP is a moderately softer material incomparison to RCA due to bituminous presence
among the aggregates. It can be observed that theincrease in secant modulus continues after the first 7
days of curing significantly. This can be due toexistence of free water in porous voids of RAP
which will lead to growth of hydration process of
cement in RAP, leading to a stronger bond between
the aggregates. However, in case of CB and RCA
the free water is absorbed by the aggregates, whichslows down the hydration process. Comparing Fig
4a with Fig 5 shows that extra curing time wouldn’t
help in development of shear strength in RAP
significantly, but it will lead to increase in stiffnessof RAP. It can be concluded that extra curing periodof RAP can develop fatigue properties of RAP.

CONCLUSION
The geotechnical properties of cement-treated
C&D materials were evaluated to assess theirperformance in pavement base and sub-baseapplications. The effect of curing duration on thestrength of the C&D materials was analyzed for the
UCS.
Based on the UCS results, RAP was found torequire 2% cement and either 7 or 28 days of curing
to meet the local road authority requirements while
RCA and CB required 4% cement with 28 days ofcuring. RAP was found to have more strength than
RCA and CB in all cases with the same cement
content and under the same curing duration while
RCA was stronger than CB. This can be attributed tothe presence of bitumen which results in RAP
aggregates having higher UCS strength than theother C&D materials for both the untreated andcement-treated scenarios. Initial dry density of RAP
aggregates makes the initial strength of untreated
RAP samples high.
This research study indicates that cementtreated C&D materials are viable construction
materials for cement-treated pavement base/subbase
applications. Their usage in pavement base/subbase
applications would significantly lower the carbon
footprint for future road constructions [21].
ACKNOWLEDGEMENTS
This research was supported under Australian
Research Council’s Linkage Projects funding
scheme (project number LP120100107).
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Fig. 5 Development of secant modulus (E 50 ) in
C&D material stabilized with 2% cement due tocuring time.

Fig. 6 Development of secant modulus (E 50 ) in
C&D material stabilized with 2% cement due tocuring time.
344

GEOMATE- Brisbane, Nov. 19-21, 2014

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N. Geotechnical characteristics of recycled crushed
brick blends for pavement sub-base applications.
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[9] Disfani M, Arulrajah A, Suthagaran V, Bo MW.
Shear Strength Behaviour of Recycled GlassBiosolids Mixtures. 62nd Canadian GeotechnicalConference. 2009;Halifax, Canada.
[10] Disfani MM, Arulrajah A, Suthagaran V, Bo
MW. Geotechnical characteristics of recycled glassbiosolid mixtures. 2009. p. 201-4.
[11] Wartman J, Grubb DG, Nasim ASM. Selectengineering characteristics of crushed glass. Journalof Materials in Civil Engineering. 2004;16(6):52639.
[12] VicRoads. SECTION 812 - CRUSHED ROCKFOR PAVEMENT BASE AND SUBBASE.
Contract Documents, VicRoads2011.
[13] Standards Australia. Method for sampling andtesting aggregates - Particle size distribution bysieving. Australian Standard 1141.11. Sydney,
Australia: Australian Standard; 1996.

[14] ASTM. Standard test method for particle-size
analysis of soils. ASTM Standard D422 - 63. WestConshohocken, PA: ASTM International; 2007.
[15] DTEI. Resilient modulus characterisation of
granular unbound pavement materials. Adelaide,
Australia.: Department for Transport, Energy andInfrastructure (DTEI),; 1991.
[16] ASTM. Standard Test Method for UnconfinedCompressive Strength of Compacted Soil-Lime
Mixtures.
ASTM
Standard
D5102
West
Conshohocken, PA: ASTM International; 2009.
[17]
Standards
Australia.
Supplementary
cementitious materials for use with portland andblended cement, Part 1: Fly ash. AS-358211998.
[18] Standards Australia. Soil compaction anddensity tests - Determination of the dry
density/moisture content relation of a soil using
modified compactive effort. Australian Standard
1289521. Sydney, Australia: Australian Standard;
2003.
[19] VicRoads. SECTION 815 - CEMENTITIOUS
TREATED CRUSHED ROCK FOR PAVEMENTSUBBASE Contract Documents, VicRoads,2013.
[20] ASTM. Standard Test Method for CBR(California Bearing Ratio) of Soils in Place. In:
ASTM D4429 - 09a, editor. West Conshohocken,
PA: ASTM International; 2009.
[21] Arulrajah A, Ali MMY, Disfani MM,
Piratheepan J, Bo MW. Geotechnical performanceof recycled glass-waste rock blends in footpath
bases. Journal of Materials in Civil Engineering.
2013;25(5):653-61.

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Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

RECENT FOAMED BITUMINOUS STABILISATION WORKS IN
QUEENSLAND

1,3

Lokanantham R. Logitharan1, Kathirgamalingam Somasundaraswaran2and Jothi M. Ramanujam3
Department of Transport and Main Roads, Queensland; 2 University of Southern Queensland, Queensland
ABSTRACT

Adapting foamed bitumen stabilisation is considered as the most cost effective approach in Queensland to expedite
the rehabilitation works, especially after the major flood devastation in 2011. This paper presents the key changes
made as well as the recent practices adapted during a road rehabilitation work to increase the return from theinvestment. In this process, initially, the designed width for subgrade lime stabilisation has been modified tominimize the moisture entry into the pavement. The dry modulus, three days soaked resilient modulus and retain
modulus were used to identify the suitable base material for construction. In addition, a trail site was used to
examine the bulking effect on base layer when adding lime as secondary agent, which helped to estimate the exact
depth for foamed stabilisation. A few innovative techniques such as a two-layer compaction to effectively
condense stabilised subgrade, was used to improve the quality of the outcome were also highlighted.
Keywords: Foamed bitumen, Flexible pavement, Pavement Rehabilitation, Stabilisation

currently foam bitumen stabilising is known as anenvironmental friendly, economical and innovative
treatment for rehabilitation works compare to theother form of stabilisation works.
This paper discusses the steps taken from thedesign stage to completion of a rehabilitation work toa flexible pavement project in Oakey, Queensland.
Specially, after the project was awarded to thecontractor, the expertise from both client andcontractor revisited the design, material specificationand construction process to improve the quality of theoutcomes. Thus, the aim of this paper is to highlightthe technical changes made, analysis and testing
adapted the follow-up actions undertaken on site toincrease the return from investment.

INTRODUCTION
In Queensland, foam bitumen stabilisation (FBS)
is becoming popular and widely accepted as a longterm economic treatment for the base and sub-baselayers in road rehabilitation works. Although thefoam bitumen stabilisation method was introduced inAustralia in 1960s, it never really gained acceptance
until 1990s with the introduction of new reclaimers
and the use of more experienced contractors [1]. In
1997, the first foam bitumen works was carried out inQueensland; however it is still new area for the roadengineers especially when it comes to identificationof suitable material as well as filed testing that need
to be carried out during construction to ensure quality
outcomes. More specifically, a full depth reclamation
works using foam bitumen still require a goodknowledge-based approach and better specifications
to achieve a quality outcome.
Traditionally, the most of the Queensland roads
have been rehabilitated using the locally available
material together with few (2~3%) adhesive agents. It
was found that adding cement for unbound pavementchange the properties of the pavement layer andbecome as bound/rigid pavement. When unboundgravels are strengthened by cementing, the particles
that were stuck together raised a significant tensile
strength, resulting in an unavoidable shrinkage effect,hence causing cracking of the pavement [2]. In
contrast foamed bitumen provides a much more
flexible pavement layer which reduces shrinkage
cracks when using lime as secondary additive.
Foamed bitumen stabilised pavement also act as awater proof layer and improve the plasticity and thestiffness of the unbound pavement material. In
consideration of similar advantages into account,

FOAM BITUMEN STABILISATION
Foamed bitumen is produced by injecting air andwater droplets under high pressure into hot bitumen.
In this process, as the water turns into steam, bitumenchanges from the liquid state into foam [3]. When thisfoamed bitumen mixed with the suitable pavement
materials it then helps to coat the fine particles within
the material to make a bond between larger particles.
This bonding is also sometimes referred as welding
action between pavement partials.
Advantages of using FBS
The advantages and disadvantages of using foam
bitumen stabilising compared to other type ofstabilising techniques are highlighted by several
researchers [6][7]. The key advantages of using FBS
are listed below:

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GEOMATE- Brisbane, Nov. 19-21, 2014

• Significantly reduce or eliminate shrinkage cracks• Increased resilient modulus for flooding/water
entry areas• Strong and flexible layer against fatigue failure• Increased shear strength and reduced moisturesusceptibility of granular material• Reduced binder and transportation costs
compared to other type of cold mixing.
• Foamed bitumen layers can be constructed inadverse weather such as light rain without
affecting any conditions for workability.
• Energy conservation due to the only heating
bitumen when stabilizing (no need to dry or heat
the material)• Reduced environmental and other side-effects
resulting from the evaporation• Reduced wastage as the existing material can beused with the imported material• No risk of binder run off or leaking• Saving in curing time as the traffic can be allowed
as soon compacted
Key requirements
The success of a foamed bitumen stabilisation ishighly dependent on material characteristics,
moisture content of the existing/imported material,
bitumen class, characteristics of the foaming agent,tight quality process during the construction
including use of correct equipment/machineries.
Other factors which affect foaming properties ofbitumen are foaming temperature, anti-foaming
agents, foaming water content and bitumen chemicalcomposition [4].
It is noted by several studies that when bitumen ata stage of foamed, it doesn't completely coat all
aggregate surfaces but has an affinity for finerparticles, those of 75 microns or less. This action withthe fine particles forms a mortar or glue which
effectively bonds with the other pavement materials
together [5]. It has also been highlighted that thequality of fine is critical rather than the quantity.
Therefore expected quality and chemical property of
the fine particles should be well specified from thelaboratory testing methods.
When foamed bitumen breaks and mixes with tiny
particles the moisture contents within the tiny
particles influences the strength of the created bond
between the particles, so it is necessary to maintain asuitable moisture content for this purpose. If theimported/existing material for foamed bitumen works
contain too much moisture or clayey then particles
create lumps before the application of bitumen andfoam will not be distributing evenly to create a strong
bond. A moisture level that is too high lengthens thecuring time, reduces the strength and density of thecompacted mix, and reduces the coating of theaggregates [6]. On the other hand, insufficientmoisture reduces the workability of the mix which
could result in inadequate dispersion of the binder.
Therefore optimum moisture content should bemaintained throughout the construction process.
Time required to mix the foam with the pavement
material is critical in foamed bitumen works.
Producing foam by adding water and air to a hot
bitumen is an easy task than maintaining the foamed
stage. Therefore appropriate expansion ratio and halflife should be used during the construction process.
Expansion ratio is defined as being the ratio between
the maximum achieved volume of the foamed
bitumen and the original volume of the non-foamed
bitumen [8]. Half-life of the bitumen is defined astime taken for the volume of foamed bitumen to settle
to half of the maximum volume [7]. The type of foam
most effective is one which has an expanded volumeof 10 to 15 when injecting one to two percent of water
to the hot bitumen[12].
Wirtgen Stabiliser (WR 2400, WR 2500) with themixing chamber in the middle is the most suitablemachine currently available for foamed bitumen
stabilising work [13]. The selection of the roller androlling pattern is critical for compaction works.
Experienced final trim operator is critical to provide
quality product within the tolerance specified in the
MRTS.
PROJECT DISCRIPTION
The project is located on Oakey-Pittsworth roadwhich is 40 km from Toowoomba. This two-lane
undivided highway segment with 2.6 km section has
been identified for rehabilitation works. This section
was severely affected during the 2011 and 2013 flood.
Since its location subject to floods, a proper treatment
is required to stand against future flood/rain events.
The construction works had been awarded to
RoadTek.
Proposed Design
The Department of Transport and Main Roads(DTMR) has carried out the initial design where
mechanistic design approach was carried using apavement design software namely CIRCLY. The
following traffic and materials parameters were usedin the preliminary design: Maximum vertical design
modulus for lime stabilised layer was 200MPa;
Maximum design modulus for foam bitumen layer
was 1200 MPa; Bitumen content for foam was 7% byvolume; Strength of post cracked phase was 500MPa
with Poisson’s Ratio of 0.35, Project Reliability was
90%, Design Traffic was 1.8 x 106 ESAs, and otherdesign loading and subgrade rutting criteria as per
Austroads 2004.
Initial design was carried out in 2012 during thepreconstruction stage. The initial design considered
the use of existing base and sub-base pavement347

GEOMATE- Brisbane, Nov. 19-21, 2014

material or replacing it with suitable material. During
the initial stage the moisture condition of existing
pavement was considered critically when proposing
mix design for foamed bitumen. As a result, it
proposed to replace unsuitable material (250mm top)with imported Type 2.5 material as per specification
given in Main Roads Technical Specification(MRTS) [11]. Further lime stabilising (300mm) was
proposed to improve the strength of subgrade toeliminate the undesirable characteristics of the
expansive soil. Lime demand test was conducted, andit was proposed to use 9% by mass that is 40kg/m2
hydrated lime to stabilise the subgrade. The initial
proposed FBS layer design was to use 3% bitumen
and 2% General Blend cement (GB) by mass as
primary and secondary stabilising agents respectively.
MODIFICATIONS FOR IMPROVED QUALITY
After the contract was awarded, the followingchanges were undertaken jointly by the client and thecontractor to improve the quality of the works. In thisprocess, the team has revised initial design, identified
proper sources for material and implemented
additional control measures to ensure the quality
outcomes from foam bituminous stabilisation
process.
Changes to subgrade design
Subgrade of this rehabilitation work has been
identified as expansive soil. Expansive soil will
expand during the wet season and shrink in dry
season; therefore the base layer would fail on the
expansive subgrade if not properly treated. In
Queensland, lime is normally applied to modify
expansive soils to improve strength characteristics,
because lime improves the plastic properties,
flocculating particles and it allows drying thematerial. In addition lime stabilising increases load
bearing capacity and achieves long term strength
retention [13]. Initial design for this work was to use
lime (9% by volume) to stabilise the subgrade. The
lane width of 4.8m (including median width) for a
direction is proposed for subgrade stabilisation,
however the design has been changed to stabilise 6m
wide to include the additional 1.2 m section below theshoulder. This is to reduce the lateral moisture
movements to the pavement. While expanding thewidth along the road it was noted that some of thesections contained small rocks and sandy soil which
has to be treated with suitable process. The section
encountered rocks have been treated by removing
rocks. The area containing sandy soil had been treatedby mixing with expansive soil. Although, initially it
was decided to use triple blend, in order to maintainconsistency across the road, later it has been decided
to cross blend and stabilise the layers with lime. The

lime demand test has been carried out to identify thelime requirement (6% by mass).
Material identification from mix design
With the foamed bitumen stabilisation it isessential that adequate fines must be available for thebitumen to bind with [7]. As per the material
classification in Main Roads Technical Specification(MRTS), Type 2.5 and Type 2.3 material with ‘C’
grading can satisfy the requirement of a foamstabilisation works [11]. Therefore, undertaking
initial investigation on available materials as well as
carrying out mix design out of these materials was
identified as critical steps.
A number of samples were prepared for varying
amount of primary and secondary stabilising agent.
The samples were prepared for a total of 16 different
type of materials. These materials were taken fromthree different quarries. The following key tests werecarried out in Herston Laboratory, Queensland(DTMR laboratory) to identify the suitable material
for this rehabilitation work:• Indirect tensile test to identify initial modulus
after three hour curing at 25°C. A minimum
expected strength of 700 MPa was set as target
according the specification [13].
• Dry modulus was obtained after placing thespecimen for three days at 40°C. Previously dry
modulus were obtained after curing the sample at
60°C. However it has been modified considering
softening point of the bituminous binder whichallows its mobilisation and possible absorption
into the aggregate [12]. Therefore currently, theDTMR, Queensland has been using 40°C as
curing temperature.
• Three days soaked modulus was obtained after
specimens soaked in water in vacuum chamber for
10 minutes at maximum pressure of 95 kPa.
When it comes to material selection, MRTS
recommends the use Type 2.5 material as it canachieve high soaked modulus in mix design;
however, there is no specific requirement for aminimum CBR value for type of materials that can beused. Therefore, the requirement for this project has
been modified to achieve a minimum strength of CBR
45 for the base layer material.
Testing results revealed few issues whenidentifying the right material as the field soaked
modulus was not achieving the minimum
requirements. However this paper is only
concentrating the construction issues. Therefore thedetail technical issues will be discussed in elsewhere.
In overall it was found that using material having
finer particles increase the soaked and retain modulus
more than material having more coarse particles.

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GEOMATE- Brisbane, Nov. 19-21, 2014

• Primer sealing, allowing traffic and monitoring• Spray sealing

Changes to base layer design
Adding 2 % cement was proposed as secondary
stabilising agent for the foamed bitumen work.
Experience from as a similar site on the Warrego
Highway showed that using cement as secondary
agent would results in crack failures. The actual
reasons for the failures are currently underinvestigation. Therefore, experts argued that using
lime instead of cement would defiantly increase
working time. Furthermore, using lime has thefollowing advantages [7]: stiffens the bitumen binder,
acts as anti-stripping agent, increases the initialstrength of the material, and has a longer working
time (up to 24 hours if need to rework). Therefore
with the consultation of design engineers, lime has
been proposed as a secondary agent.
DETAIL OF CONSTRUCTION PROCESSThe conduction works in this entire job has beenequally divided into four sections, namely Lot 1,
Lot 2, Lot 3 and Lot 4, as shown in Figure 1. This
segmental approach allows a continuous passage oftraffic in one lane with proper traffic control in place.
Based on the test results, Type 2.5 material was usedfor Lot 1, Lot 3 and Lot 4, and Type 2.3 material wasused to Lot 2.

1300m

Lot 4 : Type 2.5
Lot 3 : Type 2.5
roadbase material roadbase material
3% Bitumen and 3% Bitumen and
2% Lime by Mass 2% Lime by Mass

1300 m1300 m

Lot 2 : Type 2.3
roadbase material
3% Bitumen and
2% Lime by Mass

Section B
Section A

1300m

Lot 1 : Type 2.5
3% (B) and 2% (L)Pittsworth End (Chinage 20200)

Oakey End (Chinage 17600)

Fig.1 Site plan for segmental construction
After clearly dividing the lot’s activities into theproject plan, the following the construction works
were carryout for each lot, separately:• Removing 250mm unsuitable material using
profiler• Lime stabilising 300mm underneath foam
bitumen layer• Import 250mm layer of new base material• 250mm depth of foam bitumen stabilising

Subgrade stabilisation
Initially, an entire lot (eg., Lot 1) was milled out
using profiler and existing material and wasstockpiled away from site to use it for another projectby the contractor. The lime stabilising method has
been used to improve the subgrade. The lime demand
test has been carried out and mix design showed thesubgrade is to be treated with the lime at the rate of
40 kg/m2, which is equivalent to 9% hydrated limeby mass. Initially, the construction process has beenplanned to use 13~14 kg/m2 spread rate in three runs.
Matt/tray test has been carried out on-site to ensure
the spread rate. However it was found that spreader
operator encountered problem on maintaining
consistence spread rate. As the hydrated lime is addedwith water it turned out to be bonded so the spreadrate had been reduced to 10-11 kg/m2. Therefore
number of run increased to runs which has been
increased the cost and the project duration.
Design has also been modified on site byincreasing stabilsing width by 6m instead of original
design of 4.8m for one direction. Each Lot has beenfurther divided to five 260m sections to make thesafer construction process (example, Sections A & B
in Figure 1). Hydrated lime was spread for eachsection of 260m length, and subsequently mixedusing stabiliser in three strips: two 2.4m sections(width) and one 1.2m section to achieve a total of 6m
width. The lime stabilisation work has been carriedout in two days in two adjacent sections (say Sections
A & B). For example, subgrade lime stabilisation
took two days in the following sequences: day 1 for
3 dry run in section A and 2 dry runs in Section B,
and day 2 for 1 dry run in section A and 2 dry run insection B followed by wet run. The water truck wasconnected with stabiliser and proceeded with the wet
run to both section A and section B.
The Section A and Section B were left over thenight to cure and after second day sand replacement
tests were carried out in these two sections to checkthe subgrade density with the required specification.
The MRTS-07A clause 8.4.16 [11] specifies theminimum requirement for the rollers to be used.
Accordingly, 21Tonne Smooth drum and Padfootrollers were used to compact 300mm lime stabilised
layer. However the compaction at site has been
carried out in two stages.
In this process, after completing lime
applications, mixing and wet run the 150mm depth ofmaterial was removed using grader and bottom layer(150mm) was compacted using a 22 Tonne Padfootroller. This initial layer was compacted by eightpasses with full vibration. The next 150mm layer
brought back and compacted using the same roller
through 6 passes with full vibration. This segmental
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GEOMATE- Brisbane, Nov. 19-21, 2014

compaction process reduces the risk of failure,especially when not achieving the required ‘Relative
Dry Density (RDD) of 97% (standard compaction) as
specified in MRTS 11.07A clause 8.5.2 [11]. Once
subgrade (300mm) was compacted, a grader was used
to cut all Padfoot marks and trim the section within
the tolerance specified in MRTS 11.07A [11].
Finally, smooth drum followed by multi tyred roller(12 Tonne) compacted the trimmed sections (3 passes
with full vibration and three passes with half
vibration). The sand replacement tests were carriedout together with Dynamic Cone Penetration (DCP)
tests on a few sections to ensure the requiredcompaction. Both results show a satisfactory results,
therefore at a later stage, DCP testing process has
been adapted to speed up the construction process.
According to the design, the stabilised subgrade
should have a minimum California Bearing Ratio(CBR) value of 10. The test results show an average
CBR values between 20 and 30.
Foamed bitumen stabilisation
As soon as the completion of subgrade works andgranular material (identified from the mix design)
was delivered to the boxed out sections, the required
tip rate for delivering material was calculated andprovided to the supplier.
The material was delivered to the site with 65% to
70% of moisture content. As the success foam
bitumen stabilising is heavily dependent on the
moisture content of the material, the contractor has
been informed about the high penalty for delivering
material outside the tolerance level for the moisture
content. As the materials were delivered, the moisture
content has continuously been monitored closely onsite. Then material were spread and compacted to100% Relative Dry Density (RDD) as per therequirement of MRTS11.05 [11]. Then the section
was compacted using a smooth drum (22 Tonne) with
12 passes and trimmed to the required level prior tocommence the FBS. Once the section was trimmed to
the required level the roller was used to tighten thematerial with back watering process using a water
truck. The compaction process was carried out toensure the section got the right amount of material (bymass) prior to commencing stabilising works.
A local contractor was appointed to supply the hotbitumen to the site, and the contract includes: load,cart, heat and supply at the required temperature. The
bitumen has been supplied from Pinkinbar BP plantin Queensland, and it took 3 hours to transport thebitumen to the site from the plant.
The Class 170 bitumen has been loaded at 160
degrees. It is normal that when the bitumen is loaded
into a road tanker, the temperature dropped by about
5°C-10°C and continues to fall by a further one or two
degrees per hour while in transit [14]. In
consideration of these facts, as soon as the bitumen

arrived on site the supplier starts to heat the bitumen,
and it generally took an average of 3 hours to reach180 degrees (heating rate 10 degrees per hour). When
refining/transporting bitumen, anti-foaming agent(e.g. silicone oil) was added to reduce surface tension,as per guidance given in Shell Bitumen Handbook[4]. As the success of the foam bitumen stabilisingrelies on half life time and expansion ratio, thefoaming agent (Terric 311)was added 30 minutes
prior to the stabilising, ie., a 100 liters (0.5% by mass
: ie 0.005 x 20,000 kg) of foaming agent was added
for each 20 Tonne bitumen tanker.
Prior to commence foam bitumen stabilising(adding bitumen) the secondary agent (hydrated lime)
was spread and mixed with the base materials. The
use of hydrated lime helped to maintain the required
right moisture before commencing the foam bitumen
stabilisation. The quantity of the hydrated lime varies
with the density of the road base material. As per thedesign, for the sections A & B, an application rate of
11.5 ~ 12 km/m2 hydrated lime was used on site (~2%by mass). In this process, lime was dropped in two
2.4 m run to achieve 4.8m width. The Matt/tray test
was carried out to ensure the drop rate is achieved as
per the design requirement. As soon as spreader
dropped the lime the water truck connected with thestabiliser and commenced the mixing the lime with
granular base material. The moisture was controlled
when mixing hydrated lime with granular material. In
the construction process of FBS, the DTMR has
introduced a term “Lower Reference Level (LRL)”
which is the reduce level or bottom level of the foam
bitumen stabilised layer. The material has been mixed
to a depth 30mm above the lower reference level (inthis case 220mm instead of 250mm) to ensure thestabliser is not mixing subgrade with the existing basematerial when mixing lime.
A smooth drum
(22Tonne) compactor followed the stabiliser andprovide two passes with the full vibration and thegrader was used to correct any irregularities on themixed surface to ensure the surface is smooth justbefore staring the foam bitumen stabilisation. Thenthe trimble was used to check the surface level at
different local points.
It should be noted as soon as add the lime, thematerial will bulk (about ~30mm) due to the changeof volume, not the mass. Therefore a trail section was
done to identify the bulking depth due to the lime
stabilising. Then bulking depth was added to thedesign depth to identify the stabilising depth for foam
bitumen stabilisation. Hence the final stabilising
depth was calculated to include about 20mm ofstabilised subgrade to ensure the compaction
achieved was well below the lower reference level. In
this case the full depth of foam bitumen stabilising
was calculated to be 300mm as follows: 30mm
bulking + 250mm actual stabilising + 20mm
subgrade.

350

GEOMATE- Brisbane, Nov. 19-21, 2014

Foam bitumen stabilising continues straight after
mixing the lime, and Wirtgen WR 2500 was used for
foamed bitumen stabilizing (see Figure 2). The
injection system in WR2500 consists of a
microprocessor-controlled metering unit, an eccentricpump and an injection bar with 16 nozzles andfeeding device. The pump delivers the liquid agent(e.g. water) from a tanker truck to the injection bar[8]. Test jet system of the Wirtgen 2500 was used toensure correct bitumen expansion and half-life time
during the foam bitumen stabilisation work.

traffic was not allowed on the stabilised pavement
until the primerseal was complete and 24 hours tocure before allowing traffic. In this project Class 320
bitumen and 10mm aggregate was used forprimerseal.
Initially, a Double/Double PMB seal with
14/7mm aggregate was designed for full width as
final seal. However, the experts commented thattransverse cracks might be appeared if a fabric was
not used. In addition, Fyfe (2010) has highlighted asimilar modification to the design, and the following
were documented as justified advantages when using
fabric seal: waterproof layer, bridging shrinkage
crack, acts as a stress absorbing interlayer, and pro
long surfacing life span [15]. Therefore, in thisproject, Type II-B geotextile was used. Finally, afabric seal with tackcoat was carried out on top theprimerseal before a double/double seal with 14/7 mm
aggregate.
CONCLUSION

Fig.2 Foamed Bitumen mixing process [5]Previous works show that the reducing the depthof the stabilisation shorten the life of the pavement.
Therefore, depth of the stabilising layer is important
to be achieved to the design depth. Once commence
the foamed bitumen stabilising work the stabilisng
depth was measured using dummy level and Trimble
to ensure the bitumen stabilising has been done to thedesigned depth. Further the temperature wasconstantly checked across the pavement behind thestabiliser to ensure all nozzles are working properly.
The visual inspections were also carried out by
squeezing stabilised material by hand to identify thebitumen has spreaded properly.
Final compaction and trimming
Soon after completing the mixing process, initialcompaction was carried out using padfoot roller(22Tonne) with 6 passes. The project team ensured
that the stabilized pavement achieved requiredcompaction and wasn’t over-stiffening the pavement.
Then a grader cut the padfoot mark, and trimmed thesurface to the required level, followed by it a multirubber tyred roller (24 Tonne) used to bring the final
surface. At all times during the compaction process,it was monitored to eliminate any laminated layer due
to the variation of vibration between layers.
Sealing
The full width spread seal will not commence tillcomplete entire job, but a primerseal was carried out
to protect the pavement from adverse weather. The

After the severe floods in 2011 in Queensland, theapplication of foamed bitumen stabilisation techniquein rehabilitation works has several success stories.
This paper outlines the steps taken to improveoutcomes while rehabilitating 2.6 km section of
Oakey-Pittsworth road, Queensland. In this processof construction the stabilisation width of sub-grade
layer increased, available materials were tested tomaintain the required specification, a suitablesecondary agent as a filler for FBS is introduced, andcontinued testing were undertaken to improve thequality of the outcome.
A highly motivatedcollaborative relationship between DTMR (client)and RoadTek (contractor) provides a good platform
to identify these key changes to improve the quality
in this project. The documented scenarios highlightthe recent approaches that could be applied for similar
construction sites. This project could be considered as
experiment for making changes to the specificationby the road authories.
ACKNOWLEDGEMENTS
Authors would like to acknowledge the client,designers and field staff from Department ofTransport and Main Roads Queensland (Philip
Tweddell, Damian Volker & Belinda Krause),
Regional Program Office 07 (David O’May) and
RoadTek (Jason Dallinger & Kim Hankinson) for us
to provide research opportunity and support throughthe job.
REFERENCES[1] Vorobieff, G & Prestonnenene, N 2004,‘Bitumen Stabilisation – An Australian
Perspective’, NZIHT Stabilisation of
pavements seminar, pp. 1-19

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[2] Wilmot, T & Rodway, B 1999, ‘Stabilised
pavements selecting the additive: cementitious,
Polymer or Bitumen’, Proceedings ofinternational congress on local government
and public works, pp.1-7, < http://www.aust
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[3] Sunarjono, S 2009, ‘Laboratory stiffness
characterization of foamed cold-mix asphalt
using indirect tensile stiffness modulus test’,dinamika Teknik Sipil, Vol. 10, No. 1,pp.1-8.
[4] Read, J & Whiteoak, D. (2003), The Shell
Bitumen Handbook, Fifth Edition. Thomas
Telford Publishing, Thomas Telford Ltd, 1
Heron Quay, London E14 4JD, pp 407 – 412.
[5] Hiways Ltd (2014), Technologies: Foamed
Bitumen Recycling :Pioneering stabilisation
technology in Australiasia and South Pacific.
Available from:<http://www.hiways.com.au/stabilization/technologies/foam-bitumen-recycling> [Accessed 6
Jun. 2014].
[6] Muthen, KM 1998, ‘Foamed Asphalt Mixes –Mix Design Procedure’, Report CR-98/077,
Sabita Ltd. and CSIR Transportek[7] Ramanujam, JM & Jones, JD 2000,‘Characterisation of foamed bitumen
stabilisation’, Road System & Engineering
Technology Forum, Queensland, Australia.
pp.1-23.
[8] Wirtgen 2002, Foamed Bitumen –The
Innovative Binding Agent for Road
Construction, Windhagen,Germany, pp.1-32[9] Bowering, RH & Martin, CL 1976, ‘Foamed
Bitumen production and application of
mixtures evaluation and performance ofpavements’, <http://asphalt.csir.co.za/FArefs/
Bowering%20&%20Martin.pdf>[10] Lylemachinery.com, (2014). Features for
Wirtgen 2012 WR 2500 SK, Available from<http://www.lylemachinery.com/new_vehicle_
features.asp?veh=292478&CatDesc>[Accessed 6 Jun. 2014][11] MRTS 2009, Transport and Main Roads
Technical Specification and Standards[12] Jameson, G 2013, ‘Design and Performance of
Foamed Bitumen Stabilised Pavements:
Progress Report One’, Austroads Technical
Report, AP-T247-13, pp.1-99[13] Wilson,P Ramanujam, J & Neary, A 2012, ‘A
new procedure for lime stabilising pavement
subgrades for Queensland’, Shaping the future:
Linking policy, research and outcomes, Perth,
Australia ,25th ARRB Conference[14] BP Australia Pty Ltd (2007), Bitumen Basis :BP Bitumen Bringing Technology to thesurface, < http://www.bp.com/content/dam/bpcountry/en_au/products-services/bpbitumen/all-pages/Bitumen-basics.pdf>[15] Fyfe, R 2010, ‘Paving fabric seal design andperformance on Australian roads’, 2ndinternational and sealing conferencesustaining sprayed sealing practice, pp.1-31

352

FourthInternational Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

CHARACTERISTICS OF LIME STABILIZED EXPANSIVE SOIL FORCONSTRUCTION OF FLEXIBLE PAVEMENTS
S. Patel1, L.M. Reddy2 and J. T. Shahu3
Assistant Professor, Applied Mechanics Department, S. V. National Institute ofTechnology, Surat, India,
2
Master Student, Applied Mechanics Department, S. V. National Institute ofTechnology, Surat, India,
3
Professor, Department of Civil Engineering, Indian Institute of Technology, Delhi, India,
1

ABSTRACTA large portion of India roughly equal to 0.8 million sq. km, which is about 20% of the total land area, iscovered with expansive soil popularly known as Black Cotton (BC) soil. This soil is considered problematic forroad construction due to the presence of montmorillonite in its mineralogy which is capable of large volume
changes from the dry to the saturated state. In this paper, an attempt has been made to stabilize the problematic
expansive Black Cotton soil with lime for the effective utilization in the subbase course of flexible pavements. A
number of cylindrical test specimens were prepared from BC soil with different lime (0-12%) contents and cured
for 0, 7, 14 and 28 days. The geotechnical properties of different trial mixes, namely, unconfined compressive
strength and resilient modulus were determined. The effects of lime content, curing period and curing
temperature on unconfined compressive strength and resilient modulus were investigated. Different empiricalmodels are proposed to estimate the resilient modulus of soil-lime mixes and model constants are determined.
BC soil stabilized with a minimum lime content of 6% satisfies the criteria recommended by Indian Road
Congress for utilization in subbase layer of flexible pavements.
Keywords: Unconfined Compressive Strength, Repeated Load Triaxial Test, Resilient Modulus (M r )[10]. However, a limited research has been reported
in the literature on the behavior of stabilized
subgrade under cyclic loading.
Singh et al. [12] reported an increase in resilient
modulus value with the addition of lime and class C
fly ash to CL soil cured for 28 days. Solanki et al.
[13] and [14] observed an increase in resilient
modulus of subgrade soils for each of three different
additives, such as hydrated lime, class C fly ash andcement kiln dust. Reduction in resilient modulus
beyond certain amount of lime content was observedin the literature [14]. Ranjan et al. [11] observed anincrease in resilient modulus on addition of lime andcement to three different types of subgrade soils.
With the increase in deviator stress, resilient
modulus of untreated soil decreased and resilient
modulus of treated soil increased [11].
The objective of the present study is to determine
the effect of lime content, curing period and curing
temperature on unconfined compressive strength andresilient modulus of different soil-lime mixes and tocompare different empirical models for predicting
the resilient modulus of soil-lime mixes.
The scope of the work includes conducting aseries of unconfined compressive strength test andresilient modulus test on cylindrical specimens andcarrying out regression analysis on different
empirical models.

INTRODUCTION
India, being called as sub-continent has various
geographical, geological and climatic conditions. In
developing
countries
thesocio-economic
development depends upon the connectivity between
the different parts of the country. India is enrichedwith different types of soils in which more part ofthe country is covered with black cotton soil whichis good for agricultural purpose and in contrary,problematic for construction purpose.
Lime stabilization of black cotton soils waved
back to several centuries in India and is aconventional method in so many countries. Since thepavement structure is subjected to traffic loading it
is necessary to consider the cyclic loading effect inthe design of the pavements. AASHTO [2] hasrecommended the use of resilient modulus in thedesign of pavements.
Resilient modulus (M r ) is defined as the ratio of
deviator stress to recoverable strain. Manyorganizations in the world do not have the necessary
facilities to conduct the resilient modulus test.
Therefore, state agencies and pavement designers
use available empirical models to estimate resilient
modulus of the pavement materials. Various
engineering properties of lime stabilized soil havebeen reported in the literature [3], [4], [7], [9] and353

GEOMATE-Brisbane, Nov. 19-21, 2014

EXPERIMENTAL PROGRAM

Repeated Load Triaxial Test

The experimental program consists ofdetermination of unconfined compressive strengthand resilient modulus of different soil-lime mixes.

Repeated load triaxial test (RLTT) was carriedout on different soil-lime mixes. Cylindrical
specimens of 50mm diameter and 100mm high wereprepared in three different series same as that of
UCS test. The test was carried out in accordancewith AASTHO T 307 [1] method. First, thespecimens were subjected to 3000 loading cycles
during the conditioning phase and then tested for thedetermination of resilient modulus at fifteen
different stress levels.

Materials
Black cotton soil was collected from SVNIT
campus, Surat, India and lime was procured from thelocal market. The different geotechnical properties
of soil as obtained according to Indian Standards
were as follows: sand content = 17.5%, silt content =46.5%, clay content = 36%, specific gravity = 2.7,
liquid limit = 60.3%, plastic limit = 27.2%, plasticity
index = 33.1%, free swell index = 66.7%, optimum
moisture content (OMC) = 20% and maximum dry
density (MDD) = 1.75 g/cc. The soil was classified
as high plastic clay (CH) as per Indian Standard.

RESULTS AND DISCUSSIONS
Unconfined Compressive Strength
Effect of lime content
Figure 1 shows the variation of UCS with lime
content. There is an increase in UCS values withincrease in lime content up to certain extent anddecrease thereafter. The lime content at which thecompressive strength was maximum varies from 6%
for 7 day curing to 9% for 28 day curing period. The
strength gain in BC soil-lime mix is mainly due tothe cementitious reaction which immediately begins
by addition of lime in clay. The calcium ions of lime
react with the silica and alumina present in the soil
and form CaO・SiO 2 ・H 2 O and CaO・Al2 O 3 ・
H 2 O known as C-S-H and C-A-H gel. These
products act as a glue to bind the soil particles
together resulting in a stabilized mass. With anincrease in lime content, the quantity of gel
formation increases, thus increasing the compressive
strength. However, for lime content more than the
optimum value, the lime particles remain unutilized
and simply serve as weak filler in the mix resulting
in the reduction of the strength. Similar variations of
UCS for lime treated soil have been reported inliterature [8].

Unconfined Compressive Strength Test
Unconfined compressive strength test was
carried out on the soil mixed with different
percentages of limes (3%, 6%, 9%, and 12%). First,
soil and lime were mixed in dry state manually andthen water corresponding to the OMC was added
and mixed thoroughly. Next cylindrical specimensof 50 mm diameter and 100 mm high werecompacted in three layers by static press to achieve
the MDD of the mix obtained from modified Proctor
compaction test. Samples were sealed in polythenebags and kept for curing. Specimens were cured inthree different series for UCS test. In first series,
specimens were cured at a temperature of 30ºC for 0,
7, 14, 28 days. In second series specimens were
cured at temperatures of 40ºC and 50ºC for 7 days.
In last series specimens were cured for 3 days at
30ºC and then soaked in water for 4 days before
UCS test. UCS test was carried out by using a
conventional compression testing machine at a strain
rate of 0.6 mm/min.

Effect of curing period
3.0

Figure 2 shows the effect of curing period on
UCS of different soil-lime mixes. UCS value
increases continuously with curing period for all
mixes; however the rate of gain of strength is highduring the initial 7 days but slows down thereafter.
As the pozzolanic reaction is a slow process thequantity of gel formation increases with an increasein curing period, thus resulting in high compressive
strength.

UCS (MPa)

2.5
2.0
1.5
1.0

0 Day

7 Days

14 Days

28 Days

0.5
3

6

9

Effect of curing temperature and soaking

12

Lime(%)

Fig. 1Figure 3 shows the effect of curing temperatureand soaking on UCS values for different soil-lime
mixes. With the increase in curing temperature UCS

Variation of UCS with lime content for
30ºC curing temperature.
354

GEOMATE-Brisbane, Nov. 19-21, 2014

5.0

value increases for all lime contents. Higher curing
temperature accelerates the cementitious reaction
between soil and lime, thus increasing the strength.
The soaked UCS values of the soil-lime mixes were
found to be lower than the unsoaked UCS values.
UCS values of different soil lime mixes at 7 day
curing period before and after the cyclic tests werecompared in Fig. 3. For third series of UCS tests, 7day (3 days curing and 4 days soaking in water)
UCS values of BC soil with 3%, 6%, 9% and 12%
lime were 360, 1480, 1440 and 1310 kPa,
respectively. IRC: 51 [6] recommends a minimum 7day UCS value of 700 kPa for soil-lime mix tosatisfy the strength and durability criteria for use in
subbase course of flexible pavements. BC soil
stabilized with a minimum lime content of 6%
satisfies these criteria. UCS values obtained after
cyclic test was higher than that obtained before
cyclic test which may be due to the rearrangementand densification of soil particles during theapplication of cyclic loads. Similar trends were also
observed for 14 and 28 days curing period. The
variations of UCS values with curing temperature
obtained in this study are consistent with the results
reported in the literature [8].

UCS (MPa)

4.0

2.5

6% Lime9% Lime12% Lime

3.0
2.0
1.0

Before RLTT
After RLTT ---------

0.0
3

6

12

Fig. 3 Variation of UCS with lime content fordifferent curing temperatures at 7 day
curing period.

Resilient modulus (MPa)

140
130

0 Day

7 Days

14 Days

28 Days120
110

σd = 93.1 kPa
σ3 = 34.5 kPa

100
90
80
3

UCS (MPa)9

Lime (%)

3.0
3% Lime

300C
400C
500 C
soaked9612Lime (%)

2.0
1.5

Fig. 4 Variation of resilient modulus with lime
content for different curing period.

1.0

Effect of curing period

0.5
0

7

14

21

Variation of the resilient modulus with curing
period for different soil-lime mixes at a deviator
stress (σ d ) of 93.1 kPa and cell pressure (σ 3 ) of 34.5
kPa is shown in Fig 5. The resilient modulus of all
the soil-lime mixes increases continuously withcuring period. However, the rate of strength gain ishigh during the initial 7 day curing and slows down
thereafter. The amount of gel formation in the
pozzolanic reaction increases with increase in curing
period which binds the soil particles more efficiently
resulting in higher stiffness.

28

Curing period (days)

Fig. 2

Variation of UCS with curing period for
30ºC curing temperature.

Resilient Modulus
Effect of lime content
Figure 4 shows the variation of resilient modulus
with lime content for different curing periods at a
deviator stress (σ d ) of 93.1 kPa and cell pressure(σ 3 ) of 34.5 kPa. There is an increase in resilient
modulus value with increase in lime content up tocertain extent (9% lime content) for all curing
periods and decreases thereafter. For lime content
more than the optimum values the lime particles
remain unutilized and serve as weak filler resulting
in the reduction of resilient modulus. Similarvariations of the resilient modulus with lime content
were reported in literature [5], [12], [13], and [14].

Effect of temperature
Figure 6 shows the variation of resilient modulus
with lime content for different curing temperaturesand soaking condition. There is an increase inresilient modulus with increase in temperature due tothe accelerated pozzolanic reaction at higher
temperature which shows that the lime stabilization
is more effective in tropical countries where
temperature is high. Resilient modulus of the soaked
specimens were found to be higher than that of the355

GEOMATE-Brisbane, Nov. 19-21, 2014

unsoaked specimens except for 3% lime content.
This may be due to the development of pore waterpressure during the cyclic test as the specimens were
tested under undrained condition. The presence ofpore water increases the resistance to thedeformation resulting in higher stiffness.

four models. The regression constants obtained wereused for determining the predicted resilient modulusof the mixes. A graph was drawn between measured
resilient modulus and predicted resilient modulus,
and the corresponding R2 and rss values were
determined. Comparison between the four models
shows that the three parameter model provided abest fit regression equation for the determination ofresilient modulus of lime stabilized soil.

3% Lime6% Lime9% Lime12% Lime

130

220

28 DaysResilient moduls (MPa)Resilient modulus (MPa)

150

110

σd = 93.1 kPa
σ3 = 34.5 kPa

90

70
0

7

14

21

28

180

140

100

Curing period (days)

3% Lime6% Lime9% Lime12% Lime

60

Fig. 5 Variation of resilient modulus with curing
period for different lime content.

0

400

200

Resilient Modulus (MPa)Resilient modulus (MPa)300

Fig. 6 Variation of resilient modulus with major
principal stress for different lime content.

300C
400C
500 C
soaked120

σd = 93.1 kPa
σ3 = 34.5 kPa

100

80
3

200

Major principal stress (kPa)

160

140

100

6

9

12

9% Lime150

100

Lime (%)

0 day

7 days14 days

28 days50

Fig. 6 Variation of resilient modulus with lime
content for different curing temperature.

0

100

200

300

Major principal stress (kPa)

Effect of major principal stressFig. 7 Variation of resilient modulus with major
principal stress for different curing period.

Variation of resilient modulus with major
principal stress (σ 1 ) for different soil-lime mixes areshown in Fig. 7 and Fig. 8. There is an increase inresilient modulus with increase in stress value for all
lime content and curing period. Similar trend was
also observed for other lime contents and curing
periods.
Several constitutive stress based models for theestimation of M r are available in the literature. In
this study the fitness of four stress based models forthe determination of M r for soil-lime mixes arecompared in Table 1. The residual sum of squares(rss) and the coefficient of determination (R2)
obtained from the non-linear regression analysis
were used to compare the “goodness of fit” for the

Table 1 Stress based models with R2 and rss values
Model
𝐌𝐌𝐫𝐫
𝛔𝛔𝟑𝟑 𝐤𝐤𝟐𝟐 𝛔𝛔𝐝𝐝 𝐤𝐤𝟑𝟑
= 𝐤𝐤 𝟏𝟏 � � � �
𝐏𝐏𝐚𝐚
𝐏𝐏𝐚𝐚
𝐏𝐏𝐚𝐚
𝐌𝐌𝐫𝐫 =k 4 𝝈𝝈𝒅𝒅 𝐤𝐤𝟓𝟓

𝐌𝐌𝐫𝐫 = k 6 𝝈𝝈𝟏𝟏

𝐤𝐤𝟕𝟕

𝐤𝐤𝟗𝟗

R2

rss

0.96

11651

0.92

25920

0.94

18766

0.86
41839
𝐌𝐌𝐫𝐫 = k 8 𝜽𝜽P a is atmospheric pressure equals to 101.3 kPa
k 1 , k 2 , k 3 , k 4 , k 5 , k 6 , k 7 , k 8 are model constants

356

400

GEOMATE-Brisbane, Nov. 19-21, 2014

Predicted Resilient Modulus (MPa)Model constants (k 1 , k 2 and k 3 ) of the threeparameter model obtained for different soil-lime
mixes were given in Table 2. The value of k 1
increases with an increase in lime content upto 9%
and decreases thereafter for all curing periods andcuring temperatures. However, no consistent trends
have been observed for values of k 2 and k 3 . Figure 9shows the graph between predicted M r using threeparameter model and actual M r of all the soil-lime
mixes for fifteen different stress levels.
Table 2 Model constants of three parameter modelfor different lime content and curing period

250

R2 = 0.96

200
150
100
50
0
0

50

100

150

200

250

Actual Resilient Modulus (MPa)𝐌𝐌𝐫𝐫
𝛔𝛔𝟑𝟑 𝐤𝐤𝟐𝟐 𝛔𝛔𝐝𝐝 𝐤𝐤𝟑𝟑
= 𝐤𝐤 𝟏𝟏 � � � �
𝐏𝐏𝐚𝐚
𝐏𝐏𝐚𝐚
𝐏𝐏𝐚𝐚
Curing
Lime
k1
k2
k3
Mrp
Mra
Period(%)
00.79 0.07 0.29 72.6
72.5
30.94 0.16 0.30 78.2
80.4
0 day
6
0.96 0.13 0.27 83.0
83.4
91.03 0.09 0.27 92.6
91.0
121.01 0.12 0.27 87.6
87.0
3
1.06 0.13 0.27 91.1
92.1
6
1.16 0.16 0.24 97.0
98.8
7 days91.31 0.13 0.24 113.0 117.4
12
1.24 0.16 0.24 103.7 108.6
3
1.08 0.08 0.30 98.0
97.5
6
1.25 0.12 0.23 109.8 108.6
14 days9
1.39 0.06 0.26 129.0 128.6
12
1.33 0.07 0.26 122.3 118.6
3
1.21 0.15 0.25 102.1 100.1
6
1.33 0.13 0.20 114.7 115.5
28 days9
1.49 0.09 0.19 135.0 138.5
12
1.40 0.07 0.23 129.4 128.6
3
1.21 0.16 0.22 101.9 104.3
7 days at
61.25 0.12 0.25 108.8 110.9400C
91.36 0.08 0.25 124.0 128.6
12
1.33 0.11 0.24 116.6 118.2
3
1.22 0.09 0.24 110.2 111.8
61.30 0.10 0.21 116.6 116.9
7 days at
500 C
91.44 0.07 0.22 132.6 135.6
121.36 0.08 0.23 124.5 128.9
30.98 0.12 0.35 84.6
88.8
6
1.36 0.11 0.34 119.4 124.5
7* days91.50 0.03 0.28 144.0 147.5
121.45 0.04 0.28 137.6 141.5
M r p is predicted resilient modulus in MPa and M r a isactual resilient modulus in MPa at σ 3 = 34.5 kPa andσ d = 93.1 kPa;
*3 day curing at 300C and 4 day soaking in water.

Fig. 8 Predicted M r versus actual M r for threeparameter model.
CONCLUSIONSEngineering properties such as unconfinedcompressive strength and resilient modulus of soillime mixes were investigated and the following
conclusions were drawn:• UCS values increases with increase in lime
content up to certain extent and decreases
thereafter. UCS value was maximum at 6% and
9% lime content for 7 days and 28 days curing
period, respectively. The rate of gain of strengthis high during the initial seven days but slows
down thereafter.
• Higher the curing temperature, higher is the
UCS value obtained. It was observed thatsoaking of the specimens in water reduces its
compressive strength for 7 day curing period.
• BC soil stabilized with a minimum lime content
of 6% satisfied the strength criteria for use in
subbase course as recommended by IRC 51.
• Resilient modulus of the soil-lime mixes
increases with the increase in lime content upto
9% and decreases thereafter for all curing
periods and curing temperatures. Mr value
increases continuously with increase in curing
period and curing temperatures. Resilient
modulus of the soaked specimens wereobserved to be higher than that of the unsoaked
specimens for 6, 9 and 12% lime contents.
• The performance of four stress based models
were compared and observed that the threeparameter model outperformed the other models
with high coefficient of determination values
providing good fit model constants for thedetermination of resilient modulus.

357

GEOMATE-Brisbane, Nov. 19-21, 2014[8] Nasrizar A., Ilamparuthi K.., and Muttharam M,“Quantitative models for strength of lime
treated expansive soils”, Geocongress 2012,
ASCE, pp. 978-987.
[9] Pranay KC., Sai KV., Anand JP., Laureano H,“Evaluation of strength, resilient moduli, swelland shrinkage characteristics of four chemicallytreated sulfate soils from north Texas”, GSP 136
Innovations in Grouting and soil improvement,
ASCE 2005.
[10] Radha KD., Vincent PD., Kim D, and Chen R,“Assessing the quality of soils modified withlime kiln dust measuring electrical conductivity
with time domain reflectometry”, J. of
Transportation Research Board, 2006, pp. 101109.
[11] Ranjan KR., Pinit R, Shashank V., Anand J. P,“Resilient moduli behavior of lime cement
treated subgrade soils”, Geocongress 2012,
ASCE, pp. 1428-1437.
[12] Singh D., Rouzbeh G., Joakim GL., andZaman M, “Laboratory performance evaluationof stabilized sulfate containing with lime andclass C fly ash”, Geoflorida 2010, ASCE, pp.
757-766.
[13] Solanki P, Zaman MM, and Jeff D, “Resilient
modulus of clay subgrade stabilized with lime,
class C fly ash, cement kiln dust for pavement
design”, J. of Transportation Research Board,
2010, pp. 101-110.
[14] Solanki P., Khoury N and Zaman MM,“Engineering
properties
andmoisture
susceptibility of silty clay stabilized with lime,
class C fly ash, cement kiln dust”, J. of
Materials in civil Engg., ASCE, Vol.12, Dec.
2009, pp. 749-757.

LIST OF SYMBOLS
M r : resilient modulus
σ d : deviator stress
ε r : recoverable strain
σ 3 : cell pressure
σ 1 : major principal stressθ : bulk stress
REFERENCES[1] AASHTO T 307, “Determining the resilient
modulus of soils and aggregate materials”, 2000.
[2] AASTHO, “Guide for design of pavement
structures”, 1993.
[3] Chakkrit S., Anand JP., Vivek C., Sireesk S.,
Laureano RH, “Combined lime and cement
treatment of expansive soils with low to
medium soluble sulfate levels”, Geocongress
2008, ASCE, pp. 646-653.
[4] George SZ., Ponnaih DA., Little JA, “Effect oftemperature on soil-lime stabilization”, J. ofConstruction and Building Materials, Vol. 6 No.
4, 1992, pp. 247-252.
[5] Hossain Z., Zaman M., Doiron C., and Solanki
P, “Evaluation of mechanistic empirical design
guide input parameters for resilient modulus ofstabilized subgrade soils”, ICSDEC 2012, pp.
510-518.
[6] Indian Road Congress 51, “Guidelines for theuse of soil-lime mixes in road construction”,
1992.
[7] Muhamed A and Wanatowski D, “Effect of lime
stabilisation on the strength and micro structureof clay”, IOSR J. of Mechanical and Civil Engg.,
Vol. 6, June 2013, pp. 87-94.

358

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

UPTAKE OF ADVANCED AND SUSTAINABLE ENGINEERING
MATERIALS IN CIVIL INFRASTRUCTURE PROJECTSDavid S Thorpe
Faculty of Health, Engineering and Sciences, University of Southern Queensland,

ABSTRACT
Advanced and sustainable engineering materials, such as engineered fibre composites, geoploymer cement,
and recycled concrete have the potential to reduce demand on scarce resources, improve safety, reducegreenhouse gas emissions and contribute to positive initiatives in civil engineering design and construction inareas like foundations and structural members. For example, engineered fibre composites can replace othermaterials (such as timber), because of their high strength to weight ratio, light weight and ease of installation.
They can also have positive impacts on sustainability. While advanced materials have several advantages, theirtake-up by industry, and in particular small and medium enterprise companies (SMEs), has in a number of cases
been relatively slow. This is likely to be the result of a number of factors, such as relatively high cost, financial
risk in using an unproven technology, lack of suitable design standards, an unproven life cycle, uncertainty overlong-term sustainability issues, and possible changed building and construction methods. Advantages anddisadvantages of the use of selected advanced and sustainable materials in civil engineering projects areinvestigated. A weighted scoring methodology for improved evaluation of their advantages and disadvantages,
with a view to aiding decisions, is proposed.
Keywords: Advanced Materials; Sustainability; Innovation; Civil Engineering; Construction

process and contribute to sustainability throughincreased sustainability of scarce resources like oldgrowth timber. Other advanced and sustainable
materials are similarly being successfully used incivil engineering applications.

INTRODUCTION
Advanced and sustainable engineering materials
have the potential to make a positive contribution tocivil engineering design, construction, operation andmaintenance through reducing demand on scarce
resources, improving safety and positively impacting
on sustainability and resilience. While there havebeen a number of applications of these materials,
their uptake at a more general level in civilengineering projects, and particular the small andmedium enterprise (SME) building and construction
sector, has tended to not been as rapid as it could.

The SME construction sector has been shown tobe quite innovative in a number of areas, and inparticular in the adoption of proven products andimproved processes [3]. At the same time, there
appears to be some reserve with respect to thedevelopment of less well-known or less well proventechnologies. Price, for example, driven by thecompetitive tendering process, was found to be themain factor in a Welsh study on the adoption of
pozzolans as substitutes for cement [4].

A number of such materials have considerable
promise in terms of innovation in engineering design,
construction and asset management. Polymer
composites, for example, are well-known for theiruse in manufacturing applications like aircraft. They
have also had considerable use in non-criticalstructural applications such as bathrooms andvanities, cladding, decoration and finishing. It has
been claimed that, in 1999, the construction sector
was the world’s second largest consumer of polymer
composites, with 35% of the global market [1].
More recently, they have also been used in a number
of applications like walers in corrosive environments,
fibre composite bridge girders as alternatives totimber girders, railway sleepers, and repair andreplacement of timber piles [2]. These structural
applications of advanced materials promise toprovide considerable efficiencies to the construction

The decision-making process with respect to theadoption of new innovations (including newmaterials) is likely to be the result of a balance ofbarriers and enablers to adoption of innovations.
Other factors, such as knowledge of the innovation,client requirements and legislative factors are also
likely to impact on the decision to use advanced andsustainable materials.
This paper explores some of the issues, barriersand enablers with respect to this decision, discusses
research with respect to innovation in small builders
that illustrates the innovation process, and proposesa weighted scoring methodology for aiding thedecision making process.
359

GEOMATE- Brisbane, Nov. 19-21, 2014

inorganic aluminosilicate polymeric gel resulting
from the reaction of amorphous aluminosilicateswith alkali hydroxide and silicate solutions.” The
material may have various names, including
geopolymer cement (or concrete). It has been usedon concrete of up to 70 MPa in strength, and canattain satisfactory high early strength if thetemperature is above 20 degrees Celsius. Concrete
made with this material as binder is claimed to havehigher tensile and flexural strength, and lower
drying shrinkage, relative to concrete made with
Portland cement. It has been used in a range ofapplications like pavements, a retaining wall, watertanks, a boat ramp and precast bridge decks [8].

EXAMPLES OF ADVANCED AND
SUSTAINABLE MATERIALSThe materials selected for the discussion in thispaper are engineered fibre composites, cement(pozzolanic substitutes for cement and geopolymer
based cement) and concrete using recycled materials.
These materials have been selected because of theirpotential impact on civil engineering developments.
One definition of composite materials is that they
combine and maintain two or more distinct phases to
produce a material superior to either of the basematerials [5]. Polymer composites combine polymer
resin (for example, polyester, vinyl and epoxy) withfillers and reinforcing fibres (such as glass, aramidand carbon) used as the primary means of carrying
load, while the polymer resin protects the fibres andbinds them into a cohesive structural unit,
commonly called fibre composites [6]. As
previously discussed, they have a wide range ofapplications in civil engineering and building,particularly in corrosive environments or as
replacements for more traditional materials.

Carbon dioxide emissions from concrete madewith this material have been compared that madefrom Portland cement. One such study, on a one
cubic metre sample used in a Melbourne, Australia,
bridge, reported that when obtaining raw materials,
concrete manufacturing, and construction (transportand onsite placement) were taken into account thatthe carbon dioxide emission from the concrete madewith geopolymer cement was 9% less than that fromequivalent concrete made with Portland cement [9].

It has been claimed that in North America alone
10 billion tonnes of concrete are produced each year.
This concrete has a definite impact on theenvironment. Strategies to meet the environmental
challenge include the use of supplementary
cementitious materials (such as fly ash andgranulated blast furnace slag), use of recycledmaterials in place of natural resources, improved
durability, improved mechanical and otherproperties (for example, doubling the strength of
concrete in compression members to reduce therequired amount of material) and reuse of washwater. There are both advantages and disadvantages
with these processes. For example, while cement
made with fly ash utilizes a waste material and isuseful for mass structures because it has a delayedand different reaction from Portland cement, its
relatively slow rate of strength development makes it
unsuitable for applications requiring high earlystrength. The variation in the properties of fly ash
between different electric power plants also raises anissue with respect to quality control. Recycled
aggregate generally has lower densities than theoriginal material used because of the cement mortarthat remains attached to the original particles, andlarger water absorption than virgin aggregate. The
aggregate also varies in quality. Concrete made withrecycled aggregate tend to have lower strength that
concrete made with virgin aggregate. It is expected,
however, that a shifting public attitude towards
global warming is likely to increase the use of
concrete containing recycled materials [7].

In summary, while there are a number ofadvantages with advanced and sustainable materials,
there are also some disadvantages with them fromthe point of view of the product (material) itself. The
following sections develop this discussion further.
THE INNOVATION ADOPTION PROCESSThe uptake of advanced and sustainable
materials and their associated processes can be
described by the concept of innovation, which canbe defined as the development of an idea, practice,or object that is perceived as new by an individual orother unit of adoption. According to Rogers [10], thegeneration of innovations has the steps ofrecognizing a problem or need, research (basic andapplied), development, commercialization, diffusion
and adoption and the consequences (changes that
occur to an individual or a social system as a resultof adoption or rejection of an innovation). In the
adoption process, the potential user of the innovation
makes a decision, the stages of which are gaining
knowledge of the innovation, forming an attitude
about it (persuasion), making a decision whether toaccept or reject it, implementation of the new idea,
and confirmation of this decision. All steps in thedecision process involve communication.
The decision process is when an organization
decides to adopt or not adopt a new product orprocess. There are rewards for early adopters of aprocess. There are also negative risks, such as
potential financial loss. The materials discussed in

A geopolymer may be described as “the360GEOMATE- Brisbane, Nov. 19-21, 2014

the previous section would tend to be mainly in the
research or development phases of the innovation
process. Thus, any adopter of one of these materials
would be considered to be an early user of it.

Other enablers in the uptake of advanced andsustainable materials may include superior
performance, improved client and community
acceptance of modern energy efficient materials, andease of construction and installation (such as withthe relatively light fibre composite materials).

The Queensland Department of Transport andMain Roads have further identified that in order toachieve the successful development of a product, itis necessary for all members of the interdisciplinary
team to have a common and shared understanding of
the material and service life conditions. In theirconsideration of engineered fibre composites, themajor participants are the fibre composite designers,
manufacturers, installers, infrastructure owners andacademia [11]. There should be a sharedunderstanding and clear lines of communication
between these parties for successful adoption of the
product.

POTENTIAL ISSUES IN THE UPTAKE OF
ADVANCED AND SUSTAINABLE
MATERIALS
While there are a number of factors that facilitate
the uptake of advanced and sustainable materials in
civil engineering, a number of issues and barriers tothis uptake have also been identified.
For example, the Queensland Department ofTransport and Main Roads has identified a numberof areas in which there are deficiencies between
engineered fibre composites and other products suchas concrete and steel. One of these areas is the lackof an Australian standard for this product. While
there was a draft standard developed, it did not
progress because of a lack of industry interest.
Fragmentation and the use of Intellectual Property asa tool to closely guard information but also limit
transparency surrounding manufacturing limits the
openness of information published in papers.
Ultimately, the lack of standards poses a
professional indemnity risk for designers.

ENABLERS IN THE UPTAKE OF ADVANCED
MATERIALS
The process of forming an attitude about aninnovation, which is the focus of the persuasion
stage of the decision process, will require an
assessment of items like relative advantages,
compatibility,
complexity,
trialibility
andobservability [12]. The assessment of these factors
will require evaluation of the advantages and otherenablers of the adoption of these materials, and of
the disadvantages and other barriers to this adoption
or uptake.

Other issues identified by the Department
include uncertainty about the material properties
with changes in temperature, and deficiencies inmanufacturing and installation specifications,knowledge of design life and asset management
procedures. The risk of brittle collapse is also an
issue that remains unresolved. The Department is
mitigating these risks by working with academics,
undertaking trial installation of fibre composite
replacement girders and undertaking structural
health monitoring. It is also developing its own
specifications [19].

From the point of view of enablers of innovationin the Australian construction industry, a national
survey of 383 construction industry firms [13]identified a number of drivers for innovation in thefirms surveyed, which included efficiency,
productivity improvements and customer needs.
Better performing firms adopted a number ofadvanced practices, and invested in research anddevelopment.
Profit, market and legal related factors [14], andknowledge, along with its organization anddissemination [15], have also been identified as aids
to innovation. A United Kingdom study found thatin small construction firms, owners have the power
to ensure rapid decision-making and thus facilitate
rapid innovation, and that the process of innovation
was behavioral and cyclical in nature [16].

While these processes might be useful for larger
organizations, it is unlikely that the SME sector
would have the financial strength to support theextensive development and testing required. There
are also likely to be other barriers to the adoption of
new materials by industry, and particularly its SME
sector. For example, the Australian constructionindustry has been considered fragmented,
adversarial and having low profit margins, low-bid
tendering, inequitable risk sharing, small firm size, alack of investment in technology, a cyclical nature, alarge proportion of very small firms and a limited
history of business deliverables from researchers

A further potential driver of innovation fororganizations undertaking civil engineering projects
is the growing requirement for sustainable
construction practices, including energy efficiency
and resilience of buildings to extreme weather
events [17]. Sustainability may come at an economic
cost [18], which requires consideration.
361

GEOMATE- Brisbane, Nov. 19-21, 2014

aspect of improvement (for example, sustainability)
to the specific business objective of improving
productivity and/or efficiency.

[20]. The small firm size tends to be an international
trend [21]. It has also been found that cost-related
factors are significant barriers to innovation, as aremarket-related factors and lack of skilled staff [22].
In summary, if the construction industry is to benefit
from innovation, it has to change from an adversarial
and blame culture to a sharing one [23].

A majority of the firms stated that the innovation
was profitable, with none reporting a decrease inprofits. Most firms did not feel that they had gained
a competitive advantage by using the innovation,and there was uncertainty that using the selected
innovation had reduced risk. However, all firms
indicated that they would use the innovation again.
This was a positive sign that the innovation had beenof benefit to the firm.

Other negative factors that may have a bearing
on the decision process to use advanced andsustainable materials in civil engineering projects,
and in particular by SME firms, are likely to include
the high cost of adopting and using these materials
and the risks (particularly financial risks) of the new
innovation not being successful.

Responses to questions about sustainability
related innovations were varied, and included thepositive responses that sustainable practices weregood for business, made firms competitive and werea point of difference. Negative responses included
the cost availability (of suitable materials), that somefirms would only undertake sustainable practices if
required and that tight margins were a barrier toadopting sustainable practices.

RESEARCH INTO INNOVATION IN SMALLRESDIENTIAL BUILDERS
In order to better understand the innovation
process in the SME engineering and construction
sector, the author undertook research in 2006 into
innovation in the small firm residential building
sector in South-East Queensland, Australia [24].
One hundred small residential builders constructing
housing up to $A750,000 in value were contacted,
with 20 agreeing to a structured interview.

While not all of the firms reported problems in
implementing the selected innovation, theyexpressed concerns with respect to the availability ofsuitable trades people. Cost (which also impacts onclient expectations) and the need for legislation tokeep up with industry advances were also cited as
issues in this regard.

A qualitative methodology incorporating a semistructured interview process was used. The
objectives of the interview questions were to explore
the extent of innovation in the firms selected,
provide an understanding of how they developed or
adopted innovations, assess the value of innovations
to the firm and determine their readiness to adapt tochanges in their operating environment.

In summary, the SME builders, while generally
supportive of innovations that utilized new or
improved materials, had a number of reservations inareas like profitability and risk, and had concerns inareas like cost and availability of suitable materials.

Seven of the firms interviewed had four or fewer
staff, 11 had five to 19 staff, and two had just over
19 staff. Of these firms 18 were primarily engaged
in construction, and the other two in renovation andmaintenance. Eleven of the firms undertook design
as well as construction. All were involved in private
sector residential work.

A PROCESS FOR ASSESSING THE UPTAKE
OF MATERIALSThe above discussion has shown that while
industry is interested in adopting innovative
materials and processes, there are a number offactors that both encourage and discourage their use.
A weighted scoring process has been proposed to aid
the adoption decision process. This process focuseson the persuasion stage of that decision process, andin particular on the relative advantage of theinnovation.

There were 50 examples of innovation in thesefirms. Of these innovations, 25 were associated withthe development of a new or improved product. The
majority of other innovations were associated withthe development of a new or improved process.
Eleven of the innovations were related to new or
improved materials. Advanced materials likeengineered fibre composites were however not listedby the builders.

The stages in this process are to a) adopt a
scoring system that enables factors expressed indifferent units of measurement to be included in theevaluation on an equivalent basis; b) weight thefactors with respect to each other; and c) calculate a
total weighted score combining the weights and thescores of individual factor values.

Interviewees were also asked to select aparticular innovation and discuss in depth why they
developed or used it. The reasons given for theirdevelopment ranged from an interest in a particular362

GEOMATE- Brisbane, Nov. 19-21, 2014

In order to provide an approach that permits amix of quantitative and qualitative variables to be
combined in the same analysis on an equivalentbasis, each variable in the evaluation is assigned ascore on the same rating scale. For quantitative
variables, the score would be assigned on the basisof calculation, based on a formula that related thescores to actual variable values. Qualitative variables
would be assigned a utility value derived from a risk
profile based on the indifference point between
various combinations of worst and best expected
outcomes, given the probabilities of receiving each[25]. Stakeholder views would aid this process.

Table 1 Example Weighted Scoring Calculation for
Adoption Decision - Fibre Composite
FactorScoresMaterial
Designlife
Ease of
Building
Available
Standards
Sustain
TOTAL

While there are a number of options for
assigning the weights for each factor being assessed,
one approach is the rational management process of
Kepner and Tregoe [26]. This approach formulates agoal statement and considers the objectives
supporting this goal by dividing them into musts(which are not negotiable) and wants. The wants arethen grouped into related variables, and the groups
are ranked using pair wise comparison or othertechniques. Benefit and cost may be may beconsidered separately from the analysis, or else
assigned a score and included in the analysis.

Weight
0.25
0.15

Adopt
Item Tot.
8
2
6
0.9

Not adopt
Item Tot.
2
0.5
4
0.6

0.15

7

1.05

5

0.75

0.3

2

0.6

10

3

0.15
1.00

6

0.9
5.45

2

0.3
5.15

CONCLUSION
This paper has focused on the uptake ofadvanced and sustainable materials in civil
infrastructure projects, with particular emphasis on
their adoption by small and medium enterprisecompanies. It has overviewed the topic, discussed
examples of advanced and sustainable materials,
outlined the innovation process, discussed factors
which aid (enablers) and prevent (barriers) withrespect to uptake of these materials in civilengineering projects, discussed previous research
into a similar area and outlined a possible approachto the adoption decision process.

The final step is to calculate a total weighted
score by summing the individual weighted scores, as
follows:n

T = ∑WiSi
i =1

It is concluded that as demonstrated in the
research into innovation by small builders theindustry is quite interested in adopting new materials
and methods of design and construction, there arestill reservations that prevent the complete uptake ofadvanced and sustainable materials in civilengineering projects. While advances in methods
and the requirements of sustainable development
may facilitate this process, there is a strong
requirement for appropriate standards to be
developed, increased trials of these materials inapplications, and extensive communication to theindustry about the benefit of using advanced andsustainable materials in their businesses.

Where:T= Total Weighted ScoreWi= Weight for factor iSi= Score for factor i
This process is illustrated for engineered fibre
composites, in which the alternatives of “adopt” and“not adopt” in the replacement of a timber bridge
girder are compared. For simplicity, the analysis
uses the selected factors of material, design life, easeof construction, availability of standards, ability totrial and sustainability. A scale of 0 to 10 is used toassign scores, which are multiplied by weights
assigned to each factor and summed for each case,as shown in Table 1. In this table, “ease of
construction” has been shown as “ease of building”,“availability of standards” has been shown as“available standards”, and “sustainability” as“sustain.” The abbreviation “Tot.” has also beenused in the header rows for “Total.”

REFERENCES[1] Humphreys, MF, “The Use of Polymer
Composites in Construction”, in Proc. 2003
International Conference on Smart andSustainable Built Environment, November,
2003, Brisbane, Australia.

On the basis of the result in Table 1, the decision
would be to probably adopt the material, subject toconsideration of other factors like benefit and cost.

[2] Aravinthan, T, “Fibre Composites in Civil
Infrastructure – Research to Reality inAustralia”, in Manalo, A and Kee-Jeung Hong363

GEOMATE- Brisbane, Nov. 19-21, 2014(eds.) Research to Reality: Promoting Fibre
Composites in Civil Infrastructure, February
2014, pp. 2-7.

[14] Australian Bureau of Statistics, “Innovation inAustralian Business 2003”, ABS Catalogue No,
8158.0. Canberra: AGPS, 2005.

[3] Thorpe, D, Ryan, N., Charles, M., ‘Innovationand small residential builders: an Australianstudy’, Construction Innovation, Vol. 9, No. 2,
2009, pp. 184-200.

[15] Egbu, CO, “Managing Knowledge andIntellectual Capital for Improved Organizational
Innovations in the Construction Industry: an
Examination of Critical Success Factors”,
Engineering, Construction and Architectural
Management, Vol. 11, No. 5, 2004, pp. 301-315.

[4] O’Farrell, M and Miller, CJM, “The barriers to
new technology diffusion in the constructionindustry of South Wales”, in Current Issues in
Small Construction Enterprise Development,
Welsh Enterprise Institute Monograph No. 4, ed.
Miller, CJM. Packham, GA and Thomas, B,
Pontypridd: University of Glamorgan Business
School, 2002, pp.123–137.

[16] Sexton, M, and Barrett, P, “Appropriate
Innovation in Small Construction Firms”,
Construction Management and Economics, Vol.
27, No. 6, 2003, pp. 623-633.

[6] Humphreys, MF, op. cit.

[17] Australian Building Codes Board, “Discussion
Paper - Resilience of Buildings toExtreme Weather Events”, Canberra: AGPS,
April 2014.

[7] Meyer, C, “Recycled Materials in Concrete”, in
Mindness, M (ed.), Developments in the
Formulation and Reinforcement of Concrete,
Cambridge, England: Woodhead Publishing
Limited, 2008, pp. 208-230.

[18] Meyer, C, “The Economics of Recycling in the
US Construction Industry”, in Chun, Claisse,
NaikandGanjian(eds),
Sustainable
Construction Materials and Technologies,
London: Taylor and Francis Group, 2007.

[8] Aldred, J and Day, J, “Is Geopolymer Concretea Suitable Alternative to Traditional Concrete?”in 37th Conference on our World in Concrete &Structures”, Singapore, August 2012.

[19] Pritchard, R, op.cit.

[5] Humphreys, MF, op. cit.

[20] Hampson, KD and Brandon, P, “Construction
2020: A Vision for Australia’s Property andConstruction Industry”, Brisbane: Cooperative
Research Centre for Construction Innovation,
2004.

[9] Turner, LK and Collins, FG, “Carbon Dioxide
Equivalent (CO 2-e ) Emissions: A Comparison
between geopolymer and OPC Cement
Concrete”, Construction and Building Materials,
Vol. 43, 2013, pp. 125-130.

[21] European Commission, “Constrinnonet –Promoting Innovation in Construction Industry
SMEs Project Final Report”, Constrinnonet
Project Consortium, 2004.

[10] Rogers, EM, “Diffusion of Innovations”, 5th ed.,New York: Free Press, 2003, pp. 12, 136-168.

[22] Australian Bureau of Statistics, op. cit.
[11] Pritchard, R, “an Infrastructure Owners
Perspective of Fibre Composites”, in Manalo, A
and Kee-Jeung Hong (eds.) Research to Reality:
Promoting Fibre Composites in Civil
Infrastructure, February 2014, pp. 30-34.

[23] Egbu, CO, op. cit.
[24] Thorpe, D, Ryan, N., Charles, M.,2009, op. cit.
[25] Hamburg, M, "Statistical Analysis for Decision
Making", NY: Harcourt, Brace and World, pp.
631-644.

[12] Rogers, EM, 2003, op. cit., p. 170.
[13] Manley, K, Allan, D, Blayse, A, Coillet, M,
Hardie, M, Hough, R, MacKenzie-Smith, S,
May-Taylor, W, McFallan, S, Miller, M,
Swainston, M, Taylor, G, “BRITE Innovation
Survey”, Brisbane: Cooperative ResearchCentre for Construction Innovation, 2005.

[26] Kepner, CH and Tregoe, BB, "The New
Rational Manager", Princeton, NJ: KepnerTregoe Inc.

364

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

A CASE STUDY – USE OF EXPANDED POLYSTYRENE BLOCKS IN
LANDSLIDE REMEDIAL WORKS
M. Boyer1, K.Chew2 and Dr B. Look3
Senior Geotechnical Engineer, Jacobs SKM, 3 Principal Geotechnical Engineer, Foundation Specialist
Group, Australia

1,2

ABSTRACTThis paper describes the use of expanded polystyrene blocks (EPS) as a lightweight fill as a means ofstabilising a landslide. EPS is more commonly used for construction of embankments over soft ground. This casestudy describes the stabilisation of a fifty metre section of road in Queensland that was undergoing subsidence asa result of a large landslide. These works required re-grading of the slope and the installation of deep counterfort
drains and horizontal drains, twenty-six metres in length. Part of the landslide was also stabilised using soil nails
with high tensile steel mesh facing. The actual road was reconstructed using lightweight expanded polystyrene
fill.
Keywords: Landslide, Ground improvement, Lightweight fill, Expanded polystyrene, Soil nails

beneath the road embankment into the adjacent cut
slope. It was initially noted as a large area ofsubsidence with tension cracks in the road pavement
as shown in Fig 1. Monitoring at this site indicatedthat further movement of the area was occurring in
response to subsequent rainfall events.

INTRODUCTION
Woombye-Montville road leads up the steep
basaltic capped scarp on which the townships ofMaleny, Montville and Mapleton are located in theSunhsine Coast Hinterland, Queensland.
Multiple landslides occurred during and
immediately following an unusual heavy rainfall
event that also coincided with the January 2011
Queensland floods.

DESIGN DEVELOPMENT
Ground model
A ground model relating to this site wasdeveloped though detailed geomorphologicalmapping,
geotechnicalinvestigation
andinstrumentation which included piezometers fittedwith datalogers and inclinometers measuring groundmovement with depth. The ground model andremedial measures are shown diagrammatically as
Fig 2.
The location of critical slip surface was fairly
well known where the back scarp and secondary
scarp daylights at the surface and where
inclinometer movements have confirmed thelocation of deep slip surface within colluvial soils
just above the underlying sandstone rock in this area.
However, the location of the failure surface further
downslope could not be clearly inferred frominvestigations alone. Back analysis using limit
equilibrium methods of circular slip analysis wasused to predict the extent of the slip further downslope and establish soil parameters for further
remedial design.
Groundwater conditions were inferred fromeither those recorded in piezometric wells or wherevisible seepage from the adjacent cut slope and toeof the slope could be observed during periods ofEdge of failure>100mm depression

Secondary scarp toward
centre of landslide

Fig. 1

Areas of subsidence and tension cracks

This landslide is believed to have occurred as aresult of the combined effect of concentrated
localised perched water flows (springs) and thedamming effect of relatively low permeability
colluvium that covers much of the lower slopes overwhich this road has been constructed [1]. This
landslide is described as a deep seated rotational
failure within the colluvial soils that extends back365

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 2

Diagrammatic ground model showing failure mechanism and remedial design elements

heavy rain. Groundwater levels were found to rise
and recede rapidly in response to rainfall and thelower part of the slope became fully saturated
immediately after heavy sustained rainfall events.

This combination of loading and unloading thesystem and measures to control groundwater aims toaddress the balance of forces and provide therequired global factors of safety as indicated by limit
equilibrium computer analysis. Although thisanalysis indicated that a minimum global factor ofsafety could be achieved in the overall slope without
the use of lightweight fill, this was adopted by thedesigners to account for uncertainty around the
behaviour along pre-existing sheared surfaces andthe upper level local stability of the road shoulder. It
also made good practical sense to reconstruct theupper portion of the road embankment that had beendamaged.
The analysis for global stability can bemisleading as it indicates that the critical failuresurface is the deep seated failure which matches the
movement recorded by inclinometers. However, as
is evident by secondary slip surfaces in the edge ofthe road embankment, less critical failure surfaces
are present which present less than the acceptablefactor of safety. EPS was employed to deal tostabilise the areas where these shallow slips surfaces
were believed to be present.

Design Concept
Hutchinson [2] describes the influence line
approach to landslide analysis and stabilisation
remediation. Influence lines indicate the optimum
location of subsurface drainage measures andcorrective cuts and fills. Detailed design of theseworks combined the three main principles ofembankment stabilisation namely:
UnloadThe driving forces imposed on this landslidewere reduced by re-grading the upper part of theslope and reinforcing the cutting with soil nails. The
road embankment was re-constructed using
lightweight expanded polystyrene blocks.
Drainage
The site is drained using a combination of inclined
drains into the soil nailed slope, deep counterfort
drains and drilled horizontal wells up to twenty six
metres in length.

Design of Expanded Polystyrene (EPS)
Material Specification

Load
A VH (very high density) class block moulded
expanded polystyrene foam manufactured toAS1366 [3] was specified. This material has a unit
weight of 28 kg/m3 (<1kN/m3) and a compressive

The site has been re-graded and fill has been placed
over the toe of the landslide, increasing thestabilising forces imposed on the system.
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GEOMATE- Brisbane, Nov. 19-21, 2014

strength of 72 kN/m3 and 164 kN/m3 at 1% and 5%
strain respectively. The blocks used contained aflame retardant.

smoking during construction and the carefulselection of cutting equipment and plant to limit therisk of ignition.

Set out and Construction Control

CONSTRUCTION

The foundation to the EPS block was preparedby proof rolling, test (DCP) to confirm min CBR(3 %) which was to be trimmed to a tolerance of ±10 mm over any 4000 mm distance .The design
allowed for a “mud slab” comprising a thin layer of
cement can be used prior to placing over lower
blocks to create a level surface on which to construct
the next layer. The maximum weight of compaction
equipment was limited to 60 kN/m width or roller.
Allowable stress at the surface of the EPS blocks
was not to exceed elastic limit of blocks (165 kPa).
The sand replacement method of compaction
verification was specified where fill was placed
directly in close contact to the EPS blocks asconcerns were raised over the use of nuclear
densometer which may present errors in calculating
soil moisture as hydrogren gas exsolving from the
EPS.

Construction Challenges
During construction the following issues wereresolved during the placement of EPS blocks notenvisaged necessary at the design stage.
Set out and Construction Control
EPS block set out requirements were limited todelineating an area within which EPS fill was to beplaced. Subsequent layers were required to be laidtransversely to the layer below to create aninterlocking lattice structure which extended out
beneath the edge of the pavement. In practice thisproved difficult to accomplish without detailed set
out drawings showing where individual blocks
needed to be cut.

Equivalent Subgrade Properties
Long term compressive creep data was used toassess equivalent subgrade properties of pavements
constructed over the EPS blocks. For comparison thegrade of EPS used was similar to that of a CBR 2 %material at the stress range of concern.
Design for Durability
EPS blocks were encapsulated within a 1.5 mm
HDPE membrane lapped no less than 300mm andsealed using asphaltic rubberised seam tape. Blocks
were placed sufficiently low within the embankment
to ensure no less than 600mm of soil cover to protectfrom fuel oil and fire degradation.

Fig. 3Showing placement of EPS blocks

Material Tolerances
Tolerance between blocks – the design assumed thattolerances between adjacent blocks could be
minimised to less than 10 mm.This proved initiallydifficult to achieve as the factory cast blocks did
exhibit irregularities over their lengths. In order tominimise irregularities between blocks and ensure
blocks were stable once in place a foundation was
prepared using 150mm of good quality granular fill
and a biaxial geogrid.

Safety in Design
Blocks were cast in factory moulds 0.6 m x 1.2
m x 5 m deemed the maximum size able to be
carried by construction workers during placement.
Although specified as flame retardant, freshly castblocks were prone to pentane gas production and assuch the design required blocks to be stored outside
in the open air, covered only by traps to protect fromweather and sunlight until installed. The risk of
combustion around the EPS blocks required no

Placement and Cutting
Blocks were held in place using punched aluminium
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GEOMATE- Brisbane, Nov. 19-21, 2014

grip plates. In order to ensure blocks were stableprior to placing a second layer kiln dried fine sandwas specified to be brushed over the preparedsurface and into gaps between the blocks. A small
plate compactor was used over the blocks to assist in
working the sand into place and ensuring the blocks
were stable prior to placing a second layer. A hot
wire saw was developed to reduce risk of
combustion and create a clean cut edge which
proved very effective and adaptable toaccommodating irregular cuts at the ends of theblocks.

Blocks).
Construction of Overlying Pavement
Placement of subsequent pavement layers proceededin the normal manner although trafficking by trucks
and heavy equipment is precluded until the
pavement was completed. Crane mats were used toevenly distribute the load from delivery truck wheels.
No traffic restrictions were necessary once thepavement was completed to design level. Final coverto the EPS blocks comprised some 870mm ofcompacted pavement material.

Protection of HDPE during Construction

Post Construction Performance

The design was amended to cover only the top andsides of the blocks to avoid collecting water within afully encapsulated HDPE cell Damage wasminimised by covering the HDPE with a lean mix
screed as soon as practically possible.

Monitoring Program
Monitoring at this site has been undertaken, priorto, during and after these works. These monitoring
records comprised deep inclinometers, surface
monitoring points and groundwater monitoring wellswith instrumented data loggers.
Monitoring records
Monitoring records noted significant (up to20mm) deep and surface movement during
construction (notably the drilling of deep horizontal
relief wells and soil nails). Post construction surface
monitoring of this site continued for five months up
to June 2013.

Fig. 3

No observable movement has been noted
following construction over the monitoring period.
This period of time includes two further large
rainfall events which resulted in further landslides
around the region between February and March
2013. Groundwater monitoring indicates that thehorizontal drains have little effect on the
groundwater in this area however the deepcounterfort drains over the toe of the slope may
limiting the extent at which groundwater can rise
within the colluvium. Observations made during site
visits indicate that the deep horizontal wells anddeep counterfort drains below the embankment haveintermittent flows (as is evidenced by iron staining
around the outlets).

Showing placement of EPS blocks

Protection of EPS during Construction
Plant was carefully selected to prevent damage tothe blocks. Only light rubber tracked plant was used
to lay out material prior to compaction. A rubber
tracked mini excavator (Cat 304D) was used to placematerial over the EPS blocks. A small front end
loader (279C Pozzi Track) was used to push no lessthan 200mm of type 2.3 granular pavement material
over the EPS blocks as a protective layer prior tocompacting using a relatively small (250kg)
vibrating plate compactor. Only when 400mm ofcover was in place could a larger 2.8t twin drum
roller be used in vibration mode. All plant wasverified to ensure ground bearing pressures werelimited to less than less than 72k N/m2 (limit atwhich may cause 1 % strain of theses VH grade EPS

CONCLUSIONSThe strengthening and unloading (re-grading andlightweight fill) works were used to stabilise thissection of embankment. Global slope stability
analysis may lead to a design which considers thecritical deep failure surface only (the lowest factorof safety). Design of stabilisation measures requires
a consideration of all areas where the factors of368

GEOMATE- Brisbane, Nov. 19-21, 2014

In addition many of the innovative and practicalsolutions to the placement and construction weredeveloped in conjunction with the departments
contracting arm, RoadTek.

safety is unacceptable, and not only the deep criticalcondition. Thus EPS blocks were also used tostabilise the less critical failure surface areas at ashallow level.
No significant movement has been recorded
since completion of these works or during
subsequent heavy rainfall events. The use of
expanded polystyrene block as a lightweight fill has
been successfully used as part landslide remediation
works. Additionally a great deal of practicalknowledge regarding its installation has been
accrued as part of this project.

REFERENCES[1] Boyer, M, Chew, K. & Look, B (2013), A
case study of a hillside slope instability inSouth East
Queensland,
Australian
Geomechanics Vol 44 No 3, P77-84.
[2] Hutchinson, J. N. (1984), “An Influence
Line Approach to the Stabilisation of
Slopes by Cut and Fill” Canadian
Geotechnical Journal, Vol 21, P363-370.
[3] AS 1366.3-1992 : Rigid cellular plastics
sheets for thermal insulation - Rigid
cellular polystyrene - Moulded (RC/PS M)

ACKNOWLEDGEMENTS
The authors would like to acknowledge theDepartment of Transport and Main Roads
Engineering and Technology department with whom
this technical solution was developed.

369

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

CRACKING AND BOND SPLITTING BEHAVIORS OF CORRODEDLONGITUDINAL BARS IN REINFORCED CONCRETE BEAMS

1

Yasuji Shinohara 1 and Aris Aryanto 2
Tokyo Institute of Technology, Japan; 2 Institut Teknologi Bandung (ITB), Indonesia

ABSTRACTAn experiment was performed to evaluate cracking induced by corrosion expansion and bond splitting
behaviors of corroded longitudinal bars in reinforced concrete beam. An accelerated corrosion experiment byimpressed current was conducted on reinforced concrete beam type specimens having different amount oftransverse bars, diameter of reinforcement, and concrete strength with 6% of target corrosion weight loss of
longitudinal reinforcement. The pull-out tests were also carried out to investigate the effect of corrosion on bondsplitting behaviors. The test results showed that the corrosion cracking behavior greatly depends on concrete
strength (porosity), and that stirrups contribute substantially to the residual bond splitting capacity after cracking.
Keywords: Corrosion, Bond splitting, Bond-slip relations, Beam specimen, Concrete strengths

for assessing the structural behavior of corroded
structures were proposed and applied to a corroded
RC column in order to estimate a degradation of
structural performance due to corrosion.

INTRODUCTION
A significant reduction of bond strength has been
observed for corroded steel bar without stirrups[1] with increasing corrosion level, however, slightbond strength deterioration was observed when thestirrups have been introduced [2]. Actually, not only
longitudinal bars but also stirrups may experiencecorrosion. The corrosion of stirrups may weaken theconfinement of longitudinal bars by reducing in across section of stirrups, provoking extensive covercracking [3] and diminishing of adhesion or friction
between stirrups and surrounding concrete. The
combined effect of corroded longitudinal reinforcement and stirrups has been investigated in a few
studies [3].
The main aim of this study is to investigate thecracking induced by corrosion expansion and thebond splitting behavior of corroded reinforcements
such as bond splitting capacity, mode of failure andbond stress-slip relationships. The relative influenceof stirrups, longitudinal bar position and concrete
strength were experimentally studied. From the test
results, a formulation of bond-slip model and so on

EXPERIMENTAL PROCEDURE
Specimens And Materials
The effect of actual confinement by means ofstirrups having different ratios and configurations
was investigated in accelerated corrosion tests andpullout tests using beam type specimen. The effectof bar position on beams i.e. corner or middle bars
and its position to casting direction i.e. top or bottom
in casting were also evaluated.
Six rectangular beams were produced and tested.
Each beam had two test regions, the corrosion andthe non-corrosion regions (Fig.1). The specimen
parameters are summarized in Table 1. In this study
only longitudinal bars located at bottom side ofbeams were subjected to corrosion which has 400
mm of embedment length. On the right and the left
side of embedment length the longitudinal bars were
insulated using vinyl tape as non-corroded and un-

Table 1 Specimen’s test parametersNo.

1 and 23 and 45 and 6
7 and 89 and 1011 and 12

Designation

4L0T-∞S-NH&NC
4L2T-200S-NH&NC
4L2T-100S-NH&NC
4L4T-200S-NH&NC
3L2T-100S-NH&NC
4L2T-100S-HH&HC

Concrete
Strength(N/mm2)
24
24
24
24
24
48

Longitudinal bar
No.
bar
4
4
4
4
3
4

dia.
(mm)
19
19
19
19
22
19

370

TargetCorrosion
Rate (%)

Ratio
1.29%
1.29%
1.29%
1.29%
1.30%
1.29%

0 and 60 and 60 and 60 and 60 and 60 and 6

Transverse bars
Bar

Ratio

0
2-U6@200
2-U6@100
4-U6@200
2-U6@100
2-U6@100

0%
0.15%
0.29%
0.29%
0.29%
0.29%

GEOMATE- Brisbane, Nov. 19-21, 2014

250

400
Non-corrosion

100

C
L

4D13

D6.4@50

D6.4@50A

Stirrups

220
Additional
Stirrups
Vinyltapping 400

Stirrups

63
40
Stirrups

D6.4@50

D6.4@50

4D13
400

A

75
100
UnbondedRegionCorrosion
400
Test
Region25
250
UnbondedRegion42.5
174

Main Bar

A-A

Fig. 1 Typical specimens and bar arrangements
direction. The longitudinal bars were corroded up to
approximately 6% of corrosion weight loss. The
cracking of cover was visually observed and thecrack width at certain locations was frequently
measured using digital microscope [4]. Furthermore,a constant 10 Volt from the power supply was
charged and the current flowed on each bar wasmonitored and recorded using data logger.

bonded regions. The stirrups were also covered byvinyl tape in order to protect stirrup strain gages andto keep a constant confinement during corrosion test.
Before the accelerated corrosion test, all specimens
were cured for 28 days in the laboratory. Twoconcrete strengths of 24 and 48 N/mm2 were used
representing a normal and high strength concrete.
The concrete was poured from the side of beams, sothat the bond properties of left side is identical tothat of right side. Thus, there are four bar positionsin terms of casting direction, which is T, CT, CB,
and B. The preheated high strength of steel bar was
selected for longitudinal bars to avoid the yielding
before bond splitting failure. Two bar diameters of
19 mm and 22 mm were used for longitudinalbars. The average yield strength and elastic modulus
were 1053 and 1.87×105 N/mm2 for D19 and 980
and 1.85×105 N/mm2 for D22, respectively. For
stirrups, high strength reinforcement was also usedhaving average yield strength and elastic modulus
were 1414 and 2.0×105 N/mm2, respectively.

Pullout Test
The specimens were tested in a simple threepoint loading. Because the beam has two test regionsor specimens, corrosion and healthy regions, so after
loading test was finished for one region, it was thencontinued with another test region in opposite
loading directions by turning upside down. The
outline of loading test set-up is described in Fig. 3.
The loading was controlled by displacement and also
it was controlled by measured strain at slit in thelongitudinal bar. In addition, the slip of each bar wasmeasured using LVDT which put at end of beams.

Accelerated Corrosion Test

Load
Cell

An accelerated corrosion test through theelectrochemical process was performed. The typicalaccelerated corrosion set up for all specimens is
described in Fig. 2. During accelerated corrosion
process the specimens were placed on top of two
supports and the tank containing 3% of NaClsolution was put below the specimen. The solution
penetrated to the concrete through the water sponge.
Thus, the corrosion attack took place from one

Test
RegionTest
RegionSlit
Roll Support

Fig. 3 Overview of test setup
Gages Connector

EXPERIMENTAL RESULTS
Corrosion Weight Loss

Data Logger
Specimen

At the completion of pullout testing, the corroded
longitudinal bars were removed from their concretebeams and the corrosion product was chemicallycleaned, and then it mechanically removed by steel
wire brush and the weight loss was measured. The
summary of corrosion rate for each bar and theaverage in each beam are shown in Table 2.
From Table 2 it shows that the corrosion rates ofeach bar at a beam are different, although the output

2Ω
Water Sponge+
3% NaCl Solution

Power
SupplyCopper Plate

Fig. 2 Overview of accelerated corrosion setup
371

GEOMATE- Brisbane, Nov. 19-21, 2014

This can be attributed to lots of corrosion products
localized in a crack because of lower porosity ofhigh strength concrete, as reported by Kurumisawa
et.al [5] and, the amount of pores greater than 1μm2
is also increase for higher w/c ratio in Fig. 6. The
stress of transverse bar in high strength concrete also
increased in proportion to the crack width.

of current of each bar is relatively same. Larger
corrosion rate was mostly obtained from the cornerbar particularly bar located at top in casting (T). This
trend was observed for all specimens. This can be
due to the corrosion crack mostly occur at edge ofbeam, thus it allows water and oxygen to penetrateeasily to the bars. In addition, the bar located at topof concrete casting tends to have higher porosity
than the bottom bar due to settlement of fresh
concrete. The different of corrosion rate of each bar
are relatively large compared to the estimatedcorrosion rate by Faraday’s law (6%). However, if
the average corrosion rate in one beam is roughly
consistent with the estimated corrosion rate.

0.8

Maximum crack width

0.7

Table 2 List of test variables for specimens
Bar Location
Ave.
T
CT CB
B
10.6 4.7 3.8 5.6 6.2
8.9 4.9 4.4 4.9 5.8
8.2 4.4 5.4 6.3 6.1
7.4 4.5 4.6 5.2 5.4
7,4
3.9
6.3 5.8
6.6 4.0 6.0 6.1 5.7

Designation
4L0T-∞S-NC
4L2T-200S-NC
4L2T-100S-NC
4L4T-200S-NC
3L2T-100S-NC
4L2T-100S-HC

Fc48

0.6
0.5

Fc24

0.4
0.3

No.5

0.2
0.1

No.4

0
0

50

No.1

No.2

100

150

200

No.3

250

300

350

Ave. corrosion penetration

Fig. 5 Maximum crack width vs. average corrosion

Crack Patterns Caused By Corrosion Expansion

0.18
0.11 0.12 0.12 0.08 0.07

0.13 0.2(1) 4L0T-∞S-NC

0.1
0.11

0.15

0.12 0.1(3) 4L2T-100S-NC
0.12
0.2

0.12 0.22 0.1

0.37

0.32

0.25
0.16

(5) 3L2T-100S-NC

Crack Patterns Caused By Pullout Test
Typical crack patterns at bond splitting failure
viewed from side of beams are described in Fig. 7.
Different types of crack patterns were observed from

(1) No shear bar-healthy(2) No shear bar-corroded(3) Standard-healthy(4) Standard-corroded(5) High strength-healthy(6) High strength-corroded

0.23 0.22 0.15

0.06 0.2 0.22
0.22 0.2
0.13 0.3 0.25
0.06 0.07

0.12

0.12
0.1
0.06 0.12 0.13 0.19
0.06

(4) 4L4T-200S-NC
0.23

0.08
Support

0.1

Crack
CausedBy Pullout
Test paste [5]Fig. 6Patterns
Pore structureof hardened
cement(2) 4L2T-200S-NC
Support

0.22 0.17
0.2
0.11 0.18 0.24 0.21 0.11

0.11
0.14 0.32
0.28 0.31
0.17 0.19
0.18

w/c =0.6: Mix paste and void of 1µm2

Support

0.22 0.27 0.22 0.18

w/c =0.45: Only paste (no void): Fully void of 1µm2

Support0.17

w/c =0.3

50µm

50µm

50µm

0.07
0.62 0.55 0.49 0.33
0.44
0.3
0.65 0.47
0.12

0.45 0.52 0.76 0.62
0.7
0.38
0.21 0.54 0.47

Support0.12

SupportThe first crack (crack initiation) on the concretesurface was visually observed within a few days
after accelerated corrosion being started for all
specimens. The crack patterns and crack width at
final accelerated corrosion in Fig. 4. Generally, twomajor cracks were formed at the bottom cover ofbeams parallel to longitudinal cornered bar. The
relations between observed maximum crack widthand average corrosion penetration are also presented
in Fig. 5. The average corrosion penetration wasdetermined from the mean value of corrosion depth
penetration for all longitudinal bars in one specimen.
The corrosion penetration at first concrete cracking
is around 30-60 micrometers for all specimens. For
the 4L2T-100S-HC specimen, it clearly shows thatthe crack width is larger than specimens having
normal concrete strength at similar corrosion levels.

0.24

B
i C i
(6) 4L2T-100S-HC

Fig. 7 Crack patterns at failure by pullout test

Fig. 4 Crack patterns at final accelerated corrosion
372

GEOMATE- Brisbane, Nov. 19-21, 2014

healthy reinforcement based on the AIJ Guideline isalso described by the dot line.
For the healthy and corroded specimen withouttransverse bars, as shown in Fig. 8(1), the maximum
bond stress (bond strength) of both specimens isrelatively small, around 2 N/mm2 and it occurred atlower slip, less than 1 mm. The corroded specimen
has a slightly higher maximum bond stress than thehealthy specimen. This may be a possibility that thecorrosion product filled the void at interface between
reinforcement and concrete and enhanced the bondstress. However, after reaching maximum bondstress, the bond stress of the corroded specimen
rapidly decreases due to the initial corrosion crack.
For specimens with transverse bars, the bondstress-slip relationship of specimen No. 3 to No. 12(Fig. 8(2)-(6)) demonstrate that corrosion reduces
the bond splitting capacity when comparing the bondstrength between healthy and corroded specimens. It
also shows that maximum bond stress for healthy
specimens mostly occurred at larger slip more than 1
mm meanwhile for corroded specimens occurred at
low slip smaller than 1 mm (brittle behavior).
As expected the presence of transverse bars
increases the bond splitting capacity for healthy
specimens. An increase in transverse bars ratio also
increases the residual bond strength for corroded
specimens. Moreover, it also shows that the presenceof transverse bars enables to maintain the bondstress after reaching maximum bond stress at least

the test results depending of presence and absence ofcorrosion and stirrups. For uncorroded (healthy)
specimens without stirrups a small number ofinclined cracks were formed starting from thebottom support as observed from the side view ofbeam (Fig. 7(1)). The typical crack patterns forhealthy specimens with stirrups were dominated byinclined cracks which have large number of cracks
and more uniformly distributed along embedment
length of longitudinal bars than specimen without
stirrups. The typical crack patterns for corroded
specimens were also dominated by inclined cracks,
however, the cracks tend to propagate parallel tolongitudinal bars or a smaller slope. This can be dueto the damage of ribs on deformed bars by corrosion
process, and may reduce a wedge action by ribs.
Bond Stress-Slip Relationships
Fig.8 shows average bond stress-slip relationshipfor healthy and corroded specimens in the dash line
and the solid line, respectively since the effect of bar
location in casting direction on the bond stress-slip
relationships was relatively small. The bond stress
was estimated by dividing the tensile load acting oneach longitudinal bar calculated from strain gages atslit on the longitudinal bar by the surface area of
longitudinal bar along the embedment length. Thus,
the results are the average bond stress alongembedment length. The calculated bond strength for

4

No.1(Healthy)

No.2(Corr. 6.2%)

2

AIJ

1

0

1

2

3

1

AIJ

2
1

No.6
(Corr. 6.1%)

0

1

2

3

0

4

1

2

3

4

Slip (mm)(1) 4L0T-∞S-NH&NC(2) 4L2T-200S-NH&NC(3) 4L2T-100S-NH&NC

2
No.8(Corr. 5.4%)

5

5

4

4

AIJ

3
2

No.9
(Healthy)

No.10(Corr. 5.8%)

1

1

2

3

4

AIJ

3
2
No.11
(Healthy)

No.12(Corr. 5.7%)

1
0

0

0
0

3

Slip (mm)

AIJ

1

No.5
(Healthy)

4

Slip (mm)No.7(Healthy)3

No.4(Corr. 5.8%)

0Bond Stress (N/mm2)

4

AIJ

2

4

5
Bond Stress (N/mm2)

3

0

0

No.3
(Healthy)

Bond Stress (N/mm2)

3

5
Bond Stress (N/mm2)

4

Bond Stress (N/mm2)

5Bond Stress (N/mm2)

5

0

1

2

3

4

0

1

2

3

Slip (mm)Slip (mm)Slip (mm)(4) 4L4T-200S-NH&NC(5) 3L2T-100S-NH&NC
Fig. 8 Average bond stress-slip relationship(6) 4L2T-100S-HH&HC

373

4GEOMATE- Brisbane, Nov. 19-21, 2014

one third of maximum bond stress at larger slip
because transverse bars can prevent bond splitting
crack from widening. In addition, the initial bondstiffness is very high due to chemical adhesion
between concrete and steel bars, as a result, a slip tothe bond stress of 2 N/mm2 at beginning is only
about 0.02 mm, as reported by Aryanto et al. [4].
The bond-slip relationship for specimen withhigh concrete strength as shown in Fig. 8(6) has alarger maximum bond stress than for normal
strength specimens, such as more than 4 N/mm2 forhealthy bars. This indicates significant contributionof concrete strength on bond capacity. However, thebond stress decreases rapidly after the maximum
bond stress to lead a brittle behavior.

NUMERICAL SIMULATIONS FOR ASSESSMENT OF CORRODED RC COLUMNS
To simulate the effect of corrosion on structural
performance of a corroded reinforced concrete
column, FE analysis was carried out with special
attention in transformation of material properties ofreinforcements, concrete and bond properties due tocorrosion. The configuration of column is based on
the experimental test conducted by one of authors
before. However, some modification was made bychanging the longitudinal bar diameter and the steel
strength of longitudinal and transverse bars to makethe column failed in flexure for uncorroded columns.
FE model are summarized in Fig 10. The mechanicalproperties of current concrete and reinforcement aresummarized in Fig 11, corresponding to corrosion
level. The steel bars used a bi-linear model withoutstrain hardening. The stress generated on transversebars due to expansion of corrosion product isconsidered to be taken into account in the analysis
using the apparent yield strength. The bond stressslip relationship of longitudinal bar as estimated inthis study were adopted, as shown in Fig. 12 .

Bond Splitting Capacity

Normalized ave. bond strength

The average bond strength of each specimen
normalized with respect to that of the healthy
specimen without stirrups (No.1) plotted against
stirrups ratio is shown in Fig. 9. The test data
conducted by Morita et al. [6] which have stirrups
ratio of 0.58 was added into the graph. From Fig. 9,
for healthy specimens an increase of bond splitting
capacity was observed with increasing stirrups ratio
as illustrated by linear regression curve, solid blackline. As indicated by a linear regression of corroded
specimens, dash line, the test results showed bonddeterioration due to effect of corrosion. However, as
shown in Fig. 9 an increase in transverse bars ratio
generated higher residual bond splitting capacity.
This shows substantial contribution of confinement
provided by transverse bars in corroded specimens.
From Fig. 9, the decrease of bond strength ofcorroded longitudinal bar can be estimated for
different confinement level, or considering the
reduction area of transverse bar that might beoccurred when transverse bar also experienced
corrosion. Although the experimental data showed ascatter, the tendency of both effect of corrosion andtransverse bars ratio was identified.

0 or 0.1 constant axial load ratio
3050

Q (disp. controlled shear load
keeping vertical disp. uniformly)

900@60x14=840

Cross section: 340 mm×340 mm
Shear span ratio: 1.3
Concrete: plane stress element
Main rebar: 8-D19 with bond-slip
Shear rebar: φ8@60 with perfect bond5030

linear steel element(unit: mm)
50 60x4=240 50
340

Fig. 10 Finite element modelε

2.5

10ε max

ε max
15

σ N mm 2σ B σtTensile zone

Corrosion
Effect2
1.5

G f = 0.1 N / mm

Compressive zone

Stirrups
Confinement

σB

1
4

σt

σ N mm 2

0
0

0.2

0.4

0.6

W mm

Concrete
Longitudinal
Transverse
Corr.
σB
Ec
σt
σy
Es
σwy
Ews
level N/mm2 N/mm2 N/mm2 N/mm2 N/mm2 N/mm2 N/mm2
0%48 34300 2.8
345 2.00E+5 295 2.05E+5
3%
32 26700 1.9
325 1.93E+5 208 1.98E+5

Concrete
Confinement

Healthy
Corrosion (4-6%)

0.5

W2

W1

1

0.8

Transverse bars Ratio (pw)Fig. 9 Normalized ave. bond strength with respect tothat of the healthy specimen without stirrups

6%

26

24100

1.5

304

1.86E+5 130

1.91E+5

10 %

26

24100

1.5

277

1.71E+5

1.82E+5

39

Fig. 11 Mechanical properties for concrete and rebar
374

GEOMATE- Brisbane, Nov. 19-21, 2014

2) Concrete strength has a significant influence on
the crack width growth rate and the stressincrease of the transverse bars because of thedifference of porosity in hardened cement paste.
3) The pullout tests show that the lower maximum
bond stress and smaller slip at maximum bondstress are shown for corroded reinforcement andafter reaching maximum bond stress, the bondrapidly deteriorates for corroded reinforcement.
4) An importance contribution of transverse bars tomaintain residual bond splitting capacity forcorroded specimens. The more transverse bar isprovided, the higher residual bond splitting
strength is generated.
5) FE analysis show that the failure mode of RC
columns can be changed with increasing
corrosion levels from flexural failure precededby yielding of longitudinal bars to shear failure
before bar yielding which indicate a brittle
behavior.

Fig.13 shows the shear force and rotation angleof columns under no axial force and axial force ratioof 0.1. The shear force-rotation response of healthy
column is firstly specified by formation of bending
crack mostly located at top and bottom of column,
followed by bending shear cracks and then yieldingof longitudinal bar until reaching the maximum
force as shown in Fig.13. Compared to the corroded
columns, the cracking events and the yielding of
longitudinal bar are almost the same with the healthy
column except for specimens having an axial force
and corrosion levels of 6% and 10%. From theanalysis results it shows that larger corrosion level
increases the possibility to have shear cracking at
low load level. Moreover, the axial force promotes ashear failure before yielding of longitudinal bars asshown in Fig. 13 (2). This can be attributed to thelower apparent yield strength of transverse bar andbond deterioration induced by corrosion cracking
due to corrosion expansion. This analysis also leads
to the recognition that the failure mode of RC
columns can be changed with increasing corrosion
levels from flexural failure preceded by yielding of
longitudinal bars to shear failure before bar yielding
which indicate a brittle behavior.

ACKNOWLEDGEMENTS
The authors acknowledge the supports of the
Nuclear and Industrial Safety Agency as a part of the
project on enhancement of Ageing Management andMaintenance of Nuclear Power Stations.

