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June 2016 Volume 09 SPL No 03 ISSN 0974-5904 INTERNATIONAL JOURNAL OF EARTH SCIENCES AND ENGINEERING Indexed in: Scopus Compendex and Geobase (products hosted on Engineering Village) Elsevier, Amsterdam, Netherlands, Geo-Ref Information Services-USA, List B of Scientific Journals in Poland, Directory of Research Journals SJR: 0.17 (2014); H-index: 6 (2015); CSIR-NISCAIR, INDIA Impact Factor 0.042 (2011) EARTH SCIENCE FOR EVERYONE Special Issue of 3rd International Conference on Earth Sciences and Engineering (ICEE 2016) 17th-18th June, 2016 http://icee.cafetinnova.org/ Jointly Organized by Department of Civil Engineering, Nehru Institute of Technology, Coimbatore, India & Cafet Innova Technical Society, Hyderabad, India Published by CAFET-INNOVA Technical Society Hyderabad, INDIA http://cafetinnova.org/
CAFET-INNOVA Technical Society 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda Hyderabad – 500 029, Andhra Pradesh, INDIA Website: http://www.cafetinnova.org Mobile: +91-7411311091 Registered by Government of Andhra Pradesh Under the AP Societies Act., 2001 Regd. No.: 1575 The papers published in this journal have been peer reviewed by experts. The authors are solely responsible for the content of the papers published in the journal. Each volume, published in six bi-monthly issues, begins with February and ends with December issue. Annual subscription is on the calendar year basis and begins with the February issue every year. Note: Limited copies of back issues are available. Copyright © 2015 CAFET-INNOVA Technical Society All rights reserved with CAFET-INNOVA Technical Society. No part of this journal should be translated or reproduced in any form, Electronic, Mechanical, Photocopy, Recording or any information storage and retrieval system without prior permission in writing, from CAFET- INNOVA Technical Society.
INTERNATIONAL JOURNAL OF EARTH SCIENCES AND ENGINEERING The International Journal of Earth Sciences and Engineering (IJEE) focus on Earth sciences and Engineering with emphasis on earth sciences and engineering. Applications of interdisciplinary topics such as engineering geology, geo- instrumentation, geotechnical and geo-environmental engineering, mining engineering, rock engineering, blasting engineering, petroleum engineering, off shore and marine geo-technology, geothermal energy, resource engineering, water resources and engineering, groundwater, geochemical engineering, environmental engineering, atmospheric Sciences, Climate Change, and oceanography. Specific topics covered include earth sciences and engineering applications, RS, GIS, GPS applications in earth sciences and engineering, geo-hazards such as earthquakes, landslides, tsunami, debris flows and subsidence, rock/soil improvements and development of models validations using field, laboratory measurements. Professors / Academicians / Engineers / Researchers / Students can send their papers directly to: chiefeditor_ijee@yahoo.com CONTACT: For all editorial queries: D. Venkat Reddy (Editor-in-Chief) Professor, Department of Civil Engg. NIT-Karnataka, Surathkal, INDIA  +91-9739536078  dvr1952@gmail.com All other enquiries: Hafeez Basha. R (Managing Editor)  +91-9866587053  hafeezbasha@gmail.com Raju Aedla (Editor)  +91-7411311091  rajucits@gmail.com
EDITORIAL COMMITTEE D. Venkat Reddy NITK, Surathkal, Karnataka, INDIA EDITOR-IN-CHIEF Trilok N. Singh IIT-Bombay, Powai, INDIA EXECUTIVE EDITOR P. Ramachandra Reddy Scientist G (Retd.), NGRI, INDIA EXECUTIVE EDITOR R. Pavanaguru Professor (Retd.), OU, INDIA EXECUTIVE EDITOR Joanna Maria Dulinska Cracow University of Tech., Poland EXECUTIVE EDITOR Hafeez Basha R CAFET-INNOVA Technical Society MANAGING EDITOR Raju Aedla CAFET-INNOVA Technical Society EDITOR INTERNATIONAL EDITORIAL ADVISORY BOARD Zhuping Sheng Texas A&M University System USA Choonam Sunwoo Korea Inst. of Geo-Sci & Mineral SOUTH KOREA Hsin-Yu Shan National Chio Tung University TAIWAN Hyun Sik Yang Chonnam National Univ Gwangu SOUTH KOREA Krishna R. Reddy University of Illinois, Chicago USA L G Gwalani NiPlats Australia Limited AUSTRALIA Abdullah MS Al-Amri King Saud University, Riyadh SAUDI ARABIA Suzana Gueiros Dra Engenharia de Produção BRAZIL Shuichi TORII Kumamoto University, Kumamoto JAPAN Luigia Binda DIS, Politecnico di Milano, Milan ITALY Gonzalo M. Aiassa Cordoba Universidad Nacional ARGENTINA Nguyen Tan Phong Ho Chi Minh City University of Technology, VIETNAM Ganesh R. Joshi University of the Rykyus, Okinawa JAPAN Kyriakos G. Stathopoulos DOMI S.A. Consulting Engineers Athens, GREECE U Johnson Alengaram University of Malaya, Kuala Lumpur, MALAYSIA Robert Jankowski Gdansk University of Technology POLAND Paloma Pineda University of de Sevilla, Seville SPAIN Vahid Nourani Tabriz University IRAN Anil Cherian United Arab Emirates DUBAI P Hollis Watts WASM School of Mines Curtin University, AUSTRALIA Nicola Tarque Department of Engineering Catholic University of Peru S Neelamani Kuwait Institute for Scientific Research, SAFAT, KUWAIT Jaya naithani Université catholique de Louvain Louvain-la-Neuve, BELGIUM Mani Ram Saharan National Geotechnical Facility DST, Dehradun, INDIA G S Dwarakish NITK- Surathkal Karnataka, INDIA Subhasish Das IIT- Kharagpur, Kharagpur West Bengal, INDIA S Viswanathan IIT- Bombay, Powai, Mumbai Maharashtra, INDIA K U Maheshwar Rao IIT- Kharagpur, Kharagpur West Bengal, INDIA Ramana G V IIT– Delhi, Hauz Khas New Delhi, INDIA Usha Natesan Centre for Water Resources Anna University, Chennai, INDIA M R Madhav JNTU- Kukatpally, Hyderabad Andhra Pradesh, INDIA Kalachand Sain National Geophysical Research Institute, Hyderabad, INDIA R Sundaravadivelu IIT- Madras Tamil Nadu, INDIA M K Nagaraj NITK- Surathkal Karnataka, INDIA Arash Ebrahimabadi Azad University, Qaemshahr IRAN S M Ramasamy Gandhigram Rural University Tamil Nadu, INDIA Gholamreza Ghodrati Amiri Iran University of Sci. & Tech. Narmak, Tehran, IRAN Chachadi A G Goa University, Taleigao Plateau Goa, INDIA Girish Gopinath Geomatics Division CWRDM, Kerala, INDIA Shamsher B. Singh BITS- Pilani, Rajasthan Rajasthan, INDIA C Natarajan NIT- Tiruchirapalli, Tamil Nadu, INDIA N Ganesan NIT- Calicut, Kerala Kerala, INDIA Linhua Sun Suzhou University CHINA Pradeep Kumar R IIIT- Gachibowli, Hyderabad Andhra Pradesh, INDIA Vladimir e Vigdergauz ICEMR RAS, Moscow RUSSIA
D P Tripathy National Institute of Technology Rourkela, INDIA E Saibaba Reddy JNTU- Kukatpally, Hyderabad Andhra Pradesh, INDIA Chowdhury Quamruzzaman Dhaka University Dhaka, BANGLADESH Parekh Anant kumar B Indian Institute of Tropical Meteorology, Pune, INDIA Datta Shivane Central Ground Water Board Hyderabad, INDIA Gopal Krishan National Institute of Hydrology Roorkee, INDIA Karra Ram Chandar NITK- Surathkal Karnataka, INDIA Prasoon Kumar Singh Indian School of Mines, Dhanbad Jharkhand, INDIA A G S Reddy Central Ground Water Board, Pune, Maharashtra, INDIA Rajendra Kumar Dubey Indian School of Mines, Dhanbad Jharkhand, INDIA Subhasis Sen Retired Scientist CSIR-Nagpur, INDIA M V Ramanamurthy Geological Survey of India Bangalore, INDIA A Nallapa Reddy Chief Geologist (Retd.) ONGC Ltd., INDIA Bijay Singh Ranchi University, Ranchi Jharkhand, INDIA S Suresh Babu Adhiyamaan college of Engineering Tamil Nadu, INDIA C Sivapragasam Kalasalingam University, Tamil Nadu, INDIA Xiang Lian Zhou ShangHai JiaoTong University ShangHai, CHINA Debadatta Swain National Remote Sensing Centre Hyderabad, INDIA Kripamoy Sarkar Assam University Silchar, INDIA Ranjith Pathegama Gamage Monash University, Clayton AUSTRALIA B M Ravindra Dept. of Mines & Geology, Govt. of Karnataka, Mangalore, INDIA Nandipati Subba Rao Andhra University, Visakhapatnam Andhra Pradesh, INDIA M Suresh Gandhi University of Madras, Tamil Nadu, INDIA Autar Krishen Raina CSIR-CIMFR, Maharashtra, INDIA H K Sahoo Utkal University, Bhubaneswar Odissa, INDIA R N Tiwari Govt. P G Science College, Rewa Madhya Pradesh, INDIA Nuh Bilgin Istanbul Technical University Maslak, ISTANBUL M V Ramana CSIR NIO Goa, INDIA N Rajeshwara Rao University of Madras Tamil Nadu, INDIA Manish Kumar Tezpur University Sonitpur, Assam, INDIA Salih Muhammad Awadh College of Science University of Baghdad, IRAQ Sonali Pati Eastern Academy of Science and Technology, Bhubaneswar, INDIA Safdar Ali Shirazi University of the Punjab, Quaid-i-Azam Campus, PAKISTAN Naveed Ahmad University of Engg. & Technology, Peshawar, PAKISTAN Raj Reddy Kallu University of Nevada 1665 N Virginia St, RENO Glenn T Thong Nagaland University Meriema, Kohima, INDIA Raju Sarkar Delhi Technological University Delhi, INDIA Hanumantha Rao B School of Infrastructure IIT Bhubaneswar, INDIA Samir Kumar Bera Birbal sahni institute of palaeobotany, Lucknow, INDIA C N V Satyanarayana Reddy Andhra University Visakhapatnam, INDIA S M Hussain University of Madras Tamil Nadu, INDIA Vladimir Vigdergauz ICEMR, Russian Academy of Sciences Moscow, RUSSIA T J Renuka Prasad Bangalore University Karnataka, INDIA Deva Pratap National Institute of Technology Warangal, INDIA K. Subramanian Coimbatore Institute of Technology Tamil Nadu, INDIA Mohammed Sharif Jamia University New Delhi, INDIA A M Vasumathi K.L.N. College of Inf. Tech. Pottapalayam, Tamil Nadu, INDIA Deepak T J INTI International University Kaula Lumpur, MALAYSIA C J Kumanan Bharathidasan University Tamil Nadu, INDIA B R Manjunatha Mangalore University Karnataka, INDIA Sivaraja M N.S.N College of Engg. & Technology Tamilnadu, INDIA Ch. S. N. Murthy NITK- Surathkal Karnataka, INDIA Jitendra Virmani Jaypee Uni. of Information Tech. Himachal Pradesh, INDIA K Elangovan PSG College of Technology Coimbatore, INDIA Vikram Vishal Department of Earth Sciences IIT Roorkee, INDIA A K Verma Indian School of Mines Dhanbad, Jharkhand, INDIA Saeed Khorram Eastern Mediterranean University Famagusta, CYPRUS
INDEX Volume 09 June 2016 No.03 RESEARCH PAPERS Analysis of Effect of Reinforcement on Stability of Slopes By AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY 01-06 Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach By K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN 07-13 Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s By D KARTHIGEYAN 14-20 Mechanical Properties of High Calcium Flyash Geopolymer Concrete By V C PRABHA AND V REVATHI 21-25 Assessment of Wave Energy Potential along South Maharashtra Coast By JUSTIN THOMAS T, K H BARVE, L R RANGANATH AND G S DWARAKISH 26-31 Experimental Investigation on Strength Aspects of Glass Fiber-Reinforced Fine Grained Soil By SUCHIT KUMAR PATEL AND BALESHWAR SINGH 32-39 Role of Time Buffer on Project Monitoring and Forecasting of Steel Structures – A New Approach to Structural Planning By VISHNU S PILLAI AND C RAJASEKARAN 40-45 Utilization of Ground Granulated Blast Furnace Slag and Pulverized Fly ash in the Manufacture of Stabilized Mud Blocks By VENKATALAKSHMIYARLAGADDA AND BEULAH M 46-53 Characteristics of Concrete Containing Waste Foundry Sand and Slag Sand By JOJU JOSE AND NABIL HOSSINEY 54-59 Numerical Analysis of Bucket Foundations under Eccentric Lateral Loading in Medium Dense Sand By TANMOY KUMAR DEB AND BALESHWAR SINGH 60-65 A Short Review of Anaerobic Co-Digestion and Feasibility of Anaerobic Co-Digestion of Sewage and Food Waste for Sustainable Waste Management By DIWAKAR SOMANI, HARSHITA SRIVASTAVA, SABUMON P C AND ANJALI G 66-70 Eco-efficient Fiber Reinforced Self Compacting Concrete for Replacements of Cement and Natural Sand with Waste Materials By PRASAD M L V, PRASENJIT SAHA, ABHILASHA S AND MD FAISAL KARIM 71-77 Psychological Effects of Travel Time Use By YOSRITZAL 78-83 RS - GIS based Operational Monitoring of Indian Maritime and Environs By P KESAVA RAO, J K KISHORE, L J VIJAYA KUMAR AND MURTHY REMILLA 84-92
Simulation of Damage of Waterfront Structure of Port of Kobe during Hyogo-ken Nanbu Earthquake by Using Three-Dimensional Non-linear Parallel Finite Element Analysis By JAFRIL TANJUNG AND MAKOTO KAWAMURA 93-99 Feasibility Study of Powdered Curry Leaf and Amla Fruit as Potential Filter Media for Treating Contaminated Lake Water By N NATARAJAN, D HEMANTH KUMAR, K SAI SARAN NAVEEN, K AKHIL, K A GANESH BABU, A JYOTHSNA LAXMI AND M VASUDEVAN 100-104 Using QSWAT for Simulating Streamflow in a Highland Catchment of Humid Tropics By CELINE GEORGE AND ASWATHY MOHAN 105-108 A Critical Review of Multi Criteria Decision Making Methods for Infrastructure Planning and Sustainability Assessment of Infrastructure Projects By B SURESH, ERINJERY JOSEPH JAMES AND JEGATHAMBAL P 109-123 Soil Structure Interaction in Indian Seismic code: Recommendations for Inclusion of Potential Factors By RAVI KANT MITTAL, ADITI AND SANKET RAWAT 124-130 Estimation of PMP and Precipitations of Various Return Periods Using Statistical Approach–A Case Study for Gunderipallam Dam, Tamil Nadu, India By S DIRAVIA BALAN AND M KRISHNAVENI 131-136 Integrated River Basin Plan for Achencoil River in Kerala State, India By LINDA P JAMES AND A B ANITHA 137-143 Optimum Configuration of Rigid Barriers to Mitigate Avalanche Hazard By VINAY CHAUDHARY, R K VARMA AND MAN MOHAN SINGH 144-148 Properties of Bitumen Containing Powdered Gondorukem Rubber Additives By ELSA EKA PUTRI AND PUJA PERDANA 149-153 Analysis of Historical Strong Earthquake Impacts on Landslides at the Gansu Segment in the Bailongjiang River Basin, China By SHOUYUN LIANG, WANJIONG WU, RUISHOU BA AND YUTIAN KE 154-160 Development of Subsurface Profile Using Geophysical Test Data By SHIVAMANTH ANGADI, MAYANK K DESAI AND GOUDAPPA R DODAGOUDAR 161-164 Quality Control of Cationic Emulsion Modified Cold Mix in Flexible Pavement By M S RANADIVE AND ANUP KUMAWAT 165-169 Investigation of Influence of Terrain on Rainfall for Vembanad Basin, Kerala, India By RAKTIM HALDAR AND RAKESH KHOSA 170-174 Influence of Zinc Oxide Nanoparticle on Strength and Durability of Cement Mortar By D NIVETHITHA AND S DHARMAR 175-181 A Review on Seismic Performance of Reinforced Masonry Structures By UMADEVI R, A S ARUN KUMAR AND B V RAVI SHANKAR 182-187 Effect of Waste Paper Sludge Ash on Engineering Behaviors of Black Cotton Soils By R BARANI DHARAN 188-191 Effectiveness of Bamboo Fiber as a Strength Enhancer in Concrete By KAVITHA S AND T FELIX KALA 192-196
Use of Gold Mine Tailings in Production of Concrete-A Feasibility Study By B M RAMALINGA REDDY, K S SATYANARAYANAN, H N JAGANNATHA REDDY AND N PARTHASARATHI 197-202 Experimental Investigation on the Behaviour of Bagasse Ash Reinforced Concrete Structural Members By S AISHWARYA, K DAKSHAYINI AND P GAJALAKSHMI 203-207 Generation of Synthetic Ground Motion for a Hard Rock Site in Intra Plate Region By A RAVI KIRAN, S BANDOPADHYAY, M K AGRAWAL AND G R REDDY 208-214 Modeling and Controlling of an Coordinated Power Control Grid Connected Hybrid System with Wind, PV and Fuel Cell Sources By N S SRAMAKRISHNA, D N GAONKAR AND G S BHARATHI 215-220 An Advanced GIS based Storm Water Drainage Networking Design for Bhimrad Area of Surat City (India) By MANISHA DESAI AND JAYANTILAL N PATEL 221-228 The Performance of the Accessibility to BRT Stop: A Case Study on Transpadang Metro Bus By BAMBANG ISTIJONO, BAYU MARTANTO ADJI, TAUFIKA OPHIYANDRI, JOVI SATRIOS AND YOSRITZAL 229-234 Parents Perception toward Road Safety Related to the Potential of Cycling to School in Urban Area By BAYU MARTANTO ADJI, MOHAMED REHAN KARIM, BAMBANG ISTIJONO AND TAUFIKA OPHIYANDRI 235-243 Linkages between Catchment Landscape Dynamics and the Natural Flow Regime By VINAY S, BHARATH H A, SUBASH CHANDRAN M D, SHASHISHANKAR A AND RAMACHANDRA T V 244-251 Impact Study on Ferrocement Slabs with Different Types of Mortar Matrices By SEERAM APOORVA, M SAIHARAN, M ARAVINTHAN, H THAMIM ANSARI AND M NEELAMEGAM 252-257 Flexural Behaviour of Cold Formed Steel Hat Shaped Beams By ASHOK M, JAYABALAN P AND JAYA PRABHAKAR K 258-263 Observation of Earthquake Precursors - A Study on OLR Scenario Prior to the Earthquakes of Indian and Neighboring Region Occurred in 2016 By N VENKATANATHAN, V HAREESH AND W S VENKATESH 264-268 Stability Assessment of a Hill Slope-An Analytical and Numerical Approach By B BURAGOHAIN, J KUNDU, K SARKAR AND T N SINGH 269-273 Predictions of Vulnerability Flood and Flood Prone Areas in Watershed West Sumatra Province using Arc-GIS and Category Value By DARWIZAL DAOED, BUJANG RUSMAN, BAMBANG ISTIJONO AND ABDUL HAKAM 274-279 Economic Design of Reinforced Concrete Columns under Direct Load and Uniaxial Moments By SONIA CHUTANI AND JAGBIR SINGH 280-284 Investigation on Partial Replacement of Coarse Aggregate using E-Waste in Concrete By BALASUBRAMANIAN B, GOPALA KRISHNA GVT AND SARASWATHY V 285-288
West Sumatra Landslide During in 2012 to 2015 By ABDUL HAKAM AND BAMBANG ISTIJONO 289-293 Performance on the Study of Nano Materials for the Development of Sustainable Concrete By S SANJU, S SHARADHA AND J REVATHY 294-300 Assessment of Flood Induced Area using Geo-Spatial Technique By AJEET SINGH CHHABRA, SNIGDHADIP GHOSH AND VIJAY KUMAR DWIVEDI 301-304 Deformational Behaviour of Coal Measure Rocks By ASHUTOSH TRIPATHY, BANKIM MAHANTA AND TN SINGH 305-309 Analysis and Design of Transmission Tower Using STAAD.PRO By SAI AVINASH P, RAJASEKHAR P, SIDDHARDHA R, HARINARAYANAN R, CHAMANDEEP AND YASHDEEP 310-313 Strength Properties of Roller Compacted Concrete Pavements Containing Fly ash and Triangular Polyester Fiber By PRAMOD KESHAV KOLASE AND ATUL K DESAI 314-322 Study on the Structural Behavior of Concrete Encased Steel Composite Members By U ELAKEYA, A BHUVANESH SRE AND P GAJALAKSHMI 323-329 Hot Pixel Identification using Satellite Hyper-spectral Data By PIYUSH KUMAR GAURAV, VIVEK KUMAR GAUTAM, P MURUGAN AND M ANNADURAI 330-334 Experimental Study on the Structural Performance of Composite Beam with J-hook Connectors By SARATHKUMAR S, SIVACHIDAMBARAM M AND REVATHY J 335-340 Influence of Fly Ash on Durability and Performance of Concrete By V SESHASAYEE, B H BHARATKUMAR AND P GAJALAKSHMI 341-346 Performance Comparison of Band Ratio and Derivative Ratio Algorithms in Chlorophyll-A Estimation using Hyperspectral Data By P MURUGAN, R SIVAKUMAR, R PANDIYAN AND M ANNADURAI 347-352 Structural Response of FRP Strengthened PSC Beams By VIGNESH C K, SIVARANJAN D AND REVATHY J 353-359 Strength and Setting Times of F-Type Fly Ash-Based Geopolymer Mortar By KOLLI RAMUJEE 360-365 Groundwater Prospects Mapping in Korapuzha River basin, Kerala, India - An Integrated Approach using Multicriteria Decision Making and GIS Techniques By AMAL P SIVADAS, JESIYA N P AND GIRISH GOPINATH 366-372 Optimum Position of Multi Outrigger Belt Truss in Tall Buildings Subjected to Earthquake and Wind Load By A S JAGADHEESWARI AND C FREEDA CHRISTY 373-377 Study on Reduction in Delay due to Road Accidents using Variable Message Sign By GANGHA G, ARUNIMA JAYAKUMAR AND NIRMAL KUMAR P 378-382 Spatial and Temporal Variation in Groundwater Quality and Impact of Sea Water in the Cauvery Delta, South India By ASWIN KOKKAT, P JEGATHAMBAL AND E J JAMES 383-392
Waste Water Treatment by Phyto-Remediation Technique By ADITYA VIKRAM CHOPRA, UMANG K SHAH AND J S SUDARSAN 393-399 An Experimental Investigation on Effect of Hybrid Fiber on High Strength Self Compacting Concrete and Vibrated Concrete By K J N SAI NITESH AND S VENKATESWARA RAO 400-403 Viscosity Graded Approach for Quality Control of Bitumen By M S RANADIVE AND VINAYAK BOBADE 404-410 Effects of Domestic Rawsewage on Mechanical Properties of Concrete Incorporating GGBS (Ground Granulated Blast Furnace Slag) By SHILPA S RATNOJI, PRAVEEN S MALLAPUR, SHASHANK KANAVALLI AND K B PRAKASH 411-414 Experimental Investigation on Modulus of Elasticity of Recycled Aggregate Concrete By P S KULKARNI, A GHATGE, O KANK, A NAIR AND R ASWAR 415-419 Geotechnical Characteristics of Volcanic Soils in and around Taiz City, Yemen By JANARDHANA M R AND ABDUL-ALEAM AHMED A D AL-QADHI 420-425 Experimental Studies on the Effect of Bagasse Ash and M-Sand on Mechanical Behaviour of Concrete By BHUVANESHWARI M AND TAMILARASAN S 426-431 Factors Contributing to the Success of a Resettlement Project: A Case Study on Batanghari Dam Project, Indonesia By TAUFIKA OPHIYANDRI, UYUNG GATOT S DINATA, TAFDIL HUSNI, BAMBANG ISTIJONO AND ADI PUTRA 432-435 An Immediate Review of Flood Characteristics on Delta Lowland Sumatra using D8 Model Spatial Analysis By NURHAMIDAH, AHMAD JUNAIDI AND LIBRINA ANGGRAINI 436-442
www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.01-06 #SPL02090301 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Analysis of Effect of Reinforcement on Stability of Slopes AKSHAY KUMAR JHA 1 , MADHAV MADHIRA 2 AND G V N REDDY 2 1 Indian Railways, Hyderabad, India 2 JNTU Hyderabad, Hyderabad, India Email: akshayghungru@gmail.com, madhavmr@gmail.com, gvnreddy@jntuh.ac.in Abstract: Steepening of slopes for construction of rail/road embankments or for widening for other civil engineering structures is a necessity for development. Use of geosynthetics for steep slope construction or repair of failed slopes considering all aspects of design and environment could be a viable alternative to this problem. Literature survey indicates that efforts were made for optimization of length of reinforcement. The present paper details an analysis to optimize the length of geosynthetics from the face or near end of the slope with respect to its location and length to obtain the desired minimum factor of safety. Unreinforced and reinforced slopes are analyzed to obtain critical factors of safety. The effect of providing geosynthetic layer in shifting the critical slip circle has been identified and studied. Keywords: Reinforcement, Optimization of length, Critical slip circle, Reinforced slope, Geosynthetics 1. Introduction The analysis of earth slopes is the oldest geotechnical engineering problem that engineers have been dealing with using various techniques. The methods can be classified as Limit Equilibrium Methods, Finite Element Method based on c, reduction, Finite Element Modeling/Finite Difference Method, combination of FEM and LEM, Limit Analysis (LA), etc. Geosynthetic reinforcement of earth slope results in reducing the land requirement (Fig. 1) and preservation of natural resources (land and backfill requirements) apart from time and cost. Designing geosynthetic reinforced slope with minimum length of geosynthetics leads to further economy. Base Width B1 Less Than B0 Figure 1 Base Widths for Unreinforced and Reinforced slope Ingold [5], Jewell et al. [6], Bonparte et al. [1], Koerner [8], Verduin and Holtz [17] present design methods for earth slopes reinforced with geotextiles or /and geogrids using LEM assuming different types of failure surfaces such as circular or/and bilinear wedges. Jewell et al. [6] used Limit Equilibrium Analysis and local stress calculation for design of reinforced slope. Rowe and Soderman [14] present a method for estimating the short-term stability of reinforced embankment which has simplicity and versatility of LE but incorporates essential component of soil - structure interaction derived from FEM. Leshchinsky and Reinschmidt [9] present an analytical approach based on limit equilibrium and variational extremization of factor of safety for membrane/sheet reinforced slopes for a single layer of reinforcement which satisfies all the requirements of limit equilibrium. Schneider and Holtz [15] present a design procedure for slopes reinforced with geotextiles and geogrids which assumes bilinear surface of sliding and pore water pressures and the initial stress conditions in the slope. Leshchinsky and Boedeker [10] present an approach for stability analysis of geosynthetic reinforced earth structure using log spiral LE approach for multilayer reinforced slope. Jewell [7] presented revised design charts for steep slopes valid for all polymer reinforcement materials. These revised charts lead to savings of the order of 20-30% in reinforcement quantity. Leshchinsky et al. [11] used log spiral failure mechanism to determine the required reinforcement long term strength Zhao [18] presented a kinematic solution of the plasticity theory applied to the stability of geosynthetic reinforced soil slopes. Michalowski [13] presented kinematic limit analysis solution of reinforced slope to determine the amount of reinforcement necessary to prevent collapse of slopes due to reinforcement rupture, pullout, or direct sliding. Shiwakoti et al. [16], conducted parametric studies to investigate the effect of geosynthetic strength, soil- geosynthetic interaction coefficients, vertical spacing of geosynthetics for soil slope/wall on competent foundation and suggested optimization. Baker and Klein [2,3] modified the top-down approach of Leshchinsky (1992) to find the reinforcement force needed for the same prescribed factor of safety everywhere within the reinforced mass. Han et al. [4] present a general analytical frame work for design of flexible reinforced earth structures regardless of slope face inclination applicable to both walls and slopes.
AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 2 Leshchinsky et al. [12] presented a limit equilibrium methodology to determine the unfactored global geosynthetic strength required to ensure sufficient internal stability in reinforced earth structures, which allows seamless integration of design methodologies for reinforced earth walls and slopes. None of the above approach optimizes the length of geosynthetics by curtailing the same from the slope face. The paper details an analysis carried out to optimize the length of reinforcement from face end of slope. 2. Problem Definition An embankment of height, H, of 6.0 m with side slopes of 1.5H to 1V vertical is considered (Fig. 2). The embankment and foundation soil have cohesion, c, of 4 kPa, unit weight, of 18 kN/m3 and angle of shearing resistance, , of 260 . The geosynthetic reinforcement used has adhesion, ca, of 3 kPa, angle of interface friction between soil and reinforcement, , of 20° and ultimate tensile strength, Tult, of 200 kN/m. All the stability analyses have been carried out using Morgenstern-Price method. Figure 2 Definition Sketch 3. Stability Analysis 3.1 Unreinforced Slope Unreinforced embankments of heights 3 m, 4 m, 5 m and 6 m have been analysed using SLOPEW of Geostudio 2004 version and FSmin obtained as 1.60, 1.44, 1.33 and 1.26 respectively. Embankment with height of 6 m has FSmin less than the required value of 1.3 and hence is reinforced with geosynthetic sheet to get FSmin of 1.5. 3.2 Reinforced Slope Effect of varying the length, Lr, of geosynthetic placed at depth, Z0=3.0 m in 6.0 m high embankment is studied by increasing the Lr so as to get FSmin just greater than 1.50. Length, Lr, of the reinforcement to intercept the failure surface at 3.0 m depth was varied from 5.89 m to 6.13 m. FSmin increased from 1.48 to 1.51 (Fig. 3). Figure 3 Critical slip circle for Z0=3.0 m, FSmin = 1.51, Lr = 6.11 m Circles ABC and DEC are the critical slip circles of the unreinforced and the reinforced slopes. PQ is the total length of reinforcement, Lr. The length of reinforcement Lr has two components: QE = effective length, Le, in the stable zone and EP - the length, Lf in the unstable zone. Lf is further divided into lengths Lf1 (EB), the length in the failure zone between the critical slip circles of the reinforced and the unreinforced slopes and length, Lf2, between the critical slip circle of unreinforced slope and slope face (BP) as shown in Fig 3. It should be noted that one of the effects of inclusion of reinforcement in embankment soil is to shift the critical slip circle from ABC to DEC. This shift of the critical circle increases the factor of safety by involving larger slide mass. The effect of varying Lr on mobilized force in the reinforcement (Fr) and the factor of safety (FSmin) with right end fixed at point P and left end (Q) moved outward successively, are summarized in Table 1. Table1: Slope with Z0 = 3.0 m Lr, m Fr , kN/m FSmin 5.89 12.31 1.480 5.95 13.88 1.487 6.00 15.35 1.496 6.11 18.4 1.515 6.13 18.89 1.518 Factor of safety and the load/resistance mobilized in the reinforcement increases with increased length of reinforcement as is to be expected. FSmin increases from 1.48 to 1.51 as the length is increased from 5.89 m to 6.11 m. Similarly resistance mobilized in the reinforcement (Fr) increase from 12.31 kN/m to 18.89 kN/m. The length, Lf = (Lr - Le) is much larger than Le, the effective length of reinforcement contributing to increase in the stabilizing moment/force. The required pullout force in the reinforcement in the stable zone gets mobilized only by the corresponding resistance along the length of the reinforcement in the unstable zone. It would serve no useful purpose if the length of the reinforcement in the unstable zone is more than that required for generating the required stabilizing force. Hence minimizing Lf = (Lr - Le) by moving point P inside the soil mass and away from
Analysis of Effect of Reinforcement on Stability of Slopes International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 3 the slope face by curtailing the length of reinforcement but still maintaining FSmin above 1.50 can lead to economy. Accordingly for reinforced slope of Fig 3 Lr has been curtailed from the face end of the slope. As point P is moved inward gradually by reducing Lr, the critical circle continues to be DEC or close to it (Fig. 4), i.e., practically no shift of the critical circle. The minimum length, Lr which provides FSmin = 1.51 is obtained as 3.88 m (Fig. 4). Thus about 36% reduction is length of reinforcement is achieved without sacrificing the stability of the embankment slope as it still has FSmin of 1.51. Figure 4 Critical slip circle for slope with Z0 = 3.0 m, Lr = 3.88 m and FSmin = 1.51 FSmin continues to be close to 1.50 on reducing Lr further but at Lr = 3.78 m FSmin reduces to 1.30 and the critical circle shifts to between circle ABC and the face of the slope, a shallow failure surface. Reinforced slope as in Fig. 4 above, with the minimal length of the reinforcement arrived at, has been analysed for the slip circle ABC (Fig. 5) corresponding to that of unreinforced slope to quantify the FS so obtained. Figure 5 Reinforced slope with Z0 = 3.0 m, Lr = 3.88 m analysed for failure slip circle ABC of unreinforced slope FS for this case works out to be very high at 1.83 indicating that the critical circle that gives minimum factor of safety with reinforcement is very different from the one without the reinforcement. The circle, ABC, is not the critical circle for the reinforced slope case and thus not acceptable implying that the critical circle with consideration of reinforcement is different from that of the unreinforced case. Slope as in Fig. 4 has been analysed further for the critical slip circle DEC of reinforced slope but without considering the effect of reinforcement to get FS of 1.41 (Fig. 6). Figure 6 Slope stability with critical slip circle DEC but without considering the effect of reinforcement The factor of safety for slip circle DEC (the critical slip circle for the reinforced case) but without considering the contribution of the reinforcement is 1.41 and higher than FSmin of 1.26 obtained for the unreinforced slope. Since the critical circle shifts inward, the factor of safety even without considering the effect/contribution of the reinforcement gets increased as the effect of shift of critical slip circle is to increase FS from 1.26 to 1.41. Reinforced slopes with Z0 = 4.0 m and 5.0 m have also been analysed in similar manner as that for Z0 = 3.0 m and the results summarized in Table 2 Table 2: Factors of Safety and Lengths of Geosynthetics for Reinforced Slope with Z0 = 3.0 m, 4.0 m and 5.0 m FS Lr, m Z0, m I II III IV 3.0 1.26 1.51 1.83 1.41 3.88 4.0 1.26 1.51 1.89 1.46 4.15 5.0 1.26 1.51 1.96 1.47 4.94 Legend: I: FSmin for unreinforced slope with critical circle ABC; II: FSmin for reinforced slope with critical circle DEC; III: FS for reinforced slope analysed for circle ABC of unreinforced slope and IV: Reinforced slope analysed for critical slip circle DEC but without considering the effect of reinforcement. 4. Results and Discussion 4.1 Reinforcement At Z0 = 3.0 m FSmin of the slope for unreinforced case is 1.26 (Table 2). If however the slope is analysed with the reinforcement but considering the slip circle to be the
AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 4 same (ABC of Fig. 4) as for that for the unreinforced case, FSmin is 1.83. This FS is not the minimum and hence ABC is not the critical for the reinforced case. The contribution of reinforcement in enhancing the stability of a slope is observed to be twofold: (i) shifting of the critical slip circle deeper in to the slope involving larger slide mass or forward involving smaller slide mass and thus enhancing the factor of safety of the slope and (ii) due to contribution of reinforcement to stabilizing force/moment. FSmin of 1.26 for unreinforced case increases to 1.41 due to shifting of the critical circle to DEF an increase of 11.9%. Secondly the contribution of reinforcement to stabilizing moment/force leads to a further increase in factor of safety from 1.41 to 1.51, a contribution of about 8.2%. The contribution of reinforcement to stability in terms of change in FS is defined as follows: relative change in factor of safety due to overall effect of reinforcement (1) relative change in factor of safety due to shift of critical circle due to effect of reinforcement (2) The difference between the two relative factors of safety is the contribution of reinforcement to increase in FS. Changes in RFS for all the three cases i.e. Z0 = 3.0 m, 4.0 m and 5.0 m are detailed in Table 3. Table 3: Relative changes in factors of safety for cases with Z0 = 3.0 m, 4.0 m and 5.0 m Z0, m % % % 3.0 19.8 11.9 7.9 4.0 19.8 15.9 3.9 5.0 19.8 16.7 3.1 FSmin for the reinforced slope is 1.51 while that of the unreinforced slope is 1.26 for all the three cases. Hence percentage relative change in FS, is 19.8. The percentage relative change in FS due to shifting of critical circle, is more for 5.0 m case followed by those for the 4.0 m and 3.0 m cases. For Z0 = 3.0 m, the contribution due to shifting of critical circle is 11.9% and the balance 7.9% is the contribution of the reinforcement. The contributions of reinforcement due to shifting of critical circle are of the order of 12-17% while that due to reinforcement effect is of the order of 3-8% in the three cases analyzed. 4.2 Variation of FSmin and Fr with Lr FSmin varies linearly with length of reinforcement, Lr, for Z0 = 3.0 m, 4.0 m and 5.0 m as shown in Fig. 7. 1.4 1.42 1.44 1.46 1.48 1.5 1.52 1.54 5.6 5.8 6 6.2 6.4 6.6 Fsmin Length,m Length Vs. FSmin 3m 4m 5m Figure 7 FSmin vs. Lr for Z0 = 3.0 m, 4.0 m and 5.0 m FSmin for Z0 = 3.0 m and 4.0 m are close to each other. Variations of loads in reinforcement with length of reinforcement, Lr, are also linear (Fig. 8) but different for the three cases considered. The change in slope of Line in case of Zo =4.0 m is due to change in critical slip circle. 0 2 4 6 8 10 12 14 16 18 20 5.7 5.8 5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 ReinforcementLoad,kN/m Length,m Length Vs. ReinforcementLoad 3m 4m 5m Figure 8 Load in Reinforcement, Fr vs. Length of Reinforcement, Lr for Z0 = 3.0 m, 4.0 m and 5.0 m 4.3 Summary of Results The results of the analysis for length of reinforcement, Lr, and FS are summarized in Table 4. Table 4: Results of Analysis of Reinforced Slope with Z0 = 3.0 m, 4.0 m & 5.0 m Z0, m Lr, m Lopt =P1Q, m Lshift= P1E, m Le, m Lr- Lopt FSminDE F FSshift 3 6.11 3.88 3.26 0.62 2.23 1.51 1.41 4 6.15 4.15 3.93 0.22 2.00 1.51 1.46 5 6.45 4.94 4.79 0.15 1.51 1.51 1.47 Legend: FSshift = FS for DEC slip circle without considering effect of reinforcement; P1Q & P1E lengths of reinforcement (Fig. 4). Saving in length of reinforcement is highest in case of Z0 = 3.0 m being 2.23 m. Similarly the effective length of reinforcement Le is also highest in this case being 0.62 m. The minimum reinforcement length required out of three positions is that for Z0 = 3.0 m. The fact that for the same FSmin higher length of geosynthetics is required in case of 5.0 m is because the length contributing to FS by way of stabilising force/moment is very small i.e. only 0.15 m against
Analysis of Effect of Reinforcement on Stability of Slopes International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 5 0.62m of 3.0 m case. All the three critical circles are shown in Fig. 9 for comparison. They are close to each other but far away from that for the unreinforced case. Figure 9 Critical slip circles for reinforcement at Z0 = 3.0 m, 4.0 m and 5.0 m and for unreinforced case The critical circle is practically same (Fig. 9) for reinforcement at 4.0 m and 5.0 m from the top of embankment. Length of geosynthetic contributing to stabilising force/moment is lowest in case of Z0 = 5.0 m and highest in case of Z0=3.0 m. 5. Conclusions An analysis of interaction between an embankment slope and reinforcement is carried to identify and quantify the mechanisms contributing to increased slope stability as reflected in higher factor of safety and to optimize the length of reinforcement to be provided. A typical embankment slope 1.5H:1V of height 6.0 m with a single layer of reinforcement at 3.0 , 4.0 and 5.0 m depths from the top is examined for stability using Morgenstern and Price method. 1. The critical slip circle for the slope with reinforcement shifts inward and is very different from that for the unreinforced slope. 2. The critical circles for slope with the reinforcement at different locations (3.0 to 5.0 m depth) are different but practically same for Z0= 4.0 &5.0 m. 3. The increase in factor of safety with the provision of reinforcement in a slope is because of the shift of the critical slip circle deep in to the slope involving larger sliding mass. This results from the fact that the slip circle is deeper in to the soil and away from the critical circle corresponding to that for unreinforced embankment soil. 4. As a consequence, the reinforcement force generated becomes much smaller than that estimated based on the length corresponding to that estimated with respect to slip circle for the unreinforced slope. 5. The analysis is further carried out by curtailing the length of the reinforcement from the face of the slope to economise the use of geosynthetics. 6. The effect of providing reinforcement in the slope is thus two-fold, viz., shifting of critical circle inside of the embankment involving larger slide mass and by increase in stabilizing force/moment due to bond resistance mobilized in the reinforcement. 7. It is possible to achieve about 23 to 36% saving in the length of the reinforcement length without endangering the stability of the embankment slope. 8. The most significant finding of this study is that the reinforcement can be provided inside and not necessarily from the face of the embankment. References [1] Bonparte R., Holtz R.D. and Giroud, J.P.,"Soil reinforcement design using geotextile and geogrids", Geotextile Testing and design Engineer, ASTM STP 952, J.E.Fluet, Jr., Ed., American society for testing materials, Philadelphia,69-116, 1987. [2] Baker, R. and Klein, Y. “An integrated limiting equilibrium approach for design of reinforced soil retaining structures. Part I-Formulation.” Geotextiles Geomembranes, 22(3), 119-150, 2004 [3] Baker, R. and Klein, Y. “An integrated limiting equilibrium approach for design of reinforced soil retaining structures: Part II – Design examples.” Geotextiles Geomembranes, 22(3), 151-177, 2004 [4] Han J. and Leshchinsky, D., "General analytical framework for design of flexible reinforced earth structures”, J. of Geotechnical and Geoenvironmental Engineering. ASCE, 132, 1427-1435, 2006. [5] Ingold T.S., "An analytical study of Reinforced Embankments", proceedings 2nd international conference on geotextiles, Las Vegas, IFAI, Aug. 83-109, 1982. [6] Jewell, R.A., Paine N. and Woods R.I. " Design methods for steep reinforced embankments" Polymer grid reinforcement, Thomas Telford Limited, London, 70-81, 1985. [7] Jewell, R.A., "Application of the Revised Design Charts for Steep Slopes", Geotextiles and Geomembranes 10(1091), 203- 233,1991 [8] Koerner, R.M. (1990),"Designing with geosynthetics, 2nd Ed., N.J.: Prentice hall. [9] Leshchinsky, D. and Reinschmidt, A.J. , "Stability of membrane reinforced slopes.” J. Geotechnical Engineering, 111 (11), 1285- 1300, 1985. [10]Leshchinsky, D. and Boedeker, R.H., “Geosynthetic reinforced soil structures,” J. of Geotechnical Engineering, 115(10), 1459 – 1478, 1989.
AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 6 [11]Leshchinsky D., Ling, H. and Hanks, G., "Unified design approach to geosynthetic reinforced slope and segmental walls." Geosynthetics International, 2(5), 845-881, 1995. [12]Leshchinsky D., Zhu fan and Meehan Christopher L., "Required unfactored strength of geosynthetic in reinforced earth structures", Journal of Geotechnical and Geoenvironmental Engineering,136(2), 281-289, 2010 [13]Michalowski R L, "Stability of uniformly reinforced slopes", Journal of geotechnical and Geoenvironmental engineering, Vol 23, No. 6, 546-556, 1997. [14]Rowe K. and Soderman K. L.," An approximate method for estimating the stability of geotextile- reinforced embankments", Canadian Geotechnical Journal, 22(3), 392-398, 1985. [15]Schneider H.R and Holtz R.D. , " Design of Slopes reinforced with geotextiles and geogrids", Geotextiles and Geomembranes, Vol 3, 29- 51,1986 [16]Shiwakoti, D.R., Pradhan, T.B.S. and Leshchinsky, D., "Performance of geosynthetic - reinforced soil structures at limit equilibrium state", Geosynthetics International,5(6), 555 - 587,1998. [17]Verduin J.R and Holtz R.D, "Geosynthetically reinforced slopes", A new procedure, "Proceedings geosynthetics, San Deigo, IFAI, 1989. [18]Zhao A, "Limit Analysis of geosynthetic - reinforced slopes", Geosynthetics International, Vol. 3, No. 6., 721- 740,.1996.
www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.07-13 #SPL02090302 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach K RAM CHANDAR 1 , ASHWIN J BALIGA 1 , B S S RAO 2 AND R K BISEN 2 1 Department of Mining Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore- 575 025, India 2 Insmart Systems, Moosapet, Hyderabad-500 018, India Email: krc_karra@yahoo.com Abstract: The aim of this paper is to study the influence of select variables like mill running duration, volume of material and sieving time on the amount of weight retained in the reference sieve for basalt in a rod mill. Experimental studies were conducted based on the various factors along with their ranges and their effect on the material retained on the sieve (response variable) was determined. Minitab 17 software is used for analysis purpose. Based on the main effects, plots obtained through the general full factorial design, optimum parameters that influenced weight retention in the reference sieve were arrived at. It was found that all the main effects mill running duration, volume of material and sieving time and the interaction effects significantly influenced the weight retention in the chosen reference sieve. The main effects contributed nearly 75% and the interactive effects contributed to approximately 20%, on the amount of weight retained in the chosen reference sieve of 125 microns for ground basalt sample. As innovations are continuously on the rise, the revelation made in this research would significantly contribute to the optimization of the research activities in milling process. Keywords: Design of Experiments, Regression, Rod Mill, Taguchi Analysis 1. Introduction It is always desirable to first conduct experimental tests in laboratory scale before taking it up on an industrial scale. This enables to determine the various parameters such as liberation size, grindability, coarse to medium to fine proportion in any product of the crushing and grinding equipment and the proportion of values of gangue particles in the fines (Wills, 2006). After the mining of ores, except for a few rich in valuable minerals, the vast majority of lean ore contains large amount of gangue particles. In the metallurgical industry, these lean ores comprises of low useful components of mineral and its composition is complex, if it is directly used for smelting to extract metals. The energy consumption will be large and will result in high production costs in such operations. For more economic development and use of low-grade ore, these minerals must go through sorting and enrichment so as to abandon most of the gangue and finally processing the useful minerals in order to reach the smelting requirements. In the beneficiation process, there are two basic steps: First, disassociation that is crushing and grinding the large pieces of ore and dissociating a variety of useful minerals from the ore particles; Second, sorting, separating of particles according to their physical and chemical properties. If the product crushed is not fine enough, then the useful minerals and gangue cannot be fully separated and the sorting will become ineffective; while the pulverized product granularity becomes too thin, resulting in too much crushed particles, though a variety of useful minerals are disassociated completely, the sorting result is not necessarily good, this is because for any material size the sorting method can handle a certain limit. Therefore, the concentration should be on crushing and grinding, to select the full disassociation and crushed material for the sorting operation, so that the particle size can fit the chosen sorting method. Grinding is the final stage in the process of comminution and is achieved by varieties of mills. Mills are devices that comminute solid materials into smaller pieces due to combination of impact and abrasion, either in dry or in wet condition. The comminution takes place due to the action of mechanical forces. In case of rock crushing, this is done to produce a uniform aggregate size for construction purpose or land reclamation activity. Rod mills are analogous to ball mills, but they use long rods for grinding media. The rods grind the ore by tumbling within the mill, similar to the grinding balls in a ball mill. To prevent the conditions leading to rod charge tangling, the length to diameter ratio is maintained at 1.4 to 1.6 (Gupta and Yan, 2006). Grinding action is by line contact between the rods extending the length of the mill. Rods tumble and spin in roughly parallel alignment simulating a series of roll crushers. This results in preferential grinding of coarse material and minimizes production of slimes. Rod mills are used less in comparison to ball mills for grinding minerals. The rods used in the mill, usually high-carbon steel, can vary in both the length and the diameter. However, the smaller the rods, the larger is
K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 8 the total surface area and hence, the greater the grinding efficiency (Wills, 2006). The common sizes of mills, the initial size of feed and the reduction ratio of the feed to produce sizes are achievable during the process of comminution. In order to optimise the efficiency of comminution equipment or also to assess the influence of various parameters on the efficiency of crushers and mills, Design of Experiments (DOE) is a very useful tool. Making a set of experiments representative with regard to a given research problem is called Design of Experiments. DOE is used to study any scenario that involves a response and varies as a function of one or more independent variables. DOE is specifically designed to address complex problems where more than one variable may affect a response and two or more variables may interact with each other (Altekar et al., 2006). DOE is used wherever experimental data is collected and analysed. Its use is expected in all branches of scientific research, but DOE is becoming more widespread in engineering, manufacturing, biology, medicine, management, etc. DOE is becoming a versatile tool because of its tremendous power and efficiency. Data can be qualitative or quantitative. Qualitative data characterize things that are sorted by qualitative terms like good, better and best, these cannot be quantified in numerical values. Quantitative data characterize things by size, which requires a system of measurement. Examples of quantitative data are length, time and weight (Barrentine, 1999). DOE is based on problems involving both types of data, and the distinction between them is important. DOE has been used extensively by DuPont, Dow, Goodrich and others for over 30 years. DOE was introduced by Genichi Taguchi in Japan in early sixties. Taguchi's methods became known in the USA in the early 80s when Toyota, Honda, Canon, and many others overtook their American counterparts with high quality products (Mathews, 2010). 1.1 The Experimentation Process A simple model of experimentation is shown in the Figure 1. Processes have inputs that determine how the process operates and outputs that are produced by the process. The purpose of experiment is to determine how the inputs affect the outputs. The inputs are referred to as the variables, factors or predictors and process outputs are called the responses. In addition to these, there are controllable factors which control the process. Uncontrollable factors introduce variability into the response, due to which during replication the same values cannot be obtained, that is performing same experiments yield varied results (Mathews, 2010). Figure 1 The process of experimentation The number of experiments to be carried out is given by the formula (Barrentine, 1999): N=LF * Number of replicates Where, N= number of experiments L= number of levels F= number of factors 1.2 Procedure of Design of Experiments The procedure involved in designing the experiments is described below:  Recognition and statement of the problem There should be a felt need for research, for which there should be literature support. It also should include the clear statement of problem and objectives for research. Some ideas about the expected outcomes or the phenomenon under experimentation should be described.  Choosing the various factors and levels The next step is to choose the various factors and determine the number levels for each factor. If a researcher studies hardness of a material, the choice of qualitative or quantitative factors to be defined first. For instance, the study focuses on determining the factors that influence the amount of weight retained in a reference sieve. So the factors chosen are mill running duration, volume of the material and the sieving time. Each factor has three levels.  Response variable or dependent variable Once the factors and levels are selected, the next step is to collect the responses. In the current study, the dependent variable is the weight retained in the 125 microns reference sieve, i.e. for a particular combination of the operational variables chosen the corresponding response variable is recorded. The true response is at a very high cost of experimentation. So, the magnitude of risk to be accommodated in selection of the sample size is decided. Many recommended experimental designs must be statistically accurate and economical. Mathematical model of experimentation will be necessary for the statistical analysis.
Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 9  Conducting the experiment Once the response variable is input, in order to determine the main effects and the interaction effects, the variables should be multiplied. In the study, the main variables are the mill running duration, volume of the material and the sieving time. Interacting variables will be combination of these variables that results in second and third order equations. Replications have to be performed so as to ensure that there is little or no variance in the response variable gauged. Control is the key factor to eliminate the confounded relationship. Randomization, measurement, accuracy and maintaining as uniform an experimental environment as possible are important.  Analysis Statistical analysis is the basis if hypothesis to be tested. Graphical methods are handy and easy to understand. Simulation helps in analysis. By means of Taguchi approach, it is possible to determine the ranking of the main variables, i.e. identifying the variable that has more significant influence on the response variable. By numerical analysis, it is possible to determine whether the hypothesis is supported or not for a particular level of significance.  Interpretation, Inferences & Conclusion It is possible to determine, the influence of main effect and interaction effect on the response variable. All statements must be justified by supporting it with results of the analysis. Statistical inferences must be physically interpreted, and practical significance of the finding has to be evaluated. Synthesis may be necessary for higher level of implications. 2. Application and Benefits of DOE This section describes the various applications and benefits of DOE. 2.1 Applications of DOE DOE is a multipurpose tool that can help in many situations. A common use is planning an experiment to gather data to make a decision between two or more alternatives. In some cases, where there are multiple outputs and there is need to achieve a desirable outcome, DOE can be helpful. 2.2 Benefits of DOE Mathews (2010) stated that DOE helps to evaluate the cause and effect relationship between a set of service process variables and service performance characteristics. It enables the organizations to quantify and understand the important process variables that cause variation so that the processes can be improved.  A 20 to 70% reduction in problem-solving time. DOE gives the answers that seek minimum expenditure of time and resources.  A minimum 50% reduction in cost due to testing, machine time, labour and materials.  A 200 to 300% increase in the value, quality, and reliability of the information generated. When used correctly, DOE can provide the answers to specific questions about the behaviour of the system using an optimum number of experimental observations. 3. Methodology This section gives the details of generating the base data based on the lab experiments on rod mill and application of DOE using Minitab 17 software. The three factors chosen are mill running duration, volume of the material and sieving time. The response variable here is the quantity retained in the reference sieve. In the current study, the reference sieve is taken as 125 microns. Each factor has three levels. The numbers of replicates chosen are two. Replication or repetition is done to see whether there is any deviation when the same experiment is conducted twice. The various levels and factors taken for the study are shown in Table 1. Altogether 54 experiments were conducted. Table 1: The factors and levels Particulars Running Duration (minutes) Volume (Kgs) Sieving Time (minutes) Level 1 5 0.5 5 Level 2 10 1.0 10 Level 3 15 1.5 15 3.1 Procedure for carrying out experimentation on rod mill To carry out the laboratory experiments, basalt samples were prepared. 500 gm, 1 kg and 1.5 kg samples were prepared with 2-3 per cent tolerance limit on the sample quantity. The rods of various sizes were put in the mill followed by the sample. The lids were then closed and the mill was rested in the horizontal position. The time was then set. The Insmart rod mill operates at 46 rpm. Accordingly the number of revolutions equivalent for 5, 10 and 15 minutes of operation was set and the mill was started (Figure 2). Once the operation was completed, the rods were removed and the mill was placed in the vertical position so as to discharge the crushed sample from the mill. The ground sample of basalt can be seen in Figure 3. The crushed sample was then collected in the tray and fed into the top most sieve of the sieve assembly. The entire assembly of sieves was then placed in the Insmart Ro-tap (rotational and tapping) sieve shaker (Figure 4). The material was sieved for 5, 10 and 15 minutes. The quantity of sample retained in the sieve was weighed by means of the weighing scale. The weight retained in percentage, cumulative weight retained (X) and the quantity passed was determined. DOE approach was then used
K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 10 to determine the influence of main effects and the interactive ones on the response variable. The details of the various experiments conducted along with the quantity retained has been shown in Table 2. The Insmart Ro-tap sieve shaker along with the various sieves that was used for experimentation is shown in Figure 4. Sieve analysis is one of the oldest methods of size analysis and is accomplished by passing a known weight of sample material into series of successively finer sieves to determine percentage of weight retained in each size fraction (Venkatachalam and Degaleesan, 1982). The sets of sieve is generally selected as the ratio of the size of the opening of successive sieve is constant and equals to 2 (Wills, 2006). To find the feed material distribution, sieve analysis was carried out for nearly 500 gm, 1 kg and 1.5 kg sample with sieves set of following sizes as shown in Table 3. Figure 2 Insmart Rod Mill Where, SO= Standard Order (experiments are chosen randomly from the lot), Run Order= the actual number of experiments, RD= Mill running duration in minutes, V= Volume of the basalt sample taken in kilograms, ST= Sieving time in minutes, Qty retained= Amount of basalt weight retained in the reference sieve of 125 microns in grams. Figure 3 The ground sample of basalt Table 2: DOE Data for experiments conducted on rod mill SO RO RD (min) V (Kg) ST (min) Qty retained (gm) RD*V V*ST ST*RD RD*V*ST 20 1 15 0.5 10 312.2 7.5 5.0 150.0 75.0 26 2 15 1.5 10 296.2 22.5 15.0 150.0 225.0 11 3 10 0.5 10 281.3 5.0 5.0 100.0 50.0 13 4 10 1.0 5 296.0 10.0 5.0 50.0 50.0 49 5 15 1.0 5 300.2 15.0 5.0 75.0 75.0 35 6 5 1.5 10 266.2 7.5 15.0 50.0 75.0 16 7 10 1.5 5 239.1 15.0 7.5 50.0 75.0 12 8 10 0.5 15 316.3 5.0 7.5 150.0 75.0 50 9 15 1.0 10 302.6 15.0 10.0 150.0 150.0 21 10 15 0.5 15 320.3 7.5 7.5 225.0 112.5 37 11 10 0.5 5 262.0 5.0 2.5 50.0 25.0 47 12 15 0.5 10 313.7 7.5 5.0 150.0 75.0 27 13 15 1.5 15 297.1 22.5 22.5 225.0 337.5 23 14 15 1.0 10 303.4 15.0 10.0 150.0 150.0 6 15 5 1.0 15 292.1 5.0 15.0 75.0 75.0 15 16 10 1.0 15 302.3 10.0 15.0 150.0 150.0 14 17 10 1.0 10 295.6 10.0 10.0 100.0 100.0 40 18 10 1.0 5 297.0 10.0 5.0 50.0 50.0 8 19 5 1.5 10 262.3 7.5 15.0 50.0 75.0 41 20 10 1.0 10 297.0 10.0 10.0 100.0 100.0 31 21 5 1.0 5 290.0 5.0 5.0 25.0 25.0 24 22 15 1.0 15 308.9 15.0 15.0 225.0 225.0 2 23 5 0.5 10 286.0 2.5 5.0 50.0 25.0
Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 11 4 24 5 1.0 5 286.0 5.0 5.0 25.0 25.0 33 25 5 1.0 15 292.3 5.0 15.0 75.0 75.0 52 26 15 1.5 5 290.0 22.5 7.5 75.0 112.5 46 27 15 0.5 5 309.0 7.5 2.5 75.0 37.5 42 28 10 1.0 15 303.4 10.0 15.0 150.0 150.0 28 29 5 0.5 5 261.0 2.5 2.5 25.0 12.5 43 30 10 1.5 5 240.6 15.0 7.5 50.0 75.0 7 31 5 1.5 5 241.1 7.5 7.5 25.0 37.5 51 32 15 1.0 15 305.0 15.0 15.0 225.0 225.0 17 33 10 1.5 10 289.1 15.0 15.0 100.0 150.0 30 34 5 0.5 15 302.0 2.5 7.5 75.0 37.5 38 35 10 0.5 10 281.9 5.0 5.0 100.0 50.0 54 36 15 1.5 15 299.3 22.5 22.5 225.0 337.5 9 37 5 1.5 15 279.8 7.5 22.5 75.0 112.5 1 38 5 0.5 5 256.2 2.5 2.5 25.0 12.5 36 39 5 1.5 15 276.1 7.5 22.5 75.0 112.5 3 40 5 0.5 15 299.0 2.5 7.5 75.0 37.5 44 41 10 1.5 10 290.0 15.0 15.0 100.0 150.0 45 42 10 1.5 15 292.4 15.0 22.5 150.0 225.0 19 43 15 0.5 5 308.0 7.5 2.5 75.0 37.5 18 44 10 1.5 15 292.7 15.0 22.5 150.0 225.0 10 45 10 0.5 5 264.2 5.0 2.5 50.0 25.0 53 46 15 1.5 10 294.3 22.5 15.0 150.0 225.0 34 47 5 1.5 5 243.2 7.5 7.5 25.0 37.5 25 48 15 1.5 5 291.0 22.5 7.5 75.0 112.5 32 49 5 1.0 10 285.3 5.0 10.0 50.0 50.0 39 50 10 0.5 15 317.2 5.0 7.5 150.0 75.0 22 51 15 1.0 5 300.9 15.0 5.0 75.0 75.0 29 52 5 0.5 10 288.0 2.5 5.0 50.0 25.0 5 53 5 1.0 10 284.7 5.0 10.0 50.0 50.0 48 54 15 0.5 15 319.1 7.5 7.5 225.0 112.5 Table 3: Sizes of sieve taken for sieve analysis Mesh Number Sieve Size (mm) Sieve Size (µm) 8 2.4 2400 16 1.2 1200 30 0.6 600 60 0.25 250 120 0.125 125 230 0.063 63 400 0.037 37 After arranging the sieves into descending order of the size of opening, the material was poured into the top sieve i.e. 8 mesh sieves and a bottom pan was also provided to hold the 400 mesh size material. The full setup of the sieve was then placed onto the Ro- tap sieve shaker (Figure 4 a and b). After 5, 10 and 15 minutes of shaking each size, the fraction of material were weighed and results were noted down. The residuals plot for the response variable is shown in Figure 5. From the histogram it is clear that data follows a normal distribution. The probability plots show that the points are close to the best fit line and the fitness plots show that the points do not follow a pattern which indicates that the results are good enough. The constant variance statement can be checked with Residuals versus Fits plot. The plot displays random arrangement of residuals on either sides of 0. The analysis of variance (ANOVA) needs that the observations should be arbitrarily chosen from the population. All the main effects and the interaction effects have a significant influence on the response variable purchase as their value is less than 0.05 for 5% level of significance (Table 4). From Table 4 it is clear that the main effect running duration has the highest influence on followed by sieving time and volume. Figure 4 (a) Sieve of different sizes
K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 12 Figure 4 (b) Ro-tap sieve shaker Figure 5 Residual plot for the response variable Table 4: The p-value, Main effect and Interaction effect Source DF Adj SS Adj MS F- Value p- Value % Effect Model 18 20607.30 1144.85 31.13 Linear 6 16339.40 2723.23 74.06 Running Duration 2 6595.50 3297.76 89.68 0.00* 30.12 Volume 2 4327.20 2163.58 58.84 0.00* 19.76 Sieving Time 2 5416.70 2708.36 73.65 0.00* 24.74 2-Way Interactions 12 4267.90 355.66 9.67 RD * Volume 4 960.00 240.01 6.53 0.00* 4.38 RD * ST 4 1346.10 336.53 9.15 0.00* 6.15 Volume * 4 1961.80 490.44 13.34 0.00* 8.96 ST Error 35 1287.10 36.77 Lack of fit 8 1222.30 152.78 63.68 Pure Error 27 64.80 2.40 Total 53 21894.40 Model Summary S R-sq R-sq (Adj) R-sq (pred) 6.06 408 94.12% 91.10%% 86.01% *Indicates there is a significant influence on the response variable. The R-sq value for the model is 94.12%. This means that 94.12% of the variance in the amount of material retained in the 125 microns sieve (dependent variable) is explained by the mill running duration, volume of the material and the sieving time (which are the independent variables chosen in the study). Figure 6 Main effects plot for SN ratios SN ratio is the ratio of signal to noise. For better response the signal should be higher and the noise should be the least. The main effects plot for SN Ratios is shown in Figure 6. Let the mill running duration be denoted by A1, A2, and A3. Volume levels are denoted by B1, B2, and B3 and the sieving time levels denoted by C1, C2, and C3. From the graph it can be inferred that strategy A3 B2 C3 that is high mill running duration, mid volume and increased sieving time are the best levels for the response variable as they have the highest slopes. 3.2 Regression Regression is the determination of a statistical relationship between two or more variables. Basically there exist two variables namely independent variable which is the cause of the behavior of another one that is dependent variable. A regression equation was established that comprised terms reflecting interactions. After eliminating the terms having lower p values as error terms and including the effects of only those terms that had effective p values in the
Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 13 model, the regression equation for quantity retained in the reference sieve was established as below. y=β0+ β1x is called simple linear regression. The regression equation is thus given by (only main effects considered) as following based on table-5. Quantity retained in the reference sieve = 255.78 + 2.66* Running Duration- 17.61* Volume + 2.44 Sieving Time Table 5: Table of Regression Term Coef SE Coef T Value p value Constant 255.78 7.18 35.60 Running Duration 2.66 0.40 6.60 0.00* Volume -17.61 4.04 -4.36 0.00* Sieving Time 2.44 0.40 6.05 0.00* 3.3 Taguchi analysis: Quantity retained versus mill running duration, volume of the material and sieving time The response variable here is the quantity retained in the reference sieve. Taguchi Analysis is carried out to know the rankings of the main effects on the response variable (Table 6). Delta is calculated by subtracting the highest value in the column with smallest value. For instance the highest value for Mill running duration is 52.42 and the least value is 46.02. Delta is calculated as 52.42-46.02= 6.39. Higher value of delta indicates higher ranking of the main effect. For the experiment conducted mill running duration is ranked 1 followed by volume of the material and sieving time. Table 6: Response Table for SN Ratio Levels Running Duration (minutes) Volume (Kgs) Sieving Time (minutes) 1 46.02 48.39 47.43 2 52.42 52.00 50.25 3 49.96 48.02 50.72 Delta 6.39 3.97 3.29 Rank 1 2 3 5. Acknowledgments The authors acknowledge the research funding of M/S InSmart Systems, Hyderabad, India to carry out the research studies. References [1] A. Gupta, and D.S.Yan, “Mineral Processing and Design Operations: An Introduction”, Elsevier Publications, ISBN 9780444516367, pp. 99–106, 2006. [2] Altekar, M., Homon, C.A., Kashem, M.A., Mason, S.W., Nelson, R.M., Patnaude, L.A., Yingling, J. and Taylor, P.B., “Assay Optimization: A Statistical Design of Experiments Approach”, JALA Tutorial, pp. 34– 35, 2006. [3] B.A. Wills, “Mineral Processing Technology: An Introduction to the Practical Aspects of Ore Treatment and Mineral Recovery”, 7th ed. Amsterdam; Boston, MA (4). pp. 157, ISBN 0750644508, 2006. [4] L.B. Barrentine, “An Introduction to Design of Experiments: A Simplified Approach, American Society for Quality Control”, ISBN 9780873894449, 1999. [5] P. Mathews, “Design of Experiments with MINITAB”, New Age International, ISBN 9788122431117, 2010. [6] S. Venkatachalam, and S.N. Degaleesan, Laboratory Experiment in Mineral Engineering, Oxford & IBH Publishing Co., New Delhi, Chap. 2, 1982.