Bond (N/mm2)
Corr.
τ1
τ max
s1
level N/mm2 N/mm2 mm
0%2.05.60 0.02
2.0
3%
5.26 0.02
2.0
6%
4.93 0.02
2.0
10 %4.48 0.02

τ max
τ1
s1

s max
Slip (mm)

smax
mm
1.00
0.91
0.82
0.70

REFERENCES[1] Aryanto, A. and Shinohara, Y., ”Influence of
Bond-Slip Relationship and Tensile Strength on
Bond Behavior between Corroded Bar andConcrete,” J. Structural and Construction Eng.,AIJ, Vol.78, No.685, 2013, pp.559-567[2] Al-Sulaimani, G. J. et al., ”Influence ofCorrosion and Cracking on Bond Behavior andStrength of Reinforced Concrete Members,”
Structural Journal., ACI, Vol.87, No.2, 1990,
pp.220-231[3] Hanjari, Z., Coronelli, D. and Lundgren, K.,”Bond Capacity of Severely Corroded Bars withCorroded Stirrups,” Magazine of Concrete
Research, Vol.63, No.12, 2011, pp.953-968[4] Aryanto, A. and Shinohara, Y., “Cover Crackwidth Propagation of Reinforced Concrete
Members Induced by Corrosion,” Proc. of theJapan Concrete Institute 2013, Vol.35, No.1,
2013, pp. 1123-1128.
[5] Kurumisawa, K. and Tanaka, K. Difference inthe void structure of each driving height of thecement paste. Proceeding Japan Concr. Inst.
Res. 23, 781–786 (2001).
[6] Morita et al., “Bond Behavior of RC Memberswith Corroded Longitudinal Reinforcement,”
Proc. Annual Meeting of AIJ, 2011, pp.411-414

Fig. 12 Analytical model for bond-slip relationship
Shear Force Q (kN)

400

0%

0%

300

3%

3%

200

6%

100

10 %

6%

10 %

Shear failure
0
0.0

0.5

1.0

1.5 0.0

0.5

1.0

1.5

Rotation angle R (%)
Rotation angle R (%):bending cracks,:bending-shear cracks,:maximum:yielding transv. rebar,:yielding long. rebar(2) Axial force ratio=0.1(1) No axial force
Fig. 13 Analytical model for bond-slip relationship
CONCLUSION
1) Corrosion rate is not uniformly distributed
among longitudinal bars in a beam and overperimeter of bar caused by the different of bar
location in casting direction, the direction ofchloride diffusion, and the supply availability ofwater and oxygen.
375

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SURFACE HEAT REDUCTION OF ASPHALT CONCRETE BY TOPFILLING WITH RECYCLED AGGREGATES AND MINERALMORTAR
Mohammad Raihanul Islam1, Satoru Ishiguro1, Masayoshi Yamanaka2
1
Graduate School of Bioresources, Mie University, Japan
2
Asahidoboku Co., Ltd., Yokkaichi, Japan
ABSTRACTThe study was an attempt to elucidate the compressive strength of selected recycled aggregates and mineralmaterial (slag) mortar in different curing condition, brightness and heat absorption characteristic of thepavements surface. Mortar was top filled on open graded asphalt concrete by vibrator. The compressive strength
cylindrical samples sized with 5 cm Diameter And 10cm length were cured in 10℃, 20℃ and 30℃. Light
irradiation test conducted in environmentally controlled room with 30℃ and 50% R.H., 3 hours light irradiation
was applied on sample (30cmX30cmX5cm) pavements surface. At 30℃ water curing samples showed the best
result for all the RS mortar and 20℃ water curing showed the highest compressive strength for all the oyster
shell (OS) mortar except high early strength Portland cement (HSPC)-OS mortar due to the higher curing
temperature. Highest compressive strength of HSPC-OS mortar was for 20℃ air curing sample. In color andlight irradiation test showed the same result and according to those test result; heat was absorbed and hold inpavement surfaces according to: OS-slag < HSPC-OS < OS < White Portland Cement-Sand < Slag-Sand < Sand
< Asphalt.
Keywords: Recycled Aggregates, Mineral Material, Mortar Strength, Color, Light Irradiationa sort of capillary flow. This happens naturally when
the temperature is high enough, for example during
summer, although it can be also promoted artificiallyby induction heating or by microwave heating [6].
Objectives of this paper is to investigate theeffect of curing temperature, air and water curing on
mortar strength, to find out the most suitable curingcondition of the recycled aggregate and mineral(slag) mortar and to the effective use of theexperimental aggregates for surface heat reductionof asphalt concrete

INTRODUCTION
In Mie prefecture oyster farming is prosperingand discharges a large quantity of oyster shell. Someof the shells are pulverized in factory after removing
salt and utilized as an oyster shell [1].
WOS (waste oyster shell) sand can be resourcesof pure calcareous materials and effective inreplacement of sand, indicating appropriate
application of oyster shells, it is feasible to use in
CLSM (controlled low-strength materials) [2].
In the financial year 2012 Japan produced 24639
thousand tons of blast furnace slag and 72.6% of thatwas used in cement industry [3].
Nowadays, there is an increasing interest in theutilization of waste materials. In the case of
construction industry there was a growing trend
towards the development and use of waste as
supplementary cementitious materials [4].
Asphalt concrete is a temperature dependantmaterial that may fall within a category of materials
defined as brittle or quasi-brittle particularly atsubzero temperatures [5].
Highways are rather high cost structures, and forthat reason, it is obligatory that the materials to be
used for their constructions should be appropriately
designed [4].
Bitumen starts behaving like a Newtonian fluidat temperatures ranging from 30 ℃ to 70℃. Abovethese temperatures, bitumen may start flowing
through any possible crack open in the pavement, in

MATERIALS AND METHODS
Materials
Slag
Blast-furnace slag was used in this study. It wascollected as the steel industry by-product withspecific chemical composition (Table 1). The slag
was used with specific surface area of 4000 cm2/g
and the density was 2.88 g/cm3.
CementThree types of cement were used in this study:
Ordinary Portland Cement (OPC) with the density of
3.16 g/cm3 and specific surface area of 3290 cm2/g;
high early strength Portland cement (HSPC) with thedensity of 3.14 g/cm3 and specific surface area of376

GEOMATE- Brisbane, Nov. 19-21, 2014

4410 cm2/g and white Portland cement (WPC) withthe density of 3.05 g/cm3 and specific surface area of
3440 cm2/g.

by the help of vibrator with 1cm thickness.
Test procedure

Sand

Three cylindrical samples were used for each ageof curing. Samples produced from study aggregateswere kept in 10℃, 20℃ and 30℃ constant room
temperature for all the category just after to fill inthe mould according to the experiment design anddemoulded after three days, then, samples were
cured in water at 10℃, 20℃ and 30℃ constant room
temperature and in air at only 20℃ constant room
temperature, until the samples were used forcompressive strength measurement at 3, 7, and 28
days. Compressive strength of each specimen wasdetermined using universal testing machine with JIS
A 1108[7].
Color test was performed with Digital Color
Reader (CR -13, Konica Minolta Optics Inc.) by the
direction of the instrument manufacturer which was
followed by JIS Z 8721[8].
The asphalt-mortar samples were stored for thetest in a controlled room at 30℃ and with R.H. 50%.
Every sample placed in cork sheet frame (30cm x
30cm x 5cm) and was kept in the light irradiation
test room for 24 hours before the test for the purposeof temperature adjustment. The beam lamp
Irradiation was continued on the sample block forthree hours. The data logger was received and stored
data for total about 15 hours.
The expressions of acronym used in this paper
are shown in Table 2.

River bed sand was used in the study. Unit
weight of the used sand was 2.60 g/cm3 and thefineness modulus (FM) was 3.13.
Oyster shell
The oyster shell is a waste product produced
from oyster farming. Oyster shell aggregate
collected from an oyster shell processing factory,
Toba city in Mie Prefecture, Japan. Collectedmaterial pulverized in crushed form with the densityof 2.29 g/cm3 maximum size of 2 mm filled incommercial bag with specific specification
Asphalt concrete
Asphalt
concretepavement
block(30cmx30cmx5cm) was made and collected from
Asahidoboku Co. Ltd., Yokkaichi, Japan
Table 1 Chemical composition of ground granulated
blast furnace slag
Chemical compositions(%)
Ignition loss
SiO 2
Al 2 O 3
FeO
CaO
MgO
TiO 2
MnO
SO 3
Na 2 O
K2 O
Cl-

S-40
JIS A 6205 Test Value
≤3.0
1.08
33.24
13.87
0.32
42.51
≤10.0
5.32
0.51
0.12
≤4.0
1.92
0.20
0.31
≤0.02
0.008

Table 2 Expressions of Acronym
Acronym
OPC

Ordinary Portland cement.

HSPCHigh early
cement.

WPCWhite Portland cement

S-0%,
50%,........
S-40/Slag40
RS

Sample preparation
Mortar was prepared by different experimental
materials with design mixing proportion. Cylindricalsamples were prepared from mortar for theexperiment with 50 mm diameter and 100 mm
height. Binder aggregate ratio was 1:2 all cases.
Slag was used 75% in OS mortar and 50% in sandmortar. Specific water binder ratio was used toprepare the mortar. For oyster shell mortar; waterbinder ratio was 1.1. For oyster shell-slag mortar;water binder ratio was 1.15. For River sand mortar
in different conditions; water binder ratio was 0.5.
The above mentioned mortar was filled on asphalt
concrete pavement sample block (30cmx30cmx5cm)

OS
GGBFS

377

Original expression

strength

PortlandMortar with specific % of slag
content.
Slag with specific surface area of4000 cm2/g.
River bed sand.
Oyster shell aggregate.
Ground Granulated Blast Furnace
Slag.

Wc

Water curing

Ac

Air Curing (Temperature: 20℃;
R.H.: 55-65% )GEOMATE- Brisbane, Nov. 19-21, 2014

Compressive Strength (N/mm2)

RESULTS AND DISCUSSION

Compressive strength of RS mortar with
OPC and no slag content (Fig. 1) in all ages
was highest for 30℃ water curing and at 28
days that was about 6.5% more than 20℃ and
12% more than 10℃ water curing and lowest
for 10℃ water curing. Strength for 20℃ waterand air curing was almost same up to 7 days
and finally at 28 days the lower strength
recorded for air curing samples even than 10℃
water curing that was about 10.5% less than
20℃ and 5% less than 10℃ water curing.
About 30℃ water curing is recommended
for RS mortar with OPC and no slag content
and air curing in this case should be avoided.

40
30
20
10
0

3 Days10℃ Wc20℃ Ac7 Days28 Days
20℃ Wc30℃ WcStrength of RS mortar with WPC andno slag content.
Compressive strength of RS mortar with
OPC and 50% slag content (Fig. 3) in all ages
was highest for 30℃ water curing and at 28
days that was about 19% more than 20℃ and
66% more than 10℃ water curing and lowest
for 10℃ water curing. Strength for 20℃ air
curing was almost same or more than 20℃
water curing up to 7 days but at 28 days it wasalmost same as 10℃ and 40% less than 20℃
water curing.

50
40
30
20
10
3 Days10℃ Wc20℃ Ac7 Days28 Days
20℃ Wc30℃ WcCompressive Strength (N/mm2)

Compressive Strength (N/mm2)50

Fig. 260

060

Strength of RS mortar with OPC and noslag content.
Fig. 1

Strength for RS mortar with WPC and noslag content (Fig. 2) up to 7 days was highest
for 30℃ water curing and at 7 days that was 4%higher than 20℃ and 17% higher than 10℃
water curing and lowest for 10℃ water curing,
finally at 28 days it was almost same for allcases except 20℃ air curing. At 28 days 20℃
air curing samples showed about 23% and 21%
less strength than 20℃ and 10℃ water curingrespectively.
For RS mortar with WPC and no slag
content water curing at 10℃to 30℃ will givethe different strength at initial age but same onlater age. Air curing could give initial higher
strength and on later age it might be lower.

60
50
40
30
20
10
0

3 Days10℃ Wc20℃ Ac7 Days28 Days
20℃ Wc30℃ WcFig. 3 Strength of RS mortar with OPC and
50% slag content.

Compressive strength of OS mortar with
OPC and no slag content (Fig. 4) was highest
for 20℃ and 30℃ water curing and lowest for
10℃ water curing condition and at middle age
all of that were almost same except 10℃ water
curing with lower trend. Finally 20℃ and
10℃water curing samples showed the highest

378

GEOMATE- Brisbane, Nov. 19-21, 2014

Compressive Strength (N/mm2)

and lowest compressive strength respectively
whereas 20℃ air curing and 30℃ water curing
samples showed the same result.
For 20℃ water curing condition could be
used for OS mortar with OPC and no slag
content samples and 20℃ air curing and 30℃
water curing samples showed no difference instrength on later age.
20
18
16
14
12
10
8
6
4
2
0

3 Days

7 Days10℃ Wc20℃ AcFor OS mortar with OPC and 75% slag
content (Fig. 6); 30℃ and 10℃ water curing
sample showed the highest and lowest strength
up to 7days.At final age 20℃ water and air
curing showed the highest and lowest strength
whereas 10℃ and 30℃ water curing showed
the same result.
20℃ water curing condition could besuitable for long time strength gain whereas
20℃ air curing showed the reverse trend.
For the above results of RS and OS mortar it
was very much clear that higher curing
temperature is preferable for the compressive
strength due to the higher rate of hydration of
cement and thus 30℃ curing temperature gave
the better result than 20℃ and 20℃ was better
than 10℃ condition. Feng Lin et al (2009)
showed that the hydration reaction rateincreases with the increase in temperature andthe density of hydration products at higher
temperature is higher [9].

28 Days
20℃ Wc30℃ WcCompressive Strength (N/mm2)

Fig. 4 Strength of OS mortar with OPC andno slag content.

Compressive Strength (N/mm2)

In case of OS mortar with HSPC and no slag
content (Fig. 5) at early age 30℃ and 10℃
water curing showed the highest and lowest
compressive strength respectively, 20℃ air andwater curing samples showed the same result.
At middle age 20℃ air curing samples showed
the highest strength within the all samples andfinally it was highest; 14% more than 30℃ and31.5% more than 20℃ water curing andstrength in all other condition was almost same.
20
18
16
14
12
10
8
6
4
2
0

20
18
16
14
12
10
8
6
4
2
0

3 Days10℃ Wc20℃ Ac7 Days28 Days
20℃ Wc30℃ WcStrength of OS mortar with OPC and
75% slag content.
Fig. 6

3 Days10℃ Wc20℃ Ac7 DaysBrightness of the study pavement was measured
and expressed as numerical value. Brightness was
directly related with absorption and holding the heatof the sample. Brightest sample showed the lowest
surface heat in this study.
Within the study pavement OS-Slag mortar
sample showed the highest brightness and theasphalt with no mortar filling showed the lowest(Fig. 7). Within the sand mortar pavements; WPCSand mortar showed the highest brightness and
OPC-Sand showed the lowest and within the OS
mortar pavements; OS-Slag mortar showed thehighest and OS mortar showed the lowest brightness.

28 Days
20℃ Wc30℃ WcFig. 5 Strength of OS mortar with HSPC andno slag content.

379

GEOMATE- Brisbane, Nov. 19-21, 2014

From the above discussion it could be said thatheat will be absorbed and hold in experimental
pavement
accordingto:OS-slag<HSPCOS<OS<WPC-Sand<Slag-Sand<Sand<Asphalt.

75.9

HSPC-OS

74.2

OS

71.8

Slag-Sand

65
60
Temperature (℃)

OS+slag

reduced 30% (14.2℃), HSPC-OS mortar reduced
32% (14.8℃) and OS-Slag mortar reduced 36%(16.1℃) in compare with asphalt concrete pavementwith no top filling (Fig. 9).

65.9

WPC-Sand

70.8

Sand

61.1

Asphalt

18.1

Temperature (℃)

55
50
45
40
35
30
12

0

3

6
9
Time (hr)1215

OPC-Sand
OPC-Slag-Sand
HSPC-OS

From the above discussion heat was absorbed
and hold in pavement samples bottom and surface
accordingto:“OS-slag<HSPC-OS<OS<WPCSand<Slag-Sand<Sand<Asphalt” which supports
completely the colour test results and proved theconsistency of the both test results. This was due tothe variation of brightness and absorption of heat by
the experimental pavement surfaces.
Ishiguro et al. (2011) showed that heat reflecting
pavements reduced their surface temperature due tothe increasing in reflectance of solar radiation on the
pavement surface [1]. K. Hayashi (2014) alsomentioned that heat effects are caused by the heatabsorption and reflectance with surfaces [10].

60Asphalt
WPC-SandOS mortar
OS-Slag35

Fig. 9 Surface temperature of the experimental
pavements.

65

6
9Time (hr)40Asphalt
WPC-SandOS mortar
OS-SlagAsphalt pavement with top filling by OPC-Sand
mortar reduced the bottom heat by 12% (6℃), WPCSand mortar reduced by 20% (9.2℃), OPC-SlagSand mortar reduced 17% (8℃), OS mortar reduced
22% (10.3℃), HSPC-OS mortar reduced 25%(11.2℃) and OS-Slag mortar reduced 29.5%(12.8℃) in compare with asphalt concrete pavementwith no top filling (Fig. 8).

3

45

25

Fig. 7 Brightness of the sample pavements surface.

0

50

30

0 10 20 30 40 50 60 70 80
Brightness

25

55

CONCLUSION

15

About 30℃ water curing is recommended for
RS mortar with OPC and no slag content and air
curing in this case should be avoided. For RS mortar
with WPC and no slag content water curing at thetemperature of 10℃to 30℃ will give the different
strength at initial age but same on later age. Air
curing could give initial higher strength and on later
age it might be lower. 30℃ water curing is suitablefor RS mortar with OPC and no slag content and air
curing in this case should be avoided. For 20℃
water curing condition could be used for OS mortar
with OPC and no slag content samples and 20℃ air
curing and 30℃ water curing samples showed no

OPC-Sand
OPC-Slag-Sand
HSPC-OSFig. 8 Bottom temperature of the experimental
pavements.
Asphalt pavement with top filling by OPC-Sand
mortar reduced the surface heat by 18% (9.3℃),
WPC-Sand mortar reduced by 28% (13.3℃), OPCSlag-Sand mortar reduced 23% (11.5℃), OS mortar
380

GEOMATE- Brisbane, Nov. 19-21, 2014[4] S_ebnem Sargın , Mehmet Saltan , Nihat
Morova , Sercan Serin, Serdal Terzi,“Evaluation of rice husk ash as filler in hot mix
asphalt concrete”, Construction and Building
Materials, Vol. 48, 2013, pp. 390–397.
[5] S. Pirmohammad, M.R. Ayatollahi, “Fracture
resistance of asphalt concrete under different
loading modes and temperature conditions”,
Construction and Building Materials, Vol. 53,
2014, pp. 235–242.
[6] Alvaro García , Moises Bueno, Jose
Norambuena-Contreras, Manfred N. Partl,“Induction healing of dense asphalt concrete”,
Construction and Building Materials, Vol. 49,
2013, pp. 1–7.
[7] Japanese Industrial Standards Committee. JIS A
1108: Method of test for compressive strengthof concrete.
[8] Japanese Industrial Standards Committee. JIS Z
8721: Color specification - Specificationaccording to their three attributes.
[9] Feng Lin , Christian Meyer Hydration kinetics,“Modeling of Portland cement considering theeffects of curing temperature and appliedpressure”, Cement and Concrete Research, Vol.
39, 2009, pp. 255–265.
[10] K. Hayashi, “Study on concrete Material
Technologies to Mitigate the Urban Heat Island
Effect”, Concrete Journal, Vol. 52(3), Mar.
2014, pp. 273-279.

difference in strength on later age. 20℃ air curing
was the most suitable condition for OS mortar with
HSPC and no slag content and was one of the newlearning of this study. 20℃ water curing condition
could be suitable for long time strength gain whereas
20℃ air curing showed the reverse trend. According
to the color test result it could be said that heat will
be absorbed and hold in experimental pavement
accordingto:OS-slag<HSPC-OS<OS<WPCSand<Slag-Sand<Sand<Asphalt.
From
light
irradiation test result heat was absorbed and hold inpavement samples surface according to: “OSslag<HSPC-OS<OS<WPC-Sand<SlagSand<Sand<Asphalt” which supports completely thecolour test results.
REFERENCES[1] Satoru Ishiguro and Masayoshi Yamanaka,“Heat
ControlofPavement
SurfaceTemperature Using Oyster Shell Lime”, FirstInternational Conference on Geotechnique,
Construction materials and Environment, Mie,
Japan, Nov.2011, pp. 353-356.
[2] Wen-Ten Kuo, Her-Yung Wang, Chun-Ya Shu
and De-Sin Su, “Engineering properties ofcontrolled low-strength materials containing
waste oyster shells”, Construction and Building
Materials, Vol. 46, 2013, pp. 128–133.
[3] NIPPON SLAG ASSOCIATION, Japan,(online),<http://www.slg.jp/e/statistics/index.html>

381

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

ASPHALT BINDER EXTRACTION FROM ASPHALT CONCRETE
USING PULSED POWER TECHNOLOGY
Rétyce Ivan Hervé Dodji Togbé Amoussou, Youhei Takanabe, Nobuyasu Oyama,
Eva Arifi, Koichi Ishimatsu and Mitsuhiro Shigeishi
Graduate School of Science and Technology, Kumamoto University, Japan

ABSTRACT
Here, authors propose a pulsed power application to reclaiming aggregate from asphalt concrete lumps. This
study aims at extracting asphalt binder from controlled specimens of asphalt concrete using pulsed power
technology and evaluating the quality of the asphalt concrete recycled aggregate. Pulsed power was discharged
into 5% asphalt content straight and modified asphalt concrete specimens. The results demonstrate that theextraction of modified asphalt binder from asphalt concrete is more difficult than that of straight asphalt and also
requires more energy to produce approximately 1% asphalt content recycled coarse aggregate. Furthermore, theresults suggest that recycled aggregate quality increases with increasing pulsed power energy.
Keywords: Asphalt concrete, Modified asphalt, Recycled aggregate, Pulsed power technology

Hence, implementation of asphalt concrete
recycling methods that enhance quality of therecycled asphalt mixture by reducing the impact ofdeteriorated asphalt and modified asphalt binders isessential.
For ordinary concrete, the crushing processes tomake recycling aggregate have been overcome bypulsed power discharge inside ordinary concrete
waste to produce high-quality recycled coarse
aggregate [5]. Reference [6] defined pulsed power
discharge as a technique that spatially andtemporally compresses and superimposes stored
energy, thereby concentrating, controlling, andtransmitting a large amount of power within a small
space, for only a short time. This technique was lessenergy consuming and resulted in good quality
aggregate that was as strong as the original
aggregate to satisfy the JIS regulations for recycledcoarse aggregate for concrete class H [7].
Unfortunately, to date, no study has investigated
the applicability of pulsed power technology torecycle asphalt concrete. This study focuses on an
application of pulsed power technology to solve
problems associated with asphalt concrete recycling,
notably modified asphalt concrete. Thus, theobjectives of the present study are asphalt binder
extraction from asphalt concrete specimens using
pulsed power technology and quality evaluation of
the recycled aggregate.

INTRODUCTION
In Japan, a considerable amount of constructionwaste consists of both ordinary and asphalt concrete
while only half of the total amount of asphalt
concrete waste is recycled as materials for surfaces,binder, or base courses [1].
Asphalt concrete is a composite material inwhich a bituminous material called asphalt cementbinds coarse and fine aggregate, and filler. For road
construction, either straight or polymer modified
asphalt concrete can be utilized as binder. In thelatter case, straight asphalt is modified to improve its
binding properties with rubber or polymers
incorporated into straight asphalt to improve
resistance to rutting and cracking [2].
Asphalt concrete recycling has been promoted tosatisfy the requirements to be cost-effective,
environmentally responsible, and perform well.
However, asphalt concrete recycling for modified
asphalt pavement has some problems and does notlead to technical establishment.
While straight asphalt concrete is easily recycled
relatively efficiently, recycled modified asphalt
concrete presents problems of fatigue resistance [3].
Moreover, the incorporation of different types ofasphalt concrete waste from various sources and theaccidental mixing of debris cause inconsistencies
and unpredictable behavior of recycled asphalt
mixes.
Prevention of breakdown of recycling equipment
during modified asphalt concrete recycling isessential [4]. Furthermore, the recycled asphalt
mixture may be unpredictable and thus less durable
due to the difficulty of mix design and the quality
control by the reuse of modified asphalt waste.

EXPERIMENT
Control Specimens
Control specimens produced by Showa Rekisei
Industries Co., Ltd. Kumamoto Mixture Factory,
382

GEOMATE- Brisbane, Nov. 19-21, 2014

Kumamoto, Japan were approximately 1.2 kg ofboth straight and modified type H [8] asphalt
concrete specimens (Fig.1). Those characteristics areshown in Tables 1 and 2.

Fig. 11

𝐸𝐸 = 𝐶𝐶(𝑉𝑉)2(1)

2

where E is pulsed power discharged energy, C is thecapacitance of the Marx generator, and V is voltage
across the Marx generator.

Asphalt concrete control specimen

Table 1 Mix proportions ofcontrolled specimens

asphalt

concrete

Coarseaggregate

Fine aggregate
and Filler

Asphalt

57.60%

37.40%

5%

Fig. 2Marx Generator

Table 3 Marx generator parameters
Voltages (kV)Capacitance of theMarx generator(μF)

Table 2 Properties of straight and modified type Hasphalt
Asphalt
types

Softening
point (oC)

Penetration(10-1 mm)

Ductility(cm)

Straight (S)44.0 52.0
95.0

60 - 80

≥ 100

45.0

93.0

Modified H
(MH)

30

40

8

8

Table 4 Conditions of pulsed power discharge
inside straight asphalt specimens
Voltage(kV)

Pulsed Power Discharge into Asphalt Concrete30
30

The authors have proposed a pulsed power
application to extract asphalt binder from asphalt
concrete. Pulsed power is a technology in whichenergy is accumulated over a relatively long periodof time and then discharged in short pulses with
controllable repetition rate thus increasing its
instantaneous power [9].
Pulsed power energy (Eq. (1)) was discharged
into both, straight and modified type H asphalt
concrete specimens submerged in water (Fig.3)
using a Marx generator (Table 3) under theconditions shown in Tables 4 and 5.
The pulsed power discharged energy is
calculated using;Number ofdischarges
on 5mmmesh
25
50

Number ofdischarges
on 2.5 mm
mesh
25
50

Total
discharged
energy
(kJ)
180
360

Table 5 Conditions of pulsed power discharge
inside modified type H asphalt specimens
Voltage
(kV)

30
30
30
383

Number ofdischarges
on 5mm
mesh
50
75
100

Number ofdischarges
on 2.5 mm
mesh
50
50
50

Total
discharged
energy
(kJ)
360
450
540

GEOMATE- Brisbane, Nov. 19-21, 2014

Not only is asphalt concrete composed of asphalt
binder and aggregate but also it is composed of air
voids. The discharge of pulsed power inside asphalt
concrete causes the dielectric breakdown of the gas
inside air voids. As a result, the generated plasma
induces shock waves followed by tensile stress thatremove the asphalt binder from aggregate surface.

Water
Discharge electrode

Pulsed power discharge procedure

Asphalt concrete
specimen

Pulsed power was discharged inside asphalt
concrete controlled specimens on stainless steel
meshes with apertures of 5 mm and 2.5 mm toseparate them into both recycled aggregate over 5mm; and over 2.5 mm and the residues under 2.5mm containing the extracted asphalt binder. The
process is as follows: at the start, after discharging
the required pulsed power energy on the asphalt
concrete specimens on the 5 mm mesh, theremaining recycled aggregate over 5 mm wascollected. Then, on the 2.5 mm mesh, the sameprocess was applied on the other part of the asphalt
concrete specimens which size was smaller or equal
to 5mm to produce the over 2.5 mm recycled
aggregate. At the end, the products which size wassmaller or equal to 2.5 mm were categorized as theresidues under 2.5 mm (Fig. 3 and Table 6).

5mm apertures
stainless steel mesh
Pulsed power dischargea)Pulsed power discharge into specimens on 5mm apertures stainless sieve

Recycled aggregate
over 5mm

Table 6 Size of pulsed power discharge products
5 mm apertures
stainless steel mesh
Products smaller thanor equal to 5mmb) Production of recycled aggregate over 5 mm

Products

Recycledaggregate
over
5mm

Recycledaggregate
over
2.5mm

Residues
under
2.5 mmSize S(mm)

S>5

2.5<S≤5S≤2.5

Aggregate Recovery
To recover the original aggregate, asphalt was
extracted automatically from over 5 mm and 2.5 mm
recycled aggregate, and under 2.5 mm residues
utilizing an asphalt extraction testing machine withpropane as solvent at the Kumamoto Prefectural
Center of Constructional Technology, Kumamoto,Japan. Next, asphalt was recovered utilizing theAbson method according to ASTM D1856-09 [11].

Recycled aggregate
over 2.5 mm

2.5 mm apertures
stainless steel meshOven-Dry Density and Water Absorption Tests
Residues under 2.5mm containing
extracted asphaltc)Oven-dry density and water absorption tests were
performed on all types of recycled aggregate
according to Japanese Industrial Standards (JIS A
1109 and JIS A 1100).
Furthermore, oven-dry density tests wereconducted on virgin aggregate used to make thecontrol asphalt concrete specimens and recovered
aggregate from asphalt concrete lumps recycled
aggregate.

Production of recycled aggregate over 2.5 mm
and residues under 2.5 mm from products
smaller than or equal to 5 mm

Fig. 3

Pulse power discharge apparatus [10]384GEOMATE- Brisbane, Nov. 19-21, 2014

RESULTS AND DISCUSSION

Recycled aggregate over 5mm
Asphalt content (%)

Recycling Rates
As evident in Figs 4 and 5 with increasing pulsed
power energy the recycling rate (Eq.(2)) ofaggregate over 5 mm decreased markedly, contrary
to that of over 2.5 mm recycled aggregate, whichsignificantly increases from 128% to 141.3% forstraight asphalt and from 123% to 163% formodified type H asphalt as a result of aggregate
breaking.
𝑅𝑅 =

𝑃𝑃𝑃𝑃
𝑃𝑃𝑃𝑃

× 100

2
0

Fig. 6(2)

S - 180

S - 360

Asphalt content of recycled aggregate fromstraight asphalt concrete specimens

Recycled aggregate over 5mm
Asphalt content (%)

Recycled aggregate over 2.5mm

Recycled aggregate over 5 mm
Recycled aggregate over 2.5 mm
Recycling rate (%)

4Asphalt type - Energy (kJ)Here, R is aggregate recycling rate in percentage, PR
is proportion of recycled aggregate in percentage,
and PI is initial proportion of corresponding virgin
aggregate in asphalt concrete specimens.

150
100
50

Recycled aggregate over 2.5 mm

5
4
3
2
1
0

MH - 360

MH - 450

MH - 540

Asphalt types- Energy (kJ)

S-180

S-360

Asphalt type- Energy (kJ)Fig. 7
Fig. 4

Recycling rates of straight asphalt concrete
aggregate

As detailed in Fig. 6, for straight asphalt concrete
specimens, asphalt content of recycled aggregate
over 2.5 mm decreases to 3.41% and 3.58% from5% (whole content in a specimen) at 180 kJ and 360
kJ as pulsed power discharged energy respectively.
Asphalt content of recycled aggregate over 2.5 mm
decreases as well reaching 1.69% and 1.01% at 180
kJ and 360 kJ respectively.
As indicated in Fig.7, for type–H modified
asphalt concrete, asphalt content of recycled
aggregate over 5mm decreases to 0.97% at 540 kJ as
pulsed power discharged energy. Asphalt content ofrecycled aggregate over 2.5 mm decreases to 3.76%
at 540 kJ.
These results show that the extraction ofmodified asphalt binder is not as easy as that ofstraight asphalt and requires more pulsed power
discharge energy to produce the same asphalt
content due to the presence of polymer modifier
which increases its elasticity.
Furthermore, for both straight and type-H
modified asphalt concrete, asphalt content tests
revealed that finer recycled aggregate contained
higher asphalt content. Although asphalt content ofrecycled aggregate over 2.5 mm is higher than thatof recycled aggregate over 5 mm, asphalt content ofRecycling rate (%)

Recycled aggregateover 5 mm
Recycled aggregate over 2.5 mm

200
100
0

MH-360MH-450MH-540Asphalt type-Energy (kJ)Fig.5

Asphalt content of products from modified
asphalt concrete specimens

Recycling rates of modified type H asphalt
concrete aggregate

Asphalt Content of Recycled Aggregate
Straight and modified type H asphalt concrete
specimens required 360 kJ and 540 kJ respectively(Figs. 6 and 7) to achieve approximately 1% asphalt
content of recycled aggregate over 5 mm.

385

GEOMATE- Brisbane, Nov. 19-21, 2014

both recycled aggregate over 5 mm and 2.5 mm
decreases when pulsed power discharged energy
increases.
It could be inferred therefore that significant
amount of asphalt binder was extracted from asphalt
concrete specimens as part of the residues under 2.5mm using pulsed power discharge.

that of the virgin aggregate utilized to make thecorresponding specimens (Figs. 8 and 9).
Furthermore, an increase in pulsed power discharged
energy appears to improve the oven-dry density ofasphalt concrete recycled aggregate

Oven-dry Density

The results of water absorption tests are shownin Figs. 10 and 11. For straight asphalt, the lowest
water absorption ratio 0.73% was observed at 360 kJ
for recycled aggregate over 5 mm. For type-H
modified asphalt, the lowest 0.82% water absorption
ratio was achieved by discharging 450 kJ as pulsed
power energy. In other words, type-H modified
asphalt concrete requires more pulsed power
discharged energy to achieve approximately 0.80%
water absorption recycled aggregate over 5 mm.
According to these results it appears that the effectof pulsed power discharge on recycled aggregate
over 5 mm water absorption is similar to that on its
asphalt content and oven-dry density in terms of
quality improvement.

Water Absorption

Inspection of Fig. 8 indicates that oven-dry
density of recycled aggregate over 5 mm fromstraight asphalt concrete specimens increases from2.88 g/cm3 to 2.94 g/cm3 when pulsed power
discharged energy increases from 180 kJ to 360 kJ.
For type-H modified asphalt concrete, oven-dry
density of recycled aggregate over 5 mm increases
as well from 2.87 g/cm3 to 2.94 g/cm3 when pulsed
power discharged energy increases up to 540 kJ. It isevident from the results of oven-dry-density tests
that type-H modified asphalt concrete required moreenergy to achieve the same 2.94 g/cm3 oven dry–density recycled aggregate over 5 mm compared tostraight asphalt.

Recycled aggregate over 5mm

Fig. 8Water absorption (%)

Oven-dry density (g/cm3)

Recycled aggregate over 5 mm
Virgin aggregate over 5 mm
3
2.5
2
1.5
1
0.5
0

S-180

S-360

Virgin aggregate over 5mm
1.5
1
0.5
0

Asphalt types - Energy (kJ)Fig. 10 Water absorption of over 5 mm recycled
aggregate from straight asphalt specimens
and virgin aggregate
Recycled aggregate over 5mm

Virgin aggregate over 5 mm

MH-450

Water absorption (%)

Oven-dry density (g/cm3)

Recycled aggregate over 5 mm

MH -360

S-360

Asphalt type-Energy (kJ)Oven-dry density of recycled aggregate
over 5 mm from straight asphalt specimens

3
2.5
2
1.5
1
0.5
0

S-180

MH-540Asphalt types - Energy (kJ)

Virgin aggregate over 5 mm
1.5
1
0.5
0

MH-360MH-450MH-540Asphalt type-Energy (kJ)Fig. 9Oven-dry density of over 5 mm recycled
aggregate from modified asphalt specimens

Fig. 11 Water absorption of over 5 mm recycled
aggregate from modified type-H asphalt
specimens and virgin aggregate

For both straight and modified type-H asphalt
concrete specimens recycled aggregate over 5 mm,
the oven-dry density increases when pulsed power
discharged energy increases and is almost equal to

Furthermore, from Figs 10 and 11 it can be seenthat the effect of pulsed power discharge on water386

GEOMATE- Brisbane, Nov. 19-21, 2014absorption of recycled aggregate over 5 mm fromstraight asphalt concrete specimens is in good
agreement with that on recycled aggregate frommodified type-H asphalt concrete specimens.
Despite the relatively higher water absorption
ratio of over 5 mm recycled aggregate frommodified asphalt concrete specimens at 540 kJ,
water absorption decreases and becomes closer towater absorption of corresponding virgin aggregate
when pulsed power discharged energy increases.

this study.
REFERENCES[1] Kubo, K.: Pavement Team, Public Works
Research Institute, Japan: Recycling in Japan,
2009.
[2] Japan Modified Asphalt Association, Polymer
Modified Asphalt Pocket Guide. Japan
Modified Asphalt Association (JMAA), 2010,
pp. 3-5.
[3] Tam V, “Comparing the implementation of
concrete recycling in the Australian andJapanese constructions industries,” Journal of
Cleaner Production, Vol. 17, 2009, pp. 688-702.
[4] Su K., Hachiya Y., Maekawa R., “Laboratory
investigation of possibility of re-recyclingasphalt concretes”, Proc. 6th ICPT, 2008, pp.
435-442.
[5] Inoue S., Iizasa S., Wang D., Namihira T.,
Shigeishi M.., “Concrete recycling by pulsed
power discharge inside concrete,” Int. J. Plasma
Environmental Science and Technology, 2012,
pp. 183-188.
[6] Akiyama H., High-Voltage Pulsed PowerEngineering. Tokyo, Ohm-sha, 2003, pp. 1-2.
(in Japanese)[7] Japanese Standards Association: JIS A 5021,“Recycled aggregate for concrete-class H,”
2005.
[8] Japan Modified Asphalt Association Standard,
Quality and Test Methods of Polymer Modified
Asphalt for Road Pavement. Japan Modified
Asphalt Association (JMAA), 2007, p. 3.
[9] Bluhm H., Pulsed Power Systems: Principles
and Applications. Berlin: Springer, 2006.
[10] Namihira T., Shigeishi M., Nakashima K.,
Murakami A., Kuroki K., Kiyan T., Tomoda Y.,
Sakugawa T., Katsuki S., Hidenori A., Ohtsu M.,“Recycled coarse aggregate produced by pulsed
discharge in water,” IEEJ Trans. Fundamentals
and Materials, Vol. 6, Issue 3, 2006, pp. 197198.
[11] ASTM Standards: D1856-09, “Standard Test
Method for Recovery of Asphalt From Solution
by Abson Method,” 2009, West Conshohocken,
PA, DOI: 10.1520/D1856-09, www.astm.org.

CONCLUSION
Since pulsed power discharge inside ordinary
concrete produced high quality recycled aggregate,
the authors proposed its application to extractasphalt binder from asphalt concrete specimens.
In the course of this study, pulsed power wasdischarged into 5% asphalt content straight andmodified type H asphalt concrete. The results showthat pulsed power discharge affected aggregate

gradation by increasing the recycling rate ofaggregate over 2.5 mm up to 163% anddecreasing that of over 5mm aggregate up to
47% due to aggregate breaking. Due to the highelasticity of modified type H asphalt binder, its
extraction is more difficult than that of straightasphalt and requires more pulsed power discharged
energy. Quality of recycled aggregate improved withan increase in discharged energy characterized by
the decrease in water absorption and the increase inoven -dry density.
Further study should investigate the recovery ofmodified asphalt from the above-discussed residues
under 2.5 mm and the separation of various types ofpolymer modified asphalt into decomposed polymer
modifier and straight asphalt for separate recycling.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge thecontributions of Associate Professor Takao
Namihira, Dr. Yuichi Tomoda, Mr. Yasuo Miyazaki
and the other members of Prof. Shigeishi’s Group.
The authors would like to express their sincere
gratitude to Showa Rekisei Industries Co., Ltd.
Kumamoto Mixture Factory, Kumamoto, Japan forproviding the asphalt concrete specimens utilized in

387

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

ENGINEERING PROPERTIES OF CONCRETE INCORPORATINGWASTE CARPET FIBERS

1,2

Hossein Mohammad Hosseini1, A.S.M. Abdul Awal2, M. Zakaria Hossain3
Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
3
Graduate School of Bioresources, Mie University, Tsu-City, Japan

ABSTRACTThis paper presents test results on physical and mechanical properties of concrete containing fiber fromrecycled carpet waste. Five concrete mixes namely plain concrete (PC) i.e. concrete without carpet fibers as
control, and carpet fiber reinforced concrete (CFRC) mixes containing 0.5%, 1.0%, 1.5% and 2.0% polypropylene(PP) waste carpet fibers were made and tested for compressive, splitting tensile and flexural strengths, modulus ofelasticity and shrinkage for periods of 1, 7 and 28 days. It has been found that carpet fibers reduced the workability
and density of concrete. Concrete containing carpet fiber obtained lower compressive strength and modulus ofelasticity than plain concrete. It is observed that carpet fibers effectively improved the splitting tensile and flexuralstrengths of concrete. The obtained values of shrinkage, however, confirmed that the shrinkage strain of carpet
fiber reinforced concrete was higher than that of plain concrete. On the basis of short-term investigation, the oneyear shrinkage values of both plain concrete and concrete containing carpet fiber were also predicted byextrapolating the data obtained during this period. The results indicate that waste carpet fibers can suitably be usedas fibrous material for the production of fiber reinforced concrete with satisfactory engineering properties.
Keywords: Fiber reinforced concrete, Waste carpet fibers, Workability, Strength, Modulus of elasticity, Shrinkage.

Nylon and Polypropylene are the most synthetic
fibers used in these industries [5,6,7]. Huge amountof carpet waste is produced and part of these wastes
are in the form of fibrous materials. Generally,
industrial carpet wastes are from face and back yarns.
The face yarn is usually polypropylene or nylon fibers
and the back yarn is mainly in the form of woven
sheets (Fig.1). These fibers are mainly 50%-70%
nylon and 15%-25% polypropylene. The advantagesof using such recycled fibers include generally lower
cost to process than virgin fibers, light in weight,
good acid and alkali resistance and non-absorbent ofwater [2,5,8].

INTRODUCTION
The production and landfilling of waste are big
problems throughout the world. Recycling of thewaste materials and their use in constructionindustries are increasing in both the developed
developing countries. This has led to green andsustainable construction by reducing the cost of the
production of construction materials and waste
management. However, with the increasing
utilization of the waste materials in engineering
applications, it is necessary to understand their
physical and mechanical properties. Concrete is themost widely used construction material. However, it
has low tensile strength and low energy absorption[1]. Therefore, it is required to improve theseproperties and performance of concrete. An effective
technique to obtain these properties of concrete is byadding small fraction of short fibers to the concrete[2,3,4]. Among others, the most common fibers usedin construction are, steel fibers, synthetic fibers , suchas nylon and polypropylene, glass fibers, natural
fibers and fibers from pre and post-consumer wastes.
Since the advent of fiber reinforcing of concrete, agreat deal of testing has been led on different fibrousmaterials to determine the real characteristics andbenefits for each product. Over the decades different
types of synthetic fibers have been successfully used
to reinforced concrete.

Fig. 1 Waste products from industrial carpet: a) faceyarn b) back yarn.
The inclusion of carpet fibers is an innovative
method to improve the physical and mechanicalproperties of concrete to use these waste material inconstruction industries instead of virgin materials. In

Synthetic fibers are developed mostly to supply
the high demand for carpet and textile products.
388

GEOMATE- Brisbane, Nov. 19-21, 2014

surface dry river sand passing through 4.75 mm sieve
having water absorption of 0.70% was used as fineaggregate. The fineness modulus and specific gravity
of river sands were found to be 2.4 and 2.6,
respectively. Crushed granite of 10 mm size withspecific gravity of 2.7 having 0.5% water absorption
in a saturated surface dry (SSD) condition was used
as coarse aggregate.

the last decades numerous researchers haveinvestigated the effects of utilization of different
types of fibers in plain concrete on its engineering
properties. Wang [9,10], Vilkner et al. [11], and Zhou
and Xiang [12] have studied the effects of addition ofwaste carpet fibers on physical and mechanicalproperties of concrete. They concluded that carpet
fiber, decrease the workability and compressive
strength of concrete with reference to concrete
without using carpet fibers. However, carpet fibers
have been shown to exhibit a positive response interms of flexural strength, impact strength andtoughness of concrete [1,12,13].

The waste carpet fibers used were obtained fromENTEX Carpet Industries Sdn. Bhd, Malaysia. In thisstudy the multi-filament polypropylene carpet fibers
having 0.45 mm diameters with 30 mm length wereused and tested for their engineering properties. The
properties of the carpet fibers are shown in Table 1.
The mix proportions of carpet fiber reinforced
concrete (CFRC) are given in Table 2. A control mixof plain concrete (PC) without any carpet fibers was
also made for comparison and four fiber volume
fractions, V f of 0.5%, 1.0%, 1.5% and 2.0 were
investigated. It should be noted that, no mineral orchemical admixtures were added in concrete.

The addition of waste carpet fibers in the concrete
mix is a new area of research which needs
considerable attention. Although a number of
research works were conducted on the utilization ofthis fiber in concrete to enhance general properties ofconcrete, it necessary to conduct in-depth study on the
behavior of concrete with the wide range of mix
proportions. Since a small amount of short fibers has
been recommended for the improvement of theproperties of concrete such as impact resistance andtensile strength [14,15,16,17], it paves the way to use
PP carpet fibers to obtain desired properties in
concrete mix. The main objective of this study is toinvestigate in detail the effect of the addition of waste
PP carpet fibers on workability and density,
compressive, tensile and flexural strengths, modulus
of elasticity and shrinkage of concrete at different
volume fractions of 0.5%, 1.0%, 1.5% and 2.0%. In
addition, the engineering properties of carpet fibers
such as tensile strength, density and melting point arealso studied and presented.

Testing of Specimens
The workability of all mixes was measured by theslump test in accordance with BS EN 12350-2:2009.
Compressive strength test was conducted with 100
mm cube specimens (BS EN 12390-3:2009 and BS
EN 12390-2:2009). Cylinders measuring 100 mm x
200 mm were prepared for splitting tensile strength
test (ASTM C496 / C496M – 11) and 100 mm x 100
mm x 500 mm prism specimens were made for testing
the flexural strength at 28 days (BS EN 123905:2009). The splitting tensile strength andcompressive strength tests were measured at the ageof 1, 7 and 28 days. A short investigation for a periodof 28 days was carried out for the shrinkage test
following (ASTM C 157 and ASTM C 490). All tests
were performed at an average room temperature of
27 oC with the relative humidity, RH of 80 ± 5 %.

EXPERIMENTAL PROGRAM
Materials and Mix Proportioning
Ordinary Portland cement (OPC) with a specificgravity of 3.13 was used in this study. A saturated

Table 1 Properties of polypropylene waste carpet.
Fiber

Fiber
type

Length(mm)

Diameter(µm)

Density(kg/m3)Tensilestrength(psi)

Melting
point(oC)

Reactionwith water

PP waste carpet fiber

Multifilament

30

450

940

4700

170

Hydrophobic389

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 2 Mix proportions of concrete mixes (kg/m3).
Mix

Water

CementPC
0.5% CFRC
1.0% CFRC
1.5% CFRC
2.0% CFRC

215
215
215
215
215

430
430
430
430
430

Workability and Density
Table 3 reveals the results for the workability andwet density of concrete mixes. The slump test was
conducted to measure the workability of PC and
CFRC. As expected, the workability of concrete
containing PP waste carpet fibers with samewater/cement ratio (0.50) in all mixes was reduced theslump values ranging from 10 to 40 mm. The sturdy
fiber-matrix
bond
and
the
absenceofsuperplasticizers would have caused this reduction in
the slump value of concrete. It can be seen that theworkability of CFRC depends on the fiber volume
fraction. At V f = 0.5%, the slump value was reduced
to 40 mm compared to the 55 mm slump value
obtained for the PC. At higher volume fraction, forexample, concrete with 2.0% fiber content, the slump
values dropped to 10 mm. This indicates that theaddition of PP waste carpet fibers dramaticallyreduced the workability of concrete mix. A similar
observation has been made by Wang et al. [2], whoreported the increase of waste carpet fiber content
reduced the slump value even to near zero for highamount of fibers.

Fresh concretedensity (kg/m3)

PC

55

2385

0.5% CFRC
1.0% CFRC
1.5% CFRC
2.0% CFRC

40
20
15
10

2328
2290
2210
2150

Carpet
fiber
0.0
4.7
9.4
14.1
18.8

Mechanical Properties
Compressive strength and modulus of elasticity
Table 4 summarizes the results obtained for thecompressive strength, tensile strength, flexuralstrength, and modulus of elasticity of waste carpet
fiber reinforced concrete.
The addition of multi-filament fibers at 0.5%
dosage, a decrease of 8.6% in compressive strength
was observed. Further increase in fiber content
reduced the compressive strength further comparing
with that of plain concrete. This has also been
evidenced in the investigation by Wang et al. [2] andVilkner et al. [11] where the addition of carpet fibers
into the concrete was found to attain lower
compressive strength. Although the compressive
strength of fiber reinforced concrete was affected by
the presence of carpet fiber, the failure mode,
however, exhibited a considerable change fromfragile to a ductile state. Due to bridging action of thefiber, the cube specimens did not crush into pieces
rather holds their integrity up to the end of the test. At
typical failure mode of the 100 mm cube specimen
under compressive strength test is illustrated in Fig 2.

Table 3 Workability and density of fresh concrete.
Slump
(mm)

Coarseaggregate
910
910
910
910
910

density of about 10% was observed. This is becauseof the lower density of the PP carpet fibers (940kg/m3) that ultimately affected the whole concrete.
Therefore, this reduction in the density of concrete isan advantage of using these waste carpet fibers to
reduce the overall weight of structure.

RESULTS AND DISCUSION

Mix

Fine
aggregate
840
840
840
840
840

The values of modulus of elasticity shown in the
Table 4 are obtained from the expression (Eq. 1),
given by Neville and Brooks [18], where E c is themodulus of elasticity and f cu is the cube compressive
strength of concrete. The expected 28-day modulus ofelasticity following the expression as recommended
by BS 8110-2:1983.

In Table 3 it can be seen that the density ofconcrete decreased when carpet fiber was added tothe mixture. Concrete containing PP carpet fibers
showed a lower density than the PC. On average,
0.5% CFRC and 1.0% CFRC mixes exhibited 2.4%
and 3.9% lower density respectively as compared to
the PC. Further increase in fiber volume fraction
reduced the density; at V f = 2.0%, the reduction in

E c, 28 = 20 + 0.2 f cu, 28(1)

The results obtained in this study visibly showsthat the modulus of elasticity of concrete containing
carpet fibers in association with its lower compressive
strength was lower than that of plain concrete.

390

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 4 Mechanical properties of plain concrete and carpet fiber reinforced concrete.
Mix

Mechanical properties
Compressive
strength(MPa)
1-day 7-day

28-daySplitting tensile
strength(MPa)
1-day 7-day 28-day

Flexuralstrength(MPa)28-dayModulusof elasticity(GPa)
28-day

PC

23.4

38.2

46.5

1.6

2.2

2.7

5.3

29.3

0.5% CFRC

19.9

34.1

42.7

1.8

2.8

3.1

6.2

28.5

1.0% CFRC

15.2

28.7

29.1

1.9

2.7

3.3

5.4

25.8

1.5% CFRC

18.0

29.3

30.7

2.1

2.9

3.5

5.1

26.1

2.0% CFRC

11.4

21.7

25.5

1.9

2.6

3.0

4.4

25.1

Fig. 2 Failure mode of concrete cube under compressive load.

For example, the 28-day modulus of elasticity ofplain concrete with the equivalent compressive
strength value of 46.50 MPa was found to be 29.30
GPa. A slightly lesser value of 28.54 GPa was
obtained for concrete with 0.5% of carpet fibers
having a 28-day compressive strength of 42.70 MPa.
This is to be
expected, because the relationshipbetween compressive strength and modulus ofelasticity of concrete indicates that modulus ofelasticity increases with an increase in thecompressive strength of concrete, although there is no
accurate form of the relationship.

concrete. The 28-day splitting tensile strength of
concrete without any fiber, for example, was 2.7
MPa. At the same age a higher value of 3.5 MPa was
obtained for concrete with 1.5% carpet fiber.
The flexural strength of concrete containing
carpet fiber at 28 days for each mix is also presented
in Table 4. As can be seen in this Table the flexuralstrength of CFRC mixes were increased with respect
to that of the PC mix. On average, flexural strength
increased by 17% and 1.8% for 0.5% and 1.0% fiber
content respectively when compared with that ofplain concrete. It is interesting to note that flexuralstrength raised for fiber content of up to 1.0% andthen further increase in fiber volume fraction reduced
the flexural strength.

Splitting tensile and flexural strengths
The splitting tensile strength of both normal andfiber reinforced concrete measured at different curing
periods of 1, 7 and 28 days are also given in Table 4.
Data presented in Table 4 suggest that along withcuring time, the addition of carpet fiber in concrete
mix had a positive response on tensile strength ofDrying shrinkage
The measured values of shrinkage over a periodof 28 days are plotted in Fig. 3. It can be seen that the391

GEOMATE- Brisbane, Nov. 19-21, 2014

Shrinkage (10-6)

shrinkage strain of concrete containing PP waste
carpet fibers was higher than that of plain concrete.
The magnitude of shrinkage of plain concrete at 28
days was 490.44 x 10-6. At the same time about 9%
higher value of shrinkage i.e. 534.60 x 10-6 wasrecorded for the concrete with 0.5% carpet fiber andthis value continued to increase with the function of
the fiber volume fraction. At each age, however, thedifference in values are less. The adverse
phenomenon may be attributed to the higher porosity
in the concrete mixtures compared to that in plain
concrete due to the addition of large amount of carpet
fibers and voids produced by segregation of
aggregates. A similar tendency has been observed by
Wang et al. [2] who have used carpet fibers alongwith other recycled fibers in the concrete mix.

Following the above expression (Eq. 2), the one
year prediction shrinkage strains for concrete withdifferent amount of fiber are shown in Table 5. Data
displayed in this Table indicate that along with thetime, the addition of carpet fibers visibly increase theshrinkage strain values of concrete.
Table 5 One year predicted shrinkage values.
MixPC
0.5% CFRC
1.0% CFRC
1.5% CFRC
2.0% CFRC

28-dayShrinkage (10-6)
490.4
534.6
565.0
635.2
667.3

1-year Predicted
Shrinkage (10-6)
789.8
833.9
864.3
934.5
966.7

700

CONCLUSION

600

In this study the effects of the addition ofindustrial waste carpet fibers on properties of freshand hardened concrete have been evaluated. Based on
the experimental findings it is concluded that theaddition of carpet fibers, in general, resulted indecrease in workability, density and compressive
strength of concrete. Carpet fibers, however,effectively improved the splitting tensile strength bya maximum of about 30% at 1.5% of fibre content,
and 17% of flexural strength at 0.5% fibre content ascompared to that of concrete without any fibre.
Meanwhile, concrete containing carpet fibers showed
higher shrinkage strain values.

500
400
PC
0.5% CFRC
1.0% CFRC
1.5% CFRC
2.0% CFRC

300
200
100
0
0

10

20
30
Age (day)Fig.3 Shrinkage strain of PC and CFRC.

Although it is possible to predict long-term
behavior from short-term data, long-term
investigation including durability aspects have been
put forward as recommendation for future study inorder to understand fully the behavior of this material
in concrete.

Various expressions are available for theprediction of the development of shrinkage with time.
Among which, the equation developed by ACI 209R92-1994, is perhaps the most elaborate. Although theequation can be used to estimate ultimate shrinkage
of a wide range of moist-cured concretes, predictionof shrinkage by this equation is subject toconsiderable variation. An improvement in theaccuracy of prediction of shrinkage is made by
Neville and Brooks [18], in which long-term
shrinkage values can be obtained by extrapolating theshort-term tests of 28-day duration. The following
expression was, thus, applied to predict the one-year
shrinkage of plain concrete and concrete containing
carpet fiber.

ACKNOWLEGEMENT
The authors wish to acknowledge the cooperation and technical support received from thestaff of Structure and Materials laboratory of the
Universiti Teknologi Malaysia (UTM) in conducting
the experimental work. Special thanks to ENTEX
Carpet Industries SND. BHD, Malaysia for making
this research possible by providing waste carpet
fibers.

S h (t, τ 0 ) = S h,28 + 100 [3.61 log e (t- τ 0 ) – 12.05]1/2(2)
Where S h (t, τ 0 ) = long-term shrinkage (10-6) atage t after drying
from an earlier age τ 0 , S h, 28 =shrinkage (10-6) after 28 days, and (t – τ 0 ) = timesince start of drying (>28 days).

REFERENCES[1] Hsie M, Tu C and Song P, "Mechanicalproperties of polypropylene hybrid fiber-392

GEOMATE- Brisbane, Nov. 19-21, 2014[11] Vilkner G, Meyer C and Shimanovich S,"Proprties of glass concrete containing recycled
carpet fibers," in 6th International RILEM
Symposium on Fibre-Reinforced concretes,
Varenna, Italy, 2004.
[12] Zhou J and Xiang H, "Research on Mechanical
Properties of Recycled Fibers Concrete,"
Applied Mechanics and Materials, Vols. 94-96,
2011, pp. 1184-1187.
[13] Miraftab M, "Novel application of pre-andpost consumer carpet wastes in concrete,"
1999.
[14] Schmidt H and Cieslak M, "Concrete withcarpet recyclates: Suitability assessment by
surfaceenergyevaluation,"
Waste
Management, vol. 28, 2008, pp. 1182-1187.
[15] Song P, Hwang S and Sheu B, "Strength
properties of nylon- and polypropylene-fiberreinforced concretes," Cement and Concrete
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30, 2000, pp. 63–69.
[17] Mazaheripour M, Ghanbarpour S, Mirmoradi
S and Hosseinpour I, "The effect ofpolypropylene fibers on the properties of freshand hardened lightweight self-compacting
concrete,"
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[18] Neville A and Brooks J, Concrete Technology,
2nd ed., Pearson, 2010.

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[2] Wang Y, Wu H and Li C, "Concrete
Reinforcement with Recycled Fibers,"
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[4] Altun F, Tanrıöven F and Dirikgil T,"Experimental investigation of mechanicalproperties of hybrid fiber reinforced concrete
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393

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECTS OF MOISTURE CONTENT ON RESILIENT PROPERTIESOF RECYCLED CONCRETE AGGREGATES (RCAs)
Chaminda Gallage1, Shiran Jayakody1 and Jothi Ramanujam2
Science and Engineering Faculty, Queensland University of Technology, Australia; 2Queensland
Department of Transport and Main Roads, Australia

1

ABSTRACTIn pavement design, resilient modulus of a pavement material is one of the key design parameters. Resilient
modulus of a granular pavement material can be measured using repeated load Triaxial (RLT) test or estimatedusing empirical models. For conventional granular pavement materials, a significant amount of resilient modulus
data and empirical models to estimate this key design parameter are available. However, RCA is a relatively new
granular pavement material and therefore no such data or empirical models are available. In this study, a number
of RLT tests were conducted on RCA sample to investigate the effects of moisture content on its resilient
modulus (M r ). It was observed that the resilient modulus of RCA increased with a number of loading cycles but
decreased as the moisture content was increased. Further, using RLT test results, empirical models to estimate
the resilient modulus of RCA were enhanced and validated.

Keywords: Repeater Load Triaxial, Recycled Concrete Aggregates, Resilient Modulus, Water Content

and performances of RCA can be inconsistence dueto the presence of impurities such as asphalt, brick,and glass in RCA. In addition, water content in
RCA could have significant effect on the properties
and performances of RCA as a granular pavement
material.
Jr et al., [2] and Bennert et al.,[3] studied theperformance of RCA and reclaimed asphalt
pavement (RAP) using RLTs and concluded that
RCA performed better than the RAP materials when
considering the development of the permanentstrain. Nataatmadja and Tan [4] reported that wellgraded RCA produces a higher resilient modulus
under low deviator stress and it may be caused by
the un-hydrated cement within the RCA. Even
though, some more studies on the performance
characteristics of RCA are reported [5, 6], further
studies are needed to investigate the effects of watercontent in RCA on its resilient modulus. Resilient
modulus is one of key material elastic properties
required in pavement design.
This paper presents the results of a series of RLTtests conducted on RCA samples with different
moisture content. The results of the test series arethen used to enhance the constitutive models, which
are used to estimate the resilient modulus of granularmaterials, by taking the water content of RCA into
account. Further, the applicability of the enhanced
models to estimate the resilient modulus of the RCA
is validated using additional RLT test data.

INTRODUCTION
Population
growthanddevelopment/redevelopment activities in the globe have led to
rapid increase in construction and demolition waste(C&D waste). Recycling of C&D waste has been
identified as one of the best ways to manage C&D
waste due to its environmental, social, and economic
benefits. In 2008- 2009, Australia produced a totalof 19 million tons of C&D waste [1] of which 55%
was recycled. The C&D waste recycling sector in
Queensland, Australia is reasonably well establishedand therefore Queensland government has targeted
to increase the recycling of C&D by 50%, 60% and
75% successively in years 2014, 2017 and 2020 [1].
Therefore, it is needed to explore the applications ofthese recycled materials. About 40 % of C&D waste
is demolished concrete and recycling concrete cangenerate aggregates called “Recycled Concrete
Aggregates (RCA).
Roads are one of the biggest infrastructures inany country. In road construction, a large volume ofaggregates is used as granular layers, stabilised
granular layers, and aggregates for asphalt
production. At present, crushed rocks are thepreferred granular material used in road
construction. Use of RCA as granular pavement
material reduces the disposal of C&D waste tolandfills and the depletion of natural resources(rocks).
Lack of data on properties and performances of
RCA as a pavement granular material has limited its
use in pavement structures. Further, the properties
394

GEOMATE- Brisbane, Nov. 19-21, 2014

specified by QDTMR for standard granular
pavement material. However, the water absorption
capacity of RM001 is much higher than that ofstandard pavement granular material. This could becaused by residual cement and cement mortar pastearound the aggregates in RCA. When compaction
properties of test material are compared with thoseof standard pavement granular material, RCA has
smaller maximum dry density (MDD) and greater
optimum moisture content (OMC) than that ofstandard granular pavement material. This could be
due to lesser fines content and higher absorption
capacity of RCA compared to standard granular
pavement material.

TESTING MATERIAL
A commercially available RCA product termed
as RM001 was employed in this experimental
program. The material was obtained from a concrete
recycling company in Queensland and it was
sourced from clean concrete and can be considered
free from other impurities such as glass, bricks,
wood, soil, and asphalt. Figure 1 shows the textureof RM001.

Table 1. Physical properties of RCA

Property

Liquid Limit (PL) [%]Fig. 1 The appearance of RM001

Plasticity Index (PI)Linear Shrinkage (LS)[%]
Water absorption(particles smaller than
4.25 mm) [%]Water absorption(particles greater than
4.25 mm) [%]Specific gravity (Gs)
Maximum dry density(MDD) [g/cm3]
Optimum moisture
content (OMC) [%]*Max=Maximum

Particle size distribution (PSD) of RM001 was
obtained by performing sieve analysis in accordancewith Australian standards, AS1289.3.6.1-2009 [7].
As shown in Fig. 2, the PSD of RM001 was plottedwith upper and lower boundaries of PSDs of baselayer granular materials specified by Queensland
Department of Main Roads [8]. The RM001 has
maximum and minimum particle size 25.4 mm and0.18 mm respectively. It can be seen that theparticles larger than 20 mm shifted the upper limit of
specification and the particles smaller than 0.6 mm
propped below the lower limit of the specification.

ValuesStandard
RCA
granular(RM001) pavement
material*Max: 25
21.00
[8]
5.40
*Max: 6 [8]*Max: 3.5
1.00
[8]

5.35

<10 [15]

6.50
2.64

<10 [15]
2.85 [16]1.75>1.79 [15]13.20

8-15 [15]TESTING APPARATUS
To obtain the resilient modulus of RCA samples, theRepeated Load Triaxial (RLT) apparatus of which
the schematic diagram is shown in Fig. 3 was
employed in this study. The apparatus canaccommodate a cylindrical specimen with 100 mm
diameter and 200 mm height. The confining pressure
up to 1000 kPa is applied by pressurizing air in thecell and the applied confining pressure iscontinuously monitored by transducer connected tothe cell. The pneumatic actuator connected to thevertical shaft can apply repeated load/stress withdifferent waveforms on the sample under stress or
strain controlled conditions. The actuator has thecapacity to apply the maximum load of 12kN andhas the maximum stroke of 30 mm. The verticaldeformation of the specimen is calculated byaveraging the vertical deformation measured by two

Fig. 2 PSD of test material (RM001)
RM001 was tested for atterberg limits in accordancewith Australian and Queensland Department ofTransport and Main Roads Queensland (QDTMR)
standards [9-11], water absorption following the test
method specified QDTMR [12, 13], and standard
proctor compaction test in accordance with
Australian Standards [14] and the results are shownin Table 1.
Atterberg limits of RM001 are within the range395

GEOMATE- Brisbane, Nov. 19-21, 2014

LVDTs attached to the vertical shaft as shown in Fig.
3. RLT test is commonly conducted under undrained
condition and therefore no volume change unit isavailable. Saturated and unsaturated specimen canbe tested in the apparatus with continuous
monitoring of pore-water pressure by the transducer
connect to the bottom of the specimen. LVDTs,
Pore-pressure and cell pressure transducers, and loadcell are connected to logging system to collect the
responses of these transducers at specified timeinterval.

The resilient modulus (M r ) of RCA and theeffects of moisture content on M r were investigatedby performing a series of RLT tests on RCA
specimens. As shown in Table 2, tests were
performed using three dynamic deviator stresses(σ d ) of 175, 325, 475, and 625 kPa, with confiningpressure (σ 3 ) of 125 kPa. Tests were conducted atfour different water content values and the dry
density equal to MDD was maintained for all tests.
Specimen Preparation
Oven dried material was mixed with predetermined water content (e.g: 11.6, 13.2, 14.5,
15.5 %) and left overnight in sealed containers formoisture homogenization. Then the material wascompacted in to a split mould of 100 mm diameterand 200 mm height to achieve the pre-determined
dry density of 1.75 g/cm3. The compaction of thespecimen was done in three layers. The bulk massrequired to achieve the dry density of 1.75 g/cm3 inthe mould was calculated and one-third of that mass
was used for each layer and numbers of standard
compaction blows were applied to reach one-third of
the mould height. This method was repeated to othertwo layers to get a specimen prepared for a RLT test.
The compacted specimen was then enclosed in
0.8 mm thick rubber membrane and set in the RLTapparatus. The specimen was sealed at the top andthe bottom of the specimen and 125 kPa confiningpressure was applied and allowed to consolidate forabout 2 hours.
Loading and data interpretation
Once the sample was consolidated under 125 kPa
confining pressure, the wave form shown in Fig. 4
was repeatedly applied under undrained conditions.
For each sample, the wave form was repeated
10,000 times for each dynamic deviator stress (σ d )stage (e.g: 175, 325, 475, and 625 kPa).
Figure 5 shows a typical stress vs strain response
for a RLT test and how to obtain resilient modulus(M r ) and permanent/plastic strain (deformation)corresponding to a given loading cycle.

Fig. 3 The schematic diagram of RLT apparatus
used
METHODOLOGY
Table 2. Summary of test conditions
Moisturecontent(%)

Drydensity(g/cm3)

Confiningpressure(kPa)

Degreeofsaturation(%)

Dynamic
deviator stress(kPa)

3.0 sec
σd175, 325,
475, 625
175, 325,
13.2
1.75
125
68
475, 625
175, 325,
14.5
1.75
125
75
475, 625
175, 325,
15.5
1.75
125
80
475, 625
Note: At each stress stage, 10,000 load repetitions
were applied.
1.75

125

60

Deviator Stress

11.6

Contact stress = 5% of σd

1.0 sec

Time [sec]Fig. 4 Illustration of the vertical (deviator) stresswaveform applied

396

Deviator Stress,σd

GEOMATE- Brisbane, Nov. 19-21, 2014

1 2 3

is termed the “plastic shakedown limit”. Numbers of
researchers [17, 18] observed the shake down state
and the plastic shakedown limit for pavement
granular materials such as crushed rocks. It can beseen that RCA tends to behave like natural granularmaterial under repeated load and the applied stressconditions in this experimental program seem to beless than the plastic shakedown limit of RCA exceptn…………………………………..

Plastic strain, εp

𝑀𝑀𝑟𝑟 =

𝜎𝜎𝑑𝑑
𝜖𝜖𝑟𝑟

Axial Strain

σ d.

Resilient strain,εr

The vertical plastic strain increases with increasein sample moisture content and the principal stressratio (σ d /σ 3 ). As the moisture content is increased,
the particles are more lubricated to facilitate their
movement into air-voids. This may increase theaccumulation of plastic strain. As the stress ratio isincreased, the lateral confinement becomes smaller
compared to the dynamic deviator stress. This may
allow greater lateral displacement in the sample thatcause to increase the plastic vertical deformation.

Fig. 5 Typical stress vs strain response in RLT test
RESULTS AND DISCUSSIONSA series of RLT tests were conducted under theconditions given in Table 2 to investigate the effectsof water content on resilient properties (permanent
deformation/strain and resilient modulus (M r )) of
RCA. Further, using the resilient modulus dataobtained from the tests, a constitutive model wasenhanced to predict/estimate the resilient modulus of
RCA and its applicability was validated using
additional test data.

Resilient modulus of RCA
Figure 7 shows how resilient modulus (M r ) of
RCA varies with numbers of loading cycles. It canbe seen that, for a given stress condition which issmaller than the plastic shake down limit of RCA,
M r increases significantly with the first few numbersof loading cycles and then it increases withdecreasing rate tending to approach the steady-state
condition (zero increase in Mr with loading cycles)
which can be termed as shake down response.
Densification of the sample with the first numbers ofloading cycles could cause the increase in resilient
modulus. Once a steady-state response is achieved,
neither plastic strain nor the densification is
accumulated or occurred and therefore, no increasein M r with numbers of loading cycles can beobserved once the steady-state response is achieved.
A numbers of researchers [19, 20] observed thisphenomenon for natural crushed rocks and it can beseen that RCA behave like natural crushed rocks
under repeated loads though its M r is much less thanthat of high standard granular pavement materials(Mr=300-700MPa) specified by Austroads Ltd,
Australia [21].

Accumulation of permanent (plastic) strain in
RCA
Figure 6 depicts the accumulation of verticalplastic strain with numbers of loading cycles andhow it is affected by the sample moisture content
and dynamic deviator stress (σ d ).

Fig. 6 Accumulation of vertical plastic strain withnumbers of loading cycles
As shown in Fig. 6, for a given confiningpressure and a dynamic deviator stress, the plasticstrain increases with numbers of loading cycles.
However, the rate of increase in plastic strain(plastic strain per loading cycle) decreases withnumbers of loading cycles tending to achieve a longterm, steady-state response (no accumulation ofplastic strain and each response is hysteretic). Thisimplies that a finite amount of energy is absorbed by
the material on each stress-strain excursion. Once apurely resilient response has been obtained, thematerial is said to have “shake down” and the
maximum stress level that this condition is achieved

Fig. 7 The variation of resilient modulus (Mr) of
RCA with number of loading cycles
For each test with different water content, M r
397

GEOMATE- Brisbane, Nov. 19-21, 2014

Resilient Modulus-MPa

was calculated at 10,000th loading cycle of eachstress stage and the results are shown in Fig.8. It canbe seen that M r decreases with increase in material’s
moisture content and increases slightly with increasein stress ratio (σ d /σ 3 ) or bulk stress θ (σ 1 +σ 2 +σ 3 ).
240
230
220
210
200
190
180
170
160
150
140

To validate the applicability of enhanced model
to predict the M r of RCA with different moisture
content, a RLT test on RCA with 66 stressconditions was conducted according to the standard
method of Austroad APRG 00/33-2000 [24]. The
sample’s initial moisture content was maintained at
13.8 %. Then, for all these 66 stress conditions, M r
was calculated and also predicted using Eq. (1), (2)and (3). Fig. 9 depicts the measured and predicted
M r values and they are well agreed. With further
validation using the results of tests conducted at
different moisture contents and stress conditions, itwould be able to suggest the enhanced constitutive
model to be used to predict/estimate the M r of RCA.

σd= 175 kPa
σd= 325 kPa
σd= 475 kPa

10

11

12

13

14

15

16

Water content - %250
Predicted Resilient Modulus

Fig. 8 The variation of resilient modulus of RCA
with moisture content and stress level
More water in the sample lubricates the particles
to reduce the frictional resistance between RCA
particles and that eventually leads to reduce thestiffness (M r ) of the sample.

150
100
50
0

0

50

100

150

200

250

Measured Resilient Modulus

Constitute model to estimate M r of RCA taking
water content into accountFig. 9 Measured and predicted M r for RCA sample
with moisture content of 13.8%

It is not practicable to perform RLT tests toobtained M r of pavement granular materials.
Therefore, numbers of constitute models have beendeveloped by researchers [22, 23] to estimate the M r
for granular road materials. There is no such modelfor RCA to predict/estimate its Mr, the following,
more simple, constitute model is attempted to
predict the M r of RCA [22]:θ 
M r = k1 pa   pa 

y = x (Line of equility)

200

CONCLUSION
In this study, the resilient properties of RCA
and the effects of moisture content on theseproperties were investigated by a series of
performing Repeated Load Triaxial tests. The
following conclusions are drawn from this study:• In terms of classification properties, RM001(RCA) is comparable with standard granular
pavement material specified by QDTMR.
• For a given stress condition, the resilient
modulus of RCA decreases and the plastic strainof RCA increases with increase in moisture
content.
• RCA tends to exhibit “shake down” responseand “plastic shake down limit” that are observedin natural granular materials such as crushedrocks.
• The enhanced constitutive model will be able touse to predict the resilient modulus of RCA bytaking moisture content and stress level of thematerial into account.

k2

(1)

Where,
M r = Resilient Modulus
𝒑𝒑𝒂𝒂 = Atmospheric pressure (103.4 kPa)𝜽𝜽 = Bulk stress (𝝈𝝈𝟏𝟏 + 𝝈𝝈𝟐𝟐 + 𝝈𝝈𝟑𝟑 )𝝈𝝈𝟏𝟏 =Principal vertical stresses
𝝈𝝈𝟑𝟑 = 𝝈𝝈𝟐𝟐 =Principal radial stresses (confiningpressure)
k 1 and k 2 are model parameters
Non-linear regression analysis was used to
fit the measured M r in Fig. 8 to Eq. (1) and to obtainthe model parameters k 1 and k 2 as a function of
initial moisture content of RCA sample as shown
below:ACKNOWLEDGEMENTS
This paper is based on the second author’s
research completed as a partial fulfillment for the
PhD requirements at Queensland University ofTechnology (QUT), Brisbane, Australia. Therefore,
the first author acknowledges the scholarship
received from QUT. The authors gratefully

k 1 = -0.0435 w + 1.3397(2)k 2 = 0.0088 w + 0.3009(3)
where, w = moisture content in percentage (%)

398

GEOMATE- Brisbane, Nov. 19-21, 2014[13] MainRoads QDoTa."Material testing manual".
Test method Q214B-1996, Particle density andwater absorption of aggregates (Coarse
fraction). 2011.
[14] Australia CoS."Methods of testing soils forengineering purposes". Method 511: Soilcompaction and density tests-determination of
the dry density/moisture content relation of asoil using standard compactive effort. 2003.
[15] Arulrajah A, Piratheepan J, Disfani MM, Bo
MW."Geotechnical and Geoenvironmental
Properties of Recycled Construction and
Demolition Materials in Pavement Subbase
Applications". Journal of Materials in Civil
Engineering. 2013;25:1077-88.
[16] Vegas I, Ibañez JA, San José JT, Urzelai
A."Construction demolition wastes, Waelz slag
and MSWI bottom ash: A comparativetechnical analysis as material for road
construction".
Waste
Management.
2008;28:565-74.
[17] Werkmeister S, Dawson AR, Wellner
F."Permanent deformation behaviour of
granular materials and the Shakedown
concept". Transportation Research Record:
Journal of the Transportation Research Board.
2001:75-81.
[18] Cerni G, Cardone F, Virgili A, CamilliS."Characterisation of permanent deformation
behaviour of unbound granular materials under
repeated triaxial loading". Construction and
Building Materials. 2012;28:79-87.
[19] Vuong BT, Hazell D."Development of
performance-based specifications for unboundgranular materials". Road and Transport
Research Journal. 2003;12:13-25.
[20] Ekblad J, Isacsson U."Influence of water on
resilient properties of coarse granularmaterials". Road materials and pavement
design. 2006;7:369-404.
[21] Jameson G, Group A."Pavement structuraldesign". Guide to pavement technology part 2.
2008.
[22] Seed HB, Mitry FG, Monismith CL, Chan
CK."Predictionofflexible
pavement
deflections from laboratory repeated-load
tests". National Cooperative Highway Research
Program Report. 1967.
[23] Witczak MW, Uzan J."The universal airport
pavement design system". Report 1 of 4
Granular Material Characterization. 1988.
[24] Voung BT, Brimble R."Determination of
permanent deformation and resilient modulus
characteristics of unbound granular materials
underdrainedconditions,
In APRG
DOCUMENT APRG 00/33(MA)". Austroads
repeated load triaxial test method. 2000.

acknowledge Alex Fraser Queensland for providing
Recycled Concrete Aggregates (RCA) for thisexperimental program. Queensland Department ofTransport and Main Roads (QDTMR) and Brisbane
City Council (BCC) are greatly acknowledged forproviding some of testing facilities. A special thankgoes to Mr. Glen Barnes, senior laboratory
technician at QUT, for his great support for
conducting laboratory testing at QUT.
REFERENCES[1] Hyder Consulting ECSRS."Construction anddemolition waste status report". 2011.
[2] Jr WJP, Maher MH, Bennert TA,
GucunskiN."Behavior of construction anddemolition debris in base and subbase
applications".
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materials
ingeotechnical applications. 1998.
[3] Bennert T, Papp WJ, Maher A, Gucunski
N."Utilization of construction and demolition
debris under traffic-type loading in base andsubbase applications". Transportation researchrecord 2000:33-9.
[4] Nataatmadja A, Tan YL."Resilient Response ofrecycled
concreteroadaggregates".
Transportation engineering. 2001.
[5] Arulrajah A, J. Piratheepan MWB, Sivakugan
N."Geotechnical characteristics of recycled
crushed brick blends for pavement sub-baseapplications". Canadian Geotechnical Journal.
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[6] Conceicao Fd, Motta rdS, Vasconcelos KL,
Bernucci L."Laboratory evaluation of recycledconstruction and demolition waste forpavements". Construction and building
materials 2011;25.
[7] Australia Cos."Methods of testing soils forengineering purposes". Method 361: Soilclassification tests-determination of the particle
size distribution of a soil-standard method ofanalysis by sieving. 2009.
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399

GEOMATE, Brisbane, Nov.19-21, 2014

Environment

400

CONSERVATION AND EXPLOITATION OF BANG GRASSEFFECTIVE IN PHU MY VILLAGE, VIETNAM
Duong Minh Truyen1, Le Hong Thia1, Mashhor Mansor2
1

Cantho University, 3/2 Street, Cantho City, Vietnam;

2

School of Biological Sciences, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia.
ABSTRACT

Phu My located in Kien Giang province, South of Vietnam is a small village with the majority of the population
made of a Khmer community. The weather conditions are not encouraging for locals due to serious flooding months.
The soils and water are comparatively acidic. Therefore, only Bang grass (Lepironia articulate) – an indicator for
the wetland habitats and Nang grass (Eleocharis dulcis.) – the main food of an endangered Sarus Crane (Grusantigone) can thrive. Bang grassland area decreased due to the housing problem. To overcome the decrease of Banggrass and conserve this species, the project “Restoration and sustainable exploitation Bang grassland in Phu My,
2004” conducted to help locals make sophisticated handmade products from Bang grass. It is a good way to help the
locals to benefit and conserve Bang grass.
Keywords: Bang grass (Lepironia articulate), Phu My, exploitation, conservation

INTRODUCTION
Kien Giang Province is a diverse area of wetland
ecosystems, including mangrove forests, brackish
marshes, swamp and grasslands in Mekong Delta of
Vietnam [1]. In Kien Giang, Phu My commune is aprimitive wetland with heavy alum, organic soil andseasonally inundation. The main community in Phu
My is Khmer people. Besides Eleocharis dulcis,
Eleocharis ochrostachys, Ischaemum rugosum,
Melaleuca cajuputi…, Bang grass (Lepironia
articulata) is the main plant in Phu My [2]. Becauseof the alkaline soil, valuable food and agricultural
crops are not taken. Therefore, Bang grass plays animportant and essential role in social economic life of
locals in the region. Cutting Bang grass to weave andmake products and handicraft items is an importantpart for current revenues in Khmer community.
However, Bang grass is exploited significantly ina short time because locals transform land use into
inappropriate agricultural models. It leads to thedecrease of Bang grass area because of higher
exploitive rate than natural restoration. The
disappearance of Bang grass will affect enormously
the socio-economy as well as ecological functions ofenvironment and natural conservation. The model,
which combines natural conservation with theparticipation of the community, is conducted in Phu
My commune of Kien Giang province with the
purposes: to preserve existing ecosystems, reduce
financial burden for local governments inconservation and improve people's lives and to assess
the social and economic changes of the community
involved in the project "Sustainable exploitation ofgrassland conservation Bang combining local tradevillage, Phu My commune, Kien Luong district" from2004 to 2006.
METHODOLOGY
According to Pham Hoang Ho [3], the location ofvegetation classification Bang is described asfollows: Order: Cyperales; Family: Cyperaceae;
Genus: Lepironia; Species: Lepironia ariculata(Retz.) Domin

Fig. 1 Bang Grass (Lepironia ariculata)(according to Jackson and Jacobs [4]).
Research Methodology
2.1.1 Collect basic information
Collecting information, documents, maps,
research data related to pre-existing problems and401

Int. J. of GEOMATE, Month, Year, Vol.00, No.00 (Sl. No. 00), pp. 00-00

research areas, focusing on the study material ofplants Bang, natural characteristics, socio-economic,
management and development of the local villages.
The information was collected at the following
agencies: Technical Centre of Natural Resources andEnvironment (Department of Natural Resources andEnvironment Kien Giang), the People's Committee ofKien Luong district, People's Committee of Phu My
commune, Department of Science and Technology.
Construct the questionnaires
Based on the different groups in the community
living around the project area, constructing thequestionnaires:- Form I: households interviewed in 2004
- Form II: households participating spit and weave
products from Bang grass- Form III: intermediate households purchaseproducts from Bang grass- Form IV: employees working in the project orworking at home
The investigators interviewed each household andreported information in different questionnaire. Data
recorded will be encoded in a common code table.
Enter data stored in an Excel spreadsheet, andprocessed with statistical software SPSS.
Methods of analysis of economic efficiency- The economic efficiency of a model iscalculated by the formula: profit = total revenue –total cost
- Determine the percentage of income of eachmodel contributes to the total income per householdin the year.
Maintain and develop the traditional craft villages
for the local community
Use the rapid assessment of rural people's
participation by conducting quick interviews ofhouseholds who weaved Bang grass about
techniques, methods and material preparation.
RESULT
Exploiting Bang grass from the local community
According to the survey in 2006, more than 64%
of participating households exploited Bang grass.
Activities were taken year-round and mostly in therainy season. On an average day, an anchor puller
pulled up 20 bunch (1 bunch of Bang is about
1.834kg). Approximately 1% of people pulled up

Bang grass every day and 42% pulled up after 10days off.
Table 1 Exploitation of Bang grass in different
months
Month
1
2
3
4
5
6
7
8
9
10
11
12
Notes:

Exploitation level
**
*
*
*
*
**
**
**
***
***
***
***
(*): exploit rarely(**):exploit averagely(***):exploit significantly

bad quality
averagequality
good quality

Table 1 shows the level of exploitation of thegrass Bang Phu My community changes seasonally.
In the rainy season from September to January, water
flooded grasslands, Bang grass had good quality(height > 1.2m), and people exploited Bang grass themost. In the dry season from February to May,
exploitation levels decrease due to poor quality ofBang grass (body broken, dry, reaching heights notsuitable to exploit raw material), and people
exploited the least. From June to August, flood
started up and people started exploiting again.
Table 2 Total bunches of Bang grass exploited fromlocalsNumber ofhousehold80

Households in the project area (*)
Total household living around the229
project area exploited Bang grass
Total bunches of Bang grass
1,671,700
exploited from locals per year
Notes: (*) On average, each household had one Banggrass puller, one person pulled 20 bunch /day (7,300
bunches/year).
Table 2 showed the total number of Bang bunches
exploited from the local community (16717 million
bunches/year. Compared with the findings of Tran
Triet [2], the maximum number of total Bang
402

Int. J. of GEOMATE, Month, Year, Vol.00, No.00 (Sl. No. 00), pp. 00-00

exploitation 1,2992 million bunches/year. This
showed that exploited activities Bang of the local
community after two years constructing the projectincreased to 372,500 bunches.
Impact Communities to Bang Grass:
Exploit Bang grass
The community exploited Bang grass numerously
in rainy season when Phu My commune was flooded
fully. Pulling out and cutting were two ways, whichused to exploit Bang grass:+ Deracination: using hand to pull out the roots,
just select the high stem to exploit. This method wasused by 95% of the local community to exploit Banggrass in flooded season.
+ Cut: About 86% outside the local community
used knife and cut the grass, including saplings in thedry season.
In summary, the exploitive activities of locals
inside and outside the community increased andmade the area of Bang grass decrease and degrade
gradually. The main reasons were inappropriatetechnical exploitation and over exploitation of people
to overcome self- regenerating capability in the rainyseason.
The other impact
In 2006, grasslands were under significant impact
of digging ditches, encroaching agriculture or
melaleuca, hatching shrimp farm and burning
grasslands. The ground water level was decreasing
deeper by digging ditches in grassland, the surface
soil had exposed to the air and leaded to thealkalization. The soil properties changed had brought
about the vegatational cover on the surface changed.
Those species under drought and aluminous
conditions would be replaced by submerged species.
The agricultural encroachment of households to takeplace in the contiguous area of meadows andagricultural land reduced grassland area, which had
invested a lot of effort and money to renovate. As aresult, 5% of local people often burned grasslands,
alternating Melaleuca leucadendra in the dry season
to log rough timber. Grasslands were habitats ofmany different species of animals and plants.
Burning pastures would affect pasture conservation
objectives and the living creatures and might changed
the flora and fauna here.
Impact of the project on the community

In 2006, 64 of 122 households participated inBang exploitation. Among them, 60 households knew
information about the project and 44 households
knew the boundaries of the project because theproject set up landmarks and sentry - box. Collecting
suggestions from community, 51% of peoplecommented that Bang pasture would be forever and
49 % of respondents said that Bang pasture wasdeclining by switching to farming, shrimp and over
exploitation.
From the survey, there were 20 households
recognizing the economic values of Bang grass. Theybuit a dike and prevented strangers to exploit Banggrass. Technical exploitation of people changed moreconsistently, 64 households in the project usedderacination method, selected the mature Lepironia
ariculata with large diameter, height of 1m or more.
Exploitable Bang grass time was different; only 3.1%
of households exploited in rainy season whenflooding occurred, around 6.3 % of households
exploited all year around. Others exploited in
freetime. Thus, after two years of project’s
implementation,communities
livingaroundunderstood the values of Bang grass (the economic
and conservational values).
To create jobs for the local community
The project created jobs for the local community,
especially for Khmer women. Total number of
employees was 30 people; 26 people worked in 2005,
4 new people worked in 2006. Most products weremade in the workshop of the project. They selected
Bang grass and dried them to make handicraft iteams.
Besides working at workshop, workers had worked at
home.
Table 3 Income from production of the project

Activities
Weave
cushions
at home
Weave
mats
Weave
best color
qualitymats
Makebaskets

Raising awareness of community about Bang grassresources
403

Capacity(product/day)

Income(USD/day)Income(USD/month)

2-3

0.71 – 0.85

21.20 –
25.44

8-10

0.94 – 1.41

28.27 –
42.40

2-3

0.94 – 1.41

28.27 –
42.40

7-10

1.41 – 2.12

42.40 –
63.60

Int. J. of GEOMATE, Month, Year, Vol.00, No.00 (Sl. No. 00), pp. 00-00

From the result of socio-economic survey in 2006,
who admitted into the project was local, encouraging
Khmer people. If they knew to sew, they would betrained to become weavers. Otherwise, they weretrained to be dyers or do other activities in production
line of handbags, briefcases, hats. In case workers did
not have time to work at the workshop, they could
made cushions or mats at home. Table 1 shows thatthe income of workers made baskets was highest
42.40 – 63.60 USD/month. Workers weaved at homereceived from 21.20 – 25.44 USD/month. If
compared with other jobs, working in the project had
more stable income, fixed working time, improved
skills, learned new methods to produce many kinds ofproducts.

Economic Change

Income per year between farming and exploiting
Bang grass were compared in table 4. Locals got
about 3487.89 USD/year for farming while theincome from exploitation Bang grass was 678.45
USD/year, about 5 times lower. This was the reason
people changed to do farming and land use frompasture to rice fields. However, the lowest income
might be -282.69 USD/year. Because farmers had abad harvest, could not get the profits and got unpaid
debts from buying chemical fertilizers andinsecticides. Working in the project to make products
from Bang grass, workers could get minimum 12.72
USD/year .

from the raw materials of business had been
documented and reported every year.

The cost for exploitation Bang grass
Community in Phu My commune exploited Banggrass without paying any cost. People often
deracinated in wild Bang grasslands. Therefore, thecosts were taken from travelling and eating. If people
deracinated in project area, the cost would be 32.98
USD/basket. In case people made cushions at home,the material cost was 282.69 USD/mattress.
The profits from exploitation of the projectIf people exploited natural Bang grass for sale raw
materials and made cushions, the average profit per
year would obtain 100.35 USD. Households withmachine to press Bang had profits in the first year
from 75.38 USD to 471.15 USD. The second year,
profits rose from 84.81 USD to 1187.29 USD. The
average profits were obtained from 33.92 USD to376.92 USD. The project “Restoration andsustainable exploitation Bang grassland in Phu My,
2004” established in 12/ 2004, but until 12/2005 it
has started a new business. The project purchased
raw and dried materials to produce products such as
mats, baskets books, briefcases and hats. The revenue

Table 4 Comparison of income from farming andexploiting Bang grass
Income (USD/year)
Farming 2
crops

Exploiting Bang
grass

188.46100.35338.19126.46

Low-282.69

12.72

High

3487.89678.45Lowaverage
Average

Maintenance and development of traditional
village for local community
Handicraft villages before 2004
Weaving handicraft products was present in
Khmer community anciently and inherited by theprogeny and then it became the traditional industry of
Phu My. In wartime, people weaved products such as
cushions, baskets, hats, bags. Since 1990, only few
items used and maintained until today.
Manufacturing processes
Every dry season, Bang grass withered. However,in rainy season, it began a new growth cycle. In
harvesting time, people pulled up small handfuls,
then bundled up bunches. After being dried, Banggrass had toughness, plasticity, sustainable strengthand impermeability. Due to those characteristics,
Bang grass was used as a raw material for weaving
products. After drying, each stem was crushed on asmall stone or a plank to flat it. Weaving instruments
were a very sharp pointed piece of bamboo. First,
using hands knitted a contour connecting the stems
together. Continue knitting until the completion of
the product. Hence, to complete a product people did
not use any machinery. They only used hand to knit a
product from raw materials.
The consumer market
Handicrafts products were mainly sold to locals,
other cities in Vietnam and customers from
Cambodia. Typically, most products sold in the riceseason. Since the products were made from Bang404

Int. J. of GEOMATE, Month, Year, Vol.00, No.00 (Sl. No. 00), pp. 00-00

grass with many models, styles and colors, in 2005,
products had expanded local markets and soldabroad. The baskets, mats, mattresses had been
accepted in domestic markets, especially baskets had
been exported to Japan.

The project maintained traditional ways ofcommunity that was weaving cushions by hand.
However, there were improvements in machinery andequipment in production to save labor, save time andincreased the capacity. Bang squeezers replaced handtools. Looms used for weaving mats was shorter timethan knitting by hand. Sewing machines used sewing
baskets, contours in order to improve design and fit
with current markets’ demands.
CONCLUSION

Fig.2 Steps to knit a cushion: A. crushing instruments(pestle); B. crusing Bang grass; C. knitting a cushion.

Handicraft village of the project had positive
impacts on the local villages. Currently, productive
technology and machinery used in production has
been improved to help people reduce labor save time.
From one model of product, locals expanded todevelop about 20 types of baskets, mats, cushions
and hats. Consumption of products was also
expanding in domestic markets and international
markets.
ACKNOWLEDGEMENT
I would like to express my gratitude towards
Universiti Sains Malaysia for funding the publication
fee under the Individual Research Grant(1001/PBiologi/816217) and all the people who get
involved in the project.
REFERENCE[1]

Fig.3 Types of products: the types of bag; mats; pads;
slippers; hats and dried materials.

[2]

From the mat and pad products providing by the
local community, the project designed new productswith multiple patterns, colors, different sizes.
[3]

[4]

Fig.4 The equipments used in the production Banggrass: Bang squeezer; looms; sewing machine.

405

Nguyen, H.H., et al., The relationship ofspatial-temporalchangesinfringemangrove extent and adjacent land-use:
Case study of Kien Giang coast, Vietnam.
Ocean & Coastal Management, 2013. 76: p.
12-22.
Tran,
T.,
Combiningbiodiversity
conservation with poverty alleviation - acase study in the Mekong Delta, Vietnam.
Aquatic Ecosystem Health & Management,
2010. 13(1): p. 41-46.
Ho, P.H., Cay co vietnam = An illustrated
flora of Vietnam1991, California: Pham
Hoang Ho. v. <1 >.
Jackson, D.L. and S.W.L. Jacobs, Australian
agricultural botany1985, Sydney, N.S.W.
Beaverton, Or.: Sydney University Press ;International Specialized Book Services.
viii, 377 p.

NUTRIENT TRANSFER AND TRANSFORMATION IN
RIPARIAN GROUNDWATER WITH DIFFERENT LAND USE OF
A LOWLAND WATERSHED, EASTERN CHINA
Xuyin Yuan1,2, Lei Han1,2, Huan Wang2, Shouquan Wang2, Hailong Chen2
1. Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes of Ministryof Education, Hohai University, Nanjing, Jiangsu 210098, China;
2. College of Environment, Hohai University, Nanjing, Jiangsu 210098, China
ABSTRACT
Riparian zone is a transition zone between terrestrial and aquatic systems, which can influence thewater quality through nutrient dynamics. We investigate the changes of nutrients (N, P, C) in riparianzones with different land uses in a lowland watershed of eastern China, and illustrate the effect of land
use on the nutrient transfer and transformation in riparian zones. Our results show the forest-dominatedriparian land has high TN, moderate TOC and low TP concentrations with narrow variation ranges inspace. The agriculture-dominated riparian land has moderate TN and TP, relatively low TOC, withlarge variations in space. Higher TOC and TP concentrations occur in the urban-influenced riparianland, and significant changes are observed in this area. Hydrologic regimes will significantly affect thenutrient distribution and transfer in riparian zones, which is associated with nutrient sources and soil
properties. On the basis of lateral riparian profiles from inland to inshore, we conclude that nitrate andammonia show low transfer ratios in forest-dominated and agriculture-dominated riparian lands
respectively. But a high transfer ratio of TDP is observed in all riparian lands. TOC and DOC have asignificant effect on the transformation of N and P species in dry season.
Key words: Nutrient, Riparian groundwater, Land use, Watershed, China
and nutrient. The knowledge of interaction
between nitrogen, phosphorus and carbon
species in riparian groundwater needs expansion,
which is important for understanding thecontribution of terrestrial nutrients to aquatic
systems.
The objectives of this paper are as
followings. 1. To realize the spatial and temporalchanges of nitrogen, phosphorus and carbon in
riparian groundwater, and their relationships
with land use in eastern Chinese watershed. 2.
Analyzing the transfer and transformation
characteristics of nutrients from lands to rivers.
3.To discuss the effect of organic carbon on
nitrogen and phosphorus transformation.

INTRODUCTION
Riparian zone is a transition zone between
terrestrial and aquatic systems, which can
attenuate pollutants[1]. But riparian soils exhibit
different effectiveness on removal of nutrients
due to diversities of soil properties andgeochemical behavior of nutrients [2]. Nutrientsfrom different sources such as forest, agriculture
and urban show varied concentrations andspecies in spatial and temporal distribution,
which induce different extents of removal
efficiency[3].The nutrient characteristics areusually associated with land use and land cover,e.g. agricultural lands contain a high nitrogenconcentration and urban sewage has a highphosphorus concentration[4,5]. In addition, theriparian environmental conditions will influence
the biogeochemical cycle of nutrients.
Groundwater makes a pivotal role for thetransfer and transformation of nutrients inriparian zones. Soil properties will affect therange and extent of nutrient transfer andtransformation in groundwater [6]. To the best of
our knowledge, an understanding of the linkage
between nutrient partitioning and the land use islimited. Previous works of riparian zones takeless attention to relationships between land use

SAMPLING AND ANALYSIS METHODS
Tiaoxi watershed is located in the southwestof Taihu Lake, which covers hilly and plain
topography. The mainstream of Tiaoxi River
flow through the different lands, where reveals
the forest-dominated land in upstream, theagriculture-dominated land in midstream and theurban-dominated land in downstream. Becauseof significant human activities, the ranges ofriparian zones are less than 100m in the wholewatershed.
406

Three profiles of each land type of riparianzone were chosen to study the nutrient
characteristics in groundwater. These profiles
were vertical with the river bank. Each profile
has six sampling sites from 1m to 30m besidebank, and groundwater was collected at depth of
50cm to 100cm based on water table.
All groundwater in riparian zones wereanalyzed for TN. TP, NO 3 -N, NH 4 -N, dissolved
reactive phosphorus (DRP) with colorimetrictechniques
approvedby
MinistryofEnvironmental Protection of China [7]. The
groundwater samples were stored in chromic
acid washed glass bottles at 4℃for TOC analysis
with an Aurora 1030 TOC analyzer (USA). The
filtered samples were measured for DOC.

in groundwater followed the order of urban
riparian > cropland riparian > woodland riparian,which implied that changes of phosphorus
species were related with land use. DOC
concentration accounted for a high proportion of
TOC, general more than 50%, decreasing withwoodland groundwater > urban groundwater >cropland groundwater.
Nutrients in groundwater showed small
seasonal changes in similar land use, althoughnitrogen, phosphorus and carbon showed a slightincrease in winter usually. But the exceptionalsituation exhibited in a cropland riparian zone,
denoting the significant effectiveness ofcultivation condition on nutrients. The variationsof carbon were larger than nitrogen andphosphorus, especially in an urban riparian area,
perhaps originating from multi carbon resourcesin a same place [10]. Nitrogen and phosphorus
species showed a significant seasonal changes
which illustrated not only the source diversities,
but also biogeochemical process in riparianzone[11,12].
Nutrients from different land use not only
influenced the total concentration, but also their
species in riparian groundwater. In woodland oflower intense cultivation, nutrients showed thelower concentrations. Changes of cultivation
time and intense in cropland lead to large rangesof nutrient inputs in different seasons,particularly for nitrogen and phosphorus species.
Urban riparian area usually received continuous
sewage discharge form resident living, butnutrient concentration was significantly affectedby rain runoff. This is why nutrients in summer
are lower than in winter, due to less rain in
winter.

RESULTS AND DISCUSSIONS
Nutrient distributions in groundwater ofriparian zones with different land uses
Nitrogen,phosphorus
andcarbonconcentrations of groundwater in riparian soils
were shown in Table 1. It was evident thatnutrients in urban groundwater were higher thanthose in woodland and cropland groundwater.
But groundwater of cropland in summer had
higher TOC and NO 3 -N. Compared to nutrientsin surface water, nitrogen showed a slightdecline, but phosphorus and carbon showed asignificant decline. Because phosphorus andcarbon mostly existed in the particulate form,
and they were absorbed by riparian soils [8,9].
Among inorganic nitrogen, NO 3 -N showed asignificant higher concentration in almost sites,
indicating nitrate was dominated in groundwaterof Tiaoxi River. The proportions of DRP to TP

Table 1 Nitrogen, phosphorus and carbon concentrations of groundwater in riparian soils around different lands
SummerTN

WinterWoodlandCorpland

Urbanland

WoodlandCorpland

Urbanland

1.48 (0.83-2.49)

2.62(1.01-4.97)

3.21(1.38-6.44)

1.91(1.24-3.32)

2.72(1.67-4.90)

3.66(1.69-7.71)-

0.74(0.25-1.05)

1.73(0.77-2.70)

1.32(0.87-2.28)

0.61(0.29-0.93)

1.21(0.53-3.47)

2.45(1.15-3.71)+

0.04(0.02-0.06)

0.07(0.04-0.11)

0.13(0.06-0.36)

0.06(0.01-0.17)

0.10(0.03-0.24)

0.18(0.02-0.72)

TP

0.10(0.04-0.20)

0.09(0.04-0.13)

0.21(0.06-0.36)

0.07(0.04-0.09)

0.09(0.05-0.17)

0.11(0.06-0.19)

DRP

0.02(0.01-0.03)

0.04(0.01-0.08)

0.04(0.02-0.08)

0.04(0.02-0.06)

0.05(0.02-0.16)

0.07(0.03-0.10)

TOC

0.88(0.29-1.41)

1.87(1.19-2.81)

1.25(0.63-2.58)

1.13(0.68-1.78)

1.17(0.51-1.85)

2.57(1.64-3.54)

DOC

0.66(0.22-1.12)

0.89(0.45-1.63)

0.74(0.25-1.54)

0.78(0.36-1.17)

0.87(0.31-1.61)

1.12(0.44-2.08)

NO 3
NH 4

in riparian groundwater were displayed in Fig. 2.
These nutrients showed an elevated trend fromnearshore to offshore, where diversities existed
for different elements. Nitrogen showed asignificant increasing, and phosphorus andcarbon showed a slight increasing along theriparian profile. As a whole, a wide range ofnutrients appeared in cropland and urban

Nitrogen and phosphorus transfer from land
to river in the watershed
In order to compare the transfer characters ofnutrients, the sampling sites of same distancefrom river bank were handled in each profile.
The water samples were obtained at 1m, 5m,
10m, 15m, 20m and 30m from river bank.
Varied plots of nitrogen, phosphorus and carbon
407

groundwater. But the concentrations of nutrient
were stable in woodland groundwater.
TN in cropland riparian area, TP and TOC in
urban riparian area decreased 52.0%-63.6%,
25.6%-31.9% and 13.7%-52.1% respectively at a30m distance. But TN and TOC in woodland
riparian area didn’t show a significant variation
at the sampling distance. In winter, significant
decreasing of TN and TP exhibited in urban
riparian area, with ranges of 57.3%-74.2% and29.6%-37.0%. TOC in cropland riparian area
decreased significantly with a range of
19.8%-37.9%. But TP in cropland and woodland
had a small increase because fertilization added
the phosphorus input in these areas [13].
Changesofnutrient
speciesandtransformation in riparian groundwater
Nitrogen and phosphorus species showedsignificant variations in groundwater under
different land use. TN and NO 3 -N revealed
significant fluctuations in cropland area thanother areas in summer, but slight fluctuations in
winter. Because soils tended to absorb
particulate phosphorus and reduced the P
concentrations in groundwater[14-15]. Thanvalues of TN/TP were elevated. Cultivation
enhanced the absorption progress of soil inriparian area due to extensive porosity. The
proportions of DOC/TOC in cropland area werelower than in woodland and urban areas. This is
the same origin that particulate organic carbon iseasy to be absorbed by soils [16]. The seasonalvariations of nutrients were complicated becauseof hydrological and environmental conditions.
DRP/TP and DOC/TOC values in winter werehigher than in summer. The concentrations ofTN and NO 3 -N increased in urban riparian area,
which were associated with less dilution of
sewage in winter. But variations of TN/TP andNO 3 -N/NH 4 -N didn’t show significant rules inwoodland and cropland areas.

Fig.1 Nutrient changes of groundwater in riparian zones of different distances from river bank(Groundwater in summer shown in left, groundwater in winter shown in right)
Table 2 Nutrient ratios of riparian groundwater in different lands
Summer

WinterWoodlandCorpland

Urbanland

WoodlandCorpland

Urbanland

TN/TP

19.36(6.02-44.94)

35.11(8.44-92.68)

17.21(5.05-41.20)

28.11(14.25-58.19)

32.82(16.99-61.17)

33.42(11.84-86.25)

NO 3 -N/NH 4 -N

21.37(4.77-37.54)

26.14(12.23-35.08)

11.73(5.59-17.35)

19.93(3.75-94.74)

17.75(3.27-68.62)

22.18(3.28-69.34)

DRP/TP

0.26(0.14-0.53)

0.43(0.13-0.88)

0.23(0.07-0.64)

0.51(0.26-0.86)

0.62(0.42-1.32)

0.62(0.30-0.86)

DOC/TOC

0.76(0.66-0.84)

0.47(0.32-0.73)

0.60(0.39-0.91)

0.82(0.67-0.94)

0.58(0.32-0.85)

0.78(0.63-0.93)

Organic matter can influence nitration anddenitrification process of groundwater, and alter408

the relative ratio of nitrate and ammonia [17]. By
contrast, phosphorus is significantly affected bysoil compositions like Fe and Al, and lessaffected by organic matter[18]. As shown in
Fig.2, the correlations of TOC withNO 3 -N/NH 4 -N were better than with DP/TP,

and better correlations were shown in winterthan in summer. These situations can beinterpreted as the stable concentrations of
nutrients in winter. Besides, the microorganism
growth weakens in winter, reducing variation ofnutrients, in particular for nitrogen.

CONCLUSIONS
Nutrients of riparian groundwater of Tiaoxi
watershed are significantly influenced by land
use and land cover. Nitrogen and phosphorus
show higher concentrations in groundwater ofurban area than in woodland and cropland areas,
but higher carbon concentrations are distributed
in cropland area. NO 3 -N and DOC are
dominated species in riparian groundwater for
nitrogen and carbon, but DRP in not forphosphorus. Hydrological conditions also affectvariations of nutrients in groundwater, whichshow the higher nutrient concentrations andbetter correlations in winter. The effects oforganic carbon on nitrogen and phosphorus arealso better in winter. Variations of nutrients incropland area are significantly higher than inwoodland and urban areas, manifesting effect of
cultivation on riparian groundwater.

Fig.2 Correlations of TOC and DOC with NO 3 -N/NH 4 -N and DRP/TP in riparian groundwater
The upper four plots represent summer situations and the lower four plots represent winter situations.
Exchange Fund from Ministry of Science andTechnology of China (No.0102012DFA60830)
ACKNOWLEDGEMENTS
and the Natural Science Foundation of China(No.41372354). Binwu Liu and Xiaoyong Luo
This study was financially supported by theare appreciated for their help in field work.
International Technology Cooperation and
409

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[5] Chen LD, Peng HJ, Fu B, "Seasonalvariation of nitrogen-concentration in thesurface water and its relationship with land
use in a catchment of northern China." Journalof Environmental Sciences, 2005, 17, pp.
224-231.
[6] Vidon PC, Allan C, Burns D, "Hot spots andhot moments in riparian zones: Potential for
improved water quality management1."
JAWRA Journal of the American Water
Resources Association, 2010, 46, pp. 278-298.
[7] China Ministry of Environmental Protection,
Monitoring and analysis methods of water andwastewater. Monitoring and analysis methodsof water and wastewater. Beijing, Chinese
Environmental Sciences Press, 2002, ch.3.
[8] Schenk MK, Barber SA, “Phosphate uptake
by corn as affected by soil characteristics androot morphology”, Soil Sci.Soc. Am. J., 1979,
43, pp 880–883.
[9] Cronan CS, Piampiano JT, Patterson HH,“Influence of land use and hydrology onexports of carbon and nitrogen in a Maine
river basin”, J. Environ. Qual., 1999, 28, pp.
953-961.
[10] Meyer J, Paul M, Taulbee K, “Stream
ecosystem function in urbanising landscapes”,
Journal of the North American BenthologicalSociety , 2005, 24, pp. 602–612.
[11] Neill C, Deegan LA, Thomas SM, Cerri.C
C, “Deforestation for pasture alters nitrogenand phosphorus in small Amazonian streams”,
Ecological Applications, 2001, 11, pp. 1817
-1828.
[12] Saunders TJ, McClain ME, Llerena CA,“The biogeochemistry of dissolved nitrogen,phosphorus, and organic carbon alongterrestrial-aquatic ﬂowpaths of a montane
headwater catchment in the Peruvian
410

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

HEAVY METAL DESORPTION STUDIES ON THE ARTIFICIALLYCONTAMINATED AL-QATIF SOIL
Arif Ali Baig Moghal1, Mosleh Ali Al-Shamrani2 and Waleed M Zahid3
Assistant Professor; 2 Professor; 3 Associate Professor, Department of Civil Engineering, College ofEngineering, King Saud University, Riyadh

1

ABSTRACTIn this study, the relevance of mineralogy on the desorption capacities of Cu+2 and Pb+2 from artificiallycontaminated Al-Qatif soil has been investigated. The desorption capacities of both Cu+2 and Pb+2 using
ethylenediaminetetraacetate (EDTA) as decontaminating solution are determined. The effect of decontaminating
solution dosage and liquid to solid ratio on desorption capacities are examined. Under identical conditions, theremoval efficiency of Pb+2 ions are found to higher than Cu+2 ions. This has been attributed mainly due to thedifferences in surface charges of specific retention sites which hold these metal ions. Further, the heavy metal ion
solubility and surface properties of respective clay minerals decide the desorption rate in soil systems as the pore
fluid pH reaches the heavy metal solubility range or point of zero charge of the clay minerals. These studies provide
valuable insight with regards to their applicability as potential barrier materials for containing industrial leachates.
Keywords: Copper, Decontaminant, Desorption, EDTA, Lead, Mineralogy, Surface area.

considered important factors in desorption processes
and need to be evaluated.
Two common types of heavy metal contaminants,
copper and lead are considered in the study. Pollutionof soil and water by copper may arise from copper
mining and smelting and other industrial uses. Also,
acute concentration of copper in solutions leads toCirrhosis of the liver in children. On the other hand,lead is a non-essential element and it is not asbioavailable as other metals. It is a poisonous metal
and its intake can damage nervous connections(especially in young children) causing blood andbrain disorders. Long-term exposure to lead or its
salts can cause nephropathy, and colic-like abdominal
pains. Hence, in the present study, soil washingmethodology has been employed to reduce thetoxicity of Cu+2 and Pb+2, by using a chelant in theform of EDTA, since chelating extraction of heavy
metals has been proposed as an effective remediation
technique for contaminated soils. The effect of liquidsolid ratio in enhancing the extractability has also
been studied. The studies will enable to estimate thefraction of metal ion available for achieving selective
recovery of Cu+2 and Pb+2 individually from thecontaminated soil systems.

INTRODUCTION
Soil is a basic building block for the mostterrestric ecosystems and a complex heterogeneous
medium consisting of both solid and fluid phases. The
ability of these soils in absorbing and desorbing metal
ions from the aqueous phase assumes importancesince it governs both the environmental andagricultural issues [1]. The clay fraction
predominantly affects the metal ion concentrations inenvironmental systems owing to their ability inadsorbing these ions and further in releasing the samein part or whole when subjected to prevailing
atmospheric conditions [2].
For ex situ systems, the contaminants are generally
adsorbed on to the fine grained soil fraction andextraction of heavy metal ion complexes has been
confirmed by the use of various chelating agents like
citric acid, diethylenetriaminepentaacetic acid
(DTPA),
sodiumethylenediaminetetraacetate(EDTA), sodium nitrilotriacetate (NTA) and strongacid such as hydrochloric acid (HCl), nitric acid
(HNO 3 ) have been used to desorb metals from soils[3-6].
But, most of these research studies did notemphasize on the effect of clay mineralogy or theeffect of H+ ions on the desorption response. Basedon the solubility of heavy metals and the surface
properties of clay minerals, desorption of heavy metal
ions in soil systems occurs as the pH of the pore fluidin the soil reaches the solubility range of the heavy
metal or is lowered to the point of zero charge of theclay minerals [6]. The amount of H+ ions available in
the pore fluid and the nature of clay minerals are

MATERIALS
The tests were conducted on samples collectedfrom Al-Qatif, a coastal oasis region located on thewestern shore of the Persian Gulf in the Eastern
Province of Saudi Arabia (26° 56′ 0″ N, 50° 1′ 0″ E).
The sampling was carried out at a depth of 3.0 m. The

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physical properties and chemical composition arereported in Tables 1 and 2 respectively.
METHODOLOGY
Particle size analysis based on laser diffraction as
per ASTM B822 - 02 [7] was carried out on theselected soil sample. Laser diffraction relies on thefact that particles passing through a laser beam will
scatter light at an angle that is directly related to theirsize. As particle size decreases, the observed
scattering angle increases logarithmically. Larger
particles therefore scatter light at narrow angles withhigh intensity whereas smaller particles scatter lightat wider angles but with low intensity. From Figure 1,
it can be seen that major portion of the selected soil
has a gradation ranging from 0.1 to 10 µm. This finer
fraction is critical to the study as it affects desorptionof Cu+2 and Pb+2 quite considerably.
The predominant minerals were determined bycarrying out XRD using Bruker D8 Advance system.
Samples were scanned from 2° to 60° (2θ) using
2.2kW Cu anode long fine focus ceramic X-ray tube
at a scanning rate of 1 degree per minute. XRD
patterns of samples were then compared withstandard patterns [8]. Fig. 2 depicts comprehensive X
Ray diffraction analysis. In addition to Quartz,
Dolomite, Illite, Muscovite, and Palygorskite, thepresence of Montmorillonite (a smectite groupmineral known to induce significant swelling uponinteraction with water) is noteworthy.

Fig.1 Particle Size Distribution Curve by Laser
Diffraction Analysis

Table 1 Physical properties of the soil
Physical Property
Liquid Limit (%)
Plastic Limit (%)
Shrinkage Limit (%)
Plasticity Index (%)
Linear Shrinkage (%)% Finer than 200 μm
USCS Classification
Specific Gravity

Al - Qatif
137
60
22
77
77
99.1
CH
2.71

Fig. 2 X - Ray Diffraction Analysis
Contamination Procedure
About 0.5 kg of oven dried soil was thoroughly
mixed with deionized double distilled water in a 1:1
ratio, containing dissolved nitrate salts of copper
nitrate, Cu(NO 3 ) 2 and lead nitrate, Pb(NO 3 ) 2
separately. The entire slurry was allowed to age at
controlled temperature (23±0.5°C) for a period of 2
months. The slurry was mixed frequently during thecourse of aging period. At the end of aging period, themixture was oven dried and acid digestion techniqueusing US EPA Method 3050B [9] was employed on
the respective samples below the boiling point todetermine the Cu+2 and Pb+2 concentrations. Table 3
gives the metal concentrations of the selected metal
ions before and after contamination.

Note: ‘USCS’ refers to unified soil classification
System; ‘CH’ refers to clay with high plasticity

Table 2 Chemical composition of the soil
Chemical Composition
K+
K2 O
Al
Al 2 O 3
Si
SiO 2
Ca+2
CaO
CEC (cmol/kg)

Al – Qatif (%)
1.8
2.2
3.3
6.3
8.1
17.3
0.7
0.9
137

Desorption Batch Tests
Batch desorption experiments were carried out bymechanically shaking series of bottles containing theartificially contaminated soil samples at different
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GEOMATE- Brisbane, Nov. 19-21, 2014

initial conditions. EDTA was used as adecontamination solution. The tests were carried out
by placing 1g of soil in 100 ml teflon bottles followedby addition of varying volumes (10 mL, 20 mL, 40
mL and 50 mL) of the washing solution (HNO 3 ). In
order to determine the effect of concentration of
decontaminating solution on the extractability ofrespective metal ion, the concentration of EDTA wasvaried as 0.1 M, 0.2M and 0.5M for each dilution ratiocase. The samples were placed on a shaker table
operated at 175 rpm at room temperature.

Table 4 Effect of chelant (EDTA) concentration andliquid to solid (L/S) ratio on the removal efficienciesof Cu+2 and Pb+2
Removal efficiency (%)
DI
0.1M
0.2M
Water
L/S Ratio 1:10
Cu+2
19.1±0.5 55.3±0.5 68.7±0.5
Pb+2
16.8±0.5 48.7±0.8 71.2±1.1
L/S Ratio 1:20
Cu+2
17.3±0.5 61.2±0.5 78.6±0.8
Pb+2
15.7±0.5 58.6±0.7 81.3±0.5
L/S Ratio 1:40
Cu+2
15.6±1.7 76.5±1.6 85.3±1.3
Pb+2
18.6±0.5 69.7±0.5 89.1±0.5
L/S Ratio 1:50
Cu+2
18.2±0.5 80.1±0.7 86.7±0.7
Pb+2
14.8±0.5 77.6±0.7 91.1±0.5
Washing
Solution

Table 3 Concentration of the metal ions
Background concentration of theoriginal uncontaminated soil
Cu+2
13±0.5 mg/kg+2Pb
15±0.5 mg/kg
Metal concentration of thecontaminated soil
Cu+2
833±2 mg/kg+2
Pb
758±2 mg/kg

0.5M
81.2±0.5
89±1.384.5±0.590.6±1.2
91.1±0.993.7±0.594.3±1.1
96.2±0.7

The implication of using DI water is to arrive at
the fraction of the metal that is weakly bound to thesoil particles and is readily available for mobilization.
It can be seen from Table 3 that, the fraction of Cu+2
and Pb+2 metal ions are strongly bound and isvirtually independent of the soil to DI water ratio.
Hence, the removal efficiencies are quite low and it isevident that, the remaining fractions of the metals are
considered to be strongly bound and immobilized
within the soil matrix under natural-water conditions.
Also, with DI water, the resulting removal efficiency
is due to rapid dissolution of weakly bound Cu+2 andPb+2 ions retained at easily co-ordinated sites on theouter surfaces of clay matrix. Similar observations
have been made by Abumaizar and Smith [11] when
DI water was used to decontaminate Cd, Pb, Zn and
Cr metal ions. Generally, in contaminated soils thetotal amount of metal ion concentration in the
aqueous and solid phases is at levels much higher thanthose found in the solution phase. The solubility
values of the metal ions are typically very small andit will not yield satisfactory removal efficiencies.
Further, the respective metal ion solubility values areheavily dependent on predominant mineral phasesthat which are affected by pH and available ambient
ligands.
The effect of 0.1M EDTA on the extractability ofmetal ions (Table 3) indicates that, there is asignificant improvement in both Cu+2 and Pb+2
removal over flushing with DI water. The best
removal efficiency for both the metal ions was
obtained at a 1:50 soil to liquid ratio. Since, copper
may be present in solution as either Cu2+ or Cu+,
although the more oxidized Cu2+ predominates due tothe redox reaction in aerated water. Both copper andlead ions are prone to complexation, especially withhydroxide and carbonate ligands. The ideal mineralphases for metal complexation include those of oxide,hydroxide, carbonate and hydroxy carbonate, such as

A 2-h reaction time was deemed sufficient based
upon batch rate desorption tests conducted over a 48h period. After mixing, the samples were allowed tosettle for about 15 min and then filtered through a
0.45-µm membrane filter. The accuracy wasestablished by preparing replicate of three aliquots foreach test. In the present study, it has been assumed
that the metal concentration of the filtrate represents
that released from the contaminated soil. Removal
efficiencies were determined by dividing the heavy
metal release quantities by the initial quantity in thesoil. The residual concentration of the heavy metal
ions (Cu+2 and Pb+2) in the filtered solution wasdeterminedusing
atomicabsorption
spectrophotometry (AAS). AAS calibrations wereprepared from standard stock solutions.
RESULTS AND DISCUSSIONS
Generally, when metal-containing compounds are
dissolved in water, the metallic component exists asmobile ions in solution phase. But when these
metallic ions are complexed by inorganic or organic
ligands, they will be present in aqueous solution onlyat very low concentrations in the pH range of natural
surface and subsurface waters. When theconcentrations of these metals exceed the solubilityof their corresponding hydroxide or carbonate phaseat a given pH value, metal precipitates willintermingle and become an integral part of the soil
matrix which is of prime concern [10]. The removal
efficiencies of Cu+2 and Pb+2 using deionized double
distilled water and EDTA solution from artificiallycontaminated soil are summarized in Table 4.

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GEOMATE- Brisbane, Nov. 19-21, 2014

MO(S), M(OH) 2 (S), MCO 3 (S) and M x (OH) y (CO 3 ) z[12].
The presence of montmorillonite in Al-Qatif clay
has been confirmed by Fig. 2 and the uptake of Cu+2
and Pb+2 metal ions is considered to occur primarily
by ion exchange process on to this mineral site. The
calcium sites in Al-Qatif clay (Table 2) have theability to successfully displace a high proportion of
the metal ions retained on the clay sites at higher
molar concentrations of EDTA, thereby resulting inhigher removal efficiencies for both the metal ions.
But, at lower molar concentrations of EDTA, thecalcium ions have limited ability to dissolve
precipitated hydrous oxides of Cu+2 and Pb+2 andhence relatively smaller amounts are desorbed in theextracting solution. Also, with increase in EDTA
concentration, competition from hydronium ions forthe available oxide surfaces starts diminishing which
also results in the increased removal capacities.
Hence, relatively higher amounts of Cu+2 and Pb+2 areflushed out into the washing liquid.
The difference in removal efficiencies between themetal ions may be due to the differences in surface
charges of specific retention sites like dolomite, illite,
muscovite, and palygorskite (as seen from Fig. 2)
which hold these metal ions and also due to theparticle size distribution (the selected soil has a
gradation ranging from 0.1 to 10 µm as noted from
Fig.1). The surface properties of carbonate and FeMn oxide sites in Al-Qatif clay dictate the release of
Cu+2 and Pb+2 as the pore fluid pH reaches the theirsolubility range or point of zero charge of the oxide
sites, particularly at higher EDTA concentrations of
0.2M and 0.5M. From the batch chelant desorption
tests, EDTA was extremely effective indecontaminating Cu+2 and Pb+2 from the artificiallycontaminated Al-Qatif soil. The removal efficiencies
achieved were satisfactory and contaminatedindustrial repositories can be successfully treatedwith this technique.

(EDTA, in this case) for Al-Qatif soil in removing
Cu+2 and Pb+2 metal ions. Depending on the target
clean up level for respective metal ion, the feasibilityof soil washing with EDTA may be readily
determined using the data in Table 4 as a supporting
guide. The employed technique is relatively costcompetitive and extremely effective compared toexisting methodologies.
CONCLUSIONS
The decontamination of metal contaminated soils
is primarily controlled by the dissolution of the metalmineral bond followed by the dispersion of the target
metal ion in the selected extractant or into an easily
extractable or residual form. The results of batch
washing tests indicate that Cu+2 and Pb+2 metal ionscan be extracted from artificially contaminated soils
independently using EDTA as a chelating agent. The
use of DI water as a washing solution resulted in alesser removal efficiency of ≈ 17 - 20%, for Cu+2 andPb+2 metal ions, which confirms that these metal ions
are strongly bound and are not readily mobilized inaqueous solutions. The effect of 0.1M EDTA on theextractability of metal ions indicates that, there is asignificant improvement in both Cu+2 and Pb+2
removal over flushing with DI water. There was athreefold increase in removal efficiency with 0.1M
EDTA compared to DI water alone. With increase inconcentration of EDTA solution, relatively higher
removal efficiencies of ≈ 90 – 95 % were achieved.
The mobility of Pb+2 ions was slightly higher thanCu+2 ions. The increase in liquid/solid ratio also aids
in better removal efficiencies.
ACKNOWLEDGEMENTS
This paper is a part of a research project that was
supported by NSTIP strategic technologies programs,
12ENV2583-02 in the Kingdom of Saudi Arabia. The
authors would like to thank the Eng. Abdulla Bugshan
Research Chair for Expansive Soils and Prince Khalid
Bin Sultan Chair for Water Research for providing
the necessary facilities to carry out the experimental
work.

PRACTICAL IMPORTANCE OF THE STUDY
Heavy metal contaminated site is among the mostcommon problem constraining cleanups andassociated costs at industrial waste repositories in theKingdom of Saudi Arabia. A typical soil washingtechnique involves, vigorous washing of the soil withwater containing little amount of surfactants followedby solid/liquid separation for collecting the clay/silt
fraction. This clay/silt fraction usually is treated byimmobilization techniques and disposed off in alandfill while the bulk of the decontaminated soil isreturned back to the site. But, in soils where heavy
metals are present in higher concentrations soil
washing alone would not suffice and chelants are
required to reduce the toxicity to target levels. The
current study addresses these issues and gives
valuable insight in selecting appropriate extractant

REFERENCES[1] Bradl HB, “Adsorption of heavy metal ions on
soils and soils constituents”, J. of Colloid andInterface Science, Vol. 277, Sep. 2004, pp. 1-18.
[2] Farrah H and Pickering WF, “Extraction ofheavy metal ions sorbed on clays”, Water, Air,and Soil Pollution, Vol. 9, 1978, pp. 491-498.
[3] O’Shaughnessy JC, D’Andrea RC, Canniff MR,
St. Germain S, Venkataramanappa S, andJacaulay MJ, “ Evaluation of in situ soil flushingtechniques for heavy metals removal fromcontaminated soils”, In the Proc. of the 48th414

GEOMATE- Brisbane, Nov. 19-21, 2014[8] JCPDS, “Joint Committee for Powder
Diffraction Studies: International Centre forDiffraction Data (ICDD)”, The Powder
Diffraction File, 1999, Newtown Square, PA.
[9] USEPA, “Tests methods for evaluating solid
waste, Physical Chemical Methods”, SW-846,
Method 3050B, 1996, US Environmental
Protection Agency, Washington, DC.
[10] Chen T, Macauley E, and Hong A, “Selection
and test of effective chelators for removal ofheavy metals from contaminated soils”,
Canadian J. of Civil Engineering, Vol. 22, No. 6,
Dec. 1995, pp. 1185–1197.
[11] Abumaizar RJ, and Smith EH, “Heavy metal
contaminants removal by soil washing”, J. of
Hazardous Materials, Vol. 70, Dec. 1999, pp. 7186.
[12] Peters RW, “Chelant extraction of heavy metals
from contaminated soils”, J. of Hazardous
Materials, Vol. 66, Apr. 1999, pp. 151-210.

Purdue Industrial Waste Conference. Lewis
Publishers, Chelsea, Mich., 1993, pp.123–139.
[4] Hong A, and Chen TC, “Chelating extraction andrecovery cadmium from soil using pyridine-2,6dicarboxylic acid”, Water, Air, and Soil
Pollution, Vol. 86, 1996, pp. 335–346.
[5] Steele MC, and Pichtel J, “Ex-situ remediation ofa metalcontaminated superfund soil using
selective extractants”, J. of Environmental
Engineering, ASCE, Vol. 12, No.7, July. 1998,
pp. 639–645.
[6] Li LY, and Li RS, “The role of clay minerals andthe effect of H+ ions on removal of heavy metal(Pb2+) from contaminated soils”, Canadian
Geotechnical J., Vol. 37, No. 2, Apr. 2000, pp.
296–307.
[7] ASTM B822 – 02, Standard Test Method forParticle Size Distribution of Metal Powders andRelated Compounds by Light Scattering, 2002,
West Conshohocken, PA.

415

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

RECURRENCE INTERVALS OF METEOROLOGICAL DROUGHTEVENTS ACROSS EASTERN AUSTRALIA – IMPLICATIONS FORDISTURBED LANDSCAPES
Devanmini Halwatura1, Alex M. Lechner1,2 and Sven Arnold1
Centre for Mined Land Rehabilitation, Sustainable Mineral Institute, The University of Queensland,
Australia. 2Centre for Environment, The University of Tasmania, Hobart, Australia

1

ABSTRACT
Droughts are one of the most devastating natural hazards, often causing severe economic and environmental
damage. Across Eastern Australia climate is highly variable and frequent floods and droughts affect large areas
over prolonged periods of time. Understanding the variations and trends in these weather extremes is critical for
ecologists to assess the adequacy of management plans for anthropogenically affected landscapes such as
agricultural or post-mining land, where water often plays a critical role for ecosystem persistence.
This study focuses on analysing drought events of four selected locations (Cairns, Melbourne, Wagga Wagga,
Quilpie) across Eastern Australia using the Reconnaissance Drought Index (RDI). We used monthly total rainfall
and evaporation data of the past 40 years (1972-2013) to identify drought events. We categorised the drought
events according to their severity and duration and analysed separately the historic time series as two parts of 20
years (1972-1992 and 1993-2013). We calculated the recurrence intervals of droughts to assess trends in theoccurrence of drought events. Results show that the recurrence intervals of Melbourne and Quilpie barelychanged over time, while the drought recurrence intervals decreased in Wagga Wagga and Cairns. Thesefindings have critical implications for any rehabilitation and management plans for post-mining and agriculturalland.
Keywords: Drought, Reconnaissance Drought Index, Recurrence intervals, Land rehabilitationenergy resources [8]. These environments include anumber of abandoned and ongoing mines. There areover 34,000 recorded abandoned mines in theeastern states of Australia (New South Wales,
Queensland, and Victoria) that potentially needrestoration owing to the legislative requirement for
maintaining a sustainable mining industry inAustralia [9]. The quantification of severity,
duration, and frequency of drought events is crucial
for planning for successful regeneration of these
post-mined lands.

INTRODUCTION
Human alteration from mining, urbanisation andindustrial development can degrade lands,
significantly impacting the natural environment [1].
Re-establishment of these lands has become apriority in this century. In recent years ecologists
have focused more on global climate change [2] inaverage conditions such as mean temperature andrainfall. However, weather events such as intensestorms, changes in El Niño and La Niña cycles,
coastal flooding, extreme temperatures and droughts[4, 5] have intensified in the last decades and are thebarriers for successful rehabilitation practices [5].

Drought analyses vary according to their
purpose. Meteorological droughts are the mostfrequently studied type of drought, and standardized
drought indices, such as the ReconnaissanceDrought Index (RDI), provide the foundation for
quantifying the duration, severity, and eventually thefrequency or recurrence of meteorological drought
events [10]. Drought severity, duration andfrequency of occurrence are some of the key driversof ecosystem rehabilitation because water
availability is the primary abiotic factor forecosystem rehabilitation in semi-arid climates [8].

Droughts are one of the most harmful climatic
events and often have significant impacts onenvironment and socio-economic assets all over theworld, including Australia [6]. In proportion to its
area, Australia has a very low percentage of runoff
to rainfall. This, together with moisture deficits that
occur for decades, makes Australia a very dry place[7]. Eastern Australia, in particular, has highlyvariable and frequent droughts that affect large areas
over prolonged periods of time.

The objective of this study was to quantify theseverity and duration of drought events at four
selected locations in Eastern Australia based on the
RDI. Two historic time series of rainfall andEastern Australia comprises a broad range ofagro-climatic environments which support globallysignificant biodiversity and holds vast mineral and416

GEOMATE- Brisbane, Nov. 19-21, 2014

evaporation data for the past 40 years (1972-1992
and 1993-2013) were used to estimate the recurrence
intervals of droughts for each of these sites in order
to investigate climatic trends. We conclude by
discussing the potential use of the method outlinedin this paper as a management and risk assessment
tool for rehabilitation of disturbed landscapes.
METHODOLOGY
We selected four sites across Eastern Australia(Cairns, Melbourne, Wagga Wagga, Quilpie)(Figure 1) across different agro-climatic classes [11]and agricultural environments [12] (Table 1). For
these sites rainfall and potential evaporation (PET)data was most comprehensive, i.e. longest (40 years)
and most complete [13]. For a detailed description of
the methodology described in this paper refer to [8].
Table 1. Climate indices and climatic classificationsof selected locations across Eastern Australia.
Location andclimateclassification[14]

R/PET
[15]

R w/R s a
19932013

Figure 1. Selected locations of interest in Eastern
Australia.

Cairns (Tropical)
0.91
0.12
0.11
Melbourne
0.51
1.20
1.11
(Temperate)
Wagga Wagga
0.30
1.75
1.23
(Temperate)
Quilpie
0.14
0.73
0.51
(Temperate)aBased on average of three months of rainfall during
the winter (June-August) and summer (DecemberFebruary)

We categorized the drought events according totheir severity and duration and split the historic timeseries into two parts of 20 years (1972-1992 and1993-2013). Drought severity refers to the extent towhich precipitation is below a threshold, whereas
the drought duration is the period of rainfall deficit,
preceded and followed by periods with no deficit[17]. Drought severity and duration were fitted to a
gamma and logistic distribution, respectively [8].
We used the Frank copula to form a multivariate
distribution of the fitted distributions of severity andduration. The copula parameter was then estimatedaccording to the Inference Function for Margins(IFM) [8]. Recurrence intervals of drought events
exceeding specific values of severity or duration(indicated by the logical operator “˅”) were
calculated as:

19721992

We estimated drought severity and duration
using RDI at a 3-monthly time scale [16] based onmonthly rainfall and PET. The standardized RDIst is
given as:with

𝑹𝑹𝑹𝑹𝑹𝑹𝒔𝒔𝒔𝒔(𝒌𝒌) =𝒚𝒚𝒌𝒌 = 𝐥𝐥𝐥𝐥

�𝒌𝒌𝒚𝒚𝒌𝒌 − 𝒚𝒚� 𝒌𝒌
𝝈𝝈∑𝒋𝒋=𝒌𝒌𝒋𝒋=𝟏𝟏 𝑷𝑷𝒋𝒋

∑𝒋𝒋=𝒌𝒌𝒋𝒋=𝟏𝟏 𝑷𝑷𝑷𝑷𝑷𝑷𝒋𝒋(𝟏𝟏𝟏𝟏)𝑻𝑻˅𝑹𝑹𝑹𝑹𝑹𝑹 =(𝟏𝟏𝟏𝟏)

𝟏𝟏

𝑷𝑷(𝑺𝑺 ≥ 𝒔𝒔 ˅ 𝑫𝑫 ≥ 𝒅𝒅)

=

𝟏𝟏

.

𝟏𝟏− 𝑪𝑪[𝑭𝑭𝑺𝑺(𝒔𝒔),𝑭𝑭𝑫𝑫 (𝒅𝒅)](2)

RESULTS� is the standard deviation, y k is the month
where 𝛔𝛔k during the year, 𝐲𝐲�𝐤𝐤 is arithmetic mean of yk,
� 𝐤𝐤 is the standard deviation of k, P j and PET j
and 𝛔𝛔are precipitation and potential evapotranspiration forthe jth month of the hydrological year [10].

The recurrence intervals depicted in figure 2
describe site-specific rainfall patterns. In arid
Quilpie the recurrence interval for droughts with aseverity of 13 or duration of 17 months is one in 50
years, whereas in tropical Cairns the recurrence
interval for the same drought is one in 100 years(1972-1992) or one in 1000 years (1993-2013).
Temperate Wagga Wagga has a similar pattern of417

GEOMATE- Brisbane, Nov. 19-21, 2014

prolonged and severe droughts as arid Quilipe(1972-1992) (Figure 2) with a recurrence interval of
one in 50 years for a drought of severity 12 orduration of 18 months.

Table 2. Mean severity (µ S ) and duration (µ D ) of
selected locations across Eastern Australia andcorresponding coefficients of variation CV S andCV D for short-term (RDI 3 ) droughts from 1972 to
1992 and 1993 to 2013.

Location

µS

CV S

µD

CV D

4.5
4.3
5.5
3.4

0.5
0.7
0.9
1.1

6.1
5.3
6.8
4.5

0.4
0.5
0.7
0.7

4.8
4.5
4.6
3.5

0.4
0.7
0.6
1.1

6.4
6.1
5.7
4.7

0.3
0.4
0.4
0.7

1972-1992
CairnsMelbourne
Wagga Wagga
Quilpie
1993-2013
CairnsMelbourne
Wagga Wagga
QuilpieDISCUSSION
Land rehabilitation is a continuing issue in
Eastern Australia due to below average rainfall
resulting in decreased water availability along withhigh variable rainfall [8, 18]. However, across
Eastern Australia, site specific rainfall and drought
metrics have rarely been used [8, 19]. In this study
we assessed trends in recurrence intervals ofdroughts for selected locations across Eastern
Australia, extending a previous study on recurrence
intervals as a planning tool for ecosystemestablishment in post-mining landscapes [8]. The
findings of this study and the methods developed
may help to understand the variation of temporaldrought patterns and encourage land managers toapply recurrence intervals of droughts as an earlyrehabilitation assessment tool.

Figure 2. Recurrence intervals of drought events ofany severity or duration of interest based on historic
rainfall data for: (a) 1972-1992 and (b) 1993-2013.

Australia is often referred to as the driest
inhabited continent on Earth as it includes a large inarid zone with significant temperature andprecipitation variability [20]. Generally, theAustralian climate can rapidly alternate between dry
and wet periods, occasionally exhibiting sharptransitions or sudden shifts between the extreme
events [21]. In Eastern Australia these climatic
extremes are mainly controlled by large variations of
the El Niño Southern Oscillation (ENSO) [8], which
affects different regions at different times of the year[22]. These extreme climatic events impact on
rainfall, influencing the average severity andduration of droughts, a primary abiotic factor driving
rehabilitation (Table 2) [8].

For Quilpie and Melbourne there was very little
difference in the frequency of drought events
between the two 20-years time series (1972-1992
and 1993-2013), whereas for Cairns and Wagga
Wagga the frequency of severe and prolonged
droughts decreased over time (Figure 2). For all
locations, except for Wagga Wagga, drought
severity and duration increased between the first andthe second period (Table 2). In the first period from1972 to 1992, Wagga Wagga had the highest
drought severity and duration, and Quilpie thelowest (Table 2). For the second period, from 1993
to 2013, drought severity and duration were highest
in Cairns and lowest in Quilpie (Table 2).

418

GEOMATE- Brisbane, Nov. 19-21, 2014

water deficit and should be implemented into
rehabilitation plans of disturbed lands.

The RDI 3 detected most severe and prolonged
droughts in the tropical locations of Eastern
Australia [8]. For the historic time series of 19721992 and 1993-2013 the most severe and prolonged
droughts were detected in Wagga Wagga(temperate) and Cairns (tropical). The two locations
have seasonal rainfall patterns, e.g. in Wagga Wagga
winter rainfall is high, while in Cairns summer
rainfall is high (Table 1). In arid Quilpie evaporation
was high and seasonal rainfall patterns were absent.
In contrast to tropical Cairns and temperate Wagga
Wagga (Table 1), Quilpie has lower severity andduration of short term droughts and severe andprolonged long-term droughts [8].

REFERENCES
1.

2.

3.

The importance of rainfall variability including
extreme rainfall patterns and below average rainfall
has been highlighted in many research studies on
ecosystem rehabilitation [8, 23, 24]. As plants arevulnerable to plant available water, identifying
droughts and their characteristics play a critical rolein ecosystem rehabilitation [25]. Recurrence
intervals of short term droughts (Figure 2) can beused as metric for risk assessment, management andrehabilitation of degraded lands [19].

4.

5.

6.

Estimated recurrence interval curves incorporate
the severity and duration of drought events, also
referred to as “design droughts” [8]. They provide
the probability of occurrence of drought at aparticular severity or duration so that land managers
can assess the risk of failure of successful early
ecosystem rehabilitation by selecting the suitable
plant species for specific climatic conditions. Some
plant species are highly sensitive to specific droughtcharacteristics [26]. Similarly recurrence intervals
along with known probabilities of plantestablishment success for particular drought
conditions provide a decision support tool for land
managers to undergo a cost-benefit analysis prior torehabilitation.

7.

8.

9.

10.
Finally, this study demonstrated how differencesin recurrence intervals can be identified between twotime-series and potentially be used to identify longterm trends. Our results support climatologicalstudies that found increasing drought severity andduration to be more likely due to global climatechange [5].

11.

12.
CONCLUSION
Recurrence interval curves or design droughts can beused to identify the severity, duration and frequencyof occurrence of droughts for a given location. These
recurrence intervals can be used to analyze the riskof failure of initial ecosystem establishment due to

13.

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Bridge, G., Contested terrain: mining andthe environment. Annu. Rev. Environ.
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Mason, L., et al., Adapting to climate risks
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Halwatura, D., A.M. Lechner, and S.
Arnold, Design droughts as planning toolfor ecosystem establishment in post-mining
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Unger, C., et al., Mapping and Prioritisingrehabilitation of abandoned mines inAustralia. Proceedings Life-of-Mine, 2012:
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Tsakiris, G. and H. Vangelis, Establishingadrought
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Hinz, C., G. McGrath, and A. Hearman.
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Hodgkinson, J.H., et al., Climate
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Engelbrecht, B.M., et al., Drought
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447(7140): p. 80-82.
Arnold, S., Y. Kailichova, and T.
Baumgartl,
Germinationof
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PeerJ, 2014. 2: p. e268.

420

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EUTROPHICATED SEDIMENT REMEDIATION USING SHELLFRAGMENT AS REGIONAL UNUSED RESOURCES FOR NUTRIENTSELUTION CONTROL

1

Kazuhito Murakami1, Saki Agatsuma1, Michio Gomyo1 and Akiko Inoue-Kohama2
Department of Life and Environmental Sciences, Chiba Institute of Technology, Japan; 2 Tohoku Instituteof Technology, Japan
ABSTRACT

Dominant species of Aoko, Anabaena, has a “function of nitrogen fixation from air”, so if there is evenphosphorus in water, they can multiplicate explosively. This study aimed the removal of phosphorus by shells ofregional unused resources as eutrophication countermeasure in Hasunuma Seaside Park Pond. As result,sprinkling crushed shells was essential to the removal of phosphorus and the increase control of phytoplankton
such as Anabaena spiroides. Inhibition rate of phosphorus showed a high percentage with much quantity ofdispersion. At the N/P ratio, all dispersion system showed the higher value in comparison with no-treatedsystems. Hardness showed a high percentage with much quantity of dispersion because of Ca2+ was eluted into
water from shell body. The dominant species of phytoplankton was changed to Chlorella sp. and the growth ofthe phytoplankton was controlled until fifth or tenth day by Ca2+ eluted from shells fragment.
Keywords: Shell, Regional unused resources, Phosphorus removal, Water quality, Brackish pond

INTRODUCTION
In the lakes of Japan, the achievement rate ofchemical oxygen demand (COD) or biochemical
oxygen demand (BOD) of environment standard islower than those of rivers and sea, andeutrophication is under progressing condition. Fig.1
showed secular change of the environment standardof rivers, sea and lakes [1]. It showed highachievement rate of 92.5% in the river and 78.3% in
the sea, but that of lakes showed low value of 53.2%.
As reason for this, lakes are closed environment, andthe resources of nutrient salt are flow from rivers
and elution from sediment. Many countermeasuresagainst eutrophication have been suggested andcarried out. But it is not effective because there areproblem of cost and maintenance management. Lake
Tega and Lake Inba of Chiba prefecture in Japan are
one of the most famous eutrophicated lakes. They
are tackling water environment repair of dredge andraw water transmission business [2].
As eutrophication countermeasure of lakes, there
are physical method such as sediment transaction,
introduction of water purification and the change offlow path of influent water. But it has problem ofcost and maintenance management. Anothercountermeasure is biological method such as
removal of fishes. But it has problem of the
breakdown of ecosystem. Therefore, a new method
is demanded to solute these problems.

Fig.1 Achievement rate of environmental standards(COD, BOD) in lake, river and sea in Japan

MATERIALS AND MEYHODS

Hasunuma Seaside Park Pond (Fig.2) in Sanmu
city of Chiba prefecture locates at 350m inland from
Kujukurihama coast. This pond is strong enclosed,
and its surface area is about 10,000m², water volume
is about 7,400m3, the water depth is 0. 74m inaverage. In past, a rental boat shop opened in thispond, but the problem of stink and deterioration oflandscape occurred because Aoko occurred in every
summer (Fig.3). Improvement works of drying in thesun and drainage work conducted, but Aoko
occurred again in summer of next year [3].
Dominant species of Aoko at this pond isAnabaena spiroides (Fig.4). It has air nitrogen
fixation ability. Therefore, they can multiplication
explosively if there is enough phosphorus in water.
The other side, many shells scattered in
Kujukurihama coast on nearly of Hasunuma Seaside
Park pond. Ca of the constituent parts of shell canadsorb phosphorus as formula (1) of below.

Outline of Experimental Pond

Ca²⁺ + HPO42- + 3H2O → CaHPO4・3H2O↓
421

(1)

GEOMATE- Brisbane, Nov. 19-21, 2014

Shells are dumped as industrial wastes every
year. Using these shells wisely, they can improvewater quality and decrease industrial wastes. This
study aimed the removal of phosphorus by physicaladsorption and chemical combination with Ca eluted
from shell fragments.
Regional unused resources
In this study, Anadara broughtonii (Fig.5) was
supplied as a regional unused resources. It is clamthat belongs to species Aroodia family Arcidae.
These shells inhabit in low tide area and bottom mudof inner bay. As character of shell, it has about 42
radial ribs. And its blood is red for it has
Erythrocruorin that similar to hemoglobin [4].
This shell was broken into 1-3mm size fragment(Fig.6). It sprinkled on the bottom mud of nutrientsresources. Shells are scattered many inKujukurihama coast of neighboring of Hasunuma
Seaside Park Pond. And when its fragment sprayedon bottom mud, the surface of bottom mud looks
bright by a reflection of the light.

Fig.2 Hasunuma seaside park pond

Fig.3 Aoko in Hasunuma Seaside Park pond

Experimental Methods
Water volume in the microcosm test is generally
300-1,000 ml[5]. From this reason, clear glass
container (volume: 470ml, height: 14cm, diameter:7cm,) was used in this study. Mud sediment of 100g
collected from the pond was put in the bottom of thecontainer to become flat, and pond water of 380ml
was poured without disturbing the sediment.
Crashed shells were sprinkled on sediment mud. The
microcosm system was cultured in incubator.
Culture period was 20 days, and culture system isno-treated system and sprinkled systems of 5, 10, 20,
30, 50, 80, 90, 100g/m². Culture condition was 25
degrees(Celsius) in temperature and 2,400lux inilluminance (L/D＝12/12hr). Measuring parameters
were T-P (total phosphorous), PO4-P, T-N (total
nitrogen), NH4-N, NO2-N, NO3-N, COD,
chlorophyll a (Chl.a), pH, DO, hardness (Ca+Mg),
and phytoplankton. Phytoplankton flora wasobserved in every 5 day.

Fig.4 Anabeana spiroides (Aoko)

Fig.5 Anadara broughtonii (shell)

RESULTS AND DISCUSSION
Phosphorus removal
Fig.7 and Fig.8 showed the inhibition rate of T-P
and PO4-P. It showed high value because of there
was much sprinkled in volume. It was the highest
inhibition rate of T-P: 34.9% and PO4-P: 28%. In TP, the inhibition rate became flat at sprinkled
quantity of 5-30g/m² and 50-90g/m². The inhibition
rate of phosphorus did not change between eachquantity of dispersion.

Fig.6 Crushed shells fragment422

GEOMATE- Brisbane, Nov. 19-21, 2014

Sprinkled volume (g/m2)

Sprinkled volume (g/m2)

Fig.7 Inhibition rate of T-P in each microcosm

Fig.8 Inhibition rate of PO₄-P in each microcosma) Run 1 (5 and 50g/m2 sprinkled)control(1)5g/m2b) Run 2 (10 and 100g/m2 sprinkled)

50g/m2

control(2)10g/m2

100g/m2c) Run 3 (20 and 80g/m2 sprinkled)d) Run 4 (30 and 90g/m2 sprinkled)control(3)control(4)20g/m280g/m230g/m290g/m2cell number / mla) Run 1 (5 and 50g/m2 sprinkled)cell number / ml

Fig.9 N/P ratio in each microcosm (20days after)d) Run 4 (30 and 90g/m2 sprinkled)cell number / mlc) Run 3 (20 and 80g/m2 sprinkled)cell number / mlb) Run 2 (10 and 100g/m2 sprinkled)

Fig.10 Total cell number of phytoplankton in each microcosm
423

GEOMATE- Brisbane, Nov. 19-21, 2014b) Run 2 (10 and 100g/m2 sprinkled)hardness (mg/l)

hardness (mg/l)a) Run 1 (5 and 50g/m2 sprinkled)control(1)5g/m2control(2)50g/m2

10g/m2

100g/m2d) Run 4 (30 and 90g/m2 sprinkled)hardness (mg/l)

hardness (mg/l)c) Run 3 (20 and 80g/m2 sprinkled)control(3)20g/m280g/m2

control(4)30g/m290g/m2

Fig.11 Hardness in each microcosm (20days after)b) Run 2 (10 and 100g/m2 sprinkled)a) Run 1 (5 and 50g/m2 sprinkled)control(1)5g/m2control(2)50g/m220g/m2

100g/m2d) Run 4 (30 and 90g/m2 sprinkled)c) Run 3 (20 and 80g/m2 sprinkled)control(3)10g/m280g/m2

control(4)Fig.12 pH in each microcosm (20days after)

Sprinkled volume (g/m2)

Fig.13 Inhibition rate of COD in each microcosm
424

30g/m290g/m2

GEOMATE- Brisbane, Nov. 19-21, 2014

The inhibition rate decreased at sprinkled
quantity of 80g/m²-100g/m². As reason for this, thesprinkled shell fragments overwrapped each other,and this cause is the decrease of surface area.
The solubility product of shells in water can be
described as formula (2) of below [6],[7]. Therefore,
combination adsorption quantity of phosphorus
eluted from bottom mud and Ca2+ eluted from shellfragments was particle. As this result, themechanism of phosphorus adsorption in this study
was considered as mainly physical adsorption.

microcosm. It showed a high value so that there wasmuch sprinkled volume. As this result, it wasthought that Ca2+ that a component of the shells
eluted in water. When there is much quantity ofCO2, CaCO3 which is constituent of the shell
becomes easy to elute. In this study, quantity ofphotosynthesis by breeding controlledofphytoplankton accompany with sprinkle of shell
reduced. By this, DO value becomes low of about
5mg/L. Therefore, the water becomes the anaerobic
state, and it was thought that Ca eluted.

[Ca²⁺][CO₃²⁻] = (3.6×10⁻⁹)2 (mol/L)

pH in water(2)

Fig.12 shows the pH in each microcosm. pH is 89, and sudden change accompany with sprinkle ofshells was not observed. As this reason, CaCO3
eluted in water, it becomes formula (3) below.

N/P ratio in water
Fig.9 showed the N/P ratio in the microcosm.
N/P ratio in all sprinkled systems showed high value
than no-treated system. From this result, N/P ratio
increased by Ca2+ which adsorbed phosphorus and itchanged to the direction of the proper N/P ratio fromP excessive. However, N/P ratio is below 2.0 in all
systems. Therefore, it was state of excessive
phosphorus yet. The proper value of N/P ratio is
about 10. In Lake Inba and Lake Tega in Chiba
prefecture where well known as the mosteutrophicated lakes in Japan, N/P ratio of these lakes
are about 8.5 in summer [2]. However, N/P ratio in
Hasunuma Seaside Park Pond of previous years was
below 2.5[3], it was conditions of excessive
phosphorus. In addition, Anabeana spiroides that
dominant species of Aoko can breed if there is evenphosphorus by air nitrogen fixation ability.
Condition of phosphorus excess in Hasunuma
Seaside Park Pond is serious problem.
Relationshipbetweenphytoplankton
regional unused resources

CaCO3＋2H2O → Ca(OH)2＋H2CO3(3)

Ca (OH)2 is acidic. And H2CO3 is alkaline. By
this, water quality becomes neutral, and suddenchange of pH was not seen.
Relationship between COD inhibition rate andsprinkle volume
Fig.13 shows the inhibition rate of COD in the
microcosm. It showed a high value so that there wasmuch sprinkled in volume. Ca2+ eluted fromsprinkled shells, and it was combination withphosphorus which is nutrients, and breeding ofphytoplankton was controlled. Therefore, organic
matter in the water was reduced, COD inhibition rate
was higher.

and
CONCLUSIONSThis study focused Ca which constituent ofshells as the regional unused resources which wasmany scattering in Kujukurihama coast. It removed
phosphorus by physical absorption and Ca2+ thateluted from shells, and it aimed to improvementfrom eutrophication state of water. The results wereas follows.
1) With sprinkling the shell as regional unused
resources, phosphorus that eutrophication material
by chemical combination and physical adsorption ofshells was controlled.
2) With sprinkling the shell, N/P ratio changed to thedirection of the fair N/P ratio from P excessive.
However, N/P ratio was below 2.0 in all systems.
Therefore, it was state of excessive phosphorus yet.
3) COD inhibition rate was higher. Because Ca2+
eluted by sprinkled shells, and it was combination
with phosphorus which is nutrient salts, andbreeding of phytoplankton was controlled. Therefore,
organic matter in the water was reduced,

Fig.10 showed the daily variation ofphytoplankton in microcosm system. The dominant
species were Chlorella sp. in all systems. The
population of sprinkled systems was less than notreated system until fifth to tenth day. As reason for
this, phosphorus concentration decreased by Ca2+that constituent of shell adsorbed phosphorus. By
this, breeding of phytoplankton was controlled.
Tsunami flowed in Hasunuma Seaside Park Pond by
the Great East Japan Earthquake in March 2011, andbreeding of Anabeana spiroides as dominant speciesof Aoko were controlled. But, water quality
recovered to the state before the earthquake.
Therefore, Aoko may occur again. In this study,
sprinkled shells were effective to control
phytoplankton that formed Aoko.
Hardness in water
Fig.11 showed hardness value in the each425

GEOMATE- Brisbane, Nov. 19-21, 2014

4) Dominant species of phytoplankton was Chlorella
sp. in all system. The phytoplankton population ofsprinkled systems was less than no-treated system
until fifth to tenth day.

[3] Murakami K, Ishii T and Taki K, “Reeutrophication caused by bottom sediment sundrying in shallow and strongly enclosed parkpond”, Papers on Environmental Information
Sciences, Vol.23, 2009, pp435-440.
[4] Okuya T, “Marine Mollusca in Japan”, Tokai
University Press, 2001, 1173pp.
[5] Murakami K, Gomyo M, Agatsuma S, Amano Y
and Inoue-Kohama A, “Environmental conditionindex for estimation on eutrophic state of
enclosed aquifer ecosystem”, International
Journal of GEOMATE, Dec, 2013, Vol. 5, No. 2(Sl. No. 10), 2013, pp. 706-711.
[6] Driscoll CT, “Experimental watershed liming
study, Kluwer Academic Publishers, 1996,
248pp.
[7] Murakami K, Ishii T, Taki K and Matsushima H,“Waterplant purification in experimental
mesocosm system with long-term observation”,
in Proc. 2nd IWA-ASPIRE Conference andExhibition, 2007, CD-ROM.

ACKNOWLEDGEMENTS
Special thanks for the cooperation of Sanmu
Local Maintenance Center of Chiba Prefecture, andthis study was supported by Grant-in-Aid for
Scientific Research of JSPS (KAKENHI)(24651029) and New LRI of JCIA (2012PT4-02).
REFERENCES[1] Ministry of the Environment, “Annual Report on
the Environment in Japan”, 2013.
[2] Amano Y, Taki K, Murakami K, Ishii T and
Matsushima H, “Sediment remediation forecosystem in eutrophicated lakes”, The
Scientific World, Vol.2, 2002, pp.885-891.

426

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

THE VELOCITY REDUCTION EFFECT OF OBSTRUCTINGSTRUCTURES ON FLOOD WATER FLOWS DURING ROAD
CROSSING

1,2

Abdul Naser Abdul Ghani1, Ahmad Hilmy Abdul Hamid2 and Nursriafitah Kasnon3
Sch of Housing Building and Planning, USM, Malaysia; 3 Postgraduate Student, Sch of Housing Building
and Planning, USM, Malaysia.

ABSTRACTLaboratory experimental investigations were conducted to identify suitable shape and dimension of objects aswell as its capability to reduce flow velocity. The first stage of the study was to identify suitable shape and its
arrangement. In this test a scale of 1:20 was used in a flow table experiment. The water flow pattern was recorded
focusing on the distance and amplitude of the pattern as water flow pass the obstructing objects. The second stageof the investigation involved a hydraulic model investigation. In this investigation, the velocity reduction effect of
the selected objects shapes were studied. The results are classified into three distinguishable patterns of diffusion.
Two objects shapes and arrangements selected for use in the hydraulic model investigation indicated its capability
to reduce flow velocity satisfactorily consistent with the flow pattern in the preliminary findings.
Keywords: Flood, Road Crossing, Water Velocity, Velocity Attenuator

bridge piers and drains; policy and structural
measures for flood control and abatement; and flood
prediction. Figure 1 illustrates typical situation offloodwater during road crossing and how it affected
the vehicles.

INTRODUCTION
In a general flooding scenario, water levels risecausing areas neighboring water bodies and someroad stretch to be flooded. The primary effects offlooding include loss of life, damage to buildings andother structures such as roadways and canals. Flooded
roads and transport infrastructure make it difficult tomobilize aid to those affected or to provide
emergency health treatment [1].
The most regular and frequent type of disaster in
Malaysia is flooding. When large amount of rainfall
occurs, and the fact that it is more frequent these days,
especially over a short period of time - drain, rivers
and low lying areas will be filled with waters. With
the ever increasing and higher frequency of events,
the rainfall runoff will turn into floods or flash floods.
In its way to lower area and finally the sea, thefloodwater will cross urban, residential, industrial andagricultural area causing damages not only toproperties but also creating hindrance for escape andblocking emergency access to the affected areas.
Road infrastructure is the main access for escapeand emergency supplies. In flood events, some part oflow lying roads will be inundated creating blockage
for vehicle movement. Statistics clearly point out thehigh risk of driving in and around flooded roads andlow lying areas [2].
Intensive literature search indicated very few
previous works or information related to how
floodwater exert pressure on crossing vehicles orhuman and how the pressure can be attenuated. Mostof the previous and current works deals with floodrisk assessment and mapping; scour of channel, river,

Fig.1

Dangerous crossing [3]Yazici and Ozlay [4] proposed an evacuationroute modeling to deal with transportation route
planning during flooding - in other words, how to
avoid flooded area. Meyer and Weigel [5] suggested
an adaptive physical and management systems as an
approach to mitigate potential problems. Physicalapproach of adaptive systems was studied by Pisaniand Francesco [6] in the form of a moveable bridgethat can be adjusted during floods. Meanwhile, Cai
and Rahman [7] studied the used of road barriers aspart of an emergency evacuation systems. A
conceptual study of using Submerged Floating
Tunnel (SFT) was carried out by Grantz [8].
Drobot et al. [9] described the risk factors of427

GEOMATE- Brisbane, Nov. 19-21, 2014

driving into flooded road. They have also found outthat more than half of flood fatalities involved
vehicles driven into the floods. Cai et al. [1] andKouyi et al. [10] used computer simulation to predictflood level on potentially flooded road and the
distribution of discharges through cross roadintersections. Fairweather and Yeaman [11] studied
the influence of flooding on road pavement
deterioration and recommended further research tobetter predict pavement failure. The question now inmost flood event especially in Malaysia, at least, is
how to make sure access for escape and emergency
supplies can be safely provided.
Flowing floodwater exerts a pressure on an object
such as a car or person. The pressure will be higher
when the water depth increases. Friction between thetire and the slippery pavement will be reduced. Water,
sand, or mud tends to replace the frictional forces thatstabilize the vehicle.
In order to maintain the stability of a vehicle,
forces from flowing floodwater crossing roads must
be diffused to a minimum. This paper reports theresult of investigations on the possibility of usingroad furniture as velocity attenuating objects.

to obtained typical water flow pattern as a result of
the obstructing objects. This will help to ensure thatthe experiment can be conducted smoothly and willproduce high quality meaningful results.
Three pilot tests using the scale of 1:50, 1:30 and
1:20 were carried out. The dimensional arrangementof the road surface for water flow simulation is asshown in Fig. 2 below. The 1:20 scale was finallychosen as the experimental scale because it gave thebetter presentation of diffusing effects. Tapes were
carefully assembled on the water flow table for eachtest and the diffusing patterns were recorded by video
camera.
The road shoulder and road are marked by thecello tape. The road shoulders are marked to represent
1 meter dimension on site and the road are marked torepresent 3 meter on site. Figure 3 shows how thecello tape as diffuser model are fixed on the flow
water table.
As the shape, size and arrangement of the various
obstructing objects are expected to influence thediffusing capability of the systems, 18 such cases
were established for testing. The experiment wereconducted using the 18 pattern and size of diffusers
as shown in Fig. 3 and the result were obtained byobserving the outcome of the experiment by video.
The diffusing pattern varies with the shape,orientation and size. The maximum size of diffusing
object is 1 meter to scale of 1:20.

EXPERIMENTAL SETUP
Methodology used in this study were laboratory
experiments. The experiments were conducted in theenvironmental and infrastructure laboratory and data
were collected through observation and electronic
data logging systems consist of sensors.
Flow Pattern Experiment
The apparatus used in this experiment were waterflow table, water color, adjustable stand, camera, anddouble cello tape to represent the shape and size of
2D obstructing objects. The apparatus were set up as
shown in Fig. 2.

Fig. 3

Diffuser shapes and patterns.

Hydraulic Model Investigation

Fig. 2The experiment were set up as in Fig. 4 in which
two best object shape and pattern established fromflow table experiments were used to study thevelocity reduction effect in a 3D hydraulicenvironment.
Water were circulated into hydraulic flume asshown and sensors were placed before and after the
diffusing objects. The sensors were also placed at the
beginning, middle and end of the road cross section

Flow table set up.

Before doing the experiment for actual
observation, pilot tests were conducted. The purposeof the pilot test was to help in finding somepossibilities for the improvement possible hiccups
before the actual experiment is conducted. It was also428

GEOMATE- Brisbane, Nov. 19-21, 2014

considered high velocity flow.
Category 3 is described as the diffusion pattern of
the water is very little based on the smaller and shorter“wave like” flow created after the obstruction model.
In this case the flow became straight again at the
beginning of road crossing or no significant change inits flow pattern (straight flow). The amplitude of the
wave are also small.
Out of the 18 obstruction patterns, two patterns
can be considered as the pattern with the most capableof reducing water flow velocity. Figure 5 shows therecommended model that gave good effect on
reducing the velocity of water flow across the road.
They are two of the shape from category 1. This isbecause these object arrangement produced wave
diffusion pattern until the end of opposite roadshoulder and have high number of wave amplitude.
The longer distance of the wave diffusion, the more
velocity is being reduced. The higher number of wave
amplitude, the more velocity reduces.

to study the variation of flow after it passed throughthe diffusers. Velocity (V) were recorded andreadings were compared at every four locations of theroad scale. This experiment maintained the scale of
1:20 and it correspond to 3 m width two lane road (i.e.
road = 3m@15cm, road shoulder = 1m@5cm anddiffuser model = 1m@5cm).

Shape
and
Pattern 1

Fig. 4ShapeandPattern 2

Hydraulic model investigation.

RESULTS AND DISCUSSIONS
Fig. 5

Flow Pattern

Two best diffusing objects.

Hydraulic Performance

Based on the pilot tests carried out to identify
diffusion patterns, two major characteristics of the
diffusing water were identified and used as criteria forclassification. The first characteristic is the “wavelike” flow created by the obstructing object indicatedthat the water flow is being slowed down as it travels
longer from one point to another. This include howlong the wave like form remains while crossing theroad. In some case, the wave diminishes before it
reaches the other side of the road. In addition, there isalso the amplitude of the wave in which higher
amplitude indicating longer travel path.
The diffusing pattern can be divided into three
categories. The first category is described as the
diffusion pattern (wave) of the water flow after
passing through the diffuser model is continuous until
the road shoulder across the road. The amplitude of
the wave are maintain the same until the end of theroad shoulder.
The second category is described as the diffusion
pattern (wave) of the water flow after passing throughthe diffuser model continue until the middle of thesecond lane and become straight to the end of roadshoulder. The amplitude of wave remain similar until
it diminished into straight line again. Straight line
flow similar to the flow before the obstruction is

The hydraulic investigations focused on the watervelocity characteristics before and after passing
through the two selected diffuser objects that havebeen identified in the flow table experimentpreviously.
Table 1 details the characteristics of watervelocity as it travels before and passing the objects
until it reach the end of the road section. It can be seenthat both types of objects produce velocity diffusing
characteristics consistent with the earlier flow pattern
findings.
Table 1: Flow reduction EffectObjectType
1

Average Velocity (cm/s)
Before
1
2
3
5.12
3.98
4.96
6.31
(100%) (78%)(97%)(100%)
2
6.16
3.89
4.81
6.10
(100%) (63%)
(77%)
(97%)
Note: 1, 2, 3 are locations along road cross sections
as water travel across the model road.
The velocity reduction effect of object 1 can befurther illustrated by the following Fig. 6. It can be
429

GEOMATE- Brisbane, Nov. 19-21, 2014

seen that the amplitude of water flowing waveformare diminishing towards the end of the road section.
At point 1, i.e. just after the diffuser objects, velocity
was reduced to 78% of the water velocity frombefore. It regains speed up to 97% of the original flow
towards the end of the section and finally regain thefull velocity as before.

the objects can be placed as road furnitures in theform of planter boxes or corridor divider.

Fig. 8 Practical use of diffuser structures along
flood stretch.
CONCLUSION
Up to 37% reduction of flood velocity can beachieved by placing suitable objects along flooded
stretch. This study has identified a suitable object
shape and arrangement to reduce the floodwatervelocity when it crosses road section.
ACKNOWLEDGEMENTS

Fig. 6

Flow table
patternandcharacteristics from Object 1.

The authors would like to acknowledge financial
support for this study by research grant no.
203/PPBGN/6711257 provided by Universiti Sains
Malaysia/MOE Malaysia.

velocity

As for object 2, flow table pattern is similar toobject 1 but the diffusing effect goes beyond the endof road section as can be seen in Fig. 7 and Table 1.
At the end of the road section the velocity is at 97%of the original water speed. Also the maximum
diffusing effect of object 2 is 37% instead of 22% by
object 1. This characteristics indicate better diffusing
capability of object 2.

Fig. 7

REFERENCES[1] Hubo Cai, William Rasdorf, and Chris Tilley,“Approach to Determine Extent and Depth ofHighway Flooding”, Journal of Insfrastructure
System. Vol. 13, No. 2, June 2007, pp. 157167[2] National Hurricane Center, “Never drive
accrossafloodedroad.
Hurricane
Preparedness”. National Hurricane Center,USA.
[3] The Star Newspaper. May 17, 2011[4] Yazici A. and Ozlay, K.., “Evacuation
Network Modeling via Dynamic Traffic
Assignment with Probablistic Demand andCapacity Constraint”. Transportation Research
Record. No. 2196. pp 11-20.
[5] Meyer, M.D. and Weigel, B., “Climate Change
and Transportation Engineering: Preparing fora Sustainable Future. Journal of Transportation
Engineering”. Vol. 137, No. 6, June 2011, pp.
393-403

Velocity reduction capability of object 2.

Possible arrangement of the objects can beillustrated by the following Fig. 8. It can be seen that430

GEOMATE- Brisbane, Nov. 19-21, 2014[6] Pisani, M. A. and Ballio, F., “Feasibility
analysis of a movable bridge compensating forclearance deficit during floods”. Engineering
Structures 32 (2010). ASCE. Pages
3338_3343..
[7] Cai, H. and Asadur Rahman, “A Method to
Develop and Optimize the Placement of Road
Barriers in Emergency Evacuation for
University Campuses”. Construction Research
Congress 2010. ASCE. Pages 409-419..
[8] Grantz, W.C., “Conceptual Study for a deep
Water, Long Span, Submerged Floating
Tunnel(SFT)
Crossing”.
ProcediaEngineering 4(2010). Pages 61-70.

Environmental Hazards, Volume 7, Issue 3,
2007, Pages 227-234.
[10] Kouyi, G.L., N. Rivie`re, V. Vidalat, A.
Becquet, B. Chocat and V. Guinot, “Urban
flooding: one-dimensional modelling of the
distribution of the discharges through crossroad intersections accounting for energy
losses”. Water Science and Technology. IWA
Publishing, 2010, 61(8): pp. 2021-2026.
[11]Fairweather, H. and Yeaman, J. (2014). “A
study of the parameters affecting theperformance of roads under extreme rainfall
event”. Int. J. of GEOMATE, Sept., 2014, Vol.
7, No. 1 (Sl. No. 13), pp.955-960[9] Drobot, S.D., Benight C. and Gruntfest, E.C.,“Risk factors for driving into flooded roads”.

431

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

ROLE OF A RETAINING WALL CONSTRUCTED OF NATURALSTONES IN PLANT BIODIVERSITY
Taizo Uchida1,2, Masaaki Furuno3, Takashi Minami1, Sampei Yamashita1,2, Tadashi Uchiyama2, Teruo
Arase4 and Daisuke Hayasaka5
1
Faculty of Engineering, Kyushu Sangyo University, Japan; 2Center for Landscape Research, Kyushu
Sangyo University, Japan; 3Graduate School of Engineering, Kyushu Sangyo University, Japan; 4Faculty ofAgriculture, Shinshu University, Japan; 5Faculty of Agriculture, Kinki University, Japan

ABSTRACTThe objective of this research is to evaluate the importance of vegetation of retaining walls made of naturalstones (i.e., masonry revetment) in plant biodiversity. In this paper, plant compositions and the characteristics ofmasonry revetments were surveyed in terraced fields in Toho Village, southern Japan. In total, 43 families and88 species were recorded in the spaces of the masonry revetments. Of these 88 species, 68 (77.3%) were
herbaceous, excluding 13 (14.8%) ferns, and 7 (8.0%) species were woody plants. Native species accounted for
69 (78.4%) of the 88 species. Furthermore, numerous species not found in the horizontal environments aroundthe terraced fields were also seen in the spaces of the masonry revetments. From these results, the authors
consider that masonry revetments provide a habitat for plants and therefore contribute toward the conservation ofplant biodiversity on a local scale.
Keywords: Biodiversity, Revetment, Stone wall, Terraced field, Vegetation.

into their surroundings, have recently been highly
recommended in Japan [9].
In retaining walls using natural stones (hereafterreferred to as "masonry revetments"), many narrow
spaces appear between stones, and some plants,
animals, and insects frequently colonize the spaces(Fig. 1). Among the colonizers, plants are generally
considered as the major cause of collapse ofmasonry revetments and so become a target forremoval.
As an alternative, the objective of this paper is toevaluate the importance of masonry revetment
vegetation in plant biodiversity. In this study,

INTRODUCTION
Infrastructure elements such as roads, ports,
bridges, power stations, and so forth, arefundamental structures and services that arenecessary for supporting today's society. However, alarge number of cut slopes and embankments, whichaccompany the introduction of infrastructure, haveespecially emerged in Japan, because forests accountfor the majority of the total land area of Japan(approx. 69%, excluding land submerged in water)[4]. Therefore, to prevent failure and erosion of cut
slopes and embankments, revetment techniques havebeen rapidly developed and introduced. Some
examples of these techniques are mortar sprayings,
frame constructions, and precast segments including
concrete blocks.
Since these structures often do not harmonize
with their surroundings, a bio-engineering technique(planting and/or seeding for slope protection) has
been actively applied over the last several decades,
especially in Japan [22], to complement or enhance
the peripheral scenery. The bio-engineering
technique is also expected to ease global warming
and reduce costs in other countries [8]. However, ina few cases, application of a bio-engineering
technique is not suitable for protecting some slopes,
e.g., those in extremely soft ground or on very steep
land. At these places, retaining walls using lumber,natural stones and some other revetment material
with less brightness and saturation, which can blend

Fig. 1 Masonry revetment and some plants colonizing the spaces between stones.
432

GEOMATE- Brisbane, Nov. 19-21, 2014

therefore, plant compositions and the characteristics
of masonry revetments were surveyed in a cluster ofterraced fields. We examined a large number ofmasonry revetments under various different land
uses in the same area.

revetments with that of the surroundings, surveyingof the vegetation was also conducted in 54
horizontal environments around the paddy fields,such as walkways between paddy fields, abandoned
fields, and parking lots.

MATERIALS AND METHODS

Data Analysis

Study Site

The Braun-Blanquet cover-abundance scale (r, +,I, II, III, IV, and V) was transformed as follows: r
and +, 0.1%; I, 5.0%; II, 17.5%; III, 37.5%; IV,
62.5%, and V, 87.5%. Then, in Eq. (1), the summed
dominance ratio (SDR) of each species [15] wascalculated:

The cluster of terraced fields used in thisresearch is located at the Take section in Toho
Village in southern Japan. The terraced fields, which
are at an altitude of 280 to 420 m [21], aresurrounded by artificial forests that are mostly
Cryptomeria japonica and Chamaecyparis obtuse.
The terraced fields are mainly used for rise although
they have quickly changed into abandoned fields orfields for vegetables, grains, or housing in recent
years. Nearly all of the slopes of the terraced fields
are protected by masonry revetments with asoutheastern aspect [21]. The dimensions of therevetments are approximately as follows: height 1 to
10 m, width 10 to 25 m, and inclination angle 70° to80°. Also, the masonry revetments are the dry type[10], and on average they have 22 stones and aporosity of 7.5% per square meter.
According to data of the Automated Meteorological Data Acquisition System (AMEDAS) from2004 to 2013, this surveyed area lies in the warmtemperature zone: the values of Kira’s Warmth
Index [12] range from 125.8 to 138.6 and the annual
precipitation is 1,265 to 2,499 mm.

where F’ and C’ are the ratio of frequency andcover of each species to the numbers of the mostabundant species, respectively.
To find out whether the characteristics ofvegetation in the spaces of the masonry revetments
were different by land-use type of the terraced fields,
we conducted a Shapiro-Wilk test under the null
hypothesis that the vegetation characteristics of themasonry revetments were equivalent across all landuse types [3], [23]. The vegetation characteristics
employed were the following: total number of
species, average number of species, ShannonWiener’s diversity index (H’), and percentages ofnative, herbaceous, and ferny species.

Species Composition and Characteristics

RESULTS

Surveying of vegetation in the spaces between
stones of masonry revetments was conducted from
mid-September to early October, 2013. We
examined 55 masonry revetments at random, using asurvey quadrat located on vertical surface of therevetment at a height of 130 cm. The size of aquadrat was 100 cm long and 100 cm wide. The
species composing the vegetation were recorded
according to the methodology of the Braun-Blanquet
cover-abundance scale [2]. In addition, the land-use
type of each masonry revetment was classified as apaddy field, a dry field, an abandoned field, or"others", which included housing, parking lots, etc.
The plant nomenclature used in this paper
followed that of Miyawaki et al. (1994), Baba
(1999), and Shimizu (2003). All the recorded species
were categorized by life form (dormancy form,
disseminule form, radicoid form, and growth form).
The life forms were based on descriptions by
Raunkiaer (1934) and Numata (1990). The invasive
status (native or non-native) was also categorizedbased on published literature [1], [13], [18].
To compare the vegetation of the masonry

In total, 43 families and 88 species were obtainedin this survey. Native species accounted for 69(78.4%) of the 88 species observed in the spaces ofthe masonry revetments surveyed. Moreover, of the
88 species, 68 (77.3%) species were herbaceous,
excluding 13 (14.8%) ferns, and 7 (8.0%) species
were woody plants. Of the 68 herbaceous species, 37(54.4%) were ephemeral (annual and biennial) plants
and 31 (45.6%) were perennials. Of the 43 families
obtained in this survey, the most abundant families
were Asteraceae (19/88 species) followed by
Poaceae (9/88 species) and Leguminosae (4/88
species). Appendix 1 lists the plant compositions,land-use types, and life forms.
The species common to all land-use types (7/88
species) were Acalypha australis, Boehmeria
nipononivea, Equisetum arvence, Pteris × sefuricola,
Stenactis annuus, Trachelospermum asiaticum, andYoungia japonica. Conversely, species that emerged
only in one specific land-use type were also
observed. In only paddy fields, 15 species wereobserved, e.g., Eclipta alba, Houttuynia cordata,

SDR = (F’ + C’)/2

433

(1)

GEOMATE- Brisbane, Nov. 19-21, 2014

IxerisTable 1 Vegetation characteristics of masonry revetment in each land-use type.
Vegetation characteristics
Land-use types

Number ofsurvey plots

Total numberof species

Average numberof species

Shannon-Wiener's
diversity index (H ')Nativespecies,%

Herbaceous †Fernyspecies, % species, %Paddy fields

29

55

6.2

5.260

83.6

72.7

21.8

Dry fields

08

35

6.6

4.917

82.9

65.7

25.7

Abandoned fields

14

53

8.4

5.395

81.1

75.5

15.1

Others

04

22

8.3

4.166

72.7

77.3

18.2

P -value-

0.405ns

0.164ns0.404ns

0.103ns

0.500ns

0.954ns†

Except for ferns. Woody species, %: 100 - [herbaceous species, %] - [ferny species, %]. ns P > 0.05: not1significant using Shapiro-Wilk test.

DISCUSSION

Ixeris stolonifera, Lobelia chinensis, Osmunda
japonica, and Vigna angularis. In only dry fields, 6
species were observed: Akebia trifoliata, Asplenium
trichomanes, Chenopodium album, Gamochaeta
coarctata, Lilium formosanum, and Sonchus
oleraceus. In only abandoned fields, 16 species wereobserved, e.g., Cosmos sulphureus, Cryptomeria
japonica,
Miscanthus
sinensis,
Persicaria
lapathifolia,
Ranunculus
silerifolius,
andRhynchosia volubilis. In only the other fields forhousing, parking lots, etc., 6 species were observed:
Arthraxon hispidus, Cosmos bipinnatus, Dioscorea
polystachya, Echinacea purpurea, Lampranthus
spectabilis, and Trisetum bifidum.
Meanwhile, a total of 40 families containing 101
species were observed in the horizontal
environments around the terraced fields. It should be
especially noted that numerous species not recordedin the horizontal environments were obtained fromvegetation of the masonry revetments (48/88
species; 54.5%).
From the species found in the masonry
revetments only, many perennials (H and Ch;
39.6%) were obtained, as well as ephemeral plants(Th and Th(w); 35.4%). The dominant dispersal
modes were anemochory (D1; 43.8%) or barochory(D4; 39.6%). In the radicoid and growth forms, themajority of each form was "R5 (56.3%)" and "e(39.6%)", respectively. This implies that vegetationof the masonry revetments was spread primarily byseed.
On the other hand, no significant differenceswere found in the vegetation characteristics of themasonry revetments across the land-use types of theterraced fields (P > 0.05) (Table 1).

Numerous studies on vegetation colonizing hardsurfaces such as pavement, rubble, roofs, ruins,building walls, and stone walls (masonry
revetments) have been conducted, and it is widely
understood that these surfaces are sufficiently able tosupport various taxa [5], [10], [11], [19], [20].
However, those studies are overwhelmingly
concentrated in Europe [10], whereas information
originating in other countries and regions regarding
vegetation of hard surfaces, including masonry
revetments, is lacking despite the importance ofplant habitats.
In this study, 43 families and 88 species
including 69 (78.4%) natives were observed between
stones of the masonry revetments (Appendix 1). Our
results are not surprising, because even hard surfaces
such as cracks in pavement and mortared walls
provide good opportunities for plants to colonize[10].
In environments with hard surfaces, ephemeralannuals or short-lived taxa (due to disturbance byhuman activities) tend to be dominant instead of
perennials including woody plants [5], [7], [11].
However, many perennial herbs (45.6%; excluding
ferns) and even woody plants (8.0%) were obtainedin this survey, as well as ephemeral (annual andbiennial) plants. Additionally, a large number of
species not observed in the horizontal environments
around the terraced fields were recorded.
On a local scale, therefore, we consider that themasonry revetments play an important ecologicalrole in providing habitat for plants and in so doing,
contribute toward the conservation of plantbiodiversity. Incidentally, of the plants colonizing
the masonry revetments, the main ecological types434

GEOMATE- Brisbane, Nov. 19-21, 2014

Moisture availability is the most importantenvironmental factor for the development of hardsurface vegetation [10], [16], [20]. That is,differences of moisture conditions in the masonry
revetments, which accompany land-use change,
would lead to varied plant composition. While
infrastructure elements have long been mentioned asa force to reduce vegetation coverage, the masonry
revetments installed in various locations withdifferent moisture conditions could lead to plantbiodiversity on a local scale.
In general, plants are considered to be the major
cause of collapse of masonry revetments. Nevertheless, it is evident that masonry revetments play asignificant role, not only in protecting slopes andembankments, but also in maintaining or
ameliorating plant biodiversity on a local scale.
Therefore, it would be a challenge to be tackled in
the future to overcome or moderate a trade-off
between plant biodiversity and maintaining masonry
revetments.

were species, mainly Asteraceae and Poaceae,
propagating by seed with gravity dispersal(barochory), or wind dispersal (anemochory)mechanisms. These observations are in total
agreement with previous reports on hard surface
vegetation [6], [7], [19].
On the other hand, vegetation characteristics
such as the number of species, the diversity index(H’), and the percentage of native species in themasonry revetments were not affected by the landuse types of terraced fields (Table 1). However, theplant composition of each land-use type was highly
distinctive. Common species among land-use types
could be defined as typical species in the masonry
revetment vegetation, for example, Acalypha
australis, Equisetum arvence, Trachelospermum
asiaticum, and Youngia japonica. Conversely, thespecies observed only in a certain land-use type
would be regarded as a peculiar plant, e.g.,Lampranthus spectabilis, Lilium formosanum,
Oenanthe javanica, and Ranunculus silerifolius, thatis heavily dependent on its environment.

Appendix 1 Species recorded in this survey, and they were listed according to plant composition of each landuse type.
Land-use types
Species

FamilyLife form

Paddy fields

Dry fields

Abandoned fields

Others

Dormancy

Disseminule

Radicoid

GrowthOccurrence
frequency (%)(n =29)(n =8)(n =14)(n =4)

Acalypha australis †, γ

Euphorbiaceae

II

II

+

III

Th

R5

D3

e

Boehmeria nipononivea †, §Urticaceae

III

III

III

II

Ch

R3

D4

e

41.8

Equisetum arvence ‡Equisetaceae

I

II

I

II

G

R1

D1

e

16.4

Pteris × sefuricola ‡Pteridaceae

II

III

I

II

H

R3

D1

e

30.9

Stenactis annuus †, #, γAsteraceae

III

II

III

I

Th(w)

R5

D1

pr

49.1

Trachelospermum asiaticum ω

Apocynaceae

II

V

IV

V

Ch

R5

D1

l

25.5

Youngia japonica †, γ

Asteraceae

II

I

II

I

Th(w)

R5

D1

ps

25.5

Echinochloa crusgalli †, γ

Poaceae

II

Th

R5

D4

t

3.6

Eclipta alba †, #, γAsteraceae

+

Th

R5

D1

e

7.3

Elatostema laetevirens †, §Urticaceae

II

H

R3

D4

e

1.8

Eleusine indica †, γ

Poaceae

+

Th

R5

D4

t

3.6

Houttuynia cordata †, §Saururaceae

I

G

R1

D4

e

3.6

Ixeris stolonifera †, §Asteraceae

r

H

R4

D1

p

1.8

Lobelia chinensis †, §Campanulaceae

r

H

R3

D4

p

1.8

Mallotus japonicus ωEuphorbiaceae

r

MM

R5

D2

e

1.8

Oenanthe javanica †, §Umbelliferae

II

H

R4

D4

e

1.8

Osmunda japonica ‡Osmundaceae

I

G

R3

D1

t

5.5

Paederia scandens †, §Rubiaceae

+

Ch

R3

D4

l

3.6

Phyllanthus urinaria †, γ

Euphorbiaceae

r

Th

R5

D3

e

1.8

Sonchus asper †, #, γAsteraceae

+

Th(w)

R5

D1

pr

1.8

Vigna angularis †, γ

Leguminosae

III

Th

R5

D3

l

1.8

Viola verecunda †, §Violaceae

+

H

R3

D3

b

5.5

Akebia trifoliata ωLardizabalaceae

I

M

R3

D2

l

1.8

Asplenium trichomanes ‡Aspleniaceae

I

E

R3

D1

t

1.8

Chenopodium album †, γ

Chenopodiaceae

I

Th

R5

D4

e

1.8

Gamochaeta coarctata †, #, γAsteraceae

I

H

R5

D1

b

1.8

Lilium formosanum †, #, §Liliaceae

I

H

R5

D3

e

1.8

Sonchus oleraceus †, γ

Asteraceae

II

Th(w)

R5

D1

pr

1.8

Amphicarpaea edgeworthii †, γ

Leguminosae

Th

R5

D3

l

3.6

I

435

16.4

GEOMATE- Brisbane, Nov. 19-21, 2014

Appendix 1 Continued.
Land-use types

Life form

Paddy fields

Dry fields

Abandoned fields

Others(n =29)(n =8)(n =14)(n =4)

Species

FamilyBothriospermum zeylanicum †, γ

Boraginaceae+

Th

Capillipedium parviflorum †, §Poaceae+Ch

Conyza canadensis †, #, γAsteraceae

I

Th(w)

Cosmos sulphureus †, #, γAsteraceae+

Th

Cryptomeria japonica ω

Taxodiaceae+

Euchiton japonicus †, §Asteraceae

Ixeris japonica †, §Asteraceae

Miscanthus sinensis †, §Dormancy

Disseminule

Occurrence
frequency (%)

Radicoid

Growth

R5

D4

b

1.8

R3

D1

t

1.8

R5

D1

pr

3.6

R5

D4

e

1.8

MM

R5

D1

e

1.8

+

H

R5

D1

b

1.8

+

H

R3

D1

ps

1.8

Poaceae

I

Ch

R3

D1

t

1.8

Persicaria lapathifolia †, γ

Polygonaceae

+

Th

R5

D4

e

1.8

Ranunculus silerifolius †, §Ranunculaceae

+

Th(w)

R5

D4

e

1.8

Rhynchosia volubilis †, §Leguminosae

+

H

R5

D3

l

1.8

Sagina japonica †, γ

Caryophyllaceae

I

Th

R5

D4

b

1.8

Setaria faberi †, γ

Poaceae

+

Th

R5

D4

t

1.8

Stellaria aquatica †, γ

Caryophyllaceae

II

Th(w)

R5

D4

b

5.5

Toxicodendron radicans ω

Anacardiaceae

I

Arthraxon hispidus †, γ

Poaceae

MM

R5

D4

l

1.8

I

Th

R5

D4

t

1.8

Cosmos bipinnatus †, #, γAsteraceae

I

Th

R5

D4

e

1.8

Dioscorea polystachya †, #, §Dioscoreaceae

I

G

R5

D1

l

1.8

Echinacea purpurea †, #, §Asteraceae

I

Ch

R5

D4

e

1.8

Lampranthus spectabilis †, #, §Aizoaceae

V

Ch

R5

D4

p

3.6
3.6

Trisetum bifidum †, §Poaceae

Lactuca indica †, γ

AsteraceaerIIAchyranthes fauriei †, §Amaranthaceae

II

Artemisia princeps †, §Asteraceae

+

II

+

Ch

Asplenium sarelii ‡Aspleniaceae

I

III

II

E

Athyrium niponicum ‡Woodsiaceae

III

III

H

Athyrium vidalii ‡Woodsiaceae

II

I

I

H

Athyrium wardii ‡Woodsiaceae

+

II

I

Boehmeria spicata ω

Urticaceae

Camellia sinensis ω, #TheaceaeII

Chamaele decumbens †, §Umbelliferaer

Chamaesyce maculata †, #, γEuphorbiaceae+

Clinopodium gracile †, §LabiataerCommelina communis †, γ

Commelinaceae

II

Corydalis racemosa †, γ

Papaveraceae

r

I

I
I

II
I

I

III

H

R5

D4

e

Th

R5

D1

pr

7.3

H

R3

D2

e

14.5

R2

D4

e

5.5

R3

D1

t

21.8

R2

D1

e

23.6

R3

D1

t

12.7

H

R2

D1

e

12.7
3.6

I

Ch

R3

D4

e

IV

MM

R5

D4

e

5.5

II

G

R5

D4

ps

10.9
5.5

Th

R5

D3

b

II

I

H

R5

D4

b

9.1

I

II

Th

R5

D4

b

14.5

II

II

Th(w)

R5

D4

b

9.1

+

Th

R5

D1

pr

3.6

Th

R5

D4

t

3.6

Crassocephalum crepidioides †, #, γ Asteraceae+

Cyperus iria †, γ

Cyperaceaer

I

Deparia conilii ‡Woodsiaceae

r

II

I

H

R2

D1

e

7.3

Digitaria ciliaris †, γ

Poaceae

III

II

II

Th

R4

D4

t

30.9

Dunbaria villosa †, §Leguminosae

I

I

Fatoua villosa †, γ

Moraceaer

Galinsoga quadriradiata †, #, γAsteraceae

I

Gamochaeta pensylvanica †, #, γAsteraceae

Geranium nepalense †, §Geraniaceae+

Glechoma hederacea †, §Labiatae+

Hydrocotyle sibthorpioides †, §UmbelliferaerImpatiens balsamina †, #, γBalsaminaceae

II

Justicia procumbens †, γ

Acanthaceae

I

Lemmaphyllum microphyllum ‡Polypodiaceae

II

Lepisorus thunbergianus ‡Polypodiaceae

I

Lygodium japonicum ‡Schizaeaceae

I

Mollugo stricta †, γ

MolluginaceaerOxalis corniculata †, §Oxalidaceae

I

Oxalis dillenii †, #, §Oxalidaceae

II

II

Setaria viridis †, γ

PoaceaeII

II

Stellaria neglecta †, γ

CaryophyllaceaerTaraxacum officinale †, #, §Asteraceae

I

Thelypteris decursivepinnata ‡Thelypteridaceae

Trichosanthes cucumeroides †, §Cucurbitaceae

I

H

R3

D3

l

5.5

Th

R5

D3

e

3.6

I

II

Th

R5

D4

e

20.0

I

II

Th(w)

R5

D1

b

7.3

I

+

H

R5

D3

b

7.3

I

H

R4

D4

p

5.5

Ch

R4

D4

p

3.6

I

Th

R4

D3

b

5.5

III

Th

R5

D3

e

21.8

E

R2

D1

e

5.5

E

R3

D1

e

10.9
9.1

I
I

II
I
II

H

R2

D1

l

Th

R5

D4

b

3.6

Ch

R4

D3

p

14.5

Ch

R4

D3

p

7.3

Th

R5

D4

t

10.9

II

Th(w)

R4

D4

b

5.5

+

H

R3

D1

r

7.3

II

+

H

R3

D1

t

5.5

+

II

G

R5

D4

l

12.7

I
I

I
I

I

In land-use types Roman numerals and other symbols for each species indicate SDR classes, defined as follows:r, under 5%; +, under 10%; I, under 20%; II, under 40%; III, under 60%; IV, under 80%, and V, above 80%. †,herbaceous species (excluding ferns); ‡, ferny species; ω, woody species; #, non-native species; γ, ephemeral
herbs (annual and biennial plants), and §, perennial herbs. Highlight: species observed in masonry revetment
only.
436

GEOMATE- Brisbane, Nov. 19-21, 2014[10] Jeremy L., 2011. Vegetation of urban hardsurface. In: Niemelä J. (ed.), Urban ecology,
Oxford, New York. pp. 93-102.
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walls. Physical Geography 29, 351-373.
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Kyokai, Tokyo. 664 pp. In Japanese[15] Numata M. and Yoda K., 1957. The community
structure and succession of artificial grasslands(1). J. Jap. Soc. Herb. Crops Grassl. Farm. 3, 411. In Japanese[16] Payne R.M., 1989. The flora of walls in the
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History 133, 231-242.
[17] Raunkiaer C., 1934. Life forms of plants andplant geography. Oxford University Press,
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ACKNOWLEDGEMENTS
We are deeply grateful to K. Kondo and S.
Imado, Environ. Sci. Appl. Ecol. Lab., Kyushu
Sangyo University, for their assistance with the fieldwork. This research was supported by the Strategic
Support for Research Project by Private University(No. S1203007) from the Ministry of Education,
Culture, Sports, Science and Technology in Japan.
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Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

INFLUENCE OF EXOTIC PASTURE GRASSES AND FERTILIZATIONON THE VEGETATION RECOVERY OF LANDSLIDE SLOPESFORMED BY TYPHOON 9512 IN MIKURA-JIMA ISLAND, JAPANTeruo Arase and Tetsuo Okano
Faculty of Agriculture, Shinshu University, Japan

ABSTRACT
Typhoon 9512 hit Mikura-jima Island, Izu Islands, Japan in 1995, producing many landslide slopes. Torino-o
No. 3 landslide slope was planted with seedlings of native species (Alnus sieboldiana and Miscanthus
condensatus) as part of vegetation recovery efforts and was subsequently seeded by helicopter in 2002 withexotic pasture grasses (Agrostis stolonifera, Festuca sp., and Lespedeza cuneata). To elucidate the impact ofseeded exotic grasses in vegetation recovery, we designated seven plots in 2004, and surveyed vegetation every
summer until 2013: four fertilized plots (fowl manure applied at 0.2 g/m2) and three non-fertilized plots. The
planted native species seedlings grew steadily irrespective of fertilization, but with self-thinning in A.
sieboldiana and a peak in maximum plant height in M. condensatus in 2008. Exotic pasture grasses decreased
gradually and almost disappeared in 2013. Fertilizing temporarily enhanced the growth of M. condensatus andFestuca sp. but seemed to induce species competition. The growth forms of the invading species in herbaceous
layer were different between the plots, which confirmed the enhanced competition by fertilizing.
Keywords: Exotic pasture grasses, Fertilization, Landslide slope, Mikura-jima Island, Vegetation recovery
The thin layer of volcanic ash soil was washed away,
and the bedrock was exposed on the landslide slopes.
After the typhoon, vegetation recovery efforts were
begun with projects to build fascines (using fallentrees) to retain the soil and to transplant localitycertified seedlings of native species (Alnus
sieboldiana Matsum. and Miscanthus condensatus
Hack.) [9].

INTRODUCTION
In an insular ecosystem, such as an island,
habitat for wildlife can easily be lost due to disasteror development. Island ecosystems are generally richin endemic species but tend to be homogeneous in
habitat, making them vulnerable to invasive species[10], [13]. Thus, insular ecosystems are considered
to be prone to extinction events. However, it is moredifficult to confirm the extinction of plant species
than animal species because plants might survive
unobserved in a very limited area of the original
habitat [13].
Mikura-jima Island (area, 20.58 km2; location, ca.
180 km south of Tokyo) is an isolated island on the
Izu Islands in the Pacific Ocean off the main islandof Japan, where volcanic activity ceased ca. 7,000
years ago, leaving a long period for the developmentof the terrestrial ecosystem. It is covered with flora
typical of that of the Izu Islands, has cliffs facing thesea with a large range in elevation (the highest peakis 850.8 m), and has many streams with abundant
water [6], [12]. Mikura-jima Island was spared thedeforestation for tourism or industry that took placeon the other of the Izu Islands.
In September 1995, Typhoon 9512 hit Mikurajima Island (Fig. 1). It produced many landslide
slopes among the old-growth forests of evergreen
broad-leaved trees (e.g., Castanopsis sieboldii(Makino) Hatusima ex Yamazaki et Mashiba,
Machilus thunbergii Sieb. et Zucc., Eurya japonica
Thunb. and Buxus microphylla Sieb. et Zucc.) [1].

Fig. 1 Path of typhoon 9512. Open circles on thepath indicate its location at 9:00 on each day.
Figure based on original graph and data [7].
438GEOMATE- Brisbane, Nov. 19-21, 2014

cannot rapidly achieve even ground surface cover.
For future disaster prevention, it is desirable totransition from exotic pasture grasses to native
species. However, exotic pasture grasses have beenreported to prevent vegetation recovery: they
prevent the establishment of trees [1], [4], change
the direction of early succession [15], and may
dominate the vegetation for long periods, e.g., 20
years [5], [8], [11], [15].
In the present study, we monitored the vegetation
recovery on Trino-o No. 3 landslide slope of
Mikura-jima Island for 10 years, from 2004 to 2013.
In both non-fertilized and fertilized plots(fertilization was implemented in 2004 to support
the growth of planted native seedlings which had
inferior growth), we investigated the growth of
locality-certified seedlings of native species, exotic
pasture grasses and vegetation including newly
invading trees and herbs.
Fig. 2 Locations of landslide slopes formed bytyphoon 9512 on Mikura-jima Island.

METHODS

We focus on Trino-o No. 3 landslide slope,which is located on the northwest side of the island(Fig. 2). Vegetation recovery activities were carriedout on this slope as described above. Exotic pasturegrasses were seeded by helicopter after the localitycertified seedlings had become established;subsequently, the vegetation of the slope transitioned
to a grassland community dominated by exotic
pasture grasses in the next year [1], [9]. Then, in
2004, study plots were established, and one
treatment group was fertilized once with fowl
manure at 0.2 g/m2. In Japan, exotic pasture grasses
have come to be used frequently for revegetation
because of their rapid and homogeneous germinationand growth. Recently, ecological conservation
strategies call for the use of native species, except inurban areas. Therefore, the unintended introductionof non-native pasture grasses to Trio-o No. 3
landslide slope provides a valuable study site for
examining the competition between native and nonnative grass species.
Vegetation recovery in insolated ecosystems,
such as on an island, should be carried out in waysthat restore and do not disrupt the endemic
ecosystem. The grassland vegetation established on
Trino-o No. 3 landslide slope is undesirable, but it isnoteworthy in the sense that it is difficult to design
an exotic grassland in an insular ecosystem, even in
the context of academic research. If we monitor the
succession and the growth of each plant species, wewill be able to obtain a rare data set for examining
the effect of seeding exotic pasture grasses onlandslide slopes on islands as a part of vegetation
recovery efforts.
The strategy of using native plant species
remains unproven: since their germination andgrowth are inferior to exotic pasture grasses, they

Site and Monitoring Plots
Site and Monitoring Plots
Mikura-jima Island is located ca. 180 km southof Tokyo in the Izu Islands. Over the past 5 years,
the average annual precipitation was 2,910 mm andthe average temperature was 17.9 °C. Trino-o No. 3
landslide slope is located at elevations ranging from
Table 1 History of vegetation restoration activities
on Torino-o No. 3 landslide slope
Year
1995

1996
2000

2002

2003
2004

439

Work done
Landslides and loss of vegetation causedby typhoon 9512
precipitation: 648.5 mm
maximum wind speed: 67.8 m/s
Start of transplanting trees (on the lower
parts of the slope)Installation of founding fascines (1,100m2, 19 steps)
Transplantation of 800 A. sieboldiana
seedlings (average of one seedling per
square meter)
Transplantation of 1,750 Miscanthus
condensatus seedlings(average of 1.5 seedlings per square
meter)
Unexpected seeding of exotic pasturegrasses by helicopter in fall
Shift in vegetation to a grassland
dominated by exotic pasture grasses
Fertilization by hand to boost growth ofplanted native seedlings(fowl manure applied at 0.2 g/m2)
Establishment of monitoring plots

GEOMATE- Brisbane, Nov. 19-21, 2014

500 to 550 m above sea level with average slope of
27° and faces north. The bedrock around the site isandesite and basalt. Surrounding intact forest isdominated by evergreen broad-leaved trees, mainly
Castanopsis sieboldii.
The vegetation recovery activities conducted at
this site are listed in Table 1. The seeding of exotic
pasture grasses occurred in 2002, and the amount ofseeds and grass species is unknown; based on
subsequent surveys, the species included bent grass(Agrostis stolonifera L.), a fescue (Festuca sp.) anda sericea lespedeza (Lespedeza cuneata (Dum.
Cours.) G. Don).
In August 2004, seven plots of ca. 3 m × 2 m(5.5-7.4 m2) were established. To elucidate the effectof fertilization, we set three non-fertilized plots (C1
to C3) and four fertilized plots (F1 to F4). In
subsequent years, growth and vegetation species
were investigated in summer (early August).

For the herbaceous layer, plant height was measured
for M. condensatus, and the coverage percentage
was determined for the exotic pasture grasses.
Vegetation survey
For the herbaceous layer, two layers were
established based on height. The first herbaceous
layer, taller than 1 m, was omitted from the survey
because it comprised only M. condensatus growing
along the fascines. For the second herbaceous layer,
comprising exotic pasture grasses and invading
native species, the coverage percentage of eachspecies was determined.
Since several growth forms were observed in thesecond herbaceous layer, we classified the growthforms into four categories: b (branching form), e(erect form), l (climbing form) and t (tussocks).
Each species was classified into one of these growthforms, and the coverage percentage for each growthform was summed.
Coverage percentage data were arcsine
transformed prior to statistical analysis since they
are considered to have a binomial distribution.
Statistical operations were conducted by calculations
in a spreadsheet (Microsoft Office Excel 2003).

Growth of transplanted species and exotic
pasture grasses
Among the tree layer, transplanted trees of A.
sieboldiana and other species were measured forplant height (H) and diameter at the base (D0), andthe parameter D02H was calculated as an estimate ofaboveground biomass. Since a phenomenon like
self-thinning was observed in A. sieboldiana, weestimated the regression expression as follows:
1/x＝a +by

RESULTS
Growth of trees
Figure 3 shows the growth of A. sieboldiana andother invading trees over a period 10 years. In eachof non-fertilized and fertilized plots, a phenomenonof self-thinning was confirmed in A. sieboldiana: themean plant density decreased yearly, while
individual D02H increased and tended to reach a(1)

where x is the mean plant density of A. sieboldiana,
y is the mean individual D02H, and a and b are
constants [16]. Data of other invading tree species
were analyzed in the same way.

Fig. 3 Changes in the density and the average D02H per individual of Alnus sieboldiana in Torino-o No.3
landslide slope. The solid dots and solid line indicate non-fertilized plots, and the open dots and broken
line indicate fertilized plots.
440

GEOMATE- Brisbane, Nov. 19-21, 2014individual D02H tended to be smaller in fertilized
plots, and significant differences were detected in2011 and 2012 for mean plant density and in 2013
for individual D02H (Wilcoxon’s rank sum test, p <0.05).
Growth of Miscanthus condensatus,
pasture grasses and other invading herbs

Fig. 4

Figure 4 shows the change in mean plant heightof M. condensatus. Only in 2005, the mean plantheight was significantly greater in fertilized plots
than in non-fertilized plots (t-test, p < 0.05). There
were no significant differences in the following
years, and plant height tended toward a plateau levelin 2008 around which it fluctuated (from ca. 170 to
200 cm).
Coverage percentage of exotic pasture grasses isshown in Fig. 5. After 2005, the total coverage
percentage of exotic pasture grasses decreased withthe exception of in 2007, and no significant
differences were detected between non-fertilized andfertilized plots (Wilcoxon’s rank sum test). By
species, A. stolonifera decreased yearly, while
Festuca sp. and L. cuneata leveled off but showeddecreases after 2008. Festuca sp. increased rapidly
in fertilized plots in 2005 (the year after thefertilization), but no changes were observed in nonfertilized plots. In 2013, exotic pasture grasses wereabsent from non-fertilized plots. The remnants werestill extant in one of the fertilized plots, but thecoverage percentage was less than 1%.

Changes in the height of Miscanthus
condensatus on the Torino-o No. 3
landslide slope. The solid circles andsolid line indicate non-fertilized plots, andthe open circles and broken line indicate
fertilized plots. Error bars indicate ± 1
standard deviation (SD) (n=3 for nonfertilized plots; n=4 for fertilized plots).

plateau. Although individual D02H tended to begreater in fertilized plots, analysis of co-variancedetected no significant differences in the regression
coefficients (F-test, p = 0.108 and 0.266 for a and b,
respectively) between the non-fertilized andfertilized plots.
In contrast, other invading trees increased inboth density and individual D02H, but the density
appears to have reached a plateau in 2011 in each
non-fertilized and fertilized plot. Invading trees weredetected in 2004 in non-fertilized plots and in 2005
in fertilized plots. Both mean plant density andFig. 5

exoticGrowth form of immigrated herbs
In the monitoring plots of Trino-o No. 3
landslide slope, volunteer seedlings of trees andcomposite species were representative of e (erect

Changes in the coverage of exotic pasture grasses on Torino-o No. 3 landslide slope. □, ●, ▲ and ×
indicate the total, A. stolonifera, Festuca sp. and L. cuneata, respectively. Error bars indicate ± 1 SD
(n=3 for non-fertilized plots; n=4 for fertilized plots).
441

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 6 Changes in the coverage of non-native plants in the herbaceous layer on the Torino-o No. 3 landslide
slope with respect to growth form. ▲, ●, × and □ indicate erect form (e), climbing form (l), branchedform (b) and tussock form (t), respectively. Each bar indicates the 95% confidence interval ofdifference between means based on Tukey’s HSD.
form), P. foetida L. was representative of l (climbingform), Viola grypoceras A. Gray var. hichitoana(Nakai) F. Maek. was representative of b (branchingform), and ferns such as Stegnogramma pozoi (Lag.)
K. Iwats. were representative of t (tussocks form).
Figure 6 indicates the changes in coverage of
invading herbs with respect to growth forms. In nonfertilized plots, e dominated from 2006 to 2008, but
gave way to t. Significant differences were detected
in 2006 (e > b, l, t), in 2012 (t > b), and in 2013 (t >e,b, l) (Tukey’s HSD, p < 0.05). In contrast, in
fertilized plots, l dominated from 2005 to 2007, but
gave way to t. Significant differences were detected
in 2005 and 2006 (l > b, t), in 2009 and 2010 (e, l, t> b), in 2011 (t > e, b; l > b), and in 2012 and 2013(t > l, e, b; l > b) (Tukey’s HSD, p < 0.05).

covered completely by A. sieboldiana; that is, theself-thinning is not expected to be caused bycompetition between individuals. The Trino-o No. 3
landslide slope might be a severe environment for A.
sieboldiana, as we observed lodging or slanting oftrees in 2007 [1].
Average plant height of M. condensatus was
significantly higher in fertilized plots than in nonfertilized plots only in 2005, the year immediately
following fertilization. There were no significant
differences in the subsequent years (Fig. 4).
Therefore, the effect of fertilization was temporary
for M. condensatus, lasting only a year in the present
study.
Exotic pasture grasses tended to decrease yearly,
and Festuca sp. increased rapidly in fertilized plots
only in 2005 (the year following fertilization).
Generally, excessive fertilization causes gramineous
species to put out many offshoots and to form alarge tussock, and then to decrease in density [14]. It
is suggested that Festuca sp. is more susceptible tosuch effects of fertilization than A. stolonifera
because the latter grows as a carpet-like community
by putting down filiform stolons.
The length of time needed to transition from acommunity of exotic pasture grasses to one of native
vegetation is said to range from over 5 to 10 years[5], [8], [11], [15], and over 20 years would beneeded for harsh habitats, such as when the substrateis bare bedrock or wind-beaten bare ground [5], [11].
Simultaneous transplanting of exotic pasture grasses
and trees is reported to accelerate the changes to thesurrounding vegetation [11]. As a nitrogen-fixing
pioneer tree, Alnus sieboldiana is hypothesized to
improve the soil and protect herbaceous layer
species by shading, thus facilitating the growth of M.
condensatus and other invading native species.

DISCUSSION
Growth of Alnus sieboldiana, Miscanthus
condensatus and exotic pasture grasses
In A. sieboldiana, the mean plant density
decreased yearly, while the individual D02H
increased and tended to approach a plateau (Fig. 3).
Analysis of co-variance did not detect significant
differences in the regression coefficients between
the non-fertilized and fertilized plots. Previously, we
reported that individual D02H was greater in
fertilized plots than in non-fertilized plots based ondata collected from 2004 to 2009 [1], but thosedifferences diminished by 2013. This extended data
set indicates that a single fertilization increased
individual D02H of A. sieboldiana with effects
apparent for several years but diminishing in 10
years. However, the decrease in mean plant density
cannot be explained, because the plots were not442

GEOMATE- Brisbane, Nov. 19-21, 2014[3] Bazzaz FA, Plants in changing environment.
Cambridge: Cambridge University Press, 1996,
320 pp.
[4] Holl KD, Loik ME, Lin EH and Samuels IA,“Tropical montane forest restoration in Costa
Rica: overcoming barriers to dispersal andestablishment”. Restoration Ecology, Vol. 8,
2000, pp. 339-349.
[5] Imamoto H, Goto K, Shirai A and Washitani I,“Effect of the introduction of exotic grasses tosolid rock slopes on the vegetation successionof the site”. Ecology and Civil Engineering, Vol.
6, Aug. 2003, pp. 1-14.
[6] Issiki N, Geology of the Mikurajima,
Inambajima and Znisu districts. Yatabe:
Geological Survey of Japan, 1980, 35 pp.
[7] Japan Weather Association Ed., the yearbook of
weather in 1996. Tokyo: the Printing Bureau,
1996, 265 pp.
[8] Kodama S, Wada M, Shima K, Chiba K,“Effects of different introduced plant species oninvasion and establishment of other plant
species in the artificial slopes”. J. of theJapanese Society of Revegetation Technology,
Vol. 28, Aug. 2002, pp. 139-142.
[9] Kyoju no Kai Ed., Saving earth (1) Practices torestore nature in Mikura-jima Island. Tokyo:
Kyoju no Kai, 2004, 48 pp.
[10] Loope LL, Hamann O and Stone CP,“Comparative conservation biology of oceanic
archipelagoes –Hawaii and the Galapagos”.
BioScience, Vol. 38, 1988, pp. 272-282.
[11] Nakano Y and Futami T, “Observation on plant
succession at the past cut slope landscaping
sites in Miyakejima Island”. J. of the JapaneseSociety of Revegetation Technology, Vol. 30,
Nov. 1987, pp. 383-388.
[12] Ohba T, “Die Vegetation von Mikura-Insel
leight 200km sudlich von Tokyo”. Bull. of
Kanagawa Prefectural Museum, Vol. 1, Feb.
1971, pp. 1-53.
[13] Ono M, Wildlife in solitary island. Tokyo:
Iwanami Shoten, 1994, 239 pp.
[14] Sato K, Nishimura N and Takahashi M, Ecophysiological studies on the maintenance ofdensity of forage crop swards, I”. Grassland
Science, Vol. 11, Jun. 1965, pp. 14-19.
[15] Swada Y, Kubota K, Yashiro Y, Nishiwaki A
and Tsuda S, “Vegetation established by theaerial seeding of pasture plants after a forest firein a secondary forest in Shiga Prefecture, Japan”.
Japanese J. of Conservation Ecology, Vol. 13,
May 2008, pp. 29-36.
[16] Yoda K, Forest ecology. Tokyo: Tsukiji Shokan,
1971, 331 pp.

Change of Growth forms
Two phenomena are remarkable with regard to
growth forms. First, different growth forms
dominated the early period non-fertilized andfertilized plots; second, t (tussocks form) dominatedafter 10 years in all plots (Fig. 6).
In fertilized plots, l (climbing form) dominatedin the early period. In contrast, e (erect form)
dominated in the early period in non-fertilized plots.
Climbing plants have an advantage in thecompetition: they can grow rapidly because they do
not need to invest in supporting organs and can bring
down other plants by winding or leaning [2].
Fertilization is reported to induce species
competition within the community in the early
period because it improves the growth of somenutrient-limited species [3]. Since fertilization
temporarily increases the growth of M. condensatus
and Festuca sp., severe competition could result
within the herbaceous layer. The high abundance of
climbing plants suggests that plants of other growthforms could hardly germinate or establish seedlings
under such severely competitive conditions.
Plants of tussocks form in the study sites weremainly ferns: it is rare and unprecedented that thegrasslands dominated by exotic pasture grasses give
way to ferns in 10 years. The spores of ferns might
have been carried by rainfall or wind from thesurrounding intact forest, but their growth andpropagation are not competitive enough to generatethese shifts in numbers. In Fig. 6, only t (tussocksform) gradually and steadily increased during the 10
years of observation in both the non-fertilized andfertilized plots, and the decreasing exotic pasturegrasses (Festuca sp. and A. stolonifera) are also oftype t (tussocks form): this commonality suggeststhat ferns gradually replaced exotic pasture grasses
by occupying the same niche in the herbaceous layer.
From the above, we can conclude that thecommunity of exotic pasture grasses in this study
was succeeded by native vegetation in 10 years
irrespective of fertilization. Effect of fertilizing was
temporary, and enhanced competition in herb layer.
REFERENCES[1] Arase T, Okano T, Kimura T and Inoue S,“Influence of seeding exotic pasture grasses on
the vegetation recovery of landslide slopes
formed by typhoon 9512 in Mikura-jima Island,
Izu Islands, Japan”, J. of the Japanese Societyof Revegetation Technology, Vol. 35, Feb. 2010,
pp. 448-461[2] Bailey DR, “Weed control in tropical pastures”,
Tropical forege legumes, Skerman PJ, Cameron
DG and Riveros F Eds. Rome: FAO, 1988, pp.
136-147.

443

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

FUNDAMENTAL PROPERTIES AND ANALYSIS OF WATERQUALITY IN A RESERVOIR AFFECTED BY LITTLE WATER USE
AND TEA PLANTATION
Masaaki Kondo1 and Takamitsu Kajisa2
Graduate School of Bioresources, Mie University, Japan

1,2

ABSTRACT
There are many reservoirs in trouble on eutrophication problem. This paper focused on a reservoir whosewater has rarely been used for agriculture or drinking. The many tea plantations distributed in the dam basin aresuspected to be the cause of the reservoir’s eutrophication. It was investigated that eutrophication components
such as nitrogen and phosphorus and how they relate to the tea plantations in the basin. With reference tophosphorus, trophic levels were determined with Vollenweider plots and Carlson indices. With reference tonitrogen, a field survey was carried out to investigate the properties of sulfate and then sulfate concentration was
analyzed with a simple model. The various activities to improve the water quality of the reservoir are introduced.
In conclusion, the dam reservoir water is typically eutrophic, and might be affected by the fertilizer in tea
plantations. The motion of surface water in the dam reservoir is similar with the property of river, and then thesulfate concentration was analyzed with simple model.
Keywords: Reservoir, Eutrophication, Tea plantation, Sulfate, Improvement activities

phosphorus and how they relate to the tea
plantations in the basin. With reference tophosphorus, trophic levels were determined with
Vollenweider plots and Carlson indices andperformed comparisons with other domestic
reservoirs, and with reference to nitrogen, a fieldsurvey was carried out to investigate the properties
of sulfate and then sulfate concentration was
analyzed with a simple model.

INTRODUCTION
The K dam reservoir in the north of Nara
Prefecture, Japan, has an eutrophication problem
causing a lot of blue-green algae to bloom every
summer and needs to be protected from mold odors
in the water because this water is used as drinking
water. The many tea plantations distributed in thedam basin are suspected to be the cause of thereservoir’s eutrophication.
It has been reported that the overfertilization toalmost of the domestic tea plantations resulted thatthe surface water and groundwater surrounding thetea plantations had problems on water quality
besides the K dam basin [1]-[3]. In order to improve
the situation, many researchers tried to reduce theamount of applied fertilizer and improve thefertilization method. A rare successful water quality
improvement of groundwater and river water was
reported recently [4]. The K dam management officealso has taken various steps to combat the water
quality problem in the reservoir. For example, they
have mown weeds on the slopes surrounding thereservoir, planted purification grasses around the tea
plantations, planted buckwheat crops instead of tea
tree crops, and created a floating island with aquaticplants for the purification of reservoir water, among
other activities.
In this paper, the author gives a basic overview
of the water quality of the K dam reservoir anddiscusses the concrete actions that have been taken
to improve it. Of particular interest to us are
eutrophication components such as nitrogen and

METHOD
Parameters of Dam Reservoir and Basin
Table 1 shows the parameters of the K dam
reservoir and its basin. The K dam was built as aconcrete gravity dam in 2001 and, according to the
management officer, the sediment level at thebottom of the reservoir remains low even ten years
after the completion. Water from the reservoir has
rarely been used for agriculture or drinking in thepast and a downturn in tea leaf consumption has
significantly lowered what little water use there
originally was. Ideas and activities for increasing thewater usage of the reservoir are required besides asfollows; water supply stations around the dam areavailable in the form of automatic vending machines,
and farmers can buy reservoir water with coins andpour it into the tanks of pickup trucks to use thewater more conveniently.
The basin area of the reservoir is 18.9 km2, the444GEOMATE- Brisbane, Nov. 19-21, 2014

Table 1 Parameters of the K dam and basin
Parameters
Value
Type of dam
Concrete gravity dam
Basin area
18.9 km2
Total reservoir capacity
5.6 × 106 m3
Water surface area
0.329 km2
Mean depth
17.0 mResidence time
0.31 year
Phosphorus load in 2008
683,553 gP・yr-1
Phosphorus load in 2009
997,690 gP・yr-1
Phosphorus load in rain*
15,500 gP・yr-1*value estimated by author
Reservoir
Reser
Basin
Ba

As nutrition issues have been linked tophosphorus, the trophic level in the reservoir wasdetermined using a Vollenweider plot withphosphorus data. Trophic state index (TSI) was used
as an additional index.
There are various methods of determine thetrophic level, and in this work the Vollenweider
method was selected due to its popularity [5]. There
are two ways to make a Vollenweider plot: one, aflame method based on unit load data, and two, amethod based on actual observed concentration anddischarge data. The latter method was adopted andphosphorus concentration data was used frombetween 2008 and 2009.
TSI values were calculated using chlorophyll aand total phosphorus due to a lack of transparency
data on the reservoir.
Field Survey on Sulfate

(b)

(a)
Fig.1 Location of the (a) K dam reservoir and (b) basin
total reservoir capacity is 5.6 × 106 m3, and the water
surface area is 0.329 km2, as shown in Table 1.
Since the K dam was originally intended for
irrigation and the provision of drinking water, thebasin area and the reservoir capacity are small
compared to dams with other purposes.
Two main rivers, D River and O River, flow into
the dam reservoir, as shown in Fig. 1. A discharge
channel M also flows into the reservoir between
these main rivers. This channel is not included on
the map due to its small discharge, but information
pertaining to it is mentioned as necessary.
Data
Data used in this paper were provided by thedam office and the part of data was measured andanalyzed by the author. Dam control items werewater temperature, inlet, and outlet flow, andweather data were precipitation and air temperature.
Determination of Trophic Level in Reservoir
445

Tea trees prefer sulfur and can grow in suitably
acidic soil [6], [7]. Ammonium sulfate is often topdressed into tea plantations during tea-picking
season. Ammonium sulfate is the major quickimpact fertilizer described by (NH 4 ) 2 SO 4 as achemical formula [7]-[9]. Sulfur component
circulates through the primary production process
and accumulates in the sediment as hydrogen sulfide[10]. Fertilizer run-off from tea plantations causes
severe water quality problems that have a national
impact, which is why the author focuses on thesulfate in water here.
Sulfate is not measured by the dam office, so theauthor measured it specifically for this study. A
monthly field survey was conducted between Augustand December 2011 during the formation of thermostratification.
Since the reservoir water is not used in great
quantities, water turnover is small, so the motion of
the reservoir water could be regarded as the same asriver water during the formation of stratification.
The water in the field survey was sampled andmeasured at the surface layer in the reservoir and at
the points where two rivers and the discharge
channel flow into the reservoir. Water temperature,
pH, dissolved oxygen, and electric conductivity
were measured onsite as soon as sampling. Water
samples were taken and sulfate was then measured
in our laboratory. Other observed items included
inorganic phosphoric acid, turbidity, chemical
oxygen demand, and inorganic nitrogen such as
nitrate-nitrogen, nitrite-nitrogen, and ammonianitrogen.

GEOMATE- Brisbane, Nov. 19-21, 2014

RESULTS AND DISCUSSION
Properties of Water Quality in the Reservoir
Figure 2 shows the changes of water temperature,pH, chlorophyll a, and dissolved oxygen (DO) withtime for each layer in the reservoir. The watertemperature results show that while the reservoir
water was stratified in during summer, wintercorresponded approximately to circulation.
The amount of phytoplankton in the summer
increased at the sunlit surface layer of the reservoir,
as shown in the results for chlorophyll a. Carbonicacid assimilation by phytoplankton caused the highvalue of pH and super saturation of DO. Upon
rearranging the data in terms of the relationshipbetween the water temperature and kinds ofphytoplankton, while Bacillariophyceae tended to be
dominant in water with a temperature below 15
degrees, Cyanophyceae was dominant over 15
degrees. This is in agreement with the generalconsensus that low water temperature is adequate for
Bacillariophyceae while Cyanophyceae grows athigh temperature [11], [12].
Trophic Level in the Reservoir
Figure 3 plots data of other Japanese reservoirs[13] as well as a Vollenweider model of the K dam
reservoir. The K dam reservoir was plotted using
information from the 2008–2009 circulation seasons,and as shown, was obviously eutrophic.
Furthermore, the K dam reservoir was classified
using the trophic state index (TSI) proposed by
Carlson [14]. Data on chlorophyll a and total
phosphorus at the surface layer between June andAugust was only used to determine TSI due to thelack of transparency data. The trophic level of thereservoir was classified as rank E in terms of thehighest frequency, as shown in Table 2. Rank E wasalso given to the eutrophic level in the Vollenweider
model, as in [14], [15].
The land use for each basin is shown in Fig. 4.
Although the areas of the tea plantations are verysmall compared to the basin areas, a typical turbid
water problem caused by blue-green algae occurred
every summer. Since tea tree crops are growncommercially on the mountainsides, cultivation
conditions could be responsible for fertilizer running
off from the plantations. Figure 5 shows the changeof phosphorus load calculated from theconcentration in each river. Phosphorus load peaks
appeared in April and October. According to theFig.2 Changes of water temperature,chlorophyll-a, and dissolved oxygen with timepH,

dangerous 3
TP=0.03g/m

eutrophy

100

Permissible 3
TP=0.01g/m-1-2

gP・m ・yr

Phosphorus load per unit water surface,

1000

10

K dam lake at 2008 and 2009
TP=0.000-0.005g/m3

At 2009

TP=0.005-0.010g/m3

At 2008

TP=0.010-0.030g/m3

1

TP=0.030-0.050g/m3

oligotrophy

0.1
1

10

100

1000

TP=0.050-

g/m3

10000

H／τ, m・yr -1
H is mean depth of dam reservoir, τ is residence time.