www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.14-20 #SPL02090303 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s D KARTHIGEYAN School of Architecture, Hindustan Institute of Technology and Science, Chennai, India Email: dkarthikeyan@hindustanuniv.ac.in Abstract: Chennai, the biggest industrial, commercial, cultural, economic and educational center in South India is the capital city of the state of Tamil Nadu. Birth of this city dates back to 1639 when the English, established Fort St. George and built George Town in its vicinity which today stand as the Central Business District (CBD) of the city. Sub-CBDs have emerged in the Southern, Western and Northern Part of the city due to rapid Urbanization and enormous population explosion. This change in the character of the settlement pattern, clearly establishes the transformation of the city from the Burgess model during 1940’s which depends on a single CBD as its core, to the sector model in 1970’s which shows the change in the pattern of development due to the growth of Public Transportation and in 1970’s the Multi Nuclei Model, where certain specific localities emerge as sub CBD’s in certain specific category to assist the Main CBD. The city shows this transformation in almost all aspects but not to 100% as mentioned by the authors who formulated these theories. This paper is an attempt to establish the relationship between the CBD and Sub CBD’s in the light of ecological models. Keywords: Central Business District, CBD, Sub CBD’s and Chennai City 1. Introduction For centuries, cities have been the heart, the lifeblood of various civilizations and the epicenter of economic, political & artistic activities. Cities exert an increasing attraction on people worldwide and the population tends to concentrate in big cities. In developing countries, cities contribute more than 2/3rd of the country’s Gross Domestic Product (GDP). 2. Settlement Pattern A city is not a work of a day or a decade. It takes generations and generations to build a city. According to Victor (2012), a settlement initially starts as pedestrian oriented with streets in primitive stage, and the boundaries are limited by the distance one could walk in a reasonable period of time. C. A Doxiadis (1964), too agree with this reasons, as he points out that in the olden days the size of the towns are restricted to 2 km by 2 km which one could walk within a reasonable time and the population not more than 50,000 inhabitants. And he further elaborates to say that major capital cities cannot be restricted to this size, and it has to grow much beyond to accommodate the population of more than one million where the size could be restricted to not more than 6 Km by 6 Km. Victor (2012), further says that with the advent of Industrial revolution and migration of population towards the cities to work in the industries, paved way for the settlements to expand with the development of radial suburban rail corridors, along with few streets. These rail corridors were initially part of intercity rail tracks. Tram lines were developed and service’s extended along certain corridors, shaping the city into a better organized and developed urban area, with concentration of activities at the city center. As Commuter rail traffic started to grow, an outward spread of population were visible, as suburban areas started to emerge at a distance from the city center. Further concentration of population occurred along these rail corridors. New roadway arterials were formed radially between the radial railway lines. As city matures into a metropolis, radial and circumferential grid forms with some of the traffic corridors being rail based and the rest road based. This enhancement of connectivity accelerates the expansion and growth of the city. Chennai city is also one such city which developed in this manner. All the above said stages of development of a city are shown in Figure 1. Figure 1 Typical pattern of urban growth
Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 15 According to Victor (2012), the city’s population density will be highest in the Central Business District, and as the distance increases the density decreases, which is due to the concentration of economic and commercial activities as part of agglomeration economics. This is diagrammatically shown in Fig: 2. Figure 2 Schematic Diagram of Urban Area in Regional setting As the city grows to become a metropolis, the pressure on the CBD increases, which will lead to other problems like traffic congestion, distance between the CBD and sub urban area increases, and so on. So, all these factors will force the emergence of sub CBD’s within the metropolitan region, which will have better accessibility and other needed infrastructure facilities. This sub CBD’s comes in all the directions at a considerable distance from the CBD. The distance between the CBD and Sub CBD depends on the population and the extent of the Metropolitan area. Figure 3 Emergence of Sub CBD’s as relief poles 3. Indian Port Cities The development of port cities of Mumbai, Kolkata and Chennai as a prominent urban center and major metropolis of India is the work of the English, who wants to establish settlements in the coastal region for their trade related activities. These three cities have, in turn, worked as nuclei for the development of Maharashtra, West Bengal and Tamil Nadu states respectively, which are, at present, the most industrially advanced states of the country. Here an attempt is made to study the relationship between the classical ecological models with the city of Chennai, travelling through its growth history from 1940’s to till date. 4. Chennai The pre-eminence of Chennai in the urban scene of Tamil Nadu is discernible from the fact that the next biggest agglomeration of the state, Coimbatore and Madurai each hardly account for more than one fifth of the total population of Chennai Urban Agglomeration. According to Census of India 2011, the city had 4.68 million residents, making it the sixth most populous city in India; the Metropolitan Area, which comprises the city and its suburbs, was home to approximately 8.9 million, making it the fourth most populous metropolitan area in the country. As per Census 2011, the population of Chennai Metropolitan Area (CMA) is 8.9 million i.e., 12.3 % of the population of Tamil Nadu. This proportion has steadily increased from 8.51 %, 9.51 %, 10.42 % and 11.28 % during the years 1971, 1981, 1991 and 2001 respectively. The Second Master Plan for CMA, 2026 has projected that the population will increase to 11.19 million in 2021 and 12.58 million in 2026. Today, total extent of CMA is less than 1 percent (0.914 percent) of the total extent of the Tamil Nadu state but accommodate more than 12 percent of its population. Table: 1 Growth of population and population density in Tamil Nadu, Chennai City, Chennai urban Agglomeration and CMA during 1961 – 2011 Description Year 1961 1971 1981 1991 2001 2011 Tamil Nadu Population (In Lakhs) 336 411 484 558 624 721 Extent (sq. km.) 130069 130050 Density (persons per sq.km.) 259 317 372 430 480 555 Decadal growth rate (percentage) … 22. 17.5 15.3 11.7 15.6 Chennai city Population (In Lakhs) 17 24 32 38 43 46 Extent (sq. km.) 128.83 176 Density (persons per 13.5 19.1 18.6 21.8 24.6 26.9
D KARTHIGEYAN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 16 sq.km.) (In Thousands) Decadal growth rate (Percentage) --- 41.1 32.6 17.2 13.0 7.8 Chennai Urban Agglomeration Population (In Lakhs) 19 31 42 54 64 86 Decadal growth rate (Percentage) … 63.0 35.3 26.4 18.4 35.3 Chennai Metropolitan Area (including Chennai City) Population (In Lakhs) … 35 46 58 70 89 Extent (sq. km.) … 1189 1189 1189 1189 1189 Density (persons per sq.km.) … 2948 3870 4894 5921 7500 Decadal growth rate … … 31.2 26.4 21.0 26.6 Source: Census of India and Second Master Plan for Chennai Metropolitan Area 2026 Density in the CMA is as less as 75 persons per hectare as per Census 2011, which indicates huge scope for accommodating higher population densities as against the already denser (269 persons per hectare) Chennai city, which is shown in detail in Table: 1. 5. Evolution of Chennai Map 1 Road Map of Chennai In the early 16th century, Chennai was basically a group of small villages which were self-contained and had their own agricultural production & household industries for its survival. These villages were mostly planned around a temple, which forms its identity. The prominent villages were Mylapore and Triplicane, one a saivite and another an vaishnavite settlement. It is widely believed that Saint Thiruvalluvar lived in Mylapore. The foundation for the development of the Chennai was laid in 1639 as a British settlement and later expanded as a new town around Fort St. George. During 17th century, important roads of communication like the Poonamallie High Road, Santhome High Road and Lal Bagthadur Sashtri Road, where established which actually linked these small villages. The population, which was 19,000 in 1646, expanded to 40,000 in 1669 and the surroundings of the Fort area covering 16 hamlets were constituted as the City of Madras in 1798. In the 18th century, Mount Road was established, which still functions as the major arterial road connecting the city to the southern districts of the state. In the 19th century, establishment of the railway line, and harbor close to the George Town (CBD) helped the city to develop itself as a major commercial center in south India. Pattern of radial roads were development from the George Town in three principal directions connecting the northern, southern and western region and ring roads were development to enhance the connectivity, which is shown in Map: 1. The Eastern side was not developed, due to the presence of Coromandel Coast. 6. Emergence of Chennai as Major commercial center in South India (1940’s) In the early 20th century, George Town established itself as the main business centre but still substantial parts of it were used for residential purposes. Both sides of Mount Road, radiating from George Town upto a distance of 5 to 6 kms were occupied by large business houses, clubs and hotels; industries were few and were located in George Town and Perambur which is located in the northern part of the city. Bungalows started to come up in Kilpauk, Nungambakkam and Chetpet. By 1941 Chennai city had developed itself into a provincial metropolis enjoying the best of both worlds i.e., urban amenity and rural atmosphere. During this period, city established itself as a major commercial, military and administrative centre for the entire South India. 6.1 Burgess Model Figure 4 Burgess Model According to Park (1925), Burgess Model assumes a relationship between the socio-economic status (mainly income) of households and the distance from
Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 17 the Central Business District (CBD). The further from the CBD, the better the quality of housing, but longer the commuting time. Thus, accessing better housing is done at the expense of longer commuting times (and costs). Figure 5 Bid Rent Curve Burgess model is based on Bid Rent Curve, which assumes that the Value of the land is based on the profits that are obtainable from maintaining a business on that land. Map 2 Superimposition of Burgess Model in Chennai during 1940’s According to this model, a large city is divided in six concentric zones: 6.1.1 Zone I: Central Business District (CBD) Business activities, i.e., tertiary employment are located and urban transport infrastructure is converging, making it the most accessible. George Town – CBD of Chennai city is the place where all major business activities are preformed and NH4, NH5 and NH45 converges from the northern, western and southern directions. 6.1.2 Zone II: Factory Many industrial activities located to take advantage of nearby labor and markets. Most transport terminals (port sites and rail yards), are located adjacent to the central area. Chintadripet & Perambur locations are the one where industries started to come up and some are still running even today. It is very close to the harbor and railway stations. It also has many residential settlements nearby as labor market. 6.1.3 Zone III: Transition This zone is gradually been reconverted to other uses by expanding manufacturing / industrial activities. It contains the poorest segment of the urban population, (notably first generation immigrants) living, in the lowest housing conditions. Mannadi, an residential settlement very close to George town and perambur, established in 1940’s to take advantage of the industrial revolution, but still exist as the same. The public infrastructure in this neighbourhood is very much lower than what is needed today. 6.1.4 Zone IV: Working Class Dominated by the working class, those who were able to move away from the previous transition zone (often the second generation immigrants). Advantage of being located near the major zones of employment (I and II) and thus represents a low cost location for the working class. Vepery, a residential community is one of the finest examples. This area is famous for its schools, and other infrastructure facilities which is much better when compared to the transition zone. 6.1.5 Zone V: Residential Represents higher quality housing linked by longer commuting costs. Alwarpet and Nungmabakkam, a prominent high class residential area during 1940’s, but today it has become a mixed residential area. This is the place where many Britishers lived during that time. It is famous for its bunglow type of houses. 6.1.6 Zone VI: Commuter Mainly high class people with expensive housing in the rural & suburban areas. The commuting costs are the highest. Prior to mass diffusion of the automobile (1930s), most of these settlements were located next to rail stations. Tambaram, a residential suburb, located at a distance of more than 20 Km from the CBD in the southern side of the city. 7. Emergence of Chennai as a Major Metropolis of India (1970’s) After Independence, the population of the city got doubled from one million to two million within a span of 20 years. This sudden increase in population is due to the enormous industrial growth through the five year plans of the central government. This transformed the city into a major metropolis of national importance. The structure of the city was then approximated to a semi-circle with extensions in
D KARTHIGEYAN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 18 all possible directions from George Town and Harbour. Naturally all communication lines led to this centre and these in turn were linked with each other producing a radial and ring pattern of development. 7.1 Sector Model Hoyt (1939) suggests through his sector theory that urban areas develop in sectors alongside the main transport routes like railroads, highways and other transportation arteries into and out of a city. Various transportation routes represented greater access which makes the cities tended to grow in wedge-shaped pattern or sector. According to this model, the city is divided into five sectors, namely 7.1.1 Central Business District CBD means higher level of access and highest land value. Hoyt model almost agreed with the Burgess version of CBD as stated in the Burgess Model. In Chennai, during 1970’s George Town and its extension towards Mount road in southern direction together constitute the central business district of the City where most of the wholesale trade, specialized retail trade, banking and financial institutions were located. Figure 6 Hoyt Sector Model Map 3 Superimposition of Hoty’s Model in Chennai city during 1970’s 7.1.2 Factories/Industry Manufacturing functions developed in a wedge shape surrounding transportation routes. In Chennai, Large Scale Industries are located on the northern side of the city, especially at Manali & Ennore, whereas larger industrial estates are located on the west at Ambattur with the Heavy Vehicles Factory located further west at Avadi. Nearly 40 percent of the industrial work places are located on the north and northwestern part of the City. One more Industrial estate located on the southern part of the city planned along with Ambattur Industrial estate for a similar purpose namely Guindy Industrial estate along the Mount Road, today got converted to IT offices and other non-Polluting industries after 1990’s. 7.1.3 Low class residential Residential functions would grow in wedge-shaped patterns with a sector of low-income housing bordering manufacturing/industrial sectors due to its traffic, noise, and pollution makes these areas the least desirable. In Chennai, Washermanpet & Mannadi located in the northern and north western part of the city is completely surrounded by Industries on all the sides. 7.1.4 Middle class residential Middle income households were located furthest away from the industries. Development of residential neighborhoods occurs along the Sub urban rail network. Pallavaram, Chrompet, Saidapet, & St. Thomas Mount which was easily accessed by the sub urban rail network paved the way for the residential development for the growing middle class people. 7.1.5 High class residential It is unlikely that high class residential housing would be found near to factories or lower quality housing zones, since these residencies exercise a powerful influence on the location of undesirable neighbors. Gopalapuram, Poies Garden and Wallace Garden – all high class residential settlement found very close and accessible to mount road are occupied right now by the second and third generations of super rich people. High status residential area will also spread out along the lines of the sector by the addition of new belts of housing beyond the outer arc of the city. Besant Nagar, Adyar and Thiruvanmiyur which was planned by the City Development Authorities around 1950’s as a residential suburb. But, today these locations house the first and second generations of super rich people, which was the edge of the city corporation when it was planned. 8. Emergence of Chennai as a Major Business center in South Asia In 1990’s though George Town and Anna Salai continued as CBD, Mylapore, Thyagaraya Nagar, Nungambakkam, and Purasawalkam have developed
Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 19 as Regional Commercial Centres and Adyar, Anna Nagar and Perambur have developed as Regional Commercial Sub-Centres. This is due to the encouragement of growth along the major transport corridors and development of urban nodes at Manali, Minjur, Ambattur, Avadi, Alandur and Tambaram which all forms the outer edge of the city during this period. Government initiatives like the Relocation of wholesale Vegetable, Fruit & Flower Market and Mofussil Bus Terminus from George Town to Koyambedu, located on western edge of the city corporation limit was an initiative along the development of regional sub CBD’s and was completed in late 1990’s; Other initiatives like the shifting of Iron and Steel Market to Sathangadu, operation of a separate truck terminal at Madhavaram to avoid the entry of trucks into the city areas, and the development of Satellite town, beyond city limits at Maraimalai Nagar paved way for it. 8.1 Multi Nuclei Model Harris (1945), in his Multi Nuclei theory states that cities of greater size will develop substantial suburban area and some suburbs, having reached significant size, will start to function as smaller business districts. These smaller business districts acts as satellite nodes, or nuclei, of activity around which land use patterns will be formed. Even though CBD still acting as the major center of commerce, specialized cells of activities would develop according to specific requirements of certain activities, rent-paying abilities, and the tendency for some kinds of economic activity to cluster together. Figure 7 Multi Nuclei Model During 1990’s Thyagaraya Nagar emerged as the sub CBD for Textile and Jewellery Market. During this period Mint Street and Godown Street which are located in the CBD and doing business for Jewellery & textile Market was also functional but it is truly too little of space to handle the demand of a growing metropolis. The emergence of T. Nagar was also coupled by good accessibility, availability of public transport system and its location which is very close to the Gemini Circle which in 1990’s was considered as the center of the city, as the city was expanding very fast on the southern side. According to this model, city is divided into nine zones. At the center of this model is the CBD, which is still taken care by George Town, with light manufacturing and wholesaling activities located along transport routes like the Kolkata Highway, etc. Heavy industries would locate near the outer edge of city, perhaps surrounded by lower-income households, and suburbs of commuters like Sriperumpudur, Oragadam & Maraimalai Nagar, which was identified for large scale heavy industrial development, and all these locations were actually located in the adjoining districts of chennai like Kanchipuram and Thirvallur Districts. These locations are actually planned for heavy industries by the government, and they have also provided the necessary infrastructure for the same. This is a planned initiative, and not developed on its own. Map 4 Superimposition of Multi Nuclei Model in Chennai during 1990’s In these Multi Nuclei cities, some of the nuclei will be pre-existing settlements like T. Nagar, which today is a market for Textile and Jewellery, but it was originally planned as a Brahmin Settlement before independence; and others arising from urbanization and external economies like Adyar, Anna Nagar, which was planned as a residential area after independence, but today it stands as a regional commercial sub centers. According to Multi Nuclei theory, the numbers and functions of the nuclei differ from city to city, and it marks the city's growth. Each nucleus will vary in size and character, and the importance they exert in cities economic development. Some Nuclei’s are large industrial sites while others may be small strip
D KARTHIGEYAN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 20 shopping centers. Each Nuclei acts as a growth pole for a particular kind of land use (industry, retail, or high-quality housing). As these expand, they merge to form a single urban area, which is the phase in which the city is moving today. According to the theory, Creating smaller business districts (or individual nuclei) enable people in the suburbs to have better access to the facilities of the CBD and industrial sectors for commerce and employment. 9. The Future of Chennai City Tamil Nadu is the second largest software exporter in the country, and 90% of its export is from Chennai city alone, especially from its IT corridor (OMR). A large I.T Park at Siruseri, located at the end of the IT corridor is developed, which housing the TCS’s biggest office in the city. Chennai is also a major export hub of South East Asia. International car manufactures have established their manufacturing bases here, which make this city as the Detroit of South Asia. Large Scale manufacturing industrial activities at Sriperumpudur, and Mahindra World city developed over 1700 acres; near Maraimalai Nagar new town are some of the major developments happening today. All these developments are located within a distance of 25 to 35 Km from the CBD and Sub CBD’s are already emerged. With these new developments Chennai can emerge as a prominent business headquarters for the whole of South Asia. But due to these sudden pressures of development and in the process of expansion, the city has engulfed several fishing, agricultural villages and hamlets creating several ecological and environmental challenges that the current governance and administrative machinery is unable to cope up with. Pallikarani Marsh Land is one such location which requires our immediate attention. These IT related activities developed a lot of residential neighbourhoods around the city like Pallavaram, Thoraipakkam, Velachery which have resulted in urban sprawl. 10. Conclusion Chennai is emerging as a major metropolis of the world, and to continue its dominance in the economic, social, political and cultural front, as a Nucleus of regional development; it’s infrastructure, housing and other supporting facilities has to be planned and developed to international standards; also its Administrative machinery and governance system has to be trained and changed to be investor friendly, otherwise the city will lose its importance as the Nucleus of this regions development. References [1] http://www.medwelljournals.com/fulltext/?doi=pj ssci.2010.244.253 [2] Doxiadis (1964), “Ekistics – the science of Human settlement”, Ekistics 197, April 1972. [3] Harris, C. D. and E. L. Ullman. 1945. “The Nature of Cities”, Annals of the American Academy of Political and Social Science [4] Hoyt, Homer. 1939. The Structure and Growth of Residential Neighborhoods in American Cities. Federal Housing Administration, Washington, D. C. [5] Majid Husain (2012), Geography of India, Third edition, Tata Mcgraw hill’s winning we edge series, New Delhi. [6] Park, R. E. and E. W. Burgess. (1925), “The City”, Macmillan Co. [7] D Johnson Victor and S. Ponnuswamy (2012), “Urban Transportation: Planning, Operation and Management”, Tata Mcgraw-hill, New Delhi. [8] Second Master Plan 2026, Chennai Metropolitan Development Authority, Chennai. [9] Xiang Ming Chen, Anthony M. Orum, Krista E. Paulsen, (2013), “Introduction to Cities: How Place and Space Shape Human Experience”, Wiley Blackwell Publications. [10]Development Plan for Chennai Metropolitan Area, April, 2006, Government of Tamil Nadu.
www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.21-25 #SPL02090304 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Mechanical Properties of High Calcium Flyash Geopolymer Concrete V C PRABHA AND V REVATHI Department of Civil engineering, K.S.R. College of Engineering, Tiruchengode, Tamil Nadu, INDIA Email: prabhacsamy@gmail.com, revthiru2002@yahoo.com Abstract: The present study deals with the mechanical properties of High Calcium Fly Ash Geopolymer Concrete (HCFA GPC). A preliminary study was made on high calcium fly ash geopolymer mortar by varying sodium based alkaline activator to binder ratio to find an ideal composition. Alkaline activators were the mixture of sodium hydroxide (NaOH) and sodium silicate (Na2SiO3. Based on the compressive strength of high calcium fly ash geopolymer mortar, the optimum mix combination was arrived for the further study on concrete. Upon the optimum mix combination, mechanical properties such as compressive strength, split tensile strength and modulus of elasticity were further determined. Test results depict that strength properties of HCFA GPC were marginally higher under steam curing than ambient curing. Keywords: Geopolymer, High Calcium fly ash, Alkaline activator, Steam Curing, Strength Properties 1. Introduction Manufacturing of Portland cement is an energy intensive process and releases a large amount of greenhouse gases to the atmosphere. Recently, another form of cementations materials using silicon and aluminum activated in a high alkali solution was developed. It is referred as geopolymer or alkali- activated binder. Geopolymers was first developed by Davidovits, which consists of SiO4 and AlO4 tetrahedral networks [1-3]. Alumina silicate reactive materials dissolve in strong alkaline solutions and free SiO4 and AlO4 tetrahedral structure forms. It is also well known that geopolymers possess excellent mechanical properties [4]. Several factors such as curing mode, curing temperature, alkaline liquid to binder ratio, molarity of sodium hydroxide, ratio of sodium hydroxide to sodium silicate solution are the key factors in developing geopolymeric reaction [5-8]. The geopolymer mixtures may be subjected to curing either at room temperature or at a given temperature. It is mentioned that the reaction of the fly ash in the production of geopolymers is low at ambient temperatures [9]. The geopolymer concrete achieves high compressive strength at given temperatures between 40 to 95C [10]. Yunfen et al. [11] demonstrated the influence of concentration and modulus (SiO2: N2O) of sodium silicate solutions and curing mode in geopolymers prepared. It can be seen that the compressive strength increased with increase in modulus of sodium silicate solution. However, when the modulus exceeds 1.4, compressive strength decreased [12]. Also, elevated temperatures can increase the early strength buildup of the samples. However, the later strength after 7 days was the same at irrespective of different temperature [13, 14]. Among various source materials, low calcium fly ash (LCFA) is extensively used for geopolymer owing to its easy availability and enhanced properties. [15].As well, abundant work on geopolymer has been reported with the use of low calcium fly ash. Despite, a quite reasonable work is carried out with the use of high calcium fly ash for geopolymer. High calcium fly ash (HCFA) also contains a considerable amount of silica and alumina. [16]. High calcium fly ash has few drawbacks compared to low calcium fly ash in geopolymer. The early age compressive strength of high calcium fly ash geopolymers attains under high pressure and high temperatures of curing to get the similar strength of ordinary Portland cement binder [17-19]. While molarity of NaOH as 8M is found suitable for LCFA, HCFA needs 10M for the geopolymer synthesis [20-22]. Turkish construction industry promoted HCFA geopolymer for both cast-in-place and precast concrete products. Steam curing was applied to develop adequate compressive strength for form removal at age 1-day [23].Compressive strength and microstructure of HCFA geopolymer depend upon mass of water to fly ash ratio and [19-21]. The annual output of lignite fly ash from Neyveli Lignite Corporation station 28.5 million tons per annum at Neyveli and one open cast lignite mine of capacity 2.1 million tonnes per annum. This fly ash contains a high percentage of calcium and is being used quite extensively for construction in Tamilnadu. The knowledge of the use of high calcium lignite fly ash in producing geopolymer would be beneficial to increase the scope of HCFA. In the above background, the present study made an attempt to determine the mechanical properties of HCFA geopolymer concrete under ambient curing and steam curing. In this respect, a preliminary study was
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IJEE (Vol 09 No 03)-3rd ICEE 2016 SPL Issue-Final Copy

  • 1. June 2016 Volume 09 SPL No 03 ISSN 0974-5904 INTERNATIONAL JOURNAL OF EARTH SCIENCES AND ENGINEERING Indexed in: Scopus Compendex and Geobase (products hosted on Engineering Village) Elsevier, Amsterdam, Netherlands, Geo-Ref Information Services-USA, List B of Scientific Journals in Poland, Directory of Research Journals SJR: 0.17 (2014); H-index: 6 (2015); CSIR-NISCAIR, INDIA Impact Factor 0.042 (2011) EARTH SCIENCE FOR EVERYONE Special Issue of 3rd International Conference on Earth Sciences and Engineering (ICEE 2016) 17th-18th June, 2016 http://icee.cafetinnova.org/ Jointly Organized by Department of Civil Engineering, Nehru Institute of Technology, Coimbatore, India & Cafet Innova Technical Society, Hyderabad, India Published by CAFET-INNOVA Technical Society Hyderabad, INDIA http://cafetinnova.org/
  • 2. CAFET-INNOVA Technical Society 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda Hyderabad – 500 029, Andhra Pradesh, INDIA Website: http://www.cafetinnova.org Mobile: +91-7411311091 Registered by Government of Andhra Pradesh Under the AP Societies Act., 2001 Regd. No.: 1575 The papers published in this journal have been peer reviewed by experts. The authors are solely responsible for the content of the papers published in the journal. Each volume, published in six bi-monthly issues, begins with February and ends with December issue. Annual subscription is on the calendar year basis and begins with the February issue every year. Note: Limited copies of back issues are available. Copyright © 2015 CAFET-INNOVA Technical Society All rights reserved with CAFET-INNOVA Technical Society. No part of this journal should be translated or reproduced in any form, Electronic, Mechanical, Photocopy, Recording or any information storage and retrieval system without prior permission in writing, from CAFET- INNOVA Technical Society.