Fig.3 Plot of Vollenweider model on dam reservoirs
446

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 2 Frequency of trophic state index of the K
dam reservoir
Frequency

R
a
n
k

Score
of TSI

A

Vollenweider
model [15]TSI(chlorophyll a)TSI(Total
Phosphorus)

Below
37

1

1

OligotrophyB

37 - 47

00

Oligotrophy- middle

C

47 - 53

01

MiddleD

53 - 6102Middle eutrophy

E

Over 617

4

EutrophyFig.5 Changes of phosphorus load in river waterwith timeFig.6 Changes of sulfate concentration observed in
dam reservoir and rivers with timefrom the tea plantation. As a result, ammonia
fertilizers such as ammonium sulfate contribute to
the water quality problem in the reservoir.
Attempts at improving the water quality in thereservoir include planting certain grasses around tea
plantations that prevent soil from running off andplacing floating plant islands in the reservoir itself toabsorb nutrients.
Fig.4 Land use for each basin and area ratio of tea
plantations compared with basin (rearranging data
provided by dam office)Sulfate Concentration and Its Analysis in Surface
Layer
Results of field survey

standard of fertilizer for agricultural crops [16], basefertilizer is spread in the period running from late
February through the middle of March and in early
September. Rapeseed oil cake, an organic manure, isoften used as a base fertilizer. It takes three weeks
for rapeseed oil cake to decompose. The peaks ofphosphorus load shown in April and Octobercorrespond to the decomposing stage of rapeseed oil
cake. In general, phosphorus is absorbed in the soil
and kept in the field. However, the sloped nature oftea tree fields causes soil particles with phosphorus
to run off from the field and flow into the reservoir.
While the soil in the field retains the nitrogencomponent in the form of ammonium, ammonium
sulfate changes into nitrate nitrogen relatively
quickly and the nitrogen component might run off

Figure 6 shows the change of sulfate
concentration observed at the reservoir’s surface andat the rivers. The concentration of sulfate is larger in
D River than the other rivers, as shown. According
to Fig. 4, which illustrates the land use for eachbasin, the area ratio of a tea plantation comparedwith the basin area is 8.4 % on the D River basin,
3.0 % on the M discharge channel, and 2.6 % on the
O River basin. Therefore, in light of the nutrient loadmechanism discussed in previous section, the large
ratio of the tea area on the D River basin seems to beconnected to the high concentration of sulfate in the
D River water.
Figure 7 shows the relationship between sulfate

447

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig.8 Comparison with calculated and observed dataon concentration of sulfate
Fig.7 Relationship between sulfate load and riverdischarge

the depth of the surface layer as stratification depth.
The reservoir was assumed to be stratified between
August and December. Since the layer depth wasvaried with time, the model equation was naturally
considered with the depth change.

load L and discharge Q. The L-Q values for eachbasin are calculated as
𝐿𝐿1 = 1,271,562 ∙ 𝑄𝑄𝑟𝑟
𝐿𝐿2 = 658,914 ∙ 𝑄𝑄𝑟𝑟

0.958

0.929

𝐿𝐿3 = 1,418,766 ∙ 𝑄𝑄𝑟𝑟 1.017(1)𝑑𝑑(𝑉𝑉𝑉𝑉)
𝑑𝑑𝑑𝑑(2)= 𝐿𝐿1 + 𝐿𝐿2 + 𝐿𝐿3 − 𝑄𝑄𝑄𝑄

(4)where C is the concentration of sulfate at thereservoir surface layer, V is the water volume of thesurface layer given by multiplying water surface
area by the depth of the surface layer, t is time, andQ is reservoir outlet.
Figure 8 shows the calculation result of sulfate
concentration
and
daily
rainfall.
Sulfateconcentration in the surface layer of the reservoir
was calculated during stratification.
When the simple model was used to analyze thesulfate concentration, the calculated concentration
value was in good agreement with the observed
value. Our simulation was performed after theconcentration of sulfate decreased in early
September, and the concentrations of sulfate
gradually increased until November. Concentration
was quite low in early September. It seems that large
typhoon No.1112 (TALAS) passed through the areaat that time, and there was heavy rainfall.

(3)

where L 1 is the load of sulfate in D River, L 2 is theload of M River, L 3 is the load of O River, and Q r is
the river discharge.
Since the concentration of sulfate increases alongwith the area of a tea plantation, it is reasonable toassume that load might run off from the plantations.
Analysis of sulfate concentration
Sulfate concentration was analyzed using asimple water quality model defined with river water
inlet and reservoir outlet as shown in equation (4).
This simple model was used because, although theauthor originally intended to use a circulation modelof sulfur in water without an input-output system,
the author wanted to investigate the rough validity.
Little water use of the reservoir and reservoir
stratification means that reservoir properties will
remarkably agree with those of a river. Furthermore,biological processes and vertical mobility could be
conversely estimated from the difference between
the calculation result and the field survey
measurements.
Water temperatures at each depth were measured
at an intake tower of the reservoir and verticalprofiles of water temperatures were used to estimate

CONCLUSIONS
A great deal of effort has been made by many
Nara Prefecture officials and members of land
improvement organizations to improve the water
quality in the K dam reservoir. The author andlaboratory members have also participated in these
improvement activities as volunteers. In this paper,
the fundamental properties of the K dam reservoir
are reported using examples from the eutrophication
mechanism and various water quality improvement
methods.
448

GEOMATE- Brisbane, Nov. 19-21, 2014[4] Hirono Y, Watanabe I, and Nonaka K, “Trends
in water quality around an intensive tea-growing
area in Shizuoka, Japan(Environment) ” , Soilscience and plant nutrition, Vol.55, No.6, 2009,
pp.783-792.
[5] Vollenweider R. A., “Advances in defining
critical loading levels for phosphorus in lake
eutrophication”, Mem. lst. Ital., Idrobio., Vol. 33,
1976, pp.53-83.
[6] Konishi S, “Technical system of agriculture :soil and plant nutrition ” , Rural Culture
Association, 1987, p.177.
[7] Yoneyama T, Hasegawa I, Sekimoto H, Makino
A, Matoh T, Kawai S, and Morita A, “Plant
nutrition and fertilizers”, Asakura Publishing ,2010, pp.172-176.
[8] Ishigaki K, “ Studies on the nutritive
characteristics of tea plant”, Bulletin of the Tea
Research Station, Ministry of Agriculture andForestry, 14, 1978, pp.1-152.
[9] Ishigaki K, “Evaluation of ammonium nitrogenand nitrate on the tea plant as nitrogen source(part 1):on the concentration of nitrogen”, Tea
Research Journal, 35, 1971, pp.57-64.
[10] Wetzel R G, "Limnology, 2nd ed.", Saunders
College Publishing, 1983, p.327.
[11] Moss B, “ Ecology of fresh waters ” ,Blackwell Scientific Publications, 1980, pp.7475.
[12] Water Resources Environment Technology
Center, “Useful reading for water environmentof dam reservoir”, Sankaido Publishing, 2002,
p.64.
[13] Morikita Y and Miura S, "Predictive techniques
for eutrophication in dam reservoirs", Civil
engineering journal, Vol.25, No.4, 1983, pp.181186.
[14] Japan Society of Civil Engineers, "Thecollection of hydraulic formulae", Maruzen
Publishing, 1986, p.355.
[15] Vollenweider R A, “Input-output models withspecial reference to the phosphorus loading
concept in limnology”, Sch. Zeit. Hydrologic,
Vol.37, 1975, pp.53-84.
[16] Nara Pref., "Standard of fertilization
management for agricultural crops", 2009, p.31.

The surface layer water of the K dam reservoir
indicated approximately pH 10 during summer.
Carbonic acid assimilation by much phytoplankton
caused super saturation of dissolved oxygen in
addition to high pH.
The value of mean depth divided by residence
time was 55 m per year. Phosphorus load per unit
water surface was 2.1 g･m-2･yr-1 in 2008, and 3.1 g･
m-2･yr-1 in 2009. The TSI was the rank E level.
The reservoir water is typically eutrophic, andmight be affected by the fertilizer in tea plantations.
The area ratios of tea plantations for each basin
were less than 10 %. The concentrations ofphosphorus and sulfate in rivers were described inorder of the area ratios.
The motion of surface water in the dam reservoir
is similar with the property of river, and then theconcentration was analyzed with simple model.
It was observed that much rainfall brought about
by typhoons decreased the concentration of sulfate
and then the concentration gradually increased. Thechange of the concentration was simulated with thesimple model.
ACKNOWLEDGEMENTS
The author is indebted to the local public
officials and dam management office for providing
their cooperation and the valuable data for the study.
REFERENCES[1] Yamamoto T, Nakasone H, Kuroda H and Kato
T, "Diffuse nitrogen load pollution fromcollective tea field -case in Makinohara plateau,
Shizuoka Prefecture-", J. of Japan Society on
Water Environment, Vol.29, No.11, 2006,
pp.745-748.
[2] Ii H, Hirata T, Tanaka T, Nishikawa M,
Nakajima T, and Umehara K, "Spring pond andriver water chemistries derived from a tea
plantation in central Shizuoka Prefecture",
Proceedings of hydraulic engineering, JSCE, 44,
2000, pp.1155-1160.
[3] Takeda I, Kunimatsu T, Kihara Y, and Mori Y,"Estimation of runoff pollutants of nitrogen,phosphorus and cod from a small catchment of
tea field", J. of Japan Society on Water
Environment, Vol.25, No.9, 2002, pp.565-570.

449

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SMALL WATER DISTRIBUTION SYSTEM DISINFECTION BYPRODUCT CONTROL: WATER QUALITY MANAGEMENT USING
STORAGE SYSTEMS
Sandhya Rao Poleneni 1 and Enos C. Inniss 2
Ph.D. student, University of Missouri-Columbia, USA; 2Faculty, University of Missouri-Columbia, USA

1

ABSTRACTDisinfection, a vital part of a drinking water treatment, using chlorine is the most widely practiced process inthe world. The Stage-2 Disinfectant and Disinfection By-Product regulations force water utilities in the US to be
more concerned with their distributed water quality. Compliance requires changes to their current operational
strategy. Storage system management is an important part of the operational strategy of small scale utilities. This
study quantifies changes in DBP formation and chlorine decay in storage systems under varying operationalparameters such as mixing, contact time, and water movement using a physical model (Pipe Loop) of a
distribution system. Effective operation of storage systems can yield greater than 30% decrease in DBP
formation in distribution systems and maintain chlorine residual for a 50% longer period.
Keywords: Clearwell, Storage Tank, Pipe Loop, Trihalomethanes, Chlorinationwater demand is a complex process and hence
requires a balanced approach. With the Stage-2
Disinfectants and Disinfectant By-Product Rule
regulation compliance date approaching (October2014) many small-scale utilities in US are adopting
techniques to balance protection against microbial
risks with the risks posed by harmful by-products[6]-[8].
Storage tanks are an important part ofinfrastructure as well as the operational strategy ofsmall scale utilities [9]-[15]. Many small scale water
utilities are shut down for a part of the day and thesetanks act as a reservoir of treated water at thetreatment plant (clearwell) or in the distribution
system (tower or stand-pipe) to meet the water
demand of the town. They hold immense potential toeither improve or degrade the water quality provided
by the utility. External factors like atmospherictemperature, mixing conditions, size and shape ofthe tank, location of inlet and outlet valves, wall
coating etc. play a vital role in quality of watercoming out of the storage tanks [9]-[15]. The
volume of water entering and leaving the tank andtimeline of these events are the most importantfactors that dictate successful operation of storage
tanks. Therefore understanding the changes inchemistry of water while in the storage systems canhelp utilities utilize these structures to maintain or
improve the quality of water provided to theircustomers.

INTRODUCTION
Disinfection and distribution of treated water are
vital parts of a drinking water utility’s operation.
Though they may seem like two completely different
processes, their operation strategy needs to becomplementary in order to maintain minimum
disinfectant residual as part of the distribution
system water quality management. Chlorination is
one of the most widely used disinfection processes
in water treatment plants because chlorine is a very
effective disinfectant and is relatively easy tohandle; the capital costs of installation are low; it iscost effective, simple to dose, measure and control;
and, it has a reasonably prolonged residual [1]-[3].
Despite the benefits of chlorine, halogenateddisinfection by-products (DBPs) are formed due tothe interaction of aqueous free chlorine with naturalorganic matter (NOM), like humic substances,
present in water [4], [5].
Small-scale water utilities are known to use
different operational strategies to overcome their
physical (infrastructure, source water quality,
distribution system layout, storage system designetc.) and financial constraints to meet the water
demand and provide consistent quality water to all
its customers. In other words, though known to haveinfrastructural constraints small-scale utilities tend tobenefit a lot by making necessary changes to theway they operate each of their units based on sitespecific conditions and the formation kinetics of thecontaminant in question. Water treatment process
operation to maintain water quality with respect tonumerous contaminants in distribution systems
irrespective of seasonal changes and fluctuating

METHODSThis research was conducted using a physicalmodel of distribution system (Pipe Loop) built at the450

GEOMATE- Brisbane, Nov. 19-21, 2014

City of Columbia, Missouri (USA) Water Treatment
Plant using 10.16 cm (4 in) PVC pipe [16]. The
scenarios discussed in this paper are: Normal Run,
Storage Tank in Distribution System Run, Clearwellwith proper mixing and fill-drain cycles Run and
Clearwell without mixing and fill-drain cycles Run.
Normal run is used as the control or baseline forcomparing other scenarios and is based on typicaloperation of a drinking water treatment process
which involves treated water with disinfectant
residual entering the distribution system. In order tosimulate a Normal Run (NR), finished water fromthe City of Columbia water treatment plant(chlorinated water before ammonia addition) isallowed to enter the Pipe Loop via the Water Tank
attached to it (Fig. 1). The water was recirculated in
the looped system for 7 days with water samples
collected at daily intervals.
In order to simulate storage tank in a distribution
system scenario in the Loop, the finished water wasallowed to fill the Loop via a storage tank attached
to it. Once both tank and Loop were full, the valve
between them was shut and the water was allowed tostay in the tank and recirculate in the Loop for 2days. On day 2, the valve between tank and Loop
was opened and one-third of volume of the tank was
drained through the loop. The tank was filled to its
full capacity at high pressure to ensure proper
mixing. The process of draining one-third volume
and refilling it with new water was continued for 4
more days before the Loop and the tank weredrained completely to start the process all overagain. Water samples were collected from the tankas well as the Loop at regular intervals. Samples
were collected before draining and after refilling at
both locations.
For clearwell with proper mixing and fill-drain
cycles, the finished water was allowed to fill only
the tank attached to the Loop on day 0 with highpressure and 1/3rd of the tank was drained after 24hours using a valve at the bottom of the tank. The
tank filled to its full capacity at high pressure toensure proper mixing. The process of draining onethird volume and refilling it with new water wascontinued for 4 more days before the tank was
drained completely to start the process all overagain. Water samples were collected before draining
and after refilling the tank at regular intervals.
For clearwell without mixing and fill-drain
cycles, the finished water was allowed to fill only
the tank attached to the Loop on day 0 and the water
was allowed to sit in the tank for 7 days without any
mixing or draining and filling with new water. Water
samples were collected from the tank at regularintervals.

Fig. 1: Schematic of the Pipe Loop used inexperiments to determine effects of distribution
system management. Water tank shown was used tosimulate clearwell and storage tank
All of the collected samples were tested for free
and total chlorine residual, total organic carbon(TOC), pH, UV254 and TTHM as a function of timeover a period of 10 months. The TTHM
concentration entering the Pipe Loop averaged 40µg/L (half of MCL limit of 80) and pH averaged 8.5,
which is considerably high for a chlorinated system.
UV 254 was measured using Varian Cary 50 UVVisible Spectrophotometer following Standard
Method 5910 B [17]. Free and total chlorine residual
was measured using appropriate DPD methods(Hach methods 8021 and 8167 [18] equivalent toStandard Method 4500-Cl G [17] and a Hach pocket
Colorimeter II (Cat # 5870000) designed forcollecting
on-sitemeasurements.
TTHM
concentrations were analyzed with a Varian 3800
Gas Chromatograph (GC) equipped with a Saturn2000 Mass Spectrometer (MS) for detection
following an analysis method similar to that
described by EPA method 524.2 [19] and Standard
Method 6232 C [17] was used. Total Organic
Carbon (TOC) was measured using the combustion
Infrared Method (Standard Method 5130B [17]).
Statistical analysis of the data collected was doneusing MiniTab to ensure soundness of theconclusions. Analysis of Variance (ANOVA) and
Paired t-tests were conducted on all the data with 9099% level of significance.
RESULTS AND DISCUSSION
Normal Run Vs. Storage Tank In Distribution
System Run
Water chemistry in storage systems is unique inmany ways. Therefore, results are explained as

451

GEOMATE- Brisbane, Nov. 19-21, 2014

operated properly. The adverse effects of biofilm
formation, dead spots in the tank due to stratificationand inappropriate positioning of inlet and outlet on
water quality are extensively studied subjects. Henceit can be concluded that operation of the tank which
involves constant mixing to avoid temperature
stratification issues, proper maintenance in terms of
coating to ensure absence of biofilm, optimal
location for inlet and outlet, minimizing storage timeby draining a considerable volume of water at shortand regular intervals can be the difference between
tanks improving versus degrading water quality in
distribution systems.

comparisons with a Normal Run (Fig. 2). This
analysis is intended to statistically explain the effectof storage tank operation on water quality in termsofchlorine
residual
andtrihalomethane
concentrations.

Clearwell With And Without Mixing And FillDrain Cycles
Clearwell is a storage tank located on thepremises of a treatment facility and is used to store
finished treatment water before it is allowed to enter
the distribution system. Though the concept ofstorage time before dilution does not apply toclearwell as the finished water from the filtration
unit directly enters the clearwell. Rather the effect of
mixing, fill-drain cycles, and physical condition of
the clearwell become predominant. For a large
clearwell at any given time the mixed age of thewater in the clearwell can be 2 to 4 days which
demonstrates the adverse effect of increased contact
time with the disinfectant. The difference between
having and not having proper mixing and fill-drain
cycles during storage time is shown using the data
produced by two scenarios (Fig. 3). Storage tankdata of Normal Run represents a system with nomixing and filling cycles whereas Tank Storage Run
represents a system with complete mixing andregular filling cycles. Constant physical conditions
are maintained in both systems.
Comparison of data from the two runs shows thatthe decay of chlorine residual and formation of
TTHMs over time is dramatically different. Dilution
with new water in the Storage systems Run tends todecrease the concentration of TTHMs formed on
average by 30% over the 6-day operation relative to
the Normal Run. The dilution process helped
increase the chlorine residual in the Storage systems
Run by 65% on day 4 and by 113% on day 5 relative
to the Normal Run. On day 6 chlorine residual in theNormal Run decreased to zero when about 1.4mg/L
is still left in the Storage system Run. It is
statistically proven with a 99% level of confidence
that these two strategies produce different trends inchlorine decay and TTHM formation over time
under constant wall conditions.
These differences in TTHM concentration and
Chlorine residual between these two strategies aresolely due to mixing and filling conditions.
Therefore, it can be concluded that, in the case ofclearwells, the mixing and filling conditions play an

Fig. 2: Storage Tank run vs. Normal run chlorine
residual and TTHM trends. The percent differences
between the TTHM formation and chlorine decay
values are also noted.
Data from the Loop and storage tank shows thatthe decay of chlorine residual and formation of
TTHMs over time is dramatically different in
Storage Tank run when compared to Normal Run.
Relative to a Normal Run dilution by adding new
water to the Storage Tank tends to decrease theconcentration of TTHMs formed on average by 34%
over a 6-day operation. In addition to that, thisdilution helped maintain minimum residual in thesystem without additional chlorine unlike during theNormal Run when by the end of day 3, chlorine
residual in the system decreased to zero. The TTHM
concentration during the Storage Tank Run seems tobe between 143 and 148 µg/L after 24 hours
following the dilution for 4 days (compared to 200µg/L for the Normal Run). This range depends onthe concentration of TTHMs formed in the systembefore starting the dilution on day 2, which in turndepends on number of days the water is stored
before the dilution process started. It is statistically
proven with 99% level of confidence that these two
strategies produce different trends in chlorine decay
and TTHM formation over time under constant wallconditions.
The adverse effect of increased contact time andchlorine dosage on TTHM formation in the
distribution system is explained in detail in ourprevious research [16], [20]. Therefore, storage time
before the dilution process takes effect and contact
time in the tank play an important role in water
quality management in storage tanks. The
stabilization effect of the dilution process is uniqueand can be a blessing to utilities if the tank is452

GEOMATE- Brisbane, Nov. 19-21, 2014

important role in management of water quality.
Storage time before entering clearwell depends onthe contact time of disinfectant requirements during
filtration, therefore, it cannot be included inclearwell management. When operated under proper
mixing and filling conditions, the clearwell can
provide better water quality in terms of TTHM
formation and chlorine residual without additional
chlorine.

balance requires knowledge of system-specificconditions and factors of variability of waterchemistry in distribution systems.
ACKNOWLEDGEMENTS
Funding for this project was provided by National
Institute of Hometown Security (NIHS). Analyticaland technical support was provided by Missouri
Water Resource Research Center (MWRRC),
Columbia Water Treatment Plant (CWTP) andVandalia Water Treatment Plant (VWTP).
REFERENCES[1] Sadiq R, and Rodriguez MJ, “Disinfection byproducts (DBPs) in drinking water andpredictive models for their occurrence: areview”, J. of Science of the Total Environment,
Vol. 321, 2004, pp. 21–46.
[2] U.S. Environmental Protection Agency,“National Primary Drinking Water Regulations:
Disinfectants and Disinfection Byproducts”,
Federal Register, Vol. 63, 1998, pp. 6939069476.
[3] Warton B, Heitz A, Joll C, and Kagi R, “A new
method for calculation of the chlorine demandin natural and treated waters”, J. of Water
Research, Vol. 40, 2006, pp. 2877–2884.
[4] Adams C, Timmons T, Seitz T, Lane J, andLevotch S, “Trihalomethane and Haloacetic
Acid Disinfection By-Products in Full-Scale
Drinking Water Systems”, J of Environmental
Engineering, Vol. 131, 2005, pp. 526-534.
[5] Rook J, “The chlorination reactions of fulvic
acids in natural waters”, J of Environmental
Science and Technology, Vol. 11, 1977, pp.
478–482.
[6] Carrico B, and Singer PC, “Impact of Booster
Chlorination on Chlorine Decay and THM
Production: Simulated Analysis”, J. ofEnvironmental Engineering, Vol. 135, 2009, pp.
928-935.
[7] Clark RM, and Sivaganesan M, “Predicting
Chlorine Residuals and Formation of TTHMs in
Drinking Water”, Journal of Environmental
Engineering, Vol. 124, 1998, pp. 1203-1210.
[8] Clark RM, Adams JQ, and Lykins BW, "DBP
Control in Drinking Water; Cost andPerformance", J. of Environmental Engineering,Vol. 120, 1994, pp. 759-782.
[9] Besner MC, Gauthier V, Barbeau B, Millette R,
Chapleau R, and Prevost M, “Understanding
distribution system water quality.”, J. of
American Water Works Association, Vol. 93,
2001, pp. 101-114.
[10] Clark R, Abdesaken F, Boulos P, and Mau R,“Mixing in Distribution System Storage Tanks:
It’s Effect on Water Quality”, J. ofFig. 3: Tank Normal run vs. Tank Storage run
chlorine residual and TTHM trends. The percent
differences between the TTHM formation andchlorine decay values are also noted.
The change in TTHM formation and chlorine
decay kinetics between a high chlorine dosage
scenario and usage of chlorine boosters scenario is
explained in detail in our previous research [16],[20].
CONCLUSIONS
Operational strategies affect water quality interms of chlorine residual and TTHM formation in
distribution systems. In the case of storage systems
management, it is statistically proven that storage
time before entering the tank, mixing conditions andfillings cycles play an important role in maintaining
water quality in storage tanks located in distribution
systems as well as clearwells located at the treatment
facility. Storage time before entering the clearwell
cannot be considered as a part of clearwell
management as it is not controlled by the operationof the clearwell. Rather the primary disinfectant
contact time requirements of the state directly
influence this storage time. Proper mixing and filldrain cycles can alone hold the potential to dictate
whether a storage structure will improve or degrade
the water quality in terms of chlorine residual andTTHM formation. Operators need to realize that any
given operational strategy has potential to improvewater quality with respect to one parameter anddegrade it with respect to another. Finding a right453

GEOMATE- Brisbane, Nov. 19-21, 2014

Environmental Engineering, Vol. 122, 1996, pp.
814-821.
[11] Germeles AE, “Forced plumes and mixing of
liquids in tanks.” J. of Fluid Mechanics, Vol.
71, 1975, pp. 601–623.
[12] Grayman WM, and Clark RM, “Using computermodels to determine the effect of storage onwater quality”, J. of American Water Works
Asssociation, Vol. 85, 1993, pp. 67–77.
[13] Kennedy MS, Moegling S, Sarikelli S, andSuravallop K, (1993). “Assessing the effects ofstorage tank design on water quality” J. of
American. Water Works Association, Vol. 85,
1993, pp. 78-88.
[14] Mau R, Boulos P, Clark R, Grayman W,
Tekippe R, and Trussel R, (1995). “Explicit
mathematical models of distribution system
storage water quality”, J. of Hydraulic.
Engineering, ASCE, Vol. 121, 1995, pp. 699–709.
[15] Zachár AA, and Aszódi AA, “Numerical
Analysis of Flow Distributors to Improve
Temperature Stratification in Storage Tanks”, Jof Numerical Heat Transfer: Part A -Applications, Vol. 51, 2007, pp. 919-940.
[16] Poleneni SR, “Analysis and management of
disinfection by-product formation in distribution
systems”, M.S. Thesis, University of Missouri.
2013, ch. 3.
[17] APHA, AWWA, WEF, “Standard Methods for
the Examination of Water and Wastewater,”
20th ed. United Book Press: Baltimore, MD.
1998.
[18] Hach, “Water Analysis Handbook.” 3rd ed.
Hach Company: Loveland, CO. 1997.
[19] Munch JW, “EPA Method 524.2: Measurementof Purgeable Organic Compounds in Water by
Capillary Column Gas Chromatography/Mass
Spectrometry”, Rev. 4.1, US EPA, Office of
Research and Development: Washington, D. C.
1995.
[20] Poleneni SR and Inniss EC, “Small Water
Distribution
SystemOperations
andDisinfection By-Product Fate” J. of Water
Resource and Protection, Vol. 5, pp. 35-41.

454

PESTICIDE SUSTAINABLE MANAGEMENT PRACTICE (SMP)
INCLUDING POROUS BIOCHAR/GEOPOLYMER STRUCTURESFOR CONTAMINATED WATER REMEDIATION
Ian P Craig, Jochen Bundschuh and David Thorpe
Health, Engineering and Sciences, University of Southern Queensland, Australia
ABSTRACTAs a result of agribusiness in Australia and across the world, water is contaminated with nutrients andpesticides which threaten riverine environments, wetlands, urban drinking water supplies and also marine assets
such as the Great Barrier Reef (GBR). Much can be done and sustainable management practices (SMP) can be put
into place to reduce water impacts from agriculture. Such an SMP strategy may take the form of improved
spraying technology, improved integrated pest management, understanding pesticide environmental fate andbehaviour, acquiring a better understanding surface and groundwater hydrology, and improved contaminated water
remediation technologies. Required investment levels are insignificant compared to the economic advantages to begained from adopting appropriate SMP across Australian and global agribusiness. Work in collaboration withbiochemists needs to take place to develop enzymes which are naturally found in pesticide resistant insects or
weeds. Biochar geostructural/geopolymer based technologies need to be developed, augmented with enzyme based
products which need to be developed commercially. Such products or enhancers need to be targeted at specificpesticides (eg. ametryn, atrazine, simazine, diruron, ametryn, hexazinone, tebuthiuron, dieldrin, metalochlor, 2,4 D,
triclopyr, picloram and bromacil). Surface runoff from is conventionally managed by retention lagoons facilitatingwater reuse on-farm, but these can be breached during heavy storms. Long term deep drainage from fields andseepage from lagoons can also lead to contaminated groundwater. Research, development and testing ofappropriate non-leaking/reactive spillways and subsurface geostructures needs to take place across the various
agricultural industries. It could be that a porous geopolymer concrete in combination with biochar may prove
useful in the design of such structures. The potential for green or brown waste material derived biochar products,
which could be readily manufactured from farm refuse and manure, needs to be thoroughly investigated in thisregard. The challenge for engineers is to come up with geostructural designs which are efficient, cost effective andwhich will be taken up and embraced by Australian and world agribusiness.
Keywords Sustainable, Pesticide, Herbicide, Contaminated Water, Biochar, Porous, Geopolymer, Enzyme

INTRODUCTION
Previously, agribusiness has attempted to reduce
contamination of the environment by implementing
Integrated Pest Management (IPM) [1] which refers
to a strategy which seeks to reduce reliance on
synthetic chemical pesticides. It involves i) managing
pests below economically damaging levels rather thanseeking to eradicate them ii) relying on non-chemicalmeasures, and, iii) selecting and applying pesticides,
when they have to be used, in a way that minimizes
adverse effects on beneficial organisms, humans, andthe environment . IPM involves integrating a range oftools and strategies for managing pests. These can beconveniently grouped in seven main objectives
including i) using the correct spray equipment toproduce the biologically optimum droplet size ii)
optimising coverageiii) appropriate chemical
selection,iv) preserving beneficial insects, v)
preventing insecticide resistance vi) managing crop
and weed hosts, vii) using trap crops effectively andviii) communication and training.
Field studies over the years have demonstrated
that pesticide application using liquid based sprays isprobably at best only a few percent efficient [2].
Efficiency is defined simply in terms of thepercentage of droplets reaching the intended target.
These studies have indicated that droplet size seems
to be the most important factor which determines thisefficiency. Droplets produced by conventional
hydraulic nozzles used in agriculture generally range
in size from 30µm to 3000µm. Droplets withdiameters less than 100um have low sedimentation
velocity and shallow trajectory, and are vulnerable tooff target drift and loss to atmosphere. Droplets
greater than 300um which contain most of the volumeof the spray, have high sedimentation velocity andsteep trajectory, and are unlikely to strike a plantsurface or pest. Even within a dense crop canopy,
coarse droplets may bounce from a leaves, andtherefore simply contribute to soil and/or
groundwaterpollution.
Pesticideapplication
efficiency could be increased dramatically if thepercentage of droplets falling between 100um and300um present in the spray was increased [3].
Investment is also needed in developing
appropriate remediation technology to pesticidecontaminated water which leaves cultivated field as455

runoff. Green and brown waste derived biochar has
recently shown significant potential in this regard. A
particulate form of biochar is required to increaseavailable surface area, with carbon particles held in arigid and durable porous matrix, to prevent them
being eroded away by a moving water stream. Recent
developments in porous geopolymer concrete may
perhaps provide an answer to this design challenge.
Porous concrete/polymer materials developed forother purposes in civil engineering, may prove to bealso very useful for Porous Reactive Barrier (PRB)
designs [15], which trap contaminants from waterflowing through them.
Such technologies when assembled together in a
unified SMP strategy for sustainable agribusiness,
will undoubtedly have the potential to significantly
reduce pollution of atmosphere, soil, fresh water andoceans with pesticides.
PESTICIDEFATEAND
BEHAVIOURMONITORING AND MODELLING
Pesticides residues can be found in theatmosphere, water, soil, vegetation and organisms. In
water, pesticides can exist in a dissolved form, or canbe attached suspended matter or bottom sediments.
Pesticides are taken up by aquatic biota, possibly
being excreted in metabolised form. Within a water
system, transformation of pesticides can occur via
chemical, physical and biological processes.
Pesticide runoff into natural water systems canoccur during large rainfall or storm events. Weed
control in urban areas is often adjacent to hardsurfaces and roads with man-made drainage systems
acting as a fast conduit to ocean. Correctly designed
storm water harvesting infrastructure is often nonexistent, or at best minimal. Farms are usuallydesigned with retention storages whose combined
purpose is to collect irrigation tail water and storm
water runoff. However, during periods of highrainfall, on-farm storage of runoff can be breached,and pesticides are at risk of entering the river systems
and making it out to the GBR [4].
The development of numerical models to describe
pesticide fate and behaviour commenced in the
1970s, and were useful in understanding DDT foundin birds of prey, in the wildlife at both poles, and also
in dairy cattle directly affecting humans. Endosulfan
was found in Australian export beef during the 1990s.
HowLeaky software [5] launched by Qld Govt
DNRM, DAFF and EPA in 2003, represents the
pinnacle of development for pesticide fate andbehaviour modelling purposes. Evolution of thesoftware arose from exhaustive testing and calibration
earlier algorithms (USLE, CREAMS, GLEAMS,RZWQM, HSPF, PRZM, PERFECT). The
HowLeaky model represents a one dimensionalsoil/water balance agricultural hydrology model for
exploring the impact of different land uses and soil

management on water balance and water quality. It
has a user interface which provides a highly visual
representation of inputs and outputs. The software has
been used to explore implications of different land
uses (including crops, pasture and tress), climates,
soil types and management (tillage, crop rotation,
herbicide strategies) on hydrology, production index,
erosion and off-site sediment loss, nitrogen,phosphorus and pesticide movement [6].
WATER REMEDIATION USING
BIOCHAR GEOSTRUCTURES

POROUSThe use of ground iron based reactive barriers for
TCE to ethane, Cr(VI) to Cr(III), some heavy metals
and phosphorus has been investigated by the USEPA,
but focus is now on non-living structures forpesticide/nutrient bioremediation, because of the
problem of keeping the plants/microbes alive isalleviated. The advantage of using biochar
geostructures is longevity and reduced maintenancecosts. Added to soil in particulate form, studies havedemonstrated that biochar can increase cationexchange capacity, enhance soil microbes andaugment water retention [7,8]. These advantages are
additional to its primary use as a soil carbon store forgreenhouse gas reasons. It has also been suggested
that biochar can reduce nutrient loadings inagricultural runoff. It is established that biochar on its
own is showing promise also for the removal of someheavy metals [9] and uranium [10]. In trials in which
particulate biochar was added to soil as a soil
amendment, it was noticed that herbicide efficacy incontrolling weeds was noticeable reduced [8]. The
reason for this is presumably chemical binding of theherbicide active ingredient to the carbon particles.
From this has very recently launched a series ofinvestigations as to the potential effectiveness ofbiochar for removal of herbicides in water [11]. The
potential for biochar derived from greenwaste has
been assessed specifically for triazine basedherbicides [12]. The potential for biochar derived
from pig manure has been assessed for the herbicide
paraquat by [13] and for carbaryl plus atrazine by[14]. Deep percolation of pesticides leads to longterm pollution of groundwater resources andrepresents a new area which needs to be addressed.
Preliminary investigations of biochar based
geostructures commenced at USQ [15].
CONCLUSIONWork in collaboration with biochemists needs totake place to develop enzymes which are naturally
found in pesticide resistant insects or weeds. Biochar
geostructural/geopolymer based technologies need to
be developed, augmented with enzyme based
products which need to be developed commercially[16]. Such products or enhancers need to be targetedat specific pesticides (eg. ametryn, atrazine, simazine,456

and restoration of contaminated soils.
Environmental Pollution 159 (July, 2011) 32693282.
[8] Jones DL, Edwards-Jones G and Murphy DV
2011. Biochar mediated alterations in herbicide
breakdown and leaching in soil. Soil Biology
and[9] Chen, J.; Zhu, D. and Sun, C. 2007. Effect ofheavy metals on the sorption of hydrophobicorganic compounds to wood charcoal.
Environmental Science & Technology, 41(7),2536–2541.
[10] Kumar S, Loganathan VA, Gupta, RB andBarnett, MO 2011. An Assessment of U(VI)removal from groundwater using biochar
produced from hydrothermal carbonization.
Journal of Environmental Management 92(2011) 2504e2512[11] Kearns, J., 2013. Sustainable Decentralized
Water Treatment for Rural Developing
Communities Using Locally Generated Biochar
Adsorbents. ECHO Asia Notes May 2013 Issue
17.
[12] Zheng W, Guob M, Chowa T, Bennetta DN,
Rajagopalana N., 2010. Sorption properties ofgreenwaste biochar for two triazine pesticides.
Journal of Hazardous Materials 181 (2010) 121–
126
[13] Tsai WT and Chen, HR 2013 Adsorption
kinetics of herbicide paraquat in aqueous
solution onto a low-cost adsorbent, swinemanure-derived biochar. Int. J. Environ. Sci.
Technol. (2013) 10:1349–1356[14] Zhang, P, Sun H, Sun LYT, 2013. Adsorption
and catalytic hydrolysis of carbaryl and atrazine
on pig manure-derived biochars: Impact ofstructural properties of biochars. Journal ofHazardous Materials 244– 245 (2013) 217– 224.
[15] Craig I, Shiau J, and Erdei L 2012.
Contaminated soil/groundwater remediation
using Permeable Reactive Barrier (PRB)
techniques. Engineers Australia - Southern
Region Engineering Conference, University ofSouthern Queensland, Toowoomba, 30 August
2012. Paper no. SREC2012-2A-4.
[16] Scott et al 2010 A free-enzyme catalyst for thebioremediation of environmental atrazine
contamination. Journal of Environmental
Management May 2010.

diruron, ametryn, hexazinone, tebuthiuron, dieldrin,
metalochlor, 2,4 D, triclopyr, picloram and bromacil).
Deployment of and testing of appropriate
geostructural designs needs to take place across thevarious agricultural industries. It could be that a
porous geopolymer concrete in combination withbiochar is used in the design of subsurface of surface
structures. The potential for green or brown wastematerial derived biochar products, which could bereadily manufactured from farm refuse and manure,needs to be thoroughly investigated in this regard.
Surface runoff is managed by retention lagoons
facilitating water reuse on-farm. Loss ofcontaminated water via field deep drainage presents amuch tougher problem which up until now has notbeen satisfactorily addressed. The challenge forengineers is to come up with in-situ sub-surface
geostructural designs which are efficient, costeffective and which will be taken up and embraced byAustralian and world agribusiness.
REFERENCES[1] Pimentel, D 2002. Encyclopedia of Pest
Management. Vol 1. Marcel Dekker Inc. 02.
[2] Graham-Bryce, I.J., 1980. Physical Principles of
Pesticide Behaviour. Chapter Six – Behaviour of
Pesticides in Air. Academic Press, London[3] Craig I, Hewitt A and Terry H, 2014. Rotary
atomiser design requirements for optimum
pesticide application efficiency. Crop Protection(submitted).
[4] Henderson F and Croon F 2009. Overview of
CSIRO Water Quality Research in the Great
Barrier Reef 2003-2008. CSIRO:Water for a
Healthy Country National Research Flagship.
[5] Shaw M, Silburn DM, Thornton C, Robinson B
and McClymont D, 2011. Modelling Pesticide
Runoff from Paddocks in the Great Barrier Reef
Using Howleaky?.19th International Congress
on Modelling and Simulation.
[6] Carroll C, Waters D, Vardy S, Silburn DM,
Attard S, Thorburn PJ, Davis AM, 2012.
Paddock to Reef Monitoring and Modelling
Framework for the Great Barrier Reef: Paddock
and Catchment Component." Marine Pollution
Bulletin 65 (4–9) 136-49.
[7] Beesley L et al 2011. A review of biochar’s
potential role in the remediation, revegetation

457

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

AN EVALUATION MODEL OF MEDICAL TRANSPORT WITHTSUNAMI EARLY WARNING SYSTEM

Norimitsu Koike1, Susumu Kurahashi2
Department of Civil Engineering, Aichi Institute of Technology, Japan
2
Disaster Prevention Research Center, Aichi Institute of Technology, Japan
1

ABSTRACTThe Japanese Central Disaster Management Council announced a new damage estimate in the event of anearthquake with its epicenter in the Nankai Trough. The estimate shows the huge human damage. However, theymentioned the possibility of minimizing the casualty count by constant preparation for prompt evacuation tohigher places in the event of a tsunami. This study aims to develop a reliability analysis model for medicaltransport activity considering a tsunami risk. The model includes a risk evaluation model developed to evaluate
medical transport activity when a tsunami early warning system can be used. Our model is composed of theindices for those problems. By applying it to Chita Peninsula in Japan, it is demonstrated that the proposedmodel effectively implements the evacuation and medical transport planning. Some proposals are given for theroad network in the area.
Keywords: Risk management, Tsunami, Medical transport, Evacuation
There are many previous studies about theevacuation.
B.Wolshonpublishedtoacomprehensive review of evacuation plans of thearea affected by hurricanes. In this review, he
discussed the needs of emergency plan for special
needs and low mobility groups [3]. The medicaltransport planning for victims and patients fromview point of transport management may be needed.
This study aims to develop a reliability analysis
model for medical transport considering the tsunami
risk. The model includes a risk evaluation model
developed to evaluate medical transport when atsunami early warning system can be used. The
tsunami early warning system determines thepossibility of a tsunami by the seismic intensity andmagnitude of the earthquake at almost the same timeafter an earthquake. The system serves to draw
people’s attention to the risk of a tsunami. There are
two purposes of medical transport; one is a medical
evacuation from one high-risk place to a safer place.
Another is the emergency transport of injured tohospitals. Our model is composed of indices toevaluate such problems. Through applying them to
the Chita Peninsula in Japan, it is demonstrated thatthe proposed model effectively implements theevacuation and medical transport planning.

INTRODUCTION
The Japanese Central Disaster Management
Council recently announced a new damage estimate
in the event of an earthquake with its epicenter in the
Nankai Trough. The new estimate shows the hugehuman damage. However, they mentioned thepossibility of minimizing the casualty count byconstant preparation for prompt evacuation to higher
places in the event of a tsunami. In response to thissituation, many local tsunami evacuation plans havebeen reconsidered. Especially, the Tokai area ispointed out as a high tsunami risk area by the
Nankai trough.
After a large-scale disaster, medical transport isvery important for life-saving. D.Goldschmitt
conducted some phases of a medical disaster
response. First is the extrication. The purpose in thisphase is to get victims out of the hot zone and tosafety. Second is the filed triage. The victims areevaluated to determine their needs for medical
attention. The third is evacuation and transport. The
phase is to transport them to the definitive carelocation or the emergency departments of local
hospitals [1]. N.Koike et al. made an evaluation
model for the transport of victims in an airplane
accident in the third phase [2]. The model has been
made for serious incidents like airplane accidents.
The origin of the injured is one place just like anairport. In a large-scale disaster, however, many
places may be defined as the origin, and the injured
will be transported to some hospitals under the riskof a tsunami.

METHODOLOGY
Outline of proposed method
In the previous model, three risk factors were
proposed for reducing the risk of death. One is the458

GEOMATE- Brisbane, Nov. 19-21, 2014

left behind risk, which is an index to explain how
long the injured must wait for pickup at the injury
site. The second is the medical confusion risk, whichis indicated by the arrival interval. Major injured
persons are often brought to the hospital closest to
the incident site, and smooth medical service isdifficult. If they can be transported to a wider arrayof hospitals, the hospitals may accept a few injured
within their ability. The third is the transport risk
itself. It is the risk with a long transport time. As
convalescence of the injured may be determined bymany personal factors, it cannot be evaluated byonly an index such as lifesaving time limit. The
proposed indices are significant to compare somealternative plans.
For the evaluation of the medical transport with atsunami risk, the left behind risk is out of theconsideration. The problem is who and when will be
rescued from high-risk places. For their rescue, awarning system to assure their fast evacuation isimportant. Our proposed model has included
reducing the risk by improvement of the warning
system.

received information of a tsunami reaching in ornear the coast. This is certain information of thetsunami danger. And at the time “t3”, the tsunami iswithin sight, so people must escape to a safe place.
The perceived risk can be exchanged for the
probability of evacuation. Fig. 2 shows the relation
between the time distribution and probabilities forevacuation. If the improvement by the EEWS canprompt evacuation immediately, the distribution of
the probability of evacuating may shift to an earlytime. It will contribute to reduction of the number oftsunami victims.
Table 1 shows the evacuation ratio of people
from the tsunami risk area after an earthquake. Thisis estimated by the empirical data in Japan from theJapanese Central Disaster Management Council. The
estimation is considered to reflect people’s
awareness about the risk of tsunami. In Case A,
which is high awareness and effective warning, 70%of people can evacuate immediately, whereas only
20% of people can evacuate in Case C. It means theawareness and warning have a great influence on
evacuation behavior.

Medical risk indices
Reducing risk by the warning system
The best and unique countermeasure against atsunami attack is to evacuate from the coast.
However, it does not mean that all earthquakes cause
a huge tsunami. When a tsunami is expected tocause coastal damage, the Japan Meteorological
Agency (after this, JMA) issues a tsunami warningor advisory within 2-3 minutes after an earthquake.
The tsunami information is transmitted immediately
to disaster management organizations and media
outlets. However, the best countermeasure is forpeople to flee coastal areas immediately after anearthquake. But the time to check the informationfrom the government reduces the chance ofevacuation. In Japan, the early earthquake warning
system (after this, EEWS) is the earliest warning forthe earthquake disaster. Kurahashi et al. have beendeveloping early tsunami warning system used by
the EEWS magnitude. K.Iida pointed out theearthquake magnitude is related tsunami occurrence[4]. The system includes the equation proposed by
K.Iida. If the system can be put to practical use, thetsunami risk may well be reduced.
Fig. 1 shows an image between the time the riskof a tsunami is perceived and the time to reach atsunami after an earthquake. “t0” is the time
immediately after an earthquake. Time “t1” means
the timing of the tsunami alert by the JMA. The
perceived risk of tsunami will arise by the EEWS at
this period. The time “t2” involves a person who has

Fig. 1

Relation between time distribution andprobabilities of tsunami

Fig. 2 Relation between time distribution andprobabilities of evacuation

459

GEOMATE- Brisbane, Nov. 19-21, 2014

According to the above suppositions, theJapanese Central Disaster Management Council
makes detailed estimates of the number of tsunami
victims. The estimates show the numbers who
cannot escape from a tsunami and who fail to escapein time.
As the EEWS provides information to escape
immediately, it will reduce the number of victims
who fail to escape in time. The EEWS as indicatedby the present study will halve the number ofvictims who could not escape in time.

Second, the distance Dij is defined from origin
zones i to hospital j . Dmax is the farthest distancefrom all zones to the farthest hospital. As people try
to go to the nearest hospital, possibility to select thehospital can be defined as Fig.4.
We define the hospital select coefficient fromzone i to hospital j as follows;
(

) ⁄∑

(

)

(1)

The hospital select coefficient means thegravitation of the hospital j from zone i.
The Transport risk is written as follows;

Table 1

Evacuation ratio at the report by JapaneseCentral Disaster Management Council
(%)
Items
Evacuate
Evacuate Evacuation
immediately
less
as
after
quicking imminentearthquake
tsunamidangerCase A
70
30
0Case B
70
20
10
Case C
20
50
30
Case A: High rapid evacuation ratio and effective
warning
Case B: High rapid evacuation ratio.
Case C: Low rapid evacuation ratio.

TRij = Yij×Dij(2)

When many hospitals are located near thedamage area, the transport risk may be low, butwhen hospitals are far from the damage area, the risk
may be high.
This model calculates how many injured people
go to the hospital. However, the estimated numberof injured persons is uncertain. In this paper, therelative damage estimation at the zone i is defined asfollows;⁄∑(3)

Where Vi indicates human damage in the area i.
Although this index cannot show the absolute
number of injured persons, we can discuss thepriority of countermeasures for many injured.
Using the relative risk of human damage, themedical demand can be described with the hospital
select coefficient and the relative risk of humandamage.

The risk factors
Fig. 3 illustrates the medical conditions transport
after a tsunami. At first, people fail to escape andundergo injury. Second is the medical over-capacity
risk. Because some nearby hospitals must accept
many injured, those hospitals may be in disturbed
due to over-capacity. To avoid over-capacity, they
hope to transport to a nearby hospital, and are forced
to transport long distances. In addition, some nearby
routes cannot be used. This is the transport risk.

∑(4)

RHj: the medical over-capacity risk at hospital j
Ei: the relative risk of human damage at the zone i
If the ability of all hospitals is almost equal, theideal would be for the medical over-capacity risk
RHj to be dispersed around the hospitals.

Fig. 3 Risk of injured persons
Modeling
The model area is divided into some zones which
are set as the origin of medical transport.

Fig. 4 Relation between distance and possibility toselect the hospital j
460

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 5 Chita Peninsula road network and hospitals

Table 2 Hospital select coefficientArea
Hospital
A
B
C
D
E
F
G
H

Minamichita

Mihama

0.11
0.01
0.25
0.01
0.18
0.17
0.04
0.22

Taketoyo Tokoname

0.09
0.05
0.21
0.06
0.17
0.16
0.07
0.18

0.14
0.07
0.14
0.07
0.19
0.18
0.09
0.13

Handa

0.18
0.09
0.11
0.10
0.14
0.14
0.13
0.11

Agui

0.13
0.11
0.12
0.11
0.16
0.16
0.12
0.10

Higashiura

0.13
0.14
0.08
0.14
0.14
0.14
0.15
0.08

0.11
0.18
0.07
0.18
0.11
0.12
0.18
0.04

Obu
0.10
0.22
0.06
0.21
0.10
0.10
0.18
0.03

Tokai

Chita

0.12
0.22
0.06
0.22
0.08
0.10
0.19
0.03

0.14
0.18
0.05
0.19
0.08
0.11
0.20
0.06

Table 3 Transport risk
Area
Hospital
A
B
C
D
E
F
G
H

Total

Minami
chita
3.05
0.44
2.36
0.44
3.32
3.35
1.54
2.97
17.47

Mihama
2.17
1.66
0.09
1.68
1.56
1.60
1.95
1.21
11.92

Taketoyo Tokoname
1.58
1.79
1.49
1.80
0.13
0.33
1.93
1.71
10.76

Handa

0.22
1.94
1.89
1.92
1.56
1.53
1.67
1.90
12.63

461

1.62
1.82
1.78
1.81
1.03
0.90
1.71
1.90
12.56

Agui
1.57
1.52
1.90
1.51
1.43
1.49
1.33
1.89
12.63

Higashiura
2.47
1.96
2.07
1.95
2.48
2.50
1.95
1.50
16.89

Obu
2.54
1.46
1.91
1.63
2.49
2.57
2.36
0.95
15.91

Tokai

Chita

2.29
0.30
1.70
0.24
2.15
2.26
1.27
0.91
11.12

2.03
1.32
1.56
0.88
2.04
2.21
0.53
1.73
12.29

Toatal
19.55
14.22
16.74
13.88
18.18
18.73
16.23
16.67

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 4 Medical over-capacity risk
Area
Hospital
A
B
C
D
E
F
G
H

Relative Riskof humandamageMinamichita

MihamaTaketoyo Tokoname

Handa

Agui

Higashiura

Oubu

Tokai

Chita

0.04
0.00
0.09
0.00
0.07
0.06
0.02
0.08

0.01
0.01
0.02
0.01
0.02
0.02
0.01
0.02

0.01
0.00
0.01
0.00
0.01
0.01
0.01
0.01

0.02
0.01
0.01
0.01
0.02
0.02
0.02
0.01

0.02
0.02
0.02
0.02
0.03
0.03
0.02
0.02

0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

0.00
0.01
0.00
0.01
0.00
0.00
0.01
0.00

0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

0.01
0.01
0.00
0.01
0.00
0.00
0.01
0.00

0.01
0.01
0.00
0.01
0.00
0.01
0.01
0.00

0.37

0.10

0.06

0.13

0.16

0.03

0.03

0.02

0.05

0.05

Higashiura

Oubu

Tokai

Chita

Total
0.13
0.08
0.17
0.08
0.16
0.15
0.10
0.14

Table 5 Medical over-capacity risk of proposed system
Area
Hospital
A
B
C
D
E
F
G
H

Relateive Riskof humandamage(improvemnt)

Minamichita

MihamaTaketoyo Tokoname

Handa

Agui

0.03
0.00
0.08
0.00
0.05
0.05
0.01
0.07

0.01
0.01
0.02
0.01
0.02
0.02
0.01
0.02

0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01

0.03
0.01
0.02
0.01
0.02
0.02
0.02
0.01

0.02
0.02
0.02
0.02
0.03
0.03
0.02
0.02

0.00
0.01
0.00
0.01
0.01
0.01
0.01
0.00

0.00
0.01
0.00
0.01
0.00
0.00
0.01
0.00

0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

0.01
0.01
0.00
0.01
0.00
0.01
0.01
0.00

0.01
0.01
0.00
0.01
0.00
0.01
0.01
0.00

0.30

0.11

0.07

0.14

0.18

0.04

0.04

0.02

0.05

0.05

Total
0.13
0.08
0.16
0.09
0.15
0.15
0.10
0.14

area.
Table 4 denotes the medical over-capacity risk.
Because much human damage by tsunami attack isestimated, Minamichita is a high-risk area for humandamage. Many people will go to hospital C from the
Minamichita area.
Table 5 shows the medical over-capacity risk
with the EEWS improvement. The relative risk ofhuman damage is changed with the decreasing
number of tsunami victims. For example, the relativerisk of Minamichita goes down from 0.37 to 0.30.
On the other hand, the relative risk of the Handa area
increases from 0.16 to 0.18. It does not mean that thevictims in the Handa area increase, but the victim
ratio goes up. The total injured number of people
will decrease. Comparing both cases, the medical
over-capacity risk of some hospitals is changed.
Because of decreasing the relative risk of humandamage of the Minamichita area, the medical overcapacity risk of hospital C decreases.
Table 6 shows the result of the medical overcapacity risk and the ratio of bed number. We referto the bed number as the scale index of hospitals.
Comparing with the results and ratio of bed number,the medical over-capacity risk of hospital C, E, F
and H are higher than the ratio of bed number,whereas the hospital A, B, D and G are lower.
Although those hospitals have many beds, they arelocated far from the high-risk area.

CASE STUDY
Case study area
We have applied our model to the Chita
Peninsula in Central Japan with its population of
about 40 million. The administrative district is 10
blocks. There are 8 emergency hospitals. There is ahigh-risk area by tsunami attack in an earthquakewith its epicenter in the Nankai Trough. Fig. 5
shows the road network from the city or town office
to the emergency hospitals in Chita Peninsula. Dmax
is 40.9 km.
Results
Table 2 shows the results of the hospital selectcoefficient Yij. For example, 25% of the people in
the Minamichita area will go to hospital C. On theother hand, hospital B and D are far from the
Minamichita area. Most people will not go tohospital B and D.
Table 3 shows the result of the transport risk.
Minamichita has the highest transport risk. Because
Minamichita is located in the southeast of the Chita
Peninsula, many hospitals are far from the area.
Hospital A has the highest transport risk. Because
hospital A is located at the center of the Chita
Peninsula, many people may come from all over the462

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 6 Medical over-capacity risk and ratio of
bed number
Case
Ratio of bed
NormalImprove
numberHospital
A
0.13
0.13
0.16
B
0.08
0.08
0.15
C
0.17
0.16
0.15
D
0.08
0.09
0.18
E
0.16
0.15
0.08
F
0.15
0.15
0.04
G
0.10
0.10
0.18
H
0.14
0.14
0.07
1.00
1.00
1.00

CONCLUSION
This study proposed a reliability analysis modelfor the medical transport activity considering thetsunami risk. The model includes a risk evaluation
model to evaluate medical transport activity when
the tsunami early warning system can be used. Ourmodel is composed of evaluation indices for those
problems.
Through applying it to the Chita Peninsula inJapan, the proposal model serves to implement theevacuation and medical transport planning.
Because we set the relative risk of humandamage in our model, we cannot compare theabsolute number of injured persons between thenormal and the improvement case. If detailed data of
estimate number about of the human damage areavailable, we can evaluate the acceptable number ofhospitals and the number of injured peple.

DISCUSSION
We can observe the difference in the medical
over-capacity risk for the normal and the EEWS
warning situation. Especially, the medical overcapacity risk of some hospitals located near thewater decreases. The improvement of initial
behavior will avoid the over-capacity in theparticular hospital.
The transport risk is shown for each zone andhospital. In addition, the medical over-capacity risk
is not in proportion to the scale of the hospitals. It
needs countermeasures for the high-risk zones andhospitals. For example, if the medical ability of thehospitals near the water is reinforced, the injured can
avoid transport for a long time. The hospital selectcoefficient Yij is only decided by the distance Dij. In
future, one should consider how to select thehospital by a questionnaire survey.
In this paper, we presumed that all roads can beused. However, some road may be in fact damagedby the seismic and tsunami attack. If we set the
scenarios of the road damage, this model can apply
to evaluate the road network.

ACKNOWLEDGEMENTS
This research was partly funded by the Grantsin-Aid for Scientific Research <KAKENHI>(No.24590641).
REFERENCES[1] David Goldschmitt; “Progression of disastercare”, Medical Disaster response, CRC press,
2009, pp.145-162.
[2] Norimitsu Koike, Eizo Hideshima, Koshi
Yamamoto, Toshihide Fukai; “Study on
reliability analysis model for transport of the
injured at airplane accident,” in Proc. Int. Conf.
on ICTTS, Vol. 2, 2002, pp. 1047–1054.
[3] Brian Wolshon; The role of transportation in
evacuation and reentry: A survey of practice,
Journal of transpotation and safety &security,Vol.1, 2009, pp.224-240.
[4] Kumizi IIDA; Magnitude and energy ofearthquakes accompanied by tsunami, andtsunami energy, Journal of Earth Sciences,
Nagoya Univ. 1958, pp.101-112.

463)Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

SEASONAL VARIATION OF THE ALIEN PLANTS INVASION INTO
RIVER ECOSYSTEM

1Michiko Masuda1 and Fumitake Nishimura2
Department of Civil Engineering, Nagoya Institute of Technology, Japan; 2, Department of Environment
Engineering, Kyoto University, Japan

ABSTRACT
Many alien species have invaded into fluvial environment. The invasion of alien species affect seriously
damages to the biological diversity. Authors pointed out that invasion of alien plants is mainly occurred inspring, and recommended that the improvement of river environment should be done from summer to autumn inorder for prevent invasion of alien species. However, there is little report about the phenomenon when the
improvement of river was occurred from summer to autumn. So we investigated how the vegetation recovered at
the improvement river area with no burial seeds in summer. During the investigation we removed all emerging
seedlings in the half of the investigation area and always kept as the bare ground. As a result four of thefollowing became clear, 1) seedlings of alien species could not easily invade bared area in summer, 2) only someseedlings of a few native species can be established in summer, 3) the vegetation by native species that recoveredin summer prevented the invasion of alien species, 4) seedling removal hasten the invasion of alien species. The
character that the seeds are able to emerge anytime and anywhere like the alien plants species are advantageousat the fluvial environment where rising of the river sometimes occurs. But the condition of river bed in summer
is too severe to invade open area. Only a few native species can established their seedlings.
Keywords: Four or Five Keywords (First Characters of Each Word are in Capital/Uppercase Letters), Italic

river ecosystem about alien plants seedlings invasion
in bared land in summer.
The Ministry of Land, Infrastructure andTransport experimentally restored the old fluvial
environment consist of round pebbles using ‘Natureoriented river works’ Toki river at central Japan.
There were seeds of Sicyos angulatus, the species
notorious alien species, in this area. So to recover
the rich biodiversity of the river, all the surface soil
and pebbles were washed in order to remove theburial seeds and installed there in 2010. The
construction was finished in early summer
fortunately. Then, we investigated how the invasionof alien plants in summer to autumn was done in the“Nature oriented river work”. 1) Is there few alienplant species invasion compared native species insummer construction? 2) What kind of plant species
invasion trespasses upon bared ground from summer
to autumn? 3) Is the alien plants affect the nativeplant succession? It was paid attention to these threepoints, and analyzed.

INTRODUCTION
The weed risk assessment (WRA) has been paid
attention as a risk evaluation system of the species
before alien species intentionally introduces into
Japan. In Australia the operation results of the WRA
system have exceeded twenty years [1]. Because thedamage of the exoticism to biodiversity has become
the largest problem worldwide, the WRA begins to
be used also in Japan [2]. In the WRA, there is acheck item concerning the item concerning acharacter of ruderal strategy. Actually, the invasionof alien species with ruderal strategy has become abig problem in Japan.
Now, the vegetation of the fluvial environments
has been seriously affected by alien plants. In theriver ecosystem the bare land is formed frequently
by flood. The alien ruderal species easily invade thebare land faster than native species do [3]. The
invasion of an alien plants have been diminishing
the biodiversity at the river condition. Especially, thealien plant that invades the fluvial environment
brought in to Japan by the seed medium. Therefore,
genetic diversity is very high which adjusts easily tothe each invading environment [4].
The authors reported that the strategy of alienplants has longtime seedlings emergence in spring inprevious paper [5]. There we also suggested that theconstruction of river ecosystem should be finishedduring summer. But there is few seasonal research in

MATERIALS AND METHODSThe Study site
The study was carried out on a left bank of theToki River at Miyamae, Tajimi City (35o 33’ 56’’N,
137o 12’ 92’’E, altitude 96.6 m). Toki river is a464

GEOMATE- Brisbane, Nov. 19-21, 2014

upper river in the Shonai River water system of theextension 23km and 115 km2 in the valley area.
Because this river region had frequently received theflood damage, bank repair and a river dredge arecontinuing.
At the study area, the restoration of old fluvial
environment was finished in 2010. The environment
condition is a place of the old natural environmental
condition without dam controls. This place isconsists of round pebbles without burial seeds. And
in order to everyone can easily access the river flow
and enjoy nature condition, the loose inclination atlower riverbed is designed.

been prepared by germinating the collected seeds
under laboratory conditions. The recorded seedlings
were checked by pigment ink. Census was carriedout from June 30’2010 to Apr 24’2011 at every
week intervals. Unidentifiable seedlings constituted
only less than 0.1% of the total seedlings recorded
during the study period except grass family. Using
this data, it was compared the duration of seedlingemergence between alien and native plants by
Mann-Whiteney test.
RESULTSIn the census, we observed a total of 41 nativeplant species and 26 alien species. The number of
species observed that emerging in each season ateach treatment area showed in Table 1. In spring
there are sometimes hard rain fall in the census area
and we cannot count the seedling number exactly
because hard rainfalls had flowed out seedlings. The
number of native species is larger than that of alien
species in each condition, treatment and seasons
except for spring. The observed number of species islower in summer in all area. But the number ofnative species is larger than that of alien species andthe number of summer emergence species is smaller
than that of autumn.

Seedling emergence census
The restoration was done in the investigation
place at June in 2010, where all the buried seeds
were removed from the soil within 1m in depth. For
seedling emergence census, 20 quadrats (1 x 1m)
were set at 20m in higher bed part, medium part andwaterside part on the hydrophilicity shore protection
slope, each interval is 1m. The total area was 60m2
(Fig 1, 2). Two treatments were done in each quadrat,
one is seedling remained and the other is seedlingremoval. Two treatments were arranged like acheckerboard.
NhigherTable I. The number of species observed thatemerging in each season at each treatmentarea. Native species normal exhibit and(alien species).
Sum. Autumn. Win.
Spr.
HigherRemoved12 (8) 23 (16)
10 (7) 3 (2)No treat13 (7) 23 (17)
1 (2) 0 (0)MediumRemoved10 (2) 21 (17)
4 (6) 0 (0)No treat6 (1) 16 (15)
1 (1) 1 (0)Water side
Removed13 (7) 29 (16)
5 (5) 0 (0)No treat11 (8) 37 (22)0 (1) 0 (1)medium1m

waterside
Toki river stream
Removed area

Fig. 1

Fig. 2

Non-treatment area

The investigation areas map.

The duration of emergence in summer andautumn at each plot showed in Fig. 3 and 4 (moreprecisely data showed in Appendix 1-3). There werelarge differences observed the duration of
emergence between native species and alien species
in summer (Fig. 3). The duration of alien species
seedling emergence was shorter than that of native
species. Especially in medium plots alien species
emergence were observed at one week, thoughnative species emerged from one week to 5 weeks.
In all area seedlings of Digitaria ciliaris, Setaria
viridis and Cyperus sp were observed from 3 to 5
weeks, and a large number seedling emergenceobserved. In autumn, there was few differences

The condition of investigation areas in June
23’2010.

The species of emerging seedlings was identified
by comparison with the seedling specimen that had
465

GEOMATE- Brisbane, Nov. 19-21, 2014

native-R
native-C
alien-R
alien-Ca)50

Number of species

10

2

3

4

5

6

7

1

5

0

Number of species

10

2

3

4

5

6

7

8

2

3

4

5

6

7

8

10

b)

5

0
1

2

3

4

5

6

7

8<

c)
20

5

0
1

Fig. 3

0

8

b)

1

native-R
native-C
alien-R
alien-C

5

Number of species

1

a)

10
Number of species

10

in highest riverbed and waterside are longer those ofalien species. In medium water condition plots there
were only two alien species seedling emergenceobserved, so we cannot use this test, but alien
seedling emergences were observed once time only.
In autumn at control area of highest riverbed andmedium water level there were differences between
native species and alien species. But other condition
there was no differences observed.

Number of species

Number of species

about seedling emergence duration between alien
species and native species, but the longest seedlingemergence were native species, Eleusine indica,
Cardamine scutata and Digitaria ciliaris, in somearea (Fig. 4). In removed area in autumn, durationsof seedling emergence were longer than those of notreatment area. In alien species, Cerastium
glomeratum, Oenothera erythrosepala, Eragrostis
curvula and Mollugo pentapylla, long durations ofautumn seedling emergence were observed.

2 3 4 5 6 7 8Duration of emergence (week)
The histogram of observed summer
seedling emergence the durations. a) is thehigher bed part, b) is the medium part, c) is
the water side part. native-R is native
species observed in removed area, native-C
is native species observed in control area,
alien-R is alien species in removed area,
and alien-C is alien species in controlled
area.

c)

15

10

5

0
1
Fig. 4Mann-Whitney statistical tests were performed to
examine the presence of differences in the durationof seedling emergence among native species andalien species at each season (Table II). In summer,
the duration of seedling emergence of native species466

2 3 4 5 6 7 8<
Duration of emergence (week)

The histogram of observed autumn seedlingemergence the durations. a) is the higher
bed part, b) is the medium part, c) is thewater side part. native-R is native species
observed in removed area, native-C isnative species observed in control area,
alien-R is alien species in removed area,
and alien-C is alien species in controlledarea.

GEOMATE- Brisbane, Nov. 19-21, 2014

Table II. The result of the Mann-Whitney U test for
duration of seedling emergence of co-occurring
native species vs alien species in different moist
level plots.
seasonMoist level Removed
Control
Summerhighest**mediumwater side****
AutumnhighestN. S.
*
mediumN. S.
*
water side
N. S.
N. S.
*; p<0.05, ***; p<0.001; N. S. means nonsignificant.

of vegetation cover is more serious in alien species
than native species.
It is continuing being said that removal of thealien species in fluvial environment is very difficult[11][12]. However, it was shown by our researchfindings in the summer that invasion of alien species
was prevented. Moreover, if occupied by native
species in a summer, alien species will become
difficult to invade even if autumn condition. In orderto press down invasion of alien species, construction
plan in which an open space should be made to form
in a summer is required. However although only
Mollugo verticillata was a small number, it was able
to invade into the fluvial environment of the summer.
For this reason, in order to press down invasion of M.
verticillata, it is thought that another technique isimportant.

DISCUSSION
Invasion of alien species into some areas has had
a devastating impact on the native biodiversity [6][8]. Native species most vulnerable to the impact ofalien species invasions are those which have evolved
in isolation from high levels of competition.
Especially the invasion of alien species in the river
system, where continuous disturbance of eachrainfall occurred, is the serious problem [9]. In orderto manage the alien species Ministry of Land,
Infrastructure and Transport has constructed many
biotopes in river ecosystem. They removed burial
seeds and vegetation of alien plants from theconstruction area, but the open areas are
immediately occupied by alien species [10]. Fromthe investigation of another biotope area [5], thealien plants invasion mainly occurred in spring, andthere is rarely invasion in summer season. Then if
the construction is finished in summer, alien
invasion prevented by severe hot condition?
In our research the method to prevent alien
species invasion is cleared. In summer more 10
native species can emerge in open area at severe
condition, but there are few alien species occurred.
And the number of alien seedling was very few,
moreover the survival rate of seedling in very low.
But some native species survived in severe
conditions, the number of native species seedling islarge, and establishment of vegetation cover can
successful. Bared land in summer can easily preventthe alien species invasion. Only Mollugo verticillata
is exception, they can emerge and survive in summer
although there are few numbers (totally 10 seedlingsin higher river bed area).
In autumn there is few differences in seedlingemergence duration between native and alien
species, both species emerged longer than that insummer. But some occupied vegetation effectobserved. The prevention of alien invasion wasobserved in non-removed area. It seems there is nobared space where seedlings can emerge. The effect

CONCLUSION
The following conclusions are drawn based on
the study:1) seedlings of alien species could not easily invade
bared area in summer, 2) only some seedlings of afew native species can be established at theinvestigated area in summer, 3) the vegetation by
native species that recovered in summer prevented
the invasion of alien species, 4) seedling removal
hasten the invasion of alien species.
ACKNOWLEDGEMENTS
We wish to thank the member of Ministry ofLand, Infrastructure and Transport Shonai River
Office and Tokigawa Nature Observation Office forresearch support and permission to work in the river.
We also thank the members of our laboratory for
their assistance in the field works.
REFERENCES[1] Pheloug PC, Williams PA, Halloy SR, “A weed
risk assessment model for use as a biosecurity
tool evaluating plant introduction,” Journal ofEnvironmental Management, vol. 57, 1999, pp.
239-251.
[2] Nishida T, “Weed risk assessment-mainly inAustralia and New Zealand,” Ecology ofAgriculture and Weed, Plant Species Biology
Society, Ed. Bunichisogo, 2007, pp.121-136.
[3] Imahashi M, Washitani I, “Examination of
possibility of a river flood meadow restorationthat uses seed bank,” Conservation Ecology
Research, vol. 1, 1996, pp.145-146.
[4] Masuda M, “Invasion of alien plant: Status ofCoreopsis lanceolata L. in Japan,” Annual467

GEOMATE- Brisbane, Nov. 19-21, 2014

Journal of Engineering, Ehime University, vol.
21, Mar. 2000, pp.245-251.
[5] Masuda M. Ito Y, Nishimura F, “Process of
invading the alien plant species into the river
ecosystem”, in Proc. first Int. Conf. on
GEOMAT, 2011, pp.437-442.
[6] Pullin AS, Conservation Biology. New York:
Cambridge University Press, 2002, ch. 5.
[7] Groom MJ, Meffe GK, Carroll CR, Principles
of Conservation Biology 3rd ed. Sunderland:
Sinauer, 2005, ch. 8.
[8] Primak RB, Essentials of Conservation Biology
5th ed. Sunderland: Sinauer, 2010, ch. 10.
[9] Myers JH, Bazely DR, Ecology and control of
introduced plants. Cambridge: United Kingdom
at the University Press, 2003, ch. 5.

[10] Ministry of Environment, List of regulated
living organisms under the Invasive alien
species act, Tokyo: materials of Ministry ofEnvironment, 2011.
[11] Muranaka T, Washitani I, “The population
expansion predicted by a simulation model of
an invasive alien species, Eragrostis curvula, in
a middle-reach floodplain”, Japanese Journal ofConservation Ecology, Vol. 8, 2003, pp. 51-62.
[12] Hatase Y, Oguri H, Matsue M, “Restoration
effect of topsoil removal on the herbaceous
community invaded by Coreopsis lanceolata inthe vegetation of dry gravel”, JapaneseLandscape research, Vol. 75, 2012, pp. 445-450.

468

GEOMATE- Brisbane, Nov. 19-21, 2014

469

GEOMATE- Brisbane, Nov. 19-21, 2014

470

GEOMATE- Brisbane, Nov. 19-21, 2014471

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

LANDFILL WASTE WATER TREATMENT BY PULSEDDISCHARGE IN WATER DROPLET SPRAY
Akio Takigawa1, Keiichi Kato1, Takashi Nakajima1, Ryota Serizawa1 and Hiromu Tamba1
1Department of Civil and Environmental Engineering, Maebashi Institute of Technology,
460-01,Kamisatory-cho, Maebashi, Gunma, 371-0816, Japan
ABSTRACTIn this study, using the plasma generated from the pulsed discharge process, we examined the possibilityof simultaneous degradations of dye substance and COD component in the landfill waste water. Furthermore,
the possibility of sterilization by the plasma was investigated in the experiments. Experiments were performed
to investigate the effects of voltage, repetition rate, charging time and O2 coexistence on the sterilization anddegradations of COD and dye substance. The experimental results show that the sterilization and simultaneous
degradations of the dye substance and COD are possible by the plasma and the dye substance is easily
decomposed by the plasma from COD. The degradations of the dye substance and COD were enhanced by thepresence of O 2, while the effect on the dye substance degradation is larger than COD degradation. The results
reveal that sterilization is possible by plasma, and E. coli is completely dead as compared with the bacteria isdifficult to kill completely by the plasma.
Keywords: Landfill Waste Water, Plasma, COD, Dye Substance, Sterilization
1.

INDRODUCTION

Many of the common final disposal site in Japan,
non-combustible residue and ash comprised
incineration of waste are mainly reclaimed. Many
contaminants, such as SS, BOD, COD, dye substance,
nitrogen content and salts etc. are contained in theeffluent of these landfills [1]-[2]. In many disposalsites, the BOD value of the water meet the water
quality standard value, but the COD does not reach
the water quality standard value in many cases. The
factor of COD component is dye substance, such as
humic acid, fulvic acid etc.. These substances are
difficult to decompose biologically, as so-called
non-biodegradable organic matter.
Currently, landfill waste water treatment has
been used physical treatment and biologicaltreatment. However, biological treatments there are
the following problems. That are, the processing time
is long, the maintenance of micro-organisms isdifficult, and can be not respond to change
long-term leaching of water quality. Physicaltreatment methods commonly use aggregation,
precipitation method etc., but there are the problemsof sludge generation and high cost required toprocess.
In this study, using the plasma generated fromthe pulsed discharge process, we examined thepossibility of simultaneous degradations of dye
substance and COD component in the landfill waste
water. Furthermore, the possibility of sterilization by
the plasma was also investigated in the experiments.
The pulsed discharges produce ozone, free radicals,
ultraviolet radiation, and shockwaves in water, andcan be utilized for a more effective water treatment[3]-[5].

472

Since the breakdown voltage in water is much higher
than that in air, a large power supply and expensive
pulse forming network are required. In this study, apulsed discharge reactor is used to produce plasma ingas phase and wastewater is sprayed into the plasma
for treatment. This system combines the advantage ofusing small, simple, and inexpensive power supply
and pulse forming network for electrical discharges
in air and directly utilizing ozone, as well as free
radicals and ultraviolet radiations for treating thewastewater.
The experiments reported here were designed toinvestigate the effects of charging voltage, repetition
rate, discharging time and O2 coexistence on thesterilization and degradations of COD and dye
substance.
2.

EXPERIMENTS

The experimental apparatus is shown in fig.1.
The apparatus is combined of pulsed power generator,
pump, O2 cylinder, electrode and oscilloscope. The
discharge chamber comprised of parallel electrodes
enclosedinavinyl
chloridecontainer(140mm×140mm×350mm). The size of frog
electrode is 80mm in length, a width of 60mm, 12mm needle length is fixed to equal 72 present on thesurface. The plate electrode is made of stainless steel
and sizes of width and length are 60mm, 80mm
respectively. A showerhead for injecting droplets into
the chamber is set at the lower part in the chamber.
The experiments were carried out by using the real
landfill waste water in this study. Waste water issprayed into the reactor from a showerhead at a flowrate of 180ml/min. The sprayed water solution iscollected in a container connected to the reactor andGEOMATE-Brisbane, Nov. 19-21, 2014is circulated to the reactor by a pump

5

42

80

0.5

6

42

100

0

7

42

100

0.1

8

42

100

0.25

9

42

100

0.5

COD:366mg/ℓ, capacity:500mℓ
flow rate:180mℓ/min, cromaticity:1200°
Table 2 Experimental conditions
No. Voltage(kV)

Fig.1 Schematic diagram of the experimental
apparatus

Repetition rate

O2

(pps)

(ℓ/min)

A

35

65

0

B

35

80

0

C

35

100

0

E

40

50

0

F

40

50

0.5

G

40

50

1

E. coli :97CFU/ml,
capcity:500mℓ
flow rate:220mℓ/min, bacteria:115CFU/ml
Discharging power varies with the changes ofrepetition rate and charging voltage. The sterilizationand degradations of COD and dye substance were
examined for the various discharging power and O2
coexistence (table 1). The effects of O2 presence andreptition ratio on the sterilization was also examinedin this experiment (table 2). The ratio of
decolorization of dye substance was measured with a
UV and visible-light absorption spectrometer(Shimadzu, Uvmini-1240). The concentration of
COD was measured with a CODMn and E. coli andbacteria were measured with DD chiekka-(Asone).

Fig.2 Typical waveforms of pulse voltage anddischarge current.
The voltage and current are observed by an
oscilloscope (Iwatsu, DS-5110) via a 1/1000 highvoltage probe (North Star, PVM-2), a 0.1V/A current
probe (Person, 6600).

3.

3.1 Effects of repetition rate and charging voltage
on the ratios of COD decomposition anddecolorization

Table 1 Experimental conditions
No. Voltage(kV)

Repetition rate
(pps)

The pulse energy changes with the changes ofrepetition rate and charging voltage and current.
Fig.3 shows the effect of charging voltage on theratios of COD decomposition and decolorization.
When increasing the charging time from 0min to
30min, the COD decomposition ratios increases from
0% to 2%, 2%, 29% for the charging voltages of
32kV, 37kV and 42kV respectively. The COD
decomposition ratios increase to 7%, 14% with the

O2(ℓ/min)

1

32

100

0.5

2

37

100

0.5

3

42

100

0.5

4

42

65

0.5

RESULTS AND DISCUSSION

473

GEOMATE-Brisbane, Nov. 19-21, 2014change of the charging time from 30 to 120minutes
at the charging voltages of 32kV, 37kV, respectively.
However, at the charging voltage of 42kV, the COD
decomposition ratio increases from 29 to 36% in thesame charging time. These results show that a
constant voltage is required for the degradation of
COD components by plasma. The results carried out
at the charging voltage of 42kV also show that thecomponent of COD can be roughly divided in toindecomposable component and easily decomposable
component. The easily decomposable component is
decomposed in the initial treatment time and theindecomposable component remains in the processlate. The ratio of decolorization increases with theincreases of charging time and voltage. Whenincreasing the charging time from 0min to 120min,

decomposition and decolorization shows thatsimultaneous degradation of the dye substance and
COD are possible by the plasma and the dye
substance is easily decomposed by the plasma from
COD. Fig.4 shows the effect of repetition rate on theratios of COD decomposition and40
COD decompositin ratio (%)

35
30
25
20

35

65(pps)1080(pps)5100(pps)

0

30
25

32kV

20

37kV

15

42kV

10
5
0

30
60
90
Chaging time (min)

120

32kV
37kV

Decolorization ratio (%)

100
90
80
70
60
50
40
30
20
10
0

0

30
60
90
Charging time (min)

30
60
90
Charging time (min)120

65(pps)80(pps)100(pps)

30
60
90
120
Charging time (min)Fig.4 Effect of repetition rate on the ratios of COD
decomposition and decolorization

42kV

0

100
90
80
70
60
50
40
30
20
10
0

0

Decolorization ratio (%)

COD decompositio ratio (%)

40

15

120

Fig.3 Effect of charging voltage on the ratios of COD
decomposition and decolorization
the ratio of decolorization increases from 0% to 82 %at the charging voltage of 42kV. This maximum
decolorization ratio of 82 % is much higher than thatfor the maximum decolorization ratio of 35% at the
charging voltage of 32kV. Comparison of the effectof charging voltage on the ratios of COD

0decolorization. As the repetition rate of the applied
voltage increases from 65 to 100 pps, thedecomposition ratio of COD increase 8% in therange of the charging time, however, the variation indecolorization ratio show similar tendency for thechange of the repetition rate from 65 to 100pps.
These results show that the COD decomposition ratio
is affected by the increase in the repetition tare andthe decolorization is not affected by most to changes
in the repetition rate.
3.2 Effect of O2 coexistence on the ratios of COD
decomposition and decolorization
Fig.5 shows the effect of O2 coexistence on theratios of COD decomposition and decolorization at
the charging voltage of 42kV and repetition rate of474

GEOMATE-Brisbane, Nov. 19-21, 2014(4).
HO + HO → H2O2
Comparison of the effect of O2 flow rate on theratios of COD decomposition and decolorizationshows that the O2 coexistence enhances
decomposition rates of COD and dye substance by
the generate O and O3, and effect of O2 coexistenceon the decolorization is higher than that
decomposition of COD.

100 pps for the variation of O2 gas flow from 0 to
0.5ℓ/min. When increasing the charging time from 0
to 120 minutes at the O2 gas flow of 0ℓ/min, the0ℓ/min0.5ℓ/min3530

0.25ℓ/min25

3.3 The possibility of sterilization in the landfill
waste water treatment by the plasma

20
15
10
5
0

30
60
90
Charging time (min)

120

140

Decolorization ratio (%)

100
90
80
70
60
50
40
30
20
10
0

0

Fig.6 shows the experimental results carried out
in the experimental condition 2, which investigatedthe possibility of sterilization in the landfill waste
water treatment by the pulasma. It can be seen fromthe figure that the charging time over 20minutes,
the survival ratio of E. coli is 0%, and bacteria
survived even 60 minutes. In addition, whenincreasing the charging time from 0 to 60minutes,
the survival ratio of bacteria is lower at theA

120
0ℓ/min0.25ℓ/min
0.5ℓ/min
0

30
60
90
Charging time (min)B

100

CFU/min(mi)COD decompositin ratio (%)

40

120

80

C

60

E

40

F

20

G

0

Fig.5 Effect of O2 coexistence on the ratios of COD
decomposition and decolorization

0

10

140

decomposition ratio of COD increases from 0 to 5%.
However, The decomposition ratio of COD increases
from 0 to 36% as the increasing of O2 gas flow rate 0
to 0.5ℓ/min. This means that the variation of the O2
gas flow rate from 0 to 0.5ℓ/min results in theincrease of 31% of the COD decomposition ratio.
On the other hand, when increasing the charging timefrom 0 to 120 minutes at the O2 gas flow rate of 0ℓ/min, the decolorization ratio increases from 0 to
50 %. When increasing the O2 gas flow from 0 to 0.5ℓ/min, the maximum decolorization ratio increases
from 50 to 82%. A basic mechanism of non-thermal
plasma in electrical discharge processing for thetreatment of wastewater is considered to be theformation of a strong electric field and strong
non-thermal plasma where high-energy collisions ofmolecules with electrons generate various active
species such as OH, O, H, O3, etc.
+ e → 2O + e(1)O2
H2O + e → HO + H + e (2)(3)
O+ O 2 → O3

120
CFU/min)100

20 30 40 50
Charging time (min)

60

A

B

C

E

F

G

20 30 40 50
Charging time (min)

60

70

80
60
40
20
0

0

10

70

Fig.6 The effect of sterilization by using plasma
experimental conditions of A and F than that theother experimental conditions . These results indicatethat the bacteria are difficult to kill by plasmacompletely and survival ratio was affected by thechanges of repetition rate and O2 gas flow rate.

475

GEOMATE-Brisbane, Nov. 19-21, 2014

4.

CONCLUSIONSThe effects of the repetition rate, charging
voltage and O2 coexistence on the ratios of COD
decomposition and decolorization have been
investigated by pulsed discharge in water droplet
spray. The comparisons of the experimental results
have clarified that the sterilization and simultaneous
degradations of the dye substance and COD are
possible by the plasma and the dye substance iseasily decomposed by the plasma from COD. The
degradations of the dye substance and COD wereenhanced by the presence of O2, while the effect on
the dye substance degradation is larger than COD
degradation. The effects of repetition rate and O2
coexistence on the sterilization has also investigated.
It was found that sterilization is possible by theplasma, and E. coli is completely dead as comparedwith the bacteria is difficult to kill completely by theplasma.
5.

REFERENCES[1] Toji A, “Latest trend and introduction examples
for leachate treatment”, J.of Computer Science,
Vol.31, 2008,pp.21-25.
[2] Ishigaki T, Yamada M, “Property and treatment oflandfill leachate in the world”, J.of Computer
Science, Vol.31, 2008,pp.26-30.
[3] Nose T, Yokoyama Y, Nakamura A, Minamitani Y,“Effect of oxygen gas on the decomposition ofdye by pulsed discharge in water droplet spray”,
The Institute of Electrical Engineers of Japan,
Vol.131, 2011, pp.659-664.
[4] Willberg D M, Lang PS, Hochemer RH, Kratel A,
Hoffmann MR, “Degradation of 4-chlorophenol,
3,4-dichloroaniline, and an electrohydraulicdischarge reactor”, Environ. Sci. Technol. Vol.30,
1996, pp.2526-32534.
[5] Clements J.S, Sato M, “ Preliminary investigationof prebreakdown phenomena and chemical
reactions using a pulsed high-voltage discharge
in water”, Vol. IA-23, 1987, pp. 224-235.

476

CHALLENGING FACTORS IN THE IMPLEMENTATION OF GREEN
BUILDINGS IN MALAYSIA
Che Musa Che Omar, Hooman Abadi, Kamarusin Moh Noor
University Kuala Lumpur Business School (UniKL BiS), Kuala Lumpur, Malaysia

ABSTRACTGreen building is the foundation of the sustainable construction development. Green building is redefining
building practice and Malaysia is poised for early adoption in recondition of the potential economic andenvironmental benefits that accrue to it. The Malaysia government has played a strong role in ensuring environment
sustainability by way of introducing necessary polices and implementing them. It has resulted in the promotionof green technology that presents the most viable way of meeting with the new green-related activities
for environment conservation. In this research , the despondence were randomly selected from the professionalsof Malaysian green building index (GBI) and the method applied for collecting data is questionnaire survey.
All the questionnaires were sent out to the respondents manually or through e-mail. A total of 800 setsof questionnaire were sent out of 260 questionnaire were received based on krejcie& morgan table.
The quantitative method was used for analyzing data through SPSS 19. Based on the results, the level of developing
green building in Malaysia is not satisfied and government has a key role in the development of green buildingsin Malaysia according to GBI. The main barriers can be listed as: deficiency of knowledge and skills, second lackof specific rules and regulations, third lack among of awareness and commitment, finally lack of sustainability
elements based on green building rating like GBI.
Keywords: green building, Green Building Index (GBI), construction development, sustainability

human life. The construction industry generates thegreatest environmental impacts among all the otherindustries. Green building designs and standards aredeveloped to improve building operation energy andembodied energy efficiencies, and minimize energy
and wastes [5].

INTRODUCTION
In recent years, environmental issues such as
climate change, energy crisis, and pollution receive
a great attention from the construction industry
in
Malaysia.
Transformationofbuilding
construction and operations are significant because
the environmental impacts are expected to increase
with population growth and changes in other factors
such as demographic and economic factors. Various
measures have been carried out to minimise
the construction impacts towards environment andsustainable development was introduced to improvea quality of life for current people and future
generation [1]. The Brundtland Commission definedsustainable development as the ability to makedevelopment sustainable to ensure that it meets theneeds of the present without compromising theability of future generations
to meet their own
needs [3]. In order to implement the sustainable
development’s goals in Malaysian constructionindustry, the government introduced green building.
Green building has an important role in achieving
the aim of sustainable development [4] which is toprotect environment and to improve the quality ofGreen building practices can play a keyrole in achieving sustainability in the constructionindustry [6]. Therefore, over the last two decades theconstruction industry has made efforts to develop
green building practices [2]. Green buildings areabout resource efficiency, lifecycle effects, andbuilding performance. Smart buildings, whose core
is integrated building technology systems, are about
construction and operational efficiencies andenhanced management and occupant functions.
There are several commonalities between integratingbuilding's technology systems and constructing asustainable or “green” building [7]. Many factors arepromoting the rapid development of green buildings,
including the increasingly serious environmental
problems, the constant improvement of demands onarchitectural environment’s quality, the introduction
and development of a variety of green building477

technologies, the successive implementationof accompanying “green building evaluation
criteria” and other relevant policies and regulations.
All is well known, green building’s designis the premise and necessary conditions of green
building development, which is itself a conceptof sustainable development, and it emphasizes
the adaptation to local conditions, times and issues[8]. Unfortunately, the implementation of green
building concept in agricultural buildings (e.g.
livestock barns, greenhouses, forage storages,etc.)
are still limited. Some studies implemented similar
approaches to that adopted by green buildings, butthey neither fully addressed the concept of green
buildings nor achieved its core. resource andmaterial efficiency, and occupant's health andproductivity. Kamana and Escultura (2011) defined“sustainable building” or “green building”
as an outcome of a design which focuseson increasing the efficiency of resource use - energy,
water, and materials - while reducing building
impacts on human health and the environment
during the building’s lifecycle, through better
location,design,construction,
operation,
maintenance, and removal [9]. Pan et al. (2011)
added that a green building is an outcome of adesign philosophy which focuses on increasing
the efficiency of resource use [10]. Deuble and de
Dear (2012) stated that green buildings, often
defined as those featuring natural ventilation
capabilities, i.e. low-energy or free-runningbuildings, are now at the forefront of building
research and climate change mitigation scenarios[11].

construction is a part of the whole concept of green
building. The charter of the network for thedevelopment and use of natural resources in local
construction of the Southeast Asian on Ecoconstruction and Sustainable Development defined
the “eco-construction” as a holistic and integrated
approach that aims to support access to a healthy
habitat, primarily in rural areas, while ensuringconservation of natural resources and to build on thecultural and architectural heritage in construction.
The eco-innovation in construction leads tothe marketing of products, providing services andinnovative solutions which include bioclimaticarchitecture, and enhancing use of local natural
resource and highlight the skills of man andenterprise.
Green Technology
Green technology refers to the development andapplication of products, equipment and systems
to protect the environment and the naturalenvironment and minimize or alleviate the negative
effects of human activities [12]. Generally
greenhouse refers to the normal greenhouse
constructed for agricultural purposes and plants
research. However, this study refers to green
residentialbuildings
wherehumanslive.
It also refers to residential buildings incorporating
green technology with green space and energy
efficiency that can provide the comfort, safety andhealthy living environment. Green residentialbuildings are also constructed using sustainable
development concepts that utilize green resources
which can be found easily such as the wood (trees
harvested and replanted), solar energy, hydroelectric
power and wind power. Sustainable development
is all about meeting the needs of the present (people)
without compromising the ability of future
generations in order to meet their own needs [13].

Table 1: Presents a comparison between “green
buildings” and “non-green buildings” or “traditionalbuildings”.

What is a Green Building?
A Green building focuses on increasing
the efficiency of resource use energy, water, andmaterials while reducing building impact on humanhealth and the environment during the building’s
lifecycle, through better siting, design, construction,
operation,
maintenance,andremoval.
Green Buildings should be designed and operated
to reduce the overall impact of the built environment
on its surroundings [17].
Significant of Green Buildings
Green buildings are designed to save energy andresources, recycle materials and minimise
the emission of toxic substances throughout its life

There is deference between “green building” and“asean-construction”, where the concept of eco-478

the Public about environmental issues and our
responsibility to the future generations.
The GBI rating tool provides an opportunity
for developers and building owners to design andconstruct green, sustainable buildings that can
provide energy savings, water savings, a healthierindoor environment, better connectivity to public
transport and the adoption of recycling and greenery
for their projects and reduce our impact on theenvironment [17].
GBI is developed specifically for the Malaysiantropical climate, environmental and developmental
context, cultural and social needs and is created to:• Define green buildings by establishing a common
language and standard of measurement;• Promote integrated, whole-building designs thatprovide a better environment for all;
• Recognise and reward environmental leadership;• Transform the built environment to reduce its
negative environmental impact

cycle. Green buildings harmonise with the local
climate, traditions, culture and the surrounding
environment. Green buildings are able to sustain andimprove the quality of human life whilst maintaining
the capacity of the ecosystem at local and global
levels. Green buildings make efficient useof resources; have significant operational savings
andincreases
workplaceproductivity.
Building green sends the right message about
a company or organisation – that it is well run,
responsible, and committed to the future [17].
Green Building Definition
According to GBI (2011), “A green building focuseson increasing the efficiency of resource use - energy,
water, and materials - while reducing building
impact on human health and the environment during
the building’s lifecycle, through better sitting,design, construction, operation, maintenance, andremoval. Green Buildings should be designed andoperated to reduce the overall impact of the built
environment on its surroundings”. Buildings withgreen technology in Malaysia are considered new.
But the efforts to develop a comprehensive green
technology for buildings including residential
are underway to ensure a better quality, comfortable
and affordable to a wide range of social groups.
The government of Malaysia is currently aware thatgreen technology can be a practical, useful andan alternative approach for residential buildings[14].
1. Green buildings are designed to save energy andresources, recycle materials and minimise
the emission of toxic substances throughout its life
cycle.
2. Green buildings harmonise with the local
climate, traditions, culture and the surrounding
environment.
3. Green buildings are able to sustain and improve
the quality of human life whilst maintaining thecapacity of the ecosystem at local and global levels.
4. Green buildings make efficient use of resources;
have significant operational savings and increases
workplace productivity.
5. Building green sends the right message about
a company or organisation – that it is well run,
responsible, and committed to the future.

Table 2: THE GBI RATING SYSTEMBUILDINGS WILL BE AWARDED THE GBIRATING BASED ON 6 KEY CRITERIA:
1

Energy Efficiency (EE)

2

Indoor Environmental Quality (EQ)

3

Sustainable Site Planning & Management (SM)4Material and Resources (MR)

5

Water Efficiency (WE)

6

Innovation (IN)1) Energy Efficiency (EE): Improve energy consumption
by optimising building orientation, minimizing solar heat gain
through the building envelope, harvesting natural lighting,adopting the best practices in building services including useof renewable energy, and ensuring proper testing, commissioning
and regular maintenance.
2) Indoor Environment Quality (EQ): Achieve good quality
performance in indoor air quality, acoustics, visual and thermal
comfort. These will involve the use of low volatile organic
compound materials, application of quality air filtration, proper
control of air temperature, movement and humidity.
3) Sustainable Site Planning & Management (SM):
Selecting appropriate sites with planned access to public
transportation, community services, open spaces andlandscaping. Avoiding and conserving environmentally sensitive
areas through the redevelopment of existing sites andGreen Building Index?
The Green Building Index (GBI) is Malaysia’s
industry recognised green rating tool for buildings
to promote sustainability in the built environmentand raise awareness among Developers, Architects,
Engineers, Planners, Designers, Contractors and479

brownfields. Implementing proper construction management,
realised. This can lead to a better and safer place forstorm water management and reducing the strain on existing
reduced carbon footprint
residents and theinfrastructure capacity.
and also offers long-term
community as a whole.
4) Materials & Resources (MR): Promote the use ofsavings for the building
environment-friendly materials sourced fromowners.
sustainable sources and recycling. Implement proper
construction waste management with storage, collection
and re-use of recyclables and construction formwork and waste.
5) Water Efficiency (WE): Rainwater harvesting,water recycling and water-saving fittings.
6) Innovation (IN): Innovative design and initiatives
that meet the objectives of the GBI. Achieving points
in these targeted areas will mean that the building
Figure 1: GBI POINTS FOR RESIDENTIAL
will likely be more environment-friendly than those
AND NON-RESIDENTIAL BUILDING
that do not address the issues. Under the GBI assessment framework, points will also be awarded for achieving andincorporating environment-friendly features which
are above current industry practice.
Table 3: THE GBI RATING TOOLS FOR RESIDENTIAL
AND NON-RESIDENTIAL BUILDINGTHE GBI RATING TOOLSNON-RESIDENTIALRESIDENTIALThe GBI Non-Residential
The GBI Residential
Rating tool evaluates the
Rating tool evaluates thesustainable aspects ofsustainable aspects ofbuildings that are
residential buildings.
commercial, institutional
This includes linked
and industrial in nature.
houses, apartments,
This includes factories,
condominiums,
offices, hospitals,
townhouses, semiuniversities, colleges,
detached and bungalows.
hotels and shoppingThis tool places more
complexes.
emphasis on sustainable
Of the six criteria thatsite planning &make up the GBI rating,management, followedemphasis is placed on
by energy efficiency.
energy efficiency andThis serves to encourage
indoor environmental
developers and homequality as these have theowners to consider thegreatest impact in the areas environmental quality ofof energy use and wellhomes and their
being of the occupants and inhabitants throughusers of the building.
better site selection,
By improving on theprovisions of public
efficiency of active
transport access,(mechanical and electrical) increased community
systems as well as
services andincorporating good passive connectivity, as well as
designs together withimproved infrastructure.
proper sustainable
Such achievement will
maintenance regimes,
help reduce the negative
significant reductions in
impact to theconsumed energy can beenvironment and create a480

Classification of Green Building Systems
Green building classification system is under
the sustainable construction umbrella, and it is used
to measure the sustainability of a building. Presently,
the classification system has several standards andmost countries have their own based on their particularclimate, soil, environmental, and geographical location.
Each country uses a different system to suit the socialand cultural development of their respective countries(see Table 6). All the above classification systems
for green building have the same objectives; toincorporate green technology in housing construction
projects and new business premises. According to thisstudy conducted in 2007 by Professional Builder[16], in Malaysia only, 92%of respondents indicated that energy-efficient features
either extremely important or very important with respect to newhouse of green building implementation especially for CO2
reduction. It is also in line with the goals of the Malaysian
government to reduce CO2 emissions 40% from year 2008
onwards and overcome the problem of global warming according
to the GBI. In addition, green building design can reducethe benefit of electricity consumption by up to 30%, the ability
to reduce carbon emissions by 35%, reduce water consumption
around 30% to 50% and help to reduce the cost to be produced
Between 50% to 90% [14].

Table4: GBI CLASSIFICATIONGBI CLASSIFICATION

Table 5: COST OF GOING GREEN OVERALLCOST OF GOING GREEN OVERALL

Table 6: CLASSIFICATION SYSTEM OF GREEN BUILDING

481

government support and attitude of the population
towards green building construction. The
government should develop incentive schemes forthe projects which adopt green ideas in buildings.
The government should encourage in green building
Construction for energy efficient. Another four
aspects (i.e. managerial defects; social and culturaldefects; political and legal defects; andenvironmental and biological defects) are lesscritical compared to technical aspect but it does notmean that they are not important and should not givean attention. By considering these critical factors,
this study is expected to raising awareness for those
who are involves in green building development in
Malaysia.
The results of the study can be summarized threefolds:(i) The green building concept and exposure is stillin its early stages in Malaysia and therefore need astrong and extensive awareness and acceptance by
the community also a with close collaboration
between all players in the construction industry.
(ii) House buyers‟ perspectives towards green
residential buildings are still vague and lack proper
understanding. Perhaps, the present conditions (e.g.,
economy, financial, social and culture) prevented
them from understanding the perceived benefits,challenges and something that we possessed today(e.g., natural environment, flora, fauna, and others)
that need to be saved for future generations.
(iii) The government’s cooperation and intervention
is needed intensely in providing more information,knowledge transfer and financial incentives
sufficiently for green buildings, renewable energy,
energy-efficient and hybrid technologies which canhopefully constitute an engine of growth for the 21st
century.

Green Buildings Implementation
According to McGraw Hill construction report in2005 [15], the two (2) most cited perceptions why
green buildings must be implemented are; (i) energy
savings and productivity savings, and (ii) industry
that values the environment. Other factors that thereport cited are presented in Figure 2.
Figure2: reasons for green building implementation

REFERENCES[1]. Samari, M., Godrati, N., Esmaeilifar, R.,
Olfat, P. and Shafiei, M.W.M (2013). The
Investigation of the Barriers in Developing
Green Building in Malaysia. Modern
Applied Science, 7(2), 1-10.
[2]. Gluch, P. 2006. Building green
perspectives on environmental management
in construction. PhD Dissertation,
Chalmers University of Technology,
Gothenburg, Sweden.
[3]. Kates, R.W., Parris, T.M. and Leiserowitz,
A.A. (2005). What is Sustainable
Development: Goals, Indicators, Values
and Practice. Environment: Science andCONCLUSION
This paper has discussed the barriers of challenging
factors in the implementation of green buildings in
Malaysia. The problems related to green building
construction were identified. The problems arecommon to all countries in term of energy efficientthe major barriers are education and training,awareness, professional training, government
support, financial support, legal implications andattitude. There are some barriers, which are more
pronounced in Malaysia, for example, awareness,482

missing link? Building and Environment,
56(2012): 21-27.
[12]. KeTTHA (2011). Definisi Teknologi
Hijau. Accessed on 29 January 2013.
Available at:
http://www.kettha.gov.my/content/definisi[13]. Jennifer, P., and Jackson, T.O. (2008).
Green Buildings: Valuation Issues andPerspectives.
[14]. Green Building Index, GBI Rating
System, viewed
2011,http://www.greenbuildingindex.org/how-GBI-works2.html[15]. Cryer, B., Felder, J., Matthews, R.,
Pettigrew, M., and Okrent, B. (2006).
Evaluating the Diffusion of Green Building
Practices.
[16]. YM Adnan, MN Daud, I Ahmad, A Aziz
- Pacific Rim Property Research…DETERMINING THE CRITERIA FOR
THE CLASSIFICATION OF PURPOSE
BUILT OFFICE BUILDINGS IN
MALAYSIA, 2009 http://www.prres.net/Papers/PRPRJ_No_2_
2009_Adnan.pdf[17]. Green Building Index. Accessed on 12
February 2013. Available at:
http://www.greenbuildingindex.org/index.html

Policy for Sustainable Development,47(3),8-21.
[4]. Fisk, W.J. and Rosenfeld, A.H. (1998).
Potential Nationwide Improvement in
Productivity and Health from Better Indoor
Environment. Paper presented at 1998
Summer Study on Energy Efficiency in
Building, LBNL-41849, 23-28 August
1998, Washington, D.C.
[5]. Kwok, K.Y.G., C. Statz, and W.K.O.
Chong. 2011. Carbon emission modelingfor green building: A comprehensive studyof methodologies. Proceedings of theInternational Conference on Sustainable
Design and Construction (ICSDC):
Integrating Sustainability Practices in theConstruction Industry, pp. 9-17, 23-25
March, Kansas, USA.
[6]. Chatterjee, A.K. 2009. Sustainable
construction and green buildings on thefoundation of building ecology. IndianConcrete Journal, 83(5): 27-30.
[7]. Sinopoli, J. 2008. How do smart buildings
make a building green? Energy
Engineering, 105(6): 17-22.
[8]. Zhang, D., D. Liu, M. Xiao, and L. Chen.
2011. Research on the localization strategy
of green building. Proceedings of theInternational Conference on Civil
Engineering and Building Materials, 29-31
July, Kunming, Yunnan, China.
[9]. Kamana C.P., and E. Escultura. 2011.
Building green to attain sustainability.
International Journal of Earth Sciences andEngineering, 4(4): 725-729.
[10]. Pan, N.-F., R.J. Dzeng, and M.D. Yang.
2011. Decision making behaviors inplanning green buildings. Proceedings ofthe International Conference on Computer
Distributed Control and Intelligent
Environmental Monitoring, pp. 1710-1713,
19-20 February, Changsha Hunan, China.
[11]. Deuble, M.P., and R.J. de Dear. 2012.
Green occupants for green buildings: The

483

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

GEOTEXTILE ENCASED COLUMNS (GEC): WHY, WHERE, WHEN,
WHAT, HOW?
Dimiter Alexiew1 and Graham Thomson2
1.
2

HUESKER Synthetic GmbH, Technical Director, Gescher, Germany
HUESKER Synthetic GmbH, Area Director (Asia Pacific), Singapore
ABSTRACTThe Geotextile Encased Columns (GEC) foundation system for embankments and dikes on soft soils wasintroduced some 20 years ago and is now considered State-of-the-art in Germany and step by step worldwide.
The GECs consist of compacted non-cohesive fill similar to common sand or gravel columns with one decisivedifference: they are confined in a high-strength woven geotextile “cylinder” (encasement) controlling their
behavior.
Why: Why did the development start twenty years ago? What were the motivation and the main ideas at thattime? What were the reasons for modifications in design procedures, materials etc over the years?
Where, when: What are the typical geotechnical and logistic circumstances for an optimal application? Whenand where does it make sense? What are the restrictions, if any?
What: What are the geomechanical mechanisms behind it? What are the proper materials (fill, encasement)?
Which design procedures are sound and recommendable? What is the knowledge and experience today? What is
the need of further research, if any?
How: How should GECs be installed properly and in an efficient way? How to control the construction
process in terms of time and quality? How to eliminate problems, if any?
Keywords: Geotextile Encased Columns, GEC, Embankments, Soft Soils

INTRODUCTION
While looking for embankments on soft soils,
generally two groups of solutions exist:
Unsupported embankments (Fig. 1): there are
four main options:a) build up embankment extremely slowly
waiting for sufficient consolidation after every stage;b) replace the soft soil partially or totally;c) install a high-strength basal reinforcement
providing overall and local stability and allowingbuilding up the embankment much faster;d) combine the latter option with strip drains toaccelerate consolidation and thus the construction
process additionally.
Today only options "c" and "d" are of practicalrelevance. Despite all the pros and contras, thecommon attribute is that stability (Ultimate Limit
State - ULS) can be controlled, but not the short- andlong-term settlements (Serviceability Limit State SLS).
Supported embankments (Fig. 2): the maincommon idea is to over-bridge the soft soil layers bysupporting vertical elements of different types: rigid
piles, trench walls etc. or "softer" solutions likedifferent columns (compacted, cemented, mixed-inplace etc.). Herein the border between "pile-similarelements" and "soil improvement” seems to befluent and depends on country, traditions etc.

Fig. 1

484

Unsupported embankments on soft soil:
options "a", "b" and "d" from top to bottom.

GEOMATE- Brisbane, Nov. 19-21, 2014

stability) and the SLS (settlements and possibly
lateral embankment “spreading”).

Fig. 2

Supported embankments on soft soil on
rigid or semi-rigid elements like piles andcolumns.

Twenty years ago one specific solution more
started: the Geotextile Encased Columns (GEC);
they are discussed below in a more detailed way.

Fig. 3

WHY GEC?
The development of the GEC-System started in
the early 90ies . It was initiated by the Contractor
Möbius, Germany and developed in collaboration
with Huesker Synthetic and Kempfert & Pa,
Consultant.
The idea was to create a system providing:
Versus piles:
lower costs
ductility (especially lateral)permeability
Versus common granular columns (both in the
short- and long-terms):
mechanical stability even in extremely soft
soils
hydraulic stability
protected from soft soil intrusion
use of finer granular materials (e.g. sand) as
fill
Versus both: lower installation energy
consumption (today we call it “lower carbon
footprint”).
Note: at that time execution of unbound granularcolumns was not allowed in Germany in soils with
undrained unconsolidated shear strength S U < 15
kN/m² due to the risk of bulging during execution orlater under operation; today the limit is even higher:
25 kN/m².
Using sand was from interest because it isusually available and cheaper in typical soft soil
areas.
It became soon obvious that a proper geotextile
encasement could help to meet the goals.
The concept is depicted in Fig. 3.

The
GEC-System:
basic
overview:
embankment, horizontal reinforcement (ifneeded), encased granular columns, soft
soil, firm substratum.

B. A proper geotextile encasement was needed
to provide a sufficient lateral/radial confinement
similar to a flexible oedometer (radial alias ring
strength and tensile stiffness plus robustness)
together with filter stability and separation
capability.
C. A construction procedure was needed being
so far as possible quick, easy and not expansive,using common equipment and causing only a limited
damage to the geotextile encasement during
installation.
How to Design?
Intensive theoretical and practical research
inclusive of 1:1 GEC tests and measurement
programs was performed in the 90ies in Germany. A
simplified design procedure had been suggested
earlier in [1], but dealing only with the ULS aspect.
To make the long story shorter: in 2000 a proper
verified design method [2] - [4] was finallyestablished and is in the meantime after small
modifications included in the German Code forgeosynthetic reinforced systems [5]. It handles andsolves in a “mixed” way both the ULS and SLS
aspects (“mixed”, because it is based on a so called
second order theory, say, the deformations of the
GEC have influence on the stresses in the systemand conversely). Main points are:the two stages of design (“vertical”, dealing onlywith the vertical behavior of a column, and“horizontal”, dealing with the global stability of theembankment on GECs and adding a horizontal
reinforcement on top of them if needed);
the consideration of some lateral counterpressure from the surrounding soft soil on the GEC,
i.e. it is an interactive model;
the key role of the tensile stiffness of encasement

HOW?
A “triangle” of problems had to be handled:
A. A design procedure was needed for the
analyses of the ULS (bearing capacity, overall
485

GEOMATE- Brisbane, Nov. 19-21, 2014

in the ring alias radial direction controlling byconfinement the GECs behavior.
Assumptions, further explanations, detailed
design recommendations and equations can be foundin [2] - [7] both for the “vertical” and “horizontal”(global) design.

How to Select the Fill?
Generally a granular non-cohesive fill has to be
used due to geomechanical (shear strength, lowcompressibility, insensitiveness to water, easiercompactibility) and hydraulic (water permeability)
reasons. An important difference to the “common”
compacted stone/gravel columns is the possibility touse sands. Typical recommended requirements are:Less than 5 % of fines;
Angle of internal friction φ > 30°;
Coefficient of uniformity C U = 1.5 to 6;
Coefficient of permeability k > 10-5 m/s and at
least 100 times higher than k of the surrounding soil;
Oedometric (confined) compression modulus
E oed > 10 x E oed of surrounding soil.
In practice a wide range of materials can be used:from sands to rounded or crushed gravels andrecycled materials as e.g. concrete debris (Fig. 5).

How to Select the Encasement?
The confining encasement is a key component
and the most substantial, decisive difference to“common” compacted granular columns (beside one
other important difference: the possibility to use
sand as a fill). The design asks for two parameters ofit (reflecting correctly the physical reality and thecommon engineering sense):
Tensile stiffness (tensile modulus J, kN/m) in“ring” direction;
Design strength F d , kN/m.
The leading factor is J, controlling the radial
expansion of the column under load and thus its
vertical compression, i.e. the settlement of its top, i.e.
the settlement of embankment. Higher modulus
results in less settlement. The modulus J is timedependent due to creep and depends to 80-90% on
the polymer used [8] and to 10-20% on the
production technology of the encasement. Due to theadditional need of separation and filter stability awoven geotextile proved to be the optimal solution.
To eliminate the very negative influence of
joints/seams mostly on F d , but on J as well, modern
encasements are seamless textile flexible cylinders
delivered to the site “flat” as a roll (Fig. 4). The mostestablished encasements today comprise two
families from two different polymers, both of low
creep, but with different moduli J and strengths F d .
Their Ultimate Tensile Strength (UTS) varies from100 to 400 kN/m, the Ultimate Strain ε ult from 10 %down to 5 % and the modulus J from 1000 to 6000
kN/m. Their typical diameters amount from 0.4 m to
0.8 m.

Fig. 4

Fig. 5Different fills for GEC in a field trial.

How to Optimize the System?
The goal of the design is usually to limit thesettlements to a prescribed value (SLS) ensuring inthe same time bearing capacity and global stability(ULS).
Under given geotechnical conditions the design
engineer can vary three factors [5], [6]:The percentage of GECs a, % (area ratio of GEC
area to total embankment foundation area); based on
experience a = 10 - 20 % is recommended; diameter
and/or spacing of GECs can be varied;
Fill (e.g. sand or crushed gravel);
Ring tensile modulus J and strength ofencasement.
Obviously the higher the “a”, the better the fill
and the higher “J”, the lower the settlements.
However, the fill is often a matter of availability inan acceptable distance from the construction site;normally in problematic low land soft soil areas
sands are more accessible then gravels. The diameterof GEC can depend on the commonly available
equipment in a country or region (see installation
issues below). The parameters of real free choice are
the area ratio and the modulus/strength of

Typical woven seamless encasement asdelivered to the site before installation.

Summary: today the right choice of encasement
is practically not a matter of availability, but ofdesign optimization (see below).
486

GEOMATE- Brisbane, Nov. 19-21, 2014

encasement, the latter being also easy to transport toany place (Fig. 4).
Figures 6 and 7 show an example how increasing
ring tensile modulus and/or area ratio reduce thesettlement (same fill is assumed).

Fig. 6

Fig. 7

down, and for the replacement method it is open andthe local soil has to be excavated out (e.g. by ahelicoidal spiral tool).

Achieving the same settlement by different
area ratios and ring tensile modulus.

Reduction of settlement by increase of area
ratio, ring modulus and their combination.

Further simplified graphs of similar type for a
first orientation can be found in [6].
It is usually more efficient to choose a lower
percentage of GECs with higher tensile modulus J.
The savings of fill material, equipment, energy, time,
manpower and CO/CO 2 emission are significant. In
the example above (Figs. 6 &7) the increase of J
from 1800 to 4000 kN/m reduces the area ratio from
20 to 10 %, it means only half the numbers of GECs
need to be installed.

Fig. 8

Examples of completed GECs: in a sandplatform, in streaming water, in sludge.

Fig. 9

Scheme of the so called displacement
method of installation.

It is an advantage that steel pipes are available
worldwide; the flaps can be easily produced andadapted; a wide range of vibro-hammers and bearing
rigs is available as well, say, finally there is nothing
too specific or sophisticated. The latter makes adifference more to the majority of "common"
granular columns.
How to eliminate problems in advance:
do not foresee a steel pipe with a too thin wall;look for pipe diameters being common in acountry (it starts with metric/non-metric systems)
it is often easier to adapt the design to the pipes
commonly available than the reverse (see "how to
optimize the system" above); note that the modern
geotextile encasements (Fig. 4) can be easily
customized - not so the pipes;
use a high-class steel for the flaps;
use high-frequency vibrators (> 30 Hz) with

How to Install the GECs?
The installation technique was refined over theyears, but is generally quite simple [7]. Drive a steel
pipe down by vibration; unroll and install theencasement into the pipe; fill it; pull the pipe up by
vibration; the compacted GEC is completed (Fig. 8).
In the case of the so called displacement method(Fig. 9) the pipe is closed by flaps during driving
487

GEOMATE- Brisbane, Nov. 19-21, 2014

more than one column diameter, say by 0.5 to 0.8 m
in comparison to rigid piles with some meters.
Their behavior can be a priori controlled in abetter way in comparison to non-encased granularcolumns due to the presence of an engineered
produced in-plant element; the geotextile
encasement.
They are not practically settlement-free like rigid
piles, but most of the settlements occur before end of
construction and can be easily compensated;
however, the settlements are of other order ofmagnitude
comparedtonon-supported
embankments e.g. with basal reinforcement and strip
drains (Fig. 1).
They work additionally as vertical drains withextreme drainage capacity.
The GEC-System is ductile and to a significant
extent self-regulating and robust because of theinteraction of fill, encasement, soft soil andhorizontal reinforcement on top of GECs (if any).
Because of their permeability and filter stability
their influence on the natural hydraulic environment
is marginal.
Because of their permeability and filter stability
and mainly due to the installation method byvibrators (say, the installation energy is applied witha high frequency of small rates) the generated
dynamic pore water overpressure is smaller anddissipates quicker, say the "disturbance" of the soft
soil is limited.
The geotextile encasement works primarily as
reinforcement (although in a very specific way)providing (ring) tensile forces of key importance andsecondarily as separator and filter.

sufficient centrifugal force (> 2000 kN) and moment(> 500 Nm); resonance-free is not a must;the working height of the mast of rig should be atleast 2 to 3 m bigger than the length of theinstallation pipe;
it can be worth for larger jobs with e.g. morethan 10.000 GECs to test two or three different
vibrators before starting the job;
do not hesitate to contact a GEC-experienced
professional regarding the equipment if you do not
feel comfortable; it could save nerves and months of
execution.
WHERE/WHEN GEC?
Optimal applications:in soft soils with a S U < 30 kN/m², even better <20 kN/m² (possible down to S U = 2-3 kN/m²) andoedometric (confined) compression modulus E oed =0.5 -3,0 MN/m²;
for soft soil thickness of 8 to 30 m;
for embankments, dikes, stockpiles etc. of atleast 1.5 m height;
from interest if system settlement in the range of
0.1 to say 0.5 m in the construction stage can be
accepted and compensated (this is often the case);note, that because the GECs work also as "megadrains", primary consolidation and settlements occur
quickly; post-construction settlements are small;from interest, if ductile (especially laterally) pilesimilar elements being less sensitive to lateral soft
soil pressure in depth are required (e.g. in thevicinity of stock piles or other directly foundedloads);
from interest as ductile active foundation
elements for the loads mentioned above, reducing
the lateral trust in depth mentioned also above;from interest in seismic areas keeping the
integrity of granular columns under "shearing"seismic impact [9] - [11];from interest if a disturbance of the groundwater
regime is not acceptable (they are permeable andfilter-stable);from interest, if existing old embankments e.g.
for railroads have to be upgraded for higher speeds
increasing their static and even more dynamic
stability [7], [10], [11].

Fig. 10
Position of the GEC System
between two extrema: embankments on rigid
elements and embankments without any support.
From a general engineering point of view the
GEC-System can be positioned in terms of behavior,specifics and performance as shown in a very
simplified way in Fig. 10.

WHAT ARE GEC FINALLY?
This is a trial to add some missing points andaspects and to create a feeling what we are talking
about.
GECs are bearing pile-similar elements; it is amatter of philosophy if they should be called"piles/columns" or a "subsoil improvement system".
They are end-bearing elements. Nevertheless,due to their “softer” behavior inclusive of the toezone there is no need to enter the firm substratum by

WHAT IS THE EXPERIENCE AVAILABLE?
In the meantime large with more than 30
significant projects and more than 2300 km of
installed GECs. The most popular (German) design
procedure [2], [5] seems to work properly being
verified by measurement programs and practice; it ismay be a bit conservative [7], [12]; further
optimization is in progress. Since about ten years it
488

GEOMATE- Brisbane, Nov. 19-21, 2014[5] EBGEO 2010. Recommendations for Design
and Analysis of Earth Structures using
Geosynthetic Reinforcements. German
Geotechnical Society (DGGT), Ernst & Sohn,
Essen-Berlin, 2011 (the English version).
[6] Alexiew D, Brokemper D, Lothspeich S,"Geotextile encased columns (GEC): Loadcapacity, geotextile selection and pre-design
graphs", Proc. Geofrontiers 2005, Austin, USA,2005.
[7] Alexiew D, Raithel M, Küster V, Detert O, "15years of experience with geotextile encased
granular columns as foundation system", Proc.
Int. Symposium on Ground Improvement IS-GI,
ISSMGE TC 211, Brussels, 2012.
[8] Alexiew D, Sobolewski J, Pohlmann H,“Projects and optimized engineering withgeogrids from "non-usual" polymers”, Proc. 2nd
European Geosynthetics Conference, Bologna,
2000, pp. 239-244.
[9] Guler E, Alexiew D, Abbaspour A, Koc M,“Seismic performance of stone columns andgeosynthetic encased columns”, Proceedings
ICEGE 2013 From case history to practice,
Istanbul, 2013.
[10] Di Prisco C, Galli A, Cantarelli E, Bongiorno D,“Geo-reinforced sand columns: small scale
experimental tests and theoretical modelling”,
Proc. 8th Int. Conf. on Geosynthetics,
Yokohama, Millpress, Rotterdam, 2006,
pp.1685-1688.
[11] Di Prisco C, Galli A, “Mechanical behaviour of
geo-encased sand columns: small scale
experimental tests and numerical modelling”,
Geomechanics and Geoengineering, available
online 01 Sep 2011, 2011.
[12] Raithel M, Alexiew D, Küster V, “Loading test
on a group of geotextile encased columns andanalysis of the bearing and deformation
behaviour and global stability”, Proc.
International Conference on Ground
Improvement and Ground Control (ICGI 2012),
University of Wollongong, 2012, pp. 703-708.
[13] Tandel YK, Solanki CH, Desai AK,“Reinforced granular column for deep soil
stabilization: a review”, International Journal of
Civil and Structural Engineering, 2, No 3. 2012.
[14] Tandel YK, Solanki CH, Desai AK.
“Reinforced stone column: remedial of ordinarystone column”, International Journal ofAdvances in Engineering & Technology, No 6,
2012.
[15] Murugesan S, Rajagopal K, „Model tests on
geosynthetic-encased stone columns”,
Geosynthetics International, 14, No 6, 2007.

was always possible to create an optimized solution
due to the huge range of geotextile encasements
available today; no ULS or SLS problems known by
reason of encasements. Problems arose sometimes
during installation, e.g. slow installation progress;
typical reasons are too light vibrators or low qualityof pipe flaps, say the disrespect of basic rules.
WHAT IS THE
RESEARCH?

NEED

OF

FURTHER

Until 2002 the activities in terms of research,measurement programs, design procedures and so on
were concentrated mainly in Germany. Since about
2002-2003 international theoretical and practicalresearch, measurement programs etc became more
intensive because of the increasing worldwide
application of GECs and the efforts to study
additional aspects and applications of the system or
to optimize design. Due to brevity all the
publications in this context cannot be cited herein.
Useful compact overviews can be found in e.g. [13],[14]. Generally some basics from the late 90ies wereso far confirmed (e.g. [15]). An interesting research
is under run dealing with the behavior, possible
benefits and specialized design procedures in thecase of seismic impact.
ACKNOWLEDGEMENTS
Due to brevity the list of references herein
include only a small part of the work done overalmost twenty years in terms of executed projects,
design, installation experience, research etc. bymany engineers in Germany and worldwide from
Brazil to Australia. They all have contributed
significantly to the present State-of-the-art.
REFERENCES[1] Van Impe WF, Soil improvement techniques
and their evolution, AABalkema / Rotterdam /Brookfield, 1989.
[2] Raithel M, „Zum Trag- undVerformungsverhalten vongeokunststoffummantelten Sandsäulen“,
Schriftenreihe Geotechnik, Heft 6, Universität
Gesamthochschule Kassel, Kassel, Germany,
1999.
[3] Raithel M, Kempfert HG, „Bemessung von
geokunststoffummantelten Sandsäulen“, Die
Bautechnik (76), Heft 12, Germany, 1999.
[4] Raithel M, Kempfert HG, „Calculation models
for dam foundations with geotextile coated sandcolumns”, Proceedings of the International
Conference on Geotechnical & GeologicalEngineering GeoEng 2000, Melbourne, 2000.

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TSUNAMI-GENERATION WARNING SYSTEMUSING THE EARTHQUAKE EARLY WARNING SYSTEM
D

Susumu Kurahashi1 and Norimitsu Koike2
isaster Prevention Research Center, Aichi Institute of Technology, Japan;
2
Civil engineering, Aichi Institute of Technology, Japan

ABSTRACT
We propose an early-warning system for providing tsunami refuge time using the magnitude and depth data
provided by the Earthquake Early Warning (EEW) system of the Japan Meteorological Agency (JMA). The
EEW provides an announcement of the estimated seismic intensity and expected arrival time at specific points
and regions prior to the arrival of strong motion. The hypocenter and magnitude of the earthquake are estimatedby using wave form data observed by seismographs near the epicenter. Inukai et al. (2009) proposed a method todetermine whether a tsunami is generated by using the scaling relation between the magnitude and depth of the
hypocenter. The probability that a tsunami is generated is calculated by using the EEW information (magnitude
and depth) and Inukai’s scaling relations. In this method, the information regarding the probability that a tsunami
will be generated is issued within a few seconds by EEW. We incorporated this method into our system andverified the validity of our system.
Keywords: Earthquake Early Warning, Tsunami Warning

such information as early as possible to those that
require more time to take refuge, such as elderly
people, physically handicapped persons, and people
who live near the sea.
The JMA constructed the Earthquake Early
Warning (EEW) system, which can provide thepredicted S-wave arrival time and seismic intensityfrom an earthquake. In Japan, EEW was employednationwide and became fully operational in October
2007. The seismic intensity and arrival times of S
waves are calculated by EEW from the magnitude ofthe earthquake and hypocentral distance between the
hypocenter and target site and the sites affected at
the target site. The hypocenter and magnitude of anearthquake are determined as quickly as possible byusing only the early parts of the P waves at a few
stations close to the hypocenter. If this source
information provided by EEW can be utilized, we
may be able to calculate the probability of thegeneration of a tsunami.
The Disaster Prevention Research Center(DPREC), Aichi Institute of Technology (AIT),
Japan, has organized a consortium that is composedof enterprises in this area in order to mitigate seismic
disasters. One of the main research topics of DPREC
is to re-distribute the EEW system.
We constructed a system that provides theinformation on the possibility of the generation of atsunami by using the magnitude and depth of theoccurrence of the earthquake as observed by EEW.

INTRODUCTION
On 11 March 2011, a Mw 9.0 earthquake
occurred off the Pacific coast of Tohoku, Japan(hereinafter referred to as the Tohoku earthquake).
This was one of the largest earthquakes in terms ofmagnitude and consequence in the history of Japan.
The huge tsunami generated by this earthquake
struck the east coast along Tohoku, causing thedeaths or disappearances of 19,000 people (Fire andDisaster Management Agency, 2012). The height ofthis tsunami was not properly transmitted during thedisaster due to power failure, and people were notable to escape, since they did not believe a tsunami
would strike their area. Currently, the Japan
Meteorological Agency (JMA) issues tsunami
warnings/advisories
basedon
hypocentral
parameters, such as the location, depth andmagnitude, and the tsunami-simulation databasesystem, which stores more than 100,000 cases ofpreviously-conductedtsunami-propagation
simulation results. This system allows tsunami
warnings/advisories to be issued within about threeminutes after the events occur. For the Tohoku
earthquake, the tsunami warning of the initialwarning was issued about three minutes after theoccurrence of the earthquake. The prediction by the
JMA was a magnitude of 7.9. However, the final
moment magnitude was 9.0, and as a result, thetsunami warning was underestimated.
If adequate tsunami information is obtained (e.g.,
information on the possibility of tsunami generation),
the actions needed to protect ourselves can be
carried out. In particular, it is necessary to provide
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GEOMATE- Brisbane, Nov. 19-21, 2014

EEW SYSTEM CONSTRUCTED BY AITThe JMA has started to utilize EEW, which
includes an origin time, a hypocenter, and amagnitude estimated by using the P-wave
information observed at a nationwide seismometer
network installed by JMA and the National ResearchInstitute for Earth Science and Disaster Prevention.
JMA provides an early warning to users including
second suppliers within four seconds (average) after
the detection of P-waves. DPREC receives the early
warning and informs the offices and factories in the
Mikawa area of Japan several to dozens of seconds
before the arrival of strong motions. Figure 1 shows
the conception diagram of the EEW system. Figure 2
shows the distribution system. JMA informs theearly warning to the Japan Meteorological BusinessSupport Center (JMBSC) via dedicated lines.
DPREC receives the early warning from JMBSC via
IP/VPN and distributes the warning to about 50 sites(offices and factories) via the internet within one
second.
DPREC has also installed a seismometer network
to obtain an observed seismic intensity in order tocompare it with an estimated intensity. Furthermore,
a PC monitor is installed at a central office and candisplay various information, such as the epicenter,magnitude, seismic intensity, and arrival time, whichis estimated by EEW. It also can animate display Pand S-wave propagating fronts. DPREC obtains theobserved seismic intensities from the observationsites via the web and sends back a map of theseismic intensities to simultaneously monitor theintensities at the other sites. The re-distributed EEWsystem developed by DPREC is currently installed atabout 30 factories and successfully prevents seismic
disasters.

Figure 2 The EEW system of AITRELATIONSHIP BETWEEN MAGNITUDE
AND HYPOCENTER DEPTH
A tsunami is generated in the sea simultaneouslywith a large earthquake due to crustal deformation.
The depth of the hypocenter is related to thegeneration of a tsunami. Inukai et al. (2009)
proposed a method to determine the generation of atsunami by using the scaling relationship between
the magnitude and depth of the hypocenter. The data
for this relationship were analyzed for 146
earthquakes in which a tsunami occurred. The
equation for this relationship is
M=0.005 D + 6.21,
where M is the magnitude and D is the depth of the
hypocenter.
Figure 3 shows a graph depicting thisrelationship. The relationship shows that a tsunami
is generated if an earthquake occurs beyond amagnitude of about 6.3 for shallow earthquakes.
Figure 3 also shows the line depicting therelationship between the magnitude and depth of the
hypocenter by Iida. Inuduka’s scaling law (2009) is
more accurate than that of Iida.

Figure 1 Conception diagram of the EEW system.
Figure 3 Relationship between the magnitude
and depth of the hypocenter. The dots and circles
indicate the events in which a tsunami was and was
not generated, respectively. The thin line and dottedlines represent the Inukai law and Iida law,491

GEOMATE- Brisbane, Nov. 19-21, 2014

respectively.

INSTALLATION OF THE EEW SYSTEM
We installed this algorithm into the EEW system.
The information of the probability of a tsunami isshown on the PC monitor screen. Figure 5 shows themonitor screen, which can display the following
information.
(1) The epicenter and dynamic state of the
propagating P-wave (yellow) and S-wave (red)fronts from the epicenter to the predicting site (upper
central). Estimated seismic intensity and a margin
time prior to the arrival of strong motions at a target
site (center).
(2) The seismic intensity and arrival time by
EEW at the target site. The larger box is for the mainsite and the smaller boxes are for the other sites. The
color of each box shows the seismic intensity. Red
indicates a 5 lower or more of the JMA seismic
intensity scale, yellow a scale 3 and 4, blue a scale 1
and 2, and gray indicates a scale 0.
(3) The information provided by EEW (e.g.,
origin time, received time of the warning,
hypocenter, information number, magnitude, anddepth of hypocenter) (bottom left).
(4) Real-time data of the seismic intensity
observed by AIR-type seismometers installed at thefive sites (bottom center).
(5) Communication status between the receiving
and transmission servers at DPREC and the analyzed
server at the target site (bottom left).
(6) The indication of the probability of a tsunami.

CALCULATION METHID ALGORITHM OF
THE PROBABILITY OF THE GENERATION
OF A TSUNAMI
The EEW system also provides source
information (e.g., origin time, location of the
hypocenter, and depth of the hypocenter). In
addition, we can also obtain other information, suchas the region of the sea, the inland area, and theaccuracy of prevention. We constructed a method toprovide the probability of the generation of atsunami by using this information provided by EEW.
Figure 4 shows a flowchart of the algorithm of
the calculation method of the probability of thegeneration of a tsunami.

Figure 5 The monitor screen of the EEW system.

VERIFICATION OF THIS SYSTEM USING
THE 2011 TOHOKU EARTHQUAKE
We verified this system by using the 2011
Tohoku earthquake.

Figure 4 Procedures to calculate the probabilityof the generation of a tsunami.
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GEOMATE- Brisbane, Nov. 19-21, 2014

The EEW information is updated whenever thesource information changes. During the 2011
Tohoku earthquake, the EEW information was
updated 15 times. Table 1 shows a list of thisinformation. We calculated the probability of atsunami by using this system. As result, thisinformation was provided during the third
transmission of information, namely, after two
seconds from the first transmission of information.

CONCLUSION
By using EEW information, we proposed amethod that can produce the probability of thegeneration of a tsunami by using the relationshipbetween the magnitude and depth of the hypocenterin accordance with Inukai (2010). This method was
also incorporated into the EEW system. The
probability of the generation of a tsunami can beshown on a monitor.
As a result of the verification of this system, inwhich the 2011 Tohoku earthquake was used, theinformation of the probability of the generation of atsunami can be provided two seconds after the firsttransmission of information by the EEW system.
This time is about three minutes for the JMA
tsunami warning, which is more accurate than oursystem. However, data that can be transmitted fastercan be very useful for early warnings, especially towarn those that have physical limitations.

Table 1 EEW information for the 2011 Tohoku
earthquake.

On the other hand, the tsunami warnings andadvisories by JMA were provided within about threeminutes after the earthquake. The initial warning
issued at 14:49 JST on March 11 was based on thepromptly-estimated JMA magnitude of 7.9, and“major tsunami” warnings were issued to Iwate
Prefecture, Miyagi Prefecture, and Fukushima
Prefecture. At the same time, “tsunami” warnings
and tsunami advisories were issued for many otherareas (Ozaki, 2011).
This system cannot provide the sea height;
however, the probability of the generation of atsunami can be quickly shown.
Figure 6 shows a timeline of the 2011 Tohoku
earthquake.

REFERENCES[1] Fire and Disaster Management Agency, “Aboutthe 2011 Off the Pacific coast of Tohoku
earthquake”,website,www.fdma.go.jp/bn/higaih
ou/pdf/jishin/144.pdf, Year, 2011.
[2] Inukai N, Noto H and Kato F, “Development oftsunami generating judgment model for tsunami
warning”, 27nd Japan Society of Civil
Engineers Kanto branch Niigata meeting
research investigation exhibition, 2009.
[3] Ozaki T, “Journal paper title”, J. of Computer
Science, Vol. 1, Aug. 1987, pp. 23-49.
[4] Islam MR, “Outline of the 2011 off the Pacificcoast of Tohoku Earthquake (Mw 9.0) —Tsunamiwarnings/advisories
andobservations—”, Earth Planets Space, 63, 2011,
pp. 827-830.

Figure 6 Timeline of the 2011 Tohoku earthquakewith the EEW information and tsunami warning.

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ANALYSIS OF THE RISK OF CONFLICT AROUND THE
TRANSBOUNDARY WATER RESOURCES OF THE NORTHERNSAHARAN AQUIFER SYSTEM (NSAS)
1Mohamed Redha Menani1
Earth Sciences Department, Faculty of Sciences, Batna University, Algeria
ABSTRACTThe NSAS covers a surface about 1 000 000 km², it’s shared by Algeria, Libya and Tunisia. It’s situated in a
dry zone with a very weak current recharge but a big volume stored, estimated between 20 000 and 31 000 km3.
Since 1970 to nowadays, the exploitation of the NSAS passed of 0.6 to more 2.5 km3/year. This situation
provoked risks of water Stalinization, the reduction of the artesianisme, the increase of drawdowns …Whichthreaten the sustainable socioeconomic development engaged in the NSAS zone.
The rational and joint management of this aquifer became indispensable.The risk of conflict aroundtransboundary waters is numerically estimated on the basis of the combination of weight and quotations ofseveral indicators which have, directly or indirectly, an impact on the risk of conflict (degree of dependence tothe transboundary waters, degree of satisfaction of the different needs, geopolitical context, geographic context
and the water governance in each country).
Keywords:Transboundary water resources, NSAS, risk of conflict, governance, joint management.
Table 2 Rating intervals of the dependence degree
to the transboundary water resources (Weight: 5)

INTRODUCTION
The numerical indexation of the conflict risk
around the transboundary water resources reposeson the most representative indicators having
weights proportional to their relative importance.
However, each indicator varies in a rating fieldaccording to well defined criteria which takedifferent values according to local conditions, thus
providing a partial index of risk (weight x rate) andthe sum of these partial indices provides the global
risk index of conflict for a given region[1].This
approach allows a standardized assessment of theconflict around the transboundary water resources,
based on indicators having fixed weights according
to their relative importance (table 1).

Variation intervals
Rate
Total dependence
10
Partial dependence with difficulties of8satisfaction of the needs by otherresources (natural and technicaldifficulties)
Partial with possibilities of supplying
6
by other resources
but with a high capital cost
Partial with possibilities of supplying
4
by
other
resourceswithanadvantageous capital cost
Partial to weak with an effective2
supply by other resources
The combination between the fixed weight and thereached rate by each indicator in a given region
leads to a partial index of the risk concerning thisindicator and the sum of the partial indices provides
the global conflict risk index around thetransboundary water resources.
The rating intervals are based on criteria andstandards which take into account results ofresearch works carried out through actions at world
scale which have not only integrated
thequantitative and qualitative aspects of the resources,
but also the economic, social, educative andpolitical aspects.
According to the local conditions, risk
indicators take values between 1 and 10;the greatest
dimensions indicate a high risk of tension andconversely.
It's clear that these ratings must be established

Table 1 Risk Indicators and their respective weights
Indicators
Dependence
degreetothetransboundary water resources
Satisfaction degree of the water needs
Geopolitical context of the conflictzone
Geographic position in relation to thewater resources
Water governance and achievements inwater resources field

Weights
5
4
3
2
2

These indicators take different values in ratingintervals which depend of the local conditions(example of the rating intervals for the firstindicator in table 2).

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for each country concerned by the transboundarywater resources. The advantage of this method is its
flexibility, i.e. the user can insert intermediate andspecific steps which are not considered here andaffect to them dimensions proportional to theirrelative importance by comparison with theproposed ratings.
The partial risk index is obtained by multiplying
the fixed weight of an indicator by the rate reachedby this indicator according to the local conditions.
(IPR = I iw. I ic)
IPR: partial index of risk
Iiw: indicator fixed weight
Iic: indicator rate (variable)
The total index of risk is the sum of the partial
indexes:
GIR = ∑ PIR = ∑ Iiw * IicWith GIR: global index of risk of conflictaround the transboundary water resources
One note generally that two countries or more
involved in a transboundary water conflict do notpresent the same global index of risk because
conditions which prevail in each one of thesecountries are different. According to this procedure,
the minimum conflict risk index is 25, whereas the
maximum index is 158.

system will shelter on the horizon 2030 nearly 8
millions inhabitants.

THE NORTHERNSYSTEM (NSAS)

A summary cross geologic section of the system(see AB on Fig.1) is reported on Fig. 2.
The NSAS aquifer system has a complex
structure [6]-[7] in which one can discern:- The terminal complex (CT) constituted bycalcareous series and sands which have awater reserve of nearly 11 000 km3;
- Gypseous marls series separating the two
aquifers;- The deep aquifer called CI (continental
intercalaire), at variable deeps (between 50
and 2300 m) confined in sand formation.
The reserve stored in this aquifer isestimated at nearly 20 000 km3. Its water iswarm (60 °C by places);- Some intermediary aquifers with local
importance.
The principal zones of recharge of the NSAS
aquifer system are: the South Piedmont of the Atlasin the North-West (Algeria), The Tinrhert
Mountains in the South (Algeria), the Dahar
Mountains in the East (Tunisia), The Nafusa
Mountains in the North-East (Lybia).
Concerning the CI aquifer, the outlet zones are:the Touat-Gourara and the Tidikelt (Algeria), the El
Hamma fault zone in Tunisia and the Tawargha
source (Libya).
The outlet zones of the CT are principally: thesalted Lakes (Marouan-Melrhir in Algeria andGharsa-Djerid in Tunisia) and the golf of Syrte near
Misrata in Libya).

SAHARAN

DeepAquifer CI

UpperAquifer CT

Fig. 1 Geographical position of the Northern
Saharan aquifer system [3].

AQUIFERThe northern Saharan aquifer system is shared
between Algeria, Libya and Tunisia. It is situated ina high arid zone and covers a surface ofapproximately 1 000 000 km² with minor current
recharge but with a large volume stored, estimatedbetween 20 000 to 31 000 km3 [2]. During the last
30 years, the NSAS exploitation passed from 0.6 to
2.5 billions m3/year, leading in major risks ofsalinisation of groundwater, the shortage of thenatural releases and the depletion of water… which
threatenthesustainablesocioeconomic
development committed in the whole zone.To
counter at best these risks, a process of cooperation
was introduced since 1998 under the aegis of theNorthern Sahara Observatory (OSS) in partnershipwith institutions in charge of water resources in the
3 countries [3].
The NSAS water resources are very weakly
renewable, nearly 1billion m3/year, compared to thecurrent exploitation esteemed at 2.5 billion m3/year.
This data led to the conception of a hydrodynamics
model that allows envisaging various exploitation
scenarios of the water resources while taking into
account
perspectivesofsocioeconomic
development in the 3 countries [4]-[5].
The NSAS extension is of 1 million km² ofwhich 700 000 are in Algeria, 80 000 in Tunisia
and 250 000 in Libya (Fig 1). This strategic aquifer

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must also be analysed by comparison to the water
exploitation index estimated as percentage of theannual renewable water resources. In the case of
Libya, even if withdrawals from the NSAS
represent a relative little ratio (nearly 9 %), thiscountry is in total dependence of the non-renewable
water resources of the NSAS (Northern Sahara
Aquifer system) and of the Nubian Sandstone
Aquifer System [8].
The dependence degree to the NSAS can beappreciated by the ratio of the withdrawals fromNSAS to the total renewable water resources (Table
3).
Table 3 Withdrawals from NSAS (ratio)(WNRW) (TRWR) WNRWR/TRWR(Km3/y) (Km3/y)(%)
Algeria
1.5
12.2
12.3
Libya
0.4
0.6
66.7
Tunisia
0.54
4.7
11.5
WNRWR:Withdrawals of Non Renewable Water
Resources from NSAS.
TRWR:Total Renewable Water Resources

Fig. 2. Geological cross section of the NSAS [3]Groundwater of the CT has 2 to 5 g/l of salts,
those of the CI, 1 to 4.5 g/l. This high salinity is theorigin of the deterioration of agricultural lands.
In 2008, The NSAS was exploited by 8800
catching points (3500 for the CI and 5300 for theCT) and the exploitation was 2.5 Billions m3/year(1.5 in Algeria, 0.55 in Tunisia and 0.45 in Libya).
It’s clear that if this rhythm of exploitation
continued, the NSAS zone will be exposed toserious risks of water depletion and a deteriorationof its quality. Signs of this state are alreadyperceptible.
Between 1950 and 2000, drawdowns increased
from 25 to 50 m in many places.
According to the ERES model results, thepotentialities of the NSAS are in an order of 156
m3/s.

Libya is in a position of high dependence to the
NSAS water resources for satisfying its different
needs [9].
Tunisia and Algeria are less dependent to the
NSAS water resources. For these 2 countries, theimprovement of the mobilisation of the renewable
water resources can allows a substantial gain, inparticular in Algeria where considerable efforts are
made to increase the mobilization of surface waters
through the construction of large dams to carry itfrom 7 to 9 Km3/year.
The degree of dependence to the transboundarywater resources can be appreciated by the quotation
indicated in table 4.
Algeria:The country as a whole can beconsidered actually as being in partial dependence
to the NSAS water resources but the south of thecountry, in addition to the country’s NSAS zone, isin total dependence of these resources. In addition
the NSAS serves the extreme south (Tamanrasset)
by hydraulic transfer from Ain Salah with 750 kmof double conduct. The extreme south is situated at
2400 km far from the Mediterranean sea and an
hydraulic transfer of desalinated water for example
can't be envisaged, because very difficult
technically and non-viable economically.
Libya: The Total Renewable Water Resourcesof Libya are insignificant compared to the water
demand of this country. The dependence to the
NSAS and the NSAS’s water resources is complete
even if these are non-renewable water resources.
Tunisia: The situation can be considered as
being worse than in Algeria. Indeed, the water
resources of the country are practically used with
their threshold of renewal. The dependence to the

NUMERICAL INDEXATION OF THE RISKOF CONFLICT AROUND THE NSAS
Dependance Degree To The NSAS
The three countries are situated in a dry region
with very low atmospheric precipitations. The
situation was analyzed by country under thefollowing aspects:
The
renewable
water
resources
potentialities, including surface water ;The non-renewable water resources
captured, by distinguishing those of the NSAS;
The actual capacities of the nonconventional water resources;
The current water supply sources for thedifferent uses;
The Ratio of withdrawals from the NSAS
compared to the total production express therespective actual dependence degree of eachcountry to the NSAS water resources.
The
dependence degree to the NSAS water resources

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NSAS and to the non-conventional water resources
will increase more and more. The South of thecountry is in total dependence of the NSAS’ water
resources

operation if they are not simply blocked. However,in regions marked by normal political relations, therisk of conflict decreases very appreciably.
By geopolitical context of the zone of conflict, itis the state of relations which bond countries of thearea subject to a problem of transboundary water
resources which is aimed here. It’s obvious that if
it’s an armed conflict zone, the problem of water
becomes an additional detonator. However, if theconcerned states belong to a community space inwhich there are rules for the integrated water
resources management and commissions especiallyfor this type of conflict, the risk becomes weak then
(Table 6).

Table 4 Rating intervals of the dependence degree
to the transboundary water resources (weight: 5).
Variation intervals

Rate

Country

PIR

Total dependence
10
Libya b50
Partial dependence with
8
Algeria a40
difficulties ofTunisia c
40satisfaction of the needsby other resources(natural and technicaldifficulties)
Partial with possibilities
6of supplying by otherresources
but with a high capital
cost
Partial with possibilities
4of supplying by otherresources with anadvantageous capital
cost
Partial to weak with an2effective supply byother resources
Partial index of minimum risk (PIR min ) = fixedweight. Minimum rate = 5. 2 = 10
Partial index of maximum risk (PIR max ) = fixedweight. Maximum Rate = 5. 10 = 50

Table 6 Rating intervals of the geopolitical context(weight: 3)
Variation intervals
Rate
PIR
Zone of armed conflict 10
Libya
30
Zone of diplomatic 8
tensionZone of ethnic tension
6
Normalrelations 4
between states
Zone belonging to a 2
communitarian space
Existence of treaties, 1
Algeria 3
commissions of basins
Tunisia
Partial index of minimum risk (PIR min ) = 3
Partial Index of maximum risk (PIR max ) = 30
The Geographic Position In Relation To The
Transboundary Water Resources

Satisfaction Degree Of The Water Needs

The influence of the geographic position isrelated for example to the fact that a country
situated in the upstream part of a river has more
benefits by this situation that country located in thedownstream part, either naturally or by a provokedway (non-consensual installations and riverderivations, discharge of polluted water, notproviding in time data relating to the rises of water
which can cause grave floods in the downstream
part. etc…). This factor concerns alsotransboundary aquifers, by taking into accountrecharge zones of these aquifers, pumping fields
and natural outlet zones of these aquifers [13]-[14].
This concept integrates in an implicit way theenvironmental aspect. For example, pumping in
captive aquifers provokes a drawdown in broadzones which exceed the pumping field itself.
A country is considered under “natural
dominance” when for example the resources ofwhich it depends are located out of its territorial
limits, or when it is under bad hydro-climaticconditions compared to the riparian states (table 7).
The extreme case is when a country is under thetwo cases of domination (natural and provoked).

The NSAS’ water resources don’t serve the
NSAS’ zone only but also other regions by transfer
like in Libya notably and subsidiarily in Algeria. In
the future, Algeria planners’ project to proceed tohydraulic transfers from the NSAS towards regions
situated in the north of the country. This index is
obtained on the basis of the analysis of the different
needs (domestic, agricultural and industrial uses)
and the degree of their satisfaction in the 3
countries [10]-[11]-[12]. Due to the length of thisanalysis, only the final results are summarized intable 9.
The Geopolitical Context
Considered under the conflict aspect, thegeopolitical context of a region can be a criticalfactor. In the case of a political or armed conflict
between countries, the management of thetransboundary water resources endures the directconsequences. The cooperative committees of
dialogue have then great difficulties in their497

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

Better is the water governance, better is the water
availability, decreasing in this sense the tension
around this resource.
On the basis of the analysis of the indicators
related to the water governance [15], it appears thatthe water governance in Tunisia is the best in theregion by considering the priority accorded to therational water resources management in the
different uses [16]-[17]. The second position
occupied by Algeria is due to the big investments inthe water resources field (mobilisation of
conventional and non-conventional, desalinisationof sea water, efforts in the management sector…)[18].
Libya occupies the last position because thecentralized management of the water resources[19]-[20] and the uncertainty affecting in thisperiod of troubles, the institutional and politicalframework.

The results concerning this index are reported intable 7.
Table 7 Rating intervals of the geographical context(weight: 2)
Variationintervals
Under a natural
influence

Rate
3

PIR
Algeria
Tunisia
Libya

6
6
6

Under a provoked
7
influence
Non concerned
00Partial index of minimum risk (PIR min ) = 6 Partial
index of maximum risk (PIR max ) = 14 + 6 = 20
These results are in relation with the natural outlets
situated in Algeria and Tunisia (Salted lakes).
The 3 countries are under bad hydro-climaticconditions (dry zones) and have NSAS’groundwater natural outlets threatened.

The Global Index Of Risk (GIR)

Water Governance And Achievements In Water
Resources Sector

The Synthesis of the partial index of risk gives
the final result compiled in the table 9.

Water governance is analyzed under criteria
widely accepted in this field [15]. A great numberof documents have been consulted for this analysis.
These criteria are reported in Table 8.

Table 9 Global index of Risk
Indicators
Dependence
degreeDegree ofsatisfaction ofwater needs
Geopoliticalcontext
Geographic
Position
Water
Governance
Global Index of
Risk

Table 8 Rating intervals of the water governanceand achievements (weight: 2).
Tarification(politic)
Institutions etLegislationwater
metering andservicequality
Accesstowater and tosanitation
Managementofwater
supplyandsanitation
services,
Globalinvestments

Rate

Algeria

Libya

Tunisia

2

1.25

0.5

1.75

2

1.5

1.5

1.5

1.25

0.5

1.75

2

1.5

0.5

1.5

2

1.5

0.75

1.25

Algeria

PIR
Libya

Tunisia

40

50

40

17.5

13.5

17.5

3

30

3

6

6

6

6

12.5

4.5

72.5

112

71

CONCLUSION
The indexation mode adopted allows placing
Libya in a situation of a high risk of conflict aroundthe NSAS’ transboundary water resources
compared to the riparian countries (Algeria andTunisia)This level of risk assessed at 112 points on ascale of 158, is due to the conjunction of manyfactors, of which the most important are a total
dependence to the NSAS’ water resources but also
to the Nubian sand stones aquifer shared between
Libya, Egypt, Tchad and Soudan, a situation of
uncertainty and troubles inside the country with ahigh risk of secession between the different regionsof Libya and finally a very low level of water
governance compared to riparian countries.

7
3.75
7.75
PI =2*(10-∑ x
6
12.5
4.5
Partial index of minimum risk (PIR min ) = 2
Partial Index of maximum risk (PIR max ) = 18
Each time a condition is filled, the rate affected
at this condition is diminished of the total rate (10).

498Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051[10] Earth Trends “country profiles 1. Water
Resources and Freshwater Ecosystems.”,Algeria, 2003.
[11] Earth Trends “country profiles 2, Water
Resources and Freshwater Ecosystems, Libyan
Arab Jamahiriya.” 2003.
[12] Earth Trends “country profiles 3, Water
ResourcesandFreshwater
Ecosystems,
Tunisia.” 2005.
[13] Mamou A., Latreche D. "Aquifèrestransfrontaliers de la rive sud de laméditerranée.”ConferenceonTheinternationally shared aquifer resourcesmanagement- Mediterranean (ISARM-MED)
Key issues for sustainable management ofTransboudary aquifers in the Mediterranean andSouth Eastern Europe.Thessaloniki, Greece, 2123 oct. 2004.
[14] Baba Ouled Sy, Besbes M. “Holocene
recharge and present recharge of the Saharanaquifers. A study by numerical modeling”.
International symposium on Aquifers Systems
Management, 30 may-1th June 2006, Dijon,
France, pp 312-327,[15] Rogers, P. And Hall A.W. “Effective Water
Governance, Global Water Partnership,” 2003,
TEC Background Papers no. 7.
[16] Benabdallah S. “The Water Resources andWater Management Regimes in Tunisia.”
Proceedings of a Workshop in Tunisia (Series:
Strengthening Science-Based Decision Making
in Developing Countries), 2007, pp.81-87.
[17] Horchani A.“Water in Tunisia. A National
Perspective,
Agricultural
Water
Management.”Proceedings of a Workshop in
Tunisia, Ed. National Academies Press,
Washington, 2007, pp. 88-96..
[18] Taibi R “Global Water Mediterranean
Partnership”, 24th February 2010, Madrid,
Spain. Report and Recommendations, Final
Document, May 2010. 34 p.
[19]Al-Samarrai K., Al-Mejribi A. “Water
Governance In Libya - Challenges andResponses.
GlobalWater
Partnership.”Mediterranean, Workshop on integrated water
resources management, Tripoli, Libya, 11-12
April 2007.
[20] Salem O. “Management of Shared
Groundwater Basins in Libya. In, Policies andstrategic options for water management in theIslamic countries.”Symposium, Tehran, Islamic
Republic of Iran, 15-16 dec. 2003, UNESCO,
pp. 89 97.IHP-IV Series on Groundwater n°73).

The situation in Algeria and Tunisia is muchbetter even the high level of exploitation of thenational renewable water resources; the maximum
is reached in Tunisia.
The relative good water governance in Tunisia
risks furthermore to be stopped by the verysignificant drop of the investments in the water
resources sector observed the last two years.
The current situation in Algeria is totallydifferent. It is marked by a considerable level ofinvestments in strategic projects in the water
resources sector which will improve durably not
only the water availability but also the creation of
thousands hectares of irrigated agricultural areas,
notably in the high lands regions.
The three countries are dependent of the NSAS’
water resources and until recently, the mechanismof dialog initiated through the Sahel and SaharanObservatory (OSS) seems to have correctly
functioned, even if a clear commitment of the 3
countries on the joined management of the NSAS
water resources isn’t yet notified.
REFERENCES[1] Menani M. R.“A Numerical Method to Index
the Risk of Conflict around the Transboundary
Water Resources. Validation by a Studied Case.”
Water Resources, Vol. 36, No. 6, 2009, pp.
731–742.
[2] Baba Ouled Sy. Recharge et paleorecharge dusystème aquifère du Sahara septentrional. Thèsede Doctorat en Géologie, Univ. De Tunis El
Manar, 2005, 261 p.
[3] OSS. “Le Système aquifère du Sahara
septentrional (Algérie, Tunisie, Libye) Gestion
concertéed’unbassintransfrontalier »,Collection synthèse, n° 1 – Tunis, 2008, 56 p.
[4] OSS.
“Système aquifère du Sahara
septentrional : une conscience de bassin.
Modèle mathématique.” Volume 4. 2002, 234p.
[5] OSS “Système aquifère du Sahara septentrional– Essai de synthèse socio-économique.”2005,
73 p.
[6] Bied-Charrenton M. “Le système aquifère duSahara septentrional, une conscience de bassin.”.
Synthèse de la première partie du projet (19992002) « OSS/NSAS », 2002, 17 p.
[7] Margat J. “Les eaux fossiles”. Afriquecontemporaine, N°161 (Spécial) 1er trimestre,
1992.
[8] Salem O. “National water policy review andManagement of water scarcity In Libya. Partie I,
la gouvernance et la politique dans le domainede l’eau.” Chapitre 6, 2002, pp. 87-103.
[9] Salem O. M. “Water resources management in
Libya”. Workshop on Integrated Water
Resources Management (IWRM) in Libya,
Tripoli (11-12 April 2007).

499

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECT OF THE “120-DAY WIND” ON AGRICULTURAL AND
ENVIRONMENTAL CONDITIONS IN HERAT, AFGHANISTAN
Homayoon Ganji1 Abdul Saboor Rahmany1 Takamitsu Kajisa1 Masaaki Kondo1 and Hajime Narioka1
1Graduate School of Bioresources, Mie University, 514-8507 Kurima-machiya-cho 1577, Tsu, Japan

ABSTRACTDue to impending climate change, the problem of extreme climate data for irrigation planning is critical,
especially for areas in which data are limited. Herat province, which is located in West Afghanistan, experiences
extremely strong winds, locally known as the “120-day winds”. The effect of these strong winds on reference crop
evapotranspiration (𝐸𝐸𝐸𝐸0 ) is an important issue. The peak 𝐸𝐸𝐸𝐸0 was given more than 10mm/day at Herat. 𝐸𝐸𝐸𝐸0
exhibits a significant effect on hydrologic processes and agricultural crop performance. Therefore, this index isfrequently used by the Food and Agricultural Organization. This study analyzes 𝐸𝐸𝐸𝐸0 time-series data for both
windy and non-windy seasons using the Penman–Monteith equation to determine seasonal differences in 𝐸𝐸𝐸𝐸0 . To
determine the most influential factors of 𝐸𝐸𝐸𝐸0 rates, all factors are compared for an entire year, 2012. The windcomponent 𝐸𝐸𝐸𝐸wind is determined to be significantly influenced by the extreme wind velocities during the 120-day
wind season. Based on the similar shapes of the time-series curves for monthly wind velocity and monthly vapor
pressure, 𝐸𝐸𝐸𝐸0 is determined to be significantly influenced by the synergistic effect of wind velocity and vapor
pressure deficit.
Keywords: 120-day winds; Herat, Afghanistan; Penman–Monteith method; Evapotranspiration

INTRODUCTION

AREA

Due to impending climate change, theconsideration of extreme climate data for irrigation isessential for areas with limited data. However, studies
of extreme strong wind conditions are rare. In Heratprovince in Afghanistan, strong winds (average speed
6 m/s)—locally known as the “120-day winds”—
usually begin in early July and persist until late
September.
During summer, the prevailing winds originate in
the north at 10–15 knots (5.1–7.7 m/s). North winds
occur 40%–45% of the time from June to August and
30% of the time in September. Peak gusts of 28, 31,
23, and 20 m/s were observed in June, July, August,and September, respectively [1].
Reference crop evapotranspiration (𝐸𝐸𝐸𝐸0 ), which isan important index of hydrologic budgets for different
spatial scales, is a critical variable for understanding
regional biological processes. 𝐸𝐸𝐸𝐸0 is frequently
employed as a variable in the estimation of
evapotranspiration in rainfall-runoff and ecosystemmodeling. Long-term changes in potential
evapotranspiration can significantly affect hydrologic
processes and agricultural crop performance. To
obtain suitable daily estimates of evapotranspiration
using the Penman-Monteith equation, a wind functionthat includes humidity, air temperature and solar
radiation is necessary.

Prior to the war, Afghanistan was well known for
its agriculture and ample supply of food; wheat was
the main food source. Herat province is located inWest Afghanistan, with a geographical area of 54,778
km2 and 1,241,410 ha of irrigated land; it belongs to
the Harirud River basin (N 34° 20' 42" E 62° 11' 59").
Herat is characterized by a cold semi-arid climate,in which the average annual precipitation ranges from152 to 214 mm; this precipitation is minimal andprimarily occurs during winter and spring [2]. The
summer climate is temperate, especially in June andJuly when the maximum degree of hotness ranges
from 38 °C to 43 °C; however, the climate throughout
the remainder of the year is also reasonable.
Using data from Climatemps.com, Fig. 1 andTable 1 display the relative outline of Herat. In Fig 1,
locations with low altitudes are shown in green,maximum average annual temperatures are shown inred, and the average annual precipitation is shown inblue.
Figure 1 lists the extreme data collected for NorthSalang, which exhibits the highest ground levels, thecoolest temperatures, and the highest amounts ofprecipitation in Afghanistan Table 1. Because data forthe east side of the province is unavailable, the colors
that represent the east side of this province are fixed.
In contrast with North-Salang, Zaranj exhibits thehottest temperatures and the lowest amounts ofprecipitation. Compared with other provinces, thedata for Herat is similar to the data for Zaranj, i.e.,500

GEOMATE- Brisbane, Nov. 19-21, 2014high air temperatures, low ground levels, and low
amounts of precipitation. Therefore, the majority ofthe province is shown in yellow in Fig.1.

evapotranspiration in rainfall runoff and ecosystemmodeling because it can significantly affecthydrologic processes and agricultural crop
performance. To obtain suitable daily estimates of
evapotranspiration using the Penman–Monteith
method, which is a combination method, highaccuracy is required. The Food and Agriculture
Organization (FAO) has proposed a standardizationof this method, which is known as the FAO-56
Penman–Monteith application. The daily average
𝐸𝐸𝐸𝐸0 is given in mm/day according to Eq. (1), forexample, in which solar radiation, air temperature,humidity, and a wind function are required [3].

PURPOSEThis paper analyzes potential evaporation timeseries data for both windy and non-windy seasons
using the Penman–Monteith method in order todeterminethedifferencesin
potential
evapotranspiration, to promote modern methods ofirrigation, and to propose changes in local methods ofirrigation and rainfall irrigation. The effect that thesestrong winds exert on greater 𝐸𝐸𝐸𝐸0 is an important
issue.
A) Confirm the efficiency of raw data by
establishing the numerical order by comparing eachterm shown in the reference.
B) Confirm the effect of wind velocity on 𝐸𝐸𝐸𝐸0
during the period of the 120-day winds by evaluatingeach component of 𝐸𝐸𝐸𝐸0 .

𝐸𝐸𝐸𝐸0 = 𝐸𝐸𝐸𝐸rad + 𝐸𝐸𝐸𝐸wind

𝑬𝑬𝑬𝑬𝒓𝒓𝒓𝒓𝒓𝒓= 𝟎𝟎. 𝟒𝟒𝟒𝟒𝟒𝟒∆(𝑹𝑹𝒏𝒏 − 𝑮𝑮 ÷{∆ + 𝛄𝛄(𝟏𝟏 + 𝟎𝟎. 𝟑𝟑𝟑𝟑𝑼𝑼𝟐𝟐 )}(2)
𝐸𝐸𝐸𝐸wind = 𝛾𝛾average

13.5

1409.9

25.8

Min

−0.1

360.0

7.9 (FARAH)

HERAT

16.1

964.0

21.1

max

𝑈𝑈2 d𝐸𝐸 ÷ {∆ + 𝛾𝛾 (1 + 0.34𝑈𝑈2 )} (3)

(4)

where
𝐸𝐸𝐸𝐸0
is
the
referencecrop
evapotranspiration (mm/day), 𝐸𝐸𝐸𝐸wind is a wind term
(mm/day), 𝐸𝐸𝐸𝐸rad is a radiation term (mm/day), ∆ isthe slope of the saturated air vapor pressure curve(kPa/°C), 𝑅𝑅n is the net solar radiation at the crop
surface (NJ/m2 day), 𝐺𝐺 is the soil heat flux density(MJ/m2 day), 𝛾𝛾 is the psychrometric constant(kPa/℃), 0.06 (kPa/℃) was used for Herat, T is themean daily air temperature at a height of 2 m (℃), U2
is the wind speed at a height of 2 m (m/s), d𝐸𝐸 is thevapor pressure deficit (kPa), 𝑒𝑒s is the saturated air
vapor pressure (kPa), and 𝑒𝑒a is the actual air vapor
pressure (kPa).
RESULTS AND DISCUSSION
Considering the accuracy of the collected data andthe predicted basic equations, some features of theclimate data for Herat are shown in Fig. 2 to Fig.5.
The collection of precipitation data for ouranalysis was challenging. This problem is notessential to𝐸𝐸𝐸𝐸0 ; however, details about this problem
are shown in Table 2.
The collection of sunshine duration data was also
challenging. These data was inaccessible because it
could not be obtained from the National Climatic
Data Center (NCDC). Although it is included in the
FAO’s database, a detailed annual analysis is not
feasible because only average data is included.
However, we were able to observe cloud covermeasured at Herat International Airport using
weatherspark.com. Although this cloud cover
fraction includes daytime information, we were able
to confirm the experimental relation with the daytime
ratio n/N, in which the daytime length n was obtained

Table 1 Profile of the measured data
Altitude(m)
3366.0NORTHSALANG

900

𝑇𝑇+273d𝐸𝐸 = 𝑒𝑒s − 𝑒𝑒aFig. 1 Weather conditions for cultivating wheat inwinter in Afghanistan. Red: intensity of hotness
given by air temperature. Green: intensity oflowness of altitude. Blue: intensity of wetness given
by precipitation. The data were downloaded fromclimatemps.com.

Temperature
(°C)
21.7
JALALABAD
Red color(1)

Rainfall(mm/y)
82.7(NORTH-SALANG)
Blue color

BASIC EQUETION
𝐸𝐸𝐸𝐸0 is an important index of hydrologic budget
for different spatial scales and is a critical variable forunderstanding regional biological processes. 𝐸𝐸𝐸𝐸0 is
also an important variable in the estimation of actual501

GEOMATE- Brisbane, Nov. 19-21, 2014

4) At last, for confirming the variable andstochastic 𝑈𝑈2 that increases during the summer, therelation between air temperature 𝑇𝑇 and wind velocity
𝑈𝑈2 are shown in Fig. 5. In this Fig.5, the straight line
demonstrates that 𝑈𝑈2 is linear to the air temperature𝑇𝑇.
We are presuming it so special straight line given for120 days wind places.

Rn (MJ/m2/day)

Where n/N represents the relative sunshine
duration, n represents the actual duration of sunshine(h), and N represents the maximum possible durationof sunshine (h).

relative sunshine
duration n/N

1.0
0.8

16
14
12
10
8
6
4
2
0

y = -1.095 x + 0.848
R² = 0.872

0.4

2.0
1.0

dE

0.0
2

3

4

5 6 7 8 9 10 11 12
month in 20125wind velocity U2 (m/s)

0.00
0.10
0.20
0.30
0.40
monthly cloud cover fraction including nighttime

Fig. 2 Experimental relation between monthly cloud
cover fraction, including nighttime, and relative
sunshine duration in 2012.
12
ET0 (mm/day)

4.0

Fig. 4 Wind velocity U 2 , vapor pressure deficitd𝐸𝐸, airtemperature T, and solar radiation Rn

0.2

10

U2

3.0

1

0.6

0.0

5.0
Rn

dE((kPa)n/N = 0.848 − 1.095 × (cloud cover fraction
including nighttime)(5)

U2 (m/s)from the Herat Metrological center the experimental
results are shown in Fig. 2 and Eq. (5). In cases where
the daytime length could not be obtained, Eq. (5) was
helpful for the analysis.

ET0

4
3
2
1
0

y = 0.0915x + 1.1338
R² = 0.6928

0

10

20

30

40

average air tempereture T (oC)86Fig. 5 Experimental relation between air temperature
and wind velocity in which the data were monthly
given in 2012.

ETwind

4
2
ETrad

0
1

2

3

4

5 6 7 8month in 2012

9

CONCLUSION

10 11 12

By analyzing 𝐸𝐸𝐸𝐸0 time-series data for both windy
and non-windy seasons using the Penman–Monteithequation, the next conclusions were given.
In the process of data treatment, the practical
relation that has the large determination coefficient
0.872 between monthly cloud cover fraction andrelative sunshine duration was confirmed.
The peak 𝐸𝐸𝐸𝐸0 was more than 10mm/day. About
80% of this peak was consist of wind factor ET wind .
For this reason, 120-day winds can be expressed as
the reasons of the large ET 0 in Herat province.
In Herat province, by the occurrence of 120-day
winds, the experimental solid relation having
determination coefficient 0.6928 between monthly air
temperature and wind velocity could be seen.

Fig.3 ET rad , ET wind , and ET 0
2) In Fig. 3, 𝐸𝐸𝐸𝐸rad and 𝐸𝐸𝐸𝐸wind are shown with
𝐸𝐸𝐸𝐸0 for the months in 2012 that correspond to basiceq. (1). The peak of 𝐸𝐸𝐸𝐸0 was confirmed to exceed 10
mm/day. Although an extremely large order of 𝐸𝐸𝐸𝐸0
was given, we have not way to express this largeness,because we can’t compare that with another now.
𝐸𝐸𝐸𝐸wind was significantly larger than 𝐸𝐸𝐸𝐸rad from Juneto September during the period of 120-day winds.
3) In Fig.4, the monthly change of the 𝑈𝑈2 , 𝑅𝑅n , andd𝐸𝐸 are shown. These 𝑈𝑈2 , 𝑅𝑅n and d𝐸𝐸 are importantvaluables about 𝐸𝐸𝐸𝐸rad or 𝐸𝐸𝐸𝐸wind in eq. (2) and eq.
(3). 𝑅𝑅𝑛𝑛 and d𝐸𝐸 those have the peak at summer seemto be common. However, the occurrence of peak windvelocity 𝑈𝑈2 during the summer was also measured in
Herat province. Therefore, it is not easy for us toseparate and discuss about the impact of each of 𝑅𝑅n ,d𝐸𝐸 and 𝑈𝑈2 . This kind of difficulty is expected to exist
at where 120 days strong wind are blowing.

ACKNOWLEDEMENT
To address the challenges of data collection,
climate data is continually improving.

502

GEOMATE- Brisbane, Nov. 19-21, 2014

The feature of Accessible databases is shown in Table 2.
Table 2 Accessible online databases for irrigation planning (2014)
Name
CROPWAT (FAO)
CLIPWAT (FAO)
NCDC (NOAA)

Weatherspark.com

climatemps.com

Features
Mean rainfall data,
Mean ET 0 and that’s component data
Air temperature, dew point, and windvelocity
Basic daily data. The primary datafrom Figs. 2, 3, and 4.
Cloud cover, wind velocity, airtemperature, and humidity at the
airport. Hourly data may be available.
Payment is required. Used in eq. (5)Average air temperature andprecipitation.
Monthly average data. Used in Fig. 1.

REFERENCE[1] AFCCC/DOPA:
Herat
Afghanistan,
October, 2001.
[2] Omid AB. R, Surface Irrigation of
Afghanistan. Herat: Satarae Noghrae, 2009,ch. 8.
[3] Richard G. Allen, Luis S. Pereira, Dirk Raes,
Martin Smith: Crop evapotranspiration Guidelines for computing crop waterrequirements - FAO Irrigation and drainage
paper 56, FAO - Food and Agriculture
Organization of the United Nations, Rome,
1998.

503

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

USE OF GENETIC PROGRAMMING BASED SURROGATE MODELS TO SIMULATEGROUNDWATER FLOW AND BIOCHEMICAL TRANSPORT PROCESSES IN CONTAMINATEDMINE SITES
Hamed Koohpayehzadeh Esfahani Esfahani1 and Bithin Datta1,2
School of Engineering and Physical Sciences, James Cook University, AUSTRALIA;
2
CRC for Contamination Assessment and Remediation of the Environment (CRC-CARE), Mawson Lakes
SA 5095, AUSTRALIA
1

ABSTRACTTransport of contaminant species undergoing chemical reactions in groundwater aquifers is a complex
physical and biochemical process. Simulating this transport process involves solving complex nonlinear
equations and requires huge computational time for a given aquifer study area. Development of optimal
remediation strategies in aquifers may require repeated solution of such complex numerical simulation models.
To overcome this computational limitation and improve the computational feasibility of large number of
repeated simulations, Genetic Programming based trained surrogate models are developed to approximately
simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant isfirst simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a study area resembling a minesite. Simulation model solution results for an illustrative contaminated aquifer site is then approximated bytraining and testing a Genetic Programming (GP) based surrogate model. To decrease the total number of GP
formulations, the coordinates of observation locations are implemented as input data in the surrogate models.
Comparison of the surrogate models and numerical simulation results show that the surrogate models canprovide acceptable approximations of this complex transport process in contaminated groundwater aquifers.
Keywords: Biochemical transport simulation, Genetic programming, Acid mine drainage, contaminated aquifers,
surrogate models.
INTRODUCTION
Simulation of flow and transport processes forchemically reactive species in contaminatedgroundwater aquifers generally require extensive
computational time. When repeated simulations arenecessary to implement and solve optimization
based decision model, e.g., to develop optimal
aquifer management strategies, the computationalburden may determine the feasibility of any
methodology. To address this, trained surrogate
models approximating the simulation model can be
developed. These surrogate models are generally
computer programs describing the relationshipbetween output values (e. g., pollutant concentration
at different locations and times) and input values(e.g., pollutant flux at potential pollutant source
locations). Simulation of reactive species transport
process (i.e. Acid mine drainage (AMD)) incontaminated groundwater aquifers is complex andcomputationally intensive. Therefore it is useful todevelop trained and tested surrogate models toapproximately simulate the transport processes. In
this study, the flow and biochemical transport
simulation model is replaced by trained genetic
programming (GP) as surrogate models which can
reduce consumption time.
An accurate description of the contaminanttransport in aquifers is obtained if both chemical andphysical behaviors of contaminant species areincorporated. Solution of the transport process withchemical reactive species in groundwater wasaddressed by [1] and developed by [2-4]. One
approach couples the non-reactive transport model
MT3DMS [5] with various chemical reactive
transport simulators [6-10]. HYDROGEOCHEM[11] was the first comprehensive three dimensional
simulator of hydrogeologic transport andgeochemical reaction in saturated-unsaturated media[11]. This code was developed to solve
comprehensive heat, reactive geochemical andbiochemical transport [12]. The proposed
methodology uses HYDROGEOCHEM 5.0 (HGCH)
as the simulation model for AMD transport processwith chemically reactive pollutants for an illustrative
study area with synthetic hydro-geochemical data.
These simulation results are then utilized to train andtest a GP based surrogate model.
AMD, which is the result of wastewater frommetal mines or coal mines containing sulphur
compounds [13], is hazardous contaminant sources
for groundwater. Various sulphide minerals
constitute AMD based on their chemical weathering
reactions such as pyrite (FeS2), pyrrhotite (Fe1-xS),
chalcopyrite (CuFeS2), arsenopyrite (FeAsS), etc.
[14]. Beside mining activities, rocks’ surface
weathering in presence of water, oxygen andmicroorganisms
producesAMD.
Thesecontaminants are considerable threats for water
resources. In this study, the transport process of504

GEOMATE- Brisbane, Nov. 19-21, 2014

copper and sulphate, hazardous AMD’s compounds,along with their chemical reactions through theaquifer is considered.
A response matrix approach as an initial linear
surrogate model was earlier used to simulate theaquifer responses [15], [16]. More recently
proposed non-linear surrogate models include
Artificial Neural Network (ANN) and Genetic
Programming (GP) based surrogate models [17].
Reference [18] implemented ANN as a surrogate
model to replace the flow and transport simulationin the non-dominated front search process as wellas to save a huge amount of computational time.
References [19] and [20] used GP as meta-model
for simulation of pumping saltwater patterns in an
optimization
framework.
Reference[20]
demonstrated GP model have several advantages
compared with conventional surrogate models andANN surrogate models. These advantages are:simpler surrogate models, optimizing the model
structure more efficiently, and parsimony ofparameters. Use of GP surrogate model forgroundwater contamination management, anddevelopment of a monitoring network design
feedback methodology to identify unknown source
characteristics was addressed by [21].

solutions. It is a computer program that numericallysolves the three-dimensional groundwater flow andcontaminant transport equations for a porous
medium. The finite-element method is used in thissimulation model. The general equations for flow
through saturated-unsaturated media are obtained
based on following equations [11]:

(1)

= .

.

+

+

∗

K is the Hydraulic conductivity tensor (L/T)
and F is the generalized storage coefficient (1/L)
defined as:
=

=

(3)

+

=

( /

( /

+

(2)

)

=

)

( /

( /

)

)

Where:: effective moisture content (L3/ L3);
h: pressure head (L);t: time (T);z: potential head (L);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*) orwithdraw (= ρ) (M/ L3);
: fluid dynamic viscosity at zerobiogeochemical concentration [(M/L)/T];µ: the fluid dynamic viscosity with dissolved
biogeochemical concentrations [(M/L)/T];
α’: modified compressibility of the soil matrix(1/L);
ß: modified compressibility of the liquid (1/L);
ne: effective porosity (L3/L3);
S: degree of effective saturation of water;
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 general transport equation using advection,
dispersion/diffusion,
source/sink,andbiogeochemical reaction as the major transport
processes can be written as follows:

METHODOLOGY
The current study proposes and evaluates amethodology, which includes two steps. In the 1ststep, a numerical simulation model with specified
boundary conditions, specified existing initial
hydraulic and geochemical conditions, and withestimatedhydrogeologic
andgeochemicalparameter values is used to simulate flow andbiochemical transport processes for hazardous
compounds of AMD such as sulfate and copper, ina given contaminated aquifer. The specified
illustrative aquifer resembles an abandoned (nolonger in operation) mine site in Queensland,
Australia, where similar contaminants are present
and similar topologic and hydrogeologic conditions
exist. In the second step, trained GP models are
implemented to obtain pollution concentration at
specified locations of the contaminated aquifer.
These concentrations obtained using the surrogate
model and those obtained by solving theimplemented numerical three dimensional transient
reactive contaminant transport simulation model(HGCH) are compared to evaluate the potential
applicability of the GP based surrogate models.
Simulation Model for Groundwater Flow and
Biogeochemical Transport

∫

∫
(4)

The HGCH flow and transport simulation model
consisting of the flow simulation model and physiochemical transport model to obtain numerical
505

= −∫

+∫

.(

, ∈

)

−∫

.

+

GEOMATE- Brisbane, Nov. 19-21, 2014

nt: the total number of monitoring time steps.
nob: the total number of observation wells.
Performance
EvaluationofDeveloped
Methodology: the concentration of the i-th species in moleper unit fluid volume (M/L3);
ν: the material volume containing constantamount of media (L3);: the surface enclosing the material volume ν(L2);n:the outward unit vector normal to the surface;
Ji: the surface flux of the i-th species due todispersion and diffusion with respect to relative fluid
velocity [(M/T)/L2];
θri: the production rate of the i-th species perunit medium volume due to all biogeochemical
reactions [(M/L3)/T];
Mi: the external source/sink rate of the i-th
species per unit medium volume [(M/L3)/T];
M: the number of biogeochemical species;
Vi: the transporting velocity relative to the solidof the i-th biogeochemical species (L/T).

To evaluate the performance of the proposedsurrogate models and compare it with actual
simulation model solution results, a hypotheticalhomogeneous and isotropic aquifer is utilized as anillustrative example as shown in Fig. 1. The grey
area represent the contaminant sources S(i) which
include distributed and point source. The
monitoring networks are shown in Fig 2. Cells
marked with green circle, wells set 1, are the grid
locations containing a monitoring well which theirdata are used to train, test and validate GP models’
formulations. Moreover, Cells marked with yellow
and blue circle are the grid locations containing amonitoring well with their coordinates within, andbeyond range of location coordinates implemented
in GP formulations, respectively. Groundwater flow
and solute transport process is simulated withhydro-geological parameters as given in Table 1.
The synthetic concentration measurement data used
for the specified polluted aquifer facilitates
evaluation of the developed methodology.

Surrogate Model
Genetic Programming (GP) models are used inthis study to develop surrogate models toapproximately simulate flow and transport
processes. Trained GP models are developed using
the simulated response of the aquifer to randomly
generated source fluxes. The selected GP models
can replace the numerical simulation model to obtain
concentration of contaminants in observation wells.
GP, a branch of genetic algorithms, is anevolutionary algorithm-based methodology inspiredby biological evolution to find computer programs
that perform a user-defined task. Essentially, GP is aset of instructions and a fitness function to measure
how well a computer model has performed a task.
GP utilizes a set of input-output data which are
generated randomly by simulation model. The
numerical Simulation model creates M number ofout-put sets from M number of input sets, which is
generated by using random Latin hypercube
sampling in a defined range. The performance ofeach GP program is evaluated in terms of training,
testing, and validation using the set of input-output
patterns. The testing data evaluates the model
performance for new data without developing a new
fitness function. To compare the GP and HGCH
results at the same location, the normalized error isused as defined by the following equation:
=∑

∑

(

)

Fig.1
Example definition and flow boundary
conditions (Total Head: A= 37 m, B= 40 m, C=
33m, D = 30 m; Level (F)= 37m)

(5)

ABS: the absolute value of: the concentration simulated by the
HGCCH model at observation monitoring location
iob and at the end of time period k (ML-3).
: the concentration estimated by the GP
models at observation monitoring location iob and at
the end of time period k (ML-3).

Fig. 2506

Location of concentration measurements

GEOMATE- Brisbane, Nov. 19-21, 2014

In the incorporated scenario, copper (Cu++) andsulfate (SO4--) are introduced as initial pollutants insources, which are involved chemical reactions,which are showed in table 2.
Table 1concentration values for each of the 32 values,
Cpit(i) and C(i) as well as Spit (i) and S(i) (i=1 to 8),
representing two sources, two kind of contaminants,
and eight active stress periods. Although 128 GP
formulations need to be generate in this scenario, thewell coordinates are used as input data for GP
models to decrease the number of GP models
required. Therefore the numbers of models are
reduced to 8 models for copper, as well as eightmodels for sulfate which are generated based on
pollution concentration in sources and locations ofdata measurement. The corresponding output dataconsists of the resulting pollutant concentration
measurements due to these source fluxes at all the 10
monitoring well at time t1 =100, t2 =200, t3 =300,
t4 =400, t5 =500, t6 =600, t7 =700 and t =800 days.
1,000 data patterns comprising of inputs and thecorresponding outputs are used in the GP models.
Out of total data patterns, 40 % is used for training,
30 % for validation, and the remaining 20 % for
testing. A Latin Hypercube distribution (MATLAB
R2020b) was used for generating the random
pollution values ranging between 0 g/lit and 100
g/lit, as the input. The corresponding output data
was simulated using HGCH code. DiscipulusTM(RMLTechnologies, Inc.) is used for training,validation and testing of the GP models.

Aquifer’s properties

Aquifer Parameter
Length of study area
Width of study area
Thickness of study area
Node numbers
Element numbers
Hydraulic conductivity, K
Effective porosity, ƟLongitudinal dispersivity, αLTransverse dispersivity, αT
Horizontal anisotropy
Initial contaminant concentration
Diffusion coefficient

Unit
m
m
m

Table 2
Chemicalcontaminants’ transport

duringreactionsChemical Reaction Equations
Cu++ + H2O ↔ Cu(OH) + + H+
Cu++ + 2H2O ↔ Cu(OH) 2 + 2H+
Cu++ + 3H2O ↔ Cu(OH) 3- + 3H+
Cu++ + SO42- ↔ CuSO4

m/d
m/d
m/d
g/lit

Value
100
100
50
387
1432
10
0.3
6
3
1
0-100
0
the

Constant Rate
(Log k)-9.19-16.19-26.9
2.36

RESULTS AND DISCUSSION
The output data from HGCH are compared with
GP model results at three arbitrary monitoring
networks. The coordinates of first set of wells in thefirst network are implemented for GP models
creation, and the coordinates of second and third
monitoring networks are within and beyond therange of first well’s location, respectively. These
comparison results are shown in Figs 3, 4 and 5.
Each time step is marked on the x-axis. Each of thebars corresponds to contaminant concentration ineach well, obtained by HGCH and GP models. Fig 3shows the HGCH and GP results in different time
steps for wells set 1. Fig 4 and Fig 5 demonstratethese results for wells set 2 and set 3, respectively.
Figures 3, 4 and 5 show that the results obtained
from GP models are very close to the simulated
results obtained using a numerical simulation model.
Although few wells’ coordinates are used as input
data for GP models, these models can estimate theconcentration for all locations in the aquifer such aswells set 3, which shows acceptable results (Fig 5).
Figure 6 shows the summation of normalized
error for each monitoring network in each period oftime. As expected, generally GP models provide
relatively accurate results for well set 1. However,errors for data set 2 and 3 are also small even thoughcomplex contaminant transport process withchemical reaction of species is involved in theevaluated scenario.

The source activities are specified for eightsimilar time intervals of 100 days each. The actual
pollutant concentration from each of the sources ispresumed to be constant over a stress period. The
pollutant concentration of copper as well as sulfate
in the pit is represented as Cpit(i) and Spit(i)respectively, where i represents the stress period
number, and also C(i) and S(i) represent copper andsulfate concentrations in the point sources,
respectively at different time steps. An overall of
sixteen concentration values for each contaminant
are considered as explicit variables in the simulation
model. The concentration measurements are
simulated for 800 days since the start of thesimulation.
The
pollutantconcentration
measurement at the observation wells starts at time
t=100 days and are measured after every 100 days at
all the observation locations till t=800 days. Figure 3
shows the pollutant concentration profile in the
study area.
Genetic Programming formulation
Copper and sulfate concentration in sources are
the two main input data sets which consist of sets of507

GEOMATE- Brisbane, Nov. 19-21, 201440

and complexity, and appear to provide acceptable
results. However from the limited results in thisstudy, it cannot be concluded if the surrogate models
can replace the simulators in all situations. Thismethod can be applied to real scenarios ofcontaminated aquifers where especially repeatedrunning of numerical simulation models is required,e.g., in linked simulation-optimization model where
computational time is a major constraint. GP basedsurrogate models can increase efficiency andfeasibility of developing optimal management
strategies for complex contaminated aquifers such asmine sites.

30
20
10
0
t1

t2

t3

t4

50

40

0
RW1
RW3
RW5
RW7
RW9

Fig. 3

t5

GP1
GP3
GP5
GP7
GP9

t6

t7

RW2
RW4
RW6
RW8
RW10

GP2
GP4
GP6
GP8
GP10

30

t8

20
10
0

60

t2

t3

t5

t6

t4

40

40

20

20

0

0
t1

t2

t3

t4

RW'1
RW'3
RW'5
RW'7
RW'9

50

Fig. 5t5

t6

t7

Normolized eroor (%)

0
t8

HCHW1

GW1

HCHW2

GW2

HCHW3

GW3

HCHW4

GW4

HCHW5

GW5

HCHW6

GW6

HCHW7

GW7

HCHW8

GW8

HCHW9

GW9

HCHW10

GW10

Fig. 4t1
60Comparison data in wells set 1

Comparison data in wells set 2

The developed methodology based on GP
models for approximate simulation of the chemicallyreactive multiple species transport process appears
to result is acceptable approximate representation of
the transport process in a contaminated aquifer
resembling an abandoned mine site. The developed
GP models result in reducing the computational time

Fig. 6

RW'2
RW'4
RW'6
RW'8
RW'10

t8
GPW'2
GPW'4
GPW'6
GPW'8
GPW'10Compare data in wells set 3
4
3
2
1
0
t1

t2

wells set1

CONCLUSION

t7

GPW'1
GPW'3
GPW'5
GPW'7
GPW'9

t3

t4

t5

wells set2

t6

t7

t8

wells set3

Normalized errors for all wells sets

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508

GEOMATE- Brisbane, Nov. 19-21, 2014

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509

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

DECONTAMINATION OF RADIOACTIVE CESIUM FROM OCEANSLUDGE BY MICRO-BUBBLE AND MICROORGANISMS
Kyoichi Okamoto1 and Takeshi Toyama1
1
CST, Nihon University, Japan

ABSTRACTThe Fukushima nuclear accident of March 11, 2011, soil and water had been contaminated by radioactive
cesium. Moreover, radioactive cesium was found in the ocean sludge in Tokyo Bay by flowing from rivers. Here,it cannot be easily removed the cesium which is adsorbed to the sludge. On the other hand, one of the authors had
developed the decomposition system for ocean sludge with circulation type by micro-bubbles, which decompose
and purification sludge by activating the aerobic bacteria, after creating an aerobic state by micro-bubbles. Here,based on the hypothesis that radioactive cesium is adsorbed on the surface of the sludge deposition. It is consideredthat radioactive cesium can be eluted, after decomposing the deposited sludge by using the decomposition systemfor ocean sludge with circulation type. If the cesium will be eluted in the water, we can fix the cesium to existing
technology such as “Zeolite”. In this study, our objects is to consider the performance of removal of radioactive
cesium after the decomposition of the deposited sludge, by using the decomposition system for ocean sludge withcirculation type by micro-bubbles and activating microorganisms.
Keywords: Decontamination, Radioactive Cesium, ocean Sludge, Micro-bubble, Microorganisms

INTRODUCTION
wave

The Fukushima nuclear accident on March 11,
2011, soil and water had been contaminated byradioactive cesium. Moreover, radioactive cesium
was found in the ocean sludge in Tokyo Bay byflowing from rivers. A report says it becomes 13
times of the cesium for 7 months from August, 2011
in [1]. Here, it cannot be easy to remove the cesium
which is adsorbed to the sludge.
On the other hand, one of the authors had
developed the decomposition system for ocean sludge
with circulation type by micro-bubbles, which
decompose and purification sludge by activating the
aerobic bacteria, after creating an aerobic state bymicro-bubbles.
Here, based on the hypothesis that radioactive
cesium is adsorbed on the surface of the sludge
deposition in [2], it is considered that radioactive
cesium can be eluted, after decomposing thedeposited sludge by using the decomposition systemfor ocean sludge with circulation type.
If the cesium will be eluted in the water, we canfix the cesium by the existing technology such as“Zeolite”.
In this study, our objects is to consider the
performance of removal of radioactive cesium after
the decomposition of the deposited sludge, and also
show the mechanism of adsorption, elution and fix of
cesium as our hypothesis, by using the decomposition
system for ocean sludge with circulation type by
micro-bubbles and activating microorganisms.

current

Sea Bottom

Micro-bubble Generating

Pump

Experimental Tank

Fig. 1 Purification System of Circulation Type.

DECOMPOSITION SYSTEM WITH
CIRCULATION TYPE
It is very important to reduce sedimentary sludge
in the ocean. Plans to reduce the sludge are usually
dreading or sand covering. Dredging is a simple way
and aims to cut off the sludge. But after cutting off,
treating the dredged sludge takes much more time and,of course, cost. Sand covering, in general, gives a big
load to living organisms and the ecological system.
So that, a more efficient way is needed to reduce510

GEOMATE- Brisbane, Nov. 19-21, 2014

the sludge while not imparting environmental load in
the local sea area. Here, attention was paid to microbubble technology for application to the purificationof the sludge. The important point in this technique isto activate the bacteria existing in the area by microbubbles. Micro-bubbles (that is MB) can change
conditions into an aerobic state. If the bubbling stops,
the situation changes into anaerobic state, according
to recent research. So, we selected a method fordecomposing the sludge by microorganisms.
One of the authors had developed thedecomposition system for ocean sludge withcirculation type by micro-bubbles, shown in Fig.1,
which decompose and purification sludge byactivating the aerobic bacteria, after creating an
aerobic state by micro-bubbles.

ELUTION EXPERIMENTS FOR CESIUM
Procedure of Elution Experiment
The experimental devices consist of two parts,
shown in Fig. 1. The water circulates through twotanks. In one tank (Width40xLength28x Hight28cm),
micro-bubbles are generated. The micro-bubbles
have micro-size diameter and high solubility. Thismeans the water with high concentration of dissolved
oxygen circulates through these tanks. The other partis the experimental tank (W60xL29xH35cm). We
used sea-water 30(litter) and sludge 1(kg). Here, amicro-bubble generator is based on [3], [4] and theflow rate is 900 (litter/hour). The flow rate of water
pumps connected each tanks are 300 (litter/hour).
We had caught the sludge and the sea water at
Funabashi Port in Chiba Prefecture in JAPAN, as
shown in Fig.4 and 5. Here, we had removed under
10cm of the sludge from seabed before sampling as
experimental procedure, because we have to remove
the initial value of cesium in the sludge, as shown in
Fig. 6.

MECHANISM ON FIXING OF CESIUM FROMELUTION
In general, ocean sludge has a negative charge.
When cesium with a positive charge flows from river,sludge was adsorbed cesium, shown in Fig 2. So that,sludge adsorbed cesium cannot eliminate by usual
way.

Tokyo

Sludge--Cesium
Cs+

-

-

-

-

Adsorption

Cs+

Cs+
Cs+
Cs+

Cs+

Cs+

Cs+

- Cs+

-

-

Yokohama

- Cs+
-

Cs+

-

-

-

Cs+

Cs+

Cs+

- Cs+ -

Cs+-

Fig.2 Mechanism on Adsorption of Cesium.

Here, we have a way by using of thedecomposition system for ocean sludge withcirculation type. After decomposition of the sludge
adsorbed cesium by our system, cesium is eluted into
water, shown in Fig 3. That is our hypothesis.

ElutionAdsorption
Cs+

-

Cs+

- Cs+

-

-

-

Cs+

-

Cs+
Cs+
Cs+

Cs+

- Cs+ -

Cs+-

Decompositionof Sludge

Fix of Cesium
No Elution while
adsorption stateFig.4 Catching Point of Sludge and Sea Water at
Funabashi Port in Tokyo Bay.

Ｂｙ Usual Technology

Cs+

Cs+

Cs+

Cs+

Cs+
Cs+

Cs+

Cs+

Fig.5 Scene of Catching Sludge.

OKfor example: Zeolite,
Fiber for Adsorption etc.

Fig.3 Mechanism on Fixing of Cesium from Elution.

511

GEOMATE- Brisbane, Nov. 19-21, 2014

BeforeRemoving

After

Removal of the sludge
under 10 cm from sea bottom

Fig.8 Case 2 of Experiment for Elution of Cesium.

Fig.6 Removal of the Sludge under 10 cm from Sea
Bottom.

Results of water temperature, pH and DO as
environmental condition

We used the cesium chloride before 24 hours ofstarting time and the concentration of cesium ion is
100 (ppm). An air conditioner for water tank was set
at the tank for generating microbubbles, for the
purpose of setting water temperature 30 degree
centigrade.
After setting the decomposition system for ocean
sludge with circulation type by micro-bubbles,
experiment starts at the same time of generating
micro-bubble device.
After 6 hour, the microorganism activator was putin the experimental tank. Main staff of the activator is
Kelp and including nutrients and some enzyme. Our
used activator is reported to show effective results inpurification for grease trap.
Dissolved oxygen (DO), water temperature andpH are measured by using of multi-parameter water
quality meter. Ammonium nitrogen (NH4-N), total
nitrogen (T-N) and total phosphorus (T-P) aremeasured by using of digital-water-analyzer bydigital “Packtest”, by water filtered after sampling inexperimental tank.

Fig.9-11show the water temperature, pH and DO(Dissolved Oxygen) as the results of environmental
condition of this experiment.
Water temperature is almost constant about 30
degree centigrade after 6 hours. pH is also constant
about 7.2 to 7.8. DO in Case 1 is saturation state but
DO in Case 2 rise because of mixing at putting
microorganism activator after 6 hours, and thenbecame constant. After 24 hours, DO value riseslowly, it seemed that water is mix by the work ofsampling for measurement.

Water Temperature [℃]40

Experimental Conditions

30
20
10

0

As experimental conditions, Case 1 is a case ofusing the decomposition system for ocean sludge withcirculation type by micro-bubbles, shown in Fig.7.
Case 2 is no micro-babbles and no circulation but isused the microorganism activator, shown in Fig.8.

Case 1Case 2
24

48
Time [hour]Fig.9 Changes in Water
environmental conditions.

72

96

Temperature

as

10.0
8.0
pH

6.0
4.0
2.0
0

Case 1Case 2
24

48
Time [hour]72

96

Fig.7 Case 1 of Experiment for Elution of Cesium.
Fig.10 Changes in pH as environmental conditions.

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GEOMATE- Brisbane, Nov. 19-21, 2014

4.0

10.0

6.0
4.0
2.0
0

Case 1Case 2

3.0

T-N [mg/l]

DO [mg/l]

8.0

2.0
1.0

Case 1Case 2
24

48
Time [hour]

72

96

0

24

48
Time [hour]72

96

Fig.11 Changes in DO as environmental conditions

Fig.14 Changes in T-N.

Results of H2S, NH4-N and T-N

Results of Cesium (liquid)

Fig.12-14 are shown in results of H2S(Hydrogensulfide), NH4-N and T-N.
H2S(Hydrogen sulfide) in Case 1 decrease rapidly,
it seemed by the supply of Oxygen. Case 2 showed
always lower limit of measurement, the reason is no
H2S in sampling water by separation of water andsludge because of no movement of water.
NH4-N in case 1 has tendency of decrease but case2 has no decrease. T-N in case of 1 also has tendency
of decrease over 50% but case 2 has no decrease.

The results cesium were obtained by the ironchromatography shown in Fig 15. The result of Case
1 is considered about 30.9% elution. Results of Case
2 is not bigger than initial value, this means no elution.
8.0

Cs +

6.0

2.0

0.20

Case 1Case 2

Case 1Case 2

0.15

H 2S [mg/l]

4.0

0

24

48
Time [hour]

72

96

0.10

Fig.15 Changes in Cesium.
0.05

Results of Cesium (solid)
0

24

48
Time [hour]72

96

We paid attention to cesium and silica (Si), as
there are many chemical element in sludge. We usedthe energy dispersion type X-ray analysis device,because we can measure by the solid state. Weightratio of cesium and silica (CS/Si) in solid of dry
sludge are shown in Fig.16.
Ratio of case 2 increase 50% after 72 hours but
final result is same of initial one. It seemed cesium insolid is no change of initial value.
Ratio of case 1 decrease at first after 24 hours, it
increase at 48 and 72 hours and it decrease at 96 hours.
This is considered that Cs elutes in water bydecomposition of sludge at 24 hours and then cesium
adhere again to unwrapped silica. It is considered“Re-adsorption” occur.
Mechanism of Re-adsorption is shown in Fig.17.

Fig.12 Changes in H2S.

NH4-N [mg/l]

4.0Case 1Case 2

3.0
2.0
1.0

0

24

48
Time [hour]72

96

Fig.13 Changes in NH4-N.

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GEOMATE- Brisbane, Nov. 19-21, 2014of cesium after decomposition of sludge, and “readsorption”.
0.10

Cs / Si

0.08

Case 1Case 2ACKNOWLEDGEMENTS

0.06

The authors would like to express sincere thanks forchemical analysis to Hirosuke HIRANO, Graduate
student of Nihon University, in Japan.

0.04
0.02
0

24

48
Time [hour]

96

72

REFERENCES[1] Yomiuri News Paper, 13 times by 7 months
about cesium in ocean soil in Tokyo Bay, May,
13th, 2012.
[2] OKAMOTO Kyoichi and TOYAMA Takaeshi:
Ocean
Decontamination:
RemovalofRadioactive Cesium from Ocean Sludge byUsing Microbubbles and Activating
Microorganisms, The Japan Societyof Naval
Architects and Ocean Engineers, May, 2013.
[3] Imai, T, Shioshige, K, Ukita, M, Sekine, M,
Higuchi, T, Fukagawa, K and Fujisato, T.
Development of Device for Dissolving High
Concentration Gas for Purification at bottom
layer around enclosed water area like Dam Lake,
Proc. 39th Forum on Environmental Engineeringof Civil Engineering Society, 10-12, 2002.
[4] Matsuo, K, Maeda, K, Ohnari, H, Tsunami, Y,
and Ohnari, H., “Water Purification of a Dam
Lake Using Micro Bubble Technology”,
Progress in Multiphase Flow Research I, pp.279286, 2006.
[5] OKAMOTO Kyoichi, HOTT Kenji, TOYAMA
Takeshi and KOHONO Hideki, Purification
System of Ocean Sludge by Activating
Microorganisms, International Journal of
GEOMATE (Geotec, Const. Mat. & Env.),
Vol.6, No.1, pp.791-795, March, 2014.
[6] OKAMOTO Kyoichi and HOTT Kenji,
Purification System of Ocean Sludge by Using
Coagulants and Activating Microorganisms,
International Journal of GEOMATE (Geotec,
Const. Mat. & Env.), Vol.4, No.2, pp.574-579,
June, 2013.

Fig.16 Changes in (Cesium)/(Silica).
ElutionAdsorption
Cs+

-

Cs+

-

Cs+

Cs+

-

-

-

Cs+

-

Cs+
Cs+

Cs+

-

Cs+

-

Cs+

-

Cs+

Cs+

Decompositionof Sludge

Cs+

Cs+

Cs+
Cs+

Silica(SiO2)

Cs+

Cs+

- Cs+
Cs+

Re-Adsorption

-

Cs+

Cs+

Fig.17 Mechanism on Re-Adsorption after Elution.

CONCLUSION
We had carried out the elution experiments for
cesium after decomposing the deposited sludge byusing the decomposition system for ocean sludge withcirculation
type
bymicro-bubble
andmicroorganisms.
From the results by iron chromatography,(1) The elution of cesium is maximum 30.9% in
sea water. It seemed it is very useful system.
From the results of the energy dispersion type Xray analysis device, the weight ratio of cesium andsilica (CS/Si) in solid of dry sludge denote,(2)This is considered that Cs elutes in water bydecomposition of sludge at 24 hours and then cesium
adhere again to unwrapped silica. It is considered “readsorption” occurs.
(3) We showed the mechanism as our
hypothesis, of adsorption to sludge of cesium, elution

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SOLID WASTE MANAGEMENT THROUGH ECOLOGICAL FOOTPRINT ANALYSIS – A CASE STUDY IN KOCHI CITY, SOUTH INDIA
Subha Vishnudas1, Athira Ravi2
Faculty of civil Engineering Cochin University of Science and Technology, Kochi, India, v.subha@cusat.ac.in2
Research Scholar, Faculty of Civil Engineering Cochin University of Science and Technology, Kochi, India

1

ABSTRACT
Urbanization directly contributes to waste generation, and unscientific waste handling causes health hazards andurban environment degradation. Solid Waste Management which is already a mammoth task in India is going to be
more complicated with the increase in urbanization, changing lifestyles and increase in consumerism. Financial
constraints, institutional weaknesses, improper choice of technology and public apathy towards Municipal Solid
Waste (MSW) have made this situation worse. The current practices of the uncontrolled dumping of waste on theoutskirts of towns/cities have created a serious environmental and public health problem. Ecological footprint
analysis (EFA) is a quantitative tool that represents the ecological load imposed on the earth by humans in spatial
terms. This paper narrates the solid waste management issues in Kochi city, the commercial capital of Kerala, South
India, through the environment management tool Ecological Footprint Analysis.
Key Words: Ecological Foot Print Analysis, Solid Waste Management, South India
82% as the decadal rate of urbanisation (2001-2011)
as per Census 2011. 2011 census data positioned in
the 19th rank in the level of urbanization [3]. As per
Census 2011 Ernakulam is the most urbanized districtof Kerala. The only two agglomerations withpopulation more than 20 lakhs are Kochi and
Kozhikode Urban agglomeration. The State
Government is considering elevating the status of thecity of Kochi, its commercial capital, as a
metropolitan city. Kochi has been pushing its borders
over the last decade relentlessly, throwing to wind all
cautioning by planners that a city without a plan,
without public spaces and without respect for its
fragile ecological conditions can prosper only at ahigh cost. Rampant shortage of drinking water is justone. The condition of the roads, traffic congestions
on arterial roads, little space for pedestrians andcyclists, rising levels of noise and air pollution, solid
waste management nuisance are the others. The
difficulty has been aggravated by lack of effective
legislation, inadequate funds and services, andinability of municipal authorities to provide theservices cost-efficiently. In the eye’s of an ordinaryman, the condition of the city is very bad in thepresent stage of unplanned manner especially in thecase of solid waste management and transportsystem, and would wonder what will happen in the
future if the city is raised to a metropolitan status.
This paper narrates the solid waste management
issues in Kochi city, the commercial capital of

INTRODUCTION
Our world is urbanizing at an unprecedented
speed, as the global proportion of urban population
has increased from 28.3% in 1950 to 50% in 2010[1]. By 2015, there will be 23 cities with a population
over 10 million. The percentage of urban population
to total population in US, Europe and China is 83%,73% and 47%, respectively, which is much higher
compared to India, which is just 32%. As per WorldBank
studies,
India,
alongwith China,
Indonesia, Nigeria and the United States, will leadthe world's urban population surge by 2050. In India,
according to the 2011 Census, the urban population
grew to 377 million showing a growth rate of 2.76%
per annum during 2001-2011. The level ofurbanisation in the country as a whole increased from
27.7% in 2001 to 31.1% in 2011 – an increase of 3.3
percentage points during 2001-2011 compared to anincrease of 2.1 percentage points during 1991-2001. .
In 2050, urban India will be home to almost fourteen
percent of the world’s urban population [2]. A very
high urban population growth has occurred in thestates of Kerala and Andhra Pradesh; urban
population growth rates have increased to 6.5% perannum in Kerala and 3% per annum in Andhra
Pradesh during 2001-11 compared to just about 1%
per annum during 1991-2001. Though the population
growth rate is in a decreasing mode, Kerala have515

GEOMATE- Brisbane, Nov. 19-21, 2014

Kerala, South India, through the environment
management tool Ecological Footprint Analysis. As
the ecological footprint analysis can give a quantified
impact compared with the biocapacity of an area,
many ecological footprint studies are initiated inmany countries as a sustainability option. The
ecological footprint of waste generation has been
done in Khulna city corporation of Bangladesh andDigos city. In India, the ecological footprint study ofthe first of its kind has been done in India in Manali,
Himachal Pradesh which was initiated by a Natural
Resource Institute, University of Manitoba in June
1999.

pattern in Kochi city. Constraints of landforms
and lagoon system contributed to the concentration of
economic activities to the water front areas. The
existing land use pattern has resulted from thecomplex interactions of varied factors in the urban
structures. The characteristic feature of the central
city is the predominance of the area under water. The
water sheet consists of backwaters, rivers, canals,
tanks and ponds and altogether it forms 23.4% of thegreen land of the city. The net dry land available forurban use amounts to 71.86% of the gross land i.e.
68.18 sq.km. Truly there could be no ideal location
than this, with its protected lagoons directly
accessible from the sea, for a major terminal port andwith its hinterland bountifully blessed by nature for aconcentration of urban population and activities. But
the present pattern of the city can be classified as thatof haphazard growth with typical problems
characteristics of unplanned urban development.

DEFINITIONOF EFA
Ecological footprint analysis (EFA) is aquantitative tool that represents the ecological load
imposed on the earth by humans in spatial terms.
Ecological footprint analysis was invented in 1992 by
William Rees and Mathis Wackernagel at the
University of British Columbia. The ecologicalfootprint of a defined population is the total area ofland and water ecosystems required to produce theresources that the population consumes, and toassimilate the wastes that the population generates,
wherever on earth the relevant land/ water are located[4] The footprint is the area, expressed in global
hectares, needed to keep producing the food and fibre
we use, absorb our wastes, generate the amount ofenergy we consume and provide the space for theroads, buildings and other infrastructure we rely on.
Our ecological footprint is the sum of those areas(ecologically productive space) we need to sustain
the lifestyle of each person. This would be the area ofcropland necessary to produce the food we eat, thearea of grazing land for producing animal products;
the area of forest to produce wood and paper; the areaof sea to produce the fish and seafood we consume;
the area of land to accommodate housing andinfrastructure; and the area of forest necessary toabsorb the CO2 from our energy consumption [5]EFA OF KOCHI CITY
The study shows that the consumption rate
(EF=2.19gha) of the population in the city is very
high and it is far exceeding the national average(0.8gha) and the nations biocapacity (0.4gha) and theavailable bio capacity per person in the world(1.8gha). It also shows that shelter footprint, whichmainly depends on the house area usage and numberof occupants, is very high in the city. The improper
waste disposal at the source (residential units) is
increasing the waste footprint of the population
which results in the high goods and services
footprint. The waste disposal is the second major
component increasing the population’s ecologicalfootprint. For the detailed study of waste footprint of
the city, a questionnaire survey was conducted for
500 representative samples in three different seasonsi.e dry, wet and festival season, inside the
Corporation boundary and random samples in theoutskirts. The samples were selected based on
density of population (high and low), location (awayand near of CBD and major transportation nodes),mode of waste disposal (household level orcommunity level), type of housing unit(individual
plots, low rise building, row housing units, high risebuilding) and ownership of the building(individuals,
government, builders). Samples were selected in sucha way to include as many samples in these criteria.
The wastes generated from samples were categorized
into paper, glass, plastic, metal and organic waste(mainly food waste). The amount of paper waste wasindirectly taken from the periodicals. The amount ofglass and metal waste generated in a week was takenin account. The survey was done in three different

STUDY AREA
The study area of research is the city of Kochi in
South India, which lies between 9’48’ and 10’50’
Latitude and 76’5’ and 76’58’E Longitude. The
Kochi Municipal Corporation extends to an area of
94.88sq.km. As per census of India 2001, thepopulation of Kochi Corporation is 5,95,575 and as
per census 2011 the population is 6,01,574. Physical,
social, political and economic factors have played
their decisive role in the formation of land use

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GEOMATE- Brisbane, Nov. 19-21, 2014

seasons (dry, wet and a festival season). In
calculating the ecological footprint for household
waste generation, methodology to assess thehousehold ecological footprint, developed by M.
Wackernagel and W. Rees were used. This study
followed the simple methodology by Salequzzaman[6] applied to a particular area in Bangladesh. Thismethodology used global carrying capacity standards
and utilizes the resource consumption and waste
generation categories and the land use categories for
those consumption and waste generation. Analysis of
the data was done using waste footprint analyzer,
which is a program developed based on the equationsof ecological footprint of waste generation developed
by William Rees and Mathis Wackernagel, theauthors of the concept for inputting the survey dataand estimating the footprint values in a visual basic
platform. The analyser generated the footprint value
in hectares per capita.
The average footprint of residents in the city area
is above the national average. (2.19 > 0.8). Also it
consumption exceeds the available bio productive
space per person in the world (2.19 >1.8). According
to the Global footprint calculator if everyone like this
we would need 1.3 PLANETS to sustain our life. The
average footprint is highest in Ward No.58 (2.52gha)
because of the high shelter footprint (1.21gha)
because of high house area usage. The lowest
ecological footprint is in Ward No. 53(1.79gha) . For
all residents, the shelter footprint goes to the
maximum followed by goods and services footprint,
food footprint & mobility footprint. In most cases the
shelter footprint constitutes about 46.37% of the
footprint. Average house area usage is 400.45
sqft/person. This is contributing to high shelter
footprint. The average male footprint is greater than
the female footprint because the male mobility
footprint is more than that of female. The average
footprint of nuclear family footprint is more than thatof joint family. Mobility footprint was directly
proportional to the distance to the place of work or
education. Low land area occupancy when comparedto other units is reducing the average shelter footprintof high rise buildings. Therefore promoting wellplanned high density buildings will help us toconserve our bio productive space. The mobility
footprint of the population in the wards near to the
CBD and major transportation nodes is low becauseof their dependence on public transportation facilities
when compared to the other wards.
From the solid waste management issues studied,
it is understood that solid waste management
problems is found to be the root cause for many otherproblem areas like water logging, mosquito threat,environmental pollution etc in the city and also it

affects the serene nature of the city. Nowadays thegreed among the various manufacturing companies
and inconsistent demands of the consumer have given
way to turning a blind eye to the environment
destruction due to waste disposal we bare down upon
our finite planet. They are not bothered about thewaste generation from their own houses and work
places. But rather they blame the authorities for not
disposing these wastes.
WASTE FOOTPRINT OF KOCHI CITY
The analysis of waste footprint of the city foundthat the waste generation in Kochi City was
0.51kg/capita/day with an average household size
3.26. The solid waste components in the threeseasons are shown in Figure 1. On an average theorganic waste constitutes about 82%, 10% metal
waste, 5% glass waste, 2.3 % paper waste and 1.4%
plastic waste. In all the seasons the organic waste
constitutes the maximum. In the festival season andthe wet seasons the organic waste and the plastic
waste seems increasing. Only paper waste isrecycled. 53 people reported that newspapers andmagazines are collected by agencies from households
once in six months or more. The households areunaware of the type of recycling methods. Since theactual amount of recycled paper is difficult it was
assumed that about 90% of the paper waste isrecycled from each house. In order to assimilate thesewastes an area of
0.011 hectare per capita isrequired in the dry seasons, 0.014 hectare per capita
for the wet season and 0.013 hectare per capita for
the festival seasons.

.
Fig. 1 Waste components in Kochi City
Even though the percentage of plastic in thesolid waste is low compared to the other components,
its percentage share of total footprint is relatively
higher than other components except for metals.
Metals also contribute to higher footprint. By land
use category in the dry seasons about 102.16 sqm,
0.06sqm forest land and 12.74 sqm area of built up
land is required per person.

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GEOMATE- Brisbane, Nov. 19-21, 2014

Analysis Based on Mode of Disposal

The festival seasons demand 121.29sqm energy
land, 0.07sqm forest land and 15.13sqm built up land
for assimilating the waste generated by a single
person in the Kochi city. For the wet season the
figures are 114.20, 0.06 and 14.87 sqm respectively.
This shows that during the festival seasons, theimpact caused by the wastes in the city iscomparatively high. Paper waste, organic waste andplastic waste seems increasing during the festival
season and therefore the impact is caused by thesecomponents.

Community level disposals show high waste footprint
values when compared to household level disposal
methods. The waste footprint values are high infestival season. The low waste footprint values forhousehold level disposals shows that the waste
disposal at source itself is a sustainable option forproper solid waste management.
CONCLUSION

Analysis Based On Density of Population

The Ecological footprint has a higher flexibility
as it can be used for many different purposes. Fromthe studies, it is revealed that the consumption rate
(EF=2.19gha) of the population in the city is very
high and it is far exceeding the national average(0.8gha) and the nations biocapacity (0.4gha) and theavailable bio capacity per person in the world(1.8gha). The study also revealed that shelter
footprint, which mainly depends on the house area
usage and number of occupants, is very high in thecity. The improper waste disposal at the source(residential units) is increasing the waste footprint of
the population which results in the high goods andservices footprint. Consumption rate can be reduced
by prioritizing strategies based on the component
footprint values starting from the individual level.
The analysis of ecological footprint of waste
generation in the residential areas of Kochi city
showed that with the present trend of waste
generation and an assumed population growth rate of
4.5%, by 2051 the population will need about the fullarea of the city to assimilate the generated waste. The
research anticipates a 39% reduction in footprint
value through the programmes going to get launchedin the city and suburbs. A maximum of 51%
reduction in footprint value can be attained throughthe high optimistic value of recycling. The researchhighlights that as per the waste management
hierarchy theories the source reduction proved thefirst order hierarchy in waste management in terms ofwaste footprint values. For effective footprint
reduction through strategies, regions should develop
their own ecological footprint calculators based on
their consumption pattern and life style of the
population. This calculator should be made available
to the public through media. Provision should also begiven in the calculator so that they can compare theircurrent profile of consumption to a profile which
reduces their ecological footprint thereby making the
Ecological Footprint Analysis a public awarenesstool in addition to a technical tool. This will make
Kochi greener, cleaner, safer and self sustainable asin our good old days. To develop a calculator for

The analysis showed that as the density of
population is increasing the footprint is increasing as
the amount of waste generated is more .The average
footprint is more in the festival season. The per capita
average footprint in sqm is about 145.83 in thefestival season. The paper content in the dry seasonsis high in the high density areas. But during the otherseasons the composition of paper waste is more in the
low density areas. The glass and metal content showshigh composition during the dry and wet season in
the high density areas. Organic waste and plastic
content is more in the low density areas in allseasons.
Analysis Based on Location and Household Income
Residences which are near to CBD/MTN showhigh footprint values in the wet season and festival
season. The footprint value is about 20% more whencompared to that of the dry season. A similar trend isalso noticed in the residences away from CBD/MTN.
Analysis based on household income shows that the
average footprint is comparatively high for theincome group INR 10000 to INR15000 followed by
the above INR20000 group. The footprint is high inthe festival season for all income groups. The lowest
contributor to waste footprint is the less than
INR5000 income group.
Analysis Based on Type of House and Ownership
Details
Almost all the housing types show highfootprint values in the festival season. The average
waste foot print value is comparatively low for
individual plots except in festival season. Residences
owned by builders showed low waste footprint values
comparatively. The footprint values in the wet andfestival season are high.

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GEOMATE- Brisbane, Nov. 19-21, 2014

urban Kerala, corresponding footprint studies must be
initiated at the national level. Therefore ecologicalfootprint studies should be encouraged through R&D
programmes and a footprint calculator should be
developed especially for the urban areas of India.
REFERENCES
1.

2.

3.

4.

5.

6.

World Bank , 2011. Doing Business 2011
India:
Makingadifferencefor
entrepreneurs.
Comparingbusinessregulation of 183 economies, The
International Bank for Reconstruction andDevelopment (IBRD), Washington DC,
USA
Swerts, E., Pumain, D., Denis, E., 2014.The
future of India’s urbanization. J.Futures 56,
43-52.
Government of Kerala, 2012. State
Urbanization Report, Town and Country
Planning Department, Kerala.
Wackernagel, Mathis and W. Rees. Our
Ecological Footprint. Gabriola Island, BC:
New Society Publishers, 1996
Athira Ravi , Subha V (2013). “EcologicalFoot Print Analysis- An Overview”,
American Journal of Engineering Research(AJER) e-ISSN : 2320-0847 p-ISSN : 23200936 pp-12-19
M. Salequzzaman (2006). ―Ecological
Footprint of Waste Generation: A
Sustainable Tool for Solid Waste
Management of Khulna City Corporation of
Bangladesh‖
Environmental
Science
Discipline, Khulna University, Bangladesh

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GROUND CONDITIONS AND THE LAND OPERATIONALPARAMETERS DETERMINED IN THE PLANNING DECISIONS
Grzegorz Kmiecik1, Marta Szejnfeld2, Hanna Szymczak3, Anna Szymczak-Graczyk4
Department of Urban Planning and Architecture1,2,3, Institute of Civil Engineering and Geoengineering,
Faculty of Land Reclamation and Environmental Engineering, Department of Construction and StructuralEngineering4 University of Life Sciences1,2,3,4, Piatkowska Street 64E, 60-049 Poznan, Poland.

ABSTRACT
Optimal land-use planning is a tedious and long lasting process, and in its genesis the actions which set itself
the goal of creating spatial order and sustainable development are taken. Inherently, in almost each country
planning policy, the basic instruments of planning action are the planning decisions.
They have been determined with the details of the location, purpose, method of use as well as thearchitectural form. As the result of these decisions, the possibility of designing and implementing aharmonious space that consider all factors and functional, socio-economic, environmental, cultural, aesthetic
andcompositional
requirementsarecreated.
But
whetherplanning
decisionsalways protect interdisciplinary interests, even such an important aspect as the water ground conditions ?
The article based on specific example from Polish yard will appear the effects of skipping ground parameters
issues related with the planning of building investment on particular area, which according to Polish legislation,
are not treated as planning arrangements.
Consequently, the threats to the already existing water ground relations are very probable as far as
the changing of these relations may have significant influence or even challenge the implementation of a specificbuilding investment. This situation creates a huge risk including financial consequences and frequently has asignificant impact on the future of the building investment process, including the danger of suspension of works.
Keywords: Geotechnical conditions, Land zoning, Planning document, Investment costs.

INTRODUCTION
Undoubtedly the special planning is the art oforganizing the environment, which despite to an
aesthetic experience also performs importantfunctions starting from the socio-economic throughenvironmental or even teaching effects. However,foregoing art is easier to define, because the criteria
for determining it are not only a matter of taste, butalso refer both to the tough market or economic
rules.
The combination of these different aspects in thecreation of spatial plans requires the sustainable
performance on many levels, and therefore it isreasonable to say that special planning is also an art
unique, which should be guided by the law of
democracy. Its essence is the ability to choose thealternative solutions, that in each case will create aharmonious and balanced extent. Notwithstanding,whether the certain solution reveal successful decide
the future expense user, which is usually deeply
embedded in the context and relationships with otherpeople. Therefore, should the alternative choice waspossible and equivalent, planning should be basedon robust knowledge and understanding of thecharacteristics of the certain area as well as theempathy with respect to its current and future users.

The foremost means of expression of special
planning are the planning decisions that as well as
the local and regional level organize space striving
to its most rational use.
THE
CHARACTERDECISIONS IN POLANDOF

PLANNING

An underlying basis of each construction project is adetailed analysis of its cost-effectiveness namely
cost estimation and efficiency of such plans.
The basis for obtaining the data for theseanalyzes are the planning decisions issued in theform of broader contextual local plans or zoning
decisions usually for a single land area [1]. It
contained therein information about acceptable
method of zoning and land use as well as thearchitectural form. Moreover, the criteria determinedin above way should be the result of not only thearchitectural and urban conditions but also
environmental, cultural, historical, social, and what
is very important, also groundwater factors. Only
though properly constructed building conditions cangive a full picture of the certain land property andallow to calculate its absorption i.e. the optimal
management based on defined criteria. This attitude
is directly associated with the market value of the520

GEOMATE- Brisbane, Nov. 19-21, 2014

parcel and other economic aspects relating thebuilding project or its execution.
As it is observed the spatial planning is also an‘art’ that can be directly estimated and measured.
Furthermore, it underlies all investment activity as
obvious is the relationship that the greater amount of
information about the area, the lower is the risk indecision-making regarding the purchase of property.
According to recent studies, more than half of all
investment projects launched in Poland take place inareas avoided the zoning plans, based only on thelegal provisions of the spatial planning billconcerning so-called "good neighborliness". Hereby
the new objects and buildings are formed with thesimilar function as their neighborhood pre-existingbuildings [2].
At the same time the other factors are often ignored
such as groundwater conditions, which may
significantly affect on the nature of the investment,
regarding for instance the cost reasons.
Currently, the planning decisions very rarely
define the conditions allowing the elimination ofnatural interactions on the planned investment andvice versa. Furthermore, if the investment does notconstitute the significant impact on the decision of
the environmental condition of the project or there isno indication for preparing the environmental report
above decisions include very limited information
about the characteristics or parameters of thesubstrate [3].
It may be surprising, especially in the context of thecontemporary nature of the construction process,which consists plenty problematic factors
concerning at least difficult land conditions and timeor money limit. Whereas conditions associated withthe parameters of the ground are one of the most
cost and time consuming, that can greatly reduce thepotential of the land and its attractiveness to future
investor. Also, the environmental aspect should not
be forgotten, because the effects of interference inthe subsoil can be permanent and irreversible.
Thus, in planning documents, in addition to thetypical architectural and urban planning parameters
defining the acceptable dimensions of buildings,
their height, form and building area should also befound the records of the land parameters that
especially define the development of the plot andconsequently its form of building.
Thereby we would obtain a full picture of thepotential investment area, where in addition to thevisible characteristics affecting to its market value
such as location, access to communication, shape of
the plot, its surface or equipment in the media, wewould be able to determine the characteristics of thehidden handlers concerning the geotechnicalparameters substrate, soil and water conditions orother environmental considerations [2].
Then, one could speak of the investment process
in which the investor always has the right ofconscious choice and is not forced to choose thesolution which is necessary and become apparent
only upon the stage of design or workmanship. The
planning decision should apply equivalent solutions
correctly typed in the context of space so that theinvestor should be further guided only by his
subjective investments purposes.
PLANNINGDECISIONSAND
THE
SELECTION CRITERIA OF THE TYPE OF
INVESTMENT
Information
about
the
geological andhydrogeological specific of grounds are very
important and often fundamental when deciding
about the commence of the investment or its
character.

Fig. 1

View of historical park. Own photograph.

Above can be demonstrated on the building
project of the multi-family housing in Poznan, thefifth largest city in Poland. The investment wasplanned on a very attractive market-plot, in the city
center, adjacent to the downtown building from the
beginning of the XX century and one of the mostbeautiful urban parks with its historic Palm House.

Fig. 2521

View of historical park. Own photograph.

GEOMATE- Brisbane, Nov. 19-21, 2014

Despite the spectacular location the investmentarea was heavily degraded in the urban context as
the result of many years of functioning the chemicalplant in this place. Therefore, the planned
investment gave the great opportunity to create awhole new quality of public space, adequate for thispart of the city.