  • 3. INTERNATIONAL JOURNAL OF EARTH SCIENCES AND ENGINEERING The International Journal of Earth Sciences and Engineering (IJEE) focus on Earth sciences and Engineering with emphasis on earth sciences and engineering. Applications of interdisciplinary topics such as engineering geology, geo- instrumentation, geotechnical and geo-environmental engineering, mining engineering, rock engineering, blasting engineering, petroleum engineering, off shore and marine geo-technology, geothermal energy, resource engineering, water resources and engineering, groundwater, geochemical engineering, environmental engineering, atmospheric Sciences, Climate Change, and oceanography. Specific topics covered include earth sciences and engineering applications, RS, GIS, GPS applications in earth sciences and engineering, geo-hazards such as earthquakes, landslides, tsunami, debris flows and subsidence, rock/soil improvements and development of models validations using field, laboratory measurements. Professors / Academicians / Engineers / Researchers / Students can send their papers directly to: chiefeditor_ijee@yahoo.com CONTACT: For all editorial queries: D. Venkat Reddy (Editor-in-Chief) Professor, Department of Civil Engg. NIT-Karnataka, Surathkal, INDIA  +91-9739536078  dvr1952@gmail.com All other enquiries: Hafeez Basha. R (Managing Editor)  +91-9866587053  hafeezbasha@gmail.com Raju Aedla (Editor)  +91-7411311091  rajucits@gmail.com
  • 4. EDITORIAL COMMITTEE D. Venkat Reddy NITK, Surathkal, Karnataka, INDIA EDITOR-IN-CHIEF Trilok N. Singh IIT-Bombay, Powai, INDIA EXECUTIVE EDITOR P. Ramachandra Reddy Scientist G (Retd.), NGRI, INDIA EXECUTIVE EDITOR R. Pavanaguru Professor (Retd.), OU, INDIA EXECUTIVE EDITOR Joanna Maria Dulinska Cracow University of Tech., Poland EXECUTIVE EDITOR Hafeez Basha R CAFET-INNOVA Technical Society MANAGING EDITOR Raju Aedla CAFET-INNOVA Technical Society EDITOR INTERNATIONAL EDITORIAL ADVISORY BOARD Zhuping Sheng Texas A&M University System USA Choonam Sunwoo Korea Inst. of Geo-Sci & Mineral SOUTH KOREA Hsin-Yu Shan National Chio Tung University TAIWAN Hyun Sik Yang Chonnam National Univ Gwangu SOUTH KOREA Krishna R. Reddy University of Illinois, Chicago USA L G Gwalani NiPlats Australia Limited AUSTRALIA Abdullah MS Al-Amri King Saud University, Riyadh SAUDI ARABIA Suzana Gueiros Dra Engenharia de Produção BRAZIL Shuichi TORII Kumamoto University, Kumamoto JAPAN Luigia Binda DIS, Politecnico di Milano, Milan ITALY Gonzalo M. Aiassa Cordoba Universidad Nacional ARGENTINA Nguyen Tan Phong Ho Chi Minh City University of Technology, VIETNAM Ganesh R. Joshi University of the Rykyus, Okinawa JAPAN Kyriakos G. Stathopoulos DOMI S.A. Consulting Engineers Athens, GREECE U Johnson Alengaram University of Malaya, Kuala Lumpur, MALAYSIA Robert Jankowski Gdansk University of Technology POLAND Paloma Pineda University of de Sevilla, Seville SPAIN Vahid Nourani Tabriz University IRAN Anil Cherian United Arab Emirates DUBAI P Hollis Watts WASM School of Mines Curtin University, AUSTRALIA Nicola Tarque Department of Engineering Catholic University of Peru S Neelamani Kuwait Institute for Scientific Research, SAFAT, KUWAIT Jaya naithani Université catholique de Louvain Louvain-la-Neuve, BELGIUM Mani Ram Saharan National Geotechnical Facility DST, Dehradun, INDIA G S Dwarakish NITK- Surathkal Karnataka, INDIA Subhasish Das IIT- Kharagpur, Kharagpur West Bengal, INDIA S Viswanathan IIT- Bombay, Powai, Mumbai Maharashtra, INDIA K U Maheshwar Rao IIT- Kharagpur, Kharagpur West Bengal, INDIA Ramana G V IIT– Delhi, Hauz Khas New Delhi, INDIA Usha Natesan Centre for Water Resources Anna University, Chennai, INDIA M R Madhav JNTU- Kukatpally, Hyderabad Andhra Pradesh, INDIA Kalachand Sain National Geophysical Research Institute, Hyderabad, INDIA R Sundaravadivelu IIT- Madras Tamil Nadu, INDIA M K Nagaraj NITK- Surathkal Karnataka, INDIA Arash Ebrahimabadi Azad University, Qaemshahr IRAN S M Ramasamy Gandhigram Rural University Tamil Nadu, INDIA Gholamreza Ghodrati Amiri Iran University of Sci. & Tech. Narmak, Tehran, IRAN Chachadi A G Goa University, Taleigao Plateau Goa, INDIA Girish Gopinath Geomatics Division CWRDM, Kerala, INDIA Shamsher B. Singh BITS- Pilani, Rajasthan Rajasthan, INDIA C Natarajan NIT- Tiruchirapalli, Tamil Nadu, INDIA N Ganesan NIT- Calicut, Kerala Kerala, INDIA Linhua Sun Suzhou University CHINA Pradeep Kumar R IIIT- Gachibowli, Hyderabad Andhra Pradesh, INDIA Vladimir e Vigdergauz ICEMR RAS, Moscow RUSSIA
  • 5. D P Tripathy National Institute of Technology Rourkela, INDIA E Saibaba Reddy JNTU- Kukatpally, Hyderabad Andhra Pradesh, INDIA Chowdhury Quamruzzaman Dhaka University Dhaka, BANGLADESH Parekh Anant kumar B Indian Institute of Tropical Meteorology, Pune, INDIA Datta Shivane Central Ground Water Board Hyderabad, INDIA Gopal Krishan National Institute of Hydrology Roorkee, INDIA Karra Ram Chandar NITK- Surathkal Karnataka, INDIA Prasoon Kumar Singh Indian School of Mines, Dhanbad Jharkhand, INDIA A G S Reddy Central Ground Water Board, Pune, Maharashtra, INDIA Rajendra Kumar Dubey Indian School of Mines, Dhanbad Jharkhand, INDIA Subhasis Sen Retired Scientist CSIR-Nagpur, INDIA M V Ramanamurthy Geological Survey of India Bangalore, INDIA A Nallapa Reddy Chief Geologist (Retd.) ONGC Ltd., INDIA Bijay Singh Ranchi University, Ranchi Jharkhand, INDIA S Suresh Babu Adhiyamaan college of Engineering Tamil Nadu, INDIA C Sivapragasam Kalasalingam University, Tamil Nadu, INDIA Xiang Lian Zhou ShangHai JiaoTong University ShangHai, CHINA Debadatta Swain National Remote Sensing Centre Hyderabad, INDIA Kripamoy Sarkar Assam University Silchar, INDIA Ranjith Pathegama Gamage Monash University, Clayton AUSTRALIA B M Ravindra Dept. of Mines & Geology, Govt. of Karnataka, Mangalore, INDIA Nandipati Subba Rao Andhra University, Visakhapatnam Andhra Pradesh, INDIA M Suresh Gandhi University of Madras, Tamil Nadu, INDIA Autar Krishen Raina CSIR-CIMFR, Maharashtra, INDIA H K Sahoo Utkal University, Bhubaneswar Odissa, INDIA R N Tiwari Govt. P G Science College, Rewa Madhya Pradesh, INDIA Nuh Bilgin Istanbul Technical University Maslak, ISTANBUL M V Ramana CSIR NIO Goa, INDIA N Rajeshwara Rao University of Madras Tamil Nadu, INDIA Manish Kumar Tezpur University Sonitpur, Assam, INDIA Salih Muhammad Awadh College of Science University of Baghdad, IRAQ Sonali Pati Eastern Academy of Science and Technology, Bhubaneswar, INDIA Safdar Ali Shirazi University of the Punjab, Quaid-i-Azam Campus, PAKISTAN Naveed Ahmad University of Engg. & Technology, Peshawar, PAKISTAN Raj Reddy Kallu University of Nevada 1665 N Virginia St, RENO Glenn T Thong Nagaland University Meriema, Kohima, INDIA Raju Sarkar Delhi Technological University Delhi, INDIA Hanumantha Rao B School of Infrastructure IIT Bhubaneswar, INDIA Samir Kumar Bera Birbal sahni institute of palaeobotany, Lucknow, INDIA C N V Satyanarayana Reddy Andhra University Visakhapatnam, INDIA S M Hussain University of Madras Tamil Nadu, INDIA Vladimir Vigdergauz ICEMR, Russian Academy of Sciences Moscow, RUSSIA T J Renuka Prasad Bangalore University Karnataka, INDIA Deva Pratap National Institute of Technology Warangal, INDIA K. Subramanian Coimbatore Institute of Technology Tamil Nadu, INDIA Mohammed Sharif Jamia University New Delhi, INDIA A M Vasumathi K.L.N. College of Inf. Tech. Pottapalayam, Tamil Nadu, INDIA Deepak T J INTI International University Kaula Lumpur, MALAYSIA C J Kumanan Bharathidasan University Tamil Nadu, INDIA B R Manjunatha Mangalore University Karnataka, INDIA Sivaraja M N.S.N College of Engg. & Technology Tamilnadu, INDIA Ch. S. N. Murthy NITK- Surathkal Karnataka, INDIA Jitendra Virmani Jaypee Uni. of Information Tech. Himachal Pradesh, INDIA K Elangovan PSG College of Technology Coimbatore, INDIA Vikram Vishal Department of Earth Sciences IIT Roorkee, INDIA A K Verma Indian School of Mines Dhanbad, Jharkhand, INDIA Saeed Khorram Eastern Mediterranean University Famagusta, CYPRUS
  • 6.
  • 7. INDEX Volume 09 June 2016 No.03 RESEARCH PAPERS Analysis of Effect of Reinforcement on Stability of Slopes By AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY 01-06 Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach By K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN 07-13 Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s By D KARTHIGEYAN 14-20 Mechanical Properties of High Calcium Flyash Geopolymer Concrete By V C PRABHA AND V REVATHI 21-25 Assessment of Wave Energy Potential along South Maharashtra Coast By JUSTIN THOMAS T, K H BARVE, L R RANGANATH AND G S DWARAKISH 26-31 Experimental Investigation on Strength Aspects of Glass Fiber-Reinforced Fine Grained Soil By SUCHIT KUMAR PATEL AND BALESHWAR SINGH 32-39 Role of Time Buffer on Project Monitoring and Forecasting of Steel Structures – A New Approach to Structural Planning By VISHNU S PILLAI AND C RAJASEKARAN 40-45 Utilization of Ground Granulated Blast Furnace Slag and Pulverized Fly ash in the Manufacture of Stabilized Mud Blocks By VENKATALAKSHMIYARLAGADDA AND BEULAH M 46-53 Characteristics of Concrete Containing Waste Foundry Sand and Slag Sand By JOJU JOSE AND NABIL HOSSINEY 54-59 Numerical Analysis of Bucket Foundations under Eccentric Lateral Loading in Medium Dense Sand By TANMOY KUMAR DEB AND BALESHWAR SINGH 60-65 A Short Review of Anaerobic Co-Digestion and Feasibility of Anaerobic Co-Digestion of Sewage and Food Waste for Sustainable Waste Management By DIWAKAR SOMANI, HARSHITA SRIVASTAVA, SABUMON P C AND ANJALI G 66-70 Eco-efficient Fiber Reinforced Self Compacting Concrete for Replacements of Cement and Natural Sand with Waste Materials By PRASAD M L V, PRASENJIT SAHA, ABHILASHA S AND MD FAISAL KARIM 71-77 Psychological Effects of Travel Time Use By YOSRITZAL 78-83 RS - GIS based Operational Monitoring of Indian Maritime and Environs By P KESAVA RAO, J K KISHORE, L J VIJAYA KUMAR AND MURTHY REMILLA 84-92
  • 8. Simulation of Damage of Waterfront Structure of Port of Kobe during Hyogo-ken Nanbu Earthquake by Using Three-Dimensional Non-linear Parallel Finite Element Analysis By JAFRIL TANJUNG AND MAKOTO KAWAMURA 93-99 Feasibility Study of Powdered Curry Leaf and Amla Fruit as Potential Filter Media for Treating Contaminated Lake Water By N NATARAJAN, D HEMANTH KUMAR, K SAI SARAN NAVEEN, K AKHIL, K A GANESH BABU, A JYOTHSNA LAXMI AND M VASUDEVAN 100-104 Using QSWAT for Simulating Streamflow in a Highland Catchment of Humid Tropics By CELINE GEORGE AND ASWATHY MOHAN 105-108 A Critical Review of Multi Criteria Decision Making Methods for Infrastructure Planning and Sustainability Assessment of Infrastructure Projects By B SURESH, ERINJERY JOSEPH JAMES AND JEGATHAMBAL P 109-123 Soil Structure Interaction in Indian Seismic code: Recommendations for Inclusion of Potential Factors By RAVI KANT MITTAL, ADITI AND SANKET RAWAT 124-130 Estimation of PMP and Precipitations of Various Return Periods Using Statistical Approach–A Case Study for Gunderipallam Dam, Tamil Nadu, India By S DIRAVIA BALAN AND M KRISHNAVENI 131-136 Integrated River Basin Plan for Achencoil River in Kerala State, India By LINDA P JAMES AND A B ANITHA 137-143 Optimum Configuration of Rigid Barriers to Mitigate Avalanche Hazard By VINAY CHAUDHARY, R K VARMA AND MAN MOHAN SINGH 144-148 Properties of Bitumen Containing Powdered Gondorukem Rubber Additives By ELSA EKA PUTRI AND PUJA PERDANA 149-153 Analysis of Historical Strong Earthquake Impacts on Landslides at the Gansu Segment in the Bailongjiang River Basin, China By SHOUYUN LIANG, WANJIONG WU, RUISHOU BA AND YUTIAN KE 154-160 Development of Subsurface Profile Using Geophysical Test Data By SHIVAMANTH ANGADI, MAYANK K DESAI AND GOUDAPPA R DODAGOUDAR 161-164 Quality Control of Cationic Emulsion Modified Cold Mix in Flexible Pavement By M S RANADIVE AND ANUP KUMAWAT 165-169 Investigation of Influence of Terrain on Rainfall for Vembanad Basin, Kerala, India By RAKTIM HALDAR AND RAKESH KHOSA 170-174 Influence of Zinc Oxide Nanoparticle on Strength and Durability of Cement Mortar By D NIVETHITHA AND S DHARMAR 175-181 A Review on Seismic Performance of Reinforced Masonry Structures By UMADEVI R, A S ARUN KUMAR AND B V RAVI SHANKAR 182-187 Effect of Waste Paper Sludge Ash on Engineering Behaviors of Black Cotton Soils By R BARANI DHARAN 188-191 Effectiveness of Bamboo Fiber as a Strength Enhancer in Concrete By KAVITHA S AND T FELIX KALA 192-196
  • 9. Use of Gold Mine Tailings in Production of Concrete-A Feasibility Study By B M RAMALINGA REDDY, K S SATYANARAYANAN, H N JAGANNATHA REDDY AND N PARTHASARATHI 197-202 Experimental Investigation on the Behaviour of Bagasse Ash Reinforced Concrete Structural Members By S AISHWARYA, K DAKSHAYINI AND P GAJALAKSHMI 203-207 Generation of Synthetic Ground Motion for a Hard Rock Site in Intra Plate Region By A RAVI KIRAN, S BANDOPADHYAY, M K AGRAWAL AND G R REDDY 208-214 Modeling and Controlling of an Coordinated Power Control Grid Connected Hybrid System with Wind, PV and Fuel Cell Sources By N S SRAMAKRISHNA, D N GAONKAR AND G S BHARATHI 215-220 An Advanced GIS based Storm Water Drainage Networking Design for Bhimrad Area of Surat City (India) By MANISHA DESAI AND JAYANTILAL N PATEL 221-228 The Performance of the Accessibility to BRT Stop: A Case Study on Transpadang Metro Bus By BAMBANG ISTIJONO, BAYU MARTANTO ADJI, TAUFIKA OPHIYANDRI, JOVI SATRIOS AND YOSRITZAL 229-234 Parents Perception toward Road Safety Related to the Potential of Cycling to School in Urban Area By BAYU MARTANTO ADJI, MOHAMED REHAN KARIM, BAMBANG ISTIJONO AND TAUFIKA OPHIYANDRI 235-243 Linkages between Catchment Landscape Dynamics and the Natural Flow Regime By VINAY S, BHARATH H A, SUBASH CHANDRAN M D, SHASHISHANKAR A AND RAMACHANDRA T V 244-251 Impact Study on Ferrocement Slabs with Different Types of Mortar Matrices By SEERAM APOORVA, M SAIHARAN, M ARAVINTHAN, H THAMIM ANSARI AND M NEELAMEGAM 252-257 Flexural Behaviour of Cold Formed Steel Hat Shaped Beams By ASHOK M, JAYABALAN P AND JAYA PRABHAKAR K 258-263 Observation of Earthquake Precursors - A Study on OLR Scenario Prior to the Earthquakes of Indian and Neighboring Region Occurred in 2016 By N VENKATANATHAN, V HAREESH AND W S VENKATESH 264-268 Stability Assessment of a Hill Slope-An Analytical and Numerical Approach By B BURAGOHAIN, J KUNDU, K SARKAR AND T N SINGH 269-273 Predictions of Vulnerability Flood and Flood Prone Areas in Watershed West Sumatra Province using Arc-GIS and Category Value By DARWIZAL DAOED, BUJANG RUSMAN, BAMBANG ISTIJONO AND ABDUL HAKAM 274-279 Economic Design of Reinforced Concrete Columns under Direct Load and Uniaxial Moments By SONIA CHUTANI AND JAGBIR SINGH 280-284 Investigation on Partial Replacement of Coarse Aggregate using E-Waste in Concrete By BALASUBRAMANIAN B, GOPALA KRISHNA GVT AND SARASWATHY V 285-288
  • 10. West Sumatra Landslide During in 2012 to 2015 By ABDUL HAKAM AND BAMBANG ISTIJONO 289-293 Performance on the Study of Nano Materials for the Development of Sustainable Concrete By S SANJU, S SHARADHA AND J REVATHY 294-300 Assessment of Flood Induced Area using Geo-Spatial Technique By AJEET SINGH CHHABRA, SNIGDHADIP GHOSH AND VIJAY KUMAR DWIVEDI 301-304 Deformational Behaviour of Coal Measure Rocks By ASHUTOSH TRIPATHY, BANKIM MAHANTA AND TN SINGH 305-309 Analysis and Design of Transmission Tower Using STAAD.PRO By SAI AVINASH P, RAJASEKHAR P, SIDDHARDHA R, HARINARAYANAN R, CHAMANDEEP AND YASHDEEP 310-313 Strength Properties of Roller Compacted Concrete Pavements Containing Fly ash and Triangular Polyester Fiber By PRAMOD KESHAV KOLASE AND ATUL K DESAI 314-322 Study on the Structural Behavior of Concrete Encased Steel Composite Members By U ELAKEYA, A BHUVANESH SRE AND P GAJALAKSHMI 323-329 Hot Pixel Identification using Satellite Hyper-spectral Data By PIYUSH KUMAR GAURAV, VIVEK KUMAR GAUTAM, P MURUGAN AND M ANNADURAI 330-334 Experimental Study on the Structural Performance of Composite Beam with J-hook Connectors By SARATHKUMAR S, SIVACHIDAMBARAM M AND REVATHY J 335-340 Influence of Fly Ash on Durability and Performance of Concrete By V SESHASAYEE, B H BHARATKUMAR AND P GAJALAKSHMI 341-346 Performance Comparison of Band Ratio and Derivative Ratio Algorithms in Chlorophyll-A Estimation using Hyperspectral Data By P MURUGAN, R SIVAKUMAR, R PANDIYAN AND M ANNADURAI 347-352 Structural Response of FRP Strengthened PSC Beams By VIGNESH C K, SIVARANJAN D AND REVATHY J 353-359 Strength and Setting Times of F-Type Fly Ash-Based Geopolymer Mortar By KOLLI RAMUJEE 360-365 Groundwater Prospects Mapping in Korapuzha River basin, Kerala, India - An Integrated Approach using Multicriteria Decision Making and GIS Techniques By AMAL P SIVADAS, JESIYA N P AND GIRISH GOPINATH 366-372 Optimum Position of Multi Outrigger Belt Truss in Tall Buildings Subjected to Earthquake and Wind Load By A S JAGADHEESWARI AND C FREEDA CHRISTY 373-377 Study on Reduction in Delay due to Road Accidents using Variable Message Sign By GANGHA G, ARUNIMA JAYAKUMAR AND NIRMAL KUMAR P 378-382 Spatial and Temporal Variation in Groundwater Quality and Impact of Sea Water in the Cauvery Delta, South India By ASWIN KOKKAT, P JEGATHAMBAL AND E J JAMES 383-392
  • 11. Waste Water Treatment by Phyto-Remediation Technique By ADITYA VIKRAM CHOPRA, UMANG K SHAH AND J S SUDARSAN 393-399 An Experimental Investigation on Effect of Hybrid Fiber on High Strength Self Compacting Concrete and Vibrated Concrete By K J N SAI NITESH AND S VENKATESWARA RAO 400-403 Viscosity Graded Approach for Quality Control of Bitumen By M S RANADIVE AND VINAYAK BOBADE 404-410 Effects of Domestic Rawsewage on Mechanical Properties of Concrete Incorporating GGBS (Ground Granulated Blast Furnace Slag) By SHILPA S RATNOJI, PRAVEEN S MALLAPUR, SHASHANK KANAVALLI AND K B PRAKASH 411-414 Experimental Investigation on Modulus of Elasticity of Recycled Aggregate Concrete By P S KULKARNI, A GHATGE, O KANK, A NAIR AND R ASWAR 415-419 Geotechnical Characteristics of Volcanic Soils in and around Taiz City, Yemen By JANARDHANA M R AND ABDUL-ALEAM AHMED A D AL-QADHI 420-425 Experimental Studies on the Effect of Bagasse Ash and M-Sand on Mechanical Behaviour of Concrete By BHUVANESHWARI M AND TAMILARASAN S 426-431 Factors Contributing to the Success of a Resettlement Project: A Case Study on Batanghari Dam Project, Indonesia By TAUFIKA OPHIYANDRI, UYUNG GATOT S DINATA, TAFDIL HUSNI, BAMBANG ISTIJONO AND ADI PUTRA 432-435 An Immediate Review of Flood Characteristics on Delta Lowland Sumatra using D8 Model Spatial Analysis By NURHAMIDAH, AHMAD JUNAIDI AND LIBRINA ANGGRAINI 436-442
  • 12. www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.01-06 #SPL02090301 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Analysis of Effect of Reinforcement on Stability of Slopes AKSHAY KUMAR JHA 1 , MADHAV MADHIRA 2 AND G V N REDDY 2 1 Indian Railways, Hyderabad, India 2 JNTU Hyderabad, Hyderabad, India Email: akshayghungru@gmail.com, madhavmr@gmail.com, gvnreddy@jntuh.ac.in Abstract: Steepening of slopes for construction of rail/road embankments or for widening for other civil engineering structures is a necessity for development. Use of geosynthetics for steep slope construction or repair of failed slopes considering all aspects of design and environment could be a viable alternative to this problem. Literature survey indicates that efforts were made for optimization of length of reinforcement. The present paper details an analysis to optimize the length of geosynthetics from the face or near end of the slope with respect to its location and length to obtain the desired minimum factor of safety. Unreinforced and reinforced slopes are analyzed to obtain critical factors of safety. The effect of providing geosynthetic layer in shifting the critical slip circle has been identified and studied. Keywords: Reinforcement, Optimization of length, Critical slip circle, Reinforced slope, Geosynthetics 1. Introduction The analysis of earth slopes is the oldest geotechnical engineering problem that engineers have been dealing with using various techniques. The methods can be classified as Limit Equilibrium Methods, Finite Element Method based on c, reduction, Finite Element Modeling/Finite Difference Method, combination of FEM and LEM, Limit Analysis (LA), etc. Geosynthetic reinforcement of earth slope results in reducing the land requirement (Fig. 1) and preservation of natural resources (land and backfill requirements) apart from time and cost. Designing geosynthetic reinforced slope with minimum length of geosynthetics leads to further economy. Base Width B1 Less Than B0 Figure 1 Base Widths for Unreinforced and Reinforced slope Ingold [5], Jewell et al. [6], Bonparte et al. [1], Koerner [8], Verduin and Holtz [17] present design methods for earth slopes reinforced with geotextiles or /and geogrids using LEM assuming different types of failure surfaces such as circular or/and bilinear wedges. Jewell et al. [6] used Limit Equilibrium Analysis and local stress calculation for design of reinforced slope. Rowe and Soderman [14] present a method for estimating the short-term stability of reinforced embankment which has simplicity and versatility of LE but incorporates essential component of soil - structure interaction derived from FEM. Leshchinsky and Reinschmidt [9] present an analytical approach based on limit equilibrium and variational extremization of factor of safety for membrane/sheet reinforced slopes for a single layer of reinforcement which satisfies all the requirements of limit equilibrium. Schneider and Holtz [15] present a design procedure for slopes reinforced with geotextiles and geogrids which assumes bilinear surface of sliding and pore water pressures and the initial stress conditions in the slope. Leshchinsky and Boedeker [10] present an approach for stability analysis of geosynthetic reinforced earth structure using log spiral LE approach for multilayer reinforced slope. Jewell [7] presented revised design charts for steep slopes valid for all polymer reinforcement materials. These revised charts lead to savings of the order of 20-30% in reinforcement quantity. Leshchinsky et al. [11] used log spiral failure mechanism to determine the required reinforcement long term strength Zhao [18] presented a kinematic solution of the plasticity theory applied to the stability of geosynthetic reinforced soil slopes. Michalowski [13] presented kinematic limit analysis solution of reinforced slope to determine the amount of reinforcement necessary to prevent collapse of slopes due to reinforcement rupture, pullout, or direct sliding. Shiwakoti et al. [16], conducted parametric studies to investigate the effect of geosynthetic strength, soil- geosynthetic interaction coefficients, vertical spacing of geosynthetics for soil slope/wall on competent foundation and suggested optimization. Baker and Klein [2,3] modified the top-down approach of Leshchinsky (1992) to find the reinforcement force needed for the same prescribed factor of safety everywhere within the reinforced mass. Han et al. [4] present a general analytical frame work for design of flexible reinforced earth structures regardless of slope face inclination applicable to both walls and slopes.