Fig. 3 View showing the location of investment
Performance of Geoprojekt.
In relation to the lack of a Local Land
Development Plan, the building parameters havebeen identified in the zoning decision issued for theparcel owned by the investor, without reference tothe environmental values of the adjoining park.
Consequently, multi-family housing was decided todesign on the north-south axis, along the boundaryof the botanical garden.
In order to the most efficient use of commercial
values of the land it was assumed that the mostarchitecturally and economically reasonable solution
would be to design the underground car parking thus
releasing space for main development. This resulted
the fairly dimensional arrangement of the buildings
and gave the usable amount of surface intended by
the investor.
Implementation of the parking lot required
pursuing an earthworks at a depth of 11.0 m below
ground level. The analysis of geotechnicalconditions of foundation the buildings showed thatthe ground soil had the complex ground waterconditions as well as the level of ground water that
imposed the necessity to perform the construction ofan underground garage in the form of cavity/slot
walls erected on the slab base [4].
Generally, the investment demanded complicatedand expensive design solutions. However,preliminary analysis of soil and water conditions
made on the basis of archival material before thepurchase of the property suggested the possibility ofsuch situation, allowing the investor calculate these
extracurricular expenses in the overall cost of
construction.
These water factors, together with the decisionon building conditions were the main parameters of
the investment. They have become the foundation ofbuilding project and cost estimates.

During the advanced design works it turned outthat the planned investment would be a huge threat
to the historic neighboring forest. There was also a
feasible risk of changing the water conditions in thisbotanical park as a result of carried out excavations
works or establishing some kind of baffle in the freemovement of ground water, due to the method
applied in construction project using cavity walls.
In the event of the above investment the planning
decision refers only to the parameters ofarchitectural and urban planning, instead analyzed
additional conditions other than previously existing
context of the building.
The above example shows that the standard
approach applied in such a complex investment
turned out to be insufficient, and the planned
construction works could cause irreparable
consequences for the environment and would make
impossible to take any subsequent preventive actionin this matter.
Merelyperforming
theadditionalhydrogeological studies could gave a full picture of
the situation. It was also presented that the results ofthe study may question the financial legitimacy of
the implementation, as in the case of negative results
the complete change of profile of the investment
would be necessary. In fact without an undergroundgarage residential development would probably be
unprofitable especially in the view of high costs
incurred for the purchase price in such a strategic
location in the city. Thus, the investor has been
deprived of choice and in return ‘sentenced’ to theselection of an unexpected solution. Ultimately, tomaintain the whole investment it was necessary tochange the function of buildings to the office one
thus less favorable concerning the context of thispart of the city. Paradoxically, skipping the
groundwater issues, recognized as not planningassumption led to selection of less favorable urban
solutions [5].
Therefore, evidently the zoning conditions forthe areas with higher risk of natural hazards orextremely valuable for the city should apply the
obligation of carrying out a specific range of
geological and hydrogeological studies in order torecognize the subsoil. Obviously, this incurs certain
costs but disproportionately smaller than theinvestment ones.
The relevant solution would be to create a databasesystem with the ground conditions details which
would greatly speed up an entire investment process,minimizes financial risk or improves design works.
In addition, it could also be the perfect promoting
and investor’s drawing factor since the city
possessing
suchcomprehensiveplanning
documentation could parallel simplify the entire
building construction procedure, that will becomemuch more attractive for the future investments.

522

GEOMATE- Brisbane, Nov. 19-21, 2014

CONCLUSION
Typically, the basic criteria defined in planning
decisions are: the architectural and urban
parameters, determining acceptable size ofbuildings, their height, form or building area.
On the contrary with above remains the example
discussed in this article which proves that theinvestment can be completely dominated by the land
operational parameters not established in the legal
decision. These parameters are strictly essential at
the stage of developing the architectural andstructural solutions, that usually reflect the existingbuilding conditions. If planning decisions determine
the underground building, it shall also contain theguidelines for geological or hydrological area.
Additionally, in case of complex terrain conditions,the these architectural criteria should be described ina way that does not prohibit the investment
integrally thus showing the possible directions to theinvestor that could freely decide the optimal courseof investment.
In the example brought up in present paper there
were several optional functions for the building frommulti-family housing with a different combination of
usable space and associated underground parking to
office one. Any change of features would result thecommencement of the administrative procedures ofobtaining the required approvals or legal decisions.
Consequently, issuing that decision required the newtime-consuming results of research that in turnequals the suspension of the investment and had
major financial implications for the investor.
In contrast, the development of specific groundparameters at the design and planning stage would
greatly accelerate the investment process and thus
gave better control over the correctness of appliedurban solutions.

[2] Gwozdz-Lason M. "Parameters of the Groundsubstrates in the context of its destination in Spacial
Development Plans ", Mining and Geoengineering,Year 35, Issue 2, 2011,[3 ]Regulation of Infrastructure of November 9,2004 - on the types of projects that may
significantly affect the environment and the specificconditions for the eligibility of the project to preparea report on the project on the environment effect(Dz.U.2010.213.1397).
[4] Design materials of Geoprojekt-Poznan,[5] Kmiecik G, Szymczak H,“Planning decisions
and the risk of change to the investment assumptions
on the example of multi-family building
construction project on Sniadeckich/Glogowska
street in Poznan.”, Architecure, Civil Engineering,
Environment, Year, Book, 2014.

REFERENCES[1] The Act of 27 March 2003. of Spatial Planningand Regional Planning,523

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

EFFECT OF FLOCCULATION AIDS ON THE ELECTRIC FIELDASSISTED DEWATERING OF SOLID LIQUID SYSTEMS
Mohammed Saedi Jami1, Masashi Iwata2, Md. Monjurul Alam3 and Md Zahangir Alam4
Bioenvironmental Engineering Research Center (BERC), Department of Biotechnology Engineering,
Faculty of Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia; 2 Departmentof Chemical Engineering, Graduate School of Engineering, Osaka Prefecture University, Sakai, Japan
1,3,4

ABSTRACT
Various construction techniques such as tunnel construction and earth drilling result in the production ofhuge amount muddy water with a high solid-to-liquid ratio. Consequently there is a need for disposing theselarge quantities of muddy wastewater. Dewatering by conventional belt press filters can achieve only small
solids contents leading to high expenditure for the transport and disposal of these materials. Another option is theincineration. But since the water content is usually very high, energy consumption is the major concern. In thisstudy, constant-current electroforced sedimentation (EFS) of zinc oxide is analyzed using the Terzaghi–Voigt
combined model by neglecting the creep deformation of the material and the effect of adding dewatering aids onthe enhancement of water removal is investigated. High current density yields higher dewatering. Increase ininitial solid content slightly improves the effectiveness of dewatering. The addition of polyacrylamide as a
dewatering aid enhanced the electroforced sedimentation.
Keywords: Electroforced Sedimentation, Dewatering, Zinc Oxide, Polyacrylamide
sedimentation properties of kaolin and zinc oxide
sediments were investigated and it was found thatthe addition of 1% polyacrylamide as dewatering aid
enhanced the electroforced sedimentation of zincoxide for a given current density [5].

INTRODUCTION
The process of disposal and re-use of wastewater
is one of the most significant challenges inwastewater management. Besides, since such solid
liquid system is usually highly compressible,
mechanical dewatering is impeded due to a very
high hydrodynamic resistance of the mixture.

It is well known that the moisture content
remains unchanged at the sedimentation surface,whereas it decreases at the bottom of sedimentation
column in the electroforced sedimentation and thishas not been explained analytically yet [5]. The main
objective of this paper is to investigate theelectroforced sedimentation of zinc oxide in aqueous
medium. The effects of total solid volume per unit
cross sectional area, current density and the additionof flocculant aid were examined. The experimental
data were also compared with model prediction.

It is possible to increase the settling velocity ofhighly concentrated material remarkably by applying
direct current electric field with the increase ofelectric field intensity [1]. It happens mainly forelectroosmotic flow which results from the
movement of ions in the electric double layer alonga solid-liquid interface toward one electrode or otherbecause of the application of electric field.
Electroosmosis has been applied in soil stabilization
since before World War II [2]. L. Casagrande (19301962), had the main contribution in the developmentof the applications of electroosmosis in soil
engineering,
introduced that a permanent
stabilization of soil could be attained by usingaluminum electrodes [2].

MATERIALS AND METHOD
Experimental
An acryl tube, height and internal diameter of 42
cm and 5.5 cm, respectively, was used as
sedimentation column (Fig. 1) located in
Bioenvironmental Engineering Research Centre,
International Islamic University Malaysia. The
electrodes, both made of stainless steel, are placed inparallel at the top and the bottom of the column.
The electric field was applied by DC power in sucha way that the bottom was cathode and top wasanode as zinc oxide particles have positive charges.
The slurry used in the experiments was prepared by

The effects of flocculants aid in electroforced
sedimentation of various aqueous suspensions werestudied. Sedimentation rates of suspended kaolinite
and clay are significantly improved by flocculants,
whereas electroosmosis are not affected greatly [3].
On the other hand, anionic polymers increase therate of electroosmotic dewatering of kaolinite [4]. In
our previous study, constant current electroforced524

GEOMATE- Brisbane, Nov. 19-21, 2014

mixing a predetermined quantity of dry zinc oxide,polyacrylamide, and deionized water to form asuspension of known total solid volume per unit
cross-sectional area. The slurry was then poured into
the sedimentation column and left until gravitational
sedimentation was completed and equilibrium height
was achieved. Then direct current electric field wasapplied to achieve further sedimentation. The
electric field was provided by a dc power supply
with a capacity of 120 V and 0.5 A. The change inheight of sediment was recorded. Experiments were
performed under different current densities anddifferent total solid volumes per unit cross-sectional
area.

volumetric charge density of the liquid, and p L is theliquid pressure. x and E are the spatial coordinate
and the electric field strength in the direction ofmaterial thickness, respectively.
The first term of the right hand side of Eq. (1)represents an electro-osmotic flow in a porous
material, while the second term shows a pressure
flow in the material, both including the tortuosity
and size of flow path. If E = 0, then Eq. (1) is
reduced to the Kozeny-Carman equation which
represents the apparent flow rate through a porous
material under a liquid pressure gradient. Equation(1) was examined by use of incompressible sinteredglass beads. Consolidation ratio (U c ) is the measureof a progress of electroforced sedimentation. The
equation for the calculation of U c can be represented
by the Eq. (2) [8].
UC =H1 − H
H1 − H ∞ 32 ∞ (− 1)n −1
 (2n − 1)2 π 2 Ce = (1 − B )1 − 3 ∑θ  + B[1 − exp(− ηθ )](2)exp−
3ω02 
4 π n =1 (2n − 1)

where H 1 and H are the initial and instantaneousheight of the sediment and H ∞ is final height of thematerial, respectively. B is an empirical constantdefined by B = a c /(a c + a E ) and represents the ratioof the creep deformation to the total deformation.
U C is zero at the beginning and becomes unity at
infinity. There is a good agreement between
experimentally measured U C and theoreticallycalculated values by the use of Eq. (2) for the zincoxide sedimentation [5].

Fig. 1 Schematic diagram of experimental apparatus.
TheoryFor describing an electro-osmotic flow through acapillary tube, taking into account the applied
electric field strength and the electric field strength
in the electric double layer caused by the contact
potential difference, the Navier-Stokes equation was
solved about three decades ago [6]. The result wasalso extended to describe an electro-osmotic flow
through porous media in much the same way as in
the derivation of the Kozeny-Carman equation. The
apparent liquid velocity q through the porous
material is defined by the flow rate per unit crosssectional area of the material and represented by [7].

q=

ε3

dp 

 ρe E − L dx kS (1 − ε ) µ 202

RESULTS AND DISCUSSION
Figure 2 illustrates the sedimentation rates ofzinc oxide under three constant current densities.
The rate of sedimentation increases with theenhancement of applied current density. In ourprevious study, similar trend was reported where theincrease in the current density brought about
increase in the solid compressive pressure which is
responsible for enhance sedimentation [8].
Moreover, the rate of electroforced sedimentation ofzinc oxide of two volumes per cross-sectional area(ω0 ) was examined and the results are portrayed inFig. (3). The consolidation ratio of zinc oxide with
ω 0 = 4.7 mm is higher than that with ω0 = 5.8 mm.
There is an impact of initial volume of zinc oxide on
the rate of consolidation ratio.

(1)

where k is the Kozeny constant, ε and S 0 are theporosity and specific volume of the material
respectively, μ is the viscosity of the liquid, ρ e is the525

GEOMATE- Brisbane, Nov. 19-21, 2014

eletroforced sedimentation. The consolidation rate isfaster in the mixture of polyacrylamide and zinc
oxide
than
without
polyacrylamide.
In
consequences, it could be alleged that flocculant aid
has an effect in dewatering. Figure 5 portrays thetheoretical and experimental consolidation ratio of
the electroforced sedimentation of zinc oxide. The
theoretical values were found from calculation byusing Eq. (2), where the creep ratio B was zero, thus
the primary consolidation is main and there is no
impact of the creep deformation. Experimentallymeasured data are well comparable with thetheoretically calculated values.

Fig. 2 Rate of sedimentation of Zinc Oxide undervarious current densities.

Fig. 5 Comparision of theoretical and experimental
rate of sedimentation of Zinc Oxide under various
current densities.
CONCLUSION
This study assessed the effects of current density,
total solid volume per cross sectional area, andaddition of flocculation aid on the rate ofelectroforced sedimentation of zinc oxide. The main
parameters influencing sedimentation were theapplied current density and the addition ofpolyacrylamide in the zinc oxide slurry. After
mixing the polyacrylamide with zinc oxide, the rateof consolidation ratio of zinc oxide increased
remarkably. Beside this, the sedimentation rate ofzinc oxide is enhanced with the increasing of current
density. The initial weight of zinc oxide in slurry
has less impact on electroforced sedimentation. Zincoxide with ω0 = 4.7 mm showed higher
sedimentation than that with ω0 = 5.8 mm. However,
the electroforced sedimentation properties of otherclay particles ought to be investigated.

Fig. 3 Comparison of rate of consolidation ratio
between two solid volumes per unit cross sectional
area of Zinc Oxide.

Fig. 4 Comparison between consolidation rate ofZinc Oxide and the mixture of Zinc Oxide andPolyacrylamide.

ACKNOWLEDGEMENT

Figure 4 shows the effect of addition 0.5%
polyacrylamide with zinc oxide as flocculants aid inThis work was supported by Fundamental
Research Grant Scheme, Ministry of Higher
526

GEOMATE- Brisbane, Nov. 19-21, 2014

Education, Malaysia (Grant no FRGS-13-029-0270)
and we gratefully acknowledge the support.

[5] Jami MS, Iwata M, Muyibi S A, Karim M I A,
Al-Khatib MAFR, & Mustapha M, (2013).
“Enhanced electroforced sedimentation ofvarious solid-liquid systems”, African Journalof Biotechnology, Vol.10, Dec. 2011, pp.1890618909.
[6] Kobayashi K, Iwata M, Hosoda Y, and Yukawa
H, (1979) “Fundamental study of electroosmotic flow through perforated membrane”,
Journal of Chemical Engineering Japan, Vol.12,
2011, pp. 466–471.
[7] Kobayashi K, Hakoda M, Hosoda Y, Iwata M,
and Yukawa H, “Electro-osmotic flow throughparticle beds and electro-osmotic pressure
distribution”, Journal of Chemical Engineering
Japan, Vol.12, 1979, pp. 492–494.
[8] Jami MS, & Iwata M, “A New Method for the
Theoretical
AnalysisofElectroforced
Sedimentation Using Terzaghi‐Voigt Combined
Model”, Separation Science and Technology,
Vol. 43, 2008, pp.979-995.

REFERENCES[1] Shirato M, Aragaki T, Manabe, A, & Takeuchi
N, “Electroforced sedimentation of thick clay
suspensions in consolidation region”, AIChE
Journal, Vol.25, Sep. 1979, pp. 855-863.
[2] Adamson LG, Chilingar G V, Beeson CM, &Armstrong RA, “Electrokinetic dewatering,consolidation
andstabilizationofsoils”, Engineering Geology, Vol.1, 1966, pp.
291-304.
[3] Lockhart NC, “Electroosmotic dewatering ofclays. II. Influence of salt, acid andflocculants”, Colloids and Surfaces, Vol.6,
Apr.1983, pp. 239-251.
[4] Dussour C, Favoriti P, & Vorobiev E,“Influence of chemical additives upon both
filtration and electroosmotic dehydration of akaolin suspension”, Separation Science andTechnology, Vol. 35, 2000, pp.1179-1193.

527

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

IMPORTANCE OF CORYDALIDAE AS AN INDEX OF METALCONTAMINATION OF RIVER
Akihiro Fujino1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan;
2
Faculty of Systems Engineering, Wakayama University, Japan

1

ABSTRACT
Corydalidae is useful for evaluating a metal contamination of catchment. Metal concentration of river water
is low and very changeable. River water contamination was caused by soil. However, soil analyzing is very
difficult to reach average values because of variability of soil metal concentration. However, as Corydalidae eats
many another insects in river and live in several years in river, metal derived from wide area of soil and water forlong term is concentrated in Corydalidae body by food chain. Then it is easy to analyze metal concentration of
Corydalidae because of high concentration. As a result, Cu, Mn and Zn were on the average, 410 ppm, 775 ppm,
and 819 ppm in the polluted zone, the metal mine area. In the non-polluted zone, Cu, Mn and Zn were on the
average, 26 ppm, 45 ppm, and 100 ppm. Metal concentration is quite different between polluted and nonpolluted areas and then, it is very useful for index of metal contamination.
Keywords: metal contamination, aquatic insect, Corydalidae, river, concentration factor
The maximum and the minimum of concentration
factors of Fe for Stenopsyche marmorata were 15
million and 51900. The maximum and the minimumof concentration factors of As for Stenopsyche
marmorata were 18700 and10000 [2]. Since there
were not a concentration factor of Cu of
Stenopsyche marmorata and a concentration factorof Pb, it cannot be compared.
Corydalidae is distributed in Japan, the easternpart and southern part of Asia, South and North
America, South Africa, Madagascar, Australia, and
New Zealand [3]. The larva of Corydalidae is living
underwater for several years. The larva ofCorydalidae lives under a stone of a river bottom
and catch the other insects [3]. Therefore, it can beconsidered that the metal concentration in the larvaof Corydalidae shows the pollution for river waterand the river soil near an extraction point. The
mining site which had produced gold, silver, copper,lead, zinc, and arsenic is upstream of Waidani, andmine water is flowing into the river.

INTRODUCTION
Metal concentration of river water is low andvery changeable. There is a method to quantify ametal concentration of algae adhering to a stone of ariver bottom or an aquatic life, etc. instead ofanalyzing water directly. It is expected that metal
contamination degree of a river can be evaluated byinvestigating an aquatic insect live in a river inseveral years especially. River water contamination
was caused by soil, too. Then, to analyze soil also isnecessary for determination of metal contamination.
However, soil analyzing is very difficult because ofvariability of concentration. If an insect whichcondenses metal from water and soil is found out
and its metal concentration is analyzed, theconcentration will become an index for metal
contamination for river and soil. Baetidae, a kind of
may fly is reported to be useful as an environmental
indicator for Cd and Zn and a caddis fly for Cd, Zn,
Al, Fe, Cu, Ni, Mn, and Co [1]. Corydalidae eats
many kinds of aquatic insects containing Baetidae
and a caddis fly. Corydalidae was analyzed and aconcentration
factorwascalculated.
The
concentration factor of Stenopsyche marmorata wascompared with the concentration factor of
Corydalidae, and it was investigated whether
Corydalidae would be useful as a metal
contamination environmental indicator living thing.
The maximum and the minimum ofconcentration factors of Mn for Stenopsyche
marmorata were 490000 and 6410. The maximum
and the minimum of concentration factors of Zn for
Stenopsyche marmorata were 260000 and 25490.

INVESTIGATION AREA
The river sampling places for Corydalidae were
Waidani, Yoshinaga-cho, Bizen-shi, Okayama, andthe Kotako River and the Sugitani River in Nara,and the Kogawa of Kozagawa River branch in
Kozagawa-cho, Higashi-Muro-gun, Wakayama.
The closed mine produced gold, silver, copper,lead, zinc, and arsenic in the upstream of Waidani,
and mine water is flowing into the river. In the
Waidani area, there were three sampling areas of thelower reaches, the middle reaches and the upper
528

GEOMATE- Brisbane, Nov. 19-21, 2014

reaches. The Kotako River was in the limestone
region. There is a hot spring in the fountainhead of
the Kotato River and spring water flows into theriver. The Sugitani River was close to the the
Kotako River. the Kumano acidic rock was
distributed in the Kogawa River catchment which isa non-polluted zone with no mine and [4]. The
sampling points of the Kogawa River were in theupper reaches, the middle reaches, and the lower
reaches.

Table 1 is an analysis result of the river water
metal concentration of the Kogawa River. There are
no remains of a mine in Kogawa. The river metal
concentrations of Cu, Fe and Pb in the upper reaches
were 0.010, 0.021 and 0.061 ppm, respectively. The
river metal concentrations of Cu, Fe and Pb in the
middle reaches were 0.009, 0.053 and 0.055,
respectively. The river metal concentrations of Cu,
Fe and Pb in the lower reaches were 0.016, 0.019
and 0.016, respectively. Other metals were notdetected.
Table 1 River water metal concentration of
the Kogawa River(ppm)Fig. 1 Each investigation area in Honshu in JapanRESEARCH METHODRiver water and Corydalidae was extracted. The
extracted Corydalidae was dried. The extracted riverwater puts in concentrated nitric acid. This is forabolishing the state in which the metal has adhered
to the inner wall of bottle. The extracted dried
Corydalidae is dissolved with concentrated nitricacid. After filtering the solution for river water withconcentrated nitric acid and insect solution ofconcentrated nitric acid, solution was analyzed by
ICP plasma-emission-spectrometry equipment.
In order to determine the original metal
concentration of Corydalidae, it calculates fromanalysis result, the weight of a dried sample, and thequantity of the used concentrated nitric acid.
Eq. (1) is a formula which calculates the metal
concentration of Corydalidae. Eq. (2) is a formulawhich calculates a concentration factor.

Cu

Fe

Mn

Pb

Zn

As

the
upper
reaches

0.010

0.021

0.002

0.061

0.003

0

the
middlereaches

0.009

0.053

0.002

0.055

0.001

0

the
lower
reaches

0.016

0.019

0.001

0.065

0.001

0

Fig. 2 is Cu concentration of Corydalidae in the
Kogawa River. Cu concentration of Corydalidae in
the upper reaches was about 22 ppm to about 40
ppm. Cu concentration of Corydalidae in the middle
reaches was about 22 ppm to about 35 ppm. Cu
concentration of Corydalidae in the lower reaches
was about 15 ppm to 40 ppm. The concentration
factors of Cu of Corydalidae in the Kogawa River
were the maximum of 13000, the minimum of 2200,
and an average of 6700.

The metal concentration of Corydalidae =(1)Analysis result ×
Quantity of concentrated nitric acid
Weight of a sample

Fig. 2 Cu concentration of Corydalidae in
the Kogawa River

concentration factor =Metal concentration
River

water

of

Corydalidae (2)Fig. 3 is Fe concentration of Corydalidae in the
Kogawa River. Fe concentration of Corydalidae in
the upper reaches was about 300 ppm to about 500
ppm. Fe concentration of Corydalidae in the middle
reaches was about 350 ppm to about 500 ppm. Fe

metal concentration

RESULTS
Non-polluted zone529

GEOMATE- Brisbane, Nov. 19-21, 2014

the upper reaches was about 4 ppm. Pb
concentration of Corydaledae in the middle reaches
was about 2 ppm to about 4 ppm. Pb concentrationof Corydalidae in the lower reaches was about 1
ppm to about 4 ppm. The maximum, the minimum
and average of concentration factors of Pb for
Corydalidae in the Kogawa River were 1800, 20 and
720, respectively.
Pb concentration of the river water in the
Kogawa River is about 0.060 ppm. However, Pb
concentration of Corydalidae in the Kogawa River isabout 3 ppm, and was hardly condensed bybiological concentration.

concentration of Corydallidae in the lower reaches
was about 300 ppm to 800 ppm. The maximum, theminimum and average of concentration factors of Fe
for Corydalidae in the Kogawa River were 73000,
6400 and 34000, respectively.
Fe concentration of the river water in the middle
reaches was 0.053 ppm, and was higher than those in
the upper reaches and the lower reaches. However,
one of the Fe concentrations of Corydalidae in thelower reaches was the highest concentration.
Concentration of the Corydalidae did not relate withthose in a river.

Fig. 3

Fe concentration of Corydalidae in
the Kogawa River

Fig. 5

Fig. 4 is Mn concentration of Corydalidae in the
Kogawa River. Mn concentration of Corydalidae in
the upper reaches was about 50 ppm to about 200
ppm. Mn concentration of Corydalidae in the middle
reaches was about 50 ppm. Mn concentration of
Corydalidae in the lower reaches was about 25 ppm
to about 100 ppm. The maximum, the minimum andaverage of concentration factors of Mn for
Corydalidae in the Kogawa River were 97000,
20000 and 44000, respectively.
Most Mn concentration of the river water in the
Kogawa River was not detected. However, Mnconcentration for Corydalidae in the Kogawa River
was able to be detected to be 200 ppm and 100 ppm
because of biological concentration.
.

Fig. 4

Pb concentration of Corydalidae in
the Kogawa River

Fig. 6 is Zn concentration of Corydalidae in the
Kogawa River. Zn concentration of Corydalidae in
the upper reaches was about 140 ppm to about 180
ppm. Zn concentration of Corydalidae in the middle
reaches was about 100 ppm to about 160 ppm. Zn
concentration of Corydalidae in the lower reaches
was about 70 ppm to about 120 ppm. The maximum,
the minimum and average of concentration factors of
Zn for Corydalidae in the Kogawa River were150000, 34000 and 62000, respectively.
Most Zn concentration of the river water in the
Kogawa River was not detected. However, Znconcentration of Corydalidae in the Kogawa River
was about 140 ppm because of biologicalconcentration as well as Mn.

Mn concentration of Corydalidae in
the Kogawa River
Fig. 6 Zn concentration of Corydalidae in
the Kogawa River

Fig. 5 is Pb concentration of Corydalidae in the
Kogawa River. Pb concentration of Corydalidae in
530

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 2 River water metal concentration of the
Waikani, the Sugitani River,and the Kotako River(ppm)Fig. 7 is As concentration of Corydalidae in the
Kogawa River. As concentration of Corydalidae in
the upper reaches was about 0.5 ppm to about 2 ppm.
Most As concentration of Corydalidae in the middle
reaches was not detected. As concentration of
Corydalidae in the lower reaches was about 1 ppm toabout 5 ppm. The maximum, the minimum andaverage of concentration factors of As forCorydalidae in the Kogawa River were 1800, 300
and 940, respectively.
As concentration of the river water in the
Kogawa River was not detected. However, Asconcentration of Corydalidae in the Kogawa River isabout 3 ppm, and As can also be concentrated in the
body because of a biological concentration as wellas Mn or Zn.

Fig. 7

Cu

Fe

Mn

Pb

Zn

As

The
upper
reachesof
Waidani

0.080

0.067

0.007

0.027

0.700

0.013

The
middlereachesof
WaidaniThelowerreachesof
Waidani
KotakoRiv.
Sugitani
Riv.

0.021

0.202

0.022

0.065

0.300

0.024

0.006

0.082

0

0.056

0.111

0.006

0.001

0.008

0.001

0

0.001

0

0.008

0.082

0.005

0.006

0.002

0.028

Fig. 8 is Cu concentration of Corydalidae in the
Waidani, Kotako River, and Sugitani River. Cu
concentration of Corydalidae in the upper reaches ofthe Waidani was about 600 ppm. Cu concentrationof Corydalidae in the middle reaches was about 300
ppm. Cu concentration of Corydalidae in the lower
reaches was about 400 ppm. It turns out that Cu
concentration for Corydalidae in the upper reaches ishigher than those in the middle reaches and thelower reaches. Cu concentration of Corydalidae in
the Kotako River and the Sugitani River was about
50 ppm. The maximum, the minimum and averageof concentration factors of Cu for Corydalidae in the
Waidani were 62000, 7600 and 28000, respectively.
The concentration factor of Cu of Corydalidae in the
Kotako River was 50000. The concentration factorof Cu of Corydalidae in the Sugitani River was 3000.

As concentration of Corydalidae in
the Kogawa River

Polluted zone and limestone region
Table 2 is the river water metal concentrationnear the Waidani, Kotako River, and the Sugitani
River. The river metal concentrations of Cu, Fe, Mn,
Pb, Zn, and As in the upper reaches of the Waidani
were 0.080, 0.067, 0.007, 0.027, 0.700, and 0.013
ppm, respectively. The river metal concentrations of
Cu, Fe, Mn, Pb, Zn, and As in the middle reaches ofthe Waidani were 0.021, 0.202, 0.022, 0.065, 0.300
and 0.024 ppm, respectively. The river metal
concentrations of Cu, Fe, Pb, Zn, and As in thelower reaches of the Waidani were 0.006, 0.028,
0.056, 0.111 and 0.006 ppm, respectively. The river
metal concentrations of Mn in the middle reaches ofthe Waidani were not detected. The river metal
concentrations of Fe in the Kotako River were 0.008
ppm. The other metals were not detected. The river
metal concentrations of Cu, Fe, Mn, Pb and As in
the Sugitani River were 0.008, 0.082, 0.005, 0.006
and 0.028 ppm, respectively. Most Zn concentrationin the Sugitani River was not detected.

Fig. 8

Cu concentration of Corydalidae in the
Waidani, the Kotako River, and theSugitani River

Fig. 9 is Fe concentration of Corydalidae in the
Waidani, Kotako River, and Sugitani River. Fe
531

GEOMATE- Brisbane, Nov. 19-21, 2014

concentration of Corydalidae in the upper reaches of
Waidani and the middle reaches was about 1000
ppm. In the lower reaches, the high concentration
was detected compared with the upper reaches andthe middle reaches at 4000 ppm. Fe concentration of
Corydalidae in the Kotako River was about 1000
ppm. Fe concentration of Corydalidae in the
Sugitani River was about 3500 ppm. The maximum,
the minimum and average of concentration factors of
Fe for Corydalidae in the Waidani were 52000, 4500
and 23000, respectively. The concentration factor of
Fe of Corydalidae in the Kotako River was 78000.
The concentration factor of Fe of Corydalidae in the
Sugitani River was 43000.

Fig. 11 is Pb concentration of Corydalidae in the
Waidani, Kotako River, and Sugitani River. Pb
concentration of Corydalidae in the upper reaches ofthe Waidani is about 90 ppm. Pb concentration of
Corydalidae in the middle reaches is about 25 ppm.
Pb concentration of Corydalidae in the lower reaches
is about 10 ppm. The Kotako River and the Sugitani
River are also the almost same concentration. The
maximum, the minimum and average ofconcentration factors of Pb for Corydalidae in the
Waidani were 3200, 100 and 1200, respectively. The
concentration factor of Pb of Corydalidae in Kotako
River and Sugitani River was not able to be
calculated.

Fig. 9Fig. 11 Pb concentration of Corydalidae in the
Waidani, the Kotako River, and theSugitani River

Fe concentration of Corydalidae in the
Waidani, the Kotako River, and theSugitani River

Fig. 10 is Mn concentration of Corydalidae in the
Waidani, Kotako River, and Sugitani River. Mn
concentration of Corydalidae in the upper reaches ofthe Waidani and the middle reaches is about 250
ppm. Mn concentration of Corydalidae in the lower
reaches is about 2000 ppm. Mn concentration of
Corydalidae in Kotako River and the Sugitani Riveris about 250 ppm. The maximum, the minimum andaverage of concentration factors of Mn for
Corydalidae in the Waidani were 29000, 9800 and
19000, respectively. The concentration factor of Mn
of Corydalidae in Kotako River was 140000. The
concentration factor of Mn of Corydalidae in
Sugitani River was 29000.

Fig. 12 is Zn concentration of Corydalidae in the
Waidani, Kotako River, and Sugitani River. Zn
concentration of Corydalidae in the upper reaches ofthe Waidani is about 700 ppm. Zn concentration of
Corydalidae in the middle reaches is about 600 ppm.
Zn concentration of Corydalidae in the lower
reaches is 1200 ppm. Zn concentration of
Corydalidae in the Kotako River and the Sugitani
River is about 100 ppm. The maximum, theminimum and average of concentration factors of
Mn for Corydalidae in the Waidani were 11000,
1000 and 4600, respectively. The concentration
factor of Zn of Corydalidae in the Kotako River was
120000. The concentration factor of Zn ofCorydalidae in Sugitani River was 57000.

Fig. 10

Fig. 12

Mn concentration of Corydalidae in the
Waidani, the Kotako River, and theSugitani River.
532

Zn concentration of Corydalidae in the
Waidani, the Kotako River, and theSugitani RiverGEOMATE- Brisbane, Nov. 19-21, 2014

concentration factor of Zn of Corydalidae was
120,000 and higher than those of Stenopsyche
marmorata. The maximum concentration factor of
Fe of Corydalidae was 78000 and higher than thoseof Stenopsyche marmorata. The maximum
concentration factor of Fe of Corydalidae was 36000
and higher than those of Stenopsyche marmorata.
The maximum concentration factor of Mn, Fe,and Zn for Corydalidae were very high as well as
Stenopsyche marmorata, in this investigation, andthen, Corydalidae is useful as an index living thingof Mn, Fe, and Zn.
Since the concentration factor of As forCorydalidae was a larger numerical value than thosefor Stenopsyche marmorata, it is useful as an index
living thing for As.

Fig. 13 is As concentration of Corydalidae in the
Waidani, Kotako River, Sugitani River. As
concentration of Corydalidae in the upper reaches ofthe Waidani is about 250 ppm. As concentration of
Corydalidae in the middle reaches and the lower
reaches is about 220 ppm. As concentration of
Corydalidae in the Kotako River and the Sugitani
River is about 25 ppm. The maximum, the minimum
and average of concentration factors of Mn for
Corydalidae in the Waidani were 36000, 9000 and
22000, respectively. The concentration factor of As
of Corydalidae in the Kotako River was not able tobe calculated. The concentration factor of As of
Corydalidae in the Sugitani River was 1000.

CONCLUSION

Fig. 13

Corydalidae eats many kinds of aquatic insects as
food. Then, metal derived from wide area of soil andwater for long term is concentrated in Corydalidae
body by food chain The average of the metal
concentration of Corydalidae under polluted zone
was high. Metal concentration of Corydalidae isclarified to be influenced by river metal conditions.
The concentration factors of Fe, Mn, and Zn for
Stenopsyche marmorata were higher than those for
Corydalidae. The As concentrations and As
concentrstion factors of Corydalidae were high in ariver, then Corydalidae is effective for monitoringAs, since its concentration factor is higher than thosefor Stenopsyche marmorata.
Therefore, it can be said that Corydalidae is usefulas a metal contamination environmental indicatorliving thing of As.

As concentration of Corydalidae in the
Waidani, the Kotako River, theSugitani RiverDISCUSSION
The metal concentrations for river water andCorydalidae in the polluted zone and non-poluuted
zone were measured. It turns out that the metal
concentration for Corydalidae in the polluted zone
was higher than those in the non-polluted zone.
However, Cu and Pb concentrations of river water inthe polluted zone were not different from those in
the non-polluted zone. In the polluted zone, Cu
concentration and Pb concentration of Corydalidae
are high concentration because of a biologicalconcentration. The average concentrations of Cu, Fe,
Mn, Pb, Zn and As of Corydalidae in the nonpolluted zone were 28, 468, 60, 2, 117 and 2 ppm,
respectively. The average concentrations of Cu, Fe,
Mn, Pb, Zn and As of Corydalidae in the polluted
zone were 421, 1970, 775, 38, 820 and 234 ppm,
respectively. Metals, Cu, Fe, Mn, Pb, Zn and As areclarified to be concentrated in a body of Corydalidae
larva.
The maximum concentration factor of Mn ofCorydalidae was 140,000 and higher than those of
Stenopsyche
marmorata.
Themaximum

REFERENCES[1] Aizawa S, Kakuta K, and et.al “Evaluation ofa caddis fly as a metal contamination
environmental indicator living thing” , Bunseki
Kagaku, Vol. 43, 1994
[2] Makoto S, and et.al “Shift of a radioactive
material to a living thing from fresh water”,
Radioactive Waste Management Center, 1992
[3] Yoshinori T, Takuzou Y, “The life history of
Parachauliodes continentails in Sugihara river,
Hyogo”, Hyogo Inland Water Living Thing,Vol. 50, 1999, pp. 7-13
[4] Sadahisa S, Ryoji K, “Mineral Resources Map
of Chubu Kinki”, Geological Survey of Japan,
2000

533

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

CHEMISTRY OF RIVER WATER, RIVER INSECT AND WATER
PLANT IN THE KINOKAWA RIVER CATCHMENT
Takuma Kubohara1, Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan;
2
Faculty of Systems Engineering, Wakayama University, Japan

1

ABSTRACT
Metal concentration of insect and plant was useful for determination of metal contamination and was
proposed to be an effective index as metal contamination. Chemistry of water, river insect and water plant werestudied in the serpentinite area, the closed mine area and another area of the Kinokawa River catchment in orderto clarify influence of geological condition on water, insect and plant. Cu, Co and Ni concentrations of water
were lower than those of insects and plants. Cu and Co in river insect and water plant were affected by Cu mines
because those concentrations of river insect and water plant were high in the closed Cu mine area. Ni in river
insect and water plant were affected by serpentinite because the concentrations of river insect and water plant
were high in the serpentinite area. It was found that metals concentrations in moss, plant root and river insect
were effective indicator for the influence of geological condition because Cu and Co concentrations of moss,
plant root and river insects in the closed Cu mine area and Ni concentrations of moss and plant root in theserpentinite area were high.

Keywords: Heavy Metals, Serpentinite, Closed Cu Mines, Insects, Plants

sandstone, mudstone, conglomerate and et al. is
distributed in the northern part of research area, andSanbagawa belt composed of metamorphic rocks,
crystalline schist and et al. is distributed in thesouthern part, Hidakagawa Group composed of
sedimentary rocks, sandstone and shale is distributedin the southeast part.
The Kinokawa River catchment has serpentinite
and the closed Cu mines. The chemistry of
Serpentinite is quite different from another rocks, inparticular, serpentinite has high concentration of Mg,
and Ni. The closed Cu mine produced a lot of Cu
and Fe sulfide ore and waste water was low pH andhigh concentration of sulfate with metal.

INTRODUCTION
Generally, the environment of water area ismainly evaluated by water quality. Moreover, mostof water quality standards are established in order tokeep the human life safely.
However, biodiversity is taken seriously inrecent years. Therefore, in Japan, environmental
quality standards for water pollution andpreservation of aquatic life were established in
November 2003.
However, chemistry of aquatic life is notinvestigated enough.
Therefore, in this study, chemistry of water, river
insect and water plant was studied in order to clarify
influence of geological condition on water, insect
and plant.

STUDY METHOD
We investigated chemistry of river water, river
insect and water plant. Mg2+, Ca2+, Cu, Co and Ni
concentrations in river water and Cu, Co and Ni inriver insect and water plant were measured.
River water samples were kept cool and it was
filtered with the membrane filter with 0.45
micrometer of pore size for analysis in laboratory.
The sampled river insects and water plants were
desiccated by dryer at first. After drying, they weredissolved with concentrated nitric acid and it was
filtered with the membrane filter with 0.45
micrometer of pore size for analysis.

STUDY AREA
Fig.1 shows the location of study area. The
Kinokawa River is located in Kinki. The KinokawaRiver has its origin in Odaigahara, and flows to west
along the median tectonic line. The flow is fromSouth Nara through Kii plain into the Kii channel.
Kinokawa is class A river, and the length is 136 km,
total basin area is 1,750 km2 [1]. The catchment inWakayama prefecture is the research area.
Izumi Group composed of sedimentary rocks,534

GEOMATE- Brisbane, Nov. 19-21, 2014

mainstreamOsaka Pref.

Nara
Pref.

Cu mineSerpentinite

Cu mineflow
Wakayama
Pref.

Fig.1 Study area.
Mg2+ and Ca2+ were measured by ion exchange
chromatography. Cu, Co and Ni were measured by
ICP-AES. The actual detection limit of ICP-AES is
0.01ppm for Cu, Co and Ni.
Table.1 shows summary of field observation.
About water plant except moss, the body divided
into upper part, middle part, lower part and root.
Therefore, one part is one sample.

Table.1 Summery of field observation.
the serpentinite the closed the anotherarea
Cu mine area
area
observation July, Sep.2013,
timeFeb., Apr.2014
water

RESULTS AND DISCUSSION
Mg/Ca Equivalent Ratio in River Water

Dec.2013,
Apr.2014

Dec.2013,
Jan.2014

7

3

18

28

15

4

18

37

Dec.2013,
Apr.2014

Dec.2013,
Jan.2014

7

3

15

25

19

6

19

44

gammaridea,
dobsonfly
larva,
caddice-worm,
stonefly larva,
dragonfly larva

crane flylarva,
dobsonfly
larva,
dragonfly
larva,
corixidae,
rat-tailed
maggotcorixidae,
crane flylarva,
stoneflylarva,
dragonfly
larva

observation
Feb., Apr.2014
timeDec.2013,
Feb.,
Apr.2014

Dec.2013,
Jan.,
Feb.2014

7

3

18

28

33

27

73

133

fern, moss

coix, reed,japanesesilver grass,fern, moss

coix, reed,
paspalumsampling
pointsnumber ofsamples

observation July, Sep.2013,
timeFeb., Apr.2014

Fig.2 shows Mg/Ca equivalent ratios in riverwater. Generally, it is known that Mg/Ca ratio in theriver water is used for estimation of the geologicalcondition in the catchment.
Mg/Ca equivalent ratios in the serpentinite area
were from 0.25 to 24, those in another two areas
were from 0.12 to 0.56. Then, Mg/Ca equivalentratios in the serpentinite area were higher thananother two areas. It is known that the serpentinite
contains a lot of Mg. Therefore, river water in theserpentinite area was influenced by serpentinite.

sampling
pointsnumber ofsamplesriver
insectspeciesHeavy Metals in River Water
Figs.3, 4 and 5 show Cu, Co and Ni
concentrations in river water. Cu concentrations in
the closed Cu mine area were from under detection
limit to 0.34ppm, those in another two areas were
under detection limit. Then, Cu concentrations in theclosed Cu mine area were higher than another twoareas. But the highest Cu concentration was found at
the mining sewage and the river water. Except thehighest Cu concentration data, Cu concentrations

sampling
pointswaternumber ofplant
samples
species

535

total

GEOMATE- Brisbane, Nov. 19-21, 2014

25.00

0.40

20.00
Co(ppm)

Mg/Ca

0.30

15.00
10.00

0.10

5.00
0.00

0.20

0.00

serpentiniteareaclosed Cu
mine area

anotherarea

0.40

another
area

0.40

0.30

0.30
Ni(ppm)Cu(ppm)closed Cu
mine area

Fig.4 Co concentrations in river water.

Fig.2 Mg/Ca equivalent ratios in river water.

0.20
0.10
0.00

serpentinite
area

0.20
0.10
0.00

serpentinite closed Cu
areamine area

anotherarea

serpentiniteareaclosed Cu
mine area

anotherarea

Fig.3 Cu concentrations in river water.

Fig.5 Ni concentrations in river water.

were almost under detection limit in all area.
Co and Ni concentrations were under detection
limit in all area.
Therefore, although there are Cu mines andserpentinite in the catchment, Cu, Co and Ni
concentrations in river water were very low, almost
under detection limit except some sewage and riverfrom the Cu mine.

detection limit to 10 mg/kg-dry. Then, Cu and Co
concentrations of river insect and water plant in theclosed Cu mine area were higher than another twoareas. The Cu mines in the Kinokawa River
catchment have cupriferous pyrite [2]. It is known
that the cupriferous pyrite contains Cu, Co, etc [3].
Therefore, Cu and Co of river insects and water
plants in the closed Cu mine area were affected by
Cu mines.
In the serpentinite area, Ni concentrations ofriver insect were from under detection limit to 220
mg/kg-dry, Ni concentrations of water plant werefrom under detection limit to 270 mg/kg-dry. In
another two areas, Ni concentrations of river insect
were from under detection limit to 20 mg/kg-dry, Ni
concentrations of water plant were from underdetection limit to 30 mg/kg-dry. Then, Ni
concentrations in river insects and water plants inthe serpentinite area were higher than another twoareas. It is known that the serpentinite contains Ni.
Therefore, river insects and water plants in theserpentinite area were affected by the serpentinite.

Heavy Metals in River Insect and Water Plant
Figs.6, 7, 8, 9, 10, 11 and 12 show Cu, Co and Ni
concentrations in river insect and water plant. Fig.9
shows all Cu concentrations data, however, Fig.10
shows just less than 800mg/kg-dry for Cu
concentrations.
In the closed Cu mine area, Cu concentrations ofriver insect were from 440 mg/kg-dry to 663 mg/kgdry, Co concentrations of river insect were fromunder detection limit to 40 mg/kg-dry, Cu
concentrations of water plant were from underdetection limit to 10,000 mg/kg-dry, Co
concentrations of water plant were from underdetection limit to 61 mg/kg-dry. In another two areas,
Cu concentrations of river insect were from underdetection limit to 190 mg/kg-dry, Co concentrationsof river insect were under detection limit to 10
mg/kg-dry, Cu concentrations of water plant werefrom under detection limit to 99 mg/kg-dry, Co
concentrations of water plant were from underComparison of River Water with River Insect
and Water Plant on Heavy Metals
From Figs.3, 4 and 5, Cu, Co and Ni
concentrations in river water were from underdetection limit to 0.34ppm, under detection limit andunder detection limit, respectively.

536

GEOMATE- Brisbane, Nov. 19-21, 2014

700

12000
10000

500
8000

Cu(mg/kg-dry)

Cu(mg/kg-dry)

600

400
300
200
100
0
serpentiniteareaclosed Cu
mine area

6000
4000
2000
0

anotherarea

serpentiniteareaclosed Cu
mine area

anotherarea

Fig.9 Cu concentrations in water plant.

Fig.6 Cu concentrations in river insect.
50

800
700
600
Cu(mg/kg-dry)Co(mg/kg-dry)

40
30
20
10

500
400
300
200
100
0

0
serpentiniteareaclosed Cu
mine area

serpentinitearea

anotherareaclosed Cu
mine area

anotherarea

Fig.10 Cu concentrations in water plant(<800 mg/kg-dry).

Fig.7 Co concentrations in river insect.
250

70
60
Co(mg/kg-dry)Ni(mg/kg-dry)

200
150
100
50

50
40
30
20
10

0
serpentiniteareaclosed Cu
mine area0

anotherarea

serpentinite
area

From Figs.6, 7 and 8, Cu, Co and Ni
concentrations in river insects were from underdetection limit to 663 mg/kg-dry, from underdetection limit to 40 mg/kg-dry and from underdetection limit to 220 mg/kg-dry, respectively.
From Figs.9, 10, 11 and 12, Cu, Co and Ni
concentrations in water plants were from underdetection limit to 10,000 mg/kg-dry, from underdetection limit to 61 mg/kg-dry and from underdetection limit to 270 mg/kg-dry, respectively.
As a result, heavy metals concentrations ofinsects and plants were higher than those of riverwater. Therefore, heavy metals in insect and plant
were effective indicator for the influence ofgeological condition.
Heavy

Metalsanotherarea

Fig.11 Co concentrations in water plant.

Fig.8 Ni concentrations in river insect.

Relationship between
Geological Condition

closed Cu
mine area

300

Ni(mg/kg-dry)

250
200
150
100
50
0
serpentiniteareaclosed Cu
mine area

anotherarea

Fig.12 Ni concentrations in water plant.
almost under detection limit.
From Figs.6, 7, 9, 10 and 11, Cu and Co
concentrations in river insects and water plants inthe closed Cu mine area were higher than anothertwo areas. Therefore, those of Cu and Co
concentrations were useful for determination of
influence of Cu mines.
From Figs.8 and 12, Ni concentrations in river
insects and water plants in serpentinite area werehigher than another two areas. Therefore, those of Ni

andFrom Figs.3, 4 and 5, although there are Cu
mines and serpentinite in the catchment, Cu, Co and
Ni concentrations in river water were very low,537

GEOMATE- Brisbane, Nov. 19-21, 2014

70

12000

60

Co(mg/kg-dry)

Cu(mg/kg-dry)

10000
8000
6000
4000
2000
0

50
40
30
20
10
0

except plant root moss river insect
plant root
closed Cu mine area

Fig.13 Cu concentrations of river insect andwater plant in the closed Cu mine area.

300

700

250
Ni(mg/kg-dry)

500
400
300
200

200
150
100
50

100
0

river insect

Fig.15 Co concentrations of river insect andwater plant in the closed Cu mine area.

800
600
Cu(mg/kg-dry)

exceptmoss
plant root
plant root
closed Cu mine area

0

except plant root moss river insect
plant root
closed Cu mine area

Fig.14 Cu concentrations of river insect andwater plant in the closed Cu mine area(<800 mg/kg-dry).
concentrations were useful for determination of
influence of serpentinite.
As the above, when the contamination was notable to be found by measurement of heavy metals in
the river water, contamination was clarified bymeasurement of those in river insect and water plant.
Therefore, it was thought that heavy metals in river
insect and water plant become an important index as
contamination.

moss
except plant root
plant root
serpentinite areariver insect

Fig.16 Ni concentrations of river insect andwater plant in the serpentinite area.
concentrations of water plant were from underdetection limit to 61 mg/kg-dry, Ni concentrations ofriver insect were from under detection limit to 220
mg/kg-dry, Ni concentrations of water plant werefrom under detection limit to 270 mg/kg-dry. Then,
Co and Ni concentrations of water plants were
almost the same range as those of river insects.
Cu and Co concentrations of river insects, (A)and (B) were from 20 mg/kg-dry to 10,000 mg/kgdry and from under detection limit to 61 mg/kg-dry,
respectively. Cu and Co concentrations of (C) werefrom under detection limit to 100 mg/kg-dry andunder detection limit, respectively. Then, Cu and Co
concentrations of river insects, (A) and (B) werehigher than those of (C). Therefore, it was found thatCu and Co in river insect, moss and plant root wereeffective indicator for the influence of geologicalcondition.
On the other hand, Ni concentrations of (A) and(B) were from 10 mg/kg-dry to 270 mg/kg-dry. Ni
concentrations of river insects and (C) were fromunder detection limit to 220 mg/kg-dry, althoughmost data below 100mg/kg-dry. Then, Ni
concentrations of (A) and (B) were higher than thoseof river insects and (C). Therefore, it was found that
Ni in moss and plant root was effective indicator for
the influence of geological condition.

Compariosn of River Insects with Water Plantsfor Heavy Metals
Cu, Ni and Co concentrations of river insect andwater plant were compared at the two fields, the Cu
mine area and serpentinite area.
Figs.13, 14, 15 and 16 show the comparison
results. Fig.13 shows all Cu concentrations data,
however, Fig.14 shows just less than 800mg/kg-dry
for Cu concentrations. Water plants were classified
into moss (A) and other plant. Additionally, itclassified other plants into root (B) and other part(stem and leaf) (C).
Cu concentrations of river insect were from 440
mg/kg-dry to 663 mg/kg-dry, Cu concentrations ofwater plant were from under detection limit to
10,000 mg/kg-dry. Then, Cu concentrations of water
plant were higher than those of river insect.
Co concentrations of river insect were fromunder detection limit to 40 mg/kg-dry, Co
538

GEOMATE- Brisbane, Nov. 19-21, 2014

root and river insect were effective indicator for the
influence of geological condition because Cu and Co
concentrations of moss, plant root and river insect in
the closed Cu mine area and Ni concentrations ofmoss and plant root in the serpentinite area were
high.
Therefore, metal concentrations of insect andplant were useful for determination of metal
contamination and became an important index as
contamination.

CONCLUSION
In this study, chemistry of water, river insect andwater plant was studied in the serpentinite area, theclosed mine area and another area of the KinokawaRiver catchment in order to clarify influence ofgeological condition on water, insect and plant.
It was thought that river water in the serpentinite
area was affected by serpentinite because Mg/Ca
equivalent ratios of river water in the serpentinite
area were high.
Cu, Co and Ni concentrations of water werelower than those of insect and plant.
Cu and Co concentrations of river insect andwater plant in the closed Cu mine area and Ni
concentrations of them in the serpentinite area werehigh, although Cu, Co and Ni concentrations of riverwater in all area were almost under detection limit.
Therefore, it was thought that Cu and Co of
insects and plants in the closed Cu mine area wereaffected by Cu mines. Moreover, it was thought that
Ni of insects and plants in the serpentinite area wereaffected by serpentinite.
It was thought that heavy metals in moss, plant

REFERENCES[1] River Bureau Kinki Regional Development
Bureau Ministry of Land, Infrastructure,
Transport and Tourism, Kinokawa Basin,
http://www.kkr.mlit.go.jp/river/kasen/kinokaw
a.html[2] Wakayama City Children’s Science Museum,
http://www.city.wakayama.wakayama.jp/kodo
mo/sassi/ganseki/p9.htm[3] Miyazaki Prefecture, http://www.pref.miyazaki.
lg.jp/shoukou/kougyou/m-geo/4th/index.htm

539

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

COMPARATIVE ANALYSIS OF EMBANKMENT METHODSUTILIZING EXPANDED POLY-STYROL AND
CONVENTIONAL METHOD IN MOUNTAIN ROAD
IN JAPAN BY LIFE CYCLE ASSESSMENT
Hideyuki Ito1, Koichi Yamanaka2, Shoma Nehashi3, Atsushi Fukuda4 and Kunio Minegishi5
1,2,4,5
College of Science and Technology, Nihon University, Japan;
3
Nexco-Maintenance Kanto Company Limited, Japan

ABSTRACTIn recent years, new composite geomaterials that were developed to reduce the weight are expected to be
applies to soft ground and mountainous areas for preventing ground liquefaction and landslide in Japan. These
new composite geomaterials have some problems such as taking much time for construction, increasing theconstruction cost and adverse impacts on environment. Thus, the conventional geomaterial is usually chosen
than new composite geomaterials in Japan. However, there are few researches that analyzed the environmental
impacts (for example, CO 2 , Nox, Sox and total life-cycle cost) of new developed composite geomaterials
quantitatively from the perspective of LCA (life cycle assessment). Therefore, the purpose of this research is toestimate the total emissions of CO 2 , Nox, Sox and total life-cycle cost of 3 kinds of embankments constructed byconventional method (cut and fill), lightweight geomaterial mixed with expanded polystyrol beads and expanded
polystyrol construction method in mountain road by applying the life cycle assessment.
Keywords: Life Cycle Assessment, Lightweight Geomaterial Mixed with Expanded Polystyrol Beads, Expanded
Polystyrol Construction Method, Life Cycle Cost

life cycle including raw materials acquisition,
construction, use and waste phase.
Therefore, the purpose of this research is toestimate the total emissions of CO 2 , Nox, Sox andtotal life-cycle cost of 3 kinds of embankments
constructed by conventional method (cut and fill),lightweight geomaterial mixed with expanded
polystyrol beads and expanded polystyrol
construction method in mountain road by applying
the life cycle assessment.
In this research, total amount of air pollutants
and CO 2 emissions of conventional construction
method by cut-and-fill and new methods using lightweight geomaterial mixed with expanded polystyrol
beads and expanded polystyrol construction method
were estimated in consideration of all life cycles
including the raw materials acquisition for
construction, use, and waste phase. In addition, thetotal life cycle cost of these 3 construction methods
were also calculated and performed the comparativeevaluation of these construction methods.

INTRODUCTION
In Japan, a lot of wetlands, rivers and coastal
area have been reclaimed to increase agriculturalland because the flat plains are narrow and limited.
Thus, there are many potential areas that mightcause the ground settlement and ground liquefaction.
In addition, since it is difficult to acquire land forconstructing roads in Japan, a lot of roads andbuildings have been built in the mountains. On thesebackgrounds, recently new composite geomaterials
have been developed in Japan to reduce the weight
for applying to soft ground and mountainous areasfor preventing landslide. Composite geomaterials are
expected as landslide prevention works by weightsaving.
In the existing researches, various composite
geomaterials with additional values and new
physical properties such as the cement stabilized soil,
light weight treated soil with air foam method,liquefied soil stabilization method, and tire tip mixed
soil are developed and estimated amount of CO 2
emissions at the manufacturing phase [1]-[2]. In
addition, eco-efficiency assessment has been carriedout by the simulation and sensitivity analysis asenvironmental
assessmentofcomposite
geomaterials using construction sludge [3]. However,these existing researches are not compared with theconventional method and then estimated theemission of the air pollutants with considering all

METHOD AND SYSTEM DETAILSIn this research, Mineoka area located in thesouthern part of Chiba prefecture was selected as acase study area because landside control works are
conducted in mountainous roads (Fig.1). For
comparative
LCA
analysis,weassumedconventional method, lightweight geomaterial mixed
540

GEOMATE- Brisbane, Nov. 19-21, 2014

with expanded polystyrol beads and expanded
polystyrol construction method were adopted forconstructing mountainous roads.
Also, we set a functional unit that provides alogical basis for comparing the en,vironmental
performance of alternatives for applying LCA tothese 3 construction methods. We defined the target
road condition (2 lanes, 7m wide and 1m long) as afunctional unit as shown in the Fig.2. In addition, we
hypothesized that the inclined angle of the mountainand road slope is 35 degree and 55 degree
respectively, and then we set the ratio of cut and fillof conventional method is 3:1, the ratio of cut andfill of lightweight geomaterial mixed with expanded
polystyrol beads and expanded polystyrol
construction method is 1:3 (Fig.3).

limestone is transported to the plant for producing
stabilizing material, and then the transported soil,
sand, stabilizing material and water are mixed andleveled the ground at the road construction site. Cutand fill method is basically maintenance-free. At thewaste phase, soil and sand are recycled after
demolishing the road.

Fig. 3 System boundary of cut and fill method(conventional method).

Fig. 1

Location of case study area.

Fig. 2Functional unit.

Fig. 3

Set condition of each construction method.

Fig.4 shows the system boundary of lightweightgeomaterial mixed with expanded polystyrol beads.
Expanded polystyrol beads are produced in the plantat the phase of raw materials acquisition. At theconstruction phase, the limestone is transported tothe plant for producing stabilizing material as wellas “cut and fill (conventional method)”, and then thetransported expanded polystyrol beads, soil, sand,stabilizing material and water are mixed and leveled
the ground at the road construction site. Constructed
lightweight geomaterial mixed with expanded
polystyrol beads is also maintenance-free. Recycling
method for lightweight geomaterial mixed withexpanded polystyrol beads at the waste phase is notdetermined at present but we assumed the blowing
separator is used for recycling soil.

Fig. 4 System boundary of lightweightgeomaterial mixed with expanded polystyrol beads.

System Boundary of Each Construction Method

Fig.5 shows the system boundary of expanded
polystyrol
construction
method.
Expandedpolystyrol beads are produced in the plant at the raw

The system boundary of “cut and fill(conventional method)” is shown in Fig.3. The
541

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 1 CO 2 , Sox and Nox unit.

materials acquisition phase as well as lightweightgeomaterial mixed with expanded polystyrol beads.
The clamping materials that are used for expanded
polystyrol construction method are manufactured
from aluminum produced from imported bauxite andzinc smelt from sphalerites at the plant. The soil
generated by excavation at the road construction site,
styrofoam and clamping materials are used for
expanded polystyrol construction. At the waste
phase, all materials are disposed at the plant after
demolishing the road.

Life-cycle

Materials
Soil, Sand (kg)Limestone (kg)EPS (kg)
Aluminum (kg)
Zinc (kg)Leveling (㎥)Compaction (㎥)20t Truck (Diesel) （km）
15t Truck (Diesel) （km）
10t Truck (Diesel) （km）
4t Truck (Diesel) （km）
2t Truck (Diesel) （km）
EPS (kg)
Metal (kg)Raw Materials
Acquisition

Construction

Transport

Waste

Electricity(Thermal power plant) (kwh)

EnergyCO2(kg-CO2)0.001963
0.004688
1.31226
9.218
1.443
20.9
12.1
1.18
0.962
0.742
0.472
0.323
2.64
0.366

SOx
(g-SOx)0.003407
0.000865
0.255529
76.8
5.92
28.91883
16.74248
1.45
1.18
0.91
0.56
0.4
0.544
0.325

NOx
(g-NOx)0.010598
0.001547
1.16509630
1.327
48.17308
27.88968
3.64
2.97
2.229
1.45
1.0
1.22
0.591

0.425

0.17

0.13

Table 2 Cost unit for each material.
Materials

Unit

JPY

Polystyrene
Crushed stone
Limestone
Aluminum
Zinc

JPY/kg
JPY/kg
JPY/kg
JPY/kg
JPY/kg209.8622
0.633
76.539186.132

Electricity(Thermal power plant)

JPY/kwh16.19839

JPY/L
JPY/kg
JPY/kg78.9790.510976
0.998192
934.2707

DieselWaste (Plastic)
Waste (Metal)
Leveling & Compaction

Fig. 5 System boundary of expanded polystyrol
construction method.
Method and System Details

JPY/m3

Table 3 Air pollutants and CO 2 emissions of cut
and fill method.

For calculating the total amount of air pollutants
and CO 2 emissions, we set the CO 2 , Sox and Nox
unit (Table.1) and cost unit for each material (Table2). These units were developed based on various
databases and data such as LCA guideline forbuilding [4], IDEA (Inventory Database forEnvironmental analysis) [5], LCA databasedeveloped by Life Cycle Assessment Society ofJapan [6], database of Express Highway Research
Foundation of Japan [7] and database of JEMAILCA PRO [8]”. Cost unit for each material was
estimated Input-Output Table of ministry of internalaffairs and communications [9]. Regarding thepower consumption of blowing separation that isused for recycling soil and sand for lightweightgeomaterial mixed with expanded polystyrol beads,
we estimated it based on the result of interview
survey to a machinery manufacturer.
Estimated total amount of air pollutants and CO 2
emissions of each construction method by using
these databases are shown in Table.3, 4 and 5.

CO2
SOx
Nox
(kg-CO2) (g-SOx) (g-NOx)

Cost
(JPY)

Materials

Usage

Soil, Sand (kg)26539.8

52.1

90.4

281.3

53079.6

Limestone (kg)

405.5

1.9

0.4

0.6

256.7

6.3

208.5

288.5

480.6

5903.7

Leveling &3

Compaction (m )Soil, Sand (kg)

30.0

35.4

43.5

109.2

1077.0Limestone (kg)

160.0

51.7

64.0

160.0

1579.6

Table 4 Air pollutants and CO 2 emissions oflightweight geomaterial mixed with expanded
polystyrol beads.
Life Cycle Stage

Materials
Soil, Sand (kg)

CO2
SOx
Nox
(kg-CO2) (g-SOx) (g-NOx)
10615.0
20.8
36.2
112.5

Raw Materials
Acquisition

Limestone (kg)1105.7

5.2

1.0

1.7

699.9

EPS (kg)

88.9

116.7

22.7

103.6

18656.9

Soil, Sand (kg)2944.9

5.8

10.0

31.2

5889.8

9.7

318.5

440.6

734.0

9015.7

Construction

Transport

Waste

542

Leveling &Compaction (m3)

Usage

Cost
(JPY)
21230.0

Soil, Sand (kg)

30.0

28.9

35.4

89.1

877.5

Limestone (kg)

160.0

51.7

64.0

160.0

1579.6

EPS (kg)

160.0

51.7

64.0

160.0

1579.6

Demolition (kwh)

11.9

5.1

2.0

1.5

192.8

EPS (kg)

88.9

234.7

48.4

108.5

45.4

GEOMATE- Brisbane, Nov. 19-21, 2014

Table 5 Air pollutants and CO 2 emissions of
expanded polystyrol construction method.
CO2
SOx
Nox
(kg-CO2) (g-SOx) (g-NOx)
448.7
588.8
114.6
522.7

Cost
(JPY)

Life Cycle Stage

Materials

Raw Materials
Acquisition

Aluminum (kg)

1.2

11.0

91.7

35.8

91.3

Zinc (kg)

0.9

1.4

5.6

1.2

175.3

EPS (kg)

Construction
Transport
Waste

Usage

cycle cost than other methods. In general, the costfor polystyrol beads at raw materials acquisition
phase was caused cost increase.

94156.5

Soil, Sand (kg)2944.9

5.8

10.0

31.2

5889.8EPS (kg)

160.0

75.5

89.6

232.0

1944.1

Soil, Sand (kg)

30.0

14.2

16.8

43.5

364.5

EPS (kg)

448.7

1184.5

244.1

547.4

229.3

Metal (kg)

2.2

0.8

0.7

1.3

2.2

RESULTFig.6 shows the results of estimated air pollutants
and CO 2 emissions of each construction method ateach life cycle phase. As the result, the expanded
polystyrol construction method was the largest CO 2
emissions comparing with other methods because alarge amount of CO 2 was discharged by productionof styrofoam at raw materials acquisition phase anddisposition of expanded polystyrol beads at waste
phase. In regards to SOx emissions, the lightweightgeomaterial mixed with expanded polystyrol beads
was a bit larger than other methods due to higher
SOx emissions at construction phase. In terms ofNOx emissions, lightweight geomaterial mixed withexpanded polystyrol beads was the biggest becauseof high NOx emissions at construction and transport
phase.

Fig. 7 Estimated total life-cycle cost of eachconstruction method.

CONCLUSIONAs the result of comparative analysis of 3
construction methods including conventional
method, we concluded that adding the polystyrolmaterials to the composite geomaterials increase theair pollutants and CO 2 emissions at raw materials
acquisition and waste phase. If polystyrol materials
will be recycled, these emissions might decrease
than at present.
In this research, it was found that the cut and fillmethod (conventional geomaterial) was lower
environmental impacts and life cycle cost than otherconstruction methods. However, further study needs
to perform comprehensive evaluation that included
the perspective of safety degree for a faircomparison through life cycle impact assessment.
REFERENCES[1] K Omine, H Ochiai “Evaluation ofenvironmental impact and recycling efficiency
for composite geomaterials using wastes”,
Proceedings of the sixth Japan National
Symposium on Environmental Geotechnology,
2005, pp. 203–208.
[2] H Ochiai, K Omine “Evaluation ofenvironmental impact and development of
mixed composite materials with new additional
value.” The Foundation engineering &equipment, Vol. 32, Aug. 2004, pp.9-11.
[3] S Inazumi, H Otsu, T Isoda, Y Shigematsu“Evaluation of social environmental efficiency”.
on recycling of construction sludges as groundmaterials” Journal of geological engineering,
Vol.68. 2012, pp.163-174.
[4] Architectural Institute of Japan,“LCA guideline for building”, 2006.

Fig. 6 Estimated amount of air pollutants and CO 2
emissions of each construction method.
Fig.7 indicates the results of estimated total lifecycle cost of each construction method. The cost of
the lightweight geomaterial mixed with expanded
polystyrol beads was the cheapest but the expanded
polystyrol construction method was the biggest life543

GEOMATE- Brisbane, Nov. 19-21, 2014

[5] Advanced Industrial Science and Technology,“IDEA (Inventory Database for Environmental
analysis)”, 2010.
[6] Life Cycle Assessment Society of Japan,“LCA database”, 2003.
[7] Express Highway Research Foundation of Japan,“Proposal of Estimation Method of CO 2
emissions on Road Projects”, 2004.
[8] Japan Environmental Management Association
for Industry,“JEMAI-LCA PRO”, 2000.
[9] Ministry of Internal Affairs andCommunications,“Input-Output Tables of Japan”, 2005.

544

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

CU, ZN AND AS CONTAMINATION OF SEAWEED BESIDE SHIZUKIAND KANAYAMA METAL MINES IN JAPAN
Hiroyuki Ii
Faculty of Systems Engineering, Wakayama University, Japan

ABSTRACTBrown seaweed, Sargassum thunbergii is thought to be effective for As, Cu and Zn sensor. Green seaweed,
Ulvales, red seaweed, Caulacanthus ustulatus and Ahnfeltiopsis flabelliformis are thought to be effective for justCu sensor. High Zn concentration and large volume of Zn drainage water from the closed Kanayama mine
flowed into sea and drainage water and groundwater containing Cu Zn, As contacted with muck along the coast
also flowed into sea in the closed Shizuki mine. Cu, Zn and As concentrations for many kinds of seaweedsampled at the two mines and no contamination places, the Kii and Izu Peninsula, were measured. Cu Zn and As
concentrations for Sargassum thunbergii are 1000, several 100 and several 100 ppm at the Shizuki mine and 10,
several 1000 and 100 ppm at the Kanayama mine, and 10, several 10 and 100 ppm at the no contamination
places.
Keywords: Seaweed, Metal sensor, Metal mine, sea metal contamination
Fig.1 shows the study areas including 2 closed
metal mines, Shizuki and Kanayama mines and 5
non contamination areas, North Senjyo, South
Senjyo, Kada (Wakayama city), Saikasaki(Wakayama city) and Nawachi coasts. Both two
small metal mines are facing sea. Drainage waterand muck was accumulated on the coast. Seaweed
was sampled along the coast. Sampling date for
Kanayama is May 2013. Senjyo April 2013,
Nawachi February 2014, Kada March 2014,
Shizhuki July and Aug 2013 and March 2014, andSaikasaki May 2014. Sampled seaweed was dried
and then dissolved with concentrated nitric acidsolution. The solution after filtration was analyzed tobe metal concentration by ICP-AS. Spring water andriver water including adit drainage were also
analyzed by ICP-AS.

INTRODUCTION
Many papers about metal concentration ofseaweed are published and high bioconcentration
factor of heavy metal was found for many kind ofseaweed [1]–[2]. The relation between time or sea
metal concentration and bioconcentration factor was
clarified [3]–[5]. Metal concentration of seaweed atheavy metal contamination area was published andmetal concentration for water and contaminated soil
were also described [6]–[8]. However a monitoringof water and soil is important for evaluating
contamination, it spends long term sampling andlarge number of sampling for reaching average valueof metal concentration for water and soil because
water and soil metal concentrations are variable fortime and place. To measure metal concentration ofseaweed is easier than to measure those of water orsoil because metal concentration of seaweed ishigher than those of water or soil because of
bioconcentration factor and seaweed has long term
information. Then, the purpose of this study is tofind effective seaweed as a metal sensor. There aremany kinds of seaweeds and then eachbioconcentration factor is variable. Therefore,
effective seaweed as a metal sensor needs wide
distribution and changeable concentration depending
on metal concentration of water and soil. Then,comparing seaweed at contaminated area and noncontaminated area, we select effective seaweed as ametal sensor. In this study, Cu, Zn and As wereselected because Cu, Zn and As were popular heavy
metals in Japanese metal mine contamination area.

Japan Island

ShizukiKanayama
Senjyousiki
Wakayama
Nawachi

METHOD
Fig. 1545

Sampling points for seaweedGEOMATE- Brisbane, Nov. 19-21, 2014

water Zn concentration was also high.
Fig.4 and 5 show Cu concentration and Cu load
for spring and river waters. Although Cu load
reached several kg per year, Cu concentration wasvery low and 0.01 to 0.05 mg/l for spring and 0.005
to 0.01 mg/l for river since 2011. As concentrations
for spring and river water were under detection limit
0.001 mg/l. Then, in the Kanayama mine area Zn
contamination was quite large and Cu contamination
was also thought to bring out. As contamination was
not thought bring out or to be very small.

RESULTS
Condition for mine metal contamination area
Shizuki mine is copper mine at the Japan sea sideand primary metal minerals are pyrite FeS 2 ,spharelite
ZnS,
chalcopyrite
CuFes 2andarsenopyrite FeAsS. In this mine, there is a lot ofmuck along the coast. As the secondary metalmineral, atacamite Cu 2 (OH) 3 Cl was also found at
the spring point and at the surface of muck stonealong the coast, sea water was thought to react withspring water containing copper from mine. Table 1
shows flow rate and Cu, Zn and As concentrations
for drainage and spring water. Cu concentration was
high, a few mg/l and Cu load reached 5kg. Cu
contamination was thought to bring out. Zn and As
contamination was also thought to bring out becauseof drainage water and metal mineral including Zn
and As.

Condition for no contamination area
Senjyo coast is 3 km northwest from the
Kanayama Bay. Wakayama coast, Kada andSaikasaki are 70 km northwest from the Kanayama
Bay. Nawachi is located at the Izu peninsula in thecenter of Japan facing the Pacific Ocean. The all
coast was located far from the big city and mine area
and then heavy metal contamination was not thought
to bring out. However the Senjyo coast is close to
the Kanayama Bay and metal contamination may
occur.

Table 1 This is the example for table formatting

100

2014/3/28
0.6
1.472
0.46
0.748
0.24
0.038
0.01

10000

80

8000

60

6000

40

4000

20

Kanayama mine is located at the Kanayama Bay
in the Kii Peninsula facing the Pacific Ocean.
Although main production was Pb (Galena PbS 5%
of total metal mineral), main metal mineral is pyrite(50%) and spharelite (40%). Chalcopyrite (5%) was
also found in the vein. Drainage water from two vein
flows into the Kanayama Bay. One drainage waterflows into the bay through the river. The otherdrainage is spring on the coast facing the bay.
Fig.2 and 3 show Zn concentration and Zn load
for spring and river waters. Zn concentration ofspring and river were less than 50 to 90 mg/l and 1
to 5 mg/l. Flow rate for spring increased since 2009
till 2011 and then Zn concentration decreased.
However, Zn load increased with flow rate and since2011 Zn load for spring was 2000 to 4000 kg per
year. Zn load for river was 1000 kg per year since2011. Then total Zn load for the Kanayama Bay
3000 to 5000 kg per year and it is quite large Znload for the small bay with 100 m length and 50 m
width. Total Zn concentrations for the sea water inthe bay were 0.2 to 1.9 mg/l and soluble Zn
concentration with 0.45 filtered sea water were also
0.2 to 1.6 mg/l. Most Zn was soluble style and sea

2000

Spr i ng Zn ( kg/year )Zn( kg/year )Zn( mg/l )0
4/1/2014

4/1/2013

4/1/2012

4/1/2011

4/1/2009

0
4/1/2010

8

10000
8000

6

Zn( mg/l )
6000

4
4000
2

4/1/2014

4/1/2013

2000

4/1/2012

4/1/2009

0

Ri ver Zn( kg/year )Ri ver Zn( mg/l )Zn( kg/year )4/1/2011

0.013

2013/7/12
3
3.019
4.76
1.071
1.69
0.084
0.13

4/1/2010

0.328

drainage from adit

Spr i ng Zn ( mg/l )dateflow(l/min)
Cu(mg/l)Cu(kg/year)
Zn(mg/l)Zn(kg/year)
As(mg/l)As(kg/year)

spring atcoast
2013/7/12
0
9.377

0

Fig.2 and 3 Zn concentration and Zn load from
Spring and river in the Kanayama mine546

GEOMATE- Brisbane, Nov. 19-21, 2014

The relation between
concentration of seaweed

place

and

metal

105
104

1

Cu( mg/l )

25

10

0. 05

5

0

0

0. 02

40

4/1/2014

4/1/2013

0

4/1/2012

0

4/1/2011

20

4/1/2010

0. 01

Ri ver Cu ( kg/year )60

4/1/2009

Ri ver Cu ( mg/l )

0. 03

UP

UP
Spr i ng
Ri verKanyama bay→

S→ O SS NS SW WKWN H

1000

80
Cu( mg/l )10

Fig.7 shows Cu concentration of all sampled speciesof seaweed and placeCu( kg/year )
0. 04

100

0. 1

100

0. 05

S

→ O SS SN WS WKNW H

1

4/1/2014

0. 1

4/1/2013

15

4/1/2012

0. 15

4/1/2011

20

4/1/2010

0. 2

→

1000

As ( ppm) pl ant

0. 25

UP
Spr i ng
Ri verKanyama bay

104

Spr i ng Cu ( kg/year )30

UP

Fig.6 shows Zn concentration of all sampled
species of seaweed and place.

35

0. 3

4/1/2009

Spr i ng Cu ( mg/l )

0. 35

100
10

40
Cu( kg/year )1000

Cu ( ppm) pl ant

0. 4

Zn ( ppm) pl ant

Fig.6 shows Zn concentration of all sampled
species of seaweed under the dry weight conditiona n d p l a c e . I n t h e Ka n a ya m a B a y, m e t a lconcentrations depend on distance from spring andthe mouse of river and then sample points aredescribed by dist ance from spring and rivermouse. ”UP” is close to spring or river mouse. Right
direction from the “UP” shows far from spring. “O”
is just located at the outside of the Kanayama Bay.
“SS” and “SN” are south and north of Senjyo coast.
“WS” and “WK” are Saikasaki and Kada coasts inthe Wakayama city. “NW” is Nawachi coast. “SH”
is Shizuku mine coast. Zn concentration in seaweed
is extremely high in Kanayama Bay and reachedseveral % down the spring. The maximum value isthought to be world record in natural. River stream
area in the Kanayama Bay was also high. In the bay
Zn minimum valuesfor seaweed are 1000 ppm. Zn
concentration just outside of the bay also keeps
several 100 to several1000 ppm. South of Senjyo
coast is near the Kanayama Bay than North of

100

10

1

0. 1

UP

→ O SS SN WS WKNW SH

UP
Spr i ng
Ri verKanyama bay→

Fig.8 shows As concentration of all sampled speciesof seaweed and place
Senjyo coast. Zn concentration at south of Senjyo
coast is relatively high to north of Senjyo, Saikasaki,
Kada, and Nawachi. Zn concentration in the Shizuki
mine coast is wide variable and reached several100

Fig.4 and 5 Cu concentration and Cu load from
Spring and river in the Kanayama mine547

GEOMATE- Brisbane, Nov. 19-21, 2014

ppm. Zn concentration at the north of Senjyo is alsohigh relative to no contamination coast and thenSenjyo area is thought to be contaminated by
Kanayama mine drainage.
Fig.7 shows Cu concentration of all sampled
species of seaweed under the dry weight conditionand place. Cu concentration for seaweed at theShimizu mine shows wide range and varied fromseveral to 1000 ppm. Cu concentration of seaweedsampled at August and July 2013 in the Shizuki
mine showed high values and it shows seasonchanges. Cu contamination for seaweed was
remarkable for the Shizuki mine. Cu concentrationof seaweed in the Kanayama Bay is several toseveral 10 ppm and the same value as Senjyo andKada coasts. However, Cu concentration decreased
with distance from spring or river mouse to outside
104

1000

Pet al oni a bi nghami ae
Sar gassum t hunber gi i

1000
Cu ( ppm)

Cu ( ppm)

100

10

100
10
1

1

Ul val es
Cl adophor al es

0. 1
UP

UP
Spr i ng
Ri verKanyama bay

→

→

0. 1
Spr i ng

NSW
→ Ri ver→ O S N WS K W H

Kanyama bay
5

10

105

104
Zn ( ppm)

104
Zn ( ppm)

SS

UP

UP

S
O S N W WN SS S KWH

1000

1000
100

100
10

10

Ul val es
Cl adophor al es

1
UP
1000

UP
Spr i ng
Ri verKanyama bay→→

Pect al oni a bi nghami ae
Sar gassum t hunber gi i

1

SS

UP

UP

W WN SOS S
S NS KWH

Spr i ng

NSW
→ Ri ver→ O S N WS K W H

Kanyama bay
1000

As ( ppm)

As ( ppm)

100

10

100

10

1

Ul val es
Chl adophor al es

0. 1
UP

UP

Pect al oni a bi nghami ae
Sar gassum t hunber gi i
1

S

→ O SS N WS WKNW SH
Spr i ng→ Ri ver

UP

Kanyama bay

Fig.9 Cu, Zn and As concentration for green
seaweed(Ulvophyceae),
UlvalesandChladophorales.

UP
Spr i ng
Ri verKanyama bay

→

SS

NS

→ O S N SW KWW H

Fig.10 Cu, Zn and As concentration for brownseaweed (Phaeophyta), Pectalonia binghamiae andSargassum thunbergii.
548

GEOMATE- Brisbane, Nov. 19-21, 2014

Kanayama mine and the Shizuki mine and several
ppm at the no contamination places and at thedownstream of the river in the Kanayama mine.
Both Chladophorales and Ulvales were not effective
metal sensor for As because of narrow range
concentration.

of the bay. Cu contamination was found from Cu
concentration for seaweed in the Kanayama Bay. Cu
concentration of seaweed at the Kada and Senjyo in
the no contamination area were relative to high tothose at the Nawachi and Saikasaki coasts.
Fig.8 shows As concentration of all sampled
species of seaweed under the dry weight conditionand place. As concentration for seaweed in the
Kanayama mine with no As mineral is not highrelative to those sampled at another coast. As
concentration for seaweed at the Shimizu coastshows wide range and varied from several to 100
ppm. As concentration of seaweed sampled at Julyand August 2013 in the Shizuki mine showed highvalues and it shows season changes for As as well as
Cu. Muck from the Shizuki mine contains As
mineral and drainage water contain 0.0n mg/l for As.
Some samples shows high As values, however As
concentration for seaweed was variable and somesample shows low values. Therefore, Asconcentration was thought to depend on species.
Then, next, relationship between species and metal
concentration is shown.

105

Zn ( ppm)

104

1000
Caul acant hus
ust ul at us
Ahnf el t i opsi s
Fl abel l i f or mi s

100

10
UP

UP
Spr i ng
Ri verKanyama bay→

S→ O SS N WS WKNW SH

1000
Caul acant hus ust ul at us
Ahnf el t i opsi s Fl abel l i f or mi s
Cu ( ppm)

The relation between place and metal
concentration of green, red and brown seaweed
Fig.9 Cu, Zn and As concentration for green
seaweed(Ulvophyceae),
UlvalesandChladophorales. Ulvales and Chladophorales were
popular green seaweeds at the sampling place andthen effective candidate for a metal sensor covering
a wide habitat. Cu concentrations of Chladophorales
were uniform, 10 to 100 ppm under the different
places. Cu concentrations of Ulvales were several
100 ppm at the Shizuku mine, several 10 ppm at the
Kanayama mines and several ppm at the nocontamination places. Ulvales is effective metal
sensor for Cu because the concentration range was
100 times depending on the condition. Zn
concentrations of Ulvales and Chladophorales wereseveral 10000 ppm at the Kanayama mine andseveral 10 ppm at the no contamination places andthe Shizuki mine. Both green seaweeds were noteffective metal sensors for Zn because Shizuki mine
was thought to bring out Zn contamination but Znconcentration of seaweeds at the Shizuki mine waslow. As concentrations of Chladophorales werehigher than those of Ulvales. As concentrations ofChladophorales were uniform, several 10 ppm toseveral 100 ppm and As concentration for
Chladophorales of the Shizuki mine were notnecessary high values. As concentrations of Ulvales
were several 10 ppm at the downstream of spring in

100

10

1

SS

UP
Spr i ng

NS

UPW
→ Ri ver→ O S N WS K W H

Kanyama bay

1000
Caul acant hus ust ul at us
Ahnf el t i opsi s Fl abel l i f or mi s
As ( ppm)

100

10

1

0. 1
UP

UP
Spr i ng
Ri verKanyama bay→

S→ O SS N WS WKNW SH

Fig.11 Cu, Zn and As concentration for red
seaweed (Rhodophyta), Caulacanthus ustulatus andAhnfeltiopsis flabelliformis.
549

GEOMATE- Brisbane, Nov. 19-21, 2014

thunbergii is thought to be an effective seaweed for
As, Cu and Zn sensor.

Fig.10 Cu, Zn and As concentration for brownseaweed (Phaeophyta), Pectalonia binghamiae andSargassum thunbergii. They were popular brownseaweeds at the sampling place and then effective
candidate for a metal sensor. Cu concentrations of
Pectalonia binghamiae were uniform, several toseveral 10 ppm and not high at the Shizuki mine. Cu
concentration of Sargassum thunbergii at the
Shizuku mine were high relative to another area
having wide concentration range from 10 ppm toseveral 1000 ppm. Cu concentrations of Sargassum
thunbergii were 10 ppm at the the Kanayama mineand less than 10 ppm in the no contamination places.
Therefore, Sargassum thunbergii was thought to bean effective metal sensor for Cu. Zn concentration of
Pectalonia binghamiae were several 1000 ppm toseveral 10000 ppm at the Kanayama mine andseveral 10 ppm at the Shizuki mine and at the nocontamination places. Zn concentration ofSargassum thunbergii were several 1000 ppm at the
Kanayama mine, several 10 to several 100 ppm at
the Shizuki mine and several 10 ppm at the nocontamination places. Then, both brown seaweeds
were effective metal sensor for Zn. As concentration
sof Pectalonia binghamiae were uniform values,
however As concentration of Sargassum thunbergii
were over several 100 ppm at the Shizuki mine andseveral 10 to 100 ppm at the Kanayama mine and nocontamination places. Sargassum thunbergii wasthought to be effective metal sensor for As.
Fig.11 Cu, Zn and As concentration for red
seaweed (Rhodophyta), Caulacanthus ustulatus andAhnfeltiopsis flabelliformis. They were popular red
seaweeds at the sampling place and then effective
candidate for a metal sensor. Unfortunately
Ahnfeltiopsis flabelliformis can not be found in the
Shizuki mine however, another places, very
common. Cu concentrations of both the redseaweeds were high at the Kanayama mine and low
at the no contamination places. Cu concentrations of
Caulacanthus ustulatus was high, several 100 ppm.
Then, both the red seaweeds were thought to be aneffective metal sensor for Cu. Zn concentrations ofboth red seaweeds were several 1000 ppm to several
10000 ppm at the Kanayama mine and several 10
ppm at the Shizuki mine and at the no contamination
places. Then, both the red seaweeds were noteffective metal sensor for Zn. As concentration ofboth the red seaweeds were uniform values, several
ppm to several 10 ppm. Both the red seaweeds were
not effective metal sensor for As. Totally Sargassum

CONCLUSION
Kanayama mine was thought to be heavily Zn
and medium Cu contamination place. Shizuki mine
was thought to be heavy Cu and mediumum Zn andAs contamination place. Comparing Cu, Zn and As
concentrations for seaweed at the contamination andno contamination places, it was clarified whether
metal concentration of the seaweed depended or did
not on the contamination condition. As a result,brown seaweed, Sargassum thunbergii is thought tobe effective for As, Cu and Zn sensor. Ulvales,
Caulacanthus
ustulatus
and
Ahnfeltiopsis
flabelliformis are thought to be effective for just Cu
sensor.
REFERENCES[1] Lunde G, “Analysis of trace elements inseaweed”, J. of Sci. Fd. Argic., Vol. 21, Aug.
1970, pp. 416-418..
[2] Yamamoto T, and Ishibasi M, “The Content ofTrace Elements in Seaweeds”, in Proc. 7th Int.
Seaweed Symposium, 1971, pp. 511-514.
[3] 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.
[4] Hiyama Y and Shimizu M, “On theConcentration Factors of Radioactive Cs, Sr, Cd,
Zn and Ce in Marine Organisms”, Records ofOceanographic Works in Japan, Vol. 7, No.2,
March. 1964, pp. 43-77.
[5] Hiyama Y and Matsubara JK, “On theConcentration Factors of Radioactive I, Co, Fe
and Ru in Marine Organisms”, Records ofOceanographic Works in Japan, Vol. 7, No.2,
March. 1964, pp. 79-106.
[6] Ghada F El-Said and Amany El-Sikaily,“Chemical composition of some seaweed from
MediterraneanSeacoast,
Egypt”,
Environmental Monitoring and assessment, July
2013, Vol. 185, Issue7, pp 6089-6099[7] Alahverdi M and Savabieasfahani M, “Metal
Pollution in Seaweed and related Sediment of
the Persian Gulf, Iran”, Bull Environ. Contam.
Toxicol, Vol. 88, 2012, pp. 939-945.
[8] Griselda MRF, Evgueni S and Ignacio SR,“Heavy metal Pollution monitoring using thebrown seaweed Padina durvillaei in the coastalzone of the Santa Rosalia mining region, Bajacalfornia Peninsula, Mexico”, J. Appl. Phycol.,Vol. 21, 2009, pp. 19-26.

550

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

WATER BALANCE ANALYSIS CONSIDERING RUNOFF OFUNGAUGED CATCHMENTS IN IWAKI RIVER BASIN,NORTHERN JAPANSoichiro Kageyama1, Shingo Tomiyama2, Makoto Ikeda3 and Hiroyuki Ii4
Mitsubishi Materials Techno Corp., Japan, 2Mitsubishi Materials Corp., Japan,
4
Faculty of Systems Engineering, Wakayama University, Japan

1,3

ABSTRACTFor integrated and sustainable water resource management, it is essential to understand water balance of river
basin. Infiltration calculated by subtracting evapotranspiration and runoff from precipitation is a key factor for
groundwater resource development and is an important input data for three-dimensional groundwater flow
analysis. For estimation of runoff, it needs a great challenge to establish a method for runoff in ungauged
catchments, because gauging stations are usually set up in the limited main rivers. This paper focused on close
relation between topography and runoff. Then, the runoff of ungauged catchments in the Iwaki River Basin was
estimated by “runoff index” derived from results of geomorphometry and multivariate statistics using digital
elevation model data. Comparisons between runoff indices and measured runoff data, showed clear positive
correlations. This result proved that runoff index was useful for runoff estimation, and suggested that it waspossible to estimate runoff of ungauged catchments from runoff index by linear regression equation.
Keywords: Water Balance Analysis, DEM, Geomorphometry, Multivariate Statistics, PUB

Reference [5] classified catchments based on its
terrain feature values as well as quantitativeevaluation of terrain feature in each catchment bygeomorphometry and multivariate statistics using
digital elevation model (hereinafter, DEM) data.
Reference [6] performed the flow simulation basedon distributed runoff model using kinematic wave
equations after conducting catchment classification
using the same method. In addition, the authors
predicted the runoff of other basins that are a similar
terrain feature by applying the constructed flow
simulation model and examined its generality andvalidity. However, there was no study regarding therunoff estimation in catchments with different
terrain features. Against the background, Reference[7] focused on close relation between topography
and runoff, and suggested that it might be possible toestimate runoff of ungauged catchments by the“runoff index” based on a correlation between
terrain features and measured river flow data. This
paper is also predicated on same idea. Then therunoff of ungauged catchments in the Iwaki River
Basin, northern Japan were estimated by the “runoff
index” derived from the result of geomorphometry
and multivariate statistics using DEM data.

INTRODUCTION
For integrated and sustainable water resource
management, it is essential to understand waterbalance of river basin [1]. Water balance isexpressed simply by Eq. (1).

P= E+R+I(1)

Where; P is an amount of precipitation; E isevapotranspiration: R is runoff; and I is infiltration(groundwater recharge). Infiltration calculated bysubtracting evapotranspiration and runoff fromprecipitation is a key factor for groundwater
resource development and is an important input data
for three-dimensional groundwater flow analysis.
Therefore, it is very important that how accuracy
amounts of precipitation, evapotranspiration andrunoff are estimated. High precision precipitationand evapotranspiration distributions are easily
estimated for Japan because of recent progresses forclimate data (e.g., “1-km mesh climate data”
published by Japan Meteorological Agency [2]). On
the other hand, for estimation of runoff, it needs agreat challenge to establish a method for runoff inungauged catchments (Prediction in Ungauged
Basin: PUB), because gauging stations are usually
set up in the only limited main rivers. As existing
researches concerning PUB, while discussions witha focus on hydrology and civil engineering havebeen made [3], [4], new runoff estimation methods
from a topographic perspective have been proposed.

STUDY AREA
The Iwaki River basin is located in thenorthernmost part of Honshu, the main island ofJapan. The basin contains active volcanic regionswith high relief mountains, Mount Iwaki (1,624 m)
551

GEOMATE- Brisbane, Nov. 19-21, 2014

in the western part of the basin, Hakkoda Mountains(1,584 m) in the eastern part and Towada volcano in
the southeastern part. The Iwaki River is originatedin the mountainous area located on the margin partof the basin and flows through the alluvial fans andthe Tsugaru Plain to the Sea of Japan. This river hasa catchment area of 2,540 km2, with a length of 102
km. The study area located in the middle to upper
river basin is shown in Fig.1. This area also has
regional variations of climate and is suitable for
estimating an amount of infiltration on regional scaleby a water balance analysis.

Fig.1

To estimate monthly precipitation of August
2010, the comparison between the average monthly
value for the 30 past years and observed monthly
values of August 2010 of 32 weather observation
stations located in and near the study area wascarried out. In this study, after calculating ratio of
average and observed values in each station wasderived as a correlation coefficient value for
estimation, the correlation coefficient value map of
the study area was drawn by interpolatingcorrelation coefficient values of each station by
Kriging method. Then, the precipitation distributionof August 2010 was estimated by multiplying the
average monthly precipitation map of the mesh databy the correlation coefficient value map. The resultof estimation is shown in Fig.2.

Location map of the study area. The blackborder in the map denotes the study areaand black circles respectively denote theweather observation stations.
Fig.2

WATER BALANCE ANALYSIS
The water balance analysis performed in thisstudy consists of four items, (1) precipitation
estimation using 1-km mesh climate data, (2)evapotranspiration estimation in consideration ofland cover using 1-km mesh climate data, (3) runoff
estimation by geomorphometry and multivariate
statistics using DEM data and (4) infiltration
estimation by water balance analysis. As for (3)runoff estimation and (4) infiltration estimation, theduration of estimation is taken as one month ofAugust 2010 due to the river flow data applied to
the runoff estimation was measured between 8th to10th August 2010 in the study area.

Result of precipitation estimation of August
2008.

Estimation of Evapotranspiration
The evapotranspiration of the study area wasestimated by Makkink equation considering albedo
of each land cover class [8] shown in Eq. (2).

∆ RS
+b
∆+γ L
∆
1
=
∆ + γ 1.05 + 1.4 × exp(−0.0604T )E = (a + 0.05 − α )(2)Where; E is daily evapotranspiration; a and b are
regional constant value (a is 0.87 and b is 0.30 in the
study area [8]); alpha is albedo value of each land
cover class; DELTA is slope of saturation vapor
pressure curve; lambda is psychrometric constant;
R S is total solar radiation; L is latent heat. T istemperature. Distributions of average monthly total
solar radiation, latent heat and temperature for the 30
past years could be calculated by temperature andsunshine hours of 1-km mesh climate data, and theEstimation of Precipitation
In Japan, the 1-km mesh climate data including
average monthly precipitation, temperature andsunshine hours for the past 30 years between 1981
and 2010 is established. The mesh data is estimatedby the climate data of about 1,100 weather
observation stations of the country, which considers
topographical and urban effects on climate.
552

GEOMATE- Brisbane, Nov. 19-21, 2014

distributions of August 2010 were estimated by thesame method for precipitation estimation. As an
albedo value, values of each land use class estimated[9] were adopted. The result of estimation by
Makkink equation is shown in Fig.3.

Fig.3

estimation, a “sub-catchment” is defined as a basic
unit for estimation. The study area was subdivided
automatically into 469 sub-catchments and plains byhydrologic analysis using DEM data. The result ofdivision is shown in Fig.5.

Result of evapotranspiration estimation ofAugust 2008.

Result of sub-catchment division. The blacksmall borders in the map respectively
denote the extracted 469 sub-catchments.

Fig.5

Estimation of Runoff
Geomorphometry
Focusing on terrain that is closely related torunoff, runoff of ungauged catchments wasestimated by comparison examination between
terrain features and measured river flow data. The
flow chart of runoff estimation is shown in Fig.4.

The items of geomorphometry calculated at each
sub-catchment are as follows:“Average erosion height” calculated by Eq. (3)can be used as a factor of surface relief.
nHe = ∑ Esi − Ei

(3)i

Where; He is average erosion height of a certain
sub-catchment; n is number of pixels; Es i is anelevation of a summit plane of a certain pixel; E i isan elevation of a certain pixel. Laplacian of anelevation is defined as a derivation value of gradientand its differences show a grade of surface relief.
Laplacian is calculated by Eq. (4).

L( m,n ) = E ( m −1,n ) + E ( m +1,n ) + E ( m,n −1)+ E ( m,n +1) − 4 × E ( m,n )(4)

Where L (m, n) is laplacian of an elevation of a
pixel (m, n). In addition, a “standard deviation oflaplacian” calculated by Eq. (5) is used to evaluate
surface texture.
Fig.4

Flow chart of runoff estimationnDivision of sub-catchment

Sxlaplacian =When applying geomorphometry and runoff
553∑ ( L − L)
i =1

i

n

(5)

GEOMATE- Brisbane, Nov. 19-21, 2014

Where; Sx laplacian is a standard deviation oflaplacian of a certain sub-catchment; L i is laplacianof an elevation of a certain pixel; L is mean laplacianof a certain sub-catchment. “Drainage relief number”
is defined as average slope of a certain subcatchment and is calculated by Eq. (6).

Dr =

V
A1.5

In order to compile the results of each item andevaluate the runoff of the study area, principle
component analysis (hereinafter, PCA) was
conducted. The result of PCA is shown in Table 1.
In this study, four principal components of the first(hereinafter, PC 1) to the fourth (hereinafter, PC 4)
with eigenvalue of more than 1.00 were considered
for the examinations. In other words, the terrain
feature of the study area is characteristically
represented by these four PCs. PC 1 has clearlyhigher loadings of average erosion height (0.96),
standard deviation of laplacian (0.91) and drainage
relief number (0.73) compared with those of otheritems. Since these items are related to relief ofterrain, PC 1 is considered to be a factor
representing “steepness of terrain”. Equally, PC 2,
PC 3 and PC 4 are considered to be respectively
representing “a shape of sub-catchment and mainstream”, “deformation of sub-catchment” and“growth of low-order drainages”.

(6)

Where; Dr is average erosion height of a certain
sub-catchment; V is volume of a certain subcatchment; A is area of a certain sub-catchment. A“drainage frequency” calculated by Eq. (7) is used toevaluate a drainage network of a certain subcatchment quantitatively.
Ω

Nω
ω AΩ

Fd = ∑(7)

Table 1 Result of the PCA
Where; Fd is a drainage frequency of a certain
sub-catchment; Nω is number of ωth order streams;
Ω is maximum number of drainage order; A is areaof sub-catchment. “Bifurcation ratio of 1st and 2ndorder streams” is calculated by dividing number ofpixels of 1st order stream by number of pixels of 2ndorder stream of a certain sub-catchment.
“Drainage form ratio” calculated by Eq. (8),represents length of a main stream against area of
sub-catchment.

Rl =( Pmax ) 2
A

PC
1
2
3
4
5
6
7
8
9

(8)
Items

Where; Rl is drainage form ratio of a certain subcatchment; P max is maximum distance of drainagesof a certain sub-catchment; A is area of a certain
sub-catchment. “Basin form ratio” calculated by Eq.
(9) is used to evaluate a shape of a certain subcatchment.

Rf =( Lmax ) 2
AEigenvalue
2.40
2.12
1.40
1.01
0.90
0.62
0.35
0.14
0.07

Ave. Erosion HighSD of Laplacian
Drainage Relief No.
Drainage Freq.
Bif. Ratio (1/2)
Drainage Form R.
Basin Form R.
Kurtosis
Skewness(9)

Where; Rf is basin form ratio of a certain subcatchment; L max is maximum width of a certain subcatchment; A is area of a certain sub-catchment. In
general, “kurtosis” and “skewness” are indexes
shown as a deviation of distribution data fromGaussian distribution in a field of statistical analysis.
In this study, both items were used for measuring ashape and deformation of a certain sub-catchment.

PC 1
0.96
0.91
0.73
0.03
-0.06
-0.08
0.12
0.03
-0.08

Contribution Ratio
26.7
23.6
15.5
11.2
10.0
6.9
3.9
1.5
0.8
Loading
PC 2 PC 3-0.12 -0.05
-0.22
0.06
0.44 -0.15
0.73 -0.17-0.06 -0.03
0.79
0.44
-0.79
0.13
-0.23
0.76
0.07
0.77

PC 4
-0.06
-0.09
0.13
0.10
0.87
-0.05
0.29
0.37
-0.26

Measurement of River Flow
To obtain actual measured runoff data applied torunoff estimation, river flow measurement was
carried out between from 8th and 10th August 2008 in
6 sub-catchments have area of 5.94 to 16.74 km2.
The river flow measured by a propeller current
meter at the mouth of each catchment ranged from0.08 to 0.50 m3/s. In this study, “runoff ratio” wasadopted as measured runoff data for considering
difference of river flow depending on area of eachPrinciple component analysis

554

GEOMATE- Brisbane, Nov. 19-21, 2014

sub-catchment. Runoff ratio of a certain subcatchment is calculated by dividing an amount ofriver flow by an amount of precipitation during a
specific period. The calculated runoff ratio of 6 subcatchments ranged from 0.13 to 0.54.

Where; C PCx is contribution ratio in PC x in
Table 1. Then, the runoff index map of the study
area is shown in Fig.6. In the map, the subcatchments with high runoff index are presented bybright colors and ones with the low runoff index are
shown as dark colors. Moreover, the comparison
between the runoff index and the runoff ratio of 6
measured sub-catchments is shown in Fig.7. The
result of comparison shows that the runoff index has
a strong positive correlation (R2 = 0.71) with therunoff ratio. This result proves the validity of runoff
index, and it suggests that the runoff index can beconverted to the runoff ratio by using the regression
equation of Fig.7.

Runoff Index
To understand relationship between the terrain
features and the river flow data of the study area, thecomparison between the principle component score(hereinafter, PC score) which shows the topographic
features quantitatively and the runoff ratios of 6
measured sub-catchments was conducted. As theresult of the comparison, it became obvious that thePC 1 had a strong positive correlation (R2 = 0.75)
with the runoff ratio, and PC 4 had a positive
correlation (R2 = 0.29) with the runoff ratio. As thePC 1 represents “steepness of terrain”, a subcatchment with a high PC score shows a steep
sloping terrain and a sub-catchment with a low PCscore shows a gently sloping landscape. In general,
steepness is related to stream velocity; an increase ofsteepness is connected to an increase of river flow
and a decrease of it is connected to a decrease ofriver flow. Therefore, concerning the PC 1, subcatchments of higher PC score can be considered as
more discharged water in the stream. On the other
hand, as the PC 4 represents “growth of low-orderdrainage”, valleys are developed on a slope of a subcatchment with a high PC score and valleys arepoorly developed on a slope of a sub-catchment witha low PC score. As a slope with many valleys cancollect more surface water, sub-catchments of higher
PC score can be considered as more discharged
water in the stream.
As the result of above discussion, it became
obvious that the runoff ratio and the increasedecrease rate of river flow were related to terrain
features (“steepness of terrain” and “growth of loworder drainage”) in the study area. Therefore, itsuggests that the runoff ratio and river flow of thestudy area can be estimated by evaluating the PC
scores which show two terrain features as above. In
this study, the “Runoff Index” [7] was calculated as
the indicator of river flow on the basis of PC scoresof PC 1 and PC 4, and the runoff index was
calculated by Eq. (10).

RI = S PC1 × WPC1 + S PC 4 × W PC 4

WPC 4 = C PC 4 ÷ (C PC1 + C PC 4 )Result of runoff index estimation. The
black triangles in the map respectively
denote the measuring points of 6 subcatchments. The black quadrangle denotes
Kuzukawa Gauging Station and the blackborder denotes its catchment.

Fig.7

Result of comparison between the runoff
index and the runoff ratio of six measured
sub-catchments.

(10)

Where; RI is runoff index; S PCx is a PC score in
PC x; W PCx is weighting of PC x. Weightings ofeach PC were calculated by Eq. (11).

WPC1 = C PC1 ÷ (C PC1 + C PC 4 )Fig.6

Prediction of Runoff(11)

The estimated equation of runoff ratio and river
flow is shown in Eq. (12).
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GEOMATE- Brisbane, Nov. 19-21, 2014

RRATIO _ SC = RINDEX _ SC × 0.104 − 0.0011
RSC = RRATIO _ SC × PSC

CONCLUSION(12)While the runoff of ungauged catchments in the
Iwaki River Basin was estimated by the runoff index
derived from geomorphometry and multivariate
statistics, the infiltration estimation was carried out
by water balance analysis. Comparisons between
runoff indices and measured runoff data, showed
clear positive correlations. This result suggested that
it was possible to estimate runoff of ungauged
catchments from runoff index by linear regression
equation. Moreover, the result of verification withrelatively high precision also indicates that thepresent method could be generally applied to therunoff estimation.

Where; R RATIO_SC is estimated runoff ratio of acertain sub-catchment; R INDEX_SC is runoff index; R SC
is estimated river flow; P SC is estimated
precipitation. By applying the above estimation
method, the runoff of sub-catchments only could be
estimated. Concerning planes except for subcatchments, it would be appear that land use
contributes runoff of it in comparison to terrain
feature. Therefore, the runoff of planes could be
estimated by multiplying precipitation by known
runoff ratios of each land use (e. g., farm: 0.1, forest:
0.2, paddy field: 0.4, urban area: 0.8, water area:
1.0).

REFERENCES[1] Matsuyama H, Oki T, Masuda M, The seasonalchange of the water budget in the Congo River
Basin, J. of Meteorological Society of Japan,
Vol. 72-2, 1994, pp. 281-299.
[2] Japan Meteorological Agency, 1-km meshclimate data, 2012, Japan MeteorologicalBusiness Support Center.
[3] Tachikawa Y, Sayama T, Takara K, Matsuura H,
Yamazaki T, Yamaji A, Michihiro Y,
Development of real-time runoff forecasting
system using a physically-based distributedhydrologic model and its application to the
Yodo River basin, J. of Japan Society for
Natural Disaster Science, Vol. 26-2, 2007, pp.
189-201[4] Sayama T, Tachikawa Y, Takara K, Dataassimilation of a distributed rainfall-runoff
prediction system by Kalman filter with bias
correction, J. of Japan Society of Civil
Engineers, Vol. 64-4, 2008, pp. 226-239.
[5] Nakayama D, A study of DEM-based drainage
basin classification, Geographical Review ofJapan Ser. A, Vol. 71-3, 1998, pp. 169-186.
[6] Sakuma S, Nakayama D, Matsuyama H,
Estimation of discharge in ungauged basin using
comparative hydrological approach anddistributed runoff model, in Proc. of the General
Meeting of the Association of Japanese
Geographers, Vol. 69, 2006, pp. 239.
[7] Kageyama S, Ikeda M, Tomiyama S, Water
balance analysis considering runoff of ungauged
basin in Shimokawa area, Hokkaido, J. Japan
Soc. Hydrology and Water Resources, 2010,
Vol. 23-4, pp.
[8] Nagai A, Estimation of evaporation with ameasuring instrument of Makkink type, J. Japan
Soc. Hydrology and Water Resources, 1993,
Vol. 6-3, pp. 238-243.
[9] Kotoda K, Estimation of river basin
evapotranspiration, Environmental Research
Venter Papers, University of Tsukuba,
1986, Vol. 8, pp. 1-92.

Verification of Estimated Runoff
To verify the result of runoff estimation, thecomparison between estimated runoff and observed
runoff at Kuzukawa Gauging Station located in thesoutheastern part of the study area (Fig.6) was
performed. The amount of estimated runoff for threedays from 8th August 2008 is 402,113 m3 and it is90.2 % based on the observed runoff of 445,836 m3.
The comparison result suggests that the present
method could be generally applied to the runoff
estimation due to it could be estimated the runoff
with relatively high precision.
Estimation of Infiltration
Infiltration could be calculated by subtracting
estimated evapotranspiration and runoff fromprecipitation. The result of infiltration estimation in
August 2008 is shown in Fig.8. The amount of
estimated infiltration ranged from about 0.1 mm/day
to 9.6 mm/day. Verification of estimated infiltration
will be carried out by three-dimensional
groundwater flow analysis in the study area in future.

Fig.8 Result of infiltration estimation.

556

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

REMOVAL OF CESIUM FROM SEA SLUDGE THROUGHDECOMPOSITION OF ORGANIC MATTER WITH AQUEOUS
HYDROGEN PEROXIDEHirosuke Hirano1, Takeshi Toyama2, Nobuyuki Nishimiya3 and Kyoichi Okamoto4
1

Graduate School of Science and Engineering, Nihon University, Japan
2,3,4
College of Science and Engineering, Nihon University, Japan

ABSTRACT: The radioactive cesium scattered from the Fukushima Nuclear Power Plant has caused apollution problem in Japan. To tackle such accidents, many technologies have been developed to remove
radioactive cesium from water. However, the technology to decontaminate the sludge is much less advanced thanthat for water. Thus, we focus on the decomposition of organic matter by H2O2 for decontaminating the sludge.
The maximum decontamination of the sea sludge by H2O2 was found to be 2.6 times higher than that by water
alone, and the greatest decontamination was obtained using 34.5% H2O2. We believe the extent of
decontamination increased for this solution because the solution pH was near the pHpzc, which would suppress
the ability of the sludge to absorb Cs ions. We also examined the effect of time on the decontamination of the sea
sludge; however, only a small increase in decontamination (1.7 times the initial value) was observed.
Keywords: Cesium, Decontamination, Hydrogen peroxide, Water area

1000 ppm of nonradioactive cesium nitrate (CsNO3).
This is the same cesium isotope as the radioactive
cesium that is the object of the present
decontamination study. As shown in Figure 1, theadsorptivity of the sea sludge for Cs+ in water was
found to be 65.1%, and this adsorption occurred
instantaneously. Moreover, the properties of thehydroxide groups in the sea sludge are changed atcertain pH values. At low pH values, the hydroxidegroups are protonated as OH2+. As a result, we
assumed the adsorptivity of the sea sludge forcations would decrease. The pH value where thiseffect occurs is called the isoelectric point (point ofzero charge; pHpzc). We assumed that the pH of thesolution would affect the decontamination.

1. INTRODUCTION
In 2011, the Fukushima Nuclear Power Plant wasdestroyed by a tsunami. Radioactive cesium wasreleased across a wide area, contaminating soil andwater. As a result, cesium was even found to bepresent in the sea sludge at the bottom of Tokyo Bay
in concentrations that are 1.5–13 times the
background level [1].
To recover from this accident, methods toremove radioactive cesium from the sea sludge areneeded. There are fewer reports on thedecontamination of the sea sludge than on thedecontamination from water. In addition, themethods of decontaminating water cannot be simply
applied to decontaminate the sea sludge. For
example, iron ferrocyanide has been reported toremove Cs+ from water; however, highconcentrations of cyanide accumulated in the sludge
when this method was used. Therefore, this methodof decontaminating the sludge requires an additional
decontamination step for the removal of cyanide [2].
Therefore, in the present study, we have studied
easier methods of decontaminating the sea sludge.

2. PURPOSE OF STUDY
In the present study, we focused on using

Adsorption of Cs+ [%]100

1.1 Characteristics of Sea Sludge
The sea sludge absorbs cesium and ironferrocyanide because of the clay minerals containedin the sea sludge [2]. Clay minerals containhydroxide groups that can coordinate cations such as
Cs+ and Fe3+. We examined the adsorptivity of thesea sludge for Cs+ ions. A 10 g of the sea sludge
sample was mixed with 20 mL of water containing

80
60
40
20
0
0

12
18
Time [h]Fig. 1 Adsorption of Cs+ by sea sludge
557

6

24

GEOMATE- Brisbane, Nov. 19-21, 2014

with a concentration of 0%–34.5%. A powder
sample was then made by filtration and drying, andthe organic matter content was measured bythermogravimetry (TG) and sulfide content wasdetermined by energy dispersive X-ray spectrometry(EDX). To compare the organic matter content, thedifference in the values at 100 °C when water in thesample evaporated and 600 °C when the organic
matter is burnt off was used. To compare the sulfide
content, the ratio of sulfide in the sea sludge tosilicon dioxide (SiO2) in the sea sludge was used.
This ratio was chosen because the content of SiO2 inthe sea sludge is not greatly affected by H2O2.
The change in organic matter content is shown in
Figure 2. The organic matter content was found to
decrease as the H2O2 concentration increased. The
sulfide concentration, determined as the change in
the S/Si ratio, was lower for all H2O2 concentrations
studies compared with the value for 0%, as shown in
Figure 3.
These results indicated that purification of thesea sludge by H2O2 occurs, and was similar to thatobserved with micro-bubbles. This result indicatesthat H2O2 could potentially be used to remove
cesium from the sea sludge; thus, thedecontamination ability of H2O2 was determined in
the next experiment.

hydroxyl radicals as a new way to decontaminate thesludge. This idea was originated from a previous
study in which Cs+ was removed from the sea sludge,
with cleaning sulfide (S) and reducing total nitrogen(T-N) by using hydroxyl radicals in micro-bubbles[3].
The authors proposed that the origin of thisdecontamination effect was the decomposition oforganic matter by hydroxyl radicals or thedecomposition of organic matter by aerobic
microorganisms that were activated by the microbubbles. Therefore, the authors attempted
decontamination using anaerobic microorganisms
with the same decomposition performance as
aerobic microorganisms. However, decontaminationof the sea sludge by activation of anaerobic
microorganisms could not be confirmed. From thisresult, the authors concluded that anaerobic
conditions were not suitable for removal of cesium
and that decontamination was most effective inaerobic conditions. In addition, the authors
suggested hydroxyl radicals have shown adecomposition performance that is suitable fordecontamination of the sea sludge [4].
In the present study, we studied thedecontamination of the sea sludge by hydroxyl
radicals. To obtain hydroxyl radicals easily andsafely, we suggested using hydrogen peroxide(H2O2). H2O2 was chosen for two reasons: (i) no
equipment, such as micro-bubbles, is required, and(ii) the decontamination ability can easily becompared to the change of H2O2 concentration. We
examined the potential of hydroxyl radicals to
decontaminate the sea sludge by varying theconcentration of H2O2 and the stirring time.

3.2 Decontamination of Sea Sludge by H2O2
The changes in the extent of decontamination
using H2O2 were studied by varying the H2O2
concentration and the stirring time. Samples wereliquids obtained by filtration and the Cs+
concentrations were determined. Each 10 g sea
sludge sample was mixed with a 20 mL solution of
H2O2 and CsNO3. The concentration of H2O2 was
0%–34.5%. The concentration of CsNO3 was 500–
2000 ppm in the experiment where the cesium
concentration was varied, and was fixed at 1000
ppm in the experiment where the stirring time wasvaried. The Cs+ concentration and pH in the liquidsamples were measured using ion chromatography
and a pH meter, respectively.

3. RESULTS AND DISCUSSION
3.1 Purification of Sea Sludge by H2O2

30

0.3

20

0.2

S/Si [-]

Organic matter content
in sea sludge [%]First of all the ability of H2O2 to purify the sea
sludge was examined. A 10 g sea sludge sample
collect ed from t he Funabashi port in Chiba
prefecture was mixed with 20 mL of aqueous H2O2

10

0
0

0.1

15 20 25 30
H2O2 [%]
Fig. 2 Change of organic matter content
5

10

0
0

35

558

5

10

15 20 25
H2O2 [%]
Fig. 3 Change of values in S/Si

30

35

GEOMATE- Brisbane, Nov. 19-21, 2014

3.3 Effect of H2O2 Concentration on Sea Sludge
Decontamination

3.4 Effect of Stirring Time on Sea Sludge
Decontamination

The ability of varied concentrations of H2O2 todecontaminate the sludge that contained CsNO3 was
examined. The dissolved Cs+ concentrations in theliquid phases at different H2O2 concentrations areshown in Figure 4. The concentration of Cs+ in theliquid phase substantially leveled when theemployed H2O2 did not exceed 17.3% H2O2. The
amount of Cs+ determined in 34.5% H2O2 was muchgreater than the ones in the other conditions. By
dividing the measured values by the value for 0%
H2O2, normalized curves were obtained as shown in
Figure 5. A similar trend with H2O2 concentration isobserved for all three initial CsNO3 concentrations,which indicates that the decontamination of the sea
sludge by H2O2 was similarly effective undervarious conditions.
The pH values measured for these solutions areshown in Figure 6. The pH values decreased withincreasing H2O2 concentration and were lowest for
34.5% H2O2. As the extent of decontamination was
greatest for 34.5% H2O2, it is suggested that thepHpzc value of the sea sludge is between 3.6 and 4.1
in the present study.

Decontamination results obtained at various
H2O2 concentrations (0%–34.5%) and various
stirring times (0–24 h) were normalized by dividing
the measured values by the value for 0 h stirring as
shown in Figure 7. The values obtained for 34.5%
H2O2 did not change significantly with stirring time.
However, the other concentrations of H2O2 showed
peaks in the graph. These peaks were observed at 18h, 12 h and 6 h for 17.3%, 8.6% and 3.5% H2O2,
respectively. These results indicated that thedecontamination of the sludge by H2O2 did notchange significantly with time. The peak value wasonly 1.5 times the 0 hour concentration for 17.3%
H2O2 and only 1.7 times the 0 hour concentration for
8.6% H2O2. From these results, it is not likely thatthe decontamination effects would be enhanced
through prolonged stirring.
3.5 Discussion
We have demonstrated the ability of H2O2 toelute Cs+ from the sea sludge to water. It will bepossible to remove Cs+ from water, using the latest
Cs+
Measured value / First value [-]△: 2000 ppm● : 1000 ppm□: 500 ppm

1000

500

0
0

5

15 20 25 30 35
H2O2 [%]
Fig. 4 Removal of Cs+ from sea sludge by H2O2

14

pH [-]△: 2000 ppm● : 1000 ppm□: 500 ppm

7

0
0

5

10

15 20 25 30
H2O2 [%]
Fig. 6 Change of pH in liquid phase

3

2

1

0
0

△: 2000 ppm● : 1000 ppm□: 500 ppm

510

15 20 25 30 35
H2O2 [%]
Fig. 5 Normalized removal of Cs+ from sea sludgeby H2O2

10

35

559

Cs+
Measured value / First value [-]Cs+ ion [ppm]

1500

2

1
● : 34.5% ○: 17.3%▲: 8.6% △: 3.5%□: 0.0%

0
0

6

12
18
Time [h]Fig. 7 Change of decontamination with time24

GEOMATE- Brisbane, Nov. 19-21, 2014decontamination technology, which is currently
progressing [6]. From these facts, it will be possible
to clean an entire body of water by combining these
two technologies for decontamination of the sea
sludge and water.

[3] Okamoto
K,ToyamaT,“Oceandecontamination: Elution of radiological cesium
from ocean sludge by using micro bubble andactivating microorganisms”, in The 16th Japan
Society of Naval Architects and Ocean Engineers,
2103, pp. 257-258.
[4] Hirano H, Nishimiya N, Kojima Y, Toyama T,
Umegaki T, Okamoto K, “Investigation ofradioactive cesium decontamination from sea
sludge using microbial activity”, in The
International Symposium on Inorganic andEnvironmental Materials 2013, 2013.
[5] Yonekura N, Oomori T, Koyanagi M,“Coagulation-sedimentation rates of red soil
colloids”, Bull. of the College of Science,
University of the Ryukyus, Vol. 79, 2005, pp.
103-109.
[6] Sano M, Nakagawa K, Oda H, Obata H, Kitani S,
Yamazaki K, “Fundamental study for thedevelopment of Cs removal technique from low
levelradioactive
liquidwastesofdecontamination processes”, The Society ofChemical Engineers, 2014.
[7] Momonoi K, “The relationship between specificresistance, pH and S-potential on the chemicaltreatment of sludges”, Bull. of Nagaoka
University of Technology, 1981, pp. 47-52.
[8] Yoshida T, “About generation and the removalof the sludge - In bottom sampler examination of
the Gulf of Minamata”, HEDORO, No. 1, 1974,
pp. 11–27.
[9] Hibino T, Matsumoto H, “Distribution of fluid
mud layer in Hiroshima Bay and its seasonalvariation”, J. of JSCE, B, Vol. 62, 2006, pp. 348359.

4. CONCLUSION
The removal of Cs+ from the sea sludge by H2O2
was evidenced, and a concentration of 34.5% H2O2
was found to realize the highest extent of
decontamination. In addition, the 34.5% H2O2
sample had the lowest pH value. Therefore, it islikely that the pH value in 34.5% H2O2 was less thanor equal to the pHpzc value of the sea sludge andthat the adsorptivity of the sea sludge for Cs+
decreased at that low pH value to enhance thedecontamination effect.
Decontamination of the sea sludge by H2O2 overtime was constant for 34.5% H2O2, whereas an
upward trend of decontamination was observed for
17.3% and 8.6% H2O2. However, these values were
only 1.5–1.7 times the 0 hour value. The increase in
the decontamination ability with time is not large,
and decontamination by H2O2 can be considered
substantially instantaneous.
5. REFERENCES[1] Yomiuri Shimbun, “Cesium in Tokyo Bay's mud
is 13 times higher than 7 months ago”, Yomiuri
Shimbun, 14th May 2012.
[2] Aritomi M, Adachi T, Hosobuchi S, Watanabe N,“Decontamination technology of contaminatedwater with flocculating and settling technology”,
J. of Power and Energy Systems, Vol. 6, 2012,
pp. 412-422.

560

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

THE EFFECT OF SUMATRA FAULT EARTHQUAKES ON WEST
MALAYSIA
Noushin Naraghi Araghi1, Mohd. Nawawi2, Syed Mustafizur Rahman3 and Rosli Saad4
1,2,4
School of Physics, University Science Malaysia
3
Department of Applied Physics and Electronic Engineering,University of Rajshahi
ABSTRACTThis paper presents the effect of Sumatra fault earthquakes on west Malaysia by calculating the peak horizontal
ground acceleration (PGA). PGA is calculated by a probabilistic seismic hazard assessment (PSHA). A uniform
catalogue of earthquakes for the interest region has been provided. We used empirical relations to convert all
magnitudes to Moment Magnitude. After eliminating foreshocks and aftershocks in order to achieve reliable
results, the completeness of the catalogue and uncertainty of magnitudes have been estimated and seismicity
parameters were calculated. Our seismic source model considers the Sumatran strike slip fault that is known
historically to generate large earthquakes. The calculations were done using the logic tree method and four
attenuation relationships and slip rates for different part of this fault. Seismic hazard assessment carried out for
48 grid points. Eventually, two seismic hazard maps based PGA for 5% and 10% probability of exceedance in
50 year are presented. .

Keywords: PSHA, Sumatra fault, PGA, seismic parameters

INTRODUCTION
Although Malaysia is situated on a stable partof the world, earthquakes in Sumatra effectbuildings specially on soft soil area in Malaysia as
they have been felt some times specially in highbuildings in some part of Malaysia and Singapore[1].
The seismic waves from Sumatra travel long
distance to arrive Malaysia bedrock. Normally thehigh frequency seismic waves damp quickly but low
frequency (long period) seismic waves are stronger
to energy dissipation and they are able to travel long
distances (Fig. 1). Therefore long period waves are
considerably amplified as they reach the bedrock of
Malaysia, these waves can make resonance instructures with a natural period near the period of thesite, and make the large motions [2].
Recently numerous studies are already carriedout to determine whether these types of movements
could make damage to buildings [3], [4], [5], [6].

Fig. 2 Major tectonic plates around Malaysia

EARTHQUAKE SOURCE MODELSTECTONIC SETTING OF MALAYSIASoutheast Asia is a region of variableseismic hazard, ranging from high seismic
hazard associated with the subduction process
beneath the Indonesian and Philippine archipelagos
to moderately low seismic hazard across a large
stable region that contains the Malaysian
peninsular.
Regarding the historical evidences, west of
Malaysia is influenced by earthquakes from two
major faults [9], The Sumatran strike slip fault andSumatran subduction zone.

Malaysia is situated near two seismically active
plates. In the west, Indian Ocean plate moves
northeast and subducts under the Sumatra with theestimated velocity of 7 cm/year. This movement
produces a great Sumatran fault (Fig. 2).
The Sumatran fault is segmented into 20 parts [7].
From geodetic measurement, each segment has
different velocity. The northern segments havehigher velocity than the south part (3.7 cm/year and2cm/year, respectively) [8].
561GEOMATE- Brisbane, Nov. 19-21, 2014

SUMATRAN SUBDUCTION ZONE
Subduction of the India-Australian plate beneaththe Eurasian plate has produced the Sumatransubduction zone with the slip rate of about 67mm
per year. The nearest place of this subduction
zone is about 400km to coast of west Malaysia[10]. In this zone, most of the earthquakes areshallow. Historical records show four significant
events in the last 300 years (Fig. 3).

Fig.4 Principal active traces of the Sumatran fault zone

EARTHQUAKE DATA
Earthquake catalogs are used to estimate future
seismic activity from the locations and rates of pastearthquakes.
From the locations and frequency-magnitude
distributions of past earthquakes we can estimate thelocations and rates of future larger shocks that
dominate the hazard. For this study we compiledanewcatalogof instrumentally recorded
earthquakes by combining different catalogues. We
used the data from the United States Geological
Survey (USGS), the International SeismologicalCentre (ISC) and the local data in Malaysia (Fig. 5)[11].

Fig. 3 The Great Sumatran fault zone

SUMATRAN STRIKE SLIP FAULTThe Sumatran fault runs from beginning to end of
the whole length of Sumatra with a length more than
1500km. large historical events with Mw 5.2 and 7.7
are originated from this fault. The closest distancefrom earthquake source in this fault to the coast ofWest Malaysia is about 260km. Sumatran fault isdevided into 20 major sections including Batee fault.M max and slip rates calculated for each part of thisfault(Fig. 4). We will consider the effect of events
caused by this fault on Malaysia [7], [10].

562GEOMATE- Brisbane, Nov. 19-21, 2014

Table 1. Seismic hazard analysis for study area.

Seismic
Parameters

M
c

M max

λ

avalueb-value

Value

4.6

7.8

1.17

8.43

1.1±0.04

ATTENUATION RELATIONS ANDANALYSIS
We used 48 grid points within the study area forseismic hazard assessment (Fig. 6). Quantification ofground motion is important to understand the
behavior of any site during an earthquake.
Attenuation models are used to predict theprobability distribution of ground-shaking intensity,
as a function of variables including earthquake
magnitude, distance from the site, the faulting
mechanism, and near surface site conditions. In thepresent study, four attenuation relationships werechosen for analysis.

Fig. 5 Seismic events with moment magnitudes larger than
5.0

EARTHQUAKE RISK ANALYSIS
A homogeneous earthquake catalogue is required
for seismicity analysis. As known, moment
magnitude (M w ) does not saturate for large
earthquakes and we will use M w for our analysis. To
compile a homogeneous earthquake catalog,
different magnitudes types like body wave
magnitude (mb ) and surface wave magnitude (M S ),are converted into M w using the regression relations
derived based on global data [12].
The event list was homogenized and moment
magnitude, M w was applied in our assessment.
Completeness of the catalogue is essential.
Obviously, an incomplete catalogue could
substantially modify the b-values. The fractions of
missing small events would result in a reduction ofb-value.
Magnitude of completeness (Mc) is thesmallest amount magnitude and higher than thismagnitude, all earthquakes are recorded. Mc can beevaluated from the observed frequency magnitude
distribution. Mc is someplace that the frequency–
magnitude curve begins to digress from a linear
trend [13]. The event list would be complete foramount of bigger than Mc. [14]. In this study M c
was calculated around 4.5.
Based on the uniform catalogue, seismicity of theregion studied, seismicity parameters were
calculated utilizing the method proposed by Kijko
and Sellevoll [15] (Table 1).
A complete catalog including foreshocks andaftershocks normally will not follow the Poisson
distributions, so we will eliminate all foreshocks andaftershocks by windowing method in time and spacedomains by Gardner and Knopoff [16].

Fig6. Grid points within the study area

Four attenuation relations were used for this study[17], [18], [19], [20]. Peak ground accelerations are
generated by EZFRISK with 5%and 10% probabilityof exceedance in 50 years (Fig 7 and Fig 8).

563

GEOMATE- Brisbane, Nov. 19-21, 2014

region. Hazard in Sumatra is quite high while in
Malaysia it is low. In west Malaysia PGA is 0.02 to
0.09 for 5% probability of exceedance and 0.02 to
0.1 for 10% probability of exceedance. In thisassessment, we didn’t consider the amplification ofsoils. This factor can increase the ground motion.
The significant results of this study can besummarized as:-Making complete and updated earthquake catalogue-Production of a preliminary seismic zoning map
based on PGA over bedrock that can be used as a
guide for determining the design earthquake.
-Find and use the most suitable attenuation relation
for the study area.
ACKNOWLEDGMENT
The support for the research presented in this paper
had been provided by the Universiti Sains Malaysia.

REFERENCES
Fig. 7 PGA with 5% probability of exceedance in 50 years(return period: 975 years).

Fig. 8 PGA with 10% % probability of exceedance in 50
years (return period: 475 years).

CONCLUSION
The lack of active faults and earthquakes meanthat the Malaysia is located in a tectonically stable
564

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Megawati, K., Pan, T.-C., and Koketsu, K. "Response
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Balendra, T., Lam, N. T. K., Wilson, J. L., and Kong,
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Balendra, T., and Z. Li. "Seismic hazard of Singapore andMalaysia." Electron J Struct Eng (special issue, Earthquake
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2004 and March 28, 2005 earthquakes off NW Sumatra”,
Journal of Asian Earth Sciences, 2012, Vol 46, pp.150-160.
[14] Nuannin P, Kulhanek O, Persson L. “Variations of b-values
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hazard parameters from incomplete data files. Part II.
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[16] Knopoff L. and Gardner J. “Homogeneous catalogs ofearthquakes”, Proceedings of the National Academy of
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[17] D.M. Boore, and G.M. Atkinson, Ground -Motion
Prediction Equations for the Average Horizontal
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Spectra, 24(1), 2008, 99-138.
[18] Sadigh, K., Chang, C.-Y., Egan, J.A., Makdisi, F., Youngs,
R.R.Attenuation relationships for shallow crustal
earthquakes based on Californiastrongmotiondata. Seismol.
Res. Lett, 1997, 68, 180 – 189.
[19] Frankel, A., Mueller, C., Barnhard, T., Perkins, D.,
Leyendecker,E.V., Dickman, N., Hanson, S., Hopper, M.
National seismic hazard map: documentation June 1996.
Open-File Rep. -U.S. Geol. Surv. 1996, 96-532[20] Toro, G.R., Abrahamson, N.A., Schneider, J.F. Model ofstrong ground motions from earthquakes in Central andEastern North America: best estimates and uncertainties.
Seismol. Res, 1997, Lett. 68, 41 – 57.

565

Fourth International Conference on Geotechnique, Construction Materials and Environment ,Brisbane , Australia, Nov 19-21,2014,ISBN:978-4-9905958-3-8C3051

DEVELOPMENT OF SOIL FORMATION CORRESPONDING TOCYCLIC STRESS – DERIVED SHEAR STRAIN BASED ON
STRATUM INDEX FACTOR
Abdull Halim Abdul
Geosciences Department, University Technology PETRONAS, Bandar Seri Iskandar , 31750Tronoh ,MALAYSIA
ABSTRACTThis paper discusses the application of Laplace Transform ( LT) method in solving the shear strain equation fromstratum index factor , which involve a competitive sequential CPI model and cyclic stress formation . The
methodology of these analysis know as modified constant plastic index in consolidated soil –Derived shear strain
based on stratum index factor.
Keywords: Stratum index factor , Shear strain function

prediction value to the measured value. In the case ofa three dimensional field, the Biot’s theory of
consolidation which complex the equilibrium of total
stress,continuity of soil mass and strain of soil deformation
has been useful (Biot, 1945).
OBJECTIVE(1) Modification of Constant Plastic Index method on
CPI model based on volume matrix change of theconsolidation soil .
(2) Derived shear strain function using Laplace
Transform ( L T ) and cyclic stress formation as
stratum index factor for
stress –strain function
based on CPI Model

INTRODUCTION
It is well-known that in 1923 Terzaghi [ 1] and his
consolidation theory brought the dimension-time into
Soil Mechanics. The research about a very soft
saturated soil ground consolidation due to self-weight.
A lot of evaluation of Terzaghi one dimensional theory
has been done to compare the finite element numerical
A Constant Plastic Index (CPI ) model was set upthat state : a relationship soil consolidation formation
exist volume matrix change of shear stress - strains
curve . The curve is derived a shear stress function
on amplitude strain ( Or , 2001) or mathematical
shear strain( Hudson & Harrison ( 1977) due to (½ 𝒂 ) half of stratum index factors
The specific objectives of the research are as follows
in Figure 1 as

MODIFIED CONSTANT PLASTIC INDEX METHOD
The
deformation under cyclic stressesascompression of stratum index factors and it isconsidered a homogeneous soil
subjected
tosinusoidal shearing stressof angular velocity
stress amplitude and strain amplitude. (Teamrat ,A.Ghezzehei , and Dani Or (2001)) [ 3] . The shearing
stress applied upon purely elastic soil resulted inproportional and instantaneous strain.

After completing a cyclic load saturation,
consolidation and volume matrix change of soil is a
steady state
casewhere F (e ) 𝒆𝒐 𝒙 = 𝟏 +𝒆𝒐 ( 𝑷𝒐𝒖𝒍𝒐𝒔 (𝟏𝟗𝟖𝟏)
Equation 1
The equation (Ssul) derived will become amathematical equation as
𝒆𝒐 𝒙 =

566

∆𝒆
𝑺𝒔𝒖𝒍

𝑯

Equation 2

GEOMATE- Brisbane, Nov. 19-21, 2014
Where
H is thickness of soil layer∆e is a (final void ratio –initial void ratio)
e0 is initial void ratio
Ssul is Ultimate Consolidation Settlement
The equation 2 can be
expressed as log10.
𝑳𝒐𝒈𝒆𝒐 𝒆𝒐𝒙 = 𝑳𝒐𝒈𝒆𝒐 [

∆𝒆𝑯
𝑺𝑺𝒖𝒍

]

equation 3

𝑳𝒐𝒈𝒆𝒐 𝒆𝒐𝒙 =𝑳𝒐𝒈𝒆𝒐 (∆𝒆𝑯)−𝐥𝐨𝐠𝐞𝟎 𝐒𝐒𝐮𝐥
𝑿=

(

∆𝒆𝑯

𝑰𝒏 𝑺𝒔𝒖𝒍)𝑰𝒏𝒆𝒐equation 4

Where, x is Constant Plastic Index (CPI)F ( e ) is Void ratio Function of the potential yields
function Elastic soil ( Hardin Bankford, 1989 ) andthe equation is follows Hooke Law for a number of
equation 5clay
F (e) = e ox
Where F (e) is void ratio function
X
is constant plastic index (CPI)
eo is initial void ratio
in layer hypothesis in Figure 1 is considered with an
initially uniform void ratio e1 under its own weight,
and e2 is the base of layer which suddenly increased
the stress, then remained constant. per surface of thislayer is allowed to drain freely , hence its void ratio
will immediately reach the new equilibrium state,e2 . The base of this layer is assumed to be
impervious and thus, no drainage can occur acrossit.

DERIVED SHEAR STRAIN
STRATUM INDEX FACTOR

BASED

Figure 1 Surface and base of the layer .
In the Langrangian formulation, the compaction
within two layers is complicated because of thepresence of the fixed boundary. The Constant plastic
index (CPI) mechanism of compacted clay between
two layers is considered to be integrate Stratum Index
Factors (α) , A characteristic of compacted soil
between surface (s) and base (b) of layers
isformulated as!Unexpected End of Formula𝐞 𝐱𝟏

𝛂 = 𝐈𝐧 𝐬 𝐱𝟐

equation 6

𝐞𝐛Furthermore, to obtain the evaluation formula for the
expansion characteristic of compaction, it is proposedthat the development of CPI (x) model and Stratum
Index Factor (SIF) model be combined to get theestimate of the CPI (x) characteristic of clay.

ONconfirmed in this section by the solutions developedfor each case.

In situation where single drainage is only allowed (Kuantsai 1979)[ 1] at one of the two boundaries of thestratum, the progress of consolidation will be retarded.
In the theory of a linear soil model and the thin layer
the actual location of this boundary, whether it is in thesurface or the base, does not effected the strain rateof the stratum. This is because identical void ratiochanges occur at both boundaries. In the present
theory, however, the void ratio changes in bothboundaries will be different. Consequently, adifference in the strain rate is expected for different
locations of the drainage boundary. This will be

The inverse transformation according to the inversion
theorem is evaluated in (Lee Kuantsai 1979, pg166)
and which it is found that:𝜶𝜷𝒏 𝒄𝒐𝒔𝜷𝒏 + 𝒔𝒊𝒏𝜷𝒏 = 0
𝟐

as shear strain functionand𝜶𝜷𝒏 𝒄𝒐𝒔𝜷𝒏 − 𝒔𝒊𝒏𝜷𝒏 = 0 as shear tensile function .
𝟐

Equation 7

567

GEOMATE- Brisbane, Nov. 19-21, 2014
𝐟(𝒏, 𝑻𝒗) = 𝟏 −Surface drain
The boundary conditions in this caseare:𝒒(𝟏, 𝑻𝒗) = ∆𝑭(𝒆)equation 8
𝝏𝒒
𝝏𝒏

𝟐𝚺𝒏

𝜶

(−𝟏)𝒏 [𝜷𝒏 𝒄𝒐𝒔(𝜷𝒏 𝒏)+ 𝟐 𝒔𝒊𝒏(𝜷𝒏𝒏)]𝜶𝟐𝜶𝜶𝟐)[𝜷𝒏 ++]
𝟒
𝟒𝜷𝒏 𝟐𝜷𝒏√ (𝜷𝒏 𝟐 +(𝟎, 𝑻𝒗) = 𝜶𝒒(𝟎, 𝒕)
𝜶𝟐𝟒equation 9𝜶) 𝑻𝒗 − (𝒏 − 𝟏)]𝟐

where the 𝜷𝒏 s are the zeroes ofUsing the Laplace transform it is found ( Lee Kuantsai, 1979) that:𝜶𝜷𝒏 𝒄𝒐𝒔𝜷𝒏 + 𝒔𝒊𝒏𝜷𝒏 = 0

as shear strain and shear𝟐̅(𝒏, 𝒑) = 𝑨𝟏 𝒆𝒙𝒑(𝒎𝟏 𝒏) +𝒒
rate function

𝒎𝟏 𝜶
𝜶𝟐, 𝒎 = ± √( + 𝒑)
𝟐
𝟒
𝟐

𝑨𝟐 𝒆𝒙𝒑(𝒎𝟐 𝒏)

𝒆𝒙𝒑 [− (𝜷𝒏 𝟐 +equation 10
with,
𝑨𝟏

𝑩 ∆𝑭(𝒆)𝒑[ 𝒆𝒙𝒑(𝒎𝟐 )−𝑩𝒆𝒙𝒑(𝒎𝟏 )]𝑨𝟐 =𝐚 𝐞𝐱𝐩(𝐦𝟐 )− 𝐛
𝐩 [𝐞𝐱𝐩( 𝐦𝟐 )− 𝐞𝐱𝐩(𝐦𝟏 )]

and

𝑩=

𝒎𝟐 −𝜶
𝒎𝟏 −𝜶

The Laplace transform of the local degree ofconsolidation is given by:𝐟 ̅ (𝒏, 𝒑) =Figure 2

Shear stress and shear strain function𝒒̅ (𝒏,𝒑)𝒒(𝒏,∞)The expression for the void ratio change q can beobtained by:

After some manipulation, this is found to be:𝒒(𝒏, 𝑻𝒗) = ∆𝑭(𝒆) 𝒆𝒙𝒑[𝜶(𝒏 − 𝟏)] 𝐟(𝒏, 𝑻𝒗)𝐟(̅ 𝒏, 𝒑) =
𝜶𝟐

𝜶

𝜶𝟐

𝜶

𝜶𝟐

𝒆𝒙𝒑[− 𝟐 (𝒏−𝟏)] {√ ( 𝟒 +𝒑)𝒄𝒐𝒔𝒉[𝒏 √ ( 𝟒 +𝒑)]+ 𝟐 𝒔𝒊𝒏𝒉[ 𝒏 √( 𝟒 +𝒑)]}𝒑 {√ (𝜶𝟐𝜶𝜶𝟐𝜶𝟐+𝒑)𝒄𝒐𝒔𝒉[ √ ( +𝒑)]+ 𝒔𝒊𝒏𝒉[ √ ( +𝒑)]}𝟒
𝟒𝟐
𝟒The degree of settlement is found to be:
𝑺(𝑻𝒗) = 𝟏 −equation 11𝟐𝜶𝟐

𝒆𝒙𝒑[−(𝜷𝒏 + 𝟒 ) 𝑻𝒗]
𝚺𝜶𝟐𝜶𝟏−𝒆𝒙𝒑(−𝜶) 𝒏𝟐 𝜶𝟐+)(𝜷𝒏 + ) (𝟏 +𝟐𝜶The inverse transformation according to the inversion

𝟒

theorem is evaluated in (Lee Kuantsai 1979, pg166)
and Figure 2 from which it is found that:

568

𝟒𝜷𝒏 𝟐

𝟐𝜷𝒏 𝟐

GEOMATE- Brisbane, Nov. 19-21, 2014
The small time approximation to this can be obtained

𝑳

−𝟏

{

by considering the behaviour of the Laplace transform,

𝜶𝟐

𝟏
𝒑[ √(

𝜶𝟐
𝜶
+𝒑)+ ]
𝟒
𝟐

}=𝑳

−𝟏

{

√ ( 𝟒 +𝒑)
𝒑𝟐

}−

𝜶
𝟐

𝑻𝒗

which is:𝑺(𝒑) =As 𝒑 → ∞,𝜶𝒑[𝟏−𝒆𝒙𝒑(−𝜶)]𝒄𝒐𝒕𝒉 √ (It follows form eq.11 that,

𝟏

𝜶𝟐
𝟒

√(

𝜶𝟐
𝜶𝟐
𝜶
+𝒑) 𝒄𝒐𝒕𝒉[√ ( +𝒑)+
𝟒
𝟒
𝟐

𝑳

{

𝜶𝟐
+𝒑)
𝟒
𝒑𝟐

√(

𝑻𝒗

} ≃ 𝟐 √(

𝝅

)+

𝜶𝟐
𝟐 √𝛑

√(𝑻𝒗)𝟑+ 𝒑) → 𝟏

Which is,It follows that :𝒔(𝒑) =−𝟏𝜶𝟏𝟏−𝒆𝒙𝒑(−𝜶) 𝒑[√(𝜶𝟐 +𝒑)+𝜶 ]𝟒𝑺(𝑻𝒗) =𝒑→∞𝜶𝟏−𝒆𝒙𝒑(−𝜶)

𝑻𝒗

𝜶

𝝅

𝟐

[𝟐 √ ( ) − 𝑻𝒗 +

𝟐

𝜶𝟐
𝟔√ 𝝅

√𝑻𝒗𝟑 ]

𝑻→𝟎equation 12

Since,𝜶In large time an approximate solution can again be̅(𝒏, 𝒑) =𝒒∆𝑭(𝒆)𝒆𝒙𝒑( 𝟐 𝒏−𝜶)
𝒑

[ √(

𝜶𝟐
𝟒

+ 𝒑) 𝒄𝒐𝒔𝒉 [(𝟏 −obtained by taking the first few terms of the series𝒏)√(solution, eq.12 . A comparison of the small and large
time approximation (up to the third term in the series)

𝜶𝟐
𝟒

𝜶

𝜶𝟐

𝟐

𝟒

+ 𝒑)] − 𝒔𝒊𝒏𝒉 [(𝟏 − 𝒏)√(𝒑)]] √[ √ (𝜶𝟐𝟒+ 𝒑) 𝒄𝒐𝒔𝒉 √ (

𝜶𝟐
𝟒

+

+ 𝒑) −

with the exact solution is shown in a typical value of𝜶α=1. The agreement is seen to be very good.

𝟐(b) Based drain

𝒔𝒊𝒏𝒉 √(

𝜶𝟐
𝟒

+ 𝒑)]

and,
𝐟̅ (𝒏, 𝒑) =The boundary conditions for this case are:
𝜶𝟐

𝝏𝒒
𝝏𝒏

𝜶𝟐

𝜶

𝟒

𝟐

𝜶𝟐

𝜶
𝒆𝒙𝒑(− 𝟐 𝒏) √( 𝟒 +𝒑)𝒄𝒐𝒔𝒉[(𝟏−𝒏)√( 𝟒 +𝒑)]− 𝟐 𝒔𝒊𝒏𝒉[(𝟏−𝒏)√( 𝟒 +𝒑)]
𝜶𝟐
𝜶𝟐
𝜶
𝜶𝟐
𝒑
√( +𝒑)𝒄𝒐𝒔𝒉√( +𝒑)− 𝒔𝒊𝒏𝒉√( +𝒑)𝒒(𝟎, 𝑻𝒗) = ∆𝑭(𝒆)𝒆𝒙𝒑(−𝜶)𝟒𝟒(𝟏, 𝑻𝒗) = 𝜶𝒒(𝟏, 𝑻𝒗)
The inverse transform of this is also evaluated in Lee
Kuantsai page 169 and 59 and this chapter, from

Using the Laplace transform it is found that:which it is found that:569

GEOMATE- Brisbane, Nov. 19-21, 2014
𝐟(𝐧, 𝐓𝐯) = 𝟏 −𝟐

𝑺(𝑻) =

𝛂(−𝟏)𝐧 [𝛂𝐧 𝐜𝐨𝐬𝛂𝐧 (𝟏−𝐧)− 𝐬𝐢𝐧𝛂𝐧 (𝟏−𝐧)]
𝟐
𝚺
𝐧
𝛂𝟐
𝛂
𝛂𝟐
−
)
(𝛂𝐧 + )(𝛂𝐧 𝟐 +𝟒𝟒𝛂𝐧 𝟐𝛂𝐧𝛂𝟐𝟒𝐞𝐱𝐩 [− (𝛂𝐧 𝟐 +

𝜶𝟐 𝟏
𝟔 √𝝅

𝜶
𝒆𝒙𝒑(𝜶)−𝟏

𝑻𝒗

𝜶

𝝅

𝟐

[𝟐√( ) + 𝑻𝒗 −√𝑻𝒗𝟑 ]

equation 15𝛂) 𝐓𝐯 − 𝐧]

It is worth noting that by adding this to the expression

𝟐

for the surface drain case:and the degree of settlement is:
𝑺𝒃𝒂𝒔𝒆 + 𝑺𝒔𝒖𝒓𝒇𝒂𝒄𝒆 =𝑺(𝑻𝒗) = 𝟏 −

𝟒

𝟒𝜶𝒏

𝑻𝒗

𝜶

𝝅

𝟐

[𝟐(𝟏 +

𝒆𝒙𝒑(𝜶))√( ) − (𝒆𝒙𝒑(𝜶) − 𝟏)𝑻𝒗 +𝟐𝟐 𝜶𝒆𝒙𝒑[−(𝜶𝒏 + )𝑻𝒗]𝚺𝟒
𝒆𝒙𝒑(𝜶)−𝟏 𝒏 (𝜶 𝟐 +𝜶𝟐 )(𝟏+ 𝜶𝟐 − 𝜶 )
𝒏
𝟐
𝟐
𝟐𝜶

𝜶
𝒆𝒙𝒑(𝜶)−𝟏

𝜶𝟐

𝟐𝜶𝒏

𝟔

(𝟏 + 𝒆𝒙𝒑(𝜶))

𝟏
√𝝅

√𝑻𝒗𝟑

equation 16

where the αn are the zeroes of𝜶𝜶𝒏 𝒄𝒐𝒔 𝜶𝒏 − 𝒔𝒊𝒏 𝜶𝒏 = 0
𝟐

as

a

shear

strain

and

shear

rate

function

RESULTequation 13,
The progress of the degree of settlement with thesquare root of time factors for both surface andbase drain cases . The differential of pore waterpressure and void ratio change absent and thedegree of consolidation will move to lower
consolidation . In the surface drain the trend issimilar to the double drainage case in that fasterconsolidation achieved with larger SIF . However
the opposite is observed in the base drain casewhere larger SIF willproduce a slower
consolidation , and it can be seen thattheconsolidation with base drain is always slower
than the thin layer , while the surface drain will
always be faster . It can be seen that theconsolidation with stratum coefficient ( Lee Kuantsai
1977 ) [ 1 ] is always slower than the SIF . A

Plasticity soil . The small time approximation to thedegree of settlement is obtained by Lee Kuantsai(1979) and considering its Laplace transform:
̅(𝒑) =𝑺𝟏

𝜶𝒑[𝒆𝒙𝒑(𝜶)−𝟏] √ (𝜶𝟐 +𝒑)𝒄𝒐𝒕𝒉 √ (𝜶𝟐 +𝒑)−𝜶𝟒𝟒𝟐equation 14
As 𝒑 → ∞ ,𝒄𝒐𝒕𝒉√(𝜶𝟐𝟒+ 𝒑) → 𝟏

it follows that:
𝑺(𝒑) =𝜶𝟏

𝒆𝒙𝒑(𝜶)−𝟏 𝒑[√(𝜶𝟐 +𝒑)−𝜶]𝟒𝟐The inverse transform of this is, approximately in
Figure 13570

GEOMATE- Brisbane, Nov. 19-21, 2014
Degree of settlement is:comparison of the small and large time approximation(up to the third term in the series) with the exact
2
1
Y

0

π5

0

2 10
π

-1

𝟒

y=α/2
sin(ωt+δ)(α=0,00
9600074)

It was found that, the average degree of settlement incritical state for double drainage consolidated fasterthan for single drainage. Enhanced to increase thedegree of settlement of double drainage consolidated
was faster than to reduce the degree of settlement.

Figure 3 Single drainage for surface shear strain

SINGLE-BASED( CPI
MODEL & LEE
KUANTSAI)REFERENCES[1] Kuantsai 1977 “An Analytical And Experimental
Study Of Large Strain Soil Consolidation”: A Thesis
submitted to the University of Oxford for the Degreeof Doctor of Philosophy , Trinity Term .
[ 2 ] Robert Kirk Bowden (1988)“Compression Behavior and Shear
Strength
Characteristies of a Natural Silty Clay Sedimented in
the Laboratory ”, A thesis submitted to the University

Y

0
0

2

4

β
●
●
0●

π

●6
●
●
β

8

2
π

of Oxford for Degree of Doctor of Philosophy

y=-α/2 sin x (α=1…
X sin x…
y=-α/2-20-, Trinity Term, 1988.
[ 3 ] Leonard , G.A ,Altschaeffl, A.G (1964,1976)“Compressibility of Clay ‘’ Proceeding , ASCE ,90:SM5 :133-156 (1964)[4] “ Estimating Consolidation Settlement of Shallow
Foundation On Over consolidated Clay
” Special Report No 163 , Transport Research Board ,Washington , D.C , pp 13-16 . (1976)[4] LisandroPANTELIDIS (2007)“Determining of
the Soil Strength Characteristics Through the Plate
Bearing Test ‘Journal House of Poznan University ofTechnology , Poznah 2008ISSN 1642-9303 .
[ 5 ] Ashraf S.Osman , Malcolm D. Bolton (2“A new
method to the estimation of untrained settlement ofshallow foundation on soft clay ”, Journal
Engineering Practice and Performance if
Soft
Deposits .

Figure 4
Single drainage for base shear strainfunction . Single Surface - Case 2—t=Constant, CV
and CF = various . Single surface CPI S(Tv) increased
due to Lee Kuantsai method
The inverse transform of this is also evaluated in Lee
Kuantsai page 231 and in this chapter, from which it isfound that:𝐟(𝐧, 𝐓𝐯) = 𝟏 −
𝟐𝚺𝐧
𝛂𝟐
𝟒

𝛂
𝟐
𝟐
𝛂

(−𝟏)𝐧 [𝛂𝐧 𝐜𝐨𝐬𝛂𝐧 (𝟏−𝐧)− 𝐬𝐢𝐧𝛂𝐧 (𝟏−𝐧)]
𝛂𝟐

(𝛂𝐧 +

𝟒

𝛂
)
𝟒𝛂𝐧 𝟐𝛂𝐧)(𝛂𝐧 𝟐 +−𝟐𝛂𝐧CONCLUSION

X
solution is shown in a typical value of α=1.

π

𝟒𝛂𝐧equation 14

-2

202

𝟐
𝟐 𝛂

𝐞𝐱𝐩[−(𝛂𝐧 + )𝐓𝐯]
𝚺𝟒
𝐒(𝐓𝐯) = 𝟏 −𝐞𝐱𝐩(𝛂)−𝟏 𝐧 (𝛂 𝟐 +𝛂𝟐 )(𝟏+ 𝛂𝟐 − 𝛂 )
𝐧
𝟐
𝟐
𝟐𝛂

single-surface( CPI model )𝐞𝐱𝐩 [− (𝛂𝐧 𝟐 +𝛂) 𝐓𝐯 − 𝐧]𝟐571

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

UNEXPECTED HIGH CO2 CONCENTRATION IN
CLASSROOMS OF WAKAYAMA UNIVERSITY
1

Masahiro Yamashita1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan;
2
Faculty of Systems Engineering, Wakayama University, Japan

ABSTRACT
CO2 concentration in most classrooms in Wakayama University was over 1000 ppm, the Japanese school
Environmental Standard and sometimes reached over 4000 ppm. Airtightness for each classroom without
ventilation was estimated by measuring CO2 production volume per people number per unit time (CPPT).
Airtightness for classroom is variable because of opening door by student during lecture and most of air inclassroom was thought to be sometimes exchanged by opening door. Then, effect of opening door and window
on CO2 concentration in classroom was estimated from CO2 concentration, classroom volume, number of people,
and time by comparing CO2 concentrations under no ventilation condition and ventilation condition opening
door or window. As a result, the classroom with volume of 250 to 930 m3 needs 4.2 to 6.3 m2 area to open door
or window for not increasing CO2 concentration.
Keywords: CO2 concentration, airtightness, ventilation, portable sensor
INTRODUCTION
This study is to measure air quality in classroomof Wakayama University by focusing on CO2
concentration. CO2 concentration in a classroom isdesigned
based on the Japanese school
Environmental Standard. Ministry of Education,
Culture, Sport, Science and Technology propose that
CO2 concentration in classrooms is less than 1000
ppm [1]. When it is less than 1000 ppm, there is little
impact on the human body. But, there will be various
impacts if you are for long time in more than 1000
ppm space. For example, there are drowsiness,languor, vertigo, and headache. Classrooms are likely
high population and it isn’t customary to do
ventilation regularly in University. In addition,buildings in recent years often have high air tightness
for improvement of building technology [2]. While
this can reduce consumption of air conditioning
energy, buildings in recent years are difficult toobtain enough ventilation. CO2 concentration inclassrooms of University may be very high because
these reason.
A purpose of this study is to evaluate air
condition by measuring CO2 concentration in
lecturing classrooms of Wakayama University.

2013. Portable sensor GCH-2018 was used formeasuring CO2 concentration as shown in Fig1
Measuring place was at the back side and at 80 cm
height of each classroom.
There were two types of measurements. One isshort time measurement for obtain roughly CO2
concentration for many classrooms. Measurement
time is about 3 minutes for each classroom and total
numbers of classrooms for measurement are 94. The
other is one lecture measurement from the beginningof lecture to end of the lecture. Total measurement
time is 90 minutes for each lecture with every 15
minutes measurement. The purpose was to clarifychange of CO2 concentration with time, people,
volume of classroom, and air condition. The
measurement dates are December 2013 and January
2014 as period of winter and April, May and June2014 as period of spring.

METHOD
Survey was performed at 6 buildings inWakayama University. These are the building of
economic, the building of education, the building A
of engineering, the building B of engineering, thebuilding of tourism and the building of basic
education. The measurement dates are December

Fig. 1572

CO2 concentration meter (GCH-2018)

GEOMATE- Brisbane, Nov. 19-21, 2014

RESULT1.

3 minutes measurement

ppm. Therefore, ventilation is useful for reducing
CO2 concentrations of classrooms and keeping lessthan 2000 ppm.
Table I The CO2 concentration of classroom for thebuilding

Fig. 2 CO2 concentration at building A and B ofEngineering
Fig. 2 shows CO2 concentration at building A
and B of Engineering for 3minutes measurement.
Solid marks show no ventilation and Open marks
show ventilation. Only 20 % numbers of both thebuildings were aired by window or air conditioner.
CO2 concentration for many classrooms of bothbuildings reached over 3000 ppm. However, CO2concentrations in ventilated classroom were less than
2000ppm.

Table I is summary of these results. If
comfortable air condition is less than 1000 ppm,
building of the Education, building of the Tourism
and building of the Basic Education are almost goodcondition. But, other buildings are often 1000 ppm ormore.
Especially in building A of the Engineering,
about 35 % is over 1500ppm and about 16 % is over3000 ppm. As lecture is often done in the sameclassroom continuously and population density tends
to be higher than other buildings, CO2 concentration
was high. It was found that building of the Economic
and building B of the Engineering are often bad air
condition.
2.

Fig. 3 CO2 concentration at building of Economic,
Education, Tourism and Basic Education
Fig. 3 shows CO2 concentration at building of
Economic, Education, Tourism and Basic Educationfor 3minutes measurement. Education buildings were
not aired and the half of classrooms for Economic,
Tourism and Basic Education buildings were aired.
CO2 concentrations of classrooms for the Economic
buildings were often over 2000 ppm. CO2
concentrations of most of classrooms for Education,
Tourism and Basic Education buildings were lessthan 1500 ppm. CO2 concentrations of classrooms
with ventilation for all buildings were less than 2000

90 minutes measurement

From the 3 minutes measurement results,
classrooms of the building A and B of Engineering
were high CO2 concentrations and then, 90 minutes
measurement was performed in three classrooms of
the building A and three classrooms of the building B
of Engineering. And one classroom built by woods
for the Tourism and two large classrooms for the
Basic Education were also studied by 90 minutes
measurement. Comparing winter and spring condition,
the 90 minutes measurements were performed in
December 2013 and January 2014, and April, May
and June 2014 for 9 classrooms and 43 total times.
Fig. 4 showed CO2 concentration change withtime of G102 classroom with 970 m3 volume of the
Basic Education under both aired and no aired
conditions. Solid rhombus was no ventilation
condition with 82 people and open square wasventilation condition with 70 people. Under noventilation condition, CO2 concentration increased
with time and the increase rate was 6 ppm per
minutes. The start CO2 concentration was high, 1600
ppm and finally, CO2 concentration reached 2200
ppm. On the other hand, with ventilation by opening
a door, the start CO2 concentration was low, 800 ppm
573

GEOMATE- Brisbane, Nov. 19-21, 2014

and it kept low concentration and finally decreased to
700 ppm. The door size was 2.0 m height and 1.0 m
width. Then, it was very useful for reducing CO2
concentration by opening door.
Fig. 5 showed CO2 concentration change withtime of A203 classroom with 530 m3 volume ofbuilding A of Engineering under both aired and noaired conditions. Solid rhombus with 58 people andsquare with 80 people were no ventilation conditionand open triangle with 76 people was ventilation
condition opening a door with 2.0 m height and 1.0 m
width. However, CO2 concentration under both
ventilated and no ventilated condition increased withtime and the increase rate was almost the same. The
maximum CO2 concentration was 4500 ppm.
Fig. 6 showed CO2 concentration change withtime of B203 classroom with 250 m3 volume ofbuilding B of Engineering under both aired and noaired conditions. The people number was about 40
each time. Under no ventilation condition, CO2concentration increased with time and the increase
rate was 22 ppm per minutes. The start CO2
concentration was 700 ppm and finally, CO2concentration reached 2500 ppm. On the other hand,with ventilation (4/24) by opening a door with 2.0 m
height and 1.0 m width, the start CO2 concentration
was 1000 ppm and CO2 concentration kept 1200 ppm.
With ventilation (5/22) by opening a door andwindow both with 2.0 m height and 1.0 m width, thestart CO2 concentration was 600 ppm and CO2
concentration kept 600 ppm. With ventilation (6/5)
by opening two doors with 2.0 m height and 1.0 m
width, the start CO2 concentration was 700 ppm andCO2 concentration kept less than 1000 ppm.
Therefore, under no ventilation condition, CO2concentration reached 2500 ppm and decreased 1500
ppm by ventilation with opening a door. Two doors
and both one door and one window were able to keep
less than 1000 ppm. Then, CO2 concentration was
thought to depend on people number, classroom sizeand ventilation method.

Fig. 5 Measurement result of A203 classroom

Fig. 6 Measurement result of B203 classroom
Next, under no ventilation condition, CO2concentration was estimated by people number, time,and size of classroom. Then, CO2 concentration
increase from the start to the end of lecture wasdefined by the following equation. CPPT inclassroom is CO2 production volume (10-6m3/people/minute) per people number per unit time.

CPPTinclas sroom

End CO2 concentrat ion  Start CO2 concentrat ion * Volume of classroom (m 3 )Number of people ( people ) * Lecture time (min) *10 6

 1

Fig. 4 Measurement result of G102 classroom

The relationship between CO2 concentration at
the start time and CPPT in classroom for 11 noventilation classrooms in winter and for 7 noventilation classrooms in spring are shown in Fig. 7
and Fig. 8. CPPT for university student is generally
370*10-6 m3/people/minute [2]. The value is averageper day including exercise for walking. CPPT for rest
574

GEOMATE- Brisbane, Nov. 19-21, 2014

time is smaller than CPPT for exercise time andpeople condition in classroom is rest time. Then, themaximum CPPT in classroom was thought to be inagreement with CPPT for rest time. However, CPPT
in classroom calculated in this measurement isvariable from 10*10-6 to 250*10-6 m3/minutes/people.
The difference between both values was thought to belack of airtightness for classroom or heterogeneousconcentration. Airtightness for classroom is a gap
wind even if door and window closed [3]. Even underno ventilation condition, students sometimes opened
door during lecture and then exchanged air outside.
Measurement point in classroom was just one backside of the classroom. Then, the measured
concentration may not be necessary an average value.
Under no ventilation condition, most of CO2
concentrations in classroom were over 1000 ppm.
Next, effect of ventilation on CO2 concentration ofclassroom was studied.
.

Fig. 7in winter

Beginning CO2 concentration and CPPT

Fig. 8in spring

Beginning CO2 concentration and CPPT

Fig. 9 and 10 showed relationship between the
MAX CO2 concentration during lecture andpopulation density in winter and in spring. Solidmarks were no ventilation and open marks wereventilation conditions with regression lines for eachtype of ventilation.
Fig. 9 showed the MAX CO2 concentration andpopulation density in winter. The ventilation in
winter was opening one door with 2.0 m height and
1.0 m width in winter. As population density
increased, the MAX CO2 concentration under both noventilation and one door ventilation conditions also
increased proportionally. Slope, the maximum CO2
concentration per population density indicatedairtightness in classroom and when the value was 0,
air exchange is thought to be sufficient and CO2
concentration does not increase. Slope of regression
lines under no ventilation condition and under one
door ventilation condition were 14000*10-6
m3/people and 7800*10-6 m3/people respectively.
Fig. 10 showed the MAX CO2 concentration andpopulation density in spring. There were three typesof ventilation, one door, two doors, and one door and
one window with 2.0 m height and 1.0 m width inspring. Slope of regression line for no ventilation is
21000*10-6 m3/people. Slope of regression lines forventilation were 6000*10-6 m3/people with one door,
3500*10-6 m3/people with two doors, and 1500*10-6
m3/people with one door and one window.
Comparing winter and spring, slope ofregression line (14000*10-6 m3/people) under noventilation condition in winter was lower than those(21000*10-6 m3/people) in spring because some
winter results may be controlled by air conditioner. It
is difficult to confirm air conditioned or not becauseroom is automatically controlled. Then, spring slope
value was thought to be representative value,
21000*10-6 m3/people under no ventilation condition.
Slope of regression line (7800*10-6 m3/people)
under one door ventilation condition in winter was
higher than those (6000*10-6 m3/people) in spring.
Under same opening space, comparing two doors andone door and one window open condition, slope ofregression line (3500*10-6 m3/people) under two
doors ventilation condition was higher than those(1500*10-6 m3/people) under one door and one
window ventilation condition. Opening window wasmore effective for ventilation.
The slope difference between under noventilation condition and ventilation condition was
ventilation effect. Fig. 11 showed ventilation effect,
the difference between 21000*10-6 m3/people andeach ventilated slope value and opening area. Whenopening area is 0, the effect is 0. Then, regression
curve was calculated from origin and ventilation
effect results. Two regression curves were calculated
because results were variable. When the effect is
21000*10-6 m3/people, CO2 concentration does notincrease. From the regression curve, opening area isestimated to be 4.9 to 6.3 m2 when the effect is
21000*10-6 m3/people. The estimated opening area
for keeping no CO2 concentration increase was 4.9 to
6.3 m2 based on the maximum CO2 concentration
575

GEOMATE- Brisbane, Nov. 19-21, 2014

results. Next, from CO2 concentration increaseduring lecture and population density, opening area
for keeping no CO2 concentration increase isestimated.

Fig. 9 MAX CO2 concentration and population
density in winterFig. 10 MAX CO2 concentration and population
density in spring

Fig. 11 Effect of ventilation by opening area
approached from MAX CO2 concentration

Next, Fig. 12 and 13 showed relationshipbetween the CO2 concentration increase duringlecture and population density on the basis of theresult of 90 minutes measurement in winter and in
spring.
Fig. 12 showed the CO2 concentration increase
and population density in winter. As population
density increased, the CO2 concentration increase
under both no ventilation and one door ventilation
conditions also increased proportionally. Slope ofregression lines under no ventilation condition andunder one door ventilation condition were 5000*10-6
m3/people and 1900*10-6 m3/people respectively.
Fig. 13 showed the CO2 concentration increase
and population density in spring. Slope of regression
line for no ventilation is 15000*10 -6 m3/people. Slopeof regression lines for ventilation were 2300*10-6
m3/people with one door, 920*10-6 m3/people withtwo doors, and 90*10-6 m3/people with one door and
one window in spring.
Comparing winter and spring, slope ofregression line (5000*10-6 m3/people) under noventilation condition in winter was lower than those(15000*10-6 m3/people) in spring because some
winter results may be controlled by air conditioner. It
is difficult to confirm air conditioned or not becauseroom is automatically controlled. Then, spring slope
value was thought to be representative value,
15000*10-6 m3/people under no ventilation condition.
Slope of regression line (1900*10-6 m3/people)
under one door ventilation condition in winter was
higher than those (2300*10-6 m3/people) in spring.
Under same opening space, comparing two doors andone door and one window open condition, slope ofregression line (920*10-6 m3/people) under two doors
ventilation condition was higher than those (90*10-6
m3/people) under one door and one window
ventilation condition. Opening window was more
effective for ventilation based on the CO2
concentration increase results.
Fig. 14 showed ventilation effect, the difference
between 15000*10-6 m3/people and each ventilated
slope value and opening area. Regression curve wascalculated from origin and ventilation effect results.
Two regression curves were calculated because
results were variable. When the effect is 15000*10-6
m3/people, CO2 concentration does not increase.
From the regression curve, opening area is estimatedto be 4.2 to 6.2 m2 when the effect is 15000*10-6
m3/people. The estimated opening area for keeping
no CO2 concentration increase was 4.2 to 6.2 m2
based on the CO2 concentration increase results.
The opening areas calculated from the maximum
CO2 concentration and CO2 concentration increase
results respectively were almost the same values, 4.2
to 6.3 m2. Opening door or window area to keep noCO2 concentration increase in the classroom is atleast 4.2 to 6.3 m2.
576

GEOMATE- Brisbane, Nov. 19-21, 2014

Fig. 12 CO2 concentration increase and population
density in winteris very difficult to maintain less than 1000 ppm
without ventilation and CO2 concentration in someclassroom reached over 4000 ppm. From CO2
concentration for classroom under no ventilation
condition, CO2 production volume per people number
per unit time (CPPT) was estimated. The estimated
CPPT value in classroom was less than general CPPT
value for university student. The difference between
both values was thought to depend on lack of
airtightness for the classroom such as opening door
during lecture. Therefore opening door was thought
to be useful for ventilation and then influence of
opening door and window on CO2 concentration inclassroom
wasstudied.
ComparingCO2
concentrations under no ventilation condition andventilation condition opening door or window,
ventilation effect was calculated from CO2
concentration, classroom volume, number of people,
and time. The relation between ventilation effect andopening area by door or window was studied. When
total area to open door or window in the classroom is
at least 4.2 to 6.3 m2 (one door and one window, two
windows), CO2 concentration in the classroom withvolume of 250 to 930 m3 does not increase.
REFERENCES

Fig. 13 CO2 concentration increase and population
density in spring[1] Noriko Ochiai, Kazunari Yamashita: (2010)
Indoor carbon dioxide of Shimane University
lecture room and control of air quality[2] Homepage of Ministry of Education, Culture,
Sport, Science and Technology[3] Song SungKi: (2003) Research on the predictionof air conditioning heat load for large spacebuildins[4] Daisuke Kobayashi: (2007) A study on theinfluence of environment in the classroom brings
to children[5] Taemi Gohara, Tuyoshi Iwashita: (2002) The
indoor air condition measured in elementary
school in Kagoshima city

Fig. 14 Effect of ventilation by opening area
approached from CO2 concentration increase
CONCLUSION
Most classrooms in Wakayama University were
not satisfied with comfortable CO2 concentration. It
577

FourthInternational Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia,Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

ATTENUATION LANDFILL POTENTIAL EVALUATION FOR AMILLENIUM CITY, IN NIGERIA
Oluwapeluimi O. Ojuri1
1

Department of Civil and Environmental Engineering, Federal University of Technology, Akure, Nigeria

ABSTRACT
Akure has been selected as a millennium city in Africa by the United Nations Millennium Development
Initiative. This research was carried out to study the geotechnical considerations in the design of sanitary landfill,attenuation option for Akure Metropolis, where a dumpsite has been in use for several years. On site
investigation and laboratory tests were conducted on depth discrete soil samples up to 3.0 metres depth, to see
how suitable the site is, based known engineering regulation for design of an attenuation sanitary landfill. The
Cation Exchange Capacity (CEC) values for the site ranged between 9.02 to 10.73 milli-equivalents/100g(Meq./100g) for Na+, k+, Ca++, Mg++, and the highest PH value was 7.25. The fines content of the samples ranged
from 29.0 to 33.0%. The average unconfined compressive strength of the soil from the unconsolidated undrained
triaxial test was 270.0 kN/m2, which is adequate for bearing capacity consideration. The coefficient of
permeability value ranged between 2.2x 10 -4 and 4.0 x 10 -3 cm/sec for all the soil samples tested beneath thedumpsite up to 3.0 metres depth. The attenuation layer of a sanitary landfill should be designed using a low
permeability clay-rich soil (hydraulic conductivity <10-3 cm/s), enabling leachate to percolate slowly
downwards, simultaneously undergoing attenuation by biodegradation, sorption, filtration and ion exchange. The
optimum permeability for attenuation should be in the order of 10-4 to 10-6 cm/s. The potential for implementing
an attenuation landfill at this site is high based on the investigation conducted.
Keywords: Attenuation landfill, Cation Exchange Capacity, PH, Coefficient of permeability, Specific gravity

INTRODUCTION
Akure, a growing urban area within latitudes 7◦
10ꞌN and 7◦ 20ꞌN and between longitudes 5◦ 07ꞌE
and 5◦ 17ꞌE in Ondo State, Southwestern Nigeria
was chosen for this research work because it is oneof the few towns in Africa and the only one in
Nigeria selected as a millennium city by the United
Nations Millennium Development Initiative [1]. The
contributions of modern sanitary landfills toeffective solid waste management in any nation
cannot be overemphasized. Control and managementof Leachate generated from waste and its associatedcontaminating effect on groundwater table withrelated public health issues is one of the major
challenges of sanitary landfill design and operation.
Two different design strategies are adopted for
Leachate treatment and control in sanitary landfills,
they are: containment and treatment of Leachate onsite and attenuation through degradation, dilution
and dispersion of Leachate. Containment requiresthat all liquid and gaseous emissions produced
within the landfill are contained and collected fortreatment. The central aim of containment is,therefore, to minimize production of Leachate by
restricting access of rainwater to the waste, and toprevent its migration from the landfill of leachate
produced. This is accomplished by enclosing thewaste in artificial lining systems consisting of alandfill liner and cap. As a consequence, Leachatedrainage systems, containment ponds and leachate
treatment facilities are essential additional
components of modern containment landfills.
Experience has shown that artificial membranes will
eventually leak so modern designs usually include
composite two, three- and four-layer multi-barrier
clay/membrane liner systems. These multi-barriersystems consist of sheets of artificial membrane,most commonly high-density polyethylene, interlayered with natural or bentonite-enriched clay
layers [2], [3]. In the European Union for example,
landfill regulations make it mandatory to entomb
waste using engineered lining systems except at sites
with low in-situ hydraulic conductivity (less than 109 m/s) [4]. Leachate containment with engineered
lining systems requires a suitable geological subbase as a secondary barrier to groundwater whencontainment structures become permeable. Leakage
can result from stress cracking of the membrane,
cracking under cold conditions, damage, particularly
from stones in the protection layer and from heavy
dumping equipment, or failure of the membranes
near welded seams [5]. Synthetic liners are also
susceptible to failure if installation is not subject to578

GEOMATE-Brisbane, Nov. 19-21, 2014

strict quality controls and favourable weather
conditions [6]. Indeed, it is unlikely that any
manufactured synthetic membrane is completely freeof defects even prior to installation [7]. Lastly, somecontaminants are able to diffuse through installed
liners including intact geotextiles [8].
A key attraction of an attenuation strategy is
avoidance of the excessive costs of containment
landfills that are untenable for many developing
countries. It also avoids the long-term costs formaintenance and aftercare monitoring, which may
be required for containment landfills for decades oreven centuries after the site has ceased operating, aslong as the waste remains active. Apart from adrainage system and containment ponds to control
the leachate head in order to prevent shock loadingof the attenuating medium and a monitoring
programme, attenuation landfills have little attendant
costs. The key constraint of the attenuation strategy,
however, is the uncertain but genuine risk ofgroundwater pollution by leachate if attenuation
proves less effective than assumed when selecting
the site or if the site is not adequately managed (e.g.
with respect to drainage measures).
Little attention has been paid to the siting oflandfills. Landfills tend to be located close to urban
areas where significant volumes of municipal andindustrial wastes are produced. It is safest to position
landfills in areas removed from groundwater,
drinking-water supply sources and on sites where theunderlying geology is able to attenuate to somedegree the Leachate that is generated from the stored
wastes. Clay and organic-rich materials (overburden
or mudstone bedrock) are suitable as they both
retard groundwater flow and interact with reactive
contaminants in leachate. Unfortunately, it iscommonly difficult to choose such ideal locations
strictly on the basis of hydro- geologicalconsiderations as socio-economic considerations,
including the ‘not in my back yard’ syndrome, tend
to dominate the process of selection of landfill sites.
[9] notes that landfills and dumps in Africa
commonly occur in poorer areas, where residents areoften less able to prevent landfill siting in their own
backyard, are unlikely to benefit from waste
collection services, and invariably depend upon
local, often poorly protected sources of water.

The attenuation strategy allows leachate tomigrate outwards from the landfill and takes
advantage of the natural subsurface processes ofbiodegradation, filtration, sorption and ion exchange
to attenuate the contaminants in leachate. The
attenuation strategy is based on the dilute anddisperse principle of leachate management proposedby [10]. Natural geological barriers, may be defined
as low permeability clay-rich geological units(hydraulic conductivity <10-5m/s), which canperform the function of an attenuating layer,
enabling leachate to percolate slowly downwards,
simultaneously
undergoing
attenuationbybiodegradation, sorption, filtration and ion exchange
processes with the clays in the unit [11]. Extremely
low permeability geological units (hydraulicconductivity <10-9 m/s) cannot fulfill an attenuation
function as they perform in a similar manner to
artificial or natural lining systems providing almost
complete containment of all emissions. Similarly,
geological units with higher permeability (hydraulicconductivity >10-5 m/s) do not provide sufficientconfinement to leachate and are thus unsuitable forattenuation. The optimum permeability forattenuation is in the order of 10-6 to 10-8 m/s [12]The critical difference between the modern
attenuation approach and the former dilute anddisperse approach is that attenuation is an active
management strategy, requiring the presence of anatural in situ or imported attenuation barrier toattenuate the leachate, whereas dilute and disperse
relied on passive subsurface dilution and dispersion
processes without the presence of a specificattenuation layer. Although the concepts are similar,
it is now recognized that dispersion and dilution
alone may not sufficiently attenuate leachate toadequately protect groundwater. More recent studies
support the conclusion that clay-rich overburden andmud-rocks have the capacity to attenuate Leachate.
The effectiveness of the strategy is further confirmedby the fact that even within geological units ofrelatively high permeability and supposedly poor
attenuation potential, such as sandstone, and sandy
overburden, attenuation processes operate very
effectively, and most pollutants are moderated
within a few hundred metres [7], [13], [14], [15].

MATERIALS AND METHODS

transportation, disposal and street sweeping until
1999 when the Ondo State Waste Management
Authority (OSWMA) was established as a state
government intervention agency. From 1999,
curbside and door-to-door collection using
government supplied storage facilities or dustbins
replaced the communal system. The Government
later acquired 7 hectares (17.3 acres) of land along
Igbatoro Road in Akure for the purpose of
establishing a modern sanitary landfill that will
ensure safe and environmental friendly disposal of

Study Area
Akure is a growing urban area within latitudes 7◦
10ꞌN and 7◦ 20ꞌN and between longitudes 5o 07ꞌE
and 5o 17ꞌE in Ondo State, Nigeria. The mean annual
temperature ranges between 24oC -27oC, while theannual rainfall varies between 1500mm and
3500mm. Initially in Akure, the local government
authority was solely responsible for waste collection,
579

GEOMATE-Brisbane, Nov. 19-21, 2014solid waste generated in Akure and its environs. The
land was cleared for disposal of waste generated in
Akure and its surrounding towns in 2001. Fig. 1

shows the map of Akure and its environs, wherewaste would be generated for disposal in the
proposed sanitary landfill.

Fig. 1 Map of waste generation areas

attenuation landfill. The tests are grouped into threeclasses namely; index property geotechnical tests,geochemical tests, and hydraulic conductivity
evaluation test. The tests were carried out inaccordance with [16] and [17]. Basic geotechnicalcharacterization tests conducted on the soil samples
are; moisture content test, particle size distribution
test, Atterberg’s limit tests and specific gravity test.
Moisture content test was carried out in accordancewith section 2.3 of [15] particle size distribution was
conducted in accordance with section 2.9 of [16]Atterberg,s limit was determined in accordance withsections 2:4 and 2:5 of [16] while, specific gravity
was conducted in accordance with section 2.8 of[16]. Geochemical tests that were conducted on thesoil samples are pH test and Cation Exchange
Capacity (CEC) test; pH test was conducted inaccordance with section 3 of [16] while CEC test
was conducted in accordance with [17]. The pH
values of the soil samples are shown in Table I. PH
is the measurement of acidity or alkalinity of a

Soil Sampling
The soil samples were taken from test pits
covering the specified area of land selected along
Igbatoro road in Akure. The samples were collected
at different depth from a single test pit; at a depth of
1.5m, 2.0m and 3.0m. Samples from 1.5m, 2.0m and3.0m depths of various test pits were grouped
together and labelled as sample 1, sample 2, andsample 3 respectively. Each of the three soil samples
was stored in separate air tight polythene bag topreserve its natural moisture content. They were
thereafter taken to the geotechnical laboratory of theFederal University of Technology Akure, weregeotechnical tests were carried out on them.
Methodology
Tests were carried out to determine the suitabilityof the soil layers from which the samples were taken
for functioning as attenuation layers of an580

GEOMATE-Brisbane, Nov. 19-21, 2014

substance. The exchangeable ions are: Na+, K+,Ca++and Mg++. Permeability test was conducted inaccordance with section 5 of [16].

RESULTS AND DISCUSSION
Basic Geotechnical Characterization Tests

Geochemical Tests

The moisture content for soil samples was foundto be between 7.2% and 17.1 %. The particle size
distribution resulted in percentages passing sieve
Number 200 (0.075 mm) [percentage fines] equal to29.0% for sample 1, 34.8% for sample 2 and 35.8%
for sample 3; hydrometer analysis show that,percentage clay (< 0.002 mm) for sample 1 is 11%;sample 2 has 13% percentage clay and sample 3 has
12% percentage clay; the maximum particle size inthe samples was 2.5 mm. The specific gravity, G S
ranged between 2.58 and 2.62. Liquid limit andplastic limit for sample 1 are 45.0 and 25.9
respectively; sample 2 has liquid limit of 28.0 andplastic limit of 19.8; liquid limit for sample 3 was
36.0 and its plastic limit equals 27.9. The plasticity
index results show sample 1 to be of medium
plasticity, while sample 2 and 3 are of low plasticity.
Although the detailed requirements for anattenuation layer vary, the following criteria usually
apply: Minimum layer thickness of 3m; minimum
clay content of 10%; minimum fines (clay & silt)
content >30%; plasticity index >10% and <65%;
liquid limit < 90% and maximum particle size of
75mm (USEPA) [12]. The percentage clay content
in samples, liquid limit and the maximum particle
size in the soil samples are in consonance withUSEPA requirements for attenuation layer materials,
however plasticity index falls below therequirements for sample 2 and sample 3.

Geochemical tests conducted on the soil samples
are cation exchange capacity (CEC) and pH tests.
The CEC is an expression of the number of cation
absorption per unit weight of soil. It is defined as thesum total of exchangeable cations absorbed,
expressed in milli-equivalents/100g (Meq./100g) ofoven dry soil. The results show an increase in CEC
value with increase in sample depth. Sample 1 hasaverage CEC of 9.02 Meq./100g, sample 2 hasaverage CEC of 9.49 Meq./100g while sample 3 hasaverage CEC of 10.73 Meq./100g; for all
exchangeable ions. The typical CEC for a clayeysoil or soil with considerable clay content is between
6.00 Meq./100g to about 15.00 Meq./100g of soil.
The results of particle size test shows that, sample 1
contain 29.0% of fines, sample 2 contain 34.8% offines while sample 3 contain 35.8% of fines.
Comparing the typical CEC values for clay soil orsoil with considerable clay content with the valuesof CEC obtained for the three soil samples, it can beshown that sample 1, sample 2 and sample 3
contains a considerable amount of clay content,
therefore their CEC values fall within the range ofvalues reported in literature. The ability of naturalsoil layers to attenuate heavy metal contaminants
during the expected life span of the sanitary landfill
is enhanced by the cation exchange capacity. Hence,soil samples; 1, 2 and 3 from the site has enoughchemical strength to withstand the cations occurringin the Leachate. Table I shows the summary ofgeochemical tests. Fig. 2 shows the variation of the
CEC value with clay contents.

Table I Summary of geochemical of soil samples
Samples serial number
Depth in metres% clay content
1
1.5
11
2
2.0
12
3
3.0
13

From Table I, the pH values of the soil samples
increases with depth, the topmost layer has thelowest pH; this may be as a result of previous waste
storage on the site in the past. Sample 3 which iscollected at the deepest depth has the highest pH
value of 7.25, which makes it slightly alkaline, thismeet requirement of soil pH of 7.0 or higher for a

pH values
5.85
6.22
7.25

CEC values (Meq./100g)
9.02
9.49
10.73

sanitary landfill attenuation layer. Since most of the
micro-organisms are developed in the acidic
environment, an alkaline medium create an
unfavorable condition against the growth of the
Leachate producing microbes[17].

581CEC Values with different %Clay Contents

GEOMATE-Brisbane, Nov. 19-21, 2014

14
12
10
8
6
4
2
0

Percentage Clay in Soil Samples
CEC Values
1.5 m

2.0 m

3.0 m

Depth of Sample Collection (metres)

Fig. 2 Variation of CEC values with depth and percentage Clay content.

pH Values with different % ClayContents

Figure 3 show the variation of pH with different
percentage clay content at various sampling depth.
From Fig. 3, pH value of soil samples increases withdepth, the increase may be as a result of higher
concentration of acidic constituents from wasteleachate on the uppermost layer.

14
12
10
8
6

Percentage Clay in Soil Samples

4

pH Values

2
0

1.5 m

2.0 m

3.0 m

Depth of Sample Collection (metres)
Fig. 3 Variation of pH values with percentage clay content
𝒔𝒔𝒔𝒔𝒔𝒔 [18]. Extremely low permeability geologicalunits (hydraulic conductivity<10-9 cm/sec) cannot
fulfill an attenuation function, as they perform in asimilar manner to artificial or natural lining systems,
providing almost complete containment of allemissions. Similarly, geological units with higher
permeability (hydraulic conductivity >10-5 cm/sec
do not provide sufficient confinement to Leachate
and are, thus, unsuitable for attenuation. Table IIshow the variation of the permeability with the clay
content. Figure 4 shows the variation of permeability
with percentage clay content in the soil sample

Hydraulic Conductivity Evaluation Test
The major geotechnical test conducted on soil
samples to assess its attenuation potential was thehydraulic conductivity (coefficient of permeability)
test. Once a soil sample satisfies the permeability
requirement its chemical characteristics should bedetermined to assist in the final decision making
about site selection. The coefficient of permeability(k) for sample 1 was 3.09x10-3cm/sec; k equals
2.22x10-4cm/sec for sample 2 and, k for sample 3
was 2.37x10-3cm/sec. The optimum permeability forattenuation is in the order of 𝟏𝟏𝟏𝟏⁻⁶cm/sec-𝟏𝟏𝟏𝟏⁻⁸𝒄𝒄𝒄𝒄/

582

GEOMATE-Brisbane, Nov. 19-21, 2014

Table II Variation of permeability with clay content
Samples
Permeability% Clay content% Fines

11
12
13

29.0
34.8
35.8

3.09x10-3 cm/sec
2.37x10-3 cm/sec
2.22x10-4cm/sec

1
2
3

Wet Density (kg/m3)
2164.5
1966.2
1926.80.0035Permeability in cm/sec

0.003
0.00250.002
0.00150.001
0.0005
0

10.5

11

11.5

12

12.5

13

13.5

% Clay content
Fig. 4 Graph of permeability against percentage clay content

From the result, the permeability of soil samples
reduces with increasing in clay content. This is inagreement with reduction in permeability value withparticle size reported by [18]. However, there is a
sharp reduction in permeability values of sample 3.
This is because, the sample contain the highest
percentage of silt in addition to highest clay content.
The gradation of a soil and amount of fines it
contain, especially its clay content is a major factor
that determines the value of its permeability.
Permeability test is most important test, in addition
to CEC test used to determine the suitability ofparticular clay materials for construction of sanitary
landfill attenuation layer. Even, if the materials to be
adopted for the siting of an attenuation landfill do
not meet all other criteria; stated in materials
characterization, accurate testing is required todemonstrate that the attenuation landfill will have afield hydraulic conductivity of 𝟏𝟏 × 𝟏𝟏𝟏𝟏⁻ ⁶𝒄𝒄𝒄𝒄/𝒔𝒔𝒔𝒔𝒔𝒔
or less as reported by [12] in addition to a CEC
value ranging between 6 Meq./100g and 15
Meq./100g. From the results, it was discovered thatthe soil is only adequate in CEC but not adequate inpermeability. Hence, in order to use this material for
attenuation purpose the materials can be improved
with addition of little percentage of bentonite or by

overlaying it with other materials of suitable clay
content and permeability.
CONCLUSION
This study evaluated the attenuation potential ofsoil on a proposed sanitary attenuation landfill site.
From the study, the pH, CEC and permeability of thesoil samples collected from the site were carefully
assessed. The results obtained are as follows:
1) The average pH of the soil at 3m below theground surface was 7.25 (slightly alkaline). This issuitable for elimination of leachate producing
microbes from getting into the water table; as most
Leachate producing microbes survive well in acidic
medium than in alkaline medium. The soil above
this level could be removed in the process ofconstruction.
2) The CEC values of the samples collected atvarious depths were found to range between 9.02
Meq./100g and 10.73 Meq./100g which is inagreement with the range of values reported inliterature. This implies that, all the soil samples areof adequate capacity to trap the cation in the leachatefrom contaminating the underground water.

583

GEOMATE-Brisbane, Nov. 19-21, 2014

3) Coefficient of Permeability values of the samples
are in the range of 𝟏𝟏𝟏𝟏⁻⁴𝒄𝒄𝒄𝒄/𝒔𝒔𝒔𝒔𝒔𝒔 to 𝟏𝟏𝟏𝟏−𝟑𝟑 𝒄𝒄𝒄𝒄/𝒔𝒔𝒔𝒔𝒔𝒔
which is inadequate for materials to be adopted asattenuation landfill site. Soils with higher clay
content could be imported and mixed with the in-situ
soil to satisfy the permeability requirement. Anotheroption is the improvement of the in-situ soil withbentonite in order to meet the permeability
requirement.

forward” In Waste Disposal by Landfill, (ed. R.W.
Sarsby), Balkema, Rotterdam, 1993, pp. 167-173.
[9]
Onibokun
AG,“Synthesis
andRecommendations; In Managing the Monster: Urban
waste and governance in Africa”, (eds A.G.
Onibokun), IDRC, Ottawa, 1999, pp. 227-252.
[10] Gray DA, Mather JD, and Harrison IB,“Review of groundwater pollution from waste
disposal sites in England and Wales: with
provisional guidelines, for future site selection”,
Quart. J. Eng. Geol., Vol. 7, 1974, pp. 181-196.
[11] Allen A, “Attenuation: A Cost Effective
Landfill Strategy for Developing Countries”, In
Engineering Geology for Developing Countries.
Proc. 9th Congress of the International Associationof Engineering Geology and the Environment, (eds.
J.L. van Rooy and C.A.Jermy), South African
Institute of Engineering Geology and theEnvironment, Durban, South Africa, 2002, pp. 156167.
[12] USEPA. (US. Environmental Protection
Agency),“Municipal solid waste generation,
recycling, and disposal in United State”,
http://www.epa.gov/osw/nonhaz/municipal/pubs/ms
w06.pdf, April 20, 2008.
[13] Ball JM, and Novella PH, “Coastal Park
landfill: leachate plume migration and attenuation”,
In Proc Sardinia 2003, Ninth International Landfill
Symposium, (eds. T.H. Christensen, R. Cossu, and
R. Stegmann), CISA Publisher, Cagliari.
[14] Butler AP, Brook C, Godley A, Lewin K, andYoung CP, “Attenuation of landfill leachate inunsaturated sandstone”, In Proc. Sardinia 2003,
Ninth International Landfill Symposium, (eds. T.H.
Christensen, R. Cossu and R. Stegmann), CISA
Publisher, Cagliari, 2003.
[15] Williams GM,(1999) “Natural Attenuation ofContaminants in a Lacustrine Sand Aquifer at Villa
Farm, UK”, In Proc. Sardinia 99, SeventhInternational Landfill Symposium, (eds. T.H.
Christensen, R. Cossu and R. Stegmann), CISA
Publisher, Cagliari, Vol. 4, 1999, pp. 229-236.
[16] British Standard Institute: BS1377, “Methods ofTesting for Soils for Civil Engineering purposes”,
British Standard Institute, London, 1990.
[17] ASTM D7503. “Standard Test Method for
Measuring Exchange Complex and Cation Exchange
Capacity of Inorganic Fine-Grained Soils”, Annual
Book of ASTM Standards, in review, ASTM
International, West Conshohocken, PA,2010.
[18] Pichtel J, “Waste Management Practice;
Municipal, Hazardous, and Industrial” Taylor &Francis Group New York, 2005.
[19] ASTM (American Society of Testing andMaterials), “Annual Book of Standards”, WestConshohoken, P A, 1987.

ACKNOWLEDGEMENT
The authors would like to acknowledge thecontributions of Ehinmitan, O. O. and Ajibade, A.
A. in data collection for this work.The equipmentused for this research was made available by the
Department
of
Civil
and
Environmental
Engineering, Federal University of Technology,
Akure, Ondo State, Nigeria.

REFERENCES[1] UNIDO (2008). Millennium Cities Initiative(MCI) Investment Opportunities for Development, p.
7 Vienna, United Nations Industrial Development
Organization (UNIDO)[2]Seymour KJ, “Landfill’s lining for leachate
containment”, J. Instit. Water Environ. Man., Vol. 6,
1992, pp. 389-396.
[3] Cossu R, “The multi-barrier landfill and related
engineering problems”, In Proc. Sardinia 95, Fifth
International Landfill Symposium, (eds. T.H.
Christensen, R. Cossu and R. Stegmann), CISA
Publisher, Cagliari, Vol. 2, 1995, pp. 3-26.
[4] Allen A, “Containment landfills: the myth ofsustainability”, Eng. Geol., Vol. 60, 2001, pp. 3-19.
[5] Rollin A, Mlynarek J, Lafleur J, and Zanescu A,“An investigation of a seven years old HDPE
geomembrane used in a landfill”, In: Proc Sardinia
91, Third International Landfill Symposium, (eds.
T.H. Christensen, R. Cossu and R. Stegmann), CISA
Publisher, Cagliari, 1991, pp. 667-678.
[6] Averesch U, “Specific problems in theconstruction of composite landfill liner systems”, In
Proc. Sardinia 95, Fifth International Landfill
Symposium, (eds. T.H. Christensen, R. Cossu and R.
Stegmann), CISA Publisher, Calgiari, Vol. 2, 1995,
pp. 115-130.
[7] Christensen TH, Cossu R, and Stegmann R,“Principles of landfill barrier systems”, In
Landfilling on Waste: Barriers, (eds. T.H.
Christensen, R. Cossu and R. Stegmann), 1994, pp.
3-10.
[8] Potter HAB, and Yong RN, “Waste disposal bylandfill in Britain: problems, solutions and the way

584

GEOMATE-Brisbane, Nov. 19-21, 2014

SITE REMEDIATION IN NIGERIA: PROVEN AND INNOVATIVETECHNOLOGIES (RECOVERY OF FREE HYDROCARBON FROM
SOIL/GROUNDWATER)
Oluwapelumi O. Ojuri1

Samuel A. Ola1

Olaolu G. Fadugba1

andMicheal A. Uduebor1

1

Department of Civil and Environmental Engineering, Federal University of Technology, Akure, Nigeria

ABSTRACTThis research is concerned with geo-environmental impact assessment and remediation of contaminatedsoil/groundwater. The specific study site is Baruwa community (Latitude 06˚ 35' 12'' N, Longitude 03˚ 16' 21'' E), in
Alimosho Local government area of Lagos state, Nigeria. The estimated 65,000 people of Baruwa own about 350
hand dug wells for domestic water supply; more than 200 of these wells are at present, under lock and key because of
the oil seepage from leaking underground NNPC (Nigerian National Petroleum Corporation) pipeline. The
Geoenvironmental Engineering research group in F.U.T.Akure, started Geoenvironmental site assessment,
geotechnical, background and natural attenuation studies for the site in 2006. This has enabled delineation of thecontaminated zone. Eight (8) hydrocarbon recovery/monitoring wells (W16, W17, W18, W19, W20, W42, W43, andW44) and two bore holes (W401 and W402) were used for the pilot recovery test. Existing contaminated water supply
wells were used as hydrocarbon recovery/monitoring wells to minimize cost. Two boreholes were installed for soil
vapour extracting and gas surveys in addition to the eight existing wells within the 100m x 100m designated pilot test
area. We have already established that water supply wells are covered by pure phase leaking hydrocarbon products
from the underground pipes. Tested well waters had been found to be as much as 95 percent petrol and up to 600 mm
thickness of free hydrocarbon product on top of the ground water. Volumetric characterization of the pure phasehydrocarbon using Oil/Water Interface meter/ areal measurements and monitoring together with assessment ofvarious technologies (Natural Attenuation, In Situ Chemical Oxidation and Bioremediation) for remediation was
implemented for this site.
Keywords: Petroleum hydrocarbon, Volumetric characterization, Remediation, Pilot test, Innovative Technologies
necessitates focus of this study. This is highly relevantin the light of the increasing awareness of the
precarious trend of lack of monitoring and remedial
feasibility data for the subsoil environment in thethousands of gasoline fuel stations, and petroleum
storage/distribution underground infrastructure in
Nigeria. In Nigeria, 335,200 deaths occur annuallyfrom sanitation, water and hygiene related infections,signifying a 16.7% of total deaths from all sources.
This is indicated in the World Health Organization,
country-by-country data on the burden of water,
sanitation and hygiene related deaths globally [4].
There is now an urgent need to scientifically harness
both human and material resources especially in theemerging field of geoenvironmental engineering inorder to meet the target 10 (Halve, by 2015, theproportion of people without sustainable access tosafe drinking water and basic sanitation) of thepertinent Millennium Development Goal (Goal 7 –Ensure Environmental Sustainability).

INTRODUCTION
The Geoenvironmental Engineering researchgroup in Federal University of Technology, Akure(FUTA), started Geoenvironmental site assessment,
geotechnical, background and natural attenuation
studies for the site in 2006. The site is now basicallycharacterized with water table contour maps/directionof groundwater flow, liquid hydrocarbon thickness
contour map, periodic hydrocarbon isoconcentration
maps, periodic geochemical parameter test data andgeotechnical/stratigraphic profiles from geophysicaland geotechnical data [1]. This has enableddelineation of the contaminated zone andidentification of the likely source of hydrocarbon
contamination. Numerical modeling has also beenused to predict a period of about 48 years for thenatural attenuation of hydrocarbon contaminants at
this site [2][3]. The prevalence of the casual handlingof petroleum hydrocarbon storage, distribution anddispensing facilities (underground tanks, pipelines andgasoline stations) in developing countries like Nigeria
585

GEOMATE-Brisbane, Nov. 19-21, 2014

FUTA has a mandate to appropriate technology
for environmental sustainability through effective
management of environmental (air, water and land)
resources in order to have a direct impact on theimmediate community and the country at large.
Effective management of our environmental resources
would certainly contribute to the eradication of
extreme poverty and hunger, and ultimately ensure
environmental sustainability, thereby addressing goals
number one (1) and number seven (7) of the United
Nations’ Millennium Development Goals (MDG) [5].

METHODOLOGY
Description of the Study Area
The case study site is Baruwa community in
Alimosho Local government area of Lagos state(Latitude 6[degrees] 35' N, Longitude 3[degrees] 16'E). The height above the sea level is about 42meters(141 feet). The neighboring towns near thecommunity to the East are Kadara and Akinogun
while Fatode and Oduwale are to the south. It has anabundant rainfall of over 2,000 millimeter per year.
"BARUWA" is a Lagos suburb Community in
Alimosho Local Government Area of Lagos State;
South Western Nigeria (Figure 1a). The community is
located between the famous Iyana Ipaja and Ikotun.
The petroleum hydrocarbon contaminated site isapproximately 940m x 740m in size, within which apilot scheme area of 100m x 100m is
earmarked(Figure1b).

Fig. 1b: Field site (Baruwa, Nigeria) diagram
showing location of free product recovery pilot
test/In-situ remediation demonstration area.
The estimated 65,000 people of Baruwa own
about 350 hand dug wells for domestic water supply
and more than 200 of these wells are at present, underlock and key because of the oil seepage from leaking
underground NNPC (Nigerian National Petroleum
Corporation) pipeline.The Baruwa community is a
predominantly residential setting. Majority of thepeople within this area depend on the groundwater for
their survival. Farming was their main occupation
until civilization and development brought in diverse
infrastructure to the community. This community
suffered from the ruptured pipelines of NNPC/PPMC
between 1994 and 1996. The leakage went unchecked
for several weeks and contaminated the undergroundwater bodies of these areas, polluting wells andboreholes, thus rendering the waters unhealthy for
consumption.
Nigerian
National
Petroleum
Corporation (NNPC's) Pipeline Product Marketing
Company (PPMC's) leaking pipes, running throughthe community from the Mosimi depot in Shagamu,
Ogun State, to the Ejigbo depot in Lagos, had polluted
the entire place, destroying farms and making
cultivation impossible anymore. The Community's
wells had been polluted with no good water available
anywhere in the area for the people. Wells andboreholes were covered by leaking products from thepipes. Tested well waters had been found to be as
much as 95 percent petrol. Baruwa village is just a
few kilometres away from the state capital, Ikeja, but
the authorities have failed to stop the pipeline leakage
in the community. Because of the oil leaks village

Fig.1a. Map of Nigeria showing Lagos thecase study site.

586

GEOMATE-Brisbane, Nov. 19-21, 2014

wells have to be kept under lock and key to prevent a
potential fire disaster.
The method adopted is as follows; use of the
PETROXTRACTOR (Model 8) BELT OIL
SKIMMER (Figure 2a) to remove most of the freepetroleum hydrocarbon product from the wells; Use ofpotassium permanganate (KMnO 4 ) for in-situ
chemical oxidation for the well water together with insitu bioremediation. The above two methods could be
adequate, making it simple and cheap so that it can be
replicated in hundreds of such sites in Nigeria. As acontingency, the equipment for air sparge and soil
vapour extraction system and dual phase extraction
system would be acquired.
There was meeting with the local people tointimate them of the site remediation programme,
followed by demarcation of Pilot Test location andsite reconnaissance/ identification of monitoring wells
and sampling locations for the free product recovery
pilot test. Ten (10) hydrocarbon recovery/monitoring
wells were earmarked for use in the pilot recovery test
(Figure 3). Existing contaminated water supply wells
are being used as hydrocarbon recovery/monitoring
wells to minimize cost. We have already establishedthat water supply wells are covered by pure phaseleaking hydrocarbon products from the undergroundpipes.
Oil/Water Interface meter (Figure 2) was used tomeasure the depth to ground water for earmarked
wells and to measure thickness of free hydrocarbon on
groundwater in water supply wells.
Belt-type oil skimmers use an endless belt ofcorrosion resistant steel or synthetic medium, werelowered into the well to be skimmed. The belt passes
through resilient wiper blades where the oil was
removed from both sides of the medium. The Model 8
Oil Skimmer purchased from Abanaki Corporation
had a belt 200mm wide and 26 m long.

Field Exerimental Programme
Design and Implementation of pilot Test:
There are more than 200 hand dug domestic
water supply wells contaminated with floating
petroleum product of varying thickness (0.20m to
0.65m) at this site. Groundwater is about 25m below
ground surface in the wells. The wells are between
0.75m
and
2.00m
in
diameter.
The
geotechnical/Geoenvironmental research group in
F.U.T.Akure has an inventory of one hundred andsixty seven (167) existing contaminated wells in
Baruwa, Nigeria with well identification numbers andexact location description. Remediation started with apilot scheme area (100m x 100m), with existing 10
wells within the pilot scheme area. Baruwa site islithologically underlain with inter bedded sands,
gravelly sands, silts and clays and reddish lateritic
sandy clays. The lithology is essentially an alternating
sequence of sands and clay layers from the groundsurface to a depth of about 102m (Table 1).
Table 1:- Typical Borehole Log for Study Area
Case> size 0.15-0.200m

G.W.L = 26.55m

LayersDepthsThickness
Description of the strata
(m)
(m)
i.
0.00
3.00
Surface Red Sand
ii.
3.00
7.45
Red and Yellow Clay
iii.
10.45
4.05
Red Clay with Sand
iv.
15.00
1.45
Yellow Coarse Sand
v.
16.45
1.55
Hard with Clay
vi.
18.00
16.45
White Sand with Clay
vii.
34.45
1.55
Black Sand
viii.
36.00
1.20
White Hard Clay
ix.
37.20
2.20
Red Sand
x.
39.00
1.20
Red Sand and Clay
xi.
40.20
1.80
Fine Sand and Yellow Clay
xii.
42.00
3.00
White Sand and Red Clay
xiii.
45.00
3.00
Fine Sand and Yellow Clay
xiv.
48.00
3.00
Casey Clay
xv.
51.00
1.45
Soft Black Clay
xvi.
52.45
4.55
Hard Ash Clay
xvii.
57.00
3.00
Sandy Clayxviii.
60.00
1.80
White Clay
xix.
61.80
4.20
White Fine Sand
xx.
66.00
2.10
Hard White Clay
xxi.
68.10
2.70
Sandy Clay
xxii.
70.80
0.60
Hard White Clayxxiii.
71.40
0.60
Soft Black Clay
xxiv.
72.00
3.00
Hard White Clay
xxv.
75.00
1.90
White Coarse Sand
xxvi.
76.90
1.10
Medium Sand
xxvii.
78.00
3.00
Soft Black Clayxxviii.
81.00
3.18
Medium Sand
xxix.
84.18
2.82
White Coarse Sand
xxx.
87.00
13.90
White Coarse Sand
xxxi.
100.901.10
Gravel mixed with Clayxxxii.
102.00
3.15
White Sand mixed with ClayGWL: Groundwater Level
Total depth drilled =102.00m
Casing size=
0.150 – 0.200m (6" – 8")
Source: Lagos State Water Corporation (2006)

Fig. 2587

Model 122 (CSA) Interface Meter,
P8/LM3/60m (Solinst)

GEOMATE-Brisbane, Nov. 19-21, 2014

It was realized that most compounds had
carried out the filling and sealing up of theirrespective wells. Only three out of the ten wells within
the earmarked pilot test scheme were still opened,others wells had been sealed while some others visited
had been utilized for effluent discharge and refuse.
It was quite disappointing to realize thatmany of them cited losing hope in our coming,
previous “promise and fail” experiences they had had
and the no longer tolerable fume emission from thewells as reasons for embarking on filling and sealing
up the wells. Many of them had carried out deep depth
borehole drilling in their compounds as substitutes forthe filled wells, although they also found the water tobe non-drinkable.

RESULTS/DISCUSSION
Monitoring
After meeting with the local people andestablishing contact with necessary Agencies,
Monitoring and Oil skimming started from Mr.
Shodende’s compound which had a total freehydrocarbon product thickness of 0.52m totaling
about 1.33m3 of Liquid Hydrocarbon. Other wells
monitored within and outside the pilot test area had
between 0.22 to 0.001m of liquid hydrocarbon
The present status of the examined wells
within the pilot scheme area is indicated in Figure 3
and the monitoring test results presented in Table 2
and Figure 4.

Fig 3 Demarcation of Pilot Test location showing state of the earmarked wells for the pilot recovery test

588

GEOMATE-Brisbane, Nov. 19-21, 2014

Table 2: Information from Monitored Wells.
Depth toLiquidSurfaceID
S/N
from
Owners Name
No.
GroundLevel(m)Mr. Adelaja
Mr Adigun
Mr Lala
Mr Nwokolo
Mr Fanawopo
Mr Lasun Faremi
Mr Shodende
Pa Oyewole
Pastor Ogungbangbe
Mr Oguntola
Kamila Street*
Pastor Olorunlugo
Alhaji Saliu
Chief Peter Olawunmi
Late Chief Ajayi

23.54223.45924.03323.46

24.651
0.618
44
0.491
24.179
0.001
0.718
48
Converted to soak-away
Filled with Earth Partially and currently being used for Refuse Collection
24.21624.437
25.25
0.221
0.813
58
Filled with Sand and Sealed with Concrete.
24.49224.49325.487
0.001
0.993
54
23.519
23.52
24.47
0.001
0.95
53
24.02224.05525.842
0.033
1.787
57

24.334

24

DEPTH

24.5

24.449
0.491

0.004
0

0.618

25

24.21624.459

0.001
0.719

0.221

0.001

0.813
0.001

25.5

0.994

24.634

0.033

0.95

1.787

Thickness of water in the wells (m)26.5

Thickness of Liquid Hydrocarbon above water
surface in the wells (m)27Depth to Liquid Surface from Ground Level (m)Fig 4

PA OYEWOLE (41)

24.03
24.69

25.1240.781

26

MR SHODENDE (17)MR LASUN FAREMI (44)

MR FANAWOPO (43)MR NWOKOLO (42)MR LALA (16)MR ADIGUN (18)

MR. ADELAJA (19)

PA SELEM (15)

ALHAJI BARUWA (20)WELL OWNERS NAME

23.5

50

Building Construction Demolished, No Access to Wells.

REPORT FROM MONITORED WELLS

23

49

LATE CHIEF AJAYI

19
18
16
42
43
44
17
41
10
26
35*
22
50
59
53

ElevationofGroundlevel (m)CHIEF PETER OLAWUNMI

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

ALHAJI SALIUPa Selem

PASTOR OLORUNLUGO (44)15

Thickness ofwater in thewells (m)23.72123.72524.5060.004
0.781
Sealed with Concrete Slab Covering, but on accessing has been converted
to soak-away.
Filled with Sand and Sealed with Concrete.
Filled with Sand and Sealed with Concrete.
Filled with Earth and other Materials Partially.
Filled with Earth and other Materials Partially.

KAMILA STREET (35*)

2Thickness of
LiquidHydrocarbon
above water
surface in thewells (m)MR OGUNTOLA

Alhaji Baruwa

Depth toBottomof Wellfrom
GroundLevel(m)PASTOR OGUNGBANGBE (22)

20

Depth
to
Water
in theWell(m)

Reports of all wells monitored showing the various thicknesses of free hydrocarbon product and water

589

GEOMATE-Brisbane, Nov. 19-21, 2014

RecoveryofFree
Soil/Groundwater.”Oil Skimming
The oil skimmer was employed in recovery the freeproduct form the wells were it had been discovered.
Skimming essentially started from the well with thehighest amount of free product discovered (Well 17)
and progressed to others which had just a sheen on thesurface of the water within the wells. The placementof the belt/yoke assembly was adjusted to ensure that
it was within the hydrocarbon product. Samples werecollected at one-hour intervals and analyzed. An
improvised bailer was combined with the oil skimmer
to increase the rate of recovery of free product. At
Well 17, about over 84 Litres of free producthydrocarbon was recovered.

Hydrocarbon

from

REFRENCES[1] Torres, L. G. B.; Climent, M.; Saquelares, J.;
Bandala,E.R.;
Urquiza,G.;
Iturbe,R.,.
Characterization and treatability of a contaminatedsoil from an oil exploration zone. “Int. J. Environ. Sci.
Tech.”, 4 (3), 2007, 311-322.
[2] Clement, T.P.; Truex, M.J.; and Lee; P. A casestudy for demonstrating the application of U.S. EPA’s
monitored natural attenuation screening protocol at ahazardous waste site. “Journal of ContaminantHydrology” 59, No. 1-2, 2002, 133-162.
[3]Ola S.A. ; Ojuri O.O., “The Use of Sand Tank
Experiments to Simulate Field Conditions at theContaminated Baruwa, Site, Nigeria.” International
Journal of Applied Environmental Sciences (IJEAS)
Vol.4 No.3, 2009, 243-265.
[4] Ojuri, O.; Ola, S. A. Estimation of contaminanttransport parameters for a tropical sand in a sand tankmodel. Int. J. Environ. Sci. Tech., 7 (2), 2010, 385394.
[5] Capel, P. D., K. A. McCarthy, and J. E. Barbash.
National, holistic, watershed-scale approach tounderstand the sources, transport, and fate of
agricultural chemicals. J. Environ. Qual. 37(3): 2008.
983–993.

CONCLUSION
With the use of an improvised bailer and measuring
buckets, the bailer was carefully adjusted to fall only
within the free product zone so that minimal amountof water/sludge was obtained in the final collection.
It was realized that within a little above an hour, atotal of 104.5 litres (Free product – 84 Litres, Sludge– 3.1 Litres, Water – 17.4 Litres) of liquid mixture
was bailed out. Bailing was found to be very effective
in collection of free product, with very stringent safetymeasures put in place. Oil Skimming was adopted
alongside bailing to bring the free product to almost
sheen level. Bailing was found to have recovered
more sludge-water mix than the oil skimmer,
recovering about 10% more than the use of the oilskimmer. This is still found satisfactory owing to the
speed of recovery. Recovered Free Product was still
within the 80% range.
Methods employed in recovering free hydrocarbon
product on the pilot test scheme site were found to beeffective in removing free product from thecontaminated wells. Currently, the wells are being
pumped and samples collected before and after eachpumping to determine the extent of contamination in
the water. Other wells would be dug within the area tobe able to access the actual amount of contamination
within the various strata in the formation of the area.
ACKNOWLEDGEMENT
The authors would like to acknowledge the
TETFUND NATIONAL RESEARCH FUND (NRF)
OF THE PROF. S. A. OLA RESEARCH GROUP,FEDERAL UNIVERSITY OF TECHNOLOGY,AKURE, referenced TETF/ES/NRF/013/VOL.I, for
the Research Project titled: “Site Remediation in
Nigeria: Proven and Innovative Technologies,

590

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

A CASE STUDY ON SLOPE REMEDIATION: A GREEN SOLUTION
AND CONSTRUCTION REALITY
1

Elisabeth Simbolon1, Bindumadhava Aery1
Ground Engineering, Aurecon, Brisbane, Australia
ABSTRACTThis paper presents the case study of the remediation work carried out at Blackmans Gap Road, a part of the
Gladstone Regional Council (GRC) road network which was affected by a heavy rainfall event recorded in
December 2010 to January 2011 in Queensland. About 750m section of the road section suffered extensive
damage and a total of three (3) sites along the road were identified as requiring remediation work.
The remediation solution comprised a “sustainable and flexible” system comprising soil reinforcement andsoil nails with flexible facing. This was used successfully in the project, however construction was challenged
by variability of ground condition, despite of consistent results of geotechnical investigations. Design
parameters considered during design and tender assessments by the contractors, which were based on
geotechnical investigations were challenged as variability of ground conditions were encountered during
construction requiring modifications of the remediation solution.
The major challenges in geotechnical engineering commonly arise from uncertainties of the ground condition.
Often, assumptions and rigorous probabilistic analyses made in the design are not sufficient in particularly when
dealing with slope remediation works. An observational approach, monitoring and geotechnical inspections
were proven to be the key ingredients of the successful completion in complex ground conditions.
Keywords: Slope stabilization, Soil nail, Slope stability

INTRODUCTION
Blackmans Gap Road is a part of the Gladstone
Regional Council (GRC) road network whichconnects the Boyne Valley with Miriam Vale andAgnes Water, located in Central Queensland,
Australia. The road is located on a moderately tosteeply sloping hill side at an elevation at least 15m
to 20m above the invert level of the gully.
The roadway is likely to have been constructedby cutting into the steep hill face and side-casting
the excavated material downslope.
Between December 2010 and January 2011, a 1
in 100 year rainfall event was experienced across
Queensland. About 550mm of rainfall was recorded
at Gladstone over this period, causing significant
damage to the road network at the region, includingBlackmans Gap Road.
Approximately 750m of Blackmans Gap Road
had sustained damage due to this event and three (3)sites along the road were identified as requiring
remediation works, funded by the National Disaster
Relief and Recovery Arrangements (NDRRA).
The location of the remediation sites are shownin Figure 1. At the sites, a complete slope failure
has not occurred, however slope instability wasevident from tension cracks that have formed in theroad shoulder. If not remediated, a global failure
could occur with the resultant high safety risk to theroad users.

Site A
Site B
Site C

Fig. 124˚26’32.34”S24˚26’32.02”S24˚26’39.83”S151˚26’3.80”E
151˚26’9.84”E
151˚25’52.45”E








Plan showing site locations[5] (Google Earth, 2010)

GEOTECHNICAL CONDITIONS
The typical geotechnical section at Blackmans
Gap Road is shown in Figure 2, showing a typicalside-cast embankment of fill overlying in-situ rock.
The geological condition underlying the projectsite is dominated by the intrusive igneous rock of theCastletower Granite formation. The granite rockwas evident at the rock cuttings on the uphill slope.
The exposed cut face typically reveals a thin(approximately 1 to 2m thick) residual material
overlying weathered granite.

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GEOMATE- Brisbane, Nov. 19-21, 2014

Visualobservation
duringgeotechnicalinspection indicated the granite to be moderately
weathered, jointed with dip angle of 20 to 30° into
the slope.

water to travel in concentrated flows, eroding aseries of gullies) [3] (NCHRP Synthesis 430, 2012).
A site inspection is considered to be the most
crucial step in understanding the mechanism offailure as the site conditions often tells a “story”.
Some signs or indications of failures that should be
looked for during inspection include:• any development of tension cracks• slumping of materials• leaning trees or road signage• scouring or undercutting• blocked drainage• weak materials and structure orientation, rockoverhanging (for rock cutting)Fill
EW Granite

Cutting Provides Indication or
Residual and Rock Weathering
ProfileFig. 2

The geotechnical/geological engineers should
consider all the signs on site and assess thelikelihood of possible failures and consequences offailures to develop an appropriate remediation
solution.
At this site, approximately 2.5cm to 5cm widelongitudinal tension cracks have developed along theedge of the down-slope, which indicated initiation of
instability of the down-slope batter.
Furthersaturation of the soil, particularly following a heavy
rainfall would lead to a translational slope failure.
The roots of trees and vegetation cover on the batter
slope has assisted in protection of the slope andprevented further slope movement.
While the heavy rainfall was the trigger of
instability, the blocked table drains located at the toeof the up-slope batter were also considered as acontributing factor to saturation of the down-slope
fill.
As the table drains were blocked, thelongitudinal runoff was unable to enter the drainage
structures and resulted in sheet flow across the
roadway and saturation of the down-slope fill.
Figure 3 shows a sketch of the understanding
background of failure.

Typical section at Blackmans Gap Road

The subsurface conditions were investigated bydrilling two (2) boreholes at each site and laboratory
testing which included particle size distribution andAtterberg’s limits of the material.
The geotechnical investigation was scoped tocharacterise the subsurface conditions, inparticularly the extent of fill material and strengthcharacteristics of the subsurface material. The
borehole rig was positioned as close as possible tothe edge of the slope so the approximate extent of
the fill section can be determined. The boreholes
were drilled through the fill material and terminatedin high strength rock material.
Information obtained from boreholes andlaboratory testing indicated that the fill material
consisted of medium dense silty gravel/gravelly siltwith SPT-N values ranging from 10 to 21. The
boreholes also intercepted extremely weathered rockmaterial at approximately 1.5m to 2.5m below theexisting ground level and consistent across the site.
The rock material was also cored using an
NMLC (52mm core barrel) rock coring techniqueuntil high strength, less fractured, moderately toslightly weathered rock was encountered at typically5m depth.

CulvertUNDERSTANDING BACKGROUND OF
FAILURES

Sheet flow

Understanding the mechanism and causes ofslope failure is an important factor to be considered
in developing the remediation solution, but also themost challenging task for geotechnical/geologicalengineers.
Potential causes for slope instability range fromdeep-seated failures (such as with landslides) to
surface erosion (such as when steep slopes cause

Downslope
failureFig. 3592

Failure mode

GEOMATE- Brisbane, Nov. 19-21, 2014

AVAILABLE SLOPE STABILISATIONMETHODSREMEDIATION WORKS DESIGN
Soil Nail with Flexible Facing

As the technology is advancing, a large numberof slope stabilisation techniques are available,
ranging from a) simple solutions of providing
sufficient drainage measures, alteration of the slope
geometry and rebuilding with suitable fill or rockfill
material; to b) the use of slope protection and otherbio-engineering techniques to improve the soil
strength and, c) the use of soil nailing, gravity walland other embedded retaining structures to provide a“force system” to resist instability [2] (Oliphent etal., 2000).
The appropriate treatment approach for a site
depends on the affected area, budget and feasibility.
Although in general perception, the simple solutions
would present a cost effective solution, every site is
unique and it is critical to understand the site, water,
soil and topography as well as the need and extent of
the area to be stabilised before selecting anappropriate slope stabilisation techniques. Siteconditions and constraints can vary greatly, and a“one-size-fits-all” approach is unlikely to work.
Field studies have shown that the combined use ofstructural and vegetative slope protection system ismore cost effective and sustainable than the use ofother methods alone. [3] (NCHRP Synthesis 430,
2012).

To meet the design criteria, particularly thestability FOS, a soil nailing solution with flexible
facing was adopted in the design. Other options
were considered to have higher risks during
construction and to have little benefits to achieve therequired stability FOS due to the steep down-slope
condition and the extent of failure. The main
advantages considered for soil nailing solution
particularly include:• Meeting the required FOS for global stability
failure• Installation can be staged by nailing over a
stabilised area
• Flexible solution• Sustainable
solutionrequiring
minimalexcavation and using local or on-site material as
backfill
Soil nailing is essentially an in-situ groundreinforcement technique which involves installing
closely-spaced steel bars or nails into the slope toprovide reinforcement and strengthening of theexisting ground.
The flexible facing comprised mesh and spike
plates which is sometimes overlooked in design, forthis case also provides an important aspect in thedesign solution. Rigid shotcrete or concrete finishes
were not considered to be acceptable as these types
of facings can potentially crack as a result ofadditional hydrostatic pressure and soil movements
mobilised in the long term. A flexible facing using
high-tensile strength steel mesh will eliminate thepotential of cracking at the face and also provides a“green solution” which blends with the naturalenvironment of the site. The mesh will promote revegetation growth or greening of the slope for an
aesthetically pleasing, natural looking finish.
High tensile, Tecco Mesh product fromGeobrugg was adopted as the flexible facing for thedesign solution. In standard layout, the high-tensile
steel mesh is made of individually twisted 3mm
diameter wire of > 1770N/mm2 tensile strength.
The wire has a resilient coating of aluminium-zinccoating for corrosion protection. The mesh has atensile strength three times greater than traditional
twisted mesh. In combination with soil nails, thewire mesh stabilises any superficial instability (0 to
2m depth). The forces are transferred from the mesh
into the nail which provides global stability for theslope.
In addition to the soil nail system, the existingtable drains were also cleared off debris. Local oron-site materials were used as backfilling materials

DESIGN CONSIDERATIONS AND CRITERIA
Based on discussions with Gladstone Regional
Council, the following design guidelines were used
to undertake remediation design solution:• Reinstatement to pre-failure road width andalignment• Required factor of safety (FOS) of 1.5 for longterm conditions and 1.3 during construction• Sustainability and cost effectiveness of thestabilisation work.
A sustainable slope
stabilisation treatment is one that poses minimal
disturbance to the ecosystem. One way toensure that a project is low cost and sustainable
is to use local or on-site materials.
• Safety to workers and the road users during
construction
Safety to workers and the road users during
construction was the key driver in the developmentof the solution. The narrow road width and steep,
unstable slope imposed the risks of slope instability
and possible collision between the road user andheavy machineries used in construction. Blackmans
Gap Road was closed for two (2) months to ensure
safety to motorists.