  • 13. AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 2 Leshchinsky et al. [12] presented a limit equilibrium methodology to determine the unfactored global geosynthetic strength required to ensure sufficient internal stability in reinforced earth structures, which allows seamless integration of design methodologies for reinforced earth walls and slopes. None of the above approach optimizes the length of geosynthetics by curtailing the same from the slope face. The paper details an analysis carried out to optimize the length of reinforcement from face end of slope. 2. Problem Definition An embankment of height, H, of 6.0 m with side slopes of 1.5H to 1V vertical is considered (Fig. 2). The embankment and foundation soil have cohesion, c, of 4 kPa, unit weight, of 18 kN/m3 and angle of shearing resistance, , of 260 . The geosynthetic reinforcement used has adhesion, ca, of 3 kPa, angle of interface friction between soil and reinforcement, , of 20° and ultimate tensile strength, Tult, of 200 kN/m. All the stability analyses have been carried out using Morgenstern-Price method. Figure 2 Definition Sketch 3. Stability Analysis 3.1 Unreinforced Slope Unreinforced embankments of heights 3 m, 4 m, 5 m and 6 m have been analysed using SLOPEW of Geostudio 2004 version and FSmin obtained as 1.60, 1.44, 1.33 and 1.26 respectively. Embankment with height of 6 m has FSmin less than the required value of 1.3 and hence is reinforced with geosynthetic sheet to get FSmin of 1.5. 3.2 Reinforced Slope Effect of varying the length, Lr, of geosynthetic placed at depth, Z0=3.0 m in 6.0 m high embankment is studied by increasing the Lr so as to get FSmin just greater than 1.50. Length, Lr, of the reinforcement to intercept the failure surface at 3.0 m depth was varied from 5.89 m to 6.13 m. FSmin increased from 1.48 to 1.51 (Fig. 3). Figure 3 Critical slip circle for Z0=3.0 m, FSmin = 1.51, Lr = 6.11 m Circles ABC and DEC are the critical slip circles of the unreinforced and the reinforced slopes. PQ is the total length of reinforcement, Lr. The length of reinforcement Lr has two components: QE = effective length, Le, in the stable zone and EP - the length, Lf in the unstable zone. Lf is further divided into lengths Lf1 (EB), the length in the failure zone between the critical slip circles of the reinforced and the unreinforced slopes and length, Lf2, between the critical slip circle of unreinforced slope and slope face (BP) as shown in Fig 3. It should be noted that one of the effects of inclusion of reinforcement in embankment soil is to shift the critical slip circle from ABC to DEC. This shift of the critical circle increases the factor of safety by involving larger slide mass. The effect of varying Lr on mobilized force in the reinforcement (Fr) and the factor of safety (FSmin) with right end fixed at point P and left end (Q) moved outward successively, are summarized in Table 1. Table1: Slope with Z0 = 3.0 m Lr, m Fr , kN/m FSmin 5.89 12.31 1.480 5.95 13.88 1.487 6.00 15.35 1.496 6.11 18.4 1.515 6.13 18.89 1.518 Factor of safety and the load/resistance mobilized in the reinforcement increases with increased length of reinforcement as is to be expected. FSmin increases from 1.48 to 1.51 as the length is increased from 5.89 m to 6.11 m. Similarly resistance mobilized in the reinforcement (Fr) increase from 12.31 kN/m to 18.89 kN/m. The length, Lf = (Lr - Le) is much larger than Le, the effective length of reinforcement contributing to increase in the stabilizing moment/force. The required pullout force in the reinforcement in the stable zone gets mobilized only by the corresponding resistance along the length of the reinforcement in the unstable zone. It would serve no useful purpose if the length of the reinforcement in the unstable zone is more than that required for generating the required stabilizing force. Hence minimizing Lf = (Lr - Le) by moving point P inside the soil mass and away from
  • 14. Analysis of Effect of Reinforcement on Stability of Slopes International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 3 the slope face by curtailing the length of reinforcement but still maintaining FSmin above 1.50 can lead to economy. Accordingly for reinforced slope of Fig 3 Lr has been curtailed from the face end of the slope. As point P is moved inward gradually by reducing Lr, the critical circle continues to be DEC or close to it (Fig. 4), i.e., practically no shift of the critical circle. The minimum length, Lr which provides FSmin = 1.51 is obtained as 3.88 m (Fig. 4). Thus about 36% reduction is length of reinforcement is achieved without sacrificing the stability of the embankment slope as it still has FSmin of 1.51. Figure 4 Critical slip circle for slope with Z0 = 3.0 m, Lr = 3.88 m and FSmin = 1.51 FSmin continues to be close to 1.50 on reducing Lr further but at Lr = 3.78 m FSmin reduces to 1.30 and the critical circle shifts to between circle ABC and the face of the slope, a shallow failure surface. Reinforced slope as in Fig. 4 above, with the minimal length of the reinforcement arrived at, has been analysed for the slip circle ABC (Fig. 5) corresponding to that of unreinforced slope to quantify the FS so obtained. Figure 5 Reinforced slope with Z0 = 3.0 m, Lr = 3.88 m analysed for failure slip circle ABC of unreinforced slope FS for this case works out to be very high at 1.83 indicating that the critical circle that gives minimum factor of safety with reinforcement is very different from the one without the reinforcement. The circle, ABC, is not the critical circle for the reinforced slope case and thus not acceptable implying that the critical circle with consideration of reinforcement is different from that of the unreinforced case. Slope as in Fig. 4 has been analysed further for the critical slip circle DEC of reinforced slope but without considering the effect of reinforcement to get FS of 1.41 (Fig. 6). Figure 6 Slope stability with critical slip circle DEC but without considering the effect of reinforcement The factor of safety for slip circle DEC (the critical slip circle for the reinforced case) but without considering the contribution of the reinforcement is 1.41 and higher than FSmin of 1.26 obtained for the unreinforced slope. Since the critical circle shifts inward, the factor of safety even without considering the effect/contribution of the reinforcement gets increased as the effect of shift of critical slip circle is to increase FS from 1.26 to 1.41. Reinforced slopes with Z0 = 4.0 m and 5.0 m have also been analysed in similar manner as that for Z0 = 3.0 m and the results summarized in Table 2 Table 2: Factors of Safety and Lengths of Geosynthetics for Reinforced Slope with Z0 = 3.0 m, 4.0 m and 5.0 m FS Lr, m Z0, m I II III IV 3.0 1.26 1.51 1.83 1.41 3.88 4.0 1.26 1.51 1.89 1.46 4.15 5.0 1.26 1.51 1.96 1.47 4.94 Legend: I: FSmin for unreinforced slope with critical circle ABC; II: FSmin for reinforced slope with critical circle DEC; III: FS for reinforced slope analysed for circle ABC of unreinforced slope and IV: Reinforced slope analysed for critical slip circle DEC but without considering the effect of reinforcement. 4. Results and Discussion 4.1 Reinforcement At Z0 = 3.0 m FSmin of the slope for unreinforced case is 1.26 (Table 2). If however the slope is analysed with the reinforcement but considering the slip circle to be the
  • 15. AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 4 same (ABC of Fig. 4) as for that for the unreinforced case, FSmin is 1.83. This FS is not the minimum and hence ABC is not the critical for the reinforced case. The contribution of reinforcement in enhancing the stability of a slope is observed to be twofold: (i) shifting of the critical slip circle deeper in to the slope involving larger slide mass or forward involving smaller slide mass and thus enhancing the factor of safety of the slope and (ii) due to contribution of reinforcement to stabilizing force/moment. FSmin of 1.26 for unreinforced case increases to 1.41 due to shifting of the critical circle to DEF an increase of 11.9%. Secondly the contribution of reinforcement to stabilizing moment/force leads to a further increase in factor of safety from 1.41 to 1.51, a contribution of about 8.2%. The contribution of reinforcement to stability in terms of change in FS is defined as follows: relative change in factor of safety due to overall effect of reinforcement (1) relative change in factor of safety due to shift of critical circle due to effect of reinforcement (2) The difference between the two relative factors of safety is the contribution of reinforcement to increase in FS. Changes in RFS for all the three cases i.e. Z0 = 3.0 m, 4.0 m and 5.0 m are detailed in Table 3. Table 3: Relative changes in factors of safety for cases with Z0 = 3.0 m, 4.0 m and 5.0 m Z0, m % % % 3.0 19.8 11.9 7.9 4.0 19.8 15.9 3.9 5.0 19.8 16.7 3.1 FSmin for the reinforced slope is 1.51 while that of the unreinforced slope is 1.26 for all the three cases. Hence percentage relative change in FS, is 19.8. The percentage relative change in FS due to shifting of critical circle, is more for 5.0 m case followed by those for the 4.0 m and 3.0 m cases. For Z0 = 3.0 m, the contribution due to shifting of critical circle is 11.9% and the balance 7.9% is the contribution of the reinforcement. The contributions of reinforcement due to shifting of critical circle are of the order of 12-17% while that due to reinforcement effect is of the order of 3-8% in the three cases analyzed. 4.2 Variation of FSmin and Fr with Lr FSmin varies linearly with length of reinforcement, Lr, for Z0 = 3.0 m, 4.0 m and 5.0 m as shown in Fig. 7. 1.4 1.42 1.44 1.46 1.48 1.5 1.52 1.54 5.6 5.8 6 6.2 6.4 6.6 Fsmin Length,m Length Vs. FSmin 3m 4m 5m Figure 7 FSmin vs. Lr for Z0 = 3.0 m, 4.0 m and 5.0 m FSmin for Z0 = 3.0 m and 4.0 m are close to each other. Variations of loads in reinforcement with length of reinforcement, Lr, are also linear (Fig. 8) but different for the three cases considered. The change in slope of Line in case of Zo =4.0 m is due to change in critical slip circle. 0 2 4 6 8 10 12 14 16 18 20 5.7 5.8 5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 ReinforcementLoad,kN/m Length,m Length Vs. ReinforcementLoad 3m 4m 5m Figure 8 Load in Reinforcement, Fr vs. Length of Reinforcement, Lr for Z0 = 3.0 m, 4.0 m and 5.0 m 4.3 Summary of Results The results of the analysis for length of reinforcement, Lr, and FS are summarized in Table 4. Table 4: Results of Analysis of Reinforced Slope with Z0 = 3.0 m, 4.0 m & 5.0 m Z0, m Lr, m Lopt =P1Q, m Lshift= P1E, m Le, m Lr- Lopt FSminDE F FSshift 3 6.11 3.88 3.26 0.62 2.23 1.51 1.41 4 6.15 4.15 3.93 0.22 2.00 1.51 1.46 5 6.45 4.94 4.79 0.15 1.51 1.51 1.47 Legend: FSshift = FS for DEC slip circle without considering effect of reinforcement; P1Q & P1E lengths of reinforcement (Fig. 4). Saving in length of reinforcement is highest in case of Z0 = 3.0 m being 2.23 m. Similarly the effective length of reinforcement Le is also highest in this case being 0.62 m. The minimum reinforcement length required out of three positions is that for Z0 = 3.0 m. The fact that for the same FSmin higher length of geosynthetics is required in case of 5.0 m is because the length contributing to FS by way of stabilising force/moment is very small i.e. only 0.15 m against
  • 16. Analysis of Effect of Reinforcement on Stability of Slopes International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 5 0.62m of 3.0 m case. All the three critical circles are shown in Fig. 9 for comparison. They are close to each other but far away from that for the unreinforced case. Figure 9 Critical slip circles for reinforcement at Z0 = 3.0 m, 4.0 m and 5.0 m and for unreinforced case The critical circle is practically same (Fig. 9) for reinforcement at 4.0 m and 5.0 m from the top of embankment. Length of geosynthetic contributing to stabilising force/moment is lowest in case of Z0 = 5.0 m and highest in case of Z0=3.0 m. 5. Conclusions An analysis of interaction between an embankment slope and reinforcement is carried to identify and quantify the mechanisms contributing to increased slope stability as reflected in higher factor of safety and to optimize the length of reinforcement to be provided. A typical embankment slope 1.5H:1V of height 6.0 m with a single layer of reinforcement at 3.0 , 4.0 and 5.0 m depths from the top is examined for stability using Morgenstern and Price method. 1. The critical slip circle for the slope with reinforcement shifts inward and is very different from that for the unreinforced slope. 2. The critical circles for slope with the reinforcement at different locations (3.0 to 5.0 m depth) are different but practically same for Z0= 4.0 &5.0 m. 3. The increase in factor of safety with the provision of reinforcement in a slope is because of the shift of the critical slip circle deep in to the slope involving larger sliding mass. This results from the fact that the slip circle is deeper in to the soil and away from the critical circle corresponding to that for unreinforced embankment soil. 4. As a consequence, the reinforcement force generated becomes much smaller than that estimated based on the length corresponding to that estimated with respect to slip circle for the unreinforced slope. 5. The analysis is further carried out by curtailing the length of the reinforcement from the face of the slope to economise the use of geosynthetics. 6. The effect of providing reinforcement in the slope is thus two-fold, viz., shifting of critical circle inside of the embankment involving larger slide mass and by increase in stabilizing force/moment due to bond resistance mobilized in the reinforcement. 7. It is possible to achieve about 23 to 36% saving in the length of the reinforcement length without endangering the stability of the embankment slope. 8. The most significant finding of this study is that the reinforcement can be provided inside and not necessarily from the face of the embankment. References [1] Bonparte R., Holtz R.D. and Giroud, J.P.,"Soil reinforcement design using geotextile and geogrids", Geotextile Testing and design Engineer, ASTM STP 952, J.E.Fluet, Jr., Ed., American society for testing materials, Philadelphia,69-116, 1987. [2] Baker, R. and Klein, Y. “An integrated limiting equilibrium approach for design of reinforced soil retaining structures. Part I-Formulation.” Geotextiles Geomembranes, 22(3), 119-150, 2004 [3] Baker, R. and Klein, Y. “An integrated limiting equilibrium approach for design of reinforced soil retaining structures: Part II – Design examples.” Geotextiles Geomembranes, 22(3), 151-177, 2004 [4] Han J. and Leshchinsky, D., "General analytical framework for design of flexible reinforced earth structures”, J. of Geotechnical and Geoenvironmental Engineering. ASCE, 132, 1427-1435, 2006. [5] Ingold T.S., "An analytical study of Reinforced Embankments", proceedings 2nd international conference on geotextiles, Las Vegas, IFAI, Aug. 83-109, 1982. [6] Jewell, R.A., Paine N. and Woods R.I. " Design methods for steep reinforced embankments" Polymer grid reinforcement, Thomas Telford Limited, London, 70-81, 1985. [7] Jewell, R.A., "Application of the Revised Design Charts for Steep Slopes", Geotextiles and Geomembranes 10(1091), 203- 233,1991 [8] Koerner, R.M. (1990),"Designing with geosynthetics, 2nd Ed., N.J.: Prentice hall. [9] Leshchinsky, D. and Reinschmidt, A.J. , "Stability of membrane reinforced slopes.” J. Geotechnical Engineering, 111 (11), 1285- 1300, 1985. [10]Leshchinsky, D. and Boedeker, R.H., “Geosynthetic reinforced soil structures,” J. of Geotechnical Engineering, 115(10), 1459 – 1478, 1989.
  • 17. AKSHAY KUMAR JHA, MADHAV MADHIRA AND G V N REDDY International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 01-06 6 [11]Leshchinsky D., Ling, H. and Hanks, G., "Unified design approach to geosynthetic reinforced slope and segmental walls." Geosynthetics International, 2(5), 845-881, 1995. [12]Leshchinsky D., Zhu fan and Meehan Christopher L., "Required unfactored strength of geosynthetic in reinforced earth structures", Journal of Geotechnical and Geoenvironmental Engineering,136(2), 281-289, 2010 [13]Michalowski R L, "Stability of uniformly reinforced slopes", Journal of geotechnical and Geoenvironmental engineering, Vol 23, No. 6, 546-556, 1997. [14]Rowe K. and Soderman K. L.," An approximate method for estimating the stability of geotextile- reinforced embankments", Canadian Geotechnical Journal, 22(3), 392-398, 1985. [15]Schneider H.R and Holtz R.D. , " Design of Slopes reinforced with geotextiles and geogrids", Geotextiles and Geomembranes, Vol 3, 29- 51,1986 [16]Shiwakoti, D.R., Pradhan, T.B.S. and Leshchinsky, D., "Performance of geosynthetic - reinforced soil structures at limit equilibrium state", Geosynthetics International,5(6), 555 - 587,1998. [17]Verduin J.R and Holtz R.D, "Geosynthetically reinforced slopes", A new procedure, "Proceedings geosynthetics, San Deigo, IFAI, 1989. [18]Zhao A, "Limit Analysis of geosynthetic - reinforced slopes", Geosynthetics International, Vol. 3, No. 6., 721- 740,.1996.
  • 18. www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.07-13 #SPL02090302 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach K RAM CHANDAR 1 , ASHWIN J BALIGA 1 , B S S RAO 2 AND R K BISEN 2 1 Department of Mining Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore- 575 025, India 2 Insmart Systems, Moosapet, Hyderabad-500 018, India Email: krc_karra@yahoo.com Abstract: The aim of this paper is to study the influence of select variables like mill running duration, volume of material and sieving time on the amount of weight retained in the reference sieve for basalt in a rod mill. Experimental studies were conducted based on the various factors along with their ranges and their effect on the material retained on the sieve (response variable) was determined. Minitab 17 software is used for analysis purpose. Based on the main effects, plots obtained through the general full factorial design, optimum parameters that influenced weight retention in the reference sieve were arrived at. It was found that all the main effects mill running duration, volume of material and sieving time and the interaction effects significantly influenced the weight retention in the chosen reference sieve. The main effects contributed nearly 75% and the interactive effects contributed to approximately 20%, on the amount of weight retained in the chosen reference sieve of 125 microns for ground basalt sample. As innovations are continuously on the rise, the revelation made in this research would significantly contribute to the optimization of the research activities in milling process. Keywords: Design of Experiments, Regression, Rod Mill, Taguchi Analysis 1. Introduction It is always desirable to first conduct experimental tests in laboratory scale before taking it up on an industrial scale. This enables to determine the various parameters such as liberation size, grindability, coarse to medium to fine proportion in any product of the crushing and grinding equipment and the proportion of values of gangue particles in the fines (Wills, 2006). After the mining of ores, except for a few rich in valuable minerals, the vast majority of lean ore contains large amount of gangue particles. In the metallurgical industry, these lean ores comprises of low useful components of mineral and its composition is complex, if it is directly used for smelting to extract metals. The energy consumption will be large and will result in high production costs in such operations. For more economic development and use of low-grade ore, these minerals must go through sorting and enrichment so as to abandon most of the gangue and finally processing the useful minerals in order to reach the smelting requirements. In the beneficiation process, there are two basic steps: First, disassociation that is crushing and grinding the large pieces of ore and dissociating a variety of useful minerals from the ore particles; Second, sorting, separating of particles according to their physical and chemical properties. If the product crushed is not fine enough, then the useful minerals and gangue cannot be fully separated and the sorting will become ineffective; while the pulverized product granularity becomes too thin, resulting in too much crushed particles, though a variety of useful minerals are disassociated completely, the sorting result is not necessarily good, this is because for any material size the sorting method can handle a certain limit. Therefore, the concentration should be on crushing and grinding, to select the full disassociation and crushed material for the sorting operation, so that the particle size can fit the chosen sorting method. Grinding is the final stage in the process of comminution and is achieved by varieties of mills. Mills are devices that comminute solid materials into smaller pieces due to combination of impact and abrasion, either in dry or in wet condition. The comminution takes place due to the action of mechanical forces. In case of rock crushing, this is done to produce a uniform aggregate size for construction purpose or land reclamation activity. Rod mills are analogous to ball mills, but they use long rods for grinding media. The rods grind the ore by tumbling within the mill, similar to the grinding balls in a ball mill. To prevent the conditions leading to rod charge tangling, the length to diameter ratio is maintained at 1.4 to 1.6 (Gupta and Yan, 2006). Grinding action is by line contact between the rods extending the length of the mill. Rods tumble and spin in roughly parallel alignment simulating a series of roll crushers. This results in preferential grinding of coarse material and minimizes production of slimes. Rod mills are used less in comparison to ball mills for grinding minerals. The rods used in the mill, usually high-carbon steel, can vary in both the length and the diameter. However, the smaller the rods, the larger is
  • 19. K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 8 the total surface area and hence, the greater the grinding efficiency (Wills, 2006). The common sizes of mills, the initial size of feed and the reduction ratio of the feed to produce sizes are achievable during the process of comminution. In order to optimise the efficiency of comminution equipment or also to assess the influence of various parameters on the efficiency of crushers and mills, Design of Experiments (DOE) is a very useful tool. Making a set of experiments representative with regard to a given research problem is called Design of Experiments. DOE is used to study any scenario that involves a response and varies as a function of one or more independent variables. DOE is specifically designed to address complex problems where more than one variable may affect a response and two or more variables may interact with each other (Altekar et al., 2006). DOE is used wherever experimental data is collected and analysed. Its use is expected in all branches of scientific research, but DOE is becoming more widespread in engineering, manufacturing, biology, medicine, management, etc. DOE is becoming a versatile tool because of its tremendous power and efficiency. Data can be qualitative or quantitative. Qualitative data characterize things that are sorted by qualitative terms like good, better and best, these cannot be quantified in numerical values. Quantitative data characterize things by size, which requires a system of measurement. Examples of quantitative data are length, time and weight (Barrentine, 1999). DOE is based on problems involving both types of data, and the distinction between them is important. DOE has been used extensively by DuPont, Dow, Goodrich and others for over 30 years. DOE was introduced by Genichi Taguchi in Japan in early sixties. Taguchi's methods became known in the USA in the early 80s when Toyota, Honda, Canon, and many others overtook their American counterparts with high quality products (Mathews, 2010). 1.1 The Experimentation Process A simple model of experimentation is shown in the Figure 1. Processes have inputs that determine how the process operates and outputs that are produced by the process. The purpose of experiment is to determine how the inputs affect the outputs. The inputs are referred to as the variables, factors or predictors and process outputs are called the responses. In addition to these, there are controllable factors which control the process. Uncontrollable factors introduce variability into the response, due to which during replication the same values cannot be obtained, that is performing same experiments yield varied results (Mathews, 2010). Figure 1 The process of experimentation The number of experiments to be carried out is given by the formula (Barrentine, 1999): N=LF * Number of replicates Where, N= number of experiments L= number of levels F= number of factors 1.2 Procedure of Design of Experiments The procedure involved in designing the experiments is described below:  Recognition and statement of the problem There should be a felt need for research, for which there should be literature support. It also should include the clear statement of problem and objectives for research. Some ideas about the expected outcomes or the phenomenon under experimentation should be described.  Choosing the various factors and levels The next step is to choose the various factors and determine the number levels for each factor. If a researcher studies hardness of a material, the choice of qualitative or quantitative factors to be defined first. For instance, the study focuses on determining the factors that influence the amount of weight retained in a reference sieve. So the factors chosen are mill running duration, volume of the material and the sieving time. Each factor has three levels.  Response variable or dependent variable Once the factors and levels are selected, the next step is to collect the responses. In the current study, the dependent variable is the weight retained in the 125 microns reference sieve, i.e. for a particular combination of the operational variables chosen the corresponding response variable is recorded. The true response is at a very high cost of experimentation. So, the magnitude of risk to be accommodated in selection of the sample size is decided. Many recommended experimental designs must be statistically accurate and economical. Mathematical model of experimentation will be necessary for the statistical analysis.
  • 20. Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 9  Conducting the experiment Once the response variable is input, in order to determine the main effects and the interaction effects, the variables should be multiplied. In the study, the main variables are the mill running duration, volume of the material and the sieving time. Interacting variables will be combination of these variables that results in second and third order equations. Replications have to be performed so as to ensure that there is little or no variance in the response variable gauged. Control is the key factor to eliminate the confounded relationship. Randomization, measurement, accuracy and maintaining as uniform an experimental environment as possible are important.  Analysis Statistical analysis is the basis if hypothesis to be tested. Graphical methods are handy and easy to understand. Simulation helps in analysis. By means of Taguchi approach, it is possible to determine the ranking of the main variables, i.e. identifying the variable that has more significant influence on the response variable. By numerical analysis, it is possible to determine whether the hypothesis is supported or not for a particular level of significance.  Interpretation, Inferences & Conclusion It is possible to determine, the influence of main effect and interaction effect on the response variable. All statements must be justified by supporting it with results of the analysis. Statistical inferences must be physically interpreted, and practical significance of the finding has to be evaluated. Synthesis may be necessary for higher level of implications. 2. Application and Benefits of DOE This section describes the various applications and benefits of DOE. 2.1 Applications of DOE DOE is a multipurpose tool that can help in many situations. A common use is planning an experiment to gather data to make a decision between two or more alternatives. In some cases, where there are multiple outputs and there is need to achieve a desirable outcome, DOE can be helpful. 2.2 Benefits of DOE Mathews (2010) stated that DOE helps to evaluate the cause and effect relationship between a set of service process variables and service performance characteristics. It enables the organizations to quantify and understand the important process variables that cause variation so that the processes can be improved.  A 20 to 70% reduction in problem-solving time. DOE gives the answers that seek minimum expenditure of time and resources.  A minimum 50% reduction in cost due to testing, machine time, labour and materials.  A 200 to 300% increase in the value, quality, and reliability of the information generated. When used correctly, DOE can provide the answers to specific questions about the behaviour of the system using an optimum number of experimental observations. 3. Methodology This section gives the details of generating the base data based on the lab experiments on rod mill and application of DOE using Minitab 17 software. The three factors chosen are mill running duration, volume of the material and sieving time. The response variable here is the quantity retained in the reference sieve. In the current study, the reference sieve is taken as 125 microns. Each factor has three levels. The numbers of replicates chosen are two. Replication or repetition is done to see whether there is any deviation when the same experiment is conducted twice. The various levels and factors taken for the study are shown in Table 1. Altogether 54 experiments were conducted. Table 1: The factors and levels Particulars Running Duration (minutes) Volume (Kgs) Sieving Time (minutes) Level 1 5 0.5 5 Level 2 10 1.0 10 Level 3 15 1.5 15 3.1 Procedure for carrying out experimentation on rod mill To carry out the laboratory experiments, basalt samples were prepared. 500 gm, 1 kg and 1.5 kg samples were prepared with 2-3 per cent tolerance limit on the sample quantity. The rods of various sizes were put in the mill followed by the sample. The lids were then closed and the mill was rested in the horizontal position. The time was then set. The Insmart rod mill operates at 46 rpm. Accordingly the number of revolutions equivalent for 5, 10 and 15 minutes of operation was set and the mill was started (Figure 2). Once the operation was completed, the rods were removed and the mill was placed in the vertical position so as to discharge the crushed sample from the mill. The ground sample of basalt can be seen in Figure 3. The crushed sample was then collected in the tray and fed into the top most sieve of the sieve assembly. The entire assembly of sieves was then placed in the Insmart Ro-tap (rotational and tapping) sieve shaker (Figure 4). The material was sieved for 5, 10 and 15 minutes. The quantity of sample retained in the sieve was weighed by means of the weighing scale. The weight retained in percentage, cumulative weight retained (X) and the quantity passed was determined. DOE approach was then used
  • 21. K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 10 to determine the influence of main effects and the interactive ones on the response variable. The details of the various experiments conducted along with the quantity retained has been shown in Table 2. The Insmart Ro-tap sieve shaker along with the various sieves that was used for experimentation is shown in Figure 4. Sieve analysis is one of the oldest methods of size analysis and is accomplished by passing a known weight of sample material into series of successively finer sieves to determine percentage of weight retained in each size fraction (Venkatachalam and Degaleesan, 1982). The sets of sieve is generally selected as the ratio of the size of the opening of successive sieve is constant and equals to 2 (Wills, 2006). To find the feed material distribution, sieve analysis was carried out for nearly 500 gm, 1 kg and 1.5 kg sample with sieves set of following sizes as shown in Table 3. Figure 2 Insmart Rod Mill Where, SO= Standard Order (experiments are chosen randomly from the lot), Run Order= the actual number of experiments, RD= Mill running duration in minutes, V= Volume of the basalt sample taken in kilograms, ST= Sieving time in minutes, Qty retained= Amount of basalt weight retained in the reference sieve of 125 microns in grams. Figure 3 The ground sample of basalt Table 2: DOE Data for experiments conducted on rod mill SO RO RD (min) V (Kg) ST (min) Qty retained (gm) RD*V V*ST ST*RD RD*V*ST 20 1 15 0.5 10 312.2 7.5 5.0 150.0 75.0 26 2 15 1.5 10 296.2 22.5 15.0 150.0 225.0 11 3 10 0.5 10 281.3 5.0 5.0 100.0 50.0 13 4 10 1.0 5 296.0 10.0 5.0 50.0 50.0 49 5 15 1.0 5 300.2 15.0 5.0 75.0 75.0 35 6 5 1.5 10 266.2 7.5 15.0 50.0 75.0 16 7 10 1.5 5 239.1 15.0 7.5 50.0 75.0 12 8 10 0.5 15 316.3 5.0 7.5 150.0 75.0 50 9 15 1.0 10 302.6 15.0 10.0 150.0 150.0 21 10 15 0.5 15 320.3 7.5 7.5 225.0 112.5 37 11 10 0.5 5 262.0 5.0 2.5 50.0 25.0 47 12 15 0.5 10 313.7 7.5 5.0 150.0 75.0 27 13 15 1.5 15 297.1 22.5 22.5 225.0 337.5 23 14 15 1.0 10 303.4 15.0 10.0 150.0 150.0 6 15 5 1.0 15 292.1 5.0 15.0 75.0 75.0 15 16 10 1.0 15 302.3 10.0 15.0 150.0 150.0 14 17 10 1.0 10 295.6 10.0 10.0 100.0 100.0 40 18 10 1.0 5 297.0 10.0 5.0 50.0 50.0 8 19 5 1.5 10 262.3 7.5 15.0 50.0 75.0 41 20 10 1.0 10 297.0 10.0 10.0 100.0 100.0 31 21 5 1.0 5 290.0 5.0 5.0 25.0 25.0 24 22 15 1.0 15 308.9 15.0 15.0 225.0 225.0 2 23 5 0.5 10 286.0 2.5 5.0 50.0 25.0
  • 22. Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 11 4 24 5 1.0 5 286.0 5.0 5.0 25.0 25.0 33 25 5 1.0 15 292.3 5.0 15.0 75.0 75.0 52 26 15 1.5 5 290.0 22.5 7.5 75.0 112.5 46 27 15 0.5 5 309.0 7.5 2.5 75.0 37.5 42 28 10 1.0 15 303.4 10.0 15.0 150.0 150.0 28 29 5 0.5 5 261.0 2.5 2.5 25.0 12.5 43 30 10 1.5 5 240.6 15.0 7.5 50.0 75.0 7 31 5 1.5 5 241.1 7.5 7.5 25.0 37.5 51 32 15 1.0 15 305.0 15.0 15.0 225.0 225.0 17 33 10 1.5 10 289.1 15.0 15.0 100.0 150.0 30 34 5 0.5 15 302.0 2.5 7.5 75.0 37.5 38 35 10 0.5 10 281.9 5.0 5.0 100.0 50.0 54 36 15 1.5 15 299.3 22.5 22.5 225.0 337.5 9 37 5 1.5 15 279.8 7.5 22.5 75.0 112.5 1 38 5 0.5 5 256.2 2.5 2.5 25.0 12.5 36 39 5 1.5 15 276.1 7.5 22.5 75.0 112.5 3 40 5 0.5 15 299.0 2.5 7.5 75.0 37.5 44 41 10 1.5 10 290.0 15.0 15.0 100.0 150.0 45 42 10 1.5 15 292.4 15.0 22.5 150.0 225.0 19 43 15 0.5 5 308.0 7.5 2.5 75.0 37.5 18 44 10 1.5 15 292.7 15.0 22.5 150.0 225.0 10 45 10 0.5 5 264.2 5.0 2.5 50.0 25.0 53 46 15 1.5 10 294.3 22.5 15.0 150.0 225.0 34 47 5 1.5 5 243.2 7.5 7.5 25.0 37.5 25 48 15 1.5 5 291.0 22.5 7.5 75.0 112.5 32 49 5 1.0 10 285.3 5.0 10.0 50.0 50.0 39 50 10 0.5 15 317.2 5.0 7.5 150.0 75.0 22 51 15 1.0 5 300.9 15.0 5.0 75.0 75.0 29 52 5 0.5 10 288.0 2.5 5.0 50.0 25.0 5 53 5 1.0 10 284.7 5.0 10.0 50.0 50.0 48 54 15 0.5 15 319.1 7.5 7.5 225.0 112.5 Table 3: Sizes of sieve taken for sieve analysis Mesh Number Sieve Size (mm) Sieve Size (µm) 8 2.4 2400 16 1.2 1200 30 0.6 600 60 0.25 250 120 0.125 125 230 0.063 63 400 0.037 37 After arranging the sieves into descending order of the size of opening, the material was poured into the top sieve i.e. 8 mesh sieves and a bottom pan was also provided to hold the 400 mesh size material. The full setup of the sieve was then placed onto the Ro- tap sieve shaker (Figure 4 a and b). After 5, 10 and 15 minutes of shaking each size, the fraction of material were weighed and results were noted down. The residuals plot for the response variable is shown in Figure 5. From the histogram it is clear that data follows a normal distribution. The probability plots show that the points are close to the best fit line and the fitness plots show that the points do not follow a pattern which indicates that the results are good enough. The constant variance statement can be checked with Residuals versus Fits plot. The plot displays random arrangement of residuals on either sides of 0. The analysis of variance (ANOVA) needs that the observations should be arbitrarily chosen from the population. All the main effects and the interaction effects have a significant influence on the response variable purchase as their value is less than 0.05 for 5% level of significance (Table 4). From Table 4 it is clear that the main effect running duration has the highest influence on followed by sieving time and volume. Figure 4 (a) Sieve of different sizes
  • 23. K RAM CHANDAR, ASHWIN J BALIGA, B S S RAO AND R K BISEN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 12 Figure 4 (b) Ro-tap sieve shaker Figure 5 Residual plot for the response variable Table 4: The p-value, Main effect and Interaction effect Source DF Adj SS Adj MS F- Value p- Value % Effect Model 18 20607.30 1144.85 31.13 Linear 6 16339.40 2723.23 74.06 Running Duration 2 6595.50 3297.76 89.68 0.00* 30.12 Volume 2 4327.20 2163.58 58.84 0.00* 19.76 Sieving Time 2 5416.70 2708.36 73.65 0.00* 24.74 2-Way Interactions 12 4267.90 355.66 9.67 RD * Volume 4 960.00 240.01 6.53 0.00* 4.38 RD * ST 4 1346.10 336.53 9.15 0.00* 6.15 Volume * 4 1961.80 490.44 13.34 0.00* 8.96 ST Error 35 1287.10 36.77 Lack of fit 8 1222.30 152.78 63.68 Pure Error 27 64.80 2.40 Total 53 21894.40 Model Summary S R-sq R-sq (Adj) R-sq (pred) 6.06 408 94.12% 91.10%% 86.01% *Indicates there is a significant influence on the response variable. The R-sq value for the model is 94.12%. This means that 94.12% of the variance in the amount of material retained in the 125 microns sieve (dependent variable) is explained by the mill running duration, volume of the material and the sieving time (which are the independent variables chosen in the study). Figure 6 Main effects plot for SN ratios SN ratio is the ratio of signal to noise. For better response the signal should be higher and the noise should be the least. The main effects plot for SN Ratios is shown in Figure 6. Let the mill running duration be denoted by A1, A2, and A3. Volume levels are denoted by B1, B2, and B3 and the sieving time levels denoted by C1, C2, and C3. From the graph it can be inferred that strategy A3 B2 C3 that is high mill running duration, mid volume and increased sieving time are the best levels for the response variable as they have the highest slopes. 3.2 Regression Regression is the determination of a statistical relationship between two or more variables. Basically there exist two variables namely independent variable which is the cause of the behavior of another one that is dependent variable. A regression equation was established that comprised terms reflecting interactions. After eliminating the terms having lower p values as error terms and including the effects of only those terms that had effective p values in the
  • 24. Influence of Operational Parameters on the Efficiency of Rod Mill: A Design of Experiments Approach International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 07-13 13 model, the regression equation for quantity retained in the reference sieve was established as below. y=β0+ β1x is called simple linear regression. The regression equation is thus given by (only main effects considered) as following based on table-5. Quantity retained in the reference sieve = 255.78 + 2.66* Running Duration- 17.61* Volume + 2.44 Sieving Time Table 5: Table of Regression Term Coef SE Coef T Value p value Constant 255.78 7.18 35.60 Running Duration 2.66 0.40 6.60 0.00* Volume -17.61 4.04 -4.36 0.00* Sieving Time 2.44 0.40 6.05 0.00* 3.3 Taguchi analysis: Quantity retained versus mill running duration, volume of the material and sieving time The response variable here is the quantity retained in the reference sieve. Taguchi Analysis is carried out to know the rankings of the main effects on the response variable (Table 6). Delta is calculated by subtracting the highest value in the column with smallest value. For instance the highest value for Mill running duration is 52.42 and the least value is 46.02. Delta is calculated as 52.42-46.02= 6.39. Higher value of delta indicates higher ranking of the main effect. For the experiment conducted mill running duration is ranked 1 followed by volume of the material and sieving time. Table 6: Response Table for SN Ratio Levels Running Duration (minutes) Volume (Kgs) Sieving Time (minutes) 1 46.02 48.39 47.43 2 52.42 52.00 50.25 3 49.96 48.02 50.72 Delta 6.39 3.97 3.29 Rank 1 2 3 5. Acknowledgments The authors acknowledge the research funding of M/S InSmart Systems, Hyderabad, India to carry out the research studies. References [1] A. Gupta, and D.S.Yan, “Mineral Processing and Design Operations: An Introduction”, Elsevier Publications, ISBN 9780444516367, pp. 99–106, 2006. [2] Altekar, M., Homon, C.A., Kashem, M.A., Mason, S.W., Nelson, R.M., Patnaude, L.A., Yingling, J. and Taylor, P.B., “Assay Optimization: A Statistical Design of Experiments Approach”, JALA Tutorial, pp. 34– 35, 2006. [3] B.A. Wills, “Mineral Processing Technology: An Introduction to the Practical Aspects of Ore Treatment and Mineral Recovery”, 7th ed. Amsterdam; Boston, MA (4). pp. 157, ISBN 0750644508, 2006. [4] L.B. Barrentine, “An Introduction to Design of Experiments: A Simplified Approach, American Society for Quality Control”, ISBN 9780873894449, 1999. [5] P. Mathews, “Design of Experiments with MINITAB”, New Age International, ISBN 9788122431117, 2010. [6] S. Venkatachalam, and S.N. Degaleesan, Laboratory Experiment in Mineral Engineering, Oxford & IBH Publishing Co., New Delhi, Chap. 2, 1982.