593

GEOMATE- Brisbane, Nov. 19-21, 2014

Typical slope stability output is presented in Figure
4.
The design of the soil nail system was carried out
based on two design conditions. The first design
condition considered was the long term condition of
the slope to achieve a target stability FOS of 1.5,
assuming a low groundwater level. A fully saturated
condition was also considered in the design however
this was considered to be a short term condition andtargeted a FOS of 1.3.
Two (2) rows of soil nails were required toachieve FOS requirements. The design required
28mm diameter steel bar with working load of
133kN per nail and installed at 15degrees to thehorizontal and embedded 12m into the EW/HW
granite material to satisfy the bond length
requirement for the design. Table 2 shows the
typical soil nail details used in the project.

to ensure sustainability and cost effectiveness of thesolution.
Development of Design Parameters
Table 1 presents the material parameters used in
the design. The most important properties required
for the analyses were the unit weight and the shear
strength of the material. These parameters were
derived from the in-situ and laboratory testing aswell as using back analysis of the existing slope
profile.
The back analyses were carried out to assess thestrength parameters (friction angle,  ’ and drainedcohesion, c’) by performing stability assessment on
the existing slope geometry. A trial and error
method was carried for a range of likely material
parameters to achieve a factor of safety of 1.0
against slope failure. It was assumed that the factorof safety against global slope instability was at orclose to 1.0 at the time of slope failure.
The back analyses results showed the factor ofsafety was sensitive to the assumed depth of thecritical slip surface and the hydrostatic pressure
applied on the slope. To achieve credible strengthparameters that would model the failure to be used
for design of the remedial works, it was assumed
that the translational failure occurred through the fillmaterial and the slope was fully saturated.
The results obtained from back analysis of thematerial were compared with experience in similar
condition and typical material properties and thecomparison fell within a reasonable range of
expected values.

Table 2 Soil nail details
Item
Length of soil nails
Diameter of soil nail hole
Diameter and type of bar
Working load
Angle to horizontal
Spacing
FacingDesign
12m
150mm
28mm
133kN
15
2m in horizontal –grid pattern
Tecco G65/3 mmTable 1 Geotechnical Design Parameters
Material

Existing
fill

EW
graniteDepth (m)Unit weight, (kN/m3)
Friction angle,
 ’ (degree)
Drainedcohesion,
c’
(kPa)

0-2.5
19

2.5-5
23

MWSW
granite
>5
23

32

33

33

0 to 55 to 25

50
Fig. 4

Typical slope stability output

Dealing
Designwith Geotechnical Uncertainties in

Stability Analysis
Stability assessment was carried out using
Slope/W software, which is a limit equilibrium
program developed by Geostudio. The software iscommonly used in slope stability analysis togenerate potential failure surfaces through a slope
condition and estimate the factor of safety (FOS) for
each generated failure surface. The failure surface
with the lowest FOS is selected as the critical case.

The design requirements and assumptions were
not only documented in a geotechnical design report
but also in the construction drawings andspecifications, with the key points being:• Safety during works
594

GEOMATE- Brisbane, Nov. 19-21, 2014•••

Subsurface conditions
excavation
Installation of soil nails
Foundation conditions

encountered

As the initial excavation progressed, it exposed a
deeper fill extent in between the two borehole
locations which were spaced at 20m. The fact that
there was a great variability of ground condition in
between boreholes was unexpected, considering theextent of the failures and the consistent subsurface
profile obtained from such closely spaced boreholes.

duringA set of hold points, field testing and construction
stages were also presented in the construction
drawings and specifications to enable the criticalparameters to be reviewed during construction.
Safety during construction was considered themost important aspect in design. A safety in design
documentation was created as part of design
documentations to ensure that all the hazards
associated with construction and design wereconsidered.
Contractors input were also obtained during thedesign and tender process. The construction stages
were developed based on discussions that werecarried out with soil nail specialist contractor toensure that the work can be constructed safely.
Potential contractors also carried out a site walkover
to assess the site conditions and define theconstruction
methodology
andappropriate
equipment to be used during construction.

As soon as the issues were encountered,excavation was stopped, as deeper excavation of
unstable fill could result in safety issues andincreased risk of slope instability. A geotechnicalrepresentative inspected the site and carried out
Dynamic Cone Penetratrometer (DCP) testing toassess the extent of the fill material across the site
and in between the boreholes.
The results of the DCP tests were unexpected as
it encountered DCP blows of 5 (in average) down to
5m below the existing ground surface.
Siteinspections also observed a notable amount oforganics and some larger boulder sized particles
which raised further concerns with regards tosuitability of the fill material.
Installation of soil nails also encountered issues
with collapsing holes and jammed casing, causing aslow down in production rate.

CONSTRUCTION OF REMEDIATION
WORKS

Modifications to Remediation Solutions
Issues during Construction
As the construction fell behind from scheduledue to the unforeseen issues encountered during
construction, a decision was made to modify theremediation solution to suit the site condition andbring the construction program on schedule. It wasessential to complete the project as scheduled as
about 20 km of road stretch was closed traffic during
construction period. Any delay in completion would
cause embarrassment to the council.

Construction started with preparation of aworking platform and excavation to the bottom offill material to achieve the required subgrade
foundation conditions. The soil nails were installedfrom the top slope by an excavator with a soil naildrill attached to it – shown in Figure 5 and the Teccomesh was installed following installation of the soil
nails.

The designer reviewed the remediation solution
and the site conditions. Following discussion withthe contractor, a decision was made to remove theunsuitable soil to maximum depth of 4m. The
unsuitable fill was replaced with general fillcomplying with the Main Roads standards. Safety
during construction was managed by performing
excavation in slots and inspection by the contractor’sgeotechnical engineer.

Fig. 5

As a result of this modification, the top rows ofsoil nails were eliminated. Reinforced soil slopewith Geogrid as reinforcement were placed in lieu of
the top soil nails to increase the localized stability at
the face of the downslope. The combined system ofbetter fill, geogrid reinforcement with soil nails also
serves benefits to achieve the required global
stability FOS.

Drilling of soil nails

Eliminating the top rows of soil nails was
effective in bringing the construction on scheduleand budget.

Challenges were faced during construction as aresult of variability of the ground condition.
595

GEOMATE- Brisbane, Nov. 19-21, 2014

construction.
These challenges were overcome and the project
was completed successfully as a result of the highlevel of commitment by all parties: client, consultant
and contractors.
The major challenges in geotechnicalengineering commonly arise from uncertainties of
the ground condition. It is important for the design
to expect variability of the ground condition. The
aspects of geotechnical uncertainties must be
considered not only in the design analyses but also
in tender documentations (such as drawings andspecifications).
The geotechnical uncertainties must be managed
during construction by carrying out monitoring andgeotechnical inspections. A flexible design solutionis also considered to be beneficial. As issues areencountered, the designers must be able to review
the remediation solution and change the design tosuit site condition and construction requirement.
It is also in the opinion of the authors that amajor contributing factor to the successful
completion of the project is the collaboration of allparties involved.

Collaborative Approach
A collaborative approach was establishedbetween the designers, constructors and the principal
to resolve the issues and carry out the work as
effectively as possible and in a timely manner.
As the project progressed, an inherent teamrelationship was developed and it was evident thatthe constructors, the principals and the inspectors
had developed a much better understanding of thetechnical specifics, demonstrating on manyoccasions a greater appreciation for the geotechnicalissues and risks associated with the project.
Despite the challenges that were encountered, thecollaborative approach and commitment of allparties had led to a successful completion of the
project and the road was re-opened on the scheduled
time. The final remediated road at the completion of
construction is shown in Figure 6. The geogrid
reinforcement and soil nails have also performed
well over the period of heavy rainfall in 2013.

ACKNOWLEDGEMENTS
The author would like to acknowledge the
Gladstone Regional Council for providing an
opportunity to design this project and express herappreciation towards the Aurecon team members in
Gladstone and the contractor, the Rix group for theircooperation during the project.
REFERENCES

Fig. 6[1] B. Bindumadhava, ‘Slope stabilization using
grid beam system’, in Proc. 2nd Int. Conf. on
GEOMAT, 2011, pp.5-10[2] Oliphant, J., MacCaffey, R. Apted, R., “Soilslope stabilization methods”, An Int. Conf. on
Geotechnical and Geological Engineering,
Melbourne, Australia, November 2000
[3] Fay, L., Akin, M., Shi, X., “Cost-effective andsustainable road slope stabilization and erosion
control’, NCHRP Synthesis 430, Transportation
Research Board, Washington, DC, 2012
[4] Farrand, S., Teen, A., “Seismically induced
landslide mitigation using flexible slope
stabilization systems”, in Proc. Con. on NZSEE,
2008[5] Google earth website, 2010

Final Remediated Road

CONCLUSIONSIn the presented case study, the soil nailingtechnique combined with geogrid and flexible facing
was concluded to be a feasible slope remediation
solution at Blackmans Gap Road. The techniqueprovided a sustainable, cost effective solution.
Challenges were encountered during construction,
as a result of variability of the ground condition.
Despite of closely spaced boreholes and consistent
geotechnical investigation outcomes, unexpected
ground conditions were still encountered during596

Fourth International Conference on Geotechnique, Construction Materials andEnvironment, Brisbane, Australia, Nov. 19-21, 2014, ISBN: 978-4-9905958-3-8 C3051

AMMONIA REMOVAL CHARACTERISTICS OF POROUS
CONCRETE WITH ZEOLITE FOR ENHANCING SELFPURIFICATION ABILITY IN RIVER SYSTEM
1

Fumitake Nishimura1, Toshio Yamada2, Motohiro Tanaka2, Hirofumi Kassai2 and Michiko Masuda3
Department of Environment Engineering, Kyoto University, Japan; 2Sogo Kaihatsu Co., Inc.; 3Department
of Civil Engineering, Nagoya Institute of Technology, Japan

ABSTRACT
Ammonia removal characteristics of porous concrete with zeolite are investigated. Ammonia is one of thecommon pollutants in river water, and it can cause several adverse impacts for human activities such as watersupply and agricultural purposes. It has negative impacts on water ecosystem as well. Porous concrete withzeolite can adsorb ammonia by zeolite, and biological nitrification and its promotion can be expected because
attached ammonia on the surface of the porous concrete can promote bacterial growth of nitrifying bacteria. It is
expected that both chemical effects (ammonia adsorption) and biological effects (nitrification) can remove
ammonia effectively from river waters when the porous concrete is applied in the river as an artificial riverbed
for example. Experimental discussion is conducted in this study. It was shown that the specific surface area wasincreased by making porous concrete, and the ammonia removal rate can be increased twice as a result. It wasmade clear that chemical effect can be produced in the same level as biological effects as well. It is consideredthat both effects can increase the ammonia removal ability of porous concrete with zeolite effectively.
Keywords: Porous Concrete, Zeolite, Ammonia, Self-purification of riverconducted, and function analysis of porous concrete
from the view point of microbial attachment andpurifying ability of water quality[1],[2]. It wasreported that the microbial densities in porous
concrete were 104 - 103 cells/cm3 of nitrifying
bacteria, 107 - 108 cells/cm3 of aerobic heterotrophic
bacteria, and 107 - 108 cells/gVSS of denitrifying
bacteria, respectively[3].
On the other hand, improvements of purifying
functions of porous concrete have been tried. Oneof the cases is using zeolite partly instead of thecement. Zeolite has cation exchange function, andconcrete materials can have cation exchange
capacity if zeolite is mixed into the concrete.
Zeolite can adsorb NH4+-N especially, which is oneof the major pollutants from human activity,
therefore it is expected that porous concrete in which
zeolite is mixed can have not only biologicalpurification ability but also chemical purification
ability, especially NH4+-N adsorbing ability. The
application example for purification of river water
quality using porous concrete structure with zeolite
have been reported, however most of them is only areport of the application, and detail analyses for
purification of water quality have not been
conducted from the point of microbial attachment,
their activity, and NH4+-N adsorption.
In this study, water purifying ability of porous
concrete were investigated and evaluated throughlab-scale experimental setup. Porous concrete canbe a good attachment media for bacteria which can

INTRODUCTION
Concrete constructs are often used in rivers andsmall channels for river water control and water
utilization. Ordinary concrete constructs have beenused from the points of durability. On the other
hand, environmental functions of rivers attract
attention such as self-purification ability of riverwater, or forming diversified ecosystem surrounding
rivers. River Act was revised in 1997 in Japan andenvironmental functions of rivers have been also
focused as well as river water control (flood control)
and water utilization (water supply). Therefore,
preservation and utilization of the environmental
functions of rivers started being paid more attention.
There are concrete constructs incorporated in theriver, and porous concrete start to be used instead ofordinary concrete because it has wide surface area
and a lot of microorganisms can attach on thesurface which result in enhancing purification abilityof river water quality. Porous property promotes tocatch a lot kinds of materials as well as
microorganisms, which also helps purifying water
quality, therefore purification by porous concrete is
expected and porous concrete start to use for the
purposes. If the purification is widely applied in thearea where sewage system is undeveloped,
pollutants loadings in the catchment area can be
reduced. Setting porous concrete constructs are easycompared with that of construction of seweragesystem.
Therefore, several trials have been597

GEOMATE- Brisbane, Nov. 19-21, 2014

purify river water quality, and the addition of zeolite
to concrete enhance adsorption of NH4+-N, which
can also contribute water purification. It is also
expected that adsorption of NH4+-N on the surface ofthe concrete media increase NH4+-N concentration
which results in the concentrating microorganisms
which use NH4+-N for their metabolism. Namely
the concrete constructs can be a water purifying
system if it can have certain amount of
microorganisms and other functions such as
adsorption of pollutants.
In this study, NH4+-N is focused as one ofpollutants in river water and its removal efficiency
using porous concrete with zeolite was investigatedand evaluated. Several kind of porous concrete aretargeted and effects of its characteristics such as
shape and adding materials on the ability of
purification of water body especially river water isinvestigated.

of zeolite on water purification were investigated.
The experimental condition was summarized inTable 1. These vessels were set in water bath
controlled at 25 °C. Apparent volume ratio ofconcrete pieces to the total volume was 12.5%, andhydraulic retention time (HRT) was set to be 8hrs.
Inorganic artificial wastewater was prepared which
is simulated a polluted river water and the NH4+-N
concentration was set to be 10 mg/L.
The
composition is shown in Table 2. Aeration was
continued in order to maintain aerobic conditions,and aeration was carefully conducted as not to touch
Table 1 Experimental condition of concrete pieces
used in Cases A
Case No. Mixing ratio
Voidageof Ca type
0%
10%
20%
zeolite (%)
Case A-1
0%5
55Case A-2
10%5
55
Case A-3
20%
5
55
Case A-430%
5
55
Case A-550%555MATERIALS AND METHODS
Lab-scale experiments were conducted. Porous
concrete pieces with zeolite were prepared and they
were incorporated in to a vessel as simulated
concrete constructions. Artificial wastewater was
introduced into the vessel and the wastewater was
purified by microorganisms attached on the surfaceof the concrete materials and/or concrete material
itself by its adsorption function. The outline of theexperimental setup is shown in Figure 1. The shapeof each concrete piece is cuboid and its size is
4.9cm×4.9cm×3.2cm in each piece. In the vessel,
three different foam types of concrete piece wereincorporated. One is the ordinary concrete of which
voidage is 0%, and the other two types of concrete
pieces were porous concretes of which voidage is
10% and 20%, respectively. 5 concrete pieces ofeach type were used in a vessel, i.e. 15 concrete
pieces were used in an experimental case. 5
experimental cases were set in which mixing ratio ofzeolite in the concrete piece was different. The
mixing ratio of zeolite in the experimental Cases A
was in a range of 0-50%, and effects of mixing ratio

Table 2 Composition of artificial wastewater
Chemicals
Concentration
NH4Cl
10
mgN/L
NaHCO3107
mgCaCO3/L
KH2PO4
0.1 mgP/L
1
mgMg/LMgSO4･7H2O
Table 3 Experimental condition of concrete pieces
used in Cases B
Case No. Zeolite
Mixing Voidage Voidage
type
ratio of0%20%
zeolite (%)
Case B-1 Fe type0%
2 pieces 2 pieces
10%
2 pieces 2 pieces
20%
2 pieces 2 pieces
50%
2 pieces 2 pieces
Case B-2 Ca type0%
2 pieces 2 pieces
10%
2 pieces 2 pieces
20%
2 pieces 2 pieces
50%
2 pieces 2 pieces
Case B-3 Fe and0%
2 pieces 2 pieces
Ca type
5+5%2 pieces 2 pieces
10+10% 2 pieces 2 pieces
25+25% 2 pieces 2 pieces

Concrete pieces

influent

Table 4 Composition of the concrete pieces (kg/m3)
without zeolitewith zeolite(20%)
Cement322.1kg
234.6kg
zeolite0.0 kg46.9 kgcoarse1535 kg
1535 kg
aggregate
water
70.9 kg
75.1 kg

effluent

reactorFig.1 Schematic diagram of experimental apparatus

598

GEOMATE- Brisbane, Nov. 19-21, 2014

beaker where 300mL of tap water was filled, andthen ultrasonic irradiation was conducted twice for
3min.
After ultrasonic irradiation, remaining
microorganisms was detached from the concrete
piece by pipetting.
Mixed liquor with the biofilm is stirred well andsampled for measurement of both SS and number ofnitrifying bacteria. Measurement methods of FISH
was followed the Amann’s procedure[4]. The
collected
sample was treated with 4%paraformaldehyde immediately and kept under thecondition of 4°C for 2hrs. After that the sample waswashed for three times with PBS buffer. The sample
was preserved under the condition of -20°C after
adding the buffer solution which is the mixed liquidof equivalent amount of both PBS and ethanol.
Hybridization was conducted under 46°C for 2hrs.
Direct counting methods of fluorescing sample wasconducted
withincident-lightfluorescencemicroscope (OLYMPUS BX-FLA, OLYMPUS BX50).
The zeolite mixed in the concrete piece is madefrom coal ash. The coal ash is treated under alkali
condition with NaOH, and then Fe or Ca is added inorder to change zeolite. CEC of the zeolite is 180200 meq/100g, and its particle size is in a range of 5100μm. whereas micro pore diameter is 5-100Å. The
specific surface area is 100-500(m2/g). The
procedure to make porous concrete pieces is asfollows; The coarse aggregate is set in a cement
mixer, and water is added by bits. After mixing,
powder materials(cement and zeolite) are added, andwater start to be added in order to make the surfaceof the coarse aggregate covered by the paste whichis the mixture of the powder materials and water.
Then the mixed material is set into a steel form unit
with using form vibrator. After 1 day waiting,hardening occurs and it is demolded.
The
composition of the concrete pieces (kg/m3) issummarized in Table 4.
For start-up of these experiments, cultivatedsludge with culture media shown in Table 2 wasadded into each reactor in order to attach and grownitrifying bacteria on the surface of the concrete
piece quickly. The sludge itself was originallyobtained from domestic wastewater treatment plant(WWTP).

the concrete pieces directly for preventing unwanted
agitation on the surface of the biofilm. The artificial
wastewater was introduced continuously into thereactor, and growth of biofilm which contains
nitrifying bacteria was investigated. The inside of
the reactor was maintained under complete mixing
condition by the aeration. The continuous reaction
was conducted under the room temperature and after
accomplishing complete nitrification in which NH4+N was completely oxidized to NO3--N, nitrifying
activities were measured by batch experiment. The
concrete pieces with nitrifying biofilm were set in a
glass vessel with the artificial wastewater, andnitrifying activity was calculated by measuring thenitrate or nitrite increasing rate in the vessel. Afterthe measurement, the attached microorganisms weredetached using both ultrasonic homogenizer andpipetting by which concrete piece would not bedamaged, and the detached microorganisms were
measured as VSS.
Experimental Cases B were set in order toinvestigate effects of zeolite type on microbialactivity. In this study, three types of zeolite wereprepared, i.e. Fe type, Ca type, and their mixed
type(Fe + Ca type) were investigated.
Three reactors were prepared. They are operated
continuously like Case A. In each reactor 8 kind of
concrete pieces were incorporated. The types of theconcrete pieces about the voidage are 0 and 20%,and in each porosity types, 4 types of the concrete
pieces about the mixing ratio of zeolite wereprepared, i.e. the value of the ratio was 0, 10, 20, and50%. Two pieces in each type concrete pieces,
totally 16 of concrete piece, were set in a reactor.
Porous concretes with Fe type zeolite was set in areactor and operated as Case B-1. Porous concretes
with Ca type zeolite were used in Case B-2, andPorous concretes with both Fe type zeolite and Ca
type zeolite were used in Case B-3. The detail of theexperimental condition of concrete pieces used in
Cases B is summarized in Table 3. Same as theexperimental Cases A, concrete pieces were tookfrom the reactors in order to measure nitrifying
activity of each concrete piece after complete
nitrification was attained at the reactor.
The
nitrifying activity was measured by batch
experiments and investigated ammonia removal
characteristics in each concrete piece.
500mL of glass beakers were prepared, and the
400 mL of the artificial wastewater used in each
Case was filled. Then a concrete piece was set incarefully in order to submerge it certainly. The
liquid in each batch reactor was stirred by magnetic
stirrer. Samplings were conducted 5 times, i.e. after
0.25, 1.25, 2.75, 4.75 and 7 hrs after the beginningthe batch test. The amount of a liquid sample isdetermined as 10mL.
In order to collectmicroorganisms attached on the surface of theconcrete piece, the piece was submerged in to a

RESULTS AND DISCUSSION
The results of experimental Case A-5 are shown in
Figure 2 for example. Ammonium nitrogen was
easily transformed to nitrite nitrogen, oxidation of
nitrite nitrogen started and ammonia is quickly
oxidized to nitrate nitrogen. And about 40 days after
the start up, similar tendency were observed in theother cases. Apparent specific growth rates arecalculated from the results of continuous treatment
according to the following equation.
599

GEOMATE- Brisbane, Nov. 19-21, 2014

the removal rates among them was not so greaterthan the difference of microbial amount. The
thickness of biofilm became larger as attached

Apparent specific growth rate = [net specific growth
rate: μ (1/day)] - [detachment/death rate: d (1/day)])

12
10(mgN/L)8-6

亜硝酸性窒素NO2 -N
硝酸性窒素
NO3--N

Case
Case A-5
5+

NH4 -N
アンモニア性窒素
T-N
全窒素量

4
2
0
0

20

40

60

80

Time elapsed (days)
Fig. 2. Time course of nitrogenous
compounds (Case A-5)

attached biomass

アンモニア減少速度（mgN/hr)(mgN/hr)

NH4+-N removal rate

付着生物量(mgVSS/担体 )(mgVSS/medium)80

Porosity

70

空隙率0%
0%

60

空隙率10%
10%5020%
空隙率20%

40
30
20
10
0
0.9 0

10

0.8

20

30

40

50

60

人工ゼオライト混入率 (%)

0.7
0.6
0.5
0.4

Porosity

0.3

空隙率0%
0%

0.2

空隙率10%
10%

0.1

20%
空隙率20%

0
0

10

20

30

40

50

60

人工ゼオライト混入率
Mixingratio of artificial(%)
zeolite(%)

Fig. 3. Relationship between zeolite mixing
ratio and attached biomass, or NH4+-N
removal rate
12NH4+-N concentration(mgN/L)The results of apparent specific growth rates of
AOB were 0.330 (1/day) in Case A-1, 0.232(1/day)in Case A-2, 0.297(1/day) in Case A-3, 0.332(1/day)in Case A-4, and 0.363(1/day) in Case A-5,
respectively. On the other hand, these of NOB are
0.338(1/day) in Case A-1, 0.117(1/day) in Case A-2,
0.241(1/day) in Case A-3, 0.157(1/day) in Case A-4,
0.186(1/day) in Case A-5, respectively.
Apparent specific growth rates of nitrifying
bacteria in the cases where concrete piece without
zeolite were used were larger than these in the cases
where the pieces with zeolite are used. The apparent
specific growth rate also seems to become larger
with the increase of zeolite mixing ratio in the cases
the pieces with zeolite are used. However, thetendency was not so clear, and there were not big
difference about nitrification occurrence among theCases A. Generally, NO2--N accumulation is notobserved if ammonia concentration is about 10 mg/L,
however, NO2--N accumulation happened in allcases in this study. The reason is considered that
free ammoniums which can be exist in high ratio
under higher pH conditions. The activity of nitriteoxidation enzyme in NOB can be inhibited by FA[5],and the concentration from which the inhibition startis in a range of 1.0 - 10mgFA-N/L[6][7], in thisexperiment, initial pH value was in a range of 10 11.5, which can inhibit the nitrite oxidation enzyme
in NOB. pK at 25°C is 9.25 and the ratio of FA is ina range of 85-99%, therefore partial nitrification wascaused by higher pH at the surface of concrete
pieces.
Relationship between zeolite containing ratio andbiomass attached on the surface of the concrete
pieces, or reduction rate of NH4+-N are shown in
Figure 3. There are tendency that biomass on thesurface of the concrete pieces increased with theincrease of zeolite containing ratio. It is suggested
that ion exchange capacity and adsorption capacityof NH4+-N can promote the phenomena because
NH4+-N is one of the important substrates, andmicroorganisms themselves were concentrated on
the positive charged surface by zeolite because
microorganisms
arechargednegatively
charged[8][9]. It was also suggested that pH
increase can be suppressed when zeolite was usedinstead of cement which result in avoiding inhibitionof activity of nitrifying bacteria caused by FA
relatively.
Amount of microorganisms attaching to theporous concrete was higher than to the ordinary
concrete. NH4+-N reduction rate per unit concrete
piece was in a range of 0.39 - 0.81mgN/hr, and thevalue was on an increasing trend with an increase of
voidage or mixing ratio of zeolite. The difference of

Mixing ratio of artificial
窒素量（ＡＺ50％，時間別）
zeolite is 50%

10

０～２ｈ
２～４ｈ
４～６ｈ

8
6

６～８ｈ
4
2
0
0

5

10

15

NO3--N concentration (mgN/L)
Fig. 4. NH4+-N removal characteristics
600

20

GEOMATE- Brisbane, Nov. 19-21, 2014

during the batch experiment. NH4+-N removal rateof porous concrete was larger than that of ordinal
concrete, and there were clear tendency that NH4+-N
removal rate becomes larger with the increase ofzeolite mixing rate clearly.
Because the removal rate increase according to
the increase of specific surface area of the concrete
pieces, NH4+-N removal rate of porous concrete canbe increased due to the increase of surface area
where NH4+-N can be concentrated with zeolite,
which can result in enhancement of adsorption of
NH4+-N to zeolite. It is understood that the ratio of
NH4+-N adsorption to total NH4+-N removal rate canbe the same level of that of biological oxidation.
The adsorption of NH4+-N occurred quickly and in
the first stage, therefore it can be expected thatbuffering function can acts effectively against thesudden increase of NH4+-N concentration in waterphase. Clear difference about adsorption function
was not observed between zeolite types.
On the other hand, nitrate generation rate was 0.4-1.6mgN/(L･hr), and the rate of porous concrete washigher than that of normal concrete. There was atendency that the nitrate generation rate increase dwith the increase of zeolite ratio, however thecorrelation is not so clear than the case of ammonia

NH4+-N removal rate
(mgN/(L･hr))
アンモニア除去速度(mgN/(L･/hr))

1.8
1.6
1.4
1.2
1
0.8
0.6
Fe(porous)
Fe(ポーラス)
Fe+Ca(porous)
Fe+Ca(ポーラス)
Ca(porous)
Ca(ポーラス)

0.4
0.2

Fe(ordinary)Fe(普通)
Fe+Ca(ordinary)
Fe+Ca(普通)Ca(ordinary)Ca(普通)

0
0

10

20

30

40

50

Mixing rate of ゼオライト含有率
artificial zeolite(%)(%)
Fig. 5 Relationship between mixing rate ofartificial zeolite and NH4+-N removal rate
1.8

NO3--N generation rate
(mgN/(L･hr))amount of microorganism increased, and microbialactivity inside the biofilm can decrease relatively,
therefore, the difference of microbial activity was
not so large than that of microbial amount.
NH4+-N removal characteristics by the concrete
piece containing zeolite was shown in Figure 4. If
the concrete piece cannot adsorb NH4+-N, the total
concentration of NH4+-N and NOx-N should be 10
mgN/L during the batch experiment and thephenomena is drown as the solid line. However, theresults of the experiment was different and the total
concentration of NH4+-N and NOx-N was lower than
10 mgN/L in the initial stage, which shows that
adsorption of NH4+-N have happened. On the other
hand, biological nitrification progressed and the total
concentration of nitrogenous compounds was
beyond 10mgN/L, which means desorption of NH4+N happens and adsorption ability was regenerated
after 6 hrs from the staring the experiment. Finally,
total concentration becomes 18 mg/L, and it iscalculated that 3.2 mgN of NH4+-N was attached on
the surface of the concrete pieces. The zeolite usedin this study can adsorb NH4+-N and its adsorption
isotherm is expressed as follows.
q = 4.7C0.18
where, q: concentration in solid phase (mgN/gZ)
C: concentration in liquid phase (mgN/L)
The adsorbed amount of NH4+-N is calculable
from the equation because the concrete piece is in
the reactor operated continuously and NH4+-N islittle existed because nitrification occurs before thebatch experiment, therefore adsorbed amount of
NH4+-N was also little, however, it is shown that
attached NH4+-N on the surface of the concrete
pieces can be nitrified and adsorbing capacity can beregenerated. It is suggested concrete pieces withzeolite can remove NH4+-N by both biologicalprocess and physicochemical process, which means
multifunctionalremovalsystemcanbeaccomplished.
Next, the results of Cases B are discussed. About
for 40 days from the beginning, NO2--N was
accumulated, which were similar as the Cases A.
After that, nitrite oxidation started and NO2--N
accumulation was resolved by 60 days from the
beginning. There were not big difference among
Case B-1, Case B-2, and Case B-3 about ammonia
and nitrite oxidation, which means the type ofzeolite have a small impact on these oxidation.
Relationship between mixing ratio of zeolite in
the concrete pieces and ammonium removal rate
obtained from the batch experiment were shown in
Figure 5. And relationship between mixing ratio ofzeolite in the concrete pieces and nitrate generation
rate obtained from the batch experiment were shownin Figure 6, as well. Compete nitrification was
accomplished and nitrite accumulation wasdisappeared when batch tests were conducted.
Therefore nitrite accumulation was not observed

1.6
1.4
1.2
1
0.8
0.6
Fe(porous)

0.4

Fe(ポーラス)
Fe+Ca(porous)
Fe+Ca(ポーラス)
Ca(porous)
Ca(ポーラス)

0.2

Fe(ordinary)Fe(普通)
Fe+Ca(ordinary)
Fe+Ca(普通)Ca(ordinary)Ca(普通)

0
0

10

20

30

40

50

Mixing rate of artificial zeolite(%)
Fig. 6 Relationship between mixing rate ofartificial zeolite and NO3--N generation rate
601

GEOMATE- Brisbane, Nov. 19-21, 2014

removal rate, and the tendency was observes clearlyin the cases of using ordinary concrete comparedwith the cases of porous concrete. The surface areaof porous concrete is wider than the ordinary
concrete and its helps forming of much amount of
biofilms which can purify the river water quality.
Moreover, shape of surface area of porous concrete
can increase amount of microorganisms caught at
porous, that results in the increase of amount of
microorganisms as well. These phenomena result in
the increase of self-purifying ability. As results,
nitrate generation rate becomes twice compared withthe ordinary concrete. There are also tendencies thatnitrate generation rate of concrete piece with Fe typezeolite is larger than that with Ca type zeolite. In
this study, tap water was used for preparing artificial
wastewater, therefore Fe concentration was lower
than Ca concentration in the wastewater. Fe isnecessary for biological oxidation-reduction reaction
because enzymes relating cytochromes uses electrontransfer of Fe. It is suggested that nitrification canbe promoted by the provision of Fe from zeolite[10].
The nitrifying activity attaching concrete piece with
Fe type zeolite was 8.6 mgN/(gMLVSS･hr), whichis almost in the same level as previously reporteddata(4.77 mgN/gTS･hr)[11]. It is shown that using
concrete piece with Fe type zeolite can constitutebiofilm which accomplish enough nitrification atleast.
The density of bacteria attached on the concrete
piece is shown in Figure 7. The number of thebacteria on ordinary concrete in Case B-1 and B-2
was counted in a range from 1010 to 1011 cells byhybridization with probes of Nsm156 and NSR447,
respectively, which suggests that the cell number of
AOB such as Nitrosomonas spp., and NOB such as
Nitrospira sp. were in the same level. In Case B-3,
the number of cells hybridized with probe Nsm156
was around 1010(N), whereas that with probe
NSR447 was around 109(N). The results mean
Nitrosomonas spp. exists in priority to Nitrospira sp.
in the media. However, there were not strong
relationships between nitrification activity anddensity or microbial number of nitrifying bacteria inthis study. There was a tendency that the number ofcells hybridized with probe Nsm156 decreased with
the increase of mixing rate of artificial zeolite(%). It
is suggested that biological activity per unit amountof the nitrifying bacteria was not same. By the way,
the probe NSR447 is suitable for the detection of
Nitorospira which is closely related to Nitrospiramoscoviensis live in freshwater environment. On
the other hand, we can’t obtain clear image in using
NIT3 which is a probe for the detection of
Nitrobacter. It is also suggested that Nitorospira
was dominant as NOB compared with Nitrobacter.
in this research.
Investigation of population
dynamics of microorganisms on the surface ofconcrete media could be important research topics
for next step.
CONCLUSIONSIn this study, ammonia removal characteristics ofporous concrete with zeolite were investigated byconducting experiments. Some results obtained inthis study were summarized as follows.
(1) Concrete pieces containing zeolite can attach
microorganisms effectively and the attached amountof microorganisms can increase with the increase ofzeolite amount in the concrete pieces. Porous shape
can also increase the attaching amount of bacteria.
It is suggested that the porous concrete with zeolite
can attach microorganisms especially nitrifying
bacteria. The concrete piece can adsorb ammonia
and the adsorption ability can be regenerated bybiologically. The applicability and feasibility topreserve water environment, especially river water
quality are suggested.
(2) Nitrification activity of porous concrete with
Fe type zeolite was greater than that with Ca typezeolite. Zeolite type would affect the nitrifying
ability of concrete pieces.
(3) In this study, clear relationship between
nitrifying activity and number of nitrifying bacteria
were not observed. Population dynamics on porous
concrete will be a challenge for the future.
ACKNOWLEDGEMENTS
Acknowledgement: We thank students of water
environment laboratory in Department of Civil andEnvironmental Eng., Ehime University, Japan.

Nsm156
NSR447

1.0E+15

1.0E+14

REFERENCES

1.0E+13[1] Sung-Bum Park, Mang Tia, “An experimental
study on the water-purification properties ofporous concrete”, Cement and Concrete
Research, Vol. 34, Issue 2, Feb. 2004, pp. 177 184.
[2] Taghizadeh, M. M., et al. "Feasibility study ofwater purification using vertical porous concrete

0%
20%
50%

0%
20%
50%

0%
20%
50%

0%
20%
50%

0%
20%
50%

1.0E+120%20%50%Microbial density
菌体密度(N/gSS)(No./gSS)

1.0E+16

CC

PC

CC

PC

CC

PC

Case B-1

Case B-2

Case B-3

CASE

Fig. 7 Density of bacteria attachedon the concrete pieces
602

GEOMATE- Brisbane, Nov. 19-21, 2014

filter." Int J of Environ Sci Technol 4.4, 2007,
pp. 505 - 512.
[3] Tamai, M.: “Adherence of microorganisms onto
the porous concrete and water purification;
Porous concrete”, Ceramics Japan, 33(7),pp.542-545, 1998. (in Japanese)[4] Amann. R. I.: “In situ identification of microorganisms by whole cell hybridization with
rRNA-targeted nucleic acid probes”, Molecular
Microbial Ecology Manual 3.3.6, 1995, pp.1-15,.
[5] Fernández, B., Vilar, A., Ben, M., Kennes, C,
and Veiga,. MC: “Partial nitrification ofwastewater from an aminoplastic resin
producing factory”, Water Sci. Technol, Vol.52,
No.10-11, 2005, pp.517-524.
[6] Yang, L., and Alleman, J.E.: “Investigation ofbatchwise nitrite build-up by an enriched
nitrification culture”, Water Sci. Technol,
Vol.26(5-6), 1992, pp.997-1005.
[7] A.C. Anthonisen, B.C. Loehr, T.B.S. Prakasam,
E.G. Srinath, “Inhibition of nitrification byammonia and nitrous acid. J. of Water Pollut.
Control Fed. Vol.48, 1976, pp. 835-852.

[8] M. Mauret, E. Paul, E. Puech-Costes, M. T.
Maurette and P. Baptiste: “Application ofexperimental research methodology to the studyof nitrification in mixed culture”, Water Sci.
Technol, Vol 34(1-2), 1996, pp. 245–252.
[9] Barbara A. Jucker, Alexander J. B. Zehnder,and Hauke Harms: “Quantification of Polymer
Interactions in Bacterial Adhesion, Interaction
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[10] Darren A.Lytle: “A systematic comparison of
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[11] Onnis-Hayden, Annalisa; Dair, Daniel; Johnson,
Chandler; Schramm, Andreas; Gu, April Z.
Kinetcis and nitrifying populations in nitrogen
removal processes at a full-scale integrated
fixed-film activated sludge (IFAS) plant,
Proceedings of the Water Environment
Federation, WEFTEC 2007.

603

Authors Index

A

B

A. K. Alzoubi

225

B. Look145

A. Oya111

Barry Wai-Choo Kok

256

A.S.M. Abdul Awal

388

Behzad Fatahi

44

Abdul Naser Abdul Ghani

427

Bernat Amat

320

Abdul Saboor Rahmany

500

Bertrand Teodosio

167

Abdull Halim Abdul

566

Bindumadhava Aery

591

Ahmad Hilmy Abdul Hamid

427

Bithin Datta

504

296, 300

Brian Lamb

224

62, 72

Burak Evirgen

Ahmet Tuncan
Aiassa Martinez Gonzalo

296, 300

Akihiro Fujino

528

Burt Look

Akiko Inoue-Kohama

421

C

Akinola Johnson Olarewaju

18

C H Solanki

262

Akio Takigawa

472

C. Sreenivasulu

208

Akula Pavan

140

Celso Romanel

111

Alercia Biga Carolina

72

Chaminda Gallage

Alex M. Lechner

416

Chane Brits

83

Alireza Mohammadinia

340

Che Musa Che Omar

477

Allan Manalo

124

Chee-Ming Chan

129

Alojzy Szymański

196

Chen-Hui Tsai

36

Aminaton Marto30

Chung-Jung Lee

36

Andreas Nataatmadja

179

D

Andrzej Głuchowski

196

Anna Szymczak-Graczyk

520

Arif Ali Baig Moghal

315, 411

151

151, 394

D. F. Marks

202

D. J. Wiliams

145

D. Lacey145

Daisuke Hayasaka

432

Arrúa Pedro

62, 72

Arul Arulrajah

340

Daniel Mellish

145

Athira Ravi

515

Darius Macijauskas

173

Atsushi Fukuda

540

David Lacey

151

Atul Prabhakaran

208

Authors Index

David Thorpe

359, 455

Hailong Chen

406

Debendra Neupane

162

Hajime Narioka

500

Desai A.K.

310

Hamed Koohpayehzadeh Esfahani

504

Devanmini Halwatura

416

Hanna Szymczak

520

Dimiter Alexiew

484

Harada, H.

13

Dr B. Look

365

Hermie M. Del Pilar

334

Dr. Navin C. Shah

238

Hideaki Yasuhara

162

Dr. Sobha Cyrus

191

Hideyuki Ito

540

Duong Minh Truyen

401

Hirofumi Kassai

597

Hiromu Tamba

472

Hirosuke Hirano

557

E
Eberhardt Marcelo

62, 72Elisabeth Simbolon

591

Hiroyuki Ii

Enos C. Inniss

450

Homayoon Ganji

500

Escolástico Aguiar

320

Hooman Abadi

477

Eva Arifi

382

Hossain, M.Z.

13, 289, 293, 388

F
Faizal Pakir, Khairulanam Kasran

30

Francisca Castillo

320

Fumitake Nishimura

597

Fumitake Nishimura

464

528, 534,535, 572

Hossein Mohammad Hosseini

388

Huan Wang406

Hudson Jackson

134

Huu Hung Nguyen

44

Hyun-Suk Shin

167

I

G

Ian P Craig

455

Ikeda H

89

G. G. N. N. Amarakoon

50

Graham Thomson

484

Greg You

95

J

Grzegorz Kmiecik

520

J. N. Kirjan

202

J. Rajaraman

103

J. T. Shahu353

H
H. M. A. Rashid

250

H.H. Bui

111

Jaehun Ahn

167

Hadi Khabbaz

44

Jay Sanjayan

340

Authors Index

Jeroen Berends

256

Kunio Minegishi

540

Jia Xie

256

Kyohei Umemura

66

83, 124, 202, 244

Kyoichi Okamoto

510, 577

Jim Shiau
Jing-Cai Jiang

217

L

Jin-Ung Do

213

L.M. Reddy

353

Jochen Bundschuh

455

L.V. Nuzhdin

267Jose Carlos Solis Tito

111

Le Hong Thia

401

Jothi M. Ramanujam

346

Lei Han406

Jothi Ramanujam

394

Limin Zhang

305

Ju-Hyung Lee

213

Lokanantham R. Logitharan

346

Julian Seidel

10

M

Julius E. Seva

334

M. Boyer

365

Junichi Koseki

185

M. Fujimoto

118

M. I. Ibrahimy

289

K
K. Kawamoto

250

M. I. Ibrahimy

293

K.Chew

365

M. Inanc Onur

296

K.Thiruvenkatasamy

103

M. Inanc Onur

300

Kamarusin Moh Noor

477

M. Z. Hossain

13, 289, 293, 388

Kassim Tarhini

134

M.L. Nuzhdin

267

Katagiri M

89

Maged Almandalawi

95

Kathirgamalingam Somasundaraswaran

346

Mahdi Miri Disfani

340

Kawano M.

89

Makoto Ikeda and Hiroyuki Ii

551

Kazuhiro Oda

66

Manuel Blanco

320

Kazuhito Murakami

421Marian Drusa

283

Keigo Koizumi

66

Maricar A. Ilagan

334

Keiichi Kato

472

Marta Szejnfeld

520

Kim Dowling

95

Martin Silec

256

Kiyoyama T

89

Masaaki Furuno

432

Koichi Ishimatsu

382

Masaaki Kondo

444, 500

Koichi Yamanaka

540Authors Index

Masahiro Yamashita

572

N

Masashi Iwata

524

N. Hiraoka

118

Masayoshi Yamanaka

376

Naoki Kinoshita

162

Mashhor Mansor

401

Nathalie Touze-Foltz

320

Md Zahangir Alam

524

Neelima Satyam D.

157

Md. Monjurul Alam524

Nicholas Hytiris

56

Michael Fraser

56

Nobuyasu Oyama

382

Michal Kuba

283

Nobuyuki Nishimiya

557

Micheal A. Uduebor

585

Nor Zurairahetty Mohd Yunus

30

Michiko Masuda

464

Norimitsu Koike

458

Michiko Masuda

597

Norimitsu Koike

490

Michio Gomyo

421

Noushin Naraghi Araghi

561

Minoru Yamanaka

232

Nursriafitah Kasnon

427

Mitsuhiro Shigeishi

382

O

Mohamed Redha Menani

494

Mohammad Raihanul Islam

376

Mohammed Saedi Jami

524

Mohannad Sabry

95

Mohd Akmal Azri Jamal

30

Mohd Zarar Mohd Jenu

129

Osman El Hussien

77

Mohd. Nawawi

561

Ozumi, S.

13

Monesse Andrea Z. Antonio

334

Moshe Livneh

326

Mosleh Ali Al-Shamrani

411

Mosleh Ali Al-Shamrani

31５

Motohiro Tanaka

597

Muawia A Dafalla

315

Mustafa Tuncan

296

Mustafa Tuncan

300

Myint Win Bo

340

Ohishi K

89

Ojiro C.

13

Okuyama, S.

13

Olaolu G. Fadugba

585

Oluwapelumi O. Ojuri.

273, 578, 585

P
P. Moldrup

250

Pallavi Ravishankar B.

157

Peter Dahlhaus

95Peter K. Adegoke

273

R
R. Fukagawa

118

Rajab M. Abousnina

124

Authors Index

Ramli Bin Nazir

77

Subha Vishnudas

515

Ravin M. Tailor

238

Subhamoy Bhattacharya

208

Rétyce Ivan Hervé Dodji Togbé Amoussou 382

Sung-Ryul Kim

213

ris Aryanto

370

Suresh R Dash

208

Rosli Saad

561

Susumu Kurahashi

Ryota Serizawa

472

Sven Arnold

416

Syed Mustafizur Rahman

561

S
S. M. A. Motakabber

289, 293

458, 490

TS. Narasimha Rao

103

T. Komatsu

250

S. Patel

353

T. Saito.

250

Saki Agatsuma

421

Tadashi Uchiyama

432

Sampei Yamashita

432

Taizo Uchida

432

Samuel A. Ola

585

Takamitsu Kajisa

Sandhya Rao Poleneni

450

Takase E

89

Satoru Ishiguro

376

Takashi Minami

432

Satoru Kawasaki

50

Takashi Nakajima

472

Shingo Tomiyama

551

Takefumi Koreeda

50

Shinichi Ito66

Takeshi Toyama

Shiran Jayakody

394

Takuma Kubohara

534

Shoma Nehashi

540

Tamer Y Elkady

315

Shouquan Wang

406

Teruo Arase

432

Shuai Zhang

305

Teruo Arase

438

Shuichi Hasegawa

232

Tetsuo Okano

438

Shukla S.J

310

Thiruvengadam Tamilmani

140

Slobodan B. Mickovski

56

Tomoaki Hachimura

232

Soichiro Kageyama

551

Toshio Yamada

597

Solanki C.H

310

Tsunataka Furuya

217

Stefan Van Baars

173

Tsutomu Namikawa

24

Stephen Buttling

2

Stephen Darmawan

340444, 500

510, 557

Authors Index

U
Usama Juniansyah Fauzi

185

V
Veena. V.

191

Vlastimil Chebeň

283

W
Waleed M Zahid

411

Weena Lokuge

124

Wen-Yi Hung

36

Wojciech Sas

196

X
Xuyin Yuan

406

Y
Yamamoto S

89

Yasuji Shinohara

370

Yi-Chun Tu

36

Yohei Usuki

66

Yoshifuku T

89

Youhei Takanabe

382

Z
Zakaria Hossain

13, 289, 293, 388

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Geotechnique
Developments of geosynthetic-reinforced soil technology in Japan: retaining walls and bridge
abutments
Fumio Tatsuoka

3

Seepage-deformation coupled numerical analysis of unsaturated river embankment using anelasto-plastic model
F. Oka, S.Kimoto and R.Kato

15

Progressive failure of shallow anchor in dense sand evaluated by 2D and 3D finite element
analysis and model tests
T. Sakai and M. Rokonuzzaman

23

Design of single pile foundations using the mechanics of unsaturated soils
Vanapalli S. and Taylan Z.N.

31

Problematic soil: in search for solution
Bujang B.K. Huat

39

Characterization and modeling of various aspects of pre-failure deformation of clayey
geomaterials – fundamental theories and analyses
J.N. Mukabi

47

The maintenance of ground anchors in Nippon Expressway
Yuu Fujiwara and Toshinori Sakai

57

Stress distribution in khon kaen loess under spread footing
Pairoj Yodsa-nga and Watcharin Gasaluck

61

The effect of sheet pile length on the capacity of improved pile foundation on sand undervertical and moment loading
Tuan Van Nguyen and Pongsakorn Punrattanasin

65

Investigation of a reliable reinforcing method for embankment ground
H. M. Shahin, T. Nakai, M. Kikumoto, R. Sakai, Y. Yoshida, I. Saito, N. Nagao and K. Toda

71

Evaluation of stamps and latex shell influence on stabilometer testing results, modeled withsimulia abaqus
Dmitriy Volik

77

Characterizing the interaction of geomat with fine grained black cotton soils
Wekesa S., Mukabi J. , Okado J., Kogi S., Ndeda M. and Ogallo J.

81

Soil liquefaction susceptibility zoning due to earthquake using GIS and geotechnical data
Bhuyan Md. Habibullah, Rama Mohan Pokhrel, Jiro Kuwano and Shinya Tachibana

87

Evaluation on the results of multistage shear test
Hormdee D. and Kaikeerati N.

93

Verification of effects of countermeasures for seepage of river levees by on-site monitoring of
the water level of levees
Hiroyuki Masuyama, Yukiko Saito, Masanori Ishihara, Tetsuya Sasaki and Hirotoshi Mori

97

Influence of decreasing of soil suction on unconfined compressive strength for bentonite
Tomoyoshi Nishimura

103

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)The relationship between soil suction and the maximum unsaturated undrained shear
strengths of compacted khon kaen soil
R. Nuntasarn and W. Wannakul

107

Interpretation of coaxial and non-coaxial strain on directional variation of undrained strength ofclay
J.Rajaraman and K. Thiruvenkatasamy

113

FEM analysis of innovative shallow foundation system for reactive soils
Mostafa A. Ismail and Mohamed A. Shahin

117

Delay times of elastic waves at discontinuities in laminated specimens
Yota Togashi, Kazuo Tani, Tetsuji Okada and Hiroaki Sato

123

Geotechnical investigation of valleys using lightweight dynamic cone penetration test forlandslide risk assessment
Takashi Hanaoka, Takashi Tsuchida, Shoichi Kawabata and Shota Nakagawa

129

Study on individual landslide risk assessment of natural valleys and slopes during heavy rain
based on geotechnical investigation and analysis
Shouichi Kawabata, Takashi Tsuchida, Takashi Hanaoka and Shouta Nakagawa

135

Analyses of piping under foundation of weirs in different ground density by FEM
Okajima Kenji141

Shear deformation and failure of sandy slope according to pore pressure generation due torainfall infiltration
Katsuo Sasahara and Naoki Sakai

147

Load settlement relationships of circular footing considering dilatancy characteristics of sand
Yusuke Tomita, Tatsuaki Nishigata, Takeshi Masui and Shintaro Yao

153

Thermally modifying bentonite for construction industry
Abdoullah Namdar

159

Mesh-free analysis of beam on elastic foundation
S. M. Binesh

163

Frictional Performance Of Infilled I-Blocks With Geosynthetic Inclusions
Faisal Hj Ali, Md. Zahidul Islam Bhuiyan, Firas A. Salman and Siau Lian San

167

Varying ground water level to minimise liquefaction hazards in urban areas
Heitor A., Oka F., Kimoto S. and Higo Y.

173

Development of a new type reinforced soil wall
Hara T., Tsuji S., Yoshida M., Ito S. and Sawada K.

177

Development of design charts for reinforced embankment using excel spreadsheet slope
stability analysis
Ito Kazuki, Md. Zakaria Hossain and Toshinori Sakai

183

Numerical simulation of 2D crack growth with frictional contact in brittle materials
Kai Zhang, Jing-cai Jiang and Qing Yang

187

Interface behaviour of basalt geosynthetic with sand in direct shear mode
M.B. Hossain, M.Z. Hossain and T. Sakai

191

Effect of soil parameter uncertainty on seismic response of buried segmented pipeline
Chaminda Gallage, Pathmanathan Rajeev and Jayantha Kodikara

197

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)The sorption capacity of cu by sc-soil from batch and column tests
Arwut Yimtae, Pongsakorn Punrattanasin and Noppadol Sangiumsak

203

Construction materials
Green construction: the role of palm oil fuel ash in concrete
A.S.M. Abdul Awal

211

Behavior of collapsible loessic soil after interparticle cementation
Arrua Pedro, Aiassa Gonzalo, Eberhardt Marcelo and Claverie Eliana

221

A study on hardened soil brick using liquid type and powder type hardening agent
Jin Sung Ki., Jung Seung Yong. and Kim Tae Ho.

227

The effect of salt content in soil on the sorption capacity of heavy metals
Lerd Kerdchaiyaphum and Pongsakorn Punrattanasin

233

Manufacture of Housing Construction Materials with Jute Polymer Composite (Jutin)
Mubarak A. Khan, Fahmida Parvin, Jahid M M Islam and Md. Zakaria Hossain

239

Evaluation of strength of granulated construction waste sludge with quick lime and its
application to soil structure
Makoto Kobayashi, Hiroaki Nakamura and Hideaki Mizuno

245

Analysis of enhanced strength and deformation resistance of some tropical geomaterials
through application of in-situ based stabilization techniques
Kogi S., Ndeda M., Mukabi J.N. and Wekesa S.

251

Further developments in the swelling model of expansive clays under ASTM 4546 and CBR
testing
Moshe Livneh

257

The effect of clay, lime and rice husk ash contents on the sorption capacity of Cu, Ni and Zn by
Soils
Pongsakorn Punrattanasin and Noppadol Sanggiumsak

263

The effect of temperature on the sorption capacity of copper by soils
Noppadol Sangiumsak and Pongsakorn Punrattanasin

269

Experimental Investigation for Nitrate Reduction Using Iron Powder in Porous MediaHaruka Shimada, Kazuya Inoue, Ikko Ihara, Katsutoshi Suzuki and Tsutomu Tanaka

275

Using spatial moments in conjunction with image processing to estimate macrodispersion in
stratified porous formations
Katsutoshi Suzuki, Kazuya Inoue, Tsutomu Tanaka and Akira Kobayashi

281

The novel technology of desertification control and ecological restoration with an Hydrolysis
Polyurethane(W-OH)
Weimin Gao, Zhiren Wu, Zhishen Wu, Kentaro Iwashita, Hirondo Inagaki and Caiqian Yang

287

Migration of radioactive materials through porous media: theory and a solution for an unsteadystate problem
Khaled I. Hamza

293

Fundamental study on ecosystem support canal using porous concrete
Masuma Yoshihiro, Hasegawa Yuki, Md.Rokunuzzaman, Yamada Toshio,Kassai Hirofumi and
Sato Shushi

299

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Alternative employment of crushed shell particles in capillary barrier of soil
Satoru Nakafusa, Kaoru Kobayashi, Toshihiro Morii,Tomoyoshi Nishimura

305

A novel statistical approach for investigating the significant factors that influence theperformance score of the Turkish method
Kshama Sundar Roy, Kamrul Islam and Md. Shams Arafat

311

Ultimate strength and fatigue life of concrete structural elements reinforced with carbon fiber
sheet
Hidenori Tanaka and Yutaka Toi

317

Development of functional carbon nanotubes -asphalt composites
Tatsuo Shirakawa, Akio Tada and Noriyasu Okazaki

323

Hydraulic character of estimation method on roughness coefficient of concrete canal
Koichiro Otagaki, Koji Sai,Kenichi Fujisawa, Shinsuke Matsumoto and Shushi Sato329

Na-bentonite as rock containment barrier against heavy metals and acid leachates
Angelica Naka, Takeshi Katsumi, Toru Inui, Giancarlo Flores and Takehiro Ohta

333

The comparison of monotonic behaviors of two different calcareous sands
R. Rezvani, H. Shahnazari, H. Salehzadeh and Y. Dehnavi

337

Soaking effect on strength and performance of fine grained soil stabilized with recycled
gypsumAly Ahmed, Keizo Ugai and Taira Jinno

343

Removal of Zinc in soils using natural zeolite
Wiparat Nisapai , Arthit Neramittagapong and Sutasinee Neramittagapong

349

Heat control of pavement surface temperature using oyster shell lime
Satoru Ishiguro and Masayoshi Yamanaka

353

Buckling behavior of composite triangular plates
T.Farsadi, P.Amani and E.Heydarnia

357

Durability of cement treated highway materials
Jiraroth Sukolrat, Apisit Klummeng and Sekchai Anuvechsirikiat

365

Porous geopolymer concrete
Tawatchai Tho-in, Vanchai Sata and Prinya Chindaprasirt

371

Design and Fabrication of Composite Technology for Earth Slope Protection
Md. Toriqul Islam, Md. Zakaria Hossain and Masaaki Ishida375

Study of slump testing for hydraulic plastic grout
Hiroyasu Ishii, Kenichi Horikoshi and Masaki Kitazume381

Behavioral comparison of coarse aggregate from various quarry sites of pakistan, effect on
hardened concrete, economics and environment
Faisal Malik and S. Muhammad Jamil

387

Methods for execution of concrete piles in corrosive and destructive marine environments,
based on study of the Persian Gulf marine installations
Nasser Arafati, Abdol Hossein Fazli and Seyed Mehdi Mousavi

393

Fundamental study on particle size distribution of coarse materials by image analysis
G.H.A.J.J. Kumara, K. Hayano and K. Ogiwara

399

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Environment
Calibration and simulation of runoff models for developing watershed respond knowledge at
tropical area
Arien Heryansyah and Zulkifli Yusop

407

Effect of geological succession on macrophyte and microbiota in aquifer ecosystem in urban
coastal zone
Kazuhito Murakami and Akiko Inoue-Koham

411

Bioclean and liquid biofertilizers a new way to the green area
Sittisak Uparivong

417

Massive point cloud acquisition on a soil surface using a stereo camera
Masafumi Nakagawa, Anna Nakanishi, Hirotaka Endo and Kenta Ochiai

421

Estimation of earthquake ground motion in Padang, Indonesia
Rusnardi Rahmat Putra, J. Kiyono and Y. Ono

425

Groundwater contamination due to irrigation of treated sewage effluent in the werribee delta
Hiroyuki Ii, Masanobu Taniguchi, Ataru Satoh, Graeme Allinson, Matt Kitching, George
Croatto and Bruce Shelley

431

Process of invading the alien plant species into the river ecosystem
Michiko Masuda, Yumie Ito and Fumitake Nishimura

437

Recent meandering pattern of the Irrawaddy, Myanmar
Mayumi Matsumoto and Shigeko Haruyama

443

Physical and chemical properties of tsunami deposit in northeast area in Fukushima prefecture
after Tohoku-Kanto earthquake
Tomonori Fujikawa, Hiromu Okazawa, Takahiko Nakamura, Yasushi Takeuchi and Masaharu
Komamura

447

Changes of bottom sediment caused by Construction of the Airport Island in the Ise Bay, Japan.
Maki Oyagi, Motohiro Kawase and Akihiko Yagi

453

Proposal of simple measurement method for evaporation rate by using oxygen isotopic ratio in
the inawashiro lake
Satoshi Miyahara and Hiroyuki Ii

457

Landslide susceptibility mapping using logistic regression model with neighborhood analysis:
a case study in mizunami city
Wang Liangjie, Sawada Kazuhide and Moriguchi Shuji463

The evaluation of the river environment and water quality by image analysis in the YamatoRiver Basin in Japan
Masanobu Taniguchi, Hiroyuki Ii and Tatemasa Hirata

469

Distribution of oxygen and hydrogen stable isotopic ratios and estimation of the spring waterorigin in the Kushiro Moor
Natsuki Kawabe and Hiroyuki Ii

473

A debris flow and its risk analysis related to the 2008 Wenchuan earthquake
Yange Li, Guangqi Chen, Chuan Tang and Lu Zheng

479

Impact analysis of water price reform of Zhangye, China
Atsushi Koike, Zhongmin Xu, Kang Wang and Bunei Itoga

485

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Post earthquake rapid inspection planning for bridges in western Kentucky
Norimitsu Koike and Issam E. Harik

491

Organophosphoric acid triesters from landfill sites and sewage plants in Japan
Haruki Shimazu

497

Ground water pollution around the Oyachi-Heizu district of Yokkaichi city
Yukimasa Takemoto, Masaaki Takahashi, Kayoko Awaya, Mikihiro Ioka and Peng Guo

501

Characteristics of damage to structures induced by the tsunami of the 2011 east Japan megaearthquakeÖmer Aydan, Hisataka Tano and Takahiro Iwatate

505

Characteristics of strong motions induced by the 2011 east Japan mega earthquake with anemphasis on Tokyo bay area
Takahiro Iwatate, and Ömer Aydan

511

Inquiry of the value of parks in the characteristics and use of park planning through urban
revival planning projects in Maebashi city
Shinya Tsukada, Tetsuo Morita and Akira Yuzawa

517

A study on evaluation of quality of life in consideration of water/green environment
Tetsuo Morita, Yoshihito Kogure, Hiroshi Sugita, Tsuyoshi Baba, Shinya Tsukada and Naoki
Miyazato

521

Changes and issues in green space planning in the tokyo metropolitan area: focusing on the"capital region plan"
Tetsuo Morita, Yoshihide Nakagawa, Akinori Morimoto, Masateru Maruyama and Yoshimi
Hosokawa

527

Application of traffic simulation in road policy assessment accompanied by railway elevation
Maekawa Takuya and Hiroshi Inouye

533

Impact estimation of land cover changes of recharge area on spring discharge in marshy
environment
Masaaki Kondo and Takamitsu Kajisa

541

Numerical Study on Characteristics of Levee Breach Flood Disasters in Alluvial Floodplain
Md. Serazul Islam and Tetsuro Tsujimoto

547

Purification system of ocean sludge by activating microorganisms
Kyoichi Okamoto, Kenji Hotta, Takeshi Toyama and Hideki Kohno

553

Author index

559

Volume 2
Characterization and modeling of various aspects of pre-failure deformation of clayey
geomaterials – applications in modeling
J.N. Mukabi and M.Z. Hossain
An emergency medical care information system for fetal monitoring
Muhammad Ibn Ibrahimy
Effects of gypsum on the swelling and dispersion behaviour of fine grained soils from Sudan
Abdul Karim, M. Zein and Ahmed M. Elsharief

563

573

577

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Comparison of bearing capacity equations for vertical central loading
Muhammad Awais Shafique and Tanvir Iqbal Qayyum

583

Pull-out resistance of selected native plants in Hong Kong
Leung F.T.Y., Yan W.M., Tham L.G. and Hau B.C.H.

589

Inland navigation in carrying injured and sick disaster victims in case of a massive earthquake
in the Tokyo metropolitan area
Kazuya Egami, Keiichi Noto, Wataru Miyazaki, Kazukiyo Yamamoto and Takeo Kondo

593

Model calculation and geotechnical interpretation of the correlation co-efficient between finite
and incremental strain path of a formation
J.Rajaraman and K. Thiruvenkatasamy

597

Geocell reinforced bed subjected to simulated traffic loads
P. Sharifi, and S.N. Moghaddas Tafreshi

601

Effects of gradation of various sand deposits of Pakistan on strength of hardened concrete
Gauhar Sabih and S. Muhammad Jamil

607
613

Strengthening of landslide retaining pile wall after geodetic monitoring
Frangov G., Zayakova H., and Hamova M.

Response of tapered piles under lateral harmonic vibrations
Ahmad Dehghanpoor and Mahmoud Ghazavi
Investigation of ground movement in soil-nailed walls using 1g models and PIV method
H. Mahdavi, and M. Hajialilue-Bonab

627

623

629
Author Index

Contents of GEOMATE2012 - Volume 2(1)ID Keynote Papers
1

Use of microbial technology in geotechnical engineering
Jian Chu, Volodymyr Ivanov, Jia He and Viktor Stabnikov

1-4

2

A study on slow moving slopes
L G Tham and Xu Kai

5-11

3

Bearing capacity and settlement behaviour of shallow foundations in unsaturated
sands
Sai K. Vanapalli and Fathi M. O. Mohamed

12-21

4

Development of Piled Geo-wall
Hara, T., Tsuji, S., Yoshida, M. and Sawada, K.

22-29

5

Measurement of strain distribution along precast driven pile during full scale pileload test
Faisal Ali and Lee Sieng Kai

30-39

6

Unique grouting material composed of calcium phosphate compounds
S. Kawasaki and M. Akiyama

40-46

7

Stiffness Anisotropy and Resilient Modulus of an Unsaturated Soil under Static andCyclic loads
Charles W.W. Ng, C. Zhou and J. Xu

47-62

8

Nanoparticles for Geotechnical Engineering
Mohd Raihan Taha

63-68

Technical Papers
Geotechnique69

24

Damage Assessment and Strengthening of R/C Building Constructed on Expansive
Soils
Osama M. A. Daoud

70-75

29

Gravitational Sphere Packing Method To Find The Porosity Of The Soil Particles
With The Identical Size in cylindrical container
Mohammad Mahdi Roozbahani , Bujang B. K. Huat, Afshin Asadi

76-78

34

Parametric Study of Piled Raft Foundations to improve the Design Method
Tohidi A., MH .Sadagiani

79-84

39

Experimental Study of Suction-Monitored CBR test on Sand-Kaolin Clay Mixture
Purwana, Y.M., Nikraz H., and Jitsangiam P.

85-90

41

Foundation Strengthening of Historic Buildings by Micropiles
Azza M. Elleboudy

91-96

Contents of GEOMATE2012 - Volume 2(1)44Group effects of piles due to lateral soil movement
Hongyu Qin1 and Wei Dong Guo

97-10245

Collapse-Settlement Calculations for Embankments Based on a Collapsible Soil
Subgrade
Moshe Livneh

103-108

46

The influence of trench soil properties on the accuracy of pressure cellmeasurements in an earthfill dam
D. Elmi, A. A. Mirghasemi

109-11250

Studying the effects of considering dilation angle over the performance ofgeotechnical elements using numerical methods
Salman Hanifi, Amin Naeimabadi , Mohammad Reza Atrchian113-11750aComparing the excavating effect of single and twin tunnels on the earth surface
settlement by numerical methods
Amin Naeimabadi, Salman Hanifi , Mohammad Reza Atrchian

118-124

107

Excess Pore Pressure Characteristics of Sand Mat using Dredged Soil
M.S LEE, K. ODA

125-130

110

Effect of clays fraction to california bearing ratio laboratory test value with andwithout soaked
Soewignjo Agus NUGROHO, Syawal Satibi and Ferry Fatnanta131-136

111

Compressibility Characteristics of Residual Soil Subjected to Microbial Treatment
Lee Min Lee, Ng Wei Soon, and Yasuo Tanaka

137-140

115

Strength and aging of cement treated low plastic soils
Fabien Szymkiewicz, Antoine Guimond-Barrett, Alain Le Kouby

141-145

119

Performance Of Cantilever Sheet Pile Supporting Excavation Adjacent To Strip
Footing
Yousry M. Mowafe, Ahmed M. Eltohamy and Ahmed A. Mohamed

146-153

119a

Enhancing Stability of Slopes with Cement Kilin Dust Sand Mixture Layer
Al Serif M. Abd Alazez1, Ahmed M. Eltohamy and Ahmed Rusdy Towfek

154-161122

The effect of confining stress on the analysis of excavations with adjacent existingbuildings
Sabzi Zahra, Fakher Ali

162-166

125

Bored Pile Socket in Erratic Phyllite of Tuang Formation
D.E.L. Ong

167-171

133

Swelling deformation of the bentonite mixed with silica fume or sodium carbonate
in calcium hydroxide solution
Yuki YOKOYAMA and Kenichiro Nakarai

172-175

136

A Combined Probabilistic Method for Engineering Failure analyses andApplications in Typical Geotechnical Structures
Duruo Huang

176-181137

Parametric Study of Crossing Tunnels at Different Level
A. Tohidi, MH.Sadagiani

182-189

143

Use of post-floatation copper tailings in the construction of dump dams
Tschuschke W., Wierzbicki J.

190-195

Contents of GEOMATE2012 - Volume 2(1)150

Effects of Slope Inclination on the Rain-induced Instability of Embankment Slopes
Chaminda Gallage, Shiran Jayakody and Taro Uchimura

196-201

225

Extension of an integrated AHP and TOPSIS approach in the earth dam site
selection
Minatour Yasser, Khazaie Jahangir

202-208

227

Using Geogrid Boxes as a New Approach for Reinforcement of Rock Slopes
Ahmad Fahimifar, Arvin Abdolmaleki

209-214228

Volume Change Characteristics of Clay Mixes with Different Bentonite Percentages
J. M. Kate, Sunil Kumar, M. P. Bhorkar

215-218236

FE Analysis for Settlement of Peat Ground under Embankment Loading
Satoshi Nishimoto and Hirochika Hayashi

219-224

237

Seismic behavior of pile group in soil slopes: 1g shake table tests
H. Elahi, M. Moradi,A. Ghalandarzadeh and A. Elahi

225-229

239

Electrophoresis of Bacteria and Electro-Biogrouting
Hamed A. Keykha, Bujang B. K. Huat, Afshin Asadi, Satoru Kawasaki

230-232240

Consideration concerning reasonable modified form of Floating-type Improved
GroundHijiri Hashimoto, Satoshi Nishimoto and Hirochika Hayashi

233-236

241

Numerical Study Effect of Nail Angle Change on Stability and Displacement of
Excavation Wall in Cohesive and Cemented Non-Cohesive Soils
Navid Shahnazi, Jahangir Khazaie, Mohamad Sharifipour and Kiarash Ashtari237-241242

An investigation on behavior of geogrid reinforced soil retaining walls applying
finite difference method (F.D.M)
Jahangir Khazaie and Alireza Sadeghabadi242-252

243

Effects of humic acid and salt additives on the behaviour of lime-stabilised organic
clay.
N.Z. Mohd Yunus, D. Wanatowski, and L.R. Stace

253-256

244

Sodium Tripolyphosphate For Stabilizing Of Contaminated Soil
Amin Falamaki ,Hossein Tavallali and Shahrbanoo Rezanejad Farahmand257-260

246

Evaluation of Soil Water Characteristic Curves for Sand-Expansive Clay Mixture
T. Y. Elkady, M. A. Dafalla, A. M. Al-Mahbashi1 and Mosleh Al Shamrani261-265

247

Coastal soils improvement
Mohammad reza Atrchian, Morteza Ala,266-269

248

A Hybrid Intelligent System of Fuzzy C-Mean Clustering and Neural Networks to
Predict the Compaction Characteristics of Fine Grained Soils
Iman Ashayeri, Mahnoosh Biglari270-273249

Equivalent linear seismic ground response analysis of unsaturated soil deposits
Mahnoosh Biglari, Iman Ashayeri274-278251

The Correction of Shallow Foundation Settlement Equations by Finite Element
MethodMohammad Arab Ameri, Hakime Rabbanifar and Mehdi Arab Ameri

279-284

Amin Naeimabadi

Contents of GEOMATE2012 - Volume 2(1)255

Numerical study of earthquake hazards of liquefaction occurring on the site andsustainable transport pipes
Hamed Bavanpouri, Jahangir Khazaie, Dr.Hasan Sharafi

285-288

266

Analysis of geogrid reinforced soil retaining walls with limit equilibrium and finite
difference method
Alireza Sadeghabadi ,Jahangir Khazaie and Mostafa Yousefi Rad

289-293

270

Recent Development in Electrokinetic Stabilization of Soft Soil, A review
Hossein Moayedi, Sina Kazemian, and Bujang B. K. Huat

294-298

275

Application of ion-exchange solution soil stabilizer in increasing CBR values ofclayey soils
Reza Ziaie Moayed, Seyed Ali Hashemi and Farzad Allahyari

299-302

276

Assessment of Low Strain Wave Attenuation for Piles Cast in Very Dense Granular
Soil
Ramli Nazir and Osman El Hussien

303-307279

Dynamic Soil-Structure Interaction Considering Pore-Water Pressure Coupling
Qutayba Nazar Al-Saffar, P Akram Y. Al-Sa’aty, Mohamad T. Al-Layla

308-325

281

Analysis and design of tunnel lining in alluvial soil deposits
Nuri al-Mohamadi

326-330285

Effect of silt content on the anisotropic behaviour of silt-sand mixtures
Navid Khayat , Abbas Ghalandarzadeh

331-337

288

Optimizing the twin tunnels position for reduction the surface ground movements
Mehdi Mokhberi, Seyed Ali Farjam

338-344290

Evaluation of pile lateral capacity in clay applying evolutionary approach
Alkroosh I., Nikraz H

345-348

293

Effect of Reservoir Drawdown Rate on Phreatic Line Recession in Homogeneous
Earth Dams
R. Ziaie Moayed, V. Rashidian349-352294

The effect of lime-microsilica stabilization on California Bearing Ratio of silty soils
R. Ziaie Moayed, Y. Daghigh2, B. Pourhadi and N. Sahebzamani

353-356295

Effect of elastic modulus varieties in depth on modulus of subgrade reaction on
granular soils
Reza Ziaie Moayed, Mahdi Ali Bolandi357-360

296

Flexural Buckling Behavior of Steel Pile with Vertical Load in Liquefied Soil
Yoshihiro Kimura and Koichi Onohara

361-365

305

Two-dimensional finite difference pseudo-static deep-seated slope stability analysis
of embankments over stone column-improved soft clay
Farshad Fayyaz Jahani, Mohammad Sharifipour

366-371

308

Parametric study of Geo-grid soil reinforced retaining walls under dynamic loading
by ABAQUS software
Atrchian mohammad reza, Daghigh younes, Ghanbari namin hamed372-3802010

Sensitivity analysis in soil nail wall for Tehran-Tabriz railway by considering thecoefficient of variation for effective parameters in stability analysis
Mohammad Moghadaripour , Ardalan Akbari Hamed, Ali Ghozat

381-384

Contents of GEOMATE2012 - Volume 2(1)2012

Evaluation of Strength Parameters of Improved Collapsible Soils with Current
Additives (Case study: Atrak zone, Iran)
Mohammad Arab Ameri, Samaneh Kargar and Mehdi Arab Ameri

385-390

2100

Influences of soil material parameters in compaction simulation with soil/water/air
coupled F.E. code
S. Sakamoto, K. Kawai, V. Phommachanh and A. Iizuka

391-3962105

Lower bound limit analysis of strip footings resting on cohesive soils
S.M. Binesh, A. Gholampour

397-4022106

Upper bound limit analysis of strip footings resting on cohesive soils
S.M. Binesh, S. Raei

403-4082108

Evaluating and optimizing different methods of treating and cleaning contaminatedsoil
Mohammad Reza Atrechian,Seyed Salman Musavi Khosro Ebrahimkhani

409-412

2112

Experimental study concerning impact characteristics by collision of weight onsand cushion over steel beam
Tam Sy Ho, Hiroshi Masuya and Naoto Takashita

413-4192114

Landslides in Tea Plantation Fields in Shizuoka, JapanJun Sugawara

420-425

2115

Natural base isolation system for earthquake protection
Srijit Bandyopadhyay, Aniruddha Sengupta and G.R. Reddy

426-4312116

Comparison of Effect of Percent of Compaction, Sand and Cement on The Amountand Time of Swelling of Bentonite
Mohammad S. Pakbaz and B. Rafiee

432-435

2118

Prediction of the Axial Bearing Capacity of Piles by SPT-based and Numerical
Design Methods
Issa Shooshpasha, Ali Hasanzadeh and Abbasali Taghavi436-4392120

Application of recently developed mechanistic-empirical methods for the design ofheavily loaded pavement structures
John N. Mukabi

440-447

2121

Design of support system for excavation in black cotton soils in Guntur, India
D. Neelima Satyam, Akhila Manne

448-451

2127

Numerical modeling of pullout capacity of a pile in sand under oblique load
Md. Iftekharuzzaman and Dr. Bipul Hawlader452-4572130

Slope Failure in Residual Soils of Peru
A.Carrillo-Gil

458-461

2131

Back-analysis of Frictional Jacking Forces Based on Shear Box Testing of
Excavated Spoils
Choo Chung Siung and Dominic Ong E. L.

462-467

2132

Lime Stabilization of Tropical Soft Soils
Dygku Salma Awg Ismail, Tan Jui Siang and Siti Noor Linda Taib468-471

2138

Increase Of Piles Bundle Capacity By Making A Base Joining Them
Jan Jaremski

472-478

Contents of GEOMATE2012 - Volume 2(1)2139

The Effects of soil-Pile Interaction on Seismic Parameters of Superstructure
Mahdy Khari1, Khairul Anuar Bin Kassim, Azlan Bin Adnan

479-4842140

Investigation on Finite Element Modeling of Group of Stone Columns
M. Mirshekari , C. Behnia and S. Fakhretaha

485-4882147

Suction Controlled Triaxial Apparatus for Saturated-Unsaturated Soil Test
Luky Handoko, Noriyuki Yasufuku, Kiyoshi Oomine, Hemanta Hazarika

489-4932154

Monitoring Program and Dilapidation Survey for Grouting of Karst Cavities
Hasan A. Kamal and Hassan J. Karam

494-4972156

Numerical Analysis of Soil Nail Walls under Seismic Condition in 3D Form
Excavations
Siavash Zamiran, Hamidreza Saba

498-501

2159

Shear strength improvement of fibrous peat due to consolidation pressure
Vivi Anggraini, Nurly Gofar and Bujang bin Kim Huat

502-506

2164

Factors affecting the stability analysis of earth dam slopes subjected to reservoir
drawdown
T. Souliyavong, C. Gallage, P. Egodawatta and B. Maher

507-5122165

Lateral stress induced due root-water-uptake in unsaturated soils
Mu’azu Mohammed Abdullahi and Nazri Bin Ali

513-5172166

The effect of pre-tensioned rock bolts on seismic behavior of urban tunnels
Farshad Fayyaz Jahani, Mohammad Sharifipour

518-5232170

Effect of silt content on the anisotropic behaviour of silt-sand mixtures
Navid Khayat , Abbas Ghalandarzadeh

524-530

Construction Materials
24b

Production and Properties of High Strength Concrete for Concrete Dam
Heightening Project in Sudan
Osama M. A. Daoud and, H. S. Sagady

531-537

27

Effect of openings locations of quadratic folded plate roofing systems on their staticand dynamic behavior
Ahmed Hassan

538-54448

Improving concrete compression strength using natural additive
Abdoullah Namdar, Ideris Bin Zakaria and Nurmunira Binti Muhammad Atan

545-548

53

DEM simulations and laboratory experiments on physical and mechanicalproperties of sand-gravel mixtures
Janaka J. Kumara, Kimitoshi Hayano, Yuuki Shigekuni and Kota Sasaki

549-554

120

Rock slope stability problems in Gold Coast area in Australia
Shokouhi Ali, Gratchev Ivan, Charrismanagara Arry

555-558

121

Techno-commercial development of pre-fabricated structures using geopolymer
concrete
J. Santhosh, R.Sanjeev, P.Sethu Raja, A. Rajendra Prasad, A. Abdul Rahman

559-563

Contents of GEOMATE2012 - Volume 2(1)124

Mechanical Properties of Recycled Steel Fibre Reinforced Concrete
A.S.M. Abdul Awal, Lim Lion Yee, M. Dianah1 and M. Zakaria Hossain

564-569

134

Effects of Gradation of Various Sand Deposits of Pakistan on Strength of Hardened
Concrete
Gauhar Sabih , S. Muhammad Jamil and Kamran Akhtar

570-574

203

Assessment of recycled concrete aggregates for road base and sub-base
S. Jayakody, C. Gallage, A.Kumar

575-579232

Estimation of consolidation properties of Holocene clays with artificial neuralnetwork
Kazuhiro ODA , Minsun Lee and Shotaro Kitamura

580-585250

Measurement of The Crack Displacement Using Digital Photogrammetry for
Evaluation of The Soundness of Tunnels
A. Kanazawa, S.Nishiyama, T.Yano, T.Kikuchi

586-592

259

Numerical modelling of a small scale shallow foundation reinforced by
Soil-Mixing
Anna Grzyb, Mahmoud Dhaybi and Frederic Pellet

593-598

262

Physical modelling of a small scale shallow foundation reinforced by Soil-Mixing
Mahmoud Dhaybi and Frederic Pellet

599-604282

Prediction compressive strength of concretes containing silica fume andstyrene-butadiene rubber (SBR) with a mathematical model
A.Haghollahi, M.Shafieyzadeh

605-610283

287

Sliding stability of dry masonry block retaining structure with a resistance plate
Akihiro Hashimoto, Noriyuki Yasufuku, Yoshio Suematsu, Kazuo Fujita1 andToshimitsu Komatsu
Evaluation and Prediction Method on Neutralization of Supplied Long-term
Hydraulic Concrete Structure
Man-Kwon Choi , Yuki Hasegawa, Shinsuke Matsumoto, Shushi Sato and Tsuguhiro
Nonaka611-616617-621297

Measurement of tensile properties of geogrids
Raid R. Al-Omariand Mohammed K. Fekheraldin

622-631306

Modeling the Swelling strain and pressure of Weak Rock using Adaptive
Network-Based Fuzzy Inference System
Ramin Doostmohammadi

632-636309

Centrifuge Modeling Of Reinforced Embankments On Soft Foundation
Ali Sobhanmanesh, Nurly Gofar

637-6422102

Centrifuge model tests and finite element analyses on the seismic behavior of thequay walls backfilled with cement treated granulate soils
Hayano, K., Morikawa, Y., Fukawa, H., Takehana, K. and Tanaka, S.

643-6502109

Response of Piered Retaining Walls to Lateral Soil Movement Based on Numerical
Modeling using Matlab
Siamak Pahlevanzadeh

651-6542122

Evaluation of Thermal Response Tests in Energy Piles
Seung-Rae Lee, Seok Yoon, Hyun-Ku Park , Gi-Dae Oh

655-659

2134

Experimental Study on Mechanical Characteristics of Soil-Geosynthetic Interface
Md. Bellal Hossain, Md. Zakaria Hossain and Toshinori Sakai

660-665

Contents of GEOMATE2012 - Volume 2(1)2136

An Interpretation of Mechanical Properties of Bentonite as a Non-linear Elastic
Material
Y. Takayama, S. Tsurumi, A. Iizuka, K. Kawai

666-6712149

Effect of carbonation on strength of cement treated sandKenichiro Nakarai and Tomomi Yoshida672-675

2167

Application of PML to Analysis of Nonlinear Soil-Structure-Fluid Problem using
mixed element
Pahaiti Reheman, Hiroo Shiojiri

676-681

Environment
28

Recycled Bassanite as a Stabilizing Agent for Cohesion-less Soil
Aly Ahmed and Keizo Ugai

682-687

31

The effects of environmental on today construction industry
Mahdy Khari1, Khairul Anuar Bin Kassim, Azlan Bin Adnan

688-692

33

A Case History of Quay Wall Failure and Remedial Design
C. S. Chen

693-696

37

Environmental economical efficiency in treatment/reutilization of construction
sludges considering delay in process flow
Shinya Inazumi, Hiroyasu Ohtsu and Takayuki Isoda

697-70242

Evaluation and validation of elastic-fragile damage modeling for unsaturated
porous media in θ-stock
B. Gatmiri , M. Fathalikhani

703-708

43

47

Estimation of the Landslide Dam Sustainability in the Gigantic Seimareh Landslide
Using the Rate of Sedimentation
Zieaoddin Shoaei
Influence of soil and rock mineralogy and geomorphology on Landslides
Occurrence and soil erosion in the Merek Catchment, IranMosayeb Heshmati , Nik Muhamad Majid, J. Shamshuddin, Arifin Abdu andMuhamad Ghaituri709-7012

713-719112

The effect of historical land use on landslide initiation
Gholamreza Shoaei

720-723

114

Integrated Environmental Management for Sustained Development
J.Rajaraman and K.Thiruvenkatasamy

724-729

114a

Lowland Environmental Geotechnology of Seismosediments of Kandla Port In
India
J.Rajaraman and K.Thiruvenkatasamy

730-735

123

Single step extraction to find out soluble lead in soil
Masahiko Katoh, Satoshi Masaki, Takeshi Sato736-741

127

Biogas Production from Tannery Sludge
A.Rajendra Prasad, A.Dhanalakshmi, S.Usha and A.Abdul Rahman

742-746

131

Water Harvesting and Salinization Prevention by Capillary Barrier of Soil
Toshihiro Morii, Mitsuhiro Inoue, Kaoru Kobayashi, Tetsuya Suzuki and Takayuki
Kawai

747-752

Contents of GEOMATE2012 - Volume 2(1)204Study of the Performance of anaerobic digestion of greasy skim as a renewableenergy source
Salam J. Bash Al-Maliky

753-756

209

Seismic evaluation of NARGES soil nailed wall under Cyclic loading and Pseudo
Static forces
Ardalan Akbari Hamed , Mohammad Moghadaripour , Ali Ghozat

757-761229

Purification System of Ocean Sludge by and Using Coagulants and then Activating
Microorganisms
Kyoichi Okamoto and Kenji Hotta

762-767

233

Mechanical properties of volcanic products mixed with industrial wastes
K. Yamamoto, T. Negami2, M. Hira, N. Aramaki and Y. Hayashi

768-771

235

Measurement of Hydraulic Conductivity for Peat Ground Using CPTU
Hirochika Hayashi and Satoshi Nishimoto

772-775

252

Extraction of temporal and spatial properties on habitat of snail by means ofstatistical approach
Masaaki Kondo and Takamitsu Kajisa

776-781

265

267

268

271

274

280

The use of Nano Zero Valent Iron to remediation of contaminated soil andgroundwater
Taghizadeh Maryam , Yousefi Kebria Daryoush and Gholamreza Darvishi
A Multi-parameter Water Quality Analysis by onsite filtered 2mL Sample to
Monitor Urban River Eutrophication
Akira Kikuchi, Nor Eman Ismail, Narges Janalizadeh, Musa Mutah and Muhamad
Faiz
The intelligent performance installations in energy efficiency in green buildings
Hooman Abadi, Rouzbeh Abadi, Poona Abadi
Study the Effect of Polyvinyl Chloride (PVC) Addition on the Permeability ofAnbar Soils
Ahmed H. Abdul Kareem & Omar Mustafa
Monitoring deforestation and rangeland destruction through land use alteration
during 1955- 2002, using GIS and RS in Merek sub-basin, west Iran
Mohammad Gheitury, Mosayeb Heshmati, Mohammad Ahmadi and Nik Muhamad
Majid
The comparison of phytoremediation and electrokinetic methods in remediation of
petroleum hydrocarbons contaminated soil
Gholami Meade, Yousefi Kebria Daryoush782-785786-790791-796797-802803-807808-811286

Using Metacognitive Strategies On Listening Comprehension
Mahshid Mirzaaghaee

812-822298

Evaluation of Run-Off Supply Projects in Hamedan Province(Iran)N. Rostam Afshar, M. Abdoli

823-827

299

Protective measures of the monumental pine in Rikuzentakada withsoil-water-air-solved material coupled model
Y. Sugiyama, S. Nomura, K. Kawai and A. Iizuka

828-833

304

Effects of Biosurfactants in Electrokinetic Remediation of contaminated soils
Bour Moslem and Yousefi kebria Daryoush834-838

2117

Change in structure of ground-beetle assemblage on river areas after construction of
biotopes using the technique, “Nature oriented river works”
Michko Masuda, Takaaki Tsukada and Fumitake Nishimura

839-844

Contents of GEOMATE2012 - Volume 2(1)2123

Dense granular-fluid mixture: the effects of the natural grains characteristics andthe interstitial fluid viscosity
Anna Maria Pellegrino and Leonardo Schippa

845-850

2131

Back-analysis of Frictional Jacking Forces Based on Shear Box Testing of
Excavated Spoils
Choo Chung Siung and Dominic Ong E. L.

851-8562137

An idea of multi-functional reservoirs in mountain regions
Jan Jaremski

857-8622141

Estimation Method of Amount of Tsunami Disaster Wastes during the 2011 off the
Pacific Coast of Tohoku Earthquake
Minoru Yamanaka, Naoya Toyota, and Shuichi Hasegawa, Atsuko Nonomura

863-866

2143

Assessment of Runoff in the High Humid Foot-hill Areas of Arunachal Himalayas
Using Thornthwaite Equation
Md. Eahya Al Huda and Surendra Singh

867-871

2161

2163

2171

Natural Radiation level in Groundwater from Katsina, a Semi Arid Region of
Northern Nigeria
B.G. Muhammad and M.S. Jaafar
Cost-Performance Studies of Abandoned Shell Husks (ASH) for Soil
Reinforcement Applications
Md. Toriqul Islam, Md. Zakaria Hossain, Masaaki Ishida, Md. Bellal Hossain
and Md, Jamal Uddin
Cyclones Path and Severities: Effect on Flood Height and Damages of Land and
Embankments in BangladeshMusahaq Ali, Zakaria Hossain and Shigeko Haruyama
Author index

872-876877-880881-884885

Contents of GEOMATE 2013, Nogoya, Japan, Volume 3(1)PrefaceOrganizationx
xi

ID Keynote Papers

1

1k

GROUND DEFORMATION DURING AND AFTER EARTHQUAKES–SIMULATION AND PREDICTION BASED ON ELASTO-PLASTIC SOIL MECHANICSAkira Asaoka

22k

USE OF RECYCLED AGGREGATES FROM CONSTRUCTION AND DEMOLITION WASTES FOR THE
CONSTRUCTION OF FLEXIBLE PAVEMENTS
Márcio Muniz de Farias, Alejandra María Gómez Jiménez and Ferney Quiñones Sinisterra

12

3k

EFFECTIVE STRESS IN UNSATURATED GRANULAR MEDIA IN THE PENDULAR REGIME
Richard Wan, Sarah Khosravani and Mehdi Pouragha

4k

RECENT GEOTECHNICAL RESEARCH ADVANCES IN UNIVERSITY PUTRA MALAYSIA
Bujang B.K.Huat and Afshin Asadi

24

32

40

Technical Papers
ID

Geotechnique

41

3102

LANDSLIDES IN BANGLADESH: CAUSES AND RECOMMENDATION
Musahaq Ali, Zakaria Hossain and Shigeko Haruyama

42

3110

PRECAST SPREAD FOUNDATION IN INDUSTRIALIZED BUILDING SYSTEM
Ramli Nazir, Ehsan Momeni, A. Kadir Marsono, Houman Sohaie

47

3114

CATEGORISING GEOTECHNICAL PROPERTIES OF SUBSOIL IN SURFERS PARADISE USINGGEOGRAPHIC INFORMATION SYSTEM (GIS)
Haider Al-Ani, Leila Eslami-Andargoli, Erwin Oh and Gary Chai

53

3116

EVALUATION OF CONSTITUTIVE MODEL IN SIMULATING THE BEHAVIOR OF CEMENT-TREATED SOIL
Ay Lee Saw, C F Leung and S A Tan

59

3122

UPDATING THE PREDICTIVE MODEL FOR THE VERTICAL COLLAPSE PERCENTAGE OF COLLAPSIBLE
SOIL SUBGRADES
Moshe Livneh and Noam A. Livneh

65

3123

INFLUENCE OF FREEZE-THAW ACTION ON AIR-PERMEABILITY OF UNSATURATED SOIL GROUND
Tatsuya Ishikawa, Tetsuya Tokoro, Dai Nakamura and Satoshi Yamashita

71

Contents of GEOMATE 2013, Nogoya, Japan, Volume 3(1)3144

EFFECT OF ROCK SOCKET CHARACTERISTICS ON LOW STRAIN INTEGRITY TEST OF PILES
Ramli Bin Nazir and Osman El Hussien

77

3148

CHARACTERISTICS OF SLOPE FAILURES IN MAKINOHARA, JAPANJun Sugawara

83

3151

S-PSA WITH USING FEM FOR AN EXISTING ESTUARY DAM
T. Hara, M. Iwata, Y. Otake, Y. Honjo, T. Kato, A. Nishida and H. Yukimoto

89

3155

THE ROTATIONAL HARDENING RULE WITHOUT THE LIMIT SURFACE OF HARDENING
Hiroyuki Kyokawa, Ryoki Ohashi and Teruo Nakai

95

3157

A STUDY OF THE FORMATION MECHANISM OF BEACHROCK IN OKINAWA, JAPAN: TOWARD
MAKING ARTIFICIAL ROCK
Takashi Danjo and Satoru Kawasaki

101

3161

A STUDY ON THE SLAKING-INDUCED CREEP DEFORMATION CHARACTERISTICS OF CRUSHEDMUDSTONE
Sharma Keshab, Kiyota Takashi and Kyokawa Hiroyuki

107

3163

ASTUDY ON GROWTH OF VETIVER GRASS IN TROPICAL REGION FOR SLOPE PROTECTION
Mohammad Shariful Islam, B. A. M. Shahriar, Md. Shahidul Islam and Hossain Md. Shahin

113

3164

INTERACTION MECHANISMS OF SOIL-GEOSYNTHETIC REINFORCEMENT
Mabrouk Touahmia

119

3165

SIMULATION AND PREDICTION OF LARGE-SETTLEMENT IN ULTRA-SOFT PEAT GROUND BY
DEDUCING THE IN-SITU INITIAL CONDITIONS CONSIDERING ARTESIAN PRESSURE
Mutsumi Tashiro, Toshihiro Noda and Nguyen Hong Son

124

3175

SEISMIC RESPONSE ANALYSIS OF GEOTECHNICAL STRUCTURES BUILT OF CEMENT-TREATED
DREDGED SOIL
Takayuki Sakai, Masaki Nakano and Shotaro Yamada

130

3176

3178

3184

3193

3211
3217

3223

DEVELOPMENT OF SPH METHOD WITH AN ELASTO-PLASTIC CONSTITUTIVE MODEL CONSIDERING
SOIL SKELETON STRUCTURE AND ITS APPLICATION TO EXCAVATION PROBLEMS
Hideto Nonoyama, Masaki Nakano and Toshihiro Noda
SOUNDNESS EVALUATION OF THE EMBANKEMNTS FOR EFFECTIVE MAINTENANCE AND LONG-LIFE
OF SHIN-TOMEI EXPRESSWAY
Masaya Hinokio, Hiroshi Yamato, Kazunari Suzuki, Takayuki Sakai, Masaki Makano and Minoru
KawaidaEVALUATION OF GLASS FIBERS DERIVED-THREE DIMENSIONAL GEOMATERIAL FOR PROBLEMATIC
SOIL APPLICATIONS
Donovan Mujah, Hemanta Hazarika, Fauziah Ahmad and Muhammad Ekhlasur Rahman
STUDY ON MONITORING METHOD OF RETAINING WALL BEHAVIOR USING MEMS SENSOR
NETWORKN Minakata, S Nishiyama, T Yano, D.H Lee, J Wu and M Ryu
CASE STUDY ON THE USE OF HIGH-RESOLUTION SURFACE WAVE SURVEY FOR EXAMINING THE
CAUSE OF SUBSIDENCE OF RECLAIMED ROAD
Miura Minami and Shibuya Satoru
MODIFICATION OF KAOLIN MINERALOGY AND MORPHOLOGY BY HEAT TREATMENT AND
POSSIBILITY OF USE IN GEOTECHNICAL ENGINEERING
Nurmunira Muhammad, Ideris Zakaria and Abdoullah Namdar
SIMULATING THE EFFECT OF FLOW VOLUME ON SCOURING PROCESS AROUND BREAKWATERUNDER TSUNAMI CONDITION BY SPH METHOD
M.R. Islam, K. Hayano and A.M.K.N. Nadeesha

136

142

148

154

160

164

169

Contents of GEOMATE 2013, Nogoya, Japan, Volume 3(1)3226

DEVELOPING A NUMERICAL MODEL FOR THE STABILITY DESIGN OF TUNNEL HEADING
Jim Shiau and Ryan Kemp

175

3228

INVESTIGATION OF THE OPTIMAL SUPPORT PATTERNS IN BRACED EXCAVATION USING GROUNDANCHORS
H. M. Shahin, Teruo Nakai, Okuda Kazuaki and Kato Morihiro

181

3232

SHEAR MODULUS REDUCTION CURVES OF GUAYURIBA SANDS BY CYCLIC TRIAXIAL AND BENDER
ELEMENT TESTS
J.F. Gaitán-Serrano, M.P. Ortiz-Pulido and J.F. Camacho-Tauta

187

3234

WATER DIVERSION AND DRAINAGE IN SHALLOW LAND WASTE REPOSITORY CONSTRUCTED USING
CAPILLARY BARRIER OF SOIL
Toshihiro Morii, Kaoru Kobayashi, Kazunobu Matsumoto and Satoru Nakafusa

193

3236

REINFORCING EFFECT OF GEOSYNTHETICS
ON BEARING CAPACITY
Masuda Saki, H. M. Shahin, Nakai Teruo, Morikawa Yukihiro and Mio Susumu

199

3237

INFLUENCE OF THE STRESS HISTORY ON THE STIFFNESS OF SOIL
Asano Kanako, H.M. Shahin, Hiroyuki Kyokawa, Teruo Nakai and Ohashi Ryoki

205

3238

EFFECTIVENESS OF CRASHED TILE IN COUNTERMEASURE AGAINST LIQUEFACTION
Morikawa Yukihiro, Maeda Kenichi and Zhang Feng

211

3246

PREDICTION OF NATM TUNNEL EXCAVATION UNDER SHALLOW OVERBURDEN IN PAHANGSELANGOR RAW WATER TRANSFER TUNNEL PROJECT, MALAYSIA
Mohd Ashraf Mohamad Ismail, Goh Chin Ong, Romziah Azit, Zulkifli Nordin, Norzani Mahmood

217

3250

FUNDAMENTAL STUDY ON LATERAL RESISTANCE CHARACTERISTICS OF BALLASTED TRACKSSUBJECTED TO PSEUDO-STATIC INERTIA FORCE
Ryuta Ogawa and Kimitoshi Hayano

223

3251

USE OF ACOUSTIC EMISSION TECHNOLOGY TO STUDY THE MECHANICAL BEHAVIOUR OF VARIOUS
SANDSTONES: GEOTHERMAL ENERGY
Shao, S.S., Ranjith, P.G. and Chen, B.K.

229

3262

UNCONFINED COMPRESSIVE STRENGTH OF CEMENT TREATED SOIL/RAP MIXTURE
Jirayut Suebsuk, Aniroot Suksan, Suksun Horpibulsuk and Apichit Kumpala

235

3267

INVESTIGATION OF STRESS REDUCTION EFFECT ON STRUCTURE DUE TO BASEMAT UPLIFT USING
ENERGY CONCEPT
Takafumi Inoue and Atsushi Mikami

241

3271

SWELLING DEFORMATION OF BENTONITE MIXED WITH INORGANIC MATERIALS IN ALKALINESOLUTION
Yuki Yokoyama and Kenichiro Nakarai

247

3274

USE OF FULLY SOFTENED VERSUS PEAK STRENGTH TO PREDICT THE CAPACITY OF FOOTINGS ONGEOSYNTHETIC REINFORCED SOIL
Melia K. Iwamoto, Phillip S.K. Ooi, Jennifer E. Nicks and Michael T. Adams

252

3296

THREE DIMENSIONAL FINITE ELEMENT ANALYSIS OF SOIL NAILS IN GRANITIC SOILS
G. Ren and H. Tokhi

258

3298

SIMPLIFIED DYNAMIC AXIAL HEAD PILE STIFFNESS IMPROVEMENT ANALYSIS FOR EXISTING PILED
VIADUCT WITH BASE REINFORCEMENT
Aglipay Mary Roxanne and Konagai Kazuo

262

3312

PFC3D NUMERICAL EXPERIMENTS OF SELF-BORING IN-SITU SHEAR PRESSURE-METER MODEL TEST
Yafei Zhang, Guangli Xu and Jidong Teng

268

Contents of GEOMATE 2013, Nogoya, Japan, Volume 3(1)3318

DYNAMIC ANALYSIS OF SLOPE FAILURE USING THE MESH-FREE SPH METHOD
N. Hiraoka, A. Oya, Ha H. Bui, P. Rajeev and R. Fukagawa

274

3320

ELECTRICAL RESISTIVITY TOMOGRAPHY TO INSPECT BRIDGE FOUNDATIONS
Helsin Wang, Chih-Hsin Hu, and Chung-Yue Wang

280

3323

ULTIMATE BEARING CAPACITY ANALYSIS OF GROUND AGAINST INCLINED LOAD BY TAKINGACCOUNT OF NONLINEAR PROPERTY OF SHEAR STRENGTHDu N L, Ohtsuka S, Hoshina T, Isobe K, and Kaneda K

286

3326

PREDICTION OF SLOPE DEFORMATIONS BY ELASTIC WAVE VELOCITIES IN RELATION TO LANDSLIDEFAILURES
Muhammad Irfan and Taro Uchimura

292

3329

BOX-SHAPE RETAINING WALL SYSTEM: EXPERIMENT AND NUMERICAL PREDICTION
C.T. Nguyen, Ha H. Bui, and R. Fukagawa

298

3343

PERMEABILITY AND CONSOLIDATION BEHAVIOR OF COMPOSITE GROUND REINFORCED WITH
SAND COLUMNS
B. A. Mir and Ashish Juneja

304

3347

LABORATORY EVALUATION OF PHYSICO-CHEMICAL VARIATIONS IN BENTONITE UNDERELECTROKINETIC ENHANCEMENT
Nasim Mosavat, Erwin Oh and Gary chai

310

3358

FLOW PATTERN FOR MULTI-SIZE SILOSYi Yang, Na Li, PengYin and YM Cheng

317

Construction Materials

322

3132

IMPROVING ENGINEERING PROPERTIES OF FINE-GRAINED SOIL WITH STEEL SLAG FOR USING IN
EMBANKMENT EARTHFILL
Je-Min Baek, Satoru Shibuya, Jin-Suk Hur and Tara Nidhi Lohani

323

3156

EVALUATION EQUATION OF DIFFUSION COEFFICIENT OF CHLORIDE ION FOR CRACKED CONCRETE
Junpei Saito and Satoru Shimobe

327

3160

OPTIMIZATION OF EFFECTIVE DEPTH OF COMPACTION FOR FINE-GRAINED SOILS
Girum Y. Yesuf, Inge Hoff and Jan Vaslestad

333

3197

COMPRESSIVE STRENGTH OF CEMENT PASTES EXPOSED TO ELEVATED TEMPERATURE AND
DETERIORATION MITIGATION
Abdoullah Namdar, Ideris Bin Zakaria and Gurumurthy Hegde

339

3201

PARTICLE SIZE AND OTHER FACTORS AFFECTING THE PULLOUT BEHAVIOR OF GEOCELLSEMBEDDED IN GRAVELLY SOIL BACKFILL
Xinye Han, Takashi Kiyota, Michiyuki Harata and Fumio Tatsuoka

345

3202

EFFECT OF LOADING RATE ON STRENGTH CHARACTERISTICS OF GRANULAR BASE COURSE
MATERIAL
Yuan Zhang, Tatsuya Ishikawa and Tetsuya Tokoro

351

3207

EXPERIMENTAL STUDY OF PLYWOOD COMPARING TO FOAM FILLED HONEYCOMB STRUCTURE
Phacharaporn Bunyawanichakul, Chattarin Sunsin, and Thammakorn Sasanawin

357

3249

X-RAY IMAGE ANALYSIS OF POROSITY OF POROUS CONCRETES
Jaehun Ahn, Jinwoo Jung and Seungbae Kim

363

ID

Contents of GEOMATE 2013, Nogoya, Japan, Volume 3(1)3252

STRESS - STRAIN BEHAVIOUR OF SLAG CEMENT CONCRETE
Mustapha Boukendakdji

367

3256

ESTIMATION AND EXPERIMENTAL STUDY ON DIVERSION LENGTH OF CAPILLARY BARRIER USING
CRUSHED SHELL PARTICLESKazunobu Matsumoto, Kaoru Kobayashi , Satoru Nakafusa and Toshihiro Morii

373

3268

EXPERIMENTAL STUDY OF CONCRETE AND MORTAR MIXING WASTE TIRE RUBBER
Man-Kwon Choi, Yuki Hasegawa, Shushi Sato, Shinsuke Matsumoto and Hyeon-Tae Kim

379

3287

PILE DRIVING EFFECTS ON NEARBY BUILDING
Adhilla Ainun Musir and Abdul Naser Abdul Ghani

384

3317

LABORATORY STUDY ON THE PERFORMANCE OF RECYCLED CONCRETE AGGREGATES BLENDED
WITH RECLAIMED ASPHALT PAVEMENT AS A PAVEMENT GRANULAR MATERIAL
S. Jayakody, C. Gallage, J. Ramanujam, A.Kumar

389

3322

BEHAVIOR OF PENETRATION AND LEACHING OF CESIUM IN MORTAR HAVING VARIOUS FINE
AGGREGATES AND MOISTURE CONTENT
Masashi Ito, Kenichiro Nakarai Akihiko Hayashi and Kenji Kawai

394

3324

EFFECTS OF COARSE AGGREGATE CONTENT ON THE EROSION RATE OF CONCRETE DUE TO
SULFURIC ACID ATTACK
Yuji Hatano, Yutaka Okame and Kenji Kawai

400

3357

STUDY ON PHYSICAL PROPERTIES AND USABILITY OF SOME SELECTED RECYCLED FINE
AGGREGATESMohammad Raihanul Islam, Satoru Ishiguro

406

ID

Environment

410

3145

COMPUTER MODELING AND ANALYSIS OF THREE PHASE INDUCTION MOTOR UNDER TEMPORARYSHORT CIRCUIT FAULT IN STATOR USING WAVELET TRANSFORM
Dicky Nova Wardana, Dimas Anton Asfani, Ardyono Priyadi, and Mauridhi Hery Purnomo

411

3147

ANALYTICAL SOLUTION TO CONTAMINANT EXTRACTION CONSIDERING SMEAR EFFECT
H.Y Wang , X.W Tang and B. Bai

416

3152

MECHANISM OF C6H6 OXIDATION IN THE THREE-WAY CATALYTIC CONVERTER EQUIPPED AGASOLINE ENGINE
Akio Takigawa, Akihiro Mieda and Yongzhen Peng

422

3177

ROLE OF CURBSIDE CRACK OF ROAD IN URBAN BIODIVERSITY
Taizo Uchida, Xue J. Huan, Daisuke Hayasaka, Teruo Arase, William T. Haller and Lyn A. Gettys

427

3185

DYE TRACER EXPERIMENTS FOR IDENTIFYING SOLUTE DISPERSIVITY IN UNSATURATED POROUS
MEDIA
Kazuya Inoue, Takayuki Fujiwara and Tsutomu Tanaka

433

3188

REUSE OF AGRICULTURAL AND FOOD RESIDUES FOR RETARDING AND ATTENUATING NITRATE IN
POROUS MEDIA
Kazuya Inoue, Saki Matsuyama and Tsutomu Tanaka

439

3196

MICROSCOPIC RANGE OF IMMOBILIZATION BETWEEN HEAVY METALS AND AMENDMENT IN SOIL
THROUGH WATER MIGRATION
Shouhei Ogawa, Masahiko Katoh and Takeshi Sato

445

3198

SUB-DARCY-SCALE MODELING OF NON-UNIFORM FLOW THROUGH POROUS MEDIA WITH MIXEDWETTABILITES
Junichiro Takeuchi, Takuya Takahashi, and Masayuki Fujihara

452

Contents of GEOMATE 2013, Nogoya, Japan, Volume 3(1)
3218

3222

3224

3243

3244
3247
3248

CAPTURING PEDESTRIAN MOVEMENT SAFETY AND SECURITY ISSUES AT MAJOR TRANSPORTATIONINTERCHANGES
Zulfadly Azizi Bohari, Syahriah Bachok and Mariana Mohamed Osman
ASSESSMENT OF CHROMIUM CONTAMINATION IN SEDIMENTS OF SOUTHERN KAOHSIUNG
HARBOR, TAIWAN
Cheng-Di Dong, Chih-Feng Chen and Chiu-Wen Chen
GPS/GIS IDENTIFICATION OF POTENTIAL BUS STOP LOCATIONS AND PASSENGER’S ACCESS AND
EGRESS POINTS
Syahriah Bachok, Zakiah Ponrohono, Mariana Mohamed Osman, Zulfadly Azizi Bohari
GEOCHEMISTRY OF PALEOGENE RED BEDS IN THE NORTHERN IRAQ FORELAND BASIN: EVIDENCE
FOR PROVENANCE
Muatasam Hassan, Brian G. Jones, Ali Ismail Al Jubory, Sabah Ahmed Ismail,Abdual Salalm Mehdi Saleh
DEVELOPMENT OF BASE MATERIALS FOR SEAWEED BEDS USING VOLCANIC ASHES AND RECYCLING
MATERIALS OF INDUSTRIAL WASTESK. Yamamoto, T. Negami, T. Nakajima, H. Yano, Y. Futsuhara and K. Shima

458

464

469

475

481

CARBON FOOTPRINT AWARENESS – AN INVESTIGATION FROM TRAVEL DIARY SURVEY
Nur Sabahiah Abdul Sukorand Nur Khairiyah Basri487

OPTIMAL MONITORING NETWORK DESIGN FOR EFFICIENT IDENTIFICATION OF UNKNOWNGROUNDWATER POLLUTION SOURCES
Om Prakash and Bithin Datta

493

3257

SPATIAL DISTRIBUTION CHARACTERISTICS OF SUBTERRANEAN HOT WATER EVALUATED USINGWATER QUALITY CONCENTRATION DATA
Takamitsu Kajisa, Si Senfi, Yasunori Mori, Homayoon Ganji, Abdul Saboor Rahmany, Masaaki Kondo
and Hajime Narioka

3258

IDENTIFICATION OF POLLUTANT SOURCE CHARACTERISTICS UNDER UNCERTAINTY IN
CONTAMINATED WATER RESOURCES SYSTEMS USING ADAPTIVE SIMULATED ANEALING AND FUZZY
LOGIC
Mahsa Amirabdollahian and Bithin Datta

505

3270

POINT-BASED RENDERING FOR MASSIVE POINT CLOUD VISUALIZATION
Masafumi Nakagawa

511

3325

REDRAWING AN UNKNOWN MASONRY CAISSON BY GEOPHYSICAL METHODS
Ming-Hung Chen, Shun-Min Lee, Yung-Chuan Chou, Yao-Jen Hsu and Chih-Hsin Hu

517

3335

CONTRIBUTION OF GEOLOGICAL MAPPING AND NEW TECHNOLOGIES TO THE IDENTIFICATION OF
A MAJOR, PRE-EXISTING AND ACTIVE FAULT OVER THE CAPITAL OF TUNISIA
Adnène Kassebi and Fouad Zargouni

523

499

3338

EFFECT OF GRAIN SIZE ON MINERAL CARBONATION OF COAL COMBUSTION FLY ASH FOR CO2
SEQUESTRATION
N. L Ukwattage and P.G Ranjith

530

3349

STUDY SEISMICITY PARAMETERS OF RUDBAR REGION AND SEISMOLOGICAL ASSESSMENT OF
RUDBAR-MANJIL (IRAN) EARTHQUAKE OF JUNE1990
Noushin Naraghi Araghi, Mohd. Nawawi and Syed Mustafizur Rahman

535

3351

UNDERSTANDING TO PREDICT SOIL BEHAVIOR
J. Rajaraman, K.Thiruvenkatasamy and S. Narasimha Rao

540

3356

CASE STUDY ON SHALLOW FAILURE OF CONGLOMERATE AND SILTSTONE SLOPES DUE TO A HEAVYRAINFALL
Satoshi Kagamiahra, Satoru Shibuya, Byeong - su Kim, Shunzo Kawajiri, Tara Nidhi Lohani and
Takashi Okimura

545

Fifth International Conference on
Geotechnique, Construction Materials & Environment
OSAKA, JAPAN