  • 25. www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.14-20 #SPL02090303 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s D KARTHIGEYAN School of Architecture, Hindustan Institute of Technology and Science, Chennai, India Email: dkarthikeyan@hindustanuniv.ac.in Abstract: Chennai, the biggest industrial, commercial, cultural, economic and educational center in South India is the capital city of the state of Tamil Nadu. Birth of this city dates back to 1639 when the English, established Fort St. George and built George Town in its vicinity which today stand as the Central Business District (CBD) of the city. Sub-CBDs have emerged in the Southern, Western and Northern Part of the city due to rapid Urbanization and enormous population explosion. This change in the character of the settlement pattern, clearly establishes the transformation of the city from the Burgess model during 1940’s which depends on a single CBD as its core, to the sector model in 1970’s which shows the change in the pattern of development due to the growth of Public Transportation and in 1970’s the Multi Nuclei Model, where certain specific localities emerge as sub CBD’s in certain specific category to assist the Main CBD. The city shows this transformation in almost all aspects but not to 100% as mentioned by the authors who formulated these theories. This paper is an attempt to establish the relationship between the CBD and Sub CBD’s in the light of ecological models. Keywords: Central Business District, CBD, Sub CBD’s and Chennai City 1. Introduction For centuries, cities have been the heart, the lifeblood of various civilizations and the epicenter of economic, political & artistic activities. Cities exert an increasing attraction on people worldwide and the population tends to concentrate in big cities. In developing countries, cities contribute more than 2/3rd of the country’s Gross Domestic Product (GDP). 2. Settlement Pattern A city is not a work of a day or a decade. It takes generations and generations to build a city. According to Victor (2012), a settlement initially starts as pedestrian oriented with streets in primitive stage, and the boundaries are limited by the distance one could walk in a reasonable period of time. C. A Doxiadis (1964), too agree with this reasons, as he points out that in the olden days the size of the towns are restricted to 2 km by 2 km which one could walk within a reasonable time and the population not more than 50,000 inhabitants. And he further elaborates to say that major capital cities cannot be restricted to this size, and it has to grow much beyond to accommodate the population of more than one million where the size could be restricted to not more than 6 Km by 6 Km. Victor (2012), further says that with the advent of Industrial revolution and migration of population towards the cities to work in the industries, paved way for the settlements to expand with the development of radial suburban rail corridors, along with few streets. These rail corridors were initially part of intercity rail tracks. Tram lines were developed and service’s extended along certain corridors, shaping the city into a better organized and developed urban area, with concentration of activities at the city center. As Commuter rail traffic started to grow, an outward spread of population were visible, as suburban areas started to emerge at a distance from the city center. Further concentration of population occurred along these rail corridors. New roadway arterials were formed radially between the radial railway lines. As city matures into a metropolis, radial and circumferential grid forms with some of the traffic corridors being rail based and the rest road based. This enhancement of connectivity accelerates the expansion and growth of the city. Chennai city is also one such city which developed in this manner. All the above said stages of development of a city are shown in Figure 1. Figure 1 Typical pattern of urban growth
  • 26. Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 15 According to Victor (2012), the city’s population density will be highest in the Central Business District, and as the distance increases the density decreases, which is due to the concentration of economic and commercial activities as part of agglomeration economics. This is diagrammatically shown in Fig: 2. Figure 2 Schematic Diagram of Urban Area in Regional setting As the city grows to become a metropolis, the pressure on the CBD increases, which will lead to other problems like traffic congestion, distance between the CBD and sub urban area increases, and so on. So, all these factors will force the emergence of sub CBD’s within the metropolitan region, which will have better accessibility and other needed infrastructure facilities. This sub CBD’s comes in all the directions at a considerable distance from the CBD. The distance between the CBD and Sub CBD depends on the population and the extent of the Metropolitan area. Figure 3 Emergence of Sub CBD’s as relief poles 3. Indian Port Cities The development of port cities of Mumbai, Kolkata and Chennai as a prominent urban center and major metropolis of India is the work of the English, who wants to establish settlements in the coastal region for their trade related activities. These three cities have, in turn, worked as nuclei for the development of Maharashtra, West Bengal and Tamil Nadu states respectively, which are, at present, the most industrially advanced states of the country. Here an attempt is made to study the relationship between the classical ecological models with the city of Chennai, travelling through its growth history from 1940’s to till date. 4. Chennai The pre-eminence of Chennai in the urban scene of Tamil Nadu is discernible from the fact that the next biggest agglomeration of the state, Coimbatore and Madurai each hardly account for more than one fifth of the total population of Chennai Urban Agglomeration. According to Census of India 2011, the city had 4.68 million residents, making it the sixth most populous city in India; the Metropolitan Area, which comprises the city and its suburbs, was home to approximately 8.9 million, making it the fourth most populous metropolitan area in the country. As per Census 2011, the population of Chennai Metropolitan Area (CMA) is 8.9 million i.e., 12.3 % of the population of Tamil Nadu. This proportion has steadily increased from 8.51 %, 9.51 %, 10.42 % and 11.28 % during the years 1971, 1981, 1991 and 2001 respectively. The Second Master Plan for CMA, 2026 has projected that the population will increase to 11.19 million in 2021 and 12.58 million in 2026. Today, total extent of CMA is less than 1 percent (0.914 percent) of the total extent of the Tamil Nadu state but accommodate more than 12 percent of its population. Table: 1 Growth of population and population density in Tamil Nadu, Chennai City, Chennai urban Agglomeration and CMA during 1961 – 2011 Description Year 1961 1971 1981 1991 2001 2011 Tamil Nadu Population (In Lakhs) 336 411 484 558 624 721 Extent (sq. km.) 130069 130050 Density (persons per sq.km.) 259 317 372 430 480 555 Decadal growth rate (percentage) … 22. 17.5 15.3 11.7 15.6 Chennai city Population (In Lakhs) 17 24 32 38 43 46 Extent (sq. km.) 128.83 176 Density (persons per 13.5 19.1 18.6 21.8 24.6 26.9
  • 27. D KARTHIGEYAN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 16 sq.km.) (In Thousands) Decadal growth rate (Percentage) --- 41.1 32.6 17.2 13.0 7.8 Chennai Urban Agglomeration Population (In Lakhs) 19 31 42 54 64 86 Decadal growth rate (Percentage) … 63.0 35.3 26.4 18.4 35.3 Chennai Metropolitan Area (including Chennai City) Population (In Lakhs) … 35 46 58 70 89 Extent (sq. km.) … 1189 1189 1189 1189 1189 Density (persons per sq.km.) … 2948 3870 4894 5921 7500 Decadal growth rate … … 31.2 26.4 21.0 26.6 Source: Census of India and Second Master Plan for Chennai Metropolitan Area 2026 Density in the CMA is as less as 75 persons per hectare as per Census 2011, which indicates huge scope for accommodating higher population densities as against the already denser (269 persons per hectare) Chennai city, which is shown in detail in Table: 1. 5. Evolution of Chennai Map 1 Road Map of Chennai In the early 16th century, Chennai was basically a group of small villages which were self-contained and had their own agricultural production & household industries for its survival. These villages were mostly planned around a temple, which forms its identity. The prominent villages were Mylapore and Triplicane, one a saivite and another an vaishnavite settlement. It is widely believed that Saint Thiruvalluvar lived in Mylapore. The foundation for the development of the Chennai was laid in 1639 as a British settlement and later expanded as a new town around Fort St. George. During 17th century, important roads of communication like the Poonamallie High Road, Santhome High Road and Lal Bagthadur Sashtri Road, where established which actually linked these small villages. The population, which was 19,000 in 1646, expanded to 40,000 in 1669 and the surroundings of the Fort area covering 16 hamlets were constituted as the City of Madras in 1798. In the 18th century, Mount Road was established, which still functions as the major arterial road connecting the city to the southern districts of the state. In the 19th century, establishment of the railway line, and harbor close to the George Town (CBD) helped the city to develop itself as a major commercial center in south India. Pattern of radial roads were development from the George Town in three principal directions connecting the northern, southern and western region and ring roads were development to enhance the connectivity, which is shown in Map: 1. The Eastern side was not developed, due to the presence of Coromandel Coast. 6. Emergence of Chennai as Major commercial center in South India (1940’s) In the early 20th century, George Town established itself as the main business centre but still substantial parts of it were used for residential purposes. Both sides of Mount Road, radiating from George Town upto a distance of 5 to 6 kms were occupied by large business houses, clubs and hotels; industries were few and were located in George Town and Perambur which is located in the northern part of the city. Bungalows started to come up in Kilpauk, Nungambakkam and Chetpet. By 1941 Chennai city had developed itself into a provincial metropolis enjoying the best of both worlds i.e., urban amenity and rural atmosphere. During this period, city established itself as a major commercial, military and administrative centre for the entire South India. 6.1 Burgess Model Figure 4 Burgess Model According to Park (1925), Burgess Model assumes a relationship between the socio-economic status (mainly income) of households and the distance from
  • 28. Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 17 the Central Business District (CBD). The further from the CBD, the better the quality of housing, but longer the commuting time. Thus, accessing better housing is done at the expense of longer commuting times (and costs). Figure 5 Bid Rent Curve Burgess model is based on Bid Rent Curve, which assumes that the Value of the land is based on the profits that are obtainable from maintaining a business on that land. Map 2 Superimposition of Burgess Model in Chennai during 1940’s According to this model, a large city is divided in six concentric zones: 6.1.1 Zone I: Central Business District (CBD) Business activities, i.e., tertiary employment are located and urban transport infrastructure is converging, making it the most accessible. George Town – CBD of Chennai city is the place where all major business activities are preformed and NH4, NH5 and NH45 converges from the northern, western and southern directions. 6.1.2 Zone II: Factory Many industrial activities located to take advantage of nearby labor and markets. Most transport terminals (port sites and rail yards), are located adjacent to the central area. Chintadripet & Perambur locations are the one where industries started to come up and some are still running even today. It is very close to the harbor and railway stations. It also has many residential settlements nearby as labor market. 6.1.3 Zone III: Transition This zone is gradually been reconverted to other uses by expanding manufacturing / industrial activities. It contains the poorest segment of the urban population, (notably first generation immigrants) living, in the lowest housing conditions. Mannadi, an residential settlement very close to George town and perambur, established in 1940’s to take advantage of the industrial revolution, but still exist as the same. The public infrastructure in this neighbourhood is very much lower than what is needed today. 6.1.4 Zone IV: Working Class Dominated by the working class, those who were able to move away from the previous transition zone (often the second generation immigrants). Advantage of being located near the major zones of employment (I and II) and thus represents a low cost location for the working class. Vepery, a residential community is one of the finest examples. This area is famous for its schools, and other infrastructure facilities which is much better when compared to the transition zone. 6.1.5 Zone V: Residential Represents higher quality housing linked by longer commuting costs. Alwarpet and Nungmabakkam, a prominent high class residential area during 1940’s, but today it has become a mixed residential area. This is the place where many Britishers lived during that time. It is famous for its bunglow type of houses. 6.1.6 Zone VI: Commuter Mainly high class people with expensive housing in the rural & suburban areas. The commuting costs are the highest. Prior to mass diffusion of the automobile (1930s), most of these settlements were located next to rail stations. Tambaram, a residential suburb, located at a distance of more than 20 Km from the CBD in the southern side of the city. 7. Emergence of Chennai as a Major Metropolis of India (1970’s) After Independence, the population of the city got doubled from one million to two million within a span of 20 years. This sudden increase in population is due to the enormous industrial growth through the five year plans of the central government. This transformed the city into a major metropolis of national importance. The structure of the city was then approximated to a semi-circle with extensions in
  • 29. D KARTHIGEYAN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 18 all possible directions from George Town and Harbour. Naturally all communication lines led to this centre and these in turn were linked with each other producing a radial and ring pattern of development. 7.1 Sector Model Hoyt (1939) suggests through his sector theory that urban areas develop in sectors alongside the main transport routes like railroads, highways and other transportation arteries into and out of a city. Various transportation routes represented greater access which makes the cities tended to grow in wedge-shaped pattern or sector. According to this model, the city is divided into five sectors, namely 7.1.1 Central Business District CBD means higher level of access and highest land value. Hoyt model almost agreed with the Burgess version of CBD as stated in the Burgess Model. In Chennai, during 1970’s George Town and its extension towards Mount road in southern direction together constitute the central business district of the City where most of the wholesale trade, specialized retail trade, banking and financial institutions were located. Figure 6 Hoyt Sector Model Map 3 Superimposition of Hoty’s Model in Chennai city during 1970’s 7.1.2 Factories/Industry Manufacturing functions developed in a wedge shape surrounding transportation routes. In Chennai, Large Scale Industries are located on the northern side of the city, especially at Manali & Ennore, whereas larger industrial estates are located on the west at Ambattur with the Heavy Vehicles Factory located further west at Avadi. Nearly 40 percent of the industrial work places are located on the north and northwestern part of the City. One more Industrial estate located on the southern part of the city planned along with Ambattur Industrial estate for a similar purpose namely Guindy Industrial estate along the Mount Road, today got converted to IT offices and other non-Polluting industries after 1990’s. 7.1.3 Low class residential Residential functions would grow in wedge-shaped patterns with a sector of low-income housing bordering manufacturing/industrial sectors due to its traffic, noise, and pollution makes these areas the least desirable. In Chennai, Washermanpet & Mannadi located in the northern and north western part of the city is completely surrounded by Industries on all the sides. 7.1.4 Middle class residential Middle income households were located furthest away from the industries. Development of residential neighborhoods occurs along the Sub urban rail network. Pallavaram, Chrompet, Saidapet, & St. Thomas Mount which was easily accessed by the sub urban rail network paved the way for the residential development for the growing middle class people. 7.1.5 High class residential It is unlikely that high class residential housing would be found near to factories or lower quality housing zones, since these residencies exercise a powerful influence on the location of undesirable neighbors. Gopalapuram, Poies Garden and Wallace Garden – all high class residential settlement found very close and accessible to mount road are occupied right now by the second and third generations of super rich people. High status residential area will also spread out along the lines of the sector by the addition of new belts of housing beyond the outer arc of the city. Besant Nagar, Adyar and Thiruvanmiyur which was planned by the City Development Authorities around 1950’s as a residential suburb. But, today these locations house the first and second generations of super rich people, which was the edge of the city corporation when it was planned. 8. Emergence of Chennai as a Major Business center in South Asia In 1990’s though George Town and Anna Salai continued as CBD, Mylapore, Thyagaraya Nagar, Nungambakkam, and Purasawalkam have developed
  • 30. Transformation of Chennai City as Nucleus of Regional Development through the Emergence of Sub-CBD’s International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 19 as Regional Commercial Centres and Adyar, Anna Nagar and Perambur have developed as Regional Commercial Sub-Centres. This is due to the encouragement of growth along the major transport corridors and development of urban nodes at Manali, Minjur, Ambattur, Avadi, Alandur and Tambaram which all forms the outer edge of the city during this period. Government initiatives like the Relocation of wholesale Vegetable, Fruit & Flower Market and Mofussil Bus Terminus from George Town to Koyambedu, located on western edge of the city corporation limit was an initiative along the development of regional sub CBD’s and was completed in late 1990’s; Other initiatives like the shifting of Iron and Steel Market to Sathangadu, operation of a separate truck terminal at Madhavaram to avoid the entry of trucks into the city areas, and the development of Satellite town, beyond city limits at Maraimalai Nagar paved way for it. 8.1 Multi Nuclei Model Harris (1945), in his Multi Nuclei theory states that cities of greater size will develop substantial suburban area and some suburbs, having reached significant size, will start to function as smaller business districts. These smaller business districts acts as satellite nodes, or nuclei, of activity around which land use patterns will be formed. Even though CBD still acting as the major center of commerce, specialized cells of activities would develop according to specific requirements of certain activities, rent-paying abilities, and the tendency for some kinds of economic activity to cluster together. Figure 7 Multi Nuclei Model During 1990’s Thyagaraya Nagar emerged as the sub CBD for Textile and Jewellery Market. During this period Mint Street and Godown Street which are located in the CBD and doing business for Jewellery & textile Market was also functional but it is truly too little of space to handle the demand of a growing metropolis. The emergence of T. Nagar was also coupled by good accessibility, availability of public transport system and its location which is very close to the Gemini Circle which in 1990’s was considered as the center of the city, as the city was expanding very fast on the southern side. According to this model, city is divided into nine zones. At the center of this model is the CBD, which is still taken care by George Town, with light manufacturing and wholesaling activities located along transport routes like the Kolkata Highway, etc. Heavy industries would locate near the outer edge of city, perhaps surrounded by lower-income households, and suburbs of commuters like Sriperumpudur, Oragadam & Maraimalai Nagar, which was identified for large scale heavy industrial development, and all these locations were actually located in the adjoining districts of chennai like Kanchipuram and Thirvallur Districts. These locations are actually planned for heavy industries by the government, and they have also provided the necessary infrastructure for the same. This is a planned initiative, and not developed on its own. Map 4 Superimposition of Multi Nuclei Model in Chennai during 1990’s In these Multi Nuclei cities, some of the nuclei will be pre-existing settlements like T. Nagar, which today is a market for Textile and Jewellery, but it was originally planned as a Brahmin Settlement before independence; and others arising from urbanization and external economies like Adyar, Anna Nagar, which was planned as a residential area after independence, but today it stands as a regional commercial sub centers. According to Multi Nuclei theory, the numbers and functions of the nuclei differ from city to city, and it marks the city's growth. Each nucleus will vary in size and character, and the importance they exert in cities economic development. Some Nuclei’s are large industrial sites while others may be small strip
  • 31. D KARTHIGEYAN International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 03, June, 2016, pp. 14-20 20 shopping centers. Each Nuclei acts as a growth pole for a particular kind of land use (industry, retail, or high-quality housing). As these expand, they merge to form a single urban area, which is the phase in which the city is moving today. According to the theory, Creating smaller business districts (or individual nuclei) enable people in the suburbs to have better access to the facilities of the CBD and industrial sectors for commerce and employment. 9. The Future of Chennai City Tamil Nadu is the second largest software exporter in the country, and 90% of its export is from Chennai city alone, especially from its IT corridor (OMR). A large I.T Park at Siruseri, located at the end of the IT corridor is developed, which housing the TCS’s biggest office in the city. Chennai is also a major export hub of South East Asia. International car manufactures have established their manufacturing bases here, which make this city as the Detroit of South Asia. Large Scale manufacturing industrial activities at Sriperumpudur, and Mahindra World city developed over 1700 acres; near Maraimalai Nagar new town are some of the major developments happening today. All these developments are located within a distance of 25 to 35 Km from the CBD and Sub CBD’s are already emerged. With these new developments Chennai can emerge as a prominent business headquarters for the whole of South Asia. But due to these sudden pressures of development and in the process of expansion, the city has engulfed several fishing, agricultural villages and hamlets creating several ecological and environmental challenges that the current governance and administrative machinery is unable to cope up with. Pallikarani Marsh Land is one such location which requires our immediate attention. These IT related activities developed a lot of residential neighbourhoods around the city like Pallavaram, Thoraipakkam, Velachery which have resulted in urban sprawl. 10. Conclusion Chennai is emerging as a major metropolis of the world, and to continue its dominance in the economic, social, political and cultural front, as a Nucleus of regional development; it’s infrastructure, housing and other supporting facilities has to be planned and developed to international standards; also its Administrative machinery and governance system has to be trained and changed to be investor friendly, otherwise the city will lose its importance as the Nucleus of this regions development. References [1] http://www.medwelljournals.com/fulltext/?doi=pj ssci.2010.244.253 [2] Doxiadis (1964), “Ekistics – the science of Human settlement”, Ekistics 197, April 1972. [3] Harris, C. D. and E. L. Ullman. 1945. “The Nature of Cities”, Annals of the American Academy of Political and Social Science [4] Hoyt, Homer. 1939. The Structure and Growth of Residential Neighborhoods in American Cities. Federal Housing Administration, Washington, D. C. [5] Majid Husain (2012), Geography of India, Third edition, Tata Mcgraw hill’s winning we edge series, New Delhi. [6] Park, R. E. and E. W. Burgess. (1925), “The City”, Macmillan Co. [7] D Johnson Victor and S. Ponnuswamy (2012), “Urban Transportation: Planning, Operation and Management”, Tata Mcgraw-hill, New Delhi. [8] Second Master Plan 2026, Chennai Metropolitan Development Authority, Chennai. [9] Xiang Ming Chen, Anthony M. Orum, Krista E. Paulsen, (2013), “Introduction to Cities: How Place and Space Shape Human Experience”, Wiley Blackwell Publications. [10]Development Plan for Chennai Metropolitan Area, April, 2006, Government of Tamil Nadu.
  • 32. www.cafetinnova.org Indexed in Scopus Compendex and Geobase Elsevier, Geo-Ref Information Services-USA, List B of Scientific Journals, Poland, Directory of Research Journals ISSN 0974-5904, Volume 09, No. 03 June 2016, P.P.21-25 #SPL02090304 Copyright ©2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Mechanical Properties of High Calcium Flyash Geopolymer Concrete V C PRABHA AND V REVATHI Department of Civil engineering, K.S.R. College of Engineering, Tiruchengode, Tamil Nadu, INDIA Email: prabhacsamy@gmail.com, revthiru2002@yahoo.com Abstract: The present study deals with the mechanical properties of High Calcium Fly Ash Geopolymer Concrete (HCFA GPC). A preliminary study was made on high calcium fly ash geopolymer mortar by varying sodium based alkaline activator to binder ratio to find an ideal composition. Alkaline activators were the mixture of sodium hydroxide (NaOH) and sodium silicate (Na2SiO3. Based on the compressive strength of high calcium fly ash geopolymer mortar, the optimum mix combination was arrived for the further study on concrete. Upon the optimum mix combination, mechanical properties such as compressive strength, split tensile strength and modulus of elasticity were further determined. Test results depict that strength properties of HCFA GPC were marginally higher under steam curing than ambient curing. Keywords: Geopolymer, High Calcium fly ash, Alkaline activator, Steam Curing, Strength Properties 1. Introduction Manufacturing of Portland cement is an energy intensive process and releases a large amount of greenhouse gases to the atmosphere. Recently, another form of cementations materials using silicon and aluminum activated in a high alkali solution was developed. It is referred as geopolymer or alkali- activated binder. Geopolymers was first developed by Davidovits, which consists of SiO4 and AlO4 tetrahedral networks [1-3]. Alumina silicate reactive materials dissolve in strong alkaline solutions and free SiO4 and AlO4 tetrahedral structure forms. It is also well known that geopolymers possess excellent mechanical properties [4]. Several factors such as curing mode, curing temperature, alkaline liquid to binder ratio, molarity of sodium hydroxide, ratio of sodium hydroxide to sodium silicate solution are the key factors in developing geopolymeric reaction [5-8]. The geopolymer mixtures may be subjected to curing either at room temperature or at a given temperature. It is mentioned that the reaction of the fly ash in the production of geopolymers is low at ambient temperatures [9]. The geopolymer concrete achieves high compressive strength at given temperatures between 40 to 95C [10]. Yunfen et al. [11] demonstrated the influence of concentration and modulus (SiO2: N2O) of sodium silicate solutions and curing mode in geopolymers prepared. It can be seen that the compressive strength increased with increase in modulus of sodium silicate solution. However, when the modulus exceeds 1.4, compressive strength decreased [12]. Also, elevated temperatures can increase the early strength buildup of the samples. However, the later strength after 7 days was the same at irrespective of different temperature [13, 14]. Among various source materials, low calcium fly ash (LCFA) is extensively used for geopolymer owing to its easy availability and enhanced properties. [15].As well, abundant work on geopolymer has been reported with the use of low calcium fly ash. Despite, a quite reasonable work is carried out with the use of high calcium fly ash for geopolymer. High calcium fly ash (HCFA) also contains a considerable amount of silica and alumina. [16]. High calcium fly ash has few drawbacks compared to low calcium fly ash in geopolymer. The early age compressive strength of high calcium fly ash geopolymers attains under high pressure and high temperatures of curing to get the similar strength of ordinary Portland cement binder [17-19]. While molarity of NaOH as 8M is found suitable for LCFA, HCFA needs 10M for the geopolymer synthesis [20-22]. Turkish construction industry promoted HCFA geopolymer for both cast-in-place and precast concrete products. Steam curing was applied to develop adequate compressive strength for form removal at age 1-day [23].Compressive strength and microstructure of HCFA geopolymer depend upon mass of water to fly ash ratio and [19-21]. The annual output of lignite fly ash from Neyveli Lignite Corporation station 28.5 million tons per annum at Neyveli and one open cast lignite mine of capacity 2.1 million tonnes per annum. This fly ash contains a high percentage of calcium and is being used quite extensively for construction in Tamilnadu. The knowledge of the use of high calcium lignite fly ash in producing geopolymer would be beneficial to increase the scope of HCFA. In the above background, the present study made an attempt to determine the mechanical properties of HCFA geopolymer concrete under ambient curing and steam curing. In this respect, a preliminary study was